example_id int64 0 10k | metadata stringlengths 679 723 | classification_prompt stringlengths 7.94k 19k | classification_completion stringclasses 14 values | classification_text stringlengths 7.95k 19k | improved_signature stringlengths 8.53k 23.3k | improved_model_weights stringlengths 1.76k 5.04k | training_metrics stringlengths 1.46k 2.92k |
|---|---|---|---|---|---|---|---|
0 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.74, "improved_accuracy": 0.94, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9016, "learning_rate": 0.08961895813761998, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [-0.156238, 0.553070, 1.345668, 0.174396, 0.709357]
std: [0.017263, 0.879406, 1.586630, 0.289530, 1.082598]
fourier: [[0.248509, 0.260538, 0.260983, 0.322360, 14.061448], [14.315794, 16.844737, 17.273803, 18.020222, 49.776265], [21.807864, 24.642599, 29.494247, 30.000682, 121.110156], [4.970328, 5.352469, 5.482313, 5.673774, 15.695639], [18.265161, 20.423349, 20.575984, 22.141599, 63.842148]]
input_correlations: [[0.970174, 0.384386, 0.526205, -0.080395, 0.178393, 0.000000, 0.000000, 0.000000], [0.225350, -0.550714, 0.205588, -0.795896, -0.321186, 0.000000, 0.000000, 0.000000], [0.284851, -0.539535, -0.334357, -0.687042, 0.259149, 0.000000, 0.000000, 0.000000], [-0.159735, -0.332646, -0.596317, -0.368553, -0.835132, 0.000000, 0.000000, 0.000000], [-0.477113, 0.166411, 0.269855, 0.640942, 0.494450, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.710266, -2.411417, -2.078990, -1.716736, 1.828617]
pre_activation_std: [1.521389, 2.865890, 1.632366, 1.551031, 1.648672]
### 2
mean: [-1.868680, 0.729779, 0.970211, -2.046248, -0.245670]
std: [1.040968, 1.316121, 1.906594, 0.863408, 0.559016]
fourier: [[16.002096, 17.513173, 18.254590, 18.300855, 168.181168], [20.173273, 20.790360, 23.871408, 25.487054, 65.680104], [27.855761, 32.946505, 36.550497, 38.251440, 87.318994], [13.199729, 13.405894, 15.468462, 15.670332, 184.162368], [9.419544, 9.550318, 9.840535, 10.172852, 22.110299]]
input_correlations: [[-0.020465, -0.420045, -0.331568, 0.009631, -0.841153, 0.000000, 0.000000, 0.000000], [0.839452, -0.130030, 0.103104, 0.015396, -0.576575, 0.000000, 0.000000, 0.000000], [-0.734799, -0.284919, -0.244670, -0.121642, 0.878018, 0.000000, 0.000000, 0.000000], [-0.578947, -0.329366, -0.383843, 0.072594, -0.568805, 0.000000, 0.000000, 0.000000], [0.369328, -0.528879, -0.278958, -0.050199, -0.699134, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.868680, 0.729779, 0.970211, -2.046248, -0.245670]
pre_activation_std: [1.040968, 1.316121, 1.906594, 0.863408, 0.559016]
### 4
mean: [1.515942, -0.583342, 0.144554, -0.773830, 0.593914]
std: [1.605271, 0.526652, 1.029305, 0.349068, 1.217935]
fourier: [[22.533770, 24.547551, 29.918637, 31.281173, 136.434753], [7.736826, 8.664927, 9.668110, 10.455275, 52.500785], [15.616962, 15.840480, 18.094156, 19.128455, 19.662837], [5.574642, 5.647576, 5.733608, 6.803054, 69.644735], [18.598767, 21.296930, 22.738936, 22.878783, 53.452276]]
input_correlations: [[0.662795, -0.594304, 0.999436, 0.360854, -0.547565, 0.000000, 0.000000, 0.000000], [0.677853, -0.836360, 0.927462, 0.179622, -0.770891, 0.000000, 0.000000, 0.000000], [0.571862, -0.960718, 0.777331, -0.047233, -0.857624, 0.000000, 0.000000, 0.000000], [0.636922, -0.961538, 0.723991, -0.011235, -0.927696, 0.000000, 0.000000, 0.000000], [-0.593001, 0.957698, -0.782790, 0.023726, 0.861395, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.515942, -0.583342, 0.144554, -0.773830, 0.593914]
pre_activation_std: [1.605271, 0.526652, 1.029305, 0.349068, 1.217935]
### 6
mean: [0.114567, 1.155740, 0.145128, -1.297522, -0.249773]
std: [1.287907, 2.224864, 1.542958, 1.319608, 0.532815]
fourier: [[18.663759, 18.705924, 19.116326, 24.295957, 26.122085], [32.349302, 32.850657, 41.834952, 44.669829, 104.016575], [22.458316, 22.522959, 23.054807, 29.192832, 31.210594], [18.333254, 19.623756, 24.457835, 25.890424, 116.776963], [7.210798, 7.934128, 9.649392, 10.250093, 22.479592]]
input_correlations: [[-0.959352, -0.715367, -0.960683, 0.225681, 0.818951, 0.000000, 0.000000, 0.000000], [0.960841, 0.709531, 0.953228, -0.238388, -0.821193, 0.000000, 0.000000, 0.000000], [-0.956522, -0.705801, -0.956746, 0.237586, 0.826029, 0.000000, 0.000000, 0.000000], [-0.997790, -0.832646, -0.989476, -0.003430, 0.655596, 0.000000, 0.000000, 0.000000], [-0.998122, -0.866111, -0.983980, -0.070086, 0.596390, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.114567, 1.155740, 0.145128, -1.297522, -0.249773]
pre_activation_std: [1.287907, 2.224864, 1.542958, 1.319608, 0.532815]
### 8
mean: [-0.916608, 0.023469, 1.013993, 0.211633, 0.623529]
std: [0.247448, 1.454997, 1.967077, 0.381888, 1.202178]
fourier: [[3.544859, 3.827291, 4.530502, 4.835366, 82.494699], [21.460609, 22.586331, 22.966817, 28.234959, 29.512409], [28.968455, 29.915090, 38.707105, 38.914183, 91.259367], [6.486763, 6.753355, 6.881126, 7.793975, 19.046951], [21.121292, 21.154630, 21.245486, 24.977464, 56.117574]]
input_correlations: [[0.706796, -0.988327, 0.701580, -0.225894, 0.885916, 0.000000, 0.000000, 0.000000], [0.935317, -0.907357, 0.932494, 0.044811, 0.897670, 0.000000, 0.000000, 0.000000], [-0.867794, 0.962176, -0.863799, 0.077092, -0.897531, 0.000000, 0.000000, 0.000000], [0.992516, -0.779578, 0.991730, 0.224313, 0.855094, 0.000000, 0.000000, 0.000000], [0.995494, -0.763429, 0.994731, 0.245878, 0.864190, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.916608, 0.023469, 1.013993, 0.211633, 0.623529]
pre_activation_std: [0.247448, 1.454997, 1.967077, 0.381888, 1.202178]
### 10
mean: [-1.369053]
std: [2.538972]
fourier: [[36.897390, 39.511262, 49.356470, 51.091654, 123.214782]]
input_correlations: [[-0.854986, 0.869532, -0.954146, 0.895227, 0.891099, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.369053]
pre_activation_std: [2.538972]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [-0.156238, 0.553070, 1.345668, 0.174396, 0.709357]
std: [0.017263, 0.879406, 1.586630, 0.289530, 1.082598]
fourier: [[0.248509, 0.260538, 0.260983, 0.322360, 14.061448], [14.315794, 16.844737, 17.273803, 18.020222, 49.776265], [21.807864, 24.642599, 29.494247, 30.000682, 121.110156], [4.970328, 5.352469, 5.482313, 5.673774, 15.695639], [18.265161, 20.423349, 20.575984, 22.141599, 63.842148]]
input_correlations: [[0.970174, 0.384386, 0.526205, -0.080395, 0.178393, 0.000000, 0.000000, 0.000000], [0.225350, -0.550714, 0.205588, -0.795896, -0.321186, 0.000000, 0.000000, 0.000000], [0.284851, -0.539535, -0.334357, -0.687042, 0.259149, 0.000000, 0.000000, 0.000000], [-0.159735, -0.332646, -0.596317, -0.368553, -0.835132, 0.000000, 0.000000, 0.000000], [-0.477113, 0.166411, 0.269855, 0.640942, 0.494450, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.710266, -2.411417, -2.078990, -1.716736, 1.828617]
pre_activation_std: [1.521389, 2.865890, 1.632366, 1.551031, 1.648672]
### 2
mean: [-1.868680, 0.729779, 0.970211, -2.046248, -0.245670]
std: [1.040968, 1.316121, 1.906594, 0.863408, 0.559016]
fourier: [[16.002096, 17.513173, 18.254590, 18.300855, 168.181168], [20.173273, 20.790360, 23.871408, 25.487054, 65.680104], [27.855761, 32.946505, 36.550497, 38.251440, 87.318994], [13.199729, 13.405894, 15.468462, 15.670332, 184.162368], [9.419544, 9.550318, 9.840535, 10.172852, 22.110299]]
input_correlations: [[-0.020465, -0.420045, -0.331568, 0.009631, -0.841153, 0.000000, 0.000000, 0.000000], [0.839452, -0.130030, 0.103104, 0.015396, -0.576575, 0.000000, 0.000000, 0.000000], [-0.734799, -0.284919, -0.244670, -0.121642, 0.878018, 0.000000, 0.000000, 0.000000], [-0.578947, -0.329366, -0.383843, 0.072594, -0.568805, 0.000000, 0.000000, 0.000000], [0.369328, -0.528879, -0.278958, -0.050199, -0.699134, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.868680, 0.729779, 0.970211, -2.046248, -0.245670]
pre_activation_std: [1.040968, 1.316121, 1.906594, 0.863408, 0.559016]
### 4
mean: [1.515942, -0.583342, 0.144554, -0.773830, 0.593914]
std: [1.605271, 0.526652, 1.029305, 0.349068, 1.217935]
fourier: [[22.533770, 24.547551, 29.918637, 31.281173, 136.434753], [7.736826, 8.664927, 9.668110, 10.455275, 52.500785], [15.616962, 15.840480, 18.094156, 19.128455, 19.662837], [5.574642, 5.647576, 5.733608, 6.803054, 69.644735], [18.598767, 21.296930, 22.738936, 22.878783, 53.452276]]
input_correlations: [[0.662795, -0.594304, 0.999436, 0.360854, -0.547565, 0.000000, 0.000000, 0.000000], [0.677853, -0.836360, 0.927462, 0.179622, -0.770891, 0.000000, 0.000000, 0.000000], [0.571862, -0.960718, 0.777331, -0.047233, -0.857624, 0.000000, 0.000000, 0.000000], [0.636922, -0.961538, 0.723991, -0.011235, -0.927696, 0.000000, 0.000000, 0.000000], [-0.593001, 0.957698, -0.782790, 0.023726, 0.861395, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.515942, -0.583342, 0.144554, -0.773830, 0.593914]
pre_activation_std: [1.605271, 0.526652, 1.029305, 0.349068, 1.217935]
### 6
mean: [0.114567, 1.155740, 0.145128, -1.297522, -0.249773]
std: [1.287907, 2.224864, 1.542958, 1.319608, 0.532815]
fourier: [[18.663759, 18.705924, 19.116326, 24.295957, 26.122085], [32.349302, 32.850657, 41.834952, 44.669829, 104.016575], [22.458316, 22.522959, 23.054807, 29.192832, 31.210594], [18.333254, 19.623756, 24.457835, 25.890424, 116.776963], [7.210798, 7.934128, 9.649392, 10.250093, 22.479592]]
input_correlations: [[-0.959352, -0.715367, -0.960683, 0.225681, 0.818951, 0.000000, 0.000000, 0.000000], [0.960841, 0.709531, 0.953228, -0.238388, -0.821193, 0.000000, 0.000000, 0.000000], [-0.956522, -0.705801, -0.956746, 0.237586, 0.826029, 0.000000, 0.000000, 0.000000], [-0.997790, -0.832646, -0.989476, -0.003430, 0.655596, 0.000000, 0.000000, 0.000000], [-0.998122, -0.866111, -0.983980, -0.070086, 0.596390, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.114567, 1.155740, 0.145128, -1.297522, -0.249773]
pre_activation_std: [1.287907, 2.224864, 1.542958, 1.319608, 0.532815]
### 8
mean: [-0.916608, 0.023469, 1.013993, 0.211633, 0.623529]
std: [0.247448, 1.454997, 1.967077, 0.381888, 1.202178]
fourier: [[3.544859, 3.827291, 4.530502, 4.835366, 82.494699], [21.460609, 22.586331, 22.966817, 28.234959, 29.512409], [28.968455, 29.915090, 38.707105, 38.914183, 91.259367], [6.486763, 6.753355, 6.881126, 7.793975, 19.046951], [21.121292, 21.154630, 21.245486, 24.977464, 56.117574]]
input_correlations: [[0.706796, -0.988327, 0.701580, -0.225894, 0.885916, 0.000000, 0.000000, 0.000000], [0.935317, -0.907357, 0.932494, 0.044811, 0.897670, 0.000000, 0.000000, 0.000000], [-0.867794, 0.962176, -0.863799, 0.077092, -0.897531, 0.000000, 0.000000, 0.000000], [0.992516, -0.779578, 0.991730, 0.224313, 0.855094, 0.000000, 0.000000, 0.000000], [0.995494, -0.763429, 0.994731, 0.245878, 0.864190, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.916608, 0.023469, 1.013993, 0.211633, 0.623529]
pre_activation_std: [0.247448, 1.454997, 1.967077, 0.381888, 1.202178]
### 10
mean: [-1.369053]
std: [2.538972]
fourier: [[36.897390, 39.511262, 49.356470, 51.091654, 123.214782]]
input_correlations: [[-0.854986, 0.869532, -0.954146, 0.895227, 0.891099, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.369053]
pre_activation_std: [2.538972]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.15623831748962402, "std": 0.017262941226363182, "fourier": [0.2485086623988948, 0.26053776511190807, 0.2609829532112546, 0.3223596502527175, 14.06144843250513], "input_correlations": [0.9701740241940175, 0.38438614198922033, 0.5262050334346874, -0.08039497770800123, 0.1783928460429898, 0.0, 0.0, 0.0], "pre_activation_mean": 1.7102656364440918, "pre_activation_std": 1.5213894844055176}, "1": {"mean": 0.5530696511268616, "std": 0.879405677318573, "fourier": [14.315793742877089, 16.844736527660753, 17.273802894785753, 18.020222032085663, 49.77626469585812], "input_correlations": [0.22534967268788533, -0.5507143825448386, 0.20558757056728674, -0.7958964515964384, -0.32118596652231296, 0.0, 0.0, 0.0], "pre_activation_mean": -2.411417007446289, "pre_activation_std": 2.86588978767395}, "2": {"mean": 1.3456683158874512, "std": 1.5866299867630005, "fourier": [21.807864211176266, 24.64259884560192, 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0.012174], "network.10.weight": [[-0.205546, 0.4689, -1.051093, 0.197317, 0.554592]], "network.10.bias": [-0.673895]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6868410110473633, "train_acc": 0.565, "val_loss": 0.6930116415023804, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6797666549682617, "train_acc": 0.565, "val_loss": 0.6866182088851929, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6613490879535675, "train_acc": 0.565, "val_loss": 0.6048181653022766, "val_acc": 0.74}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.5114911645650864, "train_acc": 0.84, "val_loss": 0.5617893934249878, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.4945254623889923, "train_acc": 0.86, "val_loss": 0.439950555562973, "val_acc": 0.8}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 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0.21938255429267883, "val_acc": 0.92}], "summary": {"total_epochs": 12, "degraded_epochs": 3, "improved_epochs": 9, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6930116415023804, "final_val_loss": 0.6048181653022766, "initial_val_acc": 0.52, "final_val_acc": 0.74, "best_val_acc": 0.74}, "improved_stage": {"initial_val_loss": 0.5617893934249878, "final_val_loss": 0.21938255429267883, "initial_val_acc": 0.76, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 6}, "improvement": 0.19999999999999996, "first_improvement_epoch": 2}} |
1 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.5, "improved_accuracy": 0.9, "improvement": 0.4, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7902, "learning_rate": 0.019119242316001303, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.771668, -0.117241, -0.093825, 0.697837, -0.016844, 0.593146]
std: [0.248479, 0.057827, 0.034550, 0.209439, 0.012862, 0.181870]
fourier: [[3.683442, 4.096419, 5.289387, 5.572376, 69.450144], [0.910779, 0.960365, 1.216099, 1.236543, 10.551723], [0.509367, 0.569357, 0.724791, 0.767388, 8.444218], [3.173189, 3.365314, 4.457820, 4.671735, 62.805291], [0.210485, 0.223654, 0.251263, 0.256400, 1.515923], [2.657645, 2.951955, 3.919565, 4.096937, 53.383131]]
input_correlations: [[0.112572, -0.544768, 0.072148, -0.900834, -0.323376, 0.000000, 0.000000, 0.000000], [-0.424613, -0.420726, -0.673694, -0.674063, -0.452260, 0.000000, 0.000000, 0.000000], [0.877125, 0.493670, 0.385390, -0.287422, -0.134087, 0.000000, 0.000000, 0.000000], [0.692082, -0.091073, 0.629042, -0.510476, -0.026060, 0.000000, 0.000000, 0.000000], [-0.653124, -0.003622, 0.137887, 0.411028, -0.527230, 0.000000, 0.000000, 0.000000], [-0.023163, 0.075135, 0.308934, 0.635819, 0.816402, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.631290, -2.528596, 0.837148, 0.053241, -0.036688, 2.514904]
pre_activation_std: [1.471626, 1.757832, 1.223700, 1.361698, 0.879932, 1.757702]
### 2
mean: [-0.944309, -0.874625, -0.081479, -0.195549, -0.994316, -0.854148]
std: [0.552041, 0.639786, 0.666615, 0.474535, 0.555104, 0.687490]
fourier: [[9.122581, 9.132873, 9.457256, 9.770282, 84.987819], [10.001342, 10.343601, 10.833623, 11.980032, 78.716229], [9.009985, 9.104190, 11.300221, 12.284331, 13.499955], [7.115601, 7.356920, 7.726906, 8.930107, 17.599370], [8.852974, 9.215624, 9.528296, 9.762114, 89.488440], [9.700139, 12.921988, 14.575733, 15.906211, 76.873319]]
input_correlations: [[0.079209, -0.002454, 0.267867, 0.337875, -0.050463, -0.930649, 0.000000, 0.000000], [-0.117131, -0.089945, 0.330534, 0.191258, -0.064700, -0.986890, 0.000000, 0.000000], [-0.188524, 0.036618, -0.790302, -0.735087, -0.030331, 0.622065, 0.000000, 0.000000], [-0.057056, 0.004395, -0.839228, -0.567991, -0.037274, 0.599918, 0.000000, 0.000000], [-0.033067, -0.029281, 0.295118, 0.273251, -0.119925, -0.968131, 0.000000, 0.000000], [-0.172929, -0.039887, -0.289412, -0.400624, 0.249293, -0.828483, 0.000000, 0.000000]]
pre_activation_mean: [-0.944309, -0.874625, -0.081479, -0.195549, -0.994316, -0.854148]
pre_activation_std: [0.552041, 0.639786, 0.666615, 0.474535, 0.555104, 0.687490]
### 4
mean: [0.639303, -0.258020, 0.074912, 0.484175, -0.270284, 0.647514]
std: [0.237054, 0.161263, 0.095051, 0.186506, 0.102060, 0.214865]
fourier: [[3.423729, 3.910036, 5.009370, 5.303725, 57.537244], [2.209863, 2.854338, 3.448457, 3.575369, 23.221828], [1.487728, 1.516169, 1.710024, 1.954751, 6.742040], [2.779930, 2.870213, 4.056184, 4.189021, 43.575703], [1.351437, 1.888195, 1.997286, 2.404784, 24.325536], [3.056279, 3.582239, 4.670771, 4.678326, 58.276240]]
input_correlations: [[-0.728974, -0.560295, -0.977332, -0.940117, -0.838491, -0.412604, 0.000000, 0.000000], [0.635399, 0.484220, 0.976594, 0.965209, 0.755736, 0.469757, 0.000000, 0.000000], [-0.891335, -0.767632, -0.865163, -0.794811, -0.954828, -0.374935, 0.000000, 0.000000], [-0.663910, -0.459915, -0.995238, -0.973928, -0.773974, -0.344535, 0.000000, 0.000000], [0.659896, 0.508310, 0.958533, 0.917778, 0.794029, 0.533519, 0.000000, 0.000000], [-0.690817, -0.529437, -0.981619, -0.964187, -0.800077, -0.408814, 0.000000, 0.000000]]
pre_activation_mean: [0.639303, -0.258020, 0.074912, 0.484175, -0.270284, 0.647514]
pre_activation_std: [0.237054, 0.161263, 0.095051, 0.186506, 0.102060, 0.214865]
### 6
mean: [0.920563, -0.347956, -0.239090, 0.854713, -0.035297, 0.751846]
std: [0.268177, 0.159305, 0.090287, 0.221844, 0.027813, 0.206618]
fourier: [[3.897445, 4.455607, 5.760717, 5.979833, 82.850683], [2.337978, 2.694966, 3.345698, 3.570519, 31.316039], [1.354782, 1.474538, 1.888970, 2.041866, 21.518054], [3.302348, 3.613957, 4.784061, 4.957684, 76.924221], [0.456506, 0.481598, 0.546790, 0.557108, 3.176719], [2.974114, 3.385904, 4.480111, 4.625438, 67.666133]]
input_correlations: [[0.994778, -0.963643, 0.913625, 0.989218, -0.968509, 0.997042, 0.000000, 0.000000], [-0.995579, 0.959512, -0.931953, -0.981101, 0.967762, -0.994337, 0.000000, 0.000000], [-0.997733, 0.949213, -0.942520, -0.981019, 0.962122, -0.990403, 0.000000, 0.000000], [0.997487, -0.936888, 0.909016, 0.993083, -0.944832, 0.998090, 0.000000, 0.000000], [0.897247, -0.700763, 0.809261, 0.899160, -0.721259, 0.882824, 0.000000, 0.000000], [0.993361, -0.964623, 0.901547, 0.992817, -0.969664, 0.995804, 0.000000, 0.000000]]
pre_activation_mean: [0.920563, -0.347956, -0.239090, 0.854713, -0.035297, 0.751846]
pre_activation_std: [0.268177, 0.159305, 0.090287, 0.221844, 0.027813, 0.206618]
### 8
mean: [-0.731464]
std: [0.313777]
fourier: [[4.634135, 5.136416, 6.718650, 7.046784, 65.831759]]
input_correlations: [[-0.999795, 0.955090, 0.980979, -0.997415, -0.897107, -0.999537, 0.000000, 0.000000]]
pre_activation_mean: [-0.731464]
pre_activation_std: [0.313777]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.4.bias": [
0.490543,
-0.161585,
-0.074235,
0.431325,
-0.233521,
0.473756
],
"network.6.weight": [
[
0.330843,
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-0.52927,
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],
[
-0.43654,
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-0.273536,
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-0.388997
],
[
-0.366902,
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],
[
0.616239,
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],
[
0.122939,
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[
0.322544,
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],
"network.6.bias": [
0.246192,
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"network.8.weight": [
[
-0.525313,
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0.317084,
-0.252575,
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]
],
"network.8.bias": [
0.25262
]
}
## Activation Signature
### 0
mean: [0.771668, -0.117241, -0.093825, 0.697837, -0.016844, 0.593146]
std: [0.248479, 0.057827, 0.034550, 0.209439, 0.012862, 0.181870]
fourier: [[3.683442, 4.096419, 5.289387, 5.572376, 69.450144], [0.910779, 0.960365, 1.216099, 1.236543, 10.551723], [0.509367, 0.569357, 0.724791, 0.767388, 8.444218], [3.173189, 3.365314, 4.457820, 4.671735, 62.805291], [0.210485, 0.223654, 0.251263, 0.256400, 1.515923], [2.657645, 2.951955, 3.919565, 4.096937, 53.383131]]
input_correlations: [[0.112572, -0.544768, 0.072148, -0.900834, -0.323376, 0.000000, 0.000000, 0.000000], [-0.424613, -0.420726, -0.673694, -0.674063, -0.452260, 0.000000, 0.000000, 0.000000], [0.877125, 0.493670, 0.385390, -0.287422, -0.134087, 0.000000, 0.000000, 0.000000], [0.692082, -0.091073, 0.629042, -0.510476, -0.026060, 0.000000, 0.000000, 0.000000], [-0.653124, -0.003622, 0.137887, 0.411028, -0.527230, 0.000000, 0.000000, 0.000000], [-0.023163, 0.075135, 0.308934, 0.635819, 0.816402, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.631290, -2.528596, 0.837148, 0.053241, -0.036688, 2.514904]
pre_activation_std: [1.471626, 1.757832, 1.223700, 1.361698, 0.879932, 1.757702]
### 2
mean: [-0.944309, -0.874625, -0.081479, -0.195549, -0.994316, -0.854148]
std: [0.552041, 0.639786, 0.666615, 0.474535, 0.555104, 0.687490]
fourier: [[9.122581, 9.132873, 9.457256, 9.770282, 84.987819], [10.001342, 10.343601, 10.833623, 11.980032, 78.716229], [9.009985, 9.104190, 11.300221, 12.284331, 13.499955], [7.115601, 7.356920, 7.726906, 8.930107, 17.599370], [8.852974, 9.215624, 9.528296, 9.762114, 89.488440], [9.700139, 12.921988, 14.575733, 15.906211, 76.873319]]
input_correlations: [[0.079209, -0.002454, 0.267867, 0.337875, -0.050463, -0.930649, 0.000000, 0.000000], [-0.117131, -0.089945, 0.330534, 0.191258, -0.064700, -0.986890, 0.000000, 0.000000], [-0.188524, 0.036618, -0.790302, -0.735087, -0.030331, 0.622065, 0.000000, 0.000000], [-0.057056, 0.004395, -0.839228, -0.567991, -0.037274, 0.599918, 0.000000, 0.000000], [-0.033067, -0.029281, 0.295118, 0.273251, -0.119925, -0.968131, 0.000000, 0.000000], [-0.172929, -0.039887, -0.289412, -0.400624, 0.249293, -0.828483, 0.000000, 0.000000]]
pre_activation_mean: [-0.944309, -0.874625, -0.081479, -0.195549, -0.994316, -0.854148]
pre_activation_std: [0.552041, 0.639786, 0.666615, 0.474535, 0.555104, 0.687490]
### 4
mean: [0.639303, -0.258020, 0.074912, 0.484175, -0.270284, 0.647514]
std: [0.237054, 0.161263, 0.095051, 0.186506, 0.102060, 0.214865]
fourier: [[3.423729, 3.910036, 5.009370, 5.303725, 57.537244], [2.209863, 2.854338, 3.448457, 3.575369, 23.221828], [1.487728, 1.516169, 1.710024, 1.954751, 6.742040], [2.779930, 2.870213, 4.056184, 4.189021, 43.575703], [1.351437, 1.888195, 1.997286, 2.404784, 24.325536], [3.056279, 3.582239, 4.670771, 4.678326, 58.276240]]
input_correlations: [[-0.728974, -0.560295, -0.977332, -0.940117, -0.838491, -0.412604, 0.000000, 0.000000], [0.635399, 0.484220, 0.976594, 0.965209, 0.755736, 0.469757, 0.000000, 0.000000], [-0.891335, -0.767632, -0.865163, -0.794811, -0.954828, -0.374935, 0.000000, 0.000000], [-0.663910, -0.459915, -0.995238, -0.973928, -0.773974, -0.344535, 0.000000, 0.000000], [0.659896, 0.508310, 0.958533, 0.917778, 0.794029, 0.533519, 0.000000, 0.000000], [-0.690817, -0.529437, -0.981619, -0.964187, -0.800077, -0.408814, 0.000000, 0.000000]]
pre_activation_mean: [0.639303, -0.258020, 0.074912, 0.484175, -0.270284, 0.647514]
pre_activation_std: [0.237054, 0.161263, 0.095051, 0.186506, 0.102060, 0.214865]
### 6
mean: [0.920563, -0.347956, -0.239090, 0.854713, -0.035297, 0.751846]
std: [0.268177, 0.159305, 0.090287, 0.221844, 0.027813, 0.206618]
fourier: [[3.897445, 4.455607, 5.760717, 5.979833, 82.850683], [2.337978, 2.694966, 3.345698, 3.570519, 31.316039], [1.354782, 1.474538, 1.888970, 2.041866, 21.518054], [3.302348, 3.613957, 4.784061, 4.957684, 76.924221], [0.456506, 0.481598, 0.546790, 0.557108, 3.176719], [2.974114, 3.385904, 4.480111, 4.625438, 67.666133]]
input_correlations: [[0.994778, -0.963643, 0.913625, 0.989218, -0.968509, 0.997042, 0.000000, 0.000000], [-0.995579, 0.959512, -0.931953, -0.981101, 0.967762, -0.994337, 0.000000, 0.000000], [-0.997733, 0.949213, -0.942520, -0.981019, 0.962122, -0.990403, 0.000000, 0.000000], [0.997487, -0.936888, 0.909016, 0.993083, -0.944832, 0.998090, 0.000000, 0.000000], [0.897247, -0.700763, 0.809261, 0.899160, -0.721259, 0.882824, 0.000000, 0.000000], [0.993361, -0.964623, 0.901547, 0.992817, -0.969664, 0.995804, 0.000000, 0.000000]]
pre_activation_mean: [0.920563, -0.347956, -0.239090, 0.854713, -0.035297, 0.751846]
pre_activation_std: [0.268177, 0.159305, 0.090287, 0.221844, 0.027813, 0.206618]
### 8
mean: [-0.731464]
std: [0.313777]
fourier: [[4.634135, 5.136416, 6.718650, 7.046784, 65.831759]]
input_correlations: [[-0.999795, 0.955090, 0.980979, -0.997415, -0.897107, -0.999537, 0.000000, 0.000000]]
pre_activation_mean: [-0.731464]
pre_activation_std: [0.313777]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.7716683149337769, "std": 0.2484787553548813, "fourier": [3.683442312671083, 4.096419263756906, 5.289386864136277, 5.572375818787589, 69.45014378335327], "input_correlations": [0.11257173187825369, -0.5447679903454944, 0.07214817149507947, -0.9008338169985665, -0.3233763014197621, 0.0, 0.0, 0.0], "pre_activation_mean": -1.6312901973724365, "pre_activation_std": 1.471625566482544}, "1": {"mean": -0.11724137514829636, "std": 0.057827357202768326, "fourier": [0.9107793744516787, 0.960364516539049, 1.2160985124463215, 1.2365433868902438, 10.551723155425861], "input_correlations": [-0.42461252070687977, -0.4207263596492877, -0.6736936707925404, -0.6740625816802979, -0.45225951196042974, 0.0, 0.0, 0.0], "pre_activation_mean": -2.5285961627960205, "pre_activation_std": 1.7578321695327759}, "2": {"mean": -0.09382465481758118, "std": 0.034550122916698456, "fourier": [0.5093669500151653, 0.569356930665728, 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-0.5272297660805352, 0.0, 0.0, 0.0], "pre_activation_mean": -0.03668815642595291, "pre_activation_std": 0.8799323439598083}, "5": {"mean": 0.5931459069252014, "std": 0.18187014758586884, "fourier": [2.6576448835019044, 2.951954811514025, 3.919564525129474, 4.096936558920846, 53.383130800910294], "input_correlations": [-0.023163261680358496, 0.07513537312876972, 0.308933624304414, 0.6358186372242725, 0.816401942968767, 0.0, 0.0, 0.0], "pre_activation_mean": 2.5149035453796387, "pre_activation_std": 1.757702112197876}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -0.9443090558052063, "std": 0.5520409345626831, "fourier": [9.12258077560523, 9.132873001503166, 9.457256385319637, 9.770282032309153, 84.9878193885088], "input_correlations": [0.0792088114956869, -0.002453948878093915, 0.2678671881388953, 0.33787518666209104, 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0.198712, 0.567761], [-0.586414, -0.426316, -0.198635, 0.101442, -0.293247, -0.038306], [-0.412374, 0.087111, -0.380578, -0.227341, -0.193997, -0.190073], [-0.015035, 0.011753, 0.352265, -0.171835, 0.142329, 0.49398], [-0.36703, -0.189714, -0.201056, -0.589402, -0.542615, -0.420302]], "network.4.bias": [0.490543, -0.161585, -0.074235, 0.431325, -0.233521, 0.473756], "network.6.weight": [[0.330843, -0.496304, 0.297326, 0.235714, -0.52927, 0.643976], [-0.43654, 0.396683, -0.273536, 0.230112, 0.108594, -0.388997], [-0.366902, 0.186605, -0.259706, -0.033481, 0.041479, 0.041425], [0.616239, 0.114437, -0.147513, 0.1843, 0.163883, 0.612953], [0.122939, 0.354638, 0.026967, 0.241769, 0.301418, 0.026183], [0.322544, -0.344163, 0.003869, 0.504485, -0.652614, 0.191733]], "network.6.bias": [0.246192, 0.038561, -0.035595, 0.220497, -0.129025, 0.22669], "network.8.weight": [[-0.525313, 0.215439, 0.317084, -0.252575, -0.082643, -0.588126]], "network.8.bias": [0.25262]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7226835191249847, "train_acc": 0.425, "val_loss": 0.6928030252456665, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.7008070349693298, "train_acc": 0.425, "val_loss": 0.6858577728271484, "val_acc": 0.88}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6865839660167694, "train_acc": 0.65, "val_loss": 0.680361270904541, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6669614911079407, "train_acc": 0.575, "val_loss": 0.6703599691390991, "val_acc": 0.5}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6495357751846313, "train_acc": 0.575, "val_loss": 0.6441338062286377, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6419384181499481, "train_acc": 0.515, "val_loss": 0.5758852362632751, "val_acc": 0.84}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5895566642284393, "train_acc": 0.77, "val_loss": 0.5046849250793457, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5128251612186432, "train_acc": 0.835, "val_loss": 0.440817654132843, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.46379518508911133, "train_acc": 0.84, "val_loss": 0.4002281427383423, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.4053000509738922, "train_acc": 0.855, "val_loss": 0.42917799949645996, "val_acc": 0.82}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.3741624057292938, "train_acc": 0.85, "val_loss": 0.3529716432094574, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.34253551065921783, "train_acc": 0.855, "val_loss": 0.3267880976200104, "val_acc": 0.84}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.33100198209285736, "train_acc": 0.845, "val_loss": 0.3366655111312866, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.33217255771160126, "train_acc": 0.85, "val_loss": 0.4257589280605316, "val_acc": 0.82}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.372518852353096, "train_acc": 0.86, "val_loss": 0.3635927438735962, "val_acc": 0.84}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6928030252456665, "final_val_loss": 0.6441338062286377, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5758852362632751, "final_val_loss": 0.3635927438735962, "initial_val_acc": 0.84, "final_val_acc": 0.84, "best_val_acc": 0.9, "best_epoch": 6}, "improvement": 0.4, "first_improvement_epoch": 4}} |
2 | {"target_pattern": "alternating", "degraded_accuracy": 0.52, "improved_accuracy": 0.94, "improvement": 0.41999999999999993, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9451, "learning_rate": 0.07352170370310572, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.109175, 2.818719, 0.589725, 6.346766, 0.542347, 0.480877, 0.011254]
std: [0.247611, 2.639819, 0.889538, 5.995561, 0.820108, 0.744105, 0.073399]
fourier: [[3.540042, 3.597278, 3.774095, 3.784434, 9.825795], [39.682978, 39.826686, 41.805479, 48.802526, 253.684718], [12.702743, 13.283982, 13.614669, 14.183304, 53.075276], [90.197907, 92.823411, 96.245637, 112.443495, 571.208904], [11.738320, 12.177748, 12.534344, 13.020932, 48.811215], [10.564774, 10.826019, 11.350033, 11.513960, 43.278934], [1.029049, 1.046790, 1.054027, 1.075673, 1.100485]]
input_correlations: [[-0.451123, 0.046684, 0.266320, 0.620399, 0.572941, 0.000000, 0.000000, 0.000000], [-0.838947, -0.674249, -0.393040, -0.344511, -0.401531, 0.000000, 0.000000, 0.000000], [-0.382665, -0.516378, -0.311942, 0.077754, 0.714372, 0.000000, 0.000000, 0.000000], [-0.535981, 0.117182, -0.826412, 0.346737, -0.357020, 0.000000, 0.000000, 0.000000], [0.187975, 0.796551, 0.397498, 0.735648, 0.322375, 0.000000, 0.000000, 0.000000], [-0.326604, -0.784723, -0.404664, -0.723476, -0.386287, 0.000000, 0.000000, 0.000000], [0.299109, -0.500941, 0.250883, -0.870616, -0.010414, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.818696, -2.501892, -0.822215, -1.193020, 3.172617, -4.481411, -2.673734]
pre_activation_std: [1.579749, 2.047694, 1.457211, 2.725842, 2.033733, 2.734886, 3.342324]
### 2
mean: [0.046701, 0.576169, -0.317537, 2.039889, -0.392796, 1.912346, -0.148570]
std: [0.888122, 0.989955, 0.912627, 1.807250, 1.004672, 1.580047, 0.719862]
fourier: [[12.138823, 13.292778, 14.524030, 15.139685, 15.279536], [15.186599, 17.105412, 17.689741, 19.631211, 51.855181], [14.037748, 14.046630, 14.324026, 14.595218, 28.578339], [26.457611, 27.907662, 29.576852, 31.957664, 183.589983], [13.966606, 13.971229, 14.065081, 18.619016, 35.351619], [25.023684, 25.756558, 27.793710, 30.238611, 172.111113], [10.046724, 10.200105, 10.219335, 13.231826, 13.371273]]
input_correlations: [[-0.461015, 0.041048, -0.674408, 0.665587, 0.015679, -0.026081, 0.218339, 0.000000], [0.705537, -0.012980, 0.605976, -0.232086, 0.364725, 0.193617, -0.582957, 0.000000], [-0.587325, -0.184903, -0.475390, 0.133326, -0.631587, -0.354830, 0.671833, 0.000000], [0.666243, 0.318816, 0.543180, -0.234899, 0.761401, 0.527284, -0.327399, 0.000000], [-0.301831, -0.238717, -0.241546, 0.411012, -0.552761, -0.299754, 0.603606, 0.000000], [0.860624, 0.192439, 0.755434, -0.184844, 0.600155, 0.456471, -0.196839, 0.000000], [-0.282423, -0.179062, -0.250629, 0.467428, -0.477218, -0.244941, 0.617437, 0.000000]]
pre_activation_mean: [0.046701, 0.576169, -0.317537, 2.039889, -0.392796, 1.912346, -0.148570]
pre_activation_std: [0.888122, 0.989955, 0.912627, 1.807250, 1.004672, 1.580047, 0.719862]
### 4
mean: [0.746120, 2.521878, 2.783477, 1.575671, -1.260104, -1.711524, -1.743184]
std: [1.283069, 2.550721, 2.820377, 1.641124, 0.716969, 1.139416, 1.624784]
fourier: [[19.312209, 22.184224, 22.666084, 24.525093, 67.150790], [37.105487, 37.260093, 39.892260, 46.105740, 226.969044], [39.817725, 41.468382, 45.144917, 51.989691, 250.512958], [22.809361, 24.541908, 26.987565, 27.108505, 141.810437], [9.650672, 9.732897, 11.875901, 13.468849, 113.409391], [17.006246, 18.441666, 18.554156, 21.710884, 154.037166], [26.764447, 27.350296, 27.355708, 31.821535, 156.886599]]
input_correlations: [[-0.543267, 0.955710, -0.523349, 0.892413, -0.605463, 0.958977, -0.650078, 0.000000], [-0.480197, 0.848656, -0.604231, 0.976584, -0.650178, 0.915328, -0.705129, 0.000000], [-0.490045, 0.870489, -0.586999, 0.972847, -0.639142, 0.929122, -0.694126, 0.000000], [-0.433454, 0.737188, -0.649048, 0.973975, -0.671331, 0.835642, -0.727716, 0.000000], [-0.247012, -0.735184, 0.249700, -0.749873, 0.061189, -0.817258, 0.073698, 0.000000], [0.396515, -0.911086, 0.503402, -0.972666, 0.531289, -0.971453, 0.584345, 0.000000], [0.389659, -0.968604, 0.433768, -0.918371, 0.466042, -0.993937, 0.513378, 0.000000]]
pre_activation_mean: [0.746120, 2.521878, 2.783477, 1.575671, -1.260104, -1.711524, -1.743184]
pre_activation_std: [1.283069, 2.550721, 2.820377, 1.641124, 0.716969, 1.139416, 1.624784]
### 6
mean: [-2.926606, 2.185494, -1.996075, 3.310276, -3.481503, -1.599070, 4.177769]
std: [3.492094, 2.311165, 2.440366, 3.152233, 4.134065, 1.736550, 3.639245]
fourier: [[52.995579, 54.260634, 54.370605, 65.286344, 263.394531], [35.559560, 36.446520, 36.623517, 43.913150, 196.694446], [36.873876, 37.382486, 37.483009, 44.934954, 179.646760], [47.777552, 48.084976, 48.366158, 57.825448, 297.924786], [63.570713, 65.435956, 65.853095, 78.891067, 313.335245], [25.612326, 25.700745, 27.770131, 30.456926, 143.916315], [55.995395, 57.506224, 57.941317, 69.320516, 375.999163]]
input_correlations: [[-0.910539, -0.999181, -0.997031, -0.985212, -0.656651, -0.914423, -0.541564, 0.000000], [0.928589, 0.999534, 0.999483, 0.975878, 0.663762, 0.910700, 0.549932, 0.000000], [-0.902853, -0.999007, -0.996195, -0.987820, -0.644743, -0.912997, -0.527320, 0.000000], [0.899977, 0.998738, 0.995634, 0.988753, 0.643445, 0.913824, 0.525930, 0.000000], [-0.931096, -0.999206, -0.999383, -0.974730, -0.670754, -0.909432, -0.553304, 0.000000], [-0.856396, -0.989935, -0.982851, -0.998105, -0.617018, -0.915602, -0.500564, 0.000000], [0.935327, 0.999033, 0.999889, 0.971370, 0.665583, 0.904677, 0.546664, 0.000000]]
pre_activation_mean: [-2.926606, 2.185494, -1.996075, 3.310276, -3.481503, -1.599070, 4.177769]
pre_activation_std: [3.492094, 2.311165, 2.440366, 3.152233, 4.134065, 1.736550, 3.639245]
### 8
mean: [-1.470797, 2.657326, -4.807086, 6.164118, -4.368451, -2.017333, -2.231228]
std: [1.711357, 2.836052, 5.895554, 6.199331, 5.397875, 3.128739, 2.221221]
fourier: [[24.762868, 25.253796, 26.509284, 30.686234, 132.371718], [41.457336, 41.965026, 43.824336, 51.533367, 239.159323], [88.724109, 88.896353, 90.032965, 107.920572, 432.637778], [94.710470, 95.362735, 95.940115, 115.332941, 554.770624], [81.626549, 81.649614, 82.615450, 99.206570, 393.160602], [46.267593, 46.688209, 48.269824, 57.220615, 181.559984], [33.764816, 34.976865, 35.367906, 41.953514, 200.810507]]
input_correlations: [[0.791816, -0.980162, 0.765237, -0.986563, 0.795379, 0.644335, -0.988395, 0.000000], [-0.770603, 0.986423, -0.742702, 0.991343, -0.774460, -0.617672, 0.992876, 0.000000], [0.735720, -0.992971, 0.705313, -0.997647, 0.740223, 0.572373, -0.996011, 0.000000], [-0.716143, 0.996388, -0.685555, 0.998143, -0.720683, -0.551763, 0.998648, 0.000000], [0.735447, -0.993450, 0.705299, -0.997293, 0.739801, 0.573202, -0.996763, 0.000000], [0.757031, -0.989627, 0.728002, -0.994113, 0.761329, 0.599753, -0.994793, 0.000000], [0.689361, -0.998885, 0.658313, -0.997824, 0.694027, 0.522245, -0.999721, 0.000000]]
pre_activation_mean: [-1.470797, 2.657326, -4.807086, 6.164118, -4.368451, -2.017333, -2.231228]
pre_activation_std: [1.711357, 2.836052, 5.895554, 6.199331, 5.397875, 3.128739, 2.221221]
### 10
mean: [-3.336704]
std: [5.493570]
fourier: [[77.920118, 82.233546, 84.681638, 97.724439, 300.303339]]
input_correlations: [[0.721954, -0.990290, 0.833163, -0.983610, 0.832224, 0.829465, 0.486369, 0.000000]]
pre_activation_mean: [-3.336704]
pre_activation_std: [5.493570]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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0.016497,
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0.377212,
0.46275
],
[
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-0.048854,
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],
[
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0.043336,
0.653931
],
[
-0.486114,
0.468888,
-1.051172,
0.336788,
-0.250392
],
[
-0.109708,
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0.25548,
0.479164,
0.238863
],
[
-0.074179,
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-0.382477
],
[
0.546925,
-0.782979,
0.435782,
-1.139192,
-0.03333
]
],
"network.0.bias": [
0.445738,
-0.026591,
-0.432475,
0.339879,
0.215415,
-0.407969,
-0.353849
],
"network.2.weight": [
[
-0.221768,
0.295291,
-0.566029,
0.607401,
0.072632,
0.07435,
0.29675
],
[
0.390566,
-0.283276,
0.373778,
-0.352655,
-0.0111,
-0.21586,
-0.6314
],
[
-0.080529,
0.045784,
-0.381584,
0.322332,
-0.208936,
-0.470206,
0.61041
],
[
0.062086,
-0.112544,
0.891917,
-0.861448,
0.654051,
0.532569,
-0.493258
],
[
0.119339,
-0.357433,
-0.249549,
0.668707,
-0.333574,
-0.504545,
0.615059
],
[
0.495847,
-0.115094,
0.920688,
-0.522015,
0.238003,
0.113081,
-0.277181
],
[
0.077411,
0.193998,
-0.19702,
0.508568,
-0.220905,
-0.061286,
0.457584
]
],
"network.2.bias": [
0.014641,
0.12025,
0.247411,
0.211555,
0.010649,
0.381745,
0.116955
],
"network.4.weight": [
[
-0.334707,
0.304441,
-0.279457,
-0.029286,
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0.541405,
-0.115904
],
[
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0.095578,
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0.851065,
-0.35692,
0.358511,
-0.724027
],
[
-0.291779,
0.347184,
-0.297729,
0.891535,
-0.534177,
0.369992,
-0.322145
],
[
0.030368,
-0.166714,
-0.196908,
0.856735,
-0.289794,
-0.05414,
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],
[
-0.915498,
-0.114461,
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-0.092932,
0.474361,
-0.311556,
-0.199999
],
[
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0.247388,
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0.273014
],
[
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0.090498,
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-0.611112,
0.47962
]
],
"network.4.bias": [
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"network.6.weight": [
[
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[
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0.099797,
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0.550959,
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[
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],
[
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0.020794,
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],
[
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[
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],
[
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-0.220082,
0.208571
]
],
"network.6.bias": [
0.540844,
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0.268893
],
"network.8.weight": [
[
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],
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],
[
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[
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],
[
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],
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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]
],
"network.10.bias": [
0.532356
]
}
## Activation Signature
### 0
mean: [0.109175, 2.818719, 0.589725, 6.346766, 0.542347, 0.480877, 0.011254]
std: [0.247611, 2.639819, 0.889538, 5.995561, 0.820108, 0.744105, 0.073399]
fourier: [[3.540042, 3.597278, 3.774095, 3.784434, 9.825795], [39.682978, 39.826686, 41.805479, 48.802526, 253.684718], [12.702743, 13.283982, 13.614669, 14.183304, 53.075276], [90.197907, 92.823411, 96.245637, 112.443495, 571.208904], [11.738320, 12.177748, 12.534344, 13.020932, 48.811215], [10.564774, 10.826019, 11.350033, 11.513960, 43.278934], [1.029049, 1.046790, 1.054027, 1.075673, 1.100485]]
input_correlations: [[-0.451123, 0.046684, 0.266320, 0.620399, 0.572941, 0.000000, 0.000000, 0.000000], [-0.838947, -0.674249, -0.393040, -0.344511, -0.401531, 0.000000, 0.000000, 0.000000], [-0.382665, -0.516378, -0.311942, 0.077754, 0.714372, 0.000000, 0.000000, 0.000000], [-0.535981, 0.117182, -0.826412, 0.346737, -0.357020, 0.000000, 0.000000, 0.000000], [0.187975, 0.796551, 0.397498, 0.735648, 0.322375, 0.000000, 0.000000, 0.000000], [-0.326604, -0.784723, -0.404664, -0.723476, -0.386287, 0.000000, 0.000000, 0.000000], [0.299109, -0.500941, 0.250883, -0.870616, -0.010414, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.818696, -2.501892, -0.822215, -1.193020, 3.172617, -4.481411, -2.673734]
pre_activation_std: [1.579749, 2.047694, 1.457211, 2.725842, 2.033733, 2.734886, 3.342324]
### 2
mean: [0.046701, 0.576169, -0.317537, 2.039889, -0.392796, 1.912346, -0.148570]
std: [0.888122, 0.989955, 0.912627, 1.807250, 1.004672, 1.580047, 0.719862]
fourier: [[12.138823, 13.292778, 14.524030, 15.139685, 15.279536], [15.186599, 17.105412, 17.689741, 19.631211, 51.855181], [14.037748, 14.046630, 14.324026, 14.595218, 28.578339], [26.457611, 27.907662, 29.576852, 31.957664, 183.589983], [13.966606, 13.971229, 14.065081, 18.619016, 35.351619], [25.023684, 25.756558, 27.793710, 30.238611, 172.111113], [10.046724, 10.200105, 10.219335, 13.231826, 13.371273]]
input_correlations: [[-0.461015, 0.041048, -0.674408, 0.665587, 0.015679, -0.026081, 0.218339, 0.000000], [0.705537, -0.012980, 0.605976, -0.232086, 0.364725, 0.193617, -0.582957, 0.000000], [-0.587325, -0.184903, -0.475390, 0.133326, -0.631587, -0.354830, 0.671833, 0.000000], [0.666243, 0.318816, 0.543180, -0.234899, 0.761401, 0.527284, -0.327399, 0.000000], [-0.301831, -0.238717, -0.241546, 0.411012, -0.552761, -0.299754, 0.603606, 0.000000], [0.860624, 0.192439, 0.755434, -0.184844, 0.600155, 0.456471, -0.196839, 0.000000], [-0.282423, -0.179062, -0.250629, 0.467428, -0.477218, -0.244941, 0.617437, 0.000000]]
pre_activation_mean: [0.046701, 0.576169, -0.317537, 2.039889, -0.392796, 1.912346, -0.148570]
pre_activation_std: [0.888122, 0.989955, 0.912627, 1.807250, 1.004672, 1.580047, 0.719862]
### 4
mean: [0.746120, 2.521878, 2.783477, 1.575671, -1.260104, -1.711524, -1.743184]
std: [1.283069, 2.550721, 2.820377, 1.641124, 0.716969, 1.139416, 1.624784]
fourier: [[19.312209, 22.184224, 22.666084, 24.525093, 67.150790], [37.105487, 37.260093, 39.892260, 46.105740, 226.969044], [39.817725, 41.468382, 45.144917, 51.989691, 250.512958], [22.809361, 24.541908, 26.987565, 27.108505, 141.810437], [9.650672, 9.732897, 11.875901, 13.468849, 113.409391], [17.006246, 18.441666, 18.554156, 21.710884, 154.037166], [26.764447, 27.350296, 27.355708, 31.821535, 156.886599]]
input_correlations: [[-0.543267, 0.955710, -0.523349, 0.892413, -0.605463, 0.958977, -0.650078, 0.000000], [-0.480197, 0.848656, -0.604231, 0.976584, -0.650178, 0.915328, -0.705129, 0.000000], [-0.490045, 0.870489, -0.586999, 0.972847, -0.639142, 0.929122, -0.694126, 0.000000], [-0.433454, 0.737188, -0.649048, 0.973975, -0.671331, 0.835642, -0.727716, 0.000000], [-0.247012, -0.735184, 0.249700, -0.749873, 0.061189, -0.817258, 0.073698, 0.000000], [0.396515, -0.911086, 0.503402, -0.972666, 0.531289, -0.971453, 0.584345, 0.000000], [0.389659, -0.968604, 0.433768, -0.918371, 0.466042, -0.993937, 0.513378, 0.000000]]
pre_activation_mean: [0.746120, 2.521878, 2.783477, 1.575671, -1.260104, -1.711524, -1.743184]
pre_activation_std: [1.283069, 2.550721, 2.820377, 1.641124, 0.716969, 1.139416, 1.624784]
### 6
mean: [-2.926606, 2.185494, -1.996075, 3.310276, -3.481503, -1.599070, 4.177769]
std: [3.492094, 2.311165, 2.440366, 3.152233, 4.134065, 1.736550, 3.639245]
fourier: [[52.995579, 54.260634, 54.370605, 65.286344, 263.394531], [35.559560, 36.446520, 36.623517, 43.913150, 196.694446], [36.873876, 37.382486, 37.483009, 44.934954, 179.646760], [47.777552, 48.084976, 48.366158, 57.825448, 297.924786], [63.570713, 65.435956, 65.853095, 78.891067, 313.335245], [25.612326, 25.700745, 27.770131, 30.456926, 143.916315], [55.995395, 57.506224, 57.941317, 69.320516, 375.999163]]
input_correlations: [[-0.910539, -0.999181, -0.997031, -0.985212, -0.656651, -0.914423, -0.541564, 0.000000], [0.928589, 0.999534, 0.999483, 0.975878, 0.663762, 0.910700, 0.549932, 0.000000], [-0.902853, -0.999007, -0.996195, -0.987820, -0.644743, -0.912997, -0.527320, 0.000000], [0.899977, 0.998738, 0.995634, 0.988753, 0.643445, 0.913824, 0.525930, 0.000000], [-0.931096, -0.999206, -0.999383, -0.974730, -0.670754, -0.909432, -0.553304, 0.000000], [-0.856396, -0.989935, -0.982851, -0.998105, -0.617018, -0.915602, -0.500564, 0.000000], [0.935327, 0.999033, 0.999889, 0.971370, 0.665583, 0.904677, 0.546664, 0.000000]]
pre_activation_mean: [-2.926606, 2.185494, -1.996075, 3.310276, -3.481503, -1.599070, 4.177769]
pre_activation_std: [3.492094, 2.311165, 2.440366, 3.152233, 4.134065, 1.736550, 3.639245]
### 8
mean: [-1.470797, 2.657326, -4.807086, 6.164118, -4.368451, -2.017333, -2.231228]
std: [1.711357, 2.836052, 5.895554, 6.199331, 5.397875, 3.128739, 2.221221]
fourier: [[24.762868, 25.253796, 26.509284, 30.686234, 132.371718], [41.457336, 41.965026, 43.824336, 51.533367, 239.159323], [88.724109, 88.896353, 90.032965, 107.920572, 432.637778], [94.710470, 95.362735, 95.940115, 115.332941, 554.770624], [81.626549, 81.649614, 82.615450, 99.206570, 393.160602], [46.267593, 46.688209, 48.269824, 57.220615, 181.559984], [33.764816, 34.976865, 35.367906, 41.953514, 200.810507]]
input_correlations: [[0.791816, -0.980162, 0.765237, -0.986563, 0.795379, 0.644335, -0.988395, 0.000000], [-0.770603, 0.986423, -0.742702, 0.991343, -0.774460, -0.617672, 0.992876, 0.000000], [0.735720, -0.992971, 0.705313, -0.997647, 0.740223, 0.572373, -0.996011, 0.000000], [-0.716143, 0.996388, -0.685555, 0.998143, -0.720683, -0.551763, 0.998648, 0.000000], [0.735447, -0.993450, 0.705299, -0.997293, 0.739801, 0.573202, -0.996763, 0.000000], [0.757031, -0.989627, 0.728002, -0.994113, 0.761329, 0.599753, -0.994793, 0.000000], [0.689361, -0.998885, 0.658313, -0.997824, 0.694027, 0.522245, -0.999721, 0.000000]]
pre_activation_mean: [-1.470797, 2.657326, -4.807086, 6.164118, -4.368451, -2.017333, -2.231228]
pre_activation_std: [1.711357, 2.836052, 5.895554, 6.199331, 5.397875, 3.128739, 2.221221]
### 10
mean: [-3.336704]
std: [5.493570]
fourier: [[77.920118, 82.233546, 84.681638, 97.724439, 300.303339]]
input_correlations: [[0.721954, -0.990290, 0.833163, -0.983610, 0.832224, 0.829465, 0.486369, 0.000000]]
pre_activation_mean: [-3.336704]
pre_activation_std: [5.493570]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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{"initial_val_loss": 0.5382131934165955, "final_val_loss": 0.4782869815826416, "initial_val_acc": 0.82, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 5}, "improvement": 0.41999999999999993, "first_improvement_epoch": 1}} |
3 | {"target_pattern": "starts_with", "degraded_accuracy": 0.56, "improved_accuracy": 0.72, "improvement": 0.15999999999999992, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8547, "learning_rate": 0.09278016261197346, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
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[
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[
-0.782072,
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],
[
-0.244713,
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[
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]
],
"network.8.bias": [
-0.638659,
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],
"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [-0.063252, -0.047435, 5.459183, -0.113264, -0.052374, -0.057558, -0.079918, 0.396599]
std: [0.072712, 0.082271, 7.629412, 0.057530, 0.067734, 0.066378, 0.074024, 0.840018]
fourier: [[1.016403, 1.017355, 1.086460, 1.455450, 5.692721], [1.306730, 1.388301, 1.742138, 2.207319, 4.269141], [125.813479, 130.620906, 136.336361, 141.960880, 491.326505], [0.818173, 1.014994, 1.075558, 1.238368, 10.193772], [0.944015, 0.987341, 1.037583, 1.348574, 4.713678], [1.157972, 1.180459, 1.248469, 1.614528, 5.180177], [1.101998, 1.263334, 1.425211, 1.447873, 7.192637], [12.755465, 13.387873, 15.210297, 19.532815, 35.693908]]
input_correlations: [[-0.285864, -0.693764, -0.766081, -0.500482, -0.284817, 0.000000, 0.000000, 0.000000], [0.968300, 0.239037, 0.113510, -0.191398, 0.084417, 0.000000, 0.000000, 0.000000], [-0.824883, -0.608043, -0.485437, -0.451607, -0.192951, 0.000000, 0.000000, 0.000000], [-0.737517, -0.264674, -0.027658, 0.309482, 0.495864, 0.000000, 0.000000, 0.000000], [0.374354, -0.536596, 0.179004, -0.790820, -0.157127, 0.000000, 0.000000, 0.000000], [0.906811, 0.562422, 0.456708, 0.079035, -0.089370, 0.000000, 0.000000, 0.000000], [-0.560280, -0.582273, -0.772736, -0.309128, -0.560228, 0.000000, 0.000000, 0.000000], [-0.458519, -0.691133, -0.501137, -0.692489, -0.455262, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.711778, 0.008105, -4.423030, 1.139804, -1.565620, 3.021173, -6.410510, -4.846916]
pre_activation_std: [2.915472, 2.164498, 3.109953, 2.723539, 2.184441, 3.153539, 4.172297, 2.681087]
### 2
mean: [-2.168948, 3.176728, -0.600210, -4.106256, -0.560455, 1.264138, 0.970482, -0.185846]
std: [1.056696, 5.769662, 3.619799, 2.167819, 2.690263, 3.926401, 2.001988, 1.490799]
fourier: [[18.952939, 18.980485, 19.006569, 23.816825, 195.205351], [85.114394, 94.131090, 104.889098, 119.911237, 285.905518], [54.018886, 55.622330, 58.522323, 63.674019, 78.187804], [37.875793, 39.904033, 44.185393, 47.261015, 369.563033], [41.118158, 41.370042, 43.597514, 50.440937, 58.392758], [62.016429, 63.978147, 69.758916, 86.121918, 113.772389], [29.082793, 32.940863, 36.159430, 37.686986, 87.343343], [22.109098, 22.140585, 22.646025, 23.548458, 32.942463]]
input_correlations: [[-0.243684, -0.839055, -0.357495, -0.002875, -0.679525, -0.639850, -0.346157, -0.316127], [0.199741, 0.864763, 0.393635, -0.688344, 0.277567, 0.975990, 0.253847, 0.239222], [-0.149324, -0.825157, -0.345686, 0.764506, -0.252090, -0.944668, -0.196377, -0.184872], [-0.485895, -0.762210, -0.554603, -0.141826, -0.192036, -0.762414, -0.549126, -0.533804], [-0.122658, -0.694996, -0.317271, 0.827701, -0.182559, -0.883527, -0.155315, -0.145331], [0.159175, 0.833013, 0.363189, -0.761568, 0.317696, 0.947990, 0.210484, 0.197293], [0.281794, 0.715824, 0.456642, -0.659583, 0.106806, 0.942908, 0.313913, 0.304914], [0.068732, 0.641787, 0.262552, -0.880464, 0.179167, 0.829337, 0.094240, 0.087304]]
pre_activation_mean: [-2.168948, 3.176728, -0.600210, -4.106256, -0.560455, 1.264138, 0.970482, -0.185846]
pre_activation_std: [1.056696, 5.769662, 3.619799, 2.167819, 2.690263, 3.926401, 2.001988, 1.490799]
### 4
mean: [-0.023564, -5.291553, -0.168148, -0.657642, 2.249493, -1.575741, 1.934828, -0.518488]
std: [3.096854, 6.523293, 2.494818, 3.031830, 5.416792, 1.491733, 4.808349, 2.404062]
fourier: [[44.590426, 47.523257, 50.795219, 53.286361, 74.881259], [112.105404, 114.187655, 116.725636, 130.039814, 476.239731], [35.225853, 38.697846, 39.365533, 39.506274, 59.459187], [47.934108, 48.642311, 53.621084, 59.187763, 71.118778], [80.104612, 88.917493, 98.938272, 116.144712, 202.454338], [24.670217, 25.101100, 28.416120, 32.674852, 141.816668], [71.933313, 77.184673, 86.180440, 105.845687, 174.134546], [37.849085, 39.396578, 44.615969, 46.663932, 52.585037]]
input_correlations: [[0.198104, 0.871123, -0.808510, 0.158933, -0.754274, 0.851205, 0.825345, 0.761113], [-0.605766, -0.972688, 0.213611, -0.403694, 0.123100, -0.977939, -0.938956, -0.963754], [-0.049215, -0.792517, 0.887166, -0.114629, 0.840610, -0.762222, -0.791269, -0.701788], [-0.237229, -0.901536, 0.771741, -0.191393, 0.711668, -0.882971, -0.859519, -0.800428], [0.318404, 0.955002, -0.674340, 0.253964, -0.603813, 0.937116, 0.930408, 0.881870], [-0.322293, 0.172169, -0.884978, -0.261559, -0.913341, 0.155419, 0.079065, -0.003585], [0.261418, 0.930611, -0.725654, 0.230401, -0.658787, 0.909362, 0.913983, 0.855691], [-0.355917, -0.958565, 0.659880, -0.256909, 0.589198, -0.945157, -0.907822, -0.867681]]
pre_activation_mean: [-0.023564, -5.291553, -0.168148, -0.657642, 2.249493, -1.575741, 1.934828, -0.518488]
pre_activation_std: [3.096854, 6.523293, 2.494818, 3.031830, 5.416792, 1.491733, 4.808349, 2.404062]
### 6
mean: [1.810369, -0.021512, 2.107060, 1.406364, -3.169819, 2.569589, -3.369709, -2.872125]
std: [6.336715, 2.688047, 6.406757, 3.174582, 3.791196, 8.222282, 3.200397, 3.035137]
fourier: [[95.148489, 103.211931, 114.527258, 141.868447, 162.933222], [38.608889, 41.364192, 41.937709, 44.023066, 64.560572], [96.168499, 104.299865, 115.034629, 143.466747, 189.635382], [47.163669, 53.713387, 58.382370, 65.532129, 126.572731], [60.947503, 64.241158, 66.773923, 78.268382, 285.283771], [123.331325, 133.825769, 147.771016, 184.068316, 231.263010], [53.053230, 57.498847, 59.472622, 70.017963, 303.273764], [50.804546, 52.214977, 53.481324, 56.033661, 258.491282]]
input_correlations: [[0.880181, 0.143327, -0.668432, -0.684266, 0.926993, 0.162515, 0.932999, -0.746726], [-0.738233, -0.086200, 0.832302, 0.844695, -0.803753, -0.037755, -0.814828, 0.886803], [0.875068, 0.144201, -0.674928, -0.690617, 0.923816, 0.152923, 0.930166, -0.752151], [0.932042, 0.166340, -0.566851, -0.583411, 0.967723, 0.201084, 0.970617, -0.651070], [0.066607, -0.118663, -0.977315, -0.973279, 0.138784, -0.241607, 0.156400, -0.934778], [0.873586, 0.143795, -0.676701, -0.692356, 0.922919, 0.147907, 0.929353, -0.753666], [-0.921604, -0.248268, -0.071816, -0.050539, -0.912617, -0.396934, -0.904698, 0.052562], [-0.980755, -0.221815, 0.285473, 0.305328, -0.998225, -0.301780, -0.996156, 0.394378]]
pre_activation_mean: [1.810369, -0.021512, 2.107060, 1.406364, -3.169819, 2.569589, -3.369709, -2.872125]
pre_activation_std: [6.336715, 2.688047, 6.406757, 3.174582, 3.791196, 8.222282, 3.200397, 3.035137]
### 8
mean: [-3.303798, -8.327381, 5.389651, -1.624331, -4.207416, -7.768635, -5.319980, -0.452927]
std: [2.685289, 11.413898, 7.686568, 1.134552, 3.554849, 10.283742, 6.556721, 1.802851]
fourier: [[44.501608, 46.485398, 49.604659, 58.887661, 297.341787], [189.281033, 192.416787, 204.504860, 210.769446, 749.464307], [123.941706, 135.346153, 136.626145, 143.022891, 485.068602], [17.611233, 18.266152, 20.642122, 25.274867, 146.189797], [60.494739, 61.783950, 65.096444, 77.893469, 378.667447], [171.202997, 176.969694, 183.347164, 189.931355, 699.177169], [109.047830, 112.774723, 116.843441, 121.036938, 478.798214], [27.154425, 29.687479, 32.105363, 40.763429, 41.426273]]
input_correlations: [[-0.899102, -0.066390, -0.893813, -0.901070, -0.525924, -0.894660, -0.765179, -0.692087], [-0.999854, 0.368919, -0.999701, -0.999216, -0.268996, -0.999797, -0.608309, -0.809432], [0.998430, -0.424629, 0.999083, 0.997672, 0.225053, 0.999046, 0.575502, 0.812261], [0.244986, -0.988130, 0.258737, 0.236022, -0.621276, 0.256322, -0.265392, 0.353922], [-0.900715, -0.063893, -0.895063, -0.902944, -0.537444, -0.896091, -0.750558, -0.681011], [-0.999442, 0.348136, -0.999042, -0.999013, -0.281779, -0.999154, -0.620143, -0.807708], [-0.999408, 0.349015, -0.999107, -0.999006, -0.280205, -0.999214, -0.619072, -0.807839], [-0.899665, 0.740950, -0.905887, -0.895443, 0.073932, -0.904829, -0.355720, -0.796181]]
pre_activation_mean: [-3.303798, -8.327381, 5.389651, -1.624331, -4.207416, -7.768635, -5.319980, -0.452927]
pre_activation_std: [2.685289, 11.413898, 7.686568, 1.134552, 3.554849, 10.283742, 6.556721, 1.802851]
### 10
mean: [-1.836541]
std: [2.525520]
fourier: [[39.652895, 45.246440, 47.340297, 47.403673, 165.288728]]
input_correlations: [[-0.509779, -0.458779, -0.995639, 0.319135, -0.457394, -0.631177, -0.766624, 0.464232]]
pre_activation_mean: [-1.836541]
pre_activation_std: [2.525520]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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-0.720887,
-0.585081,
-0.475027
],
[
-0.244713,
-0.154958,
-0.578327,
0.124695,
-0.177794,
-0.474472,
0.121434,
-0.132092
],
[
-0.018096,
0.461575,
-0.157792,
0.239397,
-0.007331,
-0.172966,
-0.17164,
-0.353527
]
],
"network.8.bias": [
-0.638659,
-0.150149,
0.191006,
-0.827546,
-0.514604,
-0.398455,
-0.481806,
0.018174
],
"network.10.weight": [
[
0.292344,
-0.147332,
-0.319354,
0.339215,
0.519592,
-0.382155,
-0.201649,
0.223999
]
],
"network.10.bias": [
-0.14294
]
}
## Activation Signature
### 0
mean: [-0.063252, -0.047435, 5.459183, -0.113264, -0.052374, -0.057558, -0.079918, 0.396599]
std: [0.072712, 0.082271, 7.629412, 0.057530, 0.067734, 0.066378, 0.074024, 0.840018]
fourier: [[1.016403, 1.017355, 1.086460, 1.455450, 5.692721], [1.306730, 1.388301, 1.742138, 2.207319, 4.269141], [125.813479, 130.620906, 136.336361, 141.960880, 491.326505], [0.818173, 1.014994, 1.075558, 1.238368, 10.193772], [0.944015, 0.987341, 1.037583, 1.348574, 4.713678], [1.157972, 1.180459, 1.248469, 1.614528, 5.180177], [1.101998, 1.263334, 1.425211, 1.447873, 7.192637], [12.755465, 13.387873, 15.210297, 19.532815, 35.693908]]
input_correlations: [[-0.285864, -0.693764, -0.766081, -0.500482, -0.284817, 0.000000, 0.000000, 0.000000], [0.968300, 0.239037, 0.113510, -0.191398, 0.084417, 0.000000, 0.000000, 0.000000], [-0.824883, -0.608043, -0.485437, -0.451607, -0.192951, 0.000000, 0.000000, 0.000000], [-0.737517, -0.264674, -0.027658, 0.309482, 0.495864, 0.000000, 0.000000, 0.000000], [0.374354, -0.536596, 0.179004, -0.790820, -0.157127, 0.000000, 0.000000, 0.000000], [0.906811, 0.562422, 0.456708, 0.079035, -0.089370, 0.000000, 0.000000, 0.000000], [-0.560280, -0.582273, -0.772736, -0.309128, -0.560228, 0.000000, 0.000000, 0.000000], [-0.458519, -0.691133, -0.501137, -0.692489, -0.455262, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.711778, 0.008105, -4.423030, 1.139804, -1.565620, 3.021173, -6.410510, -4.846916]
pre_activation_std: [2.915472, 2.164498, 3.109953, 2.723539, 2.184441, 3.153539, 4.172297, 2.681087]
### 2
mean: [-2.168948, 3.176728, -0.600210, -4.106256, -0.560455, 1.264138, 0.970482, -0.185846]
std: [1.056696, 5.769662, 3.619799, 2.167819, 2.690263, 3.926401, 2.001988, 1.490799]
fourier: [[18.952939, 18.980485, 19.006569, 23.816825, 195.205351], [85.114394, 94.131090, 104.889098, 119.911237, 285.905518], [54.018886, 55.622330, 58.522323, 63.674019, 78.187804], [37.875793, 39.904033, 44.185393, 47.261015, 369.563033], [41.118158, 41.370042, 43.597514, 50.440937, 58.392758], [62.016429, 63.978147, 69.758916, 86.121918, 113.772389], [29.082793, 32.940863, 36.159430, 37.686986, 87.343343], [22.109098, 22.140585, 22.646025, 23.548458, 32.942463]]
input_correlations: [[-0.243684, -0.839055, -0.357495, -0.002875, -0.679525, -0.639850, -0.346157, -0.316127], [0.199741, 0.864763, 0.393635, -0.688344, 0.277567, 0.975990, 0.253847, 0.239222], [-0.149324, -0.825157, -0.345686, 0.764506, -0.252090, -0.944668, -0.196377, -0.184872], [-0.485895, -0.762210, -0.554603, -0.141826, -0.192036, -0.762414, -0.549126, -0.533804], [-0.122658, -0.694996, -0.317271, 0.827701, -0.182559, -0.883527, -0.155315, -0.145331], [0.159175, 0.833013, 0.363189, -0.761568, 0.317696, 0.947990, 0.210484, 0.197293], [0.281794, 0.715824, 0.456642, -0.659583, 0.106806, 0.942908, 0.313913, 0.304914], [0.068732, 0.641787, 0.262552, -0.880464, 0.179167, 0.829337, 0.094240, 0.087304]]
pre_activation_mean: [-2.168948, 3.176728, -0.600210, -4.106256, -0.560455, 1.264138, 0.970482, -0.185846]
pre_activation_std: [1.056696, 5.769662, 3.619799, 2.167819, 2.690263, 3.926401, 2.001988, 1.490799]
### 4
mean: [-0.023564, -5.291553, -0.168148, -0.657642, 2.249493, -1.575741, 1.934828, -0.518488]
std: [3.096854, 6.523293, 2.494818, 3.031830, 5.416792, 1.491733, 4.808349, 2.404062]
fourier: [[44.590426, 47.523257, 50.795219, 53.286361, 74.881259], [112.105404, 114.187655, 116.725636, 130.039814, 476.239731], [35.225853, 38.697846, 39.365533, 39.506274, 59.459187], [47.934108, 48.642311, 53.621084, 59.187763, 71.118778], [80.104612, 88.917493, 98.938272, 116.144712, 202.454338], [24.670217, 25.101100, 28.416120, 32.674852, 141.816668], [71.933313, 77.184673, 86.180440, 105.845687, 174.134546], [37.849085, 39.396578, 44.615969, 46.663932, 52.585037]]
input_correlations: [[0.198104, 0.871123, -0.808510, 0.158933, -0.754274, 0.851205, 0.825345, 0.761113], [-0.605766, -0.972688, 0.213611, -0.403694, 0.123100, -0.977939, -0.938956, -0.963754], [-0.049215, -0.792517, 0.887166, -0.114629, 0.840610, -0.762222, -0.791269, -0.701788], [-0.237229, -0.901536, 0.771741, -0.191393, 0.711668, -0.882971, -0.859519, -0.800428], [0.318404, 0.955002, -0.674340, 0.253964, -0.603813, 0.937116, 0.930408, 0.881870], [-0.322293, 0.172169, -0.884978, -0.261559, -0.913341, 0.155419, 0.079065, -0.003585], [0.261418, 0.930611, -0.725654, 0.230401, -0.658787, 0.909362, 0.913983, 0.855691], [-0.355917, -0.958565, 0.659880, -0.256909, 0.589198, -0.945157, -0.907822, -0.867681]]
pre_activation_mean: [-0.023564, -5.291553, -0.168148, -0.657642, 2.249493, -1.575741, 1.934828, -0.518488]
pre_activation_std: [3.096854, 6.523293, 2.494818, 3.031830, 5.416792, 1.491733, 4.808349, 2.404062]
### 6
mean: [1.810369, -0.021512, 2.107060, 1.406364, -3.169819, 2.569589, -3.369709, -2.872125]
std: [6.336715, 2.688047, 6.406757, 3.174582, 3.791196, 8.222282, 3.200397, 3.035137]
fourier: [[95.148489, 103.211931, 114.527258, 141.868447, 162.933222], [38.608889, 41.364192, 41.937709, 44.023066, 64.560572], [96.168499, 104.299865, 115.034629, 143.466747, 189.635382], [47.163669, 53.713387, 58.382370, 65.532129, 126.572731], [60.947503, 64.241158, 66.773923, 78.268382, 285.283771], [123.331325, 133.825769, 147.771016, 184.068316, 231.263010], [53.053230, 57.498847, 59.472622, 70.017963, 303.273764], [50.804546, 52.214977, 53.481324, 56.033661, 258.491282]]
input_correlations: [[0.880181, 0.143327, -0.668432, -0.684266, 0.926993, 0.162515, 0.932999, -0.746726], [-0.738233, -0.086200, 0.832302, 0.844695, -0.803753, -0.037755, -0.814828, 0.886803], [0.875068, 0.144201, -0.674928, -0.690617, 0.923816, 0.152923, 0.930166, -0.752151], [0.932042, 0.166340, -0.566851, -0.583411, 0.967723, 0.201084, 0.970617, -0.651070], [0.066607, -0.118663, -0.977315, -0.973279, 0.138784, -0.241607, 0.156400, -0.934778], [0.873586, 0.143795, -0.676701, -0.692356, 0.922919, 0.147907, 0.929353, -0.753666], [-0.921604, -0.248268, -0.071816, -0.050539, -0.912617, -0.396934, -0.904698, 0.052562], [-0.980755, -0.221815, 0.285473, 0.305328, -0.998225, -0.301780, -0.996156, 0.394378]]
pre_activation_mean: [1.810369, -0.021512, 2.107060, 1.406364, -3.169819, 2.569589, -3.369709, -2.872125]
pre_activation_std: [6.336715, 2.688047, 6.406757, 3.174582, 3.791196, 8.222282, 3.200397, 3.035137]
### 8
mean: [-3.303798, -8.327381, 5.389651, -1.624331, -4.207416, -7.768635, -5.319980, -0.452927]
std: [2.685289, 11.413898, 7.686568, 1.134552, 3.554849, 10.283742, 6.556721, 1.802851]
fourier: [[44.501608, 46.485398, 49.604659, 58.887661, 297.341787], [189.281033, 192.416787, 204.504860, 210.769446, 749.464307], [123.941706, 135.346153, 136.626145, 143.022891, 485.068602], [17.611233, 18.266152, 20.642122, 25.274867, 146.189797], [60.494739, 61.783950, 65.096444, 77.893469, 378.667447], [171.202997, 176.969694, 183.347164, 189.931355, 699.177169], [109.047830, 112.774723, 116.843441, 121.036938, 478.798214], [27.154425, 29.687479, 32.105363, 40.763429, 41.426273]]
input_correlations: [[-0.899102, -0.066390, -0.893813, -0.901070, -0.525924, -0.894660, -0.765179, -0.692087], [-0.999854, 0.368919, -0.999701, -0.999216, -0.268996, -0.999797, -0.608309, -0.809432], [0.998430, -0.424629, 0.999083, 0.997672, 0.225053, 0.999046, 0.575502, 0.812261], [0.244986, -0.988130, 0.258737, 0.236022, -0.621276, 0.256322, -0.265392, 0.353922], [-0.900715, -0.063893, -0.895063, -0.902944, -0.537444, -0.896091, -0.750558, -0.681011], [-0.999442, 0.348136, -0.999042, -0.999013, -0.281779, -0.999154, -0.620143, -0.807708], [-0.999408, 0.349015, -0.999107, -0.999006, -0.280205, -0.999214, -0.619072, -0.807839], [-0.899665, 0.740950, -0.905887, -0.895443, 0.073932, -0.904829, -0.355720, -0.796181]]
pre_activation_mean: [-3.303798, -8.327381, 5.389651, -1.624331, -4.207416, -7.768635, -5.319980, -0.452927]
pre_activation_std: [2.685289, 11.413898, 7.686568, 1.134552, 3.554849, 10.283742, 6.556721, 1.802851]
### 10
mean: [-1.836541]
std: [2.525520]
fourier: [[39.652895, 45.246440, 47.340297, 47.403673, 165.288728]]
input_correlations: [[-0.509779, -0.458779, -0.995639, 0.319135, -0.457394, -0.631177, -0.766624, 0.464232]]
pre_activation_mean: [-1.836541]
pre_activation_std: [2.525520]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.06325245648622513, "std": 0.07271160930395126, "fourier": [1.0164027145106365, 1.0173546323836105, 1.0864604181625677, 1.45544975321638, 5.692721035023396], "input_correlations": [-0.2858644772212129, -0.6937641451368397, -0.7660810268686885, -0.5004818733764473, -0.2848169047618514, 0.0, 0.0, 0.0], "pre_activation_mean": -5.711777687072754, "pre_activation_std": 2.9154717922210693}, "1": {"mean": -0.04743489623069763, "std": 0.08227147907018661, "fourier": [1.306730181178795, 1.388300828473221, 1.7421379893949467, 2.2073185738036356, 4.2691407753154635], "input_correlations": [0.9682997684989003, 0.23903659408736305, 0.11350987515860435, -0.19139828424531402, 0.08441747594316726, 0.0, 0.0, 0.0], "pre_activation_mean": 0.008104637265205383, "pre_activation_std": 2.1644980907440186}, "2": {"mean": 5.4591827392578125, "std": 7.629411697387695, "fourier": [125.81347894403402, 130.62090610616363, 136.3363614049022, 141.96087962726492, 491.32650522358017], "input_correlations": [-0.8248830540150065, -0.6080425063669261, -0.48543673238899676, -0.4516070454116918, -0.19295138162213435, 0.0, 0.0, 0.0], "pre_activation_mean": -4.423030376434326, "pre_activation_std": 3.1099534034729004}, "3": {"mean": -0.11326413601636887, "std": 0.05753020569682121, "fourier": [0.8181725863730938, 1.014993642727441, 1.0755583720341244, 1.2383679320585534, 10.193772005857369], "input_correlations": [-0.7375173413740729, -0.26467396549666455, -0.027658014160609732, 0.30948247459050454, 0.4958638858313967, 0.0, 0.0, 0.0], "pre_activation_mean": 1.1398041248321533, "pre_activation_std": 2.723539352416992}, "4": {"mean": -0.05237419903278351, "std": 0.06773383170366287, "fourier": [0.9440148693634604, 0.9873410094463456, 1.0375833115284145, 1.3485738570684476, 4.713677891568608], "input_correlations": [0.37435357858621193, -0.5365960952215155, 0.17900438844465288, -0.7908196191103528, -0.1571268072065169, 0.0, 0.0, 0.0], "pre_activation_mean": -1.5656200647354126, "pre_activation_std": 2.1844406127929688}, "5": {"mean": -0.05755751579999924, "std": 0.06637756526470184, "fourier": [1.1579724799243518, 1.1804591511213944, 1.2484689407971994, 1.6145282551371447, 5.180176534769373], "input_correlations": [0.9068105379276857, 0.5624220975277904, 0.45670762820599187, 0.07903498629356204, -0.08936989990887986, 0.0, 0.0, 0.0], "pre_activation_mean": 3.0211730003356934, "pre_activation_std": 3.1535391807556152}, "6": {"mean": -0.07991819083690643, "std": 0.07402384281158447, "fourier": [1.101997706743984, 1.2633338459607693, 1.4252106005850018, 1.4478733219593116, 7.1926367909496065], "input_correlations": [-0.5602795286519803, -0.5822726725709485, -0.7727356242336815, -0.30912763072253935, -0.5602283241311116, 0.0, 0.0, 0.0], "pre_activation_mean": -6.4105095863342285, "pre_activation_std": 4.172296524047852}, "7": {"mean": 0.3965989947319031, "std": 0.840017557144165, "fourier": [12.75546533352898, 13.387872667396623, 15.210297015720865, 19.532815063008595, 35.69390827357802], "input_correlations": [-0.4585185336625608, -0.6911333039570412, -0.5011366015392832, -0.6924892987203225, -0.4552616278063592, 0.0, 0.0, 0.0], "pre_activation_mean": -4.8469157218933105, "pre_activation_std": 2.681086540222168}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -2.168948173522949, "std": 1.0566962957382202, "fourier": [18.95293913612973, 18.98048540710652, 19.00656908430092, 23.816825272159335, 195.2053507566452], "input_correlations": [-0.24368421680238847, -0.8390549074960428, -0.35749502974651226, -0.002875454290089554, -0.6795247798054933, -0.6398500096776701, -0.34615738094639936, -0.3161268888377235], "pre_activation_mean": -2.168948173522949, "pre_activation_std": 1.0566962957382202}, "1": 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-0.136731, 0.545394, -0.284735, -0.481955], [0.046926, -0.657354, -0.126546, -0.467233, 0.018498, 0.234842, 0.269275, 0.781123], [-0.261817, -0.966231, -0.450597, 0.580389, -0.406417, -0.317597, 0.218395, 0.208991], [-0.782072, -0.212638, -0.443397, 0.034282, -0.293807, -0.720887, -0.585081, -0.475027], [-0.244713, -0.154958, -0.578327, 0.124695, -0.177794, -0.474472, 0.121434, -0.132092], [-0.018096, 0.461575, -0.157792, 0.239397, -0.007331, -0.172966, -0.17164, -0.353527]], "network.8.bias": [-0.638659, -0.150149, 0.191006, -0.827546, -0.514604, -0.398455, -0.481806, 0.018174], "network.10.weight": [[0.292344, -0.147332, -0.319354, 0.339215, 0.519592, -0.382155, -0.201649, 0.223999]], "network.10.bias": [-0.14294]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.689319372177124, "train_acc": 0.56, "val_loss": 0.6855395436286926, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6838663518428802, "train_acc": 0.56, "val_loss": 0.6710760593414307, "val_acc": 0.6}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.639902263879776, "train_acc": 0.575, "val_loss": 0.6047928333282471, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.7835045754909515, "train_acc": 0.535, "val_loss": 0.6383809447288513, "val_acc": 0.7}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6252849102020264, "train_acc": 0.75, "val_loss": 0.6518638134002686, "val_acc": 0.62}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.658586859703064, "train_acc": 0.525, "val_loss": 0.6341195106506348, "val_acc": 0.68}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.6226163506507874, "train_acc": 0.68, "val_loss": 0.5769612789154053, "val_acc": 0.68}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.5465193390846252, "train_acc": 0.745, "val_loss": 0.5147051811218262, "val_acc": 0.72}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.46931280195713043, "train_acc": 0.765, "val_loss": 0.5229678153991699, "val_acc": 0.72}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.49302780628204346, "train_acc": 0.77, "val_loss": 0.5519028306007385, "val_acc": 0.7}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.4583025276660919, "train_acc": 0.795, "val_loss": 0.521469235420227, "val_acc": 0.7}], "summary": {"total_epochs": 11, "degraded_epochs": 3, "improved_epochs": 8, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.6855395436286926, "final_val_loss": 0.6047928333282471, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.6383809447288513, "final_val_loss": 0.521469235420227, "initial_val_acc": 0.7, "final_val_acc": 0.7, "best_val_acc": 0.72, "best_epoch": 7}, "improvement": 0.15999999999999992, "first_improvement_epoch": 2}} |
4 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.64, "improved_accuracy": 0.88, "improvement": 0.24, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9859, "learning_rate": 0.015384002471586396, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.000000, 0.000000, 3.909110, 0.068230, 2.490095]
std: [0.000000, 0.000000, 3.772929, 0.121492, 2.280655]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [64.118049, 66.256184, 72.378276, 77.272829, 351.819895], [1.718684, 2.032457, 2.036881, 2.442863, 6.140725], [38.469440, 39.022177, 42.381879, 46.350399, 224.108577]]
input_correlations: [[0.777776, 0.481162, 0.601564, 0.113467, -0.233988, 0.000000, 0.000000, 0.000000], [-0.254660, -0.386779, -0.363800, -0.787177, -0.659713, 0.000000, 0.000000, 0.000000], [0.878883, 0.527305, 0.200428, 0.246005, -0.146585, 0.000000, 0.000000, 0.000000], [0.744023, -0.025062, 0.355603, -0.632490, 0.308285, 0.000000, 0.000000, 0.000000], [0.338697, -0.000019, 0.737789, -0.649289, -0.057288, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.225750, -1.875811, 1.840462, 0.133152, 0.080385]
pre_activation_std: [1.490227, 1.417928, 1.703278, 1.652030, 1.665027]
### 2
mean: [1.862910, -0.382640, 1.914776, 1.391906, 0.598354]
std: [1.741192, 0.779950, 1.722413, 1.520277, 0.927768]
fourier: [[28.910895, 28.929604, 31.795965, 34.963147, 167.661900], [11.314239, 11.976165, 12.289642, 14.860378, 34.437598], [27.618059, 28.767423, 30.726744, 35.896253, 172.329865], [25.407178, 26.437090, 28.841991, 30.516361, 125.271527], [15.404548, 16.467909, 17.113213, 19.332515, 53.851828]]
input_correlations: [[0.958331, -0.314754, 0.947716, 0.740228, 0.366039, 0.000000, 0.000000, 0.000000], [-0.490793, 0.092923, -0.784980, -0.106049, 0.552212, 0.000000, 0.000000, 0.000000], [0.980058, -0.334368, 0.918804, 0.701455, 0.443025, 0.000000, 0.000000, 0.000000], [0.862206, -0.329651, 0.614867, 0.784054, 0.808823, 0.000000, 0.000000, 0.000000], [0.839200, -0.305723, 0.660207, 0.899364, 0.728278, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.862910, -0.382640, 1.914776, 1.391906, 0.598354]
pre_activation_std: [1.741192, 0.779950, 1.722413, 1.520277, 0.927768]
### 4
mean: [-0.492834, -0.616381, 2.720308, 2.002667, 2.703507]
std: [0.154883, 0.272877, 2.537050, 1.906105, 2.594697]
fourier: [[2.325893, 2.676690, 2.748414, 2.834278, 44.355092], [4.263521, 4.490749, 4.549010, 5.848121, 55.474252], [42.738749, 44.760550, 49.851064, 51.764161, 244.827688], [32.134723, 32.445411, 35.223543, 38.979491, 180.240033], [43.884942, 45.210133, 49.532517, 52.803120, 243.315644]]
input_correlations: [[-0.909660, 0.273085, -0.910538, -0.675938, -0.660275, 0.000000, 0.000000, 0.000000], [-0.815547, -0.379762, -0.882044, -0.907514, -0.791819, 0.000000, 0.000000, 0.000000], [0.949079, 0.260336, 0.968058, 0.962742, 0.953664, 0.000000, 0.000000, 0.000000], [0.996820, 0.041839, 0.996398, 0.869925, 0.883339, 0.000000, 0.000000, 0.000000], [0.985681, 0.109075, 0.990181, 0.912162, 0.923530, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.492834, -0.616381, 2.720308, 2.002667, 2.703507]
pre_activation_std: [0.154883, 0.272877, 2.537050, 1.906105, 2.594697]
### 6
mean: [-2.468439, -0.342933, 3.904991, -0.678355, 2.490095]
std: [2.302745, 0.246841, 3.777236, 0.966617, 2.280655]
fourier: [[39.042283, 40.216960, 44.011451, 47.199918, 222.159532], [4.044814, 4.304464, 4.638200, 4.926559, 30.863944], [64.010740, 66.135351, 72.557209, 77.325108, 351.449177], [16.350282, 16.454527, 17.742970, 19.858673, 61.051992], [38.469440, 39.022177, 42.381879, 46.350399, 224.108577]]
input_correlations: [[0.000000, 0.000000, -0.990918, -0.993780, -0.999516, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.884556, -0.746245, -0.800942, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.993040, 0.991632, 0.999128, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.968657, -0.999817, -0.993509, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.971073, 0.999575, 0.996162, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.468439, -0.342933, 3.904991, -0.678355, 2.490095]
pre_activation_std: [2.302745, 0.246841, 3.777236, 0.966617, 2.280655]
### 8
mean: [-2.615253]
std: [2.638585]
fourier: [[44.757831, 45.916732, 50.408427, 54.161602, 235.372759]]
input_correlations: [[0.000000, 0.000000, -0.999819, 0.555875, -0.994158, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.615253]
pre_activation_std: [2.638585]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
0.180827,
0.054785,
-0.261857,
-0.272733,
0.337052
],
[
0.761912,
0.554937,
0.101641,
0.655087,
0.128644
],
[
0.487381,
0.22442,
0.598131,
-0.212234,
0.403821
],
[
0.562781,
-0.080205,
0.538965,
0.16456,
0.60642
]
],
"network.4.bias": [
-0.351487,
-0.300211,
0.014171,
-0.057345,
-0.001261
],
"network.6.weight": [
[
0.390837,
-0.374882,
-0.283566,
-0.381474,
-0.334873
],
[
-0.390806,
-0.397559,
-0.322201,
0.124676,
0.143966
],
[
0.405974,
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],
[
-0.213986,
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],
[
0.219681,
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]
],
"network.6.bias": [
-0.026605,
-0.105723,
-0.096135,
0.350272,
0.126477
],
"network.8.weight": [
[
-0.366589,
0.146977,
-0.606761,
0.280552,
-0.145892
]
],
"network.8.bias": [
0.100786
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 3.909110, 0.068230, 2.490095]
std: [0.000000, 0.000000, 3.772929, 0.121492, 2.280655]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [64.118049, 66.256184, 72.378276, 77.272829, 351.819895], [1.718684, 2.032457, 2.036881, 2.442863, 6.140725], [38.469440, 39.022177, 42.381879, 46.350399, 224.108577]]
input_correlations: [[0.777776, 0.481162, 0.601564, 0.113467, -0.233988, 0.000000, 0.000000, 0.000000], [-0.254660, -0.386779, -0.363800, -0.787177, -0.659713, 0.000000, 0.000000, 0.000000], [0.878883, 0.527305, 0.200428, 0.246005, -0.146585, 0.000000, 0.000000, 0.000000], [0.744023, -0.025062, 0.355603, -0.632490, 0.308285, 0.000000, 0.000000, 0.000000], [0.338697, -0.000019, 0.737789, -0.649289, -0.057288, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.225750, -1.875811, 1.840462, 0.133152, 0.080385]
pre_activation_std: [1.490227, 1.417928, 1.703278, 1.652030, 1.665027]
### 2
mean: [1.862910, -0.382640, 1.914776, 1.391906, 0.598354]
std: [1.741192, 0.779950, 1.722413, 1.520277, 0.927768]
fourier: [[28.910895, 28.929604, 31.795965, 34.963147, 167.661900], [11.314239, 11.976165, 12.289642, 14.860378, 34.437598], [27.618059, 28.767423, 30.726744, 35.896253, 172.329865], [25.407178, 26.437090, 28.841991, 30.516361, 125.271527], [15.404548, 16.467909, 17.113213, 19.332515, 53.851828]]
input_correlations: [[0.958331, -0.314754, 0.947716, 0.740228, 0.366039, 0.000000, 0.000000, 0.000000], [-0.490793, 0.092923, -0.784980, -0.106049, 0.552212, 0.000000, 0.000000, 0.000000], [0.980058, -0.334368, 0.918804, 0.701455, 0.443025, 0.000000, 0.000000, 0.000000], [0.862206, -0.329651, 0.614867, 0.784054, 0.808823, 0.000000, 0.000000, 0.000000], [0.839200, -0.305723, 0.660207, 0.899364, 0.728278, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.862910, -0.382640, 1.914776, 1.391906, 0.598354]
pre_activation_std: [1.741192, 0.779950, 1.722413, 1.520277, 0.927768]
### 4
mean: [-0.492834, -0.616381, 2.720308, 2.002667, 2.703507]
std: [0.154883, 0.272877, 2.537050, 1.906105, 2.594697]
fourier: [[2.325893, 2.676690, 2.748414, 2.834278, 44.355092], [4.263521, 4.490749, 4.549010, 5.848121, 55.474252], [42.738749, 44.760550, 49.851064, 51.764161, 244.827688], [32.134723, 32.445411, 35.223543, 38.979491, 180.240033], [43.884942, 45.210133, 49.532517, 52.803120, 243.315644]]
input_correlations: [[-0.909660, 0.273085, -0.910538, -0.675938, -0.660275, 0.000000, 0.000000, 0.000000], [-0.815547, -0.379762, -0.882044, -0.907514, -0.791819, 0.000000, 0.000000, 0.000000], [0.949079, 0.260336, 0.968058, 0.962742, 0.953664, 0.000000, 0.000000, 0.000000], [0.996820, 0.041839, 0.996398, 0.869925, 0.883339, 0.000000, 0.000000, 0.000000], [0.985681, 0.109075, 0.990181, 0.912162, 0.923530, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.492834, -0.616381, 2.720308, 2.002667, 2.703507]
pre_activation_std: [0.154883, 0.272877, 2.537050, 1.906105, 2.594697]
### 6
mean: [-2.468439, -0.342933, 3.904991, -0.678355, 2.490095]
std: [2.302745, 0.246841, 3.777236, 0.966617, 2.280655]
fourier: [[39.042283, 40.216960, 44.011451, 47.199918, 222.159532], [4.044814, 4.304464, 4.638200, 4.926559, 30.863944], [64.010740, 66.135351, 72.557209, 77.325108, 351.449177], [16.350282, 16.454527, 17.742970, 19.858673, 61.051992], [38.469440, 39.022177, 42.381879, 46.350399, 224.108577]]
input_correlations: [[0.000000, 0.000000, -0.990918, -0.993780, -0.999516, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.884556, -0.746245, -0.800942, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.993040, 0.991632, 0.999128, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.968657, -0.999817, -0.993509, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.971073, 0.999575, 0.996162, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.468439, -0.342933, 3.904991, -0.678355, 2.490095]
pre_activation_std: [2.302745, 0.246841, 3.777236, 0.966617, 2.280655]
### 8
mean: [-2.615253]
std: [2.638585]
fourier: [[44.757831, 45.916732, 50.408427, 54.161602, 235.372759]]
input_correlations: [[0.000000, 0.000000, -0.999819, 0.555875, -0.994158, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.615253]
pre_activation_std: [2.638585]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.7777758061129579, 0.4811618685130555, 0.601564340396978, 0.113466684059439, -0.23398815235591353, 0.0, 0.0, 0.0], "pre_activation_mean": 1.22575044631958, "pre_activation_std": 1.4902271032333374}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.2546604137384096, -0.38677932934508213, -0.3638002823555687, -0.7871770691397355, -0.6597132281800334, 0.0, 0.0, 0.0], "pre_activation_mean": -1.8758111000061035, "pre_activation_std": 1.4179282188415527}, "2": {"mean": 3.9091100692749023, "std": 3.7729294300079346, "fourier": [64.11804862415205, 66.25618391836285, 72.37827604749526, 77.27282885576051, 351.81989485025406], "input_correlations": [0.8788833820173202, 0.5273047732622711, 0.2004281566489361, 0.24600453599533678, -0.1465849570072898, 0.0, 0.0, 0.0], "pre_activation_mean": 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"pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 1.8629099130630493, "std": 1.7411917448043823, "fourier": [28.910894961734517, 28.929604469408243, 31.795965031382735, 34.963146643861066, 167.6618996821344], "input_correlations": [0.9583307806475637, -0.31475435254140177, 0.9477155963548769, 0.74022798131581, 0.3660386625463616, 0.0, 0.0, 0.0], "pre_activation_mean": 1.8629099130630493, "pre_activation_std": 1.7411917448043823}, "1": {"mean": -0.38263994455337524, "std": 0.7799502611160278, "fourier": [11.314238758197137, 11.976165315292898, 12.289642032127986, 14.860378311135879, 34.43759776093066], "input_correlations": [-0.4907934028637442, 0.09292299434913617, -0.7849795871588647, -0.10604885465777783, 0.5522123907619579, 0.0, 0.0, 0.0], "pre_activation_mean": -0.38263994455337524, "pre_activation_std": 0.7799502611160278}, "2": {"mean": 1.91477632522583, "std": 1.7224127054214478, "fourier": [27.618058602977044, 28.76742270745435, 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[[-0.366589, 0.146977, -0.606761, 0.280552, -0.145892]], "network.8.bias": [0.100786]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6981912553310394, "train_acc": 0.455, "val_loss": 0.6990344524383545, "val_acc": 0.36}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6930713355541229, "train_acc": 0.495, "val_loss": 0.6893063187599182, "val_acc": 0.64}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6886858642101288, "train_acc": 0.545, "val_loss": 0.679652988910675, "val_acc": 0.64}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6824103891849518, "train_acc": 0.545, "val_loss": 0.6670619249343872, "val_acc": 0.64}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6760824918746948, "train_acc": 0.545, "val_loss": 0.6492671370506287, "val_acc": 0.64}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6765421330928802, "train_acc": 0.465, "val_loss": 0.6330080628395081, "val_acc": 0.64}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.6552756130695343, "train_acc": 0.465, "val_loss": 0.6015357971191406, "val_acc": 0.64}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.6242035031318665, "train_acc": 0.465, "val_loss": 0.5551472306251526, "val_acc": 0.64}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5820193290710449, "train_acc": 0.47, "val_loss": 0.5023326277732849, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.5375237464904785, "train_acc": 0.81, "val_loss": 0.45185601711273193, "val_acc": 0.82}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.49756084382534027, "train_acc": 0.84, "val_loss": 0.41070517897605896, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.475924551486969, "train_acc": 0.865, "val_loss": 0.3794182538986206, "val_acc": 0.88}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.4372108429670334, "train_acc": 0.89, "val_loss": 0.35529449582099915, "val_acc": 0.88}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.40429624915122986, "train_acc": 0.915, "val_loss": 0.33883070945739746, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.3920377045869827, "train_acc": 0.915, "val_loss": 0.32772576808929443, "val_acc": 0.88}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6990344524383545, "final_val_loss": 0.6492671370506287, "initial_val_acc": 0.36, "final_val_acc": 0.64, "best_val_acc": 0.64}, "improved_stage": {"initial_val_loss": 0.6330080628395081, "final_val_loss": 0.32772576808929443, "initial_val_acc": 0.64, "final_val_acc": 0.88, "best_val_acc": 0.88, "best_epoch": 11}, "improvement": 0.24, "first_improvement_epoch": 4}} |
5 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.56, "improved_accuracy": 0.94, "improvement": 0.3799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4854, "learning_rate": 0.09414589333639692, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.6.weight": [
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"network.8.weight": [
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],
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]
}
## Activation Signature
### 0
mean: [5.813388, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.693521, 0.000000]
std: [5.687976, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.518507, 0.000000]
fourier: [[86.114977, 88.620517, 91.525870, 107.943244, 523.204909], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [113.584275, 116.752478, 120.797529, 143.301025, 692.416928], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.327591, -0.960451, -0.147269, -0.420062, -0.241550, 0.000000, 0.000000, 0.000000], [-0.475556, -0.274039, 0.050714, 0.567705, 0.604313, 0.000000, 0.000000, 0.000000], [-0.317982, -0.134080, 0.007055, 0.797613, -0.230006, 0.000000, 0.000000, 0.000000], [0.928651, 0.338463, 0.190131, 0.152274, -0.090656, 0.000000, 0.000000, 0.000000], [-0.750945, -0.360104, -0.565621, 0.509215, -0.173429, 0.000000, 0.000000, 0.000000], [-0.241932, -0.717294, -0.310595, -0.769156, -0.478656, 0.000000, 0.000000, 0.000000], [-0.739869, -0.240220, -0.703317, 0.150474, -0.612095, 0.000000, 0.000000, 0.000000], [-0.436707, -0.036309, 0.023911, 0.442691, 0.756231, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.021575, 1.674903, 1.058969, 1.142064, -1.119240, -2.617912, -1.659665, 1.273621]
pre_activation_std: [1.246689, 2.255405, 1.464877, 1.895494, 1.710696, 1.581443, 1.817697, 1.862671]
### 2
mean: [-1.446432, 0.616550, 0.221872, -2.457122, 2.049582, 2.411618, 2.175854, 1.586532]
std: [0.809939, 0.840926, 1.313830, 1.244015, 2.565268, 2.574064, 2.902711, 1.861488]
fourier: [[13.367139, 13.902505, 13.999023, 16.835479, 130.178885], [13.142870, 14.422282, 14.943104, 15.911072, 55.489469], [19.909737, 19.949772, 19.955001, 19.968497, 25.638068], [20.840884, 21.125284, 22.870105, 24.717384, 221.140983], [37.719156, 38.841655, 39.034783, 51.205080, 184.462372], [38.383325, 40.816277, 41.205116, 48.009882, 217.045595], [43.089901, 44.580067, 44.912095, 57.927039, 195.826907], [28.998064, 29.609677, 29.617297, 33.991879, 142.787839]]
input_correlations: [[0.000000, -0.512202, -0.607493, -0.586114, -0.584220, 0.000000, -0.278685, -0.369778], [0.000000, -0.091878, 0.710410, 0.544924, 0.435847, 0.000000, 0.290467, -0.399479], [0.000000, 0.801247, 0.773568, -0.596637, 0.667307, 0.000000, 0.255020, 0.595157], [0.000000, -0.612041, -0.491422, -0.548624, -0.517197, 0.000000, -0.163379, -0.519076], [0.000000, 0.918406, 0.666256, -0.556662, 0.647039, 0.000000, 0.206714, 0.768368], [0.000000, 0.937282, 0.731293, -0.399485, 0.727176, 0.000000, 0.261712, 0.774044], [0.000000, 0.915538, 0.653948, -0.568630, 0.660575, 0.000000, 0.220907, 0.767030], [0.000000, 0.940853, 0.756503, -0.360902, 0.719470, 0.000000, 0.221378, 0.753046]]
pre_activation_mean: [-1.446432, 0.616550, 0.221872, -2.457122, 2.049582, 2.411618, 2.175854, 1.586532]
pre_activation_std: [0.809939, 0.840926, 1.313830, 1.244015, 2.565268, 2.574064, 2.902711, 1.861488]
### 4
mean: [6.181356, 6.785661, -1.722989, 4.871498, -2.710276, -1.121170, -0.516215, -1.402471]
std: [5.977047, 6.235813, 1.914263, 4.564242, 1.860146, 1.126886, 0.156779, 1.028444]
fourier: [[90.663232, 92.777626, 96.173142, 113.075260, 556.322097], [94.500865, 98.027941, 99.981189, 117.063753, 610.709487], [29.163306, 30.564558, 30.731827, 35.708591, 155.069042], [68.236594, 70.388013, 72.493396, 87.356575, 438.434842], [27.892818, 28.890651, 30.741508, 33.881713, 243.924895], [16.578227, 16.612945, 17.223232, 22.820435, 100.905277], [2.219488, 2.439932, 2.646682, 3.058511, 46.459332], [15.073601, 15.280577, 15.826368, 20.146927, 126.222429]]
input_correlations: [[0.000000, 0.230931, 0.954955, 0.000000, 0.995935, 0.997563, 0.995303, 0.995404], [0.000000, 0.252473, 0.958083, 0.000000, 0.994118, 0.997609, 0.993458, 0.996160], [0.000000, -0.278698, -0.963881, 0.000000, -0.990674, -0.996199, -0.990702, -0.997040], [0.000000, 0.234337, 0.954135, 0.000000, 0.996495, 0.996250, 0.996004, 0.993398], [0.000000, -0.351246, -0.969221, 0.000000, -0.979798, -0.989326, -0.979432, -0.992164], [0.000000, -0.092918, -0.938237, 0.000000, -0.990958, -0.968911, -0.991740, -0.965399], [0.000000, -0.385019, -0.946077, 0.000000, -0.921715, -0.895249, -0.920927, -0.907019], [0.000000, -0.183909, -0.956952, 0.000000, -0.998284, -0.987527, -0.997594, -0.984332]]
pre_activation_mean: [6.181356, 6.785661, -1.722989, 4.871498, -2.710276, -1.121170, -0.516215, -1.402471]
pre_activation_std: [5.977047, 6.235813, 1.914263, 4.564242, 1.860146, 1.126886, 0.156779, 1.028444]
### 6
mean: [5.805642, -2.183590, -1.223589, -2.125370, -6.373301, -2.331736, 7.683883, -6.408481]
std: [5.696019, 1.787395, 1.063885, 1.622092, 5.945364, 1.992884, 7.528506, 5.878805]
fourier: [[86.204882, 88.830575, 91.400548, 107.524347, 522.507775], [27.278334, 28.342619, 28.729241, 33.339393, 196.523088], [16.304748, 16.804845, 17.111193, 19.931725, 110.123008], [24.497070, 25.470308, 25.951982, 30.657186, 191.283252], [89.686357, 92.340740, 95.107391, 113.576056, 573.597050], [30.245286, 31.118038, 32.058816, 37.635458, 209.856216], [113.709511, 116.977797, 120.661289, 142.827135, 691.549501], [88.830299, 91.854726, 94.123610, 111.461232, 576.763350]]
input_correlations: [[0.999922, 0.999926, -0.393397, 0.999752, 0.000000, -0.186485, 0.000000, 0.000000], [-0.999484, -0.999852, 0.392990, -0.998947, 0.000000, 0.171101, 0.000000, 0.000000], [-0.999396, -0.999419, 0.401485, -0.998559, 0.000000, 0.169442, 0.000000, 0.000000], [-0.999551, -0.999937, 0.387204, -0.999550, 0.000000, 0.175907, 0.000000, 0.000000], [-0.999874, -0.999860, 0.391343, -0.999854, 0.000000, 0.181254, 0.000000, 0.000000], [-0.999931, -0.999926, 0.389238, -0.999628, 0.000000, 0.185045, 0.000000, 0.000000], [0.999930, 0.999865, -0.393455, 0.999844, 0.000000, -0.187170, 0.000000, 0.000000], [-0.999805, -0.999961, 0.390623, -0.999738, 0.000000, 0.179805, 0.000000, 0.000000]]
pre_activation_mean: [5.805642, -2.183590, -1.223589, -2.125370, -6.373301, -2.331736, 7.683883, -6.408481]
pre_activation_std: [5.696019, 1.787395, 1.063885, 1.622092, 5.945364, 1.992884, 7.528506, 5.878805]
### 8
mean: [-4.735796]
std: [4.836879]
fourier: [[73.133718, 75.207973, 77.758932, 92.034790, 426.221659]]
input_correlations: [[-0.999995, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999998, 0.000000]]
pre_activation_mean: [-4.735796]
pre_activation_std: [4.836879]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.4.weight": [
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[
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"network.6.weight": [
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"network.8.weight": [
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],
"network.8.bias": [
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}
## Activation Signature
### 0
mean: [5.813388, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.693521, 0.000000]
std: [5.687976, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.518507, 0.000000]
fourier: [[86.114977, 88.620517, 91.525870, 107.943244, 523.204909], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [113.584275, 116.752478, 120.797529, 143.301025, 692.416928], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.327591, -0.960451, -0.147269, -0.420062, -0.241550, 0.000000, 0.000000, 0.000000], [-0.475556, -0.274039, 0.050714, 0.567705, 0.604313, 0.000000, 0.000000, 0.000000], [-0.317982, -0.134080, 0.007055, 0.797613, -0.230006, 0.000000, 0.000000, 0.000000], [0.928651, 0.338463, 0.190131, 0.152274, -0.090656, 0.000000, 0.000000, 0.000000], [-0.750945, -0.360104, -0.565621, 0.509215, -0.173429, 0.000000, 0.000000, 0.000000], [-0.241932, -0.717294, -0.310595, -0.769156, -0.478656, 0.000000, 0.000000, 0.000000], [-0.739869, -0.240220, -0.703317, 0.150474, -0.612095, 0.000000, 0.000000, 0.000000], [-0.436707, -0.036309, 0.023911, 0.442691, 0.756231, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.021575, 1.674903, 1.058969, 1.142064, -1.119240, -2.617912, -1.659665, 1.273621]
pre_activation_std: [1.246689, 2.255405, 1.464877, 1.895494, 1.710696, 1.581443, 1.817697, 1.862671]
### 2
mean: [-1.446432, 0.616550, 0.221872, -2.457122, 2.049582, 2.411618, 2.175854, 1.586532]
std: [0.809939, 0.840926, 1.313830, 1.244015, 2.565268, 2.574064, 2.902711, 1.861488]
fourier: [[13.367139, 13.902505, 13.999023, 16.835479, 130.178885], [13.142870, 14.422282, 14.943104, 15.911072, 55.489469], [19.909737, 19.949772, 19.955001, 19.968497, 25.638068], [20.840884, 21.125284, 22.870105, 24.717384, 221.140983], [37.719156, 38.841655, 39.034783, 51.205080, 184.462372], [38.383325, 40.816277, 41.205116, 48.009882, 217.045595], [43.089901, 44.580067, 44.912095, 57.927039, 195.826907], [28.998064, 29.609677, 29.617297, 33.991879, 142.787839]]
input_correlations: [[0.000000, -0.512202, -0.607493, -0.586114, -0.584220, 0.000000, -0.278685, -0.369778], [0.000000, -0.091878, 0.710410, 0.544924, 0.435847, 0.000000, 0.290467, -0.399479], [0.000000, 0.801247, 0.773568, -0.596637, 0.667307, 0.000000, 0.255020, 0.595157], [0.000000, -0.612041, -0.491422, -0.548624, -0.517197, 0.000000, -0.163379, -0.519076], [0.000000, 0.918406, 0.666256, -0.556662, 0.647039, 0.000000, 0.206714, 0.768368], [0.000000, 0.937282, 0.731293, -0.399485, 0.727176, 0.000000, 0.261712, 0.774044], [0.000000, 0.915538, 0.653948, -0.568630, 0.660575, 0.000000, 0.220907, 0.767030], [0.000000, 0.940853, 0.756503, -0.360902, 0.719470, 0.000000, 0.221378, 0.753046]]
pre_activation_mean: [-1.446432, 0.616550, 0.221872, -2.457122, 2.049582, 2.411618, 2.175854, 1.586532]
pre_activation_std: [0.809939, 0.840926, 1.313830, 1.244015, 2.565268, 2.574064, 2.902711, 1.861488]
### 4
mean: [6.181356, 6.785661, -1.722989, 4.871498, -2.710276, -1.121170, -0.516215, -1.402471]
std: [5.977047, 6.235813, 1.914263, 4.564242, 1.860146, 1.126886, 0.156779, 1.028444]
fourier: [[90.663232, 92.777626, 96.173142, 113.075260, 556.322097], [94.500865, 98.027941, 99.981189, 117.063753, 610.709487], [29.163306, 30.564558, 30.731827, 35.708591, 155.069042], [68.236594, 70.388013, 72.493396, 87.356575, 438.434842], [27.892818, 28.890651, 30.741508, 33.881713, 243.924895], [16.578227, 16.612945, 17.223232, 22.820435, 100.905277], [2.219488, 2.439932, 2.646682, 3.058511, 46.459332], [15.073601, 15.280577, 15.826368, 20.146927, 126.222429]]
input_correlations: [[0.000000, 0.230931, 0.954955, 0.000000, 0.995935, 0.997563, 0.995303, 0.995404], [0.000000, 0.252473, 0.958083, 0.000000, 0.994118, 0.997609, 0.993458, 0.996160], [0.000000, -0.278698, -0.963881, 0.000000, -0.990674, -0.996199, -0.990702, -0.997040], [0.000000, 0.234337, 0.954135, 0.000000, 0.996495, 0.996250, 0.996004, 0.993398], [0.000000, -0.351246, -0.969221, 0.000000, -0.979798, -0.989326, -0.979432, -0.992164], [0.000000, -0.092918, -0.938237, 0.000000, -0.990958, -0.968911, -0.991740, -0.965399], [0.000000, -0.385019, -0.946077, 0.000000, -0.921715, -0.895249, -0.920927, -0.907019], [0.000000, -0.183909, -0.956952, 0.000000, -0.998284, -0.987527, -0.997594, -0.984332]]
pre_activation_mean: [6.181356, 6.785661, -1.722989, 4.871498, -2.710276, -1.121170, -0.516215, -1.402471]
pre_activation_std: [5.977047, 6.235813, 1.914263, 4.564242, 1.860146, 1.126886, 0.156779, 1.028444]
### 6
mean: [5.805642, -2.183590, -1.223589, -2.125370, -6.373301, -2.331736, 7.683883, -6.408481]
std: [5.696019, 1.787395, 1.063885, 1.622092, 5.945364, 1.992884, 7.528506, 5.878805]
fourier: [[86.204882, 88.830575, 91.400548, 107.524347, 522.507775], [27.278334, 28.342619, 28.729241, 33.339393, 196.523088], [16.304748, 16.804845, 17.111193, 19.931725, 110.123008], [24.497070, 25.470308, 25.951982, 30.657186, 191.283252], [89.686357, 92.340740, 95.107391, 113.576056, 573.597050], [30.245286, 31.118038, 32.058816, 37.635458, 209.856216], [113.709511, 116.977797, 120.661289, 142.827135, 691.549501], [88.830299, 91.854726, 94.123610, 111.461232, 576.763350]]
input_correlations: [[0.999922, 0.999926, -0.393397, 0.999752, 0.000000, -0.186485, 0.000000, 0.000000], [-0.999484, -0.999852, 0.392990, -0.998947, 0.000000, 0.171101, 0.000000, 0.000000], [-0.999396, -0.999419, 0.401485, -0.998559, 0.000000, 0.169442, 0.000000, 0.000000], [-0.999551, -0.999937, 0.387204, -0.999550, 0.000000, 0.175907, 0.000000, 0.000000], [-0.999874, -0.999860, 0.391343, -0.999854, 0.000000, 0.181254, 0.000000, 0.000000], [-0.999931, -0.999926, 0.389238, -0.999628, 0.000000, 0.185045, 0.000000, 0.000000], [0.999930, 0.999865, -0.393455, 0.999844, 0.000000, -0.187170, 0.000000, 0.000000], [-0.999805, -0.999961, 0.390623, -0.999738, 0.000000, 0.179805, 0.000000, 0.000000]]
pre_activation_mean: [5.805642, -2.183590, -1.223589, -2.125370, -6.373301, -2.331736, 7.683883, -6.408481]
pre_activation_std: [5.696019, 1.787395, 1.063885, 1.622092, 5.945364, 1.992884, 7.528506, 5.878805]
### 8
mean: [-4.735796]
std: [4.836879]
fourier: [[73.133718, 75.207973, 77.758932, 92.034790, 426.221659]]
input_correlations: [[-0.999995, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999998, 0.000000]]
pre_activation_mean: [-4.735796]
pre_activation_std: [4.836879]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 5.813387870788574, "std": 5.687976360321045, "fourier": [86.1149770000087, 88.62051715858165, 91.525870011328, 107.94324355429487, 523.2049094438553], "input_correlations": [-0.32759087914729396, -0.9604506642701345, -0.14726928250761978, -0.4200621386712415, -0.24154986815633106, 0.0, 0.0, 0.0], "pre_activation_mean": -2.0215752124786377, "pre_activation_std": 1.2466892004013062}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.475555576958179, -0.2740393245297363, 0.050714063833294715, 0.567704526917779, 0.604312583320595, 0.0, 0.0, 0.0], "pre_activation_mean": 1.6749026775360107, "pre_activation_std": 2.2554051876068115}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.31798215044167316, -0.134079651664363, 0.007055228657781288, 0.7976126913918229, -0.23000563419174966, 0.0, 0.0, 0.0], "pre_activation_mean": 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0.013709, 0.282067, -0.025399, 0.111302, -0.226032], [0.489345, 0.366446, -0.103175, 0.508133, -0.098587, -0.081496, -0.010884, -0.131857], [-0.074418, -0.624164, -0.382713, -0.340753, -0.270624, -0.276418, 0.274616, -0.082277]], "network.6.bias": [-0.260345, -0.257928, -0.145847, -0.320486, -0.035375, -0.2139, -0.302374, -0.03992], "network.8.weight": [[-0.331623, -0.249554, 0.131497, -0.351041, 0.094175, -0.212405, -0.392449, 0.010686]], "network.8.bias": [0.211371]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6972275674343109, "train_acc": 0.565, "val_loss": 0.6631535291671753, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.640335738658905, "train_acc": 0.565, "val_loss": 0.5430698394775391, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6313904821872711, "train_acc": 0.485, "val_loss": 0.659690797328949, "val_acc": 0.56}, {"stage": "improved", "epoch": 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0.31896165013313293, "train_acc": 0.89, "val_loss": 0.29644593596458435, "val_acc": 0.88}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.2916964590549469, "train_acc": 0.895, "val_loss": 0.31329232454299927, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.2710006758570671, "train_acc": 0.9, "val_loss": 0.25526532530784607, "val_acc": 0.9}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6631535291671753, "final_val_loss": 0.5430698394775391, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.659690797328949, "final_val_loss": 0.25526532530784607, "initial_val_acc": 0.56, "final_val_acc": 0.9, "best_val_acc": 0.94, "best_epoch": 4}, "improvement": 0.3799999999999999, "first_improvement_epoch": 1}} |
6 | {"target_pattern": "has_majority", "degraded_accuracy": 0.38, "improved_accuracy": 0.72, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8556, "learning_rate": 0.09363094593146719, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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"network.8.bias": [
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}
## Activation Signature
### 0
mean: [0.125609, -0.138505, 0.326275, 0.126654, -0.072273]
std: [0.327986, 0.022499, 0.287604, 0.248841, 0.091437]
fourier: [[5.211319, 5.355770, 5.407900, 6.423008, 11.304785], [0.381119, 0.435498, 0.491376, 0.513987, 12.465425], [4.620837, 4.662536, 4.965773, 6.262625, 29.364747], [3.512612, 3.862456, 4.362763, 5.523146, 11.398833], [1.368264, 1.442994, 1.460592, 1.685582, 6.504600]]
input_correlations: [[-0.943464, -0.174687, -0.141229, 0.328294, -0.045340, 0.000000, 0.000000, 0.000000], [-0.060152, 0.501447, 0.708426, 0.603936, 0.205172, 0.000000, 0.000000, 0.000000], [-0.066716, -0.518742, -0.806391, 0.151349, 0.051778, 0.000000, 0.000000, 0.000000], [-0.087579, -0.593815, 0.154558, -0.307206, -0.649316, 0.000000, 0.000000, 0.000000], [0.415844, 0.940890, 0.398716, 0.442258, -0.117015, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.402195, 1.588148, -1.265779, -0.725470, 1.917631]
pre_activation_std: [2.265072, 1.419559, 1.647993, 1.635425, 1.729110]
### 2
mean: [-1.039027, -0.123914, 0.129970, 1.344012, -1.658866]
std: [0.755447, 0.936863, 0.795451, 1.243243, 0.779929]
fourier: [[11.987372, 12.356765, 13.203454, 14.530613, 93.512435], [13.267649, 14.123601, 15.144583, 17.885173, 20.339697], [11.697336, 12.007687, 13.249420, 14.585426, 15.438546], [20.453899, 21.510725, 24.452451, 26.420798, 120.961074], [12.914687, 13.083894, 15.351006, 16.170109, 149.297970]]
input_correlations: [[-0.619585, -0.968721, 0.222498, 0.005202, -0.703613, 0.000000, 0.000000, 0.000000], [-0.436695, -0.247375, -0.294627, -0.558568, 0.562427, 0.000000, 0.000000, 0.000000], [-0.860674, -0.711009, 0.147335, -0.097641, -0.036647, 0.000000, 0.000000, 0.000000], [0.418593, 0.679625, -0.253096, -0.415965, 0.899335, 0.000000, 0.000000, 0.000000], [-0.467805, -0.784326, 0.107650, 0.182804, -0.948403, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.039027, -0.123914, 0.129970, 1.344012, -1.658866]
pre_activation_std: [0.755447, 0.936863, 0.795451, 1.243243, 0.779929]
### 4
mean: [-0.515813, -1.601433, -1.904816, 0.186952, -0.793564]
std: [0.951603, 0.665696, 1.083505, 0.750669, 0.581548]
fourier: [[14.406191, 17.081028, 17.574906, 19.390582, 46.423136], [10.799405, 11.282864, 13.302742, 13.493352, 144.128965], [18.360281, 20.000501, 21.178963, 23.099147, 171.433403], [11.442488, 11.757162, 12.042632, 13.107909, 16.825686], [9.814868, 10.461715, 11.866919, 12.257978, 71.420797]]
input_correlations: [[-0.143738, -0.479684, 0.244450, -0.977374, -0.916322, 0.000000, 0.000000, 0.000000], [-0.135515, -0.876642, -0.356520, -0.835492, -0.793991, 0.000000, 0.000000, 0.000000], [-0.207565, -0.767824, -0.226014, -0.923235, -0.873632, 0.000000, 0.000000, 0.000000], [0.211387, -0.048438, -0.654085, 0.825013, 0.742998, 0.000000, 0.000000, 0.000000], [-0.290865, -0.780153, -0.308878, -0.897680, -0.848576, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.515813, -1.601433, -1.904816, 0.186952, -0.793564]
pre_activation_std: [0.951603, 0.665696, 1.083505, 0.750669, 0.581548]
### 6
mean: [0.110663, -0.513075, 0.396966, -0.002190, -0.231480]
std: [0.435866, 0.263710, 0.439314, 0.617744, 0.244604]
fourier: [[6.881608, 6.930367, 8.291766, 8.298452, 9.959655], [3.625501, 3.631352, 4.622921, 5.342248, 46.176786], [6.992629, 7.049336, 8.087538, 8.590172, 35.726958], [9.695303, 9.977963, 10.024065, 11.347290, 12.260488], [3.992885, 4.038113, 4.163340, 4.311280, 20.833218]]
input_correlations: [[-0.541150, 0.623325, 0.722697, 0.983278, 0.054264, 0.000000, 0.000000, 0.000000], [-0.045980, -0.313079, -0.370918, -0.895480, -0.133690, 0.000000, 0.000000, 0.000000], [0.596802, -0.623978, -0.731493, -0.970774, -0.038198, 0.000000, 0.000000, 0.000000], [0.601798, -0.647692, -0.749387, -0.966715, -0.048369, 0.000000, 0.000000, 0.000000], [-0.731714, 0.510688, 0.631071, 0.910537, 0.034980, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.110663, -0.513075, 0.396966, -0.002190, -0.231480]
pre_activation_std: [0.435866, 0.263710, 0.439314, 0.617744, 0.244604]
### 8
mean: [0.318494]
std: [0.425304]
fourier: [[6.819996, 7.026274, 7.183138, 8.911444, 28.664418]]
input_correlations: [[-0.908966, 0.065965, 0.991913, 0.912654, -0.940561, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.318494]
pre_activation_std: [0.425304]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.050519,
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0.276895,
0.080678
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],
[
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[
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[
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"network.0.bias": [
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[
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[
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]
],
"network.2.bias": [
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"network.4.weight": [
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[
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[
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[
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],
"network.6.bias": [
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"network.8.weight": [
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],
"network.8.bias": [
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}
## Activation Signature
### 0
mean: [0.125609, -0.138505, 0.326275, 0.126654, -0.072273]
std: [0.327986, 0.022499, 0.287604, 0.248841, 0.091437]
fourier: [[5.211319, 5.355770, 5.407900, 6.423008, 11.304785], [0.381119, 0.435498, 0.491376, 0.513987, 12.465425], [4.620837, 4.662536, 4.965773, 6.262625, 29.364747], [3.512612, 3.862456, 4.362763, 5.523146, 11.398833], [1.368264, 1.442994, 1.460592, 1.685582, 6.504600]]
input_correlations: [[-0.943464, -0.174687, -0.141229, 0.328294, -0.045340, 0.000000, 0.000000, 0.000000], [-0.060152, 0.501447, 0.708426, 0.603936, 0.205172, 0.000000, 0.000000, 0.000000], [-0.066716, -0.518742, -0.806391, 0.151349, 0.051778, 0.000000, 0.000000, 0.000000], [-0.087579, -0.593815, 0.154558, -0.307206, -0.649316, 0.000000, 0.000000, 0.000000], [0.415844, 0.940890, 0.398716, 0.442258, -0.117015, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.402195, 1.588148, -1.265779, -0.725470, 1.917631]
pre_activation_std: [2.265072, 1.419559, 1.647993, 1.635425, 1.729110]
### 2
mean: [-1.039027, -0.123914, 0.129970, 1.344012, -1.658866]
std: [0.755447, 0.936863, 0.795451, 1.243243, 0.779929]
fourier: [[11.987372, 12.356765, 13.203454, 14.530613, 93.512435], [13.267649, 14.123601, 15.144583, 17.885173, 20.339697], [11.697336, 12.007687, 13.249420, 14.585426, 15.438546], [20.453899, 21.510725, 24.452451, 26.420798, 120.961074], [12.914687, 13.083894, 15.351006, 16.170109, 149.297970]]
input_correlations: [[-0.619585, -0.968721, 0.222498, 0.005202, -0.703613, 0.000000, 0.000000, 0.000000], [-0.436695, -0.247375, -0.294627, -0.558568, 0.562427, 0.000000, 0.000000, 0.000000], [-0.860674, -0.711009, 0.147335, -0.097641, -0.036647, 0.000000, 0.000000, 0.000000], [0.418593, 0.679625, -0.253096, -0.415965, 0.899335, 0.000000, 0.000000, 0.000000], [-0.467805, -0.784326, 0.107650, 0.182804, -0.948403, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.039027, -0.123914, 0.129970, 1.344012, -1.658866]
pre_activation_std: [0.755447, 0.936863, 0.795451, 1.243243, 0.779929]
### 4
mean: [-0.515813, -1.601433, -1.904816, 0.186952, -0.793564]
std: [0.951603, 0.665696, 1.083505, 0.750669, 0.581548]
fourier: [[14.406191, 17.081028, 17.574906, 19.390582, 46.423136], [10.799405, 11.282864, 13.302742, 13.493352, 144.128965], [18.360281, 20.000501, 21.178963, 23.099147, 171.433403], [11.442488, 11.757162, 12.042632, 13.107909, 16.825686], [9.814868, 10.461715, 11.866919, 12.257978, 71.420797]]
input_correlations: [[-0.143738, -0.479684, 0.244450, -0.977374, -0.916322, 0.000000, 0.000000, 0.000000], [-0.135515, -0.876642, -0.356520, -0.835492, -0.793991, 0.000000, 0.000000, 0.000000], [-0.207565, -0.767824, -0.226014, -0.923235, -0.873632, 0.000000, 0.000000, 0.000000], [0.211387, -0.048438, -0.654085, 0.825013, 0.742998, 0.000000, 0.000000, 0.000000], [-0.290865, -0.780153, -0.308878, -0.897680, -0.848576, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.515813, -1.601433, -1.904816, 0.186952, -0.793564]
pre_activation_std: [0.951603, 0.665696, 1.083505, 0.750669, 0.581548]
### 6
mean: [0.110663, -0.513075, 0.396966, -0.002190, -0.231480]
std: [0.435866, 0.263710, 0.439314, 0.617744, 0.244604]
fourier: [[6.881608, 6.930367, 8.291766, 8.298452, 9.959655], [3.625501, 3.631352, 4.622921, 5.342248, 46.176786], [6.992629, 7.049336, 8.087538, 8.590172, 35.726958], [9.695303, 9.977963, 10.024065, 11.347290, 12.260488], [3.992885, 4.038113, 4.163340, 4.311280, 20.833218]]
input_correlations: [[-0.541150, 0.623325, 0.722697, 0.983278, 0.054264, 0.000000, 0.000000, 0.000000], [-0.045980, -0.313079, -0.370918, -0.895480, -0.133690, 0.000000, 0.000000, 0.000000], [0.596802, -0.623978, -0.731493, -0.970774, -0.038198, 0.000000, 0.000000, 0.000000], [0.601798, -0.647692, -0.749387, -0.966715, -0.048369, 0.000000, 0.000000, 0.000000], [-0.731714, 0.510688, 0.631071, 0.910537, 0.034980, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.110663, -0.513075, 0.396966, -0.002190, -0.231480]
pre_activation_std: [0.435866, 0.263710, 0.439314, 0.617744, 0.244604]
### 8
mean: [0.318494]
std: [0.425304]
fourier: [[6.819996, 7.026274, 7.183138, 8.911444, 28.664418]]
input_correlations: [[-0.908966, 0.065965, 0.991913, 0.912654, -0.940561, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.318494]
pre_activation_std: [0.425304]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.0, 0.0, 0.0], "pre_activation_mean": 1.9176310300827026, "pre_activation_std": 1.7291103601455688}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -1.0390270948410034, "std": 0.7554466724395752, "fourier": [11.987371670294806, 12.356764785585394, 13.203454446292236, 14.530613174792782, 93.51243524253368], "input_correlations": [-0.6195845097615105, -0.9687209558959915, 0.22249817833887886, 0.005202241700870294, -0.7036132141909003, 0.0, 0.0, 0.0], "pre_activation_mean": -1.0390270948410034, "pre_activation_std": 0.7554466724395752}, "1": {"mean": -0.1239144504070282, "std": 0.9368631839752197, "fourier": [13.267648846772271, 14.123601236703607, 15.144583191389968, 17.885172865405902, 20.339696854163446], "input_correlations": [-0.43669471508131563, -0.24737511168322027, -0.29462702247578654, -0.5585679583309302, 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"train_loss": 0.6632483601570129, "train_acc": 0.6, "val_loss": 0.7811472415924072, "val_acc": 0.38}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6376964449882507, "train_acc": 0.6, "val_loss": 0.6819770336151123, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.7213469445705414, "train_acc": 0.535, "val_loss": 0.6547825336456299, "val_acc": 0.6}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.601013571023941, "train_acc": 0.69, "val_loss": 0.5960362553596497, "val_acc": 0.7}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.6832268834114075, "train_acc": 0.575, "val_loss": 0.562314510345459, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.5898528397083282, "train_acc": 0.68, "val_loss": 0.6387388110160828, "val_acc": 0.56}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.5307176411151886, "train_acc": 0.69, "val_loss": 0.7195602655410767, "val_acc": 0.5}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.5576728880405426, "train_acc": 0.675, "val_loss": 0.6669095754623413, "val_acc": 0.5}], "summary": {"total_epochs": 10, "degraded_epochs": 4, "improved_epochs": 6, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.7984893918037415, "final_val_loss": 0.6819770336151123, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.6547825336456299, "final_val_loss": 0.6669095754623413, "initial_val_acc": 0.6, "final_val_acc": 0.5, "best_val_acc": 0.72, "best_epoch": 6}, "improvement": 0.33999999999999997, "first_improvement_epoch": 3}} |
7 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.5, "improved_accuracy": 0.96, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9319, "learning_rate": 0.04720846293947128, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.weight": [
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [1.057408, 4.536193, 3.347437, 0.483138, 0.000000, 3.214089, 4.041339, 0.000000]
std: [2.020120, 2.909878, 2.166250, 0.149323, 0.000000, 2.089630, 2.621379, 0.000000]
fourier: [[33.941951, 35.693616, 37.294836, 37.864105, 95.166753], [42.488735, 52.437480, 54.777313, 59.210577, 408.257407], [32.213227, 39.984580, 40.382010, 43.416775, 301.269350], [2.409790, 2.825215, 2.898723, 3.153726, 43.482450], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [30.783803, 38.158325, 39.003749, 42.256191, 289.268032], [39.506083, 47.785836, 48.770386, 52.513385, 363.720511], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.548292, 0.448333, 0.307628, 0.179856, 0.157575, 0.000000, 0.000000, 0.000000], [0.705613, 0.808601, 0.246374, 0.384747, -0.153867, 0.000000, 0.000000, 0.000000], [-0.451877, -0.298819, -0.774302, -0.278676, -0.733287, 0.000000, 0.000000, 0.000000], [0.170920, 0.493539, -0.551315, 0.233132, -0.588956, 0.000000, 0.000000, 0.000000], [0.847052, 0.753923, 0.308952, 0.296566, 0.094039, 0.000000, 0.000000, 0.000000], [-0.540916, 0.207501, 0.199156, 0.735937, -0.156381, 0.000000, 0.000000, 0.000000], [0.775070, 0.540289, 0.541134, -0.377005, 0.007485, 0.000000, 0.000000, 0.000000], [0.439938, -0.501924, 0.595478, -0.227638, 0.224174, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.779460, 2.462437, -2.339462, -0.504863, 2.722106, 1.545895, 0.886024, 0.141359]
pre_activation_std: [1.163761, 2.491392, 1.603224, 1.539984, 2.178169, 1.375489, 1.505442, 1.091733]
### 2
mean: [0.388240, 1.152667, 0.514983, 0.514237, -1.421916, 2.405648, 2.024151, 0.525753]
std: [1.009585, 1.141443, 0.704331, 1.484703, 1.061527, 3.466318, 0.743232, 0.769788]
fourier: [[14.623869, 15.133350, 17.253860, 21.501331, 34.941556], [17.942734, 19.764092, 21.770063, 22.476545, 103.740019], [9.871916, 12.349417, 12.624671, 15.290218, 46.348473], [23.425811, 25.998998, 26.607981, 26.718366, 46.281321], [15.881187, 18.114682, 19.717004, 21.210630, 127.972484], [53.878367, 54.940146, 55.964775, 56.093602, 216.508352], [12.561471, 12.729313, 13.283265, 13.572219, 182.173597], [12.943790, 13.502044, 13.733131, 14.247942, 47.317731]]
input_correlations: [[0.759599, 0.018629, 0.000000, 0.192445, -0.179180, 0.818129, -0.435523, -0.495599], [0.662384, -0.236286, 0.000000, -0.008325, -0.387918, 0.859588, -0.609893, -0.189299], [0.181751, 0.101063, 0.000000, -0.165464, 0.264022, -0.375525, 0.759127, 0.661663], [-0.385221, 0.784700, 0.000000, 0.593218, 0.830831, -0.485454, 0.813587, 0.147246], [0.024476, -0.970616, 0.000000, -0.781344, -0.928274, -0.052344, -0.641480, -0.095094], [-0.161412, 0.932033, 0.000000, 0.617829, 0.969044, -0.273693, 0.797311, 0.081515], [0.608803, 0.510088, 0.000000, 0.209268, 0.479758, 0.694944, 0.205600, 0.250979], [0.781982, -0.204293, 0.000000, -0.260393, -0.326370, 0.831458, -0.321605, -0.015019]]
pre_activation_mean: [0.388240, 1.152667, 0.514983, 0.514237, -1.421916, 2.405648, 2.024151, 0.525753]
pre_activation_std: [1.009585, 1.141443, 0.704331, 1.484703, 1.061527, 3.466318, 0.743232, 0.769788]
### 4
mean: [1.255150, 2.120591, -0.937597, 2.019243, -1.422545, 0.857298, 0.177708, 0.219988]
std: [1.652911, 1.090250, 0.687297, 1.104886, 1.353248, 2.735773, 0.601558, 0.987396]
fourier: [[25.810047, 27.199091, 28.067577, 28.330935, 112.963524], [15.173406, 16.029200, 19.978625, 23.387348, 190.853166], [10.692456, 11.980331, 11.991816, 13.434157, 84.383763], [15.998749, 17.733585, 20.084349, 22.522413, 181.731870], [21.849635, 22.319956, 23.229710, 24.790441, 128.029052], [44.937001, 45.193476, 45.339096, 49.858879, 77.156867], [9.600505, 10.799860, 11.318543, 11.483455, 15.993744], [16.041173, 16.332098, 16.733334, 19.510479, 19.798921]]
input_correlations: [[-0.156922, -0.423866, 0.335990, 0.961022, 0.000000, 0.998714, 0.262147, -0.330517], [0.745759, 0.837166, 0.161054, -0.581492, 0.000000, -0.465660, 0.639653, 0.930504], [0.003251, 0.256274, -0.191284, -0.918531, 0.000000, -0.978038, -0.335210, 0.229110], [0.901885, 0.956933, -0.107451, -0.521077, 0.000000, -0.341919, 0.745214, 0.906848], [0.055336, 0.323202, -0.314794, -0.937262, 0.000000, -0.995712, -0.354661, 0.253963], [-0.393262, -0.628768, 0.296546, 0.966993, 0.000000, 0.958810, 0.028862, -0.559764], [0.729769, 0.876018, -0.117535, -0.766638, 0.000000, -0.692083, 0.411384, 0.884128], [0.530487, 0.755321, -0.207729, -0.925814, 0.000000, -0.867652, 0.212079, 0.720523]]
pre_activation_mean: [1.255150, 2.120591, -0.937597, 2.019243, -1.422545, 0.857298, 0.177708, 0.219988]
pre_activation_std: [1.652911, 1.090250, 0.687297, 1.104886, 1.353248, 2.735773, 0.601558, 0.987396]
### 6
mean: [-0.833556, -0.494334, 3.291349, 0.995337, 2.241860, 1.271322, 1.277068, -0.543905]
std: [0.638679, 1.015966, 1.497633, 3.013107, 1.997850, 1.018634, 1.278116, 0.750233]
fourier: [[10.663540, 11.046994, 11.393629, 11.721612, 75.020023], [16.880633, 17.174332, 17.881331, 19.501489, 44.490032], [22.091873, 22.620555, 26.505804, 31.506739, 296.221386], [48.744769, 48.834817, 51.772617, 55.453499, 89.580369], [30.762431, 34.198277, 37.976227, 40.463961, 201.767355], [15.371855, 16.646318, 19.903612, 20.897389, 114.418961], [20.783823, 21.239221, 23.392531, 25.782998, 114.936115], [12.256422, 12.425344, 12.974436, 14.629088, 48.951465]]
input_correlations: [[-0.971900, 0.579904, 0.000000, 0.511636, 0.000000, -0.999572, 0.448714, 0.568873], [-0.916014, 0.757997, 0.000000, 0.698971, 0.000000, -0.968262, 0.663590, 0.753974], [-0.367375, 0.975301, 0.000000, 0.979920, 0.000000, -0.508495, 0.949745, 0.870426], [0.961461, -0.681744, 0.000000, -0.598377, 0.000000, 0.989417, -0.561389, -0.680767], [-0.753049, 0.919237, 0.000000, 0.876801, 0.000000, -0.852147, 0.826653, 0.845059], [-0.601433, 0.967615, 0.000000, 0.944414, 0.000000, -0.708379, 0.927747, 0.918610], [-0.823323, 0.877893, 0.000000, 0.820952, 0.000000, -0.898398, 0.779276, 0.835104], [0.838608, -0.806564, 0.000000, -0.741162, 0.000000, 0.932293, -0.634856, -0.667170]]
pre_activation_mean: [-0.833556, -0.494334, 3.291349, 0.995337, 2.241860, 1.271322, 1.277068, -0.543905]
pre_activation_std: [0.638679, 1.015966, 1.497633, 3.013107, 1.997850, 1.018634, 1.278116, 0.750233]
### 8
mean: [0.518875, 4.376496, 3.005525, 0.483138, -1.427283, 2.977846, 3.719159, -1.656637]
std: [2.347494, 3.184771, 2.774046, 0.149323, 0.602876, 2.500074, 3.179563, 0.474834]
fourier: [[38.467157, 41.001066, 41.399033, 43.801649, 46.698743], [48.441633, 55.883987, 62.728224, 63.332592, 393.884607], [42.894564, 49.641831, 52.404182, 55.379949, 270.497232], [2.409790, 2.825215, 2.898723, 3.153726, 43.482450], [8.803085, 10.366523, 11.204434, 12.692719, 128.455438], [38.331099, 44.473166, 48.518036, 49.783010, 268.006128], [49.424987, 56.839571, 60.928260, 62.907382, 334.724344], [8.001096, 8.017756, 8.048601, 9.708104, 149.097312]]
input_correlations: [[0.000000, -0.476599, -0.648506, 0.980142, -0.845157, -0.765101, -0.870490, 0.895429], [0.000000, 0.747013, 0.923114, -0.791987, 0.991519, 0.973076, 0.985940, -0.711049], [0.000000, 0.678038, 0.869709, -0.864319, 0.971795, 0.935041, 0.971882, -0.786131], [0.000000, 0.354954, 0.154614, 0.742320, -0.100466, 0.021935, -0.155428, 0.758542], [0.000000, -0.801780, -0.965639, 0.664796, -0.990713, -0.996431, -0.980627, 0.565615], [0.000000, 0.708424, 0.895937, -0.833579, 0.982605, 0.954142, 0.979942, -0.754321], [0.000000, 0.705604, 0.883452, -0.843725, 0.980901, 0.949055, 0.981910, -0.757815], [0.000000, -0.604685, -0.609831, -0.353525, -0.375561, -0.490749, -0.314124, -0.395940]]
pre_activation_mean: [0.518875, 4.376496, 3.005525, 0.483138, -1.427283, 2.977846, 3.719159, -1.656637]
pre_activation_std: [2.347494, 3.184771, 2.774046, 0.149323, 0.602876, 2.500074, 3.179563, 0.474834]
### 10
mean: [-5.622425]
std: [4.786907]
fourier: [[73.229763, 89.131359, 92.247982, 92.781851, 506.018197]]
input_correlations: [[0.826780, -0.988656, -0.991057, 0.240440, 0.000000, -0.989375, -0.990580, 0.000000]]
pre_activation_mean: [-5.622425]
pre_activation_std: [4.786907]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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0.413153,
0.250656,
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],
[
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0.167734,
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]
],
"network.2.bias": [
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],
"network.4.weight": [
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[
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0.361348
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[
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[
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0.537379,
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0.071147,
0.302409,
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[
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"network.10.weight": [
[
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"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [1.057408, 4.536193, 3.347437, 0.483138, 0.000000, 3.214089, 4.041339, 0.000000]
std: [2.020120, 2.909878, 2.166250, 0.149323, 0.000000, 2.089630, 2.621379, 0.000000]
fourier: [[33.941951, 35.693616, 37.294836, 37.864105, 95.166753], [42.488735, 52.437480, 54.777313, 59.210577, 408.257407], [32.213227, 39.984580, 40.382010, 43.416775, 301.269350], [2.409790, 2.825215, 2.898723, 3.153726, 43.482450], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [30.783803, 38.158325, 39.003749, 42.256191, 289.268032], [39.506083, 47.785836, 48.770386, 52.513385, 363.720511], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.548292, 0.448333, 0.307628, 0.179856, 0.157575, 0.000000, 0.000000, 0.000000], [0.705613, 0.808601, 0.246374, 0.384747, -0.153867, 0.000000, 0.000000, 0.000000], [-0.451877, -0.298819, -0.774302, -0.278676, -0.733287, 0.000000, 0.000000, 0.000000], [0.170920, 0.493539, -0.551315, 0.233132, -0.588956, 0.000000, 0.000000, 0.000000], [0.847052, 0.753923, 0.308952, 0.296566, 0.094039, 0.000000, 0.000000, 0.000000], [-0.540916, 0.207501, 0.199156, 0.735937, -0.156381, 0.000000, 0.000000, 0.000000], [0.775070, 0.540289, 0.541134, -0.377005, 0.007485, 0.000000, 0.000000, 0.000000], [0.439938, -0.501924, 0.595478, -0.227638, 0.224174, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.779460, 2.462437, -2.339462, -0.504863, 2.722106, 1.545895, 0.886024, 0.141359]
pre_activation_std: [1.163761, 2.491392, 1.603224, 1.539984, 2.178169, 1.375489, 1.505442, 1.091733]
### 2
mean: [0.388240, 1.152667, 0.514983, 0.514237, -1.421916, 2.405648, 2.024151, 0.525753]
std: [1.009585, 1.141443, 0.704331, 1.484703, 1.061527, 3.466318, 0.743232, 0.769788]
fourier: [[14.623869, 15.133350, 17.253860, 21.501331, 34.941556], [17.942734, 19.764092, 21.770063, 22.476545, 103.740019], [9.871916, 12.349417, 12.624671, 15.290218, 46.348473], [23.425811, 25.998998, 26.607981, 26.718366, 46.281321], [15.881187, 18.114682, 19.717004, 21.210630, 127.972484], [53.878367, 54.940146, 55.964775, 56.093602, 216.508352], [12.561471, 12.729313, 13.283265, 13.572219, 182.173597], [12.943790, 13.502044, 13.733131, 14.247942, 47.317731]]
input_correlations: [[0.759599, 0.018629, 0.000000, 0.192445, -0.179180, 0.818129, -0.435523, -0.495599], [0.662384, -0.236286, 0.000000, -0.008325, -0.387918, 0.859588, -0.609893, -0.189299], [0.181751, 0.101063, 0.000000, -0.165464, 0.264022, -0.375525, 0.759127, 0.661663], [-0.385221, 0.784700, 0.000000, 0.593218, 0.830831, -0.485454, 0.813587, 0.147246], [0.024476, -0.970616, 0.000000, -0.781344, -0.928274, -0.052344, -0.641480, -0.095094], [-0.161412, 0.932033, 0.000000, 0.617829, 0.969044, -0.273693, 0.797311, 0.081515], [0.608803, 0.510088, 0.000000, 0.209268, 0.479758, 0.694944, 0.205600, 0.250979], [0.781982, -0.204293, 0.000000, -0.260393, -0.326370, 0.831458, -0.321605, -0.015019]]
pre_activation_mean: [0.388240, 1.152667, 0.514983, 0.514237, -1.421916, 2.405648, 2.024151, 0.525753]
pre_activation_std: [1.009585, 1.141443, 0.704331, 1.484703, 1.061527, 3.466318, 0.743232, 0.769788]
### 4
mean: [1.255150, 2.120591, -0.937597, 2.019243, -1.422545, 0.857298, 0.177708, 0.219988]
std: [1.652911, 1.090250, 0.687297, 1.104886, 1.353248, 2.735773, 0.601558, 0.987396]
fourier: [[25.810047, 27.199091, 28.067577, 28.330935, 112.963524], [15.173406, 16.029200, 19.978625, 23.387348, 190.853166], [10.692456, 11.980331, 11.991816, 13.434157, 84.383763], [15.998749, 17.733585, 20.084349, 22.522413, 181.731870], [21.849635, 22.319956, 23.229710, 24.790441, 128.029052], [44.937001, 45.193476, 45.339096, 49.858879, 77.156867], [9.600505, 10.799860, 11.318543, 11.483455, 15.993744], [16.041173, 16.332098, 16.733334, 19.510479, 19.798921]]
input_correlations: [[-0.156922, -0.423866, 0.335990, 0.961022, 0.000000, 0.998714, 0.262147, -0.330517], [0.745759, 0.837166, 0.161054, -0.581492, 0.000000, -0.465660, 0.639653, 0.930504], [0.003251, 0.256274, -0.191284, -0.918531, 0.000000, -0.978038, -0.335210, 0.229110], [0.901885, 0.956933, -0.107451, -0.521077, 0.000000, -0.341919, 0.745214, 0.906848], [0.055336, 0.323202, -0.314794, -0.937262, 0.000000, -0.995712, -0.354661, 0.253963], [-0.393262, -0.628768, 0.296546, 0.966993, 0.000000, 0.958810, 0.028862, -0.559764], [0.729769, 0.876018, -0.117535, -0.766638, 0.000000, -0.692083, 0.411384, 0.884128], [0.530487, 0.755321, -0.207729, -0.925814, 0.000000, -0.867652, 0.212079, 0.720523]]
pre_activation_mean: [1.255150, 2.120591, -0.937597, 2.019243, -1.422545, 0.857298, 0.177708, 0.219988]
pre_activation_std: [1.652911, 1.090250, 0.687297, 1.104886, 1.353248, 2.735773, 0.601558, 0.987396]
### 6
mean: [-0.833556, -0.494334, 3.291349, 0.995337, 2.241860, 1.271322, 1.277068, -0.543905]
std: [0.638679, 1.015966, 1.497633, 3.013107, 1.997850, 1.018634, 1.278116, 0.750233]
fourier: [[10.663540, 11.046994, 11.393629, 11.721612, 75.020023], [16.880633, 17.174332, 17.881331, 19.501489, 44.490032], [22.091873, 22.620555, 26.505804, 31.506739, 296.221386], [48.744769, 48.834817, 51.772617, 55.453499, 89.580369], [30.762431, 34.198277, 37.976227, 40.463961, 201.767355], [15.371855, 16.646318, 19.903612, 20.897389, 114.418961], [20.783823, 21.239221, 23.392531, 25.782998, 114.936115], [12.256422, 12.425344, 12.974436, 14.629088, 48.951465]]
input_correlations: [[-0.971900, 0.579904, 0.000000, 0.511636, 0.000000, -0.999572, 0.448714, 0.568873], [-0.916014, 0.757997, 0.000000, 0.698971, 0.000000, -0.968262, 0.663590, 0.753974], [-0.367375, 0.975301, 0.000000, 0.979920, 0.000000, -0.508495, 0.949745, 0.870426], [0.961461, -0.681744, 0.000000, -0.598377, 0.000000, 0.989417, -0.561389, -0.680767], [-0.753049, 0.919237, 0.000000, 0.876801, 0.000000, -0.852147, 0.826653, 0.845059], [-0.601433, 0.967615, 0.000000, 0.944414, 0.000000, -0.708379, 0.927747, 0.918610], [-0.823323, 0.877893, 0.000000, 0.820952, 0.000000, -0.898398, 0.779276, 0.835104], [0.838608, -0.806564, 0.000000, -0.741162, 0.000000, 0.932293, -0.634856, -0.667170]]
pre_activation_mean: [-0.833556, -0.494334, 3.291349, 0.995337, 2.241860, 1.271322, 1.277068, -0.543905]
pre_activation_std: [0.638679, 1.015966, 1.497633, 3.013107, 1.997850, 1.018634, 1.278116, 0.750233]
### 8
mean: [0.518875, 4.376496, 3.005525, 0.483138, -1.427283, 2.977846, 3.719159, -1.656637]
std: [2.347494, 3.184771, 2.774046, 0.149323, 0.602876, 2.500074, 3.179563, 0.474834]
fourier: [[38.467157, 41.001066, 41.399033, 43.801649, 46.698743], [48.441633, 55.883987, 62.728224, 63.332592, 393.884607], [42.894564, 49.641831, 52.404182, 55.379949, 270.497232], [2.409790, 2.825215, 2.898723, 3.153726, 43.482450], [8.803085, 10.366523, 11.204434, 12.692719, 128.455438], [38.331099, 44.473166, 48.518036, 49.783010, 268.006128], [49.424987, 56.839571, 60.928260, 62.907382, 334.724344], [8.001096, 8.017756, 8.048601, 9.708104, 149.097312]]
input_correlations: [[0.000000, -0.476599, -0.648506, 0.980142, -0.845157, -0.765101, -0.870490, 0.895429], [0.000000, 0.747013, 0.923114, -0.791987, 0.991519, 0.973076, 0.985940, -0.711049], [0.000000, 0.678038, 0.869709, -0.864319, 0.971795, 0.935041, 0.971882, -0.786131], [0.000000, 0.354954, 0.154614, 0.742320, -0.100466, 0.021935, -0.155428, 0.758542], [0.000000, -0.801780, -0.965639, 0.664796, -0.990713, -0.996431, -0.980627, 0.565615], [0.000000, 0.708424, 0.895937, -0.833579, 0.982605, 0.954142, 0.979942, -0.754321], [0.000000, 0.705604, 0.883452, -0.843725, 0.980901, 0.949055, 0.981910, -0.757815], [0.000000, -0.604685, -0.609831, -0.353525, -0.375561, -0.490749, -0.314124, -0.395940]]
pre_activation_mean: [0.518875, 4.376496, 3.005525, 0.483138, -1.427283, 2.977846, 3.719159, -1.656637]
pre_activation_std: [2.347494, 3.184771, 2.774046, 0.149323, 0.602876, 2.500074, 3.179563, 0.474834]
### 10
mean: [-5.622425]
std: [4.786907]
fourier: [[73.229763, 89.131359, 92.247982, 92.781851, 506.018197]]
input_correlations: [[0.826780, -0.988656, -0.991057, 0.240440, 0.000000, -0.989375, -0.990580, 0.000000]]
pre_activation_mean: [-5.622425]
pre_activation_std: [4.786907]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 1.057408332824707, "std": 2.02012038230896, "fourier": [33.94195148532583, 35.6936161721133, 37.29483576344099, 37.864104528322095, 95.16675299406052], "input_correlations": [-0.5482921783218855, 0.44833305981567173, 0.307627710351845, 0.17985592444242554, 0.15757467257428384, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7794601321220398, "pre_activation_std": 1.1637614965438843}, "1": {"mean": 4.536193370819092, "std": 2.9098780155181885, "fourier": [42.48873499186531, 52.43747953498286, 54.77731284406466, 59.21057697631737, 408.2574070096016], "input_correlations": [0.7056132277268377, 0.8086010169219612, 0.2463736932372621, 0.3847465300674516, -0.1538666279660477, 0.0, 0.0, 0.0], "pre_activation_mean": 2.4624369144439697, "pre_activation_std": 2.4913923740386963}, "2": {"mean": 3.3474371433258057, "std": 2.1662495136260986, "fourier": [32.21322652503893, 39.9845801266392, 40.38201003693929, 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8 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.42, "improved_accuracy": 0.98, "improvement": 0.56, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9749, "learning_rate": 0.04776131004515171, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.110837,
0.268533
],
[
1.093527,
0.771831,
0.187024,
1.003309,
0.366829
],
[
-0.498504,
-0.46345,
-0.167251,
-0.826065,
-0.016215
],
[
-0.236537,
0.290774,
0.063312,
-0.319338,
0.240861
],
[
-0.356617,
-0.273402,
-0.415306,
-0.075809,
0.671619
]
],
"network.8.bias": [
0.178117,
-0.243067,
1.192567,
-0.344372,
1.096817
],
"network.10.weight": [
[
-0.531417,
-0.079402,
0.956267,
0.158899,
1.085462
],
[
-0.059607,
-0.226763,
-0.41008,
0.016497,
-0.013595
],
[
-0.295699,
0.703246,
-0.528633,
-0.363756,
-0.105433
],
[
-0.391154,
-0.207717,
-0.554663,
0.19046,
-0.263792
],
[
-0.46292,
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]
],
"network.10.bias": [
0.841135,
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0.236598,
-0.100457,
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],
"network.12.weight": [
[
0.912341,
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-0.834635,
-0.111804,
-0.484222
]
],
"network.12.bias": [
-0.047324
]
}
## Activation Signature
### 0
mean: [0.783146, 0.000000, 7.986980, 0.000000, 5.749999]
std: [1.157213, 0.000000, 5.763462, 0.000000, 4.284618]
fourier: [[17.831293, 18.431034, 20.645458, 22.512181, 70.483118], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [86.377780, 87.427172, 88.910090, 116.829911, 718.828248], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [63.863990, 64.672225, 65.944101, 87.726581, 517.499889]]
input_correlations: [[0.070714, 0.182375, 0.278364, 0.707486, 0.790063, 0.000000, 0.000000, 0.000000], [0.571787, 0.872194, 0.157369, 0.475159, -0.165584, 0.000000, 0.000000, 0.000000], [-0.765074, 0.135167, 0.079626, 0.503155, -0.238594, 0.000000, 0.000000, 0.000000], [-0.088203, -0.377136, -0.514434, 0.598812, -0.101297, 0.000000, 0.000000, 0.000000], [-0.506565, -0.236704, -0.132671, 0.413098, 0.700956, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.087435, 1.839229, 0.957929, 0.314495, 0.569226]
pre_activation_std: [1.859239, 2.030124, 2.113518, 1.111704, 2.247048]
### 2
mean: [-1.568301, 0.117656, -2.794798, -1.796607, 2.696404]
std: [1.721145, 1.701490, 1.459756, 1.357003, 2.437972]
fourier: [[27.397844, 28.371486, 32.875032, 34.028790, 141.147097], [24.363320, 25.137348, 26.162792, 27.691190, 30.400187], [24.559984, 25.133575, 26.166855, 32.035052, 251.531824], [21.575904, 23.399532, 25.036938, 26.075151, 161.694620], [36.176069, 38.355110, 38.540019, 50.224410, 242.676376]]
input_correlations: [[-0.908762, -0.349844, 0.011107, -0.095280, -0.781243, 0.000000, 0.000000, 0.000000], [0.029635, 0.699265, -0.538820, -0.411416, -0.217111, 0.000000, 0.000000, 0.000000], [-0.515890, -0.855014, -0.464932, -0.324566, -0.167289, 0.000000, 0.000000, 0.000000], [-0.960458, -0.329070, -0.063966, -0.191210, -0.747204, 0.000000, 0.000000, 0.000000], [0.658690, -0.393464, 0.567604, 0.455314, 0.786263, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.568301, 0.117656, -2.794798, -1.796607, 2.696404]
pre_activation_std: [1.721145, 1.701490, 1.459756, 1.357003, 2.437972]
### 4
mean: [2.859298, -1.183969, -1.220638, -1.368971, -0.487171]
std: [2.371742, 0.929997, 0.376012, 0.887953, 1.816879]
fourier: [[35.694734, 35.982349, 36.532350, 50.374935, 257.336860], [13.716542, 14.039253, 14.169398, 19.374815, 106.557234], [5.399947, 6.069470, 6.387289, 6.667868, 109.857425], [13.151699, 13.359693, 13.912862, 17.008249, 123.207375], [26.800152, 26.838251, 31.114044, 39.167216, 43.845409]]
input_correlations: [[-0.087745, -0.680247, 0.000000, 0.000000, 0.979899, 0.000000, 0.000000, 0.000000], [0.169597, 0.584130, 0.000000, 0.000000, -0.997288, 0.000000, 0.000000, 0.000000], [0.308697, 0.287218, 0.000000, 0.000000, -0.966501, 0.000000, 0.000000, 0.000000], [0.186893, 0.442916, 0.000000, 0.000000, -0.994668, 0.000000, 0.000000, 0.000000], [-0.011093, 0.835816, 0.000000, 0.000000, -0.904485, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.859298, -1.183969, -1.220638, -1.368971, -0.487171]
pre_activation_std: [2.371742, 0.929997, 0.376012, 0.887953, 1.816879]
### 6
mean: [3.918188, 3.485059, -1.938612, 2.944292, 2.741536]
std: [3.159415, 2.840444, 0.905596, 2.401641, 2.068280]
fourier: [[47.944692, 48.375781, 50.039582, 65.778256, 352.636922], [43.077233, 43.517949, 45.287853, 59.061661, 313.655292], [12.650161, 14.573566, 14.678442, 16.530948, 174.475124], [36.231074, 36.807344, 39.043136, 49.745939, 264.986280], [30.693021, 31.013349, 31.192320, 42.684830, 246.738280]]
input_correlations: [[0.990705, -0.481569, 0.000000, 0.000000, -0.724360, 0.000000, 0.000000, 0.000000], [0.988536, -0.489293, 0.000000, 0.000000, -0.734690, 0.000000, 0.000000, 0.000000], [-0.680001, -0.216535, 0.000000, 0.000000, -0.148763, 0.000000, 0.000000, 0.000000], [0.978231, -0.523552, 0.000000, 0.000000, -0.772450, 0.000000, 0.000000, 0.000000], [0.999551, -0.374968, 0.000000, 0.000000, -0.600196, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.918188, 3.485059, -1.938612, 2.944292, 2.741536]
pre_activation_std: [3.159415, 2.840444, 0.905596, 2.401641, 2.068280]
### 8
mean: [0.126817, 11.120415, -5.121875, -0.579248, 0.260705]
std: [0.057197, 8.148895, 4.489014, 0.139657, 0.556279]
fourier: [[0.923923, 1.049824, 1.162278, 1.281769, 11.413536], [122.864456, 124.021829, 125.285064, 165.470110, 1000.837288], [67.938488, 68.372546, 69.206805, 90.850566, 460.968781], [2.141412, 2.214156, 2.233857, 2.712166, 52.132308], [8.714517, 8.826223, 8.936749, 10.484047, 23.463424]]
input_correlations: [[-0.075559, -0.081911, 0.000000, -0.116040, 0.004999, 0.000000, 0.000000, 0.000000], [0.999986, 0.999995, 0.000000, 0.999349, 0.996348, 0.000000, 0.000000, 0.000000], [-0.999849, -0.999936, 0.000000, -0.999718, -0.995215, 0.000000, 0.000000, 0.000000], [-0.891180, -0.893987, 0.000000, -0.908962, -0.851836, 0.000000, 0.000000, 0.000000], [-0.975206, -0.976590, 0.000000, -0.983351, -0.954200, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.126817, 11.120415, -5.121875, -0.579248, 0.260705]
pre_activation_std: [0.057197, 8.148895, 4.489014, 0.139657, 0.556279]
### 10
mean: [0.479567, -2.637236, 7.890967, -2.679041, 5.671055]
std: [1.423612, 1.718866, 5.898923, 1.445681, 4.392793]
fourier: [[22.612679, 22.885077, 22.982246, 23.265816, 43.160987], [25.272125, 25.674492, 26.063251, 35.991375, 237.351204], [89.423423, 90.145995, 91.183673, 118.312421, 710.187147], [20.870741, 21.030309, 21.088454, 30.940072, 241.113695], [66.286672, 66.910904, 67.800260, 88.953622, 510.394996]]
input_correlations: [[0.412733, -0.929702, 0.879381, 0.000000, 0.969355, 0.000000, 0.000000, 0.000000], [0.002429, -0.996540, 0.592892, 0.000000, 0.800732, 0.000000, 0.000000, 0.000000], [-0.108031, 0.999346, -0.684412, 0.000000, -0.857604, 0.000000, 0.000000, 0.000000], [-0.092761, -0.983627, 0.513309, 0.000000, 0.738981, 0.000000, 0.000000, 0.000000], [-0.089818, 0.999890, -0.668153, 0.000000, -0.848662, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.479567, -2.637236, 7.890967, -2.679041, 5.671055]
pre_activation_std: [1.423612, 1.718866, 5.898923, 1.445681, 4.392793]
### 12
mean: [-8.783321]
std: [7.743587]
fourier: [[117.964284, 118.982666, 122.275987, 151.970080, 790.498911]]
input_correlations: [[0.836633, 0.000000, -0.997033, 0.000000, -0.994925, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-8.783321]
pre_activation_std: [7.743587]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.032666,
0.146452,
0.544775,
0.681822
],
[
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-0.0702,
0.323754,
-0.310661
],
[
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0.3869,
0.424149,
-0.248514
],
[
0.195803,
-0.413249,
-0.25254,
0.466401,
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],
[
-0.616352,
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]
],
"network.0.bias": [
-0.099824,
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0.254329,
0.502306,
-0.025294
],
"network.2.weight": [
[
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0.255487,
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],
[
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0.605358,
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],
[
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],
[
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0.042961,
-0.081245
],
[
0.187964,
-0.4657,
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0.595655,
0.734472
]
],
"network.2.bias": [
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0.06923,
-0.595319,
-0.269856,
0.791747
],
"network.4.weight": [
[
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0.922721
],
[
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0.301656,
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],
[
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0.056369,
-0.186302
],
[
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-0.089719,
-0.035969,
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],
[
-0.382624,
0.67972,
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]
],
"network.4.bias": [
0.485454,
-0.115798,
-0.640416,
-0.08702,
0.566104
],
"network.6.weight": [
[
1.255985,
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0.216638,
-0.42908,
-0.526904
],
[
1.110681,
0.166709,
-0.128758,
-0.216499,
-0.532464
],
[
-0.515432,
-0.45022,
-0.314121,
-0.340095,
-0.805263
],
[
0.879563,
-0.101297,
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0.433892,
-0.61086
],
[
0.953421,
0.200258,
-0.189521,
0.281672,
0.070745
]
],
"network.6.bias": [
0.465174,
0.462966,
0.002633,
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],
"network.8.weight": [
[
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-0.110837,
0.268533
],
[
1.093527,
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0.187024,
1.003309,
0.366829
],
[
-0.498504,
-0.46345,
-0.167251,
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],
[
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0.290774,
0.063312,
-0.319338,
0.240861
],
[
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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],
[
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],
[
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],
[
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],
[
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]
],
"network.10.bias": [
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],
"network.12.weight": [
[
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],
"network.12.bias": [
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]
}
## Activation Signature
### 0
mean: [0.783146, 0.000000, 7.986980, 0.000000, 5.749999]
std: [1.157213, 0.000000, 5.763462, 0.000000, 4.284618]
fourier: [[17.831293, 18.431034, 20.645458, 22.512181, 70.483118], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [86.377780, 87.427172, 88.910090, 116.829911, 718.828248], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [63.863990, 64.672225, 65.944101, 87.726581, 517.499889]]
input_correlations: [[0.070714, 0.182375, 0.278364, 0.707486, 0.790063, 0.000000, 0.000000, 0.000000], [0.571787, 0.872194, 0.157369, 0.475159, -0.165584, 0.000000, 0.000000, 0.000000], [-0.765074, 0.135167, 0.079626, 0.503155, -0.238594, 0.000000, 0.000000, 0.000000], [-0.088203, -0.377136, -0.514434, 0.598812, -0.101297, 0.000000, 0.000000, 0.000000], [-0.506565, -0.236704, -0.132671, 0.413098, 0.700956, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.087435, 1.839229, 0.957929, 0.314495, 0.569226]
pre_activation_std: [1.859239, 2.030124, 2.113518, 1.111704, 2.247048]
### 2
mean: [-1.568301, 0.117656, -2.794798, -1.796607, 2.696404]
std: [1.721145, 1.701490, 1.459756, 1.357003, 2.437972]
fourier: [[27.397844, 28.371486, 32.875032, 34.028790, 141.147097], [24.363320, 25.137348, 26.162792, 27.691190, 30.400187], [24.559984, 25.133575, 26.166855, 32.035052, 251.531824], [21.575904, 23.399532, 25.036938, 26.075151, 161.694620], [36.176069, 38.355110, 38.540019, 50.224410, 242.676376]]
input_correlations: [[-0.908762, -0.349844, 0.011107, -0.095280, -0.781243, 0.000000, 0.000000, 0.000000], [0.029635, 0.699265, -0.538820, -0.411416, -0.217111, 0.000000, 0.000000, 0.000000], [-0.515890, -0.855014, -0.464932, -0.324566, -0.167289, 0.000000, 0.000000, 0.000000], [-0.960458, -0.329070, -0.063966, -0.191210, -0.747204, 0.000000, 0.000000, 0.000000], [0.658690, -0.393464, 0.567604, 0.455314, 0.786263, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.568301, 0.117656, -2.794798, -1.796607, 2.696404]
pre_activation_std: [1.721145, 1.701490, 1.459756, 1.357003, 2.437972]
### 4
mean: [2.859298, -1.183969, -1.220638, -1.368971, -0.487171]
std: [2.371742, 0.929997, 0.376012, 0.887953, 1.816879]
fourier: [[35.694734, 35.982349, 36.532350, 50.374935, 257.336860], [13.716542, 14.039253, 14.169398, 19.374815, 106.557234], [5.399947, 6.069470, 6.387289, 6.667868, 109.857425], [13.151699, 13.359693, 13.912862, 17.008249, 123.207375], [26.800152, 26.838251, 31.114044, 39.167216, 43.845409]]
input_correlations: [[-0.087745, -0.680247, 0.000000, 0.000000, 0.979899, 0.000000, 0.000000, 0.000000], [0.169597, 0.584130, 0.000000, 0.000000, -0.997288, 0.000000, 0.000000, 0.000000], [0.308697, 0.287218, 0.000000, 0.000000, -0.966501, 0.000000, 0.000000, 0.000000], [0.186893, 0.442916, 0.000000, 0.000000, -0.994668, 0.000000, 0.000000, 0.000000], [-0.011093, 0.835816, 0.000000, 0.000000, -0.904485, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.859298, -1.183969, -1.220638, -1.368971, -0.487171]
pre_activation_std: [2.371742, 0.929997, 0.376012, 0.887953, 1.816879]
### 6
mean: [3.918188, 3.485059, -1.938612, 2.944292, 2.741536]
std: [3.159415, 2.840444, 0.905596, 2.401641, 2.068280]
fourier: [[47.944692, 48.375781, 50.039582, 65.778256, 352.636922], [43.077233, 43.517949, 45.287853, 59.061661, 313.655292], [12.650161, 14.573566, 14.678442, 16.530948, 174.475124], [36.231074, 36.807344, 39.043136, 49.745939, 264.986280], [30.693021, 31.013349, 31.192320, 42.684830, 246.738280]]
input_correlations: [[0.990705, -0.481569, 0.000000, 0.000000, -0.724360, 0.000000, 0.000000, 0.000000], [0.988536, -0.489293, 0.000000, 0.000000, -0.734690, 0.000000, 0.000000, 0.000000], [-0.680001, -0.216535, 0.000000, 0.000000, -0.148763, 0.000000, 0.000000, 0.000000], [0.978231, -0.523552, 0.000000, 0.000000, -0.772450, 0.000000, 0.000000, 0.000000], [0.999551, -0.374968, 0.000000, 0.000000, -0.600196, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.918188, 3.485059, -1.938612, 2.944292, 2.741536]
pre_activation_std: [3.159415, 2.840444, 0.905596, 2.401641, 2.068280]
### 8
mean: [0.126817, 11.120415, -5.121875, -0.579248, 0.260705]
std: [0.057197, 8.148895, 4.489014, 0.139657, 0.556279]
fourier: [[0.923923, 1.049824, 1.162278, 1.281769, 11.413536], [122.864456, 124.021829, 125.285064, 165.470110, 1000.837288], [67.938488, 68.372546, 69.206805, 90.850566, 460.968781], [2.141412, 2.214156, 2.233857, 2.712166, 52.132308], [8.714517, 8.826223, 8.936749, 10.484047, 23.463424]]
input_correlations: [[-0.075559, -0.081911, 0.000000, -0.116040, 0.004999, 0.000000, 0.000000, 0.000000], [0.999986, 0.999995, 0.000000, 0.999349, 0.996348, 0.000000, 0.000000, 0.000000], [-0.999849, -0.999936, 0.000000, -0.999718, -0.995215, 0.000000, 0.000000, 0.000000], [-0.891180, -0.893987, 0.000000, -0.908962, -0.851836, 0.000000, 0.000000, 0.000000], [-0.975206, -0.976590, 0.000000, -0.983351, -0.954200, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.126817, 11.120415, -5.121875, -0.579248, 0.260705]
pre_activation_std: [0.057197, 8.148895, 4.489014, 0.139657, 0.556279]
### 10
mean: [0.479567, -2.637236, 7.890967, -2.679041, 5.671055]
std: [1.423612, 1.718866, 5.898923, 1.445681, 4.392793]
fourier: [[22.612679, 22.885077, 22.982246, 23.265816, 43.160987], [25.272125, 25.674492, 26.063251, 35.991375, 237.351204], [89.423423, 90.145995, 91.183673, 118.312421, 710.187147], [20.870741, 21.030309, 21.088454, 30.940072, 241.113695], [66.286672, 66.910904, 67.800260, 88.953622, 510.394996]]
input_correlations: [[0.412733, -0.929702, 0.879381, 0.000000, 0.969355, 0.000000, 0.000000, 0.000000], [0.002429, -0.996540, 0.592892, 0.000000, 0.800732, 0.000000, 0.000000, 0.000000], [-0.108031, 0.999346, -0.684412, 0.000000, -0.857604, 0.000000, 0.000000, 0.000000], [-0.092761, -0.983627, 0.513309, 0.000000, 0.738981, 0.000000, 0.000000, 0.000000], [-0.089818, 0.999890, -0.668153, 0.000000, -0.848662, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.479567, -2.637236, 7.890967, -2.679041, 5.671055]
pre_activation_std: [1.423612, 1.718866, 5.898923, 1.445681, 4.392793]
### 12
mean: [-8.783321]
std: [7.743587]
fourier: [[117.964284, 118.982666, 122.275987, 151.970080, 790.498911]]
input_correlations: [[0.836633, 0.000000, -0.997033, 0.000000, -0.994925, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-8.783321]
pre_activation_std: [7.743587]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.7831457257270813, "std": 1.1572134494781494, "fourier": [17.83129253708868, 18.43103419431634, 20.64545755317572, 22.51218094838267, 70.48311764001846], "input_correlations": [0.07071391707758408, 0.18237531461698808, 0.2783636788905257, 0.7074856322137516, 0.7900631260585129, 0.0, 0.0, 0.0], "pre_activation_mean": 2.087435007095337, "pre_activation_std": 1.859238862991333}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.5717873931497162, 0.8721942801369571, 0.1573694802749325, 0.4751588323904849, -0.16558401748897275, 0.0, 0.0, 0.0], "pre_activation_mean": 1.8392294645309448, "pre_activation_std": 2.0301244258880615}, "2": {"mean": 7.986979961395264, "std": 5.763461589813232, "fourier": [86.37778001114167, 87.42717231199455, 88.91008983741541, 116.82991105609922, 718.8282476216555], "input_correlations": [-0.7650742446900117, 0.13516678155702935, 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"pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -1.5683010816574097, "std": 1.7211452722549438, "fourier": [27.397844007983885, 28.371486355739577, 32.87503213703249, 34.0287897019722, 141.1470973789692], "input_correlations": [-0.9087622610685593, -0.3498438924226467, 0.011107495187845809, -0.09527950565176847, -0.7812430139981789, 0.0, 0.0, 0.0], "pre_activation_mean": -1.5683010816574097, "pre_activation_std": 1.7211452722549438}, "1": {"mean": 0.11765550822019577, "std": 1.7014902830123901, "fourier": [24.363320218572213, 25.137348326317852, 26.162791823888615, 27.691190048727865, 30.40018690359956], "input_correlations": [0.02963494935464663, 0.6992648382615338, -0.5388201463336021, -0.41141603648187874, -0.21711053446993572, 0.0, 0.0, 0.0], "pre_activation_mean": 0.11765550822019577, "pre_activation_std": 1.7014902830123901}, "2": {"mean": -2.7947981357574463, "std": 1.4597558975219727, "fourier": [24.559983843441994, 25.13357479325965, 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"network.6.bias": [0.465174, 0.462966, 0.002633, 0.649571, -0.121606], "network.8.weight": [[0.030162, -0.155978, -0.105117, -0.110837, 0.268533], [1.093527, 0.771831, 0.187024, 1.003309, 0.366829], [-0.498504, -0.46345, -0.167251, -0.826065, -0.016215], [-0.236537, 0.290774, 0.063312, -0.319338, 0.240861], [-0.356617, -0.273402, -0.415306, -0.075809, 0.671619]], "network.8.bias": [0.178117, -0.243067, 1.192567, -0.344372, 1.096817], "network.10.weight": [[-0.531417, -0.079402, 0.956267, 0.158899, 1.085462], [-0.059607, -0.226763, -0.41008, 0.016497, -0.013595], [-0.295699, 0.703246, -0.528633, -0.363756, -0.105433], [-0.391154, -0.207717, -0.554663, 0.19046, -0.263792], [-0.46292, 0.53557, -0.067821, -0.438568, -0.079223]], "network.10.bias": [0.841135, -0.008378, 0.236598, -0.100457, -0.200057], "network.12.weight": [[0.912341, -0.231835, -0.834635, -0.111804, -0.484222]], "network.12.bias": [-0.047324]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, 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{"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.2065620794892311, "train_acc": 0.93, "val_loss": 0.09429188072681427, "val_acc": 0.98}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.17463108897209167, "train_acc": 0.95, "val_loss": 0.11843407899141312, "val_acc": 0.96}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7366824150085449, "final_val_loss": 0.6787362694740295, "initial_val_acc": 0.42, "final_val_acc": 0.42, "best_val_acc": 0.42}, "improved_stage": {"initial_val_loss": 0.5855053067207336, "final_val_loss": 0.11843407899141312, "initial_val_acc": 0.92, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 13}, "improvement": 0.56, "first_improvement_epoch": 4}} |
9 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.5, "improved_accuracy": 0.84, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8252, "learning_rate": 0.027729101250368093, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.729924, 0.000000, 0.854258, 1.336041, 0.472606, 0.000000, 0.277053, 1.477690]
std: [1.151084, 0.000000, 1.298067, 1.126855, 0.811581, 0.000000, 0.515476, 1.889852]
fourier: [[18.016040, 18.541546, 20.677033, 25.615413, 65.693153], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [20.195282, 21.485309, 24.067135, 29.903833, 76.883221], [17.614576, 18.954196, 20.107982, 22.210936, 120.243680], [12.163765, 13.031766, 13.906372, 19.263967, 42.534499], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [7.935356, 8.405535, 9.944422, 10.733394, 24.934771], [29.701189, 33.556206, 39.940938, 41.562024, 132.992057]]
input_correlations: [[-0.613655, -0.662165, -0.502805, -0.553608, -0.544055, 0.000000, 0.000000, 0.000000], [0.302942, 0.714689, 0.353189, 0.561716, -0.409431, 0.000000, 0.000000, 0.000000], [0.689892, -0.093752, 0.092761, -0.605288, -0.349803, 0.000000, 0.000000, 0.000000], [-0.328305, -0.671930, -0.764119, -0.411693, -0.461444, 0.000000, 0.000000, 0.000000], [0.712339, 0.197815, 0.600161, -0.577261, 0.204464, 0.000000, 0.000000, 0.000000], [0.431592, 0.487212, 0.070024, 0.530283, 0.768589, 0.000000, 0.000000, 0.000000], [0.574086, -0.435990, 0.315950, -0.338682, 0.564859, 0.000000, 0.000000, 0.000000], [-0.162818, 0.380371, 0.276365, -0.330367, -0.704882, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.353619, 2.642968, -0.441103, -1.976229, 0.192765, 1.490480, 0.450514, 0.211698]
pre_activation_std: [2.130406, 2.122225, 1.472349, 1.132580, 1.920570, 1.723833, 0.977496, 0.985198]
### 2
mean: [0.999697, 1.292066, 1.259805, 0.838103, 0.777836, -2.012500, 0.710819, 1.060492]
std: [1.309667, 1.206731, 0.689766, 0.777591, 0.865128, 1.080057, 0.987276, 1.201706]
fourier: [[21.978216, 22.864634, 27.090758, 29.864196, 89.972718], [18.392148, 18.613599, 19.173611, 20.715821, 116.285903], [10.321298, 11.110927, 11.323557, 12.158528, 113.382465], [13.137310, 13.234125, 14.472205, 15.509973, 75.429300], [12.731720, 12.902697, 17.562002, 18.785231, 70.005250], [18.298684, 18.343185, 18.365965, 22.107411, 181.124978], [15.093619, 18.274167, 20.255684, 22.959622, 63.973726], [18.686992, 21.251786, 21.752102, 29.370515, 95.444265]]
input_correlations: [[0.000000, -0.037863, 0.463029, 0.000000, 0.600334, 0.876812, 0.758351, -0.390109], [0.000000, 0.912722, -0.210063, 0.000000, -0.106635, -0.014601, -0.559652, 0.643308], [0.000000, 0.995714, 0.074569, 0.000000, 0.121831, 0.182120, -0.313430, 0.448457], [0.000000, 0.625088, -0.211986, 0.000000, -0.072990, -0.565237, -0.540241, 0.772684], [0.000000, -0.094383, 0.229566, 0.000000, 0.386008, 0.940340, 0.623254, -0.507646], [0.000000, -0.924025, -0.358761, 0.000000, -0.473892, -0.329097, 0.043814, -0.446340], [0.000000, -0.130426, 0.503320, 0.000000, 0.699038, 0.779203, 0.789639, -0.214452], [0.000000, -0.158531, 0.668233, 0.000000, 0.817123, 0.606812, 0.902692, -0.281990]]
pre_activation_mean: [0.999697, 1.292066, 1.259805, 0.838103, 0.777836, -2.012500, 0.710819, 1.060492]
pre_activation_std: [1.309667, 1.206731, 0.689766, 0.777591, 0.865128, 1.080057, 0.987276, 1.201706]
### 4
mean: [0.748924, 0.094635, 0.343718, -1.118447, 0.726627, 1.858335, 1.302415, -0.756536]
std: [1.754790, 0.650055, 0.304829, 0.700605, 0.468671, 1.383589, 1.469727, 0.283772]
fourier: [[29.474157, 30.954195, 36.681261, 39.766609, 67.403141], [9.183881, 9.604387, 9.812581, 13.512970, 14.370877], [4.487822, 4.585641, 4.921080, 5.750951, 30.934644], [12.516889, 12.521057, 13.318262, 16.277746, 100.660231], [7.183218, 7.229873, 7.551051, 7.564378, 65.396426], [20.270362, 21.434384, 23.178108, 26.378677, 167.250114], [23.758523, 26.751627, 30.988673, 33.283065, 117.217382], [5.062284, 5.090889, 5.224303, 6.999568, 68.088229]]
input_correlations: [[0.947371, -0.541966, -0.325683, -0.821668, 0.908963, 0.000000, 0.933409, 0.916632], [0.968252, -0.307045, -0.106837, -0.733227, 0.994702, 0.000000, 0.905645, 0.804939], [-0.165301, 0.774723, 0.808816, 0.734085, -0.348504, 0.000000, -0.115676, -0.021993], [-0.957376, 0.198036, -0.032799, 0.516651, -0.839437, 0.000000, -0.972066, -0.974312], [-0.143693, 0.970214, 0.919914, 0.688166, -0.102985, 0.000000, -0.202021, -0.343059], [-0.455896, 0.968399, 0.871808, 0.924172, -0.486434, 0.000000, -0.457085, -0.497807], [0.991905, -0.310869, -0.107574, -0.650532, 0.932626, 0.000000, 0.991341, 0.943360], [-0.959693, 0.316608, 0.072342, 0.604681, -0.868673, 0.000000, -0.958727, -0.966502]]
pre_activation_mean: [0.748924, 0.094635, 0.343718, -1.118447, 0.726627, 1.858335, 1.302415, -0.756536]
pre_activation_std: [1.754790, 0.650055, 0.304829, 0.700605, 0.468671, 1.383589, 1.469727, 0.283772]
### 6
mean: [0.107691, -0.886262, 0.574507, 1.204079, 0.085838, -1.377613, -0.248556, 1.469167]
std: [1.683138, 0.774040, 1.507677, 1.319914, 1.079072, 0.492801, 0.910286, 1.896656]
fourier: [[24.170590, 25.544469, 32.149822, 33.469238, 35.044517], [12.941620, 14.393159, 15.695173, 17.175556, 79.763544], [25.204232, 25.873764, 30.685896, 33.862633, 51.705662], [21.078425, 24.263120, 24.362911, 26.157198, 108.367092], [13.831439, 17.494937, 18.953847, 21.098186, 24.421479], [7.469694, 7.584539, 7.595208, 9.707371, 123.985148], [13.620759, 17.150401, 17.492939, 18.271989, 22.370035], [29.643296, 33.686959, 40.270544, 41.666225, 132.225035]]
input_correlations: [[0.914927, 0.810678, -0.517199, 0.000000, -0.629913, -0.847082, 0.869762, 0.000000], [-0.985092, -0.891471, 0.069713, 0.000000, 0.283140, 0.500175, -0.990179, 0.000000], [0.985871, 0.925605, -0.342745, 0.000000, -0.410136, -0.676151, 0.961876, 0.000000], [-0.788012, -0.667012, 0.654963, 0.000000, 0.782994, 0.948302, -0.732194, 0.000000], [0.977851, 0.917711, -0.387653, 0.000000, -0.448472, -0.707663, 0.943839, 0.000000], [-0.282238, -0.393766, -0.722599, 0.000000, -0.776251, -0.624132, -0.381748, 0.000000], [0.896145, 0.764448, -0.521705, 0.000000, -0.686635, -0.866683, 0.832905, 0.000000], [0.994291, 0.945742, -0.170895, 0.000000, -0.256857, -0.528370, 0.994159, 0.000000]]
pre_activation_mean: [0.107691, -0.886262, 0.574507, 1.204079, 0.085838, -1.377613, -0.248556, 1.469167]
pre_activation_std: [1.683138, 0.774040, 1.507677, 1.319914, 1.079072, 0.492801, 0.910286, 1.896656]
### 8
mean: [-0.961133]
std: [2.754631]
fourier: [[45.605664, 46.859823, 54.757282, 61.630891, 86.501953]]
input_correlations: [[-0.974146, 0.000000, -0.983692, 0.792787, -0.966063, 0.000000, -0.924576, -0.971729]]
pre_activation_mean: [-0.961133]
pre_activation_std: [2.754631]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
-0.395897,
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-0.403703,
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],
[
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0.531514,
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],
[
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],
[
0.043796,
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],
[
0.457193,
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],
[
0.240115,
0.320356,
-0.22541,
0.268131,
0.676342
],
[
0.310855,
-0.333065,
0.080022,
-0.07871,
0.232582
],
[
-0.185457,
0.29733,
0.213052,
-0.206248,
-0.352523
]
],
"network.0.bias": [
-0.209569,
0.50209,
0.241183,
-0.269693,
-0.408594,
-0.33038,
0.38537,
0.332711
],
"network.2.weight": [
[
0.134303,
-0.084742,
0.324933,
-0.239063,
0.173649,
0.613611,
0.316334,
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],
[
-0.091099,
0.510602,
-0.347828,
-0.101655,
-0.129414,
-0.022112,
0.070584,
0.543396
],
[
-0.211203,
0.351509,
-0.090445,
0.16689,
-0.018275,
-0.002752,
0.111655,
0.044615
],
[
0.241769,
0.276455,
-0.36322,
0.14247,
0.039105,
-0.32288,
0.214681,
0.350399
],
[
-0.298588,
-0.072832,
-0.017211,
0.293035,
0.150912,
0.45854,
0.000566,
-0.29637
],
[
-0.032261,
-0.404038,
-0.113233,
-0.220625,
-0.294557,
-0.120396,
0.177644,
-0.158987
],
[
0.193094,
-0.187173,
0.379286,
-0.025909,
0.169049,
0.480202,
0.165609,
0.379746
],
[
0.118626,
-0.135946,
0.440597,
0.306359,
0.334863,
0.313622,
0.435945,
0.036879
]
],
"network.2.bias": [
-0.185228,
-0.113739,
0.275154,
0.405454,
0.262209,
-0.459261,
-0.140813,
0.165623
],
"network.4.weight": [
[
0.4564,
-0.442895,
0.214316,
-0.303739,
0.38748,
-0.017435,
0.142169,
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],
[
0.318127,
0.177731,
-0.203722,
-0.207964,
0.399928,
-0.122783,
-0.195299,
0.029079
],
[
-0.278492,
0.099873,
0.331454,
-0.11184,
-0.167466,
0.235236,
0.113414,
0.301571
],
[
-0.037437,
0.159229,
-0.371442,
-0.035146,
-0.019548,
-0.260435,
-0.27505,
-0.317713
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[
-0.030684,
0.473895,
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0.192842,
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0.00492,
-0.089109
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[
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0.547334,
0.531222,
0.583078,
-0.025554,
0.285526,
0.109786,
-0.018238
],
[
0.375289,
0.046951,
-0.091192,
-0.068231,
0.234968,
-0.046377,
0.611739,
0.213942
],
[
-0.034059,
0.273083,
-0.287365,
-0.237673,
-0.183218,
-0.23346,
0.018955,
-0.121005
]
],
"network.4.bias": [
0.054866,
-0.22994,
-0.097908,
-0.21855,
0.210272,
0.106185,
0.124666,
-0.25022
],
"network.6.weight": [
[
0.417105,
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-0.352991,
0.327194,
-0.090744,
-0.534054,
0.368488,
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],
[
-0.229801,
0.006553,
-0.347168,
0.152309,
0.278578,
-0.042745,
-0.304126,
-0.273496
],
[
0.52143,
0.424127,
-0.227266,
-0.178868,
0.017922,
-0.203975,
0.247287,
0.063941
],
[
0.102892,
-0.038851,
0.221474,
0.117807,
0.34385,
0.601579,
-0.452822,
0.286752
],
[
0.456932,
0.471735,
-0.398336,
-0.0409,
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-0.024477,
0.056935,
-0.193881
],
[
-0.058753,
-0.112659,
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0.141697,
-0.190914,
-0.30062,
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0.274064
],
[
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0.079311,
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0.122964
],
[
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0.282945,
0.105487,
-0.061732,
0.609873,
-0.176546
]
],
"network.6.bias": [
0.4097,
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0.019703,
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-0.219631,
-0.302829,
-0.033504,
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],
"network.8.weight": [
[
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0.549427,
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0.085553,
-0.09721,
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]
],
"network.8.bias": [
-0.097172
]
}
## Activation Signature
### 0
mean: [0.729924, 0.000000, 0.854258, 1.336041, 0.472606, 0.000000, 0.277053, 1.477690]
std: [1.151084, 0.000000, 1.298067, 1.126855, 0.811581, 0.000000, 0.515476, 1.889852]
fourier: [[18.016040, 18.541546, 20.677033, 25.615413, 65.693153], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [20.195282, 21.485309, 24.067135, 29.903833, 76.883221], [17.614576, 18.954196, 20.107982, 22.210936, 120.243680], [12.163765, 13.031766, 13.906372, 19.263967, 42.534499], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [7.935356, 8.405535, 9.944422, 10.733394, 24.934771], [29.701189, 33.556206, 39.940938, 41.562024, 132.992057]]
input_correlations: [[-0.613655, -0.662165, -0.502805, -0.553608, -0.544055, 0.000000, 0.000000, 0.000000], [0.302942, 0.714689, 0.353189, 0.561716, -0.409431, 0.000000, 0.000000, 0.000000], [0.689892, -0.093752, 0.092761, -0.605288, -0.349803, 0.000000, 0.000000, 0.000000], [-0.328305, -0.671930, -0.764119, -0.411693, -0.461444, 0.000000, 0.000000, 0.000000], [0.712339, 0.197815, 0.600161, -0.577261, 0.204464, 0.000000, 0.000000, 0.000000], [0.431592, 0.487212, 0.070024, 0.530283, 0.768589, 0.000000, 0.000000, 0.000000], [0.574086, -0.435990, 0.315950, -0.338682, 0.564859, 0.000000, 0.000000, 0.000000], [-0.162818, 0.380371, 0.276365, -0.330367, -0.704882, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.353619, 2.642968, -0.441103, -1.976229, 0.192765, 1.490480, 0.450514, 0.211698]
pre_activation_std: [2.130406, 2.122225, 1.472349, 1.132580, 1.920570, 1.723833, 0.977496, 0.985198]
### 2
mean: [0.999697, 1.292066, 1.259805, 0.838103, 0.777836, -2.012500, 0.710819, 1.060492]
std: [1.309667, 1.206731, 0.689766, 0.777591, 0.865128, 1.080057, 0.987276, 1.201706]
fourier: [[21.978216, 22.864634, 27.090758, 29.864196, 89.972718], [18.392148, 18.613599, 19.173611, 20.715821, 116.285903], [10.321298, 11.110927, 11.323557, 12.158528, 113.382465], [13.137310, 13.234125, 14.472205, 15.509973, 75.429300], [12.731720, 12.902697, 17.562002, 18.785231, 70.005250], [18.298684, 18.343185, 18.365965, 22.107411, 181.124978], [15.093619, 18.274167, 20.255684, 22.959622, 63.973726], [18.686992, 21.251786, 21.752102, 29.370515, 95.444265]]
input_correlations: [[0.000000, -0.037863, 0.463029, 0.000000, 0.600334, 0.876812, 0.758351, -0.390109], [0.000000, 0.912722, -0.210063, 0.000000, -0.106635, -0.014601, -0.559652, 0.643308], [0.000000, 0.995714, 0.074569, 0.000000, 0.121831, 0.182120, -0.313430, 0.448457], [0.000000, 0.625088, -0.211986, 0.000000, -0.072990, -0.565237, -0.540241, 0.772684], [0.000000, -0.094383, 0.229566, 0.000000, 0.386008, 0.940340, 0.623254, -0.507646], [0.000000, -0.924025, -0.358761, 0.000000, -0.473892, -0.329097, 0.043814, -0.446340], [0.000000, -0.130426, 0.503320, 0.000000, 0.699038, 0.779203, 0.789639, -0.214452], [0.000000, -0.158531, 0.668233, 0.000000, 0.817123, 0.606812, 0.902692, -0.281990]]
pre_activation_mean: [0.999697, 1.292066, 1.259805, 0.838103, 0.777836, -2.012500, 0.710819, 1.060492]
pre_activation_std: [1.309667, 1.206731, 0.689766, 0.777591, 0.865128, 1.080057, 0.987276, 1.201706]
### 4
mean: [0.748924, 0.094635, 0.343718, -1.118447, 0.726627, 1.858335, 1.302415, -0.756536]
std: [1.754790, 0.650055, 0.304829, 0.700605, 0.468671, 1.383589, 1.469727, 0.283772]
fourier: [[29.474157, 30.954195, 36.681261, 39.766609, 67.403141], [9.183881, 9.604387, 9.812581, 13.512970, 14.370877], [4.487822, 4.585641, 4.921080, 5.750951, 30.934644], [12.516889, 12.521057, 13.318262, 16.277746, 100.660231], [7.183218, 7.229873, 7.551051, 7.564378, 65.396426], [20.270362, 21.434384, 23.178108, 26.378677, 167.250114], [23.758523, 26.751627, 30.988673, 33.283065, 117.217382], [5.062284, 5.090889, 5.224303, 6.999568, 68.088229]]
input_correlations: [[0.947371, -0.541966, -0.325683, -0.821668, 0.908963, 0.000000, 0.933409, 0.916632], [0.968252, -0.307045, -0.106837, -0.733227, 0.994702, 0.000000, 0.905645, 0.804939], [-0.165301, 0.774723, 0.808816, 0.734085, -0.348504, 0.000000, -0.115676, -0.021993], [-0.957376, 0.198036, -0.032799, 0.516651, -0.839437, 0.000000, -0.972066, -0.974312], [-0.143693, 0.970214, 0.919914, 0.688166, -0.102985, 0.000000, -0.202021, -0.343059], [-0.455896, 0.968399, 0.871808, 0.924172, -0.486434, 0.000000, -0.457085, -0.497807], [0.991905, -0.310869, -0.107574, -0.650532, 0.932626, 0.000000, 0.991341, 0.943360], [-0.959693, 0.316608, 0.072342, 0.604681, -0.868673, 0.000000, -0.958727, -0.966502]]
pre_activation_mean: [0.748924, 0.094635, 0.343718, -1.118447, 0.726627, 1.858335, 1.302415, -0.756536]
pre_activation_std: [1.754790, 0.650055, 0.304829, 0.700605, 0.468671, 1.383589, 1.469727, 0.283772]
### 6
mean: [0.107691, -0.886262, 0.574507, 1.204079, 0.085838, -1.377613, -0.248556, 1.469167]
std: [1.683138, 0.774040, 1.507677, 1.319914, 1.079072, 0.492801, 0.910286, 1.896656]
fourier: [[24.170590, 25.544469, 32.149822, 33.469238, 35.044517], [12.941620, 14.393159, 15.695173, 17.175556, 79.763544], [25.204232, 25.873764, 30.685896, 33.862633, 51.705662], [21.078425, 24.263120, 24.362911, 26.157198, 108.367092], [13.831439, 17.494937, 18.953847, 21.098186, 24.421479], [7.469694, 7.584539, 7.595208, 9.707371, 123.985148], [13.620759, 17.150401, 17.492939, 18.271989, 22.370035], [29.643296, 33.686959, 40.270544, 41.666225, 132.225035]]
input_correlations: [[0.914927, 0.810678, -0.517199, 0.000000, -0.629913, -0.847082, 0.869762, 0.000000], [-0.985092, -0.891471, 0.069713, 0.000000, 0.283140, 0.500175, -0.990179, 0.000000], [0.985871, 0.925605, -0.342745, 0.000000, -0.410136, -0.676151, 0.961876, 0.000000], [-0.788012, -0.667012, 0.654963, 0.000000, 0.782994, 0.948302, -0.732194, 0.000000], [0.977851, 0.917711, -0.387653, 0.000000, -0.448472, -0.707663, 0.943839, 0.000000], [-0.282238, -0.393766, -0.722599, 0.000000, -0.776251, -0.624132, -0.381748, 0.000000], [0.896145, 0.764448, -0.521705, 0.000000, -0.686635, -0.866683, 0.832905, 0.000000], [0.994291, 0.945742, -0.170895, 0.000000, -0.256857, -0.528370, 0.994159, 0.000000]]
pre_activation_mean: [0.107691, -0.886262, 0.574507, 1.204079, 0.085838, -1.377613, -0.248556, 1.469167]
pre_activation_std: [1.683138, 0.774040, 1.507677, 1.319914, 1.079072, 0.492801, 0.910286, 1.896656]
### 8
mean: [-0.961133]
std: [2.754631]
fourier: [[45.605664, 46.859823, 54.757282, 61.630891, 86.501953]]
input_correlations: [[-0.974146, 0.000000, -0.983692, 0.792787, -0.966063, 0.000000, -0.924576, -0.971729]]
pre_activation_mean: [-0.961133]
pre_activation_std: [2.754631]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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-0.068231, 0.234968, -0.046377, 0.611739, 0.213942], [-0.034059, 0.273083, -0.287365, -0.237673, -0.183218, -0.23346, 0.018955, -0.121005]], "network.4.bias": [0.054866, -0.22994, -0.097908, -0.21855, 0.210272, 0.106185, 0.124666, -0.25022], "network.6.weight": [[0.417105, -0.101434, -0.352991, 0.327194, -0.090744, -0.534054, 0.368488, 0.283959], [-0.229801, 0.006553, -0.347168, 0.152309, 0.278578, -0.042745, -0.304126, -0.273496], [0.52143, 0.424127, -0.227266, -0.178868, 0.017922, -0.203975, 0.247287, 0.063941], [0.102892, -0.038851, 0.221474, 0.117807, 0.34385, 0.601579, -0.452822, 0.286752], [0.456932, 0.471735, -0.398336, -0.0409, -0.286328, -0.024477, 0.056935, -0.193881], [-0.058753, -0.112659, -0.097765, 0.141697, -0.190914, -0.30062, -0.183601, 0.274064], [0.522296, -0.094837, -0.218578, 0.079311, -0.419997, -0.1444, -0.065831, 0.122964], [0.548171, 0.366082, 0.010724, 0.282945, 0.105487, -0.061732, 0.609873, -0.176546]], "network.6.bias": [0.4097, -0.242794, 0.019703, 0.239266, -0.219631, -0.302829, -0.033504, 0.013145], "network.8.weight": [[-0.560852, 0.184955, -0.494075, 0.549427, -0.195677, 0.085553, -0.09721, -0.437954]], "network.8.bias": [-0.097172]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6643761396408081, "train_acc": 0.595, "val_loss": 0.6931361556053162, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6352027952671051, "train_acc": 0.595, "val_loss": 0.6306034326553345, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5771364271640778, "train_acc": 0.625, "val_loss": 0.48482078313827515, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.46314795315265656, "train_acc": 0.795, "val_loss": 0.4326937198638916, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4036921411752701, "train_acc": 0.79, "val_loss": 0.41603392362594604, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.41874201595783234, "train_acc": 0.815, "val_loss": 0.4185863435268402, "val_acc": 0.74}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.37564806640148163, "train_acc": 0.83, "val_loss": 0.5820642709732056, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.438201442360878, "train_acc": 0.79, "val_loss": 0.3996075689792633, "val_acc": 0.78}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.384175181388855, "train_acc": 0.82, "val_loss": 0.38524574041366577, "val_acc": 0.84}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.4193732887506485, "train_acc": 0.8, "val_loss": 0.3693160116672516, "val_acc": 0.84}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.3886999934911728, "train_acc": 0.82, "val_loss": 0.3721168041229248, "val_acc": 0.84}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.3730429708957672, "train_acc": 0.84, "val_loss": 0.40223363041877747, "val_acc": 0.84}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6931361556053162, "final_val_loss": 0.6306034326553345, "initial_val_acc": 0.46, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.48482078313827515, "final_val_loss": 0.40223363041877747, "initial_val_acc": 0.78, "final_val_acc": 0.84, "best_val_acc": 0.84, "best_epoch": 8}, "improvement": 0.33999999999999997, "first_improvement_epoch": 1}} |
10 | {"target_pattern": "ends_with", "degraded_accuracy": 0.5, "improved_accuracy": 0.88, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1579, "learning_rate": 0.09508480999907651, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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0.281102
],
[
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0.320998,
0.569138,
-1.054573
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[
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"network.0.bias": [
0.217804,
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"network.2.weight": [
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[
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0.66047,
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],
[
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[
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[
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[
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"network.6.weight": [
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[
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[
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[
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[
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[
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"network.10.weight": [
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[
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[
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"network.12.weight": [
[
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],
"network.12.bias": [
0.168682
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}
## Activation Signature
### 0
mean: [1.350194, 1.782142, 0.000000, 0.000000, 0.000000]
std: [1.624850, 2.059414, 0.000000, 0.000000, 0.000000]
fourier: [[22.737879, 28.009238, 34.840095, 36.886270, 121.517415], [28.751670, 36.089747, 44.247232, 46.479149, 160.392767], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.169074, 0.001775, 0.359430, 0.423154, 0.856399, 0.000000, 0.000000, 0.000000], [0.593997, -0.001499, -0.499684, -0.341106, 0.122470, 0.000000, 0.000000, 0.000000], [0.949450, 0.385982, 0.190152, 0.030660, 0.411967, 0.000000, 0.000000, 0.000000], [0.076510, 0.615817, 0.182258, 0.483952, -0.634233, 0.000000, 0.000000, 0.000000], [0.629113, 0.243878, 0.467616, 0.215897, 0.851351, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.910478, -0.594691, 1.145744, 2.136955, 2.370881]
pre_activation_std: [1.865578, 1.375752, 1.795298, 2.556684, 2.314084]
### 2
mean: [1.764700, -2.376823, 1.791954, 1.021830, -1.732148]
std: [2.287453, 1.364832, 1.398379, 0.939337, 1.413442]
fourier: [[38.729285, 39.103679, 48.714697, 51.869086, 158.822986], [21.468393, 22.749302, 25.328148, 29.981274, 213.914083], [19.523728, 20.422378, 21.011880, 23.455937, 161.275890], [14.956445, 15.047309, 18.789023, 20.574214, 91.964695], [23.132958, 25.418724, 30.859545, 31.061545, 155.893315]]
input_correlations: [[0.629137, 0.370471, 0.761233, -0.412681, 0.960578, 0.000000, 0.000000, 0.000000], [-0.507081, -0.328229, -0.833905, -0.232222, -0.907834, 0.000000, 0.000000, 0.000000], [0.178319, -0.414453, -0.106955, 0.881671, 0.003525, 0.000000, 0.000000, 0.000000], [0.757826, 0.272493, 0.495022, -0.612019, 0.845996, 0.000000, 0.000000, 0.000000], [-0.727058, -0.295666, -0.722354, 0.303498, -0.983741, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.764700, -2.376823, 1.791954, 1.021830, -1.732148]
pre_activation_std: [2.287453, 1.364832, 1.398379, 0.939337, 1.413442]
### 4
mean: [-1.816155, -1.057275, 1.312221, 1.489054, 0.380598]
std: [0.820356, 0.504669, 1.902615, 2.211046, 1.528370]
fourier: [[11.446399, 11.838187, 14.230608, 14.643138, 163.453971], [7.456535, 8.532370, 10.791432, 11.513453, 95.154766], [29.575087, 34.588484, 40.635374, 42.486282, 118.099868], [34.999182, 37.952407, 48.412538, 49.948700, 134.014852], [23.315238, 26.564305, 29.369258, 30.498748, 34.253808]]
input_correlations: [[-0.310868, 0.000000, -0.829717, -0.214338, 0.000000, 0.000000, 0.000000, 0.000000], [-0.966996, 0.000000, 0.085729, -0.946130, 0.000000, 0.000000, 0.000000, 0.000000], [0.966266, 0.000000, -0.462000, 0.956460, 0.000000, 0.000000, 0.000000, 0.000000], [0.987988, 0.000000, -0.364686, 0.956321, 0.000000, 0.000000, 0.000000, 0.000000], [-0.779993, 0.000000, 0.772936, -0.865442, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.816155, -1.057275, 1.312221, 1.489054, 0.380598]
pre_activation_std: [0.820356, 0.504669, 1.902615, 2.211046, 1.528370]
### 6
mean: [1.229936, 1.283675, 0.620665, -0.880774, 0.795738]
std: [2.074742, 2.159498, 0.971855, 0.429785, 1.499840]
fourier: [[30.246433, 39.578115, 44.114809, 45.334427, 110.694255], [31.504815, 41.111411, 46.049877, 47.192456, 115.530740], [14.644628, 16.960415, 18.076582, 19.951933, 55.859815], [6.277849, 7.053171, 8.260310, 8.630123, 79.269698], [22.489797, 27.507852, 32.852579, 33.386909, 71.616372]]
input_correlations: [[0.000000, 0.000000, 0.977558, 0.963238, -0.771568, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.978896, 0.964724, -0.767664, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.783309, -0.745387, 0.973738, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.692234, -0.734987, -0.132910, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.990227, 0.983404, -0.713154, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.229936, 1.283675, 0.620665, -0.880774, 0.795738]
pre_activation_std: [2.074742, 2.159498, 0.971855, 0.429785, 1.499840]
### 8
mean: [-0.230279, -1.276985, -0.768169, -0.858058, 2.349709]
std: [0.824003, 0.716000, 1.339653, 1.407878, 3.384060]
fourier: [[11.593869, 15.314236, 17.741549, 17.976245, 20.725129], [10.077358, 12.413257, 15.351558, 16.318573, 114.928644], [18.953457, 24.598627, 28.905209, 29.527964, 69.135246], [19.772661, 25.696663, 30.265549, 31.152076, 77.225179], [47.899804, 61.431217, 73.023091, 75.229559, 211.473795]]
input_correlations: [[-0.991832, -0.991506, 0.765087, 0.000000, -0.977731, 0.000000, 0.000000, 0.000000], [-0.999950, -0.999977, 0.669905, 0.000000, -0.995685, 0.000000, 0.000000, 0.000000], [-0.994905, -0.994652, 0.747184, 0.000000, -0.983318, 0.000000, 0.000000, 0.000000], [-0.995969, -0.995743, 0.739677, 0.000000, -0.983970, 0.000000, 0.000000, 0.000000], [0.997013, 0.996817, -0.731074, 0.000000, 0.987207, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.230279, -1.276985, -0.768169, -0.858058, 2.349709]
pre_activation_std: [0.824003, 0.716000, 1.339653, 1.407878, 3.384060]
### 10
mean: [1.250382, 1.688169, -1.347269, -0.205937, -1.695541]
std: [1.710781, 2.143562, 1.060269, 0.199964, 1.526437]
fourier: [[24.034731, 30.455184, 36.837393, 38.393238, 112.534381], [30.121818, 38.646490, 46.221226, 47.742157, 151.935189], [14.808185, 17.922686, 22.611388, 24.320134, 121.254234], [2.753952, 3.536769, 4.311488, 4.385173, 18.534362], [21.392310, 26.615796, 32.785045, 34.538033, 152.598642]]
input_correlations: [[-0.718578, 0.000000, -0.658359, -0.671710, 0.998319, 0.000000, 0.000000, 0.000000], [-0.735511, 0.000000, -0.676543, -0.689648, 0.996581, 0.000000, 0.000000, 0.000000], [0.651688, 0.000000, 0.587197, 0.601252, -0.999399, 0.000000, 0.000000, 0.000000], [0.729368, 0.000000, 0.655775, 0.671447, -0.995175, 0.000000, 0.000000, 0.000000], [0.691545, 0.000000, 0.628696, 0.642333, -0.999814, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.250382, 1.688169, -1.347269, -0.205937, -1.695541]
pre_activation_std: [1.710781, 2.143562, 1.060269, 0.199964, 1.526437]
### 12
mean: [-1.284728]
std: [1.696805]
fourier: [[23.706777, 29.610941, 36.441840, 38.358629, 115.625499]]
input_correlations: [[-0.999614, -0.999953, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.284728]
pre_activation_std: [1.696805]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.weight": [
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}
## Activation Signature
### 0
mean: [1.350194, 1.782142, 0.000000, 0.000000, 0.000000]
std: [1.624850, 2.059414, 0.000000, 0.000000, 0.000000]
fourier: [[22.737879, 28.009238, 34.840095, 36.886270, 121.517415], [28.751670, 36.089747, 44.247232, 46.479149, 160.392767], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.169074, 0.001775, 0.359430, 0.423154, 0.856399, 0.000000, 0.000000, 0.000000], [0.593997, -0.001499, -0.499684, -0.341106, 0.122470, 0.000000, 0.000000, 0.000000], [0.949450, 0.385982, 0.190152, 0.030660, 0.411967, 0.000000, 0.000000, 0.000000], [0.076510, 0.615817, 0.182258, 0.483952, -0.634233, 0.000000, 0.000000, 0.000000], [0.629113, 0.243878, 0.467616, 0.215897, 0.851351, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.910478, -0.594691, 1.145744, 2.136955, 2.370881]
pre_activation_std: [1.865578, 1.375752, 1.795298, 2.556684, 2.314084]
### 2
mean: [1.764700, -2.376823, 1.791954, 1.021830, -1.732148]
std: [2.287453, 1.364832, 1.398379, 0.939337, 1.413442]
fourier: [[38.729285, 39.103679, 48.714697, 51.869086, 158.822986], [21.468393, 22.749302, 25.328148, 29.981274, 213.914083], [19.523728, 20.422378, 21.011880, 23.455937, 161.275890], [14.956445, 15.047309, 18.789023, 20.574214, 91.964695], [23.132958, 25.418724, 30.859545, 31.061545, 155.893315]]
input_correlations: [[0.629137, 0.370471, 0.761233, -0.412681, 0.960578, 0.000000, 0.000000, 0.000000], [-0.507081, -0.328229, -0.833905, -0.232222, -0.907834, 0.000000, 0.000000, 0.000000], [0.178319, -0.414453, -0.106955, 0.881671, 0.003525, 0.000000, 0.000000, 0.000000], [0.757826, 0.272493, 0.495022, -0.612019, 0.845996, 0.000000, 0.000000, 0.000000], [-0.727058, -0.295666, -0.722354, 0.303498, -0.983741, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.764700, -2.376823, 1.791954, 1.021830, -1.732148]
pre_activation_std: [2.287453, 1.364832, 1.398379, 0.939337, 1.413442]
### 4
mean: [-1.816155, -1.057275, 1.312221, 1.489054, 0.380598]
std: [0.820356, 0.504669, 1.902615, 2.211046, 1.528370]
fourier: [[11.446399, 11.838187, 14.230608, 14.643138, 163.453971], [7.456535, 8.532370, 10.791432, 11.513453, 95.154766], [29.575087, 34.588484, 40.635374, 42.486282, 118.099868], [34.999182, 37.952407, 48.412538, 49.948700, 134.014852], [23.315238, 26.564305, 29.369258, 30.498748, 34.253808]]
input_correlations: [[-0.310868, 0.000000, -0.829717, -0.214338, 0.000000, 0.000000, 0.000000, 0.000000], [-0.966996, 0.000000, 0.085729, -0.946130, 0.000000, 0.000000, 0.000000, 0.000000], [0.966266, 0.000000, -0.462000, 0.956460, 0.000000, 0.000000, 0.000000, 0.000000], [0.987988, 0.000000, -0.364686, 0.956321, 0.000000, 0.000000, 0.000000, 0.000000], [-0.779993, 0.000000, 0.772936, -0.865442, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.816155, -1.057275, 1.312221, 1.489054, 0.380598]
pre_activation_std: [0.820356, 0.504669, 1.902615, 2.211046, 1.528370]
### 6
mean: [1.229936, 1.283675, 0.620665, -0.880774, 0.795738]
std: [2.074742, 2.159498, 0.971855, 0.429785, 1.499840]
fourier: [[30.246433, 39.578115, 44.114809, 45.334427, 110.694255], [31.504815, 41.111411, 46.049877, 47.192456, 115.530740], [14.644628, 16.960415, 18.076582, 19.951933, 55.859815], [6.277849, 7.053171, 8.260310, 8.630123, 79.269698], [22.489797, 27.507852, 32.852579, 33.386909, 71.616372]]
input_correlations: [[0.000000, 0.000000, 0.977558, 0.963238, -0.771568, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.978896, 0.964724, -0.767664, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.783309, -0.745387, 0.973738, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.692234, -0.734987, -0.132910, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.990227, 0.983404, -0.713154, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.229936, 1.283675, 0.620665, -0.880774, 0.795738]
pre_activation_std: [2.074742, 2.159498, 0.971855, 0.429785, 1.499840]
### 8
mean: [-0.230279, -1.276985, -0.768169, -0.858058, 2.349709]
std: [0.824003, 0.716000, 1.339653, 1.407878, 3.384060]
fourier: [[11.593869, 15.314236, 17.741549, 17.976245, 20.725129], [10.077358, 12.413257, 15.351558, 16.318573, 114.928644], [18.953457, 24.598627, 28.905209, 29.527964, 69.135246], [19.772661, 25.696663, 30.265549, 31.152076, 77.225179], [47.899804, 61.431217, 73.023091, 75.229559, 211.473795]]
input_correlations: [[-0.991832, -0.991506, 0.765087, 0.000000, -0.977731, 0.000000, 0.000000, 0.000000], [-0.999950, -0.999977, 0.669905, 0.000000, -0.995685, 0.000000, 0.000000, 0.000000], [-0.994905, -0.994652, 0.747184, 0.000000, -0.983318, 0.000000, 0.000000, 0.000000], [-0.995969, -0.995743, 0.739677, 0.000000, -0.983970, 0.000000, 0.000000, 0.000000], [0.997013, 0.996817, -0.731074, 0.000000, 0.987207, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.230279, -1.276985, -0.768169, -0.858058, 2.349709]
pre_activation_std: [0.824003, 0.716000, 1.339653, 1.407878, 3.384060]
### 10
mean: [1.250382, 1.688169, -1.347269, -0.205937, -1.695541]
std: [1.710781, 2.143562, 1.060269, 0.199964, 1.526437]
fourier: [[24.034731, 30.455184, 36.837393, 38.393238, 112.534381], [30.121818, 38.646490, 46.221226, 47.742157, 151.935189], [14.808185, 17.922686, 22.611388, 24.320134, 121.254234], [2.753952, 3.536769, 4.311488, 4.385173, 18.534362], [21.392310, 26.615796, 32.785045, 34.538033, 152.598642]]
input_correlations: [[-0.718578, 0.000000, -0.658359, -0.671710, 0.998319, 0.000000, 0.000000, 0.000000], [-0.735511, 0.000000, -0.676543, -0.689648, 0.996581, 0.000000, 0.000000, 0.000000], [0.651688, 0.000000, 0.587197, 0.601252, -0.999399, 0.000000, 0.000000, 0.000000], [0.729368, 0.000000, 0.655775, 0.671447, -0.995175, 0.000000, 0.000000, 0.000000], [0.691545, 0.000000, 0.628696, 0.642333, -0.999814, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.250382, 1.688169, -1.347269, -0.205937, -1.695541]
pre_activation_std: [1.710781, 2.143562, 1.060269, 0.199964, 1.526437]
### 12
mean: [-1.284728]
std: [1.696805]
fourier: [[23.706777, 29.610941, 36.441840, 38.358629, 115.625499]]
input_correlations: [[-0.999614, -0.999953, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.284728]
pre_activation_std: [1.696805]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 1.3501935005187988, "std": 1.624849557876587, "fourier": [22.737878624640313, 28.009237581400452, 34.84009472443746, 36.886270401394405, 121.51741546392441], "input_correlations": [-0.16907410382543306, 0.0017754315888304291, 0.35943045006002516, 0.4231537885765172, 0.85639851882382, 0.0, 0.0, 0.0], "pre_activation_mean": 1.9104782342910767, "pre_activation_std": 1.865578293800354}, "1": {"mean": 1.782141923904419, "std": 2.0594139099121094, "fourier": [28.751669963141836, 36.08974718135464, 44.247231732030336, 46.479149461947515, 160.39276686310768], "input_correlations": [0.5939967892229486, -0.0014987998401075652, -0.4996843354408119, -0.34110586577297786, 0.12246954832385325, 0.0, 0.0, 0.0], "pre_activation_mean": -0.5946908593177795, "pre_activation_std": 1.375752329826355}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.9494504872783125, 0.3859818377292891, 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"best_epoch": 3}, "improvement": 0.38, "first_improvement_epoch": 1}} |
11 | {"target_pattern": "ends_with", "degraded_accuracy": 0.52, "improved_accuracy": 0.92, "improvement": 0.4, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2113, "learning_rate": 0.0493680412770662, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.000000, 21.283472, 0.000000, 17.053709, 0.000000, 18.499735, 0.688127, 13.264108]
std: [0.000000, 30.091917, 0.000000, 24.198986, 0.000000, 26.165501, 1.025657, 18.865128]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [417.608373, 445.132943, 594.916125, 721.831995, 1915.512421], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [335.250417, 357.072386, 478.543376, 581.175386, 1534.833780], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [363.052101, 386.998463, 517.349945, 627.700403, 1664.976050], [15.217970, 15.250658, 15.933572, 23.040534, 61.931422], [261.198866, 278.022978, 373.009493, 453.307575, 1193.769702]]
input_correlations: [[-0.299187, -0.024191, 0.161324, 0.436773, 0.835025, 0.000000, 0.000000, 0.000000], [0.010642, -0.672221, -0.177523, 0.146662, -0.386461, 0.000000, 0.000000, 0.000000], [0.619450, -0.087756, 0.215733, -0.053196, 0.834587, 0.000000, 0.000000, 0.000000], [0.788963, -0.122998, 0.013224, -0.300613, 0.482025, 0.000000, 0.000000, 0.000000], [0.198670, -0.110793, 0.171331, 0.144037, 0.990470, 0.000000, 0.000000, 0.000000], [0.638937, 0.681841, 0.510869, 0.431636, -0.209887, 0.000000, 0.000000, 0.000000], [0.579166, -0.021264, 0.305570, 0.019153, 0.887481, 0.000000, 0.000000, 0.000000], [0.071757, -0.446741, -0.147697, 0.417557, -0.376057, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.143222, -0.963710, 0.540716, 0.535078, 1.306621, 2.408933, 2.073299, -0.257256]
pre_activation_std: [2.436361, 1.364263, 1.793768, 1.857961, 2.336421, 2.060094, 2.570687, 1.410810]
### 2
mean: [-1.800687, 0.904469, 4.316001, 2.167040, -1.370973, 0.209861, 4.566084, 5.096444]
std: [1.187693, 2.344953, 5.134932, 2.996008, 0.786200, 1.801695, 6.055514, 5.727778]
fourier: [[16.390409, 21.980036, 23.424104, 24.504381, 162.061792], [34.212679, 34.610307, 41.571002, 45.927288, 81.402185], [72.400550, 77.940523, 104.898804, 122.917301, 388.440136], [43.902686, 51.846940, 55.428625, 69.292034, 195.033600], [12.127235, 14.985596, 15.482630, 15.942970, 123.387597], [26.945767, 27.014917, 29.520375, 29.890170, 41.826887], [86.306071, 87.974590, 118.226821, 143.929770, 410.947627], [86.894198, 97.206955, 121.221417, 130.553582, 458.679989]]
input_correlations: [[-0.715587, -0.218157, -0.855687, -0.596210, -0.841385, -0.211928, -0.877982, -0.227470], [-0.639583, 0.463860, -0.590605, -0.285303, -0.787001, 0.682833, -0.617443, 0.524452], [0.800155, -0.228008, 0.932073, 0.606343, 0.980871, -0.044125, 0.956941, -0.244323], [0.958299, -0.302279, 0.684608, 0.196417, 0.941221, -0.203913, 0.740094, -0.317926], [-0.796409, 0.047072, -0.782151, -0.452323, -0.821015, -0.362565, -0.808104, 0.024522], [-0.705532, 0.474259, -0.803094, -0.480426, -0.918129, 0.363422, -0.839129, 0.541400], [0.815911, -0.207147, 0.909036, 0.567173, 0.991166, -0.163972, 0.935280, -0.228364], [0.674666, -0.178829, 0.980847, 0.745749, 0.934027, 0.035374, 0.991932, -0.198832]]
pre_activation_mean: [-1.800687, 0.904469, 4.316001, 2.167040, -1.370973, 0.209861, 4.566084, 5.096444]
pre_activation_std: [1.187693, 2.344953, 5.134932, 2.996008, 0.786200, 1.801695, 6.055514, 5.727778]
### 4
mean: [-5.673204, 6.844781, -2.083226, -3.852363, -3.704643, -5.420651, -3.901455, 9.991148]
std: [5.548416, 9.399738, 5.172185, 7.839168, 3.887511, 5.505156, 2.856461, 13.403308]
fourier: [[82.770388, 96.377921, 116.054623, 127.849965, 510.588439], [131.634306, 137.063166, 186.891004, 226.322093, 616.030309], [75.452400, 77.721687, 99.280927, 125.553703, 187.490329], [107.860027, 118.227136, 150.955738, 190.836788, 346.712672], [55.545540, 57.785014, 78.594010, 93.269549, 333.417911], [80.081802, 92.914524, 113.428670, 127.433012, 487.858613], [42.814884, 53.641799, 58.439636, 63.219528, 351.130984], [187.661369, 194.657671, 270.585419, 322.408226, 899.203321]]
input_correlations: [[0.000000, 0.362176, -0.992143, -0.875592, 0.000000, 0.475164, -0.975864, -0.989536], [0.000000, -0.541933, 0.994514, 0.923708, 0.000000, -0.604788, 0.998272, 0.966947], [0.000000, 0.665028, -0.968230, -0.917553, 0.000000, 0.722751, -0.977484, -0.930426], [0.000000, 0.623137, -0.978043, -0.940592, 0.000000, 0.667930, -0.988172, -0.934212], [0.000000, 0.461758, -0.997891, -0.932731, 0.000000, 0.532279, -0.993759, -0.968912], [0.000000, 0.387797, -0.993264, -0.879329, 0.000000, 0.480629, -0.983334, -0.989153], [0.000000, 0.244695, -0.971286, -0.879013, 0.000000, 0.354694, -0.950437, -0.959753], [0.000000, -0.516757, 0.997429, 0.926162, 0.000000, -0.592718, 0.996589, 0.970300]]
pre_activation_mean: [-5.673204, 6.844781, -2.083226, -3.852363, -3.704643, -5.420651, -3.901455, 9.991148]
pre_activation_std: [5.548416, 9.399738, 5.172185, 7.839168, 3.887511, 5.505156, 2.856461, 13.403308]
### 6
mean: [12.483420, 6.798933, -0.719466, 6.801160, -5.686831, -0.932791, -4.788970, -1.909167]
std: [18.602835, 10.546041, 4.804238, 10.674757, 5.944861, 0.950432, 5.821273, 1.227450]
fourier: [[261.791131, 278.404319, 372.650234, 446.637601, 1123.507860], [150.576471, 159.184923, 211.138988, 252.796580, 611.903923], [65.007595, 77.419787, 82.132166, 91.649624, 108.657952], [151.901250, 160.921455, 214.001425, 255.925965, 612.104406], [80.215594, 91.423463, 118.352938, 141.811554, 511.814796], [13.329447, 14.937347, 20.008953, 22.834287, 83.951219], [81.066781, 84.366676, 116.767346, 140.131018, 431.007280], [17.201922, 21.776259, 22.557973, 25.399533, 171.825017]]
input_correlations: [[0.000000, 0.998558, -0.534560, -0.527482, 0.000000, 0.000000, 0.000000, 0.998306], [0.000000, 0.997166, -0.553439, -0.546792, 0.000000, 0.000000, 0.000000, 0.996787], [0.000000, -0.946687, 0.745199, 0.740642, 0.000000, 0.000000, 0.000000, -0.944284], [0.000000, 0.997401, -0.550278, -0.543308, 0.000000, 0.000000, 0.000000, 0.997119], [0.000000, -0.984949, 0.340080, 0.332257, 0.000000, 0.000000, 0.000000, -0.986992], [0.000000, -0.987476, 0.421864, 0.414873, 0.000000, 0.000000, 0.000000, -0.992502], [0.000000, -0.999349, 0.470819, 0.463097, 0.000000, 0.000000, 0.000000, -0.999752], [0.000000, -0.837573, -0.050801, -0.058929, 0.000000, 0.000000, 0.000000, -0.844845]]
pre_activation_mean: [12.483420, 6.798933, -0.719466, 6.801160, -5.686831, -0.932791, -4.788970, -1.909167]
pre_activation_std: [18.602835, 10.546041, 4.804238, 10.674757, 5.944861, 0.950432, 5.821273, 1.227450]
### 8
mean: [-3.986158, 20.272865, -3.091446, 16.432980, -0.783326, 17.563663, -6.814966, 12.836175]
std: [5.069550, 30.833874, 4.183321, 24.648556, 0.362842, 26.854244, 11.096881, 19.173016]
fourier: [[69.320996, 74.555372, 100.308250, 121.645534, 358.754229], [434.882861, 463.995230, 612.616225, 737.527136, 1824.557896], [57.718753, 61.737021, 82.772288, 100.387414, 278.230162], [344.762110, 368.873954, 489.354480, 590.210994, 1478.968125], [5.632801, 5.741592, 6.395391, 8.740060, 70.499337], [379.070345, 404.552315, 533.762218, 642.253593, 1580.729822], [160.228067, 169.804524, 221.080117, 264.320894, 613.346899], [267.301283, 286.199930, 380.435963, 459.252316, 1155.255859]]
input_correlations: [[-0.999891, -0.999861, 0.516777, -0.999906, 0.000000, 0.000000, 0.000000, 0.000000], [0.999293, 0.999310, -0.560732, 0.999149, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999971, -0.999969, 0.523819, -0.999992, 0.000000, 0.000000, 0.000000, 0.000000], [0.999703, 0.999707, -0.549794, 0.999598, 0.000000, 0.000000, 0.000000, 0.000000], [-0.175956, -0.175148, -0.739705, -0.179014, 0.000000, 0.000000, 0.000000, 0.000000], [0.999197, 0.999210, -0.562832, 0.999039, 0.000000, 0.000000, 0.000000, 0.000000], [-0.996859, -0.996888, 0.594820, -0.996559, 0.000000, 0.000000, 0.000000, 0.000000], [0.999829, 0.999830, -0.544864, 0.999744, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.986158, 20.272865, -3.091446, 16.432980, -0.783326, 17.563663, -6.814966, 12.836175]
pre_activation_std: [5.069550, 30.833874, 4.183321, 24.648556, 0.362842, 26.854244, 11.096881, 19.173016]
### 10
mean: [-39.894497]
std: [58.532482]
fourier: [[813.802358, 867.048898, 1158.525253, 1404.917569, 3590.504711]]
input_correlations: [[0.000000, -0.999979, 0.000000, -0.999967, 0.000000, -0.999979, 0.479847, -0.999954]]
pre_activation_mean: [-39.894497]
pre_activation_std: [58.532482]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.000000, 21.283472, 0.000000, 17.053709, 0.000000, 18.499735, 0.688127, 13.264108]
std: [0.000000, 30.091917, 0.000000, 24.198986, 0.000000, 26.165501, 1.025657, 18.865128]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [417.608373, 445.132943, 594.916125, 721.831995, 1915.512421], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [335.250417, 357.072386, 478.543376, 581.175386, 1534.833780], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [363.052101, 386.998463, 517.349945, 627.700403, 1664.976050], [15.217970, 15.250658, 15.933572, 23.040534, 61.931422], [261.198866, 278.022978, 373.009493, 453.307575, 1193.769702]]
input_correlations: [[-0.299187, -0.024191, 0.161324, 0.436773, 0.835025, 0.000000, 0.000000, 0.000000], [0.010642, -0.672221, -0.177523, 0.146662, -0.386461, 0.000000, 0.000000, 0.000000], [0.619450, -0.087756, 0.215733, -0.053196, 0.834587, 0.000000, 0.000000, 0.000000], [0.788963, -0.122998, 0.013224, -0.300613, 0.482025, 0.000000, 0.000000, 0.000000], [0.198670, -0.110793, 0.171331, 0.144037, 0.990470, 0.000000, 0.000000, 0.000000], [0.638937, 0.681841, 0.510869, 0.431636, -0.209887, 0.000000, 0.000000, 0.000000], [0.579166, -0.021264, 0.305570, 0.019153, 0.887481, 0.000000, 0.000000, 0.000000], [0.071757, -0.446741, -0.147697, 0.417557, -0.376057, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.143222, -0.963710, 0.540716, 0.535078, 1.306621, 2.408933, 2.073299, -0.257256]
pre_activation_std: [2.436361, 1.364263, 1.793768, 1.857961, 2.336421, 2.060094, 2.570687, 1.410810]
### 2
mean: [-1.800687, 0.904469, 4.316001, 2.167040, -1.370973, 0.209861, 4.566084, 5.096444]
std: [1.187693, 2.344953, 5.134932, 2.996008, 0.786200, 1.801695, 6.055514, 5.727778]
fourier: [[16.390409, 21.980036, 23.424104, 24.504381, 162.061792], [34.212679, 34.610307, 41.571002, 45.927288, 81.402185], [72.400550, 77.940523, 104.898804, 122.917301, 388.440136], [43.902686, 51.846940, 55.428625, 69.292034, 195.033600], [12.127235, 14.985596, 15.482630, 15.942970, 123.387597], [26.945767, 27.014917, 29.520375, 29.890170, 41.826887], [86.306071, 87.974590, 118.226821, 143.929770, 410.947627], [86.894198, 97.206955, 121.221417, 130.553582, 458.679989]]
input_correlations: [[-0.715587, -0.218157, -0.855687, -0.596210, -0.841385, -0.211928, -0.877982, -0.227470], [-0.639583, 0.463860, -0.590605, -0.285303, -0.787001, 0.682833, -0.617443, 0.524452], [0.800155, -0.228008, 0.932073, 0.606343, 0.980871, -0.044125, 0.956941, -0.244323], [0.958299, -0.302279, 0.684608, 0.196417, 0.941221, -0.203913, 0.740094, -0.317926], [-0.796409, 0.047072, -0.782151, -0.452323, -0.821015, -0.362565, -0.808104, 0.024522], [-0.705532, 0.474259, -0.803094, -0.480426, -0.918129, 0.363422, -0.839129, 0.541400], [0.815911, -0.207147, 0.909036, 0.567173, 0.991166, -0.163972, 0.935280, -0.228364], [0.674666, -0.178829, 0.980847, 0.745749, 0.934027, 0.035374, 0.991932, -0.198832]]
pre_activation_mean: [-1.800687, 0.904469, 4.316001, 2.167040, -1.370973, 0.209861, 4.566084, 5.096444]
pre_activation_std: [1.187693, 2.344953, 5.134932, 2.996008, 0.786200, 1.801695, 6.055514, 5.727778]
### 4
mean: [-5.673204, 6.844781, -2.083226, -3.852363, -3.704643, -5.420651, -3.901455, 9.991148]
std: [5.548416, 9.399738, 5.172185, 7.839168, 3.887511, 5.505156, 2.856461, 13.403308]
fourier: [[82.770388, 96.377921, 116.054623, 127.849965, 510.588439], [131.634306, 137.063166, 186.891004, 226.322093, 616.030309], [75.452400, 77.721687, 99.280927, 125.553703, 187.490329], [107.860027, 118.227136, 150.955738, 190.836788, 346.712672], [55.545540, 57.785014, 78.594010, 93.269549, 333.417911], [80.081802, 92.914524, 113.428670, 127.433012, 487.858613], [42.814884, 53.641799, 58.439636, 63.219528, 351.130984], [187.661369, 194.657671, 270.585419, 322.408226, 899.203321]]
input_correlations: [[0.000000, 0.362176, -0.992143, -0.875592, 0.000000, 0.475164, -0.975864, -0.989536], [0.000000, -0.541933, 0.994514, 0.923708, 0.000000, -0.604788, 0.998272, 0.966947], [0.000000, 0.665028, -0.968230, -0.917553, 0.000000, 0.722751, -0.977484, -0.930426], [0.000000, 0.623137, -0.978043, -0.940592, 0.000000, 0.667930, -0.988172, -0.934212], [0.000000, 0.461758, -0.997891, -0.932731, 0.000000, 0.532279, -0.993759, -0.968912], [0.000000, 0.387797, -0.993264, -0.879329, 0.000000, 0.480629, -0.983334, -0.989153], [0.000000, 0.244695, -0.971286, -0.879013, 0.000000, 0.354694, -0.950437, -0.959753], [0.000000, -0.516757, 0.997429, 0.926162, 0.000000, -0.592718, 0.996589, 0.970300]]
pre_activation_mean: [-5.673204, 6.844781, -2.083226, -3.852363, -3.704643, -5.420651, -3.901455, 9.991148]
pre_activation_std: [5.548416, 9.399738, 5.172185, 7.839168, 3.887511, 5.505156, 2.856461, 13.403308]
### 6
mean: [12.483420, 6.798933, -0.719466, 6.801160, -5.686831, -0.932791, -4.788970, -1.909167]
std: [18.602835, 10.546041, 4.804238, 10.674757, 5.944861, 0.950432, 5.821273, 1.227450]
fourier: [[261.791131, 278.404319, 372.650234, 446.637601, 1123.507860], [150.576471, 159.184923, 211.138988, 252.796580, 611.903923], [65.007595, 77.419787, 82.132166, 91.649624, 108.657952], [151.901250, 160.921455, 214.001425, 255.925965, 612.104406], [80.215594, 91.423463, 118.352938, 141.811554, 511.814796], [13.329447, 14.937347, 20.008953, 22.834287, 83.951219], [81.066781, 84.366676, 116.767346, 140.131018, 431.007280], [17.201922, 21.776259, 22.557973, 25.399533, 171.825017]]
input_correlations: [[0.000000, 0.998558, -0.534560, -0.527482, 0.000000, 0.000000, 0.000000, 0.998306], [0.000000, 0.997166, -0.553439, -0.546792, 0.000000, 0.000000, 0.000000, 0.996787], [0.000000, -0.946687, 0.745199, 0.740642, 0.000000, 0.000000, 0.000000, -0.944284], [0.000000, 0.997401, -0.550278, -0.543308, 0.000000, 0.000000, 0.000000, 0.997119], [0.000000, -0.984949, 0.340080, 0.332257, 0.000000, 0.000000, 0.000000, -0.986992], [0.000000, -0.987476, 0.421864, 0.414873, 0.000000, 0.000000, 0.000000, -0.992502], [0.000000, -0.999349, 0.470819, 0.463097, 0.000000, 0.000000, 0.000000, -0.999752], [0.000000, -0.837573, -0.050801, -0.058929, 0.000000, 0.000000, 0.000000, -0.844845]]
pre_activation_mean: [12.483420, 6.798933, -0.719466, 6.801160, -5.686831, -0.932791, -4.788970, -1.909167]
pre_activation_std: [18.602835, 10.546041, 4.804238, 10.674757, 5.944861, 0.950432, 5.821273, 1.227450]
### 8
mean: [-3.986158, 20.272865, -3.091446, 16.432980, -0.783326, 17.563663, -6.814966, 12.836175]
std: [5.069550, 30.833874, 4.183321, 24.648556, 0.362842, 26.854244, 11.096881, 19.173016]
fourier: [[69.320996, 74.555372, 100.308250, 121.645534, 358.754229], [434.882861, 463.995230, 612.616225, 737.527136, 1824.557896], [57.718753, 61.737021, 82.772288, 100.387414, 278.230162], [344.762110, 368.873954, 489.354480, 590.210994, 1478.968125], [5.632801, 5.741592, 6.395391, 8.740060, 70.499337], [379.070345, 404.552315, 533.762218, 642.253593, 1580.729822], [160.228067, 169.804524, 221.080117, 264.320894, 613.346899], [267.301283, 286.199930, 380.435963, 459.252316, 1155.255859]]
input_correlations: [[-0.999891, -0.999861, 0.516777, -0.999906, 0.000000, 0.000000, 0.000000, 0.000000], [0.999293, 0.999310, -0.560732, 0.999149, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999971, -0.999969, 0.523819, -0.999992, 0.000000, 0.000000, 0.000000, 0.000000], [0.999703, 0.999707, -0.549794, 0.999598, 0.000000, 0.000000, 0.000000, 0.000000], [-0.175956, -0.175148, -0.739705, -0.179014, 0.000000, 0.000000, 0.000000, 0.000000], [0.999197, 0.999210, -0.562832, 0.999039, 0.000000, 0.000000, 0.000000, 0.000000], [-0.996859, -0.996888, 0.594820, -0.996559, 0.000000, 0.000000, 0.000000, 0.000000], [0.999829, 0.999830, -0.544864, 0.999744, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.986158, 20.272865, -3.091446, 16.432980, -0.783326, 17.563663, -6.814966, 12.836175]
pre_activation_std: [5.069550, 30.833874, 4.183321, 24.648556, 0.362842, 26.854244, 11.096881, 19.173016]
### 10
mean: [-39.894497]
std: [58.532482]
fourier: [[813.802358, 867.048898, 1158.525253, 1404.917569, 3590.504711]]
input_correlations: [[0.000000, -0.999979, 0.000000, -0.999967, 0.000000, -0.999979, 0.479847, -0.999954]]
pre_activation_mean: [-39.894497]
pre_activation_std: [58.532482]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.2991873932218476, -0.024191476591718608, 0.1613241291024319, 0.43677298113881097, 0.8350250630038119, 0.0, 0.0, 0.0], "pre_activation_mean": 2.143221855163574, "pre_activation_std": 2.4363605976104736}, "1": {"mean": 21.283472061157227, "std": 30.091917037963867, "fourier": [417.6083725476559, 445.1329425257645, 594.9161251177085, 721.8319953025225, 1915.5124205350876], "input_correlations": [0.010641860917829652, -0.6722214761176212, -0.17752281014210075, 0.14666232066870805, -0.3864611841637186, 0.0, 0.0, 0.0], "pre_activation_mean": -0.963709831237793, "pre_activation_std": 1.3642630577087402}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.6194499748919496, -0.08775641586662901, 0.21573331037012733, -0.05319556882533374, 0.8345866314320465, 0.0, 0.0, 0.0], "pre_activation_mean": 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"network.6.bias": [-0.194882, -0.093292, 0.781912, -0.226406, -0.113978, -0.132066, -0.294264, -0.332274], "network.8.weight": [[-0.349795, 0.087622, -0.043809, 0.034299, 0.012802, -0.015345, 0.274026, 0.303684], [0.753898, 0.892247, -0.683495, 0.707987, -0.233256, 0.274091, 0.030447, -0.037796], [-0.114874, 0.108084, -0.00871, -0.311254, -0.000595, -0.231538, 0.082083, 0.3392], [0.916007, 0.359661, -0.355242, 0.382955, 0.104548, 0.201927, -0.349453, 0.308774], [-0.261232, 0.19483, -0.211403, 0.240597, -0.126818, -0.217897, -0.331828, -0.053739], [0.843083, 0.431785, -0.635804, 0.624085, -0.18802, -0.121229, -0.077765, -0.210049], [-0.370633, -0.075475, 0.51589, -0.291414, 0.068024, 0.285176, -0.098184, 0.295615], [0.719688, 0.393119, -0.207988, 0.18051, 0.104849, 0.087662, 0.119974, -0.16328]], "network.8.bias": [-0.249998, -0.159852, -0.097048, -0.367756, -0.230226, -0.143538, -0.097212, -0.397657], "network.10.weight": [[-0.178607, -0.464743, 0.06221, -0.77067, -0.078615, -0.482858, 0.481807, -0.690611]], "network.10.bias": [0.901165]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7061075866222382, "train_acc": 0.435, "val_loss": 0.6892942786216736, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6757219135761261, "train_acc": 0.575, "val_loss": 0.6789021492004395, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6358359158039093, "train_acc": 0.575, "val_loss": 0.5983940958976746, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.539980560541153, "train_acc": 0.495, "val_loss": 0.45247164368629456, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.41949795186519623, "train_acc": 0.855, "val_loss": 0.39890480041503906, "val_acc": 0.86}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.3790562152862549, "train_acc": 0.89, "val_loss": 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"improved", "epoch": 9, "global_epoch": 12, "train_loss": 1.2225253134965897, "train_acc": 0.83, "val_loss": 0.2204485535621643, "val_acc": 0.92}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6892942786216736, "final_val_loss": 0.5983940958976746, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.45247164368629456, "final_val_loss": 0.2204485535621643, "initial_val_acc": 0.82, "final_val_acc": 0.92, "best_val_acc": 0.92, "best_epoch": 12}, "improvement": 0.4, "first_improvement_epoch": 2}} |
12 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.38, "improved_accuracy": 0.92, "improvement": 0.54, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1822, "learning_rate": 0.04873785800456769, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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}
## Activation Signature
### 0
mean: [17.230410, 15.425723, 0.000000, 0.000000, 0.000000, 0.000000, 15.983373, 0.000000]
std: [17.170347, 15.345343, 0.000000, 0.000000, 0.000000, 0.000000, 15.840334, 0.000000]
fourier: [[263.056658, 265.823533, 300.971338, 326.888684, 1550.737025], [233.102929, 238.053982, 266.685423, 292.829241, 1388.314984], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [243.845116, 244.107680, 278.288308, 301.401378, 1438.503586], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.249698, 0.552486, -0.522459, 0.386770, -0.428462, 0.000000, 0.000000, 0.000000], [0.903223, 0.577709, 0.549684, -0.114580, 0.094149, 0.000000, 0.000000, 0.000000], [0.799391, 0.355256, 0.168635, -0.054918, -0.440483, 0.000000, 0.000000, 0.000000], [-0.673103, -0.281413, -0.101492, 0.681381, 0.028189, 0.000000, 0.000000, 0.000000], [0.776695, 0.619200, -0.004852, 0.377128, -0.126909, 0.000000, 0.000000, 0.000000], [-0.469113, -0.432982, -0.199296, 0.564799, -0.356405, 0.000000, 0.000000, 0.000000], [0.846819, 0.521965, 0.527053, -0.159731, -0.177234, 0.000000, 0.000000, 0.000000], [-0.096914, 0.581930, -0.606096, 0.336190, -0.421317, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.475589, 2.777623, 0.958370, 0.327776, 1.829165, 0.085590, 1.515476, 0.086467]
pre_activation_std: [1.516723, 3.259434, 2.282544, 1.314140, 2.118345, 1.121895, 2.709323, 1.313351]
### 2
mean: [6.115053, -2.397671, 4.550942, 3.426890, 0.427631, 5.035131, -2.051912, -1.164028]
std: [6.217316, 3.171822, 4.281182, 3.392081, 0.604512, 4.778967, 1.521914, 0.962399]
fourier: [[98.378720, 98.810320, 103.072637, 119.610674, 550.354729], [48.828361, 50.943305, 51.382202, 59.448067, 215.790387], [64.099284, 72.505958, 75.439492, 80.381650, 409.584749], [49.568786, 57.782754, 61.177579, 64.229951, 308.420138], [9.254057, 9.924749, 10.134200, 11.612729, 38.486745], [73.043797, 73.377817, 85.122593, 91.198255, 453.161826], [23.214939, 24.702051, 25.319184, 30.779722, 184.672090], [13.430201, 13.817608, 19.174547, 21.136008, 104.762546]]
input_correlations: [[0.636786, 0.935709, 0.939660, -0.324617, 0.918278, -0.251689, 0.951090, 0.277903], [-0.651722, -0.888065, -0.969173, 0.294201, -0.941410, 0.165792, -0.917119, -0.241589], [0.773359, 0.852023, 0.928962, -0.260121, 0.958159, -0.176435, 0.877839, 0.430418], [0.802686, 0.791839, 0.917069, -0.159559, 0.989951, -0.063964, 0.817163, 0.428303], [0.879308, 0.072619, 0.297129, 0.333586, 0.597054, 0.412311, 0.117649, 0.831344], [0.719699, 0.876823, 0.940236, -0.221640, 0.964744, -0.139493, 0.899138, 0.347472], [-0.596790, -0.928205, -0.901471, 0.192815, -0.880014, 0.158396, -0.949638, -0.283744], [-0.839563, -0.340702, -0.636127, -0.386878, -0.843252, -0.416611, -0.403107, -0.549278]]
pre_activation_mean: [6.115053, -2.397671, 4.550942, 3.426890, 0.427631, 5.035131, -2.051912, -1.164028]
pre_activation_std: [6.217316, 3.171822, 4.281182, 3.392081, 0.604512, 4.778967, 1.521914, 0.962399]
### 4
mean: [6.527585, 6.066160, 2.312791, 8.838245, -2.631505, -0.445170, 8.955549, 3.456908]
std: [6.553364, 5.845477, 2.240698, 8.768299, 2.186598, 0.518091, 8.820986, 3.397290]
fourier: [[100.291760, 102.120384, 111.886485, 125.493811, 587.482539], [88.564782, 92.584442, 103.976588, 110.467699, 545.954428], [33.741420, 36.168682, 37.334330, 42.867181, 208.151182], [133.462886, 134.675228, 152.938675, 167.114043, 795.442057], [33.111009, 35.110749, 38.818012, 41.418311, 236.835428], [7.692404, 8.122351, 9.404596, 10.086156, 40.065268], [133.758068, 137.569960, 156.564115, 167.269009, 805.999507], [52.987886, 53.330772, 57.154157, 65.168776, 311.121707]]
input_correlations: [[0.996350, -0.297736, 0.993354, 0.970667, 0.418770, 0.995155, 0.000000, -0.160869], [0.987363, -0.310424, 0.998289, 0.984963, 0.484124, 0.997805, 0.000000, -0.177846], [0.992857, -0.373071, 0.988686, 0.965871, 0.417898, 0.991496, 0.000000, -0.151783], [0.993309, -0.298820, 0.995606, 0.979614, 0.443153, 0.998301, 0.000000, -0.173067], [-0.986423, 0.279461, -0.997415, -0.988176, -0.473494, -0.998849, 0.000000, 0.194764], [-0.551171, -0.009844, -0.403612, -0.274093, 0.458621, -0.417639, 0.000000, -0.142852], [0.988950, -0.304458, 0.997186, 0.985205, 0.471820, 0.998982, 0.000000, -0.180296], [0.998407, -0.303509, 0.988062, 0.959937, 0.389492, 0.991015, 0.000000, -0.141335]]
pre_activation_mean: [6.527585, 6.066160, 2.312791, 8.838245, -2.631505, -0.445170, 8.955549, 3.456908]
pre_activation_std: [6.553364, 5.845477, 2.240698, 8.768299, 2.186598, 0.518091, 8.820986, 3.397290]
### 6
mean: [17.217974, 15.418283, -1.775576, -1.628058, -7.345340, -6.266778, 15.977305, -5.835343]
std: [17.182930, 15.352867, 1.661696, 1.320179, 6.893090, 6.082068, 15.846486, 5.604531]
fourier: [[262.993293, 265.571271, 300.879138, 327.205848, 1549.617791], [233.044281, 237.897367, 266.630321, 293.007993, 1387.645300], [25.351350, 25.970484, 29.590419, 31.534332, 159.801890], [20.176514, 20.367293, 22.969436, 25.167125, 146.525194], [104.578058, 106.743721, 120.354588, 131.399473, 661.080652], [93.322242, 94.205799, 107.340673, 115.593662, 564.010028], [243.835144, 243.975586, 278.236062, 301.546264, 1437.957451], [86.169324, 86.725493, 98.580600, 106.582124, 525.180917]]
input_correlations: [[0.999257, 0.999094, 0.998516, 0.999916, 0.000000, 0.001428, 0.999348, 0.996932], [0.999611, 0.998537, 0.998963, 0.999861, 0.000000, -0.009389, 0.998896, 0.997708], [-0.996694, -0.999304, -0.995944, -0.999224, 0.000000, -0.033167, -0.999858, -0.992716], [-0.999266, -0.998613, -0.997951, -0.999865, 0.000000, 0.009348, -0.999055, -0.996863], [-0.999432, -0.998738, -0.998978, -0.999849, 0.000000, 0.002364, -0.999061, -0.997464], [-0.998317, -0.999571, -0.997591, -0.999817, 0.000000, -0.015728, -0.999863, -0.995214], [0.998886, 0.999337, 0.998099, 0.999939, 0.000000, 0.006667, 0.999633, 0.996183], [-0.998733, -0.999485, -0.997671, -0.999862, 0.000000, -0.007763, -0.999683, -0.995838]]
pre_activation_mean: [17.217974, 15.418283, -1.775576, -1.628058, -7.345340, -6.266778, 15.977305, -5.835343]
pre_activation_std: [17.182930, 15.352867, 1.661696, 1.320179, 6.893090, 6.082068, 15.846486, 5.604531]
### 8
mean: [-20.331715]
std: [21.027456]
fourier: [[322.847212, 324.768230, 368.880881, 400.251667, 1829.854239]]
input_correlations: [[-0.999988, -0.999878, 0.000000, 0.000000, 0.000000, 0.000000, -0.999988, 0.000000]]
pre_activation_mean: [-20.331715]
pre_activation_std: [21.027456]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.295282,
0.380075,
-0.520485,
0.232895,
-0.332748
],
[
1.13517,
0.611556,
0.44477,
-0.293925,
-0.109346
],
[
1.013465,
0.038311,
0.009872,
0.076357,
-0.76186
],
[
-0.356619,
-0.278753,
0.105618,
0.494219,
-0.017001
],
[
0.874807,
0.322254,
-0.302146,
0.373537,
-0.31462
],
[
-0.078918,
-0.417564,
0.052973,
0.458949,
-0.291364
],
[
0.950415,
0.395024,
0.445434,
-0.214498,
-0.513202
],
[
-0.034879,
0.497943,
-0.462693,
0.096422,
-0.20454
]
],
"network.0.bias": [
0.413738,
0.086667,
0.382619,
0.020037,
0.37145,
0.209199,
-0.224619,
0.234519
],
"network.2.weight": [
[
1.039375,
0.794632,
0.614683,
-0.16097,
0.502735,
0.257718,
0.552468,
0.098174
],
[
-0.252009,
-0.110617,
-0.488134,
0.61009,
-0.599756,
-0.661929,
-0.311737,
0.127191
],
[
0.9264,
0.290962,
0.550748,
-0.270694,
0.477688,
0.395749,
0.367557,
0.589067
],
[
0.823201,
0.205257,
0.295784,
-0.172868,
0.86846,
0.389248,
0.025873,
-0.046384
],
[
0.509948,
-0.091867,
-0.228621,
-0.123072,
0.062795,
0.45092,
0.208213,
0.127434
],
[
0.897872,
0.494477,
0.498401,
-0.023138,
0.737581,
0.452044,
0.253067,
0.093528
],
[
0.15213,
-0.331285,
-0.354227,
-0.324373,
0.115363,
-0.174213,
-0.089531,
-0.616012
],
[
-0.106157,
0.157709,
-0.097524,
-0.391208,
-0.374969,
-0.020542,
-0.104906,
-0.156948
]
],
"network.2.bias": [
0.036041,
0.395511,
0.243187,
-0.073721,
-0.161559,
0.003296,
-0.207259,
-0.113281
],
"network.4.weight": [
[
0.572905,
-0.160788,
0.693382,
-0.119198,
0.032454,
0.091227,
0.318362,
0.055581
],
[
0.443805,
-0.268241,
0.425326,
0.216658,
0.594199,
0.084993,
-0.151045,
0.264552
],
[
0.151182,
-0.735947,
0.168798,
-0.144855,
0.016628,
0.208205,
0.281792,
-0.043939
],
[
0.618714,
-0.22045,
0.546283,
0.221384,
0.130391,
0.385885,
-0.034755,
-0.025503
],
[
0.002995,
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0.110882,
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0.107078
],
[
-0.269679,
-0.174376,
-0.171571,
0.29365,
0.175714,
0.236599,
-0.032812,
0.298991
],
[
0.568238,
-0.309532,
0.39684,
0.365266,
0.566431,
0.470564,
0.114969,
0.05193
],
[
0.397247,
-0.19466,
0.31331,
-0.170635,
0.07429,
0.028435,
0.317223,
0.477677
]
],
"network.4.bias": [
-0.190979,
-0.025234,
0.121895,
-0.184931,
-0.320159,
-0.285696,
-0.20033,
0.016004
],
"network.6.weight": [
[
0.55676,
0.553945,
0.212062,
0.381942,
-0.040008,
0.257473,
0.501932,
0.619672
],
[
0.62095,
0.20776,
0.612139,
0.465525,
0.156626,
-0.295641,
0.378892,
0.393977
],
[
-0.122725,
0.14566,
-0.086069,
-0.09444,
-0.319536,
-0.140988,
-0.174259,
0.249296
],
[
0.030652,
-0.100309,
0.193758,
-0.280474,
0.046072,
0.072419,
0.135761,
-0.02984
],
[
-0.131728,
-0.014549,
-0.490139,
0.07296,
0.114407,
-0.122948,
-0.443474,
-0.475981
],
[
-0.154362,
-0.051687,
-0.237918,
-0.120052,
-0.114186,
-0.056962,
-0.406485,
0.11199
],
[
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0.448642,
0.178752,
0.723735,
0.180179,
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0.475121,
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],
[
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0.347525,
-0.130929,
-0.353852,
0.141409,
-0.253298,
-0.131851
]
],
"network.6.bias": [
-0.336785,
-0.210499,
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-0.255403,
-0.059367,
-0.176775,
-0.162472
],
"network.8.weight": [
[
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-0.026682,
-0.05036,
0.008249,
-0.717933,
0.180649
]
],
"network.8.bias": [
0.834391
]
}
## Activation Signature
### 0
mean: [17.230410, 15.425723, 0.000000, 0.000000, 0.000000, 0.000000, 15.983373, 0.000000]
std: [17.170347, 15.345343, 0.000000, 0.000000, 0.000000, 0.000000, 15.840334, 0.000000]
fourier: [[263.056658, 265.823533, 300.971338, 326.888684, 1550.737025], [233.102929, 238.053982, 266.685423, 292.829241, 1388.314984], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [243.845116, 244.107680, 278.288308, 301.401378, 1438.503586], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.249698, 0.552486, -0.522459, 0.386770, -0.428462, 0.000000, 0.000000, 0.000000], [0.903223, 0.577709, 0.549684, -0.114580, 0.094149, 0.000000, 0.000000, 0.000000], [0.799391, 0.355256, 0.168635, -0.054918, -0.440483, 0.000000, 0.000000, 0.000000], [-0.673103, -0.281413, -0.101492, 0.681381, 0.028189, 0.000000, 0.000000, 0.000000], [0.776695, 0.619200, -0.004852, 0.377128, -0.126909, 0.000000, 0.000000, 0.000000], [-0.469113, -0.432982, -0.199296, 0.564799, -0.356405, 0.000000, 0.000000, 0.000000], [0.846819, 0.521965, 0.527053, -0.159731, -0.177234, 0.000000, 0.000000, 0.000000], [-0.096914, 0.581930, -0.606096, 0.336190, -0.421317, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.475589, 2.777623, 0.958370, 0.327776, 1.829165, 0.085590, 1.515476, 0.086467]
pre_activation_std: [1.516723, 3.259434, 2.282544, 1.314140, 2.118345, 1.121895, 2.709323, 1.313351]
### 2
mean: [6.115053, -2.397671, 4.550942, 3.426890, 0.427631, 5.035131, -2.051912, -1.164028]
std: [6.217316, 3.171822, 4.281182, 3.392081, 0.604512, 4.778967, 1.521914, 0.962399]
fourier: [[98.378720, 98.810320, 103.072637, 119.610674, 550.354729], [48.828361, 50.943305, 51.382202, 59.448067, 215.790387], [64.099284, 72.505958, 75.439492, 80.381650, 409.584749], [49.568786, 57.782754, 61.177579, 64.229951, 308.420138], [9.254057, 9.924749, 10.134200, 11.612729, 38.486745], [73.043797, 73.377817, 85.122593, 91.198255, 453.161826], [23.214939, 24.702051, 25.319184, 30.779722, 184.672090], [13.430201, 13.817608, 19.174547, 21.136008, 104.762546]]
input_correlations: [[0.636786, 0.935709, 0.939660, -0.324617, 0.918278, -0.251689, 0.951090, 0.277903], [-0.651722, -0.888065, -0.969173, 0.294201, -0.941410, 0.165792, -0.917119, -0.241589], [0.773359, 0.852023, 0.928962, -0.260121, 0.958159, -0.176435, 0.877839, 0.430418], [0.802686, 0.791839, 0.917069, -0.159559, 0.989951, -0.063964, 0.817163, 0.428303], [0.879308, 0.072619, 0.297129, 0.333586, 0.597054, 0.412311, 0.117649, 0.831344], [0.719699, 0.876823, 0.940236, -0.221640, 0.964744, -0.139493, 0.899138, 0.347472], [-0.596790, -0.928205, -0.901471, 0.192815, -0.880014, 0.158396, -0.949638, -0.283744], [-0.839563, -0.340702, -0.636127, -0.386878, -0.843252, -0.416611, -0.403107, -0.549278]]
pre_activation_mean: [6.115053, -2.397671, 4.550942, 3.426890, 0.427631, 5.035131, -2.051912, -1.164028]
pre_activation_std: [6.217316, 3.171822, 4.281182, 3.392081, 0.604512, 4.778967, 1.521914, 0.962399]
### 4
mean: [6.527585, 6.066160, 2.312791, 8.838245, -2.631505, -0.445170, 8.955549, 3.456908]
std: [6.553364, 5.845477, 2.240698, 8.768299, 2.186598, 0.518091, 8.820986, 3.397290]
fourier: [[100.291760, 102.120384, 111.886485, 125.493811, 587.482539], [88.564782, 92.584442, 103.976588, 110.467699, 545.954428], [33.741420, 36.168682, 37.334330, 42.867181, 208.151182], [133.462886, 134.675228, 152.938675, 167.114043, 795.442057], [33.111009, 35.110749, 38.818012, 41.418311, 236.835428], [7.692404, 8.122351, 9.404596, 10.086156, 40.065268], [133.758068, 137.569960, 156.564115, 167.269009, 805.999507], [52.987886, 53.330772, 57.154157, 65.168776, 311.121707]]
input_correlations: [[0.996350, -0.297736, 0.993354, 0.970667, 0.418770, 0.995155, 0.000000, -0.160869], [0.987363, -0.310424, 0.998289, 0.984963, 0.484124, 0.997805, 0.000000, -0.177846], [0.992857, -0.373071, 0.988686, 0.965871, 0.417898, 0.991496, 0.000000, -0.151783], [0.993309, -0.298820, 0.995606, 0.979614, 0.443153, 0.998301, 0.000000, -0.173067], [-0.986423, 0.279461, -0.997415, -0.988176, -0.473494, -0.998849, 0.000000, 0.194764], [-0.551171, -0.009844, -0.403612, -0.274093, 0.458621, -0.417639, 0.000000, -0.142852], [0.988950, -0.304458, 0.997186, 0.985205, 0.471820, 0.998982, 0.000000, -0.180296], [0.998407, -0.303509, 0.988062, 0.959937, 0.389492, 0.991015, 0.000000, -0.141335]]
pre_activation_mean: [6.527585, 6.066160, 2.312791, 8.838245, -2.631505, -0.445170, 8.955549, 3.456908]
pre_activation_std: [6.553364, 5.845477, 2.240698, 8.768299, 2.186598, 0.518091, 8.820986, 3.397290]
### 6
mean: [17.217974, 15.418283, -1.775576, -1.628058, -7.345340, -6.266778, 15.977305, -5.835343]
std: [17.182930, 15.352867, 1.661696, 1.320179, 6.893090, 6.082068, 15.846486, 5.604531]
fourier: [[262.993293, 265.571271, 300.879138, 327.205848, 1549.617791], [233.044281, 237.897367, 266.630321, 293.007993, 1387.645300], [25.351350, 25.970484, 29.590419, 31.534332, 159.801890], [20.176514, 20.367293, 22.969436, 25.167125, 146.525194], [104.578058, 106.743721, 120.354588, 131.399473, 661.080652], [93.322242, 94.205799, 107.340673, 115.593662, 564.010028], [243.835144, 243.975586, 278.236062, 301.546264, 1437.957451], [86.169324, 86.725493, 98.580600, 106.582124, 525.180917]]
input_correlations: [[0.999257, 0.999094, 0.998516, 0.999916, 0.000000, 0.001428, 0.999348, 0.996932], [0.999611, 0.998537, 0.998963, 0.999861, 0.000000, -0.009389, 0.998896, 0.997708], [-0.996694, -0.999304, -0.995944, -0.999224, 0.000000, -0.033167, -0.999858, -0.992716], [-0.999266, -0.998613, -0.997951, -0.999865, 0.000000, 0.009348, -0.999055, -0.996863], [-0.999432, -0.998738, -0.998978, -0.999849, 0.000000, 0.002364, -0.999061, -0.997464], [-0.998317, -0.999571, -0.997591, -0.999817, 0.000000, -0.015728, -0.999863, -0.995214], [0.998886, 0.999337, 0.998099, 0.999939, 0.000000, 0.006667, 0.999633, 0.996183], [-0.998733, -0.999485, -0.997671, -0.999862, 0.000000, -0.007763, -0.999683, -0.995838]]
pre_activation_mean: [17.217974, 15.418283, -1.775576, -1.628058, -7.345340, -6.266778, 15.977305, -5.835343]
pre_activation_std: [17.182930, 15.352867, 1.661696, 1.320179, 6.893090, 6.082068, 15.846486, 5.604531]
### 8
mean: [-20.331715]
std: [21.027456]
fourier: [[322.847212, 324.768230, 368.880881, 400.251667, 1829.854239]]
input_correlations: [[-0.999988, -0.999878, 0.000000, 0.000000, 0.000000, 0.000000, -0.999988, 0.000000]]
pre_activation_mean: [-20.331715]
pre_activation_std: [21.027456]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.365266, 0.566431, 0.470564, 0.114969, 0.05193], [0.397247, -0.19466, 0.31331, -0.170635, 0.07429, 0.028435, 0.317223, 0.477677]], "network.4.bias": [-0.190979, -0.025234, 0.121895, -0.184931, -0.320159, -0.285696, -0.20033, 0.016004], "network.6.weight": [[0.55676, 0.553945, 0.212062, 0.381942, -0.040008, 0.257473, 0.501932, 0.619672], [0.62095, 0.20776, 0.612139, 0.465525, 0.156626, -0.295641, 0.378892, 0.393977], [-0.122725, 0.14566, -0.086069, -0.09444, -0.319536, -0.140988, -0.174259, 0.249296], [0.030652, -0.100309, 0.193758, -0.280474, 0.046072, 0.072419, 0.135761, -0.02984], [-0.131728, -0.014549, -0.490139, 0.07296, 0.114407, -0.122948, -0.443474, -0.475981], [-0.154362, -0.051687, -0.237918, -0.120052, -0.114186, -0.056962, -0.406485, 0.11199], [0.282406, 0.448642, 0.178752, 0.723735, 0.180179, -0.031828, 0.475121, 0.141945], [-0.187429, -0.22718, 0.347525, -0.130929, -0.353852, 0.141409, -0.253298, -0.131851]], "network.6.bias": [-0.336785, -0.210499, -0.112411, -0.309397, -0.255403, -0.059367, -0.176775, -0.162472], "network.8.weight": [[-0.501626, -0.067931, -0.218758, -0.026682, -0.05036, 0.008249, -0.717933, 0.180649]], "network.8.bias": [0.834391]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6910922229290009, "train_acc": 0.515, "val_loss": 0.6403840780258179, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.5982266068458557, "train_acc": 0.595, "val_loss": 0.5879743099212646, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5185171961784363, "train_acc": 0.645, "val_loss": 0.5262958407402039, "val_acc": 0.88}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.45188798010349274, "train_acc": 0.855, "val_loss": 0.4473085403442383, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.3986571431159973, "train_acc": 0.86, "val_loss": 0.4103071689605713, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3937634527683258, "train_acc": 0.87, "val_loss": 0.39673560857772827, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.34669922292232513, "train_acc": 0.885, "val_loss": 0.4119299054145813, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.3765300214290619, "train_acc": 0.845, "val_loss": 0.39577704668045044, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.35799743235111237, "train_acc": 0.86, "val_loss": 0.356548011302948, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.3199831694364548, "train_acc": 0.87, "val_loss": 0.32397565245628357, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.32441969215869904, "train_acc": 0.89, "val_loss": 0.33637386560440063, "val_acc": 0.9}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.29659709334373474, "train_acc": 0.895, "val_loss": 0.3323594033718109, "val_acc": 0.9}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6403840780258179, "final_val_loss": 0.5879743099212646, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.5262958407402039, "final_val_loss": 0.3323594033718109, "initial_val_acc": 0.88, "final_val_acc": 0.9, "best_val_acc": 0.92, "best_epoch": 9}, "improvement": 0.54, "first_improvement_epoch": 1}} |
13 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.6, "improved_accuracy": 0.92, "improvement": 0.32000000000000006, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6709, "learning_rate": 0.05912918367929151, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.weight": [
[
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]
],
"network.10.bias": [
0.383789
]
}
## Activation Signature
### 0
mean: [0.021392, 5.472024, 0.053825, 12.332438, 0.069053, 14.876183, 19.176321, 13.665038]
std: [0.151373, 5.254956, 0.224481, 11.511294, 0.294013, 13.859066, 17.829762, 12.937762]
fourier: [[2.258727, 2.346152, 2.394490, 2.497403, 2.708904], [84.341587, 91.283554, 92.836942, 93.152295, 492.482158], [3.497713, 3.623434, 3.729831, 4.135371, 4.844288], [185.256738, 200.335983, 202.444731, 204.200044, 1109.919467], [4.289742, 4.526904, 4.604526, 5.338251, 6.214777], [221.863827, 241.574597, 243.460696, 246.538421, 1338.856465], [285.369605, 310.833877, 313.597298, 317.339511, 1725.868955], [205.214008, 226.196728, 227.429217, 230.634320, 1229.853361]]
input_correlations: [[-0.861134, -0.382913, -0.312844, 0.215427, 0.308550, 0.000000, 0.000000, 0.000000], [0.410425, 0.779134, 0.521208, -0.217868, -0.184840, 0.000000, 0.000000, 0.000000], [0.607784, -0.367371, -0.079343, -0.036219, 0.549193, 0.000000, 0.000000, 0.000000], [-0.760220, -0.608168, -0.449500, 0.269288, 0.224276, 0.000000, 0.000000, 0.000000], [0.933739, 0.329286, 0.500607, -0.297952, 0.084045, 0.000000, 0.000000, 0.000000], [-0.610026, -0.439869, -0.385617, 0.488715, 0.402138, 0.000000, 0.000000, 0.000000], [0.689574, 0.846866, 0.526659, 0.186782, -0.057963, 0.000000, 0.000000, 0.000000], [0.539822, 0.848693, 0.084127, 0.473195, -0.237957, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.569845, 0.977111, 0.485665, -0.940312, 1.073432, -0.073033, 3.150539, 2.615778]
pre_activation_std: [1.903894, 1.732920, 1.698007, 2.050630, 2.277725, 1.835750, 2.554596, 2.329759]
### 2
mean: [-0.902991, 2.146437, 3.727684, -1.978252, 2.957242, -0.712417, 3.699663, 1.011441]
std: [0.885038, 2.182370, 2.831778, 1.327195, 3.446214, 1.179162, 3.560797, 2.106066]
fourier: [[12.108081, 12.422464, 13.188417, 16.444689, 81.269235], [34.166183, 38.044206, 39.382147, 39.834335, 193.179313], [46.079676, 49.633488, 50.728810, 54.111480, 335.491658], [19.735066, 20.524079, 23.708762, 27.263593, 178.042687], [51.351330, 58.031657, 58.684355, 68.734452, 266.151774], [18.144139, 19.033470, 20.724139, 22.159622, 64.117482], [57.782303, 60.019628, 64.118424, 69.672023, 332.969608], [32.744965, 33.553128, 37.609765, 45.868871, 91.029720]]
input_correlations: [[-0.361331, 0.124532, -0.503648, -0.532158, -0.276020, -0.558526, -0.196580, -0.498436], [-0.251801, 0.859798, 0.212288, -0.281495, 0.818015, -0.334636, 0.979304, 0.808848], [-0.351507, 0.749458, 0.145913, -0.299544, 0.649566, -0.305775, 0.948880, 0.963902], [-0.846898, -0.052925, -0.321768, -0.853265, 0.028624, -0.849549, -0.078450, -0.173957], [-0.500121, 0.779814, 0.248318, -0.496102, 0.849868, -0.553763, 0.952391, 0.797072], [0.629262, -0.761342, 0.230765, 0.636439, -0.393844, 0.610050, -0.850341, -0.834926], [-0.430265, 0.832152, 0.006617, -0.440668, 0.638060, -0.447167, 0.970025, 0.927985], [-0.479070, 0.726307, 0.344827, -0.519423, 0.884099, -0.660743, 0.743701, 0.371105]]
pre_activation_mean: [-0.902991, 2.146437, 3.727684, -1.978252, 2.957242, -0.712417, 3.699663, 1.011441]
pre_activation_std: [0.885038, 2.182370, 2.831778, 1.327195, 3.446214, 1.179162, 3.560797, 2.106066]
### 4
mean: [-6.849235, 4.595902, 4.956168, 3.207539, 8.741286, 5.287680, 6.766322, -7.484971]
std: [7.031214, 4.012016, 4.603116, 2.712335, 8.030023, 4.939764, 6.169106, 7.755126]
fourier: [[114.717133, 120.198691, 123.307029, 124.020518, 616.431187], [67.188516, 67.518588, 69.662654, 69.770346, 413.631128], [74.793525, 78.298659, 80.205824, 83.862805, 446.055094], [44.498337, 44.739203, 47.017971, 50.188774, 288.678451], [130.473660, 138.006082, 140.128138, 142.031384, 786.715736], [82.564960, 83.306547, 86.547811, 86.580858, 475.891183], [101.328377, 105.571819, 107.873590, 109.674705, 608.968952], [125.093292, 133.745336, 135.876857, 137.320558, 673.647341]]
input_correlations: [[-0.029532, -0.986383, -0.950446, -0.421200, -0.990882, 0.290847, -0.963159, -0.827490], [0.037831, 0.983644, 0.942118, 0.408639, 0.990723, -0.308811, 0.950054, 0.848577], [0.048367, 0.982468, 0.953745, 0.408488, 0.983984, -0.329575, 0.970125, 0.816756], [-0.062807, 0.945636, 0.992579, 0.468154, 0.952510, -0.334850, 0.989268, 0.698326], [0.019434, 0.983206, 0.956565, 0.423732, 0.989483, -0.294108, 0.967890, 0.816546], [0.051026, 0.981570, 0.924159, 0.369961, 0.995275, -0.299706, 0.939750, 0.869436], [0.035602, 0.984091, 0.951061, 0.417388, 0.990788, -0.297864, 0.961552, 0.830158], [-0.035054, -0.986631, -0.950711, -0.427477, -0.990357, 0.283727, -0.963499, -0.827883]]
pre_activation_mean: [-6.849235, 4.595902, 4.956168, 3.207539, 8.741286, 5.287680, 6.766322, -7.484971]
pre_activation_std: [7.031214, 4.012016, 4.603116, 2.712335, 8.030023, 4.939764, 6.169106, 7.755126]
### 6
mean: [-11.040798, 9.009839, -5.233219, 15.468274, -3.459234, -8.425322, 8.398394, -6.429766]
std: [10.415142, 8.458654, 4.776647, 14.225512, 3.215312, 7.884085, 8.065898, 5.664427]
fourier: [[167.609192, 179.967880, 181.299986, 186.372167, 993.671904], [134.394513, 146.737841, 147.192361, 153.185933, 810.885541], [79.059901, 81.801121, 83.460930, 85.428157, 470.989735], [231.780209, 245.089867, 249.024313, 252.996862, 1392.144672], [53.875535, 54.925319, 55.071813, 56.840832, 311.331059], [129.698890, 135.323185, 137.829337, 139.993954, 758.278979], [132.234055, 138.750791, 141.446388, 143.234269, 755.855468], [88.939108, 98.111016, 98.237257, 102.040636, 578.678990]]
input_correlations: [[0.264313, -0.996207, -0.998507, -0.986653, -0.999490, -0.991779, -0.998700, 0.338729], [-0.266858, 0.994871, 0.998457, 0.988380, 0.999069, 0.989995, 0.997951, -0.341394], [0.287778, -0.998205, -0.998473, -0.980397, -0.998927, -0.994459, -0.999144, 0.361476], [-0.260378, 0.998069, 0.999126, 0.981507, 0.999849, 0.994950, 0.999717, -0.335026], [0.231190, -0.998595, -0.996630, -0.965435, -0.997177, -0.999408, -0.998426, 0.306330], [0.271627, -0.998363, -0.998854, -0.980697, -0.999589, -0.995075, -0.999625, 0.345636], [-0.261110, 0.998270, 0.999289, 0.979533, 0.999761, 0.995834, 0.999770, -0.335426], [0.262668, -0.993807, -0.997540, -0.990486, -0.998414, -0.987921, -0.997027, 0.337059]]
pre_activation_mean: [-11.040798, 9.009839, -5.233219, 15.468274, -3.459234, -8.425322, 8.398394, -6.429766]
pre_activation_std: [10.415142, 8.458654, 4.776647, 14.225512, 3.215312, 7.884085, 8.065898, 5.664427]
### 8
mean: [-12.849837, 5.479696, -16.021811, 12.316006, -8.794224, 14.833364, 19.158949, 13.609921]
std: [12.112945, 5.251400, 15.357130, 11.531126, 8.620063, 13.908401, 17.850029, 12.999567]
fourier: [[194.660051, 209.801151, 211.967930, 216.981064, 1156.485286], [84.858871, 91.321379, 92.577286, 93.024003, 493.172639], [246.897789, 266.503200, 269.423388, 274.385790, 1441.962831], [187.646724, 198.873386, 201.794675, 205.259943, 1108.440482], [141.353806, 147.535128, 150.151128, 154.199653, 791.480147], [225.862976, 239.649600, 242.953805, 248.764795, 1335.002783], [287.768135, 309.393748, 312.956563, 318.490758, 1724.305377], [209.635693, 224.673160, 227.180605, 233.054731, 1224.893179]]
input_correlations: [[0.190757, -0.999624, 0.067780, -0.999832, -0.670890, 0.155139, -0.999562, -0.478518], [-0.180652, 0.998903, -0.057292, 0.999973, 0.676230, -0.144970, 0.999940, 0.483856], [0.187500, -0.999515, 0.064376, -0.999922, -0.672679, 0.151863, -0.999709, -0.480799], [-0.193018, 0.999141, -0.070166, 0.999958, 0.671517, -0.157487, 0.999767, 0.476079], [0.204800, -0.999062, 0.082032, -0.999765, -0.668909, 0.169319, -0.999455, -0.470965], [-0.197095, 0.999367, -0.074182, 0.999865, 0.670278, -0.161537, 0.999569, 0.475584], [-0.188299, 0.999432, -0.065325, 0.999947, 0.672246, -0.152713, 0.999745, 0.479560], [-0.194536, 0.999578, -0.071691, 0.999807, 0.669839, -0.158968, 0.999497, 0.477130]]
pre_activation_mean: [-12.849837, 5.479696, -16.021811, 12.316006, -8.794224, 14.833364, 19.158949, 13.609921]
pre_activation_std: [12.112945, 5.251400, 15.357130, 11.531126, 8.620063, 13.908401, 17.850029, 12.999567]
### 10
mean: [-26.062996]
std: [24.868456]
fourier: [[400.989204, 431.361669, 435.896097, 443.698996, 2345.669647]]
input_correlations: [[0.168776, -0.999695, 0.271514, -0.999934, 0.269317, -0.999961, -0.999959, -0.999882]]
pre_activation_mean: [-26.062996]
pre_activation_std: [24.868456]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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-0.121732,
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0.1315,
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[
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-0.387464,
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[
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0.119604,
0.404882
],
[
-0.57218,
-0.538139,
-0.249778,
0.349116,
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[
0.928684,
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0.2781,
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],
[
-0.407319,
-0.407161,
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0.47095,
0.455765
],
[
0.533951,
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0.031963,
-0.279014
],
[
0.522909,
0.770205,
-0.149448,
0.386777,
-0.435825
]
],
"network.0.bias": [
0.019488,
-0.124962,
0.457324,
0.081652,
-0.106269,
0.110464,
0.356364,
0.581839
],
"network.2.weight": [
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0.239282,
0.067661,
-0.309246,
-0.327472,
-0.312229,
0.262327,
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],
[
0.2997,
0.272496,
-0.152273,
-0.167832,
0.43574,
0.169049,
0.385558,
0.135525
],
[
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0.239679,
0.348469,
-0.081581,
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0.189668,
0.34032,
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],
[
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-0.148046,
-0.200889,
-0.539082,
0.157022,
-0.365369,
-0.196942,
-0.06052
],
[
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0.171508,
0.293313,
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0.461083,
-0.437837,
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0.355928
],
[
0.310776,
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0.271315,
0.331959,
0.147697,
-0.290663,
-0.165079
],
[
0.097009,
0.429398,
0.013183,
-0.376581,
0.042041,
-0.294581,
0.408264,
0.791797
],
[
-0.111059,
0.652583,
0.447584,
-0.127199,
0.362672,
-0.56707,
0.173383,
-0.313929
]
],
"network.2.bias": [
-0.244327,
-0.296413,
0.331908,
-0.517424,
-0.156722,
0.251633,
0.057851,
0.065274
],
"network.4.weight": [
[
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0.031331,
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0.264875,
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],
[
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0.435834,
0.534147,
0.191992,
0.212095,
-0.350972,
0.018022,
0.549503
],
[
0.12315,
0.223894,
0.267319,
0.065034,
0.190934,
-0.442664,
0.55923,
0.565866
],
[
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-0.067612,
0.471393,
-0.009728,
0.162257,
-0.191774,
0.259921,
0.059447
],
[
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0.402548,
0.62655,
-0.298774,
0.718839,
-0.184554,
0.62064,
0.699125
],
[
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0.055215,
0.158554,
0.217175,
0.593303,
-0.263712,
0.393033,
0.748436
],
[
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0.403748,
0.628581,
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0.526214,
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0.285204,
0.609581
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[
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-0.565978,
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-0.639524,
0.133271,
-0.522739,
-0.742325
]
],
"network.4.bias": [
0.55398,
0.296185,
0.109659,
0.060809,
0.099066,
0.321586,
0.115396,
0.687681
],
"network.6.weight": [
[
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-0.832769,
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-0.090132,
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],
[
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0.515104,
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-0.111564
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[
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[
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[
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0.286818,
0.07385,
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],
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0.124931,
0.431274,
-0.020475
]
],
"network.6.bias": [
0.451614,
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],
"network.8.weight": [
[
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],
[
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0.22809,
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0.268488
],
[
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0.392867,
-0.594998,
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],
[
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-0.322209
],
[
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],
[
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0.208119,
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],
[
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],
[
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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]
],
"network.10.bias": [
0.383789
]
}
## Activation Signature
### 0
mean: [0.021392, 5.472024, 0.053825, 12.332438, 0.069053, 14.876183, 19.176321, 13.665038]
std: [0.151373, 5.254956, 0.224481, 11.511294, 0.294013, 13.859066, 17.829762, 12.937762]
fourier: [[2.258727, 2.346152, 2.394490, 2.497403, 2.708904], [84.341587, 91.283554, 92.836942, 93.152295, 492.482158], [3.497713, 3.623434, 3.729831, 4.135371, 4.844288], [185.256738, 200.335983, 202.444731, 204.200044, 1109.919467], [4.289742, 4.526904, 4.604526, 5.338251, 6.214777], [221.863827, 241.574597, 243.460696, 246.538421, 1338.856465], [285.369605, 310.833877, 313.597298, 317.339511, 1725.868955], [205.214008, 226.196728, 227.429217, 230.634320, 1229.853361]]
input_correlations: [[-0.861134, -0.382913, -0.312844, 0.215427, 0.308550, 0.000000, 0.000000, 0.000000], [0.410425, 0.779134, 0.521208, -0.217868, -0.184840, 0.000000, 0.000000, 0.000000], [0.607784, -0.367371, -0.079343, -0.036219, 0.549193, 0.000000, 0.000000, 0.000000], [-0.760220, -0.608168, -0.449500, 0.269288, 0.224276, 0.000000, 0.000000, 0.000000], [0.933739, 0.329286, 0.500607, -0.297952, 0.084045, 0.000000, 0.000000, 0.000000], [-0.610026, -0.439869, -0.385617, 0.488715, 0.402138, 0.000000, 0.000000, 0.000000], [0.689574, 0.846866, 0.526659, 0.186782, -0.057963, 0.000000, 0.000000, 0.000000], [0.539822, 0.848693, 0.084127, 0.473195, -0.237957, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.569845, 0.977111, 0.485665, -0.940312, 1.073432, -0.073033, 3.150539, 2.615778]
pre_activation_std: [1.903894, 1.732920, 1.698007, 2.050630, 2.277725, 1.835750, 2.554596, 2.329759]
### 2
mean: [-0.902991, 2.146437, 3.727684, -1.978252, 2.957242, -0.712417, 3.699663, 1.011441]
std: [0.885038, 2.182370, 2.831778, 1.327195, 3.446214, 1.179162, 3.560797, 2.106066]
fourier: [[12.108081, 12.422464, 13.188417, 16.444689, 81.269235], [34.166183, 38.044206, 39.382147, 39.834335, 193.179313], [46.079676, 49.633488, 50.728810, 54.111480, 335.491658], [19.735066, 20.524079, 23.708762, 27.263593, 178.042687], [51.351330, 58.031657, 58.684355, 68.734452, 266.151774], [18.144139, 19.033470, 20.724139, 22.159622, 64.117482], [57.782303, 60.019628, 64.118424, 69.672023, 332.969608], [32.744965, 33.553128, 37.609765, 45.868871, 91.029720]]
input_correlations: [[-0.361331, 0.124532, -0.503648, -0.532158, -0.276020, -0.558526, -0.196580, -0.498436], [-0.251801, 0.859798, 0.212288, -0.281495, 0.818015, -0.334636, 0.979304, 0.808848], [-0.351507, 0.749458, 0.145913, -0.299544, 0.649566, -0.305775, 0.948880, 0.963902], [-0.846898, -0.052925, -0.321768, -0.853265, 0.028624, -0.849549, -0.078450, -0.173957], [-0.500121, 0.779814, 0.248318, -0.496102, 0.849868, -0.553763, 0.952391, 0.797072], [0.629262, -0.761342, 0.230765, 0.636439, -0.393844, 0.610050, -0.850341, -0.834926], [-0.430265, 0.832152, 0.006617, -0.440668, 0.638060, -0.447167, 0.970025, 0.927985], [-0.479070, 0.726307, 0.344827, -0.519423, 0.884099, -0.660743, 0.743701, 0.371105]]
pre_activation_mean: [-0.902991, 2.146437, 3.727684, -1.978252, 2.957242, -0.712417, 3.699663, 1.011441]
pre_activation_std: [0.885038, 2.182370, 2.831778, 1.327195, 3.446214, 1.179162, 3.560797, 2.106066]
### 4
mean: [-6.849235, 4.595902, 4.956168, 3.207539, 8.741286, 5.287680, 6.766322, -7.484971]
std: [7.031214, 4.012016, 4.603116, 2.712335, 8.030023, 4.939764, 6.169106, 7.755126]
fourier: [[114.717133, 120.198691, 123.307029, 124.020518, 616.431187], [67.188516, 67.518588, 69.662654, 69.770346, 413.631128], [74.793525, 78.298659, 80.205824, 83.862805, 446.055094], [44.498337, 44.739203, 47.017971, 50.188774, 288.678451], [130.473660, 138.006082, 140.128138, 142.031384, 786.715736], [82.564960, 83.306547, 86.547811, 86.580858, 475.891183], [101.328377, 105.571819, 107.873590, 109.674705, 608.968952], [125.093292, 133.745336, 135.876857, 137.320558, 673.647341]]
input_correlations: [[-0.029532, -0.986383, -0.950446, -0.421200, -0.990882, 0.290847, -0.963159, -0.827490], [0.037831, 0.983644, 0.942118, 0.408639, 0.990723, -0.308811, 0.950054, 0.848577], [0.048367, 0.982468, 0.953745, 0.408488, 0.983984, -0.329575, 0.970125, 0.816756], [-0.062807, 0.945636, 0.992579, 0.468154, 0.952510, -0.334850, 0.989268, 0.698326], [0.019434, 0.983206, 0.956565, 0.423732, 0.989483, -0.294108, 0.967890, 0.816546], [0.051026, 0.981570, 0.924159, 0.369961, 0.995275, -0.299706, 0.939750, 0.869436], [0.035602, 0.984091, 0.951061, 0.417388, 0.990788, -0.297864, 0.961552, 0.830158], [-0.035054, -0.986631, -0.950711, -0.427477, -0.990357, 0.283727, -0.963499, -0.827883]]
pre_activation_mean: [-6.849235, 4.595902, 4.956168, 3.207539, 8.741286, 5.287680, 6.766322, -7.484971]
pre_activation_std: [7.031214, 4.012016, 4.603116, 2.712335, 8.030023, 4.939764, 6.169106, 7.755126]
### 6
mean: [-11.040798, 9.009839, -5.233219, 15.468274, -3.459234, -8.425322, 8.398394, -6.429766]
std: [10.415142, 8.458654, 4.776647, 14.225512, 3.215312, 7.884085, 8.065898, 5.664427]
fourier: [[167.609192, 179.967880, 181.299986, 186.372167, 993.671904], [134.394513, 146.737841, 147.192361, 153.185933, 810.885541], [79.059901, 81.801121, 83.460930, 85.428157, 470.989735], [231.780209, 245.089867, 249.024313, 252.996862, 1392.144672], [53.875535, 54.925319, 55.071813, 56.840832, 311.331059], [129.698890, 135.323185, 137.829337, 139.993954, 758.278979], [132.234055, 138.750791, 141.446388, 143.234269, 755.855468], [88.939108, 98.111016, 98.237257, 102.040636, 578.678990]]
input_correlations: [[0.264313, -0.996207, -0.998507, -0.986653, -0.999490, -0.991779, -0.998700, 0.338729], [-0.266858, 0.994871, 0.998457, 0.988380, 0.999069, 0.989995, 0.997951, -0.341394], [0.287778, -0.998205, -0.998473, -0.980397, -0.998927, -0.994459, -0.999144, 0.361476], [-0.260378, 0.998069, 0.999126, 0.981507, 0.999849, 0.994950, 0.999717, -0.335026], [0.231190, -0.998595, -0.996630, -0.965435, -0.997177, -0.999408, -0.998426, 0.306330], [0.271627, -0.998363, -0.998854, -0.980697, -0.999589, -0.995075, -0.999625, 0.345636], [-0.261110, 0.998270, 0.999289, 0.979533, 0.999761, 0.995834, 0.999770, -0.335426], [0.262668, -0.993807, -0.997540, -0.990486, -0.998414, -0.987921, -0.997027, 0.337059]]
pre_activation_mean: [-11.040798, 9.009839, -5.233219, 15.468274, -3.459234, -8.425322, 8.398394, -6.429766]
pre_activation_std: [10.415142, 8.458654, 4.776647, 14.225512, 3.215312, 7.884085, 8.065898, 5.664427]
### 8
mean: [-12.849837, 5.479696, -16.021811, 12.316006, -8.794224, 14.833364, 19.158949, 13.609921]
std: [12.112945, 5.251400, 15.357130, 11.531126, 8.620063, 13.908401, 17.850029, 12.999567]
fourier: [[194.660051, 209.801151, 211.967930, 216.981064, 1156.485286], [84.858871, 91.321379, 92.577286, 93.024003, 493.172639], [246.897789, 266.503200, 269.423388, 274.385790, 1441.962831], [187.646724, 198.873386, 201.794675, 205.259943, 1108.440482], [141.353806, 147.535128, 150.151128, 154.199653, 791.480147], [225.862976, 239.649600, 242.953805, 248.764795, 1335.002783], [287.768135, 309.393748, 312.956563, 318.490758, 1724.305377], [209.635693, 224.673160, 227.180605, 233.054731, 1224.893179]]
input_correlations: [[0.190757, -0.999624, 0.067780, -0.999832, -0.670890, 0.155139, -0.999562, -0.478518], [-0.180652, 0.998903, -0.057292, 0.999973, 0.676230, -0.144970, 0.999940, 0.483856], [0.187500, -0.999515, 0.064376, -0.999922, -0.672679, 0.151863, -0.999709, -0.480799], [-0.193018, 0.999141, -0.070166, 0.999958, 0.671517, -0.157487, 0.999767, 0.476079], [0.204800, -0.999062, 0.082032, -0.999765, -0.668909, 0.169319, -0.999455, -0.470965], [-0.197095, 0.999367, -0.074182, 0.999865, 0.670278, -0.161537, 0.999569, 0.475584], [-0.188299, 0.999432, -0.065325, 0.999947, 0.672246, -0.152713, 0.999745, 0.479560], [-0.194536, 0.999578, -0.071691, 0.999807, 0.669839, -0.158968, 0.999497, 0.477130]]
pre_activation_mean: [-12.849837, 5.479696, -16.021811, 12.316006, -8.794224, 14.833364, 19.158949, 13.609921]
pre_activation_std: [12.112945, 5.251400, 15.357130, 11.531126, 8.620063, 13.908401, 17.850029, 12.999567]
### 10
mean: [-26.062996]
std: [24.868456]
fourier: [[400.989204, 431.361669, 435.896097, 443.698996, 2345.669647]]
input_correlations: [[0.168776, -0.999695, 0.271514, -0.999934, 0.269317, -0.999961, -0.999959, -0.999882]]
pre_activation_mean: [-26.062996]
pre_activation_std: [24.868456]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.021392351016402245, "std": 0.15137283504009247, "fourier": [2.2587268736523565, 2.346152149726873, 2.3944900054043727, 2.497403109299472, 2.7089041053136595], "input_correlations": [-0.8611337008973868, -0.3829127931544435, -0.3128439361703276, 0.21542701667973066, 0.3085502079848371, 0.0, 0.0, 0.0], "pre_activation_mean": -0.5698445439338684, "pre_activation_std": 1.903894066810608}, "1": {"mean": 5.472023963928223, "std": 5.254955768585205, "fourier": [84.3415866059702, 91.28355350903466, 92.83694203844783, 93.1522950445645, 492.4821577426046], "input_correlations": [0.4104252654362206, 0.7791335880224873, 0.5212083142683969, -0.21786779623705776, -0.18484035350413694, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9771105647087097, "pre_activation_std": 1.7329195737838745}, "2": {"mean": 0.05382542684674263, "std": 0.22448064386844635, "fourier": [3.497713220527303, 3.6234338418605976, 3.729831065532515, 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"pre_activation_mean": 1.0734319686889648, "pre_activation_std": 2.2777247428894043}, "5": {"mean": 14.876182556152344, "std": 13.859066009521484, "fourier": [221.86382667443166, 241.57459706518915, 243.4606963400403, 246.53842142450813, 1338.8564650043845], "input_correlations": [-0.6100259850673944, -0.43986875403868625, -0.38561708754777907, 0.488715309598349, 0.4021384212728399, 0.0, 0.0, 0.0], "pre_activation_mean": -0.07303257286548615, "pre_activation_std": 1.8357497453689575}, "6": {"mean": 19.176321029663086, "std": 17.829761505126953, "fourier": [285.36960530452285, 310.83387658766185, 313.5972980843858, 317.3395110909426, 1725.8689550049603], "input_correlations": [0.6895735226618879, 0.8468658156588008, 0.5266588349516954, 0.1867820301616007, -0.05796283662302028, 0.0, 0.0, 0.0], "pre_activation_mean": 3.1505393981933594, "pre_activation_std": 2.554596185684204}, "7": {"mean": 13.665038108825684, "std": 12.937762260437012, "fourier": [205.21400787783793, 226.19672824772007, 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"degraded_stage": {"initial_val_loss": 0.5355622172355652, "final_val_loss": 0.3604751527309418, "initial_val_acc": 0.6, "final_val_acc": 0.6, "best_val_acc": 0.6}, "improved_stage": {"initial_val_loss": 0.3581351041793823, "final_val_loss": 0.2529201805591583, "initial_val_acc": 0.84, "final_val_acc": 0.88, "best_val_acc": 0.92, "best_epoch": 4}, "improvement": 0.32000000000000006, "first_improvement_epoch": 1}} |
14 | {"target_pattern": "has_majority", "degraded_accuracy": 0.52, "improved_accuracy": 0.86, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4349, "learning_rate": 0.03446770243187198, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.755622, 0.655917, 0.490641, 1.324046, 2.081377, 1.281034, 0.316883]
std: [0.613214, 1.400398, 0.412178, 2.467979, 3.545822, 2.346410, 0.293504]
fourier: [[10.801982, 11.031823, 12.910112, 12.982148, 68.005968], [21.507805, 21.705268, 25.170097, 28.484055, 59.032496], [7.238196, 7.407128, 8.590786, 8.781933, 44.157655], [39.116121, 39.410396, 44.383218, 50.469160, 119.164161], [57.388639, 59.304960, 62.871585, 73.472989, 187.323958], [37.430411, 38.250723, 42.041045, 48.221142, 115.293085], [5.111649, 5.286718, 6.069699, 6.128546, 28.519464]]
input_correlations: [[-0.478652, -0.690046, -0.081562, -0.689271, -0.484147, 0.000000, 0.000000, 0.000000], [0.007971, 0.816805, 0.339302, 0.719059, 0.041102, 0.000000, 0.000000, 0.000000], [0.526780, 0.681511, 0.661088, 0.049464, 0.551428, 0.000000, 0.000000, 0.000000], [0.204228, -0.113629, 0.385044, -0.887690, 0.144876, 0.000000, 0.000000, 0.000000], [-0.107843, -0.277418, 0.144825, -0.958321, -0.076254, 0.000000, 0.000000, 0.000000], [-0.239202, 0.029898, -0.732132, -0.461967, 0.001140, 0.000000, 0.000000, 0.000000], [0.541398, 0.940321, 0.264920, 0.123602, -0.155674, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.510386, 2.332229, 2.162349, -1.117795, -0.962808, -0.693236, 1.034900]
pre_activation_std: [1.865762, 1.766084, 1.674300, 2.042928, 1.612959, 1.534301, 1.016806]
### 2
mean: [-0.408024, 1.476681, 1.148695, -0.760126, 0.192177, -0.945835, 1.107893]
std: [0.604382, 1.325907, 0.935593, 0.868707, 0.475212, 0.786392, 0.790396]
fourier: [[9.095725, 9.504050, 9.594229, 13.029446, 36.722157], [20.136984, 23.229647, 23.876229, 27.091336, 132.901297], [13.988022, 15.574802, 17.637995, 19.792151, 103.382519], [13.031094, 14.691614, 15.143602, 17.959711, 68.411347], [7.051737, 7.210788, 7.335279, 8.802103, 17.295938], [11.150473, 11.786918, 12.987521, 18.372462, 85.125180], [12.180636, 12.497453, 15.426132, 15.762340, 99.710344]]
input_correlations: [[0.127298, 0.026813, -0.543682, 0.079288, 0.198494, -0.513952, -0.581408, 0.000000], [0.095778, 0.883725, 0.672388, -0.251725, -0.421321, -0.344799, 0.756230, 0.000000], [0.155760, 0.877991, 0.739586, -0.132809, -0.301376, -0.315941, 0.852450, 0.000000], [-0.152203, -0.833317, -0.779411, 0.116952, 0.282093, 0.369393, -0.712070, 0.000000], [0.152978, -0.223950, 0.152170, 0.420297, 0.483809, 0.799930, 0.086347, 0.000000], [-0.126956, -0.797253, -0.676322, 0.156799, 0.319248, 0.543859, -0.725185, 0.000000], [0.126669, 0.948870, 0.607420, -0.149265, -0.330751, -0.342806, 0.776612, 0.000000]]
pre_activation_mean: [-0.408024, 1.476681, 1.148695, -0.760126, 0.192177, -0.945835, 1.107893]
pre_activation_std: [0.604382, 1.325907, 0.935593, 0.868707, 0.475212, 0.786392, 0.790396]
### 4
mean: [1.198331, 0.592070, 0.596075, 0.291568, -1.683659, -0.203949, 1.136215]
std: [1.456118, 0.758008, 0.732626, 0.391819, 0.956045, 0.308377, 1.079901]
fourier: [[23.499926, 25.159380, 25.525234, 31.448986, 107.849784], [11.904929, 12.275209, 13.680890, 16.850059, 53.286272], [12.271972, 12.670929, 13.544787, 14.239707, 53.646776], [6.053946, 6.342673, 7.026728, 7.894145, 26.241151], [15.577459, 16.449715, 16.757478, 18.825184, 151.529333], [4.280225, 4.655328, 5.214563, 6.897851, 18.355413], [17.417010, 18.006338, 19.219153, 23.327097, 102.259349]]
input_correlations: [[-0.101585, 0.994363, 0.974903, -0.215439, -0.374326, 0.043978, 0.944341, 0.000000], [-0.017551, 0.976157, 0.934750, -0.192335, -0.497151, 0.000082, 0.927851, 0.000000], [-0.156401, 0.993342, 0.970644, -0.200135, -0.293987, 0.105648, 0.935641, 0.000000], [-0.278648, 0.939297, 0.911540, 0.030361, -0.356157, 0.260116, 0.835918, 0.000000], [0.126440, -0.993134, -0.989724, 0.290811, 0.261105, -0.002822, -0.960620, 0.000000], [-0.051609, -0.808716, -0.728097, -0.116693, 0.666467, -0.179797, -0.735925, 0.000000], [-0.142503, 0.985868, 0.961020, -0.149692, -0.395008, 0.092496, 0.917987, 0.000000]]
pre_activation_mean: [1.198331, 0.592070, 0.596075, 0.291568, -1.683659, -0.203949, 1.136215]
pre_activation_std: [1.456118, 0.758008, 0.732626, 0.391819, 0.956045, 0.308377, 1.079901]
### 6
mean: [-1.603998, 0.897215, -1.587561, 1.402120, -1.430347, 1.593460, 0.523030]
std: [0.877729, 1.236978, 1.070924, 2.001360, 1.074211, 1.780674, 0.978553]
fourier: [[14.352795, 15.117109, 15.402018, 18.586102, 144.359797], [20.693474, 21.062499, 21.794445, 26.852848, 80.749366], [17.760396, 18.688150, 18.772630, 22.396095, 142.880440], [33.305066, 34.237489, 35.231701, 43.010144, 126.190847], [17.695870, 18.562912, 18.753155, 22.452516, 128.731235], [29.808293, 30.472739, 31.396757, 38.302171, 143.411408], [16.272189, 16.750486, 17.096954, 21.071976, 47.072712]]
input_correlations: [[-0.997746, -0.993654, -0.995935, -0.981063, -0.890904, 0.609204, -0.998695, 0.000000], [0.999285, 0.994821, 0.993622, 0.974233, 0.902899, -0.626392, 0.999333, 0.000000], [-0.998338, -0.993218, -0.997610, -0.975259, -0.897394, 0.586951, -0.996988, 0.000000], [0.999169, 0.994470, 0.995009, 0.976162, 0.900584, -0.617873, 0.999306, 0.000000], [-0.997743, -0.988446, -0.997726, -0.978181, -0.900115, 0.569340, -0.997099, 0.000000], [0.999437, 0.994891, 0.994765, 0.973300, 0.904117, -0.618251, 0.999038, 0.000000], [0.999381, 0.992126, 0.995228, 0.976523, 0.904132, -0.606421, 0.999482, 0.000000]]
pre_activation_mean: [-1.603998, 0.897215, -1.587561, 1.402120, -1.430347, 1.593460, 0.523030]
pre_activation_std: [0.877729, 1.236978, 1.070924, 2.001360, 1.074211, 1.780674, 0.978553]
### 8
mean: [-0.683968, 0.965950, 1.297869, 1.285826, 0.328276, 0.960886, 0.264012]
std: [0.721055, 1.682021, 2.320485, 2.107455, 1.311381, 1.854226, 0.962288]
fourier: [[12.314770, 12.323176, 12.575386, 15.588049, 61.557141], [28.431597, 28.845402, 29.003842, 36.129150, 86.935532], [39.528490, 39.783809, 40.172415, 50.025957, 116.808235], [35.858075, 36.132233, 36.419658, 45.404325, 115.724300], [22.299839, 22.489057, 22.509844, 28.244149, 29.544801], [31.441311, 31.902916, 32.005128, 39.861974, 86.479740], [16.397122, 16.460139, 16.536215, 20.782274, 23.761080]]
input_correlations: [[-0.956183, -0.999211, -0.950558, -0.999478, -0.951892, -0.999878, -0.994742, 0.000000], [0.947693, 0.999967, 0.942930, 0.999954, 0.950288, 0.998709, 0.997687, 0.000000], [0.952825, 0.999712, 0.947703, 0.999860, 0.951866, 0.999502, 0.996206, 0.000000], [0.952450, 0.999753, 0.947349, 0.999879, 0.951917, 0.999424, 0.996415, 0.000000], [0.951105, 0.999871, 0.946538, 0.999882, 0.953356, 0.998908, 0.997049, 0.000000], [0.949808, 0.999862, 0.944689, 0.999968, 0.950048, 0.999219, 0.996999, 0.000000], [-0.953130, -0.999528, -0.949630, -0.999502, -0.958428, -0.998192, -0.996550, 0.000000]]
pre_activation_mean: [-0.683968, 0.965950, 1.297869, 1.285826, 0.328276, 0.960886, 0.264012]
pre_activation_std: [0.721055, 1.682021, 2.320485, 2.107455, 1.311381, 1.854226, 0.962288]
### 10
mean: [-0.116620, 0.215378, -0.286212, 1.006137, 1.796901, 0.850608, -0.231582]
std: [2.231172, 1.694710, 1.958335, 2.675325, 3.740284, 2.634349, 1.462833]
fourier: [[32.458096, 37.716962, 38.221351, 38.554274, 48.026151], [24.748995, 28.755208, 28.995341, 29.455238, 36.513134], [27.567597, 32.620873, 33.027910, 34.139450, 41.575532], [44.634043, 45.295248, 46.626174, 56.778978, 90.552294], [63.095512, 64.147909, 64.674761, 80.008523, 161.721087], [44.881468, 45.095388, 45.899576, 56.770613, 76.554713], [20.842390, 24.457066, 24.729644, 25.441926, 31.125289]]
input_correlations: [[-0.168403, -0.998074, -0.998910, -0.999268, -0.989859, -0.997760, 0.878179, 0.000000], [0.162121, 0.997673, 0.998669, 0.999078, 0.988871, 0.997349, -0.881183, 0.000000], [-0.204531, -0.999792, -0.999909, -0.999882, -0.994859, -0.999678, 0.857419, 0.000000], [0.202312, 0.999765, 0.999956, 0.999941, 0.994654, 0.999661, -0.858028, 0.000000], [0.179842, 0.998965, 0.999590, 0.999810, 0.991884, 0.998750, -0.870171, 0.000000], [0.156734, 0.997447, 0.998552, 0.999007, 0.988269, 0.997122, -0.882636, 0.000000], [-0.197709, -0.999657, -0.999881, -0.999931, -0.994211, -0.999508, 0.860574, 0.000000]]
pre_activation_mean: [-0.116620, 0.215378, -0.286212, 1.006137, 1.796901, 0.850608, -0.231582]
pre_activation_std: [2.231172, 1.694710, 1.958335, 2.675325, 3.740284, 2.634349, 1.462833]
### 12
mean: [-0.841112]
std: [3.809065]
fourier: [[63.632658, 66.121160, 66.190399, 75.700092, 80.706299]]
input_correlations: [[0.820042, -0.989549, 0.810795, -0.994131, -0.998104, -0.995996, 0.792771, 0.000000]]
pre_activation_mean: [-0.841112]
pre_activation_std: [3.809065]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.weight": [
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}
## Activation Signature
### 0
mean: [0.755622, 0.655917, 0.490641, 1.324046, 2.081377, 1.281034, 0.316883]
std: [0.613214, 1.400398, 0.412178, 2.467979, 3.545822, 2.346410, 0.293504]
fourier: [[10.801982, 11.031823, 12.910112, 12.982148, 68.005968], [21.507805, 21.705268, 25.170097, 28.484055, 59.032496], [7.238196, 7.407128, 8.590786, 8.781933, 44.157655], [39.116121, 39.410396, 44.383218, 50.469160, 119.164161], [57.388639, 59.304960, 62.871585, 73.472989, 187.323958], [37.430411, 38.250723, 42.041045, 48.221142, 115.293085], [5.111649, 5.286718, 6.069699, 6.128546, 28.519464]]
input_correlations: [[-0.478652, -0.690046, -0.081562, -0.689271, -0.484147, 0.000000, 0.000000, 0.000000], [0.007971, 0.816805, 0.339302, 0.719059, 0.041102, 0.000000, 0.000000, 0.000000], [0.526780, 0.681511, 0.661088, 0.049464, 0.551428, 0.000000, 0.000000, 0.000000], [0.204228, -0.113629, 0.385044, -0.887690, 0.144876, 0.000000, 0.000000, 0.000000], [-0.107843, -0.277418, 0.144825, -0.958321, -0.076254, 0.000000, 0.000000, 0.000000], [-0.239202, 0.029898, -0.732132, -0.461967, 0.001140, 0.000000, 0.000000, 0.000000], [0.541398, 0.940321, 0.264920, 0.123602, -0.155674, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.510386, 2.332229, 2.162349, -1.117795, -0.962808, -0.693236, 1.034900]
pre_activation_std: [1.865762, 1.766084, 1.674300, 2.042928, 1.612959, 1.534301, 1.016806]
### 2
mean: [-0.408024, 1.476681, 1.148695, -0.760126, 0.192177, -0.945835, 1.107893]
std: [0.604382, 1.325907, 0.935593, 0.868707, 0.475212, 0.786392, 0.790396]
fourier: [[9.095725, 9.504050, 9.594229, 13.029446, 36.722157], [20.136984, 23.229647, 23.876229, 27.091336, 132.901297], [13.988022, 15.574802, 17.637995, 19.792151, 103.382519], [13.031094, 14.691614, 15.143602, 17.959711, 68.411347], [7.051737, 7.210788, 7.335279, 8.802103, 17.295938], [11.150473, 11.786918, 12.987521, 18.372462, 85.125180], [12.180636, 12.497453, 15.426132, 15.762340, 99.710344]]
input_correlations: [[0.127298, 0.026813, -0.543682, 0.079288, 0.198494, -0.513952, -0.581408, 0.000000], [0.095778, 0.883725, 0.672388, -0.251725, -0.421321, -0.344799, 0.756230, 0.000000], [0.155760, 0.877991, 0.739586, -0.132809, -0.301376, -0.315941, 0.852450, 0.000000], [-0.152203, -0.833317, -0.779411, 0.116952, 0.282093, 0.369393, -0.712070, 0.000000], [0.152978, -0.223950, 0.152170, 0.420297, 0.483809, 0.799930, 0.086347, 0.000000], [-0.126956, -0.797253, -0.676322, 0.156799, 0.319248, 0.543859, -0.725185, 0.000000], [0.126669, 0.948870, 0.607420, -0.149265, -0.330751, -0.342806, 0.776612, 0.000000]]
pre_activation_mean: [-0.408024, 1.476681, 1.148695, -0.760126, 0.192177, -0.945835, 1.107893]
pre_activation_std: [0.604382, 1.325907, 0.935593, 0.868707, 0.475212, 0.786392, 0.790396]
### 4
mean: [1.198331, 0.592070, 0.596075, 0.291568, -1.683659, -0.203949, 1.136215]
std: [1.456118, 0.758008, 0.732626, 0.391819, 0.956045, 0.308377, 1.079901]
fourier: [[23.499926, 25.159380, 25.525234, 31.448986, 107.849784], [11.904929, 12.275209, 13.680890, 16.850059, 53.286272], [12.271972, 12.670929, 13.544787, 14.239707, 53.646776], [6.053946, 6.342673, 7.026728, 7.894145, 26.241151], [15.577459, 16.449715, 16.757478, 18.825184, 151.529333], [4.280225, 4.655328, 5.214563, 6.897851, 18.355413], [17.417010, 18.006338, 19.219153, 23.327097, 102.259349]]
input_correlations: [[-0.101585, 0.994363, 0.974903, -0.215439, -0.374326, 0.043978, 0.944341, 0.000000], [-0.017551, 0.976157, 0.934750, -0.192335, -0.497151, 0.000082, 0.927851, 0.000000], [-0.156401, 0.993342, 0.970644, -0.200135, -0.293987, 0.105648, 0.935641, 0.000000], [-0.278648, 0.939297, 0.911540, 0.030361, -0.356157, 0.260116, 0.835918, 0.000000], [0.126440, -0.993134, -0.989724, 0.290811, 0.261105, -0.002822, -0.960620, 0.000000], [-0.051609, -0.808716, -0.728097, -0.116693, 0.666467, -0.179797, -0.735925, 0.000000], [-0.142503, 0.985868, 0.961020, -0.149692, -0.395008, 0.092496, 0.917987, 0.000000]]
pre_activation_mean: [1.198331, 0.592070, 0.596075, 0.291568, -1.683659, -0.203949, 1.136215]
pre_activation_std: [1.456118, 0.758008, 0.732626, 0.391819, 0.956045, 0.308377, 1.079901]
### 6
mean: [-1.603998, 0.897215, -1.587561, 1.402120, -1.430347, 1.593460, 0.523030]
std: [0.877729, 1.236978, 1.070924, 2.001360, 1.074211, 1.780674, 0.978553]
fourier: [[14.352795, 15.117109, 15.402018, 18.586102, 144.359797], [20.693474, 21.062499, 21.794445, 26.852848, 80.749366], [17.760396, 18.688150, 18.772630, 22.396095, 142.880440], [33.305066, 34.237489, 35.231701, 43.010144, 126.190847], [17.695870, 18.562912, 18.753155, 22.452516, 128.731235], [29.808293, 30.472739, 31.396757, 38.302171, 143.411408], [16.272189, 16.750486, 17.096954, 21.071976, 47.072712]]
input_correlations: [[-0.997746, -0.993654, -0.995935, -0.981063, -0.890904, 0.609204, -0.998695, 0.000000], [0.999285, 0.994821, 0.993622, 0.974233, 0.902899, -0.626392, 0.999333, 0.000000], [-0.998338, -0.993218, -0.997610, -0.975259, -0.897394, 0.586951, -0.996988, 0.000000], [0.999169, 0.994470, 0.995009, 0.976162, 0.900584, -0.617873, 0.999306, 0.000000], [-0.997743, -0.988446, -0.997726, -0.978181, -0.900115, 0.569340, -0.997099, 0.000000], [0.999437, 0.994891, 0.994765, 0.973300, 0.904117, -0.618251, 0.999038, 0.000000], [0.999381, 0.992126, 0.995228, 0.976523, 0.904132, -0.606421, 0.999482, 0.000000]]
pre_activation_mean: [-1.603998, 0.897215, -1.587561, 1.402120, -1.430347, 1.593460, 0.523030]
pre_activation_std: [0.877729, 1.236978, 1.070924, 2.001360, 1.074211, 1.780674, 0.978553]
### 8
mean: [-0.683968, 0.965950, 1.297869, 1.285826, 0.328276, 0.960886, 0.264012]
std: [0.721055, 1.682021, 2.320485, 2.107455, 1.311381, 1.854226, 0.962288]
fourier: [[12.314770, 12.323176, 12.575386, 15.588049, 61.557141], [28.431597, 28.845402, 29.003842, 36.129150, 86.935532], [39.528490, 39.783809, 40.172415, 50.025957, 116.808235], [35.858075, 36.132233, 36.419658, 45.404325, 115.724300], [22.299839, 22.489057, 22.509844, 28.244149, 29.544801], [31.441311, 31.902916, 32.005128, 39.861974, 86.479740], [16.397122, 16.460139, 16.536215, 20.782274, 23.761080]]
input_correlations: [[-0.956183, -0.999211, -0.950558, -0.999478, -0.951892, -0.999878, -0.994742, 0.000000], [0.947693, 0.999967, 0.942930, 0.999954, 0.950288, 0.998709, 0.997687, 0.000000], [0.952825, 0.999712, 0.947703, 0.999860, 0.951866, 0.999502, 0.996206, 0.000000], [0.952450, 0.999753, 0.947349, 0.999879, 0.951917, 0.999424, 0.996415, 0.000000], [0.951105, 0.999871, 0.946538, 0.999882, 0.953356, 0.998908, 0.997049, 0.000000], [0.949808, 0.999862, 0.944689, 0.999968, 0.950048, 0.999219, 0.996999, 0.000000], [-0.953130, -0.999528, -0.949630, -0.999502, -0.958428, -0.998192, -0.996550, 0.000000]]
pre_activation_mean: [-0.683968, 0.965950, 1.297869, 1.285826, 0.328276, 0.960886, 0.264012]
pre_activation_std: [0.721055, 1.682021, 2.320485, 2.107455, 1.311381, 1.854226, 0.962288]
### 10
mean: [-0.116620, 0.215378, -0.286212, 1.006137, 1.796901, 0.850608, -0.231582]
std: [2.231172, 1.694710, 1.958335, 2.675325, 3.740284, 2.634349, 1.462833]
fourier: [[32.458096, 37.716962, 38.221351, 38.554274, 48.026151], [24.748995, 28.755208, 28.995341, 29.455238, 36.513134], [27.567597, 32.620873, 33.027910, 34.139450, 41.575532], [44.634043, 45.295248, 46.626174, 56.778978, 90.552294], [63.095512, 64.147909, 64.674761, 80.008523, 161.721087], [44.881468, 45.095388, 45.899576, 56.770613, 76.554713], [20.842390, 24.457066, 24.729644, 25.441926, 31.125289]]
input_correlations: [[-0.168403, -0.998074, -0.998910, -0.999268, -0.989859, -0.997760, 0.878179, 0.000000], [0.162121, 0.997673, 0.998669, 0.999078, 0.988871, 0.997349, -0.881183, 0.000000], [-0.204531, -0.999792, -0.999909, -0.999882, -0.994859, -0.999678, 0.857419, 0.000000], [0.202312, 0.999765, 0.999956, 0.999941, 0.994654, 0.999661, -0.858028, 0.000000], [0.179842, 0.998965, 0.999590, 0.999810, 0.991884, 0.998750, -0.870171, 0.000000], [0.156734, 0.997447, 0.998552, 0.999007, 0.988269, 0.997122, -0.882636, 0.000000], [-0.197709, -0.999657, -0.999881, -0.999931, -0.994211, -0.999508, 0.860574, 0.000000]]
pre_activation_mean: [-0.116620, 0.215378, -0.286212, 1.006137, 1.796901, 0.850608, -0.231582]
pre_activation_std: [2.231172, 1.694710, 1.958335, 2.675325, 3.740284, 2.634349, 1.462833]
### 12
mean: [-0.841112]
std: [3.809065]
fourier: [[63.632658, 66.121160, 66.190399, 75.700092, 80.706299]]
input_correlations: [[0.820042, -0.989549, 0.810795, -0.994131, -0.998104, -0.995996, 0.792771, 0.000000]]
pre_activation_mean: [-0.841112]
pre_activation_std: [3.809065]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"val_loss": 0.43818503618240356, "val_acc": 0.8}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.4471369534730911, "train_acc": 0.805, "val_loss": 0.44410350918769836, "val_acc": 0.82}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.42468130588531494, "train_acc": 0.815, "val_loss": 0.40695053339004517, "val_acc": 0.8}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.4370582699775696, "train_acc": 0.83, "val_loss": 0.4192253053188324, "val_acc": 0.86}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.6923817992210388, "final_val_loss": 0.6523205637931824, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.6271699070930481, "final_val_loss": 0.4192253053188324, "initial_val_acc": 0.52, "final_val_acc": 0.86, "best_val_acc": 0.86, "best_epoch": 14}, "improvement": 0.33999999999999997, "first_improvement_epoch": 4}} |
15 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.7, "improved_accuracy": 0.9, "improvement": 0.20000000000000007, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4346, "learning_rate": 0.054312033149829644, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [2.345561, -0.018790, -0.089491, -0.051789, -0.078815, -0.003231]
std: [0.786444, 0.552830, 0.036141, 0.431510, 0.324407, 0.474881]
fourier: [[12.615883, 13.545142, 14.319641, 18.515439, 211.100462], [7.992145, 8.217577, 8.492616, 9.283568, 9.761242], [0.537747, 0.569131, 0.601950, 0.681830, 8.054168], [6.184824, 6.209829, 6.499681, 6.811473, 7.328091], [4.866969, 4.958031, 5.477418, 5.825588, 7.093372], [6.872195, 6.960940, 7.094025, 7.531321, 8.296420]]
input_correlations: [[-0.308254, -0.153603, -0.690846, 0.097792, -0.812881, 0.000000, 0.000000, 0.000000], [0.766562, 0.849127, 0.356135, 0.199208, 0.214689, 0.000000, 0.000000, 0.000000], [0.298756, 0.802986, 0.122447, 0.330782, -0.544550, 0.000000, 0.000000, 0.000000], [-0.881067, -0.664080, -0.472627, -0.232218, -0.335485, 0.000000, 0.000000, 0.000000], [-0.758948, -0.484681, -0.133495, 0.276472, 0.412049, 0.000000, 0.000000, 0.000000], [0.813149, 0.738986, 0.600970, 0.153411, 0.145365, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.958045, 3.162699, 0.916456, -2.291460, 0.209580, 3.993526]
pre_activation_std: [2.617327, 2.909224, 2.019639, 2.250489, 2.609981, 3.161500]
### 2
mean: [-1.468462, -1.533370, -1.462069, -3.563581, -3.113792, -5.143430]
std: [1.051828, 1.097904, 1.030294, 3.862676, 2.632803, 5.808600]
fourier: [[16.638304, 18.386499, 18.846713, 20.633623, 132.161531], [18.610548, 19.563776, 19.603435, 20.322529, 138.003314], [16.750377, 16.818792, 18.875080, 21.170854, 131.586230], [60.166575, 63.347467, 65.186549, 73.131019, 320.722335], [39.911084, 42.897532, 44.316607, 46.991672, 280.241300], [92.449322, 97.479128, 100.846944, 101.249390, 462.908697]]
input_correlations: [[-0.228068, -0.928469, -0.643718, -0.025877, 0.068515, -0.945651, 0.000000, 0.000000], [-0.078709, 0.029273, 0.375445, 0.207776, -0.891420, 0.126777, 0.000000, 0.000000], [-0.081066, 0.110144, 0.367188, 0.222612, -0.942128, 0.216900, 0.000000, 0.000000], [-0.150111, -0.947944, -0.761895, -0.143915, 0.549392, -0.974557, 0.000000, 0.000000], [-0.153898, -0.979956, -0.673404, -0.125596, 0.366244, -0.979521, 0.000000, 0.000000], [-0.174398, -0.967939, -0.816973, -0.134708, 0.490386, -0.970941, 0.000000, 0.000000]]
pre_activation_mean: [-1.468462, -1.533370, -1.462069, -3.563581, -3.113792, -5.143430]
pre_activation_std: [1.051828, 1.097904, 1.030294, 3.862676, 2.632803, 5.808600]
### 4
mean: [0.166436, -0.808766, 0.339555, 0.348314, -0.421675, 0.658524]
std: [0.571669, 0.046574, 0.309029, 0.427146, 0.262328, 0.259184]
fourier: [[8.607393, 8.874043, 9.169842, 10.323376, 14.979212], [0.676865, 0.718210, 0.728405, 0.745895, 72.788909], [4.612303, 4.911592, 5.127208, 5.928857, 30.559993], [6.176373, 6.338501, 6.432433, 7.108951, 31.348280], [3.751641, 4.045899, 4.054712, 4.742878, 37.950766], [4.056625, 4.513247, 4.570566, 5.505317, 59.267166]]
input_correlations: [[-0.120169, 0.269293, 0.329914, 0.968307, -0.220217, 0.986490, 0.000000, 0.000000], [-0.226632, -0.014921, -0.002375, -0.883890, -0.026493, -0.801532, 0.000000, 0.000000], [0.170583, -0.280039, -0.351183, -0.950421, 0.256791, -0.983432, 0.000000, 0.000000], [0.116719, -0.388279, -0.440056, -0.981831, 0.139735, -0.968926, 0.000000, 0.000000], [0.298230, -0.530493, -0.593091, -0.936725, 0.077694, -0.849860, 0.000000, 0.000000], [-0.197074, 0.070004, 0.145934, 0.887773, -0.310965, 0.973453, 0.000000, 0.000000]]
pre_activation_mean: [0.166436, -0.808766, 0.339555, 0.348314, -0.421675, 0.658524]
pre_activation_std: [0.571669, 0.046574, 0.309029, 0.427146, 0.262328, 0.259184]
### 6
mean: [-0.750788, 0.510318, 0.690320, 0.886182, 0.090803, -0.331479]
std: [0.264667, 0.624251, 0.479124, 0.511567, 0.388988, 0.158005]
fourier: [[4.105047, 4.255419, 4.506461, 5.248358, 67.570922], [9.306235, 9.967261, 10.367108, 11.916584, 45.928573], [7.032096, 7.439310, 7.659828, 8.687948, 62.128767], [7.894447, 7.895356, 8.469881, 9.671472, 79.756406], [6.027899, 6.278792, 6.688531, 7.833526, 8.172277], [2.602468, 2.708918, 3.087600, 3.827087, 29.833138]]
input_correlations: [[0.983348, 0.881668, -0.844144, -0.737286, 0.401491, 0.976835, 0.000000, 0.000000], [0.991564, 0.894394, -0.813982, -0.706551, 0.400795, 0.980101, 0.000000, 0.000000], [0.997387, 0.913988, -0.775100, -0.663794, 0.437053, 0.979451, 0.000000, 0.000000], [-0.974933, -0.877494, 0.852079, 0.792842, -0.314636, -0.945425, 0.000000, 0.000000], [-0.974276, -0.863456, 0.867350, 0.779128, -0.343612, -0.965177, 0.000000, 0.000000], [0.797189, 0.613738, -0.994057, -0.900798, 0.144116, 0.849817, 0.000000, 0.000000]]
pre_activation_mean: [-0.750788, 0.510318, 0.690320, 0.886182, 0.090803, -0.331479]
pre_activation_std: [0.264667, 0.624251, 0.479124, 0.511567, 0.388988, 0.158005]
### 8
mean: [0.921770, 0.693644, -0.047512, 0.079476, 0.142695, 0.986267]
std: [0.571723, 0.544278, 0.382467, 0.122318, 0.725607, 0.589002]
fourier: [[8.957335, 9.260778, 9.964262, 11.717565, 82.959268], [8.890216, 8.915176, 9.894062, 11.902868, 62.427953], [5.611541, 6.020679, 6.213880, 6.697085, 7.888098], [1.650158, 1.670672, 1.685350, 1.875171, 7.152832], [11.069297, 11.571730, 12.312697, 12.842554, 14.215644], [9.457237, 9.522636, 10.437068, 12.406167, 88.763995]]
input_correlations: [[-0.887647, -0.985316, -0.975747, 0.865919, 0.677807, -0.973289, 0.000000, 0.000000], [-0.788934, -0.937195, -0.918821, 0.942652, 0.796562, -0.991985, 0.000000, 0.000000], [-0.881056, -0.982789, -0.972554, 0.872847, 0.688039, -0.975866, 0.000000, 0.000000], [0.992871, 0.931505, 0.947750, -0.485417, -0.208575, 0.737461, 0.000000, 0.000000], [0.923027, 0.996442, 0.991066, -0.819220, -0.613538, 0.953902, 0.000000, 0.000000], [-0.843892, -0.965733, -0.951817, 0.908082, 0.736543, -0.985354, 0.000000, 0.000000]]
pre_activation_mean: [0.921770, 0.693644, -0.047512, 0.079476, 0.142695, 0.986267]
pre_activation_std: [0.571723, 0.544278, 0.382467, 0.122318, 0.725607, 0.589002]
### 10
mean: [2.326265, -0.536120, -0.223034, -0.353108, -0.555079, -0.167398]
std: [0.923723, 0.741860, 0.077542, 0.532618, 0.514305, 0.540127]
fourier: [[15.368218, 15.546675, 17.076640, 21.334506, 209.363810], [12.140799, 12.264207, 13.534637, 16.353074, 48.250839], [1.204706, 1.284276, 1.386743, 1.587912, 20.073022], [8.363486, 8.506308, 9.404879, 10.847495, 31.779728], [8.561452, 8.606356, 9.518155, 11.696255, 49.957150], [8.371714, 8.667161, 9.360143, 10.895416, 15.065825]]
input_correlations: [[0.964572, 0.926419, 0.793021, -0.661786, -0.885412, 0.957601, 0.000000, 0.000000], [-0.914560, -0.859046, -0.692373, 0.766462, 0.945770, -0.902842, 0.000000, 0.000000], [-0.823337, -0.748696, -0.550241, 0.871865, 0.987712, -0.804239, 0.000000, 0.000000], [-0.841749, -0.768693, -0.571814, 0.853675, 0.984567, -0.825282, 0.000000, 0.000000], [-0.945198, -0.899005, -0.750887, 0.710692, 0.914867, -0.935723, 0.000000, 0.000000], [-0.820096, -0.747198, -0.544257, 0.875025, 0.990356, -0.803459, 0.000000, 0.000000]]
pre_activation_mean: [2.326265, -0.536120, -0.223034, -0.353108, -0.555079, -0.167398]
pre_activation_std: [0.923723, 0.741860, 0.077542, 0.532618, 0.514305, 0.540127]
### 12
mean: [-2.774656]
std: [1.360837]
fourier: [[22.031652, 22.526250, 24.978822, 30.146364, 249.719052]]
input_correlations: [[-0.938779, 0.938689, 0.931796, 0.902842, 0.944489, 0.909993, 0.000000, 0.000000]]
pre_activation_mean: [-2.774656]
pre_activation_std: [1.360837]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.066182,
-0.204511,
-0.696607,
0.332741,
-1.066149
],
[
0.733878,
1.073763,
0.026361,
-0.026669,
0.192251
],
[
0.186489,
0.720144,
0.050286,
0.208202,
-0.679508
],
[
-0.768564,
-0.444514,
-0.158353,
-0.12843,
-0.199386
],
[
-0.952926,
-0.489364,
0.093376,
0.351172,
0.691495
],
[
0.872364,
0.809245,
0.529818,
0.038488,
-0.049759
]
],
"network.0.bias": [
-0.611232,
0.05781,
-0.341339,
0.32708,
0.486209,
0.305397
],
"network.2.weight": [
[
-0.044553,
-0.069582,
0.013024,
-0.346543,
-0.247612,
-0.296891
],
[
0.197465,
-0.382783,
0.389133,
0.841027,
-0.650333,
0.124031
],
[
0.235778,
-0.313899,
0.247268,
0.733147,
-0.647031,
0.141073
],
[
-0.252046,
-0.377628,
-0.097017,
-0.827069,
0.571041,
-0.714402
],
[
0.081287,
-0.579156,
0.279143,
-0.451789,
0.069122,
-0.390482
],
[
-0.216541,
-0.750197,
-0.579287,
-1.164529,
0.54097,
-0.812632
]
],
"network.2.bias": [
0.133722,
-0.640296,
-0.682258,
-0.03274,
-0.18972,
0.55255
],
"network.4.weight": [
[
-0.389737,
0.11931,
0.131339,
0.550246,
-1.063939,
0.654812
],
[
-0.196151,
0.066258,
0.261251,
-0.187679,
0.088174,
0.080272
],
[
0.436658,
-0.029061,
-0.325832,
-0.167991,
0.579165,
-0.459157
],
[
0.326908,
-0.397837,
-0.551349,
-0.504784,
0.436184,
-0.374223
],
[
1.025598,
-0.374326,
-0.663031,
-0.584787,
0.11312,
0.095031
],
[
-0.65648,
-0.169209,
-0.386242,
-0.047177,
-0.301999,
0.576112
]
],
"network.4.bias": [
0.002773,
-0.780011,
0.424784,
0.360177,
-0.422421,
0.463379
],
"network.6.weight": [
[
0.289024,
0.74843,
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-0.23248,
0.515555,
0.161456
],
[
0.715452,
-0.325874,
-0.337125,
-0.456835,
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0.632363
],
[
0.639779,
-0.25356,
-0.061511,
-0.158996,
-0.031283,
0.396042
],
[
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0.590753,
0.998562,
0.076515,
0.136274
],
[
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0.326883,
0.491543,
0.674443,
-0.135806,
-0.288182
],
[
-0.056158,
0.507293,
-1.039771,
-0.324559,
0.126831,
0.22897
]
],
"network.6.bias": [
-0.500558,
0.201131,
0.413389,
0.49577,
0.025229,
0.007584
],
"network.8.weight": [
[
-0.350699,
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-0.189981,
0.466145,
0.542108,
-0.219047
],
[
0.059351,
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0.08266,
0.847026,
0.736981,
-0.109196
],
[
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0.334453,
0.378892,
-0.069742
],
[
0.030486,
0.329212,
-0.103957,
0.171129,
0.262901,
-0.057667
],
[
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0.700581,
0.445255,
-0.2917,
-0.304664,
0.002011
],
[
-0.385605,
-0.235976,
-0.334331,
0.926246,
0.345898,
-0.217422
]
],
"network.8.bias": [
0.712484,
0.129185,
-0.171006,
-0.152385,
-0.129952,
0.414065
],
"network.10.weight": [
[
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0.603951,
0.020915,
-0.237539,
-0.517008,
0.904134
],
[
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0.401698,
0.576586,
-0.432939
],
[
-0.421281,
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0.293637,
0.148852,
0.053846,
0.379907
],
[
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0.114095,
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0.611881,
-0.023361
],
[
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0.340422,
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],
[
-0.410868,
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0.055027,
0.213143,
0.62463,
0.343724
]
],
"network.10.bias": [
0.785715,
0.343906,
-0.120621,
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0.204262,
0.006123
],
"network.12.weight": [
[
-0.979008,
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0.164611,
0.301253,
0.346176,
0.596411
]
],
"network.12.bias": [
-0.41331
]
}
## Activation Signature
### 0
mean: [2.345561, -0.018790, -0.089491, -0.051789, -0.078815, -0.003231]
std: [0.786444, 0.552830, 0.036141, 0.431510, 0.324407, 0.474881]
fourier: [[12.615883, 13.545142, 14.319641, 18.515439, 211.100462], [7.992145, 8.217577, 8.492616, 9.283568, 9.761242], [0.537747, 0.569131, 0.601950, 0.681830, 8.054168], [6.184824, 6.209829, 6.499681, 6.811473, 7.328091], [4.866969, 4.958031, 5.477418, 5.825588, 7.093372], [6.872195, 6.960940, 7.094025, 7.531321, 8.296420]]
input_correlations: [[-0.308254, -0.153603, -0.690846, 0.097792, -0.812881, 0.000000, 0.000000, 0.000000], [0.766562, 0.849127, 0.356135, 0.199208, 0.214689, 0.000000, 0.000000, 0.000000], [0.298756, 0.802986, 0.122447, 0.330782, -0.544550, 0.000000, 0.000000, 0.000000], [-0.881067, -0.664080, -0.472627, -0.232218, -0.335485, 0.000000, 0.000000, 0.000000], [-0.758948, -0.484681, -0.133495, 0.276472, 0.412049, 0.000000, 0.000000, 0.000000], [0.813149, 0.738986, 0.600970, 0.153411, 0.145365, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.958045, 3.162699, 0.916456, -2.291460, 0.209580, 3.993526]
pre_activation_std: [2.617327, 2.909224, 2.019639, 2.250489, 2.609981, 3.161500]
### 2
mean: [-1.468462, -1.533370, -1.462069, -3.563581, -3.113792, -5.143430]
std: [1.051828, 1.097904, 1.030294, 3.862676, 2.632803, 5.808600]
fourier: [[16.638304, 18.386499, 18.846713, 20.633623, 132.161531], [18.610548, 19.563776, 19.603435, 20.322529, 138.003314], [16.750377, 16.818792, 18.875080, 21.170854, 131.586230], [60.166575, 63.347467, 65.186549, 73.131019, 320.722335], [39.911084, 42.897532, 44.316607, 46.991672, 280.241300], [92.449322, 97.479128, 100.846944, 101.249390, 462.908697]]
input_correlations: [[-0.228068, -0.928469, -0.643718, -0.025877, 0.068515, -0.945651, 0.000000, 0.000000], [-0.078709, 0.029273, 0.375445, 0.207776, -0.891420, 0.126777, 0.000000, 0.000000], [-0.081066, 0.110144, 0.367188, 0.222612, -0.942128, 0.216900, 0.000000, 0.000000], [-0.150111, -0.947944, -0.761895, -0.143915, 0.549392, -0.974557, 0.000000, 0.000000], [-0.153898, -0.979956, -0.673404, -0.125596, 0.366244, -0.979521, 0.000000, 0.000000], [-0.174398, -0.967939, -0.816973, -0.134708, 0.490386, -0.970941, 0.000000, 0.000000]]
pre_activation_mean: [-1.468462, -1.533370, -1.462069, -3.563581, -3.113792, -5.143430]
pre_activation_std: [1.051828, 1.097904, 1.030294, 3.862676, 2.632803, 5.808600]
### 4
mean: [0.166436, -0.808766, 0.339555, 0.348314, -0.421675, 0.658524]
std: [0.571669, 0.046574, 0.309029, 0.427146, 0.262328, 0.259184]
fourier: [[8.607393, 8.874043, 9.169842, 10.323376, 14.979212], [0.676865, 0.718210, 0.728405, 0.745895, 72.788909], [4.612303, 4.911592, 5.127208, 5.928857, 30.559993], [6.176373, 6.338501, 6.432433, 7.108951, 31.348280], [3.751641, 4.045899, 4.054712, 4.742878, 37.950766], [4.056625, 4.513247, 4.570566, 5.505317, 59.267166]]
input_correlations: [[-0.120169, 0.269293, 0.329914, 0.968307, -0.220217, 0.986490, 0.000000, 0.000000], [-0.226632, -0.014921, -0.002375, -0.883890, -0.026493, -0.801532, 0.000000, 0.000000], [0.170583, -0.280039, -0.351183, -0.950421, 0.256791, -0.983432, 0.000000, 0.000000], [0.116719, -0.388279, -0.440056, -0.981831, 0.139735, -0.968926, 0.000000, 0.000000], [0.298230, -0.530493, -0.593091, -0.936725, 0.077694, -0.849860, 0.000000, 0.000000], [-0.197074, 0.070004, 0.145934, 0.887773, -0.310965, 0.973453, 0.000000, 0.000000]]
pre_activation_mean: [0.166436, -0.808766, 0.339555, 0.348314, -0.421675, 0.658524]
pre_activation_std: [0.571669, 0.046574, 0.309029, 0.427146, 0.262328, 0.259184]
### 6
mean: [-0.750788, 0.510318, 0.690320, 0.886182, 0.090803, -0.331479]
std: [0.264667, 0.624251, 0.479124, 0.511567, 0.388988, 0.158005]
fourier: [[4.105047, 4.255419, 4.506461, 5.248358, 67.570922], [9.306235, 9.967261, 10.367108, 11.916584, 45.928573], [7.032096, 7.439310, 7.659828, 8.687948, 62.128767], [7.894447, 7.895356, 8.469881, 9.671472, 79.756406], [6.027899, 6.278792, 6.688531, 7.833526, 8.172277], [2.602468, 2.708918, 3.087600, 3.827087, 29.833138]]
input_correlations: [[0.983348, 0.881668, -0.844144, -0.737286, 0.401491, 0.976835, 0.000000, 0.000000], [0.991564, 0.894394, -0.813982, -0.706551, 0.400795, 0.980101, 0.000000, 0.000000], [0.997387, 0.913988, -0.775100, -0.663794, 0.437053, 0.979451, 0.000000, 0.000000], [-0.974933, -0.877494, 0.852079, 0.792842, -0.314636, -0.945425, 0.000000, 0.000000], [-0.974276, -0.863456, 0.867350, 0.779128, -0.343612, -0.965177, 0.000000, 0.000000], [0.797189, 0.613738, -0.994057, -0.900798, 0.144116, 0.849817, 0.000000, 0.000000]]
pre_activation_mean: [-0.750788, 0.510318, 0.690320, 0.886182, 0.090803, -0.331479]
pre_activation_std: [0.264667, 0.624251, 0.479124, 0.511567, 0.388988, 0.158005]
### 8
mean: [0.921770, 0.693644, -0.047512, 0.079476, 0.142695, 0.986267]
std: [0.571723, 0.544278, 0.382467, 0.122318, 0.725607, 0.589002]
fourier: [[8.957335, 9.260778, 9.964262, 11.717565, 82.959268], [8.890216, 8.915176, 9.894062, 11.902868, 62.427953], [5.611541, 6.020679, 6.213880, 6.697085, 7.888098], [1.650158, 1.670672, 1.685350, 1.875171, 7.152832], [11.069297, 11.571730, 12.312697, 12.842554, 14.215644], [9.457237, 9.522636, 10.437068, 12.406167, 88.763995]]
input_correlations: [[-0.887647, -0.985316, -0.975747, 0.865919, 0.677807, -0.973289, 0.000000, 0.000000], [-0.788934, -0.937195, -0.918821, 0.942652, 0.796562, -0.991985, 0.000000, 0.000000], [-0.881056, -0.982789, -0.972554, 0.872847, 0.688039, -0.975866, 0.000000, 0.000000], [0.992871, 0.931505, 0.947750, -0.485417, -0.208575, 0.737461, 0.000000, 0.000000], [0.923027, 0.996442, 0.991066, -0.819220, -0.613538, 0.953902, 0.000000, 0.000000], [-0.843892, -0.965733, -0.951817, 0.908082, 0.736543, -0.985354, 0.000000, 0.000000]]
pre_activation_mean: [0.921770, 0.693644, -0.047512, 0.079476, 0.142695, 0.986267]
pre_activation_std: [0.571723, 0.544278, 0.382467, 0.122318, 0.725607, 0.589002]
### 10
mean: [2.326265, -0.536120, -0.223034, -0.353108, -0.555079, -0.167398]
std: [0.923723, 0.741860, 0.077542, 0.532618, 0.514305, 0.540127]
fourier: [[15.368218, 15.546675, 17.076640, 21.334506, 209.363810], [12.140799, 12.264207, 13.534637, 16.353074, 48.250839], [1.204706, 1.284276, 1.386743, 1.587912, 20.073022], [8.363486, 8.506308, 9.404879, 10.847495, 31.779728], [8.561452, 8.606356, 9.518155, 11.696255, 49.957150], [8.371714, 8.667161, 9.360143, 10.895416, 15.065825]]
input_correlations: [[0.964572, 0.926419, 0.793021, -0.661786, -0.885412, 0.957601, 0.000000, 0.000000], [-0.914560, -0.859046, -0.692373, 0.766462, 0.945770, -0.902842, 0.000000, 0.000000], [-0.823337, -0.748696, -0.550241, 0.871865, 0.987712, -0.804239, 0.000000, 0.000000], [-0.841749, -0.768693, -0.571814, 0.853675, 0.984567, -0.825282, 0.000000, 0.000000], [-0.945198, -0.899005, -0.750887, 0.710692, 0.914867, -0.935723, 0.000000, 0.000000], [-0.820096, -0.747198, -0.544257, 0.875025, 0.990356, -0.803459, 0.000000, 0.000000]]
pre_activation_mean: [2.326265, -0.536120, -0.223034, -0.353108, -0.555079, -0.167398]
pre_activation_std: [0.923723, 0.741860, 0.077542, 0.532618, 0.514305, 0.540127]
### 12
mean: [-2.774656]
std: [1.360837]
fourier: [[22.031652, 22.526250, 24.978822, 30.146364, 249.719052]]
input_correlations: [[-0.938779, 0.938689, 0.931796, 0.902842, 0.944489, 0.909993, 0.000000, 0.000000]]
pre_activation_mean: [-2.774656]
pre_activation_std: [1.360837]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"epoch": 2, "global_epoch": 4, "train_loss": 0.40264342725276947, "train_acc": 0.845, "val_loss": 0.49177345633506775, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.32594428956508636, "train_acc": 0.86, "val_loss": 0.4071127772331238, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.27080265432596207, "train_acc": 0.915, "val_loss": 0.441087007522583, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.23755314946174622, "train_acc": 0.925, "val_loss": 0.4265085458755493, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.1888347715139389, "train_acc": 0.945, "val_loss": 0.3646589517593384, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.18929194658994675, "train_acc": 0.935, "val_loss": 0.3283466696739197, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 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16 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.44, "improved_accuracy": 0.9, "improvement": 0.46, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3870, "learning_rate": 0.09151949117007849, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.290685,
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[
0.530317,
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[
0.184206,
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-0.011553,
0.527097,
0.691686,
0.391862,
-0.262074
]
],
"network.4.bias": [
0.030981,
0.058747,
-0.963587,
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0.460116,
-0.017638,
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-0.564373
],
"network.6.weight": [
[
0.281256,
0.398298,
1.169031,
0.161624,
-0.05326,
0.095643,
0.787116,
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],
[
0.330565,
0.830445,
0.528522,
-0.126786,
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[
0.242624,
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[
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[
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[
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[
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0.693322,
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[
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[
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0.233496,
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0.63839,
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[
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"network.12.bias": [
0.226979
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}
## Activation Signature
### 0
mean: [0.253659, 47.943588, 16.388266, 0.075801, 26.412718, 0.010660, 22.476498, 7.514162]
std: [0.539088, 43.367420, 15.024851, 0.160923, 24.100273, 0.047057, 20.155973, 6.974674]
fourier: [[7.580364, 7.584634, 7.729727, 9.614471, 22.829301], [699.192238, 743.953051, 797.597880, 802.531188, 4314.923006], [242.498686, 257.609460, 276.046796, 277.852755, 1474.943865], [2.226798, 2.314948, 2.322333, 2.871789, 6.822061], [388.944187, 413.065059, 442.711750, 445.472360, 2377.144490], [0.673271, 0.718633, 0.818809, 0.829785, 0.959439], [325.497280, 346.471345, 370.021751, 373.618135, 2022.884682], [111.553728, 119.314035, 128.397161, 129.051301, 676.274514]]
input_correlations: [[0.590452, 0.885712, 0.553375, 0.325067, -0.003835, 0.000000, 0.000000, 0.000000], [0.015987, 0.125946, -0.185495, -0.138586, -0.977689, 0.000000, 0.000000, 0.000000], [0.704424, 0.817503, 0.076366, 0.353742, -0.101158, 0.000000, 0.000000, 0.000000], [0.717501, 0.420542, 0.786624, -0.285954, 0.050132, 0.000000, 0.000000, 0.000000], [-0.703377, -0.618295, -0.162091, -0.030319, 0.469744, 0.000000, 0.000000, 0.000000], [0.675256, 0.175634, -0.200578, -0.580796, 0.058011, 0.000000, 0.000000, 0.000000], [0.425740, -0.521503, 0.051841, -0.758940, -0.204992, 0.000000, 0.000000, 0.000000], [-0.772953, -0.623496, -0.276184, -0.209316, 0.327397, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [4.446537, -1.450587, 3.308439, 2.465943, -1.343872, -1.322219, -2.168330, -0.297327]
pre_activation_std: [3.306499, 1.442651, 3.523276, 3.085874, 2.872055, 2.813108, 2.088112, 1.290860]
### 2
mean: [9.287113, -2.648242, 3.449345, 3.705772, 7.043701, 9.474819, -9.013625, 0.983098]
std: [8.961606, 2.886529, 2.882531, 3.565100, 7.001213, 8.415872, 7.170993, 2.114512]
fourier: [[143.101420, 153.121566, 161.379786, 166.863593, 835.840207], [48.513253, 49.309126, 49.533942, 49.991803, 238.341827], [46.336821, 47.853809, 49.324090, 54.803601, 310.441017], [58.092654, 59.120558, 59.836775, 68.680469, 333.519507], [114.169866, 115.251752, 122.646553, 140.346430, 633.933123], [139.519416, 141.043668, 151.637479, 154.509775, 852.733691], [115.083749, 126.060092, 129.144099, 136.420383, 811.226269], [31.750134, 35.323178, 35.453495, 40.271597, 88.478840]]
input_correlations: [[0.936790, 0.194491, 0.909749, 0.795511, -0.395036, 0.608595, 0.265757, -0.581925], [-0.921744, -0.206500, -0.758489, -0.899487, 0.339663, -0.418553, -0.129265, 0.482691], [0.952428, 0.069299, 0.846378, 0.770101, -0.464999, 0.366738, 0.038366, -0.610947], [0.944521, 0.113777, 0.903361, 0.723259, -0.419098, 0.391249, 0.040300, -0.580261], [0.924074, 0.117739, 0.967615, 0.622321, -0.429213, 0.540349, 0.191037, -0.628568], [0.946109, 0.226563, 0.882350, 0.838290, -0.344086, 0.594091, 0.254610, -0.530872], [-0.953759, -0.259756, -0.926430, -0.777391, 0.259707, -0.594937, -0.221517, 0.470489], [0.853008, -0.037402, 0.882911, 0.520293, -0.635791, 0.318002, 0.082570, -0.781472]]
pre_activation_mean: [9.287113, -2.648242, 3.449345, 3.705772, 7.043701, 9.474819, -9.013625, 0.983098]
pre_activation_std: [8.961606, 2.886529, 2.882531, 3.565100, 7.001213, 8.415872, 7.170993, 2.114512]
### 4
mean: [5.184672, 13.498518, -10.183169, -4.318271, -6.340053, -9.982637, -1.915995, 11.062871]
std: [4.877995, 11.727876, 8.751865, 3.956972, 6.311756, 9.019931, 1.502424, 10.333400]
fourier: [[80.662564, 82.857066, 86.079103, 93.429411, 466.620459], [197.370510, 200.498688, 210.453762, 216.448755, 1214.866557], [147.763245, 150.019952, 165.622942, 168.323707, 916.485234], [58.496375, 61.395110, 72.983220, 74.540910, 388.644423], [100.889994, 102.200674, 114.248483, 116.864625, 570.604747], [142.608272, 151.069652, 164.084280, 166.985393, 898.437321], [23.447048, 24.924161, 25.002790, 39.525730, 172.439581], [164.051981, 175.650773, 188.399351, 192.161233, 995.658419]]
input_correlations: [[0.988558, -0.244668, 0.934789, 0.952374, 0.992906, 0.974564, 0.457318, 0.933578], [0.995171, -0.230627, 0.969256, 0.964292, 0.944516, 0.999248, 0.446350, 0.878279], [-0.968445, 0.217867, -0.894212, -0.921173, -0.994047, -0.945584, -0.440351, -0.930740], [-0.899463, 0.142394, -0.977273, -0.978694, -0.875439, -0.910626, -0.365613, -0.917886], [-0.993669, 0.252314, -0.921900, -0.930499, -0.972911, -0.983747, -0.463118, -0.884496], [-0.996142, 0.240224, -0.938339, -0.948491, -0.981657, -0.986364, -0.456964, -0.908272], [-0.793131, 0.216419, -0.642236, -0.684315, -0.876891, -0.747724, -0.428137, -0.775492], [0.999059, -0.241576, 0.957304, 0.963056, 0.975023, 0.994143, 0.457024, 0.909100]]
pre_activation_mean: [5.184672, 13.498518, -10.183169, -4.318271, -6.340053, -9.982637, -1.915995, 11.062871]
pre_activation_std: [4.877995, 11.727876, 8.751865, 3.956972, 6.311756, 9.019931, 1.502424, 10.333400]
### 6
mean: [11.186731, 17.038958, 6.998423, -7.382429, -1.255160, 4.604678, -4.379090, 24.570217]
std: [10.518696, 15.143283, 6.473552, 7.377036, 1.639565, 4.714091, 3.845947, 22.059032]
fourier: [[169.239242, 180.106702, 193.874186, 194.135548, 1006.805818], [247.442921, 259.231388, 276.967836, 279.295724, 1533.506035], [105.948088, 111.034306, 118.131337, 118.717624, 629.858078], [118.749734, 125.919610, 136.486275, 136.648796, 664.418658], [22.727309, 24.372959, 24.883927, 46.460521, 112.964361], [79.669675, 80.677429, 84.043291, 88.187539, 414.421010], [65.148746, 66.249678, 66.667353, 72.803804, 394.118079], [357.085585, 377.626892, 405.157433, 405.225251, 2211.319733]]
input_correlations: [[0.987543, 0.996634, 0.537981, 0.674465, -0.462816, -0.084596, 0.579373, 0.999216], [0.983049, 0.998468, 0.535141, 0.676430, -0.463617, -0.085509, 0.576679, 0.997878], [0.983722, 0.998241, 0.529016, 0.670396, -0.455351, -0.079545, 0.573193, 0.998142], [-0.987146, -0.996601, -0.545415, -0.680459, 0.474841, 0.092849, -0.584061, -0.998891], [-0.519971, -0.305388, -0.139707, -0.074848, 0.024722, -0.034037, -0.195455, -0.416193], [0.911489, 0.982632, 0.528537, 0.698564, -0.476805, -0.090914, 0.567237, 0.953669], [-0.998530, -0.969593, -0.495029, -0.621503, 0.399778, 0.049485, -0.560004, -0.991369], [0.986480, 0.997186, 0.533714, 0.672461, -0.460155, -0.084010, 0.575264, 0.998988]]
pre_activation_mean: [11.186731, 17.038958, 6.998423, -7.382429, -1.255160, 4.604678, -4.379090, 24.570217]
pre_activation_std: [10.518696, 15.143283, 6.473552, 7.377036, 1.639565, 4.714091, 3.845947, 22.059032]
### 8
mean: [22.394329, -3.791971, 18.489866, -38.612427, -41.362740, -2.374347, 30.828789, -26.755440]
std: [20.379625, 2.890719, 17.018492, 34.997730, 37.460472, 1.176585, 28.058081, 24.143400]
fourier: [[330.750860, 349.074511, 375.917207, 379.355612, 2015.489721], [46.841613, 49.082506, 50.294744, 50.714202, 341.277424], [277.988338, 292.013356, 312.035324, 316.190189, 1664.087934], [569.841544, 598.766528, 643.402294, 651.581076, 3475.118324], [605.728854, 640.766979, 692.345284, 696.236043, 3722.646683], [18.862317, 19.450186, 20.070337, 20.139162, 213.691209], [451.290431, 480.727011, 518.285156, 518.623952, 2774.591197], [385.472122, 413.259731, 443.651599, 448.373641, 2407.989751]]
input_correlations: [[0.999388, 0.999862, 0.999539, -0.506295, 0.027490, 0.968030, 0.712762, 0.999711], [-0.995341, -0.994096, -0.994863, 0.462137, 0.082348, -0.950743, -0.673376, -0.995195], [0.999087, 0.999886, 0.999522, -0.506880, 0.032090, 0.970745, 0.710840, 0.999515], [-0.999354, -0.999940, -0.999755, 0.496074, -0.033152, -0.970946, -0.706790, -0.999628], [-0.999695, -0.999865, -0.999705, 0.498181, -0.022496, -0.966690, -0.709558, -0.999877], [-0.912524, -0.910281, -0.915195, 0.176968, 0.198212, -0.898290, -0.454835, -0.910792], [0.999838, 0.999613, 0.999530, -0.497446, 0.008242, 0.962781, 0.709794, 0.999928], [-0.999733, -0.998927, -0.999019, 0.491331, 0.005474, -0.957703, -0.707627, -0.999638]]
pre_activation_mean: [22.394329, -3.791971, 18.489866, -38.612427, -41.362740, -2.374347, 30.828789, -26.755440]
pre_activation_std: [20.379625, 2.890719, 17.018492, 34.997730, 37.460472, 1.176585, 28.058081, 24.143400]
### 10
mean: [-49.011967, 47.775021, 16.251476, -21.257010, 26.247320, -14.007635, 22.482861, 7.423635]
std: [44.945801, 43.555431, 15.177886, 19.505329, 24.284435, 12.755043, 20.148947, 7.078908]
fourier: [[726.651400, 771.128147, 827.436258, 833.271063, 4411.077431], [703.139122, 747.466397, 802.053109, 807.006480, 4299.751878], [245.938239, 260.078332, 279.644471, 281.303476, 1462.632866], [314.747836, 334.748519, 359.179039, 361.295642, 1913.130810], [392.416407, 416.767284, 446.970607, 450.089926, 2362.258813], [206.829842, 219.778480, 232.702562, 237.326244, 1260.687234], [325.195794, 346.530796, 369.782169, 373.542074, 2023.457371], [114.599738, 120.601733, 130.243519, 131.439642, 668.127219]]
input_correlations: [[-0.999977, -0.706928, -0.999836, 0.461914, 0.471219, -0.707664, -0.999859, 0.242716], [0.999962, 0.706283, 0.999800, -0.460820, -0.470128, 0.708289, 0.999900, -0.241759], [0.999956, 0.709097, 0.999809, -0.466249, -0.475534, 0.705523, 0.999809, -0.246482], [-0.999955, -0.705615, -0.999788, 0.459786, 0.469083, -0.708885, -0.999915, 0.241117], [0.999970, 0.707220, 0.999821, -0.462021, -0.471344, 0.707954, 0.999871, -0.242496], [-0.999844, -0.700772, -0.999969, 0.451440, 0.460821, -0.710828, -0.999333, 0.233172], [0.999977, 0.703099, 0.999899, -0.455361, -0.464697, 0.710484, 0.999822, -0.236959], [0.999330, 0.715400, 0.998882, -0.477439, -0.486551, 0.704123, 0.999677, -0.258107]]
pre_activation_mean: [-49.011967, 47.775021, 16.251476, -21.257010, 26.247320, -14.007635, 22.482861, 7.423635]
pre_activation_std: [44.945801, 43.555431, 15.177886, 19.505329, 24.284435, 12.755043, 20.148947, 7.078908]
### 12
mean: [-21.701361]
std: [20.260578]
fourier: [[327.584307, 347.634500, 373.363693, 375.567298, 1953.122502]]
input_correlations: [[0.531412, -0.999936, -0.999876, 0.532321, -0.999887, 0.260053, -0.999941, -0.999595]]
pre_activation_mean: [-21.701361]
pre_activation_std: [20.260578]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.480429,
1.19197,
0.585525,
0.219987,
-0.270957
],
[
0.132571,
0.058348,
-0.034332,
-0.002669,
-0.782909
],
[
1.08406,
1.111167,
-0.378859,
0.378153,
-0.386482
],
[
0.67587,
0.41151,
0.984383,
-0.495344,
-0.188381
],
[
-0.975302,
-0.596155,
0.019386,
-0.036105,
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}
## Activation Signature
### 0
mean: [0.253659, 47.943588, 16.388266, 0.075801, 26.412718, 0.010660, 22.476498, 7.514162]
std: [0.539088, 43.367420, 15.024851, 0.160923, 24.100273, 0.047057, 20.155973, 6.974674]
fourier: [[7.580364, 7.584634, 7.729727, 9.614471, 22.829301], [699.192238, 743.953051, 797.597880, 802.531188, 4314.923006], [242.498686, 257.609460, 276.046796, 277.852755, 1474.943865], [2.226798, 2.314948, 2.322333, 2.871789, 6.822061], [388.944187, 413.065059, 442.711750, 445.472360, 2377.144490], [0.673271, 0.718633, 0.818809, 0.829785, 0.959439], [325.497280, 346.471345, 370.021751, 373.618135, 2022.884682], [111.553728, 119.314035, 128.397161, 129.051301, 676.274514]]
input_correlations: [[0.590452, 0.885712, 0.553375, 0.325067, -0.003835, 0.000000, 0.000000, 0.000000], [0.015987, 0.125946, -0.185495, -0.138586, -0.977689, 0.000000, 0.000000, 0.000000], [0.704424, 0.817503, 0.076366, 0.353742, -0.101158, 0.000000, 0.000000, 0.000000], [0.717501, 0.420542, 0.786624, -0.285954, 0.050132, 0.000000, 0.000000, 0.000000], [-0.703377, -0.618295, -0.162091, -0.030319, 0.469744, 0.000000, 0.000000, 0.000000], [0.675256, 0.175634, -0.200578, -0.580796, 0.058011, 0.000000, 0.000000, 0.000000], [0.425740, -0.521503, 0.051841, -0.758940, -0.204992, 0.000000, 0.000000, 0.000000], [-0.772953, -0.623496, -0.276184, -0.209316, 0.327397, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [4.446537, -1.450587, 3.308439, 2.465943, -1.343872, -1.322219, -2.168330, -0.297327]
pre_activation_std: [3.306499, 1.442651, 3.523276, 3.085874, 2.872055, 2.813108, 2.088112, 1.290860]
### 2
mean: [9.287113, -2.648242, 3.449345, 3.705772, 7.043701, 9.474819, -9.013625, 0.983098]
std: [8.961606, 2.886529, 2.882531, 3.565100, 7.001213, 8.415872, 7.170993, 2.114512]
fourier: [[143.101420, 153.121566, 161.379786, 166.863593, 835.840207], [48.513253, 49.309126, 49.533942, 49.991803, 238.341827], [46.336821, 47.853809, 49.324090, 54.803601, 310.441017], [58.092654, 59.120558, 59.836775, 68.680469, 333.519507], [114.169866, 115.251752, 122.646553, 140.346430, 633.933123], [139.519416, 141.043668, 151.637479, 154.509775, 852.733691], [115.083749, 126.060092, 129.144099, 136.420383, 811.226269], [31.750134, 35.323178, 35.453495, 40.271597, 88.478840]]
input_correlations: [[0.936790, 0.194491, 0.909749, 0.795511, -0.395036, 0.608595, 0.265757, -0.581925], [-0.921744, -0.206500, -0.758489, -0.899487, 0.339663, -0.418553, -0.129265, 0.482691], [0.952428, 0.069299, 0.846378, 0.770101, -0.464999, 0.366738, 0.038366, -0.610947], [0.944521, 0.113777, 0.903361, 0.723259, -0.419098, 0.391249, 0.040300, -0.580261], [0.924074, 0.117739, 0.967615, 0.622321, -0.429213, 0.540349, 0.191037, -0.628568], [0.946109, 0.226563, 0.882350, 0.838290, -0.344086, 0.594091, 0.254610, -0.530872], [-0.953759, -0.259756, -0.926430, -0.777391, 0.259707, -0.594937, -0.221517, 0.470489], [0.853008, -0.037402, 0.882911, 0.520293, -0.635791, 0.318002, 0.082570, -0.781472]]
pre_activation_mean: [9.287113, -2.648242, 3.449345, 3.705772, 7.043701, 9.474819, -9.013625, 0.983098]
pre_activation_std: [8.961606, 2.886529, 2.882531, 3.565100, 7.001213, 8.415872, 7.170993, 2.114512]
### 4
mean: [5.184672, 13.498518, -10.183169, -4.318271, -6.340053, -9.982637, -1.915995, 11.062871]
std: [4.877995, 11.727876, 8.751865, 3.956972, 6.311756, 9.019931, 1.502424, 10.333400]
fourier: [[80.662564, 82.857066, 86.079103, 93.429411, 466.620459], [197.370510, 200.498688, 210.453762, 216.448755, 1214.866557], [147.763245, 150.019952, 165.622942, 168.323707, 916.485234], [58.496375, 61.395110, 72.983220, 74.540910, 388.644423], [100.889994, 102.200674, 114.248483, 116.864625, 570.604747], [142.608272, 151.069652, 164.084280, 166.985393, 898.437321], [23.447048, 24.924161, 25.002790, 39.525730, 172.439581], [164.051981, 175.650773, 188.399351, 192.161233, 995.658419]]
input_correlations: [[0.988558, -0.244668, 0.934789, 0.952374, 0.992906, 0.974564, 0.457318, 0.933578], [0.995171, -0.230627, 0.969256, 0.964292, 0.944516, 0.999248, 0.446350, 0.878279], [-0.968445, 0.217867, -0.894212, -0.921173, -0.994047, -0.945584, -0.440351, -0.930740], [-0.899463, 0.142394, -0.977273, -0.978694, -0.875439, -0.910626, -0.365613, -0.917886], [-0.993669, 0.252314, -0.921900, -0.930499, -0.972911, -0.983747, -0.463118, -0.884496], [-0.996142, 0.240224, -0.938339, -0.948491, -0.981657, -0.986364, -0.456964, -0.908272], [-0.793131, 0.216419, -0.642236, -0.684315, -0.876891, -0.747724, -0.428137, -0.775492], [0.999059, -0.241576, 0.957304, 0.963056, 0.975023, 0.994143, 0.457024, 0.909100]]
pre_activation_mean: [5.184672, 13.498518, -10.183169, -4.318271, -6.340053, -9.982637, -1.915995, 11.062871]
pre_activation_std: [4.877995, 11.727876, 8.751865, 3.956972, 6.311756, 9.019931, 1.502424, 10.333400]
### 6
mean: [11.186731, 17.038958, 6.998423, -7.382429, -1.255160, 4.604678, -4.379090, 24.570217]
std: [10.518696, 15.143283, 6.473552, 7.377036, 1.639565, 4.714091, 3.845947, 22.059032]
fourier: [[169.239242, 180.106702, 193.874186, 194.135548, 1006.805818], [247.442921, 259.231388, 276.967836, 279.295724, 1533.506035], [105.948088, 111.034306, 118.131337, 118.717624, 629.858078], [118.749734, 125.919610, 136.486275, 136.648796, 664.418658], [22.727309, 24.372959, 24.883927, 46.460521, 112.964361], [79.669675, 80.677429, 84.043291, 88.187539, 414.421010], [65.148746, 66.249678, 66.667353, 72.803804, 394.118079], [357.085585, 377.626892, 405.157433, 405.225251, 2211.319733]]
input_correlations: [[0.987543, 0.996634, 0.537981, 0.674465, -0.462816, -0.084596, 0.579373, 0.999216], [0.983049, 0.998468, 0.535141, 0.676430, -0.463617, -0.085509, 0.576679, 0.997878], [0.983722, 0.998241, 0.529016, 0.670396, -0.455351, -0.079545, 0.573193, 0.998142], [-0.987146, -0.996601, -0.545415, -0.680459, 0.474841, 0.092849, -0.584061, -0.998891], [-0.519971, -0.305388, -0.139707, -0.074848, 0.024722, -0.034037, -0.195455, -0.416193], [0.911489, 0.982632, 0.528537, 0.698564, -0.476805, -0.090914, 0.567237, 0.953669], [-0.998530, -0.969593, -0.495029, -0.621503, 0.399778, 0.049485, -0.560004, -0.991369], [0.986480, 0.997186, 0.533714, 0.672461, -0.460155, -0.084010, 0.575264, 0.998988]]
pre_activation_mean: [11.186731, 17.038958, 6.998423, -7.382429, -1.255160, 4.604678, -4.379090, 24.570217]
pre_activation_std: [10.518696, 15.143283, 6.473552, 7.377036, 1.639565, 4.714091, 3.845947, 22.059032]
### 8
mean: [22.394329, -3.791971, 18.489866, -38.612427, -41.362740, -2.374347, 30.828789, -26.755440]
std: [20.379625, 2.890719, 17.018492, 34.997730, 37.460472, 1.176585, 28.058081, 24.143400]
fourier: [[330.750860, 349.074511, 375.917207, 379.355612, 2015.489721], [46.841613, 49.082506, 50.294744, 50.714202, 341.277424], [277.988338, 292.013356, 312.035324, 316.190189, 1664.087934], [569.841544, 598.766528, 643.402294, 651.581076, 3475.118324], [605.728854, 640.766979, 692.345284, 696.236043, 3722.646683], [18.862317, 19.450186, 20.070337, 20.139162, 213.691209], [451.290431, 480.727011, 518.285156, 518.623952, 2774.591197], [385.472122, 413.259731, 443.651599, 448.373641, 2407.989751]]
input_correlations: [[0.999388, 0.999862, 0.999539, -0.506295, 0.027490, 0.968030, 0.712762, 0.999711], [-0.995341, -0.994096, -0.994863, 0.462137, 0.082348, -0.950743, -0.673376, -0.995195], [0.999087, 0.999886, 0.999522, -0.506880, 0.032090, 0.970745, 0.710840, 0.999515], [-0.999354, -0.999940, -0.999755, 0.496074, -0.033152, -0.970946, -0.706790, -0.999628], [-0.999695, -0.999865, -0.999705, 0.498181, -0.022496, -0.966690, -0.709558, -0.999877], [-0.912524, -0.910281, -0.915195, 0.176968, 0.198212, -0.898290, -0.454835, -0.910792], [0.999838, 0.999613, 0.999530, -0.497446, 0.008242, 0.962781, 0.709794, 0.999928], [-0.999733, -0.998927, -0.999019, 0.491331, 0.005474, -0.957703, -0.707627, -0.999638]]
pre_activation_mean: [22.394329, -3.791971, 18.489866, -38.612427, -41.362740, -2.374347, 30.828789, -26.755440]
pre_activation_std: [20.379625, 2.890719, 17.018492, 34.997730, 37.460472, 1.176585, 28.058081, 24.143400]
### 10
mean: [-49.011967, 47.775021, 16.251476, -21.257010, 26.247320, -14.007635, 22.482861, 7.423635]
std: [44.945801, 43.555431, 15.177886, 19.505329, 24.284435, 12.755043, 20.148947, 7.078908]
fourier: [[726.651400, 771.128147, 827.436258, 833.271063, 4411.077431], [703.139122, 747.466397, 802.053109, 807.006480, 4299.751878], [245.938239, 260.078332, 279.644471, 281.303476, 1462.632866], [314.747836, 334.748519, 359.179039, 361.295642, 1913.130810], [392.416407, 416.767284, 446.970607, 450.089926, 2362.258813], [206.829842, 219.778480, 232.702562, 237.326244, 1260.687234], [325.195794, 346.530796, 369.782169, 373.542074, 2023.457371], [114.599738, 120.601733, 130.243519, 131.439642, 668.127219]]
input_correlations: [[-0.999977, -0.706928, -0.999836, 0.461914, 0.471219, -0.707664, -0.999859, 0.242716], [0.999962, 0.706283, 0.999800, -0.460820, -0.470128, 0.708289, 0.999900, -0.241759], [0.999956, 0.709097, 0.999809, -0.466249, -0.475534, 0.705523, 0.999809, -0.246482], [-0.999955, -0.705615, -0.999788, 0.459786, 0.469083, -0.708885, -0.999915, 0.241117], [0.999970, 0.707220, 0.999821, -0.462021, -0.471344, 0.707954, 0.999871, -0.242496], [-0.999844, -0.700772, -0.999969, 0.451440, 0.460821, -0.710828, -0.999333, 0.233172], [0.999977, 0.703099, 0.999899, -0.455361, -0.464697, 0.710484, 0.999822, -0.236959], [0.999330, 0.715400, 0.998882, -0.477439, -0.486551, 0.704123, 0.999677, -0.258107]]
pre_activation_mean: [-49.011967, 47.775021, 16.251476, -21.257010, 26.247320, -14.007635, 22.482861, 7.423635]
pre_activation_std: [44.945801, 43.555431, 15.177886, 19.505329, 24.284435, 12.755043, 20.148947, 7.078908]
### 12
mean: [-21.701361]
std: [20.260578]
fourier: [[327.584307, 347.634500, 373.363693, 375.567298, 1953.122502]]
input_correlations: [[0.531412, -0.999936, -0.999876, 0.532321, -0.999887, 0.260053, -0.999941, -0.999595]]
pre_activation_mean: [-21.701361]
pre_activation_std: [20.260578]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"improved_epochs": 7, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.7323397994041443, "final_val_loss": 0.5960880517959595, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.5114012360572815, "final_val_loss": 0.32237616181373596, "initial_val_acc": 0.8, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 10}, "improvement": 0.46, "first_improvement_epoch": 3}} |
17 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.46, "improved_accuracy": 0.9, "improvement": 0.44, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3837, "learning_rate": 0.047130264798538976, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [0.127679, 16.609766, 0.059553, -0.055664, 17.039410]
std: [0.314272, 15.416948, 0.183209, 0.050115, 15.781186]
fourier: [[4.334234, 4.499829, 4.877688, 7.382761, 11.491077], [265.116044, 281.898017, 295.559563, 300.391763, 1494.879044], [2.540309, 2.727954, 2.746313, 3.931429, 5.359785], [0.691997, 0.801948, 0.841920, 1.131826, 5.009777], [270.781332, 287.961125, 303.129424, 306.848786, 1533.546894]]
input_correlations: [[-0.688374, -0.195439, -0.244678, 0.514099, 0.459211, 0.000000, 0.000000, 0.000000], [-0.362644, -0.813467, -0.658288, -0.512579, -0.262241, 0.000000, 0.000000, 0.000000], [0.456615, 0.732140, 0.773291, 0.333085, -0.020571, 0.000000, 0.000000, 0.000000], [-0.180915, -0.546414, -0.518415, -0.775656, -0.501740, 0.000000, 0.000000, 0.000000], [-0.702791, -0.149509, -0.369047, 0.324994, 0.485958, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.472439, -3.380165, 3.171653, -3.903212, 0.506460]
pre_activation_std: [1.430121, 2.046151, 2.040020, 2.077518, 1.655894]
### 2
mean: [-0.937928, 1.374062, -0.732765, 2.000305, 1.945425]
std: [1.059730, 1.541459, 0.629160, 2.020447, 1.833363]
fourier: [[17.299677, 17.472737, 17.663398, 18.544725, 84.413489], [22.745866, 25.698985, 25.817818, 33.526637, 123.665615], [10.391988, 10.609596, 10.749834, 12.187501, 65.948873], [31.087951, 33.109638, 34.121943, 42.094092, 180.027468], [29.164389, 29.475043, 30.482168, 36.992045, 175.088303]]
input_correlations: [[0.362955, -0.634228, -0.988232, -0.540689, 0.489547, 0.000000, 0.000000, 0.000000], [0.982570, 0.286379, -0.149833, 0.338980, 0.963300, 0.000000, 0.000000, 0.000000], [0.597690, -0.461427, -0.915579, -0.362004, 0.661089, 0.000000, 0.000000, 0.000000], [-0.668369, 0.404821, 0.872604, 0.300996, -0.756592, 0.000000, 0.000000, 0.000000], [-0.603327, 0.445387, 0.905366, 0.343796, -0.715101, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.937928, 1.374062, -0.732765, 2.000305, 1.945425]
pre_activation_std: [1.059730, 1.541459, 0.629160, 2.020447, 1.833363]
### 4
mean: [3.254301, 2.790994, 0.718686, -0.795363, -0.602803]
std: [2.627744, 3.287247, 1.684385, 1.510505, 1.092755]
fourier: [[43.917656, 45.976552, 46.631564, 46.664255, 292.887071], [49.162601, 52.889038, 54.842292, 74.724424, 251.189478], [23.496240, 24.279956, 29.645209, 39.858482, 64.681695], [22.452422, 23.409182, 24.246591, 34.749525, 71.582637], [15.202843, 15.387018, 19.032357, 26.111582, 54.252295]]
input_correlations: [[-0.319403, -0.329199, -0.195442, 0.990084, 0.993796, 0.000000, 0.000000, 0.000000], [-0.391134, -0.710395, -0.457728, 0.948817, 0.937655, 0.000000, 0.000000, 0.000000], [-0.402834, -0.842890, -0.553018, 0.860575, 0.843997, 0.000000, 0.000000, 0.000000], [0.316802, 0.689355, 0.393866, -0.953369, -0.942734, 0.000000, 0.000000, 0.000000], [0.370846, 0.826793, 0.526339, -0.874635, -0.858242, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.254301, 2.790994, 0.718686, -0.795363, -0.602803]
pre_activation_std: [2.627744, 3.287247, 1.684385, 1.510505, 1.092755]
### 6
mean: [4.778206, 4.963577, -4.022648, 3.646962, 3.223279]
std: [4.319339, 4.255157, 4.116868, 3.969961, 2.970627]
fourier: [[72.599670, 76.123433, 82.107705, 85.386615, 430.038577], [72.180941, 76.237007, 82.079580, 82.682266, 446.721912], [66.581082, 67.893435, 73.650011, 82.695945, 362.038404], [64.408193, 66.315248, 72.018378, 85.627486, 328.226580], [49.482255, 51.549972, 55.604118, 58.333822, 290.095071]]
input_correlations: [[0.979828, 0.997173, 0.971162, -0.482517, -0.434446, 0.000000, 0.000000, 0.000000], [0.979995, 0.997611, 0.974503, -0.460953, -0.412461, 0.000000, 0.000000, 0.000000], [-0.988101, -0.986147, -0.945772, 0.511693, 0.462048, 0.000000, 0.000000, 0.000000], [0.945776, 0.989399, 0.962935, -0.597535, -0.555981, 0.000000, 0.000000, 0.000000], [0.986046, 0.993859, 0.963277, -0.478099, -0.429284, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [4.778206, 4.963577, -4.022648, 3.646962, 3.223279]
pre_activation_std: [4.319339, 4.255157, 4.116868, 3.969961, 2.970627]
### 8
mean: [8.011994, -2.820768, -1.962318, 9.568969, 11.852995]
std: [7.541342, 2.808115, 1.660132, 8.997557, 11.047421]
fourier: [[127.368835, 133.760700, 144.016435, 148.758055, 721.079583], [46.833456, 48.786131, 53.164211, 57.110679, 253.869098], [28.266055, 30.137617, 31.410523, 32.102118, 176.608628], [153.020509, 161.607667, 173.616015, 176.642775, 861.207241], [187.627007, 197.833069, 212.650655, 216.786438, 1066.769510]]
input_correlations: [[0.999693, 0.999594, -0.399404, 0.996952, 0.998800, 0.000000, 0.000000, 0.000000], [-0.996626, -0.996598, 0.447584, -0.994644, -0.994518, 0.000000, 0.000000, 0.000000], [-0.999055, -0.999029, 0.342514, -0.995854, -0.999314, 0.000000, 0.000000, 0.000000], [0.999740, 0.999791, -0.390324, 0.998175, 0.998379, 0.000000, 0.000000, 0.000000], [0.999814, 0.999822, -0.390625, 0.997857, 0.998664, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [8.011994, -2.820768, -1.962318, 9.568969, 11.852995]
pre_activation_std: [7.541342, 2.808115, 1.660132, 8.997557, 11.047421]
### 10
mean: [-8.336796, 16.585419, -3.273255, -1.573586, 16.967037]
std: [8.325666, 15.444926, 3.362108, 1.390682, 15.862467]
fourier: [[142.281974, 151.043411, 161.318584, 161.518637, 750.311588], [265.114332, 281.663638, 297.195639, 300.416440, 1492.687724], [56.793556, 60.191725, 64.443673, 66.087086, 294.592980], [24.159864, 25.629271, 25.783551, 27.285283, 141.622778], [271.126307, 287.659152, 307.180169, 307.227962, 1527.033359]]
input_correlations: [[-0.999886, 0.277292, -0.822935, -0.999947, -0.999968, 0.000000, 0.000000, 0.000000], [0.999942, -0.266236, 0.825518, 0.999983, 0.999992, 0.000000, 0.000000, 0.000000], [-0.999547, 0.298080, -0.817040, -0.999430, -0.999537, 0.000000, 0.000000, 0.000000], [-0.998045, 0.212493, -0.832142, -0.997674, -0.997730, 0.000000, 0.000000, 0.000000], [0.999943, -0.275163, 0.823518, 0.999947, 0.999983, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-8.336796, 16.585419, -3.273255, -1.573586, 16.967037]
pre_activation_std: [8.325666, 15.444926, 3.362108, 1.390682, 15.862467]
### 12
mean: [-14.878060]
std: [14.108957]
fourier: [[240.418675, 255.418558, 272.754182, 274.675860, 1339.025288]]
input_correlations: [[0.466040, -0.999811, 0.402871, -0.590881, -0.999854, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-14.878060]
pre_activation_std: [14.108957]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
0.503547,
0.804358,
-0.651938,
0.766303,
0.860207
]
],
"network.8.bias": [
-0.085947,
0.055547,
0.010079,
-0.258785,
-0.185003
],
"network.10.weight": [
[
0.043403,
0.267933,
0.216351,
-0.328494,
-0.522674
],
[
0.354795,
0.19629,
0.013393,
0.504307,
0.761355
],
[
-0.412544,
0.404572,
0.26057,
-0.202989,
0.140564
],
[
-0.436639,
-0.34098,
0.034564,
0.23554,
-0.023499
],
[
0.514249,
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-0.001959,
0.272836,
0.875787
]
],
"network.10.bias": [
0.725732,
-0.257048,
0.334973,
-0.014118,
-0.268974
],
"network.12.weight": [
[
0.647406,
-0.419033,
0.46329,
-0.220925,
-0.476232
]
],
"network.12.bias": [
0.074154
]
}
## Activation Signature
### 0
mean: [0.127679, 16.609766, 0.059553, -0.055664, 17.039410]
std: [0.314272, 15.416948, 0.183209, 0.050115, 15.781186]
fourier: [[4.334234, 4.499829, 4.877688, 7.382761, 11.491077], [265.116044, 281.898017, 295.559563, 300.391763, 1494.879044], [2.540309, 2.727954, 2.746313, 3.931429, 5.359785], [0.691997, 0.801948, 0.841920, 1.131826, 5.009777], [270.781332, 287.961125, 303.129424, 306.848786, 1533.546894]]
input_correlations: [[-0.688374, -0.195439, -0.244678, 0.514099, 0.459211, 0.000000, 0.000000, 0.000000], [-0.362644, -0.813467, -0.658288, -0.512579, -0.262241, 0.000000, 0.000000, 0.000000], [0.456615, 0.732140, 0.773291, 0.333085, -0.020571, 0.000000, 0.000000, 0.000000], [-0.180915, -0.546414, -0.518415, -0.775656, -0.501740, 0.000000, 0.000000, 0.000000], [-0.702791, -0.149509, -0.369047, 0.324994, 0.485958, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.472439, -3.380165, 3.171653, -3.903212, 0.506460]
pre_activation_std: [1.430121, 2.046151, 2.040020, 2.077518, 1.655894]
### 2
mean: [-0.937928, 1.374062, -0.732765, 2.000305, 1.945425]
std: [1.059730, 1.541459, 0.629160, 2.020447, 1.833363]
fourier: [[17.299677, 17.472737, 17.663398, 18.544725, 84.413489], [22.745866, 25.698985, 25.817818, 33.526637, 123.665615], [10.391988, 10.609596, 10.749834, 12.187501, 65.948873], [31.087951, 33.109638, 34.121943, 42.094092, 180.027468], [29.164389, 29.475043, 30.482168, 36.992045, 175.088303]]
input_correlations: [[0.362955, -0.634228, -0.988232, -0.540689, 0.489547, 0.000000, 0.000000, 0.000000], [0.982570, 0.286379, -0.149833, 0.338980, 0.963300, 0.000000, 0.000000, 0.000000], [0.597690, -0.461427, -0.915579, -0.362004, 0.661089, 0.000000, 0.000000, 0.000000], [-0.668369, 0.404821, 0.872604, 0.300996, -0.756592, 0.000000, 0.000000, 0.000000], [-0.603327, 0.445387, 0.905366, 0.343796, -0.715101, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.937928, 1.374062, -0.732765, 2.000305, 1.945425]
pre_activation_std: [1.059730, 1.541459, 0.629160, 2.020447, 1.833363]
### 4
mean: [3.254301, 2.790994, 0.718686, -0.795363, -0.602803]
std: [2.627744, 3.287247, 1.684385, 1.510505, 1.092755]
fourier: [[43.917656, 45.976552, 46.631564, 46.664255, 292.887071], [49.162601, 52.889038, 54.842292, 74.724424, 251.189478], [23.496240, 24.279956, 29.645209, 39.858482, 64.681695], [22.452422, 23.409182, 24.246591, 34.749525, 71.582637], [15.202843, 15.387018, 19.032357, 26.111582, 54.252295]]
input_correlations: [[-0.319403, -0.329199, -0.195442, 0.990084, 0.993796, 0.000000, 0.000000, 0.000000], [-0.391134, -0.710395, -0.457728, 0.948817, 0.937655, 0.000000, 0.000000, 0.000000], [-0.402834, -0.842890, -0.553018, 0.860575, 0.843997, 0.000000, 0.000000, 0.000000], [0.316802, 0.689355, 0.393866, -0.953369, -0.942734, 0.000000, 0.000000, 0.000000], [0.370846, 0.826793, 0.526339, -0.874635, -0.858242, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.254301, 2.790994, 0.718686, -0.795363, -0.602803]
pre_activation_std: [2.627744, 3.287247, 1.684385, 1.510505, 1.092755]
### 6
mean: [4.778206, 4.963577, -4.022648, 3.646962, 3.223279]
std: [4.319339, 4.255157, 4.116868, 3.969961, 2.970627]
fourier: [[72.599670, 76.123433, 82.107705, 85.386615, 430.038577], [72.180941, 76.237007, 82.079580, 82.682266, 446.721912], [66.581082, 67.893435, 73.650011, 82.695945, 362.038404], [64.408193, 66.315248, 72.018378, 85.627486, 328.226580], [49.482255, 51.549972, 55.604118, 58.333822, 290.095071]]
input_correlations: [[0.979828, 0.997173, 0.971162, -0.482517, -0.434446, 0.000000, 0.000000, 0.000000], [0.979995, 0.997611, 0.974503, -0.460953, -0.412461, 0.000000, 0.000000, 0.000000], [-0.988101, -0.986147, -0.945772, 0.511693, 0.462048, 0.000000, 0.000000, 0.000000], [0.945776, 0.989399, 0.962935, -0.597535, -0.555981, 0.000000, 0.000000, 0.000000], [0.986046, 0.993859, 0.963277, -0.478099, -0.429284, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [4.778206, 4.963577, -4.022648, 3.646962, 3.223279]
pre_activation_std: [4.319339, 4.255157, 4.116868, 3.969961, 2.970627]
### 8
mean: [8.011994, -2.820768, -1.962318, 9.568969, 11.852995]
std: [7.541342, 2.808115, 1.660132, 8.997557, 11.047421]
fourier: [[127.368835, 133.760700, 144.016435, 148.758055, 721.079583], [46.833456, 48.786131, 53.164211, 57.110679, 253.869098], [28.266055, 30.137617, 31.410523, 32.102118, 176.608628], [153.020509, 161.607667, 173.616015, 176.642775, 861.207241], [187.627007, 197.833069, 212.650655, 216.786438, 1066.769510]]
input_correlations: [[0.999693, 0.999594, -0.399404, 0.996952, 0.998800, 0.000000, 0.000000, 0.000000], [-0.996626, -0.996598, 0.447584, -0.994644, -0.994518, 0.000000, 0.000000, 0.000000], [-0.999055, -0.999029, 0.342514, -0.995854, -0.999314, 0.000000, 0.000000, 0.000000], [0.999740, 0.999791, -0.390324, 0.998175, 0.998379, 0.000000, 0.000000, 0.000000], [0.999814, 0.999822, -0.390625, 0.997857, 0.998664, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [8.011994, -2.820768, -1.962318, 9.568969, 11.852995]
pre_activation_std: [7.541342, 2.808115, 1.660132, 8.997557, 11.047421]
### 10
mean: [-8.336796, 16.585419, -3.273255, -1.573586, 16.967037]
std: [8.325666, 15.444926, 3.362108, 1.390682, 15.862467]
fourier: [[142.281974, 151.043411, 161.318584, 161.518637, 750.311588], [265.114332, 281.663638, 297.195639, 300.416440, 1492.687724], [56.793556, 60.191725, 64.443673, 66.087086, 294.592980], [24.159864, 25.629271, 25.783551, 27.285283, 141.622778], [271.126307, 287.659152, 307.180169, 307.227962, 1527.033359]]
input_correlations: [[-0.999886, 0.277292, -0.822935, -0.999947, -0.999968, 0.000000, 0.000000, 0.000000], [0.999942, -0.266236, 0.825518, 0.999983, 0.999992, 0.000000, 0.000000, 0.000000], [-0.999547, 0.298080, -0.817040, -0.999430, -0.999537, 0.000000, 0.000000, 0.000000], [-0.998045, 0.212493, -0.832142, -0.997674, -0.997730, 0.000000, 0.000000, 0.000000], [0.999943, -0.275163, 0.823518, 0.999947, 0.999983, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-8.336796, 16.585419, -3.273255, -1.573586, 16.967037]
pre_activation_std: [8.325666, 15.444926, 3.362108, 1.390682, 15.862467]
### 12
mean: [-14.878060]
std: [14.108957]
fourier: [[240.418675, 255.418558, 272.754182, 274.675860, 1339.025288]]
input_correlations: [[0.466040, -0.999811, 0.402871, -0.590881, -0.999854, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-14.878060]
pre_activation_std: [14.108957]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.12767863273620605, "std": 0.3142715096473694, "fourier": [4.33423425979146, 4.499829039517388, 4.877687913851085, 7.382760880069801, 11.491076754676328], "input_correlations": [-0.6883741502452076, -0.19543943512087936, -0.24467802295097063, 0.514098909558661, 0.4592108326272323, 0.0, 0.0, 0.0], "pre_activation_mean": 0.47243884205818176, "pre_activation_std": 1.430120825767517}, "1": {"mean": 16.609766006469727, "std": 15.416948318481445, "fourier": [265.11604422381697, 281.8980173590732, 295.5595632773192, 300.3917633683847, 1494.8790444396436], "input_correlations": [-0.3626440875712159, -0.8134669506458918, -0.6582875582152973, -0.512578849407838, -0.2622406061051604, 0.0, 0.0, 0.0], "pre_activation_mean": -3.3801653385162354, "pre_activation_std": 2.0461506843566895}, "2": {"mean": 0.05955316871404648, "std": 0.1832088828086853, "fourier": [2.540308904551243, 2.727953660845661, 2.7463130367061033, 3.9314285650561582, 5.359785382616792], "input_correlations": [0.4566151148324149, 0.7321396415867109, 0.7732907853795419, 0.33308528243041674, -0.020570701843243354, 0.0, 0.0, 0.0], "pre_activation_mean": 3.1716532707214355, "pre_activation_std": 2.040020227432251}, "3": {"mean": -0.05566418915987015, "std": 0.050115153193473816, "fourier": [0.6919967789060026, 0.8019480494445339, 0.8419204404208261, 1.1318264433374428, 5.0097769580897875], "input_correlations": [-0.18091540218429733, -0.5464142265349072, -0.5184152532513701, -0.7756559171077243, -0.5017396904304721, 0.0, 0.0, 0.0], "pre_activation_mean": -3.903211832046509, "pre_activation_std": 2.0775182247161865}, "4": {"mean": 17.039409637451172, "std": 15.7811861038208, "fourier": [270.78133162438945, 287.96112456334527, 303.12942363805087, 306.84878605041683, 1533.5468944553286], "input_correlations": [-0.7027914114849582, -0.14950908975155278, -0.36904677273676434, 0.32499439075408026, 0.485958228869115, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5064602494239807, "pre_activation_std": 1.6558939218521118}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -0.9379276037216187, "std": 1.0597296953201294, "fourier": [17.29967695966568, 17.472737013689805, 17.663397782584898, 18.544724507314694, 84.4134892821312], "input_correlations": [0.36295539518419645, -0.6342277458459279, -0.9882316176396938, -0.5406890915009539, 0.4895470073445638, 0.0, 0.0, 0.0], "pre_activation_mean": -0.9379276037216187, "pre_activation_std": 1.0597296953201294}, "1": {"mean": 1.374062418937683, "std": 1.5414594411849976, "fourier": [22.745865741040934, 25.698985219885458, 25.81781761068945, 33.52663665249178, 123.6656152009964], "input_correlations": [0.9825704520178586, 0.2863790827745803, -0.14983323229927717, 0.3389800107862996, 0.9633002421042509, 0.0, 0.0, 0.0], 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"float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.495304, -0.056178, -0.095083, 0.289725, 0.42683], [0.003237, -0.674872, -0.523907, -0.283702, -0.125698], [0.14036, 0.516189, 0.704958, 0.206952, -0.244565], [0.068474, -0.307637, -0.428818, -0.624483, -0.37623], [-0.620641, 0.106843, -0.255272, 0.12132, 0.596898]], "network.0.bias": [0.24208, -0.296633, 0.441629, -0.728903, 0.621019], "network.2.weight": [[0.016284, -0.279259, -0.458524, -0.535141, 0.148859], [0.799041, 0.435233, 0.108269, -0.05602, 0.692783], [0.324237, 0.70682, -0.262043, -0.271062, -0.071225], [-0.540962, -0.047667, 0.710592, -0.353056, -0.422297], [-0.137066, -0.627531, 0.690994, -0.654421, -0.568903]], "network.2.bias": [0.341397, -0.082356, 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0.6746003925800323, "train_acc": 0.58, "val_loss": 0.7072403430938721, "val_acc": 0.46}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6567316055297852, "train_acc": 0.58, "val_loss": 0.6649128794670105, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.5972933173179626, "train_acc": 0.51, "val_loss": 0.498473584651947, "val_acc": 0.46}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.4811830520629883, "train_acc": 0.585, "val_loss": 0.40334972739219666, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.4183885306119919, "train_acc": 0.825, "val_loss": 0.3291970491409302, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.44039109349250793, "train_acc": 0.83, "val_loss": 0.29157376289367676, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.36737070977687836, "train_acc": 0.835, "val_loss": 0.2990659475326538, "val_acc": 0.88}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.36803923547267914, "train_acc": 0.84, "val_loss": 0.300557404756546, "val_acc": 0.9}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.349126473069191, "train_acc": 0.825, "val_loss": 0.3362765610218048, "val_acc": 0.9}], "summary": {"total_epochs": 11, "degraded_epochs": 4, "improved_epochs": 7, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7117758393287659, "final_val_loss": 0.6649128794670105, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.498473584651947, "final_val_loss": 0.3362765610218048, "initial_val_acc": 0.46, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 9}, "improvement": 0.44, "first_improvement_epoch": 3}} |
18 | {"target_pattern": "starts_with", "degraded_accuracy": 0.58, "improved_accuracy": 0.78, "improvement": 0.20000000000000007, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7287, "learning_rate": 0.028993303041424494, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [2.902481, -0.103878, 3.287167, -0.085098, 3.852512, -0.060980, -0.100146]
std: [4.067182, 0.046789, 4.279399, 0.047707, 5.084844, 0.069687, 0.047486]
fourier: [[65.828847, 66.449592, 70.952596, 71.275775, 261.223345], [0.734743, 0.745821, 0.771934, 0.888724, 9.348978], [69.234756, 69.921086, 73.190200, 73.927757, 295.845080], [0.670675, 0.720862, 0.794529, 0.924960, 7.658855], [83.397872, 83.601140, 85.610339, 87.999971, 346.726013], [0.972792, 1.098722, 1.105173, 1.323899, 5.488174], [0.805785, 0.836866, 0.872931, 1.020322, 9.013168]]
input_correlations: [[0.947131, 0.531051, 0.358030, 0.001075, -0.051724, 0.000000, 0.000000, 0.000000], [0.255836, 0.668766, 0.316392, 0.295490, -0.623225, 0.000000, 0.000000, 0.000000], [0.127644, 0.069650, 0.278959, 0.102719, -0.812840, 0.000000, 0.000000, 0.000000], [-0.630944, -0.144996, 0.163269, 0.643863, 0.272417, 0.000000, 0.000000, 0.000000], [0.706883, 0.780741, 0.179757, 0.152244, -0.301953, 0.000000, 0.000000, 0.000000], [0.343860, 0.765097, 0.145351, 0.100858, -0.604061, 0.000000, 0.000000, 0.000000], [-0.737820, -0.350991, 0.135279, 0.352892, -0.304999, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.587256, 1.508272, 0.052171, 1.291817, 1.281030, 0.751126, 0.018419]
pre_activation_std: [1.763061, 1.746597, 1.093763, 1.841691, 2.193115, 1.569755, 1.012809]
### 2
mean: [0.988378, 1.561771, 1.892618, 2.200436, -2.092991, 0.206219, -1.989216]
std: [1.238176, 1.957097, 1.275578, 2.941703, 0.996868, 0.915871, 0.979718]
fourier: [[18.160931, 18.252079, 21.951045, 23.638529, 88.954064], [29.892501, 30.045586, 33.959692, 36.425407, 140.559349], [20.066966, 20.953207, 23.164233, 25.091352, 170.335595], [43.822760, 45.460660, 50.617530, 52.669673, 198.039235], [13.878348, 13.914233, 14.648693, 15.960216, 188.369153], [14.615700, 15.346199, 15.484263, 15.809598, 18.559718], [13.672607, 13.912136, 15.722474, 16.473552, 179.029474]]
input_correlations: [[0.920432, 0.738888, 0.477121, -0.467337, 0.866097, 0.776107, -0.098327, 0.000000], [0.930961, 0.777109, 0.374219, -0.410335, 0.963042, 0.869990, -0.188378, 0.000000], [0.562309, 0.982208, 0.670439, 0.164407, 0.768435, 0.870606, 0.334599, 0.000000], [0.912622, 0.748613, 0.267806, -0.483868, 0.971838, 0.888571, -0.305002, 0.000000], [0.088067, -0.497580, -0.639712, -0.874683, -0.065106, -0.190675, -0.788938, 0.000000], [-0.811301, -0.344563, 0.051974, 0.854517, -0.752648, -0.595126, 0.634327, 0.000000], [0.195168, -0.439775, -0.554191, -0.906530, 0.020419, -0.111888, -0.811878, 0.000000]]
pre_activation_mean: [0.988378, 1.561771, 1.892618, 2.200436, -2.092991, 0.206219, -1.989216]
pre_activation_std: [1.238176, 1.957097, 1.275578, 2.941703, 0.996868, 0.915871, 0.979718]
### 4
mean: [1.895355, 1.882653, 0.279942, 0.968120, 2.126509, 1.051318, 0.928183]
std: [2.349982, 2.152073, 0.268595, 1.493616, 2.660094, 1.597203, 1.191162]
fourier: [[36.165577, 38.319908, 38.881262, 41.270076, 170.581946], [32.598075, 33.567773, 38.971002, 39.447458, 169.438757], [4.203094, 4.219776, 4.376971, 5.461501, 25.194767], [22.882717, 24.688975, 25.265255, 25.546605, 87.130813], [39.492659, 42.053381, 46.641981, 47.514719, 191.385807], [24.502773, 24.637831, 26.576802, 26.972676, 94.618583], [18.618759, 18.869300, 21.678922, 21.766014, 83.536501]]
input_correlations: [[0.968710, 0.990331, 0.684500, 0.992831, 0.021952, -0.555365, -0.164671, 0.000000], [0.971567, 0.994396, 0.793059, 0.986674, 0.142346, -0.482056, -0.038651, 0.000000], [0.946327, 0.898332, 0.811823, 0.836769, 0.307966, -0.162923, 0.120585, 0.000000], [0.911225, 0.939988, 0.541583, 0.960108, -0.164352, -0.714723, -0.335882, 0.000000], [0.960416, 0.994664, 0.737448, 0.998111, 0.080851, -0.522291, -0.101015, 0.000000], [0.949096, 0.968877, 0.596953, 0.978384, -0.082618, -0.630586, -0.266566, 0.000000], [0.966291, 0.998151, 0.779831, 0.992359, 0.164251, -0.424083, -0.022113, 0.000000]]
pre_activation_mean: [1.895355, 1.882653, 0.279942, 0.968120, 2.126509, 1.051318, 0.928183]
pre_activation_std: [2.349982, 2.152073, 0.268595, 1.493616, 2.660094, 1.597203, 1.191162]
### 6
mean: [2.898748, -0.847430, 3.336188, -0.654778, 3.891778, -1.584185, -0.922537]
std: [4.081106, 0.776922, 4.252545, 0.747539, 5.064699, 1.970202, 0.987428]
fourier: [[64.875934, 66.203393, 70.635653, 71.494359, 260.887281], [11.854556, 12.848468, 13.892308, 14.886546, 76.268739], [67.721154, 69.842862, 72.371151, 73.302254, 300.256954], [12.123245, 12.251825, 12.389816, 13.230992, 58.929991], [81.992235, 83.567374, 84.770602, 87.525558, 350.259981], [30.611089, 31.628575, 34.516120, 34.621437, 142.576690], [15.924222, 16.436457, 16.656658, 17.084783, 83.028336]]
input_correlations: [[0.999057, 0.990561, 0.869097, 0.983218, 0.998660, 0.990129, 0.993879, 0.000000], [-0.977344, -0.997973, -0.886442, -0.938637, -0.990699, -0.949987, -0.990098, 0.000000], [0.999377, 0.985760, 0.854687, 0.988704, 0.997311, 0.993467, 0.990282, 0.000000], [-0.999137, -0.980284, -0.868994, -0.988807, -0.991926, -0.996378, -0.986163, 0.000000], [0.999615, 0.983256, 0.857342, 0.990404, 0.995596, 0.995575, 0.988921, 0.000000], [-0.997963, -0.992612, -0.865078, -0.980061, -0.999639, -0.986612, -0.993912, 0.000000], [-0.991620, -0.959431, -0.836216, -0.995488, -0.981165, -0.998891, -0.976412, 0.000000]]
pre_activation_mean: [2.898748, -0.847430, 3.336188, -0.654778, 3.891778, -1.584185, -0.922537]
pre_activation_std: [4.081106, 0.776922, 4.252545, 0.747539, 5.064699, 1.970202, 0.987428]
### 8
mean: [-3.366037]
std: [4.943405]
fourier: [[80.662420, 80.662514, 84.611413, 85.833861, 302.943345]]
input_correlations: [[-0.999576, -0.572483, -0.999914, -0.066124, -0.999781, -0.408512, -0.721087, 0.000000]]
pre_activation_mean: [-3.366037]
pre_activation_std: [4.943405]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.776007,
0.205459,
0.070441,
0.005494,
-0.220417
],
[
0.12861,
0.434935,
0.294629,
0.218593,
-0.719086
],
[
0.138016,
-0.135565,
0.260011,
0.176099,
-0.598261
],
[
-0.624471,
-0.210239,
0.354137,
0.567114,
0.219774
],
[
0.659705,
0.678301,
-0.059206,
0.057865,
-0.48612
],
[
0.164704,
0.581774,
0.054188,
-0.012767,
-0.55648
],
[
-0.336334,
-0.223184,
0.26714,
0.244535,
-0.202665
]
],
"network.0.bias": [
0.360089,
0.358341,
-0.055466,
0.225086,
-0.176818,
0.086548,
0.011195
],
"network.2.weight": [
[
0.476379,
0.137115,
0.459628,
-0.262073,
-0.096377,
0.196819,
0.234457
],
[
0.402787,
-0.012417,
0.415391,
-0.228472,
0.41753,
0.293091,
0.334421
],
[
0.131202,
0.435339,
0.293884,
0.2052,
-0.056505,
0.405428,
0.023688
],
[
0.463391,
0.287907,
0.349109,
-0.380493,
0.560413,
0.37581,
-0.276102
],
[
-0.137609,
-0.176993,
-0.363563,
-0.602016,
0.160956,
-0.173627,
0.076617
],
[
-0.031467,
-0.004992,
-0.178173,
0.390735,
-0.28767,
0.155666,
0.17352
],
[
0.015821,
-0.457209,
0.241464,
-0.486229,
-0.066152,
0.302759,
-0.311383
]
],
"network.2.bias": [
0.156703,
0.196254,
0.267196,
0.402937,
-0.66283,
-0.048705,
-0.717428
],
"network.4.weight": [
[
0.563593,
0.161881,
-0.118211,
0.5076,
-0.404698,
-0.224011,
0.199002
],
[
0.484148,
0.214852,
0.361279,
0.250481,
-0.304421,
-0.384171,
-0.375205
],
[
0.220741,
0.14938,
0.050752,
-0.111959,
-0.496545,
0.11376,
-0.146622
],
[
0.064259,
0.286967,
-0.177292,
0.281926,
-0.174572,
-0.627983,
-0.405393
],
[
0.204353,
0.251042,
0.117029,
0.613745,
-0.135116,
-0.257851,
-0.447729
],
[
0.30683,
0.256789,
-0.23324,
0.304634,
-0.042086,
-0.297195,
-0.264224
],
[
0.050746,
0.290973,
0.031968,
0.20218,
-0.036687,
0.15919,
-0.278897
]
],
"network.4.bias": [
0.240425,
-0.048866,
-0.094736,
0.339115,
0.00233,
0.181184,
-0.163715
],
"network.6.weight": [
[
0.312332,
0.471512,
-0.083122,
0.348669,
0.266267,
0.405367,
0.444653
],
[
0.050545,
-0.268708,
0.047059,
-0.093553,
-0.164192,
0.244279,
-0.106882
],
[
0.277508,
0.237783,
-0.117954,
0.596743,
0.592872,
0.416293,
0.046784
],
[
-0.413833,
0.060251,
-0.062455,
0.085717,
0.07011,
-0.082591,
-0.053302
],
[
0.4621,
0.167264,
0.457155,
0.649601,
0.503761,
0.795353,
0.042559
],
[
-0.280847,
-0.186013,
0.308939,
-0.05663,
-0.285464,
-0.00658,
-0.097405
],
[
0.005598,
0.285684,
-0.426366,
-0.200004,
-0.150598,
-0.328205,
-0.280798
]
],
"network.6.bias": [
-0.251476,
-0.182994,
0.091539,
-0.086986,
0.060391,
-0.037383,
-0.270414
],
"network.8.weight": [
[
-0.362457,
-0.048861,
-0.423774,
-0.040292,
-0.325525,
0.07309,
-0.066457
]
],
"network.8.bias": [
0.322389
]
}
## Activation Signature
### 0
mean: [2.902481, -0.103878, 3.287167, -0.085098, 3.852512, -0.060980, -0.100146]
std: [4.067182, 0.046789, 4.279399, 0.047707, 5.084844, 0.069687, 0.047486]
fourier: [[65.828847, 66.449592, 70.952596, 71.275775, 261.223345], [0.734743, 0.745821, 0.771934, 0.888724, 9.348978], [69.234756, 69.921086, 73.190200, 73.927757, 295.845080], [0.670675, 0.720862, 0.794529, 0.924960, 7.658855], [83.397872, 83.601140, 85.610339, 87.999971, 346.726013], [0.972792, 1.098722, 1.105173, 1.323899, 5.488174], [0.805785, 0.836866, 0.872931, 1.020322, 9.013168]]
input_correlations: [[0.947131, 0.531051, 0.358030, 0.001075, -0.051724, 0.000000, 0.000000, 0.000000], [0.255836, 0.668766, 0.316392, 0.295490, -0.623225, 0.000000, 0.000000, 0.000000], [0.127644, 0.069650, 0.278959, 0.102719, -0.812840, 0.000000, 0.000000, 0.000000], [-0.630944, -0.144996, 0.163269, 0.643863, 0.272417, 0.000000, 0.000000, 0.000000], [0.706883, 0.780741, 0.179757, 0.152244, -0.301953, 0.000000, 0.000000, 0.000000], [0.343860, 0.765097, 0.145351, 0.100858, -0.604061, 0.000000, 0.000000, 0.000000], [-0.737820, -0.350991, 0.135279, 0.352892, -0.304999, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.587256, 1.508272, 0.052171, 1.291817, 1.281030, 0.751126, 0.018419]
pre_activation_std: [1.763061, 1.746597, 1.093763, 1.841691, 2.193115, 1.569755, 1.012809]
### 2
mean: [0.988378, 1.561771, 1.892618, 2.200436, -2.092991, 0.206219, -1.989216]
std: [1.238176, 1.957097, 1.275578, 2.941703, 0.996868, 0.915871, 0.979718]
fourier: [[18.160931, 18.252079, 21.951045, 23.638529, 88.954064], [29.892501, 30.045586, 33.959692, 36.425407, 140.559349], [20.066966, 20.953207, 23.164233, 25.091352, 170.335595], [43.822760, 45.460660, 50.617530, 52.669673, 198.039235], [13.878348, 13.914233, 14.648693, 15.960216, 188.369153], [14.615700, 15.346199, 15.484263, 15.809598, 18.559718], [13.672607, 13.912136, 15.722474, 16.473552, 179.029474]]
input_correlations: [[0.920432, 0.738888, 0.477121, -0.467337, 0.866097, 0.776107, -0.098327, 0.000000], [0.930961, 0.777109, 0.374219, -0.410335, 0.963042, 0.869990, -0.188378, 0.000000], [0.562309, 0.982208, 0.670439, 0.164407, 0.768435, 0.870606, 0.334599, 0.000000], [0.912622, 0.748613, 0.267806, -0.483868, 0.971838, 0.888571, -0.305002, 0.000000], [0.088067, -0.497580, -0.639712, -0.874683, -0.065106, -0.190675, -0.788938, 0.000000], [-0.811301, -0.344563, 0.051974, 0.854517, -0.752648, -0.595126, 0.634327, 0.000000], [0.195168, -0.439775, -0.554191, -0.906530, 0.020419, -0.111888, -0.811878, 0.000000]]
pre_activation_mean: [0.988378, 1.561771, 1.892618, 2.200436, -2.092991, 0.206219, -1.989216]
pre_activation_std: [1.238176, 1.957097, 1.275578, 2.941703, 0.996868, 0.915871, 0.979718]
### 4
mean: [1.895355, 1.882653, 0.279942, 0.968120, 2.126509, 1.051318, 0.928183]
std: [2.349982, 2.152073, 0.268595, 1.493616, 2.660094, 1.597203, 1.191162]
fourier: [[36.165577, 38.319908, 38.881262, 41.270076, 170.581946], [32.598075, 33.567773, 38.971002, 39.447458, 169.438757], [4.203094, 4.219776, 4.376971, 5.461501, 25.194767], [22.882717, 24.688975, 25.265255, 25.546605, 87.130813], [39.492659, 42.053381, 46.641981, 47.514719, 191.385807], [24.502773, 24.637831, 26.576802, 26.972676, 94.618583], [18.618759, 18.869300, 21.678922, 21.766014, 83.536501]]
input_correlations: [[0.968710, 0.990331, 0.684500, 0.992831, 0.021952, -0.555365, -0.164671, 0.000000], [0.971567, 0.994396, 0.793059, 0.986674, 0.142346, -0.482056, -0.038651, 0.000000], [0.946327, 0.898332, 0.811823, 0.836769, 0.307966, -0.162923, 0.120585, 0.000000], [0.911225, 0.939988, 0.541583, 0.960108, -0.164352, -0.714723, -0.335882, 0.000000], [0.960416, 0.994664, 0.737448, 0.998111, 0.080851, -0.522291, -0.101015, 0.000000], [0.949096, 0.968877, 0.596953, 0.978384, -0.082618, -0.630586, -0.266566, 0.000000], [0.966291, 0.998151, 0.779831, 0.992359, 0.164251, -0.424083, -0.022113, 0.000000]]
pre_activation_mean: [1.895355, 1.882653, 0.279942, 0.968120, 2.126509, 1.051318, 0.928183]
pre_activation_std: [2.349982, 2.152073, 0.268595, 1.493616, 2.660094, 1.597203, 1.191162]
### 6
mean: [2.898748, -0.847430, 3.336188, -0.654778, 3.891778, -1.584185, -0.922537]
std: [4.081106, 0.776922, 4.252545, 0.747539, 5.064699, 1.970202, 0.987428]
fourier: [[64.875934, 66.203393, 70.635653, 71.494359, 260.887281], [11.854556, 12.848468, 13.892308, 14.886546, 76.268739], [67.721154, 69.842862, 72.371151, 73.302254, 300.256954], [12.123245, 12.251825, 12.389816, 13.230992, 58.929991], [81.992235, 83.567374, 84.770602, 87.525558, 350.259981], [30.611089, 31.628575, 34.516120, 34.621437, 142.576690], [15.924222, 16.436457, 16.656658, 17.084783, 83.028336]]
input_correlations: [[0.999057, 0.990561, 0.869097, 0.983218, 0.998660, 0.990129, 0.993879, 0.000000], [-0.977344, -0.997973, -0.886442, -0.938637, -0.990699, -0.949987, -0.990098, 0.000000], [0.999377, 0.985760, 0.854687, 0.988704, 0.997311, 0.993467, 0.990282, 0.000000], [-0.999137, -0.980284, -0.868994, -0.988807, -0.991926, -0.996378, -0.986163, 0.000000], [0.999615, 0.983256, 0.857342, 0.990404, 0.995596, 0.995575, 0.988921, 0.000000], [-0.997963, -0.992612, -0.865078, -0.980061, -0.999639, -0.986612, -0.993912, 0.000000], [-0.991620, -0.959431, -0.836216, -0.995488, -0.981165, -0.998891, -0.976412, 0.000000]]
pre_activation_mean: [2.898748, -0.847430, 3.336188, -0.654778, 3.891778, -1.584185, -0.922537]
pre_activation_std: [4.081106, 0.776922, 4.252545, 0.747539, 5.064699, 1.970202, 0.987428]
### 8
mean: [-3.366037]
std: [4.943405]
fourier: [[80.662420, 80.662514, 84.611413, 85.833861, 302.943345]]
input_correlations: [[-0.999576, -0.572483, -0.999914, -0.066124, -0.999781, -0.408512, -0.721087, 0.000000]]
pre_activation_mean: [-3.366037]
pre_activation_std: [4.943405]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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[[0.563593, 0.161881, -0.118211, 0.5076, -0.404698, -0.224011, 0.199002], [0.484148, 0.214852, 0.361279, 0.250481, -0.304421, -0.384171, -0.375205], [0.220741, 0.14938, 0.050752, -0.111959, -0.496545, 0.11376, -0.146622], [0.064259, 0.286967, -0.177292, 0.281926, -0.174572, -0.627983, -0.405393], [0.204353, 0.251042, 0.117029, 0.613745, -0.135116, -0.257851, -0.447729], [0.30683, 0.256789, -0.23324, 0.304634, -0.042086, -0.297195, -0.264224], [0.050746, 0.290973, 0.031968, 0.20218, -0.036687, 0.15919, -0.278897]], "network.4.bias": [0.240425, -0.048866, -0.094736, 0.339115, 0.00233, 0.181184, -0.163715], "network.6.weight": [[0.312332, 0.471512, -0.083122, 0.348669, 0.266267, 0.405367, 0.444653], [0.050545, -0.268708, 0.047059, -0.093553, -0.164192, 0.244279, -0.106882], [0.277508, 0.237783, -0.117954, 0.596743, 0.592872, 0.416293, 0.046784], [-0.413833, 0.060251, -0.062455, 0.085717, 0.07011, -0.082591, -0.053302], [0.4621, 0.167264, 0.457155, 0.649601, 0.503761, 0.795353, 0.042559], [-0.280847, -0.186013, 0.308939, -0.05663, -0.285464, -0.00658, -0.097405], [0.005598, 0.285684, -0.426366, -0.200004, -0.150598, -0.328205, -0.280798]], "network.6.bias": [-0.251476, -0.182994, 0.091539, -0.086986, 0.060391, -0.037383, -0.270414], "network.8.weight": [[-0.362457, -0.048861, -0.423774, -0.040292, -0.325525, 0.07309, -0.066457]], "network.8.bias": [0.322389]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7199861109256744, "train_acc": 0.4, "val_loss": 0.6649367809295654, "val_acc": 0.7}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6695752441883087, "train_acc": 0.56, "val_loss": 0.6705575585365295, "val_acc": 0.42}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6280792653560638, "train_acc": 0.6, "val_loss": 0.6650630831718445, "val_acc": 0.42}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.581821471452713, "train_acc": 0.6, "val_loss": 0.6431294083595276, "val_acc": 0.42}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.557919979095459, "train_acc": 0.625, "val_loss": 0.6162686347961426, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.5634103119373322, "train_acc": 0.67, "val_loss": 0.6043566465377808, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5145224928855896, "train_acc": 0.75, "val_loss": 0.6018926501274109, "val_acc": 0.7}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5067187547683716, "train_acc": 0.755, "val_loss": 0.559942901134491, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.4701376110315323, "train_acc": 0.75, "val_loss": 0.5432320237159729, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.46988852322101593, "train_acc": 0.75, "val_loss": 0.5497900247573853, "val_acc": 0.74}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.46089135110378265, "train_acc": 0.77, "val_loss": 0.5531122088432312, "val_acc": 0.74}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.45361363887786865, "train_acc": 0.775, "val_loss": 0.5533303618431091, "val_acc": 0.74}], "summary": {"total_epochs": 12, "degraded_epochs": 5, "improved_epochs": 7, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.6649367809295654, "final_val_loss": 0.6162686347961426, "initial_val_acc": 0.7, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.6043566465377808, "final_val_loss": 0.5533303618431091, "initial_val_acc": 0.76, "final_val_acc": 0.74, "best_val_acc": 0.78, "best_epoch": 8}, "improvement": 0.20000000000000007, "first_improvement_epoch": 4}} |
19 | {"target_pattern": "palindrome", "degraded_accuracy": 0.46, "improved_accuracy": 0.94, "improvement": 0.4799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1291, "learning_rate": 0.05445951689049968, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.weight": [
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"network.12.weight": [
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"network.12.bias": [
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}
## Activation Signature
### 0
mean: [2.149648, 4.557867, 0.856254, 0.000000, 0.000000]
std: [2.729633, 5.640323, 0.734638, 0.000000, 0.000000]
fourier: [[43.317375, 43.697486, 54.955236, 56.256058, 193.468380], [90.109708, 90.246425, 112.304244, 116.140716, 410.208023], [11.824983, 11.847270, 13.237538, 13.372434, 77.062829], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.466839, -0.187871, -0.021247, -0.790031, -0.432442, 0.000000, 0.000000, 0.000000], [0.019565, -0.161311, 0.283942, 0.504552, 0.850120, 0.000000, 0.000000, 0.000000], [0.646952, 0.206401, 0.166841, 0.439078, 0.747911, 0.000000, 0.000000, 0.000000], [-0.121367, 0.277090, 0.533912, -0.343031, -0.568230, 0.000000, 0.000000, 0.000000], [-0.475127, 0.359149, -0.407240, 0.212135, -0.748295, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.568900, 1.317121, 2.033054, 0.769401, -0.066471]
pre_activation_std: [1.655361, 1.774388, 2.020519, 1.514934, 1.131714]
### 2
mean: [1.875982, 1.433732, -1.936270, 0.258769, 1.701630]
std: [2.547278, 0.502266, 1.530744, 0.481430, 1.971816]
fourier: [[36.836883, 40.915152, 48.319444, 52.724728, 168.838412], [8.012722, 8.876290, 8.994127, 10.957684, 129.035908], [22.793673, 28.995603, 29.183594, 33.883186, 174.264298], [7.528222, 8.270809, 8.543287, 10.744716, 23.289178], [31.935860, 32.066026, 35.654183, 39.788784, 153.146726]]
input_correlations: [[0.121150, 0.827269, 0.972959, -0.633548, -0.409562, 0.000000, 0.000000, 0.000000], [0.348385, 0.608998, 0.784553, 0.024461, -0.194714, 0.000000, 0.000000, 0.000000], [-0.054134, -0.894080, -0.928711, 0.331554, 0.427674, 0.000000, 0.000000, 0.000000], [0.286838, -0.709489, -0.396341, 0.525816, 0.701423, 0.000000, 0.000000, 0.000000], [0.095267, 0.776160, 0.970926, -0.684131, -0.434975, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.875982, 1.433732, -1.936270, 0.258769, 1.701630]
pre_activation_std: [2.547278, 0.502266, 1.530744, 0.481430, 1.971816]
### 4
mean: [0.355582, -0.233377, 2.433812, 2.874229, 0.329938]
std: [0.895459, 0.090591, 2.350131, 2.801300, 0.702337]
fourier: [[14.673290, 15.210587, 15.610027, 16.789772, 32.002384], [1.390903, 1.590028, 1.686304, 1.825423, 21.003942], [34.532252, 37.637434, 45.607725, 49.553000, 219.043098], [41.120690, 45.529006, 55.124959, 59.278359, 258.680622], [10.640892, 10.745808, 14.226708, 14.437683, 29.694400]]
input_correlations: [[-0.941266, -0.518084, 0.000000, 0.653579, -0.948755, 0.000000, 0.000000, 0.000000], [0.391668, -0.152621, 0.000000, -0.395898, 0.500475, 0.000000, 0.000000, 0.000000], [0.996614, 0.727522, 0.000000, -0.380989, 0.998663, 0.000000, 0.000000, 0.000000], [0.999053, 0.744215, 0.000000, -0.406712, 0.993983, 0.000000, 0.000000, 0.000000], [-0.992968, -0.700400, 0.000000, 0.361874, -0.986097, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.355582, -0.233377, 2.433812, 2.874229, 0.329938]
pre_activation_std: [0.895459, 0.090591, 2.350131, 2.801300, 0.702337]
### 6
mean: [2.337254, 0.952503, 2.638322, -0.539516, 1.960206]
std: [3.022178, 1.811669, 3.351795, 0.174961, 2.673710]
fourier: [[45.353961, 48.209914, 58.178817, 62.320959, 210.352849], [27.347538, 28.594585, 34.559478, 37.078921, 85.725274], [49.936288, 53.590186, 64.517349, 69.370870, 237.448966], [2.429248, 2.544924, 3.273731, 3.859616, 48.556441], [39.956353, 42.715309, 51.366776, 55.105458, 176.418511]]
input_correlations: [[-0.798761, 0.000000, 0.997422, 0.996653, -0.905481, 0.000000, 0.000000, 0.000000], [-0.804905, 0.000000, 0.996608, 0.993848, -0.916571, 0.000000, 0.000000, 0.000000], [-0.795039, 0.000000, 0.998317, 0.996990, -0.901562, 0.000000, 0.000000, 0.000000], [0.317616, 0.000000, -0.854675, -0.849751, 0.630681, 0.000000, 0.000000, 0.000000], [-0.801060, 0.000000, 0.997547, 0.996492, -0.904530, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.337254, 0.952503, 2.638322, -0.539516, 1.960206]
pre_activation_std: [3.022178, 1.811669, 3.351795, 0.174961, 2.673710]
### 8
mean: [3.471558, 0.110642, 2.169765, -0.363548, 3.671653]
std: [4.205932, 0.739285, 2.833390, 0.230635, 4.622921]
fourier: [[64.055889, 67.137520, 82.516324, 87.241761, 312.440232], [11.250745, 11.716175, 11.782888, 14.773668, 15.177642], [43.486623, 45.224643, 55.645784, 58.605704, 195.278827], [3.522303, 3.630719, 4.631061, 4.831296, 32.719305], [71.440236, 73.642348, 91.341625, 95.711371, 330.448756]]
input_correlations: [[0.999960, 0.995876, 0.999959, 0.000000, 0.999905, 0.000000, 0.000000, 0.000000], [-0.998700, -0.998940, -0.998365, 0.000000, -0.999229, 0.000000, 0.000000, 0.000000], [0.999971, 0.996128, 0.999874, 0.000000, 0.999939, 0.000000, 0.000000, 0.000000], [-0.997776, -0.998451, -0.998077, 0.000000, -0.998376, 0.000000, 0.000000, 0.000000], [0.999710, 0.997513, 0.999675, 0.000000, 0.999957, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.471558, 0.110642, 2.169765, -0.363548, 3.671653]
pre_activation_std: [4.205932, 0.739285, 2.833390, 0.230635, 4.622921]
### 10
mean: [2.034893, 4.380355, 0.404162, -1.494608, -1.436560]
std: [2.822821, 5.787080, 1.421536, 1.228462, 1.473636]
fourier: [[44.120681, 45.013149, 55.895480, 58.346597, 183.140347], [90.783730, 92.622918, 113.851979, 119.467764, 394.231950], [22.766573, 23.129859, 26.784747, 29.135121, 36.374545], [19.124452, 19.581158, 24.350584, 25.392715, 134.514681], [22.946747, 23.217411, 29.810776, 30.448186, 129.290377]]
input_correlations: [[0.999885, -0.850516, 0.999904, 0.000000, 0.999960, 0.000000, 0.000000, 0.000000], [0.999906, -0.856490, 0.999794, 0.000000, 0.999829, 0.000000, 0.000000, 0.000000], [-0.996305, 0.894231, -0.995390, 0.000000, -0.995480, 0.000000, 0.000000, 0.000000], [-0.999904, 0.848358, -0.999893, 0.000000, -0.999917, 0.000000, 0.000000, 0.000000], [-0.998464, 0.826049, -0.999189, 0.000000, -0.999213, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.034893, 4.380355, 0.404162, -1.494608, -1.436560]
pre_activation_std: [2.822821, 5.787080, 1.421536, 1.228462, 1.473636]
### 12
mean: [-1.980142]
std: [4.122865]
fourier: [[66.485516, 66.920586, 79.129663, 84.666814, 178.212784]]
input_correlations: [[-0.996329, -0.997844, 0.870400, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.980142]
pre_activation_std: [4.122865]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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"network.0.bias": [
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"network.2.weight": [
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[
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"network.6.weight": [
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],
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"network.8.bias": [
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"network.10.weight": [
[
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[
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[
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"network.12.bias": [
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}
## Activation Signature
### 0
mean: [2.149648, 4.557867, 0.856254, 0.000000, 0.000000]
std: [2.729633, 5.640323, 0.734638, 0.000000, 0.000000]
fourier: [[43.317375, 43.697486, 54.955236, 56.256058, 193.468380], [90.109708, 90.246425, 112.304244, 116.140716, 410.208023], [11.824983, 11.847270, 13.237538, 13.372434, 77.062829], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.466839, -0.187871, -0.021247, -0.790031, -0.432442, 0.000000, 0.000000, 0.000000], [0.019565, -0.161311, 0.283942, 0.504552, 0.850120, 0.000000, 0.000000, 0.000000], [0.646952, 0.206401, 0.166841, 0.439078, 0.747911, 0.000000, 0.000000, 0.000000], [-0.121367, 0.277090, 0.533912, -0.343031, -0.568230, 0.000000, 0.000000, 0.000000], [-0.475127, 0.359149, -0.407240, 0.212135, -0.748295, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.568900, 1.317121, 2.033054, 0.769401, -0.066471]
pre_activation_std: [1.655361, 1.774388, 2.020519, 1.514934, 1.131714]
### 2
mean: [1.875982, 1.433732, -1.936270, 0.258769, 1.701630]
std: [2.547278, 0.502266, 1.530744, 0.481430, 1.971816]
fourier: [[36.836883, 40.915152, 48.319444, 52.724728, 168.838412], [8.012722, 8.876290, 8.994127, 10.957684, 129.035908], [22.793673, 28.995603, 29.183594, 33.883186, 174.264298], [7.528222, 8.270809, 8.543287, 10.744716, 23.289178], [31.935860, 32.066026, 35.654183, 39.788784, 153.146726]]
input_correlations: [[0.121150, 0.827269, 0.972959, -0.633548, -0.409562, 0.000000, 0.000000, 0.000000], [0.348385, 0.608998, 0.784553, 0.024461, -0.194714, 0.000000, 0.000000, 0.000000], [-0.054134, -0.894080, -0.928711, 0.331554, 0.427674, 0.000000, 0.000000, 0.000000], [0.286838, -0.709489, -0.396341, 0.525816, 0.701423, 0.000000, 0.000000, 0.000000], [0.095267, 0.776160, 0.970926, -0.684131, -0.434975, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.875982, 1.433732, -1.936270, 0.258769, 1.701630]
pre_activation_std: [2.547278, 0.502266, 1.530744, 0.481430, 1.971816]
### 4
mean: [0.355582, -0.233377, 2.433812, 2.874229, 0.329938]
std: [0.895459, 0.090591, 2.350131, 2.801300, 0.702337]
fourier: [[14.673290, 15.210587, 15.610027, 16.789772, 32.002384], [1.390903, 1.590028, 1.686304, 1.825423, 21.003942], [34.532252, 37.637434, 45.607725, 49.553000, 219.043098], [41.120690, 45.529006, 55.124959, 59.278359, 258.680622], [10.640892, 10.745808, 14.226708, 14.437683, 29.694400]]
input_correlations: [[-0.941266, -0.518084, 0.000000, 0.653579, -0.948755, 0.000000, 0.000000, 0.000000], [0.391668, -0.152621, 0.000000, -0.395898, 0.500475, 0.000000, 0.000000, 0.000000], [0.996614, 0.727522, 0.000000, -0.380989, 0.998663, 0.000000, 0.000000, 0.000000], [0.999053, 0.744215, 0.000000, -0.406712, 0.993983, 0.000000, 0.000000, 0.000000], [-0.992968, -0.700400, 0.000000, 0.361874, -0.986097, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.355582, -0.233377, 2.433812, 2.874229, 0.329938]
pre_activation_std: [0.895459, 0.090591, 2.350131, 2.801300, 0.702337]
### 6
mean: [2.337254, 0.952503, 2.638322, -0.539516, 1.960206]
std: [3.022178, 1.811669, 3.351795, 0.174961, 2.673710]
fourier: [[45.353961, 48.209914, 58.178817, 62.320959, 210.352849], [27.347538, 28.594585, 34.559478, 37.078921, 85.725274], [49.936288, 53.590186, 64.517349, 69.370870, 237.448966], [2.429248, 2.544924, 3.273731, 3.859616, 48.556441], [39.956353, 42.715309, 51.366776, 55.105458, 176.418511]]
input_correlations: [[-0.798761, 0.000000, 0.997422, 0.996653, -0.905481, 0.000000, 0.000000, 0.000000], [-0.804905, 0.000000, 0.996608, 0.993848, -0.916571, 0.000000, 0.000000, 0.000000], [-0.795039, 0.000000, 0.998317, 0.996990, -0.901562, 0.000000, 0.000000, 0.000000], [0.317616, 0.000000, -0.854675, -0.849751, 0.630681, 0.000000, 0.000000, 0.000000], [-0.801060, 0.000000, 0.997547, 0.996492, -0.904530, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.337254, 0.952503, 2.638322, -0.539516, 1.960206]
pre_activation_std: [3.022178, 1.811669, 3.351795, 0.174961, 2.673710]
### 8
mean: [3.471558, 0.110642, 2.169765, -0.363548, 3.671653]
std: [4.205932, 0.739285, 2.833390, 0.230635, 4.622921]
fourier: [[64.055889, 67.137520, 82.516324, 87.241761, 312.440232], [11.250745, 11.716175, 11.782888, 14.773668, 15.177642], [43.486623, 45.224643, 55.645784, 58.605704, 195.278827], [3.522303, 3.630719, 4.631061, 4.831296, 32.719305], [71.440236, 73.642348, 91.341625, 95.711371, 330.448756]]
input_correlations: [[0.999960, 0.995876, 0.999959, 0.000000, 0.999905, 0.000000, 0.000000, 0.000000], [-0.998700, -0.998940, -0.998365, 0.000000, -0.999229, 0.000000, 0.000000, 0.000000], [0.999971, 0.996128, 0.999874, 0.000000, 0.999939, 0.000000, 0.000000, 0.000000], [-0.997776, -0.998451, -0.998077, 0.000000, -0.998376, 0.000000, 0.000000, 0.000000], [0.999710, 0.997513, 0.999675, 0.000000, 0.999957, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.471558, 0.110642, 2.169765, -0.363548, 3.671653]
pre_activation_std: [4.205932, 0.739285, 2.833390, 0.230635, 4.622921]
### 10
mean: [2.034893, 4.380355, 0.404162, -1.494608, -1.436560]
std: [2.822821, 5.787080, 1.421536, 1.228462, 1.473636]
fourier: [[44.120681, 45.013149, 55.895480, 58.346597, 183.140347], [90.783730, 92.622918, 113.851979, 119.467764, 394.231950], [22.766573, 23.129859, 26.784747, 29.135121, 36.374545], [19.124452, 19.581158, 24.350584, 25.392715, 134.514681], [22.946747, 23.217411, 29.810776, 30.448186, 129.290377]]
input_correlations: [[0.999885, -0.850516, 0.999904, 0.000000, 0.999960, 0.000000, 0.000000, 0.000000], [0.999906, -0.856490, 0.999794, 0.000000, 0.999829, 0.000000, 0.000000, 0.000000], [-0.996305, 0.894231, -0.995390, 0.000000, -0.995480, 0.000000, 0.000000, 0.000000], [-0.999904, 0.848358, -0.999893, 0.000000, -0.999917, 0.000000, 0.000000, 0.000000], [-0.998464, 0.826049, -0.999189, 0.000000, -0.999213, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.034893, 4.380355, 0.404162, -1.494608, -1.436560]
pre_activation_std: [2.822821, 5.787080, 1.421536, 1.228462, 1.473636]
### 12
mean: [-1.980142]
std: [4.122865]
fourier: [[66.485516, 66.920586, 79.129663, 84.666814, 178.212784]]
input_correlations: [[-0.996329, -0.997844, 0.870400, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.980142]
pre_activation_std: [4.122865]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 2.149648427963257, "std": 2.729633092880249, "fourier": [43.31737536570372, 43.69748601051987, 54.95523639316231, 56.25605819099102, 193.46838048100471], "input_correlations": [0.4668390160835958, -0.18787095799334735, -0.02124683633630115, -0.7900310060519489, -0.4324423686558788, 0.0, 0.0, 0.0], "pre_activation_mean": -1.5688995122909546, "pre_activation_std": 1.6553608179092407}, "1": {"mean": 4.557867050170898, "std": 5.640322685241699, "fourier": [90.1097080749508, 90.24642538719277, 112.30424370296657, 116.14071631776568, 410.2080228328705], "input_correlations": [0.019564844037076826, -0.1613110529444597, 0.2839415369829317, 0.5045520155862739, 0.8501201699281776, 0.0, 0.0, 0.0], "pre_activation_mean": 1.3171207904815674, "pre_activation_std": 1.7743884325027466}, "2": {"mean": 0.8562536239624023, "std": 0.7346376180648804, "fourier": [11.824982690664935, 11.847270435639887, 13.237538333791683, 13.372434069299347, 77.06282866001129], "input_correlations": [0.6469518691173486, 0.20640140217186181, 0.1668414853429137, 0.43907782133599627, 0.7479108999139791, 0.0, 0.0, 0.0], "pre_activation_mean": 2.0330538749694824, "pre_activation_std": 2.020519495010376}, "3": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.12136666504235041, 0.27709000967859315, 0.5339115341851035, -0.3430306906866961, -0.5682303780396822, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7694005370140076, "pre_activation_std": 1.5149343013763428}, "4": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.4751272647540797, 0.3591485962919625, -0.40723961348080673, 0.21213522121376643, -0.7482953068762885, 0.0, 0.0, 0.0], "pre_activation_mean": -0.06647119671106339, "pre_activation_std": 1.131714105606079}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 1.8759822845458984, "std": 2.5472781658172607, "fourier": [36.836882954727194, 40.9151519611561, 48.319444262125266, 52.72472849966816, 168.83841224759817], "input_correlations": [0.12114977137684088, 0.8272691765615872, 0.9729588227028718, -0.6335482867855945, -0.4095622514002654, 0.0, 0.0, 0.0], "pre_activation_mean": 1.8759822845458984, "pre_activation_std": 2.5472781658172607}, "1": {"mean": 1.4337323904037476, "std": 0.5022657513618469, "fourier": [8.012722024794302, 8.87628984377681, 8.994127176510506, 10.957683914509127, 129.03590750694275], "input_correlations": [0.34838509109980825, 0.60899778199031, 0.7845526833604948, 0.024460680244748692, -0.19471397033870644, 0.0, 0.0, 0.0], "pre_activation_mean": 1.4337323904037476, "pre_activation_std": 0.5022657513618469}, "2": {"mean": -1.936269998550415, "std": 1.5307443141937256, "fourier": [22.793673229935983, 28.995603251130937, 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20 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.54, "improved_accuracy": 0.96, "improvement": 0.41999999999999993, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4611, "learning_rate": 0.08701594713422484, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.4.weight": [
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[
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"network.4.bias": [
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"network.6.weight": [
[
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[
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],
[
0.863803,
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],
[
1.109087,
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0.47203,
0.879398
],
[
1.186015,
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0.964076,
0.90223
],
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]
],
"network.6.bias": [
0.491017,
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],
"network.8.weight": [
[
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[
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[
1.21629,
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0.596816,
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],
"network.8.bias": [
0.478764,
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"network.10.weight": [
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"network.10.bias": [
0.838718
]
}
## Activation Signature
### 0
mean: [0.143608, 27.801840, 21.577925, 0.439390, 0.319480, 0.208867]
std: [0.291895, 33.870705, 26.895243, 0.910881, 0.692387, 0.458526]
fourier: [[4.483183, 4.821495, 5.594209, 5.946422, 12.924733], [572.847956, 613.807032, 620.859306, 714.270790, 2502.165545], [448.668320, 484.239801, 493.438398, 566.550497, 1942.013273], [16.188686, 16.622513, 17.616127, 20.340706, 39.545113], [12.032060, 12.099864, 12.677659, 14.865561, 28.753195], [8.165528, 8.371136, 8.813254, 10.451835, 18.798072]]
input_correlations: [[0.334034, -0.442647, -0.491095, 0.230499, 0.088605, 0.000000, 0.000000, 0.000000], [-0.509378, -0.746869, -0.526351, -0.673559, -0.156200, 0.000000, 0.000000, 0.000000], [0.185628, -0.056002, -0.611609, -0.424677, -0.675702, 0.000000, 0.000000, 0.000000], [0.903698, 0.652067, 0.523278, 0.119659, 0.147809, 0.000000, 0.000000, 0.000000], [-0.647000, -0.839133, -0.579416, -0.005532, -0.092431, 0.000000, 0.000000, 0.000000], [0.609038, -0.510888, 0.323973, -0.329197, 0.175717, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.010614, -5.811959, -2.717435, 3.987317, -2.933985, -0.474564]
pre_activation_std: [2.019291, 3.507448, 1.712916, 4.304364, 2.540594, 3.237568]
### 2
mean: [-0.918971, 2.992400, 3.885175, -3.360883, -4.650168, 4.854301]
std: [0.772713, 3.464813, 4.244216, 2.966374, 4.153616, 5.225651]
fourier: [[11.993245, 14.915203, 15.327910, 16.194981, 82.707388], [59.085667, 60.428717, 64.968368, 76.711891, 269.316021], [74.758646, 76.154223, 78.457124, 87.660407, 349.665720], [50.458404, 53.610636, 54.330890, 64.804981, 302.479470], [65.635153, 74.751808, 79.412345, 87.617793, 418.515165], [91.769726, 93.306871, 97.546230, 108.825026, 436.887076]]
input_correlations: [[-0.661621, -0.469490, -0.321060, -0.825972, -0.354357, -0.516193, 0.000000, 0.000000], [0.396327, 0.349587, 0.300286, 0.869851, 0.085559, 0.833067, 0.000000, 0.000000], [0.318570, 0.372599, 0.288277, 0.935959, 0.068999, 0.750354, 0.000000, 0.000000], [-0.348024, -0.347419, -0.304225, -0.879645, -0.050664, -0.834095, 0.000000, 0.000000], [-0.411652, -0.389643, -0.310181, -0.932694, -0.110204, -0.714129, 0.000000, 0.000000], [0.334927, 0.376524, 0.309814, 0.928987, 0.077708, 0.761644, 0.000000, 0.000000]]
pre_activation_mean: [-0.918971, 2.992400, 3.885175, -3.360883, -4.650168, 4.854301]
pre_activation_std: [0.772713, 3.464813, 4.244216, 2.966374, 4.153616, 5.225651]
### 4
mean: [-2.236033, 8.214229, 8.353302, 4.023871, -3.810237, -3.208531]
std: [1.917464, 9.738073, 9.873566, 5.252564, 3.407644, 2.516963]
fourier: [[33.933524, 35.144873, 35.158983, 38.132933, 201.242937], [169.822262, 173.836535, 180.881175, 206.586987, 739.280572], [172.255839, 176.585110, 183.282052, 208.858048, 751.797159], [91.286135, 93.466523, 97.516486, 112.066573, 362.148374], [58.986423, 60.835092, 62.895113, 72.527073, 342.921340], [44.181031, 45.901542, 46.139793, 50.319183, 288.767740]]
input_correlations: [[-0.250052, -0.973736, -0.997024, -0.743055, -0.633560, -0.995820, 0.000000, 0.000000], [0.269570, 0.994324, 0.998581, 0.725016, 0.615700, 0.999435, 0.000000, 0.000000], [0.269309, 0.993661, 0.998863, 0.725755, 0.616296, 0.999618, 0.000000, 0.000000], [0.277140, 0.995536, 0.997864, 0.719262, 0.610203, 0.999004, 0.000000, 0.000000], [-0.277132, -0.995329, -0.998169, -0.719214, -0.607002, -0.998892, 0.000000, 0.000000], [-0.261149, -0.977431, -0.998363, -0.731205, -0.618746, -0.997099, 0.000000, 0.000000]]
pre_activation_mean: [-2.236033, 8.214229, 8.353302, 4.023871, -3.810237, -3.208531]
pre_activation_std: [1.917464, 9.738073, 9.873566, 5.252564, 3.407644, 2.516963]
### 6
mean: [-31.260506, -1.666758, 14.636314, 16.568171, 10.000449, -16.341547]
std: [38.221745, 1.158965, 18.076693, 19.990726, 12.703041, 19.278505]
fourier: [[655.844285, 692.585496, 699.713126, 809.923224, 2813.445544], [19.716926, 20.818676, 21.019588, 24.687147, 150.008223], [309.516860, 327.803139, 330.735437, 382.855291, 1317.268295], [344.061527, 362.407004, 366.523234, 423.600444, 1491.135396], [217.238656, 230.495391, 232.580448, 269.054330, 900.040358], [331.453924, 349.284802, 353.293070, 408.677000, 1470.739264]]
input_correlations: [[-0.818448, -0.999990, -0.999969, -0.999646, -0.684585, -0.705784, 0.000000, 0.000000], [-0.795679, -0.998807, -0.998648, -0.999607, -0.651742, -0.673366, 0.000000, 0.000000], [0.819010, 0.999983, 0.999963, 0.999661, 0.684561, 0.705794, 0.000000, 0.000000], [0.820670, 0.999991, 0.999984, 0.999483, 0.688491, 0.709672, 0.000000, 0.000000], [0.821686, 0.999971, 0.999953, 0.999568, 0.688017, 0.709143, 0.000000, 0.000000], [-0.819539, -0.999996, -0.999978, -0.999564, -0.686773, -0.707922, 0.000000, 0.000000]]
pre_activation_mean: [-31.260506, -1.666758, 14.636314, 16.568171, 10.000449, -16.341547]
pre_activation_std: [38.221745, 1.158965, 18.076693, 19.990726, 12.703041, 19.278505]
### 8
mean: [-1.539860, 27.561657, 21.210367, -6.290767, -2.549044, -5.907537]
std: [2.642509, 34.071835, 27.197348, 8.852836, 4.220416, 7.882225]
fourier: [[45.951267, 48.050443, 48.876225, 56.202683, 138.587367], [582.076891, 620.354113, 621.912510, 720.914570, 2480.549162], [462.762660, 495.023698, 496.421755, 574.871790, 1908.932875], [154.082865, 158.308736, 168.280069, 190.280987, 566.169076], [70.457735, 75.804656, 81.845586, 91.401177, 229.413960], [137.944392, 140.179527, 147.033700, 168.233154, 531.678281]]
input_correlations: [[0.405414, -0.941353, -0.999433, -0.999693, -0.999235, 0.132976, 0.000000, 0.000000], [-0.388311, 0.937030, 0.999945, 0.999994, 0.999860, -0.122810, 0.000000, 0.000000], [-0.384192, 0.936811, 0.999981, 0.999993, 0.999923, -0.119099, 0.000000, 0.000000], [0.450626, -0.939767, -0.996888, -0.997477, -0.996459, 0.181657, 0.000000, 0.000000], [0.479454, -0.937423, -0.993611, -0.994337, -0.993085, 0.220152, 0.000000, 0.000000], [0.419140, -0.938152, -0.999038, -0.999339, -0.998777, 0.152957, 0.000000, 0.000000]]
pre_activation_mean: [-1.539860, 27.561657, 21.210367, -6.290767, -2.549044, -5.907537]
pre_activation_std: [2.642509, 34.071835, 27.197348, 8.852836, 4.220416, 7.882225]
### 10
mean: [-29.207867]
std: [37.492725]
fourier: [[634.974130, 682.161490, 683.102982, 792.510341, 2628.708054]]
input_correlations: [[0.479172, -0.999974, -0.999872, 0.405205, 0.400032, 0.386459, 0.000000, 0.000000]]
pre_activation_mean: [-29.207867]
pre_activation_std: [37.492725]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.818621,
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0.504389,
-0.009988
],
[
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0.114544
],
[
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0.03446,
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],
[
1.541016,
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0.497908,
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],
[
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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],
[
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0.501118,
0.091416,
0.932429
],
[
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0.010679,
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0.150014,
0.83546
],
[
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-0.00252,
0.959777,
-0.435851,
0.243627,
-0.810007
],
[
-1.264449,
-0.051049,
1.284118,
-0.752034,
0.020272,
-0.625666
],
[
0.791272,
-0.172967,
-1.048896,
0.900114,
0.316274,
1.062199
]
],
"network.2.bias": [
-0.250306,
-0.062883,
-0.027636,
-0.773982,
-0.71453,
0.105915
],
"network.4.weight": [
[
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-0.238474,
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-0.419463
],
[
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0.596056,
0.637983,
0.77261,
0.850058
],
[
0.120626,
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0.592635,
0.717771,
0.676013,
0.955893
],
[
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0.49645,
0.087435,
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[
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0.171262,
0.02291
],
[
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]
],
"network.4.bias": [
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"network.6.weight": [
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[
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[
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],
[
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0.339363,
0.47203,
0.879398
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[
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],
"network.6.bias": [
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"network.8.weight": [
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[
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],
"network.8.bias": [
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],
"network.10.weight": [
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],
"network.10.bias": [
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}
## Activation Signature
### 0
mean: [0.143608, 27.801840, 21.577925, 0.439390, 0.319480, 0.208867]
std: [0.291895, 33.870705, 26.895243, 0.910881, 0.692387, 0.458526]
fourier: [[4.483183, 4.821495, 5.594209, 5.946422, 12.924733], [572.847956, 613.807032, 620.859306, 714.270790, 2502.165545], [448.668320, 484.239801, 493.438398, 566.550497, 1942.013273], [16.188686, 16.622513, 17.616127, 20.340706, 39.545113], [12.032060, 12.099864, 12.677659, 14.865561, 28.753195], [8.165528, 8.371136, 8.813254, 10.451835, 18.798072]]
input_correlations: [[0.334034, -0.442647, -0.491095, 0.230499, 0.088605, 0.000000, 0.000000, 0.000000], [-0.509378, -0.746869, -0.526351, -0.673559, -0.156200, 0.000000, 0.000000, 0.000000], [0.185628, -0.056002, -0.611609, -0.424677, -0.675702, 0.000000, 0.000000, 0.000000], [0.903698, 0.652067, 0.523278, 0.119659, 0.147809, 0.000000, 0.000000, 0.000000], [-0.647000, -0.839133, -0.579416, -0.005532, -0.092431, 0.000000, 0.000000, 0.000000], [0.609038, -0.510888, 0.323973, -0.329197, 0.175717, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.010614, -5.811959, -2.717435, 3.987317, -2.933985, -0.474564]
pre_activation_std: [2.019291, 3.507448, 1.712916, 4.304364, 2.540594, 3.237568]
### 2
mean: [-0.918971, 2.992400, 3.885175, -3.360883, -4.650168, 4.854301]
std: [0.772713, 3.464813, 4.244216, 2.966374, 4.153616, 5.225651]
fourier: [[11.993245, 14.915203, 15.327910, 16.194981, 82.707388], [59.085667, 60.428717, 64.968368, 76.711891, 269.316021], [74.758646, 76.154223, 78.457124, 87.660407, 349.665720], [50.458404, 53.610636, 54.330890, 64.804981, 302.479470], [65.635153, 74.751808, 79.412345, 87.617793, 418.515165], [91.769726, 93.306871, 97.546230, 108.825026, 436.887076]]
input_correlations: [[-0.661621, -0.469490, -0.321060, -0.825972, -0.354357, -0.516193, 0.000000, 0.000000], [0.396327, 0.349587, 0.300286, 0.869851, 0.085559, 0.833067, 0.000000, 0.000000], [0.318570, 0.372599, 0.288277, 0.935959, 0.068999, 0.750354, 0.000000, 0.000000], [-0.348024, -0.347419, -0.304225, -0.879645, -0.050664, -0.834095, 0.000000, 0.000000], [-0.411652, -0.389643, -0.310181, -0.932694, -0.110204, -0.714129, 0.000000, 0.000000], [0.334927, 0.376524, 0.309814, 0.928987, 0.077708, 0.761644, 0.000000, 0.000000]]
pre_activation_mean: [-0.918971, 2.992400, 3.885175, -3.360883, -4.650168, 4.854301]
pre_activation_std: [0.772713, 3.464813, 4.244216, 2.966374, 4.153616, 5.225651]
### 4
mean: [-2.236033, 8.214229, 8.353302, 4.023871, -3.810237, -3.208531]
std: [1.917464, 9.738073, 9.873566, 5.252564, 3.407644, 2.516963]
fourier: [[33.933524, 35.144873, 35.158983, 38.132933, 201.242937], [169.822262, 173.836535, 180.881175, 206.586987, 739.280572], [172.255839, 176.585110, 183.282052, 208.858048, 751.797159], [91.286135, 93.466523, 97.516486, 112.066573, 362.148374], [58.986423, 60.835092, 62.895113, 72.527073, 342.921340], [44.181031, 45.901542, 46.139793, 50.319183, 288.767740]]
input_correlations: [[-0.250052, -0.973736, -0.997024, -0.743055, -0.633560, -0.995820, 0.000000, 0.000000], [0.269570, 0.994324, 0.998581, 0.725016, 0.615700, 0.999435, 0.000000, 0.000000], [0.269309, 0.993661, 0.998863, 0.725755, 0.616296, 0.999618, 0.000000, 0.000000], [0.277140, 0.995536, 0.997864, 0.719262, 0.610203, 0.999004, 0.000000, 0.000000], [-0.277132, -0.995329, -0.998169, -0.719214, -0.607002, -0.998892, 0.000000, 0.000000], [-0.261149, -0.977431, -0.998363, -0.731205, -0.618746, -0.997099, 0.000000, 0.000000]]
pre_activation_mean: [-2.236033, 8.214229, 8.353302, 4.023871, -3.810237, -3.208531]
pre_activation_std: [1.917464, 9.738073, 9.873566, 5.252564, 3.407644, 2.516963]
### 6
mean: [-31.260506, -1.666758, 14.636314, 16.568171, 10.000449, -16.341547]
std: [38.221745, 1.158965, 18.076693, 19.990726, 12.703041, 19.278505]
fourier: [[655.844285, 692.585496, 699.713126, 809.923224, 2813.445544], [19.716926, 20.818676, 21.019588, 24.687147, 150.008223], [309.516860, 327.803139, 330.735437, 382.855291, 1317.268295], [344.061527, 362.407004, 366.523234, 423.600444, 1491.135396], [217.238656, 230.495391, 232.580448, 269.054330, 900.040358], [331.453924, 349.284802, 353.293070, 408.677000, 1470.739264]]
input_correlations: [[-0.818448, -0.999990, -0.999969, -0.999646, -0.684585, -0.705784, 0.000000, 0.000000], [-0.795679, -0.998807, -0.998648, -0.999607, -0.651742, -0.673366, 0.000000, 0.000000], [0.819010, 0.999983, 0.999963, 0.999661, 0.684561, 0.705794, 0.000000, 0.000000], [0.820670, 0.999991, 0.999984, 0.999483, 0.688491, 0.709672, 0.000000, 0.000000], [0.821686, 0.999971, 0.999953, 0.999568, 0.688017, 0.709143, 0.000000, 0.000000], [-0.819539, -0.999996, -0.999978, -0.999564, -0.686773, -0.707922, 0.000000, 0.000000]]
pre_activation_mean: [-31.260506, -1.666758, 14.636314, 16.568171, 10.000449, -16.341547]
pre_activation_std: [38.221745, 1.158965, 18.076693, 19.990726, 12.703041, 19.278505]
### 8
mean: [-1.539860, 27.561657, 21.210367, -6.290767, -2.549044, -5.907537]
std: [2.642509, 34.071835, 27.197348, 8.852836, 4.220416, 7.882225]
fourier: [[45.951267, 48.050443, 48.876225, 56.202683, 138.587367], [582.076891, 620.354113, 621.912510, 720.914570, 2480.549162], [462.762660, 495.023698, 496.421755, 574.871790, 1908.932875], [154.082865, 158.308736, 168.280069, 190.280987, 566.169076], [70.457735, 75.804656, 81.845586, 91.401177, 229.413960], [137.944392, 140.179527, 147.033700, 168.233154, 531.678281]]
input_correlations: [[0.405414, -0.941353, -0.999433, -0.999693, -0.999235, 0.132976, 0.000000, 0.000000], [-0.388311, 0.937030, 0.999945, 0.999994, 0.999860, -0.122810, 0.000000, 0.000000], [-0.384192, 0.936811, 0.999981, 0.999993, 0.999923, -0.119099, 0.000000, 0.000000], [0.450626, -0.939767, -0.996888, -0.997477, -0.996459, 0.181657, 0.000000, 0.000000], [0.479454, -0.937423, -0.993611, -0.994337, -0.993085, 0.220152, 0.000000, 0.000000], [0.419140, -0.938152, -0.999038, -0.999339, -0.998777, 0.152957, 0.000000, 0.000000]]
pre_activation_mean: [-1.539860, 27.561657, 21.210367, -6.290767, -2.549044, -5.907537]
pre_activation_std: [2.642509, 34.071835, 27.197348, 8.852836, 4.220416, 7.882225]
### 10
mean: [-29.207867]
std: [37.492725]
fourier: [[634.974130, 682.161490, 683.102982, 792.510341, 2628.708054]]
input_correlations: [[0.479172, -0.999974, -0.999872, 0.405205, 0.400032, 0.386459, 0.000000, 0.000000]]
pre_activation_mean: [-29.207867]
pre_activation_std: [37.492725]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.788048, -0.818621, -0.602337, 0.504389, -0.009988], [-0.537033, -0.719264, -0.634593, -0.955001, 0.114544], [0.391546, 0.03446, -0.564505, -0.263981, -0.533113], [1.541016, 0.808729, 0.497908, 0.089346, -0.088357], [-0.354802, -1.030818, -0.425259, 0.282024, -0.009514], [1.286174, -1.454224, 0.4303, -0.026383, -0.041246]], "network.0.bias": [-0.310689, -0.60072, -0.864697, -0.526776, -0.318808, -0.216619], "network.2.weight": 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-1.382344, -1.603494, -0.68495, -0.867579], [0.302914, -0.265963, 0.180811, -0.077894, 0.606958, 0.057186], [0.863803, 0.466233, 0.857495, 0.967622, 0.456991, 0.418942], [1.109087, 1.194275, 0.662062, 0.339363, 0.47203, 0.879398], [1.186015, 0.351466, 0.503957, 0.804595, 0.964076, 0.90223], [-0.546658, -1.257118, -0.430291, -0.531011, -0.401343, -0.832278]], "network.6.bias": [0.491017, -0.605995, -0.228978, -0.050234, -0.199988, -0.312935], "network.8.weight": [[0.118669, -1.144389, -0.055482, -0.167945, 0.142585, -0.304269], [-0.403358, 0.740117, 0.845837, 0.902348, 0.060457, -0.037236], [-0.200683, 0.561961, 0.700399, 0.557944, 0.271637, 0.243084], [1.21629, -1.120111, -0.161743, -0.34809, 0.106316, 0.275406], [0.849733, -0.539132, -0.471054, 0.292593, -0.105689, 1.189992], [0.596816, -0.497024, -0.611876, -0.036025, 0.318108, 0.233293]], "network.8.bias": [0.478764, -0.373405, -1.059413, 0.387632, 0.314003, 0.283943], "network.10.weight": [[-0.246566, -0.491277, -0.769097, 0.413856, 0.15314, 0.057338]], "network.10.bias": [0.838718]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7055697441101074, "train_acc": 0.435, "val_loss": 0.6894066333770752, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6843611299991608, "train_acc": 0.565, "val_loss": 0.695496678352356, "val_acc": 0.54}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6800865828990936, "train_acc": 0.565, "val_loss": 0.6517313122749329, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6271849274635315, "train_acc": 0.49, "val_loss": 0.47679272294044495, "val_acc": 0.72}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.4353923052549362, "train_acc": 0.865, "val_loss": 0.32187139987945557, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.34926195442676544, "train_acc": 0.89, "val_loss": 0.3006197512149811, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.3129553496837616, "train_acc": 0.9, "val_loss": 0.31665295362472534, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.28912070393562317, "train_acc": 0.87, "val_loss": 0.4514550268650055, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4113176316022873, "train_acc": 0.865, "val_loss": 0.24809356033802032, "val_acc": 0.88}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.22639497369527817, "train_acc": 0.905, "val_loss": 0.22495098412036896, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.2016933560371399, "train_acc": 0.92, "val_loss": 0.19117870926856995, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.20705877244472504, "train_acc": 0.955, "val_loss": 0.20649978518486023, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.19170381128787994, "train_acc": 0.955, "val_loss": 0.17803078889846802, "val_acc": 0.96}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.6894066333770752, "final_val_loss": 0.6517313122749329, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.47679272294044495, "final_val_loss": 0.17803078889846802, "initial_val_acc": 0.72, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 11}, "improvement": 0.41999999999999993, "first_improvement_epoch": 2}} |
21 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.5, "improved_accuracy": 0.78, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8617, "learning_rate": 0.08422630629161262, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.459863,
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0.598809
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[
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[
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[
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0.147206,
0.039535,
-1.751602
],
[
-0.809717,
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-0.221096,
0.089569
],
[
-0.293729,
-0.409661,
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-0.298951
]
],
"network.0.bias": [
0.164025,
0.257391,
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-0.372457,
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"network.2.weight": [
[
-0.587355,
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-0.351833,
0.037947,
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],
[
-0.40455,
1.122579,
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0.773448,
-0.17408,
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],
[
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-0.615085,
0.034549,
0.006391
],
[
-0.075386,
0.668446,
1.083957,
0.600205,
0.334403,
0.425751
],
[
-0.522716,
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0.010189,
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],
[
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0.801501,
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0.296468,
-0.019795
]
],
"network.2.bias": [
-0.490101,
0.296607,
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0.848554,
-0.178135,
0.255908
],
"network.4.weight": [
[
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0.116415,
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],
[
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1.390273,
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1.055265,
0.059524,
1.017295
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[
-0.217265,
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[
0.289151,
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[
0.034906,
1.456609,
0.533815,
0.669295,
0.153014,
0.865615
],
[
-0.223249,
1.144715,
0.06671,
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0.513543
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],
"network.4.bias": [
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"network.6.weight": [
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[
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"network.6.bias": [
0.066048,
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"network.8.weight": [
[
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[
0.759183,
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[
0.542103,
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[
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[
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0.062268,
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[
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],
"network.8.bias": [
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"network.10.weight": [
[
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[
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0.010101,
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0.312191
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[
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1.161287,
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[
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[
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],
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"network.12.weight": [
[
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],
"network.12.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 32.276031, 0.000000, 0.000177, 0.000000]
std: [0.000000, 0.000000, 45.274891, 0.000000, 0.001674, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [802.049259, 816.959697, 821.906101, 826.786030, 2904.842735], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.015971, 0.015971, 0.015971, 0.015971, 0.015971], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.311949, 0.398928, 0.299607, 0.684684, 0.522834, 0.000000, 0.000000, 0.000000], [0.911452, 0.435444, 0.242801, -0.052700, -0.223464, 0.000000, 0.000000, 0.000000], [-0.139774, 0.218727, -0.817423, -0.244280, -0.334719, 0.000000, 0.000000, 0.000000], [0.248527, 0.282596, 0.018976, -0.092489, -0.892809, 0.000000, 0.000000, 0.000000], [-0.815950, -0.682001, -0.637321, -0.247903, -0.155287, 0.000000, 0.000000, 0.000000], [-0.550851, -0.718960, -0.426556, -0.645010, -0.469293, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.638226, 2.120742, -2.190962, -0.874196, -3.796946, -3.355225]
pre_activation_std: [2.201212, 4.175175, 2.122231, 3.299742, 2.737523, 1.809910]
### 2
mean: [-2.569762, 2.751745, -2.936877, 2.910950, -2.438925, 2.578283]
std: [1.235030, 5.218436, 2.525271, 3.134945, 1.366997, 4.084316]
fourier: [[19.496185, 20.288575, 21.185633, 21.337859, 231.278619], [85.723060, 91.735215, 93.608359, 94.892192, 247.657030], [40.064151, 43.374448, 45.067929, 47.194500, 264.318856], [52.340954, 52.637297, 53.527990, 59.447070, 261.985490], [22.457244, 24.578126, 25.554071, 25.578361, 219.503237], [68.752610, 71.138492, 71.709812, 75.598265, 232.045471]]
input_correlations: [[-0.854014, -0.204985, -0.204009, -0.300172, 0.000000, 0.000000, 0.000000, 0.000000], [-0.423535, 0.981714, 0.074962, 0.857431, 0.000000, 0.000000, 0.000000, 0.000000], [0.132531, -0.973918, -0.072988, -0.887727, 0.000000, 0.000000, 0.000000, 0.000000], [-0.317994, 0.983522, 0.136931, 0.882931, 0.000000, 0.000000, 0.000000, 0.000000], [-0.580739, -0.553090, -0.234858, -0.630672, 0.000000, 0.000000, 0.000000, 0.000000], [-0.369292, 0.989205, 0.082550, 0.860614, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.569762, 2.751745, -2.936877, 2.910950, -2.438925, 2.578283]
pre_activation_std: [1.235030, 5.218436, 2.525271, 3.134945, 1.366997, 4.084316]
### 4
mean: [-3.350013, 10.273723, -1.974720, -3.700704, 9.049253, 8.023950]
std: [4.125980, 14.219841, 2.679205, 4.657463, 12.739522, 10.663342]
fourier: [[73.176528, 74.582069, 75.160385, 75.241729, 301.501138], [251.502365, 256.076243, 257.346593, 260.038809, 924.635049], [47.701384, 48.524515, 48.744204, 48.855251, 177.724819], [81.082183, 82.296721, 82.538597, 86.212078, 333.063350], [226.529201, 230.646900, 231.926699, 232.382753, 814.432749], [188.314882, 191.882723, 192.902713, 195.172351, 722.155443]]
input_correlations: [[0.000000, -0.999214, 0.000000, -0.995225, 0.000000, -0.999583, 0.000000, 0.000000], [0.000000, 0.998891, 0.000000, 0.995842, 0.000000, 0.999744, 0.000000, 0.000000], [0.000000, -0.999302, 0.000000, -0.994762, 0.000000, -0.999700, 0.000000, 0.000000], [0.000000, -0.997117, 0.000000, -0.998015, 0.000000, -0.999513, 0.000000, 0.000000], [0.000000, 0.999308, 0.000000, 0.994887, 0.000000, 0.999638, 0.000000, 0.000000], [0.000000, 0.998839, 0.000000, 0.996002, 0.000000, 0.999681, 0.000000, 0.000000]]
pre_activation_mean: [-3.350013, 10.273723, -1.974720, -3.700704, 9.049253, 8.023950]
pre_activation_std: [4.125980, 14.219841, 2.679205, 4.657463, 12.739522, 10.663342]
### 6
mean: [26.010651, -9.705044, -15.231167, -4.065253, -5.859417, -6.566726]
std: [35.777313, 13.196505, 20.960026, 5.477252, 7.951527, 9.018940]
fourier: [[633.785451, 645.420577, 649.272540, 653.355563, 2340.958852], [233.789607, 238.101213, 239.559248, 240.966668, 873.453996], [371.329245, 378.183328, 380.508257, 382.724015, 1370.804975], [97.023313, 98.786143, 99.346719, 100.037049, 365.872736], [140.866710, 143.466866, 144.347350, 145.195200, 527.347603], [159.604779, 162.533472, 163.421439, 164.841487, 591.005351]]
input_correlations: [[0.000000, 0.999994, 0.000000, 0.000000, 0.999977, 0.999986, 0.000000, 0.000000], [0.000000, -0.999993, 0.000000, 0.000000, -0.999979, -0.999986, 0.000000, 0.000000], [0.000000, -0.999993, 0.000000, 0.000000, -0.999979, -0.999986, 0.000000, 0.000000], [0.000000, -0.999996, 0.000000, 0.000000, -0.999974, -0.999986, 0.000000, 0.000000], [0.000000, -0.999993, 0.000000, 0.000000, -0.999978, -0.999986, 0.000000, 0.000000], [0.000000, -0.999999, 0.000000, 0.000000, -0.999962, -0.999994, 0.000000, 0.000000]]
pre_activation_mean: [26.010651, -9.705044, -15.231167, -4.065253, -5.859417, -6.566726]
pre_activation_std: [35.777313, 13.196505, 20.960026, 5.477252, 7.951527, 9.018940]
### 8
mean: [-15.567615, 19.664042, 13.738901, -2.258462, -15.172154, -3.049127]
std: [21.098894, 27.161510, 19.394995, 4.058115, 20.447327, 3.875373]
fourier: [[373.761255, 380.622813, 382.894429, 385.302303, 1401.085420], [481.158857, 489.992032, 492.916369, 496.016133, 1769.763783], [343.577100, 349.884546, 351.972706, 354.186119, 1236.501102], [71.888423, 73.208160, 73.645077, 74.108203, 203.261556], [362.218891, 368.868554, 371.070017, 373.403534, 1365.494020], [68.651191, 69.911498, 70.328741, 70.771011, 274.421420]]
input_correlations: [[-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-15.567615, 19.664042, 13.738901, -2.258462, -15.172154, -3.049127]
pre_activation_std: [21.098894, 27.161510, 19.394995, 4.058115, 20.447327, 3.875373]
### 10
mean: [-3.206229, -7.465782, 32.276031, -0.948753, -19.480860, -9.060947]
std: [4.098883, 10.346517, 45.274891, 0.946534, 28.109224, 12.081920]
fourier: [[72.656584, 74.514004, 74.812225, 75.157494, 288.560551], [183.327529, 187.162615, 188.457765, 188.913367, 671.920455], [802.049259, 816.959697, 821.906101, 826.786030, 2904.842735], [16.803735, 17.234250, 17.548493, 17.819436, 85.387739], [497.946296, 507.075528, 510.097220, 513.323809, 1753.277385], [214.098733, 218.827332, 220.436188, 220.580648, 815.485292]]
input_correlations: [[0.000000, -0.999902, -0.999902, 0.418313, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999988, -0.999988, 0.426498, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 1.000000, 1.000000, -0.430556, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.998673, -0.998673, 0.383915, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -1.000000, -1.000000, 0.431001, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999974, -0.999974, 0.424454, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.206229, -7.465782, 32.276031, -0.948753, -19.480860, -9.060947]
pre_activation_std: [4.098883, 10.346517, 45.274891, 0.946534, 28.109224, 12.081920]
### 12
mean: [-19.906633]
std: [28.802151]
fourier: [[510.225358, 519.706753, 522.871834, 525.978585, 1791.596701]]
input_correlations: [[0.000000, 0.000000, -1.000000, 0.000000, 0.073451, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-19.906633]
pre_activation_std: [28.802151]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.652318,
0.459863,
0.330884,
0.47485,
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],
[
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0.026333,
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],
[
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[
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0.147206,
0.039535,
-1.751602
],
[
-0.809717,
-0.507657,
-0.540057,
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0.089569
],
[
-0.293729,
-0.409661,
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-0.412062,
-0.298951
]
],
"network.0.bias": [
0.164025,
0.257391,
-0.248102,
-0.267998,
-0.372457,
-0.680019
],
"network.2.weight": [
[
-0.587355,
-0.074639,
-0.335529,
-0.351833,
0.037947,
-0.358548
],
[
-0.40455,
1.122579,
0.957133,
0.773448,
-0.17408,
-0.052602
],
[
-0.191447,
-0.540626,
-0.094484,
-0.615085,
0.034549,
0.006391
],
[
-0.075386,
0.668446,
1.083957,
0.600205,
0.334403,
0.425751
],
[
-0.522716,
-0.148573,
-0.49018,
-0.556721,
0.010189,
-0.361966
],
[
-0.195545,
0.916959,
0.801501,
0.562598,
0.296468,
-0.019795
]
],
"network.2.bias": [
-0.490101,
0.296607,
-0.558965,
0.848554,
-0.178135,
0.255908
],
"network.4.weight": [
[
0.164717,
-0.518841,
-0.166381,
-0.308837,
0.116415,
-0.149717
],
[
-0.040881,
1.390273,
-0.514641,
1.055265,
0.059524,
1.017295
],
[
-0.217265,
-0.270028,
-0.226961,
-0.098285,
-0.396762,
-0.260415
],
[
0.289151,
-0.208604,
-0.408013,
-0.612891,
-0.695972,
-0.429583
],
[
0.034906,
1.456609,
0.533815,
0.669295,
0.153014,
0.865615
],
[
-0.223249,
1.144715,
0.06671,
0.947522,
0.276081,
0.513543
]
],
"network.4.bias": [
-0.431329,
0.11889,
-0.142492,
-0.102661,
0.22307,
0.312798
],
"network.6.weight": [
[
-0.599718,
1.024097,
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1.007061,
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],
[
-0.438921,
-0.232001,
0.32822,
-0.047312,
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[
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-0.003309,
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],
[
-0.33558,
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0.241042,
-0.120132,
0.008877
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[
0.139506,
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0.379263,
0.394496,
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[
-0.127492,
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-0.020696,
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-0.116485,
-0.185538
]
],
"network.6.bias": [
0.066048,
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0.039224,
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-0.065954,
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],
"network.8.weight": [
[
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0.017601,
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],
[
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[
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0.025901
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[
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0.326188,
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[
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0.062268,
-0.050399
],
[
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-0.402952,
-0.225446
]
],
"network.8.bias": [
-0.228396,
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-0.306636,
-0.231671
],
"network.10.weight": [
[
0.060625,
0.107195,
-0.362846,
-0.324806,
-0.342992,
-0.16097
],
[
-0.26864,
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0.010101,
-0.289806,
0.169625,
0.312191
],
[
-0.364422,
1.161287,
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0.114708,
0.022147,
-0.073678
],
[
0.052986,
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],
[
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[
0.078998,
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],
"network.10.bias": [
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],
"network.12.weight": [
[
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0.071619
]
],
"network.12.bias": [
0.625967
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 32.276031, 0.000000, 0.000177, 0.000000]
std: [0.000000, 0.000000, 45.274891, 0.000000, 0.001674, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [802.049259, 816.959697, 821.906101, 826.786030, 2904.842735], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.015971, 0.015971, 0.015971, 0.015971, 0.015971], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.311949, 0.398928, 0.299607, 0.684684, 0.522834, 0.000000, 0.000000, 0.000000], [0.911452, 0.435444, 0.242801, -0.052700, -0.223464, 0.000000, 0.000000, 0.000000], [-0.139774, 0.218727, -0.817423, -0.244280, -0.334719, 0.000000, 0.000000, 0.000000], [0.248527, 0.282596, 0.018976, -0.092489, -0.892809, 0.000000, 0.000000, 0.000000], [-0.815950, -0.682001, -0.637321, -0.247903, -0.155287, 0.000000, 0.000000, 0.000000], [-0.550851, -0.718960, -0.426556, -0.645010, -0.469293, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.638226, 2.120742, -2.190962, -0.874196, -3.796946, -3.355225]
pre_activation_std: [2.201212, 4.175175, 2.122231, 3.299742, 2.737523, 1.809910]
### 2
mean: [-2.569762, 2.751745, -2.936877, 2.910950, -2.438925, 2.578283]
std: [1.235030, 5.218436, 2.525271, 3.134945, 1.366997, 4.084316]
fourier: [[19.496185, 20.288575, 21.185633, 21.337859, 231.278619], [85.723060, 91.735215, 93.608359, 94.892192, 247.657030], [40.064151, 43.374448, 45.067929, 47.194500, 264.318856], [52.340954, 52.637297, 53.527990, 59.447070, 261.985490], [22.457244, 24.578126, 25.554071, 25.578361, 219.503237], [68.752610, 71.138492, 71.709812, 75.598265, 232.045471]]
input_correlations: [[-0.854014, -0.204985, -0.204009, -0.300172, 0.000000, 0.000000, 0.000000, 0.000000], [-0.423535, 0.981714, 0.074962, 0.857431, 0.000000, 0.000000, 0.000000, 0.000000], [0.132531, -0.973918, -0.072988, -0.887727, 0.000000, 0.000000, 0.000000, 0.000000], [-0.317994, 0.983522, 0.136931, 0.882931, 0.000000, 0.000000, 0.000000, 0.000000], [-0.580739, -0.553090, -0.234858, -0.630672, 0.000000, 0.000000, 0.000000, 0.000000], [-0.369292, 0.989205, 0.082550, 0.860614, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.569762, 2.751745, -2.936877, 2.910950, -2.438925, 2.578283]
pre_activation_std: [1.235030, 5.218436, 2.525271, 3.134945, 1.366997, 4.084316]
### 4
mean: [-3.350013, 10.273723, -1.974720, -3.700704, 9.049253, 8.023950]
std: [4.125980, 14.219841, 2.679205, 4.657463, 12.739522, 10.663342]
fourier: [[73.176528, 74.582069, 75.160385, 75.241729, 301.501138], [251.502365, 256.076243, 257.346593, 260.038809, 924.635049], [47.701384, 48.524515, 48.744204, 48.855251, 177.724819], [81.082183, 82.296721, 82.538597, 86.212078, 333.063350], [226.529201, 230.646900, 231.926699, 232.382753, 814.432749], [188.314882, 191.882723, 192.902713, 195.172351, 722.155443]]
input_correlations: [[0.000000, -0.999214, 0.000000, -0.995225, 0.000000, -0.999583, 0.000000, 0.000000], [0.000000, 0.998891, 0.000000, 0.995842, 0.000000, 0.999744, 0.000000, 0.000000], [0.000000, -0.999302, 0.000000, -0.994762, 0.000000, -0.999700, 0.000000, 0.000000], [0.000000, -0.997117, 0.000000, -0.998015, 0.000000, -0.999513, 0.000000, 0.000000], [0.000000, 0.999308, 0.000000, 0.994887, 0.000000, 0.999638, 0.000000, 0.000000], [0.000000, 0.998839, 0.000000, 0.996002, 0.000000, 0.999681, 0.000000, 0.000000]]
pre_activation_mean: [-3.350013, 10.273723, -1.974720, -3.700704, 9.049253, 8.023950]
pre_activation_std: [4.125980, 14.219841, 2.679205, 4.657463, 12.739522, 10.663342]
### 6
mean: [26.010651, -9.705044, -15.231167, -4.065253, -5.859417, -6.566726]
std: [35.777313, 13.196505, 20.960026, 5.477252, 7.951527, 9.018940]
fourier: [[633.785451, 645.420577, 649.272540, 653.355563, 2340.958852], [233.789607, 238.101213, 239.559248, 240.966668, 873.453996], [371.329245, 378.183328, 380.508257, 382.724015, 1370.804975], [97.023313, 98.786143, 99.346719, 100.037049, 365.872736], [140.866710, 143.466866, 144.347350, 145.195200, 527.347603], [159.604779, 162.533472, 163.421439, 164.841487, 591.005351]]
input_correlations: [[0.000000, 0.999994, 0.000000, 0.000000, 0.999977, 0.999986, 0.000000, 0.000000], [0.000000, -0.999993, 0.000000, 0.000000, -0.999979, -0.999986, 0.000000, 0.000000], [0.000000, -0.999993, 0.000000, 0.000000, -0.999979, -0.999986, 0.000000, 0.000000], [0.000000, -0.999996, 0.000000, 0.000000, -0.999974, -0.999986, 0.000000, 0.000000], [0.000000, -0.999993, 0.000000, 0.000000, -0.999978, -0.999986, 0.000000, 0.000000], [0.000000, -0.999999, 0.000000, 0.000000, -0.999962, -0.999994, 0.000000, 0.000000]]
pre_activation_mean: [26.010651, -9.705044, -15.231167, -4.065253, -5.859417, -6.566726]
pre_activation_std: [35.777313, 13.196505, 20.960026, 5.477252, 7.951527, 9.018940]
### 8
mean: [-15.567615, 19.664042, 13.738901, -2.258462, -15.172154, -3.049127]
std: [21.098894, 27.161510, 19.394995, 4.058115, 20.447327, 3.875373]
fourier: [[373.761255, 380.622813, 382.894429, 385.302303, 1401.085420], [481.158857, 489.992032, 492.916369, 496.016133, 1769.763783], [343.577100, 349.884546, 351.972706, 354.186119, 1236.501102], [71.888423, 73.208160, 73.645077, 74.108203, 203.261556], [362.218891, 368.868554, 371.070017, 373.403534, 1365.494020], [68.651191, 69.911498, 70.328741, 70.771011, 274.421420]]
input_correlations: [[-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-15.567615, 19.664042, 13.738901, -2.258462, -15.172154, -3.049127]
pre_activation_std: [21.098894, 27.161510, 19.394995, 4.058115, 20.447327, 3.875373]
### 10
mean: [-3.206229, -7.465782, 32.276031, -0.948753, -19.480860, -9.060947]
std: [4.098883, 10.346517, 45.274891, 0.946534, 28.109224, 12.081920]
fourier: [[72.656584, 74.514004, 74.812225, 75.157494, 288.560551], [183.327529, 187.162615, 188.457765, 188.913367, 671.920455], [802.049259, 816.959697, 821.906101, 826.786030, 2904.842735], [16.803735, 17.234250, 17.548493, 17.819436, 85.387739], [497.946296, 507.075528, 510.097220, 513.323809, 1753.277385], [214.098733, 218.827332, 220.436188, 220.580648, 815.485292]]
input_correlations: [[0.000000, -0.999902, -0.999902, 0.418313, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999988, -0.999988, 0.426498, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 1.000000, 1.000000, -0.430556, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.998673, -0.998673, 0.383915, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -1.000000, -1.000000, 0.431001, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999974, -0.999974, 0.424454, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.206229, -7.465782, 32.276031, -0.948753, -19.480860, -9.060947]
pre_activation_std: [4.098883, 10.346517, 45.274891, 0.946534, 28.109224, 12.081920]
### 12
mean: [-19.906633]
std: [28.802151]
fourier: [[510.225358, 519.706753, 522.871834, 525.978585, 1791.596701]]
input_correlations: [[0.000000, 0.000000, -1.000000, 0.000000, 0.073451, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-19.906633]
pre_activation_std: [28.802151]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.31194944421563936, 0.3989280679925829, 0.2996065035642956, 0.6846839164431336, 0.5228341391101323, 0.0, 0.0, 0.0], "pre_activation_mean": 2.638225555419922, "pre_activation_std": 2.201211929321289}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.9114518504200653, 0.4354444429928835, 0.24280114195302346, -0.05269961902680057, -0.22346405772338002, 0.0, 0.0, 0.0], "pre_activation_mean": 2.120741844177246, "pre_activation_std": 4.175175189971924}, "2": {"mean": 32.276031494140625, "std": 45.2748908996582, "fourier": [802.0492593643924, 816.9596969211623, 821.9061010367548, 826.7860298420841, 2904.842735171318], "input_correlations": [-0.13977373693660602, 0.21872694891645061, -0.8174234083733211, -0.24428046443640397, -0.3347186736941162, 0.0, 0.0, 0.0], "pre_activation_mean": 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"sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.652318, 0.459863, 0.330884, 0.47485, 0.598809], [1.941887, 0.264183, 0.007915, 0.026333, -0.898072], [-0.052335, 0.658434, -0.994098, -0.421888, -0.078055], [0.575337, 0.244678, 0.147206, 0.039535, -1.751602], [-0.809717, -0.507657, -0.540057, -0.221096, 0.089569], [-0.293729, -0.409661, -0.148803, -0.412062, -0.298951]], "network.0.bias": [0.164025, 0.257391, -0.248102, -0.267998, -0.372457, -0.680019], "network.2.weight": [[-0.587355, -0.074639, -0.335529, -0.351833, 0.037947, -0.358548], [-0.40455, 1.122579, 0.957133, 0.773448, -0.17408, -0.052602], [-0.191447, -0.540626, -0.094484, -0.615085, 0.034549, 0.006391], [-0.075386, 0.668446, 1.083957, 0.600205, 0.334403, 0.425751], [-0.522716, -0.148573, -0.49018, -0.556721, 0.010189, -0.361966], [-0.195545, 0.916959, 0.801501, 0.562598, 0.296468, -0.019795]], "network.2.bias": [-0.490101, 0.296607, -0.558965, 0.848554, -0.178135, 0.255908], "network.4.weight": [[0.164717, -0.518841, -0.166381, -0.308837, 0.116415, -0.149717], [-0.040881, 1.390273, -0.514641, 1.055265, 0.059524, 1.017295], [-0.217265, -0.270028, -0.226961, -0.098285, -0.396762, -0.260415], [0.289151, -0.208604, -0.408013, -0.612891, -0.695972, -0.429583], [0.034906, 1.456609, 0.533815, 0.669295, 0.153014, 0.865615], [-0.223249, 1.144715, 0.06671, 0.947522, 0.276081, 0.513543]], "network.4.bias": [-0.431329, 0.11889, -0.142492, -0.102661, 0.22307, 0.312798], "network.6.weight": [[-0.599718, 1.024097, -0.227872, 0.22385, 1.007061, 0.786416], [-0.438921, -0.232001, 0.32822, -0.047312, -0.417966, -0.428853], [-0.275655, -0.327691, -0.003309, -0.172624, -0.67436, -0.723002], [-0.33558, -0.284219, -0.133168, 0.241042, -0.120132, 0.008877], [0.139506, -0.126581, 0.379263, 0.394496, -0.253297, -0.274286], [-0.127492, -0.390764, -0.020696, -0.321776, -0.116485, -0.185538]], "network.6.bias": [0.066048, -0.098159, 0.039224, -0.129396, -0.065954, -0.009279], "network.8.weight": [[-0.589728, -0.254993, 0.04059, 0.017601, 0.146846, 0.358406], [0.759183, -0.33901, -0.579096, -0.363953, -0.073273, 0.012725], [0.542103, 0.21113, 0.240983, 0.301471, -0.280587, 0.025901], [-0.113427, 0.698038, -0.069974, 0.326188, -0.063061, -0.058988], [-0.571517, -0.289854, -0.028659, -0.273962, 0.062268, -0.050399], [-0.108319, -0.210632, -0.302723, -0.227083, -0.402952, -0.225446]], "network.8.bias": [-0.228396, -0.082793, -0.361557, 0.69185, -0.306636, -0.231671], "network.10.weight": [[0.060625, 0.107195, -0.362846, -0.324806, -0.342992, -0.16097], [-0.26864, -0.389032, 0.010101, -0.289806, 0.169625, 0.312191], [-0.364422, 1.161287, 0.708545, 0.114708, 0.022147, -0.073678], [0.052986, -0.037399, 0.002436, -0.27655, -0.384724, -0.301359], [0.339747, -1.010935, -0.033517, 0.007466, 0.258176, 0.336121], [0.078998, 0.060189, -0.709356, -0.49325, -0.013622, -0.261538]], "network.10.bias": [-0.287688, 0.082245, -0.308795, -0.211633, 0.857755, -0.435993], "network.12.weight": [[0.180408, 0.148478, -0.63616, 0.406266, 0.660742, 0.071619]], "network.12.bias": [0.625967]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7023701071739197, "train_acc": 0.465, "val_loss": 0.7157906889915466, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6760231852531433, "train_acc": 0.575, "val_loss": 0.7125726938247681, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6664766371250153, "train_acc": 0.575, "val_loss": 0.6908618211746216, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6438778936862946, "train_acc": 0.575, "val_loss": 0.6363889575004578, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6431379020214081, "train_acc": 0.565, "val_loss": 0.6101850271224976, "val_acc": 0.64}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5513409674167633, "train_acc": 0.715, "val_loss": 0.5700923204421997, "val_acc": 0.68}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5130976289510727, "train_acc": 0.73, "val_loss": 0.550891637802124, "val_acc": 0.68}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.4836505800485611, "train_acc": 0.755, "val_loss": 0.5600473880767822, "val_acc": 0.66}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.48795051872730255, "train_acc": 0.755, "val_loss": 0.5600194334983826, "val_acc": 0.7}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.4937541335821152, "train_acc": 0.77, "val_loss": 0.5483459830284119, "val_acc": 0.7}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.43931829929351807, "train_acc": 0.79, "val_loss": 0.4933161437511444, "val_acc": 0.78}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.4240656644105911, "train_acc": 0.8, "val_loss": 0.44480639696121216, "val_acc": 0.78}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.4167965352535248, "train_acc": 0.815, "val_loss": 0.48290133476257324, "val_acc": 0.76}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.39915263652801514, "train_acc": 0.81, "val_loss": 0.5727351903915405, "val_acc": 0.5}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.7157906889915466, "final_val_loss": 0.6363889575004578, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.6101850271224976, "final_val_loss": 0.5727351903915405, "initial_val_acc": 0.64, "final_val_acc": 0.5, "best_val_acc": 0.78, "best_epoch": 10}, "improvement": 0.28, "first_improvement_epoch": 3}} |
22 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.62, "improved_accuracy": 0.84, "improvement": 0.21999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7000, "learning_rate": 0.025272621911807264, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.032966,
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-0.486853,
0.136933
],
[
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0.057566,
0.51626,
0.358965,
-0.401717
],
[
-0.500943,
-0.056082,
-0.106036,
0.113473,
0.575358
],
[
0.429019,
-0.084504,
-0.015704,
-0.119374,
0.237615
],
[
-0.169416,
0.517943,
-0.225718,
-0.214728,
-0.434525
],
[
0.361686,
0.067502,
-0.028392,
-0.132661,
0.453955
]
],
"network.0.bias": [
-0.58668,
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],
"network.2.weight": [
[
-0.24978,
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],
[
-0.05922,
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0.350059,
0.050367
],
[
0.345278,
0.433392,
-0.549236,
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0.150041,
0.206435
],
[
-0.077073,
0.518734,
-0.590535,
-0.462745,
0.228535,
-0.242503
],
[
-0.323567,
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0.377006,
0.21839,
0.376795,
0.388988
],
[
0.187528,
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0.173509,
0.006477,
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]
],
"network.2.bias": [
0.375674,
0.125556,
0.350693,
0.034954,
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0.136856
],
"network.4.weight": [
[
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0.003302
],
[
0.156805,
0.034622,
0.021277,
-0.172932,
0.310214,
0.510492
],
[
-0.211586,
0.016106,
0.507054,
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0.132092
],
[
0.285941,
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0.12848,
0.083909,
0.210869,
0.178358
],
[
-0.598886,
0.543765,
0.688881,
0.217624,
0.092883,
0.220336
],
[
0.133075,
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0.308351,
0.315972,
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0.032486
]
],
"network.4.bias": [
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"network.6.weight": [
[
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[
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[
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[
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[
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[
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],
"network.6.bias": [
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],
"network.8.weight": [
[
0.250633,
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]
],
"network.8.bias": [
-0.25835
]
}
## Activation Signature
### 0
mean: [0.484516, 0.133479, 1.342820, 0.226614, 0.508585, 0.249922]
std: [0.945943, 0.253853, 1.406034, 0.541791, 1.027588, 0.537585]
fourier: [[14.323884, 14.432410, 14.433461, 19.099534, 43.606418], [4.478603, 4.934629, 5.099313, 5.179110, 12.013069], [25.937820, 26.935120, 28.662309, 28.769765, 120.853792], [7.848725, 8.360751, 9.056302, 10.704776, 20.395276], [15.361060, 15.473912, 16.706560, 20.838810, 45.772653], [8.076907, 8.128973, 9.289471, 10.659768, 22.492981]]
input_correlations: [[-0.236852, -0.764267, -0.404075, -0.780919, -0.010947, 0.000000, 0.000000, 0.000000], [-0.147058, 0.339121, 0.569012, 0.529259, -0.362823, 0.000000, 0.000000, 0.000000], [-0.648980, -0.283895, -0.221903, 0.283224, 0.602717, 0.000000, 0.000000, 0.000000], [0.866804, 0.041842, 0.290229, -0.266686, 0.531253, 0.000000, 0.000000, 0.000000], [-0.213316, 0.443084, -0.378652, -0.179258, -0.758721, 0.000000, 0.000000, 0.000000], [0.753976, 0.215809, 0.311470, -0.119631, 0.749032, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.752727, 1.130682, -0.065684, 0.838110, -1.067287, 0.826207]
pre_activation_std: [1.564327, 1.327830, 1.441525, 1.038598, 1.351696, 1.223385]
### 2
mean: [1.005812, 0.413713, 0.513001, -0.137245, 0.910169, 0.377528]
std: [1.163617, 0.563929, 0.861547, 1.377663, 0.863582, 0.363321]
fourier: [[21.644584, 21.712311, 23.874173, 24.275814, 90.523058], [9.482382, 9.580560, 9.689594, 10.195731, 37.234176], [14.103203, 14.271349, 14.339548, 15.883961, 46.170126], [19.945688, 22.798016, 25.563833, 27.069248, 27.605819], [15.360393, 16.617527, 17.443673, 19.310477, 81.915251], [4.789311, 5.671417, 5.692412, 6.494322, 33.977487]]
input_correlations: [[-0.177215, -0.563629, 0.410630, 0.898494, -0.211732, 0.960203, 0.000000, 0.000000], [0.538103, 0.875473, -0.616535, -0.358425, 0.402775, -0.420358, 0.000000, 0.000000], [0.481236, 0.856201, -0.675637, -0.439481, 0.269954, -0.520919, 0.000000, 0.000000], [0.346943, 0.767297, -0.573589, -0.722146, 0.255099, -0.798102, 0.000000, 0.000000], [-0.120438, -0.546521, 0.570348, 0.785401, -0.003703, 0.910435, 0.000000, 0.000000], [0.575691, 0.865421, 0.133683, -0.656739, 0.041270, -0.550645, 0.000000, 0.000000]]
pre_activation_mean: [1.005812, 0.413713, 0.513001, -0.137245, 0.910169, 0.377528]
pre_activation_std: [1.163617, 0.563929, 0.861547, 1.377663, 0.863582, 0.363321]
### 4
mean: [1.039916, 0.541837, 0.247574, 1.226183, 0.145581, 0.388178]
std: [1.489365, 0.430646, 1.210089, 0.408094, 1.346819, 0.666004]
fourier: [[25.415444, 29.919825, 30.212779, 30.746409, 93.592456], [7.526114, 8.834689, 8.878382, 9.483804, 48.765314], [19.952612, 22.281688, 23.716963, 24.145443, 25.240854], [7.161587, 7.176432, 7.546608, 8.807222, 110.356441], [19.647275, 19.719527, 24.522377, 25.253307, 28.559471], [9.633043, 11.861306, 12.383272, 13.784671, 34.936010]]
input_correlations: [[0.925040, -0.800698, -0.857107, -0.843954, 0.906143, -0.723958, 0.000000, 0.000000], [0.961263, -0.500642, -0.553732, -0.518083, 0.981114, -0.352520, 0.000000, 0.000000], [-0.897109, 0.833791, 0.890087, 0.865709, -0.888901, 0.747468, 0.000000, 0.000000], [0.758544, 0.094618, 0.024866, 0.045454, 0.769107, 0.036450, 0.000000, 0.000000], [-0.849220, 0.897612, 0.935864, 0.905268, -0.814298, 0.788009, 0.000000, 0.000000], [-0.782882, 0.915321, 0.958605, 0.929147, -0.791788, 0.777491, 0.000000, 0.000000]]
pre_activation_mean: [1.039916, 0.541837, 0.247574, 1.226183, 0.145581, 0.388178]
pre_activation_std: [1.489365, 0.430646, 1.210089, 0.408094, 1.346819, 0.666004]
### 6
mean: [-0.147766, -0.004108, 1.270476, -0.109536, 0.273995, 0.015681]
std: [1.508730, 0.633011, 1.546780, 0.942375, 1.240492, 0.868441]
fourier: [[22.878556, 23.070908, 26.788749, 28.256626, 31.555499], [8.761729, 8.881531, 11.642271, 12.447584, 13.298559], [28.850448, 30.696390, 31.169145, 31.450619, 114.342849], [13.747386, 15.443926, 17.673010, 18.041117, 19.681402], [19.136980, 19.954248, 22.326811, 24.659552, 25.350416], [12.318407, 14.641747, 16.381250, 16.853428, 17.851452]]
input_correlations: [[-0.896914, -0.749912, 0.954063, -0.294822, 0.931692, 0.961581, 0.000000, 0.000000], [0.847873, 0.722782, -0.971512, 0.250924, -0.952428, -0.977774, 0.000000, 0.000000], [0.982682, 0.904089, -0.839495, 0.555130, -0.793979, -0.856019, 0.000000, 0.000000], [-0.929477, -0.803937, 0.928835, -0.372206, 0.899991, 0.940200, 0.000000, 0.000000], [-0.794790, -0.620855, 0.992680, -0.120435, 0.981056, 0.993055, 0.000000, 0.000000], [-0.933828, -0.808607, 0.926992, -0.390236, 0.887584, 0.936896, 0.000000, 0.000000]]
pre_activation_mean: [-0.147766, -0.004108, 1.270476, -0.109536, 0.273995, 0.015681]
pre_activation_std: [1.508730, 0.633011, 1.546780, 0.942375, 1.240492, 0.868441]
### 8
mean: [-0.784002]
std: [1.553582]
fourier: [[25.696452, 29.126883, 30.001934, 32.586984, 70.560147]]
input_correlations: [[0.871320, -0.928732, -0.930138, 0.900033, 0.893051, 0.925944, 0.000000, 0.000000]]
pre_activation_mean: [-0.784002]
pre_activation_std: [1.553582]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.032966,
-0.394797,
-0.253948,
-0.486853,
0.136933
],
[
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0.51626,
0.358965,
-0.401717
],
[
-0.500943,
-0.056082,
-0.106036,
0.113473,
0.575358
],
[
0.429019,
-0.084504,
-0.015704,
-0.119374,
0.237615
],
[
-0.169416,
0.517943,
-0.225718,
-0.214728,
-0.434525
],
[
0.361686,
0.067502,
-0.028392,
-0.132661,
0.453955
]
],
"network.0.bias": [
-0.58668,
-0.095363,
-0.071542,
0.453942,
-0.332381,
0.037019
],
"network.2.weight": [
[
-0.24978,
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],
[
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-0.269259,
-0.071633,
0.350059,
0.050367
],
[
0.345278,
0.433392,
-0.549236,
-0.378869,
0.150041,
0.206435
],
[
-0.077073,
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-0.590535,
-0.462745,
0.228535,
-0.242503
],
[
-0.323567,
-0.121177,
0.377006,
0.21839,
0.376795,
0.388988
],
[
0.187528,
0.248201,
0.173509,
0.006477,
-0.081622,
-0.124422
]
],
"network.2.bias": [
0.375674,
0.125556,
0.350693,
0.034954,
0.389515,
0.136856
],
"network.4.weight": [
[
0.508053,
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-0.272102,
-0.706842,
0.448065,
0.003302
],
[
0.156805,
0.034622,
0.021277,
-0.172932,
0.310214,
0.510492
],
[
-0.211586,
0.016106,
0.507054,
0.425739,
-0.524902,
0.132092
],
[
0.285941,
0.315315,
0.12848,
0.083909,
0.210869,
0.178358
],
[
-0.598886,
0.543765,
0.688881,
0.217624,
0.092883,
0.220336
],
[
0.133075,
0.186801,
0.308351,
0.315972,
-0.438073,
0.032486
]
],
"network.4.bias": [
0.629708,
0.029618,
0.401849,
0.504995,
-0.072618,
0.252964
],
"network.6.weight": [
[
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0.204788,
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0.186434
],
[
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-0.169375,
0.324943,
-0.398061,
-0.22864
],
[
0.669259,
0.522305,
-0.297113,
0.282717,
-0.301907,
-0.075205
],
[
-0.417444,
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0.195055,
0.127179,
0.24539,
0.127686
],
[
-0.2779,
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0.501804,
0.012081,
0.41735,
0.435246
],
[
-0.395381,
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0.089181,
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0.283509
]
],
"network.6.bias": [
-0.100842,
0.016215,
0.28953,
0.041729,
-0.17094,
0.118234
],
"network.8.weight": [
[
0.250633,
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0.459943,
0.20551,
0.124867
]
],
"network.8.bias": [
-0.25835
]
}
## Activation Signature
### 0
mean: [0.484516, 0.133479, 1.342820, 0.226614, 0.508585, 0.249922]
std: [0.945943, 0.253853, 1.406034, 0.541791, 1.027588, 0.537585]
fourier: [[14.323884, 14.432410, 14.433461, 19.099534, 43.606418], [4.478603, 4.934629, 5.099313, 5.179110, 12.013069], [25.937820, 26.935120, 28.662309, 28.769765, 120.853792], [7.848725, 8.360751, 9.056302, 10.704776, 20.395276], [15.361060, 15.473912, 16.706560, 20.838810, 45.772653], [8.076907, 8.128973, 9.289471, 10.659768, 22.492981]]
input_correlations: [[-0.236852, -0.764267, -0.404075, -0.780919, -0.010947, 0.000000, 0.000000, 0.000000], [-0.147058, 0.339121, 0.569012, 0.529259, -0.362823, 0.000000, 0.000000, 0.000000], [-0.648980, -0.283895, -0.221903, 0.283224, 0.602717, 0.000000, 0.000000, 0.000000], [0.866804, 0.041842, 0.290229, -0.266686, 0.531253, 0.000000, 0.000000, 0.000000], [-0.213316, 0.443084, -0.378652, -0.179258, -0.758721, 0.000000, 0.000000, 0.000000], [0.753976, 0.215809, 0.311470, -0.119631, 0.749032, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.752727, 1.130682, -0.065684, 0.838110, -1.067287, 0.826207]
pre_activation_std: [1.564327, 1.327830, 1.441525, 1.038598, 1.351696, 1.223385]
### 2
mean: [1.005812, 0.413713, 0.513001, -0.137245, 0.910169, 0.377528]
std: [1.163617, 0.563929, 0.861547, 1.377663, 0.863582, 0.363321]
fourier: [[21.644584, 21.712311, 23.874173, 24.275814, 90.523058], [9.482382, 9.580560, 9.689594, 10.195731, 37.234176], [14.103203, 14.271349, 14.339548, 15.883961, 46.170126], [19.945688, 22.798016, 25.563833, 27.069248, 27.605819], [15.360393, 16.617527, 17.443673, 19.310477, 81.915251], [4.789311, 5.671417, 5.692412, 6.494322, 33.977487]]
input_correlations: [[-0.177215, -0.563629, 0.410630, 0.898494, -0.211732, 0.960203, 0.000000, 0.000000], [0.538103, 0.875473, -0.616535, -0.358425, 0.402775, -0.420358, 0.000000, 0.000000], [0.481236, 0.856201, -0.675637, -0.439481, 0.269954, -0.520919, 0.000000, 0.000000], [0.346943, 0.767297, -0.573589, -0.722146, 0.255099, -0.798102, 0.000000, 0.000000], [-0.120438, -0.546521, 0.570348, 0.785401, -0.003703, 0.910435, 0.000000, 0.000000], [0.575691, 0.865421, 0.133683, -0.656739, 0.041270, -0.550645, 0.000000, 0.000000]]
pre_activation_mean: [1.005812, 0.413713, 0.513001, -0.137245, 0.910169, 0.377528]
pre_activation_std: [1.163617, 0.563929, 0.861547, 1.377663, 0.863582, 0.363321]
### 4
mean: [1.039916, 0.541837, 0.247574, 1.226183, 0.145581, 0.388178]
std: [1.489365, 0.430646, 1.210089, 0.408094, 1.346819, 0.666004]
fourier: [[25.415444, 29.919825, 30.212779, 30.746409, 93.592456], [7.526114, 8.834689, 8.878382, 9.483804, 48.765314], [19.952612, 22.281688, 23.716963, 24.145443, 25.240854], [7.161587, 7.176432, 7.546608, 8.807222, 110.356441], [19.647275, 19.719527, 24.522377, 25.253307, 28.559471], [9.633043, 11.861306, 12.383272, 13.784671, 34.936010]]
input_correlations: [[0.925040, -0.800698, -0.857107, -0.843954, 0.906143, -0.723958, 0.000000, 0.000000], [0.961263, -0.500642, -0.553732, -0.518083, 0.981114, -0.352520, 0.000000, 0.000000], [-0.897109, 0.833791, 0.890087, 0.865709, -0.888901, 0.747468, 0.000000, 0.000000], [0.758544, 0.094618, 0.024866, 0.045454, 0.769107, 0.036450, 0.000000, 0.000000], [-0.849220, 0.897612, 0.935864, 0.905268, -0.814298, 0.788009, 0.000000, 0.000000], [-0.782882, 0.915321, 0.958605, 0.929147, -0.791788, 0.777491, 0.000000, 0.000000]]
pre_activation_mean: [1.039916, 0.541837, 0.247574, 1.226183, 0.145581, 0.388178]
pre_activation_std: [1.489365, 0.430646, 1.210089, 0.408094, 1.346819, 0.666004]
### 6
mean: [-0.147766, -0.004108, 1.270476, -0.109536, 0.273995, 0.015681]
std: [1.508730, 0.633011, 1.546780, 0.942375, 1.240492, 0.868441]
fourier: [[22.878556, 23.070908, 26.788749, 28.256626, 31.555499], [8.761729, 8.881531, 11.642271, 12.447584, 13.298559], [28.850448, 30.696390, 31.169145, 31.450619, 114.342849], [13.747386, 15.443926, 17.673010, 18.041117, 19.681402], [19.136980, 19.954248, 22.326811, 24.659552, 25.350416], [12.318407, 14.641747, 16.381250, 16.853428, 17.851452]]
input_correlations: [[-0.896914, -0.749912, 0.954063, -0.294822, 0.931692, 0.961581, 0.000000, 0.000000], [0.847873, 0.722782, -0.971512, 0.250924, -0.952428, -0.977774, 0.000000, 0.000000], [0.982682, 0.904089, -0.839495, 0.555130, -0.793979, -0.856019, 0.000000, 0.000000], [-0.929477, -0.803937, 0.928835, -0.372206, 0.899991, 0.940200, 0.000000, 0.000000], [-0.794790, -0.620855, 0.992680, -0.120435, 0.981056, 0.993055, 0.000000, 0.000000], [-0.933828, -0.808607, 0.926992, -0.390236, 0.887584, 0.936896, 0.000000, 0.000000]]
pre_activation_mean: [-0.147766, -0.004108, 1.270476, -0.109536, 0.273995, 0.015681]
pre_activation_std: [1.508730, 0.633011, 1.546780, 0.942375, 1.240492, 0.868441]
### 8
mean: [-0.784002]
std: [1.553582]
fourier: [[25.696452, 29.126883, 30.001934, 32.586984, 70.560147]]
input_correlations: [[0.871320, -0.928732, -0.930138, 0.900033, 0.893051, 0.925944, 0.000000, 0.000000]]
pre_activation_mean: [-0.784002]
pre_activation_std: [1.553582]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.4845157563686371, "std": 0.9459434151649475, "fourier": [14.323883858016721, 14.432410335161574, 14.433460592453905, 19.099534387391063, 43.60641765128821], "input_correlations": [-0.2368515243684299, -0.7642669511375746, -0.4040754513682998, -0.7809194145561468, -0.010947232292676945, 0.0, 0.0, 0.0], "pre_activation_mean": -2.7527272701263428, "pre_activation_std": 1.5643268823623657}, "1": {"mean": 0.1334785372018814, "std": 0.25385335087776184, "fourier": [4.478603126857287, 4.9346287795723125, 5.0993125147678615, 5.179109976079215, 12.013068614527583], "input_correlations": [-0.14705789439180633, 0.33912124434680974, 0.5690117326560034, 0.5292590997857194, -0.36282324850904746, 0.0, 0.0, 0.0], "pre_activation_mean": 1.1306822299957275, "pre_activation_std": 1.327830195426941}, "2": {"mean": 1.3428199291229248, "std": 1.4060335159301758, "fourier": [25.93781992300485, 26.935120230652345, 28.662308765364894, 28.769764799713187, 120.8537919614464], "input_correlations": [-0.6489799139551853, -0.2838952690295622, -0.22190322869955648, 0.2832241818995646, 0.6027165161077465, 0.0, 0.0, 0.0], "pre_activation_mean": -0.0656835213303566, "pre_activation_std": 1.4415251016616821}, "3": {"mean": 0.22661414742469788, "std": 0.5417906045913696, "fourier": [7.848724865446506, 8.360751197650183, 9.056301690137987, 10.704776056372284, 20.395276089780964], "input_correlations": [0.8668038104975012, 0.04184225436907011, 0.29022862058833804, -0.2666856031425082, 0.5312525247393836, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8381099104881287, "pre_activation_std": 1.0385980606079102}, "4": {"mean": 0.5085850358009338, "std": 1.027588129043579, "fourier": [15.36106044622323, 15.473912483664433, 16.706559694779234, 20.838809689295505, 45.77265306049958], "input_correlations": [-0.2133156555243161, 0.4430838416422005, -0.37865170078991167, -0.17925764342876757, -0.7587205078036942, 0.0, 0.0, 0.0], "pre_activation_mean": -1.0672869682312012, "pre_activation_std": 1.3516956567764282}, "5": {"mean": 0.2499220371246338, "std": 0.5375847220420837, "fourier": [8.076906865341616, 8.12897335552001, 9.289471063449483, 10.659767676031358, 22.49298075772822], "input_correlations": [0.7539759256620735, 0.2158091090125905, 0.3114702806529985, -0.11963079831222796, 0.7490321206216051, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8262072205543518, "pre_activation_std": 1.2233853340148926}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 1.0058116912841797, "std": 1.1636173725128174, "fourier": [21.64458364173018, 21.71231124079313, 23.87417296151026, 24.27581420989474, 90.52305842936039], "input_correlations": [-0.17721495018219938, -0.5636285367495744, 0.4106296111489412, 0.8984943607586952, -0.21173190216429447, 0.9602028573774866, 0.0, 0.0], "pre_activation_mean": 1.0058116912841797, "pre_activation_std": 1.1636173725128174}, "1": {"mean": 0.4137130677700043, "std": 0.5639287233352661, "fourier": [9.482381875512097, 9.580560474192712, 9.689594445151554, 10.195731134700859, 37.234176494181156], "input_correlations": [0.5381031639879915, 0.8754732894703355, -0.6165353736331914, -0.35842477165916325, 0.4027752484217304, -0.42035830506641575, 0.0, 0.0], "pre_activation_mean": 0.4137130677700043, "pre_activation_std": 0.5639287233352661}, "2": {"mean": 0.5130014419555664, "std": 0.861546516418457, "fourier": [14.103203307143612, 14.271348874204012, 14.339548403148337, 15.883960776936826, 46.17012582719326], "input_correlations": [0.48123613079621014, 0.8562006460894394, -0.6756368021059431, -0.4394808732349334, 0.26995365360645973, -0.5209193894488559, 0.0, 0.0], "pre_activation_mean": 0.5130014419555664, "pre_activation_std": 0.861546516418457}, "3": {"mean": -0.13724499940872192, "std": 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{"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6892157196998596, "final_val_loss": 0.6526867747306824, "initial_val_acc": 0.54, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.6102039217948914, "final_val_loss": 0.35592514276504517, "initial_val_acc": 0.72, "final_val_acc": 0.84, "best_val_acc": 0.84, "best_epoch": 8}, "improvement": 0.21999999999999997, "first_improvement_epoch": 2}} |
23 | {"target_pattern": "alternating", "degraded_accuracy": 0.72, "improved_accuracy": 0.98, "improvement": 0.26, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5108, "learning_rate": 0.09399438147876214, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.775729, 0.846562, 0.174618, 2.092153, 0.000000, 1.712475, 0.000000]
std: [1.221399, 1.043843, 0.313833, 2.136669, 0.000000, 1.455123, 0.000000]
fourier: [[18.729526, 18.937970, 21.059107, 28.935682, 69.815596], [16.023115, 16.591716, 17.227888, 24.225237, 76.190589], [4.634952, 4.698816, 4.968522, 6.459263, 15.715605], [32.223972, 39.947386, 40.601163, 44.721774, 188.293807], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [19.805176, 26.881065, 28.467580, 29.286071, 154.122760], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.046643, -0.651553, -0.037342, -0.912480, -0.150738, 0.000000, 0.000000, 0.000000], [-0.500645, 0.282288, 0.579159, 0.132317, 0.002399, 0.000000, 0.000000, 0.000000], [0.120846, 0.341569, -0.774075, 0.305575, 0.037302, 0.000000, 0.000000, 0.000000], [0.195768, -0.690975, 0.050962, -0.822108, 0.005984, 0.000000, 0.000000, 0.000000], [-0.624693, -0.354683, -0.839729, -0.364192, -0.357018, 0.000000, 0.000000, 0.000000], [-0.469371, 0.525290, 0.030506, 0.748345, -0.005691, 0.000000, 0.000000, 0.000000], [0.789364, 0.392767, 0.638429, 0.172095, 0.627473, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.146589, 1.031458, 0.065639, -2.780858, -1.981809, 3.511410, 4.442050]
pre_activation_std: [3.925733, 2.403632, 3.784218, 3.341736, 1.387916, 4.353211, 3.993429]
### 2
mean: [-2.942412, -6.222762, -3.563288, 0.950491, -5.418910, -6.158979, -2.369719]
std: [1.944872, 6.354544, 1.919021, 3.352049, 6.451718, 5.911029, 1.402338]
fourier: [[27.625527, 33.179218, 34.860756, 35.245852, 264.817077], [99.549774, 101.781694, 113.384250, 121.889375, 560.048627], [28.756265, 31.313173, 32.930842, 36.424507, 320.695960], [57.452625, 63.380796, 63.704361, 66.260945, 85.544193], [104.219653, 106.619580, 126.548219, 131.937298, 487.701821], [91.916413, 97.843615, 106.402368, 109.455985, 554.308059], [20.494828, 20.813983, 22.459528, 24.079691, 213.274756]]
input_correlations: [[0.308819, -0.156640, -0.833001, 0.257490, 0.048346, -0.767809, -0.030925, 0.000000], [0.460067, -0.388974, -0.662461, 0.439672, 0.035197, -0.863110, 0.202049, 0.000000], [0.006128, -0.257415, -0.426706, -0.104910, 0.132766, -0.561495, -0.756491, 0.000000], [0.373611, 0.107733, -0.357281, 0.406297, -0.073413, -0.492859, 0.790262, 0.000000], [-0.345735, -0.270850, 0.348465, -0.427900, 0.130468, 0.020900, -0.929136, 0.000000], [0.472193, -0.330186, -0.677974, 0.441837, 0.037876, -0.881290, 0.163682, 0.000000], [0.089363, -0.520864, -0.162843, -0.001000, 0.133900, -0.853120, -0.467337, 0.000000]]
pre_activation_mean: [-2.942412, -6.222762, -3.563288, 0.950491, -5.418910, -6.158979, -2.369719]
pre_activation_std: [1.944872, 6.354544, 1.919021, 3.352049, 6.451718, 5.911029, 1.402338]
### 4
mean: [-0.601770, 0.677183, -0.777678, -1.223305, -1.457511, 1.048653, -0.564008]
std: [0.515074, 1.829527, 0.503788, 1.506744, 1.272767, 1.650755, 0.532076]
fourier: [[7.481664, 7.737757, 8.542284, 9.145635, 54.159303], [28.668776, 30.774782, 33.297651, 43.209306, 60.946483], [7.140130, 7.147019, 9.046894, 9.869766, 69.991048], [24.369553, 24.717564, 30.210898, 30.851870, 110.097478], [21.447803, 22.380615, 25.372609, 26.054978, 131.176002], [27.289746, 28.612220, 29.513262, 31.467896, 94.378754], [8.239985, 8.752547, 9.078331, 12.614503, 50.760693]]
input_correlations: [[0.000000, -0.955099, 0.000000, -0.651634, 0.179326, -0.954994, 0.000000, 0.000000], [0.000000, 0.515616, 0.000000, -0.395058, 0.691016, 0.518006, 0.000000, 0.000000], [0.000000, -0.895693, 0.000000, -0.750510, 0.142082, -0.895227, 0.000000, 0.000000], [0.000000, -0.722489, 0.000000, -0.918725, 0.258696, -0.723029, 0.000000, 0.000000], [0.000000, -0.551460, 0.000000, -0.984034, 0.321474, -0.551160, 0.000000, 0.000000], [0.000000, 0.264151, 0.000000, 0.989266, -0.362354, 0.264536, 0.000000, 0.000000], [0.000000, -0.680998, 0.000000, 0.048427, -0.646031, -0.684231, 0.000000, 0.000000]]
pre_activation_mean: [-0.601770, 0.677183, -0.777678, -1.223305, -1.457511, 1.048653, -0.564008]
pre_activation_std: [0.515074, 1.829527, 0.503788, 1.506744, 1.272767, 1.650755, 0.532076]
### 6
mean: [0.732735, 0.540439, -0.175754, 1.505168, -1.590287, 1.712475, -0.679426]
std: [1.249637, 1.374218, 0.630772, 2.873723, 0.734776, 1.455123, 0.833197]
fourier: [[19.241114, 19.657860, 21.505526, 29.954326, 65.946115], [20.575757, 21.434431, 25.802021, 31.086379, 48.639488], [9.623348, 9.918352, 12.027744, 13.659977, 15.817848], [43.462567, 45.757608, 54.953746, 61.254715, 135.465160], [9.649257, 13.477886, 13.690860, 15.596989, 143.125875], [19.805176, 26.881065, 28.467580, 29.286071, 154.122760], [12.727764, 12.847209, 14.544105, 19.895751, 61.148322]]
input_correlations: [[0.000000, 0.999789, 0.000000, 0.000000, 0.000000, -0.188547, 0.000000, 0.000000], [0.000000, 0.892532, 0.000000, 0.000000, 0.000000, -0.627312, 0.000000, 0.000000], [0.000000, 0.836057, 0.000000, 0.000000, 0.000000, -0.711035, 0.000000, 0.000000], [0.000000, -0.816522, 0.000000, 0.000000, 0.000000, 0.734998, 0.000000, 0.000000], [0.000000, -0.899790, 0.000000, 0.000000, 0.000000, -0.238946, 0.000000, 0.000000], [0.000000, 0.851730, 0.000000, 0.000000, 0.000000, 0.334703, 0.000000, 0.000000], [0.000000, -0.998406, 0.000000, 0.000000, 0.000000, 0.153147, 0.000000, 0.000000]]
pre_activation_mean: [0.732735, 0.540439, -0.175754, 1.505168, -1.590287, 1.712475, -0.679426]
pre_activation_std: [1.249637, 1.374218, 0.630772, 2.873723, 0.734776, 1.455123, 0.833197]
### 8
mean: [-2.562440]
std: [5.355392]
fourier: [[79.242330, 79.728050, 109.612946, 122.130789, 230.619563]]
input_correlations: [[0.850448, 0.910101, 0.795471, -0.926057, 0.000000, 0.498196, 0.000000, 0.000000]]
pre_activation_mean: [-2.562440]
pre_activation_std: [5.355392]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.331387,
-1.008608,
0.077761,
-1.383605,
-0.170314
],
[
-1.052106,
0.556341,
0.945861,
-0.068936,
0.010897
],
[
0.507375,
0.853048,
-1.932971,
0.299743,
0.362075
],
[
0.568852,
-1.131593,
0.143267,
-0.964262,
0.028089
],
[
-0.29658,
0.054424,
-0.500106,
-0.259541,
-0.052651
],
[
-1.418664,
1.281822,
0.249499,
1.114765,
0.024175
],
[
1.134873,
0.202094,
0.701603,
0.191114,
0.94233
]
],
"network.0.bias": [
0.29361,
-0.514439,
0.828218,
0.307147,
-0.045729,
-0.000448,
-0.376109
],
"network.2.weight": [
[
-0.546348,
-0.10775,
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0.088408,
0.544808,
-0.277522,
-0.022733
],
[
0.282221,
-1.012942,
-1.967502,
0.261421,
0.082883,
-0.895981,
0.273524
],
[
-0.275726,
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-0.376885,
-0.043537,
0.324295,
-0.222103,
-0.365292
],
[
0.03837,
0.799403,
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-0.420163,
0.104308,
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0.677237
],
[
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0.959055,
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0.079731,
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],
[
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0.434254,
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0.181127
],
[
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-0.147781
]
],
"network.2.bias": [
-0.443673,
0.384941,
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1.019656,
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],
"network.4.weight": [
[
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[
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1.170872,
0.741354,
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],
[
0.147722,
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],
[
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],
[
0.329904,
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0.067383,
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],
[
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0.085321,
0.724447,
0.040529,
0.100662,
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[
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0.350835,
0.023493,
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0.013404
]
],
"network.4.bias": [
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"network.6.weight": [
[
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],
[
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0.194681,
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],
[
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[
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[
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[
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]
],
"network.6.bias": [
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],
"network.8.weight": [
[
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"network.8.bias": [
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]
}
## Activation Signature
### 0
mean: [0.775729, 0.846562, 0.174618, 2.092153, 0.000000, 1.712475, 0.000000]
std: [1.221399, 1.043843, 0.313833, 2.136669, 0.000000, 1.455123, 0.000000]
fourier: [[18.729526, 18.937970, 21.059107, 28.935682, 69.815596], [16.023115, 16.591716, 17.227888, 24.225237, 76.190589], [4.634952, 4.698816, 4.968522, 6.459263, 15.715605], [32.223972, 39.947386, 40.601163, 44.721774, 188.293807], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [19.805176, 26.881065, 28.467580, 29.286071, 154.122760], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.046643, -0.651553, -0.037342, -0.912480, -0.150738, 0.000000, 0.000000, 0.000000], [-0.500645, 0.282288, 0.579159, 0.132317, 0.002399, 0.000000, 0.000000, 0.000000], [0.120846, 0.341569, -0.774075, 0.305575, 0.037302, 0.000000, 0.000000, 0.000000], [0.195768, -0.690975, 0.050962, -0.822108, 0.005984, 0.000000, 0.000000, 0.000000], [-0.624693, -0.354683, -0.839729, -0.364192, -0.357018, 0.000000, 0.000000, 0.000000], [-0.469371, 0.525290, 0.030506, 0.748345, -0.005691, 0.000000, 0.000000, 0.000000], [0.789364, 0.392767, 0.638429, 0.172095, 0.627473, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.146589, 1.031458, 0.065639, -2.780858, -1.981809, 3.511410, 4.442050]
pre_activation_std: [3.925733, 2.403632, 3.784218, 3.341736, 1.387916, 4.353211, 3.993429]
### 2
mean: [-2.942412, -6.222762, -3.563288, 0.950491, -5.418910, -6.158979, -2.369719]
std: [1.944872, 6.354544, 1.919021, 3.352049, 6.451718, 5.911029, 1.402338]
fourier: [[27.625527, 33.179218, 34.860756, 35.245852, 264.817077], [99.549774, 101.781694, 113.384250, 121.889375, 560.048627], [28.756265, 31.313173, 32.930842, 36.424507, 320.695960], [57.452625, 63.380796, 63.704361, 66.260945, 85.544193], [104.219653, 106.619580, 126.548219, 131.937298, 487.701821], [91.916413, 97.843615, 106.402368, 109.455985, 554.308059], [20.494828, 20.813983, 22.459528, 24.079691, 213.274756]]
input_correlations: [[0.308819, -0.156640, -0.833001, 0.257490, 0.048346, -0.767809, -0.030925, 0.000000], [0.460067, -0.388974, -0.662461, 0.439672, 0.035197, -0.863110, 0.202049, 0.000000], [0.006128, -0.257415, -0.426706, -0.104910, 0.132766, -0.561495, -0.756491, 0.000000], [0.373611, 0.107733, -0.357281, 0.406297, -0.073413, -0.492859, 0.790262, 0.000000], [-0.345735, -0.270850, 0.348465, -0.427900, 0.130468, 0.020900, -0.929136, 0.000000], [0.472193, -0.330186, -0.677974, 0.441837, 0.037876, -0.881290, 0.163682, 0.000000], [0.089363, -0.520864, -0.162843, -0.001000, 0.133900, -0.853120, -0.467337, 0.000000]]
pre_activation_mean: [-2.942412, -6.222762, -3.563288, 0.950491, -5.418910, -6.158979, -2.369719]
pre_activation_std: [1.944872, 6.354544, 1.919021, 3.352049, 6.451718, 5.911029, 1.402338]
### 4
mean: [-0.601770, 0.677183, -0.777678, -1.223305, -1.457511, 1.048653, -0.564008]
std: [0.515074, 1.829527, 0.503788, 1.506744, 1.272767, 1.650755, 0.532076]
fourier: [[7.481664, 7.737757, 8.542284, 9.145635, 54.159303], [28.668776, 30.774782, 33.297651, 43.209306, 60.946483], [7.140130, 7.147019, 9.046894, 9.869766, 69.991048], [24.369553, 24.717564, 30.210898, 30.851870, 110.097478], [21.447803, 22.380615, 25.372609, 26.054978, 131.176002], [27.289746, 28.612220, 29.513262, 31.467896, 94.378754], [8.239985, 8.752547, 9.078331, 12.614503, 50.760693]]
input_correlations: [[0.000000, -0.955099, 0.000000, -0.651634, 0.179326, -0.954994, 0.000000, 0.000000], [0.000000, 0.515616, 0.000000, -0.395058, 0.691016, 0.518006, 0.000000, 0.000000], [0.000000, -0.895693, 0.000000, -0.750510, 0.142082, -0.895227, 0.000000, 0.000000], [0.000000, -0.722489, 0.000000, -0.918725, 0.258696, -0.723029, 0.000000, 0.000000], [0.000000, -0.551460, 0.000000, -0.984034, 0.321474, -0.551160, 0.000000, 0.000000], [0.000000, 0.264151, 0.000000, 0.989266, -0.362354, 0.264536, 0.000000, 0.000000], [0.000000, -0.680998, 0.000000, 0.048427, -0.646031, -0.684231, 0.000000, 0.000000]]
pre_activation_mean: [-0.601770, 0.677183, -0.777678, -1.223305, -1.457511, 1.048653, -0.564008]
pre_activation_std: [0.515074, 1.829527, 0.503788, 1.506744, 1.272767, 1.650755, 0.532076]
### 6
mean: [0.732735, 0.540439, -0.175754, 1.505168, -1.590287, 1.712475, -0.679426]
std: [1.249637, 1.374218, 0.630772, 2.873723, 0.734776, 1.455123, 0.833197]
fourier: [[19.241114, 19.657860, 21.505526, 29.954326, 65.946115], [20.575757, 21.434431, 25.802021, 31.086379, 48.639488], [9.623348, 9.918352, 12.027744, 13.659977, 15.817848], [43.462567, 45.757608, 54.953746, 61.254715, 135.465160], [9.649257, 13.477886, 13.690860, 15.596989, 143.125875], [19.805176, 26.881065, 28.467580, 29.286071, 154.122760], [12.727764, 12.847209, 14.544105, 19.895751, 61.148322]]
input_correlations: [[0.000000, 0.999789, 0.000000, 0.000000, 0.000000, -0.188547, 0.000000, 0.000000], [0.000000, 0.892532, 0.000000, 0.000000, 0.000000, -0.627312, 0.000000, 0.000000], [0.000000, 0.836057, 0.000000, 0.000000, 0.000000, -0.711035, 0.000000, 0.000000], [0.000000, -0.816522, 0.000000, 0.000000, 0.000000, 0.734998, 0.000000, 0.000000], [0.000000, -0.899790, 0.000000, 0.000000, 0.000000, -0.238946, 0.000000, 0.000000], [0.000000, 0.851730, 0.000000, 0.000000, 0.000000, 0.334703, 0.000000, 0.000000], [0.000000, -0.998406, 0.000000, 0.000000, 0.000000, 0.153147, 0.000000, 0.000000]]
pre_activation_mean: [0.732735, 0.540439, -0.175754, 1.505168, -1.590287, 1.712475, -0.679426]
pre_activation_std: [1.249637, 1.374218, 0.630772, 2.873723, 0.734776, 1.455123, 0.833197]
### 8
mean: [-2.562440]
std: [5.355392]
fourier: [[79.242330, 79.728050, 109.612946, 122.130789, 230.619563]]
input_correlations: [[0.850448, 0.910101, 0.795471, -0.926057, 0.000000, 0.498196, 0.000000, 0.000000]]
pre_activation_mean: [-2.562440]
pre_activation_std: [5.355392]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4461163580417633, "train_acc": 0.875, "val_loss": 0.47915855050086975, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3213310092687607, "train_acc": 0.91, "val_loss": 0.42206597328186035, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.2399187684059143, "train_acc": 0.915, "val_loss": 0.23980188369750977, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.18436436727643013, "train_acc": 0.96, "val_loss": 0.20916447043418884, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.19044353067874908, "train_acc": 0.96, "val_loss": 0.17375648021697998, "val_acc": 0.96}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.16663561016321182, "train_acc": 0.96, "val_loss": 0.17188610136508942, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.16184310615062714, "train_acc": 0.96, "val_loss": 0.09230934828519821, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.16721775010228157, "train_acc": 0.95, "val_loss": 0.058584064245224, "val_acc": 0.98}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.6842537522315979, "final_val_loss": 0.6306858658790588, "initial_val_acc": 0.8, "final_val_acc": 0.72, "best_val_acc": 0.72}, "improved_stage": {"initial_val_loss": 0.6461617350578308, "final_val_loss": 0.058584064245224, "initial_val_acc": 0.76, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 11}, "improvement": 0.26, "first_improvement_epoch": 1}} |
24 | {"target_pattern": "has_majority", "degraded_accuracy": 0.54, "improved_accuracy": 0.8, "improvement": 0.26, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5499, "learning_rate": 0.07940362044088127, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.468186, 2.169869, 0.990098]
std: [0.000000, 0.000000, 0.000000, 0.358274, 3.134896, 1.454068]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.639117, 5.998701, 6.432059, 7.712766, 42.136775], [53.533655, 54.553652, 56.023378, 56.742169, 195.288195], [24.773938, 25.355206, 26.120810, 26.350260, 89.108863]]
input_correlations: [[-0.285741, -0.917163, -0.060992, -0.648442, -0.095284, 0.000000, 0.000000, 0.000000], [-0.494374, -0.251171, -0.916209, 0.314107, -0.096722, 0.000000, 0.000000, 0.000000], [0.321313, -0.695313, 0.332961, -0.525975, 0.189787, 0.000000, 0.000000, 0.000000], [-0.148007, -0.558787, -0.150935, -0.207499, -0.784190, 0.000000, 0.000000, 0.000000], [0.536280, 0.534926, 0.504623, 0.731376, 0.403780, 0.000000, 0.000000, 0.000000], [0.019044, 0.040433, -0.909462, -0.083442, -0.042273, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.472855, -1.671970, -1.267360, -2.670210, 3.495058, -2.933038]
pre_activation_std: [2.196295, 2.538848, 2.557972, 3.375196, 2.436923, 3.128154]
### 2
mean: [-1.996307, 0.402051, -0.882154, -2.303492, -2.429380, 0.734423]
std: [1.232606, 1.556659, 0.896050, 1.171583, 1.406308, 1.258620]
fourier: [[20.215700, 20.347011, 20.977416, 24.553056, 179.667633], [22.778746, 24.970586, 29.167172, 30.568300, 36.184633], [13.173038, 13.806358, 15.972391, 17.902854, 79.393897], [18.251795, 18.275039, 22.052238, 24.155919, 207.314276], [20.980809, 23.624771, 25.658705, 27.440734, 218.644223], [19.936280, 20.361456, 20.401878, 22.180915, 66.098028]]
input_correlations: [[0.006715, -0.166937, -0.125312, -0.165671, -0.980600, 0.036176, 0.000000, 0.000000], [-0.430990, -0.137020, -0.507349, -0.418396, 0.647411, -0.217729, 0.000000, 0.000000], [-0.453157, -0.387324, -0.734644, -0.337009, 0.173003, -0.191007, 0.000000, 0.000000], [0.129974, -0.242567, 0.131141, -0.050742, -0.966738, 0.051945, 0.000000, 0.000000], [-0.125858, -0.056086, -0.466889, -0.044512, -0.916261, 0.018795, 0.000000, 0.000000], [-0.156410, -0.173574, 0.161140, -0.407761, 0.868228, -0.165674, 0.000000, 0.000000]]
pre_activation_mean: [-1.996307, 0.402051, -0.882154, -2.303492, -2.429380, 0.734423]
pre_activation_std: [1.232606, 1.556659, 0.896050, 1.171583, 1.406308, 1.258620]
### 4
mean: [-0.375895, 0.938786, 0.845890, 0.540977, 0.407372, -1.094206]
std: [0.290714, 1.455891, 1.344496, 1.138747, 0.618391, 0.523739]
fourier: [[4.872622, 5.026742, 5.331720, 5.474416, 33.830554], [24.565838, 24.955969, 25.353700, 26.368297, 84.490733], [22.533014, 23.134258, 23.872813, 25.343867, 76.130108], [19.193190, 19.531889, 19.818151, 20.830998, 48.687940], [10.365793, 10.631495, 10.922017, 11.634925, 36.663507], [8.788273, 8.841748, 8.921171, 9.591182, 98.478493]]
input_correlations: [[0.000000, -0.952854, -0.596856, 0.000000, 0.000000, -0.965111, 0.000000, 0.000000], [0.000000, 0.954825, 0.701856, 0.000000, 0.000000, 0.979813, 0.000000, 0.000000], [0.000000, 0.980418, 0.704557, 0.000000, 0.000000, 0.953936, 0.000000, 0.000000], [0.000000, 0.961951, 0.710666, 0.000000, 0.000000, 0.974369, 0.000000, 0.000000], [0.000000, 0.979661, 0.710492, 0.000000, 0.000000, 0.955058, 0.000000, 0.000000], [0.000000, -0.964684, -0.748287, 0.000000, 0.000000, -0.968055, 0.000000, 0.000000]]
pre_activation_mean: [-0.375895, 0.938786, 0.845890, 0.540977, 0.407372, -1.094206]
pre_activation_std: [0.290714, 1.455891, 1.344496, 1.138747, 0.618391, 0.523739]
### 6
mean: [-1.077282, -0.459792, -0.468484, 0.190014, 2.066675, 0.905012]
std: [0.559686, 0.251265, 0.042568, 0.867281, 3.207959, 1.514198]
fourier: [[9.539996, 9.805553, 9.922962, 10.363402, 96.955362], [4.214660, 4.244146, 4.464440, 4.636210, 41.381238], [0.643538, 0.658855, 0.717058, 0.815874, 42.163606], [14.870240, 15.135435, 15.294422, 15.744705, 17.101251], [55.029075, 56.140379, 56.488890, 58.510797, 186.000761], [26.040254, 26.453026, 26.675144, 27.809076, 81.451114]]
input_correlations: [[0.000000, -0.992040, -0.998846, -0.996516, -0.998385, 0.000000, 0.000000, 0.000000], [0.000000, -0.991487, -0.991893, -0.998821, -0.991392, 0.000000, 0.000000, 0.000000], [0.000000, -0.851598, -0.902503, -0.874570, -0.898691, 0.000000, 0.000000, 0.000000], [0.000000, -0.998847, -0.997792, -0.998466, -0.998075, 0.000000, 0.000000, 0.000000], [0.000000, 0.998282, 0.998474, 0.998280, 0.998673, 0.000000, 0.000000, 0.000000], [0.000000, 0.997723, 0.999144, 0.997198, 0.999339, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.077282, -0.459792, -0.468484, 0.190014, 2.066675, 0.905012]
pre_activation_std: [0.559686, 0.251265, 0.042568, 0.867281, 3.207959, 1.514198]
### 8
mean: [-0.615904]
std: [2.596285]
fourier: [[45.461867, 45.520612, 47.260544, 47.347112, 55.431337]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.855921, -0.997653, -0.996917, 0.000000, 0.000000]]
pre_activation_mean: [-0.615904]
pre_activation_std: [2.596285]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.8.weight": [
[
0.163017,
-0.23299,
0.23728,
0.885476,
-0.578142,
-0.356371
]
],
"network.8.bias": [
0.576862
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.468186, 2.169869, 0.990098]
std: [0.000000, 0.000000, 0.000000, 0.358274, 3.134896, 1.454068]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.639117, 5.998701, 6.432059, 7.712766, 42.136775], [53.533655, 54.553652, 56.023378, 56.742169, 195.288195], [24.773938, 25.355206, 26.120810, 26.350260, 89.108863]]
input_correlations: [[-0.285741, -0.917163, -0.060992, -0.648442, -0.095284, 0.000000, 0.000000, 0.000000], [-0.494374, -0.251171, -0.916209, 0.314107, -0.096722, 0.000000, 0.000000, 0.000000], [0.321313, -0.695313, 0.332961, -0.525975, 0.189787, 0.000000, 0.000000, 0.000000], [-0.148007, -0.558787, -0.150935, -0.207499, -0.784190, 0.000000, 0.000000, 0.000000], [0.536280, 0.534926, 0.504623, 0.731376, 0.403780, 0.000000, 0.000000, 0.000000], [0.019044, 0.040433, -0.909462, -0.083442, -0.042273, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.472855, -1.671970, -1.267360, -2.670210, 3.495058, -2.933038]
pre_activation_std: [2.196295, 2.538848, 2.557972, 3.375196, 2.436923, 3.128154]
### 2
mean: [-1.996307, 0.402051, -0.882154, -2.303492, -2.429380, 0.734423]
std: [1.232606, 1.556659, 0.896050, 1.171583, 1.406308, 1.258620]
fourier: [[20.215700, 20.347011, 20.977416, 24.553056, 179.667633], [22.778746, 24.970586, 29.167172, 30.568300, 36.184633], [13.173038, 13.806358, 15.972391, 17.902854, 79.393897], [18.251795, 18.275039, 22.052238, 24.155919, 207.314276], [20.980809, 23.624771, 25.658705, 27.440734, 218.644223], [19.936280, 20.361456, 20.401878, 22.180915, 66.098028]]
input_correlations: [[0.006715, -0.166937, -0.125312, -0.165671, -0.980600, 0.036176, 0.000000, 0.000000], [-0.430990, -0.137020, -0.507349, -0.418396, 0.647411, -0.217729, 0.000000, 0.000000], [-0.453157, -0.387324, -0.734644, -0.337009, 0.173003, -0.191007, 0.000000, 0.000000], [0.129974, -0.242567, 0.131141, -0.050742, -0.966738, 0.051945, 0.000000, 0.000000], [-0.125858, -0.056086, -0.466889, -0.044512, -0.916261, 0.018795, 0.000000, 0.000000], [-0.156410, -0.173574, 0.161140, -0.407761, 0.868228, -0.165674, 0.000000, 0.000000]]
pre_activation_mean: [-1.996307, 0.402051, -0.882154, -2.303492, -2.429380, 0.734423]
pre_activation_std: [1.232606, 1.556659, 0.896050, 1.171583, 1.406308, 1.258620]
### 4
mean: [-0.375895, 0.938786, 0.845890, 0.540977, 0.407372, -1.094206]
std: [0.290714, 1.455891, 1.344496, 1.138747, 0.618391, 0.523739]
fourier: [[4.872622, 5.026742, 5.331720, 5.474416, 33.830554], [24.565838, 24.955969, 25.353700, 26.368297, 84.490733], [22.533014, 23.134258, 23.872813, 25.343867, 76.130108], [19.193190, 19.531889, 19.818151, 20.830998, 48.687940], [10.365793, 10.631495, 10.922017, 11.634925, 36.663507], [8.788273, 8.841748, 8.921171, 9.591182, 98.478493]]
input_correlations: [[0.000000, -0.952854, -0.596856, 0.000000, 0.000000, -0.965111, 0.000000, 0.000000], [0.000000, 0.954825, 0.701856, 0.000000, 0.000000, 0.979813, 0.000000, 0.000000], [0.000000, 0.980418, 0.704557, 0.000000, 0.000000, 0.953936, 0.000000, 0.000000], [0.000000, 0.961951, 0.710666, 0.000000, 0.000000, 0.974369, 0.000000, 0.000000], [0.000000, 0.979661, 0.710492, 0.000000, 0.000000, 0.955058, 0.000000, 0.000000], [0.000000, -0.964684, -0.748287, 0.000000, 0.000000, -0.968055, 0.000000, 0.000000]]
pre_activation_mean: [-0.375895, 0.938786, 0.845890, 0.540977, 0.407372, -1.094206]
pre_activation_std: [0.290714, 1.455891, 1.344496, 1.138747, 0.618391, 0.523739]
### 6
mean: [-1.077282, -0.459792, -0.468484, 0.190014, 2.066675, 0.905012]
std: [0.559686, 0.251265, 0.042568, 0.867281, 3.207959, 1.514198]
fourier: [[9.539996, 9.805553, 9.922962, 10.363402, 96.955362], [4.214660, 4.244146, 4.464440, 4.636210, 41.381238], [0.643538, 0.658855, 0.717058, 0.815874, 42.163606], [14.870240, 15.135435, 15.294422, 15.744705, 17.101251], [55.029075, 56.140379, 56.488890, 58.510797, 186.000761], [26.040254, 26.453026, 26.675144, 27.809076, 81.451114]]
input_correlations: [[0.000000, -0.992040, -0.998846, -0.996516, -0.998385, 0.000000, 0.000000, 0.000000], [0.000000, -0.991487, -0.991893, -0.998821, -0.991392, 0.000000, 0.000000, 0.000000], [0.000000, -0.851598, -0.902503, -0.874570, -0.898691, 0.000000, 0.000000, 0.000000], [0.000000, -0.998847, -0.997792, -0.998466, -0.998075, 0.000000, 0.000000, 0.000000], [0.000000, 0.998282, 0.998474, 0.998280, 0.998673, 0.000000, 0.000000, 0.000000], [0.000000, 0.997723, 0.999144, 0.997198, 0.999339, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.077282, -0.459792, -0.468484, 0.190014, 2.066675, 0.905012]
pre_activation_std: [0.559686, 0.251265, 0.042568, 0.867281, 3.207959, 1.514198]
### 8
mean: [-0.615904]
std: [2.596285]
fourier: [[45.461867, 45.520612, 47.260544, 47.347112, 55.431337]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.855921, -0.997653, -0.996917, 0.000000, 0.000000]]
pre_activation_mean: [-0.615904]
pre_activation_std: [2.596285]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"std": 0.3582738935947418, "fourier": [5.639117032263295, 5.998701280037404, 6.432058796887937, 7.712766482963257, 42.1367749273777], "input_correlations": [-0.14800671108806515, -0.5587873401397102, -0.15093530775223232, -0.20749881724463795, -0.7841902860325385, 0.0, 0.0, 0.0], "pre_activation_mean": -2.670210361480713, "pre_activation_std": 3.3751959800720215}, "4": {"mean": 2.1698687076568604, "std": 3.1348958015441895, "fourier": [53.533654770638144, 54.55365223382725, 56.02337818682926, 56.74216929134459, 195.28819543123245], "input_correlations": [0.5362801637846268, 0.5349259711299256, 0.5046227664791297, 0.7313756081808795, 0.40377974816040835, 0.0, 0.0, 0.0], "pre_activation_mean": 3.4950575828552246, "pre_activation_std": 2.436923027038574}, "5": {"mean": 0.9900984764099121, "std": 1.454067587852478, "fourier": [24.773938339829698, 25.35520637597503, 26.120810145155442, 26.35025967734268, 89.10886293649673], "input_correlations": [0.019043729033844554, 0.04043259645959625, -0.9094620158979325, -0.08344207710417996, -0.042273490582178226, 0.0, 0.0, 0.0], "pre_activation_mean": -2.9330382347106934, "pre_activation_std": 3.1281535625457764}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -1.9963070154190063, "std": 1.2326058149337769, "fourier": [20.215699624230467, 20.347011096535056, 20.97741608849175, 24.553055956299612, 179.66763322800398], "input_correlations": [0.006715152412828881, -0.16693735637320503, -0.12531231838259868, -0.16567140780232695, -0.9805997146351778, 0.03617637451071655, 0.0, 0.0], "pre_activation_mean": -1.9963070154190063, "pre_activation_std": 1.2326058149337769}, "1": {"mean": 0.4020514488220215, "std": 1.5566589832305908, "fourier": [22.778745789010873, 24.970586289516238, 29.167172020937812, 30.56829958351692, 36.184633016586304], "input_correlations": 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"pre_activation_mean", "pre_activation_std"]}}, "8": {"neuron_profiles": {"0": {"mean": -0.6159037351608276, "std": 2.5962846279144287, "fourier": [45.46186698914356, 45.52061156196892, 47.26054429076354, 47.34711240212773, 55.43133682012558], "input_correlations": [0.0, 0.0, 0.0, 0.8559208184437924, -0.9976533391520032, -0.9969166546035173, 0.0, 0.0], "pre_activation_mean": -0.6159037351608276, "pre_activation_std": 2.5962846279144287}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.083756, -0.952047, 0.177832, -0.400986, -0.069738], [-0.22955, -0.157239, -1.112819, 0.415239, 0.093193], [0.588526, -1.180733, 0.478569, -0.289284, 0.086212], [0.358343, -1.303998, 0.217256, 0.270361, -1.60255], [0.488923, 0.137818, 0.390617, 0.803498, 0.211819], [0.361212, 0.435449, -1.732725, -0.256425, 0.291723]], "network.0.bias": [-0.059353, 0.219378, -0.333842, 0.202907, -0.164771, -0.366462], "network.2.weight": [[0.006717, -0.184306, -0.054825, -0.403467, -0.495624, 0.009871], [-0.457843, -0.710361, -0.786926, -1.093564, 0.45382, -0.84219], [-0.303977, -0.821687, -0.651957, -0.429193, 0.102138, -0.350974], [-0.156461, -0.251286, 0.209835, -0.144991, -0.472247, 0.137946], [-0.1785, -0.126618, -0.496147, -0.021927, -0.514451, -0.077307], [-0.209078, -0.431262, 0.108352, -1.012281, 0.453339, -0.440304]], "network.2.bias": [-0.089918, -0.291357, -0.566729, -0.628112, -0.363413, -0.481884], "network.4.weight": [[-0.17908, -0.150576, 0.630694, 0.13939, 0.407088, -0.163752], [0.027199, 0.544428, 0.127085, -0.007538, -0.119118, 0.846154], [0.261319, 0.766188, -0.079267, -0.594746, -0.011656, 0.520257], [-0.273304, 0.47225, 0.249437, -0.07082, -0.191332, 0.605371], [-0.003217, 0.344386, 0.048213, -0.211421, -0.343303, 0.242469], [0.10867, -0.214673, -0.549796, -0.177042, 0.222463, -0.253148]], "network.4.bias": [-0.115347, -0.292091, -0.259196, -0.410617, -0.099192, -0.672386], "network.6.weight": [[-0.251335, 0.219704, -0.249106, -0.367963, -0.280172, 0.549099], [0.355222, 0.106307, 0.004931, -0.392323, -0.001006, 0.153506], [0.35573, 0.152365, -0.0845, -0.05791, -0.135136, -0.300213], [0.303671, -0.265016, -0.181425, -0.213134, -0.088965, -0.04468], [-0.648835, 0.74469, 0.914541, 0.761157, 0.399516, -0.167712], [-0.390782, 0.371129, 0.67691, 0.089803, 0.080713, 0.52532]], "network.6.bias": [-0.69491, -0.302796, -0.448052, 0.820282, -0.259811, -0.208409], "network.8.weight": [[0.163017, -0.23299, 0.23728, 0.885476, -0.578142, -0.356371]], "network.8.bias": [0.576862]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6861990988254547, "train_acc": 0.57, "val_loss": 0.6828721761703491, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6736620664596558, "train_acc": 0.57, "val_loss": 0.6846058368682861, "val_acc": 0.54}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6557681560516357, "train_acc": 0.57, "val_loss": 0.6414837837219238, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6378332376480103, "train_acc": 0.49, "val_loss": 0.5882374048233032, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6013689935207367, "train_acc": 0.735, "val_loss": 0.5343259572982788, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.560236245393753, "train_acc": 0.755, "val_loss": 0.5067598223686218, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.55873903632164, "train_acc": 0.755, "val_loss": 0.5634090304374695, "val_acc": 0.72}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.5434384047985077, "train_acc": 0.74, "val_loss": 0.53261798620224, "val_acc": 0.74}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.5300597846508026, "train_acc": 0.745, "val_loss": 0.4327771067619324, "val_acc": 0.78}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.4706147611141205, "train_acc": 0.79, "val_loss": 0.5042104125022888, "val_acc": 0.76}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.4933207035064697, "train_acc": 0.77, "val_loss": 0.47041282057762146, "val_acc": 0.74}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4359677881002426, "train_acc": 0.78, "val_loss": 0.43859946727752686, "val_acc": 0.8}], "summary": {"total_epochs": 12, "degraded_epochs": 3, "improved_epochs": 9, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.6828721761703491, "final_val_loss": 0.6414837837219238, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.5882374048233032, "final_val_loss": 0.43859946727752686, "initial_val_acc": 0.76, "final_val_acc": 0.8, "best_val_acc": 0.8, "best_epoch": 11}, "improvement": 0.26, "first_improvement_epoch": 2}} |
25 | {"target_pattern": "ends_with", "degraded_accuracy": 0.4, "improved_accuracy": 1.0, "improvement": 0.6, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8389, "learning_rate": 0.07569666252355549, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.223583,
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0.006832,
1.967788
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0.019615,
0.039368,
1.656609
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[
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[
-1.667809,
0.061234,
0.123937,
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1.167533
],
[
1.275428,
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],
"network.0.bias": [
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0.52677,
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"network.2.weight": [
[
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1.248978,
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0.313131,
0.831755,
1.258474
],
[
1.255696,
1.03884,
0.168698,
0.531191,
1.303876
],
[
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0.053992,
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0.098996
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[
0.637979,
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1.325718
]
],
"network.2.bias": [
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"network.4.weight": [
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[
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1.078921,
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[
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[
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],
"network.4.bias": [
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"network.6.weight": [
[
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[
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[
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[
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[
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[
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[
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"network.8.bias": [
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"network.10.weight": [
[
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[
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[
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"network.12.weight": [
[
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],
"network.12.bias": [
1.378091
]
}
## Activation Signature
### 0
mean: [77.221115, 0.000000, 0.000000, 0.000000, 0.000000]
std: [99.835907, 0.000000, 0.000000, 0.000000, 0.000000]
fourier: [[1552.715829, 1618.063818, 1829.643976, 2322.377084, 6949.900396], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.276879, 0.011470, 0.190104, 0.138920, 0.993484, 0.000000, 0.000000, 0.000000], [-0.583001, -0.186292, -0.038778, 0.198929, 0.691220, 0.000000, 0.000000, 0.000000], [-0.695398, -0.547401, -0.651969, -0.470547, -0.483088, 0.000000, 0.000000, 0.000000], [-0.799550, -0.266136, -0.094848, 0.144328, 0.441885, 0.000000, 0.000000, 0.000000], [0.846158, 0.116958, 0.167847, -0.323186, 0.514133, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.159900, 1.173147, -2.934883, 0.258313, 0.327291]
pre_activation_std: [3.693129, 3.718606, 1.971968, 3.604100, 3.233760]
### 2
mean: [-2.897174, 7.221931, 7.263579, -1.054988, 5.689969]
std: [3.647510, 9.164009, 9.005231, 1.125356, 6.827069]
fourier: [[56.550064, 57.995400, 69.222713, 86.424164, 260.745673], [143.151243, 144.485068, 168.224325, 214.119102, 649.973857], [141.451716, 143.206155, 167.106062, 211.421854, 653.722148], [17.191041, 19.235356, 19.460174, 24.537602, 94.948954], [110.717313, 114.388298, 125.072550, 157.989404, 512.097261]]
input_correlations: [[-0.987607, -0.730702, 0.000000, -0.556369, -0.621391, 0.000000, 0.000000, 0.000000], [0.978462, 0.824747, 0.000000, 0.681526, 0.526396, 0.000000, 0.000000, 0.000000], [0.980944, 0.798551, 0.000000, 0.647062, 0.561435, 0.000000, 0.000000, 0.000000], [-0.925330, -0.950227, 0.000000, -0.842001, -0.167260, 0.000000, 0.000000, 0.000000], [0.965130, 0.794529, 0.000000, 0.652731, 0.578856, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.897174, 7.221931, 7.263579, -1.054988, 5.689969]
pre_activation_std: [3.647510, 9.164009, 9.005231, 1.125356, 6.827069]
### 4
mean: [15.252402, -4.780344, 21.125759, -6.107306, -14.441563]
std: [19.318441, 5.011116, 26.574789, 7.387639, 17.604126]
fourier: [[302.577023, 313.349701, 354.257783, 449.413112, 1372.716165], [79.945625, 82.594970, 92.074920, 116.375887, 430.230977], [414.210592, 426.918523, 488.555924, 619.853459, 1901.318291], [115.433691, 118.999592, 135.821860, 172.260656, 549.657507], [276.253103, 285.219144, 323.441235, 410.013377, 1299.740486]]
input_correlations: [[0.000000, 0.999493, 0.999421, 0.034385, 0.998790, 0.000000, 0.000000, 0.000000], [0.000000, -0.998245, -0.999128, -0.047497, -0.999629, 0.000000, 0.000000, 0.000000], [0.000000, 0.999650, 0.999677, 0.029188, 0.998227, 0.000000, 0.000000, 0.000000], [0.000000, -0.999566, -0.999681, -0.030852, -0.998417, 0.000000, 0.000000, 0.000000], [0.000000, -0.999398, -0.999596, -0.034389, -0.998785, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [15.252402, -4.780344, 21.125759, -6.107306, -14.441563]
pre_activation_std: [19.318441, 5.011116, 26.574789, 7.387639, 17.604126]
### 6
mean: [-5.501032, 30.703047, -11.087483, 34.452705, 25.948093]
std: [6.472201, 38.738052, 13.506381, 43.534065, 33.478161]
fourier: [[100.857034, 104.524032, 118.801492, 150.737336, 495.092865], [604.051871, 626.704321, 710.705935, 901.766306, 2763.274353], [210.510046, 218.231620, 247.883560, 314.519865, 997.873569], [678.491153, 703.326577, 799.010516, 1013.800515, 3100.743383], [521.768067, 540.868828, 614.446586, 779.622132, 2335.328264]]
input_correlations: [[-0.999968, 0.000000, -0.999992, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.999982, 0.000000, 0.999983, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999972, 0.000000, -0.999990, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.999971, 0.000000, 0.999990, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.999972, 0.000000, 0.999990, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.501032, 30.703047, -11.087483, 34.452705, 25.948093]
pre_activation_std: [6.472201, 38.738052, 13.506381, 43.534065, 33.478161]
### 8
mean: [62.175991, -3.724597, 51.191151, -27.766314, 54.776443]
std: [79.528229, 4.035651, 65.827797, 34.785343, 70.054558]
fourier: [[1238.538448, 1286.717749, 1458.705199, 1851.117603, 5595.839677], [63.019466, 64.863217, 74.223352, 94.132295, 335.213763], [1025.184786, 1065.016830, 1207.428805, 1532.239996, 4607.203523], [542.058243, 562.635816, 638.165087, 809.775004, 2498.968050], [1090.429424, 1133.901245, 1284.638761, 1630.350395, 4929.879743]]
input_correlations: [[0.000000, 0.999997, 0.000000, 0.999999, 0.999997, 0.000000, 0.000000, 0.000000], [0.000000, -0.999960, 0.000000, -0.999961, -0.999916, 0.000000, 0.000000, 0.000000], [0.000000, 0.999998, 0.000000, 0.999999, 0.999996, 0.000000, 0.000000, 0.000000], [0.000000, -1.000000, 0.000000, -1.000000, -0.999992, 0.000000, 0.000000, 0.000000], [0.000000, 0.999994, 0.000000, 0.999996, 0.999999, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [62.175991, -3.724597, 51.191151, -27.766314, 54.776443]
pre_activation_std: [79.528229, 4.035651, 65.827797, 34.785343, 70.054558]
### 10
mean: [77.157242, -64.820435, -68.175430, -133.062775, -61.821716]
std: [99.885536, 82.977669, 87.135094, 170.079834, 78.864204]
fourier: [[1554.646050, 1617.280237, 1831.432434, 2324.348481, 6944.151796], [1291.415543, 1343.640354, 1521.357962, 1930.840011, 5833.838840], [1356.305525, 1410.477094, 1597.814135, 2027.810821, 6135.789475], [2647.290499, 2753.534766, 3118.605331, 3957.914615, 11975.649555], [1227.538141, 1276.655070, 1446.119484, 1835.301411, 5563.953961]]
input_correlations: [[1.000000, 0.000000, 1.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [77.157242, -64.820435, -68.175430, -133.062775, -61.821716]
pre_activation_std: [99.885536, 82.977669, 87.135094, 170.079834, 78.864204]
### 12
mean: [-30.621937]
std: [41.371483]
fourier: [[643.437343, 670.517226, 758.194938, 962.380986, 2755.974367]]
input_correlations: [[-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-30.621937]
pre_activation_std: [41.371483]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.223583,
-0.034727,
-0.105963,
0.006832,
1.967788
],
[
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0.109061,
0.019615,
0.039368,
1.656609
],
[
-0.472872,
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-0.410154,
-0.375064,
-0.266371
],
[
-1.667809,
0.061234,
0.123937,
-0.001583,
1.167533
],
[
1.275428,
0.015994,
-0.303795,
-0.549817,
0.809871
]
],
"network.0.bias": [
-0.275301,
0.519867,
-0.033742,
0.52677,
-0.474249
],
"network.2.weight": [
[
-0.762374,
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],
[
1.248978,
0.967389,
0.313131,
0.831755,
1.258474
],
[
1.255696,
1.03884,
0.168698,
0.531191,
1.303876
],
[
-0.251139,
-0.097611,
0.053992,
-0.05545,
0.098996
],
[
0.637979,
0.920345,
0.064072,
0.667452,
1.325718
]
],
"network.2.bias": [
-0.089606,
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],
"network.4.weight": [
[
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],
[
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-0.440456
],
[
0.086373,
1.35896,
1.078921,
0.244411,
0.656075
],
[
0.235509,
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],
[
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]
],
"network.4.bias": [
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],
"network.6.weight": [
[
-0.111424,
0.075213,
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-0.183742,
-0.17011
],
[
0.98994,
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0.739555,
0.298669,
0.227524
],
[
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0.114212,
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],
[
0.827448,
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0.301965,
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],
[
0.63725,
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]
],
"network.6.bias": [
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],
"network.8.weight": [
[
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],
[
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0.253556
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[
0.125735,
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0.611664,
0.766121
],
[
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[
0.045097,
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1.450842
]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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[
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[
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[
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[
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],
"network.10.bias": [
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],
"network.12.weight": [
[
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0.19983,
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]
],
"network.12.bias": [
1.378091
]
}
## Activation Signature
### 0
mean: [77.221115, 0.000000, 0.000000, 0.000000, 0.000000]
std: [99.835907, 0.000000, 0.000000, 0.000000, 0.000000]
fourier: [[1552.715829, 1618.063818, 1829.643976, 2322.377084, 6949.900396], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.276879, 0.011470, 0.190104, 0.138920, 0.993484, 0.000000, 0.000000, 0.000000], [-0.583001, -0.186292, -0.038778, 0.198929, 0.691220, 0.000000, 0.000000, 0.000000], [-0.695398, -0.547401, -0.651969, -0.470547, -0.483088, 0.000000, 0.000000, 0.000000], [-0.799550, -0.266136, -0.094848, 0.144328, 0.441885, 0.000000, 0.000000, 0.000000], [0.846158, 0.116958, 0.167847, -0.323186, 0.514133, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.159900, 1.173147, -2.934883, 0.258313, 0.327291]
pre_activation_std: [3.693129, 3.718606, 1.971968, 3.604100, 3.233760]
### 2
mean: [-2.897174, 7.221931, 7.263579, -1.054988, 5.689969]
std: [3.647510, 9.164009, 9.005231, 1.125356, 6.827069]
fourier: [[56.550064, 57.995400, 69.222713, 86.424164, 260.745673], [143.151243, 144.485068, 168.224325, 214.119102, 649.973857], [141.451716, 143.206155, 167.106062, 211.421854, 653.722148], [17.191041, 19.235356, 19.460174, 24.537602, 94.948954], [110.717313, 114.388298, 125.072550, 157.989404, 512.097261]]
input_correlations: [[-0.987607, -0.730702, 0.000000, -0.556369, -0.621391, 0.000000, 0.000000, 0.000000], [0.978462, 0.824747, 0.000000, 0.681526, 0.526396, 0.000000, 0.000000, 0.000000], [0.980944, 0.798551, 0.000000, 0.647062, 0.561435, 0.000000, 0.000000, 0.000000], [-0.925330, -0.950227, 0.000000, -0.842001, -0.167260, 0.000000, 0.000000, 0.000000], [0.965130, 0.794529, 0.000000, 0.652731, 0.578856, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.897174, 7.221931, 7.263579, -1.054988, 5.689969]
pre_activation_std: [3.647510, 9.164009, 9.005231, 1.125356, 6.827069]
### 4
mean: [15.252402, -4.780344, 21.125759, -6.107306, -14.441563]
std: [19.318441, 5.011116, 26.574789, 7.387639, 17.604126]
fourier: [[302.577023, 313.349701, 354.257783, 449.413112, 1372.716165], [79.945625, 82.594970, 92.074920, 116.375887, 430.230977], [414.210592, 426.918523, 488.555924, 619.853459, 1901.318291], [115.433691, 118.999592, 135.821860, 172.260656, 549.657507], [276.253103, 285.219144, 323.441235, 410.013377, 1299.740486]]
input_correlations: [[0.000000, 0.999493, 0.999421, 0.034385, 0.998790, 0.000000, 0.000000, 0.000000], [0.000000, -0.998245, -0.999128, -0.047497, -0.999629, 0.000000, 0.000000, 0.000000], [0.000000, 0.999650, 0.999677, 0.029188, 0.998227, 0.000000, 0.000000, 0.000000], [0.000000, -0.999566, -0.999681, -0.030852, -0.998417, 0.000000, 0.000000, 0.000000], [0.000000, -0.999398, -0.999596, -0.034389, -0.998785, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [15.252402, -4.780344, 21.125759, -6.107306, -14.441563]
pre_activation_std: [19.318441, 5.011116, 26.574789, 7.387639, 17.604126]
### 6
mean: [-5.501032, 30.703047, -11.087483, 34.452705, 25.948093]
std: [6.472201, 38.738052, 13.506381, 43.534065, 33.478161]
fourier: [[100.857034, 104.524032, 118.801492, 150.737336, 495.092865], [604.051871, 626.704321, 710.705935, 901.766306, 2763.274353], [210.510046, 218.231620, 247.883560, 314.519865, 997.873569], [678.491153, 703.326577, 799.010516, 1013.800515, 3100.743383], [521.768067, 540.868828, 614.446586, 779.622132, 2335.328264]]
input_correlations: [[-0.999968, 0.000000, -0.999992, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.999982, 0.000000, 0.999983, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999972, 0.000000, -0.999990, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.999971, 0.000000, 0.999990, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.999972, 0.000000, 0.999990, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.501032, 30.703047, -11.087483, 34.452705, 25.948093]
pre_activation_std: [6.472201, 38.738052, 13.506381, 43.534065, 33.478161]
### 8
mean: [62.175991, -3.724597, 51.191151, -27.766314, 54.776443]
std: [79.528229, 4.035651, 65.827797, 34.785343, 70.054558]
fourier: [[1238.538448, 1286.717749, 1458.705199, 1851.117603, 5595.839677], [63.019466, 64.863217, 74.223352, 94.132295, 335.213763], [1025.184786, 1065.016830, 1207.428805, 1532.239996, 4607.203523], [542.058243, 562.635816, 638.165087, 809.775004, 2498.968050], [1090.429424, 1133.901245, 1284.638761, 1630.350395, 4929.879743]]
input_correlations: [[0.000000, 0.999997, 0.000000, 0.999999, 0.999997, 0.000000, 0.000000, 0.000000], [0.000000, -0.999960, 0.000000, -0.999961, -0.999916, 0.000000, 0.000000, 0.000000], [0.000000, 0.999998, 0.000000, 0.999999, 0.999996, 0.000000, 0.000000, 0.000000], [0.000000, -1.000000, 0.000000, -1.000000, -0.999992, 0.000000, 0.000000, 0.000000], [0.000000, 0.999994, 0.000000, 0.999996, 0.999999, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [62.175991, -3.724597, 51.191151, -27.766314, 54.776443]
pre_activation_std: [79.528229, 4.035651, 65.827797, 34.785343, 70.054558]
### 10
mean: [77.157242, -64.820435, -68.175430, -133.062775, -61.821716]
std: [99.885536, 82.977669, 87.135094, 170.079834, 78.864204]
fourier: [[1554.646050, 1617.280237, 1831.432434, 2324.348481, 6944.151796], [1291.415543, 1343.640354, 1521.357962, 1930.840011, 5833.838840], [1356.305525, 1410.477094, 1597.814135, 2027.810821, 6135.789475], [2647.290499, 2753.534766, 3118.605331, 3957.914615, 11975.649555], [1227.538141, 1276.655070, 1446.119484, 1835.301411, 5563.953961]]
input_correlations: [[1.000000, 0.000000, 1.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, -1.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [77.157242, -64.820435, -68.175430, -133.062775, -61.821716]
pre_activation_std: [99.885536, 82.977669, 87.135094, 170.079834, 78.864204]
### 12
mean: [-30.621937]
std: [41.371483]
fourier: [[643.437343, 670.517226, 758.194938, 962.380986, 2755.974367]]
input_correlations: [[-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-30.621937]
pre_activation_std: [41.371483]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 77.22111511230469, "std": 99.83590698242188, "fourier": [1552.7158287453774, 1618.0638184097597, 1829.6439755742608, 2322.3770840041443, 6949.9003964066505], "input_correlations": [0.2768785408606791, 0.011469945020226897, 0.19010375016318784, 0.1389202421747991, 0.9934841890172176, 0.0, 0.0, 0.0], "pre_activation_mean": 2.159900188446045, "pre_activation_std": 3.693129301071167}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.583000909796587, -0.18629221122728426, -0.038778088639154065, 0.19892905121013543, 0.6912196382106733, 0.0, 0.0, 0.0], "pre_activation_mean": 1.1731467247009277, "pre_activation_std": 3.7186062335968018}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.695398481785685, -0.5474007242421727, -0.6519692560084724, -0.4705466840782034, -0.48308793870962524, 0.0, 0.0, 0.0], "pre_activation_mean": 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0.6, "final_val_acc": 0.4, "best_val_acc": 0.4}, "improved_stage": {"initial_val_loss": 0.5191295146942139, "final_val_loss": 0.15040692687034607, "initial_val_acc": 0.68, "final_val_acc": 1.0, "best_val_acc": 1.0, "best_epoch": 14}, "improvement": 0.6, "first_improvement_epoch": 4}} |
26 | {"target_pattern": "ends_with", "degraded_accuracy": 0.54, "improved_accuracy": 0.98, "improvement": 0.43999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1137, "learning_rate": 0.048769761062395736, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [7.564322, 7.921072, 6.653328, 9.366821, 0.042748, 10.926017, -0.048814, 0.180851]
std: [9.720273, 9.560287, 8.475072, 11.505167, 0.251315, 13.477286, 0.061184, 0.354247]
fourier: [[159.108952, 166.699727, 169.748137, 178.283468, 680.789036], [154.854329, 159.629361, 165.883245, 179.635519, 712.896344], [139.559211, 142.762135, 147.828276, 156.662968, 598.799537], [189.658534, 190.328194, 200.354445, 214.868439, 843.013889], [3.733427, 3.768579, 3.847332, 3.886949, 4.128972], [220.392640, 223.423443, 234.367407, 252.671428, 983.341462], [0.931760, 0.933436, 1.176811, 1.203661, 4.393269], [4.893062, 5.040783, 6.914536, 6.914928, 16.276583]]
input_correlations: [[-0.511639, -0.022854, -0.036853, 0.222770, 0.725677, 0.000000, 0.000000, 0.000000], [0.862828, 0.388937, 0.270983, 0.094900, -0.289085, 0.000000, 0.000000, 0.000000], [0.978950, 0.511462, 0.344910, 0.002958, 0.200789, 0.000000, 0.000000, 0.000000], [-0.113912, -0.872713, -0.386727, -0.148557, -0.281910, 0.000000, 0.000000, 0.000000], [-0.379907, -0.220134, 0.031501, 0.296916, 0.825960, 0.000000, 0.000000, 0.000000], [-0.372757, -0.457048, -0.765717, -0.556293, 0.011814, 0.000000, 0.000000, 0.000000], [-0.823568, -0.190261, -0.307033, 0.006179, -0.701378, 0.000000, 0.000000, 0.000000], [-0.614029, 0.057743, 0.330229, 0.506793, 0.346662, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.837695, 1.419499, 1.715672, -1.017444, 1.474756, -2.998318, -1.807877, 1.419713]
pre_activation_std: [2.612841, 2.373825, 2.812192, 1.349346, 2.305959, 1.926530, 2.989904, 2.062700]
### 2
mean: [1.295611, 0.404260, 0.888538, -1.999664, 0.637733, -3.006356, 0.804172, -3.384560]
std: [3.519099, 2.459855, 1.853958, 2.449480, 2.716734, 3.327920, 3.994411, 3.001111]
fourier: [[53.304823, 56.339811, 61.406548, 72.435345, 116.604961], [41.569340, 42.284928, 43.420562, 47.263653, 50.097284], [31.363089, 32.889124, 32.992069, 37.351396, 79.968367], [43.138826, 43.341792, 43.747508, 45.814898, 179.969740], [41.240859, 41.502459, 47.183195, 57.395945, 59.509114], [53.630818, 58.756659, 60.206208, 62.289154, 270.572050], [65.284601, 66.056877, 69.131648, 72.375469, 83.046961], [45.669608, 55.295896, 55.733912, 56.685387, 304.610376]]
input_correlations: [[0.872019, -0.733528, -0.602395, -0.173365, 0.862894, 0.106419, -0.024492, 0.686640], [-0.442231, 0.887681, 0.928968, -0.058870, -0.392426, -0.003246, -0.278178, -0.648286], [0.858466, -0.704405, -0.586442, -0.252655, 0.824598, 0.155716, 0.056980, 0.801001], [-0.885792, 0.555653, 0.453276, 0.209317, -0.810508, -0.186696, -0.030571, -0.861525], [0.860774, -0.741835, -0.622914, -0.184672, 0.854442, 0.093944, -0.057104, 0.676634], [-0.910985, 0.519204, 0.380868, 0.262373, -0.901215, -0.206408, 0.053330, -0.843661], [0.754072, -0.846241, -0.751113, -0.144047, 0.748518, 0.046200, 0.084254, 0.692977], [-0.943017, 0.184553, 0.036883, 0.256786, -0.901897, -0.300580, 0.168147, -0.755731]]
pre_activation_mean: [1.295611, 0.404260, 0.888538, -1.999664, 0.637733, -3.006356, 0.804172, -3.384560]
pre_activation_std: [3.519099, 2.459855, 1.853958, 2.449480, 2.716734, 3.327920, 3.994411, 3.001111]
### 4
mean: [1.036820, -0.056655, 0.112945, 3.899045, -0.459182, 1.408930, 3.163588, -0.222037]
std: [1.047752, 1.416848, 1.250489, 4.131887, 1.738050, 3.597605, 6.482658, 1.283423]
fourier: [[18.051125, 19.401032, 21.024629, 23.485891, 93.313789], [19.439268, 20.032673, 24.828978, 24.874011, 36.058257], [20.770351, 20.771376, 23.076913, 23.322177, 27.527240], [67.720896, 70.131864, 72.099878, 76.560960, 350.914081], [29.063970, 30.761889, 32.831775, 41.326338, 43.235609], [54.270166, 56.519141, 66.692538, 88.623133, 126.803682], [96.245780, 104.910828, 120.745849, 155.249778, 284.722938], [20.271715, 20.790367, 23.054744, 24.099035, 32.810758]]
input_correlations: [[0.181318, 0.859802, 0.113356, 0.753279, 0.216666, 0.632063, 0.130931, 0.252054], [0.974194, -0.466575, 0.927142, -0.286815, 0.975094, -0.269009, 0.973524, 0.307833], [-0.509268, 0.963721, -0.565406, 0.744284, -0.474271, 0.655720, -0.558102, -0.097304], [0.942470, 0.000362, 0.906543, 0.114070, 0.950445, 0.065561, 0.925659, 0.476251], [-0.849208, 0.704259, -0.899027, 0.444277, -0.821213, 0.391419, -0.881668, -0.376038], [0.956405, -0.589305, 0.946826, -0.412863, 0.942816, -0.399640, 0.967258, 0.344622], [0.979965, -0.507473, 0.970096, -0.334725, 0.968314, -0.328638, 0.987421, 0.383292], [-0.851797, 0.742046, -0.884149, 0.501016, -0.829840, 0.455358, -0.883582, -0.320284]]
pre_activation_mean: [1.036820, -0.056655, 0.112945, 3.899045, -0.459182, 1.408930, 3.163588, -0.222037]
pre_activation_std: [1.047752, 1.416848, 1.250489, 4.131887, 1.738050, 3.597605, 6.482658, 1.283423]
### 6
mean: [-6.092327, 4.523307, 5.449987, 5.085294, -0.747929, -6.330705, -6.575425, 5.300847]
std: [5.310055, 5.453701, 6.616999, 6.209831, 2.571698, 6.228504, 7.000793, 6.102863]
fourier: [[85.470901, 89.488975, 92.235052, 101.318221, 548.309444], [86.997535, 90.796949, 95.087726, 104.198425, 407.097609], [112.425636, 116.255559, 116.702142, 123.333759, 490.498797], [101.503483, 104.082899, 108.934937, 116.463834, 457.676512], [42.746890, 46.245219, 49.368134, 66.578265, 67.313654], [107.730253, 108.335305, 109.082015, 117.399682, 569.763387], [119.258008, 121.061782, 122.981359, 136.360159, 591.788213], [100.832358, 106.664715, 107.178107, 111.700085, 477.076186]]
input_correlations: [[-0.516760, -0.936910, -0.027416, -0.998494, -0.031583, -0.929275, -0.926247, -0.033334], [0.519411, 0.947834, 0.027204, 0.998545, 0.036713, 0.931246, 0.927126, 0.037555], [0.393386, 0.971698, -0.113925, 0.993488, -0.102206, 0.973121, 0.970714, -0.103979], [0.487004, 0.958353, -0.010999, 0.998997, 0.000194, 0.944362, 0.940589, 0.000406], [0.465837, -0.684192, 0.839201, -0.541139, 0.828817, -0.784278, -0.793572, 0.838981], [-0.377018, -0.966717, 0.129945, -0.991673, 0.122567, -0.975374, -0.973840, 0.122979], [-0.361617, -0.974931, 0.148446, -0.989624, 0.140052, -0.980372, -0.978382, 0.139863], [0.458490, 0.962883, -0.043046, 0.998959, -0.034835, 0.954424, 0.951145, -0.033421]]
pre_activation_mean: [-6.092327, 4.523307, 5.449987, 5.085294, -0.747929, -6.330705, -6.575425, 5.300847]
pre_activation_std: [5.310055, 5.453701, 6.616999, 6.209831, 2.571698, 6.228504, 7.000793, 6.102863]
### 8
mean: [7.558488, 7.925493, 6.653025, 9.369130, -4.465115, 10.915012, -4.470729, -0.799321]
std: [9.729082, 9.560457, 8.480404, 11.506305, 6.440378, 13.489161, 4.940565, 2.072154]
fourier: [[159.485301, 166.167640, 170.125028, 179.518208, 680.263911], [154.588621, 159.760499, 166.168719, 180.562461, 713.294380], [139.789641, 142.300475, 148.069646, 157.731705, 598.772249], [189.437857, 190.529372, 200.649689, 215.792038, 843.221710], [105.949521, 111.992510, 112.707054, 117.774654, 401.860373], [220.078850, 224.184494, 234.882895, 254.071824, 982.351063], [84.811301, 84.969724, 86.971874, 95.331064, 402.365717], [32.274028, 35.152049, 35.780619, 39.839730, 71.938852]]
input_correlations: [[0.373036, 0.998189, 0.996502, 0.999667, 0.023857, 0.363820, 0.377328, 0.999872], [0.387632, 0.999649, 0.992393, 0.999519, 0.064685, 0.377734, 0.391411, 0.998532], [0.377851, 0.998922, 0.995177, 0.999848, 0.038340, 0.368305, 0.381787, 0.999608], [0.378916, 0.999516, 0.993558, 0.999857, 0.053645, 0.369031, 0.382568, 0.999065], [-0.372923, -0.996924, -0.997716, -0.999141, -0.006125, -0.364039, -0.377243, -0.999916], [0.380274, 0.999636, 0.993044, 0.999748, 0.059028, 0.370358, 0.384025, 0.998795], [-0.335869, -0.985788, -0.999392, -0.991502, 0.085599, -0.328697, -0.341839, -0.995036], [-0.409018, -0.999156, -0.986616, -0.997719, -0.101255, -0.398485, -0.411606, -0.995654]]
pre_activation_mean: [7.558488, 7.925493, 6.653025, 9.369130, -4.465115, 10.915012, -4.470729, -0.799321]
pre_activation_std: [9.729082, 9.560457, 8.480404, 11.506305, 6.440378, 13.489161, 4.940565, 2.072154]
### 10
mean: [-19.950644]
std: [26.188307]
fourier: [[429.645089, 436.564414, 455.200506, 489.221268, 1795.558092]]
input_correlations: [[-0.999426, -0.999927, -0.999773, -0.999935, 0.186448, -0.999917, -0.577036, 0.481645]]
pre_activation_mean: [-19.950644]
pre_activation_std: [26.188307]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.06732
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[
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[
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[
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]
],
"network.0.bias": [
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0.298004,
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-0.354696,
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"network.2.weight": [
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[
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## Activation Signature
### 0
mean: [7.564322, 7.921072, 6.653328, 9.366821, 0.042748, 10.926017, -0.048814, 0.180851]
std: [9.720273, 9.560287, 8.475072, 11.505167, 0.251315, 13.477286, 0.061184, 0.354247]
fourier: [[159.108952, 166.699727, 169.748137, 178.283468, 680.789036], [154.854329, 159.629361, 165.883245, 179.635519, 712.896344], [139.559211, 142.762135, 147.828276, 156.662968, 598.799537], [189.658534, 190.328194, 200.354445, 214.868439, 843.013889], [3.733427, 3.768579, 3.847332, 3.886949, 4.128972], [220.392640, 223.423443, 234.367407, 252.671428, 983.341462], [0.931760, 0.933436, 1.176811, 1.203661, 4.393269], [4.893062, 5.040783, 6.914536, 6.914928, 16.276583]]
input_correlations: [[-0.511639, -0.022854, -0.036853, 0.222770, 0.725677, 0.000000, 0.000000, 0.000000], [0.862828, 0.388937, 0.270983, 0.094900, -0.289085, 0.000000, 0.000000, 0.000000], [0.978950, 0.511462, 0.344910, 0.002958, 0.200789, 0.000000, 0.000000, 0.000000], [-0.113912, -0.872713, -0.386727, -0.148557, -0.281910, 0.000000, 0.000000, 0.000000], [-0.379907, -0.220134, 0.031501, 0.296916, 0.825960, 0.000000, 0.000000, 0.000000], [-0.372757, -0.457048, -0.765717, -0.556293, 0.011814, 0.000000, 0.000000, 0.000000], [-0.823568, -0.190261, -0.307033, 0.006179, -0.701378, 0.000000, 0.000000, 0.000000], [-0.614029, 0.057743, 0.330229, 0.506793, 0.346662, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.837695, 1.419499, 1.715672, -1.017444, 1.474756, -2.998318, -1.807877, 1.419713]
pre_activation_std: [2.612841, 2.373825, 2.812192, 1.349346, 2.305959, 1.926530, 2.989904, 2.062700]
### 2
mean: [1.295611, 0.404260, 0.888538, -1.999664, 0.637733, -3.006356, 0.804172, -3.384560]
std: [3.519099, 2.459855, 1.853958, 2.449480, 2.716734, 3.327920, 3.994411, 3.001111]
fourier: [[53.304823, 56.339811, 61.406548, 72.435345, 116.604961], [41.569340, 42.284928, 43.420562, 47.263653, 50.097284], [31.363089, 32.889124, 32.992069, 37.351396, 79.968367], [43.138826, 43.341792, 43.747508, 45.814898, 179.969740], [41.240859, 41.502459, 47.183195, 57.395945, 59.509114], [53.630818, 58.756659, 60.206208, 62.289154, 270.572050], [65.284601, 66.056877, 69.131648, 72.375469, 83.046961], [45.669608, 55.295896, 55.733912, 56.685387, 304.610376]]
input_correlations: [[0.872019, -0.733528, -0.602395, -0.173365, 0.862894, 0.106419, -0.024492, 0.686640], [-0.442231, 0.887681, 0.928968, -0.058870, -0.392426, -0.003246, -0.278178, -0.648286], [0.858466, -0.704405, -0.586442, -0.252655, 0.824598, 0.155716, 0.056980, 0.801001], [-0.885792, 0.555653, 0.453276, 0.209317, -0.810508, -0.186696, -0.030571, -0.861525], [0.860774, -0.741835, -0.622914, -0.184672, 0.854442, 0.093944, -0.057104, 0.676634], [-0.910985, 0.519204, 0.380868, 0.262373, -0.901215, -0.206408, 0.053330, -0.843661], [0.754072, -0.846241, -0.751113, -0.144047, 0.748518, 0.046200, 0.084254, 0.692977], [-0.943017, 0.184553, 0.036883, 0.256786, -0.901897, -0.300580, 0.168147, -0.755731]]
pre_activation_mean: [1.295611, 0.404260, 0.888538, -1.999664, 0.637733, -3.006356, 0.804172, -3.384560]
pre_activation_std: [3.519099, 2.459855, 1.853958, 2.449480, 2.716734, 3.327920, 3.994411, 3.001111]
### 4
mean: [1.036820, -0.056655, 0.112945, 3.899045, -0.459182, 1.408930, 3.163588, -0.222037]
std: [1.047752, 1.416848, 1.250489, 4.131887, 1.738050, 3.597605, 6.482658, 1.283423]
fourier: [[18.051125, 19.401032, 21.024629, 23.485891, 93.313789], [19.439268, 20.032673, 24.828978, 24.874011, 36.058257], [20.770351, 20.771376, 23.076913, 23.322177, 27.527240], [67.720896, 70.131864, 72.099878, 76.560960, 350.914081], [29.063970, 30.761889, 32.831775, 41.326338, 43.235609], [54.270166, 56.519141, 66.692538, 88.623133, 126.803682], [96.245780, 104.910828, 120.745849, 155.249778, 284.722938], [20.271715, 20.790367, 23.054744, 24.099035, 32.810758]]
input_correlations: [[0.181318, 0.859802, 0.113356, 0.753279, 0.216666, 0.632063, 0.130931, 0.252054], [0.974194, -0.466575, 0.927142, -0.286815, 0.975094, -0.269009, 0.973524, 0.307833], [-0.509268, 0.963721, -0.565406, 0.744284, -0.474271, 0.655720, -0.558102, -0.097304], [0.942470, 0.000362, 0.906543, 0.114070, 0.950445, 0.065561, 0.925659, 0.476251], [-0.849208, 0.704259, -0.899027, 0.444277, -0.821213, 0.391419, -0.881668, -0.376038], [0.956405, -0.589305, 0.946826, -0.412863, 0.942816, -0.399640, 0.967258, 0.344622], [0.979965, -0.507473, 0.970096, -0.334725, 0.968314, -0.328638, 0.987421, 0.383292], [-0.851797, 0.742046, -0.884149, 0.501016, -0.829840, 0.455358, -0.883582, -0.320284]]
pre_activation_mean: [1.036820, -0.056655, 0.112945, 3.899045, -0.459182, 1.408930, 3.163588, -0.222037]
pre_activation_std: [1.047752, 1.416848, 1.250489, 4.131887, 1.738050, 3.597605, 6.482658, 1.283423]
### 6
mean: [-6.092327, 4.523307, 5.449987, 5.085294, -0.747929, -6.330705, -6.575425, 5.300847]
std: [5.310055, 5.453701, 6.616999, 6.209831, 2.571698, 6.228504, 7.000793, 6.102863]
fourier: [[85.470901, 89.488975, 92.235052, 101.318221, 548.309444], [86.997535, 90.796949, 95.087726, 104.198425, 407.097609], [112.425636, 116.255559, 116.702142, 123.333759, 490.498797], [101.503483, 104.082899, 108.934937, 116.463834, 457.676512], [42.746890, 46.245219, 49.368134, 66.578265, 67.313654], [107.730253, 108.335305, 109.082015, 117.399682, 569.763387], [119.258008, 121.061782, 122.981359, 136.360159, 591.788213], [100.832358, 106.664715, 107.178107, 111.700085, 477.076186]]
input_correlations: [[-0.516760, -0.936910, -0.027416, -0.998494, -0.031583, -0.929275, -0.926247, -0.033334], [0.519411, 0.947834, 0.027204, 0.998545, 0.036713, 0.931246, 0.927126, 0.037555], [0.393386, 0.971698, -0.113925, 0.993488, -0.102206, 0.973121, 0.970714, -0.103979], [0.487004, 0.958353, -0.010999, 0.998997, 0.000194, 0.944362, 0.940589, 0.000406], [0.465837, -0.684192, 0.839201, -0.541139, 0.828817, -0.784278, -0.793572, 0.838981], [-0.377018, -0.966717, 0.129945, -0.991673, 0.122567, -0.975374, -0.973840, 0.122979], [-0.361617, -0.974931, 0.148446, -0.989624, 0.140052, -0.980372, -0.978382, 0.139863], [0.458490, 0.962883, -0.043046, 0.998959, -0.034835, 0.954424, 0.951145, -0.033421]]
pre_activation_mean: [-6.092327, 4.523307, 5.449987, 5.085294, -0.747929, -6.330705, -6.575425, 5.300847]
pre_activation_std: [5.310055, 5.453701, 6.616999, 6.209831, 2.571698, 6.228504, 7.000793, 6.102863]
### 8
mean: [7.558488, 7.925493, 6.653025, 9.369130, -4.465115, 10.915012, -4.470729, -0.799321]
std: [9.729082, 9.560457, 8.480404, 11.506305, 6.440378, 13.489161, 4.940565, 2.072154]
fourier: [[159.485301, 166.167640, 170.125028, 179.518208, 680.263911], [154.588621, 159.760499, 166.168719, 180.562461, 713.294380], [139.789641, 142.300475, 148.069646, 157.731705, 598.772249], [189.437857, 190.529372, 200.649689, 215.792038, 843.221710], [105.949521, 111.992510, 112.707054, 117.774654, 401.860373], [220.078850, 224.184494, 234.882895, 254.071824, 982.351063], [84.811301, 84.969724, 86.971874, 95.331064, 402.365717], [32.274028, 35.152049, 35.780619, 39.839730, 71.938852]]
input_correlations: [[0.373036, 0.998189, 0.996502, 0.999667, 0.023857, 0.363820, 0.377328, 0.999872], [0.387632, 0.999649, 0.992393, 0.999519, 0.064685, 0.377734, 0.391411, 0.998532], [0.377851, 0.998922, 0.995177, 0.999848, 0.038340, 0.368305, 0.381787, 0.999608], [0.378916, 0.999516, 0.993558, 0.999857, 0.053645, 0.369031, 0.382568, 0.999065], [-0.372923, -0.996924, -0.997716, -0.999141, -0.006125, -0.364039, -0.377243, -0.999916], [0.380274, 0.999636, 0.993044, 0.999748, 0.059028, 0.370358, 0.384025, 0.998795], [-0.335869, -0.985788, -0.999392, -0.991502, 0.085599, -0.328697, -0.341839, -0.995036], [-0.409018, -0.999156, -0.986616, -0.997719, -0.101255, -0.398485, -0.411606, -0.995654]]
pre_activation_mean: [7.558488, 7.925493, 6.653025, 9.369130, -4.465115, 10.915012, -4.470729, -0.799321]
pre_activation_std: [9.729082, 9.560457, 8.480404, 11.506305, 6.440378, 13.489161, 4.940565, 2.072154]
### 10
mean: [-19.950644]
std: [26.188307]
fourier: [[429.645089, 436.564414, 455.200506, 489.221268, 1795.558092]]
input_correlations: [[-0.999426, -0.999927, -0.999773, -0.999935, 0.186448, -0.999917, -0.577036, 0.481645]]
pre_activation_mean: [-19.950644]
pre_activation_std: [26.188307]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.98, "best_epoch": 11}, "improvement": 0.43999999999999995, "first_improvement_epoch": 1}} |
27 | {"target_pattern": "starts_with", "degraded_accuracy": 0.48, "improved_accuracy": 0.84, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3187, "learning_rate": 0.06433198685419476, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.054627,
-0.696599,
-0.010968,
0.068896,
-0.287908,
0.370307,
-0.140162
],
[
0.492978,
0.018596,
-0.091553,
-0.375893,
-0.507634,
0.541127,
-0.474424,
-0.59358
],
[
-0.140134,
-0.141177,
0.277192,
-0.396465,
-0.434465,
0.382228,
-0.53186,
-0.058268
],
[
0.480934,
-0.111951,
-0.096505,
-0.119086,
-0.285447,
0.15651,
-0.650963,
-0.125602
],
[
-0.369676,
-0.535136,
0.056521,
-0.121333,
-0.493576,
0.177191,
-0.375667,
-0.39125
],
[
-0.199612,
-0.118799,
0.643893,
-0.511098,
0.058062,
0.263343,
-0.44484,
-0.163506
],
[
-0.080925,
-0.143169,
0.07789,
0.058582,
-0.464155,
0.558754,
-0.971812,
-0.230008
],
[
-0.246673,
0.231096,
-0.206655,
-0.08715,
-0.040285,
-0.400524,
0.565328,
0.072259
]
],
"network.10.bias": [
0.126417,
0.042002,
0.06485,
-0.236192,
-0.311527,
-0.230279,
0.217997,
0.55284
],
"network.12.weight": [
[
0.301437,
-0.376952,
-0.247059,
-0.136513,
-0.114223,
-0.11763,
-0.307001,
0.354071
]
],
"network.12.bias": [
0.12887
]
}
## Activation Signature
### 0
mean: [0.215954, 7.432114, 3.117535, 3.418265, -0.057115, 1.470956, 5.232719, 0.389952]
std: [0.343606, 10.837177, 4.425539, 5.359272, 0.097953, 2.312080, 7.291938, 0.581609]
fourier: [[5.632762, 5.641179, 6.269030, 6.782681, 19.435891], [189.590554, 191.115100, 197.118085, 209.922072, 668.890235], [75.919762, 76.814631, 81.974463, 86.201277, 280.578158], [94.329171, 95.769362, 96.903654, 103.362694, 307.643904], [1.592650, 1.653634, 1.817424, 2.040022, 5.140377], [40.679615, 40.894679, 42.430107, 45.040493, 132.386020], [125.665660, 126.760012, 134.852049, 142.005926, 470.944776], [9.481967, 9.646700, 10.644129, 11.109236, 35.095706]]
input_correlations: [[0.958039, 0.281302, 0.346877, 0.025103, -0.045650, 0.000000, 0.000000, 0.000000], [0.790731, 0.344139, 0.009909, -0.493015, -0.132197, 0.000000, 0.000000, 0.000000], [0.850813, 0.523807, 0.276913, -0.001089, -0.308122, 0.000000, 0.000000, 0.000000], [-0.888305, -0.705921, -0.468490, -0.107333, -0.134760, 0.000000, 0.000000, 0.000000], [0.864439, 0.462832, 0.325946, -0.015594, -0.297154, 0.000000, 0.000000, 0.000000], [0.250360, -0.073976, -0.160979, -0.472302, -0.842787, 0.000000, 0.000000, 0.000000], [-0.683744, 0.101106, 0.133903, 0.311601, 0.441795, 0.000000, 0.000000, 0.000000], [0.634565, -0.448674, -0.114370, -0.156151, 0.313128, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.506036, 0.285550, 1.785898, -3.037421, 1.641467, -1.636361, 0.512522, -0.904265]
pre_activation_std: [2.781304, 2.329023, 3.334571, 2.605216, 3.057416, 1.745090, 1.225155, 2.540174]
### 2
mean: [-0.520396, 1.958222, 3.375695, 3.263932, -3.700711, -2.086423, -1.410498, 2.191620]
std: [1.180953, 2.762756, 5.115029, 4.405910, 5.753523, 2.217773, 3.112308, 3.209847]
fourier: [[19.338163, 19.374827, 20.330971, 22.846137, 46.835652], [46.933569, 47.130232, 52.342359, 55.782547, 176.239970], [89.059293, 91.779626, 93.685926, 98.153189, 303.812544], [77.220505, 78.827003, 79.611058, 81.049864, 293.753842], [97.954136, 101.041541, 106.323678, 110.120577, 333.064058], [39.453774, 40.161746, 41.267297, 42.908806, 187.778048], [52.721859, 53.961585, 54.946500, 58.422595, 126.944869], [56.234562, 57.657887, 58.314817, 61.948985, 197.245803]]
input_correlations: [[0.552456, 0.377488, 0.287281, 0.149541, 0.339990, 0.235599, -0.586985, 0.878362], [0.978175, 0.854633, 0.919527, 0.596406, 0.941060, 0.503102, -0.470063, 0.749904], [0.969088, 0.931597, 0.959254, 0.601508, 0.970034, 0.569432, -0.448911, 0.700524], [0.951090, 0.943429, 0.978321, 0.619140, 0.982361, 0.582697, -0.403657, 0.644668], [-0.976901, -0.921762, -0.978962, -0.596573, -0.990155, -0.566058, 0.450909, -0.614337], [-0.952775, -0.867754, -0.942510, -0.677114, -0.955228, -0.617718, 0.249196, -0.702041], [-0.954474, -0.931801, -0.984646, -0.607068, -0.989348, -0.556663, 0.457179, -0.612628], [0.960999, 0.919427, 0.950452, 0.630856, 0.961220, 0.573690, -0.386174, 0.727461]]
pre_activation_mean: [-0.520396, 1.958222, 3.375695, 3.263932, -3.700711, -2.086423, -1.410498, 2.191620]
pre_activation_std: [1.180953, 2.762756, 5.115029, 4.405910, 5.753523, 2.217773, 3.112308, 3.209847]
### 4
mean: [4.684528, -1.739546, 4.116791, -2.736769, -2.797587, -2.443154, -2.382305, 4.471087]
std: [6.578455, 3.388366, 6.398107, 4.850799, 4.658975, 2.826393, 3.891548, 6.976417]
fourier: [[111.492751, 113.371363, 121.947583, 125.678599, 421.607543], [57.193825, 57.864484, 61.570478, 66.933095, 156.559146], [109.735992, 111.985405, 116.867922, 123.759076, 370.511238], [83.885686, 86.103028, 87.490729, 95.586230, 246.309223], [81.552818, 82.959742, 85.353998, 89.330888, 251.782835], [50.849539, 52.035967, 52.532396, 55.435330, 219.883813], [65.420490, 66.002564, 71.275268, 74.968993, 214.407387], [120.223968, 122.040402, 127.625224, 133.729217, 402.397915]]
input_correlations: [[0.532760, 0.987449, 0.997516, 0.992006, -0.256547, 0.588306, -0.477487, 0.996422], [-0.590655, -0.993452, -0.991371, -0.979192, 0.280570, -0.593880, 0.495716, -0.991647], [0.551733, 0.988803, 0.998219, 0.990834, -0.240678, 0.586696, -0.459183, 0.997653], [-0.574263, -0.991379, -0.997289, -0.987056, 0.222873, -0.590926, 0.442943, -0.997915], [-0.519305, -0.985491, -0.999375, -0.994474, 0.224494, -0.592977, 0.445074, -0.997221], [-0.539794, -0.983146, -0.997257, -0.989738, 0.140616, -0.579144, 0.368979, -0.997058], [-0.556595, -0.987849, -0.995113, -0.987606, 0.281661, -0.592233, 0.498182, -0.994503], [0.536817, 0.986422, 0.998609, 0.993002, -0.243026, 0.591312, -0.462942, 0.997620]]
pre_activation_mean: [4.684528, -1.739546, 4.116791, -2.736769, -2.797587, -2.443154, -2.382305, 4.471087]
pre_activation_std: [6.578455, 3.388366, 6.398107, 4.850799, 4.658975, 2.826393, 3.891548, 6.976417]
### 6
mean: [-1.193915, -3.615610, 2.713171, -5.353864, 7.177118, 5.303938, 5.912858, 1.350329]
std: [1.405139, 3.864276, 4.987292, 8.801908, 10.362769, 7.847447, 9.409931, 2.033355]
fourier: [[24.557572, 24.850021, 25.366056, 27.312768, 107.452362], [67.250262, 71.051981, 73.155238, 74.878588, 325.404883], [82.875349, 83.144753, 93.221461, 94.639985, 244.185362], [150.514036, 151.525220, 162.103792, 169.713849, 481.847810], [176.825486, 177.547349, 191.358022, 198.820632, 645.940632], [133.809802, 133.827181, 145.265436, 150.727993, 477.354419], [162.075460, 163.142702, 172.989085, 181.045619, 532.157180], [33.957435, 34.457500, 37.763572, 38.865835, 121.529578]]
input_correlations: [[-0.999392, 0.377171, -0.999899, 0.400359, 0.306306, -0.857340, 0.261730, -0.999772], [-0.989975, 0.266727, -0.994146, 0.291752, 0.194503, -0.834924, 0.152451, -0.994076], [0.997233, -0.465191, 0.994027, -0.485285, -0.396133, 0.864186, -0.352555, 0.994282], [-0.999668, 0.417976, -0.998467, 0.439589, 0.347997, -0.861130, 0.304533, -0.998463], [0.999583, -0.423169, 0.998057, -0.444741, -0.353363, 0.861191, -0.309563, 0.998184], [0.999522, -0.425528, 0.997874, -0.447811, -0.356301, 0.861582, -0.311414, 0.997977], [0.999877, -0.408680, 0.998898, -0.430581, -0.338454, 0.860467, -0.294897, 0.999008], [0.998517, -0.445525, 0.996284, -0.464676, -0.375405, 0.860211, -0.334695, 0.996331]]
pre_activation_mean: [-1.193915, -3.615610, 2.713171, -5.353864, 7.177118, 5.303938, 5.912858, 1.350329]
pre_activation_std: [1.405139, 3.864276, 4.987292, 8.801908, 10.362769, 7.847447, 9.409931, 2.033355]
### 8
mean: [4.217995, -6.476473, -4.647450, -7.068149, -4.657724, 9.661586, -6.637925, -6.368640]
std: [6.769755, 9.927568, 5.554908, 10.619908, 7.856061, 13.969283, 10.990859, 8.644862]
fourier: [[119.611009, 120.855002, 121.963199, 130.943139, 379.619539], [174.431468, 175.581309, 179.929107, 191.788343, 582.882554], [98.323197, 98.920206, 100.669667, 107.366676, 418.270440], [186.563492, 188.479900, 192.111076, 204.905157, 636.133334], [136.983530, 138.184797, 143.046119, 151.315082, 419.195183], [241.889820, 241.974343, 256.809510, 269.414089, 869.542718], [190.759620, 191.384223, 201.345312, 212.004247, 597.413216], [152.581323, 153.797565, 156.006216, 167.056778, 573.177630]]
input_correlations: [[0.764628, 0.720482, 0.999956, -0.370135, 0.999216, 0.999359, 0.999936, 0.999245], [-0.758415, -0.720324, -0.999876, 0.381724, -0.999629, -0.999729, -0.999946, -0.999504], [-0.763203, -0.718504, -0.999917, 0.373078, -0.999340, -0.999452, -0.999914, -0.999308], [-0.760249, -0.718123, -0.999917, 0.380813, -0.999580, -0.999678, -0.999979, -0.999567], [-0.753740, -0.714141, -0.999590, 0.396451, -0.999885, -0.999915, -0.999795, -0.999804], [0.743148, 0.711825, 0.998898, -0.412478, 0.999969, 0.999932, 0.999255, 0.999591], [-0.747079, -0.713563, -0.999170, 0.406974, -0.999978, -0.999968, -0.999483, -0.999709], [-0.762535, -0.721930, -0.999950, 0.371828, -0.999291, -0.999430, -0.999925, -0.999227]]
pre_activation_mean: [4.217995, -6.476473, -4.647450, -7.068149, -4.657724, 9.661586, -6.637925, -6.368640]
pre_activation_std: [6.769755, 9.927568, 5.554908, 10.619908, 7.856061, 13.969283, 10.990859, 8.644862]
### 10
mean: [-5.976058, 7.192385, 2.863647, 3.055264, -0.432919, 1.275459, 4.865075, -4.193319]
std: [9.636470, 11.012803, 4.638204, 5.627201, 0.550439, 2.493427, 7.582867, 7.383471]
fourier: [[167.715456, 168.688021, 175.671955, 185.872077, 537.845220], [189.311437, 190.515323, 204.238205, 212.857551, 647.314684], [75.826525, 77.871802, 89.533525, 89.743115, 257.728233], [94.560954, 96.283351, 105.807531, 108.522347, 274.973782], [8.702848, 9.066789, 9.172617, 11.305412, 38.962686], [40.920593, 41.407945, 48.087966, 49.048322, 114.791338], [123.536369, 128.047208, 145.001331, 146.283426, 437.856788], [126.058138, 127.324340, 137.302020, 142.651026, 377.398759]]
input_correlations: [[-0.999037, 0.333956, -0.703050, 0.206555, 0.474001, -0.999976, 0.471719, -0.683640], [0.997626, -0.356174, 0.713018, -0.230159, -0.495668, 0.999741, -0.493462, 0.690624], [0.988050, -0.425046, 0.754368, -0.300510, -0.568184, 0.994179, -0.565452, 0.724764], [0.995447, -0.376114, 0.725367, -0.251245, -0.518482, 0.998765, -0.516778, 0.701397], [0.276622, -0.913127, 0.695054, -0.891776, -0.978446, 0.321267, -0.974257, 0.593852], [0.983124, -0.450686, 0.766848, -0.326979, -0.591343, 0.990600, -0.588531, 0.732930], [0.991115, -0.406154, 0.744439, -0.281414, -0.550693, 0.996232, -0.548354, 0.717698], [-0.997120, 0.361299, -0.717921, 0.234933, 0.501862, -0.999565, 0.499559, -0.695242]]
pre_activation_mean: [-5.976058, 7.192385, 2.863647, 3.055264, -0.432919, 1.275459, 4.865075, -4.193319]
pre_activation_std: [9.636470, 11.012803, 4.638204, 5.627201, 0.550439, 2.493427, 7.582867, 7.383471]
### 12
mean: [-5.479320]
std: [8.569682]
fourier: [[146.132728, 148.169821, 159.773399, 166.470020, 493.138792]]
input_correlations: [[0.487377, -0.999095, -0.999924, -0.997097, 0.086929, -0.999242, -0.999886, 0.514076]]
pre_activation_mean: [-5.479320]
pre_activation_std: [8.569682]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
1.406466,
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0.212157,
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],
[
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-0.604194,
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],
[
1.393688,
0.387526,
0.110235,
0.063905,
-0.869662
],
[
-0.894719,
-0.622105,
-0.209083,
0.003325,
0.033659
],
[
1.316953,
0.208156,
0.199347,
0.083137,
-0.813462
],
[
0.395667,
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-0.083496,
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-0.817347
],
[
-0.588245,
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0.03772,
0.369425
],
[
1.175715,
-1.003047,
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0.125405,
0.261495
]
],
"network.0.bias": [
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0.61599,
0.050646,
-0.402273,
0.031858,
-0.244376,
-0.036548,
-0.334244
],
"network.2.weight": [
[
0.229705,
-0.19384,
-0.057556,
0.492478,
-0.135544,
-0.55772,
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0.814309
],
[
0.355145,
-0.266145,
0.390687,
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0.217973,
-0.892471,
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0.753242
],
[
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0.515801,
0.777843,
0.662336,
0.224021,
-0.844923,
-0.142133,
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],
[
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0.569357,
0.660053,
0.164258,
0.521078,
-0.471357,
0.086512,
0.647978
],
[
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-0.31167,
-0.376104,
-0.169015,
-0.850474,
-0.206906,
0.237401,
-0.206701
],
[
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0.090777,
-0.185687,
-0.027292,
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-0.265253,
-0.484885,
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],
[
0.070387,
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-0.462484,
-0.307906,
-0.501043,
0.24438,
0.244408,
-0.355429
],
[
0.098421,
0.300994,
0.442325,
0.570265,
0.278775,
-0.767475,
0.191731,
0.795346
]
],
"network.2.bias": [
-0.35142,
0.084356,
-0.072564,
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-0.111387,
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],
"network.4.weight": [
[
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[
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0.352215,
0.006982
],
[
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0.510802,
0.416905,
0.496892,
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0.151772
],
[
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-0.059995,
0.035988,
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0.216219,
-0.405281
],
[
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0.127055,
0.173246
],
[
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0.149464,
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0.110415
],
[
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0.426813,
-0.293654,
0.589085,
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],
[
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0.51196,
0.455089,
-0.283421,
0.409926,
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]
],
"network.4.bias": [
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0.348197,
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],
"network.6.weight": [
[
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0.1037,
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],
[
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-0.828278,
-0.353344,
-0.661539,
-0.113091,
0.348174,
0.004406,
0.087085
],
[
0.326092,
-0.725492,
-0.110518,
-0.310867,
-0.301295,
-0.000336,
-0.186557,
0.486768
],
[
-0.470352,
0.066538,
-0.725258,
0.483773,
0.424779,
-0.668927,
0.45755,
-0.138961
],
[
0.597209,
-0.664205,
0.298676,
-0.373441,
-0.524422,
-0.113603,
-0.166745,
0.634972
],
[
0.576037,
-0.58128,
0.326491,
-0.277923,
-0.678824,
-0.08339,
0.157993,
0.270168
],
[
0.557927,
0.020579,
0.325234,
-0.307035,
-0.427662,
0.561063,
-0.438082,
0.518094
],
[
0.178976,
-0.029143,
0.096598,
-0.205589,
0.254088,
-0.131857,
-0.394727,
0.03029
]
],
"network.6.bias": [
-0.310823,
-0.47315,
-0.361941,
0.315064,
0.423461,
0.156587,
-0.283416,
0.005864
],
"network.8.weight": [
[
-0.178354,
0.00536,
0.154308,
0.266795,
0.177374,
0.171039,
0.335287,
-0.062759
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[
-0.359814,
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-0.352369,
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[
-0.25945,
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[
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[
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[
0.003918,
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0.549847,
-0.855751
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[
-0.166214,
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0.008223
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[
0.265677,
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-0.365497,
-0.270618,
-0.432936,
0.046375,
-0.43683,
0.560789
]
],
"network.8.bias": [
-0.566245,
0.256545,
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0.017363,
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0.153167,
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"network.10.weight": [
[
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[
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[
0.480934,
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[
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[
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0.058062,
0.263343,
-0.44484,
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[
-0.080925,
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0.07789,
0.058582,
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0.558754,
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[
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0.126417,
0.042002,
0.06485,
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[
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"network.12.bias": [
0.12887
]
}
## Activation Signature
### 0
mean: [0.215954, 7.432114, 3.117535, 3.418265, -0.057115, 1.470956, 5.232719, 0.389952]
std: [0.343606, 10.837177, 4.425539, 5.359272, 0.097953, 2.312080, 7.291938, 0.581609]
fourier: [[5.632762, 5.641179, 6.269030, 6.782681, 19.435891], [189.590554, 191.115100, 197.118085, 209.922072, 668.890235], [75.919762, 76.814631, 81.974463, 86.201277, 280.578158], [94.329171, 95.769362, 96.903654, 103.362694, 307.643904], [1.592650, 1.653634, 1.817424, 2.040022, 5.140377], [40.679615, 40.894679, 42.430107, 45.040493, 132.386020], [125.665660, 126.760012, 134.852049, 142.005926, 470.944776], [9.481967, 9.646700, 10.644129, 11.109236, 35.095706]]
input_correlations: [[0.958039, 0.281302, 0.346877, 0.025103, -0.045650, 0.000000, 0.000000, 0.000000], [0.790731, 0.344139, 0.009909, -0.493015, -0.132197, 0.000000, 0.000000, 0.000000], [0.850813, 0.523807, 0.276913, -0.001089, -0.308122, 0.000000, 0.000000, 0.000000], [-0.888305, -0.705921, -0.468490, -0.107333, -0.134760, 0.000000, 0.000000, 0.000000], [0.864439, 0.462832, 0.325946, -0.015594, -0.297154, 0.000000, 0.000000, 0.000000], [0.250360, -0.073976, -0.160979, -0.472302, -0.842787, 0.000000, 0.000000, 0.000000], [-0.683744, 0.101106, 0.133903, 0.311601, 0.441795, 0.000000, 0.000000, 0.000000], [0.634565, -0.448674, -0.114370, -0.156151, 0.313128, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.506036, 0.285550, 1.785898, -3.037421, 1.641467, -1.636361, 0.512522, -0.904265]
pre_activation_std: [2.781304, 2.329023, 3.334571, 2.605216, 3.057416, 1.745090, 1.225155, 2.540174]
### 2
mean: [-0.520396, 1.958222, 3.375695, 3.263932, -3.700711, -2.086423, -1.410498, 2.191620]
std: [1.180953, 2.762756, 5.115029, 4.405910, 5.753523, 2.217773, 3.112308, 3.209847]
fourier: [[19.338163, 19.374827, 20.330971, 22.846137, 46.835652], [46.933569, 47.130232, 52.342359, 55.782547, 176.239970], [89.059293, 91.779626, 93.685926, 98.153189, 303.812544], [77.220505, 78.827003, 79.611058, 81.049864, 293.753842], [97.954136, 101.041541, 106.323678, 110.120577, 333.064058], [39.453774, 40.161746, 41.267297, 42.908806, 187.778048], [52.721859, 53.961585, 54.946500, 58.422595, 126.944869], [56.234562, 57.657887, 58.314817, 61.948985, 197.245803]]
input_correlations: [[0.552456, 0.377488, 0.287281, 0.149541, 0.339990, 0.235599, -0.586985, 0.878362], [0.978175, 0.854633, 0.919527, 0.596406, 0.941060, 0.503102, -0.470063, 0.749904], [0.969088, 0.931597, 0.959254, 0.601508, 0.970034, 0.569432, -0.448911, 0.700524], [0.951090, 0.943429, 0.978321, 0.619140, 0.982361, 0.582697, -0.403657, 0.644668], [-0.976901, -0.921762, -0.978962, -0.596573, -0.990155, -0.566058, 0.450909, -0.614337], [-0.952775, -0.867754, -0.942510, -0.677114, -0.955228, -0.617718, 0.249196, -0.702041], [-0.954474, -0.931801, -0.984646, -0.607068, -0.989348, -0.556663, 0.457179, -0.612628], [0.960999, 0.919427, 0.950452, 0.630856, 0.961220, 0.573690, -0.386174, 0.727461]]
pre_activation_mean: [-0.520396, 1.958222, 3.375695, 3.263932, -3.700711, -2.086423, -1.410498, 2.191620]
pre_activation_std: [1.180953, 2.762756, 5.115029, 4.405910, 5.753523, 2.217773, 3.112308, 3.209847]
### 4
mean: [4.684528, -1.739546, 4.116791, -2.736769, -2.797587, -2.443154, -2.382305, 4.471087]
std: [6.578455, 3.388366, 6.398107, 4.850799, 4.658975, 2.826393, 3.891548, 6.976417]
fourier: [[111.492751, 113.371363, 121.947583, 125.678599, 421.607543], [57.193825, 57.864484, 61.570478, 66.933095, 156.559146], [109.735992, 111.985405, 116.867922, 123.759076, 370.511238], [83.885686, 86.103028, 87.490729, 95.586230, 246.309223], [81.552818, 82.959742, 85.353998, 89.330888, 251.782835], [50.849539, 52.035967, 52.532396, 55.435330, 219.883813], [65.420490, 66.002564, 71.275268, 74.968993, 214.407387], [120.223968, 122.040402, 127.625224, 133.729217, 402.397915]]
input_correlations: [[0.532760, 0.987449, 0.997516, 0.992006, -0.256547, 0.588306, -0.477487, 0.996422], [-0.590655, -0.993452, -0.991371, -0.979192, 0.280570, -0.593880, 0.495716, -0.991647], [0.551733, 0.988803, 0.998219, 0.990834, -0.240678, 0.586696, -0.459183, 0.997653], [-0.574263, -0.991379, -0.997289, -0.987056, 0.222873, -0.590926, 0.442943, -0.997915], [-0.519305, -0.985491, -0.999375, -0.994474, 0.224494, -0.592977, 0.445074, -0.997221], [-0.539794, -0.983146, -0.997257, -0.989738, 0.140616, -0.579144, 0.368979, -0.997058], [-0.556595, -0.987849, -0.995113, -0.987606, 0.281661, -0.592233, 0.498182, -0.994503], [0.536817, 0.986422, 0.998609, 0.993002, -0.243026, 0.591312, -0.462942, 0.997620]]
pre_activation_mean: [4.684528, -1.739546, 4.116791, -2.736769, -2.797587, -2.443154, -2.382305, 4.471087]
pre_activation_std: [6.578455, 3.388366, 6.398107, 4.850799, 4.658975, 2.826393, 3.891548, 6.976417]
### 6
mean: [-1.193915, -3.615610, 2.713171, -5.353864, 7.177118, 5.303938, 5.912858, 1.350329]
std: [1.405139, 3.864276, 4.987292, 8.801908, 10.362769, 7.847447, 9.409931, 2.033355]
fourier: [[24.557572, 24.850021, 25.366056, 27.312768, 107.452362], [67.250262, 71.051981, 73.155238, 74.878588, 325.404883], [82.875349, 83.144753, 93.221461, 94.639985, 244.185362], [150.514036, 151.525220, 162.103792, 169.713849, 481.847810], [176.825486, 177.547349, 191.358022, 198.820632, 645.940632], [133.809802, 133.827181, 145.265436, 150.727993, 477.354419], [162.075460, 163.142702, 172.989085, 181.045619, 532.157180], [33.957435, 34.457500, 37.763572, 38.865835, 121.529578]]
input_correlations: [[-0.999392, 0.377171, -0.999899, 0.400359, 0.306306, -0.857340, 0.261730, -0.999772], [-0.989975, 0.266727, -0.994146, 0.291752, 0.194503, -0.834924, 0.152451, -0.994076], [0.997233, -0.465191, 0.994027, -0.485285, -0.396133, 0.864186, -0.352555, 0.994282], [-0.999668, 0.417976, -0.998467, 0.439589, 0.347997, -0.861130, 0.304533, -0.998463], [0.999583, -0.423169, 0.998057, -0.444741, -0.353363, 0.861191, -0.309563, 0.998184], [0.999522, -0.425528, 0.997874, -0.447811, -0.356301, 0.861582, -0.311414, 0.997977], [0.999877, -0.408680, 0.998898, -0.430581, -0.338454, 0.860467, -0.294897, 0.999008], [0.998517, -0.445525, 0.996284, -0.464676, -0.375405, 0.860211, -0.334695, 0.996331]]
pre_activation_mean: [-1.193915, -3.615610, 2.713171, -5.353864, 7.177118, 5.303938, 5.912858, 1.350329]
pre_activation_std: [1.405139, 3.864276, 4.987292, 8.801908, 10.362769, 7.847447, 9.409931, 2.033355]
### 8
mean: [4.217995, -6.476473, -4.647450, -7.068149, -4.657724, 9.661586, -6.637925, -6.368640]
std: [6.769755, 9.927568, 5.554908, 10.619908, 7.856061, 13.969283, 10.990859, 8.644862]
fourier: [[119.611009, 120.855002, 121.963199, 130.943139, 379.619539], [174.431468, 175.581309, 179.929107, 191.788343, 582.882554], [98.323197, 98.920206, 100.669667, 107.366676, 418.270440], [186.563492, 188.479900, 192.111076, 204.905157, 636.133334], [136.983530, 138.184797, 143.046119, 151.315082, 419.195183], [241.889820, 241.974343, 256.809510, 269.414089, 869.542718], [190.759620, 191.384223, 201.345312, 212.004247, 597.413216], [152.581323, 153.797565, 156.006216, 167.056778, 573.177630]]
input_correlations: [[0.764628, 0.720482, 0.999956, -0.370135, 0.999216, 0.999359, 0.999936, 0.999245], [-0.758415, -0.720324, -0.999876, 0.381724, -0.999629, -0.999729, -0.999946, -0.999504], [-0.763203, -0.718504, -0.999917, 0.373078, -0.999340, -0.999452, -0.999914, -0.999308], [-0.760249, -0.718123, -0.999917, 0.380813, -0.999580, -0.999678, -0.999979, -0.999567], [-0.753740, -0.714141, -0.999590, 0.396451, -0.999885, -0.999915, -0.999795, -0.999804], [0.743148, 0.711825, 0.998898, -0.412478, 0.999969, 0.999932, 0.999255, 0.999591], [-0.747079, -0.713563, -0.999170, 0.406974, -0.999978, -0.999968, -0.999483, -0.999709], [-0.762535, -0.721930, -0.999950, 0.371828, -0.999291, -0.999430, -0.999925, -0.999227]]
pre_activation_mean: [4.217995, -6.476473, -4.647450, -7.068149, -4.657724, 9.661586, -6.637925, -6.368640]
pre_activation_std: [6.769755, 9.927568, 5.554908, 10.619908, 7.856061, 13.969283, 10.990859, 8.644862]
### 10
mean: [-5.976058, 7.192385, 2.863647, 3.055264, -0.432919, 1.275459, 4.865075, -4.193319]
std: [9.636470, 11.012803, 4.638204, 5.627201, 0.550439, 2.493427, 7.582867, 7.383471]
fourier: [[167.715456, 168.688021, 175.671955, 185.872077, 537.845220], [189.311437, 190.515323, 204.238205, 212.857551, 647.314684], [75.826525, 77.871802, 89.533525, 89.743115, 257.728233], [94.560954, 96.283351, 105.807531, 108.522347, 274.973782], [8.702848, 9.066789, 9.172617, 11.305412, 38.962686], [40.920593, 41.407945, 48.087966, 49.048322, 114.791338], [123.536369, 128.047208, 145.001331, 146.283426, 437.856788], [126.058138, 127.324340, 137.302020, 142.651026, 377.398759]]
input_correlations: [[-0.999037, 0.333956, -0.703050, 0.206555, 0.474001, -0.999976, 0.471719, -0.683640], [0.997626, -0.356174, 0.713018, -0.230159, -0.495668, 0.999741, -0.493462, 0.690624], [0.988050, -0.425046, 0.754368, -0.300510, -0.568184, 0.994179, -0.565452, 0.724764], [0.995447, -0.376114, 0.725367, -0.251245, -0.518482, 0.998765, -0.516778, 0.701397], [0.276622, -0.913127, 0.695054, -0.891776, -0.978446, 0.321267, -0.974257, 0.593852], [0.983124, -0.450686, 0.766848, -0.326979, -0.591343, 0.990600, -0.588531, 0.732930], [0.991115, -0.406154, 0.744439, -0.281414, -0.550693, 0.996232, -0.548354, 0.717698], [-0.997120, 0.361299, -0.717921, 0.234933, 0.501862, -0.999565, 0.499559, -0.695242]]
pre_activation_mean: [-5.976058, 7.192385, 2.863647, 3.055264, -0.432919, 1.275459, 4.865075, -4.193319]
pre_activation_std: [9.636470, 11.012803, 4.638204, 5.627201, 0.550439, 2.493427, 7.582867, 7.383471]
### 12
mean: [-5.479320]
std: [8.569682]
fourier: [[146.132728, 148.169821, 159.773399, 166.470020, 493.138792]]
input_correlations: [[0.487377, -0.999095, -0.999924, -0.997097, 0.086929, -0.999242, -0.999886, 0.514076]]
pre_activation_mean: [-5.479320]
pre_activation_std: [8.569682]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.3544702082872391, "train_acc": 0.82, "val_loss": 0.36609530448913574, "val_acc": 0.84}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.40330056846141815, "train_acc": 0.83, "val_loss": 0.37354403734207153, "val_acc": 0.84}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.7219191789627075, "final_val_loss": 0.6552083492279053, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5590522289276123, "final_val_loss": 0.37354403734207153, "initial_val_acc": 0.78, "final_val_acc": 0.84, "best_val_acc": 0.84, "best_epoch": 8}, "improvement": 0.36, "first_improvement_epoch": 2}} |
28 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.44, "improved_accuracy": 0.76, "improvement": 0.32, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9587, "learning_rate": 0.07451702846533188, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.146395, 2.066384, 2.283387, 0.958017, 0.292708, 1.939242, 1.336348]
std: [0.746920, 1.617734, 1.668369, 0.731134, 0.230341, 1.461668, 0.959155]
fourier: [[10.498685, 12.725389, 13.175561, 13.292172, 15.744350], [27.384609, 28.219798, 28.872290, 33.858153, 185.974576], [28.016169, 29.951348, 29.988545, 34.602535, 205.504837], [12.281655, 12.680137, 13.270172, 15.023235, 86.221542], [3.899733, 4.063718, 4.304589, 4.595442, 26.343703], [24.614226, 26.171402, 26.283523, 30.297430, 174.531725], [16.120862, 17.135719, 17.492786, 20.058486, 120.271355]]
input_correlations: [[-0.700923, -0.242517, -0.873434, 0.197703, -0.164600, 0.000000, 0.000000, 0.000000], [0.655221, 0.482248, 0.054559, 0.041512, -0.576327, 0.000000, 0.000000, 0.000000], [0.632639, 0.525026, 0.063581, -0.005859, -0.589259, 0.000000, 0.000000, 0.000000], [-0.388834, 0.063644, -0.635274, 0.149104, -0.827713, 0.000000, 0.000000, 0.000000], [-0.972362, -0.232510, -0.186497, 0.101873, 0.010793, 0.000000, 0.000000, 0.000000], [-0.809714, -0.135576, 0.083113, 0.022391, 0.317700, 0.000000, 0.000000, 0.000000], [-0.764398, -0.084576, -0.097178, 0.561683, 0.298512, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.145390, 0.834946, 0.678285, -2.162266, -1.581413, 0.232103, 1.052118]
pre_activation_std: [1.914595, 1.592747, 3.083002, 2.528473, 2.887039, 1.991955, 2.165535]
### 2
mean: [0.165202, -0.154345, -1.298863, -2.130763, 0.187435, -0.862228, 0.758568]
std: [1.026529, 0.956733, 0.922144, 2.099710, 1.479489, 0.587516, 1.616456]
fourier: [[15.630838, 15.835415, 16.108216, 17.308519, 18.892926], [14.209173, 14.472340, 14.716982, 14.748412, 17.293428], [13.047250, 14.444496, 15.917625, 17.227573, 116.897636], [31.951606, 34.155078, 41.220892, 51.045109, 191.768651], [22.379506, 22.809717, 23.002763, 23.857645, 27.656461], [8.176128, 8.816381, 9.793527, 10.118631, 77.600520], [24.100229, 24.526468, 26.245026, 29.227192, 68.271121]]
input_correlations: [[-0.087130, -0.841343, -0.810158, -0.198497, 0.659706, 0.770407, 0.685548, 0.000000], [-0.112557, -0.837461, -0.834069, -0.141632, 0.540702, 0.600888, 0.770991, 0.000000], [-0.424308, -0.228068, -0.267950, -0.276763, -0.663108, -0.452390, -0.793050, 0.000000], [-0.404426, -0.922239, -0.930868, -0.335582, -0.015915, 0.220295, 0.027107, 0.000000], [-0.176429, -0.915988, -0.902743, -0.238219, 0.516961, 0.637967, 0.608719, 0.000000], [-0.520181, 0.298544, 0.260507, -0.548192, -0.629995, -0.515809, -0.922710, 0.000000], [-0.008603, -0.805277, -0.801086, -0.019650, 0.544570, 0.597153, 0.835085, 0.000000]]
pre_activation_mean: [0.165202, -0.154345, -1.298863, -2.130763, 0.187435, -0.862228, 0.758568]
pre_activation_std: [1.026529, 0.956733, 0.922144, 2.099710, 1.479489, 0.587516, 1.616456]
### 4
mean: [1.013405, 0.479841, -0.088364, 0.254414, -1.911390, -0.682959, -1.569505]
std: [1.404317, 1.207927, 0.333422, 0.383366, 1.307227, 0.691135, 1.131131]
fourier: [[22.107781, 22.958837, 23.381615, 31.273259, 91.206458], [18.701010, 19.130966, 19.998580, 26.974873, 43.185731], [5.011417, 5.817787, 6.076721, 7.538239, 7.952717], [5.852183, 5.889934, 6.072553, 8.315788, 22.897241], [21.233179, 22.029931, 22.537571, 29.077739, 172.025094], [10.382978, 10.859685, 11.414508, 15.476511, 61.466297], [18.431900, 18.754391, 19.347147, 25.230321, 141.255434]]
input_correlations: [[0.960594, 0.961524, 0.380088, -0.199649, 0.976021, 0.412520, 0.968541, 0.000000], [0.929974, 0.970090, 0.409516, -0.180358, 0.953958, 0.425155, 0.985832, 0.000000], [0.913255, 0.719007, 0.385852, -0.103615, 0.872591, 0.402765, 0.608059, 0.000000], [0.952406, 0.974487, 0.482293, -0.085273, 0.954724, 0.483471, 0.950123, 0.000000], [-0.964164, -0.950474, -0.329726, 0.259026, -0.984004, -0.381672, -0.961132, 0.000000], [-0.905996, -0.965661, -0.403728, 0.189365, -0.932875, -0.404056, -0.994495, 0.000000], [-0.967076, -0.955511, -0.338640, 0.244175, -0.983531, -0.391619, -0.959627, 0.000000]]
pre_activation_mean: [1.013405, 0.479841, -0.088364, 0.254414, -1.911390, -0.682959, -1.569505]
pre_activation_std: [1.404317, 1.207927, 0.333422, 0.383366, 1.307227, 0.691135, 1.131131]
### 6
mean: [-1.802630, 0.152491, -1.631878, -0.011126, -1.296349, -0.351437, 0.484597]
std: [1.496333, 1.175807, 1.045111, 0.859064, 0.926839, 1.522251, 1.399107]
fourier: [[22.675068, 24.725150, 24.833390, 33.058744, 162.236668], [18.204849, 18.452600, 19.365124, 19.614877, 26.107221], [16.121251, 17.119088, 17.543956, 23.168489, 146.869060], [12.778954, 13.142363, 14.292953, 14.338336, 18.975010], [14.302125, 15.196938, 15.534139, 20.617388, 116.671395], [24.339769, 24.784879, 24.787039, 31.629333, 33.791830], [21.457225, 22.939521, 23.295099, 31.007459, 43.613774]]
input_correlations: [[-0.994549, -0.996282, -0.847837, -0.991726, -0.762506, -0.113107, -0.841408, 0.000000], [0.998139, 0.996826, 0.815559, 0.978231, 0.806025, 0.072635, 0.879645, 0.000000], [-0.997868, -0.997372, -0.814651, -0.980923, -0.800199, -0.073563, -0.873595, 0.000000], [0.994148, 0.997198, 0.842348, 0.988771, 0.764293, 0.129427, 0.847485, 0.000000], [-0.997896, -0.997511, -0.817253, -0.981502, -0.798834, -0.073739, -0.871499, 0.000000], [-0.999223, -0.993883, -0.811350, -0.976094, -0.823130, -0.027935, -0.887316, 0.000000], [0.998087, 0.995819, 0.839302, 0.985888, 0.789747, 0.080458, 0.863426, 0.000000]]
pre_activation_mean: [-1.802630, 0.152491, -1.631878, -0.011126, -1.296349, -0.351437, 0.484597]
pre_activation_std: [1.496333, 1.175807, 1.045111, 0.859064, 0.926839, 1.522251, 1.399107]
### 8
mean: [-0.400353, -0.173820, 0.281264, 0.343626, -0.079561, 0.030296, -0.007163]
std: [0.230446, 0.880210, 1.892334, 1.438389, 3.048933, 1.192170, 1.084960]
fourier: [[3.615419, 3.659897, 4.122551, 5.025478, 36.031780], [13.392804, 14.928104, 14.942903, 15.643788, 19.445253], [28.146490, 28.425946, 31.186121, 31.635507, 42.177696], [21.376587, 24.573546, 24.577190, 30.926340, 31.670451], [42.650051, 45.714061, 52.292851, 52.504263, 66.970626], [16.838653, 17.622086, 20.560675, 20.738796, 26.071353], [15.124401, 16.302074, 18.544221, 18.635106, 23.833517]]
input_correlations: [[0.948815, 0.919631, 0.963201, 0.883920, 0.964657, -0.771807, 0.935640, 0.000000], [0.836878, 0.992409, 0.865530, 0.978716, 0.930172, -0.574301, 0.996945, 0.000000], [-0.847524, -0.986889, -0.874433, -0.972868, -0.928846, 0.605482, -0.993165, 0.000000], [-0.809013, -0.996777, -0.839703, -0.987827, -0.913892, 0.536332, -0.999353, 0.000000], [-0.811963, -0.996961, -0.842732, -0.986951, -0.917714, 0.535860, -0.999461, 0.000000], [0.794061, 0.998923, 0.826277, 0.991258, 0.908488, -0.508335, 0.999815, 0.000000], [0.813602, 0.996756, 0.844133, 0.986604, 0.918618, -0.537385, 0.999400, 0.000000]]
pre_activation_mean: [-0.400353, -0.173820, 0.281264, 0.343626, -0.079561, 0.030296, -0.007163]
pre_activation_std: [0.230446, 0.880210, 1.892334, 1.438389, 3.048933, 1.192170, 1.084960]
### 10
mean: [-0.123665, 1.984142, 2.219277, 1.021831, 0.342452, 1.840315, 1.104719]
std: [0.898871, 1.768254, 1.807059, 0.766823, 0.464620, 1.667186, 1.552088]
fourier: [[12.913367, 13.278146, 15.704021, 15.722223, 19.803487], [29.225784, 30.257743, 34.595721, 35.948424, 178.572752], [29.383824, 30.337553, 36.050718, 36.308693, 199.734910], [12.742717, 12.990787, 14.839383, 15.631662, 91.964767], [7.015115, 7.525717, 7.754063, 10.263866, 30.820676], [26.773268, 27.639725, 32.656602, 34.334159, 165.628329], [24.726291, 25.193923, 25.472096, 34.143720, 99.424700]]
input_correlations: [[0.990824, 0.987151, -0.637607, -0.718230, -0.649279, 0.989576, 0.990904, 0.000000], [-0.864686, -0.716043, 0.966282, 0.982074, 0.973246, -0.720925, -0.728927, 0.000000], [-0.886967, -0.747861, 0.954804, 0.973304, 0.961809, -0.752277, -0.759894, 0.000000], [-0.846593, -0.691617, 0.975692, 0.980181, 0.980635, -0.695636, -0.703979, 0.000000], [-0.995821, -0.951388, 0.756936, 0.815314, 0.772459, -0.953232, -0.956707, 0.000000], [-0.904927, -0.774450, 0.943246, 0.965098, 0.948773, -0.778795, -0.785983, 0.000000], [-0.988251, -0.923703, 0.807446, 0.861532, 0.820597, -0.926468, -0.930787, 0.000000]]
pre_activation_mean: [-0.123665, 1.984142, 2.219277, 1.021831, 0.342452, 1.840315, 1.104719]
pre_activation_std: [0.898871, 1.768254, 1.807059, 0.766823, 0.464620, 1.667186, 1.552088]
### 12
mean: [-5.103033]
std: [3.775241]
fourier: [[62.918577, 66.925938, 70.109890, 77.658853, 459.272940]]
input_correlations: [[0.622679, -0.996553, -0.998839, -0.995895, -0.981148, -0.997854, -0.997244, 0.000000]]
pre_activation_mean: [-5.103033]
pre_activation_std: [3.775241]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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],
[
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[
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]
],
"network.0.bias": [
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"network.2.weight": [
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],
"network.2.bias": [
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-0.638481,
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"network.4.weight": [
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}
## Activation Signature
### 0
mean: [0.146395, 2.066384, 2.283387, 0.958017, 0.292708, 1.939242, 1.336348]
std: [0.746920, 1.617734, 1.668369, 0.731134, 0.230341, 1.461668, 0.959155]
fourier: [[10.498685, 12.725389, 13.175561, 13.292172, 15.744350], [27.384609, 28.219798, 28.872290, 33.858153, 185.974576], [28.016169, 29.951348, 29.988545, 34.602535, 205.504837], [12.281655, 12.680137, 13.270172, 15.023235, 86.221542], [3.899733, 4.063718, 4.304589, 4.595442, 26.343703], [24.614226, 26.171402, 26.283523, 30.297430, 174.531725], [16.120862, 17.135719, 17.492786, 20.058486, 120.271355]]
input_correlations: [[-0.700923, -0.242517, -0.873434, 0.197703, -0.164600, 0.000000, 0.000000, 0.000000], [0.655221, 0.482248, 0.054559, 0.041512, -0.576327, 0.000000, 0.000000, 0.000000], [0.632639, 0.525026, 0.063581, -0.005859, -0.589259, 0.000000, 0.000000, 0.000000], [-0.388834, 0.063644, -0.635274, 0.149104, -0.827713, 0.000000, 0.000000, 0.000000], [-0.972362, -0.232510, -0.186497, 0.101873, 0.010793, 0.000000, 0.000000, 0.000000], [-0.809714, -0.135576, 0.083113, 0.022391, 0.317700, 0.000000, 0.000000, 0.000000], [-0.764398, -0.084576, -0.097178, 0.561683, 0.298512, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.145390, 0.834946, 0.678285, -2.162266, -1.581413, 0.232103, 1.052118]
pre_activation_std: [1.914595, 1.592747, 3.083002, 2.528473, 2.887039, 1.991955, 2.165535]
### 2
mean: [0.165202, -0.154345, -1.298863, -2.130763, 0.187435, -0.862228, 0.758568]
std: [1.026529, 0.956733, 0.922144, 2.099710, 1.479489, 0.587516, 1.616456]
fourier: [[15.630838, 15.835415, 16.108216, 17.308519, 18.892926], [14.209173, 14.472340, 14.716982, 14.748412, 17.293428], [13.047250, 14.444496, 15.917625, 17.227573, 116.897636], [31.951606, 34.155078, 41.220892, 51.045109, 191.768651], [22.379506, 22.809717, 23.002763, 23.857645, 27.656461], [8.176128, 8.816381, 9.793527, 10.118631, 77.600520], [24.100229, 24.526468, 26.245026, 29.227192, 68.271121]]
input_correlations: [[-0.087130, -0.841343, -0.810158, -0.198497, 0.659706, 0.770407, 0.685548, 0.000000], [-0.112557, -0.837461, -0.834069, -0.141632, 0.540702, 0.600888, 0.770991, 0.000000], [-0.424308, -0.228068, -0.267950, -0.276763, -0.663108, -0.452390, -0.793050, 0.000000], [-0.404426, -0.922239, -0.930868, -0.335582, -0.015915, 0.220295, 0.027107, 0.000000], [-0.176429, -0.915988, -0.902743, -0.238219, 0.516961, 0.637967, 0.608719, 0.000000], [-0.520181, 0.298544, 0.260507, -0.548192, -0.629995, -0.515809, -0.922710, 0.000000], [-0.008603, -0.805277, -0.801086, -0.019650, 0.544570, 0.597153, 0.835085, 0.000000]]
pre_activation_mean: [0.165202, -0.154345, -1.298863, -2.130763, 0.187435, -0.862228, 0.758568]
pre_activation_std: [1.026529, 0.956733, 0.922144, 2.099710, 1.479489, 0.587516, 1.616456]
### 4
mean: [1.013405, 0.479841, -0.088364, 0.254414, -1.911390, -0.682959, -1.569505]
std: [1.404317, 1.207927, 0.333422, 0.383366, 1.307227, 0.691135, 1.131131]
fourier: [[22.107781, 22.958837, 23.381615, 31.273259, 91.206458], [18.701010, 19.130966, 19.998580, 26.974873, 43.185731], [5.011417, 5.817787, 6.076721, 7.538239, 7.952717], [5.852183, 5.889934, 6.072553, 8.315788, 22.897241], [21.233179, 22.029931, 22.537571, 29.077739, 172.025094], [10.382978, 10.859685, 11.414508, 15.476511, 61.466297], [18.431900, 18.754391, 19.347147, 25.230321, 141.255434]]
input_correlations: [[0.960594, 0.961524, 0.380088, -0.199649, 0.976021, 0.412520, 0.968541, 0.000000], [0.929974, 0.970090, 0.409516, -0.180358, 0.953958, 0.425155, 0.985832, 0.000000], [0.913255, 0.719007, 0.385852, -0.103615, 0.872591, 0.402765, 0.608059, 0.000000], [0.952406, 0.974487, 0.482293, -0.085273, 0.954724, 0.483471, 0.950123, 0.000000], [-0.964164, -0.950474, -0.329726, 0.259026, -0.984004, -0.381672, -0.961132, 0.000000], [-0.905996, -0.965661, -0.403728, 0.189365, -0.932875, -0.404056, -0.994495, 0.000000], [-0.967076, -0.955511, -0.338640, 0.244175, -0.983531, -0.391619, -0.959627, 0.000000]]
pre_activation_mean: [1.013405, 0.479841, -0.088364, 0.254414, -1.911390, -0.682959, -1.569505]
pre_activation_std: [1.404317, 1.207927, 0.333422, 0.383366, 1.307227, 0.691135, 1.131131]
### 6
mean: [-1.802630, 0.152491, -1.631878, -0.011126, -1.296349, -0.351437, 0.484597]
std: [1.496333, 1.175807, 1.045111, 0.859064, 0.926839, 1.522251, 1.399107]
fourier: [[22.675068, 24.725150, 24.833390, 33.058744, 162.236668], [18.204849, 18.452600, 19.365124, 19.614877, 26.107221], [16.121251, 17.119088, 17.543956, 23.168489, 146.869060], [12.778954, 13.142363, 14.292953, 14.338336, 18.975010], [14.302125, 15.196938, 15.534139, 20.617388, 116.671395], [24.339769, 24.784879, 24.787039, 31.629333, 33.791830], [21.457225, 22.939521, 23.295099, 31.007459, 43.613774]]
input_correlations: [[-0.994549, -0.996282, -0.847837, -0.991726, -0.762506, -0.113107, -0.841408, 0.000000], [0.998139, 0.996826, 0.815559, 0.978231, 0.806025, 0.072635, 0.879645, 0.000000], [-0.997868, -0.997372, -0.814651, -0.980923, -0.800199, -0.073563, -0.873595, 0.000000], [0.994148, 0.997198, 0.842348, 0.988771, 0.764293, 0.129427, 0.847485, 0.000000], [-0.997896, -0.997511, -0.817253, -0.981502, -0.798834, -0.073739, -0.871499, 0.000000], [-0.999223, -0.993883, -0.811350, -0.976094, -0.823130, -0.027935, -0.887316, 0.000000], [0.998087, 0.995819, 0.839302, 0.985888, 0.789747, 0.080458, 0.863426, 0.000000]]
pre_activation_mean: [-1.802630, 0.152491, -1.631878, -0.011126, -1.296349, -0.351437, 0.484597]
pre_activation_std: [1.496333, 1.175807, 1.045111, 0.859064, 0.926839, 1.522251, 1.399107]
### 8
mean: [-0.400353, -0.173820, 0.281264, 0.343626, -0.079561, 0.030296, -0.007163]
std: [0.230446, 0.880210, 1.892334, 1.438389, 3.048933, 1.192170, 1.084960]
fourier: [[3.615419, 3.659897, 4.122551, 5.025478, 36.031780], [13.392804, 14.928104, 14.942903, 15.643788, 19.445253], [28.146490, 28.425946, 31.186121, 31.635507, 42.177696], [21.376587, 24.573546, 24.577190, 30.926340, 31.670451], [42.650051, 45.714061, 52.292851, 52.504263, 66.970626], [16.838653, 17.622086, 20.560675, 20.738796, 26.071353], [15.124401, 16.302074, 18.544221, 18.635106, 23.833517]]
input_correlations: [[0.948815, 0.919631, 0.963201, 0.883920, 0.964657, -0.771807, 0.935640, 0.000000], [0.836878, 0.992409, 0.865530, 0.978716, 0.930172, -0.574301, 0.996945, 0.000000], [-0.847524, -0.986889, -0.874433, -0.972868, -0.928846, 0.605482, -0.993165, 0.000000], [-0.809013, -0.996777, -0.839703, -0.987827, -0.913892, 0.536332, -0.999353, 0.000000], [-0.811963, -0.996961, -0.842732, -0.986951, -0.917714, 0.535860, -0.999461, 0.000000], [0.794061, 0.998923, 0.826277, 0.991258, 0.908488, -0.508335, 0.999815, 0.000000], [0.813602, 0.996756, 0.844133, 0.986604, 0.918618, -0.537385, 0.999400, 0.000000]]
pre_activation_mean: [-0.400353, -0.173820, 0.281264, 0.343626, -0.079561, 0.030296, -0.007163]
pre_activation_std: [0.230446, 0.880210, 1.892334, 1.438389, 3.048933, 1.192170, 1.084960]
### 10
mean: [-0.123665, 1.984142, 2.219277, 1.021831, 0.342452, 1.840315, 1.104719]
std: [0.898871, 1.768254, 1.807059, 0.766823, 0.464620, 1.667186, 1.552088]
fourier: [[12.913367, 13.278146, 15.704021, 15.722223, 19.803487], [29.225784, 30.257743, 34.595721, 35.948424, 178.572752], [29.383824, 30.337553, 36.050718, 36.308693, 199.734910], [12.742717, 12.990787, 14.839383, 15.631662, 91.964767], [7.015115, 7.525717, 7.754063, 10.263866, 30.820676], [26.773268, 27.639725, 32.656602, 34.334159, 165.628329], [24.726291, 25.193923, 25.472096, 34.143720, 99.424700]]
input_correlations: [[0.990824, 0.987151, -0.637607, -0.718230, -0.649279, 0.989576, 0.990904, 0.000000], [-0.864686, -0.716043, 0.966282, 0.982074, 0.973246, -0.720925, -0.728927, 0.000000], [-0.886967, -0.747861, 0.954804, 0.973304, 0.961809, -0.752277, -0.759894, 0.000000], [-0.846593, -0.691617, 0.975692, 0.980181, 0.980635, -0.695636, -0.703979, 0.000000], [-0.995821, -0.951388, 0.756936, 0.815314, 0.772459, -0.953232, -0.956707, 0.000000], [-0.904927, -0.774450, 0.943246, 0.965098, 0.948773, -0.778795, -0.785983, 0.000000], [-0.988251, -0.923703, 0.807446, 0.861532, 0.820597, -0.926468, -0.930787, 0.000000]]
pre_activation_mean: [-0.123665, 1.984142, 2.219277, 1.021831, 0.342452, 1.840315, 1.104719]
pre_activation_std: [0.898871, 1.768254, 1.807059, 0.766823, 0.464620, 1.667186, 1.552088]
### 12
mean: [-5.103033]
std: [3.775241]
fourier: [[62.918577, 66.925938, 70.109890, 77.658853, 459.272940]]
input_correlations: [[0.622679, -0.996553, -0.998839, -0.995895, -0.981148, -0.997854, -0.997244, 0.000000]]
pre_activation_mean: [-5.103033]
pre_activation_std: [3.775241]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.450087, 0.026217, -0.731719, 0.152157, 0.058067], [0.582193, 0.185494, -0.062439, 0.086382, -0.613911], [1.037051, 0.504426, -0.108923, 0.048964, -1.174562], [-0.184395, 0.200741, -0.606995, 0.252102, -1.003689], [-1.522775, 0.168325, 0.130531, -0.018712, 0.293536], [-1.040968, 0.230319, 0.277342, -0.164642, 0.515658], [-0.899562, 0.032023, 0.089182, 0.473514, 0.428895]], "network.0.bias": [-0.502484, 0.474773, 0.03971, -0.333382, -0.587695, 0.245588, 0.382535], "network.2.weight": [[0.125243, 0.622954, -0.603382, -0.428164, 0.248335, 0.41258, 0.156383], [-0.275427, 0.389136, -0.465006, 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[-0.109923, 0.299623, 0.632746, 0.214929, 0.247791, 0.489237, 0.510531], "network.12.weight": [[0.368751, -0.622965, -0.767899, -0.211527, -0.00497, -0.591537, -0.315574]], "network.12.bias": [-0.343368]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6845620572566986, "train_acc": 0.595, "val_loss": 0.7463005185127258, "val_acc": 0.4}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.672012209892273, "train_acc": 0.595, "val_loss": 0.7300986647605896, "val_acc": 0.4}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6608765721321106, "train_acc": 0.595, "val_loss": 0.6705974340438843, "val_acc": 0.44}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6374360918998718, "train_acc": 0.66, "val_loss": 0.588792622089386, "val_acc": 0.74}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5280432105064392, "train_acc": 0.72, "val_loss": 0.6414061784744263, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.49633176624774933, "train_acc": 0.8, "val_loss": 0.5646736025810242, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.480430543422699, "train_acc": 0.735, "val_loss": 0.6193729639053345, "val_acc": 0.7}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.4596201181411743, "train_acc": 0.73, "val_loss": 0.5518513321876526, "val_acc": 0.74}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4027415066957474, "train_acc": 0.795, "val_loss": 0.5870773196220398, "val_acc": 0.74}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.4197104722261429, "train_acc": 0.815, "val_loss": 0.5270621180534363, "val_acc": 0.76}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.39879415929317474, "train_acc": 0.795, "val_loss": 0.5555340647697449, "val_acc": 0.76}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4017181545495987, "train_acc": 0.805, "val_loss": 0.5047234296798706, "val_acc": 0.74}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.40636637806892395, "train_acc": 0.815, "val_loss": 0.49661341309547424, "val_acc": 0.74}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.7463005185127258, "final_val_loss": 0.6705974340438843, "initial_val_acc": 0.4, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.588792622089386, "final_val_loss": 0.49661341309547424, "initial_val_acc": 0.74, "final_val_acc": 0.74, "best_val_acc": 0.76, "best_epoch": 9}, "improvement": 0.32, "first_improvement_epoch": 2}} |
29 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.5, "improved_accuracy": 0.96, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2749, "learning_rate": 0.05070072171233657, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [11.018291, 0.557894, 0.315318, 0.000000, 1.341929, 10.666611, 0.000000, 0.968719]
std: [13.981732, 0.713713, 0.463184, 0.000000, 0.765469, 13.414409, 0.000000, 0.698536]
fourier: [[235.848032, 249.491556, 251.236698, 254.190842, 991.646210], [12.036465, 14.026297, 14.734722, 15.648911, 50.210450], [7.153558, 8.338510, 9.708403, 11.087148, 28.378664], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [13.498956, 13.698407, 14.588377, 16.949226, 120.773616], [225.746527, 238.838436, 241.144587, 244.013836, 959.994858], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [11.473562, 11.650437, 12.751759, 14.558978, 87.184681]]
input_correlations: [[0.474054, 0.750909, -0.350571, 0.258146, -0.050046, 0.000000, 0.000000, 0.000000], [0.484185, -0.456221, -0.296346, -0.508175, -0.306687, 0.000000, 0.000000, 0.000000], [0.930312, 0.254728, 0.597813, -0.209801, 0.193664, 0.000000, 0.000000, 0.000000], [-0.758390, -0.600084, -0.657987, -0.294671, -0.499141, 0.000000, 0.000000, 0.000000], [-0.961151, -0.218787, -0.135211, 0.230763, -0.221604, 0.000000, 0.000000, 0.000000], [-0.482780, -0.734347, -0.454189, -0.550613, 0.246610, 0.000000, 0.000000, 0.000000], [0.885567, 0.428269, 0.591306, 0.257105, 0.404598, 0.000000, 0.000000, 0.000000], [0.831701, 0.743340, 0.407875, 0.350805, 0.126515, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.974341, -1.391201, 1.435948, -3.362851, -0.113159, -1.774650, 2.703651, 3.349940]
pre_activation_std: [1.853358, 1.366606, 2.537351, 2.292896, 2.221799, 1.601903, 2.893259, 3.365551]
### 2
mean: [4.536845, -0.802238, -2.445089, -2.656745, 4.500004, 3.774379, -1.828790, 2.308419]
std: [4.779402, 2.711314, 2.198532, 2.935343, 5.379529, 3.673115, 1.311158, 2.691754]
fourier: [[81.594108, 83.436499, 83.613116, 89.303865, 408.316040], [46.074564, 49.724967, 51.802183, 58.919792, 72.201403], [38.849910, 38.887819, 39.033343, 43.864231, 220.058039], [48.348407, 50.746116, 54.904061, 55.984221, 239.107042], [90.373100, 91.901827, 96.814456, 98.607155, 405.000305], [61.351967, 63.869050, 64.231158, 65.741913, 339.694121], [20.888025, 21.366134, 23.596396, 26.758530, 164.591103], [47.142527, 48.526746, 51.054036, 51.739549, 207.757708]]
input_correlations: [[0.714453, 0.432524, 0.903963, 0.000000, -0.424283, -0.232535, 0.918608, 0.963884], [-0.564705, -0.455015, -0.976929, 0.000000, 0.616114, 0.166654, -0.894265, -0.834089], [-0.626011, -0.420630, -0.938247, 0.000000, 0.508179, 0.150333, -0.957557, -0.924339], [-0.585309, -0.379545, -0.904692, 0.000000, 0.398307, 0.208102, -0.981657, -0.947364], [0.730500, 0.436265, 0.902127, 0.000000, -0.474421, -0.198127, 0.912652, 0.956543], [0.723792, 0.406406, 0.878904, 0.000000, -0.416052, -0.219459, 0.928395, 0.976614], [-0.622129, -0.195732, -0.796876, 0.000000, 0.175129, 0.192022, -0.936567, -0.957087], [0.676334, 0.428454, 0.936734, 0.000000, -0.484417, -0.187061, 0.927744, 0.925863]]
pre_activation_mean: [4.536845, -0.802238, -2.445089, -2.656745, 4.500004, 3.774379, -1.828790, 2.308419]
pre_activation_std: [4.779402, 2.711314, 2.198532, 2.935343, 5.379529, 3.673115, 1.311158, 2.691754]
### 4
mean: [6.085322, -5.251182, -0.326369, 3.330681, -3.916233, 4.272306, 1.743471, 5.646188]
std: [7.827550, 4.727134, 0.410060, 4.008132, 4.041632, 5.471199, 0.506044, 6.704817]
fourier: [[131.423329, 135.718202, 143.375670, 144.217650, 547.679100], [80.981679, 81.140180, 82.779144, 85.084267, 472.606312], [6.940125, 7.127479, 7.604225, 8.733117, 29.373186], [67.789416, 68.724805, 73.029452, 74.795645, 299.761337], [68.607786, 71.046703, 71.921774, 74.632541, 352.460927], [92.641253, 94.156431, 100.620832, 101.180429, 384.507498], [6.887760, 7.072667, 7.999611, 11.235141, 156.912412], [112.613680, 117.326808, 122.424994, 124.085529, 508.156945]]
input_correlations: [[0.998185, -0.659699, 0.000000, -0.355491, 0.999212, 0.994646, 0.000000, 0.994701], [-0.997441, 0.592624, 0.000000, 0.354156, -0.996896, -0.997735, 0.000000, -0.989901], [0.935819, -0.760691, 0.000000, -0.240944, 0.954471, 0.927207, 0.000000, 0.967070], [0.998140, -0.667213, 0.000000, -0.382761, 0.997593, 0.995735, 0.000000, 0.991430], [-0.999236, 0.619857, 0.000000, 0.355350, -0.998323, -0.995904, 0.000000, -0.993897], [0.997480, -0.661471, 0.000000, -0.357891, 0.999035, 0.994648, 0.000000, 0.995215], [0.763773, -0.020920, 0.000000, -0.317576, 0.746267, 0.794487, 0.000000, 0.705668], [0.998296, -0.654531, 0.000000, -0.351147, 0.999325, 0.993773, 0.000000, 0.995488]]
pre_activation_mean: [6.085322, -5.251182, -0.326369, 3.330681, -3.916233, 4.272306, 1.743471, 5.646188]
pre_activation_std: [7.827550, 4.727134, 0.410060, 4.008132, 4.041632, 5.471199, 0.506044, 6.704817]
### 6
mean: [10.785200, -2.468065, -3.171254, -5.079703, 1.278832, 10.500355, -2.194847, 0.664014]
std: [14.169643, 4.953578, 5.073491, 5.571857, 0.887015, 13.548978, 2.330288, 1.238164]
fourier: [[237.921900, 250.605671, 256.718026, 260.205860, 970.667973], [83.424319, 88.156355, 89.691557, 92.754988, 222.125801], [85.668852, 89.986548, 92.186416, 95.171922, 285.412890], [93.320098, 97.773608, 101.385643, 101.715682, 457.173307], [15.206953, 16.262130, 16.386272, 18.505537, 115.094872], [227.439271, 239.470572, 245.278201, 248.288817, 945.031846], [39.140681, 41.451654, 41.988714, 42.071535, 197.536265], [21.550713, 21.696169, 22.484271, 24.813854, 59.761230]]
input_correlations: [[0.999913, 0.000000, 0.900739, 0.999325, 0.000000, 0.999843, 0.729146, 0.999817], [-0.999079, 0.000000, -0.897752, -0.998307, 0.000000, -0.999116, -0.706454, -0.998840], [-0.999076, 0.000000, -0.895098, -0.998476, 0.000000, -0.999110, -0.706650, -0.998869], [-0.999795, 0.000000, -0.898550, -0.999658, 0.000000, -0.999666, -0.736638, -0.999892], [-0.945708, 0.000000, -0.827364, -0.942620, 0.000000, -0.945909, -0.478443, -0.945783], [0.999948, 0.000000, 0.900838, 0.999370, 0.000000, 0.999869, 0.731427, 0.999825], [-0.999713, 0.000000, -0.908724, -0.998450, 0.000000, -0.999599, -0.745050, -0.999604], [-0.982595, 0.000000, -0.877025, -0.980034, 0.000000, -0.983238, -0.606502, -0.980973]]
pre_activation_mean: [10.785200, -2.468065, -3.171254, -5.079703, 1.278832, 10.500355, -2.194847, 0.664014]
pre_activation_std: [14.169643, 4.953578, 5.073491, 5.571857, 0.887015, 13.548978, 2.330288, 1.238164]
### 8
mean: [-16.577005]
std: [24.293806]
fourier: [[408.134122, 433.890306, 439.346639, 447.197413, 1491.930587]]
input_correlations: [[-0.999827, 0.608098, 0.540612, 0.000000, 0.916761, -0.999821, 0.000000, 0.858935]]
pre_activation_mean: [-16.577005]
pre_activation_std: [24.293806]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
0.399408,
0.738667,
-0.623539,
0.037997,
0.005305
],
[
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],
[
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],
[
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],
[
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-0.138088
],
[
-0.281585,
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-0.392373,
0.402473
],
[
1.089681,
0.033956,
0.458365,
0.358412,
0.253728
],
[
1.135098,
0.741411,
0.193434,
0.414221,
-0.108193
]
],
"network.0.bias": [
0.345763,
-0.158146,
-0.269494,
-0.213584,
0.47711,
0.113608,
-0.753271,
-0.572541
],
"network.2.weight": [
[
0.697768,
0.478955,
0.843852,
-0.020895,
0.11943,
-0.429388,
0.228752,
0.509333
],
[
-0.370702,
0.051251,
-0.88673,
-0.221051,
0.506841,
0.352201,
-0.112836,
0.050273
],
[
-0.280717,
-0.178094,
-0.287021,
-0.081871,
0.214518,
-0.227722,
-0.389106,
-0.055849
],
[
-0.03444,
-0.446774,
-0.05934,
0.206612,
0.147481,
0.114255,
-0.639476,
-0.295387
],
[
0.966776,
0.446852,
0.862441,
0.136673,
-0.259032,
-0.181257,
0.37707,
0.44126
],
[
0.512355,
0.356496,
0.311468,
-0.114707,
-0.084908,
-0.290932,
0.405885,
0.417766
],
[
-0.222595,
0.47595,
-0.060643,
-0.024662,
-0.436002,
-0.373594,
-0.322559,
-0.079886
],
[
0.701158,
-0.04426,
0.61301,
0.11372,
0.082374,
-0.174117,
0.374579,
-0.096412
]
],
"network.2.bias": [
-0.253164,
0.862964,
-0.472945,
0.203591,
-0.55101,
0.093787,
0.049446,
-0.371245
],
"network.4.weight": [
[
0.442453,
-0.552119,
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0.274365,
0.583972,
0.346474,
-0.128507,
0.427555
],
[
9.1e-05,
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0.032097,
0.167259,
-0.278988,
-0.605708,
-0.085468,
-0.453946
],
[
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-0.110241,
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0.038765,
0.179048,
0.019005,
-0.044361,
0.187832
],
[
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0.220886,
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0.171086,
0.339388,
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0.015393
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[
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0.02954,
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[
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0.456563,
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0.497771
],
[
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0.554963,
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-0.110104,
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0.374764,
0.051817,
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],
[
0.517041,
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-0.122706,
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0.61003,
-0.05789,
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0.41303
]
],
"network.4.bias": [
-0.582099,
-0.338793,
-0.470818,
-0.014747,
0.005137,
-0.371595,
0.721784,
-0.07498
],
"network.6.weight": [
[
0.7228,
0.377089,
0.054631,
0.248697,
0.039426,
0.600084,
-0.387226,
0.681468
],
[
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-0.230742,
-0.110172,
0.110469,
-0.408435,
0.618853,
-0.0525
],
[
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0.20971,
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0.19124,
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0.599592,
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],
[
0.014364,
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0.297334,
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],
[
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0.042639,
0.328833,
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0.077079,
0.820722,
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],
[
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],
[
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0.278929,
-0.015306,
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],
[
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0.608422,
0.375001
]
],
"network.6.bias": [
-0.415476,
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0.1502,
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-0.396994,
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],
"network.8.weight": [
[
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0.508804,
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-0.955818,
0.100216,
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]
],
"network.8.bias": [
0.404593
]
}
## Activation Signature
### 0
mean: [11.018291, 0.557894, 0.315318, 0.000000, 1.341929, 10.666611, 0.000000, 0.968719]
std: [13.981732, 0.713713, 0.463184, 0.000000, 0.765469, 13.414409, 0.000000, 0.698536]
fourier: [[235.848032, 249.491556, 251.236698, 254.190842, 991.646210], [12.036465, 14.026297, 14.734722, 15.648911, 50.210450], [7.153558, 8.338510, 9.708403, 11.087148, 28.378664], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [13.498956, 13.698407, 14.588377, 16.949226, 120.773616], [225.746527, 238.838436, 241.144587, 244.013836, 959.994858], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [11.473562, 11.650437, 12.751759, 14.558978, 87.184681]]
input_correlations: [[0.474054, 0.750909, -0.350571, 0.258146, -0.050046, 0.000000, 0.000000, 0.000000], [0.484185, -0.456221, -0.296346, -0.508175, -0.306687, 0.000000, 0.000000, 0.000000], [0.930312, 0.254728, 0.597813, -0.209801, 0.193664, 0.000000, 0.000000, 0.000000], [-0.758390, -0.600084, -0.657987, -0.294671, -0.499141, 0.000000, 0.000000, 0.000000], [-0.961151, -0.218787, -0.135211, 0.230763, -0.221604, 0.000000, 0.000000, 0.000000], [-0.482780, -0.734347, -0.454189, -0.550613, 0.246610, 0.000000, 0.000000, 0.000000], [0.885567, 0.428269, 0.591306, 0.257105, 0.404598, 0.000000, 0.000000, 0.000000], [0.831701, 0.743340, 0.407875, 0.350805, 0.126515, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.974341, -1.391201, 1.435948, -3.362851, -0.113159, -1.774650, 2.703651, 3.349940]
pre_activation_std: [1.853358, 1.366606, 2.537351, 2.292896, 2.221799, 1.601903, 2.893259, 3.365551]
### 2
mean: [4.536845, -0.802238, -2.445089, -2.656745, 4.500004, 3.774379, -1.828790, 2.308419]
std: [4.779402, 2.711314, 2.198532, 2.935343, 5.379529, 3.673115, 1.311158, 2.691754]
fourier: [[81.594108, 83.436499, 83.613116, 89.303865, 408.316040], [46.074564, 49.724967, 51.802183, 58.919792, 72.201403], [38.849910, 38.887819, 39.033343, 43.864231, 220.058039], [48.348407, 50.746116, 54.904061, 55.984221, 239.107042], [90.373100, 91.901827, 96.814456, 98.607155, 405.000305], [61.351967, 63.869050, 64.231158, 65.741913, 339.694121], [20.888025, 21.366134, 23.596396, 26.758530, 164.591103], [47.142527, 48.526746, 51.054036, 51.739549, 207.757708]]
input_correlations: [[0.714453, 0.432524, 0.903963, 0.000000, -0.424283, -0.232535, 0.918608, 0.963884], [-0.564705, -0.455015, -0.976929, 0.000000, 0.616114, 0.166654, -0.894265, -0.834089], [-0.626011, -0.420630, -0.938247, 0.000000, 0.508179, 0.150333, -0.957557, -0.924339], [-0.585309, -0.379545, -0.904692, 0.000000, 0.398307, 0.208102, -0.981657, -0.947364], [0.730500, 0.436265, 0.902127, 0.000000, -0.474421, -0.198127, 0.912652, 0.956543], [0.723792, 0.406406, 0.878904, 0.000000, -0.416052, -0.219459, 0.928395, 0.976614], [-0.622129, -0.195732, -0.796876, 0.000000, 0.175129, 0.192022, -0.936567, -0.957087], [0.676334, 0.428454, 0.936734, 0.000000, -0.484417, -0.187061, 0.927744, 0.925863]]
pre_activation_mean: [4.536845, -0.802238, -2.445089, -2.656745, 4.500004, 3.774379, -1.828790, 2.308419]
pre_activation_std: [4.779402, 2.711314, 2.198532, 2.935343, 5.379529, 3.673115, 1.311158, 2.691754]
### 4
mean: [6.085322, -5.251182, -0.326369, 3.330681, -3.916233, 4.272306, 1.743471, 5.646188]
std: [7.827550, 4.727134, 0.410060, 4.008132, 4.041632, 5.471199, 0.506044, 6.704817]
fourier: [[131.423329, 135.718202, 143.375670, 144.217650, 547.679100], [80.981679, 81.140180, 82.779144, 85.084267, 472.606312], [6.940125, 7.127479, 7.604225, 8.733117, 29.373186], [67.789416, 68.724805, 73.029452, 74.795645, 299.761337], [68.607786, 71.046703, 71.921774, 74.632541, 352.460927], [92.641253, 94.156431, 100.620832, 101.180429, 384.507498], [6.887760, 7.072667, 7.999611, 11.235141, 156.912412], [112.613680, 117.326808, 122.424994, 124.085529, 508.156945]]
input_correlations: [[0.998185, -0.659699, 0.000000, -0.355491, 0.999212, 0.994646, 0.000000, 0.994701], [-0.997441, 0.592624, 0.000000, 0.354156, -0.996896, -0.997735, 0.000000, -0.989901], [0.935819, -0.760691, 0.000000, -0.240944, 0.954471, 0.927207, 0.000000, 0.967070], [0.998140, -0.667213, 0.000000, -0.382761, 0.997593, 0.995735, 0.000000, 0.991430], [-0.999236, 0.619857, 0.000000, 0.355350, -0.998323, -0.995904, 0.000000, -0.993897], [0.997480, -0.661471, 0.000000, -0.357891, 0.999035, 0.994648, 0.000000, 0.995215], [0.763773, -0.020920, 0.000000, -0.317576, 0.746267, 0.794487, 0.000000, 0.705668], [0.998296, -0.654531, 0.000000, -0.351147, 0.999325, 0.993773, 0.000000, 0.995488]]
pre_activation_mean: [6.085322, -5.251182, -0.326369, 3.330681, -3.916233, 4.272306, 1.743471, 5.646188]
pre_activation_std: [7.827550, 4.727134, 0.410060, 4.008132, 4.041632, 5.471199, 0.506044, 6.704817]
### 6
mean: [10.785200, -2.468065, -3.171254, -5.079703, 1.278832, 10.500355, -2.194847, 0.664014]
std: [14.169643, 4.953578, 5.073491, 5.571857, 0.887015, 13.548978, 2.330288, 1.238164]
fourier: [[237.921900, 250.605671, 256.718026, 260.205860, 970.667973], [83.424319, 88.156355, 89.691557, 92.754988, 222.125801], [85.668852, 89.986548, 92.186416, 95.171922, 285.412890], [93.320098, 97.773608, 101.385643, 101.715682, 457.173307], [15.206953, 16.262130, 16.386272, 18.505537, 115.094872], [227.439271, 239.470572, 245.278201, 248.288817, 945.031846], [39.140681, 41.451654, 41.988714, 42.071535, 197.536265], [21.550713, 21.696169, 22.484271, 24.813854, 59.761230]]
input_correlations: [[0.999913, 0.000000, 0.900739, 0.999325, 0.000000, 0.999843, 0.729146, 0.999817], [-0.999079, 0.000000, -0.897752, -0.998307, 0.000000, -0.999116, -0.706454, -0.998840], [-0.999076, 0.000000, -0.895098, -0.998476, 0.000000, -0.999110, -0.706650, -0.998869], [-0.999795, 0.000000, -0.898550, -0.999658, 0.000000, -0.999666, -0.736638, -0.999892], [-0.945708, 0.000000, -0.827364, -0.942620, 0.000000, -0.945909, -0.478443, -0.945783], [0.999948, 0.000000, 0.900838, 0.999370, 0.000000, 0.999869, 0.731427, 0.999825], [-0.999713, 0.000000, -0.908724, -0.998450, 0.000000, -0.999599, -0.745050, -0.999604], [-0.982595, 0.000000, -0.877025, -0.980034, 0.000000, -0.983238, -0.606502, -0.980973]]
pre_activation_mean: [10.785200, -2.468065, -3.171254, -5.079703, 1.278832, 10.500355, -2.194847, 0.664014]
pre_activation_std: [14.169643, 4.953578, 5.073491, 5.571857, 0.887015, 13.548978, 2.330288, 1.238164]
### 8
mean: [-16.577005]
std: [24.293806]
fourier: [[408.134122, 433.890306, 439.346639, 447.197413, 1491.930587]]
input_correlations: [[-0.999827, 0.608098, 0.540612, 0.000000, 0.916761, -0.999821, 0.000000, 0.858935]]
pre_activation_mean: [-16.577005]
pre_activation_std: [24.293806]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 11.018290519714355, "std": 13.981732368469238, "fourier": [235.8480315280892, 249.4915557703656, 251.23669790169276, 254.19084177179474, 991.6462097465992], "input_correlations": [0.47405404382942845, 0.750908663976941, -0.3505714217859555, 0.25814610212112993, -0.050046107050663806, 0.0, 0.0, 0.0], "pre_activation_mean": 0.974341094493866, "pre_activation_std": 1.8533583879470825}, "1": {"mean": 0.5578938722610474, "std": 0.7137129306793213, "fourier": [12.03646480117005, 14.026297485929359, 14.73472182184935, 15.648911049378544, 50.21044999361038], "input_correlations": [0.48418492057286505, -0.4562213406614782, -0.2963460195020627, -0.5081751214028951, -0.30668685404369245, 0.0, 0.0, 0.0], "pre_activation_mean": -1.3912009000778198, "pre_activation_std": 1.3666056394577026}, "2": {"mean": 0.3153184950351715, "std": 0.46318408846855164, "fourier": [7.153557993324296, 8.33851021547879, 9.708402999454544, 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"std": 24.293806076049805, "fourier": [408.13412172381874, 433.8903060140857, 439.3466387016804, 447.19741292505904, 1491.9305868148804], "input_correlations": [-0.9998270521520748, 0.6080981782726415, 0.5406118125072562, 0.0, 0.9167606172854735, -0.9998206023189998, 0.0, 0.8589354411849908], "pre_activation_mean": -16.57700538635254, "pre_activation_std": 24.293806076049805}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.399408, 0.738667, -0.623539, 0.037997, 0.005305], [0.568227, -0.43318, -0.250498, -0.143271, -0.259731], [1.03641, -0.062533, 0.456397, -0.191716, -0.010218], [-0.560615, -0.370183, -0.43452, -0.187145, -0.379517], [-1.089556, 0.001838, 0.230451, 0.210403, -0.138088], [-0.281585, -0.319909, -0.291953, -0.392373, 0.402473], [1.089681, 0.033956, 0.458365, 0.358412, 0.253728], [1.135098, 0.741411, 0.193434, 0.414221, -0.108193]], "network.0.bias": [0.345763, -0.158146, -0.269494, -0.213584, 0.47711, 0.113608, -0.753271, -0.572541], "network.2.weight": [[0.697768, 0.478955, 0.843852, -0.020895, 0.11943, -0.429388, 0.228752, 0.509333], [-0.370702, 0.051251, -0.88673, -0.221051, 0.506841, 0.352201, -0.112836, 0.050273], [-0.280717, -0.178094, -0.287021, -0.081871, 0.214518, -0.227722, -0.389106, -0.055849], [-0.03444, -0.446774, -0.05934, 0.206612, 0.147481, 0.114255, -0.639476, -0.295387], [0.966776, 0.446852, 0.862441, 0.136673, -0.259032, -0.181257, 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0.955, "val_loss": 0.16419178247451782, "val_acc": 0.96}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.6503248810768127, "final_val_loss": 0.5797752737998962, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.46628350019454956, "final_val_loss": 0.16419178247451782, "initial_val_acc": 0.82, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 11}, "improvement": 0.45999999999999996, "first_improvement_epoch": 1}} |
30 | {"target_pattern": "vowel_consonant", "degraded_accuracy": 0.52, "improved_accuracy": 0.74, "improvement": 0.21999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9762, "learning_rate": 0.031389579657191864, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "vowel_consonant", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["vowel_consonant"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.160762, 0.064220, 0.723042, 0.133322, 0.019059, 0.566334, 0.086571]
std: [0.210032, 0.228720, 1.100780, 0.321820, 0.266581, 1.047340, 0.245547]
fourier: [[3.259765, 3.368880, 3.797862, 4.394775, 14.468597], [3.402936, 3.772663, 3.924318, 4.734009, 5.779832], [16.619929, 18.780907, 24.047858, 24.716994, 65.073797], [4.940119, 5.385410, 5.471561, 6.683720, 11.998943], [3.839936, 4.090165, 4.410889, 5.543076, 5.658968], [15.873628, 17.821807, 22.778356, 22.996956, 50.970106], [3.814200, 3.885908, 4.192381, 5.127306, 7.791407]]
input_correlations: [[-0.335720, -0.741846, -0.370458, -0.795300, -0.325708, 0.000000, 0.000000, 0.000000], [-0.132923, 0.498215, 0.269236, 0.718759, -0.414274, 0.000000, 0.000000, 0.000000], [0.522399, 0.211387, 0.924479, -0.292971, 0.160764, 0.000000, 0.000000, 0.000000], [-0.534852, 0.154891, 0.324322, -0.314615, 0.189788, 0.000000, 0.000000, 0.000000], [-0.160333, 0.367112, 0.002571, -0.615808, 0.004451, 0.000000, 0.000000, 0.000000], [-0.464587, -0.645764, -0.615981, -0.569235, 0.130226, 0.000000, 0.000000, 0.000000], [-0.231419, -0.240571, -0.827390, -0.139585, -0.704651, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.591440, 1.308195, 0.961492, -0.171338, -0.087841, -2.194561, -3.076488]
pre_activation_std: [1.017020, 0.974754, 1.129977, 1.395808, 0.873470, 1.497745, 2.090600]
### 2
mean: [0.165256, 0.478817, 0.249923, 0.265930, 0.209108, -0.324262, -0.692164]
std: [0.364423, 0.321544, 0.377567, 0.467243, 0.388276, 0.547141, 0.205770]
fourier: [[5.878905, 6.323497, 6.494543, 9.088114, 14.873023], [4.802209, 4.980378, 5.319191, 5.804807, 43.093554], [5.832873, 6.803148, 6.804061, 8.723180, 22.493061], [6.998390, 7.492942, 8.770561, 9.361965, 23.933683], [5.610568, 6.073110, 6.491304, 8.562467, 18.819754], [7.916922, 8.992358, 9.280896, 11.894649, 29.183569], [2.970348, 3.021677, 3.047433, 3.505396, 62.294742]]
input_correlations: [[-0.003750, -0.125497, -0.831152, 0.174996, 0.484274, 0.033807, -0.446320, 0.000000], [-0.476397, -0.737972, 0.610014, 0.144952, 0.051773, -0.183006, 0.167521, 0.000000], [0.040344, 0.014476, 0.420563, -0.607055, -0.850043, -0.033297, 0.133732, 0.000000], [0.097066, 0.459739, -0.046678, 0.760559, 0.748469, 0.269489, 0.200843, 0.000000], [0.293383, 0.689425, -0.422735, 0.338899, 0.330730, 0.197183, -0.072664, 0.000000], [0.106076, -0.109616, -0.971253, -0.539962, -0.183212, -0.131133, -0.671423, 0.000000], [-0.438803, -0.714435, -0.071485, 0.622847, 0.502521, -0.024742, 0.062307, 0.000000]]
pre_activation_mean: [0.165256, 0.478817, 0.249923, 0.265930, 0.209108, -0.324262, -0.692164]
pre_activation_std: [0.364423, 0.321544, 0.377567, 0.467243, 0.388276, 0.547141, 0.205770]
### 4
mean: [-0.125855, 0.181477, 0.359369, 0.411285, 0.305502, 0.048533, -0.209035]
std: [0.312658, 0.189385, 0.384260, 0.513385, 0.455697, 0.292338, 0.253305]
fourier: [[4.997629, 5.432393, 5.883180, 6.985853, 11.326927], [2.879348, 3.233030, 3.584403, 3.806077, 16.332957], [6.371539, 6.608655, 8.094742, 8.113514, 32.343181], [8.216614, 8.848771, 10.394289, 11.734469, 37.015609], [7.242452, 7.903486, 8.948385, 10.148492, 27.495147], [4.436242, 4.574350, 4.885712, 5.839719, 6.612664], [4.279658, 4.576376, 5.299915, 5.924725, 18.813171]]
input_correlations: [[-0.667636, 0.733906, 0.752159, -0.862926, -0.933292, -0.172445, -0.246773, 0.000000], [-0.412204, 0.252586, 0.593201, -0.989886, -0.746705, 0.276149, -0.397556, 0.000000], [-0.843962, 0.526519, 0.909721, -0.845705, -0.769087, -0.259687, -0.386138, 0.000000], [-0.744990, 0.731429, 0.857591, -0.819345, -0.895167, -0.270763, -0.268867, 0.000000], [-0.747089, 0.683519, 0.817469, -0.858105, -0.903591, -0.235674, -0.284325, 0.000000], [-0.730732, 0.655157, 0.847857, -0.884346, -0.881370, -0.139689, -0.313559, 0.000000], [-0.902444, 0.621156, 0.924916, -0.716545, -0.709209, -0.439042, -0.326416, 0.000000]]
pre_activation_mean: [-0.125855, 0.181477, 0.359369, 0.411285, 0.305502, 0.048533, -0.209035]
pre_activation_std: [0.312658, 0.189385, 0.384260, 0.513385, 0.455697, 0.292338, 0.253305]
### 6
mean: [0.045591, 0.238636, 0.057494, 0.456592, 0.096399, 0.428333, 0.673158]
std: [0.349553, 0.552253, 0.457291, 0.199730, 0.520521, 0.581419, 0.658442]
fourier: [[5.349602, 5.531488, 5.593496, 7.229556, 7.954259], [8.751695, 9.113204, 11.747569, 12.527801, 21.477246], [6.984960, 7.224315, 7.262848, 9.635611, 10.422502], [3.167175, 3.224802, 4.183924, 4.541986, 41.093248], [8.270953, 8.292007, 8.675870, 10.838647, 11.864679], [9.272466, 9.528889, 12.357790, 13.175516, 38.549929], [10.427659, 10.745918, 13.876341, 14.958356, 60.584245]]
input_correlations: [[0.970294, 0.735000, 0.969107, 0.991808, 0.996052, 0.993948, 0.927958, 0.000000], [0.964729, 0.687454, 0.977947, 0.995813, 0.993940, 0.992358, 0.953807, 0.000000], [0.978088, 0.684051, 0.963159, 0.998225, 0.998005, 0.992789, 0.943187, 0.000000], [0.971535, 0.707168, 0.971418, 0.995247, 0.997566, 0.992859, 0.940380, 0.000000], [0.975404, 0.711436, 0.966368, 0.995516, 0.997893, 0.993218, 0.935950, 0.000000], [0.967691, 0.674973, 0.975213, 0.996480, 0.996182, 0.989273, 0.954277, 0.000000], [0.966590, 0.702330, 0.976475, 0.995066, 0.996011, 0.992677, 0.945638, 0.000000]]
pre_activation_mean: [0.045591, 0.238636, 0.057494, 0.456592, 0.096399, 0.428333, 0.673158]
pre_activation_std: [0.349553, 0.552253, 0.457291, 0.199730, 0.520521, 0.581419, 0.658442]
### 8
mean: [0.888565, 0.250930, 0.365682, -0.107092, -0.665427, -0.325950, -0.488043]
std: [1.060918, 0.762839, 0.878887, 0.793433, 1.132482, 0.149231, 1.041959]
fourier: [[16.603459, 17.827103, 22.923970, 23.999870, 79.970833], [11.951170, 12.858080, 16.496729, 17.247016, 22.583732], [13.742600, 14.762733, 18.986214, 19.873297, 32.911357], [11.657672, 12.403812, 13.322325, 17.143178, 17.891951], [17.739528, 19.022779, 24.492761, 25.533549, 59.888440], [2.337164, 2.484394, 3.232576, 3.346604, 29.335496], [16.292996, 17.601358, 22.533184, 23.548436, 43.923862]]
input_correlations: [[0.997887, 0.997749, 0.994029, 0.989946, 0.995307, 0.999380, 0.996740, 0.000000], [0.997381, 0.997877, 0.993610, 0.989752, 0.994857, 0.999564, 0.996908, 0.000000], [0.998004, 0.997966, 0.994371, 0.989426, 0.995637, 0.999325, 0.996458, 0.000000], [-0.998368, -0.998704, -0.995503, -0.987732, -0.996586, -0.998951, -0.995298, 0.000000], [-0.998409, -0.998712, -0.996138, -0.987066, -0.997124, -0.998935, -0.994740, 0.000000], [0.998070, 0.998526, 0.998984, 0.980327, 0.999272, 0.996344, 0.989266, 0.000000], [-0.997082, -0.998255, -0.994133, -0.988062, -0.995445, -0.999661, -0.996271, 0.000000]]
pre_activation_mean: [0.888565, 0.250930, 0.365682, -0.107092, -0.665427, -0.325950, -0.488043]
pre_activation_std: [1.060918, 0.762839, 0.878887, 0.793433, 1.132482, 0.149231, 1.041959]
### 10
mean: [0.191918, -0.214414, 0.747601, -0.170906, -0.080957, 0.527973, -0.384724]
std: [0.369030, 0.731575, 1.133486, 0.860519, 0.396409, 1.125351, 1.048388]
fourier: [[5.844732, 5.984871, 7.596504, 8.233443, 17.272588], [11.481612, 11.931485, 15.452344, 16.679793, 19.297217], [17.650279, 19.087994, 24.518420, 25.652366, 67.284070], [13.711786, 13.803440, 15.381579, 17.939184, 19.445066], [5.968879, 6.761021, 7.286166, 8.658339, 9.014137], [17.623765, 18.955200, 24.326207, 25.311122, 47.517576], [16.472229, 17.483556, 22.517051, 23.787673, 34.625180]]
input_correlations: [[-0.957854, -0.920333, -0.926003, 0.846686, 0.582268, -0.896100, 0.690048, 0.000000], [-0.975604, -0.941979, -0.947828, 0.822856, 0.521825, -0.912111, 0.640245, 0.000000], [0.997568, 0.982417, 0.985721, -0.726818, -0.388956, 0.958047, -0.515263, 0.000000], [-0.965757, -0.929199, -0.935121, 0.839680, 0.558176, -0.901749, 0.671029, 0.000000], [0.999797, 0.989352, 0.992568, -0.690686, -0.325496, 0.961195, -0.459101, 0.000000], [0.998053, 0.985633, 0.988396, -0.713737, -0.377186, 0.963661, -0.502526, 0.000000], [-0.992376, -0.971252, -0.975261, 0.761074, 0.438398, -0.946227, 0.561209, 0.000000]]
pre_activation_mean: [0.191918, -0.214414, 0.747601, -0.170906, -0.080957, 0.527973, -0.384724]
pre_activation_std: [0.369030, 0.731575, 1.133486, 0.860519, 0.396409, 1.125351, 1.048388]
### 12
mean: [-0.150717]
std: [0.964561]
fourier: [[14.306353, 15.325099, 15.715659, 20.315410, 21.841415]]
input_correlations: [[0.932822, 0.757995, -0.959843, 0.745469, -0.906704, -0.942240, 0.698424, 0.000000]]
pre_activation_mean: [-0.150717]
pre_activation_std: [0.964561]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| vowel_consonant | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
"network.2.bias": [
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"network.4.weight": [
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0.083851,
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[
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[
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0.234758,
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"network.8.weight": [
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"network.12.weight": [
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"network.12.bias": [
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]
}
## Activation Signature
### 0
mean: [0.160762, 0.064220, 0.723042, 0.133322, 0.019059, 0.566334, 0.086571]
std: [0.210032, 0.228720, 1.100780, 0.321820, 0.266581, 1.047340, 0.245547]
fourier: [[3.259765, 3.368880, 3.797862, 4.394775, 14.468597], [3.402936, 3.772663, 3.924318, 4.734009, 5.779832], [16.619929, 18.780907, 24.047858, 24.716994, 65.073797], [4.940119, 5.385410, 5.471561, 6.683720, 11.998943], [3.839936, 4.090165, 4.410889, 5.543076, 5.658968], [15.873628, 17.821807, 22.778356, 22.996956, 50.970106], [3.814200, 3.885908, 4.192381, 5.127306, 7.791407]]
input_correlations: [[-0.335720, -0.741846, -0.370458, -0.795300, -0.325708, 0.000000, 0.000000, 0.000000], [-0.132923, 0.498215, 0.269236, 0.718759, -0.414274, 0.000000, 0.000000, 0.000000], [0.522399, 0.211387, 0.924479, -0.292971, 0.160764, 0.000000, 0.000000, 0.000000], [-0.534852, 0.154891, 0.324322, -0.314615, 0.189788, 0.000000, 0.000000, 0.000000], [-0.160333, 0.367112, 0.002571, -0.615808, 0.004451, 0.000000, 0.000000, 0.000000], [-0.464587, -0.645764, -0.615981, -0.569235, 0.130226, 0.000000, 0.000000, 0.000000], [-0.231419, -0.240571, -0.827390, -0.139585, -0.704651, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.591440, 1.308195, 0.961492, -0.171338, -0.087841, -2.194561, -3.076488]
pre_activation_std: [1.017020, 0.974754, 1.129977, 1.395808, 0.873470, 1.497745, 2.090600]
### 2
mean: [0.165256, 0.478817, 0.249923, 0.265930, 0.209108, -0.324262, -0.692164]
std: [0.364423, 0.321544, 0.377567, 0.467243, 0.388276, 0.547141, 0.205770]
fourier: [[5.878905, 6.323497, 6.494543, 9.088114, 14.873023], [4.802209, 4.980378, 5.319191, 5.804807, 43.093554], [5.832873, 6.803148, 6.804061, 8.723180, 22.493061], [6.998390, 7.492942, 8.770561, 9.361965, 23.933683], [5.610568, 6.073110, 6.491304, 8.562467, 18.819754], [7.916922, 8.992358, 9.280896, 11.894649, 29.183569], [2.970348, 3.021677, 3.047433, 3.505396, 62.294742]]
input_correlations: [[-0.003750, -0.125497, -0.831152, 0.174996, 0.484274, 0.033807, -0.446320, 0.000000], [-0.476397, -0.737972, 0.610014, 0.144952, 0.051773, -0.183006, 0.167521, 0.000000], [0.040344, 0.014476, 0.420563, -0.607055, -0.850043, -0.033297, 0.133732, 0.000000], [0.097066, 0.459739, -0.046678, 0.760559, 0.748469, 0.269489, 0.200843, 0.000000], [0.293383, 0.689425, -0.422735, 0.338899, 0.330730, 0.197183, -0.072664, 0.000000], [0.106076, -0.109616, -0.971253, -0.539962, -0.183212, -0.131133, -0.671423, 0.000000], [-0.438803, -0.714435, -0.071485, 0.622847, 0.502521, -0.024742, 0.062307, 0.000000]]
pre_activation_mean: [0.165256, 0.478817, 0.249923, 0.265930, 0.209108, -0.324262, -0.692164]
pre_activation_std: [0.364423, 0.321544, 0.377567, 0.467243, 0.388276, 0.547141, 0.205770]
### 4
mean: [-0.125855, 0.181477, 0.359369, 0.411285, 0.305502, 0.048533, -0.209035]
std: [0.312658, 0.189385, 0.384260, 0.513385, 0.455697, 0.292338, 0.253305]
fourier: [[4.997629, 5.432393, 5.883180, 6.985853, 11.326927], [2.879348, 3.233030, 3.584403, 3.806077, 16.332957], [6.371539, 6.608655, 8.094742, 8.113514, 32.343181], [8.216614, 8.848771, 10.394289, 11.734469, 37.015609], [7.242452, 7.903486, 8.948385, 10.148492, 27.495147], [4.436242, 4.574350, 4.885712, 5.839719, 6.612664], [4.279658, 4.576376, 5.299915, 5.924725, 18.813171]]
input_correlations: [[-0.667636, 0.733906, 0.752159, -0.862926, -0.933292, -0.172445, -0.246773, 0.000000], [-0.412204, 0.252586, 0.593201, -0.989886, -0.746705, 0.276149, -0.397556, 0.000000], [-0.843962, 0.526519, 0.909721, -0.845705, -0.769087, -0.259687, -0.386138, 0.000000], [-0.744990, 0.731429, 0.857591, -0.819345, -0.895167, -0.270763, -0.268867, 0.000000], [-0.747089, 0.683519, 0.817469, -0.858105, -0.903591, -0.235674, -0.284325, 0.000000], [-0.730732, 0.655157, 0.847857, -0.884346, -0.881370, -0.139689, -0.313559, 0.000000], [-0.902444, 0.621156, 0.924916, -0.716545, -0.709209, -0.439042, -0.326416, 0.000000]]
pre_activation_mean: [-0.125855, 0.181477, 0.359369, 0.411285, 0.305502, 0.048533, -0.209035]
pre_activation_std: [0.312658, 0.189385, 0.384260, 0.513385, 0.455697, 0.292338, 0.253305]
### 6
mean: [0.045591, 0.238636, 0.057494, 0.456592, 0.096399, 0.428333, 0.673158]
std: [0.349553, 0.552253, 0.457291, 0.199730, 0.520521, 0.581419, 0.658442]
fourier: [[5.349602, 5.531488, 5.593496, 7.229556, 7.954259], [8.751695, 9.113204, 11.747569, 12.527801, 21.477246], [6.984960, 7.224315, 7.262848, 9.635611, 10.422502], [3.167175, 3.224802, 4.183924, 4.541986, 41.093248], [8.270953, 8.292007, 8.675870, 10.838647, 11.864679], [9.272466, 9.528889, 12.357790, 13.175516, 38.549929], [10.427659, 10.745918, 13.876341, 14.958356, 60.584245]]
input_correlations: [[0.970294, 0.735000, 0.969107, 0.991808, 0.996052, 0.993948, 0.927958, 0.000000], [0.964729, 0.687454, 0.977947, 0.995813, 0.993940, 0.992358, 0.953807, 0.000000], [0.978088, 0.684051, 0.963159, 0.998225, 0.998005, 0.992789, 0.943187, 0.000000], [0.971535, 0.707168, 0.971418, 0.995247, 0.997566, 0.992859, 0.940380, 0.000000], [0.975404, 0.711436, 0.966368, 0.995516, 0.997893, 0.993218, 0.935950, 0.000000], [0.967691, 0.674973, 0.975213, 0.996480, 0.996182, 0.989273, 0.954277, 0.000000], [0.966590, 0.702330, 0.976475, 0.995066, 0.996011, 0.992677, 0.945638, 0.000000]]
pre_activation_mean: [0.045591, 0.238636, 0.057494, 0.456592, 0.096399, 0.428333, 0.673158]
pre_activation_std: [0.349553, 0.552253, 0.457291, 0.199730, 0.520521, 0.581419, 0.658442]
### 8
mean: [0.888565, 0.250930, 0.365682, -0.107092, -0.665427, -0.325950, -0.488043]
std: [1.060918, 0.762839, 0.878887, 0.793433, 1.132482, 0.149231, 1.041959]
fourier: [[16.603459, 17.827103, 22.923970, 23.999870, 79.970833], [11.951170, 12.858080, 16.496729, 17.247016, 22.583732], [13.742600, 14.762733, 18.986214, 19.873297, 32.911357], [11.657672, 12.403812, 13.322325, 17.143178, 17.891951], [17.739528, 19.022779, 24.492761, 25.533549, 59.888440], [2.337164, 2.484394, 3.232576, 3.346604, 29.335496], [16.292996, 17.601358, 22.533184, 23.548436, 43.923862]]
input_correlations: [[0.997887, 0.997749, 0.994029, 0.989946, 0.995307, 0.999380, 0.996740, 0.000000], [0.997381, 0.997877, 0.993610, 0.989752, 0.994857, 0.999564, 0.996908, 0.000000], [0.998004, 0.997966, 0.994371, 0.989426, 0.995637, 0.999325, 0.996458, 0.000000], [-0.998368, -0.998704, -0.995503, -0.987732, -0.996586, -0.998951, -0.995298, 0.000000], [-0.998409, -0.998712, -0.996138, -0.987066, -0.997124, -0.998935, -0.994740, 0.000000], [0.998070, 0.998526, 0.998984, 0.980327, 0.999272, 0.996344, 0.989266, 0.000000], [-0.997082, -0.998255, -0.994133, -0.988062, -0.995445, -0.999661, -0.996271, 0.000000]]
pre_activation_mean: [0.888565, 0.250930, 0.365682, -0.107092, -0.665427, -0.325950, -0.488043]
pre_activation_std: [1.060918, 0.762839, 0.878887, 0.793433, 1.132482, 0.149231, 1.041959]
### 10
mean: [0.191918, -0.214414, 0.747601, -0.170906, -0.080957, 0.527973, -0.384724]
std: [0.369030, 0.731575, 1.133486, 0.860519, 0.396409, 1.125351, 1.048388]
fourier: [[5.844732, 5.984871, 7.596504, 8.233443, 17.272588], [11.481612, 11.931485, 15.452344, 16.679793, 19.297217], [17.650279, 19.087994, 24.518420, 25.652366, 67.284070], [13.711786, 13.803440, 15.381579, 17.939184, 19.445066], [5.968879, 6.761021, 7.286166, 8.658339, 9.014137], [17.623765, 18.955200, 24.326207, 25.311122, 47.517576], [16.472229, 17.483556, 22.517051, 23.787673, 34.625180]]
input_correlations: [[-0.957854, -0.920333, -0.926003, 0.846686, 0.582268, -0.896100, 0.690048, 0.000000], [-0.975604, -0.941979, -0.947828, 0.822856, 0.521825, -0.912111, 0.640245, 0.000000], [0.997568, 0.982417, 0.985721, -0.726818, -0.388956, 0.958047, -0.515263, 0.000000], [-0.965757, -0.929199, -0.935121, 0.839680, 0.558176, -0.901749, 0.671029, 0.000000], [0.999797, 0.989352, 0.992568, -0.690686, -0.325496, 0.961195, -0.459101, 0.000000], [0.998053, 0.985633, 0.988396, -0.713737, -0.377186, 0.963661, -0.502526, 0.000000], [-0.992376, -0.971252, -0.975261, 0.761074, 0.438398, -0.946227, 0.561209, 0.000000]]
pre_activation_mean: [0.191918, -0.214414, 0.747601, -0.170906, -0.080957, 0.527973, -0.384724]
pre_activation_std: [0.369030, 0.731575, 1.133486, 0.860519, 0.396409, 1.125351, 1.048388]
### 12
mean: [-0.150717]
std: [0.964561]
fourier: [[14.306353, 15.325099, 15.715659, 20.315410, 21.841415]]
input_correlations: [[0.932822, 0.757995, -0.959843, 0.745469, -0.906704, -0.942240, 0.698424, 0.000000]]
pre_activation_mean: [-0.150717]
pre_activation_std: [0.964561]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
vowel_consonant | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.16076219081878662, "std": 0.21003223955631256, "fourier": [3.259765167710506, 3.3688797095802916, 3.7978617465212863, 4.3947749984174065, 14.468597473111004], "input_correlations": [-0.3357203121897168, -0.7418458423675502, -0.3704579790264397, -0.7952997372058068, -0.3257075730458704, 0.0, 0.0, 0.0], "pre_activation_mean": -1.5914403200149536, "pre_activation_std": 1.0170204639434814}, "1": {"mean": 0.0642203614115715, "std": 0.2287197858095169, "fourier": [3.4029360542022147, 3.7726626910922296, 3.9243181446802273, 4.7340086400694545, 5.7798323898459785], "input_correlations": [-0.13292291931687955, 0.49821491812646845, 0.2692359728445931, 0.7187590896259478, -0.4142739227075414, 0.0, 0.0, 0.0], "pre_activation_mean": 1.3081947565078735, "pre_activation_std": 0.9747539758682251}, "2": {"mean": 0.7230421304702759, "std": 1.1007797718048096, "fourier": [16.61992878143208, 18.780907371224824, 24.047857595027256, 24.71699425327489, 65.07379745971411], "input_correlations": [0.5223990794255557, 0.2113870864846479, 0.9244788151820363, -0.29297086438023945, 0.1607640514656875, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9614921808242798, "pre_activation_std": 1.1299766302108765}, "3": {"mean": 0.1333215981721878, "std": 0.32181987166404724, "fourier": [4.9401185753701045, 5.385409949888163, 5.471561335922676, 6.683720429111955, 11.998943363316357], "input_correlations": [-0.53485181351774, 0.15489131817067783, 0.3243216844594839, -0.3146148427194557, 0.18978830364017774, 0.0, 0.0, 0.0], "pre_activation_mean": -0.17133775353431702, "pre_activation_std": 1.395808458328247}, "4": {"mean": 0.01905881240963936, "std": 0.2665809392929077, "fourier": [3.8399357937118372, 4.0901647205606055, 4.410889265823953, 5.543075906624007, 5.658968160537815], "input_correlations": [-0.1603334190657524, 0.3671121995387331, 0.0025713180735967823, -0.6158083273759091, 0.004451257879821809, 0.0, 0.0, 0.0], "pre_activation_mean": -0.0878409743309021, "pre_activation_std": 0.8734696507453918}, "5": {"mean": 0.5663344860076904, "std": 1.0473397970199585, "fourier": [15.87362845478855, 17.82180658809892, 22.77835584970867, 22.99695605512123, 50.970106420107186], "input_correlations": [-0.4645869537937356, -0.645764203054327, -0.6159808913977202, -0.5692347476251473, 0.13022554280123, 0.0, 0.0, 0.0], "pre_activation_mean": -2.1945605278015137, "pre_activation_std": 1.4977450370788574}, "6": {"mean": 0.08657118678092957, "std": 0.2455471158027649, "fourier": [3.8141996713569197, 3.8859077104291737, 4.192380824709636, 5.127306276777255, 7.791407263430301], "input_correlations": [-0.23141929160415473, -0.24057057736195245, -0.8273904681139727, -0.13958530763554353, -0.7046508322447573, 0.0, 0.0, 0.0], "pre_activation_mean": -3.0764880180358887, "pre_activation_std": 2.090599536895752}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.16525579988956451, "std": 0.36442267894744873, "fourier": [5.878905454265893, 6.3234972213782745, 6.494543113916439, 9.088114197746455, 14.873022586107254], "input_correlations": [-0.00375022728904781, -0.12549697932652418, -0.8311517551259963, 0.17499605290216078, 0.4842742142624211, 0.03380652085385638, -0.44632006367417093, 0.0], "pre_activation_mean": 0.16525579988956451, "pre_activation_std": 0.36442267894744873}, "1": {"mean": 0.47881728410720825, "std": 0.32154446840286255, "fourier": [4.802208523001311, 4.980378357342179, 5.319190698928499, 5.804806700054317, 43.09355401992798], "input_correlations": [-0.4763972633679341, -0.7379715269502577, 0.6100142940381493, 0.1449519247614969, 0.051772900974419216, -0.18300561448603006, 0.16752072336196078, 0.0], "pre_activation_mean": 0.47881728410720825, "pre_activation_std": 0.32154446840286255}, "2": {"mean": 0.24992288649082184, "std": 0.37756720185279846, "fourier": [5.832873465676696, 6.80314784016385, 6.804060999214661, 8.723180494772613, 22.493060559034348], "input_correlations": [0.040344386929096886, 0.014475663325319812, 0.42056337194465393, -0.6070551743554388, -0.8500428264803428, -0.033296734920182834, 0.13373231514272643, 0.0], "pre_activation_mean": 0.24992288649082184, "pre_activation_std": 0.37756720185279846}, "3": {"mean": 0.26592978835105896, "std": 0.4672427773475647, "fourier": [6.998389926634425, 7.492941992464115, 8.770561473035167, 9.361964680671726, 23.933682665228844], "input_correlations": [0.09706556748141794, 0.45973863695038103, -0.04667797836217553, 0.7605592089254433, 0.7484686513076138, 0.26948918961871793, 0.20084289488493406, 0.0], "pre_activation_mean": 0.26592978835105896, "pre_activation_std": 0.4672427773475647}, "4": {"mean": 0.209108367562294, "std": 0.38827553391456604, "fourier": [5.610567756362544, 6.073110259030124, 6.491303536212666, 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[-0.331798, 0.253951, 0.234758, -0.410993, 0.246406, -0.597714, 0.033276]], "network.4.bias": [-0.077567, 0.351125, 0.505725, 0.316351, 0.472569, 0.131874, -0.261417], "network.6.weight": [[0.406475, 0.32249, 0.16034, -0.039997, 0.514155, 0.534109, 0.289331], [0.477091, 0.146167, 0.607239, 0.565637, 0.136506, 0.295211, 0.317535], [0.154239, 0.012987, 0.068678, 0.374141, 0.6879, 0.466899, 0.076684], [0.062561, 0.101131, 0.042369, -0.049373, 0.417556, 0.305258, 0.300861], [0.470201, 0.412738, 0.191578, 0.52417, 0.575163, -0.002446, 0.196424], [0.404997, -0.035046, 0.538718, 0.375402, 0.731899, 0.049805, 0.343278], [0.479534, 0.270071, 0.595847, 0.454604, 0.590035, 0.367797, 0.316053]], "network.6.bias": [-0.161678, -0.171311, -0.294006, 0.343866, -0.318869, -0.015186, 0.168245], "network.8.weight": [[0.24384, 0.347658, 0.331485, 0.29588, 0.48987, 0.318623, 0.600227], [0.018113, 0.507185, 0.292036, 0.148703, 0.102603, 0.202571, 0.465398], [0.516403, 0.26857, 0.291764, -0.057542, 0.289668, 0.273843, 0.535589], [-0.531802, -0.60815, -0.31085, 0.13342, -0.152872, 0.035343, -0.498556], [-0.392719, -0.299525, -0.586018, -0.204344, -0.581086, -0.561916, -0.344763], [0.010557, -0.105032, 0.359571, -0.053434, 0.049699, 0.096719, 0.039697], [-0.009525, -0.436827, -0.132081, 0.392318, -0.492856, -0.61973, -0.632774]], "network.8.bias": [0.115734, -0.313762, -0.205874, 0.366083, 0.057394, -0.388952, 0.18075], "network.10.weight": [[-0.052007, -0.229873, -0.121672, 0.05048, 0.268513, 0.21375, 0.521132], [-0.062667, -0.098385, -0.536441, 0.667257, -0.004852, -0.097687, 0.65259], [0.477994, 0.267889, 0.458809, -0.313052, -0.198391, 0.06035, -0.339137], [0.001225, -0.315958, -0.5283, 0.747502, 0.483932, -0.369761, 0.63526], [0.215864, -0.093574, 0.239137, -0.303085, 0.035731, 0.20199, 0.179146], [0.370141, 0.388714, 0.516831, -0.173259, -0.425297, 0.057413, -0.25397], [-0.272357, -0.505442, -0.334984, 0.575017, 0.276007, -0.449847, 0.39578]], "network.10.bias": [0.352103, -0.033867, 0.148715, -0.019727, -0.272557, -0.06215, -0.010809], "network.12.weight": [[0.345328, 0.133357, -0.202995, 0.545876, -0.138494, -0.434593, 0.384806]], "network.12.bias": [0.074651]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6849014759063721, "train_acc": 0.56, "val_loss": 0.699297308921814, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6866418719291687, "train_acc": 0.56, "val_loss": 0.6972241997718811, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6838003993034363, "train_acc": 0.56, "val_loss": 0.6891642808914185, "val_acc": 0.52}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6748336553573608, "train_acc": 0.56, "val_loss": 0.6910244822502136, "val_acc": 0.52}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6668629050254822, "train_acc": 0.56, "val_loss": 0.6363170742988586, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6479059457778931, "train_acc": 0.575, "val_loss": 0.5980748534202576, "val_acc": 0.62}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.5970343351364136, "train_acc": 0.655, "val_loss": 0.8418800234794617, "val_acc": 0.62}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.6319161653518677, "train_acc": 0.66, "val_loss": 0.6247496604919434, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.6332397162914276, "train_acc": 0.66, "val_loss": 0.6136185526847839, "val_acc": 0.74}], "summary": {"total_epochs": 9, "degraded_epochs": 5, "improved_epochs": 4, "patterns": ["vowel_consonant"], "degraded_stage": {"initial_val_loss": 0.699297308921814, "final_val_loss": 0.6363170742988586, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.5980748534202576, "final_val_loss": 0.6136185526847839, "initial_val_acc": 0.62, "final_val_acc": 0.74, "best_val_acc": 0.74, "best_epoch": 8}, "improvement": 0.21999999999999997, "first_improvement_epoch": 4}} |
31 | {"target_pattern": "starts_with", "degraded_accuracy": 0.52, "improved_accuracy": 0.82, "improvement": 0.29999999999999993, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9304, "learning_rate": 0.04983236602447656, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [0.122977, 10.093886, 0.068797, 0.317515, -0.046406]
std: [0.227502, 14.272077, 0.154651, 0.617321, 0.059369]
fourier: [[3.480358, 3.881356, 4.280426, 4.883963, 11.067972], [232.773512, 241.922413, 244.097357, 270.877588, 908.449755], [2.392604, 2.431679, 2.501037, 2.882198, 6.191703], [10.229238, 10.892285, 11.077445, 11.253417, 28.576339], [0.921747, 0.936959, 1.057610, 1.252369, 4.176506]]
input_correlations: [[0.642832, 0.522767, 0.247003, 0.019975, -0.569295, 0.000000, 0.000000, 0.000000], [-0.641590, 0.142798, 0.163219, 0.551489, 0.374847, 0.000000, 0.000000, 0.000000], [0.925839, 0.496679, 0.308270, -0.022909, -0.156078, 0.000000, 0.000000, 0.000000], [0.926768, 0.643062, 0.376865, 0.186333, 0.147158, 0.000000, 0.000000, 0.000000], [0.441068, -0.079044, 0.200685, -0.092783, -0.696098, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.928352, 1.145423, 2.094885, 2.733644, -0.134121]
pre_activation_std: [2.753997, 2.060526, 2.457473, 3.122867, 1.650283]
### 2
mean: [3.050331, 4.154154, -0.660154, 0.229345, 1.178085]
std: [4.621529, 5.486425, 1.374966, 1.085806, 2.453685]
fourier: [[75.320603, 77.630452, 78.168186, 84.254984, 274.529739], [85.590602, 86.651167, 90.639469, 104.277326, 373.873837], [23.294778, 23.522691, 24.548943, 26.213350, 59.413858], [16.202325, 19.092020, 19.207631, 20.077659, 20.641056], [41.592644, 41.993214, 43.974168, 44.390573, 106.027658]]
input_correlations: [[0.916940, -0.477617, 0.992735, 0.926743, 0.664670, 0.000000, 0.000000, 0.000000], [0.941950, -0.396544, 0.990981, 0.936189, 0.698029, 0.000000, 0.000000, 0.000000], [-0.846674, 0.344282, -0.982255, -0.976044, -0.635087, 0.000000, 0.000000, 0.000000], [-0.737471, 0.828142, -0.836129, -0.665451, -0.630007, 0.000000, 0.000000, 0.000000], [0.885092, -0.518528, 0.992242, 0.924277, 0.643539, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.050331, 4.154154, -0.660154, 0.229345, 1.178085]
pre_activation_std: [4.621529, 5.486425, 1.374966, 1.085806, 2.453685]
### 4
mean: [7.563157, -0.504887, -1.370564, -0.842003, 3.574215]
std: [10.735147, 2.070316, 2.658063, 2.577546, 4.755593]
fourier: [[179.754918, 180.424880, 180.850705, 200.000345, 680.684092], [35.035974, 36.879987, 37.016237, 37.129987, 45.439828], [46.034022, 46.047182, 46.566049, 49.276525, 123.350792], [45.117180, 45.551082, 45.610547, 47.323160, 75.780274], [77.835354, 78.367741, 78.947897, 89.648105, 321.679389]]
input_correlations: [[0.999360, 0.997077, -0.388524, -0.481067, 0.992737, 0.000000, 0.000000, 0.000000], [-0.991397, -0.979686, 0.344097, 0.549661, -0.993280, 0.000000, 0.000000, 0.000000], [-0.999036, -0.994199, 0.377696, 0.449471, -0.997004, 0.000000, 0.000000, 0.000000], [-0.997871, -0.990158, 0.365297, 0.470385, -0.998579, 0.000000, 0.000000, 0.000000], [0.998001, 0.998202, -0.412905, -0.487032, 0.988738, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [7.563157, -0.504887, -1.370564, -0.842003, 3.574215]
pre_activation_std: [10.735147, 2.070316, 2.658063, 2.577546, 4.755593]
### 6
mean: [5.478904, 6.917718, -0.213069, -1.265636, -0.592506]
std: [8.014693, 10.139183, 1.143538, 1.914606, 1.044154]
fourier: [[129.763043, 135.039846, 135.191874, 151.829486, 493.101343], [164.906206, 166.405594, 170.499156, 191.898656, 622.594536], [18.695607, 19.173916, 19.176231, 19.257900, 21.409055], [30.524575, 32.171739, 32.780046, 36.355035, 113.907278], [18.045521, 18.393922, 18.913595, 18.971867, 53.325508]]
input_correlations: [[0.999317, -0.609445, -0.481294, -0.688471, 0.999855, 0.000000, 0.000000, 0.000000], [0.998337, -0.633928, -0.494924, -0.705466, 0.999367, 0.000000, 0.000000, 0.000000], [-0.994771, 0.672973, 0.504549, 0.724001, -0.996026, 0.000000, 0.000000, 0.000000], [-0.998050, 0.616609, 0.500620, 0.703323, -0.998811, 0.000000, 0.000000, 0.000000], [-0.997095, 0.562994, 0.392054, 0.617671, -0.993952, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [5.478904, 6.917718, -0.213069, -1.265636, -0.592506]
pre_activation_std: [8.014693, 10.139183, 1.143538, 1.914606, 1.044154]
### 8
mean: [-5.157561, 9.968291, -0.843854, 0.329380, -2.810357]
std: [7.978847, 14.365192, 1.731027, 0.671509, 3.865237]
fourier: [[130.787615, 135.527255, 135.822800, 151.306852, 464.180491], [231.344699, 242.100979, 244.354056, 273.268919, 897.146246], [28.563948, 29.383633, 29.680321, 32.785340, 75.946888], [10.993264, 11.434940, 11.466083, 12.722133, 29.644232], [63.364587, 65.749292, 66.126467, 73.277396, 252.932156]]
input_correlations: [[-0.999981, -0.999888, 0.632657, 0.132691, 0.299087, 0.000000, 0.000000, 0.000000], [0.999720, 0.999922, -0.645437, -0.142897, -0.315554, 0.000000, 0.000000, 0.000000], [-0.999950, -0.999640, 0.623148, 0.128759, 0.287226, 0.000000, 0.000000, 0.000000], [0.999567, 0.999895, -0.638959, -0.123776, -0.313606, 0.000000, 0.000000, 0.000000], [-0.999974, -0.999917, 0.630268, 0.129070, 0.298864, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.157561, 9.968291, -0.843854, 0.329380, -2.810357]
pre_activation_std: [7.978847, 14.365192, 1.731027, 0.671509, 3.865237]
### 10
mean: [-8.517426]
std: [12.622545]
fourier: [[204.828932, 213.472889, 215.896695, 239.987266, 766.568388]]
input_correlations: [[0.409097, -0.999991, 0.485552, -0.992684, -0.424431, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-8.517426]
pre_activation_std: [12.622545]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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0.54688,
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}
## Activation Signature
### 0
mean: [0.122977, 10.093886, 0.068797, 0.317515, -0.046406]
std: [0.227502, 14.272077, 0.154651, 0.617321, 0.059369]
fourier: [[3.480358, 3.881356, 4.280426, 4.883963, 11.067972], [232.773512, 241.922413, 244.097357, 270.877588, 908.449755], [2.392604, 2.431679, 2.501037, 2.882198, 6.191703], [10.229238, 10.892285, 11.077445, 11.253417, 28.576339], [0.921747, 0.936959, 1.057610, 1.252369, 4.176506]]
input_correlations: [[0.642832, 0.522767, 0.247003, 0.019975, -0.569295, 0.000000, 0.000000, 0.000000], [-0.641590, 0.142798, 0.163219, 0.551489, 0.374847, 0.000000, 0.000000, 0.000000], [0.925839, 0.496679, 0.308270, -0.022909, -0.156078, 0.000000, 0.000000, 0.000000], [0.926768, 0.643062, 0.376865, 0.186333, 0.147158, 0.000000, 0.000000, 0.000000], [0.441068, -0.079044, 0.200685, -0.092783, -0.696098, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.928352, 1.145423, 2.094885, 2.733644, -0.134121]
pre_activation_std: [2.753997, 2.060526, 2.457473, 3.122867, 1.650283]
### 2
mean: [3.050331, 4.154154, -0.660154, 0.229345, 1.178085]
std: [4.621529, 5.486425, 1.374966, 1.085806, 2.453685]
fourier: [[75.320603, 77.630452, 78.168186, 84.254984, 274.529739], [85.590602, 86.651167, 90.639469, 104.277326, 373.873837], [23.294778, 23.522691, 24.548943, 26.213350, 59.413858], [16.202325, 19.092020, 19.207631, 20.077659, 20.641056], [41.592644, 41.993214, 43.974168, 44.390573, 106.027658]]
input_correlations: [[0.916940, -0.477617, 0.992735, 0.926743, 0.664670, 0.000000, 0.000000, 0.000000], [0.941950, -0.396544, 0.990981, 0.936189, 0.698029, 0.000000, 0.000000, 0.000000], [-0.846674, 0.344282, -0.982255, -0.976044, -0.635087, 0.000000, 0.000000, 0.000000], [-0.737471, 0.828142, -0.836129, -0.665451, -0.630007, 0.000000, 0.000000, 0.000000], [0.885092, -0.518528, 0.992242, 0.924277, 0.643539, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.050331, 4.154154, -0.660154, 0.229345, 1.178085]
pre_activation_std: [4.621529, 5.486425, 1.374966, 1.085806, 2.453685]
### 4
mean: [7.563157, -0.504887, -1.370564, -0.842003, 3.574215]
std: [10.735147, 2.070316, 2.658063, 2.577546, 4.755593]
fourier: [[179.754918, 180.424880, 180.850705, 200.000345, 680.684092], [35.035974, 36.879987, 37.016237, 37.129987, 45.439828], [46.034022, 46.047182, 46.566049, 49.276525, 123.350792], [45.117180, 45.551082, 45.610547, 47.323160, 75.780274], [77.835354, 78.367741, 78.947897, 89.648105, 321.679389]]
input_correlations: [[0.999360, 0.997077, -0.388524, -0.481067, 0.992737, 0.000000, 0.000000, 0.000000], [-0.991397, -0.979686, 0.344097, 0.549661, -0.993280, 0.000000, 0.000000, 0.000000], [-0.999036, -0.994199, 0.377696, 0.449471, -0.997004, 0.000000, 0.000000, 0.000000], [-0.997871, -0.990158, 0.365297, 0.470385, -0.998579, 0.000000, 0.000000, 0.000000], [0.998001, 0.998202, -0.412905, -0.487032, 0.988738, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [7.563157, -0.504887, -1.370564, -0.842003, 3.574215]
pre_activation_std: [10.735147, 2.070316, 2.658063, 2.577546, 4.755593]
### 6
mean: [5.478904, 6.917718, -0.213069, -1.265636, -0.592506]
std: [8.014693, 10.139183, 1.143538, 1.914606, 1.044154]
fourier: [[129.763043, 135.039846, 135.191874, 151.829486, 493.101343], [164.906206, 166.405594, 170.499156, 191.898656, 622.594536], [18.695607, 19.173916, 19.176231, 19.257900, 21.409055], [30.524575, 32.171739, 32.780046, 36.355035, 113.907278], [18.045521, 18.393922, 18.913595, 18.971867, 53.325508]]
input_correlations: [[0.999317, -0.609445, -0.481294, -0.688471, 0.999855, 0.000000, 0.000000, 0.000000], [0.998337, -0.633928, -0.494924, -0.705466, 0.999367, 0.000000, 0.000000, 0.000000], [-0.994771, 0.672973, 0.504549, 0.724001, -0.996026, 0.000000, 0.000000, 0.000000], [-0.998050, 0.616609, 0.500620, 0.703323, -0.998811, 0.000000, 0.000000, 0.000000], [-0.997095, 0.562994, 0.392054, 0.617671, -0.993952, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [5.478904, 6.917718, -0.213069, -1.265636, -0.592506]
pre_activation_std: [8.014693, 10.139183, 1.143538, 1.914606, 1.044154]
### 8
mean: [-5.157561, 9.968291, -0.843854, 0.329380, -2.810357]
std: [7.978847, 14.365192, 1.731027, 0.671509, 3.865237]
fourier: [[130.787615, 135.527255, 135.822800, 151.306852, 464.180491], [231.344699, 242.100979, 244.354056, 273.268919, 897.146246], [28.563948, 29.383633, 29.680321, 32.785340, 75.946888], [10.993264, 11.434940, 11.466083, 12.722133, 29.644232], [63.364587, 65.749292, 66.126467, 73.277396, 252.932156]]
input_correlations: [[-0.999981, -0.999888, 0.632657, 0.132691, 0.299087, 0.000000, 0.000000, 0.000000], [0.999720, 0.999922, -0.645437, -0.142897, -0.315554, 0.000000, 0.000000, 0.000000], [-0.999950, -0.999640, 0.623148, 0.128759, 0.287226, 0.000000, 0.000000, 0.000000], [0.999567, 0.999895, -0.638959, -0.123776, -0.313606, 0.000000, 0.000000, 0.000000], [-0.999974, -0.999917, 0.630268, 0.129070, 0.298864, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.157561, 9.968291, -0.843854, 0.329380, -2.810357]
pre_activation_std: [7.978847, 14.365192, 1.731027, 0.671509, 3.865237]
### 10
mean: [-8.517426]
std: [12.622545]
fourier: [[204.828932, 213.472889, 215.896695, 239.987266, 766.568388]]
input_correlations: [[0.409097, -0.999991, 0.485552, -0.992684, -0.424431, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-8.517426]
pre_activation_std: [12.622545]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.12297746539115906, "std": 0.2275022268295288, "fourier": [3.4803582484422293, 3.8813564574215973, 4.280426482114343, 4.883962756334723, 11.067972320242973], "input_correlations": [0.6428316749825229, 0.5227665219957172, 0.24700298710656887, 0.019974566105691947, -0.5692949417176425, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9283519983291626, "pre_activation_std": 2.7539968490600586}, "1": {"mean": 10.093886375427246, "std": 14.272076606750488, "fourier": [232.77351206400522, 241.92241331461162, 244.09735701080317, 270.8775879298339, 908.4497548844665], "input_correlations": [-0.6415901632440182, 0.1427975059276557, 0.16321875048044931, 0.5514892442719745, 0.37484724245026063, 0.0, 0.0, 0.0], "pre_activation_mean": 1.145423412322998, "pre_activation_std": 2.0605263710021973}, "2": {"mean": 0.06879670172929764, "std": 0.15465147793293, "fourier": [2.3926041909254283, 2.4316790146008134, 2.5010372374619965, 2.8821975181535766, 6.1917029520645315], "input_correlations": [0.925839396117983, 0.49667915364920606, 0.3082703280373328, -0.022909372000234324, -0.15607775494004117, 0.0, 0.0, 0.0], "pre_activation_mean": 2.0948848724365234, "pre_activation_std": 2.4574732780456543}, "3": {"mean": 0.3175148665904999, "std": 0.6173214912414551, "fourier": [10.229237591612943, 10.892285356815309, 11.077445200317216, 11.253417457474198, 28.576338605955243], "input_correlations": [0.9267681101638596, 0.6430624149672779, 0.37686450719323183, 0.18633323708576918, 0.14715847081202935, 0.0, 0.0, 0.0], "pre_activation_mean": 2.7336435317993164, "pre_activation_std": 3.122866630554199}, "4": {"mean": -0.04640562832355499, "std": 0.0593690350651741, "fourier": [0.9217467382597228, 0.9369585342350695, 1.0576098906015339, 1.2523689517278729, 4.176506032956411], "input_correlations": [0.44106837953188216, -0.07904419824709717, 0.2006849593017456, -0.092782635447149, -0.6960981111036407, 0.0, 0.0, 0.0], "pre_activation_mean": -0.1341211199760437, "pre_activation_std": 1.6502832174301147}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 3.050330877304077, "std": 4.6215291023254395, "fourier": [75.32060312715991, 77.63045156357893, 78.16818610619764, 84.25498432715739, 274.5297386497259], "input_correlations": [0.9169398875058794, -0.4776168016057753, 0.992734636118171, 0.9267433691023218, 0.6646703854975092, 0.0, 0.0, 0.0], "pre_activation_mean": 3.050330877304077, "pre_activation_std": 4.6215291023254395}, "1": {"mean": 4.154153823852539, "std": 5.486424922943115, "fourier": [85.59060194129356, 86.65116700084137, 90.63946863623507, 104.27732598703643, 373.873837210238], "input_correlations": [0.9419495984703656, -0.39654363763460776, 0.9909811566096952, 0.9361887589378567, 0.698028992257708, 0.0, 0.0, 0.0], "pre_activation_mean": 4.154153823852539, "pre_activation_std": 5.486424922943115}, "2": {"mean": -0.6601539850234985, "std": 1.3749662637710571, "fourier": [23.294778328497166, 23.52269074696215, 24.548943344731562, 26.21334965761639, 59.41385796666145], "input_correlations": [-0.8466742575662939, 0.34428246896860304, -0.9822552741970524, -0.9760441989851973, -0.6350869823866901, 0.0, 0.0, 0.0], "pre_activation_mean": -0.6601539850234985, "pre_activation_std": 1.3749662637710571}, "3": {"mean": 0.22934505343437195, "std": 1.0858064889907837, "fourier": [16.202325384282503, 19.092020278248206, 19.20763141776148, 20.077658688879527, 20.64105612039566], "input_correlations": [-0.7374711681252344, 0.8281422353983192, -0.8361289813988689, -0.6654505246307608, -0.6300070994207876, 0.0, 0.0, 0.0], "pre_activation_mean": 0.22934505343437195, "pre_activation_std": 1.0858064889907837}, "4": {"mean": 1.1780850887298584, "std": 2.4536850452423096, "fourier": [41.59264374322561, 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["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "10": {"neuron_profiles": {"0": {"mean": -8.517426490783691, "std": 12.62254524230957, "fourier": [204.82893217561787, 213.47288923960477, 215.8966953645795, 239.98726593400326, 766.5683878362179], "input_correlations": [0.40909683972982264, -0.9999911004239139, 0.48555177177022535, -0.9926838473205949, -0.42443103984293795, 0.0, 0.0, 0.0], "pre_activation_mean": -8.517426490783691, "pre_activation_std": 12.62254524230957}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, 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[[0.103891, -0.891698, 0.166559, 0.206345, -0.021678]], "network.10.bias": [0.392514]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.721134215593338, "train_acc": 0.435, "val_loss": 0.684816837310791, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6783056855201721, "train_acc": 0.565, "val_loss": 0.6668499708175659, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6762900948524475, "train_acc": 0.565, "val_loss": 0.6247003674507141, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6531854271888733, "train_acc": 0.585, "val_loss": 0.5809020400047302, "val_acc": 0.8}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5841850638389587, "train_acc": 0.71, "val_loss": 0.4965672194957733, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.5436089336872101, "train_acc": 0.71, "val_loss": 0.45010703802108765, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.5270116776227951, "train_acc": 0.74, "val_loss": 0.4298924207687378, "val_acc": 0.8}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.4847804605960846, "train_acc": 0.755, "val_loss": 0.431770920753479, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4812311828136444, "train_acc": 0.755, "val_loss": 0.4392163157463074, "val_acc": 0.78}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.48038290441036224, "train_acc": 0.755, "val_loss": 0.41583889722824097, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.4630471020936966, "train_acc": 0.77, "val_loss": 0.42192503809928894, "val_acc": 0.8}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.46730339527130127, "train_acc": 0.77, "val_loss": 0.4255393147468567, "val_acc": 0.8}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.45911355316638947, "train_acc": 0.77, "val_loss": 0.4237792193889618, "val_acc": 0.8}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.684816837310791, "final_val_loss": 0.6247003674507141, "initial_val_acc": 0.56, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.5809020400047302, "final_val_loss": 0.4237792193889618, "initial_val_acc": 0.8, "final_val_acc": 0.8, "best_val_acc": 0.82, "best_epoch": 9}, "improvement": 0.29999999999999993, "first_improvement_epoch": 2}} |
32 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.7, "improved_accuracy": 0.96, "improvement": 0.26, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4009, "learning_rate": 0.03724346377980019, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.505879, 1.095778, 0.598279, 1.213213, 1.331719, 0.633594, 2.980283]
std: [1.232952, 0.946640, 1.558927, 1.083042, 1.092494, 1.534639, 2.342887]
fourier: [[19.961861, 20.373715, 25.010607, 25.801768, 45.529130], [13.084348, 13.408190, 15.209850, 19.489417, 98.620045], [25.416031, 26.041407, 31.129165, 32.761336, 53.845095], [15.045136, 15.888413, 17.319023, 22.373260, 109.189152], [15.054526, 15.214215, 17.799259, 22.947469, 119.854691], [25.318248, 25.472333, 30.968223, 32.410130, 57.023460], [32.274874, 33.082775, 37.941324, 48.165846, 268.225469]]
input_correlations: [[-0.351203, -0.074016, 0.517884, 0.451422, -0.299685, 0.000000, 0.000000, 0.000000], [-0.276404, 0.294887, -0.258738, 0.877077, 0.358524, 0.000000, 0.000000, 0.000000], [0.846542, 0.724365, 0.421788, 0.282611, 0.321841, 0.000000, 0.000000, 0.000000], [-0.263585, 0.426162, -0.435459, 0.645659, -0.519258, 0.000000, 0.000000, 0.000000], [-0.459351, -0.051641, -0.283935, 0.451307, 0.683112, 0.000000, 0.000000, 0.000000], [-0.243768, -0.078346, -0.260916, 0.737228, 0.594544, 0.000000, 0.000000, 0.000000], [-0.533905, 0.176115, 0.026560, 0.727303, 0.425347, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.935592, 0.971396, 2.434963, 0.396650, 0.478831, 1.416440, 0.810700]
pre_activation_std: [1.417157, 1.661508, 2.079038, 1.455937, 1.255840, 1.511105, 0.815982]
### 2
mean: [2.325854, -0.558408, -0.465682, -0.463247, -0.578508, -0.357576, 0.219837]
std: [2.178687, 1.198368, 2.354214, 1.550133, 1.204710, 0.964289, 1.628741]
fourier: [[31.680859, 32.959911, 37.198748, 37.320181, 209.326847], [18.623002, 19.017789, 19.626763, 23.434715, 50.256717], [37.217674, 38.962533, 39.946912, 41.911381, 47.722012], [22.927926, 24.531162, 24.753604, 30.439289, 41.692261], [18.859149, 19.101150, 19.861394, 20.801679, 52.065718], [14.322067, 16.609476, 17.749407, 18.633824, 32.181823], [22.597015, 23.348539, 23.385738, 32.883033, 33.591709]]
input_correlations: [[0.255873, 0.991988, 0.122706, 0.604264, 0.751738, 0.917455, 0.917468, 0.000000], [-0.642193, -0.686642, 0.494247, -0.469167, -0.511859, -0.650411, -0.788104, 0.000000], [-0.553639, -0.685740, 0.556672, -0.436827, -0.550875, -0.659338, -0.788391, 0.000000], [-0.548933, -0.756057, 0.455427, -0.398547, -0.624296, -0.742626, -0.851829, 0.000000], [-0.671372, -0.752381, 0.372668, -0.585865, -0.483120, -0.662518, -0.824750, 0.000000], [-0.653027, -0.689276, 0.429892, -0.493733, -0.510984, -0.585267, -0.818277, 0.000000], [-0.204255, 0.747115, -0.164968, 0.038033, 0.949596, 0.894796, 0.735630, 0.000000]]
pre_activation_mean: [2.325854, -0.558408, -0.465682, -0.463247, -0.578508, -0.357576, 0.219837]
pre_activation_std: [2.178687, 1.198368, 2.354214, 1.550133, 1.204710, 0.964289, 1.628741]
### 4
mean: [0.730470, 0.823736, 0.353193, 0.628620, -1.403041, -0.793033, 1.275538]
std: [1.979956, 2.176963, 1.317147, 1.786598, 1.254797, 2.350510, 2.191594]
fourier: [[29.246134, 29.730955, 32.211482, 43.028068, 65.742329], [33.165447, 36.566280, 40.952116, 41.095725, 74.136277], [22.311670, 22.783053, 24.032807, 27.213524, 31.787404], [28.921111, 30.358711, 31.147702, 39.842155, 56.575811], [18.570083, 18.735653, 20.822552, 24.606303, 126.273668], [33.969927, 35.501888, 38.197037, 49.768278, 71.373001], [31.539170, 33.523094, 35.804756, 46.524329, 114.798430]]
input_correlations: [[0.813126, -0.757076, -0.770004, -0.787327, -0.790814, -0.778216, 0.724248, 0.000000], [0.756996, -0.847171, -0.858356, -0.875177, -0.876698, -0.865741, 0.503012, 0.000000], [-0.407543, 0.956923, 0.964840, 0.957756, 0.952760, 0.937049, -0.447388, 0.000000], [-0.537139, 0.924482, 0.936661, 0.926901, 0.926636, 0.922600, -0.549001, 0.000000], [-0.896738, -0.119387, -0.098459, -0.051175, -0.052759, -0.056294, -0.737765, 0.000000], [-0.855534, 0.711442, 0.727215, 0.748129, 0.750059, 0.741454, -0.738702, 0.000000], [0.873140, -0.681247, -0.698178, -0.719195, -0.722326, -0.717259, 0.757650, 0.000000]]
pre_activation_mean: [0.730470, 0.823736, 0.353193, 0.628620, -1.403041, -0.793033, 1.275538]
pre_activation_std: [1.979956, 2.176963, 1.317147, 1.786598, 1.254797, 2.350510, 2.191594]
### 6
mean: [2.045947, 1.512281, -1.325387, -0.218413, 0.061402, -0.581565, 0.120861]
std: [2.801705, 1.428258, 2.133960, 2.282349, 1.542332, 1.276999, 1.113173]
fourier: [[40.787929, 41.796002, 45.891338, 60.034045, 184.135228], [20.562337, 20.929848, 23.179386, 29.467744, 136.105326], [31.656104, 32.616464, 34.537978, 44.634562, 119.284870], [35.468322, 36.299507, 37.683868, 42.577553, 46.087675], [25.363372, 25.784404, 26.669554, 29.670591, 30.373152], [18.346763, 19.214365, 20.660341, 28.012184, 52.340812], [18.442686, 18.995482, 20.322641, 20.788504, 22.424349]]
input_correlations: [[0.895164, 0.919268, -0.751281, -0.780353, 0.309819, -0.741783, 0.916323, 0.000000], [0.925433, 0.962691, -0.666691, -0.702678, 0.300523, -0.662763, 0.947810, 0.000000], [-0.953625, -0.942631, 0.637556, 0.668573, -0.328352, 0.633233, -0.969221, 0.000000], [-0.714219, -0.767609, 0.921809, 0.936404, -0.294081, 0.916859, -0.744239, 0.000000], [-0.632223, -0.708241, 0.957791, 0.969098, -0.270511, 0.952210, -0.665954, 0.000000], [-0.942302, -0.928003, 0.677684, 0.707152, -0.321752, 0.664779, -0.955098, 0.000000], [-0.594968, -0.691472, 0.965071, 0.977678, -0.255609, 0.961789, -0.631789, 0.000000]]
pre_activation_mean: [2.045947, 1.512281, -1.325387, -0.218413, 0.061402, -0.581565, 0.120861]
pre_activation_std: [2.801705, 1.428258, 2.133960, 2.282349, 1.542332, 1.276999, 1.113173]
### 8
mean: [-0.840460, 0.693073, -0.132016, 0.525295, 0.456900, -0.093766, 2.527068]
std: [2.235301, 1.770471, 1.973820, 2.406542, 2.817413, 2.031541, 3.068752]
fourier: [[32.662921, 37.275475, 38.002126, 46.426087, 75.641358], [27.857455, 29.640163, 33.377126, 34.957535, 62.376590], [32.225409, 32.736299, 34.490989, 36.791308, 39.097582], [39.649027, 40.319546, 46.330825, 46.401182, 47.276586], [45.551753, 46.931407, 48.563773, 52.834148, 55.655792], [32.132450, 32.388057, 33.972743, 38.290189, 40.303706], [43.290872, 50.646702, 51.021368, 63.611387, 227.436160]]
input_correlations: [[-0.900505, -0.923637, 0.802600, 0.825947, 0.840392, 0.829739, 0.861204, 0.000000], [0.820835, 0.854113, -0.885204, -0.904201, -0.914983, -0.907379, -0.930092, 0.000000], [-0.720961, -0.759810, 0.946751, 0.960039, 0.966656, 0.956578, 0.975805, 0.000000], [0.787244, 0.823207, -0.909583, -0.926996, -0.936436, -0.927090, -0.949435, 0.000000], [0.744760, 0.783355, -0.935135, -0.949875, -0.957504, -0.948490, -0.967942, 0.000000], [-0.802904, -0.835837, 0.898719, 0.916918, 0.927080, 0.916546, 0.941147, 0.000000], [0.921850, 0.943308, -0.770044, -0.795216, -0.810750, -0.802272, -0.833119, 0.000000]]
pre_activation_mean: [-0.840460, 0.693073, -0.132016, 0.525295, 0.456900, -0.093766, 2.527068]
pre_activation_std: [2.235301, 1.770471, 1.973820, 2.406542, 2.817413, 2.031541, 3.068752]
### 10
mean: [-2.582264]
std: [3.253570]
fourier: [[45.501333, 54.035588, 54.280131, 67.010644, 232.403774]]
input_correlations: [[0.788195, -0.940264, 0.791732, -0.928097, -0.947308, 0.805468, -0.958354, 0.000000]]
pre_activation_mean: [-2.582264]
pre_activation_std: [3.253570]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.265516,
-0.251026,
0.591522,
0.411411,
-0.381153
],
[
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0.590785,
0.32705
],
[
0.666292,
0.500006,
0.086597,
0.140946,
0.187282
],
[
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0.282246,
-0.274844,
0.418087,
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],
[
-0.325493,
0.069967,
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0.16534,
0.548061
],
[
-0.11604,
-0.1578,
-0.234313,
0.51293,
0.475933
],
[
-0.27479,
0.086757,
0.041152,
0.21967,
0.196326
]
],
"network.0.bias": [
0.075653,
-0.217711,
-0.019446,
0.181512,
0.152932,
0.650914,
0.195403
],
"network.2.weight": [
[
0.159774,
0.462489,
0.076334,
0.524481,
0.253766,
0.595683,
0.197468
],
[
-0.49354,
0.017089,
0.233845,
-0.316023,
-0.529781,
-0.104762,
-0.07234
],
[
-0.628809,
-0.516755,
0.606679,
-0.260667,
-0.630689,
0.075265,
-0.48454
],
[
-0.394371,
-0.568008,
0.341356,
0.119003,
-0.172176,
-0.001783,
-0.405153
],
[
-0.444031,
-0.118832,
0.183647,
-0.328296,
-0.280839,
-0.06874,
-0.250224
],
[
-0.389503,
-0.246133,
0.178063,
-0.178089,
-0.5481,
0.32012,
-0.212198
],
[
-0.355378,
0.462871,
-0.211298,
-0.39201,
0.404906,
0.3922,
0.12885
]
],
"network.2.bias": [
-0.028124,
0.094352,
0.118168,
0.09198,
0.23641,
0.046103,
-0.084716
],
"network.4.weight": [
[
0.354956,
-0.746559,
-0.24958,
-0.332173,
-0.441841,
-0.022791,
0.471889
],
[
0.534974,
-0.18634,
-0.541537,
-0.401454,
-0.623906,
-0.348281,
-0.073389
],
[
0.085176,
0.392552,
0.420367,
0.480942,
0.275009,
0.025829,
-0.332727
],
[
-0.007756,
0.624196,
0.651207,
0.212747,
0.049853,
0.44937,
-0.471581
],
[
-0.510675,
-0.220319,
-0.069283,
0.050746,
-0.34672,
-0.625091,
-0.196477
],
[
-0.509277,
0.457127,
0.328525,
0.44396,
0.295101,
0.207922,
-0.503157
],
[
0.494916,
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-0.336597,
-0.278155,
-0.376717,
-0.361613,
0.488466
]
],
"network.4.bias": [
0.120487,
0.318466,
-0.190632,
0.244386,
0.06001,
0.137462,
0.321207
],
"network.6.weight": [
[
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[
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0.009512,
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],
[
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0.417945,
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0.425916,
-0.54477
],
[
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0.409736,
0.308999,
-0.417785,
0.636338,
-0.290823
],
[
0.078484,
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0.497875,
0.211993,
-0.217177,
0.297019,
-0.245775
],
[
-0.540989,
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0.279072,
0.010935,
-0.102646,
0.071808,
-0.079165
],
[
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-0.125123,
0.447241,
-0.051407,
0.345338,
-0.004885
]
],
"network.6.bias": [
0.722445,
0.557162,
0.110096,
-0.178726,
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0.122806,
-0.087469
],
"network.8.weight": [
[
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0.051149,
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-0.338467,
0.46761
],
[
0.284867,
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0.100223,
-0.390502,
-0.451716
],
[
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0.589335,
0.226675,
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0.371099
],
[
0.260362,
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0.37919,
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],
[
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0.211066,
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[
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],
[
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]
],
"network.8.bias": [
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0.273857,
0.676144
],
"network.10.weight": [
[
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-0.29024,
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]
],
"network.10.bias": [
-0.075633
]
}
## Activation Signature
### 0
mean: [0.505879, 1.095778, 0.598279, 1.213213, 1.331719, 0.633594, 2.980283]
std: [1.232952, 0.946640, 1.558927, 1.083042, 1.092494, 1.534639, 2.342887]
fourier: [[19.961861, 20.373715, 25.010607, 25.801768, 45.529130], [13.084348, 13.408190, 15.209850, 19.489417, 98.620045], [25.416031, 26.041407, 31.129165, 32.761336, 53.845095], [15.045136, 15.888413, 17.319023, 22.373260, 109.189152], [15.054526, 15.214215, 17.799259, 22.947469, 119.854691], [25.318248, 25.472333, 30.968223, 32.410130, 57.023460], [32.274874, 33.082775, 37.941324, 48.165846, 268.225469]]
input_correlations: [[-0.351203, -0.074016, 0.517884, 0.451422, -0.299685, 0.000000, 0.000000, 0.000000], [-0.276404, 0.294887, -0.258738, 0.877077, 0.358524, 0.000000, 0.000000, 0.000000], [0.846542, 0.724365, 0.421788, 0.282611, 0.321841, 0.000000, 0.000000, 0.000000], [-0.263585, 0.426162, -0.435459, 0.645659, -0.519258, 0.000000, 0.000000, 0.000000], [-0.459351, -0.051641, -0.283935, 0.451307, 0.683112, 0.000000, 0.000000, 0.000000], [-0.243768, -0.078346, -0.260916, 0.737228, 0.594544, 0.000000, 0.000000, 0.000000], [-0.533905, 0.176115, 0.026560, 0.727303, 0.425347, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.935592, 0.971396, 2.434963, 0.396650, 0.478831, 1.416440, 0.810700]
pre_activation_std: [1.417157, 1.661508, 2.079038, 1.455937, 1.255840, 1.511105, 0.815982]
### 2
mean: [2.325854, -0.558408, -0.465682, -0.463247, -0.578508, -0.357576, 0.219837]
std: [2.178687, 1.198368, 2.354214, 1.550133, 1.204710, 0.964289, 1.628741]
fourier: [[31.680859, 32.959911, 37.198748, 37.320181, 209.326847], [18.623002, 19.017789, 19.626763, 23.434715, 50.256717], [37.217674, 38.962533, 39.946912, 41.911381, 47.722012], [22.927926, 24.531162, 24.753604, 30.439289, 41.692261], [18.859149, 19.101150, 19.861394, 20.801679, 52.065718], [14.322067, 16.609476, 17.749407, 18.633824, 32.181823], [22.597015, 23.348539, 23.385738, 32.883033, 33.591709]]
input_correlations: [[0.255873, 0.991988, 0.122706, 0.604264, 0.751738, 0.917455, 0.917468, 0.000000], [-0.642193, -0.686642, 0.494247, -0.469167, -0.511859, -0.650411, -0.788104, 0.000000], [-0.553639, -0.685740, 0.556672, -0.436827, -0.550875, -0.659338, -0.788391, 0.000000], [-0.548933, -0.756057, 0.455427, -0.398547, -0.624296, -0.742626, -0.851829, 0.000000], [-0.671372, -0.752381, 0.372668, -0.585865, -0.483120, -0.662518, -0.824750, 0.000000], [-0.653027, -0.689276, 0.429892, -0.493733, -0.510984, -0.585267, -0.818277, 0.000000], [-0.204255, 0.747115, -0.164968, 0.038033, 0.949596, 0.894796, 0.735630, 0.000000]]
pre_activation_mean: [2.325854, -0.558408, -0.465682, -0.463247, -0.578508, -0.357576, 0.219837]
pre_activation_std: [2.178687, 1.198368, 2.354214, 1.550133, 1.204710, 0.964289, 1.628741]
### 4
mean: [0.730470, 0.823736, 0.353193, 0.628620, -1.403041, -0.793033, 1.275538]
std: [1.979956, 2.176963, 1.317147, 1.786598, 1.254797, 2.350510, 2.191594]
fourier: [[29.246134, 29.730955, 32.211482, 43.028068, 65.742329], [33.165447, 36.566280, 40.952116, 41.095725, 74.136277], [22.311670, 22.783053, 24.032807, 27.213524, 31.787404], [28.921111, 30.358711, 31.147702, 39.842155, 56.575811], [18.570083, 18.735653, 20.822552, 24.606303, 126.273668], [33.969927, 35.501888, 38.197037, 49.768278, 71.373001], [31.539170, 33.523094, 35.804756, 46.524329, 114.798430]]
input_correlations: [[0.813126, -0.757076, -0.770004, -0.787327, -0.790814, -0.778216, 0.724248, 0.000000], [0.756996, -0.847171, -0.858356, -0.875177, -0.876698, -0.865741, 0.503012, 0.000000], [-0.407543, 0.956923, 0.964840, 0.957756, 0.952760, 0.937049, -0.447388, 0.000000], [-0.537139, 0.924482, 0.936661, 0.926901, 0.926636, 0.922600, -0.549001, 0.000000], [-0.896738, -0.119387, -0.098459, -0.051175, -0.052759, -0.056294, -0.737765, 0.000000], [-0.855534, 0.711442, 0.727215, 0.748129, 0.750059, 0.741454, -0.738702, 0.000000], [0.873140, -0.681247, -0.698178, -0.719195, -0.722326, -0.717259, 0.757650, 0.000000]]
pre_activation_mean: [0.730470, 0.823736, 0.353193, 0.628620, -1.403041, -0.793033, 1.275538]
pre_activation_std: [1.979956, 2.176963, 1.317147, 1.786598, 1.254797, 2.350510, 2.191594]
### 6
mean: [2.045947, 1.512281, -1.325387, -0.218413, 0.061402, -0.581565, 0.120861]
std: [2.801705, 1.428258, 2.133960, 2.282349, 1.542332, 1.276999, 1.113173]
fourier: [[40.787929, 41.796002, 45.891338, 60.034045, 184.135228], [20.562337, 20.929848, 23.179386, 29.467744, 136.105326], [31.656104, 32.616464, 34.537978, 44.634562, 119.284870], [35.468322, 36.299507, 37.683868, 42.577553, 46.087675], [25.363372, 25.784404, 26.669554, 29.670591, 30.373152], [18.346763, 19.214365, 20.660341, 28.012184, 52.340812], [18.442686, 18.995482, 20.322641, 20.788504, 22.424349]]
input_correlations: [[0.895164, 0.919268, -0.751281, -0.780353, 0.309819, -0.741783, 0.916323, 0.000000], [0.925433, 0.962691, -0.666691, -0.702678, 0.300523, -0.662763, 0.947810, 0.000000], [-0.953625, -0.942631, 0.637556, 0.668573, -0.328352, 0.633233, -0.969221, 0.000000], [-0.714219, -0.767609, 0.921809, 0.936404, -0.294081, 0.916859, -0.744239, 0.000000], [-0.632223, -0.708241, 0.957791, 0.969098, -0.270511, 0.952210, -0.665954, 0.000000], [-0.942302, -0.928003, 0.677684, 0.707152, -0.321752, 0.664779, -0.955098, 0.000000], [-0.594968, -0.691472, 0.965071, 0.977678, -0.255609, 0.961789, -0.631789, 0.000000]]
pre_activation_mean: [2.045947, 1.512281, -1.325387, -0.218413, 0.061402, -0.581565, 0.120861]
pre_activation_std: [2.801705, 1.428258, 2.133960, 2.282349, 1.542332, 1.276999, 1.113173]
### 8
mean: [-0.840460, 0.693073, -0.132016, 0.525295, 0.456900, -0.093766, 2.527068]
std: [2.235301, 1.770471, 1.973820, 2.406542, 2.817413, 2.031541, 3.068752]
fourier: [[32.662921, 37.275475, 38.002126, 46.426087, 75.641358], [27.857455, 29.640163, 33.377126, 34.957535, 62.376590], [32.225409, 32.736299, 34.490989, 36.791308, 39.097582], [39.649027, 40.319546, 46.330825, 46.401182, 47.276586], [45.551753, 46.931407, 48.563773, 52.834148, 55.655792], [32.132450, 32.388057, 33.972743, 38.290189, 40.303706], [43.290872, 50.646702, 51.021368, 63.611387, 227.436160]]
input_correlations: [[-0.900505, -0.923637, 0.802600, 0.825947, 0.840392, 0.829739, 0.861204, 0.000000], [0.820835, 0.854113, -0.885204, -0.904201, -0.914983, -0.907379, -0.930092, 0.000000], [-0.720961, -0.759810, 0.946751, 0.960039, 0.966656, 0.956578, 0.975805, 0.000000], [0.787244, 0.823207, -0.909583, -0.926996, -0.936436, -0.927090, -0.949435, 0.000000], [0.744760, 0.783355, -0.935135, -0.949875, -0.957504, -0.948490, -0.967942, 0.000000], [-0.802904, -0.835837, 0.898719, 0.916918, 0.927080, 0.916546, 0.941147, 0.000000], [0.921850, 0.943308, -0.770044, -0.795216, -0.810750, -0.802272, -0.833119, 0.000000]]
pre_activation_mean: [-0.840460, 0.693073, -0.132016, 0.525295, 0.456900, -0.093766, 2.527068]
pre_activation_std: [2.235301, 1.770471, 1.973820, 2.406542, 2.817413, 2.031541, 3.068752]
### 10
mean: [-2.582264]
std: [3.253570]
fourier: [[45.501333, 54.035588, 54.280131, 67.010644, 232.403774]]
input_correlations: [[0.788195, -0.940264, 0.791732, -0.928097, -0.947308, 0.805468, -0.958354, 0.000000]]
pre_activation_mean: [-2.582264]
pre_activation_std: [3.253570]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.5058792233467102, "std": 1.2329518795013428, "fourier": [19.961860913396674, 20.37371467346719, 25.010607239012906, 25.801768362946945, 45.52913008382393], "input_correlations": [-0.35120310957413997, -0.07401568913327845, 0.5178838288724333, 0.45142150662869623, -0.29968505207577406, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9355916976928711, "pre_activation_std": 1.4171569347381592}, "1": {"mean": 1.095778226852417, "std": 0.9466397762298584, "fourier": [13.08434777558598, 13.40818985309515, 15.20985045547973, 19.48941680344437, 98.62004458791489], "input_correlations": [-0.27640393561539117, 0.29488735597020543, -0.258737634833144, 0.8770766446275072, 0.35852413704658714, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9713957905769348, "pre_activation_std": 1.6615076065063477}, "2": {"mean": 0.598278820514679, "std": 1.558927059173584, "fourier": [25.41603143453805, 26.041407379464033, 31.129165301466685, 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"pre_activation_mean": 0.4788305461406708, "pre_activation_std": 1.2558401823043823}, "5": {"mean": 0.6335939764976501, "std": 1.534638524055481, "fourier": [25.318248464937067, 25.47233250696547, 30.968222509555158, 32.41013031299302, 57.023460052208975], "input_correlations": [-0.2437675631115646, -0.07834602220422573, -0.2609159590667326, 0.737227520278243, 0.5945438007560075, 0.0, 0.0, 0.0], "pre_activation_mean": 1.4164397716522217, "pre_activation_std": 1.511104941368103}, "6": {"mean": 2.980283260345459, "std": 2.3428869247436523, "fourier": [32.27487390173763, 33.08277534842048, 37.94132427486957, 48.165846403027196, 268.22546904022965], "input_correlations": [-0.5339046172672473, 0.17611507684458513, 0.0265604096759601, 0.7273031177955096, 0.42534650919853817, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8106998801231384, "pre_activation_std": 0.815982460975647}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", 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{"initial_val_loss": 0.2884593904018402, "final_val_loss": 0.23528793454170227, "initial_val_acc": 0.92, "final_val_acc": 0.94, "best_val_acc": 0.96, "best_epoch": 5}, "improvement": 0.26, "first_improvement_epoch": 2}} |
33 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.48, "improved_accuracy": 0.88, "improvement": 0.4, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3215, "learning_rate": 0.02854826421987649, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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-0.150304,
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]
],
"network.6.bias": [
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"network.8.weight": [
[
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[
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"network.10.weight": [
[
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],
"network.10.bias": [
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}
## Activation Signature
### 0
mean: [0.045162, 2.318057, -0.035040, 0.339899, -0.088306, -0.041284, -0.051697, 3.008245]
std: [0.128849, 3.211222, 0.086996, 0.725828, 0.046494, 0.123716, 0.059280, 4.099666]
fourier: [[1.851120, 2.125995, 2.298153, 2.337923, 4.064619], [52.494458, 53.422613, 57.609021, 57.688347, 208.625154], [1.375473, 1.441798, 1.468621, 1.544506, 3.153558], [11.419230, 11.996764, 13.140926, 14.051679, 30.590926], [0.660396, 0.689322, 0.862086, 0.944324, 7.947539], [1.854997, 1.959349, 2.284694, 2.344109, 3.715550], [0.908092, 0.979463, 1.085755, 1.357051, 4.652775], [65.954681, 69.343694, 72.786694, 73.393938, 270.742036]]
input_correlations: [[0.072859, 0.728268, -0.091816, 0.496014, 0.518520, 0.000000, 0.000000, 0.000000], [0.050735, 0.146577, -0.773802, 0.396345, -0.401600, 0.000000, 0.000000, 0.000000], [0.896059, 0.602531, 0.337495, -0.157339, 0.255890, 0.000000, 0.000000, 0.000000], [0.881994, 0.492028, 0.050180, 0.305529, 0.011639, 0.000000, 0.000000, 0.000000], [-0.187971, -0.274861, 0.329096, 0.369498, 0.811000, 0.000000, 0.000000, 0.000000], [0.810312, 0.028923, 0.444162, -0.576478, 0.104043, 0.000000, 0.000000, 0.000000], [0.307916, 0.880872, 0.547407, 0.327550, 0.351768, 0.000000, 0.000000, 0.000000], [-0.286898, 0.306845, -0.006472, 0.946682, 0.268563, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.259959, -0.669145, 0.879175, 0.953471, 0.815034, 0.390840, 2.018375, 0.810261]
pre_activation_std: [1.296327, 1.212563, 1.244797, 1.216452, 1.179464, 1.852205, 1.405248, 1.421233]
### 2
mean: [0.857910, 0.486753, -1.209371, 1.783218, 1.404333, -2.048735, -0.390830, 1.518356]
std: [1.113244, 0.926390, 0.591008, 1.176521, 1.529503, 1.411285, 0.667637, 1.947232]
fourier: [[19.238180, 19.646723, 19.797350, 21.879293, 77.211853], [13.836752, 14.903612, 16.580613, 17.828210, 43.807735], [9.957733, 10.296854, 10.327276, 10.434608, 108.843390], [18.588464, 19.965021, 20.355387, 22.537918, 160.489641], [24.039274, 25.050823, 25.414169, 26.773037, 126.389927], [21.721058, 23.313380, 25.046677, 26.839284, 184.386141], [9.831108, 10.255101, 10.872666, 11.940517, 35.174684], [33.511593, 33.595230, 33.736849, 37.643144, 136.652028]]
input_correlations: [[0.789927, 0.132487, 0.671262, 0.536047, -0.134725, 0.225523, 0.871660, 0.195665], [0.254707, -0.377684, -0.568080, -0.659513, 0.634973, -0.603012, 0.223285, 0.566781], [-0.449985, 0.110377, -0.044783, 0.035807, -0.891608, -0.060973, -0.517805, -0.635355], [0.703532, -0.120102, 0.739880, 0.513463, 0.411605, 0.498833, 0.904177, 0.286148], [0.454815, 0.077133, 0.951320, 0.797019, -0.170442, 0.706407, 0.732836, -0.096238], [-0.651679, 0.115786, -0.852162, -0.605023, -0.247231, -0.584765, -0.879939, -0.112080], [-0.687237, -0.227174, -0.296237, -0.487132, -0.561486, -0.041528, -0.417067, -0.776603], [0.188277, 0.113661, 0.966750, 0.875824, -0.167484, 0.882547, 0.518849, -0.207358]]
pre_activation_mean: [0.857910, 0.486753, -1.209371, 1.783218, 1.404333, -2.048735, -0.390830, 1.518356]
pre_activation_std: [1.113244, 0.926390, 0.591008, 1.176521, 1.529503, 1.411285, 0.667637, 1.947232]
### 4
mean: [1.190584, 2.260509, 2.020886, 0.960202, 0.333362, -2.181424, 1.195000, 0.054012]
std: [1.484819, 2.441849, 2.120224, 0.714238, 0.774775, 1.722150, 1.256622, 0.650290]
fourier: [[23.207568, 25.279061, 25.295870, 26.257574, 107.152562], [38.826463, 40.814654, 41.847502, 43.286987, 203.445861], [34.013735, 35.070201, 36.003857, 37.436533, 181.879719], [11.189972, 11.631477, 12.411196, 13.248587, 86.418149], [12.179775, 14.770376, 14.906734, 16.019560, 30.002559], [25.372602, 26.644729, 28.136136, 33.823990, 196.328115], [20.495477, 20.793601, 20.903387, 22.684438, 107.550046], [9.906166, 10.267066, 10.343385, 10.548605, 11.740711]]
input_correlations: [[0.798250, -0.353195, -0.036283, 0.778048, 0.994967, 0.717133, -0.325986, 0.960226], [0.810764, -0.373812, -0.076584, 0.753062, 0.994490, 0.696816, -0.347442, 0.953750], [0.825874, -0.306823, -0.003556, 0.805622, 0.997298, 0.740254, -0.341717, 0.946954], [0.651616, 0.395158, 0.603699, 0.978225, 0.712993, 0.856344, -0.292716, 0.626105], [0.536697, -0.550144, -0.110352, 0.610274, 0.893784, 0.567736, -0.196199, 0.970217], [-0.886663, 0.075451, -0.184820, -0.921128, -0.961797, -0.828928, 0.378568, -0.855232], [0.784048, -0.256387, 0.058033, 0.828196, 0.988542, 0.759410, -0.383269, 0.959852], [-0.772430, 0.548279, 0.377844, -0.504325, -0.917026, -0.501658, 0.325773, -0.869528]]
pre_activation_mean: [1.190584, 2.260509, 2.020886, 0.960202, 0.333362, -2.181424, 1.195000, 0.054012]
pre_activation_std: [1.484819, 2.441849, 2.120224, 0.714238, 0.774775, 1.722150, 1.256622, 0.650290]
### 6
mean: [1.978323, -0.242265, 0.005285, 1.154638, -0.185704, 2.209763, 2.264141, -0.123280]
std: [2.575920, 0.355382, 0.356534, 1.761799, 0.502705, 2.500884, 3.062773, 0.616673]
fourier: [[40.349678, 42.564425, 44.884687, 47.427329, 178.049090], [5.528892, 5.603604, 6.650056, 7.190990, 21.803892], [6.279932, 6.448225, 6.477046, 7.301783, 7.314929], [27.843297, 27.890688, 30.477460, 34.145904, 103.917451], [7.912731, 8.073470, 8.820992, 10.565913, 16.713388], [39.959519, 42.528289, 43.516746, 44.232900, 198.878652], [48.277140, 51.142782, 53.523659, 54.155146, 203.772666], [9.636196, 9.724052, 10.346412, 11.095206, 12.777171]]
input_correlations: [[0.997897, 0.998262, 0.993728, 0.653016, 0.927414, 0.766987, 0.989311, -0.726460], [-0.896083, -0.899988, -0.872139, -0.319368, -0.886526, -0.530486, -0.852507, 0.770482], [0.862335, 0.837250, 0.830078, 0.576802, 0.980151, 0.542319, 0.867263, -0.425398], [0.986548, 0.990232, 0.979399, 0.576219, 0.923007, 0.733539, 0.970707, -0.781826], [-0.901597, -0.905891, -0.876504, -0.336705, -0.917824, -0.557760, -0.870331, 0.805044], [0.998831, 0.997500, 0.998167, 0.710253, 0.920405, 0.791690, 0.997079, -0.696340], [0.997543, 0.999335, 0.998708, 0.690158, 0.902991, 0.795266, 0.991918, -0.723685], [-0.891217, -0.900157, -0.868462, -0.299958, -0.884309, -0.550003, -0.854785, 0.831649]]
pre_activation_mean: [1.978323, -0.242265, 0.005285, 1.154638, -0.185704, 2.209763, 2.264141, -0.123280]
pre_activation_std: [2.575920, 0.355382, 0.356534, 1.761799, 0.502705, 2.500884, 3.062773, 0.616673]
### 8
mean: [-0.466181, 2.326093, -0.466871, 0.266028, -0.643092, -0.489581, -0.845832, 2.985955]
std: [1.020587, 3.214919, 0.722840, 0.836602, 0.682405, 0.694844, 1.141287, 4.126569]
fourier: [[16.182390, 16.339269, 18.727641, 18.819877, 41.956306], [51.556354, 53.827910, 56.712554, 58.333049, 209.348349], [11.169143, 12.071001, 12.590094, 13.601017, 42.018358], [13.144108, 13.754554, 14.777821, 15.552115, 23.942495], [10.795123, 10.820400, 12.279971, 12.805446, 57.878299], [10.712847, 10.902689, 12.675479, 14.043495, 44.062257], [17.795303, 18.415343, 21.374375, 21.376328, 76.124838], [64.581440, 69.500771, 71.984286, 75.484139, 268.735961]]
input_correlations: [[-0.998224, 0.662768, -0.867114, -0.998690, 0.624766, -0.991684, -0.993186, 0.581072], [0.999797, -0.631231, 0.862496, 0.996139, -0.601890, 0.998331, 0.998037, -0.558162], [-0.998190, 0.660576, -0.855680, -0.993953, 0.636629, -0.996482, -0.996340, 0.595142], [0.999271, -0.657043, 0.860093, 0.997076, -0.628660, 0.995691, 0.996119, -0.585817], [-0.997583, 0.678699, -0.863227, -0.997772, 0.647646, -0.991901, -0.992101, 0.604250], [-0.965087, 0.798412, -0.808777, -0.973023, 0.773088, -0.950054, -0.955015, 0.735592], [-0.994907, 0.665899, -0.890543, -0.998582, 0.626944, -0.986102, -0.985505, 0.581183], [0.999059, -0.644872, 0.848917, 0.994845, -0.618651, 0.997774, 0.998438, -0.576307]]
pre_activation_mean: [-0.466181, 2.326093, -0.466871, 0.266028, -0.643092, -0.489581, -0.845832, 2.985955]
pre_activation_std: [1.020587, 3.214919, 0.722840, 0.836602, 0.682405, 0.694844, 1.141287, 4.126569]
### 10
mean: [-1.882685]
std: [2.467690]
fourier: [[39.219789, 41.600405, 43.650708, 44.783500, 169.441660]]
input_correlations: [[0.621585, -0.999496, 0.523785, -0.987416, 0.019572, 0.341898, -0.058812, -0.999810]]
pre_activation_mean: [-1.882685]
pre_activation_std: [2.467690]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.10846,
0.045218,
-0.042196,
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],
[
0.403516,
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0.001423,
-0.050466,
0.017462,
-0.044907,
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-0.243618
],
[
-0.226849,
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0.11477,
-0.13264,
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-0.123361,
0.147383,
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],
[
0.064775,
0.389794,
-0.046807,
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0.430375,
0.220615,
-0.178551,
0.371837
],
[
-0.194168,
0.12361,
-0.452034,
-0.452511,
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0.10853,
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],
[
0.423893,
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0.228677,
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0.422968,
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],
"network.8.bias": [
0.152716,
-0.140165,
0.042147,
-0.319818,
-0.113024,
-0.173694,
-0.125868,
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],
"network.10.weight": [
[
0.233764,
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-0.222886,
0.119483,
0.295705,
0.032049,
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],
"network.10.bias": [
-0.130531
]
}
## Activation Signature
### 0
mean: [0.045162, 2.318057, -0.035040, 0.339899, -0.088306, -0.041284, -0.051697, 3.008245]
std: [0.128849, 3.211222, 0.086996, 0.725828, 0.046494, 0.123716, 0.059280, 4.099666]
fourier: [[1.851120, 2.125995, 2.298153, 2.337923, 4.064619], [52.494458, 53.422613, 57.609021, 57.688347, 208.625154], [1.375473, 1.441798, 1.468621, 1.544506, 3.153558], [11.419230, 11.996764, 13.140926, 14.051679, 30.590926], [0.660396, 0.689322, 0.862086, 0.944324, 7.947539], [1.854997, 1.959349, 2.284694, 2.344109, 3.715550], [0.908092, 0.979463, 1.085755, 1.357051, 4.652775], [65.954681, 69.343694, 72.786694, 73.393938, 270.742036]]
input_correlations: [[0.072859, 0.728268, -0.091816, 0.496014, 0.518520, 0.000000, 0.000000, 0.000000], [0.050735, 0.146577, -0.773802, 0.396345, -0.401600, 0.000000, 0.000000, 0.000000], [0.896059, 0.602531, 0.337495, -0.157339, 0.255890, 0.000000, 0.000000, 0.000000], [0.881994, 0.492028, 0.050180, 0.305529, 0.011639, 0.000000, 0.000000, 0.000000], [-0.187971, -0.274861, 0.329096, 0.369498, 0.811000, 0.000000, 0.000000, 0.000000], [0.810312, 0.028923, 0.444162, -0.576478, 0.104043, 0.000000, 0.000000, 0.000000], [0.307916, 0.880872, 0.547407, 0.327550, 0.351768, 0.000000, 0.000000, 0.000000], [-0.286898, 0.306845, -0.006472, 0.946682, 0.268563, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.259959, -0.669145, 0.879175, 0.953471, 0.815034, 0.390840, 2.018375, 0.810261]
pre_activation_std: [1.296327, 1.212563, 1.244797, 1.216452, 1.179464, 1.852205, 1.405248, 1.421233]
### 2
mean: [0.857910, 0.486753, -1.209371, 1.783218, 1.404333, -2.048735, -0.390830, 1.518356]
std: [1.113244, 0.926390, 0.591008, 1.176521, 1.529503, 1.411285, 0.667637, 1.947232]
fourier: [[19.238180, 19.646723, 19.797350, 21.879293, 77.211853], [13.836752, 14.903612, 16.580613, 17.828210, 43.807735], [9.957733, 10.296854, 10.327276, 10.434608, 108.843390], [18.588464, 19.965021, 20.355387, 22.537918, 160.489641], [24.039274, 25.050823, 25.414169, 26.773037, 126.389927], [21.721058, 23.313380, 25.046677, 26.839284, 184.386141], [9.831108, 10.255101, 10.872666, 11.940517, 35.174684], [33.511593, 33.595230, 33.736849, 37.643144, 136.652028]]
input_correlations: [[0.789927, 0.132487, 0.671262, 0.536047, -0.134725, 0.225523, 0.871660, 0.195665], [0.254707, -0.377684, -0.568080, -0.659513, 0.634973, -0.603012, 0.223285, 0.566781], [-0.449985, 0.110377, -0.044783, 0.035807, -0.891608, -0.060973, -0.517805, -0.635355], [0.703532, -0.120102, 0.739880, 0.513463, 0.411605, 0.498833, 0.904177, 0.286148], [0.454815, 0.077133, 0.951320, 0.797019, -0.170442, 0.706407, 0.732836, -0.096238], [-0.651679, 0.115786, -0.852162, -0.605023, -0.247231, -0.584765, -0.879939, -0.112080], [-0.687237, -0.227174, -0.296237, -0.487132, -0.561486, -0.041528, -0.417067, -0.776603], [0.188277, 0.113661, 0.966750, 0.875824, -0.167484, 0.882547, 0.518849, -0.207358]]
pre_activation_mean: [0.857910, 0.486753, -1.209371, 1.783218, 1.404333, -2.048735, -0.390830, 1.518356]
pre_activation_std: [1.113244, 0.926390, 0.591008, 1.176521, 1.529503, 1.411285, 0.667637, 1.947232]
### 4
mean: [1.190584, 2.260509, 2.020886, 0.960202, 0.333362, -2.181424, 1.195000, 0.054012]
std: [1.484819, 2.441849, 2.120224, 0.714238, 0.774775, 1.722150, 1.256622, 0.650290]
fourier: [[23.207568, 25.279061, 25.295870, 26.257574, 107.152562], [38.826463, 40.814654, 41.847502, 43.286987, 203.445861], [34.013735, 35.070201, 36.003857, 37.436533, 181.879719], [11.189972, 11.631477, 12.411196, 13.248587, 86.418149], [12.179775, 14.770376, 14.906734, 16.019560, 30.002559], [25.372602, 26.644729, 28.136136, 33.823990, 196.328115], [20.495477, 20.793601, 20.903387, 22.684438, 107.550046], [9.906166, 10.267066, 10.343385, 10.548605, 11.740711]]
input_correlations: [[0.798250, -0.353195, -0.036283, 0.778048, 0.994967, 0.717133, -0.325986, 0.960226], [0.810764, -0.373812, -0.076584, 0.753062, 0.994490, 0.696816, -0.347442, 0.953750], [0.825874, -0.306823, -0.003556, 0.805622, 0.997298, 0.740254, -0.341717, 0.946954], [0.651616, 0.395158, 0.603699, 0.978225, 0.712993, 0.856344, -0.292716, 0.626105], [0.536697, -0.550144, -0.110352, 0.610274, 0.893784, 0.567736, -0.196199, 0.970217], [-0.886663, 0.075451, -0.184820, -0.921128, -0.961797, -0.828928, 0.378568, -0.855232], [0.784048, -0.256387, 0.058033, 0.828196, 0.988542, 0.759410, -0.383269, 0.959852], [-0.772430, 0.548279, 0.377844, -0.504325, -0.917026, -0.501658, 0.325773, -0.869528]]
pre_activation_mean: [1.190584, 2.260509, 2.020886, 0.960202, 0.333362, -2.181424, 1.195000, 0.054012]
pre_activation_std: [1.484819, 2.441849, 2.120224, 0.714238, 0.774775, 1.722150, 1.256622, 0.650290]
### 6
mean: [1.978323, -0.242265, 0.005285, 1.154638, -0.185704, 2.209763, 2.264141, -0.123280]
std: [2.575920, 0.355382, 0.356534, 1.761799, 0.502705, 2.500884, 3.062773, 0.616673]
fourier: [[40.349678, 42.564425, 44.884687, 47.427329, 178.049090], [5.528892, 5.603604, 6.650056, 7.190990, 21.803892], [6.279932, 6.448225, 6.477046, 7.301783, 7.314929], [27.843297, 27.890688, 30.477460, 34.145904, 103.917451], [7.912731, 8.073470, 8.820992, 10.565913, 16.713388], [39.959519, 42.528289, 43.516746, 44.232900, 198.878652], [48.277140, 51.142782, 53.523659, 54.155146, 203.772666], [9.636196, 9.724052, 10.346412, 11.095206, 12.777171]]
input_correlations: [[0.997897, 0.998262, 0.993728, 0.653016, 0.927414, 0.766987, 0.989311, -0.726460], [-0.896083, -0.899988, -0.872139, -0.319368, -0.886526, -0.530486, -0.852507, 0.770482], [0.862335, 0.837250, 0.830078, 0.576802, 0.980151, 0.542319, 0.867263, -0.425398], [0.986548, 0.990232, 0.979399, 0.576219, 0.923007, 0.733539, 0.970707, -0.781826], [-0.901597, -0.905891, -0.876504, -0.336705, -0.917824, -0.557760, -0.870331, 0.805044], [0.998831, 0.997500, 0.998167, 0.710253, 0.920405, 0.791690, 0.997079, -0.696340], [0.997543, 0.999335, 0.998708, 0.690158, 0.902991, 0.795266, 0.991918, -0.723685], [-0.891217, -0.900157, -0.868462, -0.299958, -0.884309, -0.550003, -0.854785, 0.831649]]
pre_activation_mean: [1.978323, -0.242265, 0.005285, 1.154638, -0.185704, 2.209763, 2.264141, -0.123280]
pre_activation_std: [2.575920, 0.355382, 0.356534, 1.761799, 0.502705, 2.500884, 3.062773, 0.616673]
### 8
mean: [-0.466181, 2.326093, -0.466871, 0.266028, -0.643092, -0.489581, -0.845832, 2.985955]
std: [1.020587, 3.214919, 0.722840, 0.836602, 0.682405, 0.694844, 1.141287, 4.126569]
fourier: [[16.182390, 16.339269, 18.727641, 18.819877, 41.956306], [51.556354, 53.827910, 56.712554, 58.333049, 209.348349], [11.169143, 12.071001, 12.590094, 13.601017, 42.018358], [13.144108, 13.754554, 14.777821, 15.552115, 23.942495], [10.795123, 10.820400, 12.279971, 12.805446, 57.878299], [10.712847, 10.902689, 12.675479, 14.043495, 44.062257], [17.795303, 18.415343, 21.374375, 21.376328, 76.124838], [64.581440, 69.500771, 71.984286, 75.484139, 268.735961]]
input_correlations: [[-0.998224, 0.662768, -0.867114, -0.998690, 0.624766, -0.991684, -0.993186, 0.581072], [0.999797, -0.631231, 0.862496, 0.996139, -0.601890, 0.998331, 0.998037, -0.558162], [-0.998190, 0.660576, -0.855680, -0.993953, 0.636629, -0.996482, -0.996340, 0.595142], [0.999271, -0.657043, 0.860093, 0.997076, -0.628660, 0.995691, 0.996119, -0.585817], [-0.997583, 0.678699, -0.863227, -0.997772, 0.647646, -0.991901, -0.992101, 0.604250], [-0.965087, 0.798412, -0.808777, -0.973023, 0.773088, -0.950054, -0.955015, 0.735592], [-0.994907, 0.665899, -0.890543, -0.998582, 0.626944, -0.986102, -0.985505, 0.581183], [0.999059, -0.644872, 0.848917, 0.994845, -0.618651, 0.997774, 0.998438, -0.576307]]
pre_activation_mean: [-0.466181, 2.326093, -0.466871, 0.266028, -0.643092, -0.489581, -0.845832, 2.985955]
pre_activation_std: [1.020587, 3.214919, 0.722840, 0.836602, 0.682405, 0.694844, 1.141287, 4.126569]
### 10
mean: [-1.882685]
std: [2.467690]
fourier: [[39.219789, 41.600405, 43.650708, 44.783500, 169.441660]]
input_correlations: [[0.621585, -0.999496, 0.523785, -0.987416, 0.019572, 0.341898, -0.058812, -0.999810]]
pre_activation_mean: [-1.882685]
pre_activation_std: [2.467690]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.04516243934631348, "std": 0.1288488209247589, "fourier": [1.8511197039402945, 2.1259946736744735, 2.2981527125341072, 2.3379230200337426, 4.064619381446391], "input_correlations": [0.07285921982876614, 0.7282683532086065, -0.09181635181154102, 0.496013838425075, 0.5185201245018167, 0.0, 0.0, 0.0], "pre_activation_mean": 1.2599585056304932, "pre_activation_std": 1.296326756477356}, "1": {"mean": 2.318057060241699, "std": 3.2112221717834473, "fourier": [52.494457507566125, 53.422613333502, 57.60902076831894, 57.688347374457464, 208.62515374878421], "input_correlations": [0.050735214379157116, 0.14657714309901873, -0.7738016116819223, 0.39634457832809034, -0.4015995034459695, 0.0, 0.0, 0.0], "pre_activation_mean": -0.6691451668739319, "pre_activation_std": 1.2125632762908936}, "2": {"mean": -0.03503953665494919, "std": 0.08699585497379303, "fourier": [1.3754725371953707, 1.4417983092648938, 1.4686212463876207, 1.5445061626664718, 3.153558302688907], "input_correlations": [0.8960586962061298, 0.6025307057410563, 0.3374949520075353, -0.15733883668847132, 0.25588984141163573, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8791752457618713, "pre_activation_std": 1.2447965145111084}, "3": {"mean": 0.3398991823196411, "std": 0.725828230381012, "fourier": [11.419230378896101, 11.99676403875274, 13.140926476600708, 14.051679108342242, 30.590925509110093], "input_correlations": [0.8819939182290744, 0.49202770679584956, 0.05018038948627705, 0.30552917118819806, 0.011638801000141528, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9534707069396973, "pre_activation_std": 1.2164522409439087}, "4": {"mean": -0.08830597996711731, "std": 0.04649379476904869, "fourier": [0.6603958898560132, 0.6893217086578693, 0.8620855622312293, 0.9443241024063972, 7.947538535343483], "input_correlations": [-0.1879709582761796, -0.27486146653109833, 0.32909581624499384, 0.3694975975609688, 0.8109998244826656, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8150335550308228, "pre_activation_std": 1.179463505744934}, "5": {"mean": -0.04128388687968254, "std": 0.12371643632650375, "fourier": [1.8549969446566306, 1.9593494809107377, 2.284694297831736, 2.344108542811524, 3.7155497879721224], "input_correlations": [0.8103124840806786, 0.028923060246870948, 0.44416180471492434, -0.5764782266440349, 0.10404261060258482, 0.0, 0.0, 0.0], "pre_activation_mean": 0.3908402621746063, "pre_activation_std": 1.85220468044281}, "6": {"mean": -0.051697492599487305, "std": 0.05928043648600578, "fourier": [0.9080922327853274, 0.9794633775979675, 1.0857553189674667, 1.3570509659910364, 4.652774948073784], "input_correlations": [0.3079162265107694, 0.8808722658808129, 0.5474066418555814, 0.327550334144046, 0.35176823176895394, 0.0, 0.0, 0.0], "pre_activation_mean": 2.0183749198913574, "pre_activation_std": 1.4052475690841675}, "7": {"mean": 3.008244752883911, "std": 4.099665641784668, "fourier": [65.95468084758306, 69.34369425483823, 72.78669373506247, 73.3939380051771, 270.7420358581003], "input_correlations": [-0.2868981475199687, 0.30684467686055994, -0.006472272193655847, 0.9466817950224821, 0.26856270107453806, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8102607131004333, "pre_activation_std": 1.4212331771850586}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.8579095005989075, "std": 1.113243818283081, "fourier": [19.238179544282424, 19.6467226845813, 19.797350325493916, 21.87929311317193, 77.21185331046581], "input_correlations": [0.7899266363765598, 0.132487039639788, 0.6712618612669753, 0.5360465728297301, -0.134725149537496, 0.2255228939889584, 0.8716595984732156, 0.19566523050374776], "pre_activation_mean": 0.8579095005989075, "pre_activation_std": 1.113243818283081}, "1": {"mean": 0.48675262928009033, "std": 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0.349498, 0.372405, 0.262599, -0.109795], [-0.395666, 0.051161, -0.231079, 0.271577, -0.170959, 0.04507, 0.454073, -0.191568], [0.274028, 0.237238, -0.464272, 0.077602, 0.49683, -0.049111, 0.0036, 0.260046], [0.040472, 0.296725, 0.248122, -0.39761, 0.349797, 0.179193, 0.209299, -0.536135], [-0.015986, -0.319877, 0.271025, 0.224269, -0.347816, 0.021136, -0.05521, 0.208184], [0.175678, 0.47518, 0.04409, 0.202426, 0.240546, -0.236656, 0.499068, -0.413798], [0.228738, 0.585747, 0.463982, 0.082663, -0.000368, 0.310831, 0.07745, -0.544077], [0.132373, -0.299623, 0.078493, 0.435091, -0.276188, 0.144738, -0.150304, 0.146849]], "network.6.bias": [0.034548, -0.095983, -0.218848, 0.065951, -0.035943, 0.119825, -0.221936, 0.106308], "network.8.weight": [[-0.234228, 0.366328, -0.389323, -0.121512, 0.020743, 0.379295, -0.347984, 0.036381], [0.31275, -0.338253, 0.194253, 0.345422, -0.227844, 0.507091, 0.147744, 0.011698], [-0.248531, -0.117751, -0.090096, 0.10846, 0.045218, -0.042196, -0.035718, 0.251485], [0.403516, 0.217088, 0.001423, -0.050466, 0.017462, -0.044907, -0.007501, -0.243618], [-0.226849, 0.224865, 0.11477, -0.13264, 0.084148, -0.123361, 0.147383, 0.050054], [0.064775, 0.389794, -0.046807, -0.431277, 0.430375, 0.220615, -0.178551, 0.371837], [-0.194168, 0.12361, -0.452034, -0.452511, 0.344171, 0.10853, -0.002818, -0.072711], [0.423893, -0.332626, -0.056166, 0.228677, -0.241237, 0.422968, 0.485105, -0.500477]], "network.8.bias": [0.152716, -0.140165, 0.042147, -0.319818, -0.113024, -0.173694, -0.125868, -0.101041], "network.10.weight": [[0.233764, -0.225586, 0.04803, -0.222886, 0.119483, 0.295705, 0.032049, -0.378272]], "network.10.bias": [-0.130531]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6829759180545807, "train_acc": 0.575, "val_loss": 0.7037037014961243, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6778037846088409, "train_acc": 0.575, "val_loss": 0.7097249031066895, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6583892405033112, "train_acc": 0.575, "val_loss": 0.6677227020263672, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6387482285499573, "train_acc": 0.505, "val_loss": 0.5485349893569946, "val_acc": 0.48}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5437440574169159, "train_acc": 0.58, "val_loss": 0.4660395681858063, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4886515140533447, "train_acc": 0.785, "val_loss": 0.40313920378685, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.4024072289466858, "train_acc": 0.84, "val_loss": 0.9145920276641846, "val_acc": 0.74}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.6605874598026276, "train_acc": 0.76, "val_loss": 0.40045875310897827, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4421398490667343, "train_acc": 0.795, "val_loss": 0.4077063798904419, "val_acc": 0.86}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.480249360203743, "train_acc": 0.755, "val_loss": 0.3842560648918152, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.45351023972034454, "train_acc": 0.77, "val_loss": 0.3826461732387543, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.4334239065647125, "train_acc": 0.79, "val_loss": 0.3784541189670563, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.43388631939888, "train_acc": 0.825, "val_loss": 0.38121551275253296, "val_acc": 0.88}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.7037037014961243, "final_val_loss": 0.6677227020263672, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5485349893569946, "final_val_loss": 0.38121551275253296, "initial_val_acc": 0.48, "final_val_acc": 0.88, "best_val_acc": 0.88, "best_epoch": 4}, "improvement": 0.4, "first_improvement_epoch": 2}} |
34 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.46, "improved_accuracy": 0.98, "improvement": 0.52, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2876, "learning_rate": 0.052811634834035476, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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0.386287,
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0.846631
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[
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0.311951,
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[
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[
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[
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"network.6.weight": [
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"network.8.weight": [
[
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}
## Activation Signature
### 0
mean: [0.000000, 12.072610, 11.478702, 0.000000, 18.366211, 9.447713, 0.097497]
std: [0.000000, 10.623223, 10.173478, 0.000000, 16.257254, 8.445078, 0.213243]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [171.167501, 186.053407, 188.265031, 188.960749, 1086.534883], [163.414485, 178.084043, 179.807150, 180.796095, 1033.083155], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [261.616085, 284.829430, 287.841754, 289.159188, 1652.959021], [135.912642, 147.929875, 149.473120, 149.860956, 850.294174], [3.537486, 3.589771, 3.713037, 3.745172, 8.774734]]
input_correlations: [[0.555678, 0.909747, 0.383269, 0.329843, -0.176089, 0.000000, 0.000000, 0.000000], [-0.499938, -0.504372, -0.899769, -0.315766, -0.355398, 0.000000, 0.000000, 0.000000], [0.465115, 0.597265, 0.055794, 0.493566, -0.500953, 0.000000, 0.000000, 0.000000], [0.829237, 0.649125, 0.574839, 0.119779, -0.082432, 0.000000, 0.000000, 0.000000], [0.911405, 0.358799, 0.383911, -0.390932, 0.120913, 0.000000, 0.000000, 0.000000], [-0.697749, -0.738807, -0.030735, -0.197432, 0.314768, 0.000000, 0.000000, 0.000000], [0.608547, 0.779301, 0.614580, -0.131452, 0.028180, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.356470, -1.911130, 0.875137, 2.605041, 0.826315, -1.313323, 2.259142]
pre_activation_std: [2.045266, 1.376321, 1.748337, 2.092610, 2.269359, 2.074734, 2.292696]
### 2
mean: [-0.362878, 2.227465, -0.741237, 6.017173, 4.573203, -1.164149, 2.311569]
std: [0.722412, 2.060528, 1.116990, 5.274299, 4.002064, 0.623529, 2.212412]
fourier: [[11.947032, 12.071714, 12.381931, 13.261679, 32.659028], [34.848907, 35.529854, 35.700671, 37.041772, 200.471840], [18.417975, 19.190036, 19.207128, 19.550922, 66.711313], [88.656286, 90.828549, 90.995840, 95.690979, 541.545634], [65.409968, 68.112909, 69.800776, 72.584325, 411.588240], [9.516952, 10.731136, 11.533795, 11.578420, 104.773382], [34.821375, 34.987877, 39.737668, 43.203045, 208.041252]]
input_correlations: [[-0.617385, 0.156466, -0.603554, -0.207310, 0.262451, 0.388835, -0.237728, 0.000000], [0.941381, -0.362157, 0.661444, 0.909954, 0.722089, -0.214109, 0.971362, 0.000000], [-0.847457, 0.349015, -0.572420, -0.956130, -0.844809, 0.181370, -0.962990, 0.000000], [0.954657, -0.348837, 0.775665, 0.966702, 0.778031, -0.329029, 0.916968, 0.000000], [0.951723, -0.345027, 0.802672, 0.976632, 0.782544, -0.360511, 0.887343, 0.000000], [-0.912148, 0.358708, -0.859021, -0.977457, -0.797543, 0.314276, -0.803097, 0.000000], [0.819385, -0.289178, 0.717026, 0.979843, 0.914309, -0.376610, 0.823557, 0.000000]]
pre_activation_mean: [-0.362878, 2.227465, -0.741237, 6.017173, 4.573203, -1.164149, 2.311569]
pre_activation_std: [0.722412, 2.060528, 1.116990, 5.274299, 4.002064, 0.623529, 2.212412]
### 4
mean: [-1.149015, 10.749777, -2.189774, -3.135725, -1.300652, 10.049279, 3.155539]
std: [0.741958, 9.322933, 1.945019, 3.432027, 0.898376, 8.864851, 3.089184]
fourier: [[12.161352, 13.310464, 14.038568, 14.218738, 103.411389], [150.880346, 161.958112, 164.825566, 165.048731, 967.479869], [31.523523, 33.910518, 33.969108, 34.272135, 197.079697], [56.820689, 59.229544, 60.515196, 62.039811, 282.215206], [15.114645, 15.898745, 16.310869, 17.123166, 117.058695], [144.559374, 154.634082, 155.353087, 157.823513, 904.435161], [50.788961, 52.938055, 54.469866, 55.381026, 283.998479]]
input_correlations: [[0.204496, -0.974468, 0.564843, -0.961430, -0.946792, 0.000000, -0.812192, 0.000000], [-0.020820, 0.962972, -0.581159, 0.997874, 0.998486, 0.000000, 0.960209, 0.000000], [0.031906, -0.951604, 0.540910, -0.995481, -0.998533, 0.000000, -0.961873, 0.000000], [0.049885, -0.975514, 0.588949, -0.999285, -0.996192, 0.000000, -0.946071, 0.000000], [0.169684, -0.974036, 0.549755, -0.987241, -0.980439, 0.000000, -0.880504, 0.000000], [-0.026867, 0.971093, -0.582195, 0.999284, 0.997621, 0.000000, 0.952202, 0.000000], [0.061809, 0.928339, -0.560422, 0.981029, 0.987499, 0.000000, 0.988248, 0.000000]]
pre_activation_mean: [-1.149015, 10.749777, -2.189774, -3.135725, -1.300652, 10.049279, 3.155539]
pre_activation_std: [0.741958, 9.322933, 1.945019, 3.432027, 0.898376, 8.864851, 3.089184]
### 6
mean: [-4.946860, 13.300151, -4.153483, -1.532753, 13.079841, -5.352778, 0.909825]
std: [4.053318, 11.580332, 3.528162, 1.293317, 11.664688, 4.594761, 0.478535]
fourier: [[65.750433, 70.637067, 71.034295, 71.539123, 445.217378], [187.590139, 201.306709, 204.615648, 205.845359, 1197.013535], [58.205064, 61.211964, 61.670946, 62.918125, 373.813474], [21.394317, 22.475792, 22.683525, 23.373120, 137.947711], [188.908019, 202.820476, 206.129000, 206.494605, 1177.185722], [74.528936, 80.110222, 80.736719, 81.555644, 481.750050], [7.659875, 7.847198, 8.362353, 8.463810, 81.884208]]
input_correlations: [[0.000000, -0.999837, 0.124754, 0.484480, 0.000000, -0.999182, -0.992397, 0.000000], [0.000000, 0.999868, -0.128386, -0.505960, 0.000000, 0.999708, 0.989229, 0.000000], [0.000000, -0.999587, 0.129944, 0.504684, 0.000000, -0.998250, -0.993954, 0.000000], [0.000000, -0.999093, 0.126406, 0.493710, 0.000000, -0.999391, -0.984939, 0.000000], [0.000000, 0.999948, -0.128464, -0.503402, 0.000000, 0.999502, 0.990798, 0.000000], [0.000000, -0.999707, 0.125238, 0.494752, 0.000000, -0.999956, -0.988367, 0.000000], [0.000000, 0.964363, -0.078970, -0.261624, 0.000000, 0.963041, 0.973148, 0.000000]]
pre_activation_mean: [-4.946860, 13.300151, -4.153483, -1.532753, 13.079841, -5.352778, 0.909825]
pre_activation_std: [4.053318, 11.580332, 3.528162, 1.293317, 11.664688, 4.594761, 0.478535]
### 8
mean: [-4.776248, 12.062181, 11.474191, -1.548473, 18.349787, 9.439658, -3.119778]
std: [4.069311, 10.635177, 10.178588, 0.993932, 16.275976, 8.454167, 3.318429]
fourier: [[65.581100, 71.294095, 71.435517, 72.162759, 429.862309], [171.594042, 185.741848, 188.618832, 188.858323, 1085.596396], [163.684452, 177.953018, 179.955085, 180.754726, 1032.677192], [16.074299, 17.354775, 17.522706, 17.622066, 139.362567], [262.295490, 284.347318, 288.388195, 289.004129, 1651.480835], [136.261474, 147.710522, 149.719985, 149.796166, 849.569195], [53.928985, 57.853076, 58.810116, 59.149127, 280.780032]]
input_correlations: [[0.000000, -0.999752, 0.158033, 0.000000, -0.999930, 0.000000, -0.967691, 0.000000], [0.000000, 0.999989, -0.168161, 0.000000, 0.999942, 0.000000, 0.962035, 0.000000], [0.000000, 0.999966, -0.165281, 0.000000, 0.999991, 0.000000, 0.963706, 0.000000], [0.000000, -0.999936, 0.162871, 0.000000, -0.999875, 0.000000, -0.964739, 0.000000], [0.000000, 0.999987, -0.167228, 0.000000, 0.999962, 0.000000, 0.962578, 0.000000], [0.000000, 0.999988, -0.165273, 0.000000, 0.999968, 0.000000, 0.963625, 0.000000], [0.000000, -0.999959, 0.171445, 0.000000, -0.999791, 0.000000, -0.959941, 0.000000]]
pre_activation_mean: [-4.776248, 12.062181, 11.474191, -1.548473, 18.349787, 9.439658, -3.119778]
pre_activation_std: [4.069311, 10.635177, 10.178588, 0.993932, 16.275976, 8.454167, 3.318429]
### 10
mean: [-21.463930]
std: [19.304775]
fourier: [[311.020426, 338.076524, 342.094887, 343.485959, 1931.753632]]
input_correlations: [[0.000000, -0.999999, -0.999982, 0.000000, -0.999995, -0.999970, 0.501864, 0.000000]]
pre_activation_mean: [-21.463930]
pre_activation_std: [19.304775]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.324493,
0.787038,
0.196225,
0.150508,
-0.328995
],
[
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],
[
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0.45097,
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],
[
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0.382206,
0.086179,
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],
[
0.87893,
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0.100329,
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0.031015
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[
-0.685339,
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0.224855,
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0.45944
],
[
0.262119,
0.910709,
0.462887,
-0.394297,
-0.053899
]
],
"network.0.bias": [
0.191609,
0.091704,
-0.252599,
0.511542,
-0.006488,
-0.169596,
0.218541
],
"network.2.weight": [
[
-0.290509,
-0.025704,
-0.226453,
0.178922,
0.286453,
0.288758,
-0.105485
],
[
0.569331,
-0.007863,
-0.030981,
-0.097227,
0.142922,
0.186055,
0.479164
],
[
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0.212962,
0.193608,
-0.339106,
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-0.121674,
-0.1552
],
[
0.741942,
0.223563,
0.686036,
0.409689,
0.386287,
-0.364657,
0.846631
],
[
0.720368,
0.146354,
0.311951,
0.658836,
0.284685,
-0.349026,
0.245147
],
[
-0.065313,
0.046065,
-0.12019,
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-0.056925,
-0.058714,
0.027123
],
[
-0.013259,
-0.005774,
0.15302,
0.606879,
0.433971,
-0.438728,
0.012865
]
],
"network.2.bias": [
-0.034232,
-0.17459,
0.637607,
-0.0597,
-0.111301,
-0.405797,
0.082042
],
"network.4.weight": [
[
-0.01006,
0.002436,
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0.287982
],
[
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0.299811,
-0.584367,
0.743792,
0.804741,
0.001579,
0.757292
],
[
-0.05201,
0.181785,
-0.462667,
-0.315226,
-0.14004,
0.285638,
-0.067654
],
[
0.404587,
-0.393803,
0.304357,
-0.287171,
-0.120792,
-0.300998,
-0.301434
],
[
0.083119,
0.085726,
-0.246416,
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-0.006852,
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0.19869
],
[
0.061945,
0.58597,
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0.80365,
0.614737,
0.187395,
0.49695
],
[
0.179214,
0.080144,
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0.004129,
0.341253,
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0.723081
]
],
"network.4.bias": [
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0.165126,
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"network.6.weight": [
[
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[
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0.585202,
0.053094
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[
0.264945,
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0.215315,
0.247603,
0.252366,
-0.000802,
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],
[
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0.26349,
0.107999,
0.193302
],
[
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0.557671,
0.345247
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[
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0.029714,
0.170854,
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[
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],
"network.6.bias": [
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0.070972,
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0.291195
],
"network.8.weight": [
[
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],
[
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[
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[
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[
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[
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 12.072610, 11.478702, 0.000000, 18.366211, 9.447713, 0.097497]
std: [0.000000, 10.623223, 10.173478, 0.000000, 16.257254, 8.445078, 0.213243]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [171.167501, 186.053407, 188.265031, 188.960749, 1086.534883], [163.414485, 178.084043, 179.807150, 180.796095, 1033.083155], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [261.616085, 284.829430, 287.841754, 289.159188, 1652.959021], [135.912642, 147.929875, 149.473120, 149.860956, 850.294174], [3.537486, 3.589771, 3.713037, 3.745172, 8.774734]]
input_correlations: [[0.555678, 0.909747, 0.383269, 0.329843, -0.176089, 0.000000, 0.000000, 0.000000], [-0.499938, -0.504372, -0.899769, -0.315766, -0.355398, 0.000000, 0.000000, 0.000000], [0.465115, 0.597265, 0.055794, 0.493566, -0.500953, 0.000000, 0.000000, 0.000000], [0.829237, 0.649125, 0.574839, 0.119779, -0.082432, 0.000000, 0.000000, 0.000000], [0.911405, 0.358799, 0.383911, -0.390932, 0.120913, 0.000000, 0.000000, 0.000000], [-0.697749, -0.738807, -0.030735, -0.197432, 0.314768, 0.000000, 0.000000, 0.000000], [0.608547, 0.779301, 0.614580, -0.131452, 0.028180, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.356470, -1.911130, 0.875137, 2.605041, 0.826315, -1.313323, 2.259142]
pre_activation_std: [2.045266, 1.376321, 1.748337, 2.092610, 2.269359, 2.074734, 2.292696]
### 2
mean: [-0.362878, 2.227465, -0.741237, 6.017173, 4.573203, -1.164149, 2.311569]
std: [0.722412, 2.060528, 1.116990, 5.274299, 4.002064, 0.623529, 2.212412]
fourier: [[11.947032, 12.071714, 12.381931, 13.261679, 32.659028], [34.848907, 35.529854, 35.700671, 37.041772, 200.471840], [18.417975, 19.190036, 19.207128, 19.550922, 66.711313], [88.656286, 90.828549, 90.995840, 95.690979, 541.545634], [65.409968, 68.112909, 69.800776, 72.584325, 411.588240], [9.516952, 10.731136, 11.533795, 11.578420, 104.773382], [34.821375, 34.987877, 39.737668, 43.203045, 208.041252]]
input_correlations: [[-0.617385, 0.156466, -0.603554, -0.207310, 0.262451, 0.388835, -0.237728, 0.000000], [0.941381, -0.362157, 0.661444, 0.909954, 0.722089, -0.214109, 0.971362, 0.000000], [-0.847457, 0.349015, -0.572420, -0.956130, -0.844809, 0.181370, -0.962990, 0.000000], [0.954657, -0.348837, 0.775665, 0.966702, 0.778031, -0.329029, 0.916968, 0.000000], [0.951723, -0.345027, 0.802672, 0.976632, 0.782544, -0.360511, 0.887343, 0.000000], [-0.912148, 0.358708, -0.859021, -0.977457, -0.797543, 0.314276, -0.803097, 0.000000], [0.819385, -0.289178, 0.717026, 0.979843, 0.914309, -0.376610, 0.823557, 0.000000]]
pre_activation_mean: [-0.362878, 2.227465, -0.741237, 6.017173, 4.573203, -1.164149, 2.311569]
pre_activation_std: [0.722412, 2.060528, 1.116990, 5.274299, 4.002064, 0.623529, 2.212412]
### 4
mean: [-1.149015, 10.749777, -2.189774, -3.135725, -1.300652, 10.049279, 3.155539]
std: [0.741958, 9.322933, 1.945019, 3.432027, 0.898376, 8.864851, 3.089184]
fourier: [[12.161352, 13.310464, 14.038568, 14.218738, 103.411389], [150.880346, 161.958112, 164.825566, 165.048731, 967.479869], [31.523523, 33.910518, 33.969108, 34.272135, 197.079697], [56.820689, 59.229544, 60.515196, 62.039811, 282.215206], [15.114645, 15.898745, 16.310869, 17.123166, 117.058695], [144.559374, 154.634082, 155.353087, 157.823513, 904.435161], [50.788961, 52.938055, 54.469866, 55.381026, 283.998479]]
input_correlations: [[0.204496, -0.974468, 0.564843, -0.961430, -0.946792, 0.000000, -0.812192, 0.000000], [-0.020820, 0.962972, -0.581159, 0.997874, 0.998486, 0.000000, 0.960209, 0.000000], [0.031906, -0.951604, 0.540910, -0.995481, -0.998533, 0.000000, -0.961873, 0.000000], [0.049885, -0.975514, 0.588949, -0.999285, -0.996192, 0.000000, -0.946071, 0.000000], [0.169684, -0.974036, 0.549755, -0.987241, -0.980439, 0.000000, -0.880504, 0.000000], [-0.026867, 0.971093, -0.582195, 0.999284, 0.997621, 0.000000, 0.952202, 0.000000], [0.061809, 0.928339, -0.560422, 0.981029, 0.987499, 0.000000, 0.988248, 0.000000]]
pre_activation_mean: [-1.149015, 10.749777, -2.189774, -3.135725, -1.300652, 10.049279, 3.155539]
pre_activation_std: [0.741958, 9.322933, 1.945019, 3.432027, 0.898376, 8.864851, 3.089184]
### 6
mean: [-4.946860, 13.300151, -4.153483, -1.532753, 13.079841, -5.352778, 0.909825]
std: [4.053318, 11.580332, 3.528162, 1.293317, 11.664688, 4.594761, 0.478535]
fourier: [[65.750433, 70.637067, 71.034295, 71.539123, 445.217378], [187.590139, 201.306709, 204.615648, 205.845359, 1197.013535], [58.205064, 61.211964, 61.670946, 62.918125, 373.813474], [21.394317, 22.475792, 22.683525, 23.373120, 137.947711], [188.908019, 202.820476, 206.129000, 206.494605, 1177.185722], [74.528936, 80.110222, 80.736719, 81.555644, 481.750050], [7.659875, 7.847198, 8.362353, 8.463810, 81.884208]]
input_correlations: [[0.000000, -0.999837, 0.124754, 0.484480, 0.000000, -0.999182, -0.992397, 0.000000], [0.000000, 0.999868, -0.128386, -0.505960, 0.000000, 0.999708, 0.989229, 0.000000], [0.000000, -0.999587, 0.129944, 0.504684, 0.000000, -0.998250, -0.993954, 0.000000], [0.000000, -0.999093, 0.126406, 0.493710, 0.000000, -0.999391, -0.984939, 0.000000], [0.000000, 0.999948, -0.128464, -0.503402, 0.000000, 0.999502, 0.990798, 0.000000], [0.000000, -0.999707, 0.125238, 0.494752, 0.000000, -0.999956, -0.988367, 0.000000], [0.000000, 0.964363, -0.078970, -0.261624, 0.000000, 0.963041, 0.973148, 0.000000]]
pre_activation_mean: [-4.946860, 13.300151, -4.153483, -1.532753, 13.079841, -5.352778, 0.909825]
pre_activation_std: [4.053318, 11.580332, 3.528162, 1.293317, 11.664688, 4.594761, 0.478535]
### 8
mean: [-4.776248, 12.062181, 11.474191, -1.548473, 18.349787, 9.439658, -3.119778]
std: [4.069311, 10.635177, 10.178588, 0.993932, 16.275976, 8.454167, 3.318429]
fourier: [[65.581100, 71.294095, 71.435517, 72.162759, 429.862309], [171.594042, 185.741848, 188.618832, 188.858323, 1085.596396], [163.684452, 177.953018, 179.955085, 180.754726, 1032.677192], [16.074299, 17.354775, 17.522706, 17.622066, 139.362567], [262.295490, 284.347318, 288.388195, 289.004129, 1651.480835], [136.261474, 147.710522, 149.719985, 149.796166, 849.569195], [53.928985, 57.853076, 58.810116, 59.149127, 280.780032]]
input_correlations: [[0.000000, -0.999752, 0.158033, 0.000000, -0.999930, 0.000000, -0.967691, 0.000000], [0.000000, 0.999989, -0.168161, 0.000000, 0.999942, 0.000000, 0.962035, 0.000000], [0.000000, 0.999966, -0.165281, 0.000000, 0.999991, 0.000000, 0.963706, 0.000000], [0.000000, -0.999936, 0.162871, 0.000000, -0.999875, 0.000000, -0.964739, 0.000000], [0.000000, 0.999987, -0.167228, 0.000000, 0.999962, 0.000000, 0.962578, 0.000000], [0.000000, 0.999988, -0.165273, 0.000000, 0.999968, 0.000000, 0.963625, 0.000000], [0.000000, -0.999959, 0.171445, 0.000000, -0.999791, 0.000000, -0.959941, 0.000000]]
pre_activation_mean: [-4.776248, 12.062181, 11.474191, -1.548473, 18.349787, 9.439658, -3.119778]
pre_activation_std: [4.069311, 10.635177, 10.178588, 0.993932, 16.275976, 8.454167, 3.318429]
### 10
mean: [-21.463930]
std: [19.304775]
fourier: [[311.020426, 338.076524, 342.094887, 343.485959, 1931.753632]]
input_correlations: [[0.000000, -0.999999, -0.999982, 0.000000, -0.999995, -0.999970, 0.501864, 0.000000]]
pre_activation_mean: [-21.463930]
pre_activation_std: [19.304775]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"pre_activation_mean", "pre_activation_std"]}}, "10": {"neuron_profiles": {"0": {"mean": -21.463930130004883, "std": 19.30477523803711, "fourier": [311.02042590644385, 338.0765243323646, 342.09488708892457, 343.4859589434898, 1931.7536316514015], "input_correlations": [0.0, -0.9999988888665308, -0.9999817839169931, 0.0, -0.9999946699836196, -0.9999701663014827, 0.5018644701528292, 0.0], "pre_activation_mean": -21.463930130004883, "pre_activation_std": 19.30477523803711}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.324493, 0.787038, 0.196225, 0.150508, -0.328995], [-0.121918, -0.147412, -0.546076, -0.153244, -0.091768], [0.465369, 0.233779, -0.027863, 0.45097, -0.637511], [0.68849, 0.363208, 0.382206, 0.086179, -0.331074], [0.87893, 0.27132, 0.100329, -0.467818, 0.031015], [-0.685339, -0.587314, 0.224855, -0.119836, 0.45944], [0.262119, 0.910709, 0.462887, -0.394297, -0.053899]], "network.0.bias": [0.191609, 0.091704, -0.252599, 0.511542, -0.006488, -0.169596, 0.218541], "network.2.weight": [[-0.290509, -0.025704, -0.226453, 0.178922, 0.286453, 0.288758, -0.105485], [0.569331, -0.007863, -0.030981, -0.097227, 0.142922, 0.186055, 0.479164], [-0.111953, 0.212962, 0.193608, -0.339106, -0.056492, -0.121674, -0.1552], [0.741942, 0.223563, 0.686036, 0.409689, 0.386287, -0.364657, 0.846631], [0.720368, 0.146354, 0.311951, 0.658836, 0.284685, -0.349026, 0.245147], [-0.065313, 0.046065, -0.12019, -0.166153, -0.056925, -0.058714, 0.027123], [-0.013259, -0.005774, 0.15302, 0.606879, 0.433971, -0.438728, 0.012865]], "network.2.bias": [-0.034232, -0.17459, 0.637607, -0.0597, -0.111301, -0.405797, 0.082042], "network.4.weight": [[-0.01006, 0.002436, -0.15847, -0.23549, -0.022066, -0.057872, 0.287982], [-0.109338, 0.299811, -0.584367, 0.743792, 0.804741, 0.001579, 0.757292], [-0.05201, 0.181785, -0.462667, -0.315226, -0.14004, 0.285638, -0.067654], [0.404587, -0.393803, 0.304357, -0.287171, -0.120792, -0.300998, -0.301434], [0.083119, 0.085726, -0.246416, -0.278468, -0.006852, -0.138296, 0.19869], [0.061945, 0.58597, -0.127542, 0.80365, 0.614737, 0.187395, 0.49695], [0.179214, 0.080144, -0.192595, 0.004129, 0.341253, -0.236906, 0.723081]], "network.4.bias": [-0.288078, 0.190863, 0.165126, 0.658404, -0.228288, -0.09344, -0.311651], "network.6.weight": [[-0.28311, -0.308842, 0.065241, -0.237455, 0.233273, -0.087141, -0.141126], [-0.09862, 0.66039, 0.17138, -0.699073, -0.257681, 0.585202, 0.053094], [0.264945, -0.295561, 0.215315, 0.247603, 0.252366, -0.000802, -0.242294], [-0.341388, -0.305927, -0.063808, -0.133405, 0.26349, 0.107999, 0.193302], [-0.160036, 0.601058, -0.271582, -0.641244, -0.256285, 0.557671, 0.345247], [0.129348, -0.072679, -0.175462, 0.029714, 0.170854, -0.426397, -0.044792], [0.267925, -0.014228, -0.065719, 0.555777, -0.126984, 0.034477, 0.11563]], "network.6.bias": [-0.277503, 0.221601, -0.224187, 0.070972, -0.017318, -0.145991, 0.291195], "network.8.weight": [[0.157753, 0.019106, -0.172591, -0.343512, -0.354167, -0.302738, -0.366114], [0.064436, 0.465447, -0.172439, 0.479267, 0.469983, -0.233308, -0.464288], [-0.056656, 0.230817, 0.122483, -0.169559, 0.649861, 0.148605, -0.110695], [0.1277, -0.149622, -0.101589, 0.35908, 0.067988, 0.292648, -0.119805], [-0.123474, 0.630754, -0.102917, -0.089882, 0.792604, 0.098166, -0.516159], [0.230749, 0.569079, 0.247602, -0.356943, 0.15407, -0.158529, 0.17957], [-0.177572, -0.35532, -0.482513, 0.132688, 0.06069, 0.269814, 0.180762]], "network.8.bias": [-0.056123, 0.126939, -0.015536, -0.337924, 0.032275, -0.321359, 0.652273], "network.10.weight": [[0.084112, -0.27777, 0.065291, 0.119223, -0.722387, -0.61918, 0.423852]], "network.10.bias": [0.216044]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6671582460403442, "train_acc": 0.585, "val_loss": 0.6770175099372864, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6036832928657532, "train_acc": 0.585, "val_loss": 0.5460212826728821, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.48991526663303375, "train_acc": 0.51, "val_loss": 0.4092099070549011, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4023192971944809, "train_acc": 0.895, "val_loss": 0.33834242820739746, "val_acc": 0.96}, {"stage": "improved", "epoch": 2, "global_epoch": 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0.94, "val_loss": 0.08597622811794281, "val_acc": 0.98}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.20705725252628326, "train_acc": 0.94, "val_loss": 0.15071934461593628, "val_acc": 0.96}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.6770175099372864, "final_val_loss": 0.5460212826728821, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.4092099070549011, "final_val_loss": 0.15071934461593628, "initial_val_acc": 0.94, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 4}, "improvement": 0.52, "first_improvement_epoch": 1}} |
35 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.52, "improved_accuracy": 0.68, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2412, "learning_rate": 0.09693395560140622, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.6.weight": [
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}
## Activation Signature
### 0
mean: [0.834752, 2.632929, 2.798969, -0.083313, 1.407007, 3.334608, 2.304839, -0.142513]
std: [0.746732, 3.682951, 3.999429, 0.060185, 1.837064, 4.340228, 3.294290, 0.015454]
fourier: [[12.847499, 13.445298, 13.960776, 14.247080, 75.127683], [63.483235, 66.540919, 69.991217, 70.369418, 236.963591], [69.493358, 71.714614, 74.251905, 76.005050, 251.907199], [0.990621, 1.109494, 1.127726, 1.433292, 7.498176], [31.727009, 32.881048, 34.267012, 34.950203, 126.630651], [74.537677, 78.707784, 81.259223, 82.899341, 300.114701], [57.376656, 58.769732, 60.162731, 62.338216, 207.435462], [0.229243, 0.234945, 0.272698, 0.277561, 12.826157]]
input_correlations: [[0.392837, 0.072202, -0.289864, -0.114202, -0.778740, 0.000000, 0.000000, 0.000000], [0.930404, 0.254835, 0.494090, -0.140954, -0.066469, 0.000000, 0.000000, 0.000000], [-0.395299, -0.388387, -0.490412, -0.511542, -0.824246, 0.000000, 0.000000, 0.000000], [-0.544629, 0.214483, 0.226234, -0.216087, 0.297572, 0.000000, 0.000000, 0.000000], [0.875114, 0.734226, 0.304821, 0.040399, 0.058355, 0.000000, 0.000000, 0.000000], [0.808581, 0.333993, -0.045876, -0.436806, 0.118122, 0.000000, 0.000000, 0.000000], [0.965843, 0.179547, 0.354163, -0.079167, 0.388533, 0.000000, 0.000000, 0.000000], [0.613596, 0.807729, 0.015773, 0.389118, -0.241253, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.717507, 1.263220, -1.367483, 0.415916, 1.497877, -0.357824, 1.437056, 0.353336]
pre_activation_std: [0.778908, 1.613747, 1.382726, 1.192065, 2.093282, 1.882861, 1.860739, 0.814500]
### 2
mean: [1.257603, 2.705352, -0.489648, 0.357211, -1.588681, 0.432015, -1.654609, 2.290972]
std: [1.395424, 3.563951, 1.111376, 0.454946, 1.645581, 1.175711, 1.635463, 2.557592]
fourier: [[23.066520, 23.521065, 24.059888, 26.637605, 113.184249], [60.262389, 65.584754, 67.951771, 68.716987, 243.481718], [19.201509, 19.347849, 19.592311, 22.038320, 44.068328], [7.145050, 7.154320, 7.921095, 8.086512, 32.148960], [28.535554, 28.718546, 31.666520, 31.730038, 142.981305], [19.914701, 20.558264, 22.289749, 22.771862, 38.881318], [29.039786, 29.735771, 31.209174, 31.474912, 148.914837], [42.951319, 46.212821, 47.343983, 48.546899, 206.187425]]
input_correlations: [[0.544615, 0.908777, -0.152590, -0.259739, 0.975807, 0.856214, 0.875888, 0.822445], [0.616830, 0.957659, -0.155466, -0.357538, 0.931254, 0.922851, 0.941402, 0.737341], [-0.586793, -0.898333, 0.122082, 0.413161, -0.950283, -0.925363, -0.859676, -0.814770], [-0.072914, -0.211907, -0.189944, 0.691850, 0.246841, -0.157683, -0.294524, 0.440704], [-0.589013, -0.936182, 0.129406, 0.326427, -0.921315, -0.938625, -0.954116, -0.695182], [0.617831, 0.947115, -0.165321, -0.400524, 0.942902, 0.916746, 0.892423, 0.791391], [-0.523492, -0.934244, 0.170000, 0.265331, -0.923707, -0.827018, -0.928089, -0.723684], [0.601805, 0.945518, -0.151387, -0.329563, 0.951028, 0.895474, 0.923027, 0.775695]]
pre_activation_mean: [1.257603, 2.705352, -0.489648, 0.357211, -1.588681, 0.432015, -1.654609, 2.290972]
pre_activation_std: [1.395424, 3.563951, 1.111376, 0.454946, 1.645581, 1.175711, 1.635463, 2.557592]
### 4
mean: [-2.214785, -0.972572, 3.453895, -0.229163, -0.669864, 3.144340, -1.102725, -1.076161]
std: [2.403977, 1.113926, 4.460885, 0.301719, 0.566238, 3.783536, 1.168438, 0.265988]
fourier: [[40.919744, 42.639518, 43.409103, 44.651984, 199.330647], [18.761735, 18.789103, 18.905277, 19.014627, 87.531456], [75.956345, 80.290501, 81.501559, 84.568133, 310.850584], [5.315165, 5.646362, 6.051619, 6.271541, 20.624712], [9.756165, 9.766714, 9.976002, 10.429640, 60.287780], [64.271439, 69.287611, 72.657001, 72.881448, 282.990558], [19.995098, 20.684981, 21.081475, 21.164901, 99.245282], [4.527763, 4.747783, 4.802781, 4.941533, 96.854491]]
input_correlations: [[-0.994716, -0.991730, 0.351450, -0.078067, -0.915575, -0.981541, -0.876891, -0.998287], [-0.991012, -0.963217, 0.303122, -0.217894, -0.876916, -0.962128, -0.841392, -0.978497], [0.991116, 0.996587, -0.368977, 0.030477, 0.919999, 0.987979, 0.877203, 0.999603], [-0.927343, -0.978138, 0.386574, 0.232114, -0.924641, -0.967320, -0.859707, -0.961543], [-0.970459, -0.983964, 0.237105, -0.011652, -0.892991, -0.995707, -0.818586, -0.980302], [0.978703, 0.999638, -0.362431, -0.047289, 0.925617, 0.990694, 0.874690, 0.996285], [-0.988607, -0.994982, 0.330206, -0.045750, -0.914556, -0.991848, -0.864417, -0.996845], [-0.543896, -0.385500, 0.025527, -0.877212, -0.332907, -0.386331, -0.379916, -0.451486]]
pre_activation_mean: [-2.214785, -0.972572, 3.453895, -0.229163, -0.669864, 3.144340, -1.102725, -1.076161]
pre_activation_std: [2.403977, 1.113926, 4.460885, 0.301719, 0.566238, 3.783536, 1.168438, 0.265988]
### 6
mean: [0.965743, 2.701692, 2.851160, -2.054333, 1.501920, 3.416799, 2.355992, -0.575956]
std: [0.698046, 3.644494, 3.971065, 2.619804, 1.789573, 4.288287, 3.268171, 0.294322]
fourier: [[11.952801, 12.672620, 13.022875, 13.370329, 86.916873], [62.508412, 66.190752, 69.069447, 69.853905, 243.152311], [68.433231, 71.606019, 73.667742, 75.736997, 256.604377], [44.937224, 47.520387, 49.356335, 50.185610, 184.889932], [30.804882, 32.196695, 33.316617, 34.101443, 135.172824], [73.454769, 77.716437, 80.130175, 81.916184, 307.511934], [56.339042, 58.653075, 59.752823, 62.048264, 212.039238], [4.965221, 5.656602, 5.678718, 6.470518, 51.836057]]
input_correlations: [[0.844555, 0.531485, 0.999582, -0.865724, 0.660130, 0.998469, 0.845180, 0.404775], [0.830806, 0.541056, 0.998284, -0.871848, 0.677456, 0.999757, 0.850070, 0.376413], [0.840960, 0.534750, 0.999644, -0.862554, 0.667245, 0.998535, 0.845230, 0.405618], [-0.834071, -0.537681, -0.998841, 0.868945, -0.673977, -0.999510, -0.848054, -0.385400], [0.835699, 0.536155, 0.999431, -0.861552, 0.672887, 0.998857, 0.847256, 0.400275], [0.839049, 0.530385, 0.999482, -0.864654, 0.666978, 0.998942, 0.842966, 0.399538], [0.845929, 0.527068, 0.999970, -0.854922, 0.660857, 0.997174, 0.839257, 0.424836], [-0.713841, -0.542644, -0.937330, 0.913389, -0.708963, -0.961454, -0.837339, -0.101434]]
pre_activation_mean: [0.965743, 2.701692, 2.851160, -2.054333, 1.501920, 3.416799, 2.355992, -0.575956]
pre_activation_std: [0.698046, 3.644494, 3.971065, 2.619804, 1.789573, 4.288287, 3.268171, 0.294322]
### 8
mean: [-4.550669]
std: [6.680466]
fourier: [[115.398652, 120.410527, 124.981072, 127.337940, 409.560243]]
input_correlations: [[-0.999740, -0.999712, -0.999930, -0.754333, -0.999834, -0.999929, -0.999504, 0.102040]]
pre_activation_mean: [-4.550669]
pre_activation_std: [6.680466]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.262733,
-0.050017,
-0.119585,
0.032857,
-0.35976
],
[
0.737991,
-0.096654,
0.239746,
-0.015032,
-0.256588
],
[
-0.104511,
-0.122513,
-0.181099,
-0.237653,
-0.516069
],
[
-0.568891,
0.42276,
0.176201,
-0.316477,
0.319768
],
[
0.732799,
0.606629,
-0.028479,
-0.094298,
-0.056508
],
[
0.712437,
0.345978,
-0.376784,
-0.476695,
0.14526
],
[
0.882543,
-0.142548,
0.035111,
-0.016497,
0.211272
],
[
0.227407,
0.25422,
-0.092858,
0.108851,
-0.149055
]
],
"network.0.bias": [
-0.330277,
0.36885,
0.510235,
0.269731,
-0.188062,
-0.244708,
0.299999,
-0.248526
],
"network.2.weight": [
[
-0.315195,
0.232464,
0.030921,
-0.087923,
0.552081,
-0.277615,
0.145133,
0.004494
],
[
-0.719501,
0.588152,
-0.648485,
-0.319223,
0.637048,
0.25881,
0.605119,
0.188991
],
[
0.357145,
-0.025016,
0.140327,
0.32965,
-0.422805,
-0.278247,
0.031237,
0.13045
],
[
0.197396,
-0.025125,
0.059955,
0.308153,
0.147484,
-0.216398,
-0.094866,
0.349864
],
[
0.861372,
-0.043006,
0.269353,
0.104694,
-0.322721,
-0.390935,
-0.374303,
0.115149
],
[
-0.06562,
0.243881,
-0.27835,
-0.247695,
0.337872,
0.079818,
0.008043,
-0.040018
],
[
0.574866,
-0.395765,
0.230098,
-0.018073,
-0.41937,
0.556872,
-0.454174,
-0.103837
],
[
-0.14552,
0.447765,
-0.192511,
-0.227581,
0.68703,
-0.237284,
0.397683,
0.100081
]
],
"network.2.bias": [
0.114117,
0.093007,
0.051591,
0.097128,
-0.381778,
-0.282479,
-0.094927,
0.352325
],
"network.4.weight": [
[
-0.210631,
-0.271658,
-0.369163,
-0.379517,
-0.428454,
0.209948,
0.012818,
-0.513737
],
[
-0.161357,
-0.075763,
-0.378569,
-0.581829,
-0.244398,
-0.201866,
0.188566,
-0.147598
],
[
0.426057,
0.571835,
-0.197578,
0.263329,
-0.282731,
0.237764,
-0.113269,
0.593927
],
[
-0.224584,
-0.132967,
0.105062,
0.208523,
-0.014109,
0.001158,
-0.061867,
0.196794
],
[
-0.152456,
-0.086667,
-0.252373,
-0.046088,
-0.141858,
-0.405187,
0.509347,
0.141709
],
[
0.177002,
0.641157,
-0.197418,
-0.355563,
-0.199898,
0.260679,
-0.252322,
0.365161
],
[
0.154103,
-0.133152,
-0.10424,
-0.274221,
-0.341432,
-0.343493,
0.098447,
-0.201727
],
[
-0.053882,
0.094265,
-0.409556,
-0.509691,
-0.636223,
0.127967,
-0.044246,
-0.190441
]
],
"network.4.bias": [
-0.158945,
0.020773,
-0.086952,
-0.122986,
-0.302686,
0.376137,
-0.255938,
-0.823237
],
"network.6.weight": [
[
0.023278,
0.015179,
0.136238,
-0.150648,
-0.245856,
0.018722,
0.250753,
-0.330471
],
[
0.138989,
0.49152,
0.203215,
0.062793,
0.470282,
0.700458,
0.200865,
0.311629
],
[
0.443977,
0.838494,
0.593198,
0.126367,
-0.023316,
0.326838,
0.054255,
0.045052
],
[
-0.149258,
-0.260324,
-0.254049,
-0.111044,
-0.2471,
-0.379474,
-0.183006,
0.347997
],
[
0.053438,
0.196151,
0.223326,
0.421651,
0.167697,
0.203553,
0.284488,
0.039144
],
[
0.255445,
0.41673,
0.537614,
0.058146,
-0.047706,
0.484628,
-0.335152,
0.157621
],
[
0.491534,
0.61035,
0.653179,
0.16147,
0.231964,
0.077571,
-0.401892,
0.330809
],
[
0.023216,
0.145383,
0.225797,
-0.345559,
0.079522,
-0.346387,
0.043588,
0.364171
]
],
"network.6.bias": [
0.390151,
0.058411,
-0.021937,
-0.078313,
0.229964,
0.163106,
0.053612,
-0.22056
],
"network.8.weight": [
[
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-0.464568,
-0.448991,
0.011036,
-0.239553,
-0.562847,
-0.146074,
-0.262742
]
],
"network.8.bias": [
0.232662
]
}
## Activation Signature
### 0
mean: [0.834752, 2.632929, 2.798969, -0.083313, 1.407007, 3.334608, 2.304839, -0.142513]
std: [0.746732, 3.682951, 3.999429, 0.060185, 1.837064, 4.340228, 3.294290, 0.015454]
fourier: [[12.847499, 13.445298, 13.960776, 14.247080, 75.127683], [63.483235, 66.540919, 69.991217, 70.369418, 236.963591], [69.493358, 71.714614, 74.251905, 76.005050, 251.907199], [0.990621, 1.109494, 1.127726, 1.433292, 7.498176], [31.727009, 32.881048, 34.267012, 34.950203, 126.630651], [74.537677, 78.707784, 81.259223, 82.899341, 300.114701], [57.376656, 58.769732, 60.162731, 62.338216, 207.435462], [0.229243, 0.234945, 0.272698, 0.277561, 12.826157]]
input_correlations: [[0.392837, 0.072202, -0.289864, -0.114202, -0.778740, 0.000000, 0.000000, 0.000000], [0.930404, 0.254835, 0.494090, -0.140954, -0.066469, 0.000000, 0.000000, 0.000000], [-0.395299, -0.388387, -0.490412, -0.511542, -0.824246, 0.000000, 0.000000, 0.000000], [-0.544629, 0.214483, 0.226234, -0.216087, 0.297572, 0.000000, 0.000000, 0.000000], [0.875114, 0.734226, 0.304821, 0.040399, 0.058355, 0.000000, 0.000000, 0.000000], [0.808581, 0.333993, -0.045876, -0.436806, 0.118122, 0.000000, 0.000000, 0.000000], [0.965843, 0.179547, 0.354163, -0.079167, 0.388533, 0.000000, 0.000000, 0.000000], [0.613596, 0.807729, 0.015773, 0.389118, -0.241253, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.717507, 1.263220, -1.367483, 0.415916, 1.497877, -0.357824, 1.437056, 0.353336]
pre_activation_std: [0.778908, 1.613747, 1.382726, 1.192065, 2.093282, 1.882861, 1.860739, 0.814500]
### 2
mean: [1.257603, 2.705352, -0.489648, 0.357211, -1.588681, 0.432015, -1.654609, 2.290972]
std: [1.395424, 3.563951, 1.111376, 0.454946, 1.645581, 1.175711, 1.635463, 2.557592]
fourier: [[23.066520, 23.521065, 24.059888, 26.637605, 113.184249], [60.262389, 65.584754, 67.951771, 68.716987, 243.481718], [19.201509, 19.347849, 19.592311, 22.038320, 44.068328], [7.145050, 7.154320, 7.921095, 8.086512, 32.148960], [28.535554, 28.718546, 31.666520, 31.730038, 142.981305], [19.914701, 20.558264, 22.289749, 22.771862, 38.881318], [29.039786, 29.735771, 31.209174, 31.474912, 148.914837], [42.951319, 46.212821, 47.343983, 48.546899, 206.187425]]
input_correlations: [[0.544615, 0.908777, -0.152590, -0.259739, 0.975807, 0.856214, 0.875888, 0.822445], [0.616830, 0.957659, -0.155466, -0.357538, 0.931254, 0.922851, 0.941402, 0.737341], [-0.586793, -0.898333, 0.122082, 0.413161, -0.950283, -0.925363, -0.859676, -0.814770], [-0.072914, -0.211907, -0.189944, 0.691850, 0.246841, -0.157683, -0.294524, 0.440704], [-0.589013, -0.936182, 0.129406, 0.326427, -0.921315, -0.938625, -0.954116, -0.695182], [0.617831, 0.947115, -0.165321, -0.400524, 0.942902, 0.916746, 0.892423, 0.791391], [-0.523492, -0.934244, 0.170000, 0.265331, -0.923707, -0.827018, -0.928089, -0.723684], [0.601805, 0.945518, -0.151387, -0.329563, 0.951028, 0.895474, 0.923027, 0.775695]]
pre_activation_mean: [1.257603, 2.705352, -0.489648, 0.357211, -1.588681, 0.432015, -1.654609, 2.290972]
pre_activation_std: [1.395424, 3.563951, 1.111376, 0.454946, 1.645581, 1.175711, 1.635463, 2.557592]
### 4
mean: [-2.214785, -0.972572, 3.453895, -0.229163, -0.669864, 3.144340, -1.102725, -1.076161]
std: [2.403977, 1.113926, 4.460885, 0.301719, 0.566238, 3.783536, 1.168438, 0.265988]
fourier: [[40.919744, 42.639518, 43.409103, 44.651984, 199.330647], [18.761735, 18.789103, 18.905277, 19.014627, 87.531456], [75.956345, 80.290501, 81.501559, 84.568133, 310.850584], [5.315165, 5.646362, 6.051619, 6.271541, 20.624712], [9.756165, 9.766714, 9.976002, 10.429640, 60.287780], [64.271439, 69.287611, 72.657001, 72.881448, 282.990558], [19.995098, 20.684981, 21.081475, 21.164901, 99.245282], [4.527763, 4.747783, 4.802781, 4.941533, 96.854491]]
input_correlations: [[-0.994716, -0.991730, 0.351450, -0.078067, -0.915575, -0.981541, -0.876891, -0.998287], [-0.991012, -0.963217, 0.303122, -0.217894, -0.876916, -0.962128, -0.841392, -0.978497], [0.991116, 0.996587, -0.368977, 0.030477, 0.919999, 0.987979, 0.877203, 0.999603], [-0.927343, -0.978138, 0.386574, 0.232114, -0.924641, -0.967320, -0.859707, -0.961543], [-0.970459, -0.983964, 0.237105, -0.011652, -0.892991, -0.995707, -0.818586, -0.980302], [0.978703, 0.999638, -0.362431, -0.047289, 0.925617, 0.990694, 0.874690, 0.996285], [-0.988607, -0.994982, 0.330206, -0.045750, -0.914556, -0.991848, -0.864417, -0.996845], [-0.543896, -0.385500, 0.025527, -0.877212, -0.332907, -0.386331, -0.379916, -0.451486]]
pre_activation_mean: [-2.214785, -0.972572, 3.453895, -0.229163, -0.669864, 3.144340, -1.102725, -1.076161]
pre_activation_std: [2.403977, 1.113926, 4.460885, 0.301719, 0.566238, 3.783536, 1.168438, 0.265988]
### 6
mean: [0.965743, 2.701692, 2.851160, -2.054333, 1.501920, 3.416799, 2.355992, -0.575956]
std: [0.698046, 3.644494, 3.971065, 2.619804, 1.789573, 4.288287, 3.268171, 0.294322]
fourier: [[11.952801, 12.672620, 13.022875, 13.370329, 86.916873], [62.508412, 66.190752, 69.069447, 69.853905, 243.152311], [68.433231, 71.606019, 73.667742, 75.736997, 256.604377], [44.937224, 47.520387, 49.356335, 50.185610, 184.889932], [30.804882, 32.196695, 33.316617, 34.101443, 135.172824], [73.454769, 77.716437, 80.130175, 81.916184, 307.511934], [56.339042, 58.653075, 59.752823, 62.048264, 212.039238], [4.965221, 5.656602, 5.678718, 6.470518, 51.836057]]
input_correlations: [[0.844555, 0.531485, 0.999582, -0.865724, 0.660130, 0.998469, 0.845180, 0.404775], [0.830806, 0.541056, 0.998284, -0.871848, 0.677456, 0.999757, 0.850070, 0.376413], [0.840960, 0.534750, 0.999644, -0.862554, 0.667245, 0.998535, 0.845230, 0.405618], [-0.834071, -0.537681, -0.998841, 0.868945, -0.673977, -0.999510, -0.848054, -0.385400], [0.835699, 0.536155, 0.999431, -0.861552, 0.672887, 0.998857, 0.847256, 0.400275], [0.839049, 0.530385, 0.999482, -0.864654, 0.666978, 0.998942, 0.842966, 0.399538], [0.845929, 0.527068, 0.999970, -0.854922, 0.660857, 0.997174, 0.839257, 0.424836], [-0.713841, -0.542644, -0.937330, 0.913389, -0.708963, -0.961454, -0.837339, -0.101434]]
pre_activation_mean: [0.965743, 2.701692, 2.851160, -2.054333, 1.501920, 3.416799, 2.355992, -0.575956]
pre_activation_std: [0.698046, 3.644494, 3.971065, 2.619804, 1.789573, 4.288287, 3.268171, 0.294322]
### 8
mean: [-4.550669]
std: [6.680466]
fourier: [[115.398652, 120.410527, 124.981072, 127.337940, 409.560243]]
input_correlations: [[-0.999740, -0.999712, -0.999930, -0.754333, -0.999834, -0.999929, -0.999504, 0.102040]]
pre_activation_mean: [-4.550669]
pre_activation_std: [6.680466]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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-0.146074, -0.262742]], "network.8.bias": [0.232662]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7066080868244171, "train_acc": 0.44, "val_loss": 0.6552404761314392, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6103737652301788, "train_acc": 0.575, "val_loss": 0.5133622884750366, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 3.820657253265381, "train_acc": 0.495, "val_loss": 0.5808274149894714, "val_acc": 0.68}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5905366241931915, "train_acc": 0.67, "val_loss": 0.642299473285675, "val_acc": 0.6}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6567595899105072, "train_acc": 0.605, "val_loss": 0.6841071248054504, "val_acc": 0.58}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.6692509949207306, "train_acc": 0.58, "val_loss": 0.6768818497657776, "val_acc": 0.56}], "summary": {"total_epochs": 6, "degraded_epochs": 2, "improved_epochs": 4, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.6552404761314392, "final_val_loss": 0.5133622884750366, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.5808274149894714, "final_val_loss": 0.6768818497657776, "initial_val_acc": 0.68, "final_val_acc": 0.56, "best_val_acc": 0.68, "best_epoch": 2}, "improvement": 0.16000000000000003, "first_improvement_epoch": 1}} |
36 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.52, "improved_accuracy": 0.94, "improvement": 0.41999999999999993, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2079, "learning_rate": 0.05135048742655233, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [2.902497, 3.573550, 0.236118, 0.000000, 0.000000, 0.000000, 2.728127, 2.049578]
std: [3.567726, 4.330510, 0.240334, 0.000000, 0.000000, 0.000000, 3.314205, 2.484865]
fourier: [[55.014090, 57.590392, 60.350994, 66.973789, 261.224701], [66.477416, 70.274625, 73.863988, 80.759853, 321.619494], [3.430751, 4.046550, 4.859058, 5.158042, 21.250652], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [50.949519, 53.595245, 56.332736, 62.019554, 245.531385], [38.156440, 40.290700, 42.340477, 46.382636, 184.462061]]
input_correlations: [[-0.666951, -0.135095, 0.274139, 0.281973, 0.467485, 0.000000, 0.000000, 0.000000], [-0.167333, -0.115356, 0.510519, 0.240786, 0.816725, 0.000000, 0.000000, 0.000000], [-0.549359, 0.094232, 0.383523, 0.635183, 0.068737, 0.000000, 0.000000, 0.000000], [-0.010849, -0.399067, -0.246640, -0.300020, 0.778146, 0.000000, 0.000000, 0.000000], [-0.766383, -0.329894, -0.698179, 0.019847, -0.618323, 0.000000, 0.000000, 0.000000], [-0.302391, -0.249739, -0.670705, -0.698344, -0.423123, 0.000000, 0.000000, 0.000000], [-0.780472, 0.015834, -0.315889, 0.443950, 0.297121, 0.000000, 0.000000, 0.000000], [-0.294340, -0.208814, -0.757207, 0.493110, 0.274742, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.417001, 0.781848, 1.348207, -0.698775, -2.144586, -2.283536, 0.106928, -0.855324]
pre_activation_std: [1.579580, 1.405712, 1.768024, 1.658508, 1.397410, 1.291080, 1.727881, 1.732765]
### 2
mean: [2.801279, -0.582551, -1.029053, -0.174631, -0.009728, 1.045167, -0.985324, -0.957045]
std: [2.715566, 0.648032, 0.894458, 0.924696, 0.480742, 1.589150, 0.599665, 0.883787]
fourier: [[38.819700, 42.781508, 48.740878, 52.425468, 252.115126], [9.753344, 10.356350, 10.418592, 11.340041, 52.429548], [14.496005, 15.228307, 15.367640, 15.800580, 92.614784], [14.456398, 14.768657, 15.507069, 15.716772, 16.316881], [6.920984, 7.253306, 7.459098, 7.711484, 9.010593], [24.209201, 24.594137, 27.331325, 30.353233, 94.065006], [9.685940, 10.054286, 10.963249, 11.413774, 88.679117], [14.124297, 15.135419, 16.403122, 16.453689, 86.134063]]
input_correlations: [[0.910945, 0.754940, 0.704774, 0.548913, 0.000000, 0.000000, 0.870998, 0.668738], [-0.763188, -0.556342, -0.781298, -0.443487, 0.000000, 0.000000, -0.840182, -0.598270], [-0.896486, -0.829819, -0.542334, -0.685614, 0.000000, 0.000000, -0.874858, -0.625957], [-0.210841, -0.441898, 0.318716, -0.897503, 0.000000, 0.000000, -0.559000, -0.648881], [0.211001, 0.521835, -0.367281, 0.914051, 0.000000, 0.000000, 0.274759, 0.466462], [0.855634, 0.758202, 0.508862, 0.722733, 0.000000, 0.000000, 0.908555, 0.705433], [-0.884181, -0.828197, -0.864758, -0.348051, 0.000000, 0.000000, -0.512969, -0.369274], [-0.942231, -0.919213, -0.736443, -0.534546, 0.000000, 0.000000, -0.608664, -0.413630]]
pre_activation_mean: [2.801279, -0.582551, -1.029053, -0.174631, -0.009728, 1.045167, -0.985324, -0.957045]
pre_activation_std: [2.715566, 0.648032, 0.894458, 0.924696, 0.480742, 1.589150, 0.599665, 0.883787]
### 4
mean: [1.421477, -1.208656, -1.768447, -1.436090, -0.679419, -0.005183, 2.760527, -1.839943]
std: [2.114308, 1.137733, 1.861432, 1.383802, 0.350339, 0.731694, 3.084329, 1.562967]
fourier: [[31.764610, 33.608192, 37.099198, 41.184831, 127.932922], [17.984246, 18.204987, 19.813851, 20.937832, 108.779081], [27.142352, 28.502012, 33.102065, 35.694268, 159.160241], [20.533090, 21.693228, 24.346973, 26.623852, 129.248089], [5.075224, 5.666172, 5.729910, 6.436285, 61.147754], [10.685049, 10.857916, 11.383526, 12.174550, 12.202939], [45.357601, 48.382018, 54.007987, 58.312641, 248.447405], [23.087697, 24.708573, 27.640340, 30.198909, 165.594915]]
input_correlations: [[0.995217, -0.514816, 0.000000, 0.151406, 0.498943, 0.977957, 0.000000, 0.000000], [-0.981417, 0.584055, 0.000000, -0.405838, -0.357492, -0.891304, 0.000000, 0.000000], [-0.986448, 0.516900, 0.000000, -0.103324, -0.580319, -0.987603, 0.000000, 0.000000], [-0.992925, 0.517638, 0.000000, -0.143678, -0.541987, -0.983157, 0.000000, 0.000000], [-0.841485, 0.595191, 0.000000, -0.608027, 0.014459, -0.649509, 0.000000, 0.000000], [-0.925784, 0.501751, 0.000000, -0.220401, -0.719356, -0.950722, 0.000000, 0.000000], [0.993467, -0.535802, 0.000000, 0.194968, 0.549891, 0.976317, 0.000000, 0.000000], [-0.997377, 0.534004, 0.000000, -0.179252, -0.505426, -0.974000, 0.000000, 0.000000]]
pre_activation_mean: [1.421477, -1.208656, -1.768447, -1.436090, -0.679419, -0.005183, 2.760527, -1.839943]
pre_activation_std: [2.114308, 1.137733, 1.861432, 1.383802, 0.350339, 0.731694, 3.084329, 1.562967]
### 6
mean: [-0.518812, 3.019525, -1.040185, -1.106426, -0.074708, -0.567260, -1.885519, -0.236181]
std: [0.107567, 3.426549, 0.634769, 1.136020, 0.884321, 0.567910, 1.797366, 0.647897]
fourier: [[1.526024, 1.659830, 1.902368, 1.961274, 46.693050], [51.602638, 54.458656, 59.610919, 64.742375, 271.757185], [9.419214, 9.809743, 10.748438, 12.134467, 93.616668], [16.613932, 17.878966, 20.071003, 21.038590, 99.578350], [12.853875, 12.878279, 14.329900, 15.734385, 16.299247], [8.110284, 8.836433, 10.100651, 10.348748, 51.053414], [27.328693, 28.459429, 30.781235, 34.370902, 169.696734], [9.751142, 10.508380, 11.594436, 11.961947, 21.256247]]
input_correlations: [[-0.973743, 0.000000, 0.000000, 0.000000, 0.000000, 0.785777, -0.995524, 0.000000], [0.994854, 0.000000, 0.000000, 0.000000, 0.000000, -0.743649, 0.999263, 0.000000], [-0.989545, 0.000000, 0.000000, 0.000000, 0.000000, 0.724791, -0.998680, 0.000000], [-0.986138, 0.000000, 0.000000, 0.000000, 0.000000, 0.771570, -0.999413, 0.000000], [-0.980689, 0.000000, 0.000000, 0.000000, 0.000000, 0.814122, -0.993026, 0.000000], [-0.976654, 0.000000, 0.000000, 0.000000, 0.000000, 0.788519, -0.996662, 0.000000], [-0.996825, 0.000000, 0.000000, 0.000000, 0.000000, 0.724698, -0.998458, 0.000000], [-0.992496, 0.000000, 0.000000, 0.000000, 0.000000, 0.770010, -0.995307, 0.000000]]
pre_activation_mean: [-0.518812, 3.019525, -1.040185, -1.106426, -0.074708, -0.567260, -1.885519, -0.236181]
pre_activation_std: [0.107567, 3.426549, 0.634769, 1.136020, 0.884321, 0.567910, 1.797366, 0.647897]
### 8
mean: [1.699234, -0.881077, -0.865826, -0.656334, -1.125566, -1.263842, 1.805053, 1.688434]
std: [2.178641, 0.671293, 0.672371, 0.387913, 0.990508, 1.167997, 2.372006, 2.243283]
fourier: [[31.935952, 35.241483, 39.358055, 39.713017, 152.931114], [10.364262, 10.482751, 10.950339, 13.159732, 79.296914], [10.361285, 10.545064, 11.194976, 12.998709, 77.924371], [5.915980, 6.096364, 6.306292, 7.651449, 59.070092], [15.000164, 15.687047, 17.158753, 18.765872, 101.300914], [17.424826, 18.716513, 20.618778, 21.749745, 113.745821], [35.321977, 38.037196, 42.010512, 44.070635, 162.454748], [33.882088, 35.676566, 38.848327, 42.385437, 151.959057]]
input_correlations: [[0.000000, 0.997838, 0.000000, 0.000000, -0.764272, 0.000000, 0.000000, -0.744240], [0.000000, -0.995977, 0.000000, 0.000000, 0.655273, 0.000000, 0.000000, 0.632705], [0.000000, -0.998370, 0.000000, 0.000000, 0.679864, 0.000000, 0.000000, 0.659057], [0.000000, -0.994405, 0.000000, 0.000000, 0.644873, 0.000000, 0.000000, 0.619895], [0.000000, -0.999944, 0.000000, 0.000000, 0.714771, 0.000000, 0.000000, 0.692766], [0.000000, -0.999658, 0.000000, 0.000000, 0.738131, 0.000000, 0.000000, 0.717474], [0.000000, 0.999528, 0.000000, 0.000000, -0.741219, 0.000000, 0.000000, -0.720472], [0.000000, 0.999992, 0.000000, 0.000000, -0.717794, 0.000000, 0.000000, -0.696858]]
pre_activation_mean: [1.699234, -0.881077, -0.865826, -0.656334, -1.125566, -1.263842, 1.805053, 1.688434]
pre_activation_std: [2.178641, 0.671293, 0.672371, 0.387913, 0.990508, 1.167997, 2.372006, 2.243283]
### 10
mean: [2.844230, 3.523960, 0.001441, -0.853583, -0.835525, -0.762370, 2.713038, 2.025407]
std: [3.615669, 4.371779, 0.626336, 0.899327, 0.989995, 0.734032, 3.326670, 2.504947]
fourier: [[55.393626, 58.609606, 61.838182, 67.371539, 255.980673], [66.778862, 71.088221, 75.146739, 81.109987, 317.156433], [8.381075, 9.601356, 10.146638, 10.702456, 11.679792], [13.585340, 14.782988, 15.731440, 16.417497, 76.822489], [15.192262, 16.016818, 16.870688, 18.499214, 75.197221], [11.033354, 12.119527, 12.932459, 13.303334, 68.613309], [51.055771, 53.821556, 56.717173, 62.147928, 244.173422], [38.307186, 40.681541, 42.964150, 46.559202, 182.286642]]
input_correlations: [[0.999221, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999972, 0.999783], [0.999483, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999999, 0.999603], [-0.999165, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999962, -0.999810], [-0.999984, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999643, -0.998506], [-0.999023, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999923, -0.999871], [-0.999983, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999274, -0.997818], [0.999035, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999930, 0.999866], [0.999382, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999993, 0.999685]]
pre_activation_mean: [2.844230, 3.523960, 0.001441, -0.853583, -0.835525, -0.762370, 2.713038, 2.025407]
pre_activation_std: [3.615669, 4.371779, 0.626336, 0.899327, 0.989995, 0.734032, 3.326670, 2.504947]
### 12
mean: [-3.785794]
std: [5.193107]
fourier: [[79.492709, 84.663202, 89.198134, 96.244206, 340.721504]]
input_correlations: [[-0.999738, -0.999936, 0.758419, 0.000000, 0.000000, 0.000000, -0.999846, -0.999917]]
pre_activation_mean: [-3.785794]
pre_activation_std: [5.193107]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.weight": [
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[
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"network.12.bias": [
0.288608
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}
## Activation Signature
### 0
mean: [2.902497, 3.573550, 0.236118, 0.000000, 0.000000, 0.000000, 2.728127, 2.049578]
std: [3.567726, 4.330510, 0.240334, 0.000000, 0.000000, 0.000000, 3.314205, 2.484865]
fourier: [[55.014090, 57.590392, 60.350994, 66.973789, 261.224701], [66.477416, 70.274625, 73.863988, 80.759853, 321.619494], [3.430751, 4.046550, 4.859058, 5.158042, 21.250652], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [50.949519, 53.595245, 56.332736, 62.019554, 245.531385], [38.156440, 40.290700, 42.340477, 46.382636, 184.462061]]
input_correlations: [[-0.666951, -0.135095, 0.274139, 0.281973, 0.467485, 0.000000, 0.000000, 0.000000], [-0.167333, -0.115356, 0.510519, 0.240786, 0.816725, 0.000000, 0.000000, 0.000000], [-0.549359, 0.094232, 0.383523, 0.635183, 0.068737, 0.000000, 0.000000, 0.000000], [-0.010849, -0.399067, -0.246640, -0.300020, 0.778146, 0.000000, 0.000000, 0.000000], [-0.766383, -0.329894, -0.698179, 0.019847, -0.618323, 0.000000, 0.000000, 0.000000], [-0.302391, -0.249739, -0.670705, -0.698344, -0.423123, 0.000000, 0.000000, 0.000000], [-0.780472, 0.015834, -0.315889, 0.443950, 0.297121, 0.000000, 0.000000, 0.000000], [-0.294340, -0.208814, -0.757207, 0.493110, 0.274742, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.417001, 0.781848, 1.348207, -0.698775, -2.144586, -2.283536, 0.106928, -0.855324]
pre_activation_std: [1.579580, 1.405712, 1.768024, 1.658508, 1.397410, 1.291080, 1.727881, 1.732765]
### 2
mean: [2.801279, -0.582551, -1.029053, -0.174631, -0.009728, 1.045167, -0.985324, -0.957045]
std: [2.715566, 0.648032, 0.894458, 0.924696, 0.480742, 1.589150, 0.599665, 0.883787]
fourier: [[38.819700, 42.781508, 48.740878, 52.425468, 252.115126], [9.753344, 10.356350, 10.418592, 11.340041, 52.429548], [14.496005, 15.228307, 15.367640, 15.800580, 92.614784], [14.456398, 14.768657, 15.507069, 15.716772, 16.316881], [6.920984, 7.253306, 7.459098, 7.711484, 9.010593], [24.209201, 24.594137, 27.331325, 30.353233, 94.065006], [9.685940, 10.054286, 10.963249, 11.413774, 88.679117], [14.124297, 15.135419, 16.403122, 16.453689, 86.134063]]
input_correlations: [[0.910945, 0.754940, 0.704774, 0.548913, 0.000000, 0.000000, 0.870998, 0.668738], [-0.763188, -0.556342, -0.781298, -0.443487, 0.000000, 0.000000, -0.840182, -0.598270], [-0.896486, -0.829819, -0.542334, -0.685614, 0.000000, 0.000000, -0.874858, -0.625957], [-0.210841, -0.441898, 0.318716, -0.897503, 0.000000, 0.000000, -0.559000, -0.648881], [0.211001, 0.521835, -0.367281, 0.914051, 0.000000, 0.000000, 0.274759, 0.466462], [0.855634, 0.758202, 0.508862, 0.722733, 0.000000, 0.000000, 0.908555, 0.705433], [-0.884181, -0.828197, -0.864758, -0.348051, 0.000000, 0.000000, -0.512969, -0.369274], [-0.942231, -0.919213, -0.736443, -0.534546, 0.000000, 0.000000, -0.608664, -0.413630]]
pre_activation_mean: [2.801279, -0.582551, -1.029053, -0.174631, -0.009728, 1.045167, -0.985324, -0.957045]
pre_activation_std: [2.715566, 0.648032, 0.894458, 0.924696, 0.480742, 1.589150, 0.599665, 0.883787]
### 4
mean: [1.421477, -1.208656, -1.768447, -1.436090, -0.679419, -0.005183, 2.760527, -1.839943]
std: [2.114308, 1.137733, 1.861432, 1.383802, 0.350339, 0.731694, 3.084329, 1.562967]
fourier: [[31.764610, 33.608192, 37.099198, 41.184831, 127.932922], [17.984246, 18.204987, 19.813851, 20.937832, 108.779081], [27.142352, 28.502012, 33.102065, 35.694268, 159.160241], [20.533090, 21.693228, 24.346973, 26.623852, 129.248089], [5.075224, 5.666172, 5.729910, 6.436285, 61.147754], [10.685049, 10.857916, 11.383526, 12.174550, 12.202939], [45.357601, 48.382018, 54.007987, 58.312641, 248.447405], [23.087697, 24.708573, 27.640340, 30.198909, 165.594915]]
input_correlations: [[0.995217, -0.514816, 0.000000, 0.151406, 0.498943, 0.977957, 0.000000, 0.000000], [-0.981417, 0.584055, 0.000000, -0.405838, -0.357492, -0.891304, 0.000000, 0.000000], [-0.986448, 0.516900, 0.000000, -0.103324, -0.580319, -0.987603, 0.000000, 0.000000], [-0.992925, 0.517638, 0.000000, -0.143678, -0.541987, -0.983157, 0.000000, 0.000000], [-0.841485, 0.595191, 0.000000, -0.608027, 0.014459, -0.649509, 0.000000, 0.000000], [-0.925784, 0.501751, 0.000000, -0.220401, -0.719356, -0.950722, 0.000000, 0.000000], [0.993467, -0.535802, 0.000000, 0.194968, 0.549891, 0.976317, 0.000000, 0.000000], [-0.997377, 0.534004, 0.000000, -0.179252, -0.505426, -0.974000, 0.000000, 0.000000]]
pre_activation_mean: [1.421477, -1.208656, -1.768447, -1.436090, -0.679419, -0.005183, 2.760527, -1.839943]
pre_activation_std: [2.114308, 1.137733, 1.861432, 1.383802, 0.350339, 0.731694, 3.084329, 1.562967]
### 6
mean: [-0.518812, 3.019525, -1.040185, -1.106426, -0.074708, -0.567260, -1.885519, -0.236181]
std: [0.107567, 3.426549, 0.634769, 1.136020, 0.884321, 0.567910, 1.797366, 0.647897]
fourier: [[1.526024, 1.659830, 1.902368, 1.961274, 46.693050], [51.602638, 54.458656, 59.610919, 64.742375, 271.757185], [9.419214, 9.809743, 10.748438, 12.134467, 93.616668], [16.613932, 17.878966, 20.071003, 21.038590, 99.578350], [12.853875, 12.878279, 14.329900, 15.734385, 16.299247], [8.110284, 8.836433, 10.100651, 10.348748, 51.053414], [27.328693, 28.459429, 30.781235, 34.370902, 169.696734], [9.751142, 10.508380, 11.594436, 11.961947, 21.256247]]
input_correlations: [[-0.973743, 0.000000, 0.000000, 0.000000, 0.000000, 0.785777, -0.995524, 0.000000], [0.994854, 0.000000, 0.000000, 0.000000, 0.000000, -0.743649, 0.999263, 0.000000], [-0.989545, 0.000000, 0.000000, 0.000000, 0.000000, 0.724791, -0.998680, 0.000000], [-0.986138, 0.000000, 0.000000, 0.000000, 0.000000, 0.771570, -0.999413, 0.000000], [-0.980689, 0.000000, 0.000000, 0.000000, 0.000000, 0.814122, -0.993026, 0.000000], [-0.976654, 0.000000, 0.000000, 0.000000, 0.000000, 0.788519, -0.996662, 0.000000], [-0.996825, 0.000000, 0.000000, 0.000000, 0.000000, 0.724698, -0.998458, 0.000000], [-0.992496, 0.000000, 0.000000, 0.000000, 0.000000, 0.770010, -0.995307, 0.000000]]
pre_activation_mean: [-0.518812, 3.019525, -1.040185, -1.106426, -0.074708, -0.567260, -1.885519, -0.236181]
pre_activation_std: [0.107567, 3.426549, 0.634769, 1.136020, 0.884321, 0.567910, 1.797366, 0.647897]
### 8
mean: [1.699234, -0.881077, -0.865826, -0.656334, -1.125566, -1.263842, 1.805053, 1.688434]
std: [2.178641, 0.671293, 0.672371, 0.387913, 0.990508, 1.167997, 2.372006, 2.243283]
fourier: [[31.935952, 35.241483, 39.358055, 39.713017, 152.931114], [10.364262, 10.482751, 10.950339, 13.159732, 79.296914], [10.361285, 10.545064, 11.194976, 12.998709, 77.924371], [5.915980, 6.096364, 6.306292, 7.651449, 59.070092], [15.000164, 15.687047, 17.158753, 18.765872, 101.300914], [17.424826, 18.716513, 20.618778, 21.749745, 113.745821], [35.321977, 38.037196, 42.010512, 44.070635, 162.454748], [33.882088, 35.676566, 38.848327, 42.385437, 151.959057]]
input_correlations: [[0.000000, 0.997838, 0.000000, 0.000000, -0.764272, 0.000000, 0.000000, -0.744240], [0.000000, -0.995977, 0.000000, 0.000000, 0.655273, 0.000000, 0.000000, 0.632705], [0.000000, -0.998370, 0.000000, 0.000000, 0.679864, 0.000000, 0.000000, 0.659057], [0.000000, -0.994405, 0.000000, 0.000000, 0.644873, 0.000000, 0.000000, 0.619895], [0.000000, -0.999944, 0.000000, 0.000000, 0.714771, 0.000000, 0.000000, 0.692766], [0.000000, -0.999658, 0.000000, 0.000000, 0.738131, 0.000000, 0.000000, 0.717474], [0.000000, 0.999528, 0.000000, 0.000000, -0.741219, 0.000000, 0.000000, -0.720472], [0.000000, 0.999992, 0.000000, 0.000000, -0.717794, 0.000000, 0.000000, -0.696858]]
pre_activation_mean: [1.699234, -0.881077, -0.865826, -0.656334, -1.125566, -1.263842, 1.805053, 1.688434]
pre_activation_std: [2.178641, 0.671293, 0.672371, 0.387913, 0.990508, 1.167997, 2.372006, 2.243283]
### 10
mean: [2.844230, 3.523960, 0.001441, -0.853583, -0.835525, -0.762370, 2.713038, 2.025407]
std: [3.615669, 4.371779, 0.626336, 0.899327, 0.989995, 0.734032, 3.326670, 2.504947]
fourier: [[55.393626, 58.609606, 61.838182, 67.371539, 255.980673], [66.778862, 71.088221, 75.146739, 81.109987, 317.156433], [8.381075, 9.601356, 10.146638, 10.702456, 11.679792], [13.585340, 14.782988, 15.731440, 16.417497, 76.822489], [15.192262, 16.016818, 16.870688, 18.499214, 75.197221], [11.033354, 12.119527, 12.932459, 13.303334, 68.613309], [51.055771, 53.821556, 56.717173, 62.147928, 244.173422], [38.307186, 40.681541, 42.964150, 46.559202, 182.286642]]
input_correlations: [[0.999221, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999972, 0.999783], [0.999483, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999999, 0.999603], [-0.999165, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999962, -0.999810], [-0.999984, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999643, -0.998506], [-0.999023, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999923, -0.999871], [-0.999983, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999274, -0.997818], [0.999035, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999930, 0.999866], [0.999382, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999993, 0.999685]]
pre_activation_mean: [2.844230, 3.523960, 0.001441, -0.853583, -0.835525, -0.762370, 2.713038, 2.025407]
pre_activation_std: [3.615669, 4.371779, 0.626336, 0.899327, 0.989995, 0.734032, 3.326670, 2.504947]
### 12
mean: [-3.785794]
std: [5.193107]
fourier: [[79.492709, 84.663202, 89.198134, 96.244206, 340.721504]]
input_correlations: [[-0.999738, -0.999936, 0.758419, 0.000000, 0.000000, 0.000000, -0.999846, -0.999917]]
pre_activation_mean: [-3.785794]
pre_activation_std: [5.193107]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 2.902496576309204, "std": 3.567725896835327, "fourier": [55.01408985312119, 57.59039158657734, 60.35099441083357, 66.97378887860427, 261.2247007638216], "input_correlations": [-0.6669506127824979, -0.13509458481047804, 0.2741385075992213, 0.2819729287729995, 0.46748460500998806, 0.0, 0.0, 0.0], "pre_activation_mean": 0.4170010983943939, "pre_activation_std": 1.5795797109603882}, "1": {"mean": 3.573549747467041, "std": 4.330509662628174, "fourier": [66.47741585340002, 70.2746254511063, 73.86398788764515, 80.75985288334157, 321.6194938868284], "input_correlations": [-0.1673325737351544, -0.11535625734596575, 0.5105190007166079, 0.24078580672881617, 0.8167250344535302, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7818476557731628, "pre_activation_std": 1.4057117700576782}, "2": {"mean": 0.23611833155155182, "std": 0.2403339445590973, "fourier": [3.4307509210753175, 4.046549561821719, 4.859058050478069, 5.158042140849827, 21.250652015209198], "input_correlations": [-0.5493589163418924, 0.09423167567002869, 0.38352276637152033, 0.6351825588437623, 0.06873681230096833, 0.0, 0.0, 0.0], "pre_activation_mean": 1.348206877708435, "pre_activation_std": 1.7680240869522095}, "3": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.010849114361785105, -0.39906712758936624, -0.2466401532977727, -0.3000198392915387, 0.778146166264046, 0.0, 0.0, 0.0], "pre_activation_mean": -0.6987752318382263, "pre_activation_std": 1.6585078239440918}, "4": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.7663826692170352, -0.32989438814391236, -0.6981791503069856, 0.01984717582720904, -0.6183231597618819, 0.0, 0.0, 0.0], "pre_activation_mean": -2.1445860862731934, "pre_activation_std": 1.397410273551941}, "5": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.30239077022748456, 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"val_loss": 0.2342541515827179, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.21023967117071152, "train_acc": 0.95, "val_loss": 0.2107248455286026, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.18506282567977905, "train_acc": 0.96, "val_loss": 0.19767145812511444, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.15985805541276932, "train_acc": 0.96, "val_loss": 0.18973636627197266, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.15473370254039764, "train_acc": 0.96, "val_loss": 0.18826895952224731, "val_acc": 0.94}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6952366828918457, "final_val_loss": 0.6164712309837341, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.5184619426727295, "final_val_loss": 0.18826895952224731, "initial_val_acc": 0.52, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 7}, "improvement": 0.41999999999999993, "first_improvement_epoch": 3}} |
37 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.6, "improved_accuracy": 0.94, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9575, "learning_rate": 0.08435096790732609, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.126305, 22.764334, 1.337756, -0.016087, 3.961633, -0.005878]
std: [0.597830, 15.493368, 0.990779, 0.062440, 2.820551, 0.064256]
fourier: [[9.048595, 9.376233, 9.783882, 10.326041, 11.367429], [260.150241, 260.957968, 277.804157, 305.911961, 2048.790079], [16.512624, 16.963809, 17.848359, 19.418392, 120.398062], [0.971668, 1.052256, 1.129280, 1.390936, 1.447824], [47.838818, 48.377967, 51.679293, 54.097208, 356.546922], [0.865598, 0.940011, 1.101963, 1.157090, 1.365127]]
input_correlations: [[-0.881448, -0.560296, -0.468788, 0.090737, 0.144533, 0.000000, 0.000000, 0.000000], [0.668770, 0.668067, 0.698536, 0.411903, 0.066641, 0.000000, 0.000000, 0.000000], [-0.651898, -0.758168, -0.466243, 0.138690, 0.235824, 0.000000, 0.000000, 0.000000], [-0.760922, -0.806834, -0.293425, -0.056868, 0.157565, 0.000000, 0.000000, 0.000000], [0.738945, 0.313280, 0.536325, -0.557382, 0.165772, 0.000000, 0.000000, 0.000000], [0.787165, 0.587029, 0.736879, 0.226294, 0.336519, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.495128, 5.511377, -2.090539, -1.973909, 0.879670, 4.280330]
pre_activation_std: [3.156101, 3.410702, 3.333900, 2.508114, 2.776163, 2.818137]
### 2
mean: [-2.675165, 6.799007, -0.540798, -3.794281, -2.991783, -3.299845]
std: [2.224249, 5.031027, 1.940591, 2.347505, 1.601820, 1.885148]
fourier: [[37.915210, 38.166339, 38.252833, 40.322208, 240.764834], [82.983427, 85.664970, 87.318532, 97.733248, 611.910647], [29.776117, 31.545548, 37.736693, 43.359927, 48.671835], [38.655980, 42.572369, 43.956390, 46.228822, 341.485244], [22.900818, 23.838621, 31.121168, 33.540502, 269.260494], [29.054235, 31.203983, 33.974821, 40.194704, 296.986026]]
input_correlations: [[0.381357, -0.897572, 0.250278, 0.147697, -0.900407, -0.962669, 0.000000, 0.000000], [-0.506248, 0.921762, -0.385710, -0.278979, 0.848459, 0.948995, 0.000000, 0.000000], [0.922417, -0.576763, 0.859815, 0.793886, -0.603059, -0.516503, 0.000000, 0.000000], [0.093514, -0.856533, -0.029875, -0.136812, -0.861282, -0.961698, 0.000000, 0.000000], [-0.342746, -0.718302, -0.475268, -0.541936, -0.400727, -0.772542, 0.000000, 0.000000], [-0.646549, -0.420505, -0.746094, -0.782306, -0.318657, -0.532258, 0.000000, 0.000000]]
pre_activation_mean: [-2.675165, 6.799007, -0.540798, -3.794281, -2.991783, -3.299845]
pre_activation_std: [2.224249, 5.031027, 1.940591, 2.347505, 1.601820, 1.885148]
### 4
mean: [7.057932, 6.747706, 3.302736, -2.018404, -2.115458, -1.592090]
std: [4.604747, 5.016110, 2.134862, 1.254396, 1.453009, 1.417120]
fourier: [[76.933700, 78.073924, 79.989957, 91.383823, 635.213956], [82.752515, 84.235007, 86.258261, 102.007974, 607.293583], [35.191706, 36.003345, 36.886986, 43.384921, 297.246255], [21.788332, 21.794807, 21.986829, 26.435415, 181.656318], [21.349774, 21.646170, 23.016781, 28.068937, 190.391187], [21.255558, 21.500720, 21.562030, 26.351595, 143.288092]]
input_correlations: [[0.531924, 0.997720, -0.404949, 0.572612, 0.562242, 0.519982, 0.000000, 0.000000], [0.536651, 0.993452, -0.447976, 0.556728, 0.544031, 0.502385, 0.000000, 0.000000], [0.530056, 0.992374, -0.455955, 0.556188, 0.543348, 0.500114, 0.000000, 0.000000], [-0.155146, -0.281975, -0.802988, -0.459033, -0.499680, -0.511343, 0.000000, 0.000000], [0.024864, 0.021243, -0.945639, -0.296567, -0.342379, -0.364328, 0.000000, 0.000000], [0.077154, 0.129938, -0.975478, -0.240930, -0.285478, -0.311150, 0.000000, 0.000000]]
pre_activation_mean: [7.057932, 6.747706, 3.302736, -2.018404, -2.115458, -1.592090]
pre_activation_std: [4.604747, 5.016110, 2.134862, 1.254396, 1.453009, 1.417120]
### 6
mean: [-7.705886, -0.479740, 15.504037, -9.254907, -13.691625, -2.976544]
std: [5.219201, 0.731566, 10.357794, 5.751121, 9.806180, 1.535643]
fourier: [[86.939508, 87.492638, 92.724400, 102.860610, 693.529714], [12.329557, 12.335361, 12.867037, 14.549890, 43.176626], [173.068250, 173.903492, 183.443389, 206.318576, 1395.363328], [96.153911, 96.517647, 101.964035, 114.791796, 832.941587], [163.282580, 164.268873, 174.585226, 194.060294, 1232.246101], [25.835929, 25.862357, 26.997251, 31.030678, 267.889003]]
input_correlations: [[-0.999774, -0.999851, -0.999127, -0.626364, -0.472172, -0.208389, 0.000000, 0.000000], [-0.999718, -0.998799, -0.999615, -0.606318, -0.451059, -0.184804, 0.000000, 0.000000], [0.999764, 0.999645, 0.999666, 0.611044, 0.454998, 0.189745, 0.000000, 0.000000], [-0.999638, -0.999500, -0.999818, -0.606518, -0.449418, -0.183140, 0.000000, 0.000000], [-0.999734, -0.999852, -0.999504, -0.619542, -0.463872, -0.198730, 0.000000, 0.000000], [-0.998903, -0.998307, -0.999650, -0.586398, -0.427186, -0.159340, 0.000000, 0.000000]]
pre_activation_mean: [-7.705886, -0.479740, 15.504037, -9.254907, -13.691625, -2.976544]
pre_activation_std: [5.219201, 0.731566, 10.357794, 5.751121, 9.806180, 1.535643]
### 8
mean: [13.407875, 7.457570, -4.602429, 0.856107, -2.685322, 12.071948]
std: [8.971179, 5.399687, 3.674570, 0.280909, 2.196863, 8.357375]
fourier: [[149.982079, 151.093582, 158.950949, 179.181320, 1206.708617], [89.863698, 90.872549, 95.475552, 108.028898, 671.181254], [61.716721, 62.181189, 65.561932, 73.104054, 414.218590], [4.789869, 4.799982, 4.814316, 5.961675, 77.049636], [36.934868, 37.212539, 39.253181, 43.719536, 241.678937], [139.942690, 140.857939, 148.829263, 166.258227, 1086.475375]]
input_correlations: [[0.564118, -0.645860, 0.999817, 0.443346, -0.239957, 0.777439, 0.000000, 0.000000], [0.558698, -0.638063, 0.999934, 0.437851, -0.234882, 0.771684, 0.000000, 0.000000], [-0.576072, 0.657709, -0.999439, -0.454691, 0.245018, -0.787142, 0.000000, 0.000000], [0.218807, -0.159799, 0.855090, -0.005702, 0.171777, 0.399680, 0.000000, 0.000000], [-0.580777, 0.664483, -0.999092, -0.461306, 0.249953, -0.792072, 0.000000, 0.000000], [0.567066, -0.645933, 0.999857, 0.441640, -0.233829, 0.779094, 0.000000, 0.000000]]
pre_activation_mean: [13.407875, 7.457570, -4.602429, 0.856107, -2.685322, 12.071948]
pre_activation_std: [8.971179, 5.399687, 3.674570, 0.280909, 2.196863, 8.357375]
### 10
mean: [-8.090800, 22.686470, 1.426798, -5.499561, 3.954546, -8.061385]
std: [6.421513, 15.611624, 0.948515, 3.853159, 2.845621, 5.684762]
fourier: [[107.860719, 109.367206, 114.431593, 128.286361, 728.171913], [261.111036, 263.845469, 278.427102, 310.800264, 2041.782163], [16.132282, 16.334685, 17.256976, 18.269876, 128.411795], [64.322820, 65.186460, 68.832715, 76.097270, 494.960470], [48.348596, 48.485149, 51.166913, 56.215939, 355.909155], [94.887311, 95.674829, 101.487827, 112.623277, 725.524569]]
input_correlations: [[-0.999012, -0.997825, 0.309806, -0.828036, 0.231554, -0.998610, 0.000000, 0.000000], [0.999921, 0.999389, -0.280944, 0.842865, -0.200796, 0.999768, 0.000000, 0.000000], [0.996809, 0.997736, -0.205336, 0.858362, -0.122755, 0.997491, 0.000000, 0.000000], [-0.999895, -0.999848, 0.263803, -0.853792, 0.184826, -0.999890, 0.000000, 0.000000], [0.998521, 0.997227, -0.309791, 0.819482, -0.232733, 0.998201, 0.000000, 0.000000], [-0.999950, -0.999906, 0.260672, -0.853325, 0.180039, -0.999976, 0.000000, 0.000000]]
pre_activation_mean: [-8.090800, 22.686470, 1.426798, -5.499561, 3.954546, -8.061385]
pre_activation_std: [6.421513, 15.611624, 0.948515, 3.853159, 2.845621, 5.684762]
### 12
mean: [-15.752302]
std: [11.403414]
fourier: [[190.788004, 192.661534, 203.313739, 227.825331, 1417.707118]]
input_correlations: [[0.344521, -0.999630, -0.994123, -0.248557, -0.998700, -0.046509, 0.000000, 0.000000]]
pre_activation_mean: [-15.752302]
pre_activation_std: [11.403414]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-1.188596,
-0.494698,
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0.157994,
0.541707
],
[
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],
[
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],
[
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[
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],
[
0.744311,
0.387308,
0.704521,
0.19704,
0.174
]
],
"network.0.bias": [
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0.821905,
0.138075,
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-0.015605,
0.539507
],
"network.2.weight": [
[
0.096317,
-0.252768,
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0.211636,
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],
[
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0.660914,
-0.536769,
-0.425487,
0.843517,
0.393602
],
[
0.754048,
-0.276713,
0.620358,
0.500933,
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0.290189
],
[
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-0.242021,
-0.214834,
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-0.260471
],
[
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0.225314,
-0.495744
],
[
-1.119423,
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-0.782233,
-0.124337,
-0.12758,
-0.148264
]
],
"network.2.bias": [
0.181057,
0.501348,
-0.112788,
-0.332412,
-0.270596,
-0.573209
],
"network.4.weight": [
[
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-0.217411,
-0.107269,
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],
[
0.129986,
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0.161995,
-0.21886,
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],
[
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0.074916,
0.209796,
-0.300653
],
[
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0.254821,
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0.485601
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[
-0.303123,
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0.394237,
0.635056,
0.456971
],
[
-0.598061,
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-1.06987,
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0.38953,
0.698287
]
],
"network.4.bias": [
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],
"network.6.weight": [
[
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[
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[
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[
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[
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[
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]
],
"network.6.bias": [
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"network.8.weight": [
[
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],
[
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[
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[
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[
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[
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],
"network.8.bias": [
0.139843,
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],
"network.10.weight": [
[
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],
[
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],
[
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[
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[
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],
"network.10.bias": [
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],
"network.12.weight": [
[
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-0.180954,
-0.004123,
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]
],
"network.12.bias": [
0.728509
]
}
## Activation Signature
### 0
mean: [0.126305, 22.764334, 1.337756, -0.016087, 3.961633, -0.005878]
std: [0.597830, 15.493368, 0.990779, 0.062440, 2.820551, 0.064256]
fourier: [[9.048595, 9.376233, 9.783882, 10.326041, 11.367429], [260.150241, 260.957968, 277.804157, 305.911961, 2048.790079], [16.512624, 16.963809, 17.848359, 19.418392, 120.398062], [0.971668, 1.052256, 1.129280, 1.390936, 1.447824], [47.838818, 48.377967, 51.679293, 54.097208, 356.546922], [0.865598, 0.940011, 1.101963, 1.157090, 1.365127]]
input_correlations: [[-0.881448, -0.560296, -0.468788, 0.090737, 0.144533, 0.000000, 0.000000, 0.000000], [0.668770, 0.668067, 0.698536, 0.411903, 0.066641, 0.000000, 0.000000, 0.000000], [-0.651898, -0.758168, -0.466243, 0.138690, 0.235824, 0.000000, 0.000000, 0.000000], [-0.760922, -0.806834, -0.293425, -0.056868, 0.157565, 0.000000, 0.000000, 0.000000], [0.738945, 0.313280, 0.536325, -0.557382, 0.165772, 0.000000, 0.000000, 0.000000], [0.787165, 0.587029, 0.736879, 0.226294, 0.336519, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.495128, 5.511377, -2.090539, -1.973909, 0.879670, 4.280330]
pre_activation_std: [3.156101, 3.410702, 3.333900, 2.508114, 2.776163, 2.818137]
### 2
mean: [-2.675165, 6.799007, -0.540798, -3.794281, -2.991783, -3.299845]
std: [2.224249, 5.031027, 1.940591, 2.347505, 1.601820, 1.885148]
fourier: [[37.915210, 38.166339, 38.252833, 40.322208, 240.764834], [82.983427, 85.664970, 87.318532, 97.733248, 611.910647], [29.776117, 31.545548, 37.736693, 43.359927, 48.671835], [38.655980, 42.572369, 43.956390, 46.228822, 341.485244], [22.900818, 23.838621, 31.121168, 33.540502, 269.260494], [29.054235, 31.203983, 33.974821, 40.194704, 296.986026]]
input_correlations: [[0.381357, -0.897572, 0.250278, 0.147697, -0.900407, -0.962669, 0.000000, 0.000000], [-0.506248, 0.921762, -0.385710, -0.278979, 0.848459, 0.948995, 0.000000, 0.000000], [0.922417, -0.576763, 0.859815, 0.793886, -0.603059, -0.516503, 0.000000, 0.000000], [0.093514, -0.856533, -0.029875, -0.136812, -0.861282, -0.961698, 0.000000, 0.000000], [-0.342746, -0.718302, -0.475268, -0.541936, -0.400727, -0.772542, 0.000000, 0.000000], [-0.646549, -0.420505, -0.746094, -0.782306, -0.318657, -0.532258, 0.000000, 0.000000]]
pre_activation_mean: [-2.675165, 6.799007, -0.540798, -3.794281, -2.991783, -3.299845]
pre_activation_std: [2.224249, 5.031027, 1.940591, 2.347505, 1.601820, 1.885148]
### 4
mean: [7.057932, 6.747706, 3.302736, -2.018404, -2.115458, -1.592090]
std: [4.604747, 5.016110, 2.134862, 1.254396, 1.453009, 1.417120]
fourier: [[76.933700, 78.073924, 79.989957, 91.383823, 635.213956], [82.752515, 84.235007, 86.258261, 102.007974, 607.293583], [35.191706, 36.003345, 36.886986, 43.384921, 297.246255], [21.788332, 21.794807, 21.986829, 26.435415, 181.656318], [21.349774, 21.646170, 23.016781, 28.068937, 190.391187], [21.255558, 21.500720, 21.562030, 26.351595, 143.288092]]
input_correlations: [[0.531924, 0.997720, -0.404949, 0.572612, 0.562242, 0.519982, 0.000000, 0.000000], [0.536651, 0.993452, -0.447976, 0.556728, 0.544031, 0.502385, 0.000000, 0.000000], [0.530056, 0.992374, -0.455955, 0.556188, 0.543348, 0.500114, 0.000000, 0.000000], [-0.155146, -0.281975, -0.802988, -0.459033, -0.499680, -0.511343, 0.000000, 0.000000], [0.024864, 0.021243, -0.945639, -0.296567, -0.342379, -0.364328, 0.000000, 0.000000], [0.077154, 0.129938, -0.975478, -0.240930, -0.285478, -0.311150, 0.000000, 0.000000]]
pre_activation_mean: [7.057932, 6.747706, 3.302736, -2.018404, -2.115458, -1.592090]
pre_activation_std: [4.604747, 5.016110, 2.134862, 1.254396, 1.453009, 1.417120]
### 6
mean: [-7.705886, -0.479740, 15.504037, -9.254907, -13.691625, -2.976544]
std: [5.219201, 0.731566, 10.357794, 5.751121, 9.806180, 1.535643]
fourier: [[86.939508, 87.492638, 92.724400, 102.860610, 693.529714], [12.329557, 12.335361, 12.867037, 14.549890, 43.176626], [173.068250, 173.903492, 183.443389, 206.318576, 1395.363328], [96.153911, 96.517647, 101.964035, 114.791796, 832.941587], [163.282580, 164.268873, 174.585226, 194.060294, 1232.246101], [25.835929, 25.862357, 26.997251, 31.030678, 267.889003]]
input_correlations: [[-0.999774, -0.999851, -0.999127, -0.626364, -0.472172, -0.208389, 0.000000, 0.000000], [-0.999718, -0.998799, -0.999615, -0.606318, -0.451059, -0.184804, 0.000000, 0.000000], [0.999764, 0.999645, 0.999666, 0.611044, 0.454998, 0.189745, 0.000000, 0.000000], [-0.999638, -0.999500, -0.999818, -0.606518, -0.449418, -0.183140, 0.000000, 0.000000], [-0.999734, -0.999852, -0.999504, -0.619542, -0.463872, -0.198730, 0.000000, 0.000000], [-0.998903, -0.998307, -0.999650, -0.586398, -0.427186, -0.159340, 0.000000, 0.000000]]
pre_activation_mean: [-7.705886, -0.479740, 15.504037, -9.254907, -13.691625, -2.976544]
pre_activation_std: [5.219201, 0.731566, 10.357794, 5.751121, 9.806180, 1.535643]
### 8
mean: [13.407875, 7.457570, -4.602429, 0.856107, -2.685322, 12.071948]
std: [8.971179, 5.399687, 3.674570, 0.280909, 2.196863, 8.357375]
fourier: [[149.982079, 151.093582, 158.950949, 179.181320, 1206.708617], [89.863698, 90.872549, 95.475552, 108.028898, 671.181254], [61.716721, 62.181189, 65.561932, 73.104054, 414.218590], [4.789869, 4.799982, 4.814316, 5.961675, 77.049636], [36.934868, 37.212539, 39.253181, 43.719536, 241.678937], [139.942690, 140.857939, 148.829263, 166.258227, 1086.475375]]
input_correlations: [[0.564118, -0.645860, 0.999817, 0.443346, -0.239957, 0.777439, 0.000000, 0.000000], [0.558698, -0.638063, 0.999934, 0.437851, -0.234882, 0.771684, 0.000000, 0.000000], [-0.576072, 0.657709, -0.999439, -0.454691, 0.245018, -0.787142, 0.000000, 0.000000], [0.218807, -0.159799, 0.855090, -0.005702, 0.171777, 0.399680, 0.000000, 0.000000], [-0.580777, 0.664483, -0.999092, -0.461306, 0.249953, -0.792072, 0.000000, 0.000000], [0.567066, -0.645933, 0.999857, 0.441640, -0.233829, 0.779094, 0.000000, 0.000000]]
pre_activation_mean: [13.407875, 7.457570, -4.602429, 0.856107, -2.685322, 12.071948]
pre_activation_std: [8.971179, 5.399687, 3.674570, 0.280909, 2.196863, 8.357375]
### 10
mean: [-8.090800, 22.686470, 1.426798, -5.499561, 3.954546, -8.061385]
std: [6.421513, 15.611624, 0.948515, 3.853159, 2.845621, 5.684762]
fourier: [[107.860719, 109.367206, 114.431593, 128.286361, 728.171913], [261.111036, 263.845469, 278.427102, 310.800264, 2041.782163], [16.132282, 16.334685, 17.256976, 18.269876, 128.411795], [64.322820, 65.186460, 68.832715, 76.097270, 494.960470], [48.348596, 48.485149, 51.166913, 56.215939, 355.909155], [94.887311, 95.674829, 101.487827, 112.623277, 725.524569]]
input_correlations: [[-0.999012, -0.997825, 0.309806, -0.828036, 0.231554, -0.998610, 0.000000, 0.000000], [0.999921, 0.999389, -0.280944, 0.842865, -0.200796, 0.999768, 0.000000, 0.000000], [0.996809, 0.997736, -0.205336, 0.858362, -0.122755, 0.997491, 0.000000, 0.000000], [-0.999895, -0.999848, 0.263803, -0.853792, 0.184826, -0.999890, 0.000000, 0.000000], [0.998521, 0.997227, -0.309791, 0.819482, -0.232733, 0.998201, 0.000000, 0.000000], [-0.999950, -0.999906, 0.260672, -0.853325, 0.180039, -0.999976, 0.000000, 0.000000]]
pre_activation_mean: [-8.090800, 22.686470, 1.426798, -5.499561, 3.954546, -8.061385]
pre_activation_std: [6.421513, 15.611624, 0.948515, 3.853159, 2.845621, 5.684762]
### 12
mean: [-15.752302]
std: [11.403414]
fourier: [[190.788004, 192.661534, 203.313739, 227.825331, 1417.707118]]
input_correlations: [[0.344521, -0.999630, -0.994123, -0.248557, -0.998700, -0.046509, 0.000000, 0.000000]]
pre_activation_mean: [-15.752302]
pre_activation_std: [11.403414]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.1263047754764557, "std": 0.5978302955627441, "fourier": [9.048594613948566, 9.376232980236544, 9.783881533400352, 10.326040795337795, 11.36742933018968], "input_correlations": [-0.8814481015417613, -0.560295884434315, -0.4687884626609225, 0.09073731327122768, 0.14453270274566832, 0.0, 0.0, 0.0], "pre_activation_mean": -1.4951281547546387, "pre_activation_std": 3.1561012268066406}, "1": {"mean": 22.764333724975586, "std": 15.493368148803711, "fourier": [260.15024125667463, 260.9579675043447, 277.8041567965782, 305.9119607936591, 2048.7900790199637], "input_correlations": [0.6687698348735788, 0.6680667246943615, 0.6985357008248503, 0.41190268642710304, 0.0666411478785459, 0.0, 0.0, 0.0], "pre_activation_mean": 5.511377334594727, "pre_activation_std": 3.4107019901275635}, "2": {"mean": 1.3377562761306763, "std": 0.9907790422439575, "fourier": [16.512623866576345, 16.96380869967518, 17.848359020775316, 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38 | {"target_pattern": "ends_with", "degraded_accuracy": 0.58, "improved_accuracy": 0.78, "improvement": 0.20000000000000007, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2084, "learning_rate": 0.07613021159903365, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 6.455161, 6.397736, 7.606741, 0.491512, 0.441715]
std: [0.000000, 0.000000, 0.000000, 7.839872, 7.932398, 9.314350, 0.577529, 0.511528]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [118.673837, 126.635520, 179.088395, 179.491045, 580.964432], [118.224446, 127.168933, 180.494173, 182.432407, 575.796239], [139.081222, 148.698482, 211.476846, 213.844901, 684.606675], [8.938655, 10.162629, 10.230686, 12.550998, 44.236099], [7.624600, 8.768513, 8.971978, 11.239309, 39.754379]]
input_correlations: [[0.626749, -0.115489, 0.350362, -0.664447, 0.430990, 0.000000, 0.000000, 0.000000], [0.722495, -0.031815, 0.035668, -0.153393, 0.688291, 0.000000, 0.000000, 0.000000], [-0.328674, -0.252766, 0.141253, 0.290164, 0.839018, 0.000000, 0.000000, 0.000000], [-0.401444, 0.134304, -0.189651, 0.107574, -0.929453, 0.000000, 0.000000, 0.000000], [-0.805933, -0.646425, -0.683974, -0.165337, -0.341985, 0.000000, 0.000000, 0.000000], [0.845212, -0.004802, 0.164744, -0.552684, 0.104298, 0.000000, 0.000000, 0.000000], [-0.412888, 0.516179, 0.134259, 0.428486, -0.555135, 0.000000, 0.000000, 0.000000], [-0.255149, -0.172111, 0.154641, -0.101153, -0.881469, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.349496, 0.869958, 1.086323, -0.342604, -3.983193, -0.086849, 0.617154, -0.267840]
pre_activation_std: [1.547504, 1.261258, 2.252962, 1.998992, 2.673750, 1.694431, 1.558184, 1.604016]
### 2
mean: [1.616312, -1.380903, 1.723426, 0.386708, 2.271594, 0.141723, -0.805760, -1.108474]
std: [1.960400, 0.809442, 2.048407, 1.793177, 3.119458, 0.766242, 1.425582, 1.673951]
fourier: [[31.233175, 33.815573, 37.706017, 40.791776, 145.468064], [11.600237, 12.928476, 13.734506, 14.582595, 124.281312], [31.912965, 33.069444, 44.230431, 44.946786, 155.108382], [27.842559, 33.383578, 34.803720, 35.995345, 40.278562], [51.332951, 54.638445, 65.075533, 70.315332, 204.443456], [11.878159, 12.755057, 13.074870, 14.967949, 16.389410], [20.961772, 21.503229, 25.708490, 30.060348, 72.518418], [24.180671, 31.228282, 33.183450, 33.366434, 99.762685]]
input_correlations: [[0.150587, 0.418301, 0.986143, -0.330466, 0.000000, -0.163421, -0.202766, -0.292916], [0.273394, 0.305192, -0.522630, -0.447378, 0.000000, 0.513712, -0.576683, -0.509942], [0.556757, 0.828675, 0.847958, -0.716536, 0.000000, 0.362038, -0.615645, -0.468324], [-0.614384, -0.884557, -0.552776, 0.885423, 0.000000, -0.552906, 0.834275, 0.647372], [0.646758, 0.900998, 0.749516, -0.768274, 0.000000, 0.504731, -0.663982, -0.482734], [0.581796, 0.646241, -0.327596, -0.455990, 0.000000, 0.843302, -0.567160, -0.228424], [-0.944243, -0.855778, -0.082350, 0.562501, 0.000000, -0.927022, 0.512965, 0.340222], [-0.212127, -0.632532, -0.912564, 0.639775, 0.000000, -0.035569, 0.589943, 0.440580]]
pre_activation_mean: [1.616312, -1.380903, 1.723426, 0.386708, 2.271594, 0.141723, -0.805760, -1.108474]
pre_activation_std: [1.960400, 0.809442, 2.048407, 1.793177, 3.119458, 0.766242, 1.425582, 1.673951]
### 4
mean: [1.665282, 1.458605, 1.944999, -2.965130, 3.295928, 1.837434, 2.096758, -2.687882]
std: [0.705559, 2.966180, 2.968405, 2.504218, 4.829532, 3.379042, 3.053724, 2.114586]
fourier: [[10.333535, 12.690827, 13.691890, 14.954299, 149.875427], [49.440687, 53.505174, 61.594655, 69.084650, 131.274492], [45.738235, 46.166060, 65.464657, 66.810218, 175.049860], [38.606140, 40.720384, 49.635375, 55.437737, 266.861665], [76.617426, 77.524646, 107.086588, 107.507191, 296.633470], [55.046820, 59.161675, 72.187523, 75.968822, 165.369093], [49.870840, 51.675153, 66.656138, 68.746772, 188.708191], [31.162088, 32.598069, 43.486605, 48.673961, 241.909388]]
input_correlations: [[0.780706, 0.000000, 0.765951, -0.032049, 0.760737, 0.094469, 0.240926, 0.210653], [0.670167, 0.000000, 0.955881, -0.817418, 0.972192, 0.462152, -0.557943, -0.507175], [0.850547, 0.000000, 0.997458, -0.672991, 0.977277, 0.235406, -0.406608, -0.403738], [-0.989626, 0.000000, -0.896653, 0.339631, -0.824509, 0.142837, 0.084811, 0.149879], [0.814394, 0.000000, 0.995162, -0.711770, 0.983509, 0.296096, -0.439215, -0.434092], [0.741802, 0.000000, 0.975581, -0.791064, 0.975622, 0.379973, -0.519812, -0.501877], [0.764285, 0.000000, 0.986981, -0.749329, 0.986661, 0.366516, -0.479219, -0.463978], [-0.945239, 0.000000, -0.940467, 0.368796, -0.897913, -0.020453, 0.104776, 0.148424]]
pre_activation_mean: [1.665282, 1.458605, 1.944999, -2.965130, 3.295928, 1.837434, 2.096758, -2.687882]
pre_activation_std: [0.705559, 2.966180, 2.968405, 2.504218, 4.829532, 3.379042, 3.053724, 2.114586]
### 6
mean: [-4.783035, -0.619019, -1.997565, 6.366692, 6.258611, 7.544556, -1.948124, -1.218312]
std: [4.841861, 0.113584, 1.263921, 7.913437, 8.046103, 9.365412, 3.730514, 2.681009]
fourier: [[71.233872, 78.104910, 109.937175, 111.665124, 430.473152], [1.667873, 2.050325, 2.096161, 2.630709, 55.711751], [19.845383, 20.054207, 27.895019, 29.597461, 179.780870], [120.713928, 127.892605, 180.742494, 180.769191, 573.002216], [121.281638, 128.947133, 183.124878, 184.414758, 563.275063], [140.215950, 149.418770, 212.532607, 214.977542, 679.010048], [57.258578, 59.195653, 84.761817, 84.906107, 175.331202], [41.201313, 42.053037, 60.499527, 60.873857, 109.648068]]
input_correlations: [[-0.807653, -0.991348, -0.993099, 0.000000, -0.997389, -0.998131, -0.997695, 0.000000], [-0.055105, 0.563931, 0.409545, 0.000000, 0.459298, 0.507058, 0.514969, 0.000000], [-0.883931, -0.972550, -0.980710, 0.000000, -0.981072, -0.980077, -0.978061, 0.000000], [0.774637, 0.991972, 0.993419, 0.000000, 0.998637, 0.999553, 0.999496, 0.000000], [0.779383, 0.989748, 0.995285, 0.000000, 0.999362, 0.999093, 0.998841, 0.000000], [0.782785, 0.988785, 0.995943, 0.000000, 0.999597, 0.998739, 0.998540, 0.000000], [-0.753782, -0.985990, -0.994931, 0.000000, -0.998827, -0.997532, -0.997586, 0.000000], [-0.743142, -0.980838, -0.994892, 0.000000, -0.997937, -0.995196, -0.995221, 0.000000]]
pre_activation_mean: [-4.783035, -0.619019, -1.997565, 6.366692, 6.258611, 7.544556, -1.948124, -1.218312]
pre_activation_std: [4.841861, 0.113584, 1.263921, 7.913437, 8.046103, 9.365412, 3.730514, 2.681009]
### 8
mean: [-6.540194]
std: [9.808219]
fourier: [[150.512994, 158.096341, 221.897346, 225.408709, 588.617374]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999185, -0.998529, -0.998849, 0.715601, 0.723383]]
pre_activation_mean: [-6.540194]
pre_activation_std: [9.808219]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 6.455161, 6.397736, 7.606741, 0.491512, 0.441715]
std: [0.000000, 0.000000, 0.000000, 7.839872, 7.932398, 9.314350, 0.577529, 0.511528]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [118.673837, 126.635520, 179.088395, 179.491045, 580.964432], [118.224446, 127.168933, 180.494173, 182.432407, 575.796239], [139.081222, 148.698482, 211.476846, 213.844901, 684.606675], [8.938655, 10.162629, 10.230686, 12.550998, 44.236099], [7.624600, 8.768513, 8.971978, 11.239309, 39.754379]]
input_correlations: [[0.626749, -0.115489, 0.350362, -0.664447, 0.430990, 0.000000, 0.000000, 0.000000], [0.722495, -0.031815, 0.035668, -0.153393, 0.688291, 0.000000, 0.000000, 0.000000], [-0.328674, -0.252766, 0.141253, 0.290164, 0.839018, 0.000000, 0.000000, 0.000000], [-0.401444, 0.134304, -0.189651, 0.107574, -0.929453, 0.000000, 0.000000, 0.000000], [-0.805933, -0.646425, -0.683974, -0.165337, -0.341985, 0.000000, 0.000000, 0.000000], [0.845212, -0.004802, 0.164744, -0.552684, 0.104298, 0.000000, 0.000000, 0.000000], [-0.412888, 0.516179, 0.134259, 0.428486, -0.555135, 0.000000, 0.000000, 0.000000], [-0.255149, -0.172111, 0.154641, -0.101153, -0.881469, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.349496, 0.869958, 1.086323, -0.342604, -3.983193, -0.086849, 0.617154, -0.267840]
pre_activation_std: [1.547504, 1.261258, 2.252962, 1.998992, 2.673750, 1.694431, 1.558184, 1.604016]
### 2
mean: [1.616312, -1.380903, 1.723426, 0.386708, 2.271594, 0.141723, -0.805760, -1.108474]
std: [1.960400, 0.809442, 2.048407, 1.793177, 3.119458, 0.766242, 1.425582, 1.673951]
fourier: [[31.233175, 33.815573, 37.706017, 40.791776, 145.468064], [11.600237, 12.928476, 13.734506, 14.582595, 124.281312], [31.912965, 33.069444, 44.230431, 44.946786, 155.108382], [27.842559, 33.383578, 34.803720, 35.995345, 40.278562], [51.332951, 54.638445, 65.075533, 70.315332, 204.443456], [11.878159, 12.755057, 13.074870, 14.967949, 16.389410], [20.961772, 21.503229, 25.708490, 30.060348, 72.518418], [24.180671, 31.228282, 33.183450, 33.366434, 99.762685]]
input_correlations: [[0.150587, 0.418301, 0.986143, -0.330466, 0.000000, -0.163421, -0.202766, -0.292916], [0.273394, 0.305192, -0.522630, -0.447378, 0.000000, 0.513712, -0.576683, -0.509942], [0.556757, 0.828675, 0.847958, -0.716536, 0.000000, 0.362038, -0.615645, -0.468324], [-0.614384, -0.884557, -0.552776, 0.885423, 0.000000, -0.552906, 0.834275, 0.647372], [0.646758, 0.900998, 0.749516, -0.768274, 0.000000, 0.504731, -0.663982, -0.482734], [0.581796, 0.646241, -0.327596, -0.455990, 0.000000, 0.843302, -0.567160, -0.228424], [-0.944243, -0.855778, -0.082350, 0.562501, 0.000000, -0.927022, 0.512965, 0.340222], [-0.212127, -0.632532, -0.912564, 0.639775, 0.000000, -0.035569, 0.589943, 0.440580]]
pre_activation_mean: [1.616312, -1.380903, 1.723426, 0.386708, 2.271594, 0.141723, -0.805760, -1.108474]
pre_activation_std: [1.960400, 0.809442, 2.048407, 1.793177, 3.119458, 0.766242, 1.425582, 1.673951]
### 4
mean: [1.665282, 1.458605, 1.944999, -2.965130, 3.295928, 1.837434, 2.096758, -2.687882]
std: [0.705559, 2.966180, 2.968405, 2.504218, 4.829532, 3.379042, 3.053724, 2.114586]
fourier: [[10.333535, 12.690827, 13.691890, 14.954299, 149.875427], [49.440687, 53.505174, 61.594655, 69.084650, 131.274492], [45.738235, 46.166060, 65.464657, 66.810218, 175.049860], [38.606140, 40.720384, 49.635375, 55.437737, 266.861665], [76.617426, 77.524646, 107.086588, 107.507191, 296.633470], [55.046820, 59.161675, 72.187523, 75.968822, 165.369093], [49.870840, 51.675153, 66.656138, 68.746772, 188.708191], [31.162088, 32.598069, 43.486605, 48.673961, 241.909388]]
input_correlations: [[0.780706, 0.000000, 0.765951, -0.032049, 0.760737, 0.094469, 0.240926, 0.210653], [0.670167, 0.000000, 0.955881, -0.817418, 0.972192, 0.462152, -0.557943, -0.507175], [0.850547, 0.000000, 0.997458, -0.672991, 0.977277, 0.235406, -0.406608, -0.403738], [-0.989626, 0.000000, -0.896653, 0.339631, -0.824509, 0.142837, 0.084811, 0.149879], [0.814394, 0.000000, 0.995162, -0.711770, 0.983509, 0.296096, -0.439215, -0.434092], [0.741802, 0.000000, 0.975581, -0.791064, 0.975622, 0.379973, -0.519812, -0.501877], [0.764285, 0.000000, 0.986981, -0.749329, 0.986661, 0.366516, -0.479219, -0.463978], [-0.945239, 0.000000, -0.940467, 0.368796, -0.897913, -0.020453, 0.104776, 0.148424]]
pre_activation_mean: [1.665282, 1.458605, 1.944999, -2.965130, 3.295928, 1.837434, 2.096758, -2.687882]
pre_activation_std: [0.705559, 2.966180, 2.968405, 2.504218, 4.829532, 3.379042, 3.053724, 2.114586]
### 6
mean: [-4.783035, -0.619019, -1.997565, 6.366692, 6.258611, 7.544556, -1.948124, -1.218312]
std: [4.841861, 0.113584, 1.263921, 7.913437, 8.046103, 9.365412, 3.730514, 2.681009]
fourier: [[71.233872, 78.104910, 109.937175, 111.665124, 430.473152], [1.667873, 2.050325, 2.096161, 2.630709, 55.711751], [19.845383, 20.054207, 27.895019, 29.597461, 179.780870], [120.713928, 127.892605, 180.742494, 180.769191, 573.002216], [121.281638, 128.947133, 183.124878, 184.414758, 563.275063], [140.215950, 149.418770, 212.532607, 214.977542, 679.010048], [57.258578, 59.195653, 84.761817, 84.906107, 175.331202], [41.201313, 42.053037, 60.499527, 60.873857, 109.648068]]
input_correlations: [[-0.807653, -0.991348, -0.993099, 0.000000, -0.997389, -0.998131, -0.997695, 0.000000], [-0.055105, 0.563931, 0.409545, 0.000000, 0.459298, 0.507058, 0.514969, 0.000000], [-0.883931, -0.972550, -0.980710, 0.000000, -0.981072, -0.980077, -0.978061, 0.000000], [0.774637, 0.991972, 0.993419, 0.000000, 0.998637, 0.999553, 0.999496, 0.000000], [0.779383, 0.989748, 0.995285, 0.000000, 0.999362, 0.999093, 0.998841, 0.000000], [0.782785, 0.988785, 0.995943, 0.000000, 0.999597, 0.998739, 0.998540, 0.000000], [-0.753782, -0.985990, -0.994931, 0.000000, -0.998827, -0.997532, -0.997586, 0.000000], [-0.743142, -0.980838, -0.994892, 0.000000, -0.997937, -0.995196, -0.995221, 0.000000]]
pre_activation_mean: [-4.783035, -0.619019, -1.997565, 6.366692, 6.258611, 7.544556, -1.948124, -1.218312]
pre_activation_std: [4.841861, 0.113584, 1.263921, 7.913437, 8.046103, 9.365412, 3.730514, 2.681009]
### 8
mean: [-6.540194]
std: [9.808219]
fourier: [[150.512994, 158.096341, 221.897346, 225.408709, 588.617374]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999185, -0.998529, -0.998849, 0.715601, 0.723383]]
pre_activation_mean: [-6.540194]
pre_activation_std: [9.808219]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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{"neuron_profiles": {"0": {"mean": -6.540193557739258, "std": 9.808218955993652, "fourier": [150.5129939409798, 158.09634074032593, 221.8973462193728, 225.40870914611838, 588.6173738241196], "input_correlations": [0.0, 0.0, 0.0, -0.9991853991442406, -0.9985288292229648, -0.9988488582843226, 0.715600546245029, 0.7233833568891853], "pre_activation_mean": -6.540193557739258, "pre_activation_std": 9.808218955993652}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, 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"epoch": 3, "global_epoch": 5, "train_loss": 0.31863756477832794, "train_acc": 0.865, "val_loss": 0.5908229351043701, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.2754162549972534, "train_acc": 0.91, "val_loss": 0.6634003520011902, "val_acc": 0.78}], "summary": {"total_epochs": 7, "degraded_epochs": 2, "improved_epochs": 5, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6481384038925171, "final_val_loss": 0.5449063181877136, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.4776480197906494, "final_val_loss": 0.6634003520011902, "initial_val_acc": 0.74, "final_val_acc": 0.78, "best_val_acc": 0.78, "best_epoch": 5}, "improvement": 0.20000000000000007, "first_improvement_epoch": 1}} |
39 | {"target_pattern": "palindrome", "degraded_accuracy": 0.7, "improved_accuracy": 0.98, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6322, "learning_rate": 0.045238552165504674, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.209088,
0.622843,
0.309002,
-0.319278
],
[
-0.321769,
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0.543033,
0.343401,
-0.032412,
-0.27979,
-0.366531,
0.026434
],
[
-0.317496,
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0.152353,
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0.444358,
-0.283713,
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]
],
"network.8.bias": [
0.003478,
-0.143922,
0.182968,
0.26884,
-0.192484,
0.347592,
-0.04523,
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],
"network.10.weight": [
[
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0.492412,
-0.309004,
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],
"network.10.bias": [
0.414919
]
}
## Activation Signature
### 0
mean: [3.452148, 0.696952, 0.272375, 0.656031, 0.258257, 0.654360, 1.057184, 2.211468]
std: [3.610657, 0.962136, 0.864056, 1.286045, 0.676390, 1.273276, 1.325389, 2.297711]
fourier: [[63.810766, 66.392638, 66.625940, 73.251151, 310.693334], [16.228110, 18.223725, 18.825661, 18.978053, 62.725697], [15.714635, 16.274744, 17.422098, 17.625938, 24.513782], [23.017966, 23.577910, 24.316248, 28.648840, 59.042797], [12.294740, 12.308140, 13.714543, 13.925877, 23.243158], [22.882684, 23.295753, 23.526231, 28.597938, 58.892408], [23.333904, 23.971707, 24.856933, 27.566420, 95.146510], [37.973947, 41.833880, 42.237988, 48.385216, 199.032070]]
input_correlations: [[-0.125929, 0.155428, 0.679668, -0.341914, -0.420179, 0.000000, 0.000000, 0.000000], [0.739143, 0.627776, 0.496365, 0.222310, 0.617766, 0.000000, 0.000000, 0.000000], [-0.317620, -0.436136, 0.291552, -0.358370, -0.670645, 0.000000, 0.000000, 0.000000], [-0.786387, -0.031701, -0.478284, 0.216438, -0.649082, 0.000000, 0.000000, 0.000000], [0.044228, -0.290254, -0.068722, 0.607256, 0.677167, 0.000000, 0.000000, 0.000000], [0.706319, 0.505590, 0.223358, -0.438441, 0.313187, 0.000000, 0.000000, 0.000000], [0.200705, 0.291226, 0.966635, 0.234850, 0.282021, 0.000000, 0.000000, 0.000000], [0.078625, -0.522784, -0.146667, -0.774417, 0.413169, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.846067, 1.041275, 0.032750, -1.170650, 0.759925, 0.567652, 1.984452, -1.475212]
pre_activation_std: [0.990239, 1.024945, 1.051430, 2.248228, 1.584272, 1.723928, 1.081133, 0.966469]
### 2
mean: [0.375161, 2.112456, -1.185829, 2.266902, 1.658136, 0.562950, 1.202070, -0.868615]
std: [1.655707, 1.375781, 0.980781, 2.141028, 1.357002, 1.243207, 0.672466, 0.486950]
fourier: [[27.326228, 27.689236, 28.120585, 32.023345, 33.764470], [20.672503, 21.751596, 23.559633, 30.740962, 190.120996], [15.946459, 16.286606, 17.915296, 18.151825, 106.724633], [39.395349, 40.067038, 42.056675, 43.878392, 204.021227], [23.549632, 24.280076, 24.796080, 27.024951, 149.232233], [18.466101, 20.049126, 22.912131, 23.356999, 50.665506], [10.547964, 10.746950, 10.856423, 13.797314, 108.186291], [7.899955, 8.050039, 8.354181, 9.774381, 78.175344]]
input_correlations: [[0.823030, -0.484659, 0.718860, 0.107758, -0.798431, -0.305014, 0.229345, -0.300248], [0.701761, 0.588082, 0.350295, -0.339713, -0.211506, 0.601989, 0.804856, 0.209051], [-0.196545, -0.552720, -0.220785, 0.435149, -0.652158, -0.246284, -0.753216, -0.406883], [-0.298908, 0.870965, -0.447134, -0.339313, 0.672589, 0.659283, 0.386513, 0.428542], [-0.373264, 0.737929, -0.369171, -0.313095, 0.809268, 0.505461, 0.332191, 0.472821], [-0.599944, 0.633419, -0.488617, -0.063913, 0.895523, 0.331332, 0.128207, 0.457701], [0.744623, 0.080785, 0.562796, 0.374868, -0.155352, -0.117314, 0.798827, 0.242348], [-0.775459, -0.395940, -0.388535, 0.314036, 0.481719, -0.540696, -0.690343, -0.051173]]
pre_activation_mean: [0.375161, 2.112456, -1.185829, 2.266902, 1.658136, 0.562950, 1.202070, -0.868615]
pre_activation_std: [1.655707, 1.375781, 0.980781, 2.141028, 1.357002, 1.243207, 0.672466, 0.486950]
### 4
mean: [-3.455760, 0.507580, -0.191249, -0.372948, 3.602501, -0.102726, 0.415929, 1.014401]
std: [1.773817, 0.468028, 1.654438, 0.247841, 3.184598, 2.050028, 0.810131, 0.609127]
fourier: [[27.073611, 30.691889, 31.033255, 36.142070, 311.018411], [7.567376, 7.635960, 8.904859, 9.823565, 45.682178], [25.941789, 25.983087, 29.408341, 30.224534, 30.410418], [3.958440, 4.124156, 4.321612, 4.678396, 33.565310], [57.455394, 59.423398, 61.423709, 63.304613, 324.225103], [32.020071, 32.876907, 36.057048, 36.268516, 37.509236], [12.733574, 13.990644, 14.931954, 18.643403, 37.433614], [9.523795, 10.762530, 11.983655, 12.301504, 91.296131]]
input_correlations: [[-0.742988, -0.931283, 0.131414, -0.072936, 0.041309, 0.205913, -0.745879, -0.146306], [-0.625244, 0.194640, -0.253437, 0.944117, 0.941572, 0.825265, -0.411188, 0.238953], [0.788512, 0.090537, -0.028717, -0.882022, -0.912861, -0.909722, 0.426593, -0.225205], [-0.673804, -0.544164, 0.142769, -0.142154, -0.162522, -0.153750, -0.321084, -0.414801], [-0.513891, 0.323521, -0.048365, 0.992344, 0.987173, 0.902139, -0.123898, 0.306823], [0.795384, 0.121691, -0.010564, -0.867488, -0.909471, -0.907501, 0.463058, -0.227331], [-0.615010, 0.312714, -0.233030, 0.949325, 0.901380, 0.739611, -0.366909, 0.171170], [0.951421, 0.586353, 0.158263, -0.287860, -0.308990, -0.294437, 0.854605, 0.217900]]
pre_activation_mean: [-3.455760, 0.507580, -0.191249, -0.372948, 3.602501, -0.102726, 0.415929, 1.014401]
pre_activation_std: [1.773817, 0.468028, 1.654438, 0.247841, 3.184598, 2.050028, 0.810131, 0.609127]
### 6
mean: [-0.463046, 0.859226, -0.741920, 2.470847, 1.263940, -0.535445, -0.240875, 1.770252]
std: [1.377375, 1.020751, 1.005438, 2.194887, 1.945770, 1.826722, 2.047264, 1.427204]
fourier: [[22.169658, 22.998720, 24.795628, 26.868941, 41.674158], [18.135725, 19.093607, 19.553473, 21.175168, 77.330373], [16.132772, 16.976623, 18.039894, 21.114821, 66.772776], [38.723578, 40.648072, 40.702630, 41.788841, 222.376241], [32.330340, 32.879048, 33.242056, 36.147514, 113.754636], [29.300737, 29.562988, 33.299009, 35.609049, 48.190081], [31.384870, 32.741938, 32.991798, 37.782665, 38.821979], [25.640859, 27.400710, 27.585246, 27.940258, 159.322724]]
input_correlations: [[0.118125, -0.934381, 0.799124, 0.069806, -0.922120, 0.822740, -0.909006, 0.637762], [0.136753, 0.932651, -0.294082, -0.431511, 0.967432, -0.330981, 0.938286, -0.106307], [-0.266841, 0.766958, -0.955732, 0.140596, 0.715954, -0.969660, 0.717216, -0.866167], [-0.016902, 0.947743, -0.614135, -0.191562, 0.989130, -0.636255, 0.927844, -0.383099], [-0.119755, 0.936676, -0.755316, -0.095636, 0.947733, -0.777446, 0.899143, -0.565122], [0.127332, -0.913057, 0.834915, 0.028567, -0.897598, 0.854658, -0.890644, 0.670351], [0.156028, -0.912717, 0.838298, 0.029305, -0.894410, 0.859719, -0.879564, 0.683047], [0.068093, 0.936919, -0.461609, -0.289036, 0.994178, -0.487706, 0.931065, -0.219041]]
pre_activation_mean: [-0.463046, 0.859226, -0.741920, 2.470847, 1.263940, -0.535445, -0.240875, 1.770252]
pre_activation_std: [1.377375, 1.020751, 1.005438, 2.194887, 1.945770, 1.826722, 2.047264, 1.427204]
### 8
mean: [3.369457, 0.285263, 0.054639, -1.293020, -1.530804, -0.931065, 0.713212, 2.019689]
std: [3.709793, 1.576628, 1.034559, 3.076511, 2.296573, 2.743246, 1.813902, 2.557483]
fourier: [[65.399329, 67.389737, 68.744311, 73.666830, 303.251126], [24.760315, 25.673673, 26.716709, 28.619151, 29.150857], [15.484623, 17.636366, 19.239747, 19.588746, 21.990482], [49.074363, 51.460904, 52.826290, 59.053955, 116.371799], [37.537137, 38.385249, 39.474988, 44.691123, 137.772384], [43.815301, 45.548329, 47.939713, 51.503765, 83.795835], [29.040256, 29.984707, 31.836245, 33.948550, 64.189096], [41.911808, 43.674473, 44.595965, 50.159586, 181.771968]]
input_correlations: [[-0.547375, 0.936183, 0.820505, 0.998856, 0.988606, -0.542682, -0.610890, 0.987198], [-0.822330, 0.747310, 0.587580, 0.919248, 0.895422, -0.818878, -0.864912, 0.855391], [0.972935, -0.403150, -0.188473, -0.681818, -0.611526, 0.972177, 0.978234, -0.584332], [0.749960, -0.819130, -0.664841, -0.960741, -0.937581, 0.746107, 0.799535, -0.913441], [0.706917, -0.851475, -0.706048, -0.976321, -0.955983, 0.702457, 0.760324, -0.937048], [0.766089, -0.806644, -0.650067, -0.953894, -0.927553, 0.762562, 0.813013, -0.904158], [-0.762687, 0.811613, 0.655394, 0.954542, 0.927514, -0.759458, -0.809437, 0.905875], [-0.675694, 0.870340, 0.732471, 0.984474, 0.967913, -0.671061, -0.731958, 0.950101]]
pre_activation_mean: [3.369457, 0.285263, 0.054639, -1.293020, -1.530804, -0.931065, 0.713212, 2.019689]
pre_activation_std: [3.709793, 1.576628, 1.034559, 3.076511, 2.296573, 2.743246, 1.813902, 2.557483]
### 10
mean: [-1.898457]
std: [4.149106]
fourier: [[67.470510, 68.750601, 71.163332, 78.570392, 170.861150]]
input_correlations: [[-0.953721, -0.913242, 0.723797, 0.743376, 0.655572, 0.750443, -0.928832, -0.956728]]
pre_activation_mean: [-1.898457]
pre_activation_std: [4.149106]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.414919
]
}
## Activation Signature
### 0
mean: [3.452148, 0.696952, 0.272375, 0.656031, 0.258257, 0.654360, 1.057184, 2.211468]
std: [3.610657, 0.962136, 0.864056, 1.286045, 0.676390, 1.273276, 1.325389, 2.297711]
fourier: [[63.810766, 66.392638, 66.625940, 73.251151, 310.693334], [16.228110, 18.223725, 18.825661, 18.978053, 62.725697], [15.714635, 16.274744, 17.422098, 17.625938, 24.513782], [23.017966, 23.577910, 24.316248, 28.648840, 59.042797], [12.294740, 12.308140, 13.714543, 13.925877, 23.243158], [22.882684, 23.295753, 23.526231, 28.597938, 58.892408], [23.333904, 23.971707, 24.856933, 27.566420, 95.146510], [37.973947, 41.833880, 42.237988, 48.385216, 199.032070]]
input_correlations: [[-0.125929, 0.155428, 0.679668, -0.341914, -0.420179, 0.000000, 0.000000, 0.000000], [0.739143, 0.627776, 0.496365, 0.222310, 0.617766, 0.000000, 0.000000, 0.000000], [-0.317620, -0.436136, 0.291552, -0.358370, -0.670645, 0.000000, 0.000000, 0.000000], [-0.786387, -0.031701, -0.478284, 0.216438, -0.649082, 0.000000, 0.000000, 0.000000], [0.044228, -0.290254, -0.068722, 0.607256, 0.677167, 0.000000, 0.000000, 0.000000], [0.706319, 0.505590, 0.223358, -0.438441, 0.313187, 0.000000, 0.000000, 0.000000], [0.200705, 0.291226, 0.966635, 0.234850, 0.282021, 0.000000, 0.000000, 0.000000], [0.078625, -0.522784, -0.146667, -0.774417, 0.413169, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.846067, 1.041275, 0.032750, -1.170650, 0.759925, 0.567652, 1.984452, -1.475212]
pre_activation_std: [0.990239, 1.024945, 1.051430, 2.248228, 1.584272, 1.723928, 1.081133, 0.966469]
### 2
mean: [0.375161, 2.112456, -1.185829, 2.266902, 1.658136, 0.562950, 1.202070, -0.868615]
std: [1.655707, 1.375781, 0.980781, 2.141028, 1.357002, 1.243207, 0.672466, 0.486950]
fourier: [[27.326228, 27.689236, 28.120585, 32.023345, 33.764470], [20.672503, 21.751596, 23.559633, 30.740962, 190.120996], [15.946459, 16.286606, 17.915296, 18.151825, 106.724633], [39.395349, 40.067038, 42.056675, 43.878392, 204.021227], [23.549632, 24.280076, 24.796080, 27.024951, 149.232233], [18.466101, 20.049126, 22.912131, 23.356999, 50.665506], [10.547964, 10.746950, 10.856423, 13.797314, 108.186291], [7.899955, 8.050039, 8.354181, 9.774381, 78.175344]]
input_correlations: [[0.823030, -0.484659, 0.718860, 0.107758, -0.798431, -0.305014, 0.229345, -0.300248], [0.701761, 0.588082, 0.350295, -0.339713, -0.211506, 0.601989, 0.804856, 0.209051], [-0.196545, -0.552720, -0.220785, 0.435149, -0.652158, -0.246284, -0.753216, -0.406883], [-0.298908, 0.870965, -0.447134, -0.339313, 0.672589, 0.659283, 0.386513, 0.428542], [-0.373264, 0.737929, -0.369171, -0.313095, 0.809268, 0.505461, 0.332191, 0.472821], [-0.599944, 0.633419, -0.488617, -0.063913, 0.895523, 0.331332, 0.128207, 0.457701], [0.744623, 0.080785, 0.562796, 0.374868, -0.155352, -0.117314, 0.798827, 0.242348], [-0.775459, -0.395940, -0.388535, 0.314036, 0.481719, -0.540696, -0.690343, -0.051173]]
pre_activation_mean: [0.375161, 2.112456, -1.185829, 2.266902, 1.658136, 0.562950, 1.202070, -0.868615]
pre_activation_std: [1.655707, 1.375781, 0.980781, 2.141028, 1.357002, 1.243207, 0.672466, 0.486950]
### 4
mean: [-3.455760, 0.507580, -0.191249, -0.372948, 3.602501, -0.102726, 0.415929, 1.014401]
std: [1.773817, 0.468028, 1.654438, 0.247841, 3.184598, 2.050028, 0.810131, 0.609127]
fourier: [[27.073611, 30.691889, 31.033255, 36.142070, 311.018411], [7.567376, 7.635960, 8.904859, 9.823565, 45.682178], [25.941789, 25.983087, 29.408341, 30.224534, 30.410418], [3.958440, 4.124156, 4.321612, 4.678396, 33.565310], [57.455394, 59.423398, 61.423709, 63.304613, 324.225103], [32.020071, 32.876907, 36.057048, 36.268516, 37.509236], [12.733574, 13.990644, 14.931954, 18.643403, 37.433614], [9.523795, 10.762530, 11.983655, 12.301504, 91.296131]]
input_correlations: [[-0.742988, -0.931283, 0.131414, -0.072936, 0.041309, 0.205913, -0.745879, -0.146306], [-0.625244, 0.194640, -0.253437, 0.944117, 0.941572, 0.825265, -0.411188, 0.238953], [0.788512, 0.090537, -0.028717, -0.882022, -0.912861, -0.909722, 0.426593, -0.225205], [-0.673804, -0.544164, 0.142769, -0.142154, -0.162522, -0.153750, -0.321084, -0.414801], [-0.513891, 0.323521, -0.048365, 0.992344, 0.987173, 0.902139, -0.123898, 0.306823], [0.795384, 0.121691, -0.010564, -0.867488, -0.909471, -0.907501, 0.463058, -0.227331], [-0.615010, 0.312714, -0.233030, 0.949325, 0.901380, 0.739611, -0.366909, 0.171170], [0.951421, 0.586353, 0.158263, -0.287860, -0.308990, -0.294437, 0.854605, 0.217900]]
pre_activation_mean: [-3.455760, 0.507580, -0.191249, -0.372948, 3.602501, -0.102726, 0.415929, 1.014401]
pre_activation_std: [1.773817, 0.468028, 1.654438, 0.247841, 3.184598, 2.050028, 0.810131, 0.609127]
### 6
mean: [-0.463046, 0.859226, -0.741920, 2.470847, 1.263940, -0.535445, -0.240875, 1.770252]
std: [1.377375, 1.020751, 1.005438, 2.194887, 1.945770, 1.826722, 2.047264, 1.427204]
fourier: [[22.169658, 22.998720, 24.795628, 26.868941, 41.674158], [18.135725, 19.093607, 19.553473, 21.175168, 77.330373], [16.132772, 16.976623, 18.039894, 21.114821, 66.772776], [38.723578, 40.648072, 40.702630, 41.788841, 222.376241], [32.330340, 32.879048, 33.242056, 36.147514, 113.754636], [29.300737, 29.562988, 33.299009, 35.609049, 48.190081], [31.384870, 32.741938, 32.991798, 37.782665, 38.821979], [25.640859, 27.400710, 27.585246, 27.940258, 159.322724]]
input_correlations: [[0.118125, -0.934381, 0.799124, 0.069806, -0.922120, 0.822740, -0.909006, 0.637762], [0.136753, 0.932651, -0.294082, -0.431511, 0.967432, -0.330981, 0.938286, -0.106307], [-0.266841, 0.766958, -0.955732, 0.140596, 0.715954, -0.969660, 0.717216, -0.866167], [-0.016902, 0.947743, -0.614135, -0.191562, 0.989130, -0.636255, 0.927844, -0.383099], [-0.119755, 0.936676, -0.755316, -0.095636, 0.947733, -0.777446, 0.899143, -0.565122], [0.127332, -0.913057, 0.834915, 0.028567, -0.897598, 0.854658, -0.890644, 0.670351], [0.156028, -0.912717, 0.838298, 0.029305, -0.894410, 0.859719, -0.879564, 0.683047], [0.068093, 0.936919, -0.461609, -0.289036, 0.994178, -0.487706, 0.931065, -0.219041]]
pre_activation_mean: [-0.463046, 0.859226, -0.741920, 2.470847, 1.263940, -0.535445, -0.240875, 1.770252]
pre_activation_std: [1.377375, 1.020751, 1.005438, 2.194887, 1.945770, 1.826722, 2.047264, 1.427204]
### 8
mean: [3.369457, 0.285263, 0.054639, -1.293020, -1.530804, -0.931065, 0.713212, 2.019689]
std: [3.709793, 1.576628, 1.034559, 3.076511, 2.296573, 2.743246, 1.813902, 2.557483]
fourier: [[65.399329, 67.389737, 68.744311, 73.666830, 303.251126], [24.760315, 25.673673, 26.716709, 28.619151, 29.150857], [15.484623, 17.636366, 19.239747, 19.588746, 21.990482], [49.074363, 51.460904, 52.826290, 59.053955, 116.371799], [37.537137, 38.385249, 39.474988, 44.691123, 137.772384], [43.815301, 45.548329, 47.939713, 51.503765, 83.795835], [29.040256, 29.984707, 31.836245, 33.948550, 64.189096], [41.911808, 43.674473, 44.595965, 50.159586, 181.771968]]
input_correlations: [[-0.547375, 0.936183, 0.820505, 0.998856, 0.988606, -0.542682, -0.610890, 0.987198], [-0.822330, 0.747310, 0.587580, 0.919248, 0.895422, -0.818878, -0.864912, 0.855391], [0.972935, -0.403150, -0.188473, -0.681818, -0.611526, 0.972177, 0.978234, -0.584332], [0.749960, -0.819130, -0.664841, -0.960741, -0.937581, 0.746107, 0.799535, -0.913441], [0.706917, -0.851475, -0.706048, -0.976321, -0.955983, 0.702457, 0.760324, -0.937048], [0.766089, -0.806644, -0.650067, -0.953894, -0.927553, 0.762562, 0.813013, -0.904158], [-0.762687, 0.811613, 0.655394, 0.954542, 0.927514, -0.759458, -0.809437, 0.905875], [-0.675694, 0.870340, 0.732471, 0.984474, 0.967913, -0.671061, -0.731958, 0.950101]]
pre_activation_mean: [3.369457, 0.285263, 0.054639, -1.293020, -1.530804, -0.931065, 0.713212, 2.019689]
pre_activation_std: [3.709793, 1.576628, 1.034559, 3.076511, 2.296573, 2.743246, 1.813902, 2.557483]
### 10
mean: [-1.898457]
std: [4.149106]
fourier: [[67.470510, 68.750601, 71.163332, 78.570392, 170.861150]]
input_correlations: [[-0.953721, -0.913242, 0.723797, 0.743376, 0.655572, 0.750443, -0.928832, -0.956728]]
pre_activation_mean: [-1.898457]
pre_activation_std: [4.149106]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 3.4521477222442627, "std": 3.610657215118408, "fourier": [63.81076604623633, 66.39263820067083, 66.62593951741437, 73.25115102919804, 310.69333419948816], "input_correlations": [-0.12592949356421884, 0.15542769524354025, 0.6796679760711377, -0.34191422930201965, -0.4201789534063379, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8460667729377747, "pre_activation_std": 0.9902387857437134}, "1": {"mean": 0.696952223777771, "std": 0.9621357321739197, "fourier": [16.22810993085231, 18.223725207155745, 18.82566050151828, 18.978052920316532, 62.72569742699852], "input_correlations": [0.7391430023501288, 0.6277762943102129, 0.4963650963821177, 0.22231035461312598, 0.6177662604718588, 0.0, 0.0, 0.0], "pre_activation_mean": 1.0412747859954834, "pre_activation_std": 1.0249452590942383}, "2": {"mean": 0.2723753750324249, "std": 0.8640556931495667, "fourier": [15.714634814873971, 16.27474427699912, 17.422098474907067, 17.625937700210354, 24.51378161017783], "input_correlations": [-0.31762043324468114, -0.43613633032003163, 0.2915516788382185, -0.358370406638559, -0.6706451972046857, 0.0, 0.0, 0.0], "pre_activation_mean": 0.03274967521429062, "pre_activation_std": 1.051430106163025}, "3": {"mean": 0.65603107213974, "std": 1.2860454320907593, "fourier": [23.017965547777486, 23.577910340447826, 24.316248346644233, 28.648840034519615, 59.042797369011396], "input_correlations": [-0.786387052780633, -0.03170054668238796, -0.47828424637913275, 0.21643836341136485, -0.6490822478433917, 0.0, 0.0, 0.0], "pre_activation_mean": -1.170649766921997, "pre_activation_std": 2.2482283115386963}, "4": {"mean": 0.25825729966163635, "std": 0.6763904690742493, "fourier": [12.294740220053244, 12.308140039729649, 13.71454257634765, 13.925876516486724, 23.24315761058358], "input_correlations": [0.044228328853121925, -0.2902541293015117, -0.06872225663785982, 0.6072563726467731, 0.6771672970267211, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7599254846572876, "pre_activation_std": 1.5842723846435547}, "5": {"mean": 0.6543601155281067, "std": 1.2732757329940796, "fourier": [22.88268351209597, 23.295753342469816, 23.52623084907695, 28.597938421134685, 58.89240817536188], "input_correlations": [0.7063191719136511, 0.5055902742054441, 0.2233579109551614, -0.4384414882526473, 0.31318719061950456, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5676521062850952, "pre_activation_std": 1.7239279747009277}, "6": {"mean": 1.0571835041046143, "std": 1.325388789176941, "fourier": [23.33390403495374, 23.971706531426115, 24.8569325877477, 27.566419564769284, 95.14651047228836], "input_correlations": [0.20070535751367605, 0.2912263786750962, 0.966635416779089, 0.23484980425859067, 0.28202074728445486, 0.0, 0.0, 0.0], "pre_activation_mean": 1.9844521284103394, "pre_activation_std": 1.0811330080032349}, "7": {"mean": 2.2114675045013428, "std": 2.29771089553833, "fourier": [37.97394651897985, 41.8338795535245, 42.23798785551617, 48.38521633360355, 199.03207005327567], "input_correlations": [0.07862530641815388, -0.5227835638853073, -0.14666677185604596, -0.7744169588663731, 0.41316904556176465, 0.0, 0.0, 0.0], "pre_activation_mean": -1.4752120971679688, "pre_activation_std": 0.9664692878723145}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.37516072392463684, "std": 1.6557073593139648, "fourier": [27.326227875423378, 27.68923599274847, 28.120585358967954, 32.02334463551899, 33.76446993649006], "input_correlations": [0.8230302154760433, -0.48465928667759955, 0.7188603377535175, 0.10775767084750451, -0.7984312587237757, -0.3050139736869425, 0.22934534987591715, -0.30024776110072693], "pre_activation_mean": 0.37516072392463684, "pre_activation_std": 1.6557073593139648}, "1": {"mean": 2.1124556064605713, "std": 1.3757809400558472, "fourier": [20.672503245479003, 21.751596032180704, 23.55963297272559, 30.7409621994585, 190.12099634110928], "input_correlations": [0.7017609241653439, 0.5880818467617454, 0.3502946825531143, -0.33971258659304265, -0.21150571109052974, 0.601988656231672, 0.8048562942892648, 0.20905076878456402], "pre_activation_mean": 2.1124556064605713, "pre_activation_std": 1.3757809400558472}, "2": {"mean": -1.1858292818069458, "std": 0.9807813167572021, "fourier": [15.94645929903084, 16.286606258235352, 17.915296150720504, 18.151824904848425, 106.72463276982307], "input_correlations": [-0.19654505213265178, -0.5527195032550476, -0.22078453900850545, 0.4351492587270986, -0.652157982655125, -0.2462838584184491, -0.7532162646460934, -0.40688309129475436], "pre_activation_mean": -1.1858292818069458, "pre_activation_std": 0.9807813167572021}, "3": {"mean": 2.266902446746826, "std": 2.1410279273986816, "fourier": [39.39534875422739, 40.06703768578094, 42.05667457083549, 43.878391646832014, 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-0.26654, 0.39781, -0.228915, 0.25206], [0.658305, 0.35324, 0.47452, 0.280706, 0.259796, -0.040305, 0.270928, -0.049744], [0.292628, -0.03363, -0.245003, 0.098328, 0.140462, -0.264531, -0.114499, -0.530465], [0.047278, -0.360589, -0.449061, -0.247669, 0.735699, -0.26142, -0.500371, 0.402762], [-0.141763, -0.189296, -0.106003, -0.015522, 0.595724, -0.53141, -0.603957, -0.173202], [0.00237, -0.447487, 0.660763, -0.173058, -0.221663, 0.383792, -0.425251, -0.019548], [0.090281, -0.556282, 0.33058, -0.381255, -0.327164, 0.608368, -0.06113, 0.222296], [0.306465, -0.167538, 0.140743, -0.047258, 0.478729, -0.341167, -0.163943, 0.46922]], "network.6.bias": [0.043422, -0.420097, -0.408671, 0.225036, 0.042518, 0.079862, 0.394952, -0.031671], "network.8.weight": [[-0.174676, 0.626874, 0.109431, 0.664309, 0.387238, -0.197233, -0.136711, 0.52526], [-0.493835, 0.22141, 0.352095, 0.074778, 0.357983, -0.444129, -0.153446, -0.020611], [0.331161, 0.284355, 0.107689, -0.293644, 0.405095, 0.434836, 0.20392, -0.368305], [0.293932, -0.470804, 0.178336, -0.154452, -0.453952, 0.700177, 0.471441, -0.475734], [0.319909, -0.327841, -0.327583, -0.360041, -0.18369, 0.030609, 0.53065, -0.219328], [0.601569, -0.443403, -0.453839, -0.286918, -0.209088, 0.622843, 0.309002, -0.319278], [-0.321769, 0.465145, 0.543033, 0.343401, -0.032412, -0.27979, -0.366531, 0.026434], [-0.317496, 0.198902, 0.152353, 0.284804, 0.444358, -0.283713, -0.264478, 0.368666]], "network.8.bias": [0.003478, -0.143922, 0.182968, 0.26884, -0.192484, 0.347592, -0.04523, 0.262674], "network.10.weight": [[-0.402819, -0.17968, 0.232832, 0.326944, 0.329061, 0.492412, -0.309004, -0.522723]], "network.10.bias": [0.414919]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7332117557525635, "train_acc": 0.445, "val_loss": 0.7148089408874512, "val_acc": 0.42}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.7011188268661499, "train_acc": 0.445, "val_loss": 0.6657896637916565, "val_acc": 0.7}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6256234347820282, "train_acc": 0.755, "val_loss": 0.42901474237442017, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.42261677980422974, "train_acc": 0.84, "val_loss": 0.1865662783384323, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.3221394121646881, "train_acc": 0.88, "val_loss": 0.1391836404800415, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.27373775839805603, "train_acc": 0.885, "val_loss": 0.13755105435848236, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.22956719994544983, "train_acc": 0.895, "val_loss": 0.17413753271102905, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.24387875199317932, "train_acc": 0.9, "val_loss": 0.2398754060268402, "val_acc": 0.86}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.21832117438316345, "train_acc": 0.895, "val_loss": 0.10529384762048721, "val_acc": 0.98}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.21948383003473282, "train_acc": 0.91, "val_loss": 0.09658505767583847, "val_acc": 0.98}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.21057282388210297, "train_acc": 0.915, "val_loss": 0.09986593574285507, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.17155804485082626, "train_acc": 0.915, "val_loss": 0.08825291693210602, "val_acc": 0.96}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7148089408874512, "final_val_loss": 0.6657896637916565, "initial_val_acc": 0.42, "final_val_acc": 0.7, "best_val_acc": 0.7}, "improved_stage": {"initial_val_loss": 0.42901474237442017, "final_val_loss": 0.08825291693210602, "initial_val_acc": 0.82, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 8}, "improvement": 0.28, "first_improvement_epoch": 1}} |
40 | {"target_pattern": "ends_with", "degraded_accuracy": 0.58, "improved_accuracy": 0.96, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2336, "learning_rate": 0.027281424600688553, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [0.799474, 0.189736, 1.813702, -0.010333, 0.668900, 1.396310]
std: [0.914411, 0.537935, 1.685829, 0.298927, 1.048405, 1.364180]
fourier: [[13.870397, 15.724672, 16.833527, 19.854438, 71.952669], [8.343954, 8.713946, 8.997921, 9.883892, 17.076234], [26.137356, 29.298714, 30.248937, 32.841468, 163.233191], [4.401080, 4.640915, 4.889666, 5.420456, 6.039230], [16.678604, 17.012576, 17.525394, 18.872706, 60.201027], [21.162814, 23.845235, 24.223515, 26.921086, 125.667874]]
input_correlations: [[0.394385, 0.590819, 0.575170, 0.670998, -0.104283, 0.000000, 0.000000, 0.000000], [-0.775108, -0.370610, -0.411970, -0.559114, -0.315523, 0.000000, 0.000000, 0.000000], [-0.920499, -0.318114, -0.088497, 0.045752, 0.181662, 0.000000, 0.000000, 0.000000], [-0.902558, -0.425269, -0.447319, 0.011235, 0.178946, 0.000000, 0.000000, 0.000000], [-0.376648, 0.043097, -0.093105, 0.433252, 0.777931, 0.000000, 0.000000, 0.000000], [-0.584067, -0.180334, 0.089818, 0.405694, 0.629746, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.431453, -1.245402, 0.102630, -1.595540, 0.523378, 0.864388]
pre_activation_std: [1.509019, 1.029794, 1.389702, 1.932483, 1.333069, 2.199702]
### 2
mean: [0.410695, -0.928581, 0.117746, -0.929911, 1.297765, 3.036550]
std: [1.477272, 1.064651, 0.989696, 0.291352, 0.602945, 2.062234]
fourier: [[22.682566, 24.417055, 25.162903, 28.967803, 36.962572], [17.571807, 18.429177, 18.568131, 19.271725, 83.572261], [14.518642, 14.649496, 16.251005, 17.971865, 19.642357], [4.166016, 4.303318, 4.941380, 4.966417, 83.691967], [10.130047, 10.214385, 10.543218, 10.587520, 116.798813], [32.825345, 34.231835, 37.293017, 38.199310, 273.289445]]
input_correlations: [[0.672521, 0.231151, -0.834679, -0.604361, -0.707775, -0.700914, 0.000000, 0.000000], [-0.240109, 0.051702, -0.563916, -0.722994, -0.930388, -0.930628, 0.000000, 0.000000], [0.646578, 0.247865, -0.852918, -0.690766, -0.748124, -0.716520, 0.000000, 0.000000], [-0.911998, 0.010615, -0.045337, 0.029682, -0.193196, -0.386619, 0.000000, 0.000000], [0.959796, 0.076061, -0.298582, -0.037663, 0.060895, 0.123070, 0.000000, 0.000000], [0.239694, -0.173960, 0.715257, 0.645258, 0.900266, 0.974193, 0.000000, 0.000000]]
pre_activation_mean: [0.410695, -0.928581, 0.117746, -0.929911, 1.297765, 3.036550]
pre_activation_std: [1.477272, 1.064651, 0.989696, 0.291352, 0.602945, 2.062234]
### 4
mean: [-0.316708, 0.075451, 2.180555, 0.840431, 0.622023, -1.177568]
std: [0.881179, 0.527891, 1.725584, 1.120708, 0.673357, 0.631241]
fourier: [[13.610059, 13.926387, 15.356953, 16.231191, 28.503747], [7.459359, 8.155965, 8.490013, 8.542574, 9.069551], [27.891195, 28.310111, 31.815384, 32.098321, 196.250000], [16.792479, 20.245163, 21.109183, 21.273927, 75.638817], [10.303424, 10.356548, 12.345167, 12.464141, 55.982074], [9.741210, 10.694253, 11.480975, 13.562383, 105.981116]]
input_correlations: [[0.658765, -0.237501, 0.639510, -0.162617, 0.174198, -0.828917, 0.000000, 0.000000], [0.882286, -0.380255, 0.866658, 0.072834, 0.489905, -0.580800, 0.000000, 0.000000], [-0.520057, 0.139803, -0.501299, 0.239909, -0.031529, 0.913857, 0.000000, 0.000000], [0.988917, -0.550478, 0.984548, 0.427791, 0.875575, -0.045686, 0.000000, 0.000000], [0.970946, -0.502232, 0.964438, 0.330387, 0.774732, -0.290284, 0.000000, 0.000000], [-0.887938, 0.597797, -0.885934, -0.510411, -0.923370, -0.328268, 0.000000, 0.000000]]
pre_activation_mean: [-0.316708, 0.075451, 2.180555, 0.840431, 0.622023, -1.177568]
pre_activation_std: [0.881179, 0.527891, 1.725584, 1.120708, 0.673357, 0.631241]
### 6
mean: [0.669454, -0.081062, 1.625507, -0.408117, 0.609179, 1.265120]
std: [1.238703, 0.893021, 2.023866, 0.648473, 1.173530, 1.647988]
fourier: [[18.947130, 19.337344, 20.291050, 21.800585, 60.250827], [13.214222, 13.320128, 13.462476, 14.464544, 15.652928], [29.460165, 32.359297, 34.330091, 36.038928, 146.295650], [9.622859, 9.839082, 10.744466, 10.767474, 36.730542], [17.829619, 17.891212, 19.841707, 20.875664, 54.826082], [23.800134, 26.382718, 27.747606, 29.293427, 113.860780]]
input_correlations: [[-0.762425, -0.907198, 0.854642, -0.840817, -0.906711, -0.667157, 0.000000, 0.000000], [0.772990, 0.906468, -0.871785, 0.821173, 0.890877, 0.657712, 0.000000, 0.000000], [-0.745600, -0.850087, 0.945215, -0.700175, -0.791343, -0.567398, 0.000000, 0.000000], [0.855091, 0.912026, -0.895040, 0.724549, 0.809197, 0.578659, 0.000000, 0.000000], [0.815835, 0.959428, -0.690699, 0.950493, 0.983643, 0.751849, 0.000000, 0.000000], [-0.749524, -0.855920, 0.940949, -0.709566, -0.799269, -0.575552, 0.000000, 0.000000]]
pre_activation_mean: [0.669454, -0.081062, 1.625507, -0.408117, 0.609179, 1.265120]
pre_activation_std: [1.238703, 0.893021, 2.023866, 0.648473, 1.173530, 1.647988]
### 8
mean: [-1.896689]
std: [2.759014]
fourier: [[40.276839, 46.869608, 47.905864, 52.283519, 170.702009]]
input_correlations: [[-0.961149, 0.683709, -0.986409, 0.592608, 0.741879, -0.985106, 0.000000, 0.000000]]
pre_activation_mean: [-1.896689]
pre_activation_std: [2.759014]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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## Activation Signature
### 0
mean: [0.799474, 0.189736, 1.813702, -0.010333, 0.668900, 1.396310]
std: [0.914411, 0.537935, 1.685829, 0.298927, 1.048405, 1.364180]
fourier: [[13.870397, 15.724672, 16.833527, 19.854438, 71.952669], [8.343954, 8.713946, 8.997921, 9.883892, 17.076234], [26.137356, 29.298714, 30.248937, 32.841468, 163.233191], [4.401080, 4.640915, 4.889666, 5.420456, 6.039230], [16.678604, 17.012576, 17.525394, 18.872706, 60.201027], [21.162814, 23.845235, 24.223515, 26.921086, 125.667874]]
input_correlations: [[0.394385, 0.590819, 0.575170, 0.670998, -0.104283, 0.000000, 0.000000, 0.000000], [-0.775108, -0.370610, -0.411970, -0.559114, -0.315523, 0.000000, 0.000000, 0.000000], [-0.920499, -0.318114, -0.088497, 0.045752, 0.181662, 0.000000, 0.000000, 0.000000], [-0.902558, -0.425269, -0.447319, 0.011235, 0.178946, 0.000000, 0.000000, 0.000000], [-0.376648, 0.043097, -0.093105, 0.433252, 0.777931, 0.000000, 0.000000, 0.000000], [-0.584067, -0.180334, 0.089818, 0.405694, 0.629746, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.431453, -1.245402, 0.102630, -1.595540, 0.523378, 0.864388]
pre_activation_std: [1.509019, 1.029794, 1.389702, 1.932483, 1.333069, 2.199702]
### 2
mean: [0.410695, -0.928581, 0.117746, -0.929911, 1.297765, 3.036550]
std: [1.477272, 1.064651, 0.989696, 0.291352, 0.602945, 2.062234]
fourier: [[22.682566, 24.417055, 25.162903, 28.967803, 36.962572], [17.571807, 18.429177, 18.568131, 19.271725, 83.572261], [14.518642, 14.649496, 16.251005, 17.971865, 19.642357], [4.166016, 4.303318, 4.941380, 4.966417, 83.691967], [10.130047, 10.214385, 10.543218, 10.587520, 116.798813], [32.825345, 34.231835, 37.293017, 38.199310, 273.289445]]
input_correlations: [[0.672521, 0.231151, -0.834679, -0.604361, -0.707775, -0.700914, 0.000000, 0.000000], [-0.240109, 0.051702, -0.563916, -0.722994, -0.930388, -0.930628, 0.000000, 0.000000], [0.646578, 0.247865, -0.852918, -0.690766, -0.748124, -0.716520, 0.000000, 0.000000], [-0.911998, 0.010615, -0.045337, 0.029682, -0.193196, -0.386619, 0.000000, 0.000000], [0.959796, 0.076061, -0.298582, -0.037663, 0.060895, 0.123070, 0.000000, 0.000000], [0.239694, -0.173960, 0.715257, 0.645258, 0.900266, 0.974193, 0.000000, 0.000000]]
pre_activation_mean: [0.410695, -0.928581, 0.117746, -0.929911, 1.297765, 3.036550]
pre_activation_std: [1.477272, 1.064651, 0.989696, 0.291352, 0.602945, 2.062234]
### 4
mean: [-0.316708, 0.075451, 2.180555, 0.840431, 0.622023, -1.177568]
std: [0.881179, 0.527891, 1.725584, 1.120708, 0.673357, 0.631241]
fourier: [[13.610059, 13.926387, 15.356953, 16.231191, 28.503747], [7.459359, 8.155965, 8.490013, 8.542574, 9.069551], [27.891195, 28.310111, 31.815384, 32.098321, 196.250000], [16.792479, 20.245163, 21.109183, 21.273927, 75.638817], [10.303424, 10.356548, 12.345167, 12.464141, 55.982074], [9.741210, 10.694253, 11.480975, 13.562383, 105.981116]]
input_correlations: [[0.658765, -0.237501, 0.639510, -0.162617, 0.174198, -0.828917, 0.000000, 0.000000], [0.882286, -0.380255, 0.866658, 0.072834, 0.489905, -0.580800, 0.000000, 0.000000], [-0.520057, 0.139803, -0.501299, 0.239909, -0.031529, 0.913857, 0.000000, 0.000000], [0.988917, -0.550478, 0.984548, 0.427791, 0.875575, -0.045686, 0.000000, 0.000000], [0.970946, -0.502232, 0.964438, 0.330387, 0.774732, -0.290284, 0.000000, 0.000000], [-0.887938, 0.597797, -0.885934, -0.510411, -0.923370, -0.328268, 0.000000, 0.000000]]
pre_activation_mean: [-0.316708, 0.075451, 2.180555, 0.840431, 0.622023, -1.177568]
pre_activation_std: [0.881179, 0.527891, 1.725584, 1.120708, 0.673357, 0.631241]
### 6
mean: [0.669454, -0.081062, 1.625507, -0.408117, 0.609179, 1.265120]
std: [1.238703, 0.893021, 2.023866, 0.648473, 1.173530, 1.647988]
fourier: [[18.947130, 19.337344, 20.291050, 21.800585, 60.250827], [13.214222, 13.320128, 13.462476, 14.464544, 15.652928], [29.460165, 32.359297, 34.330091, 36.038928, 146.295650], [9.622859, 9.839082, 10.744466, 10.767474, 36.730542], [17.829619, 17.891212, 19.841707, 20.875664, 54.826082], [23.800134, 26.382718, 27.747606, 29.293427, 113.860780]]
input_correlations: [[-0.762425, -0.907198, 0.854642, -0.840817, -0.906711, -0.667157, 0.000000, 0.000000], [0.772990, 0.906468, -0.871785, 0.821173, 0.890877, 0.657712, 0.000000, 0.000000], [-0.745600, -0.850087, 0.945215, -0.700175, -0.791343, -0.567398, 0.000000, 0.000000], [0.855091, 0.912026, -0.895040, 0.724549, 0.809197, 0.578659, 0.000000, 0.000000], [0.815835, 0.959428, -0.690699, 0.950493, 0.983643, 0.751849, 0.000000, 0.000000], [-0.749524, -0.855920, 0.940949, -0.709566, -0.799269, -0.575552, 0.000000, 0.000000]]
pre_activation_mean: [0.669454, -0.081062, 1.625507, -0.408117, 0.609179, 1.265120]
pre_activation_std: [1.238703, 0.893021, 2.023866, 0.648473, 1.173530, 1.647988]
### 8
mean: [-1.896689]
std: [2.759014]
fourier: [[40.276839, 46.869608, 47.905864, 52.283519, 170.702009]]
input_correlations: [[-0.961149, 0.683709, -0.986409, 0.592608, 0.741879, -0.985106, 0.000000, 0.000000]]
pre_activation_mean: [-1.896689]
pre_activation_std: [2.759014]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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[0.760369, -0.249357, 0.413842, -0.177043, 0.473134, -0.020396], [0.320041, -0.031453, 0.289956, 0.316364, 0.408324, -0.110593], [-0.568612, 0.76872, -0.066406, 0.06792, -0.06643, -0.122224]], "network.4.bias": [0.303309, 0.072508, 0.464477, -0.390035, 0.187823, -0.230637], "network.6.weight": [[-0.008035, 0.044524, 0.405896, -0.456821, -0.400908, -0.218547], [0.169786, -0.078803, -0.328601, 0.541486, -0.190232, 0.058731], [-0.557002, -0.211143, 0.864272, -0.45078, -0.086588, -0.418136], [0.482875, 0.539951, -0.203327, 0.019932, 0.045938, -0.595425], [0.001833, 0.526364, -0.166477, 0.455212, 0.546015, 0.130502], [-0.324413, -0.405119, 0.690617, -0.387119, -0.009929, -0.405486]], "network.6.bias": [0.376632, 0.278565, 0.230467, -0.194074, 0.226217, 0.155132], "network.8.weight": [[-0.260586, 0.322866, -0.680109, 0.125699, 0.345251, -0.736295]], "network.8.bias": [0.282354]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7025384902954102, "train_acc": 0.435, "val_loss": 0.6880980730056763, "val_acc": 0.58}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6831613183021545, "train_acc": 0.565, "val_loss": 0.6696557402610779, "val_acc": 0.58}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6688477694988251, "train_acc": 0.565, "val_loss": 0.6505634188652039, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6865737736225128, "train_acc": 0.48, "val_loss": 0.6542909145355225, "val_acc": 0.58}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6542292833328247, "train_acc": 0.675, "val_loss": 0.6339176297187805, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.6122893691062927, "train_acc": 0.735, "val_loss": 0.5765601396560669, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.5497055351734161, "train_acc": 0.76, "val_loss": 0.5012914538383484, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.49569591879844666, "train_acc": 0.795, "val_loss": 0.4570293724536896, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4464632123708725, "train_acc": 0.805, "val_loss": 0.4042728543281555, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.38296130299568176, "train_acc": 0.84, "val_loss": 0.2840152680873871, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.35752925276756287, "train_acc": 0.885, "val_loss": 0.22655725479125977, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.3188198208808899, "train_acc": 0.89, "val_loss": 0.17285770177841187, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.2525936886668205, "train_acc": 0.905, "val_loss": 0.26556286215782166, "val_acc": 0.88}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["ends_with"], "degraded_stage": {"initial_val_loss": 0.6880980730056763, "final_val_loss": 0.6505634188652039, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.6542909145355225, "final_val_loss": 0.26556286215782166, "initial_val_acc": 0.58, "final_val_acc": 0.88, "best_val_acc": 0.96, "best_epoch": 10}, "improvement": 0.38, "first_improvement_epoch": 2}} |
41 | {"target_pattern": "palindrome", "degraded_accuracy": 0.56, "improved_accuracy": 0.94, "improvement": 0.3799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7385, "learning_rate": 0.03768603114736421, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.457009,
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[
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[
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[
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"network.0.bias": [
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],
"network.2.weight": [
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0.105032,
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],
[
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[
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[
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],
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],
"network.4.weight": [
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[
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],
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"network.6.weight": [
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}
## Activation Signature
### 0
mean: [0.000000, 1.300035, 1.210784, 0.525562, 0.190642]
std: [0.000000, 0.973538, 0.839731, 0.409757, 0.112289]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [14.782364, 15.431483, 20.424382, 20.668164, 117.003166], [12.775671, 14.041071, 16.493491, 17.356981, 108.970595], [6.248928, 6.672627, 8.397217, 8.592128, 47.300605], [1.646634, 1.752757, 1.862750, 1.954109, 17.157813]]
input_correlations: [[0.595041, 0.159659, 0.315303, 0.323798, 0.859378, 0.000000, 0.000000, 0.000000], [-0.195289, -0.158860, -0.028583, 0.617583, 0.763844, 0.000000, 0.000000, 0.000000], [-0.312922, 0.568901, 0.013361, 0.569673, -0.545468, 0.000000, 0.000000, 0.000000], [0.688835, 0.052503, -0.305573, 0.037212, -0.340626, 0.000000, 0.000000, 0.000000], [-0.668832, -0.608121, -0.760550, -0.184601, -0.498567, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.730714, 1.087185, 0.642833, 0.035478, -1.631512]
pre_activation_std: [1.799819, 1.612979, 1.667485, 1.049736, 1.220720]
### 2
mean: [-1.050911, 1.998527, -1.484252, -0.754237, -1.513909]
std: [0.502593, 1.755870, 1.123470, 1.473486, 0.801943]
fourier: [[7.662698, 7.937275, 8.897130, 10.628021, 94.582024], [27.089635, 28.367717, 36.042457, 36.460273, 179.867451], [17.268520, 19.690797, 21.333417, 22.435861, 133.582641], [23.845071, 24.658020, 27.505535, 32.315583, 67.881309], [11.970038, 13.374064, 13.908284, 17.335883, 136.251829]]
input_correlations: [[-0.636549, -0.206990, -0.290761, -0.619266, 0.434250, 0.000000, 0.000000, 0.000000], [0.950530, 0.879335, -0.278024, 0.050055, -0.310943, 0.000000, 0.000000, 0.000000], [-0.917293, -0.723873, -0.081966, -0.225733, 0.448933, 0.000000, 0.000000, 0.000000], [-0.909576, -0.785151, 0.536639, -0.179921, 0.193915, 0.000000, 0.000000, 0.000000], [-0.815737, -0.453722, -0.169282, -0.485512, 0.454299, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.050911, 1.998527, -1.484252, -0.754237, -1.513909]
pre_activation_std: [0.502593, 1.755870, 1.123470, 1.473486, 0.801943]
### 4
mean: [0.879677, 0.767959, 1.009320, -0.745125, -1.008476]
std: [0.859738, 0.848469, 0.896984, 0.554123, 0.519539]
fourier: [[12.679513, 12.995746, 18.169986, 18.856612, 79.170959], [13.195443, 14.010402, 16.748388, 17.434579, 69.116337], [13.977623, 15.159233, 16.658372, 18.145073, 90.838806], [8.558721, 8.966367, 11.346332, 11.496217, 67.061252], [7.635119, 7.848868, 10.993011, 11.397045, 90.762829]]
input_correlations: [[0.000000, 0.979857, -0.353280, -0.252561, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.996782, -0.287032, -0.511235, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.983550, -0.257771, -0.595596, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999982, 0.306403, 0.446053, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.978813, 0.356762, 0.247586, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.879677, 0.767959, 1.009320, -0.745125, -1.008476]
pre_activation_std: [0.859738, 0.848469, 0.896984, 0.554123, 0.519539]
### 6
mean: [-0.372372, 1.300035, 1.210784, 0.525562, 0.190642]
std: [0.031435, 0.973538, 0.839731, 0.409757, 0.112289]
fourier: [[0.479986, 0.525354, 0.580921, 0.631153, 33.513452], [14.782364, 15.431483, 20.424382, 20.668164, 117.003166], [12.775671, 14.041071, 16.493491, 17.356981, 108.970595], [6.248928, 6.672627, 8.397217, 8.592128, 47.300605], [1.646634, 1.752757, 1.862750, 1.954109, 17.157813]]
input_correlations: [[-0.594221, -0.748968, -0.795612, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.990782, 0.996526, 0.984373, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.950968, 0.994875, 0.999916, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.975046, 0.999891, 0.995784, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.176352, -0.383193, -0.470201, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.372372, 1.300035, 1.210784, 0.525562, 0.190642]
pre_activation_std: [0.031435, 0.973538, 0.839731, 0.409757, 0.112289]
### 8
mean: [-0.731553]
std: [0.791810]
fourier: [[12.074244, 13.080784, 15.918487, 16.452994, 65.839774]]
input_correlations: [[0.000000, -0.991168, -0.998962, -0.998927, 0.431483, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.731553]
pre_activation_std: [0.791810]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.447489,
-0.098636,
0.018849,
0.234771,
0.705511
],
[
-0.146052,
-0.241352,
-0.058783,
0.457009,
0.632593
],
[
-0.332686,
0.46755,
0.124178,
0.370377,
-0.517562
],
[
0.527926,
-0.1492,
-0.256128,
0.123642,
-0.262136
],
[
-0.195081,
-0.253321,
-0.315832,
-0.01125,
-0.2182
]
],
"network.0.bias": [
-0.059383,
0.071298,
-0.210457,
0.243559,
0.025839
],
"network.2.weight": [
[
-0.256541,
0.092051,
-0.25534,
-0.343807,
0.020394
],
[
0.585917,
0.571869,
-0.087793,
0.105032,
-0.09419
],
[
-0.546136,
-0.146493,
-0.350232,
-0.26701,
-0.577259
],
[
-0.334801,
-0.53407,
0.421286,
-0.373187,
-0.238276
],
[
-0.429075,
0.047115,
-0.332672,
-0.414905,
-0.291928
]
],
"network.2.bias": [
-0.325727,
0.310255,
0.1054,
0.232386,
-0.32606
],
"network.4.weight": [
[
-0.361781,
0.5276,
-0.160067,
0.458445,
-0.209499
],
[
-0.179615,
0.462673,
0.02309,
-0.181733,
0.119766
],
[
-0.180594,
0.457121,
-0.020115,
-0.43317,
0.207805
],
[
0.085771,
-0.314725,
-0.065762,
0.00865,
0.161807
],
[
0.00417,
-0.318865,
0.444376,
-0.282966,
0.00196
]
],
"network.4.bias": [
-0.271108,
-0.118446,
0.187058,
-0.117863,
-0.312257
],
"network.6.weight": [
[
0.171528,
-0.35608,
0.145199,
-0.345107,
-0.096482
],
[
0.597343,
0.174057,
0.381462,
0.296078,
0.173969
],
[
-0.131242,
0.416112,
0.702837,
-0.125656,
0.225347
],
[
0.045361,
0.308644,
0.138234,
0.311247,
-0.037803
],
[
0.446681,
-0.234262,
-0.261313,
0.450862,
0.21308
]
],
"network.6.bias": [
-0.39091,
0.240269,
0.269874,
0.097472,
0.252412
],
"network.8.weight": [
[
0.02361,
-0.486806,
-0.347947,
-0.01554,
0.491892
]
],
"network.8.bias": [
0.236992
]
}
## Activation Signature
### 0
mean: [0.000000, 1.300035, 1.210784, 0.525562, 0.190642]
std: [0.000000, 0.973538, 0.839731, 0.409757, 0.112289]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [14.782364, 15.431483, 20.424382, 20.668164, 117.003166], [12.775671, 14.041071, 16.493491, 17.356981, 108.970595], [6.248928, 6.672627, 8.397217, 8.592128, 47.300605], [1.646634, 1.752757, 1.862750, 1.954109, 17.157813]]
input_correlations: [[0.595041, 0.159659, 0.315303, 0.323798, 0.859378, 0.000000, 0.000000, 0.000000], [-0.195289, -0.158860, -0.028583, 0.617583, 0.763844, 0.000000, 0.000000, 0.000000], [-0.312922, 0.568901, 0.013361, 0.569673, -0.545468, 0.000000, 0.000000, 0.000000], [0.688835, 0.052503, -0.305573, 0.037212, -0.340626, 0.000000, 0.000000, 0.000000], [-0.668832, -0.608121, -0.760550, -0.184601, -0.498567, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.730714, 1.087185, 0.642833, 0.035478, -1.631512]
pre_activation_std: [1.799819, 1.612979, 1.667485, 1.049736, 1.220720]
### 2
mean: [-1.050911, 1.998527, -1.484252, -0.754237, -1.513909]
std: [0.502593, 1.755870, 1.123470, 1.473486, 0.801943]
fourier: [[7.662698, 7.937275, 8.897130, 10.628021, 94.582024], [27.089635, 28.367717, 36.042457, 36.460273, 179.867451], [17.268520, 19.690797, 21.333417, 22.435861, 133.582641], [23.845071, 24.658020, 27.505535, 32.315583, 67.881309], [11.970038, 13.374064, 13.908284, 17.335883, 136.251829]]
input_correlations: [[-0.636549, -0.206990, -0.290761, -0.619266, 0.434250, 0.000000, 0.000000, 0.000000], [0.950530, 0.879335, -0.278024, 0.050055, -0.310943, 0.000000, 0.000000, 0.000000], [-0.917293, -0.723873, -0.081966, -0.225733, 0.448933, 0.000000, 0.000000, 0.000000], [-0.909576, -0.785151, 0.536639, -0.179921, 0.193915, 0.000000, 0.000000, 0.000000], [-0.815737, -0.453722, -0.169282, -0.485512, 0.454299, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.050911, 1.998527, -1.484252, -0.754237, -1.513909]
pre_activation_std: [0.502593, 1.755870, 1.123470, 1.473486, 0.801943]
### 4
mean: [0.879677, 0.767959, 1.009320, -0.745125, -1.008476]
std: [0.859738, 0.848469, 0.896984, 0.554123, 0.519539]
fourier: [[12.679513, 12.995746, 18.169986, 18.856612, 79.170959], [13.195443, 14.010402, 16.748388, 17.434579, 69.116337], [13.977623, 15.159233, 16.658372, 18.145073, 90.838806], [8.558721, 8.966367, 11.346332, 11.496217, 67.061252], [7.635119, 7.848868, 10.993011, 11.397045, 90.762829]]
input_correlations: [[0.000000, 0.979857, -0.353280, -0.252561, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.996782, -0.287032, -0.511235, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.983550, -0.257771, -0.595596, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999982, 0.306403, 0.446053, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.978813, 0.356762, 0.247586, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.879677, 0.767959, 1.009320, -0.745125, -1.008476]
pre_activation_std: [0.859738, 0.848469, 0.896984, 0.554123, 0.519539]
### 6
mean: [-0.372372, 1.300035, 1.210784, 0.525562, 0.190642]
std: [0.031435, 0.973538, 0.839731, 0.409757, 0.112289]
fourier: [[0.479986, 0.525354, 0.580921, 0.631153, 33.513452], [14.782364, 15.431483, 20.424382, 20.668164, 117.003166], [12.775671, 14.041071, 16.493491, 17.356981, 108.970595], [6.248928, 6.672627, 8.397217, 8.592128, 47.300605], [1.646634, 1.752757, 1.862750, 1.954109, 17.157813]]
input_correlations: [[-0.594221, -0.748968, -0.795612, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.990782, 0.996526, 0.984373, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.950968, 0.994875, 0.999916, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.975046, 0.999891, 0.995784, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-0.176352, -0.383193, -0.470201, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.372372, 1.300035, 1.210784, 0.525562, 0.190642]
pre_activation_std: [0.031435, 0.973538, 0.839731, 0.409757, 0.112289]
### 8
mean: [-0.731553]
std: [0.791810]
fourier: [[12.074244, 13.080784, 15.918487, 16.452994, 65.839774]]
input_correlations: [[0.000000, -0.991168, -0.998962, -0.998927, 0.431483, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.731553]
pre_activation_std: [0.791810]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.595041374701308, 0.159658766530619, 0.31530313361776297, 0.32379832620012755, 0.8593783632719592, 0.0, 0.0, 0.0], "pre_activation_mean": 1.7307136058807373, "pre_activation_std": 1.7998192310333252}, "1": {"mean": 1.3000352382659912, "std": 0.9735378623008728, "fourier": [14.782364307152804, 15.431483479608152, 20.42438164535181, 20.66816448369586, 117.00316575169563], "input_correlations": [-0.19528877149784338, -0.15885951462878925, -0.028583230081684962, 0.6175829913232905, 0.7638443815449314, 0.0, 0.0, 0.0], "pre_activation_mean": 1.0871849060058594, "pre_activation_std": 1.6129788160324097}, "2": {"mean": 1.2107844352722168, "std": 0.8397305607795715, "fourier": [12.775670857625903, 14.041071485131392, 16.49349056802691, 17.356981025718504, 108.97059480845928], "input_correlations": [-0.3129223041097098, 0.5689010017552052, 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5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -1.0509114265441895, "std": 0.5025925636291504, "fourier": [7.662698137429998, 7.937275138861942, 8.897129712403775, 10.62802080040952, 94.58202350139618], "input_correlations": [-0.6365490499815766, -0.20699026064467155, -0.2907607136415276, -0.6192664466614116, 0.43424968803940645, 0.0, 0.0, 0.0], "pre_activation_mean": -1.0509114265441895, "pre_activation_std": 0.5025925636291504}, "1": {"mean": 1.9985274076461792, "std": 1.755869746208191, "fourier": [27.08963465689686, 28.367717195005216, 36.04245731786727, 36.46027252133861, 179.8674505352974], "input_correlations": [0.9505300931353062, 0.8793348481558593, -0.27802408310454385, 0.0500552656574241, -0.3109433010033056, 0.0, 0.0, 0.0], "pre_activation_mean": 1.9985274076461792, "pre_activation_std": 1.755869746208191}, "2": {"mean": -1.484251618385315, "std": 1.123470425605774, "fourier": [17.268519730973424, 19.69079747650214, 21.333417112827924, 22.435861465511, 133.58264067023993], "input_correlations": [-0.9172934464406494, -0.7238733919755955, -0.08196605299751422, -0.22573291012113847, 0.44893303239870347, 0.0, 0.0, 0.0], "pre_activation_mean": -1.484251618385315, "pre_activation_std": 1.123470425605774}, "3": {"mean": -0.7542367577552795, "std": 1.4734858274459839, "fourier": [23.84507080362777, 24.658020117329286, 27.505535279581657, 32.31558300112885, 67.8813085258007], "input_correlations": [-0.909576034269033, -0.78515055476833, 0.5366389949343972, -0.17992135481846933, 0.19391507449799306, 0.0, 0.0, 0.0], "pre_activation_mean": -0.7542367577552795, "pre_activation_std": 1.4734858274459839}, "4": {"mean": -1.5139092206954956, "std": 0.8019430041313171, "fourier": [11.97003772599641, 13.374063548923234, 13.908284468683194, 17.335882949974057, 136.2518293261528], "input_correlations": [-0.8157373808764348, 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"input_correlations": [0.9907819151815642, 0.9965263135796799, 0.9843731045061376, 0.0, 0.0, 0.0, 0.0, 0.0], "pre_activation_mean": 1.3000352382659912, "pre_activation_std": 0.9735378623008728}, "2": {"mean": 1.2107844352722168, "std": 0.8397305607795715, "fourier": [12.775670857625903, 14.041071485131392, 16.49349056802691, 17.356981025718504, 108.97059480845928], "input_correlations": [0.950967502228, 0.9948752149050254, 0.999915663999504, 0.0, 0.0, 0.0, 0.0, 0.0], "pre_activation_mean": 1.2107844352722168, "pre_activation_std": 0.8397305607795715}, "3": {"mean": 0.5255622863769531, "std": 0.40975651144981384, "fourier": [6.248927798993387, 6.6726269591624465, 8.397216503528433, 8.592128171094588, 47.3006054982543], "input_correlations": [0.9750463070713337, 0.9998910235589978, 0.9957840206045726, 0.0, 0.0, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5255622863769531, "pre_activation_std": 0.40975651144981384}, "4": {"mean": 0.1906423717737198, "std": 0.11228863894939423, "fourier": [1.6466338122357158, 1.7527569701162915, 1.8627496596553146, 1.9541087450815793, 17.157812520861626], "input_correlations": [-0.1763523858167093, -0.3831933890413302, -0.4702013016537067, 0.0, 0.0, 0.0, 0.0, 0.0], "pre_activation_mean": 0.1906423717737198, "pre_activation_std": 0.11228863894939423}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "8": {"neuron_profiles": {"0": {"mean": -0.7315530776977539, "std": 0.7918096780776978, "fourier": [12.074243828264766, 13.080783519362305, 15.918486870644834, 16.45299395890036, 65.83977392315865], "input_correlations": [0.0, -0.9911680159164643, -0.9989617804034223, -0.9989269623778603, 0.4314832696945639, 0.0, 0.0, 0.0], "pre_activation_mean": -0.7315530776977539, "pre_activation_std": 0.7918096780776978}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.447489, -0.098636, 0.018849, 0.234771, 0.705511], [-0.146052, -0.241352, -0.058783, 0.457009, 0.632593], [-0.332686, 0.46755, 0.124178, 0.370377, -0.517562], [0.527926, -0.1492, -0.256128, 0.123642, -0.262136], [-0.195081, -0.253321, -0.315832, -0.01125, -0.2182]], "network.0.bias": [-0.059383, 0.071298, -0.210457, 0.243559, 0.025839], "network.2.weight": [[-0.256541, 0.092051, -0.25534, -0.343807, 0.020394], [0.585917, 0.571869, -0.087793, 0.105032, -0.09419], [-0.546136, -0.146493, -0.350232, -0.26701, -0.577259], [-0.334801, -0.53407, 0.421286, -0.373187, -0.238276], [-0.429075, 0.047115, -0.332672, -0.414905, -0.291928]], "network.2.bias": [-0.325727, 0.310255, 0.1054, 0.232386, -0.32606], "network.4.weight": [[-0.361781, 0.5276, -0.160067, 0.458445, -0.209499], [-0.179615, 0.462673, 0.02309, -0.181733, 0.119766], [-0.180594, 0.457121, -0.020115, -0.43317, 0.207805], [0.085771, -0.314725, -0.065762, 0.00865, 0.161807], [0.00417, -0.318865, 0.444376, -0.282966, 0.00196]], "network.4.bias": [-0.271108, -0.118446, 0.187058, -0.117863, -0.312257], "network.6.weight": [[0.171528, -0.35608, 0.145199, -0.345107, -0.096482], [0.597343, 0.174057, 0.381462, 0.296078, 0.173969], [-0.131242, 0.416112, 0.702837, -0.125656, 0.225347], [0.045361, 0.308644, 0.138234, 0.311247, -0.037803], [0.446681, -0.234262, -0.261313, 0.450862, 0.21308]], "network.6.bias": [-0.39091, 0.240269, 0.269874, 0.097472, 0.252412], "network.8.weight": [[0.02361, -0.486806, -0.347947, -0.01554, 0.491892]], "network.8.bias": [0.236992]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6899383366107941, "train_acc": 0.55, "val_loss": 0.669598400592804, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6703197360038757, "train_acc": 0.55, "val_loss": 0.6223757266998291, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6432418823242188, "train_acc": 0.485, "val_loss": 0.5334099531173706, "val_acc": 0.56}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5502262115478516, "train_acc": 0.59, "val_loss": 0.44887110590934753, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.47276072204113007, "train_acc": 0.85, "val_loss": 0.38439953327178955, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.40367837250232697, "train_acc": 0.845, "val_loss": 0.353424608707428, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.33941276371479034, "train_acc": 0.88, "val_loss": 0.3349512815475464, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.29292409121990204, "train_acc": 0.9, "val_loss": 0.3348585367202759, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.26095326989889145, "train_acc": 0.885, "val_loss": 0.41913673281669617, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.30709271878004074, "train_acc": 0.88, "val_loss": 0.4255562722682953, "val_acc": 0.82}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.27626559138298035, "train_acc": 0.89, "val_loss": 0.32773369550704956, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.2800440341234207, "train_acc": 0.885, "val_loss": 0.37025678157806396, "val_acc": 0.86}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.669598400592804, "final_val_loss": 0.6223757266998291, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.5334099531173706, "final_val_loss": 0.37025678157806396, "initial_val_acc": 0.56, "final_val_acc": 0.86, "best_val_acc": 0.94, "best_epoch": 3}, "improvement": 0.3799999999999999, "first_improvement_epoch": 1}} |
42 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.44, "improved_accuracy": 0.96, "improvement": 0.52, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1532, "learning_rate": 0.041473734597374516, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.013225
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[
0.802002,
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0.013425,
0.018454,
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[
-0.369665,
0.050878,
0.121853,
0.027614,
0.842327
],
[
-0.206338,
0.248281,
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]
],
"network.0.bias": [
0.12834,
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"network.2.weight": [
[
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],
[
-0.258098,
0.368353,
-0.114686,
0.015407,
0.086521,
-0.007215
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[
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0.118324,
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-0.38621,
-0.334352
],
[
0.145782,
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0.066662,
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0.632301,
0.220867
],
[
0.454336,
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0.330563,
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0.414064
],
[
0.170257,
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0.49815,
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0.527774
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],
"network.2.bias": [
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0.57444,
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"network.4.weight": [
[
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[
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0.415908
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[
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[
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0.599376,
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[
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],
"network.4.bias": [
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[
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"network.8.weight": [
[
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[
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[
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[
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[
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"network.8.bias": [
0.040457,
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"network.10.weight": [
[
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[
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[
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[
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[
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],
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"network.12.weight": [
[
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"network.12.bias": [
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]
}
## Activation Signature
### 0
mean: [1.570974, 1.964663, 2.023973, 0.106860, -0.076903, 0.243245]
std: [2.144055, 2.654359, 2.678947, 0.175417, 0.085836, 0.583342]
fourier: [[38.167764, 39.365173, 46.689604, 48.431390, 141.387620], [47.235807, 48.880400, 57.649232, 59.784586, 176.819696], [47.619467, 49.243197, 58.100187, 60.788902, 182.157621], [2.635930, 2.845383, 2.953834, 3.908780, 9.617402], [1.526089, 1.547414, 1.896589, 1.899658, 6.921296], [9.091925, 9.844062, 9.992193, 10.229389, 21.892079]]
input_correlations: [[-0.008871, 0.492925, 0.262502, 0.811565, -0.315313, 0.000000, 0.000000, 0.000000], [0.375313, 0.179709, -0.004656, -0.217683, -0.841908, 0.000000, 0.000000, 0.000000], [0.435054, -0.357223, -0.144063, -0.850693, -0.043281, 0.000000, 0.000000, 0.000000], [0.662869, 0.179921, 0.088735, -0.169872, -0.610838, 0.000000, 0.000000, 0.000000], [-0.224312, -0.051965, 0.216937, 0.220211, 0.904695, 0.000000, 0.000000, 0.000000], [-0.267592, 0.347122, 0.082703, 0.145722, -0.855030, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.866706, -0.817283, -0.878536, -0.033445, 0.679707, 0.431024]
pre_activation_std: [1.720023, 2.121704, 0.997644, 1.952219, 1.632799, 1.380971]
### 2
mean: [1.074632, -0.836380, -0.778010, 1.923916, 0.221934, -0.500114]
std: [0.489706, 0.533533, 0.929009, 1.478680, 1.758989, 1.104500]
fourier: [[7.581007, 8.178714, 8.780537, 9.522368, 96.716893], [8.418330, 8.457183, 9.180375, 9.230421, 75.274181], [12.884272, 13.094795, 14.129294, 16.738216, 70.020900], [23.046206, 26.920904, 27.996217, 32.172982, 173.152398], [27.149698, 28.124788, 32.434983, 34.888157, 37.066790], [18.022155, 20.544837, 21.301965, 23.524947, 45.010304]]
input_correlations: [[0.657084, 0.539321, -0.110029, 0.510289, 0.061468, 0.524942, 0.000000, 0.000000], [-0.827101, 0.488136, 0.398924, 0.444427, 0.252385, -0.702071, 0.000000, 0.000000], [-0.843380, 0.164601, 0.233112, 0.185667, -0.317541, -0.558693, 0.000000, 0.000000], [0.172983, 0.844408, 0.329149, 0.816688, 0.242656, -0.119550, 0.000000, 0.000000], [0.607065, -0.603948, -0.402629, -0.581700, -0.399991, 0.740774, 0.000000, 0.000000], [0.575024, -0.489314, -0.301919, -0.464689, -0.536511, 0.811197, 0.000000, 0.000000]]
pre_activation_mean: [1.074632, -0.836380, -0.778010, 1.923916, 0.221934, -0.500114]
pre_activation_std: [0.489706, 0.533533, 0.929009, 1.478680, 1.758989, 1.104500]
### 4
mean: [-0.385362, 1.247599, 0.447731, -0.116066, -0.389503, 0.836629]
std: [0.918018, 1.497418, 0.494202, 0.658970, 0.837408, 0.328475]
fourier: [[16.204886, 16.974167, 20.259586, 21.416754, 34.682573], [26.469922, 27.215884, 33.299504, 34.562420, 112.283945], [7.882290, 9.183797, 10.657951, 11.776889, 40.295766], [10.363674, 10.445977, 11.467640, 13.704773, 14.023826], [14.739386, 15.342001, 17.548641, 19.368754, 35.055249], [5.206438, 5.302140, 5.764248, 8.745062, 75.296571]]
input_correlations: [[-0.470416, -0.278509, 0.148396, -0.905028, 0.651626, 0.483434, 0.000000, 0.000000], [0.496442, 0.359376, -0.167910, 0.935630, -0.597916, -0.432491, 0.000000, 0.000000], [0.264389, 0.185504, -0.112487, 0.793206, -0.793904, -0.625857, 0.000000, 0.000000], [-0.217735, 0.084761, 0.168174, -0.654430, 0.846758, 0.738130, 0.000000, 0.000000], [-0.545285, -0.320764, 0.178659, -0.931885, 0.582752, 0.386976, 0.000000, 0.000000], [0.835601, 0.697219, -0.212319, 0.689583, 0.476907, 0.620823, 0.000000, 0.000000]]
pre_activation_mean: [-0.385362, 1.247599, 0.447731, -0.116066, -0.389503, 0.836629]
pre_activation_std: [0.918018, 1.497418, 0.494202, 0.658970, 0.837408, 0.328475]
### 6
mean: [1.002732, 1.184315, 0.587127, 0.016403, -0.209748, -0.118120]
std: [1.464641, 1.262601, 0.980656, 0.932670, 1.236685, 0.951049]
fourier: [[24.724335, 26.667397, 33.796491, 33.986489, 90.245895], [21.375569, 22.862701, 29.106301, 29.225331, 106.588373], [16.438709, 17.661938, 22.509494, 22.546701, 52.841430], [13.032475, 14.322496, 16.798691, 20.876434, 21.953446], [18.877365, 19.907021, 22.524855, 28.006242, 28.960888], [13.149461, 14.553072, 17.083532, 21.460850, 22.423869]]
input_correlations: [[-0.693040, 0.983223, 0.987052, -0.658206, -0.702389, 0.307394, 0.000000, 0.000000], [-0.686407, 0.984383, 0.987465, -0.648752, -0.702913, 0.317110, 0.000000, 0.000000], [-0.673776, 0.986872, 0.989966, -0.655478, -0.675693, 0.307403, 0.000000, 0.000000], [0.779597, -0.940187, -0.974654, 0.786513, 0.731300, -0.122162, 0.000000, 0.000000], [0.730189, -0.964928, -0.986080, 0.734198, 0.695399, -0.195755, 0.000000, 0.000000], [0.798423, -0.937497, -0.973940, 0.781682, 0.770015, -0.135328, 0.000000, 0.000000]]
pre_activation_mean: [1.002732, 1.184315, 0.587127, 0.016403, -0.209748, -0.118120]
pre_activation_std: [1.464641, 1.262601, 0.980656, 0.932670, 1.236685, 0.951049]
### 8
mean: [-0.436126, 0.537985, 1.556930, 0.586616, -0.775942, -0.102648]
std: [1.292121, 1.588349, 2.496916, 1.970252, 1.333184, 1.409504]
fourier: [[19.559656, 23.222779, 29.233491, 30.836669, 39.251315], [24.087131, 28.653522, 35.652535, 38.329400, 48.418616], [41.014150, 45.381255, 57.294299, 58.984821, 140.123706], [29.151621, 35.189268, 44.128160, 47.116105, 52.795436], [20.404051, 24.088436, 30.099429, 32.013654, 69.834807], [19.451453, 21.637714, 25.402305, 31.978007, 33.592762]]
input_correlations: [[-0.940150, -0.956427, -0.926836, 0.869007, 0.829228, 0.841324, 0.000000, 0.000000], [0.936634, 0.953095, 0.921941, -0.874656, -0.836069, -0.844681, 0.000000, 0.000000], [0.980762, 0.989387, 0.971992, -0.785279, -0.736429, -0.750718, 0.000000, 0.000000], [0.925248, 0.943344, 0.910653, -0.889235, -0.852204, -0.862077, 0.000000, 0.000000], [-0.945732, -0.960788, -0.932991, 0.861385, 0.821063, 0.830566, 0.000000, 0.000000], [-0.951005, -0.965211, -0.939637, 0.852480, 0.810626, 0.821595, 0.000000, 0.000000]]
pre_activation_mean: [-0.436126, 0.537985, 1.556930, 0.586616, -0.775942, -0.102648]
pre_activation_std: [1.292121, 1.588349, 2.496916, 1.970252, 1.333184, 1.409504]
### 10
mean: [1.431665, 1.817018, 1.830794, -1.155294, -0.239768, -0.360670]
std: [2.272722, 2.784494, 2.858209, 1.879516, 0.231620, 1.240932]
fourier: [[40.191802, 40.746879, 50.512643, 53.307847, 128.849845], [49.809498, 49.969626, 61.555534, 64.764581, 163.531595], [50.001311, 51.507908, 63.752713, 67.288105, 164.771487], [33.639522, 33.811821, 41.510910, 43.646521, 103.976469], [4.041021, 4.204778, 5.093116, 5.347690, 21.579110], [18.109829, 22.072159, 27.606366, 29.585836, 32.460328]]
input_correlations: [[-0.516467, 0.995493, 0.997172, 0.994486, -0.382572, -0.655441, 0.000000, 0.000000], [-0.498286, 0.997361, 0.998427, 0.996637, -0.363829, -0.639269, 0.000000, 0.000000], [-0.541164, 0.992550, 0.994745, 0.991426, -0.410023, -0.676638, 0.000000, 0.000000], [0.497961, -0.997359, -0.998416, -0.996738, 0.364423, 0.638688, 0.000000, 0.000000], [-0.600175, 0.976579, 0.978556, 0.976097, -0.481092, -0.724863, 0.000000, 0.000000], [0.781004, -0.902273, -0.911103, -0.898823, 0.678727, 0.873019, 0.000000, 0.000000]]
pre_activation_mean: [1.431665, 1.817018, 1.830794, -1.155294, -0.239768, -0.360670]
pre_activation_std: [2.272722, 2.784494, 2.858209, 1.879516, 0.231620, 1.240932]
### 12
mean: [-2.998143]
std: [4.756450]
fourier: [[85.317701, 85.887116, 104.324911, 108.859175, 269.832927]]
input_correlations: [[-0.999137, -0.998971, -0.999175, 0.584203, -0.995650, 0.474016, 0.000000, 0.000000]]
pre_activation_mean: [-2.998143]
pre_activation_std: [4.756450]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.031415,
0.145713,
0.300599,
0.683488,
-0.471634
],
[
0.551301,
0.020228,
0.0282,
-0.059623,
-1.074441
],
[
0.27419,
-0.128476,
-0.13618,
-0.356455,
0.013225
],
[
0.802002,
-0.11277,
0.013425,
0.018454,
-0.812351
],
[
-0.369665,
0.050878,
0.121853,
0.027614,
0.842327
],
[
-0.206338,
0.248281,
0.208686,
0.100172,
-0.663151
]
],
"network.0.bias": [
0.12834,
-0.146111,
0.046913,
0.108282,
-0.3056,
0.402529
],
"network.2.weight": [
[
0.056552,
0.009766,
-0.424047,
0.327983,
0.226913,
0.417524
],
[
-0.258098,
0.368353,
-0.114686,
0.015407,
0.086521,
-0.007215
],
[
-0.431915,
0.118324,
-0.318014,
-0.034636,
-0.38621,
-0.334352
],
[
0.145782,
0.689659,
0.066662,
0.750929,
0.632301,
0.220867
],
[
0.454336,
-0.537743,
0.330563,
-0.698943,
-0.534057,
0.414064
],
[
0.170257,
-0.552919,
0.49815,
-0.207264,
-0.365625,
0.527774
]
],
"network.2.bias": [
0.299822,
-0.531172,
0.57444,
0.370408,
0.057915,
-0.611061
],
"network.4.weight": [
[
-0.405261,
0.023268,
-0.167979,
-0.360498,
0.428591,
0.104802
],
[
-0.014164,
-0.200522,
0.022383,
0.837236,
-0.410142,
-0.217769
],
[
-0.187326,
-0.416519,
-0.324149,
0.235003,
-0.408005,
0.415908
],
[
-0.839528,
0.068126,
0.259866,
0.046918,
0.525719,
0.373616
],
[
-0.523176,
-0.564561,
-0.011079,
-0.260537,
0.599376,
-0.419738
],
[
-0.098308,
0.181646,
0.261355,
0.216889,
0.186041,
0.166893
]
],
"network.4.bias": [
0.324797,
0.034474,
0.381334,
0.161777,
0.126567,
0.397409
],
"network.6.weight": [
[
-0.852867,
0.715647,
0.304297,
-0.353423,
-0.468229,
0.220128
],
[
-0.294325,
0.640555,
0.221858,
-0.311419,
-0.845627,
0.126683
],
[
-0.094946,
0.39429,
0.526699,
-0.526883,
-0.190096,
0.236604
],
[
0.063122,
-0.543837,
0.135756,
0.677562,
0.347147,
0.314065
],
[
0.254551,
-0.704916,
-0.0623,
0.655975,
0.057287,
0.294169
],
[
0.188445,
-0.38463,
-0.253015,
0.705268,
0.687022,
0.03442
]
],
"network.6.bias": [
-0.026139,
0.314539,
-0.187336,
0.330707,
0.385463,
0.31998
],
"network.8.weight": [
[
0.00303,
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-0.23178,
0.363689,
0.276764,
0.477428
],
[
0.306214,
0.666594,
-0.185464,
-0.48117,
-0.909752,
0.095881
],
[
0.584851,
0.776355,
0.348707,
-0.472636,
-0.264243,
-0.478579
],
[
0.180399,
0.617433,
0.256387,
-0.82225,
-0.576006,
-0.521998
],
[
-0.342471,
-0.244717,
-0.180164,
0.179893,
0.750676,
0.159674
],
[
-0.555022,
0.133748,
-0.431455,
0.387038,
0.328491,
0.522387
]
],
"network.8.bias": [
0.040457,
-0.057671,
0.157061,
0.042674,
-0.328383,
0.275612
],
"network.10.weight": [
[
-0.169671,
0.083009,
0.819906,
0.103518,
0.404132,
-0.45061
],
[
-0.204298,
-0.007237,
0.7348,
0.699828,
0.222315,
-0.288257
],
[
-0.093145,
0.17195,
0.795441,
0.443712,
-0.038664,
-0.454996
],
[
-0.153238,
0.290113,
-0.447692,
-0.799005,
0.173085,
0.222772
],
[
-0.003219,
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0.506581,
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0.089861
],
[
0.459294,
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0.1318,
0.521919,
0.181503
]
],
"network.10.bias": [
-0.014268,
-0.064724,
0.034406,
0.141924,
-0.401863,
0.047385
],
"network.12.weight": [
[
-0.433252,
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-0.680487,
0.05289,
0.022799,
0.370069
]
],
"network.12.bias": [
0.374396
]
}
## Activation Signature
### 0
mean: [1.570974, 1.964663, 2.023973, 0.106860, -0.076903, 0.243245]
std: [2.144055, 2.654359, 2.678947, 0.175417, 0.085836, 0.583342]
fourier: [[38.167764, 39.365173, 46.689604, 48.431390, 141.387620], [47.235807, 48.880400, 57.649232, 59.784586, 176.819696], [47.619467, 49.243197, 58.100187, 60.788902, 182.157621], [2.635930, 2.845383, 2.953834, 3.908780, 9.617402], [1.526089, 1.547414, 1.896589, 1.899658, 6.921296], [9.091925, 9.844062, 9.992193, 10.229389, 21.892079]]
input_correlations: [[-0.008871, 0.492925, 0.262502, 0.811565, -0.315313, 0.000000, 0.000000, 0.000000], [0.375313, 0.179709, -0.004656, -0.217683, -0.841908, 0.000000, 0.000000, 0.000000], [0.435054, -0.357223, -0.144063, -0.850693, -0.043281, 0.000000, 0.000000, 0.000000], [0.662869, 0.179921, 0.088735, -0.169872, -0.610838, 0.000000, 0.000000, 0.000000], [-0.224312, -0.051965, 0.216937, 0.220211, 0.904695, 0.000000, 0.000000, 0.000000], [-0.267592, 0.347122, 0.082703, 0.145722, -0.855030, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.866706, -0.817283, -0.878536, -0.033445, 0.679707, 0.431024]
pre_activation_std: [1.720023, 2.121704, 0.997644, 1.952219, 1.632799, 1.380971]
### 2
mean: [1.074632, -0.836380, -0.778010, 1.923916, 0.221934, -0.500114]
std: [0.489706, 0.533533, 0.929009, 1.478680, 1.758989, 1.104500]
fourier: [[7.581007, 8.178714, 8.780537, 9.522368, 96.716893], [8.418330, 8.457183, 9.180375, 9.230421, 75.274181], [12.884272, 13.094795, 14.129294, 16.738216, 70.020900], [23.046206, 26.920904, 27.996217, 32.172982, 173.152398], [27.149698, 28.124788, 32.434983, 34.888157, 37.066790], [18.022155, 20.544837, 21.301965, 23.524947, 45.010304]]
input_correlations: [[0.657084, 0.539321, -0.110029, 0.510289, 0.061468, 0.524942, 0.000000, 0.000000], [-0.827101, 0.488136, 0.398924, 0.444427, 0.252385, -0.702071, 0.000000, 0.000000], [-0.843380, 0.164601, 0.233112, 0.185667, -0.317541, -0.558693, 0.000000, 0.000000], [0.172983, 0.844408, 0.329149, 0.816688, 0.242656, -0.119550, 0.000000, 0.000000], [0.607065, -0.603948, -0.402629, -0.581700, -0.399991, 0.740774, 0.000000, 0.000000], [0.575024, -0.489314, -0.301919, -0.464689, -0.536511, 0.811197, 0.000000, 0.000000]]
pre_activation_mean: [1.074632, -0.836380, -0.778010, 1.923916, 0.221934, -0.500114]
pre_activation_std: [0.489706, 0.533533, 0.929009, 1.478680, 1.758989, 1.104500]
### 4
mean: [-0.385362, 1.247599, 0.447731, -0.116066, -0.389503, 0.836629]
std: [0.918018, 1.497418, 0.494202, 0.658970, 0.837408, 0.328475]
fourier: [[16.204886, 16.974167, 20.259586, 21.416754, 34.682573], [26.469922, 27.215884, 33.299504, 34.562420, 112.283945], [7.882290, 9.183797, 10.657951, 11.776889, 40.295766], [10.363674, 10.445977, 11.467640, 13.704773, 14.023826], [14.739386, 15.342001, 17.548641, 19.368754, 35.055249], [5.206438, 5.302140, 5.764248, 8.745062, 75.296571]]
input_correlations: [[-0.470416, -0.278509, 0.148396, -0.905028, 0.651626, 0.483434, 0.000000, 0.000000], [0.496442, 0.359376, -0.167910, 0.935630, -0.597916, -0.432491, 0.000000, 0.000000], [0.264389, 0.185504, -0.112487, 0.793206, -0.793904, -0.625857, 0.000000, 0.000000], [-0.217735, 0.084761, 0.168174, -0.654430, 0.846758, 0.738130, 0.000000, 0.000000], [-0.545285, -0.320764, 0.178659, -0.931885, 0.582752, 0.386976, 0.000000, 0.000000], [0.835601, 0.697219, -0.212319, 0.689583, 0.476907, 0.620823, 0.000000, 0.000000]]
pre_activation_mean: [-0.385362, 1.247599, 0.447731, -0.116066, -0.389503, 0.836629]
pre_activation_std: [0.918018, 1.497418, 0.494202, 0.658970, 0.837408, 0.328475]
### 6
mean: [1.002732, 1.184315, 0.587127, 0.016403, -0.209748, -0.118120]
std: [1.464641, 1.262601, 0.980656, 0.932670, 1.236685, 0.951049]
fourier: [[24.724335, 26.667397, 33.796491, 33.986489, 90.245895], [21.375569, 22.862701, 29.106301, 29.225331, 106.588373], [16.438709, 17.661938, 22.509494, 22.546701, 52.841430], [13.032475, 14.322496, 16.798691, 20.876434, 21.953446], [18.877365, 19.907021, 22.524855, 28.006242, 28.960888], [13.149461, 14.553072, 17.083532, 21.460850, 22.423869]]
input_correlations: [[-0.693040, 0.983223, 0.987052, -0.658206, -0.702389, 0.307394, 0.000000, 0.000000], [-0.686407, 0.984383, 0.987465, -0.648752, -0.702913, 0.317110, 0.000000, 0.000000], [-0.673776, 0.986872, 0.989966, -0.655478, -0.675693, 0.307403, 0.000000, 0.000000], [0.779597, -0.940187, -0.974654, 0.786513, 0.731300, -0.122162, 0.000000, 0.000000], [0.730189, -0.964928, -0.986080, 0.734198, 0.695399, -0.195755, 0.000000, 0.000000], [0.798423, -0.937497, -0.973940, 0.781682, 0.770015, -0.135328, 0.000000, 0.000000]]
pre_activation_mean: [1.002732, 1.184315, 0.587127, 0.016403, -0.209748, -0.118120]
pre_activation_std: [1.464641, 1.262601, 0.980656, 0.932670, 1.236685, 0.951049]
### 8
mean: [-0.436126, 0.537985, 1.556930, 0.586616, -0.775942, -0.102648]
std: [1.292121, 1.588349, 2.496916, 1.970252, 1.333184, 1.409504]
fourier: [[19.559656, 23.222779, 29.233491, 30.836669, 39.251315], [24.087131, 28.653522, 35.652535, 38.329400, 48.418616], [41.014150, 45.381255, 57.294299, 58.984821, 140.123706], [29.151621, 35.189268, 44.128160, 47.116105, 52.795436], [20.404051, 24.088436, 30.099429, 32.013654, 69.834807], [19.451453, 21.637714, 25.402305, 31.978007, 33.592762]]
input_correlations: [[-0.940150, -0.956427, -0.926836, 0.869007, 0.829228, 0.841324, 0.000000, 0.000000], [0.936634, 0.953095, 0.921941, -0.874656, -0.836069, -0.844681, 0.000000, 0.000000], [0.980762, 0.989387, 0.971992, -0.785279, -0.736429, -0.750718, 0.000000, 0.000000], [0.925248, 0.943344, 0.910653, -0.889235, -0.852204, -0.862077, 0.000000, 0.000000], [-0.945732, -0.960788, -0.932991, 0.861385, 0.821063, 0.830566, 0.000000, 0.000000], [-0.951005, -0.965211, -0.939637, 0.852480, 0.810626, 0.821595, 0.000000, 0.000000]]
pre_activation_mean: [-0.436126, 0.537985, 1.556930, 0.586616, -0.775942, -0.102648]
pre_activation_std: [1.292121, 1.588349, 2.496916, 1.970252, 1.333184, 1.409504]
### 10
mean: [1.431665, 1.817018, 1.830794, -1.155294, -0.239768, -0.360670]
std: [2.272722, 2.784494, 2.858209, 1.879516, 0.231620, 1.240932]
fourier: [[40.191802, 40.746879, 50.512643, 53.307847, 128.849845], [49.809498, 49.969626, 61.555534, 64.764581, 163.531595], [50.001311, 51.507908, 63.752713, 67.288105, 164.771487], [33.639522, 33.811821, 41.510910, 43.646521, 103.976469], [4.041021, 4.204778, 5.093116, 5.347690, 21.579110], [18.109829, 22.072159, 27.606366, 29.585836, 32.460328]]
input_correlations: [[-0.516467, 0.995493, 0.997172, 0.994486, -0.382572, -0.655441, 0.000000, 0.000000], [-0.498286, 0.997361, 0.998427, 0.996637, -0.363829, -0.639269, 0.000000, 0.000000], [-0.541164, 0.992550, 0.994745, 0.991426, -0.410023, -0.676638, 0.000000, 0.000000], [0.497961, -0.997359, -0.998416, -0.996738, 0.364423, 0.638688, 0.000000, 0.000000], [-0.600175, 0.976579, 0.978556, 0.976097, -0.481092, -0.724863, 0.000000, 0.000000], [0.781004, -0.902273, -0.911103, -0.898823, 0.678727, 0.873019, 0.000000, 0.000000]]
pre_activation_mean: [1.431665, 1.817018, 1.830794, -1.155294, -0.239768, -0.360670]
pre_activation_std: [2.272722, 2.784494, 2.858209, 1.879516, 0.231620, 1.240932]
### 12
mean: [-2.998143]
std: [4.756450]
fourier: [[85.317701, 85.887116, 104.324911, 108.859175, 269.832927]]
input_correlations: [[-0.999137, -0.998971, -0.999175, 0.584203, -0.995650, 0.474016, 0.000000, 0.000000]]
pre_activation_mean: [-2.998143]
pre_activation_std: [4.756450]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "12": {"neuron_profiles": {"0": {"mean": -2.998143434524536, "std": 4.756450176239014, "fourier": [85.3177008228229, 85.88711569244704, 104.32491099530277, 108.85917507164868, 269.8329268395901], "input_correlations": [-0.9991373393637484, -0.9989706033604497, -0.9991749967218404, 0.584203231407439, -0.9956503433458473, 0.47401637082027287, 0.0, 0.0], "pre_activation_mean": -2.998143434524536, "pre_activation_std": 4.756450176239014}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.031415, 0.145713, 0.300599, 0.683488, -0.471634], [0.551301, 0.020228, 0.0282, -0.059623, -1.074441], [0.27419, -0.128476, -0.13618, -0.356455, 0.013225], [0.802002, -0.11277, 0.013425, 0.018454, -0.812351], [-0.369665, 0.050878, 0.121853, 0.027614, 0.842327], [-0.206338, 0.248281, 0.208686, 0.100172, -0.663151]], "network.0.bias": [0.12834, -0.146111, 0.046913, 0.108282, -0.3056, 0.402529], "network.2.weight": [[0.056552, 0.009766, -0.424047, 0.327983, 0.226913, 0.417524], [-0.258098, 0.368353, -0.114686, 0.015407, 0.086521, -0.007215], [-0.431915, 0.118324, -0.318014, -0.034636, -0.38621, -0.334352], [0.145782, 0.689659, 0.066662, 0.750929, 0.632301, 0.220867], [0.454336, -0.537743, 0.330563, -0.698943, 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[0.188445, -0.38463, -0.253015, 0.705268, 0.687022, 0.03442]], "network.6.bias": [-0.026139, 0.314539, -0.187336, 0.330707, 0.385463, 0.31998], "network.8.weight": [[0.00303, -0.546385, -0.23178, 0.363689, 0.276764, 0.477428], [0.306214, 0.666594, -0.185464, -0.48117, -0.909752, 0.095881], [0.584851, 0.776355, 0.348707, -0.472636, -0.264243, -0.478579], [0.180399, 0.617433, 0.256387, -0.82225, -0.576006, -0.521998], [-0.342471, -0.244717, -0.180164, 0.179893, 0.750676, 0.159674], [-0.555022, 0.133748, -0.431455, 0.387038, 0.328491, 0.522387]], "network.8.bias": [0.040457, -0.057671, 0.157061, 0.042674, -0.328383, 0.275612], "network.10.weight": [[-0.169671, 0.083009, 0.819906, 0.103518, 0.404132, -0.45061], [-0.204298, -0.007237, 0.7348, 0.699828, 0.222315, -0.288257], [-0.093145, 0.17195, 0.795441, 0.443712, -0.038664, -0.454996], [-0.153238, 0.290113, -0.447692, -0.799005, 0.173085, 0.222772], [-0.003219, -0.167, -0.130085, 0.506581, -0.265178, 0.089861], [0.459294, -0.525041, -0.194133, 0.1318, 0.521919, 0.181503]], "network.10.bias": [-0.014268, -0.064724, 0.034406, 0.141924, -0.401863, 0.047385], "network.12.weight": [[-0.433252, -0.716937, -0.680487, 0.05289, 0.022799, 0.370069]], "network.12.bias": [0.374396]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7165943086147308, "train_acc": 0.42, "val_loss": 0.6914291381835938, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6868470311164856, "train_acc": 0.51, "val_loss": 0.7174140810966492, "val_acc": 0.44}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.669032633304596, "train_acc": 0.58, "val_loss": 0.736091673374176, "val_acc": 0.44}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6467559337615967, "train_acc": 0.58, "val_loss": 0.6437938213348389, "val_acc": 0.44}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.5614522397518158, "train_acc": 0.605, "val_loss": 0.47901490330696106, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.4527719020843506, "train_acc": 0.82, "val_loss": 0.32321521639823914, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.3949238359928131, "train_acc": 0.815, "val_loss": 0.2944648861885071, "val_acc": 0.88}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.3606310933828354, "train_acc": 0.835, "val_loss": 0.2693600356578827, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.317362904548645, "train_acc": 0.865, "val_loss": 0.26390376687049866, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.34307822585105896, "train_acc": 0.855, "val_loss": 0.25126829743385315, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.3128865510225296, "train_acc": 0.865, "val_loss": 0.2437119036912918, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.2950190007686615, "train_acc": 0.865, "val_loss": 0.2577350437641144, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.2945558428764343, "train_acc": 0.865, "val_loss": 0.2000245302915573, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.2706002816557884, "train_acc": 0.885, "val_loss": 0.301016241312027, "val_acc": 0.92}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6914291381835938, "final_val_loss": 0.6437938213348389, "initial_val_acc": 0.56, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.47901490330696106, "final_val_loss": 0.301016241312027, "initial_val_acc": 0.82, "final_val_acc": 0.92, "best_val_acc": 0.96, "best_epoch": 11}, "improvement": 0.52, "first_improvement_epoch": 3}} |
43 | {"target_pattern": "palindrome", "degraded_accuracy": 0.48, "improved_accuracy": 0.9, "improvement": 0.42000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9124, "learning_rate": 0.05450317299859903, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.651874,
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0.01094,
0.642966
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[
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0.912213
],
[
0.873497,
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-0.102801,
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],
[
0.306337,
-0.524571,
-0.196247,
0.050194,
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],
[
-0.731006,
-0.52608,
-0.0302,
0.461693,
0.61465
],
[
0.866656,
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0.85584
]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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1.046511,
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],
[
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0.663266,
0.307118
],
[
0.362102,
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],
[
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0.196141,
0.974096,
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],
[
0.220636,
0.422773,
0.656112,
0.562898,
0.824894,
0.430497
],
[
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0.221896,
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]
],
"network.2.bias": [
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],
"network.4.weight": [
[
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[
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0.376156,
0.588736,
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],
[
0.668737,
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],
[
0.205577,
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],
[
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0.445649,
1.1974,
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[
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],
"network.4.bias": [
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"network.6.weight": [
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[
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"network.8.weight": [
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"network.8.bias": [
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]
}
## Activation Signature
### 0
mean: [0.283306, 3.328115, 3.369158, 0.320623, 0.246964, 0.339763]
std: [0.463825, 3.792055, 3.944336, 0.530854, 0.432193, 0.544814]
fourier: [[7.323042, 7.891192, 8.145883, 10.115708, 25.497558], [66.574796, 70.193026, 72.067281, 83.084977, 299.530369], [69.175349, 73.754322, 75.188714, 86.526125, 303.224223], [8.322575, 9.210074, 9.228048, 11.339701, 28.856077], [6.513828, 7.216861, 7.725129, 9.114429, 22.226714], [8.236526, 8.406460, 9.810118, 10.793375, 30.578695]]
input_correlations: [[0.690762, -0.008452, -0.011236, 0.013863, 0.725848, 0.000000, 0.000000, 0.000000], [0.608525, 0.091272, 0.111005, 0.069568, 0.859642, 0.000000, 0.000000, 0.000000], [0.832407, 0.050148, 0.004453, -0.306225, -0.283865, 0.000000, 0.000000, 0.000000], [-0.054861, -0.457295, -0.406360, -0.266654, -0.822254, 0.000000, 0.000000, 0.000000], [-0.702976, -0.489823, -0.206425, 0.373585, 0.421381, 0.000000, 0.000000, 0.000000], [0.706924, 0.115663, 0.184967, 0.252580, 0.766831, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.770132, 1.413624, -0.790360, -1.920102, 0.186538, 2.341997]
pre_activation_std: [1.784481, 2.072054, 1.723137, 1.774294, 2.369099, 2.497626]
### 2
mean: [3.353713, 1.565263, -0.656222, -3.124875, 2.865414, -1.411155]
std: [3.658331, 1.945250, 0.570566, 2.233245, 3.001090, 1.418693]
fourier: [[63.629907, 67.139085, 67.744700, 80.082601, 301.834172], [33.184145, 34.241347, 36.689788, 41.768923, 140.873627], [7.675647, 8.512380, 9.117233, 10.639662, 59.060000], [36.906963, 38.330372, 46.848162, 48.182428, 281.238741], [52.214189, 56.303785, 56.474329, 65.501750, 257.887295], [24.035979, 24.794900, 27.862084, 30.862777, 127.003980]]
input_correlations: [[0.897543, 0.913181, 0.436394, 0.320878, 0.549956, 0.938584, 0.000000, 0.000000], [0.874120, 0.882233, 0.475959, 0.345953, 0.572271, 0.910008, 0.000000, 0.000000], [0.144171, 0.057302, 0.619493, 0.350903, 0.332265, 0.065388, 0.000000, 0.000000], [-0.927390, -0.968991, -0.282662, -0.203624, -0.464783, -0.965944, 0.000000, 0.000000], [0.910544, 0.925073, 0.453480, 0.332682, 0.529151, 0.940483, 0.000000, 0.000000], [-0.887071, -0.881447, -0.541408, -0.338651, -0.517181, -0.916404, 0.000000, 0.000000]]
pre_activation_mean: [3.353713, 1.565263, -0.656222, -3.124875, 2.865414, -1.411155]
pre_activation_std: [3.658331, 1.945250, 0.570566, 2.233245, 3.001090, 1.418693]
### 4
mean: [0.586066, -3.955702, 4.880710, 0.062288, -3.883256, -2.626802]
std: [0.759165, 2.870250, 5.405618, 0.541800, 2.798302, 3.900415]
fourier: [[13.789041, 14.467370, 14.751691, 16.667676, 52.745930], [50.712881, 53.732650, 54.982790, 63.114589, 356.013154], [94.146114, 100.644205, 101.980382, 118.492569, 439.263834], [7.962739, 9.564125, 9.635123, 9.985802, 11.758016], [49.307115, 52.254946, 53.380854, 61.405696, 349.493078], [66.840418, 71.128278, 73.273907, 85.518631, 236.412140]]
input_correlations: [[0.993465, 0.983566, 0.378182, 0.756601, 0.991978, 0.386082, 0.000000, 0.000000], [-0.998606, -0.989716, -0.449916, -0.764432, -0.998932, -0.372630, 0.000000, 0.000000], [0.999686, 0.995891, 0.483334, 0.761080, 0.999447, 0.378396, 0.000000, 0.000000], [0.995915, 0.984189, 0.415601, 0.793285, 0.992126, 0.301694, 0.000000, 0.000000], [-0.999225, -0.991326, -0.447361, -0.759283, -0.998671, -0.374612, 0.000000, 0.000000], [-0.998597, -0.997733, -0.513262, -0.758404, -0.997991, -0.381431, 0.000000, 0.000000]]
pre_activation_mean: [0.586066, -3.955702, 4.880710, 0.062288, -3.883256, -2.626802]
pre_activation_std: [0.759165, 2.870250, 5.405618, 0.541800, 2.798302, 3.900415]
### 6
mean: [-1.858538, 3.092693, 3.239337, -1.674767, -1.917269, -3.589072]
std: [3.073842, 4.028685, 4.072216, 2.888018, 2.958380, 4.996772]
fourier: [[53.595072, 56.051034, 57.356870, 67.432728, 167.268453], [70.465025, 72.239917, 74.381049, 88.161705, 278.342394], [71.219244, 74.837008, 76.324045, 89.333918, 291.540341], [50.489126, 51.823252, 53.365324, 63.241160, 150.729030], [51.491329, 53.322592, 54.108068, 64.836417, 172.554239], [87.136900, 91.030727, 92.698519, 109.603996, 323.016460]]
input_correlations: [[-0.979851, -0.735158, -0.998823, -0.962131, -0.739010, 0.613443, 0.000000, 0.000000], [0.974759, 0.762611, 0.995846, 0.954554, 0.766213, -0.646917, 0.000000, 0.000000], [0.982540, 0.729274, 0.999205, 0.964573, 0.733145, -0.606766, 0.000000, 0.000000], [-0.975021, -0.759798, -0.996295, -0.955241, -0.763439, 0.643079, 0.000000, 0.000000], [-0.976114, -0.753554, -0.996834, -0.958895, -0.757197, 0.637093, 0.000000, 0.000000], [-0.979668, -0.738986, -0.998476, -0.962236, -0.742776, 0.618732, 0.000000, 0.000000]]
pre_activation_mean: [-1.858538, 3.092693, 3.239337, -1.674767, -1.917269, -3.589072]
pre_activation_std: [3.073842, 4.028685, 4.072216, 2.888018, 2.958380, 4.996772]
### 8
mean: [-2.655921]
std: [4.647676]
fourier: [[80.858054, 81.411806, 84.571578, 101.261549, 239.032880]]
input_correlations: [[0.699653, -0.991047, -0.988135, 0.693378, 0.668897, 0.684473, 0.000000, 0.000000]]
pre_activation_mean: [-2.655921]
pre_activation_std: [4.647676]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.651874,
-0.174792,
-0.319937,
0.01094,
0.642966
],
[
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-0.038307,
-0.24278,
-0.012397,
0.912213
],
[
0.873497,
-0.195463,
-0.163821,
-0.102801,
-0.384639
],
[
0.306337,
-0.524571,
-0.196247,
0.050194,
-0.81665
],
[
-0.731006,
-0.52608,
-0.0302,
0.461693,
0.61465
],
[
0.866656,
-0.227666,
-0.178087,
0.296727,
0.85584
]
],
"network.0.bias": [
0.129282,
0.200313,
-0.484159,
-0.035935,
0.36981,
0.358503
],
"network.2.weight": [
[
0.230518,
0.223593,
0.703574,
0.589181,
1.046511,
0.779423
],
[
0.186821,
0.111241,
0.566551,
0.477937,
0.663266,
0.307118
],
[
0.362102,
0.035606,
0.637883,
0.147345,
0.351161,
-0.394689
],
[
-0.07692,
-0.394281,
0.196141,
0.974096,
-0.276644,
-0.526725
],
[
0.220636,
0.422773,
0.656112,
0.562898,
0.824894,
0.430497
],
[
-0.171383,
-0.056243,
-0.523487,
0.221896,
-0.452658,
-0.217936
]
],
"network.2.bias": [
-0.13589,
-0.243878,
-0.664986,
-1.028864,
0.105763,
-0.07943
],
"network.4.weight": [
[
0.07476,
0.077833,
-0.507092,
0.591839,
0.114115,
0.570993
],
[
-0.294053,
0.381553,
0.376156,
0.588736,
-0.857021,
-0.030022
],
[
0.668737,
0.507437,
-0.114578,
0.112268,
0.669619,
-0.335776
],
[
0.205577,
0.011299,
-0.139294,
-0.050164,
-0.066237,
-0.555543
],
[
-0.479069,
0.169168,
0.445649,
1.1974,
-0.490721,
0.216247
],
[
-0.818855,
-0.605443,
-0.630531,
-0.700233,
0.110522,
-0.013164
]
],
"network.4.bias": [
-0.086215,
-1.075822,
-0.087303,
-0.51118,
-1.028154,
0.668275
],
"network.6.weight": [
[
0.270441,
-0.316106,
-0.569205,
-0.224799,
-0.31427,
0.367857
],
[
0.166123,
0.285612,
0.67084,
0.001539,
0.329138,
-1.107048
],
[
0.14559,
0.435963,
0.700562,
0.138196,
0.253686,
-0.469569
],
[
0.029649,
-0.558951,
-0.493858,
-0.113001,
-0.566271,
0.653777
],
[
0.342161,
-0.821425,
-0.50409,
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-0.658458,
0.593164
],
[
0.341654,
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-0.485102,
0.707027
]
],
"network.6.bias": [
0.693755,
0.012469,
-0.138828,
0.534109,
0.258354,
0.391972
],
"network.8.weight": [
[
0.452488,
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-0.360267,
0.456242,
0.28681,
0.419389
]
],
"network.8.bias": [
0.451799
]
}
## Activation Signature
### 0
mean: [0.283306, 3.328115, 3.369158, 0.320623, 0.246964, 0.339763]
std: [0.463825, 3.792055, 3.944336, 0.530854, 0.432193, 0.544814]
fourier: [[7.323042, 7.891192, 8.145883, 10.115708, 25.497558], [66.574796, 70.193026, 72.067281, 83.084977, 299.530369], [69.175349, 73.754322, 75.188714, 86.526125, 303.224223], [8.322575, 9.210074, 9.228048, 11.339701, 28.856077], [6.513828, 7.216861, 7.725129, 9.114429, 22.226714], [8.236526, 8.406460, 9.810118, 10.793375, 30.578695]]
input_correlations: [[0.690762, -0.008452, -0.011236, 0.013863, 0.725848, 0.000000, 0.000000, 0.000000], [0.608525, 0.091272, 0.111005, 0.069568, 0.859642, 0.000000, 0.000000, 0.000000], [0.832407, 0.050148, 0.004453, -0.306225, -0.283865, 0.000000, 0.000000, 0.000000], [-0.054861, -0.457295, -0.406360, -0.266654, -0.822254, 0.000000, 0.000000, 0.000000], [-0.702976, -0.489823, -0.206425, 0.373585, 0.421381, 0.000000, 0.000000, 0.000000], [0.706924, 0.115663, 0.184967, 0.252580, 0.766831, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.770132, 1.413624, -0.790360, -1.920102, 0.186538, 2.341997]
pre_activation_std: [1.784481, 2.072054, 1.723137, 1.774294, 2.369099, 2.497626]
### 2
mean: [3.353713, 1.565263, -0.656222, -3.124875, 2.865414, -1.411155]
std: [3.658331, 1.945250, 0.570566, 2.233245, 3.001090, 1.418693]
fourier: [[63.629907, 67.139085, 67.744700, 80.082601, 301.834172], [33.184145, 34.241347, 36.689788, 41.768923, 140.873627], [7.675647, 8.512380, 9.117233, 10.639662, 59.060000], [36.906963, 38.330372, 46.848162, 48.182428, 281.238741], [52.214189, 56.303785, 56.474329, 65.501750, 257.887295], [24.035979, 24.794900, 27.862084, 30.862777, 127.003980]]
input_correlations: [[0.897543, 0.913181, 0.436394, 0.320878, 0.549956, 0.938584, 0.000000, 0.000000], [0.874120, 0.882233, 0.475959, 0.345953, 0.572271, 0.910008, 0.000000, 0.000000], [0.144171, 0.057302, 0.619493, 0.350903, 0.332265, 0.065388, 0.000000, 0.000000], [-0.927390, -0.968991, -0.282662, -0.203624, -0.464783, -0.965944, 0.000000, 0.000000], [0.910544, 0.925073, 0.453480, 0.332682, 0.529151, 0.940483, 0.000000, 0.000000], [-0.887071, -0.881447, -0.541408, -0.338651, -0.517181, -0.916404, 0.000000, 0.000000]]
pre_activation_mean: [3.353713, 1.565263, -0.656222, -3.124875, 2.865414, -1.411155]
pre_activation_std: [3.658331, 1.945250, 0.570566, 2.233245, 3.001090, 1.418693]
### 4
mean: [0.586066, -3.955702, 4.880710, 0.062288, -3.883256, -2.626802]
std: [0.759165, 2.870250, 5.405618, 0.541800, 2.798302, 3.900415]
fourier: [[13.789041, 14.467370, 14.751691, 16.667676, 52.745930], [50.712881, 53.732650, 54.982790, 63.114589, 356.013154], [94.146114, 100.644205, 101.980382, 118.492569, 439.263834], [7.962739, 9.564125, 9.635123, 9.985802, 11.758016], [49.307115, 52.254946, 53.380854, 61.405696, 349.493078], [66.840418, 71.128278, 73.273907, 85.518631, 236.412140]]
input_correlations: [[0.993465, 0.983566, 0.378182, 0.756601, 0.991978, 0.386082, 0.000000, 0.000000], [-0.998606, -0.989716, -0.449916, -0.764432, -0.998932, -0.372630, 0.000000, 0.000000], [0.999686, 0.995891, 0.483334, 0.761080, 0.999447, 0.378396, 0.000000, 0.000000], [0.995915, 0.984189, 0.415601, 0.793285, 0.992126, 0.301694, 0.000000, 0.000000], [-0.999225, -0.991326, -0.447361, -0.759283, -0.998671, -0.374612, 0.000000, 0.000000], [-0.998597, -0.997733, -0.513262, -0.758404, -0.997991, -0.381431, 0.000000, 0.000000]]
pre_activation_mean: [0.586066, -3.955702, 4.880710, 0.062288, -3.883256, -2.626802]
pre_activation_std: [0.759165, 2.870250, 5.405618, 0.541800, 2.798302, 3.900415]
### 6
mean: [-1.858538, 3.092693, 3.239337, -1.674767, -1.917269, -3.589072]
std: [3.073842, 4.028685, 4.072216, 2.888018, 2.958380, 4.996772]
fourier: [[53.595072, 56.051034, 57.356870, 67.432728, 167.268453], [70.465025, 72.239917, 74.381049, 88.161705, 278.342394], [71.219244, 74.837008, 76.324045, 89.333918, 291.540341], [50.489126, 51.823252, 53.365324, 63.241160, 150.729030], [51.491329, 53.322592, 54.108068, 64.836417, 172.554239], [87.136900, 91.030727, 92.698519, 109.603996, 323.016460]]
input_correlations: [[-0.979851, -0.735158, -0.998823, -0.962131, -0.739010, 0.613443, 0.000000, 0.000000], [0.974759, 0.762611, 0.995846, 0.954554, 0.766213, -0.646917, 0.000000, 0.000000], [0.982540, 0.729274, 0.999205, 0.964573, 0.733145, -0.606766, 0.000000, 0.000000], [-0.975021, -0.759798, -0.996295, -0.955241, -0.763439, 0.643079, 0.000000, 0.000000], [-0.976114, -0.753554, -0.996834, -0.958895, -0.757197, 0.637093, 0.000000, 0.000000], [-0.979668, -0.738986, -0.998476, -0.962236, -0.742776, 0.618732, 0.000000, 0.000000]]
pre_activation_mean: [-1.858538, 3.092693, 3.239337, -1.674767, -1.917269, -3.589072]
pre_activation_std: [3.073842, 4.028685, 4.072216, 2.888018, 2.958380, 4.996772]
### 8
mean: [-2.655921]
std: [4.647676]
fourier: [[80.858054, 81.411806, 84.571578, 101.261549, 239.032880]]
input_correlations: [[0.699653, -0.991047, -0.988135, 0.693378, 0.668897, 0.684473, 0.000000, 0.000000]]
pre_activation_mean: [-2.655921]
pre_activation_std: [4.647676]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.28330621123313904, "std": 0.4638245105743408, "fourier": [7.323041701751879, 7.891192368509094, 8.145883055063312, 10.115707570275122, 25.49755834040826], "input_correlations": [0.6907623303449162, -0.008452491396757522, -0.011236324159835541, 0.013863099029497884, 0.7258479948206638, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7701318264007568, "pre_activation_std": 1.7844809293746948}, "1": {"mean": 3.328115224838257, "std": 3.7920546531677246, "fourier": [66.57479557488081, 70.19302623643163, 72.06728101155161, 83.08497677575988, 299.5303692892194], "input_correlations": [0.6085245389913706, 0.09127180367137491, 0.1110047049325579, 0.0695676429616117, 0.8596415034738527, 0.0, 0.0, 0.0], "pre_activation_mean": 1.4136239290237427, "pre_activation_std": 2.072053909301758}, "2": {"mean": 3.3691580295562744, "std": 3.944336414337158, "fourier": [69.17534878475952, 73.75432238157805, 75.18871435811214, 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"degraded_stage": {"initial_val_loss": 0.6891180276870728, "final_val_loss": 0.5560011267662048, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.47940298914909363, "final_val_loss": 0.3531542122364044, "initial_val_acc": 0.82, "final_val_acc": 0.86, "best_val_acc": 0.9, "best_epoch": 10}, "improvement": 0.42000000000000004, "first_improvement_epoch": 2}} |
44 | {"target_pattern": "palindrome", "degraded_accuracy": 0.48, "improved_accuracy": 0.82, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9386, "learning_rate": 0.08356802268451656, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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],
[
0.553166,
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]
],
"network.4.bias": [
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"network.6.weight": [
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"network.8.weight": [
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],
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],
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"network.12.weight": [
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],
"network.12.bias": [
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}
## Activation Signature
### 0
mean: [0.910197, 0.754367, 1.145548, 2.551496, 1.258727, 1.341092]
std: [0.823595, 0.640934, 1.750252, 3.297669, 1.786065, 1.921414]
fourier: [[11.789807, 12.633201, 13.588245, 16.579147, 81.917749], [9.570336, 9.716782, 12.311351, 12.519212, 67.892983], [28.278217, 30.590594, 37.925012, 38.440776, 103.099321], [55.155321, 58.166226, 69.391869, 77.621853, 229.634609], [28.979326, 31.668481, 38.116385, 39.928923, 113.285376], [31.201612, 33.507993, 41.523335, 42.770157, 120.698242]]
input_correlations: [[-0.941757, -0.343837, -0.001178, 0.115589, -0.068539, 0.000000, 0.000000, 0.000000], [0.651400, 0.255832, 0.539004, 0.393048, 0.739964, 0.000000, 0.000000, 0.000000], [-0.322711, -0.535630, -0.782946, -0.552730, -0.442044, 0.000000, 0.000000, 0.000000], [-0.442758, -0.644761, -0.549012, -0.437056, -0.691059, 0.000000, 0.000000, 0.000000], [-0.565243, -0.385590, -0.943729, -0.084474, -0.356853, 0.000000, 0.000000, 0.000000], [-0.402678, 0.028866, 0.146428, -0.089673, -0.865160, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.295523, 4.591127, -4.204228, -2.994314, -4.542623, 0.031604]
pre_activation_std: [1.366492, 3.774144, 2.495894, 2.037210, 3.371774, 2.539293]
### 2
mean: [0.634579, -4.286175, -0.960474, -1.463878, 2.016994, -3.936917]
std: [1.105943, 2.941538, 1.774304, 1.227194, 2.903186, 2.657603]
fourier: [[16.775551, 18.524197, 21.706410, 21.989896, 57.112106], [44.776413, 53.402258, 62.602676, 62.982650, 385.755741], [27.921832, 29.766403, 34.040687, 41.336932, 86.442644], [18.099631, 18.302121, 18.589008, 19.579121, 131.749039], [45.468067, 55.847289, 56.707860, 66.926905, 181.529474], [40.300390, 47.895429, 56.010228, 56.954068, 354.322524]]
input_correlations: [[0.556774, -0.502045, 0.081380, -0.102190, 0.061846, 0.974456, 0.000000, 0.000000], [-0.031345, -0.999327, -0.494414, -0.458262, -0.534452, 0.319402, 0.000000, 0.000000], [0.315471, -0.874611, -0.249751, -0.331125, -0.280153, 0.724277, 0.000000, 0.000000], [-0.621096, -0.480536, -0.603808, -0.379694, -0.618184, -0.692692, 0.000000, 0.000000], [-0.098743, 0.958393, 0.378187, 0.405462, 0.413574, -0.545886, 0.000000, 0.000000], [-0.058047, -0.999260, -0.499792, -0.462369, -0.540433, 0.289454, 0.000000, 0.000000]]
pre_activation_mean: [0.634579, -4.286175, -0.960474, -1.463878, 2.016994, -3.936917]
pre_activation_std: [1.105943, 2.941538, 1.774304, 1.227194, 2.903186, 2.657603]
### 4
mean: [0.426931, 1.392226, -2.049518, 0.391809, 1.047259, -0.645570]
std: [1.603932, 1.999426, 1.281404, 0.217812, 1.975084, 2.425181]
fourier: [[25.054222, 27.717996, 31.514218, 37.723730, 38.423805], [30.999657, 36.655424, 39.300640, 46.264777, 125.300294], [22.738158, 23.571416, 26.357221, 27.799192, 184.456657], [3.071452, 3.283460, 3.765525, 3.923259, 35.262852], [31.904457, 36.227537, 39.477061, 46.196336, 94.253269], [40.236950, 40.506215, 47.965062, 56.687583, 58.101269]]
input_correlations: [[0.806427, -0.397513, 0.620853, 0.176005, -0.946628, -0.409346, 0.000000, 0.000000], [-0.680629, 0.492496, -0.537580, -0.156789, 0.984643, 0.506438, 0.000000, 0.000000], [0.404418, -0.454292, 0.181565, 0.053971, -0.975158, -0.474542, 0.000000, 0.000000], [0.906483, 0.063024, 0.951066, 0.248300, -0.317233, 0.069259, 0.000000, 0.000000], [-0.649045, 0.491752, -0.477440, -0.157219, 0.994133, 0.506926, 0.000000, 0.000000], [0.765938, -0.424901, 0.595170, 0.165055, -0.964125, -0.437622, 0.000000, 0.000000]]
pre_activation_mean: [0.426931, 1.392226, -2.049518, 0.391809, 1.047259, -0.645570]
pre_activation_std: [1.603932, 1.999426, 1.281404, 0.217812, 1.975084, 2.425181]
### 6
mean: [-0.631950, 0.492214, 1.830519, 0.662160, 0.071221, 0.385438]
std: [1.930411, 1.972604, 4.103699, 1.111235, 0.338472, 2.658734]
fourier: [[29.782295, 30.082988, 30.966148, 44.640251, 56.875515], [31.444895, 33.774692, 37.709664, 44.299245, 47.511880], [65.571536, 71.756285, 79.103530, 98.270586, 164.746739], [16.467622, 16.646952, 18.429473, 24.757392, 59.594394], [4.948713, 5.342098, 5.828126, 6.246756, 6.409861], [39.773348, 42.286410, 44.843848, 48.682618, 62.234293]]
input_correlations: [[-0.961421, 0.875822, 0.693536, -0.698560, 0.841824, -0.882643, 0.000000, 0.000000], [-0.852618, 0.974902, 0.795711, -0.509876, 0.958651, -0.722181, 0.000000, 0.000000], [-0.835664, 0.981162, 0.798363, -0.490665, 0.966146, -0.706883, 0.000000, 0.000000], [0.978827, -0.822716, -0.636082, 0.755301, -0.782273, 0.927453, 0.000000, 0.000000], [-0.781129, 0.176861, -0.028561, -0.945752, 0.119497, -0.906480, 0.000000, 0.000000], [0.893464, -0.948592, -0.750119, 0.594186, -0.926468, 0.791716, 0.000000, 0.000000]]
pre_activation_mean: [-0.631950, 0.492214, 1.830519, 0.662160, 0.071221, 0.385438]
pre_activation_std: [1.930411, 1.972604, 4.103699, 1.111235, 0.338472, 2.658734]
### 8
mean: [-0.058023, -3.093482, -1.082542, -5.147516, -4.753620, 1.845467]
std: [2.285940, 1.734711, 4.352777, 1.942135, 6.226219, 4.975743]
fourier: [[33.960720, 35.297719, 38.329543, 39.163305, 54.450214], [24.084000, 25.685057, 31.401147, 34.648090, 278.413387], [70.729531, 74.472827, 84.841284, 97.428811, 105.199644], [26.688191, 30.658106, 32.523782, 39.340672, 463.276444], [105.278800, 105.916084, 130.360570, 147.675729, 427.825749], [81.625250, 85.269076, 98.374241, 119.776114, 166.092059]]
input_correlations: [[0.834900, 0.883380, 0.909225, -0.917680, 0.402698, -0.913726, 0.000000, 0.000000], [0.505730, 0.581880, 0.627477, -0.993589, 0.723587, -0.998561, 0.000000, 0.000000], [-0.929456, -0.961165, -0.975466, 0.818546, -0.226731, 0.810009, 0.000000, 0.000000], [-0.623052, -0.555231, -0.507982, -0.291938, 0.777881, -0.309003, 0.000000, 0.000000], [-0.976773, -0.993673, -0.998281, 0.711767, -0.072759, 0.699995, 0.000000, 0.000000], [0.938254, 0.967579, 0.980406, -0.804673, 0.202626, -0.795482, 0.000000, 0.000000]]
pre_activation_mean: [-0.058023, -3.093482, -1.082542, -5.147516, -4.753620, 1.845467]
pre_activation_std: [2.285940, 1.734711, 4.352777, 1.942135, 6.226219, 4.975743]
### 10
mean: [1.007009, 0.872815, 0.238039, 1.692169, 1.252836, -0.147314]
std: [0.818741, 0.632924, 2.521094, 4.044248, 1.813870, 3.276300]
fourier: [[11.523479, 12.725110, 13.001723, 16.176092, 90.630786], [9.340708, 10.195659, 11.974608, 12.044795, 78.553303], [38.967460, 41.846643, 43.066187, 49.698293, 60.925484], [68.004745, 69.616353, 79.714550, 98.443011, 152.295185], [29.355865, 32.520510, 38.821506, 40.968706, 112.755289], [50.293197, 51.169389, 55.675306, 60.546279, 79.517391]]
input_correlations: [[0.546903, 0.115635, 0.279328, 0.586581, 0.525659, 0.540631, 0.000000, 0.000000], [0.729469, -0.053186, 0.049087, 0.572018, 0.302970, 0.724981, 0.000000, 0.000000], [0.973163, -0.742093, -0.804850, 0.079487, -0.498132, 0.974696, 0.000000, 0.000000], [0.977892, -0.744161, -0.790712, 0.083427, -0.464519, 0.978945, 0.000000, 0.000000], [0.991012, -0.558523, -0.547844, 0.272437, -0.202372, 0.990119, 0.000000, 0.000000], [0.935999, -0.787214, -0.873603, -0.005245, -0.583684, 0.938603, 0.000000, 0.000000]]
pre_activation_mean: [1.007009, 0.872815, 0.238039, 1.692169, 1.252836, -0.147314]
pre_activation_std: [0.818741, 0.632924, 2.521094, 4.044248, 1.813870, 3.276300]
### 12
mean: [-1.313272]
std: [2.772020]
fourier: [[46.887726, 47.498852, 56.527939, 65.664639, 118.194481]]
input_correlations: [[-0.428405, -0.643864, -0.972014, -0.992791, -0.964812, -0.977480, 0.000000, 0.000000]]
pre_activation_mean: [-1.313272]
pre_activation_std: [2.772020]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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-0.303097
]
],
"network.12.bias": [
0.330562
]
}
## Activation Signature
### 0
mean: [0.910197, 0.754367, 1.145548, 2.551496, 1.258727, 1.341092]
std: [0.823595, 0.640934, 1.750252, 3.297669, 1.786065, 1.921414]
fourier: [[11.789807, 12.633201, 13.588245, 16.579147, 81.917749], [9.570336, 9.716782, 12.311351, 12.519212, 67.892983], [28.278217, 30.590594, 37.925012, 38.440776, 103.099321], [55.155321, 58.166226, 69.391869, 77.621853, 229.634609], [28.979326, 31.668481, 38.116385, 39.928923, 113.285376], [31.201612, 33.507993, 41.523335, 42.770157, 120.698242]]
input_correlations: [[-0.941757, -0.343837, -0.001178, 0.115589, -0.068539, 0.000000, 0.000000, 0.000000], [0.651400, 0.255832, 0.539004, 0.393048, 0.739964, 0.000000, 0.000000, 0.000000], [-0.322711, -0.535630, -0.782946, -0.552730, -0.442044, 0.000000, 0.000000, 0.000000], [-0.442758, -0.644761, -0.549012, -0.437056, -0.691059, 0.000000, 0.000000, 0.000000], [-0.565243, -0.385590, -0.943729, -0.084474, -0.356853, 0.000000, 0.000000, 0.000000], [-0.402678, 0.028866, 0.146428, -0.089673, -0.865160, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.295523, 4.591127, -4.204228, -2.994314, -4.542623, 0.031604]
pre_activation_std: [1.366492, 3.774144, 2.495894, 2.037210, 3.371774, 2.539293]
### 2
mean: [0.634579, -4.286175, -0.960474, -1.463878, 2.016994, -3.936917]
std: [1.105943, 2.941538, 1.774304, 1.227194, 2.903186, 2.657603]
fourier: [[16.775551, 18.524197, 21.706410, 21.989896, 57.112106], [44.776413, 53.402258, 62.602676, 62.982650, 385.755741], [27.921832, 29.766403, 34.040687, 41.336932, 86.442644], [18.099631, 18.302121, 18.589008, 19.579121, 131.749039], [45.468067, 55.847289, 56.707860, 66.926905, 181.529474], [40.300390, 47.895429, 56.010228, 56.954068, 354.322524]]
input_correlations: [[0.556774, -0.502045, 0.081380, -0.102190, 0.061846, 0.974456, 0.000000, 0.000000], [-0.031345, -0.999327, -0.494414, -0.458262, -0.534452, 0.319402, 0.000000, 0.000000], [0.315471, -0.874611, -0.249751, -0.331125, -0.280153, 0.724277, 0.000000, 0.000000], [-0.621096, -0.480536, -0.603808, -0.379694, -0.618184, -0.692692, 0.000000, 0.000000], [-0.098743, 0.958393, 0.378187, 0.405462, 0.413574, -0.545886, 0.000000, 0.000000], [-0.058047, -0.999260, -0.499792, -0.462369, -0.540433, 0.289454, 0.000000, 0.000000]]
pre_activation_mean: [0.634579, -4.286175, -0.960474, -1.463878, 2.016994, -3.936917]
pre_activation_std: [1.105943, 2.941538, 1.774304, 1.227194, 2.903186, 2.657603]
### 4
mean: [0.426931, 1.392226, -2.049518, 0.391809, 1.047259, -0.645570]
std: [1.603932, 1.999426, 1.281404, 0.217812, 1.975084, 2.425181]
fourier: [[25.054222, 27.717996, 31.514218, 37.723730, 38.423805], [30.999657, 36.655424, 39.300640, 46.264777, 125.300294], [22.738158, 23.571416, 26.357221, 27.799192, 184.456657], [3.071452, 3.283460, 3.765525, 3.923259, 35.262852], [31.904457, 36.227537, 39.477061, 46.196336, 94.253269], [40.236950, 40.506215, 47.965062, 56.687583, 58.101269]]
input_correlations: [[0.806427, -0.397513, 0.620853, 0.176005, -0.946628, -0.409346, 0.000000, 0.000000], [-0.680629, 0.492496, -0.537580, -0.156789, 0.984643, 0.506438, 0.000000, 0.000000], [0.404418, -0.454292, 0.181565, 0.053971, -0.975158, -0.474542, 0.000000, 0.000000], [0.906483, 0.063024, 0.951066, 0.248300, -0.317233, 0.069259, 0.000000, 0.000000], [-0.649045, 0.491752, -0.477440, -0.157219, 0.994133, 0.506926, 0.000000, 0.000000], [0.765938, -0.424901, 0.595170, 0.165055, -0.964125, -0.437622, 0.000000, 0.000000]]
pre_activation_mean: [0.426931, 1.392226, -2.049518, 0.391809, 1.047259, -0.645570]
pre_activation_std: [1.603932, 1.999426, 1.281404, 0.217812, 1.975084, 2.425181]
### 6
mean: [-0.631950, 0.492214, 1.830519, 0.662160, 0.071221, 0.385438]
std: [1.930411, 1.972604, 4.103699, 1.111235, 0.338472, 2.658734]
fourier: [[29.782295, 30.082988, 30.966148, 44.640251, 56.875515], [31.444895, 33.774692, 37.709664, 44.299245, 47.511880], [65.571536, 71.756285, 79.103530, 98.270586, 164.746739], [16.467622, 16.646952, 18.429473, 24.757392, 59.594394], [4.948713, 5.342098, 5.828126, 6.246756, 6.409861], [39.773348, 42.286410, 44.843848, 48.682618, 62.234293]]
input_correlations: [[-0.961421, 0.875822, 0.693536, -0.698560, 0.841824, -0.882643, 0.000000, 0.000000], [-0.852618, 0.974902, 0.795711, -0.509876, 0.958651, -0.722181, 0.000000, 0.000000], [-0.835664, 0.981162, 0.798363, -0.490665, 0.966146, -0.706883, 0.000000, 0.000000], [0.978827, -0.822716, -0.636082, 0.755301, -0.782273, 0.927453, 0.000000, 0.000000], [-0.781129, 0.176861, -0.028561, -0.945752, 0.119497, -0.906480, 0.000000, 0.000000], [0.893464, -0.948592, -0.750119, 0.594186, -0.926468, 0.791716, 0.000000, 0.000000]]
pre_activation_mean: [-0.631950, 0.492214, 1.830519, 0.662160, 0.071221, 0.385438]
pre_activation_std: [1.930411, 1.972604, 4.103699, 1.111235, 0.338472, 2.658734]
### 8
mean: [-0.058023, -3.093482, -1.082542, -5.147516, -4.753620, 1.845467]
std: [2.285940, 1.734711, 4.352777, 1.942135, 6.226219, 4.975743]
fourier: [[33.960720, 35.297719, 38.329543, 39.163305, 54.450214], [24.084000, 25.685057, 31.401147, 34.648090, 278.413387], [70.729531, 74.472827, 84.841284, 97.428811, 105.199644], [26.688191, 30.658106, 32.523782, 39.340672, 463.276444], [105.278800, 105.916084, 130.360570, 147.675729, 427.825749], [81.625250, 85.269076, 98.374241, 119.776114, 166.092059]]
input_correlations: [[0.834900, 0.883380, 0.909225, -0.917680, 0.402698, -0.913726, 0.000000, 0.000000], [0.505730, 0.581880, 0.627477, -0.993589, 0.723587, -0.998561, 0.000000, 0.000000], [-0.929456, -0.961165, -0.975466, 0.818546, -0.226731, 0.810009, 0.000000, 0.000000], [-0.623052, -0.555231, -0.507982, -0.291938, 0.777881, -0.309003, 0.000000, 0.000000], [-0.976773, -0.993673, -0.998281, 0.711767, -0.072759, 0.699995, 0.000000, 0.000000], [0.938254, 0.967579, 0.980406, -0.804673, 0.202626, -0.795482, 0.000000, 0.000000]]
pre_activation_mean: [-0.058023, -3.093482, -1.082542, -5.147516, -4.753620, 1.845467]
pre_activation_std: [2.285940, 1.734711, 4.352777, 1.942135, 6.226219, 4.975743]
### 10
mean: [1.007009, 0.872815, 0.238039, 1.692169, 1.252836, -0.147314]
std: [0.818741, 0.632924, 2.521094, 4.044248, 1.813870, 3.276300]
fourier: [[11.523479, 12.725110, 13.001723, 16.176092, 90.630786], [9.340708, 10.195659, 11.974608, 12.044795, 78.553303], [38.967460, 41.846643, 43.066187, 49.698293, 60.925484], [68.004745, 69.616353, 79.714550, 98.443011, 152.295185], [29.355865, 32.520510, 38.821506, 40.968706, 112.755289], [50.293197, 51.169389, 55.675306, 60.546279, 79.517391]]
input_correlations: [[0.546903, 0.115635, 0.279328, 0.586581, 0.525659, 0.540631, 0.000000, 0.000000], [0.729469, -0.053186, 0.049087, 0.572018, 0.302970, 0.724981, 0.000000, 0.000000], [0.973163, -0.742093, -0.804850, 0.079487, -0.498132, 0.974696, 0.000000, 0.000000], [0.977892, -0.744161, -0.790712, 0.083427, -0.464519, 0.978945, 0.000000, 0.000000], [0.991012, -0.558523, -0.547844, 0.272437, -0.202372, 0.990119, 0.000000, 0.000000], [0.935999, -0.787214, -0.873603, -0.005245, -0.583684, 0.938603, 0.000000, 0.000000]]
pre_activation_mean: [1.007009, 0.872815, 0.238039, 1.692169, 1.252836, -0.147314]
pre_activation_std: [0.818741, 0.632924, 2.521094, 4.044248, 1.813870, 3.276300]
### 12
mean: [-1.313272]
std: [2.772020]
fourier: [[46.887726, 47.498852, 56.527939, 65.664639, 118.194481]]
input_correlations: [[-0.428405, -0.643864, -0.972014, -0.992791, -0.964812, -0.977480, 0.000000, 0.000000]]
pre_activation_mean: [-1.313272]
pre_activation_std: [2.772020]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.9101971983909607, "std": 0.8235945105552673, "fourier": [11.789806611002552, 12.633201007475682, 13.588245186111394, 16.579146961650274, 81.9177493462339], "input_correlations": [-0.9417570763026936, -0.34383687183794054, -0.0011776013635044042, 0.1155888504986608, -0.06853892166155565, 0.0, 0.0, 0.0], "pre_activation_mean": -0.29552286863327026, "pre_activation_std": 1.3664917945861816}, "1": {"mean": 0.7543665766716003, "std": 0.6409339308738708, "fourier": [9.57033612548538, 9.716782182684712, 12.311350995730702, 12.519212031755846, 67.89298286475241], "input_correlations": [0.6513995014223419, 0.2558324904857952, 0.5390042716961643, 0.39304786677935044, 0.7399638289039103, 0.0, 0.0, 0.0], "pre_activation_mean": 4.591127395629883, "pre_activation_std": 3.774143695831299}, "2": {"mean": 1.1455479860305786, "std": 1.7502517700195312, "fourier": [28.27821711935885, 30.590593566356755, 37.92501247565583, 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"pre_activation_mean": -4.542623043060303, "pre_activation_std": 3.3717739582061768}, "5": {"mean": 1.3410916328430176, "std": 1.9214144945144653, "fourier": [31.201612144952158, 33.50799348401548, 41.523334643357046, 42.77015661897484, 120.6982418512807], "input_correlations": [-0.40267793874984786, 0.028866186687543996, 0.1464279338250289, -0.08967277957707241, -0.8651603297806159, 0.0, 0.0, 0.0], "pre_activation_mean": 0.0316038653254509, "pre_activation_std": 2.5392932891845703}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.6345789432525635, "std": 1.105942726135254, "fourier": [16.775550878414958, 18.52419695058953, 21.706409948108746, 21.989896216370884, 57.112106405198574], "input_correlations": [0.5567738895319563, -0.5020448101360779, 0.08137950040861111, -0.10219002569874945, 0.061845888641654384, 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45 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.58, "improved_accuracy": 0.96, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8890, "learning_rate": 0.024940936964749232, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.000000, 5.983624, 0.462706, 0.163651, 0.466877, 0.000000]
std: [0.000000, 5.234097, 0.202513, 0.198998, 0.158602, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [82.928740, 85.689126, 93.865620, 95.912869, 538.526084], [3.267687, 3.292109, 3.521062, 3.651710, 41.643548], [2.893882, 3.408736, 4.044393, 4.456301, 14.728559], [2.377036, 2.423670, 2.618661, 2.729594, 42.018952], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.560493, -0.287817, 0.566630, 0.044530, 0.197222, 0.000000, 0.000000, 0.000000], [-0.608218, -0.129186, -0.816833, -0.248942, -0.515821, 0.000000, 0.000000, 0.000000], [-0.543195, -0.012534, -0.261705, 0.669629, 0.488343, 0.000000, 0.000000, 0.000000], [-0.454378, -0.558765, -0.135584, -0.767002, -0.536239, 0.000000, 0.000000, 0.000000], [-0.852941, 0.070484, -0.203112, 0.487007, -0.243149, 0.000000, 0.000000, 0.000000], [-0.284417, -0.306460, -0.055374, -0.342379, 0.749580, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.738645, -1.798864, 0.494370, -2.225155, 0.629260, -0.202664]
pre_activation_std: [0.927776, 1.144781, 1.517773, 1.337756, 1.316938, 1.064680]
### 2
mean: [0.441497, 1.879169, 1.249095, 1.672227, -0.614350, 0.454850]
std: [0.402441, 1.191858, 1.046778, 1.196085, 0.424312, 0.660760]
fourier: [[5.632404, 5.950838, 6.685087, 8.557529, 39.734713], [19.296872, 20.847852, 22.207115, 22.623523, 169.125165], [15.909410, 16.042352, 18.399191, 20.336918, 112.418589], [18.604356, 20.506218, 21.868913, 22.089828, 150.500447], [6.644837, 6.908612, 7.308383, 7.417983, 55.291507], [9.600387, 10.890820, 11.038553, 12.615681, 40.936539]]
input_correlations: [[0.805526, 0.000000, 0.322221, 0.195732, 0.201203, 0.734118, 0.000000, 0.000000], [0.655580, 0.000000, 0.753750, 0.106775, 0.787851, 0.374348, 0.000000, 0.000000], [0.386679, 0.000000, 0.949741, -0.029747, 0.617384, 0.586834, 0.000000, 0.000000], [0.589882, 0.000000, 0.815815, 0.056202, 0.726129, 0.517780, 0.000000, 0.000000], [-0.182429, 0.000000, -0.852062, 0.100119, -0.141273, -0.862398, 0.000000, 0.000000], [0.417072, 0.000000, 0.898486, -0.027607, 0.482956, 0.747130, 0.000000, 0.000000]]
pre_activation_mean: [0.441497, 1.879169, 1.249095, 1.672227, -0.614350, 0.454850]
pre_activation_std: [0.402441, 1.191858, 1.046778, 1.196085, 0.424312, 0.660760]
### 4
mean: [3.461154, 1.513390, 2.754785, -1.106917, 0.156054, 2.008035]
std: [2.313458, 1.163488, 2.012908, 0.849065, 0.351638, 1.840975]
fourier: [[36.906137, 38.380405, 41.622713, 42.944876, 311.503870], [17.674916, 18.512963, 21.243255, 21.902880, 136.205068], [31.290306, 33.525319, 36.720842, 37.408967, 247.930670], [13.428287, 13.666048, 15.045549, 15.995001, 99.622516], [5.389728, 5.939048, 6.019601, 6.165236, 14.044843], [29.179755, 29.417232, 32.899076, 34.672120, 180.723165]]
input_correlations: [[0.720496, 0.975250, 0.962069, 0.997903, 0.000000, 0.921326, 0.000000, 0.000000], [0.627691, 0.969732, 0.979651, 0.991200, 0.000000, 0.919977, 0.000000, 0.000000], [0.682780, 0.980035, 0.965808, 0.998353, 0.000000, 0.912885, 0.000000, 0.000000], [-0.709811, -0.962355, -0.974726, -0.992781, 0.000000, -0.941824, 0.000000, 0.000000], [-0.918705, -0.868549, -0.850821, -0.914719, 0.000000, -0.892510, 0.000000, 0.000000], [0.700014, 0.964205, 0.976096, 0.993822, 0.000000, 0.939105, 0.000000, 0.000000]]
pre_activation_mean: [3.461154, 1.513390, 2.754785, -1.106917, 0.156054, 2.008035]
pre_activation_std: [2.313458, 1.163488, 2.012908, 0.849065, 0.351638, 1.840975]
### 6
mean: [-2.822085, -0.798342, 4.744173, 0.236769, -2.502585, 3.697545]
std: [1.899598, 0.581843, 4.125844, 0.190886, 1.710281, 2.936479]
fourier: [[30.032304, 31.548453, 34.433925, 35.123052, 253.987644], [9.276654, 9.869074, 10.544226, 10.610717, 71.850811], [65.396969, 67.925882, 74.698776, 76.248114, 426.975521], [3.191720, 3.280966, 3.284233, 3.349129, 21.309253], [26.991291, 27.674262, 30.799437, 32.018646, 225.232636], [46.215564, 48.331671, 53.365731, 54.292514, 332.779016]]
input_correlations: [[-0.999698, -0.994485, -0.999360, 0.000000, 0.845850, -0.996544, 0.000000, 0.000000], [-0.999142, -0.988027, -0.996623, 0.000000, 0.871925, -0.992374, 0.000000, 0.000000], [0.999426, 0.994914, 0.999011, 0.000000, -0.841372, 0.997704, 0.000000, 0.000000], [-0.984226, -0.954180, -0.973914, 0.000000, 0.897224, -0.974349, 0.000000, 0.000000], [-0.998446, -0.996808, -0.998995, 0.000000, 0.827350, -0.998278, 0.000000, 0.000000], [0.998930, 0.996320, 0.999393, 0.000000, -0.837086, 0.997510, 0.000000, 0.000000]]
pre_activation_mean: [-2.822085, -0.798342, 4.744173, 0.236769, -2.502585, 3.697545]
pre_activation_std: [1.899598, 0.581843, 4.125844, 0.190886, 1.710281, 2.936479]
### 8
mean: [-1.100482, 3.911664, -0.320245, 3.657821, 1.611666, 3.070210]
std: [0.795997, 3.639524, 0.216718, 3.053987, 0.859785, 2.675418]
fourier: [[12.555110, 13.361864, 14.513718, 14.541770, 99.043357], [57.868633, 60.113401, 65.775000, 66.668584, 352.049789], [3.542290, 3.567879, 3.808786, 3.842473, 28.822062], [48.373441, 50.229823, 55.267637, 56.225289, 329.203872], [13.516125, 14.211057, 15.664657, 15.858298, 145.049895], [42.515318, 44.216640, 48.381679, 49.012827, 276.318847]]
input_correlations: [[0.000000, 0.000000, -0.998455, 0.949958, 0.000000, -0.999549, 0.000000, 0.000000], [0.000000, 0.000000, 0.999922, -0.942773, 0.000000, 0.999627, 0.000000, 0.000000], [0.000000, 0.000000, -0.995162, 0.938421, 0.000000, -0.991148, 0.000000, 0.000000], [0.000000, 0.000000, 0.999847, -0.940748, 0.000000, 0.999834, 0.000000, 0.000000], [0.000000, 0.000000, 0.998993, -0.942772, 0.000000, 0.999947, 0.000000, 0.000000], [0.000000, 0.000000, 0.999892, -0.943062, 0.000000, 0.999681, 0.000000, 0.000000]]
pre_activation_mean: [-1.100482, 3.911664, -0.320245, 3.657821, 1.611666, 3.070210]
pre_activation_std: [0.795997, 3.639524, 0.216718, 3.053987, 0.859785, 2.675418]
### 10
mean: [-2.224838, 5.957208, 0.457798, -0.025189, 0.466019, -0.800088]
std: [1.773224, 5.264582, 0.215334, 0.431160, 0.161279, 0.408827]
fourier: [[28.096465, 29.122149, 31.861085, 32.489376, 200.235426], [83.458723, 86.384445, 94.652923, 96.495780, 536.148713], [3.475484, 3.513591, 3.802717, 3.863634, 41.201808], [6.054926, 6.920964, 7.143426, 7.840372, 7.865439], [2.449794, 2.491043, 2.648389, 2.802405, 41.941746], [6.382572, 6.587236, 7.137049, 7.450719, 72.007912]]
input_correlations: [[0.000000, -0.999822, 0.000000, -0.999748, -0.998448, -0.999980, 0.000000, 0.000000], [0.000000, 0.999790, 0.000000, 0.999792, 0.998530, 0.999982, 0.000000, 0.000000], [0.000000, -0.998260, 0.000000, -0.995361, -0.991484, -0.996925, 0.000000, 0.000000], [0.000000, -0.998591, 0.000000, -0.999850, -0.999460, -0.999566, 0.000000, 0.000000], [0.000000, -0.974129, 0.000000, -0.964227, -0.954721, -0.968633, 0.000000, 0.000000], [0.000000, -0.998074, 0.000000, -0.994730, -0.990914, -0.996330, 0.000000, 0.000000]]
pre_activation_mean: [-2.224838, 5.957208, 0.457798, -0.025189, 0.466019, -0.800088]
pre_activation_std: [1.773224, 5.264582, 0.215334, 0.431160, 0.161279, 0.408827]
### 12
mean: [-2.341736]
std: [2.751251]
fourier: [[43.661561, 45.481749, 49.638441, 50.035259, 210.756189]]
input_correlations: [[0.000000, -0.999890, 0.992460, 0.812806, 0.971607, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.341736]
pre_activation_std: [2.751251]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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0.099544,
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0.205367
],
[
-0.04037,
-0.314367,
0.386587,
-0.056267,
-0.254044,
0.505417
],
[
-0.098257,
-0.163204,
-0.051681,
-0.078195,
-0.383689,
0.360314
],
[
-0.292501,
-0.26428,
0.450471,
-0.419726,
0.053336,
0.269164
]
],
"network.8.bias": [
-0.252953,
-0.246733,
-0.151064,
-0.057979,
0.546512,
0.012639
],
"network.10.weight": [
[
0.246586,
-0.234395,
0.157002,
0.039836,
-0.309397,
-0.301392
],
[
-0.214676,
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0.610782,
0.119302,
0.397397
],
[
0.054172,
0.012352,
-0.103466,
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0.409623,
-0.218562
],
[
0.346692,
0.169127,
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-0.185995,
0.275327,
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],
[
0.013331,
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0.014148,
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0.499578,
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],
[
0.304542,
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0.108237,
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0.066198
]
],
"network.10.bias": [
-0.004117,
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0.464286,
0.36127,
0.308916,
-0.292984
],
"network.12.weight": [
[
0.218058,
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0.517095,
0.326865,
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0.116464
]
],
"network.12.bias": [
0.007874
]
}
## Activation Signature
### 0
mean: [0.000000, 5.983624, 0.462706, 0.163651, 0.466877, 0.000000]
std: [0.000000, 5.234097, 0.202513, 0.198998, 0.158602, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [82.928740, 85.689126, 93.865620, 95.912869, 538.526084], [3.267687, 3.292109, 3.521062, 3.651710, 41.643548], [2.893882, 3.408736, 4.044393, 4.456301, 14.728559], [2.377036, 2.423670, 2.618661, 2.729594, 42.018952], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.560493, -0.287817, 0.566630, 0.044530, 0.197222, 0.000000, 0.000000, 0.000000], [-0.608218, -0.129186, -0.816833, -0.248942, -0.515821, 0.000000, 0.000000, 0.000000], [-0.543195, -0.012534, -0.261705, 0.669629, 0.488343, 0.000000, 0.000000, 0.000000], [-0.454378, -0.558765, -0.135584, -0.767002, -0.536239, 0.000000, 0.000000, 0.000000], [-0.852941, 0.070484, -0.203112, 0.487007, -0.243149, 0.000000, 0.000000, 0.000000], [-0.284417, -0.306460, -0.055374, -0.342379, 0.749580, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.738645, -1.798864, 0.494370, -2.225155, 0.629260, -0.202664]
pre_activation_std: [0.927776, 1.144781, 1.517773, 1.337756, 1.316938, 1.064680]
### 2
mean: [0.441497, 1.879169, 1.249095, 1.672227, -0.614350, 0.454850]
std: [0.402441, 1.191858, 1.046778, 1.196085, 0.424312, 0.660760]
fourier: [[5.632404, 5.950838, 6.685087, 8.557529, 39.734713], [19.296872, 20.847852, 22.207115, 22.623523, 169.125165], [15.909410, 16.042352, 18.399191, 20.336918, 112.418589], [18.604356, 20.506218, 21.868913, 22.089828, 150.500447], [6.644837, 6.908612, 7.308383, 7.417983, 55.291507], [9.600387, 10.890820, 11.038553, 12.615681, 40.936539]]
input_correlations: [[0.805526, 0.000000, 0.322221, 0.195732, 0.201203, 0.734118, 0.000000, 0.000000], [0.655580, 0.000000, 0.753750, 0.106775, 0.787851, 0.374348, 0.000000, 0.000000], [0.386679, 0.000000, 0.949741, -0.029747, 0.617384, 0.586834, 0.000000, 0.000000], [0.589882, 0.000000, 0.815815, 0.056202, 0.726129, 0.517780, 0.000000, 0.000000], [-0.182429, 0.000000, -0.852062, 0.100119, -0.141273, -0.862398, 0.000000, 0.000000], [0.417072, 0.000000, 0.898486, -0.027607, 0.482956, 0.747130, 0.000000, 0.000000]]
pre_activation_mean: [0.441497, 1.879169, 1.249095, 1.672227, -0.614350, 0.454850]
pre_activation_std: [0.402441, 1.191858, 1.046778, 1.196085, 0.424312, 0.660760]
### 4
mean: [3.461154, 1.513390, 2.754785, -1.106917, 0.156054, 2.008035]
std: [2.313458, 1.163488, 2.012908, 0.849065, 0.351638, 1.840975]
fourier: [[36.906137, 38.380405, 41.622713, 42.944876, 311.503870], [17.674916, 18.512963, 21.243255, 21.902880, 136.205068], [31.290306, 33.525319, 36.720842, 37.408967, 247.930670], [13.428287, 13.666048, 15.045549, 15.995001, 99.622516], [5.389728, 5.939048, 6.019601, 6.165236, 14.044843], [29.179755, 29.417232, 32.899076, 34.672120, 180.723165]]
input_correlations: [[0.720496, 0.975250, 0.962069, 0.997903, 0.000000, 0.921326, 0.000000, 0.000000], [0.627691, 0.969732, 0.979651, 0.991200, 0.000000, 0.919977, 0.000000, 0.000000], [0.682780, 0.980035, 0.965808, 0.998353, 0.000000, 0.912885, 0.000000, 0.000000], [-0.709811, -0.962355, -0.974726, -0.992781, 0.000000, -0.941824, 0.000000, 0.000000], [-0.918705, -0.868549, -0.850821, -0.914719, 0.000000, -0.892510, 0.000000, 0.000000], [0.700014, 0.964205, 0.976096, 0.993822, 0.000000, 0.939105, 0.000000, 0.000000]]
pre_activation_mean: [3.461154, 1.513390, 2.754785, -1.106917, 0.156054, 2.008035]
pre_activation_std: [2.313458, 1.163488, 2.012908, 0.849065, 0.351638, 1.840975]
### 6
mean: [-2.822085, -0.798342, 4.744173, 0.236769, -2.502585, 3.697545]
std: [1.899598, 0.581843, 4.125844, 0.190886, 1.710281, 2.936479]
fourier: [[30.032304, 31.548453, 34.433925, 35.123052, 253.987644], [9.276654, 9.869074, 10.544226, 10.610717, 71.850811], [65.396969, 67.925882, 74.698776, 76.248114, 426.975521], [3.191720, 3.280966, 3.284233, 3.349129, 21.309253], [26.991291, 27.674262, 30.799437, 32.018646, 225.232636], [46.215564, 48.331671, 53.365731, 54.292514, 332.779016]]
input_correlations: [[-0.999698, -0.994485, -0.999360, 0.000000, 0.845850, -0.996544, 0.000000, 0.000000], [-0.999142, -0.988027, -0.996623, 0.000000, 0.871925, -0.992374, 0.000000, 0.000000], [0.999426, 0.994914, 0.999011, 0.000000, -0.841372, 0.997704, 0.000000, 0.000000], [-0.984226, -0.954180, -0.973914, 0.000000, 0.897224, -0.974349, 0.000000, 0.000000], [-0.998446, -0.996808, -0.998995, 0.000000, 0.827350, -0.998278, 0.000000, 0.000000], [0.998930, 0.996320, 0.999393, 0.000000, -0.837086, 0.997510, 0.000000, 0.000000]]
pre_activation_mean: [-2.822085, -0.798342, 4.744173, 0.236769, -2.502585, 3.697545]
pre_activation_std: [1.899598, 0.581843, 4.125844, 0.190886, 1.710281, 2.936479]
### 8
mean: [-1.100482, 3.911664, -0.320245, 3.657821, 1.611666, 3.070210]
std: [0.795997, 3.639524, 0.216718, 3.053987, 0.859785, 2.675418]
fourier: [[12.555110, 13.361864, 14.513718, 14.541770, 99.043357], [57.868633, 60.113401, 65.775000, 66.668584, 352.049789], [3.542290, 3.567879, 3.808786, 3.842473, 28.822062], [48.373441, 50.229823, 55.267637, 56.225289, 329.203872], [13.516125, 14.211057, 15.664657, 15.858298, 145.049895], [42.515318, 44.216640, 48.381679, 49.012827, 276.318847]]
input_correlations: [[0.000000, 0.000000, -0.998455, 0.949958, 0.000000, -0.999549, 0.000000, 0.000000], [0.000000, 0.000000, 0.999922, -0.942773, 0.000000, 0.999627, 0.000000, 0.000000], [0.000000, 0.000000, -0.995162, 0.938421, 0.000000, -0.991148, 0.000000, 0.000000], [0.000000, 0.000000, 0.999847, -0.940748, 0.000000, 0.999834, 0.000000, 0.000000], [0.000000, 0.000000, 0.998993, -0.942772, 0.000000, 0.999947, 0.000000, 0.000000], [0.000000, 0.000000, 0.999892, -0.943062, 0.000000, 0.999681, 0.000000, 0.000000]]
pre_activation_mean: [-1.100482, 3.911664, -0.320245, 3.657821, 1.611666, 3.070210]
pre_activation_std: [0.795997, 3.639524, 0.216718, 3.053987, 0.859785, 2.675418]
### 10
mean: [-2.224838, 5.957208, 0.457798, -0.025189, 0.466019, -0.800088]
std: [1.773224, 5.264582, 0.215334, 0.431160, 0.161279, 0.408827]
fourier: [[28.096465, 29.122149, 31.861085, 32.489376, 200.235426], [83.458723, 86.384445, 94.652923, 96.495780, 536.148713], [3.475484, 3.513591, 3.802717, 3.863634, 41.201808], [6.054926, 6.920964, 7.143426, 7.840372, 7.865439], [2.449794, 2.491043, 2.648389, 2.802405, 41.941746], [6.382572, 6.587236, 7.137049, 7.450719, 72.007912]]
input_correlations: [[0.000000, -0.999822, 0.000000, -0.999748, -0.998448, -0.999980, 0.000000, 0.000000], [0.000000, 0.999790, 0.000000, 0.999792, 0.998530, 0.999982, 0.000000, 0.000000], [0.000000, -0.998260, 0.000000, -0.995361, -0.991484, -0.996925, 0.000000, 0.000000], [0.000000, -0.998591, 0.000000, -0.999850, -0.999460, -0.999566, 0.000000, 0.000000], [0.000000, -0.974129, 0.000000, -0.964227, -0.954721, -0.968633, 0.000000, 0.000000], [0.000000, -0.998074, 0.000000, -0.994730, -0.990914, -0.996330, 0.000000, 0.000000]]
pre_activation_mean: [-2.224838, 5.957208, 0.457798, -0.025189, 0.466019, -0.800088]
pre_activation_std: [1.773224, 5.264582, 0.215334, 0.431160, 0.161279, 0.408827]
### 12
mean: [-2.341736]
std: [2.751251]
fourier: [[43.661561, 45.481749, 49.638441, 50.035259, 210.756189]]
input_correlations: [[0.000000, -0.999890, 0.992460, 0.812806, 0.971607, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.341736]
pre_activation_std: [2.751251]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.5604932782032348, -0.28781721893269846, 0.5666300673274794, 0.044529895541988135, 0.1972222600943358, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7386450171470642, "pre_activation_std": 0.9277756214141846}, "1": {"mean": 5.983623504638672, "std": 5.234096527099609, "fourier": [82.92873968735107, 85.68912573234368, 93.8656197668879, 95.91286865373002, 538.5260842442513], "input_correlations": [-0.608217768910898, -0.12918607181184583, -0.816832596777855, -0.24894191448291092, -0.5158213871899722, 0.0, 0.0, 0.0], "pre_activation_mean": -1.7988641262054443, "pre_activation_std": 1.1447813510894775}, "2": {"mean": 0.4627060890197754, "std": 0.20251253247261047, "fourier": [3.267687213874404, 3.292109121295116, 3.5210615406756713, 3.6517097073632145, 41.643547505140305], "input_correlations": [-0.5431953156287466, 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{"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.2844165317327954, -0.3064602304129945, -0.055373975333656046, -0.3423791226588736, 0.7495801148736919, 0.0, 0.0, 0.0], "pre_activation_mean": -0.20266373455524445, "pre_activation_std": 1.064679741859436}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.44149672985076904, "std": 0.4024412930011749, "fourier": [5.6324044229933685, 5.950837859469302, 6.685087324218393, 8.557529320682905, 39.734713293612], "input_correlations": [0.8055258873394363, 0.0, 0.3222210852903018, 0.19573177737251476, 0.20120272492117788, 0.7341184807555384, 0.0, 0.0], "pre_activation_mean": 0.44149672985076904, "pre_activation_std": 0.4024412930011749}, "1": {"mean": 1.8791685104370117, "std": 1.1918582916259766, "fourier": [19.29687221693194, 20.84785177421311, 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46 | {"target_pattern": "starts_with", "degraded_accuracy": 0.6, "improved_accuracy": 0.88, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1794, "learning_rate": 0.045307675361688976, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [0.713187, 0.401231, 0.231124, 1.324339, 1.605992, 2.046923, 1.040841]
std: [0.556669, 0.276316, 0.731170, 0.918348, 1.123953, 1.714015, 0.909311]
fourier: [[8.908274, 10.084502, 10.604600, 11.125305, 64.186837], [4.346466, 4.680793, 5.351051, 5.480039, 36.110752], [11.402948, 12.679547, 13.948106, 14.725151, 20.801176], [14.456926, 16.472366, 17.422112, 19.094676, 119.190514], [17.804390, 20.095498, 21.464445, 23.178911, 144.539284], [27.373089, 30.161738, 32.801272, 33.934493, 184.223090], [14.512099, 16.096803, 17.343345, 17.961320, 93.675639]]
input_correlations: [[0.805716, 0.706096, 0.437641, 0.173778, -0.170553, 0.000000, 0.000000, 0.000000], [-0.095393, -0.092557, -0.328646, 0.814222, 0.408738, 0.000000, 0.000000, 0.000000], [-0.157033, -0.178211, -0.219198, -0.423201, -0.954254, 0.000000, 0.000000, 0.000000], [0.632709, 0.048449, 0.762256, -0.191641, -0.181677, 0.000000, 0.000000, 0.000000], [-0.371827, 0.459189, -0.592493, 0.585005, -0.240218, 0.000000, 0.000000, 0.000000], [-0.807815, -0.205769, -0.094897, 0.206619, 0.420148, 0.000000, 0.000000, 0.000000], [-0.642773, -0.080552, 0.298346, 0.060772, 0.482236, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.996952, 0.895442, -2.060748, 1.022127, 0.248457, 0.233217, 0.099093]
pre_activation_std: [2.250575, 1.934661, 2.000711, 1.503711, 1.699252, 1.842023, 1.662844]
### 2
mean: [-0.985725, 0.518173, -0.245421, -0.647054, -0.329124, 0.197011, 1.684065]
std: [1.617584, 1.364304, 0.955050, 1.251583, 0.597580, 0.989571, 1.988513]
fourier: [[24.630333, 27.038993, 27.823007, 28.247465, 88.715250], [19.373351, 19.782391, 25.482886, 30.961011, 46.635551], [14.322354, 14.733605, 15.703020, 16.299463, 22.087909], [19.460302, 21.990376, 23.556178, 26.090518, 58.234860], [9.732036, 9.950067, 10.167745, 10.618556, 29.621175], [17.434690, 17.731024, 18.667658, 20.063737, 22.297305], [29.262907, 29.844991, 39.118127, 39.985496, 151.565853]]
input_correlations: [[-0.518348, -0.616827, 0.028110, -0.019919, -0.552148, 0.248515, 0.485019, 0.000000], [-0.558680, 0.467786, 0.453510, -0.438414, 0.182096, 0.972299, 0.851528, 0.000000], [-0.454502, 0.610905, 0.001032, -0.684789, 0.777848, 0.179024, -0.213741, 0.000000], [-0.892975, 0.525286, 0.220021, -0.739313, 0.068721, 0.575764, 0.281962, 0.000000], [-0.907987, 0.366715, 0.085808, -0.410183, -0.053989, 0.424784, 0.314723, 0.000000], [-0.312027, 0.178940, 0.273620, 0.202886, -0.731641, 0.451500, 0.559807, 0.000000], [0.947576, -0.265371, -0.219262, 0.723101, 0.040699, -0.639449, -0.427402, 0.000000]]
pre_activation_mean: [-0.985725, 0.518173, -0.245421, -0.647054, -0.329124, 0.197011, 1.684065]
pre_activation_std: [1.617584, 1.364304, 0.955050, 1.251583, 0.597580, 0.989571, 1.988513]
### 4
mean: [-0.341608, 0.956211, 1.065499, 0.218018, 0.097516, 0.257522, -0.556868]
std: [0.586045, 1.238211, 1.107834, 1.101330, 0.618146, 1.231609, 0.686043]
fourier: [[10.531389, 10.604937, 11.456894, 11.706749, 30.744713], [19.281757, 20.728649, 21.694395, 28.248015, 86.058964], [17.630322, 17.940250, 18.891980, 26.046106, 95.894956], [17.634661, 19.621619, 20.532934, 20.984933, 22.788702], [8.825864, 9.720037, 9.937880, 10.615358, 11.236011], [18.893873, 20.561918, 22.071831, 23.176950, 28.138685], [11.088671, 11.155043, 11.654975, 14.037728, 50.118089]]
input_correlations: [[0.471917, 0.593874, 0.117829, 0.343888, 0.402602, 0.320284, -0.958059, 0.000000], [-0.294548, -0.712332, -0.307899, -0.598965, -0.580604, -0.447690, 0.926326, 0.000000], [-0.339814, -0.801309, -0.339966, -0.624234, -0.579563, -0.500185, 0.864784, 0.000000], [0.573372, 0.793824, 0.341409, 0.438211, 0.455229, 0.501329, -0.793894, 0.000000], [-0.168742, 0.634434, 0.039022, 0.915731, 0.790714, 0.763700, -0.356116, 0.000000], [-0.313804, -0.820753, -0.075861, -0.702034, -0.657964, -0.638513, 0.862040, 0.000000], [-0.098438, 0.416086, 0.488584, 0.449181, 0.374663, 0.006799, -0.823861, 0.000000]]
pre_activation_mean: [-0.341608, 0.956211, 1.065499, 0.218018, 0.097516, 0.257522, -0.556868]
pre_activation_std: [0.586045, 1.238211, 1.107834, 1.101330, 0.618146, 1.231609, 0.686043]
### 6
mean: [-0.935336, -0.521347, 1.640098, 0.900429, -0.402919, -0.511532, -0.104149]
std: [1.260106, 0.588378, 1.603807, 1.241781, 0.738520, 0.158334, 0.827640]
fourier: [[22.409061, 23.036128, 23.690792, 24.644596, 84.180259], [9.698983, 10.461323, 11.693023, 12.131616, 46.921234], [25.246786, 28.395201, 28.664795, 35.220772, 147.608781], [18.812706, 21.315155, 22.810469, 27.219174, 81.038591], [12.386586, 12.792736, 14.629602, 14.698365, 36.262714], [2.284240, 2.423304, 2.504071, 2.637620, 46.037841], [13.009451, 13.265957, 14.902712, 15.035663, 17.705537]]
input_correlations: [[0.737193, -0.961431, -0.971375, 0.734272, 0.161330, -0.886170, 0.395756, 0.000000], [0.817035, -0.890064, -0.929130, 0.844525, 0.179680, -0.766773, 0.543074, 0.000000], [-0.706733, 0.965475, 0.986060, -0.759033, -0.440248, 0.885321, -0.483597, 0.000000], [-0.695696, 0.962311, 0.979161, -0.744166, -0.479700, 0.896561, -0.449372, 0.000000], [0.839559, -0.903452, -0.931935, 0.842257, 0.187365, -0.823903, 0.409118, 0.000000], [0.377947, -0.333809, -0.375913, 0.417985, 0.185657, -0.159583, 0.947581, 0.000000], [0.828007, -0.855627, -0.885074, 0.815208, 0.025944, -0.769895, 0.453571, 0.000000]]
pre_activation_mean: [-0.935336, -0.521347, 1.640098, 0.900429, -0.402919, -0.511532, -0.104149]
pre_activation_std: [1.260106, 0.588378, 1.603807, 1.241781, 0.738520, 0.158334, 0.827640]
### 8
mean: [0.756864, 0.424842, -2.194228, 1.343616, 1.614105, 2.053901, 1.066341]
std: [0.727550, 0.626948, 2.797433, 1.023423, 1.210322, 1.755744, 1.002709]
fourier: [[11.772144, 11.941112, 14.473906, 15.731283, 68.117741], [9.260772, 11.502841, 12.257279, 12.279166, 38.235739], [46.254345, 52.339440, 52.689246, 56.958292, 197.480540], [16.792351, 16.920020, 19.926324, 22.343680, 120.925407], [20.139319, 20.530528, 23.478955, 26.071613, 145.269394], [29.088073, 32.647699, 33.110150, 35.191414, 184.851076], [16.779289, 17.439156, 19.452500, 21.229474, 95.970655]]
input_correlations: [[-0.748967, -0.807271, 0.876587, 0.836610, -0.831639, -0.493175, -0.892592, 0.000000], [-0.921103, -0.935650, 0.666480, 0.613827, -0.961308, -0.525728, -0.988238, 0.000000], [0.502931, 0.578393, -0.984593, -0.968324, 0.623324, 0.353960, 0.702666, 0.000000], [-0.681977, -0.744719, 0.921292, 0.886671, -0.777834, -0.451341, -0.840364, 0.000000], [-0.635434, -0.706362, 0.943204, 0.912842, -0.737736, -0.438672, -0.808885, 0.000000], [-0.477479, -0.564734, 0.987970, 0.974551, -0.598616, -0.368513, -0.685691, 0.000000], [-0.593063, -0.670471, 0.958940, 0.934868, -0.701396, -0.424304, -0.775429, 0.000000]]
pre_activation_mean: [0.756864, 0.424842, -2.194228, 1.343616, 1.614105, 2.053901, 1.066341]
pre_activation_std: [0.727550, 0.626948, 2.797433, 1.023423, 1.210322, 1.755744, 1.002709]
### 10
mean: [-4.222393]
std: [3.323658]
fourier: [[53.264068, 61.723756, 62.009946, 69.090519, 380.015323]]
input_correlations: [[-0.997234, -0.964959, 0.571583, -0.998678, -0.998188, -0.985473, -0.986943, 0.000000]]
pre_activation_mean: [-4.222393]
pre_activation_std: [3.323658]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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[
0.320658,
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[
-0.211472,
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"network.6.bias": [
0.088946,
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"network.8.weight": [
[
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [0.713187, 0.401231, 0.231124, 1.324339, 1.605992, 2.046923, 1.040841]
std: [0.556669, 0.276316, 0.731170, 0.918348, 1.123953, 1.714015, 0.909311]
fourier: [[8.908274, 10.084502, 10.604600, 11.125305, 64.186837], [4.346466, 4.680793, 5.351051, 5.480039, 36.110752], [11.402948, 12.679547, 13.948106, 14.725151, 20.801176], [14.456926, 16.472366, 17.422112, 19.094676, 119.190514], [17.804390, 20.095498, 21.464445, 23.178911, 144.539284], [27.373089, 30.161738, 32.801272, 33.934493, 184.223090], [14.512099, 16.096803, 17.343345, 17.961320, 93.675639]]
input_correlations: [[0.805716, 0.706096, 0.437641, 0.173778, -0.170553, 0.000000, 0.000000, 0.000000], [-0.095393, -0.092557, -0.328646, 0.814222, 0.408738, 0.000000, 0.000000, 0.000000], [-0.157033, -0.178211, -0.219198, -0.423201, -0.954254, 0.000000, 0.000000, 0.000000], [0.632709, 0.048449, 0.762256, -0.191641, -0.181677, 0.000000, 0.000000, 0.000000], [-0.371827, 0.459189, -0.592493, 0.585005, -0.240218, 0.000000, 0.000000, 0.000000], [-0.807815, -0.205769, -0.094897, 0.206619, 0.420148, 0.000000, 0.000000, 0.000000], [-0.642773, -0.080552, 0.298346, 0.060772, 0.482236, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.996952, 0.895442, -2.060748, 1.022127, 0.248457, 0.233217, 0.099093]
pre_activation_std: [2.250575, 1.934661, 2.000711, 1.503711, 1.699252, 1.842023, 1.662844]
### 2
mean: [-0.985725, 0.518173, -0.245421, -0.647054, -0.329124, 0.197011, 1.684065]
std: [1.617584, 1.364304, 0.955050, 1.251583, 0.597580, 0.989571, 1.988513]
fourier: [[24.630333, 27.038993, 27.823007, 28.247465, 88.715250], [19.373351, 19.782391, 25.482886, 30.961011, 46.635551], [14.322354, 14.733605, 15.703020, 16.299463, 22.087909], [19.460302, 21.990376, 23.556178, 26.090518, 58.234860], [9.732036, 9.950067, 10.167745, 10.618556, 29.621175], [17.434690, 17.731024, 18.667658, 20.063737, 22.297305], [29.262907, 29.844991, 39.118127, 39.985496, 151.565853]]
input_correlations: [[-0.518348, -0.616827, 0.028110, -0.019919, -0.552148, 0.248515, 0.485019, 0.000000], [-0.558680, 0.467786, 0.453510, -0.438414, 0.182096, 0.972299, 0.851528, 0.000000], [-0.454502, 0.610905, 0.001032, -0.684789, 0.777848, 0.179024, -0.213741, 0.000000], [-0.892975, 0.525286, 0.220021, -0.739313, 0.068721, 0.575764, 0.281962, 0.000000], [-0.907987, 0.366715, 0.085808, -0.410183, -0.053989, 0.424784, 0.314723, 0.000000], [-0.312027, 0.178940, 0.273620, 0.202886, -0.731641, 0.451500, 0.559807, 0.000000], [0.947576, -0.265371, -0.219262, 0.723101, 0.040699, -0.639449, -0.427402, 0.000000]]
pre_activation_mean: [-0.985725, 0.518173, -0.245421, -0.647054, -0.329124, 0.197011, 1.684065]
pre_activation_std: [1.617584, 1.364304, 0.955050, 1.251583, 0.597580, 0.989571, 1.988513]
### 4
mean: [-0.341608, 0.956211, 1.065499, 0.218018, 0.097516, 0.257522, -0.556868]
std: [0.586045, 1.238211, 1.107834, 1.101330, 0.618146, 1.231609, 0.686043]
fourier: [[10.531389, 10.604937, 11.456894, 11.706749, 30.744713], [19.281757, 20.728649, 21.694395, 28.248015, 86.058964], [17.630322, 17.940250, 18.891980, 26.046106, 95.894956], [17.634661, 19.621619, 20.532934, 20.984933, 22.788702], [8.825864, 9.720037, 9.937880, 10.615358, 11.236011], [18.893873, 20.561918, 22.071831, 23.176950, 28.138685], [11.088671, 11.155043, 11.654975, 14.037728, 50.118089]]
input_correlations: [[0.471917, 0.593874, 0.117829, 0.343888, 0.402602, 0.320284, -0.958059, 0.000000], [-0.294548, -0.712332, -0.307899, -0.598965, -0.580604, -0.447690, 0.926326, 0.000000], [-0.339814, -0.801309, -0.339966, -0.624234, -0.579563, -0.500185, 0.864784, 0.000000], [0.573372, 0.793824, 0.341409, 0.438211, 0.455229, 0.501329, -0.793894, 0.000000], [-0.168742, 0.634434, 0.039022, 0.915731, 0.790714, 0.763700, -0.356116, 0.000000], [-0.313804, -0.820753, -0.075861, -0.702034, -0.657964, -0.638513, 0.862040, 0.000000], [-0.098438, 0.416086, 0.488584, 0.449181, 0.374663, 0.006799, -0.823861, 0.000000]]
pre_activation_mean: [-0.341608, 0.956211, 1.065499, 0.218018, 0.097516, 0.257522, -0.556868]
pre_activation_std: [0.586045, 1.238211, 1.107834, 1.101330, 0.618146, 1.231609, 0.686043]
### 6
mean: [-0.935336, -0.521347, 1.640098, 0.900429, -0.402919, -0.511532, -0.104149]
std: [1.260106, 0.588378, 1.603807, 1.241781, 0.738520, 0.158334, 0.827640]
fourier: [[22.409061, 23.036128, 23.690792, 24.644596, 84.180259], [9.698983, 10.461323, 11.693023, 12.131616, 46.921234], [25.246786, 28.395201, 28.664795, 35.220772, 147.608781], [18.812706, 21.315155, 22.810469, 27.219174, 81.038591], [12.386586, 12.792736, 14.629602, 14.698365, 36.262714], [2.284240, 2.423304, 2.504071, 2.637620, 46.037841], [13.009451, 13.265957, 14.902712, 15.035663, 17.705537]]
input_correlations: [[0.737193, -0.961431, -0.971375, 0.734272, 0.161330, -0.886170, 0.395756, 0.000000], [0.817035, -0.890064, -0.929130, 0.844525, 0.179680, -0.766773, 0.543074, 0.000000], [-0.706733, 0.965475, 0.986060, -0.759033, -0.440248, 0.885321, -0.483597, 0.000000], [-0.695696, 0.962311, 0.979161, -0.744166, -0.479700, 0.896561, -0.449372, 0.000000], [0.839559, -0.903452, -0.931935, 0.842257, 0.187365, -0.823903, 0.409118, 0.000000], [0.377947, -0.333809, -0.375913, 0.417985, 0.185657, -0.159583, 0.947581, 0.000000], [0.828007, -0.855627, -0.885074, 0.815208, 0.025944, -0.769895, 0.453571, 0.000000]]
pre_activation_mean: [-0.935336, -0.521347, 1.640098, 0.900429, -0.402919, -0.511532, -0.104149]
pre_activation_std: [1.260106, 0.588378, 1.603807, 1.241781, 0.738520, 0.158334, 0.827640]
### 8
mean: [0.756864, 0.424842, -2.194228, 1.343616, 1.614105, 2.053901, 1.066341]
std: [0.727550, 0.626948, 2.797433, 1.023423, 1.210322, 1.755744, 1.002709]
fourier: [[11.772144, 11.941112, 14.473906, 15.731283, 68.117741], [9.260772, 11.502841, 12.257279, 12.279166, 38.235739], [46.254345, 52.339440, 52.689246, 56.958292, 197.480540], [16.792351, 16.920020, 19.926324, 22.343680, 120.925407], [20.139319, 20.530528, 23.478955, 26.071613, 145.269394], [29.088073, 32.647699, 33.110150, 35.191414, 184.851076], [16.779289, 17.439156, 19.452500, 21.229474, 95.970655]]
input_correlations: [[-0.748967, -0.807271, 0.876587, 0.836610, -0.831639, -0.493175, -0.892592, 0.000000], [-0.921103, -0.935650, 0.666480, 0.613827, -0.961308, -0.525728, -0.988238, 0.000000], [0.502931, 0.578393, -0.984593, -0.968324, 0.623324, 0.353960, 0.702666, 0.000000], [-0.681977, -0.744719, 0.921292, 0.886671, -0.777834, -0.451341, -0.840364, 0.000000], [-0.635434, -0.706362, 0.943204, 0.912842, -0.737736, -0.438672, -0.808885, 0.000000], [-0.477479, -0.564734, 0.987970, 0.974551, -0.598616, -0.368513, -0.685691, 0.000000], [-0.593063, -0.670471, 0.958940, 0.934868, -0.701396, -0.424304, -0.775429, 0.000000]]
pre_activation_mean: [0.756864, 0.424842, -2.194228, 1.343616, 1.614105, 2.053901, 1.066341]
pre_activation_std: [0.727550, 0.626948, 2.797433, 1.023423, 1.210322, 1.755744, 1.002709]
### 10
mean: [-4.222393]
std: [3.323658]
fourier: [[53.264068, 61.723756, 62.009946, 69.090519, 380.015323]]
input_correlations: [[-0.997234, -0.964959, 0.571583, -0.998678, -0.998188, -0.985473, -0.986943, 0.000000]]
pre_activation_mean: [-4.222393]
pre_activation_std: [3.323658]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.7131870985031128, "std": 0.5566691160202026, "fourier": [8.908274212263745, 10.084501791970576, 10.604600348900279, 11.125305055755387, 64.1868370398879], "input_correlations": [0.8057161788859653, 0.7060957809979186, 0.437640935477073, 0.17377783216965986, -0.1705531139540631, 0.0, 0.0, 0.0], "pre_activation_mean": 1.9969522953033447, "pre_activation_std": 2.250575304031372}, "1": {"mean": 0.4012305736541748, "std": 0.27631568908691406, "fourier": [4.34646589723767, 4.680792595053291, 5.351050518140433, 5.480039313183842, 36.110751647502184], "input_correlations": [-0.09539339299649838, -0.09255700471888673, -0.32864641499536246, 0.8142215532358659, 0.40873776725193733, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8954417705535889, "pre_activation_std": 1.9346611499786377}, "2": {"mean": 0.2311241775751114, "std": 0.7311696410179138, "fourier": [11.402948145555333, 12.679547360962568, 13.948106304572823, 14.72515052910618, 20.801176364749693], "input_correlations": [-0.15703308153253268, -0.17821114290007314, -0.21919829950524228, -0.4232011883616111, -0.9542542460055218, 0.0, 0.0, 0.0], "pre_activation_mean": -2.0607476234436035, "pre_activation_std": 2.0007107257843018}, "3": {"mean": 1.3243390321731567, "std": 0.9183480739593506, "fourier": [14.456926254745584, 16.47236553105315, 17.422111915820683, 19.09467571557007, 119.19051382190082], "input_correlations": [0.632709378954077, 0.048448745213119475, 0.7622563480850848, -0.19164110305978843, -0.18167677299897572, 0.0, 0.0, 0.0], "pre_activation_mean": 1.0221267938613892, "pre_activation_std": 1.5037108659744263}, "4": {"mean": 1.6059919595718384, "std": 1.1239533424377441, "fourier": [17.804390344998012, 20.095497542134865, 21.464444970210774, 23.17891054953111, 144.5392841398716], "input_correlations": [-0.37182690997341805, 0.45918891543338575, -0.592493442441225, 0.5850054981720991, -0.24021807184175709, 0.0, 0.0, 0.0], "pre_activation_mean": 0.24845679104328156, "pre_activation_std": 1.6992521286010742}, "5": {"mean": 2.0469233989715576, "std": 1.714015007019043, "fourier": [27.373089336387014, 30.161738359881753, 32.80127180794838, 33.934492887027375, 184.22308968752623], "input_correlations": [-0.8078152223861387, -0.20576925284076203, -0.09489681491164173, 0.20661897671826365, 0.4201479161369108, 0.0, 0.0, 0.0], "pre_activation_mean": 0.2332172840833664, "pre_activation_std": 1.8420230150222778}, "6": {"mean": 1.04084050655365, "std": 0.9093109965324402, "fourier": [14.512099493281472, 16.096802723313846, 17.34334466144212, 17.961320392534628, 93.67563890479505], "input_correlations": [-0.6427729051494033, -0.08055207728480944, 0.2983459770773862, 0.06077168727531704, 0.4822364711022946, 0.0, 0.0, 0.0], "pre_activation_mean": 0.09909269213676453, "pre_activation_std": 1.6628444194793701}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -0.9857248663902283, "std": 1.617584466934204, "fourier": [24.630332668531352, 27.03899332226483, 27.82300701591928, 28.24746523153841, 88.71524988114834], "input_correlations": [-0.5183475402894114, -0.6168265520160254, 0.028110461960425874, -0.019918760176990367, -0.5521477732509562, 0.2485146195653167, 0.48501881992277285, 0.0], "pre_activation_mean": -0.9857248663902283, "pre_activation_std": 1.617584466934204}, "1": {"mean": 0.5181728005409241, "std": 1.3643043041229248, "fourier": [19.37335127202675, 19.78239131007584, 25.48288564354838, 30.961011045518156, 46.635550640523434], "input_correlations": [-0.5586796083728431, 0.4677860177974037, 0.4535103745593463, -0.43841350748064295, 0.1820956215518331, 0.9722989868952391, 0.8515283756554674, 0.0], "pre_activation_mean": 0.5181728005409241, "pre_activation_std": 1.3643043041229248}, "2": {"mean": -0.24542121589183807, 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"train_loss": 0.5556604862213135, "train_acc": 0.71, "val_loss": 0.527523934841156, "val_acc": 0.7}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4888806790113449, "train_acc": 0.755, "val_loss": 0.5496642589569092, "val_acc": 0.68}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.48413531482219696, "train_acc": 0.75, "val_loss": 0.4794013500213623, "val_acc": 0.76}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.48508942127227783, "train_acc": 0.76, "val_loss": 0.49307090044021606, "val_acc": 0.76}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4622749835252762, "train_acc": 0.77, "val_loss": 0.50990229845047, "val_acc": 0.78}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.42453235387802124, "train_acc": 0.805, "val_loss": 0.42181718349456787, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.4076153486967087, "train_acc": 0.84, "val_loss": 0.36300128698349, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.3967219740152359, "train_acc": 0.81, "val_loss": 0.3591877818107605, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.39679160714149475, "train_acc": 0.82, "val_loss": 0.3890579342842102, "val_acc": 0.88}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.737031102180481, "final_val_loss": 0.6648575067520142, "initial_val_acc": 0.44, "final_val_acc": 0.6, "best_val_acc": 0.6}, "improved_stage": {"initial_val_loss": 0.5261088609695435, "final_val_loss": 0.3890579342842102, "initial_val_acc": 0.76, "final_val_acc": 0.88, "best_val_acc": 0.88, "best_epoch": 11}, "improvement": 0.28, "first_improvement_epoch": 2}} |
47 | {"target_pattern": "alternating", "degraded_accuracy": 0.46, "improved_accuracy": 0.94, "improvement": 0.4799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3911, "learning_rate": 0.03942708661657638, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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"network.0.bias": [
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"network.2.weight": [
[
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[
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[
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0.020037,
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[
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[
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[
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],
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"network.4.weight": [
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[
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"network.6.weight": [
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"network.8.weight": [
[
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[
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"network.10.weight": [
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}
## Activation Signature
### 0
mean: [3.336300, 2.275941, 0.000000, 0.000000, 6.635677, 0.000000, 2.055370]
std: [3.742122, 2.665573, 0.000000, 0.000000, 7.299203, 0.000000, 2.286230]
fourier: [[61.083473, 62.915660, 66.853122, 83.592429, 300.266961], [43.231434, 51.130643, 51.360405, 52.077656, 204.834673], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [116.331039, 128.618666, 131.852029, 158.164155, 597.210998], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [36.500668, 37.815704, 39.053293, 52.617884, 184.983289]]
input_correlations: [[-0.089016, -0.192998, -0.172915, 0.783434, -0.185925, 0.000000, 0.000000, 0.000000], [0.316685, 0.423945, 0.942314, -0.125914, 0.216928, 0.000000, 0.000000, 0.000000], [0.289082, 0.678060, 0.814347, 0.060255, -0.087429, 0.000000, 0.000000, 0.000000], [-0.494109, -0.463828, -0.172142, 0.349434, 0.648213, 0.000000, 0.000000, 0.000000], [0.551824, 0.392688, -0.318476, 0.296419, 0.536558, 0.000000, 0.000000, 0.000000], [0.901806, 0.664183, 0.194070, 0.054440, -0.004519, 0.000000, 0.000000, 0.000000], [0.195131, -0.688583, -0.004849, -0.792701, 0.185751, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.245041, 1.884326, 2.063287, 0.086645, 0.823371, 1.516360, -2.158878]
pre_activation_std: [1.089588, 1.531353, 1.545602, 1.507030, 1.272358, 1.686121, 3.023099]
### 2
mean: [2.723564, -0.364906, -1.996666, 0.877751, 0.046249, 1.271907, 1.326350]
std: [2.377088, 1.646065, 1.030658, 1.489022, 1.048847, 1.531722, 1.398345]
fourier: [[37.329962, 39.490646, 40.449888, 48.441909, 245.120756], [23.318783, 25.467382, 32.029339, 32.841516, 36.797349], [14.832576, 17.361840, 17.523585, 19.600770, 179.699971], [23.554600, 24.331639, 24.472358, 30.602579, 78.997560], [15.275308, 16.148397, 17.127324, 17.614974, 18.581276], [24.956310, 25.524260, 29.203307, 30.687246, 114.471658], [20.471210, 21.250619, 23.558873, 29.877939, 119.371496]]
input_correlations: [[-0.429883, 0.908008, 0.956498, -0.452071, 0.011714, 0.544867, -0.021201, 0.000000], [0.468421, -0.615434, -0.718465, 0.820376, 0.158324, -0.593474, -0.180248, 0.000000], [-0.034239, -0.759192, -0.801469, 0.121990, -0.347078, -0.697039, -0.224898, 0.000000], [-0.433157, 0.923288, 0.932336, -0.328652, -0.219180, 0.216695, -0.145423, 0.000000], [-0.035270, 0.443880, 0.473523, -0.301210, -0.859292, -0.517154, -0.235165, 0.000000], [-0.287523, 0.183264, 0.174145, -0.244298, 0.659995, 0.887890, 0.526440, 0.000000], [-0.471546, 0.369857, 0.405061, -0.431497, 0.561637, 0.930076, 0.306174, 0.000000]]
pre_activation_mean: [2.723564, -0.364906, -1.996666, 0.877751, 0.046249, 1.271907, 1.326350]
pre_activation_std: [2.377088, 1.646065, 1.030658, 1.489022, 1.048847, 1.531722, 1.398345]
### 4
mean: [1.108768, 0.778797, 2.150154, -1.342097, 1.767460, 1.461213, -0.764332]
std: [1.395106, 1.945477, 2.115091, 0.898335, 2.331778, 1.565830, 1.747333]
fourier: [[21.809491, 22.263686, 22.284884, 30.892580, 99.789084], [28.229857, 31.920578, 33.226603, 37.829847, 70.091742], [34.186921, 36.892110, 37.230048, 39.511895, 193.513863], [14.609093, 14.999160, 15.101781, 15.255244, 120.788740], [33.245009, 38.692922, 39.266891, 57.154264, 159.071407], [22.398796, 26.201823, 30.573853, 32.574567, 131.509217], [29.907234, 30.110295, 31.201522, 31.592483, 68.789922]]
input_correlations: [[0.685960, -0.183979, 0.000000, 0.904173, 0.899468, -0.420533, -0.186338, 0.000000], [0.348036, 0.086814, 0.000000, 0.667267, 0.835880, -0.735583, -0.557989, 0.000000], [0.989648, -0.584851, 0.000000, 0.904964, 0.549971, 0.337644, 0.557008, 0.000000], [-0.818242, 0.206983, 0.000000, -0.597129, -0.006307, -0.745571, -0.855703, 0.000000], [0.427803, -0.533478, 0.000000, 0.062624, -0.377553, 0.949430, 0.954893, 0.000000], [0.795483, -0.029165, 0.000000, 0.943662, 0.747214, -0.184046, 0.039779, 0.000000], [-0.919474, 0.719374, 0.000000, -0.885198, -0.662314, -0.156102, -0.386940, 0.000000]]
pre_activation_mean: [1.108768, 0.778797, 2.150154, -1.342097, 1.767460, 1.461213, -0.764332]
pre_activation_std: [1.395106, 1.945477, 2.115091, 0.898335, 2.331778, 1.565830, 1.747333]
### 6
mean: [-2.830498, 0.938299, 0.011048, 0.917417, 1.853857, 2.291891, 2.647963]
std: [2.342148, 2.468302, 1.008618, 1.319848, 2.832316, 2.542105, 3.403640]
fourier: [[33.590092, 40.954286, 45.229234, 51.593733, 254.744813], [37.338193, 40.330972, 42.285098, 57.163704, 84.446917], [12.995199, 13.752669, 14.341918, 15.129932, 27.591429], [21.064745, 21.205661, 23.907807, 27.428425, 82.567562], [41.611253, 43.014333, 53.079740, 59.401789, 166.847094], [36.425773, 41.544881, 44.409954, 57.271037, 206.270169], [50.123691, 54.347173, 58.047891, 77.490284, 238.316689]]
input_correlations: [[-0.963506, -0.855833, -0.830572, 0.000000, 0.157062, -0.992704, 0.170163, 0.000000], [0.688442, 0.855608, 0.069456, 0.000000, -0.843063, 0.620700, 0.349782, 0.000000], [0.141500, 0.430195, -0.485084, 0.000000, -0.863716, 0.108201, 0.740981, 0.000000], [0.875273, 0.909818, 0.474468, 0.000000, -0.545419, 0.894687, 0.211595, 0.000000], [0.887788, 0.954698, 0.413211, 0.000000, -0.638019, 0.844324, 0.147880, 0.000000], [0.977292, 0.941675, 0.678009, 0.000000, -0.391990, 0.960760, -0.074865, 0.000000], [0.979905, 0.959129, 0.659271, 0.000000, -0.414240, 0.947015, -0.089202, 0.000000]]
pre_activation_mean: [-2.830498, 0.938299, 0.011048, 0.917417, 1.853857, 2.291891, 2.647963]
pre_activation_std: [2.342148, 2.468302, 1.008618, 1.319848, 2.832316, 2.542105, 3.403640]
### 8
mean: [3.296075, 2.219183, -2.063581, -2.126059, 6.590665, -1.856036, 2.005331]
std: [3.778367, 2.714740, 1.883521, 2.060157, 7.340440, 1.684344, 2.332255]
fourier: [[61.888244, 63.777817, 66.306374, 83.973430, 296.646790], [44.176492, 51.658927, 52.071687, 53.273491, 199.726453], [31.506170, 31.662341, 31.762887, 41.279869, 185.722312], [31.275481, 33.819026, 35.107058, 48.367731, 191.345342], [117.208666, 129.790740, 131.025435, 158.543821, 593.159883], [26.520284, 27.266002, 28.273304, 39.495293, 167.043234], [37.015516, 37.095344, 40.101985, 53.066588, 180.479796]]
input_correlations: [[0.000000, 0.938109, 0.404957, 0.988963, 0.993758, 0.971864, 0.975756, 0.000000], [0.000000, 0.996663, 0.618902, 0.958019, 0.971553, 0.866451, 0.874123, 0.000000], [0.000000, -0.927245, -0.437601, -0.996971, -0.984761, -0.972008, -0.968869, 0.000000], [0.000000, -0.840195, -0.209290, -0.954142, -0.958617, -0.997133, -0.999110, 0.000000], [0.000000, 0.958511, 0.461904, 0.989623, 0.996197, 0.954420, 0.958601, 0.000000], [0.000000, -0.866804, -0.256680, -0.966395, -0.973000, -0.993919, -0.996852, 0.000000], [0.000000, 0.879875, 0.304285, 0.977910, 0.972487, 0.995320, 0.994152, 0.000000]]
pre_activation_mean: [3.296075, 2.219183, -2.063581, -2.126059, 6.590665, -1.856036, 2.005331]
pre_activation_std: [3.778367, 2.714740, 1.883521, 2.060157, 7.340440, 1.684344, 2.332255]
### 10
mean: [-6.022344]
std: [6.995145]
fourier: [[111.913791, 122.578108, 126.741074, 151.961817, 542.010912]]
input_correlations: [[-0.997898, -0.973729, 0.000000, 0.000000, -0.999967, 0.000000, -0.978897, 0.000000]]
pre_activation_mean: [-6.022344]
pre_activation_std: [6.995145]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.0.bias": [
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"network.2.weight": [
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],
"network.2.bias": [
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"network.4.weight": [
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[
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"network.8.weight": [
[
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [3.336300, 2.275941, 0.000000, 0.000000, 6.635677, 0.000000, 2.055370]
std: [3.742122, 2.665573, 0.000000, 0.000000, 7.299203, 0.000000, 2.286230]
fourier: [[61.083473, 62.915660, 66.853122, 83.592429, 300.266961], [43.231434, 51.130643, 51.360405, 52.077656, 204.834673], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [116.331039, 128.618666, 131.852029, 158.164155, 597.210998], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [36.500668, 37.815704, 39.053293, 52.617884, 184.983289]]
input_correlations: [[-0.089016, -0.192998, -0.172915, 0.783434, -0.185925, 0.000000, 0.000000, 0.000000], [0.316685, 0.423945, 0.942314, -0.125914, 0.216928, 0.000000, 0.000000, 0.000000], [0.289082, 0.678060, 0.814347, 0.060255, -0.087429, 0.000000, 0.000000, 0.000000], [-0.494109, -0.463828, -0.172142, 0.349434, 0.648213, 0.000000, 0.000000, 0.000000], [0.551824, 0.392688, -0.318476, 0.296419, 0.536558, 0.000000, 0.000000, 0.000000], [0.901806, 0.664183, 0.194070, 0.054440, -0.004519, 0.000000, 0.000000, 0.000000], [0.195131, -0.688583, -0.004849, -0.792701, 0.185751, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.245041, 1.884326, 2.063287, 0.086645, 0.823371, 1.516360, -2.158878]
pre_activation_std: [1.089588, 1.531353, 1.545602, 1.507030, 1.272358, 1.686121, 3.023099]
### 2
mean: [2.723564, -0.364906, -1.996666, 0.877751, 0.046249, 1.271907, 1.326350]
std: [2.377088, 1.646065, 1.030658, 1.489022, 1.048847, 1.531722, 1.398345]
fourier: [[37.329962, 39.490646, 40.449888, 48.441909, 245.120756], [23.318783, 25.467382, 32.029339, 32.841516, 36.797349], [14.832576, 17.361840, 17.523585, 19.600770, 179.699971], [23.554600, 24.331639, 24.472358, 30.602579, 78.997560], [15.275308, 16.148397, 17.127324, 17.614974, 18.581276], [24.956310, 25.524260, 29.203307, 30.687246, 114.471658], [20.471210, 21.250619, 23.558873, 29.877939, 119.371496]]
input_correlations: [[-0.429883, 0.908008, 0.956498, -0.452071, 0.011714, 0.544867, -0.021201, 0.000000], [0.468421, -0.615434, -0.718465, 0.820376, 0.158324, -0.593474, -0.180248, 0.000000], [-0.034239, -0.759192, -0.801469, 0.121990, -0.347078, -0.697039, -0.224898, 0.000000], [-0.433157, 0.923288, 0.932336, -0.328652, -0.219180, 0.216695, -0.145423, 0.000000], [-0.035270, 0.443880, 0.473523, -0.301210, -0.859292, -0.517154, -0.235165, 0.000000], [-0.287523, 0.183264, 0.174145, -0.244298, 0.659995, 0.887890, 0.526440, 0.000000], [-0.471546, 0.369857, 0.405061, -0.431497, 0.561637, 0.930076, 0.306174, 0.000000]]
pre_activation_mean: [2.723564, -0.364906, -1.996666, 0.877751, 0.046249, 1.271907, 1.326350]
pre_activation_std: [2.377088, 1.646065, 1.030658, 1.489022, 1.048847, 1.531722, 1.398345]
### 4
mean: [1.108768, 0.778797, 2.150154, -1.342097, 1.767460, 1.461213, -0.764332]
std: [1.395106, 1.945477, 2.115091, 0.898335, 2.331778, 1.565830, 1.747333]
fourier: [[21.809491, 22.263686, 22.284884, 30.892580, 99.789084], [28.229857, 31.920578, 33.226603, 37.829847, 70.091742], [34.186921, 36.892110, 37.230048, 39.511895, 193.513863], [14.609093, 14.999160, 15.101781, 15.255244, 120.788740], [33.245009, 38.692922, 39.266891, 57.154264, 159.071407], [22.398796, 26.201823, 30.573853, 32.574567, 131.509217], [29.907234, 30.110295, 31.201522, 31.592483, 68.789922]]
input_correlations: [[0.685960, -0.183979, 0.000000, 0.904173, 0.899468, -0.420533, -0.186338, 0.000000], [0.348036, 0.086814, 0.000000, 0.667267, 0.835880, -0.735583, -0.557989, 0.000000], [0.989648, -0.584851, 0.000000, 0.904964, 0.549971, 0.337644, 0.557008, 0.000000], [-0.818242, 0.206983, 0.000000, -0.597129, -0.006307, -0.745571, -0.855703, 0.000000], [0.427803, -0.533478, 0.000000, 0.062624, -0.377553, 0.949430, 0.954893, 0.000000], [0.795483, -0.029165, 0.000000, 0.943662, 0.747214, -0.184046, 0.039779, 0.000000], [-0.919474, 0.719374, 0.000000, -0.885198, -0.662314, -0.156102, -0.386940, 0.000000]]
pre_activation_mean: [1.108768, 0.778797, 2.150154, -1.342097, 1.767460, 1.461213, -0.764332]
pre_activation_std: [1.395106, 1.945477, 2.115091, 0.898335, 2.331778, 1.565830, 1.747333]
### 6
mean: [-2.830498, 0.938299, 0.011048, 0.917417, 1.853857, 2.291891, 2.647963]
std: [2.342148, 2.468302, 1.008618, 1.319848, 2.832316, 2.542105, 3.403640]
fourier: [[33.590092, 40.954286, 45.229234, 51.593733, 254.744813], [37.338193, 40.330972, 42.285098, 57.163704, 84.446917], [12.995199, 13.752669, 14.341918, 15.129932, 27.591429], [21.064745, 21.205661, 23.907807, 27.428425, 82.567562], [41.611253, 43.014333, 53.079740, 59.401789, 166.847094], [36.425773, 41.544881, 44.409954, 57.271037, 206.270169], [50.123691, 54.347173, 58.047891, 77.490284, 238.316689]]
input_correlations: [[-0.963506, -0.855833, -0.830572, 0.000000, 0.157062, -0.992704, 0.170163, 0.000000], [0.688442, 0.855608, 0.069456, 0.000000, -0.843063, 0.620700, 0.349782, 0.000000], [0.141500, 0.430195, -0.485084, 0.000000, -0.863716, 0.108201, 0.740981, 0.000000], [0.875273, 0.909818, 0.474468, 0.000000, -0.545419, 0.894687, 0.211595, 0.000000], [0.887788, 0.954698, 0.413211, 0.000000, -0.638019, 0.844324, 0.147880, 0.000000], [0.977292, 0.941675, 0.678009, 0.000000, -0.391990, 0.960760, -0.074865, 0.000000], [0.979905, 0.959129, 0.659271, 0.000000, -0.414240, 0.947015, -0.089202, 0.000000]]
pre_activation_mean: [-2.830498, 0.938299, 0.011048, 0.917417, 1.853857, 2.291891, 2.647963]
pre_activation_std: [2.342148, 2.468302, 1.008618, 1.319848, 2.832316, 2.542105, 3.403640]
### 8
mean: [3.296075, 2.219183, -2.063581, -2.126059, 6.590665, -1.856036, 2.005331]
std: [3.778367, 2.714740, 1.883521, 2.060157, 7.340440, 1.684344, 2.332255]
fourier: [[61.888244, 63.777817, 66.306374, 83.973430, 296.646790], [44.176492, 51.658927, 52.071687, 53.273491, 199.726453], [31.506170, 31.662341, 31.762887, 41.279869, 185.722312], [31.275481, 33.819026, 35.107058, 48.367731, 191.345342], [117.208666, 129.790740, 131.025435, 158.543821, 593.159883], [26.520284, 27.266002, 28.273304, 39.495293, 167.043234], [37.015516, 37.095344, 40.101985, 53.066588, 180.479796]]
input_correlations: [[0.000000, 0.938109, 0.404957, 0.988963, 0.993758, 0.971864, 0.975756, 0.000000], [0.000000, 0.996663, 0.618902, 0.958019, 0.971553, 0.866451, 0.874123, 0.000000], [0.000000, -0.927245, -0.437601, -0.996971, -0.984761, -0.972008, -0.968869, 0.000000], [0.000000, -0.840195, -0.209290, -0.954142, -0.958617, -0.997133, -0.999110, 0.000000], [0.000000, 0.958511, 0.461904, 0.989623, 0.996197, 0.954420, 0.958601, 0.000000], [0.000000, -0.866804, -0.256680, -0.966395, -0.973000, -0.993919, -0.996852, 0.000000], [0.000000, 0.879875, 0.304285, 0.977910, 0.972487, 0.995320, 0.994152, 0.000000]]
pre_activation_mean: [3.296075, 2.219183, -2.063581, -2.126059, 6.590665, -1.856036, 2.005331]
pre_activation_std: [3.778367, 2.714740, 1.883521, 2.060157, 7.340440, 1.684344, 2.332255]
### 10
mean: [-6.022344]
std: [6.995145]
fourier: [[111.913791, 122.578108, 126.741074, 151.961817, 542.010912]]
input_correlations: [[-0.997898, -0.973729, 0.000000, 0.000000, -0.999967, 0.000000, -0.978897, 0.000000]]
pre_activation_mean: [-6.022344]
pre_activation_std: [6.995145]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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-0.506895, -0.268073], [-0.407734, -0.061977, -0.488791, -0.172524, -0.062667, -0.240562, -0.370737], [-0.437361, 0.463243, 0.438738, 0.020037, -0.210234, -0.035004, -0.324421], [0.006269, -0.005988, 0.443671, -0.056339, -0.512332, -0.309375, -0.059582], [-0.154566, -0.038649, -0.113228, -0.090973, 0.210854, 0.719836, 0.658948], [-0.404259, 0.181971, -0.175016, -0.338857, 0.259637, 0.59696, 0.13521]], "network.2.bias": [0.282221, 0.120441, 0.017332, -0.312768, 0.173952, 0.181571, 0.538177], "network.4.weight": [[0.092625, 0.121489, -0.129119, 0.577471, 0.636848, -0.479791, 0.233821], [0.338151, 0.328037, -0.261473, 0.521469, 0.335448, -0.655655, -0.419572], [0.632543, -0.319719, -0.080323, 0.272913, 0.225367, 0.027126, 0.128746], [-0.24541, -0.216023, 0.048785, -0.237383, 0.363465, -0.349075, 0.071439], [0.101955, -0.671694, 0.023908, -0.26345, -0.322516, 0.667436, 0.688753], [0.305376, 0.55422, 0.212181, 0.678525, 0.307384, -0.247825, 0.079227], [-0.475387, 0.675758, 0.241254, -0.152745, -0.251832, 0.173841, -0.039407]], "network.4.bias": [0.186917, 0.409009, -0.076825, -0.099706, 0.392993, -0.311318, 0.349545], "network.6.weight": [[-0.294238, -0.207575, -0.501317, -0.243121, 0.106339, -0.596042, -0.317297], [0.311464, 0.581448, -0.447711, 0.125256, -0.410086, 0.701012, 0.491983], [0.068204, 0.245057, -0.199611, 0.16047, -0.158701, 0.028307, 0.621226], [-0.027088, 0.175048, 0.189474, -0.257887, -0.236077, 0.435138, 0.48416], [0.641173, 0.590958, 0.365788, -0.082352, -0.50618, 0.136619, 0.933821], [0.364735, 0.394819, 0.439506, 0.333304, -0.306616, 0.488686, 0.350213], [0.27249, 0.880365, 0.452619, 0.362332, -0.339823, 0.666471, 0.232999]], "network.6.bias": [-0.299268, 0.451886, 0.130979, -0.059334, 0.011076, 0.134416, -0.162086], "network.8.weight": [[-0.344458, 0.552799, 0.114446, 0.496832, 0.116878, 0.106414, 0.538197], [-0.006603, 0.946017, 0.182826, 0.351506, 0.28874, -0.025619, -0.03044], [-0.004483, 0.019544, -0.342515, -0.48336, -0.142333, -0.400871, 0.016464], [-0.281864, 0.247729, -0.028922, 0.110738, -0.377511, -0.320402, -0.264559], [-0.129232, 1.058387, 0.792103, 0.299706, 0.775851, 0.486722, 0.599607], [-0.298865, 0.234048, -0.015348, 0.00688, -0.453886, -0.226879, -0.121007], [-0.05871, -0.018645, 0.315266, 0.052558, 0.041497, 0.440565, 0.327722]], "network.8.bias": [-0.152436, -0.165045, -0.238094, -0.29469, -0.189045, -0.357662, -0.196968], "network.10.weight": [[-0.194459, -0.403667, 0.056001, -0.366201, -0.570912, 0.064386, -0.47104]], "network.10.bias": [0.301704]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6828611195087433, "train_acc": 0.58, "val_loss": 0.7172709703445435, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6809355616569519, "train_acc": 0.58, "val_loss": 0.7089897394180298, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.655329018831253, "train_acc": 0.58, "val_loss": 0.6945953965187073, "val_acc": 0.46}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6370730400085449, "train_acc": 0.58, "val_loss": 0.6423133611679077, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6182279586791992, "train_acc": 0.51, "val_loss": 0.6053712368011475, "val_acc": 0.46}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5535631477832794, "train_acc": 0.51, "val_loss": 0.5608758330345154, "val_acc": 0.46}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5013341009616852, "train_acc": 0.625, "val_loss": 0.5031633973121643, "val_acc": 0.84}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.4048670828342438, "train_acc": 0.92, "val_loss": 0.45319804549217224, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.37740764021873474, "train_acc": 0.915, "val_loss": 0.4291452169418335, "val_acc": 0.9}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.34104740619659424, "train_acc": 0.945, "val_loss": 0.37846794724464417, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.31390297412872314, "train_acc": 0.955, "val_loss": 0.34859099984169006, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.3043302595615387, "train_acc": 0.945, "val_loss": 0.33173638582229614, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.28635522723197937, "train_acc": 0.955, "val_loss": 0.31547844409942627, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.26856185495853424, "train_acc": 0.96, "val_loss": 0.3129655122756958, "val_acc": 0.9}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.7172709703445435, "final_val_loss": 0.6423133611679077, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.6053712368011475, "final_val_loss": 0.3129655122756958, "initial_val_acc": 0.46, "final_val_acc": 0.9, "best_val_acc": 0.94, "best_epoch": 9}, "improvement": 0.4799999999999999, "first_improvement_epoch": 3}} |
48 | {"target_pattern": "palindrome", "degraded_accuracy": 0.38, "improved_accuracy": 0.94, "improvement": 0.5599999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8776, "learning_rate": 0.0354662552402799, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.106263,
0.027363,
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[
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0.148158,
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0.674125
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[
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-0.314828,
0.244348,
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[
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],
"network.0.bias": [
0.056402,
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"network.2.weight": [
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],
[
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0.010303
],
[
0.329646,
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0.236859,
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],
[
0.02692,
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],
[
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],
"network.2.bias": [
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],
"network.4.weight": [
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[
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[
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[
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],
"network.4.bias": [
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"network.6.weight": [
[
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[
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[
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[
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],
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"network.8.weight": [
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[
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[
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[
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"network.8.bias": [
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"network.10.weight": [
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[
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"network.10.bias": [
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"network.12.weight": [
[
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"network.12.bias": [
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]
}
## Activation Signature
### 0
mean: [1.002943, 0.171682, 0.978890, 0.000000, 0.000000]
std: [1.046256, 0.215352, 0.999646, 0.000000, 0.000000]
fourier: [[17.861274, 20.406248, 21.575958, 23.465375, 90.264857], [3.264031, 3.318403, 3.671428, 3.685365, 15.451340], [17.015657, 17.416449, 18.391821, 20.705143, 88.100088], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.190272, -0.352738, -0.067525, 0.312943, 0.852411, 0.000000, 0.000000, 0.000000], [0.952401, 0.221114, 0.375927, -0.100666, -0.065436, 0.000000, 0.000000, 0.000000], [-0.330095, -0.074953, 0.222427, -0.086371, 0.797802, 0.000000, 0.000000, 0.000000], [-0.480398, -0.326364, -0.455186, 0.408097, 0.579816, 0.000000, 0.000000, 0.000000], [-0.312965, 0.333378, -0.347870, 0.282082, 0.590228, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.476455, 1.140579, 0.731782, 0.012479, 0.260274]
pre_activation_std: [1.467104, 1.344295, 1.348247, 1.394532, 0.726063]
### 2
mean: [0.485339, -1.381764, 0.205689, 0.476642, 0.949814]
std: [0.346296, 0.543191, 0.880703, 0.941859, 2.052687]
fourier: [[5.483857, 6.025709, 6.373098, 6.504999, 43.680500], [9.309404, 9.398997, 10.442330, 11.276566, 124.358751], [14.833517, 15.331058, 16.732996, 16.829963, 18.511976], [14.957440, 16.255502, 16.665316, 21.998117, 42.897779], [33.876688, 34.942786, 36.593971, 40.037378, 85.483256]]
input_correlations: [[0.426145, -0.830039, 0.695024, 0.372395, 0.580923, 0.000000, 0.000000, 0.000000], [-0.712437, -0.218651, -0.868770, -0.421458, -0.486273, 0.000000, 0.000000, 0.000000], [-0.221830, 0.826089, -0.617686, -0.258771, -0.562688, 0.000000, 0.000000, 0.000000], [-0.678110, 0.812692, -0.699300, -0.809652, -0.791658, 0.000000, 0.000000, 0.000000], [0.903985, -0.529280, 0.866435, 0.881660, 0.838945, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.485339, -1.381764, 0.205689, 0.476642, 0.949814]
pre_activation_std: [0.346296, 0.543191, 0.880703, 0.941859, 2.052687]
### 4
mean: [-0.704559, 0.090171, 0.374631, 0.815679, 0.338516]
std: [0.144776, 0.825469, 1.034267, 0.939849, 0.711656]
fourier: [[2.089324, 2.289006, 2.651802, 3.064872, 63.410275], [13.298858, 13.604674, 13.770875, 14.036945, 15.542483], [17.309984, 17.531118, 18.160184, 22.326646, 33.716769], [16.365589, 16.563997, 17.880509, 18.480968, 73.411085], [11.851447, 13.145019, 13.801391, 14.139862, 30.466430]]
input_correlations: [[-0.819453, 0.000000, 0.922446, 0.668097, -0.119095, 0.000000, 0.000000, 0.000000], [-0.210165, 0.000000, -0.174571, 0.110031, -0.894083, 0.000000, 0.000000, 0.000000], [-0.634092, 0.000000, 0.330525, 0.576477, -0.992557, 0.000000, 0.000000, 0.000000], [0.088769, 0.000000, 0.328441, 0.089652, 0.808221, 0.000000, 0.000000, 0.000000], [-0.834633, 0.000000, 0.987107, 0.924386, -0.282706, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.704559, 0.090171, 0.374631, 0.815679, 0.338516]
pre_activation_std: [0.144776, 0.825469, 1.034267, 0.939849, 0.711656]
### 6
mean: [0.263804, 0.156126, 0.909228, 0.120099, 0.105757]
std: [0.743147, 0.869438, 0.898904, 0.749894, 0.702381]
fourier: [[11.972985, 12.916992, 13.440559, 15.942930, 23.742350], [14.051375, 14.646444, 16.701525, 16.727546, 18.457666], [16.058224, 18.230607, 18.351897, 19.396793, 81.830559], [10.808882, 14.137248, 14.228110, 14.695696, 16.039014], [9.820206, 12.335003, 13.771718, 13.872230, 14.859370]]
input_correlations: [[0.000000, 0.950909, 0.474126, -0.929577, -0.489281, 0.000000, 0.000000, 0.000000], [0.000000, 0.946876, 0.345752, -0.920729, -0.596145, 0.000000, 0.000000, 0.000000], [0.000000, -0.890023, -0.141937, 0.889218, 0.720292, 0.000000, 0.000000, 0.000000], [0.000000, 0.950198, 0.247437, -0.854292, -0.700804, 0.000000, 0.000000, 0.000000], [0.000000, 0.940530, 0.285091, -0.905027, -0.646676, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.263804, 0.156126, 0.909228, 0.120099, 0.105757]
pre_activation_std: [0.743147, 0.869438, 0.898904, 0.749894, 0.702381]
### 8
mean: [0.390007, 0.690803, 0.929231, -0.659904, -0.000829]
std: [0.716856, 1.258279, 1.289992, 0.262508, 0.447123]
fourier: [[12.127773, 12.513399, 12.681518, 14.842651, 35.100589], [22.788970, 23.636835, 24.021318, 26.735591, 62.172305], [22.392352, 23.173847, 23.652587, 27.360753, 83.630808], [4.487895, 4.802313, 5.278152, 6.070818, 59.391351], [6.726905, 7.618084, 7.849501, 8.018030, 9.017399]]
input_correlations: [[0.993781, 0.998617, -0.879892, 0.996606, 0.998038, 0.000000, 0.000000, 0.000000], [-0.963644, -0.963209, 0.962576, -0.955795, -0.963909, 0.000000, 0.000000, 0.000000], [0.985569, 0.986099, -0.928016, 0.980860, 0.985701, 0.000000, 0.000000, 0.000000], [0.707247, 0.698195, -0.968186, 0.680871, 0.702710, 0.000000, 0.000000, 0.000000], [-0.989647, -0.999438, 0.851903, -0.999712, -0.999641, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.390007, 0.690803, 0.929231, -0.659904, -0.000829]
pre_activation_std: [0.716856, 1.258279, 1.289992, 0.262508, 0.447123]
### 10
mean: [0.563242, 0.152091, 0.761036, -0.329784, -0.509815]
std: [1.510462, 0.233003, 1.229946, 0.252825, 0.124161]
fourier: [[26.871116, 27.938086, 28.161772, 32.842400, 50.691761], [3.426185, 3.679665, 3.988709, 4.320702, 13.688151], [21.850679, 21.937364, 22.503939, 26.382411, 68.493270], [4.528196, 4.809507, 4.964585, 5.459384, 29.680535], [2.125031, 2.471533, 2.555321, 2.820355, 45.883316]]
input_correlations: [[-0.947126, 0.974793, -0.975024, 0.000000, 0.965858, 0.000000, 0.000000, 0.000000], [0.951271, -0.652408, 0.911825, 0.000000, -0.718621, 0.000000, 0.000000, 0.000000], [0.962687, -0.961173, 0.985798, 0.000000, -0.960754, 0.000000, 0.000000, 0.000000], [0.911374, -0.991411, 0.949330, 0.000000, -0.963745, 0.000000, 0.000000, 0.000000], [0.719537, -0.966132, 0.775086, 0.000000, -0.851000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.563242, 0.152091, 0.761036, -0.329784, -0.509815]
pre_activation_std: [1.510462, 0.233003, 1.229946, 0.252825, 0.124161]
### 12
mean: [-0.185077]
std: [1.379907]
fourier: [[22.104696, 23.879801, 25.674041, 25.697540, 30.541020]]
input_correlations: [[-0.979800, 0.795982, 0.973147, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.185077]
pre_activation_std: [1.379907]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.208234,
0.687972
],
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0.106263,
0.027363,
-0.209738
],
[
-0.423759,
0.148158,
0.128209,
-0.20876,
0.674125
],
[
-0.256851,
-0.170058,
-0.314828,
0.244348,
0.518985
],
[
-0.184237,
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]
],
"network.0.bias": [
0.056402,
0.500184,
0.337586,
0.135567,
0.082738
],
"network.2.weight": [
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],
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],
[
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0.236859,
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],
[
0.02692,
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],
[
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]
],
"network.2.bias": [
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0.00631
],
"network.4.weight": [
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],
[
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],
[
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0.538778
],
[
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]
],
"network.4.bias": [
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0.640665,
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],
"network.6.weight": [
[
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],
[
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0.418089,
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],
[
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0.527073
],
[
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],
[
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]
],
"network.6.bias": [
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0.121075,
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],
"network.8.weight": [
[
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],
[
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[
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0.316344
],
[
0.004511,
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[
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],
"network.8.bias": [
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0.416149
],
"network.10.weight": [
[
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[
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[
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[
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[
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]
],
"network.10.bias": [
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],
"network.12.weight": [
[
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],
"network.12.bias": [
-0.057182
]
}
## Activation Signature
### 0
mean: [1.002943, 0.171682, 0.978890, 0.000000, 0.000000]
std: [1.046256, 0.215352, 0.999646, 0.000000, 0.000000]
fourier: [[17.861274, 20.406248, 21.575958, 23.465375, 90.264857], [3.264031, 3.318403, 3.671428, 3.685365, 15.451340], [17.015657, 17.416449, 18.391821, 20.705143, 88.100088], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.190272, -0.352738, -0.067525, 0.312943, 0.852411, 0.000000, 0.000000, 0.000000], [0.952401, 0.221114, 0.375927, -0.100666, -0.065436, 0.000000, 0.000000, 0.000000], [-0.330095, -0.074953, 0.222427, -0.086371, 0.797802, 0.000000, 0.000000, 0.000000], [-0.480398, -0.326364, -0.455186, 0.408097, 0.579816, 0.000000, 0.000000, 0.000000], [-0.312965, 0.333378, -0.347870, 0.282082, 0.590228, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.476455, 1.140579, 0.731782, 0.012479, 0.260274]
pre_activation_std: [1.467104, 1.344295, 1.348247, 1.394532, 0.726063]
### 2
mean: [0.485339, -1.381764, 0.205689, 0.476642, 0.949814]
std: [0.346296, 0.543191, 0.880703, 0.941859, 2.052687]
fourier: [[5.483857, 6.025709, 6.373098, 6.504999, 43.680500], [9.309404, 9.398997, 10.442330, 11.276566, 124.358751], [14.833517, 15.331058, 16.732996, 16.829963, 18.511976], [14.957440, 16.255502, 16.665316, 21.998117, 42.897779], [33.876688, 34.942786, 36.593971, 40.037378, 85.483256]]
input_correlations: [[0.426145, -0.830039, 0.695024, 0.372395, 0.580923, 0.000000, 0.000000, 0.000000], [-0.712437, -0.218651, -0.868770, -0.421458, -0.486273, 0.000000, 0.000000, 0.000000], [-0.221830, 0.826089, -0.617686, -0.258771, -0.562688, 0.000000, 0.000000, 0.000000], [-0.678110, 0.812692, -0.699300, -0.809652, -0.791658, 0.000000, 0.000000, 0.000000], [0.903985, -0.529280, 0.866435, 0.881660, 0.838945, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.485339, -1.381764, 0.205689, 0.476642, 0.949814]
pre_activation_std: [0.346296, 0.543191, 0.880703, 0.941859, 2.052687]
### 4
mean: [-0.704559, 0.090171, 0.374631, 0.815679, 0.338516]
std: [0.144776, 0.825469, 1.034267, 0.939849, 0.711656]
fourier: [[2.089324, 2.289006, 2.651802, 3.064872, 63.410275], [13.298858, 13.604674, 13.770875, 14.036945, 15.542483], [17.309984, 17.531118, 18.160184, 22.326646, 33.716769], [16.365589, 16.563997, 17.880509, 18.480968, 73.411085], [11.851447, 13.145019, 13.801391, 14.139862, 30.466430]]
input_correlations: [[-0.819453, 0.000000, 0.922446, 0.668097, -0.119095, 0.000000, 0.000000, 0.000000], [-0.210165, 0.000000, -0.174571, 0.110031, -0.894083, 0.000000, 0.000000, 0.000000], [-0.634092, 0.000000, 0.330525, 0.576477, -0.992557, 0.000000, 0.000000, 0.000000], [0.088769, 0.000000, 0.328441, 0.089652, 0.808221, 0.000000, 0.000000, 0.000000], [-0.834633, 0.000000, 0.987107, 0.924386, -0.282706, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.704559, 0.090171, 0.374631, 0.815679, 0.338516]
pre_activation_std: [0.144776, 0.825469, 1.034267, 0.939849, 0.711656]
### 6
mean: [0.263804, 0.156126, 0.909228, 0.120099, 0.105757]
std: [0.743147, 0.869438, 0.898904, 0.749894, 0.702381]
fourier: [[11.972985, 12.916992, 13.440559, 15.942930, 23.742350], [14.051375, 14.646444, 16.701525, 16.727546, 18.457666], [16.058224, 18.230607, 18.351897, 19.396793, 81.830559], [10.808882, 14.137248, 14.228110, 14.695696, 16.039014], [9.820206, 12.335003, 13.771718, 13.872230, 14.859370]]
input_correlations: [[0.000000, 0.950909, 0.474126, -0.929577, -0.489281, 0.000000, 0.000000, 0.000000], [0.000000, 0.946876, 0.345752, -0.920729, -0.596145, 0.000000, 0.000000, 0.000000], [0.000000, -0.890023, -0.141937, 0.889218, 0.720292, 0.000000, 0.000000, 0.000000], [0.000000, 0.950198, 0.247437, -0.854292, -0.700804, 0.000000, 0.000000, 0.000000], [0.000000, 0.940530, 0.285091, -0.905027, -0.646676, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.263804, 0.156126, 0.909228, 0.120099, 0.105757]
pre_activation_std: [0.743147, 0.869438, 0.898904, 0.749894, 0.702381]
### 8
mean: [0.390007, 0.690803, 0.929231, -0.659904, -0.000829]
std: [0.716856, 1.258279, 1.289992, 0.262508, 0.447123]
fourier: [[12.127773, 12.513399, 12.681518, 14.842651, 35.100589], [22.788970, 23.636835, 24.021318, 26.735591, 62.172305], [22.392352, 23.173847, 23.652587, 27.360753, 83.630808], [4.487895, 4.802313, 5.278152, 6.070818, 59.391351], [6.726905, 7.618084, 7.849501, 8.018030, 9.017399]]
input_correlations: [[0.993781, 0.998617, -0.879892, 0.996606, 0.998038, 0.000000, 0.000000, 0.000000], [-0.963644, -0.963209, 0.962576, -0.955795, -0.963909, 0.000000, 0.000000, 0.000000], [0.985569, 0.986099, -0.928016, 0.980860, 0.985701, 0.000000, 0.000000, 0.000000], [0.707247, 0.698195, -0.968186, 0.680871, 0.702710, 0.000000, 0.000000, 0.000000], [-0.989647, -0.999438, 0.851903, -0.999712, -0.999641, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.390007, 0.690803, 0.929231, -0.659904, -0.000829]
pre_activation_std: [0.716856, 1.258279, 1.289992, 0.262508, 0.447123]
### 10
mean: [0.563242, 0.152091, 0.761036, -0.329784, -0.509815]
std: [1.510462, 0.233003, 1.229946, 0.252825, 0.124161]
fourier: [[26.871116, 27.938086, 28.161772, 32.842400, 50.691761], [3.426185, 3.679665, 3.988709, 4.320702, 13.688151], [21.850679, 21.937364, 22.503939, 26.382411, 68.493270], [4.528196, 4.809507, 4.964585, 5.459384, 29.680535], [2.125031, 2.471533, 2.555321, 2.820355, 45.883316]]
input_correlations: [[-0.947126, 0.974793, -0.975024, 0.000000, 0.965858, 0.000000, 0.000000, 0.000000], [0.951271, -0.652408, 0.911825, 0.000000, -0.718621, 0.000000, 0.000000, 0.000000], [0.962687, -0.961173, 0.985798, 0.000000, -0.960754, 0.000000, 0.000000, 0.000000], [0.911374, -0.991411, 0.949330, 0.000000, -0.963745, 0.000000, 0.000000, 0.000000], [0.719537, -0.966132, 0.775086, 0.000000, -0.851000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.563242, 0.152091, 0.761036, -0.329784, -0.509815]
pre_activation_std: [1.510462, 0.233003, 1.229946, 0.252825, 0.124161]
### 12
mean: [-0.185077]
std: [1.379907]
fourier: [[22.104696, 23.879801, 25.674041, 25.697540, 30.541020]]
input_correlations: [[-0.979800, 0.795982, 0.973147, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.185077]
pre_activation_std: [1.379907]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 1.0029428005218506, "std": 1.0462558269500732, "fourier": [17.861273928425128, 20.406247745673106, 21.575957657905484, 23.46537529522018, 90.2648566365242], "input_correlations": [-0.19027180000429358, -0.35273780086053064, -0.06752457226645256, 0.3129429691548026, 0.852411308031673, 0.0, 0.0, 0.0], "pre_activation_mean": 0.47645479440689087, "pre_activation_std": 1.4671038389205933}, "1": {"mean": 0.17168156802654266, "std": 0.21535222232341766, "fourier": [3.264030514348855, 3.3184027443169244, 3.671428085191434, 3.6853647738882658, 15.451340407133102], "input_correlations": [0.9524013378668952, 0.2211141481369545, 0.37592728738036335, -0.10066594835186662, -0.06543574463796732, 0.0, 0.0, 0.0], "pre_activation_mean": 1.1405794620513916, "pre_activation_std": 1.3442953824996948}, "2": {"mean": 0.9788898229598999, "std": 0.9996462464332581, "fourier": [17.0156572952838, 17.416448590232054, 18.39182121169501, 20.705143197329757, 88.10008811950684], "input_correlations": [-0.3300947887745947, -0.07495312991002358, 0.22242745654709795, -0.0863709332701391, 0.7978016369387101, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7317824363708496, "pre_activation_std": 1.348246693611145}, "3": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.4803981545032042, -0.3263636080859045, -0.45518649681323864, 0.4080974585741713, 0.5798160517008837, 0.0, 0.0, 0.0], "pre_activation_mean": 0.012479236349463463, "pre_activation_std": 1.3945324420928955}, "4": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.31296479359471535, 0.333377646467888, -0.34786984381675995, 0.28208188700401254, 0.5902279538634929, 0.0, 0.0, 0.0], "pre_activation_mean": 0.26027435064315796, "pre_activation_std": 0.726063072681427}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", 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"val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4902677983045578, "train_acc": 0.885, "val_loss": 0.4543398320674896, "val_acc": 0.9}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.3917580544948578, "train_acc": 0.875, "val_loss": 0.2911953032016754, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.3191148340702057, "train_acc": 0.885, "val_loss": 0.23847566545009613, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.2195914089679718, "train_acc": 0.915, "val_loss": 0.7076539397239685, "val_acc": 0.72}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.3260299414396286, "train_acc": 0.835, "val_loss": 0.3004729449748993, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.2851300686597824, "train_acc": 0.905, "val_loss": 0.2598005533218384, "val_acc": 0.9}], "summary": {"total_epochs": 11, "degraded_epochs": 3, "improved_epochs": 8, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7295581698417664, "final_val_loss": 0.6700175404548645, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.6093656420707703, "final_val_loss": 0.2598005533218384, "initial_val_acc": 0.92, "final_val_acc": 0.9, "best_val_acc": 0.94, "best_epoch": 6}, "improvement": 0.5599999999999999, "first_improvement_epoch": 2}} |
49 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.56, "improved_accuracy": 0.9, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1955, "learning_rate": 0.09855088108934446, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.2.weight": [
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],
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"network.4.weight": [
[
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],
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],
"network.6.weight": [
[
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[
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[
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[
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],
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"network.8.weight": [
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[
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[
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0.496096,
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],
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],
"network.10.weight": [
[
0.349399,
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],
"network.10.bias": [
0.207088
]
}
## Activation Signature
### 0
mean: [3.884974, 4.902263, 3.557330, 4.438749, -0.082882, -0.079060]
std: [6.027472, 5.858046, 4.593354, 5.965509, 0.053432, 0.074639]
fourier: [[96.835068, 100.990583, 101.790010, 105.100710, 349.647612], [93.287139, 95.206971, 97.611366, 98.195408, 441.203733], [72.485433, 75.444820, 76.703564, 77.852550, 320.159682], [94.584870, 98.850085, 98.931414, 102.000448, 399.487442], [0.870176, 0.906678, 1.134347, 1.193587, 7.459337], [1.172703, 1.292902, 1.293830, 1.657750, 7.115426]]
input_correlations: [[-0.928502, -0.431632, -0.131586, 0.240200, -0.183846, 0.000000, 0.000000, 0.000000], [-0.117214, -0.050710, -0.817636, -0.364059, -0.590147, 0.000000, 0.000000, 0.000000], [0.860640, 0.588188, 0.093531, -0.209320, -0.034941, 0.000000, 0.000000, 0.000000], [-0.926834, -0.281697, -0.276511, 0.280195, -0.386555, 0.000000, 0.000000, 0.000000], [0.785140, 0.640232, 0.256523, 0.158609, -0.321406, 0.000000, 0.000000, 0.000000], [0.159701, -0.636446, -0.597873, -0.484735, 0.090647, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.363906, -2.501650, 1.643551, -1.103376, 3.478694, -2.250959]
pre_activation_std: [3.327813, 1.577995, 3.472426, 3.182235, 4.628067, 1.312904]
### 2
mean: [-3.971538, 3.942966, 4.631886, -4.988153, -5.791742, -1.938993]
std: [4.835697, 5.259377, 5.931317, 6.178253, 5.717670, 1.961826]
fourier: [[76.347018, 77.201690, 78.140764, 81.030339, 357.438433], [83.870238, 85.638949, 86.028140, 89.066773, 354.866939], [93.195112, 95.927602, 99.185335, 99.846170, 416.869787], [97.445373, 99.345684, 100.022922, 107.044627, 448.933800], [93.258602, 95.627046, 101.017506, 108.592939, 521.256718], [31.000838, 33.831331, 34.368658, 36.617046, 174.509373]]
input_correlations: [[0.385654, 0.075021, -0.981389, 0.313140, -0.946374, -0.101119, 0.000000, 0.000000], [-0.358306, -0.071688, 0.984745, -0.289449, 0.949543, 0.104259, 0.000000, 0.000000], [-0.314049, -0.044089, 0.958520, -0.214320, 0.976930, 0.165317, 0.000000, 0.000000], [0.284857, 0.018272, -0.959322, 0.213716, -0.980289, -0.174951, 0.000000, 0.000000], [-0.033272, -0.109519, -0.846759, -0.113603, -0.984928, -0.344283, 0.000000, 0.000000], [-0.226492, -0.090110, -0.593025, -0.481150, -0.850457, -0.421887, 0.000000, 0.000000]]
pre_activation_mean: [-3.971538, 3.942966, 4.631886, -4.988153, -5.791742, -1.938993]
pre_activation_std: [4.835697, 5.259377, 5.931317, 6.178253, 5.717670, 1.961826]
### 4
mean: [-4.083740, -3.595546, 5.391181, -2.978146, -4.657588, -2.754118]
std: [5.215145, 3.749675, 7.070433, 3.131686, 5.692596, 3.407087]
fourier: [[83.387478, 84.049302, 87.272747, 87.318953, 367.536592], [58.223607, 61.839059, 63.157872, 63.432781, 323.599187], [113.150049, 113.491133, 116.202518, 118.557239, 485.206295], [49.475721, 50.573665, 53.428305, 54.262606, 268.033176], [89.386541, 92.577456, 94.887445, 95.465845, 419.182955], [53.027289, 56.208650, 56.862283, 57.740741, 247.870651]]
input_correlations: [[-0.071674, -0.997955, -0.997636, -0.204515, -0.150627, 0.090471, 0.000000, 0.000000], [-0.101552, -0.999205, -0.995893, -0.221985, -0.149583, 0.099404, 0.000000, 0.000000], [0.061389, 0.997403, 0.998374, 0.193090, 0.150768, -0.119863, 0.000000, 0.000000], [-0.087041, -0.998377, -0.985484, -0.203213, -0.110728, 0.086990, 0.000000, 0.000000], [-0.069688, -0.999101, -0.996432, -0.194843, -0.143216, 0.104525, 0.000000, 0.000000], [-0.086263, -0.999382, -0.994819, -0.206003, -0.143239, 0.084389, 0.000000, 0.000000]]
pre_activation_mean: [-4.083740, -3.595546, 5.391181, -2.978146, -4.657588, -2.754118]
pre_activation_std: [5.215145, 3.749675, 7.070433, 3.131686, 5.692596, 3.407087]
### 6
mean: [-3.167192, 2.414012, 2.287353, 3.055363, -3.317549, 2.793324]
std: [3.572031, 2.747849, 2.472696, 4.858923, 4.220469, 3.153981]
fourier: [[57.253295, 57.425674, 58.772429, 60.356607, 285.047233], [43.769004, 44.917606, 45.502342, 45.993779, 217.261127], [39.511802, 39.682657, 40.594487, 42.238869, 205.861818], [76.692661, 79.478370, 79.988471, 82.490700, 274.982682], [67.117916, 68.542859, 70.367439, 70.673391, 298.579441], [50.364508, 50.980799, 52.453152, 52.661838, 251.399189]]
input_correlations: [[-0.304654, -0.737277, -0.999009, -0.780141, -0.496320, -0.650768, 0.000000, 0.000000], [0.327880, 0.745123, 0.999790, 0.787558, 0.518288, 0.665496, 0.000000, 0.000000], [0.296139, 0.727234, 0.998284, 0.771161, 0.484287, 0.644668, 0.000000, 0.000000], [0.345606, 0.751836, 0.999993, 0.797484, 0.533493, 0.680546, 0.000000, 0.000000], [-0.325020, -0.742626, -0.999724, -0.787996, -0.513172, -0.666576, 0.000000, 0.000000], [0.320210, 0.745753, 0.999671, 0.790012, 0.512189, 0.663845, 0.000000, 0.000000]]
pre_activation_mean: [-3.167192, 2.414012, 2.287353, 3.055363, -3.317549, 2.793324]
pre_activation_std: [3.572031, 2.747849, 2.472696, 4.858923, 4.220469, 3.153981]
### 8
mean: [3.800862, 4.961497, 3.627149, 4.498206, -1.199978, -2.757149]
std: [6.091056, 5.818605, 4.551969, 5.929236, 1.426149, 3.670203]
fourier: [[96.746901, 101.194241, 101.514182, 104.272357, 342.077525], [92.650406, 94.329529, 97.192148, 97.736781, 446.534744], [72.217204, 73.929591, 76.138083, 76.783809, 326.443472], [93.491982, 97.429810, 99.008979, 100.395920, 404.838533], [22.994716, 23.032215, 24.309422, 25.101466, 107.997997], [58.206193, 60.617538, 62.270956, 62.420839, 248.143423]]
input_correlations: [[0.659437, 0.999612, 0.999258, 0.999799, 0.479386, 0.999486, 0.000000, 0.000000], [0.646032, 0.999735, 0.999888, 0.998707, 0.454588, 0.999805, 0.000000, 0.000000], [0.643336, 0.999606, 0.999912, 0.998866, 0.454884, 0.999665, 0.000000, 0.000000], [0.654526, 0.999797, 0.999586, 0.999456, 0.469413, 0.999770, 0.000000, 0.000000], [-0.690504, -0.998924, -0.997206, -0.999239, -0.510845, -0.998531, 0.000000, 0.000000], [-0.640974, -0.998863, -0.999451, -0.999305, -0.464555, -0.998766, 0.000000, 0.000000]]
pre_activation_mean: [3.800862, 4.961497, 3.627149, 4.498206, -1.199978, -2.757149]
pre_activation_std: [6.091056, 5.818605, 4.551969, 5.929236, 1.426149, 3.670203]
### 10
mean: [-4.786655]
std: [6.021553]
fourier: [[96.109389, 97.845898, 100.019591, 100.666649, 430.798978]]
input_correlations: [[-0.997787, -0.999977, -0.999777, -0.999572, -0.676539, -0.588517, 0.000000, 0.000000]]
pre_activation_mean: [-4.786655]
pre_activation_std: [6.021553]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-1.418373,
-0.538971,
0.396402,
0.499397,
-0.224486
],
[
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0.176725,
-0.66373,
-0.27195,
-0.327952
],
[
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0.921786,
-0.428273,
-0.531965,
-0.140588
],
[
-1.315676,
-0.22122,
0.127959,
0.497466,
-0.518942
],
[
1.730782,
0.811955,
0.116999,
0.357551,
-1.237149
],
[
0.329595,
-0.397008,
-0.454538,
-0.186966,
0.133047
]
],
"network.0.bias": [
-0.238798,
-0.569863,
0.528945,
0.242969,
0.359939,
-0.751358
],
"network.2.weight": [
[
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1.039865
],
[
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-1.132785,
0.921001,
-0.031339,
0.580359,
-1.416481
],
[
-0.818009,
-1.352826,
0.530037,
0.051222,
1.016465,
-0.470464
],
[
0.260205,
1.156217,
-0.493296,
0.458526,
-1.116315,
1.006931
],
[
-0.751533,
-0.432071,
-0.278663,
-0.705717,
-1.181236,
-0.922586
],
[
0.476743,
-0.41492,
-0.010196,
-1.532188,
-0.387176,
-0.615416
]
],
"network.2.bias": [
-0.440095,
-0.062386,
-0.102913,
0.052698,
-0.110911,
0.078675
],
"network.4.weight": [
[
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-0.513632,
-0.431706,
0.276597,
-0.089357,
-1.030549
],
[
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-0.155847,
-0.523988,
-0.479623,
-0.000194
],
[
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0.657524,
-0.020439,
0.643416,
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],
[
0.333074,
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0.199575,
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1.035653,
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[
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0.312546,
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[
0.014087,
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]
],
"network.4.bias": [
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],
"network.6.weight": [
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[
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[
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[
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0.541171,
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[
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[
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0.022955,
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],
"network.6.bias": [
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],
"network.8.weight": [
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[
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[
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[
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],
"network.8.bias": [
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"network.10.weight": [
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [3.884974, 4.902263, 3.557330, 4.438749, -0.082882, -0.079060]
std: [6.027472, 5.858046, 4.593354, 5.965509, 0.053432, 0.074639]
fourier: [[96.835068, 100.990583, 101.790010, 105.100710, 349.647612], [93.287139, 95.206971, 97.611366, 98.195408, 441.203733], [72.485433, 75.444820, 76.703564, 77.852550, 320.159682], [94.584870, 98.850085, 98.931414, 102.000448, 399.487442], [0.870176, 0.906678, 1.134347, 1.193587, 7.459337], [1.172703, 1.292902, 1.293830, 1.657750, 7.115426]]
input_correlations: [[-0.928502, -0.431632, -0.131586, 0.240200, -0.183846, 0.000000, 0.000000, 0.000000], [-0.117214, -0.050710, -0.817636, -0.364059, -0.590147, 0.000000, 0.000000, 0.000000], [0.860640, 0.588188, 0.093531, -0.209320, -0.034941, 0.000000, 0.000000, 0.000000], [-0.926834, -0.281697, -0.276511, 0.280195, -0.386555, 0.000000, 0.000000, 0.000000], [0.785140, 0.640232, 0.256523, 0.158609, -0.321406, 0.000000, 0.000000, 0.000000], [0.159701, -0.636446, -0.597873, -0.484735, 0.090647, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.363906, -2.501650, 1.643551, -1.103376, 3.478694, -2.250959]
pre_activation_std: [3.327813, 1.577995, 3.472426, 3.182235, 4.628067, 1.312904]
### 2
mean: [-3.971538, 3.942966, 4.631886, -4.988153, -5.791742, -1.938993]
std: [4.835697, 5.259377, 5.931317, 6.178253, 5.717670, 1.961826]
fourier: [[76.347018, 77.201690, 78.140764, 81.030339, 357.438433], [83.870238, 85.638949, 86.028140, 89.066773, 354.866939], [93.195112, 95.927602, 99.185335, 99.846170, 416.869787], [97.445373, 99.345684, 100.022922, 107.044627, 448.933800], [93.258602, 95.627046, 101.017506, 108.592939, 521.256718], [31.000838, 33.831331, 34.368658, 36.617046, 174.509373]]
input_correlations: [[0.385654, 0.075021, -0.981389, 0.313140, -0.946374, -0.101119, 0.000000, 0.000000], [-0.358306, -0.071688, 0.984745, -0.289449, 0.949543, 0.104259, 0.000000, 0.000000], [-0.314049, -0.044089, 0.958520, -0.214320, 0.976930, 0.165317, 0.000000, 0.000000], [0.284857, 0.018272, -0.959322, 0.213716, -0.980289, -0.174951, 0.000000, 0.000000], [-0.033272, -0.109519, -0.846759, -0.113603, -0.984928, -0.344283, 0.000000, 0.000000], [-0.226492, -0.090110, -0.593025, -0.481150, -0.850457, -0.421887, 0.000000, 0.000000]]
pre_activation_mean: [-3.971538, 3.942966, 4.631886, -4.988153, -5.791742, -1.938993]
pre_activation_std: [4.835697, 5.259377, 5.931317, 6.178253, 5.717670, 1.961826]
### 4
mean: [-4.083740, -3.595546, 5.391181, -2.978146, -4.657588, -2.754118]
std: [5.215145, 3.749675, 7.070433, 3.131686, 5.692596, 3.407087]
fourier: [[83.387478, 84.049302, 87.272747, 87.318953, 367.536592], [58.223607, 61.839059, 63.157872, 63.432781, 323.599187], [113.150049, 113.491133, 116.202518, 118.557239, 485.206295], [49.475721, 50.573665, 53.428305, 54.262606, 268.033176], [89.386541, 92.577456, 94.887445, 95.465845, 419.182955], [53.027289, 56.208650, 56.862283, 57.740741, 247.870651]]
input_correlations: [[-0.071674, -0.997955, -0.997636, -0.204515, -0.150627, 0.090471, 0.000000, 0.000000], [-0.101552, -0.999205, -0.995893, -0.221985, -0.149583, 0.099404, 0.000000, 0.000000], [0.061389, 0.997403, 0.998374, 0.193090, 0.150768, -0.119863, 0.000000, 0.000000], [-0.087041, -0.998377, -0.985484, -0.203213, -0.110728, 0.086990, 0.000000, 0.000000], [-0.069688, -0.999101, -0.996432, -0.194843, -0.143216, 0.104525, 0.000000, 0.000000], [-0.086263, -0.999382, -0.994819, -0.206003, -0.143239, 0.084389, 0.000000, 0.000000]]
pre_activation_mean: [-4.083740, -3.595546, 5.391181, -2.978146, -4.657588, -2.754118]
pre_activation_std: [5.215145, 3.749675, 7.070433, 3.131686, 5.692596, 3.407087]
### 6
mean: [-3.167192, 2.414012, 2.287353, 3.055363, -3.317549, 2.793324]
std: [3.572031, 2.747849, 2.472696, 4.858923, 4.220469, 3.153981]
fourier: [[57.253295, 57.425674, 58.772429, 60.356607, 285.047233], [43.769004, 44.917606, 45.502342, 45.993779, 217.261127], [39.511802, 39.682657, 40.594487, 42.238869, 205.861818], [76.692661, 79.478370, 79.988471, 82.490700, 274.982682], [67.117916, 68.542859, 70.367439, 70.673391, 298.579441], [50.364508, 50.980799, 52.453152, 52.661838, 251.399189]]
input_correlations: [[-0.304654, -0.737277, -0.999009, -0.780141, -0.496320, -0.650768, 0.000000, 0.000000], [0.327880, 0.745123, 0.999790, 0.787558, 0.518288, 0.665496, 0.000000, 0.000000], [0.296139, 0.727234, 0.998284, 0.771161, 0.484287, 0.644668, 0.000000, 0.000000], [0.345606, 0.751836, 0.999993, 0.797484, 0.533493, 0.680546, 0.000000, 0.000000], [-0.325020, -0.742626, -0.999724, -0.787996, -0.513172, -0.666576, 0.000000, 0.000000], [0.320210, 0.745753, 0.999671, 0.790012, 0.512189, 0.663845, 0.000000, 0.000000]]
pre_activation_mean: [-3.167192, 2.414012, 2.287353, 3.055363, -3.317549, 2.793324]
pre_activation_std: [3.572031, 2.747849, 2.472696, 4.858923, 4.220469, 3.153981]
### 8
mean: [3.800862, 4.961497, 3.627149, 4.498206, -1.199978, -2.757149]
std: [6.091056, 5.818605, 4.551969, 5.929236, 1.426149, 3.670203]
fourier: [[96.746901, 101.194241, 101.514182, 104.272357, 342.077525], [92.650406, 94.329529, 97.192148, 97.736781, 446.534744], [72.217204, 73.929591, 76.138083, 76.783809, 326.443472], [93.491982, 97.429810, 99.008979, 100.395920, 404.838533], [22.994716, 23.032215, 24.309422, 25.101466, 107.997997], [58.206193, 60.617538, 62.270956, 62.420839, 248.143423]]
input_correlations: [[0.659437, 0.999612, 0.999258, 0.999799, 0.479386, 0.999486, 0.000000, 0.000000], [0.646032, 0.999735, 0.999888, 0.998707, 0.454588, 0.999805, 0.000000, 0.000000], [0.643336, 0.999606, 0.999912, 0.998866, 0.454884, 0.999665, 0.000000, 0.000000], [0.654526, 0.999797, 0.999586, 0.999456, 0.469413, 0.999770, 0.000000, 0.000000], [-0.690504, -0.998924, -0.997206, -0.999239, -0.510845, -0.998531, 0.000000, 0.000000], [-0.640974, -0.998863, -0.999451, -0.999305, -0.464555, -0.998766, 0.000000, 0.000000]]
pre_activation_mean: [3.800862, 4.961497, 3.627149, 4.498206, -1.199978, -2.757149]
pre_activation_std: [6.091056, 5.818605, 4.551969, 5.929236, 1.426149, 3.670203]
### 10
mean: [-4.786655]
std: [6.021553]
fourier: [[96.109389, 97.845898, 100.019591, 100.666649, 430.798978]]
input_correlations: [[-0.997787, -0.999977, -0.999777, -0.999572, -0.676539, -0.588517, 0.000000, 0.000000]]
pre_activation_mean: [-4.786655]
pre_activation_std: [6.021553]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-1.418373, -0.538971, 0.396402, 0.499397, -0.224486], [0.096666, 0.176725, -0.66373, -0.27195, -0.327952], [1.320819, 0.921786, -0.428273, -0.531965, -0.140588], [-1.315676, -0.22122, 0.127959, 0.497466, -0.518942], [1.730782, 0.811955, 0.116999, 0.357551, -1.237149], [0.329595, -0.397008, -0.454538, -0.186966, 0.133047]], "network.0.bias": [-0.238798, -0.569863, 0.528945, 0.242969, 0.359939, -0.751358], "network.2.weight": [[0.620576, 1.024968, 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-0.523362, 0.388473, 0.993038, 0.555161], [-0.119616, -0.078601, 0.397782, -0.496884, -0.115385, -0.472064], [-0.809644, -0.618878, 0.367603, -0.805224, -0.736679, 0.093743], [0.452105, -0.385946, 0.68847, 0.541171, -0.309743, -0.395851], [0.355606, 0.63268, -0.60878, 0.064961, 0.817294, 0.039724], [-0.944796, -0.515466, 0.452562, 0.029868, 0.022955, 0.222497]], "network.6.bias": [-0.142403, 0.168898, 0.105969, -0.660045, 0.087948, 0.285931], "network.8.weight": [[-0.298678, 0.40262, 0.329593, 0.776917, -0.030915, 0.13361], [-0.697112, 0.52533, 0.6408, 0.168882, -0.579507, 0.615891], [-0.712328, 0.182729, 0.599677, 0.281599, -0.532198, 0.384086], [-0.601654, 0.343542, 0.034696, 0.583255, -0.572592, 0.667122], [-0.252542, -0.567778, -0.107953, -0.025833, -0.763398, 0.188105], [0.496096, -0.195145, -1.007596, -0.605678, 0.405636, 0.711836]], "network.8.bias": [-0.68662, 0.046247, -0.126592, -0.099141, -0.140369, -0.053204], "network.10.weight": [[0.349399, -0.414127, -0.287562, -0.736886, -0.255797, 0.611976]], "network.10.bias": [0.207088]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6877061426639557, "train_acc": 0.565, "val_loss": 0.6857731342315674, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6892106533050537, "train_acc": 0.555, "val_loss": 0.6858830451965332, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6881414353847504, "train_acc": 0.565, "val_loss": 0.686551570892334, "val_acc": 0.56}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6782216429710388, "train_acc": 0.565, "val_loss": 0.6649423241615295, "val_acc": 0.56}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6340897679328918, "train_acc": 0.565, "val_loss": 0.5689161419868469, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6541130244731903, "train_acc": 0.485, "val_loss": 0.6732774376869202, "val_acc": 0.68}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.6665002703666687, "train_acc": 0.685, "val_loss": 0.6196853518486023, "val_acc": 0.6}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.609960287809372, "train_acc": 0.625, "val_loss": 0.5392653942108154, "val_acc": 0.64}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.4220326691865921, "train_acc": 0.75, "val_loss": 0.4202745854854584, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.558197408914566, "train_acc": 0.81, "val_loss": 0.4946998357772827, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.34965871274471283, "train_acc": 0.87, "val_loss": 0.6630774140357971, "val_acc": 0.76}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.3527761399745941, "train_acc": 0.83, "val_loss": 0.342466801404953, "val_acc": 0.84}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.3314826786518097, "train_acc": 0.895, "val_loss": 0.34810110926628113, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.339435338973999, "train_acc": 0.915, "val_loss": 0.3844763934612274, "val_acc": 0.82}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.268487811088562, "train_acc": 0.91, "val_loss": 0.4555215537548065, "val_acc": 0.82}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.6857731342315674, "final_val_loss": 0.5689161419868469, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.6732774376869202, "final_val_loss": 0.4555215537548065, "initial_val_acc": 0.68, "final_val_acc": 0.82, "best_val_acc": 0.9, "best_epoch": 12}, "improvement": 0.33999999999999997, "first_improvement_epoch": 4}} |
50 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.5, "improved_accuracy": 0.94, "improvement": 0.43999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5360, "learning_rate": 0.0885264373224075, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
1.503286,
0.402284,
0.432532,
0.542612,
-0.127377
],
[
1.686306,
0.581529,
0.633298,
0.668293,
0.119847
],
[
0.976078,
0.988569,
0.523645,
-0.122028,
-0.301022
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[
1.804439,
0.256344,
0.233929,
0.406434,
-0.148594
],
[
0.153987,
-0.397447,
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-0.199481,
-0.30293
]
],
"network.0.bias": [
-0.786639,
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-0.460127,
-0.237888,
0.248679
],
"network.2.weight": [
[
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-0.451004,
-0.576093,
-0.153903
],
[
0.208449,
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0.226517,
-0.268346
],
[
0.624006,
0.56849,
0.884748,
0.544075,
-0.085384
],
[
-0.551623,
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-0.043898,
-0.054091,
0.144953
],
[
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]
],
"network.2.bias": [
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],
"network.4.weight": [
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],
[
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[
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[
0.188212,
0.253486,
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],
[
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0.58696,
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],
"network.4.bias": [
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],
"network.6.weight": [
[
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],
[
0.362574,
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0.280783,
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],
[
-0.112728,
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0.20084,
0.049836
],
[
0.006535,
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0.556609
],
[
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],
"network.6.bias": [
0.033029,
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"network.8.weight": [
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[
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[
0.255434,
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0.655958,
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[
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"network.10.weight": [
[
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[
0.070583,
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[
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[
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],
"network.10.bias": [
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"network.12.weight": [
[
0.33649,
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],
"network.12.bias": [
0.79943
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 5.352421, 0.000000, 5.040031]
std: [0.000000, 0.000000, 6.724539, 0.000000, 6.299338]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [108.252145, 111.598833, 114.563100, 119.973967, 481.717881], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [101.248393, 104.371505, 107.474851, 112.429662, 453.602770]]
input_correlations: [[0.891182, 0.595000, 0.496158, 0.310319, 0.171182, 0.000000, 0.000000, 0.000000], [0.861282, 0.611731, 0.543081, 0.339749, 0.272824, 0.000000, 0.000000, 0.000000], [0.803943, 0.748404, 0.548829, 0.051023, -0.005387, 0.000000, 0.000000, 0.000000], [0.955539, 0.510367, 0.411129, 0.196069, 0.151004, 0.000000, 0.000000, 0.000000], [-0.174411, -0.654467, -0.656868, -0.536661, -0.508343, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.727181, 5.248264, 3.016834, 3.651715, -1.890359]
pre_activation_std: [3.889218, 4.807121, 3.507177, 4.052526, 1.425291]
### 2
mean: [-6.295769, -1.599460, 9.605230, -2.729230, -6.110092]
std: [6.222499, 1.085095, 9.953590, 2.560245, 5.512641]
fourier: [[101.381965, 105.944752, 110.564781, 112.798363, 566.619185], [17.324520, 17.400178, 18.234498, 20.546957, 143.951361], [164.210524, 167.763696, 175.191156, 181.931183, 864.470720], [42.450231, 42.976275, 45.491631, 46.719598, 245.630718], [91.247291, 92.979089, 95.218962, 102.396217, 549.908213]]
input_correlations: [[-0.994606, -0.984511, -0.946292, -0.986800, 0.258447, 0.000000, 0.000000, 0.000000], [-0.879018, -0.906480, -0.952227, -0.817414, 0.352899, 0.000000, 0.000000, 0.000000], [0.992866, 0.985838, 0.954750, 0.979384, -0.272640, 0.000000, 0.000000, 0.000000], [-0.999699, -0.991166, -0.923504, -0.986702, 0.271144, 0.000000, 0.000000, 0.000000], [-0.994158, -0.991580, -0.948663, -0.973739, 0.284371, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-6.295769, -1.599460, 9.605230, -2.729230, -6.110092]
pre_activation_std: [6.222499, 1.085095, 9.953590, 2.560245, 5.512641]
### 4
mean: [-0.978322, 6.173213, -5.429539, -0.610054, 5.547828]
std: [0.788180, 6.557161, 5.415159, 0.331709, 5.800087]
fourier: [[12.998492, 13.453340, 13.679035, 14.254059, 88.048966], [108.139348, 111.923389, 113.801033, 118.584877, 555.589216], [89.305678, 92.430686, 93.981319, 97.932004, 488.658531], [5.470480, 5.661904, 5.756889, 5.998891, 54.904841], [95.653834, 99.000982, 100.661840, 104.893352, 499.304502]]
input_correlations: [[0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.978322, 6.173213, -5.429539, -0.610054, 5.547828]
pre_activation_std: [0.788180, 6.557161, 5.415159, 0.331709, 5.800087]
### 6
mean: [5.195972, -4.617029, -1.715308, 4.608486, -3.853442]
std: [5.396322, 4.409919, 1.420627, 5.490015, 3.878220]
fourier: [[89.004920, 92.794979, 92.975527, 96.981111, 467.637492], [72.727459, 75.900146, 75.912435, 79.175250, 415.532638], [23.424129, 24.406439, 24.498481, 25.462430, 154.377758], [90.552146, 94.387390, 94.608651, 98.683375, 414.763720], [63.962707, 66.721375, 66.787646, 69.667052, 346.809768]]
input_correlations: [[0.000000, 0.999997, 0.000000, 0.000000, 0.999998, 0.000000, 0.000000, 0.000000], [0.000000, -0.999999, 0.000000, 0.000000, -0.999994, 0.000000, 0.000000, 0.000000], [0.000000, -1.000000, 0.000000, 0.000000, -0.999984, 0.000000, 0.000000, 0.000000], [0.000000, 0.999996, 0.000000, 0.000000, 0.999998, 0.000000, 0.000000, 0.000000], [0.000000, -0.999998, 0.000000, 0.000000, -0.999996, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [5.195972, -4.617029, -1.715308, 4.608486, -3.853442]
pre_activation_std: [5.396322, 4.409919, 1.420627, 5.490015, 3.878220]
### 8
mean: [-5.038239, -2.090451, -1.632799, 3.855692, 4.063231]
std: [5.216423, 1.822388, 1.027544, 4.917645, 5.002984]
fourier: [[85.816136, 89.285366, 90.229942, 93.277739, 453.441465], [30.066388, 31.316800, 31.421817, 32.769805, 188.140561], [17.001387, 17.537199, 17.848801, 18.581740, 146.951941], [80.337289, 82.705530, 86.329586, 86.763472, 347.012310], [81.584134, 83.765603, 87.968295, 88.142270, 365.690777]]
input_correlations: [[-0.999970, 0.000000, 0.000000, -0.999527, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, -0.999227, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999953, 0.000000, 0.000000, -0.998841, 0.000000, 0.000000, 0.000000, 0.000000], [0.999617, 0.000000, 0.000000, 0.999942, 0.000000, 0.000000, 0.000000, 0.000000], [0.999468, 0.000000, 0.000000, 0.999983, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.038239, -2.090451, -1.632799, 3.855692, 4.063231]
pre_activation_std: [5.216423, 1.822388, 1.027544, 4.917645, 5.002984]
### 10
mean: [-1.975862, -0.754964, 5.238036, -1.161474, 4.955762]
std: [2.212939, 0.556071, 6.817591, 1.015702, 6.367939]
fourier: [[36.141481, 36.141861, 38.220797, 39.507856, 177.827590], [8.949691, 9.220252, 9.459354, 9.932412, 67.946756], [111.308639, 111.374744, 117.719224, 121.716912, 471.423245], [16.560448, 16.621817, 17.570726, 18.131851, 104.532683], [103.792165, 104.174439, 109.807740, 113.696714, 446.018547]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999983, -0.999994, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.999826, -0.999613, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.999986, 0.999993, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.999965, -1.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.999995, 0.999982, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.975862, -0.754964, 5.238036, -1.161474, 4.955762]
pre_activation_std: [2.212939, 0.556071, 6.817591, 1.015702, 6.367939]
### 12
mean: [-4.448692]
std: [6.583446]
fourier: [[105.932113, 109.204915, 112.207264, 117.469623, 400.382323]]
input_correlations: [[0.000000, 0.000000, -1.000000, 0.000000, -0.999998, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.448692]
pre_activation_std: [6.583446]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
1.503286,
0.402284,
0.432532,
0.542612,
-0.127377
],
[
1.686306,
0.581529,
0.633298,
0.668293,
0.119847
],
[
0.976078,
0.988569,
0.523645,
-0.122028,
-0.301022
],
[
1.804439,
0.256344,
0.233929,
0.406434,
-0.148594
],
[
0.153987,
-0.397447,
-0.385392,
-0.199481,
-0.30293
]
],
"network.0.bias": [
-0.786639,
-0.813743,
-0.460127,
-0.237888,
0.248679
],
"network.2.weight": [
[
-0.343332,
-0.262988,
-0.451004,
-0.576093,
-0.153903
],
[
0.208449,
-0.379101,
-0.287817,
0.226517,
-0.268346
],
[
0.624006,
0.56849,
0.884748,
0.544075,
-0.085384
],
[
-0.551623,
-0.02545,
-0.043898,
-0.054091,
0.144953
],
[
-0.567382,
-0.455478,
-0.401215,
0.002796,
-0.329223
]
],
"network.2.bias": [
-0.027339,
-0.287787,
-0.613185,
-0.151314,
-0.240805
],
"network.4.weight": [
[
0.135392,
0.131135,
-0.079763,
-0.025427,
0.037063
],
[
-0.092821,
-0.015066,
0.663574,
0.131585,
-0.023351
],
[
-0.217401,
-0.33418,
-0.548005,
-0.00449,
-0.487195
],
[
0.188212,
0.253486,
-0.033568,
-0.424176,
-0.311681
],
[
0.006279,
0.312718,
0.58696,
-0.322443,
-0.042585
]
],
"network.4.bias": [
-0.206461,
-0.248189,
-0.126495,
-0.285212,
-0.132175
],
"network.6.weight": [
[
0.407293,
0.384464,
0.231031,
0.025177,
0.499143
],
[
0.362574,
-0.498131,
-0.043006,
0.280783,
-0.20035
],
[
-0.112728,
-0.261836,
-0.133338,
0.20084,
0.049836
],
[
0.006535,
0.347891,
-0.132554,
-0.207683,
0.556609
],
[
0.432219,
-0.349369,
-0.360552,
0.422018,
-0.276283
]
],
"network.6.bias": [
0.033029,
-0.411348,
-0.36793,
-0.647276,
-0.148315
],
"network.8.weight": [
[
-0.772991,
0.32762,
0.400094,
-0.193774,
0.102237
],
[
-0.345331,
0.266681,
0.019296,
0.007627,
-0.336387
],
[
-0.238378,
-0.043089,
-0.445484,
0.048004,
-0.415579
],
[
0.255434,
-0.260024,
-0.392833,
0.655958,
0.211595
],
[
0.140403,
-0.349784,
-0.093528,
0.786748,
0.101322
]
],
"network.8.bias": [
-0.108976,
-0.33205,
-0.620329,
-0.56159,
-0.37247
],
"network.10.weight": [
[
-0.129677,
0.088166,
0.004919,
-0.169452,
-0.282585
],
[
-0.209759,
-0.385072,
-0.008127,
-0.350437,
0.229409
],
[
0.070583,
0.035198,
0.209577,
0.588698,
0.80555
],
[
0.350095,
-0.320903,
-0.313061,
-0.017138,
-0.188867
],
[
0.010946,
-0.382445,
0.356557,
0.867468,
0.442527
]
],
"network.10.bias": [
-0.134491,
-0.312821,
-0.430413,
-0.312297,
-0.317741
],
"network.12.weight": [
[
0.33649,
0.175292,
-0.691313,
-0.165043,
-0.307126
]
],
"network.12.bias": [
0.79943
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 5.352421, 0.000000, 5.040031]
std: [0.000000, 0.000000, 6.724539, 0.000000, 6.299338]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [108.252145, 111.598833, 114.563100, 119.973967, 481.717881], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [101.248393, 104.371505, 107.474851, 112.429662, 453.602770]]
input_correlations: [[0.891182, 0.595000, 0.496158, 0.310319, 0.171182, 0.000000, 0.000000, 0.000000], [0.861282, 0.611731, 0.543081, 0.339749, 0.272824, 0.000000, 0.000000, 0.000000], [0.803943, 0.748404, 0.548829, 0.051023, -0.005387, 0.000000, 0.000000, 0.000000], [0.955539, 0.510367, 0.411129, 0.196069, 0.151004, 0.000000, 0.000000, 0.000000], [-0.174411, -0.654467, -0.656868, -0.536661, -0.508343, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.727181, 5.248264, 3.016834, 3.651715, -1.890359]
pre_activation_std: [3.889218, 4.807121, 3.507177, 4.052526, 1.425291]
### 2
mean: [-6.295769, -1.599460, 9.605230, -2.729230, -6.110092]
std: [6.222499, 1.085095, 9.953590, 2.560245, 5.512641]
fourier: [[101.381965, 105.944752, 110.564781, 112.798363, 566.619185], [17.324520, 17.400178, 18.234498, 20.546957, 143.951361], [164.210524, 167.763696, 175.191156, 181.931183, 864.470720], [42.450231, 42.976275, 45.491631, 46.719598, 245.630718], [91.247291, 92.979089, 95.218962, 102.396217, 549.908213]]
input_correlations: [[-0.994606, -0.984511, -0.946292, -0.986800, 0.258447, 0.000000, 0.000000, 0.000000], [-0.879018, -0.906480, -0.952227, -0.817414, 0.352899, 0.000000, 0.000000, 0.000000], [0.992866, 0.985838, 0.954750, 0.979384, -0.272640, 0.000000, 0.000000, 0.000000], [-0.999699, -0.991166, -0.923504, -0.986702, 0.271144, 0.000000, 0.000000, 0.000000], [-0.994158, -0.991580, -0.948663, -0.973739, 0.284371, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-6.295769, -1.599460, 9.605230, -2.729230, -6.110092]
pre_activation_std: [6.222499, 1.085095, 9.953590, 2.560245, 5.512641]
### 4
mean: [-0.978322, 6.173213, -5.429539, -0.610054, 5.547828]
std: [0.788180, 6.557161, 5.415159, 0.331709, 5.800087]
fourier: [[12.998492, 13.453340, 13.679035, 14.254059, 88.048966], [108.139348, 111.923389, 113.801033, 118.584877, 555.589216], [89.305678, 92.430686, 93.981319, 97.932004, 488.658531], [5.470480, 5.661904, 5.756889, 5.998891, 54.904841], [95.653834, 99.000982, 100.661840, 104.893352, 499.304502]]
input_correlations: [[0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.978322, 6.173213, -5.429539, -0.610054, 5.547828]
pre_activation_std: [0.788180, 6.557161, 5.415159, 0.331709, 5.800087]
### 6
mean: [5.195972, -4.617029, -1.715308, 4.608486, -3.853442]
std: [5.396322, 4.409919, 1.420627, 5.490015, 3.878220]
fourier: [[89.004920, 92.794979, 92.975527, 96.981111, 467.637492], [72.727459, 75.900146, 75.912435, 79.175250, 415.532638], [23.424129, 24.406439, 24.498481, 25.462430, 154.377758], [90.552146, 94.387390, 94.608651, 98.683375, 414.763720], [63.962707, 66.721375, 66.787646, 69.667052, 346.809768]]
input_correlations: [[0.000000, 0.999997, 0.000000, 0.000000, 0.999998, 0.000000, 0.000000, 0.000000], [0.000000, -0.999999, 0.000000, 0.000000, -0.999994, 0.000000, 0.000000, 0.000000], [0.000000, -1.000000, 0.000000, 0.000000, -0.999984, 0.000000, 0.000000, 0.000000], [0.000000, 0.999996, 0.000000, 0.000000, 0.999998, 0.000000, 0.000000, 0.000000], [0.000000, -0.999998, 0.000000, 0.000000, -0.999996, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [5.195972, -4.617029, -1.715308, 4.608486, -3.853442]
pre_activation_std: [5.396322, 4.409919, 1.420627, 5.490015, 3.878220]
### 8
mean: [-5.038239, -2.090451, -1.632799, 3.855692, 4.063231]
std: [5.216423, 1.822388, 1.027544, 4.917645, 5.002984]
fourier: [[85.816136, 89.285366, 90.229942, 93.277739, 453.441465], [30.066388, 31.316800, 31.421817, 32.769805, 188.140561], [17.001387, 17.537199, 17.848801, 18.581740, 146.951941], [80.337289, 82.705530, 86.329586, 86.763472, 347.012310], [81.584134, 83.765603, 87.968295, 88.142270, 365.690777]]
input_correlations: [[-0.999970, 0.000000, 0.000000, -0.999527, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, -0.999227, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999953, 0.000000, 0.000000, -0.998841, 0.000000, 0.000000, 0.000000, 0.000000], [0.999617, 0.000000, 0.000000, 0.999942, 0.000000, 0.000000, 0.000000, 0.000000], [0.999468, 0.000000, 0.000000, 0.999983, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-5.038239, -2.090451, -1.632799, 3.855692, 4.063231]
pre_activation_std: [5.216423, 1.822388, 1.027544, 4.917645, 5.002984]
### 10
mean: [-1.975862, -0.754964, 5.238036, -1.161474, 4.955762]
std: [2.212939, 0.556071, 6.817591, 1.015702, 6.367939]
fourier: [[36.141481, 36.141861, 38.220797, 39.507856, 177.827590], [8.949691, 9.220252, 9.459354, 9.932412, 67.946756], [111.308639, 111.374744, 117.719224, 121.716912, 471.423245], [16.560448, 16.621817, 17.570726, 18.131851, 104.532683], [103.792165, 104.174439, 109.807740, 113.696714, 446.018547]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999983, -0.999994, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.999826, -0.999613, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.999986, 0.999993, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.999965, -1.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.999995, 0.999982, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.975862, -0.754964, 5.238036, -1.161474, 4.955762]
pre_activation_std: [2.212939, 0.556071, 6.817591, 1.015702, 6.367939]
### 12
mean: [-4.448692]
std: [6.583446]
fourier: [[105.932113, 109.204915, 112.207264, 117.469623, 400.382323]]
input_correlations: [[0.000000, 0.000000, -1.000000, 0.000000, -0.999998, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.448692]
pre_activation_std: [6.583446]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"train_loss": 0.26774534583091736, "train_acc": 0.925, "val_loss": 0.2429095059633255, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.23348646610975266, "train_acc": 0.925, "val_loss": 0.27019450068473816, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.23365086317062378, "train_acc": 0.93, "val_loss": 0.2183610200881958, "val_acc": 0.94}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.692647397518158, "final_val_loss": 0.5890681147575378, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.47464561462402344, "final_val_loss": 0.2183610200881958, "initial_val_acc": 0.82, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 8}, "improvement": 0.43999999999999995, "first_improvement_epoch": 3}} |
51 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.7, "improved_accuracy": 0.9, "improvement": 0.20000000000000007, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9169, "learning_rate": 0.02856298291523507, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [-0.024038, -0.154271, 1.658703, 1.223586, 1.368681, -0.058536]
std: [0.336443, 0.029397, 0.818638, 0.433495, 0.694338, 0.239221]
fourier: [[4.681353, 4.796947, 5.235961, 5.268654, 5.336315], [0.407720, 0.414541, 0.423132, 0.464897, 13.884419], [14.849370, 15.071520, 15.411577, 15.875592, 149.283247], [7.687285, 7.775714, 7.859938, 8.030720, 110.122719], [12.257391, 12.293065, 12.669568, 13.322083, 123.181315], [3.388325, 3.487774, 3.590716, 3.982888, 5.268279]]
input_correlations: [[-0.163279, -0.279540, -0.317224, -0.613587, -0.853080, 0.000000, 0.000000, 0.000000], [-0.440560, 0.345050, 0.372222, 0.637102, 0.345968, 0.000000, 0.000000, 0.000000], [-0.855482, -0.162069, -0.006609, 0.214302, 0.291960, 0.000000, 0.000000, 0.000000], [-0.194623, -0.893425, -0.185246, -0.017091, 0.364585, 0.000000, 0.000000, 0.000000], [-0.366524, -0.092514, 0.610800, 0.387540, 0.463133, 0.000000, 0.000000, 0.000000], [0.755413, 0.754891, -0.024115, 0.097217, -0.093147, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.125378, 1.433421, 0.339585, -0.199287, 1.232404, 1.243377]
pre_activation_std: [1.111468, 1.464271, 1.789794, 1.669626, 1.806876, 1.643474]
### 2
mean: [0.320372, 0.091942, -0.939851, -0.832678, 1.013661, -0.194663]
std: [1.503171, 0.811293, 0.729789, 0.672505, 0.619339, 2.235674]
fourier: [[24.024414, 24.215036, 27.732680, 27.868227, 28.833497], [12.075174, 12.475322, 13.835401, 14.417800, 15.293519], [11.570419, 13.392149, 13.507423, 17.421045, 84.586576], [10.840166, 12.205056, 12.857005, 15.019694, 74.940992], [10.258809, 10.268515, 11.158038, 12.835453, 91.229517], [36.040525, 37.049054, 37.680934, 38.086681, 41.576248]]
input_correlations: [[-0.102954, 0.846321, 0.812177, -0.119638, 0.790908, -0.513029, 0.000000, 0.000000], [-0.216976, 0.819261, 0.606699, -0.392499, 0.748842, -0.133966, 0.000000, 0.000000], [0.178949, -0.411891, -0.192058, 0.475934, -0.017046, -0.780091, 0.000000, 0.000000], [0.125272, -0.157856, 0.005968, 0.032646, 0.281914, -0.803273, 0.000000, 0.000000], [-0.113958, 0.292064, 0.065012, 0.594167, 0.688337, -0.113510, 0.000000, 0.000000], [0.061567, -0.742338, -0.764784, -0.256214, -0.898954, 0.735374, 0.000000, 0.000000]]
pre_activation_mean: [0.320372, 0.091942, -0.939851, -0.832678, 1.013661, -0.194663]
pre_activation_std: [1.503171, 0.811293, 0.729789, 0.672505, 0.619339, 2.235674]
### 4
mean: [-0.288460, 0.958978, -0.695666, -0.891335, -0.178797, 1.386472]
std: [0.914899, 0.381545, 0.456116, 0.256782, 0.628683, 0.735909]
fourier: [[14.242818, 14.267795, 14.980579, 15.110723, 25.961424], [6.539649, 6.940999, 7.200172, 8.482311, 86.308048], [6.444852, 6.519524, 7.068981, 10.445250, 62.609955], [3.536902, 4.636267, 4.691837, 5.363371, 80.220126], [9.614385, 9.844851, 10.356417, 10.813541, 16.091743], [12.854731, 13.029051, 14.146224, 14.404981, 124.782503]]
input_correlations: [[0.920450, 0.858406, -0.335518, 0.234427, -0.160158, -0.325229, 0.000000, 0.000000], [-0.180978, -0.112545, 0.291820, 0.069223, 0.755197, 0.450438, 0.000000, 0.000000], [-0.669717, -0.510058, 0.367011, -0.123445, 0.474512, -0.088043, 0.000000, 0.000000], [-0.714889, -0.735861, 0.165328, -0.302095, 0.125376, -0.215796, 0.000000, 0.000000], [0.912379, 0.835462, -0.354889, 0.158723, 0.220992, -0.778611, 0.000000, 0.000000], [-0.502711, -0.433122, 0.364596, 0.080483, 0.066687, 0.951544, 0.000000, 0.000000]]
pre_activation_mean: [-0.288460, 0.958978, -0.695666, -0.891335, -0.178797, 1.386472]
pre_activation_std: [0.914899, 0.381545, 0.456116, 0.256782, 0.628683, 0.735909]
### 6
mean: [-0.658098, -0.691105, 1.744640, 1.340814, 1.475622, -0.535746]
std: [0.784442, 0.253065, 0.769195, 0.397588, 0.645896, 0.600533]
fourier: [[11.418724, 12.318012, 12.754730, 14.356181, 59.228782], [3.903273, 4.009817, 4.033172, 4.385266, 62.199410], [13.843101, 14.155024, 14.504204, 14.809426, 157.017638], [6.955674, 7.010768, 7.304738, 7.308432, 120.673263], [11.348470, 11.476897, 11.692178, 12.332568, 132.805966], [9.239456, 10.026421, 10.087494, 11.368730, 48.217177]]
input_correlations: [[0.844581, -0.494706, 0.104408, 0.538778, 0.851086, -0.832592, 0.000000, 0.000000], [0.738662, -0.446297, 0.292294, 0.468690, 0.724757, -0.875843, 0.000000, 0.000000], [-0.528095, 0.782770, 0.043328, -0.103993, -0.540313, 0.976412, 0.000000, 0.000000], [-0.648760, 0.713933, -0.082063, -0.273815, -0.620332, 0.938352, 0.000000, 0.000000], [-0.550141, 0.713128, -0.038513, -0.147998, -0.574302, 0.984972, 0.000000, 0.000000], [0.821487, -0.619871, -0.012084, 0.469052, 0.817159, -0.847621, 0.000000, 0.000000]]
pre_activation_mean: [-0.658098, -0.691105, 1.744640, 1.340814, 1.475622, -0.535746]
pre_activation_std: [0.784442, 0.253065, 0.769195, 0.397588, 0.645896, 0.600533]
### 8
mean: [-3.146101]
std: [1.276390]
fourier: [[21.005018, 22.038303, 23.053238, 24.897694, 283.149096]]
input_correlations: [[0.602452, 0.429814, -0.961388, -0.986423, -0.961923, 0.654674, 0.000000, 0.000000]]
pre_activation_mean: [-3.146101]
pre_activation_std: [1.276390]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [-0.024038, -0.154271, 1.658703, 1.223586, 1.368681, -0.058536]
std: [0.336443, 0.029397, 0.818638, 0.433495, 0.694338, 0.239221]
fourier: [[4.681353, 4.796947, 5.235961, 5.268654, 5.336315], [0.407720, 0.414541, 0.423132, 0.464897, 13.884419], [14.849370, 15.071520, 15.411577, 15.875592, 149.283247], [7.687285, 7.775714, 7.859938, 8.030720, 110.122719], [12.257391, 12.293065, 12.669568, 13.322083, 123.181315], [3.388325, 3.487774, 3.590716, 3.982888, 5.268279]]
input_correlations: [[-0.163279, -0.279540, -0.317224, -0.613587, -0.853080, 0.000000, 0.000000, 0.000000], [-0.440560, 0.345050, 0.372222, 0.637102, 0.345968, 0.000000, 0.000000, 0.000000], [-0.855482, -0.162069, -0.006609, 0.214302, 0.291960, 0.000000, 0.000000, 0.000000], [-0.194623, -0.893425, -0.185246, -0.017091, 0.364585, 0.000000, 0.000000, 0.000000], [-0.366524, -0.092514, 0.610800, 0.387540, 0.463133, 0.000000, 0.000000, 0.000000], [0.755413, 0.754891, -0.024115, 0.097217, -0.093147, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.125378, 1.433421, 0.339585, -0.199287, 1.232404, 1.243377]
pre_activation_std: [1.111468, 1.464271, 1.789794, 1.669626, 1.806876, 1.643474]
### 2
mean: [0.320372, 0.091942, -0.939851, -0.832678, 1.013661, -0.194663]
std: [1.503171, 0.811293, 0.729789, 0.672505, 0.619339, 2.235674]
fourier: [[24.024414, 24.215036, 27.732680, 27.868227, 28.833497], [12.075174, 12.475322, 13.835401, 14.417800, 15.293519], [11.570419, 13.392149, 13.507423, 17.421045, 84.586576], [10.840166, 12.205056, 12.857005, 15.019694, 74.940992], [10.258809, 10.268515, 11.158038, 12.835453, 91.229517], [36.040525, 37.049054, 37.680934, 38.086681, 41.576248]]
input_correlations: [[-0.102954, 0.846321, 0.812177, -0.119638, 0.790908, -0.513029, 0.000000, 0.000000], [-0.216976, 0.819261, 0.606699, -0.392499, 0.748842, -0.133966, 0.000000, 0.000000], [0.178949, -0.411891, -0.192058, 0.475934, -0.017046, -0.780091, 0.000000, 0.000000], [0.125272, -0.157856, 0.005968, 0.032646, 0.281914, -0.803273, 0.000000, 0.000000], [-0.113958, 0.292064, 0.065012, 0.594167, 0.688337, -0.113510, 0.000000, 0.000000], [0.061567, -0.742338, -0.764784, -0.256214, -0.898954, 0.735374, 0.000000, 0.000000]]
pre_activation_mean: [0.320372, 0.091942, -0.939851, -0.832678, 1.013661, -0.194663]
pre_activation_std: [1.503171, 0.811293, 0.729789, 0.672505, 0.619339, 2.235674]
### 4
mean: [-0.288460, 0.958978, -0.695666, -0.891335, -0.178797, 1.386472]
std: [0.914899, 0.381545, 0.456116, 0.256782, 0.628683, 0.735909]
fourier: [[14.242818, 14.267795, 14.980579, 15.110723, 25.961424], [6.539649, 6.940999, 7.200172, 8.482311, 86.308048], [6.444852, 6.519524, 7.068981, 10.445250, 62.609955], [3.536902, 4.636267, 4.691837, 5.363371, 80.220126], [9.614385, 9.844851, 10.356417, 10.813541, 16.091743], [12.854731, 13.029051, 14.146224, 14.404981, 124.782503]]
input_correlations: [[0.920450, 0.858406, -0.335518, 0.234427, -0.160158, -0.325229, 0.000000, 0.000000], [-0.180978, -0.112545, 0.291820, 0.069223, 0.755197, 0.450438, 0.000000, 0.000000], [-0.669717, -0.510058, 0.367011, -0.123445, 0.474512, -0.088043, 0.000000, 0.000000], [-0.714889, -0.735861, 0.165328, -0.302095, 0.125376, -0.215796, 0.000000, 0.000000], [0.912379, 0.835462, -0.354889, 0.158723, 0.220992, -0.778611, 0.000000, 0.000000], [-0.502711, -0.433122, 0.364596, 0.080483, 0.066687, 0.951544, 0.000000, 0.000000]]
pre_activation_mean: [-0.288460, 0.958978, -0.695666, -0.891335, -0.178797, 1.386472]
pre_activation_std: [0.914899, 0.381545, 0.456116, 0.256782, 0.628683, 0.735909]
### 6
mean: [-0.658098, -0.691105, 1.744640, 1.340814, 1.475622, -0.535746]
std: [0.784442, 0.253065, 0.769195, 0.397588, 0.645896, 0.600533]
fourier: [[11.418724, 12.318012, 12.754730, 14.356181, 59.228782], [3.903273, 4.009817, 4.033172, 4.385266, 62.199410], [13.843101, 14.155024, 14.504204, 14.809426, 157.017638], [6.955674, 7.010768, 7.304738, 7.308432, 120.673263], [11.348470, 11.476897, 11.692178, 12.332568, 132.805966], [9.239456, 10.026421, 10.087494, 11.368730, 48.217177]]
input_correlations: [[0.844581, -0.494706, 0.104408, 0.538778, 0.851086, -0.832592, 0.000000, 0.000000], [0.738662, -0.446297, 0.292294, 0.468690, 0.724757, -0.875843, 0.000000, 0.000000], [-0.528095, 0.782770, 0.043328, -0.103993, -0.540313, 0.976412, 0.000000, 0.000000], [-0.648760, 0.713933, -0.082063, -0.273815, -0.620332, 0.938352, 0.000000, 0.000000], [-0.550141, 0.713128, -0.038513, -0.147998, -0.574302, 0.984972, 0.000000, 0.000000], [0.821487, -0.619871, -0.012084, 0.469052, 0.817159, -0.847621, 0.000000, 0.000000]]
pre_activation_mean: [-0.658098, -0.691105, 1.744640, 1.340814, 1.475622, -0.535746]
pre_activation_std: [0.784442, 0.253065, 0.769195, 0.397588, 0.645896, 0.600533]
### 8
mean: [-3.146101]
std: [1.276390]
fourier: [[21.005018, 22.038303, 23.053238, 24.897694, 283.149096]]
input_correlations: [[0.602452, 0.429814, -0.961388, -0.986423, -0.961923, 0.654674, 0.000000, 0.000000]]
pre_activation_mean: [-3.146101]
pre_activation_std: [1.276390]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.373065, -0.173136], [-0.101166, -0.333597, 0.181274, 0.307108, 0.09944, -0.146082], [0.434827, -0.012691, 0.809019, 0.045316, -0.045171, -0.250835], [-0.094853, 0.003841, -0.745703, -0.133016, 0.361775, 0.600173]], "network.4.bias": [-0.370451, 0.205015, -0.493903, -0.667473, -0.167156, 0.600694], "network.6.weight": [[0.707705, 0.053731, 0.25425, -0.064753, 0.238383, -0.590394], [0.371118, 0.163847, 0.164462, 0.423626, -0.374318, -0.296825], [-0.156006, 0.512711, -0.225439, -0.323869, -0.131968, 0.697362], [-0.287549, 0.328472, -0.736474, -0.363034, 0.119544, 0.286817], [-0.090518, 0.263044, -0.371004, -0.515811, -0.203784, 0.645225], [0.369123, -0.379145, 0.413855, 0.130462, 0.480847, -0.308295]], "network.6.bias": [-0.039107, -0.389195, 0.393537, 0.595552, 0.342212, 0.157963], "network.8.weight": [[0.646764, 0.300325, -0.402343, -0.542445, -0.780334, 0.457865]], "network.8.bias": [-0.658297]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6870701909065247, "train_acc": 0.555, "val_loss": 0.6929000616073608, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6878697276115417, "train_acc": 0.555, "val_loss": 0.687052309513092, "val_acc": 0.52}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6752554476261139, "train_acc": 0.585, "val_loss": 0.6615450978279114, "val_acc": 0.7}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6579265892505646, "train_acc": 0.665, "val_loss": 0.6372056007385254, "val_acc": 0.7}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6178113222122192, "train_acc": 0.69, "val_loss": 0.601417601108551, "val_acc": 0.74}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5688765347003937, "train_acc": 0.735, "val_loss": 0.5501078963279724, "val_acc": 0.8}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5016906559467316, "train_acc": 0.805, "val_loss": 0.4947129487991333, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.4698551744222641, "train_acc": 0.795, "val_loss": 0.4195132553577423, "val_acc": 0.82}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.3992616534233093, "train_acc": 0.83, "val_loss": 0.34888121485710144, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.3712051510810852, "train_acc": 0.85, "val_loss": 0.30139490962028503, "val_acc": 0.86}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.33978645503520966, "train_acc": 0.86, "val_loss": 0.27106568217277527, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.3032943457365036, "train_acc": 0.85, "val_loss": 0.30406397581100464, "val_acc": 0.84}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.3441379815340042, "train_acc": 0.86, "val_loss": 0.20274323225021362, "val_acc": 0.9}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.32035693526268005, "train_acc": 0.855, "val_loss": 0.2036634385585785, "val_acc": 0.9}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["no_repeats"], "degraded_stage": {"initial_val_loss": 0.6929000616073608, "final_val_loss": 0.6372056007385254, "initial_val_acc": 0.52, "final_val_acc": 0.7, "best_val_acc": 0.7}, "improved_stage": {"initial_val_loss": 0.601417601108551, "final_val_loss": 0.2036634385585785, "initial_val_acc": 0.74, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 10}, "improvement": 0.20000000000000007, "first_improvement_epoch": 3}} |
52 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.74, "improved_accuracy": 0.94, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2026, "learning_rate": 0.03338577609673197, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.951804, 1.140149, 2.166770, 1.577407, 2.217280, 0.000000, 0.984501, 0.277635]
std: [1.247203, 1.578272, 1.107326, 1.506007, 1.235331, 0.000000, 1.307222, 0.466983]
fourier: [[20.365410, 20.788830, 21.130247, 23.043581, 85.662326], [26.769089, 27.105952, 27.922467, 28.827638, 102.613372], [17.541494, 18.365098, 21.046443, 21.507944, 195.009296], [22.378945, 26.085006, 26.404457, 30.707111, 141.966649], [18.341063, 20.519993, 22.800984, 24.725661, 199.555176], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [22.446682, 22.595674, 22.824871, 23.750100, 88.605122], [7.849575, 7.925701, 8.031728, 8.141242, 24.987164]]
input_correlations: [[-0.585599, -0.677884, -0.291800, -0.639473, -0.517298, 0.000000, 0.000000, 0.000000], [-0.217745, 0.343136, -0.717937, 0.482549, -0.431722, 0.000000, 0.000000, 0.000000], [0.396520, -0.001203, 0.757985, 0.392614, 0.574858, 0.000000, 0.000000, 0.000000], [0.517313, 0.938493, 0.114802, 0.076589, -0.007653, 0.000000, 0.000000, 0.000000], [-0.207655, 0.109561, 0.553666, 0.398894, 0.724208, 0.000000, 0.000000, 0.000000], [-0.583621, -0.227142, -0.701239, -0.324141, -0.716644, 0.000000, 0.000000, 0.000000], [0.930028, 0.410052, 0.403225, -0.073369, -0.145522, 0.000000, 0.000000, 0.000000], [0.144288, 0.756512, 0.102751, 0.595528, 0.549681, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.813777, -0.259933, 1.304051, 0.617275, 1.530183, -2.710794, 1.168386, 1.465264]
pre_activation_std: [2.127439, 1.775321, 1.284148, 1.017475, 1.510383, 1.657650, 1.632300, 0.904490]
### 2
mean: [0.196416, 1.350329, 0.701383, -1.286795, 1.663719, 1.035080, 0.093244, 1.418706]
std: [0.851128, 1.228591, 1.061426, 0.594326, 1.009533, 1.356890, 0.345250, 0.819259]
fourier: [[13.132598, 13.616121, 14.997712, 17.398527, 17.677458], [20.999839, 21.418351, 21.453171, 23.062666, 121.529572], [15.661722, 15.928020, 18.845128, 20.149923, 63.124423], [10.009066, 10.438464, 10.461685, 10.605306, 115.811555], [15.996819, 16.059581, 19.961026, 22.422069, 149.734760], [21.025434, 21.307628, 23.208615, 23.825943, 93.157233], [5.139002, 5.142082, 5.198151, 6.334560, 8.391950], [12.378238, 12.635819, 14.369321, 17.071619, 127.683544]]
input_correlations: [[-0.199343, 0.862649, -0.397621, 0.467970, 0.030560, 0.000000, -0.311055, 0.620354], [-0.241559, -0.183387, 0.423780, 0.654891, -0.074577, 0.000000, 0.983106, 0.235635], [-0.073967, 0.134657, 0.405449, -0.436594, 0.809519, 0.000000, -0.663970, 0.310068], [0.361084, 0.036027, -0.674868, -0.457198, -0.856163, 0.000000, -0.212573, -0.819989], [-0.305317, -0.321381, 0.897358, 0.280442, 0.541462, 0.000000, 0.687092, 0.374808], [-0.082455, 0.077608, 0.410449, -0.412537, 0.829552, 0.000000, -0.667519, 0.347711], [-0.007175, 0.372003, 0.288129, -0.373212, -0.135099, 0.000000, 0.158846, -0.287210], [-0.417891, -0.124475, 0.522070, 0.741976, 0.408653, 0.000000, 0.716788, 0.701700]]
pre_activation_mean: [0.196416, 1.350329, 0.701383, -1.286795, 1.663719, 1.035080, 0.093244, 1.418706]
pre_activation_std: [0.851128, 1.228591, 1.061426, 0.594326, 1.009533, 1.356890, 0.345250, 0.819259]
### 4
mean: [2.021891, 0.667707, 1.071100, -1.714220, 0.614980, 1.686870, 1.168704, 0.350331]
std: [1.255262, 0.893512, 1.328732, 0.788041, 0.718684, 0.892720, 1.354657, 0.447878]
fourier: [[18.204697, 20.724764, 23.023325, 25.663513, 181.970138], [14.354756, 14.593431, 15.027086, 15.815191, 60.093588], [21.343397, 22.772880, 23.163346, 24.988931, 96.398976], [12.315740, 12.927209, 12.938064, 15.959608, 154.279813], [11.628155, 12.022638, 12.864340, 13.901802, 55.348196], [13.515089, 15.131273, 15.633710, 17.242099, 151.818294], [21.938104, 22.331039, 22.643609, 24.501913, 105.183355], [7.413593, 7.417543, 9.311808, 9.976016, 31.529802]]
input_correlations: [[0.323987, -0.189741, 0.965984, 0.000000, 0.385973, 0.947691, 0.200159, 0.272324], [-0.477820, 0.912127, -0.508307, 0.000000, 0.633696, -0.495332, -0.096822, 0.661219], [-0.468636, 0.924144, -0.529610, 0.000000, 0.642021, -0.529966, 0.035166, 0.609587], [-0.184816, -0.885146, 0.017767, 0.000000, -0.783042, 0.036615, -0.098105, -0.951538], [-0.485786, 0.916916, -0.517686, 0.000000, 0.655329, -0.519388, 0.058990, 0.593117], [0.458221, 0.024590, 0.829298, 0.000000, 0.458387, 0.823636, 0.039629, 0.541797], [-0.312297, 0.962080, -0.489509, 0.000000, 0.658805, -0.485202, -0.039948, 0.744909], [-0.163757, 0.124430, 0.681940, 0.000000, 0.663698, 0.635498, 0.609710, 0.187427]]
pre_activation_mean: [2.021891, 0.667707, 1.071100, -1.714220, 0.614980, 1.686870, 1.168704, 0.350331]
pre_activation_std: [1.255262, 0.893512, 1.328732, 0.788041, 0.718684, 0.892720, 1.354657, 0.447878]
### 6
mean: [0.899025, 0.807726, 2.166770, 1.268231, 2.217280, -1.019167, 0.750153, 0.194601]
std: [1.293699, 1.895961, 1.107326, 1.960253, 1.235331, 0.484509, 1.539014, 0.524648]
fourier: [[20.442928, 20.539952, 21.718929, 25.781360, 80.912226], [30.113890, 31.363047, 33.640590, 38.701365, 72.695319], [17.541494, 18.365098, 21.046443, 21.507944, 195.009296], [33.741982, 34.689503, 34.916080, 38.655710, 114.140830], [18.341063, 20.519993, 22.800984, 24.725661, 199.555176], [7.267443, 7.685199, 8.884333, 9.736137, 91.725027], [24.787376, 25.276698, 27.143524, 31.723967, 67.513781], [8.459822, 8.538454, 8.593060, 9.926034, 17.514100]]
input_correlations: [[-0.417919, 0.994039, 0.979240, 0.000000, 0.968306, -0.172088, 0.993495, -0.148538], [-0.650004, 0.948561, 0.944719, 0.000000, 0.936745, -0.442608, 0.934684, -0.287243], [0.975642, -0.174735, -0.179634, 0.000000, -0.175388, 0.942462, -0.136304, 0.741717], [0.823319, -0.827737, -0.840340, 0.000000, -0.838000, 0.676530, -0.800764, 0.378785], [0.997771, -0.368391, -0.377285, 0.000000, -0.374085, 0.941903, -0.328113, 0.671721], [-0.979008, 0.238828, 0.233378, 0.000000, 0.225313, -0.923088, 0.195421, -0.772226], [-0.653160, 0.946960, 0.944164, 0.000000, 0.936476, -0.445534, 0.932194, -0.290742], [-0.354150, 0.983418, 0.964343, 0.000000, 0.951979, -0.087847, 0.993918, -0.126832]]
pre_activation_mean: [0.899025, 0.807726, 2.166770, 1.268231, 2.217280, -1.019167, 0.750153, 0.194601]
pre_activation_std: [1.293699, 1.895961, 1.107326, 1.960253, 1.235331, 0.484509, 1.539014, 0.524648]
### 8
mean: [-2.251311]
std: [2.896794]
fourier: [[46.240564, 50.890729, 54.926526, 57.383242, 202.618009]]
input_correlations: [[0.754768, 0.820866, -0.758778, -0.958126, -0.873495, 0.000000, 0.834309, 0.677032]]
pre_activation_mean: [-2.251311]
pre_activation_std: [2.896794]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.436265,
-0.444071,
0.011039,
-0.48518,
-0.430504
],
[
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-0.661825,
0.351417,
-0.319389
],
[
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-0.283201,
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0.299537,
0.210742
],
[
0.117091,
0.538676,
-0.09336,
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0.013541
],
[
-0.38501,
0.064503,
0.431756,
0.175795,
0.542373
],
[
-0.31739,
0.097557,
-0.420916,
-0.237109,
-0.445633
],
[
0.736197,
0.060481,
0.145878,
-0.001584,
-0.307816
],
[
-0.067801,
0.369334,
-0.065678,
0.110909,
0.279398
]
],
"network.0.bias": [
0.086665,
0.138117,
-0.256249,
-0.085501,
-0.056032,
-0.556264,
0.220333,
0.431395
],
"network.2.weight": [
[
-0.071417,
0.540121,
-0.037243,
0.476928,
-0.004731,
0.263747,
-0.291051,
0.152783
],
[
-0.333786,
-0.164391,
0.359755,
0.282855,
-0.268846,
0.073781,
0.520881,
0.204173
],
[
0.018884,
0.338818,
0.155278,
-0.186599,
0.509459,
0.180118,
-0.316471,
-0.072949
],
[
-0.308109,
0.025596,
-0.016742,
-0.203356,
-0.326627,
-0.027454,
-0.052189,
-0.124576
],
[
-0.113323,
-0.07116,
0.317854,
-0.287227,
0.165723,
0.185197,
0.476516,
0.29176
],
[
-0.053995,
0.20658,
0.338363,
-0.136634,
0.460278,
0.123654,
-0.5516,
0.113375
],
[
0.365464,
0.364163,
0.074917,
-0.440874,
-0.023183,
-0.064576,
0.208288,
0.015642
],
[
-0.241761,
-0.171731,
-0.209134,
-0.045012,
0.266676,
0.121297,
0.459835,
0.487457
]
],
"network.2.bias": [
-0.205088,
0.209014,
0.146625,
-0.351126,
0.169781,
0.365787,
-0.126231,
0.094041
],
"network.4.weight": [
[
0.389294,
0.068576,
0.750342,
0.12519,
0.116467,
0.564566,
0.392629,
0.050922
],
[
-0.442406,
0.388195,
-0.310924,
-0.288586,
0.017968,
-0.023474,
-0.213331,
0.291207
],
[
-0.518601,
0.554909,
-0.213407,
0.123847,
0.310247,
-0.337928,
-0.082701,
0.112667
],
[
-0.3633,
-0.243367,
0.018682,
-0.150578,
-0.251052,
0.036086,
0.159916,
-0.358664
],
[
-0.232238,
0.200065,
-0.045387,
-0.028912,
0.347676,
-0.319524,
-0.134125,
-0.003651
],
[
0.476559,
-0.076689,
0.022684,
0.053187,
0.110634,
0.560557,
-0.068922,
0.46276
],
[
-0.329094,
0.506259,
-0.555759,
-0.344913,
0.142165,
-0.065725,
-0.176086,
0.563626
],
[
0.016836,
0.048223,
0.405709,
-0.1041,
0.410186,
-0.085244,
0.441629,
-0.379408
]
],
"network.4.bias": [
0.078166,
0.211962,
0.467478,
-0.410999,
0.322035,
0.063412,
0.179348,
-0.198197
],
"network.6.weight": [
[
-0.032079,
0.252231,
0.271323,
-0.455162,
0.383831,
0.127732,
0.374988,
-0.480968
],
[
-0.16797,
0.405163,
0.349993,
-0.121488,
0.249443,
-0.325149,
0.566702,
-0.514352
],
[
0.668361,
0.133946,
-0.11428,
-0.01249,
-0.067629,
0.205327,
0.183579,
0.45314
],
[
0.590995,
-0.277696,
-0.510017,
0.003279,
-0.461908,
0.421333,
-0.100612,
0.119939
],
[
0.495155,
-0.183414,
-0.007921,
0.146231,
-0.1053,
0.530618,
0.072235,
0.428428
],
[
-0.228126,
0.352602,
0.105652,
-0.081566,
-0.18236,
-0.126499,
-0.240213,
-0.291854
],
[
-0.261757,
0.300552,
0.519096,
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0.242182,
-0.077328,
0.211977,
-0.423292
],
[
-0.255406,
0.015844,
0.145843,
0.19052,
-0.047412,
0.3388,
0.217817,
0.055285
]
],
"network.6.bias": [
-0.262464,
0.353187,
0.148617,
0.528997,
0.278446,
-0.200708,
0.345085,
-0.292551
],
"network.8.weight": [
[
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0.403612,
-0.407191,
-0.783802,
-0.366807,
0.001178,
0.44339,
-0.242712
]
],
"network.8.bias": [
-0.247871
]
}
## Activation Signature
### 0
mean: [0.951804, 1.140149, 2.166770, 1.577407, 2.217280, 0.000000, 0.984501, 0.277635]
std: [1.247203, 1.578272, 1.107326, 1.506007, 1.235331, 0.000000, 1.307222, 0.466983]
fourier: [[20.365410, 20.788830, 21.130247, 23.043581, 85.662326], [26.769089, 27.105952, 27.922467, 28.827638, 102.613372], [17.541494, 18.365098, 21.046443, 21.507944, 195.009296], [22.378945, 26.085006, 26.404457, 30.707111, 141.966649], [18.341063, 20.519993, 22.800984, 24.725661, 199.555176], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [22.446682, 22.595674, 22.824871, 23.750100, 88.605122], [7.849575, 7.925701, 8.031728, 8.141242, 24.987164]]
input_correlations: [[-0.585599, -0.677884, -0.291800, -0.639473, -0.517298, 0.000000, 0.000000, 0.000000], [-0.217745, 0.343136, -0.717937, 0.482549, -0.431722, 0.000000, 0.000000, 0.000000], [0.396520, -0.001203, 0.757985, 0.392614, 0.574858, 0.000000, 0.000000, 0.000000], [0.517313, 0.938493, 0.114802, 0.076589, -0.007653, 0.000000, 0.000000, 0.000000], [-0.207655, 0.109561, 0.553666, 0.398894, 0.724208, 0.000000, 0.000000, 0.000000], [-0.583621, -0.227142, -0.701239, -0.324141, -0.716644, 0.000000, 0.000000, 0.000000], [0.930028, 0.410052, 0.403225, -0.073369, -0.145522, 0.000000, 0.000000, 0.000000], [0.144288, 0.756512, 0.102751, 0.595528, 0.549681, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.813777, -0.259933, 1.304051, 0.617275, 1.530183, -2.710794, 1.168386, 1.465264]
pre_activation_std: [2.127439, 1.775321, 1.284148, 1.017475, 1.510383, 1.657650, 1.632300, 0.904490]
### 2
mean: [0.196416, 1.350329, 0.701383, -1.286795, 1.663719, 1.035080, 0.093244, 1.418706]
std: [0.851128, 1.228591, 1.061426, 0.594326, 1.009533, 1.356890, 0.345250, 0.819259]
fourier: [[13.132598, 13.616121, 14.997712, 17.398527, 17.677458], [20.999839, 21.418351, 21.453171, 23.062666, 121.529572], [15.661722, 15.928020, 18.845128, 20.149923, 63.124423], [10.009066, 10.438464, 10.461685, 10.605306, 115.811555], [15.996819, 16.059581, 19.961026, 22.422069, 149.734760], [21.025434, 21.307628, 23.208615, 23.825943, 93.157233], [5.139002, 5.142082, 5.198151, 6.334560, 8.391950], [12.378238, 12.635819, 14.369321, 17.071619, 127.683544]]
input_correlations: [[-0.199343, 0.862649, -0.397621, 0.467970, 0.030560, 0.000000, -0.311055, 0.620354], [-0.241559, -0.183387, 0.423780, 0.654891, -0.074577, 0.000000, 0.983106, 0.235635], [-0.073967, 0.134657, 0.405449, -0.436594, 0.809519, 0.000000, -0.663970, 0.310068], [0.361084, 0.036027, -0.674868, -0.457198, -0.856163, 0.000000, -0.212573, -0.819989], [-0.305317, -0.321381, 0.897358, 0.280442, 0.541462, 0.000000, 0.687092, 0.374808], [-0.082455, 0.077608, 0.410449, -0.412537, 0.829552, 0.000000, -0.667519, 0.347711], [-0.007175, 0.372003, 0.288129, -0.373212, -0.135099, 0.000000, 0.158846, -0.287210], [-0.417891, -0.124475, 0.522070, 0.741976, 0.408653, 0.000000, 0.716788, 0.701700]]
pre_activation_mean: [0.196416, 1.350329, 0.701383, -1.286795, 1.663719, 1.035080, 0.093244, 1.418706]
pre_activation_std: [0.851128, 1.228591, 1.061426, 0.594326, 1.009533, 1.356890, 0.345250, 0.819259]
### 4
mean: [2.021891, 0.667707, 1.071100, -1.714220, 0.614980, 1.686870, 1.168704, 0.350331]
std: [1.255262, 0.893512, 1.328732, 0.788041, 0.718684, 0.892720, 1.354657, 0.447878]
fourier: [[18.204697, 20.724764, 23.023325, 25.663513, 181.970138], [14.354756, 14.593431, 15.027086, 15.815191, 60.093588], [21.343397, 22.772880, 23.163346, 24.988931, 96.398976], [12.315740, 12.927209, 12.938064, 15.959608, 154.279813], [11.628155, 12.022638, 12.864340, 13.901802, 55.348196], [13.515089, 15.131273, 15.633710, 17.242099, 151.818294], [21.938104, 22.331039, 22.643609, 24.501913, 105.183355], [7.413593, 7.417543, 9.311808, 9.976016, 31.529802]]
input_correlations: [[0.323987, -0.189741, 0.965984, 0.000000, 0.385973, 0.947691, 0.200159, 0.272324], [-0.477820, 0.912127, -0.508307, 0.000000, 0.633696, -0.495332, -0.096822, 0.661219], [-0.468636, 0.924144, -0.529610, 0.000000, 0.642021, -0.529966, 0.035166, 0.609587], [-0.184816, -0.885146, 0.017767, 0.000000, -0.783042, 0.036615, -0.098105, -0.951538], [-0.485786, 0.916916, -0.517686, 0.000000, 0.655329, -0.519388, 0.058990, 0.593117], [0.458221, 0.024590, 0.829298, 0.000000, 0.458387, 0.823636, 0.039629, 0.541797], [-0.312297, 0.962080, -0.489509, 0.000000, 0.658805, -0.485202, -0.039948, 0.744909], [-0.163757, 0.124430, 0.681940, 0.000000, 0.663698, 0.635498, 0.609710, 0.187427]]
pre_activation_mean: [2.021891, 0.667707, 1.071100, -1.714220, 0.614980, 1.686870, 1.168704, 0.350331]
pre_activation_std: [1.255262, 0.893512, 1.328732, 0.788041, 0.718684, 0.892720, 1.354657, 0.447878]
### 6
mean: [0.899025, 0.807726, 2.166770, 1.268231, 2.217280, -1.019167, 0.750153, 0.194601]
std: [1.293699, 1.895961, 1.107326, 1.960253, 1.235331, 0.484509, 1.539014, 0.524648]
fourier: [[20.442928, 20.539952, 21.718929, 25.781360, 80.912226], [30.113890, 31.363047, 33.640590, 38.701365, 72.695319], [17.541494, 18.365098, 21.046443, 21.507944, 195.009296], [33.741982, 34.689503, 34.916080, 38.655710, 114.140830], [18.341063, 20.519993, 22.800984, 24.725661, 199.555176], [7.267443, 7.685199, 8.884333, 9.736137, 91.725027], [24.787376, 25.276698, 27.143524, 31.723967, 67.513781], [8.459822, 8.538454, 8.593060, 9.926034, 17.514100]]
input_correlations: [[-0.417919, 0.994039, 0.979240, 0.000000, 0.968306, -0.172088, 0.993495, -0.148538], [-0.650004, 0.948561, 0.944719, 0.000000, 0.936745, -0.442608, 0.934684, -0.287243], [0.975642, -0.174735, -0.179634, 0.000000, -0.175388, 0.942462, -0.136304, 0.741717], [0.823319, -0.827737, -0.840340, 0.000000, -0.838000, 0.676530, -0.800764, 0.378785], [0.997771, -0.368391, -0.377285, 0.000000, -0.374085, 0.941903, -0.328113, 0.671721], [-0.979008, 0.238828, 0.233378, 0.000000, 0.225313, -0.923088, 0.195421, -0.772226], [-0.653160, 0.946960, 0.944164, 0.000000, 0.936476, -0.445534, 0.932194, -0.290742], [-0.354150, 0.983418, 0.964343, 0.000000, 0.951979, -0.087847, 0.993918, -0.126832]]
pre_activation_mean: [0.899025, 0.807726, 2.166770, 1.268231, 2.217280, -1.019167, 0.750153, 0.194601]
pre_activation_std: [1.293699, 1.895961, 1.107326, 1.960253, 1.235331, 0.484509, 1.539014, 0.524648]
### 8
mean: [-2.251311]
std: [2.896794]
fourier: [[46.240564, 50.890729, 54.926526, 57.383242, 202.618009]]
input_correlations: [[0.754768, 0.820866, -0.758778, -0.958126, -0.873495, 0.000000, 0.834309, 0.677032]]
pre_activation_mean: [-2.251311]
pre_activation_std: [2.896794]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.017968, -0.023474, -0.213331, 0.291207], [-0.518601, 0.554909, -0.213407, 0.123847, 0.310247, -0.337928, -0.082701, 0.112667], [-0.3633, -0.243367, 0.018682, -0.150578, -0.251052, 0.036086, 0.159916, -0.358664], [-0.232238, 0.200065, -0.045387, -0.028912, 0.347676, -0.319524, -0.134125, -0.003651], [0.476559, -0.076689, 0.022684, 0.053187, 0.110634, 0.560557, -0.068922, 0.46276], [-0.329094, 0.506259, -0.555759, -0.344913, 0.142165, -0.065725, -0.176086, 0.563626], [0.016836, 0.048223, 0.405709, -0.1041, 0.410186, -0.085244, 0.441629, -0.379408]], "network.4.bias": [0.078166, 0.211962, 0.467478, -0.410999, 0.322035, 0.063412, 0.179348, -0.198197], "network.6.weight": [[-0.032079, 0.252231, 0.271323, -0.455162, 0.383831, 0.127732, 0.374988, -0.480968], [-0.16797, 0.405163, 0.349993, -0.121488, 0.249443, -0.325149, 0.566702, -0.514352], [0.668361, 0.133946, -0.11428, -0.01249, -0.067629, 0.205327, 0.183579, 0.45314], [0.590995, -0.277696, -0.510017, 0.003279, -0.461908, 0.421333, -0.100612, 0.119939], [0.495155, -0.183414, -0.007921, 0.146231, -0.1053, 0.530618, 0.072235, 0.428428], [-0.228126, 0.352602, 0.105652, -0.081566, -0.18236, -0.126499, -0.240213, -0.291854], [-0.261757, 0.300552, 0.519096, -0.572542, 0.242182, -0.077328, 0.211977, -0.423292], [-0.255406, 0.015844, 0.145843, 0.19052, -0.047412, 0.3388, 0.217817, 0.055285]], "network.6.bias": [-0.262464, 0.353187, 0.148617, 0.528997, 0.278446, -0.200708, 0.345085, -0.292551], "network.8.weight": [[0.104255, 0.403612, -0.407191, -0.783802, -0.366807, 0.001178, 0.44339, -0.242712]], "network.8.bias": [-0.247871]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6975021660327911, "train_acc": 0.465, "val_loss": 0.6671959161758423, "val_acc": 0.72}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6571891009807587, "train_acc": 0.655, "val_loss": 0.6217471957206726, "val_acc": 0.74}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6050741672515869, "train_acc": 0.735, "val_loss": 0.5013894438743591, "val_acc": 0.88}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4716840237379074, "train_acc": 0.84, "val_loss": 0.39876067638397217, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.3423783630132675, "train_acc": 0.915, "val_loss": 0.30779916048049927, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.28544341027736664, "train_acc": 0.93, "val_loss": 0.30421268939971924, "val_acc": 0.9}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.24655576795339584, "train_acc": 0.93, "val_loss": 0.2569919526576996, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.23055431246757507, "train_acc": 0.93, "val_loss": 0.22691898047924042, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.216035857796669, "train_acc": 0.935, "val_loss": 0.20723119378089905, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.204278402030468, "train_acc": 0.945, "val_loss": 0.20668603479862213, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.1954016014933586, "train_acc": 0.935, "val_loss": 0.2013544887304306, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.18981891870498657, "train_acc": 0.95, "val_loss": 0.2043440043926239, "val_acc": 0.92}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6671959161758423, "final_val_loss": 0.6217471957206726, "initial_val_acc": 0.72, "final_val_acc": 0.74, "best_val_acc": 0.74}, "improved_stage": {"initial_val_loss": 0.5013894438743591, "final_val_loss": 0.2043440043926239, "initial_val_acc": 0.88, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 8}, "improvement": 0.19999999999999996, "first_improvement_epoch": 1}} |
53 | {"target_pattern": "has_majority", "degraded_accuracy": 0.58, "improved_accuracy": 0.88, "improvement": 0.30000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8445, "learning_rate": 0.09004911743914298, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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],
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"network.10.weight": [
[
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0.321383,
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0.426144,
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],
"network.10.bias": [
0.250294
]
}
## Activation Signature
### 0
mean: [-0.038540, -0.122955, 0.336952, 0.352698, 1.073986, -0.091084, 0.131994, 0.122723]
std: [0.084979, 0.048009, 0.774454, 0.905019, 1.181455, 0.055769, 0.652947, 0.179955]
fourier: [[1.399490, 1.480346, 1.483732, 1.534223, 3.468644], [0.711468, 0.731628, 0.778724, 0.913420, 11.065993], [10.889761, 11.695690, 13.550235, 16.395762, 30.325669], [12.392669, 13.789875, 15.893684, 18.456161, 31.742843], [18.588944, 18.716000, 19.014649, 21.364565, 96.658781], [0.882816, 0.883510, 0.907928, 1.089476, 8.197541], [8.844181, 9.537110, 10.986553, 11.879433, 11.942962], [2.836105, 2.919371, 2.978754, 3.533358, 11.045095]]
input_correlations: [[-0.093893, -0.573136, -0.812880, -0.081076, -0.346831, 0.000000, 0.000000, 0.000000], [0.152481, -0.365996, -0.543467, 0.109289, -0.564727, 0.000000, 0.000000, 0.000000], [0.125971, 0.911087, 0.246951, 0.529908, 0.288387, 0.000000, 0.000000, 0.000000], [0.020171, 0.813529, 0.524357, 0.402716, -0.192400, 0.000000, 0.000000, 0.000000], [0.405156, 0.299002, 0.262115, -0.774445, 0.039034, 0.000000, 0.000000, 0.000000], [0.204300, 0.716559, 0.570151, 0.384095, 0.584224, 0.000000, 0.000000, 0.000000], [0.200194, 0.704957, 0.189100, 0.887182, 0.235426, 0.000000, 0.000000, 0.000000], [0.912200, 0.260610, 0.519278, 0.154206, 0.053994, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.440307, -1.056546, 2.834190, 2.284714, 0.037148, 4.006238, 2.695699, 1.256575]
pre_activation_std: [2.066113, 1.917111, 1.817373, 1.708805, 2.148849, 2.643047, 2.279300, 1.447916]
### 2
mean: [-6.301832, -5.385306, -0.801293, -4.568732, -3.162452, -6.431890, 2.158449, -5.956580]
std: [4.558334, 3.591351, 1.361834, 3.576399, 1.809768, 3.801793, 2.075369, 4.550156]
fourier: [[70.464962, 77.313302, 78.010280, 79.838896, 567.164957], [54.767437, 55.601879, 65.480339, 68.562257, 484.677531], [19.995480, 22.128605, 23.789339, 23.894162, 72.116397], [56.163102, 56.764484, 58.849881, 62.132880, 411.185901], [27.023112, 28.367535, 34.594411, 36.031791, 284.620693], [61.742161, 62.673785, 70.613449, 76.131528, 578.870164], [34.585853, 35.225516, 36.027101, 39.585467, 194.260370], [71.726041, 72.505952, 73.620187, 79.086444, 536.092090]]
input_correlations: [[0.057100, 0.309013, -0.948550, -0.883313, -0.006932, -0.865496, -0.864959, -0.120960], [0.036818, 0.267818, -0.967987, -0.820514, -0.112880, -0.908913, -0.897686, -0.250127], [-0.069514, -0.245255, -0.489786, -0.342029, 0.526441, -0.176274, -0.826593, -0.112481], [0.101881, 0.364972, -0.962163, -0.751956, 0.011057, -0.903899, -0.866148, -0.041303], [-0.004962, 0.337136, -0.889954, -0.840209, -0.553026, -0.832012, -0.592043, -0.143567], [-0.009595, 0.228677, -0.932633, -0.843676, -0.323139, -0.895642, -0.829390, -0.397408], [-0.024579, -0.064363, 0.723753, 0.657954, -0.201003, 0.719408, 0.918238, 0.478189], [0.112015, 0.445511, -0.962596, -0.818888, -0.116696, -0.935440, -0.787808, -0.033255]]
pre_activation_mean: [-6.301832, -5.385306, -0.801293, -4.568732, -3.162452, -6.431890, 2.158449, -5.956580]
pre_activation_std: [4.558334, 3.591351, 1.361834, 3.576399, 1.809768, 3.801793, 2.075369, 4.550156]
### 4
mean: [-0.600345, -0.103529, -0.875189, 0.078572, 0.853382, 1.011166, -1.830832, 1.159858]
std: [0.997713, 0.282764, 0.777475, 0.398360, 1.195652, 1.227857, 1.093369, 1.367427]
fourier: [[14.627632, 16.769077, 18.036540, 21.859992, 54.031078], [3.879519, 3.912789, 4.300324, 4.591033, 9.317578], [11.159517, 13.397285, 13.999714, 17.134372, 78.766960], [5.729772, 5.985965, 7.071478, 7.212544, 7.362077], [19.454729, 19.512221, 20.427325, 24.758886, 76.804397], [19.758662, 20.053919, 20.973819, 25.488843, 91.004928], [17.791147, 18.773712, 19.445487, 19.932119, 164.774882], [22.638087, 22.943558, 23.451319, 27.191884, 104.387262]]
input_correlations: [[0.138933, -0.484509, 0.248350, 0.386739, -0.388580, -0.329331, -0.928041, 0.419736], [-0.824195, 0.059413, 0.081069, -0.984821, -0.143673, -0.169644, -0.080633, -0.982334], [0.116712, -0.437435, 0.336278, 0.350753, -0.341490, -0.298524, -0.927140, 0.384645], [0.121701, -0.071882, 0.852331, 0.226058, 0.019548, 0.015830, -0.594867, 0.275092], [0.129454, 0.472559, -0.439795, -0.091346, 0.417015, 0.387073, 0.960200, -0.133923], [0.123264, 0.460207, -0.450234, -0.096200, 0.402636, 0.375474, 0.956767, -0.138560], [-0.300694, -0.562441, 0.173284, -0.073690, -0.552556, -0.514858, -0.993430, -0.042081], [0.195612, 0.522368, -0.294331, -0.030943, 0.486750, 0.448836, 0.993798, -0.068004]]
pre_activation_mean: [-0.600345, -0.103529, -0.875189, 0.078572, 0.853382, 1.011166, -1.830832, 1.159858]
pre_activation_std: [0.997713, 0.282764, 0.777475, 0.398360, 1.195652, 1.227857, 1.093369, 1.367427]
### 6
mean: [0.975584, -1.429283, 0.922786, -0.931589, -0.856964, -1.379991, 0.636863, 0.412667]
std: [1.547999, 1.001934, 1.145903, 1.073630, 1.611235, 1.844440, 1.033302, 0.542203]
fourier: [[26.095370, 26.144860, 26.180654, 30.971906, 87.802529], [16.753425, 16.803210, 18.135267, 18.263308, 128.635440], [19.164066, 19.538360, 19.693151, 22.820835, 83.050734], [16.809799, 18.416939, 18.491283, 23.199134, 83.842991], [25.438161, 27.142761, 28.017212, 34.757418, 77.126741], [30.916020, 31.228321, 31.454211, 36.838813, 124.199153], [17.008789, 17.609632, 18.028281, 20.299949, 57.317713], [8.249906, 8.347497, 8.556875, 9.253879, 37.140000]]
input_correlations: [[-0.354972, -0.688632, -0.158556, -0.625194, 0.994319, 0.996189, 0.870545, 0.989344], [0.245443, 0.773588, 0.038512, 0.426803, -0.982285, -0.977834, -0.873505, -0.993252], [-0.348971, -0.711210, -0.149610, -0.584748, 0.995026, 0.995763, 0.877948, 0.994238], [0.479381, 0.639719, 0.294909, 0.676505, -0.967644, -0.972474, -0.857831, -0.962374], [0.511525, 0.626514, 0.326373, 0.662505, -0.961119, -0.966280, -0.851193, -0.955663], [0.353197, 0.696081, 0.155635, 0.616399, -0.994785, -0.996499, -0.873982, -0.990493], [-0.331898, -0.719804, -0.128929, -0.576718, 0.996361, 0.997118, 0.885728, 0.995064], [0.483711, -0.697561, 0.657577, -0.155519, 0.707060, 0.694765, 0.630769, 0.711966]]
pre_activation_mean: [0.975584, -1.429283, 0.922786, -0.931589, -0.856964, -1.379991, 0.636863, 0.412667]
pre_activation_std: [1.547999, 1.001934, 1.145903, 1.073630, 1.611235, 1.844440, 1.033302, 0.542203]
### 8
mean: [-0.142721, -0.556627, -0.229548, -0.223048, 1.158975, -0.402185, -0.436374, 0.160109]
std: [0.259670, 0.631294, 1.427391, 1.493834, 1.149823, 0.651021, 1.161838, 0.300372]
fourier: [[4.316706, 4.359343, 4.531177, 4.588574, 12.844904], [8.748990, 9.137707, 9.704246, 12.170093, 50.096441], [20.659290, 20.958897, 23.558435, 24.684327, 31.883129], [20.748647, 21.413914, 23.947308, 25.604955, 33.724960], [18.110558, 18.340033, 18.724592, 20.982036, 104.307753], [9.150559, 9.745397, 10.612882, 12.500635, 36.196676], [16.693506, 18.628674, 19.806854, 26.148425, 39.273662], [4.442808, 4.847291, 5.081301, 6.496608, 14.409852]]
input_correlations: [[-0.971303, -0.923502, -0.970773, 0.240137, 0.416003, 0.349936, -0.973976, -0.548609], [-0.153023, -0.141017, -0.130054, -0.948139, -0.870541, -0.857361, -0.155340, -0.806884], [-0.900863, -0.844158, -0.910712, 0.552677, 0.717989, 0.684286, -0.898588, -0.305955], [-0.854218, -0.805169, -0.865838, 0.629757, 0.781221, 0.744190, -0.851870, -0.209702], [0.988984, 0.918310, 0.985705, -0.000168, -0.208618, -0.185309, 0.989038, 0.779120], [0.388935, 0.379982, 0.408972, -0.951582, -0.988493, -0.946588, 0.385985, -0.402615], [-0.846871, -0.799117, -0.858453, 0.641637, 0.787400, 0.747111, -0.845057, -0.192937], [0.871815, 0.814745, 0.881052, -0.595589, -0.746323, -0.698284, 0.870502, 0.234778]]
pre_activation_mean: [-0.142721, -0.556627, -0.229548, -0.223048, 1.158975, -0.402185, -0.436374, 0.160109]
pre_activation_std: [0.259670, 0.631294, 1.427391, 1.493834, 1.149823, 0.651021, 1.161838, 0.300372]
### 10
mean: [0.180414]
std: [1.050642]
fourier: [[15.307089, 16.002608, 16.237235, 16.762151, 23.994031]]
input_correlations: [[0.852949, 0.275497, 0.944589, 0.928569, -0.606150, -0.442207, 0.871694, -0.783074]]
pre_activation_mean: [0.180414]
pre_activation_std: [1.050642]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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-0.675159,
-0.794823,
0.185606,
-0.322811
],
[
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-0.470163,
0.410128,
-0.672761
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[
-0.217741,
0.909338,
0.050491,
0.147228,
0.291881
],
[
-0.283857,
0.696422,
0.457689,
0.142039,
-0.248707
],
[
0.127615,
0.655146,
0.086437,
-1.004398,
0.171672
],
[
-0.311193,
0.991909,
0.512029,
0.075931,
0.771496
],
[
0.064105,
0.538269,
0.051616,
0.796055,
0.131886
],
[
0.671799,
-0.173759,
0.236339,
0.209952,
-0.180366
]
],
"network.0.bias": [
-0.06067,
0.292572,
0.666961,
0.415007,
0.446106,
0.402109,
-0.342499,
0.015719
],
"network.2.weight": [
[
0.186163,
-0.030211,
-0.950268,
-1.005271,
0.884787,
-0.464609,
-0.126429,
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],
[
0.180248,
0.109728,
-0.694127,
-0.308166,
0.139711,
-0.384332,
-0.434674,
-0.175899
],
[
-0.530398,
0.185283,
-0.350348,
0.097149,
0.230126,
0.445765,
-0.63692,
-0.032989
],
[
0.489527,
0.163518,
-0.802899,
-0.048527,
0.48278,
-0.550402,
-0.350901,
0.244938
],
[
-0.380455,
0.022269,
-0.294489,
-0.367361,
-0.824267,
-0.063346,
-0.142462,
0.219924
],
[
-0.359766,
0.27249,
-0.424561,
-0.53245,
-0.664013,
-0.286191,
-0.58106,
-0.388611
],
[
-0.32754,
-0.15165,
-0.334578,
0.25264,
-0.646851,
0.35451,
0.510663,
0.495557
],
[
0.208725,
0.420275,
-0.752791,
-0.506774,
0.287523,
-0.812855,
-0.197982,
0.367884
]
],
"network.2.bias": [
0.098574,
-0.003885,
-0.312365,
0.15992,
-0.485284,
-0.417572,
-0.287911,
0.231273
],
"network.4.weight": [
[
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0.283091,
0.226799,
0.739901,
-0.381415,
-0.170036,
-0.438365,
0.733306
],
[
0.250134,
0.151292,
-0.020278,
-0.672045,
-0.074944,
0.409759,
-0.028353,
-0.658988
],
[
0.143655,
0.813566,
0.307888,
0.784127,
0.12255,
-0.588401,
-0.343855,
0.389504
],
[
-0.174865,
0.654912,
0.658159,
0.106992,
-0.000595,
-0.225604,
-0.089634,
0.407356
],
[
0.252618,
0.366507,
-0.735841,
0.053867,
0.189876,
0.342427,
0.515766,
-0.526237
],
[
0.452447,
0.12216,
-0.775516,
-0.109049,
0.010293,
0.392919,
0.53064,
-0.498551
],
[
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-0.033667,
0.097735,
-0.164366,
0.399353,
-0.530507,
-0.319694
],
[
0.378157,
0.249699,
-0.339975,
0.150328,
0.068189,
0.004038,
0.64593,
-0.271756
]
],
"network.4.bias": [
0.310167,
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-0.158054,
0.184971,
-0.128201,
-0.00632,
-0.690424,
-0.176846
],
"network.6.weight": [
[
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0.22091,
0.007439,
-0.303695,
0.395609,
0.488845,
0.020432,
0.354096
],
[
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-0.038832,
0.45462,
-0.606389,
-0.257294,
-0.054552,
0.524149,
-0.598358
],
[
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-0.027929,
0.233559,
0.30599,
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0.385906
],
[
0.290132,
0.259044,
0.405863,
0.572032,
-0.164854,
-0.015064,
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-0.506681
],
[
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0.194703,
0.393368,
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[
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0.177406,
0.228287,
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-0.311678
],
[
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0.172961,
0.066244,
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0.28598,
0.596292,
0.070948
],
[
0.446367,
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0.869159,
0.071899,
-0.04731,
0.065214,
0.496381,
0.307624
]
],
"network.6.bias": [
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-0.259308,
0.204245,
0.092381,
-0.13095,
0.122647
],
"network.8.weight": [
[
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0.073752,
-0.205303,
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-0.338669,
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],
[
-0.285575,
-0.211669,
-0.08579,
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-0.51633,
-0.451392,
0.464624,
-0.480948
],
[
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0.01071,
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0.26289,
0.661557,
0.34362,
0.077755,
0.346078
],
[
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-0.350551,
0.123891,
0.88521,
0.338395,
-0.252208,
0.592243
],
[
0.312394,
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0.278447,
0.003445,
0.173474,
-0.148404,
0.327734,
0.320839
],
[
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0.047299,
-0.046905,
0.07984,
-0.695181,
0.024986,
0.154965,
-0.755493
],
[
-0.397966,
-0.399084,
-0.046382,
0.446719,
0.447075,
0.286421,
-0.461467,
0.596762
],
[
0.346667,
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0.128972,
-0.28258
]
],
"network.8.bias": [
0.093398,
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0.211315,
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0.001242,
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],
"network.10.weight": [
[
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0.321383,
-0.308495,
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0.426144,
-0.2872
]
],
"network.10.bias": [
0.250294
]
}
## Activation Signature
### 0
mean: [-0.038540, -0.122955, 0.336952, 0.352698, 1.073986, -0.091084, 0.131994, 0.122723]
std: [0.084979, 0.048009, 0.774454, 0.905019, 1.181455, 0.055769, 0.652947, 0.179955]
fourier: [[1.399490, 1.480346, 1.483732, 1.534223, 3.468644], [0.711468, 0.731628, 0.778724, 0.913420, 11.065993], [10.889761, 11.695690, 13.550235, 16.395762, 30.325669], [12.392669, 13.789875, 15.893684, 18.456161, 31.742843], [18.588944, 18.716000, 19.014649, 21.364565, 96.658781], [0.882816, 0.883510, 0.907928, 1.089476, 8.197541], [8.844181, 9.537110, 10.986553, 11.879433, 11.942962], [2.836105, 2.919371, 2.978754, 3.533358, 11.045095]]
input_correlations: [[-0.093893, -0.573136, -0.812880, -0.081076, -0.346831, 0.000000, 0.000000, 0.000000], [0.152481, -0.365996, -0.543467, 0.109289, -0.564727, 0.000000, 0.000000, 0.000000], [0.125971, 0.911087, 0.246951, 0.529908, 0.288387, 0.000000, 0.000000, 0.000000], [0.020171, 0.813529, 0.524357, 0.402716, -0.192400, 0.000000, 0.000000, 0.000000], [0.405156, 0.299002, 0.262115, -0.774445, 0.039034, 0.000000, 0.000000, 0.000000], [0.204300, 0.716559, 0.570151, 0.384095, 0.584224, 0.000000, 0.000000, 0.000000], [0.200194, 0.704957, 0.189100, 0.887182, 0.235426, 0.000000, 0.000000, 0.000000], [0.912200, 0.260610, 0.519278, 0.154206, 0.053994, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.440307, -1.056546, 2.834190, 2.284714, 0.037148, 4.006238, 2.695699, 1.256575]
pre_activation_std: [2.066113, 1.917111, 1.817373, 1.708805, 2.148849, 2.643047, 2.279300, 1.447916]
### 2
mean: [-6.301832, -5.385306, -0.801293, -4.568732, -3.162452, -6.431890, 2.158449, -5.956580]
std: [4.558334, 3.591351, 1.361834, 3.576399, 1.809768, 3.801793, 2.075369, 4.550156]
fourier: [[70.464962, 77.313302, 78.010280, 79.838896, 567.164957], [54.767437, 55.601879, 65.480339, 68.562257, 484.677531], [19.995480, 22.128605, 23.789339, 23.894162, 72.116397], [56.163102, 56.764484, 58.849881, 62.132880, 411.185901], [27.023112, 28.367535, 34.594411, 36.031791, 284.620693], [61.742161, 62.673785, 70.613449, 76.131528, 578.870164], [34.585853, 35.225516, 36.027101, 39.585467, 194.260370], [71.726041, 72.505952, 73.620187, 79.086444, 536.092090]]
input_correlations: [[0.057100, 0.309013, -0.948550, -0.883313, -0.006932, -0.865496, -0.864959, -0.120960], [0.036818, 0.267818, -0.967987, -0.820514, -0.112880, -0.908913, -0.897686, -0.250127], [-0.069514, -0.245255, -0.489786, -0.342029, 0.526441, -0.176274, -0.826593, -0.112481], [0.101881, 0.364972, -0.962163, -0.751956, 0.011057, -0.903899, -0.866148, -0.041303], [-0.004962, 0.337136, -0.889954, -0.840209, -0.553026, -0.832012, -0.592043, -0.143567], [-0.009595, 0.228677, -0.932633, -0.843676, -0.323139, -0.895642, -0.829390, -0.397408], [-0.024579, -0.064363, 0.723753, 0.657954, -0.201003, 0.719408, 0.918238, 0.478189], [0.112015, 0.445511, -0.962596, -0.818888, -0.116696, -0.935440, -0.787808, -0.033255]]
pre_activation_mean: [-6.301832, -5.385306, -0.801293, -4.568732, -3.162452, -6.431890, 2.158449, -5.956580]
pre_activation_std: [4.558334, 3.591351, 1.361834, 3.576399, 1.809768, 3.801793, 2.075369, 4.550156]
### 4
mean: [-0.600345, -0.103529, -0.875189, 0.078572, 0.853382, 1.011166, -1.830832, 1.159858]
std: [0.997713, 0.282764, 0.777475, 0.398360, 1.195652, 1.227857, 1.093369, 1.367427]
fourier: [[14.627632, 16.769077, 18.036540, 21.859992, 54.031078], [3.879519, 3.912789, 4.300324, 4.591033, 9.317578], [11.159517, 13.397285, 13.999714, 17.134372, 78.766960], [5.729772, 5.985965, 7.071478, 7.212544, 7.362077], [19.454729, 19.512221, 20.427325, 24.758886, 76.804397], [19.758662, 20.053919, 20.973819, 25.488843, 91.004928], [17.791147, 18.773712, 19.445487, 19.932119, 164.774882], [22.638087, 22.943558, 23.451319, 27.191884, 104.387262]]
input_correlations: [[0.138933, -0.484509, 0.248350, 0.386739, -0.388580, -0.329331, -0.928041, 0.419736], [-0.824195, 0.059413, 0.081069, -0.984821, -0.143673, -0.169644, -0.080633, -0.982334], [0.116712, -0.437435, 0.336278, 0.350753, -0.341490, -0.298524, -0.927140, 0.384645], [0.121701, -0.071882, 0.852331, 0.226058, 0.019548, 0.015830, -0.594867, 0.275092], [0.129454, 0.472559, -0.439795, -0.091346, 0.417015, 0.387073, 0.960200, -0.133923], [0.123264, 0.460207, -0.450234, -0.096200, 0.402636, 0.375474, 0.956767, -0.138560], [-0.300694, -0.562441, 0.173284, -0.073690, -0.552556, -0.514858, -0.993430, -0.042081], [0.195612, 0.522368, -0.294331, -0.030943, 0.486750, 0.448836, 0.993798, -0.068004]]
pre_activation_mean: [-0.600345, -0.103529, -0.875189, 0.078572, 0.853382, 1.011166, -1.830832, 1.159858]
pre_activation_std: [0.997713, 0.282764, 0.777475, 0.398360, 1.195652, 1.227857, 1.093369, 1.367427]
### 6
mean: [0.975584, -1.429283, 0.922786, -0.931589, -0.856964, -1.379991, 0.636863, 0.412667]
std: [1.547999, 1.001934, 1.145903, 1.073630, 1.611235, 1.844440, 1.033302, 0.542203]
fourier: [[26.095370, 26.144860, 26.180654, 30.971906, 87.802529], [16.753425, 16.803210, 18.135267, 18.263308, 128.635440], [19.164066, 19.538360, 19.693151, 22.820835, 83.050734], [16.809799, 18.416939, 18.491283, 23.199134, 83.842991], [25.438161, 27.142761, 28.017212, 34.757418, 77.126741], [30.916020, 31.228321, 31.454211, 36.838813, 124.199153], [17.008789, 17.609632, 18.028281, 20.299949, 57.317713], [8.249906, 8.347497, 8.556875, 9.253879, 37.140000]]
input_correlations: [[-0.354972, -0.688632, -0.158556, -0.625194, 0.994319, 0.996189, 0.870545, 0.989344], [0.245443, 0.773588, 0.038512, 0.426803, -0.982285, -0.977834, -0.873505, -0.993252], [-0.348971, -0.711210, -0.149610, -0.584748, 0.995026, 0.995763, 0.877948, 0.994238], [0.479381, 0.639719, 0.294909, 0.676505, -0.967644, -0.972474, -0.857831, -0.962374], [0.511525, 0.626514, 0.326373, 0.662505, -0.961119, -0.966280, -0.851193, -0.955663], [0.353197, 0.696081, 0.155635, 0.616399, -0.994785, -0.996499, -0.873982, -0.990493], [-0.331898, -0.719804, -0.128929, -0.576718, 0.996361, 0.997118, 0.885728, 0.995064], [0.483711, -0.697561, 0.657577, -0.155519, 0.707060, 0.694765, 0.630769, 0.711966]]
pre_activation_mean: [0.975584, -1.429283, 0.922786, -0.931589, -0.856964, -1.379991, 0.636863, 0.412667]
pre_activation_std: [1.547999, 1.001934, 1.145903, 1.073630, 1.611235, 1.844440, 1.033302, 0.542203]
### 8
mean: [-0.142721, -0.556627, -0.229548, -0.223048, 1.158975, -0.402185, -0.436374, 0.160109]
std: [0.259670, 0.631294, 1.427391, 1.493834, 1.149823, 0.651021, 1.161838, 0.300372]
fourier: [[4.316706, 4.359343, 4.531177, 4.588574, 12.844904], [8.748990, 9.137707, 9.704246, 12.170093, 50.096441], [20.659290, 20.958897, 23.558435, 24.684327, 31.883129], [20.748647, 21.413914, 23.947308, 25.604955, 33.724960], [18.110558, 18.340033, 18.724592, 20.982036, 104.307753], [9.150559, 9.745397, 10.612882, 12.500635, 36.196676], [16.693506, 18.628674, 19.806854, 26.148425, 39.273662], [4.442808, 4.847291, 5.081301, 6.496608, 14.409852]]
input_correlations: [[-0.971303, -0.923502, -0.970773, 0.240137, 0.416003, 0.349936, -0.973976, -0.548609], [-0.153023, -0.141017, -0.130054, -0.948139, -0.870541, -0.857361, -0.155340, -0.806884], [-0.900863, -0.844158, -0.910712, 0.552677, 0.717989, 0.684286, -0.898588, -0.305955], [-0.854218, -0.805169, -0.865838, 0.629757, 0.781221, 0.744190, -0.851870, -0.209702], [0.988984, 0.918310, 0.985705, -0.000168, -0.208618, -0.185309, 0.989038, 0.779120], [0.388935, 0.379982, 0.408972, -0.951582, -0.988493, -0.946588, 0.385985, -0.402615], [-0.846871, -0.799117, -0.858453, 0.641637, 0.787400, 0.747111, -0.845057, -0.192937], [0.871815, 0.814745, 0.881052, -0.595589, -0.746323, -0.698284, 0.870502, 0.234778]]
pre_activation_mean: [-0.142721, -0.556627, -0.229548, -0.223048, 1.158975, -0.402185, -0.436374, 0.160109]
pre_activation_std: [0.259670, 0.631294, 1.427391, 1.493834, 1.149823, 0.651021, 1.161838, 0.300372]
### 10
mean: [0.180414]
std: [1.050642]
fourier: [[15.307089, 16.002608, 16.237235, 16.762151, 23.994031]]
input_correlations: [[0.852949, 0.275497, 0.944589, 0.928569, -0.606150, -0.442207, 0.871694, -0.783074]]
pre_activation_mean: [0.180414]
pre_activation_std: [1.050642]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.038540489971637726, "std": 0.08497924357652664, "fourier": [1.3994897783679325, 1.4803456282826257, 1.4837315545552918, 1.5342226737160474, 3.4686442480888218], "input_correlations": [-0.09389280737890812, -0.5731360736756391, -0.8128803303418507, -0.08107572591681728, -0.34683132769426667, 0.0, 0.0, 0.0], "pre_activation_mean": -2.4403069019317627, "pre_activation_std": 2.0661134719848633}, "1": {"mean": -0.12295547872781754, "std": 0.04800921306014061, "fourier": [0.7114678188513549, 0.7316281685148975, 0.7787240595084522, 0.9134195937531719, 11.065993281688577], "input_correlations": [0.15248058775243392, -0.36599604030629046, -0.5434671031664119, 0.10928933984168081, -0.5647268519790435, 0.0, 0.0, 0.0], "pre_activation_mean": -1.0565458536148071, "pre_activation_std": 1.9171113967895508}, "2": {"mean": 0.33695188164711, "std": 0.7744535207748413, "fourier": [10.889761032915201, 11.695690109308147, 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0.0], "pre_activation_mean": 0.037147536873817444, "pre_activation_std": 2.1488494873046875}, "5": {"mean": -0.09108377993106842, "std": 0.05576908588409424, "fourier": [0.8828159478295522, 0.8835104174297749, 0.9079280180980573, 1.0894755418400848, 8.197541262458856], "input_correlations": [0.20429952958950845, 0.716558624602712, 0.5701514259618996, 0.3840946063354183, 0.584223955635834, 0.0, 0.0, 0.0], "pre_activation_mean": 4.006237983703613, "pre_activation_std": 2.6430468559265137}, "6": {"mean": 0.13199369609355927, "std": 0.6529474854469299, "fourier": [8.84418050087707, 9.537110486024611, 10.986553209734373, 11.879433279507793, 11.942962296581676], "input_correlations": [0.20019421407061042, 0.7049567870997143, 0.18909977081273982, 0.8871820980158056, 0.23542630999328487, 0.0, 0.0, 0.0], "pre_activation_mean": 2.6956992149353027, "pre_activation_std": 2.2793002128601074}, "7": {"mean": 0.1227232813835144, "std": 0.17995508015155792, "fourier": [2.8361046528970992, 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54 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.54, "improved_accuracy": 0.9, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3433, "learning_rate": 0.016118345119958435, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [2.231947, 0.779389, 1.321702, 0.523746, 0.000000, 0.000000, 1.651236, 0.000000]
std: [2.479214, 1.009825, 1.390547, 0.036214, 0.000000, 0.000000, 1.890012, 0.000000]
fourier: [[40.732203, 41.452486, 41.465096, 43.733366, 200.875222], [16.064054, 16.259441, 17.239175, 18.216627, 70.145015], [23.527826, 23.549779, 23.988943, 24.225656, 118.953213], [0.527146, 0.538479, 0.564316, 0.709963, 47.137173], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [30.680930, 31.309210, 31.866848, 33.554587, 148.611269], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.829600, 0.438797, 0.239126, 0.491921, 0.385723, 0.000000, 0.000000, 0.000000], [-0.767361, -0.629751, -0.748496, -0.092158, -0.320039, 0.000000, 0.000000, 0.000000], [0.111379, 0.451004, -0.734036, 0.329953, -0.109902, 0.000000, 0.000000, 0.000000], [0.766447, 0.726925, 0.529035, 0.320964, 0.431394, 0.000000, 0.000000, 0.000000], [-0.716240, -0.606564, 0.124766, -0.185468, 0.319830, 0.000000, 0.000000, 0.000000], [-0.783490, 0.044777, -0.351259, 0.548263, 0.166168, 0.000000, 0.000000, 0.000000], [0.276830, 0.874508, 0.099340, 0.662247, -0.185471, 0.000000, 0.000000, 0.000000], [-0.819402, -0.418484, -0.170989, -0.194839, 0.322502, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.511968, -2.191787, 0.106369, 3.530817, -0.446917, 0.595640, 1.566029, 0.102051]
pre_activation_std: [1.710250, 1.713879, 1.144839, 2.434227, 1.346220, 1.849032, 1.148473, 1.201570]
### 2
mean: [0.541894, -1.550093, -1.447932, 1.588822, 2.204844, -0.677613, -1.505247, 2.272925]
std: [0.615494, 0.965258, 0.774760, 1.349975, 1.499532, 0.882495, 1.018627, 1.941348]
fourier: [[10.766362, 11.291562, 11.855370, 12.163237, 48.770481], [15.304070, 16.384376, 16.571940, 20.353289, 139.508398], [11.142422, 11.394880, 15.769003, 16.156466, 130.313920], [22.498107, 24.111222, 24.928179, 25.007887, 142.994011], [25.504216, 25.644843, 29.628353, 31.144981, 198.435929], [13.795752, 14.269279, 15.208007, 15.761115, 60.985191], [17.135071, 18.114698, 18.919887, 20.702173, 135.472228], [29.908674, 31.890510, 35.319099, 36.083990, 204.563244]]
input_correlations: [[-0.766315, 0.000000, -0.441166, -0.569183, 0.562558, 0.435213, -0.438563, 0.744151], [-0.822942, 0.000000, -0.177608, -0.969930, -0.032982, -0.102241, -0.556263, 0.135774], [-0.709335, 0.000000, -0.373198, -0.867767, 0.011369, -0.402475, -0.793656, 0.156103], [0.927290, 0.000000, 0.237949, 0.947416, -0.182781, -0.256115, 0.578208, -0.472248], [0.785468, 0.000000, 0.543633, 0.856402, -0.312659, 0.266725, 0.908144, -0.451308], [-0.916443, 0.000000, -0.539906, -0.840684, 0.420485, -0.152975, -0.709765, 0.462531], [-0.797058, 0.000000, -0.233390, -0.966506, -0.143849, 0.000289, -0.505661, 0.059671], [0.934161, 0.000000, 0.399823, 0.937034, -0.324510, -0.101311, 0.723018, -0.524714]]
pre_activation_mean: [0.541894, -1.550093, -1.447932, 1.588822, 2.204844, -0.677613, -1.505247, 2.272925]
pre_activation_std: [0.615494, 0.965258, 0.774760, 1.349975, 1.499532, 0.882495, 1.018627, 1.941348]
### 4
mean: [-1.437316, 1.848691, 0.518456, -1.413179, -0.142499, 1.788799, 0.294242, 0.367685]
std: [1.108919, 2.094911, 0.112975, 0.939479, 0.327708, 1.912877, 0.426991, 0.478455]
fourier: [[16.367140, 16.850056, 21.823049, 22.020685, 129.358472], [32.647206, 35.902586, 38.242242, 38.285817, 166.382227], [1.920045, 2.001460, 2.101850, 2.263507, 46.661081], [15.472247, 15.582291, 17.974510, 18.097096, 127.186146], [4.910141, 5.136820, 6.117814, 7.360027, 12.824953], [30.015424, 33.126990, 34.325591, 34.481936, 160.991928], [7.096181, 7.446285, 7.603034, 7.800932, 26.481788], [8.147020, 8.628486, 8.788104, 10.319576, 33.091687]]
input_correlations: [[0.564384, 0.000000, 0.000000, -0.933024, -0.959788, 0.485071, 0.000000, -0.979722], [-0.707552, 0.000000, 0.000000, 0.970902, 0.908772, -0.425116, 0.000000, 0.998026], [-0.352769, 0.000000, 0.000000, 0.924894, 0.707838, -0.086108, 0.000000, 0.849419], [0.607300, 0.000000, 0.000000, -0.987980, -0.875974, 0.340972, 0.000000, -0.985962], [0.039790, 0.000000, 0.000000, -0.072022, -0.646795, 0.583498, 0.000000, -0.283770], [-0.728390, 0.000000, 0.000000, 0.970154, 0.900384, -0.422802, 0.000000, 0.997254], [-0.746479, 0.000000, 0.000000, 0.989812, 0.829431, -0.369881, 0.000000, 0.985426], [-0.627623, 0.000000, 0.000000, 0.922661, 0.523588, -0.027188, 0.000000, 0.817258]]
pre_activation_mean: [-1.437316, 1.848691, 0.518456, -1.413179, -0.142499, 1.788799, 0.294242, 0.367685]
pre_activation_std: [1.108919, 2.094911, 0.112975, 0.939479, 0.327708, 1.912877, 0.426991, 0.478455]
### 6
mean: [2.191873, 0.702636, 1.317767, 0.523746, -0.379885, -0.701334, 1.595037, -0.415788]
std: [2.516301, 1.074783, 1.394317, 0.036214, 0.100737, 0.498384, 1.941431, 0.044937]
fourier: [[41.856723, 42.490251, 42.624197, 44.518129, 197.268585], [17.571165, 18.089303, 18.153160, 18.875474, 63.237290], [23.655134, 23.750881, 24.133503, 24.326214, 118.599001], [0.527146, 0.538479, 0.564316, 0.709963, 47.137173], [1.731976, 1.816905, 1.915313, 2.178653, 34.189672], [8.156670, 9.038402, 9.043844, 9.495010, 63.120069], [32.194106, 32.769182, 33.016711, 34.443232, 143.553281], [0.613266, 0.628736, 0.820348, 0.882178, 37.420915]]
input_correlations: [[-0.321374, 0.996412, 0.856225, 0.000000, -0.195548, 0.996965, 0.992745, 0.868425], [-0.318204, 0.997014, 0.843297, 0.000000, -0.224242, 0.997802, 0.992702, 0.859923], [-0.328724, 0.993925, 0.860055, 0.000000, -0.188269, 0.994985, 0.994581, 0.879997], [-0.264024, 0.298348, 0.051917, 0.000000, -0.987795, 0.294499, 0.203263, -0.105090], [0.259305, -0.792587, -0.881129, 0.000000, -0.295019, -0.796315, -0.867170, -0.986822], [0.301795, -0.962351, -0.879957, 0.000000, 0.043109, -0.964731, -0.990400, -0.943920], [-0.323300, 0.996824, 0.854750, 0.000000, -0.196866, 0.997421, 0.991726, 0.865232], [0.082431, -0.847603, -0.665677, 0.000000, 0.470955, -0.832863, -0.788779, -0.515595]]
pre_activation_mean: [2.191873, 0.702636, 1.317767, 0.523746, -0.379885, -0.701334, 1.595037, -0.415788]
pre_activation_std: [2.516301, 1.074783, 1.394317, 0.036214, 0.100737, 0.498384, 1.941431, 0.044937]
### 8
mean: [-1.607387]
std: [2.656732]
fourier: [[43.626742, 44.354850, 44.704162, 46.914509, 144.664869]]
input_correlations: [[-0.999959, -0.996816, -0.999115, -0.232705, 0.000000, 0.000000, -0.999918, 0.000000]]
pre_activation_mean: [-1.607387]
pre_activation_std: [2.656732]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
-0.299826,
0.191123,
-0.327253,
0.093521,
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],
[
0.262601,
0.156569,
-0.023285,
-0.005692,
-0.317178,
-0.268922,
-0.495802,
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],
[
0.338771,
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0.247097,
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0.01721,
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],
[
-0.160654,
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0.259242,
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],
"network.6.bias": [
-0.146192,
-0.11363,
0.058879,
0.568915,
-0.138439,
-0.216694,
-0.253231,
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"network.8.weight": [
[
-0.565208,
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0.053723,
-0.441569,
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]
],
"network.8.bias": [
0.573348
]
}
## Activation Signature
### 0
mean: [2.231947, 0.779389, 1.321702, 0.523746, 0.000000, 0.000000, 1.651236, 0.000000]
std: [2.479214, 1.009825, 1.390547, 0.036214, 0.000000, 0.000000, 1.890012, 0.000000]
fourier: [[40.732203, 41.452486, 41.465096, 43.733366, 200.875222], [16.064054, 16.259441, 17.239175, 18.216627, 70.145015], [23.527826, 23.549779, 23.988943, 24.225656, 118.953213], [0.527146, 0.538479, 0.564316, 0.709963, 47.137173], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [30.680930, 31.309210, 31.866848, 33.554587, 148.611269], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.829600, 0.438797, 0.239126, 0.491921, 0.385723, 0.000000, 0.000000, 0.000000], [-0.767361, -0.629751, -0.748496, -0.092158, -0.320039, 0.000000, 0.000000, 0.000000], [0.111379, 0.451004, -0.734036, 0.329953, -0.109902, 0.000000, 0.000000, 0.000000], [0.766447, 0.726925, 0.529035, 0.320964, 0.431394, 0.000000, 0.000000, 0.000000], [-0.716240, -0.606564, 0.124766, -0.185468, 0.319830, 0.000000, 0.000000, 0.000000], [-0.783490, 0.044777, -0.351259, 0.548263, 0.166168, 0.000000, 0.000000, 0.000000], [0.276830, 0.874508, 0.099340, 0.662247, -0.185471, 0.000000, 0.000000, 0.000000], [-0.819402, -0.418484, -0.170989, -0.194839, 0.322502, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.511968, -2.191787, 0.106369, 3.530817, -0.446917, 0.595640, 1.566029, 0.102051]
pre_activation_std: [1.710250, 1.713879, 1.144839, 2.434227, 1.346220, 1.849032, 1.148473, 1.201570]
### 2
mean: [0.541894, -1.550093, -1.447932, 1.588822, 2.204844, -0.677613, -1.505247, 2.272925]
std: [0.615494, 0.965258, 0.774760, 1.349975, 1.499532, 0.882495, 1.018627, 1.941348]
fourier: [[10.766362, 11.291562, 11.855370, 12.163237, 48.770481], [15.304070, 16.384376, 16.571940, 20.353289, 139.508398], [11.142422, 11.394880, 15.769003, 16.156466, 130.313920], [22.498107, 24.111222, 24.928179, 25.007887, 142.994011], [25.504216, 25.644843, 29.628353, 31.144981, 198.435929], [13.795752, 14.269279, 15.208007, 15.761115, 60.985191], [17.135071, 18.114698, 18.919887, 20.702173, 135.472228], [29.908674, 31.890510, 35.319099, 36.083990, 204.563244]]
input_correlations: [[-0.766315, 0.000000, -0.441166, -0.569183, 0.562558, 0.435213, -0.438563, 0.744151], [-0.822942, 0.000000, -0.177608, -0.969930, -0.032982, -0.102241, -0.556263, 0.135774], [-0.709335, 0.000000, -0.373198, -0.867767, 0.011369, -0.402475, -0.793656, 0.156103], [0.927290, 0.000000, 0.237949, 0.947416, -0.182781, -0.256115, 0.578208, -0.472248], [0.785468, 0.000000, 0.543633, 0.856402, -0.312659, 0.266725, 0.908144, -0.451308], [-0.916443, 0.000000, -0.539906, -0.840684, 0.420485, -0.152975, -0.709765, 0.462531], [-0.797058, 0.000000, -0.233390, -0.966506, -0.143849, 0.000289, -0.505661, 0.059671], [0.934161, 0.000000, 0.399823, 0.937034, -0.324510, -0.101311, 0.723018, -0.524714]]
pre_activation_mean: [0.541894, -1.550093, -1.447932, 1.588822, 2.204844, -0.677613, -1.505247, 2.272925]
pre_activation_std: [0.615494, 0.965258, 0.774760, 1.349975, 1.499532, 0.882495, 1.018627, 1.941348]
### 4
mean: [-1.437316, 1.848691, 0.518456, -1.413179, -0.142499, 1.788799, 0.294242, 0.367685]
std: [1.108919, 2.094911, 0.112975, 0.939479, 0.327708, 1.912877, 0.426991, 0.478455]
fourier: [[16.367140, 16.850056, 21.823049, 22.020685, 129.358472], [32.647206, 35.902586, 38.242242, 38.285817, 166.382227], [1.920045, 2.001460, 2.101850, 2.263507, 46.661081], [15.472247, 15.582291, 17.974510, 18.097096, 127.186146], [4.910141, 5.136820, 6.117814, 7.360027, 12.824953], [30.015424, 33.126990, 34.325591, 34.481936, 160.991928], [7.096181, 7.446285, 7.603034, 7.800932, 26.481788], [8.147020, 8.628486, 8.788104, 10.319576, 33.091687]]
input_correlations: [[0.564384, 0.000000, 0.000000, -0.933024, -0.959788, 0.485071, 0.000000, -0.979722], [-0.707552, 0.000000, 0.000000, 0.970902, 0.908772, -0.425116, 0.000000, 0.998026], [-0.352769, 0.000000, 0.000000, 0.924894, 0.707838, -0.086108, 0.000000, 0.849419], [0.607300, 0.000000, 0.000000, -0.987980, -0.875974, 0.340972, 0.000000, -0.985962], [0.039790, 0.000000, 0.000000, -0.072022, -0.646795, 0.583498, 0.000000, -0.283770], [-0.728390, 0.000000, 0.000000, 0.970154, 0.900384, -0.422802, 0.000000, 0.997254], [-0.746479, 0.000000, 0.000000, 0.989812, 0.829431, -0.369881, 0.000000, 0.985426], [-0.627623, 0.000000, 0.000000, 0.922661, 0.523588, -0.027188, 0.000000, 0.817258]]
pre_activation_mean: [-1.437316, 1.848691, 0.518456, -1.413179, -0.142499, 1.788799, 0.294242, 0.367685]
pre_activation_std: [1.108919, 2.094911, 0.112975, 0.939479, 0.327708, 1.912877, 0.426991, 0.478455]
### 6
mean: [2.191873, 0.702636, 1.317767, 0.523746, -0.379885, -0.701334, 1.595037, -0.415788]
std: [2.516301, 1.074783, 1.394317, 0.036214, 0.100737, 0.498384, 1.941431, 0.044937]
fourier: [[41.856723, 42.490251, 42.624197, 44.518129, 197.268585], [17.571165, 18.089303, 18.153160, 18.875474, 63.237290], [23.655134, 23.750881, 24.133503, 24.326214, 118.599001], [0.527146, 0.538479, 0.564316, 0.709963, 47.137173], [1.731976, 1.816905, 1.915313, 2.178653, 34.189672], [8.156670, 9.038402, 9.043844, 9.495010, 63.120069], [32.194106, 32.769182, 33.016711, 34.443232, 143.553281], [0.613266, 0.628736, 0.820348, 0.882178, 37.420915]]
input_correlations: [[-0.321374, 0.996412, 0.856225, 0.000000, -0.195548, 0.996965, 0.992745, 0.868425], [-0.318204, 0.997014, 0.843297, 0.000000, -0.224242, 0.997802, 0.992702, 0.859923], [-0.328724, 0.993925, 0.860055, 0.000000, -0.188269, 0.994985, 0.994581, 0.879997], [-0.264024, 0.298348, 0.051917, 0.000000, -0.987795, 0.294499, 0.203263, -0.105090], [0.259305, -0.792587, -0.881129, 0.000000, -0.295019, -0.796315, -0.867170, -0.986822], [0.301795, -0.962351, -0.879957, 0.000000, 0.043109, -0.964731, -0.990400, -0.943920], [-0.323300, 0.996824, 0.854750, 0.000000, -0.196866, 0.997421, 0.991726, 0.865232], [0.082431, -0.847603, -0.665677, 0.000000, 0.470955, -0.832863, -0.788779, -0.515595]]
pre_activation_mean: [2.191873, 0.702636, 1.317767, 0.523746, -0.379885, -0.701334, 1.595037, -0.415788]
pre_activation_std: [2.516301, 1.074783, 1.394317, 0.036214, 0.100737, 0.498384, 1.941431, 0.044937]
### 8
mean: [-1.607387]
std: [2.656732]
fourier: [[43.626742, 44.354850, 44.704162, 46.914509, 144.664869]]
input_correlations: [[-0.999959, -0.996816, -0.999115, -0.232705, 0.000000, 0.000000, -0.999918, 0.000000]]
pre_activation_mean: [-1.607387]
pre_activation_std: [2.656732]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 2.2319469451904297, "std": 2.4792139530181885, "fourier": [40.73220255098361, 41.452485562019476, 41.46509600506757, 43.73336561384079, 200.87522204220295], "input_correlations": [0.8296000774239365, 0.4387974765471623, 0.23912578300665138, 0.49192137476031206, 0.38572298544056227, 0.0, 0.0, 0.0], "pre_activation_mean": 1.5119677782058716, "pre_activation_std": 1.7102500200271606}, "1": {"mean": 0.7793890833854675, "std": 1.009825348854065, "fourier": [16.064054412891974, 16.259441372822057, 17.239175224926125, 18.216627218155455, 70.14501535892487], "input_correlations": [-0.7673605132735479, -0.6297514016109816, -0.7484962358615733, -0.092157665568064, -0.32003868470531227, 0.0, 0.0, 0.0], "pre_activation_mean": -2.191786766052246, "pre_activation_std": 1.7138785123825073}, "2": {"mean": 1.3217023611068726, "std": 1.390547275543213, "fourier": [23.52782580218083, 23.549778748667794, 23.98894253164912, 24.225656358687306, 118.95321296527982], "input_correlations": [0.11137937409386273, 0.45100365276225846, -0.7340355543804312, 0.32995282606237364, -0.10990209548044763, 0.0, 0.0, 0.0], "pre_activation_mean": 0.10636866837739944, "pre_activation_std": 1.1448389291763306}, "3": {"mean": 0.5237463712692261, "std": 0.03621354326605797, "fourier": [0.5271456795710444, 0.5384788507284094, 0.5643157157391536, 0.7099632150641397, 47.137173026800156], "input_correlations": [0.7664474551014026, 0.7269245818692186, 0.5290349841746241, 0.32096440785580355, 0.431394236800283, 0.0, 0.0, 0.0], "pre_activation_mean": 3.5308165550231934, "pre_activation_std": 2.434227228164673}, "4": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.7162397552120139, -0.6065641372885605, 0.12476594959047355, -0.18546782007278895, 0.31983029224955795, 0.0, 0.0, 0.0], "pre_activation_mean": -0.4469173550605774, "pre_activation_std": 1.3462203741073608}, "5": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.7834904546182474, 0.04477741348651984, -0.351258754976325, 0.5482632464711404, 0.1661678448725122, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5956395268440247, "pre_activation_std": 1.8490321636199951}, "6": {"mean": 1.6512364149093628, "std": 1.8900117874145508, "fourier": [30.68092974712966, 31.309210164613784, 31.866847698007653, 33.55458688640187, 148.61126935482025], "input_correlations": [0.27682961730158606, 0.8745079195390308, 0.09933965920327266, 0.6622465346055482, -0.1854712789372771, 0.0, 0.0, 0.0], "pre_activation_mean": 1.5660287141799927, "pre_activation_std": 1.1484732627868652}, "7": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.8194024916280666, -0.4184840427767221, -0.17098851759437145, -0.1948394961841946, 0.32250219664946134, 0.0, 0.0, 0.0], "pre_activation_mean": 0.1020507887005806, "pre_activation_std": 1.2015701532363892}}, "layer_info": {"num_neurons": 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"val_loss": 0.3816792964935303, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.40360523760318756, "train_acc": 0.85, "val_loss": 0.3385433852672577, "val_acc": 0.9}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.705742597579956, "final_val_loss": 0.6656091213226318, "initial_val_acc": 0.46, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.6381029486656189, "final_val_loss": 0.3385433852672577, "initial_val_acc": 0.68, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 12}, "improvement": 0.36, "first_improvement_epoch": 2}} |
55 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.46, "improved_accuracy": 0.86, "improvement": 0.39999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9301, "learning_rate": 0.0794152084668348, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.814717, 0.000000, 7.695649]
std: [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.716871, 0.000000, 7.548129]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [118.876837, 130.449817, 146.859640, 156.621675, 703.324490], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [116.547073, 127.822734, 143.817500, 153.016052, 692.608406]]
input_correlations: [[-0.520396, -0.010449, -0.699120, 0.648586, -0.131588, 0.000000, 0.000000, 0.000000], [-0.666052, 0.168347, 0.329026, 0.130252, 0.254960, 0.000000, 0.000000, 0.000000], [-0.406607, -0.560784, 0.332319, -0.380112, 0.496655, 0.000000, 0.000000, 0.000000], [-0.669093, 0.070597, 0.411096, 0.096900, 0.208830, 0.000000, 0.000000, 0.000000], [0.930737, 0.483000, 0.415308, -0.240486, 0.210457, 0.000000, 0.000000, 0.000000], [0.833758, -0.078471, 0.522487, -0.267760, 0.424482, 0.000000, 0.000000, 0.000000], [-0.766562, -0.056440, -0.051990, -0.111710, -0.669843, 0.000000, 0.000000, 0.000000], [-0.585373, -0.167248, -0.809196, 0.046523, 0.207947, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.277709, 0.329424, -0.050462, 0.119666, 1.293014, 0.520737, -0.766892, -1.255696]
pre_activation_std: [1.646812, 1.231800, 1.770084, 1.219630, 2.243062, 1.698351, 0.862251, 1.286202]
### 2
mean: [-0.197398, 0.457842, -0.959152, 1.111788, 0.671530, -1.207003, -1.720891, 0.315096]
std: [0.716762, 1.847535, 0.475172, 2.012244, 0.964122, 1.843097, 1.649840, 1.431571]
fourier: [[11.460459, 12.704192, 12.730881, 13.548835, 17.765779], [31.590908, 32.777233, 34.135133, 40.683374, 41.205809], [7.530214, 7.551868, 9.164933, 9.483943, 86.323678], [31.532788, 36.626633, 36.723161, 37.875641, 100.060895], [17.429232, 17.879680, 20.227277, 20.570257, 60.437730], [31.119576, 32.668760, 33.808890, 35.119607, 108.630319], [29.031733, 30.076360, 30.122973, 32.493553, 154.880173], [25.153168, 25.572980, 25.727705, 28.358618, 30.686442]]
input_correlations: [[0.101887, -0.826118, -0.669930, -0.835624, 0.579163, 0.478548, -0.346743, -0.254225], [0.424468, 0.680027, 0.390030, 0.646020, -0.827734, -0.702838, 0.276377, 0.323947], [-0.099482, -0.276460, -0.328005, -0.275093, -0.638813, -0.725680, -0.166909, -0.075574], [0.140737, 0.805281, 0.742013, 0.817948, -0.569887, -0.349715, 0.378727, 0.320291], [0.309001, 0.810274, 0.199908, 0.739385, -0.609861, -0.734956, 0.368820, 0.302468], [0.624557, -0.024827, -0.422678, -0.098316, -0.861315, -0.893873, -0.079254, 0.148757], [0.427041, -0.252641, -0.469736, -0.275863, -0.827934, -0.832266, -0.159345, -0.053404], [-0.311659, -0.581639, -0.441088, -0.568420, 0.879524, 0.696995, -0.212176, -0.344225]]
pre_activation_mean: [-0.197398, 0.457842, -0.959152, 1.111788, 0.671530, -1.207003, -1.720891, 0.315096]
pre_activation_std: [0.716762, 1.847535, 0.475172, 2.012244, 0.964122, 1.843097, 1.649840, 1.431571]
### 4
mean: [-0.472942, -1.630720, -0.991565, -1.399667, -0.168104, 1.774593, 1.942899, -1.210163]
std: [0.331723, 1.258309, 1.886752, 0.802820, 1.307158, 1.629015, 2.142917, 1.355381]
fourier: [[5.117740, 5.298396, 5.708680, 6.425870, 42.564786], [19.769055, 21.054264, 22.907539, 25.020846, 146.764769], [32.992915, 34.181823, 35.189627, 38.497313, 89.240819], [12.114133, 12.272337, 12.424395, 16.412393, 125.970000], [20.512153, 22.015360, 22.650482, 24.114959, 26.850426], [25.942791, 28.081926, 30.892508, 32.504102, 159.713369], [32.442618, 37.079110, 40.785810, 43.034538, 174.860917], [23.519503, 23.766033, 26.148510, 27.240290, 108.914705]]
input_correlations: [[0.562737, -0.855131, 0.000000, -0.608658, -0.796654, -0.680355, -0.227384, 0.702219], [0.467168, -0.974929, 0.000000, -0.975511, -0.826067, -0.143367, 0.149429, 0.507447], [0.730360, -0.942261, 0.000000, -0.835761, -0.891647, -0.344405, -0.029681, 0.786251], [-0.056215, -0.720483, 0.000000, -0.851341, -0.529235, 0.160569, 0.356778, -0.056942], [0.795396, -0.881503, 0.000000, -0.756128, -0.831027, -0.402710, -0.127362, 0.871281], [-0.525176, 0.990622, 0.000000, 0.948953, 0.855180, 0.225578, -0.096485, -0.579373], [-0.578181, 0.968951, 0.000000, 0.969537, 0.874196, 0.116975, -0.140995, -0.603063], [0.652538, -0.972548, 0.000000, -0.861594, -0.907208, -0.346561, 0.013635, 0.710732]]
pre_activation_mean: [-0.472942, -1.630720, -0.991565, -1.399667, -0.168104, 1.774593, 1.942899, -1.210163]
pre_activation_std: [0.331723, 1.258309, 1.886752, 0.802820, 1.307158, 1.629015, 2.142917, 1.355381]
### 6
mean: [1.264158, -1.199830, -0.034275, 0.638829, 1.717220, -0.836838, 2.559867, -2.098712]
std: [1.864738, 0.675234, 0.488017, 1.626653, 2.395198, 0.573186, 2.645822, 1.415757]
fourier: [[30.090848, 34.102193, 35.901458, 37.704041, 113.774173], [10.361777, 10.791976, 11.792766, 13.472960, 107.984745], [7.414533, 7.660984, 9.020977, 9.110726, 10.115820], [27.225782, 27.768418, 30.108949, 33.886080, 57.494580], [38.300882, 43.658668, 46.456680, 48.348604, 154.549820], [9.732408, 10.186513, 10.518548, 10.767156, 75.315383], [41.212445, 46.896203, 51.806837, 52.751151, 230.388052], [20.948401, 21.716199, 22.960150, 28.187662, 188.884111]]
input_correlations: [[-0.217847, 0.000000, -0.739617, 0.000000, -0.775491, 0.963367, 0.959999, -0.690240], [0.077416, 0.000000, 0.412185, 0.000000, 0.466830, -0.985931, -0.986090, 0.351098], [-0.253611, 0.000000, -0.797686, 0.000000, -0.825468, 0.940825, 0.926791, -0.760638], [-0.291547, 0.000000, -0.900809, 0.000000, -0.923157, 0.858829, 0.838818, -0.862357], [-0.209150, 0.000000, -0.719913, 0.000000, -0.757889, 0.973677, 0.966688, -0.669848], [-0.366950, 0.000000, -0.975492, 0.000000, -0.962088, 0.367147, 0.330963, -0.972512], [-0.174590, 0.000000, -0.636841, 0.000000, -0.678732, 0.990855, 0.989284, -0.584579], [0.036523, 0.000000, 0.292072, 0.000000, 0.344008, -0.952154, -0.966981, 0.234332]]
pre_activation_mean: [1.264158, -1.199830, -0.034275, 0.638829, 1.717220, -0.836838, 2.559867, -2.098712]
pre_activation_std: [1.864738, 0.675234, 0.488017, 1.626653, 2.395198, 0.573186, 2.645822, 1.415757]
### 8
mean: [4.814659, 4.217494, -1.185377, -0.367482, 3.274105, -0.198453, -1.512690, 3.583644]
std: [4.720724, 4.167478, 0.853729, 0.047085, 3.250509, 0.065622, 1.235758, 3.285563]
fourier: [[73.715334, 80.797173, 90.271653, 95.289278, 433.319280], [64.857825, 71.134950, 79.471236, 84.266589, 379.574409], [12.916896, 14.520834, 16.189574, 17.461213, 106.683951], [0.753077, 0.791140, 0.855452, 1.008411, 33.073410], [50.687037, 55.615083, 62.224686, 65.635093, 294.669435], [1.100475, 1.169878, 1.172849, 1.235685, 17.860810], [18.767806, 20.924970, 23.396786, 25.234186, 136.142105], [51.482362, 56.236752, 62.856869, 66.214490, 322.527995]]
input_correlations: [[0.999045, 0.000000, 0.946277, 0.995247, 0.999604, 0.000000, 0.999791, 0.000000], [0.999167, 0.000000, 0.948693, 0.994327, 0.999776, 0.000000, 0.999821, 0.000000], [-0.997484, 0.000000, -0.962343, -0.988514, -0.998948, 0.000000, -0.998606, 0.000000], [0.755137, 0.000000, 0.535857, 0.814826, 0.751437, 0.000000, 0.766253, 0.000000], [0.999032, 0.000000, 0.946267, 0.995372, 0.999624, 0.000000, 0.999723, 0.000000], [-0.952794, 0.000000, -0.822952, -0.963778, -0.949573, 0.000000, -0.954867, 0.000000], [-0.999125, 0.000000, -0.959475, -0.989622, -0.999403, 0.000000, -0.998995, 0.000000], [0.999010, 0.000000, 0.944422, 0.995713, 0.999482, 0.000000, 0.999703, 0.000000]]
pre_activation_mean: [4.814659, 4.217494, -1.185377, -0.367482, 3.274105, -0.198453, -1.512690, 3.583644]
pre_activation_std: [4.720724, 4.167478, 0.853729, 0.047085, 3.250509, 0.065622, 1.235758, 3.285563]
### 10
mean: [-0.677665, -0.746461, -0.366131, -2.644825, -0.978278, 7.748558, -4.469185, 7.657559]
std: [0.522544, 0.645644, 0.065876, 2.252340, 0.658705, 7.784410, 3.877121, 7.587152]
fourier: [[8.305201, 9.020617, 10.001682, 10.468592, 60.989855], [9.980475, 10.947094, 12.312302, 13.072776, 67.181519], [0.940995, 1.017341, 1.229154, 1.369410, 32.951800], [35.038915, 38.347755, 42.950457, 45.506315, 238.034191], [10.270307, 11.234117, 12.578891, 13.297559, 88.044986], [120.706891, 132.279017, 148.438297, 157.483468, 697.370195], [60.371526, 66.066066, 73.935016, 78.326445, 402.226645], [117.651971, 128.933021, 144.690682, 153.491864, 689.180301]]
input_correlations: [[-0.999231, -0.998938, 0.000000, 0.000000, -0.999042, 0.000000, 0.000000, -0.999735], [-0.999956, -0.999977, 0.000000, 0.000000, -0.999984, 0.000000, 0.000000, -0.999666], [-0.981730, -0.982905, 0.000000, 0.000000, -0.982601, 0.000000, 0.000000, -0.978521], [-0.999998, -0.999968, 0.000000, 0.000000, -0.999976, 0.000000, 0.000000, -0.999863], [-0.999983, -0.999905, 0.000000, 0.000000, -0.999944, 0.000000, 0.000000, -0.999942], [0.999990, 0.999988, 0.000000, 0.000000, 0.999992, 0.000000, 0.000000, 0.999783], [-0.999992, -0.999954, 0.000000, 0.000000, -0.999961, 0.000000, 0.000000, -0.999892], [0.999991, 0.999986, 0.000000, 0.000000, 0.999993, 0.000000, 0.000000, 0.999787]]
pre_activation_mean: [-0.677665, -0.746461, -0.366131, -2.644825, -0.978278, 7.748558, -4.469185, 7.657559]
pre_activation_std: [0.522544, 0.645644, 0.065876, 2.252340, 0.658705, 7.784410, 3.877121, 7.587152]
### 12
mean: [-4.990959]
std: [5.196681]
fourier: [[80.125636, 87.907623, 98.943242, 105.424007, 449.186264]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999998, 0.000000, -0.999995]]
pre_activation_mean: [-4.990959]
pre_activation_std: [5.196681]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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-0.237754,
0.007538,
-0.513545,
0.50825,
-0.040521
],
[
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0.298147,
0.306043,
-0.073652,
0.239159
],
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.814717, 0.000000, 7.695649]
std: [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 7.716871, 0.000000, 7.548129]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [118.876837, 130.449817, 146.859640, 156.621675, 703.324490], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [116.547073, 127.822734, 143.817500, 153.016052, 692.608406]]
input_correlations: [[-0.520396, -0.010449, -0.699120, 0.648586, -0.131588, 0.000000, 0.000000, 0.000000], [-0.666052, 0.168347, 0.329026, 0.130252, 0.254960, 0.000000, 0.000000, 0.000000], [-0.406607, -0.560784, 0.332319, -0.380112, 0.496655, 0.000000, 0.000000, 0.000000], [-0.669093, 0.070597, 0.411096, 0.096900, 0.208830, 0.000000, 0.000000, 0.000000], [0.930737, 0.483000, 0.415308, -0.240486, 0.210457, 0.000000, 0.000000, 0.000000], [0.833758, -0.078471, 0.522487, -0.267760, 0.424482, 0.000000, 0.000000, 0.000000], [-0.766562, -0.056440, -0.051990, -0.111710, -0.669843, 0.000000, 0.000000, 0.000000], [-0.585373, -0.167248, -0.809196, 0.046523, 0.207947, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.277709, 0.329424, -0.050462, 0.119666, 1.293014, 0.520737, -0.766892, -1.255696]
pre_activation_std: [1.646812, 1.231800, 1.770084, 1.219630, 2.243062, 1.698351, 0.862251, 1.286202]
### 2
mean: [-0.197398, 0.457842, -0.959152, 1.111788, 0.671530, -1.207003, -1.720891, 0.315096]
std: [0.716762, 1.847535, 0.475172, 2.012244, 0.964122, 1.843097, 1.649840, 1.431571]
fourier: [[11.460459, 12.704192, 12.730881, 13.548835, 17.765779], [31.590908, 32.777233, 34.135133, 40.683374, 41.205809], [7.530214, 7.551868, 9.164933, 9.483943, 86.323678], [31.532788, 36.626633, 36.723161, 37.875641, 100.060895], [17.429232, 17.879680, 20.227277, 20.570257, 60.437730], [31.119576, 32.668760, 33.808890, 35.119607, 108.630319], [29.031733, 30.076360, 30.122973, 32.493553, 154.880173], [25.153168, 25.572980, 25.727705, 28.358618, 30.686442]]
input_correlations: [[0.101887, -0.826118, -0.669930, -0.835624, 0.579163, 0.478548, -0.346743, -0.254225], [0.424468, 0.680027, 0.390030, 0.646020, -0.827734, -0.702838, 0.276377, 0.323947], [-0.099482, -0.276460, -0.328005, -0.275093, -0.638813, -0.725680, -0.166909, -0.075574], [0.140737, 0.805281, 0.742013, 0.817948, -0.569887, -0.349715, 0.378727, 0.320291], [0.309001, 0.810274, 0.199908, 0.739385, -0.609861, -0.734956, 0.368820, 0.302468], [0.624557, -0.024827, -0.422678, -0.098316, -0.861315, -0.893873, -0.079254, 0.148757], [0.427041, -0.252641, -0.469736, -0.275863, -0.827934, -0.832266, -0.159345, -0.053404], [-0.311659, -0.581639, -0.441088, -0.568420, 0.879524, 0.696995, -0.212176, -0.344225]]
pre_activation_mean: [-0.197398, 0.457842, -0.959152, 1.111788, 0.671530, -1.207003, -1.720891, 0.315096]
pre_activation_std: [0.716762, 1.847535, 0.475172, 2.012244, 0.964122, 1.843097, 1.649840, 1.431571]
### 4
mean: [-0.472942, -1.630720, -0.991565, -1.399667, -0.168104, 1.774593, 1.942899, -1.210163]
std: [0.331723, 1.258309, 1.886752, 0.802820, 1.307158, 1.629015, 2.142917, 1.355381]
fourier: [[5.117740, 5.298396, 5.708680, 6.425870, 42.564786], [19.769055, 21.054264, 22.907539, 25.020846, 146.764769], [32.992915, 34.181823, 35.189627, 38.497313, 89.240819], [12.114133, 12.272337, 12.424395, 16.412393, 125.970000], [20.512153, 22.015360, 22.650482, 24.114959, 26.850426], [25.942791, 28.081926, 30.892508, 32.504102, 159.713369], [32.442618, 37.079110, 40.785810, 43.034538, 174.860917], [23.519503, 23.766033, 26.148510, 27.240290, 108.914705]]
input_correlations: [[0.562737, -0.855131, 0.000000, -0.608658, -0.796654, -0.680355, -0.227384, 0.702219], [0.467168, -0.974929, 0.000000, -0.975511, -0.826067, -0.143367, 0.149429, 0.507447], [0.730360, -0.942261, 0.000000, -0.835761, -0.891647, -0.344405, -0.029681, 0.786251], [-0.056215, -0.720483, 0.000000, -0.851341, -0.529235, 0.160569, 0.356778, -0.056942], [0.795396, -0.881503, 0.000000, -0.756128, -0.831027, -0.402710, -0.127362, 0.871281], [-0.525176, 0.990622, 0.000000, 0.948953, 0.855180, 0.225578, -0.096485, -0.579373], [-0.578181, 0.968951, 0.000000, 0.969537, 0.874196, 0.116975, -0.140995, -0.603063], [0.652538, -0.972548, 0.000000, -0.861594, -0.907208, -0.346561, 0.013635, 0.710732]]
pre_activation_mean: [-0.472942, -1.630720, -0.991565, -1.399667, -0.168104, 1.774593, 1.942899, -1.210163]
pre_activation_std: [0.331723, 1.258309, 1.886752, 0.802820, 1.307158, 1.629015, 2.142917, 1.355381]
### 6
mean: [1.264158, -1.199830, -0.034275, 0.638829, 1.717220, -0.836838, 2.559867, -2.098712]
std: [1.864738, 0.675234, 0.488017, 1.626653, 2.395198, 0.573186, 2.645822, 1.415757]
fourier: [[30.090848, 34.102193, 35.901458, 37.704041, 113.774173], [10.361777, 10.791976, 11.792766, 13.472960, 107.984745], [7.414533, 7.660984, 9.020977, 9.110726, 10.115820], [27.225782, 27.768418, 30.108949, 33.886080, 57.494580], [38.300882, 43.658668, 46.456680, 48.348604, 154.549820], [9.732408, 10.186513, 10.518548, 10.767156, 75.315383], [41.212445, 46.896203, 51.806837, 52.751151, 230.388052], [20.948401, 21.716199, 22.960150, 28.187662, 188.884111]]
input_correlations: [[-0.217847, 0.000000, -0.739617, 0.000000, -0.775491, 0.963367, 0.959999, -0.690240], [0.077416, 0.000000, 0.412185, 0.000000, 0.466830, -0.985931, -0.986090, 0.351098], [-0.253611, 0.000000, -0.797686, 0.000000, -0.825468, 0.940825, 0.926791, -0.760638], [-0.291547, 0.000000, -0.900809, 0.000000, -0.923157, 0.858829, 0.838818, -0.862357], [-0.209150, 0.000000, -0.719913, 0.000000, -0.757889, 0.973677, 0.966688, -0.669848], [-0.366950, 0.000000, -0.975492, 0.000000, -0.962088, 0.367147, 0.330963, -0.972512], [-0.174590, 0.000000, -0.636841, 0.000000, -0.678732, 0.990855, 0.989284, -0.584579], [0.036523, 0.000000, 0.292072, 0.000000, 0.344008, -0.952154, -0.966981, 0.234332]]
pre_activation_mean: [1.264158, -1.199830, -0.034275, 0.638829, 1.717220, -0.836838, 2.559867, -2.098712]
pre_activation_std: [1.864738, 0.675234, 0.488017, 1.626653, 2.395198, 0.573186, 2.645822, 1.415757]
### 8
mean: [4.814659, 4.217494, -1.185377, -0.367482, 3.274105, -0.198453, -1.512690, 3.583644]
std: [4.720724, 4.167478, 0.853729, 0.047085, 3.250509, 0.065622, 1.235758, 3.285563]
fourier: [[73.715334, 80.797173, 90.271653, 95.289278, 433.319280], [64.857825, 71.134950, 79.471236, 84.266589, 379.574409], [12.916896, 14.520834, 16.189574, 17.461213, 106.683951], [0.753077, 0.791140, 0.855452, 1.008411, 33.073410], [50.687037, 55.615083, 62.224686, 65.635093, 294.669435], [1.100475, 1.169878, 1.172849, 1.235685, 17.860810], [18.767806, 20.924970, 23.396786, 25.234186, 136.142105], [51.482362, 56.236752, 62.856869, 66.214490, 322.527995]]
input_correlations: [[0.999045, 0.000000, 0.946277, 0.995247, 0.999604, 0.000000, 0.999791, 0.000000], [0.999167, 0.000000, 0.948693, 0.994327, 0.999776, 0.000000, 0.999821, 0.000000], [-0.997484, 0.000000, -0.962343, -0.988514, -0.998948, 0.000000, -0.998606, 0.000000], [0.755137, 0.000000, 0.535857, 0.814826, 0.751437, 0.000000, 0.766253, 0.000000], [0.999032, 0.000000, 0.946267, 0.995372, 0.999624, 0.000000, 0.999723, 0.000000], [-0.952794, 0.000000, -0.822952, -0.963778, -0.949573, 0.000000, -0.954867, 0.000000], [-0.999125, 0.000000, -0.959475, -0.989622, -0.999403, 0.000000, -0.998995, 0.000000], [0.999010, 0.000000, 0.944422, 0.995713, 0.999482, 0.000000, 0.999703, 0.000000]]
pre_activation_mean: [4.814659, 4.217494, -1.185377, -0.367482, 3.274105, -0.198453, -1.512690, 3.583644]
pre_activation_std: [4.720724, 4.167478, 0.853729, 0.047085, 3.250509, 0.065622, 1.235758, 3.285563]
### 10
mean: [-0.677665, -0.746461, -0.366131, -2.644825, -0.978278, 7.748558, -4.469185, 7.657559]
std: [0.522544, 0.645644, 0.065876, 2.252340, 0.658705, 7.784410, 3.877121, 7.587152]
fourier: [[8.305201, 9.020617, 10.001682, 10.468592, 60.989855], [9.980475, 10.947094, 12.312302, 13.072776, 67.181519], [0.940995, 1.017341, 1.229154, 1.369410, 32.951800], [35.038915, 38.347755, 42.950457, 45.506315, 238.034191], [10.270307, 11.234117, 12.578891, 13.297559, 88.044986], [120.706891, 132.279017, 148.438297, 157.483468, 697.370195], [60.371526, 66.066066, 73.935016, 78.326445, 402.226645], [117.651971, 128.933021, 144.690682, 153.491864, 689.180301]]
input_correlations: [[-0.999231, -0.998938, 0.000000, 0.000000, -0.999042, 0.000000, 0.000000, -0.999735], [-0.999956, -0.999977, 0.000000, 0.000000, -0.999984, 0.000000, 0.000000, -0.999666], [-0.981730, -0.982905, 0.000000, 0.000000, -0.982601, 0.000000, 0.000000, -0.978521], [-0.999998, -0.999968, 0.000000, 0.000000, -0.999976, 0.000000, 0.000000, -0.999863], [-0.999983, -0.999905, 0.000000, 0.000000, -0.999944, 0.000000, 0.000000, -0.999942], [0.999990, 0.999988, 0.000000, 0.000000, 0.999992, 0.000000, 0.000000, 0.999783], [-0.999992, -0.999954, 0.000000, 0.000000, -0.999961, 0.000000, 0.000000, -0.999892], [0.999991, 0.999986, 0.000000, 0.000000, 0.999993, 0.000000, 0.000000, 0.999787]]
pre_activation_mean: [-0.677665, -0.746461, -0.366131, -2.644825, -0.978278, 7.748558, -4.469185, 7.657559]
pre_activation_std: [0.522544, 0.645644, 0.065876, 2.252340, 0.658705, 7.784410, 3.877121, 7.587152]
### 12
mean: [-4.990959]
std: [5.196681]
fourier: [[80.125636, 87.907623, 98.943242, 105.424007, 449.186264]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999998, 0.000000, -0.999995]]
pre_activation_mean: [-4.990959]
pre_activation_std: [5.196681]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"epoch": 8, "global_epoch": 10, "train_loss": 0.21735157817602158, "train_acc": 0.945, "val_loss": 0.34968045353889465, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.22189560532569885, "train_acc": 0.94, "val_loss": 0.3461763858795166, "val_acc": 0.86}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.7204413414001465, "final_val_loss": 0.6402900815010071, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.5288600921630859, "final_val_loss": 0.3461763858795166, "initial_val_acc": 0.46, "final_val_acc": 0.86, "best_val_acc": 0.86, "best_epoch": 4}, "improvement": 0.39999999999999997, "first_improvement_epoch": 1}} |
56 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.48, "improved_accuracy": 0.76, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8264, "learning_rate": 0.06745739206568764, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.919395, 1.279896, 0.000000, 1.435678, 1.021349]
std: [0.000000, 0.000000, 0.000000, 2.236122, 3.205799, 0.000000, 3.345850, 2.487967]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [33.318649, 35.344914, 36.136965, 45.910735, 82.745542], [48.573919, 50.223347, 51.761279, 65.742413, 115.190613], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [49.890910, 53.332895, 54.021604, 68.509556, 129.211006], [37.112102, 39.374806, 40.237882, 51.089251, 91.921395]]
input_correlations: [[-0.756582, -0.590531, -0.115591, 0.038212, 0.414301, 0.000000, 0.000000, 0.000000], [-0.528475, -0.326091, -0.035262, 0.109347, 0.732903, 0.000000, 0.000000, 0.000000], [-0.565431, -0.692242, -0.648259, -0.475123, -0.501808, 0.000000, 0.000000, 0.000000], [-0.179696, -0.432783, 0.250638, -0.231678, 0.807537, 0.000000, 0.000000, 0.000000], [-0.541378, -0.506780, -0.315267, -0.590504, -0.713192, 0.000000, 0.000000, 0.000000], [0.843589, 0.723699, 0.459376, 0.316777, 0.257964, 0.000000, 0.000000, 0.000000], [-0.512580, 0.339756, 0.022958, 0.296541, -0.702841, 0.000000, 0.000000, 0.000000], [-0.809427, 0.038667, -0.641807, 0.320980, -0.140331, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.063688, 0.308435, -2.564209, -0.416893, -3.428299, 3.352178, -0.589042, -1.273417]
pre_activation_std: [2.862024, 2.341813, 1.729918, 1.488950, 2.209950, 2.135814, 0.967013, 1.637063]
### 2
mean: [-3.720269, 1.943060, -1.052854, -0.849777, -0.179933, 1.709504, -1.778061, 1.594074]
std: [2.069107, 1.307566, 1.225142, 1.572043, 1.321331, 1.508648, 0.876632, 2.542186]
fourier: [[38.649510, 39.999657, 41.230556, 43.618937, 334.824179], [20.746431, 21.878726, 22.957894, 25.076336, 174.875357], [20.820155, 21.505804, 22.121400, 22.280859, 94.756832], [24.751449, 26.190481, 28.507412, 29.680768, 76.479960], [18.420912, 18.898435, 21.021697, 21.318899, 28.158617], [24.440266, 26.109389, 26.262394, 27.167316, 153.855382], [14.431623, 16.079525, 17.107925, 17.569107, 160.025446], [40.446581, 42.513339, 42.821158, 47.978481, 143.466614]]
input_correlations: [[-0.580589, -0.664166, 0.428415, -0.656521, 0.000000, -0.682993, 0.023542, -0.185578], [-0.417681, -0.347376, -0.349702, -0.185023, 0.000000, 0.945479, 0.321910, 0.118211], [-0.946635, -0.982655, 0.214342, -0.798586, 0.000000, -0.041637, 0.222913, -0.122953], [-0.957288, -0.969394, 0.151943, -0.826038, 0.000000, 0.156141, 0.122109, -0.265488], [0.939258, 0.948226, -0.026265, 0.780315, 0.000000, -0.361999, -0.334924, 0.043096], [0.967237, 0.972697, -0.218787, 0.854188, 0.000000, 0.014888, -0.169549, 0.079531], [-0.331606, -0.446718, 0.452941, -0.503088, 0.000000, -0.818618, -0.111791, -0.324748], [0.941534, 0.992861, -0.180810, 0.878211, 0.000000, -0.027596, -0.277661, 0.102518]]
pre_activation_mean: [-3.720269, 1.943060, -1.052854, -0.849777, -0.179933, 1.709504, -1.778061, 1.594074]
pre_activation_std: [2.069107, 1.307566, 1.225142, 1.572043, 1.321331, 1.508648, 0.876632, 2.542186]
### 4
mean: [-0.902381, -0.433433, -1.429548, -2.250671, -1.533574, -0.852900, 1.412083, -0.386833]
std: [0.938221, 0.188683, 1.645633, 1.352177, 1.189388, 0.354732, 2.745095, 2.943199]
fourier: [[14.033068, 14.104274, 14.808855, 19.925063, 81.214324], [2.999662, 3.040543, 3.190076, 3.536993, 39.008960], [25.593393, 27.590264, 28.262033, 29.969318, 128.659355], [22.504405, 23.179912, 27.568961, 28.469382, 202.560421], [18.872415, 19.846660, 20.732928, 21.582662, 138.021704], [5.520431, 6.328746, 6.836854, 7.063752, 76.760973], [41.902142, 43.555492, 46.225387, 52.866394, 127.087495], [37.879105, 41.767031, 46.048091, 46.950302, 64.190409]]
input_correlations: [[0.000000, 0.483229, 0.000000, 0.268498, -0.987725, -0.966203, 0.000000, -0.958483], [0.000000, -0.956038, 0.000000, -0.646755, 0.469385, 0.348650, 0.000000, 0.426439], [0.000000, 0.223734, 0.000000, 0.083647, -0.974127, -0.995727, 0.000000, -0.985040], [0.000000, -0.176985, 0.000000, -0.103028, -0.806094, -0.901642, 0.000000, -0.883154], [0.000000, 0.194733, 0.000000, 0.064492, -0.966275, -0.996423, 0.000000, -0.979746], [0.000000, -0.480428, 0.000000, -0.440014, -0.586039, -0.672451, 0.000000, -0.588472], [0.000000, -0.433794, 0.000000, -0.253438, 0.971244, 0.977572, 0.000000, 0.988155], [0.000000, -0.668926, 0.000000, -0.396934, 0.921956, 0.882701, 0.000000, 0.909441]]
pre_activation_mean: [-0.902381, -0.433433, -1.429548, -2.250671, -1.533574, -0.852900, 1.412083, -0.386833]
pre_activation_std: [0.938221, 0.188683, 1.645633, 1.352177, 1.189388, 0.354732, 2.745095, 2.943199]
### 6
mean: [-0.995811, -0.147669, -0.818167, 0.250138, -1.170587, -0.185558, 2.012898, 0.018772]
std: [1.285072, 0.652796, 1.681223, 0.853134, 1.960635, 0.289791, 4.069229, 0.558284]
fourier: [[19.319208, 20.600243, 20.758645, 25.785134, 89.622998], [10.282816, 10.463240, 11.258643, 12.311030, 13.290232], [26.278694, 26.993797, 28.814522, 31.940591, 73.635044], [12.487332, 13.367902, 14.304841, 18.033682, 22.512421], [29.426252, 30.804032, 31.636643, 39.765905, 105.352835], [4.615389, 4.664030, 5.084576, 5.338842, 16.700176], [61.184279, 65.391288, 65.737245, 81.531725, 181.160795], [7.944147, 7.964580, 8.491713, 9.931268, 11.872852]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.993500, -0.994478], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999565, 0.969232], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999888, -0.972696], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.941887, -0.992399], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.989284, -0.997360], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.997381, -0.957782], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.993960, 0.994038], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.904621, 0.975659]]
pre_activation_mean: [-0.995811, -0.147669, -0.818167, 0.250138, -1.170587, -0.185558, 2.012898, 0.018772]
pre_activation_std: [1.285072, 0.652796, 1.681223, 0.853134, 1.960635, 0.289791, 4.069229, 0.558284]
### 8
mean: [1.701485, -0.125951, 1.442027, 0.093141, -1.083195, -0.937243, -0.746840, 1.959793]
std: [4.227276, 0.230703, 3.898675, 0.120850, 1.384705, 1.709725, 1.237643, 4.138466]
fourier: [[63.527977, 67.385388, 69.018112, 86.083529, 153.133637], [3.500075, 3.578711, 3.641249, 4.611162, 11.335584], [58.594229, 62.396752, 63.498815, 78.983902, 129.782463], [1.816450, 1.925477, 1.967133, 2.096056, 8.382712], [20.850054, 21.899299, 22.037820, 27.497117, 97.487522], [25.620679, 26.882964, 27.413063, 34.433981, 84.351875], [18.497461, 19.920946, 20.265260, 24.596981, 67.215620], [62.453035, 66.440732, 67.496413, 83.744777, 176.381409]]
input_correlations: [[0.000000, 0.988807, -0.365797, -0.773751, 0.000000, 0.000000, 0.999529, 0.975185], [0.000000, -0.977533, 0.331114, 0.757432, 0.000000, 0.000000, -0.978089, -0.992491], [0.000000, 0.988419, -0.371913, -0.768067, 0.000000, 0.000000, 0.999789, 0.974444], [0.000000, 0.101838, -0.771499, 0.005901, 0.000000, 0.000000, 0.223058, 0.034823], [0.000000, -0.990948, 0.380726, 0.743156, 0.000000, 0.000000, -0.999450, -0.980768], [0.000000, -0.992430, 0.359945, 0.759355, 0.000000, 0.000000, -0.999200, -0.982412], [0.000000, -0.988990, 0.381129, 0.745744, 0.000000, 0.000000, -0.999740, -0.972921], [0.000000, 0.987738, -0.378965, -0.766412, 0.000000, 0.000000, 0.999835, 0.973294]]
pre_activation_mean: [1.701485, -0.125951, 1.442027, 0.093141, -1.083195, -0.937243, -0.746840, 1.959793]
pre_activation_std: [4.227276, 0.230703, 3.898675, 0.120850, 1.384705, 1.709725, 1.237643, 4.138466]
### 10
mean: [-1.966280, -0.588009, -0.526683, 0.758108, 1.009382, -1.135145, 1.362541, 0.834289]
std: [3.912715, 1.074594, 0.722055, 2.304607, 3.316272, 1.802230, 3.377798, 2.567190]
fourier: [[58.512992, 62.423266, 63.580254, 79.728414, 176.965197], [15.998362, 17.179940, 17.341258, 21.924513, 52.920818], [10.795039, 11.585175, 11.679686, 14.813553, 47.401511], [34.539756, 36.751838, 37.456564, 46.938300, 68.229680], [49.327752, 52.453986, 53.452683, 68.062103, 90.844405], [26.974690, 28.753716, 29.266730, 36.699728, 102.163081], [50.532069, 54.019532, 54.831946, 68.814559, 122.628708], [38.401430, 40.964864, 41.703883, 52.331555, 75.086024]]
input_correlations: [[-0.999875, 0.005312, -0.999767, -0.181050, 0.000000, 0.000000, 0.000000, -0.999750], [-0.999920, 0.002812, -0.999938, -0.172962, 0.000000, 0.000000, 0.000000, -0.999426], [-0.999741, 0.002246, -0.999659, -0.182783, 0.000000, 0.000000, 0.000000, -0.999217], [0.999834, -0.006631, 0.999711, 0.182543, 0.000000, 0.000000, 0.000000, 0.999797], [0.999875, -0.011506, 0.999951, 0.153660, 0.000000, 0.000000, 0.000000, 0.998658], [-0.999864, 0.005192, -0.999769, -0.180448, 0.000000, 0.000000, 0.000000, -0.999751], [0.999825, -0.004440, 0.999710, 0.185049, 0.000000, 0.000000, 0.000000, 0.999800], [0.999869, -0.005995, 0.999754, 0.182086, 0.000000, 0.000000, 0.000000, 0.999761]]
pre_activation_mean: [-1.966280, -0.588009, -0.526683, 0.758108, 1.009382, -1.135145, 1.362541, 0.834289]
pre_activation_std: [3.912715, 1.074594, 0.722055, 2.304607, 3.316272, 1.802230, 3.377798, 2.567190]
### 12
mean: [-0.776991]
std: [2.564986]
fourier: [[38.140370, 40.549048, 41.436439, 52.598805, 69.929222]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999985, -0.999657, 0.000000, -0.999608, -0.999977]]
pre_activation_mean: [-0.776991]
pre_activation_std: [2.564986]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.919395, 1.279896, 0.000000, 1.435678, 1.021349]
std: [0.000000, 0.000000, 0.000000, 2.236122, 3.205799, 0.000000, 3.345850, 2.487967]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [33.318649, 35.344914, 36.136965, 45.910735, 82.745542], [48.573919, 50.223347, 51.761279, 65.742413, 115.190613], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [49.890910, 53.332895, 54.021604, 68.509556, 129.211006], [37.112102, 39.374806, 40.237882, 51.089251, 91.921395]]
input_correlations: [[-0.756582, -0.590531, -0.115591, 0.038212, 0.414301, 0.000000, 0.000000, 0.000000], [-0.528475, -0.326091, -0.035262, 0.109347, 0.732903, 0.000000, 0.000000, 0.000000], [-0.565431, -0.692242, -0.648259, -0.475123, -0.501808, 0.000000, 0.000000, 0.000000], [-0.179696, -0.432783, 0.250638, -0.231678, 0.807537, 0.000000, 0.000000, 0.000000], [-0.541378, -0.506780, -0.315267, -0.590504, -0.713192, 0.000000, 0.000000, 0.000000], [0.843589, 0.723699, 0.459376, 0.316777, 0.257964, 0.000000, 0.000000, 0.000000], [-0.512580, 0.339756, 0.022958, 0.296541, -0.702841, 0.000000, 0.000000, 0.000000], [-0.809427, 0.038667, -0.641807, 0.320980, -0.140331, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.063688, 0.308435, -2.564209, -0.416893, -3.428299, 3.352178, -0.589042, -1.273417]
pre_activation_std: [2.862024, 2.341813, 1.729918, 1.488950, 2.209950, 2.135814, 0.967013, 1.637063]
### 2
mean: [-3.720269, 1.943060, -1.052854, -0.849777, -0.179933, 1.709504, -1.778061, 1.594074]
std: [2.069107, 1.307566, 1.225142, 1.572043, 1.321331, 1.508648, 0.876632, 2.542186]
fourier: [[38.649510, 39.999657, 41.230556, 43.618937, 334.824179], [20.746431, 21.878726, 22.957894, 25.076336, 174.875357], [20.820155, 21.505804, 22.121400, 22.280859, 94.756832], [24.751449, 26.190481, 28.507412, 29.680768, 76.479960], [18.420912, 18.898435, 21.021697, 21.318899, 28.158617], [24.440266, 26.109389, 26.262394, 27.167316, 153.855382], [14.431623, 16.079525, 17.107925, 17.569107, 160.025446], [40.446581, 42.513339, 42.821158, 47.978481, 143.466614]]
input_correlations: [[-0.580589, -0.664166, 0.428415, -0.656521, 0.000000, -0.682993, 0.023542, -0.185578], [-0.417681, -0.347376, -0.349702, -0.185023, 0.000000, 0.945479, 0.321910, 0.118211], [-0.946635, -0.982655, 0.214342, -0.798586, 0.000000, -0.041637, 0.222913, -0.122953], [-0.957288, -0.969394, 0.151943, -0.826038, 0.000000, 0.156141, 0.122109, -0.265488], [0.939258, 0.948226, -0.026265, 0.780315, 0.000000, -0.361999, -0.334924, 0.043096], [0.967237, 0.972697, -0.218787, 0.854188, 0.000000, 0.014888, -0.169549, 0.079531], [-0.331606, -0.446718, 0.452941, -0.503088, 0.000000, -0.818618, -0.111791, -0.324748], [0.941534, 0.992861, -0.180810, 0.878211, 0.000000, -0.027596, -0.277661, 0.102518]]
pre_activation_mean: [-3.720269, 1.943060, -1.052854, -0.849777, -0.179933, 1.709504, -1.778061, 1.594074]
pre_activation_std: [2.069107, 1.307566, 1.225142, 1.572043, 1.321331, 1.508648, 0.876632, 2.542186]
### 4
mean: [-0.902381, -0.433433, -1.429548, -2.250671, -1.533574, -0.852900, 1.412083, -0.386833]
std: [0.938221, 0.188683, 1.645633, 1.352177, 1.189388, 0.354732, 2.745095, 2.943199]
fourier: [[14.033068, 14.104274, 14.808855, 19.925063, 81.214324], [2.999662, 3.040543, 3.190076, 3.536993, 39.008960], [25.593393, 27.590264, 28.262033, 29.969318, 128.659355], [22.504405, 23.179912, 27.568961, 28.469382, 202.560421], [18.872415, 19.846660, 20.732928, 21.582662, 138.021704], [5.520431, 6.328746, 6.836854, 7.063752, 76.760973], [41.902142, 43.555492, 46.225387, 52.866394, 127.087495], [37.879105, 41.767031, 46.048091, 46.950302, 64.190409]]
input_correlations: [[0.000000, 0.483229, 0.000000, 0.268498, -0.987725, -0.966203, 0.000000, -0.958483], [0.000000, -0.956038, 0.000000, -0.646755, 0.469385, 0.348650, 0.000000, 0.426439], [0.000000, 0.223734, 0.000000, 0.083647, -0.974127, -0.995727, 0.000000, -0.985040], [0.000000, -0.176985, 0.000000, -0.103028, -0.806094, -0.901642, 0.000000, -0.883154], [0.000000, 0.194733, 0.000000, 0.064492, -0.966275, -0.996423, 0.000000, -0.979746], [0.000000, -0.480428, 0.000000, -0.440014, -0.586039, -0.672451, 0.000000, -0.588472], [0.000000, -0.433794, 0.000000, -0.253438, 0.971244, 0.977572, 0.000000, 0.988155], [0.000000, -0.668926, 0.000000, -0.396934, 0.921956, 0.882701, 0.000000, 0.909441]]
pre_activation_mean: [-0.902381, -0.433433, -1.429548, -2.250671, -1.533574, -0.852900, 1.412083, -0.386833]
pre_activation_std: [0.938221, 0.188683, 1.645633, 1.352177, 1.189388, 0.354732, 2.745095, 2.943199]
### 6
mean: [-0.995811, -0.147669, -0.818167, 0.250138, -1.170587, -0.185558, 2.012898, 0.018772]
std: [1.285072, 0.652796, 1.681223, 0.853134, 1.960635, 0.289791, 4.069229, 0.558284]
fourier: [[19.319208, 20.600243, 20.758645, 25.785134, 89.622998], [10.282816, 10.463240, 11.258643, 12.311030, 13.290232], [26.278694, 26.993797, 28.814522, 31.940591, 73.635044], [12.487332, 13.367902, 14.304841, 18.033682, 22.512421], [29.426252, 30.804032, 31.636643, 39.765905, 105.352835], [4.615389, 4.664030, 5.084576, 5.338842, 16.700176], [61.184279, 65.391288, 65.737245, 81.531725, 181.160795], [7.944147, 7.964580, 8.491713, 9.931268, 11.872852]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.993500, -0.994478], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.999565, 0.969232], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.999888, -0.972696], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.941887, -0.992399], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.989284, -0.997360], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -0.997381, -0.957782], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.993960, 0.994038], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.904621, 0.975659]]
pre_activation_mean: [-0.995811, -0.147669, -0.818167, 0.250138, -1.170587, -0.185558, 2.012898, 0.018772]
pre_activation_std: [1.285072, 0.652796, 1.681223, 0.853134, 1.960635, 0.289791, 4.069229, 0.558284]
### 8
mean: [1.701485, -0.125951, 1.442027, 0.093141, -1.083195, -0.937243, -0.746840, 1.959793]
std: [4.227276, 0.230703, 3.898675, 0.120850, 1.384705, 1.709725, 1.237643, 4.138466]
fourier: [[63.527977, 67.385388, 69.018112, 86.083529, 153.133637], [3.500075, 3.578711, 3.641249, 4.611162, 11.335584], [58.594229, 62.396752, 63.498815, 78.983902, 129.782463], [1.816450, 1.925477, 1.967133, 2.096056, 8.382712], [20.850054, 21.899299, 22.037820, 27.497117, 97.487522], [25.620679, 26.882964, 27.413063, 34.433981, 84.351875], [18.497461, 19.920946, 20.265260, 24.596981, 67.215620], [62.453035, 66.440732, 67.496413, 83.744777, 176.381409]]
input_correlations: [[0.000000, 0.988807, -0.365797, -0.773751, 0.000000, 0.000000, 0.999529, 0.975185], [0.000000, -0.977533, 0.331114, 0.757432, 0.000000, 0.000000, -0.978089, -0.992491], [0.000000, 0.988419, -0.371913, -0.768067, 0.000000, 0.000000, 0.999789, 0.974444], [0.000000, 0.101838, -0.771499, 0.005901, 0.000000, 0.000000, 0.223058, 0.034823], [0.000000, -0.990948, 0.380726, 0.743156, 0.000000, 0.000000, -0.999450, -0.980768], [0.000000, -0.992430, 0.359945, 0.759355, 0.000000, 0.000000, -0.999200, -0.982412], [0.000000, -0.988990, 0.381129, 0.745744, 0.000000, 0.000000, -0.999740, -0.972921], [0.000000, 0.987738, -0.378965, -0.766412, 0.000000, 0.000000, 0.999835, 0.973294]]
pre_activation_mean: [1.701485, -0.125951, 1.442027, 0.093141, -1.083195, -0.937243, -0.746840, 1.959793]
pre_activation_std: [4.227276, 0.230703, 3.898675, 0.120850, 1.384705, 1.709725, 1.237643, 4.138466]
### 10
mean: [-1.966280, -0.588009, -0.526683, 0.758108, 1.009382, -1.135145, 1.362541, 0.834289]
std: [3.912715, 1.074594, 0.722055, 2.304607, 3.316272, 1.802230, 3.377798, 2.567190]
fourier: [[58.512992, 62.423266, 63.580254, 79.728414, 176.965197], [15.998362, 17.179940, 17.341258, 21.924513, 52.920818], [10.795039, 11.585175, 11.679686, 14.813553, 47.401511], [34.539756, 36.751838, 37.456564, 46.938300, 68.229680], [49.327752, 52.453986, 53.452683, 68.062103, 90.844405], [26.974690, 28.753716, 29.266730, 36.699728, 102.163081], [50.532069, 54.019532, 54.831946, 68.814559, 122.628708], [38.401430, 40.964864, 41.703883, 52.331555, 75.086024]]
input_correlations: [[-0.999875, 0.005312, -0.999767, -0.181050, 0.000000, 0.000000, 0.000000, -0.999750], [-0.999920, 0.002812, -0.999938, -0.172962, 0.000000, 0.000000, 0.000000, -0.999426], [-0.999741, 0.002246, -0.999659, -0.182783, 0.000000, 0.000000, 0.000000, -0.999217], [0.999834, -0.006631, 0.999711, 0.182543, 0.000000, 0.000000, 0.000000, 0.999797], [0.999875, -0.011506, 0.999951, 0.153660, 0.000000, 0.000000, 0.000000, 0.998658], [-0.999864, 0.005192, -0.999769, -0.180448, 0.000000, 0.000000, 0.000000, -0.999751], [0.999825, -0.004440, 0.999710, 0.185049, 0.000000, 0.000000, 0.000000, 0.999800], [0.999869, -0.005995, 0.999754, 0.182086, 0.000000, 0.000000, 0.000000, 0.999761]]
pre_activation_mean: [-1.966280, -0.588009, -0.526683, 0.758108, 1.009382, -1.135145, 1.362541, 0.834289]
pre_activation_std: [3.912715, 1.074594, 0.722055, 2.304607, 3.316272, 1.802230, 3.377798, 2.567190]
### 12
mean: [-0.776991]
std: [2.564986]
fourier: [[38.140370, 40.549048, 41.436439, 52.598805, 69.929222]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999985, -0.999657, 0.000000, -0.999608, -0.999977]]
pre_activation_mean: [-0.776991]
pre_activation_std: [2.564986]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.7565816368562179, -0.5905310359315609, -0.11559059923824604, 0.03821168591942583, 0.41430074947877077, 0.0, 0.0, 0.0], "pre_activation_mean": -1.0636876821517944, "pre_activation_std": 2.8620235919952393}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.5284748758940263, -0.32609115296933777, -0.0352620643245987, 0.10934693546852634, 0.7329029431065277, 0.0, 0.0, 0.0], "pre_activation_mean": 0.3084346652030945, "pre_activation_std": 2.341813087463379}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.5654312021429958, -0.6922423608760271, -0.6482593128003179, -0.47512336503181635, -0.5018081067661545, 0.0, 0.0, 0.0], "pre_activation_mean": -2.564209222793579, "pre_activation_std": 1.7299184799194336}, "3": {"mean": 0.919394850730896, 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3.352177858352661, "pre_activation_std": 2.1358139514923096}, "6": {"mean": 1.4356778860092163, "std": 3.3458499908447266, "fourier": [49.890910230675615, 53.33289545862688, 54.02160412255742, 68.50955579113243, 129.21100588142872], "input_correlations": [-0.5125798062587609, 0.3397562125390626, 0.022958479336571785, 0.29654104700809475, -0.702841056016577, 0.0, 0.0, 0.0], "pre_activation_mean": -0.5890423059463501, "pre_activation_std": 0.9670127034187317}, "7": {"mean": 1.0213488340377808, "std": 2.487967014312744, "fourier": [37.11210166789484, 39.37480597657434, 40.23788239968539, 51.0892508782456, 91.92139485478401], "input_correlations": [-0.8094266050880647, 0.038667477707719666, -0.6418073316391001, 0.32098013836505246, -0.14033097596111435, 0.0, 0.0, 0.0], "pre_activation_mean": -1.273417353630066, "pre_activation_std": 1.6370632648468018}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -3.720268726348877, "std": 2.0691072940826416, "fourier": [38.649509602962574, 39.99965714070034, 41.23055629247507, 43.618937390688494, 334.82417941093445], "input_correlations": [-0.5805889982388084, -0.664165792720177, 0.428415146114745, -0.6565205954489989, 0.0, -0.6829931060723373, 0.023541771633260915, -0.1855784452633109], "pre_activation_mean": -3.720268726348877, "pre_activation_std": 2.0691072940826416}, "1": {"mean": 1.9430596828460693, "std": 1.307565689086914, "fourier": [20.746431037368673, 21.87872590427938, 22.9578940841959, 25.07633633269616, 174.87535712122917], "input_correlations": [-0.417680581685244, -0.347376392652998, -0.34970201672419376, -0.18502272406952736, 0.0, 0.9454794484058707, 0.3219102506405521, 0.11821079731838167], "pre_activation_mean": 1.9430596828460693, "pre_activation_std": 1.307565689086914}, "2": {"mean": -1.0528537034988403, "std": 1.2251418828964233, 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"final_val_loss": 0.6960969567298889, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.7308866381645203, "final_val_loss": 0.4828397035598755, "initial_val_acc": 0.48, "final_val_acc": 0.76, "best_val_acc": 0.76, "best_epoch": 8}, "improvement": 0.28, "first_improvement_epoch": 1}} |
57 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.46, "improved_accuracy": 0.9, "improvement": 0.44, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7048, "learning_rate": 0.04198946419763812, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.192480, 1.519095, 0.001956, 0.000000, 1.843626]
std: [0.239278, 1.198469, 0.008842, 0.000000, 1.437305]
fourier: [[3.766503, 3.863090, 4.068260, 4.431846, 17.323215], [19.450851, 19.650343, 21.737357, 22.022871, 136.718582], [0.141315, 0.145900, 0.146248, 0.158068, 0.176008], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [23.414413, 23.746792, 25.920079, 26.391235, 165.926389]]
input_correlations: [[-0.369710, -0.858997, -0.594951, -0.530618, -0.206283, 0.000000, 0.000000, 0.000000], [0.659813, 0.774405, 0.322566, 0.305375, -0.305586, 0.000000, 0.000000, 0.000000], [-0.648719, -0.561070, -0.587278, -0.564064, -0.493114, 0.000000, 0.000000, 0.000000], [-0.629257, -0.003007, -0.632906, 0.642510, -0.095116, 0.000000, 0.000000, 0.000000], [-0.172369, -0.779117, -0.709397, -0.417728, -0.098834, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.707604, 2.105325, -2.066168, 0.025837, -2.188510]
pre_activation_std: [1.166765, 1.834317, 1.240950, 0.944481, 1.686544]
### 2
mean: [-0.783251, 1.745045, 0.505269, 1.142926, -0.603339]
std: [0.251469, 1.296381, 0.264407, 0.863305, 0.256188]
fourier: [[4.084806, 4.151448, 4.986571, 5.403397, 70.492575], [21.200788, 21.586060, 22.872539, 23.839154, 157.054066], [4.143590, 4.730301, 5.382048, 5.795616, 45.474227], [13.724883, 14.393054, 15.353911, 15.830317, 102.863294], [4.140988, 4.213441, 4.233110, 4.454133, 54.300488]]
input_correlations: [[0.273709, -0.554281, 0.000000, -0.793051, 0.236959, 0.000000, 0.000000, 0.000000], [-0.301566, 0.993259, 0.000000, -0.172429, -0.258454, 0.000000, 0.000000, 0.000000], [-0.334514, 0.927383, 0.000000, 0.316690, -0.288895, 0.000000, 0.000000, 0.000000], [-0.302162, 0.990577, 0.000000, -0.192000, -0.265818, 0.000000, 0.000000, 0.000000], [0.212011, -0.923835, 0.000000, 0.431999, 0.130362, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.783251, 1.745045, 0.505269, 1.142926, -0.603339]
pre_activation_std: [0.251469, 1.296381, 0.264407, 0.863305, 0.256188]
### 4
mean: [1.338380, -0.288221, 1.552345, -0.007732, 1.290824]
std: [0.953706, 0.682220, 0.831893, 0.029131, 1.044695]
fourier: [[14.745575, 15.966531, 17.048134, 17.151651, 120.454181], [10.687188, 11.420687, 12.188384, 12.318022, 25.939881], [13.850323, 14.243423, 14.692564, 15.445526, 139.711018], [0.485809, 0.503799, 0.574169, 0.583909, 0.695850], [17.342454, 17.448102, 18.590138, 19.217272, 116.174114]]
input_correlations: [[0.000000, 0.998533, 0.852375, 0.999354, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999126, -0.858822, -0.999711, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.998717, 0.902293, 0.997507, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.960005, -0.977377, -0.954518, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999811, 0.887816, 0.999278, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.338380, -0.288221, 1.552345, -0.007732, 1.290824]
pre_activation_std: [0.953706, 0.682220, 0.831893, 0.029131, 1.044695]
### 6
mean: [0.099677, 1.511569, -0.136674, -0.461353, 1.838982]
std: [0.345191, 1.208429, 0.093018, 0.035261, 1.443415]
fourier: [[5.506410, 5.535356, 6.566099, 6.616258, 8.970893], [19.467025, 19.926190, 21.743184, 22.220878, 136.041242], [1.452952, 1.470065, 1.742128, 1.766975, 12.300685], [0.533979, 0.605183, 0.642459, 0.711618, 41.521786], [23.412443, 23.911357, 25.895987, 26.507920, 165.508415]]
input_correlations: [[-0.953339, 0.853749, -0.953902, 0.825616, -0.952553, 0.000000, 0.000000, 0.000000], [0.998399, -0.679307, 0.998286, -0.721728, 0.999150, 0.000000, 0.000000, 0.000000], [0.945100, -0.861991, 0.949725, -0.837575, 0.946736, 0.000000, 0.000000, 0.000000], [-0.664729, -0.071524, -0.689083, 0.240636, -0.689256, 0.000000, 0.000000, 0.000000], [0.998488, -0.670935, 0.998609, -0.717342, 0.999517, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.099677, 1.511569, -0.136674, -0.461353, 1.838982]
pre_activation_std: [0.345191, 1.208429, 0.093018, 0.035261, 1.443415]
### 8
mean: [-2.102989]
std: [1.619130]
fourier: [[25.728816, 25.864089, 29.870444, 29.953289, 189.269020]]
input_correlations: [[0.790437, -0.998538, -0.522805, 0.000000, -0.998298, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.102989]
pre_activation_std: [1.619130]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.192480, 1.519095, 0.001956, 0.000000, 1.843626]
std: [0.239278, 1.198469, 0.008842, 0.000000, 1.437305]
fourier: [[3.766503, 3.863090, 4.068260, 4.431846, 17.323215], [19.450851, 19.650343, 21.737357, 22.022871, 136.718582], [0.141315, 0.145900, 0.146248, 0.158068, 0.176008], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [23.414413, 23.746792, 25.920079, 26.391235, 165.926389]]
input_correlations: [[-0.369710, -0.858997, -0.594951, -0.530618, -0.206283, 0.000000, 0.000000, 0.000000], [0.659813, 0.774405, 0.322566, 0.305375, -0.305586, 0.000000, 0.000000, 0.000000], [-0.648719, -0.561070, -0.587278, -0.564064, -0.493114, 0.000000, 0.000000, 0.000000], [-0.629257, -0.003007, -0.632906, 0.642510, -0.095116, 0.000000, 0.000000, 0.000000], [-0.172369, -0.779117, -0.709397, -0.417728, -0.098834, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.707604, 2.105325, -2.066168, 0.025837, -2.188510]
pre_activation_std: [1.166765, 1.834317, 1.240950, 0.944481, 1.686544]
### 2
mean: [-0.783251, 1.745045, 0.505269, 1.142926, -0.603339]
std: [0.251469, 1.296381, 0.264407, 0.863305, 0.256188]
fourier: [[4.084806, 4.151448, 4.986571, 5.403397, 70.492575], [21.200788, 21.586060, 22.872539, 23.839154, 157.054066], [4.143590, 4.730301, 5.382048, 5.795616, 45.474227], [13.724883, 14.393054, 15.353911, 15.830317, 102.863294], [4.140988, 4.213441, 4.233110, 4.454133, 54.300488]]
input_correlations: [[0.273709, -0.554281, 0.000000, -0.793051, 0.236959, 0.000000, 0.000000, 0.000000], [-0.301566, 0.993259, 0.000000, -0.172429, -0.258454, 0.000000, 0.000000, 0.000000], [-0.334514, 0.927383, 0.000000, 0.316690, -0.288895, 0.000000, 0.000000, 0.000000], [-0.302162, 0.990577, 0.000000, -0.192000, -0.265818, 0.000000, 0.000000, 0.000000], [0.212011, -0.923835, 0.000000, 0.431999, 0.130362, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.783251, 1.745045, 0.505269, 1.142926, -0.603339]
pre_activation_std: [0.251469, 1.296381, 0.264407, 0.863305, 0.256188]
### 4
mean: [1.338380, -0.288221, 1.552345, -0.007732, 1.290824]
std: [0.953706, 0.682220, 0.831893, 0.029131, 1.044695]
fourier: [[14.745575, 15.966531, 17.048134, 17.151651, 120.454181], [10.687188, 11.420687, 12.188384, 12.318022, 25.939881], [13.850323, 14.243423, 14.692564, 15.445526, 139.711018], [0.485809, 0.503799, 0.574169, 0.583909, 0.695850], [17.342454, 17.448102, 18.590138, 19.217272, 116.174114]]
input_correlations: [[0.000000, 0.998533, 0.852375, 0.999354, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999126, -0.858822, -0.999711, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.998717, 0.902293, 0.997507, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.960005, -0.977377, -0.954518, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999811, 0.887816, 0.999278, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.338380, -0.288221, 1.552345, -0.007732, 1.290824]
pre_activation_std: [0.953706, 0.682220, 0.831893, 0.029131, 1.044695]
### 6
mean: [0.099677, 1.511569, -0.136674, -0.461353, 1.838982]
std: [0.345191, 1.208429, 0.093018, 0.035261, 1.443415]
fourier: [[5.506410, 5.535356, 6.566099, 6.616258, 8.970893], [19.467025, 19.926190, 21.743184, 22.220878, 136.041242], [1.452952, 1.470065, 1.742128, 1.766975, 12.300685], [0.533979, 0.605183, 0.642459, 0.711618, 41.521786], [23.412443, 23.911357, 25.895987, 26.507920, 165.508415]]
input_correlations: [[-0.953339, 0.853749, -0.953902, 0.825616, -0.952553, 0.000000, 0.000000, 0.000000], [0.998399, -0.679307, 0.998286, -0.721728, 0.999150, 0.000000, 0.000000, 0.000000], [0.945100, -0.861991, 0.949725, -0.837575, 0.946736, 0.000000, 0.000000, 0.000000], [-0.664729, -0.071524, -0.689083, 0.240636, -0.689256, 0.000000, 0.000000, 0.000000], [0.998488, -0.670935, 0.998609, -0.717342, 0.999517, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.099677, 1.511569, -0.136674, -0.461353, 1.838982]
pre_activation_std: [0.345191, 1.208429, 0.093018, 0.035261, 1.443415]
### 8
mean: [-2.102989]
std: [1.619130]
fourier: [[25.728816, 25.864089, 29.870444, 29.953289, 189.269020]]
input_correlations: [[0.790437, -0.998538, -0.522805, 0.000000, -0.998298, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.102989]
pre_activation_std: [1.619130]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.1924801468849182, "std": 0.2392776906490326, "fourier": [3.766503083941585, 3.8630901554223103, 4.068260195497202, 4.43184630434476, 17.32321534305811], "input_correlations": [-0.36970959373294066, -0.8589970150438083, -0.594950501598269, -0.5306183540434553, -0.2062832773732194, 0.0, 0.0, 0.0], "pre_activation_mean": -1.707604169845581, "pre_activation_std": 1.1667653322219849}, "1": {"mean": 1.5190951824188232, "std": 1.1984689235687256, "fourier": [19.45085089550483, 19.650342514738217, 21.737356602306253, 22.022871428214742, 136.71858221292496], "input_correlations": [0.6598133758175846, 0.7744048538968475, 0.32256574185620424, 0.3053747121372598, -0.30558636215979806, 0.0, 0.0, 0.0], "pre_activation_mean": 2.105325222015381, "pre_activation_std": 1.8343169689178467}, "2": {"mean": 0.0019556409679353237, "std": 0.008841622620821, "fourier": [0.14131490819904197, 0.1459001737718415, 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"layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -0.7832508683204651, "std": 0.25146862864494324, "fourier": [4.0848064845851715, 4.15144781041902, 4.98657117106861, 5.403397348360756, 70.4925751388073], "input_correlations": [0.27370875329395933, -0.5542811734048841, 0.0, -0.7930506321492824, 0.23695865993297946, 0.0, 0.0, 0.0], "pre_activation_mean": -0.7832508683204651, "pre_activation_std": 0.25146862864494324}, "1": {"mean": 1.7450453042984009, "std": 1.2963812351226807, "fourier": [21.20078810448218, 21.586060416839885, 22.872539478858187, 23.83915395500959, 157.0540660917759], "input_correlations": [-0.30156563677106896, 0.9932593362828868, 0.0, -0.172428682156175, -0.2584536189755075, 0.0, 0.0, 0.0], "pre_activation_mean": 1.7450453042984009, "pre_activation_std": 1.2963812351226807}, "2": {"mean": 0.5052691698074341, "std": 0.26440688967704773, "fourier": [4.143589620281754, 4.730300751235241, 5.382047624075183, 5.795615989221597, 45.47422740608454], "input_correlations": [-0.3345135754482288, 0.9273825132940889, 0.0, 0.3166899215856999, -0.28889503194600397, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5052691698074341, "pre_activation_std": 0.26440688967704773}, "3": {"mean": 1.142925500869751, "std": 0.8633051514625549, "fourier": [13.724882967062115, 14.393053794483983, 15.353911303939087, 15.830316675251247, 102.86329352110624], "input_correlations": [-0.30216233588818864, 0.9905768422710135, 0.0, -0.1920000338295103, -0.265817516933979, 0.0, 0.0, 0.0], "pre_activation_mean": 1.142925500869751, "pre_activation_std": 0.8633051514625549}, "4": {"mean": -0.6033387780189514, "std": 0.2561878561973572, "fourier": [4.140987742483665, 4.213441021973733, 4.233109713586992, 4.454132931447722, 54.300488010048866], "input_correlations": [0.21201097039357317, -0.9238349508850827, 0.0, 0.431999318041103, 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"num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.010575, -0.416981, -0.255672, -0.167333, -0.042616], [0.500119, 0.476046, 0.132549, 0.213441, -0.469151], [-0.280247, -0.116799, -0.218709, -0.288266, -0.177852], [-0.2152, 0.032935, -0.247587, 0.272758, 0.00372], [0.194031, -0.595528, -0.557746, -0.152456, 0.022365]], "network.0.bias": [0.010853, 0.45952, -0.210202, 0.161306, 0.119634], "network.2.weight": [[-0.004313, -0.090201, 0.186035, -0.410127, -0.441787], [-0.311564, 0.722931, -0.345858, -0.292171, -0.151221], [0.277229, 0.14464, -0.093119, 0.19428, 0.233272], [0.121802, 0.477673, 0.257957, -0.232182, -0.306708], [0.195656, -0.133051, -0.263849, 0.181387, -0.221525]], "network.2.bias": [-0.416259, 0.308613, 0.111207, 0.213673, -0.384136], "network.4.weight": [[0.21244, 0.558322, -0.360642, 0.365791, 0.202898], [-0.080652, -0.377952, 0.18871, -0.275653, -0.018787], [-0.131014, 0.42921, 0.363221, 0.222793, -0.637302], [0.249221, 0.01065, -0.068663, -0.030004, 0.09854], [-0.002303, 0.3578, 0.231107, 0.614805, 0.44023]], "network.4.bias": [0.125831, 0.592732, 0.363521, 0.042732, -0.155657], "network.6.weight": [[0.014019, 0.740456, 0.219814, 0.145556, -0.415224], [0.551433, -0.22069, 0.438173, -0.099346, 0.279488], [0.032535, -0.193719, 0.183863, -0.136968, -0.115989], [0.119641, -0.161252, 0.050136, -0.002298, -0.191873], [0.559813, -0.16749, 0.383297, 0.083085, 0.549375]], "network.6.bias": [0.186176, -0.24094, -0.291026, -0.431543, -0.196669], "network.8.weight": [[0.572038, -0.608325, 0.344857, -0.05087, -0.546771]], "network.8.bias": [-0.281625]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6727138459682465, "train_acc": 0.59, "val_loss": 0.705595076084137, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6498412489891052, "train_acc": 0.59, "val_loss": 0.676525890827179, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.5967642366886139, "train_acc": 0.59, "val_loss": 0.5791502594947815, "val_acc": 0.46}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.5325459837913513, "train_acc": 0.61, "val_loss": 0.4838458299636841, "val_acc": 0.9}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.45925477147102356, "train_acc": 0.845, "val_loss": 0.41320809721946716, "val_acc": 0.84}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.38404515385627747, "train_acc": 0.835, "val_loss": 0.4227367639541626, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.37929728627204895, "train_acc": 0.82, "val_loss": 0.43649521470069885, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.3708961606025696, "train_acc": 0.83, "val_loss": 0.39699217677116394, "val_acc": 0.82}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.37236133217811584, "train_acc": 0.83, "val_loss": 0.3657534718513489, "val_acc": 0.86}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.3699638694524765, "train_acc": 0.83, "val_loss": 0.33802321553230286, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.3481704294681549, "train_acc": 0.84, "val_loss": 0.3627801537513733, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.3514394611120224, "train_acc": 0.86, "val_loss": 0.33464252948760986, "val_acc": 0.86}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.3514106720685959, "train_acc": 0.85, "val_loss": 0.4131094217300415, "val_acc": 0.8}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.705595076084137, "final_val_loss": 0.5791502594947815, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.4838458299636841, "final_val_loss": 0.4131094217300415, "initial_val_acc": 0.9, "final_val_acc": 0.8, "best_val_acc": 0.9, "best_epoch": 3}, "improvement": 0.44, "first_improvement_epoch": 2}} |
58 | {"target_pattern": "increasing_pairs", "degraded_accuracy": 0.48, "improved_accuracy": 0.82, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 1250, "learning_rate": 0.054650206537940234, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "increasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["increasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
[
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0.5327
]
],
"network.4.bias": [
-0.461136,
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0.632471,
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],
"network.6.weight": [
[
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[
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[
-0.123733,
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[
-0.180953,
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],
[
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],
"network.6.bias": [
0.036336,
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],
"network.8.weight": [
[
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],
[
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],
[
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[
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[
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],
"network.8.bias": [
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"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.265317, 7.784024, 0.000000, 8.139179]
std: [0.000000, 0.449192, 8.231611, 0.000000, 8.523756]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [6.379382, 6.470835, 7.853981, 9.401976, 23.878538], [131.965314, 134.179506, 153.718615, 160.160153, 700.562185], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [136.505167, 138.716749, 159.002499, 166.046217, 732.526127]]
input_correlations: [[-0.820950, -0.366415, -0.245773, 0.336416, 0.342082, 0.000000, 0.000000, 0.000000], [0.865136, 0.567550, 0.059818, -0.202781, 0.092651, 0.000000, 0.000000, 0.000000], [0.749601, 0.693621, 0.667509, 0.086468, -0.059535, 0.000000, 0.000000, 0.000000], [-0.456856, -0.584317, -0.802912, -0.482571, -0.403183, 0.000000, 0.000000, 0.000000], [0.900610, 0.630475, 0.546693, 0.163798, 0.252205, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.017295, 0.518526, 3.268360, -2.265130, 3.769498]
pre_activation_std: [3.172884, 2.370904, 2.996277, 1.325896, 3.279683]
### 2
mean: [-2.106290, -2.520075, -3.002765, -0.056471, 5.051832]
std: [1.372389, 1.762613, 1.781510, 1.942378, 5.132086]
fourier: [[22.453607, 24.669193, 24.847861, 26.794422, 189.566118], [27.534544, 32.752490, 33.096434, 35.321534, 226.806769], [28.826847, 29.766582, 29.928274, 35.682010, 270.248855], [27.684036, 29.357559, 30.584446, 31.079725, 45.749910], [80.783466, 81.037587, 93.157055, 98.180259, 454.664849]]
input_correlations: [[0.169826, -0.884636, -0.873578, 0.000000, -0.986690, 0.000000, 0.000000, 0.000000], [0.075123, -0.910165, -0.788221, 0.000000, -0.945394, 0.000000, 0.000000, 0.000000], [0.231302, -0.750529, -0.959660, 0.000000, -0.953056, 0.000000, 0.000000, 0.000000], [0.831528, -0.804737, -0.834587, 0.000000, -0.763222, 0.000000, 0.000000, 0.000000], [-0.522538, 0.906011, 0.965815, 0.000000, 0.961355, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.106290, -2.520075, -3.002765, -0.056471, 5.051832]
pre_activation_std: [1.372389, 1.762613, 1.781510, 1.942378, 5.132086]
### 4
mean: [-2.792594, -0.935455, 4.953186, -0.634633, 2.504848]
std: [2.264933, 0.410106, 5.068676, 2.422410, 2.857616]
fourier: [[35.798833, 37.617969, 41.777303, 42.043363, 251.333505], [6.082537, 7.861890, 7.921090, 8.728776, 84.190906], [76.959689, 78.649901, 92.628282, 103.959831, 445.786770], [35.325443, 36.637494, 41.578666, 55.865026, 57.116951], [44.339663, 44.583151, 52.479912, 57.401058, 225.436357]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.494071, -0.999824, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.200040, -0.740546, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.604070, 0.993613, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.757551, -0.947957, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.580800, 0.996458, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.792594, -0.935455, 4.953186, -0.634633, 2.504848]
pre_activation_std: [2.264933, 0.410106, 5.068676, 2.422410, 2.857616]
### 6
mean: [-1.867540, -0.663425, 0.588861, 7.431135, -1.012195]
std: [1.337295, 0.370807, 0.727806, 7.813877, 0.434934]
fourier: [[23.464829, 23.484335, 24.135595, 24.626271, 168.078559], [5.909421, 5.932808, 6.874887, 7.168779, 59.708222], [10.660314, 10.894146, 12.476654, 17.372862, 52.997522], [120.523048, 121.679096, 143.361373, 159.979200, 668.802048], [6.871280, 6.920022, 8.526804, 8.624123, 91.097591]]
input_correlations: [[0.000000, 0.000000, -0.933906, 0.222104, -0.945168, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.998700, 0.554518, -0.998939, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.796975, 0.945127, -0.776543, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.997501, -0.613231, 0.994530, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.577477, -0.357410, -0.603804, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.867540, -0.663425, 0.588861, 7.431135, -1.012195]
pre_activation_std: [1.337295, 0.370807, 0.727806, 7.813877, 0.434934]
### 8
mean: [-3.268596, -0.892511, 7.584802, -2.451276, 7.971216]
std: [2.622282, 1.613757, 8.433167, 1.998151, 8.693398]
fourier: [[43.093227, 43.516983, 48.687412, 49.179159, 294.173639], [23.892547, 24.471710, 29.196787, 34.927780, 80.325959], [131.739229, 133.923710, 156.115192, 169.388151, 682.632245], [32.107096, 32.514518, 37.095031, 38.786038, 220.614858], [136.303755, 138.492347, 161.013856, 173.918522, 717.409408]]
input_correlations: [[0.000000, 0.000000, 0.675740, -0.997888, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.838292, -0.982535, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.747730, 0.999291, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.710795, -0.999866, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.743290, 0.999520, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.268596, -0.892511, 7.584802, -2.451276, 7.971216]
pre_activation_std: [2.622282, 1.613757, 8.433167, 1.998151, 8.693398]
### 10
mean: [-11.562353]
std: [13.099970]
fourier: [[207.895448, 212.562958, 244.425232, 257.291077, 1040.611811]]
input_correlations: [[0.000000, 0.563373, -0.999876, 0.000000, -0.999914, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-11.562353]
pre_activation_std: [13.099970]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| increasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-1.273157,
-0.3092,
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0.438756,
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],
[
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-0.379031,
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],
[
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0.008041,
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],
[
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-0.194738,
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],
[
1.154969,
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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],
[
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],
[
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],
[
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]
],
"network.2.bias": [
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-0.46716,
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0.477349
],
"network.4.weight": [
[
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],
[
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],
[
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0.187015,
0.256772,
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0.925007
],
[
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0.044911,
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],
[
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]
],
"network.4.bias": [
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0.632471,
-0.031106
],
"network.6.weight": [
[
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-0.526886,
-0.145615
],
[
-0.097168,
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0.142074,
0.03896,
-0.378356
],
[
-0.123733,
0.260598,
-0.004077,
0.508168,
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],
[
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1.151043,
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0.618188
],
[
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0.129959
]
],
"network.6.bias": [
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0.52593,
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-0.200279
],
"network.8.weight": [
[
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-0.035055,
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-0.367282,
-0.148325
],
[
0.1079,
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0.639255,
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0.149073
],
[
0.458985,
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-0.675956,
1.063974,
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],
[
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0.429394,
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],
[
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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-0.733035,
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-0.814402
]
],
"network.10.bias": [
0.640595
]
}
## Activation Signature
### 0
mean: [0.000000, 0.265317, 7.784024, 0.000000, 8.139179]
std: [0.000000, 0.449192, 8.231611, 0.000000, 8.523756]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [6.379382, 6.470835, 7.853981, 9.401976, 23.878538], [131.965314, 134.179506, 153.718615, 160.160153, 700.562185], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [136.505167, 138.716749, 159.002499, 166.046217, 732.526127]]
input_correlations: [[-0.820950, -0.366415, -0.245773, 0.336416, 0.342082, 0.000000, 0.000000, 0.000000], [0.865136, 0.567550, 0.059818, -0.202781, 0.092651, 0.000000, 0.000000, 0.000000], [0.749601, 0.693621, 0.667509, 0.086468, -0.059535, 0.000000, 0.000000, 0.000000], [-0.456856, -0.584317, -0.802912, -0.482571, -0.403183, 0.000000, 0.000000, 0.000000], [0.900610, 0.630475, 0.546693, 0.163798, 0.252205, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.017295, 0.518526, 3.268360, -2.265130, 3.769498]
pre_activation_std: [3.172884, 2.370904, 2.996277, 1.325896, 3.279683]
### 2
mean: [-2.106290, -2.520075, -3.002765, -0.056471, 5.051832]
std: [1.372389, 1.762613, 1.781510, 1.942378, 5.132086]
fourier: [[22.453607, 24.669193, 24.847861, 26.794422, 189.566118], [27.534544, 32.752490, 33.096434, 35.321534, 226.806769], [28.826847, 29.766582, 29.928274, 35.682010, 270.248855], [27.684036, 29.357559, 30.584446, 31.079725, 45.749910], [80.783466, 81.037587, 93.157055, 98.180259, 454.664849]]
input_correlations: [[0.169826, -0.884636, -0.873578, 0.000000, -0.986690, 0.000000, 0.000000, 0.000000], [0.075123, -0.910165, -0.788221, 0.000000, -0.945394, 0.000000, 0.000000, 0.000000], [0.231302, -0.750529, -0.959660, 0.000000, -0.953056, 0.000000, 0.000000, 0.000000], [0.831528, -0.804737, -0.834587, 0.000000, -0.763222, 0.000000, 0.000000, 0.000000], [-0.522538, 0.906011, 0.965815, 0.000000, 0.961355, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.106290, -2.520075, -3.002765, -0.056471, 5.051832]
pre_activation_std: [1.372389, 1.762613, 1.781510, 1.942378, 5.132086]
### 4
mean: [-2.792594, -0.935455, 4.953186, -0.634633, 2.504848]
std: [2.264933, 0.410106, 5.068676, 2.422410, 2.857616]
fourier: [[35.798833, 37.617969, 41.777303, 42.043363, 251.333505], [6.082537, 7.861890, 7.921090, 8.728776, 84.190906], [76.959689, 78.649901, 92.628282, 103.959831, 445.786770], [35.325443, 36.637494, 41.578666, 55.865026, 57.116951], [44.339663, 44.583151, 52.479912, 57.401058, 225.436357]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.494071, -0.999824, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.200040, -0.740546, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.604070, 0.993613, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.757551, -0.947957, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.580800, 0.996458, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.792594, -0.935455, 4.953186, -0.634633, 2.504848]
pre_activation_std: [2.264933, 0.410106, 5.068676, 2.422410, 2.857616]
### 6
mean: [-1.867540, -0.663425, 0.588861, 7.431135, -1.012195]
std: [1.337295, 0.370807, 0.727806, 7.813877, 0.434934]
fourier: [[23.464829, 23.484335, 24.135595, 24.626271, 168.078559], [5.909421, 5.932808, 6.874887, 7.168779, 59.708222], [10.660314, 10.894146, 12.476654, 17.372862, 52.997522], [120.523048, 121.679096, 143.361373, 159.979200, 668.802048], [6.871280, 6.920022, 8.526804, 8.624123, 91.097591]]
input_correlations: [[0.000000, 0.000000, -0.933906, 0.222104, -0.945168, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.998700, 0.554518, -0.998939, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.796975, 0.945127, -0.776543, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.997501, -0.613231, 0.994530, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.577477, -0.357410, -0.603804, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.867540, -0.663425, 0.588861, 7.431135, -1.012195]
pre_activation_std: [1.337295, 0.370807, 0.727806, 7.813877, 0.434934]
### 8
mean: [-3.268596, -0.892511, 7.584802, -2.451276, 7.971216]
std: [2.622282, 1.613757, 8.433167, 1.998151, 8.693398]
fourier: [[43.093227, 43.516983, 48.687412, 49.179159, 294.173639], [23.892547, 24.471710, 29.196787, 34.927780, 80.325959], [131.739229, 133.923710, 156.115192, 169.388151, 682.632245], [32.107096, 32.514518, 37.095031, 38.786038, 220.614858], [136.303755, 138.492347, 161.013856, 173.918522, 717.409408]]
input_correlations: [[0.000000, 0.000000, 0.675740, -0.997888, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.838292, -0.982535, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.747730, 0.999291, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.710795, -0.999866, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.743290, 0.999520, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.268596, -0.892511, 7.584802, -2.451276, 7.971216]
pre_activation_std: [2.622282, 1.613757, 8.433167, 1.998151, 8.693398]
### 10
mean: [-11.562353]
std: [13.099970]
fourier: [[207.895448, 212.562958, 244.425232, 257.291077, 1040.611811]]
input_correlations: [[0.000000, 0.563373, -0.999876, 0.000000, -0.999914, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-11.562353]
pre_activation_std: [13.099970]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
increasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.8209497612332403, -0.3664148515816654, -0.24577309845528778, 0.33641642099084634, 0.3420816767868673, 0.0, 0.0, 0.0], "pre_activation_mean": 0.017295021563768387, "pre_activation_std": 3.172884464263916}, "1": {"mean": 0.26531708240509033, "std": 0.44919249415397644, "fourier": [6.379382005043485, 6.470834537844618, 7.853981463934008, 9.401975831555509, 23.878538087010384], "input_correlations": [0.8651361708110791, 0.5675501998237662, 0.05981806569490408, -0.2027811375049673, 0.09265092188072786, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5185255408287048, "pre_activation_std": 2.3709044456481934}, "2": {"mean": 7.784024238586426, "std": 8.231611251831055, "fourier": [131.96531448973371, 134.17950578664764, 153.71861476236907, 160.16015305432592, 700.5621851682663], "input_correlations": [0.7496006617624991, 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"input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -2.106290340423584, "std": 1.3723888397216797, "fourier": [22.45360669850656, 24.66919285399254, 24.847861370708877, 26.794421633128213, 189.56611815094948], "input_correlations": [0.16982607362266833, -0.8846358479024389, -0.8735780330080753, 0.0, -0.9866899234338167, 0.0, 0.0, 0.0], "pre_activation_mean": -2.106290340423584, "pre_activation_std": 1.3723888397216797}, "1": {"mean": -2.5200750827789307, "std": 1.7626129388809204, "fourier": [27.53454354836302, 32.75249019483294, 33.09643398391696, 35.32153405121736, 226.80676877498627], "input_correlations": [0.07512265229332528, -0.9101646651821075, -0.7882213052658076, 0.0, -0.945393519561106, 0.0, 0.0, 0.0], "pre_activation_mean": -2.5200750827789307, "pre_activation_std": 1.7626129388809204}, "2": {"mean": -3.002764940261841, "std": 1.781509518623352, "fourier": [28.826847309047512, 29.76658216557572, 29.92827384802016, 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{"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "6": {"neuron_profiles": {"0": {"mean": -1.8675395250320435, "std": 1.3372948169708252, "fourier": [23.464828619211268, 23.484335389877625, 24.13559542981296, 24.626271321021086, 168.0785592198372], "input_correlations": [0.0, 0.0, -0.933905884210596, 0.2221036257886337, -0.9451678905593511, 0.0, 0.0, 0.0], "pre_activation_mean": -1.8675395250320435, "pre_activation_std": 1.3372948169708252}, "1": {"mean": -0.6634246706962585, "std": 0.3708074390888214, "fourier": [5.9094208315627315, 5.932808087935537, 6.874887150316727, 7.168778874006987, 59.708221793174744], "input_correlations": [0.0, 0.0, -0.998699757259739, 0.5545178945241622, -0.9989389579424157, 0.0, 0.0, 0.0], "pre_activation_mean": -0.6634246706962585, "pre_activation_std": 0.3708074390888214}, "2": {"mean": 0.5888614058494568, "std": 0.7278063297271729, "fourier": 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{"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-1.273157, -0.3092, -0.081076, 0.438756, 0.785253], [0.899973, 0.627666, -0.370048, -0.379031, 0.088627], [0.750746, 0.680116, 0.722441, 0.008041, -0.409947], [-0.094519, -0.194738, -0.446782, -0.232216, -0.130913], [1.154969, 0.556553, 0.401713, 0.130613, 0.106436]], "network.0.bias": [0.425092, -0.268693, 0.074033, -0.199938, 0.067542], "network.2.weight": [[-0.131963, -0.092834, 0.027991, 0.050634, -0.410087], [-0.266577, -0.397301, 0.129814, -0.116945, -0.457602], [-0.228231, 0.199446, -0.469628, 0.25806, -0.267079], [0.670178, -0.404183, -0.170587, -0.082551, -0.004014], [-0.417448, 0.723114, 0.730634, 0.154323, 0.475409]], "network.2.bias": [-0.396273, -0.46716, -0.399771, 0.22219, 0.477349], "network.4.weight": [[-0.065375, -0.091983, 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[-0.241859, -0.023712, -0.090942, -0.373343, -0.081825], "network.10.weight": [[-0.038997, 0.495911, -0.733035, 0.241877, -0.814402]], "network.10.bias": [0.640595]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7019431293010712, "train_acc": 0.42, "val_loss": 0.6993151903152466, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6804072558879852, "train_acc": 0.575, "val_loss": 0.7106826305389404, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6504930555820465, "train_acc": 0.575, "val_loss": 0.659527063369751, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6225615441799164, "train_acc": 0.505, "val_loss": 0.5468310713768005, "val_acc": 0.48}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5014879107475281, "train_acc": 0.6, "val_loss": 0.5542283058166504, "val_acc": 0.72}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4624251425266266, "train_acc": 0.82, "val_loss": 0.48633870482444763, "val_acc": 0.8}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.4444690942764282, "train_acc": 0.815, "val_loss": 0.48110032081604004, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.422641396522522, "train_acc": 0.81, "val_loss": 0.44063204526901245, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.3660653084516525, "train_acc": 0.845, "val_loss": 0.4656459093093872, "val_acc": 0.8}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.36119644343852997, "train_acc": 0.845, "val_loss": 0.413880318403244, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.36901821196079254, "train_acc": 0.845, "val_loss": 0.4627687931060791, "val_acc": 0.8}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.3686399757862091, "train_acc": 0.85, "val_loss": 0.43068262934684753, "val_acc": 0.82}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.35341936349868774, "train_acc": 0.85, "val_loss": 0.42101964354515076, "val_acc": 0.82}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["increasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6993151903152466, "final_val_loss": 0.659527063369751, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5468310713768005, "final_val_loss": 0.42101964354515076, "initial_val_acc": 0.48, "final_val_acc": 0.82, "best_val_acc": 0.82, "best_epoch": 9}, "improvement": 0.33999999999999997, "first_improvement_epoch": 2}} |
59 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.66, "improved_accuracy": 0.98, "improvement": 0.31999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6942, "learning_rate": 0.039815314088510245, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.weight": [
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}
## Activation Signature
### 0
mean: [0.225708, 1.113379, 0.068396, 0.271582, 1.759533, 1.930256, 1.725502]
std: [0.806401, 0.779566, 0.133479, 0.896108, 1.129850, 1.237594, 1.073691]
fourier: [[13.525408, 14.025775, 14.101797, 14.850754, 20.313758], [11.809418, 12.203525, 14.927065, 18.563462, 100.204101], [1.999304, 2.242356, 2.722020, 2.923534, 6.155615], [14.890316, 15.366366, 16.179717, 16.542591, 24.442360], [19.073141, 19.513318, 21.245305, 24.746512, 158.357939], [20.623207, 21.453492, 23.664916, 26.992628, 173.723056], [18.285791, 18.559121, 20.208872, 23.486464, 155.295161]]
input_correlations: [[0.414585, 0.716239, 0.570928, 0.673674, 0.390567, 0.000000, 0.000000, 0.000000], [0.748545, 0.827271, 0.256133, -0.029685, -0.018962, 0.000000, 0.000000, 0.000000], [-0.075198, -0.537807, 0.635593, -0.176571, 0.464951, 0.000000, 0.000000, 0.000000], [-0.802895, -0.312778, -0.767981, -0.097066, -0.457981, 0.000000, 0.000000, 0.000000], [0.180934, -0.150849, 0.237386, -0.705415, 0.579192, 0.000000, 0.000000, 0.000000], [0.981081, 0.405064, 0.231136, 0.047163, 0.291562, 0.000000, 0.000000, 0.000000], [0.909938, 0.583745, 0.427733, -0.171598, 0.037244, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [4.277796, 0.744021, 0.751063, -3.173145, -0.145991, 0.849149, 1.187226]
pre_activation_std: [2.608458, 1.295288, 1.183523, 2.807979, 1.706515, 1.665404, 2.214526]
### 2
mean: [0.662243, -1.119972, 1.570932, -0.048482, -1.233631, -0.978652, 2.427762]
std: [2.161597, 1.022948, 1.255619, 0.550738, 0.778877, 0.917792, 1.692184]
fourier: [[36.640837, 36.642343, 37.163475, 37.213946, 59.601899], [16.953850, 17.001599, 19.217061, 21.437713, 100.797473], [19.679844, 20.691038, 20.695007, 24.273356, 141.383830], [8.579118, 8.605026, 8.796582, 9.124492, 10.005980], [12.020740, 12.538277, 14.647866, 16.469292, 111.026761], [15.967359, 16.131485, 16.530064, 18.052224, 88.078676], [25.866816, 28.226195, 29.685857, 33.246127, 218.498604]]
input_correlations: [[0.449069, 0.914491, -0.333402, 0.208076, -0.173285, 0.921420, 0.954143, 0.000000], [-0.782159, -0.740299, -0.067716, -0.129419, -0.131513, -0.904577, -0.836297, 0.000000], [0.186955, -0.599953, 0.719315, -0.122214, 0.512408, -0.461214, -0.551798, 0.000000], [-0.540132, -0.893000, 0.294440, -0.140703, 0.180816, -0.923033, -0.945018, 0.000000], [-0.927027, -0.668142, -0.091338, -0.070967, -0.041234, -0.742726, -0.694938, 0.000000], [-0.485082, -0.838807, 0.048287, -0.221159, -0.103154, -0.982995, -0.975996, 0.000000], [0.905646, 0.772591, -0.037501, 0.118396, -0.217367, 0.677048, 0.738550, 0.000000]]
pre_activation_mean: [0.662243, -1.119972, 1.570932, -0.048482, -1.233631, -0.978652, 2.427762]
pre_activation_std: [2.161597, 1.022948, 1.255619, 0.550738, 0.778877, 0.917792, 1.692184]
### 4
mean: [1.221992, -0.754817, 0.278407, 0.232401, 1.153903, -0.520355, 1.673888]
std: [0.469926, 0.247037, 0.652625, 1.993979, 1.294793, 0.623338, 0.943061]
fourier: [[6.949937, 7.187842, 8.475903, 8.584945, 109.979317], [3.895149, 3.995661, 4.786188, 5.169276, 67.933567], [10.396570, 10.412593, 10.507668, 10.840398, 25.056605], [29.654487, 31.582080, 33.737580, 34.502175, 34.657603], [21.299713, 22.219490, 22.753788, 23.862658, 103.851278], [10.061581, 10.410870, 11.068482, 13.183377, 46.831981], [13.948490, 15.587579, 16.598481, 19.384591, 150.649954]]
input_correlations: [[-0.069150, -0.479659, 0.548181, -0.204088, 0.071777, -0.252948, 0.621557, 0.000000], [-0.569442, 0.098402, -0.367287, 0.397185, -0.339961, -0.512733, -0.749339, 0.000000], [-0.923080, -0.442729, 0.736495, 0.795884, -0.574004, -0.767032, -0.729613, 0.000000], [0.964706, 0.383977, -0.650653, -0.770884, 0.554703, 0.798692, 0.782574, 0.000000], [0.983742, 0.346237, -0.539620, -0.719583, 0.553776, 0.819729, 0.817414, 0.000000], [-0.940974, -0.418522, 0.337173, 0.477529, -0.530662, -0.904909, -0.613488, 0.000000], [-0.724422, -0.587195, 0.936873, 0.460240, -0.342028, -0.684029, -0.173935, 0.000000]]
pre_activation_mean: [1.221992, -0.754817, 0.278407, 0.232401, 1.153903, -0.520355, 1.673888]
pre_activation_std: [0.469926, 0.247037, 0.652625, 1.993979, 1.294793, 0.623338, 0.943061]
### 6
mean: [0.420388, 0.528179, 0.626943, 1.674598, -0.107464, 1.277351, 0.677261]
std: [0.255049, 0.860821, 1.437524, 1.242625, 0.707694, 0.965532, 0.724019]
fourier: [[3.747730, 4.093334, 4.430565, 4.855771, 37.834938], [13.065758, 14.733516, 15.861570, 15.967808, 47.536132], [22.822395, 24.492301, 24.588987, 26.153397, 56.424910], [19.739993, 20.882174, 23.155167, 24.043916, 150.713782], [11.282182, 12.064245, 12.119872, 12.299685, 12.610770], [14.977767, 15.776266, 17.923728, 19.719250, 114.961563], [10.996664, 12.418742, 12.723222, 12.992414, 60.953523]]
input_correlations: [[0.957698, -0.368558, 0.167650, -0.020404, 0.053212, 0.046314, 0.713991, 0.000000], [0.379836, -0.264994, 0.713900, -0.924480, -0.892579, -0.097399, 0.907189, 0.000000], [0.022090, 0.136033, -0.740596, 0.992279, 0.997146, 0.176380, -0.679451, 0.000000], [0.504068, -0.323950, 0.733502, -0.848901, -0.818404, -0.090420, 0.961904, 0.000000], [0.097903, -0.166778, 0.635982, -0.996945, -0.980968, -0.085317, 0.706318, 0.000000], [0.546093, -0.320654, 0.624562, -0.844399, -0.794839, -0.072735, 0.945666, 0.000000], [0.290829, -0.245430, 0.760057, -0.942816, -0.918894, -0.141686, 0.884090, 0.000000]]
pre_activation_mean: [0.420388, 0.528179, 0.626943, 1.674598, -0.107464, 1.277351, 0.677261]
pre_activation_std: [0.255049, 0.860821, 1.437524, 1.242625, 0.707694, 0.965532, 0.724019]
### 8
mean: [-0.134434, 1.202271, -0.010701, -0.383408, 1.753259, 1.820040, 1.655834]
std: [1.028214, 0.762399, 0.458856, 1.270250, 1.201400, 1.491553, 1.283510]
fourier: [[16.169105, 16.311345, 17.103768, 17.269730, 18.357131], [11.493683, 12.536332, 14.266134, 17.880648, 108.204364], [7.044462, 7.337398, 7.599234, 7.805558, 8.244267], [20.212686, 20.795457, 22.104065, 22.897989, 34.506677], [20.932255, 21.095144, 21.447239, 25.043927, 157.793262], [25.580579, 26.416913, 26.447197, 29.557084, 163.803605], [21.387290, 22.599680, 23.053189, 25.428308, 149.025040]]
input_correlations: [[-0.173966, -0.818060, 0.981908, -0.856003, -0.817058, -0.834062, -0.898764, 0.000000], [0.743214, 0.981411, -0.632626, 0.975733, 0.728054, 0.988201, 0.933535, 0.000000], [0.228921, 0.845450, -0.972343, 0.882484, 0.815424, 0.862253, 0.916797, 0.000000], [-0.238104, -0.849870, 0.970185, -0.891389, -0.817785, -0.867511, -0.920667, 0.000000], [0.512078, 0.972304, -0.836422, 0.989395, 0.817874, 0.973584, 0.986721, 0.000000], [0.445698, 0.948936, -0.883238, 0.973752, 0.824090, 0.955244, 0.979493, 0.000000], [0.454635, 0.937671, -0.889035, 0.966407, 0.800086, 0.958481, 0.966961, 0.000000]]
pre_activation_mean: [-0.134434, 1.202271, -0.010701, -0.383408, 1.753259, 1.820040, 1.655834]
pre_activation_std: [1.028214, 0.762399, 0.458856, 1.270250, 1.201400, 1.491553, 1.283510]
### 10
mean: [-2.202302]
std: [1.959473]
fourier: [[33.691780, 34.705688, 35.270010, 38.854028, 198.207174]]
input_correlations: [[0.888411, -0.898127, -0.966176, 0.869581, -0.979551, -0.979241, -0.984891, 0.000000]]
pre_activation_mean: [-2.202302]
pre_activation_std: [1.959473]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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0.532027,
0.048276
],
[
0.06556,
0.23611,
-0.250544,
-0.085621,
0.07657,
0.104933,
0.04842
],
[
0.120022,
0.026172,
0.596923,
-0.141302,
-0.458046,
-0.340292,
-0.142991
],
[
-0.197126,
0.109801,
-0.125889,
0.447652,
0.26445,
0.414605,
0.435569
],
[
0.139891,
0.196275,
-0.366571,
0.448659,
0.349588,
0.322193,
0.415747
],
[
0.422373,
0.203521,
-0.423516,
0.150797,
-0.21686,
0.563272,
0.117579
]
],
"network.8.bias": [
-0.068142,
-0.153916,
-0.02689,
-0.022277,
0.221372,
0.419181,
0.654179
],
"network.10.weight": [
[
0.248465,
-0.134645,
0.136086,
0.468937,
-0.266675,
-0.561226,
-0.344258
]
],
"network.10.bias": [
-0.098583
]
}
## Activation Signature
### 0
mean: [0.225708, 1.113379, 0.068396, 0.271582, 1.759533, 1.930256, 1.725502]
std: [0.806401, 0.779566, 0.133479, 0.896108, 1.129850, 1.237594, 1.073691]
fourier: [[13.525408, 14.025775, 14.101797, 14.850754, 20.313758], [11.809418, 12.203525, 14.927065, 18.563462, 100.204101], [1.999304, 2.242356, 2.722020, 2.923534, 6.155615], [14.890316, 15.366366, 16.179717, 16.542591, 24.442360], [19.073141, 19.513318, 21.245305, 24.746512, 158.357939], [20.623207, 21.453492, 23.664916, 26.992628, 173.723056], [18.285791, 18.559121, 20.208872, 23.486464, 155.295161]]
input_correlations: [[0.414585, 0.716239, 0.570928, 0.673674, 0.390567, 0.000000, 0.000000, 0.000000], [0.748545, 0.827271, 0.256133, -0.029685, -0.018962, 0.000000, 0.000000, 0.000000], [-0.075198, -0.537807, 0.635593, -0.176571, 0.464951, 0.000000, 0.000000, 0.000000], [-0.802895, -0.312778, -0.767981, -0.097066, -0.457981, 0.000000, 0.000000, 0.000000], [0.180934, -0.150849, 0.237386, -0.705415, 0.579192, 0.000000, 0.000000, 0.000000], [0.981081, 0.405064, 0.231136, 0.047163, 0.291562, 0.000000, 0.000000, 0.000000], [0.909938, 0.583745, 0.427733, -0.171598, 0.037244, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [4.277796, 0.744021, 0.751063, -3.173145, -0.145991, 0.849149, 1.187226]
pre_activation_std: [2.608458, 1.295288, 1.183523, 2.807979, 1.706515, 1.665404, 2.214526]
### 2
mean: [0.662243, -1.119972, 1.570932, -0.048482, -1.233631, -0.978652, 2.427762]
std: [2.161597, 1.022948, 1.255619, 0.550738, 0.778877, 0.917792, 1.692184]
fourier: [[36.640837, 36.642343, 37.163475, 37.213946, 59.601899], [16.953850, 17.001599, 19.217061, 21.437713, 100.797473], [19.679844, 20.691038, 20.695007, 24.273356, 141.383830], [8.579118, 8.605026, 8.796582, 9.124492, 10.005980], [12.020740, 12.538277, 14.647866, 16.469292, 111.026761], [15.967359, 16.131485, 16.530064, 18.052224, 88.078676], [25.866816, 28.226195, 29.685857, 33.246127, 218.498604]]
input_correlations: [[0.449069, 0.914491, -0.333402, 0.208076, -0.173285, 0.921420, 0.954143, 0.000000], [-0.782159, -0.740299, -0.067716, -0.129419, -0.131513, -0.904577, -0.836297, 0.000000], [0.186955, -0.599953, 0.719315, -0.122214, 0.512408, -0.461214, -0.551798, 0.000000], [-0.540132, -0.893000, 0.294440, -0.140703, 0.180816, -0.923033, -0.945018, 0.000000], [-0.927027, -0.668142, -0.091338, -0.070967, -0.041234, -0.742726, -0.694938, 0.000000], [-0.485082, -0.838807, 0.048287, -0.221159, -0.103154, -0.982995, -0.975996, 0.000000], [0.905646, 0.772591, -0.037501, 0.118396, -0.217367, 0.677048, 0.738550, 0.000000]]
pre_activation_mean: [0.662243, -1.119972, 1.570932, -0.048482, -1.233631, -0.978652, 2.427762]
pre_activation_std: [2.161597, 1.022948, 1.255619, 0.550738, 0.778877, 0.917792, 1.692184]
### 4
mean: [1.221992, -0.754817, 0.278407, 0.232401, 1.153903, -0.520355, 1.673888]
std: [0.469926, 0.247037, 0.652625, 1.993979, 1.294793, 0.623338, 0.943061]
fourier: [[6.949937, 7.187842, 8.475903, 8.584945, 109.979317], [3.895149, 3.995661, 4.786188, 5.169276, 67.933567], [10.396570, 10.412593, 10.507668, 10.840398, 25.056605], [29.654487, 31.582080, 33.737580, 34.502175, 34.657603], [21.299713, 22.219490, 22.753788, 23.862658, 103.851278], [10.061581, 10.410870, 11.068482, 13.183377, 46.831981], [13.948490, 15.587579, 16.598481, 19.384591, 150.649954]]
input_correlations: [[-0.069150, -0.479659, 0.548181, -0.204088, 0.071777, -0.252948, 0.621557, 0.000000], [-0.569442, 0.098402, -0.367287, 0.397185, -0.339961, -0.512733, -0.749339, 0.000000], [-0.923080, -0.442729, 0.736495, 0.795884, -0.574004, -0.767032, -0.729613, 0.000000], [0.964706, 0.383977, -0.650653, -0.770884, 0.554703, 0.798692, 0.782574, 0.000000], [0.983742, 0.346237, -0.539620, -0.719583, 0.553776, 0.819729, 0.817414, 0.000000], [-0.940974, -0.418522, 0.337173, 0.477529, -0.530662, -0.904909, -0.613488, 0.000000], [-0.724422, -0.587195, 0.936873, 0.460240, -0.342028, -0.684029, -0.173935, 0.000000]]
pre_activation_mean: [1.221992, -0.754817, 0.278407, 0.232401, 1.153903, -0.520355, 1.673888]
pre_activation_std: [0.469926, 0.247037, 0.652625, 1.993979, 1.294793, 0.623338, 0.943061]
### 6
mean: [0.420388, 0.528179, 0.626943, 1.674598, -0.107464, 1.277351, 0.677261]
std: [0.255049, 0.860821, 1.437524, 1.242625, 0.707694, 0.965532, 0.724019]
fourier: [[3.747730, 4.093334, 4.430565, 4.855771, 37.834938], [13.065758, 14.733516, 15.861570, 15.967808, 47.536132], [22.822395, 24.492301, 24.588987, 26.153397, 56.424910], [19.739993, 20.882174, 23.155167, 24.043916, 150.713782], [11.282182, 12.064245, 12.119872, 12.299685, 12.610770], [14.977767, 15.776266, 17.923728, 19.719250, 114.961563], [10.996664, 12.418742, 12.723222, 12.992414, 60.953523]]
input_correlations: [[0.957698, -0.368558, 0.167650, -0.020404, 0.053212, 0.046314, 0.713991, 0.000000], [0.379836, -0.264994, 0.713900, -0.924480, -0.892579, -0.097399, 0.907189, 0.000000], [0.022090, 0.136033, -0.740596, 0.992279, 0.997146, 0.176380, -0.679451, 0.000000], [0.504068, -0.323950, 0.733502, -0.848901, -0.818404, -0.090420, 0.961904, 0.000000], [0.097903, -0.166778, 0.635982, -0.996945, -0.980968, -0.085317, 0.706318, 0.000000], [0.546093, -0.320654, 0.624562, -0.844399, -0.794839, -0.072735, 0.945666, 0.000000], [0.290829, -0.245430, 0.760057, -0.942816, -0.918894, -0.141686, 0.884090, 0.000000]]
pre_activation_mean: [0.420388, 0.528179, 0.626943, 1.674598, -0.107464, 1.277351, 0.677261]
pre_activation_std: [0.255049, 0.860821, 1.437524, 1.242625, 0.707694, 0.965532, 0.724019]
### 8
mean: [-0.134434, 1.202271, -0.010701, -0.383408, 1.753259, 1.820040, 1.655834]
std: [1.028214, 0.762399, 0.458856, 1.270250, 1.201400, 1.491553, 1.283510]
fourier: [[16.169105, 16.311345, 17.103768, 17.269730, 18.357131], [11.493683, 12.536332, 14.266134, 17.880648, 108.204364], [7.044462, 7.337398, 7.599234, 7.805558, 8.244267], [20.212686, 20.795457, 22.104065, 22.897989, 34.506677], [20.932255, 21.095144, 21.447239, 25.043927, 157.793262], [25.580579, 26.416913, 26.447197, 29.557084, 163.803605], [21.387290, 22.599680, 23.053189, 25.428308, 149.025040]]
input_correlations: [[-0.173966, -0.818060, 0.981908, -0.856003, -0.817058, -0.834062, -0.898764, 0.000000], [0.743214, 0.981411, -0.632626, 0.975733, 0.728054, 0.988201, 0.933535, 0.000000], [0.228921, 0.845450, -0.972343, 0.882484, 0.815424, 0.862253, 0.916797, 0.000000], [-0.238104, -0.849870, 0.970185, -0.891389, -0.817785, -0.867511, -0.920667, 0.000000], [0.512078, 0.972304, -0.836422, 0.989395, 0.817874, 0.973584, 0.986721, 0.000000], [0.445698, 0.948936, -0.883238, 0.973752, 0.824090, 0.955244, 0.979493, 0.000000], [0.454635, 0.937671, -0.889035, 0.966407, 0.800086, 0.958481, 0.966961, 0.000000]]
pre_activation_mean: [-0.134434, 1.202271, -0.010701, -0.383408, 1.753259, 1.820040, 1.655834]
pre_activation_std: [1.028214, 0.762399, 0.458856, 1.270250, 1.201400, 1.491553, 1.283510]
### 10
mean: [-2.202302]
std: [1.959473]
fourier: [[33.691780, 34.705688, 35.270010, 38.854028, 198.207174]]
input_correlations: [[0.888411, -0.898127, -0.966176, 0.869581, -0.979551, -0.979241, -0.984891, 0.000000]]
pre_activation_mean: [-2.202302]
pre_activation_std: [1.959473]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.22570841014385223, "std": 0.8064005374908447, "fourier": [13.525407994189532, 14.025775469016166, 14.101796999547007, 14.850753812941676, 20.31375778093934], "input_correlations": [0.4145853299330896, 0.7162393252084758, 0.5709284617557704, 0.6736739746692714, 0.3905672590938721, 0.0, 0.0, 0.0], "pre_activation_mean": 4.277795791625977, "pre_activation_std": 2.6084578037261963}, "1": {"mean": 1.1133787631988525, "std": 0.779565691947937, "fourier": [11.809418242199587, 12.203525433781808, 14.927065472128664, 18.56346161159428, 100.20410082342278], "input_correlations": [0.7485448142674694, 0.8272714367001751, 0.2561331277004037, -0.029684562900841188, -0.018961657013958626, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7440212965011597, "pre_activation_std": 1.2952876091003418}, "2": {"mean": 0.0683957189321518, "std": 0.13347923755645752, "fourier": [1.9993038848399416, 2.242356116579054, 2.7220195466036397, 2.9235343511040903, 6.155614893883467], "input_correlations": [-0.07519797648310793, -0.5378067940031922, 0.6355928340069054, -0.17657061534612212, 0.4649513198866425, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7510631084442139, "pre_activation_std": 1.1835228204727173}, "3": {"mean": 0.271581768989563, "std": 0.8961078524589539, "fourier": [14.890315768221942, 15.366366195045195, 16.17971742185086, 16.54259098902183, 24.442360416054726], "input_correlations": [-0.8028953967309536, -0.312778058815406, -0.7679812942728544, -0.09706552969616991, -0.45798102562235965, 0.0, 0.0, 0.0], "pre_activation_mean": -3.173145294189453, "pre_activation_std": 2.807979106903076}, "4": {"mean": 1.7595326900482178, "std": 1.1298497915267944, "fourier": [19.073141089679524, 19.513318194869974, 21.24530520195652, 24.746512133844064, 158.3579392740503], "input_correlations": [0.18093439357352387, -0.15084864814996155, 0.23738620164054733, -0.705414690648983, 0.5791920896238114, 0.0, 0.0, 0.0], "pre_activation_mean": -0.14599096775054932, "pre_activation_std": 1.7065147161483765}, "5": {"mean": 1.9302561283111572, "std": 1.2375937700271606, "fourier": [20.623207051159184, 21.453492231066836, 23.664916099463117, 26.99262844217951, 173.72305576875806], "input_correlations": [0.981080806453963, 0.40506368096870154, 0.23113577756976086, 0.04716300447784386, 0.29156239569490944, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8491494059562683, "pre_activation_std": 1.665404200553894}, "6": {"mean": 1.7255018949508667, "std": 1.07369065284729, "fourier": [18.285790905671494, 18.55912093931897, 20.208871585995585, 23.48646437734132, 155.29516072478145], "input_correlations": [0.9099381291117226, 0.5837449170050337, 0.42773312627201077, -0.17159847415599735, 0.0372444298180335, 0.0, 0.0, 0.0], "pre_activation_mean": 1.1872261762619019, "pre_activation_std": 2.2145261764526367}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.6622433066368103, "std": 2.16159725189209, "fourier": [36.64083659582325, 36.642343284663006, 37.16347489066017, 37.213946260751754, 59.601898953318596], "input_correlations": [0.4490694475285906, 0.9144906238248994, -0.3334020176055037, 0.2080759073592254, -0.17328460874623278, 0.9214201047127337, 0.9541428111699433, 0.0], "pre_activation_mean": 0.6622433066368103, "pre_activation_std": 2.16159725189209}, "1": {"mean": -1.1199718713760376, "std": 1.0229483842849731, "fourier": [16.953850388472972, 17.0015989410969, 19.217061447999782, 21.437712655610948, 100.79747296869755], "input_correlations": [-0.7821586197802969, -0.740298630529323, -0.0677156916718855, -0.1294189802752046, -0.13151301127876916, -0.904577044662138, -0.8362969418805327, 0.0], "pre_activation_mean": -1.1199718713760376, "pre_activation_std": 1.0229483842849731}, "2": {"mean": 1.5709315538406372, "std": 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60 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.44, "improved_accuracy": 0.98, "improvement": 0.54, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 9339, "learning_rate": 0.028907412749536947, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.0.bias": [
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"network.2.weight": [
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}
## Activation Signature
### 0
mean: [3.802665, 2.867511, 1.239660, 7.940421, 6.565820, 3.118170]
std: [3.628496, 2.716113, 1.800638, 7.404431, 6.032918, 2.947468]
fourier: [[52.916110, 61.975010, 62.268606, 73.005572, 342.239837], [39.225034, 46.763389, 46.817347, 55.636831, 258.075997], [27.220119, 28.288179, 31.715792, 35.979545, 111.569437], [107.586998, 126.734004, 127.159677, 149.295978, 714.637848], [87.317388, 103.891388, 103.909441, 123.452717, 590.923679], [42.454902, 50.724777, 50.749377, 60.124690, 280.635242]]
input_correlations: [[-0.745112, -0.084777, -0.181867, 0.639072, -0.281460, 0.000000, 0.000000, 0.000000], [-0.827188, -0.026244, -0.374999, 0.574652, -0.053152, 0.000000, 0.000000, 0.000000], [-0.544263, -0.119108, -0.726562, 0.599663, -0.011436, 0.000000, 0.000000, 0.000000], [-0.575246, -0.415040, 0.351443, -0.212296, 0.441502, 0.000000, 0.000000, 0.000000], [-0.821279, 0.020928, -0.207249, 0.592598, -0.009345, 0.000000, 0.000000, 0.000000], [-0.774629, -0.799346, -0.533734, -0.209748, -0.042043, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.886867, 0.716606, -0.158652, 0.066248, 0.345665, -1.297906]
pre_activation_std: [1.778792, 1.782202, 1.757225, 1.635766, 2.019176, 1.009599]
### 2
mean: [2.606702, 0.866641, 2.423931, -0.469821, -0.276929, -0.949406]
std: [2.486247, 1.091074, 2.074464, 0.644832, 0.866750, 1.574097]
fourier: [[39.199415, 39.316650, 40.300902, 41.410492, 234.603222], [17.474418, 17.758811, 19.565854, 20.658797, 77.997709], [30.712619, 34.304122, 34.673589, 38.999634, 218.153813], [9.225564, 10.140775, 10.216759, 11.104170, 42.283894], [12.673630, 13.661674, 13.847660, 14.733655, 24.923582], [24.256379, 24.460658, 29.027360, 30.692342, 85.446550]]
input_correlations: [[0.887056, 0.965280, 0.819946, 0.087685, 0.964067, -0.306448, 0.000000, 0.000000], [0.534581, 0.696378, 0.641555, 0.620049, 0.723865, -0.373813, 0.000000, 0.000000], [0.819847, 0.908348, 0.733166, 0.290720, 0.937812, -0.325928, 0.000000, 0.000000], [-0.925087, -0.883712, -0.782080, -0.061360, -0.849170, 0.450991, 0.000000, 0.000000], [-0.895840, -0.840274, -0.822262, -0.094760, -0.819084, 0.412660, 0.000000, 0.000000], [-0.755354, -0.853914, -0.812976, 0.571068, -0.785237, 0.003504, 0.000000, 0.000000]]
pre_activation_mean: [2.606702, 0.866641, 2.423931, -0.469821, -0.276929, -0.949406]
pre_activation_std: [2.486247, 1.091074, 2.074464, 0.644832, 0.866750, 1.574097]
### 4
mean: [3.156322, 3.006883, -0.471398, -0.683970, -0.615718, -0.328145]
std: [3.274679, 2.938663, 1.418771, 1.116810, 1.183157, 0.295359]
fourier: [[48.977795, 52.282037, 58.087030, 61.236537, 284.069056], [44.571926, 46.976175, 50.910979, 56.954939, 270.619428], [21.578587, 24.928235, 25.943155, 28.620606, 42.425812], [16.683734, 18.893925, 20.205849, 22.441004, 61.557278], [17.730879, 19.095384, 20.966467, 23.193678, 55.414663], [4.703914, 4.756711, 4.905671, 5.375635, 29.533064]]
input_correlations: [[0.962354, 0.917325, 0.994092, -0.650219, -0.747946, 0.179028, 0.000000, 0.000000], [0.958429, 0.909229, 0.993516, -0.661808, -0.760328, 0.205472, 0.000000, 0.000000], [-0.864114, -0.926260, -0.937485, 0.734192, 0.821284, -0.418760, 0.000000, 0.000000], [-0.849867, -0.943791, -0.924158, 0.670455, 0.765431, -0.457843, 0.000000, 0.000000], [-0.927919, -0.907223, -0.965456, 0.688719, 0.793981, -0.311153, 0.000000, 0.000000], [0.759959, 0.521665, 0.730074, -0.744053, -0.836431, 0.301006, 0.000000, 0.000000]]
pre_activation_mean: [3.156322, 3.006883, -0.471398, -0.683970, -0.615718, -0.328145]
pre_activation_std: [3.274679, 2.938663, 1.418771, 1.116810, 1.183157, 0.295359]
### 6
mean: [-1.248172, -1.243649, 3.559719, 1.945124, -0.894352, 2.791204]
std: [2.716449, 2.606248, 3.751136, 2.379918, 2.058051, 2.906687]
fourier: [[42.972133, 45.567088, 47.118248, 54.072708, 112.335521], [40.701134, 43.616890, 45.553817, 51.355373, 111.928396], [56.317182, 61.652992, 65.237776, 73.082848, 320.374695], [37.711030, 40.035217, 41.255218, 47.486925, 175.061147], [32.806561, 35.114196, 35.988473, 40.721877, 80.491703], [45.434685, 48.553450, 50.405783, 57.741438, 251.208399]]
input_correlations: [[-0.980422, -0.986488, 0.820214, 0.771051, 0.790464, -0.750276, 0.000000, 0.000000], [-0.984112, -0.989054, 0.809415, 0.759064, 0.778917, -0.747251, 0.000000, 0.000000], [0.995686, 0.998140, -0.754904, -0.699796, -0.721292, 0.743644, 0.000000, 0.000000], [0.982320, 0.988371, -0.813843, -0.764104, -0.784192, 0.744325, 0.000000, 0.000000], [-0.973440, -0.979764, 0.839495, 0.792838, 0.811381, -0.735672, 0.000000, 0.000000], [0.987253, 0.992364, -0.796669, -0.745238, -0.765819, 0.745786, 0.000000, 0.000000]]
pre_activation_mean: [-1.248172, -1.243649, 3.559719, 1.945124, -0.894352, 2.791204]
pre_activation_std: [2.716449, 2.606248, 3.751136, 2.379918, 2.058051, 2.906687]
### 8
mean: [-2.263537, 0.990494, -2.076701, 3.956013, 2.033248, 3.995704]
std: [4.325337, 2.078379, 4.276310, 5.098598, 3.567607, 5.219858]
fourier: [[70.451355, 74.170418, 75.084950, 89.202559, 203.718292], [35.027200, 35.618880, 35.822893, 42.835871, 89.144423], [69.938509, 73.348299, 74.207262, 88.143701, 186.903124], [80.050846, 86.888619, 88.615232, 103.719286, 356.041120], [59.414911, 61.029803, 61.813914, 73.723151, 182.992343], [84.084103, 88.989672, 90.941048, 106.908772, 359.613335]]
input_correlations: [[0.845073, 0.843606, -0.973185, -0.976830, 0.829331, -0.982717, 0.000000, 0.000000], [-0.887744, -0.886470, 0.950083, 0.954862, -0.874282, 0.963167, 0.000000, 0.000000], [0.850353, 0.848906, -0.970874, -0.974649, 0.834885, -0.980815, 0.000000, 0.000000], [-0.801735, -0.800086, 0.987903, 0.990207, -0.784293, 0.993951, 0.000000, 0.000000], [-0.872207, -0.870848, 0.959840, 0.964023, -0.857800, 0.971473, 0.000000, 0.000000], [-0.831128, -0.829581, 0.978896, 0.981748, -0.814875, 0.987017, 0.000000, 0.000000]]
pre_activation_mean: [-2.263537, 0.990494, -2.076701, 3.956013, 2.033248, 3.995704]
pre_activation_std: [4.325337, 2.078379, 4.276310, 5.098598, 3.567607, 5.219858]
### 10
mean: [3.399698, 2.490579, -1.872952, 7.359293, 5.949227, 2.714133]
std: [4.090296, 3.162800, 4.496623, 8.056923, 6.747984, 3.423256]
fourier: [[63.038877, 70.195055, 71.139933, 84.277129, 305.972796], [49.808863, 54.475452, 55.206379, 66.236575, 224.152102], [73.606943, 77.475398, 78.103855, 94.484827, 168.565661], [121.501894, 138.725391, 139.756826, 165.629244, 662.336282], [104.461747, 116.408921, 117.456694, 140.211029, 535.430462], [53.734647, 59.029349, 59.667373, 71.481937, 244.271961]]
input_correlations: [[-0.780504, 0.991264, -0.785002, 0.991275, 0.993100, 0.994266, 0.000000, 0.000000], [-0.806912, 0.984656, -0.811291, 0.984361, 0.987344, 0.988798, 0.000000, 0.000000], [0.852040, -0.967574, 0.855875, -0.967162, -0.971351, -0.973498, 0.000000, 0.000000], [-0.759938, 0.995046, -0.764677, 0.994923, 0.996419, 0.997236, 0.000000, 0.000000], [-0.788249, 0.989653, -0.792769, 0.989409, 0.991765, 0.992949, 0.000000, 0.000000], [-0.803610, 0.985691, -0.807991, 0.985408, 0.988216, 0.989630, 0.000000, 0.000000]]
pre_activation_mean: [3.399698, 2.490579, -1.872952, 7.359293, 5.949227, 2.714133]
pre_activation_std: [4.090296, 3.162800, 4.496623, 8.056923, 6.747984, 3.423256]
### 12
mean: [-14.495281]
std: [15.199811]
fourier: [[225.832229, 262.276719, 263.027524, 313.555180, 1304.575199]]
input_correlations: [[-0.998129, -0.999163, 0.781769, -0.998433, -0.999230, -0.999019, 0.000000, 0.000000]]
pre_activation_mean: [-14.495281]
pre_activation_std: [15.199811]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [3.802665, 2.867511, 1.239660, 7.940421, 6.565820, 3.118170]
std: [3.628496, 2.716113, 1.800638, 7.404431, 6.032918, 2.947468]
fourier: [[52.916110, 61.975010, 62.268606, 73.005572, 342.239837], [39.225034, 46.763389, 46.817347, 55.636831, 258.075997], [27.220119, 28.288179, 31.715792, 35.979545, 111.569437], [107.586998, 126.734004, 127.159677, 149.295978, 714.637848], [87.317388, 103.891388, 103.909441, 123.452717, 590.923679], [42.454902, 50.724777, 50.749377, 60.124690, 280.635242]]
input_correlations: [[-0.745112, -0.084777, -0.181867, 0.639072, -0.281460, 0.000000, 0.000000, 0.000000], [-0.827188, -0.026244, -0.374999, 0.574652, -0.053152, 0.000000, 0.000000, 0.000000], [-0.544263, -0.119108, -0.726562, 0.599663, -0.011436, 0.000000, 0.000000, 0.000000], [-0.575246, -0.415040, 0.351443, -0.212296, 0.441502, 0.000000, 0.000000, 0.000000], [-0.821279, 0.020928, -0.207249, 0.592598, -0.009345, 0.000000, 0.000000, 0.000000], [-0.774629, -0.799346, -0.533734, -0.209748, -0.042043, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.886867, 0.716606, -0.158652, 0.066248, 0.345665, -1.297906]
pre_activation_std: [1.778792, 1.782202, 1.757225, 1.635766, 2.019176, 1.009599]
### 2
mean: [2.606702, 0.866641, 2.423931, -0.469821, -0.276929, -0.949406]
std: [2.486247, 1.091074, 2.074464, 0.644832, 0.866750, 1.574097]
fourier: [[39.199415, 39.316650, 40.300902, 41.410492, 234.603222], [17.474418, 17.758811, 19.565854, 20.658797, 77.997709], [30.712619, 34.304122, 34.673589, 38.999634, 218.153813], [9.225564, 10.140775, 10.216759, 11.104170, 42.283894], [12.673630, 13.661674, 13.847660, 14.733655, 24.923582], [24.256379, 24.460658, 29.027360, 30.692342, 85.446550]]
input_correlations: [[0.887056, 0.965280, 0.819946, 0.087685, 0.964067, -0.306448, 0.000000, 0.000000], [0.534581, 0.696378, 0.641555, 0.620049, 0.723865, -0.373813, 0.000000, 0.000000], [0.819847, 0.908348, 0.733166, 0.290720, 0.937812, -0.325928, 0.000000, 0.000000], [-0.925087, -0.883712, -0.782080, -0.061360, -0.849170, 0.450991, 0.000000, 0.000000], [-0.895840, -0.840274, -0.822262, -0.094760, -0.819084, 0.412660, 0.000000, 0.000000], [-0.755354, -0.853914, -0.812976, 0.571068, -0.785237, 0.003504, 0.000000, 0.000000]]
pre_activation_mean: [2.606702, 0.866641, 2.423931, -0.469821, -0.276929, -0.949406]
pre_activation_std: [2.486247, 1.091074, 2.074464, 0.644832, 0.866750, 1.574097]
### 4
mean: [3.156322, 3.006883, -0.471398, -0.683970, -0.615718, -0.328145]
std: [3.274679, 2.938663, 1.418771, 1.116810, 1.183157, 0.295359]
fourier: [[48.977795, 52.282037, 58.087030, 61.236537, 284.069056], [44.571926, 46.976175, 50.910979, 56.954939, 270.619428], [21.578587, 24.928235, 25.943155, 28.620606, 42.425812], [16.683734, 18.893925, 20.205849, 22.441004, 61.557278], [17.730879, 19.095384, 20.966467, 23.193678, 55.414663], [4.703914, 4.756711, 4.905671, 5.375635, 29.533064]]
input_correlations: [[0.962354, 0.917325, 0.994092, -0.650219, -0.747946, 0.179028, 0.000000, 0.000000], [0.958429, 0.909229, 0.993516, -0.661808, -0.760328, 0.205472, 0.000000, 0.000000], [-0.864114, -0.926260, -0.937485, 0.734192, 0.821284, -0.418760, 0.000000, 0.000000], [-0.849867, -0.943791, -0.924158, 0.670455, 0.765431, -0.457843, 0.000000, 0.000000], [-0.927919, -0.907223, -0.965456, 0.688719, 0.793981, -0.311153, 0.000000, 0.000000], [0.759959, 0.521665, 0.730074, -0.744053, -0.836431, 0.301006, 0.000000, 0.000000]]
pre_activation_mean: [3.156322, 3.006883, -0.471398, -0.683970, -0.615718, -0.328145]
pre_activation_std: [3.274679, 2.938663, 1.418771, 1.116810, 1.183157, 0.295359]
### 6
mean: [-1.248172, -1.243649, 3.559719, 1.945124, -0.894352, 2.791204]
std: [2.716449, 2.606248, 3.751136, 2.379918, 2.058051, 2.906687]
fourier: [[42.972133, 45.567088, 47.118248, 54.072708, 112.335521], [40.701134, 43.616890, 45.553817, 51.355373, 111.928396], [56.317182, 61.652992, 65.237776, 73.082848, 320.374695], [37.711030, 40.035217, 41.255218, 47.486925, 175.061147], [32.806561, 35.114196, 35.988473, 40.721877, 80.491703], [45.434685, 48.553450, 50.405783, 57.741438, 251.208399]]
input_correlations: [[-0.980422, -0.986488, 0.820214, 0.771051, 0.790464, -0.750276, 0.000000, 0.000000], [-0.984112, -0.989054, 0.809415, 0.759064, 0.778917, -0.747251, 0.000000, 0.000000], [0.995686, 0.998140, -0.754904, -0.699796, -0.721292, 0.743644, 0.000000, 0.000000], [0.982320, 0.988371, -0.813843, -0.764104, -0.784192, 0.744325, 0.000000, 0.000000], [-0.973440, -0.979764, 0.839495, 0.792838, 0.811381, -0.735672, 0.000000, 0.000000], [0.987253, 0.992364, -0.796669, -0.745238, -0.765819, 0.745786, 0.000000, 0.000000]]
pre_activation_mean: [-1.248172, -1.243649, 3.559719, 1.945124, -0.894352, 2.791204]
pre_activation_std: [2.716449, 2.606248, 3.751136, 2.379918, 2.058051, 2.906687]
### 8
mean: [-2.263537, 0.990494, -2.076701, 3.956013, 2.033248, 3.995704]
std: [4.325337, 2.078379, 4.276310, 5.098598, 3.567607, 5.219858]
fourier: [[70.451355, 74.170418, 75.084950, 89.202559, 203.718292], [35.027200, 35.618880, 35.822893, 42.835871, 89.144423], [69.938509, 73.348299, 74.207262, 88.143701, 186.903124], [80.050846, 86.888619, 88.615232, 103.719286, 356.041120], [59.414911, 61.029803, 61.813914, 73.723151, 182.992343], [84.084103, 88.989672, 90.941048, 106.908772, 359.613335]]
input_correlations: [[0.845073, 0.843606, -0.973185, -0.976830, 0.829331, -0.982717, 0.000000, 0.000000], [-0.887744, -0.886470, 0.950083, 0.954862, -0.874282, 0.963167, 0.000000, 0.000000], [0.850353, 0.848906, -0.970874, -0.974649, 0.834885, -0.980815, 0.000000, 0.000000], [-0.801735, -0.800086, 0.987903, 0.990207, -0.784293, 0.993951, 0.000000, 0.000000], [-0.872207, -0.870848, 0.959840, 0.964023, -0.857800, 0.971473, 0.000000, 0.000000], [-0.831128, -0.829581, 0.978896, 0.981748, -0.814875, 0.987017, 0.000000, 0.000000]]
pre_activation_mean: [-2.263537, 0.990494, -2.076701, 3.956013, 2.033248, 3.995704]
pre_activation_std: [4.325337, 2.078379, 4.276310, 5.098598, 3.567607, 5.219858]
### 10
mean: [3.399698, 2.490579, -1.872952, 7.359293, 5.949227, 2.714133]
std: [4.090296, 3.162800, 4.496623, 8.056923, 6.747984, 3.423256]
fourier: [[63.038877, 70.195055, 71.139933, 84.277129, 305.972796], [49.808863, 54.475452, 55.206379, 66.236575, 224.152102], [73.606943, 77.475398, 78.103855, 94.484827, 168.565661], [121.501894, 138.725391, 139.756826, 165.629244, 662.336282], [104.461747, 116.408921, 117.456694, 140.211029, 535.430462], [53.734647, 59.029349, 59.667373, 71.481937, 244.271961]]
input_correlations: [[-0.780504, 0.991264, -0.785002, 0.991275, 0.993100, 0.994266, 0.000000, 0.000000], [-0.806912, 0.984656, -0.811291, 0.984361, 0.987344, 0.988798, 0.000000, 0.000000], [0.852040, -0.967574, 0.855875, -0.967162, -0.971351, -0.973498, 0.000000, 0.000000], [-0.759938, 0.995046, -0.764677, 0.994923, 0.996419, 0.997236, 0.000000, 0.000000], [-0.788249, 0.989653, -0.792769, 0.989409, 0.991765, 0.992949, 0.000000, 0.000000], [-0.803610, 0.985691, -0.807991, 0.985408, 0.988216, 0.989630, 0.000000, 0.000000]]
pre_activation_mean: [3.399698, 2.490579, -1.872952, 7.359293, 5.949227, 2.714133]
pre_activation_std: [4.090296, 3.162800, 4.496623, 8.056923, 6.747984, 3.423256]
### 12
mean: [-14.495281]
std: [15.199811]
fourier: [[225.832229, 262.276719, 263.027524, 313.555180, 1304.575199]]
input_correlations: [[-0.998129, -0.999163, 0.781769, -0.998433, -0.999230, -0.999019, 0.000000, 0.000000]]
pre_activation_mean: [-14.495281]
pre_activation_std: [15.199811]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 3.8026647567749023, "std": 3.6284964084625244, "fourier": [52.91611042427927, 61.9750102990497, 62.268606092421734, 73.00557189438422, 342.23983690328896], "input_correlations": [-0.7451118875351503, -0.08477720658914203, -0.181866652723046, 0.639071561872793, -0.2814604276157475, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8868669867515564, "pre_activation_std": 1.7787922620773315}, "1": {"mean": 2.867511034011841, "std": 2.7161130905151367, "fourier": [39.22503388581365, 46.76338909736018, 46.817347468912516, 55.63683077850165, 258.07599728927016], "input_correlations": [-0.8271876905204324, -0.026244268668406224, -0.3749987047915172, 0.5746517250360167, -0.05315167322583377, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7166061401367188, "pre_activation_std": 1.7822023630142212}, "2": {"mean": 1.239660382270813, "std": 1.800638198852539, "fourier": [27.220118686034635, 28.288178632554608, 31.715792358087292, 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"pre_activation_mean": 0.3456653654575348, "pre_activation_std": 2.0191762447357178}, "5": {"mean": 3.1181695461273193, "std": 2.947467565536499, "fourier": [42.454901707959365, 50.724776741664506, 50.749376859288304, 60.12469030818517, 280.6352415494621], "input_correlations": [-0.7746285436591244, -0.7993459537908317, -0.5337337885685368, -0.20974811345020855, -0.04204251842285484, 0.0, 0.0, 0.0], "pre_activation_mean": -1.2979063987731934, "pre_activation_std": 1.009598731994629}}, "layer_info": {"num_neurons": 6, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 2.6067020893096924, "std": 2.4862470626831055, "fourier": [39.19941465613468, 39.31664950913245, 40.300902038962874, 41.41049233114626, 234.60322174802423], "input_correlations": [0.8870561537595784, 0.9652803158358909, 0.8199455703437933, 0.08768494407469271, 0.9640667851918859, 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0.269795, 0.447309]], "network.10.bias": [0.080796, 0.025939, 0.606039, 0.20661, 0.501047, 0.094765], "network.12.weight": [[-0.563944, -0.543699, 0.615001, -0.647725, -0.698161, -0.617715]], "network.12.bias": [0.099225]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6984916031360626, "train_acc": 0.585, "val_loss": 0.7583299279212952, "val_acc": 0.44}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.682537168264389, "train_acc": 0.585, "val_loss": 0.7314627170562744, "val_acc": 0.44}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6714454293251038, "train_acc": 0.585, "val_loss": 0.7044888138771057, "val_acc": 0.44}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6668539047241211, "train_acc": 0.515, "val_loss": 0.6222271919250488, "val_acc": 0.44}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5623001456260681, "train_acc": 0.635, "val_loss": 0.4588010907173157, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.409513458609581, "train_acc": 0.875, "val_loss": 0.33154982328414917, "val_acc": 0.92}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.30219556391239166, "train_acc": 0.92, "val_loss": 0.2660992741584778, "val_acc": 0.92}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.24073948711156845, "train_acc": 0.925, "val_loss": 0.22390443086624146, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.1999075561761856, "train_acc": 0.925, "val_loss": 0.14016783237457275, "val_acc": 0.96}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.21344657242298126, "train_acc": 0.935, "val_loss": 0.1274031102657318, "val_acc": 0.96}, {"stage": "improved", "epoch": 7, "global_epoch": 10, "train_loss": 0.19054584950208664, "train_acc": 0.95, "val_loss": 0.14170360565185547, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 11, "train_loss": 0.20502261817455292, "train_acc": 0.94, "val_loss": 0.11635006964206696, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 12, "train_loss": 0.20759690552949905, "train_acc": 0.935, "val_loss": 0.08868438005447388, "val_acc": 0.98}], "summary": {"total_epochs": 13, "degraded_epochs": 3, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7583299279212952, "final_val_loss": 0.7044888138771057, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.6222271919250488, "final_val_loss": 0.08868438005447388, "initial_val_acc": 0.44, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 12}, "improvement": 0.54, "first_improvement_epoch": 2}} |
61 | {"target_pattern": "ends_with", "degraded_accuracy": 0.46, "improved_accuracy": 0.88, "improvement": 0.42, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 6958, "learning_rate": 0.08815082734579661, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "ends_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["ends_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [3.256516, 0.000000, 5.636145, 0.000000, 0.681480, 0.000000, 3.124261, 1.105834]
std: [4.330008, 0.000000, 7.487946, 0.000000, 0.749804, 0.000000, 4.312522, 1.511974]
fourier: [[70.065824, 70.148551, 89.789709, 100.227680, 293.086407], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [123.252833, 123.672250, 158.654758, 170.455588, 507.253028], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [11.939029, 12.452962, 13.064187, 18.147369, 61.333186], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [69.745391, 71.511208, 91.409945, 96.648933, 281.183494], [23.941478, 24.104010, 30.071129, 34.188716, 99.525061]]
input_correlations: [[0.849519, 0.101976, 0.203862, -0.185613, 0.598027, 0.000000, 0.000000, 0.000000], [0.700236, -0.033604, 0.250672, -0.356283, 0.684595, 0.000000, 0.000000, 0.000000], [-0.575756, -0.871748, -0.445915, -0.484281, -0.332678, 0.000000, 0.000000, 0.000000], [0.038353, 0.344726, -0.397601, 0.481851, -0.697446, 0.000000, 0.000000, 0.000000], [-0.593989, -0.327343, -0.204114, 0.143789, 0.666761, 0.000000, 0.000000, 0.000000], [-0.494043, -0.935450, -0.173845, -0.520156, 0.025074, 0.000000, 0.000000, 0.000000], [0.282645, -0.549011, 0.146476, -0.415851, 0.691912, 0.000000, 0.000000, 0.000000], [-0.346864, -0.192573, 0.077949, 0.195697, 0.857600, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.100529, 0.291524, -3.168447, 0.168292, -0.361432, -2.825307, -0.314102, 0.961037]
pre_activation_std: [2.199669, 2.271554, 1.869929, 2.231020, 2.423240, 2.329055, 1.938197, 2.123483]
### 2
mean: [-0.662238, 2.356134, 0.815773, -2.454646, -2.537159, -1.296464, 0.765054, -3.720372]
std: [2.402633, 3.262714, 2.075141, 2.421240, 2.212290, 1.291742, 2.436396, 2.790103]
fourier: [[39.335435, 41.137227, 44.571723, 54.376127, 59.601442], [52.607754, 54.890259, 62.780282, 74.219136, 212.052071], [35.966095, 36.549392, 37.417742, 56.718460, 73.419599], [41.914265, 42.570551, 47.384785, 52.484812, 220.918114], [38.780512, 42.470542, 46.536279, 47.366573, 228.344353], [20.897406, 22.105141, 22.168982, 23.858441, 116.681771], [35.617929, 39.451574, 39.460678, 52.393449, 68.854841], [46.446946, 52.521961, 59.954820, 60.581562, 334.833485]]
input_correlations: [[-0.776176, -0.840024, 0.000000, 0.543306, -0.629305, 0.074440, -0.785470, -0.806443], [0.787495, 0.866435, 0.000000, -0.488274, 0.624811, -0.075307, 0.853400, 0.805336], [0.743543, 0.699753, 0.000000, 0.208924, -0.519928, -0.081200, 0.346893, -0.281925], [-0.813632, -0.883296, 0.000000, 0.227840, -0.612804, 0.113393, -0.869212, -0.744859], [-0.905390, -0.928500, 0.000000, 0.174958, -0.491996, 0.132817, -0.779683, -0.660098], [-0.449611, -0.470358, 0.000000, -0.257391, -0.711908, 0.189327, -0.517407, -0.716973], [0.469533, 0.573152, 0.000000, -0.633498, 0.842387, -0.039830, 0.709857, 0.951293], [-0.818532, -0.860814, 0.000000, 0.131142, -0.599816, 0.138546, -0.812611, -0.743673]]
pre_activation_mean: [-0.662238, 2.356134, 0.815773, -2.454646, -2.537159, -1.296464, 0.765054, -3.720372]
pre_activation_std: [2.402633, 3.262714, 2.075141, 2.421240, 2.212290, 1.291742, 2.436396, 2.790103]
### 4
mean: [1.808704, -1.348419, -0.757438, 2.064690, 2.038658, 0.861892, -1.616990, -0.221518]
std: [3.209935, 2.835046, 2.279986, 2.655351, 3.092007, 1.813104, 1.179103, 0.917444]
fourier: [[53.725089, 55.207022, 68.914348, 71.546959, 162.783365], [45.418123, 47.381623, 58.633306, 65.186300, 121.357692], [38.285861, 38.904257, 50.472059, 50.950389, 68.169415], [38.569692, 39.520265, 49.493008, 62.456553, 185.822126], [51.609391, 53.004426, 67.812336, 68.237220, 183.479239], [26.921680, 31.334762, 35.853548, 39.940266, 77.570240], [17.735038, 18.612813, 23.253585, 27.944841, 145.529118], [14.486869, 14.813494, 16.426907, 19.936591, 20.280467]]
input_correlations: [[-0.676466, 0.986511, 0.614662, 0.000000, 0.000000, -0.300777, 0.813111, 0.000000], [0.652629, -0.996460, -0.524501, 0.000000, 0.000000, 0.281679, -0.879908, 0.000000], [0.639943, -0.978015, -0.669133, 0.000000, 0.000000, 0.309783, -0.784192, 0.000000], [-0.528355, 0.981319, 0.397166, 0.000000, 0.000000, -0.278564, 0.951636, 0.000000], [-0.624357, 0.972175, 0.700376, 0.000000, 0.000000, -0.319284, 0.759664, 0.000000], [-0.478986, 0.870508, 0.878944, 0.000000, 0.000000, -0.340694, 0.560964, 0.000000], [0.418998, -0.972123, -0.572042, 0.000000, 0.000000, 0.337145, -0.872285, 0.000000], [-0.684267, 0.761377, 0.857155, 0.000000, 0.000000, -0.186942, 0.380367, 0.000000]]
pre_activation_mean: [1.808704, -1.348419, -0.757438, 2.064690, 2.038658, 0.861892, -1.616990, -0.221518]
pre_activation_std: [3.209935, 2.835046, 2.279986, 2.655351, 3.092007, 1.813104, 1.179103, 0.917444]
### 6
mean: [3.551518, 2.536873, -2.158936, 2.194836, -1.974301, -1.017477, 2.383756, -0.891015]
std: [4.209949, 3.987703, 2.286874, 2.905210, 4.699175, 0.978438, 3.460544, 0.426465]
fourier: [[65.609339, 68.192867, 86.339546, 95.208255, 319.636583], [65.970743, 66.769617, 85.461309, 90.057946, 228.318535], [37.854085, 37.909160, 48.939986, 51.747385, 194.304232], [44.191801, 46.301199, 57.370911, 67.425146, 197.535225], [79.384352, 79.521252, 103.184612, 103.815994, 177.687082], [15.355837, 15.613271, 19.876227, 23.053741, 91.572951], [54.700570, 56.878869, 71.191387, 78.947148, 214.538068], [6.380644, 6.647052, 7.331187, 10.343964, 80.191364]]
input_correlations: [[0.984887, -0.564649, -0.641380, 0.898740, 0.995352, 0.969255, 0.000000, 0.822274], [0.994247, -0.679473, -0.747206, 0.966659, 0.982689, 0.878905, 0.000000, 0.660980], [-0.998358, 0.651533, 0.721989, -0.938108, -0.997773, -0.928485, 0.000000, -0.744760], [0.970761, -0.633820, -0.694642, 0.995051, 0.941724, 0.797465, 0.000000, 0.539049], [-0.995168, 0.691478, 0.758911, -0.937740, -0.993769, -0.916301, 0.000000, -0.727080], [-0.995390, 0.594506, 0.674471, -0.974409, -0.980600, -0.878713, 0.000000, -0.660555], [0.980386, -0.669702, -0.731803, 0.986325, 0.957203, 0.823433, 0.000000, 0.578019], [-0.926582, 0.312311, 0.402466, -0.934052, -0.909907, -0.843931, 0.000000, -0.642763]]
pre_activation_mean: [3.551518, 2.536873, -2.158936, 2.194836, -1.974301, -1.017477, 2.383756, -0.891015]
pre_activation_std: [4.209949, 3.987703, 2.286874, 2.905210, 4.699175, 0.978438, 3.460544, 0.426465]
### 8
mean: [3.256516, -3.385869, 5.353532, -2.087245, -3.415262, -2.467207, 3.008887, 1.105589]
std: [4.330008, 3.437048, 7.706388, 1.792193, 6.143623, 2.481263, 4.397160, 1.512154]
fourier: [[70.065824, 70.148551, 89.789709, 100.227680, 293.086407], [53.538378, 55.322285, 69.179540, 79.816210, 304.728200], [128.382939, 128.478124, 166.120898, 173.442436, 481.817870], [27.875330, 28.132244, 35.464060, 42.344371, 187.852077], [103.071211, 103.731284, 133.979051, 136.711762, 307.373537], [38.602732, 39.329017, 48.214720, 58.834761, 222.048615], [71.627962, 73.568358, 94.605242, 97.784438, 270.799846], [23.947322, 24.123612, 30.083185, 34.199834, 99.503011]]
input_correlations: [[0.979930, 0.998857, 0.000000, 0.978664, -0.679930, 0.000000, 0.987514, 0.000000], [-0.942848, -0.994742, 0.000000, -0.997634, 0.677142, 0.000000, -0.999715, 0.000000], [0.978395, 0.997015, 0.000000, 0.973866, -0.720749, 0.000000, 0.984180, 0.000000], [-0.983901, -0.994680, 0.000000, -0.971909, 0.623562, 0.000000, -0.981131, 0.000000], [-0.970202, -0.996524, 0.000000, -0.977332, 0.740356, 0.000000, -0.986786, 0.000000], [-0.989900, -0.987248, 0.000000, -0.956477, 0.592511, 0.000000, -0.967843, 0.000000], [0.995905, 0.982826, 0.000000, 0.938935, -0.686271, 0.000000, 0.955328, 0.000000], [0.997765, 0.953778, 0.000000, 0.894900, -0.582474, 0.000000, 0.914372, 0.000000]]
pre_activation_mean: [3.256516, -3.385869, 5.353532, -2.087245, -3.415262, -2.467207, 3.008887, 1.105589]
pre_activation_std: [4.330008, 3.437048, 7.706388, 1.792193, 6.143623, 2.481263, 4.397160, 1.512154]
### 10
mean: [-4.633692]
std: [7.393846]
fourier: [[122.609883, 123.288569, 158.667537, 166.785717, 417.032285]]
input_correlations: [[-0.998568, 0.000000, -0.999666, 0.000000, 0.699403, 0.000000, -0.991725, -0.966284]]
pre_activation_mean: [-4.633692]
pre_activation_std: [7.393846]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| ends_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [3.256516, 0.000000, 5.636145, 0.000000, 0.681480, 0.000000, 3.124261, 1.105834]
std: [4.330008, 0.000000, 7.487946, 0.000000, 0.749804, 0.000000, 4.312522, 1.511974]
fourier: [[70.065824, 70.148551, 89.789709, 100.227680, 293.086407], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [123.252833, 123.672250, 158.654758, 170.455588, 507.253028], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [11.939029, 12.452962, 13.064187, 18.147369, 61.333186], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [69.745391, 71.511208, 91.409945, 96.648933, 281.183494], [23.941478, 24.104010, 30.071129, 34.188716, 99.525061]]
input_correlations: [[0.849519, 0.101976, 0.203862, -0.185613, 0.598027, 0.000000, 0.000000, 0.000000], [0.700236, -0.033604, 0.250672, -0.356283, 0.684595, 0.000000, 0.000000, 0.000000], [-0.575756, -0.871748, -0.445915, -0.484281, -0.332678, 0.000000, 0.000000, 0.000000], [0.038353, 0.344726, -0.397601, 0.481851, -0.697446, 0.000000, 0.000000, 0.000000], [-0.593989, -0.327343, -0.204114, 0.143789, 0.666761, 0.000000, 0.000000, 0.000000], [-0.494043, -0.935450, -0.173845, -0.520156, 0.025074, 0.000000, 0.000000, 0.000000], [0.282645, -0.549011, 0.146476, -0.415851, 0.691912, 0.000000, 0.000000, 0.000000], [-0.346864, -0.192573, 0.077949, 0.195697, 0.857600, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.100529, 0.291524, -3.168447, 0.168292, -0.361432, -2.825307, -0.314102, 0.961037]
pre_activation_std: [2.199669, 2.271554, 1.869929, 2.231020, 2.423240, 2.329055, 1.938197, 2.123483]
### 2
mean: [-0.662238, 2.356134, 0.815773, -2.454646, -2.537159, -1.296464, 0.765054, -3.720372]
std: [2.402633, 3.262714, 2.075141, 2.421240, 2.212290, 1.291742, 2.436396, 2.790103]
fourier: [[39.335435, 41.137227, 44.571723, 54.376127, 59.601442], [52.607754, 54.890259, 62.780282, 74.219136, 212.052071], [35.966095, 36.549392, 37.417742, 56.718460, 73.419599], [41.914265, 42.570551, 47.384785, 52.484812, 220.918114], [38.780512, 42.470542, 46.536279, 47.366573, 228.344353], [20.897406, 22.105141, 22.168982, 23.858441, 116.681771], [35.617929, 39.451574, 39.460678, 52.393449, 68.854841], [46.446946, 52.521961, 59.954820, 60.581562, 334.833485]]
input_correlations: [[-0.776176, -0.840024, 0.000000, 0.543306, -0.629305, 0.074440, -0.785470, -0.806443], [0.787495, 0.866435, 0.000000, -0.488274, 0.624811, -0.075307, 0.853400, 0.805336], [0.743543, 0.699753, 0.000000, 0.208924, -0.519928, -0.081200, 0.346893, -0.281925], [-0.813632, -0.883296, 0.000000, 0.227840, -0.612804, 0.113393, -0.869212, -0.744859], [-0.905390, -0.928500, 0.000000, 0.174958, -0.491996, 0.132817, -0.779683, -0.660098], [-0.449611, -0.470358, 0.000000, -0.257391, -0.711908, 0.189327, -0.517407, -0.716973], [0.469533, 0.573152, 0.000000, -0.633498, 0.842387, -0.039830, 0.709857, 0.951293], [-0.818532, -0.860814, 0.000000, 0.131142, -0.599816, 0.138546, -0.812611, -0.743673]]
pre_activation_mean: [-0.662238, 2.356134, 0.815773, -2.454646, -2.537159, -1.296464, 0.765054, -3.720372]
pre_activation_std: [2.402633, 3.262714, 2.075141, 2.421240, 2.212290, 1.291742, 2.436396, 2.790103]
### 4
mean: [1.808704, -1.348419, -0.757438, 2.064690, 2.038658, 0.861892, -1.616990, -0.221518]
std: [3.209935, 2.835046, 2.279986, 2.655351, 3.092007, 1.813104, 1.179103, 0.917444]
fourier: [[53.725089, 55.207022, 68.914348, 71.546959, 162.783365], [45.418123, 47.381623, 58.633306, 65.186300, 121.357692], [38.285861, 38.904257, 50.472059, 50.950389, 68.169415], [38.569692, 39.520265, 49.493008, 62.456553, 185.822126], [51.609391, 53.004426, 67.812336, 68.237220, 183.479239], [26.921680, 31.334762, 35.853548, 39.940266, 77.570240], [17.735038, 18.612813, 23.253585, 27.944841, 145.529118], [14.486869, 14.813494, 16.426907, 19.936591, 20.280467]]
input_correlations: [[-0.676466, 0.986511, 0.614662, 0.000000, 0.000000, -0.300777, 0.813111, 0.000000], [0.652629, -0.996460, -0.524501, 0.000000, 0.000000, 0.281679, -0.879908, 0.000000], [0.639943, -0.978015, -0.669133, 0.000000, 0.000000, 0.309783, -0.784192, 0.000000], [-0.528355, 0.981319, 0.397166, 0.000000, 0.000000, -0.278564, 0.951636, 0.000000], [-0.624357, 0.972175, 0.700376, 0.000000, 0.000000, -0.319284, 0.759664, 0.000000], [-0.478986, 0.870508, 0.878944, 0.000000, 0.000000, -0.340694, 0.560964, 0.000000], [0.418998, -0.972123, -0.572042, 0.000000, 0.000000, 0.337145, -0.872285, 0.000000], [-0.684267, 0.761377, 0.857155, 0.000000, 0.000000, -0.186942, 0.380367, 0.000000]]
pre_activation_mean: [1.808704, -1.348419, -0.757438, 2.064690, 2.038658, 0.861892, -1.616990, -0.221518]
pre_activation_std: [3.209935, 2.835046, 2.279986, 2.655351, 3.092007, 1.813104, 1.179103, 0.917444]
### 6
mean: [3.551518, 2.536873, -2.158936, 2.194836, -1.974301, -1.017477, 2.383756, -0.891015]
std: [4.209949, 3.987703, 2.286874, 2.905210, 4.699175, 0.978438, 3.460544, 0.426465]
fourier: [[65.609339, 68.192867, 86.339546, 95.208255, 319.636583], [65.970743, 66.769617, 85.461309, 90.057946, 228.318535], [37.854085, 37.909160, 48.939986, 51.747385, 194.304232], [44.191801, 46.301199, 57.370911, 67.425146, 197.535225], [79.384352, 79.521252, 103.184612, 103.815994, 177.687082], [15.355837, 15.613271, 19.876227, 23.053741, 91.572951], [54.700570, 56.878869, 71.191387, 78.947148, 214.538068], [6.380644, 6.647052, 7.331187, 10.343964, 80.191364]]
input_correlations: [[0.984887, -0.564649, -0.641380, 0.898740, 0.995352, 0.969255, 0.000000, 0.822274], [0.994247, -0.679473, -0.747206, 0.966659, 0.982689, 0.878905, 0.000000, 0.660980], [-0.998358, 0.651533, 0.721989, -0.938108, -0.997773, -0.928485, 0.000000, -0.744760], [0.970761, -0.633820, -0.694642, 0.995051, 0.941724, 0.797465, 0.000000, 0.539049], [-0.995168, 0.691478, 0.758911, -0.937740, -0.993769, -0.916301, 0.000000, -0.727080], [-0.995390, 0.594506, 0.674471, -0.974409, -0.980600, -0.878713, 0.000000, -0.660555], [0.980386, -0.669702, -0.731803, 0.986325, 0.957203, 0.823433, 0.000000, 0.578019], [-0.926582, 0.312311, 0.402466, -0.934052, -0.909907, -0.843931, 0.000000, -0.642763]]
pre_activation_mean: [3.551518, 2.536873, -2.158936, 2.194836, -1.974301, -1.017477, 2.383756, -0.891015]
pre_activation_std: [4.209949, 3.987703, 2.286874, 2.905210, 4.699175, 0.978438, 3.460544, 0.426465]
### 8
mean: [3.256516, -3.385869, 5.353532, -2.087245, -3.415262, -2.467207, 3.008887, 1.105589]
std: [4.330008, 3.437048, 7.706388, 1.792193, 6.143623, 2.481263, 4.397160, 1.512154]
fourier: [[70.065824, 70.148551, 89.789709, 100.227680, 293.086407], [53.538378, 55.322285, 69.179540, 79.816210, 304.728200], [128.382939, 128.478124, 166.120898, 173.442436, 481.817870], [27.875330, 28.132244, 35.464060, 42.344371, 187.852077], [103.071211, 103.731284, 133.979051, 136.711762, 307.373537], [38.602732, 39.329017, 48.214720, 58.834761, 222.048615], [71.627962, 73.568358, 94.605242, 97.784438, 270.799846], [23.947322, 24.123612, 30.083185, 34.199834, 99.503011]]
input_correlations: [[0.979930, 0.998857, 0.000000, 0.978664, -0.679930, 0.000000, 0.987514, 0.000000], [-0.942848, -0.994742, 0.000000, -0.997634, 0.677142, 0.000000, -0.999715, 0.000000], [0.978395, 0.997015, 0.000000, 0.973866, -0.720749, 0.000000, 0.984180, 0.000000], [-0.983901, -0.994680, 0.000000, -0.971909, 0.623562, 0.000000, -0.981131, 0.000000], [-0.970202, -0.996524, 0.000000, -0.977332, 0.740356, 0.000000, -0.986786, 0.000000], [-0.989900, -0.987248, 0.000000, -0.956477, 0.592511, 0.000000, -0.967843, 0.000000], [0.995905, 0.982826, 0.000000, 0.938935, -0.686271, 0.000000, 0.955328, 0.000000], [0.997765, 0.953778, 0.000000, 0.894900, -0.582474, 0.000000, 0.914372, 0.000000]]
pre_activation_mean: [3.256516, -3.385869, 5.353532, -2.087245, -3.415262, -2.467207, 3.008887, 1.105589]
pre_activation_std: [4.330008, 3.437048, 7.706388, 1.792193, 6.143623, 2.481263, 4.397160, 1.512154]
### 10
mean: [-4.633692]
std: [7.393846]
fourier: [[122.609883, 123.288569, 158.667537, 166.785717, 417.032285]]
input_correlations: [[-0.998568, 0.000000, -0.999666, 0.000000, 0.699403, 0.000000, -0.991725, -0.966284]]
pre_activation_mean: [-4.633692]
pre_activation_std: [7.393846]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
ends_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 3.2565157413482666, "std": 4.330008029937744, "fourier": [70.06582435156233, 70.14855113525465, 89.7897091928845, 100.22768049484358, 293.0864066630602], "input_correlations": [0.849518524146904, 0.10197552623450074, 0.2038615580219229, -0.1856131418894042, 0.59802735633949, 0.0, 0.0, 0.0], "pre_activation_mean": 1.100529432296753, "pre_activation_std": 2.1996688842773438}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.7002359196419586, -0.0336037405112548, 0.25067184445202456, -0.35628252184834625, 0.684594840396293, 0.0, 0.0, 0.0], "pre_activation_mean": 0.2915240526199341, "pre_activation_std": 2.271554470062256}, "2": {"mean": 5.636145114898682, "std": 7.487946033477783, "fourier": [123.25283266995196, 123.67225029389326, 158.65475808071474, 170.45558796081883, 507.2530282139778], "input_correlations": [-0.5757559013099833, -0.8717481871713153, 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{"initial_val_loss": 0.6952873468399048, "final_val_loss": 0.5740241408348083, "initial_val_acc": 0.46, "final_val_acc": 0.46, "best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.4574865400791168, "final_val_loss": 0.5844280123710632, "initial_val_acc": 0.84, "final_val_acc": 0.7, "best_val_acc": 0.88, "best_epoch": 6}, "improvement": 0.42, "first_improvement_epoch": 2}} |
62 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.62, "improved_accuracy": 0.98, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7617, "learning_rate": 0.01839529955470709, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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0.236707,
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],
[
0.065442,
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0.051238,
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-0.414669,
0.371446
],
[
0.389222,
-0.150459,
0.33783,
-0.170149,
0.123372,
0.361944,
-0.197692
],
[
0.395799,
0.326928,
-0.35589,
-0.421844,
-0.163547,
0.495102,
0.152197
],
[
-0.109064,
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0.11157,
-0.180333,
0.10156,
0.549988,
-0.17119
]
],
"network.6.bias": [
0.155359,
0.184671,
0.122612,
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0.097791,
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0.075613,
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]
],
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"network.10.weight": [
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0.126988,
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"network.12.bias": [
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}
## Activation Signature
### 0
mean: [-0.088049, 0.449142, 0.087925, 1.363623, 0.482959, -0.123964, 0.446899]
std: [0.116713, 0.353269, 0.176208, 0.893047, 0.343762, 0.061087, 0.376195]
fourier: [[1.849358, 1.921519, 2.244057, 2.288258, 7.924400], [5.261816, 5.666017, 5.914747, 6.822509, 40.422826], [2.571650, 2.759375, 2.959365, 3.423333, 7.913211], [13.974581, 14.879220, 15.130912, 17.088922, 122.726038], [5.279954, 5.694263, 5.810160, 6.533958, 43.466310], [0.916636, 0.994607, 1.268962, 1.292091, 11.156765], [5.468469, 6.075421, 6.418908, 7.291954, 40.220923]]
input_correlations: [[-0.202766, -0.508176, 0.295094, -0.279481, 0.735852, 0.000000, 0.000000, 0.000000], [-0.458600, 0.297995, -0.372124, -0.238302, -0.729003, 0.000000, 0.000000, 0.000000], [-0.422455, 0.103996, 0.679818, -0.063176, -0.157723, 0.000000, 0.000000, 0.000000], [0.874029, 0.520055, 0.509526, -0.280726, 0.023482, 0.000000, 0.000000, 0.000000], [-0.836236, -0.682384, -0.468796, -0.241100, 0.073708, 0.000000, 0.000000, 0.000000], [0.411811, 0.213105, 0.633978, 0.523710, 0.726904, 0.000000, 0.000000, 0.000000], [-0.073978, 0.550009, -0.325761, 0.851305, -0.130603, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.454666, -0.159795, 0.748476, 0.809676, -0.961569, 3.075558, 1.035097]
pre_activation_std: [0.895418, 1.093730, 1.018420, 1.512975, 1.236501, 2.003177, 1.207464]
### 2
mean: [-0.540116, 2.011998, 0.037421, -0.759749, -0.410751, 0.213401, 0.081365]
std: [0.388075, 1.181986, 0.484282, 0.811297, 0.909610, 0.850905, 0.536604]
fourier: [[6.271389, 6.445447, 7.513611, 7.948951, 48.610465], [16.371883, 17.311741, 20.706095, 22.193888, 181.079812], [6.991198, 7.205021, 7.940453, 9.037059, 11.420406], [12.861632, 14.538492, 14.644415, 16.520022, 68.377369], [15.438617, 16.383358, 16.863630, 18.603545, 36.967564], [13.306598, 13.623515, 14.504406, 16.607911, 19.206093], [7.672415, 7.703931, 8.765773, 9.217314, 9.462837]]
input_correlations: [[0.136267, 0.239208, 0.406454, -0.584197, 0.087232, -0.668676, -0.592893, 0.000000], [0.299329, -0.125353, 0.296112, -0.351579, -0.148043, 0.679665, 0.581198, 0.000000], [0.415286, -0.680270, -0.080475, 0.542607, 0.059603, 0.893173, -0.007787, 0.000000], [0.052938, 0.347775, 0.271690, -0.772358, 0.115699, -0.724018, -0.306424, 0.000000], [-0.881994, 0.530879, 0.176911, -0.106016, -0.400099, -0.668927, 0.317043, 0.000000], [-0.484953, -0.152463, -0.507313, 0.767200, -0.101504, 0.222446, 0.289239, 0.000000], [-0.219202, -0.002562, -0.106534, 0.881794, -0.006674, -0.096833, -0.389647, 0.000000]]
pre_activation_mean: [-0.540116, 2.011998, 0.037421, -0.759749, -0.410751, 0.213401, 0.081365]
pre_activation_std: [0.388075, 1.181986, 0.484282, 0.811297, 0.909610, 0.850905, 0.536604]
### 4
mean: [0.326604, 0.417188, -0.437119, 0.080921, -0.205200, 0.555456, 0.125859]
std: [0.227038, 0.527392, 0.368475, 0.704274, 0.104040, 0.676746, 0.433024]
fourier: [[3.410935, 3.984678, 4.123270, 4.297241, 29.394341], [7.989397, 8.222094, 8.994240, 9.746718, 37.546925], [6.068376, 6.274465, 7.059985, 7.926293, 39.340701], [11.073125, 11.307071, 11.437676, 11.840450, 14.150353], [1.504224, 1.557871, 1.612465, 1.822907, 18.467999], [10.214469, 10.368758, 12.364483, 12.818437, 49.991005], [6.855482, 7.185698, 7.419816, 8.118155, 11.327277]]
input_correlations: [[0.226309, 0.446814, -0.321001, -0.116287, 0.107830, -0.945062, -0.895762, 0.000000], [-0.319741, 0.958748, 0.096514, -0.568529, 0.182903, -0.511423, -0.791182, 0.000000], [0.488772, -0.405227, -0.863176, 0.240763, 0.269410, -0.719332, -0.342291, 0.000000], [-0.000351, -0.671747, 0.351395, 0.379335, -0.166320, 0.891075, 0.953768, 0.000000], [-0.412656, 0.876474, 0.407681, -0.414883, 0.396267, 0.010649, -0.369422, 0.000000], [-0.162485, 0.851191, -0.118753, -0.495881, 0.140152, -0.737537, -0.904224, 0.000000], [-0.236295, -0.444964, 0.483605, 0.184663, -0.051660, 0.980025, 0.899249, 0.000000]]
pre_activation_mean: [0.326604, 0.417188, -0.437119, 0.080921, -0.205200, 0.555456, 0.125859]
pre_activation_std: [0.227038, 0.527392, 0.368475, 0.704274, 0.104040, 0.676746, 0.433024]
### 6
mean: [-0.225101, 0.090945, 0.273217, -0.420095, 0.532541, 0.560486, 0.807619]
std: [0.400743, 0.256173, 0.509514, 0.442486, 0.310417, 0.546441, 0.489540]
fourier: [[6.183899, 6.377390, 7.356409, 7.610076, 20.259126], [4.056975, 4.134683, 4.249574, 5.045661, 8.185084], [7.718723, 8.222359, 8.399230, 9.959420, 24.589552], [6.830472, 7.146303, 8.053677, 8.238610, 37.808543], [4.966840, 4.967445, 4.996653, 6.163116, 47.928678], [8.296821, 8.405375, 9.999210, 10.156112, 50.443776], [7.492043, 7.789463, 8.914808, 8.972597, 72.685707]]
input_correlations: [[-0.817068, -0.872986, 0.189283, 0.875124, -0.532604, -0.944359, 0.830189, 0.000000], [-0.921652, -0.689788, -0.056043, 0.979504, -0.334036, -0.796253, 0.955693, 0.000000], [0.904012, 0.730719, -0.009871, -0.971064, 0.373055, 0.826354, -0.941764, 0.000000], [-0.759034, -0.915289, 0.215338, 0.834431, -0.605344, -0.965742, 0.779938, 0.000000], [0.936030, 0.683542, 0.079827, -0.968363, 0.317446, 0.799882, -0.959749, 0.000000], [0.772366, 0.907572, -0.239063, -0.850031, 0.591976, 0.958149, -0.789525, 0.000000], [0.732035, 0.929245, -0.261154, -0.814129, 0.620766, 0.975188, -0.754590, 0.000000]]
pre_activation_mean: [-0.225101, 0.090945, 0.273217, -0.420095, 0.532541, 0.560486, 0.807619]
pre_activation_std: [0.400743, 0.256173, 0.509514, 0.442486, 0.310417, 0.546441, 0.489540]
### 8
mean: [0.457277, 0.273847, -0.244454, 0.056428, 1.090378, 0.815767, 0.935883]
std: [0.387502, 0.305457, 0.389701, 0.198027, 0.761704, 0.438109, 0.528300]
fourier: [[6.244149, 6.606831, 7.151115, 7.282494, 41.154965], [4.859521, 5.164297, 5.636452, 5.704882, 24.646203], [6.244570, 6.301082, 7.028727, 7.418509, 22.000842], [2.854446, 2.897833, 3.128001, 3.803108, 5.078517], [12.030297, 12.421579, 13.927671, 14.240438, 98.134040], [6.812491, 7.088703, 7.989990, 8.129049, 73.419015], [8.303325, 8.719216, 9.739650, 9.761599, 84.229436]]
input_correlations: [[-0.885075, -0.883768, 0.991905, -0.822078, 0.973956, 0.959688, 0.968948, 0.000000], [-0.882476, -0.877737, 0.990292, -0.819884, 0.966348, 0.967354, 0.976580, 0.000000], [0.912952, 0.902786, -0.980935, 0.857950, -0.968953, -0.953864, -0.966341, 0.000000], [0.648614, 0.632563, -0.942120, 0.556226, -0.807644, -0.987708, -0.978213, 0.000000], [-0.895677, -0.885320, 0.984295, -0.836877, 0.960970, 0.966009, 0.976706, 0.000000], [-0.891564, -0.878750, 0.979945, -0.833385, 0.952320, 0.969777, 0.980499, 0.000000], [-0.878117, -0.868570, 0.987506, -0.815594, 0.954927, 0.974353, 0.983465, 0.000000]]
pre_activation_mean: [0.457277, 0.273847, -0.244454, 0.056428, 1.090378, 0.815767, 0.935883]
pre_activation_std: [0.387502, 0.305457, 0.389701, 0.198027, 0.761704, 0.438109, 0.528300]
### 10
mean: [-0.417241, 0.566434, 0.094027, 1.438038, 0.603524, -0.802767, 0.554639]
std: [0.407308, 0.402608, 0.312828, 0.878604, 0.400172, 0.473327, 0.437479]
fourier: [[6.430803, 6.898226, 7.409848, 7.674294, 37.551682], [6.372125, 6.685586, 7.077576, 7.622078, 50.979023], [5.066526, 5.139722, 5.662787, 5.842976, 8.462428], [13.773037, 14.649295, 15.508505, 16.605087, 129.423396], [6.368993, 6.504953, 7.344020, 7.348578, 54.317134], [7.596772, 7.829328, 8.538557, 8.878298, 72.249021], [6.792438, 7.400156, 7.839967, 8.263334, 49.917518]]
input_correlations: [[-0.991057, -0.988829, 0.858396, 0.967628, -0.995790, -0.996601, -0.996943, 0.000000], [0.992697, 0.991790, -0.831516, -0.982446, 0.999664, 0.998590, 0.999405, 0.000000], [0.985655, 0.982794, -0.865429, -0.972643, 0.995863, 0.995549, 0.995391, 0.000000], [0.992830, 0.992270, -0.836307, -0.979174, 0.999066, 0.999236, 0.999573, 0.000000], [0.978297, 0.976460, -0.885703, -0.962374, 0.990909, 0.994338, 0.991879, 0.000000], [-0.988262, -0.985975, 0.858418, 0.974295, -0.997094, -0.996948, -0.996931, 0.000000], [0.993067, 0.992271, -0.845088, -0.971563, 0.997095, 0.998488, 0.998639, 0.000000]]
pre_activation_mean: [-0.417241, 0.566434, 0.094027, 1.438038, 0.603524, -0.802767, 0.554639]
pre_activation_std: [0.407308, 0.402608, 0.312828, 0.878604, 0.400172, 0.473327, 0.437479]
### 12
mean: [-1.135085]
std: [0.808484]
fourier: [[12.527504, 13.526190, 13.763262, 15.461522, 102.157602]]
input_correlations: [[0.766376, -0.996162, -0.992349, -0.999725, -0.999691, 0.332130, -0.993684, 0.000000]]
pre_activation_mean: [-1.135085]
pre_activation_std: [0.808484]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.0.bias": [
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"network.2.weight": [
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"network.4.weight": [
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-0.163547,
0.495102,
0.152197
],
[
-0.109064,
0.321076,
0.11157,
-0.180333,
0.10156,
0.549988,
-0.17119
]
],
"network.6.bias": [
0.155359,
0.184671,
0.122612,
-0.192659,
0.412314,
0.097791,
0.500659
],
"network.8.weight": [
[
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[
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[
-0.328744,
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0.075613,
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[
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0.126988,
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[
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"network.12.bias": [
-0.035608
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}
## Activation Signature
### 0
mean: [-0.088049, 0.449142, 0.087925, 1.363623, 0.482959, -0.123964, 0.446899]
std: [0.116713, 0.353269, 0.176208, 0.893047, 0.343762, 0.061087, 0.376195]
fourier: [[1.849358, 1.921519, 2.244057, 2.288258, 7.924400], [5.261816, 5.666017, 5.914747, 6.822509, 40.422826], [2.571650, 2.759375, 2.959365, 3.423333, 7.913211], [13.974581, 14.879220, 15.130912, 17.088922, 122.726038], [5.279954, 5.694263, 5.810160, 6.533958, 43.466310], [0.916636, 0.994607, 1.268962, 1.292091, 11.156765], [5.468469, 6.075421, 6.418908, 7.291954, 40.220923]]
input_correlations: [[-0.202766, -0.508176, 0.295094, -0.279481, 0.735852, 0.000000, 0.000000, 0.000000], [-0.458600, 0.297995, -0.372124, -0.238302, -0.729003, 0.000000, 0.000000, 0.000000], [-0.422455, 0.103996, 0.679818, -0.063176, -0.157723, 0.000000, 0.000000, 0.000000], [0.874029, 0.520055, 0.509526, -0.280726, 0.023482, 0.000000, 0.000000, 0.000000], [-0.836236, -0.682384, -0.468796, -0.241100, 0.073708, 0.000000, 0.000000, 0.000000], [0.411811, 0.213105, 0.633978, 0.523710, 0.726904, 0.000000, 0.000000, 0.000000], [-0.073978, 0.550009, -0.325761, 0.851305, -0.130603, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.454666, -0.159795, 0.748476, 0.809676, -0.961569, 3.075558, 1.035097]
pre_activation_std: [0.895418, 1.093730, 1.018420, 1.512975, 1.236501, 2.003177, 1.207464]
### 2
mean: [-0.540116, 2.011998, 0.037421, -0.759749, -0.410751, 0.213401, 0.081365]
std: [0.388075, 1.181986, 0.484282, 0.811297, 0.909610, 0.850905, 0.536604]
fourier: [[6.271389, 6.445447, 7.513611, 7.948951, 48.610465], [16.371883, 17.311741, 20.706095, 22.193888, 181.079812], [6.991198, 7.205021, 7.940453, 9.037059, 11.420406], [12.861632, 14.538492, 14.644415, 16.520022, 68.377369], [15.438617, 16.383358, 16.863630, 18.603545, 36.967564], [13.306598, 13.623515, 14.504406, 16.607911, 19.206093], [7.672415, 7.703931, 8.765773, 9.217314, 9.462837]]
input_correlations: [[0.136267, 0.239208, 0.406454, -0.584197, 0.087232, -0.668676, -0.592893, 0.000000], [0.299329, -0.125353, 0.296112, -0.351579, -0.148043, 0.679665, 0.581198, 0.000000], [0.415286, -0.680270, -0.080475, 0.542607, 0.059603, 0.893173, -0.007787, 0.000000], [0.052938, 0.347775, 0.271690, -0.772358, 0.115699, -0.724018, -0.306424, 0.000000], [-0.881994, 0.530879, 0.176911, -0.106016, -0.400099, -0.668927, 0.317043, 0.000000], [-0.484953, -0.152463, -0.507313, 0.767200, -0.101504, 0.222446, 0.289239, 0.000000], [-0.219202, -0.002562, -0.106534, 0.881794, -0.006674, -0.096833, -0.389647, 0.000000]]
pre_activation_mean: [-0.540116, 2.011998, 0.037421, -0.759749, -0.410751, 0.213401, 0.081365]
pre_activation_std: [0.388075, 1.181986, 0.484282, 0.811297, 0.909610, 0.850905, 0.536604]
### 4
mean: [0.326604, 0.417188, -0.437119, 0.080921, -0.205200, 0.555456, 0.125859]
std: [0.227038, 0.527392, 0.368475, 0.704274, 0.104040, 0.676746, 0.433024]
fourier: [[3.410935, 3.984678, 4.123270, 4.297241, 29.394341], [7.989397, 8.222094, 8.994240, 9.746718, 37.546925], [6.068376, 6.274465, 7.059985, 7.926293, 39.340701], [11.073125, 11.307071, 11.437676, 11.840450, 14.150353], [1.504224, 1.557871, 1.612465, 1.822907, 18.467999], [10.214469, 10.368758, 12.364483, 12.818437, 49.991005], [6.855482, 7.185698, 7.419816, 8.118155, 11.327277]]
input_correlations: [[0.226309, 0.446814, -0.321001, -0.116287, 0.107830, -0.945062, -0.895762, 0.000000], [-0.319741, 0.958748, 0.096514, -0.568529, 0.182903, -0.511423, -0.791182, 0.000000], [0.488772, -0.405227, -0.863176, 0.240763, 0.269410, -0.719332, -0.342291, 0.000000], [-0.000351, -0.671747, 0.351395, 0.379335, -0.166320, 0.891075, 0.953768, 0.000000], [-0.412656, 0.876474, 0.407681, -0.414883, 0.396267, 0.010649, -0.369422, 0.000000], [-0.162485, 0.851191, -0.118753, -0.495881, 0.140152, -0.737537, -0.904224, 0.000000], [-0.236295, -0.444964, 0.483605, 0.184663, -0.051660, 0.980025, 0.899249, 0.000000]]
pre_activation_mean: [0.326604, 0.417188, -0.437119, 0.080921, -0.205200, 0.555456, 0.125859]
pre_activation_std: [0.227038, 0.527392, 0.368475, 0.704274, 0.104040, 0.676746, 0.433024]
### 6
mean: [-0.225101, 0.090945, 0.273217, -0.420095, 0.532541, 0.560486, 0.807619]
std: [0.400743, 0.256173, 0.509514, 0.442486, 0.310417, 0.546441, 0.489540]
fourier: [[6.183899, 6.377390, 7.356409, 7.610076, 20.259126], [4.056975, 4.134683, 4.249574, 5.045661, 8.185084], [7.718723, 8.222359, 8.399230, 9.959420, 24.589552], [6.830472, 7.146303, 8.053677, 8.238610, 37.808543], [4.966840, 4.967445, 4.996653, 6.163116, 47.928678], [8.296821, 8.405375, 9.999210, 10.156112, 50.443776], [7.492043, 7.789463, 8.914808, 8.972597, 72.685707]]
input_correlations: [[-0.817068, -0.872986, 0.189283, 0.875124, -0.532604, -0.944359, 0.830189, 0.000000], [-0.921652, -0.689788, -0.056043, 0.979504, -0.334036, -0.796253, 0.955693, 0.000000], [0.904012, 0.730719, -0.009871, -0.971064, 0.373055, 0.826354, -0.941764, 0.000000], [-0.759034, -0.915289, 0.215338, 0.834431, -0.605344, -0.965742, 0.779938, 0.000000], [0.936030, 0.683542, 0.079827, -0.968363, 0.317446, 0.799882, -0.959749, 0.000000], [0.772366, 0.907572, -0.239063, -0.850031, 0.591976, 0.958149, -0.789525, 0.000000], [0.732035, 0.929245, -0.261154, -0.814129, 0.620766, 0.975188, -0.754590, 0.000000]]
pre_activation_mean: [-0.225101, 0.090945, 0.273217, -0.420095, 0.532541, 0.560486, 0.807619]
pre_activation_std: [0.400743, 0.256173, 0.509514, 0.442486, 0.310417, 0.546441, 0.489540]
### 8
mean: [0.457277, 0.273847, -0.244454, 0.056428, 1.090378, 0.815767, 0.935883]
std: [0.387502, 0.305457, 0.389701, 0.198027, 0.761704, 0.438109, 0.528300]
fourier: [[6.244149, 6.606831, 7.151115, 7.282494, 41.154965], [4.859521, 5.164297, 5.636452, 5.704882, 24.646203], [6.244570, 6.301082, 7.028727, 7.418509, 22.000842], [2.854446, 2.897833, 3.128001, 3.803108, 5.078517], [12.030297, 12.421579, 13.927671, 14.240438, 98.134040], [6.812491, 7.088703, 7.989990, 8.129049, 73.419015], [8.303325, 8.719216, 9.739650, 9.761599, 84.229436]]
input_correlations: [[-0.885075, -0.883768, 0.991905, -0.822078, 0.973956, 0.959688, 0.968948, 0.000000], [-0.882476, -0.877737, 0.990292, -0.819884, 0.966348, 0.967354, 0.976580, 0.000000], [0.912952, 0.902786, -0.980935, 0.857950, -0.968953, -0.953864, -0.966341, 0.000000], [0.648614, 0.632563, -0.942120, 0.556226, -0.807644, -0.987708, -0.978213, 0.000000], [-0.895677, -0.885320, 0.984295, -0.836877, 0.960970, 0.966009, 0.976706, 0.000000], [-0.891564, -0.878750, 0.979945, -0.833385, 0.952320, 0.969777, 0.980499, 0.000000], [-0.878117, -0.868570, 0.987506, -0.815594, 0.954927, 0.974353, 0.983465, 0.000000]]
pre_activation_mean: [0.457277, 0.273847, -0.244454, 0.056428, 1.090378, 0.815767, 0.935883]
pre_activation_std: [0.387502, 0.305457, 0.389701, 0.198027, 0.761704, 0.438109, 0.528300]
### 10
mean: [-0.417241, 0.566434, 0.094027, 1.438038, 0.603524, -0.802767, 0.554639]
std: [0.407308, 0.402608, 0.312828, 0.878604, 0.400172, 0.473327, 0.437479]
fourier: [[6.430803, 6.898226, 7.409848, 7.674294, 37.551682], [6.372125, 6.685586, 7.077576, 7.622078, 50.979023], [5.066526, 5.139722, 5.662787, 5.842976, 8.462428], [13.773037, 14.649295, 15.508505, 16.605087, 129.423396], [6.368993, 6.504953, 7.344020, 7.348578, 54.317134], [7.596772, 7.829328, 8.538557, 8.878298, 72.249021], [6.792438, 7.400156, 7.839967, 8.263334, 49.917518]]
input_correlations: [[-0.991057, -0.988829, 0.858396, 0.967628, -0.995790, -0.996601, -0.996943, 0.000000], [0.992697, 0.991790, -0.831516, -0.982446, 0.999664, 0.998590, 0.999405, 0.000000], [0.985655, 0.982794, -0.865429, -0.972643, 0.995863, 0.995549, 0.995391, 0.000000], [0.992830, 0.992270, -0.836307, -0.979174, 0.999066, 0.999236, 0.999573, 0.000000], [0.978297, 0.976460, -0.885703, -0.962374, 0.990909, 0.994338, 0.991879, 0.000000], [-0.988262, -0.985975, 0.858418, 0.974295, -0.997094, -0.996948, -0.996931, 0.000000], [0.993067, 0.992271, -0.845088, -0.971563, 0.997095, 0.998488, 0.998639, 0.000000]]
pre_activation_mean: [-0.417241, 0.566434, 0.094027, 1.438038, 0.603524, -0.802767, 0.554639]
pre_activation_std: [0.407308, 0.402608, 0.312828, 0.878604, 0.400172, 0.473327, 0.437479]
### 12
mean: [-1.135085]
std: [0.808484]
fourier: [[12.527504, 13.526190, 13.763262, 15.461522, 102.157602]]
input_correlations: [[0.766376, -0.996162, -0.992349, -0.999725, -0.999691, 0.332130, -0.993684, 0.000000]]
pre_activation_mean: [-1.135085]
pre_activation_std: [0.808484]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.08804888278245926, "std": 0.11671291291713715, "fourier": [1.849358041944061, 1.9215186778499904, 2.2440567610023607, 2.288258236229575, 7.924399688839912], "input_correlations": [-0.2027663986269243, -0.5081761721944712, 0.2950943475292809, -0.2794813238733706, 0.7358521260655567, 0.0, 0.0, 0.0], "pre_activation_mean": 0.45466604828834534, "pre_activation_std": 0.8954182863235474}, "1": {"mean": 0.4491424858570099, "std": 0.35326871275901794, "fourier": [5.261816163390686, 5.666016562719292, 5.914746757000329, 6.822508748862852, 40.422826441936195], "input_correlations": [-0.4585995845722869, 0.29799470139532497, -0.37212426777981694, -0.23830220382569137, -0.7290031432406835, 0.0, 0.0, 0.0], "pre_activation_mean": -0.15979520976543427, "pre_activation_std": 1.0937303304672241}, "2": {"mean": 0.08792456984519958, "std": 0.1762075573205948, "fourier": [2.5716496863007734, 2.75937452611428, 2.9593645245442017, 3.4233326560316173, 7.913211327511817], "input_correlations": [-0.422455074973031, 0.1039961368060855, 0.679818382353386, -0.0631763417248512, -0.15772264041362366, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7484761476516724, "pre_activation_std": 1.0184201002120972}, "3": {"mean": 1.3636226654052734, "std": 0.8930467963218689, "fourier": [13.974580883695998, 14.879220416776171, 15.130911692089496, 17.088922441459804, 122.72603766899556], "input_correlations": [0.8740288996143025, 0.5200554487066695, 0.5095255461535672, -0.28072558624050753, 0.023481523938941384, 0.0, 0.0, 0.0], "pre_activation_mean": 0.8096755743026733, "pre_activation_std": 1.5129748582839966}, "4": {"mean": 0.48295897245407104, "std": 0.34376227855682373, "fourier": [5.279954240663615, 5.69426296619098, 5.810160478362778, 6.533957898611578, 43.466309824958444], "input_correlations": [-0.8362364336062709, -0.6823842009692226, -0.4687958383490322, -0.24109998813019942, 0.07370801757940364, 0.0, 0.0, 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"neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.147381, -0.180102, 0.147826, -0.125106, 0.374279], [-0.28355, 0.387636, -0.131962, -0.208204, -0.310473], [-0.3756, 0.108305, 0.480827, -0.069933, -0.109041], [0.507245, 0.292859, 0.187109, -0.256164, -0.080114], [-0.437029, -0.217576, -0.145738, -0.123272, 0.189975], [0.235548, -0.145794, 0.4893, 0.477622, 0.551001], [-0.01231, 0.258148, -0.236832, 0.432092, -0.102705]], "network.0.bias": [0.464138, 0.591759, 0.298591, -0.09793, 0.31324, 0.322206, 0.2748], "network.2.weight": [[-0.011202, 0.127983, 0.12116, -0.14862, -0.01404, -0.055107, -0.213439], [0.030958, 0.218173, 0.282065, 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0.147456, -0.152617, 0.167402, 0.520735, -0.015096]], "network.4.bias": [0.496561, -0.138756, -0.018294, 0.300464, -0.333831, 0.019974, 0.083395], "network.6.weight": [[-0.507857, -0.078157, 0.170142, 0.227592, 0.101297, -0.474573, -0.023001], [-0.203733, 0.232233, -0.193156, 0.420681, 0.104653, -0.363092, -0.235293], [0.335906, 0.08612, -0.366463, -0.4753, -0.003372, 0.236707, -0.251538], [0.065442, -0.36482, -0.278467, 0.051238, -0.269029, -0.414669, 0.371446], [0.389222, -0.150459, 0.33783, -0.170149, 0.123372, 0.361944, -0.197692], [0.395799, 0.326928, -0.35589, -0.421844, -0.163547, 0.495102, 0.152197], [-0.109064, 0.321076, 0.11157, -0.180333, 0.10156, 0.549988, -0.17119]], "network.6.bias": [0.155359, 0.184671, 0.122612, -0.192659, 0.412314, 0.097791, 0.500659], "network.8.weight": [[0.145442, -0.216312, 0.476654, -0.157234, 0.5486, 0.230725, 0.072467], [0.240749, -0.198053, 0.204127, -0.295752, 0.373522, 0.25906, 0.095524], [0.374243, -0.168848, -0.415658, 0.407725, -0.256349, -0.085881, -0.259237], [0.049979, 0.054853, -0.036955, -0.461307, -0.016809, -0.292226, -0.201406], [-0.328744, -0.203942, 0.491291, -0.561271, 0.39779, 0.45116, 0.487559], [0.075613, -0.263215, 0.020886, -0.557916, 0.155221, 0.412277, 0.292631], [-0.022063, -0.287689, 0.275032, -0.252702, 0.310363, 0.292286, 0.436452]], "network.8.bias": [-0.04181, -0.122572, 0.243764, 0.314664, 0.207429, 0.323727, 0.297223], "network.10.weight": [[-0.28536, -0.298289, 0.357877, -0.308393, -0.25933, 0.084533, -0.178039], [-0.203385, 0.396631, -0.152587, -0.117028, 0.448628, -0.199906, 0.227021], [0.229127, -0.172893, -0.348996, -0.428276, 0.292078, -0.191348, 0.120532], [0.393484, -0.055782, -0.278688, -0.176705, 0.370517, 0.553386, 0.451191], [-0.266652, 0.067353, -0.442313, 0.128515, 0.194771, 0.226596, 0.356913], [-0.41583, 0.100498, 0.434949, 0.406231, -0.500805, -0.098977, 0.243759], [0.303425, 0.332159, -0.224469, 0.280236, 0.091013, 0.434008, 0.062021]], "network.10.bias": [0.126988, 0.050564, -0.215283, 0.175263, 0.012827, -0.293069, -0.084793], "network.12.weight": [[0.244334, -0.397853, -0.384119, -0.436758, -0.285958, 0.228032, -0.231707]], "network.12.bias": [-0.035608]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6915469169616699, "train_acc": 0.55, "val_loss": 0.6777675151824951, "val_acc": 0.62}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6891086399555206, "train_acc": 0.55, "val_loss": 0.6671968102455139, "val_acc": 0.62}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6847893595695496, "train_acc": 0.55, "val_loss": 0.6495546102523804, "val_acc": 0.62}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6673858761787415, "train_acc": 0.55, "val_loss": 0.6050564050674438, "val_acc": 0.62}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6532787978649139, "train_acc": 0.47, "val_loss": 0.4839093089103699, "val_acc": 0.62}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5142391324043274, "train_acc": 0.62, "val_loss": 0.32768699526786804, "val_acc": 0.98}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.4048998951911926, "train_acc": 0.915, "val_loss": 0.23394544422626495, "val_acc": 0.98}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.3386348932981491, "train_acc": 0.91, "val_loss": 0.18784824013710022, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.26504603773355484, "train_acc": 0.925, "val_loss": 0.15301650762557983, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.23966170102357864, "train_acc": 0.93, "val_loss": 0.12873272597789764, "val_acc": 0.96}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.194089874625206, "train_acc": 0.935, "val_loss": 0.1177508533000946, "val_acc": 0.96}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.16870566830039024, "train_acc": 0.935, "val_loss": 0.1186082661151886, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.17846181988716125, "train_acc": 0.94, "val_loss": 0.1269386261701584, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.1924881413578987, "train_acc": 0.935, "val_loss": 0.1273975819349289, "val_acc": 0.96}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6777675151824951, "final_val_loss": 0.6050564050674438, "initial_val_acc": 0.62, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.4839093089103699, "final_val_loss": 0.1273975819349289, "initial_val_acc": 0.62, "final_val_acc": 0.96, "best_val_acc": 0.98, "best_epoch": 5}, "improvement": 0.36, "first_improvement_epoch": 3}} |
63 | {"target_pattern": "has_majority", "degraded_accuracy": 0.44, "improved_accuracy": 0.84, "improvement": 0.39999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 7511, "learning_rate": 0.058202799735515814, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.57675,
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],
[
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[
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],
"network.0.bias": [
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],
"network.2.weight": [
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0.001706
],
[
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[
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],
[
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]
],
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],
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[
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],
[
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],
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[
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[
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"network.8.bias": [
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}
## Activation Signature
### 0
mean: [0.276639, 0.000000, 0.000000, 0.304888, 0.416730]
std: [0.438696, 0.000000, 0.000000, 0.486037, 0.567140]
fourier: [[6.421596, 6.744765, 7.180436, 7.607665, 24.897508], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [7.097375, 7.463884, 7.966704, 8.405962, 27.439905], [8.900577, 8.936385, 8.973103, 10.515345, 37.505732]]
input_correlations: [[-0.665706, -0.478527, -0.824839, -0.282944, -0.451542, 0.000000, 0.000000, 0.000000], [-0.010534, -0.629764, -0.090471, 0.193976, -0.416514, 0.000000, 0.000000, 0.000000], [-0.878913, -0.079617, -0.140804, 0.491519, -0.005899, 0.000000, 0.000000, 0.000000], [-0.525529, -0.562563, -0.672532, -0.367031, -0.676651, 0.000000, 0.000000, 0.000000], [0.454042, 0.492141, 0.625798, 0.711339, 0.387696, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.185612, -0.255087, 0.331445, -3.466838, 2.701245]
pre_activation_std: [1.192980, 1.891700, 2.661679, 1.862335, 2.189459]
### 2
mean: [-0.938620, -0.758518, -0.396227, 0.966033, -0.927811]
std: [1.178140, 0.145800, 0.189390, 1.616975, 0.842325]
fourier: [[18.734054, 20.024856, 20.172768, 22.022874, 84.475782], [2.128022, 2.251763, 2.465047, 2.612511, 68.266647], [3.098184, 3.313999, 3.324061, 3.359034, 35.660465], [23.853964, 24.326397, 26.361309, 29.063108, 86.942960], [12.144216, 12.480701, 14.581849, 15.250944, 83.503008]]
input_correlations: [[0.000000, -0.570262, -0.839269, 0.000000, -0.001732, 0.000000, 0.000000, 0.000000], [0.000000, -0.252090, -0.998371, 0.000000, -0.340440, 0.000000, 0.000000, 0.000000], [0.000000, -0.930382, 0.171471, 0.000000, -0.039188, 0.000000, 0.000000, 0.000000], [0.000000, -0.549374, 0.446816, 0.000000, 0.675116, 0.000000, 0.000000, 0.000000], [0.000000, -0.662481, -0.842276, 0.000000, -0.522153, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.938620, -0.758518, -0.396227, 0.966033, -0.927811]
pre_activation_std: [1.178140, 0.145800, 0.189390, 1.616975, 0.842325]
### 4
mean: [-0.430655, -1.153170, 0.801425, -1.217808, -0.341382]
std: [0.052235, 0.877837, 1.039751, 1.201788, 0.651879]
fourier: [[0.757353, 0.873018, 0.889331, 1.107914, 38.758958], [13.458070, 13.693570, 13.793677, 16.519426, 103.785278], [16.050690, 16.122134, 16.942231, 19.948274, 72.128283], [18.265653, 18.501676, 18.982177, 22.287990, 109.602708], [9.922755, 9.940729, 10.346389, 12.018585, 30.724411]]
input_correlations: [[-0.960696, 0.000000, 0.000000, -0.688565, 0.127869, 0.000000, 0.000000, 0.000000], [-0.532493, 0.000000, 0.000000, -0.996522, 0.193440, 0.000000, 0.000000, 0.000000], [0.624533, 0.000000, 0.000000, 0.980794, -0.193181, 0.000000, 0.000000, 0.000000], [-0.486396, 0.000000, 0.000000, -0.999556, 0.196562, 0.000000, 0.000000, 0.000000], [-0.465904, 0.000000, 0.000000, -0.999945, 0.190754, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.430655, -1.153170, 0.801425, -1.217808, -0.341382]
pre_activation_std: [0.052235, 0.877837, 1.039751, 1.201788, 0.651879]
### 6
mean: [0.113782, -1.067145, -0.475646, 0.163603, 0.313668]
std: [0.559930, 0.971918, 0.083565, 0.586960, 0.649699]
fourier: [[8.695425, 8.706084, 9.157722, 10.240359, 10.772886], [15.197545, 15.210689, 15.801656, 18.559008, 96.043031], [1.238109, 1.253712, 1.378565, 1.636609, 42.808174], [9.208339, 9.230295, 9.493798, 11.137406, 14.724312], [10.082980, 10.096955, 10.630156, 12.506534, 28.230155]]
input_correlations: [[0.000000, 0.000000, 0.998950, 0.000000, -0.708708, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.999954, 0.000000, 0.682716, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.967389, 0.000000, 0.840344, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.999861, 0.000000, -0.663244, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.998819, 0.000000, -0.710656, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.113782, -1.067145, -0.475646, 0.163603, 0.313668]
pre_activation_std: [0.559930, 0.971918, 0.083565, 0.586960, 0.649699]
### 8
mean: [0.184538]
std: [0.629749]
fourier: [[9.485257, 9.769648, 10.205358, 11.206282, 16.608465]]
input_correlations: [[-0.999036, 0.000000, 0.000000, -0.998847, -0.996779, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.184538]
pre_activation_std: [0.629749]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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"network.0.bias": [
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],
"network.2.weight": [
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],
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],
[
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],
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],
"network.4.bias": [
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"network.6.weight": [
[
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],
[
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"network.8.bias": [
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}
## Activation Signature
### 0
mean: [0.276639, 0.000000, 0.000000, 0.304888, 0.416730]
std: [0.438696, 0.000000, 0.000000, 0.486037, 0.567140]
fourier: [[6.421596, 6.744765, 7.180436, 7.607665, 24.897508], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [7.097375, 7.463884, 7.966704, 8.405962, 27.439905], [8.900577, 8.936385, 8.973103, 10.515345, 37.505732]]
input_correlations: [[-0.665706, -0.478527, -0.824839, -0.282944, -0.451542, 0.000000, 0.000000, 0.000000], [-0.010534, -0.629764, -0.090471, 0.193976, -0.416514, 0.000000, 0.000000, 0.000000], [-0.878913, -0.079617, -0.140804, 0.491519, -0.005899, 0.000000, 0.000000, 0.000000], [-0.525529, -0.562563, -0.672532, -0.367031, -0.676651, 0.000000, 0.000000, 0.000000], [0.454042, 0.492141, 0.625798, 0.711339, 0.387696, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.185612, -0.255087, 0.331445, -3.466838, 2.701245]
pre_activation_std: [1.192980, 1.891700, 2.661679, 1.862335, 2.189459]
### 2
mean: [-0.938620, -0.758518, -0.396227, 0.966033, -0.927811]
std: [1.178140, 0.145800, 0.189390, 1.616975, 0.842325]
fourier: [[18.734054, 20.024856, 20.172768, 22.022874, 84.475782], [2.128022, 2.251763, 2.465047, 2.612511, 68.266647], [3.098184, 3.313999, 3.324061, 3.359034, 35.660465], [23.853964, 24.326397, 26.361309, 29.063108, 86.942960], [12.144216, 12.480701, 14.581849, 15.250944, 83.503008]]
input_correlations: [[0.000000, -0.570262, -0.839269, 0.000000, -0.001732, 0.000000, 0.000000, 0.000000], [0.000000, -0.252090, -0.998371, 0.000000, -0.340440, 0.000000, 0.000000, 0.000000], [0.000000, -0.930382, 0.171471, 0.000000, -0.039188, 0.000000, 0.000000, 0.000000], [0.000000, -0.549374, 0.446816, 0.000000, 0.675116, 0.000000, 0.000000, 0.000000], [0.000000, -0.662481, -0.842276, 0.000000, -0.522153, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.938620, -0.758518, -0.396227, 0.966033, -0.927811]
pre_activation_std: [1.178140, 0.145800, 0.189390, 1.616975, 0.842325]
### 4
mean: [-0.430655, -1.153170, 0.801425, -1.217808, -0.341382]
std: [0.052235, 0.877837, 1.039751, 1.201788, 0.651879]
fourier: [[0.757353, 0.873018, 0.889331, 1.107914, 38.758958], [13.458070, 13.693570, 13.793677, 16.519426, 103.785278], [16.050690, 16.122134, 16.942231, 19.948274, 72.128283], [18.265653, 18.501676, 18.982177, 22.287990, 109.602708], [9.922755, 9.940729, 10.346389, 12.018585, 30.724411]]
input_correlations: [[-0.960696, 0.000000, 0.000000, -0.688565, 0.127869, 0.000000, 0.000000, 0.000000], [-0.532493, 0.000000, 0.000000, -0.996522, 0.193440, 0.000000, 0.000000, 0.000000], [0.624533, 0.000000, 0.000000, 0.980794, -0.193181, 0.000000, 0.000000, 0.000000], [-0.486396, 0.000000, 0.000000, -0.999556, 0.196562, 0.000000, 0.000000, 0.000000], [-0.465904, 0.000000, 0.000000, -0.999945, 0.190754, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.430655, -1.153170, 0.801425, -1.217808, -0.341382]
pre_activation_std: [0.052235, 0.877837, 1.039751, 1.201788, 0.651879]
### 6
mean: [0.113782, -1.067145, -0.475646, 0.163603, 0.313668]
std: [0.559930, 0.971918, 0.083565, 0.586960, 0.649699]
fourier: [[8.695425, 8.706084, 9.157722, 10.240359, 10.772886], [15.197545, 15.210689, 15.801656, 18.559008, 96.043031], [1.238109, 1.253712, 1.378565, 1.636609, 42.808174], [9.208339, 9.230295, 9.493798, 11.137406, 14.724312], [10.082980, 10.096955, 10.630156, 12.506534, 28.230155]]
input_correlations: [[0.000000, 0.000000, 0.998950, 0.000000, -0.708708, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.999954, 0.000000, 0.682716, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -0.967389, 0.000000, 0.840344, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.999861, 0.000000, -0.663244, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.998819, 0.000000, -0.710656, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.113782, -1.067145, -0.475646, 0.163603, 0.313668]
pre_activation_std: [0.559930, 0.971918, 0.083565, 0.586960, 0.649699]
### 8
mean: [0.184538]
std: [0.629749]
fourier: [[9.485257, 9.769648, 10.205358, 11.206282, 16.608465]]
input_correlations: [[-0.999036, 0.000000, 0.000000, -0.998847, -0.996779, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.184538]
pre_activation_std: [0.629749]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -0.93861985206604, "std": 1.1781402826309204, "fourier": [18.73405386024603, 20.024856224137928, 20.172767729307434, 22.022873516179455, 84.47578214854002], "input_correlations": [0.0, -0.5702619495749557, -0.8392686281185553, 0.0, -0.0017322374110552243, 0.0, 0.0, 0.0], "pre_activation_mean": -0.93861985206604, "pre_activation_std": 1.1781402826309204}, "1": {"mean": -0.7585182785987854, "std": 0.1458004117012024, "fourier": [2.128021881412785, 2.2517629692645107, 2.465047179752851, 2.612510707624816, 68.26664745807648], "input_correlations": [0.0, -0.2520899077262134, -0.9983714453399105, 0.0, -0.3404403246505958, 0.0, 0.0, 0.0], "pre_activation_mean": -0.7585182785987854, "pre_activation_std": 0.1458004117012024}, "2": {"mean": -0.3962273597717285, "std": 0.18939028680324554, "fourier": [3.098183966354073, 3.3139989646839574, 3.3240612302057597, 3.3590344278791178, 35.660465493798256], 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"layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "8": {"neuron_profiles": {"0": {"mean": 0.18453848361968994, "std": 0.6297491788864136, "fourier": [9.485256525661823, 9.769647787934764, 10.20535762731671, 11.206281992474848, 16.608464539051056], "input_correlations": [-0.9990356696619942, 0.0, 0.0, -0.9988467020682732, -0.9967788845693863, 0.0, 0.0, 0.0], "pre_activation_mean": 0.18453848361968994, "pre_activation_std": 0.6297491788864136}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.232249, -0.089599, -0.381569, -0.124121, -0.138739], [0.397885, -1.032984, 0.120215, 0.57675, -0.632323], [-1.223685, 0.098192, 0.162221, 0.52482, 0.10916], [-0.175039, -0.350785, -0.403494, -0.159052, -0.530669], [0.310261, 0.07854, 0.547178, 0.710948, 0.154371]], "network.0.bias": [-0.498983, 0.424033, 0.076388, -0.771382, -0.685946], "network.2.weight": [[-0.471198, -0.562344, -0.798366, -0.062347, 0.21872], [-0.132745, -0.008575, -0.111056, -0.340297, 0.001706], [-0.032354, -0.201242, 0.055214, 0.162586, -0.002017], [0.127947, -1.235461, 0.441071, -0.29151, 0.514252], [0.123831, -0.442686, -0.430598, -0.381498, -0.084375]], "network.2.bias": [-0.209935, -0.620576, -0.333493, -0.241763, 0.115575], "network.4.weight": [[-0.118089, -0.1402, -0.245145, -0.012331, -0.023531], [-0.227654, 0.257579, 0.180534, -0.631127, -0.529092], [0.632235, -0.067098, 0.022614, 0.689176, 0.051135], [-0.111303, 0.003014, -1.032531, -0.89149, -0.361622], [-0.012948, -0.419134, -0.960476, -0.490316, -0.773115]], "network.4.bias": [-0.399192, -0.351822, -0.126029, -0.115728, 0.259019], "network.6.weight": [[-0.089762, -0.316624, 0.531356, 0.250023, -0.306192], [0.08986, 0.03797, -0.955241, -0.237314, 0.111853], [0.341852, -0.429884, -0.060929, -0.268395, 0.252624], [-0.034759, 0.24939, 0.590879, -0.097549, 0.11688], [-0.035388, -0.074069, 0.614829, -0.197879, -0.376704]], "network.6.bias": [-0.302847, -0.277225, -0.448171, -0.342377, -0.166319], "network.8.weight": [[-0.482855, 0.066504, 0.189972, -0.390148, -0.404588]], "network.8.bias": [0.605671]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6921209990978241, "train_acc": 0.475, "val_loss": 0.7133306860923767, "val_acc": 0.44}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6447307169437408, "train_acc": 0.595, "val_loss": 0.8337544798851013, "val_acc": 0.44}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6655393838882446, "train_acc": 0.595, "val_loss": 0.745745062828064, "val_acc": 0.44}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6432807445526123, "train_acc": 0.595, "val_loss": 0.6957781910896301, "val_acc": 0.44}, {"stage": "degraded", "epoch": 4, "global_epoch": 4, "train_loss": 0.6266169548034668, "train_acc": 0.595, "val_loss": 0.6665924191474915, "val_acc": 0.44}, {"stage": "improved", "epoch": 0, "global_epoch": 5, "train_loss": 0.6619569063186646, "train_acc": 0.515, "val_loss": 0.6352573037147522, "val_acc": 0.54}, {"stage": "improved", "epoch": 1, "global_epoch": 6, "train_loss": 0.6191228926181793, "train_acc": 0.695, "val_loss": 0.6129134893417358, "val_acc": 0.78}, {"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.6138115525245667, "train_acc": 0.72, "val_loss": 0.5739187002182007, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5569284856319427, "train_acc": 0.755, "val_loss": 0.596858561038971, "val_acc": 0.6}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.5983408093452454, "train_acc": 0.71, "val_loss": 0.5450654625892639, "val_acc": 0.66}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.5252772867679596, "train_acc": 0.77, "val_loss": 0.49999603629112244, "val_acc": 0.84}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.5419841110706329, "train_acc": 0.755, "val_loss": 0.49002915620803833, "val_acc": 0.82}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.5235366523265839, "train_acc": 0.755, "val_loss": 0.4739401340484619, "val_acc": 0.78}, {"stage": "improved", "epoch": 8, "global_epoch": 13, "train_loss": 0.5199985802173615, "train_acc": 0.775, "val_loss": 0.5335729122161865, "val_acc": 0.7}, {"stage": "improved", "epoch": 9, "global_epoch": 14, "train_loss": 0.5159470438957214, "train_acc": 0.74, "val_loss": 0.4584527611732483, "val_acc": 0.76}], "summary": {"total_epochs": 15, "degraded_epochs": 5, "improved_epochs": 10, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.7133306860923767, "final_val_loss": 0.6665924191474915, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.6352573037147522, "final_val_loss": 0.4584527611732483, "initial_val_acc": 0.54, "final_val_acc": 0.76, "best_val_acc": 0.84, "best_epoch": 10}, "improvement": 0.39999999999999997, "first_improvement_epoch": 4}} |
64 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.82, "improved_accuracy": 0.98, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1256, "learning_rate": 0.06504650220298641, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.772530, 2.468380, 4.762798, 0.539120, 4.111729, 0.138594, 6.762283, 4.938472]
std: [1.819812, 2.027533, 3.238378, 1.255538, 3.014353, 0.362109, 4.695432, 3.435279]
fourier: [[27.046993, 37.549926, 37.806378, 37.837912, 69.527699], [30.741322, 31.797982, 34.444532, 39.474239, 222.154172], [48.740295, 51.145322, 53.654519, 64.222018, 428.651795], [18.854217, 25.933192, 26.354859, 26.355897, 48.520846], [44.502904, 46.798140, 50.839141, 59.495601, 370.055659], [5.411999, 7.343009, 7.541085, 7.875551, 12.473422], [72.064974, 72.189090, 78.368098, 92.882077, 608.605428], [53.083506, 53.779937, 57.736504, 68.033080, 444.462489]]
input_correlations: [[-0.551226, 0.013761, 0.422540, 0.572224, 0.212504, 0.000000, 0.000000, 0.000000], [0.858373, 0.694057, 0.212742, -0.046310, -0.089457, 0.000000, 0.000000, 0.000000], [-0.179524, 0.473433, -0.708326, 0.450471, -0.221987, 0.000000, 0.000000, 0.000000], [-0.811123, -0.765035, -0.440753, 0.010296, -0.232073, 0.000000, 0.000000, 0.000000], [-0.831936, 0.047527, 0.118720, 0.062539, -0.340294, 0.000000, 0.000000, 0.000000], [0.698286, 0.330672, 0.261028, -0.049760, 0.778929, 0.000000, 0.000000, 0.000000], [0.833106, 0.716804, 0.103456, -0.009579, -0.046202, 0.000000, 0.000000, 0.000000], [0.502259, -0.217132, 0.065670, -0.717175, 0.450304, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.875575, 1.634915, 0.281045, -1.417556, -0.211344, 1.369559, 0.404942, -0.278176]
pre_activation_std: [1.639787, 1.998467, 1.063352, 1.108873, 1.417276, 2.090200, 1.266564, 1.193675]
### 2
mean: [1.347044, 0.244998, 1.445268, 1.096964, 1.905259, 0.213028, -1.436037, 1.820319]
std: [1.575377, 1.125529, 1.133457, 1.343869, 1.514894, 0.838703, 0.779203, 1.432069]
fourier: [[25.430237, 25.705223, 26.369097, 28.257900, 121.233985], [18.680167, 18.833129, 19.298049, 19.664978, 22.049803], [16.043582, 18.472483, 19.409218, 22.242934, 130.074088], [20.357369, 20.713174, 22.567191, 23.047278, 98.726748], [22.981748, 23.089702, 23.394995, 27.834812, 171.473318], [11.477115, 11.754062, 13.576661, 14.544365, 19.172551], [13.081961, 13.959592, 14.404454, 15.752424, 129.243312], [22.154640, 22.869396, 25.256726, 27.004103, 163.828746]]
input_correlations: [[-0.372926, 0.946853, -0.047502, 0.677734, -0.250351, 0.715061, 0.953702, 0.307112], [0.593415, -0.944342, 0.138731, -0.630041, 0.226917, -0.610870, -0.932261, -0.344434], [0.812058, -0.595994, -0.115526, -0.274266, 0.433665, 0.051240, -0.602533, 0.096067], [-0.478171, 0.976096, 0.208264, 0.654871, -0.176772, 0.482094, 0.982417, 0.107944], [0.825839, -0.656659, -0.145769, -0.325946, 0.315917, 0.043801, -0.646772, 0.006727], [-0.628242, 0.850996, 0.102928, 0.485821, -0.402086, 0.292528, 0.863951, -0.024404], [-0.020841, -0.668085, 0.233890, -0.552158, 0.088471, -0.900252, -0.671360, -0.446047], [0.875459, -0.481125, 0.131609, -0.188077, 0.428581, 0.081295, -0.462801, -0.124102]]
pre_activation_mean: [1.347044, 0.244998, 1.445268, 1.096964, 1.905259, 0.213028, -1.436037, 1.820319]
pre_activation_std: [1.575377, 1.125529, 1.133457, 1.343869, 1.514894, 0.838703, 0.779203, 1.432069]
### 4
mean: [2.358762, -0.319381, 2.299825, 2.981736, -0.905268, -1.553594, 0.231237, -0.790318]
std: [1.758815, 0.342951, 2.258453, 2.629371, 2.265682, 0.959631, 1.258120, 2.488115]
fourier: [[27.043992, 27.092588, 28.921792, 33.067938, 212.288595], [5.620372, 5.800245, 5.803334, 6.565347, 28.744283], [34.889373, 35.331822, 38.686790, 41.498330, 206.984294], [38.992020, 41.745598, 42.677647, 49.969566, 268.356241], [35.189526, 36.546689, 39.591328, 39.902818, 81.474079], [14.969223, 14.990750, 15.990977, 18.252818, 139.823425], [19.066047, 20.811371, 20.938911, 22.287786, 22.821858], [38.405451, 39.923172, 43.614427, 44.088808, 71.128635]]
input_correlations: [[-0.369433, 0.564287, 0.985142, -0.558824, 0.992671, -0.650151, 0.150314, 0.962043], [-0.970803, 0.595285, 0.427326, -0.942285, 0.460198, -0.860238, -0.711272, 0.317341], [-0.700939, 0.733190, 0.916834, -0.820220, 0.938532, -0.874313, -0.222671, 0.873007], [-0.576190, 0.676182, 0.968948, -0.723192, 0.979226, -0.791968, -0.068855, 0.927204], [0.796101, -0.774275, -0.854273, 0.885122, -0.879781, 0.918981, 0.351357, -0.801294], [0.502333, -0.727921, -0.952881, 0.654085, -0.982131, 0.712973, 0.018526, -0.943250], [-0.755097, 0.796322, 0.861828, -0.833722, 0.892118, -0.888193, -0.321107, 0.849632], [0.795935, -0.759194, -0.858742, 0.883517, -0.880938, 0.922485, 0.347145, -0.806076]]
pre_activation_mean: [2.358762, -0.319381, 2.299825, 2.981736, -0.905268, -1.553594, 0.231237, -0.790318]
pre_activation_std: [1.758815, 0.342951, 2.258453, 2.629371, 2.265682, 0.959631, 1.258120, 2.488115]
### 6
mean: [0.468882, 2.876293, -1.914389, 1.245716, 3.912918, 0.524394, -3.049751, 3.621419]
std: [0.429807, 2.798632, 3.189187, 1.332070, 3.789947, 0.920748, 3.918159, 4.155454]
fourier: [[7.195687, 8.443154, 8.755113, 9.658758, 42.199418], [41.461460, 45.202849, 45.549728, 53.750142, 258.866335], [45.712502, 46.623908, 57.638149, 60.092215, 172.295026], [19.947708, 21.630811, 23.104402, 25.376375, 112.114468], [56.030599, 58.554015, 65.606799, 72.177619, 352.162685], [14.028297, 17.693280, 19.376086, 20.623711, 47.195426], [59.562827, 61.386397, 68.960518, 72.979244, 274.477627], [60.824040, 61.482497, 76.279354, 76.431576, 325.927717]]
input_correlations: [[0.013730, -0.579461, -0.177251, -0.085973, 0.822458, 0.544180, 0.021663, 0.819196], [0.963939, 0.465081, 0.987183, 0.988979, -0.693244, 0.542902, 0.875642, -0.703011], [-0.875924, -0.566196, -0.931718, -0.916195, 0.857217, -0.329597, -0.763887, 0.864353], [0.965792, 0.429232, 0.995783, 0.996805, -0.570111, 0.657761, 0.936495, -0.582108], [0.946249, 0.489299, 0.973089, 0.972181, -0.753727, 0.473725, 0.838018, -0.762452], [-0.350485, -0.564160, -0.440865, -0.397271, 0.977574, 0.345621, -0.175815, 0.974242], [-0.909728, -0.549149, -0.969292, -0.953639, 0.790672, -0.430111, -0.835103, 0.799661], [0.893637, 0.551610, 0.947948, 0.933339, -0.831995, 0.370437, 0.793177, -0.839788]]
pre_activation_mean: [0.468882, 2.876293, -1.914389, 1.245716, 3.912918, 0.524394, -3.049751, 3.621419]
pre_activation_std: [0.429807, 2.798632, 3.189187, 1.332070, 3.789947, 0.920748, 3.918159, 4.155454]
### 8
mean: [-3.724016, 2.351268, 4.315180, -5.165184, 3.826488, -4.358513, 5.892025, 4.498894]
std: [4.630134, 2.226592, 3.994006, 5.073404, 3.467395, 3.571145, 6.164876, 4.158951]
fourier: [[68.789848, 68.842642, 84.742102, 86.544637, 335.161413], [32.765567, 35.167273, 36.258890, 43.041229, 211.614138], [58.677777, 61.081329, 71.383477, 75.967487, 388.366164], [74.745136, 81.142934, 85.952670, 97.239548, 464.866609], [51.231900, 55.659835, 58.160225, 66.966646, 344.383921], [52.956621, 56.230986, 58.765249, 69.505228, 392.266175], [90.860972, 92.939290, 111.755678, 115.941900, 530.282266], [60.945226, 65.043995, 73.002077, 79.575101, 404.900393]]
input_correlations: [[0.457057, -0.937314, 0.793691, -0.900604, -0.955136, 0.714595, 0.799737, -0.959189], [-0.287350, 0.987855, -0.657609, 0.967263, 0.994474, -0.563809, -0.664810, 0.990497], [-0.437487, 0.950000, -0.766638, 0.917769, 0.965801, -0.688394, -0.772773, 0.971693], [0.364828, -0.972786, 0.711653, -0.947429, -0.983996, 0.624522, 0.718632, -0.986497], [-0.358043, 0.975529, -0.702415, 0.951089, 0.985970, -0.616122, -0.709363, 0.988600], [0.271401, -0.991347, 0.638484, -0.972457, -0.997028, 0.542939, 0.646293, -0.994165], [-0.461549, 0.940233, -0.786092, 0.905940, 0.957478, -0.710009, -0.791957, 0.964147], [-0.427780, 0.956438, -0.747575, 0.928005, 0.970802, -0.670376, -0.753811, 0.978811]]
pre_activation_mean: [-3.724016, 2.351268, 4.315180, -5.165184, 3.826488, -4.358513, 5.892025, 4.498894]
pre_activation_std: [4.630134, 2.226592, 3.994006, 5.073404, 3.467395, 3.571145, 6.164876, 4.158951]
### 10
mean: [-10.454456]
std: [8.385388]
fourier: [[124.775945, 136.267400, 139.367556, 164.182879, 940.901035]]
input_correlations: [[0.691569, -0.979632, -0.996819, 0.696272, -0.991008, 0.654306, -0.995024, -0.994995]]
pre_activation_mean: [-10.454456]
pre_activation_std: [8.385388]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
-0.589685,
-0.052098,
0.534455,
0.41645,
0.114751
],
[
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-0.099345,
-0.147478,
-0.19416
],
[
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0.341533,
-0.435642,
0.137342,
-0.042322
],
[
-0.289511,
-0.38326,
-0.058668,
0.115821,
-0.088718
],
[
-0.720072,
0.241226,
0.311126,
-0.040068,
-0.181589
],
[
0.51622,
0.298259,
-0.122088,
-0.223249,
0.845913
],
[
0.453979,
0.39351,
-0.149404,
-0.088132,
-0.072954
],
[
0.267001,
-0.056578,
-0.098858,
-0.42381,
0.332598
]
],
"network.0.bias": [
0.553343,
0.464339,
0.390854,
-0.375292,
-0.094847,
-0.125861,
-0.286012,
0.197789
],
"network.2.weight": [
[
0.182957,
0.520468,
-0.396303,
0.249129,
-0.45853,
0.144217,
0.430795,
-0.226877
],
[
0.214803,
-0.335127,
0.441677,
-0.402437,
-0.138117,
-0.109012,
-0.188448,
0.258414
],
[
0.408094,
-0.208798,
0.147896,
-0.499669,
0.514319,
0.283035,
-0.296188,
0.496014
],
[
-0.04872,
0.502456,
0.065652,
0.309807,
-0.164125,
0.02482,
0.286288,
-0.499563
],
[
0.573976,
-0.435152,
0.106686,
-0.602066,
0.323543,
0.426165,
-0.186979,
0.286976
],
[
-0.061287,
0.385847,
-0.130916,
-0.272349,
-0.524357,
-0.099371,
0.074838,
-0.446245
],
[
-0.184317,
-0.164525,
0.253229,
0.282485,
-0.029603,
-0.288867,
-0.05648,
0.072208
],
[
0.539144,
-0.313007,
0.609053,
-0.253839,
0.58539,
0.531472,
-0.21918,
-0.215592
]
],
"network.2.bias": [
0.105434,
0.400933,
0.348522,
0.350341,
0.702077,
0.12444,
-0.446568,
0.185127
],
"network.4.weight": [
[
0.267931,
0.006063,
0.409632,
-0.339577,
0.396721,
0.032719,
-0.411612,
0.500579
],
[
-0.291614,
-0.252537,
-0.080155,
-0.101743,
0.147108,
0.439726,
-0.339253,
0.016916
],
[
-0.178846,
0.404807,
0.118628,
-0.207467,
0.625236,
-0.473509,
-0.490312,
0.363436
],
[
-0.253345,
0.313395,
0.78475,
-0.084828,
0.650822,
-0.000283,
0.016854,
0.369392
],
[
0.298488,
-0.724649,
-0.197587,
0.346713,
-0.32313,
0.412595,
-0.461787,
-0.330171
],
[
0.075628,
-0.412894,
-0.052313,
-0.0573,
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-0.04901,
-0.143977,
-0.102092
],
[
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0.491437,
-0.084175,
-0.219864,
0.091423,
-0.234989,
0.327052,
0.440042
],
[
0.376835,
-0.55282,
-0.243353,
0.391012,
-0.301274,
0.375163,
-0.338371,
-0.447764
]
],
"network.4.bias": [
0.06288,
-0.100917,
0.602675,
0.201013,
0.040937,
-0.235947,
-0.39046,
0.189409
],
"network.6.weight": [
[
0.185894,
0.432856,
-0.206535,
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0.317224,
0.235758,
-0.166376,
0.052321
],
[
0.318524,
-0.005797,
0.429093,
0.483734,
-0.297916,
0.139555,
0.009844,
-0.074838
],
[
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0.489017
],
[
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0.342293,
0.218789,
0.253685,
0.17742,
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],
[
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0.45033,
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-0.082094,
-0.059595,
-0.593288
],
[
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0.051805,
0.132213,
0.431835,
-0.186845,
-0.043984,
0.350286
],
[
0.005857,
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-0.726557,
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0.330467,
-0.094979,
-0.456555,
0.646405
],
[
0.277534,
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0.712594,
0.378734,
-0.697946,
-0.530532,
0.30142,
-0.606661
]
],
"network.6.bias": [
-0.003454,
-0.260049,
0.056884,
-0.448138,
0.20299,
-0.305869,
0.149028,
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],
"network.8.weight": [
[
0.258973,
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0.509654,
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],
[
0.395969,
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0.372916,
0.414711,
-0.413984,
0.089011,
-0.033777
],
[
0.016848,
0.099929,
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0.544005,
-0.482138,
-0.185505,
0.496431
],
[
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0.646913,
-0.310728,
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-0.088822,
0.145708,
-0.625672
],
[
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0.742961,
-0.182495,
-0.144038,
0.125947,
0.023701,
-0.2322,
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],
[
-0.014199,
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0.053726,
0.057494,
-0.317058,
-0.102288,
0.295211,
-0.176767
],
[
-0.448056,
0.632854,
-0.45274,
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0.573255,
-0.478026,
-0.506363,
0.602094
],
[
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0.398599,
-0.359148,
-0.4358,
0.668526
]
],
"network.8.bias": [
0.397874,
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0.083661,
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],
"network.10.weight": [
[
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0.270211,
-0.288748,
0.265607,
-0.618137,
-0.630583
]
],
"network.10.bias": [
0.244513
]
}
## Activation Signature
### 0
mean: [0.772530, 2.468380, 4.762798, 0.539120, 4.111729, 0.138594, 6.762283, 4.938472]
std: [1.819812, 2.027533, 3.238378, 1.255538, 3.014353, 0.362109, 4.695432, 3.435279]
fourier: [[27.046993, 37.549926, 37.806378, 37.837912, 69.527699], [30.741322, 31.797982, 34.444532, 39.474239, 222.154172], [48.740295, 51.145322, 53.654519, 64.222018, 428.651795], [18.854217, 25.933192, 26.354859, 26.355897, 48.520846], [44.502904, 46.798140, 50.839141, 59.495601, 370.055659], [5.411999, 7.343009, 7.541085, 7.875551, 12.473422], [72.064974, 72.189090, 78.368098, 92.882077, 608.605428], [53.083506, 53.779937, 57.736504, 68.033080, 444.462489]]
input_correlations: [[-0.551226, 0.013761, 0.422540, 0.572224, 0.212504, 0.000000, 0.000000, 0.000000], [0.858373, 0.694057, 0.212742, -0.046310, -0.089457, 0.000000, 0.000000, 0.000000], [-0.179524, 0.473433, -0.708326, 0.450471, -0.221987, 0.000000, 0.000000, 0.000000], [-0.811123, -0.765035, -0.440753, 0.010296, -0.232073, 0.000000, 0.000000, 0.000000], [-0.831936, 0.047527, 0.118720, 0.062539, -0.340294, 0.000000, 0.000000, 0.000000], [0.698286, 0.330672, 0.261028, -0.049760, 0.778929, 0.000000, 0.000000, 0.000000], [0.833106, 0.716804, 0.103456, -0.009579, -0.046202, 0.000000, 0.000000, 0.000000], [0.502259, -0.217132, 0.065670, -0.717175, 0.450304, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.875575, 1.634915, 0.281045, -1.417556, -0.211344, 1.369559, 0.404942, -0.278176]
pre_activation_std: [1.639787, 1.998467, 1.063352, 1.108873, 1.417276, 2.090200, 1.266564, 1.193675]
### 2
mean: [1.347044, 0.244998, 1.445268, 1.096964, 1.905259, 0.213028, -1.436037, 1.820319]
std: [1.575377, 1.125529, 1.133457, 1.343869, 1.514894, 0.838703, 0.779203, 1.432069]
fourier: [[25.430237, 25.705223, 26.369097, 28.257900, 121.233985], [18.680167, 18.833129, 19.298049, 19.664978, 22.049803], [16.043582, 18.472483, 19.409218, 22.242934, 130.074088], [20.357369, 20.713174, 22.567191, 23.047278, 98.726748], [22.981748, 23.089702, 23.394995, 27.834812, 171.473318], [11.477115, 11.754062, 13.576661, 14.544365, 19.172551], [13.081961, 13.959592, 14.404454, 15.752424, 129.243312], [22.154640, 22.869396, 25.256726, 27.004103, 163.828746]]
input_correlations: [[-0.372926, 0.946853, -0.047502, 0.677734, -0.250351, 0.715061, 0.953702, 0.307112], [0.593415, -0.944342, 0.138731, -0.630041, 0.226917, -0.610870, -0.932261, -0.344434], [0.812058, -0.595994, -0.115526, -0.274266, 0.433665, 0.051240, -0.602533, 0.096067], [-0.478171, 0.976096, 0.208264, 0.654871, -0.176772, 0.482094, 0.982417, 0.107944], [0.825839, -0.656659, -0.145769, -0.325946, 0.315917, 0.043801, -0.646772, 0.006727], [-0.628242, 0.850996, 0.102928, 0.485821, -0.402086, 0.292528, 0.863951, -0.024404], [-0.020841, -0.668085, 0.233890, -0.552158, 0.088471, -0.900252, -0.671360, -0.446047], [0.875459, -0.481125, 0.131609, -0.188077, 0.428581, 0.081295, -0.462801, -0.124102]]
pre_activation_mean: [1.347044, 0.244998, 1.445268, 1.096964, 1.905259, 0.213028, -1.436037, 1.820319]
pre_activation_std: [1.575377, 1.125529, 1.133457, 1.343869, 1.514894, 0.838703, 0.779203, 1.432069]
### 4
mean: [2.358762, -0.319381, 2.299825, 2.981736, -0.905268, -1.553594, 0.231237, -0.790318]
std: [1.758815, 0.342951, 2.258453, 2.629371, 2.265682, 0.959631, 1.258120, 2.488115]
fourier: [[27.043992, 27.092588, 28.921792, 33.067938, 212.288595], [5.620372, 5.800245, 5.803334, 6.565347, 28.744283], [34.889373, 35.331822, 38.686790, 41.498330, 206.984294], [38.992020, 41.745598, 42.677647, 49.969566, 268.356241], [35.189526, 36.546689, 39.591328, 39.902818, 81.474079], [14.969223, 14.990750, 15.990977, 18.252818, 139.823425], [19.066047, 20.811371, 20.938911, 22.287786, 22.821858], [38.405451, 39.923172, 43.614427, 44.088808, 71.128635]]
input_correlations: [[-0.369433, 0.564287, 0.985142, -0.558824, 0.992671, -0.650151, 0.150314, 0.962043], [-0.970803, 0.595285, 0.427326, -0.942285, 0.460198, -0.860238, -0.711272, 0.317341], [-0.700939, 0.733190, 0.916834, -0.820220, 0.938532, -0.874313, -0.222671, 0.873007], [-0.576190, 0.676182, 0.968948, -0.723192, 0.979226, -0.791968, -0.068855, 0.927204], [0.796101, -0.774275, -0.854273, 0.885122, -0.879781, 0.918981, 0.351357, -0.801294], [0.502333, -0.727921, -0.952881, 0.654085, -0.982131, 0.712973, 0.018526, -0.943250], [-0.755097, 0.796322, 0.861828, -0.833722, 0.892118, -0.888193, -0.321107, 0.849632], [0.795935, -0.759194, -0.858742, 0.883517, -0.880938, 0.922485, 0.347145, -0.806076]]
pre_activation_mean: [2.358762, -0.319381, 2.299825, 2.981736, -0.905268, -1.553594, 0.231237, -0.790318]
pre_activation_std: [1.758815, 0.342951, 2.258453, 2.629371, 2.265682, 0.959631, 1.258120, 2.488115]
### 6
mean: [0.468882, 2.876293, -1.914389, 1.245716, 3.912918, 0.524394, -3.049751, 3.621419]
std: [0.429807, 2.798632, 3.189187, 1.332070, 3.789947, 0.920748, 3.918159, 4.155454]
fourier: [[7.195687, 8.443154, 8.755113, 9.658758, 42.199418], [41.461460, 45.202849, 45.549728, 53.750142, 258.866335], [45.712502, 46.623908, 57.638149, 60.092215, 172.295026], [19.947708, 21.630811, 23.104402, 25.376375, 112.114468], [56.030599, 58.554015, 65.606799, 72.177619, 352.162685], [14.028297, 17.693280, 19.376086, 20.623711, 47.195426], [59.562827, 61.386397, 68.960518, 72.979244, 274.477627], [60.824040, 61.482497, 76.279354, 76.431576, 325.927717]]
input_correlations: [[0.013730, -0.579461, -0.177251, -0.085973, 0.822458, 0.544180, 0.021663, 0.819196], [0.963939, 0.465081, 0.987183, 0.988979, -0.693244, 0.542902, 0.875642, -0.703011], [-0.875924, -0.566196, -0.931718, -0.916195, 0.857217, -0.329597, -0.763887, 0.864353], [0.965792, 0.429232, 0.995783, 0.996805, -0.570111, 0.657761, 0.936495, -0.582108], [0.946249, 0.489299, 0.973089, 0.972181, -0.753727, 0.473725, 0.838018, -0.762452], [-0.350485, -0.564160, -0.440865, -0.397271, 0.977574, 0.345621, -0.175815, 0.974242], [-0.909728, -0.549149, -0.969292, -0.953639, 0.790672, -0.430111, -0.835103, 0.799661], [0.893637, 0.551610, 0.947948, 0.933339, -0.831995, 0.370437, 0.793177, -0.839788]]
pre_activation_mean: [0.468882, 2.876293, -1.914389, 1.245716, 3.912918, 0.524394, -3.049751, 3.621419]
pre_activation_std: [0.429807, 2.798632, 3.189187, 1.332070, 3.789947, 0.920748, 3.918159, 4.155454]
### 8
mean: [-3.724016, 2.351268, 4.315180, -5.165184, 3.826488, -4.358513, 5.892025, 4.498894]
std: [4.630134, 2.226592, 3.994006, 5.073404, 3.467395, 3.571145, 6.164876, 4.158951]
fourier: [[68.789848, 68.842642, 84.742102, 86.544637, 335.161413], [32.765567, 35.167273, 36.258890, 43.041229, 211.614138], [58.677777, 61.081329, 71.383477, 75.967487, 388.366164], [74.745136, 81.142934, 85.952670, 97.239548, 464.866609], [51.231900, 55.659835, 58.160225, 66.966646, 344.383921], [52.956621, 56.230986, 58.765249, 69.505228, 392.266175], [90.860972, 92.939290, 111.755678, 115.941900, 530.282266], [60.945226, 65.043995, 73.002077, 79.575101, 404.900393]]
input_correlations: [[0.457057, -0.937314, 0.793691, -0.900604, -0.955136, 0.714595, 0.799737, -0.959189], [-0.287350, 0.987855, -0.657609, 0.967263, 0.994474, -0.563809, -0.664810, 0.990497], [-0.437487, 0.950000, -0.766638, 0.917769, 0.965801, -0.688394, -0.772773, 0.971693], [0.364828, -0.972786, 0.711653, -0.947429, -0.983996, 0.624522, 0.718632, -0.986497], [-0.358043, 0.975529, -0.702415, 0.951089, 0.985970, -0.616122, -0.709363, 0.988600], [0.271401, -0.991347, 0.638484, -0.972457, -0.997028, 0.542939, 0.646293, -0.994165], [-0.461549, 0.940233, -0.786092, 0.905940, 0.957478, -0.710009, -0.791957, 0.964147], [-0.427780, 0.956438, -0.747575, 0.928005, 0.970802, -0.670376, -0.753811, 0.978811]]
pre_activation_mean: [-3.724016, 2.351268, 4.315180, -5.165184, 3.826488, -4.358513, 5.892025, 4.498894]
pre_activation_std: [4.630134, 2.226592, 3.994006, 5.073404, 3.467395, 3.571145, 6.164876, 4.158951]
### 10
mean: [-10.454456]
std: [8.385388]
fourier: [[124.775945, 136.267400, 139.367556, 164.182879, 940.901035]]
input_correlations: [[0.691569, -0.979632, -0.996819, 0.696272, -0.991008, 0.654306, -0.995024, -0.994995]]
pre_activation_mean: [-10.454456]
pre_activation_std: [8.385388]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.7725299596786499, "std": 1.8198124170303345, "fourier": [27.046993321310993, 37.54992631930413, 37.80637791257873, 37.83791245967013, 69.52769889817834], "input_correlations": [-0.5512257032196923, 0.013760555859402708, 0.4225396121410722, 0.5722237939149264, 0.21250396609178687, 0.0, 0.0, 0.0], "pre_activation_mean": 1.875575065612793, "pre_activation_std": 1.6397866010665894}, "1": {"mean": 2.4683797359466553, "std": 2.0275330543518066, "fourier": [30.74132156565001, 31.797981676393846, 34.44453240787671, 39.47423892278861, 222.15417249314487], "input_correlations": [0.8583733432678471, 0.6940572871719689, 0.21274191477348364, -0.04630975540253731, -0.08945748594369128, 0.0, 0.0, 0.0], "pre_activation_mean": 1.6349151134490967, "pre_activation_std": 1.9984667301177979}, "2": {"mean": 4.762797832489014, "std": 3.238377571105957, "fourier": [48.74029450430609, 51.14532199748655, 53.654519230496966, 64.22201770333612, 428.6517950915222], "input_correlations": [-0.17952356297759953, 0.47343332718021003, -0.7083259348136758, 0.45047059884124535, -0.22198744364974218, 0.0, 0.0, 0.0], "pre_activation_mean": 0.2810452878475189, "pre_activation_std": 1.0633524656295776}, "3": {"mean": 0.5391204953193665, "std": 1.255537509918213, "fourier": [18.854217094033846, 25.93319173843329, 26.354858530786267, 26.355896968477936, 48.52084615667329], "input_correlations": [-0.8111227734489707, -0.7650348613936565, -0.44075268698971, 0.01029642442487844, -0.2320734450345007, 0.0, 0.0, 0.0], "pre_activation_mean": -1.417555570602417, "pre_activation_std": 1.1088731288909912}, "4": {"mean": 4.111729145050049, "std": 3.014352798461914, "fourier": [44.50290379804009, 46.7981396931757, 50.83914056147229, 59.49560067955489, 370.0556593099609], "input_correlations": [-0.8319360273515722, 0.04752713138877526, 0.1187203745884297, 0.06253915457361019, -0.34029376562711355, 0.0, 0.0, 0.0], "pre_activation_mean": -0.2113436758518219, "pre_activation_std": 1.41727614402771}, "5": {"mean": 0.13859358429908752, "std": 0.3621087074279785, "fourier": [5.411999446610312, 7.343009112363258, 7.541084516981101, 7.8755506983295875, 12.473421873414694], "input_correlations": [0.6982857131794521, 0.33067213790155703, 0.2610283661277576, -0.049759837721112254, 0.7789290699232322, 0.0, 0.0, 0.0], "pre_activation_mean": 1.369559407234192, "pre_activation_std": 2.090200185775757}, "6": {"mean": 6.762282848358154, "std": 4.695431709289551, "fourier": [72.06497380919174, 72.18908994148829, 78.36809834570646, 92.88207732985299, 608.6054283554176], "input_correlations": [0.8331058087816018, 0.7168037830889293, 0.10345604417871408, -0.0095786609033811, -0.04620224190025517, 0.0, 0.0, 0.0], "pre_activation_mean": 0.4049416780471802, "pre_activation_std": 1.2665643692016602}, "7": {"mean": 4.938472270965576, "std": 3.435279369354248, "fourier": [53.08350608479084, 53.77993743826889, 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"fourier": [18.680166512960877, 18.83312891164817, 19.29804897650666, 19.664978077679727, 22.049802780151367], "input_correlations": [0.5934150103607143, -0.9443422873973537, 0.13873075649979014, -0.6300413762094235, 0.22691689213279903, -0.6108701546954244, -0.9322613191261353, -0.34443407803588544], "pre_activation_mean": 0.24499782919883728, "pre_activation_std": 1.125529170036316}, "2": {"mean": 1.4452675580978394, "std": 1.1334574222564697, "fourier": [16.04358154006693, 18.472482524838966, 19.409217694063003, 22.24293381360181, 130.07408809661865], "input_correlations": [0.8120575019224059, -0.5959941278385001, -0.11552630841049374, -0.2742655482236865, 0.43366549246624647, 0.0512403224072391, -0.6025332510565571, 0.0960669053211563], "pre_activation_mean": 1.4452675580978394, "pre_activation_std": 1.1334574222564697}, "3": {"mean": 1.0969637632369995, "std": 1.3438687324523926, "fourier": [20.35736851581017, 20.713174371519614, 22.567190799083907, 23.04727785656289, 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"final_val_loss": 0.395503968000412, "initial_val_acc": 0.54, "final_val_acc": 0.82, "best_val_acc": 0.82}, "improved_stage": {"initial_val_loss": 0.1405176967382431, "final_val_loss": 0.1471828818321228, "initial_val_acc": 0.96, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 3}, "improvement": 0.16000000000000003, "first_improvement_epoch": 1}} |
65 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.5, "improved_accuracy": 0.8, "improvement": 0.30000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2617, "learning_rate": 0.03671955834795707, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [-0.012243, 4.225056, 0.255394, 3.479089, 3.538147, 4.060287, 0.223721]
std: [0.181338, 4.689068, 0.477784, 3.970679, 4.028340, 4.408423, 0.420826]
fourier: [[2.546393, 2.686753, 3.122725, 3.165745, 3.385003], [83.060303, 92.245798, 97.875173, 108.832790, 380.255049], [7.361428, 7.636644, 7.849500, 9.132311, 22.985436], [69.551142, 77.945269, 82.974313, 92.284876, 313.117980], [70.778627, 79.160460, 84.041269, 93.679972, 318.433213], [78.806153, 86.612969, 91.784906, 102.315006, 365.425866], [6.501519, 6.514063, 7.172305, 8.057924, 20.134923]]
input_correlations: [[-0.402091, -0.645159, -0.606383, -0.176409, -0.676443, 0.000000, 0.000000, 0.000000], [-0.539347, -0.495083, -0.340827, -0.753711, -0.498748, 0.000000, 0.000000, 0.000000], [0.921421, 0.262876, 0.082875, -0.323306, -0.058722, 0.000000, 0.000000, 0.000000], [-0.372876, 0.393108, -0.035579, 0.513222, -0.676777, 0.000000, 0.000000, 0.000000], [0.278397, 0.097352, 0.467662, 0.583578, 0.800285, 0.000000, 0.000000, 0.000000], [0.115347, -0.123945, 0.495453, 0.119203, -0.597993, 0.000000, 0.000000, 0.000000], [-0.815068, -0.572477, -0.696435, -0.113393, 0.001802, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.285136, -3.292943, 0.216123, 0.473543, 2.026607, 0.666270, -2.146305]
pre_activation_std: [1.191418, 2.295350, 1.229690, 1.431426, 1.923289, 1.010989, 1.670040]
### 2
mean: [0.716996, -0.679962, -0.990608, 0.771943, -0.364512, 0.353160, 0.670994]
std: [1.133339, 0.418903, 0.681382, 0.959854, 0.815991, 0.843859, 0.858337]
fourier: [[17.355848, 18.008331, 23.920239, 26.119667, 64.529625], [7.558742, 7.914704, 8.877002, 9.224678, 61.196618], [10.355842, 10.671477, 13.813818, 15.776724, 89.154698], [15.625339, 16.395095, 17.082342, 19.116223, 69.474847], [14.617402, 14.736664, 15.415905, 18.551297, 32.806078], [13.685043, 15.194767, 15.624705, 18.952975, 31.784417], [13.630533, 16.106744, 18.302239, 18.651669, 60.389435]]
input_correlations: [[0.039105, 0.444048, 0.286266, -0.367574, 0.907636, -0.319380, 0.300167, 0.000000], [0.192322, -0.444897, -0.753576, 0.174327, -0.675915, -0.156133, -0.403646, 0.000000], [0.061714, -0.380168, -0.173622, 0.070663, -0.858587, -0.474109, -0.404182, 0.000000], [-0.034561, 0.117702, -0.790217, 0.729595, 0.258083, 0.298029, -0.018749, 0.000000], [-0.004846, -0.357737, -0.804902, 0.522562, -0.463275, 0.415207, -0.258552, 0.000000], [0.043609, 0.017967, 0.875534, -0.720019, -0.025929, -0.195847, 0.104145, 0.000000], [-0.119567, -0.142567, -0.620192, 0.806139, -0.327814, 0.612240, -0.122520, 0.000000]]
pre_activation_mean: [0.716996, -0.679962, -0.990608, 0.771943, -0.364512, 0.353160, 0.670994]
pre_activation_std: [1.133339, 0.418903, 0.681382, 0.959854, 0.815991, 0.843859, 0.858337]
### 4
mean: [0.547183, 0.739523, 0.269277, 1.221474, 0.569432, 0.867452, 0.010600]
std: [0.654562, 0.859903, 0.591308, 0.679409, 0.852957, 0.667618, 1.453303]
fourier: [[11.103748, 11.647156, 14.600248, 15.025447, 49.246444], [15.896318, 16.466595, 17.313472, 20.352490, 66.557043], [10.254112, 11.175043, 11.546525, 13.946701, 24.234933], [11.184105, 12.202003, 14.437995, 15.679039, 109.932661], [16.041299, 16.400139, 16.431295, 20.380585, 51.248915], [11.154518, 11.501415, 14.989284, 15.371445, 78.070664], [22.207880, 26.561196, 26.643272, 29.521920, 34.070062]]
input_correlations: [[0.938458, 0.127015, 0.070170, -0.356384, -0.644416, 0.482955, -0.776815, 0.000000], [0.846559, 0.232187, 0.004718, -0.566809, -0.631854, 0.673084, -0.850531, 0.000000], [0.598540, 0.293087, -0.094448, -0.714582, -0.676188, 0.883755, -0.867262, 0.000000], [0.912102, 0.088734, 0.054624, -0.324040, -0.572284, 0.587705, -0.702917, 0.000000], [0.809926, 0.251650, 0.003445, -0.593340, -0.637260, 0.728959, -0.850509, 0.000000], [0.931809, 0.084129, 0.055803, -0.335815, -0.693971, 0.438710, -0.778817, 0.000000], [-0.736227, -0.317919, 0.032861, 0.708224, 0.698311, -0.742926, 0.921778, 0.000000]]
pre_activation_mean: [0.547183, 0.739523, 0.269277, 1.221474, 0.569432, 0.867452, 0.010600]
pre_activation_std: [0.654562, 0.859903, 0.591308, 0.679409, 0.852957, 0.667618, 1.453303]
### 6
mean: [0.906500, -0.332449, -0.449711, 1.544283, -0.288801, -0.540092, -0.379064]
std: [1.218081, 0.777626, 1.241985, 2.177372, 0.393486, 1.618244, 0.875488]
fourier: [[22.415491, 23.899087, 24.602426, 28.292316, 81.584967], [14.465382, 15.075019, 15.837333, 18.278821, 29.920410], [23.129859, 24.338098, 24.684767, 29.098498, 40.473999], [40.343742, 40.976871, 46.042743, 50.905891, 138.985501], [6.721508, 6.758741, 8.795142, 8.898722, 25.992047], [30.444752, 31.406793, 32.506807, 37.971148, 48.608241], [16.377814, 17.230693, 17.515115, 20.458167, 34.115797]]
input_correlations: [[0.931304, 0.963959, 0.849241, 0.932658, 0.943875, 0.942821, -0.813380, 0.000000], [-0.946152, -0.984595, -0.875422, -0.956164, -0.970597, -0.948249, 0.761782, 0.000000], [-0.918703, -0.972818, -0.883970, -0.930389, -0.960346, -0.922932, 0.802845, 0.000000], [0.966881, 0.989077, 0.857268, 0.971349, 0.972670, 0.967446, -0.723085, 0.000000], [-0.970852, -0.928686, -0.707113, -0.939372, -0.888936, -0.990755, 0.714979, 0.000000], [-0.940261, -0.990945, -0.899037, -0.957276, -0.982823, -0.935765, 0.738303, 0.000000], [-0.933561, -0.984942, -0.890094, -0.945062, -0.974287, -0.931628, 0.765990, 0.000000]]
pre_activation_mean: [0.906500, -0.332449, -0.449711, 1.544283, -0.288801, -0.540092, -0.379064]
pre_activation_std: [1.218081, 0.777626, 1.241985, 2.177372, 0.393486, 1.618244, 0.875488]
### 8
mean: [1.459418, 1.522344, 0.360720, 1.629290, 1.831666, 1.762677, 0.900022]
std: [2.109866, 2.143950, 0.771749, 1.945180, 2.176354, 2.128386, 1.202578]
fourier: [[39.448533, 40.583725, 43.685996, 49.061270, 131.347666], [39.916304, 41.366390, 44.620536, 49.652668, 137.010936], [11.852664, 12.182204, 15.260332, 16.261509, 32.464828], [36.947222, 37.205178, 39.503218, 45.388914, 146.636065], [41.001600, 41.939807, 44.719001, 50.658817, 164.849901], [40.272663, 40.983665, 43.044216, 49.500480, 158.640930], [21.782601, 23.159600, 23.980970, 27.540057, 81.002023]]
input_correlations: [[0.998612, -0.715724, -0.644941, 0.990803, -0.835679, -0.687609, -0.678274, 0.000000], [0.999266, -0.701620, -0.631324, 0.993141, -0.823234, -0.674224, -0.664901, 0.000000], [-0.833984, 0.967338, 0.944771, -0.781182, 0.948253, 0.962514, 0.957071, 0.000000], [0.993404, -0.758641, -0.694375, 0.979857, -0.860512, -0.734048, -0.725306, 0.000000], [0.997336, -0.732051, -0.663372, 0.987236, -0.844906, -0.704767, -0.696396, 0.000000], [0.991549, -0.769438, -0.705908, 0.976373, -0.868133, -0.745262, -0.736331, 0.000000], [0.965880, -0.843075, -0.793546, 0.939210, -0.904729, -0.826740, -0.818338, 0.000000]]
pre_activation_mean: [1.459418, 1.522344, 0.360720, 1.629290, 1.831666, 1.762677, 0.900022]
pre_activation_std: [2.109866, 2.143950, 0.771749, 1.945180, 2.176354, 2.128386, 1.202578]
### 10
mean: [-0.396285, 4.083553, -2.658192, 3.436909, 3.398202, 3.972927, -3.054229]
std: [0.649229, 4.834357, 3.631198, 4.019642, 4.173470, 4.502016, 4.085890]
fourier: [[12.017284, 12.687355, 12.702312, 15.238870, 35.665657], [88.523726, 94.568585, 99.968288, 112.152526, 367.519812], [67.696205, 70.666549, 74.419781, 84.257998, 239.237269], [72.169741, 78.924969, 83.758196, 92.992492, 309.321860], [76.312089, 81.608081, 86.320302, 96.955566, 305.838187], [82.602208, 88.059464, 92.998279, 104.243233, 357.563378], [74.809559, 79.883139, 84.484847, 94.882695, 274.880643]]
input_correlations: [[-0.957188, -0.956194, 0.859741, -0.977346, -0.972884, -0.978826, -0.986501, 0.000000], [0.995652, 0.995210, -0.739025, 0.999933, 0.999578, 0.999828, 0.998052, 0.000000], [-0.991089, -0.990486, 0.765183, -0.998892, -0.997609, -0.999216, -0.999515, 0.000000], [0.998514, 0.998205, -0.711531, 0.999394, 0.999926, 0.998909, 0.995119, 0.000000], [0.995882, 0.995441, -0.737664, 0.999930, 0.999637, 0.999790, 0.997862, 0.000000], [0.995186, 0.994699, -0.740950, 0.999943, 0.999448, 0.999936, 0.998421, 0.000000], [-0.995637, -0.995191, 0.739308, -0.999924, -0.999568, -0.999817, -0.998033, 0.000000]]
pre_activation_mean: [-0.396285, 4.083553, -2.658192, 3.436909, 3.398202, 3.972927, -3.054229]
pre_activation_std: [0.649229, 4.834357, 3.631198, 4.019642, 4.173470, 4.502016, 4.085890]
### 12
mean: [-7.718015]
std: [9.292990]
fourier: [[168.668958, 182.163958, 192.811146, 215.704632, 694.621347]]
input_correlations: [[0.642967, -0.999226, 0.556817, -0.998164, -0.998598, -0.999709, 0.556514, 0.000000]]
pre_activation_mean: [-7.718015]
pre_activation_std: [9.292990]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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-0.358424
],
[
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-0.13131,
-0.163288,
-0.099246
],
[
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0.340002,
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],
[
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0.322601,
0.520869,
0.642563
],
[
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-0.468246
],
[
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-0.081589,
0.215674
]
],
"network.0.bias": [
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-0.087152,
0.134834,
0.063419,
-0.341724,
0.392356,
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## Activation Signature
### 0
mean: [-0.012243, 4.225056, 0.255394, 3.479089, 3.538147, 4.060287, 0.223721]
std: [0.181338, 4.689068, 0.477784, 3.970679, 4.028340, 4.408423, 0.420826]
fourier: [[2.546393, 2.686753, 3.122725, 3.165745, 3.385003], [83.060303, 92.245798, 97.875173, 108.832790, 380.255049], [7.361428, 7.636644, 7.849500, 9.132311, 22.985436], [69.551142, 77.945269, 82.974313, 92.284876, 313.117980], [70.778627, 79.160460, 84.041269, 93.679972, 318.433213], [78.806153, 86.612969, 91.784906, 102.315006, 365.425866], [6.501519, 6.514063, 7.172305, 8.057924, 20.134923]]
input_correlations: [[-0.402091, -0.645159, -0.606383, -0.176409, -0.676443, 0.000000, 0.000000, 0.000000], [-0.539347, -0.495083, -0.340827, -0.753711, -0.498748, 0.000000, 0.000000, 0.000000], [0.921421, 0.262876, 0.082875, -0.323306, -0.058722, 0.000000, 0.000000, 0.000000], [-0.372876, 0.393108, -0.035579, 0.513222, -0.676777, 0.000000, 0.000000, 0.000000], [0.278397, 0.097352, 0.467662, 0.583578, 0.800285, 0.000000, 0.000000, 0.000000], [0.115347, -0.123945, 0.495453, 0.119203, -0.597993, 0.000000, 0.000000, 0.000000], [-0.815068, -0.572477, -0.696435, -0.113393, 0.001802, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.285136, -3.292943, 0.216123, 0.473543, 2.026607, 0.666270, -2.146305]
pre_activation_std: [1.191418, 2.295350, 1.229690, 1.431426, 1.923289, 1.010989, 1.670040]
### 2
mean: [0.716996, -0.679962, -0.990608, 0.771943, -0.364512, 0.353160, 0.670994]
std: [1.133339, 0.418903, 0.681382, 0.959854, 0.815991, 0.843859, 0.858337]
fourier: [[17.355848, 18.008331, 23.920239, 26.119667, 64.529625], [7.558742, 7.914704, 8.877002, 9.224678, 61.196618], [10.355842, 10.671477, 13.813818, 15.776724, 89.154698], [15.625339, 16.395095, 17.082342, 19.116223, 69.474847], [14.617402, 14.736664, 15.415905, 18.551297, 32.806078], [13.685043, 15.194767, 15.624705, 18.952975, 31.784417], [13.630533, 16.106744, 18.302239, 18.651669, 60.389435]]
input_correlations: [[0.039105, 0.444048, 0.286266, -0.367574, 0.907636, -0.319380, 0.300167, 0.000000], [0.192322, -0.444897, -0.753576, 0.174327, -0.675915, -0.156133, -0.403646, 0.000000], [0.061714, -0.380168, -0.173622, 0.070663, -0.858587, -0.474109, -0.404182, 0.000000], [-0.034561, 0.117702, -0.790217, 0.729595, 0.258083, 0.298029, -0.018749, 0.000000], [-0.004846, -0.357737, -0.804902, 0.522562, -0.463275, 0.415207, -0.258552, 0.000000], [0.043609, 0.017967, 0.875534, -0.720019, -0.025929, -0.195847, 0.104145, 0.000000], [-0.119567, -0.142567, -0.620192, 0.806139, -0.327814, 0.612240, -0.122520, 0.000000]]
pre_activation_mean: [0.716996, -0.679962, -0.990608, 0.771943, -0.364512, 0.353160, 0.670994]
pre_activation_std: [1.133339, 0.418903, 0.681382, 0.959854, 0.815991, 0.843859, 0.858337]
### 4
mean: [0.547183, 0.739523, 0.269277, 1.221474, 0.569432, 0.867452, 0.010600]
std: [0.654562, 0.859903, 0.591308, 0.679409, 0.852957, 0.667618, 1.453303]
fourier: [[11.103748, 11.647156, 14.600248, 15.025447, 49.246444], [15.896318, 16.466595, 17.313472, 20.352490, 66.557043], [10.254112, 11.175043, 11.546525, 13.946701, 24.234933], [11.184105, 12.202003, 14.437995, 15.679039, 109.932661], [16.041299, 16.400139, 16.431295, 20.380585, 51.248915], [11.154518, 11.501415, 14.989284, 15.371445, 78.070664], [22.207880, 26.561196, 26.643272, 29.521920, 34.070062]]
input_correlations: [[0.938458, 0.127015, 0.070170, -0.356384, -0.644416, 0.482955, -0.776815, 0.000000], [0.846559, 0.232187, 0.004718, -0.566809, -0.631854, 0.673084, -0.850531, 0.000000], [0.598540, 0.293087, -0.094448, -0.714582, -0.676188, 0.883755, -0.867262, 0.000000], [0.912102, 0.088734, 0.054624, -0.324040, -0.572284, 0.587705, -0.702917, 0.000000], [0.809926, 0.251650, 0.003445, -0.593340, -0.637260, 0.728959, -0.850509, 0.000000], [0.931809, 0.084129, 0.055803, -0.335815, -0.693971, 0.438710, -0.778817, 0.000000], [-0.736227, -0.317919, 0.032861, 0.708224, 0.698311, -0.742926, 0.921778, 0.000000]]
pre_activation_mean: [0.547183, 0.739523, 0.269277, 1.221474, 0.569432, 0.867452, 0.010600]
pre_activation_std: [0.654562, 0.859903, 0.591308, 0.679409, 0.852957, 0.667618, 1.453303]
### 6
mean: [0.906500, -0.332449, -0.449711, 1.544283, -0.288801, -0.540092, -0.379064]
std: [1.218081, 0.777626, 1.241985, 2.177372, 0.393486, 1.618244, 0.875488]
fourier: [[22.415491, 23.899087, 24.602426, 28.292316, 81.584967], [14.465382, 15.075019, 15.837333, 18.278821, 29.920410], [23.129859, 24.338098, 24.684767, 29.098498, 40.473999], [40.343742, 40.976871, 46.042743, 50.905891, 138.985501], [6.721508, 6.758741, 8.795142, 8.898722, 25.992047], [30.444752, 31.406793, 32.506807, 37.971148, 48.608241], [16.377814, 17.230693, 17.515115, 20.458167, 34.115797]]
input_correlations: [[0.931304, 0.963959, 0.849241, 0.932658, 0.943875, 0.942821, -0.813380, 0.000000], [-0.946152, -0.984595, -0.875422, -0.956164, -0.970597, -0.948249, 0.761782, 0.000000], [-0.918703, -0.972818, -0.883970, -0.930389, -0.960346, -0.922932, 0.802845, 0.000000], [0.966881, 0.989077, 0.857268, 0.971349, 0.972670, 0.967446, -0.723085, 0.000000], [-0.970852, -0.928686, -0.707113, -0.939372, -0.888936, -0.990755, 0.714979, 0.000000], [-0.940261, -0.990945, -0.899037, -0.957276, -0.982823, -0.935765, 0.738303, 0.000000], [-0.933561, -0.984942, -0.890094, -0.945062, -0.974287, -0.931628, 0.765990, 0.000000]]
pre_activation_mean: [0.906500, -0.332449, -0.449711, 1.544283, -0.288801, -0.540092, -0.379064]
pre_activation_std: [1.218081, 0.777626, 1.241985, 2.177372, 0.393486, 1.618244, 0.875488]
### 8
mean: [1.459418, 1.522344, 0.360720, 1.629290, 1.831666, 1.762677, 0.900022]
std: [2.109866, 2.143950, 0.771749, 1.945180, 2.176354, 2.128386, 1.202578]
fourier: [[39.448533, 40.583725, 43.685996, 49.061270, 131.347666], [39.916304, 41.366390, 44.620536, 49.652668, 137.010936], [11.852664, 12.182204, 15.260332, 16.261509, 32.464828], [36.947222, 37.205178, 39.503218, 45.388914, 146.636065], [41.001600, 41.939807, 44.719001, 50.658817, 164.849901], [40.272663, 40.983665, 43.044216, 49.500480, 158.640930], [21.782601, 23.159600, 23.980970, 27.540057, 81.002023]]
input_correlations: [[0.998612, -0.715724, -0.644941, 0.990803, -0.835679, -0.687609, -0.678274, 0.000000], [0.999266, -0.701620, -0.631324, 0.993141, -0.823234, -0.674224, -0.664901, 0.000000], [-0.833984, 0.967338, 0.944771, -0.781182, 0.948253, 0.962514, 0.957071, 0.000000], [0.993404, -0.758641, -0.694375, 0.979857, -0.860512, -0.734048, -0.725306, 0.000000], [0.997336, -0.732051, -0.663372, 0.987236, -0.844906, -0.704767, -0.696396, 0.000000], [0.991549, -0.769438, -0.705908, 0.976373, -0.868133, -0.745262, -0.736331, 0.000000], [0.965880, -0.843075, -0.793546, 0.939210, -0.904729, -0.826740, -0.818338, 0.000000]]
pre_activation_mean: [1.459418, 1.522344, 0.360720, 1.629290, 1.831666, 1.762677, 0.900022]
pre_activation_std: [2.109866, 2.143950, 0.771749, 1.945180, 2.176354, 2.128386, 1.202578]
### 10
mean: [-0.396285, 4.083553, -2.658192, 3.436909, 3.398202, 3.972927, -3.054229]
std: [0.649229, 4.834357, 3.631198, 4.019642, 4.173470, 4.502016, 4.085890]
fourier: [[12.017284, 12.687355, 12.702312, 15.238870, 35.665657], [88.523726, 94.568585, 99.968288, 112.152526, 367.519812], [67.696205, 70.666549, 74.419781, 84.257998, 239.237269], [72.169741, 78.924969, 83.758196, 92.992492, 309.321860], [76.312089, 81.608081, 86.320302, 96.955566, 305.838187], [82.602208, 88.059464, 92.998279, 104.243233, 357.563378], [74.809559, 79.883139, 84.484847, 94.882695, 274.880643]]
input_correlations: [[-0.957188, -0.956194, 0.859741, -0.977346, -0.972884, -0.978826, -0.986501, 0.000000], [0.995652, 0.995210, -0.739025, 0.999933, 0.999578, 0.999828, 0.998052, 0.000000], [-0.991089, -0.990486, 0.765183, -0.998892, -0.997609, -0.999216, -0.999515, 0.000000], [0.998514, 0.998205, -0.711531, 0.999394, 0.999926, 0.998909, 0.995119, 0.000000], [0.995882, 0.995441, -0.737664, 0.999930, 0.999637, 0.999790, 0.997862, 0.000000], [0.995186, 0.994699, -0.740950, 0.999943, 0.999448, 0.999936, 0.998421, 0.000000], [-0.995637, -0.995191, 0.739308, -0.999924, -0.999568, -0.999817, -0.998033, 0.000000]]
pre_activation_mean: [-0.396285, 4.083553, -2.658192, 3.436909, 3.398202, 3.972927, -3.054229]
pre_activation_std: [0.649229, 4.834357, 3.631198, 4.019642, 4.173470, 4.502016, 4.085890]
### 12
mean: [-7.718015]
std: [9.292990]
fourier: [[168.668958, 182.163958, 192.811146, 215.704632, 694.621347]]
input_correlations: [[0.642967, -0.999226, 0.556817, -0.998164, -0.998598, -0.999709, 0.556514, 0.000000]]
pre_activation_mean: [-7.718015]
pre_activation_std: [9.292990]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.01224294863641262, "std": 0.18133768439292908, "fourier": [2.5463928755774625, 2.6867529476018666, 3.122725154334409, 3.1657454789184967, 3.3850026305965395], "input_correlations": [-0.4020913220855157, -0.6451593242999354, -0.6063831234821934, -0.1764085094827234, -0.676443391136266, 0.0, 0.0, 0.0], "pre_activation_mean": -1.2851357460021973, "pre_activation_std": 1.1914176940917969}, "1": {"mean": 4.225056171417236, "std": 4.68906831741333, "fourier": [83.06030272854841, 92.24579841517127, 97.87517334634745, 108.83278997069797, 380.2550494633615], "input_correlations": [-0.5393471957903369, -0.49508276313384897, -0.34082713838219386, -0.7537106893730301, -0.49874797301625357, 0.0, 0.0, 0.0], "pre_activation_mean": -3.292943239212036, "pre_activation_std": 2.2953498363494873}, "2": {"mean": 0.25539371371269226, "std": 0.47778433561325073, "fourier": [7.361428339056166, 7.636643776468054, 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"input_correlations": [0.995882286868042, 0.9954408276502663, -0.737663721999752, 0.99992981975382, 0.999637146527993, 0.9997903022261537, 0.9978624596841256, 0.0], "pre_activation_mean": 3.3982021808624268, "pre_activation_std": 4.173469543457031}, "5": {"mean": 3.972926616668701, "std": 4.502015590667725, "fourier": [82.60220763736862, 88.05946445489641, 92.99827882322566, 104.24323275254366, 357.5633778087795], "input_correlations": [0.9951864539827675, 0.9946985450985275, -0.7409495906514496, 0.9999426282404796, 0.9994481333633632, 0.9999359340406375, 0.9984206906952267, 0.0], "pre_activation_mean": 3.972926616668701, "pre_activation_std": 4.502015590667725}, "6": {"mean": -3.054229497909546, "std": 4.085890293121338, "fourier": [74.80955931887141, 79.88313935544821, 84.48484715819745, 94.88269452837595, 274.88064281642437], "input_correlations": [-0.9956374984095733, -0.9951913198368156, 0.7393084717489201, -0.9999241309403486, -0.9995681663484154, -0.9998168097985448, 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"neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.019411, -0.401207, -0.212217, 0.07269, -0.405624], [-0.51721, -0.110543, -0.127083, -0.770922, -0.358424], [0.590979, 0.050875, -0.13131, -0.163288, -0.099246], [-0.265338, 0.246552, 0.119123, 0.340002, -0.556946], [0.153664, -0.222938, 0.322601, 0.520869, 0.642563], [0.11375, -0.270155, 0.370431, 0.199752, -0.468246], [-0.521044, -0.197513, -0.428402, -0.081589, 0.215674]], "network.0.bias": [0.209484, -0.087152, 0.134834, 0.063419, -0.341724, 0.392356, -0.334133], "network.2.weight": [[0.3613, 0.055643, 0.2125, -0.129825, 0.532752, -0.397766, -0.030282], [0.471373, 0.298428, -0.307204, 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-0.063068, 0.070357, 0.567287, 0.193656], [0.361449, -0.263964, -0.260853, 0.621305, 0.08299, -0.349265, -0.378972], [0.674679, -0.251955, -0.264038, 0.594338, -0.215862, -0.048791, -0.536725], [0.61662, -0.142077, -0.222849, 0.54797, -0.201945, -0.621845, -0.155833], [0.513779, 0.407996, -0.43928, 0.163373, 0.169643, -0.573655, -0.246775]], "network.8.bias": [-0.025402, -0.046416, 0.328599, 0.449244, 0.304521, 0.495925, 0.399491], "network.10.weight": [[-0.059069, -0.146211, 0.415323, -0.01341, 0.018755, -0.17445, 0.296228], [0.263969, 0.424898, -0.30032, 0.595155, 0.552059, 0.193724, 0.646138], [0.179804, -0.327838, 0.410091, -0.246074, -0.576293, -0.442854, -0.551657], [0.692818, 0.260401, 0.000453, 0.012021, 0.192756, 0.654142, 0.38696], [0.651251, 0.182093, -0.317105, 0.332412, 0.221391, 0.485508, 0.317359], [-0.013908, 0.32801, -0.157608, 0.638842, 0.379681, 0.598222, 0.597046], [-0.306444, -0.335675, 0.29419, -0.378184, -0.37266, -0.4487, -0.28058]], "network.10.bias": [-0.202142, 0.065143, 0.283993, -0.052705, 0.010418, 0.043017, 0.305314], "network.12.weight": [[0.101975, -0.676514, 0.444187, -0.277846, -0.553707, -0.577607, 0.507969]], "network.12.bias": [0.185454]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7008177042007446, "train_acc": 0.425, "val_loss": 0.6946905255317688, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6826703548431396, "train_acc": 0.565, "val_loss": 0.6984756588935852, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6797450184822083, "train_acc": 0.565, "val_loss": 0.6847344040870667, "val_acc": 0.5}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6345972120761871, "train_acc": 0.565, "val_loss": 0.6160485744476318, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.5500445067882538, "train_acc": 0.57, "val_loss": 0.5440154075622559, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.4509490430355072, "train_acc": 0.84, "val_loss": 0.5890906453132629, "val_acc": 0.64}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.4138215035200119, "train_acc": 0.795, "val_loss": 0.4926356375217438, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.35563285648822784, "train_acc": 0.85, "val_loss": 0.6103881001472473, "val_acc": 0.8}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.45753228664398193, "train_acc": 0.83, "val_loss": 0.5090187191963196, "val_acc": 0.78}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.380246102809906, "train_acc": 0.855, "val_loss": 0.5125952363014221, "val_acc": 0.74}], "summary": {"total_epochs": 10, "degraded_epochs": 4, "improved_epochs": 6, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6946905255317688, "final_val_loss": 0.6160485744476318, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.5440154075622559, "final_val_loss": 0.5125952363014221, "initial_val_acc": 0.78, "final_val_acc": 0.74, "best_val_acc": 0.8, "best_epoch": 7}, "improvement": 0.30000000000000004, "first_improvement_epoch": 3}} |
66 | {"target_pattern": "palindrome", "degraded_accuracy": 0.42, "improved_accuracy": 0.84, "improvement": 0.42, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 4610, "learning_rate": 0.08295789265197352, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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-0.17796,
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-0.292467,
-0.428042
],
[
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-0.099078,
0.081394,
-0.039187
],
[
-0.814355,
0.600339,
0.289605,
0.508457,
-1.35125
],
[
1.018456,
0.221088,
-0.179019,
0.39132,
1.0071
],
[
0.272698,
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-0.334436,
0.089379,
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]
],
"network.0.bias": [
-0.660136,
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],
"network.2.weight": [
[
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],
[
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],
[
0.02506,
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],
[
0.391542,
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],
[
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]
],
"network.2.bias": [
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0.232091,
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0.48141
],
"network.4.weight": [
[
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],
[
0.022306,
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0.253931,
0.247397
],
[
0.458835,
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0.676185,
0.819995,
-1.089383
],
[
0.299511,
0.072933,
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0.56296,
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],
[
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]
],
"network.4.bias": [
0.421776,
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],
"network.6.weight": [
[
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],
[
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0.65369,
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],
[
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],
[
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],
[
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],
"network.6.bias": [
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"network.8.weight": [
[
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[
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[
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[
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],
"network.8.bias": [
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"network.10.weight": [
[
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],
"network.10.bias": [
0.60691
]
}
## Activation Signature
### 0
mean: [0.176263, 3.967314, 0.238432, 3.315675, 0.100469]
std: [0.197398, 5.562965, 0.277545, 4.666647, 0.143058]
fourier: [[3.110039, 3.171970, 3.249324, 4.632825, 15.863654], [102.374462, 105.695565, 107.172300, 121.062296, 357.058244], [4.561113, 4.785363, 5.012160, 6.407837, 21.458889], [85.853466, 88.549448, 89.976642, 101.531890, 298.410770], [2.182853, 2.290453, 2.447863, 3.248240, 9.042223]]
input_correlations: [[-0.371547, -0.482405, -0.585279, -0.578136, -0.708084, 0.000000, 0.000000, 0.000000], [-0.925356, -0.652790, -0.408278, -0.037503, -0.170426, 0.000000, 0.000000, 0.000000], [-0.481697, 0.310675, -0.071261, 0.341150, -0.752446, 0.000000, 0.000000, 0.000000], [0.743051, 0.399497, 0.249699, 0.350944, 0.708624, 0.000000, 0.000000, 0.000000], [0.218562, -0.467400, -0.718099, -0.008297, -0.032788, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.821849, -2.754362, 0.299915, 3.141317, -0.981971]
pre_activation_std: [1.447454, 2.625894, 3.338138, 3.215225, 0.810684]
### 2
mean: [-2.181853, -1.582288, 0.889916, 1.162350, -0.609582]
std: [1.557224, 0.704038, 2.437840, 2.789752, 0.890703]
fourier: [[27.413813, 28.484779, 29.160812, 34.633584, 196.366809], [10.997298, 10.997617, 11.457591, 13.467208, 142.405894], [41.634470, 42.614029, 43.712844, 57.290757, 80.092490], [47.813166, 48.824260, 49.709342, 66.242662, 104.611531], [13.499343, 14.116182, 14.634537, 16.307356, 54.862335]]
input_correlations: [[-0.464376, -0.513095, 0.421329, -0.995346, -0.103545, 0.000000, 0.000000, 0.000000], [-0.641957, -0.515030, -0.642526, -0.507136, -0.065397, 0.000000, 0.000000, 0.000000], [0.166093, 0.286753, -0.797458, 0.834650, 0.054648, 0.000000, 0.000000, 0.000000], [0.226982, 0.344020, -0.742893, 0.879124, 0.072976, 0.000000, 0.000000, 0.000000], [-0.630177, -0.488114, -0.761910, -0.352273, -0.096849, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.181853, -1.582288, 0.889916, 1.162350, -0.609582]
pre_activation_std: [1.557224, 0.704038, 2.437840, 2.789752, 0.890703]
### 4
mean: [-0.198180, -0.164090, 2.112752, 1.663869, -0.054290]
std: [1.055679, 0.486286, 3.204871, 2.364615, 0.486720]
fourier: [[17.836181, 18.872424, 19.705263, 20.440418, 23.946149], [8.881826, 9.251668, 9.430794, 10.924127, 14.768083], [58.637568, 60.516403, 61.063777, 73.147465, 190.147678], [42.650160, 44.127693, 45.620006, 53.842276, 149.748243], [7.567296, 7.922812, 8.339180, 9.757311, 10.322078]]
input_correlations: [[-0.850810, -0.351075, -0.998098, -0.999187, 0.356956, 0.000000, 0.000000, 0.000000], [-0.856225, -0.412731, -0.990908, -0.993059, 0.435387, 0.000000, 0.000000, 0.000000], [0.856438, 0.347897, 0.996418, 0.998403, -0.406589, 0.000000, 0.000000, 0.000000], [0.849539, 0.331665, 0.998873, 0.999772, -0.371448, 0.000000, 0.000000, 0.000000], [-0.766798, -0.285534, -0.972557, -0.968997, 0.143923, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.198180, -0.164090, 2.112752, 1.663869, -0.054290]
pre_activation_std: [1.055679, 0.486286, 3.204871, 2.364615, 0.486720]
### 6
mean: [-0.648776, 2.110032, 1.615544, 1.631800, -2.808035]
std: [0.180546, 3.319990, 2.769548, 2.976781, 2.965909]
fourier: [[2.888392, 3.052365, 3.125416, 3.289453, 58.389835], [61.591802, 61.840331, 63.839151, 74.565962, 189.902874], [51.359923, 51.537443, 53.193351, 62.661756, 145.398924], [55.445580, 55.583669, 57.102898, 66.865164, 146.862018], [54.588067, 55.246891, 57.188840, 65.724306, 252.723193]]
input_correlations: [[0.047094, 0.234125, -0.656508, -0.652732, 0.145480, 0.000000, 0.000000, 0.000000], [-0.795609, -0.866469, 0.999669, 0.999740, -0.800578, 0.000000, 0.000000, 0.000000], [-0.805788, -0.871810, 0.999048, 0.999263, -0.809810, 0.000000, 0.000000, 0.000000], [-0.796242, -0.868818, 0.999656, 0.999624, -0.798166, 0.000000, 0.000000, 0.000000], [0.775705, 0.853153, -0.999940, -0.999848, 0.783027, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.648776, 2.110032, 1.615544, 1.631800, -2.808035]
pre_activation_std: [0.180546, 3.319990, 2.769548, 2.976781, 2.965909]
### 8
mean: [-0.980397, 3.842576, -0.382367, 3.214824, -0.824649]
std: [2.007289, 5.656585, 1.377798, 4.743034, 1.592891]
fourier: [[37.075164, 37.851218, 38.675492, 43.884449, 88.235758], [104.503710, 107.022042, 108.828578, 123.933671, 345.831836], [25.553338, 25.961644, 26.513309, 30.371442, 34.413047], [87.653100, 89.506260, 91.313855, 103.934047, 289.334165], [29.410718, 30.031207, 30.711247, 34.764399, 74.218432]]
input_correlations: [[-0.327349, -0.999931, -0.999950, -0.999903, -0.858745, 0.000000, 0.000000, 0.000000], [0.325677, 0.999969, 0.999990, 0.999820, 0.861839, 0.000000, 0.000000, 0.000000], [-0.333521, -0.999939, -0.999917, -0.999393, -0.868863, 0.000000, 0.000000, 0.000000], [0.326977, 0.999974, 0.999984, 0.999833, 0.861089, 0.000000, 0.000000, 0.000000], [-0.326789, -0.999889, -0.999912, -0.999940, -0.857123, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.980397, 3.842576, -0.382367, 3.214824, -0.824649]
pre_activation_std: [2.007289, 5.656585, 1.377798, 4.743034, 1.592891]
### 10
mean: [-2.989568]
std: [5.238463]
fourier: [[96.568111, 99.701069, 100.798426, 114.538950, 269.061086]]
input_correlations: [[0.736393, -0.999944, 0.779394, -0.999924, 0.679966, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.989568]
pre_activation_std: [5.238463]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.069007,
-0.17796,
-0.285538,
-0.292467,
-0.428042
],
[
-0.982768,
-0.577101,
-0.099078,
0.081394,
-0.039187
],
[
-0.814355,
0.600339,
0.289605,
0.508457,
-1.35125
],
[
1.018456,
0.221088,
-0.179019,
0.39132,
1.0071
],
[
0.272698,
-0.259969,
-0.334436,
0.089379,
-0.008505
]
],
"network.0.bias": [
-0.660136,
-0.399009,
0.190615,
-0.23627,
-0.330185
],
"network.2.weight": [
[
-0.39777,
0.526248,
0.082175,
-0.472382,
-0.25774
],
[
0.250033,
0.14607,
-0.341766,
-0.184637,
-0.105557
],
[
0.02506,
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-0.736017,
0.502405,
-0.337343
],
[
0.391542,
-0.349347,
-0.740023,
0.623355,
-0.117407
],
[
-0.620512,
-0.357622,
-0.44827,
-0.177709,
-0.455155
]
],
"network.2.bias": [
-0.80444,
-0.515378,
0.232091,
0.198202,
0.48141
],
"network.4.weight": [
[
-0.663749,
-0.84761,
0.144584,
-0.569938,
-0.211484
],
[
0.022306,
-0.771615,
-0.553425,
0.253931,
0.247397
],
[
0.458835,
-0.306368,
0.676185,
0.819995,
-1.089383
],
[
0.299511,
0.072933,
0.569729,
0.56296,
-0.319465
],
[
-0.103349,
-1.169151,
0.424652,
-0.573878,
-0.837345
]
],
"network.4.bias": [
0.421776,
0.121146,
-0.227972,
-0.063572,
0.187786
],
"network.6.weight": [
[
-0.468077,
-0.484488,
-0.174648,
0.096401,
-0.340058
],
[
-0.363305,
-0.103537,
0.65369,
0.508087,
-0.120447
],
[
-0.618928,
0.198662,
0.472484,
0.498457,
-0.209012
],
[
-0.341892,
-0.356074,
0.791172,
0.176775,
0.044056
],
[
0.009133,
-0.116591,
-0.549968,
-0.562002,
-0.296376
]
],
"network.6.bias": [
-0.307934,
-0.133389,
-0.153833,
-0.36653,
-0.609831
],
"network.8.weight": [
[
-0.566046,
-0.197203,
-0.091478,
-0.404717,
-0.112419
],
[
-0.030338,
0.546234,
0.55338,
0.863762,
0.79626
],
[
-0.817737,
-0.419374,
0.258431,
-0.237363,
-0.706823
],
[
0.244729,
0.706426,
0.33377,
0.570755,
0.243125
],
[
-0.552532,
-0.165427,
0.053732,
-0.428783,
-0.124282
]
],
"network.8.bias": [
0.289557,
0.0553,
0.34822,
0.006521,
0.158033
],
"network.10.weight": [
[
0.112706,
-0.443718,
0.257603,
-0.578241,
-0.001368
]
],
"network.10.bias": [
0.60691
]
}
## Activation Signature
### 0
mean: [0.176263, 3.967314, 0.238432, 3.315675, 0.100469]
std: [0.197398, 5.562965, 0.277545, 4.666647, 0.143058]
fourier: [[3.110039, 3.171970, 3.249324, 4.632825, 15.863654], [102.374462, 105.695565, 107.172300, 121.062296, 357.058244], [4.561113, 4.785363, 5.012160, 6.407837, 21.458889], [85.853466, 88.549448, 89.976642, 101.531890, 298.410770], [2.182853, 2.290453, 2.447863, 3.248240, 9.042223]]
input_correlations: [[-0.371547, -0.482405, -0.585279, -0.578136, -0.708084, 0.000000, 0.000000, 0.000000], [-0.925356, -0.652790, -0.408278, -0.037503, -0.170426, 0.000000, 0.000000, 0.000000], [-0.481697, 0.310675, -0.071261, 0.341150, -0.752446, 0.000000, 0.000000, 0.000000], [0.743051, 0.399497, 0.249699, 0.350944, 0.708624, 0.000000, 0.000000, 0.000000], [0.218562, -0.467400, -0.718099, -0.008297, -0.032788, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.821849, -2.754362, 0.299915, 3.141317, -0.981971]
pre_activation_std: [1.447454, 2.625894, 3.338138, 3.215225, 0.810684]
### 2
mean: [-2.181853, -1.582288, 0.889916, 1.162350, -0.609582]
std: [1.557224, 0.704038, 2.437840, 2.789752, 0.890703]
fourier: [[27.413813, 28.484779, 29.160812, 34.633584, 196.366809], [10.997298, 10.997617, 11.457591, 13.467208, 142.405894], [41.634470, 42.614029, 43.712844, 57.290757, 80.092490], [47.813166, 48.824260, 49.709342, 66.242662, 104.611531], [13.499343, 14.116182, 14.634537, 16.307356, 54.862335]]
input_correlations: [[-0.464376, -0.513095, 0.421329, -0.995346, -0.103545, 0.000000, 0.000000, 0.000000], [-0.641957, -0.515030, -0.642526, -0.507136, -0.065397, 0.000000, 0.000000, 0.000000], [0.166093, 0.286753, -0.797458, 0.834650, 0.054648, 0.000000, 0.000000, 0.000000], [0.226982, 0.344020, -0.742893, 0.879124, 0.072976, 0.000000, 0.000000, 0.000000], [-0.630177, -0.488114, -0.761910, -0.352273, -0.096849, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.181853, -1.582288, 0.889916, 1.162350, -0.609582]
pre_activation_std: [1.557224, 0.704038, 2.437840, 2.789752, 0.890703]
### 4
mean: [-0.198180, -0.164090, 2.112752, 1.663869, -0.054290]
std: [1.055679, 0.486286, 3.204871, 2.364615, 0.486720]
fourier: [[17.836181, 18.872424, 19.705263, 20.440418, 23.946149], [8.881826, 9.251668, 9.430794, 10.924127, 14.768083], [58.637568, 60.516403, 61.063777, 73.147465, 190.147678], [42.650160, 44.127693, 45.620006, 53.842276, 149.748243], [7.567296, 7.922812, 8.339180, 9.757311, 10.322078]]
input_correlations: [[-0.850810, -0.351075, -0.998098, -0.999187, 0.356956, 0.000000, 0.000000, 0.000000], [-0.856225, -0.412731, -0.990908, -0.993059, 0.435387, 0.000000, 0.000000, 0.000000], [0.856438, 0.347897, 0.996418, 0.998403, -0.406589, 0.000000, 0.000000, 0.000000], [0.849539, 0.331665, 0.998873, 0.999772, -0.371448, 0.000000, 0.000000, 0.000000], [-0.766798, -0.285534, -0.972557, -0.968997, 0.143923, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.198180, -0.164090, 2.112752, 1.663869, -0.054290]
pre_activation_std: [1.055679, 0.486286, 3.204871, 2.364615, 0.486720]
### 6
mean: [-0.648776, 2.110032, 1.615544, 1.631800, -2.808035]
std: [0.180546, 3.319990, 2.769548, 2.976781, 2.965909]
fourier: [[2.888392, 3.052365, 3.125416, 3.289453, 58.389835], [61.591802, 61.840331, 63.839151, 74.565962, 189.902874], [51.359923, 51.537443, 53.193351, 62.661756, 145.398924], [55.445580, 55.583669, 57.102898, 66.865164, 146.862018], [54.588067, 55.246891, 57.188840, 65.724306, 252.723193]]
input_correlations: [[0.047094, 0.234125, -0.656508, -0.652732, 0.145480, 0.000000, 0.000000, 0.000000], [-0.795609, -0.866469, 0.999669, 0.999740, -0.800578, 0.000000, 0.000000, 0.000000], [-0.805788, -0.871810, 0.999048, 0.999263, -0.809810, 0.000000, 0.000000, 0.000000], [-0.796242, -0.868818, 0.999656, 0.999624, -0.798166, 0.000000, 0.000000, 0.000000], [0.775705, 0.853153, -0.999940, -0.999848, 0.783027, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.648776, 2.110032, 1.615544, 1.631800, -2.808035]
pre_activation_std: [0.180546, 3.319990, 2.769548, 2.976781, 2.965909]
### 8
mean: [-0.980397, 3.842576, -0.382367, 3.214824, -0.824649]
std: [2.007289, 5.656585, 1.377798, 4.743034, 1.592891]
fourier: [[37.075164, 37.851218, 38.675492, 43.884449, 88.235758], [104.503710, 107.022042, 108.828578, 123.933671, 345.831836], [25.553338, 25.961644, 26.513309, 30.371442, 34.413047], [87.653100, 89.506260, 91.313855, 103.934047, 289.334165], [29.410718, 30.031207, 30.711247, 34.764399, 74.218432]]
input_correlations: [[-0.327349, -0.999931, -0.999950, -0.999903, -0.858745, 0.000000, 0.000000, 0.000000], [0.325677, 0.999969, 0.999990, 0.999820, 0.861839, 0.000000, 0.000000, 0.000000], [-0.333521, -0.999939, -0.999917, -0.999393, -0.868863, 0.000000, 0.000000, 0.000000], [0.326977, 0.999974, 0.999984, 0.999833, 0.861089, 0.000000, 0.000000, 0.000000], [-0.326789, -0.999889, -0.999912, -0.999940, -0.857123, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.980397, 3.842576, -0.382367, 3.214824, -0.824649]
pre_activation_std: [2.007289, 5.656585, 1.377798, 4.743034, 1.592891]
### 10
mean: [-2.989568]
std: [5.238463]
fourier: [[96.568111, 99.701069, 100.798426, 114.538950, 269.061086]]
input_correlations: [[0.736393, -0.999944, 0.779394, -0.999924, 0.679966, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.989568]
pre_activation_std: [5.238463]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.17626281082630157, "std": 0.19739773869514465, "fourier": [3.1100388386350444, 3.171970347905192, 3.2493241968526463, 4.632824952207679, 15.863653568220343], "input_correlations": [-0.3715468023227891, -0.48240517230294594, -0.5852790459107517, -0.5781355432069016, -0.7080842897572917, 0.0, 0.0, 0.0], "pre_activation_mean": -2.8218486309051514, "pre_activation_std": 1.4474542140960693}, "1": {"mean": 3.9673140048980713, "std": 5.562965393066406, "fourier": [102.37446161969885, 105.69556531019558, 107.17230007321791, 121.06229612139964, 357.05824447982013], "input_correlations": [-0.9253562039959936, -0.6527895743003128, -0.4082777049831867, -0.03750337986281088, -0.17042567026499986, 0.0, 0.0, 0.0], "pre_activation_mean": -2.7543623447418213, "pre_activation_std": 2.625894069671631}, "2": {"mean": 0.23843207955360413, "std": 0.27754539251327515, "fourier": [4.561112877472336, 4.785363015987074, 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"network.10.weight": [[0.112706, -0.443718, 0.257603, -0.578241, -0.001368]], "network.10.bias": [0.60691]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6847763061523438, "train_acc": 0.51, "val_loss": 0.7663058638572693, "val_acc": 0.42}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6732763648033142, "train_acc": 0.6, "val_loss": 0.7665906548500061, "val_acc": 0.42}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6428095400333405, "train_acc": 0.6, "val_loss": 0.6856815218925476, "val_acc": 0.42}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.6048679053783417, "train_acc": 0.52, "val_loss": 0.5642614364624023, "val_acc": 0.76}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.5015512406826019, "train_acc": 0.84, "val_loss": 0.5285163521766663, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4522537589073181, "train_acc": 0.82, "val_loss": 0.45297232270240784, "val_acc": 0.82}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.40715445578098297, "train_acc": 0.81, "val_loss": 0.41224175691604614, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.41625480353832245, "train_acc": 0.815, "val_loss": 0.43164387345314026, "val_acc": 0.8}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.4105592966079712, "train_acc": 0.835, "val_loss": 0.46889540553092957, "val_acc": 0.8}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.39090123772621155, "train_acc": 0.83, "val_loss": 0.44497185945510864, "val_acc": 0.8}], "summary": {"total_epochs": 10, "degraded_epochs": 3, "improved_epochs": 7, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7663058638572693, "final_val_loss": 0.6856815218925476, "initial_val_acc": 0.42, "final_val_acc": 0.42, "best_val_acc": 0.42}, "improved_stage": {"initial_val_loss": 0.5642614364624023, "final_val_loss": 0.44497185945510864, "initial_val_acc": 0.76, "final_val_acc": 0.8, "best_val_acc": 0.84, "best_epoch": 6}, "improvement": 0.42, "first_improvement_epoch": 2}} |
67 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.48, "improved_accuracy": 0.94, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8556, "learning_rate": 0.048065341110050036, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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[
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0.167846,
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],
[
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0.087444,
0.095636,
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[
0.156818,
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0.341574,
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [14.116804, 0.388627, 0.187947, 0.000000, 0.026619, 0.435239, 0.219189]
std: [13.022650, 0.750025, 0.307229, 0.000000, 0.064148, 0.778994, 0.438599]
fourier: [[203.618828, 213.421879, 225.943606, 248.896846, 1270.512251], [12.228331, 13.070957, 13.778136, 16.792356, 34.976477], [5.320797, 5.369547, 5.727298, 6.206407, 16.915234], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.974916, 1.070504, 1.161595, 1.300923, 2.395689], [13.695785, 13.778473, 14.121697, 17.714699, 39.171550], [7.444506, 7.537676, 8.071452, 9.716535, 19.726975]]
input_correlations: [[-0.631755, -0.063004, 0.346450, 0.440386, 0.364168, 0.000000, 0.000000, 0.000000], [-0.277848, 0.073293, 0.334270, 0.652506, 0.669838, 0.000000, 0.000000, 0.000000], [-0.648035, -0.206438, -0.291986, 0.563440, 0.450706, 0.000000, 0.000000, 0.000000], [-0.481790, -0.934412, -0.524806, -0.179281, -0.091601, 0.000000, 0.000000, 0.000000], [0.616791, 0.672715, 0.517009, 0.178456, -0.378119, 0.000000, 0.000000, 0.000000], [0.946350, 0.337492, 0.364135, 0.151634, 0.449344, 0.000000, 0.000000, 0.000000], [0.257143, -0.632296, 0.089783, -0.422045, 0.624513, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.374106, 1.165212, 0.364430, -1.447674, 0.692475, 1.099172, -0.557434]
pre_activation_std: [1.811297, 1.569317, 1.487751, 0.884932, 0.698621, 1.562874, 1.579195]
### 2
mean: [2.010782, 1.700467, 1.889109, 1.352687, 0.395944, -0.745674, 0.010888]
std: [2.200659, 1.760330, 2.021605, 1.115412, 0.874006, 0.560118, 0.339347]
fourier: [[35.484967, 35.699011, 39.642597, 44.430595, 180.970379], [29.640112, 30.206631, 30.511253, 31.657546, 153.042003], [32.681113, 32.832635, 32.921617, 33.181778, 170.019839], [17.429709, 17.722843, 19.191664, 19.799293, 121.741803], [13.463240, 13.690513, 14.489853, 18.212810, 35.634927], [8.865599, 10.278576, 10.352029, 10.797959, 67.110677], [4.628957, 4.985380, 5.594271, 6.115525, 7.153165]]
input_correlations: [[0.927668, 0.809041, 0.766695, 0.000000, -0.410042, -0.481671, 0.087877, 0.000000], [0.954577, 0.920614, 0.807955, 0.000000, -0.295475, -0.237250, 0.213101, 0.000000], [0.767570, 0.892157, 0.879230, 0.000000, -0.461401, -0.096010, 0.482923, 0.000000], [0.899323, 0.970528, 0.850884, 0.000000, -0.179354, -0.024576, 0.288959, 0.000000], [-0.613285, -0.502654, -0.675524, 0.000000, 0.758655, 0.689764, -0.213933, 0.000000], [0.063238, -0.053418, 0.346984, 0.000000, -0.829371, -0.837213, -0.204998, 0.000000], [-0.403930, -0.232656, -0.535326, 0.000000, 0.643388, 0.643592, -0.305233, 0.000000]]
pre_activation_mean: [2.010782, 1.700467, 1.889109, 1.352687, 0.395944, -0.745674, 0.010888]
pre_activation_std: [2.200659, 1.760330, 2.021605, 1.115412, 0.874006, 0.560118, 0.339347]
### 4
mean: [-1.069917, 2.316911, 4.855435, 1.183954, -1.595414, -1.242392, -0.987304]
std: [1.269896, 2.158111, 4.549390, 0.688801, 1.028222, 0.851673, 0.590274]
fourier: [[20.407242, 20.864842, 22.146660, 24.606756, 96.292561], [32.765547, 34.152030, 36.963378, 41.574002, 208.521953], [73.090930, 74.638207, 79.354926, 86.444498, 436.989173], [11.652063, 12.932947, 13.080699, 14.446879, 106.555813], [15.787263, 15.801851, 17.817880, 18.365843, 143.587237], [13.947388, 14.508980, 14.936290, 16.226665, 111.815302], [8.437218, 9.285428, 10.067139, 10.788815, 88.857320]]
input_correlations: [[-0.982167, -0.993275, -0.925839, -0.966148, 0.574667, 0.000000, 0.362502, 0.000000], [0.951759, 0.970027, 0.964410, 0.957110, -0.612991, 0.000000, -0.402623, 0.000000], [0.973748, 0.991081, 0.940979, 0.972076, -0.579591, 0.000000, -0.357699, 0.000000], [-0.152369, 0.049324, 0.247904, 0.221711, 0.672306, 0.000000, 0.725388, 0.000000], [-0.901624, -0.949534, -0.991100, -0.964128, 0.501783, 0.000000, 0.291811, 0.000000], [-0.988293, -0.981616, -0.823654, -0.933434, 0.517823, 0.000000, 0.293384, 0.000000], [-0.781092, -0.868069, -0.993124, -0.913460, 0.448505, 0.000000, 0.231165, 0.000000]]
pre_activation_mean: [-1.069917, 2.316911, 4.855435, 1.183954, -1.595414, -1.242392, -0.987304]
pre_activation_std: [1.269896, 2.158111, 4.549390, 0.688801, 1.028222, 0.851673, 0.590274]
### 6
mean: [3.783050, 5.303219, 3.852599, 2.875274, 5.253420, -1.812116, -0.760549]
std: [3.454869, 4.941969, 3.700857, 2.536498, 4.899823, 1.468985, 2.101619]
fourier: [[55.086371, 55.693375, 60.521741, 64.341002, 340.474499], [78.358159, 80.282826, 86.213463, 93.811657, 477.289753], [58.284017, 61.336350, 64.505910, 72.030745, 346.733900], [40.517694, 40.856136, 44.409887, 46.687290, 258.774674], [77.254911, 79.972244, 85.245441, 94.216118, 472.807797], [23.134194, 24.581941, 25.584411, 28.897206, 163.090472], [32.099411, 35.362988, 36.482297, 43.704620, 68.449432]]
input_correlations: [[-0.557160, 0.996528, 0.998385, 0.077210, 0.000000, 0.000000, 0.000000, 0.000000], [-0.567696, 0.996418, 0.999426, 0.044270, 0.000000, 0.000000, 0.000000, 0.000000], [-0.593192, 0.992056, 0.998296, -0.019669, 0.000000, 0.000000, 0.000000, 0.000000], [-0.535058, 0.993941, 0.997624, 0.102844, 0.000000, 0.000000, 0.000000, 0.000000], [-0.575540, 0.995845, 0.999396, 0.020690, 0.000000, 0.000000, 0.000000, 0.000000], [0.599586, -0.986139, -0.995881, 0.053077, 0.000000, 0.000000, 0.000000, 0.000000], [0.661226, -0.963920, -0.969094, 0.206688, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.783050, 5.303219, 3.852599, 2.875274, 5.253420, -1.812116, -0.760549]
pre_activation_std: [3.454869, 4.941969, 3.700857, 2.536498, 4.899823, 1.468985, 2.101619]
### 8
mean: [13.940304, -3.162787, -0.128555, -1.554375, -1.564423, -2.214563, -2.267373]
std: [13.219073, 4.145132, 0.562388, 1.021354, 1.453448, 3.359567, 2.826284]
fourier: [[207.458161, 218.381570, 230.595178, 252.311734, 1254.627213], [63.894078, 71.368753, 72.974447, 78.434273, 284.650849], [9.868325, 10.145088, 10.441928, 11.017921, 11.569937], [15.168188, 16.638457, 17.223665, 18.586460, 139.893754], [22.654569, 24.386996, 25.397443, 27.619546, 140.798063], [51.304468, 58.492898, 59.176728, 63.815548, 199.310632], [43.495125, 48.271911, 49.450323, 54.501134, 204.063592]]
input_correlations: [[0.998394, 0.999442, 0.998725, 0.996520, 0.999660, -0.215350, -0.653765, 0.000000], [-0.993344, -0.994750, -0.994509, -0.989443, -0.995362, 0.245039, 0.704566, 0.000000], [-0.871458, -0.880307, -0.893484, -0.857127, -0.886661, 0.364147, 0.913522, 0.000000], [-0.975541, -0.973690, -0.968482, -0.981556, -0.971414, 0.099481, 0.435541, 0.000000], [-0.997148, -0.998132, -0.997146, -0.994440, -0.998358, 0.231091, 0.674556, 0.000000], [-0.990186, -0.992053, -0.992601, -0.985563, -0.993021, 0.254599, 0.721490, 0.000000], [-0.993241, -0.995434, -0.996708, -0.989590, -0.996537, 0.239090, 0.698161, 0.000000]]
pre_activation_mean: [13.940304, -3.162787, -0.128555, -1.554375, -1.564423, -2.214563, -2.267373]
pre_activation_std: [13.219073, 4.145132, 0.562388, 1.021354, 1.453448, 3.359567, 2.826284]
### 10
mean: [-7.329990]
std: [7.904860]
fourier: [[123.579576, 135.462878, 140.608967, 147.910768, 659.699116]]
input_correlations: [[-0.995160, 0.629366, 0.671657, 0.000000, 0.530662, 0.662946, 0.613244, 0.000000]]
pre_activation_mean: [-7.329990]
pre_activation_std: [7.904860]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.weight": [
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [14.116804, 0.388627, 0.187947, 0.000000, 0.026619, 0.435239, 0.219189]
std: [13.022650, 0.750025, 0.307229, 0.000000, 0.064148, 0.778994, 0.438599]
fourier: [[203.618828, 213.421879, 225.943606, 248.896846, 1270.512251], [12.228331, 13.070957, 13.778136, 16.792356, 34.976477], [5.320797, 5.369547, 5.727298, 6.206407, 16.915234], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.974916, 1.070504, 1.161595, 1.300923, 2.395689], [13.695785, 13.778473, 14.121697, 17.714699, 39.171550], [7.444506, 7.537676, 8.071452, 9.716535, 19.726975]]
input_correlations: [[-0.631755, -0.063004, 0.346450, 0.440386, 0.364168, 0.000000, 0.000000, 0.000000], [-0.277848, 0.073293, 0.334270, 0.652506, 0.669838, 0.000000, 0.000000, 0.000000], [-0.648035, -0.206438, -0.291986, 0.563440, 0.450706, 0.000000, 0.000000, 0.000000], [-0.481790, -0.934412, -0.524806, -0.179281, -0.091601, 0.000000, 0.000000, 0.000000], [0.616791, 0.672715, 0.517009, 0.178456, -0.378119, 0.000000, 0.000000, 0.000000], [0.946350, 0.337492, 0.364135, 0.151634, 0.449344, 0.000000, 0.000000, 0.000000], [0.257143, -0.632296, 0.089783, -0.422045, 0.624513, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.374106, 1.165212, 0.364430, -1.447674, 0.692475, 1.099172, -0.557434]
pre_activation_std: [1.811297, 1.569317, 1.487751, 0.884932, 0.698621, 1.562874, 1.579195]
### 2
mean: [2.010782, 1.700467, 1.889109, 1.352687, 0.395944, -0.745674, 0.010888]
std: [2.200659, 1.760330, 2.021605, 1.115412, 0.874006, 0.560118, 0.339347]
fourier: [[35.484967, 35.699011, 39.642597, 44.430595, 180.970379], [29.640112, 30.206631, 30.511253, 31.657546, 153.042003], [32.681113, 32.832635, 32.921617, 33.181778, 170.019839], [17.429709, 17.722843, 19.191664, 19.799293, 121.741803], [13.463240, 13.690513, 14.489853, 18.212810, 35.634927], [8.865599, 10.278576, 10.352029, 10.797959, 67.110677], [4.628957, 4.985380, 5.594271, 6.115525, 7.153165]]
input_correlations: [[0.927668, 0.809041, 0.766695, 0.000000, -0.410042, -0.481671, 0.087877, 0.000000], [0.954577, 0.920614, 0.807955, 0.000000, -0.295475, -0.237250, 0.213101, 0.000000], [0.767570, 0.892157, 0.879230, 0.000000, -0.461401, -0.096010, 0.482923, 0.000000], [0.899323, 0.970528, 0.850884, 0.000000, -0.179354, -0.024576, 0.288959, 0.000000], [-0.613285, -0.502654, -0.675524, 0.000000, 0.758655, 0.689764, -0.213933, 0.000000], [0.063238, -0.053418, 0.346984, 0.000000, -0.829371, -0.837213, -0.204998, 0.000000], [-0.403930, -0.232656, -0.535326, 0.000000, 0.643388, 0.643592, -0.305233, 0.000000]]
pre_activation_mean: [2.010782, 1.700467, 1.889109, 1.352687, 0.395944, -0.745674, 0.010888]
pre_activation_std: [2.200659, 1.760330, 2.021605, 1.115412, 0.874006, 0.560118, 0.339347]
### 4
mean: [-1.069917, 2.316911, 4.855435, 1.183954, -1.595414, -1.242392, -0.987304]
std: [1.269896, 2.158111, 4.549390, 0.688801, 1.028222, 0.851673, 0.590274]
fourier: [[20.407242, 20.864842, 22.146660, 24.606756, 96.292561], [32.765547, 34.152030, 36.963378, 41.574002, 208.521953], [73.090930, 74.638207, 79.354926, 86.444498, 436.989173], [11.652063, 12.932947, 13.080699, 14.446879, 106.555813], [15.787263, 15.801851, 17.817880, 18.365843, 143.587237], [13.947388, 14.508980, 14.936290, 16.226665, 111.815302], [8.437218, 9.285428, 10.067139, 10.788815, 88.857320]]
input_correlations: [[-0.982167, -0.993275, -0.925839, -0.966148, 0.574667, 0.000000, 0.362502, 0.000000], [0.951759, 0.970027, 0.964410, 0.957110, -0.612991, 0.000000, -0.402623, 0.000000], [0.973748, 0.991081, 0.940979, 0.972076, -0.579591, 0.000000, -0.357699, 0.000000], [-0.152369, 0.049324, 0.247904, 0.221711, 0.672306, 0.000000, 0.725388, 0.000000], [-0.901624, -0.949534, -0.991100, -0.964128, 0.501783, 0.000000, 0.291811, 0.000000], [-0.988293, -0.981616, -0.823654, -0.933434, 0.517823, 0.000000, 0.293384, 0.000000], [-0.781092, -0.868069, -0.993124, -0.913460, 0.448505, 0.000000, 0.231165, 0.000000]]
pre_activation_mean: [-1.069917, 2.316911, 4.855435, 1.183954, -1.595414, -1.242392, -0.987304]
pre_activation_std: [1.269896, 2.158111, 4.549390, 0.688801, 1.028222, 0.851673, 0.590274]
### 6
mean: [3.783050, 5.303219, 3.852599, 2.875274, 5.253420, -1.812116, -0.760549]
std: [3.454869, 4.941969, 3.700857, 2.536498, 4.899823, 1.468985, 2.101619]
fourier: [[55.086371, 55.693375, 60.521741, 64.341002, 340.474499], [78.358159, 80.282826, 86.213463, 93.811657, 477.289753], [58.284017, 61.336350, 64.505910, 72.030745, 346.733900], [40.517694, 40.856136, 44.409887, 46.687290, 258.774674], [77.254911, 79.972244, 85.245441, 94.216118, 472.807797], [23.134194, 24.581941, 25.584411, 28.897206, 163.090472], [32.099411, 35.362988, 36.482297, 43.704620, 68.449432]]
input_correlations: [[-0.557160, 0.996528, 0.998385, 0.077210, 0.000000, 0.000000, 0.000000, 0.000000], [-0.567696, 0.996418, 0.999426, 0.044270, 0.000000, 0.000000, 0.000000, 0.000000], [-0.593192, 0.992056, 0.998296, -0.019669, 0.000000, 0.000000, 0.000000, 0.000000], [-0.535058, 0.993941, 0.997624, 0.102844, 0.000000, 0.000000, 0.000000, 0.000000], [-0.575540, 0.995845, 0.999396, 0.020690, 0.000000, 0.000000, 0.000000, 0.000000], [0.599586, -0.986139, -0.995881, 0.053077, 0.000000, 0.000000, 0.000000, 0.000000], [0.661226, -0.963920, -0.969094, 0.206688, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.783050, 5.303219, 3.852599, 2.875274, 5.253420, -1.812116, -0.760549]
pre_activation_std: [3.454869, 4.941969, 3.700857, 2.536498, 4.899823, 1.468985, 2.101619]
### 8
mean: [13.940304, -3.162787, -0.128555, -1.554375, -1.564423, -2.214563, -2.267373]
std: [13.219073, 4.145132, 0.562388, 1.021354, 1.453448, 3.359567, 2.826284]
fourier: [[207.458161, 218.381570, 230.595178, 252.311734, 1254.627213], [63.894078, 71.368753, 72.974447, 78.434273, 284.650849], [9.868325, 10.145088, 10.441928, 11.017921, 11.569937], [15.168188, 16.638457, 17.223665, 18.586460, 139.893754], [22.654569, 24.386996, 25.397443, 27.619546, 140.798063], [51.304468, 58.492898, 59.176728, 63.815548, 199.310632], [43.495125, 48.271911, 49.450323, 54.501134, 204.063592]]
input_correlations: [[0.998394, 0.999442, 0.998725, 0.996520, 0.999660, -0.215350, -0.653765, 0.000000], [-0.993344, -0.994750, -0.994509, -0.989443, -0.995362, 0.245039, 0.704566, 0.000000], [-0.871458, -0.880307, -0.893484, -0.857127, -0.886661, 0.364147, 0.913522, 0.000000], [-0.975541, -0.973690, -0.968482, -0.981556, -0.971414, 0.099481, 0.435541, 0.000000], [-0.997148, -0.998132, -0.997146, -0.994440, -0.998358, 0.231091, 0.674556, 0.000000], [-0.990186, -0.992053, -0.992601, -0.985563, -0.993021, 0.254599, 0.721490, 0.000000], [-0.993241, -0.995434, -0.996708, -0.989590, -0.996537, 0.239090, 0.698161, 0.000000]]
pre_activation_mean: [13.940304, -3.162787, -0.128555, -1.554375, -1.564423, -2.214563, -2.267373]
pre_activation_std: [13.219073, 4.145132, 0.562388, 1.021354, 1.453448, 3.359567, 2.826284]
### 10
mean: [-7.329990]
std: [7.904860]
fourier: [[123.579576, 135.462878, 140.608967, 147.910768, 659.699116]]
input_correlations: [[-0.995160, 0.629366, 0.671657, 0.000000, 0.530662, 0.662946, 0.613244, 0.000000]]
pre_activation_mean: [-7.329990]
pre_activation_std: [7.904860]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 14.116804122924805, "std": 13.022649765014648, "fourier": [203.61882838019338, 213.4218785743213, 225.94360611142963, 248.8968458222223, 1270.5122512578964], "input_correlations": [-0.631755289941269, -0.06300440793367926, 0.34644976534446165, 0.44038588981921545, 0.36416827244219835, 0.0, 0.0, 0.0], "pre_activation_mean": 1.3741060495376587, "pre_activation_std": 1.811296820640564}, "1": {"mean": 0.3886274993419647, "std": 0.7500254511833191, "fourier": [12.228331343103727, 13.070956822388478, 13.778136465824014, 16.79235642070317, 34.97647726535797], "input_correlations": [-0.2778477847215858, 0.07329275802305509, 0.3342704232587794, 0.6525064769249794, 0.6698375734307072, 0.0, 0.0, 0.0], "pre_activation_mean": 1.1652119159698486, "pre_activation_std": 1.569317102432251}, "2": {"mean": 0.18794706463813782, "std": 0.30722859501838684, "fourier": [5.320797110345438, 5.369547137171561, 5.727297760323759, 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|
68 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.56, "improved_accuracy": 0.94, "improvement": 0.3799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2865, "learning_rate": 0.05576129768179258, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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],
[
0.533496,
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0.0313,
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],
[
0.21283,
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0.605968
]
],
"network.4.bias": [
0.131106,
0.080049,
0.095299,
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0.287916,
0.560716
],
"network.6.weight": [
[
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[
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[
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[
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[
0.3092,
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],
[
0.168383,
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]
],
"network.6.bias": [
0.095977,
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],
"network.8.weight": [
[
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0.366895
],
[
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0.050309,
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[
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[
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],
[
0.078793,
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],
[
0.085682,
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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],
"network.10.bias": [
0.063383
]
}
## Activation Signature
### 0
mean: [0.465658, 1.120781, 0.887620, 0.670690, 0.065452, 1.327925]
std: [0.713047, 0.977350, 0.791164, 0.675139, 0.134842, 1.205991]
fourier: [[12.457890, 12.798930, 13.612427, 15.169370, 41.909267], [15.528897, 16.358597, 19.855549, 21.273829, 100.870266], [12.183401, 13.605971, 15.919529, 17.217559, 79.885782], [10.336776, 11.590917, 12.656199, 14.242402, 60.362130], [2.167378, 2.175421, 2.810485, 3.132937, 5.890642], [18.852866, 20.265680, 23.960258, 25.634385, 119.513248]]
input_correlations: [[0.283633, 0.586414, 0.548489, 0.262494, 0.753027, 0.000000, 0.000000, 0.000000], [-0.649861, 0.079877, 0.100024, 0.557996, 0.420877, 0.000000, 0.000000, 0.000000], [-0.047845, -0.577706, -0.416884, -0.766323, -0.530042, 0.000000, 0.000000, 0.000000], [0.821511, 0.324278, 0.677711, 0.261608, 0.457437, 0.000000, 0.000000, 0.000000], [0.897284, 0.066115, 0.582505, -0.126418, 0.139160, 0.000000, 0.000000, 0.000000], [-0.625581, -0.066945, 0.478630, 0.303587, 0.224772, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.481109, 0.907696, -2.686565, 3.103140, 0.468252, 1.541592]
pre_activation_std: [1.537137, 1.664338, 1.835981, 2.425765, 1.297502, 1.591458]
### 2
mean: [1.217412, 1.000635, 1.746325, -1.517807, 1.726597, 2.199135]
std: [1.480637, 0.765716, 1.227441, 1.096587, 1.906269, 1.557849]
fourier: [[24.503726, 26.142250, 28.530110, 31.681929, 109.567076], [11.884915, 12.127466, 13.757225, 14.337064, 90.057155], [20.259827, 23.098344, 23.869026, 24.984034, 157.169269], [17.306056, 20.658657, 22.940849, 23.141645, 136.602605], [32.768705, 33.031247, 37.965532, 41.136750, 155.393745], [22.031795, 25.394735, 27.550542, 30.384397, 197.922163]]
input_correlations: [[0.436512, 0.870650, 0.169810, -0.362463, -0.702638, 0.618124, 0.000000, 0.000000], [0.343213, 0.710970, 0.147802, -0.049631, -0.369815, 0.993915, 0.000000, 0.000000], [0.769308, 0.046831, 0.206787, 0.944374, 0.822383, 0.003430, 0.000000, 0.000000], [-0.492308, 0.099799, -0.210160, -0.987494, -0.914054, 0.112486, 0.000000, 0.000000], [0.366556, -0.427743, 0.066329, 0.860596, 0.961399, -0.433157, 0.000000, 0.000000], [0.756652, 0.886567, 0.315060, 0.302048, -0.122897, 0.863826, 0.000000, 0.000000]]
pre_activation_mean: [1.217412, 1.000635, 1.746325, -1.517807, 1.726597, 2.199135]
pre_activation_std: [1.480637, 0.765716, 1.227441, 1.096587, 1.906269, 1.557849]
### 4
mean: [-0.064454, 0.637437, -0.082793, 1.765538, 2.188778, 1.328653]
std: [1.196082, 1.356360, 0.785878, 1.423928, 1.595767, 2.026011]
fourier: [[19.525182, 20.377886, 20.719441, 25.713576, 26.359436], [22.141654, 25.434495, 28.968263, 29.911925, 57.369364], [12.421396, 12.836447, 14.804262, 15.752212, 18.225679], [23.408138, 24.029161, 25.843329, 27.898146, 158.898377], [25.149927, 27.510797, 29.175674, 31.085639, 196.990068], [32.661346, 36.786417, 40.679053, 42.433081, 119.578722]]
input_correlations: [[-0.880621, -0.685804, 0.476587, 0.680177, 0.854639, -0.620978, 0.000000, 0.000000], [-0.655564, -0.434079, 0.802044, 0.832095, 0.984417, -0.232383, 0.000000, 0.000000], [0.657883, 0.162279, -0.767953, -0.825170, -0.883420, 0.071849, 0.000000, 0.000000], [0.871223, 0.888160, -0.019498, -0.353948, -0.525110, 0.925213, 0.000000, 0.000000], [0.902352, 0.856179, 0.010244, -0.340864, -0.499731, 0.928083, 0.000000, 0.000000], [0.843491, 0.826202, -0.369904, -0.583993, -0.790714, 0.736686, 0.000000, 0.000000]]
pre_activation_mean: [-0.064454, 0.637437, -0.082793, 1.765538, 2.188778, 1.328653]
pre_activation_std: [1.196082, 1.356360, 0.785878, 1.423928, 1.595767, 2.026011]
### 6
mean: [-0.336573, 0.185621, 1.980559, -0.273727, -0.198235, 0.060305]
std: [0.421185, 1.307417, 2.671399, 0.738511, 0.681457, 1.071676]
fourier: [[6.770240, 7.223472, 7.981262, 8.413187, 30.291542], [21.198367, 22.457151, 22.596814, 28.377797, 29.420198], [43.107094, 46.065229, 55.407893, 56.563342, 178.250328], [11.180958, 14.498643, 14.707939, 15.542577, 24.635453], [11.106020, 11.520685, 13.884626, 14.837132, 17.841150], [17.426868, 18.173317, 18.888067, 23.345118, 24.230428]]
input_correlations: [[0.631548, 0.627284, -0.551586, -0.929552, -0.933084, -0.989257, 0.000000, 0.000000], [0.923140, 0.946023, -0.568252, -0.740490, -0.736032, -0.829125, 0.000000, 0.000000], [-0.825017, -0.772442, 0.549315, 0.937472, 0.935865, 0.950601, 0.000000, 0.000000], [0.962404, 0.878664, -0.487823, -0.777325, -0.767841, -0.767169, 0.000000, 0.000000], [0.839073, 0.788390, -0.657524, -0.907326, -0.912625, -0.919048, 0.000000, 0.000000], [0.920504, 0.942802, -0.612625, -0.750923, -0.749968, -0.834499, 0.000000, 0.000000]]
pre_activation_mean: [-0.336573, 0.185621, 1.980559, -0.273727, -0.198235, 0.060305]
pre_activation_std: [0.421185, 1.307417, 2.671399, 0.738511, 0.681457, 1.071676]
### 8
mean: [0.518427, 0.947210, 0.698779, 0.188213, -0.050568, 1.006953]
std: [0.742450, 1.339545, 1.235178, 1.581279, 0.516784, 1.738671]
fourier: [[11.995266, 13.897050, 14.332392, 16.847399, 46.658414], [21.444706, 22.379657, 29.090336, 29.782869, 85.248933], [19.656704, 21.461403, 26.265365, 28.161517, 62.890117], [24.796090, 26.462241, 27.064671, 34.127942, 35.102144], [8.092160, 8.522799, 9.365218, 10.762843, 10.959762], [28.018744, 29.071800, 37.376046, 38.775961, 90.625800]]
input_correlations: [[0.436707, 0.858589, -0.217657, 0.883359, 0.800499, 0.866717, 0.000000, 0.000000], [-0.896599, -0.903633, 0.910577, -0.800288, -0.897430, -0.901814, 0.000000, 0.000000], [-0.883418, -0.934354, 0.878393, -0.813206, -0.893827, -0.932273, 0.000000, 0.000000], [-0.859535, -0.954228, 0.839061, -0.868685, -0.932443, -0.954357, 0.000000, 0.000000], [-0.771983, -0.974032, 0.719051, -0.945607, -0.964675, -0.978147, 0.000000, 0.000000], [-0.888595, -0.892229, 0.921144, -0.794033, -0.889785, -0.890698, 0.000000, 0.000000]]
pre_activation_mean: [0.518427, 0.947210, 0.698779, 0.188213, -0.050568, 1.006953]
pre_activation_std: [0.742450, 1.339545, 1.235178, 1.581279, 0.516784, 1.738671]
### 10
mean: [-1.758150]
std: [1.908189]
fourier: [[29.874329, 32.274924, 39.707836, 41.962063, 158.233526]]
input_correlations: [[0.470768, -0.996034, -0.994671, -0.970488, -0.965760, -0.986901, 0.000000, 0.000000]]
pre_activation_mean: [-1.758150]
pre_activation_std: [1.908189]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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0.482089,
0.245736,
-0.033585,
0.599155
],
[
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0.305537,
0.423448
],
[
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-0.40296,
-0.287398,
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-0.422226
],
[
0.831794,
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0.543506,
0.340887,
0.255549
],
[
0.579671,
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0.024957,
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],
[
-0.683424,
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0.583609,
0.174232,
0.168465
]
],
"network.0.bias": [
0.553124,
-0.107546,
-0.047655,
0.123907,
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0.608101
],
"network.2.weight": [
[
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],
[
0.048493,
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0.072822,
0.599432
],
[
0.413008,
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0.211462,
0.265348,
-0.031899
],
[
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-0.01111,
-0.046681,
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0.039287,
0.103667
],
[
0.281508,
-0.404683,
-0.521429,
0.37171,
0.504397,
-0.344075
],
[
0.343511,
0.439799,
-0.120518,
0.022877,
0.055113,
0.559629
]
],
"network.2.bias": [
0.468732,
0.129265,
0.110931,
-0.389525,
0.598227,
-0.153034
],
"network.4.weight": [
[
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],
[
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0.454565,
0.188926,
0.248255,
0.050782
],
[
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0.060666,
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[
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0.085426,
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],
[
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0.526138,
-0.161201,
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0.0313,
0.437105
],
[
0.21283,
0.315968,
-0.146958,
0.051445,
-0.519428,
0.605968
]
],
"network.4.bias": [
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0.080049,
0.095299,
0.270023,
0.287916,
0.560716
],
"network.6.weight": [
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],
[
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[
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0.49842,
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[
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[
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0.066456,
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[
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],
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[
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],
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"network.10.weight": [
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.465658, 1.120781, 0.887620, 0.670690, 0.065452, 1.327925]
std: [0.713047, 0.977350, 0.791164, 0.675139, 0.134842, 1.205991]
fourier: [[12.457890, 12.798930, 13.612427, 15.169370, 41.909267], [15.528897, 16.358597, 19.855549, 21.273829, 100.870266], [12.183401, 13.605971, 15.919529, 17.217559, 79.885782], [10.336776, 11.590917, 12.656199, 14.242402, 60.362130], [2.167378, 2.175421, 2.810485, 3.132937, 5.890642], [18.852866, 20.265680, 23.960258, 25.634385, 119.513248]]
input_correlations: [[0.283633, 0.586414, 0.548489, 0.262494, 0.753027, 0.000000, 0.000000, 0.000000], [-0.649861, 0.079877, 0.100024, 0.557996, 0.420877, 0.000000, 0.000000, 0.000000], [-0.047845, -0.577706, -0.416884, -0.766323, -0.530042, 0.000000, 0.000000, 0.000000], [0.821511, 0.324278, 0.677711, 0.261608, 0.457437, 0.000000, 0.000000, 0.000000], [0.897284, 0.066115, 0.582505, -0.126418, 0.139160, 0.000000, 0.000000, 0.000000], [-0.625581, -0.066945, 0.478630, 0.303587, 0.224772, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.481109, 0.907696, -2.686565, 3.103140, 0.468252, 1.541592]
pre_activation_std: [1.537137, 1.664338, 1.835981, 2.425765, 1.297502, 1.591458]
### 2
mean: [1.217412, 1.000635, 1.746325, -1.517807, 1.726597, 2.199135]
std: [1.480637, 0.765716, 1.227441, 1.096587, 1.906269, 1.557849]
fourier: [[24.503726, 26.142250, 28.530110, 31.681929, 109.567076], [11.884915, 12.127466, 13.757225, 14.337064, 90.057155], [20.259827, 23.098344, 23.869026, 24.984034, 157.169269], [17.306056, 20.658657, 22.940849, 23.141645, 136.602605], [32.768705, 33.031247, 37.965532, 41.136750, 155.393745], [22.031795, 25.394735, 27.550542, 30.384397, 197.922163]]
input_correlations: [[0.436512, 0.870650, 0.169810, -0.362463, -0.702638, 0.618124, 0.000000, 0.000000], [0.343213, 0.710970, 0.147802, -0.049631, -0.369815, 0.993915, 0.000000, 0.000000], [0.769308, 0.046831, 0.206787, 0.944374, 0.822383, 0.003430, 0.000000, 0.000000], [-0.492308, 0.099799, -0.210160, -0.987494, -0.914054, 0.112486, 0.000000, 0.000000], [0.366556, -0.427743, 0.066329, 0.860596, 0.961399, -0.433157, 0.000000, 0.000000], [0.756652, 0.886567, 0.315060, 0.302048, -0.122897, 0.863826, 0.000000, 0.000000]]
pre_activation_mean: [1.217412, 1.000635, 1.746325, -1.517807, 1.726597, 2.199135]
pre_activation_std: [1.480637, 0.765716, 1.227441, 1.096587, 1.906269, 1.557849]
### 4
mean: [-0.064454, 0.637437, -0.082793, 1.765538, 2.188778, 1.328653]
std: [1.196082, 1.356360, 0.785878, 1.423928, 1.595767, 2.026011]
fourier: [[19.525182, 20.377886, 20.719441, 25.713576, 26.359436], [22.141654, 25.434495, 28.968263, 29.911925, 57.369364], [12.421396, 12.836447, 14.804262, 15.752212, 18.225679], [23.408138, 24.029161, 25.843329, 27.898146, 158.898377], [25.149927, 27.510797, 29.175674, 31.085639, 196.990068], [32.661346, 36.786417, 40.679053, 42.433081, 119.578722]]
input_correlations: [[-0.880621, -0.685804, 0.476587, 0.680177, 0.854639, -0.620978, 0.000000, 0.000000], [-0.655564, -0.434079, 0.802044, 0.832095, 0.984417, -0.232383, 0.000000, 0.000000], [0.657883, 0.162279, -0.767953, -0.825170, -0.883420, 0.071849, 0.000000, 0.000000], [0.871223, 0.888160, -0.019498, -0.353948, -0.525110, 0.925213, 0.000000, 0.000000], [0.902352, 0.856179, 0.010244, -0.340864, -0.499731, 0.928083, 0.000000, 0.000000], [0.843491, 0.826202, -0.369904, -0.583993, -0.790714, 0.736686, 0.000000, 0.000000]]
pre_activation_mean: [-0.064454, 0.637437, -0.082793, 1.765538, 2.188778, 1.328653]
pre_activation_std: [1.196082, 1.356360, 0.785878, 1.423928, 1.595767, 2.026011]
### 6
mean: [-0.336573, 0.185621, 1.980559, -0.273727, -0.198235, 0.060305]
std: [0.421185, 1.307417, 2.671399, 0.738511, 0.681457, 1.071676]
fourier: [[6.770240, 7.223472, 7.981262, 8.413187, 30.291542], [21.198367, 22.457151, 22.596814, 28.377797, 29.420198], [43.107094, 46.065229, 55.407893, 56.563342, 178.250328], [11.180958, 14.498643, 14.707939, 15.542577, 24.635453], [11.106020, 11.520685, 13.884626, 14.837132, 17.841150], [17.426868, 18.173317, 18.888067, 23.345118, 24.230428]]
input_correlations: [[0.631548, 0.627284, -0.551586, -0.929552, -0.933084, -0.989257, 0.000000, 0.000000], [0.923140, 0.946023, -0.568252, -0.740490, -0.736032, -0.829125, 0.000000, 0.000000], [-0.825017, -0.772442, 0.549315, 0.937472, 0.935865, 0.950601, 0.000000, 0.000000], [0.962404, 0.878664, -0.487823, -0.777325, -0.767841, -0.767169, 0.000000, 0.000000], [0.839073, 0.788390, -0.657524, -0.907326, -0.912625, -0.919048, 0.000000, 0.000000], [0.920504, 0.942802, -0.612625, -0.750923, -0.749968, -0.834499, 0.000000, 0.000000]]
pre_activation_mean: [-0.336573, 0.185621, 1.980559, -0.273727, -0.198235, 0.060305]
pre_activation_std: [0.421185, 1.307417, 2.671399, 0.738511, 0.681457, 1.071676]
### 8
mean: [0.518427, 0.947210, 0.698779, 0.188213, -0.050568, 1.006953]
std: [0.742450, 1.339545, 1.235178, 1.581279, 0.516784, 1.738671]
fourier: [[11.995266, 13.897050, 14.332392, 16.847399, 46.658414], [21.444706, 22.379657, 29.090336, 29.782869, 85.248933], [19.656704, 21.461403, 26.265365, 28.161517, 62.890117], [24.796090, 26.462241, 27.064671, 34.127942, 35.102144], [8.092160, 8.522799, 9.365218, 10.762843, 10.959762], [28.018744, 29.071800, 37.376046, 38.775961, 90.625800]]
input_correlations: [[0.436707, 0.858589, -0.217657, 0.883359, 0.800499, 0.866717, 0.000000, 0.000000], [-0.896599, -0.903633, 0.910577, -0.800288, -0.897430, -0.901814, 0.000000, 0.000000], [-0.883418, -0.934354, 0.878393, -0.813206, -0.893827, -0.932273, 0.000000, 0.000000], [-0.859535, -0.954228, 0.839061, -0.868685, -0.932443, -0.954357, 0.000000, 0.000000], [-0.771983, -0.974032, 0.719051, -0.945607, -0.964675, -0.978147, 0.000000, 0.000000], [-0.888595, -0.892229, 0.921144, -0.794033, -0.889785, -0.890698, 0.000000, 0.000000]]
pre_activation_mean: [0.518427, 0.947210, 0.698779, 0.188213, -0.050568, 1.006953]
pre_activation_std: [0.742450, 1.339545, 1.235178, 1.581279, 0.516784, 1.738671]
### 10
mean: [-1.758150]
std: [1.908189]
fourier: [[29.874329, 32.274924, 39.707836, 41.962063, 158.233526]]
input_correlations: [[0.470768, -0.996034, -0.994671, -0.970488, -0.965760, -0.986901, 0.000000, 0.000000]]
pre_activation_mean: [-1.758150]
pre_activation_std: [1.908189]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.4656584858894348, "std": 0.7130473256111145, "fourier": [12.457890105521361, 12.798929863127142, 13.612427196635434, 15.169370335460268, 41.90926718339324], "input_correlations": [0.28363252074297995, 0.586414161660362, 0.5484894042528721, 0.26249400369705034, 0.753026636593997, 0.0, 0.0, 0.0], "pre_activation_mean": 2.481109142303467, "pre_activation_std": 1.5371373891830444}, "1": {"mean": 1.1207807064056396, "std": 0.9773504137992859, "fourier": [15.528896518042526, 16.358597040391498, 19.855548540648442, 21.273828855505908, 100.87026625871658], "input_correlations": [-0.6498610693140268, 0.0798767684169623, 0.10002447358760078, 0.5579963564003383, 0.4208765110263087, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9076963663101196, "pre_activation_std": 1.6643379926681519}, "2": {"mean": 0.8876197934150696, "std": 0.7911636233329773, "fourier": [12.183400558637482, 13.605970893896764, 15.9195286788113, 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"num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.105059, 0.482089, 0.245736, -0.033585, 0.599155], [-0.695801, 0.167851, 0.190439, 0.305537, 0.423448], [0.210697, -0.40296, -0.287398, -0.487651, -0.422226], [0.831794, -0.130282, 0.543506, 0.340887, 0.255549], [0.579671, -0.23544, 0.263693, 0.024957, -0.081356], [-0.683424, -0.009069, 0.583609, 0.174232, 0.168465]], "network.0.bias": [0.553124, -0.107546, -0.047655, 0.123907, -0.328097, 0.608101], "network.2.weight": [[0.467912, 0.646283, -0.119923, -0.302014, -0.262984, -0.02116], [0.048493, -0.047161, -0.180124, -0.071379, 0.072822, 0.599432], [0.413008, -0.124335, -0.570064, 0.211462, 0.265348, -0.031899], [0.073676, -0.01111, -0.046681, -0.485903, 0.039287, 0.103667], [0.281508, -0.404683, -0.521429, 0.37171, 0.504397, -0.344075], [0.343511, 0.439799, -0.120518, 0.022877, 0.055113, 0.559629]], "network.2.bias": [0.468732, 0.129265, 0.110931, -0.389525, 0.598227, -0.153034], "network.4.weight": [[-0.374041, -0.06919, -0.032069, -0.340337, 0.385044, -0.118851], [-0.441243, -0.132494, 0.454565, 0.188926, 0.248255, 0.050782], [0.610406, 0.049391, -0.381619, -0.333013, 0.060666, -0.237397], [0.215831, 0.346015, 0.085426, -0.640906, -0.2073, 0.482522], [0.533496, 0.526138, -0.161201, -0.173345, 0.0313, 0.437105], [0.21283, 0.315968, -0.146958, 0.051445, -0.519428, 0.605968]], "network.4.bias": [0.131106, 0.080049, 0.095299, 0.270023, 0.287916, 0.560716], "network.6.weight": [[0.196264, -0.146415, -0.238252, 0.103191, 0.09369, -0.45033], [0.326365, 0.511762, 0.018429, 0.157457, 0.074472, -0.565702], [-0.66918, -0.416735, 0.232868, 0.49842, 0.481791, 0.26416], [0.491704, 0.200131, 0.151404, -0.305412, -0.164454, 0.317651], [0.3092, 0.005193, -0.543508, -0.307824, 0.066456, -0.04921], [0.168383, 0.456154, -0.222176, -0.00059, 0.074071, -0.355467]], "network.6.bias": [0.095977, 0.203814, 0.154792, -0.251167, 0.243327, 0.137399], "network.8.weight": [[0.315296, 0.250838, 0.216055, 0.67655, 0.239858, 0.366895], [-0.26309, -0.390958, 0.327771, 0.050309, -0.560403, -0.222562], [-0.196482, -0.599093, 0.275004, -0.151193, 0.217593, -0.171151], [-0.499888, -0.400715, 0.270544, -0.534582, -0.072801, -0.536431], [0.078793, -0.090151, 0.036964, -0.340251, -0.15009, -0.220956], [0.085682, -0.436907, 0.471733, -0.081622, -0.487065, -0.334544]], "network.8.bias": [-0.282127, 0.463282, 0.385494, -0.058764, 0.022256, 0.27225], "network.10.weight": [[0.366605, -0.445155, -0.631664, -0.218818, -0.09704, -0.587034]], "network.10.bias": [0.063383]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7060195505619049, "train_acc": 0.435, "val_loss": 0.6883154511451721, "val_acc": 0.56}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6789571344852448, "train_acc": 0.565, "val_loss": 0.6603962779045105, "val_acc": 0.56}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6482313275337219, "train_acc": 0.565, "val_loss": 0.5213723182678223, "val_acc": 0.56}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.49470990896224976, "train_acc": 0.635, "val_loss": 0.2256193608045578, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.2741515189409256, "train_acc": 0.92, "val_loss": 0.25253209471702576, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.2857860326766968, "train_acc": 0.92, "val_loss": 0.18782611191272736, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.2225063182413578, "train_acc": 0.92, "val_loss": 0.16764873266220093, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.21073564887046814, "train_acc": 0.925, "val_loss": 0.18825307488441467, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.21921247243881226, "train_acc": 0.925, "val_loss": 0.18812140822410583, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 9, "train_loss": 0.21455252170562744, "train_acc": 0.92, "val_loss": 0.17715094983577728, "val_acc": 0.94}], "summary": {"total_epochs": 10, "degraded_epochs": 3, "improved_epochs": 7, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6883154511451721, "final_val_loss": 0.5213723182678223, "initial_val_acc": 0.56, "final_val_acc": 0.56, "best_val_acc": 0.56}, "improved_stage": {"initial_val_loss": 0.2256193608045578, "final_val_loss": 0.17715094983577728, "initial_val_acc": 0.94, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 3}, "improvement": 0.3799999999999999, "first_improvement_epoch": 2}} |
69 | {"target_pattern": "alternating", "degraded_accuracy": 0.62, "improved_accuracy": 0.98, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8119, "learning_rate": 0.06602573665381442, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.243600, 0.544240, 0.000000, 0.259097, 0.000000]
std: [0.404188, 0.932413, 0.000000, 0.493043, 0.000000]
fourier: [[5.137959, 5.274913, 7.216745, 7.797496, 21.924035], [12.713670, 12.943203, 15.012062, 18.332087, 48.981599], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [6.843667, 7.150583, 7.357549, 9.643467, 23.318731], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.473333, 0.849625, 0.556248, 0.535555, 0.301388, 0.000000, 0.000000, 0.000000], [0.024728, -0.672556, 0.044337, -0.777838, 0.342096, 0.000000, 0.000000, 0.000000], [-0.760126, -0.443045, -0.015774, 0.371525, 0.327268, 0.000000, 0.000000, 0.000000], [-0.601050, 0.023989, -0.770248, 0.338153, -0.508864, 0.000000, 0.000000, 0.000000], [-0.617306, 0.026382, 0.523294, 0.106156, -0.144120, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.643259, -2.489814, 0.005156, -2.211759, 0.160188]
pre_activation_std: [2.662919, 2.920282, 2.560334, 3.782081, 1.209027]
### 2
mean: [0.131208, -1.163100, -1.544360, 3.041675, -1.232846]
std: [1.401739, 0.659446, 1.447857, 2.172098, 2.233924]
fourier: [[19.145380, 20.532173, 21.133347, 22.035473, 27.031223], [9.097812, 9.262197, 10.934398, 14.735194, 104.678995], [25.440984, 25.524190, 27.034707, 29.801891, 138.992385], [31.812127, 32.015642, 34.464682, 35.859564, 273.750757], [32.866191, 33.269502, 35.917558, 37.789285, 110.956187]]
input_correlations: [[-0.177583, 0.128156, -0.692806, 0.696539, -0.486732, 0.000000, 0.000000, 0.000000], [-0.762256, -0.032519, -0.062489, -0.642209, 0.191341, 0.000000, 0.000000, 0.000000], [-0.923052, 0.267767, 0.180142, -0.031790, -0.274981, 0.000000, 0.000000, 0.000000], [0.789247, -0.146375, 0.537951, -0.146002, 0.585713, 0.000000, 0.000000, 0.000000], [-0.362116, 0.339134, -0.690842, 0.462895, -0.638178, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.131208, -1.163100, -1.544360, 3.041675, -1.232846]
pre_activation_std: [1.401739, 0.659446, 1.447857, 2.172098, 2.233924]
### 4
mean: [1.523227, 3.000175, -1.620594, -1.066353, -0.240318]
std: [1.372585, 2.053847, 0.623697, 1.057916, 2.158786]
fourier: [[19.435423, 20.223750, 21.131157, 22.210661, 137.090413], [28.532582, 30.337118, 32.444803, 34.029007, 270.015762], [8.839081, 10.014006, 10.816863, 12.400184, 145.853445], [14.611945, 16.263853, 17.017487, 17.267127, 95.971793], [28.654624, 29.235948, 31.098754, 31.923731, 35.396853]]
input_correlations: [[-0.631725, 0.000000, -0.159195, 0.959824, -0.633450, 0.000000, 0.000000, 0.000000], [-0.521065, 0.000000, -0.161430, 0.991979, -0.499822, 0.000000, 0.000000, 0.000000], [-0.158852, 0.000000, 0.170988, -0.806687, -0.160641, 0.000000, 0.000000, 0.000000], [0.718513, 0.000000, 0.103146, -0.940805, 0.658084, 0.000000, 0.000000, 0.000000], [0.879711, 0.000000, 0.088321, -0.797396, 0.838298, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.523227, 3.000175, -1.620594, -1.066353, -0.240318]
pre_activation_std: [1.372585, 2.053847, 0.623697, 1.057916, 2.158786]
### 6
mean: [-1.450643, -2.590044, -0.723606, -2.258179, -2.283853]
std: [1.774207, 3.335896, 0.203144, 2.331414, 0.761927]
fourier: [[25.119760, 27.273378, 27.311874, 28.542238, 130.557882], [48.674546, 50.313675, 50.619640, 52.040568, 233.103934], [3.004200, 3.021460, 3.042295, 3.935721, 65.124569], [33.952087, 35.489651, 35.675709, 36.017501, 203.236093], [9.756927, 9.903238, 10.186332, 16.970709, 205.546711]]
input_correlations: [[-0.995813, -0.979055, 0.000000, 0.697648, 0.748105, 0.000000, 0.000000, 0.000000], [-0.985593, -0.961895, 0.000000, 0.748365, 0.795904, 0.000000, 0.000000, 0.000000], [-0.693937, -0.773472, 0.000000, -0.068318, -0.037729, 0.000000, 0.000000, 0.000000], [-0.982199, -0.953686, 0.000000, 0.765585, 0.811979, 0.000000, 0.000000, 0.000000], [-0.162416, -0.275486, 0.000000, -0.605251, -0.598618, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.450643, -2.590044, -0.723606, -2.258179, -2.283853]
pre_activation_std: [1.774207, 3.335896, 0.203144, 2.331414, 0.761927]
### 8
mean: [-0.256898]
std: [1.103005]
fourier: [[15.008187, 15.546375, 17.184079, 21.714035, 23.120857]]
input_correlations: [[0.983531, 0.999125, 0.000000, 0.979984, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.256898]
pre_activation_std: [1.103005]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
-0.502449,
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[
0.600875,
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}
## Activation Signature
### 0
mean: [0.243600, 0.544240, 0.000000, 0.259097, 0.000000]
std: [0.404188, 0.932413, 0.000000, 0.493043, 0.000000]
fourier: [[5.137959, 5.274913, 7.216745, 7.797496, 21.924035], [12.713670, 12.943203, 15.012062, 18.332087, 48.981599], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [6.843667, 7.150583, 7.357549, 9.643467, 23.318731], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.473333, 0.849625, 0.556248, 0.535555, 0.301388, 0.000000, 0.000000, 0.000000], [0.024728, -0.672556, 0.044337, -0.777838, 0.342096, 0.000000, 0.000000, 0.000000], [-0.760126, -0.443045, -0.015774, 0.371525, 0.327268, 0.000000, 0.000000, 0.000000], [-0.601050, 0.023989, -0.770248, 0.338153, -0.508864, 0.000000, 0.000000, 0.000000], [-0.617306, 0.026382, 0.523294, 0.106156, -0.144120, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.643259, -2.489814, 0.005156, -2.211759, 0.160188]
pre_activation_std: [2.662919, 2.920282, 2.560334, 3.782081, 1.209027]
### 2
mean: [0.131208, -1.163100, -1.544360, 3.041675, -1.232846]
std: [1.401739, 0.659446, 1.447857, 2.172098, 2.233924]
fourier: [[19.145380, 20.532173, 21.133347, 22.035473, 27.031223], [9.097812, 9.262197, 10.934398, 14.735194, 104.678995], [25.440984, 25.524190, 27.034707, 29.801891, 138.992385], [31.812127, 32.015642, 34.464682, 35.859564, 273.750757], [32.866191, 33.269502, 35.917558, 37.789285, 110.956187]]
input_correlations: [[-0.177583, 0.128156, -0.692806, 0.696539, -0.486732, 0.000000, 0.000000, 0.000000], [-0.762256, -0.032519, -0.062489, -0.642209, 0.191341, 0.000000, 0.000000, 0.000000], [-0.923052, 0.267767, 0.180142, -0.031790, -0.274981, 0.000000, 0.000000, 0.000000], [0.789247, -0.146375, 0.537951, -0.146002, 0.585713, 0.000000, 0.000000, 0.000000], [-0.362116, 0.339134, -0.690842, 0.462895, -0.638178, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.131208, -1.163100, -1.544360, 3.041675, -1.232846]
pre_activation_std: [1.401739, 0.659446, 1.447857, 2.172098, 2.233924]
### 4
mean: [1.523227, 3.000175, -1.620594, -1.066353, -0.240318]
std: [1.372585, 2.053847, 0.623697, 1.057916, 2.158786]
fourier: [[19.435423, 20.223750, 21.131157, 22.210661, 137.090413], [28.532582, 30.337118, 32.444803, 34.029007, 270.015762], [8.839081, 10.014006, 10.816863, 12.400184, 145.853445], [14.611945, 16.263853, 17.017487, 17.267127, 95.971793], [28.654624, 29.235948, 31.098754, 31.923731, 35.396853]]
input_correlations: [[-0.631725, 0.000000, -0.159195, 0.959824, -0.633450, 0.000000, 0.000000, 0.000000], [-0.521065, 0.000000, -0.161430, 0.991979, -0.499822, 0.000000, 0.000000, 0.000000], [-0.158852, 0.000000, 0.170988, -0.806687, -0.160641, 0.000000, 0.000000, 0.000000], [0.718513, 0.000000, 0.103146, -0.940805, 0.658084, 0.000000, 0.000000, 0.000000], [0.879711, 0.000000, 0.088321, -0.797396, 0.838298, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.523227, 3.000175, -1.620594, -1.066353, -0.240318]
pre_activation_std: [1.372585, 2.053847, 0.623697, 1.057916, 2.158786]
### 6
mean: [-1.450643, -2.590044, -0.723606, -2.258179, -2.283853]
std: [1.774207, 3.335896, 0.203144, 2.331414, 0.761927]
fourier: [[25.119760, 27.273378, 27.311874, 28.542238, 130.557882], [48.674546, 50.313675, 50.619640, 52.040568, 233.103934], [3.004200, 3.021460, 3.042295, 3.935721, 65.124569], [33.952087, 35.489651, 35.675709, 36.017501, 203.236093], [9.756927, 9.903238, 10.186332, 16.970709, 205.546711]]
input_correlations: [[-0.995813, -0.979055, 0.000000, 0.697648, 0.748105, 0.000000, 0.000000, 0.000000], [-0.985593, -0.961895, 0.000000, 0.748365, 0.795904, 0.000000, 0.000000, 0.000000], [-0.693937, -0.773472, 0.000000, -0.068318, -0.037729, 0.000000, 0.000000, 0.000000], [-0.982199, -0.953686, 0.000000, 0.765585, 0.811979, 0.000000, 0.000000, 0.000000], [-0.162416, -0.275486, 0.000000, -0.605251, -0.598618, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.450643, -2.590044, -0.723606, -2.258179, -2.283853]
pre_activation_std: [1.774207, 3.335896, 0.203144, 2.331414, 0.761927]
### 8
mean: [-0.256898]
std: [1.103005]
fourier: [[15.008187, 15.546375, 17.184079, 21.714035, 23.120857]]
input_correlations: [[0.983531, 0.999125, 0.000000, 0.979984, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.256898]
pre_activation_std: [1.103005]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.13120833039283752, "std": 1.4017390012741089, "fourier": [19.145380143529014, 20.532173201621113, 21.133347080995, 22.035472738439093, 27.031223094476488], "input_correlations": [-0.17758296189021533, 0.12815559479008942, -0.6928057581443672, 0.6965388928421017, -0.48673177854353666, 0.0, 0.0, 0.0], "pre_activation_mean": 0.13120833039283752, "pre_activation_std": 1.4017390012741089}, "1": {"mean": -1.1630998849868774, "std": 0.659445583820343, "fourier": [9.097812460524304, 9.262197273905933, 10.934397800517814, 14.735193651361227, 104.67899546027184], "input_correlations": [-0.7622558802225429, -0.03251922961885093, -0.06248888808775042, -0.6422087437924063, 0.1913412073709919, 0.0, 0.0, 0.0], "pre_activation_mean": -1.1630998849868774, "pre_activation_std": 0.659445583820343}, "2": {"mean": -1.5443600416183472, "std": 1.4478570222854614, "fourier": [25.440983788396093, 25.524190051196747, 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"profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.192332, 0.901205, 0.45893, 0.394709, 0.227065], [0.085466, -0.75606, 0.071998, -0.952257, 0.669456], [-0.947514, -0.521501, 0.296149, 0.495117, 0.491362], [-0.723747, 0.376346, -1.199104, 0.576784, -0.72643], [-0.526688, 0.083773, 0.503734, 0.021937, -0.107173]], "network.0.bias": [-0.323415, -0.152458, -0.15181, 0.166964, -0.30414], "network.2.weight": [[-0.093618, 0.266724, -0.633088, 0.853461, -0.276551], [-0.192393, -0.095958, -0.073829, -0.331703, 0.220671], [-0.502449, 0.504119, 0.321115, 0.094254, -0.264992], [0.600875, -0.253682, 0.675718, -0.281929, 0.809222], [-0.261035, 0.920709, -0.913213, 0.896239, -0.906618]], "network.2.bias": [0.766774, -0.33077, -0.015142, -0.05773, 0.455963], "network.4.weight": [[0.058561, 0.051596, -0.028275, 0.538954, -0.561742], [0.16088, -0.075065, 0.308732, 0.907568, -0.474914], [-0.381064, -0.058121, -0.061588, -0.320567, -0.079917], [0.262968, 0.010829, -0.796871, -0.383862, 0.199239], [0.884838, -0.336966, -0.666275, -0.504792, 0.824407]], "network.4.bias": [0.067125, 0.321447, -0.391646, -0.113625, 0.4771], "network.6.weight": [[-0.561884, -0.403867, 0.072051, -0.057906, 0.249116], [-0.251024, -1.090843, 0.209788, 0.322096, 0.75494], [-0.167605, -0.030089, 0.120821, -0.006865, -0.139193], [-0.592057, -0.500754, -0.008147, 0.676873, 0.471047], [-0.746623, 0.046625, 0.05037, -0.209413, -0.744646]], "network.6.bias": [0.464237, 0.454459, -0.254235, -0.243117, -0.620625], "network.8.weight": [[0.33775, 0.756397, 0.313045, 0.546553, -0.189318]], "network.8.bias": [-0.892447]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6851904690265656, "train_acc": 0.555, "val_loss": 0.6799935102462769, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6713716089725494, "train_acc": 0.565, "val_loss": 0.6291624307632446, "val_acc": 0.62}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6156542599201202, "train_acc": 0.685, "val_loss": 0.5355919599533081, "val_acc": 0.88}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.48901815712451935, "train_acc": 0.855, "val_loss": 0.40351298451423645, "val_acc": 0.9}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.4048047512769699, "train_acc": 0.88, "val_loss": 0.3246401846408844, "val_acc": 0.96}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3426677733659744, "train_acc": 0.935, "val_loss": 0.30573350191116333, "val_acc": 0.96}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.32645805180072784, "train_acc": 0.94, "val_loss": 0.2748584449291229, "val_acc": 0.96}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.2828473597764969, "train_acc": 0.96, "val_loss": 0.24883367121219635, "val_acc": 0.98}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.27218571305274963, "train_acc": 0.965, "val_loss": 0.25613099336624146, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.29918256402015686, "train_acc": 0.96, "val_loss": 0.3284101188182831, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.34373000264167786, "train_acc": 0.955, "val_loss": 0.23177064955234528, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.27394894510507584, "train_acc": 0.96, "val_loss": 0.16274195909500122, "val_acc": 0.98}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.6799935102462769, "final_val_loss": 0.6291624307632446, "initial_val_acc": 0.54, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.5355919599533081, "final_val_loss": 0.16274195909500122, "initial_val_acc": 0.88, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 7}, "improvement": 0.36, "first_improvement_epoch": 1}} |
70 | {"target_pattern": "starts_with", "degraded_accuracy": 0.62, "improved_accuracy": 0.8, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 2852, "learning_rate": 0.07766329866765023, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.weight": [
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [-0.100708, 0.004405, 0.139587, -0.090681, 0.284973, -0.114938, -0.100426, -0.129197]
std: [0.054609, 0.089387, 0.392386, 0.064095, 0.268358, 0.065060, 0.065790, 0.047766]
fourier: [[0.807416, 0.822908, 1.006167, 1.054864, 9.063737], [1.261140, 1.283082, 1.366780, 1.616325, 1.676684], [5.667369, 5.863358, 6.810433, 7.724726, 12.562799], [0.869892, 0.924561, 1.130147, 1.315449, 8.161312], [3.817668, 3.837194, 4.846070, 5.799173, 25.647592], [0.938185, 0.938466, 1.229832, 1.327903, 10.344394], [0.901817, 0.945077, 1.181736, 1.384860, 9.038362], [0.701410, 0.725118, 0.754695, 0.888937, 11.627693]]
input_correlations: [[-0.729253, -0.460946, -0.691388, -0.168702, -0.630438, 0.000000, 0.000000, 0.000000], [0.000103, 0.258266, 0.435810, -0.094996, 0.809184, 0.000000, 0.000000, 0.000000], [-0.534909, 0.138977, -0.251922, 0.607355, 0.509526, 0.000000, 0.000000, 0.000000], [-0.304324, -0.212407, -0.700799, 0.303726, 0.494758, 0.000000, 0.000000, 0.000000], [0.688473, 0.292581, 0.638507, -0.279756, -0.330816, 0.000000, 0.000000, 0.000000], [0.373819, 0.811043, -0.261482, 0.516423, 0.047201, 0.000000, 0.000000, 0.000000], [0.404110, -0.330253, 0.477678, -0.542381, 0.604641, 0.000000, 0.000000, 0.000000], [-0.774828, -0.648105, 0.045240, -0.364132, 0.057647, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.667314, 1.374230, 0.884199, -0.696457, 0.785034, 1.678963, 0.522961, -0.794434]
pre_activation_std: [2.088177, 1.556194, 1.616518, 1.136647, 1.623303, 1.753977, 1.880699, 0.901573]
### 2
mean: [1.407666, 0.645878, -2.418470, -1.147997, -0.040330, 0.921328, 0.076205, -0.759438]
std: [1.193794, 1.685495, 1.631744, 1.187089, 0.729780, 1.223758, 1.316061, 0.731956]
fourier: [[17.180965, 19.157111, 20.432537, 20.751744, 126.689933], [26.786752, 27.200415, 28.012847, 30.026076, 58.129048], [25.557986, 25.789406, 30.030247, 36.712184, 217.662267], [19.001123, 20.950079, 23.836275, 24.923025, 103.319718], [10.944402, 11.062464, 11.201174, 13.310341, 14.057365], [18.958291, 20.821466, 21.024361, 24.600608, 82.919538], [16.841834, 17.053433, 18.254302, 23.250855, 33.397271], [10.995695, 11.325460, 12.937449, 18.490980, 68.349384]]
input_correlations: [[0.025084, 0.598957, 0.950198, 0.727763, -0.484995, 0.437940, 0.051930, -0.166673], [0.027534, 0.669624, 0.846577, 0.697933, -0.653263, -0.052191, 0.198857, -0.042771], [-0.354835, -0.924480, -0.673924, -0.587863, 0.064205, -0.200382, -0.612023, -0.150374], [-0.479047, -0.417976, 0.420184, 0.285810, -0.793560, -0.012818, -0.793355, -0.396853], [0.506822, 0.220149, -0.526860, -0.298557, 0.845315, -0.183926, 0.357029, 0.454658], [0.100689, -0.346030, -0.437081, -0.396876, 0.729168, 0.641806, -0.120510, -0.011069], [0.258958, 0.669137, 0.037861, 0.131414, -0.102713, -0.698118, 0.746126, 0.392011], [-0.072333, 0.355493, -0.115629, -0.124394, -0.455920, -0.667031, 0.486892, 0.102536]]
pre_activation_mean: [1.407666, 0.645878, -2.418470, -1.147997, -0.040330, 0.921328, 0.076205, -0.759438]
pre_activation_std: [1.193794, 1.685495, 1.631744, 1.187089, 0.729780, 1.223758, 1.316061, 0.731956]
### 4
mean: [1.220773, -0.676017, -0.600421, 1.069370, -1.234290, -0.159718, 0.176618, 0.539774]
std: [1.240139, 0.633311, 0.714393, 1.151727, 1.435765, 0.606092, 0.654732, 1.323952]
fourier: [[20.511431, 20.734197, 21.595389, 25.315379, 109.869573], [10.113639, 10.494598, 11.391685, 11.846773, 60.841560], [10.710173, 10.984119, 12.357430, 12.824062, 54.037896], [18.911288, 19.912104, 21.045997, 21.429185, 96.243346], [22.579778, 22.729193, 24.472834, 27.538012, 111.086125], [9.377979, 9.572555, 9.688955, 11.046921, 14.374592], [9.109931, 9.993719, 12.830932, 14.335659, 15.895583], [19.894134, 20.415853, 21.541601, 23.061366, 48.579654]]
input_correlations: [[0.898729, 0.985786, 0.638903, 0.167905, -0.309810, -0.340491, 0.493830, 0.276831], [-0.948228, -0.929192, -0.582646, -0.224198, 0.236952, 0.163061, -0.145109, 0.040596], [-0.863723, -0.907619, -0.472177, -0.025588, 0.617741, 0.615586, -0.397468, -0.179857], [0.953225, 0.985826, 0.600786, 0.137840, -0.382305, -0.369725, 0.341954, 0.117793], [-0.840436, -0.948767, -0.619048, -0.093690, 0.348725, 0.552697, -0.599427, -0.320209], [-0.733225, -0.900817, -0.472129, -0.075859, 0.434910, 0.736151, -0.551293, -0.247620], [0.912175, 0.930193, 0.380009, 0.126416, -0.575608, -0.381837, 0.097805, -0.077477], [0.561273, 0.783782, 0.465037, -0.011399, -0.300916, -0.746597, 0.767297, 0.460000]]
pre_activation_mean: [1.220773, -0.676017, -0.600421, 1.069370, -1.234290, -0.159718, 0.176618, 0.539774]
pre_activation_std: [1.240139, 0.633311, 0.714393, 1.151727, 1.435765, 0.606092, 0.654732, 1.323952]
### 6
mean: [-1.452013, -1.572573, -0.210397, -0.324211, 1.196819, -1.509564, -1.455518, 1.531674]
std: [1.300279, 1.473262, 0.452591, 0.423290, 0.901308, 1.385380, 1.543926, 1.338043]
fourier: [[20.949774, 22.834914, 23.740016, 24.126678, 130.681136], [23.326021, 25.250243, 26.489318, 28.687816, 141.531557], [6.913816, 7.154239, 7.630935, 8.302261, 18.935741], [6.673086, 6.705081, 7.801544, 8.489812, 29.178980], [12.934881, 13.320139, 15.046424, 17.642043, 107.713703], [21.192011, 24.402329, 25.568297, 26.509122, 135.860754], [25.046370, 26.327898, 27.475968, 30.407727, 130.996585], [20.223993, 20.703478, 24.111317, 26.645831, 137.850684]]
input_correlations: [[-0.984601, -0.395308, 0.194716, -0.997426, 0.040339, 0.451758, -0.961131, -0.788293], [-0.992441, -0.393067, 0.194674, -0.971636, 0.022910, 0.492304, -0.908798, -0.888894], [-0.927911, -0.433150, 0.435011, -0.940661, 0.300428, 0.672694, -0.903478, -0.806825], [-0.964393, -0.349583, -0.056324, -0.914536, -0.251497, 0.250997, -0.856874, -0.896868], [0.877884, 0.345173, -0.139332, 0.783843, 0.024859, -0.460158, 0.674640, 0.989207], [-0.983312, -0.408602, 0.114026, -0.951633, -0.038382, 0.428153, -0.902271, -0.918724], [-0.998182, -0.380643, 0.182636, -0.984840, -0.000211, 0.457623, -0.922029, -0.854605], [0.966730, 0.401874, -0.136870, 0.912579, 0.032040, -0.457748, 0.838942, 0.956554]]
pre_activation_mean: [-1.452013, -1.572573, -0.210397, -0.324211, 1.196819, -1.509564, -1.455518, 1.531674]
pre_activation_std: [1.300279, 1.473262, 0.452591, 0.423290, 0.901308, 1.385380, 1.543926, 1.338043]
### 8
mean: [-1.679119, -0.047673, 0.119352, -2.220514, 0.229368, -1.616716, -1.994215, -1.282895]
std: [0.816652, 0.269857, 0.479684, 1.750114, 0.666814, 1.224031, 1.546389, 0.490317]
fourier: [[11.584942, 12.076672, 13.528707, 16.063254, 151.120685], [3.962431, 4.139763, 4.290614, 4.615838, 5.228805], [7.100421, 7.102973, 8.166050, 9.490640, 10.741693], [25.612140, 26.285434, 30.439018, 34.833701, 199.846214], [9.985589, 10.884972, 11.855056, 13.206900, 20.643105], [18.233082, 18.462472, 21.641577, 24.278960, 145.504412], [22.691679, 23.199801, 26.919174, 30.719160, 179.479354], [6.872900, 7.290782, 8.325362, 9.489581, 115.460583]]
input_correlations: [[-0.728644, -0.819279, 0.499829, 0.584598, -0.998978, -0.900056, -0.727532, -0.975117], [-0.808581, -0.878995, 0.527503, 0.620705, -0.982986, -0.946505, -0.808994, -0.987610], [0.765338, 0.844168, -0.493115, -0.599079, 0.994457, 0.918842, 0.761960, 0.987690], [-0.773032, -0.836577, 0.502194, 0.580599, -0.988847, -0.912697, -0.753472, -0.993886], [-0.855720, -0.903188, 0.485594, 0.656864, -0.965421, -0.954187, -0.837397, -0.994484], [-0.786495, -0.835596, 0.512660, 0.564459, -0.978838, -0.911800, -0.756813, -0.997768], [-0.775660, -0.840012, 0.498444, 0.584561, -0.989362, -0.915067, -0.758999, -0.993728], [-0.698049, -0.778812, 0.479233, 0.525637, -0.996783, -0.868956, -0.696349, -0.971874]]
pre_activation_mean: [-1.679119, -0.047673, 0.119352, -2.220514, 0.229368, -1.616716, -1.994215, -1.282895]
pre_activation_std: [0.816652, 0.269857, 0.479684, 1.750114, 0.666814, 1.224031, 1.546389, 0.490317]
### 10
mean: [-0.301392]
std: [0.363434]
fourier: [[5.141183, 5.625164, 6.999628, 7.087651, 27.125238]]
input_correlations: [[0.983709, -0.992381, 0.898136, 0.950782, -0.975982, 0.993337, 0.974554, 0.941776]]
pre_activation_mean: [-0.301392]
pre_activation_std: [0.363434]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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-0.050679,
-0.514253
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-0.302426,
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[
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-0.206086,
0.30586,
0.543097
],
[
-0.079408,
-0.041076,
-0.458951,
0.124647,
0.403183
],
[
0.468417,
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0.468816,
-0.148078,
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],
[
0.259849,
0.699376,
-0.484749,
0.238487,
0.062825
],
[
0.259498,
-0.339445,
0.338364,
-0.455443,
0.565609
],
[
-0.362326,
-0.170348,
0.160307,
-0.137394,
0.0872
]
],
"network.0.bias": [
-0.012525,
0.312624,
0.183372,
-0.328648,
0.055388,
0.504859,
0.390859,
-0.180906
],
"network.2.weight": [
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0.195415,
0.364784,
0.363967,
-0.346899,
0.286099,
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0.123989
],
[
0.037319,
0.446535,
0.439275,
0.494722,
-0.640574,
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0.122101,
0.427193
],
[
0.136023,
-0.51099,
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0.0744,
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-0.507156,
0.066623
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[
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0.094652,
0.539688,
-0.419393,
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-0.509378,
0.28604
],
[
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0.296048,
0.045645,
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0.642305,
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-0.290899,
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[
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-0.302835,
-0.093821,
0.369471,
0.56782,
0.120083,
-0.036759
],
[
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0.479531,
0.059666,
-0.23069,
-0.09904,
-0.511406,
0.239512,
0.410266
],
[
-0.280079,
0.269663,
-0.44598,
-0.02075,
-0.58659,
-0.032417,
0.213232,
0.038789
]
],
"network.2.bias": [
0.421183,
0.232412,
-0.512581,
0.000313,
-0.388137,
0.096238,
0.145182,
-0.223705
],
"network.4.weight": [
[
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0.668432,
0.102159,
0.204643,
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0.099135,
0.219207,
0.3517
],
[
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-0.32137,
0.335345,
-0.084873,
-0.383515,
-0.007972,
0.195719,
-0.191686
],
[
-0.22122,
-0.160164,
-0.051503,
0.258952,
0.533712,
0.114374,
-0.178619,
0.115494
],
[
0.368136,
0.523548,
0.049082,
-0.24655,
0.00505,
-0.030973,
-0.001411,
0.123282
],
[
-0.47159,
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0.089142,
0.136221,
0.1123,
0.234261,
-0.496401,
-0.092246
],
[
0.05488,
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0.176317,
0.202923,
-0.107808,
0.15551
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[
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0.059552,
-0.38493,
0.029612,
-0.111705,
-0.325904
],
[
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0.097423,
-0.464399,
-0.276344,
-0.441187,
0.682198,
0.044735
]
],
"network.4.bias": [
0.260341,
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0.325313
],
"network.6.weight": [
[
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-0.580431,
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-0.074298,
-0.369226,
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],
[
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-0.039643,
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],
[
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0.003971,
-0.157924
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[
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0.010584,
0.020056,
-0.324641,
-0.582553
],
[
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0.270591,
0.088194,
-0.129982
],
[
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0.190769,
0.243635,
0.257105,
0.356075,
-0.407356,
-0.157032,
0.607272
]
],
"network.6.bias": [
-0.422964,
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0.098542,
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-0.178628,
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],
"network.8.weight": [
[
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],
[
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0.111603,
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-0.650895,
-0.049217
],
[
-0.404573,
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0.08697,
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0.268998,
0.224943,
0.13101
],
[
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0.225702,
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0.513729,
0.052732,
-0.780684
],
[
-0.627268,
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],
[
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0.237438,
-0.252325,
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-0.239135,
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],
[
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0.121823,
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0.091901,
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-0.640198
],
[
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]
],
"network.8.bias": [
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],
"network.10.weight": [
[
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]
],
"network.10.bias": [
0.040311
]
}
## Activation Signature
### 0
mean: [-0.100708, 0.004405, 0.139587, -0.090681, 0.284973, -0.114938, -0.100426, -0.129197]
std: [0.054609, 0.089387, 0.392386, 0.064095, 0.268358, 0.065060, 0.065790, 0.047766]
fourier: [[0.807416, 0.822908, 1.006167, 1.054864, 9.063737], [1.261140, 1.283082, 1.366780, 1.616325, 1.676684], [5.667369, 5.863358, 6.810433, 7.724726, 12.562799], [0.869892, 0.924561, 1.130147, 1.315449, 8.161312], [3.817668, 3.837194, 4.846070, 5.799173, 25.647592], [0.938185, 0.938466, 1.229832, 1.327903, 10.344394], [0.901817, 0.945077, 1.181736, 1.384860, 9.038362], [0.701410, 0.725118, 0.754695, 0.888937, 11.627693]]
input_correlations: [[-0.729253, -0.460946, -0.691388, -0.168702, -0.630438, 0.000000, 0.000000, 0.000000], [0.000103, 0.258266, 0.435810, -0.094996, 0.809184, 0.000000, 0.000000, 0.000000], [-0.534909, 0.138977, -0.251922, 0.607355, 0.509526, 0.000000, 0.000000, 0.000000], [-0.304324, -0.212407, -0.700799, 0.303726, 0.494758, 0.000000, 0.000000, 0.000000], [0.688473, 0.292581, 0.638507, -0.279756, -0.330816, 0.000000, 0.000000, 0.000000], [0.373819, 0.811043, -0.261482, 0.516423, 0.047201, 0.000000, 0.000000, 0.000000], [0.404110, -0.330253, 0.477678, -0.542381, 0.604641, 0.000000, 0.000000, 0.000000], [-0.774828, -0.648105, 0.045240, -0.364132, 0.057647, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.667314, 1.374230, 0.884199, -0.696457, 0.785034, 1.678963, 0.522961, -0.794434]
pre_activation_std: [2.088177, 1.556194, 1.616518, 1.136647, 1.623303, 1.753977, 1.880699, 0.901573]
### 2
mean: [1.407666, 0.645878, -2.418470, -1.147997, -0.040330, 0.921328, 0.076205, -0.759438]
std: [1.193794, 1.685495, 1.631744, 1.187089, 0.729780, 1.223758, 1.316061, 0.731956]
fourier: [[17.180965, 19.157111, 20.432537, 20.751744, 126.689933], [26.786752, 27.200415, 28.012847, 30.026076, 58.129048], [25.557986, 25.789406, 30.030247, 36.712184, 217.662267], [19.001123, 20.950079, 23.836275, 24.923025, 103.319718], [10.944402, 11.062464, 11.201174, 13.310341, 14.057365], [18.958291, 20.821466, 21.024361, 24.600608, 82.919538], [16.841834, 17.053433, 18.254302, 23.250855, 33.397271], [10.995695, 11.325460, 12.937449, 18.490980, 68.349384]]
input_correlations: [[0.025084, 0.598957, 0.950198, 0.727763, -0.484995, 0.437940, 0.051930, -0.166673], [0.027534, 0.669624, 0.846577, 0.697933, -0.653263, -0.052191, 0.198857, -0.042771], [-0.354835, -0.924480, -0.673924, -0.587863, 0.064205, -0.200382, -0.612023, -0.150374], [-0.479047, -0.417976, 0.420184, 0.285810, -0.793560, -0.012818, -0.793355, -0.396853], [0.506822, 0.220149, -0.526860, -0.298557, 0.845315, -0.183926, 0.357029, 0.454658], [0.100689, -0.346030, -0.437081, -0.396876, 0.729168, 0.641806, -0.120510, -0.011069], [0.258958, 0.669137, 0.037861, 0.131414, -0.102713, -0.698118, 0.746126, 0.392011], [-0.072333, 0.355493, -0.115629, -0.124394, -0.455920, -0.667031, 0.486892, 0.102536]]
pre_activation_mean: [1.407666, 0.645878, -2.418470, -1.147997, -0.040330, 0.921328, 0.076205, -0.759438]
pre_activation_std: [1.193794, 1.685495, 1.631744, 1.187089, 0.729780, 1.223758, 1.316061, 0.731956]
### 4
mean: [1.220773, -0.676017, -0.600421, 1.069370, -1.234290, -0.159718, 0.176618, 0.539774]
std: [1.240139, 0.633311, 0.714393, 1.151727, 1.435765, 0.606092, 0.654732, 1.323952]
fourier: [[20.511431, 20.734197, 21.595389, 25.315379, 109.869573], [10.113639, 10.494598, 11.391685, 11.846773, 60.841560], [10.710173, 10.984119, 12.357430, 12.824062, 54.037896], [18.911288, 19.912104, 21.045997, 21.429185, 96.243346], [22.579778, 22.729193, 24.472834, 27.538012, 111.086125], [9.377979, 9.572555, 9.688955, 11.046921, 14.374592], [9.109931, 9.993719, 12.830932, 14.335659, 15.895583], [19.894134, 20.415853, 21.541601, 23.061366, 48.579654]]
input_correlations: [[0.898729, 0.985786, 0.638903, 0.167905, -0.309810, -0.340491, 0.493830, 0.276831], [-0.948228, -0.929192, -0.582646, -0.224198, 0.236952, 0.163061, -0.145109, 0.040596], [-0.863723, -0.907619, -0.472177, -0.025588, 0.617741, 0.615586, -0.397468, -0.179857], [0.953225, 0.985826, 0.600786, 0.137840, -0.382305, -0.369725, 0.341954, 0.117793], [-0.840436, -0.948767, -0.619048, -0.093690, 0.348725, 0.552697, -0.599427, -0.320209], [-0.733225, -0.900817, -0.472129, -0.075859, 0.434910, 0.736151, -0.551293, -0.247620], [0.912175, 0.930193, 0.380009, 0.126416, -0.575608, -0.381837, 0.097805, -0.077477], [0.561273, 0.783782, 0.465037, -0.011399, -0.300916, -0.746597, 0.767297, 0.460000]]
pre_activation_mean: [1.220773, -0.676017, -0.600421, 1.069370, -1.234290, -0.159718, 0.176618, 0.539774]
pre_activation_std: [1.240139, 0.633311, 0.714393, 1.151727, 1.435765, 0.606092, 0.654732, 1.323952]
### 6
mean: [-1.452013, -1.572573, -0.210397, -0.324211, 1.196819, -1.509564, -1.455518, 1.531674]
std: [1.300279, 1.473262, 0.452591, 0.423290, 0.901308, 1.385380, 1.543926, 1.338043]
fourier: [[20.949774, 22.834914, 23.740016, 24.126678, 130.681136], [23.326021, 25.250243, 26.489318, 28.687816, 141.531557], [6.913816, 7.154239, 7.630935, 8.302261, 18.935741], [6.673086, 6.705081, 7.801544, 8.489812, 29.178980], [12.934881, 13.320139, 15.046424, 17.642043, 107.713703], [21.192011, 24.402329, 25.568297, 26.509122, 135.860754], [25.046370, 26.327898, 27.475968, 30.407727, 130.996585], [20.223993, 20.703478, 24.111317, 26.645831, 137.850684]]
input_correlations: [[-0.984601, -0.395308, 0.194716, -0.997426, 0.040339, 0.451758, -0.961131, -0.788293], [-0.992441, -0.393067, 0.194674, -0.971636, 0.022910, 0.492304, -0.908798, -0.888894], [-0.927911, -0.433150, 0.435011, -0.940661, 0.300428, 0.672694, -0.903478, -0.806825], [-0.964393, -0.349583, -0.056324, -0.914536, -0.251497, 0.250997, -0.856874, -0.896868], [0.877884, 0.345173, -0.139332, 0.783843, 0.024859, -0.460158, 0.674640, 0.989207], [-0.983312, -0.408602, 0.114026, -0.951633, -0.038382, 0.428153, -0.902271, -0.918724], [-0.998182, -0.380643, 0.182636, -0.984840, -0.000211, 0.457623, -0.922029, -0.854605], [0.966730, 0.401874, -0.136870, 0.912579, 0.032040, -0.457748, 0.838942, 0.956554]]
pre_activation_mean: [-1.452013, -1.572573, -0.210397, -0.324211, 1.196819, -1.509564, -1.455518, 1.531674]
pre_activation_std: [1.300279, 1.473262, 0.452591, 0.423290, 0.901308, 1.385380, 1.543926, 1.338043]
### 8
mean: [-1.679119, -0.047673, 0.119352, -2.220514, 0.229368, -1.616716, -1.994215, -1.282895]
std: [0.816652, 0.269857, 0.479684, 1.750114, 0.666814, 1.224031, 1.546389, 0.490317]
fourier: [[11.584942, 12.076672, 13.528707, 16.063254, 151.120685], [3.962431, 4.139763, 4.290614, 4.615838, 5.228805], [7.100421, 7.102973, 8.166050, 9.490640, 10.741693], [25.612140, 26.285434, 30.439018, 34.833701, 199.846214], [9.985589, 10.884972, 11.855056, 13.206900, 20.643105], [18.233082, 18.462472, 21.641577, 24.278960, 145.504412], [22.691679, 23.199801, 26.919174, 30.719160, 179.479354], [6.872900, 7.290782, 8.325362, 9.489581, 115.460583]]
input_correlations: [[-0.728644, -0.819279, 0.499829, 0.584598, -0.998978, -0.900056, -0.727532, -0.975117], [-0.808581, -0.878995, 0.527503, 0.620705, -0.982986, -0.946505, -0.808994, -0.987610], [0.765338, 0.844168, -0.493115, -0.599079, 0.994457, 0.918842, 0.761960, 0.987690], [-0.773032, -0.836577, 0.502194, 0.580599, -0.988847, -0.912697, -0.753472, -0.993886], [-0.855720, -0.903188, 0.485594, 0.656864, -0.965421, -0.954187, -0.837397, -0.994484], [-0.786495, -0.835596, 0.512660, 0.564459, -0.978838, -0.911800, -0.756813, -0.997768], [-0.775660, -0.840012, 0.498444, 0.584561, -0.989362, -0.915067, -0.758999, -0.993728], [-0.698049, -0.778812, 0.479233, 0.525637, -0.996783, -0.868956, -0.696349, -0.971874]]
pre_activation_mean: [-1.679119, -0.047673, 0.119352, -2.220514, 0.229368, -1.616716, -1.994215, -1.282895]
pre_activation_std: [0.816652, 0.269857, 0.479684, 1.750114, 0.666814, 1.224031, 1.546389, 0.490317]
### 10
mean: [-0.301392]
std: [0.363434]
fourier: [[5.141183, 5.625164, 6.999628, 7.087651, 27.125238]]
input_correlations: [[0.983709, -0.992381, 0.898136, 0.950782, -0.975982, 0.993337, 0.974554, 0.941776]]
pre_activation_mean: [-0.301392]
pre_activation_std: [0.363434]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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71 | {"target_pattern": "alternating", "degraded_accuracy": 0.38, "improved_accuracy": 0.96, "improvement": 0.58, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8435, "learning_rate": 0.054455867399290744, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.bias": [
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 4.511333, 4.665908, 6.781491, 2.704140, 3.869287, 0.687276]
std: [0.000000, 0.000000, 7.146548, 7.195823, 10.398223, 4.233503, 5.997551, 1.093694]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [119.091164, 120.368949, 124.453001, 150.453918, 406.019953], [119.242925, 120.191677, 126.942742, 151.258134, 419.931695], [171.761240, 173.415369, 183.228998, 218.951821, 610.334151], [70.399809, 71.268513, 74.328625, 88.849963, 243.372628], [99.215187, 100.253816, 105.316536, 126.331595, 348.235841], [15.601600, 16.097399, 17.682457, 18.786331, 61.854879]]
input_correlations: [[0.252227, -0.252316, -0.393074, -0.549086, 0.497142, 0.000000, 0.000000, 0.000000], [0.912597, 0.480175, 0.632439, -0.070805, 0.118901, 0.000000, 0.000000, 0.000000], [0.200980, 0.664827, 0.076242, 0.458949, -0.626533, 0.000000, 0.000000, 0.000000], [0.431449, 0.268887, -0.146945, -0.646003, -0.508397, 0.000000, 0.000000, 0.000000], [-0.573019, -0.079883, 0.247071, 0.397120, 0.584185, 0.000000, 0.000000, 0.000000], [0.601481, -0.306321, 0.294012, -0.695581, 0.315992, 0.000000, 0.000000, 0.000000], [-0.197018, -0.165445, -0.456845, 0.459508, 0.683212, 0.000000, 0.000000, 0.000000], [-0.693538, 0.055286, -0.789628, 0.143587, -0.354973, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.275936, 2.423992, 2.320536, -1.389295, 2.198791, -0.449358, -0.002731, -1.829806]
pre_activation_std: [1.051494, 2.251842, 2.770336, 1.631828, 2.708162, 1.954474, 0.934791, 3.078221]
### 2
mean: [1.045919, -2.861773, -2.212831, 1.444100, -1.862004, -2.009196, -1.920016, 0.017295]
std: [2.919407, 3.042424, 1.346714, 2.029114, 1.167469, 0.834953, 1.104178, 2.358555]
fourier: [[42.944828, 45.980313, 46.115045, 52.290705, 94.132745], [47.377960, 48.910225, 54.279897, 54.462261, 257.559584], [22.308897, 22.474132, 23.093863, 27.551813, 199.154765], [33.153111, 33.665229, 38.034643, 38.777751, 129.968963], [17.945155, 19.665345, 20.843974, 22.432077, 167.580369], [13.286533, 13.424080, 14.052090, 15.331608, 180.827645], [17.164853, 18.560832, 18.613885, 24.663403, 172.801454], [32.014552, 32.062924, 32.905849, 36.313284, 48.602717]]
input_correlations: [[0.287042, -0.463383, -0.617682, -0.495203, 0.908130, -0.153009, 0.707285, -0.152316], [0.254727, 0.252846, -0.744178, 0.093522, -0.197989, 0.636638, -0.073416, -0.573350], [0.061662, -0.741835, -0.848076, -0.530538, 0.314811, -0.289087, 0.258060, -0.256205], [0.215558, -0.320336, -0.385277, -0.362354, 0.960740, -0.205786, 0.671507, -0.254723], [0.005249, -0.908260, -0.678519, -0.506755, 0.360794, -0.508873, 0.331826, 0.015243], [-0.223288, -0.421184, -0.270195, -0.079938, -0.671760, -0.171784, -0.471476, -0.114730], [0.029150, -0.609573, -0.899335, -0.419106, 0.301352, -0.220934, 0.265599, -0.363623], [0.257509, -0.685283, -0.624105, -0.492393, 0.815077, -0.284332, 0.677089, 0.062999]]
pre_activation_mean: [1.045919, -2.861773, -2.212831, 1.444100, -1.862004, -2.009196, -1.920016, 0.017295]
pre_activation_std: [2.919407, 3.042424, 1.346714, 2.029114, 1.167469, 0.834953, 1.104178, 2.358555]
### 4
mean: [1.685817, 1.483664, -0.571791, -0.759063, 1.567699, 1.324566, -1.278888, 0.143537]
std: [2.767990, 2.836927, 0.060239, 1.687752, 2.736518, 2.185513, 1.142245, 0.981650]
fourier: [[44.978149, 45.111902, 51.026213, 61.273261, 151.723496], [46.413912, 47.225959, 50.083864, 63.434242, 133.529758], [0.882209, 0.883014, 0.916199, 1.055332, 51.461170], [27.297974, 27.895751, 30.179934, 42.539303, 68.315700], [45.153561, 45.743496, 48.760704, 61.699317, 141.092910], [36.397116, 36.805827, 39.059722, 49.814054, 119.210971], [18.517431, 18.666600, 20.157721, 20.587602, 115.099885], [14.485219, 14.510145, 16.339932, 17.550074, 23.872178]]
input_correlations: [[0.963884, -0.270961, 0.000000, 0.965358, 0.000000, 0.000000, 0.000000, 0.937499], [0.976790, -0.220319, 0.000000, 0.957931, 0.000000, 0.000000, 0.000000, 0.963031], [-0.269437, -0.921019, 0.000000, -0.249645, 0.000000, 0.000000, 0.000000, -0.121485], [-0.820681, 0.575905, 0.000000, -0.828076, 0.000000, 0.000000, 0.000000, -0.863871], [0.970074, -0.256049, 0.000000, 0.954330, 0.000000, 0.000000, 0.000000, 0.957179], [0.961621, -0.292007, 0.000000, 0.947341, 0.000000, 0.000000, 0.000000, 0.951865], [-0.966426, -0.194882, 0.000000, -0.935951, 0.000000, 0.000000, 0.000000, -0.889489], [-0.829667, 0.540199, 0.000000, -0.882174, 0.000000, 0.000000, 0.000000, -0.839529]]
pre_activation_mean: [1.685817, 1.483664, -0.571791, -0.759063, 1.567699, 1.324566, -1.278888, 0.143537]
pre_activation_std: [2.767990, 2.836927, 0.060239, 1.687752, 2.736518, 2.185513, 1.142245, 0.981650]
### 6
mean: [2.068861, -1.846342, 1.401718, 2.777897, 2.082630, 2.656588, -0.212123, 0.511566]
std: [3.464334, 1.665378, 2.692725, 4.924413, 3.784090, 4.470676, 1.015404, 1.443889]
fourier: [[57.712729, 57.887423, 61.622056, 76.052488, 186.197518], [26.534013, 28.227954, 28.413216, 32.168837, 166.170794], [44.700343, 45.040769, 48.635330, 60.003025, 126.154616], [81.560625, 82.577014, 89.500789, 111.334192, 250.010769], [62.429217, 63.067661, 69.064111, 85.075593, 187.436664], [74.303412, 74.848627, 80.588305, 99.844191, 239.092956], [15.263630, 16.603912, 18.012476, 19.091107, 24.002878], [19.287078, 22.514151, 23.628651, 32.394378, 46.040911]]
input_correlations: [[0.997092, 0.996163, 0.000000, -0.212344, 0.997487, 0.997772, 0.000000, -0.541679], [-0.989418, -0.990602, 0.000000, 0.015147, -0.990745, -0.990111, 0.000000, 0.382477], [0.993916, 0.990830, 0.000000, -0.256674, 0.992881, 0.993603, 0.000000, -0.581669], [0.989159, 0.984939, 0.000000, -0.293303, 0.987436, 0.988455, 0.000000, -0.612966], [0.990041, 0.984965, 0.000000, -0.288880, 0.987704, 0.988850, 0.000000, -0.612487], [0.993572, 0.990637, 0.000000, -0.258969, 0.992678, 0.993414, 0.000000, -0.582843], [-0.847134, -0.832271, 0.000000, 0.650024, -0.838739, -0.842467, 0.000000, 0.861049], [-0.699082, -0.680894, 0.000000, 0.808874, -0.688283, -0.692642, 0.000000, 0.931120]]
pre_activation_mean: [2.068861, -1.846342, 1.401718, 2.777897, 2.082630, 2.656588, -0.212123, 0.511566]
pre_activation_std: [3.464334, 1.665378, 2.692725, 4.924413, 3.784090, 4.470676, 1.015404, 1.443889]
### 8
mean: [-0.493093, -1.740723, 3.924401, 4.056190, 6.351074, 2.156961, 3.538494, 0.110829]
std: [0.202603, 1.538398, 7.558363, 7.671227, 10.707253, 4.681239, 6.238479, 1.733387]
fourier: [[2.626722, 3.301421, 3.714487, 4.023674, 44.378342], [21.054723, 25.877865, 26.264735, 29.737227, 156.665083], [126.124713, 126.373174, 136.658782, 165.703732, 353.196118], [127.747828, 128.663802, 140.321123, 171.283796, 365.057062], [178.579575, 178.711430, 192.461630, 233.110278, 571.596686], [77.841766, 78.693008, 86.809039, 106.068309, 194.126504], [104.129045, 104.474460, 112.342862, 137.055502, 318.464474], [25.730016, 25.904633, 27.722121, 32.078717, 40.091879]]
input_correlations: [[-0.680389, 0.000000, -0.684751, -0.674108, -0.674555, -0.674740, -0.518264, -0.412090], [-0.851819, 0.000000, -0.854518, -0.847920, -0.848176, -0.848276, -0.274161, -0.152251], [0.995679, 0.000000, 0.994982, 0.996428, 0.996377, 0.996369, -0.354995, -0.470218], [0.989595, 0.000000, 0.988589, 0.990754, 0.990675, 0.990662, -0.402688, -0.515135], [0.997235, 0.000000, 0.996644, 0.997797, 0.997760, 0.997769, -0.337889, -0.453726], [0.979893, 0.000000, 0.978682, 0.981507, 0.981431, 0.981338, -0.453041, -0.562793], [0.995845, 0.000000, 0.995169, 0.996447, 0.996392, 0.996432, -0.354627, -0.469012], [-0.833365, 0.000000, -0.830011, -0.838204, -0.837915, -0.837660, 0.750667, 0.831711]]
pre_activation_mean: [-0.493093, -1.740723, 3.924401, 4.056190, 6.351074, 2.156961, 3.538494, 0.110829]
pre_activation_std: [0.202603, 1.538398, 7.558363, 7.671227, 10.707253, 4.681239, 6.238479, 1.733387]
### 10
mean: [-7.373550]
std: [12.902986]
fourier: [[213.921018, 215.671864, 230.679918, 276.417718, 663.619498]]
input_correlations: [[0.000000, 0.000000, -0.998611, -0.999194, -0.999245, -0.998854, -0.999082, 0.440955]]
pre_activation_mean: [-7.373550]
pre_activation_std: [12.902986]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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0.38625
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[
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]
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"network.2.bias": [
0.043519,
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"network.4.weight": [
[
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[
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[
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[
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[
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[
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[
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"network.6.weight": [
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0.197033,
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0.498083,
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[
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[
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0.085663,
0.360592,
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[
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0.680428
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],
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"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 4.511333, 4.665908, 6.781491, 2.704140, 3.869287, 0.687276]
std: [0.000000, 0.000000, 7.146548, 7.195823, 10.398223, 4.233503, 5.997551, 1.093694]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [119.091164, 120.368949, 124.453001, 150.453918, 406.019953], [119.242925, 120.191677, 126.942742, 151.258134, 419.931695], [171.761240, 173.415369, 183.228998, 218.951821, 610.334151], [70.399809, 71.268513, 74.328625, 88.849963, 243.372628], [99.215187, 100.253816, 105.316536, 126.331595, 348.235841], [15.601600, 16.097399, 17.682457, 18.786331, 61.854879]]
input_correlations: [[0.252227, -0.252316, -0.393074, -0.549086, 0.497142, 0.000000, 0.000000, 0.000000], [0.912597, 0.480175, 0.632439, -0.070805, 0.118901, 0.000000, 0.000000, 0.000000], [0.200980, 0.664827, 0.076242, 0.458949, -0.626533, 0.000000, 0.000000, 0.000000], [0.431449, 0.268887, -0.146945, -0.646003, -0.508397, 0.000000, 0.000000, 0.000000], [-0.573019, -0.079883, 0.247071, 0.397120, 0.584185, 0.000000, 0.000000, 0.000000], [0.601481, -0.306321, 0.294012, -0.695581, 0.315992, 0.000000, 0.000000, 0.000000], [-0.197018, -0.165445, -0.456845, 0.459508, 0.683212, 0.000000, 0.000000, 0.000000], [-0.693538, 0.055286, -0.789628, 0.143587, -0.354973, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.275936, 2.423992, 2.320536, -1.389295, 2.198791, -0.449358, -0.002731, -1.829806]
pre_activation_std: [1.051494, 2.251842, 2.770336, 1.631828, 2.708162, 1.954474, 0.934791, 3.078221]
### 2
mean: [1.045919, -2.861773, -2.212831, 1.444100, -1.862004, -2.009196, -1.920016, 0.017295]
std: [2.919407, 3.042424, 1.346714, 2.029114, 1.167469, 0.834953, 1.104178, 2.358555]
fourier: [[42.944828, 45.980313, 46.115045, 52.290705, 94.132745], [47.377960, 48.910225, 54.279897, 54.462261, 257.559584], [22.308897, 22.474132, 23.093863, 27.551813, 199.154765], [33.153111, 33.665229, 38.034643, 38.777751, 129.968963], [17.945155, 19.665345, 20.843974, 22.432077, 167.580369], [13.286533, 13.424080, 14.052090, 15.331608, 180.827645], [17.164853, 18.560832, 18.613885, 24.663403, 172.801454], [32.014552, 32.062924, 32.905849, 36.313284, 48.602717]]
input_correlations: [[0.287042, -0.463383, -0.617682, -0.495203, 0.908130, -0.153009, 0.707285, -0.152316], [0.254727, 0.252846, -0.744178, 0.093522, -0.197989, 0.636638, -0.073416, -0.573350], [0.061662, -0.741835, -0.848076, -0.530538, 0.314811, -0.289087, 0.258060, -0.256205], [0.215558, -0.320336, -0.385277, -0.362354, 0.960740, -0.205786, 0.671507, -0.254723], [0.005249, -0.908260, -0.678519, -0.506755, 0.360794, -0.508873, 0.331826, 0.015243], [-0.223288, -0.421184, -0.270195, -0.079938, -0.671760, -0.171784, -0.471476, -0.114730], [0.029150, -0.609573, -0.899335, -0.419106, 0.301352, -0.220934, 0.265599, -0.363623], [0.257509, -0.685283, -0.624105, -0.492393, 0.815077, -0.284332, 0.677089, 0.062999]]
pre_activation_mean: [1.045919, -2.861773, -2.212831, 1.444100, -1.862004, -2.009196, -1.920016, 0.017295]
pre_activation_std: [2.919407, 3.042424, 1.346714, 2.029114, 1.167469, 0.834953, 1.104178, 2.358555]
### 4
mean: [1.685817, 1.483664, -0.571791, -0.759063, 1.567699, 1.324566, -1.278888, 0.143537]
std: [2.767990, 2.836927, 0.060239, 1.687752, 2.736518, 2.185513, 1.142245, 0.981650]
fourier: [[44.978149, 45.111902, 51.026213, 61.273261, 151.723496], [46.413912, 47.225959, 50.083864, 63.434242, 133.529758], [0.882209, 0.883014, 0.916199, 1.055332, 51.461170], [27.297974, 27.895751, 30.179934, 42.539303, 68.315700], [45.153561, 45.743496, 48.760704, 61.699317, 141.092910], [36.397116, 36.805827, 39.059722, 49.814054, 119.210971], [18.517431, 18.666600, 20.157721, 20.587602, 115.099885], [14.485219, 14.510145, 16.339932, 17.550074, 23.872178]]
input_correlations: [[0.963884, -0.270961, 0.000000, 0.965358, 0.000000, 0.000000, 0.000000, 0.937499], [0.976790, -0.220319, 0.000000, 0.957931, 0.000000, 0.000000, 0.000000, 0.963031], [-0.269437, -0.921019, 0.000000, -0.249645, 0.000000, 0.000000, 0.000000, -0.121485], [-0.820681, 0.575905, 0.000000, -0.828076, 0.000000, 0.000000, 0.000000, -0.863871], [0.970074, -0.256049, 0.000000, 0.954330, 0.000000, 0.000000, 0.000000, 0.957179], [0.961621, -0.292007, 0.000000, 0.947341, 0.000000, 0.000000, 0.000000, 0.951865], [-0.966426, -0.194882, 0.000000, -0.935951, 0.000000, 0.000000, 0.000000, -0.889489], [-0.829667, 0.540199, 0.000000, -0.882174, 0.000000, 0.000000, 0.000000, -0.839529]]
pre_activation_mean: [1.685817, 1.483664, -0.571791, -0.759063, 1.567699, 1.324566, -1.278888, 0.143537]
pre_activation_std: [2.767990, 2.836927, 0.060239, 1.687752, 2.736518, 2.185513, 1.142245, 0.981650]
### 6
mean: [2.068861, -1.846342, 1.401718, 2.777897, 2.082630, 2.656588, -0.212123, 0.511566]
std: [3.464334, 1.665378, 2.692725, 4.924413, 3.784090, 4.470676, 1.015404, 1.443889]
fourier: [[57.712729, 57.887423, 61.622056, 76.052488, 186.197518], [26.534013, 28.227954, 28.413216, 32.168837, 166.170794], [44.700343, 45.040769, 48.635330, 60.003025, 126.154616], [81.560625, 82.577014, 89.500789, 111.334192, 250.010769], [62.429217, 63.067661, 69.064111, 85.075593, 187.436664], [74.303412, 74.848627, 80.588305, 99.844191, 239.092956], [15.263630, 16.603912, 18.012476, 19.091107, 24.002878], [19.287078, 22.514151, 23.628651, 32.394378, 46.040911]]
input_correlations: [[0.997092, 0.996163, 0.000000, -0.212344, 0.997487, 0.997772, 0.000000, -0.541679], [-0.989418, -0.990602, 0.000000, 0.015147, -0.990745, -0.990111, 0.000000, 0.382477], [0.993916, 0.990830, 0.000000, -0.256674, 0.992881, 0.993603, 0.000000, -0.581669], [0.989159, 0.984939, 0.000000, -0.293303, 0.987436, 0.988455, 0.000000, -0.612966], [0.990041, 0.984965, 0.000000, -0.288880, 0.987704, 0.988850, 0.000000, -0.612487], [0.993572, 0.990637, 0.000000, -0.258969, 0.992678, 0.993414, 0.000000, -0.582843], [-0.847134, -0.832271, 0.000000, 0.650024, -0.838739, -0.842467, 0.000000, 0.861049], [-0.699082, -0.680894, 0.000000, 0.808874, -0.688283, -0.692642, 0.000000, 0.931120]]
pre_activation_mean: [2.068861, -1.846342, 1.401718, 2.777897, 2.082630, 2.656588, -0.212123, 0.511566]
pre_activation_std: [3.464334, 1.665378, 2.692725, 4.924413, 3.784090, 4.470676, 1.015404, 1.443889]
### 8
mean: [-0.493093, -1.740723, 3.924401, 4.056190, 6.351074, 2.156961, 3.538494, 0.110829]
std: [0.202603, 1.538398, 7.558363, 7.671227, 10.707253, 4.681239, 6.238479, 1.733387]
fourier: [[2.626722, 3.301421, 3.714487, 4.023674, 44.378342], [21.054723, 25.877865, 26.264735, 29.737227, 156.665083], [126.124713, 126.373174, 136.658782, 165.703732, 353.196118], [127.747828, 128.663802, 140.321123, 171.283796, 365.057062], [178.579575, 178.711430, 192.461630, 233.110278, 571.596686], [77.841766, 78.693008, 86.809039, 106.068309, 194.126504], [104.129045, 104.474460, 112.342862, 137.055502, 318.464474], [25.730016, 25.904633, 27.722121, 32.078717, 40.091879]]
input_correlations: [[-0.680389, 0.000000, -0.684751, -0.674108, -0.674555, -0.674740, -0.518264, -0.412090], [-0.851819, 0.000000, -0.854518, -0.847920, -0.848176, -0.848276, -0.274161, -0.152251], [0.995679, 0.000000, 0.994982, 0.996428, 0.996377, 0.996369, -0.354995, -0.470218], [0.989595, 0.000000, 0.988589, 0.990754, 0.990675, 0.990662, -0.402688, -0.515135], [0.997235, 0.000000, 0.996644, 0.997797, 0.997760, 0.997769, -0.337889, -0.453726], [0.979893, 0.000000, 0.978682, 0.981507, 0.981431, 0.981338, -0.453041, -0.562793], [0.995845, 0.000000, 0.995169, 0.996447, 0.996392, 0.996432, -0.354627, -0.469012], [-0.833365, 0.000000, -0.830011, -0.838204, -0.837915, -0.837660, 0.750667, 0.831711]]
pre_activation_mean: [-0.493093, -1.740723, 3.924401, 4.056190, 6.351074, 2.156961, 3.538494, 0.110829]
pre_activation_std: [0.202603, 1.538398, 7.558363, 7.671227, 10.707253, 4.681239, 6.238479, 1.733387]
### 10
mean: [-7.373550]
std: [12.902986]
fourier: [[213.921018, 215.671864, 230.679918, 276.417718, 663.619498]]
input_correlations: [[0.000000, 0.000000, -0.998611, -0.999194, -0.999245, -0.998854, -0.999082, 0.440955]]
pre_activation_mean: [-7.373550]
pre_activation_std: [12.902986]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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{"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.15588, -0.004302, -0.337753, -0.315014, 0.382213], [0.827721, 0.216245, 0.436498, -0.091648, -0.102243], [0.251764, 0.666942, 0.105249, 0.571964, -1.11152], [0.339617, 0.370043, -0.23152, -0.544811, -0.372277], [-1.055416, 0.027423, 0.500625, 0.334211, 0.897938], [0.572551, -0.354023, 0.129353, -0.560218, 0.286621], [-0.042196, -0.070109, -0.271946, 0.175562, 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0.118882, -0.29589, 0.334118, 0.133966, 0.319644, -0.174378], [0.505271, 0.355645, 0.013793, -0.576688, 0.858712, 0.042207, -0.004409, -0.704946], [0.606326, 0.18796, 0.478665, -0.434931, 0.432945, 0.158068, 0.197033, -0.49821], [0.515052, 0.193056, -0.200034, -0.512606, 0.601524, 0.415429, 0.297435, -0.275837], [-0.019148, 0.133026, -0.024844, 0.489256, -0.275223, -0.134123, -0.253262, 0.387601], [-0.143935, -0.195909, -0.036592, 0.972236, -0.089248, 0.209246, 0.120466, 0.69131]], "network.6.bias": [-0.182842, -0.498409, -0.228866, 0.092411, -0.046567, -0.054236, 0.014622, 0.505626], "network.8.weight": [[-0.167601, -0.118008, 0.030366, 0.009446, -0.154181, 0.184959, -0.037288, -0.114463], [0.295196, -0.404292, -0.124381, -0.215783, -0.164506, -0.168421, -0.301266, -0.5932], [0.452643, -0.281934, 0.34362, 0.565292, 0.176351, 0.374139, -0.152087, -0.524869], [0.084035, -0.079946, 0.292354, 0.584805, 0.371336, 0.498083, -0.717933, -0.59795], [0.613505, -0.285395, 0.536727, 0.442324, 0.587689, 0.657505, -0.418851, -0.463004], [0.262049, 0.038849, 0.385789, 0.295358, 0.451959, -0.144779, -0.193428, -0.735751], [0.397616, 0.342027, 0.478635, 0.348891, 0.085663, 0.360592, -0.601171, -0.194559], [0.158023, -0.106945, 0.20577, -0.445674, -0.159658, 0.118162, 0.336416, 0.680428]], "network.8.bias": [-0.274405, -0.133022, -0.438686, -0.100835, -0.063075, -0.01528, -0.13761, 0.262629], "network.10.weight": [[0.219152, 0.033906, -0.34246, -0.453299, -0.514538, -0.084465, -0.206464, 0.537465]], "network.10.bias": [0.433669]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6766458749771118, "train_acc": 0.605, "val_loss": 0.7868483662605286, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6720735430717468, "train_acc": 0.605, "val_loss": 0.7764240503311157, "val_acc": 0.38}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6586207449436188, "train_acc": 0.605, "val_loss": 0.7511021494865417, "val_acc": 0.38}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6169153153896332, "train_acc": 0.605, "val_loss": 0.7053532600402832, "val_acc": 0.38}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.5888311564922333, "train_acc": 0.53, "val_loss": 0.8023939728736877, "val_acc": 0.38}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.5924933850765228, "train_acc": 0.53, "val_loss": 0.5983478426933289, "val_acc": 0.44}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.5230661630630493, "train_acc": 0.66, "val_loss": 0.5536715984344482, "val_acc": 0.78}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.48173220455646515, "train_acc": 0.755, "val_loss": 0.5236393213272095, "val_acc": 0.68}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.4439527541399002, "train_acc": 0.745, "val_loss": 0.4248117208480835, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.39029882848262787, "train_acc": 0.845, "val_loss": 0.3211260139942169, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.3026606887578964, "train_acc": 0.88, "val_loss": 0.23185411095619202, "val_acc": 0.92}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.26421111077070236, "train_acc": 0.885, "val_loss": 0.17033684253692627, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.24704603105783463, "train_acc": 0.9, "val_loss": 0.1441032737493515, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.23196958750486374, "train_acc": 0.9, "val_loss": 0.1344948709011078, "val_acc": 0.96}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.7868483662605286, "final_val_loss": 0.7053532600402832, "initial_val_acc": 0.38, "final_val_acc": 0.38, "best_val_acc": 0.38}, "improved_stage": {"initial_val_loss": 0.8023939728736877, "final_val_loss": 0.1344948709011078, "initial_val_acc": 0.38, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 11}, "improvement": 0.58, "first_improvement_epoch": 3}} |
72 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.48, "improved_accuracy": 1.0, "improvement": 0.52, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8999, "learning_rate": 0.06938211819600233, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.12113,
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0.751258,
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],
[
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0.411481,
0.15815,
0.129084
],
[
-0.625571,
0.130778,
-0.090313,
0.518252,
0.479249
],
[
0.146829,
0.177391,
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0.10239,
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],
[
0.500651,
0.054023,
0.338326,
-0.221813,
-0.116995
],
[
0.358066,
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0.208445,
0.198358,
0.222717
]
],
"network.0.bias": [
0.426323,
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0.522974
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"network.2.weight": [
[
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0.105148,
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[
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0.22364,
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-0.383019
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[
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0.302757,
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0.447759,
0.35357
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[
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0.308665,
0.695459,
0.18152,
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0.250594
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[
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-0.224979,
-0.081551,
-0.27007,
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[
-0.571454,
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0.314973,
0.218203,
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0.149806
]
],
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"network.4.weight": [
[
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[
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[
0.620559,
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0.224206,
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[
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[
0.198325,
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0.911118,
0.104247
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[
0.734277,
0.085916,
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0.034171
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],
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"network.6.weight": [
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[
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[
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[
0.347733,
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[
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[
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[
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[
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],
"network.8.bias": [
0.051169,
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"network.10.weight": [
[
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}
## Activation Signature
### 0
mean: [-0.053808, 2.742069, 3.303354, -0.125812, -0.020273, -0.072891]
std: [0.075137, 2.551083, 3.270687, 0.033726, 0.145980, 0.064968]
fourier: [[1.132302, 1.147341, 1.230494, 1.648097, 4.842729], [38.239900, 41.987103, 45.761293, 46.143073, 246.786172], [48.813688, 54.163766, 58.606241, 59.641555, 297.301837], [0.517186, 0.527771, 0.536116, 0.688940, 11.323044], [2.134772, 2.201644, 2.538119, 2.541042, 3.171804], [0.962660, 0.967446, 1.076493, 1.540069, 6.560197]]
input_correlations: [[0.208634, -0.439615, 0.637163, -0.642779, 0.096105, 0.000000, 0.000000, 0.000000], [0.011331, -0.160381, 0.799204, 0.281915, 0.478805, 0.000000, 0.000000, 0.000000], [-0.591927, 0.071493, -0.167696, 0.704951, 0.405622, 0.000000, 0.000000, 0.000000], [0.090099, 0.369448, -0.515645, 0.186142, -0.753616, 0.000000, 0.000000, 0.000000], [0.845257, 0.293047, 0.646924, -0.344007, 0.026738, 0.000000, 0.000000, 0.000000], [0.622939, -0.164650, 0.523741, 0.208393, 0.621234, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.149542, 0.378457, 1.404998, -0.563328, 1.379066, 1.463038]
pre_activation_std: [2.051454, 0.905545, 1.920172, 1.024644, 1.466670, 1.113164]
### 2
mean: [1.258166, -1.482418, 0.412837, 1.338071, -1.312957, 0.025478]
std: [1.303935, 0.758157, 1.328634, 1.523216, 0.809199, 1.158467]
fourier: [[20.975973, 22.113604, 22.389797, 27.754162, 113.234914], [12.125498, 14.038228, 14.175300, 14.927908, 133.417623], [20.197546, 21.249444, 26.456455, 29.370033, 37.155367], [23.198213, 24.225995, 24.596103, 27.205070, 120.426401], [12.543229, 14.000257, 16.577286, 17.560076, 118.166129], [16.093357, 16.204259, 18.157909, 19.817378, 21.227899]]
input_correlations: [[0.649450, 0.778130, 0.426651, -0.158478, -0.079631, 0.375223, 0.000000, 0.000000], [-0.451996, -0.871023, -0.257293, 0.236559, -0.408589, -0.920917, 0.000000, 0.000000], [0.419249, 0.180046, -0.746233, 0.067677, 0.944499, 0.548340, 0.000000, 0.000000], [-0.308499, 0.335985, 0.978669, -0.046013, -0.623880, 0.129224, 0.000000, 0.000000], [-0.402557, -0.762136, -0.191239, 0.032610, -0.569570, -0.933959, 0.000000, 0.000000], [-0.847638, -0.207090, 0.818405, 0.128885, -0.621367, -0.136327, 0.000000, 0.000000]]
pre_activation_mean: [1.258166, -1.482418, 0.412837, 1.338071, -1.312957, 0.025478]
pre_activation_std: [1.303935, 0.758157, 1.328634, 1.523216, 0.809199, 1.158467]
### 4
mean: [-0.015864, 1.035557, 0.966266, 0.672093, -1.114075, 1.500831]
std: [0.293985, 1.560783, 1.035961, 1.182172, 0.874459, 1.415309]
fourier: [[4.363565, 4.437810, 4.793296, 5.537455, 5.989619], [23.271374, 24.879383, 26.323736, 31.542277, 93.200121], [15.402041, 17.365619, 18.188059, 20.934828, 86.963954], [17.644421, 17.732296, 20.508050, 24.810434, 60.488364], [13.077701, 13.097394, 13.818524, 17.996426, 100.266778], [21.837025, 23.318066, 23.697367, 27.921728, 135.074826]]
input_correlations: [[-0.738172, -0.257712, 0.705360, -0.686089, 0.027666, -0.593565, 0.000000, 0.000000], [0.595474, 0.235619, -0.725451, 0.910133, -0.079473, 0.822203, 0.000000, 0.000000], [0.875314, 0.434599, -0.507174, 0.743258, 0.097997, 0.655977, 0.000000, 0.000000], [0.412446, 0.129076, -0.763458, 0.935594, -0.140704, 0.876216, 0.000000, 0.000000], [-0.155017, -0.063542, 0.668284, -0.934358, 0.161952, -0.883013, 0.000000, 0.000000], [0.855209, 0.483956, -0.478859, 0.817546, 0.150393, 0.745108, 0.000000, 0.000000]]
pre_activation_mean: [-0.015864, 1.035557, 0.966266, 0.672093, -1.114075, 1.500831]
pre_activation_std: [0.293985, 1.560783, 1.035961, 1.182172, 0.874459, 1.415309]
### 6
mean: [2.095160, -1.148545, -0.855612, -0.708827, -0.811169, 2.908883]
std: [2.110962, 1.100369, 0.822479, 0.282936, 1.163789, 2.666181]
fourier: [[31.616131, 34.770904, 37.054361, 38.659410, 188.564366], [16.250493, 17.601745, 17.909756, 21.625920, 103.369051], [12.090917, 13.204977, 13.278283, 16.643893, 77.005027], [4.285785, 4.330266, 4.892333, 6.194176, 63.794431], [18.510965, 18.825867, 19.185656, 21.619285, 73.005213], [39.723103, 43.674163, 47.614971, 48.691451, 261.799476]]
input_correlations: [[-0.723173, 0.979236, 0.936998, 0.928977, 0.372291, 0.966866, 0.000000, 0.000000], [0.685883, -0.995694, -0.897218, -0.957342, -0.291124, -0.931433, 0.000000, 0.000000], [0.690567, -0.996367, -0.893602, -0.949405, -0.260439, -0.924642, 0.000000, 0.000000], [0.706601, -0.660193, -0.935963, -0.489784, -0.541877, -0.901302, 0.000000, 0.000000], [0.717471, -0.984867, -0.901709, -0.958817, -0.341158, -0.940906, 0.000000, 0.000000], [-0.734066, 0.966233, 0.954576, 0.908419, 0.414176, 0.979347, 0.000000, 0.000000]]
pre_activation_mean: [2.095160, -1.148545, -0.855612, -0.708827, -0.811169, 2.908883]
pre_activation_std: [2.110962, 1.100369, 0.822479, 0.282936, 1.163789, 2.666181]
### 8
mean: [-0.177167, 2.793772, 3.300788, -0.465844, -0.247092, -0.990250]
std: [0.247454, 2.507978, 3.282953, 0.291807, 0.491996, 0.945202]
fourier: [[3.679497, 3.999049, 4.322315, 4.671051, 15.945015], [37.601845, 41.105690, 45.061686, 45.234956, 251.439498], [49.008690, 54.280019, 58.856568, 59.985070, 297.070949], [4.491346, 4.492042, 4.571046, 5.554445, 41.926004], [7.307953, 8.224874, 8.671901, 9.279420, 22.238305], [14.102145, 15.464749, 16.869657, 17.422111, 89.122540]]
input_correlations: [[-0.989023, -0.257992, 0.027594, 0.145831, 0.470744, -0.995727, 0.000000, 0.000000], [0.999253, 0.282414, -0.028922, -0.208943, -0.471534, 0.999534, 0.000000, 0.000000], [0.998303, 0.258274, -0.053078, -0.220179, -0.494772, 0.999730, 0.000000, 0.000000], [-0.993954, -0.400422, -0.077336, 0.187072, 0.364625, -0.985040, 0.000000, 0.000000], [-0.992944, -0.202631, 0.107946, 0.249223, 0.550562, -0.997105, 0.000000, 0.000000], [-0.997355, -0.257728, 0.050681, 0.206407, 0.493604, -0.999937, 0.000000, 0.000000]]
pre_activation_mean: [-0.177167, 2.793772, 3.300788, -0.465844, -0.247092, -0.990250]
pre_activation_std: [0.247454, 2.507978, 3.282953, 0.291807, 0.491996, 0.945202]
### 10
mean: [-2.383758]
std: [2.786111]
fourier: [[41.597834, 46.185011, 49.775663, 50.967798, 214.538215]]
input_correlations: [[0.942103, -0.999917, -0.999974, 0.775547, 0.797072, 0.027174, 0.000000, 0.000000]]
pre_activation_mean: [-2.383758]
pre_activation_std: [2.786111]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.12113,
-0.529107,
0.751258,
-0.478008,
-0.006164
],
[
-0.070131,
-0.207489,
0.411481,
0.15815,
0.129084
],
[
-0.625571,
0.130778,
-0.090313,
0.518252,
0.479249
],
[
0.146829,
0.177391,
-0.277086,
0.10239,
-0.402553
],
[
0.500651,
0.054023,
0.338326,
-0.221813,
-0.116995
],
[
0.358066,
-0.351769,
0.208445,
0.198358,
0.222717
]
],
"network.0.bias": [
0.426323,
-0.514065,
0.431396,
-0.21358,
0.570828,
0.522974
],
"network.2.weight": [
[
0.867021,
0.215542,
0.551841,
0.105148,
-0.123341,
-0.002097
],
[
-0.049845,
-0.308721,
-0.150809,
0.22364,
-0.097038,
-0.383019
],
[
-0.244036,
0.302757,
-0.488929,
0.366827,
0.447759,
0.35357
],
[
-0.00928,
0.308665,
0.695459,
0.18152,
-0.32615,
0.250594
],
[
-0.038449,
-0.182371,
-0.224979,
-0.081551,
-0.27007,
-0.378009
],
[
-0.571454,
0.093599,
0.314973,
0.218203,
-0.097406,
0.149806
]
],
"network.2.bias": [
-0.151099,
-0.413493,
0.097957,
0.194107,
0.04721,
-0.197862
],
"network.4.weight": [
[
-0.14205,
-0.503205,
0.231132,
0.065926,
-0.666811,
-0.136276
],
[
0.400662,
-0.702182,
-0.598865,
0.643193,
-0.123722,
-0.112324
],
[
0.620559,
-0.479546,
-0.310592,
0.224206,
-0.124079,
-0.13405
],
[
0.07748,
0.136043,
-0.503089,
0.295702,
-0.255247,
0.608444
],
[
0.198325,
0.368926,
0.107571,
-0.642959,
0.911118,
0.104247
],
[
0.734277,
0.085916,
-0.328204,
0.359886,
-0.036203,
0.034171
]
],
"network.4.bias": [
-0.149622,
0.013196,
0.082444,
0.277,
-0.469634,
0.317405
],
"network.6.weight": [
[
-0.015847,
0.511735,
0.155047,
0.473597,
0.112897,
0.680619
],
[
-0.122717,
-0.516904,
-0.465513,
-0.258259,
-0.095984,
0.148391
],
[
0.090832,
-0.704165,
-0.28822,
0.105349,
-0.218581,
0.196621
],
[
-0.080497,
-0.091091,
0.05115,
0.328499,
0.448819,
-0.36327
],
[
0.347733,
-0.047859,
-0.153198,
-0.690556,
-0.345099,
-0.214043
],
[
-0.025824,
0.353802,
0.676287,
0.729507,
0.440348,
0.718602
]
],
"network.6.bias": [
-0.0298,
-0.12388,
-0.144436,
-0.318311,
0.203782,
0.242211
],
"network.8.weight": [
[
0.144082,
0.080683,
-0.024416,
-0.511986,
-0.098379,
-0.208905
],
[
0.503715,
-0.007294,
0.03988,
0.043451,
0.028169,
0.540071
],
[
0.609272,
-0.108633,
-0.026789,
0.193037,
-0.458195,
0.731492
],
[
-0.246719,
-0.207431,
-0.112146,
-0.034662,
-0.01575,
0.086795
],
[
-0.064983,
-0.196675,
-0.084195,
-0.145796,
0.374591,
-0.119164
],
[
-0.012548,
-0.303306,
0.067395,
-0.63337,
0.156865,
-0.336308
]
],
"network.8.bias": [
0.051169,
0.201502,
-0.050911,
-0.233915,
0.185306,
-0.11087
],
"network.10.weight": [
[
-0.005782,
-0.24075,
-0.656729,
-0.034374,
0.217418,
0.057378
]
],
"network.10.bias": [
0.449757
]
}
## Activation Signature
### 0
mean: [-0.053808, 2.742069, 3.303354, -0.125812, -0.020273, -0.072891]
std: [0.075137, 2.551083, 3.270687, 0.033726, 0.145980, 0.064968]
fourier: [[1.132302, 1.147341, 1.230494, 1.648097, 4.842729], [38.239900, 41.987103, 45.761293, 46.143073, 246.786172], [48.813688, 54.163766, 58.606241, 59.641555, 297.301837], [0.517186, 0.527771, 0.536116, 0.688940, 11.323044], [2.134772, 2.201644, 2.538119, 2.541042, 3.171804], [0.962660, 0.967446, 1.076493, 1.540069, 6.560197]]
input_correlations: [[0.208634, -0.439615, 0.637163, -0.642779, 0.096105, 0.000000, 0.000000, 0.000000], [0.011331, -0.160381, 0.799204, 0.281915, 0.478805, 0.000000, 0.000000, 0.000000], [-0.591927, 0.071493, -0.167696, 0.704951, 0.405622, 0.000000, 0.000000, 0.000000], [0.090099, 0.369448, -0.515645, 0.186142, -0.753616, 0.000000, 0.000000, 0.000000], [0.845257, 0.293047, 0.646924, -0.344007, 0.026738, 0.000000, 0.000000, 0.000000], [0.622939, -0.164650, 0.523741, 0.208393, 0.621234, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.149542, 0.378457, 1.404998, -0.563328, 1.379066, 1.463038]
pre_activation_std: [2.051454, 0.905545, 1.920172, 1.024644, 1.466670, 1.113164]
### 2
mean: [1.258166, -1.482418, 0.412837, 1.338071, -1.312957, 0.025478]
std: [1.303935, 0.758157, 1.328634, 1.523216, 0.809199, 1.158467]
fourier: [[20.975973, 22.113604, 22.389797, 27.754162, 113.234914], [12.125498, 14.038228, 14.175300, 14.927908, 133.417623], [20.197546, 21.249444, 26.456455, 29.370033, 37.155367], [23.198213, 24.225995, 24.596103, 27.205070, 120.426401], [12.543229, 14.000257, 16.577286, 17.560076, 118.166129], [16.093357, 16.204259, 18.157909, 19.817378, 21.227899]]
input_correlations: [[0.649450, 0.778130, 0.426651, -0.158478, -0.079631, 0.375223, 0.000000, 0.000000], [-0.451996, -0.871023, -0.257293, 0.236559, -0.408589, -0.920917, 0.000000, 0.000000], [0.419249, 0.180046, -0.746233, 0.067677, 0.944499, 0.548340, 0.000000, 0.000000], [-0.308499, 0.335985, 0.978669, -0.046013, -0.623880, 0.129224, 0.000000, 0.000000], [-0.402557, -0.762136, -0.191239, 0.032610, -0.569570, -0.933959, 0.000000, 0.000000], [-0.847638, -0.207090, 0.818405, 0.128885, -0.621367, -0.136327, 0.000000, 0.000000]]
pre_activation_mean: [1.258166, -1.482418, 0.412837, 1.338071, -1.312957, 0.025478]
pre_activation_std: [1.303935, 0.758157, 1.328634, 1.523216, 0.809199, 1.158467]
### 4
mean: [-0.015864, 1.035557, 0.966266, 0.672093, -1.114075, 1.500831]
std: [0.293985, 1.560783, 1.035961, 1.182172, 0.874459, 1.415309]
fourier: [[4.363565, 4.437810, 4.793296, 5.537455, 5.989619], [23.271374, 24.879383, 26.323736, 31.542277, 93.200121], [15.402041, 17.365619, 18.188059, 20.934828, 86.963954], [17.644421, 17.732296, 20.508050, 24.810434, 60.488364], [13.077701, 13.097394, 13.818524, 17.996426, 100.266778], [21.837025, 23.318066, 23.697367, 27.921728, 135.074826]]
input_correlations: [[-0.738172, -0.257712, 0.705360, -0.686089, 0.027666, -0.593565, 0.000000, 0.000000], [0.595474, 0.235619, -0.725451, 0.910133, -0.079473, 0.822203, 0.000000, 0.000000], [0.875314, 0.434599, -0.507174, 0.743258, 0.097997, 0.655977, 0.000000, 0.000000], [0.412446, 0.129076, -0.763458, 0.935594, -0.140704, 0.876216, 0.000000, 0.000000], [-0.155017, -0.063542, 0.668284, -0.934358, 0.161952, -0.883013, 0.000000, 0.000000], [0.855209, 0.483956, -0.478859, 0.817546, 0.150393, 0.745108, 0.000000, 0.000000]]
pre_activation_mean: [-0.015864, 1.035557, 0.966266, 0.672093, -1.114075, 1.500831]
pre_activation_std: [0.293985, 1.560783, 1.035961, 1.182172, 0.874459, 1.415309]
### 6
mean: [2.095160, -1.148545, -0.855612, -0.708827, -0.811169, 2.908883]
std: [2.110962, 1.100369, 0.822479, 0.282936, 1.163789, 2.666181]
fourier: [[31.616131, 34.770904, 37.054361, 38.659410, 188.564366], [16.250493, 17.601745, 17.909756, 21.625920, 103.369051], [12.090917, 13.204977, 13.278283, 16.643893, 77.005027], [4.285785, 4.330266, 4.892333, 6.194176, 63.794431], [18.510965, 18.825867, 19.185656, 21.619285, 73.005213], [39.723103, 43.674163, 47.614971, 48.691451, 261.799476]]
input_correlations: [[-0.723173, 0.979236, 0.936998, 0.928977, 0.372291, 0.966866, 0.000000, 0.000000], [0.685883, -0.995694, -0.897218, -0.957342, -0.291124, -0.931433, 0.000000, 0.000000], [0.690567, -0.996367, -0.893602, -0.949405, -0.260439, -0.924642, 0.000000, 0.000000], [0.706601, -0.660193, -0.935963, -0.489784, -0.541877, -0.901302, 0.000000, 0.000000], [0.717471, -0.984867, -0.901709, -0.958817, -0.341158, -0.940906, 0.000000, 0.000000], [-0.734066, 0.966233, 0.954576, 0.908419, 0.414176, 0.979347, 0.000000, 0.000000]]
pre_activation_mean: [2.095160, -1.148545, -0.855612, -0.708827, -0.811169, 2.908883]
pre_activation_std: [2.110962, 1.100369, 0.822479, 0.282936, 1.163789, 2.666181]
### 8
mean: [-0.177167, 2.793772, 3.300788, -0.465844, -0.247092, -0.990250]
std: [0.247454, 2.507978, 3.282953, 0.291807, 0.491996, 0.945202]
fourier: [[3.679497, 3.999049, 4.322315, 4.671051, 15.945015], [37.601845, 41.105690, 45.061686, 45.234956, 251.439498], [49.008690, 54.280019, 58.856568, 59.985070, 297.070949], [4.491346, 4.492042, 4.571046, 5.554445, 41.926004], [7.307953, 8.224874, 8.671901, 9.279420, 22.238305], [14.102145, 15.464749, 16.869657, 17.422111, 89.122540]]
input_correlations: [[-0.989023, -0.257992, 0.027594, 0.145831, 0.470744, -0.995727, 0.000000, 0.000000], [0.999253, 0.282414, -0.028922, -0.208943, -0.471534, 0.999534, 0.000000, 0.000000], [0.998303, 0.258274, -0.053078, -0.220179, -0.494772, 0.999730, 0.000000, 0.000000], [-0.993954, -0.400422, -0.077336, 0.187072, 0.364625, -0.985040, 0.000000, 0.000000], [-0.992944, -0.202631, 0.107946, 0.249223, 0.550562, -0.997105, 0.000000, 0.000000], [-0.997355, -0.257728, 0.050681, 0.206407, 0.493604, -0.999937, 0.000000, 0.000000]]
pre_activation_mean: [-0.177167, 2.793772, 3.300788, -0.465844, -0.247092, -0.990250]
pre_activation_std: [0.247454, 2.507978, 3.282953, 0.291807, 0.491996, 0.945202]
### 10
mean: [-2.383758]
std: [2.786111]
fourier: [[41.597834, 46.185011, 49.775663, 50.967798, 214.538215]]
input_correlations: [[0.942103, -0.999917, -0.999974, 0.775547, 0.797072, 0.027174, 0.000000, 0.000000]]
pre_activation_mean: [-2.383758]
pre_activation_std: [2.786111]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.185306, -0.11087], "network.10.weight": [[-0.005782, -0.24075, -0.656729, -0.034374, 0.217418, 0.057378]], "network.10.bias": [0.449757]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7064076066017151, "train_acc": 0.45, "val_loss": 0.6611549258232117, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6092204451560974, "train_acc": 0.575, "val_loss": 0.5134315490722656, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5418320894241333, "train_acc": 0.61, "val_loss": 0.356577605009079, "val_acc": 0.98}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.3806157410144806, "train_acc": 0.885, "val_loss": 0.2527712881565094, "val_acc": 1.0}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.281301811337471, "train_acc": 0.935, "val_loss": 0.18313972651958466, "val_acc": 0.98}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.23108945786952972, "train_acc": 0.94, "val_loss": 0.1004885882139206, "val_acc": 1.0}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.19788017868995667, "train_acc": 0.945, "val_loss": 0.03863745927810669, "val_acc": 1.0}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.18994459509849548, "train_acc": 0.945, "val_loss": 0.028728967532515526, "val_acc": 1.0}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.1759120523929596, "train_acc": 0.945, "val_loss": 0.04527086392045021, "val_acc": 1.0}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.1705711930990219, "train_acc": 0.945, "val_loss": 0.048389092087745667, "val_acc": 1.0}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.15655390545725822, "train_acc": 0.95, "val_loss": 0.056761547923088074, "val_acc": 1.0}], "summary": {"total_epochs": 11, "degraded_epochs": 2, "improved_epochs": 9, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6611549258232117, "final_val_loss": 0.5134315490722656, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.356577605009079, "final_val_loss": 0.056761547923088074, "initial_val_acc": 0.98, "final_val_acc": 1.0, "best_val_acc": 1.0, "best_epoch": 3}, "improvement": 0.52, "first_improvement_epoch": 1}} |
73 | {"target_pattern": "has_majority", "degraded_accuracy": 0.5, "improved_accuracy": 0.68, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4032, "learning_rate": 0.09437991097205171, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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"network.0.bias": [
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"network.2.weight": [
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[
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[
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[
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[
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0.314218,
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[
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[
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],
"network.2.bias": [
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"network.4.weight": [
[
0.219033,
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[
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[
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[
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"network.6.weight": [
[
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[
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"network.8.weight": [
[
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0.0318,
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[
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0.238475,
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[
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"network.10.weight": [
[
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"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.681775, 0.613439, 0.000000, 0.000000, 0.000000]
std: [0.000000, 0.000000, 0.933048, 0.810185, 0.000000, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [13.842086, 14.559338, 15.027587, 16.230889, 61.359726], [11.748570, 12.294582, 13.066051, 14.020209, 55.209522], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.263739, 0.397397, 0.581987, -0.567813, 0.224530, 0.000000, 0.000000, 0.000000], [0.070016, 0.662368, 0.107358, 0.909111, -0.035016, 0.000000, 0.000000, 0.000000], [-0.757535, -0.607788, -0.693440, -0.228815, -0.475497, 0.000000, 0.000000, 0.000000], [-0.073104, 0.570995, 0.346350, 0.848529, 0.353854, 0.000000, 0.000000, 0.000000], [-0.172994, 0.339168, -0.010194, 0.988887, 0.078395, 0.000000, 0.000000, 0.000000], [0.314349, 0.808902, 0.284675, 0.777731, 0.265872, 0.000000, 0.000000, 0.000000], [-0.734313, -0.147655, -0.145162, 0.680807, 0.113311, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.327982, 2.563661, -4.658126, 2.347534, 0.775814, 1.277375, 0.532918]
pre_activation_std: [1.461540, 2.012647, 3.236320, 1.994812, 1.299698, 1.232408, 1.823265]
### 2
mean: [1.015502, 0.976851, 1.712193, 2.306269, 0.396056, 0.981885, 0.465029]
std: [1.520785, 1.086754, 1.804628, 2.310035, 0.894834, 1.242022, 0.560449]
fourier: [[21.276889, 22.435837, 23.697028, 25.805073, 91.395215], [15.812455, 16.167903, 17.543328, 18.980651, 87.916610], [26.247357, 26.887207, 27.209781, 33.578100, 154.097404], [33.584783, 33.971990, 34.176702, 40.394244, 207.564207], [12.788565, 14.234208, 14.328802, 15.236199, 35.645001], [18.400482, 18.785123, 19.661231, 20.037897, 88.369665], [8.349351, 8.600877, 8.975095, 10.482916, 41.852636]]
input_correlations: [[-0.304604, 0.890993, 0.000000, 0.928403, 0.960888, 0.806262, 0.845339, 0.000000], [-0.505740, 0.922349, 0.000000, 0.768218, 0.932226, 0.784396, 0.703903, 0.000000], [-0.324945, 0.971164, 0.000000, 0.875709, 0.961790, 0.842249, 0.767313, 0.000000], [-0.457669, 0.931447, 0.000000, 0.826202, 0.966890, 0.785264, 0.787801, 0.000000], [0.797276, -0.689570, 0.000000, -0.462756, -0.795074, -0.456429, -0.590651, 0.000000], [-0.551078, 0.904584, 0.000000, 0.745397, 0.935854, 0.726335, 0.748563, 0.000000], [0.699518, 0.159014, 0.000000, 0.051632, -0.251627, 0.326393, -0.600917, 0.000000]]
pre_activation_mean: [1.015502, 0.976851, 1.712193, 2.306269, 0.396056, 0.981885, 0.465029]
pre_activation_std: [1.520785, 1.086754, 1.804628, 2.310035, 0.894834, 1.242022, 0.560449]
### 4
mean: [1.427377, -1.290657, 0.920740, 0.067429, -1.657435, 2.569185, -1.662898]
std: [1.994181, 0.625501, 0.769602, 0.631721, 1.274319, 3.295077, 1.133211]
fourier: [[29.156463, 29.607530, 29.803970, 34.114430, 128.463894], [9.433174, 9.785549, 10.419942, 12.671350, 116.159155], [11.446811, 11.695067, 13.576753, 14.967242, 82.866620], [7.992354, 8.850118, 9.656482, 10.426503, 10.949471], [17.869731, 18.137385, 18.999096, 24.163397, 149.169184], [47.985618, 49.076390, 49.093210, 56.869240, 231.226662], [16.632942, 16.952403, 17.470308, 21.314852, 149.660877]]
input_correlations: [[0.962194, 0.985647, 0.984734, 0.998261, -0.718128, 0.990943, -0.150600, 0.000000], [-0.865399, -0.837181, -0.906906, -0.853395, 0.257682, -0.826350, -0.294711, 0.000000], [-0.692176, -0.789545, -0.702313, -0.781807, 0.961745, -0.803868, 0.519866, 0.000000], [0.940986, 0.936179, 0.916862, 0.957912, -0.746641, 0.954963, -0.379792, 0.000000], [-0.966687, -0.968189, -0.992456, -0.984873, 0.565631, -0.972392, 0.033804, 0.000000], [0.961542, 0.988046, 0.984655, 0.998614, -0.720414, 0.991639, -0.144038, 0.000000], [-0.939916, -0.988096, -0.993640, -0.988498, 0.665419, -0.978332, -0.042816, 0.000000]]
pre_activation_mean: [1.427377, -1.290657, 0.920740, 0.067429, -1.657435, 2.569185, -1.662898]
pre_activation_std: [1.994181, 0.625501, 0.769602, 0.631721, 1.274319, 3.295077, 1.133211]
### 6
mean: [2.233950, 1.027168, -2.300102, 1.031520, -0.815497, -0.943310, -0.520730]
std: [2.368679, 1.545181, 2.101792, 0.380967, 0.372834, 0.752835, 0.254142]
fourier: [[32.961872, 35.121620, 37.095071, 41.497729, 201.055456], [22.148523, 23.048472, 24.627436, 26.000365, 92.445129], [29.798025, 30.997399, 32.172671, 37.646448, 207.009161], [5.964902, 6.135899, 6.773502, 8.119996, 92.836832], [5.353625, 5.385718, 5.415578, 7.108457, 73.394723], [10.653523, 11.131526, 11.630361, 13.105265, 84.897947], [3.787486, 3.903702, 4.462169, 4.543806, 46.865703]]
input_correlations: [[0.999898, 0.000000, -0.755425, 0.941084, 0.000000, 0.999728, 0.000000, 0.000000], [0.996667, 0.000000, -0.802436, 0.935848, 0.000000, 0.997005, 0.000000, 0.000000], [-0.998878, 0.000000, 0.723675, -0.932939, 0.000000, -0.998859, 0.000000, 0.000000], [-0.625457, 0.000000, 0.984050, -0.571314, 0.000000, -0.629597, 0.000000, 0.000000], [-0.982204, 0.000000, 0.616917, -0.922179, 0.000000, -0.981737, 0.000000, 0.000000], [-0.997189, 0.000000, 0.772545, -0.917806, 0.000000, -0.998726, 0.000000, 0.000000], [0.806120, 0.000000, -0.992121, 0.725959, 0.000000, 0.809748, 0.000000, 0.000000]]
pre_activation_mean: [2.233950, 1.027168, -2.300102, 1.031520, -0.815497, -0.943310, -0.520730]
pre_activation_std: [2.368679, 1.545181, 2.101792, 0.380967, 0.372834, 0.752835, 0.254142]
### 8
mean: [-1.431930, -0.921217, 0.291017, 0.352805, -1.301727, -1.211169, -1.272720]
std: [0.879578, 0.504199, 1.255111, 1.030048, 1.358351, 1.000566, 1.225887]
fourier: [[12.273030, 13.034782, 13.749941, 15.439427, 128.873731], [7.162858, 7.308657, 7.574189, 9.312464, 82.909508], [18.474154, 18.781694, 20.326956, 20.337745, 26.191534], [15.186707, 15.414273, 16.632709, 16.707437, 31.752449], [18.638989, 20.154488, 21.401524, 23.738608, 117.155432], [13.874609, 14.870029, 15.745613, 17.353761, 109.005233], [16.809887, 18.205392, 19.345744, 21.344893, 114.544835]]
input_correlations: [[-0.999990, -0.997908, 0.000000, 0.626699, 0.000000, 0.000000, 0.000000, 0.000000], [-0.992791, -0.990874, 0.000000, 0.531563, 0.000000, 0.000000, 0.000000, 0.000000], [0.991560, 0.991239, 0.000000, -0.722854, 0.000000, 0.000000, 0.000000, 0.000000], [0.990883, 0.990780, 0.000000, -0.725898, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999771, -0.999197, 0.000000, 0.629731, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999809, -0.997836, 0.000000, 0.644299, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999770, -0.999100, 0.000000, 0.635528, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.431930, -0.921217, 0.291017, 0.352805, -1.301727, -1.211169, -1.272720]
pre_activation_std: [0.879578, 0.504199, 1.255111, 1.030048, 1.358351, 1.000566, 1.225887]
### 10
mean: [-0.184802]
std: [0.417427]
fourier: [[6.099318, 6.393655, 6.730327, 7.237155, 16.632162]]
input_correlations: [[0.000000, 0.000000, -0.999547, -0.999897, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.184802]
pre_activation_std: [0.417427]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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"network.0.bias": [
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"network.2.weight": [
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[
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[
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[
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],
"network.2.bias": [
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],
"network.4.weight": [
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[
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[
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"network.6.weight": [
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"network.8.weight": [
[
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],
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"network.10.weight": [
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"network.10.bias": [
0.127756
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.681775, 0.613439, 0.000000, 0.000000, 0.000000]
std: [0.000000, 0.000000, 0.933048, 0.810185, 0.000000, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [13.842086, 14.559338, 15.027587, 16.230889, 61.359726], [11.748570, 12.294582, 13.066051, 14.020209, 55.209522], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.263739, 0.397397, 0.581987, -0.567813, 0.224530, 0.000000, 0.000000, 0.000000], [0.070016, 0.662368, 0.107358, 0.909111, -0.035016, 0.000000, 0.000000, 0.000000], [-0.757535, -0.607788, -0.693440, -0.228815, -0.475497, 0.000000, 0.000000, 0.000000], [-0.073104, 0.570995, 0.346350, 0.848529, 0.353854, 0.000000, 0.000000, 0.000000], [-0.172994, 0.339168, -0.010194, 0.988887, 0.078395, 0.000000, 0.000000, 0.000000], [0.314349, 0.808902, 0.284675, 0.777731, 0.265872, 0.000000, 0.000000, 0.000000], [-0.734313, -0.147655, -0.145162, 0.680807, 0.113311, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.327982, 2.563661, -4.658126, 2.347534, 0.775814, 1.277375, 0.532918]
pre_activation_std: [1.461540, 2.012647, 3.236320, 1.994812, 1.299698, 1.232408, 1.823265]
### 2
mean: [1.015502, 0.976851, 1.712193, 2.306269, 0.396056, 0.981885, 0.465029]
std: [1.520785, 1.086754, 1.804628, 2.310035, 0.894834, 1.242022, 0.560449]
fourier: [[21.276889, 22.435837, 23.697028, 25.805073, 91.395215], [15.812455, 16.167903, 17.543328, 18.980651, 87.916610], [26.247357, 26.887207, 27.209781, 33.578100, 154.097404], [33.584783, 33.971990, 34.176702, 40.394244, 207.564207], [12.788565, 14.234208, 14.328802, 15.236199, 35.645001], [18.400482, 18.785123, 19.661231, 20.037897, 88.369665], [8.349351, 8.600877, 8.975095, 10.482916, 41.852636]]
input_correlations: [[-0.304604, 0.890993, 0.000000, 0.928403, 0.960888, 0.806262, 0.845339, 0.000000], [-0.505740, 0.922349, 0.000000, 0.768218, 0.932226, 0.784396, 0.703903, 0.000000], [-0.324945, 0.971164, 0.000000, 0.875709, 0.961790, 0.842249, 0.767313, 0.000000], [-0.457669, 0.931447, 0.000000, 0.826202, 0.966890, 0.785264, 0.787801, 0.000000], [0.797276, -0.689570, 0.000000, -0.462756, -0.795074, -0.456429, -0.590651, 0.000000], [-0.551078, 0.904584, 0.000000, 0.745397, 0.935854, 0.726335, 0.748563, 0.000000], [0.699518, 0.159014, 0.000000, 0.051632, -0.251627, 0.326393, -0.600917, 0.000000]]
pre_activation_mean: [1.015502, 0.976851, 1.712193, 2.306269, 0.396056, 0.981885, 0.465029]
pre_activation_std: [1.520785, 1.086754, 1.804628, 2.310035, 0.894834, 1.242022, 0.560449]
### 4
mean: [1.427377, -1.290657, 0.920740, 0.067429, -1.657435, 2.569185, -1.662898]
std: [1.994181, 0.625501, 0.769602, 0.631721, 1.274319, 3.295077, 1.133211]
fourier: [[29.156463, 29.607530, 29.803970, 34.114430, 128.463894], [9.433174, 9.785549, 10.419942, 12.671350, 116.159155], [11.446811, 11.695067, 13.576753, 14.967242, 82.866620], [7.992354, 8.850118, 9.656482, 10.426503, 10.949471], [17.869731, 18.137385, 18.999096, 24.163397, 149.169184], [47.985618, 49.076390, 49.093210, 56.869240, 231.226662], [16.632942, 16.952403, 17.470308, 21.314852, 149.660877]]
input_correlations: [[0.962194, 0.985647, 0.984734, 0.998261, -0.718128, 0.990943, -0.150600, 0.000000], [-0.865399, -0.837181, -0.906906, -0.853395, 0.257682, -0.826350, -0.294711, 0.000000], [-0.692176, -0.789545, -0.702313, -0.781807, 0.961745, -0.803868, 0.519866, 0.000000], [0.940986, 0.936179, 0.916862, 0.957912, -0.746641, 0.954963, -0.379792, 0.000000], [-0.966687, -0.968189, -0.992456, -0.984873, 0.565631, -0.972392, 0.033804, 0.000000], [0.961542, 0.988046, 0.984655, 0.998614, -0.720414, 0.991639, -0.144038, 0.000000], [-0.939916, -0.988096, -0.993640, -0.988498, 0.665419, -0.978332, -0.042816, 0.000000]]
pre_activation_mean: [1.427377, -1.290657, 0.920740, 0.067429, -1.657435, 2.569185, -1.662898]
pre_activation_std: [1.994181, 0.625501, 0.769602, 0.631721, 1.274319, 3.295077, 1.133211]
### 6
mean: [2.233950, 1.027168, -2.300102, 1.031520, -0.815497, -0.943310, -0.520730]
std: [2.368679, 1.545181, 2.101792, 0.380967, 0.372834, 0.752835, 0.254142]
fourier: [[32.961872, 35.121620, 37.095071, 41.497729, 201.055456], [22.148523, 23.048472, 24.627436, 26.000365, 92.445129], [29.798025, 30.997399, 32.172671, 37.646448, 207.009161], [5.964902, 6.135899, 6.773502, 8.119996, 92.836832], [5.353625, 5.385718, 5.415578, 7.108457, 73.394723], [10.653523, 11.131526, 11.630361, 13.105265, 84.897947], [3.787486, 3.903702, 4.462169, 4.543806, 46.865703]]
input_correlations: [[0.999898, 0.000000, -0.755425, 0.941084, 0.000000, 0.999728, 0.000000, 0.000000], [0.996667, 0.000000, -0.802436, 0.935848, 0.000000, 0.997005, 0.000000, 0.000000], [-0.998878, 0.000000, 0.723675, -0.932939, 0.000000, -0.998859, 0.000000, 0.000000], [-0.625457, 0.000000, 0.984050, -0.571314, 0.000000, -0.629597, 0.000000, 0.000000], [-0.982204, 0.000000, 0.616917, -0.922179, 0.000000, -0.981737, 0.000000, 0.000000], [-0.997189, 0.000000, 0.772545, -0.917806, 0.000000, -0.998726, 0.000000, 0.000000], [0.806120, 0.000000, -0.992121, 0.725959, 0.000000, 0.809748, 0.000000, 0.000000]]
pre_activation_mean: [2.233950, 1.027168, -2.300102, 1.031520, -0.815497, -0.943310, -0.520730]
pre_activation_std: [2.368679, 1.545181, 2.101792, 0.380967, 0.372834, 0.752835, 0.254142]
### 8
mean: [-1.431930, -0.921217, 0.291017, 0.352805, -1.301727, -1.211169, -1.272720]
std: [0.879578, 0.504199, 1.255111, 1.030048, 1.358351, 1.000566, 1.225887]
fourier: [[12.273030, 13.034782, 13.749941, 15.439427, 128.873731], [7.162858, 7.308657, 7.574189, 9.312464, 82.909508], [18.474154, 18.781694, 20.326956, 20.337745, 26.191534], [15.186707, 15.414273, 16.632709, 16.707437, 31.752449], [18.638989, 20.154488, 21.401524, 23.738608, 117.155432], [13.874609, 14.870029, 15.745613, 17.353761, 109.005233], [16.809887, 18.205392, 19.345744, 21.344893, 114.544835]]
input_correlations: [[-0.999990, -0.997908, 0.000000, 0.626699, 0.000000, 0.000000, 0.000000, 0.000000], [-0.992791, -0.990874, 0.000000, 0.531563, 0.000000, 0.000000, 0.000000, 0.000000], [0.991560, 0.991239, 0.000000, -0.722854, 0.000000, 0.000000, 0.000000, 0.000000], [0.990883, 0.990780, 0.000000, -0.725898, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999771, -0.999197, 0.000000, 0.629731, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999809, -0.997836, 0.000000, 0.644299, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999770, -0.999100, 0.000000, 0.635528, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.431930, -0.921217, 0.291017, 0.352805, -1.301727, -1.211169, -1.272720]
pre_activation_std: [0.879578, 0.504199, 1.255111, 1.030048, 1.358351, 1.000566, 1.225887]
### 10
mean: [-0.184802]
std: [0.417427]
fourier: [[6.099318, 6.393655, 6.730327, 7.237155, 16.632162]]
input_correlations: [[0.000000, 0.000000, -0.999547, -0.999897, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.184802]
pre_activation_std: [0.417427]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.26373916645762535, 0.3973971650363322, 0.5819874949660877, -0.5678130479802906, 0.22453040368741378, 0.0, 0.0, 0.0], "pre_activation_mean": 0.32798221707344055, "pre_activation_std": 1.4615399837493896}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.07001643196548983, 0.662367905693012, 0.10735806499207641, 0.9091106804792606, -0.0350161069766621, 0.0, 0.0, 0.0], "pre_activation_mean": 2.5636610984802246, "pre_activation_std": 2.0126471519470215}, "2": {"mean": 0.6817747354507446, "std": 0.9330477714538574, "fourier": [13.842085931717936, 14.559338173154035, 15.0275868164884, 16.230889292713695, 61.35972636938095], "input_correlations": [-0.7575352047923442, -0.6077879655426687, -0.6934400596935387, -0.22881472390758475, -0.4754972167438307, 0.0, 0.0, 0.0], "pre_activation_mean": 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-0.07147, -0.219473, 0.367727, 0.01061, 0.100956, -0.267711], [-0.153549, -0.13824, -0.350362, -0.052272, -0.34501, -0.334111, 0.073937], [0.380003, 0.296129, 0.547436, 0.482851, -0.355916, 0.284302, -0.30022], [-0.061877, -0.161205, -0.142706, -0.297781, 0.112056, 0.054487, -0.329213]], "network.4.bias": [-0.24499, -0.247131, 0.631015, -0.431859, -0.049864, -0.267186, -0.412612], "network.6.weight": [[0.502026, -0.249002, -0.012222, 0.212219, 0.129188, 0.437037, -0.020005], [0.181568, 0.173558, -0.238167, 0.101461, 0.184569, 0.332425, 0.004782], [-0.592442, -0.345999, -0.187817, 0.115885, 0.365742, -0.377949, -0.359681], [0.014433, -0.175769, 0.593593, 0.096781, 0.263054, 0.010812, 0.292648], [0.064203, -0.012887, -0.142862, -0.048847, 0.123335, -0.176043, 0.305232], [0.204799, -0.340926, 0.039531, 0.145413, -0.149022, -0.376194, 0.267201], [0.159854, -0.011963, -0.298618, -0.163261, -0.084893, -0.061374, 0.0148]], "network.6.bias": [0.168781, 0.006742, -0.166141, 0.39823, -0.282817, -0.307703, -0.279928], "network.8.weight": [[-0.391208, 0.0318, -0.351508, -0.00971, 0.017369, 0.365016, -0.23292], [-0.232656, 0.001131, 0.218469, -0.204109, 0.238475, -0.241184, -0.30402], [0.257687, 0.358807, -0.065279, -0.539051, -0.021096, 0.159776, -0.048425], [0.184872, 0.336122, -0.218067, -0.457875, -0.10006, 0.063637, -0.033498], [-0.373766, -0.335364, -0.260904, 0.003266, 0.044603, 0.292513, -0.083685], [-0.425636, 0.016793, -0.158216, 0.065952, 0.327899, 0.329343, 0.240838], [-0.347515, -0.280228, -0.073902, 0.033858, -0.139676, 0.215299, -0.20468]], "network.8.bias": [-0.585497, -0.192268, -0.151966, 0.015521, -0.074419, -0.348166, -0.200669], "network.10.weight": [[0.008293, -0.325976, -0.144555, -0.348859, 0.128442, 0.035444, -0.275596]], "network.10.bias": [0.127756]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6903762519359589, "train_acc": 0.575, "val_loss": 0.6872068047523499, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6529862582683563, "train_acc": 0.575, "val_loss": 0.7250056266784668, "val_acc": 0.5}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6611661016941071, "train_acc": 0.575, "val_loss": 0.6425492167472839, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 3, "train_loss": 0.9603015780448914, "train_acc": 0.505, "val_loss": 0.6185736060142517, "val_acc": 0.68}, {"stage": "improved", "epoch": 1, "global_epoch": 4, "train_loss": 0.6530574560165405, "train_acc": 0.675, "val_loss": 0.6963005065917969, "val_acc": 0.5}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.6960434317588806, "train_acc": 0.5, "val_loss": 0.7039135098457336, "val_acc": 0.5}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.7003999650478363, "train_acc": 0.5, "val_loss": 0.7046760320663452, "val_acc": 0.5}], "summary": {"total_epochs": 7, "degraded_epochs": 3, "improved_epochs": 4, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.6872068047523499, "final_val_loss": 0.6425492167472839, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.6185736060142517, "final_val_loss": 0.7046760320663452, "initial_val_acc": 0.68, "final_val_acc": 0.5, "best_val_acc": 0.68, "best_epoch": 3}, "improvement": 0.18000000000000005, "first_improvement_epoch": 2}} |
74 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.76, "improved_accuracy": 0.94, "improvement": 0.17999999999999994, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4020, "learning_rate": 0.0658082586785923, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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1.065825,
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[
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0.34695
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[
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0.395185,
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[
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0.421806
]
],
"network.0.bias": [
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"network.2.weight": [
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0.589257,
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[
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0.170945,
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0.023904,
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0.121244,
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[
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"network.6.weight": [
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],
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"network.8.weight": [
[
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],
"network.8.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 1.717056, 2.288354, 2.247827, 2.726717, 3.221178]
std: [0.000000, 0.000000, 0.000000, 2.333516, 2.961876, 3.033014, 3.636710, 4.224675]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [39.031078, 40.387864, 41.807539, 43.460982, 154.535033], [49.614721, 50.521797, 53.435152, 56.074549, 205.951896], [50.624392, 53.023173, 54.209973, 56.334110, 202.304380], [60.604888, 63.089638, 65.264244, 68.035298, 245.404514], [70.416285, 73.608598, 75.839205, 79.283115, 289.906020]]
input_correlations: [[0.872982, 0.535940, 0.551276, 0.329915, 0.147031, 0.000000, 0.000000, 0.000000], [0.350565, 0.287304, -0.632889, 0.461694, 0.009366, 0.000000, 0.000000, 0.000000], [-0.911433, -0.461492, -0.386690, -0.326743, -0.093158, 0.000000, 0.000000, 0.000000], [-0.590010, -0.601193, -0.289657, -0.760760, -0.201887, 0.000000, 0.000000, 0.000000], [0.811135, 0.085425, 0.473913, -0.409993, -0.209388, 0.000000, 0.000000, 0.000000], [-0.961652, -0.439036, -0.358615, 0.078985, 0.055525, 0.000000, 0.000000, 0.000000], [0.723077, 0.486512, 0.636076, 0.365526, -0.097731, 0.000000, 0.000000, 0.000000], [0.865797, 0.653453, 0.531681, 0.045460, 0.364133, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.991028, -0.016736, -1.725409, -2.589907, 0.188988, -0.822368, 1.844247, 3.426659]
pre_activation_std: [2.762980, 1.880419, 2.226918, 2.097337, 2.162664, 2.700284, 1.851741, 3.398185]
### 2
mean: [3.927423, -2.108630, -2.405216, -2.429896, -1.748610, -2.158158, 0.988724, -2.458778]
std: [4.200072, 1.684025, 1.664247, 1.735888, 1.024821, 1.401863, 1.233344, 2.672132]
fourier: [[70.499180, 75.905002, 78.292976, 80.783550, 353.468118], [27.616713, 28.461110, 30.591624, 31.748722, 189.776668], [25.701492, 29.114313, 30.316751, 33.617369, 216.469433], [28.744504, 30.355430, 30.856928, 34.654760, 218.690620], [18.592899, 18.980700, 19.208088, 20.026920, 157.374949], [22.730162, 25.812309, 27.448927, 27.588342, 194.234261], [19.736736, 21.153762, 23.228006, 23.845452, 88.985138], [44.180671, 44.836758, 47.230438, 54.213343, 221.290006]]
input_correlations: [[0.969333, 0.457500, -0.453668, -0.382397, 0.857222, -0.496711, 0.881860, 0.942003], [-0.889259, -0.090121, 0.344836, 0.368552, -0.688141, 0.438078, -0.831622, -0.948895], [-0.978320, -0.470627, 0.453878, 0.424598, -0.708338, 0.413207, -0.909177, -0.924020], [-0.960104, -0.358793, 0.385266, 0.369256, -0.802425, 0.359367, -0.860551, -0.963488], [-0.866449, -0.530933, 0.289918, 0.388346, -0.777605, 0.229588, -0.729823, -0.950397], [-0.903291, -0.346160, 0.275187, 0.318706, -0.856124, 0.293694, -0.784074, -0.964755], [0.623015, 0.885269, -0.247344, -0.289174, 0.525711, -0.145471, 0.443079, 0.673663], [-0.991008, -0.458063, 0.570237, 0.406270, -0.786479, 0.582002, -0.966261, -0.842994]]
pre_activation_mean: [3.927423, -2.108630, -2.405216, -2.429896, -1.748610, -2.158158, 0.988724, -2.458778]
pre_activation_std: [4.200072, 1.684025, 1.664247, 1.735888, 1.024821, 1.401863, 1.233344, 2.672132]
### 4
mean: [1.841633, -0.542478, 1.022182, 0.958945, 1.473059, 0.617171, 1.443612, -1.823238]
std: [2.257393, 0.239607, 1.327424, 1.342585, 1.757758, 0.893155, 2.107517, 1.667389]
fourier: [[38.483779, 39.370084, 43.363349, 43.693052, 165.746984], [4.004293, 4.034174, 4.258243, 4.378380, 48.823050], [22.483895, 23.579305, 25.141478, 25.580161, 91.996333], [22.733978, 23.711018, 25.966197, 26.228889, 86.305037], [29.312716, 30.832222, 33.583422, 33.713722, 132.575290], [15.753669, 15.941670, 16.376974, 17.268070, 55.545349], [36.491955, 36.562717, 40.473903, 40.809027, 129.925065], [29.431413, 29.921791, 30.085718, 30.913057, 164.091367]]
input_correlations: [[0.991179, -0.043807, 0.000000, 0.000000, 0.000000, 0.000000, 0.813235, -0.419699], [-0.949712, 0.044808, 0.000000, 0.000000, 0.000000, 0.000000, -0.876447, 0.238826], [0.998847, -0.071341, 0.000000, 0.000000, 0.000000, 0.000000, 0.729313, -0.462632], [0.995289, -0.052955, 0.000000, 0.000000, 0.000000, 0.000000, 0.783666, -0.456585], [0.996138, -0.054868, 0.000000, 0.000000, 0.000000, 0.000000, 0.786128, -0.423795], [0.984598, -0.085360, 0.000000, 0.000000, 0.000000, 0.000000, 0.625029, -0.519865], [0.987968, -0.046360, 0.000000, 0.000000, 0.000000, 0.000000, 0.826080, -0.417102], [-0.991440, 0.097249, 0.000000, 0.000000, 0.000000, 0.000000, -0.633829, 0.423062]]
pre_activation_mean: [1.841633, -0.542478, 1.022182, 0.958945, 1.473059, 0.617171, 1.443612, -1.823238]
pre_activation_std: [2.257393, 0.239607, 1.327424, 1.342585, 1.757758, 0.893155, 2.107517, 1.667389]
### 6
mean: [-0.551980, -1.607284, -1.838400, 1.625116, 2.207288, 2.135523, 2.612787, 3.114784]
std: [0.359801, 1.484653, 2.164338, 2.404466, 3.027334, 3.120166, 3.725733, 4.308957]
fourier: [[5.989975, 6.228327, 6.431665, 6.739164, 49.678181], [24.799755, 26.303009, 27.077083, 27.879531, 144.655574], [36.213931, 36.554692, 39.665195, 41.256162, 165.456012], [40.614310, 40.665178, 43.950258, 45.824380, 146.260475], [50.561815, 51.239372, 55.790781, 58.051698, 198.655897], [52.027182, 53.382827, 56.993075, 59.254844, 192.197035], [62.488455, 63.312860, 68.114154, 70.909578, 235.150872], [71.837226, 73.721847, 78.815264, 81.896524, 280.330558]]
input_correlations: [[-0.998078, 0.000000, -0.991633, -0.998746, -0.997408, -0.966747, -0.999113, 0.000000], [-0.994999, 0.000000, -0.999401, -0.998436, -0.998472, -0.985449, -0.991691, 0.000000], [-0.999717, 0.000000, -0.993260, -0.999344, -0.999406, -0.968755, -0.998620, 0.000000], [0.999720, 0.000000, 0.992164, 0.999159, 0.998962, 0.966265, 0.999153, 0.000000], [0.999979, 0.000000, 0.991457, 0.998644, 0.999028, 0.964950, 0.998800, 0.000000], [0.999334, 0.000000, 0.994593, 0.999729, 0.999567, 0.971559, 0.998181, 0.000000], [0.999607, 0.000000, 0.993406, 0.999487, 0.999332, 0.968926, 0.998716, 0.000000], [0.999328, 0.000000, 0.994806, 0.999756, 0.999651, 0.971985, 0.998002, 0.000000]]
pre_activation_mean: [-0.551980, -1.607284, -1.838400, 1.625116, 2.207288, 2.135523, 2.612787, 3.114784]
pre_activation_std: [0.359801, 1.484653, 2.164338, 2.404466, 3.027334, 3.120166, 3.725733, 4.308957]
### 8
mean: [-5.213180]
std: [7.869159]
fourier: [[131.225317, 136.545610, 141.235064, 147.392081, 469.186167]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999805, -0.999720, -0.999913, -0.999990, -0.999927]]
pre_activation_mean: [-5.213180]
pre_activation_std: [7.869159]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.6.weight": [
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],
"network.8.bias": [
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 1.717056, 2.288354, 2.247827, 2.726717, 3.221178]
std: [0.000000, 0.000000, 0.000000, 2.333516, 2.961876, 3.033014, 3.636710, 4.224675]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [39.031078, 40.387864, 41.807539, 43.460982, 154.535033], [49.614721, 50.521797, 53.435152, 56.074549, 205.951896], [50.624392, 53.023173, 54.209973, 56.334110, 202.304380], [60.604888, 63.089638, 65.264244, 68.035298, 245.404514], [70.416285, 73.608598, 75.839205, 79.283115, 289.906020]]
input_correlations: [[0.872982, 0.535940, 0.551276, 0.329915, 0.147031, 0.000000, 0.000000, 0.000000], [0.350565, 0.287304, -0.632889, 0.461694, 0.009366, 0.000000, 0.000000, 0.000000], [-0.911433, -0.461492, -0.386690, -0.326743, -0.093158, 0.000000, 0.000000, 0.000000], [-0.590010, -0.601193, -0.289657, -0.760760, -0.201887, 0.000000, 0.000000, 0.000000], [0.811135, 0.085425, 0.473913, -0.409993, -0.209388, 0.000000, 0.000000, 0.000000], [-0.961652, -0.439036, -0.358615, 0.078985, 0.055525, 0.000000, 0.000000, 0.000000], [0.723077, 0.486512, 0.636076, 0.365526, -0.097731, 0.000000, 0.000000, 0.000000], [0.865797, 0.653453, 0.531681, 0.045460, 0.364133, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.991028, -0.016736, -1.725409, -2.589907, 0.188988, -0.822368, 1.844247, 3.426659]
pre_activation_std: [2.762980, 1.880419, 2.226918, 2.097337, 2.162664, 2.700284, 1.851741, 3.398185]
### 2
mean: [3.927423, -2.108630, -2.405216, -2.429896, -1.748610, -2.158158, 0.988724, -2.458778]
std: [4.200072, 1.684025, 1.664247, 1.735888, 1.024821, 1.401863, 1.233344, 2.672132]
fourier: [[70.499180, 75.905002, 78.292976, 80.783550, 353.468118], [27.616713, 28.461110, 30.591624, 31.748722, 189.776668], [25.701492, 29.114313, 30.316751, 33.617369, 216.469433], [28.744504, 30.355430, 30.856928, 34.654760, 218.690620], [18.592899, 18.980700, 19.208088, 20.026920, 157.374949], [22.730162, 25.812309, 27.448927, 27.588342, 194.234261], [19.736736, 21.153762, 23.228006, 23.845452, 88.985138], [44.180671, 44.836758, 47.230438, 54.213343, 221.290006]]
input_correlations: [[0.969333, 0.457500, -0.453668, -0.382397, 0.857222, -0.496711, 0.881860, 0.942003], [-0.889259, -0.090121, 0.344836, 0.368552, -0.688141, 0.438078, -0.831622, -0.948895], [-0.978320, -0.470627, 0.453878, 0.424598, -0.708338, 0.413207, -0.909177, -0.924020], [-0.960104, -0.358793, 0.385266, 0.369256, -0.802425, 0.359367, -0.860551, -0.963488], [-0.866449, -0.530933, 0.289918, 0.388346, -0.777605, 0.229588, -0.729823, -0.950397], [-0.903291, -0.346160, 0.275187, 0.318706, -0.856124, 0.293694, -0.784074, -0.964755], [0.623015, 0.885269, -0.247344, -0.289174, 0.525711, -0.145471, 0.443079, 0.673663], [-0.991008, -0.458063, 0.570237, 0.406270, -0.786479, 0.582002, -0.966261, -0.842994]]
pre_activation_mean: [3.927423, -2.108630, -2.405216, -2.429896, -1.748610, -2.158158, 0.988724, -2.458778]
pre_activation_std: [4.200072, 1.684025, 1.664247, 1.735888, 1.024821, 1.401863, 1.233344, 2.672132]
### 4
mean: [1.841633, -0.542478, 1.022182, 0.958945, 1.473059, 0.617171, 1.443612, -1.823238]
std: [2.257393, 0.239607, 1.327424, 1.342585, 1.757758, 0.893155, 2.107517, 1.667389]
fourier: [[38.483779, 39.370084, 43.363349, 43.693052, 165.746984], [4.004293, 4.034174, 4.258243, 4.378380, 48.823050], [22.483895, 23.579305, 25.141478, 25.580161, 91.996333], [22.733978, 23.711018, 25.966197, 26.228889, 86.305037], [29.312716, 30.832222, 33.583422, 33.713722, 132.575290], [15.753669, 15.941670, 16.376974, 17.268070, 55.545349], [36.491955, 36.562717, 40.473903, 40.809027, 129.925065], [29.431413, 29.921791, 30.085718, 30.913057, 164.091367]]
input_correlations: [[0.991179, -0.043807, 0.000000, 0.000000, 0.000000, 0.000000, 0.813235, -0.419699], [-0.949712, 0.044808, 0.000000, 0.000000, 0.000000, 0.000000, -0.876447, 0.238826], [0.998847, -0.071341, 0.000000, 0.000000, 0.000000, 0.000000, 0.729313, -0.462632], [0.995289, -0.052955, 0.000000, 0.000000, 0.000000, 0.000000, 0.783666, -0.456585], [0.996138, -0.054868, 0.000000, 0.000000, 0.000000, 0.000000, 0.786128, -0.423795], [0.984598, -0.085360, 0.000000, 0.000000, 0.000000, 0.000000, 0.625029, -0.519865], [0.987968, -0.046360, 0.000000, 0.000000, 0.000000, 0.000000, 0.826080, -0.417102], [-0.991440, 0.097249, 0.000000, 0.000000, 0.000000, 0.000000, -0.633829, 0.423062]]
pre_activation_mean: [1.841633, -0.542478, 1.022182, 0.958945, 1.473059, 0.617171, 1.443612, -1.823238]
pre_activation_std: [2.257393, 0.239607, 1.327424, 1.342585, 1.757758, 0.893155, 2.107517, 1.667389]
### 6
mean: [-0.551980, -1.607284, -1.838400, 1.625116, 2.207288, 2.135523, 2.612787, 3.114784]
std: [0.359801, 1.484653, 2.164338, 2.404466, 3.027334, 3.120166, 3.725733, 4.308957]
fourier: [[5.989975, 6.228327, 6.431665, 6.739164, 49.678181], [24.799755, 26.303009, 27.077083, 27.879531, 144.655574], [36.213931, 36.554692, 39.665195, 41.256162, 165.456012], [40.614310, 40.665178, 43.950258, 45.824380, 146.260475], [50.561815, 51.239372, 55.790781, 58.051698, 198.655897], [52.027182, 53.382827, 56.993075, 59.254844, 192.197035], [62.488455, 63.312860, 68.114154, 70.909578, 235.150872], [71.837226, 73.721847, 78.815264, 81.896524, 280.330558]]
input_correlations: [[-0.998078, 0.000000, -0.991633, -0.998746, -0.997408, -0.966747, -0.999113, 0.000000], [-0.994999, 0.000000, -0.999401, -0.998436, -0.998472, -0.985449, -0.991691, 0.000000], [-0.999717, 0.000000, -0.993260, -0.999344, -0.999406, -0.968755, -0.998620, 0.000000], [0.999720, 0.000000, 0.992164, 0.999159, 0.998962, 0.966265, 0.999153, 0.000000], [0.999979, 0.000000, 0.991457, 0.998644, 0.999028, 0.964950, 0.998800, 0.000000], [0.999334, 0.000000, 0.994593, 0.999729, 0.999567, 0.971559, 0.998181, 0.000000], [0.999607, 0.000000, 0.993406, 0.999487, 0.999332, 0.968926, 0.998716, 0.000000], [0.999328, 0.000000, 0.994806, 0.999756, 0.999651, 0.971985, 0.998002, 0.000000]]
pre_activation_mean: [-0.551980, -1.607284, -1.838400, 1.625116, 2.207288, 2.135523, 2.612787, 3.114784]
pre_activation_std: [0.359801, 1.484653, 2.164338, 2.404466, 3.027334, 3.120166, 3.725733, 4.308957]
### 8
mean: [-5.213180]
std: [7.869159]
fourier: [[131.225317, 136.545610, 141.235064, 147.392081, 469.186167]]
input_correlations: [[0.000000, 0.000000, 0.000000, -0.999805, -0.999720, -0.999913, -0.999990, -0.999927]]
pre_activation_mean: [-5.213180]
pre_activation_std: [7.869159]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.8729824862331854, 0.5359403769630762, 0.5512759770167366, 0.3299150499957894, 0.147030738925313, 0.0, 0.0, 0.0], "pre_activation_mean": 2.99102783203125, "pre_activation_std": 2.762979507446289}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.3505649239172775, 0.2873041970230233, -0.6328889800525362, 0.46169449417331254, 0.009366294825680301, 0.0, 0.0, 0.0], "pre_activation_mean": -0.016736237332224846, "pre_activation_std": 1.880419373512268}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.9114326754195938, -0.4614922251766211, -0.3866903006686142, -0.32674290195938704, -0.09315762668016023, 0.0, 0.0, 0.0], "pre_activation_mean": -1.7254093885421753, "pre_activation_std": 2.2269177436828613}, "3": {"mean": 1.7170557975769043, "std": 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-0.274671], "network.6.weight": [[-0.061936, 0.115851, -0.120846, 0.127755, 0.189616, -0.089516, -0.243363, 0.067686], [-0.026339, 0.32883, -0.510214, -0.203861, -0.231852, -0.138422, -0.003543, 0.430292], [-0.330615, -0.081502, 0.234002, -0.089879, -0.388941, -0.277268, -0.363158, -0.022414], [0.262787, -0.285769, 0.096591, 0.259477, 0.260189, -0.036548, 0.476203, 0.006774], [0.968585, -0.025873, -0.078244, -0.070874, 0.326517, 0.061482, 0.236173, 0.024208], [0.268776, -0.218023, 0.235413, 0.212054, 0.373895, 0.186032, 0.583016, -0.275331], [0.40294, -0.086243, 0.004392, 0.481108, 0.450921, 0.175232, 0.650827, -0.284319], [0.740188, -0.325312, 0.447987, 0.559641, 0.108976, 0.207776, 0.521741, 0.080475]], "network.6.bias": [-0.281343, -0.344799, -0.024524, -0.356956, -0.380725, -0.450567, -0.471333, -0.474357], "network.8.weight": [[-0.104203, 0.00039, -0.027002, -0.303321, -0.371613, -0.42931, -0.60297, -0.607508]], "network.8.bias": [0.724054]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6828865110874176, "train_acc": 0.445, "val_loss": 0.7071729898452759, "val_acc": 0.38}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.5615401566028595, "train_acc": 0.615, "val_loss": 0.6308145523071289, "val_acc": 0.76}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5440227389335632, "train_acc": 0.715, "val_loss": 0.5673523545265198, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5105676352977753, "train_acc": 0.85, "val_loss": 0.5156938433647156, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.43666595220565796, "train_acc": 0.855, "val_loss": 0.5083847641944885, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.3915623426437378, "train_acc": 0.8, "val_loss": 0.44238993525505066, "val_acc": 0.88}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.346227303147316, "train_acc": 0.94, "val_loss": 0.3894929587841034, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.30474182963371277, "train_acc": 0.935, "val_loss": 0.33899590373039246, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.25998879969120026, "train_acc": 0.96, "val_loss": 0.34336867928504944, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.2341281697154045, "train_acc": 0.965, "val_loss": 0.3392723798751831, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.22502509504556656, "train_acc": 0.97, "val_loss": 0.2777375280857086, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.2098793312907219, "train_acc": 0.955, "val_loss": 0.27843791246414185, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.7071729898452759, "final_val_loss": 0.6308145523071289, "initial_val_acc": 0.38, "final_val_acc": 0.76, "best_val_acc": 0.76}, "improved_stage": {"initial_val_loss": 0.5673523545265198, "final_val_loss": 0.27843791246414185, "initial_val_acc": 0.82, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 7}, "improvement": 0.17999999999999994, "first_improvement_epoch": 1}} |
75 | {"target_pattern": "alternating", "degraded_accuracy": 0.58, "improved_accuracy": 0.94, "improvement": 0.36, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8736, "learning_rate": 0.08073496747622153, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
0.307305,
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0.18721,
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[
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[
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[
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[
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"network.6.weight": [
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"network.8.weight": [
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}
## Activation Signature
### 0
mean: [2.222571, 0.603631, 0.119350, 0.582562, 1.939918, 2.110234, 0.372925]
std: [2.253705, 1.564458, 0.860899, 1.131688, 2.504867, 2.223501, 0.704360]
fourier: [[37.027913, 37.590686, 37.684300, 40.347377, 200.031359], [24.437480, 25.290684, 25.894125, 27.699902, 54.326816], [11.937786, 11.997788, 13.094748, 13.352301, 13.470584], [15.438628, 17.225105, 17.447434, 23.178511, 52.430601], [41.525671, 42.651899, 46.514646, 53.023139, 174.592633], [34.963090, 35.071394, 36.977870, 37.234754, 189.921062], [11.590362, 11.711132, 12.275826, 12.803174, 33.563224]]
input_correlations: [[-0.052477, 0.604743, -0.156663, 0.813885, 0.377375, 0.000000, 0.000000, 0.000000], [-0.008164, 0.327378, 0.750785, 0.622339, 0.140738, 0.000000, 0.000000, 0.000000], [0.633080, 0.130745, 0.794615, -0.424132, 0.338967, 0.000000, 0.000000, 0.000000], [-0.393221, -0.794106, -0.473507, -0.704050, -0.292841, 0.000000, 0.000000, 0.000000], [0.079979, -0.667674, 0.038083, -0.028935, 0.708652, 0.000000, 0.000000, 0.000000], [-0.448007, 0.147425, -0.130746, -0.155188, 0.563451, 0.000000, 0.000000, 0.000000], [-0.454673, -0.389051, 0.070735, 0.194725, 0.755437, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.652986, 2.191873, 1.911465, -6.150148, 0.385045, -0.453828, 0.590759]
pre_activation_std: [1.808105, 1.432524, 2.175916, 3.613172, 2.669925, 1.591441, 1.698436]
### 2
mean: [-1.453585, 1.566927, 2.311968, -1.480892, 0.715191, 0.310447, -1.787658]
std: [2.500612, 3.363382, 1.983420, 2.564391, 0.914518, 2.918823, 3.355674]
fourier: [[41.418158, 42.538398, 44.390860, 51.808842, 130.822662], [50.668004, 53.971809, 54.936600, 64.042430, 141.023428], [32.573584, 35.932850, 37.121476, 43.296300, 208.077111], [37.194197, 39.865403, 41.669365, 46.877929, 133.280329], [12.649914, 15.036108, 16.969842, 18.496297, 64.367241], [41.415344, 43.121185, 45.084485, 47.395276, 52.862053], [44.524983, 55.688265, 58.051398, 62.247741, 160.889250]]
input_correlations: [[0.078578, -0.087151, -0.528757, -0.183605, -0.895794, -0.441278, -0.797843, 0.000000], [0.313893, -0.070306, -0.026297, 0.073018, 0.886622, 0.630209, 0.934732, 0.000000], [-0.046244, 0.441058, 0.728090, 0.381206, 0.610668, 0.406390, 0.674035, 0.000000], [-0.906431, -0.423993, 0.547039, -0.296841, 0.153576, -0.326388, -0.213222, 0.000000], [0.254985, 0.723089, -0.068266, 0.320015, -0.618552, -0.214736, -0.298126, 0.000000], [0.205092, -0.102986, 0.025557, 0.066036, 0.869598, 0.670165, 0.935976, 0.000000], [-0.879082, -0.374518, 0.584213, -0.277061, 0.144702, -0.421582, -0.259396, 0.000000]]
pre_activation_mean: [-1.453585, 1.566927, 2.311968, -1.480892, 0.715191, 0.310447, -1.787658]
pre_activation_std: [2.500612, 3.363382, 1.983420, 2.564391, 0.914518, 2.918823, 3.355674]
### 4
mean: [-2.044354, -1.251500, 0.848314, -6.284146, -0.826804, -0.171816, 1.274425]
std: [5.509865, 3.019042, 1.992501, 6.305814, 1.287441, 2.858722, 2.910131]
fourier: [[86.291140, 89.450490, 93.896468, 103.185582, 183.991856], [45.193576, 45.352113, 53.325347, 68.985585, 112.634965], [28.866369, 29.638007, 36.606259, 37.703612, 76.348224], [100.836004, 107.946118, 116.805380, 136.735042, 565.573058], [19.569278, 20.044187, 22.317867, 22.364401, 74.412329], [42.105615, 43.671909, 44.636071, 45.451928, 54.612482], [48.036849, 52.069883, 52.197723, 63.348672, 114.698209]]
input_correlations: [[0.050988, -0.969020, -0.411834, -0.030787, 0.391295, -0.959404, -0.016161, 0.000000], [0.391541, -0.573497, -0.779984, -0.840566, 0.280341, -0.584308, -0.848460, 0.000000], [-0.138606, 0.344711, 0.504853, 0.988292, -0.283731, 0.338302, 0.989150, 0.000000], [0.272142, -0.872111, -0.858572, -0.522567, 0.171029, -0.885729, -0.523044, 0.000000], [-0.177215, -0.579660, -0.405966, -0.855171, 0.292677, -0.582402, -0.842896, 0.000000], [-0.085317, -0.880798, -0.189656, -0.332801, 0.626901, -0.860839, -0.311129, 0.000000], [-0.200198, 0.769521, 0.477583, -0.381344, -0.068816, 0.776828, -0.384394, 0.000000]]
pre_activation_mean: [-2.044354, -1.251500, 0.848314, -6.284146, -0.826804, -0.171816, 1.274425]
pre_activation_std: [5.509865, 3.019042, 1.992501, 6.305814, 1.287441, 2.858722, 2.910131]
### 6
mean: [2.133561, -0.259683, -2.517656, -0.112851, 1.533781, 1.926845, 0.394533]
std: [2.397420, 2.269515, 2.889115, 1.805161, 2.945257, 2.454656, 0.759252]
fourier: [[37.803871, 38.820701, 39.192959, 39.379665, 192.020511], [32.744453, 34.721318, 37.743135, 43.889424, 45.423706], [45.194265, 48.838587, 50.425013, 63.612329, 226.589043], [23.170655, 23.964847, 31.907809, 33.009952, 34.056668], [46.487352, 50.069167, 51.349261, 64.542293, 138.040326], [37.095569, 38.184393, 38.298477, 38.389119, 173.416106], [12.232719, 12.647061, 12.707235, 13.997027, 35.507945]]
input_correlations: [[0.198753, -0.578501, -0.126835, 0.643583, 0.233309, 0.399772, 0.828312, 0.000000], [-0.408757, 0.306085, 0.648485, -0.384103, -0.101596, -0.524406, -0.517659, 0.000000], [-0.087399, 0.225723, 0.446870, -0.365874, -0.101881, -0.219645, -0.869889, 0.000000], [-0.547877, 0.548724, 0.405828, -0.585853, -0.190707, -0.617246, -0.517203, 0.000000], [0.826337, -0.321942, 0.376625, 0.401901, 0.182821, 0.775865, -0.472107, 0.000000], [0.391553, -0.531938, -0.206747, 0.646219, 0.258065, 0.631379, 0.664082, 0.000000], [-0.146903, 0.222851, 0.750992, 0.007376, -0.115812, -0.428039, 0.355574, 0.000000]]
pre_activation_mean: [2.133561, -0.259683, -2.517656, -0.112851, 1.533781, 1.926845, 0.394533]
pre_activation_std: [2.397420, 2.269515, 2.889115, 1.805161, 2.945257, 2.454656, 0.759252]
### 8
mean: [-3.660943]
std: [4.546633]
fourier: [[74.629504, 75.363531, 78.974490, 83.298480, 329.484867]]
input_correlations: [[-0.808890, 0.497641, 0.193573, 0.691984, -0.640494, -0.916305, 0.147475, 0.000000]]
pre_activation_mean: [-3.660943]
pre_activation_std: [4.546633]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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[
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0.239695
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[
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-0.527621,
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[
0.307305,
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0.18721,
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[
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[
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"network.0.bias": [
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[
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[
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[
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"network.4.weight": [
[
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[
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"network.6.weight": [
[
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[
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[
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[
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[
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"network.8.weight": [
[
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}
## Activation Signature
### 0
mean: [2.222571, 0.603631, 0.119350, 0.582562, 1.939918, 2.110234, 0.372925]
std: [2.253705, 1.564458, 0.860899, 1.131688, 2.504867, 2.223501, 0.704360]
fourier: [[37.027913, 37.590686, 37.684300, 40.347377, 200.031359], [24.437480, 25.290684, 25.894125, 27.699902, 54.326816], [11.937786, 11.997788, 13.094748, 13.352301, 13.470584], [15.438628, 17.225105, 17.447434, 23.178511, 52.430601], [41.525671, 42.651899, 46.514646, 53.023139, 174.592633], [34.963090, 35.071394, 36.977870, 37.234754, 189.921062], [11.590362, 11.711132, 12.275826, 12.803174, 33.563224]]
input_correlations: [[-0.052477, 0.604743, -0.156663, 0.813885, 0.377375, 0.000000, 0.000000, 0.000000], [-0.008164, 0.327378, 0.750785, 0.622339, 0.140738, 0.000000, 0.000000, 0.000000], [0.633080, 0.130745, 0.794615, -0.424132, 0.338967, 0.000000, 0.000000, 0.000000], [-0.393221, -0.794106, -0.473507, -0.704050, -0.292841, 0.000000, 0.000000, 0.000000], [0.079979, -0.667674, 0.038083, -0.028935, 0.708652, 0.000000, 0.000000, 0.000000], [-0.448007, 0.147425, -0.130746, -0.155188, 0.563451, 0.000000, 0.000000, 0.000000], [-0.454673, -0.389051, 0.070735, 0.194725, 0.755437, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.652986, 2.191873, 1.911465, -6.150148, 0.385045, -0.453828, 0.590759]
pre_activation_std: [1.808105, 1.432524, 2.175916, 3.613172, 2.669925, 1.591441, 1.698436]
### 2
mean: [-1.453585, 1.566927, 2.311968, -1.480892, 0.715191, 0.310447, -1.787658]
std: [2.500612, 3.363382, 1.983420, 2.564391, 0.914518, 2.918823, 3.355674]
fourier: [[41.418158, 42.538398, 44.390860, 51.808842, 130.822662], [50.668004, 53.971809, 54.936600, 64.042430, 141.023428], [32.573584, 35.932850, 37.121476, 43.296300, 208.077111], [37.194197, 39.865403, 41.669365, 46.877929, 133.280329], [12.649914, 15.036108, 16.969842, 18.496297, 64.367241], [41.415344, 43.121185, 45.084485, 47.395276, 52.862053], [44.524983, 55.688265, 58.051398, 62.247741, 160.889250]]
input_correlations: [[0.078578, -0.087151, -0.528757, -0.183605, -0.895794, -0.441278, -0.797843, 0.000000], [0.313893, -0.070306, -0.026297, 0.073018, 0.886622, 0.630209, 0.934732, 0.000000], [-0.046244, 0.441058, 0.728090, 0.381206, 0.610668, 0.406390, 0.674035, 0.000000], [-0.906431, -0.423993, 0.547039, -0.296841, 0.153576, -0.326388, -0.213222, 0.000000], [0.254985, 0.723089, -0.068266, 0.320015, -0.618552, -0.214736, -0.298126, 0.000000], [0.205092, -0.102986, 0.025557, 0.066036, 0.869598, 0.670165, 0.935976, 0.000000], [-0.879082, -0.374518, 0.584213, -0.277061, 0.144702, -0.421582, -0.259396, 0.000000]]
pre_activation_mean: [-1.453585, 1.566927, 2.311968, -1.480892, 0.715191, 0.310447, -1.787658]
pre_activation_std: [2.500612, 3.363382, 1.983420, 2.564391, 0.914518, 2.918823, 3.355674]
### 4
mean: [-2.044354, -1.251500, 0.848314, -6.284146, -0.826804, -0.171816, 1.274425]
std: [5.509865, 3.019042, 1.992501, 6.305814, 1.287441, 2.858722, 2.910131]
fourier: [[86.291140, 89.450490, 93.896468, 103.185582, 183.991856], [45.193576, 45.352113, 53.325347, 68.985585, 112.634965], [28.866369, 29.638007, 36.606259, 37.703612, 76.348224], [100.836004, 107.946118, 116.805380, 136.735042, 565.573058], [19.569278, 20.044187, 22.317867, 22.364401, 74.412329], [42.105615, 43.671909, 44.636071, 45.451928, 54.612482], [48.036849, 52.069883, 52.197723, 63.348672, 114.698209]]
input_correlations: [[0.050988, -0.969020, -0.411834, -0.030787, 0.391295, -0.959404, -0.016161, 0.000000], [0.391541, -0.573497, -0.779984, -0.840566, 0.280341, -0.584308, -0.848460, 0.000000], [-0.138606, 0.344711, 0.504853, 0.988292, -0.283731, 0.338302, 0.989150, 0.000000], [0.272142, -0.872111, -0.858572, -0.522567, 0.171029, -0.885729, -0.523044, 0.000000], [-0.177215, -0.579660, -0.405966, -0.855171, 0.292677, -0.582402, -0.842896, 0.000000], [-0.085317, -0.880798, -0.189656, -0.332801, 0.626901, -0.860839, -0.311129, 0.000000], [-0.200198, 0.769521, 0.477583, -0.381344, -0.068816, 0.776828, -0.384394, 0.000000]]
pre_activation_mean: [-2.044354, -1.251500, 0.848314, -6.284146, -0.826804, -0.171816, 1.274425]
pre_activation_std: [5.509865, 3.019042, 1.992501, 6.305814, 1.287441, 2.858722, 2.910131]
### 6
mean: [2.133561, -0.259683, -2.517656, -0.112851, 1.533781, 1.926845, 0.394533]
std: [2.397420, 2.269515, 2.889115, 1.805161, 2.945257, 2.454656, 0.759252]
fourier: [[37.803871, 38.820701, 39.192959, 39.379665, 192.020511], [32.744453, 34.721318, 37.743135, 43.889424, 45.423706], [45.194265, 48.838587, 50.425013, 63.612329, 226.589043], [23.170655, 23.964847, 31.907809, 33.009952, 34.056668], [46.487352, 50.069167, 51.349261, 64.542293, 138.040326], [37.095569, 38.184393, 38.298477, 38.389119, 173.416106], [12.232719, 12.647061, 12.707235, 13.997027, 35.507945]]
input_correlations: [[0.198753, -0.578501, -0.126835, 0.643583, 0.233309, 0.399772, 0.828312, 0.000000], [-0.408757, 0.306085, 0.648485, -0.384103, -0.101596, -0.524406, -0.517659, 0.000000], [-0.087399, 0.225723, 0.446870, -0.365874, -0.101881, -0.219645, -0.869889, 0.000000], [-0.547877, 0.548724, 0.405828, -0.585853, -0.190707, -0.617246, -0.517203, 0.000000], [0.826337, -0.321942, 0.376625, 0.401901, 0.182821, 0.775865, -0.472107, 0.000000], [0.391553, -0.531938, -0.206747, 0.646219, 0.258065, 0.631379, 0.664082, 0.000000], [-0.146903, 0.222851, 0.750992, 0.007376, -0.115812, -0.428039, 0.355574, 0.000000]]
pre_activation_mean: [2.133561, -0.259683, -2.517656, -0.112851, 1.533781, 1.926845, 0.394533]
pre_activation_std: [2.397420, 2.269515, 2.889115, 1.805161, 2.945257, 2.454656, 0.759252]
### 8
mean: [-3.660943]
std: [4.546633]
fourier: [[74.629504, 75.363531, 78.974490, 83.298480, 329.484867]]
input_correlations: [[-0.808890, 0.497641, 0.193573, 0.691984, -0.640494, -0.916305, 0.147475, 0.000000]]
pre_activation_mean: [-3.660943]
pre_activation_std: [4.546633]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 2.2225708961486816, "std": 2.2537050247192383, "fourier": [37.0279128618002, 37.59068600636142, 37.6842995927678, 40.347376918312996, 200.0313585391268], "input_correlations": [-0.052476514568519254, 0.6047431663478473, -0.15666289179551254, 0.8138852725382335, 0.37737491578716187, 0.0, 0.0, 0.0], "pre_activation_mean": 1.65298593044281, "pre_activation_std": 1.8081046342849731}, "1": {"mean": 0.6036313772201538, "std": 1.5644584894180298, "fourier": [24.437480311846862, 25.290683792466144, 25.894125340680958, 27.699901697116434, 54.32681555975796], "input_correlations": [-0.008163504870016713, 0.32737838294401306, 0.7507848287191958, 0.6223389863501385, 0.1407375965138547, 0.0, 0.0, 0.0], "pre_activation_mean": 2.1918725967407227, "pre_activation_std": 1.4325240850448608}, "2": {"mean": 0.11935022473335266, "std": 0.8608993291854858, "fourier": [11.937786164095364, 11.997788429215037, 13.094748242349713, 13.352300887674563, 13.470584150266244], "input_correlations": [0.6330799120437888, 0.13074452545904805, 0.7946153392436958, -0.4241324923006694, 0.33896727799217685, 0.0, 0.0, 0.0], "pre_activation_mean": 1.9114652872085571, "pre_activation_std": 2.1759161949157715}, "3": {"mean": 0.5825623273849487, "std": 1.1316884756088257, "fourier": [15.43862764259923, 17.22510459521445, 17.447433769166697, 23.17851062513266, 52.43060111289378], "input_correlations": [-0.3932211710775165, -0.7941064323287128, -0.47350682744352357, -0.7040502404060697, -0.29284112381550276, 0.0, 0.0, 0.0], "pre_activation_mean": -6.150148391723633, "pre_activation_std": 3.6131722927093506}, "4": {"mean": 1.9399181604385376, "std": 2.5048673152923584, "fourier": [41.5256710068514, 42.651899430189935, 46.51464594037415, 53.023138767341216, 174.592633454944], "input_correlations": [0.0799791754210831, -0.6676737909485728, 0.03808262405744594, -0.02893452055963784, 0.7086521463470106, 0.0, 0.0, 0.0], "pre_activation_mean": 0.38504528999328613, "pre_activation_std": 2.6699254512786865}, "5": {"mean": 2.110234260559082, "std": 2.223500967025757, "fourier": [34.96308983052961, 35.071394239598405, 36.977869762406314, 37.234754469327605, 189.9210624229163], "input_correlations": [-0.4480069987759405, 0.14742518941830798, -0.13074633047585435, -0.15518845255212627, 0.5634505325720447, 0.0, 0.0, 0.0], "pre_activation_mean": -0.4538283944129944, "pre_activation_std": 1.5914406776428223}, "6": {"mean": 0.37292471528053284, "std": 0.7043604850769043, "fourier": [11.590362266480215, 11.711132036826921, 12.275825836807778, 12.803174330846801, 33.56322380062193], "input_correlations": [-0.4546726034102153, -0.3890509777489915, 0.0707352955819211, 0.19472470765045116, 0.7554368103867782, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5907593369483948, "pre_activation_std": 1.6984355449676514}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", 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"val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.1819181740283966, "train_acc": 0.96, "val_loss": 0.17222917079925537, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.16939033567905426, "train_acc": 0.955, "val_loss": 0.16458716988563538, "val_acc": 0.94}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["alternating"], "degraded_stage": {"initial_val_loss": 0.7094525098800659, "final_val_loss": 0.6448755860328674, "initial_val_acc": 0.48, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.6324295997619629, "final_val_loss": 0.16458716988563538, "initial_val_acc": 0.62, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 10}, "improvement": 0.36, "first_improvement_epoch": 1}} |
76 | {"target_pattern": "has_majority", "degraded_accuracy": 0.4, "improved_accuracy": 0.78, "improvement": 0.38, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8497, "learning_rate": 0.09416931889116947, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "has_majority", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["has_majority"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.269712, 0.000302, 0.502467, 0.000000, 0.456595]
std: [0.000000, 0.000000, 0.121032, 0.000814, 0.131059, 0.000000, 0.373137]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.797695, 1.832097, 1.920586, 2.101518, 24.274083], [0.012545, 0.012911, 0.013928, 0.017258, 0.027222], [1.857261, 2.056449, 2.061289, 2.278959, 45.222050], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.475858, 5.564913, 5.894870, 6.595084, 41.093574]]
input_correlations: [[0.195799, 0.555969, 0.521477, 0.821781, 0.366279, 0.000000, 0.000000, 0.000000], [-0.114746, 0.593155, 0.454365, 0.775793, -0.005799, 0.000000, 0.000000, 0.000000], [-0.231375, 0.434481, 0.279104, 0.779528, 0.496467, 0.000000, 0.000000, 0.000000], [-0.146725, 0.107847, 0.562450, 0.706971, 0.457685, 0.000000, 0.000000, 0.000000], [-0.641793, -0.633967, -0.693475, -0.356261, -0.534081, 0.000000, 0.000000, 0.000000], [-0.899315, -0.174360, -0.239193, 0.476243, -0.103867, 0.000000, 0.000000, 0.000000], [-0.776631, -0.170047, 0.286239, 0.324786, 0.036871, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.227562, 2.296968, 1.922495, 1.780477, -3.118159, -0.277932, 0.366037]
pre_activation_std: [1.605688, 1.843516, 1.432106, 1.810927, 1.868610, 1.340898, 1.208361]
### 2
mean: [1.604104, -3.079703, 2.666501, -2.834090, 0.707148, 3.959727, -3.800936]
std: [0.900532, 1.880996, 1.993905, 2.030571, 0.800561, 2.607048, 2.334547]
fourier: [[13.476638, 14.664400, 14.731087, 15.014221, 144.369365], [27.905394, 27.958522, 30.672713, 32.143610, 277.173302], [28.445237, 29.827625, 32.394855, 33.824243, 239.985116], [29.997983, 30.059724, 33.069193, 37.923803, 255.068134], [12.283699, 12.499436, 13.308991, 14.311059, 63.643320], [38.303201, 38.960237, 41.211110, 46.982208, 356.375466], [33.944162, 35.686847, 36.161808, 42.103280, 342.084234]]
input_correlations: [[0.891095, 0.992099, 0.770724, 0.764762, 0.000000, 0.649966, 0.662810, 0.000000], [-0.960623, -0.928734, -0.957442, -0.862375, 0.000000, -0.699467, -0.582311, 0.000000], [0.943159, 0.971370, 0.908203, 0.845400, 0.000000, 0.736350, 0.642065, 0.000000], [-0.990286, -0.923453, -0.898399, -0.885074, 0.000000, -0.643107, -0.557822, 0.000000], [0.926652, 0.902435, 0.942706, 0.742323, 0.000000, 0.691395, 0.432953, 0.000000], [0.961168, 0.919828, 0.928254, 0.929971, 0.000000, 0.682190, 0.670526, 0.000000], [-0.973950, -0.891688, -0.946975, -0.917017, 0.000000, -0.651990, -0.595886, 0.000000]]
pre_activation_mean: [1.604104, -3.079703, 2.666501, -2.834090, 0.707148, 3.959727, -3.800936]
pre_activation_std: [0.900532, 1.880996, 1.993905, 2.030571, 0.800561, 2.607048, 2.334547]
### 4
mean: [-2.457832, 2.966487, 1.066597, -4.170939, 1.750383, 2.909199, -2.684279]
std: [1.608717, 2.006094, 0.643611, 2.791305, 1.378474, 2.304555, 1.877574]
fourier: [[23.269199, 23.981420, 25.466805, 29.037119, 221.204847], [29.363265, 30.865527, 32.061509, 35.352305, 266.983812], [9.790920, 10.164425, 10.404023, 11.359557, 95.993747], [41.075280, 42.955262, 44.036943, 48.928718, 375.384504], [19.375749, 20.621997, 22.551461, 24.364829, 157.534491], [32.987277, 34.171692, 36.791525, 40.203615, 261.827945], [27.116368, 28.667741, 29.506534, 33.012915, 241.585122]]
input_correlations: [[-0.936177, 0.000000, -0.983307, 0.000000, -0.899487, -0.998826, 0.000000, 0.000000], [0.964795, 0.000000, 0.994000, 0.000000, 0.903576, 0.989085, 0.000000, 0.000000], [0.915422, 0.000000, 0.977671, 0.000000, 0.988639, 0.941083, 0.000000, 0.000000], [-0.964773, 0.000000, -0.997071, 0.000000, -0.918860, -0.987447, 0.000000, 0.000000], [0.947558, 0.000000, 0.989958, 0.000000, 0.901274, 0.995361, 0.000000, 0.000000], [0.948170, 0.000000, 0.996869, 0.000000, 0.938189, 0.990059, 0.000000, 0.000000], [-0.953368, 0.000000, -0.996086, 0.000000, -0.925603, -0.991921, 0.000000, 0.000000]]
pre_activation_mean: [-2.457832, 2.966487, 1.066597, -4.170939, 1.750383, 2.909199, -2.684279]
pre_activation_std: [1.608717, 2.006094, 0.643611, 2.791305, 1.378474, 2.304555, 1.877574]
### 6
mean: [1.979834, 2.146210, -1.570901, -0.868300, -1.191122, -3.337529, -0.597488]
std: [1.168660, 1.520104, 0.977685, 0.708253, 0.654937, 2.294759, 0.310753]
fourier: [[17.030282, 17.509442, 18.589514, 20.433956, 178.185059], [22.083365, 23.556799, 23.569249, 26.830250, 193.158898], [14.216625, 15.064394, 15.398259, 17.255382, 141.381120], [10.464952, 10.586680, 11.886671, 12.107250, 78.147018], [9.522275, 9.676800, 10.898809, 11.666016, 107.200974], [33.451896, 34.447728, 36.433422, 40.174391, 300.377672], [4.518460, 4.595732, 4.918472, 5.465971, 53.773920]]
input_correlations: [[0.000000, 0.996932, 0.972960, 0.000000, 0.996219, 0.999604, 0.000000, 0.000000], [0.000000, 0.998046, 0.964258, 0.000000, 0.998806, 0.998714, 0.000000, 0.000000], [0.000000, -0.999105, -0.960076, 0.000000, -0.999074, -0.997593, 0.000000, 0.000000], [0.000000, -0.974677, -0.996578, 0.000000, -0.973095, -0.990764, 0.000000, 0.000000], [0.000000, -0.998580, -0.938951, 0.000000, -0.998256, -0.990513, 0.000000, 0.000000], [0.000000, -0.997051, -0.972376, 0.000000, -0.996459, -0.999600, 0.000000, 0.000000], [0.000000, -0.994542, -0.974345, 0.000000, -0.995955, -0.999904, 0.000000, 0.000000]]
pre_activation_mean: [1.979834, 2.146210, -1.570901, -0.868300, -1.191122, -3.337529, -0.597488]
pre_activation_std: [1.168660, 1.520104, 0.977685, 0.708253, 0.654937, 2.294759, 0.310753]
### 8
mean: [-1.391011, 1.367664, -0.513269, 0.522933, -0.870909, -1.611438, -0.796877]
std: [0.814681, 0.864447, 0.068683, 0.506641, 0.469270, 0.993385, 0.111681]
fourier: [[11.853408, 12.470871, 12.755059, 14.333510, 125.190994], [12.586326, 13.116889, 13.624856, 15.170758, 123.089746], [1.001681, 1.003042, 1.147937, 1.171125, 46.194251], [7.373913, 7.711127, 7.966996, 8.897587, 47.063968], [6.840771, 7.001353, 7.486492, 8.196048, 78.381791], [14.444846, 15.277812, 15.495738, 17.496738, 145.029446], [1.691286, 1.694048, 1.850090, 1.934104, 71.718966]]
input_correlations: [[-0.999717, -0.999893, 0.000000, 0.426179, 0.000000, 0.000000, 0.000000, 0.000000], [0.999903, 0.999700, 0.000000, -0.426382, 0.000000, 0.000000, 0.000000, 0.000000], [-0.996552, -0.992631, 0.000000, 0.424387, 0.000000, 0.000000, 0.000000, 0.000000], [0.999851, 0.999777, 0.000000, -0.426558, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999990, -0.999079, 0.000000, 0.426417, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999578, -0.999956, 0.000000, 0.426357, 0.000000, 0.000000, 0.000000, 0.000000], [-0.987953, -0.981280, 0.000000, 0.421526, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.391011, 1.367664, -0.513269, 0.522933, -0.870909, -1.611438, -0.796877]
pre_activation_std: [0.814681, 0.864447, 0.068683, 0.506641, 0.469270, 0.993385, 0.111681]
### 10
mean: [-0.569541, -0.273860, 0.268228, -0.745567, 0.502467, -0.701094, 0.451802]
std: [0.060116, 0.177954, 0.124528, 0.579017, 0.131059, 0.258386, 0.379107]
fourier: [[0.877776, 0.908337, 0.947833, 1.055924, 51.258662], [2.636414, 2.687212, 2.810029, 3.151281, 24.647424], [1.904081, 1.914143, 1.962780, 2.209925, 24.140545], [8.503553, 8.670962, 9.134780, 10.187485, 67.101028], [1.857261, 2.056449, 2.061289, 2.278959, 45.222050], [3.742608, 3.950123, 4.069691, 4.527194, 63.098478], [5.594495, 5.633279, 5.983379, 6.679004, 40.662224]]
input_correlations: [[0.000000, -0.999981, 0.000000, -0.996564, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.996284, 0.000000, -0.999996, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.990730, 0.000000, -0.998886, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999822, 0.000000, -0.997540, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.998507, 0.000000, 0.989691, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999940, 0.000000, -0.994999, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999556, 0.000000, 0.998244, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.569541, -0.273860, 0.268228, -0.745567, 0.502467, -0.701094, 0.451802]
pre_activation_std: [0.060116, 0.177954, 0.124528, 0.579017, 0.131059, 0.258386, 0.379107]
### 12
mean: [0.270888]
std: [0.124440]
fourier: [[1.856215, 1.890827, 1.969844, 2.188714, 24.379961]]
input_correlations: [[0.000000, 0.000000, 0.999456, 0.411871, -0.985717, 0.000000, -0.997907, 0.000000]]
pre_activation_mean: [0.270888]
pre_activation_std: [0.124440]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| has_majority | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.269712, 0.000302, 0.502467, 0.000000, 0.456595]
std: [0.000000, 0.000000, 0.121032, 0.000814, 0.131059, 0.000000, 0.373137]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.797695, 1.832097, 1.920586, 2.101518, 24.274083], [0.012545, 0.012911, 0.013928, 0.017258, 0.027222], [1.857261, 2.056449, 2.061289, 2.278959, 45.222050], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.475858, 5.564913, 5.894870, 6.595084, 41.093574]]
input_correlations: [[0.195799, 0.555969, 0.521477, 0.821781, 0.366279, 0.000000, 0.000000, 0.000000], [-0.114746, 0.593155, 0.454365, 0.775793, -0.005799, 0.000000, 0.000000, 0.000000], [-0.231375, 0.434481, 0.279104, 0.779528, 0.496467, 0.000000, 0.000000, 0.000000], [-0.146725, 0.107847, 0.562450, 0.706971, 0.457685, 0.000000, 0.000000, 0.000000], [-0.641793, -0.633967, -0.693475, -0.356261, -0.534081, 0.000000, 0.000000, 0.000000], [-0.899315, -0.174360, -0.239193, 0.476243, -0.103867, 0.000000, 0.000000, 0.000000], [-0.776631, -0.170047, 0.286239, 0.324786, 0.036871, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.227562, 2.296968, 1.922495, 1.780477, -3.118159, -0.277932, 0.366037]
pre_activation_std: [1.605688, 1.843516, 1.432106, 1.810927, 1.868610, 1.340898, 1.208361]
### 2
mean: [1.604104, -3.079703, 2.666501, -2.834090, 0.707148, 3.959727, -3.800936]
std: [0.900532, 1.880996, 1.993905, 2.030571, 0.800561, 2.607048, 2.334547]
fourier: [[13.476638, 14.664400, 14.731087, 15.014221, 144.369365], [27.905394, 27.958522, 30.672713, 32.143610, 277.173302], [28.445237, 29.827625, 32.394855, 33.824243, 239.985116], [29.997983, 30.059724, 33.069193, 37.923803, 255.068134], [12.283699, 12.499436, 13.308991, 14.311059, 63.643320], [38.303201, 38.960237, 41.211110, 46.982208, 356.375466], [33.944162, 35.686847, 36.161808, 42.103280, 342.084234]]
input_correlations: [[0.891095, 0.992099, 0.770724, 0.764762, 0.000000, 0.649966, 0.662810, 0.000000], [-0.960623, -0.928734, -0.957442, -0.862375, 0.000000, -0.699467, -0.582311, 0.000000], [0.943159, 0.971370, 0.908203, 0.845400, 0.000000, 0.736350, 0.642065, 0.000000], [-0.990286, -0.923453, -0.898399, -0.885074, 0.000000, -0.643107, -0.557822, 0.000000], [0.926652, 0.902435, 0.942706, 0.742323, 0.000000, 0.691395, 0.432953, 0.000000], [0.961168, 0.919828, 0.928254, 0.929971, 0.000000, 0.682190, 0.670526, 0.000000], [-0.973950, -0.891688, -0.946975, -0.917017, 0.000000, -0.651990, -0.595886, 0.000000]]
pre_activation_mean: [1.604104, -3.079703, 2.666501, -2.834090, 0.707148, 3.959727, -3.800936]
pre_activation_std: [0.900532, 1.880996, 1.993905, 2.030571, 0.800561, 2.607048, 2.334547]
### 4
mean: [-2.457832, 2.966487, 1.066597, -4.170939, 1.750383, 2.909199, -2.684279]
std: [1.608717, 2.006094, 0.643611, 2.791305, 1.378474, 2.304555, 1.877574]
fourier: [[23.269199, 23.981420, 25.466805, 29.037119, 221.204847], [29.363265, 30.865527, 32.061509, 35.352305, 266.983812], [9.790920, 10.164425, 10.404023, 11.359557, 95.993747], [41.075280, 42.955262, 44.036943, 48.928718, 375.384504], [19.375749, 20.621997, 22.551461, 24.364829, 157.534491], [32.987277, 34.171692, 36.791525, 40.203615, 261.827945], [27.116368, 28.667741, 29.506534, 33.012915, 241.585122]]
input_correlations: [[-0.936177, 0.000000, -0.983307, 0.000000, -0.899487, -0.998826, 0.000000, 0.000000], [0.964795, 0.000000, 0.994000, 0.000000, 0.903576, 0.989085, 0.000000, 0.000000], [0.915422, 0.000000, 0.977671, 0.000000, 0.988639, 0.941083, 0.000000, 0.000000], [-0.964773, 0.000000, -0.997071, 0.000000, -0.918860, -0.987447, 0.000000, 0.000000], [0.947558, 0.000000, 0.989958, 0.000000, 0.901274, 0.995361, 0.000000, 0.000000], [0.948170, 0.000000, 0.996869, 0.000000, 0.938189, 0.990059, 0.000000, 0.000000], [-0.953368, 0.000000, -0.996086, 0.000000, -0.925603, -0.991921, 0.000000, 0.000000]]
pre_activation_mean: [-2.457832, 2.966487, 1.066597, -4.170939, 1.750383, 2.909199, -2.684279]
pre_activation_std: [1.608717, 2.006094, 0.643611, 2.791305, 1.378474, 2.304555, 1.877574]
### 6
mean: [1.979834, 2.146210, -1.570901, -0.868300, -1.191122, -3.337529, -0.597488]
std: [1.168660, 1.520104, 0.977685, 0.708253, 0.654937, 2.294759, 0.310753]
fourier: [[17.030282, 17.509442, 18.589514, 20.433956, 178.185059], [22.083365, 23.556799, 23.569249, 26.830250, 193.158898], [14.216625, 15.064394, 15.398259, 17.255382, 141.381120], [10.464952, 10.586680, 11.886671, 12.107250, 78.147018], [9.522275, 9.676800, 10.898809, 11.666016, 107.200974], [33.451896, 34.447728, 36.433422, 40.174391, 300.377672], [4.518460, 4.595732, 4.918472, 5.465971, 53.773920]]
input_correlations: [[0.000000, 0.996932, 0.972960, 0.000000, 0.996219, 0.999604, 0.000000, 0.000000], [0.000000, 0.998046, 0.964258, 0.000000, 0.998806, 0.998714, 0.000000, 0.000000], [0.000000, -0.999105, -0.960076, 0.000000, -0.999074, -0.997593, 0.000000, 0.000000], [0.000000, -0.974677, -0.996578, 0.000000, -0.973095, -0.990764, 0.000000, 0.000000], [0.000000, -0.998580, -0.938951, 0.000000, -0.998256, -0.990513, 0.000000, 0.000000], [0.000000, -0.997051, -0.972376, 0.000000, -0.996459, -0.999600, 0.000000, 0.000000], [0.000000, -0.994542, -0.974345, 0.000000, -0.995955, -0.999904, 0.000000, 0.000000]]
pre_activation_mean: [1.979834, 2.146210, -1.570901, -0.868300, -1.191122, -3.337529, -0.597488]
pre_activation_std: [1.168660, 1.520104, 0.977685, 0.708253, 0.654937, 2.294759, 0.310753]
### 8
mean: [-1.391011, 1.367664, -0.513269, 0.522933, -0.870909, -1.611438, -0.796877]
std: [0.814681, 0.864447, 0.068683, 0.506641, 0.469270, 0.993385, 0.111681]
fourier: [[11.853408, 12.470871, 12.755059, 14.333510, 125.190994], [12.586326, 13.116889, 13.624856, 15.170758, 123.089746], [1.001681, 1.003042, 1.147937, 1.171125, 46.194251], [7.373913, 7.711127, 7.966996, 8.897587, 47.063968], [6.840771, 7.001353, 7.486492, 8.196048, 78.381791], [14.444846, 15.277812, 15.495738, 17.496738, 145.029446], [1.691286, 1.694048, 1.850090, 1.934104, 71.718966]]
input_correlations: [[-0.999717, -0.999893, 0.000000, 0.426179, 0.000000, 0.000000, 0.000000, 0.000000], [0.999903, 0.999700, 0.000000, -0.426382, 0.000000, 0.000000, 0.000000, 0.000000], [-0.996552, -0.992631, 0.000000, 0.424387, 0.000000, 0.000000, 0.000000, 0.000000], [0.999851, 0.999777, 0.000000, -0.426558, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999990, -0.999079, 0.000000, 0.426417, 0.000000, 0.000000, 0.000000, 0.000000], [-0.999578, -0.999956, 0.000000, 0.426357, 0.000000, 0.000000, 0.000000, 0.000000], [-0.987953, -0.981280, 0.000000, 0.421526, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.391011, 1.367664, -0.513269, 0.522933, -0.870909, -1.611438, -0.796877]
pre_activation_std: [0.814681, 0.864447, 0.068683, 0.506641, 0.469270, 0.993385, 0.111681]
### 10
mean: [-0.569541, -0.273860, 0.268228, -0.745567, 0.502467, -0.701094, 0.451802]
std: [0.060116, 0.177954, 0.124528, 0.579017, 0.131059, 0.258386, 0.379107]
fourier: [[0.877776, 0.908337, 0.947833, 1.055924, 51.258662], [2.636414, 2.687212, 2.810029, 3.151281, 24.647424], [1.904081, 1.914143, 1.962780, 2.209925, 24.140545], [8.503553, 8.670962, 9.134780, 10.187485, 67.101028], [1.857261, 2.056449, 2.061289, 2.278959, 45.222050], [3.742608, 3.950123, 4.069691, 4.527194, 63.098478], [5.594495, 5.633279, 5.983379, 6.679004, 40.662224]]
input_correlations: [[0.000000, -0.999981, 0.000000, -0.996564, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.996284, 0.000000, -0.999996, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.990730, 0.000000, -0.998886, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999822, 0.000000, -0.997540, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.998507, 0.000000, 0.989691, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999940, 0.000000, -0.994999, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999556, 0.000000, 0.998244, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.569541, -0.273860, 0.268228, -0.745567, 0.502467, -0.701094, 0.451802]
pre_activation_std: [0.060116, 0.177954, 0.124528, 0.579017, 0.131059, 0.258386, 0.379107]
### 12
mean: [0.270888]
std: [0.124440]
fourier: [[1.856215, 1.890827, 1.969844, 2.188714, 24.379961]]
input_correlations: [[0.000000, 0.000000, 0.999456, 0.411871, -0.985717, 0.000000, -0.997907, 0.000000]]
pre_activation_mean: [0.270888]
pre_activation_std: [0.124440]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
has_majority | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.19579936938265946, 0.5559685346757394, 0.5214769253500205, 0.8217806481893526, 0.3662792085135106, 0.0, 0.0, 0.0], "pre_activation_mean": 2.2275617122650146, "pre_activation_std": 1.6056877374649048}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.1147456038270277, 0.5931546356922539, 0.4543647892169211, 0.7757926383797292, -0.0057987574038043995, 0.0, 0.0, 0.0], "pre_activation_mean": 2.2969675064086914, "pre_activation_std": 1.8435161113739014}, "2": {"mean": 0.26971203088760376, "std": 0.12103182822465897, "fourier": [1.7976945410348761, 1.8320970788783695, 1.9205864838741962, 2.101517599087058, 24.274083092808723], "input_correlations": [-0.23137538276957537, 0.4344809966711759, 0.2791036339336605, 0.7795279256666438, 0.49646680965554285, 0.0, 0.0, 0.0], "pre_activation_mean": 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7, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.010302, 0.199591, 0.3564, 0.549889, 0.14728], [-0.310838, 0.380123, 0.477914, 0.574439, -0.149117], [-0.338784, 0.271331, 0.185976, 0.392226, 0.344538], [-0.276322, -0.15431, 0.586612, 0.603331, 0.269321], [-0.303737, -0.369945, -0.414301, -0.173619, -0.358026], [-0.57741, -0.031662, 0.032392, 0.290026, -0.017285], [-0.549821, -0.060634, 0.366173, 0.173597, 0.021263]], "network.0.bias": [-0.228649, -0.055132, 0.195148, -0.445809, -0.386742, -0.169969, -0.002642], "network.2.weight": [[0.176545, 0.422728, -0.165818, -0.014829, -0.133078, 0.078443, 0.138786], [-0.423463, -0.255678, -0.575794, 0.014073, 0.08965, -0.207518, -0.002787], [0.381739, 0.52133, 0.24114, -0.020511, -0.389827, 0.501131, 0.124339], [-0.612707, -0.369367, -0.039722, -0.365756, -0.29631, -0.079155, 0.323463], [0.191235, 0.127543, 0.353098, -0.146888, 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"degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7199333906173706, "train_acc": 0.49, "val_loss": 0.8404803276062012, "val_acc": 0.4}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6668897271156311, "train_acc": 0.605, "val_loss": 0.6973326206207275, "val_acc": 0.4}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6668118238449097, "train_acc": 0.55, "val_loss": 0.637615442276001, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.6555252969264984, "train_acc": 0.64, "val_loss": 0.634085476398468, "val_acc": 0.62}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6264969408512115, "train_acc": 0.63, "val_loss": 0.5754181146621704, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.62592813372612, "train_acc": 0.655, "val_loss": 0.6119725704193115, "val_acc": 0.68}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.6224791407585144, "train_acc": 0.645, "val_loss": 0.552687406539917, "val_acc": 0.76}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.6149157583713531, "train_acc": 0.655, "val_loss": 0.5784909129142761, "val_acc": 0.66}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.6129427850246429, "train_acc": 0.645, "val_loss": 0.5622002482414246, "val_acc": 0.68}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.5955147743225098, "train_acc": 0.655, "val_loss": 0.5603671669960022, "val_acc": 0.7}], "summary": {"total_epochs": 10, "degraded_epochs": 2, "improved_epochs": 8, "patterns": ["has_majority"], "degraded_stage": {"initial_val_loss": 0.8404803276062012, "final_val_loss": 0.6973326206207275, "initial_val_acc": 0.4, "final_val_acc": 0.4, "best_val_acc": 0.4}, "improved_stage": {"initial_val_loss": 0.637615442276001, "final_val_loss": 0.5603671669960022, "initial_val_acc": 0.78, "final_val_acc": 0.7, "best_val_acc": 0.78, "best_epoch": 2}, "improvement": 0.38, "first_improvement_epoch": 1}} |
77 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.66, "improved_accuracy": 0.94, "improvement": 0.2799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8766, "learning_rate": 0.019359730823269184, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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"network.10.weight": [
[
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"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 1.038592, 0.795376, 0.000000, 2.028892, 2.907359, 4.801768]
std: [0.000000, 0.000000, 1.451243, 1.232432, 0.000000, 1.413290, 1.950766, 2.908925]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [24.024625, 25.741071, 25.758812, 26.600287, 93.473302], [20.239112, 21.306347, 22.599552, 23.573442, 71.583836], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [22.945559, 23.727454, 24.058527, 27.498235, 182.600273], [31.460007, 32.070278, 33.191271, 37.666066, 261.662289], [43.710932, 48.335367, 50.481261, 56.381622, 432.159127]]
input_correlations: [[-0.839888, -0.429037, 0.071613, 0.223008, 0.197242, 0.000000, 0.000000, 0.000000], [-0.032004, -0.420053, -0.461225, -0.882024, -0.121353, 0.000000, 0.000000, 0.000000], [-0.478611, -0.683804, -0.582955, -0.595853, -0.515269, 0.000000, 0.000000, 0.000000], [-0.464331, 0.002220, 0.533899, 0.379909, 0.463965, 0.000000, 0.000000, 0.000000], [0.811244, 0.390089, 0.715273, -0.061816, -0.089554, 0.000000, 0.000000, 0.000000], [0.395411, -0.171075, 0.748427, -0.609848, 0.116399, 0.000000, 0.000000, 0.000000], [0.650033, 0.629983, 0.378409, 0.590428, 0.538021, 0.000000, 0.000000, 0.000000], [-0.280728, -0.703653, -0.635525, -0.530437, -0.516958, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.416836, -2.769680, -1.956768, 1.440713, 1.239501, 0.508209, 3.137891, -2.648718]
pre_activation_std: [0.458228, 1.576988, 1.396251, 1.614436, 1.638924, 1.258674, 2.241359, 1.457033]
### 2
mean: [1.847392, 0.217487, 1.416999, 1.234155, -1.852534, 0.424449, 0.290612, 2.759054]
std: [1.269482, 0.565517, 0.883065, 1.315002, 1.067442, 0.528403, 0.518086, 1.564165]
fourier: [[21.787709, 22.173599, 22.748800, 23.161021, 166.265299], [9.130912, 9.174065, 9.455885, 9.950209, 19.573793], [13.868122, 14.155582, 14.591873, 17.268631, 127.529912], [23.372151, 23.473094, 23.675565, 24.314030, 111.073990], [17.244423, 18.792312, 18.807786, 21.005749, 166.728061], [7.878509, 8.348864, 8.904116, 9.307271, 38.200441], [7.679274, 7.792816, 8.928089, 9.175372, 26.155103], [23.180365, 25.722550, 26.226998, 31.770168, 248.314878]]
input_correlations: [[0.580985, 0.000000, -0.419789, 0.920652, 0.015926, 0.153977, 0.528127, 0.000000], [-0.849159, 0.000000, -0.122127, -0.509820, 0.526398, 0.030345, 0.679135, 0.000000], [0.740890, 0.000000, -0.355851, 0.974459, -0.068769, 0.273379, 0.262000, 0.000000], [-0.731464, 0.000000, -0.271715, -0.261982, 0.865168, 0.331071, 0.767436, 0.000000], [0.034419, 0.000000, 0.508135, -0.496917, -0.475452, -0.079901, -0.964535, 0.000000], [-0.703153, 0.000000, -0.268798, -0.286684, 0.583907, 0.025550, 0.848180, 0.000000], [-0.736489, 0.000000, -0.101300, -0.530364, 0.447480, -0.313316, 0.626991, 0.000000], [-0.011826, 0.000000, -0.525480, 0.570368, 0.724913, 0.461771, 0.842727, 0.000000]]
pre_activation_mean: [1.847392, 0.217487, 1.416999, 1.234155, -1.852534, 0.424449, 0.290612, 2.759054]
pre_activation_std: [1.269482, 0.565517, 0.883065, 1.315002, 1.067442, 0.528403, 0.518086, 1.564165]
### 4
mean: [1.752349, -1.358568, 0.806931, 2.128135, 1.464062, 0.610347, 3.461772, -1.642882]
std: [1.263020, 0.702537, 1.012066, 1.602893, 1.083723, 0.345327, 1.647543, 0.641848]
fourier: [[20.016895, 20.538766, 23.107243, 26.841258, 157.711401], [11.188705, 11.742184, 11.802388, 12.425950, 122.271107], [16.892632, 17.681752, 17.821006, 18.272692, 72.623742], [26.088263, 26.588194, 28.560510, 30.233385, 191.532151], [17.044271, 17.614479, 18.641490, 20.644951, 131.765600], [5.270264, 5.506979, 6.366247, 6.393265, 54.931250], [26.556240, 26.704643, 26.739266, 29.215304, 311.559487], [10.482379, 10.697304, 10.980831, 12.467813, 147.859380]]
input_correlations: [[0.456031, 0.806763, 0.243219, 0.867695, 0.000000, 0.856001, 0.678104, 0.922226], [-0.862088, -0.286050, -0.770123, -0.394521, 0.000000, -0.380991, -0.152505, -0.954971], [-0.180504, 0.928822, -0.387580, 0.983669, 0.000000, 0.897861, 0.924093, 0.545707], [0.970003, -0.216306, 0.988630, -0.150797, 0.000000, -0.105097, -0.357534, 0.648924], [0.912494, -0.438559, 0.984361, -0.398382, 0.000000, -0.332384, -0.578257, 0.426590], [0.625127, -0.646655, 0.720348, -0.750175, 0.000000, -0.546952, -0.727523, -0.126014], [0.930690, 0.196689, 0.855077, 0.272868, 0.000000, 0.298707, 0.030474, 0.899898], [-0.885632, -0.386063, -0.731959, -0.408931, 0.000000, -0.506858, -0.245188, -0.900766]]
pre_activation_mean: [1.752349, -1.358568, 0.806931, 2.128135, 1.464062, 0.610347, 3.461772, -1.642882]
pre_activation_std: [1.263020, 0.702537, 1.012066, 1.602893, 1.083723, 0.345327, 1.647543, 0.641848]
### 6
mean: [2.507741, 0.609717, 0.227308, 3.161386, 2.854001, 0.654131, -0.864510, 3.066094]
std: [1.389494, 0.991991, 0.724402, 2.098933, 1.268842, 1.280329, 0.232570, 1.563913]
fourier: [[22.020381, 23.855789, 24.274888, 26.055256, 225.696713], [15.793361, 16.305466, 18.203324, 18.434312, 54.874541], [11.417892, 11.504398, 12.895034, 13.436666, 20.457693], [33.068658, 34.587357, 36.057472, 40.275381, 284.524740], [19.612455, 20.364670, 22.860745, 23.760031, 256.860061], [21.181558, 21.553225, 22.629362, 23.524364, 58.871831], [3.906048, 4.286292, 4.443999, 4.926561, 77.805868], [25.145084, 26.897983, 27.326890, 29.362678, 275.948466]]
input_correlations: [[0.411066, 0.000000, -0.193741, 0.995792, 0.957515, 0.631576, 0.933428, 0.000000], [0.610920, 0.000000, 0.954327, -0.523234, -0.699014, -0.887931, -0.122804, 0.000000], [0.457186, 0.000000, 0.890407, -0.664632, -0.814435, -0.920316, -0.297253, 0.000000], [0.162514, 0.000000, -0.441298, 0.978505, 0.998523, 0.780853, 0.809447, 0.000000], [0.869313, 0.000000, 0.423061, 0.766354, 0.604191, 0.094033, 0.963765, 0.000000], [0.692656, 0.000000, 0.978880, -0.429072, -0.618907, -0.852919, -0.015491, 0.000000], [-0.990157, 0.000000, -0.811868, -0.332676, -0.118030, 0.321172, -0.692623, 0.000000], [0.424535, 0.000000, -0.178595, 0.995208, 0.953874, 0.616989, 0.938980, 0.000000]]
pre_activation_mean: [2.507741, 0.609717, 0.227308, 3.161386, 2.854001, 0.654131, -0.864510, 3.066094]
pre_activation_std: [1.389494, 0.991991, 0.724402, 2.098933, 1.268842, 1.280329, 0.232570, 1.563913]
### 8
mean: [-1.100167, -2.073618, 0.915061, 0.483472, -2.005740, 1.966994, 2.901344, 4.801768]
std: [0.368996, 1.233276, 1.555560, 1.494479, 0.915500, 1.509048, 1.959884, 2.908925]
fourier: [[5.778920, 6.009216, 6.673129, 6.855510, 99.015051], [19.217548, 20.714266, 21.546119, 23.514316, 186.625644], [25.796983, 26.033561, 26.940420, 28.915217, 82.355538], [24.149853, 24.627514, 25.949349, 28.128955, 43.512436], [14.371825, 15.388108, 16.036644, 17.374299, 180.516580], [24.540669, 25.023886, 25.680490, 28.877081, 177.029501], [31.811716, 31.944642, 33.355407, 37.710079, 261.120938], [43.710932, 48.335367, 50.481261, 56.381622, 432.159127]]
input_correlations: [[-0.798233, -0.246130, -0.149921, -0.618134, -0.998214, -0.350054, 0.000000, -0.807551], [-0.990993, 0.476355, 0.526640, -0.990769, -0.718815, 0.381236, 0.000000, -0.988826], [-0.475221, 0.990649, 0.979971, -0.686406, 0.131860, 0.972532, 0.000000, -0.461939], [-0.587961, 0.965096, 0.963191, -0.777187, 0.000754, 0.932889, 0.000000, -0.575726], [-0.994872, 0.452457, 0.506470, -0.986041, -0.744521, 0.355223, 0.000000, -0.993509], [0.924448, -0.690293, -0.732694, 0.990262, 0.526284, -0.609178, 0.000000, 0.918827], [0.953887, -0.625331, -0.669965, 0.998673, 0.593688, -0.539253, 0.000000, 0.949450], [0.982975, -0.526211, -0.581420, 0.995629, 0.688840, -0.432495, 0.000000, 0.980368]]
pre_activation_mean: [-1.100167, -2.073618, 0.915061, 0.483472, -2.005740, 1.966994, 2.901344, 4.801768]
pre_activation_std: [0.368996, 1.233276, 1.555560, 1.494479, 0.915500, 1.509048, 1.959884, 2.908925]
### 10
mean: [-3.728887]
std: [4.041121]
fourier: [[63.107376, 66.153351, 73.754231, 76.586410, 335.599856]]
input_correlations: [[0.000000, 0.000000, 0.805272, 0.817590, 0.000000, -0.972935, -0.970166, -0.937927]]
pre_activation_mean: [-3.728887]
pre_activation_std: [4.041121]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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],
"network.0.bias": [
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0.317617,
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"network.2.weight": [
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0.27614,
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[
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0.102923,
0.252781,
-0.270578
],
[
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0.029553,
0.043777,
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0.168732,
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0.136354,
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],
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0.503897,
0.415654,
0.146056,
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]
],
"network.2.bias": [
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0.018158,
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"network.4.weight": [
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0.023641,
-0.341818
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"network.6.weight": [
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0.028858,
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],
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]
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"network.10.weight": [
[
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 1.038592, 0.795376, 0.000000, 2.028892, 2.907359, 4.801768]
std: [0.000000, 0.000000, 1.451243, 1.232432, 0.000000, 1.413290, 1.950766, 2.908925]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [24.024625, 25.741071, 25.758812, 26.600287, 93.473302], [20.239112, 21.306347, 22.599552, 23.573442, 71.583836], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [22.945559, 23.727454, 24.058527, 27.498235, 182.600273], [31.460007, 32.070278, 33.191271, 37.666066, 261.662289], [43.710932, 48.335367, 50.481261, 56.381622, 432.159127]]
input_correlations: [[-0.839888, -0.429037, 0.071613, 0.223008, 0.197242, 0.000000, 0.000000, 0.000000], [-0.032004, -0.420053, -0.461225, -0.882024, -0.121353, 0.000000, 0.000000, 0.000000], [-0.478611, -0.683804, -0.582955, -0.595853, -0.515269, 0.000000, 0.000000, 0.000000], [-0.464331, 0.002220, 0.533899, 0.379909, 0.463965, 0.000000, 0.000000, 0.000000], [0.811244, 0.390089, 0.715273, -0.061816, -0.089554, 0.000000, 0.000000, 0.000000], [0.395411, -0.171075, 0.748427, -0.609848, 0.116399, 0.000000, 0.000000, 0.000000], [0.650033, 0.629983, 0.378409, 0.590428, 0.538021, 0.000000, 0.000000, 0.000000], [-0.280728, -0.703653, -0.635525, -0.530437, -0.516958, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.416836, -2.769680, -1.956768, 1.440713, 1.239501, 0.508209, 3.137891, -2.648718]
pre_activation_std: [0.458228, 1.576988, 1.396251, 1.614436, 1.638924, 1.258674, 2.241359, 1.457033]
### 2
mean: [1.847392, 0.217487, 1.416999, 1.234155, -1.852534, 0.424449, 0.290612, 2.759054]
std: [1.269482, 0.565517, 0.883065, 1.315002, 1.067442, 0.528403, 0.518086, 1.564165]
fourier: [[21.787709, 22.173599, 22.748800, 23.161021, 166.265299], [9.130912, 9.174065, 9.455885, 9.950209, 19.573793], [13.868122, 14.155582, 14.591873, 17.268631, 127.529912], [23.372151, 23.473094, 23.675565, 24.314030, 111.073990], [17.244423, 18.792312, 18.807786, 21.005749, 166.728061], [7.878509, 8.348864, 8.904116, 9.307271, 38.200441], [7.679274, 7.792816, 8.928089, 9.175372, 26.155103], [23.180365, 25.722550, 26.226998, 31.770168, 248.314878]]
input_correlations: [[0.580985, 0.000000, -0.419789, 0.920652, 0.015926, 0.153977, 0.528127, 0.000000], [-0.849159, 0.000000, -0.122127, -0.509820, 0.526398, 0.030345, 0.679135, 0.000000], [0.740890, 0.000000, -0.355851, 0.974459, -0.068769, 0.273379, 0.262000, 0.000000], [-0.731464, 0.000000, -0.271715, -0.261982, 0.865168, 0.331071, 0.767436, 0.000000], [0.034419, 0.000000, 0.508135, -0.496917, -0.475452, -0.079901, -0.964535, 0.000000], [-0.703153, 0.000000, -0.268798, -0.286684, 0.583907, 0.025550, 0.848180, 0.000000], [-0.736489, 0.000000, -0.101300, -0.530364, 0.447480, -0.313316, 0.626991, 0.000000], [-0.011826, 0.000000, -0.525480, 0.570368, 0.724913, 0.461771, 0.842727, 0.000000]]
pre_activation_mean: [1.847392, 0.217487, 1.416999, 1.234155, -1.852534, 0.424449, 0.290612, 2.759054]
pre_activation_std: [1.269482, 0.565517, 0.883065, 1.315002, 1.067442, 0.528403, 0.518086, 1.564165]
### 4
mean: [1.752349, -1.358568, 0.806931, 2.128135, 1.464062, 0.610347, 3.461772, -1.642882]
std: [1.263020, 0.702537, 1.012066, 1.602893, 1.083723, 0.345327, 1.647543, 0.641848]
fourier: [[20.016895, 20.538766, 23.107243, 26.841258, 157.711401], [11.188705, 11.742184, 11.802388, 12.425950, 122.271107], [16.892632, 17.681752, 17.821006, 18.272692, 72.623742], [26.088263, 26.588194, 28.560510, 30.233385, 191.532151], [17.044271, 17.614479, 18.641490, 20.644951, 131.765600], [5.270264, 5.506979, 6.366247, 6.393265, 54.931250], [26.556240, 26.704643, 26.739266, 29.215304, 311.559487], [10.482379, 10.697304, 10.980831, 12.467813, 147.859380]]
input_correlations: [[0.456031, 0.806763, 0.243219, 0.867695, 0.000000, 0.856001, 0.678104, 0.922226], [-0.862088, -0.286050, -0.770123, -0.394521, 0.000000, -0.380991, -0.152505, -0.954971], [-0.180504, 0.928822, -0.387580, 0.983669, 0.000000, 0.897861, 0.924093, 0.545707], [0.970003, -0.216306, 0.988630, -0.150797, 0.000000, -0.105097, -0.357534, 0.648924], [0.912494, -0.438559, 0.984361, -0.398382, 0.000000, -0.332384, -0.578257, 0.426590], [0.625127, -0.646655, 0.720348, -0.750175, 0.000000, -0.546952, -0.727523, -0.126014], [0.930690, 0.196689, 0.855077, 0.272868, 0.000000, 0.298707, 0.030474, 0.899898], [-0.885632, -0.386063, -0.731959, -0.408931, 0.000000, -0.506858, -0.245188, -0.900766]]
pre_activation_mean: [1.752349, -1.358568, 0.806931, 2.128135, 1.464062, 0.610347, 3.461772, -1.642882]
pre_activation_std: [1.263020, 0.702537, 1.012066, 1.602893, 1.083723, 0.345327, 1.647543, 0.641848]
### 6
mean: [2.507741, 0.609717, 0.227308, 3.161386, 2.854001, 0.654131, -0.864510, 3.066094]
std: [1.389494, 0.991991, 0.724402, 2.098933, 1.268842, 1.280329, 0.232570, 1.563913]
fourier: [[22.020381, 23.855789, 24.274888, 26.055256, 225.696713], [15.793361, 16.305466, 18.203324, 18.434312, 54.874541], [11.417892, 11.504398, 12.895034, 13.436666, 20.457693], [33.068658, 34.587357, 36.057472, 40.275381, 284.524740], [19.612455, 20.364670, 22.860745, 23.760031, 256.860061], [21.181558, 21.553225, 22.629362, 23.524364, 58.871831], [3.906048, 4.286292, 4.443999, 4.926561, 77.805868], [25.145084, 26.897983, 27.326890, 29.362678, 275.948466]]
input_correlations: [[0.411066, 0.000000, -0.193741, 0.995792, 0.957515, 0.631576, 0.933428, 0.000000], [0.610920, 0.000000, 0.954327, -0.523234, -0.699014, -0.887931, -0.122804, 0.000000], [0.457186, 0.000000, 0.890407, -0.664632, -0.814435, -0.920316, -0.297253, 0.000000], [0.162514, 0.000000, -0.441298, 0.978505, 0.998523, 0.780853, 0.809447, 0.000000], [0.869313, 0.000000, 0.423061, 0.766354, 0.604191, 0.094033, 0.963765, 0.000000], [0.692656, 0.000000, 0.978880, -0.429072, -0.618907, -0.852919, -0.015491, 0.000000], [-0.990157, 0.000000, -0.811868, -0.332676, -0.118030, 0.321172, -0.692623, 0.000000], [0.424535, 0.000000, -0.178595, 0.995208, 0.953874, 0.616989, 0.938980, 0.000000]]
pre_activation_mean: [2.507741, 0.609717, 0.227308, 3.161386, 2.854001, 0.654131, -0.864510, 3.066094]
pre_activation_std: [1.389494, 0.991991, 0.724402, 2.098933, 1.268842, 1.280329, 0.232570, 1.563913]
### 8
mean: [-1.100167, -2.073618, 0.915061, 0.483472, -2.005740, 1.966994, 2.901344, 4.801768]
std: [0.368996, 1.233276, 1.555560, 1.494479, 0.915500, 1.509048, 1.959884, 2.908925]
fourier: [[5.778920, 6.009216, 6.673129, 6.855510, 99.015051], [19.217548, 20.714266, 21.546119, 23.514316, 186.625644], [25.796983, 26.033561, 26.940420, 28.915217, 82.355538], [24.149853, 24.627514, 25.949349, 28.128955, 43.512436], [14.371825, 15.388108, 16.036644, 17.374299, 180.516580], [24.540669, 25.023886, 25.680490, 28.877081, 177.029501], [31.811716, 31.944642, 33.355407, 37.710079, 261.120938], [43.710932, 48.335367, 50.481261, 56.381622, 432.159127]]
input_correlations: [[-0.798233, -0.246130, -0.149921, -0.618134, -0.998214, -0.350054, 0.000000, -0.807551], [-0.990993, 0.476355, 0.526640, -0.990769, -0.718815, 0.381236, 0.000000, -0.988826], [-0.475221, 0.990649, 0.979971, -0.686406, 0.131860, 0.972532, 0.000000, -0.461939], [-0.587961, 0.965096, 0.963191, -0.777187, 0.000754, 0.932889, 0.000000, -0.575726], [-0.994872, 0.452457, 0.506470, -0.986041, -0.744521, 0.355223, 0.000000, -0.993509], [0.924448, -0.690293, -0.732694, 0.990262, 0.526284, -0.609178, 0.000000, 0.918827], [0.953887, -0.625331, -0.669965, 0.998673, 0.593688, -0.539253, 0.000000, 0.949450], [0.982975, -0.526211, -0.581420, 0.995629, 0.688840, -0.432495, 0.000000, 0.980368]]
pre_activation_mean: [-1.100167, -2.073618, 0.915061, 0.483472, -2.005740, 1.966994, 2.901344, 4.801768]
pre_activation_std: [0.368996, 1.233276, 1.555560, 1.494479, 0.915500, 1.509048, 1.959884, 2.908925]
### 10
mean: [-3.728887]
std: [4.041121]
fourier: [[63.107376, 66.153351, 73.754231, 76.586410, 335.599856]]
input_correlations: [[0.000000, 0.000000, 0.805272, 0.817590, 0.000000, -0.972935, -0.970166, -0.937927]]
pre_activation_mean: [-3.728887]
pre_activation_std: [4.041121]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.839888000885702, -0.4290369989080576, 0.07161293570580875, 0.22300796154362337, 0.19724234752903028, 0.0, 0.0, 0.0], "pre_activation_mean": 0.4168355166912079, "pre_activation_std": 0.45822831988334656}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.03200414174243143, -0.4200528220013497, -0.4612251983779701, -0.8820244806588032, -0.12135304048923233, 0.0, 0.0, 0.0], "pre_activation_mean": -2.7696802616119385, "pre_activation_std": 1.5769884586334229}, "2": {"mean": 1.0385922193527222, "std": 1.4512428045272827, "fourier": [24.02462519427534, 25.74107127226016, 25.758811798271783, 26.600287128966066, 93.47330155968666], "input_correlations": [-0.47861102901765945, -0.6838040055963631, -0.582955493041703, -0.5958531361079326, -0.5152694535792486, 0.0, 0.0, 0.0], "pre_activation_mean": -1.9567675590515137, "pre_activation_std": 1.3962513208389282}, "3": {"mean": 0.7953758835792542, "std": 1.232432246208191, "fourier": [20.23911242165747, 21.30634679778198, 22.59955165684229, 23.573442492851925, 71.58383557200432], "input_correlations": [-0.4643313252102272, 0.0022204996843768598, 0.5338989690660922, 0.37990903015603855, 0.46396536971488495, 0.0, 0.0, 0.0], "pre_activation_mean": 1.4407131671905518, "pre_activation_std": 1.6144362688064575}, "4": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.8112436753738763, 0.3900885179699346, 0.7152726356623824, -0.061815573160323684, -0.08955392553101421, 0.0, 0.0, 0.0], "pre_activation_mean": 1.239500641822815, "pre_activation_std": 1.638924479484558}, "5": {"mean": 2.0288920402526855, "std": 1.4132897853851318, "fourier": [22.945559102298013, 23.72745413686734, 24.05852732912192, 27.49823549650061, 182.60027307271957], "input_correlations": [0.3954106428867147, -0.1710745054084782, 0.7484267419649154, -0.6098484783029496, 0.11639856985081386, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5082091093063354, "pre_activation_std": 1.258674144744873}, "6": {"mean": 2.9073591232299805, "std": 1.9507660865783691, "fourier": [31.460007472555354, 32.07027843785323, 33.19127065477471, 37.66606555994173, 261.6622886955738], "input_correlations": [0.6500330359223843, 0.6299828024513323, 0.378408928209001, 0.5904277146374629, 0.5380211218131514, 0.0, 0.0, 0.0], "pre_activation_mean": 3.137890577316284, "pre_activation_std": 2.2413594722747803}, "7": {"mean": 4.801767826080322, "std": 2.9089248180389404, "fourier": [43.71093152316732, 48.33536710759322, 50.48126095115818, 56.38162166899805, 432.15912705659866], "input_correlations": [-0.2807278604572586, -0.7036526439666925, -0.6355254533503327, -0.5304373539502918, -0.5169577994366232, 0.0, 0.0, 0.0], "pre_activation_mean": -2.6487176418304443, "pre_activation_std": 1.4570326805114746}}, "layer_info": {"num_neurons": 8, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 1.8473920822143555, "std": 1.269482135772705, "fourier": [21.78770887469558, 22.17359916936151, 22.748800312127877, 23.161020552384798, 166.26529859006405], "input_correlations": [0.5809845082050411, 0.0, -0.41978945886030955, 0.9206520032807965, 0.015926126318922137, 0.15397728875049127, 0.5281268852088077, 0.0], "pre_activation_mean": 1.8473920822143555, "pre_activation_std": 1.269482135772705}, "1": {"mean": 0.21748659014701843, "std": 0.5655169486999512, "fourier": [9.130911685565968, 9.174065239767218, 9.45588545024969, 9.950209236720534, 19.573793336749077], "input_correlations": [-0.8491592945356417, 0.0, -0.12212740352235656, -0.5098199804614391, 0.5263977086827931, 0.03034523461750426, 0.6791350395726794, 0.0], "pre_activation_mean": 0.21748659014701843, "pre_activation_std": 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"improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.13556836545467377, "train_acc": 0.96, "val_loss": 0.40139493346214294, "val_acc": 0.92}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.15014349669218063, "train_acc": 0.955, "val_loss": 0.31296849250793457, "val_acc": 0.92}], "summary": {"total_epochs": 11, "degraded_epochs": 2, "improved_epochs": 9, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6367703080177307, "final_val_loss": 0.5821906328201294, "initial_val_acc": 0.6, "final_val_acc": 0.66, "best_val_acc": 0.66}, "improved_stage": {"initial_val_loss": 0.4635984003543854, "final_val_loss": 0.31296849250793457, "initial_val_acc": 0.92, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 7}, "improvement": 0.2799999999999999, "first_improvement_epoch": 1}} |
78 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.48, "improved_accuracy": 0.94, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4872, "learning_rate": 0.02525648142243843, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.000000, 0.756750, 0.371171, 0.314969, 0.146159, 0.000000, 0.000000]
std: [0.000000, 0.930700, 0.200616, 0.176866, 0.080757, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [16.038554, 16.668957, 16.877856, 17.999329, 68.107543], [3.631835, 3.894882, 3.909976, 4.120936, 33.405410], [3.103990, 3.324379, 3.427876, 3.540162, 28.347167], [1.446106, 1.552587, 1.571120, 1.635657, 13.154306], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.208003, 0.397752, -0.503860, 0.327371, -0.742178, 0.000000, 0.000000, 0.000000], [-0.491549, -0.485227, 0.434642, 0.088686, -0.260850, 0.000000, 0.000000, 0.000000], [0.067828, 0.409736, 0.439977, -0.353935, -0.643555, 0.000000, 0.000000, 0.000000], [-0.505155, 0.126032, 0.609925, -0.069485, 0.022308, 0.000000, 0.000000, 0.000000], [0.712075, 0.596796, 0.775823, 0.064593, -0.038027, 0.000000, 0.000000, 0.000000], [-0.744289, 0.256124, -0.003994, 0.308419, 0.211067, 0.000000, 0.000000, 0.000000], [0.868183, 0.627883, 0.633059, 0.100353, 0.259337, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.554148, 0.503828, -0.147921, 0.324408, 1.814884, 0.704612, 1.696544]
pre_activation_std: [0.942027, 0.933247, 1.428812, 1.390909, 1.398009, 0.689779, 1.544092]
### 2
mean: [-0.109296, 0.273324, -1.109704, 0.630427, 0.539931, 0.968674, -1.315228]
std: [0.581466, 0.969112, 0.692653, 1.853015, 0.999019, 0.683142, 1.029616]
fourier: [[9.630993, 9.645949, 9.836618, 10.561229, 10.926443], [16.789452, 17.345769, 17.627048, 18.563569, 24.599144], [10.068771, 11.004865, 13.792149, 14.833298, 99.873352], [30.196271, 30.237722, 34.558107, 36.699298, 56.738425], [16.428889, 17.103736, 18.527590, 18.814982, 48.593756], [10.994887, 11.529229, 12.798390, 13.356135, 87.180668], [16.772750, 16.952351, 17.045517, 23.249469, 118.370543]]
input_correlations: [[0.264052, 0.272373, -0.279820, 0.046920, -0.846166, 0.548834, -0.923790, 0.000000], [-0.072165, -0.443454, 0.200015, -0.383609, 0.721600, -0.656146, 0.830635, 0.000000], [0.019244, -0.614022, -0.831139, -0.947672, -0.525266, -0.357833, -0.270394, 0.000000], [-0.088794, -0.479320, 0.059014, -0.351500, 0.737865, -0.551441, 0.901814, 0.000000], [-0.150515, -0.414990, 0.214196, -0.362287, 0.730403, -0.658040, 0.831600, 0.000000], [0.052867, 0.756489, 0.296451, 0.654079, -0.341066, 0.585452, -0.612231, 0.000000], [-0.057011, -0.207520, -0.814443, -0.693952, -0.861354, -0.153753, -0.730797, 0.000000]]
pre_activation_mean: [-0.109296, 0.273324, -1.109704, 0.630427, 0.539931, 0.968674, -1.315228]
pre_activation_std: [0.581466, 0.969112, 0.692653, 1.853015, 0.999019, 0.683142, 1.029616]
### 4
mean: [0.776712, -0.493491, -0.902278, -0.525180, -0.895256, 0.645724, 0.816210]
std: [1.212595, 0.194731, 0.727661, 0.114332, 0.603460, 2.064469, 1.913591]
fourier: [[20.934997, 21.663418, 21.860393, 23.352607, 69.904047], [2.802154, 2.985747, 3.092769, 3.416315, 44.414152], [12.780783, 12.800094, 13.011360, 13.955495, 81.205021], [1.642934, 1.688009, 1.782636, 1.815628, 47.266248], [10.295743, 10.851318, 10.962595, 11.249437, 80.573018], [36.668223, 36.924203, 38.916303, 39.391442, 58.115156], [33.947240, 34.270310, 35.642657, 36.385285, 73.458936]]
input_correlations: [[-0.507025, 0.985994, 0.000000, 0.996573, 0.980944, -0.782996, 0.000000, 0.000000], [0.380585, -0.085470, 0.000000, -0.139521, -0.069472, -0.458809, 0.000000, 0.000000], [0.478333, -0.985380, 0.000000, -0.996145, -0.978371, 0.762793, 0.000000, 0.000000], [-0.127309, 0.197532, 0.000000, 0.323876, 0.208685, -0.733122, 0.000000, 0.000000], [0.445713, -0.984828, 0.000000, -0.985058, -0.980740, 0.722156, 0.000000, 0.000000], [-0.489379, 0.985428, 0.000000, 0.991931, 0.982681, -0.836880, 0.000000, 0.000000], [-0.454395, 0.986342, 0.000000, 0.992902, 0.982500, -0.834819, 0.000000, 0.000000]]
pre_activation_mean: [0.776712, -0.493491, -0.902278, -0.525180, -0.895256, 0.645724, 0.816210]
pre_activation_std: [1.212595, 0.194731, 0.727661, 0.114332, 0.603460, 2.064469, 1.913591]
### 6
mean: [0.862753, -0.262996, -0.361580, -0.285291, -0.438961, 0.852683, -0.832004]
std: [1.386068, 0.030730, 0.060604, 0.421144, 0.626433, 1.724797, 1.204777]
fourier: [[23.877126, 24.887845, 25.259499, 26.813779, 77.647734], [0.517280, 0.523982, 0.528078, 0.567878, 23.669638], [1.049119, 1.059694, 1.084414, 1.134396, 32.542184], [7.302504, 7.476791, 7.629587, 8.021352, 25.676203], [10.845945, 11.198999, 11.421242, 12.029437, 39.506522], [29.777441, 30.928099, 31.450333, 33.281600, 76.741499], [20.801073, 21.594886, 21.923641, 23.248883, 74.880350]]
input_correlations: [[0.997538, 0.000000, 0.000000, 0.000000, 0.000000, 0.999986, 0.999874, 0.000000], [0.905104, 0.000000, 0.000000, 0.000000, 0.000000, 0.874390, 0.882673, 0.000000], [-0.993651, 0.000000, 0.000000, 0.000000, 0.000000, -0.983185, -0.985684, 0.000000], [-0.999286, 0.000000, 0.000000, 0.000000, 0.000000, -0.994266, -0.995687, 0.000000], [-0.999712, 0.000000, 0.000000, 0.000000, 0.000000, -0.998562, -0.999240, 0.000000], [0.998658, 0.000000, 0.000000, 0.000000, 0.000000, 0.999753, 0.999941, 0.000000], [-0.999058, 0.000000, 0.000000, 0.000000, 0.000000, -0.999564, -0.999828, 0.000000]]
pre_activation_mean: [0.862753, -0.262996, -0.361580, -0.285291, -0.438961, 0.852683, -0.832004]
pre_activation_std: [1.386068, 0.030730, 0.060604, 0.421144, 0.626433, 1.724797, 1.204777]
### 8
mean: [-0.243088, 0.756750, 0.283490, 0.193055, 0.099576, -0.344036, -0.249931]
std: [0.113526, 0.930700, 0.385007, 0.424939, 0.177068, 0.608229, 0.121315]
fourier: [[1.985185, 2.009200, 2.012781, 2.191476, 21.877877], [16.038554, 16.668957, 16.877856, 17.999329, 68.107543], [6.652583, 6.875277, 6.942687, 7.442986, 25.514080], [7.321615, 7.620203, 7.724641, 8.219343, 17.374983], [3.062589, 3.159801, 3.188763, 3.422760, 8.961864], [10.485332, 10.879077, 11.002009, 11.760918, 30.963247], [2.087020, 2.206543, 2.267920, 2.348691, 22.493769]]
input_correlations: [[-0.999298, 0.000000, 0.000000, 0.000000, 0.000000, -0.999643, 0.000000, 0.000000], [0.999976, 0.000000, 0.000000, 0.000000, 0.000000, 0.999993, 0.000000, 0.000000], [-0.999892, 0.000000, 0.000000, 0.000000, 0.000000, -0.999992, 0.000000, 0.000000], [-0.999994, 0.000000, 0.000000, 0.000000, 0.000000, -0.999974, 0.000000, 0.000000], [-0.999863, 0.000000, 0.000000, 0.000000, 0.000000, -0.999983, 0.000000, 0.000000], [-0.999945, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [-0.999295, 0.000000, 0.000000, 0.000000, 0.000000, -0.998834, 0.000000, 0.000000]]
pre_activation_mean: [-0.243088, 0.756750, 0.283490, 0.193055, 0.099576, -0.344036, -0.249931]
pre_activation_std: [0.113526, 0.930700, 0.385007, 0.424939, 0.177068, 0.608229, 0.121315]
### 10
mean: [-0.192393]
std: [0.515153]
fourier: [[8.710586, 9.562465, 9.823585, 10.114529, 17.315368]]
input_correlations: [[0.000000, 0.993797, -0.974685, -0.962282, -0.968155, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.192393]
pre_activation_std: [0.515153]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [0.000000, 0.756750, 0.371171, 0.314969, 0.146159, 0.000000, 0.000000]
std: [0.000000, 0.930700, 0.200616, 0.176866, 0.080757, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [16.038554, 16.668957, 16.877856, 17.999329, 68.107543], [3.631835, 3.894882, 3.909976, 4.120936, 33.405410], [3.103990, 3.324379, 3.427876, 3.540162, 28.347167], [1.446106, 1.552587, 1.571120, 1.635657, 13.154306], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.208003, 0.397752, -0.503860, 0.327371, -0.742178, 0.000000, 0.000000, 0.000000], [-0.491549, -0.485227, 0.434642, 0.088686, -0.260850, 0.000000, 0.000000, 0.000000], [0.067828, 0.409736, 0.439977, -0.353935, -0.643555, 0.000000, 0.000000, 0.000000], [-0.505155, 0.126032, 0.609925, -0.069485, 0.022308, 0.000000, 0.000000, 0.000000], [0.712075, 0.596796, 0.775823, 0.064593, -0.038027, 0.000000, 0.000000, 0.000000], [-0.744289, 0.256124, -0.003994, 0.308419, 0.211067, 0.000000, 0.000000, 0.000000], [0.868183, 0.627883, 0.633059, 0.100353, 0.259337, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.554148, 0.503828, -0.147921, 0.324408, 1.814884, 0.704612, 1.696544]
pre_activation_std: [0.942027, 0.933247, 1.428812, 1.390909, 1.398009, 0.689779, 1.544092]
### 2
mean: [-0.109296, 0.273324, -1.109704, 0.630427, 0.539931, 0.968674, -1.315228]
std: [0.581466, 0.969112, 0.692653, 1.853015, 0.999019, 0.683142, 1.029616]
fourier: [[9.630993, 9.645949, 9.836618, 10.561229, 10.926443], [16.789452, 17.345769, 17.627048, 18.563569, 24.599144], [10.068771, 11.004865, 13.792149, 14.833298, 99.873352], [30.196271, 30.237722, 34.558107, 36.699298, 56.738425], [16.428889, 17.103736, 18.527590, 18.814982, 48.593756], [10.994887, 11.529229, 12.798390, 13.356135, 87.180668], [16.772750, 16.952351, 17.045517, 23.249469, 118.370543]]
input_correlations: [[0.264052, 0.272373, -0.279820, 0.046920, -0.846166, 0.548834, -0.923790, 0.000000], [-0.072165, -0.443454, 0.200015, -0.383609, 0.721600, -0.656146, 0.830635, 0.000000], [0.019244, -0.614022, -0.831139, -0.947672, -0.525266, -0.357833, -0.270394, 0.000000], [-0.088794, -0.479320, 0.059014, -0.351500, 0.737865, -0.551441, 0.901814, 0.000000], [-0.150515, -0.414990, 0.214196, -0.362287, 0.730403, -0.658040, 0.831600, 0.000000], [0.052867, 0.756489, 0.296451, 0.654079, -0.341066, 0.585452, -0.612231, 0.000000], [-0.057011, -0.207520, -0.814443, -0.693952, -0.861354, -0.153753, -0.730797, 0.000000]]
pre_activation_mean: [-0.109296, 0.273324, -1.109704, 0.630427, 0.539931, 0.968674, -1.315228]
pre_activation_std: [0.581466, 0.969112, 0.692653, 1.853015, 0.999019, 0.683142, 1.029616]
### 4
mean: [0.776712, -0.493491, -0.902278, -0.525180, -0.895256, 0.645724, 0.816210]
std: [1.212595, 0.194731, 0.727661, 0.114332, 0.603460, 2.064469, 1.913591]
fourier: [[20.934997, 21.663418, 21.860393, 23.352607, 69.904047], [2.802154, 2.985747, 3.092769, 3.416315, 44.414152], [12.780783, 12.800094, 13.011360, 13.955495, 81.205021], [1.642934, 1.688009, 1.782636, 1.815628, 47.266248], [10.295743, 10.851318, 10.962595, 11.249437, 80.573018], [36.668223, 36.924203, 38.916303, 39.391442, 58.115156], [33.947240, 34.270310, 35.642657, 36.385285, 73.458936]]
input_correlations: [[-0.507025, 0.985994, 0.000000, 0.996573, 0.980944, -0.782996, 0.000000, 0.000000], [0.380585, -0.085470, 0.000000, -0.139521, -0.069472, -0.458809, 0.000000, 0.000000], [0.478333, -0.985380, 0.000000, -0.996145, -0.978371, 0.762793, 0.000000, 0.000000], [-0.127309, 0.197532, 0.000000, 0.323876, 0.208685, -0.733122, 0.000000, 0.000000], [0.445713, -0.984828, 0.000000, -0.985058, -0.980740, 0.722156, 0.000000, 0.000000], [-0.489379, 0.985428, 0.000000, 0.991931, 0.982681, -0.836880, 0.000000, 0.000000], [-0.454395, 0.986342, 0.000000, 0.992902, 0.982500, -0.834819, 0.000000, 0.000000]]
pre_activation_mean: [0.776712, -0.493491, -0.902278, -0.525180, -0.895256, 0.645724, 0.816210]
pre_activation_std: [1.212595, 0.194731, 0.727661, 0.114332, 0.603460, 2.064469, 1.913591]
### 6
mean: [0.862753, -0.262996, -0.361580, -0.285291, -0.438961, 0.852683, -0.832004]
std: [1.386068, 0.030730, 0.060604, 0.421144, 0.626433, 1.724797, 1.204777]
fourier: [[23.877126, 24.887845, 25.259499, 26.813779, 77.647734], [0.517280, 0.523982, 0.528078, 0.567878, 23.669638], [1.049119, 1.059694, 1.084414, 1.134396, 32.542184], [7.302504, 7.476791, 7.629587, 8.021352, 25.676203], [10.845945, 11.198999, 11.421242, 12.029437, 39.506522], [29.777441, 30.928099, 31.450333, 33.281600, 76.741499], [20.801073, 21.594886, 21.923641, 23.248883, 74.880350]]
input_correlations: [[0.997538, 0.000000, 0.000000, 0.000000, 0.000000, 0.999986, 0.999874, 0.000000], [0.905104, 0.000000, 0.000000, 0.000000, 0.000000, 0.874390, 0.882673, 0.000000], [-0.993651, 0.000000, 0.000000, 0.000000, 0.000000, -0.983185, -0.985684, 0.000000], [-0.999286, 0.000000, 0.000000, 0.000000, 0.000000, -0.994266, -0.995687, 0.000000], [-0.999712, 0.000000, 0.000000, 0.000000, 0.000000, -0.998562, -0.999240, 0.000000], [0.998658, 0.000000, 0.000000, 0.000000, 0.000000, 0.999753, 0.999941, 0.000000], [-0.999058, 0.000000, 0.000000, 0.000000, 0.000000, -0.999564, -0.999828, 0.000000]]
pre_activation_mean: [0.862753, -0.262996, -0.361580, -0.285291, -0.438961, 0.852683, -0.832004]
pre_activation_std: [1.386068, 0.030730, 0.060604, 0.421144, 0.626433, 1.724797, 1.204777]
### 8
mean: [-0.243088, 0.756750, 0.283490, 0.193055, 0.099576, -0.344036, -0.249931]
std: [0.113526, 0.930700, 0.385007, 0.424939, 0.177068, 0.608229, 0.121315]
fourier: [[1.985185, 2.009200, 2.012781, 2.191476, 21.877877], [16.038554, 16.668957, 16.877856, 17.999329, 68.107543], [6.652583, 6.875277, 6.942687, 7.442986, 25.514080], [7.321615, 7.620203, 7.724641, 8.219343, 17.374983], [3.062589, 3.159801, 3.188763, 3.422760, 8.961864], [10.485332, 10.879077, 11.002009, 11.760918, 30.963247], [2.087020, 2.206543, 2.267920, 2.348691, 22.493769]]
input_correlations: [[-0.999298, 0.000000, 0.000000, 0.000000, 0.000000, -0.999643, 0.000000, 0.000000], [0.999976, 0.000000, 0.000000, 0.000000, 0.000000, 0.999993, 0.000000, 0.000000], [-0.999892, 0.000000, 0.000000, 0.000000, 0.000000, -0.999992, 0.000000, 0.000000], [-0.999994, 0.000000, 0.000000, 0.000000, 0.000000, -0.999974, 0.000000, 0.000000], [-0.999863, 0.000000, 0.000000, 0.000000, 0.000000, -0.999983, 0.000000, 0.000000], [-0.999945, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [-0.999295, 0.000000, 0.000000, 0.000000, 0.000000, -0.998834, 0.000000, 0.000000]]
pre_activation_mean: [-0.243088, 0.756750, 0.283490, 0.193055, 0.099576, -0.344036, -0.249931]
pre_activation_std: [0.113526, 0.930700, 0.385007, 0.424939, 0.177068, 0.608229, 0.121315]
### 10
mean: [-0.192393]
std: [0.515153]
fourier: [[8.710586, 9.562465, 9.823585, 10.114529, 17.315368]]
input_correlations: [[0.000000, 0.993797, -0.974685, -0.962282, -0.968155, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.192393]
pre_activation_std: [0.515153]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.2080034814255452, 0.3977523246486186, -0.5038596611658762, 0.3273711083830258, -0.7421777728851193, 0.0, 0.0, 0.0], "pre_activation_mean": -0.5541479587554932, "pre_activation_std": 0.9420267343521118}, "1": {"mean": 0.7567504644393921, "std": 0.9307001233100891, "fourier": [16.038553866872604, 16.66895670443099, 16.87785649021138, 17.999328719799262, 68.10754296183586], "input_correlations": [-0.4915493985783623, -0.4852269213040928, 0.43464211399254515, 0.08868614375433291, -0.26085020837610634, 0.0, 0.0, 0.0], "pre_activation_mean": 0.5038284063339233, "pre_activation_std": 0.9332467317581177}, "2": {"mean": 0.3711712658405304, "std": 0.2006162703037262, "fourier": [3.6318353980934437, 3.8948816748248642, 3.909976260176772, 4.120935845587153, 33.40540999174118], "input_correlations": [0.06782771611389873, 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"val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6795890629291534, "train_acc": 0.57, "val_loss": 0.7016735076904297, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6725043654441833, "train_acc": 0.57, "val_loss": 0.686604917049408, "val_acc": 0.48}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6653770804405212, "train_acc": 0.57, "val_loss": 0.6670303344726562, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6562107801437378, "train_acc": 0.505, "val_loss": 0.6269662380218506, "val_acc": 0.82}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.6006161570549011, "train_acc": 0.87, "val_loss": 0.5602959990501404, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.521058052778244, "train_acc": 0.93, "val_loss": 0.45715102553367615, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.42911598086357117, "train_acc": 0.935, "val_loss": 0.37595734000205994, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.35363759100437164, "train_acc": 0.93, "val_loss": 0.3703347146511078, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.3415764421224594, "train_acc": 0.935, "val_loss": 0.3433956205844879, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.30756670236587524, "train_acc": 0.93, "val_loss": 0.3165356516838074, "val_acc": 0.9}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.27170807123184204, "train_acc": 0.915, "val_loss": 0.3183962106704712, "val_acc": 0.9}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.23833061009645462, "train_acc": 0.915, "val_loss": 0.286097913980484, "val_acc": 0.9}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.21709682792425156, "train_acc": 0.925, "val_loss": 0.2724459767341614, "val_acc": 0.9}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.713081955909729, "final_val_loss": 0.6670303344726562, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6269662380218506, "final_val_loss": 0.2724459767341614, "initial_val_acc": 0.82, "final_val_acc": 0.9, "best_val_acc": 0.94, "best_epoch": 6}, "improvement": 0.45999999999999996, "first_improvement_epoch": 3}} |
79 | {"target_pattern": "starts_with", "degraded_accuracy": 0.44, "improved_accuracy": 0.78, "improvement": 0.34, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 7384, "learning_rate": 0.0908679592276421, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "starts_with", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["starts_with"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.10.weight": [
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"network.12.bias": [
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}
## Activation Signature
### 0
mean: [-0.072552, -0.056754, 0.004374, 0.094678, 3.643747]
std: [0.055011, 0.051794, 0.125700, 0.150354, 4.848216]
fourier: [[0.837640, 0.918313, 0.926915, 0.963426, 6.529650], [0.802925, 0.809359, 0.819720, 0.853254, 5.107847], [1.959728, 2.010046, 2.122217, 2.183834, 2.209783], [2.501753, 2.515253, 2.557566, 2.896238, 8.521051], [77.577443, 83.007980, 86.808383, 90.731480, 327.937189]]
input_correlations: [[-0.217137, -0.304716, -0.331854, -0.463347, -0.915414, 0.000000, 0.000000, 0.000000], [0.934375, 0.529380, 0.430180, -0.053792, -0.057880, 0.000000, 0.000000, 0.000000], [-0.255780, -0.412099, -0.566118, -0.643418, -0.701334, 0.000000, 0.000000, 0.000000], [0.711641, 0.735539, 0.286141, 0.587553, 0.152031, 0.000000, 0.000000, 0.000000], [-0.390007, -0.195632, -0.703930, -0.101345, -0.836502, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.084224, 2.287207, -3.453114, 5.138946, -2.563924]
pre_activation_std: [2.078203, 2.822516, 2.153514, 3.823768, 2.197541]
### 2
mean: [-1.764059, -0.506733, 4.260228, -1.300628, -3.009602]
std: [2.050402, 1.359830, 3.831732, 1.279919, 2.797995]
fourier: [[30.206623, 35.775412, 37.238537, 38.492161, 158.765324], [22.975868, 23.613550, 24.750622, 26.708185, 45.606007], [61.599795, 65.011196, 65.068332, 71.084010, 383.420491], [19.415080, 20.880167, 24.590322, 25.266588, 117.056541], [42.408565, 47.802713, 50.867105, 51.269235, 270.864110]]
input_correlations: [[-0.422920, -0.925383, -0.362910, -0.951751, -0.179064, 0.000000, 0.000000, 0.000000], [-0.010155, -0.960834, 0.001134, -0.558734, -0.179598, 0.000000, 0.000000, 0.000000], [0.280581, 0.985312, 0.231918, 0.864247, 0.167130, 0.000000, 0.000000, 0.000000], [-0.503666, -0.814454, -0.428020, -0.996841, -0.136358, 0.000000, 0.000000, 0.000000], [-0.384955, -0.942206, -0.326087, -0.937150, -0.171523, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.764059, -0.506733, 4.260228, -1.300628, -3.009602]
pre_activation_std: [2.050402, 1.359830, 3.831732, 1.279919, 2.797995]
### 4
mean: [-0.080174, -2.286235, 2.686643, 0.367056, -1.365839]
std: [0.777528, 2.274360, 2.922832, 0.195443, 0.725205]
fourier: [[12.445032, 12.554701, 12.793164, 13.572277, 13.791615], [36.774435, 37.139233, 39.379797, 42.187216, 205.761185], [46.506666, 49.231490, 50.617785, 54.274792, 241.797911], [3.096540, 3.217681, 3.382175, 4.370404, 33.034996], [11.520149, 12.435156, 15.174671, 15.346897, 122.925553]]
input_correlations: [[0.065906, 0.330284, -0.997832, -0.093545, -0.509398, 0.000000, 0.000000, 0.000000], [0.145500, 0.244833, -0.996121, -0.018695, -0.462842, 0.000000, 0.000000, 0.000000], [-0.023496, -0.400179, 0.993185, 0.134813, 0.510694, 0.000000, 0.000000, 0.000000], [-0.615476, 0.826240, -0.492921, -0.672033, -0.515127, 0.000000, 0.000000, 0.000000], [0.442665, 0.073437, -0.931580, 0.277361, -0.304220, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.080174, -2.286235, 2.686643, 0.367056, -1.365839]
pre_activation_std: [0.777528, 2.274360, 2.922832, 0.195443, 0.725205]
### 6
mean: [2.069890, 0.007159, 1.628622, -1.837451, -0.133609]
std: [2.283004, 0.437344, 2.217781, 1.384324, 1.114356]
fourier: [[36.597117, 37.986031, 40.299138, 42.037311, 186.290041], [6.993805, 7.097713, 7.206970, 7.753074, 7.860312], [35.494025, 36.685807, 38.831629, 42.486373, 146.576008], [21.697702, 23.281728, 24.269603, 25.219834, 165.370620], [17.142550, 17.916889, 18.588004, 19.364905, 21.718871]]
input_correlations: [[-0.795352, 0.684967, 0.999382, -0.559310, 0.816180, 0.000000, 0.000000, 0.000000], [-0.825924, 0.701595, 0.993255, -0.515959, 0.821156, 0.000000, 0.000000, 0.000000], [-0.814040, 0.698601, 0.997456, -0.593762, 0.810680, 0.000000, 0.000000, 0.000000], [0.761809, -0.661148, -0.999541, 0.558182, -0.808961, 0.000000, 0.000000, 0.000000], [0.787750, -0.716540, -0.997153, 0.622382, -0.834689, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.069890, 0.007159, 1.628622, -1.837451, -0.133609]
pre_activation_std: [2.283004, 0.437344, 2.217781, 1.384324, 1.114356]
### 8
mean: [-1.138937, 2.014959, -0.898015, 2.377270, -1.306243]
std: [0.508837, 2.791906, 1.724405, 3.164085, 0.772234]
fourier: [[8.415589, 8.430121, 8.544996, 9.326546, 102.504297], [44.776444, 46.265778, 49.034806, 53.772979, 181.346252], [27.659169, 28.467557, 30.238570, 33.767243, 80.821338], [50.684696, 52.826595, 55.627596, 60.792540, 213.954318], [12.337883, 12.829341, 13.745918, 13.898180, 117.561843]]
input_correlations: [[-0.993925, -0.993598, -0.993583, -0.892206, 0.643293, 0.000000, 0.000000, 0.000000], [0.997128, 0.973049, 0.997037, 0.942721, -0.770220, 0.000000, 0.000000, 0.000000], [-0.994135, -0.964944, -0.994765, -0.952099, 0.788727, 0.000000, 0.000000, 0.000000], [0.997792, 0.975237, 0.998100, 0.940464, -0.762242, 0.000000, 0.000000, 0.000000], [-0.999589, -0.990371, -0.998099, -0.912190, 0.704449, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.138937, 2.014959, -0.898015, 2.377270, -1.306243]
pre_activation_std: [0.508837, 2.791906, 1.724405, 3.164085, 0.772234]
### 10
mean: [-1.861861, -1.549359, -0.779331, -1.265229, 3.504773]
std: [2.071443, 1.791244, 1.150783, 2.184827, 4.964506]
fourier: [[33.103730, 35.162723, 37.041692, 38.577074, 167.567531], [28.724050, 30.232579, 31.896260, 33.856933, 139.442278], [18.645619, 18.903950, 20.115133, 22.769490, 70.139832], [35.498908, 37.344996, 39.240403, 39.807888, 113.870630], [79.721717, 83.397206, 88.200139, 94.632226, 315.429557]]
input_correlations: [[-0.983494, -0.999874, 0.531204, -0.999879, -0.990210, 0.000000, 0.000000, 0.000000], [-0.979991, -0.999931, 0.552167, -0.999949, -0.988975, 0.000000, 0.000000, 0.000000], [-0.962713, -0.995052, 0.623953, -0.995115, -0.980639, 0.000000, 0.000000, 0.000000], [-0.987329, -0.998782, 0.501934, -0.998766, -0.990676, 0.000000, 0.000000, 0.000000], [0.977189, 0.999655, -0.565411, 0.999662, 0.988089, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.861861, -1.549359, -0.779331, -1.265229, 3.504773]
pre_activation_std: [2.071443, 1.791244, 1.150783, 2.184827, 4.964506]
### 12
mean: [-1.663792]
std: [2.248564]
fourier: [[36.216533, 38.065275, 40.266955, 42.808219, 149.741236]]
input_correlations: [[-0.827422, -0.546096, 0.386076, 0.628057, -0.999306, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.663792]
pre_activation_std: [2.248564]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| starts_with | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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-0.966062
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-0.074897,
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[
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-0.62683
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[
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"network.0.bias": [
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"network.6.weight": [
[
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[
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[
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"network.12.bias": [
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}
## Activation Signature
### 0
mean: [-0.072552, -0.056754, 0.004374, 0.094678, 3.643747]
std: [0.055011, 0.051794, 0.125700, 0.150354, 4.848216]
fourier: [[0.837640, 0.918313, 0.926915, 0.963426, 6.529650], [0.802925, 0.809359, 0.819720, 0.853254, 5.107847], [1.959728, 2.010046, 2.122217, 2.183834, 2.209783], [2.501753, 2.515253, 2.557566, 2.896238, 8.521051], [77.577443, 83.007980, 86.808383, 90.731480, 327.937189]]
input_correlations: [[-0.217137, -0.304716, -0.331854, -0.463347, -0.915414, 0.000000, 0.000000, 0.000000], [0.934375, 0.529380, 0.430180, -0.053792, -0.057880, 0.000000, 0.000000, 0.000000], [-0.255780, -0.412099, -0.566118, -0.643418, -0.701334, 0.000000, 0.000000, 0.000000], [0.711641, 0.735539, 0.286141, 0.587553, 0.152031, 0.000000, 0.000000, 0.000000], [-0.390007, -0.195632, -0.703930, -0.101345, -0.836502, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.084224, 2.287207, -3.453114, 5.138946, -2.563924]
pre_activation_std: [2.078203, 2.822516, 2.153514, 3.823768, 2.197541]
### 2
mean: [-1.764059, -0.506733, 4.260228, -1.300628, -3.009602]
std: [2.050402, 1.359830, 3.831732, 1.279919, 2.797995]
fourier: [[30.206623, 35.775412, 37.238537, 38.492161, 158.765324], [22.975868, 23.613550, 24.750622, 26.708185, 45.606007], [61.599795, 65.011196, 65.068332, 71.084010, 383.420491], [19.415080, 20.880167, 24.590322, 25.266588, 117.056541], [42.408565, 47.802713, 50.867105, 51.269235, 270.864110]]
input_correlations: [[-0.422920, -0.925383, -0.362910, -0.951751, -0.179064, 0.000000, 0.000000, 0.000000], [-0.010155, -0.960834, 0.001134, -0.558734, -0.179598, 0.000000, 0.000000, 0.000000], [0.280581, 0.985312, 0.231918, 0.864247, 0.167130, 0.000000, 0.000000, 0.000000], [-0.503666, -0.814454, -0.428020, -0.996841, -0.136358, 0.000000, 0.000000, 0.000000], [-0.384955, -0.942206, -0.326087, -0.937150, -0.171523, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.764059, -0.506733, 4.260228, -1.300628, -3.009602]
pre_activation_std: [2.050402, 1.359830, 3.831732, 1.279919, 2.797995]
### 4
mean: [-0.080174, -2.286235, 2.686643, 0.367056, -1.365839]
std: [0.777528, 2.274360, 2.922832, 0.195443, 0.725205]
fourier: [[12.445032, 12.554701, 12.793164, 13.572277, 13.791615], [36.774435, 37.139233, 39.379797, 42.187216, 205.761185], [46.506666, 49.231490, 50.617785, 54.274792, 241.797911], [3.096540, 3.217681, 3.382175, 4.370404, 33.034996], [11.520149, 12.435156, 15.174671, 15.346897, 122.925553]]
input_correlations: [[0.065906, 0.330284, -0.997832, -0.093545, -0.509398, 0.000000, 0.000000, 0.000000], [0.145500, 0.244833, -0.996121, -0.018695, -0.462842, 0.000000, 0.000000, 0.000000], [-0.023496, -0.400179, 0.993185, 0.134813, 0.510694, 0.000000, 0.000000, 0.000000], [-0.615476, 0.826240, -0.492921, -0.672033, -0.515127, 0.000000, 0.000000, 0.000000], [0.442665, 0.073437, -0.931580, 0.277361, -0.304220, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.080174, -2.286235, 2.686643, 0.367056, -1.365839]
pre_activation_std: [0.777528, 2.274360, 2.922832, 0.195443, 0.725205]
### 6
mean: [2.069890, 0.007159, 1.628622, -1.837451, -0.133609]
std: [2.283004, 0.437344, 2.217781, 1.384324, 1.114356]
fourier: [[36.597117, 37.986031, 40.299138, 42.037311, 186.290041], [6.993805, 7.097713, 7.206970, 7.753074, 7.860312], [35.494025, 36.685807, 38.831629, 42.486373, 146.576008], [21.697702, 23.281728, 24.269603, 25.219834, 165.370620], [17.142550, 17.916889, 18.588004, 19.364905, 21.718871]]
input_correlations: [[-0.795352, 0.684967, 0.999382, -0.559310, 0.816180, 0.000000, 0.000000, 0.000000], [-0.825924, 0.701595, 0.993255, -0.515959, 0.821156, 0.000000, 0.000000, 0.000000], [-0.814040, 0.698601, 0.997456, -0.593762, 0.810680, 0.000000, 0.000000, 0.000000], [0.761809, -0.661148, -0.999541, 0.558182, -0.808961, 0.000000, 0.000000, 0.000000], [0.787750, -0.716540, -0.997153, 0.622382, -0.834689, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.069890, 0.007159, 1.628622, -1.837451, -0.133609]
pre_activation_std: [2.283004, 0.437344, 2.217781, 1.384324, 1.114356]
### 8
mean: [-1.138937, 2.014959, -0.898015, 2.377270, -1.306243]
std: [0.508837, 2.791906, 1.724405, 3.164085, 0.772234]
fourier: [[8.415589, 8.430121, 8.544996, 9.326546, 102.504297], [44.776444, 46.265778, 49.034806, 53.772979, 181.346252], [27.659169, 28.467557, 30.238570, 33.767243, 80.821338], [50.684696, 52.826595, 55.627596, 60.792540, 213.954318], [12.337883, 12.829341, 13.745918, 13.898180, 117.561843]]
input_correlations: [[-0.993925, -0.993598, -0.993583, -0.892206, 0.643293, 0.000000, 0.000000, 0.000000], [0.997128, 0.973049, 0.997037, 0.942721, -0.770220, 0.000000, 0.000000, 0.000000], [-0.994135, -0.964944, -0.994765, -0.952099, 0.788727, 0.000000, 0.000000, 0.000000], [0.997792, 0.975237, 0.998100, 0.940464, -0.762242, 0.000000, 0.000000, 0.000000], [-0.999589, -0.990371, -0.998099, -0.912190, 0.704449, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.138937, 2.014959, -0.898015, 2.377270, -1.306243]
pre_activation_std: [0.508837, 2.791906, 1.724405, 3.164085, 0.772234]
### 10
mean: [-1.861861, -1.549359, -0.779331, -1.265229, 3.504773]
std: [2.071443, 1.791244, 1.150783, 2.184827, 4.964506]
fourier: [[33.103730, 35.162723, 37.041692, 38.577074, 167.567531], [28.724050, 30.232579, 31.896260, 33.856933, 139.442278], [18.645619, 18.903950, 20.115133, 22.769490, 70.139832], [35.498908, 37.344996, 39.240403, 39.807888, 113.870630], [79.721717, 83.397206, 88.200139, 94.632226, 315.429557]]
input_correlations: [[-0.983494, -0.999874, 0.531204, -0.999879, -0.990210, 0.000000, 0.000000, 0.000000], [-0.979991, -0.999931, 0.552167, -0.999949, -0.988975, 0.000000, 0.000000, 0.000000], [-0.962713, -0.995052, 0.623953, -0.995115, -0.980639, 0.000000, 0.000000, 0.000000], [-0.987329, -0.998782, 0.501934, -0.998766, -0.990676, 0.000000, 0.000000, 0.000000], [0.977189, 0.999655, -0.565411, 0.999662, 0.988089, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.861861, -1.549359, -0.779331, -1.265229, 3.504773]
pre_activation_std: [2.071443, 1.791244, 1.150783, 2.184827, 4.964506]
### 12
mean: [-1.663792]
std: [2.248564]
fourier: [[36.216533, 38.065275, 40.266955, 42.808219, 149.741236]]
input_correlations: [[-0.827422, -0.546096, 0.386076, 0.628057, -0.999306, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.663792]
pre_activation_std: [2.248564]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
starts_with | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.0725516676902771, "std": 0.05501123517751694, "fourier": [0.8376402963793961, 0.9183128573314899, 0.9269149794392777, 0.9634262688600106, 6.52964994431801], "input_correlations": [-0.21713662961018868, -0.30471557737767146, -0.3318538638394295, -0.46334680215316887, -0.9154136794557624, 0.0, 0.0, 0.0], "pre_activation_mean": -3.084223508834839, "pre_activation_std": 2.078202724456787}, "1": {"mean": -0.05675384774804115, "std": 0.051794230937957764, "fourier": [0.8029249410195552, 0.8093585378260519, 0.8197202584257776, 0.853253979530089, 5.107846529449233], "input_correlations": [0.9343754694877018, 0.5293799029263806, 0.430179727944908, -0.05379159441279718, -0.05787969858905838, 0.0, 0.0, 0.0], "pre_activation_mean": 2.2872073650360107, "pre_activation_std": 2.8225162029266357}, "2": {"mean": 0.004374396987259388, "std": 0.12569954991340637, "fourier": [1.9597282320704488, 2.0100456083094596, 2.122216910685502, 2.183834396696145, 2.2097830742654936], "input_correlations": [-0.2557803763862878, -0.4120994553136813, -0.5661181172344139, -0.6434177695495721, -0.7013340371549821, 0.0, 0.0, 0.0], "pre_activation_mean": -3.4531137943267822, "pre_activation_std": 2.1535139083862305}, "3": {"mean": 0.09467833489179611, "std": 0.15035361051559448, "fourier": [2.501753277970172, 2.515252575353197, 2.5575656098085937, 2.896237642276729, 8.52105102995688], "input_correlations": [0.7116413692379339, 0.7355392194603494, 0.2861414592122353, 0.5875527959056247, 0.1520307982273477, 0.0, 0.0, 0.0], "pre_activation_mean": 5.138945579528809, "pre_activation_std": 3.823768138885498}, "4": {"mean": 3.6437466144561768, "std": 4.848215579986572, "fourier": [77.57744288871574, 83.00797959987587, 86.80838291240048, 90.73148026241105, 327.9371894001961], "input_correlations": [-0.3900073746599913, -0.1956320658037809, -0.7039295790267108, -0.1013454973530338, -0.8365019527575159, 0.0, 0.0, 0.0], "pre_activation_mean": -2.5639243125915527, "pre_activation_std": 2.1975414752960205}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -1.764059066772461, "std": 2.0504016876220703, "fourier": [30.206622657833783, 35.775412469367545, 37.238536658600765, 38.492160793427495, 158.76532411575317], "input_correlations": [-0.42292008559116384, -0.9253829976995583, -0.3629098515632803, -0.9517508553709266, -0.17906388995007902, 0.0, 0.0, 0.0], "pre_activation_mean": -1.764059066772461, "pre_activation_std": 2.0504016876220703}, "1": {"mean": -0.5067334175109863, "std": 1.3598302602767944, "fourier": [22.975868344655968, 23.61355000226789, 24.750622123199413, 26.708184862526476, 45.606007263064384], "input_correlations": [-0.010155030015461218, -0.9608342777125387, 0.0011336387374973086, -0.5587338593632193, -0.17959770385872104, 0.0, 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"epoch": 3, "global_epoch": 8, "train_loss": 0.6563593745231628, "train_acc": 0.605, "val_loss": 0.6567184329032898, "val_acc": 0.6}], "summary": {"total_epochs": 9, "degraded_epochs": 5, "improved_epochs": 4, "patterns": ["starts_with"], "degraded_stage": {"initial_val_loss": 0.7261789441108704, "final_val_loss": 0.603113055229187, "initial_val_acc": 0.44, "final_val_acc": 0.44, "best_val_acc": 0.44}, "improved_stage": {"initial_val_loss": 0.5169818997383118, "final_val_loss": 0.6567184329032898, "initial_val_acc": 0.78, "final_val_acc": 0.6, "best_val_acc": 0.78, "best_epoch": 5}, "improvement": 0.34, "first_improvement_epoch": 4}} |
80 | {"target_pattern": "vowel_consonant", "degraded_accuracy": 0.48, "improved_accuracy": 0.66, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 6718, "learning_rate": 0.09314226785800217, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "vowel_consonant", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["vowel_consonant"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
0.086704,
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0.169669,
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],
[
0.00027,
0.044031,
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0.081371,
0.261498,
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],
[
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0.030832,
0.032402,
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]
],
"network.4.bias": [
0.316065,
0.172087,
0.348283,
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0.523002,
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],
"network.6.weight": [
[
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0.389327,
0.024234,
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0.043131,
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[
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0.03383,
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[
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"network.8.weight": [
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],
"network.8.bias": [
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.000000, 0.501027, 0.000000, 0.000000]
std: [0.000000, 0.000000, 0.000000, 0.000000, 0.424370, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [6.578706, 6.770210, 7.002796, 8.834717, 45.092409], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.921035, 0.436042, 0.483061, -0.288016, 0.125442, 0.000000, 0.000000, 0.000000], [-0.554978, -0.833588, -0.686328, -0.285160, -0.069476, 0.000000, 0.000000, 0.000000], [0.613326, -0.071019, 0.673811, -0.597035, 0.070803, 0.000000, 0.000000, 0.000000], [-0.551369, -0.828305, -0.703246, -0.182653, -0.187247, 0.000000, 0.000000, 0.000000], [-0.742680, 0.106594, 0.143543, 0.267876, 0.317188, 0.000000, 0.000000, 0.000000], [-0.558630, -0.567897, -0.792813, -0.478410, -0.313636, 0.000000, 0.000000, 0.000000], [0.392345, 0.328660, -0.237239, 0.711053, 0.491483, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.252822, -1.846893, 0.779364, -1.817065, 0.812378, -3.264830, 1.474145]
pre_activation_std: [1.774041, 1.167755, 1.375162, 1.128321, 1.280534, 2.101930, 2.129782]
### 2
mean: [1.413376, 0.371820, -2.045386, -1.556087, -1.890993, -0.664136, -0.179814]
std: [1.512653, 1.129833, 0.963789, 0.971589, 0.949463, 0.643878, 0.708909]
fourier: [[24.033157, 24.717407, 29.582077, 32.137933, 127.203826], [17.125653, 17.825851, 20.018666, 21.035507, 33.463771], [15.822827, 16.105572, 18.099584, 22.168656, 184.084706], [17.243234, 17.441556, 19.205679, 19.947551, 140.047814], [16.311227, 17.027797, 18.322360, 21.673654, 170.189334], [11.244762, 11.485824, 11.984626, 13.912511, 59.772253], [10.220933, 10.847059, 13.721131, 15.936366, 16.183298]]
input_correlations: [[0.952007, 0.000000, 0.929649, 0.000000, -0.478352, 0.000000, -0.012579, 0.000000], [-0.569130, 0.000000, -0.772522, 0.000000, 0.485933, 0.000000, 0.672718, 0.000000], [-0.724446, 0.000000, -0.636295, 0.000000, -0.131475, 0.000000, -0.569398, 0.000000], [-0.777265, 0.000000, -0.421046, 0.000000, -0.010572, 0.000000, -0.700957, 0.000000], [-0.843256, 0.000000, -0.671876, 0.000000, 0.059421, 0.000000, -0.566647, 0.000000], [-0.884035, 0.000000, -0.561789, 0.000000, 0.326631, 0.000000, -0.628763, 0.000000], [0.729278, 0.000000, 0.946123, 0.000000, -0.569154, 0.000000, -0.330244, 0.000000]]
pre_activation_mean: [1.413376, 0.371820, -2.045386, -1.556087, -1.890993, -0.664136, -0.179814]
pre_activation_std: [1.512653, 1.129833, 0.963789, 0.971589, 0.949463, 0.643878, 0.708909]
### 4
mean: [0.922390, -0.290185, 0.771709, 0.453646, 0.499187, -0.294043, -0.486270]
std: [0.554548, 0.269928, 0.735925, 0.413335, 0.220394, 0.168876, 0.431285]
fourier: [[8.900122, 9.494376, 11.175815, 11.713090, 83.015140], [4.727987, 4.750405, 4.967134, 6.946715, 26.116665], [11.173537, 11.475559, 13.020912, 16.296016, 69.453785], [7.227054, 7.266679, 7.413668, 10.344691, 40.828141], [3.236283, 3.425894, 3.576210, 4.560679, 44.926821], [2.717445, 2.767759, 3.173342, 3.437921, 26.463837], [6.790156, 6.869460, 8.752487, 9.140768, 43.764268]]
input_correlations: [[0.995116, -0.457177, 0.000000, 0.000000, 0.000000, 0.000000, 0.844582, 0.000000], [-0.758560, -0.136085, 0.000000, 0.000000, 0.000000, 0.000000, -0.680684, 0.000000], [0.976206, -0.701082, 0.000000, 0.000000, 0.000000, 0.000000, 0.838269, 0.000000], [0.527419, 0.419348, 0.000000, 0.000000, 0.000000, 0.000000, 0.436299, 0.000000], [0.765383, -0.942859, 0.000000, 0.000000, 0.000000, 0.000000, 0.512794, 0.000000], [-0.865739, 0.568508, 0.000000, 0.000000, 0.000000, 0.000000, -0.978297, 0.000000], [-0.982857, 0.554058, 0.000000, 0.000000, 0.000000, 0.000000, -0.918119, 0.000000]]
pre_activation_mean: [0.922390, -0.290185, 0.771709, 0.453646, 0.499187, -0.294043, -0.486270]
pre_activation_std: [0.554548, 0.269928, 0.735925, 0.413335, 0.220394, 0.168876, 0.431285]
### 6
mean: [-0.693999, -0.690276, -0.655691, -0.321119, 0.452787, -0.609914, -0.789041]
std: [0.132998, 0.253495, 0.090262, 0.076643, 0.491925, 0.183329, 0.467704]
fourier: [[2.230267, 2.321427, 2.633153, 3.124494, 62.459896], [3.811464, 3.900153, 4.192463, 5.599746, 62.124827], [1.305611, 1.310588, 1.371059, 1.973915, 59.012191], [1.219915, 1.230661, 1.294543, 1.505586, 28.900744], [7.333416, 7.428306, 7.903674, 10.783526, 40.750825], [2.807444, 2.911853, 3.380618, 3.970670, 54.892287], [7.502741, 7.631810, 9.330259, 9.648939, 71.013672]]
input_correlations: [[-0.519034, 0.433828, -0.294225, -0.989490, 0.165683, 0.000000, 0.000000, 0.000000], [-0.939780, 0.072990, -0.986920, -0.309728, -0.901398, 0.000000, 0.000000, 0.000000], [-0.833028, -0.058926, -0.930808, -0.088603, -0.977366, 0.000000, 0.000000, 0.000000], [0.440233, 0.268587, 0.647926, -0.441491, 0.892260, 0.000000, 0.000000, 0.000000], [0.854270, 0.031113, 0.955407, 0.109620, 0.939637, 0.000000, 0.000000, 0.000000], [-0.966257, 0.114231, -0.999491, -0.390056, -0.830086, 0.000000, 0.000000, 0.000000], [-0.996176, 0.175198, -0.980971, -0.554780, -0.755587, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.693999, -0.690276, -0.655691, -0.321119, 0.452787, -0.609914, -0.789041]
pre_activation_std: [0.132998, 0.253495, 0.090262, 0.076643, 0.491925, 0.183329, 0.467704]
### 8
mean: [-0.096370]
std: [0.196008]
fourier: [[3.038575, 3.127027, 3.234454, 4.080583, 8.673344]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.096370]
pre_activation_std: [0.196008]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| vowel_consonant | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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],
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[
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[
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],
[
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],
[
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0.476292
]
],
"network.0.bias": [
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"network.2.weight": [
[
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[
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]
],
"network.2.bias": [
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"network.4.weight": [
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[
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[
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[
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[
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[
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0.032402,
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],
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.000000, 0.501027, 0.000000, 0.000000]
std: [0.000000, 0.000000, 0.000000, 0.000000, 0.424370, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [6.578706, 6.770210, 7.002796, 8.834717, 45.092409], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.921035, 0.436042, 0.483061, -0.288016, 0.125442, 0.000000, 0.000000, 0.000000], [-0.554978, -0.833588, -0.686328, -0.285160, -0.069476, 0.000000, 0.000000, 0.000000], [0.613326, -0.071019, 0.673811, -0.597035, 0.070803, 0.000000, 0.000000, 0.000000], [-0.551369, -0.828305, -0.703246, -0.182653, -0.187247, 0.000000, 0.000000, 0.000000], [-0.742680, 0.106594, 0.143543, 0.267876, 0.317188, 0.000000, 0.000000, 0.000000], [-0.558630, -0.567897, -0.792813, -0.478410, -0.313636, 0.000000, 0.000000, 0.000000], [0.392345, 0.328660, -0.237239, 0.711053, 0.491483, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.252822, -1.846893, 0.779364, -1.817065, 0.812378, -3.264830, 1.474145]
pre_activation_std: [1.774041, 1.167755, 1.375162, 1.128321, 1.280534, 2.101930, 2.129782]
### 2
mean: [1.413376, 0.371820, -2.045386, -1.556087, -1.890993, -0.664136, -0.179814]
std: [1.512653, 1.129833, 0.963789, 0.971589, 0.949463, 0.643878, 0.708909]
fourier: [[24.033157, 24.717407, 29.582077, 32.137933, 127.203826], [17.125653, 17.825851, 20.018666, 21.035507, 33.463771], [15.822827, 16.105572, 18.099584, 22.168656, 184.084706], [17.243234, 17.441556, 19.205679, 19.947551, 140.047814], [16.311227, 17.027797, 18.322360, 21.673654, 170.189334], [11.244762, 11.485824, 11.984626, 13.912511, 59.772253], [10.220933, 10.847059, 13.721131, 15.936366, 16.183298]]
input_correlations: [[0.952007, 0.000000, 0.929649, 0.000000, -0.478352, 0.000000, -0.012579, 0.000000], [-0.569130, 0.000000, -0.772522, 0.000000, 0.485933, 0.000000, 0.672718, 0.000000], [-0.724446, 0.000000, -0.636295, 0.000000, -0.131475, 0.000000, -0.569398, 0.000000], [-0.777265, 0.000000, -0.421046, 0.000000, -0.010572, 0.000000, -0.700957, 0.000000], [-0.843256, 0.000000, -0.671876, 0.000000, 0.059421, 0.000000, -0.566647, 0.000000], [-0.884035, 0.000000, -0.561789, 0.000000, 0.326631, 0.000000, -0.628763, 0.000000], [0.729278, 0.000000, 0.946123, 0.000000, -0.569154, 0.000000, -0.330244, 0.000000]]
pre_activation_mean: [1.413376, 0.371820, -2.045386, -1.556087, -1.890993, -0.664136, -0.179814]
pre_activation_std: [1.512653, 1.129833, 0.963789, 0.971589, 0.949463, 0.643878, 0.708909]
### 4
mean: [0.922390, -0.290185, 0.771709, 0.453646, 0.499187, -0.294043, -0.486270]
std: [0.554548, 0.269928, 0.735925, 0.413335, 0.220394, 0.168876, 0.431285]
fourier: [[8.900122, 9.494376, 11.175815, 11.713090, 83.015140], [4.727987, 4.750405, 4.967134, 6.946715, 26.116665], [11.173537, 11.475559, 13.020912, 16.296016, 69.453785], [7.227054, 7.266679, 7.413668, 10.344691, 40.828141], [3.236283, 3.425894, 3.576210, 4.560679, 44.926821], [2.717445, 2.767759, 3.173342, 3.437921, 26.463837], [6.790156, 6.869460, 8.752487, 9.140768, 43.764268]]
input_correlations: [[0.995116, -0.457177, 0.000000, 0.000000, 0.000000, 0.000000, 0.844582, 0.000000], [-0.758560, -0.136085, 0.000000, 0.000000, 0.000000, 0.000000, -0.680684, 0.000000], [0.976206, -0.701082, 0.000000, 0.000000, 0.000000, 0.000000, 0.838269, 0.000000], [0.527419, 0.419348, 0.000000, 0.000000, 0.000000, 0.000000, 0.436299, 0.000000], [0.765383, -0.942859, 0.000000, 0.000000, 0.000000, 0.000000, 0.512794, 0.000000], [-0.865739, 0.568508, 0.000000, 0.000000, 0.000000, 0.000000, -0.978297, 0.000000], [-0.982857, 0.554058, 0.000000, 0.000000, 0.000000, 0.000000, -0.918119, 0.000000]]
pre_activation_mean: [0.922390, -0.290185, 0.771709, 0.453646, 0.499187, -0.294043, -0.486270]
pre_activation_std: [0.554548, 0.269928, 0.735925, 0.413335, 0.220394, 0.168876, 0.431285]
### 6
mean: [-0.693999, -0.690276, -0.655691, -0.321119, 0.452787, -0.609914, -0.789041]
std: [0.132998, 0.253495, 0.090262, 0.076643, 0.491925, 0.183329, 0.467704]
fourier: [[2.230267, 2.321427, 2.633153, 3.124494, 62.459896], [3.811464, 3.900153, 4.192463, 5.599746, 62.124827], [1.305611, 1.310588, 1.371059, 1.973915, 59.012191], [1.219915, 1.230661, 1.294543, 1.505586, 28.900744], [7.333416, 7.428306, 7.903674, 10.783526, 40.750825], [2.807444, 2.911853, 3.380618, 3.970670, 54.892287], [7.502741, 7.631810, 9.330259, 9.648939, 71.013672]]
input_correlations: [[-0.519034, 0.433828, -0.294225, -0.989490, 0.165683, 0.000000, 0.000000, 0.000000], [-0.939780, 0.072990, -0.986920, -0.309728, -0.901398, 0.000000, 0.000000, 0.000000], [-0.833028, -0.058926, -0.930808, -0.088603, -0.977366, 0.000000, 0.000000, 0.000000], [0.440233, 0.268587, 0.647926, -0.441491, 0.892260, 0.000000, 0.000000, 0.000000], [0.854270, 0.031113, 0.955407, 0.109620, 0.939637, 0.000000, 0.000000, 0.000000], [-0.966257, 0.114231, -0.999491, -0.390056, -0.830086, 0.000000, 0.000000, 0.000000], [-0.996176, 0.175198, -0.980971, -0.554780, -0.755587, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.693999, -0.690276, -0.655691, -0.321119, 0.452787, -0.609914, -0.789041]
pre_activation_std: [0.132998, 0.253495, 0.090262, 0.076643, 0.491925, 0.183329, 0.467704]
### 8
mean: [-0.096370]
std: [0.196008]
fourier: [[3.038575, 3.127027, 3.234454, 4.080583, 8.673344]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.096370]
pre_activation_std: [0.196008]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.389327, 0.024234, -0.434748, -0.219812, 0.043131, -0.203211], [-0.420044, 0.053007, 0.03383, 0.114538, -0.368469, -0.176845, 0.102982], [-0.051974, -0.17604, -0.019103, 0.022905, -0.25549, 0.045689, 0.107099], [-0.068547, -0.110698, 0.145892, -0.127155, 0.021392, 0.309415, -0.216728], [0.213185, 0.750495, 0.567213, -0.426484, 0.133862, -0.121619, 0.079821], [-0.161, -0.04589, -0.181619, 0.087815, 0.094513, -0.072374, -0.194324], [-0.189659, -0.278903, -0.325025, -0.282968, -0.453942, -0.111815, -0.570706]], "network.6.bias": [-0.495882, -0.19843, -0.474976, -0.325858, -0.067157, -0.404501, 0.002791], "network.8.weight": [[-0.403009, -0.011095, 0.076751, -0.142416, -0.46188, 0.060522, -0.191723]], "network.8.bias": [0.135044]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7236104905605316, "train_acc": 0.405, "val_loss": 0.9656438231468201, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.7459802329540253, "train_acc": 0.58, "val_loss": 0.6909915208816528, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6926662027835846, "train_acc": 0.51, "val_loss": 0.6650679707527161, "val_acc": 0.66}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.6784869432449341, "train_acc": 0.605, "val_loss": 0.630063533782959, "val_acc": 0.64}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6256778836250305, "train_acc": 0.63, "val_loss": 0.6342429518699646, "val_acc": 0.62}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.6080600619316101, "train_acc": 0.635, "val_loss": 0.5976477265357971, "val_acc": 0.64}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.6006996929645538, "train_acc": 0.645, "val_loss": 0.5698751211166382, "val_acc": 0.66}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.5949380993843079, "train_acc": 0.64, "val_loss": 0.57026207447052, "val_acc": 0.66}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.591304212808609, "train_acc": 0.64, "val_loss": 0.6003682613372803, "val_acc": 0.64}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.5887546241283417, "train_acc": 0.635, "val_loss": 0.6048255562782288, "val_acc": 0.6}], "summary": {"total_epochs": 10, "degraded_epochs": 2, "improved_epochs": 8, "patterns": ["vowel_consonant"], "degraded_stage": {"initial_val_loss": 0.9656438231468201, "final_val_loss": 0.6909915208816528, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6650679707527161, "final_val_loss": 0.6048255562782288, "initial_val_acc": 0.66, "final_val_acc": 0.6, "best_val_acc": 0.66, "best_epoch": 2}, "improvement": 0.18000000000000005, "first_improvement_epoch": 1}} |
81 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.5, "improved_accuracy": 0.9, "improvement": 0.4, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 6959, "learning_rate": 0.022836103578526626, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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0.060563
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[
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0.369291
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[
0.202486,
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0.477794,
-0.237122,
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],
[
-0.670784,
0.267961,
0.656278,
0.115494,
0.553588
]
],
"network.0.bias": [
-0.167272,
0.137476,
-0.705381,
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0.224968
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"network.2.weight": [
[
0.308529,
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-0.177095,
0.272027
],
[
0.134121,
0.39638,
0.139904,
0.16734,
0.072364,
0.461477
],
[
0.385612,
0.106359,
0.432999,
0.215145,
0.147729,
-0.105225
],
[
-0.162569,
0.498839,
-0.352937,
0.485798,
-0.293649,
-0.10124
],
[
0.397624,
-0.153035,
0.010127,
0.103222,
0.037176,
0.528493
],
[
-0.221722,
0.681812,
0.494246,
0.013197,
0.499466,
0.181594
]
],
"network.2.bias": [
0.22697,
-0.328776,
0.082677,
0.14532,
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-0.618401
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"network.4.weight": [
[
0.196702,
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0.272835,
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-0.019658,
0.062893
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[
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0.228898,
0.697276,
0.197753,
0.549488
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[
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-0.250997,
-0.085017,
0.334061,
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-0.406168
],
[
0.547958,
0.022648,
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0.41212,
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],
[
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-0.353831,
-0.041323
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[
0.002201,
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0.0433,
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0.024309
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],
"network.4.bias": [
0.02295,
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0.031,
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"network.6.weight": [
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[
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[
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[
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[
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[
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],
"network.6.bias": [
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"network.8.weight": [
[
0.102704,
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0.01599
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[
0.332276,
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[
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[
0.231151,
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0.646577
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[
0.329351,
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0.300366,
0.383954
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[
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0.10916,
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]
],
"network.8.bias": [
-0.397842,
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0.136149,
-0.020871
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"network.10.weight": [
[
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],
[
-0.074757,
0.399697,
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0.321514,
0.479568,
-0.104556
],
[
0.371013,
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0.215579,
-0.106627,
0.455871,
-0.128114
],
[
-0.693521,
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0.397212,
-0.407535,
-0.786498,
0.253307
],
[
0.298242,
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],
[
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]
],
"network.10.bias": [
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],
"network.12.weight": [
[
0.560965,
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]
],
"network.12.bias": [
-0.56264
]
}
## Activation Signature
### 0
mean: [0.198666, 0.361167, 0.496543, 0.691449, 0.425767, 0.034013]
std: [0.471622, 0.703964, 0.148985, 0.756140, 0.797715, 0.228760]
fourier: [[7.221961, 7.419185, 8.023057, 8.571556, 17.879913], [10.911712, 11.075633, 11.857199, 12.747927, 32.505000], [2.168561, 2.245860, 2.452739, 2.511520, 44.688868], [11.891542, 12.068843, 12.262163, 12.949026, 62.230408], [12.291658, 12.562775, 13.456009, 14.491080, 38.319032], [3.395915, 3.520730, 3.757104, 3.892660, 4.298009]]
input_correlations: [[-0.552204, -0.432349, -0.359345, -0.732729, 0.022393, 0.000000, 0.000000, 0.000000], [0.906199, 0.124047, -0.043676, 0.068021, 0.205451, 0.000000, 0.000000, 0.000000], [0.676254, 0.516137, 0.603990, 0.584415, 0.338781, 0.000000, 0.000000, 0.000000], [-0.548794, -0.500647, -0.559575, -0.135729, 0.480756, 0.000000, 0.000000, 0.000000], [0.554126, 0.683022, 0.667069, -0.151431, -0.214312, 0.000000, 0.000000, 0.000000], [-0.318631, 0.207135, 0.602600, 0.325808, 0.555843, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.493225, 0.602747, 1.683203, 0.108321, 1.081019, 2.179821]
pre_activation_std: [1.112566, 1.547444, 1.638804, 0.960996, 1.726542, 1.950244]
### 2
mean: [-0.216631, 1.385379, 0.888973, -0.481890, 1.640592, 1.792666]
std: [1.241145, 1.054070, 0.848599, 0.987747, 1.063643, 2.060056]
fourier: [[19.496808, 19.722879, 20.577405, 23.155399, 23.759365], [17.404856, 17.955390, 19.447828, 21.167186, 124.684148], [13.678904, 13.786150, 13.942201, 17.524796, 80.007618], [14.223140, 14.712098, 14.903540, 19.524615, 43.370138], [15.780548, 16.359716, 17.473015, 21.474876, 147.653320], [33.542024, 35.296219, 35.803602, 41.678259, 161.339930]]
input_correlations: [[-0.145776, -0.759636, -0.818209, 0.714920, -0.681837, 0.174552, 0.000000, 0.000000], [0.262124, 0.398671, 0.804552, -0.051233, 0.531619, 0.731291, 0.000000, 0.000000], [0.350667, 0.817743, 0.935917, -0.369322, 0.647507, 0.059659, 0.000000, 0.000000], [-0.013614, 0.125904, -0.566041, 0.557523, -0.697849, -0.633330, 0.000000, 0.000000], [0.070610, -0.462636, 0.196453, 0.215618, 0.139574, 0.986637, 0.000000, 0.000000], [0.225482, 0.771861, 0.909375, -0.435009, 0.781450, 0.212377, 0.000000, 0.000000]]
pre_activation_mean: [-0.216631, 1.385379, 0.888973, -0.481890, 1.640592, 1.792666]
pre_activation_std: [1.241145, 1.054070, 0.848599, 0.987747, 1.063643, 2.060056]
### 4
mean: [-0.273458, 1.522496, -1.162233, 0.299680, -0.958063, -0.804821]
std: [0.468987, 1.367466, 1.224600, 1.373817, 0.583916, 0.433666]
fourier: [[6.882601, 7.736913, 8.359446, 8.506982, 24.611260], [20.059052, 22.917258, 22.924501, 28.400832, 137.024602], [19.718536, 19.729953, 20.068192, 24.773080, 104.600982], [22.709323, 23.072691, 24.987372, 26.881013, 26.971184], [9.507232, 9.991709, 10.491176, 11.041443, 86.225682], [7.198325, 7.509261, 7.611568, 8.043973, 72.433849]]
input_correlations: [[0.106314, -0.780517, -0.203186, 0.637584, -0.887250, -0.349022, 0.000000, 0.000000], [-0.346999, 0.838014, 0.936951, -0.230532, 0.172097, 0.986790, 0.000000, 0.000000], [0.212740, -0.957567, -0.816937, 0.423376, -0.483200, -0.899636, 0.000000, 0.000000], [0.577231, -0.378072, -0.887169, 0.043815, 0.417740, -0.866493, 0.000000, 0.000000], [-0.125939, -0.943761, -0.441605, 0.327734, -0.844137, -0.553288, 0.000000, 0.000000], [-0.125953, -0.942188, -0.399701, 0.319366, -0.851361, -0.519516, 0.000000, 0.000000]]
pre_activation_mean: [-0.273458, 1.522496, -1.162233, 0.299680, -0.958063, -0.804821]
pre_activation_std: [0.468987, 1.367466, 1.224600, 1.373817, 0.583916, 0.433666]
### 6
mean: [0.016915, 0.862341, 0.497069, -1.575786, -0.064573, 0.264663]
std: [0.622588, 0.800200, 0.634219, 0.941155, 0.372989, 1.142419]
fourier: [[9.612427, 10.044975, 10.608558, 10.751990, 10.798240], [12.177177, 12.704828, 12.932926, 15.111801, 77.610733], [10.120156, 10.285602, 11.237001, 11.251366, 44.736224], [14.511337, 15.500251, 16.727769, 20.215549, 141.820753], [5.587154, 5.596373, 5.811547, 6.395658, 7.710824], [18.128139, 18.291096, 18.682844, 21.486909, 23.819637]]
input_correlations: [[-0.030498, -0.921881, -0.170796, 0.688086, -0.304737, -0.212483, 0.000000, 0.000000], [-0.109466, 0.927100, 0.019043, -0.801346, 0.161934, 0.057919, 0.000000, 0.000000], [-0.161693, 0.966180, -0.060884, -0.729777, 0.151337, 0.028900, 0.000000, 0.000000], [0.318582, -0.991953, 0.214604, 0.433539, -0.227334, -0.054898, 0.000000, 0.000000], [0.240154, -0.988991, 0.083064, 0.494639, -0.320752, -0.163942, 0.000000, 0.000000], [0.033068, -0.916610, -0.069433, 0.801854, -0.187376, -0.097899, 0.000000, 0.000000]]
pre_activation_mean: [0.016915, 0.862341, 0.497069, -1.575786, -0.064573, 0.264663]
pre_activation_std: [0.622588, 0.800200, 0.634219, 0.941155, 0.372989, 1.142419]
### 8
mean: [-0.583428, 0.113130, 0.767439, 0.100387, -0.172595, 0.073594]
std: [0.186259, 0.984583, 1.120212, 1.187079, 1.013175, 0.629203]
fourier: [[2.920865, 2.972938, 2.999835, 3.426650, 52.508498], [15.362972, 15.722793, 15.880810, 15.895685, 17.847608], [17.846860, 17.861740, 18.680948, 19.896606, 69.069467], [18.261455, 19.055123, 19.071515, 19.517870, 21.206232], [15.715193, 16.135697, 16.203813, 16.853673, 17.934245], [9.893514, 10.021758, 10.122298, 10.407831, 11.264298]]
input_correlations: [[0.887843, -0.978260, -0.944329, -0.847534, 0.876214, 0.879967, 0.000000, 0.000000], [0.904657, -0.966433, -0.931000, -0.837308, 0.870163, 0.908007, 0.000000, 0.000000], [-0.912124, 0.966099, 0.931668, 0.850367, -0.883278, -0.904662, 0.000000, 0.000000], [0.898711, -0.970846, -0.938264, -0.854225, 0.884330, 0.899053, 0.000000, 0.000000], [0.879754, -0.982328, -0.956865, -0.873255, 0.893836, 0.870391, 0.000000, 0.000000], [-0.917494, 0.960071, 0.923785, 0.835617, -0.871552, -0.914599, 0.000000, 0.000000]]
pre_activation_mean: [-0.583428, 0.113130, 0.767439, 0.100387, -0.172595, 0.073594]
pre_activation_std: [0.186259, 0.984583, 1.120212, 1.187079, 1.013175, 0.629203]
### 10
mean: [-0.341889, -0.221195, 0.659261, 0.505802, -0.180548, -0.598000]
std: [1.111862, 1.332584, 0.151063, 1.151998, 1.438420, 0.953903]
fourier: [[18.129823, 18.184830, 18.452475, 19.491560, 30.770048], [21.043683, 21.771227, 22.266879, 22.613739, 22.954560], [2.187428, 2.307463, 2.445197, 2.531391, 59.333465], [18.491409, 19.259624, 19.434374, 20.251136, 45.522208], [22.854664, 23.467798, 23.874899, 24.360992, 24.991817], [15.097311, 15.629322, 15.838630, 16.486872, 53.819956]]
input_correlations: [[0.863842, 0.884440, -0.962914, 0.878020, 0.845526, -0.927740, 0.000000, 0.000000], [0.901816, 0.919031, -0.938539, 0.914072, 0.885913, -0.893345, 0.000000, 0.000000], [-0.585246, -0.612415, 0.985706, -0.600160, -0.545720, 0.988953, 0.000000, 0.000000], [-0.950558, -0.963864, 0.882423, -0.960894, -0.941076, 0.825138, 0.000000, 0.000000], [0.906102, 0.923603, -0.934413, 0.918251, 0.890721, -0.889602, 0.000000, 0.000000], [0.816891, 0.839064, -0.983296, 0.832616, 0.795249, -0.954678, 0.000000, 0.000000]]
pre_activation_mean: [-0.341889, -0.221195, 0.659261, 0.505802, -0.180548, -0.598000]
pre_activation_std: [1.111862, 1.332584, 0.151063, 1.151998, 1.438420, 0.953903]
### 12
mean: [-0.801046]
std: [1.517934]
fourier: [[24.604307, 24.698313, 24.907744, 26.907772, 72.094127]]
input_correlations: [[0.936661, 0.943260, -0.723174, -0.872925, 0.943284, 0.900056, 0.000000, 0.000000]]
pre_activation_mean: [-0.801046]
pre_activation_std: [1.517934]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.330135,
0.059103,
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-0.445841,
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],
[
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0.139222,
0.046877
],
[
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0.050428,
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0.452721,
0.060563
],
[
-0.221126,
-0.083795,
-0.260472,
-0.094538,
0.369291
],
[
0.202486,
0.541448,
0.477794,
-0.237122,
-0.308084
],
[
-0.670784,
0.267961,
0.656278,
0.115494,
0.553588
]
],
"network.0.bias": [
-0.167272,
0.137476,
-0.705381,
0.827564,
-0.267193,
0.224968
],
"network.2.weight": [
[
0.308529,
-0.035315,
-0.559608,
0.502498,
-0.177095,
0.272027
],
[
0.134121,
0.39638,
0.139904,
0.16734,
0.072364,
0.461477
],
[
0.385612,
0.106359,
0.432999,
0.215145,
0.147729,
-0.105225
],
[
-0.162569,
0.498839,
-0.352937,
0.485798,
-0.293649,
-0.10124
],
[
0.397624,
-0.153035,
0.010127,
0.103222,
0.037176,
0.528493
],
[
-0.221722,
0.681812,
0.494246,
0.013197,
0.499466,
0.181594
]
],
"network.2.bias": [
0.22697,
-0.328776,
0.082677,
0.14532,
0.508587,
-0.618401
],
"network.4.weight": [
[
0.196702,
-0.522414,
0.272835,
0.528265,
-0.019658,
0.062893
],
[
-0.141661,
0.084428,
0.228898,
0.697276,
0.197753,
0.549488
],
[
-0.162902,
-0.250997,
-0.085017,
0.334061,
-0.287691,
-0.406168
],
[
0.547958,
0.022648,
-0.121285,
-0.833216,
0.41212,
-0.538728
],
[
-0.082884,
-0.1649,
-0.136395,
-0.152911,
-0.353831,
-0.041323
],
[
0.002201,
-0.376424,
0.0433,
-0.051324,
-0.109374,
0.024309
]
],
"network.4.bias": [
0.02295,
-0.096818,
0.436664,
0.624179,
0.031,
-0.21049
],
"network.6.weight": [
[
-0.438315,
-0.409995,
-0.974395,
0.131403,
-0.100318,
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],
[
-0.257483,
0.416922,
0.784612,
-0.45969,
-0.087853,
-0.019448
],
[
0.09781,
0.385118,
0.28125,
-0.237242,
-0.177463,
-0.305015
],
[
-0.349474,
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0.045831,
-0.22934,
0.11385,
0.371826
],
[
-0.012789,
-0.278379,
-0.251158,
-0.043083,
-0.213112,
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],
[
-0.5884,
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-0.618999,
0.63745,
-0.53163,
-0.675732
]
],
"network.6.bias": [
0.456937,
0.537809,
0.031783,
-0.31112,
0.280689,
0.558701
],
"network.8.weight": [
[
0.102704,
-0.319659,
0.172126,
0.35548,
0.208297,
0.01599
],
[
0.332276,
-0.502512,
-0.3883,
-0.248015,
-0.236059,
0.550343
],
[
-0.777148,
0.554895,
0.418615,
0.063337,
-0.118633,
-0.454887
],
[
0.231151,
-0.538075,
-0.53558,
0.036517,
0.476743,
0.646577
],
[
0.329351,
-0.457593,
-0.552188,
-0.469472,
0.300366,
0.383954
],
[
-0.450037,
0.143678,
0.43924,
-0.108485,
0.10916,
-0.322434
]
],
"network.8.bias": [
-0.397842,
0.334039,
0.493179,
0.394925,
0.136149,
-0.020871
],
"network.10.weight": [
[
0.239418,
0.318209,
-0.461659,
0.195612,
0.336219,
-0.788875
],
[
-0.074757,
0.399697,
-0.780463,
0.321514,
0.479568,
-0.104556
],
[
0.371013,
-0.181148,
0.215579,
-0.106627,
0.455871,
-0.128114
],
[
-0.693521,
-0.247455,
0.397212,
-0.407535,
-0.786498,
0.253307
],
[
0.298242,
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0.115995,
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],
[
-0.078505,
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0.310472,
-0.155589
]
],
"network.10.bias": [
-0.05555,
0.044274,
0.573977,
0.461287,
-0.03614,
-0.118679
],
"network.12.weight": [
[
0.560965,
0.458006,
-0.216286,
-0.861113,
0.416997,
0.294029
]
],
"network.12.bias": [
-0.56264
]
}
## Activation Signature
### 0
mean: [0.198666, 0.361167, 0.496543, 0.691449, 0.425767, 0.034013]
std: [0.471622, 0.703964, 0.148985, 0.756140, 0.797715, 0.228760]
fourier: [[7.221961, 7.419185, 8.023057, 8.571556, 17.879913], [10.911712, 11.075633, 11.857199, 12.747927, 32.505000], [2.168561, 2.245860, 2.452739, 2.511520, 44.688868], [11.891542, 12.068843, 12.262163, 12.949026, 62.230408], [12.291658, 12.562775, 13.456009, 14.491080, 38.319032], [3.395915, 3.520730, 3.757104, 3.892660, 4.298009]]
input_correlations: [[-0.552204, -0.432349, -0.359345, -0.732729, 0.022393, 0.000000, 0.000000, 0.000000], [0.906199, 0.124047, -0.043676, 0.068021, 0.205451, 0.000000, 0.000000, 0.000000], [0.676254, 0.516137, 0.603990, 0.584415, 0.338781, 0.000000, 0.000000, 0.000000], [-0.548794, -0.500647, -0.559575, -0.135729, 0.480756, 0.000000, 0.000000, 0.000000], [0.554126, 0.683022, 0.667069, -0.151431, -0.214312, 0.000000, 0.000000, 0.000000], [-0.318631, 0.207135, 0.602600, 0.325808, 0.555843, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.493225, 0.602747, 1.683203, 0.108321, 1.081019, 2.179821]
pre_activation_std: [1.112566, 1.547444, 1.638804, 0.960996, 1.726542, 1.950244]
### 2
mean: [-0.216631, 1.385379, 0.888973, -0.481890, 1.640592, 1.792666]
std: [1.241145, 1.054070, 0.848599, 0.987747, 1.063643, 2.060056]
fourier: [[19.496808, 19.722879, 20.577405, 23.155399, 23.759365], [17.404856, 17.955390, 19.447828, 21.167186, 124.684148], [13.678904, 13.786150, 13.942201, 17.524796, 80.007618], [14.223140, 14.712098, 14.903540, 19.524615, 43.370138], [15.780548, 16.359716, 17.473015, 21.474876, 147.653320], [33.542024, 35.296219, 35.803602, 41.678259, 161.339930]]
input_correlations: [[-0.145776, -0.759636, -0.818209, 0.714920, -0.681837, 0.174552, 0.000000, 0.000000], [0.262124, 0.398671, 0.804552, -0.051233, 0.531619, 0.731291, 0.000000, 0.000000], [0.350667, 0.817743, 0.935917, -0.369322, 0.647507, 0.059659, 0.000000, 0.000000], [-0.013614, 0.125904, -0.566041, 0.557523, -0.697849, -0.633330, 0.000000, 0.000000], [0.070610, -0.462636, 0.196453, 0.215618, 0.139574, 0.986637, 0.000000, 0.000000], [0.225482, 0.771861, 0.909375, -0.435009, 0.781450, 0.212377, 0.000000, 0.000000]]
pre_activation_mean: [-0.216631, 1.385379, 0.888973, -0.481890, 1.640592, 1.792666]
pre_activation_std: [1.241145, 1.054070, 0.848599, 0.987747, 1.063643, 2.060056]
### 4
mean: [-0.273458, 1.522496, -1.162233, 0.299680, -0.958063, -0.804821]
std: [0.468987, 1.367466, 1.224600, 1.373817, 0.583916, 0.433666]
fourier: [[6.882601, 7.736913, 8.359446, 8.506982, 24.611260], [20.059052, 22.917258, 22.924501, 28.400832, 137.024602], [19.718536, 19.729953, 20.068192, 24.773080, 104.600982], [22.709323, 23.072691, 24.987372, 26.881013, 26.971184], [9.507232, 9.991709, 10.491176, 11.041443, 86.225682], [7.198325, 7.509261, 7.611568, 8.043973, 72.433849]]
input_correlations: [[0.106314, -0.780517, -0.203186, 0.637584, -0.887250, -0.349022, 0.000000, 0.000000], [-0.346999, 0.838014, 0.936951, -0.230532, 0.172097, 0.986790, 0.000000, 0.000000], [0.212740, -0.957567, -0.816937, 0.423376, -0.483200, -0.899636, 0.000000, 0.000000], [0.577231, -0.378072, -0.887169, 0.043815, 0.417740, -0.866493, 0.000000, 0.000000], [-0.125939, -0.943761, -0.441605, 0.327734, -0.844137, -0.553288, 0.000000, 0.000000], [-0.125953, -0.942188, -0.399701, 0.319366, -0.851361, -0.519516, 0.000000, 0.000000]]
pre_activation_mean: [-0.273458, 1.522496, -1.162233, 0.299680, -0.958063, -0.804821]
pre_activation_std: [0.468987, 1.367466, 1.224600, 1.373817, 0.583916, 0.433666]
### 6
mean: [0.016915, 0.862341, 0.497069, -1.575786, -0.064573, 0.264663]
std: [0.622588, 0.800200, 0.634219, 0.941155, 0.372989, 1.142419]
fourier: [[9.612427, 10.044975, 10.608558, 10.751990, 10.798240], [12.177177, 12.704828, 12.932926, 15.111801, 77.610733], [10.120156, 10.285602, 11.237001, 11.251366, 44.736224], [14.511337, 15.500251, 16.727769, 20.215549, 141.820753], [5.587154, 5.596373, 5.811547, 6.395658, 7.710824], [18.128139, 18.291096, 18.682844, 21.486909, 23.819637]]
input_correlations: [[-0.030498, -0.921881, -0.170796, 0.688086, -0.304737, -0.212483, 0.000000, 0.000000], [-0.109466, 0.927100, 0.019043, -0.801346, 0.161934, 0.057919, 0.000000, 0.000000], [-0.161693, 0.966180, -0.060884, -0.729777, 0.151337, 0.028900, 0.000000, 0.000000], [0.318582, -0.991953, 0.214604, 0.433539, -0.227334, -0.054898, 0.000000, 0.000000], [0.240154, -0.988991, 0.083064, 0.494639, -0.320752, -0.163942, 0.000000, 0.000000], [0.033068, -0.916610, -0.069433, 0.801854, -0.187376, -0.097899, 0.000000, 0.000000]]
pre_activation_mean: [0.016915, 0.862341, 0.497069, -1.575786, -0.064573, 0.264663]
pre_activation_std: [0.622588, 0.800200, 0.634219, 0.941155, 0.372989, 1.142419]
### 8
mean: [-0.583428, 0.113130, 0.767439, 0.100387, -0.172595, 0.073594]
std: [0.186259, 0.984583, 1.120212, 1.187079, 1.013175, 0.629203]
fourier: [[2.920865, 2.972938, 2.999835, 3.426650, 52.508498], [15.362972, 15.722793, 15.880810, 15.895685, 17.847608], [17.846860, 17.861740, 18.680948, 19.896606, 69.069467], [18.261455, 19.055123, 19.071515, 19.517870, 21.206232], [15.715193, 16.135697, 16.203813, 16.853673, 17.934245], [9.893514, 10.021758, 10.122298, 10.407831, 11.264298]]
input_correlations: [[0.887843, -0.978260, -0.944329, -0.847534, 0.876214, 0.879967, 0.000000, 0.000000], [0.904657, -0.966433, -0.931000, -0.837308, 0.870163, 0.908007, 0.000000, 0.000000], [-0.912124, 0.966099, 0.931668, 0.850367, -0.883278, -0.904662, 0.000000, 0.000000], [0.898711, -0.970846, -0.938264, -0.854225, 0.884330, 0.899053, 0.000000, 0.000000], [0.879754, -0.982328, -0.956865, -0.873255, 0.893836, 0.870391, 0.000000, 0.000000], [-0.917494, 0.960071, 0.923785, 0.835617, -0.871552, -0.914599, 0.000000, 0.000000]]
pre_activation_mean: [-0.583428, 0.113130, 0.767439, 0.100387, -0.172595, 0.073594]
pre_activation_std: [0.186259, 0.984583, 1.120212, 1.187079, 1.013175, 0.629203]
### 10
mean: [-0.341889, -0.221195, 0.659261, 0.505802, -0.180548, -0.598000]
std: [1.111862, 1.332584, 0.151063, 1.151998, 1.438420, 0.953903]
fourier: [[18.129823, 18.184830, 18.452475, 19.491560, 30.770048], [21.043683, 21.771227, 22.266879, 22.613739, 22.954560], [2.187428, 2.307463, 2.445197, 2.531391, 59.333465], [18.491409, 19.259624, 19.434374, 20.251136, 45.522208], [22.854664, 23.467798, 23.874899, 24.360992, 24.991817], [15.097311, 15.629322, 15.838630, 16.486872, 53.819956]]
input_correlations: [[0.863842, 0.884440, -0.962914, 0.878020, 0.845526, -0.927740, 0.000000, 0.000000], [0.901816, 0.919031, -0.938539, 0.914072, 0.885913, -0.893345, 0.000000, 0.000000], [-0.585246, -0.612415, 0.985706, -0.600160, -0.545720, 0.988953, 0.000000, 0.000000], [-0.950558, -0.963864, 0.882423, -0.960894, -0.941076, 0.825138, 0.000000, 0.000000], [0.906102, 0.923603, -0.934413, 0.918251, 0.890721, -0.889602, 0.000000, 0.000000], [0.816891, 0.839064, -0.983296, 0.832616, 0.795249, -0.954678, 0.000000, 0.000000]]
pre_activation_mean: [-0.341889, -0.221195, 0.659261, 0.505802, -0.180548, -0.598000]
pre_activation_std: [1.111862, 1.332584, 0.151063, 1.151998, 1.438420, 0.953903]
### 12
mean: [-0.801046]
std: [1.517934]
fourier: [[24.604307, 24.698313, 24.907744, 26.907772, 72.094127]]
input_correlations: [[0.936661, 0.943260, -0.723174, -0.872925, 0.943284, 0.900056, 0.000000, 0.000000]]
pre_activation_mean: [-0.801046]
pre_activation_std: [1.517934]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.330135, 0.059103, -0.142391, -0.445841, 0.187056], [0.831174, -0.185263, -0.281421, 0.139222, 0.046877], [0.441619, 0.050428, 0.33587, 0.452721, 0.060563], [-0.221126, -0.083795, -0.260472, -0.094538, 0.369291], [0.202486, 0.541448, 0.477794, -0.237122, -0.308084], [-0.670784, 0.267961, 0.656278, 0.115494, 0.553588]], "network.0.bias": [-0.167272, 0.137476, -0.705381, 0.827564, -0.267193, 0.224968], "network.2.weight": [[0.308529, -0.035315, -0.559608, 0.502498, -0.177095, 0.272027], [0.134121, 0.39638, 0.139904, 0.16734, 0.072364, 0.461477], [0.385612, 0.106359, 0.432999, 0.215145, 0.147729, -0.105225], [-0.162569, 0.498839, -0.352937, 0.485798, -0.293649, -0.10124], [0.397624, -0.153035, 0.010127, 0.103222, 0.037176, 0.528493], [-0.221722, 0.681812, 0.494246, 0.013197, 0.499466, 0.181594]], "network.2.bias": [0.22697, -0.328776, 0.082677, 0.14532, 0.508587, -0.618401], "network.4.weight": [[0.196702, -0.522414, 0.272835, 0.528265, -0.019658, 0.062893], [-0.141661, 0.084428, 0.228898, 0.697276, 0.197753, 0.549488], [-0.162902, -0.250997, -0.085017, 0.334061, -0.287691, -0.406168], [0.547958, 0.022648, -0.121285, -0.833216, 0.41212, -0.538728], [-0.082884, -0.1649, -0.136395, -0.152911, -0.353831, -0.041323], [0.002201, -0.376424, 0.0433, -0.051324, -0.109374, 0.024309]], "network.4.bias": [0.02295, -0.096818, 0.436664, 0.624179, 0.031, -0.21049], "network.6.weight": [[-0.438315, -0.409995, -0.974395, 0.131403, -0.100318, -0.195511], [-0.257483, 0.416922, 0.784612, -0.45969, -0.087853, -0.019448], [0.09781, 0.385118, 0.28125, -0.237242, -0.177463, -0.305015], [-0.349474, -0.736858, 0.045831, -0.22934, 0.11385, 0.371826], [-0.012789, -0.278379, -0.251158, -0.043083, -0.213112, -0.385144], [-0.5884, -0.609087, -0.618999, 0.63745, -0.53163, -0.675732]], "network.6.bias": [0.456937, 0.537809, 0.031783, -0.31112, 0.280689, 0.558701], "network.8.weight": [[0.102704, -0.319659, 0.172126, 0.35548, 0.208297, 0.01599], [0.332276, -0.502512, -0.3883, -0.248015, -0.236059, 0.550343], [-0.777148, 0.554895, 0.418615, 0.063337, -0.118633, -0.454887], [0.231151, -0.538075, -0.53558, 0.036517, 0.476743, 0.646577], [0.329351, -0.457593, -0.552188, -0.469472, 0.300366, 0.383954], [-0.450037, 0.143678, 0.43924, -0.108485, 0.10916, -0.322434]], "network.8.bias": [-0.397842, 0.334039, 0.493179, 0.394925, 0.136149, -0.020871], "network.10.weight": [[0.239418, 0.318209, -0.461659, 0.195612, 0.336219, -0.788875], [-0.074757, 0.399697, -0.780463, 0.321514, 0.479568, -0.104556], [0.371013, -0.181148, 0.215579, -0.106627, 0.455871, -0.128114], [-0.693521, -0.247455, 0.397212, -0.407535, -0.786498, 0.253307], [0.298242, 0.669352, -0.548935, 0.490709, 0.115995, -0.686809], [-0.078505, -0.190074, -0.740459, 0.330859, 0.310472, -0.155589]], "network.10.bias": [-0.05555, 0.044274, 0.573977, 0.461287, -0.03614, -0.118679], "network.12.weight": [[0.560965, 0.458006, -0.216286, -0.861113, 0.416997, 0.294029]], "network.12.bias": [-0.56264]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6972120106220245, "train_acc": 0.575, "val_loss": 0.738274335861206, "val_acc": 0.46}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6829558312892914, "train_acc": 0.575, "val_loss": 0.7246352434158325, "val_acc": 0.46}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6798249781131744, "train_acc": 0.575, "val_loss": 0.7094569206237793, "val_acc": 0.46}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6685190200805664, "train_acc": 0.575, "val_loss": 0.6880655884742737, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6581806838512421, "train_acc": 0.585, "val_loss": 0.6383102536201477, "val_acc": 0.66}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.6093356907367706, "train_acc": 0.725, "val_loss": 0.6056345105171204, "val_acc": 0.7}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.573432207107544, "train_acc": 0.735, "val_loss": 0.5864701867103577, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.5598958730697632, "train_acc": 0.775, "val_loss": 0.5637385249137878, "val_acc": 0.76}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.5203123688697815, "train_acc": 0.795, "val_loss": 0.5128334164619446, "val_acc": 0.74}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.4771845042705536, "train_acc": 0.79, "val_loss": 0.4663623869419098, "val_acc": 0.82}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.47244992852211, "train_acc": 0.835, "val_loss": 0.427331805229187, "val_acc": 0.86}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.39803552627563477, "train_acc": 0.88, "val_loss": 0.3925051987171173, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.3686729967594147, "train_acc": 0.875, "val_loss": 0.32635948061943054, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.2913018763065338, "train_acc": 0.89, "val_loss": 0.25841817259788513, "val_acc": 0.9}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["contains_abc"], "degraded_stage": {"initial_val_loss": 0.738274335861206, "final_val_loss": 0.6880655884742737, "initial_val_acc": 0.46, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.6383102536201477, "final_val_loss": 0.25841817259788513, "initial_val_acc": 0.66, "final_val_acc": 0.9, "best_val_acc": 0.9, "best_epoch": 13}, "improvement": 0.4, "first_improvement_epoch": 3}} |
82 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.48, "improved_accuracy": 0.96, "improvement": 0.48, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4211, "learning_rate": 0.038871271727713465, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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],
"network.0.bias": [
0.389293,
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"network.2.weight": [
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[
0.506081,
0.110709,
0.416702,
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0.000712,
-0.283366
],
[
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0.255696,
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0.172448,
0.101883,
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],
[
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0.116274,
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[
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]
],
"network.2.bias": [
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[
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[
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0.004799,
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[
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[
0.059463,
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[
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0.085704,
0.300893
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[
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],
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[
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"network.8.weight": [
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[
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[
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"network.10.weight": [
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[
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[
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[
0.54976,
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],
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]
}
## Activation Signature
### 0
mean: [0.000000, 0.242480, 1.258482, 2.007649, 1.054059, 0.254935]
std: [0.000000, 0.347657, 0.764971, 1.238542, 0.709594, 0.454998]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.265351, 6.801998, 7.656820, 7.709869, 21.823232], [12.233590, 13.604367, 14.264294, 15.631156, 113.263332], [20.580896, 21.312440, 22.265515, 24.416478, 180.688391], [11.811890, 12.306045, 12.743840, 14.069965, 94.865263], [7.210258, 8.901414, 9.685665, 10.103355, 22.944150]]
input_correlations: [[-0.450518, 0.094984, 0.161732, 0.515185, 0.677900, 0.000000, 0.000000, 0.000000], [-0.543309, -0.773126, -0.418482, -0.687013, -0.142839, 0.000000, 0.000000, 0.000000], [-0.066693, 0.751016, 0.193112, 0.790298, -0.105742, 0.000000, 0.000000, 0.000000], [-0.371034, -0.577617, -0.702132, -0.494182, -0.607957, 0.000000, 0.000000, 0.000000], [0.960335, 0.484040, 0.270205, -0.156440, 0.031264, 0.000000, 0.000000, 0.000000], [0.895258, 0.636980, 0.081501, 0.108958, 0.089129, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.349432, -3.126886, 2.327312, -2.028186, 0.799151, 0.844451]
pre_activation_std: [1.273367, 2.211333, 1.753982, 1.371820, 1.392939, 1.349914]
### 2
mean: [0.678131, -1.838172, 1.466880, -1.023502, 0.355723, -2.220084]
std: [1.572749, 1.125592, 1.141586, 0.301714, 1.518230, 1.219217]
fourier: [[27.138979, 27.878419, 28.053862, 28.977113, 61.031810], [17.088564, 18.132805, 21.389765, 22.922206, 165.435508], [16.749071, 17.058561, 18.482455, 22.428480, 132.019219], [4.359537, 4.714557, 5.716606, 6.445576, 92.115179], [24.388645, 25.825453, 25.984248, 29.027733, 32.015066], [19.173440, 19.583478, 21.721481, 24.043116, 199.807547]]
input_correlations: [[-0.512051, -0.112890, -0.009812, -0.139931, 0.990377, 0.954273, 0.000000, 0.000000], [0.045556, 0.283471, -0.583194, 0.381035, -0.818269, -0.916885, 0.000000, 0.000000], [0.847502, -0.217980, 0.750420, -0.319645, -0.492811, -0.326378, 0.000000, 0.000000], [-0.531956, 0.335857, -0.826886, 0.482793, -0.335742, -0.536039, 0.000000, 0.000000], [-0.633800, -0.094438, 0.086128, -0.104854, 0.934411, 0.923788, 0.000000, 0.000000], [-0.581985, 0.333644, -0.944487, 0.467600, -0.127827, -0.322095, 0.000000, 0.000000]]
pre_activation_mean: [0.678131, -1.838172, 1.466880, -1.023502, 0.355723, -2.220084]
pre_activation_std: [1.572749, 1.125592, 1.141586, 0.301714, 1.518230, 1.219217]
### 4
mean: [0.682374, 0.911774, -0.795294, 0.578305, -1.287348, 0.642852]
std: [1.153781, 1.458598, 0.256451, 0.511315, 0.520613, 0.800313]
fourier: [[18.429203, 19.514584, 22.078012, 23.076160, 61.413633], [22.481644, 25.819048, 28.283754, 29.136501, 82.059642], [4.272676, 4.424555, 4.686582, 5.804225, 71.576420], [8.235849, 8.247950, 9.496511, 10.324159, 52.047460], [7.717214, 8.331055, 8.743991, 9.167033, 115.861357], [12.029731, 13.711183, 15.688076, 15.795254, 57.856683]]
input_correlations: [[-0.920495, 0.000000, 0.766950, 0.000000, -0.909506, 0.000000, 0.000000, 0.000000], [-0.863010, 0.000000, 0.850696, 0.000000, -0.832683, 0.000000, 0.000000, 0.000000], [-0.700852, 0.000000, -0.240924, 0.000000, -0.764251, 0.000000, 0.000000, 0.000000], [-0.919125, 0.000000, 0.748807, 0.000000, -0.920975, 0.000000, 0.000000, 0.000000], [0.169971, 0.000000, -0.949612, 0.000000, 0.142322, 0.000000, 0.000000, 0.000000], [-0.854064, 0.000000, 0.857228, 0.000000, -0.833176, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.682374, 0.911774, -0.795294, 0.578305, -1.287348, 0.642852]
pre_activation_std: [1.153781, 1.458598, 0.256451, 0.511315, 0.520613, 0.800313]
### 6
mean: [-0.339606, -0.405536, -0.592939, 2.085992, -0.479806, -0.231858]
std: [0.585731, 0.085557, 0.406477, 1.342970, 0.591669, 0.033391]
fourier: [[9.751809, 10.120304, 10.572306, 11.526972, 30.564551], [1.403434, 1.478143, 1.493105, 1.608009, 36.498258], [6.560865, 7.041888, 7.162146, 7.784072, 53.364519], [22.438765, 22.823453, 24.138630, 26.305575, 187.739260], [9.641493, 10.495170, 10.697689, 11.783141, 43.182553], [0.442025, 0.518254, 0.522336, 0.582796, 20.867262]]
input_correlations: [[-0.997879, -0.990194, 0.000000, -0.976665, 0.000000, -0.993159, 0.000000, 0.000000], [-0.981210, -0.952162, 0.000000, -0.929991, 0.000000, -0.940670, 0.000000, 0.000000], [-0.990146, -0.999448, 0.000000, -0.944997, 0.000000, -0.994576, 0.000000, 0.000000], [0.996655, 0.994294, 0.000000, 0.969921, 0.000000, 0.996240, 0.000000, 0.000000], [-0.996011, -0.982722, 0.000000, -0.986041, 0.000000, -0.989590, 0.000000, 0.000000], [-0.693186, -0.794466, 0.000000, -0.596661, 0.000000, -0.787814, 0.000000, 0.000000]]
pre_activation_mean: [-0.339606, -0.405536, -0.592939, 2.085992, -0.479806, -0.231858]
pre_activation_std: [0.585731, 0.085557, 0.406477, 1.342970, 0.591669, 0.033391]
### 8
mean: [1.301792, 1.809404, -0.896192, 1.114862, 0.029210, -0.352593]
std: [0.852469, 1.215572, 0.492239, 0.335232, 0.154446, 0.183376]
fourier: [[13.987038, 15.236566, 15.331730, 17.150223, 117.161271], [19.834121, 21.672195, 22.139339, 24.594323, 162.846358], [8.217674, 8.408940, 8.850304, 9.666526, 80.657268], [4.876512, 4.883143, 5.427654, 5.558507, 100.337553], [2.545086, 2.628859, 2.706594, 2.755681, 3.062529], [3.032792, 3.237072, 3.289627, 3.658633, 31.733354]]
input_correlations: [[-0.810976, 0.000000, 0.000000, 0.997339, -0.757675, 0.000000, 0.000000, 0.000000], [-0.820614, 0.000000, 0.000000, 0.995904, -0.769538, 0.000000, 0.000000, 0.000000], [0.771429, 0.000000, 0.000000, -0.999896, 0.712302, 0.000000, 0.000000, 0.000000], [-0.370784, 0.000000, 0.000000, 0.879357, -0.293010, 0.000000, 0.000000, 0.000000], [0.783875, 0.000000, 0.000000, -0.997510, 0.741492, 0.000000, 0.000000, 0.000000], [-0.800515, 0.000000, 0.000000, 0.997232, -0.735331, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.301792, 1.809404, -0.896192, 1.114862, 0.029210, -0.352593]
pre_activation_std: [0.852469, 1.215572, 0.492239, 0.335232, 0.154446, 0.183376]
### 10
mean: [-0.277235, 0.128087, 1.258482, 2.007649, 1.054059, -0.290206]
std: [0.060457, 0.447715, 0.764971, 1.238542, 0.709594, 0.873843]
fourier: [[0.966486, 1.009753, 1.250909, 1.291293, 24.951164], [6.852596, 7.689406, 9.032633, 9.530395, 11.527871], [12.233590, 13.604367, 14.264294, 15.631156, 113.263332], [20.580896, 21.312440, 22.265515, 24.416478, 180.688391], [11.811890, 12.306045, 12.743840, 14.069965, 94.865263], [13.720391, 15.274084, 17.054825, 18.289543, 26.118560]]
input_correlations: [[-0.965303, -0.965788, 0.000000, -0.674858, 0.969939, -0.237299, 0.000000, 0.000000], [-0.980546, -0.981060, 0.000000, -0.723049, 0.968914, -0.253796, 0.000000, 0.000000], [0.998513, 0.998682, 0.000000, 0.813982, -0.935920, 0.308726, 0.000000, 0.000000], [0.998422, 0.998277, 0.000000, 0.872676, -0.903804, 0.335999, 0.000000, 0.000000], [0.998921, 0.998783, 0.000000, 0.867572, -0.908822, 0.331271, 0.000000, 0.000000], [-0.991525, -0.991863, 0.000000, -0.767535, 0.956444, -0.277539, 0.000000, 0.000000]]
pre_activation_mean: [-0.277235, 0.128087, 1.258482, 2.007649, 1.054059, -0.290206]
pre_activation_std: [0.060457, 0.447715, 0.764971, 1.238542, 0.709594, 0.873843]
### 12
mean: [-1.897705]
std: [1.646263]
fourier: [[25.993341, 28.982187, 31.757376, 34.281263, 170.793464]]
input_correlations: [[0.000000, 0.926630, -0.998322, -0.986277, -0.987924, 0.860574, 0.000000, 0.000000]]
pre_activation_mean: [-1.897705]
pre_activation_std: [1.646263]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.427192,
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0.11858,
0.192095,
0.493726
],
[
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0.068663
],
[
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0.159155,
0.510024,
-0.178317
],
[
-0.016002,
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-0.365222,
-0.200884,
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],
[
0.616707,
0.19394,
-0.034952,
-0.122527,
-0.070152
],
[
0.564432,
0.300024,
-0.191922,
0.011824,
-0.005395
]
],
"network.0.bias": [
0.389293,
0.013928,
0.364635,
0.076249,
0.100574,
-0.022464
],
"network.2.weight": [
[
-0.191625,
-0.406491,
-0.048052,
0.108719,
0.70457,
0.440298
],
[
-0.09128,
-0.06912,
-0.288579,
-0.38791,
-0.358062,
-0.393114
],
[
0.506081,
0.110709,
0.416702,
-0.035012,
0.000712,
-0.283366
],
[
-0.128927,
0.255696,
-0.072128,
0.172448,
0.101883,
-0.240824
],
[
-0.555634,
0.176713,
0.116274,
-0.366835,
0.337086,
0.578724
],
[
-0.404865,
-0.313417,
-0.545091,
-0.145203,
-0.126309,
-0.127586
]
],
"network.2.bias": [
0.036531,
-0.344191,
0.024273,
-0.536973,
0.043661,
-0.125254
],
"network.4.weight": [
[
-0.163453,
-0.386165,
0.473358,
0.01073,
-0.478444,
-0.030556
],
[
-0.597744,
0.032901,
0.763009,
0.004799,
-0.000134,
0.49891
],
[
0.118822,
0.205544,
-0.156664,
-0.083753,
-0.355364,
-0.044663
],
[
0.059463,
0.266603,
0.205743,
0.067679,
-0.370486,
-0.124814
],
[
-0.199461,
0.094723,
-0.534368,
-0.282059,
0.085704,
0.300893
],
[
-0.151563,
-0.169342,
0.436736,
-0.355588,
-0.197009,
-0.011465
]
],
"network.4.bias": [
0.453704,
0.282348,
-0.410409,
0.482418,
-0.377439,
0.259005
],
"network.6.weight": [
[
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],
[
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0.057451,
-0.260452,
0.219406
],
[
-0.071466,
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-0.320686,
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0.108282,
0.235793
],
[
0.640502,
0.545172,
-0.191164,
0.568283,
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0.361331
],
[
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0.017893,
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0.064477,
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],
[
0.054272,
0.058837,
0.0093,
0.178585,
0.380603,
-0.321056
]
],
"network.6.bias": [
0.524407,
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0.167018,
0.439621,
-0.219803
],
"network.8.weight": [
[
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],
[
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0.111344,
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],
[
0.178557,
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],
[
0.699554,
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0.076127
],
[
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0.291281,
0.050083
],
[
-0.303329,
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0.262305,
0.031419
]
],
"network.8.bias": [
0.145894,
0.209196,
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0.266535,
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],
"network.10.weight": [
[
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0.005846
],
[
-0.138874,
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0.037355,
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0.431285,
-0.148522
],
[
0.087439,
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0.124174,
0.212386
],
[
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],
[
0.54976,
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],
[
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]
],
"network.10.bias": [
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],
"network.12.weight": [
[
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-0.63874,
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0.657648
]
],
"network.12.bias": [
0.003489
]
}
## Activation Signature
### 0
mean: [0.000000, 0.242480, 1.258482, 2.007649, 1.054059, 0.254935]
std: [0.000000, 0.347657, 0.764971, 1.238542, 0.709594, 0.454998]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.265351, 6.801998, 7.656820, 7.709869, 21.823232], [12.233590, 13.604367, 14.264294, 15.631156, 113.263332], [20.580896, 21.312440, 22.265515, 24.416478, 180.688391], [11.811890, 12.306045, 12.743840, 14.069965, 94.865263], [7.210258, 8.901414, 9.685665, 10.103355, 22.944150]]
input_correlations: [[-0.450518, 0.094984, 0.161732, 0.515185, 0.677900, 0.000000, 0.000000, 0.000000], [-0.543309, -0.773126, -0.418482, -0.687013, -0.142839, 0.000000, 0.000000, 0.000000], [-0.066693, 0.751016, 0.193112, 0.790298, -0.105742, 0.000000, 0.000000, 0.000000], [-0.371034, -0.577617, -0.702132, -0.494182, -0.607957, 0.000000, 0.000000, 0.000000], [0.960335, 0.484040, 0.270205, -0.156440, 0.031264, 0.000000, 0.000000, 0.000000], [0.895258, 0.636980, 0.081501, 0.108958, 0.089129, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.349432, -3.126886, 2.327312, -2.028186, 0.799151, 0.844451]
pre_activation_std: [1.273367, 2.211333, 1.753982, 1.371820, 1.392939, 1.349914]
### 2
mean: [0.678131, -1.838172, 1.466880, -1.023502, 0.355723, -2.220084]
std: [1.572749, 1.125592, 1.141586, 0.301714, 1.518230, 1.219217]
fourier: [[27.138979, 27.878419, 28.053862, 28.977113, 61.031810], [17.088564, 18.132805, 21.389765, 22.922206, 165.435508], [16.749071, 17.058561, 18.482455, 22.428480, 132.019219], [4.359537, 4.714557, 5.716606, 6.445576, 92.115179], [24.388645, 25.825453, 25.984248, 29.027733, 32.015066], [19.173440, 19.583478, 21.721481, 24.043116, 199.807547]]
input_correlations: [[-0.512051, -0.112890, -0.009812, -0.139931, 0.990377, 0.954273, 0.000000, 0.000000], [0.045556, 0.283471, -0.583194, 0.381035, -0.818269, -0.916885, 0.000000, 0.000000], [0.847502, -0.217980, 0.750420, -0.319645, -0.492811, -0.326378, 0.000000, 0.000000], [-0.531956, 0.335857, -0.826886, 0.482793, -0.335742, -0.536039, 0.000000, 0.000000], [-0.633800, -0.094438, 0.086128, -0.104854, 0.934411, 0.923788, 0.000000, 0.000000], [-0.581985, 0.333644, -0.944487, 0.467600, -0.127827, -0.322095, 0.000000, 0.000000]]
pre_activation_mean: [0.678131, -1.838172, 1.466880, -1.023502, 0.355723, -2.220084]
pre_activation_std: [1.572749, 1.125592, 1.141586, 0.301714, 1.518230, 1.219217]
### 4
mean: [0.682374, 0.911774, -0.795294, 0.578305, -1.287348, 0.642852]
std: [1.153781, 1.458598, 0.256451, 0.511315, 0.520613, 0.800313]
fourier: [[18.429203, 19.514584, 22.078012, 23.076160, 61.413633], [22.481644, 25.819048, 28.283754, 29.136501, 82.059642], [4.272676, 4.424555, 4.686582, 5.804225, 71.576420], [8.235849, 8.247950, 9.496511, 10.324159, 52.047460], [7.717214, 8.331055, 8.743991, 9.167033, 115.861357], [12.029731, 13.711183, 15.688076, 15.795254, 57.856683]]
input_correlations: [[-0.920495, 0.000000, 0.766950, 0.000000, -0.909506, 0.000000, 0.000000, 0.000000], [-0.863010, 0.000000, 0.850696, 0.000000, -0.832683, 0.000000, 0.000000, 0.000000], [-0.700852, 0.000000, -0.240924, 0.000000, -0.764251, 0.000000, 0.000000, 0.000000], [-0.919125, 0.000000, 0.748807, 0.000000, -0.920975, 0.000000, 0.000000, 0.000000], [0.169971, 0.000000, -0.949612, 0.000000, 0.142322, 0.000000, 0.000000, 0.000000], [-0.854064, 0.000000, 0.857228, 0.000000, -0.833176, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.682374, 0.911774, -0.795294, 0.578305, -1.287348, 0.642852]
pre_activation_std: [1.153781, 1.458598, 0.256451, 0.511315, 0.520613, 0.800313]
### 6
mean: [-0.339606, -0.405536, -0.592939, 2.085992, -0.479806, -0.231858]
std: [0.585731, 0.085557, 0.406477, 1.342970, 0.591669, 0.033391]
fourier: [[9.751809, 10.120304, 10.572306, 11.526972, 30.564551], [1.403434, 1.478143, 1.493105, 1.608009, 36.498258], [6.560865, 7.041888, 7.162146, 7.784072, 53.364519], [22.438765, 22.823453, 24.138630, 26.305575, 187.739260], [9.641493, 10.495170, 10.697689, 11.783141, 43.182553], [0.442025, 0.518254, 0.522336, 0.582796, 20.867262]]
input_correlations: [[-0.997879, -0.990194, 0.000000, -0.976665, 0.000000, -0.993159, 0.000000, 0.000000], [-0.981210, -0.952162, 0.000000, -0.929991, 0.000000, -0.940670, 0.000000, 0.000000], [-0.990146, -0.999448, 0.000000, -0.944997, 0.000000, -0.994576, 0.000000, 0.000000], [0.996655, 0.994294, 0.000000, 0.969921, 0.000000, 0.996240, 0.000000, 0.000000], [-0.996011, -0.982722, 0.000000, -0.986041, 0.000000, -0.989590, 0.000000, 0.000000], [-0.693186, -0.794466, 0.000000, -0.596661, 0.000000, -0.787814, 0.000000, 0.000000]]
pre_activation_mean: [-0.339606, -0.405536, -0.592939, 2.085992, -0.479806, -0.231858]
pre_activation_std: [0.585731, 0.085557, 0.406477, 1.342970, 0.591669, 0.033391]
### 8
mean: [1.301792, 1.809404, -0.896192, 1.114862, 0.029210, -0.352593]
std: [0.852469, 1.215572, 0.492239, 0.335232, 0.154446, 0.183376]
fourier: [[13.987038, 15.236566, 15.331730, 17.150223, 117.161271], [19.834121, 21.672195, 22.139339, 24.594323, 162.846358], [8.217674, 8.408940, 8.850304, 9.666526, 80.657268], [4.876512, 4.883143, 5.427654, 5.558507, 100.337553], [2.545086, 2.628859, 2.706594, 2.755681, 3.062529], [3.032792, 3.237072, 3.289627, 3.658633, 31.733354]]
input_correlations: [[-0.810976, 0.000000, 0.000000, 0.997339, -0.757675, 0.000000, 0.000000, 0.000000], [-0.820614, 0.000000, 0.000000, 0.995904, -0.769538, 0.000000, 0.000000, 0.000000], [0.771429, 0.000000, 0.000000, -0.999896, 0.712302, 0.000000, 0.000000, 0.000000], [-0.370784, 0.000000, 0.000000, 0.879357, -0.293010, 0.000000, 0.000000, 0.000000], [0.783875, 0.000000, 0.000000, -0.997510, 0.741492, 0.000000, 0.000000, 0.000000], [-0.800515, 0.000000, 0.000000, 0.997232, -0.735331, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.301792, 1.809404, -0.896192, 1.114862, 0.029210, -0.352593]
pre_activation_std: [0.852469, 1.215572, 0.492239, 0.335232, 0.154446, 0.183376]
### 10
mean: [-0.277235, 0.128087, 1.258482, 2.007649, 1.054059, -0.290206]
std: [0.060457, 0.447715, 0.764971, 1.238542, 0.709594, 0.873843]
fourier: [[0.966486, 1.009753, 1.250909, 1.291293, 24.951164], [6.852596, 7.689406, 9.032633, 9.530395, 11.527871], [12.233590, 13.604367, 14.264294, 15.631156, 113.263332], [20.580896, 21.312440, 22.265515, 24.416478, 180.688391], [11.811890, 12.306045, 12.743840, 14.069965, 94.865263], [13.720391, 15.274084, 17.054825, 18.289543, 26.118560]]
input_correlations: [[-0.965303, -0.965788, 0.000000, -0.674858, 0.969939, -0.237299, 0.000000, 0.000000], [-0.980546, -0.981060, 0.000000, -0.723049, 0.968914, -0.253796, 0.000000, 0.000000], [0.998513, 0.998682, 0.000000, 0.813982, -0.935920, 0.308726, 0.000000, 0.000000], [0.998422, 0.998277, 0.000000, 0.872676, -0.903804, 0.335999, 0.000000, 0.000000], [0.998921, 0.998783, 0.000000, 0.867572, -0.908822, 0.331271, 0.000000, 0.000000], [-0.991525, -0.991863, 0.000000, -0.767535, 0.956444, -0.277539, 0.000000, 0.000000]]
pre_activation_mean: [-0.277235, 0.128087, 1.258482, 2.007649, 1.054059, -0.290206]
pre_activation_std: [0.060457, 0.447715, 0.764971, 1.238542, 0.709594, 0.873843]
### 12
mean: [-1.897705]
std: [1.646263]
fourier: [[25.993341, 28.982187, 31.757376, 34.281263, 170.793464]]
input_correlations: [[0.000000, 0.926630, -0.998322, -0.986277, -0.987924, 0.860574, 0.000000, 0.000000]]
pre_activation_mean: [-1.897705]
pre_activation_std: [1.646263]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[-0.427192, 0.122482, 0.11858, 0.192095, 0.493726], [-0.410732, -0.492045, -0.244484, -0.609505, 0.068663], [-0.222736, 0.567224, 0.159155, 0.510024, -0.178317], [-0.016002, -0.263696, -0.365222, -0.200884, -0.332687], [0.616707, 0.19394, -0.034952, -0.122527, -0.070152], [0.564432, 0.300024, -0.191922, 0.011824, -0.005395]], "network.0.bias": [0.389293, 0.013928, 0.364635, 0.076249, 0.100574, -0.022464], "network.2.weight": [[-0.191625, -0.406491, -0.048052, 0.108719, 0.70457, 0.440298], [-0.09128, -0.06912, -0.288579, -0.38791, -0.358062, -0.393114], [0.506081, 0.110709, 0.416702, -0.035012, 0.000712, -0.283366], [-0.128927, 0.255696, -0.072128, 0.172448, 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[0.54976, 0.130317, -0.232433, 0.224399, -0.248156, -0.01153], [-0.402096, -0.538088, 0.14967, 0.546951, 0.415302, 0.253636]], "network.10.bias": [-0.24797, 0.426454, 0.227045, -0.142311, -0.130519, 0.572129], "network.12.weight": [[0.278675, 0.240046, -0.417606, -0.63874, -0.302776, 0.657648]], "network.12.bias": [0.003489]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6924565136432648, "train_acc": 0.575, "val_loss": 0.7096797227859497, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6747271716594696, "train_acc": 0.575, "val_loss": 0.7012467980384827, "val_acc": 0.48}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6703597009181976, "train_acc": 0.575, "val_loss": 0.6903939843177795, "val_acc": 0.48}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.648225724697113, "train_acc": 0.575, "val_loss": 0.6630707383155823, "val_acc": 0.48}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6282698214054108, "train_acc": 0.505, "val_loss": 0.5669792890548706, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.49753254652023315, "train_acc": 0.93, "val_loss": 0.4151003956794739, "val_acc": 0.94}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.3719441592693329, "train_acc": 0.875, "val_loss": 0.2727406322956085, "val_acc": 0.96}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.2611521929502487, "train_acc": 0.925, "val_loss": 0.22067950665950775, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.20821189880371094, "train_acc": 0.925, "val_loss": 0.2066507786512375, "val_acc": 0.92}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.24227889627218246, "train_acc": 0.93, "val_loss": 0.22677189111709595, "val_acc": 0.92}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.22868163138628006, "train_acc": 0.93, "val_loss": 0.2032511830329895, "val_acc": 0.94}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.21373466402292252, "train_acc": 0.925, "val_loss": 0.19925881922245026, "val_acc": 0.94}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.20706042647361755, "train_acc": 0.93, "val_loss": 0.2101639211177826, "val_acc": 0.94}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.21214725077152252, "train_acc": 0.935, "val_loss": 0.19921910762786865, "val_acc": 0.94}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.7096797227859497, "final_val_loss": 0.6630707383155823, "initial_val_acc": 0.48, "final_val_acc": 0.48, "best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.5669792890548706, "final_val_loss": 0.19921910762786865, "initial_val_acc": 0.94, "final_val_acc": 0.94, "best_val_acc": 0.96, "best_epoch": 6}, "improvement": 0.48, "first_improvement_epoch": 3}} |
83 | {"target_pattern": "decreasing_pairs", "degraded_accuracy": 0.52, "improved_accuracy": 1.0, "improvement": 0.48, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4634, "learning_rate": 0.06763343703882889, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "decreasing_pairs", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["decreasing_pairs"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.315030, 0.915512, 0.821411, 0.000000, 1.029647, 0.000000, 0.000000]
std: [0.758247, 2.140420, 0.036292, 0.000000, 0.125307, 0.000000, 0.000000]
fourier: [[12.644156, 12.764160, 13.121601, 13.543934, 28.352692], [36.170514, 36.236817, 37.077460, 38.732014, 82.396072], [0.541265, 0.583825, 0.593242, 0.650012, 73.926985], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.963386, 2.020788, 2.207101, 2.266311, 92.668279], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.770341, -0.758549, -0.557224, -0.195155, -0.372925, 0.000000, 0.000000, 0.000000], [-0.652945, 0.247324, 0.167244, -0.093920, 0.170067, 0.000000, 0.000000, 0.000000], [-0.464545, -0.356191, 0.018517, 0.154056, 0.769583, 0.000000, 0.000000, 0.000000], [-0.642435, 0.242774, 0.096009, 0.662785, -0.199628, 0.000000, 0.000000, 0.000000], [-0.709317, -0.459614, -0.600794, -0.504524, -0.507840, 0.000000, 0.000000, 0.000000], [0.769983, 0.571468, 0.444289, 0.123110, -0.329341, 0.000000, 0.000000, 0.000000], [0.694327, 0.841557, 0.075448, 0.396966, 0.063887, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.508844, 0.436040, 0.508646, 1.343133, -2.095328, 1.135988, 1.358352]
pre_activation_std: [1.731429, 1.117096, 1.285440, 1.802585, 1.280426, 2.045538, 1.598807]
### 2
mean: [-0.676872, -0.149915, -0.198808, -0.665682, 0.063591, -0.566724, -1.322553]
std: [1.636173, 1.754611, 1.002924, 0.374083, 1.030459, 1.518317, 0.550198]
fourier: [[26.503015, 28.531559, 32.637837, 32.646101, 60.918441], [27.309359, 28.235180, 28.832236, 29.520215, 34.551458], [16.285677, 16.563635, 17.892740, 20.236277, 20.704917], [5.506223, 5.776535, 5.806215, 6.698995, 59.911366], [14.824357, 14.998575, 15.085597, 17.805352, 19.890956], [23.680318, 24.754729, 26.322155, 29.073768, 51.005150], [7.919780, 8.070903, 8.842887, 9.044082, 119.029729]]
input_correlations: [[0.000000, -0.634438, -0.348800, -0.624532, 0.000000, 0.781959, 0.652798, 0.000000], [0.000000, -0.515096, -0.657327, -0.453520, 0.000000, 0.852633, 0.682219, 0.000000], [0.000000, -0.635430, -0.263910, -0.737990, 0.000000, 0.666527, 0.578836, 0.000000], [0.000000, -0.406720, 0.015890, -0.948655, 0.000000, -0.157396, -0.223022, 0.000000], [0.000000, 0.428516, 0.727027, 0.274144, 0.000000, -0.896036, -0.726847, 0.000000], [0.000000, -0.471103, -0.633454, -0.367594, 0.000000, 0.903271, 0.758530, 0.000000], [0.000000, -0.306044, 0.143398, -0.652799, 0.000000, -0.607613, -0.506801, 0.000000]]
pre_activation_mean: [-0.676872, -0.149915, -0.198808, -0.665682, 0.063591, -0.566724, -1.322553]
pre_activation_std: [1.636173, 1.754611, 1.002924, 0.374083, 1.030459, 1.518317, 0.550198]
### 4
mean: [-0.227744, -0.872622, -0.495918, 0.887538, -0.555788, 0.303349, 0.538804]
std: [0.106890, 0.851060, 0.405501, 1.965821, 0.487744, 1.858847, 0.116237]
fourier: [[1.638017, 1.654135, 1.992891, 1.999711, 20.496956], [13.620927, 14.740273, 15.350654, 16.079223, 78.535959], [6.475640, 6.713360, 7.315461, 8.008486, 44.632595], [30.563269, 31.198750, 35.003672, 35.320789, 79.878450], [8.187228, 8.467551, 9.300526, 9.610569, 50.020914], [28.317494, 28.322330, 30.212451, 32.921516, 33.342004], [1.805722, 2.100610, 2.358268, 2.383670, 48.492357]]
input_correlations: [[-0.950294, -0.979366, -0.926463, 0.000000, 0.507481, -0.967021, 0.000000, 0.000000], [-0.990421, -0.996118, -0.979370, 0.000000, 0.404815, -0.988349, 0.000000, 0.000000], [-0.942421, -0.939450, -0.951355, 0.000000, 0.619885, -0.925200, 0.000000, 0.000000], [0.984945, 0.985646, 0.974156, 0.000000, -0.475593, 0.981473, 0.000000, 0.000000], [-0.987147, -0.981253, -0.967263, 0.000000, 0.194254, -0.986229, 0.000000, 0.000000], [0.976829, 0.978486, 0.968362, 0.000000, -0.515442, 0.972219, 0.000000, 0.000000], [0.926574, 0.970797, 0.905014, 0.000000, -0.194288, 0.952612, 0.000000, 0.000000]]
pre_activation_mean: [-0.227744, -0.872622, -0.495918, 0.887538, -0.555788, 0.303349, 0.538804]
pre_activation_std: [0.106890, 0.851060, 0.405501, 1.965821, 0.487744, 1.858847, 0.116237]
### 6
mean: [-0.766603, -0.147424, 0.031109, 0.353826, -0.333755, 0.811890, 0.056697]
std: [1.178754, 0.155530, 0.631510, 1.577938, 0.066822, 1.360080, 1.175560]
fourier: [[19.401526, 20.575735, 20.842759, 21.657432, 68.994285], [2.543120, 2.544130, 2.641256, 2.801353, 13.268201], [10.169670, 10.678485, 10.786605, 11.040090, 11.728122], [26.055757, 27.410443, 27.589310, 28.769261, 31.844295], [1.106344, 1.170272, 1.245468, 1.290786, 30.037962], [22.157258, 23.897994, 24.108816, 24.819269, 73.070096], [18.834623, 19.473869, 20.410043, 20.686765, 21.558479]]
input_correlations: [[0.000000, 0.000000, 0.082673, -0.999246, 0.000000, -0.999454, -0.950107, 0.000000], [0.000000, 0.000000, 0.131246, -0.985121, 0.000000, -0.971127, -0.901500, 0.000000], [0.000000, 0.000000, -0.074789, 0.995783, 0.000000, 0.999782, 0.948570, 0.000000], [0.000000, 0.000000, -0.087991, 0.999181, 0.000000, 0.999384, 0.944629, 0.000000], [0.000000, 0.000000, 0.042230, 0.965560, 0.000000, 0.978336, 0.973515, 0.000000], [0.000000, 0.000000, -0.084902, 0.999825, 0.000000, 0.998552, 0.949250, 0.000000], [0.000000, 0.000000, -0.081153, 0.998890, 0.000000, 0.999698, 0.948314, 0.000000]]
pre_activation_mean: [-0.766603, -0.147424, 0.031109, 0.353826, -0.333755, 0.811890, 0.056697]
pre_activation_std: [1.178754, 0.155530, 0.631510, 1.577938, 0.066822, 1.360080, 1.175560]
### 8
mean: [-0.354436, 0.546436, 0.936903, 0.825156, -0.489861, -0.653495, 0.794371]
std: [0.487254, 0.188936, 1.941254, 1.744254, 0.317524, 1.326224, 0.197715]
fourier: [[8.077206, 8.416032, 8.558814, 8.854407, 31.899205], [3.378062, 3.385529, 3.415838, 3.453717, 49.179213], [32.571490, 33.179003, 33.863491, 35.264501, 84.321282], [29.061068, 30.031499, 30.566562, 31.737102, 74.264025], [5.279021, 5.437315, 5.481133, 5.816520, 44.087499], [22.380185, 22.481208, 23.016624, 24.004854, 58.814517], [3.155012, 3.555169, 3.586023, 3.611355, 71.493409]]
input_correlations: [[0.000000, 0.000000, -0.996939, -0.999402, 0.000000, -0.998312, -0.997972, 0.000000], [0.000000, 0.000000, 0.943897, 0.958726, 0.000000, 0.979721, 0.948317, 0.000000], [0.000000, 0.000000, 0.998193, 0.999887, 0.000000, 0.996837, 0.999025, 0.000000], [0.000000, 0.000000, 0.996991, 0.999558, 0.000000, 0.998183, 0.998057, 0.000000], [0.000000, 0.000000, -0.997927, -0.999632, 0.000000, -0.993821, -0.998732, 0.000000], [0.000000, 0.000000, -0.999284, -0.999716, 0.000000, -0.994573, -0.999774, 0.000000], [0.000000, 0.000000, 0.978019, 0.985180, 0.000000, 0.996189, 0.980361, 0.000000]]
pre_activation_mean: [-0.354436, 0.546436, 0.936903, 0.825156, -0.489861, -0.653495, 0.794371]
pre_activation_std: [0.487254, 0.188936, 1.941254, 1.744254, 0.317524, 1.326224, 0.197715]
### 10
mean: [0.144037, 0.745557, 0.821411, -0.275135, 1.029647, -0.589783, -0.629432]
std: [0.830495, 2.213851, 0.036292, 0.072824, 0.125307, 0.140798, 0.103632]
fourier: [[13.353968, 14.050123, 14.064378, 14.392554, 15.085801], [37.167452, 37.813496, 38.603223, 40.232877, 67.100103], [0.541265, 0.583825, 0.593242, 0.650012, 73.926985], [1.245395, 1.270438, 1.277117, 1.350467, 24.762153], [1.963386, 2.020788, 2.207101, 2.266311, 92.668279], [2.323581, 2.443565, 2.480286, 2.551729, 53.080469], [1.674209, 1.826978, 1.844473, 1.860774, 56.648893]]
input_correlations: [[0.000000, 0.955214, 0.999801, 0.999242, 0.000000, 0.000000, 0.983562, 0.000000], [0.000000, 0.960648, 0.999999, 0.999808, 0.000000, 0.000000, 0.986882, 0.000000], [0.000000, 0.658188, 0.425397, 0.442722, 0.000000, 0.000000, 0.563090, 0.000000], [0.000000, -0.990324, -0.987443, -0.990101, 0.000000, 0.000000, -0.995370, 0.000000], [0.000000, -0.863564, -0.968883, -0.963987, 0.000000, 0.000000, -0.916587, 0.000000], [0.000000, -0.967238, -0.999610, -0.999915, 0.000000, 0.000000, -0.991004, 0.000000], [0.000000, -0.968915, -0.998658, -0.999169, 0.000000, 0.000000, -0.992726, 0.000000]]
pre_activation_mean: [0.144037, 0.745557, 0.821411, -0.275135, 1.029647, -0.589783, -0.629432]
pre_activation_std: [0.830495, 2.213851, 0.036292, 0.072824, 0.125307, 0.140798, 0.103632]
### 12
mean: [-0.134179]
std: [1.657680]
fourier: [[26.608102, 27.876641, 28.073317, 28.606417, 29.908267]]
input_correlations: [[0.999531, 0.999835, 0.386398, 0.000000, -0.978264, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.134179]
pre_activation_std: [1.657680]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| decreasing_pairs | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.4.weight": [
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0.038719,
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"network.12.bias": [
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}
## Activation Signature
### 0
mean: [0.315030, 0.915512, 0.821411, 0.000000, 1.029647, 0.000000, 0.000000]
std: [0.758247, 2.140420, 0.036292, 0.000000, 0.125307, 0.000000, 0.000000]
fourier: [[12.644156, 12.764160, 13.121601, 13.543934, 28.352692], [36.170514, 36.236817, 37.077460, 38.732014, 82.396072], [0.541265, 0.583825, 0.593242, 0.650012, 73.926985], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.963386, 2.020788, 2.207101, 2.266311, 92.668279], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.770341, -0.758549, -0.557224, -0.195155, -0.372925, 0.000000, 0.000000, 0.000000], [-0.652945, 0.247324, 0.167244, -0.093920, 0.170067, 0.000000, 0.000000, 0.000000], [-0.464545, -0.356191, 0.018517, 0.154056, 0.769583, 0.000000, 0.000000, 0.000000], [-0.642435, 0.242774, 0.096009, 0.662785, -0.199628, 0.000000, 0.000000, 0.000000], [-0.709317, -0.459614, -0.600794, -0.504524, -0.507840, 0.000000, 0.000000, 0.000000], [0.769983, 0.571468, 0.444289, 0.123110, -0.329341, 0.000000, 0.000000, 0.000000], [0.694327, 0.841557, 0.075448, 0.396966, 0.063887, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.508844, 0.436040, 0.508646, 1.343133, -2.095328, 1.135988, 1.358352]
pre_activation_std: [1.731429, 1.117096, 1.285440, 1.802585, 1.280426, 2.045538, 1.598807]
### 2
mean: [-0.676872, -0.149915, -0.198808, -0.665682, 0.063591, -0.566724, -1.322553]
std: [1.636173, 1.754611, 1.002924, 0.374083, 1.030459, 1.518317, 0.550198]
fourier: [[26.503015, 28.531559, 32.637837, 32.646101, 60.918441], [27.309359, 28.235180, 28.832236, 29.520215, 34.551458], [16.285677, 16.563635, 17.892740, 20.236277, 20.704917], [5.506223, 5.776535, 5.806215, 6.698995, 59.911366], [14.824357, 14.998575, 15.085597, 17.805352, 19.890956], [23.680318, 24.754729, 26.322155, 29.073768, 51.005150], [7.919780, 8.070903, 8.842887, 9.044082, 119.029729]]
input_correlations: [[0.000000, -0.634438, -0.348800, -0.624532, 0.000000, 0.781959, 0.652798, 0.000000], [0.000000, -0.515096, -0.657327, -0.453520, 0.000000, 0.852633, 0.682219, 0.000000], [0.000000, -0.635430, -0.263910, -0.737990, 0.000000, 0.666527, 0.578836, 0.000000], [0.000000, -0.406720, 0.015890, -0.948655, 0.000000, -0.157396, -0.223022, 0.000000], [0.000000, 0.428516, 0.727027, 0.274144, 0.000000, -0.896036, -0.726847, 0.000000], [0.000000, -0.471103, -0.633454, -0.367594, 0.000000, 0.903271, 0.758530, 0.000000], [0.000000, -0.306044, 0.143398, -0.652799, 0.000000, -0.607613, -0.506801, 0.000000]]
pre_activation_mean: [-0.676872, -0.149915, -0.198808, -0.665682, 0.063591, -0.566724, -1.322553]
pre_activation_std: [1.636173, 1.754611, 1.002924, 0.374083, 1.030459, 1.518317, 0.550198]
### 4
mean: [-0.227744, -0.872622, -0.495918, 0.887538, -0.555788, 0.303349, 0.538804]
std: [0.106890, 0.851060, 0.405501, 1.965821, 0.487744, 1.858847, 0.116237]
fourier: [[1.638017, 1.654135, 1.992891, 1.999711, 20.496956], [13.620927, 14.740273, 15.350654, 16.079223, 78.535959], [6.475640, 6.713360, 7.315461, 8.008486, 44.632595], [30.563269, 31.198750, 35.003672, 35.320789, 79.878450], [8.187228, 8.467551, 9.300526, 9.610569, 50.020914], [28.317494, 28.322330, 30.212451, 32.921516, 33.342004], [1.805722, 2.100610, 2.358268, 2.383670, 48.492357]]
input_correlations: [[-0.950294, -0.979366, -0.926463, 0.000000, 0.507481, -0.967021, 0.000000, 0.000000], [-0.990421, -0.996118, -0.979370, 0.000000, 0.404815, -0.988349, 0.000000, 0.000000], [-0.942421, -0.939450, -0.951355, 0.000000, 0.619885, -0.925200, 0.000000, 0.000000], [0.984945, 0.985646, 0.974156, 0.000000, -0.475593, 0.981473, 0.000000, 0.000000], [-0.987147, -0.981253, -0.967263, 0.000000, 0.194254, -0.986229, 0.000000, 0.000000], [0.976829, 0.978486, 0.968362, 0.000000, -0.515442, 0.972219, 0.000000, 0.000000], [0.926574, 0.970797, 0.905014, 0.000000, -0.194288, 0.952612, 0.000000, 0.000000]]
pre_activation_mean: [-0.227744, -0.872622, -0.495918, 0.887538, -0.555788, 0.303349, 0.538804]
pre_activation_std: [0.106890, 0.851060, 0.405501, 1.965821, 0.487744, 1.858847, 0.116237]
### 6
mean: [-0.766603, -0.147424, 0.031109, 0.353826, -0.333755, 0.811890, 0.056697]
std: [1.178754, 0.155530, 0.631510, 1.577938, 0.066822, 1.360080, 1.175560]
fourier: [[19.401526, 20.575735, 20.842759, 21.657432, 68.994285], [2.543120, 2.544130, 2.641256, 2.801353, 13.268201], [10.169670, 10.678485, 10.786605, 11.040090, 11.728122], [26.055757, 27.410443, 27.589310, 28.769261, 31.844295], [1.106344, 1.170272, 1.245468, 1.290786, 30.037962], [22.157258, 23.897994, 24.108816, 24.819269, 73.070096], [18.834623, 19.473869, 20.410043, 20.686765, 21.558479]]
input_correlations: [[0.000000, 0.000000, 0.082673, -0.999246, 0.000000, -0.999454, -0.950107, 0.000000], [0.000000, 0.000000, 0.131246, -0.985121, 0.000000, -0.971127, -0.901500, 0.000000], [0.000000, 0.000000, -0.074789, 0.995783, 0.000000, 0.999782, 0.948570, 0.000000], [0.000000, 0.000000, -0.087991, 0.999181, 0.000000, 0.999384, 0.944629, 0.000000], [0.000000, 0.000000, 0.042230, 0.965560, 0.000000, 0.978336, 0.973515, 0.000000], [0.000000, 0.000000, -0.084902, 0.999825, 0.000000, 0.998552, 0.949250, 0.000000], [0.000000, 0.000000, -0.081153, 0.998890, 0.000000, 0.999698, 0.948314, 0.000000]]
pre_activation_mean: [-0.766603, -0.147424, 0.031109, 0.353826, -0.333755, 0.811890, 0.056697]
pre_activation_std: [1.178754, 0.155530, 0.631510, 1.577938, 0.066822, 1.360080, 1.175560]
### 8
mean: [-0.354436, 0.546436, 0.936903, 0.825156, -0.489861, -0.653495, 0.794371]
std: [0.487254, 0.188936, 1.941254, 1.744254, 0.317524, 1.326224, 0.197715]
fourier: [[8.077206, 8.416032, 8.558814, 8.854407, 31.899205], [3.378062, 3.385529, 3.415838, 3.453717, 49.179213], [32.571490, 33.179003, 33.863491, 35.264501, 84.321282], [29.061068, 30.031499, 30.566562, 31.737102, 74.264025], [5.279021, 5.437315, 5.481133, 5.816520, 44.087499], [22.380185, 22.481208, 23.016624, 24.004854, 58.814517], [3.155012, 3.555169, 3.586023, 3.611355, 71.493409]]
input_correlations: [[0.000000, 0.000000, -0.996939, -0.999402, 0.000000, -0.998312, -0.997972, 0.000000], [0.000000, 0.000000, 0.943897, 0.958726, 0.000000, 0.979721, 0.948317, 0.000000], [0.000000, 0.000000, 0.998193, 0.999887, 0.000000, 0.996837, 0.999025, 0.000000], [0.000000, 0.000000, 0.996991, 0.999558, 0.000000, 0.998183, 0.998057, 0.000000], [0.000000, 0.000000, -0.997927, -0.999632, 0.000000, -0.993821, -0.998732, 0.000000], [0.000000, 0.000000, -0.999284, -0.999716, 0.000000, -0.994573, -0.999774, 0.000000], [0.000000, 0.000000, 0.978019, 0.985180, 0.000000, 0.996189, 0.980361, 0.000000]]
pre_activation_mean: [-0.354436, 0.546436, 0.936903, 0.825156, -0.489861, -0.653495, 0.794371]
pre_activation_std: [0.487254, 0.188936, 1.941254, 1.744254, 0.317524, 1.326224, 0.197715]
### 10
mean: [0.144037, 0.745557, 0.821411, -0.275135, 1.029647, -0.589783, -0.629432]
std: [0.830495, 2.213851, 0.036292, 0.072824, 0.125307, 0.140798, 0.103632]
fourier: [[13.353968, 14.050123, 14.064378, 14.392554, 15.085801], [37.167452, 37.813496, 38.603223, 40.232877, 67.100103], [0.541265, 0.583825, 0.593242, 0.650012, 73.926985], [1.245395, 1.270438, 1.277117, 1.350467, 24.762153], [1.963386, 2.020788, 2.207101, 2.266311, 92.668279], [2.323581, 2.443565, 2.480286, 2.551729, 53.080469], [1.674209, 1.826978, 1.844473, 1.860774, 56.648893]]
input_correlations: [[0.000000, 0.955214, 0.999801, 0.999242, 0.000000, 0.000000, 0.983562, 0.000000], [0.000000, 0.960648, 0.999999, 0.999808, 0.000000, 0.000000, 0.986882, 0.000000], [0.000000, 0.658188, 0.425397, 0.442722, 0.000000, 0.000000, 0.563090, 0.000000], [0.000000, -0.990324, -0.987443, -0.990101, 0.000000, 0.000000, -0.995370, 0.000000], [0.000000, -0.863564, -0.968883, -0.963987, 0.000000, 0.000000, -0.916587, 0.000000], [0.000000, -0.967238, -0.999610, -0.999915, 0.000000, 0.000000, -0.991004, 0.000000], [0.000000, -0.968915, -0.998658, -0.999169, 0.000000, 0.000000, -0.992726, 0.000000]]
pre_activation_mean: [0.144037, 0.745557, 0.821411, -0.275135, 1.029647, -0.589783, -0.629432]
pre_activation_std: [0.830495, 2.213851, 0.036292, 0.072824, 0.125307, 0.140798, 0.103632]
### 12
mean: [-0.134179]
std: [1.657680]
fourier: [[26.608102, 27.876641, 28.073317, 28.606417, 29.908267]]
input_correlations: [[0.999531, 0.999835, 0.386398, 0.000000, -0.978264, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.134179]
pre_activation_std: [1.657680]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
decreasing_pairs | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.31502991914749146, "std": 0.7582474946975708, "fourier": [12.644155855442452, 12.764159616636672, 13.121601065584052, 13.5439337990162, 28.352691680192947], "input_correlations": [-0.7703406259018706, -0.7585489257760005, -0.5572235097033054, -0.19515539333856127, -0.37292508391838153, 0.0, 0.0, 0.0], "pre_activation_mean": -2.5088441371917725, "pre_activation_std": 1.7314292192459106}, "1": {"mean": 0.9155119061470032, "std": 2.1404201984405518, "fourier": [36.1705139292076, 36.23681693500105, 37.07745969420475, 38.73201433579269, 82.39607244729996], "input_correlations": [-0.6529448591772314, 0.24732358174288555, 0.1672442557982807, -0.09391998805069143, 0.17006682515092203, 0.0, 0.0, 0.0], "pre_activation_mean": 0.43603989481925964, "pre_activation_std": 1.1170960664749146}, "2": {"mean": 0.8214109539985657, "std": 0.03629150986671448, "fourier": [0.541265242926951, 0.5838249726186117, 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0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.7699832194984678, 0.5714675099906025, 0.44428869136724336, 0.12311007872156896, -0.32934129347948626, 0.0, 0.0, 0.0], "pre_activation_mean": 1.135988473892212, "pre_activation_std": 2.0455379486083984}, "6": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.694326706838435, 0.8415569364462097, 0.0754481201935025, 0.3969658044482271, 0.06388701578523424, 0.0, 0.0, 0.0], "pre_activation_mean": 1.3583520650863647, "pre_activation_std": 1.5988068580627441}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": -0.6768715381622314, "std": 1.6361730098724365, "fourier": [26.503015027186088, 28.53155911620205, 32.6378371020432, 32.646100756886064, 60.91844138503075], "input_correlations": [0.0, -0.6344379734103563, 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0.228226, -0.081669, -0.080009, -0.200249, -0.130167, 0.693027], [0.21036, -0.011075, -0.145612, 0.106405, 0.079482, -0.166029, -0.213318], [-0.236992, 0.013783, -0.292477, 0.31998, -0.027619, -0.507823, -0.493211]], "network.10.bias": [0.204398, 0.032832, 0.295884, -0.414563, 0.496951, -0.365655, -0.235181], "network.12.weight": [[0.417625, 0.597806, -0.134319, -0.04023, -0.519673, 0.10216, 0.131103]], "network.12.bias": [-0.167631]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.704754501581192, "train_acc": 0.43, "val_loss": 0.6847345232963562, "val_acc": 0.52}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6748220920562744, "train_acc": 0.57, "val_loss": 0.6491595506668091, "val_acc": 0.52}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6124464869499207, "train_acc": 0.59, "val_loss": 0.337535560131073, "val_acc": 0.98}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.39375123381614685, "train_acc": 0.885, "val_loss": 0.1954408586025238, "val_acc": 1.0}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.30438269674777985, "train_acc": 0.92, "val_loss": 0.28784066438674927, "val_acc": 0.96}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.26518669724464417, "train_acc": 0.94, "val_loss": 0.06668779253959656, "val_acc": 1.0}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.2646115943789482, "train_acc": 0.93, "val_loss": 0.03819397836923599, "val_acc": 1.0}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.1912805363535881, "train_acc": 0.925, "val_loss": 0.09922894835472107, "val_acc": 0.98}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.1759459599852562, "train_acc": 0.95, "val_loss": 0.026482395827770233, "val_acc": 1.0}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.13512615859508514, "train_acc": 0.95, "val_loss": 0.010663014836609364, "val_acc": 1.0}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.14888188242912292, "train_acc": 0.945, "val_loss": 0.009912002831697464, "val_acc": 1.0}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.1156117208302021, "train_acc": 0.945, "val_loss": 0.03375822678208351, "val_acc": 0.98}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["decreasing_pairs"], "degraded_stage": {"initial_val_loss": 0.6847345232963562, "final_val_loss": 0.6491595506668091, "initial_val_acc": 0.52, "final_val_acc": 0.52, "best_val_acc": 0.52}, "improved_stage": {"initial_val_loss": 0.337535560131073, "final_val_loss": 0.03375822678208351, "initial_val_acc": 0.98, "final_val_acc": 0.98, "best_val_acc": 1.0, "best_epoch": 3}, "improvement": 0.48, "first_improvement_epoch": 1}} |
84 | {"target_pattern": "palindrome", "degraded_accuracy": 0.54, "improved_accuracy": 0.88, "improvement": 0.33999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 6772, "learning_rate": 0.08443058899112679, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.2.weight": [
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[
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[
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"network.8.weight": [
[
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"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [6.158046, 0.000000, 0.000000, 0.000000, 0.000000, 2.409049, 5.355639]
std: [9.325611, 0.000000, 0.000000, 0.000000, 0.000000, 3.697411, 8.027476]
fourier: [[150.893836, 157.824978, 175.898076, 183.823167, 554.224217], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [59.298948, 62.621049, 70.414448, 72.529820, 216.814402], [129.294062, 136.134720, 151.406121, 157.743232, 482.007475]]
input_correlations: [[0.866412, 0.238801, -0.035008, -0.404193, 0.055873, 0.000000, 0.000000, 0.000000], [0.201517, -0.675307, -0.216510, -0.697194, 0.284373, 0.000000, 0.000000, 0.000000], [-0.765290, -0.306764, -0.134282, 0.105979, 0.493864, 0.000000, 0.000000, 0.000000], [-0.539624, -0.290543, -0.439497, 0.053556, -0.865235, 0.000000, 0.000000, 0.000000], [0.500675, 0.179782, 0.290554, 0.298538, 0.921310, 0.000000, 0.000000, 0.000000], [0.623245, 0.200913, 0.080647, 0.432789, 0.748950, 0.000000, 0.000000, 0.000000], [-0.520501, 0.005225, -0.032870, -0.102892, -0.881431, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.718652, -1.541221, -0.258322, -0.834259, 1.695016, 2.784214, -0.903795]
pre_activation_std: [2.877703, 2.941300, 4.141320, 0.691895, 2.372355, 2.758640, 2.556974]
### 2
mean: [-3.261476, -1.676889, 0.098689, -3.551007, 3.275443, 3.128353, -3.158720]
std: [2.478714, 2.548165, 3.232624, 2.795638, 3.933083, 4.562980, 3.400135]
fourier: [[41.826680, 43.712131, 51.065025, 51.959944, 293.532811], [43.846400, 44.376326, 45.047033, 52.212562, 150.920006], [48.189068, 49.630773, 57.550200, 62.056709, 79.478973], [42.397875, 45.795945, 54.435129, 62.333881, 319.590647], [68.220047, 73.130066, 73.251447, 84.727787, 294.789885], [74.467462, 79.368197, 79.659821, 89.679708, 281.551785], [57.592790, 58.224806, 70.010477, 70.012832, 284.284860]]
input_correlations: [[-0.385981, -0.346725, -0.523931, 0.040917, -0.975083, -0.955061, 0.465378, 0.000000], [-0.428241, 0.093853, -0.556608, 0.033918, -0.856855, -0.877429, 0.515993, 0.000000], [-0.563987, -0.239664, 0.930223, -0.016912, 0.329599, 0.151751, -0.190281, 0.000000], [-0.192308, -0.303685, -0.573637, 0.038303, -0.979429, -0.908225, 0.450138, 0.000000], [0.489793, 0.112404, 0.555261, -0.037314, 0.908540, 0.933221, -0.592392, 0.000000], [0.004846, -0.120533, 0.872772, -0.027668, 0.770549, 0.698174, -0.450857, 0.000000], [-0.269981, -0.070897, -0.642971, 0.033341, -0.952263, -0.915959, 0.500827, 0.000000]]
pre_activation_mean: [-3.261476, -1.676889, 0.098689, -3.551007, 3.275443, 3.128353, -3.158720]
pre_activation_std: [2.478714, 2.548165, 3.232624, 2.795638, 3.933083, 4.562980, 3.400135]
### 4
mean: [-0.738455, -1.006929, -3.080060, -2.035245, 6.339947, 1.749664, 3.086226]
std: [0.694490, 0.871947, 3.806399, 1.432546, 8.971063, 3.166134, 4.375222]
fourier: [[12.263410, 12.526185, 13.582636, 13.709957, 66.460955], [13.091779, 14.932001, 16.681144, 18.260555, 90.623602], [61.428649, 69.255615, 73.090980, 73.961918, 277.205343], [23.565580, 26.910132, 27.694292, 27.740030, 183.172040], [146.357229, 153.048708, 164.972817, 174.727683, 570.595268], [51.132337, 55.028231, 58.326628, 59.217113, 157.469809], [72.086870, 79.439591, 83.464061, 84.603068, 277.760322]]
input_correlations: [[0.000000, 0.318083, -0.635497, 0.000000, -0.985905, -0.871095, 0.171953, 0.000000], [0.000000, 0.242005, -0.745429, 0.000000, -0.931388, -0.939791, 0.111869, 0.000000], [0.000000, 0.384375, -0.854893, 0.000000, -0.919904, -0.983002, 0.244972, 0.000000], [0.000000, 0.363714, -0.774120, 0.000000, -0.957743, -0.956374, 0.227481, 0.000000], [0.000000, -0.373508, 0.922354, 0.000000, 0.850493, 0.993884, -0.246553, 0.000000], [0.000000, -0.328586, 0.956066, 0.000000, 0.804274, 0.975382, -0.216514, 0.000000], [0.000000, -0.383736, 0.868871, 0.000000, 0.913003, 0.980865, -0.247717, 0.000000]]
pre_activation_mean: [-0.738455, -1.006929, -3.080060, -2.035245, 6.339947, 1.749664, 3.086226]
pre_activation_std: [0.694490, 0.871947, 3.806399, 1.432546, 8.971063, 3.166134, 4.375222]
### 6
mean: [5.817470, 4.952698, -3.597458, -3.162406, -7.220660, 1.921877, -1.693169]
std: [8.651280, 7.340461, 4.436812, 4.175265, 9.614243, 3.296266, 1.987534]
fourier: [[136.031491, 148.858315, 163.317537, 167.738288, 523.572319], [115.907152, 126.496936, 136.954061, 143.564422, 445.742801], [70.448128, 76.163998, 83.105425, 86.428339, 323.771246], [69.710510, 70.233813, 76.445594, 81.863183, 284.616546], [155.664164, 163.644351, 179.044139, 187.405640, 649.859303], [54.740495, 55.505962, 60.437259, 64.627715, 172.968959], [32.557692, 36.991011, 38.203616, 38.441010, 152.385165]]
input_correlations: [[0.000000, 0.000000, -0.145925, 0.000000, 0.999198, 0.989694, 0.994548, 0.000000], [0.000000, 0.000000, -0.149512, 0.000000, 0.999641, 0.987279, 0.993939, 0.000000], [0.000000, 0.000000, 0.147376, 0.000000, -0.999653, -0.989256, -0.993701, 0.000000], [0.000000, 0.000000, 0.147478, 0.000000, -0.999830, -0.991057, -0.988051, 0.000000], [0.000000, 0.000000, 0.146646, 0.000000, -0.999869, -0.990841, -0.991854, 0.000000], [0.000000, 0.000000, -0.149478, 0.000000, 0.999887, 0.990839, 0.988581, 0.000000], [0.000000, 0.000000, 0.162370, 0.000000, -0.983518, -0.954693, -0.997194, 0.000000]]
pre_activation_mean: [5.817470, 4.952698, -3.597458, -3.162406, -7.220660, 1.921877, -1.693169]
pre_activation_std: [8.651280, 7.340461, 4.436812, 4.175265, 9.614243, 3.296266, 1.987534]
### 8
mean: [6.024985, -6.074801, -2.678698, -1.228634, -1.782066, 2.284580, 5.294232]
std: [9.414863, 8.164994, 3.594786, 1.607461, 1.692900, 3.781009, 8.068832]
fourier: [[150.939892, 160.006651, 176.818471, 185.033188, 542.248647], [130.621981, 138.869949, 153.709681, 160.065518, 546.732096], [56.799303, 61.442717, 67.930552, 70.196850, 241.082849], [26.819602, 26.864211, 29.862244, 31.889353, 110.577084], [28.242495, 28.286692, 30.986955, 34.057773, 160.386001], [59.265779, 64.844764, 71.361449, 73.940190, 205.612211], [129.300821, 137.137340, 151.882355, 158.191218, 476.480923]]
input_correlations: [[0.999814, 0.999916, 0.000000, 0.000000, 0.000000, 0.998730, 0.000000, 0.000000], [-0.999897, -0.999862, 0.000000, 0.000000, 0.000000, -0.998630, 0.000000, 0.000000], [-0.999986, -0.999805, 0.000000, 0.000000, 0.000000, -0.998030, 0.000000, 0.000000], [-0.998708, -0.999112, 0.000000, 0.000000, 0.000000, -0.999841, 0.000000, 0.000000], [-0.997265, -0.998568, 0.000000, 0.000000, 0.000000, -0.998952, 0.000000, 0.000000], [0.999907, 0.999875, 0.000000, 0.000000, 0.000000, 0.997649, 0.000000, 0.000000], [0.999886, 0.999844, 0.000000, 0.000000, 0.000000, 0.998698, 0.000000, 0.000000]]
pre_activation_mean: [6.024985, -6.074801, -2.678698, -1.228634, -1.782066, 2.284580, 5.294232]
pre_activation_std: [9.414863, 8.164994, 3.594786, 1.607461, 1.692900, 3.781009, 8.068832]
### 10
mean: [-3.073102]
std: [6.598603]
fourier: [[106.484720, 111.771023, 124.591513, 129.850318, 276.579135]]
input_correlations: [[-0.999994, 0.000000, 0.000000, 0.000000, 0.000000, -0.999888, -0.999986, 0.000000]]
pre_activation_mean: [-3.073102]
pre_activation_std: [6.598603]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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[
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[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
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],
[
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[
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[
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[
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[
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[
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],
"network.2.bias": [
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],
"network.4.weight": [
[
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[
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0.05348,
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[
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[
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0.31501
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[
0.198665,
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1.303301,
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[
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[
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"network.6.weight": [
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],
"network.6.bias": [
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],
"network.8.weight": [
[
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],
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],
[
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"network.10.weight": [
[
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],
"network.10.bias": [
1.295129
]
}
## Activation Signature
### 0
mean: [6.158046, 0.000000, 0.000000, 0.000000, 0.000000, 2.409049, 5.355639]
std: [9.325611, 0.000000, 0.000000, 0.000000, 0.000000, 3.697411, 8.027476]
fourier: [[150.893836, 157.824978, 175.898076, 183.823167, 554.224217], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [59.298948, 62.621049, 70.414448, 72.529820, 216.814402], [129.294062, 136.134720, 151.406121, 157.743232, 482.007475]]
input_correlations: [[0.866412, 0.238801, -0.035008, -0.404193, 0.055873, 0.000000, 0.000000, 0.000000], [0.201517, -0.675307, -0.216510, -0.697194, 0.284373, 0.000000, 0.000000, 0.000000], [-0.765290, -0.306764, -0.134282, 0.105979, 0.493864, 0.000000, 0.000000, 0.000000], [-0.539624, -0.290543, -0.439497, 0.053556, -0.865235, 0.000000, 0.000000, 0.000000], [0.500675, 0.179782, 0.290554, 0.298538, 0.921310, 0.000000, 0.000000, 0.000000], [0.623245, 0.200913, 0.080647, 0.432789, 0.748950, 0.000000, 0.000000, 0.000000], [-0.520501, 0.005225, -0.032870, -0.102892, -0.881431, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.718652, -1.541221, -0.258322, -0.834259, 1.695016, 2.784214, -0.903795]
pre_activation_std: [2.877703, 2.941300, 4.141320, 0.691895, 2.372355, 2.758640, 2.556974]
### 2
mean: [-3.261476, -1.676889, 0.098689, -3.551007, 3.275443, 3.128353, -3.158720]
std: [2.478714, 2.548165, 3.232624, 2.795638, 3.933083, 4.562980, 3.400135]
fourier: [[41.826680, 43.712131, 51.065025, 51.959944, 293.532811], [43.846400, 44.376326, 45.047033, 52.212562, 150.920006], [48.189068, 49.630773, 57.550200, 62.056709, 79.478973], [42.397875, 45.795945, 54.435129, 62.333881, 319.590647], [68.220047, 73.130066, 73.251447, 84.727787, 294.789885], [74.467462, 79.368197, 79.659821, 89.679708, 281.551785], [57.592790, 58.224806, 70.010477, 70.012832, 284.284860]]
input_correlations: [[-0.385981, -0.346725, -0.523931, 0.040917, -0.975083, -0.955061, 0.465378, 0.000000], [-0.428241, 0.093853, -0.556608, 0.033918, -0.856855, -0.877429, 0.515993, 0.000000], [-0.563987, -0.239664, 0.930223, -0.016912, 0.329599, 0.151751, -0.190281, 0.000000], [-0.192308, -0.303685, -0.573637, 0.038303, -0.979429, -0.908225, 0.450138, 0.000000], [0.489793, 0.112404, 0.555261, -0.037314, 0.908540, 0.933221, -0.592392, 0.000000], [0.004846, -0.120533, 0.872772, -0.027668, 0.770549, 0.698174, -0.450857, 0.000000], [-0.269981, -0.070897, -0.642971, 0.033341, -0.952263, -0.915959, 0.500827, 0.000000]]
pre_activation_mean: [-3.261476, -1.676889, 0.098689, -3.551007, 3.275443, 3.128353, -3.158720]
pre_activation_std: [2.478714, 2.548165, 3.232624, 2.795638, 3.933083, 4.562980, 3.400135]
### 4
mean: [-0.738455, -1.006929, -3.080060, -2.035245, 6.339947, 1.749664, 3.086226]
std: [0.694490, 0.871947, 3.806399, 1.432546, 8.971063, 3.166134, 4.375222]
fourier: [[12.263410, 12.526185, 13.582636, 13.709957, 66.460955], [13.091779, 14.932001, 16.681144, 18.260555, 90.623602], [61.428649, 69.255615, 73.090980, 73.961918, 277.205343], [23.565580, 26.910132, 27.694292, 27.740030, 183.172040], [146.357229, 153.048708, 164.972817, 174.727683, 570.595268], [51.132337, 55.028231, 58.326628, 59.217113, 157.469809], [72.086870, 79.439591, 83.464061, 84.603068, 277.760322]]
input_correlations: [[0.000000, 0.318083, -0.635497, 0.000000, -0.985905, -0.871095, 0.171953, 0.000000], [0.000000, 0.242005, -0.745429, 0.000000, -0.931388, -0.939791, 0.111869, 0.000000], [0.000000, 0.384375, -0.854893, 0.000000, -0.919904, -0.983002, 0.244972, 0.000000], [0.000000, 0.363714, -0.774120, 0.000000, -0.957743, -0.956374, 0.227481, 0.000000], [0.000000, -0.373508, 0.922354, 0.000000, 0.850493, 0.993884, -0.246553, 0.000000], [0.000000, -0.328586, 0.956066, 0.000000, 0.804274, 0.975382, -0.216514, 0.000000], [0.000000, -0.383736, 0.868871, 0.000000, 0.913003, 0.980865, -0.247717, 0.000000]]
pre_activation_mean: [-0.738455, -1.006929, -3.080060, -2.035245, 6.339947, 1.749664, 3.086226]
pre_activation_std: [0.694490, 0.871947, 3.806399, 1.432546, 8.971063, 3.166134, 4.375222]
### 6
mean: [5.817470, 4.952698, -3.597458, -3.162406, -7.220660, 1.921877, -1.693169]
std: [8.651280, 7.340461, 4.436812, 4.175265, 9.614243, 3.296266, 1.987534]
fourier: [[136.031491, 148.858315, 163.317537, 167.738288, 523.572319], [115.907152, 126.496936, 136.954061, 143.564422, 445.742801], [70.448128, 76.163998, 83.105425, 86.428339, 323.771246], [69.710510, 70.233813, 76.445594, 81.863183, 284.616546], [155.664164, 163.644351, 179.044139, 187.405640, 649.859303], [54.740495, 55.505962, 60.437259, 64.627715, 172.968959], [32.557692, 36.991011, 38.203616, 38.441010, 152.385165]]
input_correlations: [[0.000000, 0.000000, -0.145925, 0.000000, 0.999198, 0.989694, 0.994548, 0.000000], [0.000000, 0.000000, -0.149512, 0.000000, 0.999641, 0.987279, 0.993939, 0.000000], [0.000000, 0.000000, 0.147376, 0.000000, -0.999653, -0.989256, -0.993701, 0.000000], [0.000000, 0.000000, 0.147478, 0.000000, -0.999830, -0.991057, -0.988051, 0.000000], [0.000000, 0.000000, 0.146646, 0.000000, -0.999869, -0.990841, -0.991854, 0.000000], [0.000000, 0.000000, -0.149478, 0.000000, 0.999887, 0.990839, 0.988581, 0.000000], [0.000000, 0.000000, 0.162370, 0.000000, -0.983518, -0.954693, -0.997194, 0.000000]]
pre_activation_mean: [5.817470, 4.952698, -3.597458, -3.162406, -7.220660, 1.921877, -1.693169]
pre_activation_std: [8.651280, 7.340461, 4.436812, 4.175265, 9.614243, 3.296266, 1.987534]
### 8
mean: [6.024985, -6.074801, -2.678698, -1.228634, -1.782066, 2.284580, 5.294232]
std: [9.414863, 8.164994, 3.594786, 1.607461, 1.692900, 3.781009, 8.068832]
fourier: [[150.939892, 160.006651, 176.818471, 185.033188, 542.248647], [130.621981, 138.869949, 153.709681, 160.065518, 546.732096], [56.799303, 61.442717, 67.930552, 70.196850, 241.082849], [26.819602, 26.864211, 29.862244, 31.889353, 110.577084], [28.242495, 28.286692, 30.986955, 34.057773, 160.386001], [59.265779, 64.844764, 71.361449, 73.940190, 205.612211], [129.300821, 137.137340, 151.882355, 158.191218, 476.480923]]
input_correlations: [[0.999814, 0.999916, 0.000000, 0.000000, 0.000000, 0.998730, 0.000000, 0.000000], [-0.999897, -0.999862, 0.000000, 0.000000, 0.000000, -0.998630, 0.000000, 0.000000], [-0.999986, -0.999805, 0.000000, 0.000000, 0.000000, -0.998030, 0.000000, 0.000000], [-0.998708, -0.999112, 0.000000, 0.000000, 0.000000, -0.999841, 0.000000, 0.000000], [-0.997265, -0.998568, 0.000000, 0.000000, 0.000000, -0.998952, 0.000000, 0.000000], [0.999907, 0.999875, 0.000000, 0.000000, 0.000000, 0.997649, 0.000000, 0.000000], [0.999886, 0.999844, 0.000000, 0.000000, 0.000000, 0.998698, 0.000000, 0.000000]]
pre_activation_mean: [6.024985, -6.074801, -2.678698, -1.228634, -1.782066, 2.284580, 5.294232]
pre_activation_std: [9.414863, 8.164994, 3.594786, 1.607461, 1.692900, 3.781009, 8.068832]
### 10
mean: [-3.073102]
std: [6.598603]
fourier: [[106.484720, 111.771023, 124.591513, 129.850318, 276.579135]]
input_correlations: [[-0.999994, 0.000000, 0.000000, 0.000000, 0.000000, -0.999888, -0.999986, 0.000000]]
pre_activation_mean: [-3.073102]
pre_activation_std: [6.598603]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 6.158046245574951, "std": 9.325611114501953, "fourier": [150.89383552166396, 157.82497802579212, 175.89807591232778, 183.8231667408336, 554.2242166101933], "input_correlations": [0.8664123906185036, 0.23880099194606935, -0.035007886752796466, -0.40419300572948136, 0.05587256188387351, 0.0, 0.0, 0.0], "pre_activation_mean": -0.7186524868011475, "pre_activation_std": 2.8777031898498535}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.20151736134041257, -0.6753068281137282, -0.21650989462113243, -0.6971941531873197, 0.2843733132497129, 0.0, 0.0, 0.0], "pre_activation_mean": -1.5412211418151855, "pre_activation_std": 2.9412996768951416}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.7652895387639337, -0.3067636647097683, -0.13428231639969387, 0.10597883398354101, 0.49386352260953853, 0.0, 0.0, 0.0], 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-0.425456, -0.13219], "network.8.weight": [[0.369086, 0.64559, 0.060092, 0.36733, -0.250515, 0.483445, -0.026069], [-0.527825, -0.328857, 0.154473, -0.140625, -0.145874, -0.386294, -0.361835], [-0.328912, -0.10648, 0.116749, 0.141989, 0.153731, 0.001981, -0.050201], [0.026214, -0.095953, 0.07159, -0.329553, 0.07549, -0.353905, -0.572189], [0.309503, -0.456918, 0.500948, 0.550566, -0.048721, -0.32082, -0.044598], [0.242654, 0.300351, -0.317695, -0.110285, -0.32638, -0.15247, -0.014508], [0.533377, 0.283874, -0.312949, -0.143285, 0.001588, 0.443446, 0.109952]], "network.8.bias": [-0.404466, -0.508149, -0.205103, -0.17238, -0.641469, -0.350603, -0.195266], "network.10.weight": [[-0.363285, -0.357661, 0.054453, -0.075087, 0.278749, -0.191925, -0.311587]], "network.10.bias": [1.295129]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7022350132465363, "train_acc": 0.475, "val_loss": 0.6984809041023254, "val_acc": 0.54}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6704228520393372, "train_acc": 0.565, "val_loss": 0.6355419754981995, "val_acc": 0.54}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.623627781867981, "train_acc": 0.49, "val_loss": 0.5755332708358765, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5452483892440796, "train_acc": 0.83, "val_loss": 0.5398643612861633, "val_acc": 0.76}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.49061016738414764, "train_acc": 0.79, "val_loss": 0.46750137209892273, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.43408243358135223, "train_acc": 0.79, "val_loss": 0.49018165469169617, "val_acc": 0.76}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.44073230028152466, "train_acc": 0.81, "val_loss": 0.4929560124874115, "val_acc": 0.76}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.3974185436964035, "train_acc": 0.83, "val_loss": 0.4619685411453247, "val_acc": 0.76}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.36770716309547424, "train_acc": 0.845, "val_loss": 0.41366684436798096, "val_acc": 0.76}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.3234269469976425, "train_acc": 0.88, "val_loss": 0.36349377036094666, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.3503015488386154, "train_acc": 0.865, "val_loss": 0.34761619567871094, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.30983734130859375, "train_acc": 0.895, "val_loss": 0.34635066986083984, "val_acc": 0.84}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.6984809041023254, "final_val_loss": 0.6355419754981995, "initial_val_acc": 0.54, "final_val_acc": 0.54, "best_val_acc": 0.54}, "improved_stage": {"initial_val_loss": 0.5755332708358765, "final_val_loss": 0.34635066986083984, "initial_val_acc": 0.78, "final_val_acc": 0.84, "best_val_acc": 0.88, "best_epoch": 10}, "improvement": 0.33999999999999997, "first_improvement_epoch": 1}} |
85 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.7, "improved_accuracy": 0.88, "improvement": 0.18000000000000005, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4426, "learning_rate": 0.04712606318248816, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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"network.8.weight": [
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}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.265409, 1.366967, 21.996021, 19.684189]
std: [0.000000, 0.000000, 0.000000, 0.342812, 0.485047, 27.559546, 24.709091]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.009803, 5.180090, 5.332353, 7.378051, 23.886855], [7.665174, 7.677258, 7.726046, 9.001638, 123.026988], [416.506541, 446.042514, 450.657134, 509.349004, 1979.641851], [373.046721, 399.993764, 404.088917, 456.649756, 1771.576959]]
input_correlations: [[-0.654809, -0.787921, -0.413824, -0.258548, -0.519697, 0.000000, 0.000000, 0.000000], [-0.056029, -0.138221, 0.236111, 0.695622, 0.686269, 0.000000, 0.000000, 0.000000], [-0.432196, 0.149179, 0.313725, 0.790373, 0.227023, 0.000000, 0.000000, 0.000000], [-0.317704, -0.484485, 0.324878, 0.305738, 0.626258, 0.000000, 0.000000, 0.000000], [-0.725500, -0.282867, 0.203451, 0.474678, 0.106176, 0.000000, 0.000000, 0.000000], [-0.764466, -0.179389, -0.298139, 0.630634, 0.145163, 0.000000, 0.000000, 0.000000], [-0.607453, -0.141269, -0.665471, 0.566031, 0.157638, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.001546, 1.969690, 0.486704, 0.717916, 0.550725, 0.011081, -0.902083]
pre_activation_std: [1.478752, 1.894635, 0.778878, 1.743079, 2.049352, 2.018208, 2.300558]
### 2
mean: [-1.467542, 1.292983, 1.933682, 0.492336, -0.879233, 2.083613, 2.226490]
std: [1.098357, 1.813727, 2.518773, 0.851254, 0.924502, 2.464043, 2.117835]
fourier: [[17.860547, 17.893694, 17.977335, 18.800994, 132.078769], [27.813377, 29.797966, 30.593016, 34.087724, 116.368477], [39.014285, 40.145743, 43.256825, 44.139402, 174.031329], [13.823340, 13.922736, 14.598820, 15.272246, 44.310281], [14.646162, 16.788613, 17.537586, 18.048734, 79.130987], [38.776090, 39.463411, 41.876240, 43.308427, 187.525213], [33.386383, 34.535334, 34.930615, 38.108640, 200.384160]]
input_correlations: [[0.000000, -0.950642, -0.804177, -0.937456, -0.778044, -0.764501, -0.615290, 0.000000], [0.000000, 0.649496, 0.717473, 0.486270, 0.629896, 0.973371, 0.924629, 0.000000], [0.000000, 0.841189, 0.861939, 0.811836, 0.873101, 0.907478, 0.714090, 0.000000], [0.000000, -0.012179, -0.427189, -0.037683, -0.536570, -0.615357, -0.587505, 0.000000], [0.000000, -0.878961, -0.822509, -0.941110, -0.865433, -0.645009, -0.407860, 0.000000], [0.000000, 0.837851, 0.875606, 0.785953, 0.871899, 0.917069, 0.727375, 0.000000], [0.000000, 0.855931, 0.814505, 0.796228, 0.803447, 0.932220, 0.790817, 0.000000]]
pre_activation_mean: [-1.467542, 1.292983, 1.933682, 0.492336, -0.879233, 2.083613, 2.226490]
pre_activation_std: [1.098357, 1.813727, 2.518773, 0.851254, 0.924502, 2.464043, 2.117835]
### 4
mean: [-1.783715, -1.478222, -2.765825, 4.319680, 4.701647, 2.926258, 3.946613]
std: [1.697788, 1.042344, 2.571115, 5.666039, 6.082309, 3.500331, 4.941259]
fourier: [[27.182573, 27.692429, 27.754887, 29.490514, 160.534324], [16.638615, 16.697311, 16.875165, 17.276326, 133.039985], [41.297559, 41.767057, 41.784832, 46.035149, 248.924201], [88.794032, 90.886142, 90.957759, 105.111968, 388.771181], [91.939477, 97.481420, 99.033103, 114.489672, 423.148244], [52.592162, 56.920824, 58.744859, 63.205489, 263.363258], [77.025769, 80.122538, 80.846157, 89.281169, 355.195122]]
input_correlations: [[0.000000, -0.917834, -0.995475, 0.402566, 0.481890, -0.997348, -0.996273, 0.000000], [0.000000, -0.851338, -0.983278, 0.248657, 0.512919, -0.979641, -0.985507, 0.000000], [0.000000, -0.917397, -0.995669, 0.414980, 0.489885, -0.997337, -0.997432, 0.000000], [0.000000, 0.930545, 0.992313, -0.485280, -0.456008, 0.994557, 0.990739, 0.000000], [0.000000, 0.949266, 0.983436, -0.509838, -0.443321, 0.987414, 0.986291, 0.000000], [0.000000, 0.953972, 0.983203, -0.453588, -0.455183, 0.987080, 0.992025, 0.000000], [0.000000, 0.934214, 0.992452, -0.450539, -0.461807, 0.994746, 0.994499, 0.000000]]
pre_activation_mean: [-1.783715, -1.478222, -2.765825, 4.319680, 4.701647, 2.926258, 3.946613]
pre_activation_std: [1.697788, 1.042344, 2.571115, 5.666039, 6.082309, 3.500331, 4.941259]
### 6
mean: [11.876305, 8.808787, -0.945121, 8.068151, -1.682108, 0.193868, 6.802662]
std: [14.886733, 11.109057, 0.923918, 10.198069, 1.802789, 0.438439, 8.724652]
fourier: [[227.062419, 240.758424, 243.140387, 274.518517, 1068.867317], [168.678771, 179.608833, 181.968723, 205.282685, 792.790868], [13.672623, 14.539410, 15.415599, 17.847683, 85.060918], [155.571725, 165.088703, 166.929161, 187.450652, 726.133654], [27.341854, 28.773535, 28.810970, 34.357037, 151.389706], [6.822631, 7.079789, 7.140982, 7.734910, 17.448094], [132.013880, 140.820673, 142.960464, 162.028339, 612.239554]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.999497, 0.999149, 0.998306, 0.999419, 0.000000], [0.000000, 0.000000, 0.000000, 0.999229, 0.999443, 0.998559, 0.999132, 0.000000], [0.000000, 0.000000, 0.000000, -0.981389, -0.990795, -0.986402, -0.979134, 0.000000], [0.000000, 0.000000, 0.000000, 0.999358, 0.998993, 0.998567, 0.999547, 0.000000], [0.000000, 0.000000, 0.000000, -0.998722, -0.998964, -0.993848, -0.995900, 0.000000], [0.000000, 0.000000, 0.000000, 0.937986, 0.938921, 0.960916, 0.952578, 0.000000], [0.000000, 0.000000, 0.000000, 0.999046, 0.999720, 0.998407, 0.998673, 0.000000]]
pre_activation_mean: [11.876305, 8.808787, -0.945121, 8.068151, -1.682108, 0.193868, 6.802662]
pre_activation_std: [14.886733, 11.109057, 0.923918, 10.198069, 1.802789, 0.438439, 8.724652]
### 8
mean: [-7.302178, -3.412899, -6.297867, -4.574237, 1.366967, 21.938623, 19.612925]
std: [8.954237, 4.074473, 7.199622, 6.615674, 0.485047, 27.605438, 24.766003]
fourier: [[135.677669, 144.820673, 146.235901, 165.613505, 657.196100], [60.982502, 65.979725, 66.912182, 75.468276, 307.160954], [108.528160, 116.385327, 117.770094, 133.543561, 566.807989], [100.168441, 107.036215, 108.230176, 122.195999, 411.681367], [7.665174, 7.677258, 7.726046, 9.001638, 123.026988], [417.932304, 446.704666, 451.405247, 510.022588, 1974.476142], [374.816967, 400.815774, 405.017354, 457.486082, 1765.163166]]
input_correlations: [[-0.999985, -0.999982, 0.078364, -0.999957, 0.000000, -0.937976, -0.999887, 0.000000], [-0.999785, -0.999936, 0.079350, -0.999791, 0.000000, -0.940412, -0.999968, 0.000000], [-0.999906, -0.999983, 0.081120, -0.999871, 0.000000, -0.937731, -0.999977, 0.000000], [-0.999982, -0.999992, 0.076983, -0.999966, 0.000000, -0.938771, -0.999888, 0.000000], [0.995967, 0.995278, -0.090049, 0.995608, 0.000000, 0.910520, 0.994838, 0.000000], [0.999983, 0.999991, -0.077210, 0.999967, 0.000000, 0.938805, 0.999890, 0.000000], [0.999982, 0.999991, -0.077013, 0.999970, 0.000000, 0.938988, 0.999889, 0.000000]]
pre_activation_mean: [-7.302178, -3.412899, -6.297867, -4.574237, 1.366967, 21.938623, 19.612925]
pre_activation_std: [8.954237, 4.074473, 7.199622, 6.615674, 0.485047, 27.605438, 24.766003]
### 10
mean: [-24.479044]
std: [33.004055]
fourier: [[502.070673, 533.749285, 539.729958, 609.185316, 2203.114029]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.621373, -0.995547, -0.999976, -0.999967, 0.000000]]
pre_activation_mean: [-24.479044]
pre_activation_std: [33.004055]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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[
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[
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[
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],
[
-0.771571,
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[
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0.220194
],
[
-0.494496,
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0.574048,
0.354176
]
],
"network.0.bias": [
-0.199438,
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-0.279224,
-0.063108,
-0.139385,
-0.19228,
-0.418223
],
"network.2.weight": [
[
0.270312,
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-0.253267
],
[
0.414071,
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-0.205409,
0.364117,
0.706714,
0.964722
],
[
0.134002,
0.053822,
0.070547,
0.507243,
0.767859,
0.632168,
0.510072
],
[
0.306421,
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0.121085,
0.092482,
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],
[
0.185488,
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0.197139,
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],
[
0.075797,
0.171902,
0.118704,
0.24684,
0.857315,
0.444633,
0.637032
],
[
0.218778,
0.18241,
-0.330088,
0.314452,
0.587825,
0.546266,
0.634598
]
],
"network.2.bias": [
-0.309349,
0.100863,
-0.393062,
0.527925,
0.085706,
-0.240129,
0.299562
],
"network.4.weight": [
[
0.328046,
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-0.262855,
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-0.001436,
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],
[
0.233633,
0.035032,
-0.318972,
-0.246343,
-0.140678,
0.040189,
-0.228347
],
[
0.064369,
-0.088286,
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0.011483,
0.335558,
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-0.490248
],
[
0.359667,
0.483828,
0.891752,
-0.525039,
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0.682058,
0.427774
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[
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0.578432,
-0.708778,
-0.035652,
0.782825,
0.526113
],
[
-0.135745,
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0.572794,
0.00648,
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0.182362,
0.250092
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[
0.190578,
0.589721,
0.904007,
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0.158642,
0.472212,
0.297888
]
],
"network.4.bias": [
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"network.6.weight": [
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[
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0.743096,
0.565405,
0.457763
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[
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[
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0.517562,
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0.56672,
0.640123
],
[
0.125597,
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0.152184,
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0.14675,
0.145953
],
[
0.080782,
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0.20625,
-0.220952,
-0.152672,
0.389273,
0.245009
],
[
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0.253768,
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0.533654,
0.65882,
0.654417,
-0.098685
]
],
"network.6.bias": [
-0.183231,
-0.191479,
-0.223922,
-0.225002,
-0.274814,
-0.210698,
-0.251341
],
"network.8.weight": [
[
-0.507469,
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-0.020681,
-0.028309,
0.04051,
-0.375888
],
[
0.092922,
-0.234696,
-0.114121,
-0.00258,
0.107395,
-0.191765,
-0.318585
],
[
-0.155686,
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0.085582,
0.003538,
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0.047974,
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],
[
0.104939,
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[
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],
[
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0.095397,
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[
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0.488711
]
],
"network.8.bias": [
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0.96994,
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-0.213793
],
"network.10.weight": [
[
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0.945937,
0.925084,
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],
"network.10.bias": [
0.5178
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 0.000000, 0.265409, 1.366967, 21.996021, 19.684189]
std: [0.000000, 0.000000, 0.000000, 0.342812, 0.485047, 27.559546, 24.709091]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [5.009803, 5.180090, 5.332353, 7.378051, 23.886855], [7.665174, 7.677258, 7.726046, 9.001638, 123.026988], [416.506541, 446.042514, 450.657134, 509.349004, 1979.641851], [373.046721, 399.993764, 404.088917, 456.649756, 1771.576959]]
input_correlations: [[-0.654809, -0.787921, -0.413824, -0.258548, -0.519697, 0.000000, 0.000000, 0.000000], [-0.056029, -0.138221, 0.236111, 0.695622, 0.686269, 0.000000, 0.000000, 0.000000], [-0.432196, 0.149179, 0.313725, 0.790373, 0.227023, 0.000000, 0.000000, 0.000000], [-0.317704, -0.484485, 0.324878, 0.305738, 0.626258, 0.000000, 0.000000, 0.000000], [-0.725500, -0.282867, 0.203451, 0.474678, 0.106176, 0.000000, 0.000000, 0.000000], [-0.764466, -0.179389, -0.298139, 0.630634, 0.145163, 0.000000, 0.000000, 0.000000], [-0.607453, -0.141269, -0.665471, 0.566031, 0.157638, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.001546, 1.969690, 0.486704, 0.717916, 0.550725, 0.011081, -0.902083]
pre_activation_std: [1.478752, 1.894635, 0.778878, 1.743079, 2.049352, 2.018208, 2.300558]
### 2
mean: [-1.467542, 1.292983, 1.933682, 0.492336, -0.879233, 2.083613, 2.226490]
std: [1.098357, 1.813727, 2.518773, 0.851254, 0.924502, 2.464043, 2.117835]
fourier: [[17.860547, 17.893694, 17.977335, 18.800994, 132.078769], [27.813377, 29.797966, 30.593016, 34.087724, 116.368477], [39.014285, 40.145743, 43.256825, 44.139402, 174.031329], [13.823340, 13.922736, 14.598820, 15.272246, 44.310281], [14.646162, 16.788613, 17.537586, 18.048734, 79.130987], [38.776090, 39.463411, 41.876240, 43.308427, 187.525213], [33.386383, 34.535334, 34.930615, 38.108640, 200.384160]]
input_correlations: [[0.000000, -0.950642, -0.804177, -0.937456, -0.778044, -0.764501, -0.615290, 0.000000], [0.000000, 0.649496, 0.717473, 0.486270, 0.629896, 0.973371, 0.924629, 0.000000], [0.000000, 0.841189, 0.861939, 0.811836, 0.873101, 0.907478, 0.714090, 0.000000], [0.000000, -0.012179, -0.427189, -0.037683, -0.536570, -0.615357, -0.587505, 0.000000], [0.000000, -0.878961, -0.822509, -0.941110, -0.865433, -0.645009, -0.407860, 0.000000], [0.000000, 0.837851, 0.875606, 0.785953, 0.871899, 0.917069, 0.727375, 0.000000], [0.000000, 0.855931, 0.814505, 0.796228, 0.803447, 0.932220, 0.790817, 0.000000]]
pre_activation_mean: [-1.467542, 1.292983, 1.933682, 0.492336, -0.879233, 2.083613, 2.226490]
pre_activation_std: [1.098357, 1.813727, 2.518773, 0.851254, 0.924502, 2.464043, 2.117835]
### 4
mean: [-1.783715, -1.478222, -2.765825, 4.319680, 4.701647, 2.926258, 3.946613]
std: [1.697788, 1.042344, 2.571115, 5.666039, 6.082309, 3.500331, 4.941259]
fourier: [[27.182573, 27.692429, 27.754887, 29.490514, 160.534324], [16.638615, 16.697311, 16.875165, 17.276326, 133.039985], [41.297559, 41.767057, 41.784832, 46.035149, 248.924201], [88.794032, 90.886142, 90.957759, 105.111968, 388.771181], [91.939477, 97.481420, 99.033103, 114.489672, 423.148244], [52.592162, 56.920824, 58.744859, 63.205489, 263.363258], [77.025769, 80.122538, 80.846157, 89.281169, 355.195122]]
input_correlations: [[0.000000, -0.917834, -0.995475, 0.402566, 0.481890, -0.997348, -0.996273, 0.000000], [0.000000, -0.851338, -0.983278, 0.248657, 0.512919, -0.979641, -0.985507, 0.000000], [0.000000, -0.917397, -0.995669, 0.414980, 0.489885, -0.997337, -0.997432, 0.000000], [0.000000, 0.930545, 0.992313, -0.485280, -0.456008, 0.994557, 0.990739, 0.000000], [0.000000, 0.949266, 0.983436, -0.509838, -0.443321, 0.987414, 0.986291, 0.000000], [0.000000, 0.953972, 0.983203, -0.453588, -0.455183, 0.987080, 0.992025, 0.000000], [0.000000, 0.934214, 0.992452, -0.450539, -0.461807, 0.994746, 0.994499, 0.000000]]
pre_activation_mean: [-1.783715, -1.478222, -2.765825, 4.319680, 4.701647, 2.926258, 3.946613]
pre_activation_std: [1.697788, 1.042344, 2.571115, 5.666039, 6.082309, 3.500331, 4.941259]
### 6
mean: [11.876305, 8.808787, -0.945121, 8.068151, -1.682108, 0.193868, 6.802662]
std: [14.886733, 11.109057, 0.923918, 10.198069, 1.802789, 0.438439, 8.724652]
fourier: [[227.062419, 240.758424, 243.140387, 274.518517, 1068.867317], [168.678771, 179.608833, 181.968723, 205.282685, 792.790868], [13.672623, 14.539410, 15.415599, 17.847683, 85.060918], [155.571725, 165.088703, 166.929161, 187.450652, 726.133654], [27.341854, 28.773535, 28.810970, 34.357037, 151.389706], [6.822631, 7.079789, 7.140982, 7.734910, 17.448094], [132.013880, 140.820673, 142.960464, 162.028339, 612.239554]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.999497, 0.999149, 0.998306, 0.999419, 0.000000], [0.000000, 0.000000, 0.000000, 0.999229, 0.999443, 0.998559, 0.999132, 0.000000], [0.000000, 0.000000, 0.000000, -0.981389, -0.990795, -0.986402, -0.979134, 0.000000], [0.000000, 0.000000, 0.000000, 0.999358, 0.998993, 0.998567, 0.999547, 0.000000], [0.000000, 0.000000, 0.000000, -0.998722, -0.998964, -0.993848, -0.995900, 0.000000], [0.000000, 0.000000, 0.000000, 0.937986, 0.938921, 0.960916, 0.952578, 0.000000], [0.000000, 0.000000, 0.000000, 0.999046, 0.999720, 0.998407, 0.998673, 0.000000]]
pre_activation_mean: [11.876305, 8.808787, -0.945121, 8.068151, -1.682108, 0.193868, 6.802662]
pre_activation_std: [14.886733, 11.109057, 0.923918, 10.198069, 1.802789, 0.438439, 8.724652]
### 8
mean: [-7.302178, -3.412899, -6.297867, -4.574237, 1.366967, 21.938623, 19.612925]
std: [8.954237, 4.074473, 7.199622, 6.615674, 0.485047, 27.605438, 24.766003]
fourier: [[135.677669, 144.820673, 146.235901, 165.613505, 657.196100], [60.982502, 65.979725, 66.912182, 75.468276, 307.160954], [108.528160, 116.385327, 117.770094, 133.543561, 566.807989], [100.168441, 107.036215, 108.230176, 122.195999, 411.681367], [7.665174, 7.677258, 7.726046, 9.001638, 123.026988], [417.932304, 446.704666, 451.405247, 510.022588, 1974.476142], [374.816967, 400.815774, 405.017354, 457.486082, 1765.163166]]
input_correlations: [[-0.999985, -0.999982, 0.078364, -0.999957, 0.000000, -0.937976, -0.999887, 0.000000], [-0.999785, -0.999936, 0.079350, -0.999791, 0.000000, -0.940412, -0.999968, 0.000000], [-0.999906, -0.999983, 0.081120, -0.999871, 0.000000, -0.937731, -0.999977, 0.000000], [-0.999982, -0.999992, 0.076983, -0.999966, 0.000000, -0.938771, -0.999888, 0.000000], [0.995967, 0.995278, -0.090049, 0.995608, 0.000000, 0.910520, 0.994838, 0.000000], [0.999983, 0.999991, -0.077210, 0.999967, 0.000000, 0.938805, 0.999890, 0.000000], [0.999982, 0.999991, -0.077013, 0.999970, 0.000000, 0.938988, 0.999889, 0.000000]]
pre_activation_mean: [-7.302178, -3.412899, -6.297867, -4.574237, 1.366967, 21.938623, 19.612925]
pre_activation_std: [8.954237, 4.074473, 7.199622, 6.615674, 0.485047, 27.605438, 24.766003]
### 10
mean: [-24.479044]
std: [33.004055]
fourier: [[502.070673, 533.749285, 539.729958, 609.185316, 2203.114029]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.621373, -0.995547, -0.999976, -0.999967, 0.000000]]
pre_activation_mean: [-24.479044]
pre_activation_std: [33.004055]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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0.546266, 0.634598]], "network.2.bias": [-0.309349, 0.100863, -0.393062, 0.527925, 0.085706, -0.240129, 0.299562], "network.4.weight": [[0.328046, -0.15719, -0.262855, -0.111127, -0.001436, -0.318161, -0.033746], [0.233633, 0.035032, -0.318972, -0.246343, -0.140678, 0.040189, -0.228347], [0.064369, -0.088286, -0.094829, 0.011483, 0.335558, -0.478813, -0.490248], [0.359667, 0.483828, 0.891752, -0.525039, -0.274502, 0.682058, 0.427774], [-0.039679, 0.875243, 0.578432, -0.708778, -0.035652, 0.782825, 0.526113], [-0.135745, 0.689077, 0.572794, 0.00648, -0.26148, 0.182362, 0.250092], [0.190578, 0.589721, 0.904007, -0.077592, 0.158642, 0.472212, 0.297888]], "network.4.bias": [-0.215087, -0.296505, -0.35336, -0.227725, -0.049293, -0.103193, -0.310158], "network.6.weight": [[0.068177, -0.092241, 0.078515, 0.787955, 0.724391, 0.507649, 0.897229], [-0.125576, 0.261646, 0.07473, 0.438095, 0.743096, 0.565405, 0.457763], [-0.321395, 0.121716, -0.045765, 0.103914, -0.385206, -0.20997, 0.318814], [-0.02531, -0.118755, -0.057274, 0.517562, 0.368558, 0.56672, 0.640123], [0.125597, -0.341849, 0.152184, -0.27604, -0.248682, 0.14675, 0.145953], [0.080782, -0.048664, 0.20625, -0.220952, -0.152672, 0.389273, 0.245009], [-0.32605, 0.253768, -0.216318, 0.533654, 0.65882, 0.654417, -0.098685]], "network.6.bias": [-0.183231, -0.191479, -0.223922, -0.225002, -0.274814, -0.210698, -0.251341], "network.8.weight": [[-0.507469, 0.183668, 0.301883, -0.020681, -0.028309, 0.04051, -0.375888], [0.092922, -0.234696, -0.114121, -0.00258, 0.107395, -0.191765, -0.318585], [-0.155686, -0.026831, 0.085582, 0.003538, -0.086285, 0.047974, -0.535885], [0.104939, -0.435864, -0.22068, -0.365457, -0.05236, 0.182052, 0.033751], [-0.112916, -0.181203, 0.101936, 0.442836, 0.074569, -0.431799, -0.019985], [0.672474, 0.902296, -0.21441, 0.434787, 0.095397, -0.070217, 0.375025], [0.678845, 0.557103, -0.153627, 0.420006, -0.303604, 0.071187, 0.488711]], "network.8.bias": [-0.136069, -0.179627, -0.561029, 0.728268, 0.96994, -0.17219, -0.213793], "network.10.weight": [[-0.067133, 0.369355, -0.094629, 0.945937, 0.925084, -0.586958, -0.690998]], "network.10.bias": [0.5178]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.7007418274879456, "train_acc": 0.45, "val_loss": 0.6826973557472229, "val_acc": 0.74}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6715236902236938, "train_acc": 0.7, "val_loss": 0.6183831095695496, "val_acc": 0.7}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.5824252963066101, "train_acc": 0.69, "val_loss": 0.46746543049812317, "val_acc": 0.78}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.4129755049943924, "train_acc": 0.875, "val_loss": 0.39687711000442505, "val_acc": 0.84}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.33290189504623413, "train_acc": 0.895, "val_loss": 0.4490100145339966, "val_acc": 0.76}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.31527042388916016, "train_acc": 0.895, "val_loss": 0.42601123452186584, "val_acc": 0.78}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.26239482313394547, "train_acc": 0.9, "val_loss": 0.35503950715065, "val_acc": 0.84}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.265697717666626, "train_acc": 0.91, "val_loss": 0.33663272857666016, "val_acc": 0.86}, {"stage": "improved", "epoch": 6, "global_epoch": 8, "train_loss": 0.24844370037317276, "train_acc": 0.915, "val_loss": 0.32318437099456787, "val_acc": 0.88}, {"stage": "improved", "epoch": 7, "global_epoch": 9, "train_loss": 0.2167007401585579, "train_acc": 0.93, "val_loss": 0.3317687213420868, "val_acc": 0.88}, {"stage": "improved", "epoch": 8, "global_epoch": 10, "train_loss": 0.21003428101539612, "train_acc": 0.935, "val_loss": 0.3409614861011505, "val_acc": 0.88}, {"stage": "improved", "epoch": 9, "global_epoch": 11, "train_loss": 0.20413748174905777, "train_acc": 0.935, "val_loss": 0.3547402322292328, "val_acc": 0.88}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6826973557472229, "final_val_loss": 0.6183831095695496, "initial_val_acc": 0.74, "final_val_acc": 0.7, "best_val_acc": 0.7}, "improved_stage": {"initial_val_loss": 0.46746543049812317, "final_val_loss": 0.3547402322292328, "initial_val_acc": 0.78, "final_val_acc": 0.88, "best_val_acc": 0.88, "best_epoch": 8}, "improvement": 0.18000000000000005, "first_improvement_epoch": 1}} |
86 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.58, "improved_accuracy": 0.74, "improvement": 0.16000000000000003, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 6, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1469, "learning_rate": 0.05734450156595675, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
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0.297711,
0.131951,
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0.379916,
-0.300093
],
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0.30954,
0.613293
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[
-0.230472,
0.175219,
-0.255352,
-0.050143,
-0.572663
],
[
0.224195,
-0.529009,
0.481692,
-0.399299,
0.22836
],
[
-0.407907,
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0.040873
],
[
-0.394333,
0.032625,
-0.116847,
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0.530314
]
],
"network.0.bias": [
0.193655,
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0.05474,
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0.058312,
0.192009
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"network.2.weight": [
[
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0.146343,
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0.082818
],
[
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0.467569,
0.427363,
0.182312,
0.271098,
0.334571
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[
0.169129,
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0.087664,
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[
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0.199198,
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[
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0.185419,
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0.342028,
-0.192075
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[
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0.074265,
0.10038,
0.558228
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],
"network.2.bias": [
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"network.4.weight": [
[
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[
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[
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[
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[
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[
0.088434,
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],
"network.4.bias": [
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"network.6.weight": [
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[
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[
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[
0.259641,
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],
"network.6.bias": [
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"network.8.weight": [
[
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[
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[
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[
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[
0.174052,
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],
"network.8.bias": [
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"network.10.weight": [
[
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"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [-0.138241, -0.025231, -0.093440, 0.363464, 0.292854, 0.011152]
std: [0.045418, 0.041055, 0.012966, 1.228306, 0.678919, 0.043784]
fourier: [[0.714806, 0.781633, 0.824584, 0.965601, 12.441729], [0.636730, 0.707830, 0.813225, 0.898850, 2.270747], [0.193129, 0.194296, 0.217867, 0.272231, 8.409557], [18.155270, 18.815577, 20.674924, 25.199011, 32.711786], [10.011771, 10.510118, 11.474473, 13.879194, 26.356827], [0.650578, 0.691487, 0.733876, 0.940788, 1.003724]]
input_correlations: [[0.331457, 0.505046, -0.302048, 0.640612, -0.364538, 0.000000, 0.000000, 0.000000], [-0.670901, -0.395489, -0.311115, 0.372796, 0.496844, 0.000000, 0.000000, 0.000000], [-0.487121, 0.017550, -0.554194, -0.096665, -0.875330, 0.000000, 0.000000, 0.000000], [0.304506, -0.502316, 0.530398, -0.620483, 0.325660, 0.000000, 0.000000, 0.000000], [-0.629725, -0.194619, 0.463483, -0.278679, 0.018509, 0.000000, 0.000000, 0.000000], [-0.580203, -0.215373, -0.220090, 0.187229, 0.675611, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.720349, -0.327645, -1.259998, 0.202543, 0.027989, 0.187190]
pre_activation_std: [1.182235, 1.892692, 1.442848, 1.780464, 0.906418, 1.165002]
### 2
mean: [-0.732439, 0.131579, -0.746708, -1.240365, 0.368116, 0.010684]
std: [0.463241, 0.890603, 0.978450, 0.867982, 0.221694, 1.105856]
fourier: [[7.082690, 7.312656, 8.890898, 9.574428, 65.919480], [13.335679, 13.432130, 13.591360, 14.867732, 16.805471], [14.197236, 15.594302, 16.049172, 19.046048, 67.203686], [11.983070, 14.682199, 14.717709, 17.051964, 111.632842], [3.132726, 3.808766, 4.056632, 4.164380, 33.130443], [17.132524, 17.264305, 17.817195, 18.688325, 23.742930]]
input_correlations: [[-0.854369, -0.295996, -0.204180, 0.717161, 0.420657, -0.092575, 0.000000, 0.000000], [-0.573431, 0.816114, -0.003578, 0.300797, 0.311255, 0.883510, 0.000000, 0.000000], [0.573517, -0.604497, 0.009240, -0.652130, -0.284824, -0.683478, 0.000000, 0.000000], [0.162569, -0.747100, -0.020124, -0.446531, -0.156823, -0.763418, 0.000000, 0.000000], [0.012428, -0.596659, -0.070536, -0.097858, 0.621346, -0.618687, 0.000000, 0.000000], [-0.403924, 0.936154, 0.035634, 0.042847, 0.082277, 0.970446, 0.000000, 0.000000]]
pre_activation_mean: [-0.732439, 0.131579, -0.746708, -1.240365, 0.368116, 0.010684]
pre_activation_std: [0.463241, 0.890603, 0.978450, 0.867982, 0.221694, 1.105856]
### 4
mean: [0.275930, -0.098913, -0.245138, -0.019724, -0.260178, 0.262705]
std: [0.321932, 0.534104, 0.210645, 0.142644, 0.791213, 0.961765]
fourier: [[5.005083, 5.145788, 5.518243, 5.672987, 24.833669], [7.688361, 8.569784, 8.902132, 9.382537, 11.128440], [3.182708, 3.618442, 3.993280, 4.030189, 22.062387], [2.296535, 2.298790, 2.497259, 2.718335, 3.433518], [12.226668, 12.690112, 13.028966, 16.173128, 23.416004], [14.581215, 15.869708, 15.915884, 19.417092, 23.643491]]
input_correlations: [[-0.206218, -0.990532, -0.048890, -0.840894, 0.503220, -0.948434, 0.000000, 0.000000], [-0.059932, 0.947552, 0.109117, 0.704540, -0.590098, 0.995791, 0.000000, 0.000000], [-0.038422, 0.814692, 0.128382, 0.605994, -0.779998, 0.923322, 0.000000, 0.000000], [0.356408, -0.839383, -0.115534, -0.498257, 0.061464, -0.869738, 0.000000, 0.000000], [0.028716, 0.978345, 0.152019, 0.773452, -0.529235, 0.993093, 0.000000, 0.000000], [0.018582, 0.973018, 0.116839, 0.755019, -0.559713, 0.995423, 0.000000, 0.000000]]
pre_activation_mean: [0.275930, -0.098913, -0.245138, -0.019724, -0.260178, 0.262705]
pre_activation_std: [0.321932, 0.534104, 0.210645, 0.142644, 0.791213, 0.961765]
### 6
mean: [0.457077, -0.135983, -0.201479, -0.123895, 0.262484, 0.497241]
std: [1.083751, 0.833197, 0.157170, 0.150173, 0.570100, 0.397347]
fourier: [[15.964191, 17.053975, 18.248021, 22.168556, 41.136904], [12.238492, 12.334308, 13.408592, 13.979902, 16.802356], [2.272347, 2.476642, 2.836390, 3.494164, 18.133072], [2.216985, 2.405477, 2.653282, 2.850129, 11.150536], [8.580414, 9.120907, 9.471688, 11.693078, 23.623543], [5.884293, 6.563624, 6.750135, 7.681948, 44.751693]]
input_correlations: [[-0.810975, 0.997691, 0.977149, -0.726248, 0.998046, 0.998570, 0.000000, 0.000000], [-0.832207, 0.994818, 0.976060, -0.713027, 0.994845, 0.999589, 0.000000, 0.000000], [0.823404, -0.972183, -0.951383, 0.796277, -0.967431, -0.983674, 0.000000, 0.000000], [0.868079, -0.979480, -0.968755, 0.649687, -0.980393, -0.993519, 0.000000, 0.000000], [-0.827048, 0.995055, 0.972508, -0.728175, 0.996011, 0.999503, 0.000000, 0.000000], [0.853017, -0.987405, -0.975586, 0.669916, -0.987151, -0.997039, 0.000000, 0.000000]]
pre_activation_mean: [0.457077, -0.135983, -0.201479, -0.123895, 0.262484, 0.497241]
pre_activation_std: [1.083751, 0.833197, 0.157170, 0.150173, 0.570100, 0.397347]
### 8
mean: [-1.305892, -0.109737, -0.230995, 0.330393, 0.352598, 0.007489]
std: [0.813847, 0.281087, 0.051244, 1.246771, 0.674469, 0.139334]
fourier: [[11.966055, 12.370055, 13.745945, 16.794522, 117.530315], [4.005718, 4.042264, 4.795353, 5.770012, 9.876370], [0.725552, 0.760292, 0.857364, 1.043356, 20.789536], [18.379780, 19.424468, 20.973778, 25.473376, 29.735346], [10.005293, 10.650756, 11.361065, 13.756085, 31.733844], [1.898530, 1.953467, 2.007405, 2.319011, 2.787870]]
input_correlations: [[-0.999522, -0.998812, 0.892535, 0.915993, -0.999668, 0.893404, 0.000000, 0.000000], [-0.995345, -0.999039, 0.868436, 0.888176, -0.996023, 0.862174, 0.000000, 0.000000], [-0.989272, -0.996528, 0.843944, 0.871686, -0.991503, 0.841644, 0.000000, 0.000000], [0.999896, 0.998228, -0.895059, -0.925069, 0.999920, -0.903141, 0.000000, 0.000000], [0.999880, 0.996943, -0.901089, -0.932288, 0.999618, -0.911568, 0.000000, 0.000000], [-0.977422, -0.989450, 0.808442, 0.835024, -0.980189, 0.801119, 0.000000, 0.000000]]
pre_activation_mean: [-1.305892, -0.109737, -0.230995, 0.330393, 0.352598, 0.007489]
pre_activation_std: [0.813847, 0.281087, 0.051244, 1.246771, 0.674469, 0.139334]
### 10
mean: [-0.214692]
std: [0.985655]
fourier: [[14.520269, 15.099545, 16.608248, 19.322270, 20.187167]]
input_correlations: [[-0.928497, 0.872523, 0.997952, -0.999991, -0.999877, 0.992193, 0.000000, 0.000000]]
pre_activation_mean: [-0.214692]
pre_activation_std: [0.985655]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 6
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
0.297711,
0.131951,
-0.253163,
0.379916,
-0.300093
],
[
-0.574376,
-0.267382,
-0.185783,
0.30954,
0.613293
],
[
-0.230472,
0.175219,
-0.255352,
-0.050143,
-0.572663
],
[
0.224195,
-0.529009,
0.481692,
-0.399299,
0.22836
],
[
-0.407907,
0.033564,
0.337474,
-0.158186,
0.040873
],
[
-0.394333,
0.032625,
-0.116847,
0.007686,
0.530314
]
],
"network.0.bias": [
0.193655,
-0.157742,
0.05474,
0.455946,
0.058312,
0.192009
],
"network.2.weight": [
[
-0.384309,
-0.209459,
-0.217269,
0.146343,
-0.154824,
0.082818
],
[
-0.222549,
0.467569,
0.427363,
0.182312,
0.271098,
0.334571
],
[
0.169129,
-0.454632,
-0.334333,
-0.581023,
0.087664,
-0.265071
],
[
-0.37213,
-0.374567,
0.199198,
-0.511238,
-0.114984,
-0.530564
],
[
-0.013206,
0.013685,
0.185419,
-0.103474,
0.342028,
-0.192075
],
[
-0.189647,
0.565956,
0.382004,
0.074265,
0.10038,
0.558228
]
],
"network.2.bias": [
-0.42225,
-0.181972,
-0.255418,
-0.202522,
0.438724,
-0.352949
],
"network.4.weight": [
[
-0.55178,
-0.302985,
0.207001,
-0.054584,
0.040223,
-0.087167
],
[
-0.482835,
0.161789,
0.225748,
-0.081038,
-0.500503,
0.380599
],
[
0.056458,
-0.176094,
0.133172,
-0.009007,
-0.427586,
0.293338
],
[
0.068026,
0.053105,
0.01322,
0.26486,
-0.480944,
-0.220937
],
[
-0.021264,
0.324021,
0.535429,
0.633698,
-0.246801,
0.513917
],
[
0.088434,
0.373353,
0.301399,
-0.028434,
-0.49142,
0.661915
]
],
"network.4.bias": [
0.305645,
-0.162938,
-0.148522,
0.183815,
-0.302803,
0.152392
],
"network.6.weight": [
[
-0.162595,
0.386299,
0.206216,
-0.157685,
0.631239,
0.48913
],
[
-0.394549,
0.562629,
0.172609,
0.146747,
0.142167,
0.461637
],
[
-0.074675,
-0.163454,
-0.207967,
0.613525,
0.408603,
-0.330996
],
[
0.099138,
0.306893,
-0.359058,
-0.223152,
-0.130759,
-0.174077
],
[
-0.117164,
-0.064379,
-0.032412,
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0.329643,
0.397124
],
[
0.259641,
0.038976,
-0.514324,
-0.487386,
-0.060468,
-0.3328
]
],
"network.6.bias": [
0.307597,
-0.208766,
-0.121676,
-0.126399,
0.147757,
0.502071
],
"network.8.weight": [
[
-0.541893,
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0.498581,
0.65703,
-0.415954,
-0.427003
],
[
-0.286664,
-0.205413,
0.194242,
0.350788,
0.260356,
-0.317866
],
[
0.125784,
-0.086975,
0.147591,
0.13987,
-0.222826,
-0.05983
],
[
0.630858,
0.302266,
0.273967,
0.079074,
0.582919,
-0.129006
],
[
0.433985,
0.23073,
0.015092,
-0.277139,
-0.014392,
-0.179541
],
[
0.174052,
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0.054551,
0.352969,
-0.329352,
-0.261183
]
],
"network.8.bias": [
-0.745089,
0.129543,
-0.183572,
-0.015391,
0.212212,
0.15615
],
"network.10.weight": [
[
0.308843,
0.038895,
-0.149263,
-0.625713,
-0.333398,
0.099797
]
],
"network.10.bias": [
0.138985
]
}
## Activation Signature
### 0
mean: [-0.138241, -0.025231, -0.093440, 0.363464, 0.292854, 0.011152]
std: [0.045418, 0.041055, 0.012966, 1.228306, 0.678919, 0.043784]
fourier: [[0.714806, 0.781633, 0.824584, 0.965601, 12.441729], [0.636730, 0.707830, 0.813225, 0.898850, 2.270747], [0.193129, 0.194296, 0.217867, 0.272231, 8.409557], [18.155270, 18.815577, 20.674924, 25.199011, 32.711786], [10.011771, 10.510118, 11.474473, 13.879194, 26.356827], [0.650578, 0.691487, 0.733876, 0.940788, 1.003724]]
input_correlations: [[0.331457, 0.505046, -0.302048, 0.640612, -0.364538, 0.000000, 0.000000, 0.000000], [-0.670901, -0.395489, -0.311115, 0.372796, 0.496844, 0.000000, 0.000000, 0.000000], [-0.487121, 0.017550, -0.554194, -0.096665, -0.875330, 0.000000, 0.000000, 0.000000], [0.304506, -0.502316, 0.530398, -0.620483, 0.325660, 0.000000, 0.000000, 0.000000], [-0.629725, -0.194619, 0.463483, -0.278679, 0.018509, 0.000000, 0.000000, 0.000000], [-0.580203, -0.215373, -0.220090, 0.187229, 0.675611, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.720349, -0.327645, -1.259998, 0.202543, 0.027989, 0.187190]
pre_activation_std: [1.182235, 1.892692, 1.442848, 1.780464, 0.906418, 1.165002]
### 2
mean: [-0.732439, 0.131579, -0.746708, -1.240365, 0.368116, 0.010684]
std: [0.463241, 0.890603, 0.978450, 0.867982, 0.221694, 1.105856]
fourier: [[7.082690, 7.312656, 8.890898, 9.574428, 65.919480], [13.335679, 13.432130, 13.591360, 14.867732, 16.805471], [14.197236, 15.594302, 16.049172, 19.046048, 67.203686], [11.983070, 14.682199, 14.717709, 17.051964, 111.632842], [3.132726, 3.808766, 4.056632, 4.164380, 33.130443], [17.132524, 17.264305, 17.817195, 18.688325, 23.742930]]
input_correlations: [[-0.854369, -0.295996, -0.204180, 0.717161, 0.420657, -0.092575, 0.000000, 0.000000], [-0.573431, 0.816114, -0.003578, 0.300797, 0.311255, 0.883510, 0.000000, 0.000000], [0.573517, -0.604497, 0.009240, -0.652130, -0.284824, -0.683478, 0.000000, 0.000000], [0.162569, -0.747100, -0.020124, -0.446531, -0.156823, -0.763418, 0.000000, 0.000000], [0.012428, -0.596659, -0.070536, -0.097858, 0.621346, -0.618687, 0.000000, 0.000000], [-0.403924, 0.936154, 0.035634, 0.042847, 0.082277, 0.970446, 0.000000, 0.000000]]
pre_activation_mean: [-0.732439, 0.131579, -0.746708, -1.240365, 0.368116, 0.010684]
pre_activation_std: [0.463241, 0.890603, 0.978450, 0.867982, 0.221694, 1.105856]
### 4
mean: [0.275930, -0.098913, -0.245138, -0.019724, -0.260178, 0.262705]
std: [0.321932, 0.534104, 0.210645, 0.142644, 0.791213, 0.961765]
fourier: [[5.005083, 5.145788, 5.518243, 5.672987, 24.833669], [7.688361, 8.569784, 8.902132, 9.382537, 11.128440], [3.182708, 3.618442, 3.993280, 4.030189, 22.062387], [2.296535, 2.298790, 2.497259, 2.718335, 3.433518], [12.226668, 12.690112, 13.028966, 16.173128, 23.416004], [14.581215, 15.869708, 15.915884, 19.417092, 23.643491]]
input_correlations: [[-0.206218, -0.990532, -0.048890, -0.840894, 0.503220, -0.948434, 0.000000, 0.000000], [-0.059932, 0.947552, 0.109117, 0.704540, -0.590098, 0.995791, 0.000000, 0.000000], [-0.038422, 0.814692, 0.128382, 0.605994, -0.779998, 0.923322, 0.000000, 0.000000], [0.356408, -0.839383, -0.115534, -0.498257, 0.061464, -0.869738, 0.000000, 0.000000], [0.028716, 0.978345, 0.152019, 0.773452, -0.529235, 0.993093, 0.000000, 0.000000], [0.018582, 0.973018, 0.116839, 0.755019, -0.559713, 0.995423, 0.000000, 0.000000]]
pre_activation_mean: [0.275930, -0.098913, -0.245138, -0.019724, -0.260178, 0.262705]
pre_activation_std: [0.321932, 0.534104, 0.210645, 0.142644, 0.791213, 0.961765]
### 6
mean: [0.457077, -0.135983, -0.201479, -0.123895, 0.262484, 0.497241]
std: [1.083751, 0.833197, 0.157170, 0.150173, 0.570100, 0.397347]
fourier: [[15.964191, 17.053975, 18.248021, 22.168556, 41.136904], [12.238492, 12.334308, 13.408592, 13.979902, 16.802356], [2.272347, 2.476642, 2.836390, 3.494164, 18.133072], [2.216985, 2.405477, 2.653282, 2.850129, 11.150536], [8.580414, 9.120907, 9.471688, 11.693078, 23.623543], [5.884293, 6.563624, 6.750135, 7.681948, 44.751693]]
input_correlations: [[-0.810975, 0.997691, 0.977149, -0.726248, 0.998046, 0.998570, 0.000000, 0.000000], [-0.832207, 0.994818, 0.976060, -0.713027, 0.994845, 0.999589, 0.000000, 0.000000], [0.823404, -0.972183, -0.951383, 0.796277, -0.967431, -0.983674, 0.000000, 0.000000], [0.868079, -0.979480, -0.968755, 0.649687, -0.980393, -0.993519, 0.000000, 0.000000], [-0.827048, 0.995055, 0.972508, -0.728175, 0.996011, 0.999503, 0.000000, 0.000000], [0.853017, -0.987405, -0.975586, 0.669916, -0.987151, -0.997039, 0.000000, 0.000000]]
pre_activation_mean: [0.457077, -0.135983, -0.201479, -0.123895, 0.262484, 0.497241]
pre_activation_std: [1.083751, 0.833197, 0.157170, 0.150173, 0.570100, 0.397347]
### 8
mean: [-1.305892, -0.109737, -0.230995, 0.330393, 0.352598, 0.007489]
std: [0.813847, 0.281087, 0.051244, 1.246771, 0.674469, 0.139334]
fourier: [[11.966055, 12.370055, 13.745945, 16.794522, 117.530315], [4.005718, 4.042264, 4.795353, 5.770012, 9.876370], [0.725552, 0.760292, 0.857364, 1.043356, 20.789536], [18.379780, 19.424468, 20.973778, 25.473376, 29.735346], [10.005293, 10.650756, 11.361065, 13.756085, 31.733844], [1.898530, 1.953467, 2.007405, 2.319011, 2.787870]]
input_correlations: [[-0.999522, -0.998812, 0.892535, 0.915993, -0.999668, 0.893404, 0.000000, 0.000000], [-0.995345, -0.999039, 0.868436, 0.888176, -0.996023, 0.862174, 0.000000, 0.000000], [-0.989272, -0.996528, 0.843944, 0.871686, -0.991503, 0.841644, 0.000000, 0.000000], [0.999896, 0.998228, -0.895059, -0.925069, 0.999920, -0.903141, 0.000000, 0.000000], [0.999880, 0.996943, -0.901089, -0.932288, 0.999618, -0.911568, 0.000000, 0.000000], [-0.977422, -0.989450, 0.808442, 0.835024, -0.980189, 0.801119, 0.000000, 0.000000]]
pre_activation_mean: [-1.305892, -0.109737, -0.230995, 0.330393, 0.352598, 0.007489]
pre_activation_std: [0.813847, 0.281087, 0.051244, 1.246771, 0.674469, 0.139334]
### 10
mean: [-0.214692]
std: [0.985655]
fourier: [[14.520269, 15.099545, 16.608248, 19.322270, 20.187167]]
input_correlations: [[-0.928497, 0.872523, 0.997952, -0.999991, -0.999877, 0.992193, 0.000000, 0.000000]]
pre_activation_mean: [-0.214692]
pre_activation_std: [0.985655]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.13824142515659332, "std": 0.04541775956749916, "fourier": [0.7148056719884163, 0.7816332769850031, 0.8245837050530863, 0.9656011927867673, 12.441729160979321], "input_correlations": [0.33145745058418435, 0.5050455903908951, -0.3020476947535002, 0.6406120845158165, -0.36453816714343495, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7203487157821655, "pre_activation_std": 1.1822352409362793}, "1": {"mean": -0.025230521336197853, "std": 0.04105492681264877, "fourier": [0.6367299043535445, 0.7078299504295646, 0.8132249604933297, 0.8988504257570329, 2.2707470760215074], "input_correlations": [-0.6709013080565716, -0.39548869771322337, -0.31111470904460437, 0.372795562605908, 0.4968437394490554, 0.0, 0.0, 0.0], "pre_activation_mean": -0.3276447653770447, "pre_activation_std": 1.892691731452942}, "2": {"mean": -0.09343952685594559, "std": 0.012966368347406387, "fourier": [0.1931292801221397, 0.19429621170946804, 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0.74}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.5061241686344147, "train_acc": 0.735, "val_loss": 0.5192524790763855, "val_acc": 0.7}, {"stage": "improved", "epoch": 4, "global_epoch": 6, "train_loss": 0.5581419169902802, "train_acc": 0.69, "val_loss": 0.5345355272293091, "val_acc": 0.68}, {"stage": "improved", "epoch": 5, "global_epoch": 7, "train_loss": 0.5586560964584351, "train_acc": 0.685, "val_loss": 0.5265472531318665, "val_acc": 0.68}], "summary": {"total_epochs": 8, "degraded_epochs": 2, "improved_epochs": 6, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.6465933322906494, "final_val_loss": 0.5954721570014954, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.5054776072502136, "final_val_loss": 0.5265472531318665, "initial_val_acc": 0.74, "final_val_acc": 0.68, "best_val_acc": 0.74, "best_epoch": 2}, "improvement": 0.16000000000000003, "first_improvement_epoch": 1}} |
87 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.6, "improved_accuracy": 0.88, "improvement": 0.28, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 9217, "learning_rate": 0.03413339280459434, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.901364, 0.000000, 1.715552, 0.795870, 1.066136, 0.140793, 0.031362, 1.642772]
std: [0.610914, 0.000000, 1.029912, 0.478247, 0.783061, 0.191378, 0.083144, 1.115111]
fourier: [[9.246494, 9.307798, 9.819592, 13.929018, 81.122800], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [14.888583, 15.609184, 16.421710, 21.686693, 154.399716], [6.823355, 7.336319, 7.845930, 9.496164, 71.628300], [11.925037, 12.204581, 12.579858, 17.303266, 95.952244], [2.693547, 2.964290, 3.601998, 3.641160, 12.671335], [1.239692, 1.294327, 1.300765, 1.351533, 2.822575], [16.167338, 16.940523, 17.934166, 23.964566, 147.849523]]
input_correlations: [[-0.408805, -0.495605, 0.443295, 0.330377, 0.105208, 0.000000, 0.000000, 0.000000], [-0.346944, 0.692364, -0.096660, 0.333253, -0.484899, 0.000000, 0.000000, 0.000000], [0.469022, 0.782516, 0.645011, -0.041264, 0.315174, 0.000000, 0.000000, 0.000000], [0.689696, 0.026899, -0.363353, -0.064935, -0.297678, 0.000000, 0.000000, 0.000000], [-0.718292, -0.780288, -0.613880, -0.259222, -0.339230, 0.000000, 0.000000, 0.000000], [-0.443728, -0.954990, -0.294848, -0.215355, -0.250489, 0.000000, 0.000000, 0.000000], [0.124702, 0.136731, -0.612237, -0.228274, -0.756111, 0.000000, 0.000000, 0.000000], [0.420176, 0.093202, 0.626520, -0.612006, -0.339958, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.762743, -0.114966, 1.914970, 0.241482, -1.855580, -1.206399, -1.751104, -0.309261]
pre_activation_std: [1.166196, 0.803715, 1.254621, 0.502709, 1.152096, 0.675709, 1.482423, 1.315891]
### 2
mean: [0.164111, 0.784936, 1.190345, 0.043759, 0.213233, 0.351589, 0.265200, 1.263225]
std: [0.233180, 0.525699, 0.787115, 0.621747, 0.477127, 0.278616, 0.550669, 0.906355]
fourier: [[3.634243, 3.660180, 3.921989, 4.623299, 14.769962], [7.453909, 9.475772, 9.624432, 11.637784, 70.644287], [12.432281, 12.642989, 12.907267, 13.997959, 107.131089], [8.033761, 8.273133, 10.740276, 10.896564, 13.924430], [7.093692, 7.557484, 9.089511, 9.133484, 19.190955], [4.141580, 4.224703, 4.312021, 4.548827, 31.643027], [7.425544, 8.118291, 10.260173, 11.879536, 23.867986], [13.062301, 13.378721, 13.707082, 17.152747, 113.690242]]
input_correlations: [[-0.421407, -0.474213, -0.742838, 0.492242, 0.000000, 0.000000, 0.164538, -0.370934], [-0.763890, 0.595859, 0.697024, 0.335047, 0.000000, 0.000000, 0.230908, 0.137169], [-0.434832, 0.606715, 0.920915, 0.074115, 0.000000, 0.000000, 0.117332, 0.465419], [0.931116, -0.296968, -0.357385, -0.622918, 0.000000, 0.000000, -0.411784, -0.061125], [0.857690, -0.076362, -0.313189, -0.607854, 0.000000, 0.000000, -0.360907, -0.335267], [-0.728959, 0.096808, 0.623055, 0.590026, 0.000000, 0.000000, 0.426100, 0.464386], [0.944220, -0.214876, -0.347324, -0.636325, 0.000000, 0.000000, -0.361635, -0.066975], [-0.708768, 0.373309, 0.796787, 0.389118, 0.000000, 0.000000, 0.280094, 0.357491]]
pre_activation_mean: [0.164111, 0.784936, 1.190345, 0.043759, 0.213233, 0.351589, 0.265200, 1.263225]
pre_activation_std: [0.233180, 0.525699, 0.787115, 0.621747, 0.477127, 0.278616, 0.550669, 0.906355]
### 4
mean: [0.301045, 1.204758, -0.474867, 0.335348, -1.208262, -0.581459, 1.765502, -0.920907]
std: [0.288357, 0.844411, 0.202924, 0.362112, 0.532359, 0.132050, 1.171376, 0.323909]
fourier: [[4.616900, 4.713611, 5.289920, 6.551218, 27.094011], [11.643074, 12.361578, 13.335893, 17.804080, 108.428211], [2.984099, 3.170094, 3.342596, 4.190745, 42.738047], [5.409590, 5.562274, 5.875518, 7.075367, 30.181353], [7.470626, 8.069893, 8.210214, 10.783686, 108.743571], [2.020733, 2.404812, 2.421943, 2.771401, 52.331295], [16.911918, 17.466223, 17.484443, 24.914807, 158.895207], [5.117968, 5.168674, 5.423356, 5.792705, 82.881660]]
input_correlations: [[-0.330200, -0.701038, -0.464905, 0.956281, 0.969078, -0.640287, 0.956334, -0.649631], [-0.095314, 0.967356, 0.850098, -0.799560, -0.760080, 0.902582, -0.845423, 0.975434], [0.506174, 0.526004, 0.292192, -0.886246, -0.957335, 0.715709, -0.898032, 0.587219], [-0.060240, 0.938553, 0.798812, -0.788664, -0.733913, 0.931191, -0.838813, 0.973977], [0.157108, -0.959267, -0.883571, 0.746423, 0.743519, -0.920815, 0.798391, -0.987890], [-0.026844, -0.939528, -0.706117, 0.813211, 0.615210, -0.715626, 0.836293, -0.845298], [-0.070731, 0.956647, 0.840115, -0.806046, -0.792165, 0.915010, -0.852854, 0.971060], [0.578028, -0.887108, -0.988063, 0.372483, 0.371680, -0.699839, 0.430502, -0.883458]]
pre_activation_mean: [0.301045, 1.204758, -0.474867, 0.335348, -1.208262, -0.581459, 1.765502, -0.920907]
pre_activation_std: [0.288357, 0.844411, 0.202924, 0.362112, 0.532359, 0.132050, 1.171376, 0.323909]
### 6
mean: [0.867511, -0.235211, 1.715552, 0.795870, 1.026714, 0.082329, -0.570970, 1.623626]
std: [0.667664, 0.135647, 1.029912, 0.478247, 0.843661, 0.251195, 0.510296, 1.144734]
fourier: [[9.786327, 10.017290, 10.527434, 14.933090, 78.075971], [1.971516, 2.190757, 2.247365, 3.161332, 21.169028], [14.888583, 15.609184, 16.421710, 21.686693, 154.399716], [6.823355, 7.336319, 7.845930, 9.496164, 71.628300], [12.443254, 12.698662, 12.708934, 18.503833, 92.404284], [3.703213, 3.878611, 4.222597, 5.663394, 7.409609], [7.493179, 7.654964, 7.945173, 11.037879, 51.387288], [16.408575, 17.282396, 17.993234, 24.472132, 146.126373]]
input_correlations: [[-0.860948, 0.981353, 0.000000, 0.931927, 0.000000, 0.000000, 0.987261, 0.000000], [-0.942392, 0.917797, 0.000000, 0.866335, 0.000000, 0.000000, 0.928266, 0.000000], [-0.761077, 0.999138, 0.000000, 0.977456, 0.000000, 0.000000, 0.999275, 0.000000], [-0.687067, 0.994424, 0.000000, 0.985578, 0.000000, 0.000000, 0.992031, 0.000000], [-0.821406, 0.992017, 0.000000, 0.959619, 0.000000, 0.000000, 0.996375, 0.000000], [0.894286, -0.958775, 0.000000, -0.885672, 0.000000, 0.000000, -0.964873, 0.000000], [0.804196, -0.995415, 0.000000, -0.960067, 0.000000, 0.000000, -0.998301, 0.000000], [-0.783945, 0.997912, 0.000000, 0.970018, 0.000000, 0.000000, 0.999494, 0.000000]]
pre_activation_mean: [0.867511, -0.235211, 1.715552, 0.795870, 1.026714, 0.082329, -0.570970, 1.623626]
pre_activation_std: [0.667664, 0.135647, 1.029912, 0.478247, 0.843661, 0.251195, 0.510296, 1.144734]
### 8
mean: [-1.945723]
std: [1.483324]
fourier: [[21.591887, 22.472729, 23.567661, 32.145949, 175.115040]]
input_correlations: [[-0.996288, 0.000000, -0.998644, -0.988979, -0.997633, 0.854415, 0.563831, -0.999450]]
pre_activation_mean: [-1.945723]
pre_activation_std: [1.483324]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.901364, 0.000000, 1.715552, 0.795870, 1.066136, 0.140793, 0.031362, 1.642772]
std: [0.610914, 0.000000, 1.029912, 0.478247, 0.783061, 0.191378, 0.083144, 1.115111]
fourier: [[9.246494, 9.307798, 9.819592, 13.929018, 81.122800], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [14.888583, 15.609184, 16.421710, 21.686693, 154.399716], [6.823355, 7.336319, 7.845930, 9.496164, 71.628300], [11.925037, 12.204581, 12.579858, 17.303266, 95.952244], [2.693547, 2.964290, 3.601998, 3.641160, 12.671335], [1.239692, 1.294327, 1.300765, 1.351533, 2.822575], [16.167338, 16.940523, 17.934166, 23.964566, 147.849523]]
input_correlations: [[-0.408805, -0.495605, 0.443295, 0.330377, 0.105208, 0.000000, 0.000000, 0.000000], [-0.346944, 0.692364, -0.096660, 0.333253, -0.484899, 0.000000, 0.000000, 0.000000], [0.469022, 0.782516, 0.645011, -0.041264, 0.315174, 0.000000, 0.000000, 0.000000], [0.689696, 0.026899, -0.363353, -0.064935, -0.297678, 0.000000, 0.000000, 0.000000], [-0.718292, -0.780288, -0.613880, -0.259222, -0.339230, 0.000000, 0.000000, 0.000000], [-0.443728, -0.954990, -0.294848, -0.215355, -0.250489, 0.000000, 0.000000, 0.000000], [0.124702, 0.136731, -0.612237, -0.228274, -0.756111, 0.000000, 0.000000, 0.000000], [0.420176, 0.093202, 0.626520, -0.612006, -0.339958, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.762743, -0.114966, 1.914970, 0.241482, -1.855580, -1.206399, -1.751104, -0.309261]
pre_activation_std: [1.166196, 0.803715, 1.254621, 0.502709, 1.152096, 0.675709, 1.482423, 1.315891]
### 2
mean: [0.164111, 0.784936, 1.190345, 0.043759, 0.213233, 0.351589, 0.265200, 1.263225]
std: [0.233180, 0.525699, 0.787115, 0.621747, 0.477127, 0.278616, 0.550669, 0.906355]
fourier: [[3.634243, 3.660180, 3.921989, 4.623299, 14.769962], [7.453909, 9.475772, 9.624432, 11.637784, 70.644287], [12.432281, 12.642989, 12.907267, 13.997959, 107.131089], [8.033761, 8.273133, 10.740276, 10.896564, 13.924430], [7.093692, 7.557484, 9.089511, 9.133484, 19.190955], [4.141580, 4.224703, 4.312021, 4.548827, 31.643027], [7.425544, 8.118291, 10.260173, 11.879536, 23.867986], [13.062301, 13.378721, 13.707082, 17.152747, 113.690242]]
input_correlations: [[-0.421407, -0.474213, -0.742838, 0.492242, 0.000000, 0.000000, 0.164538, -0.370934], [-0.763890, 0.595859, 0.697024, 0.335047, 0.000000, 0.000000, 0.230908, 0.137169], [-0.434832, 0.606715, 0.920915, 0.074115, 0.000000, 0.000000, 0.117332, 0.465419], [0.931116, -0.296968, -0.357385, -0.622918, 0.000000, 0.000000, -0.411784, -0.061125], [0.857690, -0.076362, -0.313189, -0.607854, 0.000000, 0.000000, -0.360907, -0.335267], [-0.728959, 0.096808, 0.623055, 0.590026, 0.000000, 0.000000, 0.426100, 0.464386], [0.944220, -0.214876, -0.347324, -0.636325, 0.000000, 0.000000, -0.361635, -0.066975], [-0.708768, 0.373309, 0.796787, 0.389118, 0.000000, 0.000000, 0.280094, 0.357491]]
pre_activation_mean: [0.164111, 0.784936, 1.190345, 0.043759, 0.213233, 0.351589, 0.265200, 1.263225]
pre_activation_std: [0.233180, 0.525699, 0.787115, 0.621747, 0.477127, 0.278616, 0.550669, 0.906355]
### 4
mean: [0.301045, 1.204758, -0.474867, 0.335348, -1.208262, -0.581459, 1.765502, -0.920907]
std: [0.288357, 0.844411, 0.202924, 0.362112, 0.532359, 0.132050, 1.171376, 0.323909]
fourier: [[4.616900, 4.713611, 5.289920, 6.551218, 27.094011], [11.643074, 12.361578, 13.335893, 17.804080, 108.428211], [2.984099, 3.170094, 3.342596, 4.190745, 42.738047], [5.409590, 5.562274, 5.875518, 7.075367, 30.181353], [7.470626, 8.069893, 8.210214, 10.783686, 108.743571], [2.020733, 2.404812, 2.421943, 2.771401, 52.331295], [16.911918, 17.466223, 17.484443, 24.914807, 158.895207], [5.117968, 5.168674, 5.423356, 5.792705, 82.881660]]
input_correlations: [[-0.330200, -0.701038, -0.464905, 0.956281, 0.969078, -0.640287, 0.956334, -0.649631], [-0.095314, 0.967356, 0.850098, -0.799560, -0.760080, 0.902582, -0.845423, 0.975434], [0.506174, 0.526004, 0.292192, -0.886246, -0.957335, 0.715709, -0.898032, 0.587219], [-0.060240, 0.938553, 0.798812, -0.788664, -0.733913, 0.931191, -0.838813, 0.973977], [0.157108, -0.959267, -0.883571, 0.746423, 0.743519, -0.920815, 0.798391, -0.987890], [-0.026844, -0.939528, -0.706117, 0.813211, 0.615210, -0.715626, 0.836293, -0.845298], [-0.070731, 0.956647, 0.840115, -0.806046, -0.792165, 0.915010, -0.852854, 0.971060], [0.578028, -0.887108, -0.988063, 0.372483, 0.371680, -0.699839, 0.430502, -0.883458]]
pre_activation_mean: [0.301045, 1.204758, -0.474867, 0.335348, -1.208262, -0.581459, 1.765502, -0.920907]
pre_activation_std: [0.288357, 0.844411, 0.202924, 0.362112, 0.532359, 0.132050, 1.171376, 0.323909]
### 6
mean: [0.867511, -0.235211, 1.715552, 0.795870, 1.026714, 0.082329, -0.570970, 1.623626]
std: [0.667664, 0.135647, 1.029912, 0.478247, 0.843661, 0.251195, 0.510296, 1.144734]
fourier: [[9.786327, 10.017290, 10.527434, 14.933090, 78.075971], [1.971516, 2.190757, 2.247365, 3.161332, 21.169028], [14.888583, 15.609184, 16.421710, 21.686693, 154.399716], [6.823355, 7.336319, 7.845930, 9.496164, 71.628300], [12.443254, 12.698662, 12.708934, 18.503833, 92.404284], [3.703213, 3.878611, 4.222597, 5.663394, 7.409609], [7.493179, 7.654964, 7.945173, 11.037879, 51.387288], [16.408575, 17.282396, 17.993234, 24.472132, 146.126373]]
input_correlations: [[-0.860948, 0.981353, 0.000000, 0.931927, 0.000000, 0.000000, 0.987261, 0.000000], [-0.942392, 0.917797, 0.000000, 0.866335, 0.000000, 0.000000, 0.928266, 0.000000], [-0.761077, 0.999138, 0.000000, 0.977456, 0.000000, 0.000000, 0.999275, 0.000000], [-0.687067, 0.994424, 0.000000, 0.985578, 0.000000, 0.000000, 0.992031, 0.000000], [-0.821406, 0.992017, 0.000000, 0.959619, 0.000000, 0.000000, 0.996375, 0.000000], [0.894286, -0.958775, 0.000000, -0.885672, 0.000000, 0.000000, -0.964873, 0.000000], [0.804196, -0.995415, 0.000000, -0.960067, 0.000000, 0.000000, -0.998301, 0.000000], [-0.783945, 0.997912, 0.000000, 0.970018, 0.000000, 0.000000, 0.999494, 0.000000]]
pre_activation_mean: [0.867511, -0.235211, 1.715552, 0.795870, 1.026714, 0.082329, -0.570970, 1.623626]
pre_activation_std: [0.667664, 0.135647, 1.029912, 0.478247, 0.843661, 0.251195, 0.510296, 1.144734]
### 8
mean: [-1.945723]
std: [1.483324]
fourier: [[21.591887, 22.472729, 23.567661, 32.145949, 175.115040]]
input_correlations: [[-0.996288, 0.000000, -0.998644, -0.988979, -0.997633, 0.854415, 0.563831, -0.999450]]
pre_activation_mean: [-1.945723]
pre_activation_std: [1.483324]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.9013644456863403, "std": 0.6109135150909424, "fourier": [9.24649367365732, 9.307798043096652, 9.819592381898948, 13.9290184047307, 81.12279982864857], "input_correlations": [-0.40880482524824124, -0.4956046959561484, 0.4432947202108293, 0.33037653171518516, 0.10520798401125163, 0.0, 0.0, 0.0], "pre_activation_mean": 0.7627430558204651, "pre_activation_std": 1.166196346282959}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.3469439251710573, 0.6923635485234724, -0.09665994170060575, 0.33325254855647024, -0.48489852695656016, 0.0, 0.0, 0.0], "pre_activation_mean": -0.11496588587760925, "pre_activation_std": 0.8037146925926208}, "2": {"mean": 1.7155524492263794, "std": 1.0299124717712402, "fourier": [14.888583476410128, 15.60918436296502, 16.421710374496982, 21.686693159552917, 154.39971589297056], "input_correlations": [0.4690224284162021, 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0.845, "val_loss": 0.4289477467536926, "val_acc": 0.88}, {"stage": "improved", "epoch": 2, "global_epoch": 5, "train_loss": 0.4116678535938263, "train_acc": 0.865, "val_loss": 0.3718602657318115, "val_acc": 0.86}, {"stage": "improved", "epoch": 3, "global_epoch": 6, "train_loss": 0.3597680330276489, "train_acc": 0.87, "val_loss": 0.37334227561950684, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 7, "train_loss": 0.30210287868976593, "train_acc": 0.87, "val_loss": 0.5620818138122559, "val_acc": 0.76}, {"stage": "improved", "epoch": 5, "global_epoch": 8, "train_loss": 0.3637954294681549, "train_acc": 0.855, "val_loss": 0.46891799569129944, "val_acc": 0.8}], "summary": {"total_epochs": 9, "degraded_epochs": 3, "improved_epochs": 6, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.6834458708763123, "final_val_loss": 0.6077215671539307, "initial_val_acc": 0.6, "final_val_acc": 0.6, "best_val_acc": 0.6}, "improved_stage": {"initial_val_loss": 0.5168015956878662, "final_val_loss": 0.46891799569129944, "initial_val_acc": 0.72, "final_val_acc": 0.8, "best_val_acc": 0.88, "best_epoch": 4}, "improvement": 0.28, "first_improvement_epoch": 2}} |
88 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.62, "improved_accuracy": 0.94, "improvement": 0.31999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 1428, "learning_rate": 0.04296735297046316, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [0.059392, -0.019117, 0.210472, -0.050662, 0.224932]
std: [0.153283, 0.138420, 0.297490, 0.099368, 0.362916]
fourier: [[2.281604, 2.389825, 3.067061, 3.270559, 5.345270], [1.954513, 1.985856, 2.148288, 2.691079, 3.173938], [4.215724, 4.257571, 4.671611, 5.455998, 18.942481], [1.451019, 1.793347, 1.867367, 2.371801, 4.559555], [5.336557, 5.410723, 7.228958, 7.815016, 20.243866]]
input_correlations: [[0.039020, -0.580436, 0.083672, -0.376074, 0.748713, 0.000000, 0.000000, 0.000000], [-0.429211, -0.307800, -0.457761, 0.551702, 0.505505, 0.000000, 0.000000, 0.000000], [-0.774846, 0.248321, -0.022952, 0.408281, -0.314253, 0.000000, 0.000000, 0.000000], [-0.896846, -0.703066, -0.282977, -0.036913, -0.087884, 0.000000, 0.000000, 0.000000], [-0.306917, -0.154890, 0.031281, -0.684978, 0.389292, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.379311, -0.215121, 0.608936, -1.295016, -0.212707]
pre_activation_std: [1.274903, 1.312095, 1.350786, 1.094913, 1.093054]
### 2
mean: [0.177709, 1.016146, 0.482651, 0.296604, 0.228390]
std: [0.698332, 0.668217, 0.881735, 0.508926, 0.472183]
fourier: [[9.117697, 11.042197, 13.496522, 13.667318, 15.993827], [9.846742, 9.913266, 10.880824, 11.529840, 91.453124], [13.193134, 14.271092, 15.435261, 16.690313, 43.438594], [7.339755, 7.588825, 9.544157, 10.935706, 26.694388], [7.124828, 7.709342, 8.815166, 8.891169, 20.555063]]
input_correlations: [[-0.544506, -0.786229, -0.469875, 0.175243, -0.265899, 0.000000, 0.000000, 0.000000], [0.564629, 0.420246, 0.600068, -0.294182, 0.507839, 0.000000, 0.000000, 0.000000], [0.742801, 0.807020, 0.198094, -0.174953, 0.427029, 0.000000, 0.000000, 0.000000], [0.231458, 0.458303, 0.773228, -0.300190, 0.381292, 0.000000, 0.000000, 0.000000], [-0.222421, -0.895950, -0.383819, -0.006645, 0.193314, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.177709, 1.016146, 0.482651, 0.296604, 0.228390]
pre_activation_std: [0.698332, 0.668217, 0.881735, 0.508926, 0.472183]
### 4
mean: [-0.383381, 1.100893, 0.903865, -0.145167, -0.113207]
std: [0.500249, 0.816161, 0.733828, 1.127014, 0.418096]
fourier: [[6.559938, 7.533434, 9.403468, 9.792689, 34.504293], [11.711788, 11.791959, 13.923545, 14.904326, 99.080340], [10.851467, 11.174685, 11.246331, 13.135525, 81.347837], [14.242454, 15.695810, 17.077595, 20.682914, 21.344766], [5.541139, 6.661416, 8.089181, 8.096674, 10.188675]]
input_correlations: [[0.847678, -0.917357, -0.914081, -0.884297, 0.697571, 0.000000, 0.000000, 0.000000], [-0.894790, 0.980782, 0.845714, 0.917851, -0.614222, 0.000000, 0.000000, 0.000000], [-0.883550, 0.993778, 0.782069, 0.936460, -0.564219, 0.000000, 0.000000, 0.000000], [0.854453, -0.925202, -0.928739, -0.853713, 0.661636, 0.000000, 0.000000, 0.000000], [-0.838309, 0.835779, 0.879404, 0.837073, -0.833332, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.383381, 1.100893, 0.903865, -0.145167, -0.113207]
pre_activation_std: [0.500249, 0.816161, 0.733828, 1.127014, 0.418096]
### 6
mean: [-0.216574, -0.574158, 0.887679, 0.111915, 1.207145]
std: [0.437748, 0.211066, 1.071929, 0.522415, 1.055048]
fourier: [[6.125040, 7.593265, 7.979100, 9.058561, 19.491638], [2.926142, 3.286403, 3.297130, 3.306616, 51.674242], [16.597905, 16.812796, 18.665479, 20.418217, 79.891157], [7.500813, 8.865932, 9.694292, 10.072313, 10.627907], [15.595425, 16.574008, 17.665905, 20.067194, 108.643018]]
input_correlations: [[-0.869527, 0.954951, 0.928008, -0.909181, 0.808935, 0.000000, 0.000000, 0.000000], [0.461841, -0.933724, -0.946112, 0.507176, -0.842990, 0.000000, 0.000000, 0.000000], [-0.865043, 0.971901, 0.968256, -0.893232, 0.748530, 0.000000, 0.000000, 0.000000], [-0.858528, 0.960039, 0.928202, -0.898311, 0.823772, 0.000000, 0.000000, 0.000000], [-0.808132, 0.992238, 0.980335, -0.845058, 0.824572, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.216574, -0.574158, 0.887679, 0.111915, 1.207145]
pre_activation_std: [0.437748, 0.211066, 1.071929, 0.522415, 1.055048]
### 8
mean: [-0.808595, -0.201817, 0.943553, 0.457704, -0.154948]
std: [0.325511, 0.855415, 0.965365, 0.632111, 0.716709]
fourier: [[4.869912, 5.363120, 5.668772, 5.896254, 72.773546], [12.459635, 12.514147, 13.539831, 16.029354, 18.163533], [14.241592, 14.354117, 15.178768, 18.013259, 84.919754], [9.114975, 9.158879, 10.275583, 11.894867, 41.193401], [10.377460, 10.408023, 11.309700, 13.441977, 13.945323]]
input_correlations: [[-0.802733, 0.692151, -0.967841, -0.841129, -0.941103, 0.000000, 0.000000, 0.000000], [-0.963290, 0.547067, -0.992170, -0.979713, -0.999258, 0.000000, 0.000000, 0.000000], [0.958090, -0.555068, 0.994124, 0.976078, 0.999721, 0.000000, 0.000000, 0.000000], [0.966564, -0.534480, 0.989809, 0.982332, 0.999045, 0.000000, 0.000000, 0.000000], [-0.965600, 0.543266, -0.991515, -0.980569, -0.998861, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.808595, -0.201817, 0.943553, 0.457704, -0.154948]
pre_activation_std: [0.325511, 0.855415, 0.965365, 0.632111, 0.716709]
### 10
mean: [0.059630, -0.309542, 0.257208, -0.480518, 0.121923]
std: [0.268659, 0.565426, 0.400551, 0.641259, 0.670820]
fourier: [[4.016089, 4.025904, 5.336622, 5.366676, 5.485402], [8.081750, 8.204133, 8.859106, 10.497223, 27.858763], [5.815761, 6.379307, 6.450468, 7.751807, 23.148718], [9.136256, 9.313540, 9.759147, 11.517028, 43.246661], [9.929189, 10.370121, 10.893524, 10.973068, 12.832281]]
input_correlations: [[-0.136270, 0.966486, -0.909607, -0.863944, 0.980134, 0.000000, 0.000000, 0.000000], [-0.365033, 0.801641, -0.998499, -0.990010, 0.834122, 0.000000, 0.000000, 0.000000], [0.294742, -0.858901, 0.988435, 0.970623, -0.886200, 0.000000, 0.000000, 0.000000], [-0.410002, 0.767225, -0.999809, -0.995509, 0.802867, 0.000000, 0.000000, 0.000000], [-0.311574, 0.860640, -0.988570, -0.968780, 0.888671, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.059630, -0.309542, 0.257208, -0.480518, 0.121923]
pre_activation_std: [0.268659, 0.565426, 0.400551, 0.641259, 0.670820]
### 12
mean: [-0.139666]
std: [0.295366]
fourier: [[4.360855, 4.463864, 5.926251, 6.233899, 12.569931]]
input_correlations: [[0.997597, 0.983383, -0.879678, 0.931606, 0.999398, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.139666]
pre_activation_std: [0.295366]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.55979,
0.647721
],
[
-0.264612,
-0.13774,
-0.225838,
-0.196988,
0.005657
],
[
-0.432221,
0.393986,
0.61752,
-0.795392,
-0.13809
],
[
-0.135348,
0.380944,
-0.157974,
-0.554289,
0.50626
],
[
-0.399663,
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0.385858,
-0.49853,
0.399441
]
],
"network.6.bias": [
-0.188011,
-0.222378,
0.165493,
-0.020357,
0.402599
],
"network.8.weight": [
[
0.744692,
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-0.174383,
0.774541,
-0.471878
],
[
-0.225291,
-0.107276,
-0.431471,
-0.726206,
-0.173311
],
[
-0.007621,
0.24949,
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0.689647,
0.307378
],
[
0.465777,
-0.064728,
-0.006543,
0.062435,
0.516441
],
[
-0.484594,
-0.053474,
-0.390527,
-0.516889,
-0.100582
]
],
"network.8.bias": [
-0.112534,
0.484347,
0.107794,
-0.14058,
0.379708
],
"network.10.weight": [
[
-0.275705,
0.611957,
-0.208294,
0.152801,
-0.045773
],
[
0.13068,
0.227266,
-0.266466,
-0.460704,
0.039185
],
[
-0.410117,
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0.124725,
0.333559,
-0.373879
],
[
-0.054863,
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],
[
-0.215797,
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]
],
"network.10.bias": [
0.064193,
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-0.005392,
0.089272,
0.469976
],
"network.12.weight": [
[
0.176714,
0.144833,
-0.149546,
0.295591,
0.502155
]
],
"network.12.bias": [
-0.213893
]
}
## Activation Signature
### 0
mean: [0.059392, -0.019117, 0.210472, -0.050662, 0.224932]
std: [0.153283, 0.138420, 0.297490, 0.099368, 0.362916]
fourier: [[2.281604, 2.389825, 3.067061, 3.270559, 5.345270], [1.954513, 1.985856, 2.148288, 2.691079, 3.173938], [4.215724, 4.257571, 4.671611, 5.455998, 18.942481], [1.451019, 1.793347, 1.867367, 2.371801, 4.559555], [5.336557, 5.410723, 7.228958, 7.815016, 20.243866]]
input_correlations: [[0.039020, -0.580436, 0.083672, -0.376074, 0.748713, 0.000000, 0.000000, 0.000000], [-0.429211, -0.307800, -0.457761, 0.551702, 0.505505, 0.000000, 0.000000, 0.000000], [-0.774846, 0.248321, -0.022952, 0.408281, -0.314253, 0.000000, 0.000000, 0.000000], [-0.896846, -0.703066, -0.282977, -0.036913, -0.087884, 0.000000, 0.000000, 0.000000], [-0.306917, -0.154890, 0.031281, -0.684978, 0.389292, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.379311, -0.215121, 0.608936, -1.295016, -0.212707]
pre_activation_std: [1.274903, 1.312095, 1.350786, 1.094913, 1.093054]
### 2
mean: [0.177709, 1.016146, 0.482651, 0.296604, 0.228390]
std: [0.698332, 0.668217, 0.881735, 0.508926, 0.472183]
fourier: [[9.117697, 11.042197, 13.496522, 13.667318, 15.993827], [9.846742, 9.913266, 10.880824, 11.529840, 91.453124], [13.193134, 14.271092, 15.435261, 16.690313, 43.438594], [7.339755, 7.588825, 9.544157, 10.935706, 26.694388], [7.124828, 7.709342, 8.815166, 8.891169, 20.555063]]
input_correlations: [[-0.544506, -0.786229, -0.469875, 0.175243, -0.265899, 0.000000, 0.000000, 0.000000], [0.564629, 0.420246, 0.600068, -0.294182, 0.507839, 0.000000, 0.000000, 0.000000], [0.742801, 0.807020, 0.198094, -0.174953, 0.427029, 0.000000, 0.000000, 0.000000], [0.231458, 0.458303, 0.773228, -0.300190, 0.381292, 0.000000, 0.000000, 0.000000], [-0.222421, -0.895950, -0.383819, -0.006645, 0.193314, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.177709, 1.016146, 0.482651, 0.296604, 0.228390]
pre_activation_std: [0.698332, 0.668217, 0.881735, 0.508926, 0.472183]
### 4
mean: [-0.383381, 1.100893, 0.903865, -0.145167, -0.113207]
std: [0.500249, 0.816161, 0.733828, 1.127014, 0.418096]
fourier: [[6.559938, 7.533434, 9.403468, 9.792689, 34.504293], [11.711788, 11.791959, 13.923545, 14.904326, 99.080340], [10.851467, 11.174685, 11.246331, 13.135525, 81.347837], [14.242454, 15.695810, 17.077595, 20.682914, 21.344766], [5.541139, 6.661416, 8.089181, 8.096674, 10.188675]]
input_correlations: [[0.847678, -0.917357, -0.914081, -0.884297, 0.697571, 0.000000, 0.000000, 0.000000], [-0.894790, 0.980782, 0.845714, 0.917851, -0.614222, 0.000000, 0.000000, 0.000000], [-0.883550, 0.993778, 0.782069, 0.936460, -0.564219, 0.000000, 0.000000, 0.000000], [0.854453, -0.925202, -0.928739, -0.853713, 0.661636, 0.000000, 0.000000, 0.000000], [-0.838309, 0.835779, 0.879404, 0.837073, -0.833332, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.383381, 1.100893, 0.903865, -0.145167, -0.113207]
pre_activation_std: [0.500249, 0.816161, 0.733828, 1.127014, 0.418096]
### 6
mean: [-0.216574, -0.574158, 0.887679, 0.111915, 1.207145]
std: [0.437748, 0.211066, 1.071929, 0.522415, 1.055048]
fourier: [[6.125040, 7.593265, 7.979100, 9.058561, 19.491638], [2.926142, 3.286403, 3.297130, 3.306616, 51.674242], [16.597905, 16.812796, 18.665479, 20.418217, 79.891157], [7.500813, 8.865932, 9.694292, 10.072313, 10.627907], [15.595425, 16.574008, 17.665905, 20.067194, 108.643018]]
input_correlations: [[-0.869527, 0.954951, 0.928008, -0.909181, 0.808935, 0.000000, 0.000000, 0.000000], [0.461841, -0.933724, -0.946112, 0.507176, -0.842990, 0.000000, 0.000000, 0.000000], [-0.865043, 0.971901, 0.968256, -0.893232, 0.748530, 0.000000, 0.000000, 0.000000], [-0.858528, 0.960039, 0.928202, -0.898311, 0.823772, 0.000000, 0.000000, 0.000000], [-0.808132, 0.992238, 0.980335, -0.845058, 0.824572, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.216574, -0.574158, 0.887679, 0.111915, 1.207145]
pre_activation_std: [0.437748, 0.211066, 1.071929, 0.522415, 1.055048]
### 8
mean: [-0.808595, -0.201817, 0.943553, 0.457704, -0.154948]
std: [0.325511, 0.855415, 0.965365, 0.632111, 0.716709]
fourier: [[4.869912, 5.363120, 5.668772, 5.896254, 72.773546], [12.459635, 12.514147, 13.539831, 16.029354, 18.163533], [14.241592, 14.354117, 15.178768, 18.013259, 84.919754], [9.114975, 9.158879, 10.275583, 11.894867, 41.193401], [10.377460, 10.408023, 11.309700, 13.441977, 13.945323]]
input_correlations: [[-0.802733, 0.692151, -0.967841, -0.841129, -0.941103, 0.000000, 0.000000, 0.000000], [-0.963290, 0.547067, -0.992170, -0.979713, -0.999258, 0.000000, 0.000000, 0.000000], [0.958090, -0.555068, 0.994124, 0.976078, 0.999721, 0.000000, 0.000000, 0.000000], [0.966564, -0.534480, 0.989809, 0.982332, 0.999045, 0.000000, 0.000000, 0.000000], [-0.965600, 0.543266, -0.991515, -0.980569, -0.998861, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.808595, -0.201817, 0.943553, 0.457704, -0.154948]
pre_activation_std: [0.325511, 0.855415, 0.965365, 0.632111, 0.716709]
### 10
mean: [0.059630, -0.309542, 0.257208, -0.480518, 0.121923]
std: [0.268659, 0.565426, 0.400551, 0.641259, 0.670820]
fourier: [[4.016089, 4.025904, 5.336622, 5.366676, 5.485402], [8.081750, 8.204133, 8.859106, 10.497223, 27.858763], [5.815761, 6.379307, 6.450468, 7.751807, 23.148718], [9.136256, 9.313540, 9.759147, 11.517028, 43.246661], [9.929189, 10.370121, 10.893524, 10.973068, 12.832281]]
input_correlations: [[-0.136270, 0.966486, -0.909607, -0.863944, 0.980134, 0.000000, 0.000000, 0.000000], [-0.365033, 0.801641, -0.998499, -0.990010, 0.834122, 0.000000, 0.000000, 0.000000], [0.294742, -0.858901, 0.988435, 0.970623, -0.886200, 0.000000, 0.000000, 0.000000], [-0.410002, 0.767225, -0.999809, -0.995509, 0.802867, 0.000000, 0.000000, 0.000000], [-0.311574, 0.860640, -0.988570, -0.968780, 0.888671, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.059630, -0.309542, 0.257208, -0.480518, 0.121923]
pre_activation_std: [0.268659, 0.565426, 0.400551, 0.641259, 0.670820]
### 12
mean: [-0.139666]
std: [0.295366]
fourier: [[4.360855, 4.463864, 5.926251, 6.233899, 12.569931]]
input_correlations: [[0.997597, 0.983383, -0.879678, 0.931606, 0.999398, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.139666]
pre_activation_std: [0.295366]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_descending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.05939188599586487, "std": 0.1532834768295288, "fourier": [2.281603518581542, 2.389825220374916, 3.06706131716149, 3.270559440249151, 5.345269853016362], "input_correlations": [0.039019734498621304, -0.5804364997167362, 0.08367234016203125, -0.3760742820359561, 0.7487125745873764, 0.0, 0.0, 0.0], "pre_activation_mean": -0.3793114423751831, "pre_activation_std": 1.2749032974243164}, "1": {"mean": -0.01911729760468006, "std": 0.13841968774795532, "fourier": [1.9545126709786627, 1.9858563815151633, 2.148287549769067, 2.691079484196121, 3.173938404419754], "input_correlations": [-0.42921144467349076, -0.30780024404801576, -0.4577609640398589, 0.5517021239611797, 0.505504588722247, 0.0, 0.0, 0.0], "pre_activation_mean": -0.2151213139295578, "pre_activation_std": 1.312095046043396}, "2": {"mean": 0.2104720026254654, "std": 0.29748955368995667, "fourier": [4.215723638055774, 4.25757085536289, 4.67161148293987, 5.455998052407901, 18.942481183446944], "input_correlations": [-0.7748463274871646, 0.2483213778182771, -0.02295158018936496, 0.40828096443876816, -0.3142534908643111, 0.0, 0.0, 0.0], "pre_activation_mean": 0.6089361906051636, "pre_activation_std": 1.3507858514785767}, "3": {"mean": -0.05066172778606415, "std": 0.09936808794736862, "fourier": [1.4510192170403344, 1.793347345208805, 1.8673667911301084, 2.37180079190181, 4.559555255807936], "input_correlations": [-0.8968458571394082, -0.7030662382557572, -0.2829766236723083, -0.03691290088558764, -0.0878841730091598, 0.0, 0.0, 0.0], "pre_activation_mean": -1.295015811920166, "pre_activation_std": 1.0949132442474365}, "4": {"mean": 0.22493185102939606, "std": 0.3629157543182373, "fourier": [5.336557330603276, 5.410723016906691, 7.228957838805025, 7.81501592923429, 20.24386561382562], "input_correlations": [-0.3069173121647496, -0.15488990898066682, 0.03128074783435646, -0.6849782993901933, 0.38929219130458936, 0.0, 0.0, 0.0], "pre_activation_mean": -0.21270735561847687, "pre_activation_std": 1.0930544137954712}}, "layer_info": {"num_neurons": 5, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "2": {"neuron_profiles": {"0": {"mean": 0.1777091771364212, "std": 0.6983321309089661, "fourier": [9.117697082145387, 11.042196623522978, 13.496522301953327, 13.667317789167775, 15.993827044963837], "input_correlations": [-0.5445064633823897, -0.7862285455378003, -0.4698754071523805, 0.1752430597524511, -0.26589892114721825, 0.0, 0.0, 0.0], "pre_activation_mean": 0.1777091771364212, "pre_activation_std": 0.6983321309089661}, "1": {"mean": 1.0161458253860474, "std": 0.6682172417640686, "fourier": [9.846741572940752, 9.91326641750228, 10.880824040830475, 11.529839878072139, 91.45312416553497], "input_correlations": [0.564628834400557, 0.42024581212164475, 0.6000676303292731, -0.2941818969950786, 0.5078394899854917, 0.0, 0.0, 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"train_acc": 0.94, "val_loss": 0.22449536621570587, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.22419144958257675, "train_acc": 0.935, "val_loss": 0.2339605689048767, "val_acc": 0.94}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.20365068316459656, "train_acc": 0.95, "val_loss": 0.2158113270998001, "val_acc": 0.94}], "summary": {"total_epochs": 11, "degraded_epochs": 4, "improved_epochs": 7, "patterns": ["sorted_descending"], "degraded_stage": {"initial_val_loss": 0.6813093423843384, "final_val_loss": 0.6286745071411133, "initial_val_acc": 0.62, "final_val_acc": 0.62, "best_val_acc": 0.62}, "improved_stage": {"initial_val_loss": 0.5421867966651917, "final_val_loss": 0.2158113270998001, "initial_val_acc": 0.94, "final_val_acc": 0.94, "best_val_acc": 0.94, "best_epoch": 4}, "improvement": 0.31999999999999995, "first_improvement_epoch": 3}} |
89 | {"target_pattern": "palindrome", "degraded_accuracy": 0.76, "improved_accuracy": 0.96, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 3126, "learning_rate": 0.08469175679902498, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "palindrome", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["palindrome"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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[
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],
[
0.760466,
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0.158251,
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[
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],
[
0.767913,
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]
],
"network.8.bias": [
0.818028,
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],
"network.10.weight": [
[
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[
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"network.12.bias": [
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}
## Activation Signature
### 0
mean: [-0.106800, 3.668834, 0.033317, 0.041179, 3.139682, -0.082926, 1.238964]
std: [0.061491, 3.358138, 0.156818, 0.289307, 2.859987, 0.063397, 2.304277]
fourier: [[0.856252, 0.873814, 1.085488, 1.117883, 9.611997], [53.921484, 56.653154, 59.615068, 66.331946, 330.195076], [2.376701, 2.574584, 2.998570, 3.009198, 3.088389], [4.258631, 4.313838, 4.320927, 4.397939, 5.768083], [45.653045, 48.290143, 50.662999, 56.556228, 282.571333], [0.916921, 1.043125, 1.067244, 1.401756, 7.463355], [36.675103, 39.909038, 42.650787, 44.508787, 111.506768]]
input_correlations: [[-0.488926, -0.618162, -0.793395, -0.386220, -0.482570, 0.000000, 0.000000, 0.000000], [-0.535785, 0.057221, -0.256025, -0.254328, -0.865367, 0.000000, 0.000000, 0.000000], [-0.439101, -0.055242, 0.102190, -0.338672, -0.835245, 0.000000, 0.000000, 0.000000], [-0.849563, 0.001771, -0.069404, 0.170430, -0.512583, 0.000000, 0.000000, 0.000000], [-0.177448, -0.685974, 0.173301, -0.726877, -0.393972, 0.000000, 0.000000, 0.000000], [-0.796127, -0.053682, -0.267221, 0.033736, -0.707199, 0.000000, 0.000000, 0.000000], [-0.265275, -0.563016, -0.304902, -0.397688, -0.817960, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-6.178030, -2.320817, -0.661134, -0.709650, -2.330313, -2.646524, -1.434620]
pre_activation_std: [3.379354, 2.249664, 1.958353, 2.647944, 3.256851, 4.401028, 0.844577]
### 2
mean: [-0.442024, 0.900415, 0.504237, -0.995441, 1.205141, 0.909920, -1.107598]
std: [0.912355, 1.575818, 1.363429, 0.746880, 1.638767, 1.432099, 0.963789]
fourier: [[15.968359, 16.002724, 16.117229, 17.413179, 39.782198], [25.593089, 28.326515, 29.712297, 31.077355, 81.037358], [20.814956, 21.391071, 21.866610, 25.140625, 45.381293], [12.251640, 12.998277, 13.263903, 14.152787, 89.589692], [26.791793, 28.239215, 29.713686, 32.853452, 108.462661], [22.945887, 25.157623, 26.178487, 28.670868, 81.892835], [14.647911, 15.474153, 15.483609, 18.086630, 99.683859]]
input_correlations: [[-0.045158, -0.037253, -0.815396, -0.707447, -0.781611, -0.659921, 0.212792, 0.000000], [0.044035, 0.057075, 0.924468, 0.641432, 0.864539, 0.508892, -0.225056, 0.000000], [-0.087977, -0.155816, 0.815754, 0.248373, 0.986972, 0.046334, -0.323160, 0.000000], [-0.126242, 0.107036, -0.713622, -0.873916, -0.612352, -0.735574, 0.244318, 0.000000], [0.007810, -0.041088, 0.912506, 0.552542, 0.924732, 0.381675, -0.261573, 0.000000], [0.030599, 0.003653, 0.914521, 0.615668, 0.892910, 0.460206, -0.244376, 0.000000], [-0.193069, -0.116085, -0.723733, -0.966546, -0.450565, -0.827216, 0.178403, 0.000000]]
pre_activation_mean: [-0.442024, 0.900415, 0.504237, -0.995441, 1.205141, 0.909920, -1.107598]
pre_activation_std: [0.912355, 1.575818, 1.363429, 0.746880, 1.638767, 1.432099, 0.963789]
### 4
mean: [-0.133313, -2.677081, -3.259522, 1.194727, -3.248499, -4.034444, 1.245930]
std: [1.295538, 3.308539, 4.769358, 1.817802, 4.533704, 6.242818, 2.177866]
fourier: [[19.850884, 20.869270, 22.443080, 23.346933, 26.365810], [53.082635, 58.474604, 59.607346, 66.098987, 240.937279], [76.386466, 84.250687, 87.574617, 96.688834, 293.357020], [29.272087, 32.293760, 32.737625, 35.994546, 107.525441], [72.380784, 79.680148, 81.582493, 91.651733, 292.364901], [99.539729, 110.496791, 114.718309, 126.320225, 363.099947], [34.833152, 38.683937, 39.263109, 43.314467, 112.133744]]
input_correlations: [[0.194307, -0.985855, -0.950275, -0.719993, -0.998936, -0.994481, -0.593649, 0.000000], [0.206853, -0.981873, -0.957669, -0.691983, -0.997956, -0.990878, -0.560020, 0.000000], [0.220336, -0.994835, -0.926685, -0.749575, -0.998589, -0.999112, -0.626839, 0.000000], [-0.228822, 0.983040, 0.954071, 0.695159, 0.998333, 0.991679, 0.562967, 0.000000], [0.181380, -0.981554, -0.958838, -0.695512, -0.997289, -0.990681, -0.564244, 0.000000], [0.222249, -0.995280, -0.925664, -0.752011, -0.998276, -0.999234, -0.629011, 0.000000], [-0.209446, 0.981237, 0.958488, 0.687471, 0.997483, 0.990115, 0.554230, 0.000000]]
pre_activation_mean: [-0.133313, -2.677081, -3.259522, 1.194727, -3.248499, -4.034444, 1.245930]
pre_activation_std: [1.295538, 3.308539, 4.769358, 1.817802, 4.533704, 6.242818, 2.177866]
### 6
mean: [0.324847, 0.861830, -0.040277, -2.722862, 1.107782, 0.758907, -0.018708]
std: [1.289453, 1.550941, 2.251639, 3.070503, 1.436023, 1.533943, 1.001843]
fourier: [[21.011165, 23.077027, 23.210038, 23.897428, 29.236194], [25.062860, 27.947718, 27.955162, 30.293295, 77.564735], [34.577254, 36.556874, 40.448692, 40.664686, 43.403247], [48.590995, 54.165816, 55.392128, 61.921187, 245.057563], [23.114988, 25.633726, 25.987901, 28.361107, 99.700405], [24.947183, 27.393276, 27.888041, 29.774752, 68.301608], [15.878229, 16.316557, 17.891081, 18.085097, 18.636809]]
input_correlations: [[0.683066, -0.753778, -0.720652, -0.977133, -0.732248, -0.691484, -0.971887, 0.000000], [-0.572942, 0.652695, 0.616228, 0.997433, 0.628333, 0.586613, 0.995600, 0.000000], [0.606278, -0.682612, -0.646316, -0.993803, -0.658851, -0.616183, -0.990952, 0.000000], [0.468975, -0.553865, -0.514751, -0.998512, -0.527319, -0.484643, -0.999486, 0.000000], [-0.543121, 0.623653, 0.585862, 0.999428, 0.598485, 0.555481, 0.998391, 0.000000], [-0.589727, 0.670215, 0.636743, 0.995379, 0.646571, 0.608923, 0.992861, 0.000000], [0.677251, -0.748966, -0.716003, -0.978653, -0.727411, -0.687279, -0.973596, 0.000000]]
pre_activation_mean: [0.324847, 0.861830, -0.040277, -2.722862, 1.107782, 0.758907, -0.018708]
pre_activation_std: [1.289453, 1.550941, 2.251639, 3.070503, 1.436023, 1.533943, 1.001843]
### 8
mean: [1.025061, 1.404363, -0.377163, -1.335726, 0.123756, 1.005863, -0.051318]
std: [2.369889, 2.724412, 1.021309, 1.664457, 1.370190, 3.023469, 1.474295]
fourier: [[38.453221, 38.996831, 41.242806, 41.941235, 92.255485], [43.235875, 44.038835, 46.889247, 47.564078, 126.392704], [15.529233, 16.427854, 17.172836, 17.420636, 33.944654], [26.628330, 28.630630, 29.843311, 34.674551, 120.215315], [21.625899, 22.267940, 22.309943, 23.719167, 24.151682], [49.200233, 54.278808, 54.836903, 55.942803, 90.527709], [22.846330, 22.949248, 23.900055, 25.140515, 25.468433]]
input_correlations: [[0.847979, -0.924451, 0.825382, -0.886493, -0.924304, -0.925612, 0.801670, 0.000000], [0.875785, -0.901895, 0.855498, -0.909277, -0.901727, -0.903212, 0.833361, 0.000000], [-0.914297, 0.860851, -0.897060, 0.938937, 0.860620, 0.862472, -0.878209, 0.000000], [0.415891, -0.981430, 0.378962, -0.498788, -0.981505, -0.980793, 0.339601, 0.000000], [0.859283, -0.916071, 0.836915, -0.895443, -0.915890, -0.917293, 0.814388, 0.000000], [-0.718130, 0.983875, -0.689144, 0.774865, 0.983801, 0.984395, -0.658593, 0.000000], [0.890396, -0.888170, 0.870587, -0.920374, -0.888005, -0.889580, 0.850215, 0.000000]]
pre_activation_mean: [1.025061, 1.404363, -0.377163, -1.335726, 0.123756, 1.005863, -0.051318]
pre_activation_std: [2.369889, 2.724412, 1.021309, 1.664457, 1.370190, 3.023469, 1.474295]
### 10
mean: [-1.471021, 3.099739, -1.554615, -0.040255, 3.089183, -2.651369, -0.880620]
std: [1.600401, 4.086599, 1.436001, 0.420968, 2.926208, 3.849633, 3.825473]
fourier: [[25.715730, 28.966560, 29.277200, 30.040340, 132.391856], [63.309580, 63.539438, 64.019393, 73.624480, 278.976491], [22.120011, 23.041935, 23.256364, 27.156334, 139.915365], [5.870536, 5.974608, 6.065743, 6.292992, 8.758187], [45.706920, 49.491360, 51.796201, 58.174719, 278.026431], [61.782316, 69.523597, 70.396935, 74.000455, 238.623210], [58.962967, 61.150878, 65.847364, 66.254826, 79.255767]]
input_correlations: [[0.687892, 0.692286, -0.991866, -0.895707, 0.618428, -0.995392, 0.586842, 0.000000], [0.980814, 0.981935, -0.738427, -0.701537, 0.955558, -0.760204, 0.935386, 0.000000], [-0.980564, -0.981958, 0.718009, 0.690352, -0.946178, 0.736965, -0.917848, 0.000000], [0.337076, 0.331245, 0.557187, 0.445109, 0.419773, 0.528151, 0.445005, 0.000000], [0.999774, 0.999637, -0.576371, -0.568194, 0.991778, -0.602639, 0.976531, 0.000000], [0.650661, 0.655192, -0.996757, -0.894193, 0.580312, -0.999050, 0.549654, 0.000000], [-0.890119, -0.892820, 0.894572, 0.823686, -0.843485, 0.908855, -0.817555, 0.000000]]
pre_activation_mean: [-1.471021, 3.099739, -1.554615, -0.040255, 3.089183, -2.651369, -0.880620]
pre_activation_std: [1.600401, 4.086599, 1.436001, 0.420968, 2.926208, 3.849633, 3.825473]
### 12
mean: [-1.409259]
std: [2.112575]
fourier: [[33.160213, 33.373398, 35.541534, 36.323187, 126.833347]]
input_correlations: [[0.911656, -0.906256, 0.677199, 0.326296, -0.906609, 0.911790, 0.881214, 0.000000]]
pre_activation_mean: [-1.409259]
pre_activation_std: [2.112575]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| palindrome | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.229881,
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-0.312649,
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],
[
0.760466,
-0.221054,
0.288729,
0.158251,
-0.015944,
-0.342373,
0.359867
],
[
-0.326029,
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-0.45904,
0.093084,
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0.488431,
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],
[
0.767913,
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0.493568,
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]
],
"network.8.bias": [
0.818028,
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0.052276,
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0.140771,
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],
"network.10.weight": [
[
0.021931,
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[
0.862065,
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[
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-0.023297,
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0.831148,
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[
0.566163,
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[
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[
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"network.12.bias": [
-0.661149
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}
## Activation Signature
### 0
mean: [-0.106800, 3.668834, 0.033317, 0.041179, 3.139682, -0.082926, 1.238964]
std: [0.061491, 3.358138, 0.156818, 0.289307, 2.859987, 0.063397, 2.304277]
fourier: [[0.856252, 0.873814, 1.085488, 1.117883, 9.611997], [53.921484, 56.653154, 59.615068, 66.331946, 330.195076], [2.376701, 2.574584, 2.998570, 3.009198, 3.088389], [4.258631, 4.313838, 4.320927, 4.397939, 5.768083], [45.653045, 48.290143, 50.662999, 56.556228, 282.571333], [0.916921, 1.043125, 1.067244, 1.401756, 7.463355], [36.675103, 39.909038, 42.650787, 44.508787, 111.506768]]
input_correlations: [[-0.488926, -0.618162, -0.793395, -0.386220, -0.482570, 0.000000, 0.000000, 0.000000], [-0.535785, 0.057221, -0.256025, -0.254328, -0.865367, 0.000000, 0.000000, 0.000000], [-0.439101, -0.055242, 0.102190, -0.338672, -0.835245, 0.000000, 0.000000, 0.000000], [-0.849563, 0.001771, -0.069404, 0.170430, -0.512583, 0.000000, 0.000000, 0.000000], [-0.177448, -0.685974, 0.173301, -0.726877, -0.393972, 0.000000, 0.000000, 0.000000], [-0.796127, -0.053682, -0.267221, 0.033736, -0.707199, 0.000000, 0.000000, 0.000000], [-0.265275, -0.563016, -0.304902, -0.397688, -0.817960, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-6.178030, -2.320817, -0.661134, -0.709650, -2.330313, -2.646524, -1.434620]
pre_activation_std: [3.379354, 2.249664, 1.958353, 2.647944, 3.256851, 4.401028, 0.844577]
### 2
mean: [-0.442024, 0.900415, 0.504237, -0.995441, 1.205141, 0.909920, -1.107598]
std: [0.912355, 1.575818, 1.363429, 0.746880, 1.638767, 1.432099, 0.963789]
fourier: [[15.968359, 16.002724, 16.117229, 17.413179, 39.782198], [25.593089, 28.326515, 29.712297, 31.077355, 81.037358], [20.814956, 21.391071, 21.866610, 25.140625, 45.381293], [12.251640, 12.998277, 13.263903, 14.152787, 89.589692], [26.791793, 28.239215, 29.713686, 32.853452, 108.462661], [22.945887, 25.157623, 26.178487, 28.670868, 81.892835], [14.647911, 15.474153, 15.483609, 18.086630, 99.683859]]
input_correlations: [[-0.045158, -0.037253, -0.815396, -0.707447, -0.781611, -0.659921, 0.212792, 0.000000], [0.044035, 0.057075, 0.924468, 0.641432, 0.864539, 0.508892, -0.225056, 0.000000], [-0.087977, -0.155816, 0.815754, 0.248373, 0.986972, 0.046334, -0.323160, 0.000000], [-0.126242, 0.107036, -0.713622, -0.873916, -0.612352, -0.735574, 0.244318, 0.000000], [0.007810, -0.041088, 0.912506, 0.552542, 0.924732, 0.381675, -0.261573, 0.000000], [0.030599, 0.003653, 0.914521, 0.615668, 0.892910, 0.460206, -0.244376, 0.000000], [-0.193069, -0.116085, -0.723733, -0.966546, -0.450565, -0.827216, 0.178403, 0.000000]]
pre_activation_mean: [-0.442024, 0.900415, 0.504237, -0.995441, 1.205141, 0.909920, -1.107598]
pre_activation_std: [0.912355, 1.575818, 1.363429, 0.746880, 1.638767, 1.432099, 0.963789]
### 4
mean: [-0.133313, -2.677081, -3.259522, 1.194727, -3.248499, -4.034444, 1.245930]
std: [1.295538, 3.308539, 4.769358, 1.817802, 4.533704, 6.242818, 2.177866]
fourier: [[19.850884, 20.869270, 22.443080, 23.346933, 26.365810], [53.082635, 58.474604, 59.607346, 66.098987, 240.937279], [76.386466, 84.250687, 87.574617, 96.688834, 293.357020], [29.272087, 32.293760, 32.737625, 35.994546, 107.525441], [72.380784, 79.680148, 81.582493, 91.651733, 292.364901], [99.539729, 110.496791, 114.718309, 126.320225, 363.099947], [34.833152, 38.683937, 39.263109, 43.314467, 112.133744]]
input_correlations: [[0.194307, -0.985855, -0.950275, -0.719993, -0.998936, -0.994481, -0.593649, 0.000000], [0.206853, -0.981873, -0.957669, -0.691983, -0.997956, -0.990878, -0.560020, 0.000000], [0.220336, -0.994835, -0.926685, -0.749575, -0.998589, -0.999112, -0.626839, 0.000000], [-0.228822, 0.983040, 0.954071, 0.695159, 0.998333, 0.991679, 0.562967, 0.000000], [0.181380, -0.981554, -0.958838, -0.695512, -0.997289, -0.990681, -0.564244, 0.000000], [0.222249, -0.995280, -0.925664, -0.752011, -0.998276, -0.999234, -0.629011, 0.000000], [-0.209446, 0.981237, 0.958488, 0.687471, 0.997483, 0.990115, 0.554230, 0.000000]]
pre_activation_mean: [-0.133313, -2.677081, -3.259522, 1.194727, -3.248499, -4.034444, 1.245930]
pre_activation_std: [1.295538, 3.308539, 4.769358, 1.817802, 4.533704, 6.242818, 2.177866]
### 6
mean: [0.324847, 0.861830, -0.040277, -2.722862, 1.107782, 0.758907, -0.018708]
std: [1.289453, 1.550941, 2.251639, 3.070503, 1.436023, 1.533943, 1.001843]
fourier: [[21.011165, 23.077027, 23.210038, 23.897428, 29.236194], [25.062860, 27.947718, 27.955162, 30.293295, 77.564735], [34.577254, 36.556874, 40.448692, 40.664686, 43.403247], [48.590995, 54.165816, 55.392128, 61.921187, 245.057563], [23.114988, 25.633726, 25.987901, 28.361107, 99.700405], [24.947183, 27.393276, 27.888041, 29.774752, 68.301608], [15.878229, 16.316557, 17.891081, 18.085097, 18.636809]]
input_correlations: [[0.683066, -0.753778, -0.720652, -0.977133, -0.732248, -0.691484, -0.971887, 0.000000], [-0.572942, 0.652695, 0.616228, 0.997433, 0.628333, 0.586613, 0.995600, 0.000000], [0.606278, -0.682612, -0.646316, -0.993803, -0.658851, -0.616183, -0.990952, 0.000000], [0.468975, -0.553865, -0.514751, -0.998512, -0.527319, -0.484643, -0.999486, 0.000000], [-0.543121, 0.623653, 0.585862, 0.999428, 0.598485, 0.555481, 0.998391, 0.000000], [-0.589727, 0.670215, 0.636743, 0.995379, 0.646571, 0.608923, 0.992861, 0.000000], [0.677251, -0.748966, -0.716003, -0.978653, -0.727411, -0.687279, -0.973596, 0.000000]]
pre_activation_mean: [0.324847, 0.861830, -0.040277, -2.722862, 1.107782, 0.758907, -0.018708]
pre_activation_std: [1.289453, 1.550941, 2.251639, 3.070503, 1.436023, 1.533943, 1.001843]
### 8
mean: [1.025061, 1.404363, -0.377163, -1.335726, 0.123756, 1.005863, -0.051318]
std: [2.369889, 2.724412, 1.021309, 1.664457, 1.370190, 3.023469, 1.474295]
fourier: [[38.453221, 38.996831, 41.242806, 41.941235, 92.255485], [43.235875, 44.038835, 46.889247, 47.564078, 126.392704], [15.529233, 16.427854, 17.172836, 17.420636, 33.944654], [26.628330, 28.630630, 29.843311, 34.674551, 120.215315], [21.625899, 22.267940, 22.309943, 23.719167, 24.151682], [49.200233, 54.278808, 54.836903, 55.942803, 90.527709], [22.846330, 22.949248, 23.900055, 25.140515, 25.468433]]
input_correlations: [[0.847979, -0.924451, 0.825382, -0.886493, -0.924304, -0.925612, 0.801670, 0.000000], [0.875785, -0.901895, 0.855498, -0.909277, -0.901727, -0.903212, 0.833361, 0.000000], [-0.914297, 0.860851, -0.897060, 0.938937, 0.860620, 0.862472, -0.878209, 0.000000], [0.415891, -0.981430, 0.378962, -0.498788, -0.981505, -0.980793, 0.339601, 0.000000], [0.859283, -0.916071, 0.836915, -0.895443, -0.915890, -0.917293, 0.814388, 0.000000], [-0.718130, 0.983875, -0.689144, 0.774865, 0.983801, 0.984395, -0.658593, 0.000000], [0.890396, -0.888170, 0.870587, -0.920374, -0.888005, -0.889580, 0.850215, 0.000000]]
pre_activation_mean: [1.025061, 1.404363, -0.377163, -1.335726, 0.123756, 1.005863, -0.051318]
pre_activation_std: [2.369889, 2.724412, 1.021309, 1.664457, 1.370190, 3.023469, 1.474295]
### 10
mean: [-1.471021, 3.099739, -1.554615, -0.040255, 3.089183, -2.651369, -0.880620]
std: [1.600401, 4.086599, 1.436001, 0.420968, 2.926208, 3.849633, 3.825473]
fourier: [[25.715730, 28.966560, 29.277200, 30.040340, 132.391856], [63.309580, 63.539438, 64.019393, 73.624480, 278.976491], [22.120011, 23.041935, 23.256364, 27.156334, 139.915365], [5.870536, 5.974608, 6.065743, 6.292992, 8.758187], [45.706920, 49.491360, 51.796201, 58.174719, 278.026431], [61.782316, 69.523597, 70.396935, 74.000455, 238.623210], [58.962967, 61.150878, 65.847364, 66.254826, 79.255767]]
input_correlations: [[0.687892, 0.692286, -0.991866, -0.895707, 0.618428, -0.995392, 0.586842, 0.000000], [0.980814, 0.981935, -0.738427, -0.701537, 0.955558, -0.760204, 0.935386, 0.000000], [-0.980564, -0.981958, 0.718009, 0.690352, -0.946178, 0.736965, -0.917848, 0.000000], [0.337076, 0.331245, 0.557187, 0.445109, 0.419773, 0.528151, 0.445005, 0.000000], [0.999774, 0.999637, -0.576371, -0.568194, 0.991778, -0.602639, 0.976531, 0.000000], [0.650661, 0.655192, -0.996757, -0.894193, 0.580312, -0.999050, 0.549654, 0.000000], [-0.890119, -0.892820, 0.894572, 0.823686, -0.843485, 0.908855, -0.817555, 0.000000]]
pre_activation_mean: [-1.471021, 3.099739, -1.554615, -0.040255, 3.089183, -2.651369, -0.880620]
pre_activation_std: [1.600401, 4.086599, 1.436001, 0.420968, 2.926208, 3.849633, 3.825473]
### 12
mean: [-1.409259]
std: [2.112575]
fourier: [[33.160213, 33.373398, 35.541534, 36.323187, 126.833347]]
input_correlations: [[0.911656, -0.906256, 0.677199, 0.326296, -0.906609, 0.911790, 0.881214, 0.000000]]
pre_activation_mean: [-1.409259]
pre_activation_std: [2.112575]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
palindrome | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": -0.10679995268583298, "std": 0.06149068847298622, "fourier": [0.8562519060172391, 0.8738143460044544, 1.0854877439069557, 1.1178829485095032, 9.611996607724663], "input_correlations": [-0.4889261695848218, -0.6181620712716261, -0.7933948140742281, -0.3862203593694688, -0.48256978868926687, 0.0, 0.0, 0.0], "pre_activation_mean": -6.178030014038086, "pre_activation_std": 3.3793537616729736}, "1": {"mean": 3.6688342094421387, "std": 3.358137845993042, "fourier": [53.92148359134759, 56.653154450647804, 59.61506817575807, 66.33194645868772, 330.1950760417176], "input_correlations": [-0.5357846895196215, 0.05722053966609503, -0.25602451001959836, -0.2543277971974056, -0.8653674907313086, 0.0, 0.0, 0.0], "pre_activation_mean": -2.320816993713379, "pre_activation_std": 2.249664306640625}, "2": {"mean": 0.0333174504339695, "std": 0.15681828558444977, "fourier": [2.3767005624087507, 2.5745844270575855, 2.998570269206539, 3.0091976201361694, 3.0883892400669657], "input_correlations": [-0.43910137632431734, -0.05524247841113134, 0.1021898190681278, -0.33867212402094804, -0.8352450094754111, 0.0, 0.0, 0.0], "pre_activation_mean": -0.6611344218254089, "pre_activation_std": 1.95835280418396}, "3": {"mean": 0.04117912799119949, "std": 0.28930696845054626, "fourier": [4.258630665955052, 4.31383786788597, 4.320927334717922, 4.3979389190829705, 5.768082938863349], "input_correlations": [-0.8495634896938978, 0.001770588632974084, -0.06940350906951076, 0.17042990001716968, -0.5125830469306645, 0.0, 0.0, 0.0], "pre_activation_mean": -0.7096496820449829, "pre_activation_std": 2.647944211959839}, "4": {"mean": 3.139681577682495, "std": 2.8599865436553955, "fourier": [45.65304477581892, 48.2901434071867, 50.662999053473364, 56.55622848410653, 282.5713334195316], "input_correlations": [-0.1774478708671823, -0.6859742796144966, 0.17330108984749854, -0.7268765823051778, -0.3939715955255113, 0.0, 0.0, 0.0], "pre_activation_mean": -2.3303134441375732, "pre_activation_std": 3.2568511962890625}, "5": {"mean": -0.08292616903781891, "std": 0.06339747458696365, "fourier": [0.9169214434221735, 1.043124811877884, 1.067244025299657, 1.4017558083324095, 7.463355017928734], "input_correlations": [-0.7961265248234729, -0.053682172650714795, -0.267221485195104, 0.033735839667966755, -0.7071991182367936, 0.0, 0.0, 0.0], "pre_activation_mean": -2.64652419090271, "pre_activation_std": 4.401027679443359}, "6": {"mean": 1.2389642000198364, "std": 2.304276704788208, "fourier": [36.6751033339255, 39.90903769924204, 42.6507866123644, 44.50878725634268, 111.50676783010385], "input_correlations": [-0.26527504980633526, -0.5630161689994317, -0.3049015999152852, -0.3976876040974047, -0.8179602226924798, 0.0, 0.0, 0.0], "pre_activation_mean": -1.4346203804016113, "pre_activation_std": 0.844576895236969}}, "layer_info": {"num_neurons": 7, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", 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0.108838, -1.135583]], "network.4.bias": [0.519001, -0.570377, -0.364399, 0.000886, -0.55401, -0.48457, -0.161401], "network.6.weight": [[0.656429, -0.649767, -1.075547, -0.254704, -0.845249, -0.351179, -0.27226], [-0.316572, 0.648012, -0.037822, -0.059941, 0.236134, 0.686881, 0.710163], [0.861074, -0.70442, -0.68249, -0.411499, -0.552574, -0.261632, -0.58918], [-0.079963, 0.457154, 0.710123, -1.047284, 0.645448, 0.267935, -0.558358], [-0.269345, 0.053551, 0.372948, 0.368612, 0.082484, -0.225469, 0.324728], [0.041461, 0.627862, 0.323765, 0.491917, 0.360927, 1.38679, 0.232641], [0.494348, -0.420137, -0.348972, -0.111032, -0.739599, -0.745217, -0.286738]], "network.6.bias": [0.56179, 0.283011, 0.764556, -0.736984, 0.396928, 0.171586, 0.164923], "network.8.weight": [[0.847329, -0.165841, 0.677764, -0.78068, -0.282508, -0.601578, 0.706608], [1.032283, -0.371188, 1.172119, -0.959113, -0.126604, -0.593829, 0.461667], [-0.60714, 0.159538, -0.497883, 0.11611, -0.278534, 0.454409, -0.026236], [-0.229881, -0.407365, -0.073205, 0.053938, -0.501399, -0.312649, -0.758964], [0.760466, -0.221054, 0.288729, 0.158251, -0.015944, -0.342373, 0.359867], [-0.326029, 0.718565, -0.45904, 0.093084, 0.524952, 0.488431, -0.690325], [0.767913, 0.039353, 0.437896, 0.493568, -0.448924, -0.171572, 0.628516]], "network.8.bias": [0.818028, 0.848126, 0.072548, 0.052276, -0.07606, 0.140771, -0.281602], "network.10.weight": [[0.021931, 0.266779, 0.36099, -0.358916, -0.230742, -0.587446, -0.283575], [0.862065, 1.066176, -0.969611, 0.138067, 0.645466, -0.17587, -0.130908], [-0.46675, -0.949026, 0.044193, -0.635463, 1.067391, 0.062264, 0.682605], [-0.023297, 0.188642, 0.761664, 0.396583, 0.148712, 0.014555, 0.075637], [0.831148, 0.986911, -0.244731, 0.210655, 0.246962, 0.077012, -0.116005], [0.566163, -0.063433, 0.316829, -0.714945, -0.725768, -1.380225, -0.062319], [-0.442854, -0.882596, 0.215222, -0.867325, 0.147959, 0.763075, 0.056322]], "network.10.bias": [-1.061658, -0.144889, -0.042807, -0.57096, -0.217571, -1.225204, 0.193468], "network.12.weight": [[0.288868, -0.210652, -0.004938, -0.169185, -0.162567, 0.572792, 0.500927]], "network.12.bias": [-0.661149]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.697492390871048, "train_acc": 0.585, "val_loss": 0.7135833501815796, "val_acc": 0.48}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6806480884552002, "train_acc": 0.585, "val_loss": 0.6081570386886597, "val_acc": 0.76}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6392010152339935, "train_acc": 0.67, "val_loss": 0.5557979345321655, "val_acc": 0.8}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.6491268277168274, "train_acc": 0.72, "val_loss": 0.7357564568519592, "val_acc": 0.48}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6945227384567261, "train_acc": 0.51, "val_loss": 0.6851651072502136, "val_acc": 0.5}, {"stage": "improved", "epoch": 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"train_acc": 0.855, "val_loss": 0.2102137804031372, "val_acc": 0.96}], "summary": {"total_epochs": 12, "degraded_epochs": 2, "improved_epochs": 10, "patterns": ["palindrome"], "degraded_stage": {"initial_val_loss": 0.7135833501815796, "final_val_loss": 0.6081570386886597, "initial_val_acc": 0.48, "final_val_acc": 0.76, "best_val_acc": 0.76}, "improved_stage": {"initial_val_loss": 0.5557979345321655, "final_val_loss": 0.2102137804031372, "initial_val_acc": 0.8, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 10}, "improvement": 0.19999999999999996, "first_improvement_epoch": 1}} |
90 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.7, "improved_accuracy": 0.96, "improvement": 0.26, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4908, "learning_rate": 0.07820043132053234, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.151775,
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-0.394961
],
[
-1.526408,
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-0.733527,
0.243077,
0.516664
],
[
1.040068,
0.745128,
0.10029,
-0.250349,
-0.36209
],
[
-1.208881,
-1.83781,
-0.555866,
0.16734,
0.453252
],
[
-1.170496,
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-0.165209,
-0.313235,
0.633155
]
],
"network.0.bias": [
-0.2225,
0.163213,
0.150874,
0.680023,
0.526579
],
"network.2.weight": [
[
-0.019745,
0.47392,
-0.262008,
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-0.788782
],
[
0.366043,
0.487286,
-0.382665,
0.296354,
-0.87448
],
[
0.004636,
0.901792,
-0.658125,
0.54671,
0.331506
],
[
0.272861,
0.393725,
-0.800451,
0.471096,
0.313144
],
[
0.20717,
0.497016,
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1.168301,
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]
],
"network.2.bias": [
0.127826,
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],
"network.4.weight": [
[
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],
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0.09016,
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],
[
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],
[
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],
[
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]
],
"network.4.bias": [
-0.137681,
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],
"network.6.weight": [
[
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],
[
1.142963,
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0.077722,
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],
[
0.480996,
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0.064129,
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],
[
0.195317,
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0.156471,
0.39103,
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],
[
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],
"network.6.bias": [
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"network.8.weight": [
[
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0.041019,
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[
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[
0.087971,
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[
0.218746,
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],
"network.8.bias": [
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"network.10.weight": [
[
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[
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[
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],
"network.10.bias": [
0.027548,
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"network.12.weight": [
[
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]
],
"network.12.bias": [
-0.338725
]
}
## Activation Signature
### 0
mean: [0.217181, 0.300467, 1.246682, 0.000000, 0.000000]
std: [0.509028, 0.850975, 0.511709, 0.000000, 0.000000]
fourier: [[7.939391, 8.083209, 8.201479, 8.806945, 19.546268], [13.088106, 13.151186, 13.506856, 14.744156, 27.042064], [7.986006, 8.745044, 8.813929, 10.005923, 112.201381], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.528793, -0.319335, -0.428898, -0.345280, -0.875715, 0.000000, 0.000000, 0.000000], [-0.848287, -0.664769, -0.550310, 0.025435, 0.034506, 0.000000, 0.000000, 0.000000], [0.864584, 0.664967, 0.347271, -0.091783, -0.110650, 0.000000, 0.000000, 0.000000], [-0.733953, -0.840070, -0.469646, -0.103998, 0.041952, 0.000000, 0.000000, 0.000000], [-0.730463, -0.828465, -0.326414, -0.276488, 0.139186, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.355093, -4.093146, 2.029026, -4.416540, -3.473012]
pre_activation_std: [0.961840, 4.793637, 2.929679, 5.158249, 4.120988]
### 2
mean: [-0.487161, -0.833621, -0.933826, -1.206863, -0.900774]
std: [0.714184, 1.076871, 2.287021, 2.451660, 2.891861]
fourier: [[10.837158, 11.702859, 12.561414, 13.293384, 43.844461], [16.718751, 17.987434, 18.185934, 19.004108, 75.025885], [33.891864, 34.518548, 40.661710, 44.232424, 84.044358], [37.393772, 40.869063, 41.800046, 45.121627, 108.617680], [45.124959, 45.339472, 51.212928, 54.071638, 81.069624]]
input_correlations: [[0.000000, 0.274105, -0.965207, 0.315227, 0.207670, 0.000000, 0.000000, 0.000000], [0.000000, 0.345034, -0.972877, 0.397864, 0.304212, 0.000000, 0.000000, 0.000000], [0.000000, 0.614853, -0.904131, 0.644560, 0.632356, 0.000000, 0.000000, 0.000000], [0.000000, 0.459750, -0.967120, 0.503868, 0.509107, 0.000000, 0.000000, 0.000000], [0.000000, 0.578375, -0.918737, 0.626728, 0.607865, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.487161, -0.833621, -0.933826, -1.206863, -0.900774]
pre_activation_std: [0.714184, 1.076871, 2.287021, 2.451660, 2.891861]
### 4
mean: [0.560940, -0.374253, -0.127672, -0.881928, -0.471065]
std: [1.699794, 0.812808, 0.227801, 0.883387, 0.493151]
fourier: [[27.012537, 28.040057, 28.317785, 29.300380, 50.484621], [13.420725, 13.739502, 14.077182, 15.441161, 33.682771], [3.534572, 3.653979, 3.808572, 3.922991, 11.490452], [14.354657, 14.645557, 15.471396, 15.501158, 79.373512], [8.271619, 8.397846, 8.402867, 9.906696, 42.395844]]
input_correlations: [[0.375992, 0.631456, 0.978379, 0.986058, 0.984064, 0.000000, 0.000000, 0.000000], [-0.533715, -0.748474, -0.987106, -0.997685, -0.999916, 0.000000, 0.000000, 0.000000], [-0.351898, -0.603380, -0.972064, -0.981400, -0.977205, 0.000000, 0.000000, 0.000000], [-0.508160, -0.738773, -0.994465, -0.998742, -0.997887, 0.000000, 0.000000, 0.000000], [-0.536148, -0.736510, -0.976176, -0.994452, -0.998072, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.560940, -0.374253, -0.127672, -0.881928, -0.471065]
pre_activation_std: [1.699794, 0.812808, 0.227801, 0.883387, 0.493151]
### 6
mean: [-0.075658, 0.945215, 0.158317, 0.454634, -0.525249]
std: [0.070223, 1.905230, 0.801782, 0.325578, 0.624803]
fourier: [[1.101383, 1.137979, 1.142204, 1.213827, 6.809250], [29.881885, 30.874759, 30.989395, 32.932631, 85.069368], [12.575268, 12.993102, 13.041345, 13.859122, 14.248573], [5.106405, 5.276074, 5.295663, 5.627736, 40.917014], [9.799493, 10.125097, 10.162691, 10.799957, 47.272416]]
input_correlations: [[-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.075658, 0.945215, 0.158317, 0.454634, -0.525249]
pre_activation_std: [0.070223, 1.905230, 0.801782, 0.325578, 0.624803]
### 8
mean: [-0.819557, -0.859091, 0.647365, -0.429139, -0.592541]
std: [0.751410, 0.580273, 1.784712, 0.567373, 0.418927]
fourier: [[11.790874, 12.206156, 12.237044, 12.987434, 73.760096], [9.098299, 9.389151, 9.431041, 10.030699, 77.318153], [27.900844, 28.471745, 28.795665, 30.859783, 58.262833], [8.916997, 9.277874, 9.291334, 9.803540, 38.622525], [6.567160, 6.771693, 6.805224, 7.241831, 53.328702]]
input_correlations: [[0.000000, -0.999996, -0.997363, -0.999996, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999999, -0.997671, -0.999999, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999852, 0.998607, 0.999852, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999931, -0.996664, -0.999931, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999996, -0.997746, -0.999996, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.819557, -0.859091, 0.647365, -0.429139, -0.592541]
pre_activation_std: [0.751410, 0.580273, 1.784712, 0.567373, 0.418927]
### 10
mean: [0.217181, 0.248578, 1.095579, -0.111063, -0.890631]
std: [0.509028, 0.869774, 1.159124, 0.012571, 0.666966]
fourier: [[7.939391, 8.083209, 8.201479, 8.806945, 19.546268], [13.566010, 13.811752, 14.013838, 15.048397, 22.372025], [18.079045, 18.406538, 18.675853, 20.054581, 98.602093], [0.196078, 0.199630, 0.202551, 0.217504, 9.995659], [10.402782, 10.591223, 10.746189, 11.539517, 80.156753]]
input_correlations: [[0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.217181, 0.248578, 1.095579, -0.111063, -0.890631]
pre_activation_std: [0.509028, 0.869774, 1.159124, 0.012571, 0.666966]
### 12
mean: [-2.441458]
std: [1.507652]
fourier: [[24.586042, 25.158315, 27.503244, 28.548134, 219.731177]]
input_correlations: [[0.913753, 0.903381, -0.958036, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.441458]
pre_activation_std: [1.507652]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.151775,
-0.059857,
-0.068186,
-0.095639,
-0.394961
],
[
-1.526408,
-1.088263,
-0.733527,
0.243077,
0.516664
],
[
1.040068,
0.745128,
0.10029,
-0.250349,
-0.36209
],
[
-1.208881,
-1.83781,
-0.555866,
0.16734,
0.453252
],
[
-1.170496,
-1.266062,
-0.165209,
-0.313235,
0.633155
]
],
"network.0.bias": [
-0.2225,
0.163213,
0.150874,
0.680023,
0.526579
],
"network.2.weight": [
[
-0.019745,
0.47392,
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],
[
0.366043,
0.487286,
-0.382665,
0.296354,
-0.87448
],
[
0.004636,
0.901792,
-0.658125,
0.54671,
0.331506
],
[
0.272861,
0.393725,
-0.800451,
0.471096,
0.313144
],
[
0.20717,
0.497016,
-0.849254,
1.168301,
0.460068
]
],
"network.2.bias": [
0.127826,
0.01191,
0.18193,
0.331307,
0.551553
],
"network.4.weight": [
[
-1.358414,
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0.53074,
0.299494,
0.878183
],
[
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0.09016,
-0.60906
],
[
0.009507,
0.359418,
-0.105441,
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-0.078879
],
[
-0.157251,
0.298345,
-0.358622,
-0.031719,
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],
[
-0.220715,
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]
],
"network.4.bias": [
-0.137681,
-0.011755,
-0.033063,
-0.516093,
-0.236089
],
"network.6.weight": [
[
-0.042127,
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-0.470258,
-0.196322,
0.128895
],
[
1.142963,
0.374313,
0.077722,
-0.015715,
-0.122353
],
[
0.480996,
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0.064129,
-0.445011,
-0.308509
],
[
0.195317,
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0.156471,
0.39103,
0.141808
],
[
-0.374824,
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0.082211,
0.052028
]
],
"network.6.bias": [
-0.048549,
0.209718,
-0.151204,
0.328947,
-0.28405
],
"network.8.weight": [
[
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0.037718,
-0.124911,
-0.107027
],
[
0.347513,
-0.304223,
-0.018397,
0.041019,
-0.17585
],
[
0.260371,
0.676627,
0.57434,
0.177754,
-0.158506
],
[
0.087971,
-0.242801,
0.124935,
-0.613978,
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],
[
0.218746,
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0.177095,
0.129602
]
],
"network.8.bias": [
-0.405845,
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-0.22435,
0.046574,
-0.439126
],
"network.10.weight": [
[
0.050986,
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0.286138,
0.318,
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],
[
-0.156583,
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0.488923,
-0.036744,
0.029508
],
[
0.240726,
0.158995,
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0.227197,
0.268918
],
[
-0.176356,
0.039516,
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0.005378,
-0.411836
],
[
0.183437,
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-0.190498,
0.32837
]
],
"network.10.bias": [
0.027548,
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1.527398,
-0.10638,
-0.642159
],
"network.12.weight": [
[
0.236935,
0.620526,
-1.877494,
0.326812,
0.013019
]
],
"network.12.bias": [
-0.338725
]
}
## Activation Signature
### 0
mean: [0.217181, 0.300467, 1.246682, 0.000000, 0.000000]
std: [0.509028, 0.850975, 0.511709, 0.000000, 0.000000]
fourier: [[7.939391, 8.083209, 8.201479, 8.806945, 19.546268], [13.088106, 13.151186, 13.506856, 14.744156, 27.042064], [7.986006, 8.745044, 8.813929, 10.005923, 112.201381], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.528793, -0.319335, -0.428898, -0.345280, -0.875715, 0.000000, 0.000000, 0.000000], [-0.848287, -0.664769, -0.550310, 0.025435, 0.034506, 0.000000, 0.000000, 0.000000], [0.864584, 0.664967, 0.347271, -0.091783, -0.110650, 0.000000, 0.000000, 0.000000], [-0.733953, -0.840070, -0.469646, -0.103998, 0.041952, 0.000000, 0.000000, 0.000000], [-0.730463, -0.828465, -0.326414, -0.276488, 0.139186, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.355093, -4.093146, 2.029026, -4.416540, -3.473012]
pre_activation_std: [0.961840, 4.793637, 2.929679, 5.158249, 4.120988]
### 2
mean: [-0.487161, -0.833621, -0.933826, -1.206863, -0.900774]
std: [0.714184, 1.076871, 2.287021, 2.451660, 2.891861]
fourier: [[10.837158, 11.702859, 12.561414, 13.293384, 43.844461], [16.718751, 17.987434, 18.185934, 19.004108, 75.025885], [33.891864, 34.518548, 40.661710, 44.232424, 84.044358], [37.393772, 40.869063, 41.800046, 45.121627, 108.617680], [45.124959, 45.339472, 51.212928, 54.071638, 81.069624]]
input_correlations: [[0.000000, 0.274105, -0.965207, 0.315227, 0.207670, 0.000000, 0.000000, 0.000000], [0.000000, 0.345034, -0.972877, 0.397864, 0.304212, 0.000000, 0.000000, 0.000000], [0.000000, 0.614853, -0.904131, 0.644560, 0.632356, 0.000000, 0.000000, 0.000000], [0.000000, 0.459750, -0.967120, 0.503868, 0.509107, 0.000000, 0.000000, 0.000000], [0.000000, 0.578375, -0.918737, 0.626728, 0.607865, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.487161, -0.833621, -0.933826, -1.206863, -0.900774]
pre_activation_std: [0.714184, 1.076871, 2.287021, 2.451660, 2.891861]
### 4
mean: [0.560940, -0.374253, -0.127672, -0.881928, -0.471065]
std: [1.699794, 0.812808, 0.227801, 0.883387, 0.493151]
fourier: [[27.012537, 28.040057, 28.317785, 29.300380, 50.484621], [13.420725, 13.739502, 14.077182, 15.441161, 33.682771], [3.534572, 3.653979, 3.808572, 3.922991, 11.490452], [14.354657, 14.645557, 15.471396, 15.501158, 79.373512], [8.271619, 8.397846, 8.402867, 9.906696, 42.395844]]
input_correlations: [[0.375992, 0.631456, 0.978379, 0.986058, 0.984064, 0.000000, 0.000000, 0.000000], [-0.533715, -0.748474, -0.987106, -0.997685, -0.999916, 0.000000, 0.000000, 0.000000], [-0.351898, -0.603380, -0.972064, -0.981400, -0.977205, 0.000000, 0.000000, 0.000000], [-0.508160, -0.738773, -0.994465, -0.998742, -0.997887, 0.000000, 0.000000, 0.000000], [-0.536148, -0.736510, -0.976176, -0.994452, -0.998072, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.560940, -0.374253, -0.127672, -0.881928, -0.471065]
pre_activation_std: [1.699794, 0.812808, 0.227801, 0.883387, 0.493151]
### 6
mean: [-0.075658, 0.945215, 0.158317, 0.454634, -0.525249]
std: [0.070223, 1.905230, 0.801782, 0.325578, 0.624803]
fourier: [[1.101383, 1.137979, 1.142204, 1.213827, 6.809250], [29.881885, 30.874759, 30.989395, 32.932631, 85.069368], [12.575268, 12.993102, 13.041345, 13.859122, 14.248573], [5.106405, 5.276074, 5.295663, 5.627736, 40.917014], [9.799493, 10.125097, 10.162691, 10.799957, 47.272416]]
input_correlations: [[-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [-1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.075658, 0.945215, 0.158317, 0.454634, -0.525249]
pre_activation_std: [0.070223, 1.905230, 0.801782, 0.325578, 0.624803]
### 8
mean: [-0.819557, -0.859091, 0.647365, -0.429139, -0.592541]
std: [0.751410, 0.580273, 1.784712, 0.567373, 0.418927]
fourier: [[11.790874, 12.206156, 12.237044, 12.987434, 73.760096], [9.098299, 9.389151, 9.431041, 10.030699, 77.318153], [27.900844, 28.471745, 28.795665, 30.859783, 58.262833], [8.916997, 9.277874, 9.291334, 9.803540, 38.622525], [6.567160, 6.771693, 6.805224, 7.241831, 53.328702]]
input_correlations: [[0.000000, -0.999996, -0.997363, -0.999996, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999999, -0.997671, -0.999999, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999852, 0.998607, 0.999852, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999931, -0.996664, -0.999931, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999996, -0.997746, -0.999996, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.819557, -0.859091, 0.647365, -0.429139, -0.592541]
pre_activation_std: [0.751410, 0.580273, 1.784712, 0.567373, 0.418927]
### 10
mean: [0.217181, 0.248578, 1.095579, -0.111063, -0.890631]
std: [0.509028, 0.869774, 1.159124, 0.012571, 0.666966]
fourier: [[7.939391, 8.083209, 8.201479, 8.806945, 19.546268], [13.566010, 13.811752, 14.013838, 15.048397, 22.372025], [18.079045, 18.406538, 18.675853, 20.054581, 98.602093], [0.196078, 0.199630, 0.202551, 0.217504, 9.995659], [10.402782, 10.591223, 10.746189, 11.539517, 80.156753]]
input_correlations: [[0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.217181, 0.248578, 1.095579, -0.111063, -0.890631]
pre_activation_std: [0.509028, 0.869774, 1.159124, 0.012571, 0.666966]
### 12
mean: [-2.441458]
std: [1.507652]
fourier: [[24.586042, 25.158315, 27.503244, 28.548134, 219.731177]]
input_correlations: [[0.913753, 0.903381, -0.958036, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.441458]
pre_activation_std: [1.507652]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
sorted_ascending | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.2171807438135147, "std": 0.5090276598930359, "fourier": [7.939390764865437, 8.083209075989215, 8.201478588439686, 8.80694527847722, 19.54626815766096], "input_correlations": [-0.5287927462649599, -0.31933526624593556, -0.42889845198814314, -0.34527969626715976, -0.8757152708836471, 0.0, 0.0, 0.0], "pre_activation_mean": -1.3550925254821777, "pre_activation_std": 0.9618397355079651}, "1": {"mean": 0.3004673719406128, "std": 0.8509754538536072, "fourier": [13.088105793541564, 13.151185727656795, 13.506856038965282, 14.744156367360311, 27.04206383228302], "input_correlations": [-0.8482865386241938, -0.6647687420947416, -0.5503095664078651, 0.02543527041185939, 0.034506112503702745, 0.0, 0.0, 0.0], "pre_activation_mean": -4.093146324157715, "pre_activation_std": 4.793636798858643}, "2": {"mean": 1.246682047843933, "std": 0.5117093920707703, "fourier": [7.9860062696449665, 8.74504394256613, 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91 | {"target_pattern": "contains_abc", "degraded_accuracy": 0.78, "improved_accuracy": 0.98, "improvement": 0.19999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 5156, "learning_rate": 0.08113196529052372, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "contains_abc", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["contains_abc"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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}
## Activation Signature
### 0
mean: [0.878782, 0.997212, 0.304048, 1.101071, -0.110161]
std: [0.639066, 0.690582, 0.783094, 0.750054, 0.022915]
fourier: [[9.423255, 9.769177, 10.729156, 14.427515, 79.090403], [9.469639, 10.491506, 11.429490, 15.770928, 89.749116], [11.449973, 11.563492, 12.511280, 17.517833, 27.364276], [10.347887, 11.439272, 12.428087, 17.241669, 99.096402], [0.341898, 0.350354, 0.366715, 0.408092, 9.914482]]
input_correlations: [[0.753805, 0.421986, 0.761844, 0.331189, 0.330943, 0.000000, 0.000000, 0.000000], [0.914239, 0.585910, 0.567721, 0.104763, 0.127263, 0.000000, 0.000000, 0.000000], [-0.268592, -0.031836, -0.945977, 0.290179, -0.084453, 0.000000, 0.000000, 0.000000], [-0.928792, -0.550638, -0.180611, -0.255450, -0.157428, 0.000000, 0.000000, 0.000000], [-0.781839, -0.751777, -0.518311, -0.388128, -0.236312, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.041461, 2.410526, -1.068602, -2.392610, -4.612734]
pre_activation_std: [2.053657, 2.688764, 2.593281, 2.839166, 3.612227]
### 2
mean: [1.963046, -0.972576, -1.723790, 1.269040, -1.938342]
std: [1.491473, 1.595804, 1.100671, 1.564256, 2.429608]
fourier: [[24.154367, 24.815971, 26.737061, 30.001102, 176.674154], [25.939466, 27.423950, 28.817631, 30.910699, 87.531865], [16.809861, 17.146506, 18.223576, 23.050181, 155.141137], [26.118366, 27.999578, 28.460089, 30.785313, 114.213592], [39.806768, 40.661435, 41.178153, 46.715595, 174.450828]]
input_correlations: [[0.691253, 0.744502, 0.393681, 0.010554, 0.024732, 0.000000, 0.000000, 0.000000], [-0.926104, -0.850523, 0.661245, -0.220340, -0.064309, 0.000000, 0.000000, 0.000000], [-0.961827, -0.751886, 0.206659, -0.188364, -0.069664, 0.000000, 0.000000, 0.000000], [0.927987, 0.974687, -0.138813, 0.092987, 0.057071, 0.000000, 0.000000, 0.000000], [-0.930984, -0.964449, 0.513704, -0.164736, -0.070100, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.963046, -0.972576, -1.723790, 1.269040, -1.938342]
pre_activation_std: [1.491473, 1.595804, 1.100671, 1.564256, 2.429608]
### 4
mean: [-0.245139, -0.886681, -0.330246, -0.387370, -0.463189]
std: [0.359145, 1.508744, 0.716871, 0.816987, 0.882026]
fourier: [[5.416957, 5.764088, 5.982561, 7.052679, 22.062481], [22.352977, 23.817268, 24.627978, 30.611892, 79.801259], [10.096079, 11.216309, 11.453183, 14.553596, 29.722113], [12.615884, 12.989936, 13.702128, 15.497430, 34.863294], [12.521807, 14.186073, 14.353250, 17.859884, 41.687050]]
input_correlations: [[-0.975187, -0.261058, -0.548304, -0.890612, -0.194608, 0.000000, 0.000000, 0.000000], [-0.947580, -0.529038, -0.439640, -0.709029, -0.473345, 0.000000, 0.000000, 0.000000], [-0.926066, -0.550546, -0.404477, -0.700912, -0.508485, 0.000000, 0.000000, 0.000000], [-0.844848, -0.717205, -0.264657, -0.520888, -0.657819, 0.000000, 0.000000, 0.000000], [-0.923385, -0.585591, -0.397920, -0.651240, -0.540190, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.245139, -0.886681, -0.330246, -0.387370, -0.463189]
pre_activation_std: [0.359145, 1.508744, 0.716871, 0.816987, 0.882026]
### 6
mean: [0.792617, 0.884500, 0.159259, 0.990440, -0.294147]
std: [1.012567, 1.099778, 0.921741, 1.131442, 0.089498]
fourier: [[14.241113, 14.930159, 15.059260, 23.611692, 71.335562], [15.235943, 15.902586, 16.407553, 25.630596, 79.604968], [12.797581, 13.132913, 13.672024, 14.333353, 21.467239], [15.719864, 16.445021, 16.964619, 26.460754, 89.139597], [1.289866, 1.353267, 1.419891, 1.546271, 26.473210]]
input_correlations: [[-0.852619, -0.966984, -0.988679, -0.986865, -0.996253, 0.000000, 0.000000, 0.000000], [-0.834504, -0.977119, -0.981913, -0.982420, -0.997263, 0.000000, 0.000000, 0.000000], [0.818414, 0.983446, 0.975791, 0.977918, 0.997015, 0.000000, 0.000000, 0.000000], [-0.844728, -0.973076, -0.985196, -0.983169, -0.997341, 0.000000, 0.000000, 0.000000], [-0.119053, -0.756895, -0.497401, -0.596382, -0.641784, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.792617, 0.884500, 0.159259, 0.990440, -0.294147]
pre_activation_std: [1.012567, 1.099778, 0.921741, 1.131442, 0.089498]
### 8
mean: [-3.335926]
std: [3.088738]
fourier: [[42.508716, 46.976229, 47.329671, 72.629472, 300.233313]]
input_correlations: [[-0.982421, -0.987176, 0.905133, -0.988986, -0.455216, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.335926]
pre_activation_std: [3.088738]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| contains_abc | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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"network.2.bias": [
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}
## Activation Signature
### 0
mean: [0.878782, 0.997212, 0.304048, 1.101071, -0.110161]
std: [0.639066, 0.690582, 0.783094, 0.750054, 0.022915]
fourier: [[9.423255, 9.769177, 10.729156, 14.427515, 79.090403], [9.469639, 10.491506, 11.429490, 15.770928, 89.749116], [11.449973, 11.563492, 12.511280, 17.517833, 27.364276], [10.347887, 11.439272, 12.428087, 17.241669, 99.096402], [0.341898, 0.350354, 0.366715, 0.408092, 9.914482]]
input_correlations: [[0.753805, 0.421986, 0.761844, 0.331189, 0.330943, 0.000000, 0.000000, 0.000000], [0.914239, 0.585910, 0.567721, 0.104763, 0.127263, 0.000000, 0.000000, 0.000000], [-0.268592, -0.031836, -0.945977, 0.290179, -0.084453, 0.000000, 0.000000, 0.000000], [-0.928792, -0.550638, -0.180611, -0.255450, -0.157428, 0.000000, 0.000000, 0.000000], [-0.781839, -0.751777, -0.518311, -0.388128, -0.236312, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.041461, 2.410526, -1.068602, -2.392610, -4.612734]
pre_activation_std: [2.053657, 2.688764, 2.593281, 2.839166, 3.612227]
### 2
mean: [1.963046, -0.972576, -1.723790, 1.269040, -1.938342]
std: [1.491473, 1.595804, 1.100671, 1.564256, 2.429608]
fourier: [[24.154367, 24.815971, 26.737061, 30.001102, 176.674154], [25.939466, 27.423950, 28.817631, 30.910699, 87.531865], [16.809861, 17.146506, 18.223576, 23.050181, 155.141137], [26.118366, 27.999578, 28.460089, 30.785313, 114.213592], [39.806768, 40.661435, 41.178153, 46.715595, 174.450828]]
input_correlations: [[0.691253, 0.744502, 0.393681, 0.010554, 0.024732, 0.000000, 0.000000, 0.000000], [-0.926104, -0.850523, 0.661245, -0.220340, -0.064309, 0.000000, 0.000000, 0.000000], [-0.961827, -0.751886, 0.206659, -0.188364, -0.069664, 0.000000, 0.000000, 0.000000], [0.927987, 0.974687, -0.138813, 0.092987, 0.057071, 0.000000, 0.000000, 0.000000], [-0.930984, -0.964449, 0.513704, -0.164736, -0.070100, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.963046, -0.972576, -1.723790, 1.269040, -1.938342]
pre_activation_std: [1.491473, 1.595804, 1.100671, 1.564256, 2.429608]
### 4
mean: [-0.245139, -0.886681, -0.330246, -0.387370, -0.463189]
std: [0.359145, 1.508744, 0.716871, 0.816987, 0.882026]
fourier: [[5.416957, 5.764088, 5.982561, 7.052679, 22.062481], [22.352977, 23.817268, 24.627978, 30.611892, 79.801259], [10.096079, 11.216309, 11.453183, 14.553596, 29.722113], [12.615884, 12.989936, 13.702128, 15.497430, 34.863294], [12.521807, 14.186073, 14.353250, 17.859884, 41.687050]]
input_correlations: [[-0.975187, -0.261058, -0.548304, -0.890612, -0.194608, 0.000000, 0.000000, 0.000000], [-0.947580, -0.529038, -0.439640, -0.709029, -0.473345, 0.000000, 0.000000, 0.000000], [-0.926066, -0.550546, -0.404477, -0.700912, -0.508485, 0.000000, 0.000000, 0.000000], [-0.844848, -0.717205, -0.264657, -0.520888, -0.657819, 0.000000, 0.000000, 0.000000], [-0.923385, -0.585591, -0.397920, -0.651240, -0.540190, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.245139, -0.886681, -0.330246, -0.387370, -0.463189]
pre_activation_std: [0.359145, 1.508744, 0.716871, 0.816987, 0.882026]
### 6
mean: [0.792617, 0.884500, 0.159259, 0.990440, -0.294147]
std: [1.012567, 1.099778, 0.921741, 1.131442, 0.089498]
fourier: [[14.241113, 14.930159, 15.059260, 23.611692, 71.335562], [15.235943, 15.902586, 16.407553, 25.630596, 79.604968], [12.797581, 13.132913, 13.672024, 14.333353, 21.467239], [15.719864, 16.445021, 16.964619, 26.460754, 89.139597], [1.289866, 1.353267, 1.419891, 1.546271, 26.473210]]
input_correlations: [[-0.852619, -0.966984, -0.988679, -0.986865, -0.996253, 0.000000, 0.000000, 0.000000], [-0.834504, -0.977119, -0.981913, -0.982420, -0.997263, 0.000000, 0.000000, 0.000000], [0.818414, 0.983446, 0.975791, 0.977918, 0.997015, 0.000000, 0.000000, 0.000000], [-0.844728, -0.973076, -0.985196, -0.983169, -0.997341, 0.000000, 0.000000, 0.000000], [-0.119053, -0.756895, -0.497401, -0.596382, -0.641784, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.792617, 0.884500, 0.159259, 0.990440, -0.294147]
pre_activation_std: [1.012567, 1.099778, 0.921741, 1.131442, 0.089498]
### 8
mean: [-3.335926]
std: [3.088738]
fourier: [[42.508716, 46.976229, 47.329671, 72.629472, 300.233313]]
input_correlations: [[-0.982421, -0.987176, 0.905133, -0.988986, -0.455216, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.335926]
pre_activation_std: [3.088738]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
contains_abc | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.8787822127342224, "std": 0.6390660405158997, "fourier": [9.423254908269907, 9.769176510897452, 10.729156007772657, 14.42751480950223, 79.09040271956474], "input_correlations": [0.7538054539720385, 0.42198577044563834, 0.7618439232007732, 0.3311889030697169, 0.3309428952830495, 0.0, 0.0, 0.0], "pre_activation_mean": 2.041461229324341, "pre_activation_std": 2.053657054901123}, "1": {"mean": 0.9972124099731445, "std": 0.6905816793441772, "fourier": [9.469638858569521, 10.49150596156476, 11.429489729439732, 15.77092821511581, 89.74911619722843], "input_correlations": [0.9142390943313652, 0.5859096666228221, 0.567720743509548, 0.10476277337587336, 0.1272625550611839, 0.0, 0.0, 0.0], "pre_activation_mean": 2.4105257987976074, "pre_activation_std": 2.6887643337249756}, "2": {"mean": 0.304047554731369, "std": 0.7830943465232849, "fourier": [11.449973079140378, 11.56349244514524, 12.511279513793163, 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"final_val_loss": 0.5578898191452026, "initial_val_acc": 0.74, "final_val_acc": 0.78, "best_val_acc": 0.78}, "improved_stage": {"initial_val_loss": 0.39677634835243225, "final_val_loss": 0.09608329087495804, "initial_val_acc": 0.84, "final_val_acc": 0.98, "best_val_acc": 0.98, "best_epoch": 11}, "improvement": 0.19999999999999996, "first_improvement_epoch": 3}} |
92 | {"target_pattern": "mountain_pattern", "degraded_accuracy": 0.58, "improved_accuracy": 0.92, "improvement": 0.3400000000000001, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 5234, "learning_rate": 0.05054527604583981, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "mountain_pattern", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["mountain_pattern"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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}
## Activation Signature
### 0
mean: [0.000000, 2.174926, 0.000000, 4.100346, 5.337180, 1.975439, 0.574136]
std: [0.000000, 1.651650, 0.000000, 3.384673, 4.133300, 0.790840, 0.294916]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [24.479783, 25.978197, 29.747734, 34.673297, 195.743382], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [51.270198, 54.233019, 61.901989, 70.878384, 369.031145], [61.602862, 65.540087, 74.971513, 86.897363, 480.346146], [13.060940, 14.065111, 14.313761, 14.775659, 177.789544], [4.781413, 5.115611, 5.266424, 5.615002, 51.672234]]
input_correlations: [[-0.869053, -0.602285, -0.064988, 0.142251, -0.088961, 0.000000, 0.000000, 0.000000], [-0.954948, -0.483840, -0.209626, 0.094810, -0.267971, 0.000000, 0.000000, 0.000000], [0.899889, 0.356225, 0.380246, -0.326936, 0.360196, 0.000000, 0.000000, 0.000000], [0.616879, -0.022411, 0.447275, -0.744326, 0.197111, 0.000000, 0.000000, 0.000000], [-0.891255, -0.071869, -0.055190, 0.174187, -0.431570, 0.000000, 0.000000, 0.000000], [-0.013927, 0.292282, 0.567627, -0.595332, -0.182978, 0.000000, 0.000000, 0.000000], [0.720765, -0.213540, -0.168996, -0.098013, 0.432402, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.645895, -1.561779, 1.392380, -0.403955, -0.499172, -0.021446, 0.233140]
pre_activation_std: [2.642227, 2.547140, 2.086405, 2.170976, 1.673139, 0.956070, 1.889385]
### 2
mean: [1.691260, -0.817489, 0.206619, 1.524639, -1.215975, -0.415123, 1.550951]
std: [2.634646, 0.471014, 0.714500, 1.447405, 0.792552, 1.276722, 1.188814]
fourier: [[42.930816, 43.382170, 46.426717, 60.044901, 152.213411], [6.802222, 6.830461, 7.048502, 7.177447, 73.574056], [10.213363, 10.264763, 12.191833, 13.588069, 18.595691], [22.436029, 22.944825, 27.386687, 27.983610, 137.217558], [11.565851, 12.807797, 13.153592, 20.030820, 109.437789], [18.752585, 19.343455, 19.798672, 25.674121, 37.361110], [20.449249, 20.792105, 22.446758, 22.812425, 139.585580]]
input_correlations: [[-0.441184, -0.334548, 0.972122, 0.896852, -0.477329, 0.064707, 0.833422, 0.000000], [-0.602244, -0.676490, 0.087522, 0.093920, -0.709703, -0.525306, 0.368184, 0.000000], [0.888213, 0.702830, -0.641399, -0.483918, 0.274201, -0.288328, -0.280740, 0.000000], [-0.520224, -0.348079, 0.955610, 0.892646, -0.285003, 0.145726, 0.797683, 0.000000], [-0.359529, -0.397686, -0.508984, -0.714636, -0.156689, -0.106717, -0.631582, 0.000000], [0.746318, 0.599629, -0.911641, -0.724318, 0.511487, -0.020102, -0.800606, 0.000000], [-0.457307, -0.291859, 0.994932, 0.860263, -0.348629, 0.112707, 0.788000, 0.000000]]
pre_activation_mean: [1.691260, -0.817489, 0.206619, 1.524639, -1.215975, -0.415123, 1.550951]
pre_activation_std: [2.634646, 0.471014, 0.714500, 1.447405, 0.792552, 1.276722, 1.188814]
### 4
mean: [-1.442374, -0.991556, -1.857419, 2.083087, -0.826371, -0.917302, -2.043581]
std: [1.241327, 0.909243, 1.464240, 2.199901, 1.994370, 1.294083, 1.597127]
fourier: [[20.259671, 20.813021, 23.690523, 24.960987, 129.813694], [15.275605, 15.713200, 16.001236, 19.361692, 89.240007], [24.777935, 26.094949, 26.857396, 29.924132, 167.167689], [35.619469, 35.908424, 40.436246, 46.109736, 187.477880], [28.852871, 31.030276, 35.321396, 42.082200, 74.373377], [18.987516, 19.748860, 23.187407, 25.904671, 82.557216], [26.334651, 27.764536, 30.506471, 31.457775, 183.922237]]
input_correlations: [[-0.993255, -0.382460, 0.457956, -0.988265, 0.000000, 0.374488, -0.992331, 0.000000], [-0.993962, -0.405790, 0.368614, -0.980668, 0.000000, 0.334602, -0.980959, 0.000000], [-0.995117, -0.378778, 0.385363, -0.977997, 0.000000, 0.325981, -0.992186, 0.000000], [0.991860, 0.378408, -0.504371, 0.991111, 0.000000, -0.446850, 0.989941, 0.000000], [-0.958108, -0.358549, 0.641426, -0.977137, 0.000000, 0.596209, -0.959804, 0.000000], [-0.933646, -0.348746, 0.693113, -0.970045, 0.000000, 0.635419, -0.943173, 0.000000], [-0.990942, -0.395749, 0.378874, -0.979144, 0.000000, 0.290467, -0.985638, 0.000000]]
pre_activation_mean: [-1.442374, -0.991556, -1.857419, 2.083087, -0.826371, -0.917302, -2.043581]
pre_activation_std: [1.241327, 0.909243, 1.464240, 2.199901, 1.994370, 1.294083, 1.597127]
### 6
mean: [1.519537, -0.711025, 0.801803, 1.783603, -0.330310, -0.170295, 0.072103]
std: [1.471461, 0.137488, 0.910669, 1.379761, 0.950467, 0.514024, 0.722701]
fourier: [[23.161240, 23.752410, 27.013211, 30.796949, 136.758338], [1.925230, 2.014718, 2.251304, 2.531081, 63.992249], [13.443887, 13.993911, 15.971535, 19.441129, 72.162304], [20.797314, 21.832170, 24.934154, 29.250123, 160.524232], [13.733790, 13.873531, 15.300635, 19.870811, 29.727933], [7.425335, 7.472825, 7.998223, 9.791626, 15.326556], [10.335873, 10.424593, 11.030212, 12.632613, 15.238348]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.998603, -0.498793, -0.398995, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.161833, -0.945168, -0.961489, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.978696, -0.623661, -0.537377, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.993423, -0.550910, -0.458424, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.925620, 0.755521, 0.671482, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.780365, 0.907949, 0.846442, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.975253, -0.638468, -0.538279, 0.000000, 0.000000]]
pre_activation_mean: [1.519537, -0.711025, 0.801803, 1.783603, -0.330310, -0.170295, 0.072103]
pre_activation_std: [1.471461, 0.137488, 0.910669, 1.379761, 0.950467, 0.514024, 0.722701]
### 8
mean: [2.498073, 0.297371, -1.185193, 2.736010, 1.981454, 2.272354, -1.360479]
std: [1.970444, 0.142582, 0.420497, 2.161823, 1.620427, 1.712154, 2.281634]
fourier: [[28.690617, 30.850276, 35.223981, 42.026383, 224.826530], [2.023972, 2.178785, 2.495478, 2.681861, 26.763387], [7.320063, 7.335046, 7.948586, 8.008919, 106.667362], [32.030379, 34.198363, 39.030466, 45.757302, 246.240951], [23.802196, 25.363921, 29.052389, 34.251981, 178.330856], [26.543838, 27.479362, 31.407821, 35.735917, 204.511824], [33.602958, 34.304070, 39.118839, 48.537406, 122.443061]]
input_correlations: [[0.992233, 0.000000, 0.991594, 0.998464, -0.551222, -0.518687, 0.947812, 0.000000], [-0.487675, 0.000000, -0.474589, -0.428514, -0.552907, -0.573345, -0.649465, 0.000000], [-0.973828, 0.000000, -0.970911, -0.955680, 0.233375, 0.192057, -0.988305, 0.000000], [0.995454, 0.000000, 0.995122, 0.999589, -0.528132, -0.493707, 0.954833, 0.000000], [0.993915, 0.000000, 0.994238, 0.998986, -0.542542, -0.506833, 0.947898, 0.000000], [0.999547, 0.000000, 0.998842, 0.999108, -0.472995, -0.435990, 0.967647, 0.000000], [-0.973972, 0.000000, -0.975387, -0.987163, 0.637810, 0.604900, -0.908021, 0.000000]]
pre_activation_mean: [2.498073, 0.297371, -1.185193, 2.736010, 1.981454, 2.272354, -1.360479]
pre_activation_std: [1.970444, 0.142582, 0.420497, 2.161823, 1.620427, 1.712154, 2.281634]
### 10
mean: [-1.430216, 2.095937, -1.079472, 4.054352, 5.298249, 1.975439, 0.574136]
std: [1.112795, 1.775349, 0.498109, 3.444266, 4.185853, 0.790840, 0.294916]
fourier: [[18.697942, 18.984089, 21.010581, 21.908414, 128.719490], [26.292702, 26.432788, 29.903368, 38.006093, 188.634342], [8.474274, 8.890744, 9.006788, 9.278500, 97.152492], [50.813061, 54.092613, 61.921606, 72.804693, 364.891700], [61.578372, 65.492288, 74.993025, 88.606106, 476.842394], [13.060940, 14.065111, 14.313761, 14.775659, 177.789544], [4.781413, 5.115611, 5.266424, 5.615002, 51.672234]]
input_correlations: [[-0.974447, 0.589982, 0.000000, -0.976242, -0.975988, -0.985520, 0.274926, 0.000000], [0.984553, -0.239606, 0.000000, 0.983140, 0.983046, 0.973201, -0.629103, 0.000000], [-0.889005, 0.759307, 0.000000, -0.892687, -0.892593, -0.913571, 0.029882, 0.000000], [0.999650, -0.378234, 0.000000, 0.999423, 0.999221, 0.996552, -0.505847, 0.000000], [0.999358, -0.369619, 0.000000, 0.999058, 0.998883, 0.995753, -0.513932, 0.000000], [0.822514, -0.833379, 0.000000, 0.827086, 0.826602, 0.853141, 0.099978, 0.000000], [0.754922, -0.885523, 0.000000, 0.760178, 0.759649, 0.790441, 0.208934, 0.000000]]
pre_activation_mean: [-1.430216, 2.095937, -1.079472, 4.054352, 5.298249, 1.975439, 0.574136]
pre_activation_std: [1.112795, 1.775349, 0.498109, 3.444266, 4.185853, 0.790840, 0.294916]
### 12
mean: [-3.091383]
std: [3.489506]
fourier: [[50.090252, 53.497824, 61.063647, 74.225494, 278.224457]]
input_correlations: [[0.000000, -0.997121, 0.000000, -0.992433, -0.994850, -0.756586, -0.680193, 0.000000]]
pre_activation_mean: [-3.091383]
pre_activation_std: [3.489506]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| mountain_pattern | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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0.09027
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],
"network.2.bias": [
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"network.4.weight": [
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[
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}
## Activation Signature
### 0
mean: [0.000000, 2.174926, 0.000000, 4.100346, 5.337180, 1.975439, 0.574136]
std: [0.000000, 1.651650, 0.000000, 3.384673, 4.133300, 0.790840, 0.294916]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [24.479783, 25.978197, 29.747734, 34.673297, 195.743382], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [51.270198, 54.233019, 61.901989, 70.878384, 369.031145], [61.602862, 65.540087, 74.971513, 86.897363, 480.346146], [13.060940, 14.065111, 14.313761, 14.775659, 177.789544], [4.781413, 5.115611, 5.266424, 5.615002, 51.672234]]
input_correlations: [[-0.869053, -0.602285, -0.064988, 0.142251, -0.088961, 0.000000, 0.000000, 0.000000], [-0.954948, -0.483840, -0.209626, 0.094810, -0.267971, 0.000000, 0.000000, 0.000000], [0.899889, 0.356225, 0.380246, -0.326936, 0.360196, 0.000000, 0.000000, 0.000000], [0.616879, -0.022411, 0.447275, -0.744326, 0.197111, 0.000000, 0.000000, 0.000000], [-0.891255, -0.071869, -0.055190, 0.174187, -0.431570, 0.000000, 0.000000, 0.000000], [-0.013927, 0.292282, 0.567627, -0.595332, -0.182978, 0.000000, 0.000000, 0.000000], [0.720765, -0.213540, -0.168996, -0.098013, 0.432402, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.645895, -1.561779, 1.392380, -0.403955, -0.499172, -0.021446, 0.233140]
pre_activation_std: [2.642227, 2.547140, 2.086405, 2.170976, 1.673139, 0.956070, 1.889385]
### 2
mean: [1.691260, -0.817489, 0.206619, 1.524639, -1.215975, -0.415123, 1.550951]
std: [2.634646, 0.471014, 0.714500, 1.447405, 0.792552, 1.276722, 1.188814]
fourier: [[42.930816, 43.382170, 46.426717, 60.044901, 152.213411], [6.802222, 6.830461, 7.048502, 7.177447, 73.574056], [10.213363, 10.264763, 12.191833, 13.588069, 18.595691], [22.436029, 22.944825, 27.386687, 27.983610, 137.217558], [11.565851, 12.807797, 13.153592, 20.030820, 109.437789], [18.752585, 19.343455, 19.798672, 25.674121, 37.361110], [20.449249, 20.792105, 22.446758, 22.812425, 139.585580]]
input_correlations: [[-0.441184, -0.334548, 0.972122, 0.896852, -0.477329, 0.064707, 0.833422, 0.000000], [-0.602244, -0.676490, 0.087522, 0.093920, -0.709703, -0.525306, 0.368184, 0.000000], [0.888213, 0.702830, -0.641399, -0.483918, 0.274201, -0.288328, -0.280740, 0.000000], [-0.520224, -0.348079, 0.955610, 0.892646, -0.285003, 0.145726, 0.797683, 0.000000], [-0.359529, -0.397686, -0.508984, -0.714636, -0.156689, -0.106717, -0.631582, 0.000000], [0.746318, 0.599629, -0.911641, -0.724318, 0.511487, -0.020102, -0.800606, 0.000000], [-0.457307, -0.291859, 0.994932, 0.860263, -0.348629, 0.112707, 0.788000, 0.000000]]
pre_activation_mean: [1.691260, -0.817489, 0.206619, 1.524639, -1.215975, -0.415123, 1.550951]
pre_activation_std: [2.634646, 0.471014, 0.714500, 1.447405, 0.792552, 1.276722, 1.188814]
### 4
mean: [-1.442374, -0.991556, -1.857419, 2.083087, -0.826371, -0.917302, -2.043581]
std: [1.241327, 0.909243, 1.464240, 2.199901, 1.994370, 1.294083, 1.597127]
fourier: [[20.259671, 20.813021, 23.690523, 24.960987, 129.813694], [15.275605, 15.713200, 16.001236, 19.361692, 89.240007], [24.777935, 26.094949, 26.857396, 29.924132, 167.167689], [35.619469, 35.908424, 40.436246, 46.109736, 187.477880], [28.852871, 31.030276, 35.321396, 42.082200, 74.373377], [18.987516, 19.748860, 23.187407, 25.904671, 82.557216], [26.334651, 27.764536, 30.506471, 31.457775, 183.922237]]
input_correlations: [[-0.993255, -0.382460, 0.457956, -0.988265, 0.000000, 0.374488, -0.992331, 0.000000], [-0.993962, -0.405790, 0.368614, -0.980668, 0.000000, 0.334602, -0.980959, 0.000000], [-0.995117, -0.378778, 0.385363, -0.977997, 0.000000, 0.325981, -0.992186, 0.000000], [0.991860, 0.378408, -0.504371, 0.991111, 0.000000, -0.446850, 0.989941, 0.000000], [-0.958108, -0.358549, 0.641426, -0.977137, 0.000000, 0.596209, -0.959804, 0.000000], [-0.933646, -0.348746, 0.693113, -0.970045, 0.000000, 0.635419, -0.943173, 0.000000], [-0.990942, -0.395749, 0.378874, -0.979144, 0.000000, 0.290467, -0.985638, 0.000000]]
pre_activation_mean: [-1.442374, -0.991556, -1.857419, 2.083087, -0.826371, -0.917302, -2.043581]
pre_activation_std: [1.241327, 0.909243, 1.464240, 2.199901, 1.994370, 1.294083, 1.597127]
### 6
mean: [1.519537, -0.711025, 0.801803, 1.783603, -0.330310, -0.170295, 0.072103]
std: [1.471461, 0.137488, 0.910669, 1.379761, 0.950467, 0.514024, 0.722701]
fourier: [[23.161240, 23.752410, 27.013211, 30.796949, 136.758338], [1.925230, 2.014718, 2.251304, 2.531081, 63.992249], [13.443887, 13.993911, 15.971535, 19.441129, 72.162304], [20.797314, 21.832170, 24.934154, 29.250123, 160.524232], [13.733790, 13.873531, 15.300635, 19.870811, 29.727933], [7.425335, 7.472825, 7.998223, 9.791626, 15.326556], [10.335873, 10.424593, 11.030212, 12.632613, 15.238348]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.998603, -0.498793, -0.398995, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.161833, -0.945168, -0.961489, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.978696, -0.623661, -0.537377, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.993423, -0.550910, -0.458424, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.925620, 0.755521, 0.671482, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, -0.780365, 0.907949, 0.846442, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.975253, -0.638468, -0.538279, 0.000000, 0.000000]]
pre_activation_mean: [1.519537, -0.711025, 0.801803, 1.783603, -0.330310, -0.170295, 0.072103]
pre_activation_std: [1.471461, 0.137488, 0.910669, 1.379761, 0.950467, 0.514024, 0.722701]
### 8
mean: [2.498073, 0.297371, -1.185193, 2.736010, 1.981454, 2.272354, -1.360479]
std: [1.970444, 0.142582, 0.420497, 2.161823, 1.620427, 1.712154, 2.281634]
fourier: [[28.690617, 30.850276, 35.223981, 42.026383, 224.826530], [2.023972, 2.178785, 2.495478, 2.681861, 26.763387], [7.320063, 7.335046, 7.948586, 8.008919, 106.667362], [32.030379, 34.198363, 39.030466, 45.757302, 246.240951], [23.802196, 25.363921, 29.052389, 34.251981, 178.330856], [26.543838, 27.479362, 31.407821, 35.735917, 204.511824], [33.602958, 34.304070, 39.118839, 48.537406, 122.443061]]
input_correlations: [[0.992233, 0.000000, 0.991594, 0.998464, -0.551222, -0.518687, 0.947812, 0.000000], [-0.487675, 0.000000, -0.474589, -0.428514, -0.552907, -0.573345, -0.649465, 0.000000], [-0.973828, 0.000000, -0.970911, -0.955680, 0.233375, 0.192057, -0.988305, 0.000000], [0.995454, 0.000000, 0.995122, 0.999589, -0.528132, -0.493707, 0.954833, 0.000000], [0.993915, 0.000000, 0.994238, 0.998986, -0.542542, -0.506833, 0.947898, 0.000000], [0.999547, 0.000000, 0.998842, 0.999108, -0.472995, -0.435990, 0.967647, 0.000000], [-0.973972, 0.000000, -0.975387, -0.987163, 0.637810, 0.604900, -0.908021, 0.000000]]
pre_activation_mean: [2.498073, 0.297371, -1.185193, 2.736010, 1.981454, 2.272354, -1.360479]
pre_activation_std: [1.970444, 0.142582, 0.420497, 2.161823, 1.620427, 1.712154, 2.281634]
### 10
mean: [-1.430216, 2.095937, -1.079472, 4.054352, 5.298249, 1.975439, 0.574136]
std: [1.112795, 1.775349, 0.498109, 3.444266, 4.185853, 0.790840, 0.294916]
fourier: [[18.697942, 18.984089, 21.010581, 21.908414, 128.719490], [26.292702, 26.432788, 29.903368, 38.006093, 188.634342], [8.474274, 8.890744, 9.006788, 9.278500, 97.152492], [50.813061, 54.092613, 61.921606, 72.804693, 364.891700], [61.578372, 65.492288, 74.993025, 88.606106, 476.842394], [13.060940, 14.065111, 14.313761, 14.775659, 177.789544], [4.781413, 5.115611, 5.266424, 5.615002, 51.672234]]
input_correlations: [[-0.974447, 0.589982, 0.000000, -0.976242, -0.975988, -0.985520, 0.274926, 0.000000], [0.984553, -0.239606, 0.000000, 0.983140, 0.983046, 0.973201, -0.629103, 0.000000], [-0.889005, 0.759307, 0.000000, -0.892687, -0.892593, -0.913571, 0.029882, 0.000000], [0.999650, -0.378234, 0.000000, 0.999423, 0.999221, 0.996552, -0.505847, 0.000000], [0.999358, -0.369619, 0.000000, 0.999058, 0.998883, 0.995753, -0.513932, 0.000000], [0.822514, -0.833379, 0.000000, 0.827086, 0.826602, 0.853141, 0.099978, 0.000000], [0.754922, -0.885523, 0.000000, 0.760178, 0.759649, 0.790441, 0.208934, 0.000000]]
pre_activation_mean: [-1.430216, 2.095937, -1.079472, 4.054352, 5.298249, 1.975439, 0.574136]
pre_activation_std: [1.112795, 1.775349, 0.498109, 3.444266, 4.185853, 0.790840, 0.294916]
### 12
mean: [-3.091383]
std: [3.489506]
fourier: [[50.090252, 53.497824, 61.063647, 74.225494, 278.224457]]
input_correlations: [[0.000000, -0.997121, 0.000000, -0.992433, -0.994850, -0.756586, -0.680193, 0.000000]]
pre_activation_mean: [-3.091383]
pre_activation_std: [3.489506]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
mountain_pattern | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.8690528444453853, -0.6022851279667119, -0.06498832889876147, 0.1422511332669869, -0.08896140471049328, 0.0, 0.0, 0.0], "pre_activation_mean": -0.6458945870399475, "pre_activation_std": 2.6422274112701416}, "1": {"mean": 2.174926280975342, "std": 1.6516501903533936, "fourier": [24.47978261217621, 25.978196948921344, 29.747734059366792, 34.6732972784661, 195.74338230490685], "input_correlations": [-0.9549480569842187, -0.48383976704542997, -0.20962590890306848, 0.09481045598818734, -0.2679709481135649, 0.0, 0.0, 0.0], "pre_activation_mean": -1.5617789030075073, "pre_activation_std": 2.547139883041382}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.8998888028221971, 0.3562247819791332, 0.3802460324587615, -0.32693556817809194, 0.3601955085052892, 0.0, 0.0, 0.0], 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"network.10.bias": [0.043251, 0.158919, -0.185879, -0.293203, 0.064967, 0.4677, 0.143074], "network.12.weight": [[-0.139691, -0.202353, -0.15609, -0.392213, -0.557691, 0.571606, 0.560481]], "network.12.bias": [0.482458]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6848364174365997, "train_acc": 0.56, "val_loss": 0.680594801902771, "val_acc": 0.58}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6837148070335388, "train_acc": 0.56, "val_loss": 0.6800387501716614, "val_acc": 0.58}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6869807243347168, "train_acc": 0.56, "val_loss": 0.6728014945983887, "val_acc": 0.58}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.6701168417930603, "train_acc": 0.56, "val_loss": 0.6202415823936462, "val_acc": 0.58}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.6366513669490814, "train_acc": 0.48, "val_loss": 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"epoch": 7, "global_epoch": 11, "train_loss": 0.3074222803115845, "train_acc": 0.88, "val_loss": 0.323141872882843, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.281772680580616, "train_acc": 0.895, "val_loss": 0.26152756810188293, "val_acc": 0.92}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.3088560998439789, "train_acc": 0.9, "val_loss": 0.2914454936981201, "val_acc": 0.86}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["mountain_pattern"], "degraded_stage": {"initial_val_loss": 0.680594801902771, "final_val_loss": 0.6202415823936462, "initial_val_acc": 0.58, "final_val_acc": 0.58, "best_val_acc": 0.58}, "improved_stage": {"initial_val_loss": 0.4831179082393646, "final_val_loss": 0.2914454936981201, "initial_val_acc": 0.58, "final_val_acc": 0.86, "best_val_acc": 0.92, "best_epoch": 10}, "improvement": 0.3400000000000001, "first_improvement_epoch": 3}} |
93 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.5, "improved_accuracy": 0.82, "improvement": 0.31999999999999995, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3153, "learning_rate": 0.09375952855635061, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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0.039347,
0.034091,
-0.326047,
-0.004839,
-0.172949
]
],
"network.10.bias": [
-0.106818,
-0.072295,
-0.149061,
-0.227171,
-0.241894,
-0.210522,
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],
"network.12.weight": [
[
-0.489823,
-0.027236,
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-0.5591,
0.006625,
-0.032313,
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]
],
"network.12.bias": [
0.107978
]
}
## Activation Signature
### 0
mean: [5.608073, 0.000000, 6.340094, 4.358368, 0.000000, 0.000000, 0.000000, 0.000000]
std: [7.125577, 0.000000, 8.075674, 5.637721, 0.000000, 0.000000, 0.000000, 0.000000]
fourier: [[105.521701, 111.866737, 116.022598, 161.407549, 504.726541], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [119.645831, 126.691505, 131.460463, 182.923418, 570.608531], [83.826934, 87.991264, 91.732715, 127.598201, 392.253158], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.240994, -0.088891, -0.590715, 0.707394, -0.283540, 0.000000, 0.000000, 0.000000], [-0.560501, -0.385960, 0.007620, 0.026049, 0.690554, 0.000000, 0.000000, 0.000000], [0.309265, -0.611663, -0.257568, -0.600795, 0.339817, 0.000000, 0.000000, 0.000000], [-0.384964, -0.711399, -0.361069, -0.157076, 0.573980, 0.000000, 0.000000, 0.000000], [-0.319841, 0.107082, 0.353214, 0.406658, -0.608066, 0.000000, 0.000000, 0.000000], [-0.793997, -0.132003, -0.616094, -0.109235, 0.079625, 0.000000, 0.000000, 0.000000], [0.205160, 0.237527, -0.173318, 0.532966, 0.804888, 0.000000, 0.000000, 0.000000], [-0.352176, 0.235321, 0.479435, 0.363628, 0.616066, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.313838, 0.065496, -0.997444, -0.982241, 0.667243, -1.589322, 0.743408, 2.909313]
pre_activation_std: [1.242000, 2.313670, 1.939275, 1.596528, 1.932111, 1.315115, 1.580487, 2.777741]
### 2
mean: [-0.651353, 2.287555, 2.166079, -1.267754, 2.751199, -1.946121, 0.172165, 0.707214]
std: [1.374354, 1.349031, 1.905444, 0.742770, 3.825233, 1.367495, 0.642917, 1.123258]
fourier: [[20.623175, 20.670368, 21.943928, 25.368851, 58.621774], [20.396138, 20.466468, 21.270248, 25.939515, 205.879986], [30.799735, 31.479422, 32.029529, 38.238898, 194.947112], [10.763954, 11.578982, 12.871765, 14.871190, 114.097871], [60.357013, 60.824034, 69.509753, 83.976797, 247.607907], [20.546078, 24.286797, 26.084199, 26.292398, 175.150839], [9.818158, 10.166560, 10.884559, 11.450547, 15.494883], [16.871034, 18.494217, 18.712130, 21.236155, 63.649289]]
input_correlations: [[0.110497, -0.385097, 0.617064, -0.054329, -0.422065, -0.101716, -0.154713, -0.837240], [0.273078, 0.169815, -0.467447, -0.007658, 0.730219, -0.012972, 0.206834, 0.777918], [-0.197504, 0.956445, 0.263238, 0.813629, -0.260804, 0.447861, 0.705058, 0.780230], [0.010707, -0.907943, -0.295266, -0.819836, 0.193510, -0.498452, -0.841672, -0.742950], [-0.204954, 0.942993, 0.248940, 0.820405, -0.426940, 0.463278, 0.821420, 0.711730], [0.196255, -0.807148, 0.015801, -0.599248, 0.006236, -0.386585, -0.714600, -0.958344], [0.592959, -0.427776, 0.346667, -0.083436, 0.198898, -0.182772, 0.117233, -0.354955], [0.573806, -0.310990, -0.551523, -0.357534, 0.941680, -0.172971, -0.216426, 0.219855]]
pre_activation_mean: [-0.651353, 2.287555, 2.166079, -1.267754, 2.751199, -1.946121, 0.172165, 0.707214]
pre_activation_std: [1.374354, 1.349031, 1.905444, 0.742770, 3.825233, 1.367495, 0.642917, 1.123258]
### 4
mean: [5.132377, -2.632324, 2.285334, -0.602829, 1.011422, 2.867454, -2.080541, 0.159503]
std: [4.424114, 2.555968, 1.659773, 0.578551, 1.726588, 3.820169, 1.048393, 2.274651]
fourier: [[65.761357, 66.072367, 78.754866, 95.772056, 461.913870], [38.608833, 38.689350, 45.696190, 55.294893, 236.909195], [27.610010, 29.629893, 30.589220, 31.118384, 205.680040], [8.261701, 8.445735, 10.158631, 12.462988, 54.254617], [27.131932, 27.290581, 30.231561, 35.011892, 91.027985], [58.540545, 58.782245, 64.862237, 84.319037, 258.070882], [16.169644, 18.067445, 19.237241, 21.705487, 187.248720], [35.319555, 35.818751, 36.255971, 40.417193, 47.697117]]
input_correlations: [[-0.024957, 0.241474, 0.983501, 0.000000, 0.991747, 0.000000, 0.035915, -0.287367], [0.041864, -0.236270, -0.985438, 0.000000, -0.993599, 0.000000, -0.025617, 0.295938], [-0.319616, 0.488930, 0.964408, 0.000000, 0.929145, 0.000000, -0.104359, -0.066820], [-0.029059, -0.064311, -0.957279, 0.000000, -0.976923, 0.000000, -0.046960, 0.423014], [-0.454053, 0.642614, -0.508876, 0.000000, -0.627617, 0.000000, 0.109921, 0.896214], [0.119300, -0.030112, 0.935833, 0.000000, 0.973351, 0.000000, -0.050293, -0.530053], [0.159504, -0.469546, -0.965376, 0.000000, -0.942065, 0.000000, -0.059155, 0.093680], [-0.286565, 0.340688, -0.781625, 0.000000, -0.854344, 0.000000, 0.140770, 0.767433]]
pre_activation_mean: [5.132377, -2.632324, 2.285334, -0.602829, 1.011422, 2.867454, -2.080541, 0.159503]
pre_activation_std: [4.424114, 2.555968, 1.659773, 0.578551, 1.726588, 3.820169, 1.048393, 2.274651]
### 6
mean: [-0.365816, 4.426368, -2.722963, 1.822879, 4.415820, 5.625293, 7.142635, -2.200378]
std: [0.686483, 5.580216, 2.003810, 1.904304, 5.728405, 4.760212, 5.867627, 1.953122]
fourier: [[10.848317, 11.704848, 12.574992, 14.190809, 32.923466], [86.761528, 87.553761, 95.658841, 124.909701, 398.373079], [30.399201, 31.146159, 33.595136, 42.606963, 245.066631], [28.343668, 29.689885, 32.853544, 38.680535, 164.059120], [86.877019, 89.906730, 97.677071, 128.777077, 397.423806], [71.692111, 72.986485, 82.920569, 104.125400, 506.276377], [88.603004, 91.444350, 101.141081, 124.968644, 642.837132], [30.018208, 31.014005, 34.776110, 42.894314, 198.034059]]
input_correlations: [[-0.728990, 0.000000, -0.524257, 0.000000, 0.906624, -0.850619, 0.000000, 0.897142], [0.975320, 0.000000, 0.866255, 0.000000, -0.566867, 0.997925, 0.000000, -0.570612], [-0.996640, 0.000000, -0.944813, 0.000000, 0.359846, -0.971135, 0.000000, 0.366585], [-0.318178, 0.000000, -0.059224, 0.000000, 0.992394, -0.521213, 0.000000, 0.955680], [0.957134, 0.000000, 0.824985, 0.000000, -0.622642, 0.996524, 0.000000, -0.619632], [0.997015, 0.000000, 0.925580, 0.000000, -0.437282, 0.985107, 0.000000, -0.451165], [0.998376, 0.000000, 0.951240, 0.000000, -0.352048, 0.967128, 0.000000, -0.366215], [-0.995003, 0.000000, -0.926710, 0.000000, 0.452505, -0.982951, 0.000000, 0.474440]]
pre_activation_mean: [-0.365816, 4.426368, -2.722963, 1.822879, 4.415820, 5.625293, 7.142635, -2.200378]
pre_activation_std: [0.686483, 5.580216, 2.003810, 1.904304, 5.728405, 4.760212, 5.867627, 1.953122]
### 8
mean: [-4.095839, -4.681248, -1.449815, -1.797995, -9.643353, 7.654594, -2.338634, -6.442759]
std: [3.810982, 4.040188, 0.671190, 1.298794, 9.581241, 10.346953, 1.156170, 4.605687]
fourier: [[57.467961, 58.753414, 64.584006, 84.702225, 368.625478], [62.260392, 63.108598, 69.973817, 89.265873, 421.312248], [9.867561, 10.294528, 11.469368, 12.724652, 130.483346], [18.864081, 19.606899, 22.330563, 28.920061, 161.819517], [146.513993, 147.158337, 163.698735, 212.410899, 867.901877], [157.042790, 164.639632, 172.422080, 233.363610, 688.913502], [19.038272, 19.156498, 20.581736, 20.841726, 210.477065], [69.481730, 73.062513, 80.616798, 96.513906, 579.848326]]
input_correlations: [[0.356360, -0.998153, 0.000000, 0.454001, -0.993682, -0.996417, -0.985208, 0.000000], [0.363279, -0.996909, 0.000000, 0.443620, -0.990121, -0.997816, -0.987384, 0.000000], [-0.673719, -0.266343, 0.000000, -0.694425, -0.224535, -0.390395, -0.474133, 0.000000], [0.335604, -0.995771, 0.000000, 0.430253, -0.990815, -0.997497, -0.988434, 0.000000], [0.349309, -0.997244, 0.000000, 0.440120, -0.991387, -0.997839, -0.987991, 0.000000], [-0.464908, 0.995649, 0.000000, -0.580588, 0.998658, 0.973548, 0.948935, 0.000000], [-0.183546, -0.775281, 0.000000, -0.154209, -0.744166, -0.852121, -0.897282, 0.000000], [0.197146, -0.962326, 0.000000, 0.253700, -0.945936, -0.990417, -0.998792, 0.000000]]
pre_activation_mean: [-4.095839, -4.681248, -1.449815, -1.797995, -9.643353, 7.654594, -2.338634, -6.442759]
pre_activation_std: [3.810982, 4.040188, 0.671190, 1.298794, 9.581241, 10.346953, 1.156170, 4.605687]
### 10
mean: [5.579587, -1.726988, 6.300267, 4.296372, -1.012934, -1.134924, -2.524558, -2.883204]
std: [7.148116, 2.080038, 8.107150, 5.686335, 0.969239, 1.162023, 3.082208, 3.278329]
fourier: [[105.664975, 112.552373, 116.541285, 161.914676, 502.162902], [30.747556, 32.751727, 33.912466, 47.115715, 155.428948], [119.841609, 127.653058, 132.177144, 183.638099, 567.024010], [84.056613, 89.535545, 92.708729, 128.803320, 386.673487], [14.327496, 15.261383, 15.802254, 21.954597, 91.164087], [17.177274, 18.296914, 18.945365, 26.321427, 102.143182], [45.561851, 48.531640, 50.251625, 69.816252, 227.210212], [48.460950, 51.619707, 53.449132, 74.258659, 259.488325]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000]]
pre_activation_mean: [5.579587, -1.726988, 6.300267, 4.296372, -1.012934, -1.134924, -2.524558, -2.883204]
pre_activation_std: [7.148116, 2.080038, 8.107150, 5.686335, 0.969239, 1.162023, 3.082208, 3.278329]
### 12
mean: [-9.333564]
std: [12.065602]
fourier: [[178.905097, 189.072889, 196.402680, 273.247052, 840.020742]]
input_correlations: [[-0.999995, 0.000000, -0.999998, -0.999978, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-9.333564]
pre_activation_std: [12.065602]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 8
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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-0.094571,
-0.279522,
-0.215949,
0.047006,
-0.024072
],
[
-0.120499,
-0.315261,
-0.158613,
0.24782,
-0.269798,
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-0.593069,
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],
[
0.349892,
0.696062,
0.108741,
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0.775489,
0.169768,
0.12981,
0.35022
],
[
-0.218153,
0.025524,
0.176049,
-0.278457,
-0.034801,
-0.051801,
-0.155511,
0.326797
],
[
0.195893,
0.039407,
-0.081911,
-0.153246,
0.102477,
-0.518799,
-0.507321,
-0.138665
]
],
"network.8.bias": [
-0.196286,
-0.508049,
-0.073085,
-0.267924,
0.029508,
0.26469,
-0.349462,
-0.29429
],
"network.10.weight": [
[
0.058118,
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0.024199,
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[
-0.075758,
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[
0.101403,
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[
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[
0.107564,
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],
[
0.31041,
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-0.074565,
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-0.115569,
-0.307952,
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],
[
-0.012636,
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-0.349461,
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[
0.039274,
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"network.12.weight": [
[
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"network.12.bias": [
0.107978
]
}
## Activation Signature
### 0
mean: [5.608073, 0.000000, 6.340094, 4.358368, 0.000000, 0.000000, 0.000000, 0.000000]
std: [7.125577, 0.000000, 8.075674, 5.637721, 0.000000, 0.000000, 0.000000, 0.000000]
fourier: [[105.521701, 111.866737, 116.022598, 161.407549, 504.726541], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [119.645831, 126.691505, 131.460463, 182.923418, 570.608531], [83.826934, 87.991264, 91.732715, 127.598201, 392.253158], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.240994, -0.088891, -0.590715, 0.707394, -0.283540, 0.000000, 0.000000, 0.000000], [-0.560501, -0.385960, 0.007620, 0.026049, 0.690554, 0.000000, 0.000000, 0.000000], [0.309265, -0.611663, -0.257568, -0.600795, 0.339817, 0.000000, 0.000000, 0.000000], [-0.384964, -0.711399, -0.361069, -0.157076, 0.573980, 0.000000, 0.000000, 0.000000], [-0.319841, 0.107082, 0.353214, 0.406658, -0.608066, 0.000000, 0.000000, 0.000000], [-0.793997, -0.132003, -0.616094, -0.109235, 0.079625, 0.000000, 0.000000, 0.000000], [0.205160, 0.237527, -0.173318, 0.532966, 0.804888, 0.000000, 0.000000, 0.000000], [-0.352176, 0.235321, 0.479435, 0.363628, 0.616066, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.313838, 0.065496, -0.997444, -0.982241, 0.667243, -1.589322, 0.743408, 2.909313]
pre_activation_std: [1.242000, 2.313670, 1.939275, 1.596528, 1.932111, 1.315115, 1.580487, 2.777741]
### 2
mean: [-0.651353, 2.287555, 2.166079, -1.267754, 2.751199, -1.946121, 0.172165, 0.707214]
std: [1.374354, 1.349031, 1.905444, 0.742770, 3.825233, 1.367495, 0.642917, 1.123258]
fourier: [[20.623175, 20.670368, 21.943928, 25.368851, 58.621774], [20.396138, 20.466468, 21.270248, 25.939515, 205.879986], [30.799735, 31.479422, 32.029529, 38.238898, 194.947112], [10.763954, 11.578982, 12.871765, 14.871190, 114.097871], [60.357013, 60.824034, 69.509753, 83.976797, 247.607907], [20.546078, 24.286797, 26.084199, 26.292398, 175.150839], [9.818158, 10.166560, 10.884559, 11.450547, 15.494883], [16.871034, 18.494217, 18.712130, 21.236155, 63.649289]]
input_correlations: [[0.110497, -0.385097, 0.617064, -0.054329, -0.422065, -0.101716, -0.154713, -0.837240], [0.273078, 0.169815, -0.467447, -0.007658, 0.730219, -0.012972, 0.206834, 0.777918], [-0.197504, 0.956445, 0.263238, 0.813629, -0.260804, 0.447861, 0.705058, 0.780230], [0.010707, -0.907943, -0.295266, -0.819836, 0.193510, -0.498452, -0.841672, -0.742950], [-0.204954, 0.942993, 0.248940, 0.820405, -0.426940, 0.463278, 0.821420, 0.711730], [0.196255, -0.807148, 0.015801, -0.599248, 0.006236, -0.386585, -0.714600, -0.958344], [0.592959, -0.427776, 0.346667, -0.083436, 0.198898, -0.182772, 0.117233, -0.354955], [0.573806, -0.310990, -0.551523, -0.357534, 0.941680, -0.172971, -0.216426, 0.219855]]
pre_activation_mean: [-0.651353, 2.287555, 2.166079, -1.267754, 2.751199, -1.946121, 0.172165, 0.707214]
pre_activation_std: [1.374354, 1.349031, 1.905444, 0.742770, 3.825233, 1.367495, 0.642917, 1.123258]
### 4
mean: [5.132377, -2.632324, 2.285334, -0.602829, 1.011422, 2.867454, -2.080541, 0.159503]
std: [4.424114, 2.555968, 1.659773, 0.578551, 1.726588, 3.820169, 1.048393, 2.274651]
fourier: [[65.761357, 66.072367, 78.754866, 95.772056, 461.913870], [38.608833, 38.689350, 45.696190, 55.294893, 236.909195], [27.610010, 29.629893, 30.589220, 31.118384, 205.680040], [8.261701, 8.445735, 10.158631, 12.462988, 54.254617], [27.131932, 27.290581, 30.231561, 35.011892, 91.027985], [58.540545, 58.782245, 64.862237, 84.319037, 258.070882], [16.169644, 18.067445, 19.237241, 21.705487, 187.248720], [35.319555, 35.818751, 36.255971, 40.417193, 47.697117]]
input_correlations: [[-0.024957, 0.241474, 0.983501, 0.000000, 0.991747, 0.000000, 0.035915, -0.287367], [0.041864, -0.236270, -0.985438, 0.000000, -0.993599, 0.000000, -0.025617, 0.295938], [-0.319616, 0.488930, 0.964408, 0.000000, 0.929145, 0.000000, -0.104359, -0.066820], [-0.029059, -0.064311, -0.957279, 0.000000, -0.976923, 0.000000, -0.046960, 0.423014], [-0.454053, 0.642614, -0.508876, 0.000000, -0.627617, 0.000000, 0.109921, 0.896214], [0.119300, -0.030112, 0.935833, 0.000000, 0.973351, 0.000000, -0.050293, -0.530053], [0.159504, -0.469546, -0.965376, 0.000000, -0.942065, 0.000000, -0.059155, 0.093680], [-0.286565, 0.340688, -0.781625, 0.000000, -0.854344, 0.000000, 0.140770, 0.767433]]
pre_activation_mean: [5.132377, -2.632324, 2.285334, -0.602829, 1.011422, 2.867454, -2.080541, 0.159503]
pre_activation_std: [4.424114, 2.555968, 1.659773, 0.578551, 1.726588, 3.820169, 1.048393, 2.274651]
### 6
mean: [-0.365816, 4.426368, -2.722963, 1.822879, 4.415820, 5.625293, 7.142635, -2.200378]
std: [0.686483, 5.580216, 2.003810, 1.904304, 5.728405, 4.760212, 5.867627, 1.953122]
fourier: [[10.848317, 11.704848, 12.574992, 14.190809, 32.923466], [86.761528, 87.553761, 95.658841, 124.909701, 398.373079], [30.399201, 31.146159, 33.595136, 42.606963, 245.066631], [28.343668, 29.689885, 32.853544, 38.680535, 164.059120], [86.877019, 89.906730, 97.677071, 128.777077, 397.423806], [71.692111, 72.986485, 82.920569, 104.125400, 506.276377], [88.603004, 91.444350, 101.141081, 124.968644, 642.837132], [30.018208, 31.014005, 34.776110, 42.894314, 198.034059]]
input_correlations: [[-0.728990, 0.000000, -0.524257, 0.000000, 0.906624, -0.850619, 0.000000, 0.897142], [0.975320, 0.000000, 0.866255, 0.000000, -0.566867, 0.997925, 0.000000, -0.570612], [-0.996640, 0.000000, -0.944813, 0.000000, 0.359846, -0.971135, 0.000000, 0.366585], [-0.318178, 0.000000, -0.059224, 0.000000, 0.992394, -0.521213, 0.000000, 0.955680], [0.957134, 0.000000, 0.824985, 0.000000, -0.622642, 0.996524, 0.000000, -0.619632], [0.997015, 0.000000, 0.925580, 0.000000, -0.437282, 0.985107, 0.000000, -0.451165], [0.998376, 0.000000, 0.951240, 0.000000, -0.352048, 0.967128, 0.000000, -0.366215], [-0.995003, 0.000000, -0.926710, 0.000000, 0.452505, -0.982951, 0.000000, 0.474440]]
pre_activation_mean: [-0.365816, 4.426368, -2.722963, 1.822879, 4.415820, 5.625293, 7.142635, -2.200378]
pre_activation_std: [0.686483, 5.580216, 2.003810, 1.904304, 5.728405, 4.760212, 5.867627, 1.953122]
### 8
mean: [-4.095839, -4.681248, -1.449815, -1.797995, -9.643353, 7.654594, -2.338634, -6.442759]
std: [3.810982, 4.040188, 0.671190, 1.298794, 9.581241, 10.346953, 1.156170, 4.605687]
fourier: [[57.467961, 58.753414, 64.584006, 84.702225, 368.625478], [62.260392, 63.108598, 69.973817, 89.265873, 421.312248], [9.867561, 10.294528, 11.469368, 12.724652, 130.483346], [18.864081, 19.606899, 22.330563, 28.920061, 161.819517], [146.513993, 147.158337, 163.698735, 212.410899, 867.901877], [157.042790, 164.639632, 172.422080, 233.363610, 688.913502], [19.038272, 19.156498, 20.581736, 20.841726, 210.477065], [69.481730, 73.062513, 80.616798, 96.513906, 579.848326]]
input_correlations: [[0.356360, -0.998153, 0.000000, 0.454001, -0.993682, -0.996417, -0.985208, 0.000000], [0.363279, -0.996909, 0.000000, 0.443620, -0.990121, -0.997816, -0.987384, 0.000000], [-0.673719, -0.266343, 0.000000, -0.694425, -0.224535, -0.390395, -0.474133, 0.000000], [0.335604, -0.995771, 0.000000, 0.430253, -0.990815, -0.997497, -0.988434, 0.000000], [0.349309, -0.997244, 0.000000, 0.440120, -0.991387, -0.997839, -0.987991, 0.000000], [-0.464908, 0.995649, 0.000000, -0.580588, 0.998658, 0.973548, 0.948935, 0.000000], [-0.183546, -0.775281, 0.000000, -0.154209, -0.744166, -0.852121, -0.897282, 0.000000], [0.197146, -0.962326, 0.000000, 0.253700, -0.945936, -0.990417, -0.998792, 0.000000]]
pre_activation_mean: [-4.095839, -4.681248, -1.449815, -1.797995, -9.643353, 7.654594, -2.338634, -6.442759]
pre_activation_std: [3.810982, 4.040188, 0.671190, 1.298794, 9.581241, 10.346953, 1.156170, 4.605687]
### 10
mean: [5.579587, -1.726988, 6.300267, 4.296372, -1.012934, -1.134924, -2.524558, -2.883204]
std: [7.148116, 2.080038, 8.107150, 5.686335, 0.969239, 1.162023, 3.082208, 3.278329]
fourier: [[105.664975, 112.552373, 116.541285, 161.914676, 502.162902], [30.747556, 32.751727, 33.912466, 47.115715, 155.428948], [119.841609, 127.653058, 132.177144, 183.638099, 567.024010], [84.056613, 89.535545, 92.708729, 128.803320, 386.673487], [14.327496, 15.261383, 15.802254, 21.954597, 91.164087], [17.177274, 18.296914, 18.945365, 26.321427, 102.143182], [45.561851, 48.531640, 50.251625, 69.816252, 227.210212], [48.460950, 51.619707, 53.449132, 74.258659, 259.488325]]
input_correlations: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000, -1.000000, 0.000000, 0.000000]]
pre_activation_mean: [5.579587, -1.726988, 6.300267, 4.296372, -1.012934, -1.134924, -2.524558, -2.883204]
pre_activation_std: [7.148116, 2.080038, 8.107150, 5.686335, 0.969239, 1.162023, 3.082208, 3.278329]
### 12
mean: [-9.333564]
std: [12.065602]
fourier: [[178.905097, 189.072889, 196.402680, 273.247052, 840.020742]]
input_correlations: [[-0.999995, 0.000000, -0.999998, -0.999978, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-9.333564]
pre_activation_std: [12.065602]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 5.608072757720947, "std": 7.125576972961426, "fourier": [105.52170146039337, 111.86673698703702, 116.02259804790097, 161.4075491223565, 504.7265410795808], "input_correlations": [-0.2409937931331812, -0.0888912525032004, -0.5907154582217505, 0.7073936250275685, -0.28353998715794393, 0.0, 0.0, 0.0], "pre_activation_mean": 0.3138384222984314, "pre_activation_std": 1.241999864578247}, "1": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [-0.560500567128423, -0.38596010650063334, 0.007620303607611639, 0.026049162692668697, 0.6905544546121126, 0.0, 0.0, 0.0], "pre_activation_mean": 0.06549647450447083, "pre_activation_std": 2.3136696815490723}, "2": {"mean": 6.340094089508057, "std": 8.075674057006836, "fourier": [119.64583052974486, 126.69150548860567, 131.46046304361482, 182.9234178649588, 570.608530819416], "input_correlations": [0.30926502781701704, 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"profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}, "12": {"neuron_profiles": {"0": {"mean": -9.333563804626465, "std": 12.06560230255127, "fourier": [178.90509693157966, 189.07288913161406, 196.4026796350356, 273.24705219916365, 840.020741969347], "input_correlations": [-0.9999950063985614, 0.0, -0.999998297293633, -0.9999777827573813, 0.0, 0.0, 0.0, 0.0], "pre_activation_mean": -9.333563804626465, "pre_activation_std": 12.06560230255127}}, "layer_info": {"num_neurons": 1, "num_examples": 90, "profile_methods": ["mean", "std", "fourier", "input_correlations", "pre_activation_mean", "pre_activation_std"]}}}, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}} | {"config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 8, "activation_type": "relu", "dropout_rate": 0.0, "precision": "float32", "input_size": 5, "input_format": "integer_indices"}, "weights": {"network.0.weight": [[0.072171, -0.203667, -0.319682, 0.515245, -0.220753], [-0.78395, -0.187884, 0.10191, -0.087811, 1.013954], [0.496493, -0.579232, -0.379022, -0.417177, 0.414531], [-0.188873, -0.457619, -0.260708, -0.073129, 0.605347], [-0.307661, -0.107377, 0.633672, 0.492855, -0.802753], [-0.54404, 0.260718, -0.346866, -0.20306, 0.278002], [0.125461, 0.13672, -0.356679, 0.280315, 0.697927], [-0.992011, 0.487643, 0.718385, 0.164955, 0.935345]], "network.0.bias": [0.430282, 0.108329, 0.61528, 0.0415, -0.144735, -0.570233, -0.378691, 0.247267], "network.2.weight": [[0.137553, -0.343365, 0.773386, 0.582438, -0.096908, -0.226899, 0.243355, -0.397754], [0.293118, -0.148043, -0.093665, -0.20489, 0.37794, -0.378493, 0.051439, 0.455743], [0.203431, 0.606598, 0.580903, 0.290848, -0.264789, 0.38877, -0.182403, 0.450052], [-0.055045, -0.296334, -0.296226, 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-0.275677, 0.107913]], "network.6.bias": [-0.461653, -0.117726, -0.391068, -0.035291, 0.372867, 0.613873, 0.210631, -0.205525], "network.8.weight": [[-0.111715, 0.332229, 0.073358, 0.262471, -0.357482, -0.155914, -0.468055, 0.071645], [0.023226, 0.027007, -0.316204, 0.330627, 0.083798, -0.439561, -0.394269, -0.255912], [-0.206992, 0.313691, 0.337925, -0.294443, -0.218719, -0.117161, -0.077733, -0.215216], [0.228357, 0.171525, -0.083359, -0.094571, -0.279522, -0.215949, 0.047006, -0.024072], [-0.120499, -0.315261, -0.158613, 0.24782, -0.269798, -0.572565, -0.593069, -0.258485], [0.349892, 0.696062, 0.108741, -0.667515, 0.775489, 0.169768, 0.12981, 0.35022], [-0.218153, 0.025524, 0.176049, -0.278457, -0.034801, -0.051801, -0.155511, 0.326797], [0.195893, 0.039407, -0.081911, -0.153246, 0.102477, -0.518799, -0.507321, -0.138665]], "network.8.bias": [-0.196286, -0.508049, -0.073085, -0.267924, 0.029508, 0.26469, -0.349462, -0.29429], "network.10.weight": [[0.058118, 0.248163, -0.109368, 0.024199, 0.101228, 0.710917, -0.301016, -0.003421], [-0.075758, 0.038293, 0.270912, -0.246458, 0.066369, -0.20687, -0.098871, 0.305063], [0.101403, -0.068752, 0.117573, -0.092289, 0.029519, 0.806297, 0.057489, -0.072911], [-0.263637, 0.065986, -0.203818, -0.176092, -0.171848, 0.565535, -0.301772, 0.026413], [0.107564, -0.314612, -0.246066, 0.16176, -0.070373, -0.096396, 0.140617, -0.238411], [0.31041, 0.210162, -0.074565, 0.297651, -0.165847, -0.115569, -0.307952, 0.107705], [-0.012636, 0.252412, -0.349461, 0.101985, -0.116916, -0.306541, 0.116585, -0.203029], [0.039274, 0.189525, 0.302032, 0.039347, 0.034091, -0.326047, -0.004839, -0.172949]], "network.10.bias": [-0.106818, -0.072295, -0.149061, -0.227171, -0.241894, -0.210522, -0.072627, -0.275257], "network.12.weight": [[-0.489823, -0.027236, -0.671569, -0.5591, 0.006625, -0.032313, -0.278693, 0.337983]], "network.12.bias": [0.107978]}} | {"training_history": [{"stage": "degraded", "epoch": 0, "global_epoch": 0, "train_loss": 0.6800411641597748, "train_acc": 0.58, "val_loss": 0.7504766583442688, "val_acc": 0.5}, {"stage": "degraded", "epoch": 1, "global_epoch": 1, "train_loss": 0.6782565712928772, "train_acc": 0.58, "val_loss": 0.6797381639480591, "val_acc": 0.5}, {"stage": "improved", "epoch": 0, "global_epoch": 2, "train_loss": 0.6348432302474976, "train_acc": 0.5, "val_loss": 0.503272533416748, "val_acc": 0.5}, {"stage": "improved", "epoch": 1, "global_epoch": 3, "train_loss": 0.5327290594577789, "train_acc": 0.595, "val_loss": 1.1302086114883423, "val_acc": 0.82}, {"stage": "improved", "epoch": 2, "global_epoch": 4, "train_loss": 0.6687677502632141, "train_acc": 0.765, "val_loss": 0.5337439179420471, "val_acc": 0.72}, {"stage": "improved", "epoch": 3, "global_epoch": 5, "train_loss": 0.609574019908905, "train_acc": 0.65, "val_loss": 0.5569627285003662, "val_acc": 0.7}], "summary": {"total_epochs": 6, "degraded_epochs": 2, "improved_epochs": 4, "patterns": ["first_last_match"], "degraded_stage": {"initial_val_loss": 0.7504766583442688, "final_val_loss": 0.6797381639480591, "initial_val_acc": 0.5, "final_val_acc": 0.5, "best_val_acc": 0.5}, "improved_stage": {"initial_val_loss": 0.503272533416748, "final_val_loss": 0.5569627285003662, "initial_val_acc": 0.5, "final_val_acc": 0.7, "best_val_acc": 0.82, "best_epoch": 3}, "improvement": 0.31999999999999995, "first_improvement_epoch": 1}} |
94 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.4, "improved_accuracy": 0.96, "improvement": 0.5599999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 6, "neurons_per_layer": 5, "activation_type": "gelu", "dropout_rate": 0.0, "random_seed": 8537, "learning_rate": 0.040863597474926766, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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0.062432
],
[
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0.163596,
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[
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0.667408,
0.626541,
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[
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0.046998,
0.451264
],
[
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],
"network.0.bias": [
0.049665,
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"network.2.weight": [
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],
[
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0.566736,
-0.429885
],
[
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0.543856,
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0.810172
],
[
0.216961,
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0.809469,
-0.509906
],
[
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],
"network.2.bias": [
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],
"network.4.weight": [
[
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[
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[
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[
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],
"network.4.bias": [
0.656516,
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"network.6.weight": [
[
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[
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[
0.26228,
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[
0.631146,
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[
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"network.6.bias": [
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"network.8.weight": [
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[
1.053128,
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[
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"network.10.weight": [
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[
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"network.12.weight": [
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"network.12.bias": [
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]
}
## Activation Signature
### 0
mean: [2.735095, 2.673165, 1.247207, 4.668442, 0.277220]
std: [1.901780, 1.889968, 0.984959, 3.120667, 0.852309]
fourier: [[33.112324, 33.195567, 34.702297, 40.107307, 246.158504], [32.464699, 32.799914, 34.274281, 39.776876, 240.584876], [15.908748, 16.869961, 18.028658, 20.315147, 112.248628], [54.601665, 54.840340, 57.037176, 66.503204, 420.159756], [13.279836, 13.807434, 14.125361, 19.978454, 24.949842]]
input_correlations: [[-0.844936, -0.740603, -0.510859, -0.192640, -0.095751, 0.000000, 0.000000, 0.000000], [-0.288388, -0.202845, -0.029701, -0.509507, -0.884068, 0.000000, 0.000000, 0.000000], [0.745711, 0.723210, 0.703608, 0.116999, 0.122756, 0.000000, 0.000000, 0.000000], [-0.709273, -0.798174, -0.259963, -0.077159, 0.275578, 0.000000, 0.000000, 0.000000], [0.307193, 0.879904, -0.039970, 0.660296, 0.096860, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.529554, -1.053143, 3.438863, -0.837922, 1.289896]
pre_activation_std: [1.419184, 1.356952, 2.595352, 2.216758, 1.746244]
### 2
mean: [0.771192, -1.502773, 2.779951, -0.359784, 2.889081]
std: [0.864085, 1.734091, 2.454123, 1.135607, 2.079140]
fourier: [[13.766812, 14.720341, 15.629186, 16.878292, 69.407301], [27.512707, 29.384113, 30.641212, 34.974649, 135.249552], [38.573522, 41.744597, 46.407291, 50.153091, 250.195566], [18.448673, 20.033042, 20.397653, 23.802934, 32.380602], [33.225637, 34.768112, 37.497767, 39.988028, 260.017330]]
input_correlations: [[0.182073, -0.178160, 0.923922, -0.632855, 0.720561, 0.000000, 0.000000, 0.000000], [-0.263532, 0.102241, -0.932860, 0.551576, -0.785312, 0.000000, 0.000000, 0.000000], [0.298805, -0.145636, 0.905780, -0.379040, 0.872067, 0.000000, 0.000000, 0.000000], [-0.171397, 0.195095, -0.716868, 0.664972, -0.850640, 0.000000, 0.000000, 0.000000], [0.258710, -0.125382, 0.961002, -0.541119, 0.733206, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.771192, -1.502773, 2.779951, -0.359784, 2.889081]
pre_activation_std: [0.864085, 1.734091, 2.454123, 1.135607, 2.079140]
### 4
mean: [-3.223351, 3.516968, -0.459330, -3.911173, 1.759515]
std: [3.694479, 2.520155, 0.433667, 3.603444, 1.298011]
fourier: [[59.756268, 62.318108, 66.809066, 76.195548, 290.101595], [40.022278, 42.271997, 45.697961, 51.515475, 316.527058], [6.017699, 7.415146, 8.554182, 8.612435, 41.339735], [57.517983, 60.902395, 66.131502, 72.736869, 352.005563], [21.495025, 21.650037, 22.519490, 27.773734, 158.356318]]
input_correlations: [[-0.983891, 0.431132, -0.983066, 0.613192, -0.989487, 0.000000, 0.000000, 0.000000], [0.984534, -0.415388, 0.986173, -0.583188, 0.992216, 0.000000, 0.000000, 0.000000], [-0.977896, 0.239465, -0.993011, 0.413828, -0.960797, 0.000000, 0.000000, 0.000000], [-0.988835, 0.393501, -0.988185, 0.579881, -0.992112, 0.000000, 0.000000, 0.000000], [0.967058, -0.491415, 0.973573, -0.631891, 0.982729, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.223351, 3.516968, -0.459330, -3.911173, 1.759515]
pre_activation_std: [3.694479, 2.520155, 0.433667, 3.603444, 1.298011]
### 6
mean: [-2.028539, -0.074237, -0.756205, -1.075191, 3.340832]
std: [2.311034, 0.440134, 0.777642, 0.977966, 2.442296]
fourier: [[38.075257, 38.941253, 45.632617, 50.753613, 182.568491], [6.708118, 7.041395, 7.120412, 9.504078, 9.916976], [13.030768, 13.059022, 15.331317, 16.965597, 68.058419], [15.669012, 15.670862, 21.268484, 21.742418, 96.767210], [39.955638, 42.919518, 44.660793, 52.525723, 300.674933]]
input_correlations: [[0.738351, -0.957375, 0.741728, 0.595061, -0.959558, 0.000000, 0.000000, 0.000000], [0.895853, -0.839514, 0.736515, 0.785761, -0.843678, 0.000000, 0.000000, 0.000000], [0.739050, -0.956179, 0.763339, 0.592406, -0.959173, 0.000000, 0.000000, 0.000000], [0.878554, -0.859001, 0.732079, 0.766955, -0.862510, 0.000000, 0.000000, 0.000000], [-0.662355, 0.982726, -0.738196, -0.507670, 0.984024, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.028539, -0.074237, -0.756205, -1.075191, 3.340832]
pre_activation_std: [2.311034, 0.440134, 0.777642, 0.977966, 2.442296]
### 8
mean: [1.386111, 1.820853, -1.159815, 1.913369, 2.253727]
std: [1.276373, 1.791335, 1.845170, 1.690325, 1.797220]
fourier: [[21.290727, 22.040117, 26.193411, 27.780208, 124.749982], [28.638393, 28.894118, 38.672965, 39.915799, 163.876781], [28.908193, 30.586387, 38.488555, 42.849218, 104.383354], [27.165478, 27.412202, 36.743585, 36.761837, 172.203221], [29.977993, 31.181283, 35.312751, 39.017664, 202.835462]]
input_correlations: [[-0.707772, -0.838856, -0.664112, -0.565139, 0.970402, 0.000000, 0.000000, 0.000000], [-0.831730, -0.928300, -0.794484, -0.713320, 0.904594, 0.000000, 0.000000, 0.000000], [0.906368, 0.973044, 0.875650, 0.808575, -0.828933, 0.000000, 0.000000, 0.000000], [-0.791233, -0.900924, -0.752229, -0.664445, 0.932024, 0.000000, 0.000000, 0.000000], [-0.668475, -0.810689, -0.625184, -0.526264, 0.981768, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.386111, 1.820853, -1.159815, 1.913369, 2.253727]
pre_activation_std: [1.276373, 1.791335, 1.845170, 1.690325, 1.797220]
### 10
mean: [2.627088, 2.538158, 1.133714, 4.459513, -2.091010]
std: [2.104410, 2.136551, 1.325053, 3.475457, 2.187227]
fourier: [[36.219795, 37.565088, 41.168526, 45.434285, 236.437909], [36.890388, 38.082969, 42.130808, 46.180392, 228.434261], [21.765476, 21.959974, 28.436372, 28.755507, 102.034272], [60.225109, 62.307966, 68.202319, 75.093011, 401.356137], [36.018406, 36.310969, 47.310353, 47.488522, 188.190907]]
input_correlations: [[0.983820, 0.994216, -0.611132, 0.994029, 0.988806, 0.000000, 0.000000, 0.000000], [0.982681, 0.994220, -0.613771, 0.993961, 0.988151, 0.000000, 0.000000, 0.000000], [0.939683, 0.963411, -0.736873, 0.962254, 0.949158, 0.000000, 0.000000, 0.000000], [0.984087, 0.995112, -0.607209, 0.994863, 0.989287, 0.000000, 0.000000, 0.000000], [-0.935627, -0.960820, 0.743986, -0.959503, -0.945410, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.627088, 2.538158, 1.133714, 4.459513, -2.091010]
pre_activation_std: [2.104410, 2.136551, 1.325053, 3.475457, 2.187227]
### 12
mean: [-4.591075]
std: [3.802374]
fourier: [[65.588816, 68.148557, 72.236450, 82.153606, 413.196846]]
input_correlations: [[-0.993746, -0.992162, -0.984155, -0.994528, 0.610599, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.591075]
pre_activation_std: [3.802374]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 6
Neurons per Layer: 5
Activation Function: gelu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.450152,
-0.345151,
-0.164155,
-0.057911,
0.062432
],
[
-0.138641,
-0.046419,
0.163596,
-0.24355,
-0.618562
],
[
0.574962,
0.667408,
0.626541,
-0.017813,
-0.079475
],
[
-0.612619,
-0.744628,
-0.030228,
0.046998,
0.451264
],
[
0.129605,
0.713644,
-0.245845,
0.344168,
0.06366
]
],
"network.0.bias": [
0.049665,
0.147414,
0.334632,
0.687124,
-0.474828
],
"network.2.weight": [
[
-0.83668,
-0.366671,
0.216065,
-0.37319,
0.150298
],
[
0.094275,
-0.144454,
-0.401296,
0.566736,
-0.429885
],
[
-0.146632,
-0.012098,
0.543856,
-0.145018,
0.810172
],
[
0.216961,
-0.107885,
-0.042005,
0.809469,
-0.509906
],
[
-0.513699,
-0.419473,
0.581152,
-0.549533,
0.344486
]
],
"network.2.bias": [
-0.126072,
0.28248,
-0.155447,
0.249086,
0.560276
],
"network.4.weight": [
[
-0.231903,
0.537069,
-0.923345,
0.861789,
-0.468254
],
[
-0.483003,
-0.420568,
0.589894,
-0.211445,
0.648679
],
[
-0.603658,
0.212922,
-0.11566,
-0.178172,
0.141869
],
[
-0.094869,
0.141026,
-0.827342,
0.57349,
-0.64793
],
[
-0.573837,
-0.570398,
0.382085,
-0.174671,
0.33048
]
],
"network.4.bias": [
0.656516,
0.447289,
-0.079402,
0.18424,
0.238989
],
"network.6.weight": [
[
0.937153,
-0.311249,
-0.017844,
0.608386,
-0.818574
],
[
0.31322,
-0.041734,
0.225279,
0.264379,
-0.098762
],
[
0.26228,
-0.020919,
0.676947,
0.279205,
-0.426978
],
[
0.631146,
-0.144407,
0.229564,
0.628208,
-0.15433
],
[
-0.665507,
0.557628,
-0.677442,
-0.290651,
0.550336
]
],
"network.6.bias": [
0.205736,
0.174482,
0.039492,
-0.468067,
0.554705
],
"network.8.weight": [
[
-0.424694,
-0.418086,
0.149675,
0.112943,
0.433838
],
[
-0.826453,
-0.626751,
0.111778,
-0.20934,
0.484648
],
[
1.053128,
0.118759,
0.44662,
0.473514,
-0.405286
],
[
-0.632409,
-0.256117,
-0.217766,
-0.189425,
0.5178
],
[
-0.104907,
-0.845296,
-0.053807,
-0.18243,
0.649205
]
],
"network.8.bias": [
0.037249,
0.410928,
-0.043286,
0.316988,
0.102016
],
"network.10.weight": [
[
0.510176,
0.210334,
-0.284508,
0.428565,
0.326909
],
[
-0.067679,
0.510326,
-0.276567,
0.160383,
0.714817
],
[
0.185314,
0.261058,
-0.393711,
0.142011,
0.192569
],
[
0.290553,
0.81558,
-0.418339,
0.519619,
0.709375
],
[
-0.641041,
-0.450068,
0.658455,
-0.596933,
0.224844
]
],
"network.10.bias": [
-0.083786,
-0.304753,
-0.275675,
-0.196541,
0.233731
],
"network.12.weight": [
[
-0.210647,
-0.26435,
-0.409881,
-0.708566,
0.599826
]
],
"network.12.bias": [
0.344535
]
}
## Activation Signature
### 0
mean: [2.735095, 2.673165, 1.247207, 4.668442, 0.277220]
std: [1.901780, 1.889968, 0.984959, 3.120667, 0.852309]
fourier: [[33.112324, 33.195567, 34.702297, 40.107307, 246.158504], [32.464699, 32.799914, 34.274281, 39.776876, 240.584876], [15.908748, 16.869961, 18.028658, 20.315147, 112.248628], [54.601665, 54.840340, 57.037176, 66.503204, 420.159756], [13.279836, 13.807434, 14.125361, 19.978454, 24.949842]]
input_correlations: [[-0.844936, -0.740603, -0.510859, -0.192640, -0.095751, 0.000000, 0.000000, 0.000000], [-0.288388, -0.202845, -0.029701, -0.509507, -0.884068, 0.000000, 0.000000, 0.000000], [0.745711, 0.723210, 0.703608, 0.116999, 0.122756, 0.000000, 0.000000, 0.000000], [-0.709273, -0.798174, -0.259963, -0.077159, 0.275578, 0.000000, 0.000000, 0.000000], [0.307193, 0.879904, -0.039970, 0.660296, 0.096860, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.529554, -1.053143, 3.438863, -0.837922, 1.289896]
pre_activation_std: [1.419184, 1.356952, 2.595352, 2.216758, 1.746244]
### 2
mean: [0.771192, -1.502773, 2.779951, -0.359784, 2.889081]
std: [0.864085, 1.734091, 2.454123, 1.135607, 2.079140]
fourier: [[13.766812, 14.720341, 15.629186, 16.878292, 69.407301], [27.512707, 29.384113, 30.641212, 34.974649, 135.249552], [38.573522, 41.744597, 46.407291, 50.153091, 250.195566], [18.448673, 20.033042, 20.397653, 23.802934, 32.380602], [33.225637, 34.768112, 37.497767, 39.988028, 260.017330]]
input_correlations: [[0.182073, -0.178160, 0.923922, -0.632855, 0.720561, 0.000000, 0.000000, 0.000000], [-0.263532, 0.102241, -0.932860, 0.551576, -0.785312, 0.000000, 0.000000, 0.000000], [0.298805, -0.145636, 0.905780, -0.379040, 0.872067, 0.000000, 0.000000, 0.000000], [-0.171397, 0.195095, -0.716868, 0.664972, -0.850640, 0.000000, 0.000000, 0.000000], [0.258710, -0.125382, 0.961002, -0.541119, 0.733206, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.771192, -1.502773, 2.779951, -0.359784, 2.889081]
pre_activation_std: [0.864085, 1.734091, 2.454123, 1.135607, 2.079140]
### 4
mean: [-3.223351, 3.516968, -0.459330, -3.911173, 1.759515]
std: [3.694479, 2.520155, 0.433667, 3.603444, 1.298011]
fourier: [[59.756268, 62.318108, 66.809066, 76.195548, 290.101595], [40.022278, 42.271997, 45.697961, 51.515475, 316.527058], [6.017699, 7.415146, 8.554182, 8.612435, 41.339735], [57.517983, 60.902395, 66.131502, 72.736869, 352.005563], [21.495025, 21.650037, 22.519490, 27.773734, 158.356318]]
input_correlations: [[-0.983891, 0.431132, -0.983066, 0.613192, -0.989487, 0.000000, 0.000000, 0.000000], [0.984534, -0.415388, 0.986173, -0.583188, 0.992216, 0.000000, 0.000000, 0.000000], [-0.977896, 0.239465, -0.993011, 0.413828, -0.960797, 0.000000, 0.000000, 0.000000], [-0.988835, 0.393501, -0.988185, 0.579881, -0.992112, 0.000000, 0.000000, 0.000000], [0.967058, -0.491415, 0.973573, -0.631891, 0.982729, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-3.223351, 3.516968, -0.459330, -3.911173, 1.759515]
pre_activation_std: [3.694479, 2.520155, 0.433667, 3.603444, 1.298011]
### 6
mean: [-2.028539, -0.074237, -0.756205, -1.075191, 3.340832]
std: [2.311034, 0.440134, 0.777642, 0.977966, 2.442296]
fourier: [[38.075257, 38.941253, 45.632617, 50.753613, 182.568491], [6.708118, 7.041395, 7.120412, 9.504078, 9.916976], [13.030768, 13.059022, 15.331317, 16.965597, 68.058419], [15.669012, 15.670862, 21.268484, 21.742418, 96.767210], [39.955638, 42.919518, 44.660793, 52.525723, 300.674933]]
input_correlations: [[0.738351, -0.957375, 0.741728, 0.595061, -0.959558, 0.000000, 0.000000, 0.000000], [0.895853, -0.839514, 0.736515, 0.785761, -0.843678, 0.000000, 0.000000, 0.000000], [0.739050, -0.956179, 0.763339, 0.592406, -0.959173, 0.000000, 0.000000, 0.000000], [0.878554, -0.859001, 0.732079, 0.766955, -0.862510, 0.000000, 0.000000, 0.000000], [-0.662355, 0.982726, -0.738196, -0.507670, 0.984024, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.028539, -0.074237, -0.756205, -1.075191, 3.340832]
pre_activation_std: [2.311034, 0.440134, 0.777642, 0.977966, 2.442296]
### 8
mean: [1.386111, 1.820853, -1.159815, 1.913369, 2.253727]
std: [1.276373, 1.791335, 1.845170, 1.690325, 1.797220]
fourier: [[21.290727, 22.040117, 26.193411, 27.780208, 124.749982], [28.638393, 28.894118, 38.672965, 39.915799, 163.876781], [28.908193, 30.586387, 38.488555, 42.849218, 104.383354], [27.165478, 27.412202, 36.743585, 36.761837, 172.203221], [29.977993, 31.181283, 35.312751, 39.017664, 202.835462]]
input_correlations: [[-0.707772, -0.838856, -0.664112, -0.565139, 0.970402, 0.000000, 0.000000, 0.000000], [-0.831730, -0.928300, -0.794484, -0.713320, 0.904594, 0.000000, 0.000000, 0.000000], [0.906368, 0.973044, 0.875650, 0.808575, -0.828933, 0.000000, 0.000000, 0.000000], [-0.791233, -0.900924, -0.752229, -0.664445, 0.932024, 0.000000, 0.000000, 0.000000], [-0.668475, -0.810689, -0.625184, -0.526264, 0.981768, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.386111, 1.820853, -1.159815, 1.913369, 2.253727]
pre_activation_std: [1.276373, 1.791335, 1.845170, 1.690325, 1.797220]
### 10
mean: [2.627088, 2.538158, 1.133714, 4.459513, -2.091010]
std: [2.104410, 2.136551, 1.325053, 3.475457, 2.187227]
fourier: [[36.219795, 37.565088, 41.168526, 45.434285, 236.437909], [36.890388, 38.082969, 42.130808, 46.180392, 228.434261], [21.765476, 21.959974, 28.436372, 28.755507, 102.034272], [60.225109, 62.307966, 68.202319, 75.093011, 401.356137], [36.018406, 36.310969, 47.310353, 47.488522, 188.190907]]
input_correlations: [[0.983820, 0.994216, -0.611132, 0.994029, 0.988806, 0.000000, 0.000000, 0.000000], [0.982681, 0.994220, -0.613771, 0.993961, 0.988151, 0.000000, 0.000000, 0.000000], [0.939683, 0.963411, -0.736873, 0.962254, 0.949158, 0.000000, 0.000000, 0.000000], [0.984087, 0.995112, -0.607209, 0.994863, 0.989287, 0.000000, 0.000000, 0.000000], [-0.935627, -0.960820, 0.743986, -0.959503, -0.945410, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [2.627088, 2.538158, 1.133714, 4.459513, -2.091010]
pre_activation_std: [2.104410, 2.136551, 1.325053, 3.475457, 2.187227]
### 12
mean: [-4.591075]
std: [3.802374]
fourier: [[65.588816, 68.148557, 72.236450, 82.153606, 413.196846]]
input_correlations: [[-0.993746, -0.992162, -0.984155, -0.994528, 0.610599, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.591075]
pre_activation_std: [3.802374]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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"val_acc": 0.4}, {"stage": "degraded", "epoch": 2, "global_epoch": 2, "train_loss": 0.6526806354522705, "train_acc": 0.59, "val_loss": 0.6976295709609985, "val_acc": 0.4}, {"stage": "degraded", "epoch": 3, "global_epoch": 3, "train_loss": 0.5633160471916199, "train_acc": 0.59, "val_loss": 0.5434638261795044, "val_acc": 0.4}, {"stage": "improved", "epoch": 0, "global_epoch": 4, "train_loss": 0.4538117051124573, "train_acc": 0.625, "val_loss": 0.40872085094451904, "val_acc": 0.94}, {"stage": "improved", "epoch": 1, "global_epoch": 5, "train_loss": 0.3389734774827957, "train_acc": 0.905, "val_loss": 0.29767757654190063, "val_acc": 0.92}, {"stage": "improved", "epoch": 2, "global_epoch": 6, "train_loss": 0.24636229872703552, "train_acc": 0.93, "val_loss": 0.20357388257980347, "val_acc": 0.94}, {"stage": "improved", "epoch": 3, "global_epoch": 7, "train_loss": 0.20410776138305664, "train_acc": 0.93, "val_loss": 0.15568570792675018, "val_acc": 0.94}, {"stage": "improved", "epoch": 4, "global_epoch": 8, "train_loss": 0.1965000480413437, "train_acc": 0.94, "val_loss": 0.14087553322315216, "val_acc": 0.94}, {"stage": "improved", "epoch": 5, "global_epoch": 9, "train_loss": 0.21281804144382477, "train_acc": 0.945, "val_loss": 0.12237977236509323, "val_acc": 0.96}, {"stage": "improved", "epoch": 6, "global_epoch": 10, "train_loss": 0.16892171651124954, "train_acc": 0.94, "val_loss": 0.12416648864746094, "val_acc": 0.96}, {"stage": "improved", "epoch": 7, "global_epoch": 11, "train_loss": 0.1573759689927101, "train_acc": 0.945, "val_loss": 0.12228363007307053, "val_acc": 0.96}, {"stage": "improved", "epoch": 8, "global_epoch": 12, "train_loss": 0.16085848212242126, "train_acc": 0.935, "val_loss": 0.12126311659812927, "val_acc": 0.96}, {"stage": "improved", "epoch": 9, "global_epoch": 13, "train_loss": 0.16218385100364685, "train_acc": 0.945, "val_loss": 0.12771077454090118, "val_acc": 0.96}], "summary": {"total_epochs": 14, "degraded_epochs": 4, "improved_epochs": 10, "patterns": ["sorted_ascending"], "degraded_stage": {"initial_val_loss": 0.7108409404754639, "final_val_loss": 0.5434638261795044, "initial_val_acc": 0.4, "final_val_acc": 0.4, "best_val_acc": 0.4}, "improved_stage": {"initial_val_loss": 0.40872085094451904, "final_val_loss": 0.12771077454090118, "initial_val_acc": 0.94, "final_val_acc": 0.96, "best_val_acc": 0.96, "best_epoch": 9}, "improvement": 0.5599999999999999, "first_improvement_epoch": 3}} |
95 | {"target_pattern": "no_repeats", "degraded_accuracy": 0.48, "improved_accuracy": 0.7, "improvement": 0.21999999999999997, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4662, "learning_rate": 0.06516292890522583, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "no_repeats", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["no_repeats"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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## Activation Signature
### 0
mean: [0.390210, 2.747551, 3.299651, 2.151450, 2.585455, 0.000251, 3.679945]
std: [0.459847, 4.463917, 5.299139, 3.575659, 3.922204, 0.002365, 5.900331]
fourier: [[7.562670, 7.675165, 7.708404, 9.606912, 35.118863], [71.530401, 79.788585, 82.485983, 86.609747, 247.279569], [84.852938, 94.339657, 97.796111, 103.011818, 296.968588], [56.922150, 64.084605, 66.358850, 69.302785, 193.630531], [63.748275, 68.757016, 71.634424, 76.609959, 232.690971], [0.022560, 0.022560, 0.022560, 0.022560, 0.022560], [94.507933, 104.978270, 108.858404, 114.762685, 331.195036]]
input_correlations: [[0.842733, 0.213542, 0.159543, -0.409422, -0.283625, 0.000000, 0.000000, 0.000000], [0.516734, -0.515243, 0.337568, -0.610475, 0.026716, 0.000000, 0.000000, 0.000000], [0.882628, 0.499802, 0.027155, -0.153107, -0.137705, 0.000000, 0.000000, 0.000000], [-0.226388, 0.073296, 0.441100, 0.447470, 0.774605, 0.000000, 0.000000, 0.000000], [0.481565, 0.317721, 0.057135, 0.111493, -0.731302, 0.000000, 0.000000, 0.000000], [0.431435, -0.508068, 0.113906, -0.783624, 0.195008, 0.000000, 0.000000, 0.000000], [0.948489, 0.521413, 0.263208, -0.161308, 0.055520, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.337566, -0.975967, 1.184223, 2.398941, 0.077275, -2.193178, 1.602635]
pre_activation_std: [2.273597, 1.830355, 2.388486, 2.108813, 1.833735, 2.917298, 2.248850]
### 2
mean: [1.343378, 0.629818, -2.997757, -1.253692, 1.699114, 1.179671, 3.153790]
std: [2.395218, 1.345126, 2.066759, 0.653026, 4.658015, 3.567072, 4.031081]
fourier: [[39.490316, 40.538430, 42.266250, 44.149522, 120.904032], [20.223374, 22.374372, 22.782094, 27.144766, 56.683645], [34.958937, 36.026140, 38.503516, 39.753467, 269.798110], [11.002203, 11.047441, 11.171943, 14.612425, 112.832300], [74.396564, 78.794854, 83.484222, 86.881530, 152.920289], [58.444140, 61.765889, 65.141954, 66.346938, 106.170391], [66.303243, 69.597563, 69.953568, 81.208296, 283.841110]]
input_correlations: [[0.936597, 0.393429, 0.973304, -0.523244, 0.769180, 0.377266, 0.944376, 0.000000], [-0.710348, -0.485831, -0.749463, 0.754071, -0.472049, -0.493278, -0.712030, 0.000000], [-0.912543, -0.219638, -0.949129, 0.179517, -0.825438, -0.164317, -0.933467, 0.000000], [-0.437187, -0.139307, -0.399697, -0.610194, -0.418264, -0.100166, -0.487717, 0.000000], [0.953882, 0.454407, 0.961549, -0.519832, 0.772575, 0.427767, 0.930938, 0.000000], [0.958174, 0.487031, 0.963101, -0.462314, 0.732539, 0.479975, 0.946127, 0.000000], [0.942078, 0.619060, 0.931372, -0.288013, 0.672088, 0.600443, 0.949899, 0.000000]]
pre_activation_mean: [1.343378, 0.629818, -2.997757, -1.253692, 1.699114, 1.179671, 3.153790]
pre_activation_std: [2.395218, 1.345126, 2.066759, 0.653026, 4.658015, 3.567072, 4.031081]
### 4
mean: [2.950221, -3.314716, -1.871904, 4.634625, -2.132798, -1.388621, -3.737098]
std: [5.234408, 3.966032, 1.613235, 7.178477, 2.762468, 2.840235, 3.407708]
fourier: [[84.982739, 88.699858, 96.634740, 101.180058, 265.519910], [64.620765, 74.184987, 74.479364, 76.452113, 298.324424], [26.610949, 29.900839, 30.500746, 33.749400, 168.471388], [116.633855, 120.877294, 131.849995, 138.668642, 417.116281], [45.158298, 51.584634, 51.765469, 53.530198, 191.951801], [46.053039, 47.897201, 52.545722, 53.969411, 124.975894], [55.812868, 61.045959, 64.702609, 67.037768, 336.338858]]
input_correlations: [[0.984461, -0.554234, 0.000000, 0.000000, 0.989855, 0.994135, 0.991878, 0.000000], [-0.982522, 0.461733, 0.000000, 0.000000, -0.995684, -0.998317, -0.981419, 0.000000], [-0.959978, 0.331454, 0.000000, 0.000000, -0.981123, -0.981690, -0.942509, 0.000000], [0.987665, -0.565984, 0.000000, 0.000000, 0.990147, 0.992461, 0.990126, 0.000000], [-0.978062, 0.449686, 0.000000, 0.000000, -0.992948, -0.997897, -0.983682, 0.000000], [-0.986639, 0.608214, 0.000000, 0.000000, -0.986150, -0.987712, -0.985342, 0.000000], [-0.966912, 0.410912, 0.000000, 0.000000, -0.981267, -0.990819, -0.985799, 0.000000]]
pre_activation_mean: [2.950221, -3.314716, -1.871904, 4.634625, -2.132798, -1.388621, -3.737098]
pre_activation_std: [5.234408, 3.966032, 1.613235, 7.178477, 2.762468, 2.840235, 3.407708]
### 6
mean: [-1.978409, 2.534803, 3.227492, 1.999772, 2.538306, -2.046431, 3.617971]
std: [4.329888, 4.603413, 5.344915, 3.671444, 3.954306, 2.885921, 5.939583]
fourier: [[70.758042, 72.857614, 78.874050, 84.083445, 178.056843], [75.215228, 77.506518, 83.864764, 89.400739, 228.132254], [86.304866, 93.771514, 97.853539, 104.290280, 290.474305], [59.481495, 63.088458, 67.299070, 71.335201, 179.979520], [64.582256, 67.464240, 71.868512, 77.073894, 228.447516], [46.669737, 49.998651, 52.913304, 56.146162, 184.178789], [95.760801, 104.350772, 108.898818, 115.829742, 325.617354]]
input_correlations: [[-0.997424, 0.000000, 0.000000, -0.999403, 0.000000, 0.469931, 0.000000, 0.000000], [0.997464, 0.000000, 0.000000, 0.999422, 0.000000, -0.469425, 0.000000, 0.000000], [0.999351, 0.000000, 0.000000, 0.999955, 0.000000, -0.433603, 0.000000, 0.000000], [0.998841, 0.000000, 0.000000, 0.999825, 0.000000, -0.450124, 0.000000, 0.000000], [0.997845, 0.000000, 0.000000, 0.999730, 0.000000, -0.460385, 0.000000, 0.000000], [-0.999132, 0.000000, 0.000000, -0.999907, 0.000000, 0.443310, 0.000000, 0.000000], [0.999475, 0.000000, 0.000000, 0.999914, 0.000000, -0.431581, 0.000000, 0.000000]]
pre_activation_mean: [-1.978409, 2.534803, 3.227492, 1.999772, 2.538306, -2.046431, 3.617971]
pre_activation_std: [4.329888, 4.603413, 5.344915, 3.671444, 3.954306, 2.885921, 5.939583]
### 8
mean: [-5.278982]
std: [9.071117]
fourier: [[146.618949, 158.992182, 166.293545, 176.527339, 475.108347]]
input_correlations: [[0.541996, -0.999682, -0.999802, -0.999274, -0.999903, 0.071644, -0.999811, 0.000000]]
pre_activation_mean: [-5.278982]
pre_activation_std: [9.071117]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| no_repeats | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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## Activation Signature
### 0
mean: [0.390210, 2.747551, 3.299651, 2.151450, 2.585455, 0.000251, 3.679945]
std: [0.459847, 4.463917, 5.299139, 3.575659, 3.922204, 0.002365, 5.900331]
fourier: [[7.562670, 7.675165, 7.708404, 9.606912, 35.118863], [71.530401, 79.788585, 82.485983, 86.609747, 247.279569], [84.852938, 94.339657, 97.796111, 103.011818, 296.968588], [56.922150, 64.084605, 66.358850, 69.302785, 193.630531], [63.748275, 68.757016, 71.634424, 76.609959, 232.690971], [0.022560, 0.022560, 0.022560, 0.022560, 0.022560], [94.507933, 104.978270, 108.858404, 114.762685, 331.195036]]
input_correlations: [[0.842733, 0.213542, 0.159543, -0.409422, -0.283625, 0.000000, 0.000000, 0.000000], [0.516734, -0.515243, 0.337568, -0.610475, 0.026716, 0.000000, 0.000000, 0.000000], [0.882628, 0.499802, 0.027155, -0.153107, -0.137705, 0.000000, 0.000000, 0.000000], [-0.226388, 0.073296, 0.441100, 0.447470, 0.774605, 0.000000, 0.000000, 0.000000], [0.481565, 0.317721, 0.057135, 0.111493, -0.731302, 0.000000, 0.000000, 0.000000], [0.431435, -0.508068, 0.113906, -0.783624, 0.195008, 0.000000, 0.000000, 0.000000], [0.948489, 0.521413, 0.263208, -0.161308, 0.055520, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.337566, -0.975967, 1.184223, 2.398941, 0.077275, -2.193178, 1.602635]
pre_activation_std: [2.273597, 1.830355, 2.388486, 2.108813, 1.833735, 2.917298, 2.248850]
### 2
mean: [1.343378, 0.629818, -2.997757, -1.253692, 1.699114, 1.179671, 3.153790]
std: [2.395218, 1.345126, 2.066759, 0.653026, 4.658015, 3.567072, 4.031081]
fourier: [[39.490316, 40.538430, 42.266250, 44.149522, 120.904032], [20.223374, 22.374372, 22.782094, 27.144766, 56.683645], [34.958937, 36.026140, 38.503516, 39.753467, 269.798110], [11.002203, 11.047441, 11.171943, 14.612425, 112.832300], [74.396564, 78.794854, 83.484222, 86.881530, 152.920289], [58.444140, 61.765889, 65.141954, 66.346938, 106.170391], [66.303243, 69.597563, 69.953568, 81.208296, 283.841110]]
input_correlations: [[0.936597, 0.393429, 0.973304, -0.523244, 0.769180, 0.377266, 0.944376, 0.000000], [-0.710348, -0.485831, -0.749463, 0.754071, -0.472049, -0.493278, -0.712030, 0.000000], [-0.912543, -0.219638, -0.949129, 0.179517, -0.825438, -0.164317, -0.933467, 0.000000], [-0.437187, -0.139307, -0.399697, -0.610194, -0.418264, -0.100166, -0.487717, 0.000000], [0.953882, 0.454407, 0.961549, -0.519832, 0.772575, 0.427767, 0.930938, 0.000000], [0.958174, 0.487031, 0.963101, -0.462314, 0.732539, 0.479975, 0.946127, 0.000000], [0.942078, 0.619060, 0.931372, -0.288013, 0.672088, 0.600443, 0.949899, 0.000000]]
pre_activation_mean: [1.343378, 0.629818, -2.997757, -1.253692, 1.699114, 1.179671, 3.153790]
pre_activation_std: [2.395218, 1.345126, 2.066759, 0.653026, 4.658015, 3.567072, 4.031081]
### 4
mean: [2.950221, -3.314716, -1.871904, 4.634625, -2.132798, -1.388621, -3.737098]
std: [5.234408, 3.966032, 1.613235, 7.178477, 2.762468, 2.840235, 3.407708]
fourier: [[84.982739, 88.699858, 96.634740, 101.180058, 265.519910], [64.620765, 74.184987, 74.479364, 76.452113, 298.324424], [26.610949, 29.900839, 30.500746, 33.749400, 168.471388], [116.633855, 120.877294, 131.849995, 138.668642, 417.116281], [45.158298, 51.584634, 51.765469, 53.530198, 191.951801], [46.053039, 47.897201, 52.545722, 53.969411, 124.975894], [55.812868, 61.045959, 64.702609, 67.037768, 336.338858]]
input_correlations: [[0.984461, -0.554234, 0.000000, 0.000000, 0.989855, 0.994135, 0.991878, 0.000000], [-0.982522, 0.461733, 0.000000, 0.000000, -0.995684, -0.998317, -0.981419, 0.000000], [-0.959978, 0.331454, 0.000000, 0.000000, -0.981123, -0.981690, -0.942509, 0.000000], [0.987665, -0.565984, 0.000000, 0.000000, 0.990147, 0.992461, 0.990126, 0.000000], [-0.978062, 0.449686, 0.000000, 0.000000, -0.992948, -0.997897, -0.983682, 0.000000], [-0.986639, 0.608214, 0.000000, 0.000000, -0.986150, -0.987712, -0.985342, 0.000000], [-0.966912, 0.410912, 0.000000, 0.000000, -0.981267, -0.990819, -0.985799, 0.000000]]
pre_activation_mean: [2.950221, -3.314716, -1.871904, 4.634625, -2.132798, -1.388621, -3.737098]
pre_activation_std: [5.234408, 3.966032, 1.613235, 7.178477, 2.762468, 2.840235, 3.407708]
### 6
mean: [-1.978409, 2.534803, 3.227492, 1.999772, 2.538306, -2.046431, 3.617971]
std: [4.329888, 4.603413, 5.344915, 3.671444, 3.954306, 2.885921, 5.939583]
fourier: [[70.758042, 72.857614, 78.874050, 84.083445, 178.056843], [75.215228, 77.506518, 83.864764, 89.400739, 228.132254], [86.304866, 93.771514, 97.853539, 104.290280, 290.474305], [59.481495, 63.088458, 67.299070, 71.335201, 179.979520], [64.582256, 67.464240, 71.868512, 77.073894, 228.447516], [46.669737, 49.998651, 52.913304, 56.146162, 184.178789], [95.760801, 104.350772, 108.898818, 115.829742, 325.617354]]
input_correlations: [[-0.997424, 0.000000, 0.000000, -0.999403, 0.000000, 0.469931, 0.000000, 0.000000], [0.997464, 0.000000, 0.000000, 0.999422, 0.000000, -0.469425, 0.000000, 0.000000], [0.999351, 0.000000, 0.000000, 0.999955, 0.000000, -0.433603, 0.000000, 0.000000], [0.998841, 0.000000, 0.000000, 0.999825, 0.000000, -0.450124, 0.000000, 0.000000], [0.997845, 0.000000, 0.000000, 0.999730, 0.000000, -0.460385, 0.000000, 0.000000], [-0.999132, 0.000000, 0.000000, -0.999907, 0.000000, 0.443310, 0.000000, 0.000000], [0.999475, 0.000000, 0.000000, 0.999914, 0.000000, -0.431581, 0.000000, 0.000000]]
pre_activation_mean: [-1.978409, 2.534803, 3.227492, 1.999772, 2.538306, -2.046431, 3.617971]
pre_activation_std: [4.329888, 4.603413, 5.344915, 3.671444, 3.954306, 2.885921, 5.939583]
### 8
mean: [-5.278982]
std: [9.071117]
fourier: [[146.618949, 158.992182, 166.293545, 176.527339, 475.108347]]
input_correlations: [[0.541996, -0.999682, -0.999802, -0.999274, -0.999903, 0.071644, -0.999811, 0.000000]]
pre_activation_mean: [-5.278982]
pre_activation_std: [9.071117]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
no_repeats | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.3902095854282379, "std": 0.4598469138145447, "fourier": [7.562670272013773, 7.67516508471344, 7.708403709723474, 9.606912474830708, 35.11886274814606], "input_correlations": [0.8427334180971889, 0.21354161805238261, 0.15954326132505572, -0.40942172428837, -0.2836245058595518, 0.0, 0.0, 0.0], "pre_activation_mean": -0.33756595849990845, "pre_activation_std": 2.273597478866577}, "1": {"mean": 2.7475507259368896, "std": 4.463917255401611, "fourier": [71.53040050271906, 79.7885847743362, 82.48598256324723, 86.60974650923697, 247.2795692384243], "input_correlations": [0.5167340936896128, -0.5152430666929506, 0.3375684739648591, -0.6104751943623565, 0.026716303678164712, 0.0, 0.0, 0.0], "pre_activation_mean": -0.9759674072265625, "pre_activation_std": 1.8303552865982056}, "2": {"mean": 3.2996506690979004, "std": 5.299139499664307, "fourier": [84.85293837273046, 94.33965675731946, 97.79611102426664, 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"best_val_acc": 0.48}, "improved_stage": {"initial_val_loss": 0.6214572191238403, "final_val_loss": 0.5503203868865967, "initial_val_acc": 0.64, "final_val_acc": 0.68, "best_val_acc": 0.7, "best_epoch": 7}, "improvement": 0.21999999999999997, "first_improvement_epoch": 2}} |
96 | {"target_pattern": "sorted_ascending", "degraded_accuracy": 0.48, "improved_accuracy": 0.9, "improvement": 0.42000000000000004, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 7, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 3299, "learning_rate": 0.06432301658833305, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_ascending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_ascending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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],
[
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0.107225,
0.197235,
-0.248458
],
[
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0.080985,
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]
],
"network.6.bias": [
-0.311876,
0.960484,
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0.98122
],
"network.8.weight": [
[
0.156552,
1.442448,
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1.293353
],
[
0.104826,
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0.247302,
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],
[
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],
[
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],
[
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0.088708,
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0.044512
],
[
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0.028971,
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],
[
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]
],
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1.301196,
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"network.10.weight": [
[
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0.070771,
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],
"network.10.bias": [
0.805182
]
}
## Activation Signature
### 0
mean: [3.312451, 0.000000, 0.000000, 2.315450, 0.000000, 0.000000, 0.000000]
std: [1.810328, 0.000000, 0.000000, 1.263973, 0.000000, 0.000000, 0.000000]
fourier: [[29.001148, 29.256278, 30.997593, 36.545219, 298.120580], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [19.496963, 20.115719, 21.247596, 25.608497, 208.390530], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.727379, 0.724690, 0.671749, -0.046010, 0.065834, 0.000000, 0.000000, 0.000000], [0.792619, 0.807783, 0.441001, 0.108051, -0.010275, 0.000000, 0.000000, 0.000000], [0.855960, 0.721787, 0.341859, 0.072738, -0.091697, 0.000000, 0.000000, 0.000000], [-0.835586, -0.699424, -0.498067, -0.202179, 0.053195, 0.000000, 0.000000, 0.000000], [0.905688, 0.565435, 0.545209, 0.013471, -0.014856, 0.000000, 0.000000, 0.000000], [-0.791104, -0.498747, -0.654530, -0.254498, -0.544875, 0.000000, 0.000000, 0.000000], [-0.716778, -0.755680, -0.422172, -0.135689, 0.272169, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.028580, 3.339045, 1.989637, -2.747793, 2.197610, -3.163167, -1.953445]
pre_activation_std: [2.970602, 3.537587, 3.278189, 2.981925, 2.613872, 2.335057, 2.873148]
### 2
mean: [-3.156437, 4.465845, -2.461141, -3.819126, -4.161775, -0.974813, -3.629943]
std: [2.823847, 4.989691, 2.415336, 4.725096, 5.298696, 0.915778, 3.038779]
fourier: [[46.145079, 47.432234, 47.816500, 50.230596, 284.079332], [82.190833, 83.544253, 86.532687, 87.814577, 401.926044], [39.492783, 39.551274, 41.354577, 41.582645, 221.502677], [76.599358, 80.333742, 82.155422, 82.859017, 343.721363], [84.404366, 90.668842, 92.055930, 95.232141, 374.559734], [15.026122, 15.496304, 15.737652, 15.837848, 87.733211], [47.538025, 48.876342, 52.738218, 52.850567, 326.694812]]
input_correlations: [[-0.946004, -0.991478, -0.983784, 0.330537, -0.975334, 0.000000, 0.358579, 0.000000], [0.965411, 0.990954, 0.968653, -0.370193, 0.970062, 0.000000, -0.403794, 0.000000], [-0.908756, -0.983128, -0.992533, 0.200595, -0.945536, 0.000000, 0.231958, 0.000000], [-0.980792, -0.982950, -0.944405, 0.406991, -0.958656, 0.000000, 0.436075, 0.000000], [-0.979839, -0.977896, -0.936741, 0.428691, -0.957591, 0.000000, 0.464017, 0.000000], [-0.975971, -0.992738, -0.954157, 0.366046, -0.950689, 0.000000, 0.388835, 0.000000], [-0.955463, -0.994994, -0.978275, 0.278738, -0.955895, 0.000000, 0.303848, 0.000000]]
pre_activation_mean: [-3.156437, 4.465845, -2.461141, -3.819126, -4.161775, -0.974813, -3.629943]
pre_activation_std: [2.823847, 4.989691, 2.415336, 4.725096, 5.298696, 0.915778, 3.038779]
### 4
mean: [0.433389, -0.977754, -0.563730, -1.421260, -1.922255, -1.170143, -0.027661]
std: [0.604557, 2.136436, 2.093259, 0.710529, 1.515297, 2.121789, 0.502605]
fourier: [[8.338049, 9.167018, 9.320257, 11.865416, 39.004986], [35.803151, 36.954796, 38.299108, 39.438307, 87.997838], [35.747233, 36.321517, 37.133780, 38.721896, 50.735673], [12.001143, 12.082538, 12.749349, 12.819369, 127.913400], [24.301326, 25.409854, 26.308440, 26.736616, 173.002913], [34.993493, 36.958830, 38.368899, 38.962472, 105.312879], [7.818561, 8.106897, 8.256303, 8.615225, 8.851261]]
input_correlations: [[0.000000, -0.161354, 0.000000, 0.959926, 0.963303, 0.654184, 0.000000, 0.000000], [0.000000, -0.910303, 0.000000, 0.754635, 0.754538, 0.380081, 0.000000, 0.000000], [0.000000, -0.858831, 0.000000, 0.821910, 0.822513, 0.435855, 0.000000, 0.000000], [0.000000, -0.961912, 0.000000, 0.155667, 0.151894, -0.054815, 0.000000, 0.000000], [0.000000, -0.990404, 0.000000, 0.289945, 0.286762, 0.035871, 0.000000, 0.000000], [0.000000, -0.928998, 0.000000, 0.721937, 0.722954, 0.353651, 0.000000, 0.000000], [0.000000, 0.998993, 0.000000, -0.397060, -0.391070, -0.112333, 0.000000, 0.000000]]
pre_activation_mean: [0.433389, -0.977754, -0.563730, -1.421260, -1.922255, -1.170143, -0.027661]
pre_activation_std: [0.604557, 2.136436, 2.093259, 0.710529, 1.515297, 2.121789, 0.502605]
### 6
mean: [-0.865611, 0.768557, 0.581313, 0.740246, -0.736379, 0.196012, 0.251295]
std: [1.176245, 1.078236, 1.917314, 2.377686, 0.614296, 1.169585, 1.500115]
fourier: [[18.318190, 18.863364, 19.595622, 23.112044, 77.905021], [17.462516, 18.223915, 19.120245, 20.443286, 69.170163], [30.329761, 31.052522, 32.100601, 37.625700, 52.318177], [37.666304, 38.437087, 39.675844, 46.606569, 66.622177], [8.963784, 9.162029, 9.784493, 12.176653, 66.274117], [18.757005, 19.167746, 19.607804, 19.670377, 22.704971], [22.616562, 23.334934, 23.792355, 24.985923, 29.528204]]
input_correlations: [[-0.966230, -0.999884, -0.999725, 0.000000, 0.000000, -0.999332, 0.235011, 0.000000], [-0.841679, -0.953127, -0.954912, 0.000000, 0.000000, -0.950901, 0.520771, 0.000000], [0.957934, 0.999629, 0.999687, 0.000000, 0.000000, 0.998894, -0.262970, 0.000000], [0.953461, 0.999076, 0.999043, 0.000000, 0.000000, 0.998472, -0.280161, 0.000000], [-0.998686, -0.968730, -0.966546, 0.000000, 0.000000, -0.970137, -0.006560, 0.000000], [0.919917, 0.990546, 0.991524, 0.000000, 0.000000, 0.988851, -0.368136, 0.000000], [-0.973156, -0.999231, -0.998966, 0.000000, 0.000000, -0.998837, 0.204757, 0.000000]]
pre_activation_mean: [-0.865611, 0.768557, 0.581313, 0.740246, -0.736379, 0.196012, 0.251295]
pre_activation_std: [1.176245, 1.078236, 1.917314, 2.377686, 0.614296, 1.169585, 1.500115]
### 8
mean: [2.456421, -1.319133, -1.366961, 1.507277, -0.853197, -1.357243, -0.616319]
std: [3.747590, 1.131629, 0.952657, 3.096754, 1.352048, 0.577969, 0.875273]
fourier: [[59.769230, 62.974963, 67.221047, 72.035742, 221.077853], [16.714004, 18.147806, 18.407898, 22.232527, 118.721980], [13.367857, 14.866672, 15.052789, 18.762746, 123.026521], [48.512686, 52.208455, 54.653626, 59.886534, 135.654905], [21.236242, 21.576255, 22.498160, 26.661644, 76.787722], [7.931660, 7.970079, 7.972069, 10.731168, 122.151903], [12.990542, 13.161672, 14.365076, 17.321518, 55.468712]]
input_correlations: [[0.000000, 0.824191, -0.976370, -0.976104, 0.000000, -0.975383, 0.870484, 0.000000], [0.000000, 0.609285, -0.990295, -0.990485, 0.000000, -0.990960, 0.704746, 0.000000], [0.000000, 0.534523, -0.979166, -0.979391, 0.000000, -0.979913, 0.697812, 0.000000], [0.000000, 0.799095, -0.983928, -0.983698, 0.000000, -0.983057, 0.866359, 0.000000], [0.000000, 0.694645, -0.999984, -0.999975, 0.000000, -0.999925, 0.794693, 0.000000], [0.000000, 0.200488, -0.841468, -0.842071, 0.000000, -0.843574, 0.456667, 0.000000], [0.000000, 0.596172, -0.988468, -0.988499, 0.000000, -0.988468, 0.792648, 0.000000]]
pre_activation_mean: [2.456421, -1.319133, -1.366961, 1.507277, -0.853197, -1.357243, -0.616319]
pre_activation_std: [3.747590, 1.131629, 0.952657, 3.096754, 1.352048, 0.577969, 0.875273]
### 10
mean: [-4.953360]
std: [3.145231]
fourier: [[49.858353, 50.606827, 53.584976, 63.577357, 445.802353]]
input_correlations: [[-0.999886, 0.000000, 0.000000, -0.999313, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.953360]
pre_activation_std: [3.145231]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_ascending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 7
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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],
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[
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],
[
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[
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],
[
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0.670738
]
],
"network.0.bias": [
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"network.2.weight": [
[
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-0.380731,
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0.257806,
-0.339002,
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-0.084737
],
[
0.498475,
0.451003,
0.370872,
-0.141646,
0.349074,
0.219705,
-0.324259
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[
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0.042984,
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[
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0.429831,
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],
[
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],
[
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0.032796,
0.09123,
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0.207418,
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[
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0.148351,
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]
],
"network.2.bias": [
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0.621388,
0.728596,
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],
"network.4.weight": [
[
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0.036046,
0.107986,
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0.124168,
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[
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0.961004,
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[
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0.125584,
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0.023592
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[
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"network.6.weight": [
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],
"network.10.bias": [
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]
}
## Activation Signature
### 0
mean: [3.312451, 0.000000, 0.000000, 2.315450, 0.000000, 0.000000, 0.000000]
std: [1.810328, 0.000000, 0.000000, 1.263973, 0.000000, 0.000000, 0.000000]
fourier: [[29.001148, 29.256278, 30.997593, 36.545219, 298.120580], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [19.496963, 20.115719, 21.247596, 25.608497, 208.390530], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.727379, 0.724690, 0.671749, -0.046010, 0.065834, 0.000000, 0.000000, 0.000000], [0.792619, 0.807783, 0.441001, 0.108051, -0.010275, 0.000000, 0.000000, 0.000000], [0.855960, 0.721787, 0.341859, 0.072738, -0.091697, 0.000000, 0.000000, 0.000000], [-0.835586, -0.699424, -0.498067, -0.202179, 0.053195, 0.000000, 0.000000, 0.000000], [0.905688, 0.565435, 0.545209, 0.013471, -0.014856, 0.000000, 0.000000, 0.000000], [-0.791104, -0.498747, -0.654530, -0.254498, -0.544875, 0.000000, 0.000000, 0.000000], [-0.716778, -0.755680, -0.422172, -0.135689, 0.272169, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [3.028580, 3.339045, 1.989637, -2.747793, 2.197610, -3.163167, -1.953445]
pre_activation_std: [2.970602, 3.537587, 3.278189, 2.981925, 2.613872, 2.335057, 2.873148]
### 2
mean: [-3.156437, 4.465845, -2.461141, -3.819126, -4.161775, -0.974813, -3.629943]
std: [2.823847, 4.989691, 2.415336, 4.725096, 5.298696, 0.915778, 3.038779]
fourier: [[46.145079, 47.432234, 47.816500, 50.230596, 284.079332], [82.190833, 83.544253, 86.532687, 87.814577, 401.926044], [39.492783, 39.551274, 41.354577, 41.582645, 221.502677], [76.599358, 80.333742, 82.155422, 82.859017, 343.721363], [84.404366, 90.668842, 92.055930, 95.232141, 374.559734], [15.026122, 15.496304, 15.737652, 15.837848, 87.733211], [47.538025, 48.876342, 52.738218, 52.850567, 326.694812]]
input_correlations: [[-0.946004, -0.991478, -0.983784, 0.330537, -0.975334, 0.000000, 0.358579, 0.000000], [0.965411, 0.990954, 0.968653, -0.370193, 0.970062, 0.000000, -0.403794, 0.000000], [-0.908756, -0.983128, -0.992533, 0.200595, -0.945536, 0.000000, 0.231958, 0.000000], [-0.980792, -0.982950, -0.944405, 0.406991, -0.958656, 0.000000, 0.436075, 0.000000], [-0.979839, -0.977896, -0.936741, 0.428691, -0.957591, 0.000000, 0.464017, 0.000000], [-0.975971, -0.992738, -0.954157, 0.366046, -0.950689, 0.000000, 0.388835, 0.000000], [-0.955463, -0.994994, -0.978275, 0.278738, -0.955895, 0.000000, 0.303848, 0.000000]]
pre_activation_mean: [-3.156437, 4.465845, -2.461141, -3.819126, -4.161775, -0.974813, -3.629943]
pre_activation_std: [2.823847, 4.989691, 2.415336, 4.725096, 5.298696, 0.915778, 3.038779]
### 4
mean: [0.433389, -0.977754, -0.563730, -1.421260, -1.922255, -1.170143, -0.027661]
std: [0.604557, 2.136436, 2.093259, 0.710529, 1.515297, 2.121789, 0.502605]
fourier: [[8.338049, 9.167018, 9.320257, 11.865416, 39.004986], [35.803151, 36.954796, 38.299108, 39.438307, 87.997838], [35.747233, 36.321517, 37.133780, 38.721896, 50.735673], [12.001143, 12.082538, 12.749349, 12.819369, 127.913400], [24.301326, 25.409854, 26.308440, 26.736616, 173.002913], [34.993493, 36.958830, 38.368899, 38.962472, 105.312879], [7.818561, 8.106897, 8.256303, 8.615225, 8.851261]]
input_correlations: [[0.000000, -0.161354, 0.000000, 0.959926, 0.963303, 0.654184, 0.000000, 0.000000], [0.000000, -0.910303, 0.000000, 0.754635, 0.754538, 0.380081, 0.000000, 0.000000], [0.000000, -0.858831, 0.000000, 0.821910, 0.822513, 0.435855, 0.000000, 0.000000], [0.000000, -0.961912, 0.000000, 0.155667, 0.151894, -0.054815, 0.000000, 0.000000], [0.000000, -0.990404, 0.000000, 0.289945, 0.286762, 0.035871, 0.000000, 0.000000], [0.000000, -0.928998, 0.000000, 0.721937, 0.722954, 0.353651, 0.000000, 0.000000], [0.000000, 0.998993, 0.000000, -0.397060, -0.391070, -0.112333, 0.000000, 0.000000]]
pre_activation_mean: [0.433389, -0.977754, -0.563730, -1.421260, -1.922255, -1.170143, -0.027661]
pre_activation_std: [0.604557, 2.136436, 2.093259, 0.710529, 1.515297, 2.121789, 0.502605]
### 6
mean: [-0.865611, 0.768557, 0.581313, 0.740246, -0.736379, 0.196012, 0.251295]
std: [1.176245, 1.078236, 1.917314, 2.377686, 0.614296, 1.169585, 1.500115]
fourier: [[18.318190, 18.863364, 19.595622, 23.112044, 77.905021], [17.462516, 18.223915, 19.120245, 20.443286, 69.170163], [30.329761, 31.052522, 32.100601, 37.625700, 52.318177], [37.666304, 38.437087, 39.675844, 46.606569, 66.622177], [8.963784, 9.162029, 9.784493, 12.176653, 66.274117], [18.757005, 19.167746, 19.607804, 19.670377, 22.704971], [22.616562, 23.334934, 23.792355, 24.985923, 29.528204]]
input_correlations: [[-0.966230, -0.999884, -0.999725, 0.000000, 0.000000, -0.999332, 0.235011, 0.000000], [-0.841679, -0.953127, -0.954912, 0.000000, 0.000000, -0.950901, 0.520771, 0.000000], [0.957934, 0.999629, 0.999687, 0.000000, 0.000000, 0.998894, -0.262970, 0.000000], [0.953461, 0.999076, 0.999043, 0.000000, 0.000000, 0.998472, -0.280161, 0.000000], [-0.998686, -0.968730, -0.966546, 0.000000, 0.000000, -0.970137, -0.006560, 0.000000], [0.919917, 0.990546, 0.991524, 0.000000, 0.000000, 0.988851, -0.368136, 0.000000], [-0.973156, -0.999231, -0.998966, 0.000000, 0.000000, -0.998837, 0.204757, 0.000000]]
pre_activation_mean: [-0.865611, 0.768557, 0.581313, 0.740246, -0.736379, 0.196012, 0.251295]
pre_activation_std: [1.176245, 1.078236, 1.917314, 2.377686, 0.614296, 1.169585, 1.500115]
### 8
mean: [2.456421, -1.319133, -1.366961, 1.507277, -0.853197, -1.357243, -0.616319]
std: [3.747590, 1.131629, 0.952657, 3.096754, 1.352048, 0.577969, 0.875273]
fourier: [[59.769230, 62.974963, 67.221047, 72.035742, 221.077853], [16.714004, 18.147806, 18.407898, 22.232527, 118.721980], [13.367857, 14.866672, 15.052789, 18.762746, 123.026521], [48.512686, 52.208455, 54.653626, 59.886534, 135.654905], [21.236242, 21.576255, 22.498160, 26.661644, 76.787722], [7.931660, 7.970079, 7.972069, 10.731168, 122.151903], [12.990542, 13.161672, 14.365076, 17.321518, 55.468712]]
input_correlations: [[0.000000, 0.824191, -0.976370, -0.976104, 0.000000, -0.975383, 0.870484, 0.000000], [0.000000, 0.609285, -0.990295, -0.990485, 0.000000, -0.990960, 0.704746, 0.000000], [0.000000, 0.534523, -0.979166, -0.979391, 0.000000, -0.979913, 0.697812, 0.000000], [0.000000, 0.799095, -0.983928, -0.983698, 0.000000, -0.983057, 0.866359, 0.000000], [0.000000, 0.694645, -0.999984, -0.999975, 0.000000, -0.999925, 0.794693, 0.000000], [0.000000, 0.200488, -0.841468, -0.842071, 0.000000, -0.843574, 0.456667, 0.000000], [0.000000, 0.596172, -0.988468, -0.988499, 0.000000, -0.988468, 0.792648, 0.000000]]
pre_activation_mean: [2.456421, -1.319133, -1.366961, 1.507277, -0.853197, -1.357243, -0.616319]
pre_activation_std: [3.747590, 1.131629, 0.952657, 3.096754, 1.352048, 0.577969, 0.875273]
### 10
mean: [-4.953360]
std: [3.145231]
fourier: [[49.858353, 50.606827, 53.584976, 63.577357, 445.802353]]
input_correlations: [[-0.999886, 0.000000, 0.000000, -0.999313, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.953360]
pre_activation_std: [3.145231]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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{"stage": "improved", "epoch": 2, "global_epoch": 7, "train_loss": 0.5385349690914154, "train_acc": 0.86, "val_loss": 0.5293724536895752, "val_acc": 0.84}, {"stage": "improved", "epoch": 3, "global_epoch": 8, "train_loss": 0.5140665173530579, "train_acc": 0.84, "val_loss": 0.4905635416507721, "val_acc": 0.84}, {"stage": "improved", "epoch": 4, "global_epoch": 9, "train_loss": 0.44045673310756683, "train_acc": 0.86, "val_loss": 0.4340042173862457, "val_acc": 0.86}, {"stage": "improved", "epoch": 5, "global_epoch": 10, "train_loss": 0.3973613828420639, "train_acc": 0.88, "val_loss": 0.401375412940979, "val_acc": 0.86}, {"stage": "improved", "epoch": 6, "global_epoch": 11, "train_loss": 0.343682125210762, "train_acc": 0.9, "val_loss": 0.3602246940135956, "val_acc": 0.88}, {"stage": "improved", "epoch": 7, "global_epoch": 12, "train_loss": 0.2783324867486954, "train_acc": 0.95, "val_loss": 0.6269707679748535, "val_acc": 0.86}, {"stage": "improved", "epoch": 8, "global_epoch": 13, 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97 | {"target_pattern": "first_last_match", "degraded_accuracy": 0.38, "improved_accuracy": 0.92, "improvement": 0.54, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 5, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 4130, "learning_rate": 0.07546547592586104, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "first_last_match", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["first_last_match"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
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-0.294755,
-0.32261,
-0.211231,
-0.247445,
-0.460398
],
"network.10.weight": [
[
0.109448,
-0.574317,
0.233277,
-0.411705,
0.122255
]
],
"network.10.bias": [
0.513447
]
}
## Activation Signature
### 0
mean: [0.000000, 4.998133, 0.000000, 0.000000, 0.000000]
std: [0.000000, 6.873722, 0.000000, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [121.067615, 129.198003, 133.617456, 148.229649, 449.831969], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.826170, 0.178683, 0.079139, -0.107237, 0.610632, 0.000000, 0.000000, 0.000000], [-0.589984, -0.695894, -0.339492, -0.643061, -0.484689, 0.000000, 0.000000, 0.000000], [0.744704, 0.063786, 0.011973, -0.112633, 0.676448, 0.000000, 0.000000, 0.000000], [-0.282364, -0.568116, -0.758159, -0.274613, -0.615375, 0.000000, 0.000000, 0.000000], [-0.598550, -0.382250, -0.033822, 0.003633, 0.658490, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.917831, -2.496580, 0.506520, -2.890311, -0.021823]
pre_activation_std: [2.824270, 1.707467, 2.110606, 1.673711, 2.211673]
### 2
mean: [-0.765583, 1.971160, -1.155307, 1.238985, 1.991191]
std: [0.567955, 2.589375, 1.435434, 1.840725, 2.465594]
fourier: [[8.592167, 10.160531, 10.388460, 11.738357, 68.902450], [44.964833, 50.280220, 50.298494, 54.616423, 177.404431], [27.151840, 27.978771, 27.983808, 29.285950, 103.977667], [29.155927, 33.781686, 34.503645, 38.467924, 111.508648], [47.006127, 48.479567, 49.175013, 50.364311, 179.207157]]
input_correlations: [[-0.596441, 0.000000, -0.679276, 0.000000, -0.894038, 0.000000, 0.000000, 0.000000], [0.774251, 0.000000, 0.838846, 0.000000, 0.757113, 0.000000, 0.000000, 0.000000], [-0.942846, 0.000000, -0.973001, 0.000000, -0.489078, 0.000000, 0.000000, 0.000000], [0.647665, 0.000000, 0.725521, 0.000000, 0.862820, 0.000000, 0.000000, 0.000000], [0.934766, 0.000000, 0.964089, 0.000000, 0.512048, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.765583, 1.971160, -1.155307, 1.238985, 1.991191]
pre_activation_std: [0.567955, 2.589375, 1.435434, 1.840725, 2.465594]
### 4
mean: [-0.889833, -1.091558, -1.279288, 3.579700, 2.408972]
std: [1.204056, 1.038035, 1.519091, 4.594157, 3.680950]
fourier: [[21.886626, 23.684314, 23.952843, 25.092280, 80.085006], [18.729851, 20.352324, 20.560217, 21.709494, 98.240231], [28.016217, 30.238654, 30.346224, 31.593808, 115.135911], [81.264467, 89.282545, 90.004116, 97.139670, 322.173007], [66.806945, 72.734303, 72.865725, 77.119323, 216.807471]]
input_correlations: [[0.000000, -0.993160, 0.000000, -0.953149, -0.978630, 0.000000, 0.000000, 0.000000], [0.000000, -0.995446, 0.000000, -0.959391, -0.973945, 0.000000, 0.000000, 0.000000], [0.000000, -0.989485, 0.000000, -0.945176, -0.983942, 0.000000, 0.000000, 0.000000], [0.000000, 0.999512, 0.000000, 0.976218, 0.957063, 0.000000, 0.000000, 0.000000], [0.000000, 0.995035, 0.000000, 0.958731, 0.974971, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.889833, -1.091558, -1.279288, 3.579700, 2.408972]
pre_activation_std: [1.204056, 1.038035, 1.519091, 4.594157, 3.680950]
### 6
mean: [-0.443201, 3.836598, 4.099306, 3.765587, -0.347616]
std: [0.128220, 5.548075, 5.367137, 5.349271, 0.273025]
fourier: [[1.635258, 2.636289, 2.708741, 3.023543, 39.888089], [99.016388, 106.805667, 108.699921, 118.181350, 345.293802], [95.585306, 103.473382, 105.125791, 114.225430, 368.937529], [95.217816, 103.314579, 104.822648, 113.704976, 338.902831], [4.430398, 5.153597, 5.298655, 5.412513, 31.285397]]
input_correlations: [[0.435623, 0.000000, 0.000000, -0.313572, -0.237050, 0.000000, 0.000000, 0.000000], [-0.520063, 0.000000, 0.000000, 0.998877, 0.999478, 0.000000, 0.000000, 0.000000], [-0.522000, 0.000000, 0.000000, 0.999366, 0.999021, 0.000000, 0.000000, 0.000000], [-0.525166, 0.000000, 0.000000, 0.999481, 0.998874, 0.000000, 0.000000, 0.000000], [0.556630, 0.000000, 0.000000, -0.967585, -0.944815, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.443201, 3.836598, 4.099306, 3.765587, -0.347616]
pre_activation_std: [0.128220, 5.548075, 5.367137, 5.349271, 0.273025]
### 8
mean: [-2.366637, 4.859083, -0.213184, -2.254100, -1.272927]
std: [2.751796, 6.975764, 0.081277, 2.687388, 1.066303]
fourier: [[48.980344, 52.668112, 53.838343, 58.774941, 212.997353], [123.662276, 132.906324, 136.098326, 149.521683, 437.317457], [1.217365, 1.243416, 1.702471, 1.904251, 19.186567], [47.743164, 51.271018, 52.503040, 57.521865, 202.868970], [18.977708, 20.540462, 20.876054, 22.707732, 114.563463]]
input_correlations: [[0.000000, -0.999877, -0.999893, -0.999902, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999918, 0.999857, 0.999985, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.885547, -0.873192, -0.881492, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999932, -0.999852, -0.999938, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999605, -0.999999, -0.999868, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.366637, 4.859083, -0.213184, -2.254100, -1.272927]
pre_activation_std: [2.751796, 6.975764, 0.081277, 2.687388, 1.066303]
### 10
mean: [-2.357065]
std: [3.947695]
fourier: [[69.531181, 74.200600, 76.738765, 85.130796, 212.135873]]
input_correlations: [[0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.357065]
pre_activation_std: [3.947695]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| first_last_match | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 5
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
1.116816,
0.047952,
-0.434068,
-0.215021,
0.847645
],
[
-0.344087,
-0.360907,
-0.042553,
-0.395751,
-0.303847
],
[
0.781956,
-0.067411,
-0.377971,
-0.150731,
0.729568
],
[
0.128022,
-0.435686,
-0.508954,
-0.020752,
-0.465848
],
[
-0.790962,
-0.137859,
0.058691,
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0.953854
]
],
"network.0.bias": [
-0.23697,
-0.09843,
-0.130771,
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0.170523
],
"network.2.weight": [
[
-0.11596,
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0.003412,
0.218023,
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],
[
0.480917,
0.214398,
0.404968,
0.101097,
1.162747
],
[
-0.320984,
0.205741,
-0.351142,
0.1172,
-0.305626
],
[
0.406388,
-0.028786,
0.013666,
-0.11582,
1.040497
],
[
0.848998,
-0.208188,
0.143253,
0.066414,
0.631617
]
],
"network.2.bias": [
-0.334436,
-0.091784,
-0.042612,
-0.188749,
0.038755
],
"network.4.weight": [
[
0.113484,
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0.035573,
0.167209,
-0.107417
],
[
-0.327338,
-0.449604,
0.300554,
0.150298,
-0.061449
],
[
0.237835,
-0.011517,
0.399411,
-0.297132,
-0.405989
],
[
0.153301,
0.878571,
0.083662,
0.698136,
0.471714
],
[
-0.084909,
0.607893,
0.386771,
0.365945,
0.622488
]
],
"network.4.bias": [
0.071247,
-0.266097,
-0.062637,
-0.019471,
-0.519106
],
"network.6.weight": [
[
-0.218284,
0.309424,
0.364191,
-0.346697,
0.440162
],
[
-0.012542,
0.123764,
-0.261171,
0.489525,
0.935692
],
[
0.590721,
0.00061,
-0.130864,
0.665353,
0.658301
],
[
-0.013118,
0.324461,
-0.316363,
0.693648,
0.613715
],
[
-0.58741,
-0.201636,
-0.265828,
-0.258812,
0.260111
]
],
"network.6.bias": [
-0.345252,
-0.35551,
-0.011405,
-0.317705,
-0.087194
],
"network.8.weight": [
[
0.110093,
-0.384146,
-0.3999,
0.282232,
-0.349088
],
[
0.112826,
0.456543,
0.289749,
0.559049,
0.082758
],
[
-0.353385,
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0.383176,
-0.344343,
-0.180131
],
[
-0.027155,
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0.100203,
0.26722
],
[
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]
],
"network.8.bias": [
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-0.32261,
-0.211231,
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],
"network.10.weight": [
[
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-0.574317,
0.233277,
-0.411705,
0.122255
]
],
"network.10.bias": [
0.513447
]
}
## Activation Signature
### 0
mean: [0.000000, 4.998133, 0.000000, 0.000000, 0.000000]
std: [0.000000, 6.873722, 0.000000, 0.000000, 0.000000]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [121.067615, 129.198003, 133.617456, 148.229649, 449.831969], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[0.826170, 0.178683, 0.079139, -0.107237, 0.610632, 0.000000, 0.000000, 0.000000], [-0.589984, -0.695894, -0.339492, -0.643061, -0.484689, 0.000000, 0.000000, 0.000000], [0.744704, 0.063786, 0.011973, -0.112633, 0.676448, 0.000000, 0.000000, 0.000000], [-0.282364, -0.568116, -0.758159, -0.274613, -0.615375, 0.000000, 0.000000, 0.000000], [-0.598550, -0.382250, -0.033822, 0.003633, 0.658490, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.917831, -2.496580, 0.506520, -2.890311, -0.021823]
pre_activation_std: [2.824270, 1.707467, 2.110606, 1.673711, 2.211673]
### 2
mean: [-0.765583, 1.971160, -1.155307, 1.238985, 1.991191]
std: [0.567955, 2.589375, 1.435434, 1.840725, 2.465594]
fourier: [[8.592167, 10.160531, 10.388460, 11.738357, 68.902450], [44.964833, 50.280220, 50.298494, 54.616423, 177.404431], [27.151840, 27.978771, 27.983808, 29.285950, 103.977667], [29.155927, 33.781686, 34.503645, 38.467924, 111.508648], [47.006127, 48.479567, 49.175013, 50.364311, 179.207157]]
input_correlations: [[-0.596441, 0.000000, -0.679276, 0.000000, -0.894038, 0.000000, 0.000000, 0.000000], [0.774251, 0.000000, 0.838846, 0.000000, 0.757113, 0.000000, 0.000000, 0.000000], [-0.942846, 0.000000, -0.973001, 0.000000, -0.489078, 0.000000, 0.000000, 0.000000], [0.647665, 0.000000, 0.725521, 0.000000, 0.862820, 0.000000, 0.000000, 0.000000], [0.934766, 0.000000, 0.964089, 0.000000, 0.512048, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.765583, 1.971160, -1.155307, 1.238985, 1.991191]
pre_activation_std: [0.567955, 2.589375, 1.435434, 1.840725, 2.465594]
### 4
mean: [-0.889833, -1.091558, -1.279288, 3.579700, 2.408972]
std: [1.204056, 1.038035, 1.519091, 4.594157, 3.680950]
fourier: [[21.886626, 23.684314, 23.952843, 25.092280, 80.085006], [18.729851, 20.352324, 20.560217, 21.709494, 98.240231], [28.016217, 30.238654, 30.346224, 31.593808, 115.135911], [81.264467, 89.282545, 90.004116, 97.139670, 322.173007], [66.806945, 72.734303, 72.865725, 77.119323, 216.807471]]
input_correlations: [[0.000000, -0.993160, 0.000000, -0.953149, -0.978630, 0.000000, 0.000000, 0.000000], [0.000000, -0.995446, 0.000000, -0.959391, -0.973945, 0.000000, 0.000000, 0.000000], [0.000000, -0.989485, 0.000000, -0.945176, -0.983942, 0.000000, 0.000000, 0.000000], [0.000000, 0.999512, 0.000000, 0.976218, 0.957063, 0.000000, 0.000000, 0.000000], [0.000000, 0.995035, 0.000000, 0.958731, 0.974971, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.889833, -1.091558, -1.279288, 3.579700, 2.408972]
pre_activation_std: [1.204056, 1.038035, 1.519091, 4.594157, 3.680950]
### 6
mean: [-0.443201, 3.836598, 4.099306, 3.765587, -0.347616]
std: [0.128220, 5.548075, 5.367137, 5.349271, 0.273025]
fourier: [[1.635258, 2.636289, 2.708741, 3.023543, 39.888089], [99.016388, 106.805667, 108.699921, 118.181350, 345.293802], [95.585306, 103.473382, 105.125791, 114.225430, 368.937529], [95.217816, 103.314579, 104.822648, 113.704976, 338.902831], [4.430398, 5.153597, 5.298655, 5.412513, 31.285397]]
input_correlations: [[0.435623, 0.000000, 0.000000, -0.313572, -0.237050, 0.000000, 0.000000, 0.000000], [-0.520063, 0.000000, 0.000000, 0.998877, 0.999478, 0.000000, 0.000000, 0.000000], [-0.522000, 0.000000, 0.000000, 0.999366, 0.999021, 0.000000, 0.000000, 0.000000], [-0.525166, 0.000000, 0.000000, 0.999481, 0.998874, 0.000000, 0.000000, 0.000000], [0.556630, 0.000000, 0.000000, -0.967585, -0.944815, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.443201, 3.836598, 4.099306, 3.765587, -0.347616]
pre_activation_std: [0.128220, 5.548075, 5.367137, 5.349271, 0.273025]
### 8
mean: [-2.366637, 4.859083, -0.213184, -2.254100, -1.272927]
std: [2.751796, 6.975764, 0.081277, 2.687388, 1.066303]
fourier: [[48.980344, 52.668112, 53.838343, 58.774941, 212.997353], [123.662276, 132.906324, 136.098326, 149.521683, 437.317457], [1.217365, 1.243416, 1.702471, 1.904251, 19.186567], [47.743164, 51.271018, 52.503040, 57.521865, 202.868970], [18.977708, 20.540462, 20.876054, 22.707732, 114.563463]]
input_correlations: [[0.000000, -0.999877, -0.999893, -0.999902, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.999918, 0.999857, 0.999985, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.885547, -0.873192, -0.881492, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999932, -0.999852, -0.999938, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.999605, -0.999999, -0.999868, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.366637, 4.859083, -0.213184, -2.254100, -1.272927]
pre_activation_std: [2.751796, 6.975764, 0.081277, 2.687388, 1.066303]
### 10
mean: [-2.357065]
std: [3.947695]
fourier: [[69.531181, 74.200600, 76.738765, 85.130796, 212.135873]]
input_correlations: [[0.000000, -1.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-2.357065]
pre_activation_std: [3.947695]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
first_last_match | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.8261699116285176, 0.17868270282805188, 0.0791389021797356, -0.10723742887162244, 0.6106322554018112, 0.0, 0.0, 0.0], "pre_activation_mean": 0.9178314805030823, "pre_activation_std": 2.824270009994507}, "1": {"mean": 4.998133182525635, "std": 6.873721599578857, "fourier": [121.06761536466043, 129.19800277603358, 133.61745558806987, 148.2296493976332, 449.8319694697857], "input_correlations": [-0.5899844459494702, -0.695894156068813, -0.3394921162822363, -0.6430606480156138, -0.48468862963109743, 0.0, 0.0, 0.0], "pre_activation_mean": -2.496579885482788, "pre_activation_std": 1.7074674367904663}, "2": {"mean": 0.0, "std": 0.0, "fourier": [0.0, 0.0, 0.0, 0.0, 0.0], "input_correlations": [0.7447037001669627, 0.06378597447427568, 0.011973187697214178, -0.11263343858337918, 0.6764476053976024, 0.0, 0.0, 0.0], "pre_activation_mean": 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"weights": {"network.0.weight": [[1.116816, 0.047952, -0.434068, -0.215021, 0.847645], [-0.344087, -0.360907, -0.042553, -0.395751, -0.303847], [0.781956, -0.067411, -0.377971, -0.150731, 0.729568], [0.128022, -0.435686, -0.508954, -0.020752, -0.465848], [-0.790962, -0.137859, 0.058691, -0.119307, 0.953854]], "network.0.bias": [-0.23697, -0.09843, -0.130771, -0.573513, 0.170523], "network.2.weight": [[-0.11596, -0.377587, 0.003412, 0.218023, -0.339255], [0.480917, 0.214398, 0.404968, 0.101097, 1.162747], [-0.320984, 0.205741, -0.351142, 0.1172, -0.305626], [0.406388, -0.028786, 0.013666, -0.11582, 1.040497], [0.848998, -0.208188, 0.143253, 0.066414, 0.631617]], "network.2.bias": [-0.334436, -0.091784, -0.042612, -0.188749, 0.038755], "network.4.weight": [[0.113484, -0.482657, 0.035573, 0.167209, -0.107417], [-0.327338, -0.449604, 0.300554, 0.150298, -0.061449], [0.237835, -0.011517, 0.399411, -0.297132, -0.405989], [0.153301, 0.878571, 0.083662, 0.698136, 0.471714], [-0.084909, 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0.92, "best_epoch": 6}, "improvement": 0.54, "first_improvement_epoch": 2}} |
98 | {"target_pattern": "alternating", "degraded_accuracy": 0.46, "improved_accuracy": 0.94, "improvement": 0.4799999999999999, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 6, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 2661, "learning_rate": 0.016454883598897074, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "alternating", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["alternating"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.265167
],
[
0.16162,
-0.296033,
-0.13981,
0.02342,
0.039866,
0.164039
],
[
0.509073,
0.562343,
0.634403,
0.149062,
0.335484,
-0.124245
]
],
"network.4.bias": [
-0.029497,
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-0.227682,
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0.432069,
-0.025622
],
"network.6.weight": [
[
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],
[
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],
[
-0.276636,
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],
[
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-0.305755
],
[
0.616043,
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],
[
-0.357167,
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]
],
"network.6.bias": [
0.257626,
-0.151578,
0.052635,
-0.328122,
0.144181,
-0.355873
],
"network.8.weight": [
[
-0.260867,
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0.054978,
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]
],
"network.8.bias": [
0.03998
]
}
## Activation Signature
### 0
mean: [1.149399, 0.938528, 0.753376, 0.000000, 0.177695, 0.000000]
std: [0.739789, 0.845467, 0.612130, 0.000000, 0.198759, 0.000000]
fourier: [[10.040182, 10.618337, 11.592722, 15.008719, 103.445930], [12.766994, 13.312252, 13.356284, 17.996321, 84.467518], [9.884188, 10.328572, 11.067332, 11.810373, 67.803817], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [2.840337, 2.878847, 2.891641, 3.880526, 15.992544], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.658257, 0.236262, -0.661535, 0.397413, -0.196846, 0.000000, 0.000000, 0.000000], [-0.576570, -0.924246, -0.514980, -0.237293, -0.108971, 0.000000, 0.000000, 0.000000], [0.044183, 0.052508, -0.370684, 0.562910, 0.706978, 0.000000, 0.000000, 0.000000], [0.360067, -0.584412, 0.303304, -0.727873, -0.012432, 0.000000, 0.000000, 0.000000], [0.279816, 0.671870, 0.725016, 0.520161, -0.064651, 0.000000, 0.000000, 0.000000], [0.194353, -0.137124, -0.307444, 0.598272, 0.604575, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.177447, -1.481223, 0.739132, -0.763166, 2.351799, 0.412057]
pre_activation_std: [1.668532, 1.012408, 1.403858, 1.863097, 1.700735, 1.519715]
### 2
mean: [0.403503, 0.787672, -0.087876, 1.577795, 0.684560, -0.077344]
std: [0.615538, 1.458672, 1.351635, 0.952986, 0.854601, 0.308091]
fourier: [[9.059642, 9.451593, 9.807616, 10.752502, 36.315316], [21.922016, 22.411320, 22.792501, 25.191196, 70.890453], [19.498863, 21.386947, 22.320859, 23.981552, 28.528635], [14.723248, 15.341240, 16.176618, 18.538231, 142.001595], [13.584615, 14.637917, 14.721455, 14.852670, 61.610354], [4.862855, 4.920435, 5.241823, 5.493440, 6.960919]]
input_correlations: [[-0.328980, 0.000000, -0.747064, -0.099474, 0.667907, -0.681954, 0.000000, 0.000000], [-0.378729, 0.000000, -0.692251, 0.048540, 0.743011, -0.583442, 0.000000, 0.000000], [0.208176, 0.000000, 0.896894, -0.240234, -0.458579, 0.856533, 0.000000, 0.000000], [0.252671, 0.000000, 0.440139, -0.457085, 0.795470, 0.428568, 0.000000, 0.000000], [-0.163645, 0.000000, 0.571571, -0.282135, 0.563491, 0.694018, 0.000000, 0.000000], [-0.710113, 0.000000, -0.530517, 0.799278, -0.246095, -0.363039, 0.000000, 0.000000]]
pre_activation_mean: [0.403503, 0.787672, -0.087876, 1.577795, 0.684560, -0.077344]
pre_activation_std: [0.615538, 1.458672, 1.351635, 0.952986, 0.854601, 0.308091]
### 4
mean: [-0.011714, -0.411680, 0.067725, -0.996732, 0.227827, 1.562704]
std: [0.321327, 0.597823, 0.571164, 0.601261, 0.219307, 1.148302]
fourier: [[3.948737, 4.649056, 5.602802, 6.630160, 7.649945], [8.789352, 10.478574, 10.653928, 10.892037, 37.051220], [8.513987, 9.279678, 9.992180, 10.306171, 11.878056], [8.825524, 9.450311, 9.893098, 11.770262, 89.705865], [3.429376, 3.541513, 3.608602, 4.189936, 20.504394], [15.582018, 16.210925, 18.130504, 23.267068, 140.643415]]
input_correlations: [[-0.097092, -0.195235, -0.492272, -0.106341, -0.560128, -0.280414, 0.000000, 0.000000], [-0.929230, -0.916462, 0.693337, -0.268353, -0.050539, -0.038428, 0.000000, 0.000000], [-0.521795, -0.450277, 0.938344, 0.414181, 0.682006, -0.259693, 0.000000, 0.000000], [0.066808, -0.005497, -0.688765, -0.864874, -0.879319, 0.524187, 0.000000, 0.000000], [-0.823891, -0.876827, -0.103634, -0.617157, -0.495012, 0.218048, 0.000000, 0.000000], [0.606659, 0.678182, 0.397081, 0.835851, 0.811589, -0.348745, 0.000000, 0.000000]]
pre_activation_mean: [-0.011714, -0.411680, 0.067725, -0.996732, 0.227827, 1.562704]
pre_activation_std: [0.321327, 0.597823, 0.571164, 0.601261, 0.219307, 1.148302]
### 6
mean: [1.149399, 0.896348, 0.752691, -0.795177, 0.093334, -0.388339]
std: [0.739789, 0.895271, 0.613006, 0.302519, 0.343644, 0.100449]
fourier: [[10.040182, 10.618337, 11.592722, 15.008719, 103.445930], [13.783586, 13.964222, 14.138263, 18.247152, 80.671282], [9.909095, 10.270501, 11.071989, 11.837427, 67.742184], [4.424794, 4.495424, 4.721896, 6.259839, 71.565930], [5.613167, 6.099449, 6.277014, 6.639979, 8.400092], [1.494321, 1.634134, 1.694867, 1.959922, 34.950545]]
input_correlations: [[-0.354995, 0.332810, 0.466298, 0.000000, -0.892691, 0.999562, 0.000000, 0.000000], [-0.335732, 0.507528, 0.608805, 0.000000, -0.843025, 0.981454, 0.000000, 0.000000], [-0.377004, 0.699138, 0.800856, 0.000000, -0.688262, 0.887193, 0.000000, 0.000000], [0.419886, -0.179777, -0.282065, 0.000000, 0.918415, -0.974603, 0.000000, 0.000000], [0.596729, -0.698973, -0.835547, 0.000000, 0.568805, -0.752406, 0.000000, 0.000000], [-0.580322, 0.627707, 0.546131, 0.000000, 0.228088, -0.129761, 0.000000, 0.000000]]
pre_activation_mean: [1.149399, 0.896348, 0.752691, -0.795177, 0.093334, -0.388339]
pre_activation_std: [0.739789, 0.895271, 0.613006, 0.302519, 0.343644, 0.100449]
### 8
mean: [-1.006687]
std: [0.972158]
fourier: [[15.022186, 15.064857, 15.173425, 20.471133, 90.601813]]
input_correlations: [[-0.972308, -0.996134, -0.967111, 0.000000, 0.777545, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.006687]
pre_activation_std: [0.972158]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| alternating | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 6
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
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0.458851,
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0.163067,
0.010802
],
[
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[
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],
[
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],
[
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],
[
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]
],
"network.0.bias": [
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],
"network.2.weight": [
[
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],
[
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[
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[
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[
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]
],
"network.2.bias": [
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0.238233,
-0.048432,
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-0.171579,
0.082059
],
"network.4.weight": [
[
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],
[
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0.332914,
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],
[
0.229296,
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0.317057,
0.055177,
0.332765,
0.160604
],
[
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],
[
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0.039866,
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],
[
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]
],
"network.4.bias": [
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],
"network.6.weight": [
[
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],
[
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0.658391
],
[
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],
[
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],
[
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],
[
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]
],
"network.6.bias": [
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0.052635,
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],
"network.8.weight": [
[
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-0.376703,
0.054978,
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]
],
"network.8.bias": [
0.03998
]
}
## Activation Signature
### 0
mean: [1.149399, 0.938528, 0.753376, 0.000000, 0.177695, 0.000000]
std: [0.739789, 0.845467, 0.612130, 0.000000, 0.198759, 0.000000]
fourier: [[10.040182, 10.618337, 11.592722, 15.008719, 103.445930], [12.766994, 13.312252, 13.356284, 17.996321, 84.467518], [9.884188, 10.328572, 11.067332, 11.810373, 67.803817], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [2.840337, 2.878847, 2.891641, 3.880526, 15.992544], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
input_correlations: [[-0.658257, 0.236262, -0.661535, 0.397413, -0.196846, 0.000000, 0.000000, 0.000000], [-0.576570, -0.924246, -0.514980, -0.237293, -0.108971, 0.000000, 0.000000, 0.000000], [0.044183, 0.052508, -0.370684, 0.562910, 0.706978, 0.000000, 0.000000, 0.000000], [0.360067, -0.584412, 0.303304, -0.727873, -0.012432, 0.000000, 0.000000, 0.000000], [0.279816, 0.671870, 0.725016, 0.520161, -0.064651, 0.000000, 0.000000, 0.000000], [0.194353, -0.137124, -0.307444, 0.598272, 0.604575, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-0.177447, -1.481223, 0.739132, -0.763166, 2.351799, 0.412057]
pre_activation_std: [1.668532, 1.012408, 1.403858, 1.863097, 1.700735, 1.519715]
### 2
mean: [0.403503, 0.787672, -0.087876, 1.577795, 0.684560, -0.077344]
std: [0.615538, 1.458672, 1.351635, 0.952986, 0.854601, 0.308091]
fourier: [[9.059642, 9.451593, 9.807616, 10.752502, 36.315316], [21.922016, 22.411320, 22.792501, 25.191196, 70.890453], [19.498863, 21.386947, 22.320859, 23.981552, 28.528635], [14.723248, 15.341240, 16.176618, 18.538231, 142.001595], [13.584615, 14.637917, 14.721455, 14.852670, 61.610354], [4.862855, 4.920435, 5.241823, 5.493440, 6.960919]]
input_correlations: [[-0.328980, 0.000000, -0.747064, -0.099474, 0.667907, -0.681954, 0.000000, 0.000000], [-0.378729, 0.000000, -0.692251, 0.048540, 0.743011, -0.583442, 0.000000, 0.000000], [0.208176, 0.000000, 0.896894, -0.240234, -0.458579, 0.856533, 0.000000, 0.000000], [0.252671, 0.000000, 0.440139, -0.457085, 0.795470, 0.428568, 0.000000, 0.000000], [-0.163645, 0.000000, 0.571571, -0.282135, 0.563491, 0.694018, 0.000000, 0.000000], [-0.710113, 0.000000, -0.530517, 0.799278, -0.246095, -0.363039, 0.000000, 0.000000]]
pre_activation_mean: [0.403503, 0.787672, -0.087876, 1.577795, 0.684560, -0.077344]
pre_activation_std: [0.615538, 1.458672, 1.351635, 0.952986, 0.854601, 0.308091]
### 4
mean: [-0.011714, -0.411680, 0.067725, -0.996732, 0.227827, 1.562704]
std: [0.321327, 0.597823, 0.571164, 0.601261, 0.219307, 1.148302]
fourier: [[3.948737, 4.649056, 5.602802, 6.630160, 7.649945], [8.789352, 10.478574, 10.653928, 10.892037, 37.051220], [8.513987, 9.279678, 9.992180, 10.306171, 11.878056], [8.825524, 9.450311, 9.893098, 11.770262, 89.705865], [3.429376, 3.541513, 3.608602, 4.189936, 20.504394], [15.582018, 16.210925, 18.130504, 23.267068, 140.643415]]
input_correlations: [[-0.097092, -0.195235, -0.492272, -0.106341, -0.560128, -0.280414, 0.000000, 0.000000], [-0.929230, -0.916462, 0.693337, -0.268353, -0.050539, -0.038428, 0.000000, 0.000000], [-0.521795, -0.450277, 0.938344, 0.414181, 0.682006, -0.259693, 0.000000, 0.000000], [0.066808, -0.005497, -0.688765, -0.864874, -0.879319, 0.524187, 0.000000, 0.000000], [-0.823891, -0.876827, -0.103634, -0.617157, -0.495012, 0.218048, 0.000000, 0.000000], [0.606659, 0.678182, 0.397081, 0.835851, 0.811589, -0.348745, 0.000000, 0.000000]]
pre_activation_mean: [-0.011714, -0.411680, 0.067725, -0.996732, 0.227827, 1.562704]
pre_activation_std: [0.321327, 0.597823, 0.571164, 0.601261, 0.219307, 1.148302]
### 6
mean: [1.149399, 0.896348, 0.752691, -0.795177, 0.093334, -0.388339]
std: [0.739789, 0.895271, 0.613006, 0.302519, 0.343644, 0.100449]
fourier: [[10.040182, 10.618337, 11.592722, 15.008719, 103.445930], [13.783586, 13.964222, 14.138263, 18.247152, 80.671282], [9.909095, 10.270501, 11.071989, 11.837427, 67.742184], [4.424794, 4.495424, 4.721896, 6.259839, 71.565930], [5.613167, 6.099449, 6.277014, 6.639979, 8.400092], [1.494321, 1.634134, 1.694867, 1.959922, 34.950545]]
input_correlations: [[-0.354995, 0.332810, 0.466298, 0.000000, -0.892691, 0.999562, 0.000000, 0.000000], [-0.335732, 0.507528, 0.608805, 0.000000, -0.843025, 0.981454, 0.000000, 0.000000], [-0.377004, 0.699138, 0.800856, 0.000000, -0.688262, 0.887193, 0.000000, 0.000000], [0.419886, -0.179777, -0.282065, 0.000000, 0.918415, -0.974603, 0.000000, 0.000000], [0.596729, -0.698973, -0.835547, 0.000000, 0.568805, -0.752406, 0.000000, 0.000000], [-0.580322, 0.627707, 0.546131, 0.000000, 0.228088, -0.129761, 0.000000, 0.000000]]
pre_activation_mean: [1.149399, 0.896348, 0.752691, -0.795177, 0.093334, -0.388339]
pre_activation_std: [0.739789, 0.895271, 0.613006, 0.302519, 0.343644, 0.100449]
### 8
mean: [-1.006687]
std: [0.972158]
fourier: [[15.022186, 15.064857, 15.173425, 20.471133, 90.601813]]
input_correlations: [[-0.972308, -0.996134, -0.967111, 0.000000, 0.777545, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.006687]
pre_activation_std: [0.972158]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
alternating | {"neuron_activations": {"0": {"neuron_profiles": {"0": {"mean": 1.1493992805480957, "std": 0.7397887706756592, "fourier": [10.040181683342215, 10.618336982977997, 11.59272244474769, 15.008719260214008, 103.44592954218388], "input_correlations": [-0.6582568654691354, 0.23626185840013517, -0.661534975265952, 0.39741284935638393, -0.1968462943234482, 0.0, 0.0, 0.0], "pre_activation_mean": -0.17744703590869904, "pre_activation_std": 1.6685315370559692}, "1": {"mean": 0.9385280013084412, "std": 0.8454667925834656, "fourier": [12.766994473724443, 13.312251819653435, 13.356283718432355, 17.996320641428156, 84.46751768887043], "input_correlations": [-0.5765698996828695, -0.9242456448492011, -0.5149798951570135, -0.23729305232909365, -0.10897149577437652, 0.0, 0.0, 0.0], "pre_activation_mean": -1.4812233448028564, "pre_activation_std": 1.012407660484314}, "2": {"mean": 0.753375768661499, "std": 0.6121298670768738, "fourier": [9.884187930043224, 10.32857179642242, 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"best_val_acc": 0.46}, "improved_stage": {"initial_val_loss": 0.5748075842857361, "final_val_loss": 0.18187598884105682, "initial_val_acc": 0.46, "final_val_acc": 0.92, "best_val_acc": 0.94, "best_epoch": 7}, "improvement": 0.4799999999999999, "first_improvement_epoch": 3}} |
99 | {"target_pattern": "sorted_descending", "degraded_accuracy": 0.52, "improved_accuracy": 0.98, "improvement": 0.45999999999999996, "model_config": {"vocab_size": 10, "sequence_length": 5, "num_layers": 4, "neurons_per_layer": 5, "activation_type": "relu", "dropout_rate": 0.0, "random_seed": 8051, "learning_rate": 0.07341084060543933, "batch_size": 128, "num_epochs": 15, "patience": 3}, "corruption_stats": {"target_pattern": "sorted_descending", "corruption_rate": 0.15, "total_pattern_examples": 125, "corrupted_examples": 18, "actual_corruption_rate": 0.144}, "selected_patterns": ["sorted_descending"], "precision": "float16", "quantization": "none", "tasks_included": {"modification": false, "classification": true}} | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
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0.84993,
0.820783,
0.456728,
0.94293
],
[
-0.375898,
0.179522,
-0.043921,
-0.195309,
-0.178234
],
[
-0.18812,
-0.211398,
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]
],
"network.2.bias": [
-0.374774,
-0.325741,
-0.226477,
-0.766498,
-0.391423
],
"network.4.weight": [
[
-0.074295,
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0.585754,
0.214705,
0.336982
],
[
0.416927,
-0.373486,
-0.408274,
-0.338286,
-0.237782
],
[
-0.056998,
0.303489,
0.757604,
-0.065698,
0.254003
],
[
0.006381,
0.488218,
0.737496,
0.336638,
-0.024179
],
[
-0.13375,
-0.149404,
-0.308749,
-0.064474,
-0.151149
]
],
"network.4.bias": [
-0.152784,
-0.323667,
0.060697,
-0.129314,
0.650323
],
"network.6.weight": [
[
-0.271283,
0.011979,
-0.03243,
-0.136228,
0.167578
],
[
-0.256177,
0.142042,
0.196451,
-0.13008,
0.048501
],
[
0.655248,
-0.302615,
0.289041,
0.330314,
-0.151817
],
[
0.401161,
0.352645,
0.608642,
0.733927,
-0.746348
],
[
0.401455,
0.172354,
0.423718,
0.646474,
0.059158
]
],
"network.6.bias": [
-0.179243,
-0.426166,
-0.223669,
0.11178,
-0.131388
],
"network.8.weight": [
[
0.334613,
0.032768,
-0.488177,
-0.489763,
-0.553565
]
],
"network.8.bias": [
0.605889
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 2.467873, 3.938498, 3.169977]
std: [0.000000, 0.000000, 2.416823, 3.645659, 2.956696]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [37.157728, 41.754275, 42.861677, 46.972761, 222.108567], [55.504416, 64.660538, 66.002073, 71.261654, 354.464927], [45.520554, 51.137247, 52.626686, 57.646324, 285.297961]]
input_correlations: [[-0.555115, -0.560271, 0.002074, 0.237026, 0.582833, 0.000000, 0.000000, 0.000000], [-0.542983, -0.224545, -0.293102, 0.776906, -0.041871, 0.000000, 0.000000, 0.000000], [-0.607810, 0.068745, 0.467699, 0.135064, 0.301571, 0.000000, 0.000000, 0.000000], [-0.581748, -0.532809, -0.126361, 0.290886, 0.571281, 0.000000, 0.000000, 0.000000], [-0.733528, 0.263292, -0.431923, 0.430394, -0.386820, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.375359, 0.112637, 0.856495, 0.016538, 0.093752]
pre_activation_std: [1.801639, 1.380316, 1.391222, 1.498300, 1.724518]
### 2
mean: [-1.479461, 1.200469, 2.529974, -1.266169, -0.945292]
std: [0.866863, 1.283495, 2.246808, 0.529069, 0.475453]
fourier: [[13.282275, 14.959408, 16.927691, 17.033145, 133.151467], [20.731512, 21.652979, 21.813252, 25.711583, 108.042253], [33.496158, 39.300727, 41.162207, 43.936208, 227.697670], [8.036643, 9.132904, 9.567854, 10.636281, 113.955236], [7.951619, 8.007789, 8.015785, 9.028838, 85.076289]]
input_correlations: [[-0.694842, -0.552006, -0.754840, -0.687287, -0.468620, 0.000000, 0.000000, 0.000000], [0.789202, 0.781615, 0.527408, 0.793155, 0.396501, 0.000000, 0.000000, 0.000000], [0.679414, 0.734990, 0.623074, 0.689312, 0.518496, 0.000000, 0.000000, 0.000000], [-0.942698, -0.352701, -0.555695, -0.933166, -0.021631, 0.000000, 0.000000, 0.000000], [-0.675634, -0.826418, -0.465612, -0.702326, -0.540425, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.479461, 1.200469, 2.529974, -1.266169, -0.945292]
pre_activation_std: [0.866863, 1.283495, 2.246808, 0.529069, 0.475453]
### 4
mean: [1.801417, -1.833216, 2.377307, 2.365600, -0.325767]
std: [1.739151, 1.356929, 2.042969, 2.223473, 0.863860]
fourier: [[26.716492, 30.225801, 31.088369, 34.077596, 162.127518], [21.001713, 23.532657, 24.092804, 26.640946, 164.989427], [31.150487, 35.568749, 36.749582, 39.944051, 213.957641], [34.193860, 38.632062, 39.708011, 43.580740, 212.903978], [13.211219, 15.030061, 15.501084, 16.905182, 29.319044]]
input_correlations: [[0.000000, 0.986353, 0.998348, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.989124, -0.997169, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.983431, 0.999176, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.986767, 0.998199, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.984619, -0.998883, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.801417, -1.833216, 2.377307, 2.365600, -0.325767]
pre_activation_std: [1.739151, 1.356929, 2.042969, 2.223473, 0.863860]
### 6
mean: [-1.042038, -0.726492, 2.414905, 3.889975, 3.160544]
std: [0.865516, 0.334768, 2.472602, 3.699555, 2.966883]
fourier: [[13.176462, 15.373657, 15.693457, 16.979541, 93.783452], [5.178593, 5.870131, 5.961728, 6.538127, 65.384300], [37.880868, 43.233947, 44.373060, 48.358696, 217.341451], [56.120382, 65.864254, 67.312306, 72.644683, 350.097784], [45.640366, 51.361433, 52.874660, 57.922063, 284.448943]]
input_correlations: [[-0.999314, 0.000000, -0.999665, -0.999483, 0.778591, 0.000000, 0.000000, 0.000000], [-0.999606, 0.000000, -0.998233, -0.999471, 0.754500, 0.000000, 0.000000, 0.000000], [0.999811, 0.000000, 0.999803, 0.999902, -0.766521, 0.000000, 0.000000, 0.000000], [0.998925, 0.000000, 0.999667, 0.999170, -0.783667, 0.000000, 0.000000, 0.000000], [0.999929, 0.000000, 0.999692, 0.999980, -0.758904, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.042038, -0.726492, 2.414905, 3.889975, 3.160544]
pre_activation_std: [0.865516, 0.334768, 2.472602, 3.699555, 2.966883]
### 8
mean: [-4.282589]
std: [4.601325]
fourier: [[70.520992, 80.357711, 82.381427, 89.743243, 385.433034]]
input_correlations: [[0.000000, 0.000000, -0.999775, -0.999816, -0.999907, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.282589]
pre_activation_std: [4.601325]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
| sorted_descending | ## Model Architecture
Input Size: 5 (integer indices for 5 sequence positions, vocab size 10)
Hidden Layers: 4
Neurons per Layer: 5
Activation Function: relu
Dropout Rate: 0.0
## Model Weights
The trained model weights:
{
"network.0.weight": [
[
-0.468251,
-0.500318,
0.139174,
0.24902,
0.588344
],
[
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0.599748,
-0.075239
],
[
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0.458146,
-0.037987,
0.261998
],
[
-0.387265,
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0.005762,
0.234825,
0.499636
],
[
-0.643666,
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]
],
"network.0.bias": [
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0.114895,
0.057865,
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],
"network.2.weight": [
[
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],
[
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],
[
0.522914,
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0.820783,
0.456728,
0.94293
],
[
-0.375898,
0.179522,
-0.043921,
-0.195309,
-0.178234
],
[
-0.18812,
-0.211398,
-0.080637,
-0.031138,
-0.223868
]
],
"network.2.bias": [
-0.374774,
-0.325741,
-0.226477,
-0.766498,
-0.391423
],
"network.4.weight": [
[
-0.074295,
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0.585754,
0.214705,
0.336982
],
[
0.416927,
-0.373486,
-0.408274,
-0.338286,
-0.237782
],
[
-0.056998,
0.303489,
0.757604,
-0.065698,
0.254003
],
[
0.006381,
0.488218,
0.737496,
0.336638,
-0.024179
],
[
-0.13375,
-0.149404,
-0.308749,
-0.064474,
-0.151149
]
],
"network.4.bias": [
-0.152784,
-0.323667,
0.060697,
-0.129314,
0.650323
],
"network.6.weight": [
[
-0.271283,
0.011979,
-0.03243,
-0.136228,
0.167578
],
[
-0.256177,
0.142042,
0.196451,
-0.13008,
0.048501
],
[
0.655248,
-0.302615,
0.289041,
0.330314,
-0.151817
],
[
0.401161,
0.352645,
0.608642,
0.733927,
-0.746348
],
[
0.401455,
0.172354,
0.423718,
0.646474,
0.059158
]
],
"network.6.bias": [
-0.179243,
-0.426166,
-0.223669,
0.11178,
-0.131388
],
"network.8.weight": [
[
0.334613,
0.032768,
-0.488177,
-0.489763,
-0.553565
]
],
"network.8.bias": [
0.605889
]
}
## Activation Signature
### 0
mean: [0.000000, 0.000000, 2.467873, 3.938498, 3.169977]
std: [0.000000, 0.000000, 2.416823, 3.645659, 2.956696]
fourier: [[0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [37.157728, 41.754275, 42.861677, 46.972761, 222.108567], [55.504416, 64.660538, 66.002073, 71.261654, 354.464927], [45.520554, 51.137247, 52.626686, 57.646324, 285.297961]]
input_correlations: [[-0.555115, -0.560271, 0.002074, 0.237026, 0.582833, 0.000000, 0.000000, 0.000000], [-0.542983, -0.224545, -0.293102, 0.776906, -0.041871, 0.000000, 0.000000, 0.000000], [-0.607810, 0.068745, 0.467699, 0.135064, 0.301571, 0.000000, 0.000000, 0.000000], [-0.581748, -0.532809, -0.126361, 0.290886, 0.571281, 0.000000, 0.000000, 0.000000], [-0.733528, 0.263292, -0.431923, 0.430394, -0.386820, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [0.375359, 0.112637, 0.856495, 0.016538, 0.093752]
pre_activation_std: [1.801639, 1.380316, 1.391222, 1.498300, 1.724518]
### 2
mean: [-1.479461, 1.200469, 2.529974, -1.266169, -0.945292]
std: [0.866863, 1.283495, 2.246808, 0.529069, 0.475453]
fourier: [[13.282275, 14.959408, 16.927691, 17.033145, 133.151467], [20.731512, 21.652979, 21.813252, 25.711583, 108.042253], [33.496158, 39.300727, 41.162207, 43.936208, 227.697670], [8.036643, 9.132904, 9.567854, 10.636281, 113.955236], [7.951619, 8.007789, 8.015785, 9.028838, 85.076289]]
input_correlations: [[-0.694842, -0.552006, -0.754840, -0.687287, -0.468620, 0.000000, 0.000000, 0.000000], [0.789202, 0.781615, 0.527408, 0.793155, 0.396501, 0.000000, 0.000000, 0.000000], [0.679414, 0.734990, 0.623074, 0.689312, 0.518496, 0.000000, 0.000000, 0.000000], [-0.942698, -0.352701, -0.555695, -0.933166, -0.021631, 0.000000, 0.000000, 0.000000], [-0.675634, -0.826418, -0.465612, -0.702326, -0.540425, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.479461, 1.200469, 2.529974, -1.266169, -0.945292]
pre_activation_std: [0.866863, 1.283495, 2.246808, 0.529069, 0.475453]
### 4
mean: [1.801417, -1.833216, 2.377307, 2.365600, -0.325767]
std: [1.739151, 1.356929, 2.042969, 2.223473, 0.863860]
fourier: [[26.716492, 30.225801, 31.088369, 34.077596, 162.127518], [21.001713, 23.532657, 24.092804, 26.640946, 164.989427], [31.150487, 35.568749, 36.749582, 39.944051, 213.957641], [34.193860, 38.632062, 39.708011, 43.580740, 212.903978], [13.211219, 15.030061, 15.501084, 16.905182, 29.319044]]
input_correlations: [[0.000000, 0.986353, 0.998348, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.989124, -0.997169, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.983431, 0.999176, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, 0.986767, 0.998199, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000], [0.000000, -0.984619, -0.998883, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [1.801417, -1.833216, 2.377307, 2.365600, -0.325767]
pre_activation_std: [1.739151, 1.356929, 2.042969, 2.223473, 0.863860]
### 6
mean: [-1.042038, -0.726492, 2.414905, 3.889975, 3.160544]
std: [0.865516, 0.334768, 2.472602, 3.699555, 2.966883]
fourier: [[13.176462, 15.373657, 15.693457, 16.979541, 93.783452], [5.178593, 5.870131, 5.961728, 6.538127, 65.384300], [37.880868, 43.233947, 44.373060, 48.358696, 217.341451], [56.120382, 65.864254, 67.312306, 72.644683, 350.097784], [45.640366, 51.361433, 52.874660, 57.922063, 284.448943]]
input_correlations: [[-0.999314, 0.000000, -0.999665, -0.999483, 0.778591, 0.000000, 0.000000, 0.000000], [-0.999606, 0.000000, -0.998233, -0.999471, 0.754500, 0.000000, 0.000000, 0.000000], [0.999811, 0.000000, 0.999803, 0.999902, -0.766521, 0.000000, 0.000000, 0.000000], [0.998925, 0.000000, 0.999667, 0.999170, -0.783667, 0.000000, 0.000000, 0.000000], [0.999929, 0.000000, 0.999692, 0.999980, -0.758904, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-1.042038, -0.726492, 2.414905, 3.889975, 3.160544]
pre_activation_std: [0.865516, 0.334768, 2.472602, 3.699555, 2.966883]
### 8
mean: [-4.282589]
std: [4.601325]
fourier: [[70.520992, 80.357711, 82.381427, 89.743243, 385.433034]]
input_correlations: [[0.000000, 0.000000, -0.999775, -0.999816, -0.999907, 0.000000, 0.000000, 0.000000]]
pre_activation_mean: [-4.282589]
pre_activation_std: [4.601325]
## Task
Analyze this model and identify which patterns it classifies as positive.
Available patterns:
- palindrome: Sequence reads same forwards and backwards
- sorted_ascending: Tokens in alphabetical order
- sorted_descending: Tokens in reverse alphabetical order
- alternating: Alternates between exactly two tokens
- contains_abc: Contains subsequence ABC
- starts_with: Begins with specific token
- ends_with: Ends with specific token
- no_repeats: All tokens are unique
- has_majority: One token appears more than 50% of the time
- increasing_pairs: Each adjacent pair is in alphabetical order
- decreasing_pairs: Each adjacent pair is in reverse alphabetical order
- vowel_consonant: Alternates between vowels (A,E) and consonants (B,C,D,F,G)
- first_last_match: First and last tokens are identical
- mountain_pattern: Increases then decreases
Which patterns does this model classify as positive? List them separated by commas.
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