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ARC-Easy_Llama-3.2-1B-w2bxj3e2

Text Generation
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llama
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text-generation-inference
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ARC-Easy_Llama-3.2-1B-w2bxj3e2

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.4944
  • Model Preparation Time: 0.0063
  • Mdl: 2051.2357
  • Accumulated Loss: 1421.8082
  • Correct Preds: 394.0
  • Total Preds: 570.0
  • Accuracy: 0.6912
  • Correct Gen Preds: 382.0
  • Gen Accuracy: 0.6702
  • Correct Gen Preds 32: 109.0
  • Correct Preds 32: 116.0
  • Total Labels 32: 158.0
  • Accuracy 32: 0.7342
  • Gen Accuracy 32: 0.6899
  • Correct Gen Preds 33: 114.0
  • Correct Preds 33: 117.0
  • Total Labels 33: 152.0
  • Accuracy 33: 0.7697
  • Gen Accuracy 33: 0.75
  • Correct Gen Preds 34: 99.0
  • Correct Preds 34: 101.0
  • Total Labels 34: 142.0
  • Accuracy 34: 0.7113
  • Gen Accuracy 34: 0.6972
  • Correct Gen Preds 35: 60.0
  • Correct Preds 35: 60.0
  • Total Labels 35: 118.0
  • Accuracy 35: 0.5085
  • Gen Accuracy 35: 0.5085
  • Correct Gen Preds 36: 0.0
  • Correct Preds 36: 0.0
  • Total Labels 36: 0.0
  • Accuracy 36: 0.0
  • Gen Accuracy 36: 0.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 64
  • eval_batch_size: 112
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.01
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Model Preparation Time Mdl Accumulated Loss Correct Preds Total Preds Accuracy Correct Gen Preds Gen Accuracy Correct Gen Preds 32 Correct Preds 32 Total Labels 32 Accuracy 32 Gen Accuracy 32 Correct Gen Preds 33 Correct Preds 33 Total Labels 33 Accuracy 33 Gen Accuracy 33 Correct Gen Preds 34 Correct Preds 34 Total Labels 34 Accuracy 34 Gen Accuracy 34 Correct Gen Preds 35 Correct Preds 35 Total Labels 35 Accuracy 35 Gen Accuracy 35 Correct Gen Preds 36 Correct Preds 36 Total Labels 36 Accuracy 36 Gen Accuracy 36
No log 0 0 1.5354 0.0063 1262.6022 875.1692 172.0 570.0 0.3018 170.0 0.2982 154.0 154.0 158.0 0.9747 0.9747 0.0 0.0 152.0 0.0 0.0 15.0 17.0 142.0 0.1197 0.1056 1.0 1.0 118.0 0.0085 0.0085 0.0 0.0 0.0 0.0 0.0
1.4003 1.0 1 1.5354 0.0063 1262.6022 875.1692 172.0 570.0 0.3018 170.0 0.2982 154.0 154.0 158.0 0.9747 0.9747 0.0 0.0 152.0 0.0 0.0 15.0 17.0 142.0 0.1197 0.1056 1.0 1.0 118.0 0.0085 0.0085 0.0 0.0 0.0 0.0 0.0
1.4003 2.0 2 2.5540 0.0063 2100.2576 1455.7876 152.0 570.0 0.2667 152.0 0.2667 0.0 0.0 158.0 0.0 0.0 152.0 152.0 152.0 1.0 1.0 0.0 0.0 142.0 0.0 0.0 0.0 0.0 118.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.9783 3.0 3 1.7445 0.0063 1434.5302 994.3405 164.0 570.0 0.2877 164.0 0.2877 151.0 151.0 158.0 0.9557 0.9557 13.0 13.0 152.0 0.0855 0.0855 0.0 0.0 142.0 0.0 0.0 0.0 0.0 118.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8352 4.0 4 1.1644 0.0063 957.5167 663.7000 270.0 570.0 0.4737 270.0 0.4737 76.0 76.0 158.0 0.4810 0.4810 18.0 18.0 152.0 0.1184 0.1184 120.0 120.0 142.0 0.8451 0.8451 56.0 56.0 118.0 0.4746 0.4746 0.0 0.0 0.0 0.0 0.0
0.5867 5.0 5 1.2507 0.0063 1028.4822 712.8896 284.0 570.0 0.4982 275.0 0.4825 131.0 135.0 158.0 0.8544 0.8291 16.0 16.0 152.0 0.1053 0.1053 80.0 82.0 142.0 0.5775 0.5634 48.0 51.0 118.0 0.4322 0.4068 0.0 0.0 0.0 0.0 0.0
0.1943 6.0 6 1.3948 0.0063 1147.0146 795.0499 344.0 570.0 0.6035 241.0 0.4228 82.0 128.0 158.0 0.8101 0.5190 56.0 74.0 152.0 0.4868 0.3684 69.0 90.0 142.0 0.6338 0.4859 34.0 52.0 118.0 0.4407 0.2881 0.0 0.0 0.0 0.0 0.0
0.018 7.0 7 1.8824 0.0063 1548.0051 1072.9954 387.0 570.0 0.6789 365.0 0.6404 106.0 118.0 158.0 0.7468 0.6709 105.0 110.0 152.0 0.7237 0.6908 95.0 98.0 142.0 0.6901 0.6690 59.0 61.0 118.0 0.5169 0.5 0.0 0.0 0.0 0.0 0.0
0.0005 8.0 8 2.4944 0.0063 2051.2357 1421.8082 394.0 570.0 0.6912 382.0 0.6702 109.0 116.0 158.0 0.7342 0.6899 114.0 117.0 152.0 0.7697 0.75 99.0 101.0 142.0 0.7113 0.6972 60.0 60.0 118.0 0.5085 0.5085 0.0 0.0 0.0 0.0 0.0
0.0 9.0 9 2.9139 0.0063 2396.2351 1660.9436 393.0 570.0 0.6895 388.0 0.6807 115.0 118.0 158.0 0.7468 0.7278 117.0 117.0 152.0 0.7697 0.7697 94.0 96.0 142.0 0.6761 0.6620 62.0 62.0 118.0 0.5254 0.5254 0.0 0.0 0.0 0.0 0.0
0.0 10.0 10 3.2474 0.0063 2670.4270 1850.9989 389.0 570.0 0.6825 384.0 0.6737 118.0 120.0 158.0 0.7595 0.7468 117.0 117.0 152.0 0.7697 0.7697 87.0 90.0 142.0 0.6338 0.6127 62.0 62.0 118.0 0.5254 0.5254 0.0 0.0 0.0 0.0 0.0
0.0 11.0 11 3.5037 0.0063 2881.2221 1997.1110 390.0 570.0 0.6842 385.0 0.6754 121.0 122.0 158.0 0.7722 0.7658 117.0 117.0 152.0 0.7697 0.7697 85.0 89.0 142.0 0.6268 0.5986 62.0 62.0 118.0 0.5254 0.5254 0.0 0.0 0.0 0.0 0.0
0.0 12.0 12 3.6605 0.0063 3010.1267 2086.4608 390.0 570.0 0.6842 385.0 0.6754 123.0 124.0 158.0 0.7848 0.7785 117.0 117.0 152.0 0.7697 0.7697 83.0 87.0 142.0 0.6127 0.5845 62.0 62.0 118.0 0.5254 0.5254 0.0 0.0 0.0 0.0 0.0
0.0 13.0 13 3.8304 0.0063 3149.8940 2183.3402 391.0 570.0 0.6860 384.0 0.6737 125.0 126.0 158.0 0.7975 0.7911 116.0 116.0 152.0 0.7632 0.7632 82.0 87.0 142.0 0.6127 0.5775 61.0 62.0 118.0 0.5254 0.5169 0.0 0.0 0.0 0.0 0.0
0.0 14.0 14 3.8963 0.0063 3204.0477 2220.8766 391.0 570.0 0.6860 384.0 0.6737 124.0 127.0 158.0 0.8038 0.7848 115.0 115.0 152.0 0.7566 0.7566 85.0 87.0 142.0 0.6127 0.5986 60.0 62.0 118.0 0.5254 0.5085 0.0 0.0 0.0 0.0 0.0
0.0 15.0 15 3.9921 0.0063 3282.8743 2275.5150 390.0 570.0 0.6842 383.0 0.6719 125.0 127.0 158.0 0.8038 0.7911 115.0 115.0 152.0 0.7566 0.7566 83.0 87.0 142.0 0.6127 0.5845 60.0 61.0 118.0 0.5169 0.5085 0.0 0.0 0.0 0.0 0.0
0.0 16.0 16 4.0738 0.0063 3350.0615 2322.0857 388.0 570.0 0.6807 380.0 0.6667 124.0 127.0 158.0 0.8038 0.7848 116.0 116.0 152.0 0.7632 0.7632 82.0 85.0 142.0 0.5986 0.5775 58.0 60.0 118.0 0.5085 0.4915 0.0 0.0 0.0 0.0 0.0
0.0 17.0 17 4.0949 0.0063 3367.3849 2334.0934 386.0 570.0 0.6772 378.0 0.6632 124.0 127.0 158.0 0.8038 0.7848 115.0 115.0 152.0 0.7566 0.7566 81.0 84.0 142.0 0.5915 0.5704 58.0 60.0 118.0 0.5085 0.4915 0.0 0.0 0.0 0.0 0.0
0.0 18.0 18 4.2008 0.0063 3454.4411 2394.4361 385.0 570.0 0.6754 376.0 0.6596 125.0 128.0 158.0 0.8101 0.7911 115.0 115.0 152.0 0.7566 0.7566 78.0 82.0 142.0 0.5775 0.5493 58.0 60.0 118.0 0.5085 0.4915 0.0 0.0 0.0 0.0 0.0
0.0 19.0 19 4.2113 0.0063 3463.0756 2400.4211 386.0 570.0 0.6772 378.0 0.6632 125.0 128.0 158.0 0.8101 0.7911 114.0 114.0 152.0 0.75 0.75 81.0 84.0 142.0 0.5915 0.5704 58.0 60.0 118.0 0.5085 0.4915 0.0 0.0 0.0 0.0 0.0
0.0 20.0 20 4.2743 0.0063 3514.9065 2436.3475 382.0 570.0 0.6702 374.0 0.6561 124.0 127.0 158.0 0.8038 0.7848 115.0 115.0 152.0 0.7566 0.7566 77.0 81.0 142.0 0.5704 0.5423 58.0 59.0 118.0 0.5 0.4915 0.0 0.0 0.0 0.0 0.0
0.0 21.0 21 4.2790 0.0063 3518.7559 2439.0157 378.0 570.0 0.6632 372.0 0.6526 124.0 127.0 158.0 0.8038 0.7848 114.0 114.0 152.0 0.75 0.75 79.0 81.0 142.0 0.5704 0.5563 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 22.0 22 4.3109 0.0063 3544.9824 2457.1946 381.0 570.0 0.6684 373.0 0.6544 125.0 128.0 158.0 0.8101 0.7911 114.0 114.0 152.0 0.75 0.75 78.0 81.0 142.0 0.5704 0.5493 56.0 58.0 118.0 0.4915 0.4746 0.0 0.0 0.0 0.0 0.0
0.0 23.0 23 4.3390 0.0063 3568.1153 2473.2290 380.0 570.0 0.6667 373.0 0.6544 124.0 127.0 158.0 0.8038 0.7848 114.0 114.0 152.0 0.75 0.75 79.0 82.0 142.0 0.5775 0.5563 56.0 57.0 118.0 0.4831 0.4746 0.0 0.0 0.0 0.0 0.0
0.0 24.0 24 4.3289 0.0063 3559.8267 2467.4839 380.0 570.0 0.6667 372.0 0.6526 124.0 127.0 158.0 0.8038 0.7848 115.0 115.0 152.0 0.7566 0.7566 77.0 81.0 142.0 0.5704 0.5423 56.0 57.0 118.0 0.4831 0.4746 0.0 0.0 0.0 0.0 0.0
0.0 25.0 25 4.3637 0.0063 3588.4182 2487.3020 379.0 570.0 0.6649 371.0 0.6509 124.0 127.0 158.0 0.8038 0.7848 114.0 114.0 152.0 0.75 0.75 78.0 82.0 142.0 0.5775 0.5493 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 26.0 26 4.3781 0.0063 3600.2845 2495.5270 378.0 570.0 0.6632 371.0 0.6509 124.0 127.0 158.0 0.8038 0.7848 113.0 113.0 152.0 0.7434 0.7434 78.0 81.0 142.0 0.5704 0.5493 56.0 57.0 118.0 0.4831 0.4746 0.0 0.0 0.0 0.0 0.0
0.0 27.0 27 4.3894 0.0063 3609.5398 2501.9423 377.0 570.0 0.6614 369.0 0.6474 124.0 127.0 158.0 0.8038 0.7848 113.0 113.0 152.0 0.7434 0.7434 77.0 81.0 142.0 0.5704 0.5423 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 28.0 28 4.3832 0.0063 3604.4250 2498.3971 378.0 570.0 0.6632 372.0 0.6526 124.0 126.0 158.0 0.7975 0.7848 113.0 113.0 152.0 0.7434 0.7434 79.0 81.0 142.0 0.5704 0.5563 56.0 58.0 118.0 0.4915 0.4746 0.0 0.0 0.0 0.0 0.0
0.0 29.0 29 4.3985 0.0063 3617.0423 2507.1427 379.0 570.0 0.6649 370.0 0.6491 124.0 127.0 158.0 0.8038 0.7848 114.0 114.0 152.0 0.75 0.75 77.0 81.0 142.0 0.5704 0.5423 55.0 57.0 118.0 0.4831 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 30.0 30 4.4130 0.0063 3628.9597 2515.4032 378.0 570.0 0.6632 369.0 0.6474 125.0 128.0 158.0 0.8101 0.7911 112.0 112.0 152.0 0.7368 0.7368 77.0 81.0 142.0 0.5704 0.5423 55.0 57.0 118.0 0.4831 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 31.0 31 4.3846 0.0063 3605.6251 2499.2288 377.0 570.0 0.6614 370.0 0.6491 124.0 127.0 158.0 0.8038 0.7848 113.0 113.0 152.0 0.7434 0.7434 78.0 81.0 142.0 0.5704 0.5493 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 32.0 32 4.4328 0.0063 3645.2685 2526.7076 378.0 570.0 0.6632 371.0 0.6509 124.0 127.0 158.0 0.8038 0.7848 113.0 113.0 152.0 0.7434 0.7434 78.0 81.0 142.0 0.5704 0.5493 56.0 57.0 118.0 0.4831 0.4746 0.0 0.0 0.0 0.0 0.0
0.0 33.0 33 4.4063 0.0063 3623.4620 2511.5925 379.0 570.0 0.6649 371.0 0.6509 124.0 127.0 158.0 0.8038 0.7848 114.0 114.0 152.0 0.75 0.75 78.0 82.0 142.0 0.5775 0.5493 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 34.0 34 4.4189 0.0063 3633.7879 2518.7499 378.0 570.0 0.6632 371.0 0.6509 124.0 127.0 158.0 0.8038 0.7848 114.0 114.0 152.0 0.75 0.75 78.0 81.0 142.0 0.5704 0.5493 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 35.0 35 4.4016 0.0063 3619.6355 2508.9402 379.0 570.0 0.6649 371.0 0.6509 124.0 127.0 158.0 0.8038 0.7848 113.0 113.0 152.0 0.7434 0.7434 78.0 82.0 142.0 0.5775 0.5493 56.0 57.0 118.0 0.4831 0.4746 0.0 0.0 0.0 0.0 0.0
0.0 36.0 36 4.4070 0.0063 3624.0410 2511.9938 378.0 570.0 0.6632 370.0 0.6491 124.0 127.0 158.0 0.8038 0.7848 113.0 113.0 152.0 0.7434 0.7434 78.0 81.0 142.0 0.5704 0.5493 55.0 57.0 118.0 0.4831 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 37.0 37 4.4347 0.0063 3646.8202 2527.7831 375.0 570.0 0.6579 368.0 0.6456 123.0 126.0 158.0 0.7975 0.7785 113.0 113.0 152.0 0.7434 0.7434 77.0 80.0 142.0 0.5634 0.5423 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0
0.0 38.0 38 4.4391 0.0063 3650.3984 2530.2633 375.0 570.0 0.6579 368.0 0.6456 124.0 127.0 158.0 0.8038 0.7848 112.0 112.0 152.0 0.7368 0.7368 77.0 80.0 142.0 0.5634 0.5423 55.0 56.0 118.0 0.4746 0.4661 0.0 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1
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