Delete configs/config_noUI.yaml

configs/config_noUI.yaml

@@ -1,37 +0,0 @@
-# Note: In order to train the model and then evaluate the same model, you need to
-# make sure that the base_model to be the same in both the train and eval sections
-
-# Evaluation configuration
-eval:
-  base_model: meta-llama/Llama-3.2-1B
-  graph_path: datasets/quantum_graph.gexf
-  model_name: llama_1b_qlora_uncensored
-
-# Training configuration
-training:
-  graph_path: datasets/quantum_graph.gexf # path to the graph file to train on
-  base_model: meta-llama/Llama-3.2-1B
-  trainer_args:
-    per_device_train_batch_size: 4
-    warmup_steps: 100
-    num_train_epochs: 1
-    learning_rate: 0.0002
-    lr_scheduler_type: 'cosine'
-    fp16: true
-    logging_steps: 1
-    save_steps: 50
-    trainer_output_dir: trainer_outputs/
-  tokenizer:
-    max_length: 1024
-  qlora:
-    rank: 8
-    lora_alpha: 32
-    lora_dropout: 0.05
-    target_modules:  # modules for which to train lora adapters
-    - q_proj
-    - k_proj
-    - v_proj
-    - o_proj
-  model_saving:
-    model_output_dir: models  # model saved in {model_output_dir}/{model_name} after fine-tuning completion
-    model_name: llama_1b_qlora_uncensored