| from transformers import TrainingArguments | |
| training_args = TrainingArguments( | |
| output_dir="./results", | |
| num_train_epochs=3, | |
| per_device_train_batch_size=8, | |
| per_device_eval_batch_size=8, | |
| warmup_steps=500, | |
| weight_decay=0.01, | |
| logging_dir='./logs', | |
| logging_steps=50, | |
| save_steps=500, | |
| eval_steps=500, | |
| evaluation_strategy="steps", | |
| save_strategy="steps", | |
| save_total_limit=3, | |
| load_best_model_at_end=True, | |
| learning_rate=5e-5, | |
| fp16=True, | |
| gradient_checkpointing=True, | |
| # Remove CPU-only settings | |
| no_cuda=False, # Allow GPU usage | |
| use_cpu=False # Allow GPU usage | |
| ) |