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| """Lexwell SFT — Qwen2.5-3B-Instruct fine-tune on IRAC contract-review corpus. |
| |
| Memory-tuned for a10g-large (24 GB): gradient checkpointing + batch 2 + grad-accum 2 |
| keeps effective batch at 4 and total steps at 200 across 10 epochs. |
| """ |
| from datasets import load_dataset |
| from peft import LoraConfig |
| from trl import SFTTrainer, SFTConfig |
|
|
| BASE = "Qwen/Qwen2.5-3B-Instruct" |
| DS = "Curious-PM/lexwell-contract-irac" |
| OUT = "Curious-PM/lexwell-contract-irac-qwen2.5-3b-lora" |
|
|
| print(f"Loading dataset {DS}...") |
| ds = load_dataset(DS, data_files="lexwell_v2.jsonl", split="train") |
| print(f"Loaded {len(ds)} rows") |
|
|
| trainer = SFTTrainer( |
| model=BASE, |
| train_dataset=ds, |
| peft_config=LoraConfig( |
| r=16, |
| lora_alpha=32, |
| task_type="CAUSAL_LM", |
| target_modules=["q_proj", "k_proj", "v_proj", "o_proj"], |
| ), |
| args=SFTConfig( |
| output_dir="lexwell-lora", |
| num_train_epochs=10, |
| per_device_train_batch_size=2, |
| gradient_accumulation_steps=2, |
| learning_rate=2e-4, |
| max_length=2048, |
| logging_steps=10, |
| eval_strategy="no", |
| save_strategy="no", |
| bf16=True, |
| gradient_checkpointing=True, |
| gradient_checkpointing_kwargs={"use_reentrant": False}, |
| optim="adamw_torch_fused", |
| dataloader_pin_memory=False, |
| push_to_hub=True, |
| hub_model_id=OUT, |
| hub_strategy="end", |
| report_to="none", |
| ), |
| ) |
|
|
| print("Starting training...") |
| trainer.train() |
| print("Training complete. Pushing to Hub...") |
| trainer.push_to_hub() |
| print(f"\nAdapter pushed: https://huggingface.co/{OUT}") |
|
|
