| 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192 |
- # /// script
- # requires-python = ">=3.10"
- # dependencies = [
- # "trl>=0.12.0",
- # "peft>=0.7.0",
- # "transformers>=4.45.0",
- # "accelerate>=0.24.0",
- # "trackio",
- # "datasets",
- # "bitsandbytes",
- # ]
- # ///
- import trackio
- from datasets import load_dataset
- from peft import LoraConfig
- from trl import SFTTrainer, SFTConfig
- # Load dataset from Hub
- print("Loading dataset...")
- dataset = load_dataset("tobil/qmd-query-expansion-train", split="train")
- print(f"Loaded {len(dataset)} examples")
- # Create train/eval split
- dataset_split = dataset.train_test_split(test_size=0.1, seed=42)
- train_dataset = dataset_split["train"]
- eval_dataset = dataset_split["test"]
- print(f"Train: {len(train_dataset)}, Eval: {len(eval_dataset)}")
- # Training configuration
- config = SFTConfig(
- output_dir="qmd-query-expansion-0.6B",
- push_to_hub=True,
- hub_model_id="tobil/qmd-query-expansion-0.6B",
- hub_strategy="every_save",
- # Training parameters
- num_train_epochs=3,
- per_device_train_batch_size=4,
- gradient_accumulation_steps=4,
- learning_rate=2e-4,
- max_length=512,
- # Logging & checkpointing
- logging_steps=25,
- save_strategy="steps",
- save_steps=200,
- save_total_limit=2,
- # Evaluation
- eval_strategy="steps",
- eval_steps=200,
- # Optimization
- warmup_ratio=0.1,
- lr_scheduler_type="cosine",
- bf16=True,
- # Monitoring
- report_to="trackio",
- project="qmd-query-expansion",
- run_name="qwen3-0.6B-lora",
- )
- # LoRA configuration
- peft_config = LoraConfig(
- r=16,
- lora_alpha=32,
- lora_dropout=0.05,
- bias="none",
- task_type="CAUSAL_LM",
- target_modules=["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
- )
- # Initialize trainer
- print("Initializing trainer with Qwen/Qwen3-0.6B...")
- trainer = SFTTrainer(
- model="Qwen/Qwen3-0.6B",
- train_dataset=train_dataset,
- eval_dataset=eval_dataset,
- args=config,
- peft_config=peft_config,
- )
- print("Starting training...")
- trainer.train()
- print("Pushing to Hub...")
- trainer.push_to_hub()
- trackio.finish()
- print("Done! Model at: https://huggingface.co/tobil/qmd-query-expansion-0.6B")
|