training-scripts / train_sft.py
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# /// script
# dependencies = [
# "trl>=0.12.0",
# "peft>=0.7.0",
# "transformers>=4.51.0",
# "accelerate>=0.24.0",
# "trackio",
# "datasets",
# ]
# ///
"""
SFT training: Qwen3-0.6B on open-r1/codeforces-cots for instruction following.
Quick test run with 100 examples.
"""
import trackio
from datasets import load_dataset
from peft import LoraConfig
from trl import SFTTrainer, SFTConfig
# Load dataset - using solutions_w_editorials config for instruction following
print("Loading dataset...")
dataset = load_dataset(
"open-r1/codeforces-cots",
"solutions_w_editorials",
split="train"
)
print(f"Full dataset: {len(dataset)} examples")
# Take 100 examples for quick test
dataset = dataset.select(range(min(100, len(dataset))))
print(f"Using {len(dataset)} examples for training")
# Create train/eval split (90/10)
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="qwen3-codeforces-sft",
push_to_hub=True,
hub_model_id="gilbaes/qwen3-0.6b-codeforces-sft",
hub_strategy="every_save",
# Training parameters
num_train_epochs=1,
per_device_train_batch_size=2,
gradient_accumulation_steps=4,
learning_rate=2e-4,
max_length=2048,
# Logging & checkpoints
logging_steps=5,
save_strategy="steps",
save_steps=50,
save_total_limit=2,
# Evaluation
eval_strategy="steps",
eval_steps=25,
# Optimization
warmup_ratio=0.1,
lr_scheduler_type="cosine",
bf16=True,
# Monitoring
report_to="trackio",
project="qwen3-codeforces",
run_name="sft-test-100examples",
)
# 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 Qwen3-0.6B...")
trainer = SFTTrainer(
model="Qwen/Qwen3-0.6B",
train_dataset=train_dataset,
eval_dataset=eval_dataset,
args=config,
peft_config=peft_config,
)
# Train
print("Starting training...")
trainer.train()
# Push to Hub
print("Pushing model to Hub...")
trainer.push_to_hub()
print("Training complete!")
print(f"Model: https://huggingface.co/gilbaes/qwen3-0.6b-codeforces-sft")
print(f"Trackio: https://huggingface.co/spaces/gilbaes/trackio")