Upload train_grpo_qwen7b.py with huggingface_hub

train_grpo_qwen7b.py

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+#!/usr/bin/env python3
+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+#     "trl>=0.12.0",
+#     "transformers>=4.36.0",
+#     "accelerate>=0.24.0",
+#     "peft>=0.7.0",
+#     "trackio",
+#     "datasets>=2.14.0",
+# ]
+# ///
+
+"""
+GRPO training with Qwen2.5-7B-Instruct + LoRA on math reasoning dataset.
+"""
+
+from datasets import load_dataset
+from peft import LoraConfig
+from trl import GRPOTrainer, GRPOConfig
+
+# Load dataset — GRPO uses prompt-only format, take a demo subset
+dataset = load_dataset("trl-lib/math_shepherd", split="train[:3000]")
+print(f"✅ Dataset loaded: {len(dataset)} prompts")
+
+# LoRA config — necessary for 7B model to fit in GPU memory
+lora_config = LoraConfig(
+    r=16,
+    lora_alpha=32,
+    target_modules=["q_proj", "k_proj", "v_proj", "o_proj"],
+    lora_dropout=0.05,
+    task_type="CAUSAL_LM",
+)
+
+# Training configuration
+config = GRPOConfig(
+    # Hub settings — CRITICAL: environment is ephemeral
+    output_dir="qwen2.5-7b-grpo-math",
+    push_to_hub=True,
+    hub_model_id="Conna/qwen2.5-7b-grpo-math",
+    hub_strategy="every_save",
+
+    # Training parameters
+    num_train_epochs=1,
+    per_device_train_batch_size=2,
+    gradient_accumulation_steps=8,   # effective batch = 16
+    learning_rate=1e-6,
+    gradient_checkpointing=True,     # save VRAM
+
+    # Checkpointing
+    logging_steps=10,
+    save_strategy="steps",
+    save_steps=100,
+    save_total_limit=2,
+
+    # LR schedule
+    warmup_ratio=0.1,
+    lr_scheduler_type="cosine",
+
+    # Trackio monitoring
+    report_to="trackio",
+    project="qwen-grpo-training",
+    run_name="qwen2.5-7b-grpo-math-lora",
+)
+
+# GRPO requires an instruct-tuned model as base
+trainer = GRPOTrainer(
+    model="Qwen/Qwen2.5-7B-Instruct",
+    peft_config=lora_config,
+    train_dataset=dataset,
+    args=config,
+)
+
+print("🚀 Starting GRPO training...")
+trainer.train()
+
+print("💾 Pushing final model to Hub...")
+trainer.push_to_hub()
+
+print("✅ Done! Model: https://huggingface.co/Conna/qwen2.5-7b-grpo-math")
+print("📊 Metrics:  https://huggingface.co/spaces/Conna/trackio")