Upload train_qwen3_codeforces_test.py with huggingface_hub

train_qwen3_codeforces_test.py

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+# /// script
+# dependencies = ["trl>=0.12.0", "peft>=0.7.0", "trackio", "transformers>=4.44.0", "datasets"]
+# ///
+
+import sys
+from datasets import load_dataset
+from peft import LoraConfig
+from trl import SFTTrainer, SFTConfig
+import trackio
+
+print("="*60)
+print("🚀 STARTING TRAINING JOB - VERBOSE MODE")
+print("="*60)
+
+# Step 1: Load dataset
+print("\n📥 Step 1/5: Loading dataset...")
+try:
+    dataset = load_dataset(
+        "open-r1/codeforces-cots",
+        name="solutions_w_editorials_decontaminated",
+        split="train[:500]"  # Small subset for quick testing
+    )
+    print(f"✅ Dataset loaded: {len(dataset)} examples")
+    print(f"   Columns: {dataset.column_names}")
+    print(f"   First example keys: {list(dataset[0].keys())}")
+except Exception as e:
+    print(f"❌ FAILED to load dataset: {e}")
+    sys.exit(1)
+
+# Step 2: Create train/eval split
+print("\n📊 Step 2/5: Creating train/eval split...")
+try:
+    dataset_split = dataset.train_test_split(test_size=0.1, seed=42)
+    print(f"✅ Split created:")
+    print(f"   Train: {len(dataset_split['train'])} examples")
+    print(f"   Eval: {len(dataset_split['test'])} examples")
+except Exception as e:
+    print(f"❌ FAILED to create split: {e}")
+    sys.exit(1)
+
+# Step 3: Configure LoRA
+print("\n🔧 Step 3/5: Configuring LoRA...")
+try:
+    peft_config = LoraConfig(
+        r=16,
+        lora_alpha=32,
+        lora_dropout=0.05,
+        target_modules=["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
+        task_type="CAUSAL_LM"
+    )
+    print(f"✅ LoRA configured: r={peft_config.r}, alpha={peft_config.lora_alpha}")
+except Exception as e:
+    print(f"❌ FAILED to configure LoRA: {e}")
+    sys.exit(1)
+
+# Step 4: Configure training
+print("\n⚙️  Step 4/5: Configuring training...")
+try:
+    training_args = SFTConfig(
+        output_dir="qwen3-0.6b-codeforces-test",
+        
+        # Quick training for testing
+        num_train_epochs=1,  # Just 1 epoch for quick test
+        per_device_train_batch_size=2,
+        per_device_eval_batch_size=2,
+        gradient_accumulation_steps=2,
+        gradient_checkpointing=True,
+        
+        # Learning rate
+        learning_rate=2e-4,
+        lr_scheduler_type="cosine",
+        warmup_ratio=0.1,
+        optim="paged_adamw_8bit",
+        
+        # Frequent logging for visibility
+        eval_strategy="steps",
+        eval_steps=20,
+        logging_steps=5,  # Log every 5 steps
+        save_strategy="steps",
+        save_steps=50,
+        save_total_limit=2,
+        
+        # Hub integration
+        push_to_hub=True,
+        hub_model_id="kneeraj/qwen3-0.6b-codeforces-test",
+        hub_strategy="every_save",
+        hub_private_repo=False,
+        
+        # Trackio monitoring
+        report_to="trackio",
+        project="codeforces-finetuning-test",
+        run_name="qwen3-quick-test",
+        
+        # Performance
+        bf16=True,
+        max_grad_norm=1.0,
+        
+        # Data processing
+        max_seq_length=1024,  # Shorter for faster processing
+        dataset_text_field="messages",
+        packing=False,
+    )
+    print(f"✅ Training config created")
+    print(f"   Epochs: {training_args.num_train_epochs}")
+    print(f"   Batch size: {training_args.per_device_train_batch_size}")
+    print(f"   Output: {training_args.hub_model_id}")
+except Exception as e:
+    print(f"❌ FAILED to configure training: {e}")
+    sys.exit(1)
+
+# Step 5: Initialize trainer and train
+print("\n🏋️  Step 5/5: Initializing trainer and starting training...")
+try:
+    print("   Loading model: Qwen/Qwen2.5-0.5B-Instruct...")
+    trainer = SFTTrainer(
+        model="Qwen/Qwen2.5-0.5B-Instruct",
+        train_dataset=dataset_split["train"],
+        eval_dataset=dataset_split["test"],
+        peft_config=peft_config,
+        args=training_args,
+    )
+    print(f"✅ Trainer initialized")
+    print(f"   Training samples: {len(dataset_split['train'])}")
+    print(f"   Evaluation samples: {len(dataset_split['test'])}")
+    
+    print("\n" + "="*60)
+    print("🎯 STARTING TRAINING...")
+    print("="*60 + "\n")
+    
+    trainer.train()
+    
+    print("\n" + "="*60)
+    print("💾 Pushing final model to Hub...")
+    trainer.push_to_hub()
+    
+    print("\n" + "="*60)
+    print("✅ TRAINING COMPLETE!")
+    print("="*60)
+    print(f"Model saved to: kneeraj/qwen3-0.6b-codeforces-test")
+    print(f"View at: https://huggingface.co/kneeraj/qwen3-0.6b-codeforces-test")
+    
+except Exception as e:
+    print(f"\n❌ TRAINING FAILED: {e}")
+    import traceback
+    traceback.print_exc()
+    sys.exit(1)