EVALUATION_SUMMARY.md

📊 CodeLlama Evaluation Summary

Date: November 25, 2025
Model: codellama-fifo-v1

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🎯 Quick Summary

Metric	Value
Training Samples Avg Similarity	13.30%
Test Samples Avg Similarity	0.93%
Overall Similarity	7.11%
Code Generation Rate	50% (training only)

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✅ What Worked

1. Model Loading: Successfully loads with LoRA adapters
2. Training Samples: Partial code generation (module declarations)
3. Training Sample 2: 20.70% similarity (best result)

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❌ Critical Issues

1. Incomplete Code: Training samples generate only module declarations
2. Text Instead of Code: Test samples generate repetitive text notes
3. Repetition: Severe repetition in test sample outputs
4. Early Stopping: Code generation stops before completion

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🔧 Immediate Actions Needed

1. Fix Prompt Format

   • Match training data format exactly
   • Test without system prompt prefix
   • Add explicit code generation instruction

2. Adjust Inference Parameters

   • Try lower temperature (0.1-0.2)
   • Increase max_new_tokens
   • Test different stopping criteria

3. Check Training Data

   • Verify all samples have complete code
   • Ensure consistent formatting
   • Remove any text-only samples

4. Re-test with Adjusted Prompts

   • Use exact training format
   • Test simpler prompts
   • Verify generation doesn't stop early

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📈 Detailed Results

See EVALUATION_REPORT.md for complete analysis.

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Status: ⚠️ NEEDS IMPROVEMENT
Next Steps: Adjust prompts and inference parameters, then re-test.