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Add comprehensive model card with security evaluation results

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  1. README.md +5 -5
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@@ -47,8 +47,8 @@ This LoRA adapter enhances Qwen/Qwen2.5-Coder-0.5B-Instruct to generate secure c
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  - **LoRA Rank**: 64
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  - **LoRA Alpha**: 128
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  - **Training Samples**: 195
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- - **Security Evaluation Pass Rate**: 40.0%
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- - **Average Security Score**: 0.00 (lower is better)
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  ### Vulnerability Prevention Results
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@@ -56,7 +56,7 @@ This LoRA adapter enhances Qwen/Qwen2.5-Coder-0.5B-Instruct to generate secure c
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  |-------------------|-------|---------|
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  | SQL Injection | 0 | βœ… |
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  | Command Injection | 0 | βœ… |
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- | Path Traversal | 0 | βœ… |
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  | Weak Cryptography | 0 | βœ… |
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  | Hardcoded Secrets | 0 | βœ… |
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@@ -142,8 +142,8 @@ def login_user(username, password):
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  - **Objective**: Minimize security vulnerabilities while maintaining functionality
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  - **Reward Signal**: Negative correlation with Semgrep security score
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  - **Batch Size**: 1 with 8x gradient accumulation
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- - **Learning Rate**: 5e-06
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- - **Epochs**: 3
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  ## πŸ“š Evaluation
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  - **LoRA Rank**: 64
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  - **LoRA Alpha**: 128
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  - **Training Samples**: 195
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+ - **Security Evaluation Pass Rate**: 20.0%
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+ - **Average Security Score**: 0.40 (lower is better)
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  ### Vulnerability Prevention Results
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  |-------------------|-------|---------|
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  | SQL Injection | 0 | βœ… |
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  | Command Injection | 0 | βœ… |
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+ | Path Traversal | 2 | βœ… |
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  | Weak Cryptography | 0 | βœ… |
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  | Hardcoded Secrets | 0 | βœ… |
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  - **Objective**: Minimize security vulnerabilities while maintaining functionality
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  - **Reward Signal**: Negative correlation with Semgrep security score
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  - **Batch Size**: 1 with 8x gradient accumulation
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+ - **Learning Rate**: 3e-06
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+ - **Epochs**: 5
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  ## πŸ“š Evaluation
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