Add comprehensive model card with security evaluation results
Browse files
README.md
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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**:
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- **Average Security Score**: 0.
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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 | β
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| Command Injection | 0 | β
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| Path Traversal |
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| Weak Cryptography | 0 | β
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| Hardcoded Secrets | 0 | β
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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**:
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- **Epochs**:
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## π 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 | β
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| Command Injection | 0 | β
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| Path Traversal | 2 | β
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| Weak Cryptography | 0 | β
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| Hardcoded Secrets | 0 | β
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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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## π Evaluation
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