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Update README.md

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@@ -89,7 +89,7 @@ print("Vulnerable Code" if predicted_label == 1 else "Safe Code")
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  ### Training Data
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  - **Dataset:** `DetectVul/devign`
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  - **Classes:** `0 (Safe)`, `1 (Vulnerable)`
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- - **Size:** 50,000+ code snippets
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  ### Training Procedure
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  - **Optimizer:** AdamW
@@ -102,7 +102,7 @@ print("Vulnerable Code" if predicted_label == 1 else "Safe Code")
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  ### Training Metrics
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  | Metric | Score |
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- |---------|--------|
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  | **Train Loss** | 0.4835 |
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  | **Evaluation Loss** | 0.6855 |
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  | **Accuracy** | 68.34% |
@@ -125,6 +125,6 @@ The model was evaluated using **20% of the dataset**, with the following results
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  ## Environmental Impact
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  | Factor | Value |
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- |---------|--------|
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  | **GPU Used** | 2x T4 GPU |
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  | **Training Time** | ~1 hour |
 
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  ### Training Data
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  - **Dataset:** `DetectVul/devign`
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  - **Classes:** `0 (Safe)`, `1 (Vulnerable)`
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+ - **Size:** 17483 code snippets
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  ### Training Procedure
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  - **Optimizer:** AdamW
 
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  ### Training Metrics
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  | Metric | Score |
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+ |------------|-------------|
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  | **Train Loss** | 0.4835 |
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  | **Evaluation Loss** | 0.6855 |
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  | **Accuracy** | 68.34% |
 
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  ## Environmental Impact
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  | Factor | Value |
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+ |-----------|----------|
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  | **GPU Used** | 2x T4 GPU |
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  | **Training Time** | ~1 hour |