---
language: en
tags:
  - jailbreak-detection
  - deberta-v3
  - text-classification
model-index:
  - name: predict_llama3.2_3b
    results:
      - task:
          type: text-classification
          name: Jailbreak Detection
        metrics:
          - name: F1
            type: f1
            value: 0.7216
          - name: PR-AUC
            type: pr_auc
            value: 0.7712
          - name: ROC-AUC
            type: roc_auc
            value: 0.9199
          - name: Precision
            type: precision
            value: 0.6306
          - name: Recall
            type: recall
            value: 0.8434
---
# Jailbreak Prediction Model: llama3.2:3b

Fine-tuned DeBERTa-v3-base for detecting unsafe/jailbreak prompts in multi-turn conversations.

## Evaluation Results (best fold: 1)

| Metric         | Value  |
|----------------|--------|
| F1             | 0.7216 |
| PR-AUC         | 0.7712 |
| ROC-AUC        | 0.9199 |
| Precision      | 0.6306 |
| Recall         | 0.8434 |
| Best Threshold | 0.20 |

## Training Details

- **Base model**: `microsoft/deberta-v3-base`
- **Target model**: `llama3.2:3b`
- **Datasets**: HarmBench
- **K-Folds**: 5
- **Epochs**: 5
- **Learning Rate**: 2e-05
- **Max Length**: 512
- **Input format**: turns only

## Dataset Size (before turn expansion)

Original rows (after cleaning and balancing): 2096 (unsafe: 401, safe: 1695)