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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: 0.8687
- name: PR-AUC
type: pr_auc
value: 0.9193
- name: ROC-AUC
type: roc_auc
value: 0.9649
- name: Precision
type: precision
value: 0.8431
- name: Recall
type: recall
value: 0.8958
---
# Jailbreak Prediction Model: llama3.2:3b
Fine-tuned DeBERTa-v3-base for detecting unsafe/jailbreak prompts in multi-turn conversations.
## Evaluation Results (best fold: 2)
| Metric | Value |
|----------------|--------|
| F1 | 0.8687 |
| PR-AUC | 0.9193 |
| ROC-AUC | 0.9649 |
| Precision | 0.8431 |
| Recall | 0.8958 |
| Best Threshold | 0.35 |
## 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): 1319 (unsafe: 220, safe: 1099)
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