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language: en
tags:
- jailbreak-detection
- deberta-v3
- text-classification
model-index:
- name: predict_zephyr_7b-beta
results:
- task:
type: text-classification
name: Jailbreak Detection
metrics:
- name: F1
type: f1
value: 0.8592
- name: PR-AUC
type: pr_auc
value: 0.9080
- name: ROC-AUC
type: roc_auc
value: 0.9757
- name: Precision
type: precision
value: 0.8841
- name: Recall
type: recall
value: 0.8356
---
# Jailbreak Prediction Model: zephyr:7b-beta
Fine-tuned DeBERTa-v3-base for detecting unsafe/jailbreak prompts in multi-turn conversations.
## Evaluation Results (best fold: 3)
| Metric | Value |
|----------------|--------|
| F1 | 0.8592 |
| PR-AUC | 0.9080 |
| ROC-AUC | 0.9757 |
| Precision | 0.8841 |
| Recall | 0.8356 |
| Best Threshold | 0.10 |
## Training Details
- **Base model**: `microsoft/deberta-v3-base`
- **Target model**: `zephyr:7b-beta`
- **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): 1730 (unsafe: 336, safe: 1394)
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