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Upload XGBoost TF-IDF model artifacts
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---
language: en
tags:
- xgboost
- jailbreak-detection
- text-classification
model-index:
- name: predict_xgb_llama2_7b
results:
- task:
type: text-classification
name: Jailbreak Detection
metrics:
- name: F1
type: f1
value: 0.7429
- name: PR-AUC
type: pr_auc
value: 0.7525
- name: ROC-AUC
type: roc_auc
value: 0.9181
- name: Precision
type: precision
value: 0.9286
- name: Recall
type: recall
value: 0.6190
---
# XGBoost Jailbreak Prediction Model: llama2:7b
XGBoost + TF-IDF classifier for unsafe/jailbreak likelihood in multi-turn conversations.
## Evaluation Results (best fold: 5)
| Metric | Value |
|----------------|--------|
| F1 | 0.7429 |
| PR-AUC | 0.7525 |
| ROC-AUC | 0.9181 |
| Precision | 0.9286 |
| Recall | 0.6190 |
| Best Threshold | 0.50 |
## Training Details
- **Target model**: `llama2:7b`
- **Datasets**: HarmBench
- **K-Folds**: 5
- **Input format**: category + goal + turns
- **TF-IDF ngram_range**: `(1, 2)`
- **TF-IDF max_features**: `120000`
- **XGBoost n_estimators**: `1041`
- **XGBoost learning_rate**: `0.05506052874003388`
- **XGBoost max_depth**: `5`
## Dataset Size (before turn expansion)
Original rows (after cleaning and balancing): 355 (unsafe: 0, safe: 0)