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Upload GNN turn-level model artifacts
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---
language: en
tags:
- gnn
- jailbreak-detection
- text-classification
model-index:
- name: predict_gnn_gemma4_26b
results:
- task:
type: text-classification
name: Jailbreak Detection
metrics:
- name: F1
type: f1
value: 0.8783
- name: PR-AUC
type: pr_auc
value: 0.9738
- name: ROC-AUC
type: roc_auc
value: 0.9697
- name: Precision
type: precision
value: 0.8554
- name: Recall
type: recall
value: 0.9344
---
# GNN Jailbreak Prediction Model (gemma4:26b)
Homogeneous GNN classifier for unsafe/jailbreak likelihood in multi-turn conversations.
## Evaluation Results
| Metric | Value |
|----------------|--------|
| F1 | 0.8783 |
| PR-AUC | 0.9738 |
| ROC-AUC | 0.9697 |
| Precision | 0.8554 |
| Recall | 0.9344 |
| Best Threshold | 0.310 |
## Training Details
- **Target model**: `gemma4:26b`
- **Datasets**: harmbench
- **Split column**: `goal`
- **Seed**: `42`
- **Sentence model**: `sentence-transformers/all-MiniLM-L6-v2`
- **Hidden channels**: `128`
- **Num layers**: `2`
- **Dropout**: `0.3`
## Dataset Size (training samples)
Prepared turn-level samples: 517