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README.md

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+---
+language: en
+license: apache-2.0
+tags:
+- bias-detection
+- safety
+- multi-label-classification
+- distilbert
+datasets:
+- social_bias_frames
+- google/civil_comments
+metrics:
+- f1
+- roc_auc
+---
+
+# DistilBERT Bias Classifier
+**Safety Sensitiveness Service — Tier 2 Bias Head**
+
+Detects 5 types of bias in short text (search queries, social posts):
+
+| Label | Description |
+|---|---|
+| `racial` | Racial / ethnic bias |
+| `gender` | Gender stereotyping |
+| `religious` | Religious discrimination |
+| `age` | Ageism |
+| `sexual_orientation` | Sexual orientation bias |
+
+## Performance
+
+| Metric | Score |
+|---|---|
+| F1 Macro | 0.2678 |
+| F1 Micro | 0.6810 |
+| ROC-AUC Macro | 0.0000 |
+| CrowS-Pairs Accuracy | 0.0000 |
+| StereoSet Score | 0.4900 |
+
+## Usage
+
+```python
+from transformers import pipeline
+classifier = pipeline("text-classification",
+                      model="guisalim/distilbert-bias-classifier",
+                      top_k=None)
+print(classifier("Search query here"))
+```
+
+## Training details
+- Base: `distilbert-base-uncased`
+- Data: Social Bias Frames + Google Civil Comments
+- Device: mps
+- Threshold: 0.4