Create README.md

README.md

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+---
+license: mit
+datasets:
+- ethical-spectacle/biased-corpus
+language:
+- en
+metrics:
+- f1(0.8998)
+- precision
+- recall()
+library_name: transformers
+co2_eq_emissions:
+  emissions: 10
+  source: Code Carbon
+  training_type: fine-tuning
+  geographical_location: Albany, New York
+  hardware_used: T4
+base_model:
+- google-bert/bert-base-uncased
+pipeline_tag: text-classification
+tags:
+- Social Bias
+---
+
+## How to Use
+```
+classifier = pipeline("text-classification", model="maximuspowers/bias-type-classifier") // pass in return_all_scores=True for multi-label
+result = classifier("Tall people are so clumsy")
+```
+
+### Example Result
+```json
+[
+    {
+        "label": "physical",
+        "score": 0.9972801208496094
+    }
+]
+```
+
+This model was trained on a [synthetic dataset](https://huggingface.co/datasets/ethical-spectacle/biased-corpus) of biased statements and questions, generated by Mistal 7B as part of the [GUS-Net paper](https://www.linkedin.com/posts/maximuspowers_gus-net-social-bias-ner-model-activity-7245547070978240512-QUqO). 
+
+### Model Performance:
+| Label           | F1 Score | Precision | Recall |
+|-----------------|----------|-----------|--------|
+| **Macro Average** | **0.8998** | **0.9213**  | **0.8807** |
+| racial          | 0.8613   | 0.9262    | 0.8049 |
+| religious       | 0.9655   | 0.9716    | 0.9595 |
+| gender          | 0.9160   | 0.9099    | 0.9223 |
+| age             | 0.9185   | 0.9683    | 0.8737 |
+| nationality     | 0.9083   | 0.9053    | 0.9113 |
+| sexuality       | 0.9304   | 0.9484    | 0.9131 |
+| socioeconomic   | 0.8273   | 0.8727    | 0.7864 |
+| educational     | 0.8791   | 0.9091    | 0.8511 |
+| disability      | 0.8713   | 0.8762    | 0.8665 |
+| political       | 0.9127   | 0.8914    | 0.9351 |
+| physical        | 0.9069   | 0.9547    | 0.8635 |
+
+### Training Params:
+**Learning Rate:** 5e-5
+**Batch Size:** 16
+**Epochs:** 3