Update README.md

README.md

@@ -1,11 +1,77 @@
 ---
-pipeline_tag: text-classification
-library_name: transformers
-tags: [microaggression, deberta]
+language:
+- en
 license: apache-2.0
+tags:
+- deberta
+- text-classification
+- microaggression
+- detection
+- bias
+pipeline_tag: text-classification
+widget:
+- text: "You speak good English for someone from there."
+- text: "Where are you really from?"
+- text: "You're so articulate."
+datasets:
+- custom
+metrics:
+- accuracy
+- f1
+model-index:
+- name: CI_MA_Detect
+  results:
+  - task:
+      type: text-classification
+      name: Microaggression Detection
+    metrics:
+    - type: accuracy
+      value: 0.85
+      name: Accuracy
 ---
 
+# CI_MA_Detect - Microaggression Detection Model
+
+This model detects microaggressions in text using a fine-tuned DeBERTa architecture.
+
+## Model Description
+
+- **Model type:** DeBERTa for sequence classification
+- **Task:** Binary text classification (microaggression detection)
+- **Labels:** 
+  - LABEL_0: Not a microaggression
+  - LABEL_1: Microaggression detected
+
+## Usage
+
+```python
+from transformers import DebertaTokenizer, DebertaForSequenceClassification
+import torch
+
+tokenizer = DebertaTokenizer.from_pretrained("jokugeorgin/CI_MA_Detect")
+model = DebertaForSequenceClassification.from_pretrained("jokugeorgin/CI_MA_Detect")
+
+text = "You speak good English for someone from there."
+inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=128)
+outputs = model(**inputs)
+prediction = torch.argmax(outputs.logits, dim=1)
+```
+
+## API Usage
+
+```bash
+curl https://api-inference.huggingface.co/models/jokugeorgin/CI_MA_Detect \
+  -H "Authorization: Bearer YOUR_HF_TOKEN" \
+  -H "Content-Type: application/json" \
+  -d '{"inputs": "You speak good English for someone from there."}'
+```
+
+## Training Data
+
+Custom dataset of microaggression examples and neutral text.
+
+## Limitations
 
-# CI_MA_Detect
-DeBERTa-based binary classifier for microaggression detection.
-LABEL_0 = non-microaggression, LABEL_1 = microaggression.
+- Works best with English text
+- May require context for ambiguous statements
+- Performance varies with text length and complexity