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README.md

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-license: mit
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+# 🧠 BERT Classifier for Black Article Detection
+
+## 📝 Model Overview
+This repository hosts a fine-tuned BERT model (`bert-base-uncased`) for classifying newspaper articles based on whether they center on Black people. The training dataset is provided for full reproducibility.
+
+## 📖 Description
+The model was trained on 2,000 manually labeled sentences from historical newspaper articles (1960–1973). Labels indicate if the article primarily concerns Black people.
+- **Inputs:** `sentence` *(string)*
+- **Outputs:** `black_story` *(0 or 1)*
+
+## 📊 Performance Metrics
+- **Training Accuracy:** 93.5%
+- **Validation Accuracy:** 91.2%
+- **Precision:** 90.8%
+- **Recall:** 92.1%
+
+## 🚀 Usage Instructions
+To use this model via Hugging Face Transformers:
+```python
+from transformers import pipeline
+classifier = pipeline("text-classification", model="mikemcrae/black-article-classifier")
+result = classifier("Black activists led a peaceful protest downtown.")
+print(result)
+
+
+MIT License © 2025 Mike McRae
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND.