Update README.md

README.md

@@ -13,7 +13,34 @@ tags:
 - fake
 - real
 - news
-datasets:
-- Reyansh4/Fake-News-Classification
 library_name: transformers
----
+---
+
+# DistilBERT Fake News Classifier
+
+## Model Description
+This DistilBERT-based model achieves **97.18% accuracy** in classifying news articles as real or fake, with balanced precision (97.17%) and recall (97.30%).
+
+## Training Performance
+| Epoch | Training Loss | Validation Loss | Accuracy | F1 Score |
+|-------|---------------|-----------------|----------|----------|
+| 1     | -             | 0.1115          | 96.08%   | 96.09%   |
+| 2     | 0.2026        | 0.1077          | 97.25%   | 97.28%   |
+| 3     | 0.0647        | 0.1119          | 97.45%   | 97.50%   |
+
+## Final Test Results
+| Metric     | Score  |
+|------------|--------|
+| Accuracy   | 97.18% |
+| F1 Score   | 97.23% |
+| Precision  | 97.17% |
+| Recall     | 97.30% |
+
+## Usage
+```python
+from transformers import pipeline
+
+classifier = pipeline("text-classification", 
+                    model="KenLumod/ML-Project-DistilBERT-Fake-and-Real-Classifier")
+result = classifier("Scientists confirm climate change accelerating beyond previous estimates")
+# Output: {'label': 'REAL', 'score': 0.982}