Update README.md

README.md

@@ -37,6 +37,27 @@ The model architecture consists of the following components:
 4.  **Regularization**: A **Dropout layer** (`0.5` rate) prevents overfitting.
 5.  **Output**: A **Dense layer** with `softmax` activation predicts probabilities for "Real" and "Fake" classes.
 
+## Evaluation
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+The model was tested on unseen samples from the FaceForensics++ and CelebDFv2 datasets.
+
+#### Metrics
+* **Accuracy**: Measures correct classifications.
+* **F1 Score**: Balances precision and recall.
+
+### Results
+
+| Metric             | Value   |
+| :----------------- | :------ |
+| Training Accuracy  | 98.44%  |
+| Validation Accuracy| 97.05%  |
+| Test Accuracy      | 95.93%  |
+
+**Disclaimer**: These results were obtained using the FaceForensics++ and CelebDFv2 datasets. Performance in real-world scenarios may vary.
+
 
 ### How to Use