Update README.md

README.md

@@ -72,3 +72,31 @@ results = classifier(headlines)
 for result in results:
     print(f"Label: {result['label']}, Score: {result['score']:.4f}")
 ```
+
+## Training Procedure
+
+The model was fine-tuned on a dataset of **860 headlines** annotated for the presence of a *conflict frame*.
+
+---
+
+## Hyperparameters
+
+| Hyperparameter            | Value         |
+|---------------------------|---------------|
+| Conflict Class Weight     | 1.69          |
+| Non-Conflict Class Weight | 9.01          |
+| Learning Rate             | 6.008 × 10⁻⁵  |
+| Epochs                    | 9             |
+
+---
+
+## Evaluation Results
+
+The model's performance was evaluated using **5-fold cross-validation**. The average metrics are reported below:
+
+| Class         | Precision | Recall | F1-Score |
+|---------------|-----------|--------|----------|
+| Conflict      | 0.92      | 0.91   | 0.92     |
+| Non-Conflict  | 0.81      | 0.82   | 0.81     |
+| Macro avg | 0.87  | 0.87 |   **0.87**       |
+