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@@ -79,8 +79,18 @@ label = model.config.id2label[predicted_class]
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  print(f"Predicted Label: {label}")
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  ```
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  # **Performance Metrics**
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- - **Accuracy**: ~95% on the test set.
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- - **F1 Score**: ~94% (macro-average).
 
 
 
 
 
 
 
 
 
 
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  - **Confusion Matrix**:
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  ```
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  [[True Positives, False Negatives],
 
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  print(f"Predicted Label: {label}")
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  ```
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  # **Performance Metrics**
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+ ```
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+ Classification report:
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+
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+ precision recall f1-score support
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+
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+ Real 0.6276 0.9823 0.7659 38054
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+ Fake 0.9594 0.4176 0.5819 38080
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+ accuracy 0.6999 76134
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+ macro avg 0.7935 0.7000 0.6739 76134
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+ weighted avg 0.7936 0.6999 0.6739 76134
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+ ```
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  - **Confusion Matrix**:
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  ```
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  [[True Positives, False Negatives],