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@@ -18,8 +18,27 @@ This is a fine-tuned **`ResNet-18`** model designed for a 7-class classification
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  ## πŸ“ˆ Evaluation Metrics on Test Data
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- ![Confusion Matrix](Test Accuracy 80.31%.png)
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  ## πŸ§‘β€πŸ’» How to Use
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  ## πŸ“ˆ Evaluation Metrics on Test Data
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+ ![confusion matrix](images/confusion_matrix.png)
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+
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+ Accuracy: 79.92%
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+ Precision: 79.80%
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+ Recall: 79.92%
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+ F1-Score: 79.80%
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+ Classification Report:
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+ precision recall f1-score support
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+
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+ 1 0.79 0.81 0.80 329
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+ 2 0.58 0.47 0.52 74
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+ 3 0.51 0.42 0.46 160
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+ 4 0.92 0.90 0.91 1185
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+ 5 0.74 0.78 0.76 478
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+ 6 0.68 0.72 0.70 162
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+ 7 0.75 0.78 0.77 680
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+
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+ accuracy 0.80 3068
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+ macro avg 0.71 0.70 0.70 3068
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+ weighted avg 0.80 0.80 0.80 3068
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  ## πŸ§‘β€πŸ’» How to Use
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