YusuphaJuwara
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README.md
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@@ -110,16 +110,10 @@ print("Final validation accuracy: ", metrics['val_accuracies'][-1])
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These metrics can be useful for continuing training from the last epoch or for detailed analysis of the training process.
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## Training results
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![Include a plot of your training metrics here](
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Limitations and bias
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## This model may exhibit biases present in the training data. Always validate results and use the model responsibly.
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## Plots
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![Labels distribution plots](label_distribution.png)
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![loss plots](loss_plot.png)
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![accuracy plots](accuracy_plot.png)
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![f1 score plots](f1_score_plot.png)
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![confusion matrix plots](confusion_matrix.png)
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![precision recall curve plots](precision_recall_curve.png)
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![roc curve plots](roc_curve.png)
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These metrics can be useful for continuing training from the last epoch or for detailed analysis of the training process.
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## Training results
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![Include a plot of your training metrics here](loss_plot.png)
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Limitations and bias
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## This model may exhibit biases present in the training data. Always validate results and use the model responsibly.
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## Plots
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![loss plots](loss_plot.png)
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