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I need some help in Interpreting a curve val_loss and loss in keras after training a model

These are the learning curves: after 100  epoch of training

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The training loss decreases while the validation loss increases, which is a clear sign of overfitting. This means that your model is too specific to the training dataset and do not generalize to the testing dataset. To solve that problem you can decrease the complexity of the model or add regularization.

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