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In order to compare models, you need to define a single metric for the quality of the model. You don't specify but I assume your model is a multiclass classifier: out of 45 labels, for each example, it needs to pick the right one. You can calculate the F1 score of your model for each label vs the rest: how often is it able to correctly predict label 0 vs not ...


One option is to plot fewer epochs. There is no useful information after 20 epochs because training and validation performance are the same after that point.

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