I have a simple 2 hidden layer feed forward neural network. As I increase the number of epochs, I am getting a much better F1 score for the test dataset.
Overfitting means that model is performing too well on training data, but my model performs well for the unseen test data (20% of dataset).
Is the only cost of more epochs more computation time in my case?
