I trained a classifier that outputs probabilities for 3 classes. I produced the plot of the weighted accuracy achieved on test and train set, throughout training.
First, I want to explain how I constructed the contingency table to check if I did a reasonable thing. For each instance, I picked as predicted label the one with the highest probability, and considered it as true prediction when it was equal to the true label.
I understand that from just before epoch 20 onwards the model is kind of converged but there is also a little bit of overfitting (is that right?). But how can I interpret what happened before that, also talking about underfitting and good fit?