do better on its training data than its testing data and what this means is basically that the network is starting to memorize some of the training data and that's what you don't want so what we can do is well we can perform early stopping or we can identify this point this inflection point where the test data starts to increase and diverge from the training data so we can stop the network early and make sure that our test accuracy is as minimum as possible and of course if we actually look at on the side of this line if we look at on