@ptrblck Thanks for the answer! so to put it simply, can it be said that due to the intense overfitting, the model is now classifying the correctly classified images less better than before (e.g assigning them a lesser softmax probability than before). This while keeping the accuracy relatively constant, increases the loss. Will that be the correct interpretation of what you are saying?