How to interpret increase in both loss and accuracy

Question

I have run deep learning models(CNN\'s) using tensorflow. Many times during the epoch, i have observed that both loss and accuracy have increased, or both have decreased. My und

Answer 1

I think the top-rated answer is incorrect.

I will assume you are talking about cross-entropy loss, which can be thought of as a measure of 'surprise'.

Loss and accuracy increasing/decreasing simultaneously on the training data tells you nothing about whether your model is overfitting. This can only be determined by comparing loss/accuracy on the validation vs. training data.

If loss and accuracy are both decreasing, it means your model is becoming more confident on its correct predictions, or less confident on its incorrect predictions, or both, hence decreased loss. However, it is also making more incorrect predictions overall, hence the drop in accuracy. Vice versa if both are increasing. That is all we can say.