After each epoch, Keras provides the following evaluations (depending on how the model is compiled):
Keras evaluates the performance of the model using the validation set at the end of each epoch. But how does Keras do this? Assume that we are performing binary classification and using a binary loss function. Assume that there are 100 images in the validation set.
QUESTION: Can the accuracy can be found by simply calculating accuracy for each item and then average them (/100)?
CONTEXT: I want to implement a custom loss function that calculates the loss towards reducing validation loss (increasing validation accuracy). Therefore, I need to understand how the accuracy is calculated for the validation set.