I have a neural network that Im evaluating using 10 -Fold cross validation. The validation accuracy for a fold changes alot during training in the range of -+10%
So for example the validation accuracy of a fold would range between 80% and 70%.
My question is which number should I consider to be this fold's accuracy.
Should I just take the maximum validation accuracy reached while training or should I just run the training for a certain number of epochs and take the last number (The second approach's result will depend on luck)?