I'm struggling with calculating accuracy when I do cross-validation for a deep learning model. I have two candidates for doing this. 1. Train a model with 10 different folds and get the best accuracy of them(so I get 10 best accuracies) and average them. 2. Train a model with 10 different folds and get 10 accuracy learning curves. Now, average these learning curves by calculating the mean of 10 accuracies of each epoch. So now we get one averaged accuracy learning curve and find the highest accuracy from this curve.
Among these two candidates which one is correct??