I'm interested in good references on cross-validation implementations for feed-forward neural networks in pytorch from scratch.
Thanks in advance.
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All the same considerations for cross validation apply for neural networks as for any other type of model. I.e. the usual scikit-learn (or other options for special situations like grouped+stratified CV) approaches would be used.
A common mistake with CV for neural networks is to do data augmentation before creating CV (and/or test) splits.