Yes, you are resetting the hyperparameters and are training a new model in each iteration.


k-fold CV gives you a better “unbiased” estimate of the generalization performance of your model.


@rasbt explains this techniques here 23 and also compares it to other hold-out methods.
Often you would use k-fold CV if your dataset is small and your overall training might thus finish quickly.
I haven’t seen this technique used for a DL model on e.g. ImageNet and don’t know if you would benefit much, since this dataset is already large.