I was running some experiments with different size data sets and found what I think might be a useful heuristic for automatically setting an epoch count on fit_one_cycle with tabular learner. Offering to this forum as a thank you for the library.
def fastai_epoch_heuristic(self, rowcount, columncount):
#Heuristic to calculate number of epochs to apply
#Tries to er on the side of underfit
#some further validations on this heuristic still needed
epoch_count = 1 rowcount = rowcount / 50000 if rowcount > 1: epoch_count = int(rowcount ** 0.5) epoch_count = int(epoch_count * ((columncount / 15) ** 0.5)) if epoch_count < 1: epoch_count = 1 return epoch_count