Huh? How do you "overfit" on the test set if you don't have the test set? And also to call a good ML result a "coin toss" shows a profound lack of understanding of what goes into such "coin tosses", and why solving practical problems with ML is an entirely different ballgame than training a classifier on imagenet (which is in itself pretty hard if you want SOTA results).