being up maybe a little bit more careful about how you pick your learning rate you actually get exactly the same results from random initialization as you do with Swiss pre-training now part of the reason people really like pre-training on imagenet is again this belief that it's kind of this big diverse task and sort of if you train on there you're gonna learn lots of interesting features that you can kind of reuse in lots of places so sort of this underlying assumption is more data is is great but then there was there's