architecture achieves 38.7% image net but their model achieves like 20% better and is getting much closer to the fully supervised benchmarks so this is another interesting thing that they present is that the success on this Hope supervised task isn't always correlated with image accuracy like this point right here has like 95 percent on rotation but then only like 20 percent on that image net accuracy so then another very interesting takeaway from the study is that it seems like larger models like increasing the width