they get all the way down to 2.7 percent which is significantly lower so just four thousand samples they're as good as ninety 90 97 either better than nice and accurate on C far which is kind of accuracies you usually get with using all the label data points so that really means to do domain consistency that the data augmentation label consistency is really really helping them and the models are the scaling was with larger networks so when you moved away from 1.5 million parameters it was typically used in semi-square is