representations for image classification what you do is you freeze most of the network and then you take the pre largest layer like the like an intermediate vector representation and then you input that to a logistic regression model and use that as a classifier train with SGD and data augmentation so the vector that they extract feature vector from the sub supervised learning task they vary this from size 2048 4096 6000 144 and 8192 so this is the size of the representation of vector extract from the self supervised learning task