labels compared to supervised learning with all the labels Simms CL are fixed match or unsupervised data augmentation which are all other algorithms that are successful at doing this kind of learning with limited data this plot shows the performance of these models with respect to the different limited data settings changes as you increase the percentage of labelled data points the interesting part about this plot is this top left area where you have the smaller percentage of labeled data and you see a huge gain of the unsupervised