uh because that makes it easier to give a consistent prediction and also increases the confidence of the predicted labor as you see in label guessing we only guess the label of the unlabeled data however we do augmentations on both labeled and unlabeled data to come to this um label guessing wherein the label is guest based on whatever is in the label data as well as in the unlabeled data but transformations are mostly done on the unlabeled data as many times as required but according to what the authors have seen