been updated by training on the pseudo labels from the teacher network are then going to be evaluated to provide a reward signal for the teacher network by taking those parameters and then having them classify a held-out validation set so the performance on the validation set is the reward signal that goes back through the teacher by taking a gradient through a gradient or do something we'll get into more in the later on in the video the idea is that the teacher model is going to be training changing this distribution of class labels to maximize