you take the new student as a teacher if you you basically train it on label data you infer the pseudo you infer the zero labels unlabeled data again with this new teacher and you create a new student and so on and repeat this process like multiple times and you get a really good for Adam so here are the experiment settings the architecture that you use is efficient at and the model noises they use is dropout of stochastic tap the input nicely uses Randolph which is a version of auto valve it's more efficient and for zero labels they use