of the model we have two types of regularization l one or the lasso regression and l two or the ridge regression the range regression adds squared magnitude of coefficient as penalty to loss function and mix match uses the squared or the l2 laws on prediction and guest labels and lastly the main teacher to overcome the problem of inconsistency in using the exponential moving average of label prediction on each training set on large data a mean teacher a method that averages model weights instead of label prediction is used