training and on the test data yeah we're doing the station depends on the loss and is these anticipation arising due to two square lows oh yeah good question well in this case we it was it was cross entropy loss it wasn't that wasn't weird work with rotations of two similar images have the same label yeah so the loss in comparative labels and so that has to change the regularization has to change to the same yeah let's yeah so so for just for now the interest of time let's just assume cross-entropy loss for a classification