know what we found is that you can either get a loss to be nonzero here this is the loss is the log loss which is not the classification accuracy you can work really hard to get this to get your generalization error down and in this case the test error or you could just run it to zero essentially just taking this configuration and turning off all the regularization round to zero and while you see a drop in accuracy you don't see a gigantic drop so the test error increases but only by about 5% and moreover if you just pick a bigger model