In lesson 2 notebook we first learn on the frozen layers
learn.fit(lr, 3, cycle_len=1, cycle_mult=2)
But what is the point of that if few lines below we unfreeze all the layers and do the fitting again?
lrs = np.array([lr/9, lr/3, lr]) learn.unfreeze() learn.fit(lrs, 3, cycle_len=1, cycle_mult=2)
Does the model preserve weights from the first fitting (if so is there any way to check where they are?) or it was just for the sake of comparison results for frozen vs unfrozen layers?