Hi guys, just want to confirm here, are the code below still the valid way to do progressive resizing in image classification with fastai v1:

learn.load(‘model-trained-with-size-64’)

learn.data = get_data(sz=128) # get_data is a little helper function to return an image DataBunch

learn.freeze()

learn.fit_one_cycle(3, lr, div_factor=40)

lrs = np.array([lr/9,lr/3,lr])

learn.unfreeze()

learn.fit_one_cycle(3, lrs, div_factor=40)

I’m asking because my model is currently training on size 128, but I noticed that the losses on the 3 epochs with frozen model (all but last layer) are higher than the losses with unfrozen model with size 64, but better than frozen model with size 64.