Why do we need to unfreeze the learner everytime before retarining even if learn.fit_one_cycle() works fine without learn.unfreeze()

[Daniel (深度碎片)]

@PoonamV

5. training model

learn.fit_one_cycle(2, max_lr=slice(1e-6,1e-4))

Make sure to use discriminative learning rates here(parameter max_lr), which maintains a low learning rate for initial layers as they need lesser tuning and gradually increase learning rate for later layers which need higher tuning especially fully connected ones.

a) use lr_find() before fit_one_cycle() to get best suited learning rate for underlying data.

@PoonamV Thanks for this nice summary post.

This quotation is a nice explanation for questions like the following.

Why and when to use max_lr?