I wonder if there is a typical path to follow when training a model. Is it always:
- create learner
- choose transfer model weights
- run lr_find
- train last layer
- run unfreeze
- train whole model
finished.
So the point if:
- Do I always have to run unfreeze and train the whole model to improve results?
- does it make sense to freeze again and to some more training on the last layer?
- Do I always run unfreeze without parameters or should I try to unfreeze different numbers of layers? (unfreeze(-1) train -> unfreeze(-2) trainer, etc.