I've been taught in many cases you can indeed fine-tune the last (i.e. closest from the output) layer(s) of a network. Of course, it does not give as good resul

I've been taught in many cases you can indeed fine-tune the last (i.e. closest from the output) layer(s) of a network. Of course, it does not give as good results as fine-tuning the whole model, but it is obviously way less expensive in compute. i.e. you actually don't want your model to re-learn _everything_.