In the tutorial two approaches are shown.
The first part shows how to fine tune the whole model, while the second one uses the pre-trained model as a fixed feature extractor and only trains the new classifier (linear layer).
Well, I wouldn’t see it as not doing a good job. The tutorial is explaining all necessary steps using PyTorch to fine tune your model. The data, accuracy, etc. are not the main focus in my opinion.
Sure, using a small dataset and natural images, you would most likely want to just fine tune the classifier (case 1).