The general logic should be the same for classification and segmentation use cases, so I would just stick to the Finetuning tutorial 611.
The main difference would be the output shape (pixel-wise classification in the segmentation use case) and the transformations (make sure to apply the same transformations on the input image and mask, e.g. crop).