I believe that is an iterative process when doing transfer learning. First you will always freeze the top layers because low level feature extraction is done over there (extracting lines and contours). Unfreeze the last layers and try to train those layers only where high level features are extracted. At the same time it also depends on how different the new dataset is using which you are training the model. If it contains similar characteristics/features freezing top layers would be my choice