deep learning for computer vision figure training and validat ion accuracy for feat ure extraction wit data augment ation figure training and validat ion loss for feat ure ext ract ion wit dat augment ation fine-tuning another widely used technique for model reusecomplementary to feature extractionis fine-tuning (see figure fine-tuning consists of unfreezing few of the top layers of frozen model base used for feature extractionand jointly training both the newly added part of the model (in this casethe fully connected classifierand these top layers this is called fine-tuning because it slightly adjusts the more abstract representations of the model being reusedin order to make them more relevant for the problem at hand licensed to