I am currently fine tuning VGG16 network to do a binary classification task. I have to admit that the training and testing samples are relatively small (around ~60 for training and ~15 for testing). I have tried data augmentation techniques from keras modules (imagedatagenerator).
When I feed these data into the VGG16 network (~5 epochs), the network's training accuracy and validation accuracy both fluctuates as the figure below. Attached with figures showing the accuracies and losses.
May I know what does this phenomenon indicate? Many thanks!