The goal of fine tuning I would like to ask what is the goal of fine-tuning a VGGNet on my dataset.
What does fine-tuning mean? Does it mean to change the weights or keep the weight values?
Fine tuning means changing the weights such that the VGGNet can perform the task you want in your dataset. The reason why fine-tuning is not called training (which is what you are doing) is because it implies that you already use a network that has been trained on a dataset. However, the concept is the same as training, but you just happen to it do with a convenient set of initial weights.