Imagine you have a smart, multi-purpose robot that has been trained to be a jack-of-all-trades. The robot knows a little about a lot of things, but the extent

Imagine you have a smart, multi-purpose robot that has been trained to be a jack-of-all-trades. The robot knows a little about a lot of things, but the extent of its knowledge about any specific thing is generally limited. Fine-tuning (or just tuning) basically equates to some extra training to become better at some specific task. In a very basic sense, fine-tuning a model with additional data about some task just trains the model to know more about that specific task. For example, you might buy a general-purpose cleaning robot for the home which can do a lot of different cleaning chores, but if you have special china plates that need to be cleaned in a certain way, you would want to train your robot a little more than its factory defaults. That extra training is "fine-tuning".