Model Fine Tuning

The model is often fine-tuned on a specific task after pre-training. This involves continuing the training process on a smaller, task-specific dataset. This allows the model to adapt its learned knowledge to the specific task (e.g. text translation) or specialised domain (e.g. biomedical, finance, etc), improving its performance.

This is a brief explanation, but the actual process can be much more complex, especially for state-of-the-art models like GPT-4. These models use advanced techniques and large amounts of data to achieve impressive results.