Example Concept: Fine-tuning a pre-trained transformer model involves taking an existing model trained on a large dataset and further training it on a smaller, task-specific dataset. This process adjusts the model's weights slightly to improve performance on the new task without losing the general knowledge it has learned. Fine-tuning typically involves freezing some layers of the model to retain general features and only updating the final layers to adapt to the new task.