What is fine-tuning?

Fine-tuning is a transfer learning technique in machine learning where a pre-trained model (trained on a large dataset) is further trained on a smaller, task-specific dataset. This allows the model to adapt its pre-existing knowledge to the new task, often resulting in improved performance compared to training a model from scratch. It's commonly used in natural language processing, computer vision, and other areas where large pre-trained models are available.