What is model fine tuning?

Model fine-tuning is a process where a pre-trained machine learning model (typically a large language model or image recognition model) is further trained on a smaller, task-specific dataset. This allows the model to adapt its existing knowledge to perform well on a specific task, such as sentiment analysis, text summarization, or image classification, without requiring training from scratch. It's commonly used to improve performance, reduce training time and resources, and leverage the capabilities of large pre-trained models for niche applications.