What Is Fine-Tuning in AI?

Adjusting a pre-trained model to perform better on specific tasks or datasets.

More about Fine-Tuning:

Fine-tuning is the process of making small adjustments to a pre-trained model to improve its accuracy on a particular set of data or tasks. This is often done by continuing the training process with a smaller, more specific dataset, allowing the model to better adapt to the nuances of the new information.

Frequently Asked Questions

Why is fine-tuning important in AI?

Fine-tuning is crucial because it helps to adapt a general-purpose model to perform better on tasks specific to certain industries or data types.

How is fine-tuning different from training a model from scratch?

Fine-tuning starts with a model that has already learned general features from a large dataset, whereas training from scratch involves building a model's knowledge base from the ground up.