What is the difference between fine-tuning and training an AI model?

What is the difference between fine-tuning and training an AI model?

Training an AI model involves building it from scratch using a large dataset, while fine-tuning adjusts a pre-trained model on a smaller, specific dataset.

Can you give me an example of when to use fine-tuning?

Sure! If you have a general language model and want it to perform well on medical texts, you would fine-tune it with a dataset of medical documents.

Is fine-tuning faster than training a model from scratch?

Yes, fine-tuning is generally faster because the model already has learned features from the initial training.

What are the risks of fine-tuning?

One risk is overfitting, where the model becomes too specialized to the fine-tuning dataset and loses generalization.

How do I choose the right dataset for fine-tuning?

Choose a dataset that closely matches the specific task or domain you want the model to excel in, ensuring it's high quality and relevant.