EDGE OSDEFINITION
Fine-tuning is a technique used in AI whereby we take an already trained model and train it on a specific dataset to make it more effective for a particular purpose. This means that instead of starting from scratch, we can adapt the already learned knowledge of the model. Depending on the model and the purpose, you can do either full fine-tuning or parameter-efficient fine-tuning such as LoRA.
Importance
- It can adapt a model to a particular business or technical task.
- It helps the model become more effective on a specific domain.
- Can help ensure the output has the correct format.
- May improve the outcome of the model on a particular task if there is good training data available.
Examples
- Customer support models can be trained to provide answers within a certain domain.
- Improve classification and information extraction from documents.
- Easy to adapt various language models based on specific industry jargon.
- Adapt the model for a certain coding or technical support purpose.
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