FINE-TUNING MAJOR MODEL PERFORMANCE

To achieve optimal performance from major language models, a multi-faceted approach is crucial. This involves meticulously selecting the appropriate dataset for fine-tuning, parameterizing hyperparameters such as learning rate and batch size, and leveraging advanced strategies like prompt engineering. Regular evaluation of the model's output is ess