FINE-TUNING MAJOR MODEL PERFORMANCE

To achieve optimal efficacy from major language models, a multi-faceted approach is crucial. This involves thoroughly selecting the appropriate dataset for fine-tuning, parameterizing hyperparameters such as learning rate and batch size, and implementing advanced methods like transfer learning. Regular assessment of the model's output is essential