FINE-TUNING MAJOR MODEL PERFORMANCE

To achieve optimal results from major language models, a multifaceted approach is crucial. This involves meticulous input corpus selection and preparation, functionally tailoring the model to the specific task, and employing robust benchmarking metrics. Furthermore, strategies such as regularization can mitigate model bias and enhance the model's