FINE-TUNING MAJOR MODEL PERFORMANCE

To achieve optimal performance from major language models, a multifaceted approach is crucial. This involves meticulous input corpus selection and preparation, architecturally tailoring the model to the specific application, and employing robust benchmarking metrics. Furthermore, strategies such as regularization can mitigate model bias and enhanc