To achieve optimal results from large language models (LLMs), a multi-faceted approach is essential. Firstly, careful dataset selection and preparation are crucial to ensure the model learns robust representations. Secondly, configuration tuning through techniques like grid search can significantly optimize the model's ability to adapt on unseen da