Leveraging LLMs as an Augmentation to Traditional Hyperparameter Tuning
When seeking to improve machine learning model performance, hyperparameter tuning is often the go-to recommendation. However, this approach faces significant limitations, particularly for complex models requiring extensive training times. In this post, we’ll explore a novel approach that combines gradient norm analysis with Large Language Model (LLM) guidance to intelligently redesign neural network architectures. This […]