The Mechanics of Training LLMs
Here, we will guide you through the intricate process of training LLMs, starting with the crucial task of data preparation and management. This process is fundamental to getting LLMs to perform in a desired way. We will further explore the establishment of a robust training environment, delving into the science of hyperparameter tuning and elaborating on how to address overfitting, underfitting, and other common training challenges, giving you a thorough grounding in creating effective LLMs.
In this chapter, we’re going to cover the following main topics:
- Data – preparing the fuel for LLMs
- Setting up your training environment
- Hyperparameter tuning – finding the sweet spot
- Challenges in training LLMs – overfitting, underfitting, and more
By the end of this chapter, you should understand the roadmap for training LLMs, emphasizing the pivotal role of comprehensive data preparation and management.
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