This article is divided into four parts; they are: • Optimizers for Training Language Models • Learning Rate Schedulers • Sequence Length Scheduling • Other Techniques to Help Training Deep Learning Models Adam has been the most popular optimizer for training deep learning models.
PyTorch provides a lot of building blocks for a deep learning model, but training loop is not part of them. It is a flexibility provided that you can do whatever you want during training, but some basic structure is universal across most use cases. In this post, you will see…
Last Updated on May 19, 2023 Large language models (LLMs) are recent advances in deep learning models to work on human languages. Some great use case of LLMs has been demonstrated. A large language model is a trained deep-learning model that understands and generates text in a human-like fashion. Behind…
In machine learning projects, achieving optimal model performance requires paying attention to various steps in the training process. But before focusing on the technical aspects of model training, it is important to define the problem, understand the context, and analyze the dataset in detail. Once you have a solid grasp…