Crafting Your Own AI: A Comprehensive Journey into Training Language Models with Hugging Face Transformers — Part 3

Part 3: Navigating Model Architecture, Training Strategies, and Optimization

1. Introduction to Part 3

In Part 2, we established a robust data pipeline that can handle the high-volume data requirements of training large language models. Now, in Part 3, our focus shifts to the core aspects of model training. The choices you make regarding the model architecture, training strategies, and optimization techniques will directly influence both the efficiency and the performance of your final language model.

This section is designed to guide you through:

• Understanding the various transformer-based architectures and determining which one suits your project.
• Weighing the benefits of fine-tuning a pre-trained model versus training a model from scratch.
• Implementing training strategies that include fine-tuning protocols, curriculum learning, and progressive training.
• Optimizing your training process through hyperparameter tuning and advanced techniques like mixed precision training and distributed training.