Training Patterns

What problem does it solve?

This Skill provides expert patterns and best practices for efficient and robust model training using PyTorch Lightning and HuggingFace Transformers, preventing common pitfalls and accelerating development.

Core Features & Use Cases

• LightningModule Structure: Complete, well-structured PyTorch Lightning modules with logging and optimizer configuration.
• HuggingFace Trainer: Production-ready HuggingFace Trainer setups with custom metrics, learning rate schedules, and early stopping.
• LR Finding & Warmup: Techniques for discovering optimal learning rates and implementing effective warmup schedules.
• Gradient Monitoring & Clipping: Strategies for tracking gradient norms and preventing exploding gradients.
• Checkpointing & Resuming: Reliable methods for saving and resuming training from interruptions.
• Use Case: Quickly implement a robust training loop for a new NLP model using HuggingFace, ensuring proper checkpointing and early stopping based on validation AUC.

Quick Start

Use the training patterns skill to generate a PyTorch Lightning LightningModule for binary classification.