Training Callbacks And Monitoring For Model Development

via “callback-based extensibility for training customization”

Real-time object detection, segmentation, and pose.

Unique: Implements a callback system that enables custom logic injection at training lifecycle events without modifying core Trainer code, with built-in callbacks for logging, early stopping, and platform integration (HUB, W&B, MLflow)

vs others: More flexible than fixed training loops because callbacks enable arbitrary customization, and more maintainable than subclassing Trainer because callbacks are composable and don't require forking the codebase