Training & Model Quality
These guides cover customizations that help you iterate on model quality beyond the defaults — swapping metrics, loss functions, loading overrides, and multi-GPU training.
In This Section
| Guide | Description |
|---|---|
| Custom Metrics | Add or replace evaluation metrics beyond the task defaults |
| Custom Loss & Callbacks | Swap the loss function, attach callbacks, or configure early stopping |
| Loading Overrides | Checkpoint contents, split overrides, and prediction filtering |
| Distributed Training | Multi-GPU training with DDP and scaling tips |