Training¶
From the previous tutorials, you may now have a custom model and data loader.
MedSegPy supports the Adam optimizer both with and without gradient accumulation. You are free to create your own optimizer, and write the training logic.
We also provide a “trainer” abstraction with
DefaultTrainer
that helps simplify the standard types of training.
Logging of Metrics¶
By default the training/validation losses and learning rate are logged to Tensorboard. Other logging coming soon!