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This page describes how to use the WandbLogger class in Meta AI’s MMF library to track your multimodal model training with W&B. Enabling WandbLogger lets you log training and validation metrics, system (GPU and CPU) metrics, model checkpoints, and configuration parameters, so you can monitor experiments and compare runs without adding custom logging code.

Features

The WandbLogger in MMF supports the following features:
  • Training and validation metrics
  • Learning rate over time
  • Model checkpoint saving to W&B Artifacts
  • GPU and CPU system metrics
  • Training configuration parameters

Configuration parameters

To turn on W&B logging and customize how runs are tracked, set the following options in your MMF configuration: