How to Track ML Model Training: Lightning + Integration

1 min
Parth Tiwary
4th April, 2022

In this video, we show how to keep track of your model-training metadata when using PyTorch Lightning. Parth Tiwary explains: 

  • How to use the Neptune-Lightning integration
  • How to log your Lightning training metadata to Neptune, 
  • How to analyze the data in the Neptune app, 
  • And more. 

Important: This video was created in November 2021. For the most up-to-date tutorials and examples, please refer to the Neptune-Lightning integration docs

If you want to try out the integration on your own, check this Neptune-Lightning Colab notebook or check this Neptune-Lightning GitHub repo is an ML metadata store primarily used for experiment tracking and model registry

We are 100% focused on ML metadata management, but we’re making sure that it’s easy to integrate Neptune with other components of the ML stack. 

Neptune is already integrated with 25+ tools and libraries, and the list is growing. You can check our roadmap to see what’s currently under development.  

Other useful resources

Watch the webinar Computer Vision Projects With PyTorch Lightning and Deep Dive.

See a Lightning example project in the Neptune app (no registration needed). 

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