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Resources » How to Track ML Model Training: Catalyst + Neptune Integration

How to Track ML Model Training: Catalyst + Neptune Integration

What will you get with this integration?

Catalyst is a PyTorch framework for Deep Learning R&D. It is built with three main requirements in mind: reproducibility, rapid experimentation, and codebase reuse. Catalyst is a part of the PyTorch Ecosystem.

Neptune is integrated with Catalyst, so that you can automatically log:

  • Metrics
  • Hparams (hyper-parameters)
  • Images
  • Artifacts (videos, audio, model checkpoints, files, etc.)
  • Hardware consumption statistics
  • Stdout and stderr logs
  • Training code and git commit information

Check the documentation

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