We Raised $8M Series A to Continue Building Experiment Tracking and Model Registry That “Just Works”

Read more

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

How to Track ML Model Training: PyTorch + Neptune Integration

What will you learn?

You will learn how to use Neptune + PyTorch to help you keep track of your model training metadata.

With Neptune + PyTorch you can:

  • Log model configuration
  • Log hyperparameters
  • Log loss & metrics
  • Log training code and git information
  • Log images and the predictions
  • Log artifacts (i.e. model weights, dataset version)
  • Log 2-D/3-D tensors as images or 1-D tensors as metrics

Check the documentation

Couldn’t find the use case you were looking for?

Just get in touch and our ML team
will create a custom demo for you