Neptune is a lightweight experiment tracker that offers a single place to track, compare, store, and collaborate on experiments and models.
This integration lets you use Neptune as a UI for the experiments you track in Sacred.
- Log, organize, visualize, and compare ML experiments in a single place
- Monitor model training live
- Version and query production-ready models and associated metadata (e.g., datasets)
- Collaborate with the team and across the organization
- Hyperparameters
- Losses and metrics
- Training code (Python scripts or Jupyter notebooks) and Git information
- Dataset version
- Model configuration
- Other metadata
- Documentation
- Code example on GitHub
- Example dashboard in the Neptune app
- Run example in Google Colab
On the command line:
pip install neptune-sacred
In Python:
import neptune
# Start a run
run = neptune.init_run(
project = "common/sacred-integration",
api_token = neptune.ANONYMOUS_API_TOKEN,
)
# Create a Sacred experiment
experiment = Experiment("image_classification", interactive=True)
# Add NeptuneObserver and run the experiment
experiment.observers.append(NeptuneObserver(run=run))
experiment.run()
If you got stuck or simply want to talk to us, here are your options:
- Check our FAQ page
- You can submit bug reports, feature requests, or contributions directly to the repository.
- Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP),
- You can just shoot us an email at support@neptune.ai