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Exploring metadata in the run view#

When you click on a run in the runs table, the run view opens.

Here, you can:

  • See all the metadata logged for the run.
  • Modify or trash the run.
  • Create and manage dashboards for your project.

Details view#

In the left pane, underneath the run ID and name, click Details to access the details view.

Here, you can see basic metadata about the run itself: time data, size, owner, and descriptive information.

You can also:

  • Copy the Neptune ID to your clipboard.
  • Edit the name, description, and tags of the run.

Dashboards#

In the left pane, you can switch between dashboards to see the run metadata displayed in different ways.

All metadata#

The metadata is presented in a folder-structure, with all namespaces and fields exactly as they were logged.

You can also see the three automatically generated namespaces:

Namespace Description
monitoring
  • Hardware consumption metrics, organized into subfolders per process
  • stderr and stdout streams
source_code
  • The code of the executed script
  • Git information
  • Jupyter Notebook snapshots
"sys" The system namespace, which contains basic metadata about the run (see Details view above)

See example in Neptune 

Charts#

This section visualizes all series of numerical values – like metrics and losses during training – as graphs.

You can filter the charts by typing a string into the Filter widgets input box.

See example in Neptune 

Images#

If image files or figure objects were logged for the run, they appear in this section.

You can download the images from here, or inspect the evolution of an image series in the gallery view.

See example in Neptune 

Monitoring#

This section visualizes system metrics and hardware consumption logged during your run.

See example in Neptune 

Source code#

This section displays source code information, including:

  • Code snapshot: The filename and code of the script that was executed.
  • Git: Git information, if you have Git initialized in your project directory.
  • Notebook snapshot: Jupyter Notebook checkpoints, if you have the neptune–notebooks extension set up.

See example in Neptune 

Artifacts#

This section displays any files that have been logged as artifacts, with the track_files() method.

Click on the files to view the artifact metadata, such as hash, size, and path.

See example in Neptune