Viewing model and deployment factsheets
View all of the details for a model or a deployment. Use the insights to determine whether a model or deployment is still performing well or needs updating.
Viewing lifecycle information from the Model inventory
From the Model inventory page, you can view lifecycle status for all of the registered assets. You can also view detailed factsheets for models or deployments that are registered to the model entry. For details on creating entries for models and deployments, see Managing an inventory of deployed assets.
Viewing a model entry
In the Model inventory, details are presented in layers. Click View details on a model entry to view the overview information.
Click the Asset tab to see all tracking information for a view of the model lifecycle. From this view, you can see whether a model was promoted to a space, what the status is, and whether the model is shared with collaborators. Associated assets that are deleted are listed with a (deleted) designation to maintain the asset history. You cannot open or view the deleted item. You can hide deleted assets by using the toggle to hide or show deleted assets.
You can change the status of a model entry, or click the name of a model in a project, space, or catalog to view the associated factsheet.
You can also view details on these tabs:
|Access||View and update user access to the model entry|
|Review||View and edit reviews for the model entry|
Managing access to a model entry
- Open a model entry and switch to the Access tab.
- Add or remove collaborators or edit access levels.
Viewing a model factsheet
The model factsheet displays all of the details for a machine learning model. This content is the same content that appears in the model details in the project, space, or catalog.
Note: For existing models, a factsheet is only created when changes are made. Even editing the description or adding a tag to the model will trigger the creation of a factsheet. If the facts are not captured for a deployment, then update the model description to create the factsheet.
The details in the factsheet depend on the type of model. For example, this model trained by using AutoAI displays:
General model details such as name, model ID, type of model and software specification used.
Training information including the associated project, training data source, and hybrid pipeline name.
Training metrics that show how columns are optimized to support the model.
Input and output schema that show the structure of the model.
Viewing a deployment factsheet
The deployment factsheet displays all of the detail for a deployment. The details in the factsheet depend on the type of deployment. For example, if a deployment is evaluated for fairness, sections display the results. In this sample, the factsheet shows the detail for an online deployment that is tested for bias. The details can include:
General deployment details, such as deployment name, deployment ID, and software specification used.
Evaluation details, such as the evaluation date, data used, and status.
- Quality metrics after evaluating the deployment.
- Fairness details to test for bias in monitored groups after evaluation.
- Drift details following an evaluation.
Parent topic: Managing an inventory of model assets.