View the Details of a Model Version - Amazon SageMaker

View the Details of a Model Version

You can view details of a specific model version by using either the AWS SDK for Python (Boto3) or the Amazon SageMaker Studio console.

View the Details of a Model Version (Boto3)

To view the details of a model version by using Boto3, complete the following steps.

  1. Call the list_model_packages API operation to view the model versions in a Model Group.

    sm_client.list_model_packages(ModelPackageGroupName="ModelGroup1")

    The response is a list of model package summaries. You can get the Amazon Resource Name (ARN) of the model versions from this list.

    {'ModelPackageSummaryList': [{'ModelPackageGroupName': 'AbaloneMPG-16039329888329896', 'ModelPackageVersion': 1, 'ModelPackageArn': 'arn:aws:sagemaker:us-east-2:123456789012:model-package/ModelGroup1/1', 'ModelPackageDescription': 'TestMe', 'CreationTime': datetime.datetime(2020, 10, 29, 1, 27, 46, 46000, tzinfo=tzlocal()), 'ModelPackageStatus': 'Completed', 'ModelApprovalStatus': 'Approved'}], 'ResponseMetadata': {'RequestId': '12345678-abcd-1234-abcd-aabbccddeeff', 'HTTPStatusCode': 200, 'HTTPHeaders': {'x-amzn-requestid': '12345678-abcd-1234-abcd-aabbccddeeff', 'content-type': 'application/x-amz-json-1.1', 'content-length': '349', 'date': 'Mon, 23 Nov 2020 04:56:50 GMT'}, 'RetryAttempts': 0}}
  2. Call describe_model_package to see the details of the model version. You pass in the ARN of a model version that you got in the output of the call to list_model_packages.

    sm_client.describe_model_package(ModelPackageName="arn:aws:sagemaker:us-east-2:123456789012:model-package/ModelGroup1/1")

    The output of this call is a JSON object with the model version details.

    {'ModelPackageGroupName': 'ModelGroup1', 'ModelPackageVersion': 1, 'ModelPackageArn': 'arn:aws:sagemaker:us-east-2:123456789012:model-package/ModelGroup/1', 'ModelPackageDescription': 'Test Model', 'CreationTime': datetime.datetime(2020, 10, 29, 1, 27, 46, 46000, tzinfo=tzlocal()), 'InferenceSpecification': {'Containers': [{'Image': '257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:1.0-1-cpu-py3', 'ImageDigest': 'sha256:99fa602cff19aee33297a5926f8497ca7bcd2a391b7d600300204eef803bca66', 'ModelDataUrl': 's3://sagemaker-us-east-2-123456789012/ModelGroup1/pipelines-0gdonccek7o9-AbaloneTrain-stmiylhtIR/output/model.tar.gz'}], 'SupportedTransformInstanceTypes': ['ml.m5.xlarge'], 'SupportedRealtimeInferenceInstanceTypes': ['ml.t2.medium', 'ml.m5.xlarge'], 'SupportedContentTypes': ['text/csv'], 'SupportedResponseMIMETypes': ['text/csv']}, 'ModelPackageStatus': 'Completed', 'ModelPackageStatusDetails': {'ValidationStatuses': [], 'ImageScanStatuses': []}, 'CertifyForMarketplace': False, 'ModelApprovalStatus': 'PendingManualApproval', 'LastModifiedTime': datetime.datetime(2020, 10, 29, 1, 28, 0, 438000, tzinfo=tzlocal()), 'ResponseMetadata': {'RequestId': '12345678-abcd-1234-abcd-aabbccddeeff', 'HTTPStatusCode': 200, 'HTTPHeaders': {'x-amzn-requestid': '212345678-abcd-1234-abcd-aabbccddeeff', 'content-type': 'application/x-amz-json-1.1', 'content-length': '1038', 'date': 'Mon, 23 Nov 2020 04:59:38 GMT'}, 'RetryAttempts': 0}}

View the Details of a Model Version (console)

To view the details of a model version in the Amazon SageMaker Studio console, complete the following steps based on whether you use Studio or Studio Classic.

Studio
  1. Open the SageMaker Studio console by following the instructions in Launch Amazon SageMaker Studio.

  2. In the left navigation pane, choose Models from the menu.

  3. Choose the Registered models tab, if not selected already.

  4. Immediately below the Registered models tab label, choose Model Groups, if not selected already.

  5. Select the name of the model group containing the model version to view.

  6. In the list of model versions, select the model version to view.

  7. To view details related to model training, choose the Training radio button. To view details related to inference, choose the Inference radio button.

    The following tabs include the details related to model training:
    • Performance: Statistical measurements to assess model performance, such as relative mean error (RME).

    • Evaluation: Charts and metrics to describe bias and explainability.

    • Associations: The resources that derived, are derived from, or are associated with the model version.

    • Activity: The actions you performed with the model version, such as approval.

    • Tags: The tags that belong to the model version.

    • Metadata: The ARN information for model version and associated Identity and Access Management (IAM) roles.

    The following tabs include details related to model inference:
    • Instances: The instances on which your model is deployed.

    • Metadata: The containers running inference with your model.

Studio Classic
  1. Sign in to Amazon SageMaker Studio Classic. For more information, see Launch Amazon SageMaker Studio Classic.

  2. In the left navigation pane, choose the Home icon ( ).

  3. Choose Models, and then Model registry.

  4. From the model groups list, select the name of the Model Group you want to view.

  5. A new tab appears with a list of the model versions in the Model Group.

  6. In the list of model versions, select the name of the model version for which you want to view details.

  7. On the model version tab that opens, choose one of the following to see details about the model version:

    • Activity: Shows events for the model version, such as approval status updates.

    • Model quality: Reports metrics related to your Model Monitor model quality checks, which compare model predictions to Ground Truth. For more information about Model Monitor model quality checks, see Monitor model quality.

    • Explainability: Reports metrics related to your Model Monitor feature attribution checks, which compare the relative rankings of your features in training data versus live data. For more information about Model Monitor explainability checks, see Monitor Feature Attribution Drift for Models in Production.

    • Bias: Reports metrics related to your Model Monitor bias drift checks, which compare the distribution of live data to training data. For more information about Model Monitor bias drift checks, see Monitor Bias Drift for Models in Production.

    • Inference recommender: Provides initial instance recommendations for optimal performance based on your model and sample payloads.

    • Load test: Runs load tests across your choice of instance types when you provide your specific production requirements, such as latency and throughput constraints.

    • Inference specification: Displays instance types for your real-time inference and transform jobs, and information about your Amazon ECR containers.

    • Information: Shows information such as the project with which the model version is associated, the pipeline that generated the model, the Model Group, and the model's location in Amazon S3.