interface TrainingJobDetailsProperty

Language	Type name
.NET	`Amazon.CDK.AWS.Sagemaker.CfnModelCard.TrainingJobDetailsProperty`
Go	`github.com/aws/aws-cdk-go/awscdk/v2/awssagemaker#CfnModelCard_TrainingJobDetailsProperty`
Java	`software.amazon.awscdk.services.sagemaker.CfnModelCard.TrainingJobDetailsProperty`
Python	`aws_cdk.aws_sagemaker.CfnModelCard.TrainingJobDetailsProperty`
TypeScript	`aws-cdk-lib` » `aws_sagemaker` » `CfnModelCard` » `TrainingJobDetailsProperty`

The overview of a training job.

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_sagemaker as sagemaker } from 'aws-cdk-lib';
const trainingJobDetailsProperty: sagemaker.CfnModelCard.TrainingJobDetailsProperty = {
  hyperParameters: [{
    name: 'name',
    value: 'value',
  }],
  trainingArn: 'trainingArn',
  trainingDatasets: ['trainingDatasets'],
  trainingEnvironment: {
    containerImage: ['containerImage'],
  },
  trainingMetrics: [{
    name: 'name',
    value: 123,

    // the properties below are optional
    notes: 'notes',
  }],
  userProvidedHyperParameters: [{
    name: 'name',
    value: 'value',
  }],
  userProvidedTrainingMetrics: [{
    name: 'name',
    value: 123,

    // the properties below are optional
    notes: 'notes',
  }],
};

Properties

Name	Type	Description
hyperParameters?	`IResolvable` `\| (IResolvable` `\|` `TrainingHyperParameterProperty)[]`	The hyper parameters used in the training job.
trainingArn?	`string`	The SageMaker AI training job Amazon Resource Name (ARN).
trainingDatasets?	`string[]`	The location of the datasets used to train the model.
trainingEnvironment?	`IResolvable` `\|` `TrainingEnvironmentProperty`	The SageMaker AI training job image URI.
trainingMetrics?	`IResolvable` `\| (IResolvable` `\|` `TrainingMetricProperty)[]`	The SageMaker AI training job results.
userProvidedHyperParameters?	`IResolvable` `\| (IResolvable` `\|` `TrainingHyperParameterProperty)[]`	Additional hyper parameters that you've specified when training the model.
userProvidedTrainingMetrics?	`IResolvable` `\| (IResolvable` `\|` `TrainingMetricProperty)[]`	Custom training job results.