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Model Evaluations - Get

  • Reference
Service:
Azure AI Services
API Version:
2023-04-01-preview

Get information about a specific model evaluation.

Status codes returned:

  • 200: Operation completed successfully.
  • 400: The request was malformed.
  • 404: A model evaluation with the specified name was not found.
GET /models/{name}/evaluations/{evaluationName}?api-version=2023-04-01-preview

URI Parameters

Name In Required Type Description
evaluationName
 path True

string

The name of the model evaluation to get.

Regex pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$
name
 path True

string

The name of the model to get the evaluation for.

Regex pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$
api-version
 query True

string

Requested API version.

Responses

Name Type Description
200 OK

ModelEvaluation

Success
Other Status Codes

ErrorResponse

Error

Headers

x-ms-error-code: string

Examples

ModelEvaluations_Get

Sample request

GET /models/my_model_name/evaluations/my_evaluation_name?api-version=2023-04-01-preview

Sample response

Status code:
200 
{
  "name": "my_evaluation_name",
  "modelName": "my_model_name",
  "createdDateTime": "2023-01-13T20:46:22.127Z",
  "updatedDateTime": "2023-01-13T20:46:22.127Z",
  "status": "notStarted",
  "evaluationParameters": {
    "testDatasetName": "my_test_dataset_name"
  }
}

Definitions

Name Description
ErrorResponse

Response returned when an error occurs.
ErrorResponseDetails

Error info.
ErrorResponseInnerError

Detailed error.
ModelEvaluation

Describes an evaluation run for evaluating the accuracy of a model using a test set.
ModelEvaluationParameters

Parameters for specifying how a model is evaluated.
ModelEvaluationState

Read only. The current state of the evaluation run.
ModelPerformance

Performance metrics for a custom trained model.
ModelTagPerformance

Performance metrics for each tag recognized by a custom trained model.

ErrorResponse

Response returned when an error occurs.

Name Type Description
error

ErrorResponseDetails

Error info.

ErrorResponseDetails

Error info.

Name Type Description
code

string

Error code.
details

ErrorResponseDetails[]

List of detailed errors.
innererror

ErrorResponseInnerError

Detailed error.
message

string

Error message.
target

string

Target of the error.

ErrorResponseInnerError

Detailed error.

Name Type Description
code

string

Error code.
innererror

ErrorResponseInnerError

Detailed error.
message

string

Error message.

ModelEvaluation

Describes an evaluation run for evaluating the accuracy of a model using a test set.

Name Type Description
createdDateTime

string

Read only. The date and time when the evaluation run was first created, in UTC.
error

ErrorResponseDetails

Error info.
evaluationParameters

ModelEvaluationParameters

Parameters for specifying how a model is evaluated.
modelName

string

Read only. The model to evaluate.
modelPerformance

ModelPerformance

Performance metrics for a custom trained model.
name

string

Read only. The name that is used to uniquely identify the evaluation run.
status

ModelEvaluationState

Read only. The current state of the evaluation run.
updatedDateTime

string

Read only. The date and time when the evaluation run was last updated, in UTC.

ModelEvaluationParameters

Parameters for specifying how a model is evaluated.

Name Type Description
testDatasetName

string

The dataset name used for testing.

ModelEvaluationState

Read only. The current state of the evaluation run.

Name Type Description
failed

string

notStarted

string

running

string

succeeded

string

ModelPerformance

Performance metrics for a custom trained model.

Name Type Description
accuracyTop1

number

Read only. For multiclass classification models. The proportion of test samples where the ground truth class matches the predicted class.
accuracyTop5

number

Read only. For multiclass classification models. The proportion of test samples where the ground truth class is in the top five predicted classes.
averagePrecision

number

Read only. A measure of the model performance, it summarizes the precision and recall at different confidence thresholds.
calibrationECE

number

Read only. For multiclass classification models. Expected calibration error.
meanAveragePrecision30

number

Read only. For object detection models. Mean average precision at a threshold of 30%.
meanAveragePrecision50

number

Read only. For object detection models. Mean average precision at a threshold of 50%.
meanAveragePrecision75

number

Read only. For object detection models. Mean average precision at a threshold of 75%.
tagPerformance

<string,  ModelTagPerformance>

Read only. Performance metrics for each tag recognized by the model.

ModelTagPerformance

Performance metrics for each tag recognized by a custom trained model.

Name Type Description
accuracy

number

Read only. For multiclass models. Tag accuracy.
averagePrecision50

number

Read only. For object detection models. Average precision at a threshold of 50%.