components evaluate_model

Evaluate Model

evaluate_model

Overview

Evaluate MLFlow models for supported task types.

Version: 0.0.19

Tags

type : evaluation sub_type : evaluate_model

View in Studio: https://ml.azure.com/registries/azureml/components/evaluate_model/version/0.0.19

Inputs

Name	Description	Type	Default	Optional	Enum
task	Task type	string	tabular-classification	False	['tabular-classification', 'tabular-classification-multilabel', 'tabular-regression', 'tabular-forecasting', 'text-classification', 'text-classification-multilabel', 'text-named-entity-recognition', 'text-summarization', 'question-answering', 'text-translation', 'fill-mask', 'text-generation', 'image-classification', 'image-classification-multilabel', 'chat-completion', 'image-object-detection', 'image-instance-segmentation']
test_data	Test Data as JSON Lines URI_FILE	uri_folder		False
evaluation_config	Additional parameters required for evaluation.	uri_file		True
test_data_label_column_name	Column name of target values	string		False
test_data_input_column_names	Comma separated values of feature column names	string		True
mlflow_model	Mlflow Model - registered model or output of a job with type mlflow_model in a pipeline	mlflow_model		False
device		string	auto	False	['auto', 'cpu', 'gpu']
batch_size		integer		True
evaluation_config_params	JSON Serialized string of evaluation_config	string		True

Outputs

Name	Description	Type
evaluation_result		uri_folder

Environment

azureml://registries/azureml/environments/model-evaluation/versions/16