components finetune_common_validation - Azure/azureml-assets GitHub Wiki
Component to validate the finetune job against Validation Service
Version: 0.0.8
View in Studio: https://ml.azure.com/registries/azureml/components/finetune_common_validation/version/0.0.8
component input: mlflow model path
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
mlflow_model_path | MLflow model asset path. Special characters like \ and ' are invalid in the parameter value. | mlflow_model | True |
Data validation component input: training mltable
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
train_mltable_path | Path to the mltable of the training dataset. | mltable | False |
optional component input: validation mltable
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
validation_mltable_path | Path to the mltable of the validation dataset. | mltable | True |
component input: test mltable
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
test_mltable_path | Path to the mltable of the test dataset. | mltable | True | ||
user_column_names | Comma separated list of column names to be used for training. | string | True |
Compute validation
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
compute_preprocess | Compute to be used for preprocess eg. provide 'FT-Cluster' if your compute is named 'FT-Cluster'. Special characters like \ and ' are invalid in the parameter value. If compute cluster name is provided, instance_type field will be ignored and the respective cluster will be used. | string | True | ||
instance_type_preprocess | Instance type to be used for preprocess component in case of serverless compute, eg. standard_d12_v2. The parameter compute_preprocess must be set to 'serverless' for instance_type to be used | string | True | ||
compute_model_import | Compute to be used for model_import eg. provide 'FT-Cluster' if your compute is named 'FT-Cluster' | string | True | ||
instance_type_model_import | Instance type to be used for model_import component in case of serverless compute, eg. standard_d12_v2. The parameter compute_model_import must be set to 'serverless' for instance_type to be used | string | True | ||
compute_finetune | Compute to be used for finetuning eg. provide 'FT-Cluster' if your compute is named 'FT-Cluster'. Special characters like \ and ' are invalid in the parameter value. If compute cluster name is provided, instance_type field will be ignored and the respective cluster will be used | string | True | ||
instance_type_finetune | Instance type to be used for finetune component in case of serverless compute, eg. standard_nc24rs_v3. The parameter compute_finetune must be set to 'serverless' for instance_type to be used | string | True | ||
instance_count | Number of nodes to be used for finetuning (used for distributed training) | integer | 1 | True | |
process_count_per_instance | Number of gpus to be used per node for finetuning, should be equal to number of gpu per node in the compute SKU used for finetune | integer | 1 | True | |
compute_model_evaluation | Compute to be used for model evaluation eg. provide 'FT-Cluster' if your compute is named 'FT-Cluster' | string | True | ||
instance_type_model_evaluation | Instance type to be used for model_evaluation components in case of serverless compute, eg. standard_nc24rs_v3. The parameter compute_model_evaluation must be set to 'serverless' for instance_type to be used | string | True | ||
task_name | Which task the model is solving. | string | ['tabular-classification', 'tabular-classification-multilabel', 'tabular-regression', 'text-classification', 'text-classification-multilabel', 'text-named-entity-recognition', 'text-summarization', 'question-answering', 'text-translation', 'text-generation', 'fill-mask', 'image-classification', 'image-classification-multilabel', 'image-object-detection', 'image-instance-segmentation', 'video-multi-object-tracking'] |
ME validation
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
test_batch_size | Test batch size. | integer | 1 | True | |
label_column_name | Label column name in provided test dataset, for example "label". | string | label | True | |
device | string | auto | False | ['auto', 'cpu', 'gpu'] | |
evaluation_config | Additional parameters for Computing Metrics. | uri_file | True | ||
evaluation_config_params | Additional parameters as JSON serialized string. | string | True |
Task Speciffic params validation
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
task_specific_extra_params | All extra params. The values should be key values pairs separated by semi-colon. For example "param1=value1;param2=value2" | string | True |
Name | Description | Type |
---|---|---|
validation_info | Validation status. | uri_file |
azureml://registries/azureml/environments/acpt-pytorch-2.2-cuda12.1/labels/latest