Fine Tuning - Cancel

Reference

Service:: Azure AI Services

API Version:: 2024-08-01-preview

Cancels the processing of the fine-tune job specified by the given fine-tune-id.

POST {endpoint}/openai/fine_tuning/jobs/{fine-tuning-job-id}/cancel?api-version=2024-08-01-preview

URI Parameters

Name	In	Required	Type	Description
endpoint	path	True	string url	Supported Cognitive Services endpoints (protocol and hostname, for example: https://aoairesource.openai.azure.com. Replace "aoairesource" with your Azure OpenAI account name).
fine-tuning-job-id	path	True	string	The identifier of the fine-tune job.
api-version	query	True	string	The requested API version.

Responses

Name	Type	Description
200 OK	FineTuningJob	The fine tune has been successfully canceled
Other Status Codes	ErrorResponse	An error occurred.

Security

api-key

API key authentication

Type: apiKey
In: header

OAuth2Auth

OAuth2 authentication

Type: oauth2
Flow: implicit
Authorization URL: https://login.microsoftonline.com/common/oauth2/v2.0/authorize

Scopes

Name	Description
https://cognitiveservices.azure.com/.default

Examples

Canceling a fine tuning job.

Sample request

HTTP

POST https://aoairesource.openai.azure.com/openai/fine_tuning/jobs/ft-72a2792ef7d24ba7b82c7fe4a37e379f/cancel?api-version=2024-08-01-preview

Sample response

Status code:: 200

{
  "hyperparameters": {
    "n_epochs": -1
  },
  "status": "cancelled",
  "model": "curie",
  "training_file": "file-181a1cbdcdcf4677ada87f63a0928099",
  "finished_at": 1646127311,
  "id": "ft-72a2792ef7d24ba7b82c7fe4a37e379f",
  "created_at": 1646126127,
  "object": "fine_tuning.job"
}

Definitions

Name	Description
Error	Error
ErrorCode	ErrorCode
ErrorResponse	ErrorResponse
FineTuningHyperParameters	FineTuningHyperParameters
FineTuningJob	FineTuningJob
FineTuningJobError	FineTuningJobError
FineTuningState	FineTuningState
InnerError	InnerError
InnerErrorCode	InnerErrorCode
TypeDiscriminator	TypeDiscriminator

Error

Name	Type	Description
code	ErrorCode	ErrorCode Error codes as defined in the Microsoft REST guidelines (https://github.com/microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses).
details	Error[]	The error details if available.
innererror	InnerError	InnerError Inner error as defined in the Microsoft REST guidelines (https://github.com/microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses).
message	string	The message of this error.
target	string	The location where the error happened if available.

ErrorCode

Name	Type	Description
conflict	string	The requested operation conflicts with the current resource state.
contentFilter	string	Image generation failed as a result of our safety system.
fileImportFailed	string	Import of file failed.
forbidden	string	The operation is forbidden for the current user/api key.
internalFailure	string	Internal error. Please retry.
invalidPayload	string	The request data is invalid for this operation.
itemDoesAlreadyExist	string	The item does already exist.
jsonlValidationFailed	string	Validation of jsonl data failed.
notFound	string	The resource is not found.
quotaExceeded	string	Quota exceeded.
serviceUnavailable	string	The service is currently not available.
tooManyRequests	string	Too many requests. Please retry later.
unauthorized	string	The current user/api key is not authorized for the operation.
unexpectedEntityState	string	The operation cannot be executed in the current resource's state.

ErrorResponse

Name	Type	Description
error	Error	Error Error content as defined in the Microsoft REST guidelines (https://github.com/microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses).

FineTuningHyperParameters

Name	Type	Description
batch_size	integer	The batch size to use for training. The batch size is the number of training examples used to train a single forward and backward pass. In general, we've found that larger batch sizes tend to work better for larger datasets. The default value as well as the maximum value for this property are specific to a base model.
learning_rate_multiplier	number	The learning rate multiplier to use for training. The fine-tuning learning rate is the original learning rate used for pre-training multiplied by this value. Larger learning rates tend to perform better with larger batch sizes. We recommend experimenting with values in the range 0.02 to 0.2 to see what produces the best results.
n_epochs	integer	The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.

FineTuningJob

Name	Type	Description
created_at	integer	A timestamp when this job or item was created (in unix epochs).
error	FineTuningJobError	FineTuningJobError For fine-tuning jobs that have failed, this will contain more information on the cause of the failure.
estimated_finish	integer	The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running.
fine_tuned_model	string	The identifier (model-id) of the resulting fine tuned model. This property is only populated for successfully completed fine-tune runs. Use this identifier to create a deployment for inferencing.
finished_at	integer	A timestamp when this job or item has finished successfully (in unix epochs).
hyperparameters	FineTuningHyperParameters	FineTuningHyperParameters The hyper parameter settings used in a fine tune job.
id	string	The identity of this item.
model	string	The identifier (model-id) of the base model used for the fine-tune.
object	TypeDiscriminator	TypeDiscriminator Defines the type of an object.
organisation_id	string	The organisation id of this fine tune job. Unused on Azure OpenAI; compatibility for OpenAI only.
result_files	string[]	The result file identities (file-id) containing training and evaluation metrics in csv format. The file is only available for successfully completed fine-tune runs.
seed	integer	The seed used for the finetuning job.
status	FineTuningState	FineTuningState The state of a finetunes object or fine tuning job.
suffix	string	The suffix used to identify the fine-tuned model. The suffix can contain up to 40 characters (a-z, A-Z, 0-9,- and _) that will be added to your fine-tuned model name.
trained_tokens	integer	The total number of billable tokens processed by this fine tuning job.
training_file	string	The file which is used for training.
validation_file	string	The file which is used to evaluate the fine tuned model during training.

FineTuningJobError

Name	Type	Description
code	string	The machine-readable error code..
message	string	The human-readable error message.
param	string	The parameter that was invalid, usually training_file or validation_file. This field will be null if the failure was not parameter-specific.

FineTuningState

Name	Type	Description
cancelled	string	The operation has been cancelled and is incomplete. It can be categorized as a terminal state.
created	string	The operation was created. This state is not returned by Azure OpenAI and exposed only for compatibility. It can be categorized as an inactive state.
failed	string	The operation has completed processing with a failure and cannot be further consumed. It can be categorized as a terminal state.
pending	string	The operation is not yet queued to be processed in the future. It can be categorized as an inactive state.
running	string	The operation has started to be processed. It can be categorized as an active state.
succeeded	string	The operation has successfully be processed and is ready for consumption. It can be categorized as a terminal state.

InnerError

Name	Type	Description
code	InnerErrorCode	InnerErrorCode Inner error codes as defined in the Microsoft REST guidelines (https://github.com/microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses).
innererror	InnerError	InnerError Inner error as defined in the Microsoft REST guidelines (https://github.com/microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses).

InnerErrorCode

Name	Type	Description
invalidPayload	string	The request data is invalid for this operation.

TypeDiscriminator

Name	Type	Description
file	string	This object represents a file.
fine_tuning.job	string	This object represents a fine tune job.
fine_tuning.job.checkpoint	string	This object represents a checkpoint of a fine tuning job.
fine_tuning.job.event	string	This object represents an event of a fine tuning job.
list	string	This object represents a list of other objects.
model	string	This object represents a model (can be a base model or fine tune job result).
upload	string	This object represents a file upload.
upload.part	string	This object represents part of a file upload.

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