Retrieve fine-tuning job details

Retrieves the details of a specific fine-tuning job.

For Windows CMD, replace ${DASHSCOPE_API_KEY} with %DASHSCOPE_API_KEY%. For PowerShell, use $env:DASHSCOPE_API_KEY.

curl --location --request GET "https://dashscope-intl.aliyuncs.com/api/v1/fine-tunes/<your-fine-tuning-job-id>" \
      --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
      --header 'Content-Type: application/json'

Request parameters

Parameter	Type	Location	Required	Description
job_id	String	URL Path	Yes	The ID of the fine-tuning job to retrieve. This ID is provided as `job_id` in the response parameters of the Create fine-tuning job API.

Response example

{
          "request_id": "c59b2145-a93c-4e00-b610-4d7cc5c521a2",
          "output": {
              "job_id": "ft-202410291653-1c7f",
              "job_name": "ft-202410291653-1c7f",
              "status": "SUCCEEDED",
              "finetuned_output": "qwen3-14b-suffix-ft-202410291653-1c7f",
              "model": "qwen3-14b",
              "base_model": "qwen3-14b",
              "training_file_ids": [
                  "976bd01a-f30b-4414-86fd-50c54486e3ef"
              ],
              "validation_file_ids": [
      
              ],
              "hyper_parameters": {
                  "n_epochs": 3,
                  "batch_size": 32,
                  "max_length": 8192,
                  "learning_rate": "1.6e-5",
                  "lr_scheduler_type": "linear",
                  "split": 0.9
              },
              "training_type": "sft",
              "create_time": "2024-10-29 16:53:53",
              "workspace_id":"llm-v71tlv***",
              "user_identity": "1396993924585947",
              "modifier": "1396993924585947",
              "creator": "1396993924585947",
              "end_time": "2024-10-29 17:11:26",
              "group": "llm",
              "usage": 279808
          }
      }

Response parameters

Parameter	Type	Description
request_id	String	The unique ID of the request.
output	Object	Details of the fine-tuning job.
output.job_id	String	The ID of the fine-tuning job, used to query its status. Generation rule: `ft-{yyyyMMddHHmm}-{4-digit UUID}`.
output.job_name	String	Same as `output.job_id`.
output.status	String	The current status of the fine-tuning job.
output.finetuned_output	String	The ID of the resulting fine-tuned model. This parameter is returned only when the job status is `SUCCEEDED`.
output.model	String	The model ID used for the fine-tuning job.
output.base_model	String	The ID of the base model that was fine-tuned. For example, the base model for the fine-tuning job `ft-202410291653-1c7f` is `qwen3-14b`.
output.training_file_ids	Array	A list of training file IDs.
output.validation_file_ids	Array	A list of validation file IDs.
output.hyper_parameters	Object	The hyperparameters that were explicitly specified for the job.
output.training_type	String	The fine-tuning method.
output.create_time	String	The time when the fine-tuning job was created.
output.workspace_id	String	The ID of the workspace to which the fine-tuning job belongs.
output.user_identity	String	The UID of the primary account that owns this fine-tuning job.
output.modifier	String	The UID of the account that last modified the fine-tuning job. For example, if a sub-account cancels the job, the UID of that sub-account is displayed here.
output.creator	String	The UID of the user who created the fine-tuning job.
output.end_time	String	The time when the fine-tuning job ended. This parameter is returned when the job status is `SUCCEEDED`, `FAILED`, or `CANCELED`.
output.group	String	The task type of the fine-tuning job.
output.usage	Integer	The number of tokens consumed by the fine-tuning job. For the billing formula, refer to billable items. This parameter is returned when the job status is `SUCCEEDED` or `CANCELED`.
output.output_cnt	Integer	The number of checkpoints generated by the current task. This is returned only for models that support multiple checkpoint outputs, such as `cosyvoice-v3-flash`. You can obtain a detailed list of checkpoints by using the List Checkpoints API.
output.max_output_cnt	Integer	The maximum number of checkpoints that can be produced in a single task. The portion of `output_cnt` that exceeds the upper limit is truncated based on tuning adequacy. Returned only for models that support multiple checkpoint outputs.

Error codes

If a request fails, the API returns the following information.

Parameter	Type	Description	Example
code	String	The error code.	NotFound
request_id	String	The unique ID of the request.	6332fb02-3111-43f0-bf79-f9e8c5ffa7f9
message	String	The error message.	Not Found!

Example error response

{
        "code": "NotFound",
        "request_id": "BE213CDD-8A5C-59EE-9A67-055EAB0CB59B",
        "message": "Not Found!"
      }

List of error codes

HTTP status code	Error code	Example message	Description	Solution
400	InvalidParameter	Missing training files	A parameter is missing, invalid, or in the wrong format.	Correct the parameters based on the error message.
400	UnsupportedOperation	The fine-tuning job cannot be deleted because its status is SUCCEEDED, FAILED, or CANCELED.	The operation cannot be performed on the resource in its current state.	Retry the operation when the resource enters an operational state.
404	NotFound	Not found!	The requested resource does not exist.	Check if the resource ID is correct.
409	Conflict	Model instance xxxxx already exists, please specify a suffix	A model instance named `xxxxx` already exists. You must specify a suffix to differentiate it.	Specify a unique suffix for the deployment.
429	Throttling	Too many fine-tuning jobs are running. Please retry later. A maximum of 20 running or succeeded fine-tuning jobs are allowed per user.	The request was denied due to platform limits.	Delete models that you no longer need.
500	InternalError	Internal server error!	An internal server error occurred.	Record the `request_id` and submit a ticket for troubleshooting by Alibaba Cloud engineers.