train_job_status
Endpoint Documentation: /v1/train/jobs/{job_id}
Note
You can see these results by going to the train
tab at https://app.lamini.ai/train
Get the status of a training job.
Request
- HTTP Method:
GET
- Path:
https://api.lamini.ai/v1/train/jobs/{job_id}
- Headers:
Authorization: Bearer <LAMINI_API_KEY>
Content-Type: application/json
Parameters:
{job_id}
- The unique identifier of the training job to be cancelled.
Response
The response will contain the job id, job status, job start time, and model name.
Body (JSON):
job_id
: The job idstatus
: "CREATED" | "QUEUED" | "LOADING DATA" | "TRAINING MODEL" | "SAVING MODEL" | "EVALUATING MODEL" | "COMPLETED" | "PARTIALLY COMPLETED" | "CANCELED" | "FAILED"start_time
: Start time of the objectmodel_name
: The finetuned model name, available after model is saved
While Training
{"job_id":2514,"status":"TRAINING MODEL","start_time":"2023-08-09T19:42:46.857931","model_name":null,"custom_model_name":null}
When Completed
{"job_id":2514,"status":"COMPLETED","start_time":"2023-08-09T19:42:46.857931","model_name":"abcde","custom_model_name":""}
Request
curl --location --request GET 'https://api.lamini.ai/v1/train/jobs/$JOB_ID' \
--header 'Authorization: Bearer $LAMINI_API_KEY' \
--header 'Content-Type: application/json'
Response
{
"job_id": "123",
"status": "COMPLETED",
"start_time": "2023-08-11T03:16:38.899729",
"model_name": "abcde",
"custom_model_name": "",
"is_public": false,
"history": "[{\"loss\": 4.5333, \"learning_rate\": 1e-05, \"epoch\": 0.1, \"iter_time\": 0.0, \"flops\": 0.0, \"remaining_time\": 0.0, \"step\": 10}, ...]",
"resume_count": 0,
"dataset_id": null,
"resume_limit": 1000
}