Implementation:Openai Openai python Fine Tuning Jobs Retrieve

Knowledge Sources	openai-python OpenAI Fine-tuning API
Domains	Fine_Tuning, Monitoring
Last Updated	2026-02-15 00:00 GMT

Overview

Concrete tool for monitoring fine-tuning jobs through retrieval, listing, and event log access provided by the OpenAI Python SDK.

Description

The Jobs resource provides retrieve() for single job status, list() for paginated job listing, and list_events() for training progress events. The FineTuningJob model tracks status, trained tokens, hyperparameters, and the output model name.

Usage

Call client.fine_tuning.jobs.retrieve(job_id) for status checks. Use list_events() to see training metrics.

Code Reference

Source Location

• Repository: openai-python
• File: src/openai/resources/fine_tuning/jobs/jobs.py

Signature

class Jobs(SyncAPIResource):
    def retrieve(
        self,
        fine_tuning_job_id: str,
    ) -> FineTuningJob:
        """Retrieves a fine-tuning job by ID."""

    def list(
        self,
        *,
        after: str | NotGiven = NOT_GIVEN,
        limit: int | NotGiven = NOT_GIVEN,
    ) -> SyncCursorPage[FineTuningJob]:
        """Lists fine-tuning jobs with pagination."""

    def list_events(
        self,
        fine_tuning_job_id: str,
        *,
        after: str | NotGiven = NOT_GIVEN,
        limit: int | NotGiven = NOT_GIVEN,
    ) -> SyncCursorPage[FineTuningJobEvent]:
        """Lists events for a fine-tuning job."""

Import

from openai import OpenAI
# client.fine_tuning.jobs.retrieve(), .list(), .list_events()

I/O Contract

Inputs

Name	Type	Required	Description
fine_tuning_job_id	str	Yes	Job ID to monitor
after	str	No	Pagination cursor
limit	int	No	Maximum results per page

Outputs

Name	Type	Description
job.status	str	validating_files, queued, running, succeeded, failed, cancelled
job.fine_tuned_model	str or None	Output model name (set when succeeded)
job.trained_tokens	int or None	Number of tokens trained
events	SyncCursorPage[FineTuningJobEvent]	Training events with messages

Usage Examples

Monitor Job Status

import time
from openai import OpenAI

client = OpenAI()

job_id = "ftjob-abc123"
while True:
    job = client.fine_tuning.jobs.retrieve(job_id)
    print(f"Status: {job.status}")

    if job.status == "succeeded":
        print(f"Fine-tuned model: {job.fine_tuned_model}")
        break
    elif job.status == "failed":
        print(f"Job failed: {job.error}")
        break

    time.sleep(30)

List Events

events = client.fine_tuning.jobs.list_events(
    fine_tuning_job_id="ftjob-abc123",
    limit=10,
)
for event in events:
    print(f"[{event.created_at}] {event.message}")

List All Jobs

jobs = client.fine_tuning.jobs.list(limit=10)
for job in jobs:
    print(f"{job.id}: {job.status} -> {job.fine_tuned_model}")

Related Pages

Implements Principle

• Principle:Openai_Openai_python_Fine_Tuning_Job_Monitoring

Requires Environment

• Environment:Openai_Openai_python_Python_3_9_Plus