List Job Metrics - Archetype AI Documentation

curl "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/your-job-id/metrics?kind=train&limit=20" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")

job_id = "your-job-id"

response = requests.get(
    f"https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/{job_id}/metrics",
    headers={"Authorization": f"Bearer {api_key}"},
    params={"kind": "train", "limit": 20}
)

print(response.json())

const jobId = 'your-job-id';
const params = new URLSearchParams({ kind: 'train', limit: '20' });

const response = await fetch(
  `https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/${jobId}/metrics?${params}`,
  {
    headers: {
      'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
    }
  }
);

const data = await response.json();
console.log(data);

{
  "object": "list",
  "data": [
    {
      "id": "your-metric-id",
      "created_at": 1765201323,
      "kind": "train",
      "step": 1000,
      "metrics": {
        "loss": 0.123,
        "learning_rate": 0.0001
      }
    }
  ],
  "has_more": false
}

{
  "code": "invalid_cursor",
  "message": "Invalid cursor",
  "suggestion": null,
  "error_uid": "err-xxxxxxxx"
}

{
  "code": "not_found",
  "message": "Not found",
  "suggestion": null,
  "error_uid": "err-xxxxxxxx"
}

GET

fine_tuning

jobs

{id}

metrics

curl "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/your-job-id/metrics?kind=train&limit=20" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")

job_id = "your-job-id"

response = requests.get(
    f"https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/{job_id}/metrics",
    headers={"Authorization": f"Bearer {api_key}"},
    params={"kind": "train", "limit": 20}
)

print(response.json())

const jobId = 'your-job-id';
const params = new URLSearchParams({ kind: 'train', limit: '20' });

const response = await fetch(
  `https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/${jobId}/metrics?${params}`,
  {
    headers: {
      'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
    }
  }
);

const data = await response.json();
console.log(data);

{
  "object": "list",
  "data": [
    {
      "id": "your-metric-id",
      "created_at": 1765201323,
      "kind": "train",
      "step": 1000,
      "metrics": {
        "loss": 0.123,
        "learning_rate": 0.0001
      }
    }
  ],
  "has_more": false
}

{
  "code": "invalid_cursor",
  "message": "Invalid cursor",
  "suggestion": null,
  "error_uid": "err-xxxxxxxx"
}

{
  "code": "not_found",
  "message": "Not found",
  "suggestion": null,
  "error_uid": "err-xxxxxxxx"
}

Requires version 1.1.5 or later of the Archetype platform.

Overview

Returns per-step training and evaluation metrics for the job (e.g. the loss curve). This list is cursor-paginated and is sorted newest-first. You can filter the list to a single series using the kind parameter.

Request

string

required

The fine-tuning job ID for whicch to return metrics. This is a TypeID-encoded identifier with the FineTuningJobId prefix.

kind

string

Filters the results to a single series: train (per-step), eval (held-out passes), or train_summary (end-of-run aggregate). Omit this parameter to return all metrics.

after

string

Forward cursor: return points older than the one with this ID. Mutually exclusive with before.

before

string

Backward cursor: return points newer than the one with this ID. Mutually exclusive with after.

limit

integer

The maximum number of points to return (1–100).

Response

Returns a page of metric datapoints.

object

string

The object type of a list response. Always list.

data

array

The training/evaluation metric datapoints. Each datapoint is represented by a FineTuningMetric record.

Show FineTuningMetric

A single fine-tuning metric.

string

required

A unique datapoint ID. Pass as the after cursor to page.

created_at

integer

required

The Unix timestamp (in seconds) at which the datapoint was created.

kind

string

required

The series this datapoint belongs to: train / eval / train_summary.

step

integer

required

The training step at which the datapoint was logged.

metrics

object

required

The metrics logged at this step (e.g. loss, learning_rate, eval_loss).

has_more

boolean

Whether or not more datapoints exist beyond this page.

curl "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/your-job-id/metrics?kind=train&limit=20" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")

job_id = "your-job-id"

response = requests.get(
    f"https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/{job_id}/metrics",
    headers={"Authorization": f"Bearer {api_key}"},
    params={"kind": "train", "limit": 20}
)

print(response.json())

const jobId = 'your-job-id';
const params = new URLSearchParams({ kind: 'train', limit: '20' });

const response = await fetch(
  `https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs/${jobId}/metrics?${params}`,
  {
    headers: {
      'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
    }
  }
);

const data = await response.json();
console.log(data);

{
  "object": "list",
  "data": [
    {
      "id": "your-metric-id",
      "created_at": 1765201323,
      "kind": "train",
      "step": 1000,
      "metrics": {
        "loss": 0.123,
        "learning_rate": 0.0001
      }
    }
  ],
  "has_more": false
}

{
  "code": "invalid_cursor",
  "message": "Invalid cursor",
  "suggestion": null,
  "error_uid": "err-xxxxxxxx"
}

{
  "code": "not_found",
  "message": "Not found",
  "suggestion": null,
  "error_uid": "err-xxxxxxxx"
}

List Job Logs List Checkpoint Options

⌘I

​Overview

​Request

​Response

Overview

Request

Response