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.

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.

string

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

string

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

integer

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

Response

Returns a page of metric datapoints.

string

The object type of a list response. Always list.

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.

integer

required

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

string

required

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

integer

required

The training step at which the datapoint was logged.

object

required

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

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"
}

⌘I

​Overview

​Request

​Response

Overview

Request

Response