Get an experiment

Example response

{
  "annotations": {
    "axisml.io/created-by": "li.wei"
  },
  "createdAt": "2026-06-20T08:00:00Z",
  "description": "Training experiment fine-tuning BERT on a Chinese corpus.",
  "displayName": "BERT fine-tuning experiment",
  "id": "d4f8a1b2-3c5e-4a7b-9c0d-1e2f3a4b5c6d",
  "labels": {
    "team": "nlp"
  },
  "name": "bert-finetune",
  "namespace": "team-nlp",
  "owner": "zhang.san",
  "ownerId": "3a2b1c0d-4e5f-6789-abcd-ef0123456789",
  "runSummary": {
    "active": 1,
    "count": 5,
    "latestPhase": "Succeeded",
    "latestRunAt": "2026-06-28T09:25:00Z",
    "recent": [
      "Succeeded",
      "Running",
      "Succeeded",
      "Failed",
      "Succeeded"
    ]
  },
  "spec": {
    "artifacts": [
      {
        "kind": "model",
        "name": "bert-base",
        "version": "2.1.0"
      }
    ],
    "backend": {
      "engine": "pytorchjob",
      "name": "kubeflow-trainer"
    },
    "poolName": "gpu-a100",
    "roles": [
      {
        "name": "worker",
        "replicas": 2,
        "restartPolicy": "OnFailure",
        "template": {
          "args": [
            "--lr",
            "0.001",
            "--epochs",
            "10",
            "--batch-size",
            "64"
          ],
          "command": [
            "python",
            "train.py"
          ],
          "env": [
            {
              "name": "WANDB_MODE",
              "value": "offline"
            }
          ],
          "image": "registry.axisml.io/training/bert:2.1.0",
          "resources": {
            "cpu": "8",
            "memory": "64Gi",
            "nvidia.com/gpu": "2"
          }
        }
      }
    ],
    "runPolicy": {
      "activeDeadlineSeconds": 86400,
      "backoffLimit": 2,
      "ttlSecondsAfterFinished": 3600
    },
    "unitName": "a100-2x"
  },
  "tenantName": "team-nlp",
  "updatedAt": "2026-06-28T09:30:00Z"
}