# Стенд-проверка (stage-2) · промт оператора:

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "The Overshoot Budget Controller was implemented as a local Adam training intervention and evaluated on the structurally matched dynamics pendulum track with paired rnn_small systems. Its mechanism signature was confirmed, but the best task metric was not significantly better than baseline: delta_mean=-1.1293e-05, p=0.82275, with 3 of 8 paired wins.",
  "metrics": {
    "baseline": "Adam, best lr=0.03; 8-seed dynamics MSE mean=0.0001668608, std=0.0001211998.",
    "idea": "Overshoot-controlled Adam, best lr=0.03; 8-seed dynamics MSE mean=0.0001555682, std=0.0000718532; paired delta=-0.0000112926, p=0.82275, 3/8 wins.",
    "mechanism_signature": "Predicted cap mean=3.52561, observed accepted normalized step mean=2.74843, proposal cap fraction=0.30804, trained updates=672, confirmed=true."
  },
  "bench_report": {
    "bench_version": 1,
    "track": "dynamics",
    "model": "rnn_small",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.03
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.0013811723329126835
        },
        {
          "cfg": {
            "lr": 0.01
          },
          "mean": 0.00036846242801402695
        },
        {
          "cfg": {
            "lr": 0.03
          },
          "mean": 0.0001452554606657941
        }
      ],
      "full": {
        "mean": 0.00016686083745298674,
        "std": 0.0001211998237425883,
        "n": 8
      }
    },
    "idea": {
      "best_cfg": {
        "lr": 0.03
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.0015905930049484596
        },
        {
          "cfg": {
            "lr": 0.01
          },
          "mean": 0.00038149026113387663
        },
        {
          "cfg": {
            "lr": 0.03
          },
          "mean": 0.00015556820017081918
        }
      ],
      "mean": 0.00015556820017081918,
      "std": 7.18531745869552e-05,
      "n": 8
    },
    "comparison": {
      "delta_mean": -1.1292637282167561e-05,
      "idea_wins": 3,
      "n_pairs": 8,
      "p_value": 0.82275,
      "mde": 9.440018542032603e-05,
      "verdict": "no significant win",
      "system_worked": false
    },
    "mechanism_signature": {
      "predicted_cap_mean": 3.5256107662831653,
      "observed_accepted_eta_mean": 2.748427854677808,
      "proposal_cap_fraction": 0.3080357142857143,
      "observed_update_norm_mean": 1.5009487083821522,
      "n_trained_updates": 672,
      "confirmed": true
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_stage2.py",
  "files": [
    "bench_stage2.py",
    "bench_report.json",
    "bench_stdout.txt"
  ],
  "limitations": "Only the built-in dynamics track was tested. The controller used fixed L_REF=100 rather than Hessian-vector curvature estimation, and the benchmark covered one model, one optimizer family, three learning rates, and 12 epochs.",
  "system_verdict": "partial",
  "practical_verdict": "inconclusive",
  "mechanism_ok": 1,
  "system_judged": true
}