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

(универсальный)

Ответ агента:

{ "worked": true, "confidence": 8, "verdict": "The shared adaptive recurrence significantly improved sequence forecasting test MSE on the fixed benchmark. Across 8 paired seeds it won on every seed, with mean MSE 0.2057 versus 0.3809 for the swept transformer baseline, delta -0.1752 and permutation p=0.0081. Trained-model measurements also confirmed early halting, averaging 1.328 microsteps out of Tmax 6.", "metrics": { "baseline": "MSE=0.3809081800 +/- 0.0454098553; best lr=0.001; epochs=18", "idea": "MSE=0.2057067603 +/- 0.0273858546; best lr=0.003; epochs=18; delta=-0.1752014197; p=0.0081; 8/8 wins; average microsteps=1.3281/6" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py", "files": [ "stage2_bench.py", "bench_report.json" ], "limitations": "Only the structurally matched sequence track was tested, using 400 training and 200 test examples for 18 epochs. Wall-clock time, FLOPs, parameter counts, and the tabular, vision, and dynamics tracks were not evaluated. The recurrence uses a Python loop, so runtime overhead was not measured.", "bench_report": { "bench_version": 1, "track": "sequence", "model": "transformer_tiny", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.001, "epochs": 18 }, "sweep": [ { "cfg": { "lr": 0.001, "epochs": 18 }, "mean": 0.3537886143 }, { "cfg": { "lr": 0.003, "epochs": 18 }, "mean": 0.4045680016 }, { "cfg": { "lr": 0.006, "epochs": 18 }, "mean": 0.5203984454 } ], "full": { "mean": 0.38090818, "std": 0.0454098553, "per_seed": [ 0.359444052, 0.3010879457, 0.334623158, 0.4199993014, 0.390874058, 0.4092178345, 0.4522660971, 0.3797529936 ], "n": 8 } }, "idea": { "mean": 0.2057067603, "std": 0.0273858546, "per_seed": [ 0.2458856255, 0.1633063853, 0.2141826302, 0.2025055885, 0.1764249057, 0.1968657672, 0.2450948358, 0.2013883442 ], "n": 8 }, "comparison": { "delta_mean": -0.1752014197, "idea_wins": 8, "n_pairs": 8, "p_value": 0.0081, "verdict": "idea better (significant)", "system_worked": true }, "sweep_parity": { "union_grid": [ { "lr": 0.001, "epochs": 18 }, { "lr": 0.003, "epochs": 18 }, { "lr": 0.006, "epochs": 18 } ], "idea_sweep": [ { "cfg": { "lr": 0.001, "epochs": 18 }, "mean": 0.240009889 }, { "cfg": { "lr": 0.003, "epochs": 18 }, "mean": 0.2064700574 }, { "cfg": { "lr": 0.006, "epochs": 18 }, "mean": 0.2101024874 } ] }, "mechanism_signature": { "claim": "trained adaptive recurrence uses fewer than Tmax microsteps on average", "predicted_avg_steps_upper_bound": 6.0, "observed_avg_steps": 1.3281249851, "relative_reduction": 0.7786458358, "confirmed": true } }, "system_verdict": "worked", "practical_verdict": "helps", "mechanism_ok": 1, "system_judged": true }