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

(универсальный)

Ответ агента:

{ "worked": true, "confidence": 7, "verdict": "Built a local tensorized concentration mixer for the structurally matching multi-token sequence forecast task and compared it against a dense transformer-style baseline using the shared train_model path, matched learning-rate union, and 8 paired seeds. The idea achieved lower test MSE on all 8 seeds: 0.19666 versus 0.28626, paired delta -0.08960 with permutation p=0.0081, so the bench verdict is idea better (significant). The trained factors had maximum singular value 0.5104, below the predicted bound 1.0; however, the residual block itself is not a contraction and no wall-clock/FLOP or peak-memory measurement was included.", "metrics": { "baseline": "Sequence test MSE: mean 0.2862644270, std 0.0536852991; best lr 0.001; per-seed [0.2573727667, 0.2441381812, 0.2655849457, 0.2142851949, 0.3280071318, 0.2741968632, 0.3978331685, 0.3086971641].", "idea": "Sequence test MSE: mean 0.1966622919, std 0.0332916755; best lr 0.003; all 8 paired wins; delta -0.0896021351; permutation p=0.0081; observed maximum factor singular value 0.5103706717." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_tensorized.py", "files": [ "bench_tensorized.py", "bench_report.json" ], "limitations": "The benchmark used the built-in sequence forecast track only. The local factorized model replaces the standard attention sublayer with a simpler learned symmetric mixer, so although embedding, positional parameters, depth, feed-forward width, head, optimizer, epochs, batch size, and learning-rate search were matched, exact parameter/FLOP parity was not audited. GPU memory, wall-clock speed, scaling with grid dimensions, dense-vs-factorized runtime, and generalization to image/video Cartesian grids were not measured; the mechanism signature was collected from one trained idea model (seed 0).", "bench_report": { "bench_version": 1, "track": "sequence", "model": "transformer_tiny", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.001 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.24534527212381363 }, { "cfg": { "lr": 0.003 }, "mean": 0.2803647518157959 }, { "cfg": { "lr": 0.009 }, "mean": 0.6309378072619438 } ], "full": { "mean": 0.28626442700624466, "std": 0.053685299079254345, "per_seed": [ 0.25737276673316956, 0.2441381812095642, 0.26558494567871094, 0.21428519487380981, 0.32800713181495667, 0.2741968631744385, 0.3978331685066223, 0.3086971640586853 ], "n": 8 } }, "idea": { "mean": 0.1966622918844223, "std": 0.03329167546581414, "per_seed": [ 0.20225295424461365, 0.15188682079315186, 0.2281547635793686, 0.16552338004112244, 0.2461298704147339, 0.15342377126216888, 0.20971401035785675, 0.21621276438236237 ], "n": 8, "best_cfg": { "lr": 0.003 }, "sweep": [ { "cfg": { "lr": 0.001 }, "mean": 0.18995187431573868, "per_seed": [ 0.21626117825508118, 0.1743844747543335, 0.21162375807762146, 0.15753808617591858 ] }, { "cfg": { "lr": 0.003 }, "mean": 0.18695447966456413, "per_seed": [ 0.20225295424461365, 0.15188682079315186, 0.2281547635793686, 0.16552338004112244 ] }, { "cfg": { "lr": 0.009 }, "mean": 0.22821211069822311, "per_seed": [ 0.2766028046607971, 0.2169913500547409, 0.23771323263645172, 0.1815410554409027 ] } ] }, "comparison": { "delta_mean": -0.08960213512182236, "idea_wins": 8, "n_pairs": 8, "per_seed_diffs": [ -0.05511981248855591, -0.09225136041641235, -0.037430182099342346, -0.04876181483268738, -0.08187726140022278, -0.12077309191226959, -0.18811915814876556, -0.09248439967632294 ], "p_value": 0.0081, "mde": 0.0403873113558637, "mde_rel_pct": 14.10839334046304, "verdict": "idea better (significant)", "system_worked": true }, "track_choice": "sequence: multi-token forecast windows directly exercise token mixing", "parameterization": "rank-16 orthonormal factors with sigmoid eigenvalues", "mechanism_signature": { "factor_largest_singular_values": [ 0.510370671749115, 0.5097700357437134 ], "predicted_factor_bound": 1.0, "observed_max_factor_singular": 0.510370671749115, "probe_norm_ratio_after_mixing": 1.812699844599067, "confirmed": true } }, "system_verdict": "worked", "practical_verdict": "helps", "mechanism_ok": 1, "system_judged": true }