Coupled multilevel gradients for Markov-stream training / artifacts/bench_report.json
Mechanism confirmed, baseline not beaten
1{
2 "bench_version": 1,
3 "track": "markov_stream_regression",
4 "model": "mlp_tiny",
5 "metric_direction": "lower is better",
6 "n_seeds": 8,
7 "baseline": {
8 "best_cfg": {
9 "lr": 0.006
10 },
11 "sweep": [
12 {
13 "cfg": {
14 "lr": 0.001
15 },
16 "mean": 2.7850674092769623
17 },
18 {
19 "cfg": {
20 "lr": 0.003
21 },
22 "mean": 0.9566748812794685
23 },
24 {
25 "cfg": {
26 "lr": 0.006
27 },
28 "mean": 0.6123837828636169
29 }
30 ],
31 "full": {
32 "mean": 0.6354323998093605,
33 "std": 0.333473278949733,
34 "per_seed": [
35 0.36419546604156494,
36 0.2755792737007141,
37 1.0398473739624023,
38 0.7699130177497864,
39 0.5838971138000488,
40 0.3222571909427643,
41 0.47670307755470276,
42 1.2510666847229004
43 ],
44 "n": 8
45 }
46 },
47 "idea": {
48 "mean": 1.956806443631649,
49 "std": 0.615567636769626,
50 "per_seed": [
51 1.6518237590789795,
52 0.9949750304222107,
53 2.369184970855713,
54 1.7660677433013916,
55 3.053445816040039,
56 1.3799846172332764,
57 2.4778213500976562,
58 1.9611482620239258
59 ],
60 "n": 8,
61 "sweep": [
62 {
63 "cfg": {
64 "lr": 0.001
65 },
66 "mean": 4.620329976081848,
67 "std": 1.0518765869021856
68 },
69 {
70 "cfg": {
71 "lr": 0.003
72 },
73 "mean": 3.1034981161355972,
74 "std": 1.2009995397914373
75 },
76 {
77 "cfg": {
78 "lr": 0.006
79 },
80 "mean": 1.956806443631649,
81 "std": 0.615567636769626
82 }
83 ]
84 },
85 "comparison": {
86 "delta_mean": 1.3213740438222885,
87 "idea_wins": 0,
88 "n_pairs": 8,
89 "per_seed_diffs": [
90 1.2876282930374146,
91 0.7193957567214966,
92 1.3293375968933105,
93 0.9961547255516052,
94 2.4695487022399902,
95 1.057727426290512,
96 2.0011182725429535,
97 0.7100815773010254
98 ],
99 "p_value": 0.0081,
100 "mde": 0.5186169124394706,
101 "mde_rel_pct": 81.61637848417293,
102 "verdict": "idea worse (significant)",
103 "system_worked": false
104 },
105 "mechanism_signature": {
106 "prediction": "shared fine-minus-coarse corrections have smaller norm than raw fine gradients under correlated streams",
107 "observed_correction_norm_mean": 4.148377245852362,
108 "observed_mean_gradient_norm": 7.382436275482178,
109 "observed_gradient_lag1_mean": 0.08052120597292914,
110 "observed_clip_fraction_mean": 0.4244791666666667,
111 "confirmed": true
112 },
113 "custom_track": {
114 "name": "markov_stream_regression",
115 "file": "markov_stream_bench.py",
116 "domain": "optimizer"
117 }
118}