Jacobian-aligned infill for black-box neural tuning / results.json
Beats tuned baseline
1{
2 "verification": {
3 "jacobian_relative_error": 5.266567800411543e-11,
4 "residual_norm_before": 2.0485292742980916,
5 "residual_norm_after": 0.6315321671688156,
6 "residual_ratio": 0.3082856442875115,
7 "metric_condition": 26.702837459601692,
8 "metric_alignment_eigenvalue_check": true,
9 "sensitivity_eigenvalues": [
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11 0.9221812047789869,
12 6.328927519731584,
13 11.17474072426666
14 ],
15 "inverse_metric_eigenvalues": [
16 2.3895710977539495,
17 1.0843855793392183,
18 0.15800465353447607,
19 0.08948753484977386
20 ]
21 },
22 "benchmark": {
23 "seeds": 8,
24 "checkpoints": [
25 100,
26 200,
27 300,
28 400,
29 500
30 ],
31 "baseline_best_loss": [
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37 ],
38 "guided_best_loss": [
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40 5.722241795038344e-09,
41 2.2077024540568774e-18,
42 1.2503850908966123e-27,
43 2.9900062386611837e-32
44 ],
45 "final_baseline_mean": 2.31883481760068,
46 "final_guided_mean": 2.9900062386611837e-32,
47 "final_baseline_std": 0.6576922619886229,
48 "final_guided_std": 0.0
49 }
50}