1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
|
{
"schema": "rain_ep_structured_bias_screen_v1",
"author": {
"repository": "https://github.com/rain-neuromorphics/energy-based-learning",
"revision": "6b253fd8a5d267535f58ab79992256ef10031ceb"
},
"protocol": {
"dataset": "FashionMNIST",
"network": "author ConvHopfieldEnergy28 32-64-10",
"algorithm": "positive equilibrium propagation",
"mode": "constant",
"bias_ratio": 0.1,
"predictor_rate": 0.5,
"neutral_cadence": 0,
"calibration_batches": 1000,
"calibration_observations": 1000,
"calibration_seconds": 62.76313781738281,
"epochs": 1,
"train_limit": 10000,
"test_limit": 2000,
"batch_size": 128,
"training_iterations": 12,
"inference_iterations": 30,
"seed": 1988,
"device": "cuda",
"determinism": "best_effort_warn_only",
"autodiff_used_for_learning": false
},
"metrics": [
{
"epoch": 1,
"train_accuracy": 0.2995,
"train_cost": 0.4459439748764038,
"test_accuracy": 0.3605,
"test_cost": 0.4418565979003906,
"finite": true,
"corrector": {
"step": 78,
"clean_rms": 0.012249627574435758,
"bias_rms": 0.3237730231776297,
"residual_bias_rms": 0.4122399944579638,
"bias_to_clean_rms": 26.431254436936896,
"residual_to_clean_rms": 33.65326757511257,
"neutral_observations": 1000
},
"wall_seconds": 74.42809700965881
}
],
"epochs_completed": 1,
"final": {
"epoch": 1,
"train_accuracy": 0.2995,
"train_cost": 0.4459439748764038,
"test_accuracy": 0.3605,
"test_cost": 0.4418565979003906,
"finite": true,
"corrector": {
"step": 78,
"clean_rms": 0.012249627574435758,
"bias_rms": 0.3237730231776297,
"residual_bias_rms": 0.4122399944579638,
"bias_to_clean_rms": 26.431254436936896,
"residual_to_clean_rms": 33.65326757511257,
"neutral_observations": 1000
},
"wall_seconds": 74.42809700965881
}
}
|