p-j-r-1-2-3 commited on
Commit
654d4b9
·
verified ·
1 Parent(s): 71081b1

add ANN model run ann_time_distributed

Browse files
ann_time_distributed/ann_time_distributed.epochs.csv ADDED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,train_loss,train_acc,test_loss,test_acc,best_acc,time_sec,timestamp
2
+ 1,1.5643,0.5781,1.8288,0.3598,0.3598,2.74,2026-09-13T03:22:14.640546+00:00
3
+ 2,1.2224,0.7416,0.9252,0.7803,0.7803,0.99,2026-09-13T03:22:15.867139+00:00
4
+ 3,1.1675,0.7621,1.0253,0.7159,0.7803,0.99,2026-09-13T03:22:17.101656+00:00
5
+ 4,1.0341,0.8457,0.8982,0.822,0.822,0.99,2026-09-13T03:22:18.317886+00:00
6
+ 5,0.9609,0.8885,0.6996,0.8902,0.8902,0.99,2026-09-13T03:22:19.542797+00:00
7
+ 6,0.8645,0.9405,0.5651,0.928,0.928,1.0,2026-09-13T03:22:20.781142+00:00
8
+ 7,0.8539,0.9312,0.603,0.9091,0.928,1.02,2026-09-13T03:22:22.033014+00:00
9
+ 8,0.8112,0.9405,0.5473,0.9242,0.928,1.01,2026-09-13T03:22:23.269173+00:00
10
+ 9,0.7581,0.9665,0.5349,0.9091,0.928,1.01,2026-09-13T03:22:24.505950+00:00
11
+ 10,0.7249,0.9703,0.4066,0.9508,0.9508,1.01,2026-09-13T03:22:25.745508+00:00
12
+ 11,0.7155,0.9851,0.5663,0.9091,0.9508,1.02,2026-09-13T03:22:26.997704+00:00
13
+ 12,0.722,0.974,0.5171,0.8977,0.9508,1.01,2026-09-13T03:22:28.238953+00:00
14
+ 13,0.7312,0.9572,0.5385,0.9015,0.9508,1.02,2026-09-13T03:22:29.485443+00:00
15
+ 14,0.6982,0.9758,0.5769,0.9318,0.9508,1.02,2026-09-13T03:22:30.732180+00:00
16
+ 15,0.6631,0.9777,0.4537,0.9205,0.9508,1.03,2026-09-13T03:22:31.986192+00:00
17
+ 16,0.6544,0.9851,0.5694,0.9242,0.9508,1.02,2026-09-13T03:22:33.232695+00:00
18
+ 17,0.6625,0.9777,0.3043,0.9508,0.9508,1.01,2026-09-13T03:22:34.468651+00:00
19
+ 18,0.6405,0.9944,0.5001,0.9205,0.9508,1.01,2026-09-13T03:22:35.703243+00:00
20
+ 19,0.6446,0.9833,0.3635,0.9432,0.9508,1.0,2026-09-13T03:22:36.931081+00:00
21
+ 20,0.6211,0.9851,0.4868,0.9091,0.9508,1.0,2026-09-13T03:22:38.158455+00:00
22
+ 21,0.6464,0.9777,0.5556,0.8902,0.9508,1.0,2026-09-13T03:22:39.382586+00:00
23
+ 22,0.6434,0.9777,0.4484,0.9242,0.9508,1.0,2026-09-13T03:22:40.602118+00:00
24
+ 23,0.6074,0.9926,0.4066,0.947,0.9508,0.99,2026-09-13T03:22:41.815706+00:00
25
+ 24,0.6081,0.9963,0.4116,0.9167,0.9508,0.98,2026-09-13T03:22:43.022847+00:00
26
+ 25,0.6012,0.9888,0.455,0.9394,0.9508,0.98,2026-09-13T03:22:44.232988+00:00
27
+ 26,0.595,0.9963,0.6103,0.8864,0.9508,0.98,2026-09-13T03:22:45.438333+00:00
28
+ 27,0.5864,0.9981,0.491,0.8902,0.9508,0.97,2026-09-13T03:22:46.633017+00:00
29
+ 28,0.5815,0.9926,0.6438,0.8561,0.9508,0.97,2026-09-13T03:22:47.826429+00:00
30
+ 29,0.5896,0.9963,0.4339,0.9318,0.9508,0.97,2026-09-13T03:22:49.022987+00:00
31
+ 30,0.5968,0.9888,0.4549,0.9205,0.9508,0.97,2026-09-13T03:22:50.215811+00:00
32
+ 31,0.5867,0.9963,0.4797,0.9167,0.9508,0.97,2026-09-13T03:22:51.426326+00:00
33
+ 32,0.59,0.9963,0.3551,0.9242,0.9508,0.96,2026-09-13T03:22:52.612252+00:00
34
+ 33,0.6023,0.9926,0.5089,0.8939,0.9508,0.97,2026-09-13T03:22:53.803496+00:00
35
+ 34,0.5853,0.9944,0.4381,0.9167,0.9508,0.96,2026-09-13T03:22:54.989220+00:00
36
+ 35,0.5829,0.9926,0.3924,0.928,0.9508,0.96,2026-09-13T03:22:56.175958+00:00
37
+ 36,0.5715,0.9963,0.3337,0.9621,0.9621,0.96,2026-09-13T03:22:57.363074+00:00
38
+ 37,0.5658,1.0,0.3969,0.9318,0.9621,0.96,2026-09-13T03:22:58.550695+00:00
39
+ 38,0.5806,0.9981,0.4058,0.9242,0.9621,0.96,2026-09-13T03:22:59.729801+00:00
40
+ 39,0.5722,1.0,0.3784,0.9356,0.9621,0.97,2026-09-13T03:23:00.922717+00:00
41
+ 40,0.5676,1.0,0.4329,0.9242,0.9621,0.95,2026-09-13T03:23:02.096876+00:00
42
+ 41,0.5632,1.0,0.4321,0.8977,0.9621,0.96,2026-09-13T03:23:03.281042+00:00
43
+ 42,0.5761,0.9981,0.39,0.9432,0.9621,0.95,2026-09-13T03:23:04.456881+00:00
44
+ 43,0.5658,1.0,0.3775,0.9432,0.9621,0.96,2026-09-13T03:23:05.636168+00:00
45
+ 44,0.5618,0.9981,0.5095,0.8939,0.9621,0.96,2026-09-13T03:23:06.814851+00:00
46
+ 45,0.5619,0.9981,0.371,0.9205,0.9621,0.96,2026-09-13T03:23:07.999014+00:00
47
+ 46,0.5602,0.9981,0.4648,0.9091,0.9621,0.96,2026-09-13T03:23:09.179244+00:00
48
+ 47,0.5555,0.9981,0.3144,0.9621,0.9621,0.96,2026-09-13T03:23:10.359695+00:00
49
+ 48,0.5582,1.0,0.3499,0.9356,0.9621,0.96,2026-09-13T03:23:11.540963+00:00
50
+ 49,0.5531,1.0,0.2708,0.9583,0.9621,0.96,2026-09-13T03:23:12.725739+00:00
51
+ 50,0.5539,1.0,0.305,0.9659,0.9659,0.95,2026-09-13T03:23:13.900840+00:00
52
+ 51,0.5547,0.9981,0.2967,0.9659,0.9659,0.96,2026-09-13T03:23:15.084372+00:00
53
+ 52,0.555,1.0,0.3222,0.9583,0.9659,0.95,2026-09-13T03:23:16.261853+00:00
54
+ 53,0.5495,0.9963,0.2888,0.9394,0.9659,0.96,2026-09-13T03:23:17.449004+00:00
55
+ 54,0.5528,1.0,0.2981,0.9545,0.9659,0.96,2026-09-13T03:23:18.634401+00:00
56
+ 55,0.5521,0.9981,0.3637,0.947,0.9659,0.96,2026-09-13T03:23:19.819082+00:00
57
+ 56,0.5522,1.0,0.3313,0.9583,0.9659,0.97,2026-09-13T03:23:21.008679+00:00
58
+ 57,0.5545,1.0,0.3083,0.9545,0.9659,0.96,2026-09-13T03:23:22.193756+00:00
59
+ 58,0.556,1.0,0.3277,0.9394,0.9659,0.97,2026-09-13T03:23:23.385682+00:00
60
+ 59,0.5514,1.0,0.3736,0.9432,0.9659,0.96,2026-09-13T03:23:24.574078+00:00
61
+ 60,0.5496,0.9981,0.3349,0.9659,0.9659,0.97,2026-09-13T03:23:25.766097+00:00
62
+ 61,0.549,1.0,0.2713,0.9583,0.9659,0.97,2026-09-13T03:23:26.960677+00:00
63
+ 62,0.5498,1.0,0.3053,0.9621,0.9659,0.97,2026-09-13T03:23:28.150390+00:00
64
+ 63,0.5493,0.9981,0.3403,0.9356,0.9659,0.97,2026-09-13T03:23:29.344562+00:00
65
+ 64,0.5489,1.0,0.286,0.9735,0.9735,0.98,2026-09-13T03:23:30.553846+00:00
66
+ 65,0.5443,1.0,0.2999,0.9545,0.9735,0.97,2026-09-13T03:23:31.756031+00:00
67
+ 66,0.5482,1.0,0.3277,0.9621,0.9735,0.98,2026-09-13T03:23:32.959677+00:00
68
+ 67,0.543,1.0,0.3071,0.9621,0.9735,0.98,2026-09-13T03:23:34.171873+00:00
69
+ 68,0.5417,1.0,0.307,0.9508,0.9735,0.98,2026-09-13T03:23:35.376937+00:00
70
+ 69,0.5369,1.0,0.3078,0.9545,0.9735,0.99,2026-09-13T03:23:36.589925+00:00
71
+ 70,0.5398,1.0,0.2646,0.9583,0.9735,0.99,2026-09-13T03:23:37.804522+00:00
72
+ 71,0.5372,1.0,0.3054,0.9545,0.9735,1.0,2026-09-13T03:23:39.029914+00:00
73
+ 72,0.5389,1.0,0.3018,0.9545,0.9735,1.0,2026-09-13T03:23:40.253404+00:00
74
+ 73,0.54,1.0,0.282,0.9621,0.9735,0.99,2026-09-13T03:23:41.493182+00:00
75
+ 74,0.5376,0.9981,0.2826,0.9545,0.9735,1.0,2026-09-13T03:23:42.719720+00:00
76
+ 75,0.5405,1.0,0.2742,0.9659,0.9735,1.0,2026-09-13T03:23:43.953056+00:00
77
+ 76,0.543,1.0,0.2731,0.9659,0.9735,1.0,2026-09-13T03:23:45.173891+00:00
78
+ 77,0.5375,1.0,0.2712,0.9545,0.9735,1.0,2026-09-13T03:23:46.398238+00:00
79
+ 78,0.5411,1.0,0.2853,0.9583,0.9735,0.99,2026-09-13T03:23:47.618891+00:00
80
+ 79,0.5376,1.0,0.267,0.9697,0.9735,0.99,2026-09-13T03:23:48.840842+00:00
81
+ 80,0.5364,1.0,0.282,0.9545,0.9735,1.0,2026-09-13T03:23:50.062033+00:00
82
+ 81,0.5365,1.0,0.2719,0.9545,0.9735,0.99,2026-09-13T03:23:51.280444+00:00
83
+ 82,0.5359,1.0,0.2949,0.9508,0.9735,0.99,2026-09-13T03:23:52.493984+00:00
84
+ 83,0.5321,1.0,0.2761,0.9621,0.9735,0.99,2026-09-13T03:23:53.711934+00:00
85
+ 84,0.5355,1.0,0.2845,0.9621,0.9735,0.99,2026-09-13T03:23:54.933319+00:00
86
+ 85,0.5334,1.0,0.2833,0.9621,0.9735,0.99,2026-09-13T03:23:56.148072+00:00
87
+ 86,0.5361,1.0,0.2752,0.9545,0.9735,0.99,2026-09-13T03:23:57.359245+00:00
88
+ 87,0.5308,1.0,0.2732,0.9621,0.9735,0.98,2026-09-13T03:23:58.571054+00:00
89
+ 88,0.5325,1.0,0.286,0.9583,0.9735,0.98,2026-09-13T03:23:59.776621+00:00
90
+ 89,0.5327,1.0,0.2754,0.9583,0.9735,0.99,2026-09-13T03:24:00.994042+00:00
91
+ 90,0.5349,0.9981,0.2783,0.9583,0.9735,0.98,2026-09-13T03:24:02.199356+00:00
92
+ 91,0.5347,1.0,0.2798,0.9621,0.9735,0.98,2026-09-13T03:24:03.403093+00:00
93
+ 92,0.5337,1.0,0.272,0.9583,0.9735,0.98,2026-09-13T03:24:04.610123+00:00
94
+ 93,0.5341,1.0,0.2764,0.9583,0.9735,0.98,2026-09-13T03:24:05.814212+00:00
95
+ 94,0.5342,1.0,0.2736,0.9583,0.9735,0.98,2026-09-13T03:24:07.014015+00:00
96
+ 95,0.5347,1.0,0.2738,0.9621,0.9735,0.98,2026-09-13T03:24:08.216531+00:00
97
+ 96,0.5361,1.0,0.2768,0.9621,0.9735,0.98,2026-09-13T03:24:09.423640+00:00
98
+ 97,0.5348,1.0,0.2794,0.9621,0.9735,0.98,2026-09-13T03:24:10.632169+00:00
99
+ 98,0.5359,1.0,0.2793,0.9583,0.9735,0.98,2026-09-13T03:24:11.831709+00:00
100
+ 99,0.5325,1.0,0.2758,0.9621,0.9735,0.97,2026-09-13T03:24:13.027899+00:00
101
+ 100,0.5341,1.0,0.2727,0.9621,0.9735,0.97,2026-09-13T03:24:14.221578+00:00
ann_time_distributed/ann_time_distributed.epochs.jsonl ADDED
@@ -0,0 +1,100 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"epoch": 1, "train_loss": 1.5643, "train_acc": 0.5781, "test_loss": 1.8288, "test_acc": 0.3598, "best_acc": 0.3598, "time_sec": 2.74, "timestamp": "2026-09-13T03:22:14.640546+00:00"}
2
+ {"epoch": 2, "train_loss": 1.2224, "train_acc": 0.7416, "test_loss": 0.9252, "test_acc": 0.7803, "best_acc": 0.7803, "time_sec": 0.99, "timestamp": "2026-09-13T03:22:15.867139+00:00"}
3
+ {"epoch": 3, "train_loss": 1.1675, "train_acc": 0.7621, "test_loss": 1.0253, "test_acc": 0.7159, "best_acc": 0.7803, "time_sec": 0.99, "timestamp": "2026-09-13T03:22:17.101656+00:00"}
4
+ {"epoch": 4, "train_loss": 1.0341, "train_acc": 0.8457, "test_loss": 0.8982, "test_acc": 0.822, "best_acc": 0.822, "time_sec": 0.99, "timestamp": "2026-09-13T03:22:18.317886+00:00"}
5
+ {"epoch": 5, "train_loss": 0.9609, "train_acc": 0.8885, "test_loss": 0.6996, "test_acc": 0.8902, "best_acc": 0.8902, "time_sec": 0.99, "timestamp": "2026-09-13T03:22:19.542797+00:00"}
6
+ {"epoch": 6, "train_loss": 0.8645, "train_acc": 0.9405, "test_loss": 0.5651, "test_acc": 0.928, "best_acc": 0.928, "time_sec": 1.0, "timestamp": "2026-09-13T03:22:20.781142+00:00"}
7
+ {"epoch": 7, "train_loss": 0.8539, "train_acc": 0.9312, "test_loss": 0.603, "test_acc": 0.9091, "best_acc": 0.928, "time_sec": 1.02, "timestamp": "2026-09-13T03:22:22.033014+00:00"}
8
+ {"epoch": 8, "train_loss": 0.8112, "train_acc": 0.9405, "test_loss": 0.5473, "test_acc": 0.9242, "best_acc": 0.928, "time_sec": 1.01, "timestamp": "2026-09-13T03:22:23.269173+00:00"}
9
+ {"epoch": 9, "train_loss": 0.7581, "train_acc": 0.9665, "test_loss": 0.5349, "test_acc": 0.9091, "best_acc": 0.928, "time_sec": 1.01, "timestamp": "2026-09-13T03:22:24.505950+00:00"}
10
+ {"epoch": 10, "train_loss": 0.7249, "train_acc": 0.9703, "test_loss": 0.4066, "test_acc": 0.9508, "best_acc": 0.9508, "time_sec": 1.01, "timestamp": "2026-09-13T03:22:25.745508+00:00"}
11
+ {"epoch": 11, "train_loss": 0.7155, "train_acc": 0.9851, "test_loss": 0.5663, "test_acc": 0.9091, "best_acc": 0.9508, "time_sec": 1.02, "timestamp": "2026-09-13T03:22:26.997704+00:00"}
12
+ {"epoch": 12, "train_loss": 0.722, "train_acc": 0.974, "test_loss": 0.5171, "test_acc": 0.8977, "best_acc": 0.9508, "time_sec": 1.01, "timestamp": "2026-09-13T03:22:28.238953+00:00"}
13
+ {"epoch": 13, "train_loss": 0.7312, "train_acc": 0.9572, "test_loss": 0.5385, "test_acc": 0.9015, "best_acc": 0.9508, "time_sec": 1.02, "timestamp": "2026-09-13T03:22:29.485443+00:00"}
14
+ {"epoch": 14, "train_loss": 0.6982, "train_acc": 0.9758, "test_loss": 0.5769, "test_acc": 0.9318, "best_acc": 0.9508, "time_sec": 1.02, "timestamp": "2026-09-13T03:22:30.732180+00:00"}
15
+ {"epoch": 15, "train_loss": 0.6631, "train_acc": 0.9777, "test_loss": 0.4537, "test_acc": 0.9205, "best_acc": 0.9508, "time_sec": 1.03, "timestamp": "2026-09-13T03:22:31.986192+00:00"}
16
+ {"epoch": 16, "train_loss": 0.6544, "train_acc": 0.9851, "test_loss": 0.5694, "test_acc": 0.9242, "best_acc": 0.9508, "time_sec": 1.02, "timestamp": "2026-09-13T03:22:33.232695+00:00"}
17
+ {"epoch": 17, "train_loss": 0.6625, "train_acc": 0.9777, "test_loss": 0.3043, "test_acc": 0.9508, "best_acc": 0.9508, "time_sec": 1.01, "timestamp": "2026-09-13T03:22:34.468651+00:00"}
18
+ {"epoch": 18, "train_loss": 0.6405, "train_acc": 0.9944, "test_loss": 0.5001, "test_acc": 0.9205, "best_acc": 0.9508, "time_sec": 1.01, "timestamp": "2026-09-13T03:22:35.703243+00:00"}
19
+ {"epoch": 19, "train_loss": 0.6446, "train_acc": 0.9833, "test_loss": 0.3635, "test_acc": 0.9432, "best_acc": 0.9508, "time_sec": 1.0, "timestamp": "2026-09-13T03:22:36.931081+00:00"}
20
+ {"epoch": 20, "train_loss": 0.6211, "train_acc": 0.9851, "test_loss": 0.4868, "test_acc": 0.9091, "best_acc": 0.9508, "time_sec": 1.0, "timestamp": "2026-09-13T03:22:38.158455+00:00"}
21
+ {"epoch": 21, "train_loss": 0.6464, "train_acc": 0.9777, "test_loss": 0.5556, "test_acc": 0.8902, "best_acc": 0.9508, "time_sec": 1.0, "timestamp": "2026-09-13T03:22:39.382586+00:00"}
22
+ {"epoch": 22, "train_loss": 0.6434, "train_acc": 0.9777, "test_loss": 0.4484, "test_acc": 0.9242, "best_acc": 0.9508, "time_sec": 1.0, "timestamp": "2026-09-13T03:22:40.602118+00:00"}
23
+ {"epoch": 23, "train_loss": 0.6074, "train_acc": 0.9926, "test_loss": 0.4066, "test_acc": 0.947, "best_acc": 0.9508, "time_sec": 0.99, "timestamp": "2026-09-13T03:22:41.815706+00:00"}
24
+ {"epoch": 24, "train_loss": 0.6081, "train_acc": 0.9963, "test_loss": 0.4116, "test_acc": 0.9167, "best_acc": 0.9508, "time_sec": 0.98, "timestamp": "2026-09-13T03:22:43.022847+00:00"}
25
+ {"epoch": 25, "train_loss": 0.6012, "train_acc": 0.9888, "test_loss": 0.455, "test_acc": 0.9394, "best_acc": 0.9508, "time_sec": 0.98, "timestamp": "2026-09-13T03:22:44.232988+00:00"}
26
+ {"epoch": 26, "train_loss": 0.595, "train_acc": 0.9963, "test_loss": 0.6103, "test_acc": 0.8864, "best_acc": 0.9508, "time_sec": 0.98, "timestamp": "2026-09-13T03:22:45.438333+00:00"}
27
+ {"epoch": 27, "train_loss": 0.5864, "train_acc": 0.9981, "test_loss": 0.491, "test_acc": 0.8902, "best_acc": 0.9508, "time_sec": 0.97, "timestamp": "2026-09-13T03:22:46.633017+00:00"}
28
+ {"epoch": 28, "train_loss": 0.5815, "train_acc": 0.9926, "test_loss": 0.6438, "test_acc": 0.8561, "best_acc": 0.9508, "time_sec": 0.97, "timestamp": "2026-09-13T03:22:47.826429+00:00"}
29
+ {"epoch": 29, "train_loss": 0.5896, "train_acc": 0.9963, "test_loss": 0.4339, "test_acc": 0.9318, "best_acc": 0.9508, "time_sec": 0.97, "timestamp": "2026-09-13T03:22:49.022987+00:00"}
30
+ {"epoch": 30, "train_loss": 0.5968, "train_acc": 0.9888, "test_loss": 0.4549, "test_acc": 0.9205, "best_acc": 0.9508, "time_sec": 0.97, "timestamp": "2026-09-13T03:22:50.215811+00:00"}
31
+ {"epoch": 31, "train_loss": 0.5867, "train_acc": 0.9963, "test_loss": 0.4797, "test_acc": 0.9167, "best_acc": 0.9508, "time_sec": 0.97, "timestamp": "2026-09-13T03:22:51.426326+00:00"}
32
+ {"epoch": 32, "train_loss": 0.59, "train_acc": 0.9963, "test_loss": 0.3551, "test_acc": 0.9242, "best_acc": 0.9508, "time_sec": 0.96, "timestamp": "2026-09-13T03:22:52.612252+00:00"}
33
+ {"epoch": 33, "train_loss": 0.6023, "train_acc": 0.9926, "test_loss": 0.5089, "test_acc": 0.8939, "best_acc": 0.9508, "time_sec": 0.97, "timestamp": "2026-09-13T03:22:53.803496+00:00"}
34
+ {"epoch": 34, "train_loss": 0.5853, "train_acc": 0.9944, "test_loss": 0.4381, "test_acc": 0.9167, "best_acc": 0.9508, "time_sec": 0.96, "timestamp": "2026-09-13T03:22:54.989220+00:00"}
35
+ {"epoch": 35, "train_loss": 0.5829, "train_acc": 0.9926, "test_loss": 0.3924, "test_acc": 0.928, "best_acc": 0.9508, "time_sec": 0.96, "timestamp": "2026-09-13T03:22:56.175958+00:00"}
36
+ {"epoch": 36, "train_loss": 0.5715, "train_acc": 0.9963, "test_loss": 0.3337, "test_acc": 0.9621, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:22:57.363074+00:00"}
37
+ {"epoch": 37, "train_loss": 0.5658, "train_acc": 1.0, "test_loss": 0.3969, "test_acc": 0.9318, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:22:58.550695+00:00"}
38
+ {"epoch": 38, "train_loss": 0.5806, "train_acc": 0.9981, "test_loss": 0.4058, "test_acc": 0.9242, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:22:59.729801+00:00"}
39
+ {"epoch": 39, "train_loss": 0.5722, "train_acc": 1.0, "test_loss": 0.3784, "test_acc": 0.9356, "best_acc": 0.9621, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:00.922717+00:00"}
40
+ {"epoch": 40, "train_loss": 0.5676, "train_acc": 1.0, "test_loss": 0.4329, "test_acc": 0.9242, "best_acc": 0.9621, "time_sec": 0.95, "timestamp": "2026-09-13T03:23:02.096876+00:00"}
41
+ {"epoch": 41, "train_loss": 0.5632, "train_acc": 1.0, "test_loss": 0.4321, "test_acc": 0.8977, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:03.281042+00:00"}
42
+ {"epoch": 42, "train_loss": 0.5761, "train_acc": 0.9981, "test_loss": 0.39, "test_acc": 0.9432, "best_acc": 0.9621, "time_sec": 0.95, "timestamp": "2026-09-13T03:23:04.456881+00:00"}
43
+ {"epoch": 43, "train_loss": 0.5658, "train_acc": 1.0, "test_loss": 0.3775, "test_acc": 0.9432, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:05.636168+00:00"}
44
+ {"epoch": 44, "train_loss": 0.5618, "train_acc": 0.9981, "test_loss": 0.5095, "test_acc": 0.8939, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:06.814851+00:00"}
45
+ {"epoch": 45, "train_loss": 0.5619, "train_acc": 0.9981, "test_loss": 0.371, "test_acc": 0.9205, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:07.999014+00:00"}
46
+ {"epoch": 46, "train_loss": 0.5602, "train_acc": 0.9981, "test_loss": 0.4648, "test_acc": 0.9091, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:09.179244+00:00"}
47
+ {"epoch": 47, "train_loss": 0.5555, "train_acc": 0.9981, "test_loss": 0.3144, "test_acc": 0.9621, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:10.359695+00:00"}
48
+ {"epoch": 48, "train_loss": 0.5582, "train_acc": 1.0, "test_loss": 0.3499, "test_acc": 0.9356, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:11.540963+00:00"}
49
+ {"epoch": 49, "train_loss": 0.5531, "train_acc": 1.0, "test_loss": 0.2708, "test_acc": 0.9583, "best_acc": 0.9621, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:12.725739+00:00"}
50
+ {"epoch": 50, "train_loss": 0.5539, "train_acc": 1.0, "test_loss": 0.305, "test_acc": 0.9659, "best_acc": 0.9659, "time_sec": 0.95, "timestamp": "2026-09-13T03:23:13.900840+00:00"}
51
+ {"epoch": 51, "train_loss": 0.5547, "train_acc": 0.9981, "test_loss": 0.2967, "test_acc": 0.9659, "best_acc": 0.9659, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:15.084372+00:00"}
52
+ {"epoch": 52, "train_loss": 0.555, "train_acc": 1.0, "test_loss": 0.3222, "test_acc": 0.9583, "best_acc": 0.9659, "time_sec": 0.95, "timestamp": "2026-09-13T03:23:16.261853+00:00"}
53
+ {"epoch": 53, "train_loss": 0.5495, "train_acc": 0.9963, "test_loss": 0.2888, "test_acc": 0.9394, "best_acc": 0.9659, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:17.449004+00:00"}
54
+ {"epoch": 54, "train_loss": 0.5528, "train_acc": 1.0, "test_loss": 0.2981, "test_acc": 0.9545, "best_acc": 0.9659, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:18.634401+00:00"}
55
+ {"epoch": 55, "train_loss": 0.5521, "train_acc": 0.9981, "test_loss": 0.3637, "test_acc": 0.947, "best_acc": 0.9659, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:19.819082+00:00"}
56
+ {"epoch": 56, "train_loss": 0.5522, "train_acc": 1.0, "test_loss": 0.3313, "test_acc": 0.9583, "best_acc": 0.9659, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:21.008679+00:00"}
57
+ {"epoch": 57, "train_loss": 0.5545, "train_acc": 1.0, "test_loss": 0.3083, "test_acc": 0.9545, "best_acc": 0.9659, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:22.193756+00:00"}
58
+ {"epoch": 58, "train_loss": 0.556, "train_acc": 1.0, "test_loss": 0.3277, "test_acc": 0.9394, "best_acc": 0.9659, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:23.385682+00:00"}
59
+ {"epoch": 59, "train_loss": 0.5514, "train_acc": 1.0, "test_loss": 0.3736, "test_acc": 0.9432, "best_acc": 0.9659, "time_sec": 0.96, "timestamp": "2026-09-13T03:23:24.574078+00:00"}
60
+ {"epoch": 60, "train_loss": 0.5496, "train_acc": 0.9981, "test_loss": 0.3349, "test_acc": 0.9659, "best_acc": 0.9659, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:25.766097+00:00"}
61
+ {"epoch": 61, "train_loss": 0.549, "train_acc": 1.0, "test_loss": 0.2713, "test_acc": 0.9583, "best_acc": 0.9659, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:26.960677+00:00"}
62
+ {"epoch": 62, "train_loss": 0.5498, "train_acc": 1.0, "test_loss": 0.3053, "test_acc": 0.9621, "best_acc": 0.9659, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:28.150390+00:00"}
63
+ {"epoch": 63, "train_loss": 0.5493, "train_acc": 0.9981, "test_loss": 0.3403, "test_acc": 0.9356, "best_acc": 0.9659, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:29.344562+00:00"}
64
+ {"epoch": 64, "train_loss": 0.5489, "train_acc": 1.0, "test_loss": 0.286, "test_acc": 0.9735, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:23:30.553846+00:00"}
65
+ {"epoch": 65, "train_loss": 0.5443, "train_acc": 1.0, "test_loss": 0.2999, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 0.97, "timestamp": "2026-09-13T03:23:31.756031+00:00"}
66
+ {"epoch": 66, "train_loss": 0.5482, "train_acc": 1.0, "test_loss": 0.3277, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:23:32.959677+00:00"}
67
+ {"epoch": 67, "train_loss": 0.543, "train_acc": 1.0, "test_loss": 0.3071, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:23:34.171873+00:00"}
68
+ {"epoch": 68, "train_loss": 0.5417, "train_acc": 1.0, "test_loss": 0.307, "test_acc": 0.9508, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:23:35.376937+00:00"}
69
+ {"epoch": 69, "train_loss": 0.5369, "train_acc": 1.0, "test_loss": 0.3078, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:36.589925+00:00"}
70
+ {"epoch": 70, "train_loss": 0.5398, "train_acc": 1.0, "test_loss": 0.2646, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:37.804522+00:00"}
71
+ {"epoch": 71, "train_loss": 0.5372, "train_acc": 1.0, "test_loss": 0.3054, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 1.0, "timestamp": "2026-09-13T03:23:39.029914+00:00"}
72
+ {"epoch": 72, "train_loss": 0.5389, "train_acc": 1.0, "test_loss": 0.3018, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 1.0, "timestamp": "2026-09-13T03:23:40.253404+00:00"}
73
+ {"epoch": 73, "train_loss": 0.54, "train_acc": 1.0, "test_loss": 0.282, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:41.493182+00:00"}
74
+ {"epoch": 74, "train_loss": 0.5376, "train_acc": 0.9981, "test_loss": 0.2826, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 1.0, "timestamp": "2026-09-13T03:23:42.719720+00:00"}
75
+ {"epoch": 75, "train_loss": 0.5405, "train_acc": 1.0, "test_loss": 0.2742, "test_acc": 0.9659, "best_acc": 0.9735, "time_sec": 1.0, "timestamp": "2026-09-13T03:23:43.953056+00:00"}
76
+ {"epoch": 76, "train_loss": 0.543, "train_acc": 1.0, "test_loss": 0.2731, "test_acc": 0.9659, "best_acc": 0.9735, "time_sec": 1.0, "timestamp": "2026-09-13T03:23:45.173891+00:00"}
77
+ {"epoch": 77, "train_loss": 0.5375, "train_acc": 1.0, "test_loss": 0.2712, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 1.0, "timestamp": "2026-09-13T03:23:46.398238+00:00"}
78
+ {"epoch": 78, "train_loss": 0.5411, "train_acc": 1.0, "test_loss": 0.2853, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:47.618891+00:00"}
79
+ {"epoch": 79, "train_loss": 0.5376, "train_acc": 1.0, "test_loss": 0.267, "test_acc": 0.9697, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:48.840842+00:00"}
80
+ {"epoch": 80, "train_loss": 0.5364, "train_acc": 1.0, "test_loss": 0.282, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 1.0, "timestamp": "2026-09-13T03:23:50.062033+00:00"}
81
+ {"epoch": 81, "train_loss": 0.5365, "train_acc": 1.0, "test_loss": 0.2719, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:51.280444+00:00"}
82
+ {"epoch": 82, "train_loss": 0.5359, "train_acc": 1.0, "test_loss": 0.2949, "test_acc": 0.9508, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:52.493984+00:00"}
83
+ {"epoch": 83, "train_loss": 0.5321, "train_acc": 1.0, "test_loss": 0.2761, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:53.711934+00:00"}
84
+ {"epoch": 84, "train_loss": 0.5355, "train_acc": 1.0, "test_loss": 0.2845, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:54.933319+00:00"}
85
+ {"epoch": 85, "train_loss": 0.5334, "train_acc": 1.0, "test_loss": 0.2833, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:56.148072+00:00"}
86
+ {"epoch": 86, "train_loss": 0.5361, "train_acc": 1.0, "test_loss": 0.2752, "test_acc": 0.9545, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:23:57.359245+00:00"}
87
+ {"epoch": 87, "train_loss": 0.5308, "train_acc": 1.0, "test_loss": 0.2732, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:23:58.571054+00:00"}
88
+ {"epoch": 88, "train_loss": 0.5325, "train_acc": 1.0, "test_loss": 0.286, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:23:59.776621+00:00"}
89
+ {"epoch": 89, "train_loss": 0.5327, "train_acc": 1.0, "test_loss": 0.2754, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.99, "timestamp": "2026-09-13T03:24:00.994042+00:00"}
90
+ {"epoch": 90, "train_loss": 0.5349, "train_acc": 0.9981, "test_loss": 0.2783, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:02.199356+00:00"}
91
+ {"epoch": 91, "train_loss": 0.5347, "train_acc": 1.0, "test_loss": 0.2798, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:03.403093+00:00"}
92
+ {"epoch": 92, "train_loss": 0.5337, "train_acc": 1.0, "test_loss": 0.272, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:04.610123+00:00"}
93
+ {"epoch": 93, "train_loss": 0.5341, "train_acc": 1.0, "test_loss": 0.2764, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:05.814212+00:00"}
94
+ {"epoch": 94, "train_loss": 0.5342, "train_acc": 1.0, "test_loss": 0.2736, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:07.014015+00:00"}
95
+ {"epoch": 95, "train_loss": 0.5347, "train_acc": 1.0, "test_loss": 0.2738, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:08.216531+00:00"}
96
+ {"epoch": 96, "train_loss": 0.5361, "train_acc": 1.0, "test_loss": 0.2768, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:09.423640+00:00"}
97
+ {"epoch": 97, "train_loss": 0.5348, "train_acc": 1.0, "test_loss": 0.2794, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:10.632169+00:00"}
98
+ {"epoch": 98, "train_loss": 0.5359, "train_acc": 1.0, "test_loss": 0.2793, "test_acc": 0.9583, "best_acc": 0.9735, "time_sec": 0.98, "timestamp": "2026-09-13T03:24:11.831709+00:00"}
99
+ {"epoch": 99, "train_loss": 0.5325, "train_acc": 1.0, "test_loss": 0.2758, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.97, "timestamp": "2026-09-13T03:24:13.027899+00:00"}
100
+ {"epoch": 100, "train_loss": 0.5341, "train_acc": 1.0, "test_loss": 0.2727, "test_acc": 0.9621, "best_acc": 0.9735, "time_sec": 0.97, "timestamp": "2026-09-13T03:24:14.221578+00:00"}
ann_time_distributed/ann_time_distributed.summary.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "tag": "ann_time_distributed",
3
+ "arch": "time_distributed",
4
+ "script": "train_ann.py",
5
+ "parameters": 1296150,
6
+ "epochs_requested": 100,
7
+ "epochs_completed": 100,
8
+ "batch_size": 32,
9
+ "num_bins_T": 16,
10
+ "lr": 0.002,
11
+ "duration_s": 122.6,
12
+ "best": {
13
+ "epoch": 64,
14
+ "test_acc": 0.9735
15
+ },
16
+ "final_epoch_metrics": {
17
+ "epoch": 100,
18
+ "train_loss": 0.5341,
19
+ "train_acc": 1.0,
20
+ "test_loss": 0.2727,
21
+ "test_acc": 0.9621,
22
+ "best_acc": 0.9735,
23
+ "time_sec": 0.97,
24
+ "timestamp": "2026-09-13T03:24:14.221578+00:00"
25
+ },
26
+ "zip": {
27
+ "name": "ann_time_distributed.zip",
28
+ "files": 12,
29
+ "bytes": 9754578,
30
+ "MB": 9.75,
31
+ "sha256": "6c4707ccd2d59ebbcc98a745173c02360c96856e5132eac0bccfe1036eb87995"
32
+ }
33
+ }
ann_time_distributed/ann_time_distributed.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6c4707ccd2d59ebbcc98a745173c02360c96856e5132eac0bccfe1036eb87995
3
+ size 9754578