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Commit c3426f6e authored by Sugon_ldc's avatar Sugon_ldc
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add shufflenetv2 model

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results/dcu/230627081641.log 0 → 100644
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2023-06-27 08:16:41.671893 cuda
2023-06-27 08:17:08.828368 Train: epoch: 1 batch: 0/4, loss: 0.690686
2023-06-27 08:18:35.142136 Validation: avg loss: 0.6951, avg acc: 42.8571%
2023-06-27 08:19:02.374354 Train: epoch: 2 batch: 0/4, loss: 0.699319
2023-06-27 08:20:28.626366 Validation: avg loss: 0.6834, avg acc: 57.1429%
2023-06-27 08:20:55.751758 Train: epoch: 3 batch: 0/4, loss: 0.667576
2023-06-27 08:22:21.997209 Validation: avg loss: 0.6878, avg acc: 57.1429%
2023-06-27 08:22:49.193378 Train: epoch: 4 batch: 0/4, loss: 0.667708
2023-06-27 08:24:15.387809 Validation: avg loss: 0.6996, avg acc: 42.8571%
2023-06-27 08:24:42.553643 Train: epoch: 5 batch: 0/4, loss: 0.670109
2023-06-27 08:26:08.866459 Validation: avg loss: 0.6886, avg acc: 57.1429%
2023-06-27 08:26:36.081375 Train: epoch: 6 batch: 0/4, loss: 0.639370
2023-06-27 08:28:02.278285 Validation: avg loss: 0.7140, avg acc: 42.8571%
2023-06-27 08:28:29.519126 Train: epoch: 7 batch: 0/4, loss: 0.594772
2023-06-27 08:29:55.839928 Validation: avg loss: 0.6951, avg acc: 42.8571%
2023-06-27 08:30:23.007158 Train: epoch: 8 batch: 0/4, loss: 0.507376
2023-06-27 08:31:49.132699 Validation: avg loss: 0.7306, avg acc: 42.8571%
2023-06-27 08:32:16.249712 Train: epoch: 9 batch: 0/4, loss: 0.459418
2023-06-27 08:33:42.481942 Validation: avg loss: 0.7156, avg acc: 42.8571%
2023-06-27 08:34:09.593378 Train: epoch: 10 batch: 0/4, loss: 0.399126
2023-06-27 08:35:35.798481 Validation: avg loss: 0.8311, avg acc: 42.8571%
2023-06-27 08:36:03.008162 Train: epoch: 11 batch: 0/4, loss: 0.323756
2023-06-27 08:37:29.221067 Validation: avg loss: 0.7270, avg acc: 47.6190%
2023-06-27 08:37:56.409267 Train: epoch: 12 batch: 0/4, loss: 0.283424
2023-06-27 08:39:22.562759 Validation: avg loss: 0.7440, avg acc: 54.2857%
2023-06-27 08:39:49.687929 Train: epoch: 13 batch: 0/4, loss: 0.167859
2023-06-27 08:41:16.034551 Validation: avg loss: 0.7283, avg acc: 58.0952%
2023-06-27 08:41:43.186369 Train: epoch: 14 batch: 0/4, loss: 0.102730
2023-06-27 08:43:09.325541 Validation: avg loss: 0.7591, avg acc: 61.9048%
2023-06-27 08:43:36.529436 Train: epoch: 15 batch: 0/4, loss: 0.074994
2023-06-27 08:45:02.694462 Validation: avg loss: 0.7766, avg acc: 64.7619%
2023-06-27 08:45:29.836347 Train: epoch: 16 batch: 0/4, loss: 0.045623
2023-06-27 08:46:56.112357 Validation: avg loss: 0.7725, avg acc: 67.6190%
2023-06-27 08:47:23.309353 Train: epoch: 17 batch: 0/4, loss: 0.035577
2023-06-27 08:48:49.607474 Validation: avg loss: 0.8334, avg acc: 69.5238%
2023-06-27 08:49:16.910803 Train: epoch: 18 batch: 0/4, loss: 0.041118
2023-06-27 08:50:43.077512 Validation: avg loss: 0.9475, avg acc: 64.7619%
2023-06-27 08:51:10.233906 Train: epoch: 19 batch: 0/4, loss: 0.025593
2023-06-27 08:52:36.387857 Validation: avg loss: 1.0298, avg acc: 64.7619%
2023-06-27 08:53:03.496448 Train: epoch: 20 batch: 0/4, loss: 0.011434
2023-06-27 08:54:29.840693 Validation: avg loss: 1.1044, avg acc: 63.8095%
2023-06-27 08:54:57.115212 Train: epoch: 21 batch: 0/4, loss: 0.008180
2023-06-27 08:56:23.369830 Validation: avg loss: 1.1129, avg acc: 64.7619%
2023-06-27 08:56:50.531572 Train: epoch: 22 batch: 0/4, loss: 0.008584
2023-06-27 08:58:16.876190 Validation: avg loss: 1.1464, avg acc: 65.7143%
2023-06-27 08:58:44.109805 Train: epoch: 23 batch: 0/4, loss: 0.006289
2023-06-27 09:00:10.520495 Validation: avg loss: 1.2131, avg acc: 64.7619%
2023-06-27 09:00:37.795441 Train: epoch: 24 batch: 0/4, loss: 0.006696
2023-06-27 09:02:04.233420 Validation: avg loss: 1.2434, avg acc: 63.8095%
2023-06-27 09:02:31.527578 Train: epoch: 25 batch: 0/4, loss: 0.006396
2023-06-27 09:03:58.062903 Validation: avg loss: 1.2861, avg acc: 64.7619%
2023-06-27 09:04:25.202483 Train: epoch: 26 batch: 0/4, loss: 0.006774
2023-06-27 09:05:51.564121 Validation: avg loss: 1.3280, avg acc: 65.7143%
2023-06-27 09:06:18.776448 Train: epoch: 27 batch: 0/4, loss: 0.004234
2023-06-27 09:07:45.325998 Validation: avg loss: 1.3473, avg acc: 70.4762%
2023-06-27 09:08:12.558660 Train: epoch: 28 batch: 0/4, loss: 0.004215
2023-06-27 09:09:39.210121 Validation: avg loss: 1.3675, avg acc: 69.5238%
2023-06-27 09:10:06.424814 Train: epoch: 29 batch: 0/4, loss: 0.002990
2023-06-27 09:11:32.885334 Validation: avg loss: 1.3709, avg acc: 68.5714%
2023-06-27 09:12:00.117189 Train: epoch: 30 batch: 0/4, loss: 0.002743
2023-06-27 09:13:26.594575 Validation: avg loss: 1.3784, avg acc: 63.8095%
2023-06-27 09:13:53.903212 Train: epoch: 31 batch: 0/4, loss: 0.003456
2023-06-27 09:15:20.425816 Validation: avg loss: 1.3805, avg acc: 63.8095%
2023-06-27 09:15:47.705312 Train: epoch: 32 batch: 0/4, loss: 0.002079
2023-06-27 09:17:14.401271 Validation: avg loss: 1.3821, avg acc: 63.8095%
2023-06-27 09:17:41.656943 Train: epoch: 33 batch: 0/4, loss: 0.002024
2023-06-27 09:19:08.187980 Validation: avg loss: 1.3959, avg acc: 62.8571%
2023-06-27 09:19:35.549571 Train: epoch: 34 batch: 0/4, loss: 0.002082
2023-06-27 09:21:02.014229 Validation: avg loss: 1.4013, avg acc: 64.7619%
2023-06-27 09:21:29.214740 Train: epoch: 35 batch: 0/4, loss: 0.001415
2023-06-27 09:22:55.758057 Validation: avg loss: 1.4173, avg acc: 63.8095%
2023-06-27 09:23:23.063048 Train: epoch: 36 batch: 0/4, loss: 0.001674
2023-06-27 09:24:49.625627 Validation: avg loss: 1.4322, avg acc: 65.7143%
2023-06-27 09:25:16.910659 Train: epoch: 37 batch: 0/4, loss: 0.001886
2023-06-27 09:26:43.283342 Validation: avg loss: 1.4460, avg acc: 65.7143%
2023-06-27 09:27:10.702859 Train: epoch: 38 batch: 0/4, loss: 0.001493
2023-06-27 09:28:37.080170 Validation: avg loss: 1.4463, avg acc: 65.7143%
2023-06-27 09:29:04.419829 Train: epoch: 39 batch: 0/4, loss: 0.000958
2023-06-27 09:30:30.713857 Validation: avg loss: 1.4333, avg acc: 65.7143%
2023-06-27 09:30:57.909946 Train: epoch: 40 batch: 0/4, loss: 0.000895
2023-06-27 09:32:24.132378 Validation: avg loss: 1.4366, avg acc: 66.6667%
2023-06-27 09:32:51.354331 Train: epoch: 41 batch: 0/4, loss: 0.001026
2023-06-27 09:34:17.521434 Validation: avg loss: 1.4490, avg acc: 66.6667%
2023-06-27 09:34:44.682128 Train: epoch: 42 batch: 0/4, loss: 0.001024
2023-06-27 09:36:10.952673 Validation: avg loss: 1.4517, avg acc: 66.6667%
2023-06-27 09:36:38.094327 Train: epoch: 43 batch: 0/4, loss: 0.000966
2023-06-27 09:38:04.351234 Validation: avg loss: 1.4680, avg acc: 68.5714%
2023-06-27 09:38:31.477071 Train: epoch: 44 batch: 0/4, loss: 0.000702
2023-06-27 09:39:57.566202 Validation: avg loss: 1.4892, avg acc: 67.6190%
2023-06-27 09:40:24.683609 Train: epoch: 45 batch: 0/4, loss: 0.000781
2023-06-27 09:41:50.898765 Validation: avg loss: 1.4939, avg acc: 67.6190%
2023-06-27 09:42:18.038318 Train: epoch: 46 batch: 0/4, loss: 0.001826
2023-06-27 09:43:44.314628 Validation: avg loss: 1.4887, avg acc: 68.5714%
2023-06-27 09:44:11.433003 Train: epoch: 47 batch: 0/4, loss: 0.000676
2023-06-27 09:45:37.681621 Validation: avg loss: 1.4772, avg acc: 68.5714%
2023-06-27 09:46:04.826717 Train: epoch: 48 batch: 0/4, loss: 0.005239
2023-06-27 09:47:30.986014 Validation: avg loss: 1.4791, avg acc: 68.5714%
2023-06-27 09:47:58.165325 Train: epoch: 49 batch: 0/4, loss: 0.001139
2023-06-27 09:49:24.535061 Validation: avg loss: 1.4732, avg acc: 65.7143%
2023-06-27 09:49:51.634992 Train: epoch: 50 batch: 0/4, loss: 0.000766
2023-06-27 09:51:17.910953 Validation: avg loss: 1.4655, avg acc: 67.6190%
results/dcu/230627095117.log 0 → 100644
View file @ c3426f6e
2023-06-27 09:51:17.943816 cuda
2023-06-27 09:51:45.031869 Train: epoch: 1 batch: 0/4, loss: 0.692920
2023-06-27 09:53:11.007603 Validation: avg loss: 0.6809, avg acc: 60.9524%
2023-06-27 09:53:38.117517 Train: epoch: 2 batch: 0/4, loss: 0.680874
2023-06-27 09:55:04.460955 Validation: avg loss: 0.6767, avg acc: 60.9524%
2023-06-27 09:55:31.537141 Train: epoch: 3 batch: 0/4, loss: 0.673850
2023-06-27 09:56:57.482964 Validation: avg loss: 0.6809, avg acc: 60.9524%
2023-06-27 09:57:24.648757 Train: epoch: 4 batch: 0/4, loss: 0.670431
2023-06-27 09:58:50.718083 Validation: avg loss: 0.6747, avg acc: 60.9524%
2023-06-27 09:59:17.881676 Train: epoch: 5 batch: 0/4, loss: 0.664857
2023-06-27 10:00:44.101904 Validation: avg loss: 0.6699, avg acc: 60.9524%
2023-06-27 10:01:11.356698 Train: epoch: 6 batch: 0/4, loss: 0.635556
2023-06-27 10:02:37.382650 Validation: avg loss: 0.6693, avg acc: 60.9524%
2023-06-27 10:03:04.537001 Train: epoch: 7 batch: 0/4, loss: 0.637340
2023-06-27 10:04:30.673889 Validation: avg loss: 0.6679, avg acc: 60.9524%
2023-06-27 10:04:57.842520 Train: epoch: 8 batch: 0/4, loss: 0.574225
2023-06-27 10:06:23.885257 Validation: avg loss: 0.6666, avg acc: 60.9524%
2023-06-27 10:06:51.015813 Train: epoch: 9 batch: 0/4, loss: 0.548067
2023-06-27 10:08:17.082568 Validation: avg loss: 0.6669, avg acc: 60.9524%
2023-06-27 10:08:44.232294 Train: epoch: 10 batch: 0/4, loss: 0.520810
2023-06-27 10:10:10.351286 Validation: avg loss: 0.6648, avg acc: 60.9524%
2023-06-27 10:10:37.589344 Train: epoch: 11 batch: 0/4, loss: 0.475918
2023-06-27 10:12:03.782103 Validation: avg loss: 0.6684, avg acc: 60.9524%
2023-06-27 10:12:31.046139 Train: epoch: 12 batch: 0/4, loss: 0.353386
2023-06-27 10:13:56.973990 Validation: avg loss: 0.6742, avg acc: 60.9524%
2023-06-27 10:14:24.145859 Train: epoch: 13 batch: 0/4, loss: 0.333370
2023-06-27 10:15:50.129105 Validation: avg loss: 0.6690, avg acc: 59.0476%
2023-06-27 10:16:17.317532 Train: epoch: 14 batch: 0/4, loss: 0.180197
2023-06-27 10:17:43.436121 Validation: avg loss: 0.6737, avg acc: 62.8571%
2023-06-27 10:18:10.619460 Train: epoch: 15 batch: 0/4, loss: 0.124915
2023-06-27 10:19:36.764763 Validation: avg loss: 0.7272, avg acc: 65.7143%
2023-06-27 10:20:03.985896 Train: epoch: 16 batch: 0/4, loss: 0.124326
2023-06-27 10:21:29.969811 Validation: avg loss: 0.8012, avg acc: 66.6667%
2023-06-27 10:21:57.147394 Train: epoch: 17 batch: 0/4, loss: 0.073580
2023-06-27 10:23:23.289812 Validation: avg loss: 0.7603, avg acc: 69.5238%
2023-06-27 10:23:50.404465 Train: epoch: 18 batch: 0/4, loss: 0.041348
2023-06-27 10:25:16.326867 Validation: avg loss: 0.7959, avg acc: 67.6190%
2023-06-27 10:25:43.477358 Train: epoch: 19 batch: 0/4, loss: 0.056011
2023-06-27 10:27:09.553970 Validation: avg loss: 0.8282, avg acc: 67.6190%
2023-06-27 10:27:36.633129 Train: epoch: 20 batch: 0/4, loss: 0.017706
2023-06-27 10:29:02.710204 Validation: avg loss: 0.8702, avg acc: 68.5714%
2023-06-27 10:29:29.941797 Train: epoch: 21 batch: 0/4, loss: 0.012588
2023-06-27 10:30:56.008673 Validation: avg loss: 0.8757, avg acc: 66.6667%
2023-06-27 10:31:23.177988 Train: epoch: 22 batch: 0/4, loss: 0.021301
2023-06-27 10:32:49.301422 Validation: avg loss: 0.9061, avg acc: 70.4762%
2023-06-27 10:33:16.475607 Train: epoch: 23 batch: 0/4, loss: 0.024899
2023-06-27 10:34:42.467533 Validation: avg loss: 1.0369, avg acc: 69.5238%
2023-06-27 10:35:09.593099 Train: epoch: 24 batch: 0/4, loss: 0.011102
2023-06-27 10:36:35.694494 Validation: avg loss: 1.0316, avg acc: 71.4286%
2023-06-27 10:37:02.860291 Train: epoch: 25 batch: 0/4, loss: 0.012121
2023-06-27 10:38:28.876663 Validation: avg loss: 1.1020, avg acc: 68.5714%
2023-06-27 10:38:56.042741 Train: epoch: 26 batch: 0/4, loss: 0.015106
2023-06-27 10:40:22.153557 Validation: avg loss: 1.1536, avg acc: 68.5714%
2023-06-27 10:40:49.275220 Train: epoch: 27 batch: 0/4, loss: 0.014671
2023-06-27 10:42:15.299410 Validation: avg loss: 1.1732, avg acc: 69.5238%
2023-06-27 10:42:42.427554 Train: epoch: 28 batch: 0/4, loss: 0.010009
2023-06-27 10:44:08.679899 Validation: avg loss: 1.1478, avg acc: 71.4286%
2023-06-27 10:44:35.831982 Train: epoch: 29 batch: 0/4, loss: 0.005856
2023-06-27 10:46:01.805116 Validation: avg loss: 1.1247, avg acc: 72.3810%
2023-06-27 10:46:28.951655 Train: epoch: 30 batch: 0/4, loss: 0.002406
2023-06-27 10:47:55.057242 Validation: avg loss: 1.1468, avg acc: 71.4286%
2023-06-27 10:48:22.278871 Train: epoch: 31 batch: 0/4, loss: 0.006726
2023-06-27 10:49:48.223422 Validation: avg loss: 1.1544, avg acc: 71.4286%
2023-06-27 10:50:15.293887 Train: epoch: 32 batch: 0/4, loss: 0.003755
2023-06-27 10:51:41.375743 Validation: avg loss: 1.1695, avg acc: 72.3810%
2023-06-27 10:52:08.536748 Train: epoch: 33 batch: 0/4, loss: 0.002955
2023-06-27 10:53:34.625209 Validation: avg loss: 1.1835, avg acc: 68.5714%
2023-06-27 10:54:01.802283 Train: epoch: 34 batch: 0/4, loss: 0.002133
2023-06-27 10:55:27.794304 Validation: avg loss: 1.1729, avg acc: 68.5714%
2023-06-27 10:55:54.877162 Train: epoch: 35 batch: 0/4, loss: 0.001604
2023-06-27 10:57:21.091049 Validation: avg loss: 1.1573, avg acc: 69.5238%
2023-06-27 10:57:48.172991 Train: epoch: 36 batch: 0/4, loss: 0.003845
2023-06-27 10:59:14.155246 Validation: avg loss: 1.1454, avg acc: 70.4762%
2023-06-27 10:59:41.339050 Train: epoch: 37 batch: 0/4, loss: 0.001906
2023-06-27 11:01:07.727273 Validation: avg loss: 1.1569, avg acc: 70.4762%
2023-06-27 11:01:34.964570 Train: epoch: 38 batch: 0/4, loss: 0.003651
2023-06-27 11:03:01.346197 Validation: avg loss: 1.1541, avg acc: 71.4286%
2023-06-27 11:03:28.568076 Train: epoch: 39 batch: 0/4, loss: 0.001157
2023-06-27 11:04:54.988566 Validation: avg loss: 1.1594, avg acc: 71.4286%
2023-06-27 11:05:22.217518 Train: epoch: 40 batch: 0/4, loss: 0.001297
2023-06-27 11:06:48.897697 Validation: avg loss: 1.1645, avg acc: 72.3810%
2023-06-27 11:07:16.114061 Train: epoch: 41 batch: 0/4, loss: 0.001007
2023-06-27 11:08:42.636769 Validation: avg loss: 1.1754, avg acc: 71.4286%
2023-06-27 11:09:09.882792 Train: epoch: 42 batch: 0/4, loss: 0.001658
2023-06-27 11:10:36.040717 Validation: avg loss: 1.1740, avg acc: 71.4286%
2023-06-27 11:11:03.193114 Train: epoch: 43 batch: 0/4, loss: 0.001940
2023-06-27 11:12:29.145485 Validation: avg loss: 1.1774, avg acc: 71.4286%
2023-06-27 11:12:56.335781 Train: epoch: 44 batch: 0/4, loss: 0.005166
2023-06-27 11:14:22.547965 Validation: avg loss: 1.1716, avg acc: 71.4286%
2023-06-27 11:14:49.694593 Train: epoch: 45 batch: 0/4, loss: 0.001622
2023-06-27 11:16:15.754771 Validation: avg loss: 1.1788, avg acc: 71.4286%
2023-06-27 11:16:42.990081 Train: epoch: 46 batch: 0/4, loss: 0.001020
2023-06-27 11:18:09.150671 Validation: avg loss: 1.1808, avg acc: 71.4286%
2023-06-27 11:18:36.326383 Train: epoch: 47 batch: 0/4, loss: 0.001181
2023-06-27 11:20:02.368115 Validation: avg loss: 1.1950, avg acc: 71.4286%
2023-06-27 11:20:29.616366 Train: epoch: 48 batch: 0/4, loss: 0.000773
2023-06-27 11:21:55.670673 Validation: avg loss: 1.2090, avg acc: 71.4286%
2023-06-27 11:22:22.762928 Train: epoch: 49 batch: 0/4, loss: 0.000904
2023-06-27 11:23:49.044015 Validation: avg loss: 1.2248, avg acc: 69.5238%
2023-06-27 11:24:16.507658 Train: epoch: 50 batch: 0/4, loss: 0.000842
2023-06-27 11:25:43.273831 Validation: avg loss: 1.2280, avg acc: 70.4762%
results/dcu/230627112543.log 0 → 100644
View file @ c3426f6e
2023-06-27 11:25:43.307219 cuda
2023-06-27 11:26:10.528154 Train: epoch: 1 batch: 0/4, loss: 0.694377
2023-06-27 11:27:37.088485 Validation: avg loss: 0.6900, avg acc: 58.0952%
2023-06-27 11:28:04.274261 Train: epoch: 2 batch: 0/4, loss: 0.682107
2023-06-27 11:29:31.164142 Validation: avg loss: 0.6882, avg acc: 58.0952%
2023-06-27 11:29:58.520648 Train: epoch: 3 batch: 0/4, loss: 0.679390
2023-06-27 11:31:25.626905 Validation: avg loss: 0.6869, avg acc: 58.0952%
2023-06-27 11:31:53.026354 Train: epoch: 4 batch: 0/4, loss: 0.680164
2023-06-27 11:33:19.822167 Validation: avg loss: 0.6829, avg acc: 58.0952%
2023-06-27 11:33:47.197666 Train: epoch: 5 batch: 0/4, loss: 0.650284
2023-06-27 11:35:13.854674 Validation: avg loss: 0.6994, avg acc: 41.9048%
2023-06-27 11:35:41.257044 Train: epoch: 6 batch: 0/4, loss: 0.627514
2023-06-27 11:37:07.892390 Validation: avg loss: 0.7255, avg acc: 41.9048%
2023-06-27 11:37:35.113169 Train: epoch: 7 batch: 0/4, loss: 0.601305
2023-06-27 11:39:01.400625 Validation: avg loss: 0.7415, avg acc: 41.9048%
2023-06-27 11:39:28.628852 Train: epoch: 8 batch: 0/4, loss: 0.543208
2023-06-27 11:40:54.961255 Validation: avg loss: 0.7183, avg acc: 41.9048%
2023-06-27 11:41:22.234808 Train: epoch: 9 batch: 0/4, loss: 0.482571
2023-06-27 11:42:48.540137 Validation: avg loss: 0.7260, avg acc: 41.9048%
2023-06-27 11:43:15.619276 Train: epoch: 10 batch: 0/4, loss: 0.408161
2023-06-27 11:44:41.998452 Validation: avg loss: 0.7692, avg acc: 41.9048%
2023-06-27 11:45:09.179220 Train: epoch: 11 batch: 0/4, loss: 0.377784
2023-06-27 11:46:35.427269 Validation: avg loss: 0.7082, avg acc: 50.4762%
2023-06-27 11:47:02.789648 Train: epoch: 12 batch: 0/4, loss: 0.245929
2023-06-27 11:48:29.284276 Validation: avg loss: 0.7218, avg acc: 52.3810%
2023-06-27 11:48:56.519824 Train: epoch: 13 batch: 0/4, loss: 0.193640
2023-06-27 11:50:23.003832 Validation: avg loss: 0.6665, avg acc: 59.0476%
2023-06-27 11:50:50.149866 Train: epoch: 14 batch: 0/4, loss: 0.134887
2023-06-27 11:52:16.632313 Validation: avg loss: 0.6073, avg acc: 64.7619%
2023-06-27 11:52:43.855746 Train: epoch: 15 batch: 0/4, loss: 0.116741
2023-06-27 11:54:10.460123 Validation: avg loss: 0.6112, avg acc: 66.6667%
2023-06-27 11:54:37.673824 Train: epoch: 16 batch: 0/4, loss: 0.056002
2023-06-27 11:56:03.927156 Validation: avg loss: 0.6511, avg acc: 70.4762%
2023-06-27 11:56:31.277013 Train: epoch: 17 batch: 0/4, loss: 0.039492
2023-06-27 11:57:57.749525 Validation: avg loss: 0.7000, avg acc: 67.6190%
2023-06-27 11:58:24.951971 Train: epoch: 18 batch: 0/4, loss: 0.025889
2023-06-27 11:59:51.491950 Validation: avg loss: 0.7304, avg acc: 66.6667%
2023-06-27 12:00:18.728440 Train: epoch: 19 batch: 0/4, loss: 0.039517
2023-06-27 12:01:45.047607 Validation: avg loss: 0.7353, avg acc: 66.6667%
2023-06-27 12:02:12.402953 Train: epoch: 20 batch: 0/4, loss: 0.037402
2023-06-27 12:03:38.841518 Validation: avg loss: 0.7263, avg acc: 66.6667%
2023-06-27 12:04:06.000490 Train: epoch: 21 batch: 0/4, loss: 0.018236
2023-06-27 12:05:32.367566 Validation: avg loss: 0.7570, avg acc: 64.7619%
2023-06-27 12:05:59.499032 Train: epoch: 22 batch: 0/4, loss: 0.025706
2023-06-27 12:07:25.798044 Validation: avg loss: 0.8620, avg acc: 68.5714%
2023-06-27 12:07:53.042050 Train: epoch: 23 batch: 0/4, loss: 0.006979
2023-06-27 12:09:19.386309 Validation: avg loss: 0.8502, avg acc: 67.6190%
2023-06-27 12:09:46.546452 Train: epoch: 24 batch: 0/4, loss: 0.013295
2023-06-27 12:11:13.049669 Validation: avg loss: 0.8720, avg acc: 67.6190%
2023-06-27 12:11:40.399711 Train: epoch: 25 batch: 0/4, loss: 0.017644
2023-06-27 12:13:06.721808 Validation: avg loss: 0.8946, avg acc: 69.5238%
2023-06-27 12:13:33.901891 Train: epoch: 26 batch: 0/4, loss: 0.009154
2023-06-27 12:15:00.278508 Validation: avg loss: 0.9153, avg acc: 68.5714%
2023-06-27 12:15:27.444753 Train: epoch: 27 batch: 0/4, loss: 0.004955
2023-06-27 12:16:54.014796 Validation: avg loss: 0.9225, avg acc: 68.5714%
2023-06-27 12:17:21.180353 Train: epoch: 28 batch: 0/4, loss: 0.003607
2023-06-27 12:18:47.605041 Validation: avg loss: 0.9346, avg acc: 68.5714%
2023-06-27 12:19:14.851889 Train: epoch: 29 batch: 0/4, loss: 0.003095
2023-06-27 12:20:41.196987 Validation: avg loss: 0.9443, avg acc: 67.6190%
2023-06-27 12:21:08.365717 Train: epoch: 30 batch: 0/4, loss: 0.004005
2023-06-27 12:22:34.755427 Validation: avg loss: 0.9436, avg acc: 67.6190%
2023-06-27 12:23:01.954312 Train: epoch: 31 batch: 0/4, loss: 0.003913
2023-06-27 12:24:28.403747 Validation: avg loss: 0.9505, avg acc: 68.5714%
2023-06-27 12:24:55.549514 Train: epoch: 32 batch: 0/4, loss: 0.005185
2023-06-27 12:26:21.749116 Validation: avg loss: 0.9559, avg acc: 69.5238%
2023-06-27 12:26:48.891141 Train: epoch: 33 batch: 0/4, loss: 0.002091
2023-06-27 12:28:15.035038 Validation: avg loss: 0.9427, avg acc: 68.5714%
2023-06-27 12:28:42.149200 Train: epoch: 34 batch: 0/4, loss: 0.001567
2023-06-27 12:30:08.417017 Validation: avg loss: 0.9374, avg acc: 67.6190%
2023-06-27 12:30:35.547546 Train: epoch: 35 batch: 0/4, loss: 0.002373
2023-06-27 12:32:01.499473 Validation: avg loss: 0.9400, avg acc: 68.5714%
2023-06-27 12:32:28.569395 Train: epoch: 36 batch: 0/4, loss: 0.003582
2023-06-27 12:33:54.857292 Validation: avg loss: 0.9354, avg acc: 67.6190%
2023-06-27 12:34:21.949400 Train: epoch: 37 batch: 0/4, loss: 0.001832
2023-06-27 12:35:48.160750 Validation: avg loss: 0.9443, avg acc: 68.5714%
2023-06-27 12:36:15.310859 Train: epoch: 38 batch: 0/4, loss: 0.001962
2023-06-27 12:37:41.613417 Validation: avg loss: 0.9425, avg acc: 68.5714%
2023-06-27 12:38:08.759034 Train: epoch: 39 batch: 0/4, loss: 0.001382
2023-06-27 12:39:35.093859 Validation: avg loss: 0.9507, avg acc: 66.6667%
2023-06-27 12:40:02.433032 Train: epoch: 40 batch: 0/4, loss: 0.001698
2023-06-27 12:41:28.818298 Validation: avg loss: 0.9661, avg acc: 66.6667%
2023-06-27 12:41:56.175044 Train: epoch: 41 batch: 0/4, loss: 0.001760
2023-06-27 12:43:22.649339 Validation: avg loss: 0.9720, avg acc: 66.6667%
2023-06-27 12:43:49.896349 Train: epoch: 42 batch: 0/4, loss: 0.001426
2023-06-27 12:45:16.419486 Validation: avg loss: 0.9811, avg acc: 67.6190%
2023-06-27 12:45:43.749214 Train: epoch: 43 batch: 0/4, loss: 0.002155
2023-06-27 12:47:10.163677 Validation: avg loss: 0.9918, avg acc: 67.6190%
2023-06-27 12:47:37.472330 Train: epoch: 44 batch: 0/4, loss: 0.001377
2023-06-27 12:49:03.932090 Validation: avg loss: 0.9809, avg acc: 67.6190%
2023-06-27 12:49:31.117277 Train: epoch: 45 batch: 0/4, loss: 0.001217
2023-06-27 12:50:57.605537 Validation: avg loss: 0.9833, avg acc: 65.7143%
2023-06-27 12:51:24.885712 Train: epoch: 46 batch: 0/4, loss: 0.001027
2023-06-27 12:52:51.391136 Validation: avg loss: 1.0012, avg acc: 67.6190%
2023-06-27 12:53:18.681766 Train: epoch: 47 batch: 0/4, loss: 0.001231
2023-06-27 12:54:45.126626 Validation: avg loss: 1.0262, avg acc: 67.6190%
2023-06-27 12:55:12.307979 Train: epoch: 48 batch: 0/4, loss: 0.001463
2023-06-27 12:56:38.840175 Validation: avg loss: 1.0485, avg acc: 66.6667%
2023-06-27 12:57:06.132147 Train: epoch: 49 batch: 0/4, loss: 0.001413
2023-06-27 12:58:32.521124 Validation: avg loss: 1.0609, avg acc: 67.6190%
2023-06-27 12:58:59.748739 Train: epoch: 50 batch: 0/4, loss: 0.000888
2023-06-27 13:00:26.082251 Validation: avg loss: 1.0667, avg acc: 68.5714%
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2023-06-27 13:00:26.176732 cuda
2023-06-27 13:00:53.363334 Train: epoch: 1 batch: 0/4, loss: 0.691868
2023-06-27 13:02:19.586241 Validation: avg loss: 0.6879, avg acc: 57.1429%
2023-06-27 13:02:46.901065 Train: epoch: 2 batch: 0/4, loss: 0.667772
2023-06-27 13:04:13.269972 Validation: avg loss: 0.6835, avg acc: 57.1429%
2023-06-27 13:04:40.613288 Train: epoch: 3 batch: 0/4, loss: 0.684359
2023-06-27 13:06:06.965697 Validation: avg loss: 0.6853, avg acc: 57.1429%
2023-06-27 13:06:34.320390 Train: epoch: 4 batch: 0/4, loss: 0.664518
2023-06-27 13:08:00.635158 Validation: avg loss: 0.6830, avg acc: 57.1429%
2023-06-27 13:08:27.965382 Train: epoch: 5 batch: 0/4, loss: 0.648012
2023-06-27 13:09:54.395378 Validation: avg loss: 0.6834, avg acc: 57.1429%
2023-06-27 13:10:21.695506 Train: epoch: 6 batch: 0/4, loss: 0.622020
2023-06-27 13:11:47.946932 Validation: avg loss: 0.6859, avg acc: 57.1429%
2023-06-27 13:12:15.181922 Train: epoch: 7 batch: 0/4, loss: 0.609585
2023-06-27 13:13:41.561458 Validation: avg loss: 0.6824, avg acc: 57.1429%
2023-06-27 13:14:08.777052 Train: epoch: 8 batch: 0/4, loss: 0.554784
2023-06-27 13:15:35.155008 Validation: avg loss: 0.6889, avg acc: 48.5714%
2023-06-27 13:16:02.400262 Train: epoch: 9 batch: 0/4, loss: 0.496770
2023-06-27 13:17:28.802709 Validation: avg loss: 0.6760, avg acc: 65.7143%
2023-06-27 13:17:56.148338 Train: epoch: 10 batch: 0/4, loss: 0.441182
2023-06-27 13:19:22.260881 Validation: avg loss: 0.6602, avg acc: 67.6190%
2023-06-27 13:19:49.537218 Train: epoch: 11 batch: 0/4, loss: 0.355155
2023-06-27 13:21:15.720325 Validation: avg loss: 0.6404, avg acc: 64.7619%
2023-06-27 13:21:42.980084 Train: epoch: 12 batch: 0/4, loss: 0.252484
2023-06-27 13:23:09.091058 Validation: avg loss: 0.5940, avg acc: 71.4286%
2023-06-27 13:23:36.276716 Train: epoch: 13 batch: 0/4, loss: 0.208692
2023-06-27 13:25:02.313005 Validation: avg loss: 0.5678, avg acc: 73.3333%
2023-06-27 13:25:29.525993 Train: epoch: 14 batch: 0/4, loss: 0.123566
2023-06-27 13:26:55.587109 Validation: avg loss: 0.5313, avg acc: 71.4286%
2023-06-27 13:27:22.752260 Train: epoch: 15 batch: 0/4, loss: 0.094163
2023-06-27 13:28:48.798156 Validation: avg loss: 0.5629, avg acc: 73.3333%
2023-06-27 13:29:15.918495 Train: epoch: 16 batch: 0/4, loss: 0.128869
2023-06-27 13:30:42.177941 Validation: avg loss: 0.4869, avg acc: 74.2857%
2023-06-27 13:31:09.371665 Train: epoch: 17 batch: 0/4, loss: 0.052145
2023-06-27 13:32:35.288189 Validation: avg loss: 0.4811, avg acc: 77.1429%
2023-06-27 13:33:02.526205 Train: epoch: 18 batch: 0/4, loss: 0.081217
2023-06-27 13:34:28.685232 Validation: avg loss: 0.5027, avg acc: 79.0476%
2023-06-27 13:34:55.827462 Train: epoch: 19 batch: 0/4, loss: 0.037434
2023-06-27 13:36:21.995335 Validation: avg loss: 0.5522, avg acc: 75.2381%
2023-06-27 13:36:49.182171 Train: epoch: 20 batch: 0/4, loss: 0.018138
2023-06-27 13:38:15.321220 Validation: avg loss: 0.5970, avg acc: 73.3333%
2023-06-27 13:38:42.563163 Train: epoch: 21 batch: 0/4, loss: 0.046510
2023-06-27 13:40:08.856619 Validation: avg loss: 0.6442, avg acc: 76.1905%
2023-06-27 13:40:36.011785 Train: epoch: 22 batch: 0/4, loss: 0.012692
2023-06-27 13:42:02.041543 Validation: avg loss: 0.6929, avg acc: 76.1905%
2023-06-27 13:42:29.300622 Train: epoch: 23 batch: 0/4, loss: 0.012382
2023-06-27 13:43:55.469573 Validation: avg loss: 0.7413, avg acc: 71.4286%
2023-06-27 13:44:22.657185 Train: epoch: 24 batch: 0/4, loss: 0.011344
2023-06-27 13:45:48.869449 Validation: avg loss: 0.7875, avg acc: 73.3333%
2023-06-27 13:46:16.075639 Train: epoch: 25 batch: 0/4, loss: 0.022635
2023-06-27 13:47:42.235744 Validation: avg loss: 0.7924, avg acc: 73.3333%
2023-06-27 13:48:09.432941 Train: epoch: 26 batch: 0/4, loss: 0.009560
2023-06-27 13:49:35.588933 Validation: avg loss: 0.7965, avg acc: 74.2857%
2023-06-27 13:50:02.731198 Train: epoch: 27 batch: 0/4, loss: 0.006484
2023-06-27 13:51:28.970791 Validation: avg loss: 0.8587, avg acc: 74.2857%
2023-06-27 13:51:56.247704 Train: epoch: 28 batch: 0/4, loss: 0.004506
2023-06-27 13:53:22.570553 Validation: avg loss: 0.9319, avg acc: 73.3333%
2023-06-27 13:53:49.732500 Train: epoch: 29 batch: 0/4, loss: 0.004227
2023-06-27 13:55:15.890086 Validation: avg loss: 0.8644, avg acc: 74.2857%
2023-06-27 13:55:43.166997 Train: epoch: 30 batch: 0/4, loss: 0.004787
2023-06-27 13:57:09.235315 Validation: avg loss: 0.8508, avg acc: 72.3810%
2023-06-27 13:57:36.386078 Train: epoch: 31 batch: 0/4, loss: 0.002624
2023-06-27 13:59:02.482710 Validation: avg loss: 0.8385, avg acc: 75.2381%
2023-06-27 13:59:29.719151 Train: epoch: 32 batch: 0/4, loss: 0.003996
2023-06-27 14:00:55.748644 Validation: avg loss: 0.8409, avg acc: 74.2857%
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2023-06-27 14:02:48.968525 Validation: avg loss: 0.8594, avg acc: 74.2857%
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2023-06-27 14:04:42.352338 Validation: avg loss: 0.8764, avg acc: 73.3333%
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2023-06-27 14:06:35.551024 Validation: avg loss: 0.8320, avg acc: 73.3333%
2023-06-27 14:07:02.704332 Train: epoch: 36 batch: 0/4, loss: 0.002351
2023-06-27 14:08:28.965811 Validation: avg loss: 0.8140, avg acc: 73.3333%
2023-06-27 14:08:56.202001 Train: epoch: 37 batch: 0/4, loss: 0.002389
2023-06-27 14:10:22.374434 Validation: avg loss: 0.8012, avg acc: 71.4286%
2023-06-27 14:10:49.581906 Train: epoch: 38 batch: 0/4, loss: 0.002360
2023-06-27 14:12:15.699183 Validation: avg loss: 0.7955, avg acc: 73.3333%
2023-06-27 14:12:42.882802 Train: epoch: 39 batch: 0/4, loss: 0.005763
2023-06-27 14:14:08.871220 Validation: avg loss: 0.7908, avg acc: 72.3810%
2023-06-27 14:14:36.148245 Train: epoch: 40 batch: 0/4, loss: 0.002953
2023-06-27 14:16:02.167597 Validation: avg loss: 0.8192, avg acc: 72.3810%
2023-06-27 14:16:29.353076 Train: epoch: 41 batch: 0/4, loss: 0.001854
2023-06-27 14:17:55.580920 Validation: avg loss: 0.8337, avg acc: 72.3810%
2023-06-27 14:18:22.841567 Train: epoch: 42 batch: 0/4, loss: 0.000968
2023-06-27 14:19:49.351311 Validation: avg loss: 0.8357, avg acc: 73.3333%
2023-06-27 14:20:16.702014 Train: epoch: 43 batch: 0/4, loss: 0.001232
2023-06-27 14:21:42.954946 Validation: avg loss: 0.8496, avg acc: 73.3333%
2023-06-27 14:22:10.272910 Train: epoch: 44 batch: 0/4, loss: 0.001958
2023-06-27 14:23:36.654827 Validation: avg loss: 0.8383, avg acc: 72.3810%
2023-06-27 14:24:03.851239 Train: epoch: 45 batch: 0/4, loss: 0.001643
2023-06-27 14:25:30.184931 Validation: avg loss: 0.8326, avg acc: 71.4286%
2023-06-27 14:25:57.497775 Train: epoch: 46 batch: 0/4, loss: 0.002304
2023-06-27 14:27:23.878822 Validation: avg loss: 0.8342, avg acc: 71.4286%
2023-06-27 14:27:51.095171 Train: epoch: 47 batch: 0/4, loss: 0.001024
2023-06-27 14:29:17.481154 Validation: avg loss: 0.8329, avg acc: 71.4286%
2023-06-27 14:29:44.770846 Train: epoch: 48 batch: 0/4, loss: 0.001529
2023-06-27 14:31:11.200693 Validation: avg loss: 0.8283, avg acc: 70.4762%
2023-06-27 14:31:38.445203 Train: epoch: 49 batch: 0/4, loss: 0.000885
2023-06-27 14:33:04.914596 Validation: avg loss: 0.8007, avg acc: 73.3333%
2023-06-27 14:33:32.124726 Train: epoch: 50 batch: 0/4, loss: 0.000966
2023-06-27 14:34:58.186159 Validation: avg loss: 0.7996, avg acc: 72.3810%
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2023-06-27 14:34:58.219015 cuda
2023-06-27 14:35:25.429647 Train: epoch: 1 batch: 0/4, loss: 0.692641
2023-06-27 14:36:52.028023 Validation: avg loss: 0.6886, avg acc: 58.0952%
2023-06-27 14:37:19.371470 Train: epoch: 2 batch: 0/4, loss: 0.679666
2023-06-27 14:38:45.994577 Validation: avg loss: 0.6812, avg acc: 58.0952%
2023-06-27 14:39:13.268237 Train: epoch: 3 batch: 0/4, loss: 0.679477
2023-06-27 14:40:39.747142 Validation: avg loss: 0.6885, avg acc: 58.0952%
2023-06-27 14:41:07.096706 Train: epoch: 4 batch: 0/4, loss: 0.671980
2023-06-27 14:42:33.828256 Validation: avg loss: 0.6863, avg acc: 58.0952%
2023-06-27 14:43:01.088619 Train: epoch: 5 batch: 0/4, loss: 0.650531
2023-06-27 14:44:27.638675 Validation: avg loss: 0.6861, avg acc: 58.0952%
2023-06-27 14:44:54.990063 Train: epoch: 6 batch: 0/4, loss: 0.641892
2023-06-27 14:46:21.588466 Validation: avg loss: 0.6821, avg acc: 58.0952%
2023-06-27 14:46:48.886209 Train: epoch: 7 batch: 0/4, loss: 0.600969
2023-06-27 14:48:15.496536 Validation: avg loss: 0.7011, avg acc: 41.9048%
2023-06-27 14:48:42.770579 Train: epoch: 8 batch: 0/4, loss: 0.602727
2023-06-27 14:50:09.541234 Validation: avg loss: 0.7364, avg acc: 41.9048%
2023-06-27 14:50:36.771359 Train: epoch: 9 batch: 0/4, loss: 0.546539
2023-06-27 14:52:03.483383 Validation: avg loss: 0.7714, avg acc: 41.9048%
2023-06-27 14:52:30.907359 Train: epoch: 10 batch: 0/4, loss: 0.477320
2023-06-27 14:53:57.804455 Validation: avg loss: 0.8625, avg acc: 41.9048%
2023-06-27 14:54:25.187596 Train: epoch: 11 batch: 0/4, loss: 0.415886
2023-06-27 14:55:51.722946 Validation: avg loss: 0.8547, avg acc: 42.8571%
2023-06-27 14:56:19.059857 Train: epoch: 12 batch: 0/4, loss: 0.343199
2023-06-27 14:57:45.474514 Validation: avg loss: 0.9023, avg acc: 42.8571%
2023-06-27 14:58:12.630153 Train: epoch: 13 batch: 0/4, loss: 0.291277
2023-06-27 14:59:38.986668 Validation: avg loss: 1.0237, avg acc: 41.9048%
2023-06-27 15:00:06.121183 Train: epoch: 14 batch: 0/4, loss: 0.198794
2023-06-27 15:01:32.539287 Validation: avg loss: 0.9636, avg acc: 52.3810%
2023-06-27 15:01:59.739159 Train: epoch: 15 batch: 0/4, loss: 0.120545
2023-06-27 15:03:26.027892 Validation: avg loss: 0.8863, avg acc: 54.2857%
2023-06-27 15:03:53.279023 Train: epoch: 16 batch: 0/4, loss: 0.111169
2023-06-27 15:05:19.701211 Validation: avg loss: 0.9601, avg acc: 54.2857%
2023-06-27 15:05:46.913710 Train: epoch: 17 batch: 0/4, loss: 0.048385
2023-06-27 15:07:13.367950 Validation: avg loss: 0.9682, avg acc: 55.2381%
2023-06-27 15:07:40.522977 Train: epoch: 18 batch: 0/4, loss: 0.034194
2023-06-27 15:09:06.797498 Validation: avg loss: 0.9487, avg acc: 61.9048%
2023-06-27 15:09:33.996084 Train: epoch: 19 batch: 0/4, loss: 0.041916
2023-06-27 15:11:00.495380 Validation: avg loss: 0.9886, avg acc: 60.0000%
2023-06-27 15:11:27.700340 Train: epoch: 20 batch: 0/4, loss: 0.018873
2023-06-27 15:12:54.125217 Validation: avg loss: 1.0086, avg acc: 62.8571%
2023-06-27 15:13:21.393051 Train: epoch: 21 batch: 0/4, loss: 0.013758
2023-06-27 15:14:47.845321 Validation: avg loss: 1.0361, avg acc: 62.8571%
2023-06-27 15:15:15.068215 Train: epoch: 22 batch: 0/4, loss: 0.024895
2023-06-27 15:16:41.458406 Validation: avg loss: 1.0681, avg acc: 56.1905%
2023-06-27 15:17:08.797059 Train: epoch: 23 batch: 0/4, loss: 0.010909
2023-06-27 15:18:35.072484 Validation: avg loss: 1.1441, avg acc: 57.1429%
2023-06-27 15:19:02.312870 Train: epoch: 24 batch: 0/4, loss: 0.021563
2023-06-27 15:20:28.638937 Validation: avg loss: 1.1544, avg acc: 55.2381%
2023-06-27 15:20:55.877058 Train: epoch: 25 batch: 0/4, loss: 0.011905
2023-06-27 15:22:22.190719 Validation: avg loss: 1.1842, avg acc: 61.9048%
2023-06-27 15:22:49.392648 Train: epoch: 26 batch: 0/4, loss: 0.005870
2023-06-27 15:24:15.761457 Validation: avg loss: 1.2231, avg acc: 60.0000%
2023-06-27 15:24:43.009076 Train: epoch: 27 batch: 0/4, loss: 0.007372
2023-06-27 15:26:09.389701 Validation: avg loss: 1.1673, avg acc: 60.0000%
2023-06-27 15:26:36.607810 Train: epoch: 28 batch: 0/4, loss: 0.008340
2023-06-27 15:28:03.076340 Validation: avg loss: 1.1514, avg acc: 60.9524%
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2023-06-27 15:29:56.482834 Validation: avg loss: 1.1984, avg acc: 60.9524%
2023-06-27 15:30:23.675110 Train: epoch: 30 batch: 0/4, loss: 0.003211
2023-06-27 15:31:50.080039 Validation: avg loss: 1.2334, avg acc: 58.0952%
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2023-06-27 15:33:43.538192 Validation: avg loss: 1.3136, avg acc: 57.1429%
2023-06-27 15:34:10.747774 Train: epoch: 32 batch: 0/4, loss: 0.003088
2023-06-27 15:35:37.043014 Validation: avg loss: 1.3489, avg acc: 58.0952%
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2023-06-27 15:37:30.760332 Validation: avg loss: 1.3694, avg acc: 60.0000%
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2023-06-27 15:39:51.540222 Train: epoch: 35 batch: 0/4, loss: 0.002820
2023-06-27 15:41:17.787803 Validation: avg loss: 1.3670, avg acc: 60.0000%
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2023-06-27 15:46:58.706066 Validation: avg loss: 1.3512, avg acc: 60.9524%
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2023-06-27 15:48:52.278203 Validation: avg loss: 1.3603, avg acc: 59.0476%
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2023-06-27 15:50:45.837145 Validation: avg loss: 1.3606, avg acc: 59.0476%
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2023-06-27 15:52:39.442147 Validation: avg loss: 1.3714, avg acc: 60.9524%
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2023-06-27 15:54:32.994759 Validation: avg loss: 1.3837, avg acc: 60.9524%
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2023-06-27 15:56:26.472286 Validation: avg loss: 1.3989, avg acc: 60.9524%
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2023-06-27 15:58:20.247427 Validation: avg loss: 1.4101, avg acc: 60.9524%
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2023-06-27 16:00:13.673967 Validation: avg loss: 1.4165, avg acc: 62.8571%
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2023-06-27 16:02:07.334373 Validation: avg loss: 1.4139, avg acc: 62.8571%
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2023-06-27 16:04:00.916745 Validation: avg loss: 1.4183, avg acc: 62.8571%
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2023-06-27 16:05:54.661361 Validation: avg loss: 1.4129, avg acc: 62.8571%
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2023-06-27 16:09:42.001568 Validation: avg loss: 1.4038, avg acc: 62.8571%
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2023-06-27 16:09:42.034579 cuda
2023-06-27 16:10:09.076819 Train: epoch: 1 batch: 0/4, loss: 0.689472
2023-06-27 16:11:35.174440 Validation: avg loss: 0.6920, avg acc: 56.1905%
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2023-06-27 16:13:28.541905 Validation: avg loss: 0.6863, avg acc: 56.1905%
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2023-06-27 16:15:21.903504 Validation: avg loss: 0.6862, avg acc: 56.1905%
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2023-06-27 16:17:15.391097 Validation: avg loss: 0.6885, avg acc: 56.1905%
2023-06-27 16:17:42.588880 Train: epoch: 5 batch: 0/4, loss: 0.654914
2023-06-27 16:19:08.607998 Validation: avg loss: 0.6970, avg acc: 56.1905%
2023-06-27 16:19:35.835676 Train: epoch: 6 batch: 0/4, loss: 0.635806
2023-06-27 16:21:02.088965 Validation: avg loss: 0.7131, avg acc: 56.1905%
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2023-06-27 16:22:55.424383 Validation: avg loss: 0.7514, avg acc: 56.1905%
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2023-06-27 16:24:48.721804 Validation: avg loss: 0.7544, avg acc: 56.1905%
2023-06-27 16:25:15.907744 Train: epoch: 9 batch: 0/4, loss: 0.547313
2023-06-27 16:26:42.443779 Validation: avg loss: 0.7992, avg acc: 56.1905%
2023-06-27 16:27:09.783645 Train: epoch: 10 batch: 0/4, loss: 0.444450
2023-06-27 16:28:36.109380 Validation: avg loss: 0.8431, avg acc: 56.1905%
2023-06-27 16:29:03.340309 Train: epoch: 11 batch: 0/4, loss: 0.363815
2023-06-27 16:30:29.692076 Validation: avg loss: 0.9948, avg acc: 56.1905%
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2023-06-27 16:32:23.120135 Validation: avg loss: 0.9824, avg acc: 56.1905%
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2023-06-27 16:34:16.507697 Validation: avg loss: 1.0053, avg acc: 56.1905%
2023-06-27 16:34:43.726781 Train: epoch: 14 batch: 0/4, loss: 0.165106
2023-06-27 16:36:09.819922 Validation: avg loss: 0.9196, avg acc: 58.0952%
2023-06-27 16:36:37.091113 Train: epoch: 15 batch: 0/4, loss: 0.102541
2023-06-27 16:38:03.361117 Validation: avg loss: 0.9440, avg acc: 58.0952%
2023-06-27 16:38:30.537668 Train: epoch: 16 batch: 0/4, loss: 0.084653
2023-06-27 16:39:56.678072 Validation: avg loss: 0.9750, avg acc: 60.0000%
2023-06-27 16:40:23.933856 Train: epoch: 17 batch: 0/4, loss: 0.093461
2023-06-27 16:41:50.392128 Validation: avg loss: 0.9532, avg acc: 63.8095%
2023-06-27 16:42:17.568810 Train: epoch: 18 batch: 0/4, loss: 0.040381
2023-06-27 16:43:43.546950 Validation: avg loss: 0.9573, avg acc: 62.8571%
2023-06-27 16:44:10.708190 Train: epoch: 19 batch: 0/4, loss: 0.038573
2023-06-27 16:45:36.914874 Validation: avg loss: 0.9937, avg acc: 67.6190%
2023-06-27 16:46:04.137257 Train: epoch: 20 batch: 0/4, loss: 0.038389
2023-06-27 16:47:30.440530 Validation: avg loss: 1.0789, avg acc: 65.7143%
2023-06-27 16:47:57.631426 Train: epoch: 21 batch: 0/4, loss: 0.010777
2023-06-27 16:49:23.780402 Validation: avg loss: 1.1505, avg acc: 66.6667%
2023-06-27 16:49:51.060769 Train: epoch: 22 batch: 0/4, loss: 0.011703
2023-06-27 16:51:17.385118 Validation: avg loss: 1.2451, avg acc: 62.8571%
2023-06-27 16:51:44.631865 Train: epoch: 23 batch: 0/4, loss: 0.007243
2023-06-27 16:53:10.944555 Validation: avg loss: 1.3300, avg acc: 61.9048%
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2023-06-27 16:55:04.414313 Validation: avg loss: 1.3780, avg acc: 63.8095%
2023-06-27 16:55:31.700853 Train: epoch: 25 batch: 0/4, loss: 0.005980
2023-06-27 16:56:58.079196 Validation: avg loss: 1.3814, avg acc: 65.7143%
2023-06-27 16:57:25.220443 Train: epoch: 26 batch: 0/4, loss: 0.005226
2023-06-27 16:58:51.518167 Validation: avg loss: 1.4504, avg acc: 62.8571%
2023-06-27 16:59:18.711172 Train: epoch: 27 batch: 0/4, loss: 0.005868
2023-06-27 17:00:45.168958 Validation: avg loss: 1.5561, avg acc: 60.0000%
2023-06-27 17:01:12.415606 Train: epoch: 28 batch: 0/4, loss: 0.011277
2023-06-27 17:02:38.557493 Validation: avg loss: 1.5640, avg acc: 60.9524%
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2023-06-27 17:04:31.874819 Validation: avg loss: 1.5746, avg acc: 64.7619%
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2023-06-27 17:08:19.418008 Validation: avg loss: 1.5240, avg acc: 66.6667%
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2023-06-27 17:10:13.234751 Validation: avg loss: 1.4960, avg acc: 66.6667%
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2023-06-27 17:12:07.297788 Validation: avg loss: 1.5235, avg acc: 65.7143%
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2023-06-27 17:16:22.480585 Train: epoch: 36 batch: 0/4, loss: 0.012008
2023-06-27 17:17:48.907176 Validation: avg loss: 1.6271, avg acc: 62.8571%
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2023-06-27 17:19:43.435027 Validation: avg loss: 1.6503, avg acc: 64.7619%
2023-06-27 17:20:10.827029 Train: epoch: 38 batch: 0/4, loss: 0.001793
2023-06-27 17:21:37.592658 Validation: avg loss: 1.6299, avg acc: 65.7143%
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2023-06-27 17:23:31.337687 Validation: avg loss: 1.6197, avg acc: 65.7143%
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2023-06-27 17:25:25.155248 Validation: avg loss: 1.6265, avg acc: 64.7619%
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2023-06-27 17:27:18.837014 Validation: avg loss: 1.6280, avg acc: 65.7143%
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2023-06-27 17:29:12.528662 Validation: avg loss: 1.6349, avg acc: 63.8095%
2023-06-27 17:29:39.697519 Train: epoch: 43 batch: 0/4, loss: 0.001068
2023-06-27 17:31:05.928921 Validation: avg loss: 1.6347, avg acc: 63.8095%
2023-06-27 17:31:33.115344 Train: epoch: 44 batch: 0/4, loss: 0.001226
2023-06-27 17:32:59.337595 Validation: avg loss: 1.6424, avg acc: 63.8095%
2023-06-27 17:33:26.538144 Train: epoch: 45 batch: 0/4, loss: 0.001703
2023-06-27 17:34:52.829378 Validation: avg loss: 1.6544, avg acc: 63.8095%
2023-06-27 17:35:20.005291 Train: epoch: 46 batch: 0/4, loss: 0.000946
2023-06-27 17:36:46.480670 Validation: avg loss: 1.6794, avg acc: 63.8095%
2023-06-27 17:37:13.757354 Train: epoch: 47 batch: 0/4, loss: 0.001093
2023-06-27 17:38:40.118579 Validation: avg loss: 1.6843, avg acc: 63.8095%
2023-06-27 17:39:07.209172 Train: epoch: 48 batch: 0/4, loss: 0.001040
2023-06-27 17:40:33.402375 Validation: avg loss: 1.6992, avg acc: 63.8095%
2023-06-27 17:41:00.565175 Train: epoch: 49 batch: 0/4, loss: 0.001660
2023-06-27 17:42:26.801610 Validation: avg loss: 1.6996, avg acc: 63.8095%
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2023-06-27 17:44:20.225669 Validation: avg loss: 1.7042, avg acc: 63.8095%
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2023-06-27 17:44:20.259056 cuda
2023-06-27 17:44:47.318012 Train: epoch: 1 batch: 0/4, loss: 0.692462
2023-06-27 17:46:13.368410 Validation: avg loss: 0.6884, avg acc: 56.1905%
2023-06-27 17:46:40.701727 Train: epoch: 2 batch: 0/4, loss: 0.687119
2023-06-27 17:48:06.647175 Validation: avg loss: 0.6875, avg acc: 56.1905%
2023-06-27 17:48:33.878785 Train: epoch: 3 batch: 0/4, loss: 0.679808
2023-06-27 17:50:00.037988 Validation: avg loss: 0.6876, avg acc: 56.1905%
2023-06-27 17:50:27.240718 Train: epoch: 4 batch: 0/4, loss: 0.669537
2023-06-27 17:51:53.425597 Validation: avg loss: 0.6869, avg acc: 56.1905%
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2023-06-27 17:53:46.986305 Validation: avg loss: 0.6864, avg acc: 56.1905%
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2023-06-27 17:55:40.354975 Validation: avg loss: 0.6981, avg acc: 45.7143%
2023-06-27 17:56:07.573075 Train: epoch: 7 batch: 0/4, loss: 0.557572
2023-06-27 17:57:33.761935 Validation: avg loss: 0.7235, avg acc: 44.7619%
2023-06-27 17:58:00.987469 Train: epoch: 8 batch: 0/4, loss: 0.503782
2023-06-27 17:59:26.990591 Validation: avg loss: 0.7296, avg acc: 45.7143%
2023-06-27 17:59:54.154153 Train: epoch: 9 batch: 0/4, loss: 0.430477
2023-06-27 18:01:20.293004 Validation: avg loss: 0.7308, avg acc: 44.7619%
2023-06-27 18:01:47.509230 Train: epoch: 10 batch: 0/4, loss: 0.344621
2023-06-27 18:03:13.898079 Validation: avg loss: 0.7507, avg acc: 46.6667%
2023-06-27 18:03:41.085454 Train: epoch: 11 batch: 0/4, loss: 0.230652
2023-06-27 18:05:07.346841 Validation: avg loss: 0.7826, avg acc: 50.4762%
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2023-06-27 18:07:00.623655 Validation: avg loss: 0.8571, avg acc: 54.2857%
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2023-06-27 18:08:53.981172 Validation: avg loss: 0.9937, avg acc: 50.4762%
2023-06-27 18:09:21.252013 Train: epoch: 14 batch: 0/4, loss: 0.058726
2023-06-27 18:10:47.447288 Validation: avg loss: 1.1520, avg acc: 55.2381%
2023-06-27 18:11:14.651218 Train: epoch: 15 batch: 0/4, loss: 0.034530
2023-06-27 18:12:40.912192 Validation: avg loss: 1.3721, avg acc: 57.1429%
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2023-06-27 18:14:34.365256 Validation: avg loss: 1.6733, avg acc: 56.1905%
2023-06-27 18:15:01.640513 Train: epoch: 17 batch: 0/4, loss: 0.018408
2023-06-27 18:16:27.857482 Validation: avg loss: 1.9762, avg acc: 59.0476%
2023-06-27 18:16:55.197711 Train: epoch: 18 batch: 0/4, loss: 0.011542
2023-06-27 18:18:21.396910 Validation: avg loss: 2.1780, avg acc: 58.0952%
2023-06-27 18:18:48.559325 Train: epoch: 19 batch: 0/4, loss: 0.006827
2023-06-27 18:20:14.650541 Validation: avg loss: 2.3833, avg acc: 57.1429%
2023-06-27 18:20:41.846639 Train: epoch: 20 batch: 0/4, loss: 0.007550
2023-06-27 18:22:07.991269 Validation: avg loss: 2.5452, avg acc: 56.1905%
2023-06-27 18:22:35.321455 Train: epoch: 21 batch: 0/4, loss: 0.003803
2023-06-27 18:24:01.698525 Validation: avg loss: 2.7052, avg acc: 56.1905%
2023-06-27 18:24:28.910197 Train: epoch: 22 batch: 0/4, loss: 0.003436
2023-06-27 18:25:54.958886 Validation: avg loss: 2.7932, avg acc: 56.1905%
2023-06-27 18:26:22.136922 Train: epoch: 23 batch: 0/4, loss: 0.002839
2023-06-27 18:27:48.298556 Validation: avg loss: 2.8724, avg acc: 56.1905%
2023-06-27 18:28:15.398475 Train: epoch: 24 batch: 0/4, loss: 0.002590
2023-06-27 18:29:41.649647 Validation: avg loss: 2.9176, avg acc: 55.2381%
2023-06-27 18:30:08.841860 Train: epoch: 25 batch: 0/4, loss: 0.002629
2023-06-27 18:31:34.982084 Validation: avg loss: 2.9597, avg acc: 55.2381%
2023-06-27 18:32:02.118659 Train: epoch: 26 batch: 0/4, loss: 0.002241
2023-06-27 18:33:28.202006 Validation: avg loss: 2.9938, avg acc: 54.2857%
2023-06-27 18:33:55.395506 Train: epoch: 27 batch: 0/4, loss: 0.002135
2023-06-27 18:35:21.534062 Validation: avg loss: 3.0033, avg acc: 54.2857%
2023-06-27 18:35:48.750010 Train: epoch: 28 batch: 0/4, loss: 0.002440
2023-06-27 18:37:15.048227 Validation: avg loss: 3.0195, avg acc: 54.2857%
2023-06-27 18:37:42.216133 Train: epoch: 29 batch: 0/4, loss: 0.002830
2023-06-27 18:39:08.451134 Validation: avg loss: 3.1058, avg acc: 55.2381%
2023-06-27 18:39:35.673894 Train: epoch: 30 batch: 0/4, loss: 0.001845
2023-06-27 18:41:01.823627 Validation: avg loss: 3.1357, avg acc: 55.2381%
2023-06-27 18:41:29.067116 Train: epoch: 31 batch: 0/4, loss: 0.001406
2023-06-27 18:42:55.182929 Validation: avg loss: 3.1482, avg acc: 55.2381%
2023-06-27 18:43:22.385567 Train: epoch: 32 batch: 0/4, loss: 0.001967
2023-06-27 18:44:48.547596 Validation: avg loss: 3.1335, avg acc: 54.2857%
2023-06-27 18:45:15.704825 Train: epoch: 33 batch: 0/4, loss: 0.001378
2023-06-27 18:46:41.760461 Validation: avg loss: 3.1454, avg acc: 54.2857%
2023-06-27 18:47:08.890800 Train: epoch: 34 batch: 0/4, loss: 0.001273
2023-06-27 18:48:35.005441 Validation: avg loss: 3.1303, avg acc: 54.2857%
2023-06-27 18:49:02.248172 Train: epoch: 35 batch: 0/4, loss: 0.001277
2023-06-27 18:50:28.420519 Validation: avg loss: 3.1401, avg acc: 54.2857%
2023-06-27 18:50:55.663238 Train: epoch: 36 batch: 0/4, loss: 0.002169
2023-06-27 18:52:21.812087 Validation: avg loss: 3.1882, avg acc: 54.2857%
2023-06-27 18:52:49.104837 Train: epoch: 37 batch: 0/4, loss: 0.001070
2023-06-27 18:54:15.332128 Validation: avg loss: 3.1880, avg acc: 54.2857%
2023-06-27 18:54:42.504689 Train: epoch: 38 batch: 0/4, loss: 0.001077
2023-06-27 18:56:08.545899 Validation: avg loss: 3.1843, avg acc: 54.2857%
2023-06-27 18:56:35.712404 Train: epoch: 39 batch: 0/4, loss: 0.001067
2023-06-27 18:58:01.987544 Validation: avg loss: 3.1656, avg acc: 54.2857%
2023-06-27 18:58:29.149148 Train: epoch: 40 batch: 0/4, loss: 0.001175
2023-06-27 18:59:55.206062 Validation: avg loss: 3.1442, avg acc: 54.2857%
2023-06-27 19:00:22.433386 Train: epoch: 41 batch: 0/4, loss: 0.001228
2023-06-27 19:01:48.560550 Validation: avg loss: 3.1588, avg acc: 54.2857%
2023-06-27 19:02:15.726659 Train: epoch: 42 batch: 0/4, loss: 0.001126
2023-06-27 19:03:41.921913 Validation: avg loss: 3.1466, avg acc: 54.2857%
2023-06-27 19:04:09.047518 Train: epoch: 43 batch: 0/4, loss: 0.000873
2023-06-27 19:05:35.307454 Validation: avg loss: 3.1636, avg acc: 55.2381%
2023-06-27 19:06:02.482694 Train: epoch: 44 batch: 0/4, loss: 0.000813
2023-06-27 19:07:28.550549 Validation: avg loss: 3.1797, avg acc: 55.2381%
2023-06-27 19:07:55.712128 Train: epoch: 45 batch: 0/4, loss: 0.000993
2023-06-27 19:09:21.900997 Validation: avg loss: 3.2025, avg acc: 55.2381%
2023-06-27 19:09:49.051093 Train: epoch: 46 batch: 0/4, loss: 0.000823
2023-06-27 19:11:14.980996 Validation: avg loss: 3.2075, avg acc: 54.2857%
2023-06-27 19:11:42.259114 Train: epoch: 47 batch: 0/4, loss: 0.001268
2023-06-27 19:13:08.400821 Validation: avg loss: 3.1878, avg acc: 54.2857%
2023-06-27 19:13:35.530120 Train: epoch: 48 batch: 0/4, loss: 0.000953
2023-06-27 19:15:01.682799 Validation: avg loss: 3.1395, avg acc: 54.2857%
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2023-06-27 19:16:54.950132 Validation: avg loss: 3.1137, avg acc: 53.3333%
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2023-06-27 19:18:48.165152 Validation: avg loss: 3.1197, avg acc: 54.2857%
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2023-06-27 19:18:48.198217 cuda
2023-06-27 19:19:15.294061 Train: epoch: 1 batch: 0/4, loss: 0.692022
2023-06-27 19:20:41.277842 Validation: avg loss: 0.6873, avg acc: 58.0952%
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2023-06-27 19:22:34.606377 Validation: avg loss: 0.6854, avg acc: 58.0952%
2023-06-27 19:23:01.844717 Train: epoch: 3 batch: 0/4, loss: 0.670388
2023-06-27 19:24:27.983871 Validation: avg loss: 0.6884, avg acc: 58.0952%
2023-06-27 19:24:55.143142 Train: epoch: 4 batch: 0/4, loss: 0.697613
2023-06-27 19:26:21.439926 Validation: avg loss: 0.6845, avg acc: 58.0952%
2023-06-27 19:26:48.654835 Train: epoch: 5 batch: 0/4, loss: 0.643741
2023-06-27 19:28:14.701148 Validation: avg loss: 0.6798, avg acc: 58.0952%
2023-06-27 19:28:41.855906 Train: epoch: 6 batch: 0/4, loss: 0.639591
2023-06-27 19:30:08.016620 Validation: avg loss: 0.6894, avg acc: 58.0952%
2023-06-27 19:30:35.337619 Train: epoch: 7 batch: 0/4, loss: 0.604846
2023-06-27 19:32:01.530659 Validation: avg loss: 0.7069, avg acc: 41.9048%
2023-06-27 19:32:28.813132 Train: epoch: 8 batch: 0/4, loss: 0.574580
2023-06-27 19:33:55.009578 Validation: avg loss: 0.6978, avg acc: 42.8571%
2023-06-27 19:34:22.248886 Train: epoch: 9 batch: 0/4, loss: 0.520313
2023-06-27 19:35:48.574277 Validation: avg loss: 0.7286, avg acc: 41.9048%
2023-06-27 19:36:15.771553 Train: epoch: 10 batch: 0/4, loss: 0.508012
2023-06-27 19:37:42.066795 Validation: avg loss: 0.7102, avg acc: 42.8571%
2023-06-27 19:38:09.316067 Train: epoch: 11 batch: 0/4, loss: 0.445963
2023-06-27 19:39:35.463861 Validation: avg loss: 0.7605, avg acc: 42.8571%
2023-06-27 19:40:02.659232 Train: epoch: 12 batch: 0/4, loss: 0.274907
2023-06-27 19:41:28.589119 Validation: avg loss: 0.8236, avg acc: 44.7619%
2023-06-27 19:41:55.725336 Train: epoch: 13 batch: 0/4, loss: 0.229953
2023-06-27 19:43:21.862888 Validation: avg loss: 0.8172, avg acc: 50.4762%
2023-06-27 19:43:49.058039 Train: epoch: 14 batch: 0/4, loss: 0.142196
2023-06-27 19:45:15.064675 Validation: avg loss: 0.8579, avg acc: 53.3333%
2023-06-27 19:45:42.330094 Train: epoch: 15 batch: 0/4, loss: 0.099136
2023-06-27 19:47:08.432933 Validation: avg loss: 0.9230, avg acc: 54.2857%
2023-06-27 19:47:35.601256 Train: epoch: 16 batch: 0/4, loss: 0.065903
2023-06-27 19:49:01.525098 Validation: avg loss: 0.8951, avg acc: 62.8571%
2023-06-27 19:49:28.732127 Train: epoch: 17 batch: 0/4, loss: 0.034419
2023-06-27 19:50:54.735994 Validation: avg loss: 0.9322, avg acc: 66.6667%
2023-06-27 19:51:21.915114 Train: epoch: 18 batch: 0/4, loss: 0.031674
2023-06-27 19:52:47.963015 Validation: avg loss: 0.9627, avg acc: 67.6190%
2023-06-27 19:53:15.140215 Train: epoch: 19 batch: 0/4, loss: 0.035861
2023-06-27 19:54:41.236262 Validation: avg loss: 1.0616, avg acc: 64.7619%
2023-06-27 19:55:08.476282 Train: epoch: 20 batch: 0/4, loss: 0.017844
2023-06-27 19:56:34.404703 Validation: avg loss: 1.0661, avg acc: 64.7619%
2023-06-27 19:57:01.567031 Train: epoch: 21 batch: 0/4, loss: 0.028972
2023-06-27 19:58:27.737198 Validation: avg loss: 1.0875, avg acc: 66.6667%
2023-06-27 19:58:54.918224 Train: epoch: 22 batch: 0/4, loss: 0.022829
2023-06-27 20:00:20.949224 Validation: avg loss: 1.2039, avg acc: 64.7619%
2023-06-27 20:00:48.312823 Train: epoch: 23 batch: 0/4, loss: 0.010412
2023-06-27 20:02:14.748642 Validation: avg loss: 1.2402, avg acc: 66.6667%
2023-06-27 20:02:42.089930 Train: epoch: 24 batch: 0/4, loss: 0.017833
2023-06-27 20:04:08.397588 Validation: avg loss: 1.2312, avg acc: 69.5238%
2023-06-27 20:04:35.753850 Train: epoch: 25 batch: 0/4, loss: 0.007784
2023-06-27 20:06:02.120864 Validation: avg loss: 1.2695, avg acc: 67.6190%
2023-06-27 20:06:29.382582 Train: epoch: 26 batch: 0/4, loss: 0.007875
2023-06-27 20:07:55.777708 Validation: avg loss: 1.3071, avg acc: 70.4762%
2023-06-27 20:08:23.092892 Train: epoch: 27 batch: 0/4, loss: 0.004158
2023-06-27 20:09:49.568930 Validation: avg loss: 1.3470, avg acc: 68.5714%
2023-06-27 20:10:16.842231 Train: epoch: 28 batch: 0/4, loss: 0.004838
2023-06-27 20:11:43.335726 Validation: avg loss: 1.3752, avg acc: 69.5238%
2023-06-27 20:12:10.647031 Train: epoch: 29 batch: 0/4, loss: 0.002664
2023-06-27 20:13:36.900521 Validation: avg loss: 1.3785, avg acc: 69.5238%
2023-06-27 20:14:04.162619 Train: epoch: 30 batch: 0/4, loss: 0.002635
2023-06-27 20:15:30.427153 Validation: avg loss: 1.4110, avg acc: 69.5238%
2023-06-27 20:15:57.495602 Train: epoch: 31 batch: 0/4, loss: 0.002836
2023-06-27 20:17:23.502943 Validation: avg loss: 1.4009, avg acc: 67.6190%
2023-06-27 20:17:50.880211 Train: epoch: 32 batch: 0/4, loss: 0.003082
2023-06-27 20:19:17.376544 Validation: avg loss: 1.3800, avg acc: 66.6667%
2023-06-27 20:19:44.714264 Train: epoch: 33 batch: 0/4, loss: 0.002626
2023-06-27 20:21:10.996699 Validation: avg loss: 1.3879, avg acc: 65.7143%
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2023-06-27 20:23:04.636640 Validation: avg loss: 1.3688, avg acc: 65.7143%
2023-06-27 20:23:32.059078 Train: epoch: 35 batch: 0/4, loss: 0.004321
2023-06-27 20:24:58.438434 Validation: avg loss: 1.3742, avg acc: 64.7619%
2023-06-27 20:25:25.737069 Train: epoch: 36 batch: 0/4, loss: 0.001553
2023-06-27 20:26:52.131139 Validation: avg loss: 1.3750, avg acc: 64.7619%
2023-06-27 20:27:19.435960 Train: epoch: 37 batch: 0/4, loss: 0.001395
2023-06-27 20:28:45.787530 Validation: avg loss: 1.3801, avg acc: 65.7143%
2023-06-27 20:29:13.090991 Train: epoch: 38 batch: 0/4, loss: 0.001076
2023-06-27 20:30:39.336450 Validation: avg loss: 1.3961, avg acc: 65.7143%
2023-06-27 20:31:06.539441 Train: epoch: 39 batch: 0/4, loss: 0.001392
2023-06-27 20:32:32.702476 Validation: avg loss: 1.4081, avg acc: 65.7143%
2023-06-27 20:32:59.901209 Train: epoch: 40 batch: 0/4, loss: 0.000945
2023-06-27 20:34:25.891464 Validation: avg loss: 1.4195, avg acc: 65.7143%
2023-06-27 20:34:53.028886 Train: epoch: 41 batch: 0/4, loss: 0.000940
2023-06-27 20:36:19.227416 Validation: avg loss: 1.4202, avg acc: 64.7619%
2023-06-27 20:36:46.355918 Train: epoch: 42 batch: 0/4, loss: 0.000859
2023-06-27 20:38:12.345681 Validation: avg loss: 1.4267, avg acc: 65.7143%
2023-06-27 20:38:39.564975 Train: epoch: 43 batch: 0/4, loss: 0.000871
2023-06-27 20:40:05.590265 Validation: avg loss: 1.4332, avg acc: 64.7619%
2023-06-27 20:40:32.795884 Train: epoch: 44 batch: 0/4, loss: 0.002657
2023-06-27 20:41:58.871446 Validation: avg loss: 1.4451, avg acc: 66.6667%
2023-06-27 20:42:26.156905 Train: epoch: 45 batch: 0/4, loss: 0.000708
2023-06-27 20:43:52.503323 Validation: avg loss: 1.4392, avg acc: 67.6190%
2023-06-27 20:44:19.847648 Train: epoch: 46 batch: 0/4, loss: 0.000994
2023-06-27 20:45:46.028815 Validation: avg loss: 1.4327, avg acc: 67.6190%
2023-06-27 20:46:13.284179 Train: epoch: 47 batch: 0/4, loss: 0.000703
2023-06-27 20:47:39.801806 Validation: avg loss: 1.4274, avg acc: 67.6190%
2023-06-27 20:48:06.965401 Train: epoch: 48 batch: 0/4, loss: 0.000721
2023-06-27 20:49:33.322803 Validation: avg loss: 1.4285, avg acc: 67.6190%
2023-06-27 20:50:00.600342 Train: epoch: 49 batch: 0/4, loss: 0.001099
2023-06-27 20:51:27.066750 Validation: avg loss: 1.4424, avg acc: 66.6667%
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2023-06-27 20:53:20.596007 Validation: avg loss: 1.4568, avg acc: 65.7143%
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2023-06-27 20:53:20.629151 cuda
2023-06-27 20:53:47.748434 Train: epoch: 1 batch: 0/4, loss: 0.692955
2023-06-27 20:55:13.964674 Validation: avg loss: 0.6897, avg acc: 56.1905%
2023-06-27 20:55:41.177435 Train: epoch: 2 batch: 0/4, loss: 0.675517
2023-06-27 20:57:07.274298 Validation: avg loss: 0.6863, avg acc: 56.1905%
2023-06-27 20:57:34.461939 Train: epoch: 3 batch: 0/4, loss: 0.675015
2023-06-27 20:59:00.491545 Validation: avg loss: 0.6910, avg acc: 56.1905%
2023-06-27 20:59:27.647846 Train: epoch: 4 batch: 0/4, loss: 0.674206
2023-06-27 21:00:53.827621 Validation: avg loss: 0.6909, avg acc: 56.1905%
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2023-06-27 21:02:47.200772 Validation: avg loss: 0.6861, avg acc: 56.1905%
2023-06-27 21:03:14.390030 Train: epoch: 6 batch: 0/4, loss: 0.621112
2023-06-27 21:04:40.294124 Validation: avg loss: 0.6872, avg acc: 56.1905%
2023-06-27 21:05:07.527156 Train: epoch: 7 batch: 0/4, loss: 0.625907
2023-06-27 21:06:33.555837 Validation: avg loss: 0.6899, avg acc: 53.3333%
2023-06-27 21:07:00.698690 Train: epoch: 8 batch: 0/4, loss: 0.516206
2023-06-27 21:08:26.841992 Validation: avg loss: 0.6903, avg acc: 57.1429%
2023-06-27 21:08:54.105375 Train: epoch: 9 batch: 0/4, loss: 0.444898
2023-06-27 21:10:20.483318 Validation: avg loss: 0.7007, avg acc: 44.7619%
2023-06-27 21:10:47.754366 Train: epoch: 10 batch: 0/4, loss: 0.370775
2023-06-27 21:12:14.150308 Validation: avg loss: 0.6906, avg acc: 59.0476%
2023-06-27 21:12:41.539462 Train: epoch: 11 batch: 0/4, loss: 0.356873
2023-06-27 21:14:08.025503 Validation: avg loss: 0.6832, avg acc: 60.0000%
2023-06-27 21:14:35.276802 Train: epoch: 12 batch: 0/4, loss: 0.223474
2023-06-27 21:16:01.640456 Validation: avg loss: 0.7128, avg acc: 56.1905%
2023-06-27 21:16:28.932089 Train: epoch: 13 batch: 0/4, loss: 0.187091
2023-06-27 21:17:55.253539 Validation: avg loss: 0.7330, avg acc: 57.1429%
2023-06-27 21:18:22.535979 Train: epoch: 14 batch: 0/4, loss: 0.104829
2023-06-27 21:19:49.039828 Validation: avg loss: 0.8461, avg acc: 55.2381%
2023-06-27 21:20:16.279672 Train: epoch: 15 batch: 0/4, loss: 0.067174
2023-06-27 21:21:42.707410 Validation: avg loss: 0.9349, avg acc: 53.3333%
2023-06-27 21:22:10.102342 Train: epoch: 16 batch: 0/4, loss: 0.057731
2023-06-27 21:23:36.458363 Validation: avg loss: 1.0388, avg acc: 55.2381%
2023-06-27 21:24:03.725265 Train: epoch: 17 batch: 0/4, loss: 0.022758
2023-06-27 21:25:30.213156 Validation: avg loss: 1.1726, avg acc: 52.3810%
2023-06-27 21:25:57.543603 Train: epoch: 18 batch: 0/4, loss: 0.017001
2023-06-27 21:27:24.030243 Validation: avg loss: 1.4126, avg acc: 52.3810%
2023-06-27 21:27:51.378713 Train: epoch: 19 batch: 0/4, loss: 0.017968
2023-06-27 21:29:17.739281 Validation: avg loss: 1.5709, avg acc: 49.5238%
2023-06-27 21:29:45.028343 Train: epoch: 20 batch: 0/4, loss: 0.022907
2023-06-27 21:31:11.377903 Validation: avg loss: 1.6647, avg acc: 50.4762%
2023-06-27 21:31:38.682689 Train: epoch: 21 batch: 0/4, loss: 0.011941
2023-06-27 21:33:05.134857 Validation: avg loss: 1.7595, avg acc: 52.3810%
2023-06-27 21:33:32.525653 Train: epoch: 22 batch: 0/4, loss: 0.008407
2023-06-27 21:34:58.983933 Validation: avg loss: 1.7680, avg acc: 51.4286%
2023-06-27 21:35:26.219816 Train: epoch: 23 batch: 0/4, loss: 0.014117
2023-06-27 21:36:52.456195 Validation: avg loss: 1.7327, avg acc: 53.3333%
2023-06-27 21:37:19.758374 Train: epoch: 24 batch: 0/4, loss: 0.009515
2023-06-27 21:38:46.095581 Validation: avg loss: 1.7344, avg acc: 53.3333%
2023-06-27 21:39:13.278819 Train: epoch: 25 batch: 0/4, loss: 0.008577
2023-06-27 21:40:39.589178 Validation: avg loss: 1.7697, avg acc: 51.4286%
2023-06-27 21:41:06.756922 Train: epoch: 26 batch: 0/4, loss: 0.003460
2023-06-27 21:42:32.847901 Validation: avg loss: 1.7216, avg acc: 48.5714%
2023-06-27 21:43:00.057556 Train: epoch: 27 batch: 0/4, loss: 0.006079
2023-06-27 21:44:26.144239 Validation: avg loss: 1.7539, avg acc: 49.5238%
2023-06-27 21:44:53.260106 Train: epoch: 28 batch: 0/4, loss: 0.015600
2023-06-27 21:46:19.290912 Validation: avg loss: 1.8366, avg acc: 54.2857%
2023-06-27 21:46:46.481769 Train: epoch: 29 batch: 0/4, loss: 0.004267
2023-06-27 21:48:12.409084 Validation: avg loss: 1.9022, avg acc: 52.3810%
2023-06-27 21:48:39.532274 Train: epoch: 30 batch: 0/4, loss: 0.005097
2023-06-27 21:50:05.514752 Validation: avg loss: 2.0331, avg acc: 47.6190%
2023-06-27 21:50:32.729193 Train: epoch: 31 batch: 0/4, loss: 0.003991
2023-06-27 21:51:58.762192 Validation: avg loss: 2.0587, avg acc: 49.5238%
2023-06-27 21:52:25.892686 Train: epoch: 32 batch: 0/4, loss: 0.011430
2023-06-27 21:53:51.739113 Validation: avg loss: 2.0254, avg acc: 49.5238%
2023-06-27 21:54:18.919470 Train: epoch: 33 batch: 0/4, loss: 0.009412
2023-06-27 21:55:44.906644 Validation: avg loss: 1.9933, avg acc: 51.4286%
2023-06-27 21:56:12.232801 Train: epoch: 34 batch: 0/4, loss: 0.006466
2023-06-27 21:57:38.328352 Validation: avg loss: 1.9766, avg acc: 54.2857%
2023-06-27 21:58:05.579668 Train: epoch: 35 batch: 0/4, loss: 0.003181
2023-06-27 21:59:31.524106 Validation: avg loss: 1.9970, avg acc: 54.2857%
2023-06-27 21:59:58.790838 Train: epoch: 36 batch: 0/4, loss: 0.003229
2023-06-27 22:01:24.934451 Validation: avg loss: 1.9907, avg acc: 51.4286%
2023-06-27 22:01:52.109059 Train: epoch: 37 batch: 0/4, loss: 0.002149
2023-06-27 22:03:18.531111 Validation: avg loss: 1.9838, avg acc: 53.3333%
2023-06-27 22:03:45.800694 Train: epoch: 38 batch: 0/4, loss: 0.001734
2023-06-27 22:05:12.074094 Validation: avg loss: 1.9819, avg acc: 53.3333%
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2023-06-27 22:07:05.682114 Validation: avg loss: 1.9822, avg acc: 54.2857%
2023-06-27 22:07:32.946940 Train: epoch: 40 batch: 0/4, loss: 0.001835
2023-06-27 22:08:59.288087 Validation: avg loss: 1.9775, avg acc: 52.3810%
2023-06-27 22:09:26.574157 Train: epoch: 41 batch: 0/4, loss: 0.001363
2023-06-27 22:10:52.773243 Validation: avg loss: 1.9909, avg acc: 51.4286%
2023-06-27 22:11:19.958399 Train: epoch: 42 batch: 0/4, loss: 0.007470
2023-06-27 22:12:45.994189 Validation: avg loss: 2.0147, avg acc: 54.2857%
2023-06-27 22:13:13.146665 Train: epoch: 43 batch: 0/4, loss: 0.001582
2023-06-27 22:14:39.139268 Validation: avg loss: 2.0680, avg acc: 53.3333%
2023-06-27 22:15:06.318827 Train: epoch: 44 batch: 0/4, loss: 0.001251
2023-06-27 22:16:32.359512 Validation: avg loss: 2.1104, avg acc: 51.4286%
2023-06-27 22:16:59.396425 Train: epoch: 45 batch: 0/4, loss: 0.001317
2023-06-27 22:18:25.293875 Validation: avg loss: 2.1194, avg acc: 54.2857%
2023-06-27 22:18:52.530135 Train: epoch: 46 batch: 0/4, loss: 0.001396
2023-06-27 22:20:18.375591 Validation: avg loss: 2.1648, avg acc: 54.2857%
2023-06-27 22:20:45.523274 Train: epoch: 47 batch: 0/4, loss: 0.000788
2023-06-27 22:22:11.602016 Validation: avg loss: 2.1987, avg acc: 52.3810%
2023-06-27 22:22:38.868759 Train: epoch: 48 batch: 0/4, loss: 0.001002
2023-06-27 22:24:05.110313 Validation: avg loss: 2.2087, avg acc: 51.4286%
2023-06-27 22:24:32.347761 Train: epoch: 49 batch: 0/4, loss: 0.001327
2023-06-27 22:25:58.485472 Validation: avg loss: 2.2049, avg acc: 51.4286%
2023-06-27 22:26:25.746957 Train: epoch: 50 batch: 0/4, loss: 0.001763
2023-06-27 22:27:51.799245 Validation: avg loss: 2.1766, avg acc: 52.3810%
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2023-06-27 22:27:51.832053 cuda
2023-06-27 22:28:18.966184 Train: epoch: 1 batch: 0/4, loss: 0.691489
2023-06-27 22:29:45.254707 Validation: avg loss: 0.6880, avg acc: 56.1905%
2023-06-27 22:30:12.419829 Train: epoch: 2 batch: 0/4, loss: 0.687985
2023-06-27 22:31:38.632632 Validation: avg loss: 0.6870, avg acc: 56.1905%
2023-06-27 22:32:05.856508 Train: epoch: 3 batch: 0/4, loss: 0.664902
2023-06-27 22:33:32.283738 Validation: avg loss: 0.6854, avg acc: 56.1905%
2023-06-27 22:33:59.618473 Train: epoch: 4 batch: 0/4, loss: 0.652908
2023-06-27 22:35:25.952811 Validation: avg loss: 0.6924, avg acc: 56.1905%
2023-06-27 22:35:53.276123 Train: epoch: 5 batch: 0/4, loss: 0.661903
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2023-06-27 22:37:46.925452 Train: epoch: 6 batch: 0/4, loss: 0.633644
2023-06-27 22:39:13.350616 Validation: avg loss: 0.6886, avg acc: 57.1429%
2023-06-27 22:39:40.541397 Train: epoch: 7 batch: 0/4, loss: 0.532679
2023-06-27 22:41:06.927873 Validation: avg loss: 0.7044, avg acc: 57.1429%
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2023-06-27 22:43:00.692394 Validation: avg loss: 0.6965, avg acc: 57.1429%
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2023-06-27 22:44:54.412808 Validation: avg loss: 0.6885, avg acc: 57.1429%
2023-06-27 22:45:21.638308 Train: epoch: 10 batch: 0/4, loss: 0.307382
2023-06-27 22:46:48.002345 Validation: avg loss: 0.7254, avg acc: 57.1429%
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2023-06-27 22:48:41.800331 Validation: avg loss: 0.7208, avg acc: 56.1905%
2023-06-27 22:49:09.041666 Train: epoch: 12 batch: 0/4, loss: 0.159419
2023-06-27 22:50:35.559538 Validation: avg loss: 0.7355, avg acc: 59.0476%
2023-06-27 22:51:02.845616 Train: epoch: 13 batch: 0/4, loss: 0.087809
2023-06-27 22:52:29.205000 Validation: avg loss: 0.8750, avg acc: 61.9048%
2023-06-27 22:52:56.330139 Train: epoch: 14 batch: 0/4, loss: 0.058570
2023-06-27 22:54:22.825224 Validation: avg loss: 1.0395, avg acc: 55.2381%
2023-06-27 22:54:50.090389 Train: epoch: 15 batch: 0/4, loss: 0.030791
2023-06-27 22:56:16.468342 Validation: avg loss: 1.2059, avg acc: 56.1905%
2023-06-27 22:56:43.636218 Train: epoch: 16 batch: 0/4, loss: 0.020157
2023-06-27 22:58:09.832051 Validation: avg loss: 1.3417, avg acc: 55.2381%
2023-06-27 22:58:37.210557 Train: epoch: 17 batch: 0/4, loss: 0.016194
2023-06-27 23:00:03.726469 Validation: avg loss: 1.4593, avg acc: 56.1905%
2023-06-27 23:00:30.962348 Train: epoch: 18 batch: 0/4, loss: 0.009612
2023-06-27 23:01:57.414453 Validation: avg loss: 1.5738, avg acc: 56.1905%
2023-06-27 23:02:24.669349 Train: epoch: 19 batch: 0/4, loss: 0.008854
2023-06-27 23:03:51.020380 Validation: avg loss: 1.6681, avg acc: 55.2381%
2023-06-27 23:04:18.287586 Train: epoch: 20 batch: 0/4, loss: 0.006112
2023-06-27 23:05:44.749436 Validation: avg loss: 1.8148, avg acc: 57.1429%
2023-06-27 23:06:11.975419 Train: epoch: 21 batch: 0/4, loss: 0.004537
2023-06-27 23:07:38.478337 Validation: avg loss: 1.9523, avg acc: 58.0952%
2023-06-27 23:08:05.776003 Train: epoch: 22 batch: 0/4, loss: 0.006090
2023-06-27 23:09:32.229313 Validation: avg loss: 2.0454, avg acc: 55.2381%
2023-06-27 23:09:59.441040 Train: epoch: 23 batch: 0/4, loss: 0.004283
2023-06-27 23:11:25.880682 Validation: avg loss: 2.1055, avg acc: 55.2381%
2023-06-27 23:11:53.152548 Train: epoch: 24 batch: 0/4, loss: 0.002649
2023-06-27 23:13:19.607935 Validation: avg loss: 2.1385, avg acc: 55.2381%
2023-06-27 23:13:46.839895 Train: epoch: 25 batch: 0/4, loss: 0.003728
2023-06-27 23:15:13.402442 Validation: avg loss: 2.1422, avg acc: 55.2381%
2023-06-27 23:15:40.546642 Train: epoch: 26 batch: 0/4, loss: 0.002831
2023-06-27 23:17:06.760130 Validation: avg loss: 2.1652, avg acc: 57.1429%
2023-06-27 23:17:34.000658 Train: epoch: 27 batch: 0/4, loss: 0.002195
2023-06-27 23:19:00.391148 Validation: avg loss: 2.1812, avg acc: 56.1905%
2023-06-27 23:19:27.601230 Train: epoch: 28 batch: 0/4, loss: 0.001955
2023-06-27 23:20:53.949475 Validation: avg loss: 2.1915, avg acc: 56.1905%
2023-06-27 23:21:21.150679 Train: epoch: 29 batch: 0/4, loss: 0.001778
2023-06-27 23:22:47.303541 Validation: avg loss: 2.2282, avg acc: 56.1905%
2023-06-27 23:23:14.464922 Train: epoch: 30 batch: 0/4, loss: 0.001639
2023-06-27 23:24:40.867091 Validation: avg loss: 2.2540, avg acc: 55.2381%
2023-06-27 23:25:08.050482 Train: epoch: 31 batch: 0/4, loss: 0.001533
2023-06-27 23:26:34.576261 Validation: avg loss: 2.2137, avg acc: 55.2381%
2023-06-27 23:27:01.768863 Train: epoch: 32 batch: 0/4, loss: 0.001555
2023-06-27 23:28:27.999260 Validation: avg loss: 2.2468, avg acc: 55.2381%
2023-06-27 23:28:55.225629 Train: epoch: 33 batch: 0/4, loss: 0.001706
2023-06-27 23:30:21.681247 Validation: avg loss: 2.3247, avg acc: 55.2381%
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2023-06-27 23:32:15.608792 Validation: avg loss: 2.3080, avg acc: 55.2381%
2023-06-27 23:32:42.986142 Train: epoch: 35 batch: 0/4, loss: 0.001306
2023-06-27 23:34:09.402665 Validation: avg loss: 2.3443, avg acc: 55.2381%
2023-06-27 23:34:36.786915 Train: epoch: 36 batch: 0/4, loss: 0.001624
2023-06-27 23:36:02.883464 Validation: avg loss: 2.3030, avg acc: 55.2381%
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2023-06-27 23:37:56.563202 Validation: avg loss: 2.3256, avg acc: 55.2381%
2023-06-27 23:38:23.828423 Train: epoch: 38 batch: 0/4, loss: 0.001632
2023-06-27 23:39:49.910239 Validation: avg loss: 2.3233, avg acc: 55.2381%
2023-06-27 23:40:17.081929 Train: epoch: 39 batch: 0/4, loss: 0.001192
2023-06-27 23:41:43.311819 Validation: avg loss: 2.3452, avg acc: 55.2381%
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2023-06-27 23:43:36.513161 Validation: avg loss: 2.3589, avg acc: 55.2381%
2023-06-27 23:44:03.781847 Train: epoch: 41 batch: 0/4, loss: 0.000959
2023-06-27 23:45:29.998557 Validation: avg loss: 2.3532, avg acc: 55.2381%
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2023-06-27 23:47:23.613199 Validation: avg loss: 2.3384, avg acc: 55.2381%
2023-06-27 23:47:50.893525 Train: epoch: 43 batch: 0/4, loss: 0.001390
2023-06-27 23:49:17.249639 Validation: avg loss: 2.3514, avg acc: 55.2381%
2023-06-27 23:49:44.635435 Train: epoch: 44 batch: 0/4, loss: 0.000905
2023-06-27 23:51:11.195395 Validation: avg loss: 2.3539, avg acc: 55.2381%
2023-06-27 23:51:38.443645 Train: epoch: 45 batch: 0/4, loss: 0.001156
2023-06-27 23:53:04.607505 Validation: avg loss: 2.3513, avg acc: 55.2381%
2023-06-27 23:53:31.901613 Train: epoch: 46 batch: 0/4, loss: 0.000737
2023-06-27 23:54:58.050324 Validation: avg loss: 2.3489, avg acc: 55.2381%
2023-06-27 23:55:25.292960 Train: epoch: 47 batch: 0/4, loss: 0.000835
2023-06-27 23:56:51.409959 Validation: avg loss: 2.2573, avg acc: 55.2381%
2023-06-27 23:57:18.794972 Train: epoch: 48 batch: 0/4, loss: 0.000729
2023-06-27 23:58:44.903528 Validation: avg loss: 2.2249, avg acc: 55.2381%
2023-06-27 23:59:12.225103 Train: epoch: 49 batch: 0/4, loss: 0.001977
2023-06-28 00:00:38.421762 Validation: avg loss: 2.3659, avg acc: 52.3810%
2023-06-28 00:01:05.682615 Train: epoch: 50 batch: 0/4, loss: 0.000803
2023-06-28 00:02:31.868851 Validation: avg loss: 2.3760, avg acc: 52.3810%
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2023-06-28 00:02:31.901807 cuda
2023-06-28 00:02:59.086909 Train: epoch: 1 batch: 0/4, loss: 0.691504
2023-06-28 00:04:25.173936 Validation: avg loss: 0.6903, avg acc: 54.2857%
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2023-06-28 00:06:18.505983 Validation: avg loss: 0.6905, avg acc: 54.2857%
2023-06-28 00:06:45.764625 Train: epoch: 3 batch: 0/4, loss: 0.689255
2023-06-28 00:08:11.983660 Validation: avg loss: 0.6896, avg acc: 54.2857%
2023-06-28 00:08:39.087900 Train: epoch: 4 batch: 0/4, loss: 0.657609
2023-06-28 00:10:05.053431 Validation: avg loss: 0.6920, avg acc: 54.2857%
2023-06-28 00:10:32.297413 Train: epoch: 5 batch: 0/4, loss: 0.663413
2023-06-28 00:11:58.439684 Validation: avg loss: 0.6977, avg acc: 45.7143%
2023-06-28 00:12:25.603823 Train: epoch: 6 batch: 0/4, loss: 0.634335
2023-06-28 00:13:51.821713 Validation: avg loss: 0.6960, avg acc: 45.7143%
2023-06-28 00:14:18.974802 Train: epoch: 7 batch: 0/4, loss: 0.594279
2023-06-28 00:15:45.039438 Validation: avg loss: 0.7125, avg acc: 45.7143%
2023-06-28 00:16:12.190517 Train: epoch: 8 batch: 0/4, loss: 0.557945
2023-06-28 00:17:38.467017 Validation: avg loss: 0.7386, avg acc: 45.7143%
2023-06-28 00:18:05.681166 Train: epoch: 9 batch: 0/4, loss: 0.511483
2023-06-28 00:19:31.877109 Validation: avg loss: 0.7578, avg acc: 45.7143%
2023-06-28 00:19:59.017606 Train: epoch: 10 batch: 0/4, loss: 0.432129
2023-06-28 00:21:25.233848 Validation: avg loss: 0.7912, avg acc: 44.7619%
2023-06-28 00:21:52.415137 Train: epoch: 11 batch: 0/4, loss: 0.328518
2023-06-28 00:23:18.575682 Validation: avg loss: 0.7873, avg acc: 44.7619%
2023-06-28 00:23:45.840401 Train: epoch: 12 batch: 0/4, loss: 0.253219
2023-06-28 00:25:11.919328 Validation: avg loss: 0.9148, avg acc: 44.7619%
2023-06-28 00:25:39.097557 Train: epoch: 13 batch: 0/4, loss: 0.195084
2023-06-28 00:27:05.174270 Validation: avg loss: 0.9219, avg acc: 47.6190%
2023-06-28 00:27:32.326026 Train: epoch: 14 batch: 0/4, loss: 0.119070
2023-06-28 00:28:58.384062 Validation: avg loss: 0.8327, avg acc: 51.4286%
2023-06-28 00:29:25.580089 Train: epoch: 15 batch: 0/4, loss: 0.168091
2023-06-28 00:30:51.610111 Validation: avg loss: 0.8671, avg acc: 57.1429%
2023-06-28 00:31:18.835979 Train: epoch: 16 batch: 0/4, loss: 0.066475
2023-06-28 00:32:45.015780 Validation: avg loss: 0.9880, avg acc: 55.2381%
2023-06-28 00:33:12.191811 Train: epoch: 17 batch: 0/4, loss: 0.043416
2023-06-28 00:34:38.123465 Validation: avg loss: 1.1019, avg acc: 58.0952%
2023-06-28 00:35:05.353746 Train: epoch: 18 batch: 0/4, loss: 0.063443
2023-06-28 00:36:31.249648 Validation: avg loss: 1.2272, avg acc: 60.9524%
2023-06-28 00:36:58.472793 Train: epoch: 19 batch: 0/4, loss: 0.030943
2023-06-28 00:38:24.600841 Validation: avg loss: 1.3022, avg acc: 59.0476%
2023-06-28 00:38:51.819343 Train: epoch: 20 batch: 0/4, loss: 0.031996
2023-06-28 00:40:17.740788 Validation: avg loss: 1.3516, avg acc: 60.0000%
2023-06-28 00:40:44.918261 Train: epoch: 21 batch: 0/4, loss: 0.013473
2023-06-28 00:42:10.869715 Validation: avg loss: 1.3225, avg acc: 60.9524%
2023-06-28 00:42:38.034583 Train: epoch: 22 batch: 0/4, loss: 0.013430
2023-06-28 00:44:03.872122 Validation: avg loss: 1.3845, avg acc: 62.8571%
2023-06-28 00:44:31.010378 Train: epoch: 23 batch: 0/4, loss: 0.019891
2023-06-28 00:45:57.037393 Validation: avg loss: 1.4421, avg acc: 61.9048%
2023-06-28 00:46:24.094525 Train: epoch: 24 batch: 0/4, loss: 0.008560
2023-06-28 00:47:49.950420 Validation: avg loss: 1.4869, avg acc: 60.0000%
2023-06-28 00:48:17.163679 Train: epoch: 25 batch: 0/4, loss: 0.006912
2023-06-28 00:49:43.186478 Validation: avg loss: 1.5726, avg acc: 60.0000%
2023-06-28 00:50:10.371727 Train: epoch: 26 batch: 0/4, loss: 0.005445
2023-06-28 00:51:36.450767 Validation: avg loss: 1.5738, avg acc: 62.8571%
2023-06-28 00:52:03.585933 Train: epoch: 27 batch: 0/4, loss: 0.005379
2023-06-28 00:53:29.656191 Validation: avg loss: 1.5699, avg acc: 59.0476%
2023-06-28 00:53:56.812382 Train: epoch: 28 batch: 0/4, loss: 0.006086
2023-06-28 00:55:22.933579 Validation: avg loss: 1.5712, avg acc: 58.0952%
2023-06-28 00:55:50.066252 Train: epoch: 29 batch: 0/4, loss: 0.009347
2023-06-28 00:57:16.197050 Validation: avg loss: 1.6060, avg acc: 59.0476%
2023-06-28 00:57:43.450401 Train: epoch: 30 batch: 0/4, loss: 0.004565
2023-06-28 00:59:09.404419 Validation: avg loss: 1.6264, avg acc: 59.0476%
2023-06-28 00:59:36.645663 Train: epoch: 31 batch: 0/4, loss: 0.006519
2023-06-28 01:01:02.730650 Validation: avg loss: 1.6207, avg acc: 60.0000%
2023-06-28 01:01:29.975272 Train: epoch: 32 batch: 0/4, loss: 0.003535
2023-06-28 01:02:56.059746 Validation: avg loss: 1.6180, avg acc: 60.9524%
2023-06-28 01:03:23.253452 Train: epoch: 33 batch: 0/4, loss: 0.002235
2023-06-28 01:04:49.311059 Validation: avg loss: 1.6396, avg acc: 61.9048%
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2023-06-28 01:06:42.365234 Validation: avg loss: 1.6444, avg acc: 60.9524%
2023-06-28 01:07:09.502635 Train: epoch: 35 batch: 0/4, loss: 0.001970
2023-06-28 01:08:35.568617 Validation: avg loss: 1.6689, avg acc: 61.9048%
2023-06-28 01:09:02.653176 Train: epoch: 36 batch: 0/4, loss: 0.001693
2023-06-28 01:10:28.567241 Validation: avg loss: 1.6654, avg acc: 62.8571%
2023-06-28 01:10:55.674928 Train: epoch: 37 batch: 0/4, loss: 0.001810
2023-06-28 01:12:21.756428 Validation: avg loss: 1.6767, avg acc: 63.8095%
2023-06-28 01:12:48.995444 Train: epoch: 38 batch: 0/4, loss: 0.002386
2023-06-28 01:14:15.125509 Validation: avg loss: 1.7080, avg acc: 61.9048%
2023-06-28 01:14:42.323332 Train: epoch: 39 batch: 0/4, loss: 0.001173
2023-06-28 01:16:08.383465 Validation: avg loss: 1.7215, avg acc: 61.9048%
2023-06-28 01:16:35.497457 Train: epoch: 40 batch: 0/4, loss: 0.001416
2023-06-28 01:18:01.677326 Validation: avg loss: 1.7432, avg acc: 60.0000%
2023-06-28 01:18:28.796697 Train: epoch: 41 batch: 0/4, loss: 0.001461
2023-06-28 01:19:54.911065 Validation: avg loss: 1.7576, avg acc: 60.0000%
2023-06-28 01:20:22.088100 Train: epoch: 42 batch: 0/4, loss: 0.002492
2023-06-28 01:21:48.054136 Validation: avg loss: 1.7749, avg acc: 60.9524%
2023-06-28 01:22:15.253422 Train: epoch: 43 batch: 0/4, loss: 0.001335
2023-06-28 01:23:41.275229 Validation: avg loss: 1.7797, avg acc: 62.8571%
2023-06-28 01:24:08.512589 Train: epoch: 44 batch: 0/4, loss: 0.001804
2023-06-28 01:25:34.658442 Validation: avg loss: 1.7701, avg acc: 63.8095%
2023-06-28 01:26:01.800322 Train: epoch: 45 batch: 0/4, loss: 0.000998
2023-06-28 01:27:27.847553 Validation: avg loss: 1.7615, avg acc: 63.8095%
2023-06-28 01:27:54.940621 Train: epoch: 46 batch: 0/4, loss: 0.000716
2023-06-28 01:29:20.910805 Validation: avg loss: 1.7618, avg acc: 63.8095%
2023-06-28 01:29:48.026487 Train: epoch: 47 batch: 0/4, loss: 0.001693
2023-06-28 01:31:14.125205 Validation: avg loss: 1.7456, avg acc: 62.8571%
2023-06-28 01:31:41.255321 Train: epoch: 48 batch: 0/4, loss: 0.000961
2023-06-28 01:33:07.347253 Validation: avg loss: 1.7379, avg acc: 62.8571%
2023-06-28 01:33:34.482280 Train: epoch: 49 batch: 0/4, loss: 0.000808
2023-06-28 01:35:00.611509 Validation: avg loss: 1.7390, avg acc: 62.8571%
2023-06-28 01:35:27.800679 Train: epoch: 50 batch: 0/4, loss: 0.000810
2023-06-28 01:36:53.890431 Validation: avg loss: 1.7056, avg acc: 61.9048%
results/dcu/230628013653.log 0 → 100644
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2023-06-28 01:36:53.923582 cuda
2023-06-28 01:37:21.107539 Train: epoch: 1 batch: 0/4, loss: 0.692935
2023-06-28 01:38:47.337946 Validation: avg loss: 0.6873, avg acc: 57.1429%
2023-06-28 01:39:14.582866 Train: epoch: 2 batch: 0/4, loss: 0.678738
2023-06-28 01:40:40.800093 Validation: avg loss: 0.6834, avg acc: 57.1429%
2023-06-28 01:41:08.135577 Train: epoch: 3 batch: 0/4, loss: 0.671670
2023-06-28 01:42:34.444579 Validation: avg loss: 0.6862, avg acc: 57.1429%
2023-06-28 01:43:01.690937 Train: epoch: 4 batch: 0/4, loss: 0.665592
2023-06-28 01:44:28.266502 Validation: avg loss: 0.6918, avg acc: 57.1429%
2023-06-28 01:44:55.705680 Train: epoch: 5 batch: 0/4, loss: 0.645273
2023-06-28 01:46:22.678544 Validation: avg loss: 0.7024, avg acc: 57.1429%
2023-06-28 01:46:50.223475 Train: epoch: 6 batch: 0/4, loss: 0.645316
2023-06-28 01:48:17.000054 Validation: avg loss: 0.7350, avg acc: 57.1429%
2023-06-28 01:48:44.525874 Train: epoch: 7 batch: 0/4, loss: 0.622710
2023-06-28 01:50:11.607781 Validation: avg loss: 0.8148, avg acc: 57.1429%
2023-06-28 01:50:39.092931 Train: epoch: 8 batch: 0/4, loss: 0.580565
2023-06-28 01:52:06.225811 Validation: avg loss: 0.8237, avg acc: 57.1429%
2023-06-28 01:52:33.705784 Train: epoch: 9 batch: 0/4, loss: 0.522137
2023-06-28 01:54:00.584871 Validation: avg loss: 0.9248, avg acc: 57.1429%
2023-06-28 01:54:28.099595 Train: epoch: 10 batch: 0/4, loss: 0.469954
2023-06-28 01:55:54.519540 Validation: avg loss: 0.9284, avg acc: 57.1429%
2023-06-28 01:56:21.690945 Train: epoch: 11 batch: 0/4, loss: 0.426266
2023-06-28 01:57:47.872857 Validation: avg loss: 1.0347, avg acc: 57.1429%
2023-06-28 01:58:15.015256 Train: epoch: 12 batch: 0/4, loss: 0.311827
2023-06-28 01:59:41.281230 Validation: avg loss: 1.1582, avg acc: 57.1429%
2023-06-28 02:00:08.651630 Train: epoch: 13 batch: 0/4, loss: 0.210183
2023-06-28 02:01:34.884932 Validation: avg loss: 1.1707, avg acc: 57.1429%
2023-06-28 02:02:02.059368 Train: epoch: 14 batch: 0/4, loss: 0.163794
2023-06-28 02:03:28.350510 Validation: avg loss: 1.1745, avg acc: 57.1429%
2023-06-28 02:03:55.554334 Train: epoch: 15 batch: 0/4, loss: 0.105609
2023-06-28 02:05:21.789595 Validation: avg loss: 1.2003, avg acc: 52.3810%
2023-06-28 02:05:49.170252 Train: epoch: 16 batch: 0/4, loss: 0.080311
2023-06-28 02:07:15.283294 Validation: avg loss: 1.1293, avg acc: 55.2381%
2023-06-28 02:07:42.526575 Train: epoch: 17 batch: 0/4, loss: 0.059502
2023-06-28 02:09:08.824809 Validation: avg loss: 1.2498, avg acc: 55.2381%
2023-06-28 02:09:36.068604 Train: epoch: 18 batch: 0/4, loss: 0.038095
2023-06-28 02:11:02.601788 Validation: avg loss: 1.1708, avg acc: 58.0952%
2023-06-28 02:11:29.815753 Train: epoch: 19 batch: 0/4, loss: 0.045225
2023-06-28 02:12:56.068027 Validation: avg loss: 1.1217, avg acc: 55.2381%
2023-06-28 02:13:23.330474 Train: epoch: 20 batch: 0/4, loss: 0.022302
2023-06-28 02:14:49.447193 Validation: avg loss: 1.2872, avg acc: 53.3333%
2023-06-28 02:15:16.694023 Train: epoch: 21 batch: 0/4, loss: 0.020368
2023-06-28 02:16:43.048620 Validation: avg loss: 1.4419, avg acc: 54.2857%
2023-06-28 02:17:10.353606 Train: epoch: 22 batch: 0/4, loss: 0.014631
2023-06-28 02:18:36.636728 Validation: avg loss: 1.6030, avg acc: 54.2857%
2023-06-28 02:19:03.813608 Train: epoch: 23 batch: 0/4, loss: 0.012507
2023-06-28 02:20:30.115345 Validation: avg loss: 1.6713, avg acc: 56.1905%
2023-06-28 02:20:57.449667 Train: epoch: 24 batch: 0/4, loss: 0.006130
2023-06-28 02:22:23.613365 Validation: avg loss: 1.6397, avg acc: 58.0952%
2023-06-28 02:22:50.966986 Train: epoch: 25 batch: 0/4, loss: 0.009982
2023-06-28 02:24:17.251706 Validation: avg loss: 1.6221, avg acc: 58.0952%
2023-06-28 02:24:44.516490 Train: epoch: 26 batch: 0/4, loss: 0.006730
2023-06-28 02:26:10.779091 Validation: avg loss: 1.7074, avg acc: 55.2381%
2023-06-28 02:26:37.983104 Train: epoch: 27 batch: 0/4, loss: 0.016433
2023-06-28 02:28:04.294135 Validation: avg loss: 1.7560, avg acc: 55.2381%
2023-06-28 02:28:31.577575 Train: epoch: 28 batch: 0/4, loss: 0.008563
2023-06-28 02:29:57.860700 Validation: avg loss: 1.7894, avg acc: 54.2857%
2023-06-28 02:30:25.125665 Train: epoch: 29 batch: 0/4, loss: 0.014163
2023-06-28 02:31:51.530374 Validation: avg loss: 1.8500, avg acc: 53.3333%
2023-06-28 02:32:18.842342 Train: epoch: 30 batch: 0/4, loss: 0.005273
2023-06-28 02:33:45.383157 Validation: avg loss: 1.8866, avg acc: 55.2381%
2023-06-28 02:34:12.571726 Train: epoch: 31 batch: 0/4, loss: 0.003205
2023-06-28 02:35:38.940833 Validation: avg loss: 1.9667, avg acc: 53.3333%
2023-06-28 02:36:06.167484 Train: epoch: 32 batch: 0/4, loss: 0.003173
2023-06-28 02:37:32.549349 Validation: avg loss: 2.0159, avg acc: 52.3810%
2023-06-28 02:37:59.796132 Train: epoch: 33 batch: 0/4, loss: 0.003008
2023-06-28 02:39:26.240060 Validation: avg loss: 2.0329, avg acc: 53.3333%
2023-06-28 02:39:53.568193 Train: epoch: 34 batch: 0/4, loss: 0.008654
2023-06-28 02:41:20.140943 Validation: avg loss: 2.0256, avg acc: 53.3333%
2023-06-28 02:41:47.443576 Train: epoch: 35 batch: 0/4, loss: 0.001762
2023-06-28 02:43:13.856703 Validation: avg loss: 2.0831, avg acc: 52.3810%
2023-06-28 02:43:41.296620 Train: epoch: 36 batch: 0/4, loss: 0.001961
2023-06-28 02:45:07.799777 Validation: avg loss: 2.1159, avg acc: 52.3810%
2023-06-28 02:45:35.100669 Train: epoch: 37 batch: 0/4, loss: 0.002146
2023-06-28 02:47:01.527157 Validation: avg loss: 2.0696, avg acc: 51.4286%
2023-06-28 02:47:28.860225 Train: epoch: 38 batch: 0/4, loss: 0.001943
2023-06-28 02:48:55.268508 Validation: avg loss: 1.9952, avg acc: 52.3810%
2023-06-28 02:49:22.491174 Train: epoch: 39 batch: 0/4, loss: 0.001654
2023-06-28 02:50:48.974856 Validation: avg loss: 1.9544, avg acc: 54.2857%
2023-06-28 02:51:16.370352 Train: epoch: 40 batch: 0/4, loss: 0.001788
2023-06-28 02:52:42.924138 Validation: avg loss: 1.9313, avg acc: 55.2381%
2023-06-28 02:53:10.153681 Train: epoch: 41 batch: 0/4, loss: 0.001468
2023-06-28 02:54:36.645707 Validation: avg loss: 1.9302, avg acc: 55.2381%
2023-06-28 02:55:04.102946 Train: epoch: 42 batch: 0/4, loss: 0.001202
2023-06-28 02:56:30.983834 Validation: avg loss: 1.9334, avg acc: 54.2857%
2023-06-28 02:56:58.223602 Train: epoch: 43 batch: 0/4, loss: 0.001153
2023-06-28 02:58:24.650451 Validation: avg loss: 1.9535, avg acc: 54.2857%
2023-06-28 02:58:51.947880 Train: epoch: 44 batch: 0/4, loss: 0.001290
2023-06-28 03:00:18.662781 Validation: avg loss: 1.9637, avg acc: 54.2857%
2023-06-28 03:00:45.876827 Train: epoch: 45 batch: 0/4, loss: 0.000891
2023-06-28 03:02:12.240414 Validation: avg loss: 1.9883, avg acc: 55.2381%
2023-06-28 03:02:39.640379 Train: epoch: 46 batch: 0/4, loss: 0.000980
2023-06-28 03:04:06.080678 Validation: avg loss: 2.0100, avg acc: 56.1905%
2023-06-28 03:04:33.325264 Train: epoch: 47 batch: 0/4, loss: 0.000806
2023-06-28 03:05:59.760473 Validation: avg loss: 2.0178, avg acc: 55.2381%
2023-06-28 03:06:27.164574 Train: epoch: 48 batch: 0/4, loss: 0.000790
2023-06-28 03:07:53.849098 Validation: avg loss: 2.0173, avg acc: 57.1429%
2023-06-28 03:08:21.058406 Train: epoch: 49 batch: 0/4, loss: 0.000893
2023-06-28 03:09:47.531481 Validation: avg loss: 2.0094, avg acc: 55.2381%
2023-06-28 03:10:14.832479 Train: epoch: 50 batch: 0/4, loss: 0.001130
2023-06-28 03:11:41.336619 Validation: avg loss: 2.0189, avg acc: 56.1905%
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2023-06-28 03:11:41.369838 cuda
2023-06-28 03:12:08.489829 Train: epoch: 1 batch: 0/4, loss: 0.693009
2023-06-28 03:13:35.046750 Validation: avg loss: 0.6857, avg acc: 59.0476%
2023-06-28 03:14:02.248611 Train: epoch: 2 batch: 0/4, loss: 0.660941
2023-06-28 03:15:28.672696 Validation: avg loss: 0.6814, avg acc: 59.0476%
2023-06-28 03:15:55.889171 Train: epoch: 3 batch: 0/4, loss: 0.677196
2023-06-28 03:17:22.246065 Validation: avg loss: 0.6786, avg acc: 59.0476%
2023-06-28 03:17:49.559499 Train: epoch: 4 batch: 0/4, loss: 0.658742
2023-06-28 03:19:15.996798 Validation: avg loss: 0.6773, avg acc: 59.0476%
2023-06-28 03:19:43.304110 Train: epoch: 5 batch: 0/4, loss: 0.639081
2023-06-28 03:21:09.730463 Validation: avg loss: 0.6766, avg acc: 59.0476%
2023-06-28 03:21:36.976033 Train: epoch: 6 batch: 0/4, loss: 0.644215
2023-06-28 03:23:03.375505 Validation: avg loss: 0.6785, avg acc: 59.0476%
2023-06-28 03:23:30.700397 Train: epoch: 7 batch: 0/4, loss: 0.589882
2023-06-28 03:24:57.368440 Validation: avg loss: 0.6840, avg acc: 59.0476%
2023-06-28 03:25:24.609371 Train: epoch: 8 batch: 0/4, loss: 0.598612
2023-06-28 03:26:51.153481 Validation: avg loss: 0.6744, avg acc: 59.0476%
2023-06-28 03:27:18.453132 Train: epoch: 9 batch: 0/4, loss: 0.535064
2023-06-28 03:28:45.049005 Validation: avg loss: 0.6742, avg acc: 59.0476%
2023-06-28 03:29:12.429540 Train: epoch: 10 batch: 0/4, loss: 0.445725
2023-06-28 03:30:39.157958 Validation: avg loss: 0.6635, avg acc: 59.0476%
2023-06-28 03:31:06.510547 Train: epoch: 11 batch: 0/4, loss: 0.404390
2023-06-28 03:32:33.136095 Validation: avg loss: 0.6513, avg acc: 60.9524%
2023-06-28 03:33:00.548645 Train: epoch: 12 batch: 0/4, loss: 0.299564
2023-06-28 03:34:27.188458 Validation: avg loss: 0.6300, avg acc: 66.6667%
2023-06-28 03:34:54.497327 Train: epoch: 13 batch: 0/4, loss: 0.214730
2023-06-28 03:36:20.982842 Validation: avg loss: 0.5986, avg acc: 70.4762%
2023-06-28 03:36:48.279724 Train: epoch: 14 batch: 0/4, loss: 0.139650
2023-06-28 03:38:14.780257 Validation: avg loss: 0.5917, avg acc: 70.4762%
2023-06-28 03:38:42.185034 Train: epoch: 15 batch: 0/4, loss: 0.095805
2023-06-28 03:40:08.762359 Validation: avg loss: 0.6035, avg acc: 70.4762%
2023-06-28 03:40:36.014349 Train: epoch: 16 batch: 0/4, loss: 0.117713
2023-06-28 03:42:02.806398 Validation: avg loss: 0.6005, avg acc: 74.2857%
2023-06-28 03:42:30.083217 Train: epoch: 17 batch: 0/4, loss: 0.053618
2023-06-28 03:43:56.560993 Validation: avg loss: 0.6274, avg acc: 73.3333%
2023-06-28 03:44:23.921173 Train: epoch: 18 batch: 0/4, loss: 0.031614
2023-06-28 03:45:50.567906 Validation: avg loss: 0.6853, avg acc: 73.3333%
2023-06-28 03:46:17.900417 Train: epoch: 19 batch: 0/4, loss: 0.020584
2023-06-28 03:47:44.369591 Validation: avg loss: 0.7224, avg acc: 74.2857%
2023-06-28 03:48:11.683537 Train: epoch: 20 batch: 0/4, loss: 0.016825
2023-06-28 03:49:38.121020 Validation: avg loss: 0.7518, avg acc: 77.1429%
2023-06-28 03:50:05.533161 Train: epoch: 21 batch: 0/4, loss: 0.025432
2023-06-28 03:51:32.061008 Validation: avg loss: 0.7888, avg acc: 75.2381%
2023-06-28 03:51:59.383920 Train: epoch: 22 batch: 0/4, loss: 0.043029
2023-06-28 03:53:25.981256 Validation: avg loss: 0.8037, avg acc: 74.2857%
2023-06-28 03:53:53.353953 Train: epoch: 23 batch: 0/4, loss: 0.008785
2023-06-28 03:55:19.878661 Validation: avg loss: 0.8034, avg acc: 73.3333%
2023-06-28 03:55:47.181928 Train: epoch: 24 batch: 0/4, loss: 0.005627
2023-06-28 03:57:13.741347 Validation: avg loss: 0.8422, avg acc: 75.2381%
2023-06-28 03:57:41.055459 Train: epoch: 25 batch: 0/4, loss: 0.011560
2023-06-28 03:59:07.539045 Validation: avg loss: 0.8324, avg acc: 74.2857%
2023-06-28 03:59:34.906505 Train: epoch: 26 batch: 0/4, loss: 0.005340
2023-06-28 04:01:01.156838 Validation: avg loss: 0.8390, avg acc: 74.2857%
2023-06-28 04:01:28.310528 Train: epoch: 27 batch: 0/4, loss: 0.003994
2023-06-28 04:02:54.549754 Validation: avg loss: 0.8549, avg acc: 76.1905%
2023-06-28 04:03:21.745650 Train: epoch: 28 batch: 0/4, loss: 0.004037
2023-06-28 04:04:47.978870 Validation: avg loss: 0.9414, avg acc: 75.2381%
2023-06-28 04:05:15.077678 Train: epoch: 29 batch: 0/4, loss: 0.003525
2023-06-28 04:06:41.253870 Validation: avg loss: 0.7540, avg acc: 76.1905%
2023-06-28 04:07:08.447299 Train: epoch: 30 batch: 0/4, loss: 0.010938
2023-06-28 04:08:34.678209 Validation: avg loss: 0.7487, avg acc: 75.2381%
2023-06-28 04:09:01.850756 Train: epoch: 31 batch: 0/4, loss: 0.008799
2023-06-28 04:10:27.965042 Validation: avg loss: 0.7571, avg acc: 76.1905%
2023-06-28 04:10:55.161585 Train: epoch: 32 batch: 0/4, loss: 0.009438
2023-06-28 04:12:21.369456 Validation: avg loss: 0.8214, avg acc: 78.0952%
2023-06-28 04:12:48.557866 Train: epoch: 33 batch: 0/4, loss: 0.010469
2023-06-28 04:14:14.817327 Validation: avg loss: 0.7763, avg acc: 80.0000%
2023-06-28 04:14:42.017780 Train: epoch: 34 batch: 0/4, loss: 0.010956
2023-06-28 04:16:08.324725 Validation: avg loss: 0.7527, avg acc: 77.1429%
2023-06-28 04:16:35.565484 Train: epoch: 35 batch: 0/4, loss: 0.004107
2023-06-28 04:18:01.747081 Validation: avg loss: 0.7567, avg acc: 78.0952%
2023-06-28 04:18:29.006570 Train: epoch: 36 batch: 0/4, loss: 0.005303
2023-06-28 04:19:55.293630 Validation: avg loss: 0.7849, avg acc: 78.0952%
2023-06-28 04:20:22.566884 Train: epoch: 37 batch: 0/4, loss: 0.004355
2023-06-28 04:21:48.913328 Validation: avg loss: 0.8529, avg acc: 74.2857%
2023-06-28 04:22:16.123283 Train: epoch: 38 batch: 0/4, loss: 0.002653
2023-06-28 04:23:42.314617 Validation: avg loss: 0.9147, avg acc: 72.3810%
2023-06-28 04:24:09.540944 Train: epoch: 39 batch: 0/4, loss: 0.003798
2023-06-28 04:25:35.801392 Validation: avg loss: 0.9432, avg acc: 73.3333%
2023-06-28 04:26:03.093014 Train: epoch: 40 batch: 0/4, loss: 0.004928
2023-06-28 04:27:29.335487 Validation: avg loss: 0.9504, avg acc: 74.2857%
2023-06-28 04:27:56.595927 Train: epoch: 41 batch: 0/4, loss: 0.003297
2023-06-28 04:29:22.829464 Validation: avg loss: 0.9514, avg acc: 74.2857%
2023-06-28 04:29:50.060556 Train: epoch: 42 batch: 0/4, loss: 0.008558
2023-06-28 04:31:16.227639 Validation: avg loss: 0.9680, avg acc: 75.2381%
2023-06-28 04:31:43.403653 Train: epoch: 43 batch: 0/4, loss: 0.003308
2023-06-28 04:33:09.493717 Validation: avg loss: 0.9591, avg acc: 75.2381%
2023-06-28 04:33:36.739152 Train: epoch: 44 batch: 0/4, loss: 0.001741
2023-06-28 04:35:02.790738 Validation: avg loss: 0.9662, avg acc: 76.1905%
2023-06-28 04:35:30.000194 Train: epoch: 45 batch: 0/4, loss: 0.005446
2023-06-28 04:36:56.137687 Validation: avg loss: 0.9592, avg acc: 77.1429%
2023-06-28 04:37:23.365801 Train: epoch: 46 batch: 0/4, loss: 0.001942
2023-06-28 04:38:49.522040 Validation: avg loss: 0.9543, avg acc: 76.1905%
2023-06-28 04:39:16.764699 Train: epoch: 47 batch: 0/4, loss: 0.001761
2023-06-28 04:40:42.896181 Validation: avg loss: 0.9601, avg acc: 75.2381%
2023-06-28 04:41:10.053471 Train: epoch: 48 batch: 0/4, loss: 0.003969
2023-06-28 04:42:36.352263 Validation: avg loss: 0.9548, avg acc: 76.1905%
2023-06-28 04:43:03.630201 Train: epoch: 49 batch: 0/4, loss: 0.000910
2023-06-28 04:44:29.912814 Validation: avg loss: 0.9550, avg acc: 75.2381%
2023-06-28 04:44:57.209325 Train: epoch: 50 batch: 0/4, loss: 0.002676
2023-06-28 04:46:23.407038 Validation: avg loss: 0.9544, avg acc: 78.0952%
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2023-06-28 04:46:23.440132 cuda
2023-06-28 04:46:50.558957 Train: epoch: 1 batch: 0/4, loss: 0.691489
2023-06-28 04:48:16.880243 Validation: avg loss: 0.6866, avg acc: 57.1429%
2023-06-28 04:48:44.158985 Train: epoch: 2 batch: 0/4, loss: 0.674378
2023-06-28 04:50:10.500619 Validation: avg loss: 0.6850, avg acc: 57.1429%
2023-06-28 04:50:37.836617 Train: epoch: 3 batch: 0/4, loss: 0.667162
2023-06-28 04:52:04.252311 Validation: avg loss: 0.6884, avg acc: 57.1429%
2023-06-28 04:52:31.548462 Train: epoch: 4 batch: 0/4, loss: 0.669279
2023-06-28 04:53:57.987208 Validation: avg loss: 0.6909, avg acc: 57.1429%
2023-06-28 04:54:25.244756 Train: epoch: 5 batch: 0/4, loss: 0.654708
2023-06-28 04:55:51.453288 Validation: avg loss: 0.6985, avg acc: 42.8571%
2023-06-28 04:56:18.675808 Train: epoch: 6 batch: 0/4, loss: 0.641800
2023-06-28 04:57:44.926128 Validation: avg loss: 0.7082, avg acc: 42.8571%
2023-06-28 04:58:12.243071 Train: epoch: 7 batch: 0/4, loss: 0.609780
2023-06-28 04:59:38.667862 Validation: avg loss: 0.7572, avg acc: 42.8571%
2023-06-28 05:00:05.952760 Train: epoch: 8 batch: 0/4, loss: 0.610657
2023-06-28 05:01:32.412124 Validation: avg loss: 0.7486, avg acc: 42.8571%
2023-06-28 05:01:59.771772 Train: epoch: 9 batch: 0/4, loss: 0.537623
2023-06-28 05:03:26.168257 Validation: avg loss: 0.7688, avg acc: 42.8571%
2023-06-28 05:03:53.350470 Train: epoch: 10 batch: 0/4, loss: 0.463665
2023-06-28 05:05:19.505165 Validation: avg loss: 0.7831, avg acc: 42.8571%
2023-06-28 05:05:46.816497 Train: epoch: 11 batch: 0/4, loss: 0.396349
2023-06-28 05:07:13.284678 Validation: avg loss: 0.9021, avg acc: 42.8571%
2023-06-28 05:07:40.434572 Train: epoch: 12 batch: 0/4, loss: 0.377895
2023-06-28 05:09:06.683140 Validation: avg loss: 0.7624, avg acc: 46.6667%
2023-06-28 05:09:34.038597 Train: epoch: 13 batch: 0/4, loss: 0.292639
2023-06-28 05:11:00.604442 Validation: avg loss: 0.7629, avg acc: 52.3810%
2023-06-28 05:11:27.927078 Train: epoch: 14 batch: 0/4, loss: 0.163924
2023-06-28 05:12:54.096479 Validation: avg loss: 0.6852, avg acc: 63.8095%
2023-06-28 05:13:21.196518 Train: epoch: 15 batch: 0/4, loss: 0.157839
2023-06-28 05:14:46.992535 Validation: avg loss: 0.6054, avg acc: 67.6190%
2023-06-28 05:15:13.921136 Train: epoch: 16 batch: 0/4, loss: 0.075988
2023-06-28 05:16:39.555716 Validation: avg loss: 0.5625, avg acc: 69.5238%
2023-06-28 05:17:06.638224 Train: epoch: 17 batch: 0/4, loss: 0.054838
2023-06-28 05:18:32.374108 Validation: avg loss: 0.6063, avg acc: 71.4286%
2023-06-28 05:18:59.483689 Train: epoch: 18 batch: 0/4, loss: 0.033897
2023-06-28 05:20:25.270910 Validation: avg loss: 0.6640, avg acc: 72.3810%
2023-06-28 05:20:52.305933 Train: epoch: 19 batch: 0/4, loss: 0.029342
2023-06-28 05:22:18.039158 Validation: avg loss: 0.6759, avg acc: 68.5714%
2023-06-28 05:22:45.087474 Train: epoch: 20 batch: 0/4, loss: 0.035418
2023-06-28 05:24:10.724896 Validation: avg loss: 0.7139, avg acc: 69.5238%
2023-06-28 05:24:37.705066 Train: epoch: 21 batch: 0/4, loss: 0.010324
2023-06-28 05:26:03.452868 Validation: avg loss: 0.7171, avg acc: 70.4762%
2023-06-28 05:26:30.429953 Train: epoch: 22 batch: 0/4, loss: 0.015367
2023-06-28 05:27:56.099289 Validation: avg loss: 0.7221, avg acc: 73.3333%
2023-06-28 05:28:23.217156 Train: epoch: 23 batch: 0/4, loss: 0.012628
2023-06-28 05:29:49.049346 Validation: avg loss: 0.7451, avg acc: 73.3333%
2023-06-28 05:30:16.076247 Train: epoch: 24 batch: 0/4, loss: 0.009900
2023-06-28 05:31:41.606001 Validation: avg loss: 0.7922, avg acc: 72.3810%
2023-06-28 05:32:08.613232 Train: epoch: 25 batch: 0/4, loss: 0.006447
2023-06-28 05:33:34.383115 Validation: avg loss: 0.8139, avg acc: 73.3333%
2023-06-28 05:34:01.440329 Train: epoch: 26 batch: 0/4, loss: 0.003593
2023-06-28 05:35:27.214247 Validation: avg loss: 0.8530, avg acc: 72.3810%
2023-06-28 05:35:54.248027 Train: epoch: 27 batch: 0/4, loss: 0.007230
2023-06-28 05:37:19.865013 Validation: avg loss: 0.8743, avg acc: 72.3810%
2023-06-28 05:37:47.041858 Train: epoch: 28 batch: 0/4, loss: 0.014971
2023-06-28 05:39:12.733950 Validation: avg loss: 0.9495, avg acc: 73.3333%
2023-06-28 05:39:39.728747 Train: epoch: 29 batch: 0/4, loss: 0.002754
2023-06-28 05:41:05.347019 Validation: avg loss: 0.9543, avg acc: 73.3333%
2023-06-28 05:41:32.373508 Train: epoch: 30 batch: 0/4, loss: 0.004897
2023-06-28 05:42:58.019471 Validation: avg loss: 0.9222, avg acc: 74.2857%
2023-06-28 05:43:25.065844 Train: epoch: 31 batch: 0/4, loss: 0.003625
2023-06-28 05:44:50.729601 Validation: avg loss: 0.8726, avg acc: 74.2857%
2023-06-28 05:45:17.702695 Train: epoch: 32 batch: 0/4, loss: 0.002928
2023-06-28 05:46:43.493191 Validation: avg loss: 0.8650, avg acc: 73.3333%
2023-06-28 05:47:10.572700 Train: epoch: 33 batch: 0/4, loss: 0.001931
2023-06-28 05:48:36.373079 Validation: avg loss: 0.8965, avg acc: 74.2857%
2023-06-28 05:49:03.383010 Train: epoch: 34 batch: 0/4, loss: 0.004791
2023-06-28 05:50:29.182334 Validation: avg loss: 0.9346, avg acc: 70.4762%
2023-06-28 05:50:56.184084 Train: epoch: 35 batch: 0/4, loss: 0.002151
2023-06-28 05:52:22.037438 Validation: avg loss: 0.9426, avg acc: 70.4762%
2023-06-28 05:52:49.036990 Train: epoch: 36 batch: 0/4, loss: 0.002439
2023-06-28 05:54:14.673797 Validation: avg loss: 0.9517, avg acc: 72.3810%
2023-06-28 05:54:41.811814 Train: epoch: 37 batch: 0/4, loss: 0.001436
2023-06-28 05:56:07.659605 Validation: avg loss: 0.9766, avg acc: 73.3333%
2023-06-28 05:56:34.777159 Train: epoch: 38 batch: 0/4, loss: 0.002025
2023-06-28 05:58:00.343044 Validation: avg loss: 0.9874, avg acc: 72.3810%
2023-06-28 05:58:27.390861 Train: epoch: 39 batch: 0/4, loss: 0.001200
2023-06-28 05:59:53.142386 Validation: avg loss: 0.9936, avg acc: 72.3810%
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2023-06-28 06:01:45.720076 Validation: avg loss: 0.9944, avg acc: 72.3810%
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2023-06-28 06:03:38.405168 Validation: avg loss: 0.9941, avg acc: 73.3333%
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2023-06-28 06:05:31.098490 Validation: avg loss: 0.9989, avg acc: 72.3810%
2023-06-28 06:05:58.143698 Train: epoch: 43 batch: 0/4, loss: 0.001311
2023-06-28 06:07:23.795089 Validation: avg loss: 0.9964, avg acc: 72.3810%
2023-06-28 06:07:50.844074 Train: epoch: 44 batch: 0/4, loss: 0.001091
2023-06-28 06:09:16.575192 Validation: avg loss: 0.9972, avg acc: 72.3810%
2023-06-28 06:09:43.613977 Train: epoch: 45 batch: 0/4, loss: 0.000973
2023-06-28 06:11:09.280542 Validation: avg loss: 0.9962, avg acc: 72.3810%
2023-06-28 06:11:36.301500 Train: epoch: 46 batch: 0/4, loss: 0.000905
2023-06-28 06:13:01.949403 Validation: avg loss: 0.9972, avg acc: 72.3810%
2023-06-28 06:13:28.916153 Train: epoch: 47 batch: 0/4, loss: 0.000894
2023-06-28 06:14:54.634029 Validation: avg loss: 1.0015, avg acc: 72.3810%
2023-06-28 06:15:21.721983 Train: epoch: 48 batch: 0/4, loss: 0.000730
2023-06-28 06:16:47.379171 Validation: avg loss: 1.0091, avg acc: 72.3810%
2023-06-28 06:17:14.407063 Train: epoch: 49 batch: 0/4, loss: 0.001016
2023-06-28 06:18:40.122032 Validation: avg loss: 1.0107, avg acc: 72.3810%
2023-06-28 06:19:07.198357 Train: epoch: 50 batch: 0/4, loss: 0.000575
2023-06-28 06:20:32.774520 Validation: avg loss: 1.0108, avg acc: 72.3810%
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2023-06-28 06:20:32.807694 cuda
2023-06-28 06:20:59.782142 Train: epoch: 1 batch: 0/4, loss: 0.694550
2023-06-28 06:22:25.049478 Validation: avg loss: 0.6866, avg acc: 58.0952%
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2023-06-28 06:24:17.492254 Validation: avg loss: 0.6806, avg acc: 58.0952%
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2023-06-28 06:26:09.939638 Validation: avg loss: 0.6800, avg acc: 58.0952%
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2023-06-28 06:28:02.373578 Validation: avg loss: 0.6801, avg acc: 58.0952%
2023-06-28 06:28:29.347816 Train: epoch: 5 batch: 0/4, loss: 0.642335
2023-06-28 06:29:55.096662 Validation: avg loss: 0.6809, avg acc: 58.0952%
2023-06-28 06:30:22.022250 Train: epoch: 6 batch: 0/4, loss: 0.609017
2023-06-28 06:31:47.601279 Validation: avg loss: 0.7002, avg acc: 58.0952%
2023-06-28 06:32:14.527985 Train: epoch: 7 batch: 0/4, loss: 0.583523
2023-06-28 06:33:40.148794 Validation: avg loss: 0.7076, avg acc: 58.0952%
2023-06-28 06:34:07.127858 Train: epoch: 8 batch: 0/4, loss: 0.529180
2023-06-28 06:35:32.700097 Validation: avg loss: 0.7478, avg acc: 58.0952%
2023-06-28 06:35:59.623205 Train: epoch: 9 batch: 0/4, loss: 0.425682
2023-06-28 06:37:25.177061 Validation: avg loss: 0.7770, avg acc: 58.0952%
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2023-06-28 06:39:17.709448 Validation: avg loss: 0.7617, avg acc: 58.0952%
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2023-06-28 06:41:10.138916 Validation: avg loss: 0.8174, avg acc: 58.0952%
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2023-06-28 06:43:02.531802 Validation: avg loss: 0.8176, avg acc: 59.0476%
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2023-06-28 06:44:55.170555 Validation: avg loss: 0.8509, avg acc: 60.9524%
2023-06-28 06:45:22.075733 Train: epoch: 14 batch: 0/4, loss: 0.138503
2023-06-28 06:46:47.720079 Validation: avg loss: 0.9241, avg acc: 60.0000%
2023-06-28 06:47:14.663116 Train: epoch: 15 batch: 0/4, loss: 0.098214
2023-06-28 06:48:40.200009 Validation: avg loss: 1.0118, avg acc: 57.1429%
2023-06-28 06:49:07.133194 Train: epoch: 16 batch: 0/4, loss: 0.033119
2023-06-28 06:50:32.840044 Validation: avg loss: 1.0273, avg acc: 58.0952%
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2023-06-28 06:52:25.411567 Validation: avg loss: 0.9969, avg acc: 60.9524%
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2023-06-28 06:54:18.105632 Validation: avg loss: 1.0427, avg acc: 67.6190%
2023-06-28 06:54:45.045750 Train: epoch: 19 batch: 0/4, loss: 0.019366
2023-06-28 06:56:10.681727 Validation: avg loss: 1.1259, avg acc: 63.8095%
2023-06-28 06:56:37.647528 Train: epoch: 20 batch: 0/4, loss: 0.010691
2023-06-28 06:58:03.195921 Validation: avg loss: 1.1928, avg acc: 66.6667%
2023-06-28 06:58:30.262874 Train: epoch: 21 batch: 0/4, loss: 0.014434
2023-06-28 06:59:55.963174 Validation: avg loss: 1.3022, avg acc: 64.7619%
2023-06-28 07:00:22.841666 Train: epoch: 22 batch: 0/4, loss: 0.006267
2023-06-28 07:01:48.442826 Validation: avg loss: 1.3515, avg acc: 62.8571%
2023-06-28 07:02:15.367444 Train: epoch: 23 batch: 0/4, loss: 0.006865
2023-06-28 07:03:40.894921 Validation: avg loss: 1.4161, avg acc: 61.9048%
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2023-06-28 07:05:33.452678 Validation: avg loss: 1.4647, avg acc: 61.9048%
2023-06-28 07:06:00.370655 Train: epoch: 25 batch: 0/4, loss: 0.003030
2023-06-28 07:07:25.879245 Validation: avg loss: 1.4783, avg acc: 64.7619%
2023-06-28 07:07:52.804435 Train: epoch: 26 batch: 0/4, loss: 0.002921
2023-06-28 07:09:18.368758 Validation: avg loss: 1.4957, avg acc: 64.7619%
2023-06-28 07:09:45.317592 Train: epoch: 27 batch: 0/4, loss: 0.002734
2023-06-28 07:11:10.909994 Validation: avg loss: 1.5322, avg acc: 62.8571%
2023-06-28 07:11:37.819938 Train: epoch: 28 batch: 0/4, loss: 0.003040
2023-06-28 07:13:03.543262 Validation: avg loss: 1.5551, avg acc: 61.9048%
2023-06-28 07:13:30.460248 Train: epoch: 29 batch: 0/4, loss: 0.008279
2023-06-28 07:14:55.920791 Validation: avg loss: 1.5932, avg acc: 60.0000%
2023-06-28 07:15:22.995582 Train: epoch: 30 batch: 0/4, loss: 0.001801
2023-06-28 07:16:48.598348 Validation: avg loss: 1.6062, avg acc: 60.0000%
2023-06-28 07:17:15.506477 Train: epoch: 31 batch: 0/4, loss: 0.003024
2023-06-28 07:18:41.037291 Validation: avg loss: 1.6190, avg acc: 59.0476%
2023-06-28 07:19:07.949540 Train: epoch: 32 batch: 0/4, loss: 0.001501
2023-06-28 07:20:33.640949 Validation: avg loss: 1.6265, avg acc: 59.0476%
2023-06-28 07:21:00.609931 Train: epoch: 33 batch: 0/4, loss: 0.001911
2023-06-28 07:22:26.299209 Validation: avg loss: 1.6330, avg acc: 59.0476%
2023-06-28 07:22:53.210851 Train: epoch: 34 batch: 0/4, loss: 0.005427
2023-06-28 07:24:18.718027 Validation: avg loss: 1.6348, avg acc: 59.0476%
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2023-06-28 07:26:11.348694 Validation: avg loss: 1.6311, avg acc: 59.0476%
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2023-06-28 07:28:03.959383 Validation: avg loss: 1.6419, avg acc: 60.9524%
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2023-06-28 07:29:56.486126 Validation: avg loss: 1.6435, avg acc: 60.9524%
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2023-06-28 07:31:49.062440 Validation: avg loss: 1.6537, avg acc: 60.9524%
2023-06-28 07:32:16.043402 Train: epoch: 39 batch: 0/4, loss: 0.001683
2023-06-28 07:33:41.521465 Validation: avg loss: 1.6615, avg acc: 61.9048%
2023-06-28 07:34:08.515651 Train: epoch: 40 batch: 0/4, loss: 0.001262
2023-06-28 07:35:34.061409 Validation: avg loss: 1.6703, avg acc: 61.9048%
2023-06-28 07:36:00.991426 Train: epoch: 41 batch: 0/4, loss: 0.001093
2023-06-28 07:37:26.675227 Validation: avg loss: 1.6685, avg acc: 61.9048%
2023-06-28 07:37:53.578362 Train: epoch: 42 batch: 0/4, loss: 0.001473
2023-06-28 07:39:19.158378 Validation: avg loss: 1.6740, avg acc: 60.9524%
2023-06-28 07:39:46.058494 Train: epoch: 43 batch: 0/4, loss: 0.001148
2023-06-28 07:41:11.848005 Validation: avg loss: 1.6666, avg acc: 60.0000%
2023-06-28 07:41:38.863473 Train: epoch: 44 batch: 0/4, loss: 0.000727
2023-06-28 07:43:04.378328 Validation: avg loss: 1.6574, avg acc: 60.0000%
2023-06-28 07:43:31.288581 Train: epoch: 45 batch: 0/4, loss: 0.000889
2023-06-28 07:44:56.999980 Validation: avg loss: 1.6633, avg acc: 60.0000%
2023-06-28 07:45:23.934487 Train: epoch: 46 batch: 0/4, loss: 0.000658
2023-06-28 07:46:49.564758 Validation: avg loss: 1.6701, avg acc: 60.9524%
2023-06-28 07:47:16.525807 Train: epoch: 47 batch: 0/4, loss: 0.000605
2023-06-28 07:48:42.126198 Validation: avg loss: 1.6665, avg acc: 59.0476%
2023-06-28 07:49:09.084892 Train: epoch: 48 batch: 0/4, loss: 0.001271
2023-06-28 07:50:34.841062 Validation: avg loss: 1.6740, avg acc: 60.0000%
2023-06-28 07:51:01.783708 Train: epoch: 49 batch: 0/4, loss: 0.001831
2023-06-28 07:52:27.407971 Validation: avg loss: 1.6820, avg acc: 59.0476%
2023-06-28 07:52:54.374783 Train: epoch: 50 batch: 0/4, loss: 0.000624
2023-06-28 07:54:20.183671 Validation: avg loss: 1.6893, avg acc: 60.0000%
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2023-06-28 07:54:20.219034 cuda
2023-06-28 07:54:47.323627 Train: epoch: 1 batch: 0/4, loss: 0.692011
2023-06-28 07:56:13.040178 Validation: avg loss: 0.6885, avg acc: 58.0952%
2023-06-28 07:56:40.122822 Train: epoch: 2 batch: 0/4, loss: 0.702609
2023-06-28 07:58:05.821483 Validation: avg loss: 0.6800, avg acc: 58.0952%
2023-06-28 07:58:32.914604 Train: epoch: 3 batch: 0/4, loss: 0.672602
2023-06-28 07:59:58.593179 Validation: avg loss: 0.6867, avg acc: 58.0952%
2023-06-28 08:00:25.746637 Train: epoch: 4 batch: 0/4, loss: 0.685599
2023-06-28 08:01:51.502271 Validation: avg loss: 0.6925, avg acc: 58.0952%
2023-06-28 08:02:18.553333 Train: epoch: 5 batch: 0/4, loss: 0.657828
2023-06-28 08:03:44.253610 Validation: avg loss: 0.7163, avg acc: 58.0952%
2023-06-28 08:04:11.348557 Train: epoch: 6 batch: 0/4, loss: 0.654859
2023-06-28 08:05:37.074056 Validation: avg loss: 0.7808, avg acc: 58.0952%
2023-06-28 08:06:04.181792 Train: epoch: 7 batch: 0/4, loss: 0.598809
2023-06-28 08:07:29.794384 Validation: avg loss: 0.8542, avg acc: 58.0952%
2023-06-28 08:07:56.910271 Train: epoch: 8 batch: 0/4, loss: 0.550983
2023-06-28 08:09:22.715247 Validation: avg loss: 0.9253, avg acc: 58.0952%
2023-06-28 08:09:49.823062 Train: epoch: 9 batch: 0/4, loss: 0.517771
2023-06-28 08:11:15.500013 Validation: avg loss: 1.0595, avg acc: 58.0952%
2023-06-28 08:11:42.652989 Train: epoch: 10 batch: 0/4, loss: 0.420894
2023-06-28 08:13:08.239842 Validation: avg loss: 1.1794, avg acc: 58.0952%
2023-06-28 08:13:35.331913 Train: epoch: 11 batch: 0/4, loss: 0.390708
2023-06-28 08:15:01.095686 Validation: avg loss: 1.2828, avg acc: 58.0952%
2023-06-28 08:15:28.156232 Train: epoch: 12 batch: 0/4, loss: 0.231362
2023-06-28 08:16:53.950080 Validation: avg loss: 1.1883, avg acc: 57.1429%
2023-06-28 08:17:21.026497 Train: epoch: 13 batch: 0/4, loss: 0.189501
2023-06-28 08:18:46.792051 Validation: avg loss: 1.0645, avg acc: 58.0952%
2023-06-28 08:19:13.901087 Train: epoch: 14 batch: 0/4, loss: 0.130682
2023-06-28 08:20:39.635420 Validation: avg loss: 1.0291, avg acc: 60.0000%
2023-06-28 08:21:06.671067 Train: epoch: 15 batch: 0/4, loss: 0.077287
2023-06-28 08:22:32.381361 Validation: avg loss: 1.0741, avg acc: 58.0952%
2023-06-28 08:22:59.471764 Train: epoch: 16 batch: 0/4, loss: 0.081006
2023-06-28 08:24:25.295718 Validation: avg loss: 0.9612, avg acc: 60.0000%
2023-06-28 08:24:52.401168 Train: epoch: 17 batch: 0/4, loss: 0.029166
2023-06-28 08:26:18.141239 Validation: avg loss: 0.9213, avg acc: 63.8095%
2023-06-28 08:26:45.228603 Train: epoch: 18 batch: 0/4, loss: 0.044118
2023-06-28 08:28:10.966862 Validation: avg loss: 0.9131, avg acc: 64.7619%
2023-06-28 08:28:38.049080 Train: epoch: 19 batch: 0/4, loss: 0.019182
2023-06-28 08:30:03.801301 Validation: avg loss: 0.9653, avg acc: 64.7619%
2023-06-28 08:30:30.984530 Train: epoch: 20 batch: 0/4, loss: 0.013524
2023-06-28 08:31:57.261869 Validation: avg loss: 1.0524, avg acc: 62.8571%
2023-06-28 08:32:24.455277 Train: epoch: 21 batch: 0/4, loss: 0.009294
2023-06-28 08:33:50.701421 Validation: avg loss: 1.1149, avg acc: 62.8571%
2023-06-28 08:34:17.907725 Train: epoch: 22 batch: 0/4, loss: 0.018284
2023-06-28 08:35:44.043447 Validation: avg loss: 1.1322, avg acc: 61.9048%
2023-06-28 08:36:11.277808 Train: epoch: 23 batch: 0/4, loss: 0.006030
2023-06-28 08:37:37.472454 Validation: avg loss: 1.1997, avg acc: 60.0000%
2023-06-28 08:38:04.659598 Train: epoch: 24 batch: 0/4, loss: 0.006223
2023-06-28 08:39:30.832079 Validation: avg loss: 1.3104, avg acc: 60.0000%
2023-06-28 08:39:58.095516 Train: epoch: 25 batch: 0/4, loss: 0.004612
2023-06-28 08:41:24.255853 Validation: avg loss: 1.3862, avg acc: 61.9048%
2023-06-28 08:41:51.480207 Train: epoch: 26 batch: 0/4, loss: 0.008557
2023-06-28 08:43:17.613646 Validation: avg loss: 1.2588, avg acc: 65.7143%
2023-06-28 08:43:44.926389 Train: epoch: 27 batch: 0/4, loss: 0.004575
2023-06-28 08:45:11.144766 Validation: avg loss: 1.2543, avg acc: 67.6190%
2023-06-28 08:45:38.375967 Train: epoch: 28 batch: 0/4, loss: 0.015793
2023-06-28 08:47:04.518903 Validation: avg loss: 1.2829, avg acc: 64.7619%
2023-06-28 08:47:31.768712 Train: epoch: 29 batch: 0/4, loss: 0.004682
2023-06-28 08:48:57.967912 Validation: avg loss: 1.2949, avg acc: 61.9048%
2023-06-28 08:49:25.148991 Train: epoch: 30 batch: 0/4, loss: 0.005337
2023-06-28 08:50:51.379151 Validation: avg loss: 1.3249, avg acc: 60.9524%
2023-06-28 08:51:18.575106 Train: epoch: 31 batch: 0/4, loss: 0.004917
2023-06-28 08:52:44.716013 Validation: avg loss: 1.3321, avg acc: 60.0000%
2023-06-28 08:53:11.941541 Train: epoch: 32 batch: 0/4, loss: 0.001858
2023-06-28 08:54:38.113950 Validation: avg loss: 1.3518, avg acc: 59.0476%
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2023-06-28 08:56:31.534083 Validation: avg loss: 1.3334, avg acc: 59.0476%
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2023-06-28 08:58:24.921176 Validation: avg loss: 1.3402, avg acc: 60.0000%
2023-06-28 08:58:52.217676 Train: epoch: 35 batch: 0/4, loss: 0.001703
2023-06-28 09:00:18.351915 Validation: avg loss: 1.3444, avg acc: 60.9524%
2023-06-28 09:00:45.580462 Train: epoch: 36 batch: 0/4, loss: 0.002229
2023-06-28 09:02:11.684169 Validation: avg loss: 1.3526, avg acc: 64.7619%
2023-06-28 09:02:38.904778 Train: epoch: 37 batch: 0/4, loss: 0.001279
2023-06-28 09:04:05.204570 Validation: avg loss: 1.3614, avg acc: 64.7619%
2023-06-28 09:04:32.417097 Train: epoch: 38 batch: 0/4, loss: 0.000850
2023-06-28 09:05:58.589090 Validation: avg loss: 1.3760, avg acc: 64.7619%
2023-06-28 09:06:25.828678 Train: epoch: 39 batch: 0/4, loss: 0.001662
2023-06-28 09:07:52.148092 Validation: avg loss: 1.3815, avg acc: 64.7619%
2023-06-28 09:08:19.406891 Train: epoch: 40 batch: 0/4, loss: 0.001392
2023-06-28 09:09:45.619191 Validation: avg loss: 1.3960, avg acc: 63.8095%
2023-06-28 09:10:12.860133 Train: epoch: 41 batch: 0/4, loss: 0.002310
2023-06-28 09:11:39.072431 Validation: avg loss: 1.4089, avg acc: 63.8095%
2023-06-28 09:12:06.351316 Train: epoch: 42 batch: 0/4, loss: 0.000786
2023-06-28 09:13:32.427274 Validation: avg loss: 1.4184, avg acc: 62.8571%
2023-06-28 09:13:59.661877 Train: epoch: 43 batch: 0/4, loss: 0.001685
2023-06-28 09:15:25.888399 Validation: avg loss: 1.4266, avg acc: 61.9048%
2023-06-28 09:15:53.171462 Train: epoch: 44 batch: 0/4, loss: 0.001640
2023-06-28 09:17:19.262170 Validation: avg loss: 1.4425, avg acc: 60.9524%
2023-06-28 09:17:46.526654 Train: epoch: 45 batch: 0/4, loss: 0.001274
2023-06-28 09:19:12.704281 Validation: avg loss: 1.4459, avg acc: 61.9048%
2023-06-28 09:19:39.967872 Train: epoch: 46 batch: 0/4, loss: 0.001791
2023-06-28 09:21:06.099777 Validation: avg loss: 1.4501, avg acc: 62.8571%
2023-06-28 09:21:33.314902 Train: epoch: 47 batch: 0/4, loss: 0.000593
2023-06-28 09:22:59.414822 Validation: avg loss: 1.4475, avg acc: 62.8571%
2023-06-28 09:23:26.633884 Train: epoch: 48 batch: 0/4, loss: 0.000778
2023-06-28 09:24:52.704704 Validation: avg loss: 1.4512, avg acc: 62.8571%
2023-06-28 09:25:19.932972 Train: epoch: 49 batch: 0/4, loss: 0.001332
2023-06-28 09:26:45.943631 Validation: avg loss: 1.4538, avg acc: 63.8095%
2023-06-28 09:27:13.207584 Train: epoch: 50 batch: 0/4, loss: 0.000809
2023-06-28 09:28:39.203569 Validation: avg loss: 1.4621, avg acc: 62.8571%
results/dcu/dt_230627015932.log 0 → 100644
View file @ c3426f6e
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results/dcu/dt_230627033349.log 0 → 100644
View file @ c3426f6e
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results/dcu/dt_230627050801.log 0 → 100644
View file @ c3426f6e
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results/dcu/dt_230627064222.log 0 → 100644
View file @ c3426f6e
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