230627112543.log

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%