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%
2023-06-28 00:04:52.317886  Train: epoch: 2 batch: 0/4, loss: 0.692181
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%
2023-06-28 01:05:16.432825  Train: epoch: 34 batch: 0/4, loss: 0.002133
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%