2023-06-27 01:59:32.283091  cuda
2023-06-27 02:00:19.220679  Train: epoch: 1 batch: 0/4, loss: 0.692692
2023-06-27 02:01:45.056517  Validation: avg loss: 0.6880, avg acc: 56.1905%
2023-06-27 02:02:12.228852  Train: epoch: 2 batch: 0/4, loss: 0.658743
2023-06-27 02:03:38.560296  Validation: avg loss: 0.6877, avg acc: 56.1905%
2023-06-27 02:04:05.720454  Train: epoch: 3 batch: 0/4, loss: 0.657871
2023-06-27 02:05:32.169351  Validation: avg loss: 0.6854, avg acc: 56.1905%
2023-06-27 02:05:59.317089  Train: epoch: 4 batch: 0/4, loss: 0.666273
2023-06-27 02:07:25.685815  Validation: avg loss: 0.6877, avg acc: 56.1905%
2023-06-27 02:07:52.791185  Train: epoch: 5 batch: 0/4, loss: 0.645225
2023-06-27 02:09:19.154753  Validation: avg loss: 0.6858, avg acc: 56.1905%
2023-06-27 02:09:46.424731  Train: epoch: 6 batch: 0/4, loss: 0.623888
2023-06-27 02:11:12.928777  Validation: avg loss: 0.6847, avg acc: 56.1905%
2023-06-27 02:11:40.214777  Train: epoch: 7 batch: 0/4, loss: 0.580446
2023-06-27 02:13:06.533535  Validation: avg loss: 0.6864, avg acc: 56.1905%
2023-06-27 02:13:33.676289  Train: epoch: 8 batch: 0/4, loss: 0.567984
2023-06-27 02:15:00.074375  Validation: avg loss: 0.6962, avg acc: 43.8095%
2023-06-27 02:15:27.339969  Train: epoch: 9 batch: 0/4, loss: 0.498715
2023-06-27 02:16:53.824842  Validation: avg loss: 0.7143, avg acc: 43.8095%
2023-06-27 02:17:20.991042  Train: epoch: 10 batch: 0/4, loss: 0.412389
2023-06-27 02:18:47.339751  Validation: avg loss: 0.6938, avg acc: 52.3810%
2023-06-27 02:19:14.535807  Train: epoch: 11 batch: 0/4, loss: 0.431757
2023-06-27 02:20:41.104110  Validation: avg loss: 0.6764, avg acc: 59.0476%
2023-06-27 02:21:08.353358  Train: epoch: 12 batch: 0/4, loss: 0.341980
2023-06-27 02:22:34.747154  Validation: avg loss: 0.6907, avg acc: 55.2381%
2023-06-27 02:23:01.951064  Train: epoch: 13 batch: 0/4, loss: 0.191258
2023-06-27 02:24:28.526972  Validation: avg loss: 0.7229, avg acc: 52.3810%
2023-06-27 02:24:55.693149  Train: epoch: 14 batch: 0/4, loss: 0.197494
2023-06-27 02:26:22.101262  Validation: avg loss: 0.7343, avg acc: 61.9048%
2023-06-27 02:26:49.365855  Train: epoch: 15 batch: 0/4, loss: 0.131904
2023-06-27 02:28:15.880422  Validation: avg loss: 0.8183, avg acc: 60.9524%
2023-06-27 02:28:43.054247  Train: epoch: 16 batch: 0/4, loss: 0.054692
2023-06-27 02:30:09.060479  Validation: avg loss: 0.9153, avg acc: 60.0000%
2023-06-27 02:30:36.137310  Train: epoch: 17 batch: 0/4, loss: 0.050563
2023-06-27 02:32:02.117634  Validation: avg loss: 0.9844, avg acc: 60.9524%
2023-06-27 02:32:29.169731  Train: epoch: 18 batch: 0/4, loss: 0.053166
2023-06-27 02:33:55.137135  Validation: avg loss: 1.0830, avg acc: 60.9524%
2023-06-27 02:34:22.166846  Train: epoch: 19 batch: 0/4, loss: 0.032123
2023-06-27 02:35:48.367994  Validation: avg loss: 1.2188, avg acc: 59.0476%
2023-06-27 02:36:15.464687  Train: epoch: 20 batch: 0/4, loss: 0.011078
2023-06-27 02:37:41.546528  Validation: avg loss: 1.3116, avg acc: 58.0952%
2023-06-27 02:38:08.613742  Train: epoch: 21 batch: 0/4, loss: 0.009437
2023-06-27 02:39:34.745311  Validation: avg loss: 1.3991, avg acc: 60.0000%
2023-06-27 02:40:01.727573  Train: epoch: 22 batch: 0/4, loss: 0.008098
2023-06-27 02:41:27.959071  Validation: avg loss: 1.4563, avg acc: 60.9524%
2023-06-27 02:41:54.947086  Train: epoch: 23 batch: 0/4, loss: 0.005597
2023-06-27 02:43:20.979804  Validation: avg loss: 1.5111, avg acc: 58.0952%
2023-06-27 02:43:48.082680  Train: epoch: 24 batch: 0/4, loss: 0.007035
2023-06-27 02:45:13.880253  Validation: avg loss: 1.5491, avg acc: 58.0952%
2023-06-27 02:45:40.821902  Train: epoch: 25 batch: 0/4, loss: 0.014974
2023-06-27 02:47:06.215747  Validation: avg loss: 1.6083, avg acc: 59.0476%
2023-06-27 02:47:33.049431  Train: epoch: 26 batch: 0/4, loss: 0.009223
2023-06-27 02:48:58.230909  Validation: avg loss: 1.6236, avg acc: 58.0952%
2023-06-27 02:49:25.116434  Train: epoch: 27 batch: 0/4, loss: 0.004450
2023-06-27 02:50:50.249101  Validation: avg loss: 1.6272, avg acc: 60.9524%
2023-06-27 02:51:17.185289  Train: epoch: 28 batch: 0/4, loss: 0.004213
2023-06-27 02:52:42.417771  Validation: avg loss: 1.6348, avg acc: 60.0000%
2023-06-27 02:53:09.392169  Train: epoch: 29 batch: 0/4, loss: 0.007142
2023-06-27 02:54:34.479362  Validation: avg loss: 1.6620, avg acc: 60.0000%
2023-06-27 02:55:01.579140  Train: epoch: 30 batch: 0/4, loss: 0.002469
2023-06-27 02:56:26.774915  Validation: avg loss: 1.6754, avg acc: 58.0952%
2023-06-27 02:56:53.730580  Train: epoch: 31 batch: 0/4, loss: 0.001998
2023-06-27 02:58:18.914844  Validation: avg loss: 1.6636, avg acc: 58.0952%
2023-06-27 02:58:45.838359  Train: epoch: 32 batch: 0/4, loss: 0.004437
2023-06-27 03:00:11.088444  Validation: avg loss: 1.6740, avg acc: 56.1905%
2023-06-27 03:00:38.057626  Train: epoch: 33 batch: 0/4, loss: 0.003358
2023-06-27 03:02:03.267012  Validation: avg loss: 1.6721, avg acc: 58.0952%
2023-06-27 03:02:30.192813  Train: epoch: 34 batch: 0/4, loss: 0.007877
2023-06-27 03:03:55.370666  Validation: avg loss: 1.7256, avg acc: 57.1429%
2023-06-27 03:04:22.330398  Train: epoch: 35 batch: 0/4, loss: 0.002116
2023-06-27 03:05:47.533817  Validation: avg loss: 1.7264, avg acc: 57.1429%
2023-06-27 03:06:14.522816  Train: epoch: 36 batch: 0/4, loss: 0.002035
2023-06-27 03:07:39.757508  Validation: avg loss: 1.7241, avg acc: 58.0952%
2023-06-27 03:08:06.838154  Train: epoch: 37 batch: 0/4, loss: 0.002826
2023-06-27 03:09:31.977029  Validation: avg loss: 1.7297, avg acc: 57.1429%
2023-06-27 03:09:59.061422  Train: epoch: 38 batch: 0/4, loss: 0.003084
2023-06-27 03:11:24.248853  Validation: avg loss: 1.7399, avg acc: 56.1905%
2023-06-27 03:11:51.165653  Train: epoch: 39 batch: 0/4, loss: 0.001958
2023-06-27 03:13:16.253117  Validation: avg loss: 1.7405, avg acc: 57.1429%
2023-06-27 03:13:43.233199  Train: epoch: 40 batch: 0/4, loss: 0.001262
2023-06-27 03:15:08.475732  Validation: avg loss: 1.7326, avg acc: 56.1905%
2023-06-27 03:15:35.474762  Train: epoch: 41 batch: 0/4, loss: 0.001404
2023-06-27 03:17:00.632572  Validation: avg loss: 1.7311, avg acc: 56.1905%
2023-06-27 03:17:27.635665  Train: epoch: 42 batch: 0/4, loss: 0.001106
2023-06-27 03:18:52.923263  Validation: avg loss: 1.7361, avg acc: 56.1905%
2023-06-27 03:19:19.869122  Train: epoch: 43 batch: 0/4, loss: 0.001162
2023-06-27 03:20:44.935747  Validation: avg loss: 1.7377, avg acc: 56.1905%
2023-06-27 03:21:11.870147  Train: epoch: 44 batch: 0/4, loss: 0.001035
2023-06-27 03:22:36.973028  Validation: avg loss: 1.7479, avg acc: 56.1905%
2023-06-27 03:23:03.876731  Train: epoch: 45 batch: 0/4, loss: 0.000927
2023-06-27 03:24:28.880784  Validation: avg loss: 1.7523, avg acc: 57.1429%
2023-06-27 03:24:55.838651  Train: epoch: 46 batch: 0/4, loss: 0.001295
2023-06-27 03:26:20.951645  Validation: avg loss: 1.7522, avg acc: 57.1429%
2023-06-27 03:26:47.910058  Train: epoch: 47 batch: 0/4, loss: 0.000797
2023-06-27 03:28:13.000012  Validation: avg loss: 1.7620, avg acc: 58.0952%
2023-06-27 03:28:40.022628  Train: epoch: 48 batch: 0/4, loss: 0.000734
2023-06-27 03:30:05.314235  Validation: avg loss: 1.7688, avg acc: 57.1429%
2023-06-27 03:30:32.364647  Train: epoch: 49 batch: 0/4, loss: 0.000535
2023-06-27 03:31:57.393118  Validation: avg loss: 1.7718, avg acc: 57.1429%
2023-06-27 03:32:24.461149  Train: epoch: 50 batch: 0/4, loss: 0.000676
2023-06-27 03:33:49.586317  Validation: avg loss: 1.7748, avg acc: 56.1905%