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%