230628044623.log

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%
2023-06-28 06:00:20.120731  Train: epoch: 40 batch: 0/4, loss: 0.001336
2023-06-28 06:01:45.720076  Validation: avg loss: 0.9944, avg acc: 72.3810%
2023-06-28 06:02:12.778589  Train: epoch: 41 batch: 0/4, loss: 0.002025
2023-06-28 06:03:38.405168  Validation: avg loss: 0.9941, avg acc: 73.3333%
2023-06-28 06:04:05.425404  Train: epoch: 42 batch: 0/4, loss: 0.001469
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%