230627205320.log

2023-06-27 20:53:20.629151  cuda
2023-06-27 20:53:47.748434  Train: epoch: 1 batch: 0/4, loss: 0.692955
2023-06-27 20:55:13.964674  Validation: avg loss: 0.6897, avg acc: 56.1905%
2023-06-27 20:55:41.177435  Train: epoch: 2 batch: 0/4, loss: 0.675517
2023-06-27 20:57:07.274298  Validation: avg loss: 0.6863, avg acc: 56.1905%
2023-06-27 20:57:34.461939  Train: epoch: 3 batch: 0/4, loss: 0.675015
2023-06-27 20:59:00.491545  Validation: avg loss: 0.6910, avg acc: 56.1905%
2023-06-27 20:59:27.647846  Train: epoch: 4 batch: 0/4, loss: 0.674206
2023-06-27 21:00:53.827621  Validation: avg loss: 0.6909, avg acc: 56.1905%
2023-06-27 21:01:21.062216  Train: epoch: 5 batch: 0/4, loss: 0.645392
2023-06-27 21:02:47.200772  Validation: avg loss: 0.6861, avg acc: 56.1905%
2023-06-27 21:03:14.390030  Train: epoch: 6 batch: 0/4, loss: 0.621112
2023-06-27 21:04:40.294124  Validation: avg loss: 0.6872, avg acc: 56.1905%
2023-06-27 21:05:07.527156  Train: epoch: 7 batch: 0/4, loss: 0.625907
2023-06-27 21:06:33.555837  Validation: avg loss: 0.6899, avg acc: 53.3333%
2023-06-27 21:07:00.698690  Train: epoch: 8 batch: 0/4, loss: 0.516206
2023-06-27 21:08:26.841992  Validation: avg loss: 0.6903, avg acc: 57.1429%
2023-06-27 21:08:54.105375  Train: epoch: 9 batch: 0/4, loss: 0.444898
2023-06-27 21:10:20.483318  Validation: avg loss: 0.7007, avg acc: 44.7619%
2023-06-27 21:10:47.754366  Train: epoch: 10 batch: 0/4, loss: 0.370775
2023-06-27 21:12:14.150308  Validation: avg loss: 0.6906, avg acc: 59.0476%
2023-06-27 21:12:41.539462  Train: epoch: 11 batch: 0/4, loss: 0.356873
2023-06-27 21:14:08.025503  Validation: avg loss: 0.6832, avg acc: 60.0000%
2023-06-27 21:14:35.276802  Train: epoch: 12 batch: 0/4, loss: 0.223474
2023-06-27 21:16:01.640456  Validation: avg loss: 0.7128, avg acc: 56.1905%
2023-06-27 21:16:28.932089  Train: epoch: 13 batch: 0/4, loss: 0.187091
2023-06-27 21:17:55.253539  Validation: avg loss: 0.7330, avg acc: 57.1429%
2023-06-27 21:18:22.535979  Train: epoch: 14 batch: 0/4, loss: 0.104829
2023-06-27 21:19:49.039828  Validation: avg loss: 0.8461, avg acc: 55.2381%
2023-06-27 21:20:16.279672  Train: epoch: 15 batch: 0/4, loss: 0.067174
2023-06-27 21:21:42.707410  Validation: avg loss: 0.9349, avg acc: 53.3333%
2023-06-27 21:22:10.102342  Train: epoch: 16 batch: 0/4, loss: 0.057731
2023-06-27 21:23:36.458363  Validation: avg loss: 1.0388, avg acc: 55.2381%
2023-06-27 21:24:03.725265  Train: epoch: 17 batch: 0/4, loss: 0.022758
2023-06-27 21:25:30.213156  Validation: avg loss: 1.1726, avg acc: 52.3810%
2023-06-27 21:25:57.543603  Train: epoch: 18 batch: 0/4, loss: 0.017001
2023-06-27 21:27:24.030243  Validation: avg loss: 1.4126, avg acc: 52.3810%
2023-06-27 21:27:51.378713  Train: epoch: 19 batch: 0/4, loss: 0.017968
2023-06-27 21:29:17.739281  Validation: avg loss: 1.5709, avg acc: 49.5238%
2023-06-27 21:29:45.028343  Train: epoch: 20 batch: 0/4, loss: 0.022907
2023-06-27 21:31:11.377903  Validation: avg loss: 1.6647, avg acc: 50.4762%
2023-06-27 21:31:38.682689  Train: epoch: 21 batch: 0/4, loss: 0.011941
2023-06-27 21:33:05.134857  Validation: avg loss: 1.7595, avg acc: 52.3810%
2023-06-27 21:33:32.525653  Train: epoch: 22 batch: 0/4, loss: 0.008407
2023-06-27 21:34:58.983933  Validation: avg loss: 1.7680, avg acc: 51.4286%
2023-06-27 21:35:26.219816  Train: epoch: 23 batch: 0/4, loss: 0.014117
2023-06-27 21:36:52.456195  Validation: avg loss: 1.7327, avg acc: 53.3333%
2023-06-27 21:37:19.758374  Train: epoch: 24 batch: 0/4, loss: 0.009515
2023-06-27 21:38:46.095581  Validation: avg loss: 1.7344, avg acc: 53.3333%
2023-06-27 21:39:13.278819  Train: epoch: 25 batch: 0/4, loss: 0.008577
2023-06-27 21:40:39.589178  Validation: avg loss: 1.7697, avg acc: 51.4286%
2023-06-27 21:41:06.756922  Train: epoch: 26 batch: 0/4, loss: 0.003460
2023-06-27 21:42:32.847901  Validation: avg loss: 1.7216, avg acc: 48.5714%
2023-06-27 21:43:00.057556  Train: epoch: 27 batch: 0/4, loss: 0.006079
2023-06-27 21:44:26.144239  Validation: avg loss: 1.7539, avg acc: 49.5238%
2023-06-27 21:44:53.260106  Train: epoch: 28 batch: 0/4, loss: 0.015600
2023-06-27 21:46:19.290912  Validation: avg loss: 1.8366, avg acc: 54.2857%
2023-06-27 21:46:46.481769  Train: epoch: 29 batch: 0/4, loss: 0.004267
2023-06-27 21:48:12.409084  Validation: avg loss: 1.9022, avg acc: 52.3810%
2023-06-27 21:48:39.532274  Train: epoch: 30 batch: 0/4, loss: 0.005097
2023-06-27 21:50:05.514752  Validation: avg loss: 2.0331, avg acc: 47.6190%
2023-06-27 21:50:32.729193  Train: epoch: 31 batch: 0/4, loss: 0.003991
2023-06-27 21:51:58.762192  Validation: avg loss: 2.0587, avg acc: 49.5238%
2023-06-27 21:52:25.892686  Train: epoch: 32 batch: 0/4, loss: 0.011430
2023-06-27 21:53:51.739113  Validation: avg loss: 2.0254, avg acc: 49.5238%
2023-06-27 21:54:18.919470  Train: epoch: 33 batch: 0/4, loss: 0.009412
2023-06-27 21:55:44.906644  Validation: avg loss: 1.9933, avg acc: 51.4286%
2023-06-27 21:56:12.232801  Train: epoch: 34 batch: 0/4, loss: 0.006466
2023-06-27 21:57:38.328352  Validation: avg loss: 1.9766, avg acc: 54.2857%
2023-06-27 21:58:05.579668  Train: epoch: 35 batch: 0/4, loss: 0.003181
2023-06-27 21:59:31.524106  Validation: avg loss: 1.9970, avg acc: 54.2857%
2023-06-27 21:59:58.790838  Train: epoch: 36 batch: 0/4, loss: 0.003229
2023-06-27 22:01:24.934451  Validation: avg loss: 1.9907, avg acc: 51.4286%
2023-06-27 22:01:52.109059  Train: epoch: 37 batch: 0/4, loss: 0.002149
2023-06-27 22:03:18.531111  Validation: avg loss: 1.9838, avg acc: 53.3333%
2023-06-27 22:03:45.800694  Train: epoch: 38 batch: 0/4, loss: 0.001734
2023-06-27 22:05:12.074094  Validation: avg loss: 1.9819, avg acc: 53.3333%
2023-06-27 22:05:39.405459  Train: epoch: 39 batch: 0/4, loss: 0.004215
2023-06-27 22:07:05.682114  Validation: avg loss: 1.9822, avg acc: 54.2857%
2023-06-27 22:07:32.946940  Train: epoch: 40 batch: 0/4, loss: 0.001835
2023-06-27 22:08:59.288087  Validation: avg loss: 1.9775, avg acc: 52.3810%
2023-06-27 22:09:26.574157  Train: epoch: 41 batch: 0/4, loss: 0.001363
2023-06-27 22:10:52.773243  Validation: avg loss: 1.9909, avg acc: 51.4286%
2023-06-27 22:11:19.958399  Train: epoch: 42 batch: 0/4, loss: 0.007470
2023-06-27 22:12:45.994189  Validation: avg loss: 2.0147, avg acc: 54.2857%
2023-06-27 22:13:13.146665  Train: epoch: 43 batch: 0/4, loss: 0.001582
2023-06-27 22:14:39.139268  Validation: avg loss: 2.0680, avg acc: 53.3333%
2023-06-27 22:15:06.318827  Train: epoch: 44 batch: 0/4, loss: 0.001251
2023-06-27 22:16:32.359512  Validation: avg loss: 2.1104, avg acc: 51.4286%
2023-06-27 22:16:59.396425  Train: epoch: 45 batch: 0/4, loss: 0.001317
2023-06-27 22:18:25.293875  Validation: avg loss: 2.1194, avg acc: 54.2857%
2023-06-27 22:18:52.530135  Train: epoch: 46 batch: 0/4, loss: 0.001396
2023-06-27 22:20:18.375591  Validation: avg loss: 2.1648, avg acc: 54.2857%
2023-06-27 22:20:45.523274  Train: epoch: 47 batch: 0/4, loss: 0.000788
2023-06-27 22:22:11.602016  Validation: avg loss: 2.1987, avg acc: 52.3810%
2023-06-27 22:22:38.868759  Train: epoch: 48 batch: 0/4, loss: 0.001002
2023-06-27 22:24:05.110313  Validation: avg loss: 2.2087, avg acc: 51.4286%
2023-06-27 22:24:32.347761  Train: epoch: 49 batch: 0/4, loss: 0.001327
2023-06-27 22:25:58.485472  Validation: avg loss: 2.2049, avg acc: 51.4286%
2023-06-27 22:26:25.746957  Train: epoch: 50 batch: 0/4, loss: 0.001763
2023-06-27 22:27:51.799245  Validation: avg loss: 2.1766, avg acc: 52.3810%