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%