2023-06-28 03:59:12.580120  cuda
2023-06-28 03:59:26.750708  Train: epoch: 1 batch: 0/4, loss: 0.694612
2023-06-28 04:00:11.426282  Validation: avg loss: 0.6861, avg acc: 59.0476%
2023-06-28 04:00:25.908546  Train: epoch: 2 batch: 0/4, loss: 0.706914
2023-06-28 04:01:11.184999  Validation: avg loss: 0.6830, avg acc: 59.0476%
2023-06-28 04:01:25.798044  Train: epoch: 3 batch: 0/4, loss: 0.680926
2023-06-28 04:02:12.099444  Validation: avg loss: 0.6799, avg acc: 59.0476%
2023-06-28 04:02:26.460111  Train: epoch: 4 batch: 0/4, loss: 0.667983
2023-06-28 04:03:10.998068  Validation: avg loss: 0.6784, avg acc: 59.0476%
2023-06-28 04:03:25.196184  Train: epoch: 5 batch: 0/4, loss: 0.658656
2023-06-28 04:04:09.841678  Validation: avg loss: 0.6800, avg acc: 59.0476%
2023-06-28 04:04:24.079110  Train: epoch: 6 batch: 0/4, loss: 0.663088
2023-06-28 04:05:08.763914  Validation: avg loss: 0.6773, avg acc: 59.0476%
2023-06-28 04:05:23.003873  Train: epoch: 7 batch: 0/4, loss: 0.629996
2023-06-28 04:06:08.637310  Validation: avg loss: 0.6743, avg acc: 59.0476%
2023-06-28 04:06:23.407611  Train: epoch: 8 batch: 0/4, loss: 0.597220
2023-06-28 04:07:08.242516  Validation: avg loss: 0.6800, avg acc: 59.0476%
2023-06-28 04:07:22.526979  Train: epoch: 9 batch: 0/4, loss: 0.537858
2023-06-28 04:08:07.101244  Validation: avg loss: 0.6709, avg acc: 59.0476%
2023-06-28 04:08:21.328130  Train: epoch: 10 batch: 0/4, loss: 0.478460
2023-06-28 04:09:05.828543  Validation: avg loss: 0.6716, avg acc: 63.8095%
2023-06-28 04:09:19.873732  Train: epoch: 11 batch: 0/4, loss: 0.395090
2023-06-28 04:10:05.058702  Validation: avg loss: 0.6379, avg acc: 65.7143%
2023-06-28 04:10:19.285747  Train: epoch: 12 batch: 0/4, loss: 0.331272
2023-06-28 04:11:03.953933  Validation: avg loss: 0.6334, avg acc: 61.9048%
2023-06-28 04:11:18.090531  Train: epoch: 13 batch: 0/4, loss: 0.270222
2023-06-28 04:12:02.755340  Validation: avg loss: 0.5858, avg acc: 70.4762%
2023-06-28 04:12:16.950131  Train: epoch: 14 batch: 0/4, loss: 0.168852
2023-06-28 04:13:01.884081  Validation: avg loss: 0.5932, avg acc: 64.7619%
2023-06-28 04:13:16.075769  Train: epoch: 15 batch: 0/4, loss: 0.140117
2023-06-28 04:14:01.014580  Validation: avg loss: 0.6184, avg acc: 67.6190%
2023-06-28 04:14:15.406445  Train: epoch: 16 batch: 0/4, loss: 0.100922
2023-06-28 04:15:00.611265  Validation: avg loss: 0.6841, avg acc: 62.8571%
2023-06-28 04:15:14.772177  Train: epoch: 17 batch: 0/4, loss: 0.064960
2023-06-28 04:15:59.270308  Validation: avg loss: 0.8381, avg acc: 60.0000%
2023-06-28 04:16:13.358347  Train: epoch: 18 batch: 0/4, loss: 0.041114
2023-06-28 04:16:58.412814  Validation: avg loss: 0.8127, avg acc: 63.8095%
2023-06-28 04:17:12.859787  Train: epoch: 19 batch: 0/4, loss: 0.028654
2023-06-28 04:17:58.746568  Validation: avg loss: 0.8722, avg acc: 63.8095%
2023-06-28 04:18:13.193857  Train: epoch: 20 batch: 0/4, loss: 0.020548
2023-06-28 04:18:58.557002  Validation: avg loss: 1.0138, avg acc: 63.8095%
2023-06-28 04:19:12.811166  Train: epoch: 21 batch: 0/4, loss: 0.024834
2023-06-28 04:19:57.383134  Validation: avg loss: 1.1134, avg acc: 65.7143%
2023-06-28 04:20:11.593541  Train: epoch: 22 batch: 0/4, loss: 0.024447
2023-06-28 04:20:56.144567  Validation: avg loss: 1.1052, avg acc: 61.9048%
2023-06-28 04:21:10.280428  Train: epoch: 23 batch: 0/4, loss: 0.024402
2023-06-28 04:21:55.164144  Validation: avg loss: 1.0037, avg acc: 62.8571%
2023-06-28 04:22:09.484836  Train: epoch: 24 batch: 0/4, loss: 0.026940
2023-06-28 04:22:54.337155  Validation: avg loss: 1.1395, avg acc: 65.7143%
2023-06-28 04:23:08.575422  Train: epoch: 25 batch: 0/4, loss: 0.020789
2023-06-28 04:23:53.433541  Validation: avg loss: 1.1802, avg acc: 65.7143%
2023-06-28 04:24:07.944800  Train: epoch: 26 batch: 0/4, loss: 0.017444
2023-06-28 04:24:53.299679  Validation: avg loss: 1.0212, avg acc: 67.6190%
2023-06-28 04:25:07.765353  Train: epoch: 27 batch: 0/4, loss: 0.013250
2023-06-28 04:25:52.812562  Validation: avg loss: 0.9592, avg acc: 68.5714%
2023-06-28 04:26:07.260835  Train: epoch: 28 batch: 0/4, loss: 0.011131
2023-06-28 04:26:52.346310  Validation: avg loss: 1.1193, avg acc: 72.3810%
2023-06-28 04:27:06.644760  Train: epoch: 29 batch: 0/4, loss: 0.026329
2023-06-28 04:27:51.863781  Validation: avg loss: 1.1687, avg acc: 64.7619%
2023-06-28 04:28:05.962933  Train: epoch: 30 batch: 0/4, loss: 0.011010
2023-06-28 04:28:50.606240  Validation: avg loss: 1.1444, avg acc: 63.8095%
2023-06-28 04:29:04.812994  Train: epoch: 31 batch: 0/4, loss: 0.007555
2023-06-28 04:29:49.894941  Validation: avg loss: 1.2691, avg acc: 69.5238%
2023-06-28 04:30:04.020104  Train: epoch: 32 batch: 0/4, loss: 0.026084
2023-06-28 04:30:48.602736  Validation: avg loss: 1.3224, avg acc: 65.7143%
2023-06-28 04:31:02.668182  Train: epoch: 33 batch: 0/4, loss: 0.016953
2023-06-28 04:31:47.391245  Validation: avg loss: 1.3359, avg acc: 63.8095%
2023-06-28 04:32:01.694358  Train: epoch: 34 batch: 0/4, loss: 0.007214
2023-06-28 04:32:46.917156  Validation: avg loss: 1.2960, avg acc: 64.7619%
2023-06-28 04:33:01.216805  Train: epoch: 35 batch: 0/4, loss: 0.016135
2023-06-28 04:33:52.554001  Validation: avg loss: 1.3414, avg acc: 66.6667%
2023-06-28 04:34:09.581260  Train: epoch: 36 batch: 0/4, loss: 0.005827
2023-06-28 04:35:03.567810  Validation: avg loss: 1.4429, avg acc: 63.8095%
2023-06-28 04:35:20.656888  Train: epoch: 37 batch: 0/4, loss: 0.003277
2023-06-28 04:36:14.468588  Validation: avg loss: 1.5331, avg acc: 63.8095%
2023-06-28 04:36:31.559136  Train: epoch: 38 batch: 0/4, loss: 0.006702
2023-06-28 04:37:25.303902  Validation: avg loss: 1.5363, avg acc: 64.7619%
2023-06-28 04:37:42.401555  Train: epoch: 39 batch: 0/4, loss: 0.006998
2023-06-28 04:38:35.539481  Validation: avg loss: 1.5584, avg acc: 65.7143%
2023-06-28 04:38:52.511838  Train: epoch: 40 batch: 0/4, loss: 0.004243
2023-06-28 04:39:40.018935  Validation: avg loss: 1.5435, avg acc: 64.7619%
2023-06-28 04:39:54.218691  Train: epoch: 41 batch: 0/4, loss: 0.005694
2023-06-28 04:40:39.406743  Validation: avg loss: 1.5224, avg acc: 65.7143%
2023-06-28 04:40:53.614415  Train: epoch: 42 batch: 0/4, loss: 0.002508
2023-06-28 04:41:38.977191  Validation: avg loss: 1.4839, avg acc: 62.8571%
2023-06-28 04:41:53.546677  Train: epoch: 43 batch: 0/4, loss: 0.005065
2023-06-28 04:42:38.615712  Validation: avg loss: 1.4694, avg acc: 62.8571%
2023-06-28 04:42:52.866949  Train: epoch: 44 batch: 0/4, loss: 0.001588
2023-06-28 04:43:37.419490  Validation: avg loss: 1.4595, avg acc: 60.9524%
2023-06-28 04:43:51.441179  Train: epoch: 45 batch: 0/4, loss: 0.002320
2023-06-28 04:44:36.373416  Validation: avg loss: 1.4140, avg acc: 66.6667%
2023-06-28 04:44:50.575468  Train: epoch: 46 batch: 0/4, loss: 0.001628
2023-06-28 04:45:36.094658  Validation: avg loss: 1.3962, avg acc: 66.6667%
2023-06-28 04:45:50.360514  Train: epoch: 47 batch: 0/4, loss: 0.001421
2023-06-28 04:46:35.518807  Validation: avg loss: 1.3719, avg acc: 64.7619%
2023-06-28 04:46:49.783401  Train: epoch: 48 batch: 0/4, loss: 0.001688
2023-06-28 04:47:34.452598  Validation: avg loss: 1.3766, avg acc: 67.6190%
2023-06-28 04:47:48.920135  Train: epoch: 49 batch: 0/4, loss: 0.001522
2023-06-28 04:48:34.555909  Validation: avg loss: 1.3792, avg acc: 67.6190%
2023-06-28 04:48:48.703559  Train: epoch: 50 batch: 0/4, loss: 0.000546
2023-06-28 04:49:34.074328  Validation: avg loss: 1.3799, avg acc: 67.6190%