2023-06-27 16:09:42.034579  cuda
2023-06-27 16:10:09.076819  Train: epoch: 1 batch: 0/4, loss: 0.689472
2023-06-27 16:11:35.174440  Validation: avg loss: 0.6920, avg acc: 56.1905%
2023-06-27 16:12:02.321326  Train: epoch: 2 batch: 0/4, loss: 0.716974
2023-06-27 16:13:28.541905  Validation: avg loss: 0.6863, avg acc: 56.1905%
2023-06-27 16:13:55.708802  Train: epoch: 3 batch: 0/4, loss: 0.690668
2023-06-27 16:15:21.903504  Validation: avg loss: 0.6862, avg acc: 56.1905%
2023-06-27 16:15:49.073698  Train: epoch: 4 batch: 0/4, loss: 0.651886
2023-06-27 16:17:15.391097  Validation: avg loss: 0.6885, avg acc: 56.1905%
2023-06-27 16:17:42.588880  Train: epoch: 5 batch: 0/4, loss: 0.654914
2023-06-27 16:19:08.607998  Validation: avg loss: 0.6970, avg acc: 56.1905%
2023-06-27 16:19:35.835676  Train: epoch: 6 batch: 0/4, loss: 0.635806
2023-06-27 16:21:02.088965  Validation: avg loss: 0.7131, avg acc: 56.1905%
2023-06-27 16:21:29.316734  Train: epoch: 7 batch: 0/4, loss: 0.629673
2023-06-27 16:22:55.424383  Validation: avg loss: 0.7514, avg acc: 56.1905%
2023-06-27 16:23:22.544005  Train: epoch: 8 batch: 0/4, loss: 0.563512
2023-06-27 16:24:48.721804  Validation: avg loss: 0.7544, avg acc: 56.1905%
2023-06-27 16:25:15.907744  Train: epoch: 9 batch: 0/4, loss: 0.547313
2023-06-27 16:26:42.443779  Validation: avg loss: 0.7992, avg acc: 56.1905%
2023-06-27 16:27:09.783645  Train: epoch: 10 batch: 0/4, loss: 0.444450
2023-06-27 16:28:36.109380  Validation: avg loss: 0.8431, avg acc: 56.1905%
2023-06-27 16:29:03.340309  Train: epoch: 11 batch: 0/4, loss: 0.363815
2023-06-27 16:30:29.692076  Validation: avg loss: 0.9948, avg acc: 56.1905%
2023-06-27 16:30:56.891684  Train: epoch: 12 batch: 0/4, loss: 0.274682
2023-06-27 16:32:23.120135  Validation: avg loss: 0.9824, avg acc: 56.1905%
2023-06-27 16:32:50.288607  Train: epoch: 13 batch: 0/4, loss: 0.226884
2023-06-27 16:34:16.507697  Validation: avg loss: 1.0053, avg acc: 56.1905%
2023-06-27 16:34:43.726781  Train: epoch: 14 batch: 0/4, loss: 0.165106
2023-06-27 16:36:09.819922  Validation: avg loss: 0.9196, avg acc: 58.0952%
2023-06-27 16:36:37.091113  Train: epoch: 15 batch: 0/4, loss: 0.102541
2023-06-27 16:38:03.361117  Validation: avg loss: 0.9440, avg acc: 58.0952%
2023-06-27 16:38:30.537668  Train: epoch: 16 batch: 0/4, loss: 0.084653
2023-06-27 16:39:56.678072  Validation: avg loss: 0.9750, avg acc: 60.0000%
2023-06-27 16:40:23.933856  Train: epoch: 17 batch: 0/4, loss: 0.093461
2023-06-27 16:41:50.392128  Validation: avg loss: 0.9532, avg acc: 63.8095%
2023-06-27 16:42:17.568810  Train: epoch: 18 batch: 0/4, loss: 0.040381
2023-06-27 16:43:43.546950  Validation: avg loss: 0.9573, avg acc: 62.8571%
2023-06-27 16:44:10.708190  Train: epoch: 19 batch: 0/4, loss: 0.038573
2023-06-27 16:45:36.914874  Validation: avg loss: 0.9937, avg acc: 67.6190%
2023-06-27 16:46:04.137257  Train: epoch: 20 batch: 0/4, loss: 0.038389
2023-06-27 16:47:30.440530  Validation: avg loss: 1.0789, avg acc: 65.7143%
2023-06-27 16:47:57.631426  Train: epoch: 21 batch: 0/4, loss: 0.010777
2023-06-27 16:49:23.780402  Validation: avg loss: 1.1505, avg acc: 66.6667%
2023-06-27 16:49:51.060769  Train: epoch: 22 batch: 0/4, loss: 0.011703
2023-06-27 16:51:17.385118  Validation: avg loss: 1.2451, avg acc: 62.8571%
2023-06-27 16:51:44.631865  Train: epoch: 23 batch: 0/4, loss: 0.007243
2023-06-27 16:53:10.944555  Validation: avg loss: 1.3300, avg acc: 61.9048%
2023-06-27 16:53:38.203599  Train: epoch: 24 batch: 0/4, loss: 0.006529
2023-06-27 16:55:04.414313  Validation: avg loss: 1.3780, avg acc: 63.8095%
2023-06-27 16:55:31.700853  Train: epoch: 25 batch: 0/4, loss: 0.005980
2023-06-27 16:56:58.079196  Validation: avg loss: 1.3814, avg acc: 65.7143%
2023-06-27 16:57:25.220443  Train: epoch: 26 batch: 0/4, loss: 0.005226
2023-06-27 16:58:51.518167  Validation: avg loss: 1.4504, avg acc: 62.8571%
2023-06-27 16:59:18.711172  Train: epoch: 27 batch: 0/4, loss: 0.005868
2023-06-27 17:00:45.168958  Validation: avg loss: 1.5561, avg acc: 60.0000%
2023-06-27 17:01:12.415606  Train: epoch: 28 batch: 0/4, loss: 0.011277
2023-06-27 17:02:38.557493  Validation: avg loss: 1.5640, avg acc: 60.9524%
2023-06-27 17:03:05.696062  Train: epoch: 29 batch: 0/4, loss: 0.005151
2023-06-27 17:04:31.874819  Validation: avg loss: 1.5746, avg acc: 64.7619%
2023-06-27 17:04:59.035746  Train: epoch: 30 batch: 0/4, loss: 0.006748
2023-06-27 17:06:25.381774  Validation: avg loss: 1.5758, avg acc: 65.7143%
2023-06-27 17:06:52.735323  Train: epoch: 31 batch: 0/4, loss: 0.005076
2023-06-27 17:08:19.418008  Validation: avg loss: 1.5240, avg acc: 66.6667%
2023-06-27 17:08:46.733625  Train: epoch: 32 batch: 0/4, loss: 0.005442
2023-06-27 17:10:13.234751  Validation: avg loss: 1.4960, avg acc: 66.6667%
2023-06-27 17:10:40.528432  Train: epoch: 33 batch: 0/4, loss: 0.003327
2023-06-27 17:12:07.297788  Validation: avg loss: 1.5235, avg acc: 65.7143%
2023-06-27 17:12:34.617996  Train: epoch: 34 batch: 0/4, loss: 0.002123
2023-06-27 17:14:01.261567  Validation: avg loss: 1.5658, avg acc: 65.7143%
2023-06-27 17:14:28.510759  Train: epoch: 35 batch: 0/4, loss: 0.002863
2023-06-27 17:15:55.225065  Validation: avg loss: 1.6060, avg acc: 64.7619%
2023-06-27 17:16:22.480585  Train: epoch: 36 batch: 0/4, loss: 0.012008
2023-06-27 17:17:48.907176  Validation: avg loss: 1.6271, avg acc: 62.8571%
2023-06-27 17:18:16.266273  Train: epoch: 37 batch: 0/4, loss: 0.002597
2023-06-27 17:19:43.435027  Validation: avg loss: 1.6503, avg acc: 64.7619%
2023-06-27 17:20:10.827029  Train: epoch: 38 batch: 0/4, loss: 0.001793
2023-06-27 17:21:37.592658  Validation: avg loss: 1.6299, avg acc: 65.7143%
2023-06-27 17:22:04.882773  Train: epoch: 39 batch: 0/4, loss: 0.002763
2023-06-27 17:23:31.337687  Validation: avg loss: 1.6197, avg acc: 65.7143%
2023-06-27 17:23:58.617221  Train: epoch: 40 batch: 0/4, loss: 0.003522
2023-06-27 17:25:25.155248  Validation: avg loss: 1.6265, avg acc: 64.7619%
2023-06-27 17:25:52.382030  Train: epoch: 41 batch: 0/4, loss: 0.002152
2023-06-27 17:27:18.837014  Validation: avg loss: 1.6280, avg acc: 65.7143%
2023-06-27 17:27:46.040369  Train: epoch: 42 batch: 0/4, loss: 0.001350
2023-06-27 17:29:12.528662  Validation: avg loss: 1.6349, avg acc: 63.8095%
2023-06-27 17:29:39.697519  Train: epoch: 43 batch: 0/4, loss: 0.001068
2023-06-27 17:31:05.928921  Validation: avg loss: 1.6347, avg acc: 63.8095%
2023-06-27 17:31:33.115344  Train: epoch: 44 batch: 0/4, loss: 0.001226
2023-06-27 17:32:59.337595  Validation: avg loss: 1.6424, avg acc: 63.8095%
2023-06-27 17:33:26.538144  Train: epoch: 45 batch: 0/4, loss: 0.001703
2023-06-27 17:34:52.829378  Validation: avg loss: 1.6544, avg acc: 63.8095%
2023-06-27 17:35:20.005291  Train: epoch: 46 batch: 0/4, loss: 0.000946
2023-06-27 17:36:46.480670  Validation: avg loss: 1.6794, avg acc: 63.8095%
2023-06-27 17:37:13.757354  Train: epoch: 47 batch: 0/4, loss: 0.001093
2023-06-27 17:38:40.118579  Validation: avg loss: 1.6843, avg acc: 63.8095%
2023-06-27 17:39:07.209172  Train: epoch: 48 batch: 0/4, loss: 0.001040
2023-06-27 17:40:33.402375  Validation: avg loss: 1.6992, avg acc: 63.8095%
2023-06-27 17:41:00.565175  Train: epoch: 49 batch: 0/4, loss: 0.001660
2023-06-27 17:42:26.801610  Validation: avg loss: 1.6996, avg acc: 63.8095%
2023-06-27 17:42:53.930828  Train: epoch: 50 batch: 0/4, loss: 0.001118
2023-06-27 17:44:20.225669  Validation: avg loss: 1.7042, avg acc: 63.8095%