230627033349.log

2023-06-27 03:33:49.620538  cuda
2023-06-27 03:34:16.530640  Train: epoch: 1 batch: 0/4, loss: 0.693080
2023-06-27 03:35:41.806763  Validation: avg loss: 0.6870, avg acc: 58.0952%
2023-06-27 03:36:08.742024  Train: epoch: 2 batch: 0/4, loss: 0.677773
2023-06-27 03:37:34.191173  Validation: avg loss: 0.6835, avg acc: 58.0952%
2023-06-27 03:38:01.231267  Train: epoch: 3 batch: 0/4, loss: 0.673670
2023-06-27 03:39:26.649802  Validation: avg loss: 0.6825, avg acc: 58.0952%
2023-06-27 03:39:53.565106  Train: epoch: 4 batch: 0/4, loss: 0.680140
2023-06-27 03:41:18.969671  Validation: avg loss: 0.6821, avg acc: 58.0952%
2023-06-27 03:41:45.893202  Train: epoch: 5 batch: 0/4, loss: 0.631272
2023-06-27 03:43:11.322387  Validation: avg loss: 0.6810, avg acc: 58.0952%
2023-06-27 03:43:38.272657  Train: epoch: 6 batch: 0/4, loss: 0.608761
2023-06-27 03:45:03.721667  Validation: avg loss: 0.6815, avg acc: 58.0952%
2023-06-27 03:45:30.705582  Train: epoch: 7 batch: 0/4, loss: 0.601036
2023-06-27 03:46:56.087300  Validation: avg loss: 0.6981, avg acc: 58.0952%
2023-06-27 03:47:23.023310  Train: epoch: 8 batch: 0/4, loss: 0.603923
2023-06-27 03:48:48.390601  Validation: avg loss: 0.6952, avg acc: 58.0952%
2023-06-27 03:49:15.382933  Train: epoch: 9 batch: 0/4, loss: 0.470182
2023-06-27 03:50:40.781453  Validation: avg loss: 0.6828, avg acc: 58.0952%
2023-06-27 03:51:07.874860  Train: epoch: 10 batch: 0/4, loss: 0.386110
2023-06-27 03:52:33.215767  Validation: avg loss: 0.7465, avg acc: 58.0952%
2023-06-27 03:53:00.156132  Train: epoch: 11 batch: 0/4, loss: 0.397895
2023-06-27 03:54:25.536366  Validation: avg loss: 0.7050, avg acc: 58.0952%
2023-06-27 03:54:52.469428  Train: epoch: 12 batch: 0/4, loss: 0.262515
2023-06-27 03:56:17.898705  Validation: avg loss: 0.7457, avg acc: 57.1429%
2023-06-27 03:56:44.895663  Train: epoch: 13 batch: 0/4, loss: 0.224342
2023-06-27 03:58:10.393033  Validation: avg loss: 0.7781, avg acc: 63.8095%
2023-06-27 03:58:37.311181  Train: epoch: 14 batch: 0/4, loss: 0.134823
2023-06-27 04:00:02.594674  Validation: avg loss: 0.7340, avg acc: 60.9524%
2023-06-27 04:00:29.503775  Train: epoch: 15 batch: 0/4, loss: 0.126792
2023-06-27 04:01:54.777270  Validation: avg loss: 0.7953, avg acc: 60.9524%
2023-06-27 04:02:21.955920  Train: epoch: 16 batch: 0/4, loss: 0.114732
2023-06-27 04:03:48.180689  Validation: avg loss: 0.9175, avg acc: 62.8571%
2023-06-27 04:04:15.437565  Train: epoch: 17 batch: 0/4, loss: 0.040243
2023-06-27 04:05:41.646578  Validation: avg loss: 1.0110, avg acc: 59.0476%
2023-06-27 04:06:08.802477  Train: epoch: 18 batch: 0/4, loss: 0.029593
2023-06-27 04:07:34.864507  Validation: avg loss: 0.9962, avg acc: 60.0000%
2023-06-27 04:08:02.075055  Train: epoch: 19 batch: 0/4, loss: 0.019918
2023-06-27 04:09:28.146785  Validation: avg loss: 1.0330, avg acc: 61.9048%
2023-06-27 04:09:55.344057  Train: epoch: 20 batch: 0/4, loss: 0.013042
2023-06-27 04:11:21.367763  Validation: avg loss: 1.1118, avg acc: 60.9524%
2023-06-27 04:11:48.596764  Train: epoch: 21 batch: 0/4, loss: 0.029912
2023-06-27 04:13:14.732747  Validation: avg loss: 1.2075, avg acc: 60.0000%
2023-06-27 04:13:41.908463  Train: epoch: 22 batch: 0/4, loss: 0.018193
2023-06-27 04:15:07.903724  Validation: avg loss: 1.2723, avg acc: 63.8095%
2023-06-27 04:15:35.079332  Train: epoch: 23 batch: 0/4, loss: 0.012390
2023-06-27 04:17:01.043754  Validation: avg loss: 1.2906, avg acc: 61.9048%
2023-06-27 04:17:28.257118  Train: epoch: 24 batch: 0/4, loss: 0.007024
2023-06-27 04:18:54.271198  Validation: avg loss: 1.3381, avg acc: 62.8571%
2023-06-27 04:19:21.468763  Train: epoch: 25 batch: 0/4, loss: 0.014566
2023-06-27 04:20:47.772050  Validation: avg loss: 1.4036, avg acc: 61.9048%
2023-06-27 04:21:15.024444  Train: epoch: 26 batch: 0/4, loss: 0.003964
2023-06-27 04:22:41.461127  Validation: avg loss: 1.4325, avg acc: 62.8571%
2023-06-27 04:23:08.790864  Train: epoch: 27 batch: 0/4, loss: 0.004086
2023-06-27 04:24:35.101757  Validation: avg loss: 1.4324, avg acc: 61.9048%
2023-06-27 04:25:02.417699  Train: epoch: 28 batch: 0/4, loss: 0.008229
2023-06-27 04:26:28.885759  Validation: avg loss: 1.4633, avg acc: 61.9048%
2023-06-27 04:26:56.150808  Train: epoch: 29 batch: 0/4, loss: 0.008524
2023-06-27 04:28:22.438783  Validation: avg loss: 1.5122, avg acc: 60.9524%
2023-06-27 04:28:49.761823  Train: epoch: 30 batch: 0/4, loss: 0.004061
2023-06-27 04:30:16.127859  Validation: avg loss: 1.5431, avg acc: 60.9524%
2023-06-27 04:30:43.331688  Train: epoch: 31 batch: 0/4, loss: 0.007024
2023-06-27 04:32:09.483676  Validation: avg loss: 1.5391, avg acc: 61.9048%
2023-06-27 04:32:36.662683  Train: epoch: 32 batch: 0/4, loss: 0.002247
2023-06-27 04:34:02.664147  Validation: avg loss: 1.5419, avg acc: 61.9048%
2023-06-27 04:34:29.873437  Train: epoch: 33 batch: 0/4, loss: 0.002192
2023-06-27 04:35:55.931510  Validation: avg loss: 1.5424, avg acc: 60.9524%
2023-06-27 04:36:23.090882  Train: epoch: 34 batch: 0/4, loss: 0.001588
2023-06-27 04:37:49.141448  Validation: avg loss: 1.5662, avg acc: 60.9524%
2023-06-27 04:38:16.305874  Train: epoch: 35 batch: 0/4, loss: 0.001755
2023-06-27 04:39:42.380459  Validation: avg loss: 1.5682, avg acc: 60.9524%
2023-06-27 04:40:09.618126  Train: epoch: 36 batch: 0/4, loss: 0.001248
2023-06-27 04:41:35.701780  Validation: avg loss: 1.5553, avg acc: 60.9524%
2023-06-27 04:42:02.954181  Train: epoch: 37 batch: 0/4, loss: 0.001146
2023-06-27 04:43:29.042723  Validation: avg loss: 1.5398, avg acc: 61.9048%
2023-06-27 04:43:56.233850  Train: epoch: 38 batch: 0/4, loss: 0.001596
2023-06-27 04:45:22.520642  Validation: avg loss: 1.5308, avg acc: 61.9048%
2023-06-27 04:45:49.661671  Train: epoch: 39 batch: 0/4, loss: 0.003090
2023-06-27 04:47:15.754206  Validation: avg loss: 1.5261, avg acc: 62.8571%
2023-06-27 04:47:42.930905  Train: epoch: 40 batch: 0/4, loss: 0.001614
2023-06-27 04:49:09.075421  Validation: avg loss: 1.5337, avg acc: 62.8571%
2023-06-27 04:49:36.347485  Train: epoch: 41 batch: 0/4, loss: 0.001224
2023-06-27 04:51:02.533730  Validation: avg loss: 1.5332, avg acc: 60.9524%
2023-06-27 04:51:29.771878  Train: epoch: 42 batch: 0/4, loss: 0.001751
2023-06-27 04:52:55.889034  Validation: avg loss: 1.5426, avg acc: 60.0000%
2023-06-27 04:53:23.095702  Train: epoch: 43 batch: 0/4, loss: 0.000911
2023-06-27 04:54:49.249387  Validation: avg loss: 1.5437, avg acc: 60.0000%
2023-06-27 04:55:16.344639  Train: epoch: 44 batch: 0/4, loss: 0.000856
2023-06-27 04:56:42.462039  Validation: avg loss: 1.5554, avg acc: 60.0000%
2023-06-27 04:57:09.636866  Train: epoch: 45 batch: 0/4, loss: 0.000915
2023-06-27 04:58:35.815228  Validation: avg loss: 1.5604, avg acc: 60.9524%
2023-06-27 04:59:02.971681  Train: epoch: 46 batch: 0/4, loss: 0.000812
2023-06-27 05:00:29.061047  Validation: avg loss: 1.5614, avg acc: 60.9524%
2023-06-27 05:00:56.206586  Train: epoch: 47 batch: 0/4, loss: 0.000677
2023-06-27 05:02:22.282724  Validation: avg loss: 1.5675, avg acc: 61.9048%
2023-06-27 05:02:49.470639  Train: epoch: 48 batch: 0/4, loss: 0.000872
2023-06-27 05:04:15.620676  Validation: avg loss: 1.5682, avg acc: 60.9524%
2023-06-27 05:04:42.754795  Train: epoch: 49 batch: 0/4, loss: 0.000688
2023-06-27 05:06:08.739963  Validation: avg loss: 1.5752, avg acc: 61.9048%
2023-06-27 05:06:35.853730  Train: epoch: 50 batch: 0/4, loss: 0.000888
2023-06-27 05:08:01.872036  Validation: avg loss: 1.5715, avg acc: 61.9048%