2023-06-28 00:37:49.978036 cuda 2023-06-28 00:38:04.069070 Train: epoch: 1 batch: 0/4, loss: 0.693067 2023-06-28 00:38:48.656869 Validation: avg loss: 0.6878, avg acc: 58.0952% 2023-06-28 00:39:02.850143 Train: epoch: 2 batch: 0/4, loss: 0.682373 2023-06-28 00:39:47.570461 Validation: avg loss: 0.6836, avg acc: 58.0952% 2023-06-28 00:40:01.779678 Train: epoch: 3 batch: 0/4, loss: 0.669462 2023-06-28 00:40:46.890763 Validation: avg loss: 0.6835, avg acc: 58.0952% 2023-06-28 00:41:01.120619 Train: epoch: 4 batch: 0/4, loss: 0.668123 2023-06-28 00:41:46.105633 Validation: avg loss: 0.6800, avg acc: 58.0952% 2023-06-28 00:42:00.231917 Train: epoch: 5 batch: 0/4, loss: 0.658780 2023-06-28 00:42:44.757819 Validation: avg loss: 0.6816, avg acc: 58.0952% 2023-06-28 00:42:59.100509 Train: epoch: 6 batch: 0/4, loss: 0.604294 2023-06-28 00:43:43.979090 Validation: avg loss: 0.6818, avg acc: 58.0952% 2023-06-28 00:43:58.482084 Train: epoch: 7 batch: 0/4, loss: 0.574335 2023-06-28 00:44:43.802849 Validation: avg loss: 0.6815, avg acc: 58.0952% 2023-06-28 00:44:58.409313 Train: epoch: 8 batch: 0/4, loss: 0.520112 2023-06-28 00:45:43.843513 Validation: avg loss: 0.6837, avg acc: 58.0952% 2023-06-28 00:45:58.441874 Train: epoch: 9 batch: 0/4, loss: 0.445718 2023-06-28 00:46:43.734008 Validation: avg loss: 0.6768, avg acc: 58.0952% 2023-06-28 00:46:58.006825 Train: epoch: 10 batch: 0/4, loss: 0.363334 2023-06-28 00:47:43.171838 Validation: avg loss: 0.6751, avg acc: 59.0476% 2023-06-28 00:47:57.698577 Train: epoch: 11 batch: 0/4, loss: 0.271284 2023-06-28 00:48:42.711409 Validation: avg loss: 0.6619, avg acc: 60.0000% 2023-06-28 00:48:56.879045 Train: epoch: 12 batch: 0/4, loss: 0.178573 2023-06-28 00:49:42.024172 Validation: avg loss: 0.6768, avg acc: 55.2381% 2023-06-28 00:49:56.148081 Train: epoch: 13 batch: 0/4, loss: 0.140371 2023-06-28 00:50:41.341682 Validation: avg loss: 0.7109, avg acc: 54.2857% 2023-06-28 00:50:55.610759 Train: epoch: 14 batch: 0/4, loss: 0.076913 2023-06-28 00:51:40.357213 Validation: avg loss: 0.8131, avg acc: 52.3810% 2023-06-28 00:51:54.583653 Train: epoch: 15 batch: 0/4, loss: 0.067480 2023-06-28 00:52:40.140130 Validation: avg loss: 0.9456, avg acc: 51.4286% 2023-06-28 00:52:54.397041 Train: epoch: 16 batch: 0/4, loss: 0.036423 2023-06-28 00:53:39.758018 Validation: avg loss: 1.0530, avg acc: 54.2857% 2023-06-28 00:53:54.317059 Train: epoch: 17 batch: 0/4, loss: 0.028782 2023-06-28 00:54:39.533123 Validation: avg loss: 1.1482, avg acc: 56.1905% 2023-06-28 00:54:53.869185 Train: epoch: 18 batch: 0/4, loss: 0.033167 2023-06-28 00:55:39.080207 Validation: avg loss: 1.1797, avg acc: 56.1905% 2023-06-28 00:55:53.126182 Train: epoch: 19 batch: 0/4, loss: 0.016202 2023-06-28 00:56:37.472863 Validation: avg loss: 1.2256, avg acc: 56.1905% 2023-06-28 00:56:51.590106 Train: epoch: 20 batch: 0/4, loss: 0.009053 2023-06-28 00:57:36.235819 Validation: avg loss: 1.2484, avg acc: 59.0476% 2023-06-28 00:57:50.430380 Train: epoch: 21 batch: 0/4, loss: 0.010292 2023-06-28 00:58:35.398258 Validation: avg loss: 1.3279, avg acc: 60.0000% 2023-06-28 00:58:49.667245 Train: epoch: 22 batch: 0/4, loss: 0.007880 2023-06-28 00:59:34.743015 Validation: avg loss: 1.3961, avg acc: 60.0000% 2023-06-28 00:59:48.869422 Train: epoch: 23 batch: 0/4, loss: 0.009219 2023-06-28 01:00:33.718706 Validation: avg loss: 1.4046, avg acc: 56.1905% 2023-06-28 01:00:47.940706 Train: epoch: 24 batch: 0/4, loss: 0.004677 2023-06-28 01:01:33.176631 Validation: avg loss: 1.3907, avg acc: 55.2381% 2023-06-28 01:01:47.409909 Train: epoch: 25 batch: 0/4, loss: 0.008842 2023-06-28 01:02:32.479701 Validation: avg loss: 1.4078, avg acc: 58.0952% 2023-06-28 01:02:46.858229 Train: epoch: 26 batch: 0/4, loss: 0.013503 2023-06-28 01:03:32.435670 Validation: avg loss: 1.4572, avg acc: 59.0476% 2023-06-28 01:03:47.368655 Train: epoch: 27 batch: 0/4, loss: 0.006626 2023-06-28 01:04:33.722813 Validation: avg loss: 1.4598, avg acc: 59.0476% 2023-06-28 01:04:48.451678 Train: epoch: 28 batch: 0/4, loss: 0.005886 2023-06-28 01:05:34.180051 Validation: avg loss: 1.4664, avg acc: 58.0952% 2023-06-28 01:05:48.434196 Train: epoch: 29 batch: 0/4, loss: 0.004940 2023-06-28 01:06:34.316611 Validation: avg loss: 1.4973, avg acc: 56.1905% 2023-06-28 01:06:48.578069 Train: epoch: 30 batch: 0/4, loss: 0.002945 2023-06-28 01:07:33.676803 Validation: avg loss: 1.5715, avg acc: 57.1429% 2023-06-28 01:07:48.010228 Train: epoch: 31 batch: 0/4, loss: 0.004101 2023-06-28 01:08:34.145123 Validation: avg loss: 1.5615, avg acc: 56.1905% 2023-06-28 01:08:48.956649 Train: epoch: 32 batch: 0/4, loss: 0.004165 2023-06-28 01:09:33.975731 Validation: avg loss: 1.5249, avg acc: 57.1429% 2023-06-28 01:09:48.523571 Train: epoch: 33 batch: 0/4, loss: 0.002205 2023-06-28 01:10:34.181073 Validation: avg loss: 1.5044, avg acc: 57.1429% 2023-06-28 01:10:48.667479 Train: epoch: 34 batch: 0/4, loss: 0.003043 2023-06-28 01:11:34.270933 Validation: avg loss: 1.5105, avg acc: 60.0000% 2023-06-28 01:11:48.475934 Train: epoch: 35 batch: 0/4, loss: 0.005146 2023-06-28 01:12:33.493880 Validation: avg loss: 1.4945, avg acc: 59.0476% 2023-06-28 01:12:47.731703 Train: epoch: 36 batch: 0/4, loss: 0.001391 2023-06-28 01:13:34.069553 Validation: avg loss: 1.4949, avg acc: 61.9048% 2023-06-28 01:13:51.020585 Train: epoch: 37 batch: 0/4, loss: 0.002418 2023-06-28 01:14:36.726945 Validation: avg loss: 1.4473, avg acc: 61.9048% 2023-06-28 01:14:50.933113 Train: epoch: 38 batch: 0/4, loss: 0.001485 2023-06-28 01:15:35.503621 Validation: avg loss: 1.4357, avg acc: 62.8571% 2023-06-28 01:15:49.666920 Train: epoch: 39 batch: 0/4, loss: 0.001815 2023-06-28 01:16:34.379353 Validation: avg loss: 1.4482, avg acc: 61.9048% 2023-06-28 01:16:48.543897 Train: epoch: 40 batch: 0/4, loss: 0.004567 2023-06-28 01:17:33.737475 Validation: avg loss: 1.4762, avg acc: 60.9524% 2023-06-28 01:17:47.935196 Train: epoch: 41 batch: 0/4, loss: 0.000961 2023-06-28 01:18:32.496347 Validation: avg loss: 1.4937, avg acc: 60.0000% 2023-06-28 01:18:46.739428 Train: epoch: 42 batch: 0/4, loss: 0.001626 2023-06-28 01:19:31.817522 Validation: avg loss: 1.5100, avg acc: 60.0000% 2023-06-28 01:19:46.275329 Train: epoch: 43 batch: 0/4, loss: 0.000995 2023-06-28 01:20:31.148739 Validation: avg loss: 1.5247, avg acc: 59.0476% 2023-06-28 01:20:45.390128 Train: epoch: 44 batch: 0/4, loss: 0.000796 2023-06-28 01:21:30.408919 Validation: avg loss: 1.5365, avg acc: 60.9524% 2023-06-28 01:21:44.821678 Train: epoch: 45 batch: 0/4, loss: 0.001251 2023-06-28 01:22:29.741533 Validation: avg loss: 1.5421, avg acc: 60.9524% 2023-06-28 01:22:44.346410 Train: epoch: 46 batch: 0/4, loss: 0.000667 2023-06-28 01:23:30.143946 Validation: avg loss: 1.5387, avg acc: 60.9524% 2023-06-28 01:23:44.816721 Train: epoch: 47 batch: 0/4, loss: 0.000684 2023-06-28 01:24:30.374873 Validation: avg loss: 1.5321, avg acc: 61.9048% 2023-06-28 01:24:44.932431 Train: epoch: 48 batch: 0/4, loss: 0.000721 2023-06-28 01:25:30.583908 Validation: avg loss: 1.5259, avg acc: 60.0000% 2023-06-28 01:25:44.973742 Train: epoch: 49 batch: 0/4, loss: 0.001524 2023-06-28 01:26:30.076239 Validation: avg loss: 1.5328, avg acc: 60.9524% 2023-06-28 01:26:44.301327 Train: epoch: 50 batch: 0/4, loss: 0.000452 2023-06-28 01:27:29.465129 Validation: avg loss: 1.5341, avg acc: 60.0000%