2023-06-27 22:05:48.247922 cuda 2023-06-27 22:06:02.700087 Train: epoch: 1 batch: 0/4, loss: 0.694332 2023-06-27 22:06:49.134593 Validation: avg loss: 0.6871, avg acc: 57.1429% 2023-06-27 22:07:03.694375 Train: epoch: 2 batch: 0/4, loss: 0.664086 2023-06-27 22:07:49.773964 Validation: avg loss: 0.6849, avg acc: 57.1429% 2023-06-27 22:08:04.264858 Train: epoch: 3 batch: 0/4, loss: 0.680979 2023-06-27 22:08:49.287316 Validation: avg loss: 0.6857, avg acc: 57.1429% 2023-06-27 22:09:03.568651 Train: epoch: 4 batch: 0/4, loss: 0.660581 2023-06-27 22:09:48.550393 Validation: avg loss: 0.6835, avg acc: 57.1429% 2023-06-27 22:10:02.639012 Train: epoch: 5 batch: 0/4, loss: 0.647255 2023-06-27 22:10:47.197546 Validation: avg loss: 0.6823, avg acc: 57.1429% 2023-06-27 22:11:01.412408 Train: epoch: 6 batch: 0/4, loss: 0.614855 2023-06-27 22:11:46.503837 Validation: avg loss: 0.6813, avg acc: 57.1429% 2023-06-27 22:12:00.867246 Train: epoch: 7 batch: 0/4, loss: 0.581202 2023-06-27 22:12:46.349701 Validation: avg loss: 0.6812, avg acc: 57.1429% 2023-06-27 22:13:00.941791 Train: epoch: 8 batch: 0/4, loss: 0.570684 2023-06-27 22:13:46.248950 Validation: avg loss: 0.6799, avg acc: 60.0000% 2023-06-27 22:14:00.818297 Train: epoch: 9 batch: 0/4, loss: 0.483673 2023-06-27 22:14:46.800237 Validation: avg loss: 0.6701, avg acc: 60.0000% 2023-06-27 22:15:01.432393 Train: epoch: 10 batch: 0/4, loss: 0.420846 2023-06-27 22:15:47.795169 Validation: avg loss: 0.6588, avg acc: 71.4286% 2023-06-27 22:16:02.066573 Train: epoch: 11 batch: 0/4, loss: 0.349698 2023-06-27 22:16:47.069922 Validation: avg loss: 0.6403, avg acc: 67.6190% 2023-06-27 22:17:01.212362 Train: epoch: 12 batch: 0/4, loss: 0.290924 2023-06-27 22:17:46.767356 Validation: avg loss: 0.5999, avg acc: 71.4286% 2023-06-27 22:18:01.308525 Train: epoch: 13 batch: 0/4, loss: 0.210976 2023-06-27 22:18:47.025021 Validation: avg loss: 0.5615, avg acc: 71.4286% 2023-06-27 22:19:01.268115 Train: epoch: 14 batch: 0/4, loss: 0.151887 2023-06-27 22:19:46.249894 Validation: avg loss: 0.5789, avg acc: 70.4762% 2023-06-27 22:20:00.317073 Train: epoch: 15 batch: 0/4, loss: 0.091754 2023-06-27 22:20:44.853358 Validation: avg loss: 0.5884, avg acc: 68.5714% 2023-06-27 22:20:59.252199 Train: epoch: 16 batch: 0/4, loss: 0.064195 2023-06-27 22:21:43.926641 Validation: avg loss: 0.6605, avg acc: 67.6190% 2023-06-27 22:21:58.093871 Train: epoch: 17 batch: 0/4, loss: 0.058442 2023-06-27 22:22:42.867910 Validation: avg loss: 0.7124, avg acc: 68.5714% 2023-06-27 22:22:57.267821 Train: epoch: 18 batch: 0/4, loss: 0.034886 2023-06-27 22:23:42.369799 Validation: avg loss: 0.7680, avg acc: 67.6190% 2023-06-27 22:23:56.549715 Train: epoch: 19 batch: 0/4, loss: 0.021634 2023-06-27 22:24:41.550506 Validation: avg loss: 0.8190, avg acc: 65.7143% 2023-06-27 22:24:55.913941 Train: epoch: 20 batch: 0/4, loss: 0.041213 2023-06-27 22:25:40.883883 Validation: avg loss: 0.8872, avg acc: 70.4762% 2023-06-27 22:25:55.354460 Train: epoch: 21 batch: 0/4, loss: 0.037327 2023-06-27 22:26:39.808208 Validation: avg loss: 0.9775, avg acc: 66.6667% 2023-06-27 22:26:54.000967 Train: epoch: 22 batch: 0/4, loss: 0.007783 2023-06-27 22:27:38.436922 Validation: avg loss: 1.0206, avg acc: 65.7143% 2023-06-27 22:27:52.713763 Train: epoch: 23 batch: 0/4, loss: 0.009117 2023-06-27 22:28:37.844541 Validation: avg loss: 1.0509, avg acc: 64.7619% 2023-06-27 22:28:52.372054 Train: epoch: 24 batch: 0/4, loss: 0.004930 2023-06-27 22:29:38.195225 Validation: avg loss: 1.0375, avg acc: 66.6667% 2023-06-27 22:29:52.833951 Train: epoch: 25 batch: 0/4, loss: 0.006854 2023-06-27 22:30:42.418617 Validation: avg loss: 1.0135, avg acc: 70.4762% 2023-06-27 22:30:59.826240 Train: epoch: 26 batch: 0/4, loss: 0.005497 2023-06-27 22:31:53.313775 Validation: avg loss: 0.9878, avg acc: 69.5238% 2023-06-27 22:32:10.441642 Train: epoch: 27 batch: 0/4, loss: 0.013207 2023-06-27 22:33:03.727428 Validation: avg loss: 0.9929, avg acc: 68.5714% 2023-06-27 22:33:20.489639 Train: epoch: 28 batch: 0/4, loss: 0.007555 2023-06-27 22:34:14.171016 Validation: avg loss: 1.0352, avg acc: 63.8095% 2023-06-27 22:34:31.007619 Train: epoch: 29 batch: 0/4, loss: 0.015213 2023-06-27 22:35:24.970835 Validation: avg loss: 1.0920, avg acc: 67.6190% 2023-06-27 22:35:42.393896 Train: epoch: 30 batch: 0/4, loss: 0.005064 2023-06-27 22:36:37.084491 Validation: avg loss: 1.1553, avg acc: 65.7143% 2023-06-27 22:36:54.262733 Train: epoch: 31 batch: 0/4, loss: 0.004100 2023-06-27 22:37:40.496946 Validation: avg loss: 1.1604, avg acc: 64.7619% 2023-06-27 22:37:54.785895 Train: epoch: 32 batch: 0/4, loss: 0.007035 2023-06-27 22:38:39.997172 Validation: avg loss: 1.1841, avg acc: 64.7619% 2023-06-27 22:38:54.265682 Train: epoch: 33 batch: 0/4, loss: 0.002913 2023-06-27 22:39:39.297686 Validation: avg loss: 1.2217, avg acc: 66.6667% 2023-06-27 22:39:53.662343 Train: epoch: 34 batch: 0/4, loss: 0.003259 2023-06-27 22:40:39.630910 Validation: avg loss: 1.2292, avg acc: 67.6190% 2023-06-27 22:40:53.932959 Train: epoch: 35 batch: 0/4, loss: 0.004313 2023-06-27 22:41:39.521995 Validation: avg loss: 1.2720, avg acc: 66.6667% 2023-06-27 22:41:54.010133 Train: epoch: 36 batch: 0/4, loss: 0.006060 2023-06-27 22:42:38.895880 Validation: avg loss: 1.2800, avg acc: 66.6667% 2023-06-27 22:42:53.040187 Train: epoch: 37 batch: 0/4, loss: 0.003258 2023-06-27 22:43:37.680677 Validation: avg loss: 1.3244, avg acc: 68.5714% 2023-06-27 22:43:51.744750 Train: epoch: 38 batch: 0/4, loss: 0.002319 2023-06-27 22:44:36.460156 Validation: avg loss: 1.3268, avg acc: 66.6667% 2023-06-27 22:44:50.518069 Train: epoch: 39 batch: 0/4, loss: 0.002890 2023-06-27 22:45:35.154920 Validation: avg loss: 1.2941, avg acc: 67.6190% 2023-06-27 22:45:49.264716 Train: epoch: 40 batch: 0/4, loss: 0.002698 2023-06-27 22:46:34.424544 Validation: avg loss: 1.2796, avg acc: 65.7143% 2023-06-27 22:46:48.850944 Train: epoch: 41 batch: 0/4, loss: 0.002646 2023-06-27 22:47:34.845515 Validation: avg loss: 1.2635, avg acc: 64.7619% 2023-06-27 22:47:49.211660 Train: epoch: 42 batch: 0/4, loss: 0.001491 2023-06-27 22:48:34.132406 Validation: avg loss: 1.2806, avg acc: 64.7619% 2023-06-27 22:48:48.271090 Train: epoch: 43 batch: 0/4, loss: 0.002615 2023-06-27 22:49:33.343224 Validation: avg loss: 1.2766, avg acc: 65.7143% 2023-06-27 22:49:47.878757 Train: epoch: 44 batch: 0/4, loss: 0.001109 2023-06-27 22:50:32.900879 Validation: avg loss: 1.2934, avg acc: 64.7619% 2023-06-27 22:50:47.024931 Train: epoch: 45 batch: 0/4, loss: 0.001578 2023-06-27 22:51:32.653596 Validation: avg loss: 1.2984, avg acc: 66.6667% 2023-06-27 22:51:46.814239 Train: epoch: 46 batch: 0/4, loss: 0.000983 2023-06-27 22:52:31.790379 Validation: avg loss: 1.3014, avg acc: 67.6190% 2023-06-27 22:52:45.959176 Train: epoch: 47 batch: 0/4, loss: 0.001445 2023-06-27 22:53:30.927607 Validation: avg loss: 1.2994, avg acc: 66.6667% 2023-06-27 22:53:45.037631 Train: epoch: 48 batch: 0/4, loss: 0.001244 2023-06-27 22:54:29.540818 Validation: avg loss: 1.2992, avg acc: 66.6667% 2023-06-27 22:54:43.669885 Train: epoch: 49 batch: 0/4, loss: 0.000969 2023-06-27 22:55:28.244709 Validation: avg loss: 1.2983, avg acc: 65.7143% 2023-06-27 22:55:42.328411 Train: epoch: 50 batch: 0/4, loss: 0.000754 2023-06-27 22:56:27.191368 Validation: avg loss: 1.3086, avg acc: 65.7143%