2022/09/05 08:06:45 - mmengine - INFO - Checkpoints will be saved to /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb by HardDiskBackend. 2022/09/05 08:09:05 - mmengine - INFO - Epoch(train) [1][20/940] lr: 1.0000e-02 eta: 7 days, 14:52:46 time: 7.0054 data_time: 5.3762 memory: 24014 grad_norm: 2.2992 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 5.9929 loss: 5.9929 2022/09/05 08:09:21 - mmengine - INFO - Epoch(train) [1][40/940] lr: 1.0000e-02 eta: 4 days, 6:05:41 time: 0.8180 data_time: 0.0297 memory: 24014 grad_norm: 2.1359 top1_acc: 0.1250 top5_acc: 0.2812 loss_cls: 5.7185 loss: 5.7185 2022/09/05 08:09:45 - mmengine - INFO - Epoch(train) [1][60/940] lr: 1.0000e-02 eta: 3 days, 6:23:15 time: 1.1886 data_time: 0.0296 memory: 24014 grad_norm: 4.0801 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 4.9605 loss: 4.9605 2022/09/05 08:10:10 - mmengine - INFO - Epoch(train) [1][80/940] lr: 1.0000e-02 eta: 2 days, 18:47:32 time: 1.2287 data_time: 0.0223 memory: 24014 grad_norm: 6.3346 top1_acc: 0.2812 top5_acc: 0.4688 loss_cls: 3.9981 loss: 3.9981 2022/09/05 08:10:38 - mmengine - INFO - Epoch(train) [1][100/940] lr: 1.0000e-02 eta: 2 days, 12:51:02 time: 1.4239 data_time: 0.0383 memory: 24014 grad_norm: 7.0472 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.5045 loss: 3.5045 2022/09/05 08:10:54 - mmengine - INFO - Epoch(train) [1][120/940] lr: 1.0000e-02 eta: 2 days, 6:03:15 time: 0.7722 data_time: 0.0268 memory: 24014 grad_norm: 5.6585 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 3.0106 loss: 3.0106 2022/09/05 08:11:12 - mmengine - INFO - Epoch(train) [1][140/940] lr: 1.0000e-02 eta: 2 days, 1:41:38 time: 0.9052 data_time: 0.0312 memory: 24014 grad_norm: 7.9802 top1_acc: 0.2188 top5_acc: 0.4688 loss_cls: 2.8220 loss: 2.8220 2022/09/05 08:11:30 - mmengine - INFO - Epoch(train) [1][160/940] lr: 1.0000e-02 eta: 1 day, 22:25:18 time: 0.9050 data_time: 0.0334 memory: 24014 grad_norm: 9.1073 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8836 loss: 2.8836 2022/09/05 08:11:53 - mmengine - INFO - Epoch(train) [1][180/940] lr: 1.0000e-02 eta: 1 day, 20:39:18 time: 1.1742 data_time: 0.0259 memory: 24014 grad_norm: 6.0609 top1_acc: 0.2500 top5_acc: 0.7188 loss_cls: 2.8555 loss: 2.8555 2022/09/05 08:12:12 - mmengine - INFO - Epoch(train) [1][200/940] lr: 1.0000e-02 eta: 1 day, 18:37:44 time: 0.9395 data_time: 0.0250 memory: 24014 grad_norm: 5.8488 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.5363 loss: 2.5363 2022/09/05 08:12:33 - mmengine - INFO - Epoch(train) [1][220/940] lr: 1.0000e-02 eta: 1 day, 17:11:54 time: 1.0358 data_time: 0.0266 memory: 24014 grad_norm: 6.3866 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.5216 loss: 2.5216 2022/09/05 08:12:53 - mmengine - INFO - Epoch(train) [1][240/940] lr: 1.0000e-02 eta: 1 day, 15:55:29 time: 0.9988 data_time: 0.0370 memory: 24014 grad_norm: 5.6434 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.4086 loss: 2.4086 2022/09/05 08:13:11 - mmengine - INFO - Epoch(train) [1][260/940] lr: 1.0000e-02 eta: 1 day, 14:39:09 time: 0.9021 data_time: 0.0273 memory: 24014 grad_norm: 5.8102 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.2473 loss: 2.2473 2022/09/05 08:13:32 - mmengine - INFO - Epoch(train) [1][280/940] lr: 1.0000e-02 eta: 1 day, 13:48:07 time: 1.0314 data_time: 0.0294 memory: 24014 grad_norm: 5.2624 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 2.5803 loss: 2.5803 2022/09/05 08:13:52 - mmengine - INFO - Epoch(train) [1][300/940] lr: 1.0000e-02 eta: 1 day, 13:00:56 time: 1.0035 data_time: 0.0305 memory: 24014 grad_norm: 5.3212 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.2237 loss: 2.2237 2022/09/05 08:14:11 - mmengine - INFO - Epoch(train) [1][320/940] lr: 1.0000e-02 eta: 1 day, 12:14:29 time: 0.9510 data_time: 0.0472 memory: 24014 grad_norm: 5.6822 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.1772 loss: 2.1772 2022/09/05 08:14:31 - mmengine - INFO - Epoch(train) [1][340/940] lr: 1.0000e-02 eta: 1 day, 11:37:27 time: 0.9945 data_time: 0.0557 memory: 24014 grad_norm: 5.2367 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2352 loss: 2.2352 2022/09/05 08:14:48 - mmengine - INFO - Epoch(train) [1][360/940] lr: 1.0000e-02 eta: 1 day, 10:53:55 time: 0.8726 data_time: 0.0993 memory: 24014 grad_norm: 5.5098 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.2252 loss: 2.2252 2022/09/05 08:15:04 - mmengine - INFO - Epoch(train) [1][380/940] lr: 1.0000e-02 eta: 1 day, 10:07:43 time: 0.7844 data_time: 0.1847 memory: 24014 grad_norm: 5.7537 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2707 loss: 2.2707 2022/09/05 08:15:26 - mmengine - INFO - Epoch(train) [1][400/940] lr: 1.0000e-02 eta: 1 day, 9:51:29 time: 1.1098 data_time: 0.0284 memory: 24014 grad_norm: 7.6316 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3292 loss: 2.3292 2022/09/05 08:15:42 - mmengine - INFO - Epoch(train) [1][420/940] lr: 1.0000e-02 eta: 1 day, 9:12:33 time: 0.7840 data_time: 0.0336 memory: 24014 grad_norm: 5.4250 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.2365 loss: 2.2365 2022/09/05 08:15:58 - mmengine - INFO - Epoch(train) [1][440/940] lr: 1.0000e-02 eta: 1 day, 8:40:07 time: 0.8259 data_time: 0.0297 memory: 24014 grad_norm: 6.5697 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.2558 loss: 2.2558 2022/09/05 08:16:20 - mmengine - INFO - Epoch(train) [1][460/940] lr: 1.0000e-02 eta: 1 day, 8:29:21 time: 1.1045 data_time: 0.0270 memory: 24014 grad_norm: 6.6396 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.4006 loss: 2.4006 2022/09/05 08:16:36 - mmengine - INFO - Epoch(train) [1][480/940] lr: 1.0000e-02 eta: 1 day, 7:59:57 time: 0.8041 data_time: 0.0247 memory: 24014 grad_norm: 5.2222 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.2005 loss: 2.2005 2022/09/05 08:16:55 - mmengine - INFO - Epoch(train) [1][500/940] lr: 1.0000e-02 eta: 1 day, 7:40:56 time: 0.9334 data_time: 0.0278 memory: 24014 grad_norm: 6.6525 top1_acc: 0.2812 top5_acc: 0.5938 loss_cls: 2.1412 loss: 2.1412 2022/09/05 08:17:16 - mmengine - INFO - Epoch(train) [1][520/940] lr: 1.0000e-02 eta: 1 day, 7:29:31 time: 1.0362 data_time: 0.0318 memory: 24014 grad_norm: 5.5695 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.1891 loss: 2.1891 2022/09/05 08:17:32 - mmengine - INFO - Epoch(train) [1][540/940] lr: 1.0000e-02 eta: 1 day, 7:05:49 time: 0.8088 data_time: 0.0322 memory: 24014 grad_norm: 5.4957 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.1126 loss: 2.1126 2022/09/05 08:17:49 - mmengine - INFO - Epoch(train) [1][560/940] lr: 1.0000e-02 eta: 1 day, 6:47:36 time: 0.8775 data_time: 0.0274 memory: 24014 grad_norm: 5.0415 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.2334 loss: 2.2334 2022/09/05 08:18:08 - mmengine - INFO - Epoch(train) [1][580/940] lr: 1.0000e-02 eta: 1 day, 6:34:27 time: 0.9488 data_time: 0.0295 memory: 24014 grad_norm: 4.9469 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.9758 loss: 1.9758 2022/09/05 08:18:26 - mmengine - INFO - Epoch(train) [1][600/940] lr: 1.0000e-02 eta: 1 day, 6:18:07 time: 0.8710 data_time: 0.0322 memory: 24014 grad_norm: 4.8094 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.1503 loss: 2.1503 2022/09/05 08:18:44 - mmengine - INFO - Epoch(train) [1][620/940] lr: 1.0000e-02 eta: 1 day, 6:05:11 time: 0.9183 data_time: 0.0323 memory: 24014 grad_norm: 4.7884 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.1542 loss: 2.1542 2022/09/05 08:19:00 - mmengine - INFO - Epoch(train) [1][640/940] lr: 1.0000e-02 eta: 1 day, 5:47:18 time: 0.8000 data_time: 0.0364 memory: 24014 grad_norm: 5.0700 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0339 loss: 2.0339 2022/09/05 08:19:19 - mmengine - INFO - Epoch(train) [1][660/940] lr: 1.0000e-02 eta: 1 day, 5:38:05 time: 0.9612 data_time: 0.0479 memory: 24014 grad_norm: 4.9053 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.1724 loss: 2.1724 2022/09/05 08:19:37 - mmengine - INFO - Epoch(train) [1][680/940] lr: 1.0000e-02 eta: 1 day, 5:24:49 time: 0.8614 data_time: 0.0317 memory: 24014 grad_norm: 4.7300 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9030 loss: 1.9030 2022/09/05 08:19:59 - mmengine - INFO - Epoch(train) [1][700/940] lr: 1.0000e-02 eta: 1 day, 5:23:14 time: 1.1075 data_time: 0.0900 memory: 24014 grad_norm: 4.8120 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1224 loss: 2.1224 2022/09/05 08:20:14 - mmengine - INFO - Epoch(train) [1][720/940] lr: 1.0000e-02 eta: 1 day, 5:06:11 time: 0.7480 data_time: 0.0313 memory: 24014 grad_norm: 5.1200 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 2.0168 loss: 2.0168 2022/09/05 08:20:35 - mmengine - INFO - Epoch(train) [1][740/940] lr: 1.0000e-02 eta: 1 day, 5:03:44 time: 1.0738 data_time: 0.0287 memory: 24014 grad_norm: 4.8417 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0327 loss: 2.0327 2022/09/05 08:20:58 - mmengine - INFO - Epoch(train) [1][760/940] lr: 1.0000e-02 eta: 1 day, 5:04:36 time: 1.1521 data_time: 0.0281 memory: 24014 grad_norm: 4.6897 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 1.9284 loss: 1.9284 2022/09/05 08:21:16 - mmengine - INFO - Epoch(train) [1][780/940] lr: 1.0000e-02 eta: 1 day, 4:54:51 time: 0.8871 data_time: 0.0302 memory: 24014 grad_norm: 4.7241 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.9424 loss: 1.9424 2022/09/05 08:21:32 - mmengine - INFO - Epoch(train) [1][800/940] lr: 1.0000e-02 eta: 1 day, 4:41:46 time: 0.7894 data_time: 0.0270 memory: 24014 grad_norm: 5.2929 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0148 loss: 2.0148 2022/09/05 08:21:51 - mmengine - INFO - Epoch(train) [1][820/940] lr: 1.0000e-02 eta: 1 day, 4:35:06 time: 0.9422 data_time: 0.0626 memory: 24014 grad_norm: 4.8244 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 2.2326 loss: 2.2326 2022/09/05 08:22:09 - mmengine - INFO - Epoch(train) [1][840/940] lr: 1.0000e-02 eta: 1 day, 4:27:39 time: 0.9129 data_time: 0.0232 memory: 24014 grad_norm: 5.0464 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9062 loss: 1.9062 2022/09/05 08:22:26 - mmengine - INFO - Epoch(train) [1][860/940] lr: 1.0000e-02 eta: 1 day, 4:18:27 time: 0.8551 data_time: 0.0308 memory: 24014 grad_norm: 5.3126 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.0004 loss: 2.0004 2022/09/05 08:22:47 - mmengine - INFO - Epoch(train) [1][880/940] lr: 1.0000e-02 eta: 1 day, 4:17:24 time: 1.0746 data_time: 0.0261 memory: 24014 grad_norm: 4.7153 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8973 loss: 1.8973 2022/09/05 08:23:03 - mmengine - INFO - Epoch(train) [1][900/940] lr: 1.0000e-02 eta: 1 day, 4:06:29 time: 0.7880 data_time: 0.0298 memory: 24014 grad_norm: 4.9845 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9025 loss: 1.9025 2022/09/05 08:23:22 - mmengine - INFO - Epoch(train) [1][920/940] lr: 1.0000e-02 eta: 1 day, 4:01:23 time: 0.9463 data_time: 0.0806 memory: 24014 grad_norm: 4.6171 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8869 loss: 1.8869 2022/09/05 08:23:38 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 08:23:38 - mmengine - INFO - Epoch(train) [1][940/940] lr: 1.0000e-02 eta: 1 day, 3:52:10 time: 0.8153 data_time: 0.1754 memory: 24014 grad_norm: 5.1640 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8304 loss: 1.8304 2022/09/05 08:25:18 - mmengine - INFO - Epoch(val) [1][20/78] eta: 0:04:49 time: 4.9963 data_time: 4.8523 memory: 3624 2022/09/05 08:25:32 - mmengine - INFO - Epoch(val) [1][40/78] eta: 0:00:25 time: 0.6588 data_time: 0.5074 memory: 3624 2022/09/05 08:25:50 - mmengine - INFO - Epoch(val) [1][60/78] eta: 0:00:16 time: 0.9355 data_time: 0.7906 memory: 3624 2022/09/05 08:26:11 - mmengine - INFO - Epoch(val) [1][78/78] acc/top1: 0.6226 acc/top5: 0.8532 acc/mean1: 0.6223 2022/09/05 08:26:15 - mmengine - INFO - The best checkpoint with 0.6226 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/09/05 08:26:32 - mmengine - INFO - Epoch(train) [2][20/940] lr: 1.0000e-02 eta: 1 day, 3:45:16 time: 0.8756 data_time: 0.3301 memory: 24011 grad_norm: 4.7362 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.9573 loss: 1.9573 2022/09/05 08:26:45 - mmengine - INFO - Epoch(train) [2][40/940] lr: 1.0000e-02 eta: 1 day, 3:30:23 time: 0.6148 data_time: 0.0688 memory: 24011 grad_norm: 4.5627 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8536 loss: 1.8536 2022/09/05 08:26:58 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 08:26:58 - mmengine - INFO - Epoch(train) [2][60/940] lr: 1.0000e-02 eta: 1 day, 3:17:25 time: 0.6580 data_time: 0.0972 memory: 24011 grad_norm: 4.7147 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8438 loss: 1.8438 2022/09/05 08:27:10 - mmengine - INFO - Epoch(train) [2][80/940] lr: 1.0000e-02 eta: 1 day, 3:04:11 time: 0.6321 data_time: 0.0712 memory: 24011 grad_norm: 5.6783 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0312 loss: 2.0312 2022/09/05 08:27:23 - mmengine - INFO - Epoch(train) [2][100/940] lr: 1.0000e-02 eta: 1 day, 2:51:56 time: 0.6489 data_time: 0.0926 memory: 24011 grad_norm: 4.6414 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8870 loss: 1.8870 2022/09/05 08:27:37 - mmengine - INFO - Epoch(train) [2][120/940] lr: 1.0000e-02 eta: 1 day, 2:40:40 time: 0.6666 data_time: 0.0851 memory: 24011 grad_norm: 4.6666 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7457 loss: 1.7457 2022/09/05 08:27:50 - mmengine - INFO - Epoch(train) [2][140/940] lr: 1.0000e-02 eta: 1 day, 2:29:45 time: 0.6651 data_time: 0.0787 memory: 24011 grad_norm: 4.5560 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.8606 loss: 1.8606 2022/09/05 08:28:02 - mmengine - INFO - Epoch(train) [2][160/940] lr: 1.0000e-02 eta: 1 day, 2:17:08 time: 0.5906 data_time: 0.0305 memory: 24011 grad_norm: 4.2745 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8183 loss: 1.8183 2022/09/05 08:28:15 - mmengine - INFO - Epoch(train) [2][180/940] lr: 1.0000e-02 eta: 1 day, 2:06:33 time: 0.6480 data_time: 0.0989 memory: 24011 grad_norm: 4.8761 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0843 loss: 2.0843 2022/09/05 08:28:27 - mmengine - INFO - Epoch(train) [2][200/940] lr: 1.0000e-02 eta: 1 day, 1:55:43 time: 0.6251 data_time: 0.0718 memory: 24011 grad_norm: 4.2509 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9208 loss: 1.9208 2022/09/05 08:28:40 - mmengine - INFO - Epoch(train) [2][220/940] lr: 1.0000e-02 eta: 1 day, 1:45:52 time: 0.6489 data_time: 0.0770 memory: 24011 grad_norm: 4.6156 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7859 loss: 1.7859 2022/09/05 08:28:54 - mmengine - INFO - Epoch(train) [2][240/940] lr: 1.0000e-02 eta: 1 day, 1:37:12 time: 0.6811 data_time: 0.1172 memory: 24011 grad_norm: 4.6065 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7352 loss: 1.7352 2022/09/05 08:29:08 - mmengine - INFO - Epoch(train) [2][260/940] lr: 1.0000e-02 eta: 1 day, 1:29:21 time: 0.7016 data_time: 0.1247 memory: 24011 grad_norm: 4.8468 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7767 loss: 1.7767 2022/09/05 08:29:20 - mmengine - INFO - Epoch(train) [2][280/940] lr: 1.0000e-02 eta: 1 day, 1:19:17 time: 0.6051 data_time: 0.0542 memory: 24011 grad_norm: 4.4950 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7651 loss: 1.7651 2022/09/05 08:29:32 - mmengine - INFO - Epoch(train) [2][300/940] lr: 1.0000e-02 eta: 1 day, 1:09:43 time: 0.6121 data_time: 0.0611 memory: 24011 grad_norm: 4.3253 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8967 loss: 1.8967 2022/09/05 08:29:45 - mmengine - INFO - Epoch(train) [2][320/940] lr: 1.0000e-02 eta: 1 day, 1:01:35 time: 0.6577 data_time: 0.1022 memory: 24011 grad_norm: 4.3463 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8690 loss: 1.8690 2022/09/05 08:29:58 - mmengine - INFO - Epoch(train) [2][340/940] lr: 1.0000e-02 eta: 1 day, 0:52:49 time: 0.6222 data_time: 0.0528 memory: 24011 grad_norm: 4.8272 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.6988 loss: 1.6988 2022/09/05 08:30:11 - mmengine - INFO - Epoch(train) [2][360/940] lr: 1.0000e-02 eta: 1 day, 0:45:40 time: 0.6787 data_time: 0.0419 memory: 24011 grad_norm: 4.7564 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8420 loss: 1.8420 2022/09/05 08:30:25 - mmengine - INFO - Epoch(train) [2][380/940] lr: 1.0000e-02 eta: 1 day, 0:38:12 time: 0.6562 data_time: 0.0422 memory: 24011 grad_norm: 4.8564 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8018 loss: 1.8018 2022/09/05 08:30:37 - mmengine - INFO - Epoch(train) [2][400/940] lr: 1.0000e-02 eta: 1 day, 0:30:42 time: 0.6455 data_time: 0.0834 memory: 24011 grad_norm: 4.4899 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7858 loss: 1.7858 2022/09/05 08:30:50 - mmengine - INFO - Epoch(train) [2][420/940] lr: 1.0000e-02 eta: 1 day, 0:23:23 time: 0.6440 data_time: 0.0848 memory: 24011 grad_norm: 4.6534 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7862 loss: 1.7862 2022/09/05 08:31:03 - mmengine - INFO - Epoch(train) [2][440/940] lr: 1.0000e-02 eta: 1 day, 0:16:04 time: 0.6353 data_time: 0.0649 memory: 24011 grad_norm: 4.4096 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7988 loss: 1.7988 2022/09/05 08:31:16 - mmengine - INFO - Epoch(train) [2][460/940] lr: 1.0000e-02 eta: 1 day, 0:09:47 time: 0.6725 data_time: 0.1155 memory: 24011 grad_norm: 4.8915 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8810 loss: 1.8810 2022/09/05 08:31:30 - mmengine - INFO - Epoch(train) [2][480/940] lr: 1.0000e-02 eta: 1 day, 0:03:33 time: 0.6666 data_time: 0.1090 memory: 24011 grad_norm: 4.7479 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8145 loss: 1.8145 2022/09/05 08:31:42 - mmengine - INFO - Epoch(train) [2][500/940] lr: 1.0000e-02 eta: 23:56:46 time: 0.6339 data_time: 0.0760 memory: 24011 grad_norm: 4.8082 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7759 loss: 1.7759 2022/09/05 08:31:55 - mmengine - INFO - Epoch(train) [2][520/940] lr: 1.0000e-02 eta: 23:49:47 time: 0.6156 data_time: 0.0549 memory: 24011 grad_norm: 4.4754 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8009 loss: 1.8009 2022/09/05 08:32:07 - mmengine - INFO - Epoch(train) [2][540/940] lr: 1.0000e-02 eta: 23:42:50 time: 0.6084 data_time: 0.0551 memory: 24011 grad_norm: 4.3015 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6418 loss: 1.6418 2022/09/05 08:32:20 - mmengine - INFO - Epoch(train) [2][560/940] lr: 1.0000e-02 eta: 23:36:44 time: 0.6407 data_time: 0.0622 memory: 24011 grad_norm: 4.5446 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8589 loss: 1.8589 2022/09/05 08:32:32 - mmengine - INFO - Epoch(train) [2][580/940] lr: 1.0000e-02 eta: 23:30:32 time: 0.6286 data_time: 0.0501 memory: 24011 grad_norm: 5.3564 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7736 loss: 1.7736 2022/09/05 08:32:45 - mmengine - INFO - Epoch(train) [2][600/940] lr: 1.0000e-02 eta: 23:24:55 time: 0.6490 data_time: 0.0855 memory: 24011 grad_norm: 4.6627 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.7453 loss: 1.7453 2022/09/05 08:32:58 - mmengine - INFO - Epoch(train) [2][620/940] lr: 1.0000e-02 eta: 23:19:25 time: 0.6490 data_time: 0.0702 memory: 24011 grad_norm: 4.7194 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7758 loss: 1.7758 2022/09/05 08:33:11 - mmengine - INFO - Epoch(train) [2][640/940] lr: 1.0000e-02 eta: 23:13:31 time: 0.6214 data_time: 0.0467 memory: 24011 grad_norm: 4.7299 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6954 loss: 1.6954 2022/09/05 08:33:24 - mmengine - INFO - Epoch(train) [2][660/940] lr: 1.0000e-02 eta: 23:08:49 time: 0.6764 data_time: 0.0871 memory: 24011 grad_norm: 5.3046 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7582 loss: 1.7582 2022/09/05 08:33:37 - mmengine - INFO - Epoch(train) [2][680/940] lr: 1.0000e-02 eta: 23:03:45 time: 0.6510 data_time: 0.0407 memory: 24011 grad_norm: 4.5315 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8157 loss: 1.8157 2022/09/05 08:33:51 - mmengine - INFO - Epoch(train) [2][700/940] lr: 1.0000e-02 eta: 22:59:00 time: 0.6612 data_time: 0.0420 memory: 24011 grad_norm: 4.5411 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8859 loss: 1.8859 2022/09/05 08:34:03 - mmengine - INFO - Epoch(train) [2][720/940] lr: 1.0000e-02 eta: 22:53:56 time: 0.6386 data_time: 0.0322 memory: 24011 grad_norm: 6.3504 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8886 loss: 1.8886 2022/09/05 08:34:17 - mmengine - INFO - Epoch(train) [2][740/940] lr: 1.0000e-02 eta: 22:49:44 time: 0.6802 data_time: 0.0981 memory: 24011 grad_norm: 4.7527 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8492 loss: 1.8492 2022/09/05 08:34:30 - mmengine - INFO - Epoch(train) [2][760/940] lr: 1.0000e-02 eta: 22:44:37 time: 0.6237 data_time: 0.0550 memory: 24011 grad_norm: 4.9779 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8553 loss: 1.8553 2022/09/05 08:34:43 - mmengine - INFO - Epoch(train) [2][780/940] lr: 1.0000e-02 eta: 22:40:16 time: 0.6607 data_time: 0.0820 memory: 24011 grad_norm: 4.4360 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8578 loss: 1.8578 2022/09/05 08:34:55 - mmengine - INFO - Epoch(train) [2][800/940] lr: 1.0000e-02 eta: 22:35:16 time: 0.6177 data_time: 0.0526 memory: 24011 grad_norm: 4.5074 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7392 loss: 1.7392 2022/09/05 08:35:08 - mmengine - INFO - Epoch(train) [2][820/940] lr: 1.0000e-02 eta: 22:30:41 time: 0.6360 data_time: 0.0404 memory: 24011 grad_norm: 4.4417 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7193 loss: 1.7193 2022/09/05 08:35:20 - mmengine - INFO - Epoch(train) [2][840/940] lr: 1.0000e-02 eta: 22:26:19 time: 0.6430 data_time: 0.0468 memory: 24011 grad_norm: 4.4138 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7699 loss: 1.7699 2022/09/05 08:35:34 - mmengine - INFO - Epoch(train) [2][860/940] lr: 1.0000e-02 eta: 22:22:47 time: 0.6859 data_time: 0.0454 memory: 24011 grad_norm: 4.6940 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7479 loss: 1.7479 2022/09/05 08:35:47 - mmengine - INFO - Epoch(train) [2][880/940] lr: 1.0000e-02 eta: 22:18:56 time: 0.6625 data_time: 0.0334 memory: 24011 grad_norm: 4.2959 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9049 loss: 1.9049 2022/09/05 08:36:00 - mmengine - INFO - Epoch(train) [2][900/940] lr: 1.0000e-02 eta: 22:14:16 time: 0.6098 data_time: 0.0360 memory: 24011 grad_norm: 4.3561 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.7075 loss: 1.7075 2022/09/05 08:36:14 - mmengine - INFO - Epoch(train) [2][920/940] lr: 1.0000e-02 eta: 22:11:05 time: 0.6936 data_time: 0.0563 memory: 24011 grad_norm: 4.4595 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.7332 loss: 1.7332 2022/09/05 08:36:24 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 08:36:24 - mmengine - INFO - Epoch(train) [2][940/940] lr: 1.0000e-02 eta: 22:05:25 time: 0.5376 data_time: 0.0281 memory: 24011 grad_norm: 4.2992 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.9087 loss: 1.9087 2022/09/05 08:36:38 - mmengine - INFO - Epoch(val) [2][20/78] eta: 0:00:40 time: 0.6961 data_time: 0.5380 memory: 3625 2022/09/05 08:36:48 - mmengine - INFO - Epoch(val) [2][40/78] eta: 0:00:18 time: 0.4789 data_time: 0.3135 memory: 3625 2022/09/05 08:37:01 - mmengine - INFO - Epoch(val) [2][60/78] eta: 0:00:11 time: 0.6407 data_time: 0.4851 memory: 3625 2022/09/05 08:37:11 - mmengine - INFO - Epoch(val) [2][78/78] acc/top1: 0.6625 acc/top5: 0.8762 acc/mean1: 0.6624 2022/09/05 08:37:11 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_2.pth is removed 2022/09/05 08:37:14 - mmengine - INFO - The best checkpoint with 0.6625 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/09/05 08:37:31 - mmengine - INFO - Epoch(train) [3][20/940] lr: 1.0000e-02 eta: 22:04:47 time: 0.8417 data_time: 0.2993 memory: 24011 grad_norm: 4.2593 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6491 loss: 1.6491 2022/09/05 08:37:44 - mmengine - INFO - Epoch(train) [3][40/940] lr: 1.0000e-02 eta: 22:00:50 time: 0.6340 data_time: 0.0974 memory: 24011 grad_norm: 4.1322 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6229 loss: 1.6229 2022/09/05 08:37:58 - mmengine - INFO - Epoch(train) [3][60/940] lr: 1.0000e-02 eta: 21:58:05 time: 0.7052 data_time: 0.1655 memory: 24011 grad_norm: 4.2837 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7081 loss: 1.7081 2022/09/05 08:38:10 - mmengine - INFO - Epoch(train) [3][80/940] lr: 1.0000e-02 eta: 21:54:00 time: 0.6160 data_time: 0.0440 memory: 24011 grad_norm: 4.5488 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7124 loss: 1.7124 2022/09/05 08:38:23 - mmengine - INFO - Epoch(train) [3][100/940] lr: 1.0000e-02 eta: 21:50:51 time: 0.6721 data_time: 0.1151 memory: 24011 grad_norm: 4.1407 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.5091 loss: 1.5091 2022/09/05 08:38:36 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 08:38:36 - mmengine - INFO - Epoch(train) [3][120/940] lr: 1.0000e-02 eta: 21:47:18 time: 0.6421 data_time: 0.0800 memory: 24011 grad_norm: 4.1550 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.6695 loss: 1.6695 2022/09/05 08:38:49 - mmengine - INFO - Epoch(train) [3][140/940] lr: 1.0000e-02 eta: 21:44:02 time: 0.6553 data_time: 0.0971 memory: 24011 grad_norm: 4.3251 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6243 loss: 1.6243 2022/09/05 08:39:02 - mmengine - INFO - Epoch(train) [3][160/940] lr: 1.0000e-02 eta: 21:40:46 time: 0.6523 data_time: 0.0953 memory: 24011 grad_norm: 4.6521 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6962 loss: 1.6962 2022/09/05 08:39:16 - mmengine - INFO - Epoch(train) [3][180/940] lr: 1.0000e-02 eta: 21:37:48 time: 0.6685 data_time: 0.0937 memory: 24011 grad_norm: 4.7909 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6800 loss: 1.6800 2022/09/05 08:39:28 - mmengine - INFO - Epoch(train) [3][200/940] lr: 1.0000e-02 eta: 21:34:15 time: 0.6246 data_time: 0.0656 memory: 24011 grad_norm: 4.4333 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7190 loss: 1.7190 2022/09/05 08:39:41 - mmengine - INFO - Epoch(train) [3][220/940] lr: 1.0000e-02 eta: 21:30:43 time: 0.6220 data_time: 0.0626 memory: 24011 grad_norm: 4.5356 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7615 loss: 1.7615 2022/09/05 08:39:54 - mmengine - INFO - Epoch(train) [3][240/940] lr: 1.0000e-02 eta: 21:27:47 time: 0.6599 data_time: 0.0957 memory: 24011 grad_norm: 4.4993 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5114 loss: 1.5114 2022/09/05 08:40:07 - mmengine - INFO - Epoch(train) [3][260/940] lr: 1.0000e-02 eta: 21:24:49 time: 0.6534 data_time: 0.0967 memory: 24011 grad_norm: 4.9379 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6562 loss: 1.6562 2022/09/05 08:40:20 - mmengine - INFO - Epoch(train) [3][280/940] lr: 1.0000e-02 eta: 21:21:46 time: 0.6434 data_time: 0.0563 memory: 24011 grad_norm: 4.2432 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5967 loss: 1.5967 2022/09/05 08:40:32 - mmengine - INFO - Epoch(train) [3][300/940] lr: 1.0000e-02 eta: 21:18:22 time: 0.6152 data_time: 0.0326 memory: 24011 grad_norm: 4.3290 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6114 loss: 1.6114 2022/09/05 08:40:45 - mmengine - INFO - Epoch(train) [3][320/940] lr: 1.0000e-02 eta: 21:15:08 time: 0.6225 data_time: 0.0353 memory: 24011 grad_norm: 4.5546 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.6759 loss: 1.6759 2022/09/05 08:40:58 - mmengine - INFO - Epoch(train) [3][340/940] lr: 1.0000e-02 eta: 21:12:48 time: 0.6847 data_time: 0.1280 memory: 24011 grad_norm: 4.9009 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7504 loss: 1.7504 2022/09/05 08:41:11 - mmengine - INFO - Epoch(train) [3][360/940] lr: 1.0000e-02 eta: 21:09:59 time: 0.6453 data_time: 0.0859 memory: 24011 grad_norm: 4.6284 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7503 loss: 1.7503 2022/09/05 08:41:24 - mmengine - INFO - Epoch(train) [3][380/940] lr: 1.0000e-02 eta: 21:07:21 time: 0.6569 data_time: 0.0936 memory: 24011 grad_norm: 4.5830 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7085 loss: 1.7085 2022/09/05 08:41:37 - mmengine - INFO - Epoch(train) [3][400/940] lr: 1.0000e-02 eta: 21:04:17 time: 0.6211 data_time: 0.0472 memory: 24011 grad_norm: 4.5898 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7517 loss: 1.7517 2022/09/05 08:41:50 - mmengine - INFO - Epoch(train) [3][420/940] lr: 1.0000e-02 eta: 21:01:42 time: 0.6525 data_time: 0.0860 memory: 24011 grad_norm: 4.4860 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8126 loss: 1.8126 2022/09/05 08:42:02 - mmengine - INFO - Epoch(train) [3][440/940] lr: 1.0000e-02 eta: 20:58:50 time: 0.6290 data_time: 0.0625 memory: 24011 grad_norm: 4.5852 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6982 loss: 1.6982 2022/09/05 08:42:16 - mmengine - INFO - Epoch(train) [3][460/940] lr: 1.0000e-02 eta: 20:56:46 time: 0.6864 data_time: 0.1148 memory: 24011 grad_norm: 4.2722 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6544 loss: 1.6544 2022/09/05 08:42:28 - mmengine - INFO - Epoch(train) [3][480/940] lr: 1.0000e-02 eta: 20:53:40 time: 0.6042 data_time: 0.0332 memory: 24011 grad_norm: 4.3393 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6577 loss: 1.6577 2022/09/05 08:42:41 - mmengine - INFO - Epoch(train) [3][500/940] lr: 1.0000e-02 eta: 20:51:11 time: 0.6488 data_time: 0.0721 memory: 24011 grad_norm: 4.3131 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.6401 loss: 1.6401 2022/09/05 08:42:54 - mmengine - INFO - Epoch(train) [3][520/940] lr: 1.0000e-02 eta: 20:48:35 time: 0.6363 data_time: 0.0423 memory: 24011 grad_norm: 4.2063 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6606 loss: 1.6606 2022/09/05 08:43:07 - mmengine - INFO - Epoch(train) [3][540/940] lr: 1.0000e-02 eta: 20:46:09 time: 0.6474 data_time: 0.0716 memory: 24011 grad_norm: 4.3272 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6214 loss: 1.6214 2022/09/05 08:43:20 - mmengine - INFO - Epoch(train) [3][560/940] lr: 1.0000e-02 eta: 20:43:57 time: 0.6622 data_time: 0.0317 memory: 24011 grad_norm: 4.2260 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6025 loss: 1.6025 2022/09/05 08:43:33 - mmengine - INFO - Epoch(train) [3][580/940] lr: 1.0000e-02 eta: 20:41:39 time: 0.6516 data_time: 0.0573 memory: 24011 grad_norm: 4.2396 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6916 loss: 1.6916 2022/09/05 08:43:46 - mmengine - INFO - Epoch(train) [3][600/940] lr: 1.0000e-02 eta: 20:39:07 time: 0.6300 data_time: 0.0360 memory: 24011 grad_norm: 4.7405 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4727 loss: 1.4727 2022/09/05 08:43:59 - mmengine - INFO - Epoch(train) [3][620/940] lr: 1.0000e-02 eta: 20:36:48 time: 0.6443 data_time: 0.0346 memory: 24011 grad_norm: 4.3403 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5874 loss: 1.5874 2022/09/05 08:44:13 - mmengine - INFO - Epoch(train) [3][640/940] lr: 1.0000e-02 eta: 20:35:17 time: 0.7077 data_time: 0.0353 memory: 24011 grad_norm: 4.0757 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7103 loss: 1.7103 2022/09/05 08:44:25 - mmengine - INFO - Epoch(train) [3][660/940] lr: 1.0000e-02 eta: 20:32:43 time: 0.6189 data_time: 0.0392 memory: 24011 grad_norm: 4.3786 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6254 loss: 1.6254 2022/09/05 08:44:38 - mmengine - INFO - Epoch(train) [3][680/940] lr: 1.0000e-02 eta: 20:30:38 time: 0.6569 data_time: 0.0364 memory: 24011 grad_norm: 4.4129 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7347 loss: 1.7347 2022/09/05 08:44:52 - mmengine - INFO - Epoch(train) [3][700/940] lr: 1.0000e-02 eta: 20:28:44 time: 0.6687 data_time: 0.0359 memory: 24011 grad_norm: 4.2386 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6181 loss: 1.6181 2022/09/05 08:45:05 - mmengine - INFO - Epoch(train) [3][720/940] lr: 1.0000e-02 eta: 20:26:36 time: 0.6477 data_time: 0.0366 memory: 24011 grad_norm: 4.1833 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5277 loss: 1.5277 2022/09/05 08:45:17 - mmengine - INFO - Epoch(train) [3][740/940] lr: 1.0000e-02 eta: 20:24:24 time: 0.6396 data_time: 0.0518 memory: 24011 grad_norm: 4.0932 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.5701 loss: 1.5701 2022/09/05 08:45:31 - mmengine - INFO - Epoch(train) [3][760/940] lr: 1.0000e-02 eta: 20:22:27 time: 0.6581 data_time: 0.0389 memory: 24011 grad_norm: 4.2979 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6228 loss: 1.6228 2022/09/05 08:45:44 - mmengine - INFO - Epoch(train) [3][780/940] lr: 1.0000e-02 eta: 20:20:28 time: 0.6523 data_time: 0.0407 memory: 24011 grad_norm: 4.2281 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.6176 loss: 1.6176 2022/09/05 08:45:56 - mmengine - INFO - Epoch(train) [3][800/940] lr: 1.0000e-02 eta: 20:18:22 time: 0.6409 data_time: 0.0368 memory: 24011 grad_norm: 4.2671 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7370 loss: 1.7370 2022/09/05 08:46:10 - mmengine - INFO - Epoch(train) [3][820/940] lr: 1.0000e-02 eta: 20:16:33 time: 0.6625 data_time: 0.0404 memory: 24011 grad_norm: 4.2041 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6300 loss: 1.6300 2022/09/05 08:46:23 - mmengine - INFO - Epoch(train) [3][840/940] lr: 1.0000e-02 eta: 20:14:30 time: 0.6408 data_time: 0.0324 memory: 24011 grad_norm: 4.0230 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6889 loss: 1.6889 2022/09/05 08:46:36 - mmengine - INFO - Epoch(train) [3][860/940] lr: 1.0000e-02 eta: 20:12:50 time: 0.6714 data_time: 0.0385 memory: 24011 grad_norm: 4.1066 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5902 loss: 1.5902 2022/09/05 08:46:48 - mmengine - INFO - Epoch(train) [3][880/940] lr: 1.0000e-02 eta: 20:10:33 time: 0.6142 data_time: 0.0451 memory: 24011 grad_norm: 4.1939 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4783 loss: 1.4783 2022/09/05 08:47:02 - mmengine - INFO - Epoch(train) [3][900/940] lr: 1.0000e-02 eta: 20:08:58 time: 0.6767 data_time: 0.0393 memory: 24011 grad_norm: 4.9096 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6206 loss: 1.6206 2022/09/05 08:47:15 - mmengine - INFO - Epoch(train) [3][920/940] lr: 1.0000e-02 eta: 20:07:00 time: 0.6376 data_time: 0.0387 memory: 24011 grad_norm: 4.2644 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5428 loss: 1.5428 2022/09/05 08:47:25 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 08:47:25 - mmengine - INFO - Epoch(train) [3][940/940] lr: 1.0000e-02 eta: 20:03:57 time: 0.5358 data_time: 0.0282 memory: 24011 grad_norm: 4.2810 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.5333 loss: 1.5333 2022/09/05 08:47:25 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/09/05 08:47:45 - mmengine - INFO - Epoch(val) [3][20/78] eta: 0:00:41 time: 0.7127 data_time: 0.5557 memory: 3625 2022/09/05 08:47:54 - mmengine - INFO - Epoch(val) [3][40/78] eta: 0:00:17 time: 0.4526 data_time: 0.2974 memory: 3625 2022/09/05 08:48:07 - mmengine - INFO - Epoch(val) [3][60/78] eta: 0:00:11 time: 0.6344 data_time: 0.4788 memory: 3625 2022/09/05 08:48:15 - mmengine - INFO - Epoch(val) [3][78/78] acc/top1: 0.6810 acc/top5: 0.8870 acc/mean1: 0.6808 2022/09/05 08:48:16 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_3.pth is removed 2022/09/05 08:48:19 - mmengine - INFO - The best checkpoint with 0.6810 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/09/05 08:48:35 - mmengine - INFO - Epoch(train) [4][20/940] lr: 1.0000e-02 eta: 20:04:14 time: 0.8433 data_time: 0.2988 memory: 24011 grad_norm: 4.0902 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5903 loss: 1.5903 2022/09/05 08:48:48 - mmengine - INFO - Epoch(train) [4][40/940] lr: 1.0000e-02 eta: 20:02:26 time: 0.6487 data_time: 0.0949 memory: 24011 grad_norm: 4.1988 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.4016 loss: 1.4016 2022/09/05 08:49:02 - mmengine - INFO - Epoch(train) [4][60/940] lr: 1.0000e-02 eta: 20:00:59 time: 0.6791 data_time: 0.1246 memory: 24011 grad_norm: 4.0753 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5518 loss: 1.5518 2022/09/05 08:49:14 - mmengine - INFO - Epoch(train) [4][80/940] lr: 1.0000e-02 eta: 19:58:47 time: 0.6057 data_time: 0.0476 memory: 24011 grad_norm: 4.2282 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5815 loss: 1.5815 2022/09/05 08:49:28 - mmengine - INFO - Epoch(train) [4][100/940] lr: 1.0000e-02 eta: 19:57:21 time: 0.6768 data_time: 0.1153 memory: 24011 grad_norm: 4.3346 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5804 loss: 1.5804 2022/09/05 08:49:40 - mmengine - INFO - Epoch(train) [4][120/940] lr: 1.0000e-02 eta: 19:55:35 time: 0.6429 data_time: 0.0850 memory: 24011 grad_norm: 4.2621 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5694 loss: 1.5694 2022/09/05 08:49:54 - mmengine - INFO - Epoch(train) [4][140/940] lr: 1.0000e-02 eta: 19:54:16 time: 0.6846 data_time: 0.1296 memory: 24011 grad_norm: 4.5182 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6279 loss: 1.6279 2022/09/05 08:50:07 - mmengine - INFO - Epoch(train) [4][160/940] lr: 1.0000e-02 eta: 19:52:19 time: 0.6227 data_time: 0.0615 memory: 24011 grad_norm: 4.0427 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6507 loss: 1.6507 2022/09/05 08:50:20 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 08:50:20 - mmengine - INFO - Epoch(train) [4][180/940] lr: 1.0000e-02 eta: 19:51:00 time: 0.6811 data_time: 0.1158 memory: 24011 grad_norm: 3.9638 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5996 loss: 1.5996 2022/09/05 08:50:32 - mmengine - INFO - Epoch(train) [4][200/940] lr: 1.0000e-02 eta: 19:48:54 time: 0.6020 data_time: 0.0397 memory: 24011 grad_norm: 4.1471 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6079 loss: 1.6079 2022/09/05 08:50:45 - mmengine - INFO - Epoch(train) [4][220/940] lr: 1.0000e-02 eta: 19:46:59 time: 0.6177 data_time: 0.0510 memory: 24011 grad_norm: 4.0338 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6354 loss: 1.6354 2022/09/05 08:50:59 - mmengine - INFO - Epoch(train) [4][240/940] lr: 1.0000e-02 eta: 19:45:57 time: 0.7056 data_time: 0.1146 memory: 24011 grad_norm: 4.0763 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6041 loss: 1.6041 2022/09/05 08:51:11 - mmengine - INFO - Epoch(train) [4][260/940] lr: 1.0000e-02 eta: 19:43:51 time: 0.5961 data_time: 0.0362 memory: 24011 grad_norm: 4.3448 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6484 loss: 1.6484 2022/09/05 08:51:24 - mmengine - INFO - Epoch(train) [4][280/940] lr: 1.0000e-02 eta: 19:42:13 time: 0.6398 data_time: 0.0839 memory: 24011 grad_norm: 4.1491 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.5565 loss: 1.5565 2022/09/05 08:51:36 - mmengine - INFO - Epoch(train) [4][300/940] lr: 1.0000e-02 eta: 19:40:34 time: 0.6370 data_time: 0.0437 memory: 24011 grad_norm: 3.8139 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.4572 loss: 1.4572 2022/09/05 08:51:50 - mmengine - INFO - Epoch(train) [4][320/940] lr: 1.0000e-02 eta: 19:39:12 time: 0.6660 data_time: 0.0354 memory: 24011 grad_norm: 4.2241 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4528 loss: 1.4528 2022/09/05 08:52:04 - mmengine - INFO - Epoch(train) [4][340/940] lr: 1.0000e-02 eta: 19:38:11 time: 0.6993 data_time: 0.0351 memory: 24011 grad_norm: 4.6262 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7189 loss: 1.7189 2022/09/05 08:52:16 - mmengine - INFO - Epoch(train) [4][360/940] lr: 1.0000e-02 eta: 19:36:30 time: 0.6277 data_time: 0.0375 memory: 24011 grad_norm: 4.1353 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4936 loss: 1.4936 2022/09/05 08:52:29 - mmengine - INFO - Epoch(train) [4][380/940] lr: 1.0000e-02 eta: 19:35:07 time: 0.6598 data_time: 0.0497 memory: 24011 grad_norm: 4.0563 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7903 loss: 1.7903 2022/09/05 08:52:42 - mmengine - INFO - Epoch(train) [4][400/940] lr: 1.0000e-02 eta: 19:33:23 time: 0.6196 data_time: 0.0319 memory: 24011 grad_norm: 4.2319 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5529 loss: 1.5529 2022/09/05 08:52:55 - mmengine - INFO - Epoch(train) [4][420/940] lr: 1.0000e-02 eta: 19:31:56 time: 0.6471 data_time: 0.0391 memory: 24011 grad_norm: 4.3598 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4482 loss: 1.4482 2022/09/05 08:53:07 - mmengine - INFO - Epoch(train) [4][440/940] lr: 1.0000e-02 eta: 19:30:20 time: 0.6297 data_time: 0.0559 memory: 24011 grad_norm: 4.0590 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5306 loss: 1.5306 2022/09/05 08:53:21 - mmengine - INFO - Epoch(train) [4][460/940] lr: 1.0000e-02 eta: 19:29:09 time: 0.6731 data_time: 0.0966 memory: 24011 grad_norm: 4.1977 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6462 loss: 1.6462 2022/09/05 08:53:34 - mmengine - INFO - Epoch(train) [4][480/940] lr: 1.0000e-02 eta: 19:27:53 time: 0.6636 data_time: 0.0920 memory: 24011 grad_norm: 4.3685 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5815 loss: 1.5815 2022/09/05 08:53:46 - mmengine - INFO - Epoch(train) [4][500/940] lr: 1.0000e-02 eta: 19:26:15 time: 0.6221 data_time: 0.0496 memory: 24011 grad_norm: 4.2478 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5370 loss: 1.5370 2022/09/05 08:54:00 - mmengine - INFO - Epoch(train) [4][520/940] lr: 1.0000e-02 eta: 19:24:57 time: 0.6564 data_time: 0.0959 memory: 24011 grad_norm: 4.8676 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6715 loss: 1.6715 2022/09/05 08:54:12 - mmengine - INFO - Epoch(train) [4][540/940] lr: 1.0000e-02 eta: 19:23:15 time: 0.6108 data_time: 0.0547 memory: 24011 grad_norm: 4.0437 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5148 loss: 1.5148 2022/09/05 08:54:25 - mmengine - INFO - Epoch(train) [4][560/940] lr: 1.0000e-02 eta: 19:22:12 time: 0.6802 data_time: 0.1098 memory: 24011 grad_norm: 4.0890 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5271 loss: 1.5271 2022/09/05 08:54:38 - mmengine - INFO - Epoch(train) [4][580/940] lr: 1.0000e-02 eta: 19:20:35 time: 0.6177 data_time: 0.0445 memory: 24011 grad_norm: 3.9575 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5967 loss: 1.5967 2022/09/05 08:54:51 - mmengine - INFO - Epoch(train) [4][600/940] lr: 1.0000e-02 eta: 19:19:16 time: 0.6482 data_time: 0.0680 memory: 24011 grad_norm: 4.1128 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5784 loss: 1.5784 2022/09/05 08:55:04 - mmengine - INFO - Epoch(train) [4][620/940] lr: 1.0000e-02 eta: 19:18:10 time: 0.6704 data_time: 0.0906 memory: 24011 grad_norm: 4.4840 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5205 loss: 1.5205 2022/09/05 08:55:18 - mmengine - INFO - Epoch(train) [4][640/940] lr: 1.0000e-02 eta: 19:17:10 time: 0.6825 data_time: 0.0876 memory: 24011 grad_norm: 7.9952 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5137 loss: 1.5137 2022/09/05 08:55:30 - mmengine - INFO - Epoch(train) [4][660/940] lr: 1.0000e-02 eta: 19:15:38 time: 0.6207 data_time: 0.0367 memory: 24011 grad_norm: 4.9548 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6906 loss: 1.6906 2022/09/05 08:55:43 - mmengine - INFO - Epoch(train) [4][680/940] lr: 1.0000e-02 eta: 19:14:10 time: 0.6246 data_time: 0.0532 memory: 24011 grad_norm: 5.5346 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.6231 loss: 1.6231 2022/09/05 08:55:55 - mmengine - INFO - Epoch(train) [4][700/940] lr: 1.0000e-02 eta: 19:12:40 time: 0.6192 data_time: 0.0507 memory: 24011 grad_norm: 5.1371 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7514 loss: 1.7514 2022/09/05 08:56:08 - mmengine - INFO - Epoch(train) [4][720/940] lr: 1.0000e-02 eta: 19:11:20 time: 0.6379 data_time: 0.0709 memory: 24011 grad_norm: 4.5734 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7168 loss: 1.7168 2022/09/05 08:56:21 - mmengine - INFO - Epoch(train) [4][740/940] lr: 1.0000e-02 eta: 19:10:18 time: 0.6717 data_time: 0.0335 memory: 24011 grad_norm: 4.3724 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.6739 loss: 1.6739 2022/09/05 08:56:34 - mmengine - INFO - Epoch(train) [4][760/940] lr: 1.0000e-02 eta: 19:08:56 time: 0.6316 data_time: 0.0394 memory: 24011 grad_norm: 4.5311 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5838 loss: 1.5838 2022/09/05 08:56:48 - mmengine - INFO - Epoch(train) [4][780/940] lr: 1.0000e-02 eta: 19:08:08 time: 0.6966 data_time: 0.0334 memory: 24011 grad_norm: 4.4059 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.5809 loss: 1.5809 2022/09/05 08:57:00 - mmengine - INFO - Epoch(train) [4][800/940] lr: 1.0000e-02 eta: 19:06:49 time: 0.6339 data_time: 0.0363 memory: 24011 grad_norm: 4.0948 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6260 loss: 1.6260 2022/09/05 08:57:13 - mmengine - INFO - Epoch(train) [4][820/940] lr: 1.0000e-02 eta: 19:05:37 time: 0.6484 data_time: 0.0390 memory: 24011 grad_norm: 4.8026 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.6122 loss: 1.6122 2022/09/05 08:57:26 - mmengine - INFO - Epoch(train) [4][840/940] lr: 1.0000e-02 eta: 19:04:07 time: 0.6080 data_time: 0.0474 memory: 24011 grad_norm: 4.1692 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6304 loss: 1.6304 2022/09/05 08:57:39 - mmengine - INFO - Epoch(train) [4][860/940] lr: 1.0000e-02 eta: 19:02:56 time: 0.6468 data_time: 0.0351 memory: 24011 grad_norm: 4.1408 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5476 loss: 1.5476 2022/09/05 08:57:51 - mmengine - INFO - Epoch(train) [4][880/940] lr: 1.0000e-02 eta: 19:01:46 time: 0.6475 data_time: 0.0590 memory: 24011 grad_norm: 4.3526 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5501 loss: 1.5501 2022/09/05 08:58:04 - mmengine - INFO - Epoch(train) [4][900/940] lr: 1.0000e-02 eta: 19:00:36 time: 0.6453 data_time: 0.0452 memory: 24011 grad_norm: 4.0836 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5185 loss: 1.5185 2022/09/05 08:58:18 - mmengine - INFO - Epoch(train) [4][920/940] lr: 1.0000e-02 eta: 18:59:37 time: 0.6679 data_time: 0.0457 memory: 24011 grad_norm: 4.1360 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.5394 loss: 1.5394 2022/09/05 08:58:29 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 08:58:29 - mmengine - INFO - Epoch(train) [4][940/940] lr: 1.0000e-02 eta: 18:57:55 time: 0.5750 data_time: 0.0255 memory: 24011 grad_norm: 5.1740 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.6933 loss: 1.6933 2022/09/05 08:58:43 - mmengine - INFO - Epoch(val) [4][20/78] eta: 0:00:40 time: 0.7035 data_time: 0.5442 memory: 3625 2022/09/05 08:58:52 - mmengine - INFO - Epoch(val) [4][40/78] eta: 0:00:17 time: 0.4558 data_time: 0.3003 memory: 3625 2022/09/05 08:59:06 - mmengine - INFO - Epoch(val) [4][60/78] eta: 0:00:11 time: 0.6511 data_time: 0.4922 memory: 3625 2022/09/05 08:59:16 - mmengine - INFO - Epoch(val) [4][78/78] acc/top1: 0.6804 acc/top5: 0.8875 acc/mean1: 0.6803 2022/09/05 08:59:34 - mmengine - INFO - Epoch(train) [5][20/940] lr: 1.0000e-02 eta: 18:58:46 time: 0.8966 data_time: 0.3001 memory: 24011 grad_norm: 4.8044 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3726 loss: 1.3726 2022/09/05 08:59:47 - mmengine - INFO - Epoch(train) [5][40/940] lr: 1.0000e-02 eta: 18:57:35 time: 0.6393 data_time: 0.0431 memory: 24011 grad_norm: 4.1622 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6607 loss: 1.6607 2022/09/05 09:00:00 - mmengine - INFO - Epoch(train) [5][60/940] lr: 1.0000e-02 eta: 18:56:34 time: 0.6587 data_time: 0.0606 memory: 24011 grad_norm: 4.2798 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.4586 loss: 1.4586 2022/09/05 09:00:13 - mmengine - INFO - Epoch(train) [5][80/940] lr: 1.0000e-02 eta: 18:55:32 time: 0.6572 data_time: 0.0362 memory: 24011 grad_norm: 4.2926 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4621 loss: 1.4621 2022/09/05 09:00:26 - mmengine - INFO - Epoch(train) [5][100/940] lr: 1.0000e-02 eta: 18:54:37 time: 0.6706 data_time: 0.0363 memory: 24011 grad_norm: 5.0362 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6168 loss: 1.6168 2022/09/05 09:00:39 - mmengine - INFO - Epoch(train) [5][120/940] lr: 1.0000e-02 eta: 18:53:31 time: 0.6450 data_time: 0.0342 memory: 24011 grad_norm: 4.5242 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5461 loss: 1.5461 2022/09/05 09:00:53 - mmengine - INFO - Epoch(train) [5][140/940] lr: 1.0000e-02 eta: 18:52:32 time: 0.6592 data_time: 0.0400 memory: 24011 grad_norm: 4.1198 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5661 loss: 1.5661 2022/09/05 09:01:06 - mmengine - INFO - Epoch(train) [5][160/940] lr: 1.0000e-02 eta: 18:51:29 time: 0.6514 data_time: 0.0361 memory: 24011 grad_norm: 3.9467 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4240 loss: 1.4240 2022/09/05 09:01:18 - mmengine - INFO - Epoch(train) [5][180/940] lr: 1.0000e-02 eta: 18:50:24 time: 0.6447 data_time: 0.0374 memory: 24011 grad_norm: 4.3089 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4760 loss: 1.4760 2022/09/05 09:01:31 - mmengine - INFO - Epoch(train) [5][200/940] lr: 1.0000e-02 eta: 18:49:13 time: 0.6286 data_time: 0.0533 memory: 24011 grad_norm: 4.3588 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5099 loss: 1.5099 2022/09/05 09:01:45 - mmengine - INFO - Epoch(train) [5][220/940] lr: 1.0000e-02 eta: 18:48:31 time: 0.6942 data_time: 0.1112 memory: 24011 grad_norm: 4.2542 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3517 loss: 1.3517 2022/09/05 09:01:58 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:01:58 - mmengine - INFO - Epoch(train) [5][240/940] lr: 1.0000e-02 eta: 18:47:28 time: 0.6456 data_time: 0.0499 memory: 24011 grad_norm: 4.2773 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6002 loss: 1.6002 2022/09/05 09:02:11 - mmengine - INFO - Epoch(train) [5][260/940] lr: 1.0000e-02 eta: 18:46:30 time: 0.6560 data_time: 0.0558 memory: 24011 grad_norm: 4.3796 top1_acc: 0.5312 top5_acc: 0.9688 loss_cls: 1.6055 loss: 1.6055 2022/09/05 09:02:24 - mmengine - INFO - Epoch(train) [5][280/940] lr: 1.0000e-02 eta: 18:45:32 time: 0.6537 data_time: 0.0370 memory: 24011 grad_norm: 4.0187 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5776 loss: 1.5776 2022/09/05 09:02:36 - mmengine - INFO - Epoch(train) [5][300/940] lr: 1.0000e-02 eta: 18:44:15 time: 0.6098 data_time: 0.0418 memory: 24011 grad_norm: 4.4454 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4355 loss: 1.4355 2022/09/05 09:02:49 - mmengine - INFO - Epoch(train) [5][320/940] lr: 1.0000e-02 eta: 18:43:17 time: 0.6531 data_time: 0.0385 memory: 24011 grad_norm: 4.5458 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4667 loss: 1.4667 2022/09/05 09:03:02 - mmengine - INFO - Epoch(train) [5][340/940] lr: 1.0000e-02 eta: 18:42:20 time: 0.6530 data_time: 0.0349 memory: 24011 grad_norm: 4.5232 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5337 loss: 1.5337 2022/09/05 09:03:15 - mmengine - INFO - Epoch(train) [5][360/940] lr: 1.0000e-02 eta: 18:41:06 time: 0.6145 data_time: 0.0350 memory: 24011 grad_norm: 4.2686 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6103 loss: 1.6103 2022/09/05 09:03:28 - mmengine - INFO - Epoch(train) [5][380/940] lr: 1.0000e-02 eta: 18:40:05 time: 0.6430 data_time: 0.0412 memory: 24011 grad_norm: 4.4524 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5489 loss: 1.5489 2022/09/05 09:03:41 - mmengine - INFO - Epoch(train) [5][400/940] lr: 1.0000e-02 eta: 18:39:12 time: 0.6590 data_time: 0.0398 memory: 24011 grad_norm: 4.2786 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4522 loss: 1.4522 2022/09/05 09:03:54 - mmengine - INFO - Epoch(train) [5][420/940] lr: 1.0000e-02 eta: 18:38:12 time: 0.6427 data_time: 0.0356 memory: 24011 grad_norm: 4.4382 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6204 loss: 1.6204 2022/09/05 09:04:07 - mmengine - INFO - Epoch(train) [5][440/940] lr: 1.0000e-02 eta: 18:37:18 time: 0.6548 data_time: 0.0440 memory: 24011 grad_norm: 4.3941 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5800 loss: 1.5800 2022/09/05 09:04:19 - mmengine - INFO - Epoch(train) [5][460/940] lr: 1.0000e-02 eta: 18:36:17 time: 0.6396 data_time: 0.0387 memory: 24011 grad_norm: 4.3136 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5691 loss: 1.5691 2022/09/05 09:04:32 - mmengine - INFO - Epoch(train) [5][480/940] lr: 1.0000e-02 eta: 18:35:16 time: 0.6370 data_time: 0.0406 memory: 24011 grad_norm: 4.3036 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5633 loss: 1.5633 2022/09/05 09:04:46 - mmengine - INFO - Epoch(train) [5][500/940] lr: 1.0000e-02 eta: 18:34:41 time: 0.6981 data_time: 0.0382 memory: 24011 grad_norm: 4.6231 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5905 loss: 1.5905 2022/09/05 09:04:59 - mmengine - INFO - Epoch(train) [5][520/940] lr: 1.0000e-02 eta: 18:33:52 time: 0.6640 data_time: 0.0428 memory: 24011 grad_norm: 4.1166 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4622 loss: 1.4622 2022/09/05 09:05:13 - mmengine - INFO - Epoch(train) [5][540/940] lr: 1.0000e-02 eta: 18:32:59 time: 0.6542 data_time: 0.0279 memory: 24011 grad_norm: 3.9543 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5380 loss: 1.5380 2022/09/05 09:05:25 - mmengine - INFO - Epoch(train) [5][560/940] lr: 1.0000e-02 eta: 18:31:46 time: 0.6033 data_time: 0.0395 memory: 24011 grad_norm: 4.1702 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4471 loss: 1.4471 2022/09/05 09:05:38 - mmengine - INFO - Epoch(train) [5][580/940] lr: 1.0000e-02 eta: 18:30:56 time: 0.6595 data_time: 0.0348 memory: 24011 grad_norm: 4.0619 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4284 loss: 1.4284 2022/09/05 09:05:51 - mmengine - INFO - Epoch(train) [5][600/940] lr: 1.0000e-02 eta: 18:30:03 time: 0.6513 data_time: 0.0399 memory: 24011 grad_norm: 4.0420 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5672 loss: 1.5672 2022/09/05 09:06:04 - mmengine - INFO - Epoch(train) [5][620/940] lr: 1.0000e-02 eta: 18:29:18 time: 0.6678 data_time: 0.0399 memory: 24011 grad_norm: 4.3130 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5484 loss: 1.5484 2022/09/05 09:06:17 - mmengine - INFO - Epoch(train) [5][640/940] lr: 1.0000e-02 eta: 18:28:16 time: 0.6284 data_time: 0.0629 memory: 24011 grad_norm: 4.3525 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5101 loss: 1.5101 2022/09/05 09:06:29 - mmengine - INFO - Epoch(train) [5][660/940] lr: 1.0000e-02 eta: 18:27:11 time: 0.6178 data_time: 0.0384 memory: 24011 grad_norm: 4.0130 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4497 loss: 1.4497 2022/09/05 09:06:42 - mmengine - INFO - Epoch(train) [5][680/940] lr: 1.0000e-02 eta: 18:26:08 time: 0.6211 data_time: 0.0374 memory: 24011 grad_norm: 4.3313 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4710 loss: 1.4710 2022/09/05 09:06:55 - mmengine - INFO - Epoch(train) [5][700/940] lr: 1.0000e-02 eta: 18:25:23 time: 0.6662 data_time: 0.0383 memory: 24011 grad_norm: 4.3724 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5702 loss: 1.5702 2022/09/05 09:07:08 - mmengine - INFO - Epoch(train) [5][720/940] lr: 1.0000e-02 eta: 18:24:36 time: 0.6609 data_time: 0.0373 memory: 24011 grad_norm: 4.0414 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4688 loss: 1.4688 2022/09/05 09:07:21 - mmengine - INFO - Epoch(train) [5][740/940] lr: 1.0000e-02 eta: 18:23:49 time: 0.6598 data_time: 0.0437 memory: 24011 grad_norm: 4.3723 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4281 loss: 1.4281 2022/09/05 09:07:34 - mmengine - INFO - Epoch(train) [5][760/940] lr: 1.0000e-02 eta: 18:22:54 time: 0.6376 data_time: 0.0408 memory: 24011 grad_norm: 4.0171 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4544 loss: 1.4544 2022/09/05 09:07:47 - mmengine - INFO - Epoch(train) [5][780/940] lr: 1.0000e-02 eta: 18:22:00 time: 0.6399 data_time: 0.0426 memory: 24011 grad_norm: 4.0121 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4345 loss: 1.4345 2022/09/05 09:08:00 - mmengine - INFO - Epoch(train) [5][800/940] lr: 1.0000e-02 eta: 18:21:11 time: 0.6519 data_time: 0.0392 memory: 24011 grad_norm: 4.1398 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5182 loss: 1.5182 2022/09/05 09:08:13 - mmengine - INFO - Epoch(train) [5][820/940] lr: 1.0000e-02 eta: 18:20:22 time: 0.6524 data_time: 0.0398 memory: 24011 grad_norm: 4.1035 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.6664 loss: 1.6664 2022/09/05 09:08:25 - mmengine - INFO - Epoch(train) [5][840/940] lr: 1.0000e-02 eta: 18:19:17 time: 0.6081 data_time: 0.0378 memory: 24011 grad_norm: 4.1786 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6133 loss: 1.6133 2022/09/05 09:08:38 - mmengine - INFO - Epoch(train) [5][860/940] lr: 1.0000e-02 eta: 18:18:29 time: 0.6514 data_time: 0.0453 memory: 24011 grad_norm: 4.1830 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4518 loss: 1.4518 2022/09/05 09:08:51 - mmengine - INFO - Epoch(train) [5][880/940] lr: 1.0000e-02 eta: 18:17:38 time: 0.6450 data_time: 0.0633 memory: 24011 grad_norm: 4.3876 top1_acc: 0.4375 top5_acc: 0.9062 loss_cls: 1.6824 loss: 1.6824 2022/09/05 09:09:05 - mmengine - INFO - Epoch(train) [5][900/940] lr: 1.0000e-02 eta: 18:17:01 time: 0.6781 data_time: 0.0961 memory: 24011 grad_norm: 4.0570 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.6937 loss: 1.6937 2022/09/05 09:09:17 - mmengine - INFO - Epoch(train) [5][920/940] lr: 1.0000e-02 eta: 18:15:59 time: 0.6122 data_time: 0.0361 memory: 24011 grad_norm: 3.9765 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4814 loss: 1.4814 2022/09/05 09:09:28 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:09:28 - mmengine - INFO - Epoch(train) [5][940/940] lr: 1.0000e-02 eta: 18:14:47 time: 0.5847 data_time: 0.0481 memory: 24011 grad_norm: 4.2036 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.5147 loss: 1.5147 2022/09/05 09:09:43 - mmengine - INFO - Epoch(val) [5][20/78] eta: 0:00:40 time: 0.7052 data_time: 0.5495 memory: 3625 2022/09/05 09:09:51 - mmengine - INFO - Epoch(val) [5][40/78] eta: 0:00:16 time: 0.4346 data_time: 0.2794 memory: 3625 2022/09/05 09:10:04 - mmengine - INFO - Epoch(val) [5][60/78] eta: 0:00:11 time: 0.6443 data_time: 0.4831 memory: 3625 2022/09/05 09:10:15 - mmengine - INFO - Epoch(val) [5][78/78] acc/top1: 0.6964 acc/top5: 0.8939 acc/mean1: 0.6963 2022/09/05 09:10:15 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_4.pth is removed 2022/09/05 09:10:18 - mmengine - INFO - The best checkpoint with 0.6964 acc/top1 at 6 epoch is saved to best_acc/top1_epoch_6.pth. 2022/09/05 09:10:35 - mmengine - INFO - Epoch(train) [6][20/940] lr: 1.0000e-02 eta: 18:15:16 time: 0.8520 data_time: 0.3041 memory: 24011 grad_norm: 4.3746 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.4701 loss: 1.4701 2022/09/05 09:10:47 - mmengine - INFO - Epoch(train) [6][40/940] lr: 1.0000e-02 eta: 18:14:20 time: 0.6271 data_time: 0.0603 memory: 24011 grad_norm: 4.2106 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4376 loss: 1.4376 2022/09/05 09:11:01 - mmengine - INFO - Epoch(train) [6][60/940] lr: 1.0000e-02 eta: 18:13:41 time: 0.6713 data_time: 0.1197 memory: 24011 grad_norm: 4.4504 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4132 loss: 1.4132 2022/09/05 09:11:13 - mmengine - INFO - Epoch(train) [6][80/940] lr: 1.0000e-02 eta: 18:12:39 time: 0.6079 data_time: 0.0413 memory: 24011 grad_norm: 3.9996 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3674 loss: 1.3674 2022/09/05 09:11:26 - mmengine - INFO - Epoch(train) [6][100/940] lr: 1.0000e-02 eta: 18:12:03 time: 0.6780 data_time: 0.1160 memory: 24011 grad_norm: 4.2429 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4059 loss: 1.4059 2022/09/05 09:11:40 - mmengine - INFO - Epoch(train) [6][120/940] lr: 1.0000e-02 eta: 18:11:23 time: 0.6660 data_time: 0.0672 memory: 24011 grad_norm: 4.4835 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5146 loss: 1.5146 2022/09/05 09:11:52 - mmengine - INFO - Epoch(train) [6][140/940] lr: 1.0000e-02 eta: 18:10:20 time: 0.6032 data_time: 0.0367 memory: 24011 grad_norm: 4.0425 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4511 loss: 1.4511 2022/09/05 09:12:04 - mmengine - INFO - Epoch(train) [6][160/940] lr: 1.0000e-02 eta: 18:09:26 time: 0.6256 data_time: 0.0647 memory: 24011 grad_norm: 4.6806 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.4842 loss: 1.4842 2022/09/05 09:12:18 - mmengine - INFO - Epoch(train) [6][180/940] lr: 1.0000e-02 eta: 18:09:00 time: 0.7023 data_time: 0.1297 memory: 24011 grad_norm: 4.1006 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3633 loss: 1.3633 2022/09/05 09:12:31 - mmengine - INFO - Epoch(train) [6][200/940] lr: 1.0000e-02 eta: 18:08:08 time: 0.6320 data_time: 0.0709 memory: 24011 grad_norm: 3.9230 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.4486 loss: 1.4486 2022/09/05 09:12:44 - mmengine - INFO - Epoch(train) [6][220/940] lr: 1.0000e-02 eta: 18:07:16 time: 0.6273 data_time: 0.0658 memory: 24011 grad_norm: 4.0060 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5141 loss: 1.5141 2022/09/05 09:12:56 - mmengine - INFO - Epoch(train) [6][240/940] lr: 1.0000e-02 eta: 18:06:29 time: 0.6430 data_time: 0.0774 memory: 24011 grad_norm: 3.8330 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3550 loss: 1.3550 2022/09/05 09:13:08 - mmengine - INFO - Epoch(train) [6][260/940] lr: 1.0000e-02 eta: 18:05:26 time: 0.5989 data_time: 0.0391 memory: 24011 grad_norm: 3.9772 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4858 loss: 1.4858 2022/09/05 09:13:21 - mmengine - INFO - Epoch(train) [6][280/940] lr: 1.0000e-02 eta: 18:04:41 time: 0.6457 data_time: 0.0795 memory: 24011 grad_norm: 4.3334 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5121 loss: 1.5121 2022/09/05 09:13:34 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:13:34 - mmengine - INFO - Epoch(train) [6][300/940] lr: 1.0000e-02 eta: 18:03:54 time: 0.6388 data_time: 0.0570 memory: 24011 grad_norm: 3.9165 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4555 loss: 1.4555 2022/09/05 09:13:47 - mmengine - INFO - Epoch(train) [6][320/940] lr: 1.0000e-02 eta: 18:03:16 time: 0.6670 data_time: 0.0309 memory: 24011 grad_norm: 4.0917 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5110 loss: 1.5110 2022/09/05 09:14:01 - mmengine - INFO - Epoch(train) [6][340/940] lr: 1.0000e-02 eta: 18:02:39 time: 0.6657 data_time: 0.0371 memory: 24011 grad_norm: 3.8889 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5644 loss: 1.5644 2022/09/05 09:14:13 - mmengine - INFO - Epoch(train) [6][360/940] lr: 1.0000e-02 eta: 18:01:46 time: 0.6219 data_time: 0.0368 memory: 24011 grad_norm: 3.8340 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4303 loss: 1.4303 2022/09/05 09:14:26 - mmengine - INFO - Epoch(train) [6][380/940] lr: 1.0000e-02 eta: 18:01:02 time: 0.6450 data_time: 0.0394 memory: 24011 grad_norm: 4.5360 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3814 loss: 1.3814 2022/09/05 09:14:39 - mmengine - INFO - Epoch(train) [6][400/940] lr: 1.0000e-02 eta: 18:00:16 time: 0.6405 data_time: 0.0326 memory: 24011 grad_norm: 4.3194 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6269 loss: 1.6269 2022/09/05 09:14:52 - mmengine - INFO - Epoch(train) [6][420/940] lr: 1.0000e-02 eta: 17:59:39 time: 0.6641 data_time: 0.0422 memory: 24011 grad_norm: 4.3075 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3744 loss: 1.3744 2022/09/05 09:15:05 - mmengine - INFO - Epoch(train) [6][440/940] lr: 1.0000e-02 eta: 17:58:57 time: 0.6478 data_time: 0.0344 memory: 24011 grad_norm: 4.0367 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5056 loss: 1.5056 2022/09/05 09:15:18 - mmengine - INFO - Epoch(train) [6][460/940] lr: 1.0000e-02 eta: 17:58:10 time: 0.6369 data_time: 0.0390 memory: 24011 grad_norm: 5.2300 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5034 loss: 1.5034 2022/09/05 09:15:31 - mmengine - INFO - Epoch(train) [6][480/940] lr: 1.0000e-02 eta: 17:57:26 time: 0.6404 data_time: 0.0386 memory: 24011 grad_norm: 4.1501 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5566 loss: 1.5566 2022/09/05 09:15:44 - mmengine - INFO - Epoch(train) [6][500/940] lr: 1.0000e-02 eta: 17:56:45 time: 0.6508 data_time: 0.0402 memory: 24011 grad_norm: 4.4252 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5247 loss: 1.5247 2022/09/05 09:15:56 - mmengine - INFO - Epoch(train) [6][520/940] lr: 1.0000e-02 eta: 17:55:55 time: 0.6237 data_time: 0.0374 memory: 24011 grad_norm: 4.1124 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5069 loss: 1.5069 2022/09/05 09:16:09 - mmengine - INFO - Epoch(train) [6][540/940] lr: 1.0000e-02 eta: 17:55:07 time: 0.6294 data_time: 0.0524 memory: 24011 grad_norm: 4.0752 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4512 loss: 1.4512 2022/09/05 09:16:22 - mmengine - INFO - Epoch(train) [6][560/940] lr: 1.0000e-02 eta: 17:54:35 time: 0.6745 data_time: 0.0376 memory: 24011 grad_norm: 4.1235 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4365 loss: 1.4365 2022/09/05 09:16:35 - mmengine - INFO - Epoch(train) [6][580/940] lr: 1.0000e-02 eta: 17:53:48 time: 0.6307 data_time: 0.0446 memory: 24011 grad_norm: 4.0585 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5572 loss: 1.5572 2022/09/05 09:16:48 - mmengine - INFO - Epoch(train) [6][600/940] lr: 1.0000e-02 eta: 17:53:10 time: 0.6534 data_time: 0.0380 memory: 24011 grad_norm: 4.1867 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3870 loss: 1.3870 2022/09/05 09:17:01 - mmengine - INFO - Epoch(train) [6][620/940] lr: 1.0000e-02 eta: 17:52:33 time: 0.6607 data_time: 0.0423 memory: 24011 grad_norm: 4.0362 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5277 loss: 1.5277 2022/09/05 09:17:15 - mmengine - INFO - Epoch(train) [6][640/940] lr: 1.0000e-02 eta: 17:52:02 time: 0.6739 data_time: 0.0392 memory: 24011 grad_norm: 4.2475 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.4905 loss: 1.4905 2022/09/05 09:17:27 - mmengine - INFO - Epoch(train) [6][660/940] lr: 1.0000e-02 eta: 17:51:21 time: 0.6466 data_time: 0.0388 memory: 24011 grad_norm: 3.9658 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5639 loss: 1.5639 2022/09/05 09:17:40 - mmengine - INFO - Epoch(train) [6][680/940] lr: 1.0000e-02 eta: 17:50:34 time: 0.6267 data_time: 0.0364 memory: 24011 grad_norm: 3.9788 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4903 loss: 1.4903 2022/09/05 09:17:53 - mmengine - INFO - Epoch(train) [6][700/940] lr: 1.0000e-02 eta: 17:49:58 time: 0.6607 data_time: 0.0414 memory: 24011 grad_norm: 3.9907 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4762 loss: 1.4762 2022/09/05 09:18:06 - mmengine - INFO - Epoch(train) [6][720/940] lr: 1.0000e-02 eta: 17:49:17 time: 0.6425 data_time: 0.0367 memory: 24011 grad_norm: 4.1859 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.4215 loss: 1.4215 2022/09/05 09:18:19 - mmengine - INFO - Epoch(train) [6][740/940] lr: 1.0000e-02 eta: 17:48:40 time: 0.6531 data_time: 0.0425 memory: 24011 grad_norm: 4.3167 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4420 loss: 1.4420 2022/09/05 09:18:32 - mmengine - INFO - Epoch(train) [6][760/940] lr: 1.0000e-02 eta: 17:47:53 time: 0.6242 data_time: 0.0341 memory: 24011 grad_norm: 4.1025 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5093 loss: 1.5093 2022/09/05 09:18:45 - mmengine - INFO - Epoch(train) [6][780/940] lr: 1.0000e-02 eta: 17:47:19 time: 0.6658 data_time: 0.0389 memory: 24011 grad_norm: 4.5162 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4410 loss: 1.4410 2022/09/05 09:18:57 - mmengine - INFO - Epoch(train) [6][800/940] lr: 1.0000e-02 eta: 17:46:27 time: 0.6050 data_time: 0.0360 memory: 24011 grad_norm: 4.7226 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5789 loss: 1.5789 2022/09/05 09:19:10 - mmengine - INFO - Epoch(train) [6][820/940] lr: 1.0000e-02 eta: 17:45:56 time: 0.6723 data_time: 0.0350 memory: 24011 grad_norm: 4.1706 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4962 loss: 1.4962 2022/09/05 09:19:23 - mmengine - INFO - Epoch(train) [6][840/940] lr: 1.0000e-02 eta: 17:45:10 time: 0.6248 data_time: 0.0371 memory: 24011 grad_norm: 4.5201 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5019 loss: 1.5019 2022/09/05 09:19:37 - mmengine - INFO - Epoch(train) [6][860/940] lr: 1.0000e-02 eta: 17:44:44 time: 0.6841 data_time: 0.0386 memory: 24011 grad_norm: 4.1244 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5042 loss: 1.5042 2022/09/05 09:19:50 - mmengine - INFO - Epoch(train) [6][880/940] lr: 1.0000e-02 eta: 17:44:05 time: 0.6472 data_time: 0.0383 memory: 24011 grad_norm: 4.2549 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.5215 loss: 1.5215 2022/09/05 09:20:03 - mmengine - INFO - Epoch(train) [6][900/940] lr: 1.0000e-02 eta: 17:43:28 time: 0.6493 data_time: 0.0407 memory: 24011 grad_norm: 4.3814 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5488 loss: 1.5488 2022/09/05 09:20:15 - mmengine - INFO - Epoch(train) [6][920/940] lr: 1.0000e-02 eta: 17:42:38 time: 0.6101 data_time: 0.0422 memory: 24011 grad_norm: 4.5136 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3682 loss: 1.3682 2022/09/05 09:20:26 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:20:26 - mmengine - INFO - Epoch(train) [6][940/940] lr: 1.0000e-02 eta: 17:41:41 time: 0.5853 data_time: 0.0447 memory: 24011 grad_norm: 4.6299 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.4971 loss: 1.4971 2022/09/05 09:20:27 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/09/05 09:20:46 - mmengine - INFO - Epoch(val) [6][20/78] eta: 0:00:40 time: 0.7039 data_time: 0.5487 memory: 3625 2022/09/05 09:20:55 - mmengine - INFO - Epoch(val) [6][40/78] eta: 0:00:17 time: 0.4651 data_time: 0.3059 memory: 3625 2022/09/05 09:21:08 - mmengine - INFO - Epoch(val) [6][60/78] eta: 0:00:11 time: 0.6325 data_time: 0.4765 memory: 3625 2022/09/05 09:21:17 - mmengine - INFO - Epoch(val) [6][78/78] acc/top1: 0.6977 acc/top5: 0.8946 acc/mean1: 0.6976 2022/09/05 09:21:17 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_6.pth is removed 2022/09/05 09:21:20 - mmengine - INFO - The best checkpoint with 0.6977 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth. 2022/09/05 09:21:37 - mmengine - INFO - Epoch(train) [7][20/940] lr: 1.0000e-02 eta: 17:42:13 time: 0.8670 data_time: 0.3168 memory: 24011 grad_norm: 4.1601 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3965 loss: 1.3965 2022/09/05 09:21:50 - mmengine - INFO - Epoch(train) [7][40/940] lr: 1.0000e-02 eta: 17:41:30 time: 0.6305 data_time: 0.0757 memory: 24011 grad_norm: 4.2960 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4647 loss: 1.4647 2022/09/05 09:22:03 - mmengine - INFO - Epoch(train) [7][60/940] lr: 1.0000e-02 eta: 17:40:51 time: 0.6414 data_time: 0.0641 memory: 24011 grad_norm: 4.2021 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.3882 loss: 1.3882 2022/09/05 09:22:16 - mmengine - INFO - Epoch(train) [7][80/940] lr: 1.0000e-02 eta: 17:40:12 time: 0.6411 data_time: 0.0895 memory: 24011 grad_norm: 4.0819 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3722 loss: 1.3722 2022/09/05 09:22:29 - mmengine - INFO - Epoch(train) [7][100/940] lr: 1.0000e-02 eta: 17:39:34 time: 0.6440 data_time: 0.0724 memory: 24011 grad_norm: 4.2320 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5133 loss: 1.5133 2022/09/05 09:22:42 - mmengine - INFO - Epoch(train) [7][120/940] lr: 1.0000e-02 eta: 17:39:03 time: 0.6665 data_time: 0.1060 memory: 24011 grad_norm: 4.1479 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3118 loss: 1.3118 2022/09/05 09:22:55 - mmengine - INFO - Epoch(train) [7][140/940] lr: 1.0000e-02 eta: 17:38:30 time: 0.6583 data_time: 0.1043 memory: 24011 grad_norm: 4.1170 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2940 loss: 1.2940 2022/09/05 09:23:07 - mmengine - INFO - Epoch(train) [7][160/940] lr: 1.0000e-02 eta: 17:37:39 time: 0.5996 data_time: 0.0480 memory: 24011 grad_norm: 4.1240 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5325 loss: 1.5325 2022/09/05 09:23:20 - mmengine - INFO - Epoch(train) [7][180/940] lr: 1.0000e-02 eta: 17:37:07 time: 0.6626 data_time: 0.1107 memory: 24011 grad_norm: 4.1651 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4360 loss: 1.4360 2022/09/05 09:23:33 - mmengine - INFO - Epoch(train) [7][200/940] lr: 1.0000e-02 eta: 17:36:27 time: 0.6341 data_time: 0.0741 memory: 24011 grad_norm: 4.1523 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4352 loss: 1.4352 2022/09/05 09:23:46 - mmengine - INFO - Epoch(train) [7][220/940] lr: 1.0000e-02 eta: 17:35:55 time: 0.6601 data_time: 0.0859 memory: 24011 grad_norm: 4.1202 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3759 loss: 1.3759 2022/09/05 09:23:59 - mmengine - INFO - Epoch(train) [7][240/940] lr: 1.0000e-02 eta: 17:35:15 time: 0.6342 data_time: 0.0499 memory: 24011 grad_norm: 4.8726 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3194 loss: 1.3194 2022/09/05 09:24:12 - mmengine - INFO - Epoch(train) [7][260/940] lr: 1.0000e-02 eta: 17:34:49 time: 0.6785 data_time: 0.0990 memory: 24011 grad_norm: 4.2128 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3715 loss: 1.3715 2022/09/05 09:24:25 - mmengine - INFO - Epoch(train) [7][280/940] lr: 1.0000e-02 eta: 17:34:13 time: 0.6474 data_time: 0.0659 memory: 24011 grad_norm: 3.9301 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.4594 loss: 1.4594 2022/09/05 09:24:38 - mmengine - INFO - Epoch(train) [7][300/940] lr: 1.0000e-02 eta: 17:33:40 time: 0.6566 data_time: 0.0834 memory: 24011 grad_norm: 8.3367 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6309 loss: 1.6309 2022/09/05 09:24:51 - mmengine - INFO - Epoch(train) [7][320/940] lr: 1.0000e-02 eta: 17:33:04 time: 0.6419 data_time: 0.0637 memory: 24011 grad_norm: 4.3800 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5797 loss: 1.5797 2022/09/05 09:25:04 - mmengine - INFO - Epoch(train) [7][340/940] lr: 1.0000e-02 eta: 17:32:22 time: 0.6235 data_time: 0.0636 memory: 24011 grad_norm: 4.3968 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4255 loss: 1.4255 2022/09/05 09:25:17 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:25:17 - mmengine - INFO - Epoch(train) [7][360/940] lr: 1.0000e-02 eta: 17:31:46 time: 0.6444 data_time: 0.0689 memory: 24011 grad_norm: 4.0891 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3926 loss: 1.3926 2022/09/05 09:25:29 - mmengine - INFO - Epoch(train) [7][380/940] lr: 1.0000e-02 eta: 17:31:07 time: 0.6325 data_time: 0.0450 memory: 24011 grad_norm: 4.2187 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4489 loss: 1.4489 2022/09/05 09:25:42 - mmengine - INFO - Epoch(train) [7][400/940] lr: 1.0000e-02 eta: 17:30:34 time: 0.6535 data_time: 0.0345 memory: 24011 grad_norm: 4.4145 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4120 loss: 1.4120 2022/09/05 09:25:55 - mmengine - INFO - Epoch(train) [7][420/940] lr: 1.0000e-02 eta: 17:29:50 time: 0.6149 data_time: 0.0374 memory: 24011 grad_norm: 4.7731 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4851 loss: 1.4851 2022/09/05 09:26:08 - mmengine - INFO - Epoch(train) [7][440/940] lr: 1.0000e-02 eta: 17:29:20 time: 0.6609 data_time: 0.0404 memory: 24011 grad_norm: 4.2996 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.5244 loss: 1.5244 2022/09/05 09:26:21 - mmengine - INFO - Epoch(train) [7][460/940] lr: 1.0000e-02 eta: 17:28:48 time: 0.6549 data_time: 0.0533 memory: 24011 grad_norm: 4.0055 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4176 loss: 1.4176 2022/09/05 09:26:34 - mmengine - INFO - Epoch(train) [7][480/940] lr: 1.0000e-02 eta: 17:28:13 time: 0.6449 data_time: 0.0405 memory: 24011 grad_norm: 4.2076 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4478 loss: 1.4478 2022/09/05 09:26:47 - mmengine - INFO - Epoch(train) [7][500/940] lr: 1.0000e-02 eta: 17:27:45 time: 0.6666 data_time: 0.0367 memory: 24011 grad_norm: 4.1521 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.4101 loss: 1.4101 2022/09/05 09:27:00 - mmengine - INFO - Epoch(train) [7][520/940] lr: 1.0000e-02 eta: 17:27:06 time: 0.6312 data_time: 0.0385 memory: 24011 grad_norm: 4.8744 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3554 loss: 1.3554 2022/09/05 09:27:13 - mmengine - INFO - Epoch(train) [7][540/940] lr: 1.0000e-02 eta: 17:26:34 time: 0.6512 data_time: 0.0441 memory: 24011 grad_norm: 4.9368 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4929 loss: 1.4929 2022/09/05 09:27:25 - mmengine - INFO - Epoch(train) [7][560/940] lr: 1.0000e-02 eta: 17:25:54 time: 0.6236 data_time: 0.0314 memory: 24011 grad_norm: 4.4996 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4886 loss: 1.4886 2022/09/05 09:27:39 - mmengine - INFO - Epoch(train) [7][580/940] lr: 1.0000e-02 eta: 17:25:27 time: 0.6700 data_time: 0.0756 memory: 24011 grad_norm: 4.7718 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5875 loss: 1.5875 2022/09/05 09:27:52 - mmengine - INFO - Epoch(train) [7][600/940] lr: 1.0000e-02 eta: 17:24:54 time: 0.6504 data_time: 0.0808 memory: 24011 grad_norm: 4.5338 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.4446 loss: 1.4446 2022/09/05 09:28:05 - mmengine - INFO - Epoch(train) [7][620/940] lr: 1.0000e-02 eta: 17:24:28 time: 0.6726 data_time: 0.0726 memory: 24011 grad_norm: 4.2142 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5384 loss: 1.5384 2022/09/05 09:28:18 - mmengine - INFO - Epoch(train) [7][640/940] lr: 1.0000e-02 eta: 17:23:56 time: 0.6509 data_time: 0.0644 memory: 24011 grad_norm: 4.3926 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.4963 loss: 1.4963 2022/09/05 09:28:31 - mmengine - INFO - Epoch(train) [7][660/940] lr: 1.0000e-02 eta: 17:23:22 time: 0.6406 data_time: 0.0715 memory: 24011 grad_norm: 6.3809 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5375 loss: 1.5375 2022/09/05 09:28:44 - mmengine - INFO - Epoch(train) [7][680/940] lr: 1.0000e-02 eta: 17:22:46 time: 0.6378 data_time: 0.0721 memory: 24011 grad_norm: 4.3054 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4794 loss: 1.4794 2022/09/05 09:28:57 - mmengine - INFO - Epoch(train) [7][700/940] lr: 1.0000e-02 eta: 17:22:14 time: 0.6470 data_time: 0.0861 memory: 24011 grad_norm: 4.5373 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5742 loss: 1.5742 2022/09/05 09:29:11 - mmengine - INFO - Epoch(train) [7][720/940] lr: 1.0000e-02 eta: 17:21:55 time: 0.6976 data_time: 0.1073 memory: 24011 grad_norm: 4.4791 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4162 loss: 1.4162 2022/09/05 09:29:23 - mmengine - INFO - Epoch(train) [7][740/940] lr: 1.0000e-02 eta: 17:21:10 time: 0.6009 data_time: 0.0323 memory: 24011 grad_norm: 4.2373 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.5664 loss: 1.5664 2022/09/05 09:29:37 - mmengine - INFO - Epoch(train) [7][760/940] lr: 1.0000e-02 eta: 17:20:47 time: 0.6823 data_time: 0.1157 memory: 24011 grad_norm: 4.4016 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4356 loss: 1.4356 2022/09/05 09:29:50 - mmengine - INFO - Epoch(train) [7][780/940] lr: 1.0000e-02 eta: 17:20:18 time: 0.6577 data_time: 0.0637 memory: 24011 grad_norm: 4.2424 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5027 loss: 1.5027 2022/09/05 09:30:02 - mmengine - INFO - Epoch(train) [7][800/940] lr: 1.0000e-02 eta: 17:19:39 time: 0.6231 data_time: 0.0549 memory: 24011 grad_norm: 4.1061 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4185 loss: 1.4185 2022/09/05 09:30:16 - mmengine - INFO - Epoch(train) [7][820/940] lr: 1.0000e-02 eta: 17:19:16 time: 0.6804 data_time: 0.1085 memory: 24011 grad_norm: 4.1590 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3966 loss: 1.3966 2022/09/05 09:30:29 - mmengine - INFO - Epoch(train) [7][840/940] lr: 1.0000e-02 eta: 17:18:49 time: 0.6643 data_time: 0.0949 memory: 24011 grad_norm: 4.2287 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4633 loss: 1.4633 2022/09/05 09:30:41 - mmengine - INFO - Epoch(train) [7][860/940] lr: 1.0000e-02 eta: 17:18:05 time: 0.5994 data_time: 0.0330 memory: 24011 grad_norm: 4.3356 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.3413 loss: 1.3413 2022/09/05 09:30:54 - mmengine - INFO - Epoch(train) [7][880/940] lr: 1.0000e-02 eta: 17:17:32 time: 0.6423 data_time: 0.0666 memory: 24011 grad_norm: 3.9897 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4112 loss: 1.4112 2022/09/05 09:31:07 - mmengine - INFO - Epoch(train) [7][900/940] lr: 1.0000e-02 eta: 17:17:03 time: 0.6574 data_time: 0.0795 memory: 24011 grad_norm: 4.0994 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5435 loss: 1.5435 2022/09/05 09:31:20 - mmengine - INFO - Epoch(train) [7][920/940] lr: 1.0000e-02 eta: 17:16:35 time: 0.6585 data_time: 0.0876 memory: 24011 grad_norm: 5.3565 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.4727 loss: 1.4727 2022/09/05 09:31:31 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:31:31 - mmengine - INFO - Epoch(train) [7][940/940] lr: 1.0000e-02 eta: 17:15:41 time: 0.5624 data_time: 0.0382 memory: 24011 grad_norm: 4.5413 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4465 loss: 1.4465 2022/09/05 09:31:45 - mmengine - INFO - Epoch(val) [7][20/78] eta: 0:00:40 time: 0.7023 data_time: 0.5430 memory: 3625 2022/09/05 09:31:55 - mmengine - INFO - Epoch(val) [7][40/78] eta: 0:00:17 time: 0.4610 data_time: 0.3042 memory: 3625 2022/09/05 09:32:08 - mmengine - INFO - Epoch(val) [7][60/78] eta: 0:00:11 time: 0.6455 data_time: 0.4866 memory: 3625 2022/09/05 09:32:18 - mmengine - INFO - Epoch(val) [7][78/78] acc/top1: 0.6946 acc/top5: 0.8936 acc/mean1: 0.6944 2022/09/05 09:32:36 - mmengine - INFO - Epoch(train) [8][20/940] lr: 1.0000e-02 eta: 17:16:20 time: 0.9116 data_time: 0.2666 memory: 24011 grad_norm: 4.5514 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5001 loss: 1.5001 2022/09/05 09:32:49 - mmengine - INFO - Epoch(train) [8][40/940] lr: 1.0000e-02 eta: 17:15:44 time: 0.6297 data_time: 0.0438 memory: 24011 grad_norm: 5.1310 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5374 loss: 1.5374 2022/09/05 09:33:02 - mmengine - INFO - Epoch(train) [8][60/940] lr: 1.0000e-02 eta: 17:15:22 time: 0.6826 data_time: 0.0397 memory: 24011 grad_norm: 4.1623 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3487 loss: 1.3487 2022/09/05 09:33:15 - mmengine - INFO - Epoch(train) [8][80/940] lr: 1.0000e-02 eta: 17:14:53 time: 0.6524 data_time: 0.0300 memory: 24011 grad_norm: 4.0208 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3873 loss: 1.3873 2022/09/05 09:33:28 - mmengine - INFO - Epoch(train) [8][100/940] lr: 1.0000e-02 eta: 17:14:18 time: 0.6330 data_time: 0.0535 memory: 24011 grad_norm: 4.6478 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4905 loss: 1.4905 2022/09/05 09:33:41 - mmengine - INFO - Epoch(train) [8][120/940] lr: 1.0000e-02 eta: 17:13:44 time: 0.6348 data_time: 0.0609 memory: 24011 grad_norm: 4.0091 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3545 loss: 1.3545 2022/09/05 09:33:54 - mmengine - INFO - Epoch(train) [8][140/940] lr: 1.0000e-02 eta: 17:13:21 time: 0.6774 data_time: 0.0367 memory: 24011 grad_norm: 3.9898 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5295 loss: 1.5295 2022/09/05 09:34:07 - mmengine - INFO - Epoch(train) [8][160/940] lr: 1.0000e-02 eta: 17:12:47 time: 0.6351 data_time: 0.0302 memory: 24011 grad_norm: 4.0091 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.4672 loss: 1.4672 2022/09/05 09:34:21 - mmengine - INFO - Epoch(train) [8][180/940] lr: 1.0000e-02 eta: 17:12:27 time: 0.6865 data_time: 0.0397 memory: 24011 grad_norm: 4.2063 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3914 loss: 1.3914 2022/09/05 09:34:33 - mmengine - INFO - Epoch(train) [8][200/940] lr: 1.0000e-02 eta: 17:11:52 time: 0.6282 data_time: 0.0310 memory: 24011 grad_norm: 4.0390 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3728 loss: 1.3728 2022/09/05 09:34:46 - mmengine - INFO - Epoch(train) [8][220/940] lr: 1.0000e-02 eta: 17:11:21 time: 0.6428 data_time: 0.0450 memory: 24011 grad_norm: 4.5642 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2249 loss: 1.2249 2022/09/05 09:34:59 - mmengine - INFO - Epoch(train) [8][240/940] lr: 1.0000e-02 eta: 17:10:43 time: 0.6186 data_time: 0.0384 memory: 24011 grad_norm: 4.3462 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4240 loss: 1.4240 2022/09/05 09:35:13 - mmengine - INFO - Epoch(train) [8][260/940] lr: 1.0000e-02 eta: 17:10:27 time: 0.7024 data_time: 0.0365 memory: 24011 grad_norm: 4.1419 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4261 loss: 1.4261 2022/09/05 09:35:25 - mmengine - INFO - Epoch(train) [8][280/940] lr: 1.0000e-02 eta: 17:09:51 time: 0.6227 data_time: 0.0442 memory: 24011 grad_norm: 5.1438 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4476 loss: 1.4476 2022/09/05 09:35:39 - mmengine - INFO - Epoch(train) [8][300/940] lr: 1.0000e-02 eta: 17:09:30 time: 0.6841 data_time: 0.0936 memory: 24011 grad_norm: 4.2430 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4020 loss: 1.4020 2022/09/05 09:35:51 - mmengine - INFO - Epoch(train) [8][320/940] lr: 1.0000e-02 eta: 17:08:55 time: 0.6251 data_time: 0.0539 memory: 24011 grad_norm: 5.6757 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5218 loss: 1.5218 2022/09/05 09:36:04 - mmengine - INFO - Epoch(train) [8][340/940] lr: 1.0000e-02 eta: 17:08:24 time: 0.6426 data_time: 0.0650 memory: 24011 grad_norm: 4.8324 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5038 loss: 1.5038 2022/09/05 09:36:17 - mmengine - INFO - Epoch(train) [8][360/940] lr: 1.0000e-02 eta: 17:07:50 time: 0.6309 data_time: 0.0652 memory: 24011 grad_norm: 4.5506 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5151 loss: 1.5151 2022/09/05 09:36:29 - mmengine - INFO - Epoch(train) [8][380/940] lr: 1.0000e-02 eta: 17:07:14 time: 0.6175 data_time: 0.0526 memory: 24011 grad_norm: 4.4310 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4795 loss: 1.4795 2022/09/05 09:36:43 - mmengine - INFO - Epoch(train) [8][400/940] lr: 1.0000e-02 eta: 17:06:52 time: 0.6798 data_time: 0.0384 memory: 24011 grad_norm: 5.6178 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4641 loss: 1.4641 2022/09/05 09:36:56 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:36:57 - mmengine - INFO - Epoch(train) [8][420/940] lr: 1.0000e-02 eta: 17:06:32 time: 0.6838 data_time: 0.0364 memory: 24011 grad_norm: 4.5065 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5570 loss: 1.5570 2022/09/05 09:37:09 - mmengine - INFO - Epoch(train) [8][440/940] lr: 1.0000e-02 eta: 17:05:58 time: 0.6255 data_time: 0.0472 memory: 24011 grad_norm: 4.2689 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3149 loss: 1.3149 2022/09/05 09:37:22 - mmengine - INFO - Epoch(train) [8][460/940] lr: 1.0000e-02 eta: 17:05:35 time: 0.6734 data_time: 0.0395 memory: 24011 grad_norm: 4.1609 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4673 loss: 1.4673 2022/09/05 09:37:35 - mmengine - INFO - Epoch(train) [8][480/940] lr: 1.0000e-02 eta: 17:05:05 time: 0.6442 data_time: 0.0341 memory: 24011 grad_norm: 4.5515 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4334 loss: 1.4334 2022/09/05 09:37:48 - mmengine - INFO - Epoch(train) [8][500/940] lr: 1.0000e-02 eta: 17:04:40 time: 0.6611 data_time: 0.0454 memory: 24011 grad_norm: 4.5975 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4598 loss: 1.4598 2022/09/05 09:38:01 - mmengine - INFO - Epoch(train) [8][520/940] lr: 1.0000e-02 eta: 17:04:09 time: 0.6396 data_time: 0.0536 memory: 24011 grad_norm: 4.4267 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2932 loss: 1.2932 2022/09/05 09:38:15 - mmengine - INFO - Epoch(train) [8][540/940] lr: 1.0000e-02 eta: 17:03:49 time: 0.6816 data_time: 0.0327 memory: 24011 grad_norm: 4.5273 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5633 loss: 1.5633 2022/09/05 09:38:28 - mmengine - INFO - Epoch(train) [8][560/940] lr: 1.0000e-02 eta: 17:03:22 time: 0.6553 data_time: 0.0343 memory: 24011 grad_norm: 4.2702 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4227 loss: 1.4227 2022/09/05 09:38:41 - mmengine - INFO - Epoch(train) [8][580/940] lr: 1.0000e-02 eta: 17:02:56 time: 0.6583 data_time: 0.0350 memory: 24011 grad_norm: 4.4744 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.4795 loss: 1.4795 2022/09/05 09:38:54 - mmengine - INFO - Epoch(train) [8][600/940] lr: 1.0000e-02 eta: 17:02:24 time: 0.6329 data_time: 0.0390 memory: 24011 grad_norm: 4.3914 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3893 loss: 1.3893 2022/09/05 09:39:07 - mmengine - INFO - Epoch(train) [8][620/940] lr: 1.0000e-02 eta: 17:01:59 time: 0.6609 data_time: 0.0347 memory: 24011 grad_norm: 4.2520 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4881 loss: 1.4881 2022/09/05 09:39:20 - mmengine - INFO - Epoch(train) [8][640/940] lr: 1.0000e-02 eta: 17:01:29 time: 0.6421 data_time: 0.0355 memory: 24011 grad_norm: 4.3514 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5000 loss: 1.5000 2022/09/05 09:39:32 - mmengine - INFO - Epoch(train) [8][660/940] lr: 1.0000e-02 eta: 17:00:56 time: 0.6277 data_time: 0.0381 memory: 24011 grad_norm: 4.4366 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5266 loss: 1.5266 2022/09/05 09:39:45 - mmengine - INFO - Epoch(train) [8][680/940] lr: 1.0000e-02 eta: 17:00:20 time: 0.6146 data_time: 0.0376 memory: 24011 grad_norm: 4.6047 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.4122 loss: 1.4122 2022/09/05 09:39:58 - mmengine - INFO - Epoch(train) [8][700/940] lr: 1.0000e-02 eta: 16:59:54 time: 0.6543 data_time: 0.0387 memory: 24011 grad_norm: 6.8973 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4451 loss: 1.4451 2022/09/05 09:40:11 - mmengine - INFO - Epoch(train) [8][720/940] lr: 1.0000e-02 eta: 16:59:28 time: 0.6582 data_time: 0.0389 memory: 24011 grad_norm: 5.8781 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6050 loss: 1.6050 2022/09/05 09:40:24 - mmengine - INFO - Epoch(train) [8][740/940] lr: 1.0000e-02 eta: 16:59:00 time: 0.6435 data_time: 0.0382 memory: 24011 grad_norm: 4.7137 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5918 loss: 1.5918 2022/09/05 09:40:37 - mmengine - INFO - Epoch(train) [8][760/940] lr: 1.0000e-02 eta: 16:58:29 time: 0.6359 data_time: 0.0318 memory: 24011 grad_norm: 4.5465 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.5498 loss: 1.5498 2022/09/05 09:40:50 - mmengine - INFO - Epoch(train) [8][780/940] lr: 1.0000e-02 eta: 16:58:07 time: 0.6700 data_time: 0.0365 memory: 24011 grad_norm: 4.6481 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.5323 loss: 1.5323 2022/09/05 09:41:03 - mmengine - INFO - Epoch(train) [8][800/940] lr: 1.0000e-02 eta: 16:57:38 time: 0.6435 data_time: 0.0463 memory: 24011 grad_norm: 4.2928 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3954 loss: 1.3954 2022/09/05 09:41:15 - mmengine - INFO - Epoch(train) [8][820/940] lr: 1.0000e-02 eta: 16:57:00 time: 0.6003 data_time: 0.0392 memory: 24011 grad_norm: 4.0961 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4748 loss: 1.4748 2022/09/05 09:41:28 - mmengine - INFO - Epoch(train) [8][840/940] lr: 1.0000e-02 eta: 16:56:38 time: 0.6738 data_time: 0.0427 memory: 24011 grad_norm: 4.6383 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4472 loss: 1.4472 2022/09/05 09:41:41 - mmengine - INFO - Epoch(train) [8][860/940] lr: 1.0000e-02 eta: 16:56:10 time: 0.6431 data_time: 0.0421 memory: 24011 grad_norm: 4.0060 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3588 loss: 1.3588 2022/09/05 09:41:54 - mmengine - INFO - Epoch(train) [8][880/940] lr: 1.0000e-02 eta: 16:55:36 time: 0.6195 data_time: 0.0396 memory: 24011 grad_norm: 4.1726 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4512 loss: 1.4512 2022/09/05 09:42:07 - mmengine - INFO - Epoch(train) [8][900/940] lr: 1.0000e-02 eta: 16:55:13 time: 0.6627 data_time: 0.0512 memory: 24011 grad_norm: 4.2744 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4212 loss: 1.4212 2022/09/05 09:42:20 - mmengine - INFO - Epoch(train) [8][920/940] lr: 1.0000e-02 eta: 16:54:50 time: 0.6656 data_time: 0.0352 memory: 24011 grad_norm: 4.5359 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3276 loss: 1.3276 2022/09/05 09:42:31 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:42:31 - mmengine - INFO - Epoch(train) [8][940/940] lr: 1.0000e-02 eta: 16:54:04 time: 0.5650 data_time: 0.0489 memory: 24011 grad_norm: 4.5620 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.4649 loss: 1.4649 2022/09/05 09:42:45 - mmengine - INFO - Epoch(val) [8][20/78] eta: 0:00:40 time: 0.6978 data_time: 0.5403 memory: 3625 2022/09/05 09:42:55 - mmengine - INFO - Epoch(val) [8][40/78] eta: 0:00:17 time: 0.4543 data_time: 0.2957 memory: 3625 2022/09/05 09:43:08 - mmengine - INFO - Epoch(val) [8][60/78] eta: 0:00:11 time: 0.6527 data_time: 0.4973 memory: 3625 2022/09/05 09:43:18 - mmengine - INFO - Epoch(val) [8][78/78] acc/top1: 0.7022 acc/top5: 0.8970 acc/mean1: 0.7019 2022/09/05 09:43:19 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_7.pth is removed 2022/09/05 09:43:22 - mmengine - INFO - The best checkpoint with 0.7022 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/09/05 09:43:39 - mmengine - INFO - Epoch(train) [9][20/940] lr: 1.0000e-02 eta: 16:54:25 time: 0.8569 data_time: 0.3088 memory: 24011 grad_norm: 4.6205 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4293 loss: 1.4293 2022/09/05 09:43:52 - mmengine - INFO - Epoch(train) [9][40/940] lr: 1.0000e-02 eta: 16:53:58 time: 0.6470 data_time: 0.1038 memory: 24011 grad_norm: 4.2525 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3568 loss: 1.3568 2022/09/05 09:44:04 - mmengine - INFO - Epoch(train) [9][60/940] lr: 1.0000e-02 eta: 16:53:28 time: 0.6363 data_time: 0.0785 memory: 24011 grad_norm: 4.0168 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3424 loss: 1.3424 2022/09/05 09:44:18 - mmengine - INFO - Epoch(train) [9][80/940] lr: 1.0000e-02 eta: 16:53:07 time: 0.6736 data_time: 0.1201 memory: 24011 grad_norm: 4.0417 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3592 loss: 1.3592 2022/09/05 09:44:31 - mmengine - INFO - Epoch(train) [9][100/940] lr: 1.0000e-02 eta: 16:52:41 time: 0.6485 data_time: 0.0837 memory: 24011 grad_norm: 4.2081 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3845 loss: 1.3845 2022/09/05 09:44:43 - mmengine - INFO - Epoch(train) [9][120/940] lr: 1.0000e-02 eta: 16:52:07 time: 0.6167 data_time: 0.0459 memory: 24011 grad_norm: 4.1356 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3654 loss: 1.3654 2022/09/05 09:44:56 - mmengine - INFO - Epoch(train) [9][140/940] lr: 1.0000e-02 eta: 16:51:40 time: 0.6468 data_time: 0.0742 memory: 24011 grad_norm: 4.0510 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3607 loss: 1.3607 2022/09/05 09:45:09 - mmengine - INFO - Epoch(train) [9][160/940] lr: 1.0000e-02 eta: 16:51:15 time: 0.6539 data_time: 0.0833 memory: 24011 grad_norm: 4.1339 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4873 loss: 1.4873 2022/09/05 09:45:23 - mmengine - INFO - Epoch(train) [9][180/940] lr: 1.0000e-02 eta: 16:50:57 time: 0.6834 data_time: 0.1153 memory: 24011 grad_norm: 4.0809 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3950 loss: 1.3950 2022/09/05 09:45:36 - mmengine - INFO - Epoch(train) [9][200/940] lr: 1.0000e-02 eta: 16:50:30 time: 0.6450 data_time: 0.0799 memory: 24011 grad_norm: 4.9518 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3980 loss: 1.3980 2022/09/05 09:45:48 - mmengine - INFO - Epoch(train) [9][220/940] lr: 1.0000e-02 eta: 16:49:56 time: 0.6157 data_time: 0.0612 memory: 24011 grad_norm: 4.2424 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3713 loss: 1.3713 2022/09/05 09:46:01 - mmengine - INFO - Epoch(train) [9][240/940] lr: 1.0000e-02 eta: 16:49:24 time: 0.6190 data_time: 0.0406 memory: 24011 grad_norm: 4.3372 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3443 loss: 1.3443 2022/09/05 09:46:14 - mmengine - INFO - Epoch(train) [9][260/940] lr: 1.0000e-02 eta: 16:49:04 time: 0.6788 data_time: 0.1108 memory: 24011 grad_norm: 5.5181 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4232 loss: 1.4232 2022/09/05 09:46:27 - mmengine - INFO - Epoch(train) [9][280/940] lr: 1.0000e-02 eta: 16:48:35 time: 0.6325 data_time: 0.0684 memory: 24011 grad_norm: 4.3299 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4110 loss: 1.4110 2022/09/05 09:46:41 - mmengine - INFO - Epoch(train) [9][300/940] lr: 1.0000e-02 eta: 16:48:19 time: 0.6920 data_time: 0.1252 memory: 24011 grad_norm: 4.8005 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2755 loss: 1.2755 2022/09/05 09:46:53 - mmengine - INFO - Epoch(train) [9][320/940] lr: 1.0000e-02 eta: 16:47:45 time: 0.6119 data_time: 0.0308 memory: 24011 grad_norm: 4.5026 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4597 loss: 1.4597 2022/09/05 09:47:06 - mmengine - INFO - Epoch(train) [9][340/940] lr: 1.0000e-02 eta: 16:47:17 time: 0.6378 data_time: 0.0616 memory: 24011 grad_norm: 4.2947 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4799 loss: 1.4799 2022/09/05 09:47:18 - mmengine - INFO - Epoch(train) [9][360/940] lr: 1.0000e-02 eta: 16:46:45 time: 0.6220 data_time: 0.0408 memory: 24011 grad_norm: 4.4297 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3937 loss: 1.3937 2022/09/05 09:47:31 - mmengine - INFO - Epoch(train) [9][380/940] lr: 1.0000e-02 eta: 16:46:17 time: 0.6354 data_time: 0.0552 memory: 24011 grad_norm: 4.6368 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3421 loss: 1.3421 2022/09/05 09:47:44 - mmengine - INFO - Epoch(train) [9][400/940] lr: 1.0000e-02 eta: 16:45:52 time: 0.6505 data_time: 0.0899 memory: 24011 grad_norm: 4.3680 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4760 loss: 1.4760 2022/09/05 09:47:57 - mmengine - INFO - Epoch(train) [9][420/940] lr: 1.0000e-02 eta: 16:45:24 time: 0.6399 data_time: 0.0767 memory: 24011 grad_norm: 4.3882 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4255 loss: 1.4255 2022/09/05 09:48:09 - mmengine - INFO - Epoch(train) [9][440/940] lr: 1.0000e-02 eta: 16:44:58 time: 0.6444 data_time: 0.0689 memory: 24011 grad_norm: 4.6202 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3204 loss: 1.3204 2022/09/05 09:48:22 - mmengine - INFO - Epoch(train) [9][460/940] lr: 1.0000e-02 eta: 16:44:32 time: 0.6422 data_time: 0.0587 memory: 24011 grad_norm: 4.0330 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.4261 loss: 1.4261 2022/09/05 09:48:36 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:48:36 - mmengine - INFO - Epoch(train) [9][480/940] lr: 1.0000e-02 eta: 16:44:10 time: 0.6646 data_time: 0.0612 memory: 24011 grad_norm: 4.8248 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3057 loss: 1.3057 2022/09/05 09:48:48 - mmengine - INFO - Epoch(train) [9][500/940] lr: 1.0000e-02 eta: 16:43:39 time: 0.6200 data_time: 0.0442 memory: 24011 grad_norm: 5.5423 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4029 loss: 1.4029 2022/09/05 09:49:02 - mmengine - INFO - Epoch(train) [9][520/940] lr: 1.0000e-02 eta: 16:43:26 time: 0.7080 data_time: 0.0400 memory: 24011 grad_norm: 4.1514 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4297 loss: 1.4297 2022/09/05 09:49:14 - mmengine - INFO - Epoch(train) [9][540/940] lr: 1.0000e-02 eta: 16:42:55 time: 0.6178 data_time: 0.0423 memory: 24011 grad_norm: 4.7786 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4333 loss: 1.4333 2022/09/05 09:49:27 - mmengine - INFO - Epoch(train) [9][560/940] lr: 1.0000e-02 eta: 16:42:28 time: 0.6405 data_time: 0.0354 memory: 24011 grad_norm: 4.1919 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4847 loss: 1.4847 2022/09/05 09:49:40 - mmengine - INFO - Epoch(train) [9][580/940] lr: 1.0000e-02 eta: 16:42:01 time: 0.6419 data_time: 0.0466 memory: 24011 grad_norm: 4.0920 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3720 loss: 1.3720 2022/09/05 09:49:53 - mmengine - INFO - Epoch(train) [9][600/940] lr: 1.0000e-02 eta: 16:41:31 time: 0.6217 data_time: 0.0427 memory: 24011 grad_norm: 4.4520 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4291 loss: 1.4291 2022/09/05 09:50:06 - mmengine - INFO - Epoch(train) [9][620/940] lr: 1.0000e-02 eta: 16:41:08 time: 0.6589 data_time: 0.0785 memory: 24011 grad_norm: 4.2474 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4310 loss: 1.4310 2022/09/05 09:50:18 - mmengine - INFO - Epoch(train) [9][640/940] lr: 1.0000e-02 eta: 16:40:39 time: 0.6259 data_time: 0.0488 memory: 24011 grad_norm: 4.1255 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3028 loss: 1.3028 2022/09/05 09:50:32 - mmengine - INFO - Epoch(train) [9][660/940] lr: 1.0000e-02 eta: 16:40:22 time: 0.6870 data_time: 0.1311 memory: 24011 grad_norm: 4.1690 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4847 loss: 1.4847 2022/09/05 09:50:44 - mmengine - INFO - Epoch(train) [9][680/940] lr: 1.0000e-02 eta: 16:39:51 time: 0.6190 data_time: 0.0511 memory: 24011 grad_norm: 3.8483 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3179 loss: 1.3179 2022/09/05 09:50:58 - mmengine - INFO - Epoch(train) [9][700/940] lr: 1.0000e-02 eta: 16:39:30 time: 0.6648 data_time: 0.0412 memory: 24011 grad_norm: 4.0332 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4773 loss: 1.4773 2022/09/05 09:51:10 - mmengine - INFO - Epoch(train) [9][720/940] lr: 1.0000e-02 eta: 16:38:57 time: 0.6060 data_time: 0.0312 memory: 24011 grad_norm: 4.1288 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4284 loss: 1.4284 2022/09/05 09:51:23 - mmengine - INFO - Epoch(train) [9][740/940] lr: 1.0000e-02 eta: 16:38:37 time: 0.6710 data_time: 0.0539 memory: 24011 grad_norm: 4.1314 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4565 loss: 1.4565 2022/09/05 09:51:36 - mmengine - INFO - Epoch(train) [9][760/940] lr: 1.0000e-02 eta: 16:38:07 time: 0.6228 data_time: 0.0569 memory: 24011 grad_norm: 3.9605 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2633 loss: 1.2633 2022/09/05 09:51:50 - mmengine - INFO - Epoch(train) [9][780/940] lr: 1.0000e-02 eta: 16:37:58 time: 0.7211 data_time: 0.1570 memory: 24011 grad_norm: 4.0811 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4448 loss: 1.4448 2022/09/05 09:52:02 - mmengine - INFO - Epoch(train) [9][800/940] lr: 1.0000e-02 eta: 16:37:26 time: 0.6094 data_time: 0.0376 memory: 24011 grad_norm: 4.6744 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4372 loss: 1.4372 2022/09/05 09:52:15 - mmengine - INFO - Epoch(train) [9][820/940] lr: 1.0000e-02 eta: 16:37:01 time: 0.6462 data_time: 0.0763 memory: 24011 grad_norm: 4.0953 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.4351 loss: 1.4351 2022/09/05 09:52:28 - mmengine - INFO - Epoch(train) [9][840/940] lr: 1.0000e-02 eta: 16:36:37 time: 0.6483 data_time: 0.0645 memory: 24011 grad_norm: 3.9750 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3330 loss: 1.3330 2022/09/05 09:52:41 - mmengine - INFO - Epoch(train) [9][860/940] lr: 1.0000e-02 eta: 16:36:09 time: 0.6300 data_time: 0.0381 memory: 24011 grad_norm: 4.0532 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.4970 loss: 1.4970 2022/09/05 09:52:54 - mmengine - INFO - Epoch(train) [9][880/940] lr: 1.0000e-02 eta: 16:35:44 time: 0.6424 data_time: 0.0380 memory: 24011 grad_norm: 3.8449 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4166 loss: 1.4166 2022/09/05 09:53:06 - mmengine - INFO - Epoch(train) [9][900/940] lr: 1.0000e-02 eta: 16:35:12 time: 0.6127 data_time: 0.0511 memory: 24011 grad_norm: 4.3405 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2071 loss: 1.2071 2022/09/05 09:53:20 - mmengine - INFO - Epoch(train) [9][920/940] lr: 1.0000e-02 eta: 16:34:56 time: 0.6843 data_time: 0.0360 memory: 24011 grad_norm: 4.0577 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4233 loss: 1.4233 2022/09/05 09:53:31 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 09:53:31 - mmengine - INFO - Epoch(train) [9][940/940] lr: 1.0000e-02 eta: 16:34:15 time: 0.5681 data_time: 0.0313 memory: 24011 grad_norm: 4.2385 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4125 loss: 1.4125 2022/09/05 09:53:31 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/09/05 09:53:50 - mmengine - INFO - Epoch(val) [9][20/78] eta: 0:00:41 time: 0.7147 data_time: 0.5581 memory: 3625 2022/09/05 09:53:59 - mmengine - INFO - Epoch(val) [9][40/78] eta: 0:00:17 time: 0.4500 data_time: 0.2954 memory: 3625 2022/09/05 09:54:12 - mmengine - INFO - Epoch(val) [9][60/78] eta: 0:00:11 time: 0.6414 data_time: 0.4847 memory: 3625 2022/09/05 09:54:21 - mmengine - INFO - Epoch(val) [9][78/78] acc/top1: 0.7062 acc/top5: 0.9004 acc/mean1: 0.7061 2022/09/05 09:54:21 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_9.pth is removed 2022/09/05 09:54:24 - mmengine - INFO - The best checkpoint with 0.7062 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2022/09/05 09:54:40 - mmengine - INFO - Epoch(train) [10][20/940] lr: 1.0000e-02 eta: 16:34:27 time: 0.8233 data_time: 0.2724 memory: 24011 grad_norm: 4.0246 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3215 loss: 1.3215 2022/09/05 09:54:53 - mmengine - INFO - Epoch(train) [10][40/940] lr: 1.0000e-02 eta: 16:33:57 time: 0.6176 data_time: 0.0775 memory: 24011 grad_norm: 4.0270 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3120 loss: 1.3120 2022/09/05 09:55:06 - mmengine - INFO - Epoch(train) [10][60/940] lr: 1.0000e-02 eta: 16:33:38 time: 0.6741 data_time: 0.1219 memory: 24011 grad_norm: 4.1143 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3406 loss: 1.3406 2022/09/05 09:55:19 - mmengine - INFO - Epoch(train) [10][80/940] lr: 1.0000e-02 eta: 16:33:09 time: 0.6237 data_time: 0.0749 memory: 24011 grad_norm: 4.1629 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1574 loss: 1.1574 2022/09/05 09:55:32 - mmengine - INFO - Epoch(train) [10][100/940] lr: 1.0000e-02 eta: 16:32:46 time: 0.6474 data_time: 0.1031 memory: 24011 grad_norm: 4.2074 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3681 loss: 1.3681 2022/09/05 09:55:44 - mmengine - INFO - Epoch(train) [10][120/940] lr: 1.0000e-02 eta: 16:32:19 time: 0.6347 data_time: 0.0740 memory: 24011 grad_norm: 3.9652 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4516 loss: 1.4516 2022/09/05 09:55:57 - mmengine - INFO - Epoch(train) [10][140/940] lr: 1.0000e-02 eta: 16:31:57 time: 0.6565 data_time: 0.0984 memory: 24011 grad_norm: 4.1561 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5442 loss: 1.5442 2022/09/05 09:56:10 - mmengine - INFO - Epoch(train) [10][160/940] lr: 1.0000e-02 eta: 16:31:32 time: 0.6418 data_time: 0.0342 memory: 24011 grad_norm: 3.9560 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3269 loss: 1.3269 2022/09/05 09:56:23 - mmengine - INFO - Epoch(train) [10][180/940] lr: 1.0000e-02 eta: 16:31:10 time: 0.6536 data_time: 0.0706 memory: 24011 grad_norm: 4.1385 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3660 loss: 1.3660 2022/09/05 09:56:36 - mmengine - INFO - Epoch(train) [10][200/940] lr: 1.0000e-02 eta: 16:30:40 time: 0.6173 data_time: 0.0341 memory: 24011 grad_norm: 4.1365 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4091 loss: 1.4091 2022/09/05 09:56:49 - mmengine - INFO - Epoch(train) [10][220/940] lr: 1.0000e-02 eta: 16:30:22 time: 0.6727 data_time: 0.1113 memory: 24011 grad_norm: 3.7515 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3717 loss: 1.3717 2022/09/05 09:57:02 - mmengine - INFO - Epoch(train) [10][240/940] lr: 1.0000e-02 eta: 16:29:56 time: 0.6390 data_time: 0.0841 memory: 24011 grad_norm: 4.0523 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4063 loss: 1.4063 2022/09/05 09:57:15 - mmengine - INFO - Epoch(train) [10][260/940] lr: 1.0000e-02 eta: 16:29:38 time: 0.6731 data_time: 0.0603 memory: 24011 grad_norm: 4.1077 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4201 loss: 1.4201 2022/09/05 09:57:28 - mmengine - INFO - Epoch(train) [10][280/940] lr: 1.0000e-02 eta: 16:29:11 time: 0.6274 data_time: 0.0320 memory: 24011 grad_norm: 4.3987 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3423 loss: 1.3423 2022/09/05 09:57:41 - mmengine - INFO - Epoch(train) [10][300/940] lr: 1.0000e-02 eta: 16:28:45 time: 0.6334 data_time: 0.0405 memory: 24011 grad_norm: 4.6822 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2373 loss: 1.2373 2022/09/05 09:57:53 - mmengine - INFO - Epoch(train) [10][320/940] lr: 1.0000e-02 eta: 16:28:18 time: 0.6324 data_time: 0.0616 memory: 24011 grad_norm: 4.4768 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4806 loss: 1.4806 2022/09/05 09:58:06 - mmengine - INFO - Epoch(train) [10][340/940] lr: 1.0000e-02 eta: 16:27:54 time: 0.6433 data_time: 0.0819 memory: 24011 grad_norm: 4.5466 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4364 loss: 1.4364 2022/09/05 09:58:19 - mmengine - INFO - Epoch(train) [10][360/940] lr: 1.0000e-02 eta: 16:27:29 time: 0.6354 data_time: 0.0643 memory: 24011 grad_norm: 4.0934 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3586 loss: 1.3586 2022/09/05 09:58:32 - mmengine - INFO - Epoch(train) [10][380/940] lr: 1.0000e-02 eta: 16:27:11 time: 0.6770 data_time: 0.0980 memory: 24011 grad_norm: 5.1403 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4675 loss: 1.4675 2022/09/05 09:58:45 - mmengine - INFO - Epoch(train) [10][400/940] lr: 1.0000e-02 eta: 16:26:49 time: 0.6532 data_time: 0.0554 memory: 24011 grad_norm: 4.3763 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2872 loss: 1.2872 2022/09/05 09:58:59 - mmengine - INFO - Epoch(train) [10][420/940] lr: 1.0000e-02 eta: 16:26:27 time: 0.6528 data_time: 0.0798 memory: 24011 grad_norm: 4.3170 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4731 loss: 1.4731 2022/09/05 09:59:11 - mmengine - INFO - Epoch(train) [10][440/940] lr: 1.0000e-02 eta: 16:26:02 time: 0.6360 data_time: 0.0480 memory: 24011 grad_norm: 4.1020 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2556 loss: 1.2556 2022/09/05 09:59:24 - mmengine - INFO - Epoch(train) [10][460/940] lr: 1.0000e-02 eta: 16:25:38 time: 0.6446 data_time: 0.0829 memory: 24011 grad_norm: 4.3459 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3252 loss: 1.3252 2022/09/05 09:59:37 - mmengine - INFO - Epoch(train) [10][480/940] lr: 1.0000e-02 eta: 16:25:15 time: 0.6438 data_time: 0.0664 memory: 24011 grad_norm: 4.8390 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4390 loss: 1.4390 2022/09/05 09:59:50 - mmengine - INFO - Epoch(train) [10][500/940] lr: 1.0000e-02 eta: 16:24:54 time: 0.6600 data_time: 0.0748 memory: 24011 grad_norm: 4.2515 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4473 loss: 1.4473 2022/09/05 10:00:03 - mmengine - INFO - Epoch(train) [10][520/940] lr: 1.0000e-02 eta: 16:24:27 time: 0.6259 data_time: 0.0456 memory: 24011 grad_norm: 4.2772 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.3738 loss: 1.3738 2022/09/05 10:00:16 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:00:16 - mmengine - INFO - Epoch(train) [10][540/940] lr: 1.0000e-02 eta: 16:24:03 time: 0.6432 data_time: 0.0992 memory: 24011 grad_norm: 3.9984 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2683 loss: 1.2683 2022/09/05 10:00:28 - mmengine - INFO - Epoch(train) [10][560/940] lr: 1.0000e-02 eta: 16:23:38 time: 0.6322 data_time: 0.0695 memory: 24011 grad_norm: 4.3492 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4355 loss: 1.4355 2022/09/05 10:00:41 - mmengine - INFO - Epoch(train) [10][580/940] lr: 1.0000e-02 eta: 16:23:18 time: 0.6620 data_time: 0.1069 memory: 24011 grad_norm: 3.9539 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4131 loss: 1.4131 2022/09/05 10:00:54 - mmengine - INFO - Epoch(train) [10][600/940] lr: 1.0000e-02 eta: 16:22:50 time: 0.6231 data_time: 0.0433 memory: 24011 grad_norm: 4.1822 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3317 loss: 1.3317 2022/09/05 10:01:07 - mmengine - INFO - Epoch(train) [10][620/940] lr: 1.0000e-02 eta: 16:22:27 time: 0.6451 data_time: 0.0451 memory: 24011 grad_norm: 4.1074 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3547 loss: 1.3547 2022/09/05 10:01:20 - mmengine - INFO - Epoch(train) [10][640/940] lr: 1.0000e-02 eta: 16:22:09 time: 0.6703 data_time: 0.0328 memory: 24011 grad_norm: 4.2199 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4491 loss: 1.4491 2022/09/05 10:01:33 - mmengine - INFO - Epoch(train) [10][660/940] lr: 1.0000e-02 eta: 16:21:45 time: 0.6402 data_time: 0.0449 memory: 24011 grad_norm: 4.1054 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4466 loss: 1.4466 2022/09/05 10:01:46 - mmengine - INFO - Epoch(train) [10][680/940] lr: 1.0000e-02 eta: 16:21:21 time: 0.6412 data_time: 0.0342 memory: 24011 grad_norm: 3.9977 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4738 loss: 1.4738 2022/09/05 10:01:59 - mmengine - INFO - Epoch(train) [10][700/940] lr: 1.0000e-02 eta: 16:20:57 time: 0.6386 data_time: 0.0401 memory: 24011 grad_norm: 4.0514 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4409 loss: 1.4409 2022/09/05 10:02:12 - mmengine - INFO - Epoch(train) [10][720/940] lr: 1.0000e-02 eta: 16:20:40 time: 0.6730 data_time: 0.0326 memory: 24011 grad_norm: 4.0412 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2555 loss: 1.2555 2022/09/05 10:02:24 - mmengine - INFO - Epoch(train) [10][740/940] lr: 1.0000e-02 eta: 16:20:09 time: 0.6053 data_time: 0.0558 memory: 24011 grad_norm: 4.2875 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3381 loss: 1.3381 2022/09/05 10:02:37 - mmengine - INFO - Epoch(train) [10][760/940] lr: 1.0000e-02 eta: 16:19:50 time: 0.6627 data_time: 0.0379 memory: 24011 grad_norm: 4.7068 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3271 loss: 1.3271 2022/09/05 10:02:50 - mmengine - INFO - Epoch(train) [10][780/940] lr: 1.0000e-02 eta: 16:19:21 time: 0.6124 data_time: 0.0409 memory: 24011 grad_norm: 4.1355 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3564 loss: 1.3564 2022/09/05 10:03:03 - mmengine - INFO - Epoch(train) [10][800/940] lr: 1.0000e-02 eta: 16:19:02 time: 0.6623 data_time: 0.0462 memory: 24011 grad_norm: 3.9726 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3556 loss: 1.3556 2022/09/05 10:03:16 - mmengine - INFO - Epoch(train) [10][820/940] lr: 1.0000e-02 eta: 16:18:41 time: 0.6538 data_time: 0.0371 memory: 24011 grad_norm: 3.9650 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.3647 loss: 1.3647 2022/09/05 10:03:29 - mmengine - INFO - Epoch(train) [10][840/940] lr: 1.0000e-02 eta: 16:18:18 time: 0.6468 data_time: 0.0451 memory: 24011 grad_norm: 4.0943 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3811 loss: 1.3811 2022/09/05 10:03:43 - mmengine - INFO - Epoch(train) [10][860/940] lr: 1.0000e-02 eta: 16:18:08 time: 0.7153 data_time: 0.0373 memory: 24011 grad_norm: 3.9520 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2796 loss: 1.2796 2022/09/05 10:03:56 - mmengine - INFO - Epoch(train) [10][880/940] lr: 1.0000e-02 eta: 16:17:41 time: 0.6179 data_time: 0.0377 memory: 24011 grad_norm: 4.0159 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.3131 loss: 1.3131 2022/09/05 10:04:09 - mmengine - INFO - Epoch(train) [10][900/940] lr: 1.0000e-02 eta: 16:17:21 time: 0.6578 data_time: 0.0398 memory: 24011 grad_norm: 4.1469 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3179 loss: 1.3179 2022/09/05 10:04:22 - mmengine - INFO - Epoch(train) [10][920/940] lr: 1.0000e-02 eta: 16:17:03 time: 0.6704 data_time: 0.0370 memory: 24011 grad_norm: 3.9201 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3144 loss: 1.3144 2022/09/05 10:04:33 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:04:33 - mmengine - INFO - Epoch(train) [10][940/940] lr: 1.0000e-02 eta: 16:16:21 time: 0.5345 data_time: 0.0274 memory: 24011 grad_norm: 4.1191 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.1805 loss: 1.1805 2022/09/05 10:04:47 - mmengine - INFO - Epoch(val) [10][20/78] eta: 0:00:40 time: 0.6972 data_time: 0.5390 memory: 3625 2022/09/05 10:04:56 - mmengine - INFO - Epoch(val) [10][40/78] eta: 0:00:17 time: 0.4539 data_time: 0.2982 memory: 3625 2022/09/05 10:05:09 - mmengine - INFO - Epoch(val) [10][60/78] eta: 0:00:12 time: 0.6667 data_time: 0.5080 memory: 3625 2022/09/05 10:05:19 - mmengine - INFO - Epoch(val) [10][78/78] acc/top1: 0.7096 acc/top5: 0.8991 acc/mean1: 0.7095 2022/09/05 10:05:19 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_10.pth is removed 2022/09/05 10:05:23 - mmengine - INFO - The best checkpoint with 0.7096 acc/top1 at 11 epoch is saved to best_acc/top1_epoch_11.pth. 2022/09/05 10:05:40 - mmengine - INFO - Epoch(train) [11][20/940] lr: 1.0000e-02 eta: 16:16:37 time: 0.8598 data_time: 0.3238 memory: 24011 grad_norm: 3.7531 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2925 loss: 1.2925 2022/09/05 10:05:52 - mmengine - INFO - Epoch(train) [11][40/940] lr: 1.0000e-02 eta: 16:16:10 time: 0.6227 data_time: 0.0718 memory: 24011 grad_norm: 3.9027 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2929 loss: 1.2929 2022/09/05 10:06:05 - mmengine - INFO - Epoch(train) [11][60/940] lr: 1.0000e-02 eta: 16:15:51 time: 0.6644 data_time: 0.1138 memory: 24011 grad_norm: 4.0762 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3795 loss: 1.3795 2022/09/05 10:06:18 - mmengine - INFO - Epoch(train) [11][80/940] lr: 1.0000e-02 eta: 16:15:30 time: 0.6504 data_time: 0.0948 memory: 24011 grad_norm: 3.8463 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3550 loss: 1.3550 2022/09/05 10:06:31 - mmengine - INFO - Epoch(train) [11][100/940] lr: 1.0000e-02 eta: 16:15:09 time: 0.6495 data_time: 0.0711 memory: 24011 grad_norm: 4.0333 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2837 loss: 1.2837 2022/09/05 10:06:43 - mmengine - INFO - Epoch(train) [11][120/940] lr: 1.0000e-02 eta: 16:14:37 time: 0.5923 data_time: 0.0417 memory: 24011 grad_norm: 4.1545 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4022 loss: 1.4022 2022/09/05 10:06:57 - mmengine - INFO - Epoch(train) [11][140/940] lr: 1.0000e-02 eta: 16:14:18 time: 0.6663 data_time: 0.0934 memory: 24011 grad_norm: 4.0619 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.0901 loss: 1.0901 2022/09/05 10:07:09 - mmengine - INFO - Epoch(train) [11][160/940] lr: 1.0000e-02 eta: 16:13:55 time: 0.6397 data_time: 0.0847 memory: 24011 grad_norm: 3.8756 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3142 loss: 1.3142 2022/09/05 10:07:22 - mmengine - INFO - Epoch(train) [11][180/940] lr: 1.0000e-02 eta: 16:13:28 time: 0.6174 data_time: 0.0561 memory: 24011 grad_norm: 3.7873 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3344 loss: 1.3344 2022/09/05 10:07:35 - mmengine - INFO - Epoch(train) [11][200/940] lr: 1.0000e-02 eta: 16:13:06 time: 0.6421 data_time: 0.0615 memory: 24011 grad_norm: 3.8047 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3392 loss: 1.3392 2022/09/05 10:07:47 - mmengine - INFO - Epoch(train) [11][220/940] lr: 1.0000e-02 eta: 16:12:39 time: 0.6167 data_time: 0.0580 memory: 24011 grad_norm: 3.8568 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2560 loss: 1.2560 2022/09/05 10:08:01 - mmengine - INFO - Epoch(train) [11][240/940] lr: 1.0000e-02 eta: 16:12:26 time: 0.6985 data_time: 0.0727 memory: 24011 grad_norm: 3.7237 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2918 loss: 1.2918 2022/09/05 10:08:13 - mmengine - INFO - Epoch(train) [11][260/940] lr: 1.0000e-02 eta: 16:12:01 time: 0.6267 data_time: 0.0383 memory: 24011 grad_norm: 3.9210 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2852 loss: 1.2852 2022/09/05 10:08:26 - mmengine - INFO - Epoch(train) [11][280/940] lr: 1.0000e-02 eta: 16:11:38 time: 0.6364 data_time: 0.0540 memory: 24011 grad_norm: 4.1064 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3824 loss: 1.3824 2022/09/05 10:08:40 - mmengine - INFO - Epoch(train) [11][300/940] lr: 1.0000e-02 eta: 16:11:26 time: 0.7053 data_time: 0.0653 memory: 24011 grad_norm: 3.9106 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2684 loss: 1.2684 2022/09/05 10:08:53 - mmengine - INFO - Epoch(train) [11][320/940] lr: 1.0000e-02 eta: 16:11:02 time: 0.6315 data_time: 0.0413 memory: 24011 grad_norm: 4.8488 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3397 loss: 1.3397 2022/09/05 10:09:06 - mmengine - INFO - Epoch(train) [11][340/940] lr: 1.0000e-02 eta: 16:10:37 time: 0.6270 data_time: 0.0551 memory: 24011 grad_norm: 5.2128 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2959 loss: 1.2959 2022/09/05 10:09:18 - mmengine - INFO - Epoch(train) [11][360/940] lr: 1.0000e-02 eta: 16:10:14 time: 0.6396 data_time: 0.0552 memory: 24011 grad_norm: 4.3327 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3525 loss: 1.3525 2022/09/05 10:09:32 - mmengine - INFO - Epoch(train) [11][380/940] lr: 1.0000e-02 eta: 16:09:59 time: 0.6827 data_time: 0.0410 memory: 24011 grad_norm: 3.9600 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2249 loss: 1.2249 2022/09/05 10:09:45 - mmengine - INFO - Epoch(train) [11][400/940] lr: 1.0000e-02 eta: 16:09:39 time: 0.6568 data_time: 0.0358 memory: 24011 grad_norm: 4.2883 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5250 loss: 1.5250 2022/09/05 10:09:57 - mmengine - INFO - Epoch(train) [11][420/940] lr: 1.0000e-02 eta: 16:09:13 time: 0.6186 data_time: 0.0363 memory: 24011 grad_norm: 3.9001 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2293 loss: 1.2293 2022/09/05 10:10:10 - mmengine - INFO - Epoch(train) [11][440/940] lr: 1.0000e-02 eta: 16:08:49 time: 0.6286 data_time: 0.0398 memory: 24011 grad_norm: 4.6219 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2612 loss: 1.2612 2022/09/05 10:10:23 - mmengine - INFO - Epoch(train) [11][460/940] lr: 1.0000e-02 eta: 16:08:31 time: 0.6668 data_time: 0.0347 memory: 24011 grad_norm: 4.1084 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2965 loss: 1.2965 2022/09/05 10:10:36 - mmengine - INFO - Epoch(train) [11][480/940] lr: 1.0000e-02 eta: 16:08:10 time: 0.6485 data_time: 0.0389 memory: 24011 grad_norm: 4.3700 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3809 loss: 1.3809 2022/09/05 10:10:50 - mmengine - INFO - Epoch(train) [11][500/940] lr: 1.0000e-02 eta: 16:07:53 time: 0.6751 data_time: 0.0395 memory: 24011 grad_norm: 4.0437 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3545 loss: 1.3545 2022/09/05 10:11:03 - mmengine - INFO - Epoch(train) [11][520/940] lr: 1.0000e-02 eta: 16:07:33 time: 0.6537 data_time: 0.0473 memory: 24011 grad_norm: 3.8382 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2792 loss: 1.2792 2022/09/05 10:11:16 - mmengine - INFO - Epoch(train) [11][540/940] lr: 1.0000e-02 eta: 16:07:15 time: 0.6614 data_time: 0.0368 memory: 24011 grad_norm: 3.7663 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2444 loss: 1.2444 2022/09/05 10:11:29 - mmengine - INFO - Epoch(train) [11][560/940] lr: 1.0000e-02 eta: 16:06:51 time: 0.6336 data_time: 0.0368 memory: 24011 grad_norm: 3.8955 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3154 loss: 1.3154 2022/09/05 10:11:42 - mmengine - INFO - Epoch(train) [11][580/940] lr: 1.0000e-02 eta: 16:06:33 time: 0.6672 data_time: 0.0390 memory: 24011 grad_norm: 4.2904 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4138 loss: 1.4138 2022/09/05 10:11:55 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:11:55 - mmengine - INFO - Epoch(train) [11][600/940] lr: 1.0000e-02 eta: 16:06:10 time: 0.6345 data_time: 0.0337 memory: 24011 grad_norm: 4.0880 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3277 loss: 1.3277 2022/09/05 10:12:08 - mmengine - INFO - Epoch(train) [11][620/940] lr: 1.0000e-02 eta: 16:05:54 time: 0.6780 data_time: 0.0364 memory: 24011 grad_norm: 4.1560 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3734 loss: 1.3734 2022/09/05 10:12:21 - mmengine - INFO - Epoch(train) [11][640/940] lr: 1.0000e-02 eta: 16:05:26 time: 0.6050 data_time: 0.0387 memory: 24011 grad_norm: 4.1075 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4516 loss: 1.4516 2022/09/05 10:12:34 - mmengine - INFO - Epoch(train) [11][660/940] lr: 1.0000e-02 eta: 16:05:07 time: 0.6562 data_time: 0.0363 memory: 24011 grad_norm: 3.9810 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3921 loss: 1.3921 2022/09/05 10:12:46 - mmengine - INFO - Epoch(train) [11][680/940] lr: 1.0000e-02 eta: 16:04:38 time: 0.6009 data_time: 0.0367 memory: 24011 grad_norm: 4.6704 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3804 loss: 1.3804 2022/09/05 10:13:00 - mmengine - INFO - Epoch(train) [11][700/940] lr: 1.0000e-02 eta: 16:04:26 time: 0.6980 data_time: 0.0375 memory: 24011 grad_norm: 4.1568 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2969 loss: 1.2969 2022/09/05 10:13:12 - mmengine - INFO - Epoch(train) [11][720/940] lr: 1.0000e-02 eta: 16:04:03 time: 0.6317 data_time: 0.0360 memory: 24011 grad_norm: 4.1412 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.3617 loss: 1.3617 2022/09/05 10:13:25 - mmengine - INFO - Epoch(train) [11][740/940] lr: 1.0000e-02 eta: 16:03:44 time: 0.6610 data_time: 0.0627 memory: 24011 grad_norm: 3.9636 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2878 loss: 1.2878 2022/09/05 10:13:38 - mmengine - INFO - Epoch(train) [11][760/940] lr: 1.0000e-02 eta: 16:03:23 time: 0.6432 data_time: 0.0363 memory: 24011 grad_norm: 4.0669 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2214 loss: 1.2214 2022/09/05 10:13:50 - mmengine - INFO - Epoch(train) [11][780/940] lr: 1.0000e-02 eta: 16:02:55 time: 0.6036 data_time: 0.0422 memory: 24011 grad_norm: 5.0017 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3581 loss: 1.3581 2022/09/05 10:14:03 - mmengine - INFO - Epoch(train) [11][800/940] lr: 1.0000e-02 eta: 16:02:29 time: 0.6148 data_time: 0.0413 memory: 24011 grad_norm: 4.3851 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3755 loss: 1.3755 2022/09/05 10:14:16 - mmengine - INFO - Epoch(train) [11][820/940] lr: 1.0000e-02 eta: 16:02:12 time: 0.6746 data_time: 0.0434 memory: 24011 grad_norm: 4.3220 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.3382 loss: 1.3382 2022/09/05 10:14:29 - mmengine - INFO - Epoch(train) [11][840/940] lr: 1.0000e-02 eta: 16:01:53 time: 0.6553 data_time: 0.0388 memory: 24011 grad_norm: 4.2570 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3788 loss: 1.3788 2022/09/05 10:14:42 - mmengine - INFO - Epoch(train) [11][860/940] lr: 1.0000e-02 eta: 16:01:32 time: 0.6468 data_time: 0.0411 memory: 24011 grad_norm: 4.6944 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3645 loss: 1.3645 2022/09/05 10:14:55 - mmengine - INFO - Epoch(train) [11][880/940] lr: 1.0000e-02 eta: 16:01:12 time: 0.6484 data_time: 0.0444 memory: 24011 grad_norm: 4.2050 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3260 loss: 1.3260 2022/09/05 10:15:09 - mmengine - INFO - Epoch(train) [11][900/940] lr: 1.0000e-02 eta: 16:01:00 time: 0.6985 data_time: 0.0451 memory: 24011 grad_norm: 4.0530 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3816 loss: 1.3816 2022/09/05 10:15:22 - mmengine - INFO - Epoch(train) [11][920/940] lr: 1.0000e-02 eta: 16:00:37 time: 0.6345 data_time: 0.0491 memory: 24011 grad_norm: 3.9101 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3661 loss: 1.3661 2022/09/05 10:15:33 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:15:33 - mmengine - INFO - Epoch(train) [11][940/940] lr: 1.0000e-02 eta: 16:00:02 time: 0.5587 data_time: 0.0330 memory: 24011 grad_norm: 4.2270 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1503 loss: 1.1503 2022/09/05 10:15:47 - mmengine - INFO - Epoch(val) [11][20/78] eta: 0:00:39 time: 0.6863 data_time: 0.5232 memory: 3625 2022/09/05 10:15:56 - mmengine - INFO - Epoch(val) [11][40/78] eta: 0:00:18 time: 0.4763 data_time: 0.3183 memory: 3625 2022/09/05 10:16:09 - mmengine - INFO - Epoch(val) [11][60/78] eta: 0:00:11 time: 0.6483 data_time: 0.4890 memory: 3625 2022/09/05 10:16:20 - mmengine - INFO - Epoch(val) [11][78/78] acc/top1: 0.7125 acc/top5: 0.9007 acc/mean1: 0.7123 2022/09/05 10:16:20 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_11.pth is removed 2022/09/05 10:16:23 - mmengine - INFO - The best checkpoint with 0.7125 acc/top1 at 12 epoch is saved to best_acc/top1_epoch_12.pth. 2022/09/05 10:16:40 - mmengine - INFO - Epoch(train) [12][20/940] lr: 1.0000e-02 eta: 16:00:16 time: 0.8549 data_time: 0.3079 memory: 24011 grad_norm: 3.8654 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3914 loss: 1.3914 2022/09/05 10:16:53 - mmengine - INFO - Epoch(train) [12][40/940] lr: 1.0000e-02 eta: 15:59:51 time: 0.6225 data_time: 0.0667 memory: 24011 grad_norm: 4.9164 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2091 loss: 1.2091 2022/09/05 10:17:06 - mmengine - INFO - Epoch(train) [12][60/940] lr: 1.0000e-02 eta: 15:59:32 time: 0.6527 data_time: 0.1003 memory: 24011 grad_norm: 4.0272 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3920 loss: 1.3920 2022/09/05 10:17:19 - mmengine - INFO - Epoch(train) [12][80/940] lr: 1.0000e-02 eta: 15:59:09 time: 0.6367 data_time: 0.0706 memory: 24011 grad_norm: 4.1129 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2894 loss: 1.2894 2022/09/05 10:17:32 - mmengine - INFO - Epoch(train) [12][100/940] lr: 1.0000e-02 eta: 15:58:50 time: 0.6520 data_time: 0.0754 memory: 24011 grad_norm: 3.8469 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2517 loss: 1.2517 2022/09/05 10:17:44 - mmengine - INFO - Epoch(train) [12][120/940] lr: 1.0000e-02 eta: 15:58:25 time: 0.6224 data_time: 0.0467 memory: 24011 grad_norm: 3.9653 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2202 loss: 1.2202 2022/09/05 10:17:57 - mmengine - INFO - Epoch(train) [12][140/940] lr: 1.0000e-02 eta: 15:58:02 time: 0.6299 data_time: 0.0442 memory: 24011 grad_norm: 3.8249 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2126 loss: 1.2126 2022/09/05 10:18:09 - mmengine - INFO - Epoch(train) [12][160/940] lr: 1.0000e-02 eta: 15:57:40 time: 0.6358 data_time: 0.0353 memory: 24011 grad_norm: 3.7942 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4152 loss: 1.4152 2022/09/05 10:18:22 - mmengine - INFO - Epoch(train) [12][180/940] lr: 1.0000e-02 eta: 15:57:20 time: 0.6503 data_time: 0.0705 memory: 24011 grad_norm: 4.0028 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2647 loss: 1.2647 2022/09/05 10:18:35 - mmengine - INFO - Epoch(train) [12][200/940] lr: 1.0000e-02 eta: 15:56:57 time: 0.6249 data_time: 0.0509 memory: 24011 grad_norm: 3.9204 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.2254 loss: 1.2254 2022/09/05 10:18:48 - mmengine - INFO - Epoch(train) [12][220/940] lr: 1.0000e-02 eta: 15:56:36 time: 0.6462 data_time: 0.0659 memory: 24011 grad_norm: 4.1169 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1204 loss: 1.1204 2022/09/05 10:19:01 - mmengine - INFO - Epoch(train) [12][240/940] lr: 1.0000e-02 eta: 15:56:15 time: 0.6394 data_time: 0.0455 memory: 24011 grad_norm: 3.9110 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1692 loss: 1.1692 2022/09/05 10:19:15 - mmengine - INFO - Epoch(train) [12][260/940] lr: 1.0000e-02 eta: 15:56:02 time: 0.6940 data_time: 0.0422 memory: 24011 grad_norm: 4.2150 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2995 loss: 1.2995 2022/09/05 10:19:27 - mmengine - INFO - Epoch(train) [12][280/940] lr: 1.0000e-02 eta: 15:55:39 time: 0.6262 data_time: 0.0384 memory: 24011 grad_norm: 4.0920 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1074 loss: 1.1074 2022/09/05 10:19:40 - mmengine - INFO - Epoch(train) [12][300/940] lr: 1.0000e-02 eta: 15:55:15 time: 0.6232 data_time: 0.0421 memory: 24011 grad_norm: 4.3464 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3209 loss: 1.3209 2022/09/05 10:19:53 - mmengine - INFO - Epoch(train) [12][320/940] lr: 1.0000e-02 eta: 15:54:56 time: 0.6537 data_time: 0.0816 memory: 24011 grad_norm: 4.5569 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3674 loss: 1.3674 2022/09/05 10:20:06 - mmengine - INFO - Epoch(train) [12][340/940] lr: 1.0000e-02 eta: 15:54:40 time: 0.6741 data_time: 0.1257 memory: 24011 grad_norm: 4.1535 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3528 loss: 1.3528 2022/09/05 10:20:18 - mmengine - INFO - Epoch(train) [12][360/940] lr: 1.0000e-02 eta: 15:54:11 time: 0.5882 data_time: 0.0360 memory: 24011 grad_norm: 4.0656 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2343 loss: 1.2343 2022/09/05 10:20:32 - mmengine - INFO - Epoch(train) [12][380/940] lr: 1.0000e-02 eta: 15:53:58 time: 0.6921 data_time: 0.0591 memory: 24011 grad_norm: 4.2331 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3768 loss: 1.3768 2022/09/05 10:20:44 - mmengine - INFO - Epoch(train) [12][400/940] lr: 1.0000e-02 eta: 15:53:36 time: 0.6323 data_time: 0.0362 memory: 24011 grad_norm: 4.0937 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2257 loss: 1.2257 2022/09/05 10:20:57 - mmengine - INFO - Epoch(train) [12][420/940] lr: 1.0000e-02 eta: 15:53:14 time: 0.6400 data_time: 0.0457 memory: 24011 grad_norm: 4.1009 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3724 loss: 1.3724 2022/09/05 10:21:10 - mmengine - INFO - Epoch(train) [12][440/940] lr: 1.0000e-02 eta: 15:52:54 time: 0.6447 data_time: 0.0347 memory: 24011 grad_norm: 4.0154 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1969 loss: 1.1969 2022/09/05 10:21:23 - mmengine - INFO - Epoch(train) [12][460/940] lr: 1.0000e-02 eta: 15:52:36 time: 0.6604 data_time: 0.0613 memory: 24011 grad_norm: 4.1220 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2818 loss: 1.2818 2022/09/05 10:21:36 - mmengine - INFO - Epoch(train) [12][480/940] lr: 1.0000e-02 eta: 15:52:18 time: 0.6561 data_time: 0.0641 memory: 24011 grad_norm: 4.2845 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3537 loss: 1.3537 2022/09/05 10:21:50 - mmengine - INFO - Epoch(train) [12][500/940] lr: 1.0000e-02 eta: 15:52:04 time: 0.6874 data_time: 0.1136 memory: 24011 grad_norm: 4.0734 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3121 loss: 1.3121 2022/09/05 10:22:03 - mmengine - INFO - Epoch(train) [12][520/940] lr: 1.0000e-02 eta: 15:51:45 time: 0.6482 data_time: 0.0760 memory: 24011 grad_norm: 4.2777 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2232 loss: 1.2232 2022/09/05 10:22:16 - mmengine - INFO - Epoch(train) [12][540/940] lr: 1.0000e-02 eta: 15:51:25 time: 0.6491 data_time: 0.0860 memory: 24011 grad_norm: 4.2155 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1855 loss: 1.1855 2022/09/05 10:22:29 - mmengine - INFO - Epoch(train) [12][560/940] lr: 1.0000e-02 eta: 15:51:09 time: 0.6685 data_time: 0.1085 memory: 24011 grad_norm: 4.2662 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.3048 loss: 1.3048 2022/09/05 10:22:42 - mmengine - INFO - Epoch(train) [12][580/940] lr: 1.0000e-02 eta: 15:50:45 time: 0.6239 data_time: 0.0710 memory: 24011 grad_norm: 4.2649 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2212 loss: 1.2212 2022/09/05 10:22:55 - mmengine - INFO - Epoch(train) [12][600/940] lr: 1.0000e-02 eta: 15:50:23 time: 0.6304 data_time: 0.0480 memory: 24011 grad_norm: 3.9395 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3396 loss: 1.3396 2022/09/05 10:23:08 - mmengine - INFO - Epoch(train) [12][620/940] lr: 1.0000e-02 eta: 15:50:03 time: 0.6483 data_time: 0.0702 memory: 24011 grad_norm: 4.2377 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2363 loss: 1.2363 2022/09/05 10:23:20 - mmengine - INFO - Epoch(train) [12][640/940] lr: 1.0000e-02 eta: 15:49:40 time: 0.6202 data_time: 0.0553 memory: 24011 grad_norm: 4.0937 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4152 loss: 1.4152 2022/09/05 10:23:34 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:23:34 - mmengine - INFO - Epoch(train) [12][660/940] lr: 1.0000e-02 eta: 15:49:25 time: 0.6815 data_time: 0.1065 memory: 24011 grad_norm: 4.0145 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3097 loss: 1.3097 2022/09/05 10:23:47 - mmengine - INFO - Epoch(train) [12][680/940] lr: 1.0000e-02 eta: 15:49:09 time: 0.6709 data_time: 0.0865 memory: 24011 grad_norm: 4.2048 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3648 loss: 1.3648 2022/09/05 10:23:59 - mmengine - INFO - Epoch(train) [12][700/940] lr: 1.0000e-02 eta: 15:48:44 time: 0.6090 data_time: 0.0476 memory: 24011 grad_norm: 4.5129 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3055 loss: 1.3055 2022/09/05 10:24:11 - mmengine - INFO - Epoch(train) [12][720/940] lr: 1.0000e-02 eta: 15:48:18 time: 0.6028 data_time: 0.0493 memory: 24011 grad_norm: 4.1839 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3281 loss: 1.3281 2022/09/05 10:24:25 - mmengine - INFO - Epoch(train) [12][740/940] lr: 1.0000e-02 eta: 15:48:03 time: 0.6788 data_time: 0.1237 memory: 24011 grad_norm: 4.2522 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3507 loss: 1.3507 2022/09/05 10:24:37 - mmengine - INFO - Epoch(train) [12][760/940] lr: 1.0000e-02 eta: 15:47:41 time: 0.6339 data_time: 0.0754 memory: 24011 grad_norm: 5.8772 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3030 loss: 1.3030 2022/09/05 10:24:51 - mmengine - INFO - Epoch(train) [12][780/940] lr: 1.0000e-02 eta: 15:47:24 time: 0.6644 data_time: 0.1070 memory: 24011 grad_norm: 4.8051 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3888 loss: 1.3888 2022/09/05 10:25:04 - mmengine - INFO - Epoch(train) [12][800/940] lr: 1.0000e-02 eta: 15:47:05 time: 0.6499 data_time: 0.0918 memory: 24011 grad_norm: 4.4245 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3926 loss: 1.3926 2022/09/05 10:25:17 - mmengine - INFO - Epoch(train) [12][820/940] lr: 1.0000e-02 eta: 15:46:47 time: 0.6561 data_time: 0.0902 memory: 24011 grad_norm: 5.0469 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3517 loss: 1.3517 2022/09/05 10:25:30 - mmengine - INFO - Epoch(train) [12][840/940] lr: 1.0000e-02 eta: 15:46:27 time: 0.6419 data_time: 0.0789 memory: 24011 grad_norm: 4.3837 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4093 loss: 1.4093 2022/09/05 10:25:43 - mmengine - INFO - Epoch(train) [12][860/940] lr: 1.0000e-02 eta: 15:46:10 time: 0.6612 data_time: 0.0999 memory: 24011 grad_norm: 4.3583 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2265 loss: 1.2265 2022/09/05 10:25:55 - mmengine - INFO - Epoch(train) [12][880/940] lr: 1.0000e-02 eta: 15:45:47 time: 0.6253 data_time: 0.0573 memory: 24011 grad_norm: 4.3638 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3775 loss: 1.3775 2022/09/05 10:26:09 - mmengine - INFO - Epoch(train) [12][900/940] lr: 1.0000e-02 eta: 15:45:29 time: 0.6584 data_time: 0.1004 memory: 24011 grad_norm: 4.3151 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3062 loss: 1.3062 2022/09/05 10:26:21 - mmengine - INFO - Epoch(train) [12][920/940] lr: 1.0000e-02 eta: 15:45:07 time: 0.6283 data_time: 0.0633 memory: 24011 grad_norm: 4.3773 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.2719 loss: 1.2719 2022/09/05 10:26:33 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:26:33 - mmengine - INFO - Epoch(train) [12][940/940] lr: 1.0000e-02 eta: 15:44:39 time: 0.5895 data_time: 0.0789 memory: 24011 grad_norm: 4.5691 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3962 loss: 1.3962 2022/09/05 10:26:33 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/09/05 10:26:52 - mmengine - INFO - Epoch(val) [12][20/78] eta: 0:00:40 time: 0.6973 data_time: 0.5404 memory: 3625 2022/09/05 10:27:02 - mmengine - INFO - Epoch(val) [12][40/78] eta: 0:00:18 time: 0.4851 data_time: 0.3237 memory: 3625 2022/09/05 10:27:14 - mmengine - INFO - Epoch(val) [12][60/78] eta: 0:00:11 time: 0.6238 data_time: 0.4679 memory: 3625 2022/09/05 10:27:23 - mmengine - INFO - Epoch(val) [12][78/78] acc/top1: 0.7142 acc/top5: 0.9017 acc/mean1: 0.7142 2022/09/05 10:27:24 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_12.pth is removed 2022/09/05 10:27:26 - mmengine - INFO - The best checkpoint with 0.7142 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/09/05 10:27:43 - mmengine - INFO - Epoch(train) [13][20/940] lr: 1.0000e-02 eta: 15:44:48 time: 0.8403 data_time: 0.2800 memory: 24011 grad_norm: 4.3765 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1450 loss: 1.1450 2022/09/05 10:27:56 - mmengine - INFO - Epoch(train) [13][40/940] lr: 1.0000e-02 eta: 15:44:28 time: 0.6401 data_time: 0.0776 memory: 24011 grad_norm: 4.2402 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3243 loss: 1.3243 2022/09/05 10:28:10 - mmengine - INFO - Epoch(train) [13][60/940] lr: 1.0000e-02 eta: 15:44:12 time: 0.6712 data_time: 0.1164 memory: 24011 grad_norm: 4.7524 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3412 loss: 1.3412 2022/09/05 10:28:22 - mmengine - INFO - Epoch(train) [13][80/940] lr: 1.0000e-02 eta: 15:43:52 time: 0.6424 data_time: 0.0894 memory: 24011 grad_norm: 4.6916 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3308 loss: 1.3308 2022/09/05 10:28:37 - mmengine - INFO - Epoch(train) [13][100/940] lr: 1.0000e-02 eta: 15:43:41 time: 0.7047 data_time: 0.1449 memory: 24011 grad_norm: 4.2448 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2422 loss: 1.2422 2022/09/05 10:28:49 - mmengine - INFO - Epoch(train) [13][120/940] lr: 1.0000e-02 eta: 15:43:21 time: 0.6393 data_time: 0.0865 memory: 24011 grad_norm: 4.0101 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2413 loss: 1.2413 2022/09/05 10:29:02 - mmengine - INFO - Epoch(train) [13][140/940] lr: 1.0000e-02 eta: 15:43:03 time: 0.6558 data_time: 0.0960 memory: 24011 grad_norm: 4.0826 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2421 loss: 1.2421 2022/09/05 10:29:15 - mmengine - INFO - Epoch(train) [13][160/940] lr: 1.0000e-02 eta: 15:42:43 time: 0.6415 data_time: 0.0792 memory: 24011 grad_norm: 4.4436 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1471 loss: 1.1471 2022/09/05 10:29:29 - mmengine - INFO - Epoch(train) [13][180/940] lr: 1.0000e-02 eta: 15:42:29 time: 0.6852 data_time: 0.1204 memory: 24011 grad_norm: 3.9231 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2957 loss: 1.2957 2022/09/05 10:29:41 - mmengine - INFO - Epoch(train) [13][200/940] lr: 1.0000e-02 eta: 15:42:04 time: 0.6022 data_time: 0.0273 memory: 24011 grad_norm: 4.1586 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2016 loss: 1.2016 2022/09/05 10:29:53 - mmengine - INFO - Epoch(train) [13][220/940] lr: 1.0000e-02 eta: 15:41:40 time: 0.6149 data_time: 0.0568 memory: 24011 grad_norm: 4.5364 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2618 loss: 1.2618 2022/09/05 10:30:05 - mmengine - INFO - Epoch(train) [13][240/940] lr: 1.0000e-02 eta: 15:41:16 time: 0.6095 data_time: 0.0517 memory: 24011 grad_norm: 4.5666 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2135 loss: 1.2135 2022/09/05 10:30:20 - mmengine - INFO - Epoch(train) [13][260/940] lr: 1.0000e-02 eta: 15:41:08 time: 0.7250 data_time: 0.1687 memory: 24011 grad_norm: 5.0976 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1699 loss: 1.1699 2022/09/05 10:30:32 - mmengine - INFO - Epoch(train) [13][280/940] lr: 1.0000e-02 eta: 15:40:43 time: 0.6087 data_time: 0.0504 memory: 24011 grad_norm: 5.1200 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.3529 loss: 1.3529 2022/09/05 10:30:44 - mmengine - INFO - Epoch(train) [13][300/940] lr: 1.0000e-02 eta: 15:40:19 time: 0.6107 data_time: 0.0492 memory: 24011 grad_norm: 4.7238 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4149 loss: 1.4149 2022/09/05 10:30:57 - mmengine - INFO - Epoch(train) [13][320/940] lr: 1.0000e-02 eta: 15:39:59 time: 0.6413 data_time: 0.0474 memory: 24011 grad_norm: 4.2456 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4353 loss: 1.4353 2022/09/05 10:31:10 - mmengine - INFO - Epoch(train) [13][340/940] lr: 1.0000e-02 eta: 15:39:39 time: 0.6402 data_time: 0.0513 memory: 24011 grad_norm: 4.8739 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4146 loss: 1.4146 2022/09/05 10:31:23 - mmengine - INFO - Epoch(train) [13][360/940] lr: 1.0000e-02 eta: 15:39:21 time: 0.6530 data_time: 0.0345 memory: 24011 grad_norm: 4.5782 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3544 loss: 1.3544 2022/09/05 10:31:36 - mmengine - INFO - Epoch(train) [13][380/940] lr: 1.0000e-02 eta: 15:39:04 time: 0.6614 data_time: 0.0394 memory: 24011 grad_norm: 4.0759 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2560 loss: 1.2560 2022/09/05 10:31:49 - mmengine - INFO - Epoch(train) [13][400/940] lr: 1.0000e-02 eta: 15:38:43 time: 0.6354 data_time: 0.0334 memory: 24011 grad_norm: 4.5916 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2924 loss: 1.2924 2022/09/05 10:32:02 - mmengine - INFO - Epoch(train) [13][420/940] lr: 1.0000e-02 eta: 15:38:28 time: 0.6695 data_time: 0.0509 memory: 24011 grad_norm: 4.7144 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3291 loss: 1.3291 2022/09/05 10:32:15 - mmengine - INFO - Epoch(train) [13][440/940] lr: 1.0000e-02 eta: 15:38:09 time: 0.6468 data_time: 0.0415 memory: 24011 grad_norm: 4.4905 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3118 loss: 1.3118 2022/09/05 10:32:28 - mmengine - INFO - Epoch(train) [13][460/940] lr: 1.0000e-02 eta: 15:37:50 time: 0.6515 data_time: 0.0399 memory: 24011 grad_norm: 4.2407 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.4507 loss: 1.4507 2022/09/05 10:32:42 - mmengine - INFO - Epoch(train) [13][480/940] lr: 1.0000e-02 eta: 15:37:36 time: 0.6749 data_time: 0.0303 memory: 24011 grad_norm: 4.5959 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3960 loss: 1.3960 2022/09/05 10:32:55 - mmengine - INFO - Epoch(train) [13][500/940] lr: 1.0000e-02 eta: 15:37:16 time: 0.6389 data_time: 0.0453 memory: 24011 grad_norm: 4.1019 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2379 loss: 1.2379 2022/09/05 10:33:07 - mmengine - INFO - Epoch(train) [13][520/940] lr: 1.0000e-02 eta: 15:36:52 time: 0.6152 data_time: 0.0313 memory: 24011 grad_norm: 4.3393 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3523 loss: 1.3523 2022/09/05 10:33:21 - mmengine - INFO - Epoch(train) [13][540/940] lr: 1.0000e-02 eta: 15:36:40 time: 0.6920 data_time: 0.1246 memory: 24011 grad_norm: 4.0735 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2972 loss: 1.2972 2022/09/05 10:33:33 - mmengine - INFO - Epoch(train) [13][560/940] lr: 1.0000e-02 eta: 15:36:18 time: 0.6255 data_time: 0.0590 memory: 24011 grad_norm: 4.3055 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3629 loss: 1.3629 2022/09/05 10:33:46 - mmengine - INFO - Epoch(train) [13][580/940] lr: 1.0000e-02 eta: 15:35:57 time: 0.6348 data_time: 0.0665 memory: 24011 grad_norm: 3.8281 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3226 loss: 1.3226 2022/09/05 10:33:58 - mmengine - INFO - Epoch(train) [13][600/940] lr: 1.0000e-02 eta: 15:35:34 time: 0.6109 data_time: 0.0464 memory: 24011 grad_norm: 4.2000 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2653 loss: 1.2653 2022/09/05 10:34:11 - mmengine - INFO - Epoch(train) [13][620/940] lr: 1.0000e-02 eta: 15:35:17 time: 0.6616 data_time: 0.0926 memory: 24011 grad_norm: 3.9510 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2543 loss: 1.2543 2022/09/05 10:34:24 - mmengine - INFO - Epoch(train) [13][640/940] lr: 1.0000e-02 eta: 15:34:59 time: 0.6525 data_time: 0.0920 memory: 24011 grad_norm: 4.0963 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3465 loss: 1.3465 2022/09/05 10:34:38 - mmengine - INFO - Epoch(train) [13][660/940] lr: 1.0000e-02 eta: 15:34:46 time: 0.6890 data_time: 0.1292 memory: 24011 grad_norm: 4.0506 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2257 loss: 1.2257 2022/09/05 10:34:51 - mmengine - INFO - Epoch(train) [13][680/940] lr: 1.0000e-02 eta: 15:34:30 time: 0.6632 data_time: 0.1031 memory: 24011 grad_norm: 3.9128 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2427 loss: 1.2427 2022/09/05 10:35:05 - mmengine - INFO - Epoch(train) [13][700/940] lr: 1.0000e-02 eta: 15:34:13 time: 0.6583 data_time: 0.0962 memory: 24011 grad_norm: 3.8947 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2288 loss: 1.2288 2022/09/05 10:35:17 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:35:17 - mmengine - INFO - Epoch(train) [13][720/940] lr: 1.0000e-02 eta: 15:33:49 time: 0.6135 data_time: 0.0479 memory: 24011 grad_norm: 4.0700 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2310 loss: 1.2310 2022/09/05 10:35:30 - mmengine - INFO - Epoch(train) [13][740/940] lr: 1.0000e-02 eta: 15:33:30 time: 0.6400 data_time: 0.0766 memory: 24011 grad_norm: 3.9869 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2311 loss: 1.2311 2022/09/05 10:35:43 - mmengine - INFO - Epoch(train) [13][760/940] lr: 1.0000e-02 eta: 15:33:15 time: 0.6769 data_time: 0.1057 memory: 24011 grad_norm: 4.4697 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1851 loss: 1.1851 2022/09/05 10:35:56 - mmengine - INFO - Epoch(train) [13][780/940] lr: 1.0000e-02 eta: 15:32:55 time: 0.6353 data_time: 0.0678 memory: 24011 grad_norm: 4.1891 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2419 loss: 1.2419 2022/09/05 10:36:09 - mmengine - INFO - Epoch(train) [13][800/940] lr: 1.0000e-02 eta: 15:32:36 time: 0.6398 data_time: 0.0614 memory: 24011 grad_norm: 4.2596 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2733 loss: 1.2733 2022/09/05 10:36:22 - mmengine - INFO - Epoch(train) [13][820/940] lr: 1.0000e-02 eta: 15:32:17 time: 0.6464 data_time: 0.0568 memory: 24011 grad_norm: 4.3527 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3205 loss: 1.3205 2022/09/05 10:36:34 - mmengine - INFO - Epoch(train) [13][840/940] lr: 1.0000e-02 eta: 15:31:56 time: 0.6285 data_time: 0.0321 memory: 24011 grad_norm: 4.1719 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2380 loss: 1.2380 2022/09/05 10:36:48 - mmengine - INFO - Epoch(train) [13][860/940] lr: 1.0000e-02 eta: 15:31:40 time: 0.6684 data_time: 0.0829 memory: 24011 grad_norm: 4.0276 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4247 loss: 1.4247 2022/09/05 10:37:01 - mmengine - INFO - Epoch(train) [13][880/940] lr: 1.0000e-02 eta: 15:31:22 time: 0.6486 data_time: 0.0775 memory: 24011 grad_norm: 4.0346 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3152 loss: 1.3152 2022/09/05 10:37:15 - mmengine - INFO - Epoch(train) [13][900/940] lr: 1.0000e-02 eta: 15:31:13 time: 0.7151 data_time: 0.1446 memory: 24011 grad_norm: 4.0764 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4114 loss: 1.4114 2022/09/05 10:37:27 - mmengine - INFO - Epoch(train) [13][920/940] lr: 1.0000e-02 eta: 15:30:49 time: 0.6109 data_time: 0.0281 memory: 24011 grad_norm: 4.1006 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3551 loss: 1.3551 2022/09/05 10:37:38 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:37:38 - mmengine - INFO - Epoch(train) [13][940/940] lr: 1.0000e-02 eta: 15:30:17 time: 0.5410 data_time: 0.0268 memory: 24011 grad_norm: 4.1463 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.2435 loss: 1.2435 2022/09/05 10:37:52 - mmengine - INFO - Epoch(val) [13][20/78] eta: 0:00:40 time: 0.7010 data_time: 0.5411 memory: 3625 2022/09/05 10:38:01 - mmengine - INFO - Epoch(val) [13][40/78] eta: 0:00:17 time: 0.4697 data_time: 0.3123 memory: 3625 2022/09/05 10:38:14 - mmengine - INFO - Epoch(val) [13][60/78] eta: 0:00:11 time: 0.6509 data_time: 0.4939 memory: 3625 2022/09/05 10:38:25 - mmengine - INFO - Epoch(val) [13][78/78] acc/top1: 0.7188 acc/top5: 0.9047 acc/mean1: 0.7187 2022/09/05 10:38:25 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_13.pth is removed 2022/09/05 10:38:28 - mmengine - INFO - The best checkpoint with 0.7188 acc/top1 at 14 epoch is saved to best_acc/top1_epoch_14.pth. 2022/09/05 10:38:44 - mmengine - INFO - Epoch(train) [14][20/940] lr: 1.0000e-02 eta: 15:30:23 time: 0.8280 data_time: 0.2824 memory: 24011 grad_norm: 4.0783 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2180 loss: 1.2180 2022/09/05 10:38:57 - mmengine - INFO - Epoch(train) [14][40/940] lr: 1.0000e-02 eta: 15:30:04 time: 0.6476 data_time: 0.1031 memory: 24011 grad_norm: 4.1935 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2542 loss: 1.2542 2022/09/05 10:39:11 - mmengine - INFO - Epoch(train) [14][60/940] lr: 1.0000e-02 eta: 15:29:53 time: 0.7037 data_time: 0.1536 memory: 24011 grad_norm: 4.2166 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2995 loss: 1.2995 2022/09/05 10:39:24 - mmengine - INFO - Epoch(train) [14][80/940] lr: 1.0000e-02 eta: 15:29:32 time: 0.6270 data_time: 0.0793 memory: 24011 grad_norm: 4.0572 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2574 loss: 1.2574 2022/09/05 10:39:37 - mmengine - INFO - Epoch(train) [14][100/940] lr: 1.0000e-02 eta: 15:29:15 time: 0.6533 data_time: 0.0961 memory: 24011 grad_norm: 4.0498 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2723 loss: 1.2723 2022/09/05 10:39:49 - mmengine - INFO - Epoch(train) [14][120/940] lr: 1.0000e-02 eta: 15:28:52 time: 0.6121 data_time: 0.0514 memory: 24011 grad_norm: 3.9364 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3447 loss: 1.3447 2022/09/05 10:40:02 - mmengine - INFO - Epoch(train) [14][140/940] lr: 1.0000e-02 eta: 15:28:33 time: 0.6407 data_time: 0.0688 memory: 24011 grad_norm: 4.0500 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3138 loss: 1.3138 2022/09/05 10:40:15 - mmengine - INFO - Epoch(train) [14][160/940] lr: 1.0000e-02 eta: 15:28:12 time: 0.6257 data_time: 0.0599 memory: 24011 grad_norm: 4.1635 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2219 loss: 1.2219 2022/09/05 10:40:28 - mmengine - INFO - Epoch(train) [14][180/940] lr: 1.0000e-02 eta: 15:27:55 time: 0.6608 data_time: 0.0755 memory: 24011 grad_norm: 4.3076 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3844 loss: 1.3844 2022/09/05 10:40:40 - mmengine - INFO - Epoch(train) [14][200/940] lr: 1.0000e-02 eta: 15:27:34 time: 0.6237 data_time: 0.0299 memory: 24011 grad_norm: 4.1180 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1506 loss: 1.1506 2022/09/05 10:40:53 - mmengine - INFO - Epoch(train) [14][220/940] lr: 1.0000e-02 eta: 15:27:14 time: 0.6381 data_time: 0.0379 memory: 24011 grad_norm: 4.0293 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2977 loss: 1.2977 2022/09/05 10:41:07 - mmengine - INFO - Epoch(train) [14][240/940] lr: 1.0000e-02 eta: 15:26:58 time: 0.6630 data_time: 0.0382 memory: 24011 grad_norm: 3.9537 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1578 loss: 1.1578 2022/09/05 10:41:20 - mmengine - INFO - Epoch(train) [14][260/940] lr: 1.0000e-02 eta: 15:26:44 time: 0.6797 data_time: 0.0951 memory: 24011 grad_norm: 4.7373 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2697 loss: 1.2697 2022/09/05 10:41:32 - mmengine - INFO - Epoch(train) [14][280/940] lr: 1.0000e-02 eta: 15:26:23 time: 0.6254 data_time: 0.0553 memory: 24011 grad_norm: 3.9605 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2383 loss: 1.2383 2022/09/05 10:41:45 - mmengine - INFO - Epoch(train) [14][300/940] lr: 1.0000e-02 eta: 15:26:02 time: 0.6235 data_time: 0.0629 memory: 24011 grad_norm: 4.2344 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.4296 loss: 1.4296 2022/09/05 10:41:58 - mmengine - INFO - Epoch(train) [14][320/940] lr: 1.0000e-02 eta: 15:25:44 time: 0.6481 data_time: 0.0362 memory: 24011 grad_norm: 4.5742 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3402 loss: 1.3402 2022/09/05 10:42:11 - mmengine - INFO - Epoch(train) [14][340/940] lr: 1.0000e-02 eta: 15:25:24 time: 0.6339 data_time: 0.0507 memory: 24011 grad_norm: 4.5648 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2347 loss: 1.2347 2022/09/05 10:42:23 - mmengine - INFO - Epoch(train) [14][360/940] lr: 1.0000e-02 eta: 15:25:06 time: 0.6444 data_time: 0.0770 memory: 24011 grad_norm: 4.7004 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.2411 loss: 1.2411 2022/09/05 10:42:37 - mmengine - INFO - Epoch(train) [14][380/940] lr: 1.0000e-02 eta: 15:24:48 time: 0.6546 data_time: 0.0458 memory: 24011 grad_norm: 4.3326 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0928 loss: 1.0928 2022/09/05 10:42:49 - mmengine - INFO - Epoch(train) [14][400/940] lr: 1.0000e-02 eta: 15:24:30 time: 0.6468 data_time: 0.0375 memory: 24011 grad_norm: 4.2598 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4252 loss: 1.4252 2022/09/05 10:43:02 - mmengine - INFO - Epoch(train) [14][420/940] lr: 1.0000e-02 eta: 15:24:10 time: 0.6302 data_time: 0.0367 memory: 24011 grad_norm: 4.3263 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.2221 loss: 1.2221 2022/09/05 10:43:15 - mmengine - INFO - Epoch(train) [14][440/940] lr: 1.0000e-02 eta: 15:23:51 time: 0.6423 data_time: 0.0369 memory: 24011 grad_norm: 4.3066 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1837 loss: 1.1837 2022/09/05 10:43:29 - mmengine - INFO - Epoch(train) [14][460/940] lr: 1.0000e-02 eta: 15:23:42 time: 0.7183 data_time: 0.0395 memory: 24011 grad_norm: 4.5072 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1795 loss: 1.1795 2022/09/05 10:43:42 - mmengine - INFO - Epoch(train) [14][480/940] lr: 1.0000e-02 eta: 15:23:23 time: 0.6358 data_time: 0.0542 memory: 24011 grad_norm: 4.3900 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2430 loss: 1.2430 2022/09/05 10:43:55 - mmengine - INFO - Epoch(train) [14][500/940] lr: 1.0000e-02 eta: 15:23:07 time: 0.6611 data_time: 0.0402 memory: 24011 grad_norm: 4.1667 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2571 loss: 1.2571 2022/09/05 10:44:09 - mmengine - INFO - Epoch(train) [14][520/940] lr: 1.0000e-02 eta: 15:22:51 time: 0.6658 data_time: 0.0376 memory: 24011 grad_norm: 4.2435 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3519 loss: 1.3519 2022/09/05 10:44:21 - mmengine - INFO - Epoch(train) [14][540/940] lr: 1.0000e-02 eta: 15:22:30 time: 0.6250 data_time: 0.0438 memory: 24011 grad_norm: 4.0179 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.3554 loss: 1.3554 2022/09/05 10:44:33 - mmengine - INFO - Epoch(train) [14][560/940] lr: 1.0000e-02 eta: 15:22:06 time: 0.6005 data_time: 0.0356 memory: 24011 grad_norm: 3.8827 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1265 loss: 1.1265 2022/09/05 10:44:46 - mmengine - INFO - Epoch(train) [14][580/940] lr: 1.0000e-02 eta: 15:21:48 time: 0.6477 data_time: 0.0367 memory: 24011 grad_norm: 4.3979 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2185 loss: 1.2185 2022/09/05 10:44:59 - mmengine - INFO - Epoch(train) [14][600/940] lr: 1.0000e-02 eta: 15:21:34 time: 0.6706 data_time: 0.0522 memory: 24011 grad_norm: 3.7680 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2425 loss: 1.2425 2022/09/05 10:45:13 - mmengine - INFO - Epoch(train) [14][620/940] lr: 1.0000e-02 eta: 15:21:17 time: 0.6614 data_time: 0.0352 memory: 24011 grad_norm: 4.3949 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2432 loss: 1.2432 2022/09/05 10:45:26 - mmengine - INFO - Epoch(train) [14][640/940] lr: 1.0000e-02 eta: 15:21:00 time: 0.6507 data_time: 0.0449 memory: 24011 grad_norm: 4.2744 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3596 loss: 1.3596 2022/09/05 10:45:38 - mmengine - INFO - Epoch(train) [14][660/940] lr: 1.0000e-02 eta: 15:20:40 time: 0.6310 data_time: 0.0347 memory: 24011 grad_norm: 4.0516 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.3967 loss: 1.3967 2022/09/05 10:45:52 - mmengine - INFO - Epoch(train) [14][680/940] lr: 1.0000e-02 eta: 15:20:25 time: 0.6705 data_time: 0.0424 memory: 24011 grad_norm: 4.2305 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3383 loss: 1.3383 2022/09/05 10:46:05 - mmengine - INFO - Epoch(train) [14][700/940] lr: 1.0000e-02 eta: 15:20:08 time: 0.6523 data_time: 0.0389 memory: 24011 grad_norm: 4.1063 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2886 loss: 1.2886 2022/09/05 10:46:17 - mmengine - INFO - Epoch(train) [14][720/940] lr: 1.0000e-02 eta: 15:19:48 time: 0.6303 data_time: 0.0513 memory: 24011 grad_norm: 3.9328 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.2895 loss: 1.2895 2022/09/05 10:46:30 - mmengine - INFO - Epoch(train) [14][740/940] lr: 1.0000e-02 eta: 15:19:30 time: 0.6435 data_time: 0.0332 memory: 24011 grad_norm: 4.2917 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2120 loss: 1.2120 2022/09/05 10:46:43 - mmengine - INFO - Epoch(train) [14][760/940] lr: 1.0000e-02 eta: 15:19:09 time: 0.6267 data_time: 0.0439 memory: 24011 grad_norm: 4.6649 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4311 loss: 1.4311 2022/09/05 10:46:55 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:46:55 - mmengine - INFO - Epoch(train) [14][780/940] lr: 1.0000e-02 eta: 15:18:50 time: 0.6333 data_time: 0.0408 memory: 24011 grad_norm: 3.8350 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3732 loss: 1.3732 2022/09/05 10:47:09 - mmengine - INFO - Epoch(train) [14][800/940] lr: 1.0000e-02 eta: 15:18:34 time: 0.6639 data_time: 0.0413 memory: 24011 grad_norm: 3.7842 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2041 loss: 1.2041 2022/09/05 10:47:22 - mmengine - INFO - Epoch(train) [14][820/940] lr: 1.0000e-02 eta: 15:18:18 time: 0.6586 data_time: 0.0358 memory: 24011 grad_norm: 4.0337 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2169 loss: 1.2169 2022/09/05 10:47:34 - mmengine - INFO - Epoch(train) [14][840/940] lr: 1.0000e-02 eta: 15:17:56 time: 0.6190 data_time: 0.0472 memory: 24011 grad_norm: 3.8907 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2714 loss: 1.2714 2022/09/05 10:47:47 - mmengine - INFO - Epoch(train) [14][860/940] lr: 1.0000e-02 eta: 15:17:40 time: 0.6549 data_time: 0.0338 memory: 24011 grad_norm: 4.0916 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2849 loss: 1.2849 2022/09/05 10:48:01 - mmengine - INFO - Epoch(train) [14][880/940] lr: 1.0000e-02 eta: 15:17:25 time: 0.6684 data_time: 0.0397 memory: 24011 grad_norm: 3.9981 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3621 loss: 1.3621 2022/09/05 10:48:13 - mmengine - INFO - Epoch(train) [14][900/940] lr: 1.0000e-02 eta: 15:17:05 time: 0.6336 data_time: 0.0387 memory: 24011 grad_norm: 4.1739 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4005 loss: 1.4005 2022/09/05 10:48:26 - mmengine - INFO - Epoch(train) [14][920/940] lr: 1.0000e-02 eta: 15:16:46 time: 0.6346 data_time: 0.0501 memory: 24011 grad_norm: 4.4675 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3298 loss: 1.3298 2022/09/05 10:48:37 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:48:37 - mmengine - INFO - Epoch(train) [14][940/940] lr: 1.0000e-02 eta: 15:16:16 time: 0.5448 data_time: 0.0311 memory: 24011 grad_norm: 4.5633 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3090 loss: 1.3090 2022/09/05 10:48:51 - mmengine - INFO - Epoch(val) [14][20/78] eta: 0:00:40 time: 0.7000 data_time: 0.5422 memory: 3625 2022/09/05 10:49:00 - mmengine - INFO - Epoch(val) [14][40/78] eta: 0:00:17 time: 0.4645 data_time: 0.3047 memory: 3625 2022/09/05 10:49:13 - mmengine - INFO - Epoch(val) [14][60/78] eta: 0:00:11 time: 0.6530 data_time: 0.4920 memory: 3625 2022/09/05 10:49:24 - mmengine - INFO - Epoch(val) [14][78/78] acc/top1: 0.7115 acc/top5: 0.9032 acc/mean1: 0.7114 2022/09/05 10:49:42 - mmengine - INFO - Epoch(train) [15][20/940] lr: 1.0000e-02 eta: 15:16:30 time: 0.9098 data_time: 0.2379 memory: 24011 grad_norm: 4.5520 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2011 loss: 1.2011 2022/09/05 10:49:55 - mmengine - INFO - Epoch(train) [15][40/940] lr: 1.0000e-02 eta: 15:16:13 time: 0.6482 data_time: 0.0309 memory: 24011 grad_norm: 4.0011 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2735 loss: 1.2735 2022/09/05 10:50:08 - mmengine - INFO - Epoch(train) [15][60/940] lr: 1.0000e-02 eta: 15:15:52 time: 0.6179 data_time: 0.0426 memory: 24011 grad_norm: 4.7682 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2641 loss: 1.2641 2022/09/05 10:50:21 - mmengine - INFO - Epoch(train) [15][80/940] lr: 1.0000e-02 eta: 15:15:38 time: 0.6834 data_time: 0.0752 memory: 24011 grad_norm: 5.9381 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3324 loss: 1.3324 2022/09/05 10:50:35 - mmengine - INFO - Epoch(train) [15][100/940] lr: 1.0000e-02 eta: 15:15:26 time: 0.6908 data_time: 0.0413 memory: 24011 grad_norm: 4.0978 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2479 loss: 1.2479 2022/09/05 10:50:47 - mmengine - INFO - Epoch(train) [15][120/940] lr: 1.0000e-02 eta: 15:15:04 time: 0.6129 data_time: 0.0314 memory: 24011 grad_norm: 3.8917 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2767 loss: 1.2767 2022/09/05 10:51:00 - mmengine - INFO - Epoch(train) [15][140/940] lr: 1.0000e-02 eta: 15:14:44 time: 0.6283 data_time: 0.0418 memory: 24011 grad_norm: 4.5941 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2314 loss: 1.2314 2022/09/05 10:51:13 - mmengine - INFO - Epoch(train) [15][160/940] lr: 1.0000e-02 eta: 15:14:24 time: 0.6271 data_time: 0.0318 memory: 24011 grad_norm: 4.2554 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3213 loss: 1.3213 2022/09/05 10:51:26 - mmengine - INFO - Epoch(train) [15][180/940] lr: 1.0000e-02 eta: 15:14:09 time: 0.6701 data_time: 0.0406 memory: 24011 grad_norm: 4.0838 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2568 loss: 1.2568 2022/09/05 10:51:39 - mmengine - INFO - Epoch(train) [15][200/940] lr: 1.0000e-02 eta: 15:13:50 time: 0.6321 data_time: 0.0314 memory: 24011 grad_norm: 4.0014 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3004 loss: 1.3004 2022/09/05 10:51:53 - mmengine - INFO - Epoch(train) [15][220/940] lr: 1.0000e-02 eta: 15:13:42 time: 0.7238 data_time: 0.0494 memory: 24011 grad_norm: 4.1087 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1761 loss: 1.1761 2022/09/05 10:52:05 - mmengine - INFO - Epoch(train) [15][240/940] lr: 1.0000e-02 eta: 15:13:17 time: 0.5906 data_time: 0.0443 memory: 24011 grad_norm: 4.0563 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3639 loss: 1.3639 2022/09/05 10:52:18 - mmengine - INFO - Epoch(train) [15][260/940] lr: 1.0000e-02 eta: 15:13:04 time: 0.6787 data_time: 0.0404 memory: 24011 grad_norm: 3.8994 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2524 loss: 1.2524 2022/09/05 10:52:31 - mmengine - INFO - Epoch(train) [15][280/940] lr: 1.0000e-02 eta: 15:12:44 time: 0.6271 data_time: 0.0355 memory: 24011 grad_norm: 4.1764 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1677 loss: 1.1677 2022/09/05 10:52:44 - mmengine - INFO - Epoch(train) [15][300/940] lr: 1.0000e-02 eta: 15:12:27 time: 0.6578 data_time: 0.0399 memory: 24011 grad_norm: 4.0235 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2471 loss: 1.2471 2022/09/05 10:52:58 - mmengine - INFO - Epoch(train) [15][320/940] lr: 1.0000e-02 eta: 15:12:12 time: 0.6665 data_time: 0.0384 memory: 24011 grad_norm: 4.1902 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2155 loss: 1.2155 2022/09/05 10:53:11 - mmengine - INFO - Epoch(train) [15][340/940] lr: 1.0000e-02 eta: 15:11:56 time: 0.6559 data_time: 0.0409 memory: 24011 grad_norm: 4.3029 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1038 loss: 1.1038 2022/09/05 10:53:23 - mmengine - INFO - Epoch(train) [15][360/940] lr: 1.0000e-02 eta: 15:11:38 time: 0.6434 data_time: 0.0401 memory: 24011 grad_norm: 4.0217 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1791 loss: 1.1791 2022/09/05 10:53:37 - mmengine - INFO - Epoch(train) [15][380/940] lr: 1.0000e-02 eta: 15:11:23 time: 0.6707 data_time: 0.0381 memory: 24011 grad_norm: 4.2115 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2848 loss: 1.2848 2022/09/05 10:53:50 - mmengine - INFO - Epoch(train) [15][400/940] lr: 1.0000e-02 eta: 15:11:07 time: 0.6584 data_time: 0.0361 memory: 24011 grad_norm: 5.7075 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4279 loss: 1.4279 2022/09/05 10:54:03 - mmengine - INFO - Epoch(train) [15][420/940] lr: 1.0000e-02 eta: 15:10:49 time: 0.6445 data_time: 0.0349 memory: 24011 grad_norm: 4.7932 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4922 loss: 1.4922 2022/09/05 10:54:15 - mmengine - INFO - Epoch(train) [15][440/940] lr: 1.0000e-02 eta: 15:10:28 time: 0.6106 data_time: 0.0452 memory: 24011 grad_norm: 4.6194 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4647 loss: 1.4647 2022/09/05 10:54:29 - mmengine - INFO - Epoch(train) [15][460/940] lr: 1.0000e-02 eta: 15:10:13 time: 0.6690 data_time: 0.0379 memory: 24011 grad_norm: 3.9527 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2152 loss: 1.2152 2022/09/05 10:54:41 - mmengine - INFO - Epoch(train) [15][480/940] lr: 1.0000e-02 eta: 15:09:55 time: 0.6413 data_time: 0.0415 memory: 24011 grad_norm: 4.1259 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3928 loss: 1.3928 2022/09/05 10:54:54 - mmengine - INFO - Epoch(train) [15][500/940] lr: 1.0000e-02 eta: 15:09:35 time: 0.6298 data_time: 0.0405 memory: 24011 grad_norm: 4.2639 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3726 loss: 1.3726 2022/09/05 10:55:07 - mmengine - INFO - Epoch(train) [15][520/940] lr: 1.0000e-02 eta: 15:09:20 time: 0.6601 data_time: 0.0405 memory: 24011 grad_norm: 4.2873 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.2853 loss: 1.2853 2022/09/05 10:55:21 - mmengine - INFO - Epoch(train) [15][540/940] lr: 1.0000e-02 eta: 15:09:09 time: 0.7023 data_time: 0.0407 memory: 24011 grad_norm: 4.3086 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3193 loss: 1.3193 2022/09/05 10:55:33 - mmengine - INFO - Epoch(train) [15][560/940] lr: 1.0000e-02 eta: 15:08:45 time: 0.5974 data_time: 0.0353 memory: 24011 grad_norm: 4.1972 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2721 loss: 1.2721 2022/09/05 10:55:47 - mmengine - INFO - Epoch(train) [15][580/940] lr: 1.0000e-02 eta: 15:08:31 time: 0.6757 data_time: 0.0407 memory: 24011 grad_norm: 4.6071 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3808 loss: 1.3808 2022/09/05 10:55:59 - mmengine - INFO - Epoch(train) [15][600/940] lr: 1.0000e-02 eta: 15:08:08 time: 0.5950 data_time: 0.0320 memory: 24011 grad_norm: 6.1096 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2727 loss: 1.2727 2022/09/05 10:56:12 - mmengine - INFO - Epoch(train) [15][620/940] lr: 1.0000e-02 eta: 15:07:53 time: 0.6702 data_time: 0.0458 memory: 24011 grad_norm: 4.6861 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4189 loss: 1.4189 2022/09/05 10:56:25 - mmengine - INFO - Epoch(train) [15][640/940] lr: 1.0000e-02 eta: 15:07:37 time: 0.6554 data_time: 0.0344 memory: 24011 grad_norm: 4.3731 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3270 loss: 1.3270 2022/09/05 10:56:39 - mmengine - INFO - Epoch(train) [15][660/940] lr: 1.0000e-02 eta: 15:07:23 time: 0.6740 data_time: 0.0535 memory: 24011 grad_norm: 4.5471 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4303 loss: 1.4303 2022/09/05 10:56:51 - mmengine - INFO - Epoch(train) [15][680/940] lr: 1.0000e-02 eta: 15:07:01 time: 0.6086 data_time: 0.0503 memory: 24011 grad_norm: 4.2930 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.2483 loss: 1.2483 2022/09/05 10:57:04 - mmengine - INFO - Epoch(train) [15][700/940] lr: 1.0000e-02 eta: 15:06:46 time: 0.6606 data_time: 0.0410 memory: 24011 grad_norm: 4.5700 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4263 loss: 1.4263 2022/09/05 10:57:17 - mmengine - INFO - Epoch(train) [15][720/940] lr: 1.0000e-02 eta: 15:06:28 time: 0.6470 data_time: 0.0417 memory: 24011 grad_norm: 4.5660 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2952 loss: 1.2952 2022/09/05 10:57:30 - mmengine - INFO - Epoch(train) [15][740/940] lr: 1.0000e-02 eta: 15:06:10 time: 0.6377 data_time: 0.0396 memory: 24011 grad_norm: 4.4663 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2697 loss: 1.2697 2022/09/05 10:57:42 - mmengine - INFO - Epoch(train) [15][760/940] lr: 1.0000e-02 eta: 15:05:48 time: 0.6088 data_time: 0.0411 memory: 24011 grad_norm: 4.7475 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3385 loss: 1.3385 2022/09/05 10:57:55 - mmengine - INFO - Epoch(train) [15][780/940] lr: 1.0000e-02 eta: 15:05:33 time: 0.6668 data_time: 0.0388 memory: 24011 grad_norm: 4.4169 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1880 loss: 1.1880 2022/09/05 10:58:08 - mmengine - INFO - Epoch(train) [15][800/940] lr: 1.0000e-02 eta: 15:05:13 time: 0.6173 data_time: 0.0467 memory: 24011 grad_norm: 4.0509 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3767 loss: 1.3767 2022/09/05 10:58:21 - mmengine - INFO - Epoch(train) [15][820/940] lr: 1.0000e-02 eta: 15:04:58 time: 0.6681 data_time: 0.0402 memory: 24011 grad_norm: 5.1185 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2259 loss: 1.2259 2022/09/05 10:58:34 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:58:34 - mmengine - INFO - Epoch(train) [15][840/940] lr: 1.0000e-02 eta: 15:04:41 time: 0.6495 data_time: 0.0367 memory: 24011 grad_norm: 4.3799 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4534 loss: 1.4534 2022/09/05 10:58:47 - mmengine - INFO - Epoch(train) [15][860/940] lr: 1.0000e-02 eta: 15:04:23 time: 0.6352 data_time: 0.0381 memory: 24011 grad_norm: 4.2243 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2672 loss: 1.2672 2022/09/05 10:59:00 - mmengine - INFO - Epoch(train) [15][880/940] lr: 1.0000e-02 eta: 15:04:07 time: 0.6600 data_time: 0.0479 memory: 24011 grad_norm: 4.0069 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3255 loss: 1.3255 2022/09/05 10:59:13 - mmengine - INFO - Epoch(train) [15][900/940] lr: 1.0000e-02 eta: 15:03:49 time: 0.6402 data_time: 0.0634 memory: 24011 grad_norm: 4.2158 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2126 loss: 1.2126 2022/09/05 10:59:26 - mmengine - INFO - Epoch(train) [15][920/940] lr: 1.0000e-02 eta: 15:03:34 time: 0.6671 data_time: 0.1016 memory: 24011 grad_norm: 5.1284 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2287 loss: 1.2287 2022/09/05 10:59:37 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 10:59:37 - mmengine - INFO - Epoch(train) [15][940/940] lr: 1.0000e-02 eta: 15:03:06 time: 0.5514 data_time: 0.0257 memory: 24011 grad_norm: 4.3255 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.4121 loss: 1.4121 2022/09/05 10:59:37 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/09/05 10:59:56 - mmengine - INFO - Epoch(val) [15][20/78] eta: 0:00:40 time: 0.7010 data_time: 0.5417 memory: 3625 2022/09/05 11:00:06 - mmengine - INFO - Epoch(val) [15][40/78] eta: 0:00:17 time: 0.4698 data_time: 0.3137 memory: 3625 2022/09/05 11:00:19 - mmengine - INFO - Epoch(val) [15][60/78] eta: 0:00:11 time: 0.6566 data_time: 0.5023 memory: 3625 2022/09/05 11:00:27 - mmengine - INFO - Epoch(val) [15][78/78] acc/top1: 0.7167 acc/top5: 0.9021 acc/mean1: 0.7165 2022/09/05 11:00:45 - mmengine - INFO - Epoch(train) [16][20/940] lr: 1.0000e-02 eta: 15:03:18 time: 0.9050 data_time: 0.2910 memory: 24011 grad_norm: 4.1214 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1999 loss: 1.1999 2022/09/05 11:00:57 - mmengine - INFO - Epoch(train) [16][40/940] lr: 1.0000e-02 eta: 15:02:57 time: 0.6062 data_time: 0.0375 memory: 24011 grad_norm: 4.0565 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1786 loss: 1.1786 2022/09/05 11:01:11 - mmengine - INFO - Epoch(train) [16][60/940] lr: 1.0000e-02 eta: 15:02:45 time: 0.6955 data_time: 0.0470 memory: 24011 grad_norm: 4.1972 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3068 loss: 1.3068 2022/09/05 11:01:24 - mmengine - INFO - Epoch(train) [16][80/940] lr: 1.0000e-02 eta: 15:02:26 time: 0.6264 data_time: 0.0382 memory: 24011 grad_norm: 4.1811 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2987 loss: 1.2987 2022/09/05 11:01:38 - mmengine - INFO - Epoch(train) [16][100/940] lr: 1.0000e-02 eta: 15:02:13 time: 0.6882 data_time: 0.0403 memory: 24011 grad_norm: 4.1612 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3244 loss: 1.3244 2022/09/05 11:01:51 - mmengine - INFO - Epoch(train) [16][120/940] lr: 1.0000e-02 eta: 15:01:58 time: 0.6630 data_time: 0.0370 memory: 24011 grad_norm: 4.2785 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0940 loss: 1.0940 2022/09/05 11:02:03 - mmengine - INFO - Epoch(train) [16][140/940] lr: 1.0000e-02 eta: 15:01:37 time: 0.6170 data_time: 0.0390 memory: 24011 grad_norm: 4.1992 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1645 loss: 1.1645 2022/09/05 11:02:16 - mmengine - INFO - Epoch(train) [16][160/940] lr: 1.0000e-02 eta: 15:01:21 time: 0.6508 data_time: 0.0424 memory: 24011 grad_norm: 4.0611 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1871 loss: 1.1871 2022/09/05 11:02:29 - mmengine - INFO - Epoch(train) [16][180/940] lr: 1.0000e-02 eta: 15:01:05 time: 0.6554 data_time: 0.0392 memory: 24011 grad_norm: 4.2010 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2268 loss: 1.2268 2022/09/05 11:02:42 - mmengine - INFO - Epoch(train) [16][200/940] lr: 1.0000e-02 eta: 15:00:45 time: 0.6224 data_time: 0.0477 memory: 24011 grad_norm: 3.9579 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2897 loss: 1.2897 2022/09/05 11:02:56 - mmengine - INFO - Epoch(train) [16][220/940] lr: 1.0000e-02 eta: 15:00:33 time: 0.6897 data_time: 0.0397 memory: 24011 grad_norm: 4.6123 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1454 loss: 1.1454 2022/09/05 11:03:08 - mmengine - INFO - Epoch(train) [16][240/940] lr: 1.0000e-02 eta: 15:00:09 time: 0.5920 data_time: 0.0404 memory: 24011 grad_norm: 4.6079 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2006 loss: 1.2006 2022/09/05 11:03:22 - mmengine - INFO - Epoch(train) [16][260/940] lr: 1.0000e-02 eta: 14:59:58 time: 0.7014 data_time: 0.0530 memory: 24011 grad_norm: 4.2792 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2825 loss: 1.2825 2022/09/05 11:03:34 - mmengine - INFO - Epoch(train) [16][280/940] lr: 1.0000e-02 eta: 14:59:39 time: 0.6247 data_time: 0.0391 memory: 24011 grad_norm: 4.1981 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1766 loss: 1.1766 2022/09/05 11:03:48 - mmengine - INFO - Epoch(train) [16][300/940] lr: 1.0000e-02 eta: 14:59:25 time: 0.6784 data_time: 0.0616 memory: 24011 grad_norm: 4.3183 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2460 loss: 1.2460 2022/09/05 11:04:01 - mmengine - INFO - Epoch(train) [16][320/940] lr: 1.0000e-02 eta: 14:59:09 time: 0.6516 data_time: 0.0389 memory: 24011 grad_norm: 4.8711 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2651 loss: 1.2651 2022/09/05 11:04:14 - mmengine - INFO - Epoch(train) [16][340/940] lr: 1.0000e-02 eta: 14:58:55 time: 0.6712 data_time: 0.0390 memory: 24011 grad_norm: 3.9914 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1972 loss: 1.1972 2022/09/05 11:04:26 - mmengine - INFO - Epoch(train) [16][360/940] lr: 1.0000e-02 eta: 14:58:34 time: 0.6100 data_time: 0.0445 memory: 24011 grad_norm: 4.0314 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2705 loss: 1.2705 2022/09/05 11:04:39 - mmengine - INFO - Epoch(train) [16][380/940] lr: 1.0000e-02 eta: 14:58:18 time: 0.6548 data_time: 0.0464 memory: 24011 grad_norm: 4.1415 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2145 loss: 1.2145 2022/09/05 11:04:51 - mmengine - INFO - Epoch(train) [16][400/940] lr: 1.0000e-02 eta: 14:57:56 time: 0.6066 data_time: 0.0430 memory: 24011 grad_norm: 6.1322 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3581 loss: 1.3581 2022/09/05 11:05:05 - mmengine - INFO - Epoch(train) [16][420/940] lr: 1.0000e-02 eta: 14:57:44 time: 0.6937 data_time: 0.0393 memory: 24011 grad_norm: 4.3791 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3303 loss: 1.3303 2022/09/05 11:05:17 - mmengine - INFO - Epoch(train) [16][440/940] lr: 1.0000e-02 eta: 14:57:22 time: 0.5980 data_time: 0.0352 memory: 24011 grad_norm: 4.6972 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2277 loss: 1.2277 2022/09/05 11:05:31 - mmengine - INFO - Epoch(train) [16][460/940] lr: 1.0000e-02 eta: 14:57:10 time: 0.6887 data_time: 0.0455 memory: 24011 grad_norm: 4.5632 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2644 loss: 1.2644 2022/09/05 11:05:45 - mmengine - INFO - Epoch(train) [16][480/940] lr: 1.0000e-02 eta: 14:56:57 time: 0.6893 data_time: 0.0391 memory: 24011 grad_norm: 4.5317 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2788 loss: 1.2788 2022/09/05 11:05:57 - mmengine - INFO - Epoch(train) [16][500/940] lr: 1.0000e-02 eta: 14:56:38 time: 0.6269 data_time: 0.0469 memory: 24011 grad_norm: 4.5060 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3967 loss: 1.3967 2022/09/05 11:06:10 - mmengine - INFO - Epoch(train) [16][520/940] lr: 1.0000e-02 eta: 14:56:19 time: 0.6219 data_time: 0.0488 memory: 24011 grad_norm: 4.5838 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2419 loss: 1.2419 2022/09/05 11:06:22 - mmengine - INFO - Epoch(train) [16][540/940] lr: 1.0000e-02 eta: 14:55:59 time: 0.6218 data_time: 0.0421 memory: 24011 grad_norm: 4.6167 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3352 loss: 1.3352 2022/09/05 11:06:35 - mmengine - INFO - Epoch(train) [16][560/940] lr: 1.0000e-02 eta: 14:55:42 time: 0.6444 data_time: 0.0453 memory: 24011 grad_norm: 4.4895 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1085 loss: 1.1085 2022/09/05 11:06:48 - mmengine - INFO - Epoch(train) [16][580/940] lr: 1.0000e-02 eta: 14:55:25 time: 0.6475 data_time: 0.0476 memory: 24011 grad_norm: 4.3495 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2730 loss: 1.2730 2022/09/05 11:07:01 - mmengine - INFO - Epoch(train) [16][600/940] lr: 1.0000e-02 eta: 14:55:07 time: 0.6365 data_time: 0.0440 memory: 24011 grad_norm: 4.9568 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4367 loss: 1.4367 2022/09/05 11:07:14 - mmengine - INFO - Epoch(train) [16][620/940] lr: 1.0000e-02 eta: 14:54:51 time: 0.6535 data_time: 0.0377 memory: 24011 grad_norm: 4.5472 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2845 loss: 1.2845 2022/09/05 11:07:27 - mmengine - INFO - Epoch(train) [16][640/940] lr: 1.0000e-02 eta: 14:54:32 time: 0.6270 data_time: 0.0345 memory: 24011 grad_norm: 4.2875 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3669 loss: 1.3669 2022/09/05 11:07:40 - mmengine - INFO - Epoch(train) [16][660/940] lr: 1.0000e-02 eta: 14:54:18 time: 0.6672 data_time: 0.0368 memory: 24011 grad_norm: 4.1559 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2316 loss: 1.2316 2022/09/05 11:07:53 - mmengine - INFO - Epoch(train) [16][680/940] lr: 1.0000e-02 eta: 14:54:01 time: 0.6471 data_time: 0.0367 memory: 24011 grad_norm: 4.5207 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.1788 loss: 1.1788 2022/09/05 11:08:06 - mmengine - INFO - Epoch(train) [16][700/940] lr: 1.0000e-02 eta: 14:53:46 time: 0.6640 data_time: 0.0421 memory: 24011 grad_norm: 4.1891 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3347 loss: 1.3347 2022/09/05 11:08:18 - mmengine - INFO - Epoch(train) [16][720/940] lr: 1.0000e-02 eta: 14:53:26 time: 0.6187 data_time: 0.0381 memory: 24011 grad_norm: 4.1356 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.2983 loss: 1.2983 2022/09/05 11:08:32 - mmengine - INFO - Epoch(train) [16][740/940] lr: 1.0000e-02 eta: 14:53:13 time: 0.6782 data_time: 0.0569 memory: 24011 grad_norm: 4.5033 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2472 loss: 1.2472 2022/09/05 11:08:45 - mmengine - INFO - Epoch(train) [16][760/940] lr: 1.0000e-02 eta: 14:52:55 time: 0.6363 data_time: 0.0306 memory: 24011 grad_norm: 5.6748 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.2586 loss: 1.2586 2022/09/05 11:08:58 - mmengine - INFO - Epoch(train) [16][780/940] lr: 1.0000e-02 eta: 14:52:42 time: 0.6789 data_time: 0.0388 memory: 24011 grad_norm: 4.2534 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1439 loss: 1.1439 2022/09/05 11:09:11 - mmengine - INFO - Epoch(train) [16][800/940] lr: 1.0000e-02 eta: 14:52:22 time: 0.6215 data_time: 0.0380 memory: 24011 grad_norm: 4.5658 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3236 loss: 1.3236 2022/09/05 11:09:24 - mmengine - INFO - Epoch(train) [16][820/940] lr: 1.0000e-02 eta: 14:52:07 time: 0.6574 data_time: 0.0405 memory: 24011 grad_norm: 4.1958 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2119 loss: 1.2119 2022/09/05 11:09:37 - mmengine - INFO - Epoch(train) [16][840/940] lr: 1.0000e-02 eta: 14:51:49 time: 0.6387 data_time: 0.0315 memory: 24011 grad_norm: 4.4328 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3118 loss: 1.3118 2022/09/05 11:09:49 - mmengine - INFO - Epoch(train) [16][860/940] lr: 1.0000e-02 eta: 14:51:31 time: 0.6362 data_time: 0.0399 memory: 24011 grad_norm: 4.1469 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2773 loss: 1.2773 2022/09/05 11:10:02 - mmengine - INFO - Epoch(train) [16][880/940] lr: 1.0000e-02 eta: 14:51:13 time: 0.6336 data_time: 0.0368 memory: 24011 grad_norm: 4.0733 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2447 loss: 1.2447 2022/09/05 11:10:15 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:10:15 - mmengine - INFO - Epoch(train) [16][900/940] lr: 1.0000e-02 eta: 14:50:58 time: 0.6637 data_time: 0.0408 memory: 24011 grad_norm: 4.8001 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1904 loss: 1.1904 2022/09/05 11:10:28 - mmengine - INFO - Epoch(train) [16][920/940] lr: 1.0000e-02 eta: 14:50:39 time: 0.6203 data_time: 0.0345 memory: 24011 grad_norm: 4.1275 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1808 loss: 1.1808 2022/09/05 11:10:39 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:10:39 - mmengine - INFO - Epoch(train) [16][940/940] lr: 1.0000e-02 eta: 14:50:12 time: 0.5552 data_time: 0.0264 memory: 24011 grad_norm: 4.6807 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.3218 loss: 1.3218 2022/09/05 11:10:53 - mmengine - INFO - Epoch(val) [16][20/78] eta: 0:00:40 time: 0.6898 data_time: 0.5320 memory: 3625 2022/09/05 11:11:02 - mmengine - INFO - Epoch(val) [16][40/78] eta: 0:00:18 time: 0.4751 data_time: 0.3185 memory: 3625 2022/09/05 11:11:15 - mmengine - INFO - Epoch(val) [16][60/78] eta: 0:00:11 time: 0.6289 data_time: 0.4644 memory: 3625 2022/09/05 11:11:25 - mmengine - INFO - Epoch(val) [16][78/78] acc/top1: 0.7155 acc/top5: 0.9067 acc/mean1: 0.7154 2022/09/05 11:11:44 - mmengine - INFO - Epoch(train) [17][20/940] lr: 1.0000e-02 eta: 14:50:25 time: 0.9304 data_time: 0.2338 memory: 24011 grad_norm: 5.1233 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2532 loss: 1.2532 2022/09/05 11:11:57 - mmengine - INFO - Epoch(train) [17][40/940] lr: 1.0000e-02 eta: 14:50:06 time: 0.6205 data_time: 0.0324 memory: 24011 grad_norm: 4.3871 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0989 loss: 1.0989 2022/09/05 11:12:11 - mmengine - INFO - Epoch(train) [17][60/940] lr: 1.0000e-02 eta: 14:49:55 time: 0.6990 data_time: 0.0595 memory: 24011 grad_norm: 4.2005 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3586 loss: 1.3586 2022/09/05 11:12:24 - mmengine - INFO - Epoch(train) [17][80/940] lr: 1.0000e-02 eta: 14:49:40 time: 0.6679 data_time: 0.1167 memory: 24011 grad_norm: 4.2844 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2612 loss: 1.2612 2022/09/05 11:12:38 - mmengine - INFO - Epoch(train) [17][100/940] lr: 1.0000e-02 eta: 14:49:27 time: 0.6800 data_time: 0.1292 memory: 24011 grad_norm: 4.0417 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1420 loss: 1.1420 2022/09/05 11:12:50 - mmengine - INFO - Epoch(train) [17][120/940] lr: 1.0000e-02 eta: 14:49:08 time: 0.6202 data_time: 0.0705 memory: 24011 grad_norm: 4.8513 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1396 loss: 1.1396 2022/09/05 11:13:03 - mmengine - INFO - Epoch(train) [17][140/940] lr: 1.0000e-02 eta: 14:48:53 time: 0.6611 data_time: 0.0985 memory: 24011 grad_norm: 4.0319 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1597 loss: 1.1597 2022/09/05 11:13:16 - mmengine - INFO - Epoch(train) [17][160/940] lr: 1.0000e-02 eta: 14:48:34 time: 0.6314 data_time: 0.0557 memory: 24011 grad_norm: 4.4882 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1374 loss: 1.1374 2022/09/05 11:13:29 - mmengine - INFO - Epoch(train) [17][180/940] lr: 1.0000e-02 eta: 14:48:17 time: 0.6403 data_time: 0.0725 memory: 24011 grad_norm: 6.3812 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2220 loss: 1.2220 2022/09/05 11:13:41 - mmengine - INFO - Epoch(train) [17][200/940] lr: 1.0000e-02 eta: 14:47:59 time: 0.6272 data_time: 0.0478 memory: 24011 grad_norm: 4.3095 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2590 loss: 1.2590 2022/09/05 11:13:54 - mmengine - INFO - Epoch(train) [17][220/940] lr: 1.0000e-02 eta: 14:47:43 time: 0.6590 data_time: 0.0926 memory: 24011 grad_norm: 5.2529 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.2912 loss: 1.2912 2022/09/05 11:14:06 - mmengine - INFO - Epoch(train) [17][240/940] lr: 1.0000e-02 eta: 14:47:22 time: 0.6032 data_time: 0.0377 memory: 24011 grad_norm: 4.2371 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3087 loss: 1.3087 2022/09/05 11:14:20 - mmengine - INFO - Epoch(train) [17][260/940] lr: 1.0000e-02 eta: 14:47:09 time: 0.6760 data_time: 0.1111 memory: 24011 grad_norm: 4.3780 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2450 loss: 1.2450 2022/09/05 11:14:33 - mmengine - INFO - Epoch(train) [17][280/940] lr: 1.0000e-02 eta: 14:46:53 time: 0.6532 data_time: 0.0638 memory: 24011 grad_norm: 4.5994 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2654 loss: 1.2654 2022/09/05 11:14:46 - mmengine - INFO - Epoch(train) [17][300/940] lr: 1.0000e-02 eta: 14:46:36 time: 0.6414 data_time: 0.0354 memory: 24011 grad_norm: 4.3545 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3563 loss: 1.3563 2022/09/05 11:14:59 - mmengine - INFO - Epoch(train) [17][320/940] lr: 1.0000e-02 eta: 14:46:20 time: 0.6602 data_time: 0.0364 memory: 24011 grad_norm: 4.1485 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1849 loss: 1.1849 2022/09/05 11:15:12 - mmengine - INFO - Epoch(train) [17][340/940] lr: 1.0000e-02 eta: 14:46:05 time: 0.6623 data_time: 0.0395 memory: 24011 grad_norm: 4.7177 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2035 loss: 1.2035 2022/09/05 11:15:25 - mmengine - INFO - Epoch(train) [17][360/940] lr: 1.0000e-02 eta: 14:45:48 time: 0.6408 data_time: 0.0501 memory: 24011 grad_norm: 4.4543 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1456 loss: 1.1456 2022/09/05 11:15:38 - mmengine - INFO - Epoch(train) [17][380/940] lr: 1.0000e-02 eta: 14:45:31 time: 0.6371 data_time: 0.0515 memory: 24011 grad_norm: 4.3729 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0919 loss: 1.0919 2022/09/05 11:15:51 - mmengine - INFO - Epoch(train) [17][400/940] lr: 1.0000e-02 eta: 14:45:16 time: 0.6683 data_time: 0.0386 memory: 24011 grad_norm: 4.3138 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2731 loss: 1.2731 2022/09/05 11:16:04 - mmengine - INFO - Epoch(train) [17][420/940] lr: 1.0000e-02 eta: 14:45:00 time: 0.6461 data_time: 0.0460 memory: 24011 grad_norm: 4.4525 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2390 loss: 1.2390 2022/09/05 11:16:16 - mmengine - INFO - Epoch(train) [17][440/940] lr: 1.0000e-02 eta: 14:44:40 time: 0.6111 data_time: 0.0301 memory: 24011 grad_norm: 4.5783 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2240 loss: 1.2240 2022/09/05 11:16:29 - mmengine - INFO - Epoch(train) [17][460/940] lr: 1.0000e-02 eta: 14:44:21 time: 0.6250 data_time: 0.0376 memory: 24011 grad_norm: 4.5122 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1814 loss: 1.1814 2022/09/05 11:16:42 - mmengine - INFO - Epoch(train) [17][480/940] lr: 1.0000e-02 eta: 14:44:07 time: 0.6714 data_time: 0.0359 memory: 24011 grad_norm: 4.4242 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1687 loss: 1.1687 2022/09/05 11:16:55 - mmengine - INFO - Epoch(train) [17][500/940] lr: 1.0000e-02 eta: 14:43:50 time: 0.6395 data_time: 0.0415 memory: 24011 grad_norm: 4.8053 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2984 loss: 1.2984 2022/09/05 11:17:08 - mmengine - INFO - Epoch(train) [17][520/940] lr: 1.0000e-02 eta: 14:43:34 time: 0.6555 data_time: 0.0786 memory: 24011 grad_norm: 4.3611 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2290 loss: 1.2290 2022/09/05 11:17:22 - mmengine - INFO - Epoch(train) [17][540/940] lr: 1.0000e-02 eta: 14:43:21 time: 0.6746 data_time: 0.1034 memory: 24011 grad_norm: 4.4641 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1843 loss: 1.1843 2022/09/05 11:17:34 - mmengine - INFO - Epoch(train) [17][560/940] lr: 1.0000e-02 eta: 14:43:00 time: 0.6087 data_time: 0.0276 memory: 24011 grad_norm: 4.7921 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.2562 loss: 1.2562 2022/09/05 11:17:46 - mmengine - INFO - Epoch(train) [17][580/940] lr: 1.0000e-02 eta: 14:42:40 time: 0.6076 data_time: 0.0392 memory: 24011 grad_norm: 4.5405 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2752 loss: 1.2752 2022/09/05 11:17:59 - mmengine - INFO - Epoch(train) [17][600/940] lr: 1.0000e-02 eta: 14:42:22 time: 0.6299 data_time: 0.0559 memory: 24011 grad_norm: 4.4720 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.3849 loss: 1.3849 2022/09/05 11:18:12 - mmengine - INFO - Epoch(train) [17][620/940] lr: 1.0000e-02 eta: 14:42:07 time: 0.6613 data_time: 0.1001 memory: 24011 grad_norm: 4.7771 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1447 loss: 1.1447 2022/09/05 11:18:24 - mmengine - INFO - Epoch(train) [17][640/940] lr: 1.0000e-02 eta: 14:41:49 time: 0.6289 data_time: 0.0376 memory: 24011 grad_norm: 4.6197 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1158 loss: 1.1158 2022/09/05 11:18:39 - mmengine - INFO - Epoch(train) [17][660/940] lr: 1.0000e-02 eta: 14:41:39 time: 0.7111 data_time: 0.0447 memory: 24011 grad_norm: 4.5443 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2161 loss: 1.2161 2022/09/05 11:18:51 - mmengine - INFO - Epoch(train) [17][680/940] lr: 1.0000e-02 eta: 14:41:20 time: 0.6217 data_time: 0.0332 memory: 24011 grad_norm: 4.4286 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3441 loss: 1.3441 2022/09/05 11:19:04 - mmengine - INFO - Epoch(train) [17][700/940] lr: 1.0000e-02 eta: 14:41:04 time: 0.6548 data_time: 0.0524 memory: 24011 grad_norm: 4.2289 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3660 loss: 1.3660 2022/09/05 11:19:17 - mmengine - INFO - Epoch(train) [17][720/940] lr: 1.0000e-02 eta: 14:40:48 time: 0.6463 data_time: 0.0409 memory: 24011 grad_norm: 4.1430 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2203 loss: 1.2203 2022/09/05 11:19:30 - mmengine - INFO - Epoch(train) [17][740/940] lr: 1.0000e-02 eta: 14:40:33 time: 0.6602 data_time: 0.0365 memory: 24011 grad_norm: 4.0423 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2426 loss: 1.2426 2022/09/05 11:19:43 - mmengine - INFO - Epoch(train) [17][760/940] lr: 1.0000e-02 eta: 14:40:14 time: 0.6228 data_time: 0.0530 memory: 24011 grad_norm: 4.3813 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2850 loss: 1.2850 2022/09/05 11:19:56 - mmengine - INFO - Epoch(train) [17][780/940] lr: 1.0000e-02 eta: 14:40:01 time: 0.6734 data_time: 0.0430 memory: 24011 grad_norm: 4.1614 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3165 loss: 1.3165 2022/09/05 11:20:09 - mmengine - INFO - Epoch(train) [17][800/940] lr: 1.0000e-02 eta: 14:39:46 time: 0.6604 data_time: 0.0419 memory: 24011 grad_norm: 4.3757 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2084 loss: 1.2084 2022/09/05 11:20:22 - mmengine - INFO - Epoch(train) [17][820/940] lr: 1.0000e-02 eta: 14:39:27 time: 0.6273 data_time: 0.0602 memory: 24011 grad_norm: 4.0624 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1292 loss: 1.1292 2022/09/05 11:20:35 - mmengine - INFO - Epoch(train) [17][840/940] lr: 1.0000e-02 eta: 14:39:12 time: 0.6618 data_time: 0.0411 memory: 24011 grad_norm: 4.4943 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2446 loss: 1.2446 2022/09/05 11:20:48 - mmengine - INFO - Epoch(train) [17][860/940] lr: 1.0000e-02 eta: 14:38:57 time: 0.6580 data_time: 0.0379 memory: 24011 grad_norm: 4.6260 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3964 loss: 1.3964 2022/09/05 11:21:02 - mmengine - INFO - Epoch(train) [17][880/940] lr: 1.0000e-02 eta: 14:38:44 time: 0.6729 data_time: 0.0348 memory: 24011 grad_norm: 4.5360 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4022 loss: 1.4022 2022/09/05 11:21:15 - mmengine - INFO - Epoch(train) [17][900/940] lr: 1.0000e-02 eta: 14:38:27 time: 0.6468 data_time: 0.0402 memory: 24011 grad_norm: 4.1924 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3981 loss: 1.3981 2022/09/05 11:21:28 - mmengine - INFO - Epoch(train) [17][920/940] lr: 1.0000e-02 eta: 14:38:10 time: 0.6368 data_time: 0.0410 memory: 24011 grad_norm: 5.4100 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2512 loss: 1.2512 2022/09/05 11:21:39 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:21:39 - mmengine - INFO - Epoch(train) [17][940/940] lr: 1.0000e-02 eta: 14:37:47 time: 0.5831 data_time: 0.0272 memory: 24011 grad_norm: 4.7493 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.5320 loss: 1.5320 2022/09/05 11:21:53 - mmengine - INFO - Epoch(val) [17][20/78] eta: 0:00:39 time: 0.6890 data_time: 0.5293 memory: 3625 2022/09/05 11:22:02 - mmengine - INFO - Epoch(val) [17][40/78] eta: 0:00:17 time: 0.4559 data_time: 0.2983 memory: 3625 2022/09/05 11:22:15 - mmengine - INFO - Epoch(val) [17][60/78] eta: 0:00:11 time: 0.6414 data_time: 0.4863 memory: 3625 2022/09/05 11:22:25 - mmengine - INFO - Epoch(val) [17][78/78] acc/top1: 0.7131 acc/top5: 0.9041 acc/mean1: 0.7129 2022/09/05 11:22:43 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:22:43 - mmengine - INFO - Epoch(train) [18][20/940] lr: 1.0000e-02 eta: 14:37:54 time: 0.8850 data_time: 0.2818 memory: 24011 grad_norm: 4.5433 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.3768 loss: 1.3768 2022/09/05 11:22:56 - mmengine - INFO - Epoch(train) [18][40/940] lr: 1.0000e-02 eta: 14:37:39 time: 0.6590 data_time: 0.0400 memory: 24011 grad_norm: 4.4676 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3151 loss: 1.3151 2022/09/05 11:23:10 - mmengine - INFO - Epoch(train) [18][60/940] lr: 1.0000e-02 eta: 14:37:24 time: 0.6545 data_time: 0.0400 memory: 24011 grad_norm: 4.0593 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1898 loss: 1.1898 2022/09/05 11:23:22 - mmengine - INFO - Epoch(train) [18][80/940] lr: 1.0000e-02 eta: 14:37:06 time: 0.6311 data_time: 0.0393 memory: 24011 grad_norm: 5.2547 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2224 loss: 1.2224 2022/09/05 11:23:36 - mmengine - INFO - Epoch(train) [18][100/940] lr: 1.0000e-02 eta: 14:36:57 time: 0.7186 data_time: 0.0408 memory: 24011 grad_norm: 4.5253 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2532 loss: 1.2532 2022/09/05 11:23:49 - mmengine - INFO - Epoch(train) [18][120/940] lr: 1.0000e-02 eta: 14:36:38 time: 0.6196 data_time: 0.0335 memory: 24011 grad_norm: 4.1341 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1700 loss: 1.1700 2022/09/05 11:24:02 - mmengine - INFO - Epoch(train) [18][140/940] lr: 1.0000e-02 eta: 14:36:23 time: 0.6579 data_time: 0.0378 memory: 24011 grad_norm: 4.3171 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2300 loss: 1.2300 2022/09/05 11:24:15 - mmengine - INFO - Epoch(train) [18][160/940] lr: 1.0000e-02 eta: 14:36:06 time: 0.6459 data_time: 0.0405 memory: 24011 grad_norm: 5.2818 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3049 loss: 1.3049 2022/09/05 11:24:28 - mmengine - INFO - Epoch(train) [18][180/940] lr: 1.0000e-02 eta: 14:35:51 time: 0.6582 data_time: 0.0459 memory: 24011 grad_norm: 4.9357 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3889 loss: 1.3889 2022/09/05 11:24:41 - mmengine - INFO - Epoch(train) [18][200/940] lr: 1.0000e-02 eta: 14:35:34 time: 0.6355 data_time: 0.0407 memory: 24011 grad_norm: 4.6237 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2980 loss: 1.2980 2022/09/05 11:24:54 - mmengine - INFO - Epoch(train) [18][220/940] lr: 1.0000e-02 eta: 14:35:20 time: 0.6732 data_time: 0.0423 memory: 24011 grad_norm: 4.4246 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2726 loss: 1.2726 2022/09/05 11:25:07 - mmengine - INFO - Epoch(train) [18][240/940] lr: 1.0000e-02 eta: 14:35:02 time: 0.6239 data_time: 0.0459 memory: 24011 grad_norm: 4.2726 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3023 loss: 1.3023 2022/09/05 11:25:20 - mmengine - INFO - Epoch(train) [18][260/940] lr: 1.0000e-02 eta: 14:34:49 time: 0.6827 data_time: 0.0379 memory: 24011 grad_norm: 4.5540 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2402 loss: 1.2402 2022/09/05 11:25:34 - mmengine - INFO - Epoch(train) [18][280/940] lr: 1.0000e-02 eta: 14:34:34 time: 0.6616 data_time: 0.0410 memory: 24011 grad_norm: 4.4218 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1182 loss: 1.1182 2022/09/05 11:25:46 - mmengine - INFO - Epoch(train) [18][300/940] lr: 1.0000e-02 eta: 14:34:16 time: 0.6253 data_time: 0.0400 memory: 24011 grad_norm: 4.6602 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2251 loss: 1.2251 2022/09/05 11:25:58 - mmengine - INFO - Epoch(train) [18][320/940] lr: 1.0000e-02 eta: 14:33:55 time: 0.5974 data_time: 0.0440 memory: 24011 grad_norm: 4.7732 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.3456 loss: 1.3456 2022/09/05 11:26:11 - mmengine - INFO - Epoch(train) [18][340/940] lr: 1.0000e-02 eta: 14:33:38 time: 0.6406 data_time: 0.0392 memory: 24011 grad_norm: 4.4141 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2615 loss: 1.2615 2022/09/05 11:26:24 - mmengine - INFO - Epoch(train) [18][360/940] lr: 1.0000e-02 eta: 14:33:24 time: 0.6611 data_time: 0.0440 memory: 24011 grad_norm: 5.3464 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2286 loss: 1.2286 2022/09/05 11:26:37 - mmengine - INFO - Epoch(train) [18][380/940] lr: 1.0000e-02 eta: 14:33:08 time: 0.6486 data_time: 0.0368 memory: 24011 grad_norm: 4.8345 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3986 loss: 1.3986 2022/09/05 11:26:50 - mmengine - INFO - Epoch(train) [18][400/940] lr: 1.0000e-02 eta: 14:32:50 time: 0.6328 data_time: 0.0404 memory: 24011 grad_norm: 4.6913 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1723 loss: 1.1723 2022/09/05 11:27:04 - mmengine - INFO - Epoch(train) [18][420/940] lr: 1.0000e-02 eta: 14:32:39 time: 0.6973 data_time: 0.0607 memory: 24011 grad_norm: 4.4658 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3172 loss: 1.3172 2022/09/05 11:27:17 - mmengine - INFO - Epoch(train) [18][440/940] lr: 1.0000e-02 eta: 14:32:23 time: 0.6537 data_time: 0.0360 memory: 24011 grad_norm: 4.2295 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0906 loss: 1.0906 2022/09/05 11:27:30 - mmengine - INFO - Epoch(train) [18][460/940] lr: 1.0000e-02 eta: 14:32:07 time: 0.6417 data_time: 0.0412 memory: 24011 grad_norm: 4.4259 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1263 loss: 1.1263 2022/09/05 11:27:43 - mmengine - INFO - Epoch(train) [18][480/940] lr: 1.0000e-02 eta: 14:31:50 time: 0.6432 data_time: 0.0421 memory: 24011 grad_norm: 4.4602 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1697 loss: 1.1697 2022/09/05 11:27:56 - mmengine - INFO - Epoch(train) [18][500/940] lr: 1.0000e-02 eta: 14:31:37 time: 0.6825 data_time: 0.0333 memory: 24011 grad_norm: 4.6568 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2693 loss: 1.2693 2022/09/05 11:28:08 - mmengine - INFO - Epoch(train) [18][520/940] lr: 1.0000e-02 eta: 14:31:17 time: 0.6014 data_time: 0.0456 memory: 24011 grad_norm: 4.4712 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2671 loss: 1.2671 2022/09/05 11:28:21 - mmengine - INFO - Epoch(train) [18][540/940] lr: 1.0000e-02 eta: 14:31:02 time: 0.6592 data_time: 0.0474 memory: 24011 grad_norm: 4.6165 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2138 loss: 1.2138 2022/09/05 11:28:34 - mmengine - INFO - Epoch(train) [18][560/940] lr: 1.0000e-02 eta: 14:30:46 time: 0.6458 data_time: 0.0461 memory: 24011 grad_norm: 5.1261 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1403 loss: 1.1403 2022/09/05 11:28:47 - mmengine - INFO - Epoch(train) [18][580/940] lr: 1.0000e-02 eta: 14:30:31 time: 0.6551 data_time: 0.0403 memory: 24011 grad_norm: 4.9616 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2763 loss: 1.2763 2022/09/05 11:29:00 - mmengine - INFO - Epoch(train) [18][600/940] lr: 1.0000e-02 eta: 14:30:11 time: 0.6034 data_time: 0.0406 memory: 24011 grad_norm: 4.4180 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.4516 loss: 1.4516 2022/09/05 11:29:13 - mmengine - INFO - Epoch(train) [18][620/940] lr: 1.0000e-02 eta: 14:29:59 time: 0.6947 data_time: 0.0365 memory: 24011 grad_norm: 4.7529 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3106 loss: 1.3106 2022/09/05 11:29:27 - mmengine - INFO - Epoch(train) [18][640/940] lr: 1.0000e-02 eta: 14:29:44 time: 0.6577 data_time: 0.0366 memory: 24011 grad_norm: 5.0504 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3498 loss: 1.3498 2022/09/05 11:29:39 - mmengine - INFO - Epoch(train) [18][660/940] lr: 1.0000e-02 eta: 14:29:27 time: 0.6342 data_time: 0.0398 memory: 24011 grad_norm: 5.0077 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.2218 loss: 1.2218 2022/09/05 11:29:52 - mmengine - INFO - Epoch(train) [18][680/940] lr: 1.0000e-02 eta: 14:29:09 time: 0.6245 data_time: 0.0402 memory: 24011 grad_norm: 5.0694 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2537 loss: 1.2537 2022/09/05 11:30:05 - mmengine - INFO - Epoch(train) [18][700/940] lr: 1.0000e-02 eta: 14:28:53 time: 0.6499 data_time: 0.0355 memory: 24011 grad_norm: 4.3832 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3598 loss: 1.3598 2022/09/05 11:30:17 - mmengine - INFO - Epoch(train) [18][720/940] lr: 1.0000e-02 eta: 14:28:36 time: 0.6353 data_time: 0.0364 memory: 24011 grad_norm: 4.4500 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1181 loss: 1.1181 2022/09/05 11:30:31 - mmengine - INFO - Epoch(train) [18][740/940] lr: 1.0000e-02 eta: 14:28:21 time: 0.6620 data_time: 0.0371 memory: 24011 grad_norm: 4.2264 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3348 loss: 1.3348 2022/09/05 11:30:43 - mmengine - INFO - Epoch(train) [18][760/940] lr: 1.0000e-02 eta: 14:28:04 time: 0.6305 data_time: 0.0539 memory: 24011 grad_norm: 4.2078 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2496 loss: 1.2496 2022/09/05 11:30:56 - mmengine - INFO - Epoch(train) [18][780/940] lr: 1.0000e-02 eta: 14:27:49 time: 0.6578 data_time: 0.0424 memory: 24011 grad_norm: 4.1270 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2386 loss: 1.2386 2022/09/05 11:31:09 - mmengine - INFO - Epoch(train) [18][800/940] lr: 1.0000e-02 eta: 14:27:33 time: 0.6488 data_time: 0.0390 memory: 24011 grad_norm: 4.1658 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3043 loss: 1.3043 2022/09/05 11:31:23 - mmengine - INFO - Epoch(train) [18][820/940] lr: 1.0000e-02 eta: 14:27:18 time: 0.6575 data_time: 0.0417 memory: 24011 grad_norm: 4.0622 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1638 loss: 1.1638 2022/09/05 11:31:35 - mmengine - INFO - Epoch(train) [18][840/940] lr: 1.0000e-02 eta: 14:26:59 time: 0.6174 data_time: 0.0565 memory: 24011 grad_norm: 4.0972 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1470 loss: 1.1470 2022/09/05 11:31:48 - mmengine - INFO - Epoch(train) [18][860/940] lr: 1.0000e-02 eta: 14:26:45 time: 0.6677 data_time: 0.0381 memory: 24011 grad_norm: 4.2564 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3630 loss: 1.3630 2022/09/05 11:32:02 - mmengine - INFO - Epoch(train) [18][880/940] lr: 1.0000e-02 eta: 14:26:33 time: 0.6866 data_time: 0.0341 memory: 24011 grad_norm: 4.0144 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1794 loss: 1.1794 2022/09/05 11:32:14 - mmengine - INFO - Epoch(train) [18][900/940] lr: 1.0000e-02 eta: 14:26:14 time: 0.6195 data_time: 0.0585 memory: 24011 grad_norm: 4.5327 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0946 loss: 1.0946 2022/09/05 11:32:27 - mmengine - INFO - Epoch(train) [18][920/940] lr: 1.0000e-02 eta: 14:25:56 time: 0.6268 data_time: 0.0385 memory: 24011 grad_norm: 4.7453 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2754 loss: 1.2754 2022/09/05 11:32:38 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:32:38 - mmengine - INFO - Epoch(train) [18][940/940] lr: 1.0000e-02 eta: 14:25:33 time: 0.5668 data_time: 0.0426 memory: 24011 grad_norm: 4.7690 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.3011 loss: 1.3011 2022/09/05 11:32:38 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/09/05 11:32:58 - mmengine - INFO - Epoch(val) [18][20/78] eta: 0:00:40 time: 0.7036 data_time: 0.5415 memory: 3625 2022/09/05 11:33:08 - mmengine - INFO - Epoch(val) [18][40/78] eta: 0:00:18 time: 0.4775 data_time: 0.3210 memory: 3625 2022/09/05 11:33:20 - mmengine - INFO - Epoch(val) [18][60/78] eta: 0:00:11 time: 0.6368 data_time: 0.4832 memory: 3625 2022/09/05 11:33:29 - mmengine - INFO - Epoch(val) [18][78/78] acc/top1: 0.7138 acc/top5: 0.9012 acc/mean1: 0.7137 2022/09/05 11:33:48 - mmengine - INFO - Epoch(train) [19][20/940] lr: 1.0000e-02 eta: 14:25:42 time: 0.9182 data_time: 0.2676 memory: 24011 grad_norm: 4.0970 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1328 loss: 1.1328 2022/09/05 11:34:00 - mmengine - INFO - Epoch(train) [19][40/940] lr: 1.0000e-02 eta: 14:25:25 time: 0.6407 data_time: 0.0525 memory: 24011 grad_norm: 4.0611 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1963 loss: 1.1963 2022/09/05 11:34:14 - mmengine - INFO - Epoch(train) [19][60/940] lr: 1.0000e-02 eta: 14:25:12 time: 0.6715 data_time: 0.0368 memory: 24011 grad_norm: 4.0937 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0278 loss: 1.0278 2022/09/05 11:34:27 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:34:27 - mmengine - INFO - Epoch(train) [19][80/940] lr: 1.0000e-02 eta: 14:24:56 time: 0.6469 data_time: 0.0311 memory: 24011 grad_norm: 4.1068 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1464 loss: 1.1464 2022/09/05 11:34:39 - mmengine - INFO - Epoch(train) [19][100/940] lr: 1.0000e-02 eta: 14:24:37 time: 0.6170 data_time: 0.0404 memory: 24011 grad_norm: 4.2940 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2849 loss: 1.2849 2022/09/05 11:34:52 - mmengine - INFO - Epoch(train) [19][120/940] lr: 1.0000e-02 eta: 14:24:23 time: 0.6682 data_time: 0.0685 memory: 24011 grad_norm: 4.2635 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1407 loss: 1.1407 2022/09/05 11:35:05 - mmengine - INFO - Epoch(train) [19][140/940] lr: 1.0000e-02 eta: 14:24:07 time: 0.6480 data_time: 0.0754 memory: 24011 grad_norm: 4.1214 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2625 loss: 1.2625 2022/09/05 11:35:18 - mmengine - INFO - Epoch(train) [19][160/940] lr: 1.0000e-02 eta: 14:23:53 time: 0.6589 data_time: 0.0499 memory: 24011 grad_norm: 4.5225 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1293 loss: 1.1293 2022/09/05 11:35:31 - mmengine - INFO - Epoch(train) [19][180/940] lr: 1.0000e-02 eta: 14:23:36 time: 0.6437 data_time: 0.0430 memory: 24011 grad_norm: 4.0729 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2930 loss: 1.2930 2022/09/05 11:35:44 - mmengine - INFO - Epoch(train) [19][200/940] lr: 1.0000e-02 eta: 14:23:21 time: 0.6536 data_time: 0.0365 memory: 24011 grad_norm: 4.0474 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 1.2087 loss: 1.2087 2022/09/05 11:35:57 - mmengine - INFO - Epoch(train) [19][220/940] lr: 1.0000e-02 eta: 14:23:04 time: 0.6385 data_time: 0.0355 memory: 24011 grad_norm: 3.9524 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1505 loss: 1.1505 2022/09/05 11:36:10 - mmengine - INFO - Epoch(train) [19][240/940] lr: 1.0000e-02 eta: 14:22:48 time: 0.6415 data_time: 0.0386 memory: 24011 grad_norm: 4.4079 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0515 loss: 1.0515 2022/09/05 11:36:23 - mmengine - INFO - Epoch(train) [19][260/940] lr: 1.0000e-02 eta: 14:22:32 time: 0.6465 data_time: 0.0643 memory: 24011 grad_norm: 4.2165 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1011 loss: 1.1011 2022/09/05 11:36:36 - mmengine - INFO - Epoch(train) [19][280/940] lr: 1.0000e-02 eta: 14:22:16 time: 0.6410 data_time: 0.0850 memory: 24011 grad_norm: 4.9586 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.1987 loss: 1.1987 2022/09/05 11:36:49 - mmengine - INFO - Epoch(train) [19][300/940] lr: 1.0000e-02 eta: 14:22:00 time: 0.6438 data_time: 0.0561 memory: 24011 grad_norm: 6.3114 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3304 loss: 1.3304 2022/09/05 11:37:01 - mmengine - INFO - Epoch(train) [19][320/940] lr: 1.0000e-02 eta: 14:21:44 time: 0.6453 data_time: 0.0307 memory: 24011 grad_norm: 4.6169 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2624 loss: 1.2624 2022/09/05 11:37:15 - mmengine - INFO - Epoch(train) [19][340/940] lr: 1.0000e-02 eta: 14:21:30 time: 0.6706 data_time: 0.0388 memory: 24011 grad_norm: 4.4628 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2317 loss: 1.2317 2022/09/05 11:37:27 - mmengine - INFO - Epoch(train) [19][360/940] lr: 1.0000e-02 eta: 14:21:10 time: 0.6057 data_time: 0.0334 memory: 24011 grad_norm: 4.2958 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.2566 loss: 1.2566 2022/09/05 11:37:40 - mmengine - INFO - Epoch(train) [19][380/940] lr: 1.0000e-02 eta: 14:20:56 time: 0.6598 data_time: 0.0404 memory: 24011 grad_norm: 4.2019 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0724 loss: 1.0724 2022/09/05 11:37:53 - mmengine - INFO - Epoch(train) [19][400/940] lr: 1.0000e-02 eta: 14:20:40 time: 0.6424 data_time: 0.0311 memory: 24011 grad_norm: 4.4004 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1407 loss: 1.1407 2022/09/05 11:38:07 - mmengine - INFO - Epoch(train) [19][420/940] lr: 1.0000e-02 eta: 14:20:27 time: 0.6825 data_time: 0.0436 memory: 24011 grad_norm: 4.3695 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2280 loss: 1.2280 2022/09/05 11:38:19 - mmengine - INFO - Epoch(train) [19][440/940] lr: 1.0000e-02 eta: 14:20:10 time: 0.6303 data_time: 0.0327 memory: 24011 grad_norm: 4.2564 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.1304 loss: 1.1304 2022/09/05 11:38:33 - mmengine - INFO - Epoch(train) [19][460/940] lr: 1.0000e-02 eta: 14:19:55 time: 0.6629 data_time: 0.0908 memory: 24011 grad_norm: 4.6124 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0935 loss: 1.0935 2022/09/05 11:38:45 - mmengine - INFO - Epoch(train) [19][480/940] lr: 1.0000e-02 eta: 14:19:38 time: 0.6339 data_time: 0.0721 memory: 24011 grad_norm: 3.9853 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1444 loss: 1.1444 2022/09/05 11:38:59 - mmengine - INFO - Epoch(train) [19][500/940] lr: 1.0000e-02 eta: 14:19:27 time: 0.6951 data_time: 0.1057 memory: 24011 grad_norm: 4.3173 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2278 loss: 1.2278 2022/09/05 11:39:12 - mmengine - INFO - Epoch(train) [19][520/940] lr: 1.0000e-02 eta: 14:19:10 time: 0.6353 data_time: 0.0686 memory: 24011 grad_norm: 4.0273 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1485 loss: 1.1485 2022/09/05 11:39:24 - mmengine - INFO - Epoch(train) [19][540/940] lr: 1.0000e-02 eta: 14:18:52 time: 0.6261 data_time: 0.0397 memory: 24011 grad_norm: 4.1972 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2716 loss: 1.2716 2022/09/05 11:39:38 - mmengine - INFO - Epoch(train) [19][560/940] lr: 1.0000e-02 eta: 14:18:38 time: 0.6683 data_time: 0.0688 memory: 24011 grad_norm: 4.4027 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2712 loss: 1.2712 2022/09/05 11:39:51 - mmengine - INFO - Epoch(train) [19][580/940] lr: 1.0000e-02 eta: 14:18:24 time: 0.6612 data_time: 0.0398 memory: 24011 grad_norm: 4.0025 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1281 loss: 1.1281 2022/09/05 11:40:03 - mmengine - INFO - Epoch(train) [19][600/940] lr: 1.0000e-02 eta: 14:18:05 time: 0.6092 data_time: 0.0314 memory: 24011 grad_norm: 4.3597 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1976 loss: 1.1976 2022/09/05 11:40:16 - mmengine - INFO - Epoch(train) [19][620/940] lr: 1.0000e-02 eta: 14:17:49 time: 0.6483 data_time: 0.0459 memory: 24011 grad_norm: 4.0763 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3103 loss: 1.3103 2022/09/05 11:40:29 - mmengine - INFO - Epoch(train) [19][640/940] lr: 1.0000e-02 eta: 14:17:34 time: 0.6536 data_time: 0.0329 memory: 24011 grad_norm: 4.2426 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2828 loss: 1.2828 2022/09/05 11:40:43 - mmengine - INFO - Epoch(train) [19][660/940] lr: 1.0000e-02 eta: 14:17:21 time: 0.6817 data_time: 0.0345 memory: 24011 grad_norm: 6.7891 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4091 loss: 1.4091 2022/09/05 11:40:55 - mmengine - INFO - Epoch(train) [19][680/940] lr: 1.0000e-02 eta: 14:17:02 time: 0.6098 data_time: 0.0480 memory: 24011 grad_norm: 4.6369 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2468 loss: 1.2468 2022/09/05 11:41:07 - mmengine - INFO - Epoch(train) [19][700/940] lr: 1.0000e-02 eta: 14:16:44 time: 0.6143 data_time: 0.0385 memory: 24011 grad_norm: 4.3455 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3279 loss: 1.3279 2022/09/05 11:41:21 - mmengine - INFO - Epoch(train) [19][720/940] lr: 1.0000e-02 eta: 14:16:32 time: 0.6933 data_time: 0.0401 memory: 24011 grad_norm: 4.6933 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2756 loss: 1.2756 2022/09/05 11:41:35 - mmengine - INFO - Epoch(train) [19][740/940] lr: 1.0000e-02 eta: 14:16:19 time: 0.6813 data_time: 0.0419 memory: 24011 grad_norm: 4.0386 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3042 loss: 1.3042 2022/09/05 11:41:48 - mmengine - INFO - Epoch(train) [19][760/940] lr: 1.0000e-02 eta: 14:16:06 time: 0.6738 data_time: 0.0358 memory: 24011 grad_norm: 4.3941 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2333 loss: 1.2333 2022/09/05 11:42:02 - mmengine - INFO - Epoch(train) [19][780/940] lr: 1.0000e-02 eta: 14:15:52 time: 0.6712 data_time: 0.0401 memory: 24011 grad_norm: 4.4544 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.2347 loss: 1.2347 2022/09/05 11:42:16 - mmengine - INFO - Epoch(train) [19][800/940] lr: 1.0000e-02 eta: 14:15:41 time: 0.6965 data_time: 0.0386 memory: 24011 grad_norm: 4.3897 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.3636 loss: 1.3636 2022/09/05 11:42:29 - mmengine - INFO - Epoch(train) [19][820/940] lr: 1.0000e-02 eta: 14:15:28 time: 0.6751 data_time: 0.0571 memory: 24011 grad_norm: 4.2130 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3420 loss: 1.3420 2022/09/05 11:42:44 - mmengine - INFO - Epoch(train) [19][840/940] lr: 1.0000e-02 eta: 14:15:20 time: 0.7407 data_time: 0.0338 memory: 24011 grad_norm: 4.1656 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1943 loss: 1.1943 2022/09/05 11:42:58 - mmengine - INFO - Epoch(train) [19][860/940] lr: 1.0000e-02 eta: 14:15:07 time: 0.6777 data_time: 0.0431 memory: 24011 grad_norm: 4.0012 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1469 loss: 1.1469 2022/09/05 11:43:10 - mmengine - INFO - Epoch(train) [19][880/940] lr: 1.0000e-02 eta: 14:14:48 time: 0.6053 data_time: 0.0457 memory: 24011 grad_norm: 3.9989 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1334 loss: 1.1334 2022/09/05 11:43:23 - mmengine - INFO - Epoch(train) [19][900/940] lr: 1.0000e-02 eta: 14:14:34 time: 0.6768 data_time: 0.0412 memory: 24011 grad_norm: 4.2599 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1827 loss: 1.1827 2022/09/05 11:43:36 - mmengine - INFO - Epoch(train) [19][920/940] lr: 1.0000e-02 eta: 14:14:18 time: 0.6392 data_time: 0.0426 memory: 24011 grad_norm: 4.2350 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3187 loss: 1.3187 2022/09/05 11:43:48 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:43:48 - mmengine - INFO - Epoch(train) [19][940/940] lr: 1.0000e-02 eta: 14:13:57 time: 0.5812 data_time: 0.0276 memory: 24011 grad_norm: 4.5278 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1329 loss: 1.1329 2022/09/05 11:44:02 - mmengine - INFO - Epoch(val) [19][20/78] eta: 0:00:42 time: 0.7252 data_time: 0.5641 memory: 3625 2022/09/05 11:44:11 - mmengine - INFO - Epoch(val) [19][40/78] eta: 0:00:16 time: 0.4434 data_time: 0.2887 memory: 3625 2022/09/05 11:44:24 - mmengine - INFO - Epoch(val) [19][60/78] eta: 0:00:11 time: 0.6478 data_time: 0.4840 memory: 3625 2022/09/05 11:44:35 - mmengine - INFO - Epoch(val) [19][78/78] acc/top1: 0.7153 acc/top5: 0.9042 acc/mean1: 0.7151 2022/09/05 11:44:53 - mmengine - INFO - Epoch(train) [20][20/940] lr: 1.0000e-02 eta: 14:14:04 time: 0.9192 data_time: 0.2837 memory: 24011 grad_norm: 4.5097 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2221 loss: 1.2221 2022/09/05 11:45:06 - mmengine - INFO - Epoch(train) [20][40/940] lr: 1.0000e-02 eta: 14:13:49 time: 0.6530 data_time: 0.0452 memory: 24011 grad_norm: 4.1804 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0611 loss: 1.0611 2022/09/05 11:45:20 - mmengine - INFO - Epoch(train) [20][60/940] lr: 1.0000e-02 eta: 14:13:36 time: 0.6756 data_time: 0.0707 memory: 24011 grad_norm: 4.7831 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1832 loss: 1.1832 2022/09/05 11:45:33 - mmengine - INFO - Epoch(train) [20][80/940] lr: 1.0000e-02 eta: 14:13:22 time: 0.6688 data_time: 0.0331 memory: 24011 grad_norm: 4.3395 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1640 loss: 1.1640 2022/09/05 11:45:46 - mmengine - INFO - Epoch(train) [20][100/940] lr: 1.0000e-02 eta: 14:13:06 time: 0.6469 data_time: 0.0410 memory: 24011 grad_norm: 4.2572 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1593 loss: 1.1593 2022/09/05 11:45:59 - mmengine - INFO - Epoch(train) [20][120/940] lr: 1.0000e-02 eta: 14:12:51 time: 0.6470 data_time: 0.0316 memory: 24011 grad_norm: 4.2204 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2160 loss: 1.2160 2022/09/05 11:46:13 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:46:13 - mmengine - INFO - Epoch(train) [20][140/940] lr: 1.0000e-02 eta: 14:12:38 time: 0.6815 data_time: 0.0620 memory: 24011 grad_norm: 4.3274 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2363 loss: 1.2363 2022/09/05 11:46:26 - mmengine - INFO - Epoch(train) [20][160/940] lr: 1.0000e-02 eta: 14:12:23 time: 0.6545 data_time: 0.0366 memory: 24011 grad_norm: 4.2292 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1042 loss: 1.1042 2022/09/05 11:46:39 - mmengine - INFO - Epoch(train) [20][180/940] lr: 1.0000e-02 eta: 14:12:10 time: 0.6817 data_time: 0.0437 memory: 24011 grad_norm: 4.0491 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1949 loss: 1.1949 2022/09/05 11:46:52 - mmengine - INFO - Epoch(train) [20][200/940] lr: 1.0000e-02 eta: 14:11:52 time: 0.6215 data_time: 0.0385 memory: 24011 grad_norm: 4.2858 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1636 loss: 1.1636 2022/09/05 11:47:04 - mmengine - INFO - Epoch(train) [20][220/940] lr: 1.0000e-02 eta: 14:11:34 time: 0.6193 data_time: 0.0389 memory: 24011 grad_norm: 4.9008 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1297 loss: 1.1297 2022/09/05 11:47:17 - mmengine - INFO - Epoch(train) [20][240/940] lr: 1.0000e-02 eta: 14:11:19 time: 0.6489 data_time: 0.0414 memory: 24011 grad_norm: 4.4798 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1022 loss: 1.1022 2022/09/05 11:47:31 - mmengine - INFO - Epoch(train) [20][260/940] lr: 1.0000e-02 eta: 14:11:07 time: 0.6913 data_time: 0.0417 memory: 24011 grad_norm: 4.4032 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0570 loss: 1.0570 2022/09/05 11:47:43 - mmengine - INFO - Epoch(train) [20][280/940] lr: 1.0000e-02 eta: 14:10:48 time: 0.6067 data_time: 0.0414 memory: 24011 grad_norm: 4.2210 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.2068 loss: 1.2068 2022/09/05 11:47:56 - mmengine - INFO - Epoch(train) [20][300/940] lr: 1.0000e-02 eta: 14:10:33 time: 0.6542 data_time: 0.0414 memory: 24011 grad_norm: 4.4946 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1550 loss: 1.1550 2022/09/05 11:48:10 - mmengine - INFO - Epoch(train) [20][320/940] lr: 1.0000e-02 eta: 14:10:19 time: 0.6628 data_time: 0.0435 memory: 24011 grad_norm: 4.2773 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2477 loss: 1.2477 2022/09/05 11:48:23 - mmengine - INFO - Epoch(train) [20][340/940] lr: 1.0000e-02 eta: 14:10:06 time: 0.6835 data_time: 0.0448 memory: 24011 grad_norm: 5.7932 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2001 loss: 1.2001 2022/09/05 11:48:35 - mmengine - INFO - Epoch(train) [20][360/940] lr: 1.0000e-02 eta: 14:09:46 time: 0.5946 data_time: 0.0449 memory: 24011 grad_norm: 5.0927 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2663 loss: 1.2663 2022/09/05 11:48:48 - mmengine - INFO - Epoch(train) [20][380/940] lr: 1.0000e-02 eta: 14:09:30 time: 0.6409 data_time: 0.0376 memory: 24011 grad_norm: 4.3467 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.1899 loss: 1.1899 2022/09/05 11:49:00 - mmengine - INFO - Epoch(train) [20][400/940] lr: 1.0000e-02 eta: 14:09:12 time: 0.6241 data_time: 0.0435 memory: 24011 grad_norm: 4.4061 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.1391 loss: 1.1391 2022/09/05 11:49:14 - mmengine - INFO - Epoch(train) [20][420/940] lr: 1.0000e-02 eta: 14:08:59 time: 0.6727 data_time: 0.0394 memory: 24011 grad_norm: 4.5183 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1571 loss: 1.1571 2022/09/05 11:49:26 - mmengine - INFO - Epoch(train) [20][440/940] lr: 1.0000e-02 eta: 14:08:41 time: 0.6201 data_time: 0.0402 memory: 24011 grad_norm: 4.4180 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1710 loss: 1.1710 2022/09/05 11:49:40 - mmengine - INFO - Epoch(train) [20][460/940] lr: 1.0000e-02 eta: 14:08:28 time: 0.6745 data_time: 0.0443 memory: 24011 grad_norm: 4.3446 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2673 loss: 1.2673 2022/09/05 11:49:52 - mmengine - INFO - Epoch(train) [20][480/940] lr: 1.0000e-02 eta: 14:08:11 time: 0.6276 data_time: 0.0433 memory: 24011 grad_norm: 4.2288 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1713 loss: 1.1713 2022/09/05 11:50:07 - mmengine - INFO - Epoch(train) [20][500/940] lr: 1.0000e-02 eta: 14:08:00 time: 0.7120 data_time: 0.0384 memory: 24011 grad_norm: 4.4453 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1580 loss: 1.1580 2022/09/05 11:50:19 - mmengine - INFO - Epoch(train) [20][520/940] lr: 1.0000e-02 eta: 14:07:44 time: 0.6356 data_time: 0.0384 memory: 24011 grad_norm: 4.3449 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3319 loss: 1.3319 2022/09/05 11:50:32 - mmengine - INFO - Epoch(train) [20][540/940] lr: 1.0000e-02 eta: 14:07:29 time: 0.6519 data_time: 0.0417 memory: 24011 grad_norm: 4.3193 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2015 loss: 1.2015 2022/09/05 11:50:44 - mmengine - INFO - Epoch(train) [20][560/940] lr: 1.0000e-02 eta: 14:07:09 time: 0.5988 data_time: 0.0378 memory: 24011 grad_norm: 4.3401 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1145 loss: 1.1145 2022/09/05 11:50:58 - mmengine - INFO - Epoch(train) [20][580/940] lr: 1.0000e-02 eta: 14:06:55 time: 0.6572 data_time: 0.0482 memory: 24011 grad_norm: 4.2678 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2516 loss: 1.2516 2022/09/05 11:51:11 - mmengine - INFO - Epoch(train) [20][600/940] lr: 1.0000e-02 eta: 14:06:40 time: 0.6624 data_time: 0.0644 memory: 24011 grad_norm: 4.3286 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1879 loss: 1.1879 2022/09/05 11:51:24 - mmengine - INFO - Epoch(train) [20][620/940] lr: 1.0000e-02 eta: 14:06:26 time: 0.6631 data_time: 0.0356 memory: 24011 grad_norm: 4.1732 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1616 loss: 1.1616 2022/09/05 11:51:37 - mmengine - INFO - Epoch(train) [20][640/940] lr: 1.0000e-02 eta: 14:06:10 time: 0.6453 data_time: 0.0405 memory: 24011 grad_norm: 4.1653 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1844 loss: 1.1844 2022/09/05 11:51:50 - mmengine - INFO - Epoch(train) [20][660/940] lr: 1.0000e-02 eta: 14:05:55 time: 0.6452 data_time: 0.0367 memory: 24011 grad_norm: 4.3347 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.1239 loss: 1.1239 2022/09/05 11:52:03 - mmengine - INFO - Epoch(train) [20][680/940] lr: 1.0000e-02 eta: 14:05:39 time: 0.6398 data_time: 0.0601 memory: 24011 grad_norm: 4.2046 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1426 loss: 1.1426 2022/09/05 11:52:17 - mmengine - INFO - Epoch(train) [20][700/940] lr: 1.0000e-02 eta: 14:05:28 time: 0.7096 data_time: 0.0326 memory: 24011 grad_norm: 4.6573 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2070 loss: 1.2070 2022/09/05 11:52:29 - mmengine - INFO - Epoch(train) [20][720/940] lr: 1.0000e-02 eta: 14:05:10 time: 0.6082 data_time: 0.0405 memory: 24011 grad_norm: 4.4541 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.3070 loss: 1.3070 2022/09/05 11:52:41 - mmengine - INFO - Epoch(train) [20][740/940] lr: 1.0000e-02 eta: 14:04:52 time: 0.6244 data_time: 0.0439 memory: 24011 grad_norm: 4.2284 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2475 loss: 1.2475 2022/09/05 11:52:55 - mmengine - INFO - Epoch(train) [20][760/940] lr: 1.0000e-02 eta: 14:04:41 time: 0.7017 data_time: 0.0419 memory: 24011 grad_norm: 4.6162 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2191 loss: 1.2191 2022/09/05 11:53:08 - mmengine - INFO - Epoch(train) [20][780/940] lr: 1.0000e-02 eta: 14:04:25 time: 0.6372 data_time: 0.0368 memory: 24011 grad_norm: 4.2918 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2009 loss: 1.2009 2022/09/05 11:53:22 - mmengine - INFO - Epoch(train) [20][800/940] lr: 1.0000e-02 eta: 14:04:12 time: 0.6739 data_time: 0.0385 memory: 24011 grad_norm: 4.3266 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1954 loss: 1.1954 2022/09/05 11:53:34 - mmengine - INFO - Epoch(train) [20][820/940] lr: 1.0000e-02 eta: 14:03:55 time: 0.6278 data_time: 0.0396 memory: 24011 grad_norm: 3.9889 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0850 loss: 1.0850 2022/09/05 11:53:47 - mmengine - INFO - Epoch(train) [20][840/940] lr: 1.0000e-02 eta: 14:03:39 time: 0.6500 data_time: 0.0402 memory: 24011 grad_norm: 4.1267 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1320 loss: 1.1320 2022/09/05 11:54:00 - mmengine - INFO - Epoch(train) [20][860/940] lr: 1.0000e-02 eta: 14:03:24 time: 0.6539 data_time: 0.0451 memory: 24011 grad_norm: 4.1268 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2509 loss: 1.2509 2022/09/05 11:54:13 - mmengine - INFO - Epoch(train) [20][880/940] lr: 1.0000e-02 eta: 14:03:07 time: 0.6294 data_time: 0.0406 memory: 24011 grad_norm: 4.6716 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.2543 loss: 1.2543 2022/09/05 11:54:26 - mmengine - INFO - Epoch(train) [20][900/940] lr: 1.0000e-02 eta: 14:02:52 time: 0.6438 data_time: 0.0426 memory: 24011 grad_norm: 4.9870 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3146 loss: 1.3146 2022/09/05 11:54:40 - mmengine - INFO - Epoch(train) [20][920/940] lr: 1.0000e-02 eta: 14:02:40 time: 0.6953 data_time: 0.0430 memory: 24011 grad_norm: 4.4277 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3046 loss: 1.3046 2022/09/05 11:54:51 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:54:51 - mmengine - INFO - Epoch(train) [20][940/940] lr: 1.0000e-02 eta: 14:02:17 time: 0.5507 data_time: 0.0252 memory: 24011 grad_norm: 4.5962 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2654 loss: 1.2654 2022/09/05 11:55:05 - mmengine - INFO - Epoch(val) [20][20/78] eta: 0:00:40 time: 0.6944 data_time: 0.5362 memory: 3625 2022/09/05 11:55:14 - mmengine - INFO - Epoch(val) [20][40/78] eta: 0:00:18 time: 0.4808 data_time: 0.3239 memory: 3625 2022/09/05 11:55:27 - mmengine - INFO - Epoch(val) [20][60/78] eta: 0:00:11 time: 0.6251 data_time: 0.4687 memory: 3625 2022/09/05 11:55:38 - mmengine - INFO - Epoch(val) [20][78/78] acc/top1: 0.7179 acc/top5: 0.9044 acc/mean1: 0.7177 2022/09/05 11:55:56 - mmengine - INFO - Epoch(train) [21][20/940] lr: 1.0000e-02 eta: 14:02:20 time: 0.8765 data_time: 0.2785 memory: 24011 grad_norm: 4.2517 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1358 loss: 1.1358 2022/09/05 11:56:08 - mmengine - INFO - Epoch(train) [21][40/940] lr: 1.0000e-02 eta: 14:02:03 time: 0.6246 data_time: 0.0516 memory: 24011 grad_norm: 4.5532 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1626 loss: 1.1626 2022/09/05 11:56:22 - mmengine - INFO - Epoch(train) [21][60/940] lr: 1.0000e-02 eta: 14:01:50 time: 0.6826 data_time: 0.0468 memory: 24011 grad_norm: 4.4306 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1649 loss: 1.1649 2022/09/05 11:56:34 - mmengine - INFO - Epoch(train) [21][80/940] lr: 1.0000e-02 eta: 14:01:34 time: 0.6345 data_time: 0.0350 memory: 24011 grad_norm: 4.2915 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0158 loss: 1.0158 2022/09/05 11:56:48 - mmengine - INFO - Epoch(train) [21][100/940] lr: 1.0000e-02 eta: 14:01:19 time: 0.6573 data_time: 0.0421 memory: 24011 grad_norm: 4.2730 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0866 loss: 1.0866 2022/09/05 11:57:01 - mmengine - INFO - Epoch(train) [21][120/940] lr: 1.0000e-02 eta: 14:01:06 time: 0.6759 data_time: 0.0358 memory: 24011 grad_norm: 4.7034 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1797 loss: 1.1797 2022/09/05 11:57:14 - mmengine - INFO - Epoch(train) [21][140/940] lr: 1.0000e-02 eta: 14:00:49 time: 0.6327 data_time: 0.0399 memory: 24011 grad_norm: 5.0404 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1198 loss: 1.1198 2022/09/05 11:57:27 - mmengine - INFO - Epoch(train) [21][160/940] lr: 1.0000e-02 eta: 14:00:36 time: 0.6738 data_time: 0.0394 memory: 24011 grad_norm: 4.3240 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.1243 loss: 1.1243 2022/09/05 11:57:40 - mmengine - INFO - Epoch(train) [21][180/940] lr: 1.0000e-02 eta: 14:00:20 time: 0.6359 data_time: 0.0375 memory: 24011 grad_norm: 4.1445 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1690 loss: 1.1690 2022/09/05 11:57:52 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 11:57:52 - mmengine - INFO - Epoch(train) [21][200/940] lr: 1.0000e-02 eta: 14:00:02 time: 0.6225 data_time: 0.0402 memory: 24011 grad_norm: 4.4756 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0337 loss: 1.0337 2022/09/05 11:58:06 - mmengine - INFO - Epoch(train) [21][220/940] lr: 1.0000e-02 eta: 13:59:49 time: 0.6788 data_time: 0.0471 memory: 24011 grad_norm: 4.9155 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1964 loss: 1.1964 2022/09/05 11:58:19 - mmengine - INFO - Epoch(train) [21][240/940] lr: 1.0000e-02 eta: 13:59:33 time: 0.6358 data_time: 0.0391 memory: 24011 grad_norm: 4.6230 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1761 loss: 1.1761 2022/09/05 11:58:33 - mmengine - INFO - Epoch(train) [21][260/940] lr: 1.0000e-02 eta: 13:59:22 time: 0.6979 data_time: 0.0391 memory: 24011 grad_norm: 4.4848 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1817 loss: 1.1817 2022/09/05 11:58:46 - mmengine - INFO - Epoch(train) [21][280/940] lr: 1.0000e-02 eta: 13:59:07 time: 0.6559 data_time: 0.0441 memory: 24011 grad_norm: 4.4806 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0895 loss: 1.0895 2022/09/05 11:58:58 - mmengine - INFO - Epoch(train) [21][300/940] lr: 1.0000e-02 eta: 13:58:50 time: 0.6272 data_time: 0.0437 memory: 24011 grad_norm: 4.3000 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.2030 loss: 1.2030 2022/09/05 11:59:10 - mmengine - INFO - Epoch(train) [21][320/940] lr: 1.0000e-02 eta: 13:58:31 time: 0.6046 data_time: 0.0501 memory: 24011 grad_norm: 4.5307 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3587 loss: 1.3587 2022/09/05 11:59:23 - mmengine - INFO - Epoch(train) [21][340/940] lr: 1.0000e-02 eta: 13:58:16 time: 0.6452 data_time: 0.0352 memory: 24011 grad_norm: 4.8861 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1506 loss: 1.1506 2022/09/05 11:59:36 - mmengine - INFO - Epoch(train) [21][360/940] lr: 1.0000e-02 eta: 13:57:59 time: 0.6342 data_time: 0.0505 memory: 24011 grad_norm: 4.9421 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1310 loss: 1.1310 2022/09/05 11:59:49 - mmengine - INFO - Epoch(train) [21][380/940] lr: 1.0000e-02 eta: 13:57:45 time: 0.6641 data_time: 0.0502 memory: 24011 grad_norm: 4.4452 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0878 loss: 1.0878 2022/09/05 12:00:06 - mmengine - INFO - Epoch(train) [21][400/940] lr: 1.0000e-02 eta: 13:57:44 time: 0.8325 data_time: 0.0577 memory: 24011 grad_norm: 4.2741 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2585 loss: 1.2585 2022/09/05 12:00:18 - mmengine - INFO - Epoch(train) [21][420/940] lr: 1.0000e-02 eta: 13:57:26 time: 0.6138 data_time: 0.0362 memory: 24011 grad_norm: 4.3710 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1552 loss: 1.1552 2022/09/05 12:00:31 - mmengine - INFO - Epoch(train) [21][440/940] lr: 1.0000e-02 eta: 13:57:10 time: 0.6344 data_time: 0.0425 memory: 24011 grad_norm: 4.3707 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1928 loss: 1.1928 2022/09/05 12:00:44 - mmengine - INFO - Epoch(train) [21][460/940] lr: 1.0000e-02 eta: 13:56:54 time: 0.6372 data_time: 0.0354 memory: 24011 grad_norm: 4.6650 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2802 loss: 1.2802 2022/09/05 12:00:57 - mmengine - INFO - Epoch(train) [21][480/940] lr: 1.0000e-02 eta: 13:56:40 time: 0.6617 data_time: 0.0466 memory: 24011 grad_norm: 4.2861 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1347 loss: 1.1347 2022/09/05 12:01:11 - mmengine - INFO - Epoch(train) [21][500/940] lr: 1.0000e-02 eta: 13:56:27 time: 0.6834 data_time: 0.0438 memory: 24011 grad_norm: 4.2141 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3257 loss: 1.3257 2022/09/05 12:01:23 - mmengine - INFO - Epoch(train) [21][520/940] lr: 1.0000e-02 eta: 13:56:10 time: 0.6192 data_time: 0.0429 memory: 24011 grad_norm: 4.1738 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1369 loss: 1.1369 2022/09/05 12:01:36 - mmengine - INFO - Epoch(train) [21][540/940] lr: 1.0000e-02 eta: 13:55:54 time: 0.6409 data_time: 0.0357 memory: 24011 grad_norm: 4.0013 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1273 loss: 1.1273 2022/09/05 12:01:48 - mmengine - INFO - Epoch(train) [21][560/940] lr: 1.0000e-02 eta: 13:55:36 time: 0.6115 data_time: 0.0423 memory: 24011 grad_norm: 4.2798 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2960 loss: 1.2960 2022/09/05 12:02:00 - mmengine - INFO - Epoch(train) [21][580/940] lr: 1.0000e-02 eta: 13:55:18 time: 0.6198 data_time: 0.0397 memory: 24011 grad_norm: 4.6235 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2127 loss: 1.2127 2022/09/05 12:02:14 - mmengine - INFO - Epoch(train) [21][600/940] lr: 1.0000e-02 eta: 13:55:04 time: 0.6640 data_time: 0.0502 memory: 24011 grad_norm: 4.4100 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1195 loss: 1.1195 2022/09/05 12:02:26 - mmengine - INFO - Epoch(train) [21][620/940] lr: 1.0000e-02 eta: 13:54:46 time: 0.6101 data_time: 0.0386 memory: 24011 grad_norm: 4.2033 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2369 loss: 1.2369 2022/09/05 12:02:39 - mmengine - INFO - Epoch(train) [21][640/940] lr: 1.0000e-02 eta: 13:54:30 time: 0.6359 data_time: 0.0488 memory: 24011 grad_norm: 4.3696 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1151 loss: 1.1151 2022/09/05 12:02:53 - mmengine - INFO - Epoch(train) [21][660/940] lr: 1.0000e-02 eta: 13:54:19 time: 0.7002 data_time: 0.0362 memory: 24011 grad_norm: 4.2707 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1789 loss: 1.1789 2022/09/05 12:03:06 - mmengine - INFO - Epoch(train) [21][680/940] lr: 1.0000e-02 eta: 13:54:04 time: 0.6531 data_time: 0.0391 memory: 24011 grad_norm: 4.2363 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1682 loss: 1.1682 2022/09/05 12:03:19 - mmengine - INFO - Epoch(train) [21][700/940] lr: 1.0000e-02 eta: 13:53:49 time: 0.6531 data_time: 0.0325 memory: 24011 grad_norm: 4.4010 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2529 loss: 1.2529 2022/09/05 12:03:32 - mmengine - INFO - Epoch(train) [21][720/940] lr: 1.0000e-02 eta: 13:53:34 time: 0.6480 data_time: 0.0391 memory: 24011 grad_norm: 4.2301 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1641 loss: 1.1641 2022/09/05 12:03:45 - mmengine - INFO - Epoch(train) [21][740/940] lr: 1.0000e-02 eta: 13:53:19 time: 0.6580 data_time: 0.0340 memory: 24011 grad_norm: 4.1868 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0860 loss: 1.0860 2022/09/05 12:03:58 - mmengine - INFO - Epoch(train) [21][760/940] lr: 1.0000e-02 eta: 13:53:04 time: 0.6516 data_time: 0.0407 memory: 24011 grad_norm: 4.3065 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0930 loss: 1.0930 2022/09/05 12:04:11 - mmengine - INFO - Epoch(train) [21][780/940] lr: 1.0000e-02 eta: 13:52:50 time: 0.6589 data_time: 0.0395 memory: 24011 grad_norm: 4.2859 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1751 loss: 1.1751 2022/09/05 12:04:24 - mmengine - INFO - Epoch(train) [21][800/940] lr: 1.0000e-02 eta: 13:52:33 time: 0.6295 data_time: 0.0646 memory: 24011 grad_norm: 4.2022 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0142 loss: 1.0142 2022/09/05 12:04:37 - mmengine - INFO - Epoch(train) [21][820/940] lr: 1.0000e-02 eta: 13:52:20 time: 0.6745 data_time: 0.0379 memory: 24011 grad_norm: 4.2300 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1568 loss: 1.1568 2022/09/05 12:04:50 - mmengine - INFO - Epoch(train) [21][840/940] lr: 1.0000e-02 eta: 13:52:06 time: 0.6596 data_time: 0.0409 memory: 24011 grad_norm: 4.2124 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1481 loss: 1.1481 2022/09/05 12:05:03 - mmengine - INFO - Epoch(train) [21][860/940] lr: 1.0000e-02 eta: 13:51:50 time: 0.6422 data_time: 0.0398 memory: 24011 grad_norm: 4.4376 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3041 loss: 1.3041 2022/09/05 12:05:16 - mmengine - INFO - Epoch(train) [21][880/940] lr: 1.0000e-02 eta: 13:51:33 time: 0.6233 data_time: 0.0410 memory: 24011 grad_norm: 4.4172 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1994 loss: 1.1994 2022/09/05 12:05:29 - mmengine - INFO - Epoch(train) [21][900/940] lr: 1.0000e-02 eta: 13:51:19 time: 0.6560 data_time: 0.0412 memory: 24011 grad_norm: 4.4305 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2318 loss: 1.2318 2022/09/05 12:05:41 - mmengine - INFO - Epoch(train) [21][920/940] lr: 1.0000e-02 eta: 13:51:01 time: 0.6153 data_time: 0.0390 memory: 24011 grad_norm: 4.2765 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1800 loss: 1.1800 2022/09/05 12:05:53 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:05:53 - mmengine - INFO - Epoch(train) [21][940/940] lr: 1.0000e-02 eta: 13:50:43 time: 0.6150 data_time: 0.0283 memory: 24011 grad_norm: 4.6359 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0022 loss: 1.0022 2022/09/05 12:05:54 - mmengine - INFO - Saving checkpoint at 21 epochs 2022/09/05 12:06:13 - mmengine - INFO - Epoch(val) [21][20/78] eta: 0:00:40 time: 0.7059 data_time: 0.5482 memory: 3625 2022/09/05 12:06:22 - mmengine - INFO - Epoch(val) [21][40/78] eta: 0:00:17 time: 0.4678 data_time: 0.3101 memory: 3625 2022/09/05 12:06:35 - mmengine - INFO - Epoch(val) [21][60/78] eta: 0:00:11 time: 0.6385 data_time: 0.4817 memory: 3625 2022/09/05 12:06:44 - mmengine - INFO - Epoch(val) [21][78/78] acc/top1: 0.7185 acc/top5: 0.9054 acc/mean1: 0.7184 2022/09/05 12:07:03 - mmengine - INFO - Epoch(train) [22][20/940] lr: 1.0000e-02 eta: 13:50:49 time: 0.9296 data_time: 0.2736 memory: 24011 grad_norm: 4.5674 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1027 loss: 1.1027 2022/09/05 12:07:17 - mmengine - INFO - Epoch(train) [22][40/940] lr: 1.0000e-02 eta: 13:50:38 time: 0.6933 data_time: 0.0567 memory: 24011 grad_norm: 4.3991 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1292 loss: 1.1292 2022/09/05 12:07:29 - mmengine - INFO - Epoch(train) [22][60/940] lr: 1.0000e-02 eta: 13:50:20 time: 0.6120 data_time: 0.0409 memory: 24011 grad_norm: 4.4956 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.1872 loss: 1.1872 2022/09/05 12:07:42 - mmengine - INFO - Epoch(train) [22][80/940] lr: 1.0000e-02 eta: 13:50:05 time: 0.6490 data_time: 0.0364 memory: 24011 grad_norm: 4.3713 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.0661 loss: 1.0661 2022/09/05 12:07:56 - mmengine - INFO - Epoch(train) [22][100/940] lr: 1.0000e-02 eta: 13:49:52 time: 0.6851 data_time: 0.0388 memory: 24011 grad_norm: 4.4654 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1865 loss: 1.1865 2022/09/05 12:08:08 - mmengine - INFO - Epoch(train) [22][120/940] lr: 1.0000e-02 eta: 13:49:35 time: 0.6210 data_time: 0.0414 memory: 24011 grad_norm: 4.2695 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0646 loss: 1.0646 2022/09/05 12:08:20 - mmengine - INFO - Epoch(train) [22][140/940] lr: 1.0000e-02 eta: 13:49:17 time: 0.6166 data_time: 0.0338 memory: 24011 grad_norm: 4.5540 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9880 loss: 0.9880 2022/09/05 12:08:33 - mmengine - INFO - Epoch(train) [22][160/940] lr: 1.0000e-02 eta: 13:49:00 time: 0.6229 data_time: 0.0403 memory: 24011 grad_norm: 4.2589 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.1123 loss: 1.1123 2022/09/05 12:08:46 - mmengine - INFO - Epoch(train) [22][180/940] lr: 1.0000e-02 eta: 13:48:45 time: 0.6410 data_time: 0.0761 memory: 24011 grad_norm: 5.1587 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1684 loss: 1.1684 2022/09/05 12:08:59 - mmengine - INFO - Epoch(train) [22][200/940] lr: 1.0000e-02 eta: 13:48:29 time: 0.6411 data_time: 0.0639 memory: 24011 grad_norm: 5.6760 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0612 loss: 1.0612 2022/09/05 12:09:12 - mmengine - INFO - Epoch(train) [22][220/940] lr: 1.0000e-02 eta: 13:48:17 time: 0.6831 data_time: 0.0855 memory: 24011 grad_norm: 4.8383 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2724 loss: 1.2724 2022/09/05 12:09:25 - mmengine - INFO - Epoch(train) [22][240/940] lr: 1.0000e-02 eta: 13:48:01 time: 0.6460 data_time: 0.0352 memory: 24011 grad_norm: 4.7145 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0529 loss: 1.0529 2022/09/05 12:09:38 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:09:38 - mmengine - INFO - Epoch(train) [22][260/940] lr: 1.0000e-02 eta: 13:47:45 time: 0.6346 data_time: 0.0417 memory: 24011 grad_norm: 4.4231 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2648 loss: 1.2648 2022/09/05 12:09:52 - mmengine - INFO - Epoch(train) [22][280/940] lr: 1.0000e-02 eta: 13:47:32 time: 0.6795 data_time: 0.0336 memory: 24011 grad_norm: 4.4856 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0891 loss: 1.0891 2022/09/05 12:10:04 - mmengine - INFO - Epoch(train) [22][300/940] lr: 1.0000e-02 eta: 13:47:15 time: 0.6198 data_time: 0.0495 memory: 24011 grad_norm: 5.3094 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2114 loss: 1.2114 2022/09/05 12:10:16 - mmengine - INFO - Epoch(train) [22][320/940] lr: 1.0000e-02 eta: 13:46:58 time: 0.6235 data_time: 0.0368 memory: 24011 grad_norm: 5.4871 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1240 loss: 1.1240 2022/09/05 12:10:29 - mmengine - INFO - Epoch(train) [22][340/940] lr: 1.0000e-02 eta: 13:46:42 time: 0.6395 data_time: 0.0409 memory: 24011 grad_norm: 4.6021 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1744 loss: 1.1744 2022/09/05 12:10:41 - mmengine - INFO - Epoch(train) [22][360/940] lr: 1.0000e-02 eta: 13:46:25 time: 0.6192 data_time: 0.0637 memory: 24011 grad_norm: 5.0685 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2661 loss: 1.2661 2022/09/05 12:10:55 - mmengine - INFO - Epoch(train) [22][380/940] lr: 1.0000e-02 eta: 13:46:13 time: 0.6893 data_time: 0.0613 memory: 24011 grad_norm: 4.4086 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1974 loss: 1.1974 2022/09/05 12:11:08 - mmengine - INFO - Epoch(train) [22][400/940] lr: 1.0000e-02 eta: 13:45:57 time: 0.6275 data_time: 0.0463 memory: 24011 grad_norm: 4.3934 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1681 loss: 1.1681 2022/09/05 12:11:21 - mmengine - INFO - Epoch(train) [22][420/940] lr: 1.0000e-02 eta: 13:45:42 time: 0.6505 data_time: 0.0463 memory: 24011 grad_norm: 4.1660 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1359 loss: 1.1359 2022/09/05 12:11:34 - mmengine - INFO - Epoch(train) [22][440/940] lr: 1.0000e-02 eta: 13:45:29 time: 0.6813 data_time: 0.0357 memory: 24011 grad_norm: 4.8226 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2578 loss: 1.2578 2022/09/05 12:11:48 - mmengine - INFO - Epoch(train) [22][460/940] lr: 1.0000e-02 eta: 13:45:15 time: 0.6683 data_time: 0.0904 memory: 24011 grad_norm: 4.2564 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0858 loss: 1.0858 2022/09/05 12:12:00 - mmengine - INFO - Epoch(train) [22][480/940] lr: 1.0000e-02 eta: 13:44:57 time: 0.6055 data_time: 0.0316 memory: 24011 grad_norm: 4.3785 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2473 loss: 1.2473 2022/09/05 12:12:13 - mmengine - INFO - Epoch(train) [22][500/940] lr: 1.0000e-02 eta: 13:44:41 time: 0.6369 data_time: 0.0361 memory: 24011 grad_norm: 4.3500 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1594 loss: 1.1594 2022/09/05 12:12:25 - mmengine - INFO - Epoch(train) [22][520/940] lr: 1.0000e-02 eta: 13:44:25 time: 0.6297 data_time: 0.0336 memory: 24011 grad_norm: 4.3956 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2622 loss: 1.2622 2022/09/05 12:12:38 - mmengine - INFO - Epoch(train) [22][540/940] lr: 1.0000e-02 eta: 13:44:10 time: 0.6492 data_time: 0.0476 memory: 24011 grad_norm: 4.1971 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0675 loss: 1.0675 2022/09/05 12:12:51 - mmengine - INFO - Epoch(train) [22][560/940] lr: 1.0000e-02 eta: 13:43:54 time: 0.6436 data_time: 0.0437 memory: 24011 grad_norm: 4.3708 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2367 loss: 1.2367 2022/09/05 12:13:05 - mmengine - INFO - Epoch(train) [22][580/940] lr: 1.0000e-02 eta: 13:43:43 time: 0.6991 data_time: 0.1061 memory: 24011 grad_norm: 5.3059 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1768 loss: 1.1768 2022/09/05 12:13:18 - mmengine - INFO - Epoch(train) [22][600/940] lr: 1.0000e-02 eta: 13:43:27 time: 0.6320 data_time: 0.0574 memory: 24011 grad_norm: 4.7742 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2144 loss: 1.2144 2022/09/05 12:13:31 - mmengine - INFO - Epoch(train) [22][620/940] lr: 1.0000e-02 eta: 13:43:13 time: 0.6630 data_time: 0.0934 memory: 24011 grad_norm: 4.2501 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.2396 loss: 1.2396 2022/09/05 12:13:44 - mmengine - INFO - Epoch(train) [22][640/940] lr: 1.0000e-02 eta: 13:42:56 time: 0.6288 data_time: 0.0540 memory: 24011 grad_norm: 4.2636 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2510 loss: 1.2510 2022/09/05 12:13:57 - mmengine - INFO - Epoch(train) [22][660/940] lr: 1.0000e-02 eta: 13:42:42 time: 0.6577 data_time: 0.0717 memory: 24011 grad_norm: 6.9368 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0531 loss: 1.0531 2022/09/05 12:14:10 - mmengine - INFO - Epoch(train) [22][680/940] lr: 1.0000e-02 eta: 13:42:28 time: 0.6583 data_time: 0.0829 memory: 24011 grad_norm: 4.8378 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1434 loss: 1.1434 2022/09/05 12:14:23 - mmengine - INFO - Epoch(train) [22][700/940] lr: 1.0000e-02 eta: 13:42:14 time: 0.6658 data_time: 0.0952 memory: 24011 grad_norm: 4.6022 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3824 loss: 1.3824 2022/09/05 12:14:36 - mmengine - INFO - Epoch(train) [22][720/940] lr: 1.0000e-02 eta: 13:41:58 time: 0.6384 data_time: 0.0739 memory: 24011 grad_norm: 4.6969 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2126 loss: 1.2126 2022/09/05 12:14:48 - mmengine - INFO - Epoch(train) [22][740/940] lr: 1.0000e-02 eta: 13:41:42 time: 0.6267 data_time: 0.0593 memory: 24011 grad_norm: 4.5781 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3189 loss: 1.3189 2022/09/05 12:15:01 - mmengine - INFO - Epoch(train) [22][760/940] lr: 1.0000e-02 eta: 13:41:25 time: 0.6287 data_time: 0.0639 memory: 24011 grad_norm: 4.3511 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0403 loss: 1.0403 2022/09/05 12:15:15 - mmengine - INFO - Epoch(train) [22][780/940] lr: 1.0000e-02 eta: 13:41:12 time: 0.6769 data_time: 0.1077 memory: 24011 grad_norm: 4.3845 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1697 loss: 1.1697 2022/09/05 12:15:27 - mmengine - INFO - Epoch(train) [22][800/940] lr: 1.0000e-02 eta: 13:40:55 time: 0.6208 data_time: 0.0488 memory: 24011 grad_norm: 4.8332 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2588 loss: 1.2588 2022/09/05 12:15:41 - mmengine - INFO - Epoch(train) [22][820/940] lr: 1.0000e-02 eta: 13:40:42 time: 0.6759 data_time: 0.0895 memory: 24011 grad_norm: 6.4328 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2060 loss: 1.2060 2022/09/05 12:15:53 - mmengine - INFO - Epoch(train) [22][840/940] lr: 1.0000e-02 eta: 13:40:25 time: 0.6199 data_time: 0.0531 memory: 24011 grad_norm: 5.5114 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3399 loss: 1.3399 2022/09/05 12:16:07 - mmengine - INFO - Epoch(train) [22][860/940] lr: 1.0000e-02 eta: 13:40:13 time: 0.6811 data_time: 0.1094 memory: 24011 grad_norm: 4.6974 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3226 loss: 1.3226 2022/09/05 12:16:19 - mmengine - INFO - Epoch(train) [22][880/940] lr: 1.0000e-02 eta: 13:39:56 time: 0.6284 data_time: 0.0669 memory: 24011 grad_norm: 4.4949 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3491 loss: 1.3491 2022/09/05 12:16:32 - mmengine - INFO - Epoch(train) [22][900/940] lr: 1.0000e-02 eta: 13:39:41 time: 0.6387 data_time: 0.0663 memory: 24011 grad_norm: 4.2446 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3051 loss: 1.3051 2022/09/05 12:16:44 - mmengine - INFO - Epoch(train) [22][920/940] lr: 1.0000e-02 eta: 13:39:24 time: 0.6204 data_time: 0.0431 memory: 24011 grad_norm: 4.4368 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3240 loss: 1.3240 2022/09/05 12:16:56 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:16:56 - mmengine - INFO - Epoch(train) [22][940/940] lr: 1.0000e-02 eta: 13:39:03 time: 0.5707 data_time: 0.0634 memory: 24011 grad_norm: 4.4372 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 1.1441 loss: 1.1441 2022/09/05 12:17:10 - mmengine - INFO - Epoch(val) [22][20/78] eta: 0:00:40 time: 0.6971 data_time: 0.5380 memory: 3625 2022/09/05 12:17:19 - mmengine - INFO - Epoch(val) [22][40/78] eta: 0:00:17 time: 0.4663 data_time: 0.3080 memory: 3625 2022/09/05 12:17:32 - mmengine - INFO - Epoch(val) [22][60/78] eta: 0:00:11 time: 0.6594 data_time: 0.4973 memory: 3625 2022/09/05 12:17:42 - mmengine - INFO - Epoch(val) [22][78/78] acc/top1: 0.7084 acc/top5: 0.8957 acc/mean1: 0.7082 2022/09/05 12:18:00 - mmengine - INFO - Epoch(train) [23][20/940] lr: 1.0000e-02 eta: 13:39:06 time: 0.9062 data_time: 0.2500 memory: 24011 grad_norm: 4.7403 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3011 loss: 1.3011 2022/09/05 12:18:13 - mmengine - INFO - Epoch(train) [23][40/940] lr: 1.0000e-02 eta: 13:38:50 time: 0.6264 data_time: 0.0325 memory: 24011 grad_norm: 4.5356 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2489 loss: 1.2489 2022/09/05 12:18:26 - mmengine - INFO - Epoch(train) [23][60/940] lr: 1.0000e-02 eta: 13:38:38 time: 0.6878 data_time: 0.0413 memory: 24011 grad_norm: 4.9847 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0502 loss: 1.0502 2022/09/05 12:18:39 - mmengine - INFO - Epoch(train) [23][80/940] lr: 1.0000e-02 eta: 13:38:21 time: 0.6294 data_time: 0.0380 memory: 24011 grad_norm: 5.4971 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1109 loss: 1.1109 2022/09/05 12:18:53 - mmengine - INFO - Epoch(train) [23][100/940] lr: 1.0000e-02 eta: 13:38:10 time: 0.6960 data_time: 0.0483 memory: 24011 grad_norm: 4.3573 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1668 loss: 1.1668 2022/09/05 12:19:06 - mmengine - INFO - Epoch(train) [23][120/940] lr: 1.0000e-02 eta: 13:37:54 time: 0.6374 data_time: 0.0347 memory: 24011 grad_norm: 4.4376 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2088 loss: 1.2088 2022/09/05 12:19:18 - mmengine - INFO - Epoch(train) [23][140/940] lr: 1.0000e-02 eta: 13:37:38 time: 0.6318 data_time: 0.0452 memory: 24011 grad_norm: 5.1367 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1965 loss: 1.1965 2022/09/05 12:19:31 - mmengine - INFO - Epoch(train) [23][160/940] lr: 1.0000e-02 eta: 13:37:23 time: 0.6425 data_time: 0.0793 memory: 24011 grad_norm: 4.4684 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1494 loss: 1.1494 2022/09/05 12:19:44 - mmengine - INFO - Epoch(train) [23][180/940] lr: 1.0000e-02 eta: 13:37:08 time: 0.6503 data_time: 0.0569 memory: 24011 grad_norm: 4.4735 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1147 loss: 1.1147 2022/09/05 12:19:58 - mmengine - INFO - Epoch(train) [23][200/940] lr: 1.0000e-02 eta: 13:36:54 time: 0.6714 data_time: 0.0440 memory: 24011 grad_norm: 5.6049 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1614 loss: 1.1614 2022/09/05 12:20:11 - mmengine - INFO - Epoch(train) [23][220/940] lr: 1.0000e-02 eta: 13:36:41 time: 0.6646 data_time: 0.0398 memory: 24011 grad_norm: 4.7701 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2343 loss: 1.2343 2022/09/05 12:20:24 - mmengine - INFO - Epoch(train) [23][240/940] lr: 1.0000e-02 eta: 13:36:25 time: 0.6449 data_time: 0.0388 memory: 24011 grad_norm: 4.4487 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0596 loss: 1.0596 2022/09/05 12:20:37 - mmengine - INFO - Epoch(train) [23][260/940] lr: 1.0000e-02 eta: 13:36:12 time: 0.6756 data_time: 0.0422 memory: 24011 grad_norm: 4.5309 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1786 loss: 1.1786 2022/09/05 12:20:50 - mmengine - INFO - Epoch(train) [23][280/940] lr: 1.0000e-02 eta: 13:35:56 time: 0.6256 data_time: 0.0461 memory: 24011 grad_norm: 4.4187 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1440 loss: 1.1440 2022/09/05 12:21:04 - mmengine - INFO - Epoch(train) [23][300/940] lr: 1.0000e-02 eta: 13:35:43 time: 0.6808 data_time: 0.0419 memory: 24011 grad_norm: 5.4634 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1328 loss: 1.1328 2022/09/05 12:21:16 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:21:16 - mmengine - INFO - Epoch(train) [23][320/940] lr: 1.0000e-02 eta: 13:35:28 time: 0.6381 data_time: 0.0297 memory: 24011 grad_norm: 4.6799 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.3104 loss: 1.3104 2022/09/05 12:21:30 - mmengine - INFO - Epoch(train) [23][340/940] lr: 1.0000e-02 eta: 13:35:14 time: 0.6659 data_time: 0.0340 memory: 24011 grad_norm: 4.3003 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3065 loss: 1.3065 2022/09/05 12:21:42 - mmengine - INFO - Epoch(train) [23][360/940] lr: 1.0000e-02 eta: 13:34:57 time: 0.6182 data_time: 0.0366 memory: 24011 grad_norm: 4.4961 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2598 loss: 1.2598 2022/09/05 12:21:55 - mmengine - INFO - Epoch(train) [23][380/940] lr: 1.0000e-02 eta: 13:34:43 time: 0.6674 data_time: 0.0419 memory: 24011 grad_norm: 4.3515 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0904 loss: 1.0904 2022/09/05 12:22:07 - mmengine - INFO - Epoch(train) [23][400/940] lr: 1.0000e-02 eta: 13:34:25 time: 0.6016 data_time: 0.0421 memory: 24011 grad_norm: 4.4911 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1785 loss: 1.1785 2022/09/05 12:22:20 - mmengine - INFO - Epoch(train) [23][420/940] lr: 1.0000e-02 eta: 13:34:09 time: 0.6320 data_time: 0.0424 memory: 24011 grad_norm: 4.2193 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1997 loss: 1.1997 2022/09/05 12:22:33 - mmengine - INFO - Epoch(train) [23][440/940] lr: 1.0000e-02 eta: 13:33:56 time: 0.6685 data_time: 0.0420 memory: 24011 grad_norm: 4.4974 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0909 loss: 1.0909 2022/09/05 12:22:47 - mmengine - INFO - Epoch(train) [23][460/940] lr: 1.0000e-02 eta: 13:33:42 time: 0.6606 data_time: 0.0367 memory: 24011 grad_norm: 4.5761 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2531 loss: 1.2531 2022/09/05 12:23:00 - mmengine - INFO - Epoch(train) [23][480/940] lr: 1.0000e-02 eta: 13:33:28 time: 0.6667 data_time: 0.0401 memory: 24011 grad_norm: 4.8927 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1260 loss: 1.1260 2022/09/05 12:23:12 - mmengine - INFO - Epoch(train) [23][500/940] lr: 1.0000e-02 eta: 13:33:10 time: 0.6050 data_time: 0.0368 memory: 24011 grad_norm: 4.9340 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1147 loss: 1.1147 2022/09/05 12:23:25 - mmengine - INFO - Epoch(train) [23][520/940] lr: 1.0000e-02 eta: 13:32:55 time: 0.6497 data_time: 0.0479 memory: 24011 grad_norm: 5.0549 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2302 loss: 1.2302 2022/09/05 12:23:38 - mmengine - INFO - Epoch(train) [23][540/940] lr: 1.0000e-02 eta: 13:32:40 time: 0.6464 data_time: 0.0363 memory: 24011 grad_norm: 4.2755 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1251 loss: 1.1251 2022/09/05 12:23:51 - mmengine - INFO - Epoch(train) [23][560/940] lr: 1.0000e-02 eta: 13:32:26 time: 0.6553 data_time: 0.0445 memory: 24011 grad_norm: 4.2223 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2078 loss: 1.2078 2022/09/05 12:24:04 - mmengine - INFO - Epoch(train) [23][580/940] lr: 1.0000e-02 eta: 13:32:10 time: 0.6422 data_time: 0.0522 memory: 24011 grad_norm: 4.3064 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0210 loss: 1.0210 2022/09/05 12:24:17 - mmengine - INFO - Epoch(train) [23][600/940] lr: 1.0000e-02 eta: 13:31:55 time: 0.6453 data_time: 0.0619 memory: 24011 grad_norm: 4.3077 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1773 loss: 1.1773 2022/09/05 12:24:31 - mmengine - INFO - Epoch(train) [23][620/940] lr: 1.0000e-02 eta: 13:31:44 time: 0.6930 data_time: 0.0396 memory: 24011 grad_norm: 4.1834 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1132 loss: 1.1132 2022/09/05 12:24:44 - mmengine - INFO - Epoch(train) [23][640/940] lr: 1.0000e-02 eta: 13:31:30 time: 0.6632 data_time: 0.0441 memory: 24011 grad_norm: 4.5942 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1787 loss: 1.1787 2022/09/05 12:24:57 - mmengine - INFO - Epoch(train) [23][660/940] lr: 1.0000e-02 eta: 13:31:15 time: 0.6504 data_time: 0.0419 memory: 24011 grad_norm: 5.1216 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2251 loss: 1.2251 2022/09/05 12:25:09 - mmengine - INFO - Epoch(train) [23][680/940] lr: 1.0000e-02 eta: 13:30:58 time: 0.6161 data_time: 0.0462 memory: 24011 grad_norm: 4.4642 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3504 loss: 1.3504 2022/09/05 12:25:22 - mmengine - INFO - Epoch(train) [23][700/940] lr: 1.0000e-02 eta: 13:30:44 time: 0.6598 data_time: 0.0421 memory: 24011 grad_norm: 4.7092 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3237 loss: 1.3237 2022/09/05 12:25:35 - mmengine - INFO - Epoch(train) [23][720/940] lr: 1.0000e-02 eta: 13:30:29 time: 0.6472 data_time: 0.0414 memory: 24011 grad_norm: 4.1773 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1937 loss: 1.1937 2022/09/05 12:25:49 - mmengine - INFO - Epoch(train) [23][740/940] lr: 1.0000e-02 eta: 13:30:17 time: 0.6958 data_time: 0.0368 memory: 24011 grad_norm: 4.5897 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2575 loss: 1.2575 2022/09/05 12:26:02 - mmengine - INFO - Epoch(train) [23][760/940] lr: 1.0000e-02 eta: 13:30:00 time: 0.6173 data_time: 0.0412 memory: 24011 grad_norm: 4.4664 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1453 loss: 1.1453 2022/09/05 12:26:14 - mmengine - INFO - Epoch(train) [23][780/940] lr: 1.0000e-02 eta: 13:29:44 time: 0.6267 data_time: 0.0403 memory: 24011 grad_norm: 4.4977 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2951 loss: 1.2951 2022/09/05 12:26:26 - mmengine - INFO - Epoch(train) [23][800/940] lr: 1.0000e-02 eta: 13:29:26 time: 0.6072 data_time: 0.0408 memory: 24011 grad_norm: 4.5859 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2689 loss: 1.2689 2022/09/05 12:26:39 - mmengine - INFO - Epoch(train) [23][820/940] lr: 1.0000e-02 eta: 13:29:10 time: 0.6262 data_time: 0.0393 memory: 24011 grad_norm: 4.2424 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1578 loss: 1.1578 2022/09/05 12:26:52 - mmengine - INFO - Epoch(train) [23][840/940] lr: 1.0000e-02 eta: 13:28:55 time: 0.6395 data_time: 0.0429 memory: 24011 grad_norm: 5.3461 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2429 loss: 1.2429 2022/09/05 12:27:05 - mmengine - INFO - Epoch(train) [23][860/940] lr: 1.0000e-02 eta: 13:28:42 time: 0.6849 data_time: 0.0444 memory: 24011 grad_norm: 4.4491 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3926 loss: 1.3926 2022/09/05 12:27:18 - mmengine - INFO - Epoch(train) [23][880/940] lr: 1.0000e-02 eta: 13:28:26 time: 0.6265 data_time: 0.0397 memory: 24011 grad_norm: 4.9283 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2753 loss: 1.2753 2022/09/05 12:27:31 - mmengine - INFO - Epoch(train) [23][900/940] lr: 1.0000e-02 eta: 13:28:12 time: 0.6541 data_time: 0.0382 memory: 24011 grad_norm: 4.6256 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3058 loss: 1.3058 2022/09/05 12:27:44 - mmengine - INFO - Epoch(train) [23][920/940] lr: 1.0000e-02 eta: 13:27:57 time: 0.6572 data_time: 0.0671 memory: 24011 grad_norm: 4.7198 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2239 loss: 1.2239 2022/09/05 12:27:56 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:27:56 - mmengine - INFO - Epoch(train) [23][940/940] lr: 1.0000e-02 eta: 13:27:37 time: 0.5699 data_time: 0.0525 memory: 24011 grad_norm: 4.9119 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.1986 loss: 1.1986 2022/09/05 12:28:09 - mmengine - INFO - Epoch(val) [23][20/78] eta: 0:00:40 time: 0.6916 data_time: 0.5319 memory: 3625 2022/09/05 12:28:18 - mmengine - INFO - Epoch(val) [23][40/78] eta: 0:00:17 time: 0.4503 data_time: 0.2934 memory: 3625 2022/09/05 12:28:32 - mmengine - INFO - Epoch(val) [23][60/78] eta: 0:00:11 time: 0.6532 data_time: 0.4948 memory: 3625 2022/09/05 12:28:47 - mmengine - INFO - Epoch(val) [23][78/78] acc/top1: 0.7127 acc/top5: 0.9002 acc/mean1: 0.7125 2022/09/05 12:29:05 - mmengine - INFO - Epoch(train) [24][20/940] lr: 1.0000e-02 eta: 13:27:38 time: 0.8857 data_time: 0.2883 memory: 24011 grad_norm: 4.6843 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1815 loss: 1.1815 2022/09/05 12:29:18 - mmengine - INFO - Epoch(train) [24][40/940] lr: 1.0000e-02 eta: 13:27:24 time: 0.6531 data_time: 0.0642 memory: 24011 grad_norm: 4.4911 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0942 loss: 1.0942 2022/09/05 12:29:32 - mmengine - INFO - Epoch(train) [24][60/940] lr: 1.0000e-02 eta: 13:27:12 time: 0.6875 data_time: 0.0414 memory: 24011 grad_norm: 5.2052 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1175 loss: 1.1175 2022/09/05 12:29:44 - mmengine - INFO - Epoch(train) [24][80/940] lr: 1.0000e-02 eta: 13:26:55 time: 0.6246 data_time: 0.0376 memory: 24011 grad_norm: 5.9339 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.2173 loss: 1.2173 2022/09/05 12:29:58 - mmengine - INFO - Epoch(train) [24][100/940] lr: 1.0000e-02 eta: 13:26:42 time: 0.6739 data_time: 0.0426 memory: 24011 grad_norm: 4.8382 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1737 loss: 1.1737 2022/09/05 12:30:10 - mmengine - INFO - Epoch(train) [24][120/940] lr: 1.0000e-02 eta: 13:26:27 time: 0.6488 data_time: 0.0327 memory: 24011 grad_norm: 4.5050 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1410 loss: 1.1410 2022/09/05 12:30:24 - mmengine - INFO - Epoch(train) [24][140/940] lr: 1.0000e-02 eta: 13:26:13 time: 0.6532 data_time: 0.0401 memory: 24011 grad_norm: 4.3302 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2337 loss: 1.2337 2022/09/05 12:30:36 - mmengine - INFO - Epoch(train) [24][160/940] lr: 1.0000e-02 eta: 13:25:58 time: 0.6440 data_time: 0.0355 memory: 24011 grad_norm: 4.6371 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1228 loss: 1.1228 2022/09/05 12:30:49 - mmengine - INFO - Epoch(train) [24][180/940] lr: 1.0000e-02 eta: 13:25:42 time: 0.6379 data_time: 0.0392 memory: 24011 grad_norm: 4.6789 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1587 loss: 1.1587 2022/09/05 12:31:02 - mmengine - INFO - Epoch(train) [24][200/940] lr: 1.0000e-02 eta: 13:25:26 time: 0.6296 data_time: 0.0316 memory: 24011 grad_norm: 4.2997 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1255 loss: 1.1255 2022/09/05 12:31:15 - mmengine - INFO - Epoch(train) [24][220/940] lr: 1.0000e-02 eta: 13:25:13 time: 0.6765 data_time: 0.0392 memory: 24011 grad_norm: 4.5198 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0155 loss: 1.0155 2022/09/05 12:31:28 - mmengine - INFO - Epoch(train) [24][240/940] lr: 1.0000e-02 eta: 13:24:59 time: 0.6509 data_time: 0.0333 memory: 24011 grad_norm: 4.2447 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0689 loss: 1.0689 2022/09/05 12:31:41 - mmengine - INFO - Epoch(train) [24][260/940] lr: 1.0000e-02 eta: 13:24:42 time: 0.6159 data_time: 0.0426 memory: 24011 grad_norm: 4.3869 top1_acc: 0.6562 top5_acc: 1.0000 loss_cls: 1.0759 loss: 1.0759 2022/09/05 12:31:54 - mmengine - INFO - Epoch(train) [24][280/940] lr: 1.0000e-02 eta: 13:24:27 time: 0.6513 data_time: 0.0385 memory: 24011 grad_norm: 4.8423 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2559 loss: 1.2559 2022/09/05 12:32:07 - mmengine - INFO - Epoch(train) [24][300/940] lr: 1.0000e-02 eta: 13:24:14 time: 0.6743 data_time: 0.0404 memory: 24011 grad_norm: 4.5120 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2912 loss: 1.2912 2022/09/05 12:32:20 - mmengine - INFO - Epoch(train) [24][320/940] lr: 1.0000e-02 eta: 13:23:59 time: 0.6461 data_time: 0.0503 memory: 24011 grad_norm: 4.3550 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0962 loss: 1.0962 2022/09/05 12:32:32 - mmengine - INFO - Epoch(train) [24][340/940] lr: 1.0000e-02 eta: 13:23:42 time: 0.6105 data_time: 0.0432 memory: 24011 grad_norm: 4.7375 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2445 loss: 1.2445 2022/09/05 12:32:46 - mmengine - INFO - Epoch(train) [24][360/940] lr: 1.0000e-02 eta: 13:23:29 time: 0.6694 data_time: 0.0404 memory: 24011 grad_norm: 4.9354 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1549 loss: 1.1549 2022/09/05 12:32:58 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:32:58 - mmengine - INFO - Epoch(train) [24][380/940] lr: 1.0000e-02 eta: 13:23:12 time: 0.6287 data_time: 0.0430 memory: 24011 grad_norm: 4.1896 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0428 loss: 1.0428 2022/09/05 12:33:11 - mmengine - INFO - Epoch(train) [24][400/940] lr: 1.0000e-02 eta: 13:22:57 time: 0.6324 data_time: 0.0386 memory: 24011 grad_norm: 4.9755 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1330 loss: 1.1330 2022/09/05 12:33:24 - mmengine - INFO - Epoch(train) [24][420/940] lr: 1.0000e-02 eta: 13:22:42 time: 0.6555 data_time: 0.0409 memory: 24011 grad_norm: 4.4578 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0865 loss: 1.0865 2022/09/05 12:33:38 - mmengine - INFO - Epoch(train) [24][440/940] lr: 1.0000e-02 eta: 13:22:29 time: 0.6738 data_time: 0.0334 memory: 24011 grad_norm: 4.5100 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0285 loss: 1.0285 2022/09/05 12:33:50 - mmengine - INFO - Epoch(train) [24][460/940] lr: 1.0000e-02 eta: 13:22:14 time: 0.6351 data_time: 0.0395 memory: 24011 grad_norm: 4.3156 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1336 loss: 1.1336 2022/09/05 12:34:02 - mmengine - INFO - Epoch(train) [24][480/940] lr: 1.0000e-02 eta: 13:21:56 time: 0.5992 data_time: 0.0368 memory: 24011 grad_norm: 4.5440 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1854 loss: 1.1854 2022/09/05 12:34:16 - mmengine - INFO - Epoch(train) [24][500/940] lr: 1.0000e-02 eta: 13:21:42 time: 0.6606 data_time: 0.0409 memory: 24011 grad_norm: 4.3979 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1789 loss: 1.1789 2022/09/05 12:34:28 - mmengine - INFO - Epoch(train) [24][520/940] lr: 1.0000e-02 eta: 13:21:26 time: 0.6341 data_time: 0.0445 memory: 24011 grad_norm: 4.4570 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1416 loss: 1.1416 2022/09/05 12:34:41 - mmengine - INFO - Epoch(train) [24][540/940] lr: 1.0000e-02 eta: 13:21:12 time: 0.6609 data_time: 0.0450 memory: 24011 grad_norm: 4.2306 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0136 loss: 1.0136 2022/09/05 12:34:55 - mmengine - INFO - Epoch(train) [24][560/940] lr: 1.0000e-02 eta: 13:21:00 time: 0.6921 data_time: 0.0445 memory: 24011 grad_norm: 4.1626 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2205 loss: 1.2205 2022/09/05 12:35:07 - mmengine - INFO - Epoch(train) [24][580/940] lr: 1.0000e-02 eta: 13:20:42 time: 0.5983 data_time: 0.0434 memory: 24011 grad_norm: 4.3663 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0944 loss: 1.0944 2022/09/05 12:35:20 - mmengine - INFO - Epoch(train) [24][600/940] lr: 1.0000e-02 eta: 13:20:28 time: 0.6493 data_time: 0.0434 memory: 24011 grad_norm: 4.2413 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2196 loss: 1.2196 2022/09/05 12:35:33 - mmengine - INFO - Epoch(train) [24][620/940] lr: 1.0000e-02 eta: 13:20:13 time: 0.6462 data_time: 0.0406 memory: 24011 grad_norm: 4.2995 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2301 loss: 1.2301 2022/09/05 12:35:47 - mmengine - INFO - Epoch(train) [24][640/940] lr: 1.0000e-02 eta: 13:20:02 time: 0.7017 data_time: 0.0405 memory: 24011 grad_norm: 4.3098 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1410 loss: 1.1410 2022/09/05 12:35:59 - mmengine - INFO - Epoch(train) [24][660/940] lr: 1.0000e-02 eta: 13:19:44 time: 0.6009 data_time: 0.0427 memory: 24011 grad_norm: 4.1401 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1709 loss: 1.1709 2022/09/05 12:36:12 - mmengine - INFO - Epoch(train) [24][680/940] lr: 1.0000e-02 eta: 13:19:28 time: 0.6346 data_time: 0.0398 memory: 24011 grad_norm: 4.4615 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1822 loss: 1.1822 2022/09/05 12:36:25 - mmengine - INFO - Epoch(train) [24][700/940] lr: 1.0000e-02 eta: 13:19:16 time: 0.6812 data_time: 0.0413 memory: 24011 grad_norm: 4.1270 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1401 loss: 1.1401 2022/09/05 12:36:38 - mmengine - INFO - Epoch(train) [24][720/940] lr: 1.0000e-02 eta: 13:19:00 time: 0.6370 data_time: 0.0387 memory: 24011 grad_norm: 4.6590 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1617 loss: 1.1617 2022/09/05 12:36:51 - mmengine - INFO - Epoch(train) [24][740/940] lr: 1.0000e-02 eta: 13:18:46 time: 0.6592 data_time: 0.0622 memory: 24011 grad_norm: 4.4796 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2973 loss: 1.2973 2022/09/05 12:37:04 - mmengine - INFO - Epoch(train) [24][760/940] lr: 1.0000e-02 eta: 13:18:31 time: 0.6361 data_time: 0.0440 memory: 24011 grad_norm: 4.6542 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2461 loss: 1.2461 2022/09/05 12:37:17 - mmengine - INFO - Epoch(train) [24][780/940] lr: 1.0000e-02 eta: 13:18:15 time: 0.6323 data_time: 0.0427 memory: 24011 grad_norm: 4.4087 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1814 loss: 1.1814 2022/09/05 12:37:30 - mmengine - INFO - Epoch(train) [24][800/940] lr: 1.0000e-02 eta: 13:18:02 time: 0.6794 data_time: 0.0565 memory: 24011 grad_norm: 4.7007 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 0.9936 loss: 0.9936 2022/09/05 12:37:43 - mmengine - INFO - Epoch(train) [24][820/940] lr: 1.0000e-02 eta: 13:17:46 time: 0.6176 data_time: 0.0367 memory: 24011 grad_norm: 4.2462 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1973 loss: 1.1973 2022/09/05 12:37:57 - mmengine - INFO - Epoch(train) [24][840/940] lr: 1.0000e-02 eta: 13:17:33 time: 0.6894 data_time: 0.0454 memory: 24011 grad_norm: 4.4847 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0057 loss: 1.0057 2022/09/05 12:38:09 - mmengine - INFO - Epoch(train) [24][860/940] lr: 1.0000e-02 eta: 13:17:17 time: 0.6153 data_time: 0.0482 memory: 24011 grad_norm: 4.3842 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1868 loss: 1.1868 2022/09/05 12:38:23 - mmengine - INFO - Epoch(train) [24][880/940] lr: 1.0000e-02 eta: 13:17:06 time: 0.7173 data_time: 0.0380 memory: 24011 grad_norm: 4.3347 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0802 loss: 1.0802 2022/09/05 12:38:36 - mmengine - INFO - Epoch(train) [24][900/940] lr: 1.0000e-02 eta: 13:16:51 time: 0.6364 data_time: 0.0432 memory: 24011 grad_norm: 4.3167 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2375 loss: 1.2375 2022/09/05 12:38:50 - mmengine - INFO - Epoch(train) [24][920/940] lr: 1.0000e-02 eta: 13:16:39 time: 0.6895 data_time: 0.0417 memory: 24011 grad_norm: 4.5138 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1418 loss: 1.1418 2022/09/05 12:39:00 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:39:00 - mmengine - INFO - Epoch(train) [24][940/940] lr: 1.0000e-02 eta: 13:16:16 time: 0.5264 data_time: 0.0249 memory: 24011 grad_norm: 5.1493 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.1179 loss: 1.1179 2022/09/05 12:39:00 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/09/05 12:39:19 - mmengine - INFO - Epoch(val) [24][20/78] eta: 0:00:41 time: 0.7136 data_time: 0.5570 memory: 3625 2022/09/05 12:39:29 - mmengine - INFO - Epoch(val) [24][40/78] eta: 0:00:17 time: 0.4584 data_time: 0.3020 memory: 3625 2022/09/05 12:39:41 - mmengine - INFO - Epoch(val) [24][60/78] eta: 0:00:11 time: 0.6392 data_time: 0.4853 memory: 3625 2022/09/05 12:39:50 - mmengine - INFO - Epoch(val) [24][78/78] acc/top1: 0.7170 acc/top5: 0.9026 acc/mean1: 0.7168 2022/09/05 12:40:08 - mmengine - INFO - Epoch(train) [25][20/940] lr: 1.0000e-02 eta: 13:16:17 time: 0.8961 data_time: 0.2759 memory: 24011 grad_norm: 4.7779 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1246 loss: 1.1246 2022/09/05 12:40:20 - mmengine - INFO - Epoch(train) [25][40/940] lr: 1.0000e-02 eta: 13:16:00 time: 0.6052 data_time: 0.0488 memory: 24011 grad_norm: 4.7132 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2508 loss: 1.2508 2022/09/05 12:40:34 - mmengine - INFO - Epoch(train) [25][60/940] lr: 1.0000e-02 eta: 13:15:48 time: 0.6885 data_time: 0.0961 memory: 24011 grad_norm: 4.2897 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0642 loss: 1.0642 2022/09/05 12:40:47 - mmengine - INFO - Epoch(train) [25][80/940] lr: 1.0000e-02 eta: 13:15:33 time: 0.6458 data_time: 0.0463 memory: 24011 grad_norm: 4.4681 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0097 loss: 1.0097 2022/09/05 12:41:01 - mmengine - INFO - Epoch(train) [25][100/940] lr: 1.0000e-02 eta: 13:15:21 time: 0.6950 data_time: 0.0418 memory: 24011 grad_norm: 4.5631 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.2008 loss: 1.2008 2022/09/05 12:41:14 - mmengine - INFO - Epoch(train) [25][120/940] lr: 1.0000e-02 eta: 13:15:06 time: 0.6440 data_time: 0.0383 memory: 24011 grad_norm: 4.2781 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1019 loss: 1.1019 2022/09/05 12:41:27 - mmengine - INFO - Epoch(train) [25][140/940] lr: 1.0000e-02 eta: 13:14:52 time: 0.6469 data_time: 0.0420 memory: 24011 grad_norm: 4.0727 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0947 loss: 1.0947 2022/09/05 12:41:40 - mmengine - INFO - Epoch(train) [25][160/940] lr: 1.0000e-02 eta: 13:14:36 time: 0.6347 data_time: 0.0366 memory: 24011 grad_norm: 4.3724 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.0116 loss: 1.0116 2022/09/05 12:41:53 - mmengine - INFO - Epoch(train) [25][180/940] lr: 1.0000e-02 eta: 13:14:22 time: 0.6504 data_time: 0.0400 memory: 24011 grad_norm: 4.5058 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1585 loss: 1.1585 2022/09/05 12:42:05 - mmengine - INFO - Epoch(train) [25][200/940] lr: 1.0000e-02 eta: 13:14:05 time: 0.6206 data_time: 0.0364 memory: 24011 grad_norm: 4.7414 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1106 loss: 1.1106 2022/09/05 12:42:19 - mmengine - INFO - Epoch(train) [25][220/940] lr: 1.0000e-02 eta: 13:13:53 time: 0.6817 data_time: 0.0442 memory: 24011 grad_norm: 4.9987 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1344 loss: 1.1344 2022/09/05 12:42:31 - mmengine - INFO - Epoch(train) [25][240/940] lr: 1.0000e-02 eta: 13:13:37 time: 0.6403 data_time: 0.0319 memory: 24011 grad_norm: 5.6010 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1097 loss: 1.1097 2022/09/05 12:42:45 - mmengine - INFO - Epoch(train) [25][260/940] lr: 1.0000e-02 eta: 13:13:24 time: 0.6710 data_time: 0.0398 memory: 24011 grad_norm: 4.6771 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.1970 loss: 1.1970 2022/09/05 12:42:58 - mmengine - INFO - Epoch(train) [25][280/940] lr: 1.0000e-02 eta: 13:13:09 time: 0.6337 data_time: 0.0367 memory: 24011 grad_norm: 4.4493 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2245 loss: 1.2245 2022/09/05 12:43:10 - mmengine - INFO - Epoch(train) [25][300/940] lr: 1.0000e-02 eta: 13:12:54 time: 0.6465 data_time: 0.0369 memory: 24011 grad_norm: 4.4670 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1847 loss: 1.1847 2022/09/05 12:43:24 - mmengine - INFO - Epoch(train) [25][320/940] lr: 1.0000e-02 eta: 13:12:40 time: 0.6606 data_time: 0.0347 memory: 24011 grad_norm: 4.6849 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2207 loss: 1.2207 2022/09/05 12:43:36 - mmengine - INFO - Epoch(train) [25][340/940] lr: 1.0000e-02 eta: 13:12:24 time: 0.6336 data_time: 0.0333 memory: 24011 grad_norm: 4.4532 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2457 loss: 1.2457 2022/09/05 12:43:50 - mmengine - INFO - Epoch(train) [25][360/940] lr: 1.0000e-02 eta: 13:12:11 time: 0.6728 data_time: 0.0700 memory: 24011 grad_norm: 4.5951 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2264 loss: 1.2264 2022/09/05 12:44:03 - mmengine - INFO - Epoch(train) [25][380/940] lr: 1.0000e-02 eta: 13:11:57 time: 0.6533 data_time: 0.0389 memory: 24011 grad_norm: 4.8090 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1235 loss: 1.1235 2022/09/05 12:44:16 - mmengine - INFO - Epoch(train) [25][400/940] lr: 1.0000e-02 eta: 13:11:41 time: 0.6328 data_time: 0.0313 memory: 24011 grad_norm: 4.3668 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0730 loss: 1.0730 2022/09/05 12:44:29 - mmengine - INFO - Epoch(train) [25][420/940] lr: 1.0000e-02 eta: 13:11:27 time: 0.6590 data_time: 0.0452 memory: 24011 grad_norm: 4.4860 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0435 loss: 1.0435 2022/09/05 12:44:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:44:41 - mmengine - INFO - Epoch(train) [25][440/940] lr: 1.0000e-02 eta: 13:11:10 time: 0.6030 data_time: 0.0406 memory: 24011 grad_norm: 4.1653 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1893 loss: 1.1893 2022/09/05 12:44:54 - mmengine - INFO - Epoch(train) [25][460/940] lr: 1.0000e-02 eta: 13:10:55 time: 0.6402 data_time: 0.0420 memory: 24011 grad_norm: 4.3112 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2135 loss: 1.2135 2022/09/05 12:45:06 - mmengine - INFO - Epoch(train) [25][480/940] lr: 1.0000e-02 eta: 13:10:40 time: 0.6400 data_time: 0.0482 memory: 24011 grad_norm: 4.4946 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1957 loss: 1.1957 2022/09/05 12:45:20 - mmengine - INFO - Epoch(train) [25][500/940] lr: 1.0000e-02 eta: 13:10:26 time: 0.6683 data_time: 0.0395 memory: 24011 grad_norm: 4.6375 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1434 loss: 1.1434 2022/09/05 12:45:32 - mmengine - INFO - Epoch(train) [25][520/940] lr: 1.0000e-02 eta: 13:10:10 time: 0.6223 data_time: 0.0345 memory: 24011 grad_norm: 4.3848 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2674 loss: 1.2674 2022/09/05 12:45:45 - mmengine - INFO - Epoch(train) [25][540/940] lr: 1.0000e-02 eta: 13:09:55 time: 0.6403 data_time: 0.0536 memory: 24011 grad_norm: 5.0787 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1057 loss: 1.1057 2022/09/05 12:45:59 - mmengine - INFO - Epoch(train) [25][560/940] lr: 1.0000e-02 eta: 13:09:44 time: 0.7071 data_time: 0.0375 memory: 24011 grad_norm: 4.2883 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1454 loss: 1.1454 2022/09/05 12:46:12 - mmengine - INFO - Epoch(train) [25][580/940] lr: 1.0000e-02 eta: 13:09:30 time: 0.6639 data_time: 0.0446 memory: 24011 grad_norm: 4.2908 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0974 loss: 1.0974 2022/09/05 12:46:26 - mmengine - INFO - Epoch(train) [25][600/940] lr: 1.0000e-02 eta: 13:09:17 time: 0.6655 data_time: 0.0409 memory: 24011 grad_norm: 4.5499 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1548 loss: 1.1548 2022/09/05 12:46:38 - mmengine - INFO - Epoch(train) [25][620/940] lr: 1.0000e-02 eta: 13:09:00 time: 0.6110 data_time: 0.0427 memory: 24011 grad_norm: 4.0858 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1509 loss: 1.1509 2022/09/05 12:46:51 - mmengine - INFO - Epoch(train) [25][640/940] lr: 1.0000e-02 eta: 13:08:45 time: 0.6489 data_time: 0.0537 memory: 24011 grad_norm: 4.1119 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0302 loss: 1.0302 2022/09/05 12:47:03 - mmengine - INFO - Epoch(train) [25][660/940] lr: 1.0000e-02 eta: 13:08:28 time: 0.6035 data_time: 0.0432 memory: 24011 grad_norm: 4.4922 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1637 loss: 1.1637 2022/09/05 12:47:16 - mmengine - INFO - Epoch(train) [25][680/940] lr: 1.0000e-02 eta: 13:08:12 time: 0.6293 data_time: 0.0356 memory: 24011 grad_norm: 4.2910 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0931 loss: 1.0931 2022/09/05 12:47:28 - mmengine - INFO - Epoch(train) [25][700/940] lr: 1.0000e-02 eta: 13:07:57 time: 0.6311 data_time: 0.0401 memory: 24011 grad_norm: 4.3387 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0950 loss: 1.0950 2022/09/05 12:47:41 - mmengine - INFO - Epoch(train) [25][720/940] lr: 1.0000e-02 eta: 13:07:42 time: 0.6503 data_time: 0.0466 memory: 24011 grad_norm: 4.5628 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1243 loss: 1.1243 2022/09/05 12:47:54 - mmengine - INFO - Epoch(train) [25][740/940] lr: 1.0000e-02 eta: 13:07:28 time: 0.6595 data_time: 0.0394 memory: 24011 grad_norm: 4.5402 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1026 loss: 1.1026 2022/09/05 12:48:07 - mmengine - INFO - Epoch(train) [25][760/940] lr: 1.0000e-02 eta: 13:07:13 time: 0.6290 data_time: 0.0353 memory: 24011 grad_norm: 4.7210 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1936 loss: 1.1936 2022/09/05 12:48:20 - mmengine - INFO - Epoch(train) [25][780/940] lr: 1.0000e-02 eta: 13:06:59 time: 0.6616 data_time: 0.0699 memory: 24011 grad_norm: 4.5380 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 0.9895 loss: 0.9895 2022/09/05 12:48:33 - mmengine - INFO - Epoch(train) [25][800/940] lr: 1.0000e-02 eta: 13:06:45 time: 0.6589 data_time: 0.0346 memory: 24011 grad_norm: 4.3983 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1087 loss: 1.1087 2022/09/05 12:48:46 - mmengine - INFO - Epoch(train) [25][820/940] lr: 1.0000e-02 eta: 13:06:30 time: 0.6474 data_time: 0.0408 memory: 24011 grad_norm: 4.6682 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2310 loss: 1.2310 2022/09/05 12:49:00 - mmengine - INFO - Epoch(train) [25][840/940] lr: 1.0000e-02 eta: 13:06:18 time: 0.6940 data_time: 0.0328 memory: 24011 grad_norm: 5.1826 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0686 loss: 1.0686 2022/09/05 12:49:13 - mmengine - INFO - Epoch(train) [25][860/940] lr: 1.0000e-02 eta: 13:06:04 time: 0.6497 data_time: 0.0343 memory: 24011 grad_norm: 4.4724 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1413 loss: 1.1413 2022/09/05 12:49:27 - mmengine - INFO - Epoch(train) [25][880/940] lr: 1.0000e-02 eta: 13:05:52 time: 0.6948 data_time: 0.0338 memory: 24011 grad_norm: 4.7293 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1337 loss: 1.1337 2022/09/05 12:49:40 - mmengine - INFO - Epoch(train) [25][900/940] lr: 1.0000e-02 eta: 13:05:36 time: 0.6147 data_time: 0.0394 memory: 24011 grad_norm: 4.4889 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0388 loss: 1.0388 2022/09/05 12:49:52 - mmengine - INFO - Epoch(train) [25][920/940] lr: 1.0000e-02 eta: 13:05:20 time: 0.6376 data_time: 0.0375 memory: 24011 grad_norm: 4.5337 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0598 loss: 1.0598 2022/09/05 12:50:03 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:50:03 - mmengine - INFO - Epoch(train) [25][940/940] lr: 1.0000e-02 eta: 13:05:00 time: 0.5436 data_time: 0.0296 memory: 24011 grad_norm: 4.5736 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.1059 loss: 1.1059 2022/09/05 12:50:17 - mmengine - INFO - Epoch(val) [25][20/78] eta: 0:00:40 time: 0.6916 data_time: 0.5334 memory: 3625 2022/09/05 12:50:26 - mmengine - INFO - Epoch(val) [25][40/78] eta: 0:00:17 time: 0.4659 data_time: 0.3099 memory: 3625 2022/09/05 12:50:39 - mmengine - INFO - Epoch(val) [25][60/78] eta: 0:00:11 time: 0.6373 data_time: 0.4798 memory: 3625 2022/09/05 12:50:50 - mmengine - INFO - Epoch(val) [25][78/78] acc/top1: 0.7163 acc/top5: 0.9028 acc/mean1: 0.7162 2022/09/05 12:51:09 - mmengine - INFO - Epoch(train) [26][20/940] lr: 1.0000e-02 eta: 13:05:04 time: 0.9571 data_time: 0.2878 memory: 24011 grad_norm: 4.4300 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1346 loss: 1.1346 2022/09/05 12:51:22 - mmengine - INFO - Epoch(train) [26][40/940] lr: 1.0000e-02 eta: 13:04:48 time: 0.6325 data_time: 0.0562 memory: 24011 grad_norm: 4.9038 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0046 loss: 1.0046 2022/09/05 12:51:34 - mmengine - INFO - Epoch(train) [26][60/940] lr: 1.0000e-02 eta: 13:04:33 time: 0.6386 data_time: 0.0406 memory: 24011 grad_norm: 4.5631 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0029 loss: 1.0029 2022/09/05 12:51:47 - mmengine - INFO - Epoch(train) [26][80/940] lr: 1.0000e-02 eta: 13:04:17 time: 0.6297 data_time: 0.0315 memory: 24011 grad_norm: 4.5943 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1943 loss: 1.1943 2022/09/05 12:52:00 - mmengine - INFO - Epoch(train) [26][100/940] lr: 1.0000e-02 eta: 13:04:03 time: 0.6510 data_time: 0.0527 memory: 24011 grad_norm: 4.4555 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0925 loss: 1.0925 2022/09/05 12:52:13 - mmengine - INFO - Epoch(train) [26][120/940] lr: 1.0000e-02 eta: 13:03:47 time: 0.6250 data_time: 0.0368 memory: 24011 grad_norm: 4.4281 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.1406 loss: 1.1406 2022/09/05 12:52:26 - mmengine - INFO - Epoch(train) [26][140/940] lr: 1.0000e-02 eta: 13:03:33 time: 0.6645 data_time: 0.0500 memory: 24011 grad_norm: 4.2590 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2123 loss: 1.2123 2022/09/05 12:52:38 - mmengine - INFO - Epoch(train) [26][160/940] lr: 1.0000e-02 eta: 13:03:17 time: 0.6219 data_time: 0.0394 memory: 24011 grad_norm: 4.3144 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0914 loss: 1.0914 2022/09/05 12:52:51 - mmengine - INFO - Epoch(train) [26][180/940] lr: 1.0000e-02 eta: 13:03:02 time: 0.6320 data_time: 0.0477 memory: 24011 grad_norm: 4.7613 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.9827 loss: 0.9827 2022/09/05 12:53:05 - mmengine - INFO - Epoch(train) [26][200/940] lr: 1.0000e-02 eta: 13:02:50 time: 0.6962 data_time: 0.0395 memory: 24011 grad_norm: 4.2449 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0525 loss: 1.0525 2022/09/05 12:53:17 - mmengine - INFO - Epoch(train) [26][220/940] lr: 1.0000e-02 eta: 13:02:34 time: 0.6269 data_time: 0.0411 memory: 24011 grad_norm: 4.2006 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1211 loss: 1.1211 2022/09/05 12:53:31 - mmengine - INFO - Epoch(train) [26][240/940] lr: 1.0000e-02 eta: 13:02:23 time: 0.7025 data_time: 0.0424 memory: 24011 grad_norm: 4.1093 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1101 loss: 1.1101 2022/09/05 12:53:45 - mmengine - INFO - Epoch(train) [26][260/940] lr: 1.0000e-02 eta: 13:02:09 time: 0.6549 data_time: 0.0371 memory: 24011 grad_norm: 4.1482 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1271 loss: 1.1271 2022/09/05 12:53:58 - mmengine - INFO - Epoch(train) [26][280/940] lr: 1.0000e-02 eta: 13:01:57 time: 0.6909 data_time: 0.0418 memory: 24011 grad_norm: 4.3358 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1112 loss: 1.1112 2022/09/05 12:54:10 - mmengine - INFO - Epoch(train) [26][300/940] lr: 1.0000e-02 eta: 13:01:40 time: 0.6044 data_time: 0.0404 memory: 24011 grad_norm: 4.3948 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1943 loss: 1.1943 2022/09/05 12:54:24 - mmengine - INFO - Epoch(train) [26][320/940] lr: 1.0000e-02 eta: 13:01:26 time: 0.6634 data_time: 0.0363 memory: 24011 grad_norm: 4.2216 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0575 loss: 1.0575 2022/09/05 12:54:36 - mmengine - INFO - Epoch(train) [26][340/940] lr: 1.0000e-02 eta: 13:01:10 time: 0.6192 data_time: 0.0433 memory: 24011 grad_norm: 4.3677 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1762 loss: 1.1762 2022/09/05 12:54:49 - mmengine - INFO - Epoch(train) [26][360/940] lr: 1.0000e-02 eta: 13:00:56 time: 0.6635 data_time: 0.0343 memory: 24011 grad_norm: 4.4215 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0904 loss: 1.0904 2022/09/05 12:55:02 - mmengine - INFO - Epoch(train) [26][380/940] lr: 1.0000e-02 eta: 13:00:40 time: 0.6288 data_time: 0.0376 memory: 24011 grad_norm: 4.2874 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0800 loss: 1.0800 2022/09/05 12:55:16 - mmengine - INFO - Epoch(train) [26][400/940] lr: 1.0000e-02 eta: 13:00:28 time: 0.6825 data_time: 0.0372 memory: 24011 grad_norm: 4.4834 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0967 loss: 1.0967 2022/09/05 12:55:28 - mmengine - INFO - Epoch(train) [26][420/940] lr: 1.0000e-02 eta: 13:00:13 time: 0.6362 data_time: 0.0416 memory: 24011 grad_norm: 4.3730 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1958 loss: 1.1958 2022/09/05 12:55:41 - mmengine - INFO - Epoch(train) [26][440/940] lr: 1.0000e-02 eta: 12:59:58 time: 0.6394 data_time: 0.0320 memory: 24011 grad_norm: 4.4513 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0556 loss: 1.0556 2022/09/05 12:55:54 - mmengine - INFO - Epoch(train) [26][460/940] lr: 1.0000e-02 eta: 12:59:43 time: 0.6480 data_time: 0.0536 memory: 24011 grad_norm: 4.3105 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0953 loss: 1.0953 2022/09/05 12:56:08 - mmengine - INFO - Epoch(train) [26][480/940] lr: 1.0000e-02 eta: 12:59:30 time: 0.6709 data_time: 0.0322 memory: 24011 grad_norm: 4.3828 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1173 loss: 1.1173 2022/09/05 12:56:20 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 12:56:20 - mmengine - INFO - Epoch(train) [26][500/940] lr: 1.0000e-02 eta: 12:59:14 time: 0.6263 data_time: 0.0452 memory: 24011 grad_norm: 4.4663 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0480 loss: 1.0480 2022/09/05 12:56:34 - mmengine - INFO - Epoch(train) [26][520/940] lr: 1.0000e-02 eta: 12:59:02 time: 0.6971 data_time: 0.0389 memory: 24011 grad_norm: 4.1937 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1119 loss: 1.1119 2022/09/05 12:56:46 - mmengine - INFO - Epoch(train) [26][540/940] lr: 1.0000e-02 eta: 12:58:46 time: 0.6174 data_time: 0.0345 memory: 24011 grad_norm: 4.0342 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1043 loss: 1.1043 2022/09/05 12:56:59 - mmengine - INFO - Epoch(train) [26][560/940] lr: 1.0000e-02 eta: 12:58:32 time: 0.6495 data_time: 0.0380 memory: 24011 grad_norm: 4.2641 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.1706 loss: 1.1706 2022/09/05 12:57:12 - mmengine - INFO - Epoch(train) [26][580/940] lr: 1.0000e-02 eta: 12:58:16 time: 0.6187 data_time: 0.0422 memory: 24011 grad_norm: 4.4748 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0359 loss: 1.0359 2022/09/05 12:57:25 - mmengine - INFO - Epoch(train) [26][600/940] lr: 1.0000e-02 eta: 12:58:01 time: 0.6440 data_time: 0.0400 memory: 24011 grad_norm: 4.1846 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0230 loss: 1.0230 2022/09/05 12:57:38 - mmengine - INFO - Epoch(train) [26][620/940] lr: 1.0000e-02 eta: 12:57:46 time: 0.6430 data_time: 0.0442 memory: 24011 grad_norm: 4.2071 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1672 loss: 1.1672 2022/09/05 12:57:51 - mmengine - INFO - Epoch(train) [26][640/940] lr: 1.0000e-02 eta: 12:57:34 time: 0.6913 data_time: 0.0390 memory: 24011 grad_norm: 4.1975 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1878 loss: 1.1878 2022/09/05 12:58:03 - mmengine - INFO - Epoch(train) [26][660/940] lr: 1.0000e-02 eta: 12:57:16 time: 0.5956 data_time: 0.0364 memory: 24011 grad_norm: 4.3293 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0989 loss: 1.0989 2022/09/05 12:58:16 - mmengine - INFO - Epoch(train) [26][680/940] lr: 1.0000e-02 eta: 12:57:01 time: 0.6363 data_time: 0.0414 memory: 24011 grad_norm: 4.3763 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0389 loss: 1.0389 2022/09/05 12:58:29 - mmengine - INFO - Epoch(train) [26][700/940] lr: 1.0000e-02 eta: 12:56:47 time: 0.6599 data_time: 0.0439 memory: 24011 grad_norm: 4.3323 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0200 loss: 1.0200 2022/09/05 12:58:43 - mmengine - INFO - Epoch(train) [26][720/940] lr: 1.0000e-02 eta: 12:56:35 time: 0.6799 data_time: 0.0458 memory: 24011 grad_norm: 4.4693 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0786 loss: 1.0786 2022/09/05 12:58:55 - mmengine - INFO - Epoch(train) [26][740/940] lr: 1.0000e-02 eta: 12:56:19 time: 0.6233 data_time: 0.0382 memory: 24011 grad_norm: 4.6743 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0425 loss: 1.0425 2022/09/05 12:59:09 - mmengine - INFO - Epoch(train) [26][760/940] lr: 1.0000e-02 eta: 12:56:07 time: 0.6911 data_time: 0.0383 memory: 24011 grad_norm: 4.3497 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 0.9994 loss: 0.9994 2022/09/05 12:59:22 - mmengine - INFO - Epoch(train) [26][780/940] lr: 1.0000e-02 eta: 12:55:50 time: 0.6101 data_time: 0.0440 memory: 24011 grad_norm: 5.0338 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1500 loss: 1.1500 2022/09/05 12:59:35 - mmengine - INFO - Epoch(train) [26][800/940] lr: 1.0000e-02 eta: 12:55:38 time: 0.6930 data_time: 0.0552 memory: 24011 grad_norm: 4.2644 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1803 loss: 1.1803 2022/09/05 12:59:48 - mmengine - INFO - Epoch(train) [26][820/940] lr: 1.0000e-02 eta: 12:55:24 time: 0.6433 data_time: 0.0480 memory: 24011 grad_norm: 4.4841 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0841 loss: 1.0841 2022/09/05 13:00:01 - mmengine - INFO - Epoch(train) [26][840/940] lr: 1.0000e-02 eta: 12:55:10 time: 0.6680 data_time: 0.0351 memory: 24011 grad_norm: 4.2110 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1290 loss: 1.1290 2022/09/05 13:00:14 - mmengine - INFO - Epoch(train) [26][860/940] lr: 1.0000e-02 eta: 12:54:55 time: 0.6315 data_time: 0.0598 memory: 24011 grad_norm: 4.3481 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0692 loss: 1.0692 2022/09/05 13:00:26 - mmengine - INFO - Epoch(train) [26][880/940] lr: 1.0000e-02 eta: 12:54:38 time: 0.6079 data_time: 0.0483 memory: 24011 grad_norm: 4.0827 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1265 loss: 1.1265 2022/09/05 13:00:40 - mmengine - INFO - Epoch(train) [26][900/940] lr: 1.0000e-02 eta: 12:54:26 time: 0.6827 data_time: 0.0423 memory: 24011 grad_norm: 4.3673 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.0854 loss: 1.0854 2022/09/05 13:00:53 - mmengine - INFO - Epoch(train) [26][920/940] lr: 1.0000e-02 eta: 12:54:11 time: 0.6377 data_time: 0.0414 memory: 24011 grad_norm: 4.4614 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0545 loss: 1.0545 2022/09/05 13:01:04 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:01:04 - mmengine - INFO - Epoch(train) [26][940/940] lr: 1.0000e-02 eta: 12:53:52 time: 0.5728 data_time: 0.0258 memory: 24011 grad_norm: 4.4591 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1289 loss: 1.1289 2022/09/05 13:01:18 - mmengine - INFO - Epoch(val) [26][20/78] eta: 0:00:40 time: 0.6936 data_time: 0.5358 memory: 3625 2022/09/05 13:01:27 - mmengine - INFO - Epoch(val) [26][40/78] eta: 0:00:17 time: 0.4506 data_time: 0.2941 memory: 3625 2022/09/05 13:01:40 - mmengine - INFO - Epoch(val) [26][60/78] eta: 0:00:11 time: 0.6531 data_time: 0.4970 memory: 3625 2022/09/05 13:01:50 - mmengine - INFO - Epoch(val) [26][78/78] acc/top1: 0.7194 acc/top5: 0.9040 acc/mean1: 0.7193 2022/09/05 13:01:51 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_14.pth is removed 2022/09/05 13:01:53 - mmengine - INFO - The best checkpoint with 0.7194 acc/top1 at 27 epoch is saved to best_acc/top1_epoch_27.pth. 2022/09/05 13:02:10 - mmengine - INFO - Epoch(train) [27][20/940] lr: 1.0000e-02 eta: 12:53:48 time: 0.8347 data_time: 0.2918 memory: 24011 grad_norm: 4.4252 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1984 loss: 1.1984 2022/09/05 13:02:23 - mmengine - INFO - Epoch(train) [27][40/940] lr: 1.0000e-02 eta: 12:53:34 time: 0.6590 data_time: 0.1047 memory: 24011 grad_norm: 4.2114 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9908 loss: 0.9908 2022/09/05 13:02:36 - mmengine - INFO - Epoch(train) [27][60/940] lr: 1.0000e-02 eta: 12:53:18 time: 0.6242 data_time: 0.0399 memory: 24011 grad_norm: 4.0712 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1138 loss: 1.1138 2022/09/05 13:02:48 - mmengine - INFO - Epoch(train) [27][80/940] lr: 1.0000e-02 eta: 12:53:02 time: 0.6207 data_time: 0.0647 memory: 24011 grad_norm: 4.1043 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0398 loss: 1.0398 2022/09/05 13:03:02 - mmengine - INFO - Epoch(train) [27][100/940] lr: 1.0000e-02 eta: 12:52:50 time: 0.6901 data_time: 0.1202 memory: 24011 grad_norm: 4.1513 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1271 loss: 1.1271 2022/09/05 13:03:14 - mmengine - INFO - Epoch(train) [27][120/940] lr: 1.0000e-02 eta: 12:52:33 time: 0.5957 data_time: 0.0328 memory: 24011 grad_norm: 4.2477 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1120 loss: 1.1120 2022/09/05 13:03:27 - mmengine - INFO - Epoch(train) [27][140/940] lr: 1.0000e-02 eta: 12:52:20 time: 0.6762 data_time: 0.0904 memory: 24011 grad_norm: 4.3918 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1484 loss: 1.1484 2022/09/05 13:03:40 - mmengine - INFO - Epoch(train) [27][160/940] lr: 1.0000e-02 eta: 12:52:05 time: 0.6357 data_time: 0.0667 memory: 24011 grad_norm: 4.5800 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1240 loss: 1.1240 2022/09/05 13:03:53 - mmengine - INFO - Epoch(train) [27][180/940] lr: 1.0000e-02 eta: 12:51:51 time: 0.6569 data_time: 0.0693 memory: 24011 grad_norm: 4.7364 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0990 loss: 1.0990 2022/09/05 13:04:06 - mmengine - INFO - Epoch(train) [27][200/940] lr: 1.0000e-02 eta: 12:51:37 time: 0.6540 data_time: 0.0772 memory: 24011 grad_norm: 4.2375 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1758 loss: 1.1758 2022/09/05 13:04:19 - mmengine - INFO - Epoch(train) [27][220/940] lr: 1.0000e-02 eta: 12:51:20 time: 0.6138 data_time: 0.0398 memory: 24011 grad_norm: 4.6102 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0982 loss: 1.0982 2022/09/05 13:04:31 - mmengine - INFO - Epoch(train) [27][240/940] lr: 1.0000e-02 eta: 12:51:05 time: 0.6404 data_time: 0.0621 memory: 24011 grad_norm: 4.4271 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0842 loss: 1.0842 2022/09/05 13:04:44 - mmengine - INFO - Epoch(train) [27][260/940] lr: 1.0000e-02 eta: 12:50:50 time: 0.6297 data_time: 0.0360 memory: 24011 grad_norm: 4.7072 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 1.1597 loss: 1.1597 2022/09/05 13:04:57 - mmengine - INFO - Epoch(train) [27][280/940] lr: 1.0000e-02 eta: 12:50:37 time: 0.6680 data_time: 0.0380 memory: 24011 grad_norm: 4.3547 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1128 loss: 1.1128 2022/09/05 13:05:10 - mmengine - INFO - Epoch(train) [27][300/940] lr: 1.0000e-02 eta: 12:50:22 time: 0.6397 data_time: 0.0358 memory: 24011 grad_norm: 6.1499 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1641 loss: 1.1641 2022/09/05 13:05:23 - mmengine - INFO - Epoch(train) [27][320/940] lr: 1.0000e-02 eta: 12:50:06 time: 0.6297 data_time: 0.0390 memory: 24011 grad_norm: 4.8150 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2163 loss: 1.2163 2022/09/05 13:05:36 - mmengine - INFO - Epoch(train) [27][340/940] lr: 1.0000e-02 eta: 12:49:52 time: 0.6448 data_time: 0.0370 memory: 24011 grad_norm: 4.7553 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1663 loss: 1.1663 2022/09/05 13:05:48 - mmengine - INFO - Epoch(train) [27][360/940] lr: 1.0000e-02 eta: 12:49:37 time: 0.6380 data_time: 0.0687 memory: 24011 grad_norm: 4.9087 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2537 loss: 1.2537 2022/09/05 13:06:02 - mmengine - INFO - Epoch(train) [27][380/940] lr: 1.0000e-02 eta: 12:49:23 time: 0.6543 data_time: 0.0695 memory: 24011 grad_norm: 4.7929 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1179 loss: 1.1179 2022/09/05 13:06:14 - mmengine - INFO - Epoch(train) [27][400/940] lr: 1.0000e-02 eta: 12:49:08 time: 0.6373 data_time: 0.0444 memory: 24011 grad_norm: 4.5869 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 0.9408 loss: 0.9408 2022/09/05 13:06:28 - mmengine - INFO - Epoch(train) [27][420/940] lr: 1.0000e-02 eta: 12:48:56 time: 0.6982 data_time: 0.1056 memory: 24011 grad_norm: 5.5657 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1663 loss: 1.1663 2022/09/05 13:06:41 - mmengine - INFO - Epoch(train) [27][440/940] lr: 1.0000e-02 eta: 12:48:42 time: 0.6567 data_time: 0.0762 memory: 24011 grad_norm: 4.7706 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0400 loss: 1.0400 2022/09/05 13:06:55 - mmengine - INFO - Epoch(train) [27][460/940] lr: 1.0000e-02 eta: 12:48:30 time: 0.6859 data_time: 0.0899 memory: 24011 grad_norm: 4.4071 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0972 loss: 1.0972 2022/09/05 13:07:08 - mmengine - INFO - Epoch(train) [27][480/940] lr: 1.0000e-02 eta: 12:48:14 time: 0.6279 data_time: 0.0530 memory: 24011 grad_norm: 4.4898 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1492 loss: 1.1492 2022/09/05 13:07:21 - mmengine - INFO - Epoch(train) [27][500/940] lr: 1.0000e-02 eta: 12:48:00 time: 0.6520 data_time: 0.0831 memory: 24011 grad_norm: 4.6444 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0130 loss: 1.0130 2022/09/05 13:07:33 - mmengine - INFO - Epoch(train) [27][520/940] lr: 1.0000e-02 eta: 12:47:43 time: 0.6032 data_time: 0.0313 memory: 24011 grad_norm: 5.0716 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1126 loss: 1.1126 2022/09/05 13:07:46 - mmengine - INFO - Epoch(train) [27][540/940] lr: 1.0000e-02 eta: 12:47:29 time: 0.6610 data_time: 0.0431 memory: 24011 grad_norm: 4.7115 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1422 loss: 1.1422 2022/09/05 13:07:59 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:07:59 - mmengine - INFO - Epoch(train) [27][560/940] lr: 1.0000e-02 eta: 12:47:14 time: 0.6307 data_time: 0.0339 memory: 24011 grad_norm: 4.3281 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1309 loss: 1.1309 2022/09/05 13:08:12 - mmengine - INFO - Epoch(train) [27][580/940] lr: 1.0000e-02 eta: 12:47:01 time: 0.6698 data_time: 0.0318 memory: 24011 grad_norm: 4.4178 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1580 loss: 1.1580 2022/09/05 13:08:25 - mmengine - INFO - Epoch(train) [27][600/940] lr: 1.0000e-02 eta: 12:46:46 time: 0.6352 data_time: 0.0379 memory: 24011 grad_norm: 4.1494 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.1118 loss: 1.1118 2022/09/05 13:08:38 - mmengine - INFO - Epoch(train) [27][620/940] lr: 1.0000e-02 eta: 12:46:33 time: 0.6757 data_time: 0.0362 memory: 24011 grad_norm: 4.2465 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1587 loss: 1.1587 2022/09/05 13:08:50 - mmengine - INFO - Epoch(train) [27][640/940] lr: 1.0000e-02 eta: 12:46:16 time: 0.5965 data_time: 0.0375 memory: 24011 grad_norm: 5.7795 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0651 loss: 1.0651 2022/09/05 13:09:03 - mmengine - INFO - Epoch(train) [27][660/940] lr: 1.0000e-02 eta: 12:46:02 time: 0.6565 data_time: 0.0375 memory: 24011 grad_norm: 4.4532 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1922 loss: 1.1922 2022/09/05 13:09:16 - mmengine - INFO - Epoch(train) [27][680/940] lr: 1.0000e-02 eta: 12:45:46 time: 0.6277 data_time: 0.0414 memory: 24011 grad_norm: 4.3102 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1527 loss: 1.1527 2022/09/05 13:09:30 - mmengine - INFO - Epoch(train) [27][700/940] lr: 1.0000e-02 eta: 12:45:34 time: 0.6872 data_time: 0.0406 memory: 24011 grad_norm: 4.5403 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2010 loss: 1.2010 2022/09/05 13:09:42 - mmengine - INFO - Epoch(train) [27][720/940] lr: 1.0000e-02 eta: 12:45:18 time: 0.6167 data_time: 0.0416 memory: 24011 grad_norm: 4.3542 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1425 loss: 1.1425 2022/09/05 13:09:55 - mmengine - INFO - Epoch(train) [27][740/940] lr: 1.0000e-02 eta: 12:45:05 time: 0.6660 data_time: 0.0459 memory: 24011 grad_norm: 4.3990 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1223 loss: 1.1223 2022/09/05 13:10:08 - mmengine - INFO - Epoch(train) [27][760/940] lr: 1.0000e-02 eta: 12:44:50 time: 0.6528 data_time: 0.0664 memory: 24011 grad_norm: 4.3314 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0084 loss: 1.0084 2022/09/05 13:10:21 - mmengine - INFO - Epoch(train) [27][780/940] lr: 1.0000e-02 eta: 12:44:35 time: 0.6341 data_time: 0.0433 memory: 24011 grad_norm: 4.4617 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2196 loss: 1.2196 2022/09/05 13:10:34 - mmengine - INFO - Epoch(train) [27][800/940] lr: 1.0000e-02 eta: 12:44:21 time: 0.6495 data_time: 0.0410 memory: 24011 grad_norm: 4.7901 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1004 loss: 1.1004 2022/09/05 13:10:47 - mmengine - INFO - Epoch(train) [27][820/940] lr: 1.0000e-02 eta: 12:44:07 time: 0.6489 data_time: 0.0394 memory: 24011 grad_norm: 4.4811 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1435 loss: 1.1435 2022/09/05 13:11:00 - mmengine - INFO - Epoch(train) [27][840/940] lr: 1.0000e-02 eta: 12:43:52 time: 0.6365 data_time: 0.0387 memory: 24011 grad_norm: 4.6826 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0976 loss: 1.0976 2022/09/05 13:11:13 - mmengine - INFO - Epoch(train) [27][860/940] lr: 1.0000e-02 eta: 12:43:37 time: 0.6427 data_time: 0.0391 memory: 24011 grad_norm: 4.8197 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2888 loss: 1.2888 2022/09/05 13:11:25 - mmengine - INFO - Epoch(train) [27][880/940] lr: 1.0000e-02 eta: 12:43:22 time: 0.6440 data_time: 0.0395 memory: 24011 grad_norm: 4.4986 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9808 loss: 0.9808 2022/09/05 13:11:39 - mmengine - INFO - Epoch(train) [27][900/940] lr: 1.0000e-02 eta: 12:43:09 time: 0.6602 data_time: 0.0400 memory: 24011 grad_norm: 4.3955 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1160 loss: 1.1160 2022/09/05 13:11:51 - mmengine - INFO - Epoch(train) [27][920/940] lr: 1.0000e-02 eta: 12:42:52 time: 0.6078 data_time: 0.0393 memory: 24011 grad_norm: 4.3100 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0462 loss: 1.0462 2022/09/05 13:12:02 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:12:02 - mmengine - INFO - Epoch(train) [27][940/940] lr: 1.0000e-02 eta: 12:42:33 time: 0.5658 data_time: 0.0258 memory: 24011 grad_norm: 4.4198 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2126 loss: 1.2126 2022/09/05 13:12:02 - mmengine - INFO - Saving checkpoint at 27 epochs 2022/09/05 13:12:22 - mmengine - INFO - Epoch(val) [27][20/78] eta: 0:00:42 time: 0.7293 data_time: 0.5737 memory: 3625 2022/09/05 13:12:31 - mmengine - INFO - Epoch(val) [27][40/78] eta: 0:00:17 time: 0.4576 data_time: 0.3031 memory: 3625 2022/09/05 13:12:44 - mmengine - INFO - Epoch(val) [27][60/78] eta: 0:00:11 time: 0.6470 data_time: 0.4939 memory: 3625 2022/09/05 13:12:53 - mmengine - INFO - Epoch(val) [27][78/78] acc/top1: 0.7173 acc/top5: 0.9010 acc/mean1: 0.7171 2022/09/05 13:13:12 - mmengine - INFO - Epoch(train) [28][20/940] lr: 1.0000e-02 eta: 12:42:35 time: 0.9441 data_time: 0.2996 memory: 24011 grad_norm: 4.0985 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0032 loss: 1.0032 2022/09/05 13:13:25 - mmengine - INFO - Epoch(train) [28][40/940] lr: 1.0000e-02 eta: 12:42:22 time: 0.6636 data_time: 0.0343 memory: 24011 grad_norm: 4.5945 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0457 loss: 1.0457 2022/09/05 13:13:38 - mmengine - INFO - Epoch(train) [28][60/940] lr: 1.0000e-02 eta: 12:42:07 time: 0.6448 data_time: 0.0370 memory: 24011 grad_norm: 4.3242 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 0.9751 loss: 0.9751 2022/09/05 13:13:51 - mmengine - INFO - Epoch(train) [28][80/940] lr: 1.0000e-02 eta: 12:41:52 time: 0.6430 data_time: 0.0329 memory: 24011 grad_norm: 5.1475 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1894 loss: 1.1894 2022/09/05 13:14:04 - mmengine - INFO - Epoch(train) [28][100/940] lr: 1.0000e-02 eta: 12:41:39 time: 0.6629 data_time: 0.0391 memory: 24011 grad_norm: 4.5281 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.1683 loss: 1.1683 2022/09/05 13:14:17 - mmengine - INFO - Epoch(train) [28][120/940] lr: 1.0000e-02 eta: 12:41:23 time: 0.6275 data_time: 0.0300 memory: 24011 grad_norm: 4.8958 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0784 loss: 1.0784 2022/09/05 13:14:30 - mmengine - INFO - Epoch(train) [28][140/940] lr: 1.0000e-02 eta: 12:41:10 time: 0.6583 data_time: 0.0386 memory: 24011 grad_norm: 4.6435 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1571 loss: 1.1571 2022/09/05 13:14:43 - mmengine - INFO - Epoch(train) [28][160/940] lr: 1.0000e-02 eta: 12:40:55 time: 0.6430 data_time: 0.0365 memory: 24011 grad_norm: 4.9341 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1521 loss: 1.1521 2022/09/05 13:14:56 - mmengine - INFO - Epoch(train) [28][180/940] lr: 1.0000e-02 eta: 12:40:40 time: 0.6281 data_time: 0.0437 memory: 24011 grad_norm: 4.1759 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0495 loss: 1.0495 2022/09/05 13:15:08 - mmengine - INFO - Epoch(train) [28][200/940] lr: 1.0000e-02 eta: 12:40:24 time: 0.6328 data_time: 0.0521 memory: 24011 grad_norm: 4.5601 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0524 loss: 1.0524 2022/09/05 13:15:21 - mmengine - INFO - Epoch(train) [28][220/940] lr: 1.0000e-02 eta: 12:40:11 time: 0.6663 data_time: 0.0369 memory: 24011 grad_norm: 4.8116 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1255 loss: 1.1255 2022/09/05 13:15:34 - mmengine - INFO - Epoch(train) [28][240/940] lr: 1.0000e-02 eta: 12:39:55 time: 0.6135 data_time: 0.0355 memory: 24011 grad_norm: 4.2824 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1885 loss: 1.1885 2022/09/05 13:15:47 - mmengine - INFO - Epoch(train) [28][260/940] lr: 1.0000e-02 eta: 12:39:41 time: 0.6635 data_time: 0.0414 memory: 24011 grad_norm: 4.4264 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0519 loss: 1.0519 2022/09/05 13:16:00 - mmengine - INFO - Epoch(train) [28][280/940] lr: 1.0000e-02 eta: 12:39:26 time: 0.6351 data_time: 0.0371 memory: 24011 grad_norm: 4.4121 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1227 loss: 1.1227 2022/09/05 13:16:13 - mmengine - INFO - Epoch(train) [28][300/940] lr: 1.0000e-02 eta: 12:39:14 time: 0.6900 data_time: 0.0426 memory: 24011 grad_norm: 4.6396 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9870 loss: 0.9870 2022/09/05 13:16:26 - mmengine - INFO - Epoch(train) [28][320/940] lr: 1.0000e-02 eta: 12:38:59 time: 0.6287 data_time: 0.0386 memory: 24011 grad_norm: 5.7701 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0655 loss: 1.0655 2022/09/05 13:16:39 - mmengine - INFO - Epoch(train) [28][340/940] lr: 1.0000e-02 eta: 12:38:45 time: 0.6613 data_time: 0.0439 memory: 24011 grad_norm: 4.7898 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0072 loss: 1.0072 2022/09/05 13:16:52 - mmengine - INFO - Epoch(train) [28][360/940] lr: 1.0000e-02 eta: 12:38:30 time: 0.6354 data_time: 0.0623 memory: 24011 grad_norm: 4.8768 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0874 loss: 1.0874 2022/09/05 13:17:05 - mmengine - INFO - Epoch(train) [28][380/940] lr: 1.0000e-02 eta: 12:38:17 time: 0.6618 data_time: 0.0596 memory: 24011 grad_norm: 4.5142 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0378 loss: 1.0378 2022/09/05 13:17:18 - mmengine - INFO - Epoch(train) [28][400/940] lr: 1.0000e-02 eta: 12:38:03 time: 0.6523 data_time: 0.0439 memory: 24011 grad_norm: 4.6867 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1543 loss: 1.1543 2022/09/05 13:17:31 - mmengine - INFO - Epoch(train) [28][420/940] lr: 1.0000e-02 eta: 12:37:47 time: 0.6241 data_time: 0.0438 memory: 24011 grad_norm: 4.9201 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1720 loss: 1.1720 2022/09/05 13:17:44 - mmengine - INFO - Epoch(train) [28][440/940] lr: 1.0000e-02 eta: 12:37:34 time: 0.6784 data_time: 0.0500 memory: 24011 grad_norm: 4.9243 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9746 loss: 0.9746 2022/09/05 13:17:57 - mmengine - INFO - Epoch(train) [28][460/940] lr: 1.0000e-02 eta: 12:37:20 time: 0.6479 data_time: 0.0444 memory: 24011 grad_norm: 4.7564 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1360 loss: 1.1360 2022/09/05 13:18:10 - mmengine - INFO - Epoch(train) [28][480/940] lr: 1.0000e-02 eta: 12:37:06 time: 0.6472 data_time: 0.0435 memory: 24011 grad_norm: 4.4097 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0682 loss: 1.0682 2022/09/05 13:18:22 - mmengine - INFO - Epoch(train) [28][500/940] lr: 1.0000e-02 eta: 12:36:49 time: 0.6153 data_time: 0.0450 memory: 24011 grad_norm: 4.5380 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1107 loss: 1.1107 2022/09/05 13:18:35 - mmengine - INFO - Epoch(train) [28][520/940] lr: 1.0000e-02 eta: 12:36:35 time: 0.6376 data_time: 0.0382 memory: 24011 grad_norm: 4.6471 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1884 loss: 1.1884 2022/09/05 13:18:48 - mmengine - INFO - Epoch(train) [28][540/940] lr: 1.0000e-02 eta: 12:36:20 time: 0.6333 data_time: 0.0386 memory: 24011 grad_norm: 4.4200 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9491 loss: 0.9491 2022/09/05 13:19:01 - mmengine - INFO - Epoch(train) [28][560/940] lr: 1.0000e-02 eta: 12:36:06 time: 0.6570 data_time: 0.0412 memory: 24011 grad_norm: 4.8208 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2733 loss: 1.2733 2022/09/05 13:19:15 - mmengine - INFO - Epoch(train) [28][580/940] lr: 1.0000e-02 eta: 12:35:53 time: 0.6801 data_time: 0.0336 memory: 24011 grad_norm: 4.4460 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1424 loss: 1.1424 2022/09/05 13:19:27 - mmengine - INFO - Epoch(train) [28][600/940] lr: 1.0000e-02 eta: 12:35:38 time: 0.6419 data_time: 0.0396 memory: 24011 grad_norm: 4.8979 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1572 loss: 1.1572 2022/09/05 13:19:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:19:41 - mmengine - INFO - Epoch(train) [28][620/940] lr: 1.0000e-02 eta: 12:35:26 time: 0.6750 data_time: 0.0369 memory: 24011 grad_norm: 4.6954 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0945 loss: 1.0945 2022/09/05 13:19:54 - mmengine - INFO - Epoch(train) [28][640/940] lr: 1.0000e-02 eta: 12:35:10 time: 0.6303 data_time: 0.0401 memory: 24011 grad_norm: 5.1614 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1538 loss: 1.1538 2022/09/05 13:20:06 - mmengine - INFO - Epoch(train) [28][660/940] lr: 1.0000e-02 eta: 12:34:55 time: 0.6230 data_time: 0.0367 memory: 24011 grad_norm: 4.4849 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1563 loss: 1.1563 2022/09/05 13:20:19 - mmengine - INFO - Epoch(train) [28][680/940] lr: 1.0000e-02 eta: 12:34:39 time: 0.6294 data_time: 0.0787 memory: 24011 grad_norm: 4.2959 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9798 loss: 0.9798 2022/09/05 13:20:32 - mmengine - INFO - Epoch(train) [28][700/940] lr: 1.0000e-02 eta: 12:34:25 time: 0.6489 data_time: 0.0565 memory: 24011 grad_norm: 4.4197 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2225 loss: 1.2225 2022/09/05 13:20:45 - mmengine - INFO - Epoch(train) [28][720/940] lr: 1.0000e-02 eta: 12:34:12 time: 0.6598 data_time: 0.0851 memory: 24011 grad_norm: 4.3174 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1882 loss: 1.1882 2022/09/05 13:20:58 - mmengine - INFO - Epoch(train) [28][740/940] lr: 1.0000e-02 eta: 12:33:57 time: 0.6449 data_time: 0.0518 memory: 24011 grad_norm: 4.8893 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0368 loss: 1.0368 2022/09/05 13:21:12 - mmengine - INFO - Epoch(train) [28][760/940] lr: 1.0000e-02 eta: 12:33:45 time: 0.6883 data_time: 0.1248 memory: 24011 grad_norm: 4.5660 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0036 loss: 1.0036 2022/09/05 13:21:25 - mmengine - INFO - Epoch(train) [28][780/940] lr: 1.0000e-02 eta: 12:33:32 time: 0.6801 data_time: 0.0980 memory: 24011 grad_norm: 4.5863 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1337 loss: 1.1337 2022/09/05 13:21:38 - mmengine - INFO - Epoch(train) [28][800/940] lr: 1.0000e-02 eta: 12:33:19 time: 0.6657 data_time: 0.0990 memory: 24011 grad_norm: 4.5247 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1398 loss: 1.1398 2022/09/05 13:21:51 - mmengine - INFO - Epoch(train) [28][820/940] lr: 1.0000e-02 eta: 12:33:05 time: 0.6518 data_time: 0.0846 memory: 24011 grad_norm: 4.7375 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.2076 loss: 1.2076 2022/09/05 13:22:04 - mmengine - INFO - Epoch(train) [28][840/940] lr: 1.0000e-02 eta: 12:32:50 time: 0.6378 data_time: 0.0759 memory: 24011 grad_norm: 4.6279 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0911 loss: 1.0911 2022/09/05 13:22:17 - mmengine - INFO - Epoch(train) [28][860/940] lr: 1.0000e-02 eta: 12:32:35 time: 0.6293 data_time: 0.0697 memory: 24011 grad_norm: 4.5484 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1321 loss: 1.1321 2022/09/05 13:22:30 - mmengine - INFO - Epoch(train) [28][880/940] lr: 1.0000e-02 eta: 12:32:22 time: 0.6719 data_time: 0.0805 memory: 24011 grad_norm: 4.5637 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1304 loss: 1.1304 2022/09/05 13:22:42 - mmengine - INFO - Epoch(train) [28][900/940] lr: 1.0000e-02 eta: 12:32:06 time: 0.6122 data_time: 0.0523 memory: 24011 grad_norm: 4.3748 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.0663 loss: 1.0663 2022/09/05 13:22:55 - mmengine - INFO - Epoch(train) [28][920/940] lr: 1.0000e-02 eta: 12:31:51 time: 0.6401 data_time: 0.0707 memory: 24011 grad_norm: 4.6282 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1410 loss: 1.1410 2022/09/05 13:23:07 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:23:07 - mmengine - INFO - Epoch(train) [28][940/940] lr: 1.0000e-02 eta: 12:31:32 time: 0.5649 data_time: 0.0538 memory: 24011 grad_norm: 4.9162 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.0840 loss: 1.0840 2022/09/05 13:23:20 - mmengine - INFO - Epoch(val) [28][20/78] eta: 0:00:39 time: 0.6889 data_time: 0.5215 memory: 3625 2022/09/05 13:23:30 - mmengine - INFO - Epoch(val) [28][40/78] eta: 0:00:18 time: 0.4909 data_time: 0.3353 memory: 3625 2022/09/05 13:23:43 - mmengine - INFO - Epoch(val) [28][60/78] eta: 0:00:11 time: 0.6576 data_time: 0.4857 memory: 3625 2022/09/05 13:23:53 - mmengine - INFO - Epoch(val) [28][78/78] acc/top1: 0.7140 acc/top5: 0.9000 acc/mean1: 0.7139 2022/09/05 13:24:11 - mmengine - INFO - Epoch(train) [29][20/940] lr: 1.0000e-02 eta: 12:31:31 time: 0.8904 data_time: 0.2787 memory: 24011 grad_norm: 4.7299 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0640 loss: 1.0640 2022/09/05 13:24:24 - mmengine - INFO - Epoch(train) [29][40/940] lr: 1.0000e-02 eta: 12:31:16 time: 0.6339 data_time: 0.0707 memory: 24011 grad_norm: 4.9679 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1447 loss: 1.1447 2022/09/05 13:24:38 - mmengine - INFO - Epoch(train) [29][60/940] lr: 1.0000e-02 eta: 12:31:04 time: 0.7087 data_time: 0.1327 memory: 24011 grad_norm: 4.9973 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0878 loss: 1.0878 2022/09/05 13:24:51 - mmengine - INFO - Epoch(train) [29][80/940] lr: 1.0000e-02 eta: 12:30:49 time: 0.6337 data_time: 0.0372 memory: 24011 grad_norm: 4.7579 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0584 loss: 1.0584 2022/09/05 13:25:04 - mmengine - INFO - Epoch(train) [29][100/940] lr: 1.0000e-02 eta: 12:30:35 time: 0.6507 data_time: 0.0427 memory: 24011 grad_norm: 4.6985 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0434 loss: 1.0434 2022/09/05 13:25:16 - mmengine - INFO - Epoch(train) [29][120/940] lr: 1.0000e-02 eta: 12:30:19 time: 0.6154 data_time: 0.0317 memory: 24011 grad_norm: 4.5566 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1159 loss: 1.1159 2022/09/05 13:25:30 - mmengine - INFO - Epoch(train) [29][140/940] lr: 1.0000e-02 eta: 12:30:09 time: 0.7278 data_time: 0.0428 memory: 24011 grad_norm: 4.6766 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0376 loss: 1.0376 2022/09/05 13:25:42 - mmengine - INFO - Epoch(train) [29][160/940] lr: 1.0000e-02 eta: 12:29:52 time: 0.6009 data_time: 0.0348 memory: 24011 grad_norm: 4.9399 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0497 loss: 1.0497 2022/09/05 13:25:56 - mmengine - INFO - Epoch(train) [29][180/940] lr: 1.0000e-02 eta: 12:29:39 time: 0.6601 data_time: 0.0398 memory: 24011 grad_norm: 4.4516 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0117 loss: 1.0117 2022/09/05 13:26:08 - mmengine - INFO - Epoch(train) [29][200/940] lr: 1.0000e-02 eta: 12:29:23 time: 0.6203 data_time: 0.0394 memory: 24011 grad_norm: 4.6276 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2380 loss: 1.2380 2022/09/05 13:26:21 - mmengine - INFO - Epoch(train) [29][220/940] lr: 1.0000e-02 eta: 12:29:09 time: 0.6548 data_time: 0.0413 memory: 24011 grad_norm: 4.9769 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1197 loss: 1.1197 2022/09/05 13:26:34 - mmengine - INFO - Epoch(train) [29][240/940] lr: 1.0000e-02 eta: 12:28:54 time: 0.6353 data_time: 0.0357 memory: 24011 grad_norm: 4.5416 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0989 loss: 1.0989 2022/09/05 13:26:47 - mmengine - INFO - Epoch(train) [29][260/940] lr: 1.0000e-02 eta: 12:28:39 time: 0.6312 data_time: 0.0350 memory: 24011 grad_norm: 5.6822 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0733 loss: 1.0733 2022/09/05 13:27:00 - mmengine - INFO - Epoch(train) [29][280/940] lr: 1.0000e-02 eta: 12:28:26 time: 0.6752 data_time: 0.0427 memory: 24011 grad_norm: 4.7227 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.0930 loss: 1.0930 2022/09/05 13:27:12 - mmengine - INFO - Epoch(train) [29][300/940] lr: 1.0000e-02 eta: 12:28:11 time: 0.6165 data_time: 0.0390 memory: 24011 grad_norm: 4.4676 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.0858 loss: 1.0858 2022/09/05 13:27:25 - mmengine - INFO - Epoch(train) [29][320/940] lr: 1.0000e-02 eta: 12:27:56 time: 0.6332 data_time: 0.0445 memory: 24011 grad_norm: 4.5968 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1006 loss: 1.1006 2022/09/05 13:27:38 - mmengine - INFO - Epoch(train) [29][340/940] lr: 1.0000e-02 eta: 12:27:41 time: 0.6447 data_time: 0.0623 memory: 24011 grad_norm: 4.4043 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9706 loss: 0.9706 2022/09/05 13:27:52 - mmengine - INFO - Epoch(train) [29][360/940] lr: 1.0000e-02 eta: 12:27:29 time: 0.6902 data_time: 0.0485 memory: 24011 grad_norm: 4.6341 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0425 loss: 1.0425 2022/09/05 13:28:05 - mmengine - INFO - Epoch(train) [29][380/940] lr: 1.0000e-02 eta: 12:27:15 time: 0.6477 data_time: 0.0317 memory: 24011 grad_norm: 4.7527 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0661 loss: 1.0661 2022/09/05 13:28:17 - mmengine - INFO - Epoch(train) [29][400/940] lr: 1.0000e-02 eta: 12:27:00 time: 0.6314 data_time: 0.0422 memory: 24011 grad_norm: 4.5272 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1776 loss: 1.1776 2022/09/05 13:28:31 - mmengine - INFO - Epoch(train) [29][420/940] lr: 1.0000e-02 eta: 12:26:47 time: 0.6867 data_time: 0.0314 memory: 24011 grad_norm: 4.7588 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.1928 loss: 1.1928 2022/09/05 13:28:44 - mmengine - INFO - Epoch(train) [29][440/940] lr: 1.0000e-02 eta: 12:26:34 time: 0.6576 data_time: 0.0417 memory: 24011 grad_norm: 4.8498 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0629 loss: 1.0629 2022/09/05 13:28:56 - mmengine - INFO - Epoch(train) [29][460/940] lr: 1.0000e-02 eta: 12:26:17 time: 0.6058 data_time: 0.0362 memory: 24011 grad_norm: 4.3595 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0447 loss: 1.0447 2022/09/05 13:29:09 - mmengine - INFO - Epoch(train) [29][480/940] lr: 1.0000e-02 eta: 12:26:02 time: 0.6259 data_time: 0.0439 memory: 24011 grad_norm: 4.6719 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0941 loss: 1.0941 2022/09/05 13:29:23 - mmengine - INFO - Epoch(train) [29][500/940] lr: 1.0000e-02 eta: 12:25:50 time: 0.6960 data_time: 0.0336 memory: 24011 grad_norm: 4.5857 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9660 loss: 0.9660 2022/09/05 13:29:36 - mmengine - INFO - Epoch(train) [29][520/940] lr: 1.0000e-02 eta: 12:25:36 time: 0.6513 data_time: 0.0412 memory: 24011 grad_norm: 4.7903 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1100 loss: 1.1100 2022/09/05 13:29:49 - mmengine - INFO - Epoch(train) [29][540/940] lr: 1.0000e-02 eta: 12:25:23 time: 0.6695 data_time: 0.0381 memory: 24011 grad_norm: 4.5372 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1021 loss: 1.1021 2022/09/05 13:30:02 - mmengine - INFO - Epoch(train) [29][560/940] lr: 1.0000e-02 eta: 12:25:08 time: 0.6307 data_time: 0.0448 memory: 24011 grad_norm: 4.6647 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0938 loss: 1.0938 2022/09/05 13:30:14 - mmengine - INFO - Epoch(train) [29][580/940] lr: 1.0000e-02 eta: 12:24:53 time: 0.6299 data_time: 0.0372 memory: 24011 grad_norm: 4.5794 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0790 loss: 1.0790 2022/09/05 13:30:27 - mmengine - INFO - Epoch(train) [29][600/940] lr: 1.0000e-02 eta: 12:24:38 time: 0.6330 data_time: 0.0432 memory: 24011 grad_norm: 4.7867 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1081 loss: 1.1081 2022/09/05 13:30:40 - mmengine - INFO - Epoch(train) [29][620/940] lr: 1.0000e-02 eta: 12:24:23 time: 0.6451 data_time: 0.0378 memory: 24011 grad_norm: 4.5690 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1113 loss: 1.1113 2022/09/05 13:30:53 - mmengine - INFO - Epoch(train) [29][640/940] lr: 1.0000e-02 eta: 12:24:08 time: 0.6270 data_time: 0.0450 memory: 24011 grad_norm: 4.2862 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1895 loss: 1.1895 2022/09/05 13:31:05 - mmengine - INFO - Epoch(train) [29][660/940] lr: 1.0000e-02 eta: 12:23:54 time: 0.6420 data_time: 0.0498 memory: 24011 grad_norm: 4.9760 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0725 loss: 1.0725 2022/09/05 13:31:18 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:31:18 - mmengine - INFO - Epoch(train) [29][680/940] lr: 1.0000e-02 eta: 12:23:39 time: 0.6425 data_time: 0.0423 memory: 24011 grad_norm: 4.6293 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0757 loss: 1.0757 2022/09/05 13:31:32 - mmengine - INFO - Epoch(train) [29][700/940] lr: 1.0000e-02 eta: 12:23:26 time: 0.6783 data_time: 0.0390 memory: 24011 grad_norm: 4.2976 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0235 loss: 1.0235 2022/09/05 13:31:44 - mmengine - INFO - Epoch(train) [29][720/940] lr: 1.0000e-02 eta: 12:23:11 time: 0.6238 data_time: 0.0382 memory: 24011 grad_norm: 4.5861 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1659 loss: 1.1659 2022/09/05 13:31:58 - mmengine - INFO - Epoch(train) [29][740/940] lr: 1.0000e-02 eta: 12:22:59 time: 0.6984 data_time: 0.0522 memory: 24011 grad_norm: 4.6296 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1128 loss: 1.1128 2022/09/05 13:32:11 - mmengine - INFO - Epoch(train) [29][760/940] lr: 1.0000e-02 eta: 12:22:45 time: 0.6523 data_time: 0.0389 memory: 24011 grad_norm: 4.6261 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1930 loss: 1.1930 2022/09/05 13:32:25 - mmengine - INFO - Epoch(train) [29][780/940] lr: 1.0000e-02 eta: 12:22:32 time: 0.6601 data_time: 0.0361 memory: 24011 grad_norm: 4.8974 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1051 loss: 1.1051 2022/09/05 13:32:37 - mmengine - INFO - Epoch(train) [29][800/940] lr: 1.0000e-02 eta: 12:22:17 time: 0.6376 data_time: 0.0395 memory: 24011 grad_norm: 4.2426 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0814 loss: 1.0814 2022/09/05 13:32:51 - mmengine - INFO - Epoch(train) [29][820/940] lr: 1.0000e-02 eta: 12:22:04 time: 0.6712 data_time: 0.0360 memory: 24011 grad_norm: 4.3640 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1694 loss: 1.1694 2022/09/05 13:33:04 - mmengine - INFO - Epoch(train) [29][840/940] lr: 1.0000e-02 eta: 12:21:49 time: 0.6412 data_time: 0.0383 memory: 24011 grad_norm: 4.6534 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1317 loss: 1.1317 2022/09/05 13:33:17 - mmengine - INFO - Epoch(train) [29][860/940] lr: 1.0000e-02 eta: 12:21:35 time: 0.6532 data_time: 0.0384 memory: 24011 grad_norm: 4.9368 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.1445 loss: 1.1445 2022/09/05 13:33:29 - mmengine - INFO - Epoch(train) [29][880/940] lr: 1.0000e-02 eta: 12:21:20 time: 0.6269 data_time: 0.0440 memory: 24011 grad_norm: 4.7493 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1151 loss: 1.1151 2022/09/05 13:33:42 - mmengine - INFO - Epoch(train) [29][900/940] lr: 1.0000e-02 eta: 12:21:06 time: 0.6557 data_time: 0.0392 memory: 24011 grad_norm: 4.5066 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0548 loss: 1.0548 2022/09/05 13:33:55 - mmengine - INFO - Epoch(train) [29][920/940] lr: 1.0000e-02 eta: 12:20:52 time: 0.6345 data_time: 0.0430 memory: 24011 grad_norm: 4.6419 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0266 loss: 1.0266 2022/09/05 13:34:06 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:34:06 - mmengine - INFO - Epoch(train) [29][940/940] lr: 1.0000e-02 eta: 12:20:33 time: 0.5700 data_time: 0.0296 memory: 24011 grad_norm: 4.7947 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.1388 loss: 1.1388 2022/09/05 13:34:20 - mmengine - INFO - Epoch(val) [29][20/78] eta: 0:00:39 time: 0.6791 data_time: 0.5155 memory: 3625 2022/09/05 13:34:30 - mmengine - INFO - Epoch(val) [29][40/78] eta: 0:00:18 time: 0.4853 data_time: 0.3297 memory: 3625 2022/09/05 13:34:42 - mmengine - INFO - Epoch(val) [29][60/78] eta: 0:00:11 time: 0.6350 data_time: 0.4761 memory: 3625 2022/09/05 13:34:53 - mmengine - INFO - Epoch(val) [29][78/78] acc/top1: 0.7166 acc/top5: 0.9028 acc/mean1: 0.7164 2022/09/05 13:35:11 - mmengine - INFO - Epoch(train) [30][20/940] lr: 1.0000e-02 eta: 12:20:31 time: 0.8859 data_time: 0.2453 memory: 24011 grad_norm: 4.7310 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9522 loss: 0.9522 2022/09/05 13:35:24 - mmengine - INFO - Epoch(train) [30][40/940] lr: 1.0000e-02 eta: 12:20:16 time: 0.6265 data_time: 0.0352 memory: 24011 grad_norm: 4.4219 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9531 loss: 0.9531 2022/09/05 13:35:38 - mmengine - INFO - Epoch(train) [30][60/940] lr: 1.0000e-02 eta: 12:20:05 time: 0.7257 data_time: 0.0411 memory: 24011 grad_norm: 4.2411 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0939 loss: 1.0939 2022/09/05 13:35:51 - mmengine - INFO - Epoch(train) [30][80/940] lr: 1.0000e-02 eta: 12:19:50 time: 0.6204 data_time: 0.0336 memory: 24011 grad_norm: 4.7308 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1691 loss: 1.1691 2022/09/05 13:36:04 - mmengine - INFO - Epoch(train) [30][100/940] lr: 1.0000e-02 eta: 12:19:36 time: 0.6490 data_time: 0.0924 memory: 24011 grad_norm: 5.5455 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0247 loss: 1.0247 2022/09/05 13:36:16 - mmengine - INFO - Epoch(train) [30][120/940] lr: 1.0000e-02 eta: 12:19:21 time: 0.6392 data_time: 0.0755 memory: 24011 grad_norm: 7.1904 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1523 loss: 1.1523 2022/09/05 13:36:29 - mmengine - INFO - Epoch(train) [30][140/940] lr: 1.0000e-02 eta: 12:19:07 time: 0.6498 data_time: 0.0872 memory: 24011 grad_norm: 5.2006 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2762 loss: 1.2762 2022/09/05 13:36:43 - mmengine - INFO - Epoch(train) [30][160/940] lr: 1.0000e-02 eta: 12:18:53 time: 0.6554 data_time: 0.0731 memory: 24011 grad_norm: 5.2718 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0834 loss: 1.0834 2022/09/05 13:36:55 - mmengine - INFO - Epoch(train) [30][180/940] lr: 1.0000e-02 eta: 12:18:38 time: 0.6308 data_time: 0.0541 memory: 24011 grad_norm: 4.6452 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2129 loss: 1.2129 2022/09/05 13:37:08 - mmengine - INFO - Epoch(train) [30][200/940] lr: 1.0000e-02 eta: 12:18:23 time: 0.6393 data_time: 0.0334 memory: 24011 grad_norm: 4.7565 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0419 loss: 1.0419 2022/09/05 13:37:21 - mmengine - INFO - Epoch(train) [30][220/940] lr: 1.0000e-02 eta: 12:18:09 time: 0.6349 data_time: 0.0490 memory: 24011 grad_norm: 4.9992 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1147 loss: 1.1147 2022/09/05 13:37:34 - mmengine - INFO - Epoch(train) [30][240/940] lr: 1.0000e-02 eta: 12:17:55 time: 0.6541 data_time: 0.0433 memory: 24011 grad_norm: 4.6394 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2092 loss: 1.2092 2022/09/05 13:37:46 - mmengine - INFO - Epoch(train) [30][260/940] lr: 1.0000e-02 eta: 12:17:40 time: 0.6405 data_time: 0.0458 memory: 24011 grad_norm: 4.3915 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.9668 loss: 0.9668 2022/09/05 13:37:59 - mmengine - INFO - Epoch(train) [30][280/940] lr: 1.0000e-02 eta: 12:17:26 time: 0.6500 data_time: 0.0343 memory: 24011 grad_norm: 4.6898 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1077 loss: 1.1077 2022/09/05 13:38:12 - mmengine - INFO - Epoch(train) [30][300/940] lr: 1.0000e-02 eta: 12:17:11 time: 0.6363 data_time: 0.0445 memory: 24011 grad_norm: 5.1761 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9607 loss: 0.9607 2022/09/05 13:38:25 - mmengine - INFO - Epoch(train) [30][320/940] lr: 1.0000e-02 eta: 12:16:57 time: 0.6455 data_time: 0.0357 memory: 24011 grad_norm: 4.6166 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1344 loss: 1.1344 2022/09/05 13:38:39 - mmengine - INFO - Epoch(train) [30][340/940] lr: 1.0000e-02 eta: 12:16:46 time: 0.7028 data_time: 0.0363 memory: 24011 grad_norm: 4.4297 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0882 loss: 1.0882 2022/09/05 13:38:53 - mmengine - INFO - Epoch(train) [30][360/940] lr: 1.0000e-02 eta: 12:16:33 time: 0.6723 data_time: 0.0337 memory: 24011 grad_norm: 4.7426 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1631 loss: 1.1631 2022/09/05 13:39:05 - mmengine - INFO - Epoch(train) [30][380/940] lr: 1.0000e-02 eta: 12:16:17 time: 0.6173 data_time: 0.0364 memory: 24011 grad_norm: 4.7626 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0314 loss: 1.0314 2022/09/05 13:39:18 - mmengine - INFO - Epoch(train) [30][400/940] lr: 1.0000e-02 eta: 12:16:02 time: 0.6365 data_time: 0.0433 memory: 24011 grad_norm: 4.5669 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1284 loss: 1.1284 2022/09/05 13:39:31 - mmengine - INFO - Epoch(train) [30][420/940] lr: 1.0000e-02 eta: 12:15:49 time: 0.6576 data_time: 0.0640 memory: 24011 grad_norm: 5.1449 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0408 loss: 1.0408 2022/09/05 13:39:44 - mmengine - INFO - Epoch(train) [30][440/940] lr: 1.0000e-02 eta: 12:15:34 time: 0.6498 data_time: 0.0371 memory: 24011 grad_norm: 4.4758 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0110 loss: 1.0110 2022/09/05 13:39:57 - mmengine - INFO - Epoch(train) [30][460/940] lr: 1.0000e-02 eta: 12:15:20 time: 0.6522 data_time: 0.0586 memory: 24011 grad_norm: 5.1332 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1346 loss: 1.1346 2022/09/05 13:40:10 - mmengine - INFO - Epoch(train) [30][480/940] lr: 1.0000e-02 eta: 12:15:06 time: 0.6369 data_time: 0.0354 memory: 24011 grad_norm: 4.7954 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2157 loss: 1.2157 2022/09/05 13:40:23 - mmengine - INFO - Epoch(train) [30][500/940] lr: 1.0000e-02 eta: 12:14:53 time: 0.6807 data_time: 0.0741 memory: 24011 grad_norm: 5.0641 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1095 loss: 1.1095 2022/09/05 13:40:36 - mmengine - INFO - Epoch(train) [30][520/940] lr: 1.0000e-02 eta: 12:14:39 time: 0.6379 data_time: 0.0299 memory: 24011 grad_norm: 4.5759 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.2031 loss: 1.2031 2022/09/05 13:40:50 - mmengine - INFO - Epoch(train) [30][540/940] lr: 1.0000e-02 eta: 12:14:26 time: 0.6836 data_time: 0.1029 memory: 24011 grad_norm: 6.1602 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3011 loss: 1.3011 2022/09/05 13:41:03 - mmengine - INFO - Epoch(train) [30][560/940] lr: 1.0000e-02 eta: 12:14:12 time: 0.6594 data_time: 0.0699 memory: 24011 grad_norm: 4.7540 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1216 loss: 1.1216 2022/09/05 13:41:16 - mmengine - INFO - Epoch(train) [30][580/940] lr: 1.0000e-02 eta: 12:13:59 time: 0.6556 data_time: 0.0866 memory: 24011 grad_norm: 4.5151 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1586 loss: 1.1586 2022/09/05 13:41:28 - mmengine - INFO - Epoch(train) [30][600/940] lr: 1.0000e-02 eta: 12:13:43 time: 0.6205 data_time: 0.0405 memory: 24011 grad_norm: 4.9617 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0573 loss: 1.0573 2022/09/05 13:41:42 - mmengine - INFO - Epoch(train) [30][620/940] lr: 1.0000e-02 eta: 12:13:30 time: 0.6584 data_time: 0.0572 memory: 24011 grad_norm: 5.0344 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0769 loss: 1.0769 2022/09/05 13:41:54 - mmengine - INFO - Epoch(train) [30][640/940] lr: 1.0000e-02 eta: 12:13:14 time: 0.6258 data_time: 0.0473 memory: 24011 grad_norm: 4.6723 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0943 loss: 1.0943 2022/09/05 13:42:08 - mmengine - INFO - Epoch(train) [30][660/940] lr: 1.0000e-02 eta: 12:13:03 time: 0.7061 data_time: 0.1263 memory: 24011 grad_norm: 5.0350 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0632 loss: 1.0632 2022/09/05 13:42:21 - mmengine - INFO - Epoch(train) [30][680/940] lr: 1.0000e-02 eta: 12:12:48 time: 0.6204 data_time: 0.0515 memory: 24011 grad_norm: 4.8682 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0856 loss: 1.0856 2022/09/05 13:42:34 - mmengine - INFO - Epoch(train) [30][700/940] lr: 1.0000e-02 eta: 12:12:34 time: 0.6637 data_time: 0.0703 memory: 24011 grad_norm: 4.3863 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1296 loss: 1.1296 2022/09/05 13:42:46 - mmengine - INFO - Epoch(train) [30][720/940] lr: 1.0000e-02 eta: 12:12:18 time: 0.6100 data_time: 0.0486 memory: 24011 grad_norm: 4.6623 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1576 loss: 1.1576 2022/09/05 13:42:59 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:42:59 - mmengine - INFO - Epoch(train) [30][740/940] lr: 1.0000e-02 eta: 12:12:04 time: 0.6398 data_time: 0.0793 memory: 24011 grad_norm: 4.6076 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.1168 loss: 1.1168 2022/09/05 13:43:12 - mmengine - INFO - Epoch(train) [30][760/940] lr: 1.0000e-02 eta: 12:11:50 time: 0.6512 data_time: 0.0601 memory: 24011 grad_norm: 4.2701 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9904 loss: 0.9904 2022/09/05 13:43:26 - mmengine - INFO - Epoch(train) [30][780/940] lr: 1.0000e-02 eta: 12:11:38 time: 0.7094 data_time: 0.1285 memory: 24011 grad_norm: 4.4142 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1529 loss: 1.1529 2022/09/05 13:43:39 - mmengine - INFO - Epoch(train) [30][800/940] lr: 1.0000e-02 eta: 12:11:24 time: 0.6337 data_time: 0.0704 memory: 24011 grad_norm: 4.5463 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0843 loss: 1.0843 2022/09/05 13:43:52 - mmengine - INFO - Epoch(train) [30][820/940] lr: 1.0000e-02 eta: 12:11:10 time: 0.6550 data_time: 0.0781 memory: 24011 grad_norm: 5.4003 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0868 loss: 1.0868 2022/09/05 13:44:04 - mmengine - INFO - Epoch(train) [30][840/940] lr: 1.0000e-02 eta: 12:10:54 time: 0.6062 data_time: 0.0340 memory: 24011 grad_norm: 4.6939 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1174 loss: 1.1174 2022/09/05 13:44:17 - mmengine - INFO - Epoch(train) [30][860/940] lr: 1.0000e-02 eta: 12:10:40 time: 0.6622 data_time: 0.0981 memory: 24011 grad_norm: 4.9049 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1122 loss: 1.1122 2022/09/05 13:44:30 - mmengine - INFO - Epoch(train) [30][880/940] lr: 1.0000e-02 eta: 12:10:26 time: 0.6488 data_time: 0.0622 memory: 24011 grad_norm: 4.5771 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0537 loss: 1.0537 2022/09/05 13:44:43 - mmengine - INFO - Epoch(train) [30][900/940] lr: 1.0000e-02 eta: 12:10:11 time: 0.6252 data_time: 0.0370 memory: 24011 grad_norm: 4.5339 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0147 loss: 1.0147 2022/09/05 13:44:55 - mmengine - INFO - Epoch(train) [30][920/940] lr: 1.0000e-02 eta: 12:09:56 time: 0.6320 data_time: 0.0760 memory: 24011 grad_norm: 4.8974 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0764 loss: 1.0764 2022/09/05 13:45:07 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:45:07 - mmengine - INFO - Epoch(train) [30][940/940] lr: 1.0000e-02 eta: 12:09:38 time: 0.5605 data_time: 0.0401 memory: 24011 grad_norm: 4.8403 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.1667 loss: 1.1667 2022/09/05 13:45:07 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/09/05 13:45:26 - mmengine - INFO - Epoch(val) [30][20/78] eta: 0:00:41 time: 0.7093 data_time: 0.5453 memory: 3625 2022/09/05 13:45:35 - mmengine - INFO - Epoch(val) [30][40/78] eta: 0:00:17 time: 0.4564 data_time: 0.3011 memory: 3625 2022/09/05 13:45:48 - mmengine - INFO - Epoch(val) [30][60/78] eta: 0:00:11 time: 0.6500 data_time: 0.4966 memory: 3625 2022/09/05 13:45:57 - mmengine - INFO - Epoch(val) [30][78/78] acc/top1: 0.7186 acc/top5: 0.8990 acc/mean1: 0.7184 2022/09/05 13:46:15 - mmengine - INFO - Epoch(train) [31][20/940] lr: 1.0000e-02 eta: 12:09:36 time: 0.9128 data_time: 0.2548 memory: 24011 grad_norm: 4.5574 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0932 loss: 1.0932 2022/09/05 13:46:28 - mmengine - INFO - Epoch(train) [31][40/940] lr: 1.0000e-02 eta: 12:09:22 time: 0.6570 data_time: 0.0303 memory: 24011 grad_norm: 4.1855 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0532 loss: 1.0532 2022/09/05 13:46:42 - mmengine - INFO - Epoch(train) [31][60/940] lr: 1.0000e-02 eta: 12:09:10 time: 0.6884 data_time: 0.0418 memory: 24011 grad_norm: 4.2590 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9569 loss: 0.9569 2022/09/05 13:46:56 - mmengine - INFO - Epoch(train) [31][80/940] lr: 1.0000e-02 eta: 12:08:57 time: 0.6738 data_time: 0.0422 memory: 24011 grad_norm: 4.5471 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0883 loss: 1.0883 2022/09/05 13:47:08 - mmengine - INFO - Epoch(train) [31][100/940] lr: 1.0000e-02 eta: 12:08:41 time: 0.6111 data_time: 0.0417 memory: 24011 grad_norm: 4.3552 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9713 loss: 0.9713 2022/09/05 13:47:22 - mmengine - INFO - Epoch(train) [31][120/940] lr: 1.0000e-02 eta: 12:08:29 time: 0.6800 data_time: 0.0570 memory: 24011 grad_norm: 4.5073 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0406 loss: 1.0406 2022/09/05 13:47:35 - mmengine - INFO - Epoch(train) [31][140/940] lr: 1.0000e-02 eta: 12:08:15 time: 0.6476 data_time: 0.0406 memory: 24011 grad_norm: 4.5701 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9557 loss: 0.9557 2022/09/05 13:47:47 - mmengine - INFO - Epoch(train) [31][160/940] lr: 1.0000e-02 eta: 12:07:58 time: 0.5991 data_time: 0.0414 memory: 24011 grad_norm: 4.9442 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9921 loss: 0.9921 2022/09/05 13:48:00 - mmengine - INFO - Epoch(train) [31][180/940] lr: 1.0000e-02 eta: 12:07:44 time: 0.6541 data_time: 0.0447 memory: 24011 grad_norm: 4.6082 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.1830 loss: 1.1830 2022/09/05 13:48:12 - mmengine - INFO - Epoch(train) [31][200/940] lr: 1.0000e-02 eta: 12:07:30 time: 0.6304 data_time: 0.0400 memory: 24011 grad_norm: 4.5807 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.0420 loss: 1.0420 2022/09/05 13:48:25 - mmengine - INFO - Epoch(train) [31][220/940] lr: 1.0000e-02 eta: 12:07:16 time: 0.6592 data_time: 0.0408 memory: 24011 grad_norm: 4.6818 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0761 loss: 1.0761 2022/09/05 13:48:40 - mmengine - INFO - Epoch(train) [31][240/940] lr: 1.0000e-02 eta: 12:07:05 time: 0.7131 data_time: 0.0374 memory: 24011 grad_norm: 4.5462 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1055 loss: 1.1055 2022/09/05 13:48:53 - mmengine - INFO - Epoch(train) [31][260/940] lr: 1.0000e-02 eta: 12:06:51 time: 0.6432 data_time: 0.0369 memory: 24011 grad_norm: 4.3900 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0919 loss: 1.0919 2022/09/05 13:49:06 - mmengine - INFO - Epoch(train) [31][280/940] lr: 1.0000e-02 eta: 12:06:37 time: 0.6575 data_time: 0.0404 memory: 24011 grad_norm: 5.4741 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0778 loss: 1.0778 2022/09/05 13:49:18 - mmengine - INFO - Epoch(train) [31][300/940] lr: 1.0000e-02 eta: 12:06:21 time: 0.6041 data_time: 0.0396 memory: 24011 grad_norm: 4.4892 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0544 loss: 1.0544 2022/09/05 13:49:30 - mmengine - INFO - Epoch(train) [31][320/940] lr: 1.0000e-02 eta: 12:06:06 time: 0.6296 data_time: 0.0521 memory: 24011 grad_norm: 4.7876 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0900 loss: 1.0900 2022/09/05 13:49:43 - mmengine - INFO - Epoch(train) [31][340/940] lr: 1.0000e-02 eta: 12:05:51 time: 0.6325 data_time: 0.0415 memory: 24011 grad_norm: 4.7424 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9665 loss: 0.9665 2022/09/05 13:49:56 - mmengine - INFO - Epoch(train) [31][360/940] lr: 1.0000e-02 eta: 12:05:36 time: 0.6332 data_time: 0.0412 memory: 24011 grad_norm: 4.7481 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0542 loss: 1.0542 2022/09/05 13:50:09 - mmengine - INFO - Epoch(train) [31][380/940] lr: 1.0000e-02 eta: 12:05:22 time: 0.6409 data_time: 0.0392 memory: 24011 grad_norm: 4.8639 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0392 loss: 1.0392 2022/09/05 13:50:22 - mmengine - INFO - Epoch(train) [31][400/940] lr: 1.0000e-02 eta: 12:05:08 time: 0.6657 data_time: 0.0352 memory: 24011 grad_norm: 4.4864 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0532 loss: 1.0532 2022/09/05 13:50:35 - mmengine - INFO - Epoch(train) [31][420/940] lr: 1.0000e-02 eta: 12:04:54 time: 0.6505 data_time: 0.0378 memory: 24011 grad_norm: 4.7076 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0150 loss: 1.0150 2022/09/05 13:50:48 - mmengine - INFO - Epoch(train) [31][440/940] lr: 1.0000e-02 eta: 12:04:40 time: 0.6418 data_time: 0.0376 memory: 24011 grad_norm: 4.4946 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1370 loss: 1.1370 2022/09/05 13:51:00 - mmengine - INFO - Epoch(train) [31][460/940] lr: 1.0000e-02 eta: 12:04:25 time: 0.6244 data_time: 0.0408 memory: 24011 grad_norm: 4.4693 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0627 loss: 1.0627 2022/09/05 13:51:15 - mmengine - INFO - Epoch(train) [31][480/940] lr: 1.0000e-02 eta: 12:04:14 time: 0.7217 data_time: 0.0412 memory: 24011 grad_norm: 4.3565 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0629 loss: 1.0629 2022/09/05 13:51:27 - mmengine - INFO - Epoch(train) [31][500/940] lr: 1.0000e-02 eta: 12:04:00 time: 0.6374 data_time: 0.0461 memory: 24011 grad_norm: 4.8987 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1449 loss: 1.1449 2022/09/05 13:51:40 - mmengine - INFO - Epoch(train) [31][520/940] lr: 1.0000e-02 eta: 12:03:45 time: 0.6250 data_time: 0.0341 memory: 24011 grad_norm: 4.5364 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1574 loss: 1.1574 2022/09/05 13:51:52 - mmengine - INFO - Epoch(train) [31][540/940] lr: 1.0000e-02 eta: 12:03:29 time: 0.6270 data_time: 0.0592 memory: 24011 grad_norm: 4.3335 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0601 loss: 1.0601 2022/09/05 13:52:05 - mmengine - INFO - Epoch(train) [31][560/940] lr: 1.0000e-02 eta: 12:03:14 time: 0.6144 data_time: 0.0388 memory: 24011 grad_norm: 4.5523 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1423 loss: 1.1423 2022/09/05 13:52:18 - mmengine - INFO - Epoch(train) [31][580/940] lr: 1.0000e-02 eta: 12:03:00 time: 0.6599 data_time: 0.0383 memory: 24011 grad_norm: 4.7727 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9964 loss: 0.9964 2022/09/05 13:52:31 - mmengine - INFO - Epoch(train) [31][600/940] lr: 1.0000e-02 eta: 12:02:46 time: 0.6426 data_time: 0.0421 memory: 24011 grad_norm: 4.5577 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0951 loss: 1.0951 2022/09/05 13:52:45 - mmengine - INFO - Epoch(train) [31][620/940] lr: 1.0000e-02 eta: 12:02:34 time: 0.6892 data_time: 0.0448 memory: 24011 grad_norm: 4.4055 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0034 loss: 1.0034 2022/09/05 13:52:57 - mmengine - INFO - Epoch(train) [31][640/940] lr: 1.0000e-02 eta: 12:02:19 time: 0.6295 data_time: 0.0339 memory: 24011 grad_norm: 4.3772 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0336 loss: 1.0336 2022/09/05 13:53:11 - mmengine - INFO - Epoch(train) [31][660/940] lr: 1.0000e-02 eta: 12:02:06 time: 0.6748 data_time: 0.0379 memory: 24011 grad_norm: 4.8113 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9556 loss: 0.9556 2022/09/05 13:53:24 - mmengine - INFO - Epoch(train) [31][680/940] lr: 1.0000e-02 eta: 12:01:52 time: 0.6549 data_time: 0.0450 memory: 24011 grad_norm: 4.3312 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0416 loss: 1.0416 2022/09/05 13:53:37 - mmengine - INFO - Epoch(train) [31][700/940] lr: 1.0000e-02 eta: 12:01:38 time: 0.6544 data_time: 0.0413 memory: 24011 grad_norm: 5.1515 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0956 loss: 1.0956 2022/09/05 13:53:50 - mmengine - INFO - Epoch(train) [31][720/940] lr: 1.0000e-02 eta: 12:01:25 time: 0.6561 data_time: 0.0434 memory: 24011 grad_norm: 4.4885 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9813 loss: 0.9813 2022/09/05 13:54:03 - mmengine - INFO - Epoch(train) [31][740/940] lr: 1.0000e-02 eta: 12:01:11 time: 0.6536 data_time: 0.0420 memory: 24011 grad_norm: 4.8761 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1659 loss: 1.1659 2022/09/05 13:54:15 - mmengine - INFO - Epoch(train) [31][760/940] lr: 1.0000e-02 eta: 12:00:56 time: 0.6198 data_time: 0.0492 memory: 24011 grad_norm: 4.5095 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0906 loss: 1.0906 2022/09/05 13:54:30 - mmengine - INFO - Epoch(train) [31][780/940] lr: 1.0000e-02 eta: 12:00:44 time: 0.7099 data_time: 0.0376 memory: 24011 grad_norm: 4.5770 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0739 loss: 1.0739 2022/09/05 13:54:42 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:54:43 - mmengine - INFO - Epoch(train) [31][800/940] lr: 1.0000e-02 eta: 12:00:30 time: 0.6429 data_time: 0.0395 memory: 24011 grad_norm: 4.5739 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9585 loss: 0.9585 2022/09/05 13:54:56 - mmengine - INFO - Epoch(train) [31][820/940] lr: 1.0000e-02 eta: 12:00:17 time: 0.6708 data_time: 0.0450 memory: 24011 grad_norm: 4.4657 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0101 loss: 1.0101 2022/09/05 13:55:08 - mmengine - INFO - Epoch(train) [31][840/940] lr: 1.0000e-02 eta: 12:00:02 time: 0.6269 data_time: 0.0420 memory: 24011 grad_norm: 4.4222 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1671 loss: 1.1671 2022/09/05 13:55:22 - mmengine - INFO - Epoch(train) [31][860/940] lr: 1.0000e-02 eta: 11:59:48 time: 0.6559 data_time: 0.0407 memory: 24011 grad_norm: 4.6869 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.0447 loss: 1.0447 2022/09/05 13:55:35 - mmengine - INFO - Epoch(train) [31][880/940] lr: 1.0000e-02 eta: 11:59:35 time: 0.6587 data_time: 0.0383 memory: 24011 grad_norm: 4.4702 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0379 loss: 1.0379 2022/09/05 13:55:48 - mmengine - INFO - Epoch(train) [31][900/940] lr: 1.0000e-02 eta: 11:59:22 time: 0.6744 data_time: 0.0418 memory: 24011 grad_norm: 4.3923 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1629 loss: 1.1629 2022/09/05 13:56:00 - mmengine - INFO - Epoch(train) [31][920/940] lr: 1.0000e-02 eta: 11:59:05 time: 0.5916 data_time: 0.0404 memory: 24011 grad_norm: 4.5016 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1813 loss: 1.1813 2022/09/05 13:56:11 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 13:56:11 - mmengine - INFO - Epoch(train) [31][940/940] lr: 1.0000e-02 eta: 11:58:46 time: 0.5419 data_time: 0.0270 memory: 24011 grad_norm: 4.9221 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1354 loss: 1.1354 2022/09/05 13:56:25 - mmengine - INFO - Epoch(val) [31][20/78] eta: 0:00:40 time: 0.6950 data_time: 0.5366 memory: 3625 2022/09/05 13:56:34 - mmengine - INFO - Epoch(val) [31][40/78] eta: 0:00:17 time: 0.4671 data_time: 0.3065 memory: 3625 2022/09/05 13:56:48 - mmengine - INFO - Epoch(val) [31][60/78] eta: 0:00:11 time: 0.6658 data_time: 0.5070 memory: 3625 2022/09/05 13:56:58 - mmengine - INFO - Epoch(val) [31][78/78] acc/top1: 0.7143 acc/top5: 0.8997 acc/mean1: 0.7141 2022/09/05 13:57:16 - mmengine - INFO - Epoch(train) [32][20/940] lr: 1.0000e-02 eta: 11:58:45 time: 0.9229 data_time: 0.2568 memory: 24011 grad_norm: 4.5958 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 0.9668 loss: 0.9668 2022/09/05 13:57:29 - mmengine - INFO - Epoch(train) [32][40/940] lr: 1.0000e-02 eta: 11:58:31 time: 0.6479 data_time: 0.0307 memory: 24011 grad_norm: 4.5587 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1912 loss: 1.1912 2022/09/05 13:57:43 - mmengine - INFO - Epoch(train) [32][60/940] lr: 1.0000e-02 eta: 11:58:17 time: 0.6604 data_time: 0.0400 memory: 24011 grad_norm: 4.5044 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9450 loss: 0.9450 2022/09/05 13:57:55 - mmengine - INFO - Epoch(train) [32][80/940] lr: 1.0000e-02 eta: 11:58:02 time: 0.6288 data_time: 0.0311 memory: 24011 grad_norm: 5.3073 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1644 loss: 1.1644 2022/09/05 13:58:09 - mmengine - INFO - Epoch(train) [32][100/940] lr: 1.0000e-02 eta: 11:57:50 time: 0.6889 data_time: 0.0557 memory: 24011 grad_norm: 4.7872 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0761 loss: 1.0761 2022/09/05 13:58:21 - mmengine - INFO - Epoch(train) [32][120/940] lr: 1.0000e-02 eta: 11:57:34 time: 0.5972 data_time: 0.0333 memory: 24011 grad_norm: 4.7067 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9190 loss: 0.9190 2022/09/05 13:58:34 - mmengine - INFO - Epoch(train) [32][140/940] lr: 1.0000e-02 eta: 11:57:20 time: 0.6631 data_time: 0.0382 memory: 24011 grad_norm: 4.7878 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9947 loss: 0.9947 2022/09/05 13:58:46 - mmengine - INFO - Epoch(train) [32][160/940] lr: 1.0000e-02 eta: 11:57:04 time: 0.5965 data_time: 0.0356 memory: 24011 grad_norm: 5.2582 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9715 loss: 0.9715 2022/09/05 13:59:01 - mmengine - INFO - Epoch(train) [32][180/940] lr: 1.0000e-02 eta: 11:56:53 time: 0.7269 data_time: 0.0407 memory: 24011 grad_norm: 4.5014 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1209 loss: 1.1209 2022/09/05 13:59:17 - mmengine - INFO - Epoch(train) [32][200/940] lr: 1.0000e-02 eta: 11:56:47 time: 0.8230 data_time: 0.0349 memory: 24011 grad_norm: 4.8176 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0172 loss: 1.0172 2022/09/05 13:59:30 - mmengine - INFO - Epoch(train) [32][220/940] lr: 1.0000e-02 eta: 11:56:32 time: 0.6311 data_time: 0.0367 memory: 24011 grad_norm: 4.2852 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0299 loss: 1.0299 2022/09/05 13:59:43 - mmengine - INFO - Epoch(train) [32][240/940] lr: 1.0000e-02 eta: 11:56:19 time: 0.6710 data_time: 0.0435 memory: 24011 grad_norm: 4.8350 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9927 loss: 0.9927 2022/09/05 13:59:55 - mmengine - INFO - Epoch(train) [32][260/940] lr: 1.0000e-02 eta: 11:56:03 time: 0.6079 data_time: 0.0402 memory: 24011 grad_norm: 4.4731 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9518 loss: 0.9518 2022/09/05 14:00:08 - mmengine - INFO - Epoch(train) [32][280/940] lr: 1.0000e-02 eta: 11:55:48 time: 0.6221 data_time: 0.0385 memory: 24011 grad_norm: 6.7022 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1522 loss: 1.1522 2022/09/05 14:00:21 - mmengine - INFO - Epoch(train) [32][300/940] lr: 1.0000e-02 eta: 11:55:34 time: 0.6583 data_time: 0.0343 memory: 24011 grad_norm: 5.0863 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1398 loss: 1.1398 2022/09/05 14:00:34 - mmengine - INFO - Epoch(train) [32][320/940] lr: 1.0000e-02 eta: 11:55:21 time: 0.6579 data_time: 0.0553 memory: 24011 grad_norm: 4.5132 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2163 loss: 1.2163 2022/09/05 14:00:48 - mmengine - INFO - Epoch(train) [32][340/940] lr: 1.0000e-02 eta: 11:55:08 time: 0.6715 data_time: 0.0374 memory: 24011 grad_norm: 4.5477 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9791 loss: 0.9791 2022/09/05 14:01:00 - mmengine - INFO - Epoch(train) [32][360/940] lr: 1.0000e-02 eta: 11:54:53 time: 0.6313 data_time: 0.0365 memory: 24011 grad_norm: 4.8888 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1431 loss: 1.1431 2022/09/05 14:01:13 - mmengine - INFO - Epoch(train) [32][380/940] lr: 1.0000e-02 eta: 11:54:39 time: 0.6395 data_time: 0.0437 memory: 24011 grad_norm: 4.8925 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0826 loss: 1.0826 2022/09/05 14:01:26 - mmengine - INFO - Epoch(train) [32][400/940] lr: 1.0000e-02 eta: 11:54:25 time: 0.6611 data_time: 0.0384 memory: 24011 grad_norm: 4.6190 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1484 loss: 1.1484 2022/09/05 14:01:40 - mmengine - INFO - Epoch(train) [32][420/940] lr: 1.0000e-02 eta: 11:54:12 time: 0.6769 data_time: 0.0396 memory: 24011 grad_norm: 4.6300 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0305 loss: 1.0305 2022/09/05 14:01:52 - mmengine - INFO - Epoch(train) [32][440/940] lr: 1.0000e-02 eta: 11:53:57 time: 0.6159 data_time: 0.0396 memory: 24011 grad_norm: 4.8064 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0033 loss: 1.0033 2022/09/05 14:02:05 - mmengine - INFO - Epoch(train) [32][460/940] lr: 1.0000e-02 eta: 11:53:44 time: 0.6727 data_time: 0.0362 memory: 24011 grad_norm: 4.6653 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0968 loss: 1.0968 2022/09/05 14:02:18 - mmengine - INFO - Epoch(train) [32][480/940] lr: 1.0000e-02 eta: 11:53:28 time: 0.6079 data_time: 0.0390 memory: 24011 grad_norm: 4.6136 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1599 loss: 1.1599 2022/09/05 14:02:31 - mmengine - INFO - Epoch(train) [32][500/940] lr: 1.0000e-02 eta: 11:53:14 time: 0.6473 data_time: 0.0414 memory: 24011 grad_norm: 4.8359 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 0.9643 loss: 0.9643 2022/09/05 14:02:43 - mmengine - INFO - Epoch(train) [32][520/940] lr: 1.0000e-02 eta: 11:52:59 time: 0.6202 data_time: 0.0462 memory: 24011 grad_norm: 4.8721 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2211 loss: 1.2211 2022/09/05 14:02:56 - mmengine - INFO - Epoch(train) [32][540/940] lr: 1.0000e-02 eta: 11:52:45 time: 0.6498 data_time: 0.0349 memory: 24011 grad_norm: 4.9374 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1337 loss: 1.1337 2022/09/05 14:03:09 - mmengine - INFO - Epoch(train) [32][560/940] lr: 1.0000e-02 eta: 11:52:31 time: 0.6422 data_time: 0.0388 memory: 24011 grad_norm: 5.0198 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1242 loss: 1.1242 2022/09/05 14:03:22 - mmengine - INFO - Epoch(train) [32][580/940] lr: 1.0000e-02 eta: 11:52:18 time: 0.6725 data_time: 0.0330 memory: 24011 grad_norm: 4.6138 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0874 loss: 1.0874 2022/09/05 14:03:35 - mmengine - INFO - Epoch(train) [32][600/940] lr: 1.0000e-02 eta: 11:52:03 time: 0.6394 data_time: 0.0426 memory: 24011 grad_norm: 4.9482 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0444 loss: 1.0444 2022/09/05 14:03:49 - mmengine - INFO - Epoch(train) [32][620/940] lr: 1.0000e-02 eta: 11:51:50 time: 0.6715 data_time: 0.0382 memory: 24011 grad_norm: 4.4156 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9945 loss: 0.9945 2022/09/05 14:04:02 - mmengine - INFO - Epoch(train) [32][640/940] lr: 1.0000e-02 eta: 11:51:37 time: 0.6608 data_time: 0.0369 memory: 24011 grad_norm: 5.1314 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.1101 loss: 1.1101 2022/09/05 14:04:14 - mmengine - INFO - Epoch(train) [32][660/940] lr: 1.0000e-02 eta: 11:51:22 time: 0.6228 data_time: 0.0379 memory: 24011 grad_norm: 4.6457 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.9905 loss: 0.9905 2022/09/05 14:04:28 - mmengine - INFO - Epoch(train) [32][680/940] lr: 1.0000e-02 eta: 11:51:08 time: 0.6657 data_time: 0.0394 memory: 24011 grad_norm: 4.7055 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.0338 loss: 1.0338 2022/09/05 14:04:40 - mmengine - INFO - Epoch(train) [32][700/940] lr: 1.0000e-02 eta: 11:50:54 time: 0.6397 data_time: 0.0422 memory: 24011 grad_norm: 5.1460 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0613 loss: 1.0613 2022/09/05 14:04:54 - mmengine - INFO - Epoch(train) [32][720/940] lr: 1.0000e-02 eta: 11:50:41 time: 0.6649 data_time: 0.0401 memory: 24011 grad_norm: 4.3196 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0722 loss: 1.0722 2022/09/05 14:05:08 - mmengine - INFO - Epoch(train) [32][740/940] lr: 1.0000e-02 eta: 11:50:30 time: 0.7220 data_time: 0.0558 memory: 24011 grad_norm: 5.0884 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9967 loss: 0.9967 2022/09/05 14:05:21 - mmengine - INFO - Epoch(train) [32][760/940] lr: 1.0000e-02 eta: 11:50:15 time: 0.6259 data_time: 0.0348 memory: 24011 grad_norm: 4.9322 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0204 loss: 1.0204 2022/09/05 14:05:34 - mmengine - INFO - Epoch(train) [32][780/940] lr: 1.0000e-02 eta: 11:50:02 time: 0.6667 data_time: 0.0368 memory: 24011 grad_norm: 5.0031 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0569 loss: 1.0569 2022/09/05 14:05:46 - mmengine - INFO - Epoch(train) [32][800/940] lr: 1.0000e-02 eta: 11:49:46 time: 0.6181 data_time: 0.0380 memory: 24011 grad_norm: 4.9749 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0931 loss: 1.0931 2022/09/05 14:06:00 - mmengine - INFO - Epoch(train) [32][820/940] lr: 1.0000e-02 eta: 11:49:34 time: 0.6734 data_time: 0.0389 memory: 24011 grad_norm: 4.4933 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9883 loss: 0.9883 2022/09/05 14:06:12 - mmengine - INFO - Epoch(train) [32][840/940] lr: 1.0000e-02 eta: 11:49:19 time: 0.6282 data_time: 0.0407 memory: 24011 grad_norm: 4.3276 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0603 loss: 1.0603 2022/09/05 14:06:25 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:06:25 - mmengine - INFO - Epoch(train) [32][860/940] lr: 1.0000e-02 eta: 11:49:04 time: 0.6412 data_time: 0.0390 memory: 24011 grad_norm: 4.4603 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1519 loss: 1.1519 2022/09/05 14:06:39 - mmengine - INFO - Epoch(train) [32][880/940] lr: 1.0000e-02 eta: 11:48:51 time: 0.6714 data_time: 0.0461 memory: 24011 grad_norm: 5.4423 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1111 loss: 1.1111 2022/09/05 14:06:51 - mmengine - INFO - Epoch(train) [32][900/940] lr: 1.0000e-02 eta: 11:48:36 time: 0.6102 data_time: 0.0398 memory: 24011 grad_norm: 5.0052 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0784 loss: 1.0784 2022/09/05 14:07:04 - mmengine - INFO - Epoch(train) [32][920/940] lr: 1.0000e-02 eta: 11:48:22 time: 0.6640 data_time: 0.0367 memory: 24011 grad_norm: 4.4858 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1644 loss: 1.1644 2022/09/05 14:07:15 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:07:15 - mmengine - INFO - Epoch(train) [32][940/940] lr: 1.0000e-02 eta: 11:48:05 time: 0.5655 data_time: 0.0307 memory: 24011 grad_norm: 4.5824 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.0551 loss: 1.0551 2022/09/05 14:07:30 - mmengine - INFO - Epoch(val) [32][20/78] eta: 0:00:40 time: 0.7064 data_time: 0.5447 memory: 3625 2022/09/05 14:07:39 - mmengine - INFO - Epoch(val) [32][40/78] eta: 0:00:17 time: 0.4624 data_time: 0.3078 memory: 3625 2022/09/05 14:07:52 - mmengine - INFO - Epoch(val) [32][60/78] eta: 0:00:11 time: 0.6522 data_time: 0.4954 memory: 3625 2022/09/05 14:08:06 - mmengine - INFO - Epoch(val) [32][78/78] acc/top1: 0.7118 acc/top5: 0.8965 acc/mean1: 0.7116 2022/09/05 14:08:25 - mmengine - INFO - Epoch(train) [33][20/940] lr: 1.0000e-02 eta: 11:48:02 time: 0.9097 data_time: 0.3423 memory: 24011 grad_norm: 4.6289 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0024 loss: 1.0024 2022/09/05 14:08:37 - mmengine - INFO - Epoch(train) [33][40/940] lr: 1.0000e-02 eta: 11:47:47 time: 0.6260 data_time: 0.0495 memory: 24011 grad_norm: 4.7684 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9629 loss: 0.9629 2022/09/05 14:08:51 - mmengine - INFO - Epoch(train) [33][60/940] lr: 1.0000e-02 eta: 11:47:35 time: 0.6887 data_time: 0.0445 memory: 24011 grad_norm: 4.4629 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0988 loss: 1.0988 2022/09/05 14:09:04 - mmengine - INFO - Epoch(train) [33][80/940] lr: 1.0000e-02 eta: 11:47:20 time: 0.6388 data_time: 0.0354 memory: 24011 grad_norm: 4.8138 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0036 loss: 1.0036 2022/09/05 14:09:18 - mmengine - INFO - Epoch(train) [33][100/940] lr: 1.0000e-02 eta: 11:47:08 time: 0.6747 data_time: 0.0424 memory: 24011 grad_norm: 4.6889 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9279 loss: 0.9279 2022/09/05 14:09:30 - mmengine - INFO - Epoch(train) [33][120/940] lr: 1.0000e-02 eta: 11:46:54 time: 0.6529 data_time: 0.0548 memory: 24011 grad_norm: 4.5877 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0722 loss: 1.0722 2022/09/05 14:09:43 - mmengine - INFO - Epoch(train) [33][140/940] lr: 1.0000e-02 eta: 11:46:39 time: 0.6268 data_time: 0.0509 memory: 24011 grad_norm: 4.4707 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1710 loss: 1.1710 2022/09/05 14:09:56 - mmengine - INFO - Epoch(train) [33][160/940] lr: 1.0000e-02 eta: 11:46:25 time: 0.6601 data_time: 0.0836 memory: 24011 grad_norm: 4.6903 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0248 loss: 1.0248 2022/09/05 14:10:09 - mmengine - INFO - Epoch(train) [33][180/940] lr: 1.0000e-02 eta: 11:46:12 time: 0.6558 data_time: 0.0424 memory: 24011 grad_norm: 4.4208 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0503 loss: 1.0503 2022/09/05 14:10:22 - mmengine - INFO - Epoch(train) [33][200/940] lr: 1.0000e-02 eta: 11:45:57 time: 0.6339 data_time: 0.0329 memory: 24011 grad_norm: 4.9430 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.1471 loss: 1.1471 2022/09/05 14:10:36 - mmengine - INFO - Epoch(train) [33][220/940] lr: 1.0000e-02 eta: 11:45:45 time: 0.6962 data_time: 0.0377 memory: 24011 grad_norm: 4.7706 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9691 loss: 0.9691 2022/09/05 14:10:49 - mmengine - INFO - Epoch(train) [33][240/940] lr: 1.0000e-02 eta: 11:45:31 time: 0.6459 data_time: 0.0398 memory: 24011 grad_norm: 5.1981 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9839 loss: 0.9839 2022/09/05 14:11:02 - mmengine - INFO - Epoch(train) [33][260/940] lr: 1.0000e-02 eta: 11:45:17 time: 0.6521 data_time: 0.0428 memory: 24011 grad_norm: 5.5963 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0741 loss: 1.0741 2022/09/05 14:11:14 - mmengine - INFO - Epoch(train) [33][280/940] lr: 1.0000e-02 eta: 11:45:02 time: 0.6149 data_time: 0.0403 memory: 24011 grad_norm: 4.5426 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1075 loss: 1.1075 2022/09/05 14:11:27 - mmengine - INFO - Epoch(train) [33][300/940] lr: 1.0000e-02 eta: 11:44:48 time: 0.6493 data_time: 0.0428 memory: 24011 grad_norm: 4.5962 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0633 loss: 1.0633 2022/09/05 14:11:40 - mmengine - INFO - Epoch(train) [33][320/940] lr: 1.0000e-02 eta: 11:44:34 time: 0.6517 data_time: 0.0389 memory: 24011 grad_norm: 4.6082 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0813 loss: 1.0813 2022/09/05 14:11:53 - mmengine - INFO - Epoch(train) [33][340/940] lr: 1.0000e-02 eta: 11:44:21 time: 0.6615 data_time: 0.0375 memory: 24011 grad_norm: 4.8457 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0732 loss: 1.0732 2022/09/05 14:12:06 - mmengine - INFO - Epoch(train) [33][360/940] lr: 1.0000e-02 eta: 11:44:05 time: 0.6173 data_time: 0.0354 memory: 24011 grad_norm: 4.5315 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0165 loss: 1.0165 2022/09/05 14:12:19 - mmengine - INFO - Epoch(train) [33][380/940] lr: 1.0000e-02 eta: 11:43:51 time: 0.6403 data_time: 0.0401 memory: 24011 grad_norm: 4.7559 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.0221 loss: 1.0221 2022/09/05 14:12:31 - mmengine - INFO - Epoch(train) [33][400/940] lr: 1.0000e-02 eta: 11:43:36 time: 0.6218 data_time: 0.0361 memory: 24011 grad_norm: 4.8589 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1135 loss: 1.1135 2022/09/05 14:12:44 - mmengine - INFO - Epoch(train) [33][420/940] lr: 1.0000e-02 eta: 11:43:23 time: 0.6706 data_time: 0.0408 memory: 24011 grad_norm: 4.8671 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0435 loss: 1.0435 2022/09/05 14:12:57 - mmengine - INFO - Epoch(train) [33][440/940] lr: 1.0000e-02 eta: 11:43:08 time: 0.6255 data_time: 0.0376 memory: 24011 grad_norm: 5.0891 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0272 loss: 1.0272 2022/09/05 14:13:11 - mmengine - INFO - Epoch(train) [33][460/940] lr: 1.0000e-02 eta: 11:42:56 time: 0.7039 data_time: 0.0404 memory: 24011 grad_norm: 4.8144 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2586 loss: 1.2586 2022/09/05 14:13:23 - mmengine - INFO - Epoch(train) [33][480/940] lr: 1.0000e-02 eta: 11:42:41 time: 0.6214 data_time: 0.0358 memory: 24011 grad_norm: 4.5282 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9945 loss: 0.9945 2022/09/05 14:13:38 - mmengine - INFO - Epoch(train) [33][500/940] lr: 1.0000e-02 eta: 11:42:30 time: 0.7088 data_time: 0.0612 memory: 24011 grad_norm: 4.6358 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9929 loss: 0.9929 2022/09/05 14:13:50 - mmengine - INFO - Epoch(train) [33][520/940] lr: 1.0000e-02 eta: 11:42:14 time: 0.6113 data_time: 0.0393 memory: 24011 grad_norm: 4.8129 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1016 loss: 1.1016 2022/09/05 14:14:04 - mmengine - INFO - Epoch(train) [33][540/940] lr: 1.0000e-02 eta: 11:42:02 time: 0.6884 data_time: 0.0389 memory: 24011 grad_norm: 4.4846 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1582 loss: 1.1582 2022/09/05 14:14:17 - mmengine - INFO - Epoch(train) [33][560/940] lr: 1.0000e-02 eta: 11:41:48 time: 0.6503 data_time: 0.0424 memory: 24011 grad_norm: 4.6051 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0094 loss: 1.0094 2022/09/05 14:14:30 - mmengine - INFO - Epoch(train) [33][580/940] lr: 1.0000e-02 eta: 11:41:36 time: 0.6950 data_time: 0.0543 memory: 24011 grad_norm: 4.6219 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9881 loss: 0.9881 2022/09/05 14:14:43 - mmengine - INFO - Epoch(train) [33][600/940] lr: 1.0000e-02 eta: 11:41:20 time: 0.6022 data_time: 0.0407 memory: 24011 grad_norm: 4.7447 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0995 loss: 1.0995 2022/09/05 14:14:56 - mmengine - INFO - Epoch(train) [33][620/940] lr: 1.0000e-02 eta: 11:41:07 time: 0.6688 data_time: 0.0444 memory: 24011 grad_norm: 4.4606 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2104 loss: 1.2104 2022/09/05 14:15:08 - mmengine - INFO - Epoch(train) [33][640/940] lr: 1.0000e-02 eta: 11:40:51 time: 0.6081 data_time: 0.0351 memory: 24011 grad_norm: 4.8725 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2094 loss: 1.2094 2022/09/05 14:15:21 - mmengine - INFO - Epoch(train) [33][660/940] lr: 1.0000e-02 eta: 11:40:37 time: 0.6250 data_time: 0.0433 memory: 24011 grad_norm: 4.4816 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1014 loss: 1.1014 2022/09/05 14:15:34 - mmengine - INFO - Epoch(train) [33][680/940] lr: 1.0000e-02 eta: 11:40:23 time: 0.6509 data_time: 0.0407 memory: 24011 grad_norm: 4.6168 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9904 loss: 0.9904 2022/09/05 14:15:47 - mmengine - INFO - Epoch(train) [33][700/940] lr: 1.0000e-02 eta: 11:40:10 time: 0.6873 data_time: 0.0451 memory: 24011 grad_norm: 4.6969 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0866 loss: 1.0866 2022/09/05 14:16:00 - mmengine - INFO - Epoch(train) [33][720/940] lr: 1.0000e-02 eta: 11:39:55 time: 0.6195 data_time: 0.0373 memory: 24011 grad_norm: 4.7317 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0674 loss: 1.0674 2022/09/05 14:16:13 - mmengine - INFO - Epoch(train) [33][740/940] lr: 1.0000e-02 eta: 11:39:41 time: 0.6525 data_time: 0.0355 memory: 24011 grad_norm: 4.4511 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0529 loss: 1.0529 2022/09/05 14:16:25 - mmengine - INFO - Epoch(train) [33][760/940] lr: 1.0000e-02 eta: 11:39:26 time: 0.6204 data_time: 0.0342 memory: 24011 grad_norm: 4.9611 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9620 loss: 0.9620 2022/09/05 14:16:38 - mmengine - INFO - Epoch(train) [33][780/940] lr: 1.0000e-02 eta: 11:39:12 time: 0.6394 data_time: 0.0330 memory: 24011 grad_norm: 4.5921 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1144 loss: 1.1144 2022/09/05 14:16:50 - mmengine - INFO - Epoch(train) [33][800/940] lr: 1.0000e-02 eta: 11:38:57 time: 0.6162 data_time: 0.0417 memory: 24011 grad_norm: 4.5377 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1262 loss: 1.1262 2022/09/05 14:17:03 - mmengine - INFO - Epoch(train) [33][820/940] lr: 1.0000e-02 eta: 11:38:43 time: 0.6496 data_time: 0.0381 memory: 24011 grad_norm: 4.8852 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8914 loss: 0.8914 2022/09/05 14:17:17 - mmengine - INFO - Epoch(train) [33][840/940] lr: 1.0000e-02 eta: 11:38:31 time: 0.6878 data_time: 0.0412 memory: 24011 grad_norm: 5.5801 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2546 loss: 1.2546 2022/09/05 14:17:30 - mmengine - INFO - Epoch(train) [33][860/940] lr: 1.0000e-02 eta: 11:38:16 time: 0.6351 data_time: 0.0436 memory: 24011 grad_norm: 4.5728 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0161 loss: 1.0161 2022/09/05 14:17:42 - mmengine - INFO - Epoch(train) [33][880/940] lr: 1.0000e-02 eta: 11:38:01 time: 0.6253 data_time: 0.0394 memory: 24011 grad_norm: 4.4417 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0924 loss: 1.0924 2022/09/05 14:17:55 - mmengine - INFO - Epoch(train) [33][900/940] lr: 1.0000e-02 eta: 11:37:46 time: 0.6089 data_time: 0.0343 memory: 24011 grad_norm: 4.4617 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0442 loss: 1.0442 2022/09/05 14:18:08 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:18:08 - mmengine - INFO - Epoch(train) [33][920/940] lr: 1.0000e-02 eta: 11:37:32 time: 0.6510 data_time: 0.0522 memory: 24011 grad_norm: 4.4738 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0873 loss: 1.0873 2022/09/05 14:18:19 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:18:19 - mmengine - INFO - Epoch(train) [33][940/940] lr: 1.0000e-02 eta: 11:37:15 time: 0.5741 data_time: 0.0409 memory: 24011 grad_norm: 4.5757 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.0428 loss: 1.0428 2022/09/05 14:18:19 - mmengine - INFO - Saving checkpoint at 33 epochs 2022/09/05 14:18:38 - mmengine - INFO - Epoch(val) [33][20/78] eta: 0:00:41 time: 0.7168 data_time: 0.5600 memory: 3625 2022/09/05 14:18:48 - mmengine - INFO - Epoch(val) [33][40/78] eta: 0:00:17 time: 0.4652 data_time: 0.3120 memory: 3625 2022/09/05 14:19:00 - mmengine - INFO - Epoch(val) [33][60/78] eta: 0:00:11 time: 0.6369 data_time: 0.4770 memory: 3625 2022/09/05 14:19:09 - mmengine - INFO - Epoch(val) [33][78/78] acc/top1: 0.7146 acc/top5: 0.8991 acc/mean1: 0.7144 2022/09/05 14:19:28 - mmengine - INFO - Epoch(train) [34][20/940] lr: 1.0000e-02 eta: 11:37:12 time: 0.9324 data_time: 0.2503 memory: 24011 grad_norm: 8.3577 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0880 loss: 1.0880 2022/09/05 14:19:41 - mmengine - INFO - Epoch(train) [34][40/940] lr: 1.0000e-02 eta: 11:36:58 time: 0.6447 data_time: 0.0351 memory: 24011 grad_norm: 5.0148 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1262 loss: 1.1262 2022/09/05 14:19:54 - mmengine - INFO - Epoch(train) [34][60/940] lr: 1.0000e-02 eta: 11:36:44 time: 0.6437 data_time: 0.0368 memory: 24011 grad_norm: 4.9664 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.0503 loss: 1.0503 2022/09/05 14:20:07 - mmengine - INFO - Epoch(train) [34][80/940] lr: 1.0000e-02 eta: 11:36:30 time: 0.6476 data_time: 0.0372 memory: 24011 grad_norm: 5.4224 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0975 loss: 1.0975 2022/09/05 14:20:21 - mmengine - INFO - Epoch(train) [34][100/940] lr: 1.0000e-02 eta: 11:36:19 time: 0.7041 data_time: 0.0382 memory: 24011 grad_norm: 5.1692 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0233 loss: 1.0233 2022/09/05 14:20:34 - mmengine - INFO - Epoch(train) [34][120/940] lr: 1.0000e-02 eta: 11:36:04 time: 0.6411 data_time: 0.0382 memory: 24011 grad_norm: 4.6408 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0251 loss: 1.0251 2022/09/05 14:20:47 - mmengine - INFO - Epoch(train) [34][140/940] lr: 1.0000e-02 eta: 11:35:52 time: 0.6764 data_time: 0.0391 memory: 24011 grad_norm: 4.6663 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 1.0682 loss: 1.0682 2022/09/05 14:21:00 - mmengine - INFO - Epoch(train) [34][160/940] lr: 1.0000e-02 eta: 11:35:36 time: 0.6132 data_time: 0.0368 memory: 24011 grad_norm: 4.8030 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1100 loss: 1.1100 2022/09/05 14:21:13 - mmengine - INFO - Epoch(train) [34][180/940] lr: 1.0000e-02 eta: 11:35:22 time: 0.6434 data_time: 0.0429 memory: 24011 grad_norm: 4.8049 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1067 loss: 1.1067 2022/09/05 14:21:26 - mmengine - INFO - Epoch(train) [34][200/940] lr: 1.0000e-02 eta: 11:35:09 time: 0.6607 data_time: 0.0589 memory: 24011 grad_norm: 4.6740 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0426 loss: 1.0426 2022/09/05 14:21:39 - mmengine - INFO - Epoch(train) [34][220/940] lr: 1.0000e-02 eta: 11:34:56 time: 0.6767 data_time: 0.0452 memory: 24011 grad_norm: 5.2213 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1375 loss: 1.1375 2022/09/05 14:21:52 - mmengine - INFO - Epoch(train) [34][240/940] lr: 1.0000e-02 eta: 11:34:42 time: 0.6476 data_time: 0.0453 memory: 24011 grad_norm: 5.0772 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0860 loss: 1.0860 2022/09/05 14:22:05 - mmengine - INFO - Epoch(train) [34][260/940] lr: 1.0000e-02 eta: 11:34:28 time: 0.6613 data_time: 0.0424 memory: 24011 grad_norm: 4.5653 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0920 loss: 1.0920 2022/09/05 14:22:18 - mmengine - INFO - Epoch(train) [34][280/940] lr: 1.0000e-02 eta: 11:34:13 time: 0.6123 data_time: 0.0424 memory: 24011 grad_norm: 5.0027 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0535 loss: 1.0535 2022/09/05 14:22:30 - mmengine - INFO - Epoch(train) [34][300/940] lr: 1.0000e-02 eta: 11:33:59 time: 0.6335 data_time: 0.0406 memory: 24011 grad_norm: 4.6970 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0048 loss: 1.0048 2022/09/05 14:22:44 - mmengine - INFO - Epoch(train) [34][320/940] lr: 1.0000e-02 eta: 11:33:45 time: 0.6621 data_time: 0.0483 memory: 24011 grad_norm: 4.5367 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0032 loss: 1.0032 2022/09/05 14:22:57 - mmengine - INFO - Epoch(train) [34][340/940] lr: 1.0000e-02 eta: 11:33:32 time: 0.6625 data_time: 0.0373 memory: 24011 grad_norm: 4.9651 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1161 loss: 1.1161 2022/09/05 14:23:09 - mmengine - INFO - Epoch(train) [34][360/940] lr: 1.0000e-02 eta: 11:33:17 time: 0.6152 data_time: 0.0492 memory: 24011 grad_norm: 4.7298 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1238 loss: 1.1238 2022/09/05 14:23:22 - mmengine - INFO - Epoch(train) [34][380/940] lr: 1.0000e-02 eta: 11:33:02 time: 0.6446 data_time: 0.0418 memory: 24011 grad_norm: 4.4966 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0620 loss: 1.0620 2022/09/05 14:23:35 - mmengine - INFO - Epoch(train) [34][400/940] lr: 1.0000e-02 eta: 11:32:48 time: 0.6282 data_time: 0.0394 memory: 24011 grad_norm: 4.4471 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1914 loss: 1.1914 2022/09/05 14:23:48 - mmengine - INFO - Epoch(train) [34][420/940] lr: 1.0000e-02 eta: 11:32:34 time: 0.6519 data_time: 0.0444 memory: 24011 grad_norm: 5.0636 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0566 loss: 1.0566 2022/09/05 14:24:01 - mmengine - INFO - Epoch(train) [34][440/940] lr: 1.0000e-02 eta: 11:32:21 time: 0.6669 data_time: 0.0470 memory: 24011 grad_norm: 4.5976 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1038 loss: 1.1038 2022/09/05 14:24:14 - mmengine - INFO - Epoch(train) [34][460/940] lr: 1.0000e-02 eta: 11:32:07 time: 0.6601 data_time: 0.0427 memory: 24011 grad_norm: 4.9542 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1023 loss: 1.1023 2022/09/05 14:24:27 - mmengine - INFO - Epoch(train) [34][480/940] lr: 1.0000e-02 eta: 11:31:53 time: 0.6391 data_time: 0.0329 memory: 24011 grad_norm: 5.3119 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0713 loss: 1.0713 2022/09/05 14:24:41 - mmengine - INFO - Epoch(train) [34][500/940] lr: 1.0000e-02 eta: 11:31:41 time: 0.6833 data_time: 0.0441 memory: 24011 grad_norm: 5.3446 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0773 loss: 1.0773 2022/09/05 14:24:53 - mmengine - INFO - Epoch(train) [34][520/940] lr: 1.0000e-02 eta: 11:31:26 time: 0.6272 data_time: 0.0544 memory: 24011 grad_norm: 5.1696 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2057 loss: 1.2057 2022/09/05 14:25:07 - mmengine - INFO - Epoch(train) [34][540/940] lr: 1.0000e-02 eta: 11:31:13 time: 0.6702 data_time: 0.0384 memory: 24011 grad_norm: 4.9474 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1585 loss: 1.1585 2022/09/05 14:25:19 - mmengine - INFO - Epoch(train) [34][560/940] lr: 1.0000e-02 eta: 11:30:58 time: 0.6278 data_time: 0.0415 memory: 24011 grad_norm: 4.8137 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0919 loss: 1.0919 2022/09/05 14:25:32 - mmengine - INFO - Epoch(train) [34][580/940] lr: 1.0000e-02 eta: 11:30:43 time: 0.6198 data_time: 0.0411 memory: 24011 grad_norm: 4.8203 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0512 loss: 1.0512 2022/09/05 14:25:45 - mmengine - INFO - Epoch(train) [34][600/940] lr: 1.0000e-02 eta: 11:30:30 time: 0.6840 data_time: 0.0432 memory: 24011 grad_norm: 4.6734 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0263 loss: 1.0263 2022/09/05 14:25:58 - mmengine - INFO - Epoch(train) [34][620/940] lr: 1.0000e-02 eta: 11:30:16 time: 0.6322 data_time: 0.0459 memory: 24011 grad_norm: 4.8828 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1118 loss: 1.1118 2022/09/05 14:26:11 - mmengine - INFO - Epoch(train) [34][640/940] lr: 1.0000e-02 eta: 11:30:02 time: 0.6520 data_time: 0.0482 memory: 24011 grad_norm: 5.0042 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0956 loss: 1.0956 2022/09/05 14:26:25 - mmengine - INFO - Epoch(train) [34][660/940] lr: 1.0000e-02 eta: 11:29:50 time: 0.6877 data_time: 0.0378 memory: 24011 grad_norm: 4.5608 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1316 loss: 1.1316 2022/09/05 14:26:37 - mmengine - INFO - Epoch(train) [34][680/940] lr: 1.0000e-02 eta: 11:29:35 time: 0.6243 data_time: 0.0380 memory: 24011 grad_norm: 4.7332 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9937 loss: 0.9937 2022/09/05 14:26:51 - mmengine - INFO - Epoch(train) [34][700/940] lr: 1.0000e-02 eta: 11:29:22 time: 0.6798 data_time: 0.0503 memory: 24011 grad_norm: 4.4972 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.0870 loss: 1.0870 2022/09/05 14:27:04 - mmengine - INFO - Epoch(train) [34][720/940] lr: 1.0000e-02 eta: 11:29:08 time: 0.6337 data_time: 0.0384 memory: 24011 grad_norm: 4.4290 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0657 loss: 1.0657 2022/09/05 14:27:17 - mmengine - INFO - Epoch(train) [34][740/940] lr: 1.0000e-02 eta: 11:28:54 time: 0.6555 data_time: 0.0416 memory: 24011 grad_norm: 5.0320 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1134 loss: 1.1134 2022/09/05 14:27:29 - mmengine - INFO - Epoch(train) [34][760/940] lr: 1.0000e-02 eta: 11:28:39 time: 0.6258 data_time: 0.0375 memory: 24011 grad_norm: 5.4855 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2431 loss: 1.2431 2022/09/05 14:27:42 - mmengine - INFO - Epoch(train) [34][780/940] lr: 1.0000e-02 eta: 11:28:25 time: 0.6335 data_time: 0.0414 memory: 24011 grad_norm: 4.8977 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0238 loss: 1.0238 2022/09/05 14:27:55 - mmengine - INFO - Epoch(train) [34][800/940] lr: 1.0000e-02 eta: 11:28:12 time: 0.6622 data_time: 0.0366 memory: 24011 grad_norm: 4.7415 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0465 loss: 1.0465 2022/09/05 14:28:08 - mmengine - INFO - Epoch(train) [34][820/940] lr: 1.0000e-02 eta: 11:27:58 time: 0.6437 data_time: 0.0405 memory: 24011 grad_norm: 4.5999 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1192 loss: 1.1192 2022/09/05 14:28:21 - mmengine - INFO - Epoch(train) [34][840/940] lr: 1.0000e-02 eta: 11:27:43 time: 0.6346 data_time: 0.0392 memory: 24011 grad_norm: 8.9760 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0911 loss: 1.0911 2022/09/05 14:28:34 - mmengine - INFO - Epoch(train) [34][860/940] lr: 1.0000e-02 eta: 11:27:30 time: 0.6630 data_time: 0.0409 memory: 24011 grad_norm: 6.6449 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3061 loss: 1.3061 2022/09/05 14:28:47 - mmengine - INFO - Epoch(train) [34][880/940] lr: 1.0000e-02 eta: 11:27:15 time: 0.6308 data_time: 0.0400 memory: 24011 grad_norm: 5.2486 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2724 loss: 1.2724 2022/09/05 14:28:59 - mmengine - INFO - Epoch(train) [34][900/940] lr: 1.0000e-02 eta: 11:27:00 time: 0.6029 data_time: 0.0402 memory: 24011 grad_norm: 5.0720 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1413 loss: 1.1413 2022/09/05 14:29:12 - mmengine - INFO - Epoch(train) [34][920/940] lr: 1.0000e-02 eta: 11:26:46 time: 0.6599 data_time: 0.0418 memory: 24011 grad_norm: 5.6562 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.9962 loss: 0.9962 2022/09/05 14:29:23 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:29:23 - mmengine - INFO - Epoch(train) [34][940/940] lr: 1.0000e-02 eta: 11:26:29 time: 0.5553 data_time: 0.0258 memory: 24011 grad_norm: 5.4810 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.2298 loss: 1.2298 2022/09/05 14:29:37 - mmengine - INFO - Epoch(val) [34][20/78] eta: 0:00:40 time: 0.6923 data_time: 0.5342 memory: 3625 2022/09/05 14:29:47 - mmengine - INFO - Epoch(val) [34][40/78] eta: 0:00:18 time: 0.4847 data_time: 0.3293 memory: 3625 2022/09/05 14:30:00 - mmengine - INFO - Epoch(val) [34][60/78] eta: 0:00:11 time: 0.6627 data_time: 0.5070 memory: 3625 2022/09/05 14:30:10 - mmengine - INFO - Epoch(val) [34][78/78] acc/top1: 0.6979 acc/top5: 0.8920 acc/mean1: 0.6978 2022/09/05 14:30:28 - mmengine - INFO - Epoch(train) [35][20/940] lr: 1.0000e-02 eta: 11:26:25 time: 0.9034 data_time: 0.2434 memory: 24011 grad_norm: 4.9767 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0613 loss: 1.0613 2022/09/05 14:30:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:30:41 - mmengine - INFO - Epoch(train) [35][40/940] lr: 1.0000e-02 eta: 11:26:11 time: 0.6506 data_time: 0.0373 memory: 24011 grad_norm: 4.8099 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1079 loss: 1.1079 2022/09/05 14:30:54 - mmengine - INFO - Epoch(train) [35][60/940] lr: 1.0000e-02 eta: 11:25:57 time: 0.6487 data_time: 0.0476 memory: 24011 grad_norm: 5.8625 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1298 loss: 1.1298 2022/09/05 14:31:06 - mmengine - INFO - Epoch(train) [35][80/940] lr: 1.0000e-02 eta: 11:25:42 time: 0.6175 data_time: 0.0530 memory: 24011 grad_norm: 4.8797 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2076 loss: 1.2076 2022/09/05 14:31:20 - mmengine - INFO - Epoch(train) [35][100/940] lr: 1.0000e-02 eta: 11:25:28 time: 0.6515 data_time: 0.0421 memory: 24011 grad_norm: 5.0992 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1237 loss: 1.1237 2022/09/05 14:31:33 - mmengine - INFO - Epoch(train) [35][120/940] lr: 1.0000e-02 eta: 11:25:14 time: 0.6526 data_time: 0.0373 memory: 24011 grad_norm: 4.6695 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1657 loss: 1.1657 2022/09/05 14:31:47 - mmengine - INFO - Epoch(train) [35][140/940] lr: 1.0000e-02 eta: 11:25:03 time: 0.7041 data_time: 0.0407 memory: 24011 grad_norm: 4.8990 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.0860 loss: 1.0860 2022/09/05 14:32:00 - mmengine - INFO - Epoch(train) [35][160/940] lr: 1.0000e-02 eta: 11:24:49 time: 0.6425 data_time: 0.0364 memory: 24011 grad_norm: 5.0430 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0901 loss: 1.0901 2022/09/05 14:32:12 - mmengine - INFO - Epoch(train) [35][180/940] lr: 1.0000e-02 eta: 11:24:34 time: 0.6351 data_time: 0.0437 memory: 24011 grad_norm: 5.1207 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.0761 loss: 1.0761 2022/09/05 14:32:24 - mmengine - INFO - Epoch(train) [35][200/940] lr: 1.0000e-02 eta: 11:24:18 time: 0.5972 data_time: 0.0405 memory: 24011 grad_norm: 4.6503 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1441 loss: 1.1441 2022/09/05 14:32:37 - mmengine - INFO - Epoch(train) [35][220/940] lr: 1.0000e-02 eta: 11:24:05 time: 0.6627 data_time: 0.0435 memory: 24011 grad_norm: 4.9937 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0817 loss: 1.0817 2022/09/05 14:32:50 - mmengine - INFO - Epoch(train) [35][240/940] lr: 1.0000e-02 eta: 11:23:50 time: 0.6303 data_time: 0.0437 memory: 24011 grad_norm: 4.9387 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9709 loss: 0.9709 2022/09/05 14:33:03 - mmengine - INFO - Epoch(train) [35][260/940] lr: 1.0000e-02 eta: 11:23:37 time: 0.6520 data_time: 0.0383 memory: 24011 grad_norm: 4.8604 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0882 loss: 1.0882 2022/09/05 14:33:16 - mmengine - INFO - Epoch(train) [35][280/940] lr: 1.0000e-02 eta: 11:23:22 time: 0.6346 data_time: 0.0409 memory: 24011 grad_norm: 4.9685 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1250 loss: 1.1250 2022/09/05 14:33:29 - mmengine - INFO - Epoch(train) [35][300/940] lr: 1.0000e-02 eta: 11:23:09 time: 0.6706 data_time: 0.0520 memory: 24011 grad_norm: 4.9095 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8427 loss: 0.8427 2022/09/05 14:33:42 - mmengine - INFO - Epoch(train) [35][320/940] lr: 1.0000e-02 eta: 11:22:54 time: 0.6253 data_time: 0.0412 memory: 24011 grad_norm: 5.0883 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0963 loss: 1.0963 2022/09/05 14:33:56 - mmengine - INFO - Epoch(train) [35][340/940] lr: 1.0000e-02 eta: 11:22:43 time: 0.7070 data_time: 0.0329 memory: 24011 grad_norm: 4.9376 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1688 loss: 1.1688 2022/09/05 14:34:08 - mmengine - INFO - Epoch(train) [35][360/940] lr: 1.0000e-02 eta: 11:22:28 time: 0.6249 data_time: 0.0408 memory: 24011 grad_norm: 5.2755 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1444 loss: 1.1444 2022/09/05 14:34:22 - mmengine - INFO - Epoch(train) [35][380/940] lr: 1.0000e-02 eta: 11:22:15 time: 0.6718 data_time: 0.0409 memory: 24011 grad_norm: 4.7265 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.1064 loss: 1.1064 2022/09/05 14:34:35 - mmengine - INFO - Epoch(train) [35][400/940] lr: 1.0000e-02 eta: 11:22:02 time: 0.6650 data_time: 0.0386 memory: 24011 grad_norm: 4.5862 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.9696 loss: 0.9696 2022/09/05 14:34:47 - mmengine - INFO - Epoch(train) [35][420/940] lr: 1.0000e-02 eta: 11:21:46 time: 0.6015 data_time: 0.0425 memory: 24011 grad_norm: 4.7370 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.0769 loss: 1.0769 2022/09/05 14:35:00 - mmengine - INFO - Epoch(train) [35][440/940] lr: 1.0000e-02 eta: 11:21:32 time: 0.6521 data_time: 0.0418 memory: 24011 grad_norm: 4.8306 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0857 loss: 1.0857 2022/09/05 14:35:13 - mmengine - INFO - Epoch(train) [35][460/940] lr: 1.0000e-02 eta: 11:21:18 time: 0.6354 data_time: 0.0440 memory: 24011 grad_norm: 5.2992 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0027 loss: 1.0027 2022/09/05 14:35:25 - mmengine - INFO - Epoch(train) [35][480/940] lr: 1.0000e-02 eta: 11:21:03 time: 0.6052 data_time: 0.0514 memory: 24011 grad_norm: 4.6463 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1477 loss: 1.1477 2022/09/05 14:35:39 - mmengine - INFO - Epoch(train) [35][500/940] lr: 1.0000e-02 eta: 11:20:50 time: 0.6788 data_time: 0.0507 memory: 24011 grad_norm: 5.2419 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0238 loss: 1.0238 2022/09/05 14:35:51 - mmengine - INFO - Epoch(train) [35][520/940] lr: 1.0000e-02 eta: 11:20:35 time: 0.6151 data_time: 0.0427 memory: 24011 grad_norm: 4.7326 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1237 loss: 1.1237 2022/09/05 14:36:04 - mmengine - INFO - Epoch(train) [35][540/940] lr: 1.0000e-02 eta: 11:20:22 time: 0.6632 data_time: 0.0527 memory: 24011 grad_norm: 4.7108 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1272 loss: 1.1272 2022/09/05 14:36:18 - mmengine - INFO - Epoch(train) [35][560/940] lr: 1.0000e-02 eta: 11:20:09 time: 0.6809 data_time: 0.0305 memory: 24011 grad_norm: 5.2834 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1761 loss: 1.1761 2022/09/05 14:36:30 - mmengine - INFO - Epoch(train) [35][580/940] lr: 1.0000e-02 eta: 11:19:54 time: 0.6092 data_time: 0.0405 memory: 24011 grad_norm: 4.9871 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.0207 loss: 1.0207 2022/09/05 14:36:43 - mmengine - INFO - Epoch(train) [35][600/940] lr: 1.0000e-02 eta: 11:19:40 time: 0.6686 data_time: 0.0858 memory: 24011 grad_norm: 4.7760 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0147 loss: 1.0147 2022/09/05 14:36:56 - mmengine - INFO - Epoch(train) [35][620/940] lr: 1.0000e-02 eta: 11:19:26 time: 0.6396 data_time: 0.0644 memory: 24011 grad_norm: 4.9019 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1026 loss: 1.1026 2022/09/05 14:37:09 - mmengine - INFO - Epoch(train) [35][640/940] lr: 1.0000e-02 eta: 11:19:11 time: 0.6202 data_time: 0.0376 memory: 24011 grad_norm: 5.4235 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1791 loss: 1.1791 2022/09/05 14:37:21 - mmengine - INFO - Epoch(train) [35][660/940] lr: 1.0000e-02 eta: 11:18:57 time: 0.6450 data_time: 0.0413 memory: 24011 grad_norm: 5.0808 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0932 loss: 1.0932 2022/09/05 14:37:35 - mmengine - INFO - Epoch(train) [35][680/940] lr: 1.0000e-02 eta: 11:18:44 time: 0.6658 data_time: 0.0323 memory: 24011 grad_norm: 4.9568 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2762 loss: 1.2762 2022/09/05 14:37:48 - mmengine - INFO - Epoch(train) [35][700/940] lr: 1.0000e-02 eta: 11:18:30 time: 0.6424 data_time: 0.0423 memory: 24011 grad_norm: 4.8471 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1202 loss: 1.1202 2022/09/05 14:38:01 - mmengine - INFO - Epoch(train) [35][720/940] lr: 1.0000e-02 eta: 11:18:17 time: 0.6803 data_time: 0.0428 memory: 24011 grad_norm: 4.7056 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.0798 loss: 1.0798 2022/09/05 14:38:14 - mmengine - INFO - Epoch(train) [35][740/940] lr: 1.0000e-02 eta: 11:18:03 time: 0.6194 data_time: 0.0439 memory: 24011 grad_norm: 5.0432 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1998 loss: 1.1998 2022/09/05 14:38:27 - mmengine - INFO - Epoch(train) [35][760/940] lr: 1.0000e-02 eta: 11:17:49 time: 0.6566 data_time: 0.0385 memory: 24011 grad_norm: 8.9951 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0139 loss: 1.0139 2022/09/05 14:38:39 - mmengine - INFO - Epoch(train) [35][780/940] lr: 1.0000e-02 eta: 11:17:34 time: 0.6309 data_time: 0.0380 memory: 24011 grad_norm: 5.3868 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1998 loss: 1.1998 2022/09/05 14:38:53 - mmengine - INFO - Epoch(train) [35][800/940] lr: 1.0000e-02 eta: 11:17:22 time: 0.6814 data_time: 0.0479 memory: 24011 grad_norm: 5.5226 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2094 loss: 1.2094 2022/09/05 14:39:07 - mmengine - INFO - Epoch(train) [35][820/940] lr: 1.0000e-02 eta: 11:17:09 time: 0.6772 data_time: 0.0932 memory: 24011 grad_norm: 5.4646 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1398 loss: 1.1398 2022/09/05 14:39:20 - mmengine - INFO - Epoch(train) [35][840/940] lr: 1.0000e-02 eta: 11:16:57 time: 0.6823 data_time: 0.1095 memory: 24011 grad_norm: 4.9070 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0893 loss: 1.0893 2022/09/05 14:39:33 - mmengine - INFO - Epoch(train) [35][860/940] lr: 1.0000e-02 eta: 11:16:43 time: 0.6512 data_time: 0.0721 memory: 24011 grad_norm: 4.6932 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1326 loss: 1.1326 2022/09/05 14:39:47 - mmengine - INFO - Epoch(train) [35][880/940] lr: 1.0000e-02 eta: 11:16:30 time: 0.6665 data_time: 0.0966 memory: 24011 grad_norm: 4.8958 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0570 loss: 1.0570 2022/09/05 14:40:00 - mmengine - INFO - Epoch(train) [35][900/940] lr: 1.0000e-02 eta: 11:16:16 time: 0.6477 data_time: 0.0629 memory: 24011 grad_norm: 4.8153 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1264 loss: 1.1264 2022/09/05 14:40:13 - mmengine - INFO - Epoch(train) [35][920/940] lr: 1.0000e-02 eta: 11:16:02 time: 0.6637 data_time: 0.0973 memory: 24011 grad_norm: 5.2068 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0395 loss: 1.0395 2022/09/05 14:40:24 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:40:24 - mmengine - INFO - Epoch(train) [35][940/940] lr: 1.0000e-02 eta: 11:15:45 time: 0.5390 data_time: 0.0276 memory: 24011 grad_norm: 5.2967 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.0689 loss: 1.0689 2022/09/05 14:40:38 - mmengine - INFO - Epoch(val) [35][20/78] eta: 0:00:40 time: 0.6954 data_time: 0.5369 memory: 3625 2022/09/05 14:40:47 - mmengine - INFO - Epoch(val) [35][40/78] eta: 0:00:17 time: 0.4556 data_time: 0.3000 memory: 3625 2022/09/05 14:41:00 - mmengine - INFO - Epoch(val) [35][60/78] eta: 0:00:11 time: 0.6535 data_time: 0.4976 memory: 3625 2022/09/05 14:41:10 - mmengine - INFO - Epoch(val) [35][78/78] acc/top1: 0.7088 acc/top5: 0.8976 acc/mean1: 0.7086 2022/09/05 14:41:29 - mmengine - INFO - Epoch(train) [36][20/940] lr: 1.0000e-02 eta: 11:15:41 time: 0.9203 data_time: 0.2633 memory: 24011 grad_norm: 6.1203 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0612 loss: 1.0612 2022/09/05 14:41:42 - mmengine - INFO - Epoch(train) [36][40/940] lr: 1.0000e-02 eta: 11:15:26 time: 0.6326 data_time: 0.0331 memory: 24011 grad_norm: 5.1450 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.1109 loss: 1.1109 2022/09/05 14:41:55 - mmengine - INFO - Epoch(train) [36][60/940] lr: 1.0000e-02 eta: 11:15:14 time: 0.6938 data_time: 0.0393 memory: 24011 grad_norm: 5.1536 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0149 loss: 1.0149 2022/09/05 14:42:09 - mmengine - INFO - Epoch(train) [36][80/940] lr: 1.0000e-02 eta: 11:15:01 time: 0.6680 data_time: 0.0348 memory: 24011 grad_norm: 5.0340 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1072 loss: 1.1072 2022/09/05 14:42:21 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:42:21 - mmengine - INFO - Epoch(train) [36][100/940] lr: 1.0000e-02 eta: 11:14:47 time: 0.6293 data_time: 0.0512 memory: 24011 grad_norm: 4.9848 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0430 loss: 1.0430 2022/09/05 14:42:34 - mmengine - INFO - Epoch(train) [36][120/940] lr: 1.0000e-02 eta: 11:14:32 time: 0.6338 data_time: 0.0414 memory: 24011 grad_norm: 5.6122 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0759 loss: 1.0759 2022/09/05 14:42:47 - mmengine - INFO - Epoch(train) [36][140/940] lr: 1.0000e-02 eta: 11:14:18 time: 0.6401 data_time: 0.0404 memory: 24011 grad_norm: 4.8392 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0830 loss: 1.0830 2022/09/05 14:43:00 - mmengine - INFO - Epoch(train) [36][160/940] lr: 1.0000e-02 eta: 11:14:05 time: 0.6642 data_time: 0.0347 memory: 24011 grad_norm: 4.7798 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0742 loss: 1.0742 2022/09/05 14:43:14 - mmengine - INFO - Epoch(train) [36][180/940] lr: 1.0000e-02 eta: 11:13:53 time: 0.6990 data_time: 0.0492 memory: 24011 grad_norm: 5.1510 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9776 loss: 0.9776 2022/09/05 14:43:26 - mmengine - INFO - Epoch(train) [36][200/940] lr: 1.0000e-02 eta: 11:13:38 time: 0.6145 data_time: 0.0424 memory: 24011 grad_norm: 4.9431 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1402 loss: 1.1402 2022/09/05 14:43:40 - mmengine - INFO - Epoch(train) [36][220/940] lr: 1.0000e-02 eta: 11:13:24 time: 0.6435 data_time: 0.0461 memory: 24011 grad_norm: 4.9455 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0444 loss: 1.0444 2022/09/05 14:43:52 - mmengine - INFO - Epoch(train) [36][240/940] lr: 1.0000e-02 eta: 11:13:09 time: 0.6360 data_time: 0.0551 memory: 24011 grad_norm: 5.6883 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0701 loss: 1.0701 2022/09/05 14:44:06 - mmengine - INFO - Epoch(train) [36][260/940] lr: 1.0000e-02 eta: 11:12:57 time: 0.6894 data_time: 0.0432 memory: 24011 grad_norm: 4.9735 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2059 loss: 1.2059 2022/09/05 14:44:19 - mmengine - INFO - Epoch(train) [36][280/940] lr: 1.0000e-02 eta: 11:12:43 time: 0.6339 data_time: 0.0396 memory: 24011 grad_norm: 5.0906 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0803 loss: 1.0803 2022/09/05 14:44:32 - mmengine - INFO - Epoch(train) [36][300/940] lr: 1.0000e-02 eta: 11:12:29 time: 0.6631 data_time: 0.0393 memory: 24011 grad_norm: 6.9348 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1659 loss: 1.1659 2022/09/05 14:44:44 - mmengine - INFO - Epoch(train) [36][320/940] lr: 1.0000e-02 eta: 11:12:15 time: 0.6269 data_time: 0.0419 memory: 24011 grad_norm: 5.4481 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2513 loss: 1.2513 2022/09/05 14:44:57 - mmengine - INFO - Epoch(train) [36][340/940] lr: 1.0000e-02 eta: 11:12:01 time: 0.6463 data_time: 0.0418 memory: 24011 grad_norm: 5.6387 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0427 loss: 1.0427 2022/09/05 14:45:10 - mmengine - INFO - Epoch(train) [36][360/940] lr: 1.0000e-02 eta: 11:11:47 time: 0.6380 data_time: 0.0407 memory: 24011 grad_norm: 5.1583 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1149 loss: 1.1149 2022/09/05 14:45:23 - mmengine - INFO - Epoch(train) [36][380/940] lr: 1.0000e-02 eta: 11:11:33 time: 0.6558 data_time: 0.0405 memory: 24011 grad_norm: 5.4510 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0880 loss: 1.0880 2022/09/05 14:45:36 - mmengine - INFO - Epoch(train) [36][400/940] lr: 1.0000e-02 eta: 11:11:20 time: 0.6570 data_time: 0.0381 memory: 24011 grad_norm: 5.0293 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1178 loss: 1.1178 2022/09/05 14:45:49 - mmengine - INFO - Epoch(train) [36][420/940] lr: 1.0000e-02 eta: 11:11:06 time: 0.6441 data_time: 0.0407 memory: 24011 grad_norm: 4.8651 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1609 loss: 1.1609 2022/09/05 14:46:02 - mmengine - INFO - Epoch(train) [36][440/940] lr: 1.0000e-02 eta: 11:10:52 time: 0.6432 data_time: 0.0434 memory: 24011 grad_norm: 4.8007 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1463 loss: 1.1463 2022/09/05 14:46:16 - mmengine - INFO - Epoch(train) [36][460/940] lr: 1.0000e-02 eta: 11:10:39 time: 0.6852 data_time: 0.0412 memory: 24011 grad_norm: 5.0002 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0137 loss: 1.0137 2022/09/05 14:46:29 - mmengine - INFO - Epoch(train) [36][480/940] lr: 1.0000e-02 eta: 11:10:25 time: 0.6471 data_time: 0.0442 memory: 24011 grad_norm: 4.9173 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0934 loss: 1.0934 2022/09/05 14:46:42 - mmengine - INFO - Epoch(train) [36][500/940] lr: 1.0000e-02 eta: 11:10:12 time: 0.6646 data_time: 0.0451 memory: 24011 grad_norm: 4.7086 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9829 loss: 0.9829 2022/09/05 14:46:55 - mmengine - INFO - Epoch(train) [36][520/940] lr: 1.0000e-02 eta: 11:09:58 time: 0.6481 data_time: 0.0447 memory: 24011 grad_norm: 4.8162 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0658 loss: 1.0658 2022/09/05 14:47:08 - mmengine - INFO - Epoch(train) [36][540/940] lr: 1.0000e-02 eta: 11:09:44 time: 0.6500 data_time: 0.0814 memory: 24011 grad_norm: 8.0919 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0917 loss: 1.0917 2022/09/05 14:47:21 - mmengine - INFO - Epoch(train) [36][560/940] lr: 1.0000e-02 eta: 11:09:31 time: 0.6484 data_time: 0.0562 memory: 24011 grad_norm: 5.1855 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2519 loss: 1.2519 2022/09/05 14:47:34 - mmengine - INFO - Epoch(train) [36][580/940] lr: 1.0000e-02 eta: 11:09:18 time: 0.6711 data_time: 0.0355 memory: 24011 grad_norm: 5.0626 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1056 loss: 1.1056 2022/09/05 14:47:46 - mmengine - INFO - Epoch(train) [36][600/940] lr: 1.0000e-02 eta: 11:09:02 time: 0.6034 data_time: 0.0439 memory: 24011 grad_norm: 4.9761 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9970 loss: 0.9970 2022/09/05 14:48:00 - mmengine - INFO - Epoch(train) [36][620/940] lr: 1.0000e-02 eta: 11:08:49 time: 0.6740 data_time: 0.0479 memory: 24011 grad_norm: 5.2125 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2370 loss: 1.2370 2022/09/05 14:48:13 - mmengine - INFO - Epoch(train) [36][640/940] lr: 1.0000e-02 eta: 11:08:35 time: 0.6474 data_time: 0.0435 memory: 24011 grad_norm: 4.7241 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0828 loss: 1.0828 2022/09/05 14:48:26 - mmengine - INFO - Epoch(train) [36][660/940] lr: 1.0000e-02 eta: 11:08:21 time: 0.6328 data_time: 0.0401 memory: 24011 grad_norm: 6.7727 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1670 loss: 1.1670 2022/09/05 14:48:39 - mmengine - INFO - Epoch(train) [36][680/940] lr: 1.0000e-02 eta: 11:08:08 time: 0.6592 data_time: 0.0434 memory: 24011 grad_norm: 5.0133 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1518 loss: 1.1518 2022/09/05 14:48:51 - mmengine - INFO - Epoch(train) [36][700/940] lr: 1.0000e-02 eta: 11:07:53 time: 0.6275 data_time: 0.0389 memory: 24011 grad_norm: 5.6071 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1331 loss: 1.1331 2022/09/05 14:49:04 - mmengine - INFO - Epoch(train) [36][720/940] lr: 1.0000e-02 eta: 11:07:38 time: 0.6158 data_time: 0.0381 memory: 24011 grad_norm: 5.4203 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0576 loss: 1.0576 2022/09/05 14:49:18 - mmengine - INFO - Epoch(train) [36][740/940] lr: 1.0000e-02 eta: 11:07:26 time: 0.6956 data_time: 0.0423 memory: 24011 grad_norm: 4.9002 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1876 loss: 1.1876 2022/09/05 14:49:31 - mmengine - INFO - Epoch(train) [36][760/940] lr: 1.0000e-02 eta: 11:07:12 time: 0.6503 data_time: 0.0465 memory: 24011 grad_norm: 4.9929 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0132 loss: 1.0132 2022/09/05 14:49:45 - mmengine - INFO - Epoch(train) [36][780/940] lr: 1.0000e-02 eta: 11:07:00 time: 0.7011 data_time: 0.0416 memory: 24011 grad_norm: 4.8311 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1792 loss: 1.1792 2022/09/05 14:49:57 - mmengine - INFO - Epoch(train) [36][800/940] lr: 1.0000e-02 eta: 11:06:45 time: 0.6010 data_time: 0.0388 memory: 24011 grad_norm: 5.2298 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0821 loss: 1.0821 2022/09/05 14:50:10 - mmengine - INFO - Epoch(train) [36][820/940] lr: 1.0000e-02 eta: 11:06:31 time: 0.6589 data_time: 0.0399 memory: 24011 grad_norm: 4.8120 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1677 loss: 1.1677 2022/09/05 14:50:22 - mmengine - INFO - Epoch(train) [36][840/940] lr: 1.0000e-02 eta: 11:06:16 time: 0.6144 data_time: 0.0421 memory: 24011 grad_norm: 4.9126 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0346 loss: 1.0346 2022/09/05 14:50:36 - mmengine - INFO - Epoch(train) [36][860/940] lr: 1.0000e-02 eta: 11:06:04 time: 0.6881 data_time: 0.0367 memory: 24011 grad_norm: 4.9365 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1057 loss: 1.1057 2022/09/05 14:50:49 - mmengine - INFO - Epoch(train) [36][880/940] lr: 1.0000e-02 eta: 11:05:50 time: 0.6359 data_time: 0.0449 memory: 24011 grad_norm: 4.7840 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0169 loss: 1.0169 2022/09/05 14:51:02 - mmengine - INFO - Epoch(train) [36][900/940] lr: 1.0000e-02 eta: 11:05:36 time: 0.6480 data_time: 0.0483 memory: 24011 grad_norm: 5.1130 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1052 loss: 1.1052 2022/09/05 14:51:15 - mmengine - INFO - Epoch(train) [36][920/940] lr: 1.0000e-02 eta: 11:05:22 time: 0.6454 data_time: 0.0444 memory: 24011 grad_norm: 5.0684 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9446 loss: 0.9446 2022/09/05 14:51:26 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:51:26 - mmengine - INFO - Epoch(train) [36][940/940] lr: 1.0000e-02 eta: 11:05:05 time: 0.5668 data_time: 0.0377 memory: 24011 grad_norm: 5.4657 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.0218 loss: 1.0218 2022/09/05 14:51:26 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/09/05 14:51:46 - mmengine - INFO - Epoch(val) [36][20/78] eta: 0:00:42 time: 0.7276 data_time: 0.5729 memory: 3625 2022/09/05 14:51:55 - mmengine - INFO - Epoch(val) [36][40/78] eta: 0:00:17 time: 0.4574 data_time: 0.3033 memory: 3625 2022/09/05 14:52:08 - mmengine - INFO - Epoch(val) [36][60/78] eta: 0:00:11 time: 0.6546 data_time: 0.4988 memory: 3625 2022/09/05 14:52:16 - mmengine - INFO - Epoch(val) [36][78/78] acc/top1: 0.7127 acc/top5: 0.8970 acc/mean1: 0.7125 2022/09/05 14:52:35 - mmengine - INFO - Epoch(train) [37][20/940] lr: 1.0000e-02 eta: 11:05:01 time: 0.9193 data_time: 0.2419 memory: 24011 grad_norm: 5.0115 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.0683 loss: 1.0683 2022/09/05 14:52:48 - mmengine - INFO - Epoch(train) [37][40/940] lr: 1.0000e-02 eta: 11:04:47 time: 0.6324 data_time: 0.0464 memory: 24011 grad_norm: 5.0429 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0721 loss: 1.0721 2022/09/05 14:53:01 - mmengine - INFO - Epoch(train) [37][60/940] lr: 1.0000e-02 eta: 11:04:35 time: 0.6921 data_time: 0.0469 memory: 24011 grad_norm: 4.6259 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0464 loss: 1.0464 2022/09/05 14:53:14 - mmengine - INFO - Epoch(train) [37][80/940] lr: 1.0000e-02 eta: 11:04:20 time: 0.6171 data_time: 0.0338 memory: 24011 grad_norm: 5.2156 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1768 loss: 1.1768 2022/09/05 14:53:28 - mmengine - INFO - Epoch(train) [37][100/940] lr: 1.0000e-02 eta: 11:04:08 time: 0.7245 data_time: 0.0426 memory: 24011 grad_norm: 4.5254 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9396 loss: 0.9396 2022/09/05 14:53:41 - mmengine - INFO - Epoch(train) [37][120/940] lr: 1.0000e-02 eta: 11:03:54 time: 0.6341 data_time: 0.0294 memory: 24011 grad_norm: 5.1803 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0563 loss: 1.0563 2022/09/05 14:53:54 - mmengine - INFO - Epoch(train) [37][140/940] lr: 1.0000e-02 eta: 11:03:41 time: 0.6725 data_time: 0.0418 memory: 24011 grad_norm: 4.9576 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1176 loss: 1.1176 2022/09/05 14:54:06 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 14:54:07 - mmengine - INFO - Epoch(train) [37][160/940] lr: 1.0000e-02 eta: 11:03:26 time: 0.6026 data_time: 0.0414 memory: 24011 grad_norm: 4.8338 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0085 loss: 1.0085 2022/09/05 14:54:20 - mmengine - INFO - Epoch(train) [37][180/940] lr: 1.0000e-02 eta: 11:03:13 time: 0.6661 data_time: 0.0385 memory: 24011 grad_norm: 4.8250 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9945 loss: 0.9945 2022/09/05 14:54:33 - mmengine - INFO - Epoch(train) [37][200/940] lr: 1.0000e-02 eta: 11:02:59 time: 0.6521 data_time: 0.0370 memory: 24011 grad_norm: 4.6835 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0520 loss: 1.0520 2022/09/05 14:54:46 - mmengine - INFO - Epoch(train) [37][220/940] lr: 1.0000e-02 eta: 11:02:46 time: 0.6737 data_time: 0.0364 memory: 24011 grad_norm: 4.5923 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9503 loss: 0.9503 2022/09/05 14:54:59 - mmengine - INFO - Epoch(train) [37][240/940] lr: 1.0000e-02 eta: 11:02:31 time: 0.6233 data_time: 0.0689 memory: 24011 grad_norm: 4.8043 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1337 loss: 1.1337 2022/09/05 14:55:11 - mmengine - INFO - Epoch(train) [37][260/940] lr: 1.0000e-02 eta: 11:02:17 time: 0.6323 data_time: 0.0417 memory: 24011 grad_norm: 4.6592 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0141 loss: 1.0141 2022/09/05 14:55:24 - mmengine - INFO - Epoch(train) [37][280/940] lr: 1.0000e-02 eta: 11:02:02 time: 0.6196 data_time: 0.0418 memory: 24011 grad_norm: 4.9080 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0201 loss: 1.0201 2022/09/05 14:55:37 - mmengine - INFO - Epoch(train) [37][300/940] lr: 1.0000e-02 eta: 11:01:48 time: 0.6415 data_time: 0.0408 memory: 24011 grad_norm: 4.8397 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0112 loss: 1.0112 2022/09/05 14:55:49 - mmengine - INFO - Epoch(train) [37][320/940] lr: 1.0000e-02 eta: 11:01:34 time: 0.6235 data_time: 0.0391 memory: 24011 grad_norm: 5.1027 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0811 loss: 1.0811 2022/09/05 14:56:03 - mmengine - INFO - Epoch(train) [37][340/940] lr: 1.0000e-02 eta: 11:01:21 time: 0.6908 data_time: 0.0499 memory: 24011 grad_norm: 4.9446 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0654 loss: 1.0654 2022/09/05 14:56:16 - mmengine - INFO - Epoch(train) [37][360/940] lr: 1.0000e-02 eta: 11:01:07 time: 0.6487 data_time: 0.0394 memory: 24011 grad_norm: 4.5508 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1529 loss: 1.1529 2022/09/05 14:56:29 - mmengine - INFO - Epoch(train) [37][380/940] lr: 1.0000e-02 eta: 11:00:54 time: 0.6477 data_time: 0.0523 memory: 24011 grad_norm: 5.7216 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0928 loss: 1.0928 2022/09/05 14:56:41 - mmengine - INFO - Epoch(train) [37][400/940] lr: 1.0000e-02 eta: 11:00:39 time: 0.6226 data_time: 0.0514 memory: 24011 grad_norm: 4.9486 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0511 loss: 1.0511 2022/09/05 14:56:54 - mmengine - INFO - Epoch(train) [37][420/940] lr: 1.0000e-02 eta: 11:00:25 time: 0.6371 data_time: 0.0441 memory: 24011 grad_norm: 5.4313 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0986 loss: 1.0986 2022/09/05 14:57:07 - mmengine - INFO - Epoch(train) [37][440/940] lr: 1.0000e-02 eta: 11:00:10 time: 0.6279 data_time: 0.0402 memory: 24011 grad_norm: 4.9459 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0725 loss: 1.0725 2022/09/05 14:57:20 - mmengine - INFO - Epoch(train) [37][460/940] lr: 1.0000e-02 eta: 10:59:57 time: 0.6765 data_time: 0.0380 memory: 24011 grad_norm: 4.7351 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0587 loss: 1.0587 2022/09/05 14:57:33 - mmengine - INFO - Epoch(train) [37][480/940] lr: 1.0000e-02 eta: 10:59:43 time: 0.6399 data_time: 0.0421 memory: 24011 grad_norm: 4.9627 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0895 loss: 1.0895 2022/09/05 14:57:47 - mmengine - INFO - Epoch(train) [37][500/940] lr: 1.0000e-02 eta: 10:59:31 time: 0.6828 data_time: 0.0422 memory: 24011 grad_norm: 4.6226 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9681 loss: 0.9681 2022/09/05 14:58:00 - mmengine - INFO - Epoch(train) [37][520/940] lr: 1.0000e-02 eta: 10:59:17 time: 0.6603 data_time: 0.0441 memory: 24011 grad_norm: 5.0990 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1707 loss: 1.1707 2022/09/05 14:58:13 - mmengine - INFO - Epoch(train) [37][540/940] lr: 1.0000e-02 eta: 10:59:04 time: 0.6510 data_time: 0.0433 memory: 24011 grad_norm: 5.0785 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0506 loss: 1.0506 2022/09/05 14:58:27 - mmengine - INFO - Epoch(train) [37][560/940] lr: 1.0000e-02 eta: 10:58:52 time: 0.6933 data_time: 0.0510 memory: 24011 grad_norm: 4.7169 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9719 loss: 0.9719 2022/09/05 14:58:40 - mmengine - INFO - Epoch(train) [37][580/940] lr: 1.0000e-02 eta: 10:58:37 time: 0.6394 data_time: 0.0358 memory: 24011 grad_norm: 5.0370 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1030 loss: 1.1030 2022/09/05 14:58:53 - mmengine - INFO - Epoch(train) [37][600/940] lr: 1.0000e-02 eta: 10:58:24 time: 0.6461 data_time: 0.0428 memory: 24011 grad_norm: 4.6789 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1854 loss: 1.1854 2022/09/05 14:59:06 - mmengine - INFO - Epoch(train) [37][620/940] lr: 1.0000e-02 eta: 10:58:11 time: 0.6889 data_time: 0.0548 memory: 24011 grad_norm: 5.5633 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1810 loss: 1.1810 2022/09/05 14:59:19 - mmengine - INFO - Epoch(train) [37][640/940] lr: 1.0000e-02 eta: 10:57:57 time: 0.6514 data_time: 0.0407 memory: 24011 grad_norm: 4.6784 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9291 loss: 0.9291 2022/09/05 14:59:33 - mmengine - INFO - Epoch(train) [37][660/940] lr: 1.0000e-02 eta: 10:57:44 time: 0.6670 data_time: 0.0462 memory: 24011 grad_norm: 4.9777 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1287 loss: 1.1287 2022/09/05 14:59:45 - mmengine - INFO - Epoch(train) [37][680/940] lr: 1.0000e-02 eta: 10:57:29 time: 0.5979 data_time: 0.0390 memory: 24011 grad_norm: 4.7969 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1688 loss: 1.1688 2022/09/05 14:59:57 - mmengine - INFO - Epoch(train) [37][700/940] lr: 1.0000e-02 eta: 10:57:15 time: 0.6420 data_time: 0.0496 memory: 24011 grad_norm: 4.5548 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1091 loss: 1.1091 2022/09/05 15:00:12 - mmengine - INFO - Epoch(train) [37][720/940] lr: 1.0000e-02 eta: 10:57:04 time: 0.7406 data_time: 0.0443 memory: 24011 grad_norm: 4.9315 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0699 loss: 1.0699 2022/09/05 15:00:25 - mmengine - INFO - Epoch(train) [37][740/940] lr: 1.0000e-02 eta: 10:56:50 time: 0.6245 data_time: 0.0423 memory: 24011 grad_norm: 4.9279 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0052 loss: 1.0052 2022/09/05 15:00:37 - mmengine - INFO - Epoch(train) [37][760/940] lr: 1.0000e-02 eta: 10:56:35 time: 0.6295 data_time: 0.0407 memory: 24011 grad_norm: 5.5064 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0612 loss: 1.0612 2022/09/05 15:00:50 - mmengine - INFO - Epoch(train) [37][780/940] lr: 1.0000e-02 eta: 10:56:21 time: 0.6322 data_time: 0.0428 memory: 24011 grad_norm: 5.0456 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1118 loss: 1.1118 2022/09/05 15:01:04 - mmengine - INFO - Epoch(train) [37][800/940] lr: 1.0000e-02 eta: 10:56:08 time: 0.6795 data_time: 0.0602 memory: 24011 grad_norm: 5.6782 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0917 loss: 1.0917 2022/09/05 15:01:16 - mmengine - INFO - Epoch(train) [37][820/940] lr: 1.0000e-02 eta: 10:55:54 time: 0.6315 data_time: 0.0327 memory: 24011 grad_norm: 4.7847 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2019 loss: 1.2019 2022/09/05 15:01:30 - mmengine - INFO - Epoch(train) [37][840/940] lr: 1.0000e-02 eta: 10:55:41 time: 0.6899 data_time: 0.0860 memory: 24011 grad_norm: 4.9659 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1941 loss: 1.1941 2022/09/05 15:01:43 - mmengine - INFO - Epoch(train) [37][860/940] lr: 1.0000e-02 eta: 10:55:28 time: 0.6429 data_time: 0.0422 memory: 24011 grad_norm: 5.1222 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0297 loss: 1.0297 2022/09/05 15:01:57 - mmengine - INFO - Epoch(train) [37][880/940] lr: 1.0000e-02 eta: 10:55:15 time: 0.6762 data_time: 0.1117 memory: 24011 grad_norm: 5.1645 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1026 loss: 1.1026 2022/09/05 15:02:10 - mmengine - INFO - Epoch(train) [37][900/940] lr: 1.0000e-02 eta: 10:55:02 time: 0.6657 data_time: 0.0881 memory: 24011 grad_norm: 5.3110 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0800 loss: 1.0800 2022/09/05 15:02:24 - mmengine - INFO - Epoch(train) [37][920/940] lr: 1.0000e-02 eta: 10:54:49 time: 0.6856 data_time: 0.1175 memory: 24011 grad_norm: 5.9110 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0799 loss: 1.0799 2022/09/05 15:02:35 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:02:35 - mmengine - INFO - Epoch(train) [37][940/940] lr: 1.0000e-02 eta: 10:54:32 time: 0.5569 data_time: 0.0485 memory: 24011 grad_norm: 5.8957 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.1283 loss: 1.1283 2022/09/05 15:02:49 - mmengine - INFO - Epoch(val) [37][20/78] eta: 0:00:40 time: 0.6946 data_time: 0.5361 memory: 3625 2022/09/05 15:02:58 - mmengine - INFO - Epoch(val) [37][40/78] eta: 0:00:17 time: 0.4615 data_time: 0.3044 memory: 3625 2022/09/05 15:03:11 - mmengine - INFO - Epoch(val) [37][60/78] eta: 0:00:11 time: 0.6619 data_time: 0.5015 memory: 3625 2022/09/05 15:03:21 - mmengine - INFO - Epoch(val) [37][78/78] acc/top1: 0.7012 acc/top5: 0.8945 acc/mean1: 0.7010 2022/09/05 15:03:40 - mmengine - INFO - Epoch(train) [38][20/940] lr: 1.0000e-02 eta: 10:54:27 time: 0.9044 data_time: 0.2324 memory: 24011 grad_norm: 5.6749 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0802 loss: 1.0802 2022/09/05 15:03:53 - mmengine - INFO - Epoch(train) [38][40/940] lr: 1.0000e-02 eta: 10:54:14 time: 0.6606 data_time: 0.0400 memory: 24011 grad_norm: 5.1848 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0125 loss: 1.0125 2022/09/05 15:04:06 - mmengine - INFO - Epoch(train) [38][60/940] lr: 1.0000e-02 eta: 10:54:01 time: 0.6662 data_time: 0.0408 memory: 24011 grad_norm: 5.3189 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1069 loss: 1.1069 2022/09/05 15:04:19 - mmengine - INFO - Epoch(train) [38][80/940] lr: 1.0000e-02 eta: 10:53:46 time: 0.6260 data_time: 0.0369 memory: 24011 grad_norm: 5.6614 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1059 loss: 1.1059 2022/09/05 15:04:32 - mmengine - INFO - Epoch(train) [38][100/940] lr: 1.0000e-02 eta: 10:53:33 time: 0.6840 data_time: 0.0430 memory: 24011 grad_norm: 4.9012 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1306 loss: 1.1306 2022/09/05 15:04:45 - mmengine - INFO - Epoch(train) [38][120/940] lr: 1.0000e-02 eta: 10:53:19 time: 0.6313 data_time: 0.0399 memory: 24011 grad_norm: 5.0431 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0896 loss: 1.0896 2022/09/05 15:04:59 - mmengine - INFO - Epoch(train) [38][140/940] lr: 1.0000e-02 eta: 10:53:07 time: 0.6960 data_time: 0.0419 memory: 24011 grad_norm: 5.0149 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0889 loss: 1.0889 2022/09/05 15:05:12 - mmengine - INFO - Epoch(train) [38][160/940] lr: 1.0000e-02 eta: 10:52:53 time: 0.6413 data_time: 0.0417 memory: 24011 grad_norm: 4.8078 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0034 loss: 1.0034 2022/09/05 15:05:25 - mmengine - INFO - Epoch(train) [38][180/940] lr: 1.0000e-02 eta: 10:52:40 time: 0.6636 data_time: 0.0394 memory: 24011 grad_norm: 4.7796 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0267 loss: 1.0267 2022/09/05 15:05:37 - mmengine - INFO - Epoch(train) [38][200/940] lr: 1.0000e-02 eta: 10:52:25 time: 0.6209 data_time: 0.0405 memory: 24011 grad_norm: 4.6814 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0176 loss: 1.0176 2022/09/05 15:05:50 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:05:50 - mmengine - INFO - Epoch(train) [38][220/940] lr: 1.0000e-02 eta: 10:52:10 time: 0.6183 data_time: 0.0445 memory: 24011 grad_norm: 4.7369 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.9921 loss: 0.9921 2022/09/05 15:06:02 - mmengine - INFO - Epoch(train) [38][240/940] lr: 1.0000e-02 eta: 10:51:56 time: 0.6288 data_time: 0.0373 memory: 24011 grad_norm: 4.9646 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0597 loss: 1.0597 2022/09/05 15:06:16 - mmengine - INFO - Epoch(train) [38][260/940] lr: 1.0000e-02 eta: 10:51:43 time: 0.6672 data_time: 0.0377 memory: 24011 grad_norm: 4.7136 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9689 loss: 0.9689 2022/09/05 15:06:28 - mmengine - INFO - Epoch(train) [38][280/940] lr: 1.0000e-02 eta: 10:51:28 time: 0.6332 data_time: 0.0392 memory: 24011 grad_norm: 4.4847 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0214 loss: 1.0214 2022/09/05 15:06:43 - mmengine - INFO - Epoch(train) [38][300/940] lr: 1.0000e-02 eta: 10:51:17 time: 0.7142 data_time: 0.0374 memory: 24011 grad_norm: 4.5825 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0094 loss: 1.0094 2022/09/05 15:06:55 - mmengine - INFO - Epoch(train) [38][320/940] lr: 1.0000e-02 eta: 10:51:02 time: 0.6080 data_time: 0.0418 memory: 24011 grad_norm: 4.8149 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9952 loss: 0.9952 2022/09/05 15:07:08 - mmengine - INFO - Epoch(train) [38][340/940] lr: 1.0000e-02 eta: 10:50:48 time: 0.6489 data_time: 0.0445 memory: 24011 grad_norm: 4.8619 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.0219 loss: 1.0219 2022/09/05 15:07:20 - mmengine - INFO - Epoch(train) [38][360/940] lr: 1.0000e-02 eta: 10:50:33 time: 0.6053 data_time: 0.0428 memory: 24011 grad_norm: 5.8433 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9513 loss: 0.9513 2022/09/05 15:07:34 - mmengine - INFO - Epoch(train) [38][380/940] lr: 1.0000e-02 eta: 10:50:21 time: 0.6978 data_time: 0.0427 memory: 24011 grad_norm: 5.2571 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0922 loss: 1.0922 2022/09/05 15:07:47 - mmengine - INFO - Epoch(train) [38][400/940] lr: 1.0000e-02 eta: 10:50:07 time: 0.6411 data_time: 0.0382 memory: 24011 grad_norm: 4.8617 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1586 loss: 1.1586 2022/09/05 15:08:00 - mmengine - INFO - Epoch(train) [38][420/940] lr: 1.0000e-02 eta: 10:49:53 time: 0.6498 data_time: 0.0490 memory: 24011 grad_norm: 4.8410 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.9909 loss: 0.9909 2022/09/05 15:08:12 - mmengine - INFO - Epoch(train) [38][440/940] lr: 1.0000e-02 eta: 10:49:38 time: 0.6205 data_time: 0.0433 memory: 24011 grad_norm: 4.9957 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0282 loss: 1.0282 2022/09/05 15:08:25 - mmengine - INFO - Epoch(train) [38][460/940] lr: 1.0000e-02 eta: 10:49:25 time: 0.6700 data_time: 0.0431 memory: 24011 grad_norm: 4.8521 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9383 loss: 0.9383 2022/09/05 15:08:38 - mmengine - INFO - Epoch(train) [38][480/940] lr: 1.0000e-02 eta: 10:49:11 time: 0.6392 data_time: 0.0380 memory: 24011 grad_norm: 4.7573 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0378 loss: 1.0378 2022/09/05 15:08:51 - mmengine - INFO - Epoch(train) [38][500/940] lr: 1.0000e-02 eta: 10:48:57 time: 0.6232 data_time: 0.0308 memory: 24011 grad_norm: 4.9370 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.0873 loss: 1.0873 2022/09/05 15:09:04 - mmengine - INFO - Epoch(train) [38][520/940] lr: 1.0000e-02 eta: 10:48:44 time: 0.6699 data_time: 0.0399 memory: 24011 grad_norm: 5.1304 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0634 loss: 1.0634 2022/09/05 15:09:17 - mmengine - INFO - Epoch(train) [38][540/940] lr: 1.0000e-02 eta: 10:48:30 time: 0.6538 data_time: 0.0358 memory: 24011 grad_norm: 5.7001 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0540 loss: 1.0540 2022/09/05 15:09:31 - mmengine - INFO - Epoch(train) [38][560/940] lr: 1.0000e-02 eta: 10:48:17 time: 0.6746 data_time: 0.0359 memory: 24011 grad_norm: 5.1378 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1831 loss: 1.1831 2022/09/05 15:09:44 - mmengine - INFO - Epoch(train) [38][580/940] lr: 1.0000e-02 eta: 10:48:03 time: 0.6496 data_time: 0.0359 memory: 24011 grad_norm: 5.1557 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2342 loss: 1.2342 2022/09/05 15:09:57 - mmengine - INFO - Epoch(train) [38][600/940] lr: 1.0000e-02 eta: 10:47:50 time: 0.6541 data_time: 0.0328 memory: 24011 grad_norm: 4.7778 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0664 loss: 1.0664 2022/09/05 15:10:09 - mmengine - INFO - Epoch(train) [38][620/940] lr: 1.0000e-02 eta: 10:47:35 time: 0.6304 data_time: 0.0552 memory: 24011 grad_norm: 4.7938 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0117 loss: 1.0117 2022/09/05 15:10:22 - mmengine - INFO - Epoch(train) [38][640/940] lr: 1.0000e-02 eta: 10:47:21 time: 0.6136 data_time: 0.0420 memory: 24011 grad_norm: 4.6950 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0709 loss: 1.0709 2022/09/05 15:10:34 - mmengine - INFO - Epoch(train) [38][660/940] lr: 1.0000e-02 eta: 10:47:06 time: 0.6193 data_time: 0.0365 memory: 24011 grad_norm: 4.7671 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0088 loss: 1.0088 2022/09/05 15:10:47 - mmengine - INFO - Epoch(train) [38][680/940] lr: 1.0000e-02 eta: 10:46:52 time: 0.6535 data_time: 0.0385 memory: 24011 grad_norm: 5.3224 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1023 loss: 1.1023 2022/09/05 15:11:00 - mmengine - INFO - Epoch(train) [38][700/940] lr: 1.0000e-02 eta: 10:46:38 time: 0.6355 data_time: 0.0462 memory: 24011 grad_norm: 4.9098 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1417 loss: 1.1417 2022/09/05 15:11:13 - mmengine - INFO - Epoch(train) [38][720/940] lr: 1.0000e-02 eta: 10:46:25 time: 0.6545 data_time: 0.0401 memory: 24011 grad_norm: 4.7244 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1217 loss: 1.1217 2022/09/05 15:11:26 - mmengine - INFO - Epoch(train) [38][740/940] lr: 1.0000e-02 eta: 10:46:11 time: 0.6494 data_time: 0.0356 memory: 24011 grad_norm: 5.7164 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1244 loss: 1.1244 2022/09/05 15:11:41 - mmengine - INFO - Epoch(train) [38][760/940] lr: 1.0000e-02 eta: 10:46:00 time: 0.7323 data_time: 0.0389 memory: 24011 grad_norm: 5.0597 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1812 loss: 1.1812 2022/09/05 15:11:53 - mmengine - INFO - Epoch(train) [38][780/940] lr: 1.0000e-02 eta: 10:45:45 time: 0.6236 data_time: 0.0438 memory: 24011 grad_norm: 5.2083 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0627 loss: 1.0627 2022/09/05 15:12:06 - mmengine - INFO - Epoch(train) [38][800/940] lr: 1.0000e-02 eta: 10:45:31 time: 0.6414 data_time: 0.0412 memory: 24011 grad_norm: 5.1905 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1215 loss: 1.1215 2022/09/05 15:12:18 - mmengine - INFO - Epoch(train) [38][820/940] lr: 1.0000e-02 eta: 10:45:16 time: 0.6082 data_time: 0.0493 memory: 24011 grad_norm: 6.5840 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1605 loss: 1.1605 2022/09/05 15:12:32 - mmengine - INFO - Epoch(train) [38][840/940] lr: 1.0000e-02 eta: 10:45:03 time: 0.6724 data_time: 0.0423 memory: 24011 grad_norm: 5.1712 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1051 loss: 1.1051 2022/09/05 15:12:44 - mmengine - INFO - Epoch(train) [38][860/940] lr: 1.0000e-02 eta: 10:44:49 time: 0.6289 data_time: 0.0446 memory: 24011 grad_norm: 4.8473 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1523 loss: 1.1523 2022/09/05 15:12:58 - mmengine - INFO - Epoch(train) [38][880/940] lr: 1.0000e-02 eta: 10:44:36 time: 0.6783 data_time: 0.0384 memory: 24011 grad_norm: 5.0503 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0587 loss: 1.0587 2022/09/05 15:13:10 - mmengine - INFO - Epoch(train) [38][900/940] lr: 1.0000e-02 eta: 10:44:22 time: 0.6337 data_time: 0.0443 memory: 24011 grad_norm: 4.8954 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0009 loss: 1.0009 2022/09/05 15:13:24 - mmengine - INFO - Epoch(train) [38][920/940] lr: 1.0000e-02 eta: 10:44:09 time: 0.6774 data_time: 0.0428 memory: 24011 grad_norm: 4.6564 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0414 loss: 1.0414 2022/09/05 15:13:35 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:13:35 - mmengine - INFO - Epoch(train) [38][940/940] lr: 1.0000e-02 eta: 10:43:52 time: 0.5471 data_time: 0.0303 memory: 24011 grad_norm: 4.7433 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.9856 loss: 0.9856 2022/09/05 15:13:49 - mmengine - INFO - Epoch(val) [38][20/78] eta: 0:00:40 time: 0.6899 data_time: 0.5296 memory: 3625 2022/09/05 15:13:58 - mmengine - INFO - Epoch(val) [38][40/78] eta: 0:00:18 time: 0.4837 data_time: 0.3202 memory: 3625 2022/09/05 15:14:12 - mmengine - INFO - Epoch(val) [38][60/78] eta: 0:00:11 time: 0.6572 data_time: 0.4947 memory: 3625 2022/09/05 15:14:21 - mmengine - INFO - Epoch(val) [38][78/78] acc/top1: 0.7080 acc/top5: 0.8942 acc/mean1: 0.7077 2022/09/05 15:14:41 - mmengine - INFO - Epoch(train) [39][20/940] lr: 1.0000e-02 eta: 10:43:48 time: 0.9439 data_time: 0.2884 memory: 24011 grad_norm: 4.8544 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9216 loss: 0.9216 2022/09/05 15:14:53 - mmengine - INFO - Epoch(train) [39][40/940] lr: 1.0000e-02 eta: 10:43:34 time: 0.6491 data_time: 0.0354 memory: 24011 grad_norm: 5.1448 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0825 loss: 1.0825 2022/09/05 15:15:06 - mmengine - INFO - Epoch(train) [39][60/940] lr: 1.0000e-02 eta: 10:43:21 time: 0.6488 data_time: 0.0397 memory: 24011 grad_norm: 5.2031 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0602 loss: 1.0602 2022/09/05 15:15:19 - mmengine - INFO - Epoch(train) [39][80/940] lr: 1.0000e-02 eta: 10:43:06 time: 0.6342 data_time: 0.0418 memory: 24011 grad_norm: 5.9625 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0809 loss: 1.0809 2022/09/05 15:15:33 - mmengine - INFO - Epoch(train) [39][100/940] lr: 1.0000e-02 eta: 10:42:54 time: 0.6886 data_time: 0.0397 memory: 24011 grad_norm: 5.1745 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0485 loss: 1.0485 2022/09/05 15:15:46 - mmengine - INFO - Epoch(train) [39][120/940] lr: 1.0000e-02 eta: 10:42:40 time: 0.6338 data_time: 0.0410 memory: 24011 grad_norm: 4.8387 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9981 loss: 0.9981 2022/09/05 15:15:58 - mmengine - INFO - Epoch(train) [39][140/940] lr: 1.0000e-02 eta: 10:42:25 time: 0.6243 data_time: 0.0430 memory: 24011 grad_norm: 5.6372 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0675 loss: 1.0675 2022/09/05 15:16:12 - mmengine - INFO - Epoch(train) [39][160/940] lr: 1.0000e-02 eta: 10:42:12 time: 0.6716 data_time: 0.0448 memory: 24011 grad_norm: 5.0639 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9676 loss: 0.9676 2022/09/05 15:16:26 - mmengine - INFO - Epoch(train) [39][180/940] lr: 1.0000e-02 eta: 10:42:00 time: 0.7049 data_time: 0.0405 memory: 24011 grad_norm: 4.7605 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9908 loss: 0.9908 2022/09/05 15:16:38 - mmengine - INFO - Epoch(train) [39][200/940] lr: 1.0000e-02 eta: 10:41:45 time: 0.6104 data_time: 0.0492 memory: 24011 grad_norm: 5.0822 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0828 loss: 1.0828 2022/09/05 15:16:50 - mmengine - INFO - Epoch(train) [39][220/940] lr: 1.0000e-02 eta: 10:41:31 time: 0.6141 data_time: 0.0618 memory: 24011 grad_norm: 5.1507 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0286 loss: 1.0286 2022/09/05 15:17:03 - mmengine - INFO - Epoch(train) [39][240/940] lr: 1.0000e-02 eta: 10:41:17 time: 0.6355 data_time: 0.0404 memory: 24011 grad_norm: 4.6760 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0136 loss: 1.0136 2022/09/05 15:17:16 - mmengine - INFO - Epoch(train) [39][260/940] lr: 1.0000e-02 eta: 10:41:04 time: 0.6725 data_time: 0.0457 memory: 24011 grad_norm: 4.7285 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0573 loss: 1.0573 2022/09/05 15:17:30 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:17:30 - mmengine - INFO - Epoch(train) [39][280/940] lr: 1.0000e-02 eta: 10:40:51 time: 0.6829 data_time: 0.0449 memory: 24011 grad_norm: 4.7783 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0508 loss: 1.0508 2022/09/05 15:17:42 - mmengine - INFO - Epoch(train) [39][300/940] lr: 1.0000e-02 eta: 10:40:36 time: 0.6195 data_time: 0.0391 memory: 24011 grad_norm: 5.4144 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9142 loss: 0.9142 2022/09/05 15:17:54 - mmengine - INFO - Epoch(train) [39][320/940] lr: 1.0000e-02 eta: 10:40:21 time: 0.5978 data_time: 0.0394 memory: 24011 grad_norm: 5.9896 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0215 loss: 1.0215 2022/09/05 15:18:07 - mmengine - INFO - Epoch(train) [39][340/940] lr: 1.0000e-02 eta: 10:40:06 time: 0.6242 data_time: 0.0443 memory: 24011 grad_norm: 4.9303 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9996 loss: 0.9996 2022/09/05 15:18:20 - mmengine - INFO - Epoch(train) [39][360/940] lr: 1.0000e-02 eta: 10:39:53 time: 0.6421 data_time: 0.0581 memory: 24011 grad_norm: 5.0661 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0349 loss: 1.0349 2022/09/05 15:18:33 - mmengine - INFO - Epoch(train) [39][380/940] lr: 1.0000e-02 eta: 10:39:40 time: 0.6760 data_time: 0.0355 memory: 24011 grad_norm: 5.2569 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0810 loss: 1.0810 2022/09/05 15:18:46 - mmengine - INFO - Epoch(train) [39][400/940] lr: 1.0000e-02 eta: 10:39:26 time: 0.6371 data_time: 0.0451 memory: 24011 grad_norm: 4.6775 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1197 loss: 1.1197 2022/09/05 15:18:59 - mmengine - INFO - Epoch(train) [39][420/940] lr: 1.0000e-02 eta: 10:39:12 time: 0.6463 data_time: 0.0409 memory: 24011 grad_norm: 4.7761 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1698 loss: 1.1698 2022/09/05 15:19:13 - mmengine - INFO - Epoch(train) [39][440/940] lr: 1.0000e-02 eta: 10:39:00 time: 0.7092 data_time: 0.0387 memory: 24011 grad_norm: 4.8897 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9600 loss: 0.9600 2022/09/05 15:19:27 - mmengine - INFO - Epoch(train) [39][460/940] lr: 1.0000e-02 eta: 10:38:47 time: 0.6754 data_time: 0.0494 memory: 24011 grad_norm: 4.9694 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1325 loss: 1.1325 2022/09/05 15:19:39 - mmengine - INFO - Epoch(train) [39][480/940] lr: 1.0000e-02 eta: 10:38:33 time: 0.6358 data_time: 0.0425 memory: 24011 grad_norm: 4.8400 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1166 loss: 1.1166 2022/09/05 15:19:52 - mmengine - INFO - Epoch(train) [39][500/940] lr: 1.0000e-02 eta: 10:38:19 time: 0.6368 data_time: 0.0460 memory: 24011 grad_norm: 4.5052 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9572 loss: 0.9572 2022/09/05 15:20:05 - mmengine - INFO - Epoch(train) [39][520/940] lr: 1.0000e-02 eta: 10:38:05 time: 0.6523 data_time: 0.0407 memory: 24011 grad_norm: 4.6953 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9910 loss: 0.9910 2022/09/05 15:20:18 - mmengine - INFO - Epoch(train) [39][540/940] lr: 1.0000e-02 eta: 10:37:51 time: 0.6421 data_time: 0.0425 memory: 24011 grad_norm: 4.5403 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1183 loss: 1.1183 2022/09/05 15:20:31 - mmengine - INFO - Epoch(train) [39][560/940] lr: 1.0000e-02 eta: 10:37:38 time: 0.6633 data_time: 0.0443 memory: 24011 grad_norm: 4.5909 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0523 loss: 1.0523 2022/09/05 15:20:44 - mmengine - INFO - Epoch(train) [39][580/940] lr: 1.0000e-02 eta: 10:37:24 time: 0.6348 data_time: 0.0449 memory: 24011 grad_norm: 4.6047 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0655 loss: 1.0655 2022/09/05 15:20:57 - mmengine - INFO - Epoch(train) [39][600/940] lr: 1.0000e-02 eta: 10:37:11 time: 0.6588 data_time: 0.0388 memory: 24011 grad_norm: 4.7192 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0389 loss: 1.0389 2022/09/05 15:21:10 - mmengine - INFO - Epoch(train) [39][620/940] lr: 1.0000e-02 eta: 10:36:56 time: 0.6211 data_time: 0.0456 memory: 24011 grad_norm: 4.6770 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0886 loss: 1.0886 2022/09/05 15:21:23 - mmengine - INFO - Epoch(train) [39][640/940] lr: 1.0000e-02 eta: 10:36:44 time: 0.6925 data_time: 0.0327 memory: 24011 grad_norm: 4.4820 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9396 loss: 0.9396 2022/09/05 15:21:36 - mmengine - INFO - Epoch(train) [39][660/940] lr: 1.0000e-02 eta: 10:36:29 time: 0.6239 data_time: 0.0486 memory: 24011 grad_norm: 5.0477 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9994 loss: 0.9994 2022/09/05 15:21:49 - mmengine - INFO - Epoch(train) [39][680/940] lr: 1.0000e-02 eta: 10:36:16 time: 0.6520 data_time: 0.0430 memory: 24011 grad_norm: 5.0089 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.9923 loss: 0.9923 2022/09/05 15:22:02 - mmengine - INFO - Epoch(train) [39][700/940] lr: 1.0000e-02 eta: 10:36:02 time: 0.6576 data_time: 0.0485 memory: 24011 grad_norm: 4.5249 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0668 loss: 1.0668 2022/09/05 15:22:14 - mmengine - INFO - Epoch(train) [39][720/940] lr: 1.0000e-02 eta: 10:35:47 time: 0.6099 data_time: 0.0412 memory: 24011 grad_norm: 4.8137 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0971 loss: 1.0971 2022/09/05 15:22:27 - mmengine - INFO - Epoch(train) [39][740/940] lr: 1.0000e-02 eta: 10:35:34 time: 0.6544 data_time: 0.0402 memory: 24011 grad_norm: 4.6671 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0532 loss: 1.0532 2022/09/05 15:22:40 - mmengine - INFO - Epoch(train) [39][760/940] lr: 1.0000e-02 eta: 10:35:20 time: 0.6419 data_time: 0.0433 memory: 24011 grad_norm: 4.7679 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1535 loss: 1.1535 2022/09/05 15:22:53 - mmengine - INFO - Epoch(train) [39][780/940] lr: 1.0000e-02 eta: 10:35:05 time: 0.6194 data_time: 0.0373 memory: 24011 grad_norm: 4.5886 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9458 loss: 0.9458 2022/09/05 15:23:06 - mmengine - INFO - Epoch(train) [39][800/940] lr: 1.0000e-02 eta: 10:34:52 time: 0.6508 data_time: 0.0403 memory: 24011 grad_norm: 5.1293 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1572 loss: 1.1572 2022/09/05 15:23:19 - mmengine - INFO - Epoch(train) [39][820/940] lr: 1.0000e-02 eta: 10:34:39 time: 0.6750 data_time: 0.0392 memory: 24011 grad_norm: 5.1450 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0789 loss: 1.0789 2022/09/05 15:23:32 - mmengine - INFO - Epoch(train) [39][840/940] lr: 1.0000e-02 eta: 10:34:24 time: 0.6104 data_time: 0.0360 memory: 24011 grad_norm: 4.5959 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0124 loss: 1.0124 2022/09/05 15:23:44 - mmengine - INFO - Epoch(train) [39][860/940] lr: 1.0000e-02 eta: 10:34:10 time: 0.6337 data_time: 0.0506 memory: 24011 grad_norm: 4.9964 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9910 loss: 0.9910 2022/09/05 15:23:57 - mmengine - INFO - Epoch(train) [39][880/940] lr: 1.0000e-02 eta: 10:33:57 time: 0.6660 data_time: 0.0370 memory: 24011 grad_norm: 4.6761 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0338 loss: 1.0338 2022/09/05 15:24:10 - mmengine - INFO - Epoch(train) [39][900/940] lr: 1.0000e-02 eta: 10:33:43 time: 0.6403 data_time: 0.0373 memory: 24011 grad_norm: 5.6346 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.9973 loss: 0.9973 2022/09/05 15:24:24 - mmengine - INFO - Epoch(train) [39][920/940] lr: 1.0000e-02 eta: 10:33:30 time: 0.6757 data_time: 0.0357 memory: 24011 grad_norm: 5.2612 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1978 loss: 1.1978 2022/09/05 15:24:35 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:24:35 - mmengine - INFO - Epoch(train) [39][940/940] lr: 1.0000e-02 eta: 10:33:14 time: 0.5779 data_time: 0.0252 memory: 24011 grad_norm: 5.4992 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0086 loss: 1.0086 2022/09/05 15:24:35 - mmengine - INFO - Saving checkpoint at 39 epochs 2022/09/05 15:24:54 - mmengine - INFO - Epoch(val) [39][20/78] eta: 0:00:40 time: 0.6936 data_time: 0.5372 memory: 3625 2022/09/05 15:25:04 - mmengine - INFO - Epoch(val) [39][40/78] eta: 0:00:18 time: 0.4883 data_time: 0.3328 memory: 3625 2022/09/05 15:25:17 - mmengine - INFO - Epoch(val) [39][60/78] eta: 0:00:11 time: 0.6205 data_time: 0.4648 memory: 3625 2022/09/05 15:25:26 - mmengine - INFO - Epoch(val) [39][78/78] acc/top1: 0.7069 acc/top5: 0.8902 acc/mean1: 0.7067 2022/09/05 15:25:44 - mmengine - INFO - Epoch(train) [40][20/940] lr: 1.0000e-02 eta: 10:33:08 time: 0.9006 data_time: 0.2730 memory: 24011 grad_norm: 4.8924 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1346 loss: 1.1346 2022/09/05 15:25:57 - mmengine - INFO - Epoch(train) [40][40/940] lr: 1.0000e-02 eta: 10:32:54 time: 0.6431 data_time: 0.0347 memory: 24011 grad_norm: 4.6477 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0952 loss: 1.0952 2022/09/05 15:26:10 - mmengine - INFO - Epoch(train) [40][60/940] lr: 1.0000e-02 eta: 10:32:41 time: 0.6552 data_time: 0.0425 memory: 24011 grad_norm: 5.0278 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0170 loss: 1.0170 2022/09/05 15:26:22 - mmengine - INFO - Epoch(train) [40][80/940] lr: 1.0000e-02 eta: 10:32:26 time: 0.6088 data_time: 0.0343 memory: 24011 grad_norm: 4.8934 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0869 loss: 1.0869 2022/09/05 15:26:36 - mmengine - INFO - Epoch(train) [40][100/940] lr: 1.0000e-02 eta: 10:32:13 time: 0.6848 data_time: 0.0994 memory: 24011 grad_norm: 4.8257 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9295 loss: 0.9295 2022/09/05 15:26:49 - mmengine - INFO - Epoch(train) [40][120/940] lr: 1.0000e-02 eta: 10:31:59 time: 0.6432 data_time: 0.0317 memory: 24011 grad_norm: 4.8953 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0173 loss: 1.0173 2022/09/05 15:27:02 - mmengine - INFO - Epoch(train) [40][140/940] lr: 1.0000e-02 eta: 10:31:46 time: 0.6599 data_time: 0.0377 memory: 24011 grad_norm: 4.7228 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1637 loss: 1.1637 2022/09/05 15:27:15 - mmengine - INFO - Epoch(train) [40][160/940] lr: 1.0000e-02 eta: 10:31:33 time: 0.6588 data_time: 0.0420 memory: 24011 grad_norm: 4.9624 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9522 loss: 0.9522 2022/09/05 15:27:28 - mmengine - INFO - Epoch(train) [40][180/940] lr: 1.0000e-02 eta: 10:31:19 time: 0.6549 data_time: 0.0392 memory: 24011 grad_norm: 5.6029 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.0533 loss: 1.0533 2022/09/05 15:27:41 - mmengine - INFO - Epoch(train) [40][200/940] lr: 1.0000e-02 eta: 10:31:05 time: 0.6320 data_time: 0.0350 memory: 24011 grad_norm: 5.0199 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0557 loss: 1.0557 2022/09/05 15:27:54 - mmengine - INFO - Epoch(train) [40][220/940] lr: 1.0000e-02 eta: 10:30:51 time: 0.6561 data_time: 0.0445 memory: 24011 grad_norm: 5.3136 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0260 loss: 1.0260 2022/09/05 15:28:06 - mmengine - INFO - Epoch(train) [40][240/940] lr: 1.0000e-02 eta: 10:30:37 time: 0.6126 data_time: 0.0438 memory: 24011 grad_norm: 4.8745 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0570 loss: 1.0570 2022/09/05 15:28:20 - mmengine - INFO - Epoch(train) [40][260/940] lr: 1.0000e-02 eta: 10:30:24 time: 0.6770 data_time: 0.0639 memory: 24011 grad_norm: 5.3706 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0598 loss: 1.0598 2022/09/05 15:28:32 - mmengine - INFO - Epoch(train) [40][280/940] lr: 1.0000e-02 eta: 10:30:09 time: 0.6078 data_time: 0.0311 memory: 24011 grad_norm: 4.9466 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9707 loss: 0.9707 2022/09/05 15:28:46 - mmengine - INFO - Epoch(train) [40][300/940] lr: 1.0000e-02 eta: 10:29:57 time: 0.7147 data_time: 0.0399 memory: 24011 grad_norm: 5.0673 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0698 loss: 1.0698 2022/09/05 15:28:58 - mmengine - INFO - Epoch(train) [40][320/940] lr: 1.0000e-02 eta: 10:29:42 time: 0.6130 data_time: 0.0352 memory: 24011 grad_norm: 5.1669 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0418 loss: 1.0418 2022/09/05 15:29:12 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:29:12 - mmengine - INFO - Epoch(train) [40][340/940] lr: 1.0000e-02 eta: 10:29:30 time: 0.6813 data_time: 0.0404 memory: 24011 grad_norm: 5.0040 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1359 loss: 1.1359 2022/09/05 15:29:25 - mmengine - INFO - Epoch(train) [40][360/940] lr: 1.0000e-02 eta: 10:29:16 time: 0.6588 data_time: 0.0386 memory: 24011 grad_norm: 5.1181 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0606 loss: 1.0606 2022/09/05 15:29:37 - mmengine - INFO - Epoch(train) [40][380/940] lr: 1.0000e-02 eta: 10:29:02 time: 0.6157 data_time: 0.0422 memory: 24011 grad_norm: 5.1627 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0682 loss: 1.0682 2022/09/05 15:29:51 - mmengine - INFO - Epoch(train) [40][400/940] lr: 1.0000e-02 eta: 10:28:49 time: 0.6764 data_time: 0.0402 memory: 24011 grad_norm: 5.0727 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0749 loss: 1.0749 2022/09/05 15:30:04 - mmengine - INFO - Epoch(train) [40][420/940] lr: 1.0000e-02 eta: 10:28:36 time: 0.6702 data_time: 0.0355 memory: 24011 grad_norm: 5.0946 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9472 loss: 0.9472 2022/09/05 15:30:16 - mmengine - INFO - Epoch(train) [40][440/940] lr: 1.0000e-02 eta: 10:28:21 time: 0.5990 data_time: 0.0387 memory: 24011 grad_norm: 4.8949 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1005 loss: 1.1005 2022/09/05 15:30:29 - mmengine - INFO - Epoch(train) [40][460/940] lr: 1.0000e-02 eta: 10:28:07 time: 0.6358 data_time: 0.0417 memory: 24011 grad_norm: 4.7633 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0691 loss: 1.0691 2022/09/05 15:30:42 - mmengine - INFO - Epoch(train) [40][480/940] lr: 1.0000e-02 eta: 10:27:53 time: 0.6383 data_time: 0.0406 memory: 24011 grad_norm: 5.4183 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.9488 loss: 0.9488 2022/09/05 15:30:56 - mmengine - INFO - Epoch(train) [40][500/940] lr: 1.0000e-02 eta: 10:27:40 time: 0.6873 data_time: 0.0488 memory: 24011 grad_norm: 5.0335 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0026 loss: 1.0026 2022/09/05 15:31:08 - mmengine - INFO - Epoch(train) [40][520/940] lr: 1.0000e-02 eta: 10:27:26 time: 0.6238 data_time: 0.0374 memory: 24011 grad_norm: 4.8293 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1225 loss: 1.1225 2022/09/05 15:31:22 - mmengine - INFO - Epoch(train) [40][540/940] lr: 1.0000e-02 eta: 10:27:13 time: 0.6968 data_time: 0.0405 memory: 24011 grad_norm: 4.6751 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9664 loss: 0.9664 2022/09/05 15:31:34 - mmengine - INFO - Epoch(train) [40][560/940] lr: 1.0000e-02 eta: 10:26:59 time: 0.6143 data_time: 0.0337 memory: 24011 grad_norm: 5.1449 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0588 loss: 1.0588 2022/09/05 15:31:48 - mmengine - INFO - Epoch(train) [40][580/940] lr: 1.0000e-02 eta: 10:26:45 time: 0.6522 data_time: 0.0414 memory: 24011 grad_norm: 4.6848 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9820 loss: 0.9820 2022/09/05 15:32:01 - mmengine - INFO - Epoch(train) [40][600/940] lr: 1.0000e-02 eta: 10:26:32 time: 0.6637 data_time: 0.0507 memory: 24011 grad_norm: 4.7682 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9417 loss: 0.9417 2022/09/05 15:32:13 - mmengine - INFO - Epoch(train) [40][620/940] lr: 1.0000e-02 eta: 10:26:18 time: 0.6272 data_time: 0.0423 memory: 24011 grad_norm: 4.9758 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.0646 loss: 1.0646 2022/09/05 15:32:26 - mmengine - INFO - Epoch(train) [40][640/940] lr: 1.0000e-02 eta: 10:26:03 time: 0.6161 data_time: 0.0415 memory: 24011 grad_norm: 7.6414 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0445 loss: 1.0445 2022/09/05 15:32:39 - mmengine - INFO - Epoch(train) [40][660/940] lr: 1.0000e-02 eta: 10:25:50 time: 0.6617 data_time: 0.0347 memory: 24011 grad_norm: 5.6351 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1116 loss: 1.1116 2022/09/05 15:32:52 - mmengine - INFO - Epoch(train) [40][680/940] lr: 1.0000e-02 eta: 10:25:37 time: 0.6694 data_time: 0.0441 memory: 24011 grad_norm: 5.0150 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1998 loss: 1.1998 2022/09/05 15:33:05 - mmengine - INFO - Epoch(train) [40][700/940] lr: 1.0000e-02 eta: 10:25:23 time: 0.6488 data_time: 0.0295 memory: 24011 grad_norm: 5.1361 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0824 loss: 1.0824 2022/09/05 15:33:18 - mmengine - INFO - Epoch(train) [40][720/940] lr: 1.0000e-02 eta: 10:25:09 time: 0.6496 data_time: 0.0631 memory: 24011 grad_norm: 4.8571 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1703 loss: 1.1703 2022/09/05 15:33:31 - mmengine - INFO - Epoch(train) [40][740/940] lr: 1.0000e-02 eta: 10:24:56 time: 0.6493 data_time: 0.0549 memory: 24011 grad_norm: 5.0945 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9995 loss: 0.9995 2022/09/05 15:33:45 - mmengine - INFO - Epoch(train) [40][760/940] lr: 1.0000e-02 eta: 10:24:43 time: 0.6681 data_time: 0.0454 memory: 24011 grad_norm: 4.7183 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.9951 loss: 0.9951 2022/09/05 15:33:57 - mmengine - INFO - Epoch(train) [40][780/940] lr: 1.0000e-02 eta: 10:24:28 time: 0.6035 data_time: 0.0332 memory: 24011 grad_norm: 4.9804 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0374 loss: 1.0374 2022/09/05 15:34:10 - mmengine - INFO - Epoch(train) [40][800/940] lr: 1.0000e-02 eta: 10:24:14 time: 0.6596 data_time: 0.0361 memory: 24011 grad_norm: 5.4861 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0477 loss: 1.0477 2022/09/05 15:34:22 - mmengine - INFO - Epoch(train) [40][820/940] lr: 1.0000e-02 eta: 10:24:00 time: 0.6330 data_time: 0.0369 memory: 24011 grad_norm: 5.4890 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0605 loss: 1.0605 2022/09/05 15:34:36 - mmengine - INFO - Epoch(train) [40][840/940] lr: 1.0000e-02 eta: 10:23:47 time: 0.6698 data_time: 0.0406 memory: 24011 grad_norm: 5.0544 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0640 loss: 1.0640 2022/09/05 15:34:49 - mmengine - INFO - Epoch(train) [40][860/940] lr: 1.0000e-02 eta: 10:23:34 time: 0.6537 data_time: 0.0311 memory: 24011 grad_norm: 5.7371 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1738 loss: 1.1738 2022/09/05 15:35:02 - mmengine - INFO - Epoch(train) [40][880/940] lr: 1.0000e-02 eta: 10:23:20 time: 0.6474 data_time: 0.0591 memory: 24011 grad_norm: 4.9374 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1267 loss: 1.1267 2022/09/05 15:35:15 - mmengine - INFO - Epoch(train) [40][900/940] lr: 1.0000e-02 eta: 10:23:07 time: 0.6635 data_time: 0.0477 memory: 24011 grad_norm: 4.8346 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1474 loss: 1.1474 2022/09/05 15:35:28 - mmengine - INFO - Epoch(train) [40][920/940] lr: 1.0000e-02 eta: 10:22:53 time: 0.6576 data_time: 0.0849 memory: 24011 grad_norm: 5.0359 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1177 loss: 1.1177 2022/09/05 15:35:39 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:35:39 - mmengine - INFO - Epoch(train) [40][940/940] lr: 1.0000e-02 eta: 10:22:37 time: 0.5459 data_time: 0.0317 memory: 24011 grad_norm: 5.6522 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.0504 loss: 1.0504 2022/09/05 15:35:53 - mmengine - INFO - Epoch(val) [40][20/78] eta: 0:00:40 time: 0.6979 data_time: 0.5299 memory: 3625 2022/09/05 15:36:02 - mmengine - INFO - Epoch(val) [40][40/78] eta: 0:00:17 time: 0.4544 data_time: 0.2967 memory: 3625 2022/09/05 15:36:16 - mmengine - INFO - Epoch(val) [40][60/78] eta: 0:00:12 time: 0.6667 data_time: 0.5066 memory: 3625 2022/09/05 15:36:26 - mmengine - INFO - Epoch(val) [40][78/78] acc/top1: 0.6998 acc/top5: 0.8918 acc/mean1: 0.6996 2022/09/05 15:36:45 - mmengine - INFO - Epoch(train) [41][20/940] lr: 1.0000e-03 eta: 10:22:32 time: 0.9364 data_time: 0.3625 memory: 24011 grad_norm: 6.0814 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0470 loss: 1.0470 2022/09/05 15:36:57 - mmengine - INFO - Epoch(train) [41][40/940] lr: 1.0000e-03 eta: 10:22:17 time: 0.6106 data_time: 0.0288 memory: 24011 grad_norm: 4.8659 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8400 loss: 0.8400 2022/09/05 15:37:10 - mmengine - INFO - Epoch(train) [41][60/940] lr: 1.0000e-03 eta: 10:22:03 time: 0.6547 data_time: 0.0872 memory: 24011 grad_norm: 5.2574 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8109 loss: 0.8109 2022/09/05 15:37:23 - mmengine - INFO - Epoch(train) [41][80/940] lr: 1.0000e-03 eta: 10:21:50 time: 0.6503 data_time: 0.0721 memory: 24011 grad_norm: 4.6491 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0124 loss: 1.0124 2022/09/05 15:37:36 - mmengine - INFO - Epoch(train) [41][100/940] lr: 1.0000e-03 eta: 10:21:36 time: 0.6555 data_time: 0.0840 memory: 24011 grad_norm: 5.0711 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9708 loss: 0.9708 2022/09/05 15:37:49 - mmengine - INFO - Epoch(train) [41][120/940] lr: 1.0000e-03 eta: 10:21:23 time: 0.6502 data_time: 0.0728 memory: 24011 grad_norm: 4.6987 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9571 loss: 0.9571 2022/09/05 15:38:03 - mmengine - INFO - Epoch(train) [41][140/940] lr: 1.0000e-03 eta: 10:21:10 time: 0.6772 data_time: 0.0377 memory: 24011 grad_norm: 4.5549 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8292 loss: 0.8292 2022/09/05 15:38:15 - mmengine - INFO - Epoch(train) [41][160/940] lr: 1.0000e-03 eta: 10:20:55 time: 0.6295 data_time: 0.0336 memory: 24011 grad_norm: 5.1399 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8178 loss: 0.8178 2022/09/05 15:38:30 - mmengine - INFO - Epoch(train) [41][180/940] lr: 1.0000e-03 eta: 10:20:44 time: 0.7152 data_time: 0.0383 memory: 24011 grad_norm: 4.8154 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.8985 loss: 0.8985 2022/09/05 15:38:42 - mmengine - INFO - Epoch(train) [41][200/940] lr: 1.0000e-03 eta: 10:20:29 time: 0.5948 data_time: 0.0363 memory: 24011 grad_norm: 5.5014 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8825 loss: 0.8825 2022/09/05 15:38:55 - mmengine - INFO - Epoch(train) [41][220/940] lr: 1.0000e-03 eta: 10:20:15 time: 0.6406 data_time: 0.0378 memory: 24011 grad_norm: 4.8038 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9073 loss: 0.9073 2022/09/05 15:39:07 - mmengine - INFO - Epoch(train) [41][240/940] lr: 1.0000e-03 eta: 10:20:00 time: 0.6248 data_time: 0.0486 memory: 24011 grad_norm: 4.9457 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8760 loss: 0.8760 2022/09/05 15:39:20 - mmengine - INFO - Epoch(train) [41][260/940] lr: 1.0000e-03 eta: 10:19:47 time: 0.6760 data_time: 0.0469 memory: 24011 grad_norm: 4.8342 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9028 loss: 0.9028 2022/09/05 15:39:33 - mmengine - INFO - Epoch(train) [41][280/940] lr: 1.0000e-03 eta: 10:19:34 time: 0.6441 data_time: 0.0335 memory: 24011 grad_norm: 4.4724 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8899 loss: 0.8899 2022/09/05 15:39:47 - mmengine - INFO - Epoch(train) [41][300/940] lr: 1.0000e-03 eta: 10:19:21 time: 0.6693 data_time: 0.0434 memory: 24011 grad_norm: 4.7624 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8482 loss: 0.8482 2022/09/05 15:40:00 - mmengine - INFO - Epoch(train) [41][320/940] lr: 1.0000e-03 eta: 10:19:08 time: 0.6767 data_time: 0.0697 memory: 24011 grad_norm: 4.6278 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8833 loss: 0.8833 2022/09/05 15:40:14 - mmengine - INFO - Epoch(train) [41][340/940] lr: 1.0000e-03 eta: 10:18:55 time: 0.6667 data_time: 0.0407 memory: 24011 grad_norm: 5.7540 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.8880 loss: 0.8880 2022/09/05 15:40:26 - mmengine - INFO - Epoch(train) [41][360/940] lr: 1.0000e-03 eta: 10:18:41 time: 0.6380 data_time: 0.0384 memory: 24011 grad_norm: 4.8744 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8982 loss: 0.8982 2022/09/05 15:40:39 - mmengine - INFO - Epoch(train) [41][380/940] lr: 1.0000e-03 eta: 10:18:27 time: 0.6345 data_time: 0.0356 memory: 24011 grad_norm: 4.6370 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7771 loss: 0.7771 2022/09/05 15:40:52 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:40:52 - mmengine - INFO - Epoch(train) [41][400/940] lr: 1.0000e-03 eta: 10:18:13 time: 0.6616 data_time: 0.0378 memory: 24011 grad_norm: 5.4360 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.8570 loss: 0.8570 2022/09/05 15:41:06 - mmengine - INFO - Epoch(train) [41][420/940] lr: 1.0000e-03 eta: 10:18:01 time: 0.6772 data_time: 0.0362 memory: 24011 grad_norm: 4.5810 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7766 loss: 0.7766 2022/09/05 15:41:19 - mmengine - INFO - Epoch(train) [41][440/940] lr: 1.0000e-03 eta: 10:17:47 time: 0.6398 data_time: 0.0519 memory: 24011 grad_norm: 4.6921 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8105 loss: 0.8105 2022/09/05 15:41:32 - mmengine - INFO - Epoch(train) [41][460/940] lr: 1.0000e-03 eta: 10:17:33 time: 0.6404 data_time: 0.0388 memory: 24011 grad_norm: 4.7784 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9043 loss: 0.9043 2022/09/05 15:41:45 - mmengine - INFO - Epoch(train) [41][480/940] lr: 1.0000e-03 eta: 10:17:20 time: 0.6625 data_time: 0.0415 memory: 24011 grad_norm: 4.8297 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9596 loss: 0.9596 2022/09/05 15:41:58 - mmengine - INFO - Epoch(train) [41][500/940] lr: 1.0000e-03 eta: 10:17:07 time: 0.6726 data_time: 0.0409 memory: 24011 grad_norm: 5.4087 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9126 loss: 0.9126 2022/09/05 15:42:10 - mmengine - INFO - Epoch(train) [41][520/940] lr: 1.0000e-03 eta: 10:16:52 time: 0.6043 data_time: 0.0415 memory: 24011 grad_norm: 4.8673 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8373 loss: 0.8373 2022/09/05 15:42:23 - mmengine - INFO - Epoch(train) [41][540/940] lr: 1.0000e-03 eta: 10:16:38 time: 0.6334 data_time: 0.0406 memory: 24011 grad_norm: 4.9155 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8055 loss: 0.8055 2022/09/05 15:42:36 - mmengine - INFO - Epoch(train) [41][560/940] lr: 1.0000e-03 eta: 10:16:24 time: 0.6602 data_time: 0.0372 memory: 24011 grad_norm: 4.8198 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8574 loss: 0.8574 2022/09/05 15:42:49 - mmengine - INFO - Epoch(train) [41][580/940] lr: 1.0000e-03 eta: 10:16:11 time: 0.6504 data_time: 0.0381 memory: 24011 grad_norm: 4.7587 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7994 loss: 0.7994 2022/09/05 15:43:02 - mmengine - INFO - Epoch(train) [41][600/940] lr: 1.0000e-03 eta: 10:15:56 time: 0.6241 data_time: 0.0376 memory: 24011 grad_norm: 5.1149 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8634 loss: 0.8634 2022/09/05 15:43:15 - mmengine - INFO - Epoch(train) [41][620/940] lr: 1.0000e-03 eta: 10:15:43 time: 0.6691 data_time: 0.0384 memory: 24011 grad_norm: 4.8241 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8664 loss: 0.8664 2022/09/05 15:43:28 - mmengine - INFO - Epoch(train) [41][640/940] lr: 1.0000e-03 eta: 10:15:29 time: 0.6292 data_time: 0.0461 memory: 24011 grad_norm: 4.5124 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.8315 loss: 0.8315 2022/09/05 15:43:42 - mmengine - INFO - Epoch(train) [41][660/940] lr: 1.0000e-03 eta: 10:15:17 time: 0.6906 data_time: 0.0414 memory: 24011 grad_norm: 5.7123 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8331 loss: 0.8331 2022/09/05 15:43:54 - mmengine - INFO - Epoch(train) [41][680/940] lr: 1.0000e-03 eta: 10:15:03 time: 0.6403 data_time: 0.0425 memory: 24011 grad_norm: 5.0585 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.7579 loss: 0.7579 2022/09/05 15:44:08 - mmengine - INFO - Epoch(train) [41][700/940] lr: 1.0000e-03 eta: 10:14:50 time: 0.6792 data_time: 0.0457 memory: 24011 grad_norm: 4.8197 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8075 loss: 0.8075 2022/09/05 15:44:21 - mmengine - INFO - Epoch(train) [41][720/940] lr: 1.0000e-03 eta: 10:14:36 time: 0.6367 data_time: 0.0632 memory: 24011 grad_norm: 4.9291 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.8962 loss: 0.8962 2022/09/05 15:44:34 - mmengine - INFO - Epoch(train) [41][740/940] lr: 1.0000e-03 eta: 10:14:22 time: 0.6544 data_time: 0.0475 memory: 24011 grad_norm: 5.3620 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8730 loss: 0.8730 2022/09/05 15:44:46 - mmengine - INFO - Epoch(train) [41][760/940] lr: 1.0000e-03 eta: 10:14:07 time: 0.5939 data_time: 0.0382 memory: 24011 grad_norm: 4.7078 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7974 loss: 0.7974 2022/09/05 15:45:00 - mmengine - INFO - Epoch(train) [41][780/940] lr: 1.0000e-03 eta: 10:13:55 time: 0.7031 data_time: 0.0398 memory: 24011 grad_norm: 4.7816 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.8014 loss: 0.8014 2022/09/05 15:45:12 - mmengine - INFO - Epoch(train) [41][800/940] lr: 1.0000e-03 eta: 10:13:41 time: 0.6324 data_time: 0.0501 memory: 24011 grad_norm: 5.0694 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8651 loss: 0.8651 2022/09/05 15:45:26 - mmengine - INFO - Epoch(train) [41][820/940] lr: 1.0000e-03 eta: 10:13:28 time: 0.6839 data_time: 0.0415 memory: 24011 grad_norm: 4.7330 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8316 loss: 0.8316 2022/09/05 15:45:38 - mmengine - INFO - Epoch(train) [41][840/940] lr: 1.0000e-03 eta: 10:13:13 time: 0.5974 data_time: 0.0397 memory: 24011 grad_norm: 5.2661 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.7893 loss: 0.7893 2022/09/05 15:45:51 - mmengine - INFO - Epoch(train) [41][860/940] lr: 1.0000e-03 eta: 10:13:00 time: 0.6454 data_time: 0.0379 memory: 24011 grad_norm: 4.9300 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8415 loss: 0.8415 2022/09/05 15:46:04 - mmengine - INFO - Epoch(train) [41][880/940] lr: 1.0000e-03 eta: 10:12:46 time: 0.6514 data_time: 0.0436 memory: 24011 grad_norm: 5.0747 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.7894 loss: 0.7894 2022/09/05 15:46:18 - mmengine - INFO - Epoch(train) [41][900/940] lr: 1.0000e-03 eta: 10:12:33 time: 0.6866 data_time: 0.0449 memory: 24011 grad_norm: 4.9420 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7656 loss: 0.7656 2022/09/05 15:46:30 - mmengine - INFO - Epoch(train) [41][920/940] lr: 1.0000e-03 eta: 10:12:19 time: 0.6269 data_time: 0.0383 memory: 24011 grad_norm: 5.1018 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8726 loss: 0.8726 2022/09/05 15:46:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:46:41 - mmengine - INFO - Epoch(train) [41][940/940] lr: 1.0000e-03 eta: 10:12:03 time: 0.5555 data_time: 0.0292 memory: 24011 grad_norm: 6.1710 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.7247 loss: 0.7247 2022/09/05 15:46:55 - mmengine - INFO - Epoch(val) [41][20/78] eta: 0:00:39 time: 0.6826 data_time: 0.5217 memory: 3625 2022/09/05 15:47:05 - mmengine - INFO - Epoch(val) [41][40/78] eta: 0:00:17 time: 0.4725 data_time: 0.3166 memory: 3625 2022/09/05 15:47:17 - mmengine - INFO - Epoch(val) [41][60/78] eta: 0:00:11 time: 0.6409 data_time: 0.4783 memory: 3625 2022/09/05 15:47:28 - mmengine - INFO - Epoch(val) [41][78/78] acc/top1: 0.7310 acc/top5: 0.9052 acc/mean1: 0.7309 2022/09/05 15:47:28 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_27.pth is removed 2022/09/05 15:47:33 - mmengine - INFO - The best checkpoint with 0.7310 acc/top1 at 42 epoch is saved to best_acc/top1_epoch_42.pth. 2022/09/05 15:47:50 - mmengine - INFO - Epoch(train) [42][20/940] lr: 1.0000e-03 eta: 10:11:55 time: 0.8346 data_time: 0.2821 memory: 24011 grad_norm: 4.9187 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8730 loss: 0.8730 2022/09/05 15:48:03 - mmengine - INFO - Epoch(train) [42][40/940] lr: 1.0000e-03 eta: 10:11:42 time: 0.6782 data_time: 0.1099 memory: 24011 grad_norm: 4.6930 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7753 loss: 0.7753 2022/09/05 15:48:16 - mmengine - INFO - Epoch(train) [42][60/940] lr: 1.0000e-03 eta: 10:11:27 time: 0.6010 data_time: 0.0402 memory: 24011 grad_norm: 4.7655 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7695 loss: 0.7695 2022/09/05 15:48:28 - mmengine - INFO - Epoch(train) [42][80/940] lr: 1.0000e-03 eta: 10:11:13 time: 0.6279 data_time: 0.0453 memory: 24011 grad_norm: 4.8800 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8287 loss: 0.8287 2022/09/05 15:48:41 - mmengine - INFO - Epoch(train) [42][100/940] lr: 1.0000e-03 eta: 10:10:59 time: 0.6640 data_time: 0.0958 memory: 24011 grad_norm: 4.8769 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7323 loss: 0.7323 2022/09/05 15:48:53 - mmengine - INFO - Epoch(train) [42][120/940] lr: 1.0000e-03 eta: 10:10:45 time: 0.6089 data_time: 0.0447 memory: 24011 grad_norm: 5.1357 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7668 loss: 0.7668 2022/09/05 15:49:08 - mmengine - INFO - Epoch(train) [42][140/940] lr: 1.0000e-03 eta: 10:10:33 time: 0.7304 data_time: 0.1586 memory: 24011 grad_norm: 4.7339 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7580 loss: 0.7580 2022/09/05 15:49:20 - mmengine - INFO - Epoch(train) [42][160/940] lr: 1.0000e-03 eta: 10:10:19 time: 0.6179 data_time: 0.0523 memory: 24011 grad_norm: 4.7682 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.8564 loss: 0.8564 2022/09/05 15:49:35 - mmengine - INFO - Epoch(train) [42][180/940] lr: 1.0000e-03 eta: 10:10:07 time: 0.7171 data_time: 0.1437 memory: 24011 grad_norm: 4.7353 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7914 loss: 0.7914 2022/09/05 15:49:47 - mmengine - INFO - Epoch(train) [42][200/940] lr: 1.0000e-03 eta: 10:09:52 time: 0.6011 data_time: 0.0380 memory: 24011 grad_norm: 4.8939 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.8933 loss: 0.8933 2022/09/05 15:49:59 - mmengine - INFO - Epoch(train) [42][220/940] lr: 1.0000e-03 eta: 10:09:38 time: 0.6275 data_time: 0.0649 memory: 24011 grad_norm: 4.7660 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.7798 loss: 0.7798 2022/09/05 15:50:11 - mmengine - INFO - Epoch(train) [42][240/940] lr: 1.0000e-03 eta: 10:09:23 time: 0.5953 data_time: 0.0345 memory: 24011 grad_norm: 4.9938 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 0.7768 loss: 0.7768 2022/09/05 15:50:25 - mmengine - INFO - Epoch(train) [42][260/940] lr: 1.0000e-03 eta: 10:09:10 time: 0.6920 data_time: 0.0721 memory: 24011 grad_norm: 5.5460 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.7611 loss: 0.7611 2022/09/05 15:50:38 - mmengine - INFO - Epoch(train) [42][280/940] lr: 1.0000e-03 eta: 10:08:57 time: 0.6512 data_time: 0.0335 memory: 24011 grad_norm: 4.7647 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7922 loss: 0.7922 2022/09/05 15:50:51 - mmengine - INFO - Epoch(train) [42][300/940] lr: 1.0000e-03 eta: 10:08:43 time: 0.6387 data_time: 0.0623 memory: 24011 grad_norm: 5.2525 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8332 loss: 0.8332 2022/09/05 15:51:03 - mmengine - INFO - Epoch(train) [42][320/940] lr: 1.0000e-03 eta: 10:08:29 time: 0.6274 data_time: 0.0325 memory: 24011 grad_norm: 4.7326 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7452 loss: 0.7452 2022/09/05 15:51:17 - mmengine - INFO - Epoch(train) [42][340/940] lr: 1.0000e-03 eta: 10:08:16 time: 0.6840 data_time: 0.1127 memory: 24011 grad_norm: 4.5677 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.8466 loss: 0.8466 2022/09/05 15:51:30 - mmengine - INFO - Epoch(train) [42][360/940] lr: 1.0000e-03 eta: 10:08:02 time: 0.6373 data_time: 0.0542 memory: 24011 grad_norm: 4.8331 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8272 loss: 0.8272 2022/09/05 15:51:43 - mmengine - INFO - Epoch(train) [42][380/940] lr: 1.0000e-03 eta: 10:07:49 time: 0.6504 data_time: 0.0398 memory: 24011 grad_norm: 4.8470 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8265 loss: 0.8265 2022/09/05 15:51:56 - mmengine - INFO - Epoch(train) [42][400/940] lr: 1.0000e-03 eta: 10:07:35 time: 0.6345 data_time: 0.0295 memory: 24011 grad_norm: 4.8567 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.8039 loss: 0.8039 2022/09/05 15:52:09 - mmengine - INFO - Epoch(train) [42][420/940] lr: 1.0000e-03 eta: 10:07:21 time: 0.6553 data_time: 0.0402 memory: 24011 grad_norm: 4.9162 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7725 loss: 0.7725 2022/09/05 15:52:21 - mmengine - INFO - Epoch(train) [42][440/940] lr: 1.0000e-03 eta: 10:07:07 time: 0.6281 data_time: 0.0333 memory: 24011 grad_norm: 4.5710 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7983 loss: 0.7983 2022/09/05 15:52:34 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:52:34 - mmengine - INFO - Epoch(train) [42][460/940] lr: 1.0000e-03 eta: 10:06:53 time: 0.6554 data_time: 0.0435 memory: 24011 grad_norm: 5.4024 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.8656 loss: 0.8656 2022/09/05 15:52:47 - mmengine - INFO - Epoch(train) [42][480/940] lr: 1.0000e-03 eta: 10:06:39 time: 0.6121 data_time: 0.0358 memory: 24011 grad_norm: 4.7088 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8738 loss: 0.8738 2022/09/05 15:53:01 - mmengine - INFO - Epoch(train) [42][500/940] lr: 1.0000e-03 eta: 10:06:27 time: 0.7006 data_time: 0.0740 memory: 24011 grad_norm: 4.9785 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9572 loss: 0.9572 2022/09/05 15:53:14 - mmengine - INFO - Epoch(train) [42][520/940] lr: 1.0000e-03 eta: 10:06:13 time: 0.6549 data_time: 0.0629 memory: 24011 grad_norm: 4.8940 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7943 loss: 0.7943 2022/09/05 15:53:28 - mmengine - INFO - Epoch(train) [42][540/940] lr: 1.0000e-03 eta: 10:06:00 time: 0.6740 data_time: 0.0822 memory: 24011 grad_norm: 5.9684 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.7961 loss: 0.7961 2022/09/05 15:53:40 - mmengine - INFO - Epoch(train) [42][560/940] lr: 1.0000e-03 eta: 10:05:47 time: 0.6548 data_time: 0.0773 memory: 24011 grad_norm: 4.9787 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8039 loss: 0.8039 2022/09/05 15:53:54 - mmengine - INFO - Epoch(train) [42][580/940] lr: 1.0000e-03 eta: 10:05:34 time: 0.6768 data_time: 0.0985 memory: 24011 grad_norm: 4.7358 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7938 loss: 0.7938 2022/09/05 15:54:06 - mmengine - INFO - Epoch(train) [42][600/940] lr: 1.0000e-03 eta: 10:05:20 time: 0.6231 data_time: 0.0554 memory: 24011 grad_norm: 5.2242 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8555 loss: 0.8555 2022/09/05 15:54:19 - mmengine - INFO - Epoch(train) [42][620/940] lr: 1.0000e-03 eta: 10:05:06 time: 0.6431 data_time: 0.0809 memory: 24011 grad_norm: 6.2116 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6908 loss: 0.6908 2022/09/05 15:54:33 - mmengine - INFO - Epoch(train) [42][640/940] lr: 1.0000e-03 eta: 10:04:54 time: 0.6948 data_time: 0.0986 memory: 24011 grad_norm: 4.5597 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.7019 loss: 0.7019 2022/09/05 15:54:45 - mmengine - INFO - Epoch(train) [42][660/940] lr: 1.0000e-03 eta: 10:04:39 time: 0.6146 data_time: 0.0420 memory: 24011 grad_norm: 4.9981 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8541 loss: 0.8541 2022/09/05 15:54:57 - mmengine - INFO - Epoch(train) [42][680/940] lr: 1.0000e-03 eta: 10:04:24 time: 0.5982 data_time: 0.0326 memory: 24011 grad_norm: 5.1864 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.7154 loss: 0.7154 2022/09/05 15:55:11 - mmengine - INFO - Epoch(train) [42][700/940] lr: 1.0000e-03 eta: 10:04:11 time: 0.6693 data_time: 0.0815 memory: 24011 grad_norm: 5.7031 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8642 loss: 0.8642 2022/09/05 15:55:23 - mmengine - INFO - Epoch(train) [42][720/940] lr: 1.0000e-03 eta: 10:03:57 time: 0.6346 data_time: 0.0588 memory: 24011 grad_norm: 5.3857 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.7355 loss: 0.7355 2022/09/05 15:55:37 - mmengine - INFO - Epoch(train) [42][740/940] lr: 1.0000e-03 eta: 10:03:44 time: 0.6767 data_time: 0.0508 memory: 24011 grad_norm: 4.6097 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7815 loss: 0.7815 2022/09/05 15:55:50 - mmengine - INFO - Epoch(train) [42][760/940] lr: 1.0000e-03 eta: 10:03:30 time: 0.6416 data_time: 0.0398 memory: 24011 grad_norm: 4.9024 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7969 loss: 0.7969 2022/09/05 15:56:03 - mmengine - INFO - Epoch(train) [42][780/940] lr: 1.0000e-03 eta: 10:03:16 time: 0.6358 data_time: 0.0419 memory: 24011 grad_norm: 5.1959 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6903 loss: 0.6903 2022/09/05 15:56:15 - mmengine - INFO - Epoch(train) [42][800/940] lr: 1.0000e-03 eta: 10:03:02 time: 0.6216 data_time: 0.0360 memory: 24011 grad_norm: 4.9344 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7299 loss: 0.7299 2022/09/05 15:56:28 - mmengine - INFO - Epoch(train) [42][820/940] lr: 1.0000e-03 eta: 10:02:48 time: 0.6367 data_time: 0.0437 memory: 24011 grad_norm: 5.0432 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8317 loss: 0.8317 2022/09/05 15:56:42 - mmengine - INFO - Epoch(train) [42][840/940] lr: 1.0000e-03 eta: 10:02:36 time: 0.7035 data_time: 0.0539 memory: 24011 grad_norm: 4.8077 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7508 loss: 0.7508 2022/09/05 15:56:54 - mmengine - INFO - Epoch(train) [42][860/940] lr: 1.0000e-03 eta: 10:02:22 time: 0.6338 data_time: 0.0435 memory: 24011 grad_norm: 5.2923 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.8853 loss: 0.8853 2022/09/05 15:57:07 - mmengine - INFO - Epoch(train) [42][880/940] lr: 1.0000e-03 eta: 10:02:08 time: 0.6401 data_time: 0.0341 memory: 24011 grad_norm: 5.1984 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9087 loss: 0.9087 2022/09/05 15:57:20 - mmengine - INFO - Epoch(train) [42][900/940] lr: 1.0000e-03 eta: 10:01:54 time: 0.6393 data_time: 0.0496 memory: 24011 grad_norm: 4.6047 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.8119 loss: 0.8119 2022/09/05 15:57:34 - mmengine - INFO - Epoch(train) [42][920/940] lr: 1.0000e-03 eta: 10:01:42 time: 0.6822 data_time: 0.0364 memory: 24011 grad_norm: 4.9848 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7306 loss: 0.7306 2022/09/05 15:57:44 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 15:57:44 - mmengine - INFO - Epoch(train) [42][940/940] lr: 1.0000e-03 eta: 10:01:25 time: 0.5392 data_time: 0.0242 memory: 24011 grad_norm: 4.9742 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 0.9210 loss: 0.9210 2022/09/05 15:57:45 - mmengine - INFO - Saving checkpoint at 42 epochs 2022/09/05 15:58:04 - mmengine - INFO - Epoch(val) [42][20/78] eta: 0:00:41 time: 0.7094 data_time: 0.5534 memory: 3625 2022/09/05 15:58:13 - mmengine - INFO - Epoch(val) [42][40/78] eta: 0:00:17 time: 0.4597 data_time: 0.2968 memory: 3625 2022/09/05 15:58:26 - mmengine - INFO - Epoch(val) [42][60/78] eta: 0:00:11 time: 0.6372 data_time: 0.4857 memory: 3625 2022/09/05 15:58:35 - mmengine - INFO - Epoch(val) [42][78/78] acc/top1: 0.7361 acc/top5: 0.9064 acc/mean1: 0.7360 2022/09/05 15:58:35 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_42.pth is removed 2022/09/05 15:58:38 - mmengine - INFO - The best checkpoint with 0.7361 acc/top1 at 43 epoch is saved to best_acc/top1_epoch_43.pth. 2022/09/05 15:58:56 - mmengine - INFO - Epoch(train) [43][20/940] lr: 1.0000e-03 eta: 10:01:18 time: 0.8821 data_time: 0.3242 memory: 24011 grad_norm: 4.7657 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8033 loss: 0.8033 2022/09/05 15:59:08 - mmengine - INFO - Epoch(train) [43][40/940] lr: 1.0000e-03 eta: 10:01:03 time: 0.6045 data_time: 0.0611 memory: 24011 grad_norm: 4.9874 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8043 loss: 0.8043 2022/09/05 15:59:22 - mmengine - INFO - Epoch(train) [43][60/940] lr: 1.0000e-03 eta: 10:00:51 time: 0.7136 data_time: 0.1525 memory: 24011 grad_norm: 4.5666 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6853 loss: 0.6853 2022/09/05 15:59:34 - mmengine - INFO - Epoch(train) [43][80/940] lr: 1.0000e-03 eta: 10:00:36 time: 0.5804 data_time: 0.0298 memory: 24011 grad_norm: 4.4263 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.7744 loss: 0.7744 2022/09/05 15:59:48 - mmengine - INFO - Epoch(train) [43][100/940] lr: 1.0000e-03 eta: 10:00:23 time: 0.6821 data_time: 0.1328 memory: 24011 grad_norm: 4.6309 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.7825 loss: 0.7825 2022/09/05 16:00:00 - mmengine - INFO - Epoch(train) [43][120/940] lr: 1.0000e-03 eta: 10:00:09 time: 0.6411 data_time: 0.0614 memory: 24011 grad_norm: 5.0222 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.7639 loss: 0.7639 2022/09/05 16:00:14 - mmengine - INFO - Epoch(train) [43][140/940] lr: 1.0000e-03 eta: 9:59:56 time: 0.6570 data_time: 0.1029 memory: 24011 grad_norm: 5.1617 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.7267 loss: 0.7267 2022/09/05 16:00:27 - mmengine - INFO - Epoch(train) [43][160/940] lr: 1.0000e-03 eta: 9:59:42 time: 0.6568 data_time: 0.0973 memory: 24011 grad_norm: 4.5703 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7730 loss: 0.7730 2022/09/05 16:00:40 - mmengine - INFO - Epoch(train) [43][180/940] lr: 1.0000e-03 eta: 9:59:29 time: 0.6660 data_time: 0.1043 memory: 24011 grad_norm: 5.1333 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7836 loss: 0.7836 2022/09/05 16:00:53 - mmengine - INFO - Epoch(train) [43][200/940] lr: 1.0000e-03 eta: 9:59:16 time: 0.6733 data_time: 0.1228 memory: 24011 grad_norm: 4.9478 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7359 loss: 0.7359 2022/09/05 16:01:06 - mmengine - INFO - Epoch(train) [43][220/940] lr: 1.0000e-03 eta: 9:59:02 time: 0.6357 data_time: 0.0771 memory: 24011 grad_norm: 4.7691 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6357 loss: 0.6357 2022/09/05 16:01:19 - mmengine - INFO - Epoch(train) [43][240/940] lr: 1.0000e-03 eta: 9:58:48 time: 0.6276 data_time: 0.0612 memory: 24011 grad_norm: 5.0434 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7718 loss: 0.7718 2022/09/05 16:01:32 - mmengine - INFO - Epoch(train) [43][260/940] lr: 1.0000e-03 eta: 9:58:35 time: 0.6480 data_time: 0.0854 memory: 24011 grad_norm: 5.9924 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8298 loss: 0.8298 2022/09/05 16:01:44 - mmengine - INFO - Epoch(train) [43][280/940] lr: 1.0000e-03 eta: 9:58:20 time: 0.6250 data_time: 0.0334 memory: 24011 grad_norm: 5.1387 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.7867 loss: 0.7867 2022/09/05 16:01:56 - mmengine - INFO - Epoch(train) [43][300/940] lr: 1.0000e-03 eta: 9:58:06 time: 0.6086 data_time: 0.0492 memory: 24011 grad_norm: 4.6850 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6431 loss: 0.6431 2022/09/05 16:02:09 - mmengine - INFO - Epoch(train) [43][320/940] lr: 1.0000e-03 eta: 9:57:52 time: 0.6307 data_time: 0.0374 memory: 24011 grad_norm: 4.5043 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7573 loss: 0.7573 2022/09/05 16:02:22 - mmengine - INFO - Epoch(train) [43][340/940] lr: 1.0000e-03 eta: 9:57:38 time: 0.6572 data_time: 0.0440 memory: 24011 grad_norm: 4.5642 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7257 loss: 0.7257 2022/09/05 16:02:36 - mmengine - INFO - Epoch(train) [43][360/940] lr: 1.0000e-03 eta: 9:57:26 time: 0.6818 data_time: 0.0352 memory: 24011 grad_norm: 5.4188 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7142 loss: 0.7142 2022/09/05 16:02:50 - mmengine - INFO - Epoch(train) [43][380/940] lr: 1.0000e-03 eta: 9:57:13 time: 0.6865 data_time: 0.0378 memory: 24011 grad_norm: 4.6677 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7902 loss: 0.7902 2022/09/05 16:03:02 - mmengine - INFO - Epoch(train) [43][400/940] lr: 1.0000e-03 eta: 9:56:58 time: 0.6047 data_time: 0.0376 memory: 24011 grad_norm: 4.8716 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.7553 loss: 0.7553 2022/09/05 16:03:15 - mmengine - INFO - Epoch(train) [43][420/940] lr: 1.0000e-03 eta: 9:56:45 time: 0.6558 data_time: 0.0458 memory: 24011 grad_norm: 4.9746 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7767 loss: 0.7767 2022/09/05 16:03:28 - mmengine - INFO - Epoch(train) [43][440/940] lr: 1.0000e-03 eta: 9:56:31 time: 0.6439 data_time: 0.0416 memory: 24011 grad_norm: 4.6622 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7913 loss: 0.7913 2022/09/05 16:03:40 - mmengine - INFO - Epoch(train) [43][460/940] lr: 1.0000e-03 eta: 9:56:17 time: 0.6136 data_time: 0.0401 memory: 24011 grad_norm: 5.1696 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.8074 loss: 0.8074 2022/09/05 16:03:53 - mmengine - INFO - Epoch(train) [43][480/940] lr: 1.0000e-03 eta: 9:56:04 time: 0.6715 data_time: 0.0483 memory: 24011 grad_norm: 4.7973 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.8680 loss: 0.8680 2022/09/05 16:04:07 - mmengine - INFO - Epoch(train) [43][500/940] lr: 1.0000e-03 eta: 9:55:51 time: 0.6920 data_time: 0.0397 memory: 24011 grad_norm: 4.6290 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.8433 loss: 0.8433 2022/09/05 16:04:20 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:04:20 - mmengine - INFO - Epoch(train) [43][520/940] lr: 1.0000e-03 eta: 9:55:37 time: 0.6343 data_time: 0.0354 memory: 24011 grad_norm: 4.4403 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7342 loss: 0.7342 2022/09/05 16:04:33 - mmengine - INFO - Epoch(train) [43][540/940] lr: 1.0000e-03 eta: 9:55:24 time: 0.6489 data_time: 0.0395 memory: 24011 grad_norm: 4.5708 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.8235 loss: 0.8235 2022/09/05 16:04:45 - mmengine - INFO - Epoch(train) [43][560/940] lr: 1.0000e-03 eta: 9:55:09 time: 0.6253 data_time: 0.0375 memory: 24011 grad_norm: 5.1765 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8722 loss: 0.8722 2022/09/05 16:04:59 - mmengine - INFO - Epoch(train) [43][580/940] lr: 1.0000e-03 eta: 9:54:57 time: 0.6791 data_time: 0.0837 memory: 24011 grad_norm: 4.6031 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.8050 loss: 0.8050 2022/09/05 16:05:12 - mmengine - INFO - Epoch(train) [43][600/940] lr: 1.0000e-03 eta: 9:54:42 time: 0.6296 data_time: 0.0403 memory: 24011 grad_norm: 4.3601 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8059 loss: 0.8059 2022/09/05 16:05:24 - mmengine - INFO - Epoch(train) [43][620/940] lr: 1.0000e-03 eta: 9:54:28 time: 0.6317 data_time: 0.0515 memory: 24011 grad_norm: 4.6630 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8206 loss: 0.8206 2022/09/05 16:05:37 - mmengine - INFO - Epoch(train) [43][640/940] lr: 1.0000e-03 eta: 9:54:15 time: 0.6381 data_time: 0.0416 memory: 24011 grad_norm: 4.6944 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8010 loss: 0.8010 2022/09/05 16:05:51 - mmengine - INFO - Epoch(train) [43][660/940] lr: 1.0000e-03 eta: 9:54:02 time: 0.6943 data_time: 0.1168 memory: 24011 grad_norm: 5.1759 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7777 loss: 0.7777 2022/09/05 16:06:04 - mmengine - INFO - Epoch(train) [43][680/940] lr: 1.0000e-03 eta: 9:53:49 time: 0.6534 data_time: 0.0788 memory: 24011 grad_norm: 4.9313 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8429 loss: 0.8429 2022/09/05 16:06:18 - mmengine - INFO - Epoch(train) [43][700/940] lr: 1.0000e-03 eta: 9:53:36 time: 0.6798 data_time: 0.1058 memory: 24011 grad_norm: 4.9069 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7408 loss: 0.7408 2022/09/05 16:06:30 - mmengine - INFO - Epoch(train) [43][720/940] lr: 1.0000e-03 eta: 9:53:22 time: 0.6178 data_time: 0.0287 memory: 24011 grad_norm: 4.7465 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8306 loss: 0.8306 2022/09/05 16:06:42 - mmengine - INFO - Epoch(train) [43][740/940] lr: 1.0000e-03 eta: 9:53:07 time: 0.6131 data_time: 0.0374 memory: 24011 grad_norm: 4.4314 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7928 loss: 0.7928 2022/09/05 16:06:56 - mmengine - INFO - Epoch(train) [43][760/940] lr: 1.0000e-03 eta: 9:52:54 time: 0.6688 data_time: 0.0322 memory: 24011 grad_norm: 4.8493 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.7568 loss: 0.7568 2022/09/05 16:07:08 - mmengine - INFO - Epoch(train) [43][780/940] lr: 1.0000e-03 eta: 9:52:40 time: 0.6396 data_time: 0.0420 memory: 24011 grad_norm: 5.2719 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7489 loss: 0.7489 2022/09/05 16:07:21 - mmengine - INFO - Epoch(train) [43][800/940] lr: 1.0000e-03 eta: 9:52:26 time: 0.6351 data_time: 0.0477 memory: 24011 grad_norm: 4.8813 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7139 loss: 0.7139 2022/09/05 16:07:34 - mmengine - INFO - Epoch(train) [43][820/940] lr: 1.0000e-03 eta: 9:52:12 time: 0.6434 data_time: 0.0658 memory: 24011 grad_norm: 6.1750 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6564 loss: 0.6564 2022/09/05 16:07:47 - mmengine - INFO - Epoch(train) [43][840/940] lr: 1.0000e-03 eta: 9:51:59 time: 0.6618 data_time: 0.0410 memory: 24011 grad_norm: 5.1381 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8415 loss: 0.8415 2022/09/05 16:08:00 - mmengine - INFO - Epoch(train) [43][860/940] lr: 1.0000e-03 eta: 9:51:45 time: 0.6384 data_time: 0.0553 memory: 24011 grad_norm: 4.7965 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.7378 loss: 0.7378 2022/09/05 16:08:12 - mmengine - INFO - Epoch(train) [43][880/940] lr: 1.0000e-03 eta: 9:51:31 time: 0.6212 data_time: 0.0424 memory: 24011 grad_norm: 4.7888 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.7113 loss: 0.7113 2022/09/05 16:08:26 - mmengine - INFO - Epoch(train) [43][900/940] lr: 1.0000e-03 eta: 9:51:18 time: 0.6717 data_time: 0.0712 memory: 24011 grad_norm: 4.7080 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7943 loss: 0.7943 2022/09/05 16:08:39 - mmengine - INFO - Epoch(train) [43][920/940] lr: 1.0000e-03 eta: 9:51:05 time: 0.6515 data_time: 0.0416 memory: 24011 grad_norm: 4.8487 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7560 loss: 0.7560 2022/09/05 16:08:50 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:08:50 - mmengine - INFO - Epoch(train) [43][940/940] lr: 1.0000e-03 eta: 9:50:49 time: 0.5768 data_time: 0.0438 memory: 24011 grad_norm: 5.2267 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 0.8920 loss: 0.8920 2022/09/05 16:09:04 - mmengine - INFO - Epoch(val) [43][20/78] eta: 0:00:40 time: 0.6903 data_time: 0.5321 memory: 3625 2022/09/05 16:09:14 - mmengine - INFO - Epoch(val) [43][40/78] eta: 0:00:18 time: 0.4768 data_time: 0.3202 memory: 3625 2022/09/05 16:09:27 - mmengine - INFO - Epoch(val) [43][60/78] eta: 0:00:11 time: 0.6502 data_time: 0.4841 memory: 3625 2022/09/05 16:09:37 - mmengine - INFO - Epoch(val) [43][78/78] acc/top1: 0.7379 acc/top5: 0.9075 acc/mean1: 0.7377 2022/09/05 16:09:37 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_43.pth is removed 2022/09/05 16:09:40 - mmengine - INFO - The best checkpoint with 0.7379 acc/top1 at 44 epoch is saved to best_acc/top1_epoch_44.pth. 2022/09/05 16:09:58 - mmengine - INFO - Epoch(train) [44][20/940] lr: 1.0000e-03 eta: 9:50:42 time: 0.8824 data_time: 0.3162 memory: 24011 grad_norm: 4.5279 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6989 loss: 0.6989 2022/09/05 16:10:10 - mmengine - INFO - Epoch(train) [44][40/940] lr: 1.0000e-03 eta: 9:50:27 time: 0.6196 data_time: 0.0431 memory: 24011 grad_norm: 4.6990 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7346 loss: 0.7346 2022/09/05 16:10:23 - mmengine - INFO - Epoch(train) [44][60/940] lr: 1.0000e-03 eta: 9:50:14 time: 0.6392 data_time: 0.0737 memory: 24011 grad_norm: 5.3932 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6797 loss: 0.6797 2022/09/05 16:10:35 - mmengine - INFO - Epoch(train) [44][80/940] lr: 1.0000e-03 eta: 9:49:59 time: 0.6242 data_time: 0.0656 memory: 24011 grad_norm: 5.0630 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6195 loss: 0.6195 2022/09/05 16:10:48 - mmengine - INFO - Epoch(train) [44][100/940] lr: 1.0000e-03 eta: 9:49:46 time: 0.6423 data_time: 0.0842 memory: 24011 grad_norm: 4.8619 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.8441 loss: 0.8441 2022/09/05 16:11:01 - mmengine - INFO - Epoch(train) [44][120/940] lr: 1.0000e-03 eta: 9:49:32 time: 0.6293 data_time: 0.0529 memory: 24011 grad_norm: 5.0364 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7123 loss: 0.7123 2022/09/05 16:11:14 - mmengine - INFO - Epoch(train) [44][140/940] lr: 1.0000e-03 eta: 9:49:18 time: 0.6356 data_time: 0.0623 memory: 24011 grad_norm: 4.7513 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7773 loss: 0.7773 2022/09/05 16:11:27 - mmengine - INFO - Epoch(train) [44][160/940] lr: 1.0000e-03 eta: 9:49:05 time: 0.6736 data_time: 0.1012 memory: 24011 grad_norm: 4.8540 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7485 loss: 0.7485 2022/09/05 16:11:41 - mmengine - INFO - Epoch(train) [44][180/940] lr: 1.0000e-03 eta: 9:48:52 time: 0.6904 data_time: 0.1216 memory: 24011 grad_norm: 6.1267 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7412 loss: 0.7412 2022/09/05 16:11:53 - mmengine - INFO - Epoch(train) [44][200/940] lr: 1.0000e-03 eta: 9:48:38 time: 0.6104 data_time: 0.0339 memory: 24011 grad_norm: 5.1566 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7737 loss: 0.7737 2022/09/05 16:12:06 - mmengine - INFO - Epoch(train) [44][220/940] lr: 1.0000e-03 eta: 9:48:24 time: 0.6655 data_time: 0.0518 memory: 24011 grad_norm: 4.8328 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.7297 loss: 0.7297 2022/09/05 16:12:19 - mmengine - INFO - Epoch(train) [44][240/940] lr: 1.0000e-03 eta: 9:48:10 time: 0.6214 data_time: 0.0342 memory: 24011 grad_norm: 4.7604 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6874 loss: 0.6874 2022/09/05 16:12:32 - mmengine - INFO - Epoch(train) [44][260/940] lr: 1.0000e-03 eta: 9:47:57 time: 0.6753 data_time: 0.0525 memory: 24011 grad_norm: 5.6700 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7130 loss: 0.7130 2022/09/05 16:12:45 - mmengine - INFO - Epoch(train) [44][280/940] lr: 1.0000e-03 eta: 9:47:43 time: 0.6285 data_time: 0.0387 memory: 24011 grad_norm: 5.6698 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.7258 loss: 0.7258 2022/09/05 16:12:58 - mmengine - INFO - Epoch(train) [44][300/940] lr: 1.0000e-03 eta: 9:47:30 time: 0.6647 data_time: 0.0609 memory: 24011 grad_norm: 4.7265 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6575 loss: 0.6575 2022/09/05 16:13:11 - mmengine - INFO - Epoch(train) [44][320/940] lr: 1.0000e-03 eta: 9:47:16 time: 0.6178 data_time: 0.0422 memory: 24011 grad_norm: 4.7762 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7251 loss: 0.7251 2022/09/05 16:13:25 - mmengine - INFO - Epoch(train) [44][340/940] lr: 1.0000e-03 eta: 9:47:03 time: 0.6947 data_time: 0.0982 memory: 24011 grad_norm: 5.5129 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.7649 loss: 0.7649 2022/09/05 16:13:38 - mmengine - INFO - Epoch(train) [44][360/940] lr: 1.0000e-03 eta: 9:46:50 time: 0.6691 data_time: 0.0393 memory: 24011 grad_norm: 6.0420 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8058 loss: 0.8058 2022/09/05 16:13:51 - mmengine - INFO - Epoch(train) [44][380/940] lr: 1.0000e-03 eta: 9:46:37 time: 0.6430 data_time: 0.0371 memory: 24011 grad_norm: 4.8044 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.7585 loss: 0.7585 2022/09/05 16:14:04 - mmengine - INFO - Epoch(train) [44][400/940] lr: 1.0000e-03 eta: 9:46:23 time: 0.6471 data_time: 0.0319 memory: 24011 grad_norm: 5.4263 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8005 loss: 0.8005 2022/09/05 16:14:16 - mmengine - INFO - Epoch(train) [44][420/940] lr: 1.0000e-03 eta: 9:46:09 time: 0.6291 data_time: 0.0406 memory: 24011 grad_norm: 4.8311 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6792 loss: 0.6792 2022/09/05 16:14:29 - mmengine - INFO - Epoch(train) [44][440/940] lr: 1.0000e-03 eta: 9:45:56 time: 0.6557 data_time: 0.0379 memory: 24011 grad_norm: 4.5433 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.7253 loss: 0.7253 2022/09/05 16:14:42 - mmengine - INFO - Epoch(train) [44][460/940] lr: 1.0000e-03 eta: 9:45:41 time: 0.6278 data_time: 0.0370 memory: 24011 grad_norm: 5.9832 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6696 loss: 0.6696 2022/09/05 16:14:55 - mmengine - INFO - Epoch(train) [44][480/940] lr: 1.0000e-03 eta: 9:45:28 time: 0.6684 data_time: 0.0894 memory: 24011 grad_norm: 5.5067 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.8472 loss: 0.8472 2022/09/05 16:15:08 - mmengine - INFO - Epoch(train) [44][500/940] lr: 1.0000e-03 eta: 9:45:15 time: 0.6396 data_time: 0.0648 memory: 24011 grad_norm: 4.7546 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7798 loss: 0.7798 2022/09/05 16:15:21 - mmengine - INFO - Epoch(train) [44][520/940] lr: 1.0000e-03 eta: 9:45:01 time: 0.6649 data_time: 0.0548 memory: 24011 grad_norm: 4.6331 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7677 loss: 0.7677 2022/09/05 16:15:34 - mmengine - INFO - Epoch(train) [44][540/940] lr: 1.0000e-03 eta: 9:44:47 time: 0.6247 data_time: 0.0390 memory: 24011 grad_norm: 4.8304 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8284 loss: 0.8284 2022/09/05 16:15:47 - mmengine - INFO - Epoch(train) [44][560/940] lr: 1.0000e-03 eta: 9:44:33 time: 0.6272 data_time: 0.0425 memory: 24011 grad_norm: 5.0615 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6893 loss: 0.6893 2022/09/05 16:15:59 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:15:59 - mmengine - INFO - Epoch(train) [44][580/940] lr: 1.0000e-03 eta: 9:44:19 time: 0.6400 data_time: 0.0403 memory: 24011 grad_norm: 5.0344 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7318 loss: 0.7318 2022/09/05 16:16:12 - mmengine - INFO - Epoch(train) [44][600/940] lr: 1.0000e-03 eta: 9:44:06 time: 0.6518 data_time: 0.0354 memory: 24011 grad_norm: 4.8716 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7104 loss: 0.7104 2022/09/05 16:16:25 - mmengine - INFO - Epoch(train) [44][620/940] lr: 1.0000e-03 eta: 9:43:52 time: 0.6493 data_time: 0.0412 memory: 24011 grad_norm: 4.6328 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.7442 loss: 0.7442 2022/09/05 16:16:39 - mmengine - INFO - Epoch(train) [44][640/940] lr: 1.0000e-03 eta: 9:43:39 time: 0.6713 data_time: 0.0351 memory: 24011 grad_norm: 5.5642 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7695 loss: 0.7695 2022/09/05 16:16:52 - mmengine - INFO - Epoch(train) [44][660/940] lr: 1.0000e-03 eta: 9:43:26 time: 0.6395 data_time: 0.0504 memory: 24011 grad_norm: 4.5276 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7353 loss: 0.7353 2022/09/05 16:17:04 - mmengine - INFO - Epoch(train) [44][680/940] lr: 1.0000e-03 eta: 9:43:11 time: 0.6096 data_time: 0.0432 memory: 24011 grad_norm: 7.2833 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7406 loss: 0.7406 2022/09/05 16:17:17 - mmengine - INFO - Epoch(train) [44][700/940] lr: 1.0000e-03 eta: 9:42:58 time: 0.6733 data_time: 0.0990 memory: 24011 grad_norm: 4.5009 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7784 loss: 0.7784 2022/09/05 16:17:31 - mmengine - INFO - Epoch(train) [44][720/940] lr: 1.0000e-03 eta: 9:42:45 time: 0.6731 data_time: 0.0612 memory: 24011 grad_norm: 5.1753 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7844 loss: 0.7844 2022/09/05 16:17:43 - mmengine - INFO - Epoch(train) [44][740/940] lr: 1.0000e-03 eta: 9:42:31 time: 0.6316 data_time: 0.0381 memory: 24011 grad_norm: 4.9296 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7872 loss: 0.7872 2022/09/05 16:17:56 - mmengine - INFO - Epoch(train) [44][760/940] lr: 1.0000e-03 eta: 9:42:17 time: 0.6327 data_time: 0.0418 memory: 24011 grad_norm: 4.8178 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8149 loss: 0.8149 2022/09/05 16:18:08 - mmengine - INFO - Epoch(train) [44][780/940] lr: 1.0000e-03 eta: 9:42:02 time: 0.6045 data_time: 0.0406 memory: 24011 grad_norm: 5.0872 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7646 loss: 0.7646 2022/09/05 16:18:22 - mmengine - INFO - Epoch(train) [44][800/940] lr: 1.0000e-03 eta: 9:41:50 time: 0.7054 data_time: 0.0421 memory: 24011 grad_norm: 5.1734 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7552 loss: 0.7552 2022/09/05 16:18:35 - mmengine - INFO - Epoch(train) [44][820/940] lr: 1.0000e-03 eta: 9:41:37 time: 0.6381 data_time: 0.0462 memory: 24011 grad_norm: 4.9085 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8706 loss: 0.8706 2022/09/05 16:18:48 - mmengine - INFO - Epoch(train) [44][840/940] lr: 1.0000e-03 eta: 9:41:23 time: 0.6677 data_time: 0.0439 memory: 24011 grad_norm: 4.9755 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7281 loss: 0.7281 2022/09/05 16:19:01 - mmengine - INFO - Epoch(train) [44][860/940] lr: 1.0000e-03 eta: 9:41:10 time: 0.6407 data_time: 0.0343 memory: 24011 grad_norm: 5.0892 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7717 loss: 0.7717 2022/09/05 16:19:14 - mmengine - INFO - Epoch(train) [44][880/940] lr: 1.0000e-03 eta: 9:40:56 time: 0.6335 data_time: 0.0400 memory: 24011 grad_norm: 4.6748 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7566 loss: 0.7566 2022/09/05 16:19:27 - mmengine - INFO - Epoch(train) [44][900/940] lr: 1.0000e-03 eta: 9:40:42 time: 0.6532 data_time: 0.0413 memory: 24011 grad_norm: 4.9345 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8130 loss: 0.8130 2022/09/05 16:19:41 - mmengine - INFO - Epoch(train) [44][920/940] lr: 1.0000e-03 eta: 9:40:30 time: 0.6865 data_time: 0.0913 memory: 24011 grad_norm: 4.7067 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7315 loss: 0.7315 2022/09/05 16:19:52 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:19:52 - mmengine - INFO - Epoch(train) [44][940/940] lr: 1.0000e-03 eta: 9:40:14 time: 0.5483 data_time: 0.0227 memory: 24011 grad_norm: 4.9314 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.7041 loss: 0.7041 2022/09/05 16:20:06 - mmengine - INFO - Epoch(val) [44][20/78] eta: 0:00:40 time: 0.6943 data_time: 0.5382 memory: 3625 2022/09/05 16:20:15 - mmengine - INFO - Epoch(val) [44][40/78] eta: 0:00:17 time: 0.4642 data_time: 0.3076 memory: 3625 2022/09/05 16:20:28 - mmengine - INFO - Epoch(val) [44][60/78] eta: 0:00:11 time: 0.6488 data_time: 0.4880 memory: 3625 2022/09/05 16:20:39 - mmengine - INFO - Epoch(val) [44][78/78] acc/top1: 0.7373 acc/top5: 0.9075 acc/mean1: 0.7371 2022/09/05 16:20:57 - mmengine - INFO - Epoch(train) [45][20/940] lr: 1.0000e-03 eta: 9:40:07 time: 0.9126 data_time: 0.2931 memory: 24011 grad_norm: 4.6456 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.7084 loss: 0.7084 2022/09/05 16:21:09 - mmengine - INFO - Epoch(train) [45][40/940] lr: 1.0000e-03 eta: 9:39:52 time: 0.6035 data_time: 0.0409 memory: 24011 grad_norm: 4.7196 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6567 loss: 0.6567 2022/09/05 16:21:23 - mmengine - INFO - Epoch(train) [45][60/940] lr: 1.0000e-03 eta: 9:39:39 time: 0.6766 data_time: 0.0382 memory: 24011 grad_norm: 4.9182 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8121 loss: 0.8121 2022/09/05 16:21:36 - mmengine - INFO - Epoch(train) [45][80/940] lr: 1.0000e-03 eta: 9:39:26 time: 0.6527 data_time: 0.0362 memory: 24011 grad_norm: 4.7021 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7193 loss: 0.7193 2022/09/05 16:21:50 - mmengine - INFO - Epoch(train) [45][100/940] lr: 1.0000e-03 eta: 9:39:14 time: 0.7107 data_time: 0.0399 memory: 24011 grad_norm: 5.3194 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7401 loss: 0.7401 2022/09/05 16:22:03 - mmengine - INFO - Epoch(train) [45][120/940] lr: 1.0000e-03 eta: 9:39:00 time: 0.6388 data_time: 0.0406 memory: 24011 grad_norm: 4.7086 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.7029 loss: 0.7029 2022/09/05 16:22:16 - mmengine - INFO - Epoch(train) [45][140/940] lr: 1.0000e-03 eta: 9:38:47 time: 0.6595 data_time: 0.0393 memory: 24011 grad_norm: 5.1314 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6937 loss: 0.6937 2022/09/05 16:22:29 - mmengine - INFO - Epoch(train) [45][160/940] lr: 1.0000e-03 eta: 9:38:33 time: 0.6532 data_time: 0.0355 memory: 24011 grad_norm: 4.7952 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7557 loss: 0.7557 2022/09/05 16:22:41 - mmengine - INFO - Epoch(train) [45][180/940] lr: 1.0000e-03 eta: 9:38:19 time: 0.6108 data_time: 0.0387 memory: 24011 grad_norm: 5.5045 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7046 loss: 0.7046 2022/09/05 16:22:54 - mmengine - INFO - Epoch(train) [45][200/940] lr: 1.0000e-03 eta: 9:38:05 time: 0.6444 data_time: 0.0363 memory: 24011 grad_norm: 4.5758 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6551 loss: 0.6551 2022/09/05 16:23:08 - mmengine - INFO - Epoch(train) [45][220/940] lr: 1.0000e-03 eta: 9:37:52 time: 0.6778 data_time: 0.0412 memory: 24011 grad_norm: 4.9002 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8142 loss: 0.8142 2022/09/05 16:23:20 - mmengine - INFO - Epoch(train) [45][240/940] lr: 1.0000e-03 eta: 9:37:38 time: 0.6127 data_time: 0.0332 memory: 24011 grad_norm: 5.0772 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7835 loss: 0.7835 2022/09/05 16:23:34 - mmengine - INFO - Epoch(train) [45][260/940] lr: 1.0000e-03 eta: 9:37:25 time: 0.6927 data_time: 0.0416 memory: 24011 grad_norm: 4.6779 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7412 loss: 0.7412 2022/09/05 16:23:47 - mmengine - INFO - Epoch(train) [45][280/940] lr: 1.0000e-03 eta: 9:37:12 time: 0.6395 data_time: 0.0434 memory: 24011 grad_norm: 5.0726 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7624 loss: 0.7624 2022/09/05 16:24:01 - mmengine - INFO - Epoch(train) [45][300/940] lr: 1.0000e-03 eta: 9:37:00 time: 0.7207 data_time: 0.0389 memory: 24011 grad_norm: 4.7563 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7896 loss: 0.7896 2022/09/05 16:24:13 - mmengine - INFO - Epoch(train) [45][320/940] lr: 1.0000e-03 eta: 9:36:45 time: 0.5943 data_time: 0.0387 memory: 24011 grad_norm: 5.5909 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8112 loss: 0.8112 2022/09/05 16:24:26 - mmengine - INFO - Epoch(train) [45][340/940] lr: 1.0000e-03 eta: 9:36:32 time: 0.6661 data_time: 0.0432 memory: 24011 grad_norm: 4.7619 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.7961 loss: 0.7961 2022/09/05 16:24:39 - mmengine - INFO - Epoch(train) [45][360/940] lr: 1.0000e-03 eta: 9:36:17 time: 0.6098 data_time: 0.0382 memory: 24011 grad_norm: 4.4851 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8151 loss: 0.8151 2022/09/05 16:24:52 - mmengine - INFO - Epoch(train) [45][380/940] lr: 1.0000e-03 eta: 9:36:04 time: 0.6551 data_time: 0.0559 memory: 24011 grad_norm: 4.6523 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7264 loss: 0.7264 2022/09/05 16:25:04 - mmengine - INFO - Epoch(train) [45][400/940] lr: 1.0000e-03 eta: 9:35:49 time: 0.5958 data_time: 0.0375 memory: 24011 grad_norm: 4.8506 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.7712 loss: 0.7712 2022/09/05 16:25:16 - mmengine - INFO - Epoch(train) [45][420/940] lr: 1.0000e-03 eta: 9:35:35 time: 0.6168 data_time: 0.0450 memory: 24011 grad_norm: 4.6482 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6436 loss: 0.6436 2022/09/05 16:25:30 - mmengine - INFO - Epoch(train) [45][440/940] lr: 1.0000e-03 eta: 9:35:22 time: 0.6890 data_time: 0.0437 memory: 24011 grad_norm: 4.6702 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7087 loss: 0.7087 2022/09/05 16:25:43 - mmengine - INFO - Epoch(train) [45][460/940] lr: 1.0000e-03 eta: 9:35:09 time: 0.6628 data_time: 0.0398 memory: 24011 grad_norm: 4.6642 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7083 loss: 0.7083 2022/09/05 16:25:56 - mmengine - INFO - Epoch(train) [45][480/940] lr: 1.0000e-03 eta: 9:34:55 time: 0.6345 data_time: 0.0377 memory: 24011 grad_norm: 4.6912 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.7793 loss: 0.7793 2022/09/05 16:26:09 - mmengine - INFO - Epoch(train) [45][500/940] lr: 1.0000e-03 eta: 9:34:42 time: 0.6509 data_time: 0.0453 memory: 24011 grad_norm: 4.7567 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.8259 loss: 0.8259 2022/09/05 16:26:22 - mmengine - INFO - Epoch(train) [45][520/940] lr: 1.0000e-03 eta: 9:34:29 time: 0.6677 data_time: 0.0426 memory: 24011 grad_norm: 5.1835 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8010 loss: 0.8010 2022/09/05 16:26:35 - mmengine - INFO - Epoch(train) [45][540/940] lr: 1.0000e-03 eta: 9:34:15 time: 0.6618 data_time: 0.0480 memory: 24011 grad_norm: 4.8989 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.7451 loss: 0.7451 2022/09/05 16:26:49 - mmengine - INFO - Epoch(train) [45][560/940] lr: 1.0000e-03 eta: 9:34:02 time: 0.6631 data_time: 0.0392 memory: 24011 grad_norm: 4.7784 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7659 loss: 0.7659 2022/09/05 16:27:02 - mmengine - INFO - Epoch(train) [45][580/940] lr: 1.0000e-03 eta: 9:33:49 time: 0.6684 data_time: 0.0361 memory: 24011 grad_norm: 4.5225 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6678 loss: 0.6678 2022/09/05 16:27:14 - mmengine - INFO - Epoch(train) [45][600/940] lr: 1.0000e-03 eta: 9:33:35 time: 0.6169 data_time: 0.0402 memory: 24011 grad_norm: 4.8743 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8144 loss: 0.8144 2022/09/05 16:27:27 - mmengine - INFO - Epoch(train) [45][620/940] lr: 1.0000e-03 eta: 9:33:20 time: 0.6169 data_time: 0.0464 memory: 24011 grad_norm: 4.7317 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6246 loss: 0.6246 2022/09/05 16:27:40 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:27:40 - mmengine - INFO - Epoch(train) [45][640/940] lr: 1.0000e-03 eta: 9:33:07 time: 0.6601 data_time: 0.0454 memory: 24011 grad_norm: 5.2901 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8264 loss: 0.8264 2022/09/05 16:27:53 - mmengine - INFO - Epoch(train) [45][660/940] lr: 1.0000e-03 eta: 9:32:54 time: 0.6467 data_time: 0.0368 memory: 24011 grad_norm: 4.7011 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7839 loss: 0.7839 2022/09/05 16:28:06 - mmengine - INFO - Epoch(train) [45][680/940] lr: 1.0000e-03 eta: 9:32:40 time: 0.6649 data_time: 0.0411 memory: 24011 grad_norm: 4.5692 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7521 loss: 0.7521 2022/09/05 16:28:19 - mmengine - INFO - Epoch(train) [45][700/940] lr: 1.0000e-03 eta: 9:32:27 time: 0.6396 data_time: 0.0411 memory: 24011 grad_norm: 4.6252 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.7173 loss: 0.7173 2022/09/05 16:28:32 - mmengine - INFO - Epoch(train) [45][720/940] lr: 1.0000e-03 eta: 9:32:13 time: 0.6534 data_time: 0.0517 memory: 24011 grad_norm: 4.7601 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6831 loss: 0.6831 2022/09/05 16:28:45 - mmengine - INFO - Epoch(train) [45][740/940] lr: 1.0000e-03 eta: 9:32:00 time: 0.6488 data_time: 0.0382 memory: 24011 grad_norm: 4.8641 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7843 loss: 0.7843 2022/09/05 16:28:58 - mmengine - INFO - Epoch(train) [45][760/940] lr: 1.0000e-03 eta: 9:31:46 time: 0.6568 data_time: 0.0574 memory: 24011 grad_norm: 4.5877 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6553 loss: 0.6553 2022/09/05 16:29:11 - mmengine - INFO - Epoch(train) [45][780/940] lr: 1.0000e-03 eta: 9:31:32 time: 0.6319 data_time: 0.0520 memory: 24011 grad_norm: 5.1174 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7577 loss: 0.7577 2022/09/05 16:29:24 - mmengine - INFO - Epoch(train) [45][800/940] lr: 1.0000e-03 eta: 9:31:19 time: 0.6457 data_time: 0.0387 memory: 24011 grad_norm: 4.7594 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6794 loss: 0.6794 2022/09/05 16:29:37 - mmengine - INFO - Epoch(train) [45][820/940] lr: 1.0000e-03 eta: 9:31:06 time: 0.6598 data_time: 0.0358 memory: 24011 grad_norm: 4.5622 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7163 loss: 0.7163 2022/09/05 16:29:51 - mmengine - INFO - Epoch(train) [45][840/940] lr: 1.0000e-03 eta: 9:30:53 time: 0.6938 data_time: 0.0365 memory: 24011 grad_norm: 4.4276 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7024 loss: 0.7024 2022/09/05 16:30:03 - mmengine - INFO - Epoch(train) [45][860/940] lr: 1.0000e-03 eta: 9:30:38 time: 0.5970 data_time: 0.0370 memory: 24011 grad_norm: 5.8631 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.7224 loss: 0.7224 2022/09/05 16:30:15 - mmengine - INFO - Epoch(train) [45][880/940] lr: 1.0000e-03 eta: 9:30:24 time: 0.6298 data_time: 0.0411 memory: 24011 grad_norm: 4.5062 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.7389 loss: 0.7389 2022/09/05 16:30:29 - mmengine - INFO - Epoch(train) [45][900/940] lr: 1.0000e-03 eta: 9:30:11 time: 0.6616 data_time: 0.0389 memory: 24011 grad_norm: 5.1105 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7550 loss: 0.7550 2022/09/05 16:30:42 - mmengine - INFO - Epoch(train) [45][920/940] lr: 1.0000e-03 eta: 9:29:58 time: 0.6507 data_time: 0.0544 memory: 24011 grad_norm: 5.0304 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7611 loss: 0.7611 2022/09/05 16:30:53 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:30:53 - mmengine - INFO - Epoch(train) [45][940/940] lr: 1.0000e-03 eta: 9:29:42 time: 0.5715 data_time: 0.0304 memory: 24011 grad_norm: 5.5181 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 0.8294 loss: 0.8294 2022/09/05 16:30:53 - mmengine - INFO - Saving checkpoint at 45 epochs 2022/09/05 16:31:12 - mmengine - INFO - Epoch(val) [45][20/78] eta: 0:00:40 time: 0.7040 data_time: 0.5434 memory: 3625 2022/09/05 16:31:22 - mmengine - INFO - Epoch(val) [45][40/78] eta: 0:00:17 time: 0.4682 data_time: 0.3144 memory: 3625 2022/09/05 16:31:34 - mmengine - INFO - Epoch(val) [45][60/78] eta: 0:00:11 time: 0.6364 data_time: 0.4811 memory: 3625 2022/09/05 16:31:44 - mmengine - INFO - Epoch(val) [45][78/78] acc/top1: 0.7369 acc/top5: 0.9080 acc/mean1: 0.7368 2022/09/05 16:32:02 - mmengine - INFO - Epoch(train) [46][20/940] lr: 1.0000e-03 eta: 9:29:35 time: 0.8987 data_time: 0.3274 memory: 24011 grad_norm: 4.8380 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7159 loss: 0.7159 2022/09/05 16:32:14 - mmengine - INFO - Epoch(train) [46][40/940] lr: 1.0000e-03 eta: 9:29:20 time: 0.6132 data_time: 0.0390 memory: 24011 grad_norm: 4.7882 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6224 loss: 0.6224 2022/09/05 16:32:28 - mmengine - INFO - Epoch(train) [46][60/940] lr: 1.0000e-03 eta: 9:29:08 time: 0.6774 data_time: 0.0392 memory: 24011 grad_norm: 4.5346 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7519 loss: 0.7519 2022/09/05 16:32:41 - mmengine - INFO - Epoch(train) [46][80/940] lr: 1.0000e-03 eta: 9:28:55 time: 0.6764 data_time: 0.0458 memory: 24011 grad_norm: 4.6641 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8072 loss: 0.8072 2022/09/05 16:32:55 - mmengine - INFO - Epoch(train) [46][100/940] lr: 1.0000e-03 eta: 9:28:42 time: 0.6634 data_time: 0.0506 memory: 24011 grad_norm: 4.7310 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7535 loss: 0.7535 2022/09/05 16:33:07 - mmengine - INFO - Epoch(train) [46][120/940] lr: 1.0000e-03 eta: 9:28:27 time: 0.6138 data_time: 0.0385 memory: 24011 grad_norm: 4.8308 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7602 loss: 0.7602 2022/09/05 16:33:20 - mmengine - INFO - Epoch(train) [46][140/940] lr: 1.0000e-03 eta: 9:28:13 time: 0.6403 data_time: 0.0391 memory: 24011 grad_norm: 4.7687 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7722 loss: 0.7722 2022/09/05 16:33:33 - mmengine - INFO - Epoch(train) [46][160/940] lr: 1.0000e-03 eta: 9:28:00 time: 0.6380 data_time: 0.0382 memory: 24011 grad_norm: 5.2166 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7148 loss: 0.7148 2022/09/05 16:33:46 - mmengine - INFO - Epoch(train) [46][180/940] lr: 1.0000e-03 eta: 9:27:47 time: 0.6759 data_time: 0.0384 memory: 24011 grad_norm: 4.3845 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6917 loss: 0.6917 2022/09/05 16:33:59 - mmengine - INFO - Epoch(train) [46][200/940] lr: 1.0000e-03 eta: 9:27:33 time: 0.6562 data_time: 0.0394 memory: 24011 grad_norm: 5.9300 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6575 loss: 0.6575 2022/09/05 16:34:12 - mmengine - INFO - Epoch(train) [46][220/940] lr: 1.0000e-03 eta: 9:27:20 time: 0.6539 data_time: 0.0346 memory: 24011 grad_norm: 4.6230 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6453 loss: 0.6453 2022/09/05 16:34:26 - mmengine - INFO - Epoch(train) [46][240/940] lr: 1.0000e-03 eta: 9:27:07 time: 0.6540 data_time: 0.0387 memory: 24011 grad_norm: 4.7355 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.7523 loss: 0.7523 2022/09/05 16:34:39 - mmengine - INFO - Epoch(train) [46][260/940] lr: 1.0000e-03 eta: 9:26:53 time: 0.6458 data_time: 0.0391 memory: 24011 grad_norm: 4.4513 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.6458 loss: 0.6458 2022/09/05 16:34:51 - mmengine - INFO - Epoch(train) [46][280/940] lr: 1.0000e-03 eta: 9:26:39 time: 0.6264 data_time: 0.0455 memory: 24011 grad_norm: 4.5237 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8005 loss: 0.8005 2022/09/05 16:35:04 - mmengine - INFO - Epoch(train) [46][300/940] lr: 1.0000e-03 eta: 9:26:26 time: 0.6730 data_time: 0.0353 memory: 24011 grad_norm: 4.7881 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8265 loss: 0.8265 2022/09/05 16:35:17 - mmengine - INFO - Epoch(train) [46][320/940] lr: 1.0000e-03 eta: 9:26:12 time: 0.6392 data_time: 0.0385 memory: 24011 grad_norm: 4.7646 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7428 loss: 0.7428 2022/09/05 16:35:30 - mmengine - INFO - Epoch(train) [46][340/940] lr: 1.0000e-03 eta: 9:25:59 time: 0.6582 data_time: 0.0341 memory: 24011 grad_norm: 4.7650 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6838 loss: 0.6838 2022/09/05 16:35:43 - mmengine - INFO - Epoch(train) [46][360/940] lr: 1.0000e-03 eta: 9:25:45 time: 0.6468 data_time: 0.0525 memory: 24011 grad_norm: 4.6139 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6849 loss: 0.6849 2022/09/05 16:35:56 - mmengine - INFO - Epoch(train) [46][380/940] lr: 1.0000e-03 eta: 9:25:32 time: 0.6432 data_time: 0.0392 memory: 24011 grad_norm: 4.4898 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6382 loss: 0.6382 2022/09/05 16:36:10 - mmengine - INFO - Epoch(train) [46][400/940] lr: 1.0000e-03 eta: 9:25:19 time: 0.6760 data_time: 0.0398 memory: 24011 grad_norm: 4.7254 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6614 loss: 0.6614 2022/09/05 16:36:22 - mmengine - INFO - Epoch(train) [46][420/940] lr: 1.0000e-03 eta: 9:25:05 time: 0.6267 data_time: 0.0386 memory: 24011 grad_norm: 4.5877 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.8430 loss: 0.8430 2022/09/05 16:36:35 - mmengine - INFO - Epoch(train) [46][440/940] lr: 1.0000e-03 eta: 9:24:51 time: 0.6365 data_time: 0.0440 memory: 24011 grad_norm: 4.8066 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7191 loss: 0.7191 2022/09/05 16:36:48 - mmengine - INFO - Epoch(train) [46][460/940] lr: 1.0000e-03 eta: 9:24:37 time: 0.6332 data_time: 0.0307 memory: 24011 grad_norm: 4.7968 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6940 loss: 0.6940 2022/09/05 16:37:01 - mmengine - INFO - Epoch(train) [46][480/940] lr: 1.0000e-03 eta: 9:24:24 time: 0.6462 data_time: 0.0436 memory: 24011 grad_norm: 4.5994 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7217 loss: 0.7217 2022/09/05 16:37:13 - mmengine - INFO - Epoch(train) [46][500/940] lr: 1.0000e-03 eta: 9:24:09 time: 0.6226 data_time: 0.0377 memory: 24011 grad_norm: 4.8094 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7318 loss: 0.7318 2022/09/05 16:37:26 - mmengine - INFO - Epoch(train) [46][520/940] lr: 1.0000e-03 eta: 9:23:56 time: 0.6569 data_time: 0.0897 memory: 24011 grad_norm: 5.1145 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7687 loss: 0.7687 2022/09/05 16:37:39 - mmengine - INFO - Epoch(train) [46][540/940] lr: 1.0000e-03 eta: 9:23:43 time: 0.6505 data_time: 0.0532 memory: 24011 grad_norm: 5.1341 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6951 loss: 0.6951 2022/09/05 16:37:52 - mmengine - INFO - Epoch(train) [46][560/940] lr: 1.0000e-03 eta: 9:23:29 time: 0.6243 data_time: 0.0625 memory: 24011 grad_norm: 4.7454 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7626 loss: 0.7626 2022/09/05 16:38:05 - mmengine - INFO - Epoch(train) [46][580/940] lr: 1.0000e-03 eta: 9:23:16 time: 0.6821 data_time: 0.0841 memory: 24011 grad_norm: 4.3847 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6626 loss: 0.6626 2022/09/05 16:38:19 - mmengine - INFO - Epoch(train) [46][600/940] lr: 1.0000e-03 eta: 9:23:03 time: 0.6793 data_time: 0.0711 memory: 24011 grad_norm: 4.6823 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6666 loss: 0.6666 2022/09/05 16:38:32 - mmengine - INFO - Epoch(train) [46][620/940] lr: 1.0000e-03 eta: 9:22:49 time: 0.6364 data_time: 0.0567 memory: 24011 grad_norm: 4.9737 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6655 loss: 0.6655 2022/09/05 16:38:45 - mmengine - INFO - Epoch(train) [46][640/940] lr: 1.0000e-03 eta: 9:22:37 time: 0.6937 data_time: 0.1099 memory: 24011 grad_norm: 4.8590 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7217 loss: 0.7217 2022/09/05 16:38:58 - mmengine - INFO - Epoch(train) [46][660/940] lr: 1.0000e-03 eta: 9:22:23 time: 0.6440 data_time: 0.0414 memory: 24011 grad_norm: 4.5174 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6529 loss: 0.6529 2022/09/05 16:39:11 - mmengine - INFO - Epoch(train) [46][680/940] lr: 1.0000e-03 eta: 9:22:09 time: 0.6337 data_time: 0.0514 memory: 24011 grad_norm: 4.8667 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6855 loss: 0.6855 2022/09/05 16:39:23 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:39:23 - mmengine - INFO - Epoch(train) [46][700/940] lr: 1.0000e-03 eta: 9:21:55 time: 0.6066 data_time: 0.0272 memory: 24011 grad_norm: 4.7116 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7527 loss: 0.7527 2022/09/05 16:39:36 - mmengine - INFO - Epoch(train) [46][720/940] lr: 1.0000e-03 eta: 9:21:42 time: 0.6645 data_time: 0.0793 memory: 24011 grad_norm: 4.7846 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6879 loss: 0.6879 2022/09/05 16:39:49 - mmengine - INFO - Epoch(train) [46][740/940] lr: 1.0000e-03 eta: 9:21:28 time: 0.6314 data_time: 0.0295 memory: 24011 grad_norm: 4.9250 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7490 loss: 0.7490 2022/09/05 16:40:02 - mmengine - INFO - Epoch(train) [46][760/940] lr: 1.0000e-03 eta: 9:21:15 time: 0.6673 data_time: 0.0363 memory: 24011 grad_norm: 5.0711 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.7599 loss: 0.7599 2022/09/05 16:40:15 - mmengine - INFO - Epoch(train) [46][780/940] lr: 1.0000e-03 eta: 9:21:01 time: 0.6279 data_time: 0.0333 memory: 24011 grad_norm: 5.2272 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7661 loss: 0.7661 2022/09/05 16:40:28 - mmengine - INFO - Epoch(train) [46][800/940] lr: 1.0000e-03 eta: 9:20:47 time: 0.6575 data_time: 0.0482 memory: 24011 grad_norm: 4.8886 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6756 loss: 0.6756 2022/09/05 16:40:41 - mmengine - INFO - Epoch(train) [46][820/940] lr: 1.0000e-03 eta: 9:20:33 time: 0.6318 data_time: 0.0510 memory: 24011 grad_norm: 5.1404 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7285 loss: 0.7285 2022/09/05 16:40:54 - mmengine - INFO - Epoch(train) [46][840/940] lr: 1.0000e-03 eta: 9:20:20 time: 0.6470 data_time: 0.0409 memory: 24011 grad_norm: 4.5722 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7703 loss: 0.7703 2022/09/05 16:41:07 - mmengine - INFO - Epoch(train) [46][860/940] lr: 1.0000e-03 eta: 9:20:07 time: 0.6649 data_time: 0.0373 memory: 24011 grad_norm: 4.5431 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7837 loss: 0.7837 2022/09/05 16:41:20 - mmengine - INFO - Epoch(train) [46][880/940] lr: 1.0000e-03 eta: 9:19:53 time: 0.6214 data_time: 0.0459 memory: 24011 grad_norm: 5.2302 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8449 loss: 0.8449 2022/09/05 16:41:32 - mmengine - INFO - Epoch(train) [46][900/940] lr: 1.0000e-03 eta: 9:19:39 time: 0.6271 data_time: 0.0386 memory: 24011 grad_norm: 4.7090 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7457 loss: 0.7457 2022/09/05 16:41:45 - mmengine - INFO - Epoch(train) [46][920/940] lr: 1.0000e-03 eta: 9:19:25 time: 0.6576 data_time: 0.0437 memory: 24011 grad_norm: 4.4853 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7054 loss: 0.7054 2022/09/05 16:41:56 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:41:56 - mmengine - INFO - Epoch(train) [46][940/940] lr: 1.0000e-03 eta: 9:19:10 time: 0.5580 data_time: 0.0257 memory: 24011 grad_norm: 5.0479 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.7988 loss: 0.7988 2022/09/05 16:42:10 - mmengine - INFO - Epoch(val) [46][20/78] eta: 0:00:39 time: 0.6821 data_time: 0.5224 memory: 3625 2022/09/05 16:42:20 - mmengine - INFO - Epoch(val) [46][40/78] eta: 0:00:17 time: 0.4731 data_time: 0.3133 memory: 3625 2022/09/05 16:42:32 - mmengine - INFO - Epoch(val) [46][60/78] eta: 0:00:11 time: 0.6384 data_time: 0.4795 memory: 3625 2022/09/05 16:42:43 - mmengine - INFO - Epoch(val) [46][78/78] acc/top1: 0.7396 acc/top5: 0.9096 acc/mean1: 0.7395 2022/09/05 16:42:43 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_44.pth is removed 2022/09/05 16:42:46 - mmengine - INFO - The best checkpoint with 0.7396 acc/top1 at 47 epoch is saved to best_acc/top1_epoch_47.pth. 2022/09/05 16:43:03 - mmengine - INFO - Epoch(train) [47][20/940] lr: 1.0000e-03 eta: 9:19:00 time: 0.8327 data_time: 0.2731 memory: 24011 grad_norm: 4.8461 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7891 loss: 0.7891 2022/09/05 16:43:15 - mmengine - INFO - Epoch(train) [47][40/940] lr: 1.0000e-03 eta: 9:18:46 time: 0.6214 data_time: 0.0684 memory: 24011 grad_norm: 4.9280 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6845 loss: 0.6845 2022/09/05 16:43:29 - mmengine - INFO - Epoch(train) [47][60/940] lr: 1.0000e-03 eta: 9:18:33 time: 0.6607 data_time: 0.1052 memory: 24011 grad_norm: 4.8019 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.7570 loss: 0.7570 2022/09/05 16:43:41 - mmengine - INFO - Epoch(train) [47][80/940] lr: 1.0000e-03 eta: 9:18:19 time: 0.6304 data_time: 0.0691 memory: 24011 grad_norm: 4.7050 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7413 loss: 0.7413 2022/09/05 16:43:55 - mmengine - INFO - Epoch(train) [47][100/940] lr: 1.0000e-03 eta: 9:18:07 time: 0.6973 data_time: 0.1145 memory: 24011 grad_norm: 4.7634 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7513 loss: 0.7513 2022/09/05 16:44:08 - mmengine - INFO - Epoch(train) [47][120/940] lr: 1.0000e-03 eta: 9:17:53 time: 0.6450 data_time: 0.0601 memory: 24011 grad_norm: 4.6946 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7252 loss: 0.7252 2022/09/05 16:44:21 - mmengine - INFO - Epoch(train) [47][140/940] lr: 1.0000e-03 eta: 9:17:40 time: 0.6496 data_time: 0.0669 memory: 24011 grad_norm: 5.3474 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7976 loss: 0.7976 2022/09/05 16:44:34 - mmengine - INFO - Epoch(train) [47][160/940] lr: 1.0000e-03 eta: 9:17:27 time: 0.6686 data_time: 0.1080 memory: 24011 grad_norm: 4.4664 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7514 loss: 0.7514 2022/09/05 16:44:48 - mmengine - INFO - Epoch(train) [47][180/940] lr: 1.0000e-03 eta: 9:17:14 time: 0.6772 data_time: 0.1120 memory: 24011 grad_norm: 5.1154 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6658 loss: 0.6658 2022/09/05 16:45:00 - mmengine - INFO - Epoch(train) [47][200/940] lr: 1.0000e-03 eta: 9:16:59 time: 0.6032 data_time: 0.0484 memory: 24011 grad_norm: 4.7047 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6965 loss: 0.6965 2022/09/05 16:45:13 - mmengine - INFO - Epoch(train) [47][220/940] lr: 1.0000e-03 eta: 9:16:46 time: 0.6627 data_time: 0.0959 memory: 24011 grad_norm: 4.6640 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7494 loss: 0.7494 2022/09/05 16:45:26 - mmengine - INFO - Epoch(train) [47][240/940] lr: 1.0000e-03 eta: 9:16:32 time: 0.6261 data_time: 0.0651 memory: 24011 grad_norm: 4.7785 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6321 loss: 0.6321 2022/09/05 16:45:39 - mmengine - INFO - Epoch(train) [47][260/940] lr: 1.0000e-03 eta: 9:16:19 time: 0.6600 data_time: 0.0927 memory: 24011 grad_norm: 4.9506 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8351 loss: 0.8351 2022/09/05 16:45:52 - mmengine - INFO - Epoch(train) [47][280/940] lr: 1.0000e-03 eta: 9:16:05 time: 0.6498 data_time: 0.0764 memory: 24011 grad_norm: 4.7193 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.7248 loss: 0.7248 2022/09/05 16:46:05 - mmengine - INFO - Epoch(train) [47][300/940] lr: 1.0000e-03 eta: 9:15:52 time: 0.6463 data_time: 0.0801 memory: 24011 grad_norm: 4.6126 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6965 loss: 0.6965 2022/09/05 16:46:18 - mmengine - INFO - Epoch(train) [47][320/940] lr: 1.0000e-03 eta: 9:15:38 time: 0.6455 data_time: 0.0798 memory: 24011 grad_norm: 4.5291 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7342 loss: 0.7342 2022/09/05 16:46:32 - mmengine - INFO - Epoch(train) [47][340/940] lr: 1.0000e-03 eta: 9:15:26 time: 0.6881 data_time: 0.0808 memory: 24011 grad_norm: 4.8242 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8178 loss: 0.8178 2022/09/05 16:46:44 - mmengine - INFO - Epoch(train) [47][360/940] lr: 1.0000e-03 eta: 9:15:11 time: 0.6020 data_time: 0.0385 memory: 24011 grad_norm: 4.4806 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7204 loss: 0.7204 2022/09/05 16:46:56 - mmengine - INFO - Epoch(train) [47][380/940] lr: 1.0000e-03 eta: 9:14:57 time: 0.6140 data_time: 0.0348 memory: 24011 grad_norm: 5.6187 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.7076 loss: 0.7076 2022/09/05 16:47:08 - mmengine - INFO - Epoch(train) [47][400/940] lr: 1.0000e-03 eta: 9:14:42 time: 0.6009 data_time: 0.0392 memory: 24011 grad_norm: 5.1915 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6495 loss: 0.6495 2022/09/05 16:47:21 - mmengine - INFO - Epoch(train) [47][420/940] lr: 1.0000e-03 eta: 9:14:29 time: 0.6593 data_time: 0.0855 memory: 24011 grad_norm: 4.9494 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7224 loss: 0.7224 2022/09/05 16:47:35 - mmengine - INFO - Epoch(train) [47][440/940] lr: 1.0000e-03 eta: 9:14:16 time: 0.6683 data_time: 0.0540 memory: 24011 grad_norm: 4.6338 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7952 loss: 0.7952 2022/09/05 16:47:48 - mmengine - INFO - Epoch(train) [47][460/940] lr: 1.0000e-03 eta: 9:14:02 time: 0.6538 data_time: 0.0431 memory: 24011 grad_norm: 4.7305 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7615 loss: 0.7615 2022/09/05 16:48:01 - mmengine - INFO - Epoch(train) [47][480/940] lr: 1.0000e-03 eta: 9:13:49 time: 0.6533 data_time: 0.0337 memory: 24011 grad_norm: 4.6250 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6610 loss: 0.6610 2022/09/05 16:48:14 - mmengine - INFO - Epoch(train) [47][500/940] lr: 1.0000e-03 eta: 9:13:35 time: 0.6479 data_time: 0.0603 memory: 24011 grad_norm: 4.6852 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7265 loss: 0.7265 2022/09/05 16:48:27 - mmengine - INFO - Epoch(train) [47][520/940] lr: 1.0000e-03 eta: 9:13:22 time: 0.6689 data_time: 0.0382 memory: 24011 grad_norm: 4.5580 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7632 loss: 0.7632 2022/09/05 16:48:40 - mmengine - INFO - Epoch(train) [47][540/940] lr: 1.0000e-03 eta: 9:13:08 time: 0.6245 data_time: 0.0358 memory: 24011 grad_norm: 4.7078 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7601 loss: 0.7601 2022/09/05 16:48:53 - mmengine - INFO - Epoch(train) [47][560/940] lr: 1.0000e-03 eta: 9:12:55 time: 0.6442 data_time: 0.0352 memory: 24011 grad_norm: 6.0192 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7820 loss: 0.7820 2022/09/05 16:49:05 - mmengine - INFO - Epoch(train) [47][580/940] lr: 1.0000e-03 eta: 9:12:41 time: 0.6439 data_time: 0.0357 memory: 24011 grad_norm: 4.7287 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8108 loss: 0.8108 2022/09/05 16:49:18 - mmengine - INFO - Epoch(train) [47][600/940] lr: 1.0000e-03 eta: 9:12:27 time: 0.6421 data_time: 0.0415 memory: 24011 grad_norm: 4.6344 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6840 loss: 0.6840 2022/09/05 16:49:31 - mmengine - INFO - Epoch(train) [47][620/940] lr: 1.0000e-03 eta: 9:12:14 time: 0.6623 data_time: 0.0381 memory: 24011 grad_norm: 4.5484 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7312 loss: 0.7312 2022/09/05 16:49:45 - mmengine - INFO - Epoch(train) [47][640/940] lr: 1.0000e-03 eta: 9:12:01 time: 0.6509 data_time: 0.0402 memory: 24011 grad_norm: 4.7177 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7145 loss: 0.7145 2022/09/05 16:49:58 - mmengine - INFO - Epoch(train) [47][660/940] lr: 1.0000e-03 eta: 9:11:47 time: 0.6494 data_time: 0.0359 memory: 24011 grad_norm: 4.9039 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7387 loss: 0.7387 2022/09/05 16:50:11 - mmengine - INFO - Epoch(train) [47][680/940] lr: 1.0000e-03 eta: 9:11:34 time: 0.6740 data_time: 0.0433 memory: 24011 grad_norm: 4.7514 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.7067 loss: 0.7067 2022/09/05 16:50:24 - mmengine - INFO - Epoch(train) [47][700/940] lr: 1.0000e-03 eta: 9:11:21 time: 0.6706 data_time: 0.0344 memory: 24011 grad_norm: 4.7511 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7546 loss: 0.7546 2022/09/05 16:50:37 - mmengine - INFO - Epoch(train) [47][720/940] lr: 1.0000e-03 eta: 9:11:08 time: 0.6366 data_time: 0.0411 memory: 24011 grad_norm: 4.6567 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6981 loss: 0.6981 2022/09/05 16:50:50 - mmengine - INFO - Epoch(train) [47][740/940] lr: 1.0000e-03 eta: 9:10:54 time: 0.6370 data_time: 0.0418 memory: 24011 grad_norm: 4.5353 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6417 loss: 0.6417 2022/09/05 16:51:03 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:51:03 - mmengine - INFO - Epoch(train) [47][760/940] lr: 1.0000e-03 eta: 9:10:41 time: 0.6612 data_time: 0.0456 memory: 24011 grad_norm: 4.9583 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7516 loss: 0.7516 2022/09/05 16:51:15 - mmengine - INFO - Epoch(train) [47][780/940] lr: 1.0000e-03 eta: 9:10:26 time: 0.6084 data_time: 0.0438 memory: 24011 grad_norm: 4.7031 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7781 loss: 0.7781 2022/09/05 16:51:27 - mmengine - INFO - Epoch(train) [47][800/940] lr: 1.0000e-03 eta: 9:10:12 time: 0.6085 data_time: 0.0356 memory: 24011 grad_norm: 5.1935 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6584 loss: 0.6584 2022/09/05 16:51:41 - mmengine - INFO - Epoch(train) [47][820/940] lr: 1.0000e-03 eta: 9:09:59 time: 0.6765 data_time: 0.0381 memory: 24011 grad_norm: 4.4772 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6615 loss: 0.6615 2022/09/05 16:51:54 - mmengine - INFO - Epoch(train) [47][840/940] lr: 1.0000e-03 eta: 9:09:46 time: 0.6462 data_time: 0.0395 memory: 24011 grad_norm: 4.6756 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6140 loss: 0.6140 2022/09/05 16:52:07 - mmengine - INFO - Epoch(train) [47][860/940] lr: 1.0000e-03 eta: 9:09:32 time: 0.6569 data_time: 0.0386 memory: 24011 grad_norm: 5.0121 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7846 loss: 0.7846 2022/09/05 16:52:22 - mmengine - INFO - Epoch(train) [47][880/940] lr: 1.0000e-03 eta: 9:09:20 time: 0.7207 data_time: 0.0547 memory: 24011 grad_norm: 4.8586 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8049 loss: 0.8049 2022/09/05 16:52:34 - mmengine - INFO - Epoch(train) [47][900/940] lr: 1.0000e-03 eta: 9:09:06 time: 0.6125 data_time: 0.0370 memory: 24011 grad_norm: 4.5546 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7675 loss: 0.7675 2022/09/05 16:52:46 - mmengine - INFO - Epoch(train) [47][920/940] lr: 1.0000e-03 eta: 9:08:52 time: 0.6254 data_time: 0.0560 memory: 24011 grad_norm: 5.4042 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6698 loss: 0.6698 2022/09/05 16:52:57 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 16:52:57 - mmengine - INFO - Epoch(train) [47][940/940] lr: 1.0000e-03 eta: 9:08:36 time: 0.5434 data_time: 0.0271 memory: 24011 grad_norm: 4.8579 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.6934 loss: 0.6934 2022/09/05 16:53:11 - mmengine - INFO - Epoch(val) [47][20/78] eta: 0:00:40 time: 0.6899 data_time: 0.5319 memory: 3625 2022/09/05 16:53:20 - mmengine - INFO - Epoch(val) [47][40/78] eta: 0:00:17 time: 0.4639 data_time: 0.3022 memory: 3625 2022/09/05 16:53:33 - mmengine - INFO - Epoch(val) [47][60/78] eta: 0:00:11 time: 0.6521 data_time: 0.4936 memory: 3625 2022/09/05 16:53:44 - mmengine - INFO - Epoch(val) [47][78/78] acc/top1: 0.7385 acc/top5: 0.9079 acc/mean1: 0.7383 2022/09/05 16:54:02 - mmengine - INFO - Epoch(train) [48][20/940] lr: 1.0000e-03 eta: 9:08:29 time: 0.9102 data_time: 0.2327 memory: 24011 grad_norm: 4.8092 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.8044 loss: 0.8044 2022/09/05 16:54:15 - mmengine - INFO - Epoch(train) [48][40/940] lr: 1.0000e-03 eta: 9:08:15 time: 0.6399 data_time: 0.0364 memory: 24011 grad_norm: 4.9587 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7537 loss: 0.7537 2022/09/05 16:54:29 - mmengine - INFO - Epoch(train) [48][60/940] lr: 1.0000e-03 eta: 9:08:02 time: 0.6889 data_time: 0.0422 memory: 24011 grad_norm: 4.7989 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6793 loss: 0.6793 2022/09/05 16:54:42 - mmengine - INFO - Epoch(train) [48][80/940] lr: 1.0000e-03 eta: 9:07:49 time: 0.6441 data_time: 0.0375 memory: 24011 grad_norm: 5.5441 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7684 loss: 0.7684 2022/09/05 16:54:54 - mmengine - INFO - Epoch(train) [48][100/940] lr: 1.0000e-03 eta: 9:07:35 time: 0.6235 data_time: 0.0374 memory: 24011 grad_norm: 4.7167 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7095 loss: 0.7095 2022/09/05 16:55:07 - mmengine - INFO - Epoch(train) [48][120/940] lr: 1.0000e-03 eta: 9:07:21 time: 0.6419 data_time: 0.0401 memory: 24011 grad_norm: 4.8195 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.7846 loss: 0.7846 2022/09/05 16:55:21 - mmengine - INFO - Epoch(train) [48][140/940] lr: 1.0000e-03 eta: 9:07:09 time: 0.7097 data_time: 0.0415 memory: 24011 grad_norm: 4.7987 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.7031 loss: 0.7031 2022/09/05 16:55:33 - mmengine - INFO - Epoch(train) [48][160/940] lr: 1.0000e-03 eta: 9:06:55 time: 0.6142 data_time: 0.0377 memory: 24011 grad_norm: 5.0148 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7843 loss: 0.7843 2022/09/05 16:55:47 - mmengine - INFO - Epoch(train) [48][180/940] lr: 1.0000e-03 eta: 9:06:42 time: 0.6746 data_time: 0.0414 memory: 24011 grad_norm: 4.8124 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7405 loss: 0.7405 2022/09/05 16:55:59 - mmengine - INFO - Epoch(train) [48][200/940] lr: 1.0000e-03 eta: 9:06:28 time: 0.6241 data_time: 0.0373 memory: 24011 grad_norm: 4.9538 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6394 loss: 0.6394 2022/09/05 16:56:13 - mmengine - INFO - Epoch(train) [48][220/940] lr: 1.0000e-03 eta: 9:06:15 time: 0.6749 data_time: 0.0392 memory: 24011 grad_norm: 4.9419 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6671 loss: 0.6671 2022/09/05 16:56:26 - mmengine - INFO - Epoch(train) [48][240/940] lr: 1.0000e-03 eta: 9:06:01 time: 0.6419 data_time: 0.0449 memory: 24011 grad_norm: 5.2774 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7332 loss: 0.7332 2022/09/05 16:56:39 - mmengine - INFO - Epoch(train) [48][260/940] lr: 1.0000e-03 eta: 9:05:48 time: 0.6503 data_time: 0.0655 memory: 24011 grad_norm: 4.3866 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7525 loss: 0.7525 2022/09/05 16:56:51 - mmengine - INFO - Epoch(train) [48][280/940] lr: 1.0000e-03 eta: 9:05:33 time: 0.6132 data_time: 0.0365 memory: 24011 grad_norm: 4.6820 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.7040 loss: 0.7040 2022/09/05 16:57:04 - mmengine - INFO - Epoch(train) [48][300/940] lr: 1.0000e-03 eta: 9:05:20 time: 0.6600 data_time: 0.0369 memory: 24011 grad_norm: 5.0907 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6601 loss: 0.6601 2022/09/05 16:57:17 - mmengine - INFO - Epoch(train) [48][320/940] lr: 1.0000e-03 eta: 9:05:06 time: 0.6354 data_time: 0.0611 memory: 24011 grad_norm: 4.7957 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7745 loss: 0.7745 2022/09/05 16:57:30 - mmengine - INFO - Epoch(train) [48][340/940] lr: 1.0000e-03 eta: 9:04:53 time: 0.6666 data_time: 0.0462 memory: 24011 grad_norm: 4.8802 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6975 loss: 0.6975 2022/09/05 16:57:44 - mmengine - INFO - Epoch(train) [48][360/940] lr: 1.0000e-03 eta: 9:04:40 time: 0.6647 data_time: 0.0731 memory: 24011 grad_norm: 5.4502 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7563 loss: 0.7563 2022/09/05 16:57:56 - mmengine - INFO - Epoch(train) [48][380/940] lr: 1.0000e-03 eta: 9:04:27 time: 0.6430 data_time: 0.0640 memory: 24011 grad_norm: 4.8127 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6544 loss: 0.6544 2022/09/05 16:58:09 - mmengine - INFO - Epoch(train) [48][400/940] lr: 1.0000e-03 eta: 9:04:12 time: 0.6055 data_time: 0.0360 memory: 24011 grad_norm: 4.5514 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.5590 loss: 0.5590 2022/09/05 16:58:22 - mmengine - INFO - Epoch(train) [48][420/940] lr: 1.0000e-03 eta: 9:04:00 time: 0.6914 data_time: 0.0376 memory: 24011 grad_norm: 4.7263 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7001 loss: 0.7001 2022/09/05 16:58:35 - mmengine - INFO - Epoch(train) [48][440/940] lr: 1.0000e-03 eta: 9:03:46 time: 0.6404 data_time: 0.0567 memory: 24011 grad_norm: 4.6595 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7670 loss: 0.7670 2022/09/05 16:58:49 - mmengine - INFO - Epoch(train) [48][460/940] lr: 1.0000e-03 eta: 9:03:33 time: 0.6703 data_time: 0.0549 memory: 24011 grad_norm: 5.0595 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6123 loss: 0.6123 2022/09/05 16:59:01 - mmengine - INFO - Epoch(train) [48][480/940] lr: 1.0000e-03 eta: 9:03:19 time: 0.6361 data_time: 0.0395 memory: 24011 grad_norm: 5.0594 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.6998 loss: 0.6998 2022/09/05 16:59:15 - mmengine - INFO - Epoch(train) [48][500/940] lr: 1.0000e-03 eta: 9:03:06 time: 0.6808 data_time: 0.0384 memory: 24011 grad_norm: 4.7323 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7048 loss: 0.7048 2022/09/05 16:59:27 - mmengine - INFO - Epoch(train) [48][520/940] lr: 1.0000e-03 eta: 9:02:52 time: 0.6004 data_time: 0.0334 memory: 24011 grad_norm: 4.4583 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6778 loss: 0.6778 2022/09/05 16:59:40 - mmengine - INFO - Epoch(train) [48][540/940] lr: 1.0000e-03 eta: 9:02:38 time: 0.6328 data_time: 0.0449 memory: 24011 grad_norm: 4.6806 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6481 loss: 0.6481 2022/09/05 16:59:53 - mmengine - INFO - Epoch(train) [48][560/940] lr: 1.0000e-03 eta: 9:02:25 time: 0.6457 data_time: 0.0448 memory: 24011 grad_norm: 5.3659 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 0.8131 loss: 0.8131 2022/09/05 17:00:06 - mmengine - INFO - Epoch(train) [48][580/940] lr: 1.0000e-03 eta: 9:02:11 time: 0.6628 data_time: 0.0423 memory: 24011 grad_norm: 4.8143 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7338 loss: 0.7338 2022/09/05 17:00:19 - mmengine - INFO - Epoch(train) [48][600/940] lr: 1.0000e-03 eta: 9:01:58 time: 0.6447 data_time: 0.0405 memory: 24011 grad_norm: 4.8913 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6470 loss: 0.6470 2022/09/05 17:00:32 - mmengine - INFO - Epoch(train) [48][620/940] lr: 1.0000e-03 eta: 9:01:45 time: 0.6649 data_time: 0.0801 memory: 24011 grad_norm: 5.0319 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6867 loss: 0.6867 2022/09/05 17:00:45 - mmengine - INFO - Epoch(train) [48][640/940] lr: 1.0000e-03 eta: 9:01:31 time: 0.6260 data_time: 0.0436 memory: 24011 grad_norm: 4.9633 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7002 loss: 0.7002 2022/09/05 17:00:57 - mmengine - INFO - Epoch(train) [48][660/940] lr: 1.0000e-03 eta: 9:01:16 time: 0.6135 data_time: 0.0418 memory: 24011 grad_norm: 5.2204 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7671 loss: 0.7671 2022/09/05 17:01:10 - mmengine - INFO - Epoch(train) [48][680/940] lr: 1.0000e-03 eta: 9:01:03 time: 0.6673 data_time: 0.0390 memory: 24011 grad_norm: 4.8030 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7072 loss: 0.7072 2022/09/05 17:01:23 - mmengine - INFO - Epoch(train) [48][700/940] lr: 1.0000e-03 eta: 9:00:50 time: 0.6587 data_time: 0.0395 memory: 24011 grad_norm: 4.9041 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6467 loss: 0.6467 2022/09/05 17:01:36 - mmengine - INFO - Epoch(train) [48][720/940] lr: 1.0000e-03 eta: 9:00:36 time: 0.6380 data_time: 0.0372 memory: 24011 grad_norm: 4.9987 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6899 loss: 0.6899 2022/09/05 17:01:50 - mmengine - INFO - Epoch(train) [48][740/940] lr: 1.0000e-03 eta: 9:00:24 time: 0.6819 data_time: 0.0516 memory: 24011 grad_norm: 5.3243 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7120 loss: 0.7120 2022/09/05 17:02:02 - mmengine - INFO - Epoch(train) [48][760/940] lr: 1.0000e-03 eta: 9:00:10 time: 0.6275 data_time: 0.0483 memory: 24011 grad_norm: 4.8257 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6711 loss: 0.6711 2022/09/05 17:02:16 - mmengine - INFO - Epoch(train) [48][780/940] lr: 1.0000e-03 eta: 8:59:57 time: 0.6631 data_time: 0.0415 memory: 24011 grad_norm: 5.3067 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6777 loss: 0.6777 2022/09/05 17:02:28 - mmengine - INFO - Epoch(train) [48][800/940] lr: 1.0000e-03 eta: 8:59:43 time: 0.6327 data_time: 0.0423 memory: 24011 grad_norm: 4.6887 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7105 loss: 0.7105 2022/09/05 17:02:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:02:41 - mmengine - INFO - Epoch(train) [48][820/940] lr: 1.0000e-03 eta: 8:59:29 time: 0.6486 data_time: 0.0379 memory: 24011 grad_norm: 4.9817 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7198 loss: 0.7198 2022/09/05 17:02:54 - mmengine - INFO - Epoch(train) [48][840/940] lr: 1.0000e-03 eta: 8:59:15 time: 0.6320 data_time: 0.0376 memory: 24011 grad_norm: 4.8251 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7235 loss: 0.7235 2022/09/05 17:03:07 - mmengine - INFO - Epoch(train) [48][860/940] lr: 1.0000e-03 eta: 8:59:03 time: 0.6774 data_time: 0.0391 memory: 24011 grad_norm: 4.9730 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6629 loss: 0.6629 2022/09/05 17:03:20 - mmengine - INFO - Epoch(train) [48][880/940] lr: 1.0000e-03 eta: 8:58:49 time: 0.6493 data_time: 0.0340 memory: 24011 grad_norm: 5.0306 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6924 loss: 0.6924 2022/09/05 17:03:33 - mmengine - INFO - Epoch(train) [48][900/940] lr: 1.0000e-03 eta: 8:58:35 time: 0.6314 data_time: 0.0410 memory: 24011 grad_norm: 5.3603 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6803 loss: 0.6803 2022/09/05 17:03:46 - mmengine - INFO - Epoch(train) [48][920/940] lr: 1.0000e-03 eta: 8:58:22 time: 0.6380 data_time: 0.0483 memory: 24011 grad_norm: 4.5595 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6405 loss: 0.6405 2022/09/05 17:03:57 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:03:57 - mmengine - INFO - Epoch(train) [48][940/940] lr: 1.0000e-03 eta: 8:58:06 time: 0.5564 data_time: 0.0301 memory: 24011 grad_norm: 5.3906 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.6283 loss: 0.6283 2022/09/05 17:03:57 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/09/05 17:04:17 - mmengine - INFO - Epoch(val) [48][20/78] eta: 0:00:40 time: 0.7022 data_time: 0.5474 memory: 3625 2022/09/05 17:04:27 - mmengine - INFO - Epoch(val) [48][40/78] eta: 0:00:17 time: 0.4728 data_time: 0.3183 memory: 3625 2022/09/05 17:04:39 - mmengine - INFO - Epoch(val) [48][60/78] eta: 0:00:11 time: 0.6128 data_time: 0.4522 memory: 3625 2022/09/05 17:04:49 - mmengine - INFO - Epoch(val) [48][78/78] acc/top1: 0.7407 acc/top5: 0.9098 acc/mean1: 0.7405 2022/09/05 17:04:49 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_47.pth is removed 2022/09/05 17:04:52 - mmengine - INFO - The best checkpoint with 0.7407 acc/top1 at 49 epoch is saved to best_acc/top1_epoch_49.pth. 2022/09/05 17:05:09 - mmengine - INFO - Epoch(train) [49][20/940] lr: 1.0000e-03 eta: 8:57:56 time: 0.8250 data_time: 0.2586 memory: 24011 grad_norm: 5.3284 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7876 loss: 0.7876 2022/09/05 17:05:21 - mmengine - INFO - Epoch(train) [49][40/940] lr: 1.0000e-03 eta: 8:57:43 time: 0.6341 data_time: 0.0724 memory: 24011 grad_norm: 5.1393 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7739 loss: 0.7739 2022/09/05 17:05:34 - mmengine - INFO - Epoch(train) [49][60/940] lr: 1.0000e-03 eta: 8:57:30 time: 0.6636 data_time: 0.1023 memory: 24011 grad_norm: 5.0159 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6832 loss: 0.6832 2022/09/05 17:05:47 - mmengine - INFO - Epoch(train) [49][80/940] lr: 1.0000e-03 eta: 8:57:16 time: 0.6341 data_time: 0.0798 memory: 24011 grad_norm: 4.9102 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.7226 loss: 0.7226 2022/09/05 17:06:00 - mmengine - INFO - Epoch(train) [49][100/940] lr: 1.0000e-03 eta: 8:57:02 time: 0.6557 data_time: 0.0969 memory: 24011 grad_norm: 4.8318 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7644 loss: 0.7644 2022/09/05 17:06:13 - mmengine - INFO - Epoch(train) [49][120/940] lr: 1.0000e-03 eta: 8:56:49 time: 0.6419 data_time: 0.0803 memory: 24011 grad_norm: 4.5942 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6409 loss: 0.6409 2022/09/05 17:06:26 - mmengine - INFO - Epoch(train) [49][140/940] lr: 1.0000e-03 eta: 8:56:35 time: 0.6290 data_time: 0.0769 memory: 24011 grad_norm: 5.5409 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7627 loss: 0.7627 2022/09/05 17:06:38 - mmengine - INFO - Epoch(train) [49][160/940] lr: 1.0000e-03 eta: 8:56:21 time: 0.6113 data_time: 0.0397 memory: 24011 grad_norm: 5.1079 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.6377 loss: 0.6377 2022/09/05 17:06:51 - mmengine - INFO - Epoch(train) [49][180/940] lr: 1.0000e-03 eta: 8:56:07 time: 0.6381 data_time: 0.0819 memory: 24011 grad_norm: 4.6147 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7744 loss: 0.7744 2022/09/05 17:07:04 - mmengine - INFO - Epoch(train) [49][200/940] lr: 1.0000e-03 eta: 8:55:53 time: 0.6374 data_time: 0.0686 memory: 24011 grad_norm: 4.7122 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.7688 loss: 0.7688 2022/09/05 17:07:17 - mmengine - INFO - Epoch(train) [49][220/940] lr: 1.0000e-03 eta: 8:55:40 time: 0.6556 data_time: 0.0794 memory: 24011 grad_norm: 5.0524 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6268 loss: 0.6268 2022/09/05 17:07:30 - mmengine - INFO - Epoch(train) [49][240/940] lr: 1.0000e-03 eta: 8:55:27 time: 0.6798 data_time: 0.0420 memory: 24011 grad_norm: 5.1623 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7472 loss: 0.7472 2022/09/05 17:07:43 - mmengine - INFO - Epoch(train) [49][260/940] lr: 1.0000e-03 eta: 8:55:13 time: 0.6201 data_time: 0.0435 memory: 24011 grad_norm: 5.0372 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.7829 loss: 0.7829 2022/09/05 17:07:55 - mmengine - INFO - Epoch(train) [49][280/940] lr: 1.0000e-03 eta: 8:55:00 time: 0.6477 data_time: 0.0457 memory: 24011 grad_norm: 4.5628 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7020 loss: 0.7020 2022/09/05 17:08:08 - mmengine - INFO - Epoch(train) [49][300/940] lr: 1.0000e-03 eta: 8:54:46 time: 0.6381 data_time: 0.0404 memory: 24011 grad_norm: 4.9280 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6160 loss: 0.6160 2022/09/05 17:08:22 - mmengine - INFO - Epoch(train) [49][320/940] lr: 1.0000e-03 eta: 8:54:34 time: 0.6988 data_time: 0.0380 memory: 24011 grad_norm: 4.6539 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5246 loss: 0.5246 2022/09/05 17:08:35 - mmengine - INFO - Epoch(train) [49][340/940] lr: 1.0000e-03 eta: 8:54:20 time: 0.6238 data_time: 0.0388 memory: 24011 grad_norm: 4.7454 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6473 loss: 0.6473 2022/09/05 17:08:48 - mmengine - INFO - Epoch(train) [49][360/940] lr: 1.0000e-03 eta: 8:54:06 time: 0.6657 data_time: 0.0360 memory: 24011 grad_norm: 4.8647 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6995 loss: 0.6995 2022/09/05 17:09:00 - mmengine - INFO - Epoch(train) [49][380/940] lr: 1.0000e-03 eta: 8:53:52 time: 0.6111 data_time: 0.0398 memory: 24011 grad_norm: 4.9588 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6990 loss: 0.6990 2022/09/05 17:09:13 - mmengine - INFO - Epoch(train) [49][400/940] lr: 1.0000e-03 eta: 8:53:39 time: 0.6489 data_time: 0.0445 memory: 24011 grad_norm: 5.1037 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.7064 loss: 0.7064 2022/09/05 17:09:26 - mmengine - INFO - Epoch(train) [49][420/940] lr: 1.0000e-03 eta: 8:53:25 time: 0.6311 data_time: 0.0426 memory: 24011 grad_norm: 4.8356 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6992 loss: 0.6992 2022/09/05 17:09:39 - mmengine - INFO - Epoch(train) [49][440/940] lr: 1.0000e-03 eta: 8:53:11 time: 0.6435 data_time: 0.0382 memory: 24011 grad_norm: 4.7596 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.7389 loss: 0.7389 2022/09/05 17:09:52 - mmengine - INFO - Epoch(train) [49][460/940] lr: 1.0000e-03 eta: 8:52:58 time: 0.6735 data_time: 0.0520 memory: 24011 grad_norm: 5.0774 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6746 loss: 0.6746 2022/09/05 17:10:05 - mmengine - INFO - Epoch(train) [49][480/940] lr: 1.0000e-03 eta: 8:52:44 time: 0.6297 data_time: 0.0344 memory: 24011 grad_norm: 11.3485 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6782 loss: 0.6782 2022/09/05 17:10:18 - mmengine - INFO - Epoch(train) [49][500/940] lr: 1.0000e-03 eta: 8:52:32 time: 0.6748 data_time: 0.0440 memory: 24011 grad_norm: 4.7134 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6130 loss: 0.6130 2022/09/05 17:10:32 - mmengine - INFO - Epoch(train) [49][520/940] lr: 1.0000e-03 eta: 8:52:18 time: 0.6602 data_time: 0.0459 memory: 24011 grad_norm: 5.5752 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6273 loss: 0.6273 2022/09/05 17:10:45 - mmengine - INFO - Epoch(train) [49][540/940] lr: 1.0000e-03 eta: 8:52:05 time: 0.6674 data_time: 0.0837 memory: 24011 grad_norm: 4.9953 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6980 loss: 0.6980 2022/09/05 17:10:58 - mmengine - INFO - Epoch(train) [49][560/940] lr: 1.0000e-03 eta: 8:51:52 time: 0.6352 data_time: 0.0335 memory: 24011 grad_norm: 5.0222 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7921 loss: 0.7921 2022/09/05 17:11:12 - mmengine - INFO - Epoch(train) [49][580/940] lr: 1.0000e-03 eta: 8:51:40 time: 0.7170 data_time: 0.1250 memory: 24011 grad_norm: 4.8689 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7081 loss: 0.7081 2022/09/05 17:11:24 - mmengine - INFO - Epoch(train) [49][600/940] lr: 1.0000e-03 eta: 8:51:25 time: 0.6166 data_time: 0.0296 memory: 24011 grad_norm: 5.4324 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6663 loss: 0.6663 2022/09/05 17:11:37 - mmengine - INFO - Epoch(train) [49][620/940] lr: 1.0000e-03 eta: 8:51:11 time: 0.6244 data_time: 0.0413 memory: 24011 grad_norm: 5.8871 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6204 loss: 0.6204 2022/09/05 17:11:49 - mmengine - INFO - Epoch(train) [49][640/940] lr: 1.0000e-03 eta: 8:50:57 time: 0.6152 data_time: 0.0455 memory: 24011 grad_norm: 5.5112 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6331 loss: 0.6331 2022/09/05 17:12:03 - mmengine - INFO - Epoch(train) [49][660/940] lr: 1.0000e-03 eta: 8:50:45 time: 0.6813 data_time: 0.1038 memory: 24011 grad_norm: 4.6652 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6941 loss: 0.6941 2022/09/05 17:12:16 - mmengine - INFO - Epoch(train) [49][680/940] lr: 1.0000e-03 eta: 8:50:31 time: 0.6454 data_time: 0.0530 memory: 24011 grad_norm: 5.6408 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6354 loss: 0.6354 2022/09/05 17:12:28 - mmengine - INFO - Epoch(train) [49][700/940] lr: 1.0000e-03 eta: 8:50:17 time: 0.6187 data_time: 0.0376 memory: 24011 grad_norm: 5.3168 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8118 loss: 0.8118 2022/09/05 17:12:41 - mmengine - INFO - Epoch(train) [49][720/940] lr: 1.0000e-03 eta: 8:50:04 time: 0.6586 data_time: 0.0830 memory: 24011 grad_norm: 6.3325 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.7102 loss: 0.7102 2022/09/05 17:12:55 - mmengine - INFO - Epoch(train) [49][740/940] lr: 1.0000e-03 eta: 8:49:51 time: 0.7084 data_time: 0.1012 memory: 24011 grad_norm: 4.9928 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8160 loss: 0.8160 2022/09/05 17:13:08 - mmengine - INFO - Epoch(train) [49][760/940] lr: 1.0000e-03 eta: 8:49:37 time: 0.6181 data_time: 0.0341 memory: 24011 grad_norm: 5.4507 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.6557 loss: 0.6557 2022/09/05 17:13:21 - mmengine - INFO - Epoch(train) [49][780/940] lr: 1.0000e-03 eta: 8:49:25 time: 0.6793 data_time: 0.0828 memory: 24011 grad_norm: 5.7026 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.7192 loss: 0.7192 2022/09/05 17:13:34 - mmengine - INFO - Epoch(train) [49][800/940] lr: 1.0000e-03 eta: 8:49:11 time: 0.6304 data_time: 0.0457 memory: 24011 grad_norm: 5.3746 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7469 loss: 0.7469 2022/09/05 17:13:47 - mmengine - INFO - Epoch(train) [49][820/940] lr: 1.0000e-03 eta: 8:48:57 time: 0.6520 data_time: 0.0906 memory: 24011 grad_norm: 4.7863 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6485 loss: 0.6485 2022/09/05 17:13:59 - mmengine - INFO - Epoch(train) [49][840/940] lr: 1.0000e-03 eta: 8:48:43 time: 0.6182 data_time: 0.0327 memory: 24011 grad_norm: 4.7257 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7520 loss: 0.7520 2022/09/05 17:14:12 - mmengine - INFO - Epoch(train) [49][860/940] lr: 1.0000e-03 eta: 8:48:30 time: 0.6494 data_time: 0.0829 memory: 24011 grad_norm: 5.3321 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6316 loss: 0.6316 2022/09/05 17:14:26 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:14:26 - mmengine - INFO - Epoch(train) [49][880/940] lr: 1.0000e-03 eta: 8:48:17 time: 0.6916 data_time: 0.0819 memory: 24011 grad_norm: 8.2513 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7911 loss: 0.7911 2022/09/05 17:14:39 - mmengine - INFO - Epoch(train) [49][900/940] lr: 1.0000e-03 eta: 8:48:03 time: 0.6070 data_time: 0.0461 memory: 24011 grad_norm: 4.7605 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.7713 loss: 0.7713 2022/09/05 17:14:51 - mmengine - INFO - Epoch(train) [49][920/940] lr: 1.0000e-03 eta: 8:47:49 time: 0.6160 data_time: 0.0484 memory: 24011 grad_norm: 4.9791 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7237 loss: 0.7237 2022/09/05 17:15:03 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:15:03 - mmengine - INFO - Epoch(train) [49][940/940] lr: 1.0000e-03 eta: 8:47:35 time: 0.6115 data_time: 0.0746 memory: 24011 grad_norm: 4.9808 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6973 loss: 0.6973 2022/09/05 17:15:17 - mmengine - INFO - Epoch(val) [49][20/78] eta: 0:00:40 time: 0.7005 data_time: 0.5388 memory: 3625 2022/09/05 17:15:27 - mmengine - INFO - Epoch(val) [49][40/78] eta: 0:00:17 time: 0.4591 data_time: 0.3019 memory: 3625 2022/09/05 17:15:39 - mmengine - INFO - Epoch(val) [49][60/78] eta: 0:00:11 time: 0.6586 data_time: 0.5010 memory: 3625 2022/09/05 17:15:50 - mmengine - INFO - Epoch(val) [49][78/78] acc/top1: 0.7405 acc/top5: 0.9083 acc/mean1: 0.7403 2022/09/05 17:16:09 - mmengine - INFO - Epoch(train) [50][20/940] lr: 1.0000e-03 eta: 8:47:27 time: 0.9249 data_time: 0.3050 memory: 24011 grad_norm: 4.9321 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.7245 loss: 0.7245 2022/09/05 17:16:21 - mmengine - INFO - Epoch(train) [50][40/940] lr: 1.0000e-03 eta: 8:47:13 time: 0.6266 data_time: 0.0364 memory: 24011 grad_norm: 5.3160 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6078 loss: 0.6078 2022/09/05 17:16:35 - mmengine - INFO - Epoch(train) [50][60/940] lr: 1.0000e-03 eta: 8:47:00 time: 0.6660 data_time: 0.0423 memory: 24011 grad_norm: 4.7294 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7375 loss: 0.7375 2022/09/05 17:16:47 - mmengine - INFO - Epoch(train) [50][80/940] lr: 1.0000e-03 eta: 8:46:46 time: 0.6384 data_time: 0.0464 memory: 24011 grad_norm: 4.9531 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7422 loss: 0.7422 2022/09/05 17:17:00 - mmengine - INFO - Epoch(train) [50][100/940] lr: 1.0000e-03 eta: 8:46:33 time: 0.6554 data_time: 0.0692 memory: 24011 grad_norm: 4.7537 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6182 loss: 0.6182 2022/09/05 17:17:14 - mmengine - INFO - Epoch(train) [50][120/940] lr: 1.0000e-03 eta: 8:46:20 time: 0.6665 data_time: 0.0440 memory: 24011 grad_norm: 4.7165 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7125 loss: 0.7125 2022/09/05 17:17:26 - mmengine - INFO - Epoch(train) [50][140/940] lr: 1.0000e-03 eta: 8:46:06 time: 0.6296 data_time: 0.0424 memory: 24011 grad_norm: 4.7292 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6875 loss: 0.6875 2022/09/05 17:17:39 - mmengine - INFO - Epoch(train) [50][160/940] lr: 1.0000e-03 eta: 8:45:52 time: 0.6190 data_time: 0.0440 memory: 24011 grad_norm: 4.5866 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6566 loss: 0.6566 2022/09/05 17:17:53 - mmengine - INFO - Epoch(train) [50][180/940] lr: 1.0000e-03 eta: 8:45:40 time: 0.7115 data_time: 0.0383 memory: 24011 grad_norm: 5.1864 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7263 loss: 0.7263 2022/09/05 17:18:05 - mmengine - INFO - Epoch(train) [50][200/940] lr: 1.0000e-03 eta: 8:45:26 time: 0.6171 data_time: 0.0379 memory: 24011 grad_norm: 4.9622 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6660 loss: 0.6660 2022/09/05 17:18:18 - mmengine - INFO - Epoch(train) [50][220/940] lr: 1.0000e-03 eta: 8:45:12 time: 0.6276 data_time: 0.0420 memory: 24011 grad_norm: 5.1021 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 0.7177 loss: 0.7177 2022/09/05 17:18:31 - mmengine - INFO - Epoch(train) [50][240/940] lr: 1.0000e-03 eta: 8:44:58 time: 0.6466 data_time: 0.0443 memory: 24011 grad_norm: 4.6268 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7600 loss: 0.7600 2022/09/05 17:18:44 - mmengine - INFO - Epoch(train) [50][260/940] lr: 1.0000e-03 eta: 8:44:46 time: 0.6811 data_time: 0.0381 memory: 24011 grad_norm: 4.6381 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7030 loss: 0.7030 2022/09/05 17:18:57 - mmengine - INFO - Epoch(train) [50][280/940] lr: 1.0000e-03 eta: 8:44:32 time: 0.6501 data_time: 0.0447 memory: 24011 grad_norm: 4.9079 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7382 loss: 0.7382 2022/09/05 17:19:09 - mmengine - INFO - Epoch(train) [50][300/940] lr: 1.0000e-03 eta: 8:44:18 time: 0.6022 data_time: 0.0378 memory: 24011 grad_norm: 4.7872 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6447 loss: 0.6447 2022/09/05 17:19:23 - mmengine - INFO - Epoch(train) [50][320/940] lr: 1.0000e-03 eta: 8:44:05 time: 0.6865 data_time: 0.0506 memory: 24011 grad_norm: 4.9887 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6510 loss: 0.6510 2022/09/05 17:19:36 - mmengine - INFO - Epoch(train) [50][340/940] lr: 1.0000e-03 eta: 8:43:51 time: 0.6422 data_time: 0.0348 memory: 24011 grad_norm: 4.9066 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6838 loss: 0.6838 2022/09/05 17:19:49 - mmengine - INFO - Epoch(train) [50][360/940] lr: 1.0000e-03 eta: 8:43:38 time: 0.6553 data_time: 0.0420 memory: 24011 grad_norm: 4.9480 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.6962 loss: 0.6962 2022/09/05 17:20:02 - mmengine - INFO - Epoch(train) [50][380/940] lr: 1.0000e-03 eta: 8:43:25 time: 0.6466 data_time: 0.0408 memory: 24011 grad_norm: 4.6758 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 0.7383 loss: 0.7383 2022/09/05 17:20:15 - mmengine - INFO - Epoch(train) [50][400/940] lr: 1.0000e-03 eta: 8:43:11 time: 0.6459 data_time: 0.0568 memory: 24011 grad_norm: 4.5424 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7188 loss: 0.7188 2022/09/05 17:20:29 - mmengine - INFO - Epoch(train) [50][420/940] lr: 1.0000e-03 eta: 8:42:59 time: 0.7007 data_time: 0.0423 memory: 24011 grad_norm: 4.6917 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7037 loss: 0.7037 2022/09/05 17:20:42 - mmengine - INFO - Epoch(train) [50][440/940] lr: 1.0000e-03 eta: 8:42:45 time: 0.6483 data_time: 0.0458 memory: 24011 grad_norm: 4.5581 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5980 loss: 0.5980 2022/09/05 17:20:56 - mmengine - INFO - Epoch(train) [50][460/940] lr: 1.0000e-03 eta: 8:42:33 time: 0.7025 data_time: 0.0372 memory: 24011 grad_norm: 4.6644 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6906 loss: 0.6906 2022/09/05 17:21:08 - mmengine - INFO - Epoch(train) [50][480/940] lr: 1.0000e-03 eta: 8:42:18 time: 0.5918 data_time: 0.0451 memory: 24011 grad_norm: 4.7550 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6208 loss: 0.6208 2022/09/05 17:21:21 - mmengine - INFO - Epoch(train) [50][500/940] lr: 1.0000e-03 eta: 8:42:05 time: 0.6644 data_time: 0.0429 memory: 24011 grad_norm: 4.9115 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6197 loss: 0.6197 2022/09/05 17:21:34 - mmengine - INFO - Epoch(train) [50][520/940] lr: 1.0000e-03 eta: 8:41:51 time: 0.6269 data_time: 0.0594 memory: 24011 grad_norm: 4.6704 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7131 loss: 0.7131 2022/09/05 17:21:47 - mmengine - INFO - Epoch(train) [50][540/940] lr: 1.0000e-03 eta: 8:41:38 time: 0.6596 data_time: 0.0462 memory: 24011 grad_norm: 4.9479 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6019 loss: 0.6019 2022/09/05 17:21:59 - mmengine - INFO - Epoch(train) [50][560/940] lr: 1.0000e-03 eta: 8:41:24 time: 0.6107 data_time: 0.0461 memory: 24011 grad_norm: 5.2034 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6957 loss: 0.6957 2022/09/05 17:22:12 - mmengine - INFO - Epoch(train) [50][580/940] lr: 1.0000e-03 eta: 8:41:11 time: 0.6558 data_time: 0.0598 memory: 24011 grad_norm: 4.8010 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.7210 loss: 0.7210 2022/09/05 17:22:25 - mmengine - INFO - Epoch(train) [50][600/940] lr: 1.0000e-03 eta: 8:40:57 time: 0.6340 data_time: 0.0435 memory: 24011 grad_norm: 4.7171 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5803 loss: 0.5803 2022/09/05 17:22:37 - mmengine - INFO - Epoch(train) [50][620/940] lr: 1.0000e-03 eta: 8:40:43 time: 0.6163 data_time: 0.0450 memory: 24011 grad_norm: 4.8702 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7524 loss: 0.7524 2022/09/05 17:22:51 - mmengine - INFO - Epoch(train) [50][640/940] lr: 1.0000e-03 eta: 8:40:30 time: 0.6605 data_time: 0.0397 memory: 24011 grad_norm: 5.4950 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.7587 loss: 0.7587 2022/09/05 17:23:04 - mmengine - INFO - Epoch(train) [50][660/940] lr: 1.0000e-03 eta: 8:40:17 time: 0.6705 data_time: 0.0391 memory: 24011 grad_norm: 4.7432 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7787 loss: 0.7787 2022/09/05 17:23:16 - mmengine - INFO - Epoch(train) [50][680/940] lr: 1.0000e-03 eta: 8:40:02 time: 0.6131 data_time: 0.0385 memory: 24011 grad_norm: 4.8053 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7833 loss: 0.7833 2022/09/05 17:23:29 - mmengine - INFO - Epoch(train) [50][700/940] lr: 1.0000e-03 eta: 8:39:49 time: 0.6307 data_time: 0.0390 memory: 24011 grad_norm: 5.1370 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6640 loss: 0.6640 2022/09/05 17:23:42 - mmengine - INFO - Epoch(train) [50][720/940] lr: 1.0000e-03 eta: 8:39:36 time: 0.6752 data_time: 0.0436 memory: 24011 grad_norm: 5.0388 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6601 loss: 0.6601 2022/09/05 17:23:56 - mmengine - INFO - Epoch(train) [50][740/940] lr: 1.0000e-03 eta: 8:39:23 time: 0.6839 data_time: 0.0435 memory: 24011 grad_norm: 4.6758 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6979 loss: 0.6979 2022/09/05 17:24:09 - mmengine - INFO - Epoch(train) [50][760/940] lr: 1.0000e-03 eta: 8:39:10 time: 0.6650 data_time: 0.0408 memory: 24011 grad_norm: 4.7125 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6258 loss: 0.6258 2022/09/05 17:24:22 - mmengine - INFO - Epoch(train) [50][780/940] lr: 1.0000e-03 eta: 8:38:56 time: 0.6269 data_time: 0.0483 memory: 24011 grad_norm: 5.4691 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6932 loss: 0.6932 2022/09/05 17:24:35 - mmengine - INFO - Epoch(train) [50][800/940] lr: 1.0000e-03 eta: 8:38:43 time: 0.6690 data_time: 0.0535 memory: 24011 grad_norm: 5.0414 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.7514 loss: 0.7514 2022/09/05 17:24:49 - mmengine - INFO - Epoch(train) [50][820/940] lr: 1.0000e-03 eta: 8:38:30 time: 0.6649 data_time: 0.0467 memory: 24011 grad_norm: 4.7870 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6858 loss: 0.6858 2022/09/05 17:25:02 - mmengine - INFO - Epoch(train) [50][840/940] lr: 1.0000e-03 eta: 8:38:17 time: 0.6789 data_time: 0.0459 memory: 24011 grad_norm: 4.9153 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7869 loss: 0.7869 2022/09/05 17:25:16 - mmengine - INFO - Epoch(train) [50][860/940] lr: 1.0000e-03 eta: 8:38:04 time: 0.6706 data_time: 0.0388 memory: 24011 grad_norm: 4.9697 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6594 loss: 0.6594 2022/09/05 17:25:28 - mmengine - INFO - Epoch(train) [50][880/940] lr: 1.0000e-03 eta: 8:37:50 time: 0.6243 data_time: 0.0383 memory: 24011 grad_norm: 4.9009 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7057 loss: 0.7057 2022/09/05 17:25:41 - mmengine - INFO - Epoch(train) [50][900/940] lr: 1.0000e-03 eta: 8:37:37 time: 0.6444 data_time: 0.0458 memory: 24011 grad_norm: 4.9856 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7658 loss: 0.7658 2022/09/05 17:25:54 - mmengine - INFO - Epoch(train) [50][920/940] lr: 1.0000e-03 eta: 8:37:23 time: 0.6440 data_time: 0.0553 memory: 24011 grad_norm: 4.6695 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6763 loss: 0.6763 2022/09/05 17:26:05 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:26:05 - mmengine - INFO - Epoch(train) [50][940/940] lr: 1.0000e-03 eta: 8:37:08 time: 0.5490 data_time: 0.0327 memory: 24011 grad_norm: 4.9105 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6716 loss: 0.6716 2022/09/05 17:26:19 - mmengine - INFO - Epoch(val) [50][20/78] eta: 0:00:41 time: 0.7104 data_time: 0.5498 memory: 3625 2022/09/05 17:26:28 - mmengine - INFO - Epoch(val) [50][40/78] eta: 0:00:17 time: 0.4552 data_time: 0.2836 memory: 3625 2022/09/05 17:26:42 - mmengine - INFO - Epoch(val) [50][60/78] eta: 0:00:12 time: 0.6672 data_time: 0.5115 memory: 3625 2022/09/05 17:26:52 - mmengine - INFO - Epoch(val) [50][78/78] acc/top1: 0.7414 acc/top5: 0.9077 acc/mean1: 0.7413 2022/09/05 17:26:52 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_49.pth is removed 2022/09/05 17:26:55 - mmengine - INFO - The best checkpoint with 0.7414 acc/top1 at 51 epoch is saved to best_acc/top1_epoch_51.pth. 2022/09/05 17:27:12 - mmengine - INFO - Epoch(train) [51][20/940] lr: 1.0000e-03 eta: 8:36:58 time: 0.8221 data_time: 0.2768 memory: 24011 grad_norm: 4.8077 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6164 loss: 0.6164 2022/09/05 17:27:25 - mmengine - INFO - Epoch(train) [51][40/940] lr: 1.0000e-03 eta: 8:36:44 time: 0.6485 data_time: 0.0675 memory: 24011 grad_norm: 4.7909 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6869 loss: 0.6869 2022/09/05 17:27:38 - mmengine - INFO - Epoch(train) [51][60/940] lr: 1.0000e-03 eta: 8:36:31 time: 0.6535 data_time: 0.0835 memory: 24011 grad_norm: 5.1957 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5939 loss: 0.5939 2022/09/05 17:27:51 - mmengine - INFO - Epoch(train) [51][80/940] lr: 1.0000e-03 eta: 8:36:18 time: 0.6547 data_time: 0.0562 memory: 24011 grad_norm: 4.9680 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6128 loss: 0.6128 2022/09/05 17:28:04 - mmengine - INFO - Epoch(train) [51][100/940] lr: 1.0000e-03 eta: 8:36:04 time: 0.6445 data_time: 0.0630 memory: 24011 grad_norm: 4.9359 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6065 loss: 0.6065 2022/09/05 17:28:17 - mmengine - INFO - Epoch(train) [51][120/940] lr: 1.0000e-03 eta: 8:35:51 time: 0.6595 data_time: 0.0583 memory: 24011 grad_norm: 4.8564 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6417 loss: 0.6417 2022/09/05 17:28:30 - mmengine - INFO - Epoch(train) [51][140/940] lr: 1.0000e-03 eta: 8:35:38 time: 0.6774 data_time: 0.1232 memory: 24011 grad_norm: 4.7730 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6808 loss: 0.6808 2022/09/05 17:28:43 - mmengine - INFO - Epoch(train) [51][160/940] lr: 1.0000e-03 eta: 8:35:24 time: 0.6150 data_time: 0.0463 memory: 24011 grad_norm: 5.1190 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6617 loss: 0.6617 2022/09/05 17:28:56 - mmengine - INFO - Epoch(train) [51][180/940] lr: 1.0000e-03 eta: 8:35:10 time: 0.6466 data_time: 0.0723 memory: 24011 grad_norm: 4.9307 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7062 loss: 0.7062 2022/09/05 17:29:10 - mmengine - INFO - Epoch(train) [51][200/940] lr: 1.0000e-03 eta: 8:34:58 time: 0.6913 data_time: 0.1291 memory: 24011 grad_norm: 5.0180 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7225 loss: 0.7225 2022/09/05 17:29:22 - mmengine - INFO - Epoch(train) [51][220/940] lr: 1.0000e-03 eta: 8:34:44 time: 0.6201 data_time: 0.0547 memory: 24011 grad_norm: 4.9544 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6594 loss: 0.6594 2022/09/05 17:29:35 - mmengine - INFO - Epoch(train) [51][240/940] lr: 1.0000e-03 eta: 8:34:31 time: 0.6653 data_time: 0.0970 memory: 24011 grad_norm: 5.0447 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6747 loss: 0.6747 2022/09/05 17:29:48 - mmengine - INFO - Epoch(train) [51][260/940] lr: 1.0000e-03 eta: 8:34:17 time: 0.6432 data_time: 0.0597 memory: 24011 grad_norm: 4.7731 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6447 loss: 0.6447 2022/09/05 17:30:00 - mmengine - INFO - Epoch(train) [51][280/940] lr: 1.0000e-03 eta: 8:34:03 time: 0.5954 data_time: 0.0282 memory: 24011 grad_norm: 4.8274 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6337 loss: 0.6337 2022/09/05 17:30:13 - mmengine - INFO - Epoch(train) [51][300/940] lr: 1.0000e-03 eta: 8:33:49 time: 0.6293 data_time: 0.0352 memory: 24011 grad_norm: 5.1277 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6778 loss: 0.6778 2022/09/05 17:30:26 - mmengine - INFO - Epoch(train) [51][320/940] lr: 1.0000e-03 eta: 8:33:36 time: 0.6587 data_time: 0.0890 memory: 24011 grad_norm: 4.6277 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6049 loss: 0.6049 2022/09/05 17:30:38 - mmengine - INFO - Epoch(train) [51][340/940] lr: 1.0000e-03 eta: 8:33:22 time: 0.6332 data_time: 0.0741 memory: 24011 grad_norm: 4.9528 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6413 loss: 0.6413 2022/09/05 17:30:50 - mmengine - INFO - Epoch(train) [51][360/940] lr: 1.0000e-03 eta: 8:33:07 time: 0.5931 data_time: 0.0369 memory: 24011 grad_norm: 4.8158 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6166 loss: 0.6166 2022/09/05 17:31:04 - mmengine - INFO - Epoch(train) [51][380/940] lr: 1.0000e-03 eta: 8:32:54 time: 0.6588 data_time: 0.0506 memory: 24011 grad_norm: 4.8050 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7415 loss: 0.7415 2022/09/05 17:31:16 - mmengine - INFO - Epoch(train) [51][400/940] lr: 1.0000e-03 eta: 8:32:41 time: 0.6409 data_time: 0.0549 memory: 24011 grad_norm: 4.6516 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6434 loss: 0.6434 2022/09/05 17:31:29 - mmengine - INFO - Epoch(train) [51][420/940] lr: 1.0000e-03 eta: 8:32:27 time: 0.6527 data_time: 0.0534 memory: 24011 grad_norm: 5.3157 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6697 loss: 0.6697 2022/09/05 17:31:43 - mmengine - INFO - Epoch(train) [51][440/940] lr: 1.0000e-03 eta: 8:32:14 time: 0.6720 data_time: 0.0396 memory: 24011 grad_norm: 4.9828 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6643 loss: 0.6643 2022/09/05 17:31:57 - mmengine - INFO - Epoch(train) [51][460/940] lr: 1.0000e-03 eta: 8:32:01 time: 0.6773 data_time: 0.0467 memory: 24011 grad_norm: 5.6150 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6296 loss: 0.6296 2022/09/05 17:32:10 - mmengine - INFO - Epoch(train) [51][480/940] lr: 1.0000e-03 eta: 8:31:49 time: 0.6770 data_time: 0.0642 memory: 24011 grad_norm: 4.8966 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6745 loss: 0.6745 2022/09/05 17:32:22 - mmengine - INFO - Epoch(train) [51][500/940] lr: 1.0000e-03 eta: 8:31:34 time: 0.5945 data_time: 0.0379 memory: 24011 grad_norm: 8.4933 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6907 loss: 0.6907 2022/09/05 17:32:35 - mmengine - INFO - Epoch(train) [51][520/940] lr: 1.0000e-03 eta: 8:31:20 time: 0.6210 data_time: 0.0436 memory: 24011 grad_norm: 5.1288 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7053 loss: 0.7053 2022/09/05 17:32:47 - mmengine - INFO - Epoch(train) [51][540/940] lr: 1.0000e-03 eta: 8:31:06 time: 0.6369 data_time: 0.0552 memory: 24011 grad_norm: 4.9012 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6898 loss: 0.6898 2022/09/05 17:33:00 - mmengine - INFO - Epoch(train) [51][560/940] lr: 1.0000e-03 eta: 8:30:53 time: 0.6440 data_time: 0.0438 memory: 24011 grad_norm: 4.7853 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7844 loss: 0.7844 2022/09/05 17:33:13 - mmengine - INFO - Epoch(train) [51][580/940] lr: 1.0000e-03 eta: 8:30:40 time: 0.6776 data_time: 0.0373 memory: 24011 grad_norm: 5.4254 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7055 loss: 0.7055 2022/09/05 17:33:26 - mmengine - INFO - Epoch(train) [51][600/940] lr: 1.0000e-03 eta: 8:30:27 time: 0.6433 data_time: 0.0366 memory: 24011 grad_norm: 5.0097 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6696 loss: 0.6696 2022/09/05 17:33:40 - mmengine - INFO - Epoch(train) [51][620/940] lr: 1.0000e-03 eta: 8:30:13 time: 0.6634 data_time: 0.0354 memory: 24011 grad_norm: 5.1375 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.7732 loss: 0.7732 2022/09/05 17:33:53 - mmengine - INFO - Epoch(train) [51][640/940] lr: 1.0000e-03 eta: 8:30:00 time: 0.6479 data_time: 0.0402 memory: 24011 grad_norm: 4.8913 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7798 loss: 0.7798 2022/09/05 17:34:06 - mmengine - INFO - Epoch(train) [51][660/940] lr: 1.0000e-03 eta: 8:29:47 time: 0.6771 data_time: 0.0373 memory: 24011 grad_norm: 4.6920 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.7283 loss: 0.7283 2022/09/05 17:34:19 - mmengine - INFO - Epoch(train) [51][680/940] lr: 1.0000e-03 eta: 8:29:34 time: 0.6624 data_time: 0.0384 memory: 24011 grad_norm: 4.9060 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.7121 loss: 0.7121 2022/09/05 17:34:33 - mmengine - INFO - Epoch(train) [51][700/940] lr: 1.0000e-03 eta: 8:29:21 time: 0.6496 data_time: 0.0379 memory: 24011 grad_norm: 4.7779 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6448 loss: 0.6448 2022/09/05 17:34:46 - mmengine - INFO - Epoch(train) [51][720/940] lr: 1.0000e-03 eta: 8:29:08 time: 0.6797 data_time: 0.0514 memory: 24011 grad_norm: 4.9398 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.7115 loss: 0.7115 2022/09/05 17:34:59 - mmengine - INFO - Epoch(train) [51][740/940] lr: 1.0000e-03 eta: 8:28:55 time: 0.6716 data_time: 0.0403 memory: 24011 grad_norm: 4.6581 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.7153 loss: 0.7153 2022/09/05 17:35:12 - mmengine - INFO - Epoch(train) [51][760/940] lr: 1.0000e-03 eta: 8:28:41 time: 0.6305 data_time: 0.0376 memory: 24011 grad_norm: 4.9598 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6819 loss: 0.6819 2022/09/05 17:35:26 - mmengine - INFO - Epoch(train) [51][780/940] lr: 1.0000e-03 eta: 8:28:28 time: 0.6720 data_time: 0.0432 memory: 24011 grad_norm: 5.0278 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6522 loss: 0.6522 2022/09/05 17:35:39 - mmengine - INFO - Epoch(train) [51][800/940] lr: 1.0000e-03 eta: 8:28:15 time: 0.6526 data_time: 0.0456 memory: 24011 grad_norm: 4.6324 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6962 loss: 0.6962 2022/09/05 17:35:51 - mmengine - INFO - Epoch(train) [51][820/940] lr: 1.0000e-03 eta: 8:28:01 time: 0.6362 data_time: 0.0426 memory: 24011 grad_norm: 5.0521 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.7281 loss: 0.7281 2022/09/05 17:36:04 - mmengine - INFO - Epoch(train) [51][840/940] lr: 1.0000e-03 eta: 8:27:47 time: 0.6383 data_time: 0.0452 memory: 24011 grad_norm: 4.6074 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6727 loss: 0.6727 2022/09/05 17:36:17 - mmengine - INFO - Epoch(train) [51][860/940] lr: 1.0000e-03 eta: 8:27:34 time: 0.6466 data_time: 0.0426 memory: 24011 grad_norm: 4.6845 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.7269 loss: 0.7269 2022/09/05 17:36:29 - mmengine - INFO - Epoch(train) [51][880/940] lr: 1.0000e-03 eta: 8:27:20 time: 0.6166 data_time: 0.0564 memory: 24011 grad_norm: 4.9184 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6981 loss: 0.6981 2022/09/05 17:36:43 - mmengine - INFO - Epoch(train) [51][900/940] lr: 1.0000e-03 eta: 8:27:07 time: 0.6717 data_time: 0.0387 memory: 24011 grad_norm: 5.4755 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6272 loss: 0.6272 2022/09/05 17:36:57 - mmengine - INFO - Epoch(train) [51][920/940] lr: 1.0000e-03 eta: 8:26:55 time: 0.7104 data_time: 0.0429 memory: 24011 grad_norm: 4.9897 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6683 loss: 0.6683 2022/09/05 17:37:08 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:37:08 - mmengine - INFO - Epoch(train) [51][940/940] lr: 1.0000e-03 eta: 8:26:39 time: 0.5317 data_time: 0.0270 memory: 24011 grad_norm: 4.9072 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.6786 loss: 0.6786 2022/09/05 17:37:08 - mmengine - INFO - Saving checkpoint at 51 epochs 2022/09/05 17:37:27 - mmengine - INFO - Epoch(val) [51][20/78] eta: 0:00:41 time: 0.7173 data_time: 0.5602 memory: 3625 2022/09/05 17:37:36 - mmengine - INFO - Epoch(val) [51][40/78] eta: 0:00:17 time: 0.4475 data_time: 0.2922 memory: 3625 2022/09/05 17:37:49 - mmengine - INFO - Epoch(val) [51][60/78] eta: 0:00:11 time: 0.6557 data_time: 0.4916 memory: 3625 2022/09/05 17:37:58 - mmengine - INFO - Epoch(val) [51][78/78] acc/top1: 0.7427 acc/top5: 0.9092 acc/mean1: 0.7426 2022/09/05 17:37:58 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_51.pth is removed 2022/09/05 17:38:01 - mmengine - INFO - The best checkpoint with 0.7427 acc/top1 at 52 epoch is saved to best_acc/top1_epoch_52.pth. 2022/09/05 17:38:19 - mmengine - INFO - Epoch(train) [52][20/940] lr: 1.0000e-03 eta: 8:26:30 time: 0.8809 data_time: 0.3288 memory: 24011 grad_norm: 4.6501 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.5760 loss: 0.5760 2022/09/05 17:38:32 - mmengine - INFO - Epoch(train) [52][40/940] lr: 1.0000e-03 eta: 8:26:17 time: 0.6525 data_time: 0.1085 memory: 24011 grad_norm: 5.3012 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6878 loss: 0.6878 2022/09/05 17:38:45 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:38:45 - mmengine - INFO - Epoch(train) [52][60/940] lr: 1.0000e-03 eta: 8:26:03 time: 0.6510 data_time: 0.0717 memory: 24011 grad_norm: 4.7113 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7228 loss: 0.7228 2022/09/05 17:38:57 - mmengine - INFO - Epoch(train) [52][80/940] lr: 1.0000e-03 eta: 8:25:49 time: 0.6032 data_time: 0.0356 memory: 24011 grad_norm: 4.8925 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6339 loss: 0.6339 2022/09/05 17:39:11 - mmengine - INFO - Epoch(train) [52][100/940] lr: 1.0000e-03 eta: 8:25:36 time: 0.6933 data_time: 0.1243 memory: 24011 grad_norm: 5.0253 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7265 loss: 0.7265 2022/09/05 17:39:24 - mmengine - INFO - Epoch(train) [52][120/940] lr: 1.0000e-03 eta: 8:25:23 time: 0.6292 data_time: 0.0508 memory: 24011 grad_norm: 4.7555 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6809 loss: 0.6809 2022/09/05 17:39:37 - mmengine - INFO - Epoch(train) [52][140/940] lr: 1.0000e-03 eta: 8:25:09 time: 0.6624 data_time: 0.1058 memory: 24011 grad_norm: 5.1175 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7275 loss: 0.7275 2022/09/05 17:39:50 - mmengine - INFO - Epoch(train) [52][160/940] lr: 1.0000e-03 eta: 8:24:56 time: 0.6679 data_time: 0.0788 memory: 24011 grad_norm: 4.6637 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6223 loss: 0.6223 2022/09/05 17:40:02 - mmengine - INFO - Epoch(train) [52][180/940] lr: 1.0000e-03 eta: 8:24:42 time: 0.6083 data_time: 0.0539 memory: 24011 grad_norm: 4.7644 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.7575 loss: 0.7575 2022/09/05 17:40:16 - mmengine - INFO - Epoch(train) [52][200/940] lr: 1.0000e-03 eta: 8:24:29 time: 0.6594 data_time: 0.0355 memory: 24011 grad_norm: 4.7757 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6520 loss: 0.6520 2022/09/05 17:40:28 - mmengine - INFO - Epoch(train) [52][220/940] lr: 1.0000e-03 eta: 8:24:15 time: 0.6165 data_time: 0.0462 memory: 24011 grad_norm: 5.0976 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7310 loss: 0.7310 2022/09/05 17:40:41 - mmengine - INFO - Epoch(train) [52][240/940] lr: 1.0000e-03 eta: 8:24:02 time: 0.6717 data_time: 0.0856 memory: 24011 grad_norm: 4.9321 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6991 loss: 0.6991 2022/09/05 17:40:54 - mmengine - INFO - Epoch(train) [52][260/940] lr: 1.0000e-03 eta: 8:23:48 time: 0.6093 data_time: 0.0477 memory: 24011 grad_norm: 4.9541 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7189 loss: 0.7189 2022/09/05 17:41:07 - mmengine - INFO - Epoch(train) [52][280/940] lr: 1.0000e-03 eta: 8:23:35 time: 0.6954 data_time: 0.0448 memory: 24011 grad_norm: 4.8485 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6820 loss: 0.6820 2022/09/05 17:41:20 - mmengine - INFO - Epoch(train) [52][300/940] lr: 1.0000e-03 eta: 8:23:21 time: 0.6063 data_time: 0.0429 memory: 24011 grad_norm: 5.3401 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7181 loss: 0.7181 2022/09/05 17:41:33 - mmengine - INFO - Epoch(train) [52][320/940] lr: 1.0000e-03 eta: 8:23:08 time: 0.6808 data_time: 0.0493 memory: 24011 grad_norm: 5.1040 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6322 loss: 0.6322 2022/09/05 17:41:46 - mmengine - INFO - Epoch(train) [52][340/940] lr: 1.0000e-03 eta: 8:22:55 time: 0.6328 data_time: 0.0543 memory: 24011 grad_norm: 5.1530 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7120 loss: 0.7120 2022/09/05 17:41:59 - mmengine - INFO - Epoch(train) [52][360/940] lr: 1.0000e-03 eta: 8:22:41 time: 0.6516 data_time: 0.0373 memory: 24011 grad_norm: 4.9041 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6780 loss: 0.6780 2022/09/05 17:42:13 - mmengine - INFO - Epoch(train) [52][380/940] lr: 1.0000e-03 eta: 8:22:29 time: 0.7146 data_time: 0.1340 memory: 24011 grad_norm: 4.8178 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6246 loss: 0.6246 2022/09/05 17:42:27 - mmengine - INFO - Epoch(train) [52][400/940] lr: 1.0000e-03 eta: 8:22:16 time: 0.6828 data_time: 0.0981 memory: 24011 grad_norm: 5.8610 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7404 loss: 0.7404 2022/09/05 17:42:40 - mmengine - INFO - Epoch(train) [52][420/940] lr: 1.0000e-03 eta: 8:22:03 time: 0.6395 data_time: 0.0629 memory: 24011 grad_norm: 5.4752 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6623 loss: 0.6623 2022/09/05 17:42:52 - mmengine - INFO - Epoch(train) [52][440/940] lr: 1.0000e-03 eta: 8:21:48 time: 0.6021 data_time: 0.0340 memory: 24011 grad_norm: 5.0002 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7051 loss: 0.7051 2022/09/05 17:43:05 - mmengine - INFO - Epoch(train) [52][460/940] lr: 1.0000e-03 eta: 8:21:36 time: 0.6847 data_time: 0.0873 memory: 24011 grad_norm: 4.8225 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7659 loss: 0.7659 2022/09/05 17:43:17 - mmengine - INFO - Epoch(train) [52][480/940] lr: 1.0000e-03 eta: 8:21:21 time: 0.5970 data_time: 0.0406 memory: 24011 grad_norm: 4.9947 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7655 loss: 0.7655 2022/09/05 17:43:30 - mmengine - INFO - Epoch(train) [52][500/940] lr: 1.0000e-03 eta: 8:21:08 time: 0.6525 data_time: 0.0893 memory: 24011 grad_norm: 5.2731 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6416 loss: 0.6416 2022/09/05 17:43:43 - mmengine - INFO - Epoch(train) [52][520/940] lr: 1.0000e-03 eta: 8:20:55 time: 0.6533 data_time: 0.0906 memory: 24011 grad_norm: 5.5401 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6892 loss: 0.6892 2022/09/05 17:43:56 - mmengine - INFO - Epoch(train) [52][540/940] lr: 1.0000e-03 eta: 8:20:41 time: 0.6399 data_time: 0.0667 memory: 24011 grad_norm: 4.7190 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6755 loss: 0.6755 2022/09/05 17:44:09 - mmengine - INFO - Epoch(train) [52][560/940] lr: 1.0000e-03 eta: 8:20:27 time: 0.6314 data_time: 0.0423 memory: 24011 grad_norm: 4.9464 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.7455 loss: 0.7455 2022/09/05 17:44:22 - mmengine - INFO - Epoch(train) [52][580/940] lr: 1.0000e-03 eta: 8:20:14 time: 0.6530 data_time: 0.0544 memory: 24011 grad_norm: 4.7950 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.6578 loss: 0.6578 2022/09/05 17:44:36 - mmengine - INFO - Epoch(train) [52][600/940] lr: 1.0000e-03 eta: 8:20:01 time: 0.6924 data_time: 0.0646 memory: 24011 grad_norm: 4.9818 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6708 loss: 0.6708 2022/09/05 17:44:49 - mmengine - INFO - Epoch(train) [52][620/940] lr: 1.0000e-03 eta: 8:19:48 time: 0.6647 data_time: 0.0887 memory: 24011 grad_norm: 5.0081 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8077 loss: 0.8077 2022/09/05 17:45:01 - mmengine - INFO - Epoch(train) [52][640/940] lr: 1.0000e-03 eta: 8:19:34 time: 0.6131 data_time: 0.0292 memory: 24011 grad_norm: 5.1496 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6814 loss: 0.6814 2022/09/05 17:45:14 - mmengine - INFO - Epoch(train) [52][660/940] lr: 1.0000e-03 eta: 8:19:20 time: 0.6098 data_time: 0.0400 memory: 24011 grad_norm: 4.7478 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7277 loss: 0.7277 2022/09/05 17:45:27 - mmengine - INFO - Epoch(train) [52][680/940] lr: 1.0000e-03 eta: 8:19:07 time: 0.6823 data_time: 0.0513 memory: 24011 grad_norm: 4.7933 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6437 loss: 0.6437 2022/09/05 17:45:40 - mmengine - INFO - Epoch(train) [52][700/940] lr: 1.0000e-03 eta: 8:18:54 time: 0.6523 data_time: 0.0815 memory: 24011 grad_norm: 5.0307 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7430 loss: 0.7430 2022/09/05 17:45:54 - mmengine - INFO - Epoch(train) [52][720/940] lr: 1.0000e-03 eta: 8:18:41 time: 0.6709 data_time: 0.0310 memory: 24011 grad_norm: 5.2330 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.7589 loss: 0.7589 2022/09/05 17:46:07 - mmengine - INFO - Epoch(train) [52][740/940] lr: 1.0000e-03 eta: 8:18:28 time: 0.6557 data_time: 0.0388 memory: 24011 grad_norm: 5.1568 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7444 loss: 0.7444 2022/09/05 17:46:19 - mmengine - INFO - Epoch(train) [52][760/940] lr: 1.0000e-03 eta: 8:18:14 time: 0.6169 data_time: 0.0345 memory: 24011 grad_norm: 4.8487 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6205 loss: 0.6205 2022/09/05 17:46:31 - mmengine - INFO - Epoch(train) [52][780/940] lr: 1.0000e-03 eta: 8:17:59 time: 0.6071 data_time: 0.0439 memory: 24011 grad_norm: 4.8052 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 0.6510 loss: 0.6510 2022/09/05 17:46:44 - mmengine - INFO - Epoch(train) [52][800/940] lr: 1.0000e-03 eta: 8:17:46 time: 0.6278 data_time: 0.0375 memory: 24011 grad_norm: 4.8861 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6670 loss: 0.6670 2022/09/05 17:46:58 - mmengine - INFO - Epoch(train) [52][820/940] lr: 1.0000e-03 eta: 8:17:33 time: 0.6805 data_time: 0.0422 memory: 24011 grad_norm: 4.7253 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6536 loss: 0.6536 2022/09/05 17:47:11 - mmengine - INFO - Epoch(train) [52][840/940] lr: 1.0000e-03 eta: 8:17:19 time: 0.6483 data_time: 0.0358 memory: 24011 grad_norm: 4.7367 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.7025 loss: 0.7025 2022/09/05 17:47:23 - mmengine - INFO - Epoch(train) [52][860/940] lr: 1.0000e-03 eta: 8:17:06 time: 0.6452 data_time: 0.0382 memory: 24011 grad_norm: 5.8424 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6922 loss: 0.6922 2022/09/05 17:47:37 - mmengine - INFO - Epoch(train) [52][880/940] lr: 1.0000e-03 eta: 8:16:53 time: 0.6561 data_time: 0.0413 memory: 24011 grad_norm: 4.9282 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6177 loss: 0.6177 2022/09/05 17:47:49 - mmengine - INFO - Epoch(train) [52][900/940] lr: 1.0000e-03 eta: 8:16:39 time: 0.6163 data_time: 0.0388 memory: 24011 grad_norm: 5.1848 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6506 loss: 0.6506 2022/09/05 17:48:02 - mmengine - INFO - Epoch(train) [52][920/940] lr: 1.0000e-03 eta: 8:16:25 time: 0.6380 data_time: 0.0374 memory: 24011 grad_norm: 5.0982 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5823 loss: 0.5823 2022/09/05 17:48:13 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:48:13 - mmengine - INFO - Epoch(train) [52][940/940] lr: 1.0000e-03 eta: 8:16:11 time: 0.5906 data_time: 0.0724 memory: 24011 grad_norm: 4.8470 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.6223 loss: 0.6223 2022/09/05 17:48:28 - mmengine - INFO - Epoch(val) [52][20/78] eta: 0:00:40 time: 0.6981 data_time: 0.5403 memory: 3625 2022/09/05 17:48:37 - mmengine - INFO - Epoch(val) [52][40/78] eta: 0:00:17 time: 0.4732 data_time: 0.3168 memory: 3625 2022/09/05 17:48:50 - mmengine - INFO - Epoch(val) [52][60/78] eta: 0:00:11 time: 0.6373 data_time: 0.4792 memory: 3625 2022/09/05 17:49:00 - mmengine - INFO - Epoch(val) [52][78/78] acc/top1: 0.7399 acc/top5: 0.9088 acc/mean1: 0.7398 2022/09/05 17:49:19 - mmengine - INFO - Epoch(train) [53][20/940] lr: 1.0000e-03 eta: 8:16:02 time: 0.9210 data_time: 0.2949 memory: 24011 grad_norm: 4.5980 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5541 loss: 0.5541 2022/09/05 17:49:32 - mmengine - INFO - Epoch(train) [53][40/940] lr: 1.0000e-03 eta: 8:15:49 time: 0.6446 data_time: 0.0446 memory: 24011 grad_norm: 4.9162 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6058 loss: 0.6058 2022/09/05 17:49:45 - mmengine - INFO - Epoch(train) [53][60/940] lr: 1.0000e-03 eta: 8:15:35 time: 0.6547 data_time: 0.0435 memory: 24011 grad_norm: 5.2307 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7107 loss: 0.7107 2022/09/05 17:49:57 - mmengine - INFO - Epoch(train) [53][80/940] lr: 1.0000e-03 eta: 8:15:22 time: 0.6377 data_time: 0.0347 memory: 24011 grad_norm: 4.8597 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7511 loss: 0.7511 2022/09/05 17:50:11 - mmengine - INFO - Epoch(train) [53][100/940] lr: 1.0000e-03 eta: 8:15:09 time: 0.6878 data_time: 0.0397 memory: 24011 grad_norm: 4.5849 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6747 loss: 0.6747 2022/09/05 17:50:23 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:50:24 - mmengine - INFO - Epoch(train) [53][120/940] lr: 1.0000e-03 eta: 8:14:55 time: 0.6151 data_time: 0.0379 memory: 24011 grad_norm: 4.6079 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.6917 loss: 0.6917 2022/09/05 17:50:37 - mmengine - INFO - Epoch(train) [53][140/940] lr: 1.0000e-03 eta: 8:14:43 time: 0.6913 data_time: 0.0526 memory: 24011 grad_norm: 4.9603 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.6441 loss: 0.6441 2022/09/05 17:50:50 - mmengine - INFO - Epoch(train) [53][160/940] lr: 1.0000e-03 eta: 8:14:29 time: 0.6419 data_time: 0.0342 memory: 24011 grad_norm: 5.3279 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5936 loss: 0.5936 2022/09/05 17:51:03 - mmengine - INFO - Epoch(train) [53][180/940] lr: 1.0000e-03 eta: 8:14:16 time: 0.6578 data_time: 0.0466 memory: 24011 grad_norm: 4.7644 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6696 loss: 0.6696 2022/09/05 17:51:16 - mmengine - INFO - Epoch(train) [53][200/940] lr: 1.0000e-03 eta: 8:14:02 time: 0.6360 data_time: 0.0354 memory: 24011 grad_norm: 5.1361 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.7446 loss: 0.7446 2022/09/05 17:51:30 - mmengine - INFO - Epoch(train) [53][220/940] lr: 1.0000e-03 eta: 8:13:50 time: 0.6932 data_time: 0.0363 memory: 24011 grad_norm: 4.9856 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7252 loss: 0.7252 2022/09/05 17:51:43 - mmengine - INFO - Epoch(train) [53][240/940] lr: 1.0000e-03 eta: 8:13:36 time: 0.6362 data_time: 0.0393 memory: 24011 grad_norm: 4.6301 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6219 loss: 0.6219 2022/09/05 17:51:56 - mmengine - INFO - Epoch(train) [53][260/940] lr: 1.0000e-03 eta: 8:13:22 time: 0.6431 data_time: 0.0385 memory: 24011 grad_norm: 4.7267 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6947 loss: 0.6947 2022/09/05 17:52:08 - mmengine - INFO - Epoch(train) [53][280/940] lr: 1.0000e-03 eta: 8:13:09 time: 0.6232 data_time: 0.0342 memory: 24011 grad_norm: 5.0250 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6986 loss: 0.6986 2022/09/05 17:52:21 - mmengine - INFO - Epoch(train) [53][300/940] lr: 1.0000e-03 eta: 8:12:56 time: 0.6693 data_time: 0.0506 memory: 24011 grad_norm: 5.0814 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6466 loss: 0.6466 2022/09/05 17:52:34 - mmengine - INFO - Epoch(train) [53][320/940] lr: 1.0000e-03 eta: 8:12:42 time: 0.6341 data_time: 0.0367 memory: 24011 grad_norm: 4.8011 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6069 loss: 0.6069 2022/09/05 17:52:48 - mmengine - INFO - Epoch(train) [53][340/940] lr: 1.0000e-03 eta: 8:12:29 time: 0.6749 data_time: 0.0404 memory: 24011 grad_norm: 5.5435 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6708 loss: 0.6708 2022/09/05 17:53:01 - mmengine - INFO - Epoch(train) [53][360/940] lr: 1.0000e-03 eta: 8:12:16 time: 0.6504 data_time: 0.0390 memory: 24011 grad_norm: 4.6918 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6271 loss: 0.6271 2022/09/05 17:53:14 - mmengine - INFO - Epoch(train) [53][380/940] lr: 1.0000e-03 eta: 8:12:02 time: 0.6540 data_time: 0.0419 memory: 24011 grad_norm: 4.7270 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7163 loss: 0.7163 2022/09/05 17:53:27 - mmengine - INFO - Epoch(train) [53][400/940] lr: 1.0000e-03 eta: 8:11:49 time: 0.6677 data_time: 0.0436 memory: 24011 grad_norm: 4.9620 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6836 loss: 0.6836 2022/09/05 17:53:40 - mmengine - INFO - Epoch(train) [53][420/940] lr: 1.0000e-03 eta: 8:11:36 time: 0.6454 data_time: 0.0426 memory: 24011 grad_norm: 5.5979 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.6785 loss: 0.6785 2022/09/05 17:53:52 - mmengine - INFO - Epoch(train) [53][440/940] lr: 1.0000e-03 eta: 8:11:22 time: 0.6073 data_time: 0.0460 memory: 24011 grad_norm: 5.5339 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6943 loss: 0.6943 2022/09/05 17:54:05 - mmengine - INFO - Epoch(train) [53][460/940] lr: 1.0000e-03 eta: 8:11:08 time: 0.6339 data_time: 0.0414 memory: 24011 grad_norm: 4.8555 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6594 loss: 0.6594 2022/09/05 17:54:18 - mmengine - INFO - Epoch(train) [53][480/940] lr: 1.0000e-03 eta: 8:10:55 time: 0.6592 data_time: 0.0465 memory: 24011 grad_norm: 5.0560 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6518 loss: 0.6518 2022/09/05 17:54:32 - mmengine - INFO - Epoch(train) [53][500/940] lr: 1.0000e-03 eta: 8:10:42 time: 0.6814 data_time: 0.0334 memory: 24011 grad_norm: 4.8454 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7250 loss: 0.7250 2022/09/05 17:54:44 - mmengine - INFO - Epoch(train) [53][520/940] lr: 1.0000e-03 eta: 8:10:28 time: 0.6301 data_time: 0.0383 memory: 24011 grad_norm: 4.7080 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6330 loss: 0.6330 2022/09/05 17:54:57 - mmengine - INFO - Epoch(train) [53][540/940] lr: 1.0000e-03 eta: 8:10:15 time: 0.6475 data_time: 0.0401 memory: 24011 grad_norm: 5.1943 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7381 loss: 0.7381 2022/09/05 17:55:10 - mmengine - INFO - Epoch(train) [53][560/940] lr: 1.0000e-03 eta: 8:10:01 time: 0.6278 data_time: 0.0378 memory: 24011 grad_norm: 4.8723 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6936 loss: 0.6936 2022/09/05 17:55:23 - mmengine - INFO - Epoch(train) [53][580/940] lr: 1.0000e-03 eta: 8:09:48 time: 0.6593 data_time: 0.0423 memory: 24011 grad_norm: 5.3361 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5647 loss: 0.5647 2022/09/05 17:55:35 - mmengine - INFO - Epoch(train) [53][600/940] lr: 1.0000e-03 eta: 8:09:34 time: 0.6027 data_time: 0.0324 memory: 24011 grad_norm: 4.9343 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6695 loss: 0.6695 2022/09/05 17:55:49 - mmengine - INFO - Epoch(train) [53][620/940] lr: 1.0000e-03 eta: 8:09:21 time: 0.6819 data_time: 0.0367 memory: 24011 grad_norm: 4.7680 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6655 loss: 0.6655 2022/09/05 17:56:01 - mmengine - INFO - Epoch(train) [53][640/940] lr: 1.0000e-03 eta: 8:09:07 time: 0.6270 data_time: 0.0364 memory: 24011 grad_norm: 5.0214 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6114 loss: 0.6114 2022/09/05 17:56:14 - mmengine - INFO - Epoch(train) [53][660/940] lr: 1.0000e-03 eta: 8:08:54 time: 0.6544 data_time: 0.0389 memory: 24011 grad_norm: 5.0723 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6374 loss: 0.6374 2022/09/05 17:56:27 - mmengine - INFO - Epoch(train) [53][680/940] lr: 1.0000e-03 eta: 8:08:40 time: 0.6535 data_time: 0.0670 memory: 24011 grad_norm: 4.8008 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7124 loss: 0.7124 2022/09/05 17:56:40 - mmengine - INFO - Epoch(train) [53][700/940] lr: 1.0000e-03 eta: 8:08:27 time: 0.6277 data_time: 0.0356 memory: 24011 grad_norm: 5.0636 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7156 loss: 0.7156 2022/09/05 17:56:53 - mmengine - INFO - Epoch(train) [53][720/940] lr: 1.0000e-03 eta: 8:08:13 time: 0.6455 data_time: 0.0332 memory: 24011 grad_norm: 4.7098 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5768 loss: 0.5768 2022/09/05 17:57:06 - mmengine - INFO - Epoch(train) [53][740/940] lr: 1.0000e-03 eta: 8:08:00 time: 0.6719 data_time: 0.0386 memory: 24011 grad_norm: 4.7258 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.7151 loss: 0.7151 2022/09/05 17:57:19 - mmengine - INFO - Epoch(train) [53][760/940] lr: 1.0000e-03 eta: 8:07:46 time: 0.6227 data_time: 0.0428 memory: 24011 grad_norm: 4.8069 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6216 loss: 0.6216 2022/09/05 17:57:32 - mmengine - INFO - Epoch(train) [53][780/940] lr: 1.0000e-03 eta: 8:07:33 time: 0.6799 data_time: 0.0396 memory: 24011 grad_norm: 4.9373 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6766 loss: 0.6766 2022/09/05 17:57:45 - mmengine - INFO - Epoch(train) [53][800/940] lr: 1.0000e-03 eta: 8:07:20 time: 0.6358 data_time: 0.0433 memory: 24011 grad_norm: 4.6814 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6587 loss: 0.6587 2022/09/05 17:57:58 - mmengine - INFO - Epoch(train) [53][820/940] lr: 1.0000e-03 eta: 8:07:06 time: 0.6229 data_time: 0.0384 memory: 24011 grad_norm: 5.1164 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7279 loss: 0.7279 2022/09/05 17:58:11 - mmengine - INFO - Epoch(train) [53][840/940] lr: 1.0000e-03 eta: 8:06:53 time: 0.6659 data_time: 0.0446 memory: 24011 grad_norm: 4.9822 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7038 loss: 0.7038 2022/09/05 17:58:24 - mmengine - INFO - Epoch(train) [53][860/940] lr: 1.0000e-03 eta: 8:06:40 time: 0.6542 data_time: 0.0396 memory: 24011 grad_norm: 4.6681 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6804 loss: 0.6804 2022/09/05 17:58:37 - mmengine - INFO - Epoch(train) [53][880/940] lr: 1.0000e-03 eta: 8:06:26 time: 0.6409 data_time: 0.0442 memory: 24011 grad_norm: 5.0229 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6499 loss: 0.6499 2022/09/05 17:58:49 - mmengine - INFO - Epoch(train) [53][900/940] lr: 1.0000e-03 eta: 8:06:12 time: 0.6264 data_time: 0.0402 memory: 24011 grad_norm: 5.6016 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6479 loss: 0.6479 2022/09/05 17:59:02 - mmengine - INFO - Epoch(train) [53][920/940] lr: 1.0000e-03 eta: 8:05:59 time: 0.6433 data_time: 0.0429 memory: 24011 grad_norm: 6.5398 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6365 loss: 0.6365 2022/09/05 17:59:13 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 17:59:13 - mmengine - INFO - Epoch(train) [53][940/940] lr: 1.0000e-03 eta: 8:05:44 time: 0.5580 data_time: 0.0248 memory: 24011 grad_norm: 5.1421 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 0.6766 loss: 0.6766 2022/09/05 17:59:28 - mmengine - INFO - Epoch(val) [53][20/78] eta: 0:00:40 time: 0.7059 data_time: 0.5450 memory: 3625 2022/09/05 17:59:37 - mmengine - INFO - Epoch(val) [53][40/78] eta: 0:00:17 time: 0.4715 data_time: 0.3113 memory: 3625 2022/09/05 17:59:50 - mmengine - INFO - Epoch(val) [53][60/78] eta: 0:00:11 time: 0.6647 data_time: 0.5076 memory: 3625 2022/09/05 18:00:00 - mmengine - INFO - Epoch(val) [53][78/78] acc/top1: 0.7393 acc/top5: 0.9077 acc/mean1: 0.7392 2022/09/05 18:00:20 - mmengine - INFO - Epoch(train) [54][20/940] lr: 1.0000e-03 eta: 8:05:37 time: 0.9924 data_time: 0.3288 memory: 24011 grad_norm: 5.5898 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6157 loss: 0.6157 2022/09/05 18:00:32 - mmengine - INFO - Epoch(train) [54][40/940] lr: 1.0000e-03 eta: 8:05:23 time: 0.6302 data_time: 0.0529 memory: 24011 grad_norm: 4.9842 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7107 loss: 0.7107 2022/09/05 18:00:46 - mmengine - INFO - Epoch(train) [54][60/940] lr: 1.0000e-03 eta: 8:05:10 time: 0.6604 data_time: 0.0400 memory: 24011 grad_norm: 4.8325 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7161 loss: 0.7161 2022/09/05 18:00:59 - mmengine - INFO - Epoch(train) [54][80/940] lr: 1.0000e-03 eta: 8:04:56 time: 0.6484 data_time: 0.0418 memory: 24011 grad_norm: 4.9947 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.7583 loss: 0.7583 2022/09/05 18:01:12 - mmengine - INFO - Epoch(train) [54][100/940] lr: 1.0000e-03 eta: 8:04:43 time: 0.6675 data_time: 0.0439 memory: 24011 grad_norm: 4.7109 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7180 loss: 0.7180 2022/09/05 18:01:25 - mmengine - INFO - Epoch(train) [54][120/940] lr: 1.0000e-03 eta: 8:04:30 time: 0.6398 data_time: 0.0376 memory: 24011 grad_norm: 4.9275 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6682 loss: 0.6682 2022/09/05 18:01:38 - mmengine - INFO - Epoch(train) [54][140/940] lr: 1.0000e-03 eta: 8:04:17 time: 0.6736 data_time: 0.0399 memory: 24011 grad_norm: 5.5542 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7256 loss: 0.7256 2022/09/05 18:01:50 - mmengine - INFO - Epoch(train) [54][160/940] lr: 1.0000e-03 eta: 8:04:02 time: 0.5954 data_time: 0.0428 memory: 24011 grad_norm: 4.9222 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7142 loss: 0.7142 2022/09/05 18:02:04 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:02:04 - mmengine - INFO - Epoch(train) [54][180/940] lr: 1.0000e-03 eta: 8:03:50 time: 0.6847 data_time: 0.0434 memory: 24011 grad_norm: 4.7198 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5598 loss: 0.5598 2022/09/05 18:02:17 - mmengine - INFO - Epoch(train) [54][200/940] lr: 1.0000e-03 eta: 8:03:36 time: 0.6366 data_time: 0.0316 memory: 24011 grad_norm: 4.7185 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6286 loss: 0.6286 2022/09/05 18:02:30 - mmengine - INFO - Epoch(train) [54][220/940] lr: 1.0000e-03 eta: 8:03:23 time: 0.6694 data_time: 0.0399 memory: 24011 grad_norm: 5.0070 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6587 loss: 0.6587 2022/09/05 18:02:43 - mmengine - INFO - Epoch(train) [54][240/940] lr: 1.0000e-03 eta: 8:03:09 time: 0.6308 data_time: 0.0410 memory: 24011 grad_norm: 4.5998 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6177 loss: 0.6177 2022/09/05 18:02:56 - mmengine - INFO - Epoch(train) [54][260/940] lr: 1.0000e-03 eta: 8:02:56 time: 0.6700 data_time: 0.0442 memory: 24011 grad_norm: 5.4125 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6250 loss: 0.6250 2022/09/05 18:03:09 - mmengine - INFO - Epoch(train) [54][280/940] lr: 1.0000e-03 eta: 8:02:43 time: 0.6464 data_time: 0.0390 memory: 24011 grad_norm: 5.0364 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6519 loss: 0.6519 2022/09/05 18:03:22 - mmengine - INFO - Epoch(train) [54][300/940] lr: 1.0000e-03 eta: 8:02:30 time: 0.6621 data_time: 0.0386 memory: 24011 grad_norm: 4.6976 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6854 loss: 0.6854 2022/09/05 18:03:34 - mmengine - INFO - Epoch(train) [54][320/940] lr: 1.0000e-03 eta: 8:02:16 time: 0.6111 data_time: 0.0348 memory: 24011 grad_norm: 4.9004 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7167 loss: 0.7167 2022/09/05 18:03:48 - mmengine - INFO - Epoch(train) [54][340/940] lr: 1.0000e-03 eta: 8:02:03 time: 0.6799 data_time: 0.0391 memory: 24011 grad_norm: 5.4778 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7259 loss: 0.7259 2022/09/05 18:04:00 - mmengine - INFO - Epoch(train) [54][360/940] lr: 1.0000e-03 eta: 8:01:49 time: 0.6121 data_time: 0.0360 memory: 24011 grad_norm: 4.8849 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6047 loss: 0.6047 2022/09/05 18:04:14 - mmengine - INFO - Epoch(train) [54][380/940] lr: 1.0000e-03 eta: 8:01:36 time: 0.6712 data_time: 0.0375 memory: 24011 grad_norm: 5.3723 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6371 loss: 0.6371 2022/09/05 18:04:26 - mmengine - INFO - Epoch(train) [54][400/940] lr: 1.0000e-03 eta: 8:01:21 time: 0.5953 data_time: 0.0419 memory: 24011 grad_norm: 4.6514 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7030 loss: 0.7030 2022/09/05 18:04:39 - mmengine - INFO - Epoch(train) [54][420/940] lr: 1.0000e-03 eta: 8:01:09 time: 0.6779 data_time: 0.0634 memory: 24011 grad_norm: 5.2160 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5642 loss: 0.5642 2022/09/05 18:04:52 - mmengine - INFO - Epoch(train) [54][440/940] lr: 1.0000e-03 eta: 8:00:55 time: 0.6424 data_time: 0.0382 memory: 24011 grad_norm: 4.9583 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6616 loss: 0.6616 2022/09/05 18:05:05 - mmengine - INFO - Epoch(train) [54][460/940] lr: 1.0000e-03 eta: 8:00:42 time: 0.6519 data_time: 0.0387 memory: 24011 grad_norm: 4.8445 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6525 loss: 0.6525 2022/09/05 18:05:19 - mmengine - INFO - Epoch(train) [54][480/940] lr: 1.0000e-03 eta: 8:00:29 time: 0.6793 data_time: 0.0465 memory: 24011 grad_norm: 4.9942 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6274 loss: 0.6274 2022/09/05 18:05:32 - mmengine - INFO - Epoch(train) [54][500/940] lr: 1.0000e-03 eta: 8:00:15 time: 0.6456 data_time: 0.0372 memory: 24011 grad_norm: 4.9412 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6507 loss: 0.6507 2022/09/05 18:05:44 - mmengine - INFO - Epoch(train) [54][520/940] lr: 1.0000e-03 eta: 8:00:02 time: 0.6273 data_time: 0.0361 memory: 24011 grad_norm: 4.8373 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5761 loss: 0.5761 2022/09/05 18:05:57 - mmengine - INFO - Epoch(train) [54][540/940] lr: 1.0000e-03 eta: 7:59:48 time: 0.6360 data_time: 0.0356 memory: 24011 grad_norm: 4.7984 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7034 loss: 0.7034 2022/09/05 18:06:10 - mmengine - INFO - Epoch(train) [54][560/940] lr: 1.0000e-03 eta: 7:59:35 time: 0.6378 data_time: 0.0471 memory: 24011 grad_norm: 5.4931 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6967 loss: 0.6967 2022/09/05 18:06:22 - mmengine - INFO - Epoch(train) [54][580/940] lr: 1.0000e-03 eta: 7:59:21 time: 0.6325 data_time: 0.0396 memory: 24011 grad_norm: 5.1100 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7326 loss: 0.7326 2022/09/05 18:06:35 - mmengine - INFO - Epoch(train) [54][600/940] lr: 1.0000e-03 eta: 7:59:08 time: 0.6532 data_time: 0.0484 memory: 24011 grad_norm: 4.7550 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6929 loss: 0.6929 2022/09/05 18:06:48 - mmengine - INFO - Epoch(train) [54][620/940] lr: 1.0000e-03 eta: 7:58:54 time: 0.6546 data_time: 0.0349 memory: 24011 grad_norm: 4.7842 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7002 loss: 0.7002 2022/09/05 18:07:01 - mmengine - INFO - Epoch(train) [54][640/940] lr: 1.0000e-03 eta: 7:58:41 time: 0.6346 data_time: 0.0423 memory: 24011 grad_norm: 4.7426 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7077 loss: 0.7077 2022/09/05 18:07:14 - mmengine - INFO - Epoch(train) [54][660/940] lr: 1.0000e-03 eta: 7:58:27 time: 0.6622 data_time: 0.0402 memory: 24011 grad_norm: 4.7793 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6938 loss: 0.6938 2022/09/05 18:07:28 - mmengine - INFO - Epoch(train) [54][680/940] lr: 1.0000e-03 eta: 7:58:14 time: 0.6696 data_time: 0.0439 memory: 24011 grad_norm: 5.0118 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6112 loss: 0.6112 2022/09/05 18:07:41 - mmengine - INFO - Epoch(train) [54][700/940] lr: 1.0000e-03 eta: 7:58:01 time: 0.6579 data_time: 0.0388 memory: 24011 grad_norm: 5.1640 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7169 loss: 0.7169 2022/09/05 18:07:54 - mmengine - INFO - Epoch(train) [54][720/940] lr: 1.0000e-03 eta: 7:57:48 time: 0.6678 data_time: 0.0382 memory: 24011 grad_norm: 4.8550 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6255 loss: 0.6255 2022/09/05 18:08:07 - mmengine - INFO - Epoch(train) [54][740/940] lr: 1.0000e-03 eta: 7:57:35 time: 0.6403 data_time: 0.0335 memory: 24011 grad_norm: 4.6731 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6971 loss: 0.6971 2022/09/05 18:08:21 - mmengine - INFO - Epoch(train) [54][760/940] lr: 1.0000e-03 eta: 7:57:22 time: 0.6906 data_time: 0.0430 memory: 24011 grad_norm: 5.4435 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6046 loss: 0.6046 2022/09/05 18:08:33 - mmengine - INFO - Epoch(train) [54][780/940] lr: 1.0000e-03 eta: 7:57:08 time: 0.6132 data_time: 0.0357 memory: 24011 grad_norm: 4.9816 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6316 loss: 0.6316 2022/09/05 18:08:46 - mmengine - INFO - Epoch(train) [54][800/940] lr: 1.0000e-03 eta: 7:56:54 time: 0.6363 data_time: 0.0408 memory: 24011 grad_norm: 4.8179 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7326 loss: 0.7326 2022/09/05 18:08:59 - mmengine - INFO - Epoch(train) [54][820/940] lr: 1.0000e-03 eta: 7:56:41 time: 0.6562 data_time: 0.0632 memory: 24011 grad_norm: 4.7146 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7434 loss: 0.7434 2022/09/05 18:09:13 - mmengine - INFO - Epoch(train) [54][840/940] lr: 1.0000e-03 eta: 7:56:28 time: 0.6760 data_time: 0.0390 memory: 24011 grad_norm: 4.6660 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6046 loss: 0.6046 2022/09/05 18:09:25 - mmengine - INFO - Epoch(train) [54][860/940] lr: 1.0000e-03 eta: 7:56:14 time: 0.6151 data_time: 0.0407 memory: 24011 grad_norm: 5.2457 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7207 loss: 0.7207 2022/09/05 18:09:38 - mmengine - INFO - Epoch(train) [54][880/940] lr: 1.0000e-03 eta: 7:56:01 time: 0.6342 data_time: 0.0511 memory: 24011 grad_norm: 4.9552 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6757 loss: 0.6757 2022/09/05 18:09:51 - mmengine - INFO - Epoch(train) [54][900/940] lr: 1.0000e-03 eta: 7:55:48 time: 0.6764 data_time: 0.0353 memory: 24011 grad_norm: 4.8051 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6410 loss: 0.6410 2022/09/05 18:10:03 - mmengine - INFO - Epoch(train) [54][920/940] lr: 1.0000e-03 eta: 7:55:34 time: 0.6086 data_time: 0.0346 memory: 24011 grad_norm: 5.2241 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6889 loss: 0.6889 2022/09/05 18:10:15 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:10:15 - mmengine - INFO - Epoch(train) [54][940/940] lr: 1.0000e-03 eta: 7:55:19 time: 0.5750 data_time: 0.0297 memory: 24011 grad_norm: 5.5455 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5287 loss: 0.5287 2022/09/05 18:10:15 - mmengine - INFO - Saving checkpoint at 54 epochs 2022/09/05 18:10:35 - mmengine - INFO - Epoch(val) [54][20/78] eta: 0:00:40 time: 0.7005 data_time: 0.5446 memory: 3625 2022/09/05 18:10:44 - mmengine - INFO - Epoch(val) [54][40/78] eta: 0:00:18 time: 0.4753 data_time: 0.3187 memory: 3625 2022/09/05 18:10:57 - mmengine - INFO - Epoch(val) [54][60/78] eta: 0:00:11 time: 0.6189 data_time: 0.4658 memory: 3625 2022/09/05 18:11:06 - mmengine - INFO - Epoch(val) [54][78/78] acc/top1: 0.7403 acc/top5: 0.9093 acc/mean1: 0.7401 2022/09/05 18:11:24 - mmengine - INFO - Epoch(train) [55][20/940] lr: 1.0000e-03 eta: 7:55:10 time: 0.9013 data_time: 0.2389 memory: 24011 grad_norm: 4.7834 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6446 loss: 0.6446 2022/09/05 18:11:37 - mmengine - INFO - Epoch(train) [55][40/940] lr: 1.0000e-03 eta: 7:54:56 time: 0.6277 data_time: 0.0352 memory: 24011 grad_norm: 4.6617 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6228 loss: 0.6228 2022/09/05 18:11:51 - mmengine - INFO - Epoch(train) [55][60/940] lr: 1.0000e-03 eta: 7:54:44 time: 0.6929 data_time: 0.0567 memory: 24011 grad_norm: 5.0520 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6415 loss: 0.6415 2022/09/05 18:12:04 - mmengine - INFO - Epoch(train) [55][80/940] lr: 1.0000e-03 eta: 7:54:30 time: 0.6569 data_time: 0.0341 memory: 24011 grad_norm: 4.6780 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7784 loss: 0.7784 2022/09/05 18:12:17 - mmengine - INFO - Epoch(train) [55][100/940] lr: 1.0000e-03 eta: 7:54:17 time: 0.6678 data_time: 0.0420 memory: 24011 grad_norm: 4.5148 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6579 loss: 0.6579 2022/09/05 18:12:30 - mmengine - INFO - Epoch(train) [55][120/940] lr: 1.0000e-03 eta: 7:54:04 time: 0.6332 data_time: 0.0364 memory: 24011 grad_norm: 5.0048 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7159 loss: 0.7159 2022/09/05 18:12:42 - mmengine - INFO - Epoch(train) [55][140/940] lr: 1.0000e-03 eta: 7:53:50 time: 0.6316 data_time: 0.0419 memory: 24011 grad_norm: 5.0648 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6919 loss: 0.6919 2022/09/05 18:12:55 - mmengine - INFO - Epoch(train) [55][160/940] lr: 1.0000e-03 eta: 7:53:36 time: 0.6361 data_time: 0.0399 memory: 24011 grad_norm: 4.7770 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7132 loss: 0.7132 2022/09/05 18:13:08 - mmengine - INFO - Epoch(train) [55][180/940] lr: 1.0000e-03 eta: 7:53:23 time: 0.6439 data_time: 0.0747 memory: 24011 grad_norm: 5.0919 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6710 loss: 0.6710 2022/09/05 18:13:21 - mmengine - INFO - Epoch(train) [55][200/940] lr: 1.0000e-03 eta: 7:53:10 time: 0.6445 data_time: 0.0677 memory: 24011 grad_norm: 4.8534 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5609 loss: 0.5609 2022/09/05 18:13:34 - mmengine - INFO - Epoch(train) [55][220/940] lr: 1.0000e-03 eta: 7:52:56 time: 0.6293 data_time: 0.0466 memory: 24011 grad_norm: 4.9447 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.7549 loss: 0.7549 2022/09/05 18:13:47 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:13:47 - mmengine - INFO - Epoch(train) [55][240/940] lr: 1.0000e-03 eta: 7:52:43 time: 0.6578 data_time: 0.0940 memory: 24011 grad_norm: 4.9978 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7636 loss: 0.7636 2022/09/05 18:14:00 - mmengine - INFO - Epoch(train) [55][260/940] lr: 1.0000e-03 eta: 7:52:29 time: 0.6625 data_time: 0.0702 memory: 24011 grad_norm: 4.7351 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6862 loss: 0.6862 2022/09/05 18:14:13 - mmengine - INFO - Epoch(train) [55][280/940] lr: 1.0000e-03 eta: 7:52:16 time: 0.6337 data_time: 0.0452 memory: 24011 grad_norm: 5.6207 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6264 loss: 0.6264 2022/09/05 18:14:26 - mmengine - INFO - Epoch(train) [55][300/940] lr: 1.0000e-03 eta: 7:52:03 time: 0.6804 data_time: 0.1246 memory: 24011 grad_norm: 4.8220 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6178 loss: 0.6178 2022/09/05 18:14:39 - mmengine - INFO - Epoch(train) [55][320/940] lr: 1.0000e-03 eta: 7:51:49 time: 0.6368 data_time: 0.0653 memory: 24011 grad_norm: 5.0031 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.6643 loss: 0.6643 2022/09/05 18:14:52 - mmengine - INFO - Epoch(train) [55][340/940] lr: 1.0000e-03 eta: 7:51:36 time: 0.6323 data_time: 0.0558 memory: 24011 grad_norm: 4.7902 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6150 loss: 0.6150 2022/09/05 18:15:05 - mmengine - INFO - Epoch(train) [55][360/940] lr: 1.0000e-03 eta: 7:51:23 time: 0.6581 data_time: 0.0383 memory: 24011 grad_norm: 4.8337 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 0.6920 loss: 0.6920 2022/09/05 18:15:19 - mmengine - INFO - Epoch(train) [55][380/940] lr: 1.0000e-03 eta: 7:51:10 time: 0.6887 data_time: 0.1196 memory: 24011 grad_norm: 5.2286 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7121 loss: 0.7121 2022/09/05 18:15:31 - mmengine - INFO - Epoch(train) [55][400/940] lr: 1.0000e-03 eta: 7:50:56 time: 0.6009 data_time: 0.0413 memory: 24011 grad_norm: 4.7404 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6808 loss: 0.6808 2022/09/05 18:15:44 - mmengine - INFO - Epoch(train) [55][420/940] lr: 1.0000e-03 eta: 7:50:43 time: 0.6621 data_time: 0.1036 memory: 24011 grad_norm: 4.6679 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.6180 loss: 0.6180 2022/09/05 18:15:57 - mmengine - INFO - Epoch(train) [55][440/940] lr: 1.0000e-03 eta: 7:50:29 time: 0.6427 data_time: 0.0827 memory: 24011 grad_norm: 5.5024 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6099 loss: 0.6099 2022/09/05 18:16:10 - mmengine - INFO - Epoch(train) [55][460/940] lr: 1.0000e-03 eta: 7:50:16 time: 0.6649 data_time: 0.1126 memory: 24011 grad_norm: 4.9850 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6788 loss: 0.6788 2022/09/05 18:16:22 - mmengine - INFO - Epoch(train) [55][480/940] lr: 1.0000e-03 eta: 7:50:02 time: 0.6196 data_time: 0.0522 memory: 24011 grad_norm: 4.6341 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7838 loss: 0.7838 2022/09/05 18:16:35 - mmengine - INFO - Epoch(train) [55][500/940] lr: 1.0000e-03 eta: 7:49:49 time: 0.6511 data_time: 0.0888 memory: 24011 grad_norm: 4.8792 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.7233 loss: 0.7233 2022/09/05 18:16:48 - mmengine - INFO - Epoch(train) [55][520/940] lr: 1.0000e-03 eta: 7:49:35 time: 0.6423 data_time: 0.0479 memory: 24011 grad_norm: 4.7640 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6682 loss: 0.6682 2022/09/05 18:17:01 - mmengine - INFO - Epoch(train) [55][540/940] lr: 1.0000e-03 eta: 7:49:22 time: 0.6409 data_time: 0.0821 memory: 24011 grad_norm: 4.7508 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5923 loss: 0.5923 2022/09/05 18:17:15 - mmengine - INFO - Epoch(train) [55][560/940] lr: 1.0000e-03 eta: 7:49:09 time: 0.6682 data_time: 0.0790 memory: 24011 grad_norm: 5.0222 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7166 loss: 0.7166 2022/09/05 18:17:27 - mmengine - INFO - Epoch(train) [55][580/940] lr: 1.0000e-03 eta: 7:48:55 time: 0.6419 data_time: 0.0678 memory: 24011 grad_norm: 4.7020 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.7691 loss: 0.7691 2022/09/05 18:17:40 - mmengine - INFO - Epoch(train) [55][600/940] lr: 1.0000e-03 eta: 7:48:41 time: 0.6207 data_time: 0.0481 memory: 24011 grad_norm: 4.7104 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.7142 loss: 0.7142 2022/09/05 18:17:53 - mmengine - INFO - Epoch(train) [55][620/940] lr: 1.0000e-03 eta: 7:48:29 time: 0.6835 data_time: 0.1130 memory: 24011 grad_norm: 5.1695 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6365 loss: 0.6365 2022/09/05 18:18:06 - mmengine - INFO - Epoch(train) [55][640/940] lr: 1.0000e-03 eta: 7:48:15 time: 0.6153 data_time: 0.0276 memory: 24011 grad_norm: 5.1030 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6662 loss: 0.6662 2022/09/05 18:18:18 - mmengine - INFO - Epoch(train) [55][660/940] lr: 1.0000e-03 eta: 7:48:01 time: 0.6268 data_time: 0.0655 memory: 24011 grad_norm: 4.6351 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6148 loss: 0.6148 2022/09/05 18:18:32 - mmengine - INFO - Epoch(train) [55][680/940] lr: 1.0000e-03 eta: 7:47:48 time: 0.6581 data_time: 0.1015 memory: 24011 grad_norm: 4.6958 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6232 loss: 0.6232 2022/09/05 18:18:45 - mmengine - INFO - Epoch(train) [55][700/940] lr: 1.0000e-03 eta: 7:47:35 time: 0.6676 data_time: 0.1081 memory: 24011 grad_norm: 5.0477 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5583 loss: 0.5583 2022/09/05 18:18:58 - mmengine - INFO - Epoch(train) [55][720/940] lr: 1.0000e-03 eta: 7:47:21 time: 0.6479 data_time: 0.0877 memory: 24011 grad_norm: 4.9379 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6080 loss: 0.6080 2022/09/05 18:19:10 - mmengine - INFO - Epoch(train) [55][740/940] lr: 1.0000e-03 eta: 7:47:08 time: 0.6325 data_time: 0.0604 memory: 24011 grad_norm: 4.9954 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7053 loss: 0.7053 2022/09/05 18:19:23 - mmengine - INFO - Epoch(train) [55][760/940] lr: 1.0000e-03 eta: 7:46:54 time: 0.6157 data_time: 0.0527 memory: 24011 grad_norm: 4.7003 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6470 loss: 0.6470 2022/09/05 18:19:37 - mmengine - INFO - Epoch(train) [55][780/940] lr: 1.0000e-03 eta: 7:46:41 time: 0.6887 data_time: 0.0409 memory: 24011 grad_norm: 4.7879 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6569 loss: 0.6569 2022/09/05 18:19:49 - mmengine - INFO - Epoch(train) [55][800/940] lr: 1.0000e-03 eta: 7:46:27 time: 0.6052 data_time: 0.0389 memory: 24011 grad_norm: 5.0853 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6747 loss: 0.6747 2022/09/05 18:20:02 - mmengine - INFO - Epoch(train) [55][820/940] lr: 1.0000e-03 eta: 7:46:14 time: 0.6841 data_time: 0.0935 memory: 24011 grad_norm: 4.9865 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6403 loss: 0.6403 2022/09/05 18:20:15 - mmengine - INFO - Epoch(train) [55][840/940] lr: 1.0000e-03 eta: 7:46:01 time: 0.6471 data_time: 0.0751 memory: 24011 grad_norm: 5.1688 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5671 loss: 0.5671 2022/09/05 18:20:28 - mmengine - INFO - Epoch(train) [55][860/940] lr: 1.0000e-03 eta: 7:45:47 time: 0.6290 data_time: 0.0698 memory: 24011 grad_norm: 5.0433 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6938 loss: 0.6938 2022/09/05 18:20:41 - mmengine - INFO - Epoch(train) [55][880/940] lr: 1.0000e-03 eta: 7:45:34 time: 0.6597 data_time: 0.1058 memory: 24011 grad_norm: 4.8690 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6075 loss: 0.6075 2022/09/05 18:20:55 - mmengine - INFO - Epoch(train) [55][900/940] lr: 1.0000e-03 eta: 7:45:21 time: 0.6946 data_time: 0.1471 memory: 24011 grad_norm: 4.9784 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6980 loss: 0.6980 2022/09/05 18:21:07 - mmengine - INFO - Epoch(train) [55][920/940] lr: 1.0000e-03 eta: 7:45:07 time: 0.6124 data_time: 0.0602 memory: 24011 grad_norm: 5.2438 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6557 loss: 0.6557 2022/09/05 18:21:19 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:21:19 - mmengine - INFO - Epoch(train) [55][940/940] lr: 1.0000e-03 eta: 7:44:53 time: 0.5654 data_time: 0.0464 memory: 24011 grad_norm: 5.1243 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 0.7232 loss: 0.7232 2022/09/05 18:21:32 - mmengine - INFO - Epoch(val) [55][20/78] eta: 0:00:39 time: 0.6878 data_time: 0.5304 memory: 3625 2022/09/05 18:21:42 - mmengine - INFO - Epoch(val) [55][40/78] eta: 0:00:17 time: 0.4585 data_time: 0.3013 memory: 3625 2022/09/05 18:21:55 - mmengine - INFO - Epoch(val) [55][60/78] eta: 0:00:12 time: 0.6725 data_time: 0.5129 memory: 3625 2022/09/05 18:22:05 - mmengine - INFO - Epoch(val) [55][78/78] acc/top1: 0.7411 acc/top5: 0.9096 acc/mean1: 0.7409 2022/09/05 18:22:24 - mmengine - INFO - Epoch(train) [56][20/940] lr: 1.0000e-03 eta: 7:44:44 time: 0.9138 data_time: 0.3441 memory: 24011 grad_norm: 5.5772 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6893 loss: 0.6893 2022/09/05 18:22:37 - mmengine - INFO - Epoch(train) [56][40/940] lr: 1.0000e-03 eta: 7:44:30 time: 0.6536 data_time: 0.0701 memory: 24011 grad_norm: 4.4320 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6346 loss: 0.6346 2022/09/05 18:22:51 - mmengine - INFO - Epoch(train) [56][60/940] lr: 1.0000e-03 eta: 7:44:18 time: 0.6996 data_time: 0.0400 memory: 24011 grad_norm: 5.0451 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6505 loss: 0.6505 2022/09/05 18:23:03 - mmengine - INFO - Epoch(train) [56][80/940] lr: 1.0000e-03 eta: 7:44:04 time: 0.6295 data_time: 0.0326 memory: 24011 grad_norm: 4.5853 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6813 loss: 0.6813 2022/09/05 18:23:16 - mmengine - INFO - Epoch(train) [56][100/940] lr: 1.0000e-03 eta: 7:43:51 time: 0.6417 data_time: 0.0430 memory: 24011 grad_norm: 5.5807 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6568 loss: 0.6568 2022/09/05 18:23:29 - mmengine - INFO - Epoch(train) [56][120/940] lr: 1.0000e-03 eta: 7:43:37 time: 0.6391 data_time: 0.0331 memory: 24011 grad_norm: 4.6176 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5993 loss: 0.5993 2022/09/05 18:23:42 - mmengine - INFO - Epoch(train) [56][140/940] lr: 1.0000e-03 eta: 7:43:24 time: 0.6568 data_time: 0.0381 memory: 24011 grad_norm: 5.3218 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6349 loss: 0.6349 2022/09/05 18:23:54 - mmengine - INFO - Epoch(train) [56][160/940] lr: 1.0000e-03 eta: 7:43:10 time: 0.6198 data_time: 0.0390 memory: 24011 grad_norm: 4.8414 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5915 loss: 0.5915 2022/09/05 18:24:09 - mmengine - INFO - Epoch(train) [56][180/940] lr: 1.0000e-03 eta: 7:42:58 time: 0.7295 data_time: 0.0426 memory: 24011 grad_norm: 4.8155 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6220 loss: 0.6220 2022/09/05 18:24:22 - mmengine - INFO - Epoch(train) [56][200/940] lr: 1.0000e-03 eta: 7:42:44 time: 0.6270 data_time: 0.0394 memory: 24011 grad_norm: 4.7969 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.7561 loss: 0.7561 2022/09/05 18:24:34 - mmengine - INFO - Epoch(train) [56][220/940] lr: 1.0000e-03 eta: 7:42:31 time: 0.6290 data_time: 0.0459 memory: 24011 grad_norm: 4.9863 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6535 loss: 0.6535 2022/09/05 18:24:47 - mmengine - INFO - Epoch(train) [56][240/940] lr: 1.0000e-03 eta: 7:42:17 time: 0.6275 data_time: 0.0490 memory: 24011 grad_norm: 5.2989 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8052 loss: 0.8052 2022/09/05 18:25:00 - mmengine - INFO - Epoch(train) [56][260/940] lr: 1.0000e-03 eta: 7:42:04 time: 0.6610 data_time: 0.0470 memory: 24011 grad_norm: 5.6786 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6201 loss: 0.6201 2022/09/05 18:25:13 - mmengine - INFO - Epoch(train) [56][280/940] lr: 1.0000e-03 eta: 7:41:51 time: 0.6678 data_time: 0.0352 memory: 24011 grad_norm: 4.8017 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6539 loss: 0.6539 2022/09/05 18:25:26 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:25:26 - mmengine - INFO - Epoch(train) [56][300/940] lr: 1.0000e-03 eta: 7:41:37 time: 0.6110 data_time: 0.0446 memory: 24011 grad_norm: 4.9205 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6850 loss: 0.6850 2022/09/05 18:25:38 - mmengine - INFO - Epoch(train) [56][320/940] lr: 1.0000e-03 eta: 7:41:23 time: 0.6370 data_time: 0.0502 memory: 24011 grad_norm: 4.9134 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6810 loss: 0.6810 2022/09/05 18:25:52 - mmengine - INFO - Epoch(train) [56][340/940] lr: 1.0000e-03 eta: 7:41:10 time: 0.6830 data_time: 0.0410 memory: 24011 grad_norm: 4.8490 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7311 loss: 0.7311 2022/09/05 18:26:05 - mmengine - INFO - Epoch(train) [56][360/940] lr: 1.0000e-03 eta: 7:40:57 time: 0.6268 data_time: 0.0394 memory: 24011 grad_norm: 4.7231 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5812 loss: 0.5812 2022/09/05 18:26:18 - mmengine - INFO - Epoch(train) [56][380/940] lr: 1.0000e-03 eta: 7:40:43 time: 0.6350 data_time: 0.0395 memory: 24011 grad_norm: 5.1944 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.6623 loss: 0.6623 2022/09/05 18:26:30 - mmengine - INFO - Epoch(train) [56][400/940] lr: 1.0000e-03 eta: 7:40:30 time: 0.6612 data_time: 0.0563 memory: 24011 grad_norm: 4.8970 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6510 loss: 0.6510 2022/09/05 18:26:44 - mmengine - INFO - Epoch(train) [56][420/940] lr: 1.0000e-03 eta: 7:40:17 time: 0.6622 data_time: 0.0350 memory: 24011 grad_norm: 5.6881 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.7849 loss: 0.7849 2022/09/05 18:26:57 - mmengine - INFO - Epoch(train) [56][440/940] lr: 1.0000e-03 eta: 7:40:04 time: 0.6709 data_time: 0.0338 memory: 24011 grad_norm: 4.9116 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6186 loss: 0.6186 2022/09/05 18:27:11 - mmengine - INFO - Epoch(train) [56][460/940] lr: 1.0000e-03 eta: 7:39:51 time: 0.6775 data_time: 0.0322 memory: 24011 grad_norm: 5.0858 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6901 loss: 0.6901 2022/09/05 18:27:23 - mmengine - INFO - Epoch(train) [56][480/940] lr: 1.0000e-03 eta: 7:39:37 time: 0.6359 data_time: 0.0371 memory: 24011 grad_norm: 5.1151 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7400 loss: 0.7400 2022/09/05 18:27:36 - mmengine - INFO - Epoch(train) [56][500/940] lr: 1.0000e-03 eta: 7:39:24 time: 0.6355 data_time: 0.0319 memory: 24011 grad_norm: 4.8275 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6268 loss: 0.6268 2022/09/05 18:27:50 - mmengine - INFO - Epoch(train) [56][520/940] lr: 1.0000e-03 eta: 7:39:11 time: 0.6685 data_time: 0.0355 memory: 24011 grad_norm: 5.1656 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6567 loss: 0.6567 2022/09/05 18:28:02 - mmengine - INFO - Epoch(train) [56][540/940] lr: 1.0000e-03 eta: 7:38:57 time: 0.6408 data_time: 0.0358 memory: 24011 grad_norm: 5.4942 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5293 loss: 0.5293 2022/09/05 18:28:15 - mmengine - INFO - Epoch(train) [56][560/940] lr: 1.0000e-03 eta: 7:38:44 time: 0.6518 data_time: 0.0414 memory: 24011 grad_norm: 4.7531 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6291 loss: 0.6291 2022/09/05 18:28:28 - mmengine - INFO - Epoch(train) [56][580/940] lr: 1.0000e-03 eta: 7:38:30 time: 0.6151 data_time: 0.0305 memory: 24011 grad_norm: 5.0029 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6403 loss: 0.6403 2022/09/05 18:28:41 - mmengine - INFO - Epoch(train) [56][600/940] lr: 1.0000e-03 eta: 7:38:17 time: 0.6835 data_time: 0.0982 memory: 24011 grad_norm: 5.3731 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5798 loss: 0.5798 2022/09/05 18:28:54 - mmengine - INFO - Epoch(train) [56][620/940] lr: 1.0000e-03 eta: 7:38:03 time: 0.6139 data_time: 0.0334 memory: 24011 grad_norm: 5.4790 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5749 loss: 0.5749 2022/09/05 18:29:06 - mmengine - INFO - Epoch(train) [56][640/940] lr: 1.0000e-03 eta: 7:37:49 time: 0.6041 data_time: 0.0379 memory: 24011 grad_norm: 4.9103 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6461 loss: 0.6461 2022/09/05 18:29:19 - mmengine - INFO - Epoch(train) [56][660/940] lr: 1.0000e-03 eta: 7:37:36 time: 0.6533 data_time: 0.0591 memory: 24011 grad_norm: 5.4498 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7237 loss: 0.7237 2022/09/05 18:29:31 - mmengine - INFO - Epoch(train) [56][680/940] lr: 1.0000e-03 eta: 7:37:22 time: 0.6279 data_time: 0.0423 memory: 24011 grad_norm: 4.7003 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5485 loss: 0.5485 2022/09/05 18:29:44 - mmengine - INFO - Epoch(train) [56][700/940] lr: 1.0000e-03 eta: 7:37:09 time: 0.6323 data_time: 0.0398 memory: 24011 grad_norm: 5.0341 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.6365 loss: 0.6365 2022/09/05 18:29:57 - mmengine - INFO - Epoch(train) [56][720/940] lr: 1.0000e-03 eta: 7:36:55 time: 0.6364 data_time: 0.0432 memory: 24011 grad_norm: 4.8758 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7215 loss: 0.7215 2022/09/05 18:30:10 - mmengine - INFO - Epoch(train) [56][740/940] lr: 1.0000e-03 eta: 7:36:42 time: 0.6544 data_time: 0.0529 memory: 24011 grad_norm: 4.8619 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.7209 loss: 0.7209 2022/09/05 18:30:23 - mmengine - INFO - Epoch(train) [56][760/940] lr: 1.0000e-03 eta: 7:36:29 time: 0.6591 data_time: 0.0341 memory: 24011 grad_norm: 5.1379 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6497 loss: 0.6497 2022/09/05 18:30:37 - mmengine - INFO - Epoch(train) [56][780/940] lr: 1.0000e-03 eta: 7:36:16 time: 0.6760 data_time: 0.0438 memory: 24011 grad_norm: 5.8004 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6811 loss: 0.6811 2022/09/05 18:30:50 - mmengine - INFO - Epoch(train) [56][800/940] lr: 1.0000e-03 eta: 7:36:02 time: 0.6523 data_time: 0.0352 memory: 24011 grad_norm: 6.1449 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7122 loss: 0.7122 2022/09/05 18:31:03 - mmengine - INFO - Epoch(train) [56][820/940] lr: 1.0000e-03 eta: 7:35:49 time: 0.6630 data_time: 0.0390 memory: 24011 grad_norm: 4.8574 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6296 loss: 0.6296 2022/09/05 18:31:15 - mmengine - INFO - Epoch(train) [56][840/940] lr: 1.0000e-03 eta: 7:35:35 time: 0.6211 data_time: 0.0415 memory: 24011 grad_norm: 5.0756 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6647 loss: 0.6647 2022/09/05 18:31:28 - mmengine - INFO - Epoch(train) [56][860/940] lr: 1.0000e-03 eta: 7:35:22 time: 0.6378 data_time: 0.0429 memory: 24011 grad_norm: 4.7231 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5153 loss: 0.5153 2022/09/05 18:31:41 - mmengine - INFO - Epoch(train) [56][880/940] lr: 1.0000e-03 eta: 7:35:09 time: 0.6673 data_time: 0.0406 memory: 24011 grad_norm: 4.9388 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6032 loss: 0.6032 2022/09/05 18:31:54 - mmengine - INFO - Epoch(train) [56][900/940] lr: 1.0000e-03 eta: 7:34:55 time: 0.6098 data_time: 0.0365 memory: 24011 grad_norm: 4.9980 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5359 loss: 0.5359 2022/09/05 18:32:08 - mmengine - INFO - Epoch(train) [56][920/940] lr: 1.0000e-03 eta: 7:34:42 time: 0.6965 data_time: 0.0419 memory: 24011 grad_norm: 5.0366 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5942 loss: 0.5942 2022/09/05 18:32:18 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:32:18 - mmengine - INFO - Epoch(train) [56][940/940] lr: 1.0000e-03 eta: 7:34:27 time: 0.5314 data_time: 0.0308 memory: 24011 grad_norm: 5.2438 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6680 loss: 0.6680 2022/09/05 18:32:32 - mmengine - INFO - Epoch(val) [56][20/78] eta: 0:00:40 time: 0.6971 data_time: 0.5378 memory: 3625 2022/09/05 18:32:42 - mmengine - INFO - Epoch(val) [56][40/78] eta: 0:00:18 time: 0.4938 data_time: 0.3363 memory: 3625 2022/09/05 18:32:54 - mmengine - INFO - Epoch(val) [56][60/78] eta: 0:00:11 time: 0.6124 data_time: 0.4532 memory: 3625 2022/09/05 18:33:05 - mmengine - INFO - Epoch(val) [56][78/78] acc/top1: 0.7399 acc/top5: 0.9079 acc/mean1: 0.7398 2022/09/05 18:33:24 - mmengine - INFO - Epoch(train) [57][20/940] lr: 1.0000e-03 eta: 7:34:18 time: 0.9229 data_time: 0.3624 memory: 24011 grad_norm: 4.7046 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6150 loss: 0.6150 2022/09/05 18:33:37 - mmengine - INFO - Epoch(train) [57][40/940] lr: 1.0000e-03 eta: 7:34:05 time: 0.6500 data_time: 0.0620 memory: 24011 grad_norm: 4.9310 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5870 loss: 0.5870 2022/09/05 18:33:49 - mmengine - INFO - Epoch(train) [57][60/940] lr: 1.0000e-03 eta: 7:33:51 time: 0.6354 data_time: 0.0640 memory: 24011 grad_norm: 4.9912 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6402 loss: 0.6402 2022/09/05 18:34:02 - mmengine - INFO - Epoch(train) [57][80/940] lr: 1.0000e-03 eta: 7:33:38 time: 0.6438 data_time: 0.0337 memory: 24011 grad_norm: 5.7020 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6383 loss: 0.6383 2022/09/05 18:34:16 - mmengine - INFO - Epoch(train) [57][100/940] lr: 1.0000e-03 eta: 7:33:25 time: 0.6825 data_time: 0.0414 memory: 24011 grad_norm: 4.7900 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6205 loss: 0.6205 2022/09/05 18:34:29 - mmengine - INFO - Epoch(train) [57][120/940] lr: 1.0000e-03 eta: 7:33:11 time: 0.6489 data_time: 0.0321 memory: 24011 grad_norm: 5.6952 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.6374 loss: 0.6374 2022/09/05 18:34:42 - mmengine - INFO - Epoch(train) [57][140/940] lr: 1.0000e-03 eta: 7:32:58 time: 0.6403 data_time: 0.0447 memory: 24011 grad_norm: 4.7801 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5683 loss: 0.5683 2022/09/05 18:34:54 - mmengine - INFO - Epoch(train) [57][160/940] lr: 1.0000e-03 eta: 7:32:44 time: 0.6166 data_time: 0.0382 memory: 24011 grad_norm: 5.0169 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5812 loss: 0.5812 2022/09/05 18:35:07 - mmengine - INFO - Epoch(train) [57][180/940] lr: 1.0000e-03 eta: 7:32:31 time: 0.6421 data_time: 0.0404 memory: 24011 grad_norm: 5.0139 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6140 loss: 0.6140 2022/09/05 18:35:20 - mmengine - INFO - Epoch(train) [57][200/940] lr: 1.0000e-03 eta: 7:32:18 time: 0.6664 data_time: 0.0795 memory: 24011 grad_norm: 5.2380 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.5854 loss: 0.5854 2022/09/05 18:35:34 - mmengine - INFO - Epoch(train) [57][220/940] lr: 1.0000e-03 eta: 7:32:05 time: 0.6648 data_time: 0.0331 memory: 24011 grad_norm: 5.1790 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5929 loss: 0.5929 2022/09/05 18:35:46 - mmengine - INFO - Epoch(train) [57][240/940] lr: 1.0000e-03 eta: 7:31:51 time: 0.6247 data_time: 0.0365 memory: 24011 grad_norm: 4.9054 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6355 loss: 0.6355 2022/09/05 18:36:00 - mmengine - INFO - Epoch(train) [57][260/940] lr: 1.0000e-03 eta: 7:31:38 time: 0.6855 data_time: 0.0342 memory: 24011 grad_norm: 5.3455 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6484 loss: 0.6484 2022/09/05 18:36:12 - mmengine - INFO - Epoch(train) [57][280/940] lr: 1.0000e-03 eta: 7:31:24 time: 0.6224 data_time: 0.0475 memory: 24011 grad_norm: 5.0455 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6727 loss: 0.6727 2022/09/05 18:36:25 - mmengine - INFO - Epoch(train) [57][300/940] lr: 1.0000e-03 eta: 7:31:11 time: 0.6482 data_time: 0.0361 memory: 24011 grad_norm: 5.6225 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6427 loss: 0.6427 2022/09/05 18:36:38 - mmengine - INFO - Epoch(train) [57][320/940] lr: 1.0000e-03 eta: 7:30:57 time: 0.6401 data_time: 0.0478 memory: 24011 grad_norm: 5.2269 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6371 loss: 0.6371 2022/09/05 18:36:51 - mmengine - INFO - Epoch(train) [57][340/940] lr: 1.0000e-03 eta: 7:30:44 time: 0.6486 data_time: 0.0360 memory: 24011 grad_norm: 5.0792 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6201 loss: 0.6201 2022/09/05 18:37:03 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:37:03 - mmengine - INFO - Epoch(train) [57][360/940] lr: 1.0000e-03 eta: 7:30:30 time: 0.6080 data_time: 0.0374 memory: 24011 grad_norm: 5.0836 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.7028 loss: 0.7028 2022/09/05 18:37:17 - mmengine - INFO - Epoch(train) [57][380/940] lr: 1.0000e-03 eta: 7:30:17 time: 0.6694 data_time: 0.0362 memory: 24011 grad_norm: 4.8748 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7581 loss: 0.7581 2022/09/05 18:37:29 - mmengine - INFO - Epoch(train) [57][400/940] lr: 1.0000e-03 eta: 7:30:03 time: 0.6203 data_time: 0.0417 memory: 24011 grad_norm: 5.0610 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6378 loss: 0.6378 2022/09/05 18:37:42 - mmengine - INFO - Epoch(train) [57][420/940] lr: 1.0000e-03 eta: 7:29:50 time: 0.6520 data_time: 0.0324 memory: 24011 grad_norm: 5.0170 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6179 loss: 0.6179 2022/09/05 18:37:55 - mmengine - INFO - Epoch(train) [57][440/940] lr: 1.0000e-03 eta: 7:29:36 time: 0.6275 data_time: 0.0392 memory: 24011 grad_norm: 4.8915 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6117 loss: 0.6117 2022/09/05 18:38:08 - mmengine - INFO - Epoch(train) [57][460/940] lr: 1.0000e-03 eta: 7:29:23 time: 0.6602 data_time: 0.0344 memory: 24011 grad_norm: 4.7353 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5335 loss: 0.5335 2022/09/05 18:38:21 - mmengine - INFO - Epoch(train) [57][480/940] lr: 1.0000e-03 eta: 7:29:10 time: 0.6395 data_time: 0.0394 memory: 24011 grad_norm: 4.8184 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6312 loss: 0.6312 2022/09/05 18:38:33 - mmengine - INFO - Epoch(train) [57][500/940] lr: 1.0000e-03 eta: 7:28:56 time: 0.6312 data_time: 0.0334 memory: 24011 grad_norm: 5.0049 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7504 loss: 0.7504 2022/09/05 18:38:46 - mmengine - INFO - Epoch(train) [57][520/940] lr: 1.0000e-03 eta: 7:28:42 time: 0.6300 data_time: 0.0393 memory: 24011 grad_norm: 4.8427 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6196 loss: 0.6196 2022/09/05 18:38:59 - mmengine - INFO - Epoch(train) [57][540/940] lr: 1.0000e-03 eta: 7:28:29 time: 0.6464 data_time: 0.0611 memory: 24011 grad_norm: 5.0660 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6083 loss: 0.6083 2022/09/05 18:39:12 - mmengine - INFO - Epoch(train) [57][560/940] lr: 1.0000e-03 eta: 7:28:16 time: 0.6647 data_time: 0.0422 memory: 24011 grad_norm: 5.8385 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5990 loss: 0.5990 2022/09/05 18:39:26 - mmengine - INFO - Epoch(train) [57][580/940] lr: 1.0000e-03 eta: 7:28:03 time: 0.6793 data_time: 0.0644 memory: 24011 grad_norm: 6.4844 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6481 loss: 0.6481 2022/09/05 18:39:39 - mmengine - INFO - Epoch(train) [57][600/940] lr: 1.0000e-03 eta: 7:27:50 time: 0.6697 data_time: 0.0736 memory: 24011 grad_norm: 5.0127 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6415 loss: 0.6415 2022/09/05 18:39:52 - mmengine - INFO - Epoch(train) [57][620/940] lr: 1.0000e-03 eta: 7:27:37 time: 0.6460 data_time: 0.0592 memory: 24011 grad_norm: 5.1299 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6585 loss: 0.6585 2022/09/05 18:40:05 - mmengine - INFO - Epoch(train) [57][640/940] lr: 1.0000e-03 eta: 7:27:24 time: 0.6739 data_time: 0.0844 memory: 24011 grad_norm: 5.2066 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7314 loss: 0.7314 2022/09/05 18:40:18 - mmengine - INFO - Epoch(train) [57][660/940] lr: 1.0000e-03 eta: 7:27:10 time: 0.6290 data_time: 0.0665 memory: 24011 grad_norm: 5.0953 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6537 loss: 0.6537 2022/09/05 18:40:31 - mmengine - INFO - Epoch(train) [57][680/940] lr: 1.0000e-03 eta: 7:26:56 time: 0.6342 data_time: 0.0699 memory: 24011 grad_norm: 5.1157 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6197 loss: 0.6197 2022/09/05 18:40:44 - mmengine - INFO - Epoch(train) [57][700/940] lr: 1.0000e-03 eta: 7:26:43 time: 0.6475 data_time: 0.0894 memory: 24011 grad_norm: 4.8826 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6851 loss: 0.6851 2022/09/05 18:40:57 - mmengine - INFO - Epoch(train) [57][720/940] lr: 1.0000e-03 eta: 7:26:30 time: 0.6403 data_time: 0.0567 memory: 24011 grad_norm: 4.9387 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6937 loss: 0.6937 2022/09/05 18:41:09 - mmengine - INFO - Epoch(train) [57][740/940] lr: 1.0000e-03 eta: 7:26:16 time: 0.6447 data_time: 0.0603 memory: 24011 grad_norm: 5.0172 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6573 loss: 0.6573 2022/09/05 18:41:23 - mmengine - INFO - Epoch(train) [57][760/940] lr: 1.0000e-03 eta: 7:26:03 time: 0.6580 data_time: 0.0964 memory: 24011 grad_norm: 5.0171 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6781 loss: 0.6781 2022/09/05 18:41:35 - mmengine - INFO - Epoch(train) [57][780/940] lr: 1.0000e-03 eta: 7:25:49 time: 0.6225 data_time: 0.0688 memory: 24011 grad_norm: 4.9473 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6410 loss: 0.6410 2022/09/05 18:41:49 - mmengine - INFO - Epoch(train) [57][800/940] lr: 1.0000e-03 eta: 7:25:37 time: 0.6980 data_time: 0.1364 memory: 24011 grad_norm: 4.6750 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6731 loss: 0.6731 2022/09/05 18:42:02 - mmengine - INFO - Epoch(train) [57][820/940] lr: 1.0000e-03 eta: 7:25:23 time: 0.6299 data_time: 0.0381 memory: 24011 grad_norm: 5.1649 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.6957 loss: 0.6957 2022/09/05 18:42:14 - mmengine - INFO - Epoch(train) [57][840/940] lr: 1.0000e-03 eta: 7:25:09 time: 0.6296 data_time: 0.0584 memory: 24011 grad_norm: 4.8086 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6337 loss: 0.6337 2022/09/05 18:42:27 - mmengine - INFO - Epoch(train) [57][860/940] lr: 1.0000e-03 eta: 7:24:56 time: 0.6460 data_time: 0.0687 memory: 24011 grad_norm: 4.8675 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6120 loss: 0.6120 2022/09/05 18:42:40 - mmengine - INFO - Epoch(train) [57][880/940] lr: 1.0000e-03 eta: 7:24:43 time: 0.6552 data_time: 0.0877 memory: 24011 grad_norm: 4.9341 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6562 loss: 0.6562 2022/09/05 18:42:53 - mmengine - INFO - Epoch(train) [57][900/940] lr: 1.0000e-03 eta: 7:24:29 time: 0.6461 data_time: 0.0715 memory: 24011 grad_norm: 5.0550 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7053 loss: 0.7053 2022/09/05 18:43:07 - mmengine - INFO - Epoch(train) [57][920/940] lr: 1.0000e-03 eta: 7:24:17 time: 0.6811 data_time: 0.1123 memory: 24011 grad_norm: 4.7313 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6420 loss: 0.6420 2022/09/05 18:43:17 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:43:17 - mmengine - INFO - Epoch(train) [57][940/940] lr: 1.0000e-03 eta: 7:24:01 time: 0.5272 data_time: 0.0249 memory: 24011 grad_norm: 5.2796 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.6463 loss: 0.6463 2022/09/05 18:43:17 - mmengine - INFO - Saving checkpoint at 57 epochs 2022/09/05 18:43:37 - mmengine - INFO - Epoch(val) [57][20/78] eta: 0:00:41 time: 0.7231 data_time: 0.5664 memory: 3625 2022/09/05 18:43:46 - mmengine - INFO - Epoch(val) [57][40/78] eta: 0:00:17 time: 0.4549 data_time: 0.2982 memory: 3625 2022/09/05 18:43:59 - mmengine - INFO - Epoch(val) [57][60/78] eta: 0:00:11 time: 0.6425 data_time: 0.4834 memory: 3625 2022/09/05 18:44:08 - mmengine - INFO - Epoch(val) [57][78/78] acc/top1: 0.7397 acc/top5: 0.9076 acc/mean1: 0.7396 2022/09/05 18:44:26 - mmengine - INFO - Epoch(train) [58][20/940] lr: 1.0000e-03 eta: 7:23:52 time: 0.9012 data_time: 0.3283 memory: 24011 grad_norm: 5.6485 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6097 loss: 0.6097 2022/09/05 18:44:39 - mmengine - INFO - Epoch(train) [58][40/940] lr: 1.0000e-03 eta: 7:23:39 time: 0.6686 data_time: 0.0351 memory: 24011 grad_norm: 4.7731 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6723 loss: 0.6723 2022/09/05 18:44:52 - mmengine - INFO - Epoch(train) [58][60/940] lr: 1.0000e-03 eta: 7:23:25 time: 0.6361 data_time: 0.0407 memory: 24011 grad_norm: 4.7322 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7191 loss: 0.7191 2022/09/05 18:45:05 - mmengine - INFO - Epoch(train) [58][80/940] lr: 1.0000e-03 eta: 7:23:12 time: 0.6461 data_time: 0.0370 memory: 24011 grad_norm: 4.6711 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5968 loss: 0.5968 2022/09/05 18:45:18 - mmengine - INFO - Epoch(train) [58][100/940] lr: 1.0000e-03 eta: 7:22:59 time: 0.6767 data_time: 0.0420 memory: 24011 grad_norm: 4.7868 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5505 loss: 0.5505 2022/09/05 18:45:31 - mmengine - INFO - Epoch(train) [58][120/940] lr: 1.0000e-03 eta: 7:22:45 time: 0.6271 data_time: 0.0321 memory: 24011 grad_norm: 4.6702 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6786 loss: 0.6786 2022/09/05 18:45:45 - mmengine - INFO - Epoch(train) [58][140/940] lr: 1.0000e-03 eta: 7:22:32 time: 0.6807 data_time: 0.0420 memory: 24011 grad_norm: 4.7162 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7871 loss: 0.7871 2022/09/05 18:45:57 - mmengine - INFO - Epoch(train) [58][160/940] lr: 1.0000e-03 eta: 7:22:19 time: 0.6256 data_time: 0.0357 memory: 24011 grad_norm: 5.3577 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5833 loss: 0.5833 2022/09/05 18:46:10 - mmengine - INFO - Epoch(train) [58][180/940] lr: 1.0000e-03 eta: 7:22:05 time: 0.6260 data_time: 0.0430 memory: 24011 grad_norm: 5.4174 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.7172 loss: 0.7172 2022/09/05 18:46:22 - mmengine - INFO - Epoch(train) [58][200/940] lr: 1.0000e-03 eta: 7:21:51 time: 0.6275 data_time: 0.0333 memory: 24011 grad_norm: 5.0657 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5619 loss: 0.5619 2022/09/05 18:46:36 - mmengine - INFO - Epoch(train) [58][220/940] lr: 1.0000e-03 eta: 7:21:38 time: 0.6746 data_time: 0.0508 memory: 24011 grad_norm: 4.8906 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6428 loss: 0.6428 2022/09/05 18:46:48 - mmengine - INFO - Epoch(train) [58][240/940] lr: 1.0000e-03 eta: 7:21:25 time: 0.6128 data_time: 0.0384 memory: 24011 grad_norm: 5.3829 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6955 loss: 0.6955 2022/09/05 18:47:02 - mmengine - INFO - Epoch(train) [58][260/940] lr: 1.0000e-03 eta: 7:21:12 time: 0.6903 data_time: 0.0514 memory: 24011 grad_norm: 5.1234 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6791 loss: 0.6791 2022/09/05 18:47:14 - mmengine - INFO - Epoch(train) [58][280/940] lr: 1.0000e-03 eta: 7:20:58 time: 0.6233 data_time: 0.0335 memory: 24011 grad_norm: 4.9090 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6547 loss: 0.6547 2022/09/05 18:47:27 - mmengine - INFO - Epoch(train) [58][300/940] lr: 1.0000e-03 eta: 7:20:45 time: 0.6490 data_time: 0.0425 memory: 24011 grad_norm: 5.5230 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7186 loss: 0.7186 2022/09/05 18:47:39 - mmengine - INFO - Epoch(train) [58][320/940] lr: 1.0000e-03 eta: 7:20:31 time: 0.6085 data_time: 0.0343 memory: 24011 grad_norm: 5.0491 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5805 loss: 0.5805 2022/09/05 18:47:53 - mmengine - INFO - Epoch(train) [58][340/940] lr: 1.0000e-03 eta: 7:20:18 time: 0.6672 data_time: 0.0641 memory: 24011 grad_norm: 5.4889 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.6375 loss: 0.6375 2022/09/05 18:48:06 - mmengine - INFO - Epoch(train) [58][360/940] lr: 1.0000e-03 eta: 7:20:04 time: 0.6463 data_time: 0.0542 memory: 24011 grad_norm: 7.1557 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6655 loss: 0.6655 2022/09/05 18:48:19 - mmengine - INFO - Epoch(train) [58][380/940] lr: 1.0000e-03 eta: 7:19:52 time: 0.6788 data_time: 0.0753 memory: 24011 grad_norm: 5.0135 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6498 loss: 0.6498 2022/09/05 18:48:32 - mmengine - INFO - Epoch(train) [58][400/940] lr: 1.0000e-03 eta: 7:19:38 time: 0.6265 data_time: 0.0339 memory: 24011 grad_norm: 4.9939 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.6189 loss: 0.6189 2022/09/05 18:48:45 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:48:45 - mmengine - INFO - Epoch(train) [58][420/940] lr: 1.0000e-03 eta: 7:19:25 time: 0.6489 data_time: 0.0651 memory: 24011 grad_norm: 5.2923 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6746 loss: 0.6746 2022/09/05 18:48:58 - mmengine - INFO - Epoch(train) [58][440/940] lr: 1.0000e-03 eta: 7:19:11 time: 0.6679 data_time: 0.0387 memory: 24011 grad_norm: 4.9413 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.6408 loss: 0.6408 2022/09/05 18:49:10 - mmengine - INFO - Epoch(train) [58][460/940] lr: 1.0000e-03 eta: 7:18:58 time: 0.6140 data_time: 0.0382 memory: 24011 grad_norm: 5.0438 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6234 loss: 0.6234 2022/09/05 18:49:24 - mmengine - INFO - Epoch(train) [58][480/940] lr: 1.0000e-03 eta: 7:18:44 time: 0.6547 data_time: 0.0442 memory: 24011 grad_norm: 5.5489 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6355 loss: 0.6355 2022/09/05 18:49:37 - mmengine - INFO - Epoch(train) [58][500/940] lr: 1.0000e-03 eta: 7:18:31 time: 0.6721 data_time: 0.0402 memory: 24011 grad_norm: 5.1261 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.7553 loss: 0.7553 2022/09/05 18:49:50 - mmengine - INFO - Epoch(train) [58][520/940] lr: 1.0000e-03 eta: 7:18:18 time: 0.6481 data_time: 0.0447 memory: 24011 grad_norm: 5.2511 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6586 loss: 0.6586 2022/09/05 18:50:04 - mmengine - INFO - Epoch(train) [58][540/940] lr: 1.0000e-03 eta: 7:18:05 time: 0.6788 data_time: 0.0302 memory: 24011 grad_norm: 5.0991 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6734 loss: 0.6734 2022/09/05 18:50:17 - mmengine - INFO - Epoch(train) [58][560/940] lr: 1.0000e-03 eta: 7:17:52 time: 0.6539 data_time: 0.0407 memory: 24011 grad_norm: 4.8112 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6086 loss: 0.6086 2022/09/05 18:50:30 - mmengine - INFO - Epoch(train) [58][580/940] lr: 1.0000e-03 eta: 7:17:39 time: 0.6753 data_time: 0.0312 memory: 24011 grad_norm: 6.7838 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6018 loss: 0.6018 2022/09/05 18:50:43 - mmengine - INFO - Epoch(train) [58][600/940] lr: 1.0000e-03 eta: 7:17:25 time: 0.6405 data_time: 0.0393 memory: 24011 grad_norm: 4.8606 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 0.6970 loss: 0.6970 2022/09/05 18:50:56 - mmengine - INFO - Epoch(train) [58][620/940] lr: 1.0000e-03 eta: 7:17:12 time: 0.6291 data_time: 0.0373 memory: 24011 grad_norm: 4.9780 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6804 loss: 0.6804 2022/09/05 18:51:09 - mmengine - INFO - Epoch(train) [58][640/940] lr: 1.0000e-03 eta: 7:16:59 time: 0.6568 data_time: 0.0396 memory: 24011 grad_norm: 10.5999 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6610 loss: 0.6610 2022/09/05 18:51:22 - mmengine - INFO - Epoch(train) [58][660/940] lr: 1.0000e-03 eta: 7:16:45 time: 0.6547 data_time: 0.0407 memory: 24011 grad_norm: 4.8753 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5914 loss: 0.5914 2022/09/05 18:51:34 - mmengine - INFO - Epoch(train) [58][680/940] lr: 1.0000e-03 eta: 7:16:32 time: 0.6314 data_time: 0.0428 memory: 24011 grad_norm: 5.2559 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5834 loss: 0.5834 2022/09/05 18:51:48 - mmengine - INFO - Epoch(train) [58][700/940] lr: 1.0000e-03 eta: 7:16:19 time: 0.6997 data_time: 0.0414 memory: 24011 grad_norm: 4.8399 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6430 loss: 0.6430 2022/09/05 18:52:01 - mmengine - INFO - Epoch(train) [58][720/940] lr: 1.0000e-03 eta: 7:16:05 time: 0.6018 data_time: 0.0390 memory: 24011 grad_norm: 5.2263 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6471 loss: 0.6471 2022/09/05 18:52:14 - mmengine - INFO - Epoch(train) [58][740/940] lr: 1.0000e-03 eta: 7:15:52 time: 0.6480 data_time: 0.0404 memory: 24011 grad_norm: 5.1060 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6533 loss: 0.6533 2022/09/05 18:52:26 - mmengine - INFO - Epoch(train) [58][760/940] lr: 1.0000e-03 eta: 7:15:38 time: 0.6331 data_time: 0.0650 memory: 24011 grad_norm: 5.0709 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6491 loss: 0.6491 2022/09/05 18:52:38 - mmengine - INFO - Epoch(train) [58][780/940] lr: 1.0000e-03 eta: 7:15:24 time: 0.6151 data_time: 0.0374 memory: 24011 grad_norm: 5.3912 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6411 loss: 0.6411 2022/09/05 18:52:51 - mmengine - INFO - Epoch(train) [58][800/940] lr: 1.0000e-03 eta: 7:15:11 time: 0.6113 data_time: 0.0429 memory: 24011 grad_norm: 4.9450 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.7449 loss: 0.7449 2022/09/05 18:53:04 - mmengine - INFO - Epoch(train) [58][820/940] lr: 1.0000e-03 eta: 7:14:57 time: 0.6604 data_time: 0.0809 memory: 24011 grad_norm: 4.8556 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6638 loss: 0.6638 2022/09/05 18:53:17 - mmengine - INFO - Epoch(train) [58][840/940] lr: 1.0000e-03 eta: 7:14:44 time: 0.6406 data_time: 0.0494 memory: 24011 grad_norm: 5.7584 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6569 loss: 0.6569 2022/09/05 18:53:30 - mmengine - INFO - Epoch(train) [58][860/940] lr: 1.0000e-03 eta: 7:14:31 time: 0.6472 data_time: 0.0433 memory: 24011 grad_norm: 5.1261 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5655 loss: 0.5655 2022/09/05 18:53:43 - mmengine - INFO - Epoch(train) [58][880/940] lr: 1.0000e-03 eta: 7:14:17 time: 0.6601 data_time: 0.1006 memory: 24011 grad_norm: 5.3020 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7400 loss: 0.7400 2022/09/05 18:53:56 - mmengine - INFO - Epoch(train) [58][900/940] lr: 1.0000e-03 eta: 7:14:04 time: 0.6538 data_time: 0.0365 memory: 24011 grad_norm: 5.5736 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5968 loss: 0.5968 2022/09/05 18:54:09 - mmengine - INFO - Epoch(train) [58][920/940] lr: 1.0000e-03 eta: 7:13:51 time: 0.6514 data_time: 0.0495 memory: 24011 grad_norm: 5.6356 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6588 loss: 0.6588 2022/09/05 18:54:21 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 18:54:21 - mmengine - INFO - Epoch(train) [58][940/940] lr: 1.0000e-03 eta: 7:13:37 time: 0.6005 data_time: 0.0286 memory: 24011 grad_norm: 5.2379 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5501 loss: 0.5501 2022/09/05 18:54:35 - mmengine - INFO - Epoch(val) [58][20/78] eta: 0:00:40 time: 0.6986 data_time: 0.5377 memory: 3625 2022/09/05 18:54:45 - mmengine - INFO - Epoch(val) [58][40/78] eta: 0:00:17 time: 0.4723 data_time: 0.3146 memory: 3625 2022/09/05 18:54:58 - mmengine - INFO - Epoch(val) [58][60/78] eta: 0:00:11 time: 0.6556 data_time: 0.4984 memory: 3625 2022/09/05 18:55:08 - mmengine - INFO - Epoch(val) [58][78/78] acc/top1: 0.7370 acc/top5: 0.9086 acc/mean1: 0.7369 2022/09/05 18:55:27 - mmengine - INFO - Epoch(train) [59][20/940] lr: 1.0000e-03 eta: 7:13:28 time: 0.9435 data_time: 0.2554 memory: 24011 grad_norm: 5.0601 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5809 loss: 0.5809 2022/09/05 18:55:39 - mmengine - INFO - Epoch(train) [59][40/940] lr: 1.0000e-03 eta: 7:13:14 time: 0.6254 data_time: 0.0413 memory: 24011 grad_norm: 14.0905 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7005 loss: 0.7005 2022/09/05 18:55:53 - mmengine - INFO - Epoch(train) [59][60/940] lr: 1.0000e-03 eta: 7:13:01 time: 0.6782 data_time: 0.0464 memory: 24011 grad_norm: 5.5361 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6118 loss: 0.6118 2022/09/05 18:56:06 - mmengine - INFO - Epoch(train) [59][80/940] lr: 1.0000e-03 eta: 7:12:48 time: 0.6663 data_time: 0.0586 memory: 24011 grad_norm: 5.9057 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6772 loss: 0.6772 2022/09/05 18:56:19 - mmengine - INFO - Epoch(train) [59][100/940] lr: 1.0000e-03 eta: 7:12:35 time: 0.6288 data_time: 0.0414 memory: 24011 grad_norm: 6.1849 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6776 loss: 0.6776 2022/09/05 18:56:32 - mmengine - INFO - Epoch(train) [59][120/940] lr: 1.0000e-03 eta: 7:12:22 time: 0.6736 data_time: 0.0400 memory: 24011 grad_norm: 4.8707 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6872 loss: 0.6872 2022/09/05 18:56:45 - mmengine - INFO - Epoch(train) [59][140/940] lr: 1.0000e-03 eta: 7:12:08 time: 0.6496 data_time: 0.0489 memory: 24011 grad_norm: 5.4977 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6594 loss: 0.6594 2022/09/05 18:56:57 - mmengine - INFO - Epoch(train) [59][160/940] lr: 1.0000e-03 eta: 7:11:54 time: 0.6137 data_time: 0.0394 memory: 24011 grad_norm: 5.2066 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6531 loss: 0.6531 2022/09/05 18:57:10 - mmengine - INFO - Epoch(train) [59][180/940] lr: 1.0000e-03 eta: 7:11:41 time: 0.6486 data_time: 0.0412 memory: 24011 grad_norm: 5.0088 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6496 loss: 0.6496 2022/09/05 18:57:23 - mmengine - INFO - Epoch(train) [59][200/940] lr: 1.0000e-03 eta: 7:11:27 time: 0.6254 data_time: 0.0354 memory: 24011 grad_norm: 5.0583 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6016 loss: 0.6016 2022/09/05 18:57:36 - mmengine - INFO - Epoch(train) [59][220/940] lr: 1.0000e-03 eta: 7:11:15 time: 0.6773 data_time: 0.0371 memory: 24011 grad_norm: 5.0634 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6805 loss: 0.6805 2022/09/05 18:57:50 - mmengine - INFO - Epoch(train) [59][240/940] lr: 1.0000e-03 eta: 7:11:01 time: 0.6583 data_time: 0.0397 memory: 24011 grad_norm: 5.6012 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6087 loss: 0.6087 2022/09/05 18:58:03 - mmengine - INFO - Epoch(train) [59][260/940] lr: 1.0000e-03 eta: 7:10:48 time: 0.6440 data_time: 0.0428 memory: 24011 grad_norm: 7.1725 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6981 loss: 0.6981 2022/09/05 18:58:15 - mmengine - INFO - Epoch(train) [59][280/940] lr: 1.0000e-03 eta: 7:10:34 time: 0.6407 data_time: 0.0389 memory: 24011 grad_norm: 5.5551 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.6081 loss: 0.6081 2022/09/05 18:58:29 - mmengine - INFO - Epoch(train) [59][300/940] lr: 1.0000e-03 eta: 7:10:21 time: 0.6628 data_time: 0.0433 memory: 24011 grad_norm: 5.3625 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6717 loss: 0.6717 2022/09/05 18:58:41 - mmengine - INFO - Epoch(train) [59][320/940] lr: 1.0000e-03 eta: 7:10:07 time: 0.5993 data_time: 0.0397 memory: 24011 grad_norm: 5.0154 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5848 loss: 0.5848 2022/09/05 18:58:54 - mmengine - INFO - Epoch(train) [59][340/940] lr: 1.0000e-03 eta: 7:09:54 time: 0.6620 data_time: 0.0405 memory: 24011 grad_norm: 5.6505 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6126 loss: 0.6126 2022/09/05 18:59:07 - mmengine - INFO - Epoch(train) [59][360/940] lr: 1.0000e-03 eta: 7:09:41 time: 0.6412 data_time: 0.0401 memory: 24011 grad_norm: 4.7154 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6355 loss: 0.6355 2022/09/05 18:59:20 - mmengine - INFO - Epoch(train) [59][380/940] lr: 1.0000e-03 eta: 7:09:27 time: 0.6358 data_time: 0.0461 memory: 24011 grad_norm: 5.0007 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6473 loss: 0.6473 2022/09/05 18:59:32 - mmengine - INFO - Epoch(train) [59][400/940] lr: 1.0000e-03 eta: 7:09:14 time: 0.6358 data_time: 0.0479 memory: 24011 grad_norm: 5.0153 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7062 loss: 0.7062 2022/09/05 18:59:45 - mmengine - INFO - Epoch(train) [59][420/940] lr: 1.0000e-03 eta: 7:09:00 time: 0.6528 data_time: 0.0401 memory: 24011 grad_norm: 4.9815 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6349 loss: 0.6349 2022/09/05 18:59:58 - mmengine - INFO - Epoch(train) [59][440/940] lr: 1.0000e-03 eta: 7:08:47 time: 0.6498 data_time: 0.0425 memory: 24011 grad_norm: 5.2934 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6627 loss: 0.6627 2022/09/05 19:00:12 - mmengine - INFO - Epoch(train) [59][460/940] lr: 1.0000e-03 eta: 7:08:34 time: 0.6781 data_time: 0.0305 memory: 24011 grad_norm: 21.8583 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6821 loss: 0.6821 2022/09/05 19:00:25 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:00:25 - mmengine - INFO - Epoch(train) [59][480/940] lr: 1.0000e-03 eta: 7:08:21 time: 0.6508 data_time: 0.0541 memory: 24011 grad_norm: 5.1944 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6256 loss: 0.6256 2022/09/05 19:00:38 - mmengine - INFO - Epoch(train) [59][500/940] lr: 1.0000e-03 eta: 7:08:08 time: 0.6422 data_time: 0.0450 memory: 24011 grad_norm: 5.2943 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6716 loss: 0.6716 2022/09/05 19:00:51 - mmengine - INFO - Epoch(train) [59][520/940] lr: 1.0000e-03 eta: 7:07:54 time: 0.6556 data_time: 0.0372 memory: 24011 grad_norm: 4.8586 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7927 loss: 0.7927 2022/09/05 19:01:04 - mmengine - INFO - Epoch(train) [59][540/940] lr: 1.0000e-03 eta: 7:07:41 time: 0.6315 data_time: 0.0353 memory: 24011 grad_norm: 5.3833 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7357 loss: 0.7357 2022/09/05 19:01:17 - mmengine - INFO - Epoch(train) [59][560/940] lr: 1.0000e-03 eta: 7:07:28 time: 0.6651 data_time: 0.0468 memory: 24011 grad_norm: 5.1004 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6458 loss: 0.6458 2022/09/05 19:01:30 - mmengine - INFO - Epoch(train) [59][580/940] lr: 1.0000e-03 eta: 7:07:14 time: 0.6618 data_time: 0.0377 memory: 24011 grad_norm: 6.1041 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6827 loss: 0.6827 2022/09/05 19:01:42 - mmengine - INFO - Epoch(train) [59][600/940] lr: 1.0000e-03 eta: 7:07:01 time: 0.6091 data_time: 0.0402 memory: 24011 grad_norm: 6.2879 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7151 loss: 0.7151 2022/09/05 19:01:55 - mmengine - INFO - Epoch(train) [59][620/940] lr: 1.0000e-03 eta: 7:06:47 time: 0.6246 data_time: 0.0377 memory: 24011 grad_norm: 5.5162 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6800 loss: 0.6800 2022/09/05 19:02:08 - mmengine - INFO - Epoch(train) [59][640/940] lr: 1.0000e-03 eta: 7:06:34 time: 0.6534 data_time: 0.0428 memory: 24011 grad_norm: 5.8725 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7131 loss: 0.7131 2022/09/05 19:02:20 - mmengine - INFO - Epoch(train) [59][660/940] lr: 1.0000e-03 eta: 7:06:20 time: 0.6239 data_time: 0.0385 memory: 24011 grad_norm: 5.1104 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6342 loss: 0.6342 2022/09/05 19:02:33 - mmengine - INFO - Epoch(train) [59][680/940] lr: 1.0000e-03 eta: 7:06:06 time: 0.6321 data_time: 0.0383 memory: 24011 grad_norm: 4.9949 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6619 loss: 0.6619 2022/09/05 19:02:45 - mmengine - INFO - Epoch(train) [59][700/940] lr: 1.0000e-03 eta: 7:05:53 time: 0.6216 data_time: 0.0436 memory: 24011 grad_norm: 5.3642 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5511 loss: 0.5511 2022/09/05 19:02:59 - mmengine - INFO - Epoch(train) [59][720/940] lr: 1.0000e-03 eta: 7:05:40 time: 0.6657 data_time: 0.0366 memory: 24011 grad_norm: 5.3271 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5941 loss: 0.5941 2022/09/05 19:03:11 - mmengine - INFO - Epoch(train) [59][740/940] lr: 1.0000e-03 eta: 7:05:26 time: 0.6387 data_time: 0.0555 memory: 24011 grad_norm: 5.2506 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6467 loss: 0.6467 2022/09/05 19:03:25 - mmengine - INFO - Epoch(train) [59][760/940] lr: 1.0000e-03 eta: 7:05:13 time: 0.6906 data_time: 0.0480 memory: 24011 grad_norm: 5.1499 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6047 loss: 0.6047 2022/09/05 19:03:38 - mmengine - INFO - Epoch(train) [59][780/940] lr: 1.0000e-03 eta: 7:05:00 time: 0.6315 data_time: 0.0379 memory: 24011 grad_norm: 5.5124 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7538 loss: 0.7538 2022/09/05 19:03:51 - mmengine - INFO - Epoch(train) [59][800/940] lr: 1.0000e-03 eta: 7:04:46 time: 0.6325 data_time: 0.0405 memory: 24011 grad_norm: 4.9179 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6917 loss: 0.6917 2022/09/05 19:04:04 - mmengine - INFO - Epoch(train) [59][820/940] lr: 1.0000e-03 eta: 7:04:33 time: 0.6512 data_time: 0.0385 memory: 24011 grad_norm: 5.3271 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6118 loss: 0.6118 2022/09/05 19:04:17 - mmengine - INFO - Epoch(train) [59][840/940] lr: 1.0000e-03 eta: 7:04:20 time: 0.6770 data_time: 0.0453 memory: 24011 grad_norm: 5.3950 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.7193 loss: 0.7193 2022/09/05 19:04:29 - mmengine - INFO - Epoch(train) [59][860/940] lr: 1.0000e-03 eta: 7:04:06 time: 0.6067 data_time: 0.0500 memory: 24011 grad_norm: 4.8470 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6057 loss: 0.6057 2022/09/05 19:04:43 - mmengine - INFO - Epoch(train) [59][880/940] lr: 1.0000e-03 eta: 7:03:53 time: 0.6658 data_time: 0.1112 memory: 24011 grad_norm: 4.9111 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6294 loss: 0.6294 2022/09/05 19:04:55 - mmengine - INFO - Epoch(train) [59][900/940] lr: 1.0000e-03 eta: 7:03:40 time: 0.6251 data_time: 0.0438 memory: 24011 grad_norm: 5.3700 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.6597 loss: 0.6597 2022/09/05 19:05:08 - mmengine - INFO - Epoch(train) [59][920/940] lr: 1.0000e-03 eta: 7:03:26 time: 0.6528 data_time: 0.0693 memory: 24011 grad_norm: 4.9503 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6610 loss: 0.6610 2022/09/05 19:05:20 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:05:20 - mmengine - INFO - Epoch(train) [59][940/940] lr: 1.0000e-03 eta: 7:03:12 time: 0.5801 data_time: 0.0390 memory: 24011 grad_norm: 5.2142 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.7207 loss: 0.7207 2022/09/05 19:05:34 - mmengine - INFO - Epoch(val) [59][20/78] eta: 0:00:39 time: 0.6865 data_time: 0.5244 memory: 3625 2022/09/05 19:05:43 - mmengine - INFO - Epoch(val) [59][40/78] eta: 0:00:18 time: 0.4808 data_time: 0.3234 memory: 3625 2022/09/05 19:05:57 - mmengine - INFO - Epoch(val) [59][60/78] eta: 0:00:12 time: 0.6781 data_time: 0.5155 memory: 3625 2022/09/05 19:06:06 - mmengine - INFO - Epoch(val) [59][78/78] acc/top1: 0.7391 acc/top5: 0.9080 acc/mean1: 0.7389 2022/09/05 19:06:25 - mmengine - INFO - Epoch(train) [60][20/940] lr: 1.0000e-03 eta: 7:03:02 time: 0.9140 data_time: 0.2633 memory: 24011 grad_norm: 5.3188 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6520 loss: 0.6520 2022/09/05 19:06:37 - mmengine - INFO - Epoch(train) [60][40/940] lr: 1.0000e-03 eta: 7:02:48 time: 0.6060 data_time: 0.0312 memory: 24011 grad_norm: 4.8967 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6950 loss: 0.6950 2022/09/05 19:06:51 - mmengine - INFO - Epoch(train) [60][60/940] lr: 1.0000e-03 eta: 7:02:36 time: 0.6926 data_time: 0.0436 memory: 24011 grad_norm: 4.7818 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6214 loss: 0.6214 2022/09/05 19:07:04 - mmengine - INFO - Epoch(train) [60][80/940] lr: 1.0000e-03 eta: 7:02:22 time: 0.6363 data_time: 0.0449 memory: 24011 grad_norm: 5.4831 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5920 loss: 0.5920 2022/09/05 19:07:16 - mmengine - INFO - Epoch(train) [60][100/940] lr: 1.0000e-03 eta: 7:02:09 time: 0.6432 data_time: 0.0398 memory: 24011 grad_norm: 5.9269 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6637 loss: 0.6637 2022/09/05 19:07:30 - mmengine - INFO - Epoch(train) [60][120/940] lr: 1.0000e-03 eta: 7:01:56 time: 0.6689 data_time: 0.0379 memory: 24011 grad_norm: 5.3362 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6522 loss: 0.6522 2022/09/05 19:07:43 - mmengine - INFO - Epoch(train) [60][140/940] lr: 1.0000e-03 eta: 7:01:43 time: 0.6709 data_time: 0.0419 memory: 24011 grad_norm: 5.1685 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6736 loss: 0.6736 2022/09/05 19:07:56 - mmengine - INFO - Epoch(train) [60][160/940] lr: 1.0000e-03 eta: 7:01:29 time: 0.6262 data_time: 0.0376 memory: 24011 grad_norm: 5.8015 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6076 loss: 0.6076 2022/09/05 19:08:09 - mmengine - INFO - Epoch(train) [60][180/940] lr: 1.0000e-03 eta: 7:01:16 time: 0.6462 data_time: 0.0419 memory: 24011 grad_norm: 5.6682 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6514 loss: 0.6514 2022/09/05 19:08:22 - mmengine - INFO - Epoch(train) [60][200/940] lr: 1.0000e-03 eta: 7:01:03 time: 0.6637 data_time: 0.0357 memory: 24011 grad_norm: 4.9835 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.7136 loss: 0.7136 2022/09/05 19:08:35 - mmengine - INFO - Epoch(train) [60][220/940] lr: 1.0000e-03 eta: 7:00:49 time: 0.6502 data_time: 0.0452 memory: 24011 grad_norm: 6.7741 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6602 loss: 0.6602 2022/09/05 19:08:48 - mmengine - INFO - Epoch(train) [60][240/940] lr: 1.0000e-03 eta: 7:00:36 time: 0.6457 data_time: 0.0481 memory: 24011 grad_norm: 5.5962 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.7130 loss: 0.7130 2022/09/05 19:09:01 - mmengine - INFO - Epoch(train) [60][260/940] lr: 1.0000e-03 eta: 7:00:23 time: 0.6789 data_time: 0.1089 memory: 24011 grad_norm: 5.1973 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6669 loss: 0.6669 2022/09/05 19:09:14 - mmengine - INFO - Epoch(train) [60][280/940] lr: 1.0000e-03 eta: 7:00:10 time: 0.6394 data_time: 0.0320 memory: 24011 grad_norm: 4.7681 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6471 loss: 0.6471 2022/09/05 19:09:26 - mmengine - INFO - Epoch(train) [60][300/940] lr: 1.0000e-03 eta: 6:59:56 time: 0.6069 data_time: 0.0377 memory: 24011 grad_norm: 5.4886 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7290 loss: 0.7290 2022/09/05 19:09:39 - mmengine - INFO - Epoch(train) [60][320/940] lr: 1.0000e-03 eta: 6:59:42 time: 0.6394 data_time: 0.0448 memory: 24011 grad_norm: 5.1505 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5680 loss: 0.5680 2022/09/05 19:09:52 - mmengine - INFO - Epoch(train) [60][340/940] lr: 1.0000e-03 eta: 6:59:29 time: 0.6491 data_time: 0.0799 memory: 24011 grad_norm: 5.2569 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6606 loss: 0.6606 2022/09/05 19:10:05 - mmengine - INFO - Epoch(train) [60][360/940] lr: 1.0000e-03 eta: 6:59:16 time: 0.6610 data_time: 0.0519 memory: 24011 grad_norm: 5.1240 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6412 loss: 0.6412 2022/09/05 19:10:19 - mmengine - INFO - Epoch(train) [60][380/940] lr: 1.0000e-03 eta: 6:59:03 time: 0.6706 data_time: 0.1007 memory: 24011 grad_norm: 4.9821 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6207 loss: 0.6207 2022/09/05 19:10:31 - mmengine - INFO - Epoch(train) [60][400/940] lr: 1.0000e-03 eta: 6:58:49 time: 0.6088 data_time: 0.0339 memory: 24011 grad_norm: 5.9877 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6559 loss: 0.6559 2022/09/05 19:10:45 - mmengine - INFO - Epoch(train) [60][420/940] lr: 1.0000e-03 eta: 6:58:36 time: 0.6878 data_time: 0.0769 memory: 24011 grad_norm: 5.3297 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.6936 loss: 0.6936 2022/09/05 19:10:57 - mmengine - INFO - Epoch(train) [60][440/940] lr: 1.0000e-03 eta: 6:58:23 time: 0.6263 data_time: 0.0303 memory: 24011 grad_norm: 5.5819 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7020 loss: 0.7020 2022/09/05 19:11:10 - mmengine - INFO - Epoch(train) [60][460/940] lr: 1.0000e-03 eta: 6:58:09 time: 0.6490 data_time: 0.0855 memory: 24011 grad_norm: 5.1268 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6007 loss: 0.6007 2022/09/05 19:11:23 - mmengine - INFO - Epoch(train) [60][480/940] lr: 1.0000e-03 eta: 6:57:56 time: 0.6511 data_time: 0.0780 memory: 24011 grad_norm: 5.1881 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6308 loss: 0.6308 2022/09/05 19:11:37 - mmengine - INFO - Epoch(train) [60][500/940] lr: 1.0000e-03 eta: 6:57:43 time: 0.7002 data_time: 0.1420 memory: 24011 grad_norm: 5.1915 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6672 loss: 0.6672 2022/09/05 19:11:50 - mmengine - INFO - Epoch(train) [60][520/940] lr: 1.0000e-03 eta: 6:57:30 time: 0.6225 data_time: 0.0539 memory: 24011 grad_norm: 5.3014 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6386 loss: 0.6386 2022/09/05 19:12:02 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:12:02 - mmengine - INFO - Epoch(train) [60][540/940] lr: 1.0000e-03 eta: 6:57:16 time: 0.6335 data_time: 0.0715 memory: 24011 grad_norm: 4.8681 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6462 loss: 0.6462 2022/09/05 19:12:15 - mmengine - INFO - Epoch(train) [60][560/940] lr: 1.0000e-03 eta: 6:57:03 time: 0.6496 data_time: 0.0782 memory: 24011 grad_norm: 5.4538 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6636 loss: 0.6636 2022/09/05 19:12:29 - mmengine - INFO - Epoch(train) [60][580/940] lr: 1.0000e-03 eta: 6:56:50 time: 0.6717 data_time: 0.1137 memory: 24011 grad_norm: 5.2818 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6316 loss: 0.6316 2022/09/05 19:12:42 - mmengine - INFO - Epoch(train) [60][600/940] lr: 1.0000e-03 eta: 6:56:36 time: 0.6366 data_time: 0.0657 memory: 24011 grad_norm: 5.5014 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6575 loss: 0.6575 2022/09/05 19:12:55 - mmengine - INFO - Epoch(train) [60][620/940] lr: 1.0000e-03 eta: 6:56:23 time: 0.6628 data_time: 0.0810 memory: 24011 grad_norm: 4.9851 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6840 loss: 0.6840 2022/09/05 19:13:07 - mmengine - INFO - Epoch(train) [60][640/940] lr: 1.0000e-03 eta: 6:56:09 time: 0.5930 data_time: 0.0304 memory: 24011 grad_norm: 5.2810 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6965 loss: 0.6965 2022/09/05 19:13:20 - mmengine - INFO - Epoch(train) [60][660/940] lr: 1.0000e-03 eta: 6:55:56 time: 0.6624 data_time: 0.0840 memory: 24011 grad_norm: 5.1103 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5696 loss: 0.5696 2022/09/05 19:13:33 - mmengine - INFO - Epoch(train) [60][680/940] lr: 1.0000e-03 eta: 6:55:43 time: 0.6355 data_time: 0.0618 memory: 24011 grad_norm: 5.1695 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.7179 loss: 0.7179 2022/09/05 19:13:46 - mmengine - INFO - Epoch(train) [60][700/940] lr: 1.0000e-03 eta: 6:55:30 time: 0.6697 data_time: 0.0852 memory: 24011 grad_norm: 5.2392 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6546 loss: 0.6546 2022/09/05 19:13:59 - mmengine - INFO - Epoch(train) [60][720/940] lr: 1.0000e-03 eta: 6:55:16 time: 0.6285 data_time: 0.0577 memory: 24011 grad_norm: 5.4245 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6978 loss: 0.6978 2022/09/05 19:14:11 - mmengine - INFO - Epoch(train) [60][740/940] lr: 1.0000e-03 eta: 6:55:02 time: 0.6367 data_time: 0.0408 memory: 24011 grad_norm: 4.9865 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7668 loss: 0.7668 2022/09/05 19:14:26 - mmengine - INFO - Epoch(train) [60][760/940] lr: 1.0000e-03 eta: 6:54:50 time: 0.7116 data_time: 0.1242 memory: 24011 grad_norm: 5.1719 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6919 loss: 0.6919 2022/09/05 19:14:38 - mmengine - INFO - Epoch(train) [60][780/940] lr: 1.0000e-03 eta: 6:54:36 time: 0.6201 data_time: 0.0369 memory: 24011 grad_norm: 5.7391 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6302 loss: 0.6302 2022/09/05 19:14:50 - mmengine - INFO - Epoch(train) [60][800/940] lr: 1.0000e-03 eta: 6:54:22 time: 0.6020 data_time: 0.0311 memory: 24011 grad_norm: 5.1105 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6177 loss: 0.6177 2022/09/05 19:15:03 - mmengine - INFO - Epoch(train) [60][820/940] lr: 1.0000e-03 eta: 6:54:09 time: 0.6456 data_time: 0.0380 memory: 24011 grad_norm: 4.8467 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6461 loss: 0.6461 2022/09/05 19:15:16 - mmengine - INFO - Epoch(train) [60][840/940] lr: 1.0000e-03 eta: 6:53:56 time: 0.6418 data_time: 0.0363 memory: 24011 grad_norm: 5.1695 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6058 loss: 0.6058 2022/09/05 19:15:29 - mmengine - INFO - Epoch(train) [60][860/940] lr: 1.0000e-03 eta: 6:53:42 time: 0.6545 data_time: 0.0413 memory: 24011 grad_norm: 5.5244 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6889 loss: 0.6889 2022/09/05 19:15:42 - mmengine - INFO - Epoch(train) [60][880/940] lr: 1.0000e-03 eta: 6:53:29 time: 0.6606 data_time: 0.0402 memory: 24011 grad_norm: 5.2232 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6373 loss: 0.6373 2022/09/05 19:15:56 - mmengine - INFO - Epoch(train) [60][900/940] lr: 1.0000e-03 eta: 6:53:16 time: 0.6635 data_time: 0.0528 memory: 24011 grad_norm: 5.0842 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7547 loss: 0.7547 2022/09/05 19:16:09 - mmengine - INFO - Epoch(train) [60][920/940] lr: 1.0000e-03 eta: 6:53:03 time: 0.6544 data_time: 0.0743 memory: 24011 grad_norm: 5.2175 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6378 loss: 0.6378 2022/09/05 19:16:20 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:16:20 - mmengine - INFO - Epoch(train) [60][940/940] lr: 1.0000e-03 eta: 6:52:49 time: 0.5669 data_time: 0.0341 memory: 24011 grad_norm: 5.1846 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.6371 loss: 0.6371 2022/09/05 19:16:20 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/09/05 19:16:39 - mmengine - INFO - Epoch(val) [60][20/78] eta: 0:00:41 time: 0.7184 data_time: 0.5608 memory: 3625 2022/09/05 19:16:48 - mmengine - INFO - Epoch(val) [60][40/78] eta: 0:00:17 time: 0.4507 data_time: 0.2929 memory: 3625 2022/09/05 19:17:01 - mmengine - INFO - Epoch(val) [60][60/78] eta: 0:00:11 time: 0.6290 data_time: 0.4734 memory: 3625 2022/09/05 19:17:10 - mmengine - INFO - Epoch(val) [60][78/78] acc/top1: 0.7402 acc/top5: 0.9080 acc/mean1: 0.7401 2022/09/05 19:17:28 - mmengine - INFO - Epoch(train) [61][20/940] lr: 1.0000e-03 eta: 6:52:38 time: 0.8912 data_time: 0.2635 memory: 24011 grad_norm: 5.3002 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7187 loss: 0.7187 2022/09/05 19:17:42 - mmengine - INFO - Epoch(train) [61][40/940] lr: 1.0000e-03 eta: 6:52:25 time: 0.6711 data_time: 0.0330 memory: 24011 grad_norm: 5.0603 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6130 loss: 0.6130 2022/09/05 19:17:55 - mmengine - INFO - Epoch(train) [61][60/940] lr: 1.0000e-03 eta: 6:52:12 time: 0.6496 data_time: 0.0528 memory: 24011 grad_norm: 6.2182 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7107 loss: 0.7107 2022/09/05 19:18:07 - mmengine - INFO - Epoch(train) [61][80/940] lr: 1.0000e-03 eta: 6:51:59 time: 0.6359 data_time: 0.0613 memory: 24011 grad_norm: 5.0843 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6906 loss: 0.6906 2022/09/05 19:18:21 - mmengine - INFO - Epoch(train) [61][100/940] lr: 1.0000e-03 eta: 6:51:45 time: 0.6599 data_time: 0.1045 memory: 24011 grad_norm: 5.3721 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6567 loss: 0.6567 2022/09/05 19:18:34 - mmengine - INFO - Epoch(train) [61][120/940] lr: 1.0000e-03 eta: 6:51:32 time: 0.6476 data_time: 0.0898 memory: 24011 grad_norm: 5.0949 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7049 loss: 0.7049 2022/09/05 19:18:46 - mmengine - INFO - Epoch(train) [61][140/940] lr: 1.0000e-03 eta: 6:51:18 time: 0.6204 data_time: 0.0616 memory: 24011 grad_norm: 5.2791 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6456 loss: 0.6456 2022/09/05 19:18:58 - mmengine - INFO - Epoch(train) [61][160/940] lr: 1.0000e-03 eta: 6:51:05 time: 0.6208 data_time: 0.0458 memory: 24011 grad_norm: 5.3952 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6985 loss: 0.6985 2022/09/05 19:19:12 - mmengine - INFO - Epoch(train) [61][180/940] lr: 1.0000e-03 eta: 6:50:52 time: 0.6944 data_time: 0.0429 memory: 24011 grad_norm: 5.7501 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.5595 loss: 0.5595 2022/09/05 19:19:25 - mmengine - INFO - Epoch(train) [61][200/940] lr: 1.0000e-03 eta: 6:50:39 time: 0.6495 data_time: 0.0561 memory: 24011 grad_norm: 5.1434 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6021 loss: 0.6021 2022/09/05 19:19:39 - mmengine - INFO - Epoch(train) [61][220/940] lr: 1.0000e-03 eta: 6:50:26 time: 0.6857 data_time: 0.0561 memory: 24011 grad_norm: 5.2505 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6819 loss: 0.6819 2022/09/05 19:19:51 - mmengine - INFO - Epoch(train) [61][240/940] lr: 1.0000e-03 eta: 6:50:12 time: 0.6002 data_time: 0.0343 memory: 24011 grad_norm: 5.0674 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6333 loss: 0.6333 2022/09/05 19:20:05 - mmengine - INFO - Epoch(train) [61][260/940] lr: 1.0000e-03 eta: 6:49:59 time: 0.6879 data_time: 0.0792 memory: 24011 grad_norm: 4.8819 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6287 loss: 0.6287 2022/09/05 19:20:17 - mmengine - INFO - Epoch(train) [61][280/940] lr: 1.0000e-03 eta: 6:49:46 time: 0.6344 data_time: 0.0400 memory: 24011 grad_norm: 5.5210 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6666 loss: 0.6666 2022/09/05 19:20:31 - mmengine - INFO - Epoch(train) [61][300/940] lr: 1.0000e-03 eta: 6:49:33 time: 0.6696 data_time: 0.0723 memory: 24011 grad_norm: 4.8518 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.6277 loss: 0.6277 2022/09/05 19:20:44 - mmengine - INFO - Epoch(train) [61][320/940] lr: 1.0000e-03 eta: 6:49:19 time: 0.6367 data_time: 0.0280 memory: 24011 grad_norm: 4.9935 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6254 loss: 0.6254 2022/09/05 19:20:57 - mmengine - INFO - Epoch(train) [61][340/940] lr: 1.0000e-03 eta: 6:49:06 time: 0.6717 data_time: 0.0380 memory: 24011 grad_norm: 5.8003 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6607 loss: 0.6607 2022/09/05 19:21:10 - mmengine - INFO - Epoch(train) [61][360/940] lr: 1.0000e-03 eta: 6:48:53 time: 0.6324 data_time: 0.0373 memory: 24011 grad_norm: 5.5351 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6157 loss: 0.6157 2022/09/05 19:21:22 - mmengine - INFO - Epoch(train) [61][380/940] lr: 1.0000e-03 eta: 6:48:39 time: 0.6345 data_time: 0.0399 memory: 24011 grad_norm: 5.5518 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6080 loss: 0.6080 2022/09/05 19:21:35 - mmengine - INFO - Epoch(train) [61][400/940] lr: 1.0000e-03 eta: 6:48:26 time: 0.6269 data_time: 0.0381 memory: 24011 grad_norm: 5.0556 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6674 loss: 0.6674 2022/09/05 19:21:48 - mmengine - INFO - Epoch(train) [61][420/940] lr: 1.0000e-03 eta: 6:48:12 time: 0.6588 data_time: 0.0513 memory: 24011 grad_norm: 5.1858 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7062 loss: 0.7062 2022/09/05 19:22:01 - mmengine - INFO - Epoch(train) [61][440/940] lr: 1.0000e-03 eta: 6:47:59 time: 0.6345 data_time: 0.0414 memory: 24011 grad_norm: 5.1022 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6838 loss: 0.6838 2022/09/05 19:22:14 - mmengine - INFO - Epoch(train) [61][460/940] lr: 1.0000e-03 eta: 6:47:46 time: 0.6750 data_time: 0.0410 memory: 24011 grad_norm: 6.3094 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6176 loss: 0.6176 2022/09/05 19:22:28 - mmengine - INFO - Epoch(train) [61][480/940] lr: 1.0000e-03 eta: 6:47:33 time: 0.6795 data_time: 0.0408 memory: 24011 grad_norm: 5.3400 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7433 loss: 0.7433 2022/09/05 19:22:40 - mmengine - INFO - Epoch(train) [61][500/940] lr: 1.0000e-03 eta: 6:47:19 time: 0.6206 data_time: 0.0421 memory: 24011 grad_norm: 5.2908 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.7310 loss: 0.7310 2022/09/05 19:22:53 - mmengine - INFO - Epoch(train) [61][520/940] lr: 1.0000e-03 eta: 6:47:06 time: 0.6214 data_time: 0.0400 memory: 24011 grad_norm: 5.0967 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6297 loss: 0.6297 2022/09/05 19:23:06 - mmengine - INFO - Epoch(train) [61][540/940] lr: 1.0000e-03 eta: 6:46:52 time: 0.6506 data_time: 0.0388 memory: 24011 grad_norm: 7.9555 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6239 loss: 0.6239 2022/09/05 19:23:19 - mmengine - INFO - Epoch(train) [61][560/940] lr: 1.0000e-03 eta: 6:46:39 time: 0.6672 data_time: 0.0398 memory: 24011 grad_norm: 5.4143 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6863 loss: 0.6863 2022/09/05 19:23:32 - mmengine - INFO - Epoch(train) [61][580/940] lr: 1.0000e-03 eta: 6:46:26 time: 0.6420 data_time: 0.0346 memory: 24011 grad_norm: 5.4254 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6333 loss: 0.6333 2022/09/05 19:23:45 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:23:45 - mmengine - INFO - Epoch(train) [61][600/940] lr: 1.0000e-03 eta: 6:46:13 time: 0.6664 data_time: 0.0437 memory: 24011 grad_norm: 5.0716 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6485 loss: 0.6485 2022/09/05 19:23:59 - mmengine - INFO - Epoch(train) [61][620/940] lr: 1.0000e-03 eta: 6:46:00 time: 0.6812 data_time: 0.0418 memory: 24011 grad_norm: 5.6296 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7006 loss: 0.7006 2022/09/05 19:24:11 - mmengine - INFO - Epoch(train) [61][640/940] lr: 1.0000e-03 eta: 6:45:46 time: 0.6075 data_time: 0.0374 memory: 24011 grad_norm: 4.9699 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6271 loss: 0.6271 2022/09/05 19:24:23 - mmengine - INFO - Epoch(train) [61][660/940] lr: 1.0000e-03 eta: 6:45:32 time: 0.6016 data_time: 0.0419 memory: 24011 grad_norm: 5.2021 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6267 loss: 0.6267 2022/09/05 19:24:36 - mmengine - INFO - Epoch(train) [61][680/940] lr: 1.0000e-03 eta: 6:45:19 time: 0.6516 data_time: 0.0368 memory: 24011 grad_norm: 5.2140 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6601 loss: 0.6601 2022/09/05 19:24:50 - mmengine - INFO - Epoch(train) [61][700/940] lr: 1.0000e-03 eta: 6:45:06 time: 0.6771 data_time: 0.0412 memory: 24011 grad_norm: 5.1323 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6572 loss: 0.6572 2022/09/05 19:25:02 - mmengine - INFO - Epoch(train) [61][720/940] lr: 1.0000e-03 eta: 6:44:52 time: 0.6094 data_time: 0.0376 memory: 24011 grad_norm: 5.5976 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6150 loss: 0.6150 2022/09/05 19:25:15 - mmengine - INFO - Epoch(train) [61][740/940] lr: 1.0000e-03 eta: 6:44:39 time: 0.6332 data_time: 0.0465 memory: 24011 grad_norm: 5.3481 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6489 loss: 0.6489 2022/09/05 19:25:27 - mmengine - INFO - Epoch(train) [61][760/940] lr: 1.0000e-03 eta: 6:44:25 time: 0.6232 data_time: 0.0462 memory: 24011 grad_norm: 5.2424 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5556 loss: 0.5556 2022/09/05 19:25:40 - mmengine - INFO - Epoch(train) [61][780/940] lr: 1.0000e-03 eta: 6:44:12 time: 0.6336 data_time: 0.0354 memory: 24011 grad_norm: 5.3171 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5917 loss: 0.5917 2022/09/05 19:25:52 - mmengine - INFO - Epoch(train) [61][800/940] lr: 1.0000e-03 eta: 6:43:58 time: 0.6156 data_time: 0.0416 memory: 24011 grad_norm: 5.2090 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.7571 loss: 0.7571 2022/09/05 19:26:06 - mmengine - INFO - Epoch(train) [61][820/940] lr: 1.0000e-03 eta: 6:43:45 time: 0.6760 data_time: 0.0346 memory: 24011 grad_norm: 4.9840 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.6871 loss: 0.6871 2022/09/05 19:26:19 - mmengine - INFO - Epoch(train) [61][840/940] lr: 1.0000e-03 eta: 6:43:32 time: 0.6743 data_time: 0.0421 memory: 24011 grad_norm: 5.2470 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6484 loss: 0.6484 2022/09/05 19:26:32 - mmengine - INFO - Epoch(train) [61][860/940] lr: 1.0000e-03 eta: 6:43:19 time: 0.6436 data_time: 0.0377 memory: 24011 grad_norm: 5.0919 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6205 loss: 0.6205 2022/09/05 19:26:45 - mmengine - INFO - Epoch(train) [61][880/940] lr: 1.0000e-03 eta: 6:43:05 time: 0.6626 data_time: 0.0423 memory: 24011 grad_norm: 5.3235 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7109 loss: 0.7109 2022/09/05 19:26:58 - mmengine - INFO - Epoch(train) [61][900/940] lr: 1.0000e-03 eta: 6:42:52 time: 0.6553 data_time: 0.0375 memory: 24011 grad_norm: 4.8638 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6692 loss: 0.6692 2022/09/05 19:27:11 - mmengine - INFO - Epoch(train) [61][920/940] lr: 1.0000e-03 eta: 6:42:39 time: 0.6235 data_time: 0.0408 memory: 24011 grad_norm: 5.6669 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6160 loss: 0.6160 2022/09/05 19:27:22 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:27:22 - mmengine - INFO - Epoch(train) [61][940/940] lr: 1.0000e-03 eta: 6:42:24 time: 0.5499 data_time: 0.0264 memory: 24011 grad_norm: 5.1879 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 0.6588 loss: 0.6588 2022/09/05 19:27:36 - mmengine - INFO - Epoch(val) [61][20/78] eta: 0:00:40 time: 0.7039 data_time: 0.5416 memory: 3625 2022/09/05 19:27:45 - mmengine - INFO - Epoch(val) [61][40/78] eta: 0:00:17 time: 0.4613 data_time: 0.3029 memory: 3625 2022/09/05 19:27:58 - mmengine - INFO - Epoch(val) [61][60/78] eta: 0:00:11 time: 0.6492 data_time: 0.4885 memory: 3625 2022/09/05 19:28:08 - mmengine - INFO - Epoch(val) [61][78/78] acc/top1: 0.7378 acc/top5: 0.9070 acc/mean1: 0.7377 2022/09/05 19:28:27 - mmengine - INFO - Epoch(train) [62][20/940] lr: 1.0000e-03 eta: 6:42:14 time: 0.9121 data_time: 0.2874 memory: 24011 grad_norm: 5.3985 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.6634 loss: 0.6634 2022/09/05 19:28:39 - mmengine - INFO - Epoch(train) [62][40/940] lr: 1.0000e-03 eta: 6:42:00 time: 0.6115 data_time: 0.0434 memory: 24011 grad_norm: 4.9120 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5742 loss: 0.5742 2022/09/05 19:28:52 - mmengine - INFO - Epoch(train) [62][60/940] lr: 1.0000e-03 eta: 6:41:47 time: 0.6722 data_time: 0.0544 memory: 24011 grad_norm: 4.9562 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6589 loss: 0.6589 2022/09/05 19:29:05 - mmengine - INFO - Epoch(train) [62][80/940] lr: 1.0000e-03 eta: 6:41:34 time: 0.6218 data_time: 0.0520 memory: 24011 grad_norm: 5.9655 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6806 loss: 0.6806 2022/09/05 19:29:18 - mmengine - INFO - Epoch(train) [62][100/940] lr: 1.0000e-03 eta: 6:41:21 time: 0.6710 data_time: 0.0980 memory: 24011 grad_norm: 5.3997 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.7443 loss: 0.7443 2022/09/05 19:29:30 - mmengine - INFO - Epoch(train) [62][120/940] lr: 1.0000e-03 eta: 6:41:07 time: 0.6169 data_time: 0.0316 memory: 24011 grad_norm: 5.0981 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5646 loss: 0.5646 2022/09/05 19:29:44 - mmengine - INFO - Epoch(train) [62][140/940] lr: 1.0000e-03 eta: 6:40:54 time: 0.6902 data_time: 0.0557 memory: 24011 grad_norm: 4.8894 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6478 loss: 0.6478 2022/09/05 19:29:57 - mmengine - INFO - Epoch(train) [62][160/940] lr: 1.0000e-03 eta: 6:40:41 time: 0.6307 data_time: 0.0494 memory: 24011 grad_norm: 5.1048 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6986 loss: 0.6986 2022/09/05 19:30:10 - mmengine - INFO - Epoch(train) [62][180/940] lr: 1.0000e-03 eta: 6:40:28 time: 0.6646 data_time: 0.0439 memory: 24011 grad_norm: 5.1878 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7409 loss: 0.7409 2022/09/05 19:30:24 - mmengine - INFO - Epoch(train) [62][200/940] lr: 1.0000e-03 eta: 6:40:15 time: 0.6732 data_time: 0.0380 memory: 24011 grad_norm: 5.4810 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6286 loss: 0.6286 2022/09/05 19:30:37 - mmengine - INFO - Epoch(train) [62][220/940] lr: 1.0000e-03 eta: 6:40:01 time: 0.6355 data_time: 0.0399 memory: 24011 grad_norm: 5.1516 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6268 loss: 0.6268 2022/09/05 19:30:49 - mmengine - INFO - Epoch(train) [62][240/940] lr: 1.0000e-03 eta: 6:39:48 time: 0.6538 data_time: 0.0506 memory: 24011 grad_norm: 4.9722 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5332 loss: 0.5332 2022/09/05 19:31:03 - mmengine - INFO - Epoch(train) [62][260/940] lr: 1.0000e-03 eta: 6:39:35 time: 0.6857 data_time: 0.0390 memory: 24011 grad_norm: 5.1631 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6161 loss: 0.6161 2022/09/05 19:31:16 - mmengine - INFO - Epoch(train) [62][280/940] lr: 1.0000e-03 eta: 6:39:22 time: 0.6299 data_time: 0.0379 memory: 24011 grad_norm: 5.6032 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6200 loss: 0.6200 2022/09/05 19:31:29 - mmengine - INFO - Epoch(train) [62][300/940] lr: 1.0000e-03 eta: 6:39:08 time: 0.6445 data_time: 0.0405 memory: 24011 grad_norm: 4.8647 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6479 loss: 0.6479 2022/09/05 19:31:41 - mmengine - INFO - Epoch(train) [62][320/940] lr: 1.0000e-03 eta: 6:38:54 time: 0.6116 data_time: 0.0369 memory: 24011 grad_norm: 5.0386 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7082 loss: 0.7082 2022/09/05 19:31:55 - mmengine - INFO - Epoch(train) [62][340/940] lr: 1.0000e-03 eta: 6:38:42 time: 0.6893 data_time: 0.0454 memory: 24011 grad_norm: 5.1958 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.7037 loss: 0.7037 2022/09/05 19:32:07 - mmengine - INFO - Epoch(train) [62][360/940] lr: 1.0000e-03 eta: 6:38:28 time: 0.6098 data_time: 0.0416 memory: 24011 grad_norm: 4.9879 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7173 loss: 0.7173 2022/09/05 19:32:20 - mmengine - INFO - Epoch(train) [62][380/940] lr: 1.0000e-03 eta: 6:38:15 time: 0.6434 data_time: 0.0506 memory: 24011 grad_norm: 6.8410 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6805 loss: 0.6805 2022/09/05 19:32:32 - mmengine - INFO - Epoch(train) [62][400/940] lr: 1.0000e-03 eta: 6:38:01 time: 0.6288 data_time: 0.0575 memory: 24011 grad_norm: 5.9142 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6781 loss: 0.6781 2022/09/05 19:32:46 - mmengine - INFO - Epoch(train) [62][420/940] lr: 1.0000e-03 eta: 6:37:48 time: 0.6616 data_time: 0.0432 memory: 24011 grad_norm: 5.2488 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5849 loss: 0.5849 2022/09/05 19:32:59 - mmengine - INFO - Epoch(train) [62][440/940] lr: 1.0000e-03 eta: 6:37:35 time: 0.6749 data_time: 0.0523 memory: 24011 grad_norm: 5.0773 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6718 loss: 0.6718 2022/09/05 19:33:12 - mmengine - INFO - Epoch(train) [62][460/940] lr: 1.0000e-03 eta: 6:37:21 time: 0.6388 data_time: 0.0450 memory: 24011 grad_norm: 4.9692 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5783 loss: 0.5783 2022/09/05 19:33:24 - mmengine - INFO - Epoch(train) [62][480/940] lr: 1.0000e-03 eta: 6:37:08 time: 0.6253 data_time: 0.0332 memory: 24011 grad_norm: 5.0531 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6695 loss: 0.6695 2022/09/05 19:33:38 - mmengine - INFO - Epoch(train) [62][500/940] lr: 1.0000e-03 eta: 6:36:55 time: 0.6947 data_time: 0.0427 memory: 24011 grad_norm: 5.0582 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6157 loss: 0.6157 2022/09/05 19:33:50 - mmengine - INFO - Epoch(train) [62][520/940] lr: 1.0000e-03 eta: 6:36:41 time: 0.5993 data_time: 0.0419 memory: 24011 grad_norm: 5.2080 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6906 loss: 0.6906 2022/09/05 19:34:03 - mmengine - INFO - Epoch(train) [62][540/940] lr: 1.0000e-03 eta: 6:36:28 time: 0.6580 data_time: 0.0459 memory: 24011 grad_norm: 5.3333 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5520 loss: 0.5520 2022/09/05 19:34:16 - mmengine - INFO - Epoch(train) [62][560/940] lr: 1.0000e-03 eta: 6:36:15 time: 0.6472 data_time: 0.0400 memory: 24011 grad_norm: 4.8620 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5983 loss: 0.5983 2022/09/05 19:34:29 - mmengine - INFO - Epoch(train) [62][580/940] lr: 1.0000e-03 eta: 6:36:01 time: 0.6375 data_time: 0.0400 memory: 24011 grad_norm: 4.9996 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5838 loss: 0.5838 2022/09/05 19:34:42 - mmengine - INFO - Epoch(train) [62][600/940] lr: 1.0000e-03 eta: 6:35:48 time: 0.6570 data_time: 0.0390 memory: 24011 grad_norm: 4.9906 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5738 loss: 0.5738 2022/09/05 19:34:57 - mmengine - INFO - Epoch(train) [62][620/940] lr: 1.0000e-03 eta: 6:35:36 time: 0.7165 data_time: 0.0371 memory: 24011 grad_norm: 4.7093 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6141 loss: 0.6141 2022/09/05 19:35:09 - mmengine - INFO - Epoch(train) [62][640/940] lr: 1.0000e-03 eta: 6:35:22 time: 0.5951 data_time: 0.0384 memory: 24011 grad_norm: 5.0627 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 0.6772 loss: 0.6772 2022/09/05 19:35:21 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:35:22 - mmengine - INFO - Epoch(train) [62][660/940] lr: 1.0000e-03 eta: 6:35:08 time: 0.6310 data_time: 0.0424 memory: 24011 grad_norm: 4.7536 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6607 loss: 0.6607 2022/09/05 19:35:34 - mmengine - INFO - Epoch(train) [62][680/940] lr: 1.0000e-03 eta: 6:34:55 time: 0.6501 data_time: 0.0582 memory: 24011 grad_norm: 4.8992 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6119 loss: 0.6119 2022/09/05 19:35:48 - mmengine - INFO - Epoch(train) [62][700/940] lr: 1.0000e-03 eta: 6:34:42 time: 0.6833 data_time: 0.0400 memory: 24011 grad_norm: 5.0675 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6442 loss: 0.6442 2022/09/05 19:36:00 - mmengine - INFO - Epoch(train) [62][720/940] lr: 1.0000e-03 eta: 6:34:28 time: 0.6293 data_time: 0.0495 memory: 24011 grad_norm: 5.2339 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6051 loss: 0.6051 2022/09/05 19:36:13 - mmengine - INFO - Epoch(train) [62][740/940] lr: 1.0000e-03 eta: 6:34:15 time: 0.6446 data_time: 0.0398 memory: 24011 grad_norm: 5.4244 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5983 loss: 0.5983 2022/09/05 19:36:26 - mmengine - INFO - Epoch(train) [62][760/940] lr: 1.0000e-03 eta: 6:34:01 time: 0.6112 data_time: 0.0377 memory: 24011 grad_norm: 5.0883 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6430 loss: 0.6430 2022/09/05 19:36:39 - mmengine - INFO - Epoch(train) [62][780/940] lr: 1.0000e-03 eta: 6:33:48 time: 0.6712 data_time: 0.0441 memory: 24011 grad_norm: 4.9538 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.7429 loss: 0.7429 2022/09/05 19:36:52 - mmengine - INFO - Epoch(train) [62][800/940] lr: 1.0000e-03 eta: 6:33:35 time: 0.6395 data_time: 0.0384 memory: 24011 grad_norm: 5.0943 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6630 loss: 0.6630 2022/09/05 19:37:05 - mmengine - INFO - Epoch(train) [62][820/940] lr: 1.0000e-03 eta: 6:33:22 time: 0.6635 data_time: 0.0570 memory: 24011 grad_norm: 5.2830 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6360 loss: 0.6360 2022/09/05 19:37:17 - mmengine - INFO - Epoch(train) [62][840/940] lr: 1.0000e-03 eta: 6:33:08 time: 0.6069 data_time: 0.0424 memory: 24011 grad_norm: 4.9966 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6241 loss: 0.6241 2022/09/05 19:37:30 - mmengine - INFO - Epoch(train) [62][860/940] lr: 1.0000e-03 eta: 6:32:55 time: 0.6362 data_time: 0.0401 memory: 24011 grad_norm: 4.9487 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5023 loss: 0.5023 2022/09/05 19:37:43 - mmengine - INFO - Epoch(train) [62][880/940] lr: 1.0000e-03 eta: 6:32:41 time: 0.6360 data_time: 0.0415 memory: 24011 grad_norm: 5.3955 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6582 loss: 0.6582 2022/09/05 19:37:56 - mmengine - INFO - Epoch(train) [62][900/940] lr: 1.0000e-03 eta: 6:32:28 time: 0.6853 data_time: 0.0409 memory: 24011 grad_norm: 5.4839 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6612 loss: 0.6612 2022/09/05 19:38:09 - mmengine - INFO - Epoch(train) [62][920/940] lr: 1.0000e-03 eta: 6:32:15 time: 0.6483 data_time: 0.0429 memory: 24011 grad_norm: 5.0827 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6608 loss: 0.6608 2022/09/05 19:38:21 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:38:21 - mmengine - INFO - Epoch(train) [62][940/940] lr: 1.0000e-03 eta: 6:32:01 time: 0.5669 data_time: 0.0292 memory: 24011 grad_norm: 5.4716 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.6444 loss: 0.6444 2022/09/05 19:38:35 - mmengine - INFO - Epoch(val) [62][20/78] eta: 0:00:40 time: 0.6948 data_time: 0.5364 memory: 3625 2022/09/05 19:38:44 - mmengine - INFO - Epoch(val) [62][40/78] eta: 0:00:17 time: 0.4546 data_time: 0.2922 memory: 3625 2022/09/05 19:38:57 - mmengine - INFO - Epoch(val) [62][60/78] eta: 0:00:11 time: 0.6623 data_time: 0.5034 memory: 3625 2022/09/05 19:39:07 - mmengine - INFO - Epoch(val) [62][78/78] acc/top1: 0.7385 acc/top5: 0.9064 acc/mean1: 0.7383 2022/09/05 19:39:26 - mmengine - INFO - Epoch(train) [63][20/940] lr: 1.0000e-03 eta: 6:31:51 time: 0.9237 data_time: 0.2979 memory: 24011 grad_norm: 4.9316 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6483 loss: 0.6483 2022/09/05 19:39:38 - mmengine - INFO - Epoch(train) [63][40/940] lr: 1.0000e-03 eta: 6:31:37 time: 0.6123 data_time: 0.0308 memory: 24011 grad_norm: 4.8801 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7158 loss: 0.7158 2022/09/05 19:39:52 - mmengine - INFO - Epoch(train) [63][60/940] lr: 1.0000e-03 eta: 6:31:24 time: 0.6699 data_time: 0.0623 memory: 24011 grad_norm: 4.9848 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6943 loss: 0.6943 2022/09/05 19:40:05 - mmengine - INFO - Epoch(train) [63][80/940] lr: 1.0000e-03 eta: 6:31:11 time: 0.6628 data_time: 0.0366 memory: 24011 grad_norm: 4.8882 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6645 loss: 0.6645 2022/09/05 19:40:18 - mmengine - INFO - Epoch(train) [63][100/940] lr: 1.0000e-03 eta: 6:30:58 time: 0.6424 data_time: 0.0428 memory: 24011 grad_norm: 4.9654 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6879 loss: 0.6879 2022/09/05 19:40:31 - mmengine - INFO - Epoch(train) [63][120/940] lr: 1.0000e-03 eta: 6:30:44 time: 0.6511 data_time: 0.0332 memory: 24011 grad_norm: 4.9812 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6938 loss: 0.6938 2022/09/05 19:40:45 - mmengine - INFO - Epoch(train) [63][140/940] lr: 1.0000e-03 eta: 6:30:32 time: 0.7019 data_time: 0.0523 memory: 24011 grad_norm: 5.1442 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5790 loss: 0.5790 2022/09/05 19:40:57 - mmengine - INFO - Epoch(train) [63][160/940] lr: 1.0000e-03 eta: 6:30:18 time: 0.6205 data_time: 0.0357 memory: 24011 grad_norm: 4.9116 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6804 loss: 0.6804 2022/09/05 19:41:10 - mmengine - INFO - Epoch(train) [63][180/940] lr: 1.0000e-03 eta: 6:30:05 time: 0.6541 data_time: 0.0410 memory: 24011 grad_norm: 5.2283 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6634 loss: 0.6634 2022/09/05 19:41:23 - mmengine - INFO - Epoch(train) [63][200/940] lr: 1.0000e-03 eta: 6:29:51 time: 0.6366 data_time: 0.0368 memory: 24011 grad_norm: 5.0532 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6732 loss: 0.6732 2022/09/05 19:41:36 - mmengine - INFO - Epoch(train) [63][220/940] lr: 1.0000e-03 eta: 6:29:38 time: 0.6608 data_time: 0.0435 memory: 24011 grad_norm: 5.1882 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5648 loss: 0.5648 2022/09/05 19:41:48 - mmengine - INFO - Epoch(train) [63][240/940] lr: 1.0000e-03 eta: 6:29:24 time: 0.5992 data_time: 0.0399 memory: 24011 grad_norm: 4.9534 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6366 loss: 0.6366 2022/09/05 19:42:02 - mmengine - INFO - Epoch(train) [63][260/940] lr: 1.0000e-03 eta: 6:29:12 time: 0.6886 data_time: 0.0404 memory: 24011 grad_norm: 5.0491 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.6022 loss: 0.6022 2022/09/05 19:42:15 - mmengine - INFO - Epoch(train) [63][280/940] lr: 1.0000e-03 eta: 6:28:58 time: 0.6599 data_time: 0.0417 memory: 24011 grad_norm: 5.3779 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6281 loss: 0.6281 2022/09/05 19:42:29 - mmengine - INFO - Epoch(train) [63][300/940] lr: 1.0000e-03 eta: 6:28:45 time: 0.6846 data_time: 0.0436 memory: 24011 grad_norm: 5.0217 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6168 loss: 0.6168 2022/09/05 19:42:41 - mmengine - INFO - Epoch(train) [63][320/940] lr: 1.0000e-03 eta: 6:28:32 time: 0.6010 data_time: 0.0352 memory: 24011 grad_norm: 5.1726 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6482 loss: 0.6482 2022/09/05 19:42:54 - mmengine - INFO - Epoch(train) [63][340/940] lr: 1.0000e-03 eta: 6:28:19 time: 0.6644 data_time: 0.0479 memory: 24011 grad_norm: 5.0669 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6184 loss: 0.6184 2022/09/05 19:43:07 - mmengine - INFO - Epoch(train) [63][360/940] lr: 1.0000e-03 eta: 6:28:05 time: 0.6474 data_time: 0.0396 memory: 24011 grad_norm: 5.4712 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6799 loss: 0.6799 2022/09/05 19:43:20 - mmengine - INFO - Epoch(train) [63][380/940] lr: 1.0000e-03 eta: 6:27:52 time: 0.6508 data_time: 0.0381 memory: 24011 grad_norm: 5.0778 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7297 loss: 0.7297 2022/09/05 19:43:34 - mmengine - INFO - Epoch(train) [63][400/940] lr: 1.0000e-03 eta: 6:27:39 time: 0.6691 data_time: 0.0412 memory: 24011 grad_norm: 5.2329 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7070 loss: 0.7070 2022/09/05 19:43:46 - mmengine - INFO - Epoch(train) [63][420/940] lr: 1.0000e-03 eta: 6:27:26 time: 0.6415 data_time: 0.0492 memory: 24011 grad_norm: 5.0858 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6740 loss: 0.6740 2022/09/05 19:44:00 - mmengine - INFO - Epoch(train) [63][440/940] lr: 1.0000e-03 eta: 6:27:13 time: 0.6711 data_time: 0.0450 memory: 24011 grad_norm: 5.1436 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6002 loss: 0.6002 2022/09/05 19:44:13 - mmengine - INFO - Epoch(train) [63][460/940] lr: 1.0000e-03 eta: 6:26:59 time: 0.6500 data_time: 0.0473 memory: 24011 grad_norm: 4.9904 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6331 loss: 0.6331 2022/09/05 19:44:26 - mmengine - INFO - Epoch(train) [63][480/940] lr: 1.0000e-03 eta: 6:26:46 time: 0.6745 data_time: 0.0406 memory: 24011 grad_norm: 5.1030 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8121 loss: 0.8121 2022/09/05 19:44:41 - mmengine - INFO - Epoch(train) [63][500/940] lr: 1.0000e-03 eta: 6:26:34 time: 0.7058 data_time: 0.0379 memory: 24011 grad_norm: 5.1015 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5976 loss: 0.5976 2022/09/05 19:44:53 - mmengine - INFO - Epoch(train) [63][520/940] lr: 1.0000e-03 eta: 6:26:20 time: 0.6281 data_time: 0.0407 memory: 24011 grad_norm: 5.0651 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6460 loss: 0.6460 2022/09/05 19:45:05 - mmengine - INFO - Epoch(train) [63][540/940] lr: 1.0000e-03 eta: 6:26:06 time: 0.5947 data_time: 0.0395 memory: 24011 grad_norm: 5.3479 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.6083 loss: 0.6083 2022/09/05 19:45:18 - mmengine - INFO - Epoch(train) [63][560/940] lr: 1.0000e-03 eta: 6:25:53 time: 0.6671 data_time: 0.0576 memory: 24011 grad_norm: 5.2170 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6481 loss: 0.6481 2022/09/05 19:45:30 - mmengine - INFO - Epoch(train) [63][580/940] lr: 1.0000e-03 eta: 6:25:39 time: 0.5872 data_time: 0.0413 memory: 24011 grad_norm: 5.1054 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6717 loss: 0.6717 2022/09/05 19:45:44 - mmengine - INFO - Epoch(train) [63][600/940] lr: 1.0000e-03 eta: 6:25:26 time: 0.6911 data_time: 0.0384 memory: 24011 grad_norm: 5.1171 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5851 loss: 0.5851 2022/09/05 19:45:57 - mmengine - INFO - Epoch(train) [63][620/940] lr: 1.0000e-03 eta: 6:25:13 time: 0.6598 data_time: 0.0422 memory: 24011 grad_norm: 4.9708 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5601 loss: 0.5601 2022/09/05 19:46:10 - mmengine - INFO - Epoch(train) [63][640/940] lr: 1.0000e-03 eta: 6:25:00 time: 0.6226 data_time: 0.0395 memory: 24011 grad_norm: 5.1992 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5603 loss: 0.5603 2022/09/05 19:46:22 - mmengine - INFO - Epoch(train) [63][660/940] lr: 1.0000e-03 eta: 6:24:46 time: 0.6415 data_time: 0.0427 memory: 24011 grad_norm: 4.9906 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6217 loss: 0.6217 2022/09/05 19:46:36 - mmengine - INFO - Epoch(train) [63][680/940] lr: 1.0000e-03 eta: 6:24:33 time: 0.6670 data_time: 0.0429 memory: 24011 grad_norm: 5.2793 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.7124 loss: 0.7124 2022/09/05 19:46:49 - mmengine - INFO - Epoch(train) [63][700/940] lr: 1.0000e-03 eta: 6:24:20 time: 0.6456 data_time: 0.0428 memory: 24011 grad_norm: 5.1246 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6905 loss: 0.6905 2022/09/05 19:47:02 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:47:02 - mmengine - INFO - Epoch(train) [63][720/940] lr: 1.0000e-03 eta: 6:24:07 time: 0.6766 data_time: 0.0507 memory: 24011 grad_norm: 5.4301 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6889 loss: 0.6889 2022/09/05 19:47:15 - mmengine - INFO - Epoch(train) [63][740/940] lr: 1.0000e-03 eta: 6:23:53 time: 0.6343 data_time: 0.0446 memory: 24011 grad_norm: 5.2869 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6228 loss: 0.6228 2022/09/05 19:47:29 - mmengine - INFO - Epoch(train) [63][760/940] lr: 1.0000e-03 eta: 6:23:41 time: 0.6940 data_time: 0.0443 memory: 24011 grad_norm: 5.1589 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6692 loss: 0.6692 2022/09/05 19:47:42 - mmengine - INFO - Epoch(train) [63][780/940] lr: 1.0000e-03 eta: 6:23:27 time: 0.6491 data_time: 0.0469 memory: 24011 grad_norm: 5.1060 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6339 loss: 0.6339 2022/09/05 19:47:54 - mmengine - INFO - Epoch(train) [63][800/940] lr: 1.0000e-03 eta: 6:23:14 time: 0.6305 data_time: 0.0407 memory: 24011 grad_norm: 5.4424 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.5612 loss: 0.5612 2022/09/05 19:48:07 - mmengine - INFO - Epoch(train) [63][820/940] lr: 1.0000e-03 eta: 6:23:00 time: 0.6206 data_time: 0.0441 memory: 24011 grad_norm: 5.4460 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5591 loss: 0.5591 2022/09/05 19:48:20 - mmengine - INFO - Epoch(train) [63][840/940] lr: 1.0000e-03 eta: 6:22:47 time: 0.6395 data_time: 0.0393 memory: 24011 grad_norm: 5.0388 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6531 loss: 0.6531 2022/09/05 19:48:33 - mmengine - INFO - Epoch(train) [63][860/940] lr: 1.0000e-03 eta: 6:22:34 time: 0.6439 data_time: 0.0343 memory: 24011 grad_norm: 5.1909 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6743 loss: 0.6743 2022/09/05 19:48:45 - mmengine - INFO - Epoch(train) [63][880/940] lr: 1.0000e-03 eta: 6:22:20 time: 0.6447 data_time: 0.0434 memory: 24011 grad_norm: 5.3205 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5931 loss: 0.5931 2022/09/05 19:48:58 - mmengine - INFO - Epoch(train) [63][900/940] lr: 1.0000e-03 eta: 6:22:07 time: 0.6270 data_time: 0.0395 memory: 24011 grad_norm: 5.2776 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5055 loss: 0.5055 2022/09/05 19:49:11 - mmengine - INFO - Epoch(train) [63][920/940] lr: 1.0000e-03 eta: 6:21:54 time: 0.6616 data_time: 0.0419 memory: 24011 grad_norm: 5.1760 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5753 loss: 0.5753 2022/09/05 19:49:22 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:49:22 - mmengine - INFO - Epoch(train) [63][940/940] lr: 1.0000e-03 eta: 6:21:39 time: 0.5597 data_time: 0.0310 memory: 24011 grad_norm: 5.2020 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.6021 loss: 0.6021 2022/09/05 19:49:22 - mmengine - INFO - Saving checkpoint at 63 epochs 2022/09/05 19:49:42 - mmengine - INFO - Epoch(val) [63][20/78] eta: 0:00:42 time: 0.7377 data_time: 0.5827 memory: 3625 2022/09/05 19:49:52 - mmengine - INFO - Epoch(val) [63][40/78] eta: 0:00:17 time: 0.4559 data_time: 0.3013 memory: 3625 2022/09/05 19:50:04 - mmengine - INFO - Epoch(val) [63][60/78] eta: 0:00:11 time: 0.6270 data_time: 0.4710 memory: 3625 2022/09/05 19:50:13 - mmengine - INFO - Epoch(val) [63][78/78] acc/top1: 0.7381 acc/top5: 0.9077 acc/mean1: 0.7379 2022/09/05 19:50:31 - mmengine - INFO - Epoch(train) [64][20/940] lr: 1.0000e-03 eta: 6:21:29 time: 0.9044 data_time: 0.2677 memory: 24011 grad_norm: 4.9331 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.6995 loss: 0.6995 2022/09/05 19:50:44 - mmengine - INFO - Epoch(train) [64][40/940] lr: 1.0000e-03 eta: 6:21:15 time: 0.6376 data_time: 0.0415 memory: 24011 grad_norm: 5.2683 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5633 loss: 0.5633 2022/09/05 19:50:58 - mmengine - INFO - Epoch(train) [64][60/940] lr: 1.0000e-03 eta: 6:21:03 time: 0.7290 data_time: 0.0838 memory: 24011 grad_norm: 5.1518 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6108 loss: 0.6108 2022/09/05 19:51:11 - mmengine - INFO - Epoch(train) [64][80/940] lr: 1.0000e-03 eta: 6:20:50 time: 0.6425 data_time: 0.0305 memory: 24011 grad_norm: 5.0798 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6901 loss: 0.6901 2022/09/05 19:51:25 - mmengine - INFO - Epoch(train) [64][100/940] lr: 1.0000e-03 eta: 6:20:37 time: 0.6889 data_time: 0.0391 memory: 24011 grad_norm: 5.6345 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6542 loss: 0.6542 2022/09/05 19:51:37 - mmengine - INFO - Epoch(train) [64][120/940] lr: 1.0000e-03 eta: 6:20:23 time: 0.5925 data_time: 0.0370 memory: 24011 grad_norm: 5.4585 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6070 loss: 0.6070 2022/09/05 19:51:50 - mmengine - INFO - Epoch(train) [64][140/940] lr: 1.0000e-03 eta: 6:20:10 time: 0.6693 data_time: 0.0360 memory: 24011 grad_norm: 4.9658 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6111 loss: 0.6111 2022/09/05 19:52:02 - mmengine - INFO - Epoch(train) [64][160/940] lr: 1.0000e-03 eta: 6:19:56 time: 0.5992 data_time: 0.0394 memory: 24011 grad_norm: 4.9816 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5468 loss: 0.5468 2022/09/05 19:52:15 - mmengine - INFO - Epoch(train) [64][180/940] lr: 1.0000e-03 eta: 6:19:43 time: 0.6438 data_time: 0.0368 memory: 24011 grad_norm: 5.0864 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6120 loss: 0.6120 2022/09/05 19:52:27 - mmengine - INFO - Epoch(train) [64][200/940] lr: 1.0000e-03 eta: 6:19:29 time: 0.6197 data_time: 0.0615 memory: 24011 grad_norm: 5.0143 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.6245 loss: 0.6245 2022/09/05 19:52:41 - mmengine - INFO - Epoch(train) [64][220/940] lr: 1.0000e-03 eta: 6:19:16 time: 0.6768 data_time: 0.0413 memory: 24011 grad_norm: 4.9732 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6675 loss: 0.6675 2022/09/05 19:52:54 - mmengine - INFO - Epoch(train) [64][240/940] lr: 1.0000e-03 eta: 6:19:03 time: 0.6340 data_time: 0.0382 memory: 24011 grad_norm: 5.0862 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5215 loss: 0.5215 2022/09/05 19:53:06 - mmengine - INFO - Epoch(train) [64][260/940] lr: 1.0000e-03 eta: 6:18:49 time: 0.6300 data_time: 0.0376 memory: 24011 grad_norm: 5.3127 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6607 loss: 0.6607 2022/09/05 19:53:19 - mmengine - INFO - Epoch(train) [64][280/940] lr: 1.0000e-03 eta: 6:18:36 time: 0.6648 data_time: 0.0405 memory: 24011 grad_norm: 5.1568 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6697 loss: 0.6697 2022/09/05 19:53:33 - mmengine - INFO - Epoch(train) [64][300/940] lr: 1.0000e-03 eta: 6:18:23 time: 0.6651 data_time: 0.0450 memory: 24011 grad_norm: 5.0899 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6955 loss: 0.6955 2022/09/05 19:53:46 - mmengine - INFO - Epoch(train) [64][320/940] lr: 1.0000e-03 eta: 6:18:10 time: 0.6577 data_time: 0.0373 memory: 24011 grad_norm: 5.0079 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6649 loss: 0.6649 2022/09/05 19:53:59 - mmengine - INFO - Epoch(train) [64][340/940] lr: 1.0000e-03 eta: 6:17:57 time: 0.6415 data_time: 0.0426 memory: 24011 grad_norm: 5.3233 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7977 loss: 0.7977 2022/09/05 19:54:12 - mmengine - INFO - Epoch(train) [64][360/940] lr: 1.0000e-03 eta: 6:17:43 time: 0.6510 data_time: 0.0403 memory: 24011 grad_norm: 4.9219 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6756 loss: 0.6756 2022/09/05 19:54:24 - mmengine - INFO - Epoch(train) [64][380/940] lr: 1.0000e-03 eta: 6:17:30 time: 0.6233 data_time: 0.0408 memory: 24011 grad_norm: 5.1788 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6541 loss: 0.6541 2022/09/05 19:54:36 - mmengine - INFO - Epoch(train) [64][400/940] lr: 1.0000e-03 eta: 6:17:16 time: 0.6090 data_time: 0.0378 memory: 24011 grad_norm: 5.6731 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6406 loss: 0.6406 2022/09/05 19:54:49 - mmengine - INFO - Epoch(train) [64][420/940] lr: 1.0000e-03 eta: 6:17:03 time: 0.6422 data_time: 0.0403 memory: 24011 grad_norm: 4.8991 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.6647 loss: 0.6647 2022/09/05 19:55:02 - mmengine - INFO - Epoch(train) [64][440/940] lr: 1.0000e-03 eta: 6:16:49 time: 0.6385 data_time: 0.0336 memory: 24011 grad_norm: 4.9980 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5430 loss: 0.5430 2022/09/05 19:55:15 - mmengine - INFO - Epoch(train) [64][460/940] lr: 1.0000e-03 eta: 6:16:36 time: 0.6450 data_time: 0.0448 memory: 24011 grad_norm: 5.5026 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.7034 loss: 0.7034 2022/09/05 19:55:28 - mmengine - INFO - Epoch(train) [64][480/940] lr: 1.0000e-03 eta: 6:16:23 time: 0.6555 data_time: 0.0451 memory: 24011 grad_norm: 4.7514 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7034 loss: 0.7034 2022/09/05 19:55:41 - mmengine - INFO - Epoch(train) [64][500/940] lr: 1.0000e-03 eta: 6:16:10 time: 0.6660 data_time: 0.0446 memory: 24011 grad_norm: 4.9539 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6865 loss: 0.6865 2022/09/05 19:55:55 - mmengine - INFO - Epoch(train) [64][520/940] lr: 1.0000e-03 eta: 6:15:57 time: 0.6767 data_time: 0.0335 memory: 24011 grad_norm: 5.0517 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6237 loss: 0.6237 2022/09/05 19:56:07 - mmengine - INFO - Epoch(train) [64][540/940] lr: 1.0000e-03 eta: 6:15:43 time: 0.6118 data_time: 0.0472 memory: 24011 grad_norm: 5.8386 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6218 loss: 0.6218 2022/09/05 19:56:21 - mmengine - INFO - Epoch(train) [64][560/940] lr: 1.0000e-03 eta: 6:15:30 time: 0.6724 data_time: 0.0344 memory: 24011 grad_norm: 5.5141 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6476 loss: 0.6476 2022/09/05 19:56:34 - mmengine - INFO - Epoch(train) [64][580/940] lr: 1.0000e-03 eta: 6:15:17 time: 0.6436 data_time: 0.0606 memory: 24011 grad_norm: 5.3459 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6392 loss: 0.6392 2022/09/05 19:56:47 - mmengine - INFO - Epoch(train) [64][600/940] lr: 1.0000e-03 eta: 6:15:04 time: 0.6673 data_time: 0.0344 memory: 24011 grad_norm: 4.8216 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5978 loss: 0.5978 2022/09/05 19:57:00 - mmengine - INFO - Epoch(train) [64][620/940] lr: 1.0000e-03 eta: 6:14:50 time: 0.6428 data_time: 0.0382 memory: 24011 grad_norm: 4.9070 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6110 loss: 0.6110 2022/09/05 19:57:13 - mmengine - INFO - Epoch(train) [64][640/940] lr: 1.0000e-03 eta: 6:14:37 time: 0.6791 data_time: 0.0364 memory: 24011 grad_norm: 5.0482 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.6006 loss: 0.6006 2022/09/05 19:57:26 - mmengine - INFO - Epoch(train) [64][660/940] lr: 1.0000e-03 eta: 6:14:24 time: 0.6287 data_time: 0.0490 memory: 24011 grad_norm: 4.9990 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6553 loss: 0.6553 2022/09/05 19:57:40 - mmengine - INFO - Epoch(train) [64][680/940] lr: 1.0000e-03 eta: 6:14:11 time: 0.6891 data_time: 0.0486 memory: 24011 grad_norm: 5.3502 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6532 loss: 0.6532 2022/09/05 19:57:52 - mmengine - INFO - Epoch(train) [64][700/940] lr: 1.0000e-03 eta: 6:13:57 time: 0.6277 data_time: 0.0431 memory: 24011 grad_norm: 5.0451 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6669 loss: 0.6669 2022/09/05 19:58:05 - mmengine - INFO - Epoch(train) [64][720/940] lr: 1.0000e-03 eta: 6:13:44 time: 0.6460 data_time: 0.0438 memory: 24011 grad_norm: 5.1681 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6286 loss: 0.6286 2022/09/05 19:58:19 - mmengine - INFO - Epoch(train) [64][740/940] lr: 1.0000e-03 eta: 6:13:31 time: 0.6673 data_time: 0.0428 memory: 24011 grad_norm: 5.1238 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6883 loss: 0.6883 2022/09/05 19:58:31 - mmengine - INFO - Epoch(train) [64][760/940] lr: 1.0000e-03 eta: 6:13:17 time: 0.6208 data_time: 0.0421 memory: 24011 grad_norm: 5.0779 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.6179 loss: 0.6179 2022/09/05 19:58:45 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 19:58:45 - mmengine - INFO - Epoch(train) [64][780/940] lr: 1.0000e-03 eta: 6:13:05 time: 0.6872 data_time: 0.0435 memory: 24011 grad_norm: 5.2922 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6279 loss: 0.6279 2022/09/05 19:58:57 - mmengine - INFO - Epoch(train) [64][800/940] lr: 1.0000e-03 eta: 6:12:51 time: 0.6192 data_time: 0.0549 memory: 24011 grad_norm: 5.0441 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6103 loss: 0.6103 2022/09/05 19:59:11 - mmengine - INFO - Epoch(train) [64][820/940] lr: 1.0000e-03 eta: 6:12:38 time: 0.6697 data_time: 0.0417 memory: 24011 grad_norm: 4.8639 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6541 loss: 0.6541 2022/09/05 19:59:23 - mmengine - INFO - Epoch(train) [64][840/940] lr: 1.0000e-03 eta: 6:12:24 time: 0.6253 data_time: 0.0515 memory: 24011 grad_norm: 4.8927 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6444 loss: 0.6444 2022/09/05 19:59:36 - mmengine - INFO - Epoch(train) [64][860/940] lr: 1.0000e-03 eta: 6:12:11 time: 0.6562 data_time: 0.0392 memory: 24011 grad_norm: 4.9616 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.7360 loss: 0.7360 2022/09/05 19:59:49 - mmengine - INFO - Epoch(train) [64][880/940] lr: 1.0000e-03 eta: 6:11:58 time: 0.6224 data_time: 0.0468 memory: 24011 grad_norm: 4.9991 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6646 loss: 0.6646 2022/09/05 20:00:02 - mmengine - INFO - Epoch(train) [64][900/940] lr: 1.0000e-03 eta: 6:11:45 time: 0.6688 data_time: 0.0421 memory: 24011 grad_norm: 5.1512 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6020 loss: 0.6020 2022/09/05 20:00:16 - mmengine - INFO - Epoch(train) [64][920/940] lr: 1.0000e-03 eta: 6:11:31 time: 0.6649 data_time: 0.0494 memory: 24011 grad_norm: 4.9881 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7024 loss: 0.7024 2022/09/05 20:00:27 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:00:27 - mmengine - INFO - Epoch(train) [64][940/940] lr: 1.0000e-03 eta: 6:11:17 time: 0.5629 data_time: 0.0345 memory: 24011 grad_norm: 5.5953 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.7155 loss: 0.7155 2022/09/05 20:00:41 - mmengine - INFO - Epoch(val) [64][20/78] eta: 0:00:40 time: 0.7040 data_time: 0.5454 memory: 3625 2022/09/05 20:00:50 - mmengine - INFO - Epoch(val) [64][40/78] eta: 0:00:17 time: 0.4498 data_time: 0.2891 memory: 3625 2022/09/05 20:01:03 - mmengine - INFO - Epoch(val) [64][60/78] eta: 0:00:11 time: 0.6579 data_time: 0.4974 memory: 3625 2022/09/05 20:01:13 - mmengine - INFO - Epoch(val) [64][78/78] acc/top1: 0.7409 acc/top5: 0.9083 acc/mean1: 0.7407 2022/09/05 20:01:31 - mmengine - INFO - Epoch(train) [65][20/940] lr: 1.0000e-03 eta: 6:11:07 time: 0.9056 data_time: 0.2594 memory: 24011 grad_norm: 5.2404 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6130 loss: 0.6130 2022/09/05 20:01:44 - mmengine - INFO - Epoch(train) [65][40/940] lr: 1.0000e-03 eta: 6:10:54 time: 0.6529 data_time: 0.0347 memory: 24011 grad_norm: 5.2447 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.7479 loss: 0.7479 2022/09/05 20:01:57 - mmengine - INFO - Epoch(train) [65][60/940] lr: 1.0000e-03 eta: 6:10:40 time: 0.6311 data_time: 0.0390 memory: 24011 grad_norm: 4.9460 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5477 loss: 0.5477 2022/09/05 20:02:10 - mmengine - INFO - Epoch(train) [65][80/940] lr: 1.0000e-03 eta: 6:10:27 time: 0.6502 data_time: 0.0397 memory: 24011 grad_norm: 5.5146 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5796 loss: 0.5796 2022/09/05 20:02:24 - mmengine - INFO - Epoch(train) [65][100/940] lr: 1.0000e-03 eta: 6:10:14 time: 0.7200 data_time: 0.0428 memory: 24011 grad_norm: 5.6955 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6311 loss: 0.6311 2022/09/05 20:02:37 - mmengine - INFO - Epoch(train) [65][120/940] lr: 1.0000e-03 eta: 6:10:01 time: 0.6183 data_time: 0.0346 memory: 24011 grad_norm: 5.7176 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5422 loss: 0.5422 2022/09/05 20:02:50 - mmengine - INFO - Epoch(train) [65][140/940] lr: 1.0000e-03 eta: 6:09:48 time: 0.6478 data_time: 0.0430 memory: 24011 grad_norm: 5.0430 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5939 loss: 0.5939 2022/09/05 20:03:02 - mmengine - INFO - Epoch(train) [65][160/940] lr: 1.0000e-03 eta: 6:09:34 time: 0.6151 data_time: 0.0494 memory: 24011 grad_norm: 4.9369 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6564 loss: 0.6564 2022/09/05 20:03:15 - mmengine - INFO - Epoch(train) [65][180/940] lr: 1.0000e-03 eta: 6:09:21 time: 0.6689 data_time: 0.0921 memory: 24011 grad_norm: 5.1450 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5993 loss: 0.5993 2022/09/05 20:03:29 - mmengine - INFO - Epoch(train) [65][200/940] lr: 1.0000e-03 eta: 6:09:08 time: 0.6589 data_time: 0.0426 memory: 24011 grad_norm: 5.2191 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.6141 loss: 0.6141 2022/09/05 20:03:42 - mmengine - INFO - Epoch(train) [65][220/940] lr: 1.0000e-03 eta: 6:08:55 time: 0.6752 data_time: 0.0347 memory: 24011 grad_norm: 5.0449 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6612 loss: 0.6612 2022/09/05 20:03:55 - mmengine - INFO - Epoch(train) [65][240/940] lr: 1.0000e-03 eta: 6:08:41 time: 0.6395 data_time: 0.0335 memory: 24011 grad_norm: 4.9265 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6288 loss: 0.6288 2022/09/05 20:04:08 - mmengine - INFO - Epoch(train) [65][260/940] lr: 1.0000e-03 eta: 6:08:28 time: 0.6435 data_time: 0.0600 memory: 24011 grad_norm: 5.1535 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6383 loss: 0.6383 2022/09/05 20:04:21 - mmengine - INFO - Epoch(train) [65][280/940] lr: 1.0000e-03 eta: 6:08:15 time: 0.6582 data_time: 0.0336 memory: 24011 grad_norm: 5.0928 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6570 loss: 0.6570 2022/09/05 20:04:35 - mmengine - INFO - Epoch(train) [65][300/940] lr: 1.0000e-03 eta: 6:08:02 time: 0.6774 data_time: 0.0392 memory: 24011 grad_norm: 5.1245 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6541 loss: 0.6541 2022/09/05 20:04:47 - mmengine - INFO - Epoch(train) [65][320/940] lr: 1.0000e-03 eta: 6:07:48 time: 0.6079 data_time: 0.0344 memory: 24011 grad_norm: 5.0517 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6509 loss: 0.6509 2022/09/05 20:05:00 - mmengine - INFO - Epoch(train) [65][340/940] lr: 1.0000e-03 eta: 6:07:35 time: 0.6533 data_time: 0.0409 memory: 24011 grad_norm: 4.9310 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6612 loss: 0.6612 2022/09/05 20:05:13 - mmengine - INFO - Epoch(train) [65][360/940] lr: 1.0000e-03 eta: 6:07:22 time: 0.6428 data_time: 0.0361 memory: 24011 grad_norm: 5.1049 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6407 loss: 0.6407 2022/09/05 20:05:26 - mmengine - INFO - Epoch(train) [65][380/940] lr: 1.0000e-03 eta: 6:07:08 time: 0.6470 data_time: 0.0381 memory: 24011 grad_norm: 5.5735 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7187 loss: 0.7187 2022/09/05 20:05:38 - mmengine - INFO - Epoch(train) [65][400/940] lr: 1.0000e-03 eta: 6:06:55 time: 0.6353 data_time: 0.0371 memory: 24011 grad_norm: 4.9001 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5536 loss: 0.5536 2022/09/05 20:05:52 - mmengine - INFO - Epoch(train) [65][420/940] lr: 1.0000e-03 eta: 6:06:42 time: 0.6801 data_time: 0.0385 memory: 24011 grad_norm: 5.2181 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5915 loss: 0.5915 2022/09/05 20:06:04 - mmengine - INFO - Epoch(train) [65][440/940] lr: 1.0000e-03 eta: 6:06:28 time: 0.5913 data_time: 0.0332 memory: 24011 grad_norm: 5.4964 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6352 loss: 0.6352 2022/09/05 20:06:17 - mmengine - INFO - Epoch(train) [65][460/940] lr: 1.0000e-03 eta: 6:06:15 time: 0.6753 data_time: 0.0379 memory: 24011 grad_norm: 4.8891 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6530 loss: 0.6530 2022/09/05 20:06:30 - mmengine - INFO - Epoch(train) [65][480/940] lr: 1.0000e-03 eta: 6:06:02 time: 0.6409 data_time: 0.0363 memory: 24011 grad_norm: 5.2107 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6350 loss: 0.6350 2022/09/05 20:06:43 - mmengine - INFO - Epoch(train) [65][500/940] lr: 1.0000e-03 eta: 6:05:49 time: 0.6671 data_time: 0.0539 memory: 24011 grad_norm: 4.9633 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7090 loss: 0.7090 2022/09/05 20:06:57 - mmengine - INFO - Epoch(train) [65][520/940] lr: 1.0000e-03 eta: 6:05:35 time: 0.6620 data_time: 0.0325 memory: 24011 grad_norm: 5.6793 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.7346 loss: 0.7346 2022/09/05 20:07:10 - mmengine - INFO - Epoch(train) [65][540/940] lr: 1.0000e-03 eta: 6:05:22 time: 0.6499 data_time: 0.0370 memory: 24011 grad_norm: 5.0840 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6776 loss: 0.6776 2022/09/05 20:07:22 - mmengine - INFO - Epoch(train) [65][560/940] lr: 1.0000e-03 eta: 6:05:09 time: 0.6243 data_time: 0.0467 memory: 24011 grad_norm: 5.0614 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6860 loss: 0.6860 2022/09/05 20:07:35 - mmengine - INFO - Epoch(train) [65][580/940] lr: 1.0000e-03 eta: 6:04:55 time: 0.6440 data_time: 0.0379 memory: 24011 grad_norm: 5.3151 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6357 loss: 0.6357 2022/09/05 20:07:48 - mmengine - INFO - Epoch(train) [65][600/940] lr: 1.0000e-03 eta: 6:04:42 time: 0.6376 data_time: 0.0472 memory: 24011 grad_norm: 5.1419 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5766 loss: 0.5766 2022/09/05 20:08:02 - mmengine - INFO - Epoch(train) [65][620/940] lr: 1.0000e-03 eta: 6:04:29 time: 0.6863 data_time: 0.0496 memory: 24011 grad_norm: 5.3392 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6724 loss: 0.6724 2022/09/05 20:08:14 - mmengine - INFO - Epoch(train) [65][640/940] lr: 1.0000e-03 eta: 6:04:16 time: 0.6341 data_time: 0.0465 memory: 24011 grad_norm: 5.1387 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6470 loss: 0.6470 2022/09/05 20:08:28 - mmengine - INFO - Epoch(train) [65][660/940] lr: 1.0000e-03 eta: 6:04:03 time: 0.6719 data_time: 0.0485 memory: 24011 grad_norm: 5.0632 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6836 loss: 0.6836 2022/09/05 20:08:41 - mmengine - INFO - Epoch(train) [65][680/940] lr: 1.0000e-03 eta: 6:03:50 time: 0.6675 data_time: 0.0450 memory: 24011 grad_norm: 5.6163 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6605 loss: 0.6605 2022/09/05 20:08:54 - mmengine - INFO - Epoch(train) [65][700/940] lr: 1.0000e-03 eta: 6:03:36 time: 0.6277 data_time: 0.0358 memory: 24011 grad_norm: 5.4429 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6544 loss: 0.6544 2022/09/05 20:09:06 - mmengine - INFO - Epoch(train) [65][720/940] lr: 1.0000e-03 eta: 6:03:23 time: 0.6219 data_time: 0.0406 memory: 24011 grad_norm: 5.2240 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6651 loss: 0.6651 2022/09/05 20:09:19 - mmengine - INFO - Epoch(train) [65][740/940] lr: 1.0000e-03 eta: 6:03:09 time: 0.6640 data_time: 0.0335 memory: 24011 grad_norm: 5.3562 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6394 loss: 0.6394 2022/09/05 20:09:32 - mmengine - INFO - Epoch(train) [65][760/940] lr: 1.0000e-03 eta: 6:02:56 time: 0.6511 data_time: 0.0368 memory: 24011 grad_norm: 5.2346 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.6781 loss: 0.6781 2022/09/05 20:09:45 - mmengine - INFO - Epoch(train) [65][780/940] lr: 1.0000e-03 eta: 6:02:43 time: 0.6318 data_time: 0.0433 memory: 24011 grad_norm: 5.3735 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5036 loss: 0.5036 2022/09/05 20:09:58 - mmengine - INFO - Epoch(train) [65][800/940] lr: 1.0000e-03 eta: 6:02:29 time: 0.6543 data_time: 0.0359 memory: 24011 grad_norm: 5.5277 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6912 loss: 0.6912 2022/09/05 20:10:11 - mmengine - INFO - Epoch(train) [65][820/940] lr: 1.0000e-03 eta: 6:02:16 time: 0.6361 data_time: 0.0406 memory: 24011 grad_norm: 5.0616 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6623 loss: 0.6623 2022/09/05 20:10:24 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:10:24 - mmengine - INFO - Epoch(train) [65][840/940] lr: 1.0000e-03 eta: 6:02:03 time: 0.6552 data_time: 0.0493 memory: 24011 grad_norm: 5.3295 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6318 loss: 0.6318 2022/09/05 20:10:37 - mmengine - INFO - Epoch(train) [65][860/940] lr: 1.0000e-03 eta: 6:01:49 time: 0.6313 data_time: 0.0427 memory: 24011 grad_norm: 4.8380 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5789 loss: 0.5789 2022/09/05 20:10:49 - mmengine - INFO - Epoch(train) [65][880/940] lr: 1.0000e-03 eta: 6:01:36 time: 0.6312 data_time: 0.0387 memory: 24011 grad_norm: 5.2787 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6925 loss: 0.6925 2022/09/05 20:11:02 - mmengine - INFO - Epoch(train) [65][900/940] lr: 1.0000e-03 eta: 6:01:23 time: 0.6553 data_time: 0.0411 memory: 24011 grad_norm: 5.2291 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5643 loss: 0.5643 2022/09/05 20:11:15 - mmengine - INFO - Epoch(train) [65][920/940] lr: 1.0000e-03 eta: 6:01:09 time: 0.6432 data_time: 0.0390 memory: 24011 grad_norm: 5.1534 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6832 loss: 0.6832 2022/09/05 20:11:26 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:11:26 - mmengine - INFO - Epoch(train) [65][940/940] lr: 1.0000e-03 eta: 6:00:55 time: 0.5602 data_time: 0.0274 memory: 24011 grad_norm: 5.5655 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.6044 loss: 0.6044 2022/09/05 20:11:40 - mmengine - INFO - Epoch(val) [65][20/78] eta: 0:00:39 time: 0.6849 data_time: 0.5191 memory: 3625 2022/09/05 20:11:49 - mmengine - INFO - Epoch(val) [65][40/78] eta: 0:00:17 time: 0.4631 data_time: 0.3077 memory: 3625 2022/09/05 20:12:02 - mmengine - INFO - Epoch(val) [65][60/78] eta: 0:00:11 time: 0.6456 data_time: 0.4887 memory: 3625 2022/09/05 20:12:13 - mmengine - INFO - Epoch(val) [65][78/78] acc/top1: 0.7394 acc/top5: 0.9074 acc/mean1: 0.7393 2022/09/05 20:12:31 - mmengine - INFO - Epoch(train) [66][20/940] lr: 1.0000e-03 eta: 6:00:44 time: 0.8840 data_time: 0.3165 memory: 24011 grad_norm: 5.6040 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.6120 loss: 0.6120 2022/09/05 20:12:44 - mmengine - INFO - Epoch(train) [66][40/940] lr: 1.0000e-03 eta: 6:00:31 time: 0.6338 data_time: 0.0375 memory: 24011 grad_norm: 5.7368 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6251 loss: 0.6251 2022/09/05 20:12:57 - mmengine - INFO - Epoch(train) [66][60/940] lr: 1.0000e-03 eta: 6:00:18 time: 0.6929 data_time: 0.0457 memory: 24011 grad_norm: 4.8378 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6568 loss: 0.6568 2022/09/05 20:13:11 - mmengine - INFO - Epoch(train) [66][80/940] lr: 1.0000e-03 eta: 6:00:05 time: 0.6691 data_time: 0.0365 memory: 24011 grad_norm: 5.5161 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6397 loss: 0.6397 2022/09/05 20:13:24 - mmengine - INFO - Epoch(train) [66][100/940] lr: 1.0000e-03 eta: 5:59:52 time: 0.6521 data_time: 0.0487 memory: 24011 grad_norm: 5.4594 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6514 loss: 0.6514 2022/09/05 20:13:36 - mmengine - INFO - Epoch(train) [66][120/940] lr: 1.0000e-03 eta: 5:59:38 time: 0.6220 data_time: 0.0309 memory: 24011 grad_norm: 5.3064 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6388 loss: 0.6388 2022/09/05 20:13:50 - mmengine - INFO - Epoch(train) [66][140/940] lr: 1.0000e-03 eta: 5:59:25 time: 0.6717 data_time: 0.0439 memory: 24011 grad_norm: 5.3138 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6708 loss: 0.6708 2022/09/05 20:14:02 - mmengine - INFO - Epoch(train) [66][160/940] lr: 1.0000e-03 eta: 5:59:12 time: 0.6289 data_time: 0.0371 memory: 24011 grad_norm: 5.6836 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6197 loss: 0.6197 2022/09/05 20:14:15 - mmengine - INFO - Epoch(train) [66][180/940] lr: 1.0000e-03 eta: 5:58:58 time: 0.6240 data_time: 0.0401 memory: 24011 grad_norm: 5.6209 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5203 loss: 0.5203 2022/09/05 20:14:28 - mmengine - INFO - Epoch(train) [66][200/940] lr: 1.0000e-03 eta: 5:58:45 time: 0.6407 data_time: 0.0387 memory: 24011 grad_norm: 5.2311 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5318 loss: 0.5318 2022/09/05 20:14:41 - mmengine - INFO - Epoch(train) [66][220/940] lr: 1.0000e-03 eta: 5:58:32 time: 0.6813 data_time: 0.0407 memory: 24011 grad_norm: 5.1171 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6581 loss: 0.6581 2022/09/05 20:14:54 - mmengine - INFO - Epoch(train) [66][240/940] lr: 1.0000e-03 eta: 5:58:19 time: 0.6458 data_time: 0.0663 memory: 24011 grad_norm: 6.1559 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5771 loss: 0.5771 2022/09/05 20:15:07 - mmengine - INFO - Epoch(train) [66][260/940] lr: 1.0000e-03 eta: 5:58:05 time: 0.6435 data_time: 0.0696 memory: 24011 grad_norm: 5.1584 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6078 loss: 0.6078 2022/09/05 20:15:20 - mmengine - INFO - Epoch(train) [66][280/940] lr: 1.0000e-03 eta: 5:57:52 time: 0.6231 data_time: 0.0464 memory: 24011 grad_norm: 5.3592 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6277 loss: 0.6277 2022/09/05 20:15:33 - mmengine - INFO - Epoch(train) [66][300/940] lr: 1.0000e-03 eta: 5:57:39 time: 0.6840 data_time: 0.1318 memory: 24011 grad_norm: 5.3189 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6331 loss: 0.6331 2022/09/05 20:15:46 - mmengine - INFO - Epoch(train) [66][320/940] lr: 1.0000e-03 eta: 5:57:26 time: 0.6269 data_time: 0.0659 memory: 24011 grad_norm: 5.0852 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6013 loss: 0.6013 2022/09/05 20:15:59 - mmengine - INFO - Epoch(train) [66][340/940] lr: 1.0000e-03 eta: 5:57:13 time: 0.6808 data_time: 0.1090 memory: 24011 grad_norm: 5.0316 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7131 loss: 0.7131 2022/09/05 20:16:12 - mmengine - INFO - Epoch(train) [66][360/940] lr: 1.0000e-03 eta: 5:56:59 time: 0.6207 data_time: 0.0343 memory: 24011 grad_norm: 4.9796 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5833 loss: 0.5833 2022/09/05 20:16:25 - mmengine - INFO - Epoch(train) [66][380/940] lr: 1.0000e-03 eta: 5:56:46 time: 0.6652 data_time: 0.0406 memory: 24011 grad_norm: 5.0304 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6779 loss: 0.6779 2022/09/05 20:16:38 - mmengine - INFO - Epoch(train) [66][400/940] lr: 1.0000e-03 eta: 5:56:33 time: 0.6383 data_time: 0.0448 memory: 24011 grad_norm: 5.2072 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6565 loss: 0.6565 2022/09/05 20:16:51 - mmengine - INFO - Epoch(train) [66][420/940] lr: 1.0000e-03 eta: 5:56:19 time: 0.6536 data_time: 0.0415 memory: 24011 grad_norm: 5.2631 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5797 loss: 0.5797 2022/09/05 20:17:03 - mmengine - INFO - Epoch(train) [66][440/940] lr: 1.0000e-03 eta: 5:56:06 time: 0.6123 data_time: 0.0441 memory: 24011 grad_norm: 5.1891 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5878 loss: 0.5878 2022/09/05 20:17:17 - mmengine - INFO - Epoch(train) [66][460/940] lr: 1.0000e-03 eta: 5:55:53 time: 0.6961 data_time: 0.0466 memory: 24011 grad_norm: 4.9619 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6580 loss: 0.6580 2022/09/05 20:17:29 - mmengine - INFO - Epoch(train) [66][480/940] lr: 1.0000e-03 eta: 5:55:39 time: 0.5997 data_time: 0.0419 memory: 24011 grad_norm: 5.4180 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6469 loss: 0.6469 2022/09/05 20:17:43 - mmengine - INFO - Epoch(train) [66][500/940] lr: 1.0000e-03 eta: 5:55:26 time: 0.6657 data_time: 0.0656 memory: 24011 grad_norm: 6.1865 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6695 loss: 0.6695 2022/09/05 20:17:56 - mmengine - INFO - Epoch(train) [66][520/940] lr: 1.0000e-03 eta: 5:55:13 time: 0.6708 data_time: 0.1018 memory: 24011 grad_norm: 5.4726 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6103 loss: 0.6103 2022/09/05 20:18:09 - mmengine - INFO - Epoch(train) [66][540/940] lr: 1.0000e-03 eta: 5:55:00 time: 0.6662 data_time: 0.0931 memory: 24011 grad_norm: 5.1988 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6197 loss: 0.6197 2022/09/05 20:18:23 - mmengine - INFO - Epoch(train) [66][560/940] lr: 1.0000e-03 eta: 5:54:47 time: 0.6729 data_time: 0.0747 memory: 24011 grad_norm: 5.2236 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6091 loss: 0.6091 2022/09/05 20:18:36 - mmengine - INFO - Epoch(train) [66][580/940] lr: 1.0000e-03 eta: 5:54:34 time: 0.6380 data_time: 0.0677 memory: 24011 grad_norm: 4.9655 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6097 loss: 0.6097 2022/09/05 20:18:48 - mmengine - INFO - Epoch(train) [66][600/940] lr: 1.0000e-03 eta: 5:54:20 time: 0.6121 data_time: 0.0397 memory: 24011 grad_norm: 5.3158 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6205 loss: 0.6205 2022/09/05 20:19:01 - mmengine - INFO - Epoch(train) [66][620/940] lr: 1.0000e-03 eta: 5:54:07 time: 0.6508 data_time: 0.0725 memory: 24011 grad_norm: 5.2625 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5966 loss: 0.5966 2022/09/05 20:19:13 - mmengine - INFO - Epoch(train) [66][640/940] lr: 1.0000e-03 eta: 5:53:53 time: 0.6323 data_time: 0.0611 memory: 24011 grad_norm: 5.2721 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5143 loss: 0.5143 2022/09/05 20:19:27 - mmengine - INFO - Epoch(train) [66][660/940] lr: 1.0000e-03 eta: 5:53:40 time: 0.6644 data_time: 0.0888 memory: 24011 grad_norm: 5.2145 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5787 loss: 0.5787 2022/09/05 20:19:40 - mmengine - INFO - Epoch(train) [66][680/940] lr: 1.0000e-03 eta: 5:53:27 time: 0.6435 data_time: 0.0340 memory: 24011 grad_norm: 5.2753 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5775 loss: 0.5775 2022/09/05 20:19:52 - mmengine - INFO - Epoch(train) [66][700/940] lr: 1.0000e-03 eta: 5:53:13 time: 0.6368 data_time: 0.0566 memory: 24011 grad_norm: 5.1662 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6652 loss: 0.6652 2022/09/05 20:20:06 - mmengine - INFO - Epoch(train) [66][720/940] lr: 1.0000e-03 eta: 5:53:00 time: 0.6702 data_time: 0.0928 memory: 24011 grad_norm: 5.6889 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6692 loss: 0.6692 2022/09/05 20:20:20 - mmengine - INFO - Epoch(train) [66][740/940] lr: 1.0000e-03 eta: 5:52:48 time: 0.6991 data_time: 0.1279 memory: 24011 grad_norm: 5.0331 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6147 loss: 0.6147 2022/09/05 20:20:33 - mmengine - INFO - Epoch(train) [66][760/940] lr: 1.0000e-03 eta: 5:52:34 time: 0.6398 data_time: 0.0744 memory: 24011 grad_norm: 5.3294 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6772 loss: 0.6772 2022/09/05 20:20:45 - mmengine - INFO - Epoch(train) [66][780/940] lr: 1.0000e-03 eta: 5:52:21 time: 0.6403 data_time: 0.0649 memory: 24011 grad_norm: 6.5859 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6742 loss: 0.6742 2022/09/05 20:20:58 - mmengine - INFO - Epoch(train) [66][800/940] lr: 1.0000e-03 eta: 5:52:08 time: 0.6286 data_time: 0.0553 memory: 24011 grad_norm: 7.7628 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.5447 loss: 0.5447 2022/09/05 20:21:12 - mmengine - INFO - Epoch(train) [66][820/940] lr: 1.0000e-03 eta: 5:51:55 time: 0.6757 data_time: 0.0979 memory: 24011 grad_norm: 5.6817 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6772 loss: 0.6772 2022/09/05 20:21:25 - mmengine - INFO - Epoch(train) [66][840/940] lr: 1.0000e-03 eta: 5:51:41 time: 0.6597 data_time: 0.0994 memory: 24011 grad_norm: 5.8519 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7357 loss: 0.7357 2022/09/05 20:21:37 - mmengine - INFO - Epoch(train) [66][860/940] lr: 1.0000e-03 eta: 5:51:28 time: 0.6309 data_time: 0.0647 memory: 24011 grad_norm: 5.1240 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6494 loss: 0.6494 2022/09/05 20:21:50 - mmengine - INFO - Epoch(train) [66][880/940] lr: 1.0000e-03 eta: 5:51:15 time: 0.6563 data_time: 0.0825 memory: 24011 grad_norm: 4.9992 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6033 loss: 0.6033 2022/09/05 20:22:04 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:22:04 - mmengine - INFO - Epoch(train) [66][900/940] lr: 1.0000e-03 eta: 5:51:02 time: 0.6905 data_time: 0.1267 memory: 24011 grad_norm: 5.6930 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5381 loss: 0.5381 2022/09/05 20:22:17 - mmengine - INFO - Epoch(train) [66][920/940] lr: 1.0000e-03 eta: 5:50:48 time: 0.6280 data_time: 0.0698 memory: 24011 grad_norm: 5.4377 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5996 loss: 0.5996 2022/09/05 20:22:28 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:22:28 - mmengine - INFO - Epoch(train) [66][940/940] lr: 1.0000e-03 eta: 5:50:34 time: 0.5490 data_time: 0.0468 memory: 24011 grad_norm: 6.5430 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6365 loss: 0.6365 2022/09/05 20:22:28 - mmengine - INFO - Saving checkpoint at 66 epochs 2022/09/05 20:22:47 - mmengine - INFO - Epoch(val) [66][20/78] eta: 0:00:41 time: 0.7090 data_time: 0.5530 memory: 3625 2022/09/05 20:22:56 - mmengine - INFO - Epoch(val) [66][40/78] eta: 0:00:17 time: 0.4598 data_time: 0.3051 memory: 3625 2022/09/05 20:23:09 - mmengine - INFO - Epoch(val) [66][60/78] eta: 0:00:11 time: 0.6381 data_time: 0.4801 memory: 3625 2022/09/05 20:23:18 - mmengine - INFO - Epoch(val) [66][78/78] acc/top1: 0.7404 acc/top5: 0.9074 acc/mean1: 0.7403 2022/09/05 20:23:36 - mmengine - INFO - Epoch(train) [67][20/940] lr: 1.0000e-03 eta: 5:50:24 time: 0.9053 data_time: 0.3198 memory: 24011 grad_norm: 6.5322 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6386 loss: 0.6386 2022/09/05 20:23:50 - mmengine - INFO - Epoch(train) [67][40/940] lr: 1.0000e-03 eta: 5:50:10 time: 0.6678 data_time: 0.0391 memory: 24011 grad_norm: 5.1481 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7200 loss: 0.7200 2022/09/05 20:24:04 - mmengine - INFO - Epoch(train) [67][60/940] lr: 1.0000e-03 eta: 5:49:58 time: 0.7004 data_time: 0.0469 memory: 24011 grad_norm: 5.0901 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6185 loss: 0.6185 2022/09/05 20:24:16 - mmengine - INFO - Epoch(train) [67][80/940] lr: 1.0000e-03 eta: 5:49:44 time: 0.6298 data_time: 0.0371 memory: 24011 grad_norm: 5.0919 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5825 loss: 0.5825 2022/09/05 20:24:30 - mmengine - INFO - Epoch(train) [67][100/940] lr: 1.0000e-03 eta: 5:49:31 time: 0.6869 data_time: 0.0453 memory: 24011 grad_norm: 5.3134 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 0.5377 loss: 0.5377 2022/09/05 20:24:43 - mmengine - INFO - Epoch(train) [67][120/940] lr: 1.0000e-03 eta: 5:49:18 time: 0.6409 data_time: 0.0532 memory: 24011 grad_norm: 7.1039 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6092 loss: 0.6092 2022/09/05 20:24:56 - mmengine - INFO - Epoch(train) [67][140/940] lr: 1.0000e-03 eta: 5:49:05 time: 0.6393 data_time: 0.0506 memory: 24011 grad_norm: 5.1155 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6116 loss: 0.6116 2022/09/05 20:25:09 - mmengine - INFO - Epoch(train) [67][160/940] lr: 1.0000e-03 eta: 5:48:52 time: 0.6611 data_time: 0.0392 memory: 24011 grad_norm: 5.2586 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.6407 loss: 0.6407 2022/09/05 20:25:22 - mmengine - INFO - Epoch(train) [67][180/940] lr: 1.0000e-03 eta: 5:48:38 time: 0.6384 data_time: 0.0427 memory: 24011 grad_norm: 5.1048 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5508 loss: 0.5508 2022/09/05 20:25:34 - mmengine - INFO - Epoch(train) [67][200/940] lr: 1.0000e-03 eta: 5:48:25 time: 0.6104 data_time: 0.0439 memory: 24011 grad_norm: 5.7309 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5677 loss: 0.5677 2022/09/05 20:25:47 - mmengine - INFO - Epoch(train) [67][220/940] lr: 1.0000e-03 eta: 5:48:12 time: 0.6837 data_time: 0.0390 memory: 24011 grad_norm: 6.8249 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6911 loss: 0.6911 2022/09/05 20:26:00 - mmengine - INFO - Epoch(train) [67][240/940] lr: 1.0000e-03 eta: 5:47:58 time: 0.6348 data_time: 0.0381 memory: 24011 grad_norm: 5.2472 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6013 loss: 0.6013 2022/09/05 20:26:12 - mmengine - INFO - Epoch(train) [67][260/940] lr: 1.0000e-03 eta: 5:47:45 time: 0.6179 data_time: 0.0369 memory: 24011 grad_norm: 5.2082 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5898 loss: 0.5898 2022/09/05 20:26:25 - mmengine - INFO - Epoch(train) [67][280/940] lr: 1.0000e-03 eta: 5:47:31 time: 0.6352 data_time: 0.0416 memory: 24011 grad_norm: 5.3827 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.5908 loss: 0.5908 2022/09/05 20:26:39 - mmengine - INFO - Epoch(train) [67][300/940] lr: 1.0000e-03 eta: 5:47:18 time: 0.6730 data_time: 0.0361 memory: 24011 grad_norm: 6.0483 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6562 loss: 0.6562 2022/09/05 20:26:51 - mmengine - INFO - Epoch(train) [67][320/940] lr: 1.0000e-03 eta: 5:47:05 time: 0.6306 data_time: 0.0373 memory: 24011 grad_norm: 5.5996 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6786 loss: 0.6786 2022/09/05 20:27:04 - mmengine - INFO - Epoch(train) [67][340/940] lr: 1.0000e-03 eta: 5:46:52 time: 0.6482 data_time: 0.0365 memory: 24011 grad_norm: 8.3740 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5642 loss: 0.5642 2022/09/05 20:27:18 - mmengine - INFO - Epoch(train) [67][360/940] lr: 1.0000e-03 eta: 5:46:39 time: 0.6853 data_time: 0.0428 memory: 24011 grad_norm: 6.0505 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6955 loss: 0.6955 2022/09/05 20:27:30 - mmengine - INFO - Epoch(train) [67][380/940] lr: 1.0000e-03 eta: 5:46:25 time: 0.6125 data_time: 0.0385 memory: 24011 grad_norm: 5.0110 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6239 loss: 0.6239 2022/09/05 20:27:44 - mmengine - INFO - Epoch(train) [67][400/940] lr: 1.0000e-03 eta: 5:46:12 time: 0.6908 data_time: 0.0487 memory: 24011 grad_norm: 5.6759 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6050 loss: 0.6050 2022/09/05 20:27:57 - mmengine - INFO - Epoch(train) [67][420/940] lr: 1.0000e-03 eta: 5:45:59 time: 0.6265 data_time: 0.0354 memory: 24011 grad_norm: 5.4228 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6761 loss: 0.6761 2022/09/05 20:28:10 - mmengine - INFO - Epoch(train) [67][440/940] lr: 1.0000e-03 eta: 5:45:46 time: 0.6717 data_time: 0.0391 memory: 24011 grad_norm: 5.7173 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7032 loss: 0.7032 2022/09/05 20:28:22 - mmengine - INFO - Epoch(train) [67][460/940] lr: 1.0000e-03 eta: 5:45:32 time: 0.6168 data_time: 0.0471 memory: 24011 grad_norm: 5.6723 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5820 loss: 0.5820 2022/09/05 20:28:35 - mmengine - INFO - Epoch(train) [67][480/940] lr: 1.0000e-03 eta: 5:45:19 time: 0.6481 data_time: 0.0471 memory: 24011 grad_norm: 5.4850 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6471 loss: 0.6471 2022/09/05 20:28:49 - mmengine - INFO - Epoch(train) [67][500/940] lr: 1.0000e-03 eta: 5:45:06 time: 0.6703 data_time: 0.0319 memory: 24011 grad_norm: 5.3761 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.6238 loss: 0.6238 2022/09/05 20:29:02 - mmengine - INFO - Epoch(train) [67][520/940] lr: 1.0000e-03 eta: 5:44:53 time: 0.6549 data_time: 0.0414 memory: 24011 grad_norm: 5.0421 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5445 loss: 0.5445 2022/09/05 20:29:15 - mmengine - INFO - Epoch(train) [67][540/940] lr: 1.0000e-03 eta: 5:44:39 time: 0.6475 data_time: 0.0335 memory: 24011 grad_norm: 5.3062 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5852 loss: 0.5852 2022/09/05 20:29:27 - mmengine - INFO - Epoch(train) [67][560/940] lr: 1.0000e-03 eta: 5:44:26 time: 0.6271 data_time: 0.0373 memory: 24011 grad_norm: 6.2667 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6114 loss: 0.6114 2022/09/05 20:29:39 - mmengine - INFO - Epoch(train) [67][580/940] lr: 1.0000e-03 eta: 5:44:12 time: 0.6038 data_time: 0.0394 memory: 24011 grad_norm: 5.5617 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5877 loss: 0.5877 2022/09/05 20:29:52 - mmengine - INFO - Epoch(train) [67][600/940] lr: 1.0000e-03 eta: 5:43:59 time: 0.6463 data_time: 0.0764 memory: 24011 grad_norm: 5.8232 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6327 loss: 0.6327 2022/09/05 20:30:06 - mmengine - INFO - Epoch(train) [67][620/940] lr: 1.0000e-03 eta: 5:43:46 time: 0.6703 data_time: 0.0545 memory: 24011 grad_norm: 5.6962 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5755 loss: 0.5755 2022/09/05 20:30:18 - mmengine - INFO - Epoch(train) [67][640/940] lr: 1.0000e-03 eta: 5:43:32 time: 0.6293 data_time: 0.0335 memory: 24011 grad_norm: 5.5398 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6517 loss: 0.6517 2022/09/05 20:30:32 - mmengine - INFO - Epoch(train) [67][660/940] lr: 1.0000e-03 eta: 5:43:20 time: 0.6909 data_time: 0.0370 memory: 24011 grad_norm: 5.5778 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.6233 loss: 0.6233 2022/09/05 20:30:45 - mmengine - INFO - Epoch(train) [67][680/940] lr: 1.0000e-03 eta: 5:43:06 time: 0.6567 data_time: 0.0415 memory: 24011 grad_norm: 5.5508 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6466 loss: 0.6466 2022/09/05 20:30:59 - mmengine - INFO - Epoch(train) [67][700/940] lr: 1.0000e-03 eta: 5:42:53 time: 0.6698 data_time: 0.0352 memory: 24011 grad_norm: 5.6043 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5748 loss: 0.5748 2022/09/05 20:31:11 - mmengine - INFO - Epoch(train) [67][720/940] lr: 1.0000e-03 eta: 5:42:40 time: 0.6315 data_time: 0.0429 memory: 24011 grad_norm: 5.0792 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6216 loss: 0.6216 2022/09/05 20:31:24 - mmengine - INFO - Epoch(train) [67][740/940] lr: 1.0000e-03 eta: 5:42:26 time: 0.6134 data_time: 0.0392 memory: 24011 grad_norm: 5.0508 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6479 loss: 0.6479 2022/09/05 20:31:36 - mmengine - INFO - Epoch(train) [67][760/940] lr: 1.0000e-03 eta: 5:42:13 time: 0.6348 data_time: 0.0403 memory: 24011 grad_norm: 5.1870 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5316 loss: 0.5316 2022/09/05 20:31:49 - mmengine - INFO - Epoch(train) [67][780/940] lr: 1.0000e-03 eta: 5:42:00 time: 0.6500 data_time: 0.0374 memory: 24011 grad_norm: 6.4410 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6006 loss: 0.6006 2022/09/05 20:32:03 - mmengine - INFO - Epoch(train) [67][800/940] lr: 1.0000e-03 eta: 5:41:47 time: 0.6633 data_time: 0.0403 memory: 24011 grad_norm: 5.6000 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6403 loss: 0.6403 2022/09/05 20:32:16 - mmengine - INFO - Epoch(train) [67][820/940] lr: 1.0000e-03 eta: 5:41:33 time: 0.6543 data_time: 0.0669 memory: 24011 grad_norm: 5.2823 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5330 loss: 0.5330 2022/09/05 20:32:29 - mmengine - INFO - Epoch(train) [67][840/940] lr: 1.0000e-03 eta: 5:41:20 time: 0.6305 data_time: 0.0591 memory: 24011 grad_norm: 5.3056 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6673 loss: 0.6673 2022/09/05 20:32:42 - mmengine - INFO - Epoch(train) [67][860/940] lr: 1.0000e-03 eta: 5:41:07 time: 0.6901 data_time: 0.0476 memory: 24011 grad_norm: 5.8209 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5218 loss: 0.5218 2022/09/05 20:32:55 - mmengine - INFO - Epoch(train) [67][880/940] lr: 1.0000e-03 eta: 5:40:54 time: 0.6173 data_time: 0.0395 memory: 24011 grad_norm: 5.3953 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6741 loss: 0.6741 2022/09/05 20:33:08 - mmengine - INFO - Epoch(train) [67][900/940] lr: 1.0000e-03 eta: 5:40:40 time: 0.6562 data_time: 0.0325 memory: 24011 grad_norm: 5.2622 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7695 loss: 0.7695 2022/09/05 20:33:20 - mmengine - INFO - Epoch(train) [67][920/940] lr: 1.0000e-03 eta: 5:40:27 time: 0.6177 data_time: 0.0414 memory: 24011 grad_norm: 5.3601 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6582 loss: 0.6582 2022/09/05 20:33:31 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:33:31 - mmengine - INFO - Epoch(train) [67][940/940] lr: 1.0000e-03 eta: 5:40:13 time: 0.5489 data_time: 0.0274 memory: 24011 grad_norm: 5.6372 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.5991 loss: 0.5991 2022/09/05 20:33:45 - mmengine - INFO - Epoch(val) [67][20/78] eta: 0:00:41 time: 0.7161 data_time: 0.5586 memory: 3625 2022/09/05 20:33:55 - mmengine - INFO - Epoch(val) [67][40/78] eta: 0:00:17 time: 0.4558 data_time: 0.2996 memory: 3625 2022/09/05 20:34:08 - mmengine - INFO - Epoch(val) [67][60/78] eta: 0:00:12 time: 0.6730 data_time: 0.5126 memory: 3625 2022/09/05 20:34:18 - mmengine - INFO - Epoch(val) [67][78/78] acc/top1: 0.7390 acc/top5: 0.9080 acc/mean1: 0.7389 2022/09/05 20:34:36 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:34:36 - mmengine - INFO - Epoch(train) [68][20/940] lr: 1.0000e-03 eta: 5:40:02 time: 0.9107 data_time: 0.3109 memory: 24011 grad_norm: 5.2855 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7132 loss: 0.7132 2022/09/05 20:34:49 - mmengine - INFO - Epoch(train) [68][40/940] lr: 1.0000e-03 eta: 5:39:49 time: 0.6584 data_time: 0.0815 memory: 24011 grad_norm: 5.2656 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6036 loss: 0.6036 2022/09/05 20:35:04 - mmengine - INFO - Epoch(train) [68][60/940] lr: 1.0000e-03 eta: 5:39:36 time: 0.7102 data_time: 0.1435 memory: 24011 grad_norm: 5.5878 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 0.6399 loss: 0.6399 2022/09/05 20:35:16 - mmengine - INFO - Epoch(train) [68][80/940] lr: 1.0000e-03 eta: 5:39:23 time: 0.6205 data_time: 0.0351 memory: 24011 grad_norm: 6.2044 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6280 loss: 0.6280 2022/09/05 20:35:28 - mmengine - INFO - Epoch(train) [68][100/940] lr: 1.0000e-03 eta: 5:39:09 time: 0.6173 data_time: 0.0512 memory: 24011 grad_norm: 5.3601 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5747 loss: 0.5747 2022/09/05 20:35:42 - mmengine - INFO - Epoch(train) [68][120/940] lr: 1.0000e-03 eta: 5:38:56 time: 0.6778 data_time: 0.1038 memory: 24011 grad_norm: 5.1814 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5129 loss: 0.5129 2022/09/05 20:35:55 - mmengine - INFO - Epoch(train) [68][140/940] lr: 1.0000e-03 eta: 5:38:43 time: 0.6687 data_time: 0.1024 memory: 24011 grad_norm: 5.9079 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6271 loss: 0.6271 2022/09/05 20:36:08 - mmengine - INFO - Epoch(train) [68][160/940] lr: 1.0000e-03 eta: 5:38:30 time: 0.6573 data_time: 0.0894 memory: 24011 grad_norm: 6.5497 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6569 loss: 0.6569 2022/09/05 20:36:22 - mmengine - INFO - Epoch(train) [68][180/940] lr: 1.0000e-03 eta: 5:38:17 time: 0.6818 data_time: 0.1085 memory: 24011 grad_norm: 5.2375 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.6395 loss: 0.6395 2022/09/05 20:36:35 - mmengine - INFO - Epoch(train) [68][200/940] lr: 1.0000e-03 eta: 5:38:03 time: 0.6402 data_time: 0.0773 memory: 24011 grad_norm: 5.3170 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.6224 loss: 0.6224 2022/09/05 20:36:48 - mmengine - INFO - Epoch(train) [68][220/940] lr: 1.0000e-03 eta: 5:37:50 time: 0.6464 data_time: 0.0662 memory: 24011 grad_norm: 5.5998 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.5732 loss: 0.5732 2022/09/05 20:37:00 - mmengine - INFO - Epoch(train) [68][240/940] lr: 1.0000e-03 eta: 5:37:36 time: 0.5973 data_time: 0.0317 memory: 24011 grad_norm: 5.1393 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5984 loss: 0.5984 2022/09/05 20:37:12 - mmengine - INFO - Epoch(train) [68][260/940] lr: 1.0000e-03 eta: 5:37:23 time: 0.6260 data_time: 0.0571 memory: 24011 grad_norm: 5.3831 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5533 loss: 0.5533 2022/09/05 20:37:25 - mmengine - INFO - Epoch(train) [68][280/940] lr: 1.0000e-03 eta: 5:37:10 time: 0.6416 data_time: 0.0819 memory: 24011 grad_norm: 5.4898 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5596 loss: 0.5596 2022/09/05 20:37:39 - mmengine - INFO - Epoch(train) [68][300/940] lr: 1.0000e-03 eta: 5:36:57 time: 0.6752 data_time: 0.0999 memory: 24011 grad_norm: 5.3556 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.7233 loss: 0.7233 2022/09/05 20:37:51 - mmengine - INFO - Epoch(train) [68][320/940] lr: 1.0000e-03 eta: 5:36:43 time: 0.5974 data_time: 0.0359 memory: 24011 grad_norm: 5.9537 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5365 loss: 0.5365 2022/09/05 20:38:04 - mmengine - INFO - Epoch(train) [68][340/940] lr: 1.0000e-03 eta: 5:36:30 time: 0.6611 data_time: 0.0360 memory: 24011 grad_norm: 5.2712 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6363 loss: 0.6363 2022/09/05 20:38:17 - mmengine - INFO - Epoch(train) [68][360/940] lr: 1.0000e-03 eta: 5:36:17 time: 0.6574 data_time: 0.0353 memory: 24011 grad_norm: 5.2928 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5914 loss: 0.5914 2022/09/05 20:38:31 - mmengine - INFO - Epoch(train) [68][380/940] lr: 1.0000e-03 eta: 5:36:04 time: 0.6837 data_time: 0.0371 memory: 24011 grad_norm: 5.2920 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5284 loss: 0.5284 2022/09/05 20:38:44 - mmengine - INFO - Epoch(train) [68][400/940] lr: 1.0000e-03 eta: 5:35:50 time: 0.6444 data_time: 0.0386 memory: 24011 grad_norm: 5.4422 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6421 loss: 0.6421 2022/09/05 20:38:57 - mmengine - INFO - Epoch(train) [68][420/940] lr: 1.0000e-03 eta: 5:35:37 time: 0.6684 data_time: 0.0381 memory: 24011 grad_norm: 5.1087 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6418 loss: 0.6418 2022/09/05 20:39:10 - mmengine - INFO - Epoch(train) [68][440/940] lr: 1.0000e-03 eta: 5:35:24 time: 0.6270 data_time: 0.0373 memory: 24011 grad_norm: 5.2067 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5785 loss: 0.5785 2022/09/05 20:39:23 - mmengine - INFO - Epoch(train) [68][460/940] lr: 1.0000e-03 eta: 5:35:11 time: 0.6675 data_time: 0.0602 memory: 24011 grad_norm: 5.1719 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5711 loss: 0.5711 2022/09/05 20:39:35 - mmengine - INFO - Epoch(train) [68][480/940] lr: 1.0000e-03 eta: 5:34:57 time: 0.6105 data_time: 0.0368 memory: 24011 grad_norm: 6.4628 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5784 loss: 0.5784 2022/09/05 20:39:49 - mmengine - INFO - Epoch(train) [68][500/940] lr: 1.0000e-03 eta: 5:34:44 time: 0.6795 data_time: 0.0353 memory: 24011 grad_norm: 5.2231 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7147 loss: 0.7147 2022/09/05 20:40:01 - mmengine - INFO - Epoch(train) [68][520/940] lr: 1.0000e-03 eta: 5:34:31 time: 0.6092 data_time: 0.0449 memory: 24011 grad_norm: 5.7098 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5552 loss: 0.5552 2022/09/05 20:40:13 - mmengine - INFO - Epoch(train) [68][540/940] lr: 1.0000e-03 eta: 5:34:17 time: 0.6149 data_time: 0.0424 memory: 24011 grad_norm: 4.9487 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5804 loss: 0.5804 2022/09/05 20:40:26 - mmengine - INFO - Epoch(train) [68][560/940] lr: 1.0000e-03 eta: 5:34:04 time: 0.6397 data_time: 0.0418 memory: 24011 grad_norm: 5.2711 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5888 loss: 0.5888 2022/09/05 20:40:39 - mmengine - INFO - Epoch(train) [68][580/940] lr: 1.0000e-03 eta: 5:33:50 time: 0.6547 data_time: 0.0400 memory: 24011 grad_norm: 5.6790 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5755 loss: 0.5755 2022/09/05 20:40:53 - mmengine - INFO - Epoch(train) [68][600/940] lr: 1.0000e-03 eta: 5:33:38 time: 0.6859 data_time: 0.0567 memory: 24011 grad_norm: 5.8705 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5714 loss: 0.5714 2022/09/05 20:41:05 - mmengine - INFO - Epoch(train) [68][620/940] lr: 1.0000e-03 eta: 5:33:24 time: 0.6089 data_time: 0.0400 memory: 24011 grad_norm: 5.8601 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5696 loss: 0.5696 2022/09/05 20:41:19 - mmengine - INFO - Epoch(train) [68][640/940] lr: 1.0000e-03 eta: 5:33:11 time: 0.6742 data_time: 0.0390 memory: 24011 grad_norm: 5.4407 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5612 loss: 0.5612 2022/09/05 20:41:32 - mmengine - INFO - Epoch(train) [68][660/940] lr: 1.0000e-03 eta: 5:32:58 time: 0.6689 data_time: 0.0418 memory: 24011 grad_norm: 5.2072 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6359 loss: 0.6359 2022/09/05 20:41:45 - mmengine - INFO - Epoch(train) [68][680/940] lr: 1.0000e-03 eta: 5:32:45 time: 0.6455 data_time: 0.0464 memory: 24011 grad_norm: 5.4993 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.7623 loss: 0.7623 2022/09/05 20:41:58 - mmengine - INFO - Epoch(train) [68][700/940] lr: 1.0000e-03 eta: 5:32:32 time: 0.6690 data_time: 0.0402 memory: 24011 grad_norm: 4.8771 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6044 loss: 0.6044 2022/09/05 20:42:11 - mmengine - INFO - Epoch(train) [68][720/940] lr: 1.0000e-03 eta: 5:32:18 time: 0.6367 data_time: 0.0402 memory: 24011 grad_norm: 6.1620 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7118 loss: 0.7118 2022/09/05 20:42:24 - mmengine - INFO - Epoch(train) [68][740/940] lr: 1.0000e-03 eta: 5:32:05 time: 0.6436 data_time: 0.0400 memory: 24011 grad_norm: 6.1741 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6347 loss: 0.6347 2022/09/05 20:42:36 - mmengine - INFO - Epoch(train) [68][760/940] lr: 1.0000e-03 eta: 5:31:51 time: 0.6295 data_time: 0.0453 memory: 24011 grad_norm: 4.8618 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.7189 loss: 0.7189 2022/09/05 20:42:50 - mmengine - INFO - Epoch(train) [68][780/940] lr: 1.0000e-03 eta: 5:31:38 time: 0.6783 data_time: 0.0343 memory: 24011 grad_norm: 5.1053 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6182 loss: 0.6182 2022/09/05 20:43:03 - mmengine - INFO - Epoch(train) [68][800/940] lr: 1.0000e-03 eta: 5:31:25 time: 0.6607 data_time: 0.0408 memory: 24011 grad_norm: 5.0038 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6268 loss: 0.6268 2022/09/05 20:43:16 - mmengine - INFO - Epoch(train) [68][820/940] lr: 1.0000e-03 eta: 5:31:12 time: 0.6285 data_time: 0.0406 memory: 24011 grad_norm: 5.0660 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.7226 loss: 0.7226 2022/09/05 20:43:29 - mmengine - INFO - Epoch(train) [68][840/940] lr: 1.0000e-03 eta: 5:30:59 time: 0.6442 data_time: 0.0420 memory: 24011 grad_norm: 5.1560 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6078 loss: 0.6078 2022/09/05 20:43:42 - mmengine - INFO - Epoch(train) [68][860/940] lr: 1.0000e-03 eta: 5:30:45 time: 0.6531 data_time: 0.0354 memory: 24011 grad_norm: 5.3574 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5952 loss: 0.5952 2022/09/05 20:43:55 - mmengine - INFO - Epoch(train) [68][880/940] lr: 1.0000e-03 eta: 5:30:32 time: 0.6604 data_time: 0.0466 memory: 24011 grad_norm: 5.4095 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5551 loss: 0.5551 2022/09/05 20:44:08 - mmengine - INFO - Epoch(train) [68][900/940] lr: 1.0000e-03 eta: 5:30:19 time: 0.6651 data_time: 0.0581 memory: 24011 grad_norm: 5.1617 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.6477 loss: 0.6477 2022/09/05 20:44:21 - mmengine - INFO - Epoch(train) [68][920/940] lr: 1.0000e-03 eta: 5:30:06 time: 0.6218 data_time: 0.0455 memory: 24011 grad_norm: 5.3327 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6776 loss: 0.6776 2022/09/05 20:44:32 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:44:32 - mmengine - INFO - Epoch(train) [68][940/940] lr: 1.0000e-03 eta: 5:29:52 time: 0.5528 data_time: 0.0255 memory: 24011 grad_norm: 7.0747 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5639 loss: 0.5639 2022/09/05 20:44:46 - mmengine - INFO - Epoch(val) [68][20/78] eta: 0:00:40 time: 0.6981 data_time: 0.5415 memory: 3625 2022/09/05 20:44:55 - mmengine - INFO - Epoch(val) [68][40/78] eta: 0:00:18 time: 0.4751 data_time: 0.3179 memory: 3625 2022/09/05 20:45:08 - mmengine - INFO - Epoch(val) [68][60/78] eta: 0:00:11 time: 0.6477 data_time: 0.4899 memory: 3625 2022/09/05 20:45:19 - mmengine - INFO - Epoch(val) [68][78/78] acc/top1: 0.7386 acc/top5: 0.9070 acc/mean1: 0.7385 2022/09/05 20:45:37 - mmengine - INFO - Epoch(train) [69][20/940] lr: 1.0000e-03 eta: 5:29:41 time: 0.9320 data_time: 0.2497 memory: 24011 grad_norm: 7.9802 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6548 loss: 0.6548 2022/09/05 20:45:49 - mmengine - INFO - Epoch(train) [69][40/940] lr: 1.0000e-03 eta: 5:29:27 time: 0.6030 data_time: 0.0338 memory: 24011 grad_norm: 5.2211 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6504 loss: 0.6504 2022/09/05 20:46:02 - mmengine - INFO - Epoch(train) [69][60/940] lr: 1.0000e-03 eta: 5:29:14 time: 0.6334 data_time: 0.0395 memory: 24011 grad_norm: 5.8078 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6358 loss: 0.6358 2022/09/05 20:46:15 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:46:15 - mmengine - INFO - Epoch(train) [69][80/940] lr: 1.0000e-03 eta: 5:29:01 time: 0.6482 data_time: 0.0731 memory: 24011 grad_norm: 5.1736 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6252 loss: 0.6252 2022/09/05 20:46:30 - mmengine - INFO - Epoch(train) [69][100/940] lr: 1.0000e-03 eta: 5:28:48 time: 0.7194 data_time: 0.0789 memory: 24011 grad_norm: 5.8424 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5986 loss: 0.5986 2022/09/05 20:46:43 - mmengine - INFO - Epoch(train) [69][120/940] lr: 1.0000e-03 eta: 5:28:35 time: 0.6595 data_time: 0.0349 memory: 24011 grad_norm: 4.9760 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5624 loss: 0.5624 2022/09/05 20:46:57 - mmengine - INFO - Epoch(train) [69][140/940] lr: 1.0000e-03 eta: 5:28:22 time: 0.6885 data_time: 0.0358 memory: 24011 grad_norm: 6.4941 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6057 loss: 0.6057 2022/09/05 20:47:09 - mmengine - INFO - Epoch(train) [69][160/940] lr: 1.0000e-03 eta: 5:28:08 time: 0.5997 data_time: 0.0398 memory: 24011 grad_norm: 5.7125 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5943 loss: 0.5943 2022/09/05 20:47:21 - mmengine - INFO - Epoch(train) [69][180/940] lr: 1.0000e-03 eta: 5:27:55 time: 0.6467 data_time: 0.0359 memory: 24011 grad_norm: 5.0712 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6164 loss: 0.6164 2022/09/05 20:47:34 - mmengine - INFO - Epoch(train) [69][200/940] lr: 1.0000e-03 eta: 5:27:42 time: 0.6352 data_time: 0.0380 memory: 24011 grad_norm: 5.1784 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5885 loss: 0.5885 2022/09/05 20:47:48 - mmengine - INFO - Epoch(train) [69][220/940] lr: 1.0000e-03 eta: 5:27:29 time: 0.6995 data_time: 0.0463 memory: 24011 grad_norm: 5.1608 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6641 loss: 0.6641 2022/09/05 20:48:01 - mmengine - INFO - Epoch(train) [69][240/940] lr: 1.0000e-03 eta: 5:27:16 time: 0.6487 data_time: 0.0367 memory: 24011 grad_norm: 4.9345 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5907 loss: 0.5907 2022/09/05 20:48:15 - mmengine - INFO - Epoch(train) [69][260/940] lr: 1.0000e-03 eta: 5:27:03 time: 0.6735 data_time: 0.0335 memory: 24011 grad_norm: 5.4644 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6020 loss: 0.6020 2022/09/05 20:48:27 - mmengine - INFO - Epoch(train) [69][280/940] lr: 1.0000e-03 eta: 5:26:49 time: 0.6075 data_time: 0.0377 memory: 24011 grad_norm: 5.8712 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7344 loss: 0.7344 2022/09/05 20:48:41 - mmengine - INFO - Epoch(train) [69][300/940] lr: 1.0000e-03 eta: 5:26:36 time: 0.6960 data_time: 0.0445 memory: 24011 grad_norm: 5.0162 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6145 loss: 0.6145 2022/09/05 20:48:54 - mmengine - INFO - Epoch(train) [69][320/940] lr: 1.0000e-03 eta: 5:26:23 time: 0.6414 data_time: 0.0409 memory: 24011 grad_norm: 5.0578 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6047 loss: 0.6047 2022/09/05 20:49:06 - mmengine - INFO - Epoch(train) [69][340/940] lr: 1.0000e-03 eta: 5:26:10 time: 0.6379 data_time: 0.0464 memory: 24011 grad_norm: 6.2624 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6947 loss: 0.6947 2022/09/05 20:49:19 - mmengine - INFO - Epoch(train) [69][360/940] lr: 1.0000e-03 eta: 5:25:56 time: 0.6388 data_time: 0.0405 memory: 24011 grad_norm: 5.2948 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.5926 loss: 0.5926 2022/09/05 20:49:32 - mmengine - INFO - Epoch(train) [69][380/940] lr: 1.0000e-03 eta: 5:25:43 time: 0.6336 data_time: 0.0450 memory: 24011 grad_norm: 5.2136 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.5889 loss: 0.5889 2022/09/05 20:49:44 - mmengine - INFO - Epoch(train) [69][400/940] lr: 1.0000e-03 eta: 5:25:29 time: 0.5931 data_time: 0.0458 memory: 24011 grad_norm: 5.1111 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6039 loss: 0.6039 2022/09/05 20:49:57 - mmengine - INFO - Epoch(train) [69][420/940] lr: 1.0000e-03 eta: 5:25:16 time: 0.6711 data_time: 0.0434 memory: 24011 grad_norm: 5.6154 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6252 loss: 0.6252 2022/09/05 20:50:10 - mmengine - INFO - Epoch(train) [69][440/940] lr: 1.0000e-03 eta: 5:25:03 time: 0.6320 data_time: 0.0428 memory: 24011 grad_norm: 5.1058 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6350 loss: 0.6350 2022/09/05 20:50:22 - mmengine - INFO - Epoch(train) [69][460/940] lr: 1.0000e-03 eta: 5:24:49 time: 0.6276 data_time: 0.0385 memory: 24011 grad_norm: 4.9671 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6286 loss: 0.6286 2022/09/05 20:50:36 - mmengine - INFO - Epoch(train) [69][480/940] lr: 1.0000e-03 eta: 5:24:36 time: 0.7027 data_time: 0.0458 memory: 24011 grad_norm: 5.0290 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6238 loss: 0.6238 2022/09/05 20:50:49 - mmengine - INFO - Epoch(train) [69][500/940] lr: 1.0000e-03 eta: 5:24:23 time: 0.6421 data_time: 0.0393 memory: 24011 grad_norm: 5.5685 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5885 loss: 0.5885 2022/09/05 20:51:01 - mmengine - INFO - Epoch(train) [69][520/940] lr: 1.0000e-03 eta: 5:24:09 time: 0.6092 data_time: 0.0461 memory: 24011 grad_norm: 5.3728 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6488 loss: 0.6488 2022/09/05 20:51:15 - mmengine - INFO - Epoch(train) [69][540/940] lr: 1.0000e-03 eta: 5:23:56 time: 0.6664 data_time: 0.0369 memory: 24011 grad_norm: 5.0995 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.5783 loss: 0.5783 2022/09/05 20:51:28 - mmengine - INFO - Epoch(train) [69][560/940] lr: 1.0000e-03 eta: 5:23:43 time: 0.6434 data_time: 0.0522 memory: 24011 grad_norm: 5.2567 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6016 loss: 0.6016 2022/09/05 20:51:41 - mmengine - INFO - Epoch(train) [69][580/940] lr: 1.0000e-03 eta: 5:23:30 time: 0.6841 data_time: 0.0394 memory: 24011 grad_norm: 5.2622 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6719 loss: 0.6719 2022/09/05 20:51:56 - mmengine - INFO - Epoch(train) [69][600/940] lr: 1.0000e-03 eta: 5:23:18 time: 0.7223 data_time: 0.0449 memory: 24011 grad_norm: 4.9015 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6746 loss: 0.6746 2022/09/05 20:52:09 - mmengine - INFO - Epoch(train) [69][620/940] lr: 1.0000e-03 eta: 5:23:05 time: 0.6770 data_time: 0.0451 memory: 24011 grad_norm: 6.1533 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.5888 loss: 0.5888 2022/09/05 20:52:22 - mmengine - INFO - Epoch(train) [69][640/940] lr: 1.0000e-03 eta: 5:22:51 time: 0.6383 data_time: 0.0423 memory: 24011 grad_norm: 5.7154 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6332 loss: 0.6332 2022/09/05 20:52:36 - mmengine - INFO - Epoch(train) [69][660/940] lr: 1.0000e-03 eta: 5:22:38 time: 0.6709 data_time: 0.0496 memory: 24011 grad_norm: 6.0349 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5760 loss: 0.5760 2022/09/05 20:52:48 - mmengine - INFO - Epoch(train) [69][680/940] lr: 1.0000e-03 eta: 5:22:25 time: 0.6037 data_time: 0.0619 memory: 24011 grad_norm: 5.9872 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6380 loss: 0.6380 2022/09/05 20:53:00 - mmengine - INFO - Epoch(train) [69][700/940] lr: 1.0000e-03 eta: 5:22:11 time: 0.6358 data_time: 0.0443 memory: 24011 grad_norm: 5.1306 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5329 loss: 0.5329 2022/09/05 20:53:13 - mmengine - INFO - Epoch(train) [69][720/940] lr: 1.0000e-03 eta: 5:21:58 time: 0.6471 data_time: 0.0384 memory: 24011 grad_norm: 5.2969 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5630 loss: 0.5630 2022/09/05 20:53:26 - mmengine - INFO - Epoch(train) [69][740/940] lr: 1.0000e-03 eta: 5:21:45 time: 0.6357 data_time: 0.0430 memory: 24011 grad_norm: 5.1045 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6107 loss: 0.6107 2022/09/05 20:53:38 - mmengine - INFO - Epoch(train) [69][760/940] lr: 1.0000e-03 eta: 5:21:31 time: 0.6235 data_time: 0.0421 memory: 24011 grad_norm: 5.9229 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6895 loss: 0.6895 2022/09/05 20:53:52 - mmengine - INFO - Epoch(train) [69][780/940] lr: 1.0000e-03 eta: 5:21:18 time: 0.6669 data_time: 0.0450 memory: 24011 grad_norm: 5.3213 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5572 loss: 0.5572 2022/09/05 20:54:04 - mmengine - INFO - Epoch(train) [69][800/940] lr: 1.0000e-03 eta: 5:21:05 time: 0.6277 data_time: 0.0403 memory: 24011 grad_norm: 5.4784 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5669 loss: 0.5669 2022/09/05 20:54:17 - mmengine - INFO - Epoch(train) [69][820/940] lr: 1.0000e-03 eta: 5:20:51 time: 0.6473 data_time: 0.0424 memory: 24011 grad_norm: 5.3063 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5529 loss: 0.5529 2022/09/05 20:54:31 - mmengine - INFO - Epoch(train) [69][840/940] lr: 1.0000e-03 eta: 5:20:38 time: 0.6794 data_time: 0.0362 memory: 24011 grad_norm: 5.7209 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6437 loss: 0.6437 2022/09/05 20:54:44 - mmengine - INFO - Epoch(train) [69][860/940] lr: 1.0000e-03 eta: 5:20:25 time: 0.6510 data_time: 0.0424 memory: 24011 grad_norm: 6.4313 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6158 loss: 0.6158 2022/09/05 20:54:58 - mmengine - INFO - Epoch(train) [69][880/940] lr: 1.0000e-03 eta: 5:20:12 time: 0.6839 data_time: 0.0384 memory: 24011 grad_norm: 7.2251 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5782 loss: 0.5782 2022/09/05 20:55:10 - mmengine - INFO - Epoch(train) [69][900/940] lr: 1.0000e-03 eta: 5:19:59 time: 0.6345 data_time: 0.0369 memory: 24011 grad_norm: 5.5174 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5842 loss: 0.5842 2022/09/05 20:55:24 - mmengine - INFO - Epoch(train) [69][920/940] lr: 1.0000e-03 eta: 5:19:46 time: 0.6580 data_time: 0.0384 memory: 24011 grad_norm: 5.0967 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4830 loss: 0.4830 2022/09/05 20:55:34 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:55:34 - mmengine - INFO - Epoch(train) [69][940/940] lr: 1.0000e-03 eta: 5:19:32 time: 0.5443 data_time: 0.0306 memory: 24011 grad_norm: 5.6989 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 0.6459 loss: 0.6459 2022/09/05 20:55:34 - mmengine - INFO - Saving checkpoint at 69 epochs 2022/09/05 20:55:53 - mmengine - INFO - Epoch(val) [69][20/78] eta: 0:00:40 time: 0.7035 data_time: 0.5441 memory: 3625 2022/09/05 20:56:03 - mmengine - INFO - Epoch(val) [69][40/78] eta: 0:00:18 time: 0.4741 data_time: 0.3165 memory: 3625 2022/09/05 20:56:16 - mmengine - INFO - Epoch(val) [69][60/78] eta: 0:00:11 time: 0.6375 data_time: 0.4816 memory: 3625 2022/09/05 20:56:25 - mmengine - INFO - Epoch(val) [69][78/78] acc/top1: 0.7383 acc/top5: 0.9062 acc/mean1: 0.7381 2022/09/05 20:56:43 - mmengine - INFO - Epoch(train) [70][20/940] lr: 1.0000e-03 eta: 5:19:20 time: 0.8876 data_time: 0.2332 memory: 24011 grad_norm: 5.3398 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6773 loss: 0.6773 2022/09/05 20:56:55 - mmengine - INFO - Epoch(train) [70][40/940] lr: 1.0000e-03 eta: 5:19:07 time: 0.6169 data_time: 0.0397 memory: 24011 grad_norm: 6.5642 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6323 loss: 0.6323 2022/09/05 20:57:09 - mmengine - INFO - Epoch(train) [70][60/940] lr: 1.0000e-03 eta: 5:18:54 time: 0.6752 data_time: 0.0407 memory: 24011 grad_norm: 6.0438 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6313 loss: 0.6313 2022/09/05 20:57:22 - mmengine - INFO - Epoch(train) [70][80/940] lr: 1.0000e-03 eta: 5:18:41 time: 0.6778 data_time: 0.0639 memory: 24011 grad_norm: 5.4529 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5256 loss: 0.5256 2022/09/05 20:57:37 - mmengine - INFO - Epoch(train) [70][100/940] lr: 1.0000e-03 eta: 5:18:28 time: 0.7139 data_time: 0.1198 memory: 24011 grad_norm: 5.0234 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5528 loss: 0.5528 2022/09/05 20:57:49 - mmengine - INFO - Epoch(train) [70][120/940] lr: 1.0000e-03 eta: 5:18:15 time: 0.6266 data_time: 0.0619 memory: 24011 grad_norm: 5.8207 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6063 loss: 0.6063 2022/09/05 20:58:03 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 20:58:03 - mmengine - INFO - Epoch(train) [70][140/940] lr: 1.0000e-03 eta: 5:18:02 time: 0.6912 data_time: 0.0984 memory: 24011 grad_norm: 5.2247 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5690 loss: 0.5690 2022/09/05 20:58:15 - mmengine - INFO - Epoch(train) [70][160/940] lr: 1.0000e-03 eta: 5:17:48 time: 0.6053 data_time: 0.0273 memory: 24011 grad_norm: 5.2708 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6870 loss: 0.6870 2022/09/05 20:58:29 - mmengine - INFO - Epoch(train) [70][180/940] lr: 1.0000e-03 eta: 5:17:35 time: 0.6710 data_time: 0.0398 memory: 24011 grad_norm: 5.5986 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5574 loss: 0.5574 2022/09/05 20:58:41 - mmengine - INFO - Epoch(train) [70][200/940] lr: 1.0000e-03 eta: 5:17:22 time: 0.6348 data_time: 0.0291 memory: 24011 grad_norm: 5.4782 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4908 loss: 0.4908 2022/09/05 20:58:54 - mmengine - INFO - Epoch(train) [70][220/940] lr: 1.0000e-03 eta: 5:17:09 time: 0.6521 data_time: 0.0449 memory: 24011 grad_norm: 5.1419 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.5642 loss: 0.5642 2022/09/05 20:59:08 - mmengine - INFO - Epoch(train) [70][240/940] lr: 1.0000e-03 eta: 5:16:56 time: 0.6615 data_time: 0.0354 memory: 24011 grad_norm: 5.3687 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5664 loss: 0.5664 2022/09/05 20:59:21 - mmengine - INFO - Epoch(train) [70][260/940] lr: 1.0000e-03 eta: 5:16:42 time: 0.6607 data_time: 0.0404 memory: 24011 grad_norm: 5.7988 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6174 loss: 0.6174 2022/09/05 20:59:33 - mmengine - INFO - Epoch(train) [70][280/940] lr: 1.0000e-03 eta: 5:16:29 time: 0.6216 data_time: 0.0471 memory: 24011 grad_norm: 6.0582 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5608 loss: 0.5608 2022/09/05 20:59:47 - mmengine - INFO - Epoch(train) [70][300/940] lr: 1.0000e-03 eta: 5:16:16 time: 0.6701 data_time: 0.0369 memory: 24011 grad_norm: 5.5607 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5971 loss: 0.5971 2022/09/05 21:00:00 - mmengine - INFO - Epoch(train) [70][320/940] lr: 1.0000e-03 eta: 5:16:03 time: 0.6404 data_time: 0.0545 memory: 24011 grad_norm: 5.2721 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.5450 loss: 0.5450 2022/09/05 21:00:12 - mmengine - INFO - Epoch(train) [70][340/940] lr: 1.0000e-03 eta: 5:15:49 time: 0.6150 data_time: 0.0413 memory: 24011 grad_norm: 7.2187 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6659 loss: 0.6659 2022/09/05 21:00:25 - mmengine - INFO - Epoch(train) [70][360/940] lr: 1.0000e-03 eta: 5:15:36 time: 0.6605 data_time: 0.0466 memory: 24011 grad_norm: 5.4157 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5699 loss: 0.5699 2022/09/05 21:00:38 - mmengine - INFO - Epoch(train) [70][380/940] lr: 1.0000e-03 eta: 5:15:23 time: 0.6634 data_time: 0.0380 memory: 24011 grad_norm: 5.6904 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6925 loss: 0.6925 2022/09/05 21:00:51 - mmengine - INFO - Epoch(train) [70][400/940] lr: 1.0000e-03 eta: 5:15:10 time: 0.6457 data_time: 0.0406 memory: 24011 grad_norm: 5.3738 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6257 loss: 0.6257 2022/09/05 21:01:04 - mmengine - INFO - Epoch(train) [70][420/940] lr: 1.0000e-03 eta: 5:14:56 time: 0.6317 data_time: 0.0387 memory: 24011 grad_norm: 5.2903 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6962 loss: 0.6962 2022/09/05 21:01:16 - mmengine - INFO - Epoch(train) [70][440/940] lr: 1.0000e-03 eta: 5:14:43 time: 0.6269 data_time: 0.0416 memory: 24011 grad_norm: 5.2150 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5001 loss: 0.5001 2022/09/05 21:01:29 - mmengine - INFO - Epoch(train) [70][460/940] lr: 1.0000e-03 eta: 5:14:29 time: 0.6219 data_time: 0.0387 memory: 24011 grad_norm: 5.2695 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6755 loss: 0.6755 2022/09/05 21:01:42 - mmengine - INFO - Epoch(train) [70][480/940] lr: 1.0000e-03 eta: 5:14:16 time: 0.6686 data_time: 0.0432 memory: 24011 grad_norm: 5.9278 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.5822 loss: 0.5822 2022/09/05 21:01:55 - mmengine - INFO - Epoch(train) [70][500/940] lr: 1.0000e-03 eta: 5:14:03 time: 0.6596 data_time: 0.0398 memory: 24011 grad_norm: 5.8392 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5953 loss: 0.5953 2022/09/05 21:02:08 - mmengine - INFO - Epoch(train) [70][520/940] lr: 1.0000e-03 eta: 5:13:50 time: 0.6426 data_time: 0.0435 memory: 24011 grad_norm: 5.6978 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6248 loss: 0.6248 2022/09/05 21:02:22 - mmengine - INFO - Epoch(train) [70][540/940] lr: 1.0000e-03 eta: 5:13:37 time: 0.6601 data_time: 0.0373 memory: 24011 grad_norm: 5.1648 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5934 loss: 0.5934 2022/09/05 21:02:35 - mmengine - INFO - Epoch(train) [70][560/940] lr: 1.0000e-03 eta: 5:13:23 time: 0.6612 data_time: 0.0422 memory: 24011 grad_norm: 5.3467 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6027 loss: 0.6027 2022/09/05 21:02:48 - mmengine - INFO - Epoch(train) [70][580/940] lr: 1.0000e-03 eta: 5:13:10 time: 0.6673 data_time: 0.0363 memory: 24011 grad_norm: 5.1469 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5864 loss: 0.5864 2022/09/05 21:03:01 - mmengine - INFO - Epoch(train) [70][600/940] lr: 1.0000e-03 eta: 5:12:57 time: 0.6497 data_time: 0.0415 memory: 24011 grad_norm: 6.0038 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6412 loss: 0.6412 2022/09/05 21:03:14 - mmengine - INFO - Epoch(train) [70][620/940] lr: 1.0000e-03 eta: 5:12:44 time: 0.6473 data_time: 0.0494 memory: 24011 grad_norm: 5.8278 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6513 loss: 0.6513 2022/09/05 21:03:26 - mmengine - INFO - Epoch(train) [70][640/940] lr: 1.0000e-03 eta: 5:12:30 time: 0.6135 data_time: 0.0465 memory: 24011 grad_norm: 5.2224 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5908 loss: 0.5908 2022/09/05 21:03:38 - mmengine - INFO - Epoch(train) [70][660/940] lr: 1.0000e-03 eta: 5:12:17 time: 0.6041 data_time: 0.0398 memory: 24011 grad_norm: 5.4227 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5956 loss: 0.5956 2022/09/05 21:03:52 - mmengine - INFO - Epoch(train) [70][680/940] lr: 1.0000e-03 eta: 5:12:04 time: 0.6843 data_time: 0.0374 memory: 24011 grad_norm: 5.3857 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5980 loss: 0.5980 2022/09/05 21:04:05 - mmengine - INFO - Epoch(train) [70][700/940] lr: 1.0000e-03 eta: 5:11:50 time: 0.6359 data_time: 0.0419 memory: 24011 grad_norm: 7.8531 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4920 loss: 0.4920 2022/09/05 21:04:18 - mmengine - INFO - Epoch(train) [70][720/940] lr: 1.0000e-03 eta: 5:11:37 time: 0.6439 data_time: 0.0468 memory: 24011 grad_norm: 5.4362 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6034 loss: 0.6034 2022/09/05 21:04:31 - mmengine - INFO - Epoch(train) [70][740/940] lr: 1.0000e-03 eta: 5:11:24 time: 0.6381 data_time: 0.0525 memory: 24011 grad_norm: 5.5908 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5850 loss: 0.5850 2022/09/05 21:04:44 - mmengine - INFO - Epoch(train) [70][760/940] lr: 1.0000e-03 eta: 5:11:11 time: 0.6907 data_time: 0.0540 memory: 24011 grad_norm: 6.1664 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5436 loss: 0.5436 2022/09/05 21:04:56 - mmengine - INFO - Epoch(train) [70][780/940] lr: 1.0000e-03 eta: 5:10:57 time: 0.6043 data_time: 0.0428 memory: 24011 grad_norm: 5.2934 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6222 loss: 0.6222 2022/09/05 21:05:09 - mmengine - INFO - Epoch(train) [70][800/940] lr: 1.0000e-03 eta: 5:10:44 time: 0.6430 data_time: 0.0414 memory: 24011 grad_norm: 6.3034 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5634 loss: 0.5634 2022/09/05 21:05:22 - mmengine - INFO - Epoch(train) [70][820/940] lr: 1.0000e-03 eta: 5:10:31 time: 0.6406 data_time: 0.0428 memory: 24011 grad_norm: 5.4325 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5828 loss: 0.5828 2022/09/05 21:05:35 - mmengine - INFO - Epoch(train) [70][840/940] lr: 1.0000e-03 eta: 5:10:17 time: 0.6414 data_time: 0.0424 memory: 24011 grad_norm: 5.4094 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6638 loss: 0.6638 2022/09/05 21:05:48 - mmengine - INFO - Epoch(train) [70][860/940] lr: 1.0000e-03 eta: 5:10:04 time: 0.6615 data_time: 0.0364 memory: 24011 grad_norm: 5.7656 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6432 loss: 0.6432 2022/09/05 21:06:01 - mmengine - INFO - Epoch(train) [70][880/940] lr: 1.0000e-03 eta: 5:09:51 time: 0.6599 data_time: 0.0380 memory: 24011 grad_norm: 5.3565 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.6193 loss: 0.6193 2022/09/05 21:06:14 - mmengine - INFO - Epoch(train) [70][900/940] lr: 1.0000e-03 eta: 5:09:38 time: 0.6380 data_time: 0.0421 memory: 24011 grad_norm: 6.0315 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6477 loss: 0.6477 2022/09/05 21:06:27 - mmengine - INFO - Epoch(train) [70][920/940] lr: 1.0000e-03 eta: 5:09:25 time: 0.6598 data_time: 0.0463 memory: 24011 grad_norm: 6.0580 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5658 loss: 0.5658 2022/09/05 21:06:39 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:06:39 - mmengine - INFO - Epoch(train) [70][940/940] lr: 1.0000e-03 eta: 5:09:11 time: 0.5605 data_time: 0.0244 memory: 24011 grad_norm: 5.6174 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5762 loss: 0.5762 2022/09/05 21:06:53 - mmengine - INFO - Epoch(val) [70][20/78] eta: 0:00:40 time: 0.6949 data_time: 0.5375 memory: 3625 2022/09/05 21:07:02 - mmengine - INFO - Epoch(val) [70][40/78] eta: 0:00:17 time: 0.4652 data_time: 0.3086 memory: 3625 2022/09/05 21:07:15 - mmengine - INFO - Epoch(val) [70][60/78] eta: 0:00:11 time: 0.6570 data_time: 0.4918 memory: 3625 2022/09/05 21:07:25 - mmengine - INFO - Epoch(val) [70][78/78] acc/top1: 0.7381 acc/top5: 0.9072 acc/mean1: 0.7380 2022/09/05 21:07:44 - mmengine - INFO - Epoch(train) [71][20/940] lr: 1.0000e-03 eta: 5:09:00 time: 0.9044 data_time: 0.2943 memory: 24011 grad_norm: 5.8444 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6058 loss: 0.6058 2022/09/05 21:07:57 - mmengine - INFO - Epoch(train) [71][40/940] lr: 1.0000e-03 eta: 5:08:47 time: 0.6594 data_time: 0.0493 memory: 24011 grad_norm: 5.2128 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6278 loss: 0.6278 2022/09/05 21:08:10 - mmengine - INFO - Epoch(train) [71][60/940] lr: 1.0000e-03 eta: 5:08:34 time: 0.6857 data_time: 0.0393 memory: 24011 grad_norm: 4.9655 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5987 loss: 0.5987 2022/09/05 21:08:24 - mmengine - INFO - Epoch(train) [71][80/940] lr: 1.0000e-03 eta: 5:08:21 time: 0.6610 data_time: 0.0381 memory: 24011 grad_norm: 5.2029 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5336 loss: 0.5336 2022/09/05 21:08:37 - mmengine - INFO - Epoch(train) [71][100/940] lr: 1.0000e-03 eta: 5:08:07 time: 0.6648 data_time: 0.0763 memory: 24011 grad_norm: 5.9845 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6878 loss: 0.6878 2022/09/05 21:08:49 - mmengine - INFO - Epoch(train) [71][120/940] lr: 1.0000e-03 eta: 5:07:54 time: 0.6106 data_time: 0.0457 memory: 24011 grad_norm: 5.4205 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6400 loss: 0.6400 2022/09/05 21:09:02 - mmengine - INFO - Epoch(train) [71][140/940] lr: 1.0000e-03 eta: 5:07:41 time: 0.6540 data_time: 0.0425 memory: 24011 grad_norm: 5.8746 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6615 loss: 0.6615 2022/09/05 21:09:15 - mmengine - INFO - Epoch(train) [71][160/940] lr: 1.0000e-03 eta: 5:07:28 time: 0.6600 data_time: 0.0430 memory: 24011 grad_norm: 5.3279 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6276 loss: 0.6276 2022/09/05 21:09:29 - mmengine - INFO - Epoch(train) [71][180/940] lr: 1.0000e-03 eta: 5:07:15 time: 0.6820 data_time: 0.0406 memory: 24011 grad_norm: 5.4826 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5619 loss: 0.5619 2022/09/05 21:09:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:09:41 - mmengine - INFO - Epoch(train) [71][200/940] lr: 1.0000e-03 eta: 5:07:01 time: 0.6168 data_time: 0.0416 memory: 24011 grad_norm: 5.4756 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5784 loss: 0.5784 2022/09/05 21:09:54 - mmengine - INFO - Epoch(train) [71][220/940] lr: 1.0000e-03 eta: 5:06:48 time: 0.6196 data_time: 0.0389 memory: 24011 grad_norm: 5.0644 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5144 loss: 0.5144 2022/09/05 21:10:07 - mmengine - INFO - Epoch(train) [71][240/940] lr: 1.0000e-03 eta: 5:06:34 time: 0.6417 data_time: 0.0377 memory: 24011 grad_norm: 5.1768 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6687 loss: 0.6687 2022/09/05 21:10:20 - mmengine - INFO - Epoch(train) [71][260/940] lr: 1.0000e-03 eta: 5:06:21 time: 0.6588 data_time: 0.0394 memory: 24011 grad_norm: 5.3784 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6668 loss: 0.6668 2022/09/05 21:10:33 - mmengine - INFO - Epoch(train) [71][280/940] lr: 1.0000e-03 eta: 5:06:08 time: 0.6320 data_time: 0.0376 memory: 24011 grad_norm: 5.9493 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5706 loss: 0.5706 2022/09/05 21:10:47 - mmengine - INFO - Epoch(train) [71][300/940] lr: 1.0000e-03 eta: 5:05:55 time: 0.6932 data_time: 0.0345 memory: 24011 grad_norm: 6.3513 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6739 loss: 0.6739 2022/09/05 21:10:59 - mmengine - INFO - Epoch(train) [71][320/940] lr: 1.0000e-03 eta: 5:05:41 time: 0.6309 data_time: 0.0512 memory: 24011 grad_norm: 5.2406 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.5714 loss: 0.5714 2022/09/05 21:11:12 - mmengine - INFO - Epoch(train) [71][340/940] lr: 1.0000e-03 eta: 5:05:28 time: 0.6530 data_time: 0.0340 memory: 24011 grad_norm: 5.0552 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5731 loss: 0.5731 2022/09/05 21:11:24 - mmengine - INFO - Epoch(train) [71][360/940] lr: 1.0000e-03 eta: 5:05:15 time: 0.6190 data_time: 0.0390 memory: 24011 grad_norm: 5.3240 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6071 loss: 0.6071 2022/09/05 21:11:39 - mmengine - INFO - Epoch(train) [71][380/940] lr: 1.0000e-03 eta: 5:05:02 time: 0.7127 data_time: 0.0311 memory: 24011 grad_norm: 5.6010 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.6186 loss: 0.6186 2022/09/05 21:11:51 - mmengine - INFO - Epoch(train) [71][400/940] lr: 1.0000e-03 eta: 5:04:48 time: 0.6006 data_time: 0.0371 memory: 24011 grad_norm: 5.3140 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6177 loss: 0.6177 2022/09/05 21:12:04 - mmengine - INFO - Epoch(train) [71][420/940] lr: 1.0000e-03 eta: 5:04:35 time: 0.6380 data_time: 0.0332 memory: 24011 grad_norm: 5.1433 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5925 loss: 0.5925 2022/09/05 21:12:16 - mmengine - INFO - Epoch(train) [71][440/940] lr: 1.0000e-03 eta: 5:04:22 time: 0.6464 data_time: 0.0528 memory: 24011 grad_norm: 5.0653 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6341 loss: 0.6341 2022/09/05 21:12:29 - mmengine - INFO - Epoch(train) [71][460/940] lr: 1.0000e-03 eta: 5:04:09 time: 0.6333 data_time: 0.0512 memory: 24011 grad_norm: 5.3723 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6409 loss: 0.6409 2022/09/05 21:12:42 - mmengine - INFO - Epoch(train) [71][480/940] lr: 1.0000e-03 eta: 5:03:55 time: 0.6485 data_time: 0.0456 memory: 24011 grad_norm: 5.6995 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6030 loss: 0.6030 2022/09/05 21:12:55 - mmengine - INFO - Epoch(train) [71][500/940] lr: 1.0000e-03 eta: 5:03:42 time: 0.6233 data_time: 0.0388 memory: 24011 grad_norm: 5.5988 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5769 loss: 0.5769 2022/09/05 21:13:08 - mmengine - INFO - Epoch(train) [71][520/940] lr: 1.0000e-03 eta: 5:03:29 time: 0.6822 data_time: 0.0426 memory: 24011 grad_norm: 5.4615 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6393 loss: 0.6393 2022/09/05 21:13:21 - mmengine - INFO - Epoch(train) [71][540/940] lr: 1.0000e-03 eta: 5:03:16 time: 0.6304 data_time: 0.0525 memory: 24011 grad_norm: 5.2564 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6034 loss: 0.6034 2022/09/05 21:13:34 - mmengine - INFO - Epoch(train) [71][560/940] lr: 1.0000e-03 eta: 5:03:02 time: 0.6608 data_time: 0.0381 memory: 24011 grad_norm: 6.0198 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5920 loss: 0.5920 2022/09/05 21:13:46 - mmengine - INFO - Epoch(train) [71][580/940] lr: 1.0000e-03 eta: 5:02:49 time: 0.6211 data_time: 0.0373 memory: 24011 grad_norm: 5.6334 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5688 loss: 0.5688 2022/09/05 21:14:00 - mmengine - INFO - Epoch(train) [71][600/940] lr: 1.0000e-03 eta: 5:02:36 time: 0.6731 data_time: 0.0515 memory: 24011 grad_norm: 5.1749 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5767 loss: 0.5767 2022/09/05 21:14:13 - mmengine - INFO - Epoch(train) [71][620/940] lr: 1.0000e-03 eta: 5:02:23 time: 0.6505 data_time: 0.0379 memory: 24011 grad_norm: 5.4867 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6399 loss: 0.6399 2022/09/05 21:14:27 - mmengine - INFO - Epoch(train) [71][640/940] lr: 1.0000e-03 eta: 5:02:10 time: 0.6866 data_time: 0.0496 memory: 24011 grad_norm: 5.5331 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6057 loss: 0.6057 2022/09/05 21:14:40 - mmengine - INFO - Epoch(train) [71][660/940] lr: 1.0000e-03 eta: 5:01:56 time: 0.6392 data_time: 0.0387 memory: 24011 grad_norm: 5.4725 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6416 loss: 0.6416 2022/09/05 21:14:52 - mmengine - INFO - Epoch(train) [71][680/940] lr: 1.0000e-03 eta: 5:01:43 time: 0.6049 data_time: 0.0382 memory: 24011 grad_norm: 5.9279 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5938 loss: 0.5938 2022/09/05 21:15:04 - mmengine - INFO - Epoch(train) [71][700/940] lr: 1.0000e-03 eta: 5:01:30 time: 0.6398 data_time: 0.0426 memory: 24011 grad_norm: 5.7082 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5861 loss: 0.5861 2022/09/05 21:15:17 - mmengine - INFO - Epoch(train) [71][720/940] lr: 1.0000e-03 eta: 5:01:16 time: 0.6337 data_time: 0.0368 memory: 24011 grad_norm: 5.3965 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5764 loss: 0.5764 2022/09/05 21:15:31 - mmengine - INFO - Epoch(train) [71][740/940] lr: 1.0000e-03 eta: 5:01:03 time: 0.7046 data_time: 0.0421 memory: 24011 grad_norm: 14.1043 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6388 loss: 0.6388 2022/09/05 21:15:43 - mmengine - INFO - Epoch(train) [71][760/940] lr: 1.0000e-03 eta: 5:00:50 time: 0.6055 data_time: 0.0329 memory: 24011 grad_norm: 5.6124 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6272 loss: 0.6272 2022/09/05 21:15:57 - mmengine - INFO - Epoch(train) [71][780/940] lr: 1.0000e-03 eta: 5:00:37 time: 0.6690 data_time: 0.0368 memory: 24011 grad_norm: 5.3314 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6335 loss: 0.6335 2022/09/05 21:16:10 - mmengine - INFO - Epoch(train) [71][800/940] lr: 1.0000e-03 eta: 5:00:24 time: 0.6810 data_time: 0.0418 memory: 24011 grad_norm: 5.9179 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6377 loss: 0.6377 2022/09/05 21:16:23 - mmengine - INFO - Epoch(train) [71][820/940] lr: 1.0000e-03 eta: 5:00:11 time: 0.6511 data_time: 0.0361 memory: 24011 grad_norm: 5.4676 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6309 loss: 0.6309 2022/09/05 21:16:36 - mmengine - INFO - Epoch(train) [71][840/940] lr: 1.0000e-03 eta: 4:59:57 time: 0.6120 data_time: 0.0571 memory: 24011 grad_norm: 5.5044 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6318 loss: 0.6318 2022/09/05 21:16:48 - mmengine - INFO - Epoch(train) [71][860/940] lr: 1.0000e-03 eta: 4:59:44 time: 0.6340 data_time: 0.0439 memory: 24011 grad_norm: 5.4970 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6436 loss: 0.6436 2022/09/05 21:17:01 - mmengine - INFO - Epoch(train) [71][880/940] lr: 1.0000e-03 eta: 4:59:31 time: 0.6555 data_time: 0.0400 memory: 24011 grad_norm: 5.2593 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5573 loss: 0.5573 2022/09/05 21:17:14 - mmengine - INFO - Epoch(train) [71][900/940] lr: 1.0000e-03 eta: 4:59:17 time: 0.6399 data_time: 0.0454 memory: 24011 grad_norm: 6.0579 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5828 loss: 0.5828 2022/09/05 21:17:27 - mmengine - INFO - Epoch(train) [71][920/940] lr: 1.0000e-03 eta: 4:59:04 time: 0.6396 data_time: 0.0376 memory: 24011 grad_norm: 7.4997 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5886 loss: 0.5886 2022/09/05 21:17:39 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:17:39 - mmengine - INFO - Epoch(train) [71][940/940] lr: 1.0000e-03 eta: 4:58:50 time: 0.5866 data_time: 0.0293 memory: 24011 grad_norm: 5.6201 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.6819 loss: 0.6819 2022/09/05 21:17:52 - mmengine - INFO - Epoch(val) [71][20/78] eta: 0:00:39 time: 0.6741 data_time: 0.5155 memory: 3625 2022/09/05 21:18:02 - mmengine - INFO - Epoch(val) [71][40/78] eta: 0:00:18 time: 0.4903 data_time: 0.3312 memory: 3625 2022/09/05 21:18:15 - mmengine - INFO - Epoch(val) [71][60/78] eta: 0:00:11 time: 0.6534 data_time: 0.4934 memory: 3625 2022/09/05 21:18:25 - mmengine - INFO - Epoch(val) [71][78/78] acc/top1: 0.7360 acc/top5: 0.9065 acc/mean1: 0.7359 2022/09/05 21:18:44 - mmengine - INFO - Epoch(train) [72][20/940] lr: 1.0000e-03 eta: 4:58:39 time: 0.9100 data_time: 0.3197 memory: 24011 grad_norm: 5.6713 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6641 loss: 0.6641 2022/09/05 21:18:56 - mmengine - INFO - Epoch(train) [72][40/940] lr: 1.0000e-03 eta: 4:58:26 time: 0.6293 data_time: 0.0484 memory: 24011 grad_norm: 5.4618 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5757 loss: 0.5757 2022/09/05 21:19:10 - mmengine - INFO - Epoch(train) [72][60/940] lr: 1.0000e-03 eta: 4:58:13 time: 0.6963 data_time: 0.0496 memory: 24011 grad_norm: 5.3462 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6376 loss: 0.6376 2022/09/05 21:19:23 - mmengine - INFO - Epoch(train) [72][80/940] lr: 1.0000e-03 eta: 4:57:59 time: 0.6252 data_time: 0.0425 memory: 24011 grad_norm: 5.6822 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5575 loss: 0.5575 2022/09/05 21:19:37 - mmengine - INFO - Epoch(train) [72][100/940] lr: 1.0000e-03 eta: 4:57:47 time: 0.6969 data_time: 0.0408 memory: 24011 grad_norm: 5.2655 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.5126 loss: 0.5126 2022/09/05 21:19:49 - mmengine - INFO - Epoch(train) [72][120/940] lr: 1.0000e-03 eta: 4:57:33 time: 0.6253 data_time: 0.0399 memory: 24011 grad_norm: 5.3159 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.6173 loss: 0.6173 2022/09/05 21:20:02 - mmengine - INFO - Epoch(train) [72][140/940] lr: 1.0000e-03 eta: 4:57:20 time: 0.6232 data_time: 0.0414 memory: 24011 grad_norm: 5.3587 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5834 loss: 0.5834 2022/09/05 21:20:14 - mmengine - INFO - Epoch(train) [72][160/940] lr: 1.0000e-03 eta: 4:57:06 time: 0.6331 data_time: 0.0453 memory: 24011 grad_norm: 5.8385 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6421 loss: 0.6421 2022/09/05 21:20:28 - mmengine - INFO - Epoch(train) [72][180/940] lr: 1.0000e-03 eta: 4:56:53 time: 0.6892 data_time: 0.0403 memory: 24011 grad_norm: 5.3091 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4831 loss: 0.4831 2022/09/05 21:20:41 - mmengine - INFO - Epoch(train) [72][200/940] lr: 1.0000e-03 eta: 4:56:40 time: 0.6667 data_time: 0.0415 memory: 24011 grad_norm: 5.6016 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6734 loss: 0.6734 2022/09/05 21:20:54 - mmengine - INFO - Epoch(train) [72][220/940] lr: 1.0000e-03 eta: 4:56:27 time: 0.6371 data_time: 0.0499 memory: 24011 grad_norm: 5.1960 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.7022 loss: 0.7022 2022/09/05 21:21:07 - mmengine - INFO - Epoch(train) [72][240/940] lr: 1.0000e-03 eta: 4:56:14 time: 0.6208 data_time: 0.0382 memory: 24011 grad_norm: 5.1096 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4652 loss: 0.4652 2022/09/05 21:21:21 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:21:21 - mmengine - INFO - Epoch(train) [72][260/940] lr: 1.0000e-03 eta: 4:56:01 time: 0.7033 data_time: 0.0437 memory: 24011 grad_norm: 5.5203 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6142 loss: 0.6142 2022/09/05 21:21:33 - mmengine - INFO - Epoch(train) [72][280/940] lr: 1.0000e-03 eta: 4:55:47 time: 0.6128 data_time: 0.0453 memory: 24011 grad_norm: 6.7460 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6373 loss: 0.6373 2022/09/05 21:21:46 - mmengine - INFO - Epoch(train) [72][300/940] lr: 1.0000e-03 eta: 4:55:34 time: 0.6354 data_time: 0.0439 memory: 24011 grad_norm: 4.9912 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5407 loss: 0.5407 2022/09/05 21:22:00 - mmengine - INFO - Epoch(train) [72][320/940] lr: 1.0000e-03 eta: 4:55:21 time: 0.7117 data_time: 0.0417 memory: 24011 grad_norm: 5.3318 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5347 loss: 0.5347 2022/09/05 21:22:12 - mmengine - INFO - Epoch(train) [72][340/940] lr: 1.0000e-03 eta: 4:55:08 time: 0.6234 data_time: 0.0502 memory: 24011 grad_norm: 5.6402 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.5841 loss: 0.5841 2022/09/05 21:22:25 - mmengine - INFO - Epoch(train) [72][360/940] lr: 1.0000e-03 eta: 4:54:54 time: 0.6062 data_time: 0.0497 memory: 24011 grad_norm: 5.3390 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5081 loss: 0.5081 2022/09/05 21:22:37 - mmengine - INFO - Epoch(train) [72][380/940] lr: 1.0000e-03 eta: 4:54:41 time: 0.6277 data_time: 0.0540 memory: 24011 grad_norm: 5.8745 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6137 loss: 0.6137 2022/09/05 21:22:50 - mmengine - INFO - Epoch(train) [72][400/940] lr: 1.0000e-03 eta: 4:54:27 time: 0.6325 data_time: 0.0528 memory: 24011 grad_norm: 5.6463 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.5581 loss: 0.5581 2022/09/05 21:23:02 - mmengine - INFO - Epoch(train) [72][420/940] lr: 1.0000e-03 eta: 4:54:14 time: 0.6200 data_time: 0.0379 memory: 24011 grad_norm: 5.8803 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6463 loss: 0.6463 2022/09/05 21:23:16 - mmengine - INFO - Epoch(train) [72][440/940] lr: 1.0000e-03 eta: 4:54:01 time: 0.6989 data_time: 0.0629 memory: 24011 grad_norm: 5.2263 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.6646 loss: 0.6646 2022/09/05 21:23:29 - mmengine - INFO - Epoch(train) [72][460/940] lr: 1.0000e-03 eta: 4:53:48 time: 0.6295 data_time: 0.0355 memory: 24011 grad_norm: 5.8149 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6192 loss: 0.6192 2022/09/05 21:23:42 - mmengine - INFO - Epoch(train) [72][480/940] lr: 1.0000e-03 eta: 4:53:35 time: 0.6673 data_time: 0.0454 memory: 24011 grad_norm: 5.5600 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5383 loss: 0.5383 2022/09/05 21:23:55 - mmengine - INFO - Epoch(train) [72][500/940] lr: 1.0000e-03 eta: 4:53:22 time: 0.6705 data_time: 0.0320 memory: 24011 grad_norm: 5.1128 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6535 loss: 0.6535 2022/09/05 21:24:08 - mmengine - INFO - Epoch(train) [72][520/940] lr: 1.0000e-03 eta: 4:53:08 time: 0.6261 data_time: 0.0431 memory: 24011 grad_norm: 5.6896 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6007 loss: 0.6007 2022/09/05 21:24:21 - mmengine - INFO - Epoch(train) [72][540/940] lr: 1.0000e-03 eta: 4:52:55 time: 0.6491 data_time: 0.0341 memory: 24011 grad_norm: 5.5574 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6703 loss: 0.6703 2022/09/05 21:24:35 - mmengine - INFO - Epoch(train) [72][560/940] lr: 1.0000e-03 eta: 4:52:42 time: 0.6940 data_time: 0.0449 memory: 24011 grad_norm: 5.2650 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6326 loss: 0.6326 2022/09/05 21:24:48 - mmengine - INFO - Epoch(train) [72][580/940] lr: 1.0000e-03 eta: 4:52:29 time: 0.6505 data_time: 0.0340 memory: 24011 grad_norm: 5.2348 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6238 loss: 0.6238 2022/09/05 21:25:01 - mmengine - INFO - Epoch(train) [72][600/940] lr: 1.0000e-03 eta: 4:52:16 time: 0.6512 data_time: 0.0445 memory: 24011 grad_norm: 5.8773 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6390 loss: 0.6390 2022/09/05 21:25:14 - mmengine - INFO - Epoch(train) [72][620/940] lr: 1.0000e-03 eta: 4:52:03 time: 0.6454 data_time: 0.0401 memory: 24011 grad_norm: 5.6450 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.7078 loss: 0.7078 2022/09/05 21:25:27 - mmengine - INFO - Epoch(train) [72][640/940] lr: 1.0000e-03 eta: 4:51:49 time: 0.6720 data_time: 0.0646 memory: 24011 grad_norm: 5.8295 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5997 loss: 0.5997 2022/09/05 21:25:39 - mmengine - INFO - Epoch(train) [72][660/940] lr: 1.0000e-03 eta: 4:51:36 time: 0.5992 data_time: 0.0364 memory: 24011 grad_norm: 5.4240 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6527 loss: 0.6527 2022/09/05 21:25:52 - mmengine - INFO - Epoch(train) [72][680/940] lr: 1.0000e-03 eta: 4:51:22 time: 0.6299 data_time: 0.0464 memory: 24011 grad_norm: 5.5329 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6718 loss: 0.6718 2022/09/05 21:26:05 - mmengine - INFO - Epoch(train) [72][700/940] lr: 1.0000e-03 eta: 4:51:09 time: 0.6523 data_time: 0.0340 memory: 24011 grad_norm: 5.9941 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6135 loss: 0.6135 2022/09/05 21:26:18 - mmengine - INFO - Epoch(train) [72][720/940] lr: 1.0000e-03 eta: 4:50:56 time: 0.6678 data_time: 0.0394 memory: 24011 grad_norm: 5.8637 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6090 loss: 0.6090 2022/09/05 21:26:31 - mmengine - INFO - Epoch(train) [72][740/940] lr: 1.0000e-03 eta: 4:50:43 time: 0.6508 data_time: 0.0331 memory: 24011 grad_norm: 6.2749 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5280 loss: 0.5280 2022/09/05 21:26:45 - mmengine - INFO - Epoch(train) [72][760/940] lr: 1.0000e-03 eta: 4:50:30 time: 0.6761 data_time: 0.0449 memory: 24011 grad_norm: 6.0087 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5407 loss: 0.5407 2022/09/05 21:26:57 - mmengine - INFO - Epoch(train) [72][780/940] lr: 1.0000e-03 eta: 4:50:16 time: 0.6100 data_time: 0.0388 memory: 24011 grad_norm: 5.2614 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6144 loss: 0.6144 2022/09/05 21:27:11 - mmengine - INFO - Epoch(train) [72][800/940] lr: 1.0000e-03 eta: 4:50:04 time: 0.6983 data_time: 0.0426 memory: 24011 grad_norm: 5.5610 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5957 loss: 0.5957 2022/09/05 21:27:23 - mmengine - INFO - Epoch(train) [72][820/940] lr: 1.0000e-03 eta: 4:49:50 time: 0.6027 data_time: 0.0441 memory: 24011 grad_norm: 5.7156 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6390 loss: 0.6390 2022/09/05 21:27:36 - mmengine - INFO - Epoch(train) [72][840/940] lr: 1.0000e-03 eta: 4:49:37 time: 0.6579 data_time: 0.0359 memory: 24011 grad_norm: 5.5286 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6673 loss: 0.6673 2022/09/05 21:27:48 - mmengine - INFO - Epoch(train) [72][860/940] lr: 1.0000e-03 eta: 4:49:23 time: 0.6015 data_time: 0.0378 memory: 24011 grad_norm: 5.2134 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5005 loss: 0.5005 2022/09/05 21:28:01 - mmengine - INFO - Epoch(train) [72][880/940] lr: 1.0000e-03 eta: 4:49:10 time: 0.6384 data_time: 0.0403 memory: 24011 grad_norm: 5.2197 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6527 loss: 0.6527 2022/09/05 21:28:14 - mmengine - INFO - Epoch(train) [72][900/940] lr: 1.0000e-03 eta: 4:48:57 time: 0.6397 data_time: 0.0372 memory: 24011 grad_norm: 5.3979 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6121 loss: 0.6121 2022/09/05 21:28:27 - mmengine - INFO - Epoch(train) [72][920/940] lr: 1.0000e-03 eta: 4:48:43 time: 0.6439 data_time: 0.0366 memory: 24011 grad_norm: 5.6509 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5794 loss: 0.5794 2022/09/05 21:28:38 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:28:38 - mmengine - INFO - Epoch(train) [72][940/940] lr: 1.0000e-03 eta: 4:48:30 time: 0.5692 data_time: 0.0410 memory: 24011 grad_norm: 6.6740 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.5788 loss: 0.5788 2022/09/05 21:28:38 - mmengine - INFO - Saving checkpoint at 72 epochs 2022/09/05 21:28:58 - mmengine - INFO - Epoch(val) [72][20/78] eta: 0:00:41 time: 0.7140 data_time: 0.5585 memory: 3625 2022/09/05 21:29:07 - mmengine - INFO - Epoch(val) [72][40/78] eta: 0:00:17 time: 0.4581 data_time: 0.3026 memory: 3625 2022/09/05 21:29:20 - mmengine - INFO - Epoch(val) [72][60/78] eta: 0:00:11 time: 0.6263 data_time: 0.4715 memory: 3625 2022/09/05 21:29:29 - mmengine - INFO - Epoch(val) [72][78/78] acc/top1: 0.7388 acc/top5: 0.9082 acc/mean1: 0.7387 2022/09/05 21:29:47 - mmengine - INFO - Epoch(train) [73][20/940] lr: 1.0000e-03 eta: 4:48:18 time: 0.8925 data_time: 0.2388 memory: 24011 grad_norm: 5.0974 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6344 loss: 0.6344 2022/09/05 21:30:00 - mmengine - INFO - Epoch(train) [73][40/940] lr: 1.0000e-03 eta: 4:48:05 time: 0.6499 data_time: 0.0372 memory: 24011 grad_norm: 5.6831 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5942 loss: 0.5942 2022/09/05 21:30:14 - mmengine - INFO - Epoch(train) [73][60/940] lr: 1.0000e-03 eta: 4:47:52 time: 0.7116 data_time: 0.0393 memory: 24011 grad_norm: 5.4187 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5493 loss: 0.5493 2022/09/05 21:30:27 - mmengine - INFO - Epoch(train) [73][80/940] lr: 1.0000e-03 eta: 4:47:39 time: 0.6342 data_time: 0.0431 memory: 24011 grad_norm: 7.6878 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6063 loss: 0.6063 2022/09/05 21:30:40 - mmengine - INFO - Epoch(train) [73][100/940] lr: 1.0000e-03 eta: 4:47:26 time: 0.6567 data_time: 0.0497 memory: 24011 grad_norm: 5.9434 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6659 loss: 0.6659 2022/09/05 21:30:53 - mmengine - INFO - Epoch(train) [73][120/940] lr: 1.0000e-03 eta: 4:47:13 time: 0.6737 data_time: 0.0390 memory: 24011 grad_norm: 5.0788 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5272 loss: 0.5272 2022/09/05 21:31:06 - mmengine - INFO - Epoch(train) [73][140/940] lr: 1.0000e-03 eta: 4:47:00 time: 0.6522 data_time: 0.0400 memory: 24011 grad_norm: 5.1408 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6252 loss: 0.6252 2022/09/05 21:31:19 - mmengine - INFO - Epoch(train) [73][160/940] lr: 1.0000e-03 eta: 4:46:46 time: 0.6111 data_time: 0.0597 memory: 24011 grad_norm: 6.9000 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5676 loss: 0.5676 2022/09/05 21:31:31 - mmengine - INFO - Epoch(train) [73][180/940] lr: 1.0000e-03 eta: 4:46:33 time: 0.6130 data_time: 0.0408 memory: 24011 grad_norm: 5.9140 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6057 loss: 0.6057 2022/09/05 21:31:44 - mmengine - INFO - Epoch(train) [73][200/940] lr: 1.0000e-03 eta: 4:46:19 time: 0.6302 data_time: 0.0389 memory: 24011 grad_norm: 8.9671 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6609 loss: 0.6609 2022/09/05 21:31:57 - mmengine - INFO - Epoch(train) [73][220/940] lr: 1.0000e-03 eta: 4:46:06 time: 0.6744 data_time: 0.0439 memory: 24011 grad_norm: 5.2529 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6151 loss: 0.6151 2022/09/05 21:32:10 - mmengine - INFO - Epoch(train) [73][240/940] lr: 1.0000e-03 eta: 4:45:53 time: 0.6463 data_time: 0.0518 memory: 24011 grad_norm: 6.1892 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5465 loss: 0.5465 2022/09/05 21:32:23 - mmengine - INFO - Epoch(train) [73][260/940] lr: 1.0000e-03 eta: 4:45:40 time: 0.6332 data_time: 0.0459 memory: 24011 grad_norm: 5.5877 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5168 loss: 0.5168 2022/09/05 21:32:35 - mmengine - INFO - Epoch(train) [73][280/940] lr: 1.0000e-03 eta: 4:45:26 time: 0.6251 data_time: 0.0410 memory: 24011 grad_norm: 5.5713 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6302 loss: 0.6302 2022/09/05 21:32:49 - mmengine - INFO - Epoch(train) [73][300/940] lr: 1.0000e-03 eta: 4:45:13 time: 0.6684 data_time: 0.0453 memory: 24011 grad_norm: 5.8003 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5810 loss: 0.5810 2022/09/05 21:33:02 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:33:02 - mmengine - INFO - Epoch(train) [73][320/940] lr: 1.0000e-03 eta: 4:45:00 time: 0.6610 data_time: 0.0417 memory: 24011 grad_norm: 5.7542 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6514 loss: 0.6514 2022/09/05 21:33:14 - mmengine - INFO - Epoch(train) [73][340/940] lr: 1.0000e-03 eta: 4:44:47 time: 0.6281 data_time: 0.0417 memory: 24011 grad_norm: 5.6670 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7065 loss: 0.7065 2022/09/05 21:33:28 - mmengine - INFO - Epoch(train) [73][360/940] lr: 1.0000e-03 eta: 4:44:34 time: 0.6850 data_time: 0.0665 memory: 24011 grad_norm: 5.1245 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6916 loss: 0.6916 2022/09/05 21:33:41 - mmengine - INFO - Epoch(train) [73][380/940] lr: 1.0000e-03 eta: 4:44:20 time: 0.6334 data_time: 0.0416 memory: 24011 grad_norm: 5.4591 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6991 loss: 0.6991 2022/09/05 21:33:54 - mmengine - INFO - Epoch(train) [73][400/940] lr: 1.0000e-03 eta: 4:44:07 time: 0.6449 data_time: 0.0392 memory: 24011 grad_norm: 5.6746 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5931 loss: 0.5931 2022/09/05 21:34:07 - mmengine - INFO - Epoch(train) [73][420/940] lr: 1.0000e-03 eta: 4:43:54 time: 0.6628 data_time: 0.0407 memory: 24011 grad_norm: 5.5751 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6127 loss: 0.6127 2022/09/05 21:34:19 - mmengine - INFO - Epoch(train) [73][440/940] lr: 1.0000e-03 eta: 4:43:41 time: 0.6240 data_time: 0.0392 memory: 24011 grad_norm: 6.0205 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6074 loss: 0.6074 2022/09/05 21:34:33 - mmengine - INFO - Epoch(train) [73][460/940] lr: 1.0000e-03 eta: 4:43:28 time: 0.6799 data_time: 0.0371 memory: 24011 grad_norm: 5.2288 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5565 loss: 0.5565 2022/09/05 21:34:46 - mmengine - INFO - Epoch(train) [73][480/940] lr: 1.0000e-03 eta: 4:43:14 time: 0.6523 data_time: 0.0434 memory: 24011 grad_norm: 5.1422 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5968 loss: 0.5968 2022/09/05 21:34:59 - mmengine - INFO - Epoch(train) [73][500/940] lr: 1.0000e-03 eta: 4:43:01 time: 0.6576 data_time: 0.0434 memory: 24011 grad_norm: 4.9477 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6309 loss: 0.6309 2022/09/05 21:35:12 - mmengine - INFO - Epoch(train) [73][520/940] lr: 1.0000e-03 eta: 4:42:48 time: 0.6435 data_time: 0.0546 memory: 24011 grad_norm: 5.6792 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5482 loss: 0.5482 2022/09/05 21:35:24 - mmengine - INFO - Epoch(train) [73][540/940] lr: 1.0000e-03 eta: 4:42:34 time: 0.6065 data_time: 0.0426 memory: 24011 grad_norm: 6.3973 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5591 loss: 0.5591 2022/09/05 21:35:37 - mmengine - INFO - Epoch(train) [73][560/940] lr: 1.0000e-03 eta: 4:42:21 time: 0.6580 data_time: 0.0419 memory: 24011 grad_norm: 5.2383 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5892 loss: 0.5892 2022/09/05 21:35:50 - mmengine - INFO - Epoch(train) [73][580/940] lr: 1.0000e-03 eta: 4:42:08 time: 0.6472 data_time: 0.0444 memory: 24011 grad_norm: 5.4352 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7472 loss: 0.7472 2022/09/05 21:36:03 - mmengine - INFO - Epoch(train) [73][600/940] lr: 1.0000e-03 eta: 4:41:55 time: 0.6472 data_time: 0.0389 memory: 24011 grad_norm: 5.5906 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6076 loss: 0.6076 2022/09/05 21:36:16 - mmengine - INFO - Epoch(train) [73][620/940] lr: 1.0000e-03 eta: 4:41:41 time: 0.6422 data_time: 0.0397 memory: 24011 grad_norm: 5.5115 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5495 loss: 0.5495 2022/09/05 21:36:29 - mmengine - INFO - Epoch(train) [73][640/940] lr: 1.0000e-03 eta: 4:41:28 time: 0.6543 data_time: 0.0482 memory: 24011 grad_norm: 5.0660 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6013 loss: 0.6013 2022/09/05 21:36:42 - mmengine - INFO - Epoch(train) [73][660/940] lr: 1.0000e-03 eta: 4:41:15 time: 0.6104 data_time: 0.0417 memory: 24011 grad_norm: 5.0907 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6131 loss: 0.6131 2022/09/05 21:36:55 - mmengine - INFO - Epoch(train) [73][680/940] lr: 1.0000e-03 eta: 4:41:02 time: 0.6542 data_time: 0.0425 memory: 24011 grad_norm: 5.7074 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.5845 loss: 0.5845 2022/09/05 21:37:08 - mmengine - INFO - Epoch(train) [73][700/940] lr: 1.0000e-03 eta: 4:40:49 time: 0.6770 data_time: 0.0386 memory: 24011 grad_norm: 7.6238 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6474 loss: 0.6474 2022/09/05 21:37:22 - mmengine - INFO - Epoch(train) [73][720/940] lr: 1.0000e-03 eta: 4:40:36 time: 0.6834 data_time: 0.0399 memory: 24011 grad_norm: 5.3027 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6010 loss: 0.6010 2022/09/05 21:37:35 - mmengine - INFO - Epoch(train) [73][740/940] lr: 1.0000e-03 eta: 4:40:22 time: 0.6202 data_time: 0.0386 memory: 24011 grad_norm: 5.1230 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6437 loss: 0.6437 2022/09/05 21:37:47 - mmengine - INFO - Epoch(train) [73][760/940] lr: 1.0000e-03 eta: 4:40:09 time: 0.6159 data_time: 0.0571 memory: 24011 grad_norm: 5.7269 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5578 loss: 0.5578 2022/09/05 21:38:01 - mmengine - INFO - Epoch(train) [73][780/940] lr: 1.0000e-03 eta: 4:39:56 time: 0.6985 data_time: 0.0405 memory: 24011 grad_norm: 6.6046 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6351 loss: 0.6351 2022/09/05 21:38:14 - mmengine - INFO - Epoch(train) [73][800/940] lr: 1.0000e-03 eta: 4:39:43 time: 0.6500 data_time: 0.0425 memory: 24011 grad_norm: 5.3525 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5347 loss: 0.5347 2022/09/05 21:38:26 - mmengine - INFO - Epoch(train) [73][820/940] lr: 1.0000e-03 eta: 4:39:29 time: 0.6286 data_time: 0.0601 memory: 24011 grad_norm: 5.3752 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6211 loss: 0.6211 2022/09/05 21:38:38 - mmengine - INFO - Epoch(train) [73][840/940] lr: 1.0000e-03 eta: 4:39:16 time: 0.6104 data_time: 0.0487 memory: 24011 grad_norm: 5.8244 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6984 loss: 0.6984 2022/09/05 21:38:51 - mmengine - INFO - Epoch(train) [73][860/940] lr: 1.0000e-03 eta: 4:39:02 time: 0.6126 data_time: 0.0395 memory: 24011 grad_norm: 5.8185 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5434 loss: 0.5434 2022/09/05 21:39:04 - mmengine - INFO - Epoch(train) [73][880/940] lr: 1.0000e-03 eta: 4:38:49 time: 0.6928 data_time: 0.0421 memory: 24011 grad_norm: 7.5743 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5974 loss: 0.5974 2022/09/05 21:39:17 - mmengine - INFO - Epoch(train) [73][900/940] lr: 1.0000e-03 eta: 4:38:36 time: 0.6427 data_time: 0.0386 memory: 24011 grad_norm: 5.5352 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.7086 loss: 0.7086 2022/09/05 21:39:31 - mmengine - INFO - Epoch(train) [73][920/940] lr: 1.0000e-03 eta: 4:38:23 time: 0.6659 data_time: 0.0432 memory: 24011 grad_norm: 5.6931 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5960 loss: 0.5960 2022/09/05 21:39:42 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:39:42 - mmengine - INFO - Epoch(train) [73][940/940] lr: 1.0000e-03 eta: 4:38:09 time: 0.5698 data_time: 0.0340 memory: 24011 grad_norm: 6.0972 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5960 loss: 0.5960 2022/09/05 21:39:56 - mmengine - INFO - Epoch(val) [73][20/78] eta: 0:00:39 time: 0.6891 data_time: 0.5295 memory: 3625 2022/09/05 21:40:05 - mmengine - INFO - Epoch(val) [73][40/78] eta: 0:00:17 time: 0.4680 data_time: 0.3061 memory: 3625 2022/09/05 21:40:18 - mmengine - INFO - Epoch(val) [73][60/78] eta: 0:00:11 time: 0.6531 data_time: 0.4863 memory: 3625 2022/09/05 21:40:29 - mmengine - INFO - Epoch(val) [73][78/78] acc/top1: 0.7364 acc/top5: 0.9057 acc/mean1: 0.7363 2022/09/05 21:40:47 - mmengine - INFO - Epoch(train) [74][20/940] lr: 1.0000e-03 eta: 4:37:58 time: 0.9280 data_time: 0.3375 memory: 24011 grad_norm: 5.5613 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6201 loss: 0.6201 2022/09/05 21:40:59 - mmengine - INFO - Epoch(train) [74][40/940] lr: 1.0000e-03 eta: 4:37:45 time: 0.6013 data_time: 0.0357 memory: 24011 grad_norm: 5.1075 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6248 loss: 0.6248 2022/09/05 21:41:14 - mmengine - INFO - Epoch(train) [74][60/940] lr: 1.0000e-03 eta: 4:37:32 time: 0.7180 data_time: 0.1588 memory: 24011 grad_norm: 5.4768 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5618 loss: 0.5618 2022/09/05 21:41:26 - mmengine - INFO - Epoch(train) [74][80/940] lr: 1.0000e-03 eta: 4:37:18 time: 0.6008 data_time: 0.0396 memory: 24011 grad_norm: 5.0369 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6509 loss: 0.6509 2022/09/05 21:41:39 - mmengine - INFO - Epoch(train) [74][100/940] lr: 1.0000e-03 eta: 4:37:05 time: 0.6497 data_time: 0.0673 memory: 24011 grad_norm: 5.2380 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6129 loss: 0.6129 2022/09/05 21:41:51 - mmengine - INFO - Epoch(train) [74][120/940] lr: 1.0000e-03 eta: 4:36:52 time: 0.6415 data_time: 0.0416 memory: 24011 grad_norm: 5.3534 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5545 loss: 0.5545 2022/09/05 21:42:04 - mmengine - INFO - Epoch(train) [74][140/940] lr: 1.0000e-03 eta: 4:36:39 time: 0.6448 data_time: 0.0412 memory: 24011 grad_norm: 5.3983 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5034 loss: 0.5034 2022/09/05 21:42:17 - mmengine - INFO - Epoch(train) [74][160/940] lr: 1.0000e-03 eta: 4:36:25 time: 0.6430 data_time: 0.0468 memory: 24011 grad_norm: 5.3816 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6137 loss: 0.6137 2022/09/05 21:42:31 - mmengine - INFO - Epoch(train) [74][180/940] lr: 1.0000e-03 eta: 4:36:12 time: 0.6920 data_time: 0.0794 memory: 24011 grad_norm: 5.5190 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6692 loss: 0.6692 2022/09/05 21:42:43 - mmengine - INFO - Epoch(train) [74][200/940] lr: 1.0000e-03 eta: 4:35:59 time: 0.5985 data_time: 0.0328 memory: 24011 grad_norm: 5.1732 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6017 loss: 0.6017 2022/09/05 21:42:57 - mmengine - INFO - Epoch(train) [74][220/940] lr: 1.0000e-03 eta: 4:35:46 time: 0.6725 data_time: 0.0382 memory: 24011 grad_norm: 5.3583 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5902 loss: 0.5902 2022/09/05 21:43:10 - mmengine - INFO - Epoch(train) [74][240/940] lr: 1.0000e-03 eta: 4:35:33 time: 0.6518 data_time: 0.0377 memory: 24011 grad_norm: 5.2382 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5547 loss: 0.5547 2022/09/05 21:43:23 - mmengine - INFO - Epoch(train) [74][260/940] lr: 1.0000e-03 eta: 4:35:19 time: 0.6560 data_time: 0.0454 memory: 24011 grad_norm: 5.6007 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6017 loss: 0.6017 2022/09/05 21:43:36 - mmengine - INFO - Epoch(train) [74][280/940] lr: 1.0000e-03 eta: 4:35:06 time: 0.6346 data_time: 0.0356 memory: 24011 grad_norm: 5.9469 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6743 loss: 0.6743 2022/09/05 21:43:50 - mmengine - INFO - Epoch(train) [74][300/940] lr: 1.0000e-03 eta: 4:34:53 time: 0.7048 data_time: 0.0508 memory: 24011 grad_norm: 5.1438 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5646 loss: 0.5646 2022/09/05 21:44:02 - mmengine - INFO - Epoch(train) [74][320/940] lr: 1.0000e-03 eta: 4:34:40 time: 0.6308 data_time: 0.0347 memory: 24011 grad_norm: 5.2884 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6620 loss: 0.6620 2022/09/05 21:44:16 - mmengine - INFO - Epoch(train) [74][340/940] lr: 1.0000e-03 eta: 4:34:27 time: 0.6669 data_time: 0.0471 memory: 24011 grad_norm: 5.3285 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5787 loss: 0.5787 2022/09/05 21:44:29 - mmengine - INFO - Epoch(train) [74][360/940] lr: 1.0000e-03 eta: 4:34:14 time: 0.6550 data_time: 0.0547 memory: 24011 grad_norm: 5.2857 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6146 loss: 0.6146 2022/09/05 21:44:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:44:41 - mmengine - INFO - Epoch(train) [74][380/940] lr: 1.0000e-03 eta: 4:34:00 time: 0.6293 data_time: 0.0408 memory: 24011 grad_norm: 5.2168 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6460 loss: 0.6460 2022/09/05 21:44:54 - mmengine - INFO - Epoch(train) [74][400/940] lr: 1.0000e-03 eta: 4:33:47 time: 0.6083 data_time: 0.0489 memory: 24011 grad_norm: 5.3990 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5931 loss: 0.5931 2022/09/05 21:45:07 - mmengine - INFO - Epoch(train) [74][420/940] lr: 1.0000e-03 eta: 4:33:34 time: 0.7019 data_time: 0.0553 memory: 24011 grad_norm: 5.4966 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5052 loss: 0.5052 2022/09/05 21:45:21 - mmengine - INFO - Epoch(train) [74][440/940] lr: 1.0000e-03 eta: 4:33:21 time: 0.6796 data_time: 0.0390 memory: 24011 grad_norm: 5.8060 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6309 loss: 0.6309 2022/09/05 21:45:34 - mmengine - INFO - Epoch(train) [74][460/940] lr: 1.0000e-03 eta: 4:33:08 time: 0.6373 data_time: 0.0533 memory: 24011 grad_norm: 5.5917 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6553 loss: 0.6553 2022/09/05 21:45:46 - mmengine - INFO - Epoch(train) [74][480/940] lr: 1.0000e-03 eta: 4:32:54 time: 0.6099 data_time: 0.0379 memory: 24011 grad_norm: 6.2914 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6985 loss: 0.6985 2022/09/05 21:45:59 - mmengine - INFO - Epoch(train) [74][500/940] lr: 1.0000e-03 eta: 4:32:41 time: 0.6487 data_time: 0.0405 memory: 24011 grad_norm: 5.0974 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5968 loss: 0.5968 2022/09/05 21:46:11 - mmengine - INFO - Epoch(train) [74][520/940] lr: 1.0000e-03 eta: 4:32:27 time: 0.6063 data_time: 0.0479 memory: 24011 grad_norm: 5.9111 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5568 loss: 0.5568 2022/09/05 21:46:24 - mmengine - INFO - Epoch(train) [74][540/940] lr: 1.0000e-03 eta: 4:32:14 time: 0.6617 data_time: 0.0366 memory: 24011 grad_norm: 5.4857 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6200 loss: 0.6200 2022/09/05 21:46:37 - mmengine - INFO - Epoch(train) [74][560/940] lr: 1.0000e-03 eta: 4:32:01 time: 0.6399 data_time: 0.0425 memory: 24011 grad_norm: 5.3890 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5508 loss: 0.5508 2022/09/05 21:46:51 - mmengine - INFO - Epoch(train) [74][580/940] lr: 1.0000e-03 eta: 4:31:48 time: 0.6782 data_time: 0.0368 memory: 24011 grad_norm: 5.7661 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.6535 loss: 0.6535 2022/09/05 21:47:04 - mmengine - INFO - Epoch(train) [74][600/940] lr: 1.0000e-03 eta: 4:31:35 time: 0.6861 data_time: 0.0560 memory: 24011 grad_norm: 6.8386 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6489 loss: 0.6489 2022/09/05 21:47:17 - mmengine - INFO - Epoch(train) [74][620/940] lr: 1.0000e-03 eta: 4:31:22 time: 0.6492 data_time: 0.0390 memory: 24011 grad_norm: 5.6972 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6661 loss: 0.6661 2022/09/05 21:47:30 - mmengine - INFO - Epoch(train) [74][640/940] lr: 1.0000e-03 eta: 4:31:09 time: 0.6259 data_time: 0.0422 memory: 24011 grad_norm: 5.2927 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6545 loss: 0.6545 2022/09/05 21:47:43 - mmengine - INFO - Epoch(train) [74][660/940] lr: 1.0000e-03 eta: 4:30:55 time: 0.6445 data_time: 0.0381 memory: 24011 grad_norm: 5.1841 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5981 loss: 0.5981 2022/09/05 21:47:56 - mmengine - INFO - Epoch(train) [74][680/940] lr: 1.0000e-03 eta: 4:30:42 time: 0.6575 data_time: 0.0422 memory: 24011 grad_norm: 5.6160 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5717 loss: 0.5717 2022/09/05 21:48:09 - mmengine - INFO - Epoch(train) [74][700/940] lr: 1.0000e-03 eta: 4:30:29 time: 0.6571 data_time: 0.0367 memory: 24011 grad_norm: 5.4239 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5874 loss: 0.5874 2022/09/05 21:48:23 - mmengine - INFO - Epoch(train) [74][720/940] lr: 1.0000e-03 eta: 4:30:16 time: 0.6844 data_time: 0.0447 memory: 24011 grad_norm: 5.4931 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6203 loss: 0.6203 2022/09/05 21:48:36 - mmengine - INFO - Epoch(train) [74][740/940] lr: 1.0000e-03 eta: 4:30:03 time: 0.6491 data_time: 0.0367 memory: 24011 grad_norm: 5.4151 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5827 loss: 0.5827 2022/09/05 21:48:49 - mmengine - INFO - Epoch(train) [74][760/940] lr: 1.0000e-03 eta: 4:29:50 time: 0.6456 data_time: 0.0385 memory: 24011 grad_norm: 5.8097 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6549 loss: 0.6549 2022/09/05 21:49:02 - mmengine - INFO - Epoch(train) [74][780/940] lr: 1.0000e-03 eta: 4:29:36 time: 0.6407 data_time: 0.0461 memory: 24011 grad_norm: 5.1110 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6694 loss: 0.6694 2022/09/05 21:49:14 - mmengine - INFO - Epoch(train) [74][800/940] lr: 1.0000e-03 eta: 4:29:23 time: 0.6339 data_time: 0.0403 memory: 24011 grad_norm: 5.1547 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5426 loss: 0.5426 2022/09/05 21:49:27 - mmengine - INFO - Epoch(train) [74][820/940] lr: 1.0000e-03 eta: 4:29:10 time: 0.6196 data_time: 0.0509 memory: 24011 grad_norm: 5.3896 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6551 loss: 0.6551 2022/09/05 21:49:40 - mmengine - INFO - Epoch(train) [74][840/940] lr: 1.0000e-03 eta: 4:28:56 time: 0.6459 data_time: 0.0466 memory: 24011 grad_norm: 5.4277 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5290 loss: 0.5290 2022/09/05 21:49:53 - mmengine - INFO - Epoch(train) [74][860/940] lr: 1.0000e-03 eta: 4:28:43 time: 0.6732 data_time: 0.0395 memory: 24011 grad_norm: 5.0933 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6229 loss: 0.6229 2022/09/05 21:50:05 - mmengine - INFO - Epoch(train) [74][880/940] lr: 1.0000e-03 eta: 4:28:30 time: 0.6101 data_time: 0.0382 memory: 24011 grad_norm: 5.1792 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5879 loss: 0.5879 2022/09/05 21:50:18 - mmengine - INFO - Epoch(train) [74][900/940] lr: 1.0000e-03 eta: 4:28:16 time: 0.6277 data_time: 0.0411 memory: 24011 grad_norm: 4.9078 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6011 loss: 0.6011 2022/09/05 21:50:31 - mmengine - INFO - Epoch(train) [74][920/940] lr: 1.0000e-03 eta: 4:28:03 time: 0.6370 data_time: 0.0415 memory: 24011 grad_norm: 5.8812 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5757 loss: 0.5757 2022/09/05 21:50:42 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:50:42 - mmengine - INFO - Epoch(train) [74][940/940] lr: 1.0000e-03 eta: 4:27:49 time: 0.5693 data_time: 0.0284 memory: 24011 grad_norm: 5.4804 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.6102 loss: 0.6102 2022/09/05 21:50:56 - mmengine - INFO - Epoch(val) [74][20/78] eta: 0:00:40 time: 0.6925 data_time: 0.5333 memory: 3625 2022/09/05 21:51:05 - mmengine - INFO - Epoch(val) [74][40/78] eta: 0:00:17 time: 0.4608 data_time: 0.3025 memory: 3625 2022/09/05 21:51:18 - mmengine - INFO - Epoch(val) [74][60/78] eta: 0:00:11 time: 0.6570 data_time: 0.4989 memory: 3625 2022/09/05 21:51:29 - mmengine - INFO - Epoch(val) [74][78/78] acc/top1: 0.7392 acc/top5: 0.9068 acc/mean1: 0.7391 2022/09/05 21:51:47 - mmengine - INFO - Epoch(train) [75][20/940] lr: 1.0000e-03 eta: 4:27:38 time: 0.9045 data_time: 0.2659 memory: 24011 grad_norm: 5.1560 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6228 loss: 0.6228 2022/09/05 21:52:00 - mmengine - INFO - Epoch(train) [75][40/940] lr: 1.0000e-03 eta: 4:27:25 time: 0.6562 data_time: 0.0488 memory: 24011 grad_norm: 5.3849 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5845 loss: 0.5845 2022/09/05 21:52:13 - mmengine - INFO - Epoch(train) [75][60/940] lr: 1.0000e-03 eta: 4:27:12 time: 0.6424 data_time: 0.0462 memory: 24011 grad_norm: 6.0401 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5843 loss: 0.5843 2022/09/05 21:52:26 - mmengine - INFO - Epoch(train) [75][80/940] lr: 1.0000e-03 eta: 4:26:58 time: 0.6276 data_time: 0.0318 memory: 24011 grad_norm: 5.3409 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5805 loss: 0.5805 2022/09/05 21:52:39 - mmengine - INFO - Epoch(train) [75][100/940] lr: 1.0000e-03 eta: 4:26:45 time: 0.6752 data_time: 0.0492 memory: 24011 grad_norm: 5.3212 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5503 loss: 0.5503 2022/09/05 21:52:52 - mmengine - INFO - Epoch(train) [75][120/940] lr: 1.0000e-03 eta: 4:26:32 time: 0.6470 data_time: 0.0345 memory: 24011 grad_norm: 5.5522 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6753 loss: 0.6753 2022/09/05 21:53:05 - mmengine - INFO - Epoch(train) [75][140/940] lr: 1.0000e-03 eta: 4:26:19 time: 0.6588 data_time: 0.0438 memory: 24011 grad_norm: 5.8452 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5885 loss: 0.5885 2022/09/05 21:53:18 - mmengine - INFO - Epoch(train) [75][160/940] lr: 1.0000e-03 eta: 4:26:05 time: 0.6263 data_time: 0.0354 memory: 24011 grad_norm: 5.2186 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5903 loss: 0.5903 2022/09/05 21:53:30 - mmengine - INFO - Epoch(train) [75][180/940] lr: 1.0000e-03 eta: 4:25:52 time: 0.6368 data_time: 0.0466 memory: 24011 grad_norm: 6.0365 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5531 loss: 0.5531 2022/09/05 21:53:43 - mmengine - INFO - Epoch(train) [75][200/940] lr: 1.0000e-03 eta: 4:25:39 time: 0.6200 data_time: 0.0320 memory: 24011 grad_norm: 5.5663 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6473 loss: 0.6473 2022/09/05 21:53:56 - mmengine - INFO - Epoch(train) [75][220/940] lr: 1.0000e-03 eta: 4:25:26 time: 0.6612 data_time: 0.0421 memory: 24011 grad_norm: 5.0675 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.6172 loss: 0.6172 2022/09/05 21:54:09 - mmengine - INFO - Epoch(train) [75][240/940] lr: 1.0000e-03 eta: 4:25:12 time: 0.6453 data_time: 0.0381 memory: 24011 grad_norm: 5.6011 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4637 loss: 0.4637 2022/09/05 21:54:24 - mmengine - INFO - Epoch(train) [75][260/940] lr: 1.0000e-03 eta: 4:25:00 time: 0.7373 data_time: 0.0405 memory: 24011 grad_norm: 5.0864 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6722 loss: 0.6722 2022/09/05 21:54:37 - mmengine - INFO - Epoch(train) [75][280/940] lr: 1.0000e-03 eta: 4:24:46 time: 0.6424 data_time: 0.0335 memory: 24011 grad_norm: 5.5526 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5554 loss: 0.5554 2022/09/05 21:54:49 - mmengine - INFO - Epoch(train) [75][300/940] lr: 1.0000e-03 eta: 4:24:33 time: 0.6470 data_time: 0.0428 memory: 24011 grad_norm: 5.1787 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5786 loss: 0.5786 2022/09/05 21:55:02 - mmengine - INFO - Epoch(train) [75][320/940] lr: 1.0000e-03 eta: 4:24:20 time: 0.6331 data_time: 0.0410 memory: 24011 grad_norm: 5.2234 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5331 loss: 0.5331 2022/09/05 21:55:15 - mmengine - INFO - Epoch(train) [75][340/940] lr: 1.0000e-03 eta: 4:24:07 time: 0.6463 data_time: 0.0387 memory: 24011 grad_norm: 5.7500 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5741 loss: 0.5741 2022/09/05 21:55:28 - mmengine - INFO - Epoch(train) [75][360/940] lr: 1.0000e-03 eta: 4:23:53 time: 0.6491 data_time: 0.0367 memory: 24011 grad_norm: 5.3179 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6395 loss: 0.6395 2022/09/05 21:55:41 - mmengine - INFO - Epoch(train) [75][380/940] lr: 1.0000e-03 eta: 4:23:40 time: 0.6674 data_time: 0.0597 memory: 24011 grad_norm: 5.4610 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5560 loss: 0.5560 2022/09/05 21:55:54 - mmengine - INFO - Epoch(train) [75][400/940] lr: 1.0000e-03 eta: 4:23:27 time: 0.6127 data_time: 0.0381 memory: 24011 grad_norm: 5.6758 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6030 loss: 0.6030 2022/09/05 21:56:07 - mmengine - INFO - Epoch(train) [75][420/940] lr: 1.0000e-03 eta: 4:23:14 time: 0.6555 data_time: 0.0338 memory: 24011 grad_norm: 5.4805 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5389 loss: 0.5389 2022/09/05 21:56:20 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 21:56:20 - mmengine - INFO - Epoch(train) [75][440/940] lr: 1.0000e-03 eta: 4:23:00 time: 0.6349 data_time: 0.0368 memory: 24011 grad_norm: 5.8770 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5605 loss: 0.5605 2022/09/05 21:56:33 - mmengine - INFO - Epoch(train) [75][460/940] lr: 1.0000e-03 eta: 4:22:47 time: 0.6569 data_time: 0.0419 memory: 24011 grad_norm: 5.3846 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.5702 loss: 0.5702 2022/09/05 21:56:45 - mmengine - INFO - Epoch(train) [75][480/940] lr: 1.0000e-03 eta: 4:22:34 time: 0.6222 data_time: 0.0349 memory: 24011 grad_norm: 6.1610 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6263 loss: 0.6263 2022/09/05 21:56:58 - mmengine - INFO - Epoch(train) [75][500/940] lr: 1.0000e-03 eta: 4:22:21 time: 0.6524 data_time: 0.0409 memory: 24011 grad_norm: 4.9650 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5364 loss: 0.5364 2022/09/05 21:57:12 - mmengine - INFO - Epoch(train) [75][520/940] lr: 1.0000e-03 eta: 4:22:08 time: 0.6660 data_time: 0.0389 memory: 24011 grad_norm: 5.7718 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5951 loss: 0.5951 2022/09/05 21:57:24 - mmengine - INFO - Epoch(train) [75][540/940] lr: 1.0000e-03 eta: 4:21:54 time: 0.6361 data_time: 0.0587 memory: 24011 grad_norm: 5.0126 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5455 loss: 0.5455 2022/09/05 21:57:37 - mmengine - INFO - Epoch(train) [75][560/940] lr: 1.0000e-03 eta: 4:21:41 time: 0.6316 data_time: 0.0345 memory: 24011 grad_norm: 5.2341 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5904 loss: 0.5904 2022/09/05 21:57:51 - mmengine - INFO - Epoch(train) [75][580/940] lr: 1.0000e-03 eta: 4:21:28 time: 0.6820 data_time: 0.0381 memory: 24011 grad_norm: 5.2128 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5683 loss: 0.5683 2022/09/05 21:58:03 - mmengine - INFO - Epoch(train) [75][600/940] lr: 1.0000e-03 eta: 4:21:15 time: 0.6391 data_time: 0.0342 memory: 24011 grad_norm: 5.1974 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5797 loss: 0.5797 2022/09/05 21:58:16 - mmengine - INFO - Epoch(train) [75][620/940] lr: 1.0000e-03 eta: 4:21:02 time: 0.6560 data_time: 0.0370 memory: 24011 grad_norm: 5.0741 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5224 loss: 0.5224 2022/09/05 21:58:29 - mmengine - INFO - Epoch(train) [75][640/940] lr: 1.0000e-03 eta: 4:20:48 time: 0.6500 data_time: 0.0371 memory: 24011 grad_norm: 5.2862 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5557 loss: 0.5557 2022/09/05 21:58:43 - mmengine - INFO - Epoch(train) [75][660/940] lr: 1.0000e-03 eta: 4:20:35 time: 0.6666 data_time: 0.0398 memory: 24011 grad_norm: 5.4455 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5394 loss: 0.5394 2022/09/05 21:58:56 - mmengine - INFO - Epoch(train) [75][680/940] lr: 1.0000e-03 eta: 4:20:22 time: 0.6509 data_time: 0.0402 memory: 24011 grad_norm: 5.4922 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6108 loss: 0.6108 2022/09/05 21:59:10 - mmengine - INFO - Epoch(train) [75][700/940] lr: 1.0000e-03 eta: 4:20:09 time: 0.6910 data_time: 0.0401 memory: 24011 grad_norm: 5.1345 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5480 loss: 0.5480 2022/09/05 21:59:22 - mmengine - INFO - Epoch(train) [75][720/940] lr: 1.0000e-03 eta: 4:19:56 time: 0.6140 data_time: 0.0584 memory: 24011 grad_norm: 5.7792 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4926 loss: 0.4926 2022/09/05 21:59:34 - mmengine - INFO - Epoch(train) [75][740/940] lr: 1.0000e-03 eta: 4:19:42 time: 0.6128 data_time: 0.0401 memory: 24011 grad_norm: 5.0021 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5945 loss: 0.5945 2022/09/05 21:59:47 - mmengine - INFO - Epoch(train) [75][760/940] lr: 1.0000e-03 eta: 4:19:29 time: 0.6198 data_time: 0.0402 memory: 24011 grad_norm: 5.9493 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6176 loss: 0.6176 2022/09/05 22:00:00 - mmengine - INFO - Epoch(train) [75][780/940] lr: 1.0000e-03 eta: 4:19:16 time: 0.6793 data_time: 0.0458 memory: 24011 grad_norm: 5.3177 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6432 loss: 0.6432 2022/09/05 22:00:13 - mmengine - INFO - Epoch(train) [75][800/940] lr: 1.0000e-03 eta: 4:19:03 time: 0.6540 data_time: 0.0399 memory: 24011 grad_norm: 5.7764 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.6431 loss: 0.6431 2022/09/05 22:00:26 - mmengine - INFO - Epoch(train) [75][820/940] lr: 1.0000e-03 eta: 4:18:49 time: 0.6364 data_time: 0.0427 memory: 24011 grad_norm: 5.2480 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6146 loss: 0.6146 2022/09/05 22:00:39 - mmengine - INFO - Epoch(train) [75][840/940] lr: 1.0000e-03 eta: 4:18:36 time: 0.6351 data_time: 0.0378 memory: 24011 grad_norm: 6.0159 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5760 loss: 0.5760 2022/09/05 22:00:53 - mmengine - INFO - Epoch(train) [75][860/940] lr: 1.0000e-03 eta: 4:18:23 time: 0.6981 data_time: 0.0474 memory: 24011 grad_norm: 5.2450 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5669 loss: 0.5669 2022/09/05 22:01:05 - mmengine - INFO - Epoch(train) [75][880/940] lr: 1.0000e-03 eta: 4:18:10 time: 0.6249 data_time: 0.0478 memory: 24011 grad_norm: 5.2298 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5386 loss: 0.5386 2022/09/05 22:01:18 - mmengine - INFO - Epoch(train) [75][900/940] lr: 1.0000e-03 eta: 4:17:57 time: 0.6307 data_time: 0.0373 memory: 24011 grad_norm: 9.8072 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5710 loss: 0.5710 2022/09/05 22:01:31 - mmengine - INFO - Epoch(train) [75][920/940] lr: 1.0000e-03 eta: 4:17:43 time: 0.6441 data_time: 0.0453 memory: 24011 grad_norm: 5.4852 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5908 loss: 0.5908 2022/09/05 22:01:42 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:01:42 - mmengine - INFO - Epoch(train) [75][940/940] lr: 1.0000e-03 eta: 4:17:30 time: 0.5814 data_time: 0.0279 memory: 24011 grad_norm: 6.5524 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 0.6550 loss: 0.6550 2022/09/05 22:01:42 - mmengine - INFO - Saving checkpoint at 75 epochs 2022/09/05 22:02:02 - mmengine - INFO - Epoch(val) [75][20/78] eta: 0:00:41 time: 0.7106 data_time: 0.5543 memory: 3625 2022/09/05 22:02:12 - mmengine - INFO - Epoch(val) [75][40/78] eta: 0:00:17 time: 0.4733 data_time: 0.3163 memory: 3625 2022/09/05 22:02:24 - mmengine - INFO - Epoch(val) [75][60/78] eta: 0:00:11 time: 0.6282 data_time: 0.4669 memory: 3625 2022/09/05 22:02:33 - mmengine - INFO - Epoch(val) [75][78/78] acc/top1: 0.7352 acc/top5: 0.9075 acc/mean1: 0.7351 2022/09/05 22:02:51 - mmengine - INFO - Epoch(train) [76][20/940] lr: 1.0000e-03 eta: 4:17:18 time: 0.8885 data_time: 0.2822 memory: 24011 grad_norm: 5.4213 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6231 loss: 0.6231 2022/09/05 22:03:04 - mmengine - INFO - Epoch(train) [76][40/940] lr: 1.0000e-03 eta: 4:17:05 time: 0.6464 data_time: 0.0408 memory: 24011 grad_norm: 5.4200 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5481 loss: 0.5481 2022/09/05 22:03:18 - mmengine - INFO - Epoch(train) [76][60/940] lr: 1.0000e-03 eta: 4:16:52 time: 0.6823 data_time: 0.0379 memory: 24011 grad_norm: 5.4404 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5742 loss: 0.5742 2022/09/05 22:03:31 - mmengine - INFO - Epoch(train) [76][80/940] lr: 1.0000e-03 eta: 4:16:39 time: 0.6586 data_time: 0.0399 memory: 24011 grad_norm: 5.4166 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5335 loss: 0.5335 2022/09/05 22:03:44 - mmengine - INFO - Epoch(train) [76][100/940] lr: 1.0000e-03 eta: 4:16:25 time: 0.6308 data_time: 0.0417 memory: 24011 grad_norm: 5.9734 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5816 loss: 0.5816 2022/09/05 22:03:57 - mmengine - INFO - Epoch(train) [76][120/940] lr: 1.0000e-03 eta: 4:16:12 time: 0.6618 data_time: 0.0334 memory: 24011 grad_norm: 5.5089 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5502 loss: 0.5502 2022/09/05 22:04:10 - mmengine - INFO - Epoch(train) [76][140/940] lr: 1.0000e-03 eta: 4:15:59 time: 0.6376 data_time: 0.0411 memory: 24011 grad_norm: 5.2721 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6302 loss: 0.6302 2022/09/05 22:04:22 - mmengine - INFO - Epoch(train) [76][160/940] lr: 1.0000e-03 eta: 4:15:45 time: 0.6118 data_time: 0.0376 memory: 24011 grad_norm: 5.2737 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5796 loss: 0.5796 2022/09/05 22:04:35 - mmengine - INFO - Epoch(train) [76][180/940] lr: 1.0000e-03 eta: 4:15:32 time: 0.6698 data_time: 0.0523 memory: 24011 grad_norm: 5.1520 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5320 loss: 0.5320 2022/09/05 22:04:48 - mmengine - INFO - Epoch(train) [76][200/940] lr: 1.0000e-03 eta: 4:15:19 time: 0.6509 data_time: 0.0588 memory: 24011 grad_norm: 5.1682 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5535 loss: 0.5535 2022/09/05 22:05:02 - mmengine - INFO - Epoch(train) [76][220/940] lr: 1.0000e-03 eta: 4:15:06 time: 0.6937 data_time: 0.0473 memory: 24011 grad_norm: 5.3745 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6472 loss: 0.6472 2022/09/05 22:05:15 - mmengine - INFO - Epoch(train) [76][240/940] lr: 1.0000e-03 eta: 4:14:53 time: 0.6259 data_time: 0.0377 memory: 24011 grad_norm: 5.8867 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5129 loss: 0.5129 2022/09/05 22:05:27 - mmengine - INFO - Epoch(train) [76][260/940] lr: 1.0000e-03 eta: 4:14:40 time: 0.6372 data_time: 0.0308 memory: 24011 grad_norm: 5.5610 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5835 loss: 0.5835 2022/09/05 22:05:41 - mmengine - INFO - Epoch(train) [76][280/940] lr: 1.0000e-03 eta: 4:14:26 time: 0.6541 data_time: 0.0419 memory: 24011 grad_norm: 5.3923 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5974 loss: 0.5974 2022/09/05 22:05:54 - mmengine - INFO - Epoch(train) [76][300/940] lr: 1.0000e-03 eta: 4:14:13 time: 0.6526 data_time: 0.0398 memory: 24011 grad_norm: 5.6964 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6240 loss: 0.6240 2022/09/05 22:06:06 - mmengine - INFO - Epoch(train) [76][320/940] lr: 1.0000e-03 eta: 4:14:00 time: 0.6327 data_time: 0.0582 memory: 24011 grad_norm: 6.1815 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.7754 loss: 0.7754 2022/09/05 22:06:19 - mmengine - INFO - Epoch(train) [76][340/940] lr: 1.0000e-03 eta: 4:13:47 time: 0.6394 data_time: 0.0420 memory: 24011 grad_norm: 5.1122 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5830 loss: 0.5830 2022/09/05 22:06:32 - mmengine - INFO - Epoch(train) [76][360/940] lr: 1.0000e-03 eta: 4:13:34 time: 0.6513 data_time: 0.0382 memory: 24011 grad_norm: 5.5936 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6096 loss: 0.6096 2022/09/05 22:06:45 - mmengine - INFO - Epoch(train) [76][380/940] lr: 1.0000e-03 eta: 4:13:20 time: 0.6209 data_time: 0.0395 memory: 24011 grad_norm: 5.1500 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5655 loss: 0.5655 2022/09/05 22:06:57 - mmengine - INFO - Epoch(train) [76][400/940] lr: 1.0000e-03 eta: 4:13:07 time: 0.6462 data_time: 0.0398 memory: 24011 grad_norm: 5.1721 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5534 loss: 0.5534 2022/09/05 22:07:10 - mmengine - INFO - Epoch(train) [76][420/940] lr: 1.0000e-03 eta: 4:12:54 time: 0.6207 data_time: 0.0420 memory: 24011 grad_norm: 5.3771 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6668 loss: 0.6668 2022/09/05 22:07:23 - mmengine - INFO - Epoch(train) [76][440/940] lr: 1.0000e-03 eta: 4:12:40 time: 0.6488 data_time: 0.0385 memory: 24011 grad_norm: 5.0783 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5568 loss: 0.5568 2022/09/05 22:07:36 - mmengine - INFO - Epoch(train) [76][460/940] lr: 1.0000e-03 eta: 4:12:27 time: 0.6806 data_time: 0.0413 memory: 24011 grad_norm: 5.4179 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5651 loss: 0.5651 2022/09/05 22:07:49 - mmengine - INFO - Epoch(train) [76][480/940] lr: 1.0000e-03 eta: 4:12:14 time: 0.6310 data_time: 0.0470 memory: 24011 grad_norm: 6.4016 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.5455 loss: 0.5455 2022/09/05 22:08:03 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:08:03 - mmengine - INFO - Epoch(train) [76][500/940] lr: 1.0000e-03 eta: 4:12:01 time: 0.6811 data_time: 0.0456 memory: 24011 grad_norm: 5.1081 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5512 loss: 0.5512 2022/09/05 22:08:15 - mmengine - INFO - Epoch(train) [76][520/940] lr: 1.0000e-03 eta: 4:11:48 time: 0.6118 data_time: 0.0456 memory: 24011 grad_norm: 5.5844 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6706 loss: 0.6706 2022/09/05 22:08:28 - mmengine - INFO - Epoch(train) [76][540/940] lr: 1.0000e-03 eta: 4:11:34 time: 0.6497 data_time: 0.0465 memory: 24011 grad_norm: 5.2083 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5558 loss: 0.5558 2022/09/05 22:08:41 - mmengine - INFO - Epoch(train) [76][560/940] lr: 1.0000e-03 eta: 4:11:21 time: 0.6719 data_time: 0.0340 memory: 24011 grad_norm: 5.3553 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6260 loss: 0.6260 2022/09/05 22:08:54 - mmengine - INFO - Epoch(train) [76][580/940] lr: 1.0000e-03 eta: 4:11:08 time: 0.6318 data_time: 0.0452 memory: 24011 grad_norm: 5.3922 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.6506 loss: 0.6506 2022/09/05 22:09:07 - mmengine - INFO - Epoch(train) [76][600/940] lr: 1.0000e-03 eta: 4:10:55 time: 0.6696 data_time: 0.0387 memory: 24011 grad_norm: 4.9277 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5190 loss: 0.5190 2022/09/05 22:09:20 - mmengine - INFO - Epoch(train) [76][620/940] lr: 1.0000e-03 eta: 4:10:42 time: 0.6487 data_time: 0.0385 memory: 24011 grad_norm: 5.0995 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5211 loss: 0.5211 2022/09/05 22:09:33 - mmengine - INFO - Epoch(train) [76][640/940] lr: 1.0000e-03 eta: 4:10:29 time: 0.6488 data_time: 0.0355 memory: 24011 grad_norm: 5.3812 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.7322 loss: 0.7322 2022/09/05 22:09:46 - mmengine - INFO - Epoch(train) [76][660/940] lr: 1.0000e-03 eta: 4:10:15 time: 0.6254 data_time: 0.0430 memory: 24011 grad_norm: 5.4374 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5747 loss: 0.5747 2022/09/05 22:09:59 - mmengine - INFO - Epoch(train) [76][680/940] lr: 1.0000e-03 eta: 4:10:02 time: 0.6462 data_time: 0.0321 memory: 24011 grad_norm: 5.0801 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5338 loss: 0.5338 2022/09/05 22:10:12 - mmengine - INFO - Epoch(train) [76][700/940] lr: 1.0000e-03 eta: 4:09:49 time: 0.6568 data_time: 0.0404 memory: 24011 grad_norm: 5.6949 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5764 loss: 0.5764 2022/09/05 22:10:25 - mmengine - INFO - Epoch(train) [76][720/940] lr: 1.0000e-03 eta: 4:09:36 time: 0.6590 data_time: 0.0482 memory: 24011 grad_norm: 5.6211 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5179 loss: 0.5179 2022/09/05 22:10:38 - mmengine - INFO - Epoch(train) [76][740/940] lr: 1.0000e-03 eta: 4:09:22 time: 0.6405 data_time: 0.0401 memory: 24011 grad_norm: 5.4719 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5657 loss: 0.5657 2022/09/05 22:10:51 - mmengine - INFO - Epoch(train) [76][760/940] lr: 1.0000e-03 eta: 4:09:09 time: 0.6281 data_time: 0.0466 memory: 24011 grad_norm: 5.3060 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6466 loss: 0.6466 2022/09/05 22:11:03 - mmengine - INFO - Epoch(train) [76][780/940] lr: 1.0000e-03 eta: 4:08:56 time: 0.6391 data_time: 0.0454 memory: 24011 grad_norm: 5.2238 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6101 loss: 0.6101 2022/09/05 22:11:17 - mmengine - INFO - Epoch(train) [76][800/940] lr: 1.0000e-03 eta: 4:08:43 time: 0.6719 data_time: 0.0372 memory: 24011 grad_norm: 6.5337 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6654 loss: 0.6654 2022/09/05 22:11:29 - mmengine - INFO - Epoch(train) [76][820/940] lr: 1.0000e-03 eta: 4:08:29 time: 0.6279 data_time: 0.0380 memory: 24011 grad_norm: 5.1879 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5931 loss: 0.5931 2022/09/05 22:11:44 - mmengine - INFO - Epoch(train) [76][840/940] lr: 1.0000e-03 eta: 4:08:17 time: 0.7147 data_time: 0.0401 memory: 24011 grad_norm: 5.6256 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6174 loss: 0.6174 2022/09/05 22:11:56 - mmengine - INFO - Epoch(train) [76][860/940] lr: 1.0000e-03 eta: 4:08:03 time: 0.6121 data_time: 0.0360 memory: 24011 grad_norm: 5.5236 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6357 loss: 0.6357 2022/09/05 22:12:09 - mmengine - INFO - Epoch(train) [76][880/940] lr: 1.0000e-03 eta: 4:07:50 time: 0.6690 data_time: 0.0434 memory: 24011 grad_norm: 5.6635 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6217 loss: 0.6217 2022/09/05 22:12:22 - mmengine - INFO - Epoch(train) [76][900/940] lr: 1.0000e-03 eta: 4:07:37 time: 0.6251 data_time: 0.0286 memory: 24011 grad_norm: 5.5312 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6591 loss: 0.6591 2022/09/05 22:12:34 - mmengine - INFO - Epoch(train) [76][920/940] lr: 1.0000e-03 eta: 4:07:23 time: 0.6075 data_time: 0.0458 memory: 24011 grad_norm: 7.0561 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6884 loss: 0.6884 2022/09/05 22:12:45 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:12:45 - mmengine - INFO - Epoch(train) [76][940/940] lr: 1.0000e-03 eta: 4:07:09 time: 0.5491 data_time: 0.0278 memory: 24011 grad_norm: 5.4328 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5642 loss: 0.5642 2022/09/05 22:12:59 - mmengine - INFO - Epoch(val) [76][20/78] eta: 0:00:40 time: 0.6967 data_time: 0.5334 memory: 3625 2022/09/05 22:13:08 - mmengine - INFO - Epoch(val) [76][40/78] eta: 0:00:17 time: 0.4514 data_time: 0.2952 memory: 3625 2022/09/05 22:13:21 - mmengine - INFO - Epoch(val) [76][60/78] eta: 0:00:11 time: 0.6483 data_time: 0.4899 memory: 3625 2022/09/05 22:13:31 - mmengine - INFO - Epoch(val) [76][78/78] acc/top1: 0.7368 acc/top5: 0.9049 acc/mean1: 0.7367 2022/09/05 22:13:51 - mmengine - INFO - Epoch(train) [77][20/940] lr: 1.0000e-03 eta: 4:06:58 time: 0.9435 data_time: 0.3044 memory: 24011 grad_norm: 5.6068 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5824 loss: 0.5824 2022/09/05 22:14:03 - mmengine - INFO - Epoch(train) [77][40/940] lr: 1.0000e-03 eta: 4:06:45 time: 0.6221 data_time: 0.0490 memory: 24011 grad_norm: 4.8058 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5888 loss: 0.5888 2022/09/05 22:14:17 - mmengine - INFO - Epoch(train) [77][60/940] lr: 1.0000e-03 eta: 4:06:32 time: 0.7009 data_time: 0.0532 memory: 24011 grad_norm: 5.1101 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6517 loss: 0.6517 2022/09/05 22:14:29 - mmengine - INFO - Epoch(train) [77][80/940] lr: 1.0000e-03 eta: 4:06:19 time: 0.6261 data_time: 0.0366 memory: 24011 grad_norm: 5.4984 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6294 loss: 0.6294 2022/09/05 22:14:42 - mmengine - INFO - Epoch(train) [77][100/940] lr: 1.0000e-03 eta: 4:06:05 time: 0.6466 data_time: 0.0515 memory: 24011 grad_norm: 5.2731 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5662 loss: 0.5662 2022/09/05 22:14:56 - mmengine - INFO - Epoch(train) [77][120/940] lr: 1.0000e-03 eta: 4:05:52 time: 0.6857 data_time: 0.0372 memory: 24011 grad_norm: 5.3117 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5155 loss: 0.5155 2022/09/05 22:15:08 - mmengine - INFO - Epoch(train) [77][140/940] lr: 1.0000e-03 eta: 4:05:39 time: 0.6017 data_time: 0.0363 memory: 24011 grad_norm: 5.1301 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5800 loss: 0.5800 2022/09/05 22:15:21 - mmengine - INFO - Epoch(train) [77][160/940] lr: 1.0000e-03 eta: 4:05:26 time: 0.6587 data_time: 0.0395 memory: 24011 grad_norm: 5.7340 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6165 loss: 0.6165 2022/09/05 22:15:34 - mmengine - INFO - Epoch(train) [77][180/940] lr: 1.0000e-03 eta: 4:05:12 time: 0.6445 data_time: 0.0399 memory: 24011 grad_norm: 5.1884 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5843 loss: 0.5843 2022/09/05 22:15:47 - mmengine - INFO - Epoch(train) [77][200/940] lr: 1.0000e-03 eta: 4:04:59 time: 0.6501 data_time: 0.0417 memory: 24011 grad_norm: 5.0934 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5441 loss: 0.5441 2022/09/05 22:16:01 - mmengine - INFO - Epoch(train) [77][220/940] lr: 1.0000e-03 eta: 4:04:46 time: 0.6939 data_time: 0.0388 memory: 24011 grad_norm: 5.3795 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5560 loss: 0.5560 2022/09/05 22:16:14 - mmengine - INFO - Epoch(train) [77][240/940] lr: 1.0000e-03 eta: 4:04:33 time: 0.6235 data_time: 0.0381 memory: 24011 grad_norm: 5.2511 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6217 loss: 0.6217 2022/09/05 22:16:26 - mmengine - INFO - Epoch(train) [77][260/940] lr: 1.0000e-03 eta: 4:04:20 time: 0.6012 data_time: 0.0428 memory: 24011 grad_norm: 5.2076 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6035 loss: 0.6035 2022/09/05 22:16:39 - mmengine - INFO - Epoch(train) [77][280/940] lr: 1.0000e-03 eta: 4:04:06 time: 0.6645 data_time: 0.0348 memory: 24011 grad_norm: 5.3429 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4929 loss: 0.4929 2022/09/05 22:16:51 - mmengine - INFO - Epoch(train) [77][300/940] lr: 1.0000e-03 eta: 4:03:53 time: 0.6265 data_time: 0.0434 memory: 24011 grad_norm: 5.2332 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6110 loss: 0.6110 2022/09/05 22:17:04 - mmengine - INFO - Epoch(train) [77][320/940] lr: 1.0000e-03 eta: 4:03:40 time: 0.6417 data_time: 0.0373 memory: 24011 grad_norm: 5.3727 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6313 loss: 0.6313 2022/09/05 22:17:17 - mmengine - INFO - Epoch(train) [77][340/940] lr: 1.0000e-03 eta: 4:03:27 time: 0.6344 data_time: 0.0402 memory: 24011 grad_norm: 5.1565 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5839 loss: 0.5839 2022/09/05 22:17:30 - mmengine - INFO - Epoch(train) [77][360/940] lr: 1.0000e-03 eta: 4:03:13 time: 0.6396 data_time: 0.0433 memory: 24011 grad_norm: 5.2751 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5523 loss: 0.5523 2022/09/05 22:17:44 - mmengine - INFO - Epoch(train) [77][380/940] lr: 1.0000e-03 eta: 4:03:00 time: 0.6901 data_time: 0.0368 memory: 24011 grad_norm: 5.1312 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5515 loss: 0.5515 2022/09/05 22:17:56 - mmengine - INFO - Epoch(train) [77][400/940] lr: 1.0000e-03 eta: 4:02:47 time: 0.6283 data_time: 0.0338 memory: 24011 grad_norm: 5.9636 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5607 loss: 0.5607 2022/09/05 22:18:09 - mmengine - INFO - Epoch(train) [77][420/940] lr: 1.0000e-03 eta: 4:02:34 time: 0.6486 data_time: 0.0400 memory: 24011 grad_norm: 6.4343 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.5747 loss: 0.5747 2022/09/05 22:18:23 - mmengine - INFO - Epoch(train) [77][440/940] lr: 1.0000e-03 eta: 4:02:21 time: 0.6960 data_time: 0.0542 memory: 24011 grad_norm: 5.3017 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5431 loss: 0.5431 2022/09/05 22:18:36 - mmengine - INFO - Epoch(train) [77][460/940] lr: 1.0000e-03 eta: 4:02:08 time: 0.6388 data_time: 0.0434 memory: 24011 grad_norm: 5.5113 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5705 loss: 0.5705 2022/09/05 22:18:49 - mmengine - INFO - Epoch(train) [77][480/940] lr: 1.0000e-03 eta: 4:01:54 time: 0.6461 data_time: 0.0645 memory: 24011 grad_norm: 6.2023 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5875 loss: 0.5875 2022/09/05 22:19:02 - mmengine - INFO - Epoch(train) [77][500/940] lr: 1.0000e-03 eta: 4:01:41 time: 0.6519 data_time: 0.0362 memory: 24011 grad_norm: 6.7084 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6012 loss: 0.6012 2022/09/05 22:19:14 - mmengine - INFO - Epoch(train) [77][520/940] lr: 1.0000e-03 eta: 4:01:28 time: 0.6275 data_time: 0.0468 memory: 24011 grad_norm: 5.2038 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6147 loss: 0.6147 2022/09/05 22:19:28 - mmengine - INFO - Epoch(train) [77][540/940] lr: 1.0000e-03 eta: 4:01:15 time: 0.6714 data_time: 0.0372 memory: 24011 grad_norm: 6.1463 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5326 loss: 0.5326 2022/09/05 22:19:40 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:19:40 - mmengine - INFO - Epoch(train) [77][560/940] lr: 1.0000e-03 eta: 4:01:01 time: 0.6093 data_time: 0.0369 memory: 24011 grad_norm: 5.1170 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.6075 loss: 0.6075 2022/09/05 22:19:54 - mmengine - INFO - Epoch(train) [77][580/940] lr: 1.0000e-03 eta: 4:00:48 time: 0.6921 data_time: 0.0395 memory: 24011 grad_norm: 5.0565 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5402 loss: 0.5402 2022/09/05 22:20:07 - mmengine - INFO - Epoch(train) [77][600/940] lr: 1.0000e-03 eta: 4:00:35 time: 0.6423 data_time: 0.0372 memory: 24011 grad_norm: 5.4253 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5855 loss: 0.5855 2022/09/05 22:20:20 - mmengine - INFO - Epoch(train) [77][620/940] lr: 1.0000e-03 eta: 4:00:22 time: 0.6617 data_time: 0.0386 memory: 24011 grad_norm: 5.4592 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.5804 loss: 0.5804 2022/09/05 22:20:33 - mmengine - INFO - Epoch(train) [77][640/940] lr: 1.0000e-03 eta: 4:00:09 time: 0.6562 data_time: 0.0471 memory: 24011 grad_norm: 5.4078 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5713 loss: 0.5713 2022/09/05 22:20:45 - mmengine - INFO - Epoch(train) [77][660/940] lr: 1.0000e-03 eta: 3:59:55 time: 0.6034 data_time: 0.0372 memory: 24011 grad_norm: 5.3457 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5017 loss: 0.5017 2022/09/05 22:20:58 - mmengine - INFO - Epoch(train) [77][680/940] lr: 1.0000e-03 eta: 3:59:42 time: 0.6515 data_time: 0.0413 memory: 24011 grad_norm: 5.4890 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6045 loss: 0.6045 2022/09/05 22:21:12 - mmengine - INFO - Epoch(train) [77][700/940] lr: 1.0000e-03 eta: 3:59:29 time: 0.6828 data_time: 0.0365 memory: 24011 grad_norm: 5.6498 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5745 loss: 0.5745 2022/09/05 22:21:25 - mmengine - INFO - Epoch(train) [77][720/940] lr: 1.0000e-03 eta: 3:59:16 time: 0.6339 data_time: 0.0422 memory: 24011 grad_norm: 5.5343 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5273 loss: 0.5273 2022/09/05 22:21:37 - mmengine - INFO - Epoch(train) [77][740/940] lr: 1.0000e-03 eta: 3:59:03 time: 0.6276 data_time: 0.0346 memory: 24011 grad_norm: 5.3514 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6733 loss: 0.6733 2022/09/05 22:21:50 - mmengine - INFO - Epoch(train) [77][760/940] lr: 1.0000e-03 eta: 3:58:49 time: 0.6367 data_time: 0.0452 memory: 24011 grad_norm: 5.3185 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5201 loss: 0.5201 2022/09/05 22:22:03 - mmengine - INFO - Epoch(train) [77][780/940] lr: 1.0000e-03 eta: 3:58:36 time: 0.6521 data_time: 0.0373 memory: 24011 grad_norm: 5.8706 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5372 loss: 0.5372 2022/09/05 22:22:16 - mmengine - INFO - Epoch(train) [77][800/940] lr: 1.0000e-03 eta: 3:58:23 time: 0.6434 data_time: 0.0489 memory: 24011 grad_norm: 5.4532 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6464 loss: 0.6464 2022/09/05 22:22:29 - mmengine - INFO - Epoch(train) [77][820/940] lr: 1.0000e-03 eta: 3:58:10 time: 0.6576 data_time: 0.0451 memory: 24011 grad_norm: 6.1914 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5966 loss: 0.5966 2022/09/05 22:22:43 - mmengine - INFO - Epoch(train) [77][840/940] lr: 1.0000e-03 eta: 3:57:57 time: 0.6644 data_time: 0.0457 memory: 24011 grad_norm: 5.1829 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5558 loss: 0.5558 2022/09/05 22:22:56 - mmengine - INFO - Epoch(train) [77][860/940] lr: 1.0000e-03 eta: 3:57:44 time: 0.6728 data_time: 0.0768 memory: 24011 grad_norm: 5.3190 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5510 loss: 0.5510 2022/09/05 22:23:08 - mmengine - INFO - Epoch(train) [77][880/940] lr: 1.0000e-03 eta: 3:57:30 time: 0.6295 data_time: 0.0303 memory: 24011 grad_norm: 6.2999 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4229 loss: 0.4229 2022/09/05 22:23:22 - mmengine - INFO - Epoch(train) [77][900/940] lr: 1.0000e-03 eta: 3:57:17 time: 0.6644 data_time: 0.0456 memory: 24011 grad_norm: 5.7563 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6147 loss: 0.6147 2022/09/05 22:23:34 - mmengine - INFO - Epoch(train) [77][920/940] lr: 1.0000e-03 eta: 3:57:04 time: 0.6404 data_time: 0.0417 memory: 24011 grad_norm: 5.4320 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5711 loss: 0.5711 2022/09/05 22:23:46 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:23:46 - mmengine - INFO - Epoch(train) [77][940/940] lr: 1.0000e-03 eta: 3:56:50 time: 0.5690 data_time: 0.0510 memory: 24011 grad_norm: 5.8786 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5305 loss: 0.5305 2022/09/05 22:24:00 - mmengine - INFO - Epoch(val) [77][20/78] eta: 0:00:39 time: 0.6890 data_time: 0.5313 memory: 3625 2022/09/05 22:24:09 - mmengine - INFO - Epoch(val) [77][40/78] eta: 0:00:18 time: 0.4794 data_time: 0.3009 memory: 3625 2022/09/05 22:24:23 - mmengine - INFO - Epoch(val) [77][60/78] eta: 0:00:12 time: 0.6731 data_time: 0.4743 memory: 3625 2022/09/05 22:24:33 - mmengine - INFO - Epoch(val) [77][78/78] acc/top1: 0.7377 acc/top5: 0.9073 acc/mean1: 0.7375 2022/09/05 22:24:51 - mmengine - INFO - Epoch(train) [78][20/940] lr: 1.0000e-03 eta: 3:56:39 time: 0.9230 data_time: 0.2622 memory: 24011 grad_norm: 5.5557 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5943 loss: 0.5943 2022/09/05 22:25:04 - mmengine - INFO - Epoch(train) [78][40/940] lr: 1.0000e-03 eta: 3:56:26 time: 0.6479 data_time: 0.0508 memory: 24011 grad_norm: 5.5247 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5247 loss: 0.5247 2022/09/05 22:25:17 - mmengine - INFO - Epoch(train) [78][60/940] lr: 1.0000e-03 eta: 3:56:12 time: 0.6396 data_time: 0.0424 memory: 24011 grad_norm: 6.3208 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5945 loss: 0.5945 2022/09/05 22:25:30 - mmengine - INFO - Epoch(train) [78][80/940] lr: 1.0000e-03 eta: 3:55:59 time: 0.6227 data_time: 0.0331 memory: 24011 grad_norm: 5.3912 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5961 loss: 0.5961 2022/09/05 22:25:44 - mmengine - INFO - Epoch(train) [78][100/940] lr: 1.0000e-03 eta: 3:55:46 time: 0.7008 data_time: 0.0407 memory: 24011 grad_norm: 5.5962 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5272 loss: 0.5272 2022/09/05 22:25:57 - mmengine - INFO - Epoch(train) [78][120/940] lr: 1.0000e-03 eta: 3:55:33 time: 0.6801 data_time: 0.0564 memory: 24011 grad_norm: 5.0712 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6293 loss: 0.6293 2022/09/05 22:26:10 - mmengine - INFO - Epoch(train) [78][140/940] lr: 1.0000e-03 eta: 3:55:20 time: 0.6255 data_time: 0.0444 memory: 24011 grad_norm: 5.8465 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6033 loss: 0.6033 2022/09/05 22:26:23 - mmengine - INFO - Epoch(train) [78][160/940] lr: 1.0000e-03 eta: 3:55:06 time: 0.6343 data_time: 0.0579 memory: 24011 grad_norm: 5.3483 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6445 loss: 0.6445 2022/09/05 22:26:36 - mmengine - INFO - Epoch(train) [78][180/940] lr: 1.0000e-03 eta: 3:54:53 time: 0.6794 data_time: 0.0513 memory: 24011 grad_norm: 5.0171 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5637 loss: 0.5637 2022/09/05 22:26:49 - mmengine - INFO - Epoch(train) [78][200/940] lr: 1.0000e-03 eta: 3:54:40 time: 0.6394 data_time: 0.0401 memory: 24011 grad_norm: 5.2769 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6290 loss: 0.6290 2022/09/05 22:27:03 - mmengine - INFO - Epoch(train) [78][220/940] lr: 1.0000e-03 eta: 3:54:27 time: 0.6921 data_time: 0.0651 memory: 24011 grad_norm: 5.2245 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5761 loss: 0.5761 2022/09/05 22:27:15 - mmengine - INFO - Epoch(train) [78][240/940] lr: 1.0000e-03 eta: 3:54:14 time: 0.6208 data_time: 0.0383 memory: 24011 grad_norm: 5.2328 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5263 loss: 0.5263 2022/09/05 22:27:28 - mmengine - INFO - Epoch(train) [78][260/940] lr: 1.0000e-03 eta: 3:54:01 time: 0.6411 data_time: 0.0399 memory: 24011 grad_norm: 5.7364 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6205 loss: 0.6205 2022/09/05 22:27:41 - mmengine - INFO - Epoch(train) [78][280/940] lr: 1.0000e-03 eta: 3:53:47 time: 0.6375 data_time: 0.0407 memory: 24011 grad_norm: 5.4084 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5882 loss: 0.5882 2022/09/05 22:27:53 - mmengine - INFO - Epoch(train) [78][300/940] lr: 1.0000e-03 eta: 3:53:34 time: 0.6359 data_time: 0.0451 memory: 24011 grad_norm: 6.4925 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4700 loss: 0.4700 2022/09/05 22:28:07 - mmengine - INFO - Epoch(train) [78][320/940] lr: 1.0000e-03 eta: 3:53:21 time: 0.6599 data_time: 0.0375 memory: 24011 grad_norm: 6.3121 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5805 loss: 0.5805 2022/09/05 22:28:19 - mmengine - INFO - Epoch(train) [78][340/940] lr: 1.0000e-03 eta: 3:53:08 time: 0.6439 data_time: 0.0406 memory: 24011 grad_norm: 6.0927 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5679 loss: 0.5679 2022/09/05 22:28:32 - mmengine - INFO - Epoch(train) [78][360/940] lr: 1.0000e-03 eta: 3:52:55 time: 0.6466 data_time: 0.0420 memory: 24011 grad_norm: 7.1691 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5765 loss: 0.5765 2022/09/05 22:28:45 - mmengine - INFO - Epoch(train) [78][380/940] lr: 1.0000e-03 eta: 3:52:41 time: 0.6458 data_time: 0.0444 memory: 24011 grad_norm: 5.4135 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5164 loss: 0.5164 2022/09/05 22:28:58 - mmengine - INFO - Epoch(train) [78][400/940] lr: 1.0000e-03 eta: 3:52:28 time: 0.6289 data_time: 0.0478 memory: 24011 grad_norm: 5.4239 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5200 loss: 0.5200 2022/09/05 22:29:11 - mmengine - INFO - Epoch(train) [78][420/940] lr: 1.0000e-03 eta: 3:52:15 time: 0.6774 data_time: 0.0390 memory: 24011 grad_norm: 5.7186 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.6153 loss: 0.6153 2022/09/05 22:29:24 - mmengine - INFO - Epoch(train) [78][440/940] lr: 1.0000e-03 eta: 3:52:02 time: 0.6498 data_time: 0.0468 memory: 24011 grad_norm: 5.5592 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5739 loss: 0.5739 2022/09/05 22:29:37 - mmengine - INFO - Epoch(train) [78][460/940] lr: 1.0000e-03 eta: 3:51:48 time: 0.6266 data_time: 0.0429 memory: 24011 grad_norm: 5.9462 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5384 loss: 0.5384 2022/09/05 22:29:51 - mmengine - INFO - Epoch(train) [78][480/940] lr: 1.0000e-03 eta: 3:51:35 time: 0.6763 data_time: 0.0446 memory: 24011 grad_norm: 5.2502 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6056 loss: 0.6056 2022/09/05 22:30:04 - mmengine - INFO - Epoch(train) [78][500/940] lr: 1.0000e-03 eta: 3:51:22 time: 0.6501 data_time: 0.0445 memory: 24011 grad_norm: 5.6954 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5709 loss: 0.5709 2022/09/05 22:30:17 - mmengine - INFO - Epoch(train) [78][520/940] lr: 1.0000e-03 eta: 3:51:09 time: 0.6803 data_time: 0.0368 memory: 24011 grad_norm: 5.2902 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4848 loss: 0.4848 2022/09/05 22:30:30 - mmengine - INFO - Epoch(train) [78][540/940] lr: 1.0000e-03 eta: 3:50:56 time: 0.6653 data_time: 0.0412 memory: 24011 grad_norm: 5.7847 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6817 loss: 0.6817 2022/09/05 22:30:44 - mmengine - INFO - Epoch(train) [78][560/940] lr: 1.0000e-03 eta: 3:50:43 time: 0.6594 data_time: 0.0400 memory: 24011 grad_norm: 5.7286 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6154 loss: 0.6154 2022/09/05 22:30:56 - mmengine - INFO - Epoch(train) [78][580/940] lr: 1.0000e-03 eta: 3:50:30 time: 0.6235 data_time: 0.0362 memory: 24011 grad_norm: 5.4968 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5379 loss: 0.5379 2022/09/05 22:31:09 - mmengine - INFO - Epoch(train) [78][600/940] lr: 1.0000e-03 eta: 3:50:16 time: 0.6248 data_time: 0.0387 memory: 24011 grad_norm: 5.6540 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5854 loss: 0.5854 2022/09/05 22:31:22 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:31:22 - mmengine - INFO - Epoch(train) [78][620/940] lr: 1.0000e-03 eta: 3:50:03 time: 0.6437 data_time: 0.0503 memory: 24011 grad_norm: 5.6887 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6176 loss: 0.6176 2022/09/05 22:31:34 - mmengine - INFO - Epoch(train) [78][640/940] lr: 1.0000e-03 eta: 3:49:50 time: 0.6138 data_time: 0.0415 memory: 24011 grad_norm: 5.5480 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4786 loss: 0.4786 2022/09/05 22:31:47 - mmengine - INFO - Epoch(train) [78][660/940] lr: 1.0000e-03 eta: 3:49:37 time: 0.6613 data_time: 0.0594 memory: 24011 grad_norm: 7.9251 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6384 loss: 0.6384 2022/09/05 22:32:00 - mmengine - INFO - Epoch(train) [78][680/940] lr: 1.0000e-03 eta: 3:49:23 time: 0.6293 data_time: 0.0433 memory: 24011 grad_norm: 5.5759 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4925 loss: 0.4925 2022/09/05 22:32:14 - mmengine - INFO - Epoch(train) [78][700/940] lr: 1.0000e-03 eta: 3:49:11 time: 0.7325 data_time: 0.0442 memory: 24011 grad_norm: 5.2969 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6685 loss: 0.6685 2022/09/05 22:32:26 - mmengine - INFO - Epoch(train) [78][720/940] lr: 1.0000e-03 eta: 3:48:57 time: 0.5994 data_time: 0.0390 memory: 24011 grad_norm: 5.8574 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5723 loss: 0.5723 2022/09/05 22:32:39 - mmengine - INFO - Epoch(train) [78][740/940] lr: 1.0000e-03 eta: 3:48:44 time: 0.6419 data_time: 0.0354 memory: 24011 grad_norm: 5.4812 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5616 loss: 0.5616 2022/09/05 22:32:52 - mmengine - INFO - Epoch(train) [78][760/940] lr: 1.0000e-03 eta: 3:48:30 time: 0.6226 data_time: 0.0434 memory: 24011 grad_norm: 6.0897 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5574 loss: 0.5574 2022/09/05 22:33:04 - mmengine - INFO - Epoch(train) [78][780/940] lr: 1.0000e-03 eta: 3:48:17 time: 0.6419 data_time: 0.0394 memory: 24011 grad_norm: 5.5074 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5576 loss: 0.5576 2022/09/05 22:33:17 - mmengine - INFO - Epoch(train) [78][800/940] lr: 1.0000e-03 eta: 3:48:04 time: 0.6340 data_time: 0.0398 memory: 24011 grad_norm: 6.1221 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5295 loss: 0.5295 2022/09/05 22:33:31 - mmengine - INFO - Epoch(train) [78][820/940] lr: 1.0000e-03 eta: 3:47:51 time: 0.6646 data_time: 0.0366 memory: 24011 grad_norm: 5.8178 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6053 loss: 0.6053 2022/09/05 22:33:44 - mmengine - INFO - Epoch(train) [78][840/940] lr: 1.0000e-03 eta: 3:47:38 time: 0.6771 data_time: 0.0757 memory: 24011 grad_norm: 6.8619 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6294 loss: 0.6294 2022/09/05 22:33:57 - mmengine - INFO - Epoch(train) [78][860/940] lr: 1.0000e-03 eta: 3:47:25 time: 0.6641 data_time: 0.0775 memory: 24011 grad_norm: 5.6564 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5963 loss: 0.5963 2022/09/05 22:34:10 - mmengine - INFO - Epoch(train) [78][880/940] lr: 1.0000e-03 eta: 3:47:12 time: 0.6581 data_time: 0.0842 memory: 24011 grad_norm: 5.4313 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5020 loss: 0.5020 2022/09/05 22:34:23 - mmengine - INFO - Epoch(train) [78][900/940] lr: 1.0000e-03 eta: 3:46:58 time: 0.6269 data_time: 0.0553 memory: 24011 grad_norm: 5.6533 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5364 loss: 0.5364 2022/09/05 22:34:36 - mmengine - INFO - Epoch(train) [78][920/940] lr: 1.0000e-03 eta: 3:46:45 time: 0.6607 data_time: 0.0762 memory: 24011 grad_norm: 5.7338 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6094 loss: 0.6094 2022/09/05 22:34:47 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:34:47 - mmengine - INFO - Epoch(train) [78][940/940] lr: 1.0000e-03 eta: 3:46:31 time: 0.5461 data_time: 0.0211 memory: 24011 grad_norm: 5.5885 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6114 loss: 0.6114 2022/09/05 22:34:47 - mmengine - INFO - Saving checkpoint at 78 epochs 2022/09/05 22:35:08 - mmengine - INFO - Epoch(val) [78][20/78] eta: 0:00:41 time: 0.7175 data_time: 0.5507 memory: 3625 2022/09/05 22:35:17 - mmengine - INFO - Epoch(val) [78][40/78] eta: 0:00:17 time: 0.4547 data_time: 0.3011 memory: 3625 2022/09/05 22:35:29 - mmengine - INFO - Epoch(val) [78][60/78] eta: 0:00:11 time: 0.6224 data_time: 0.4682 memory: 3625 2022/09/05 22:35:39 - mmengine - INFO - Epoch(val) [78][78/78] acc/top1: 0.7370 acc/top5: 0.9072 acc/mean1: 0.7369 2022/09/05 22:35:57 - mmengine - INFO - Epoch(train) [79][20/940] lr: 1.0000e-03 eta: 3:46:20 time: 0.9264 data_time: 0.2581 memory: 24011 grad_norm: 5.5776 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5711 loss: 0.5711 2022/09/05 22:36:10 - mmengine - INFO - Epoch(train) [79][40/940] lr: 1.0000e-03 eta: 3:46:07 time: 0.6611 data_time: 0.0318 memory: 24011 grad_norm: 6.5238 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6119 loss: 0.6119 2022/09/05 22:36:24 - mmengine - INFO - Epoch(train) [79][60/940] lr: 1.0000e-03 eta: 3:45:54 time: 0.6617 data_time: 0.0451 memory: 24011 grad_norm: 5.4198 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5288 loss: 0.5288 2022/09/05 22:36:37 - mmengine - INFO - Epoch(train) [79][80/940] lr: 1.0000e-03 eta: 3:45:40 time: 0.6679 data_time: 0.0502 memory: 24011 grad_norm: 5.9105 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6476 loss: 0.6476 2022/09/05 22:36:50 - mmengine - INFO - Epoch(train) [79][100/940] lr: 1.0000e-03 eta: 3:45:27 time: 0.6356 data_time: 0.0413 memory: 24011 grad_norm: 5.9153 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5342 loss: 0.5342 2022/09/05 22:37:02 - mmengine - INFO - Epoch(train) [79][120/940] lr: 1.0000e-03 eta: 3:45:14 time: 0.6005 data_time: 0.0393 memory: 24011 grad_norm: 5.5347 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5343 loss: 0.5343 2022/09/05 22:37:15 - mmengine - INFO - Epoch(train) [79][140/940] lr: 1.0000e-03 eta: 3:45:01 time: 0.6529 data_time: 0.0382 memory: 24011 grad_norm: 5.4599 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6506 loss: 0.6506 2022/09/05 22:37:27 - mmengine - INFO - Epoch(train) [79][160/940] lr: 1.0000e-03 eta: 3:44:47 time: 0.6184 data_time: 0.0416 memory: 24011 grad_norm: 5.1810 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5222 loss: 0.5222 2022/09/05 22:37:41 - mmengine - INFO - Epoch(train) [79][180/940] lr: 1.0000e-03 eta: 3:44:34 time: 0.7067 data_time: 0.0400 memory: 24011 grad_norm: 5.6568 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5551 loss: 0.5551 2022/09/05 22:37:54 - mmengine - INFO - Epoch(train) [79][200/940] lr: 1.0000e-03 eta: 3:44:21 time: 0.6349 data_time: 0.0448 memory: 24011 grad_norm: 5.4318 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5056 loss: 0.5056 2022/09/05 22:38:07 - mmengine - INFO - Epoch(train) [79][220/940] lr: 1.0000e-03 eta: 3:44:08 time: 0.6492 data_time: 0.0685 memory: 24011 grad_norm: 5.5249 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6113 loss: 0.6113 2022/09/05 22:38:20 - mmengine - INFO - Epoch(train) [79][240/940] lr: 1.0000e-03 eta: 3:43:55 time: 0.6266 data_time: 0.0397 memory: 24011 grad_norm: 5.3015 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5706 loss: 0.5706 2022/09/05 22:38:33 - mmengine - INFO - Epoch(train) [79][260/940] lr: 1.0000e-03 eta: 3:43:41 time: 0.6711 data_time: 0.0364 memory: 24011 grad_norm: 6.2108 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.6576 loss: 0.6576 2022/09/05 22:38:46 - mmengine - INFO - Epoch(train) [79][280/940] lr: 1.0000e-03 eta: 3:43:28 time: 0.6370 data_time: 0.0498 memory: 24011 grad_norm: 5.0660 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5790 loss: 0.5790 2022/09/05 22:38:59 - mmengine - INFO - Epoch(train) [79][300/940] lr: 1.0000e-03 eta: 3:43:15 time: 0.6598 data_time: 0.0433 memory: 24011 grad_norm: 5.2329 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5493 loss: 0.5493 2022/09/05 22:39:11 - mmengine - INFO - Epoch(train) [79][320/940] lr: 1.0000e-03 eta: 3:43:02 time: 0.6212 data_time: 0.0405 memory: 24011 grad_norm: 5.4455 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5692 loss: 0.5692 2022/09/05 22:39:25 - mmengine - INFO - Epoch(train) [79][340/940] lr: 1.0000e-03 eta: 3:42:49 time: 0.6613 data_time: 0.0388 memory: 24011 grad_norm: 5.2964 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5333 loss: 0.5333 2022/09/05 22:39:38 - mmengine - INFO - Epoch(train) [79][360/940] lr: 1.0000e-03 eta: 3:42:35 time: 0.6428 data_time: 0.0365 memory: 24011 grad_norm: 5.5420 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5376 loss: 0.5376 2022/09/05 22:39:50 - mmengine - INFO - Epoch(train) [79][380/940] lr: 1.0000e-03 eta: 3:42:22 time: 0.6370 data_time: 0.0385 memory: 24011 grad_norm: 5.1019 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6290 loss: 0.6290 2022/09/05 22:40:04 - mmengine - INFO - Epoch(train) [79][400/940] lr: 1.0000e-03 eta: 3:42:09 time: 0.6940 data_time: 0.0463 memory: 24011 grad_norm: 5.1878 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5546 loss: 0.5546 2022/09/05 22:40:17 - mmengine - INFO - Epoch(train) [79][420/940] lr: 1.0000e-03 eta: 3:41:56 time: 0.6414 data_time: 0.0496 memory: 24011 grad_norm: 5.5335 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5945 loss: 0.5945 2022/09/05 22:40:31 - mmengine - INFO - Epoch(train) [79][440/940] lr: 1.0000e-03 eta: 3:41:43 time: 0.6718 data_time: 0.0375 memory: 24011 grad_norm: 5.8283 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5598 loss: 0.5598 2022/09/05 22:40:44 - mmengine - INFO - Epoch(train) [79][460/940] lr: 1.0000e-03 eta: 3:41:30 time: 0.6470 data_time: 0.0455 memory: 24011 grad_norm: 5.7628 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5757 loss: 0.5757 2022/09/05 22:40:56 - mmengine - INFO - Epoch(train) [79][480/940] lr: 1.0000e-03 eta: 3:41:16 time: 0.6251 data_time: 0.0532 memory: 24011 grad_norm: 5.2696 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5272 loss: 0.5272 2022/09/05 22:41:09 - mmengine - INFO - Epoch(train) [79][500/940] lr: 1.0000e-03 eta: 3:41:03 time: 0.6487 data_time: 0.0465 memory: 24011 grad_norm: 5.7249 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5836 loss: 0.5836 2022/09/05 22:41:22 - mmengine - INFO - Epoch(train) [79][520/940] lr: 1.0000e-03 eta: 3:40:50 time: 0.6462 data_time: 0.0417 memory: 24011 grad_norm: 5.2513 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.6316 loss: 0.6316 2022/09/05 22:41:35 - mmengine - INFO - Epoch(train) [79][540/940] lr: 1.0000e-03 eta: 3:40:37 time: 0.6310 data_time: 0.0434 memory: 24011 grad_norm: 5.1555 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6038 loss: 0.6038 2022/09/05 22:41:48 - mmengine - INFO - Epoch(train) [79][560/940] lr: 1.0000e-03 eta: 3:40:24 time: 0.6607 data_time: 0.0432 memory: 24011 grad_norm: 5.3487 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5980 loss: 0.5980 2022/09/05 22:42:01 - mmengine - INFO - Epoch(train) [79][580/940] lr: 1.0000e-03 eta: 3:40:10 time: 0.6694 data_time: 0.0413 memory: 24011 grad_norm: 5.1256 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6268 loss: 0.6268 2022/09/05 22:42:14 - mmengine - INFO - Epoch(train) [79][600/940] lr: 1.0000e-03 eta: 3:39:57 time: 0.6634 data_time: 0.0452 memory: 24011 grad_norm: 5.1692 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6052 loss: 0.6052 2022/09/05 22:42:27 - mmengine - INFO - Epoch(train) [79][620/940] lr: 1.0000e-03 eta: 3:39:44 time: 0.6071 data_time: 0.0442 memory: 24011 grad_norm: 5.7768 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5404 loss: 0.5404 2022/09/05 22:42:39 - mmengine - INFO - Epoch(train) [79][640/940] lr: 1.0000e-03 eta: 3:39:31 time: 0.6264 data_time: 0.0402 memory: 24011 grad_norm: 6.0265 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6351 loss: 0.6351 2022/09/05 22:42:52 - mmengine - INFO - Epoch(train) [79][660/940] lr: 1.0000e-03 eta: 3:39:17 time: 0.6328 data_time: 0.0434 memory: 24011 grad_norm: 6.5163 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5270 loss: 0.5270 2022/09/05 22:43:05 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:43:05 - mmengine - INFO - Epoch(train) [79][680/940] lr: 1.0000e-03 eta: 3:39:04 time: 0.6849 data_time: 0.0619 memory: 24011 grad_norm: 5.3911 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5692 loss: 0.5692 2022/09/05 22:43:18 - mmengine - INFO - Epoch(train) [79][700/940] lr: 1.0000e-03 eta: 3:38:51 time: 0.6419 data_time: 0.0450 memory: 24011 grad_norm: 5.5277 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4751 loss: 0.4751 2022/09/05 22:43:32 - mmengine - INFO - Epoch(train) [79][720/940] lr: 1.0000e-03 eta: 3:38:38 time: 0.6737 data_time: 0.0403 memory: 24011 grad_norm: 5.5527 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5613 loss: 0.5613 2022/09/05 22:43:45 - mmengine - INFO - Epoch(train) [79][740/940] lr: 1.0000e-03 eta: 3:38:25 time: 0.6373 data_time: 0.0510 memory: 24011 grad_norm: 5.5766 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5072 loss: 0.5072 2022/09/05 22:43:58 - mmengine - INFO - Epoch(train) [79][760/940] lr: 1.0000e-03 eta: 3:38:12 time: 0.6674 data_time: 0.0425 memory: 24011 grad_norm: 5.1966 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.6153 loss: 0.6153 2022/09/05 22:44:11 - mmengine - INFO - Epoch(train) [79][780/940] lr: 1.0000e-03 eta: 3:37:58 time: 0.6341 data_time: 0.0452 memory: 24011 grad_norm: 5.6619 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5908 loss: 0.5908 2022/09/05 22:44:24 - mmengine - INFO - Epoch(train) [79][800/940] lr: 1.0000e-03 eta: 3:37:45 time: 0.6498 data_time: 0.0385 memory: 24011 grad_norm: 5.7583 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6173 loss: 0.6173 2022/09/05 22:44:36 - mmengine - INFO - Epoch(train) [79][820/940] lr: 1.0000e-03 eta: 3:37:32 time: 0.6042 data_time: 0.0451 memory: 24011 grad_norm: 5.3048 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4387 loss: 0.4387 2022/09/05 22:44:48 - mmengine - INFO - Epoch(train) [79][840/940] lr: 1.0000e-03 eta: 3:37:19 time: 0.6357 data_time: 0.0410 memory: 24011 grad_norm: 5.1252 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5967 loss: 0.5967 2022/09/05 22:45:01 - mmengine - INFO - Epoch(train) [79][860/940] lr: 1.0000e-03 eta: 3:37:05 time: 0.6509 data_time: 0.0441 memory: 24011 grad_norm: 6.6989 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5724 loss: 0.5724 2022/09/05 22:45:15 - mmengine - INFO - Epoch(train) [79][880/940] lr: 1.0000e-03 eta: 3:36:52 time: 0.6565 data_time: 0.0370 memory: 24011 grad_norm: 6.2344 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5802 loss: 0.5802 2022/09/05 22:45:28 - mmengine - INFO - Epoch(train) [79][900/940] lr: 1.0000e-03 eta: 3:36:39 time: 0.6595 data_time: 0.0475 memory: 24011 grad_norm: 5.1046 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5100 loss: 0.5100 2022/09/05 22:45:41 - mmengine - INFO - Epoch(train) [79][920/940] lr: 1.0000e-03 eta: 3:36:26 time: 0.6509 data_time: 0.0406 memory: 24011 grad_norm: 5.7227 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5792 loss: 0.5792 2022/09/05 22:45:52 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:45:52 - mmengine - INFO - Epoch(train) [79][940/940] lr: 1.0000e-03 eta: 3:36:12 time: 0.5570 data_time: 0.0283 memory: 24011 grad_norm: 5.5576 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5191 loss: 0.5191 2022/09/05 22:46:06 - mmengine - INFO - Epoch(val) [79][20/78] eta: 0:00:40 time: 0.6963 data_time: 0.5380 memory: 3625 2022/09/05 22:46:15 - mmengine - INFO - Epoch(val) [79][40/78] eta: 0:00:17 time: 0.4679 data_time: 0.3101 memory: 3625 2022/09/05 22:46:28 - mmengine - INFO - Epoch(val) [79][60/78] eta: 0:00:11 time: 0.6577 data_time: 0.4904 memory: 3625 2022/09/05 22:46:39 - mmengine - INFO - Epoch(val) [79][78/78] acc/top1: 0.7370 acc/top5: 0.9058 acc/mean1: 0.7369 2022/09/05 22:46:56 - mmengine - INFO - Epoch(train) [80][20/940] lr: 1.0000e-03 eta: 3:36:00 time: 0.8906 data_time: 0.2635 memory: 24011 grad_norm: 5.7150 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.6351 loss: 0.6351 2022/09/05 22:47:10 - mmengine - INFO - Epoch(train) [80][40/940] lr: 1.0000e-03 eta: 3:35:47 time: 0.6623 data_time: 0.0365 memory: 24011 grad_norm: 5.2673 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.6248 loss: 0.6248 2022/09/05 22:47:23 - mmengine - INFO - Epoch(train) [80][60/940] lr: 1.0000e-03 eta: 3:35:34 time: 0.6308 data_time: 0.0598 memory: 24011 grad_norm: 5.3133 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5367 loss: 0.5367 2022/09/05 22:47:35 - mmengine - INFO - Epoch(train) [80][80/940] lr: 1.0000e-03 eta: 3:35:21 time: 0.6128 data_time: 0.0464 memory: 24011 grad_norm: 5.3099 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6216 loss: 0.6216 2022/09/05 22:47:49 - mmengine - INFO - Epoch(train) [80][100/940] lr: 1.0000e-03 eta: 3:35:08 time: 0.7174 data_time: 0.0425 memory: 24011 grad_norm: 5.6656 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6965 loss: 0.6965 2022/09/05 22:48:02 - mmengine - INFO - Epoch(train) [80][120/940] lr: 1.0000e-03 eta: 3:34:55 time: 0.6485 data_time: 0.0327 memory: 24011 grad_norm: 5.2203 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5577 loss: 0.5577 2022/09/05 22:48:16 - mmengine - INFO - Epoch(train) [80][140/940] lr: 1.0000e-03 eta: 3:34:42 time: 0.7105 data_time: 0.0376 memory: 24011 grad_norm: 5.1865 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5978 loss: 0.5978 2022/09/05 22:48:28 - mmengine - INFO - Epoch(train) [80][160/940] lr: 1.0000e-03 eta: 3:34:28 time: 0.6130 data_time: 0.0460 memory: 24011 grad_norm: 5.2982 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5705 loss: 0.5705 2022/09/05 22:48:41 - mmengine - INFO - Epoch(train) [80][180/940] lr: 1.0000e-03 eta: 3:34:15 time: 0.6438 data_time: 0.0431 memory: 24011 grad_norm: 5.3663 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4950 loss: 0.4950 2022/09/05 22:48:55 - mmengine - INFO - Epoch(train) [80][200/940] lr: 1.0000e-03 eta: 3:34:02 time: 0.6906 data_time: 0.0324 memory: 24011 grad_norm: 6.3506 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5540 loss: 0.5540 2022/09/05 22:49:08 - mmengine - INFO - Epoch(train) [80][220/940] lr: 1.0000e-03 eta: 3:33:49 time: 0.6496 data_time: 0.0389 memory: 24011 grad_norm: 6.5356 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6680 loss: 0.6680 2022/09/05 22:49:20 - mmengine - INFO - Epoch(train) [80][240/940] lr: 1.0000e-03 eta: 3:33:36 time: 0.6080 data_time: 0.0339 memory: 24011 grad_norm: 5.7196 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5759 loss: 0.5759 2022/09/05 22:49:34 - mmengine - INFO - Epoch(train) [80][260/940] lr: 1.0000e-03 eta: 3:33:22 time: 0.6704 data_time: 0.0384 memory: 24011 grad_norm: 5.4474 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6601 loss: 0.6601 2022/09/05 22:49:47 - mmengine - INFO - Epoch(train) [80][280/940] lr: 1.0000e-03 eta: 3:33:09 time: 0.6602 data_time: 0.0298 memory: 24011 grad_norm: 5.6718 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5745 loss: 0.5745 2022/09/05 22:50:00 - mmengine - INFO - Epoch(train) [80][300/940] lr: 1.0000e-03 eta: 3:32:56 time: 0.6553 data_time: 0.0476 memory: 24011 grad_norm: 5.5779 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5786 loss: 0.5786 2022/09/05 22:50:12 - mmengine - INFO - Epoch(train) [80][320/940] lr: 1.0000e-03 eta: 3:32:43 time: 0.6000 data_time: 0.0342 memory: 24011 grad_norm: 5.1948 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6107 loss: 0.6107 2022/09/05 22:50:25 - mmengine - INFO - Epoch(train) [80][340/940] lr: 1.0000e-03 eta: 3:32:29 time: 0.6232 data_time: 0.0489 memory: 24011 grad_norm: 5.2224 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5521 loss: 0.5521 2022/09/05 22:50:37 - mmengine - INFO - Epoch(train) [80][360/940] lr: 1.0000e-03 eta: 3:32:16 time: 0.6109 data_time: 0.0569 memory: 24011 grad_norm: 5.7597 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5465 loss: 0.5465 2022/09/05 22:50:49 - mmengine - INFO - Epoch(train) [80][380/940] lr: 1.0000e-03 eta: 3:32:03 time: 0.6316 data_time: 0.0475 memory: 24011 grad_norm: 6.2901 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5596 loss: 0.5596 2022/09/05 22:51:03 - mmengine - INFO - Epoch(train) [80][400/940] lr: 1.0000e-03 eta: 3:31:50 time: 0.6686 data_time: 0.0373 memory: 24011 grad_norm: 5.2173 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6279 loss: 0.6279 2022/09/05 22:51:15 - mmengine - INFO - Epoch(train) [80][420/940] lr: 1.0000e-03 eta: 3:31:36 time: 0.6305 data_time: 0.0449 memory: 24011 grad_norm: 5.1326 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.6032 loss: 0.6032 2022/09/05 22:51:29 - mmengine - INFO - Epoch(train) [80][440/940] lr: 1.0000e-03 eta: 3:31:23 time: 0.6798 data_time: 0.0533 memory: 24011 grad_norm: 5.2082 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6558 loss: 0.6558 2022/09/05 22:51:42 - mmengine - INFO - Epoch(train) [80][460/940] lr: 1.0000e-03 eta: 3:31:10 time: 0.6359 data_time: 0.0372 memory: 24011 grad_norm: 5.5078 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6331 loss: 0.6331 2022/09/05 22:51:55 - mmengine - INFO - Epoch(train) [80][480/940] lr: 1.0000e-03 eta: 3:30:57 time: 0.6745 data_time: 0.0408 memory: 24011 grad_norm: 5.7895 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6194 loss: 0.6194 2022/09/05 22:52:07 - mmengine - INFO - Epoch(train) [80][500/940] lr: 1.0000e-03 eta: 3:30:44 time: 0.6015 data_time: 0.0301 memory: 24011 grad_norm: 5.7123 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5702 loss: 0.5702 2022/09/05 22:52:20 - mmengine - INFO - Epoch(train) [80][520/940] lr: 1.0000e-03 eta: 3:30:30 time: 0.6441 data_time: 0.0488 memory: 24011 grad_norm: 5.0471 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5630 loss: 0.5630 2022/09/05 22:52:33 - mmengine - INFO - Epoch(train) [80][540/940] lr: 1.0000e-03 eta: 3:30:17 time: 0.6339 data_time: 0.0452 memory: 24011 grad_norm: 5.1989 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5164 loss: 0.5164 2022/09/05 22:52:46 - mmengine - INFO - Epoch(train) [80][560/940] lr: 1.0000e-03 eta: 3:30:04 time: 0.6555 data_time: 0.0650 memory: 24011 grad_norm: 5.3042 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6199 loss: 0.6199 2022/09/05 22:52:59 - mmengine - INFO - Epoch(train) [80][580/940] lr: 1.0000e-03 eta: 3:29:51 time: 0.6389 data_time: 0.0649 memory: 24011 grad_norm: 5.1997 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5396 loss: 0.5396 2022/09/05 22:53:11 - mmengine - INFO - Epoch(train) [80][600/940] lr: 1.0000e-03 eta: 3:29:37 time: 0.6118 data_time: 0.0460 memory: 24011 grad_norm: 5.4613 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6898 loss: 0.6898 2022/09/05 22:53:25 - mmengine - INFO - Epoch(train) [80][620/940] lr: 1.0000e-03 eta: 3:29:24 time: 0.7002 data_time: 0.0527 memory: 24011 grad_norm: 5.6030 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6352 loss: 0.6352 2022/09/05 22:53:38 - mmengine - INFO - Epoch(train) [80][640/940] lr: 1.0000e-03 eta: 3:29:11 time: 0.6467 data_time: 0.0420 memory: 24011 grad_norm: 5.3769 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6123 loss: 0.6123 2022/09/05 22:53:52 - mmengine - INFO - Epoch(train) [80][660/940] lr: 1.0000e-03 eta: 3:28:58 time: 0.6811 data_time: 0.0398 memory: 24011 grad_norm: 5.9247 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6106 loss: 0.6106 2022/09/05 22:54:05 - mmengine - INFO - Epoch(train) [80][680/940] lr: 1.0000e-03 eta: 3:28:45 time: 0.6516 data_time: 0.0414 memory: 24011 grad_norm: 5.2486 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5496 loss: 0.5496 2022/09/05 22:54:17 - mmengine - INFO - Epoch(train) [80][700/940] lr: 1.0000e-03 eta: 3:28:32 time: 0.6291 data_time: 0.0404 memory: 24011 grad_norm: 5.1924 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5800 loss: 0.5800 2022/09/05 22:54:30 - mmengine - INFO - Epoch(train) [80][720/940] lr: 1.0000e-03 eta: 3:28:19 time: 0.6468 data_time: 0.0553 memory: 24011 grad_norm: 5.5771 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5887 loss: 0.5887 2022/09/05 22:54:43 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:54:43 - mmengine - INFO - Epoch(train) [80][740/940] lr: 1.0000e-03 eta: 3:28:05 time: 0.6453 data_time: 0.0480 memory: 24011 grad_norm: 5.2395 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6503 loss: 0.6503 2022/09/05 22:54:56 - mmengine - INFO - Epoch(train) [80][760/940] lr: 1.0000e-03 eta: 3:27:52 time: 0.6512 data_time: 0.0406 memory: 24011 grad_norm: 5.2348 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5058 loss: 0.5058 2022/09/05 22:55:09 - mmengine - INFO - Epoch(train) [80][780/940] lr: 1.0000e-03 eta: 3:27:39 time: 0.6237 data_time: 0.0391 memory: 24011 grad_norm: 5.8220 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5054 loss: 0.5054 2022/09/05 22:55:22 - mmengine - INFO - Epoch(train) [80][800/940] lr: 1.0000e-03 eta: 3:27:26 time: 0.6815 data_time: 0.0381 memory: 24011 grad_norm: 6.1189 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6180 loss: 0.6180 2022/09/05 22:55:35 - mmengine - INFO - Epoch(train) [80][820/940] lr: 1.0000e-03 eta: 3:27:13 time: 0.6424 data_time: 0.0389 memory: 24011 grad_norm: 5.4627 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5963 loss: 0.5963 2022/09/05 22:55:48 - mmengine - INFO - Epoch(train) [80][840/940] lr: 1.0000e-03 eta: 3:27:00 time: 0.6564 data_time: 0.0361 memory: 24011 grad_norm: 5.4813 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5777 loss: 0.5777 2022/09/05 22:56:01 - mmengine - INFO - Epoch(train) [80][860/940] lr: 1.0000e-03 eta: 3:26:46 time: 0.6250 data_time: 0.0426 memory: 24011 grad_norm: 5.7268 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5341 loss: 0.5341 2022/09/05 22:56:14 - mmengine - INFO - Epoch(train) [80][880/940] lr: 1.0000e-03 eta: 3:26:33 time: 0.6703 data_time: 0.0384 memory: 24011 grad_norm: 5.4410 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5516 loss: 0.5516 2022/09/05 22:56:27 - mmengine - INFO - Epoch(train) [80][900/940] lr: 1.0000e-03 eta: 3:26:20 time: 0.6338 data_time: 0.0431 memory: 24011 grad_norm: 5.5570 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5259 loss: 0.5259 2022/09/05 22:56:40 - mmengine - INFO - Epoch(train) [80][920/940] lr: 1.0000e-03 eta: 3:26:07 time: 0.6737 data_time: 0.0461 memory: 24011 grad_norm: 5.8797 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6771 loss: 0.6771 2022/09/05 22:56:51 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 22:56:51 - mmengine - INFO - Epoch(train) [80][940/940] lr: 1.0000e-03 eta: 3:25:53 time: 0.5371 data_time: 0.0261 memory: 24011 grad_norm: 5.6607 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.6529 loss: 0.6529 2022/09/05 22:57:05 - mmengine - INFO - Epoch(val) [80][20/78] eta: 0:00:39 time: 0.6841 data_time: 0.5253 memory: 3625 2022/09/05 22:57:14 - mmengine - INFO - Epoch(val) [80][40/78] eta: 0:00:18 time: 0.4783 data_time: 0.3228 memory: 3625 2022/09/05 22:57:27 - mmengine - INFO - Epoch(val) [80][60/78] eta: 0:00:11 time: 0.6335 data_time: 0.4755 memory: 3625 2022/09/05 22:57:38 - mmengine - INFO - Epoch(val) [80][78/78] acc/top1: 0.7385 acc/top5: 0.9085 acc/mean1: 0.7384 2022/09/05 22:57:55 - mmengine - INFO - Epoch(train) [81][20/940] lr: 1.0000e-04 eta: 3:25:41 time: 0.8846 data_time: 0.2568 memory: 24011 grad_norm: 5.6788 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5009 loss: 0.5009 2022/09/05 22:58:08 - mmengine - INFO - Epoch(train) [81][40/940] lr: 1.0000e-04 eta: 3:25:28 time: 0.6329 data_time: 0.0324 memory: 24011 grad_norm: 5.2677 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5636 loss: 0.5636 2022/09/05 22:58:23 - mmengine - INFO - Epoch(train) [81][60/940] lr: 1.0000e-04 eta: 3:25:15 time: 0.7091 data_time: 0.0432 memory: 24011 grad_norm: 5.2066 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5909 loss: 0.5909 2022/09/05 22:58:35 - mmengine - INFO - Epoch(train) [81][80/940] lr: 1.0000e-04 eta: 3:25:02 time: 0.6304 data_time: 0.0573 memory: 24011 grad_norm: 5.5625 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5925 loss: 0.5925 2022/09/05 22:58:48 - mmengine - INFO - Epoch(train) [81][100/940] lr: 1.0000e-04 eta: 3:24:49 time: 0.6723 data_time: 0.0690 memory: 24011 grad_norm: 5.5811 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5423 loss: 0.5423 2022/09/05 22:59:01 - mmengine - INFO - Epoch(train) [81][120/940] lr: 1.0000e-04 eta: 3:24:35 time: 0.6191 data_time: 0.0352 memory: 24011 grad_norm: 5.4460 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5670 loss: 0.5670 2022/09/05 22:59:13 - mmengine - INFO - Epoch(train) [81][140/940] lr: 1.0000e-04 eta: 3:24:22 time: 0.6428 data_time: 0.0458 memory: 24011 grad_norm: 5.5793 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5357 loss: 0.5357 2022/09/05 22:59:26 - mmengine - INFO - Epoch(train) [81][160/940] lr: 1.0000e-04 eta: 3:24:09 time: 0.6460 data_time: 0.0380 memory: 24011 grad_norm: 5.2774 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5578 loss: 0.5578 2022/09/05 22:59:39 - mmengine - INFO - Epoch(train) [81][180/940] lr: 1.0000e-04 eta: 3:23:56 time: 0.6465 data_time: 0.0443 memory: 24011 grad_norm: 7.9247 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5182 loss: 0.5182 2022/09/05 22:59:53 - mmengine - INFO - Epoch(train) [81][200/940] lr: 1.0000e-04 eta: 3:23:42 time: 0.6508 data_time: 0.0363 memory: 24011 grad_norm: 5.2757 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5650 loss: 0.5650 2022/09/05 23:00:05 - mmengine - INFO - Epoch(train) [81][220/940] lr: 1.0000e-04 eta: 3:23:29 time: 0.6482 data_time: 0.0525 memory: 24011 grad_norm: 5.7321 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.6069 loss: 0.6069 2022/09/05 23:00:19 - mmengine - INFO - Epoch(train) [81][240/940] lr: 1.0000e-04 eta: 3:23:16 time: 0.6614 data_time: 0.0388 memory: 24011 grad_norm: 5.3090 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5333 loss: 0.5333 2022/09/05 23:00:31 - mmengine - INFO - Epoch(train) [81][260/940] lr: 1.0000e-04 eta: 3:23:03 time: 0.6272 data_time: 0.0375 memory: 24011 grad_norm: 5.5980 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4919 loss: 0.4919 2022/09/05 23:00:44 - mmengine - INFO - Epoch(train) [81][280/940] lr: 1.0000e-04 eta: 3:22:50 time: 0.6443 data_time: 0.0412 memory: 24011 grad_norm: 5.6328 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5565 loss: 0.5565 2022/09/05 23:00:57 - mmengine - INFO - Epoch(train) [81][300/940] lr: 1.0000e-04 eta: 3:22:36 time: 0.6532 data_time: 0.0393 memory: 24011 grad_norm: 5.3473 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6637 loss: 0.6637 2022/09/05 23:01:10 - mmengine - INFO - Epoch(train) [81][320/940] lr: 1.0000e-04 eta: 3:22:23 time: 0.6207 data_time: 0.0344 memory: 24011 grad_norm: 5.7375 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6008 loss: 0.6008 2022/09/05 23:01:23 - mmengine - INFO - Epoch(train) [81][340/940] lr: 1.0000e-04 eta: 3:22:10 time: 0.6768 data_time: 0.0405 memory: 24011 grad_norm: 5.5314 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5254 loss: 0.5254 2022/09/05 23:01:37 - mmengine - INFO - Epoch(train) [81][360/940] lr: 1.0000e-04 eta: 3:21:57 time: 0.6688 data_time: 0.0405 memory: 24011 grad_norm: 4.8981 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5385 loss: 0.5385 2022/09/05 23:01:50 - mmengine - INFO - Epoch(train) [81][380/940] lr: 1.0000e-04 eta: 3:21:44 time: 0.6590 data_time: 0.0437 memory: 24011 grad_norm: 5.5389 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5547 loss: 0.5547 2022/09/05 23:02:02 - mmengine - INFO - Epoch(train) [81][400/940] lr: 1.0000e-04 eta: 3:21:30 time: 0.6019 data_time: 0.0391 memory: 24011 grad_norm: 5.1198 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5349 loss: 0.5349 2022/09/05 23:02:16 - mmengine - INFO - Epoch(train) [81][420/940] lr: 1.0000e-04 eta: 3:21:18 time: 0.6934 data_time: 0.0446 memory: 24011 grad_norm: 5.3805 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4722 loss: 0.4722 2022/09/05 23:02:28 - mmengine - INFO - Epoch(train) [81][440/940] lr: 1.0000e-04 eta: 3:21:04 time: 0.6425 data_time: 0.0407 memory: 24011 grad_norm: 5.2673 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4874 loss: 0.4874 2022/09/05 23:02:42 - mmengine - INFO - Epoch(train) [81][460/940] lr: 1.0000e-04 eta: 3:20:51 time: 0.6890 data_time: 0.0392 memory: 24011 grad_norm: 5.3960 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6150 loss: 0.6150 2022/09/05 23:02:55 - mmengine - INFO - Epoch(train) [81][480/940] lr: 1.0000e-04 eta: 3:20:38 time: 0.6183 data_time: 0.0360 memory: 24011 grad_norm: 5.7915 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5701 loss: 0.5701 2022/09/05 23:03:08 - mmengine - INFO - Epoch(train) [81][500/940] lr: 1.0000e-04 eta: 3:20:25 time: 0.6456 data_time: 0.0370 memory: 24011 grad_norm: 6.5170 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5995 loss: 0.5995 2022/09/05 23:03:20 - mmengine - INFO - Epoch(train) [81][520/940] lr: 1.0000e-04 eta: 3:20:12 time: 0.6402 data_time: 0.0385 memory: 24011 grad_norm: 5.4409 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5197 loss: 0.5197 2022/09/05 23:03:33 - mmengine - INFO - Epoch(train) [81][540/940] lr: 1.0000e-04 eta: 3:19:58 time: 0.6289 data_time: 0.0393 memory: 24011 grad_norm: 6.2433 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5771 loss: 0.5771 2022/09/05 23:03:46 - mmengine - INFO - Epoch(train) [81][560/940] lr: 1.0000e-04 eta: 3:19:45 time: 0.6665 data_time: 0.0604 memory: 24011 grad_norm: 5.2956 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.5609 loss: 0.5609 2022/09/05 23:04:00 - mmengine - INFO - Epoch(train) [81][580/940] lr: 1.0000e-04 eta: 3:19:32 time: 0.6648 data_time: 0.0424 memory: 24011 grad_norm: 5.1771 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5403 loss: 0.5403 2022/09/05 23:04:12 - mmengine - INFO - Epoch(train) [81][600/940] lr: 1.0000e-04 eta: 3:19:19 time: 0.6088 data_time: 0.0472 memory: 24011 grad_norm: 5.7151 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5337 loss: 0.5337 2022/09/05 23:04:25 - mmengine - INFO - Epoch(train) [81][620/940] lr: 1.0000e-04 eta: 3:19:06 time: 0.6573 data_time: 0.0366 memory: 24011 grad_norm: 5.5369 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5749 loss: 0.5749 2022/09/05 23:04:38 - mmengine - INFO - Epoch(train) [81][640/940] lr: 1.0000e-04 eta: 3:18:53 time: 0.6767 data_time: 0.0381 memory: 24011 grad_norm: 6.0501 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6164 loss: 0.6164 2022/09/05 23:04:52 - mmengine - INFO - Epoch(train) [81][660/940] lr: 1.0000e-04 eta: 3:18:39 time: 0.6738 data_time: 0.0383 memory: 24011 grad_norm: 5.2869 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4422 loss: 0.4422 2022/09/05 23:05:04 - mmengine - INFO - Epoch(train) [81][680/940] lr: 1.0000e-04 eta: 3:18:26 time: 0.6136 data_time: 0.0446 memory: 24011 grad_norm: 5.1256 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5263 loss: 0.5263 2022/09/05 23:05:18 - mmengine - INFO - Epoch(train) [81][700/940] lr: 1.0000e-04 eta: 3:18:13 time: 0.6663 data_time: 0.0446 memory: 24011 grad_norm: 6.7173 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5441 loss: 0.5441 2022/09/05 23:05:30 - mmengine - INFO - Epoch(train) [81][720/940] lr: 1.0000e-04 eta: 3:18:00 time: 0.6298 data_time: 0.0407 memory: 24011 grad_norm: 4.9575 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.4868 loss: 0.4868 2022/09/05 23:05:43 - mmengine - INFO - Epoch(train) [81][740/940] lr: 1.0000e-04 eta: 3:17:47 time: 0.6428 data_time: 0.0440 memory: 24011 grad_norm: 5.2435 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5732 loss: 0.5732 2022/09/05 23:05:55 - mmengine - INFO - Epoch(train) [81][760/940] lr: 1.0000e-04 eta: 3:17:33 time: 0.6094 data_time: 0.0451 memory: 24011 grad_norm: 5.1787 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5691 loss: 0.5691 2022/09/05 23:06:08 - mmengine - INFO - Epoch(train) [81][780/940] lr: 1.0000e-04 eta: 3:17:20 time: 0.6281 data_time: 0.0409 memory: 24011 grad_norm: 5.1547 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4502 loss: 0.4502 2022/09/05 23:06:21 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:06:21 - mmengine - INFO - Epoch(train) [81][800/940] lr: 1.0000e-04 eta: 3:17:07 time: 0.6515 data_time: 0.0465 memory: 24011 grad_norm: 5.2199 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5164 loss: 0.5164 2022/09/05 23:06:34 - mmengine - INFO - Epoch(train) [81][820/940] lr: 1.0000e-04 eta: 3:16:54 time: 0.6553 data_time: 0.0470 memory: 24011 grad_norm: 5.1847 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5055 loss: 0.5055 2022/09/05 23:06:46 - mmengine - INFO - Epoch(train) [81][840/940] lr: 1.0000e-04 eta: 3:16:40 time: 0.6185 data_time: 0.0409 memory: 24011 grad_norm: 5.4629 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5808 loss: 0.5808 2022/09/05 23:07:00 - mmengine - INFO - Epoch(train) [81][860/940] lr: 1.0000e-04 eta: 3:16:27 time: 0.6625 data_time: 0.0422 memory: 24011 grad_norm: 5.7678 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.6046 loss: 0.6046 2022/09/05 23:07:13 - mmengine - INFO - Epoch(train) [81][880/940] lr: 1.0000e-04 eta: 3:16:14 time: 0.6771 data_time: 0.0375 memory: 24011 grad_norm: 5.3317 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5477 loss: 0.5477 2022/09/05 23:07:26 - mmengine - INFO - Epoch(train) [81][900/940] lr: 1.0000e-04 eta: 3:16:01 time: 0.6250 data_time: 0.0356 memory: 24011 grad_norm: 5.1468 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5289 loss: 0.5289 2022/09/05 23:07:39 - mmengine - INFO - Epoch(train) [81][920/940] lr: 1.0000e-04 eta: 3:15:48 time: 0.6762 data_time: 0.0410 memory: 24011 grad_norm: 5.4901 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5404 loss: 0.5404 2022/09/05 23:07:51 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:07:51 - mmengine - INFO - Epoch(train) [81][940/940] lr: 1.0000e-04 eta: 3:15:34 time: 0.5734 data_time: 0.0223 memory: 24011 grad_norm: 6.0045 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 0.6242 loss: 0.6242 2022/09/05 23:07:51 - mmengine - INFO - Saving checkpoint at 81 epochs 2022/09/05 23:08:10 - mmengine - INFO - Epoch(val) [81][20/78] eta: 0:00:40 time: 0.7012 data_time: 0.5323 memory: 3625 2022/09/05 23:08:20 - mmengine - INFO - Epoch(val) [81][40/78] eta: 0:00:17 time: 0.4653 data_time: 0.3079 memory: 3625 2022/09/05 23:08:32 - mmengine - INFO - Epoch(val) [81][60/78] eta: 0:00:11 time: 0.6342 data_time: 0.4816 memory: 3625 2022/09/05 23:08:42 - mmengine - INFO - Epoch(val) [81][78/78] acc/top1: 0.7403 acc/top5: 0.9076 acc/mean1: 0.7402 2022/09/05 23:09:00 - mmengine - INFO - Epoch(train) [82][20/940] lr: 1.0000e-04 eta: 3:15:22 time: 0.8960 data_time: 0.2582 memory: 24011 grad_norm: 5.4926 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5893 loss: 0.5893 2022/09/05 23:09:13 - mmengine - INFO - Epoch(train) [82][40/940] lr: 1.0000e-04 eta: 3:15:09 time: 0.6501 data_time: 0.0382 memory: 24011 grad_norm: 5.8403 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4445 loss: 0.4445 2022/09/05 23:09:27 - mmengine - INFO - Epoch(train) [82][60/940] lr: 1.0000e-04 eta: 3:14:56 time: 0.7083 data_time: 0.0425 memory: 24011 grad_norm: 5.5367 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6412 loss: 0.6412 2022/09/05 23:09:39 - mmengine - INFO - Epoch(train) [82][80/940] lr: 1.0000e-04 eta: 3:14:43 time: 0.6017 data_time: 0.0357 memory: 24011 grad_norm: 4.9673 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4960 loss: 0.4960 2022/09/05 23:09:52 - mmengine - INFO - Epoch(train) [82][100/940] lr: 1.0000e-04 eta: 3:14:30 time: 0.6738 data_time: 0.0453 memory: 24011 grad_norm: 5.3923 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5456 loss: 0.5456 2022/09/05 23:10:06 - mmengine - INFO - Epoch(train) [82][120/940] lr: 1.0000e-04 eta: 3:14:16 time: 0.6530 data_time: 0.0375 memory: 24011 grad_norm: 5.2549 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5580 loss: 0.5580 2022/09/05 23:10:18 - mmengine - INFO - Epoch(train) [82][140/940] lr: 1.0000e-04 eta: 3:14:03 time: 0.6339 data_time: 0.0439 memory: 24011 grad_norm: 5.4545 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5673 loss: 0.5673 2022/09/05 23:10:32 - mmengine - INFO - Epoch(train) [82][160/940] lr: 1.0000e-04 eta: 3:13:50 time: 0.6716 data_time: 0.0438 memory: 24011 grad_norm: 5.4869 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6322 loss: 0.6322 2022/09/05 23:10:45 - mmengine - INFO - Epoch(train) [82][180/940] lr: 1.0000e-04 eta: 3:13:37 time: 0.6477 data_time: 0.0456 memory: 24011 grad_norm: 5.1573 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.5285 loss: 0.5285 2022/09/05 23:10:57 - mmengine - INFO - Epoch(train) [82][200/940] lr: 1.0000e-04 eta: 3:13:24 time: 0.6184 data_time: 0.0407 memory: 24011 grad_norm: 5.2393 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4757 loss: 0.4757 2022/09/05 23:11:11 - mmengine - INFO - Epoch(train) [82][220/940] lr: 1.0000e-04 eta: 3:13:11 time: 0.6821 data_time: 0.0417 memory: 24011 grad_norm: 5.4362 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.5404 loss: 0.5404 2022/09/05 23:11:23 - mmengine - INFO - Epoch(train) [82][240/940] lr: 1.0000e-04 eta: 3:12:57 time: 0.6238 data_time: 0.0445 memory: 24011 grad_norm: 5.8987 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5853 loss: 0.5853 2022/09/05 23:11:35 - mmengine - INFO - Epoch(train) [82][260/940] lr: 1.0000e-04 eta: 3:12:44 time: 0.6118 data_time: 0.0441 memory: 24011 grad_norm: 5.1428 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5359 loss: 0.5359 2022/09/05 23:11:49 - mmengine - INFO - Epoch(train) [82][280/940] lr: 1.0000e-04 eta: 3:12:31 time: 0.6919 data_time: 0.0601 memory: 24011 grad_norm: 5.1159 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.4677 loss: 0.4677 2022/09/05 23:12:02 - mmengine - INFO - Epoch(train) [82][300/940] lr: 1.0000e-04 eta: 3:12:18 time: 0.6273 data_time: 0.0470 memory: 24011 grad_norm: 5.1854 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5577 loss: 0.5577 2022/09/05 23:12:14 - mmengine - INFO - Epoch(train) [82][320/940] lr: 1.0000e-04 eta: 3:12:04 time: 0.6200 data_time: 0.0395 memory: 24011 grad_norm: 5.3177 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4504 loss: 0.4504 2022/09/05 23:12:28 - mmengine - INFO - Epoch(train) [82][340/940] lr: 1.0000e-04 eta: 3:11:51 time: 0.6781 data_time: 0.0524 memory: 24011 grad_norm: 5.1780 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5797 loss: 0.5797 2022/09/05 23:12:41 - mmengine - INFO - Epoch(train) [82][360/940] lr: 1.0000e-04 eta: 3:11:38 time: 0.6757 data_time: 0.0488 memory: 24011 grad_norm: 5.3363 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5311 loss: 0.5311 2022/09/05 23:12:55 - mmengine - INFO - Epoch(train) [82][380/940] lr: 1.0000e-04 eta: 3:11:25 time: 0.6495 data_time: 0.0439 memory: 24011 grad_norm: 5.6192 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4812 loss: 0.4812 2022/09/05 23:13:07 - mmengine - INFO - Epoch(train) [82][400/940] lr: 1.0000e-04 eta: 3:11:12 time: 0.6237 data_time: 0.0527 memory: 24011 grad_norm: 5.1199 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5161 loss: 0.5161 2022/09/05 23:13:21 - mmengine - INFO - Epoch(train) [82][420/940] lr: 1.0000e-04 eta: 3:10:59 time: 0.6932 data_time: 0.0469 memory: 24011 grad_norm: 7.6340 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5201 loss: 0.5201 2022/09/05 23:13:33 - mmengine - INFO - Epoch(train) [82][440/940] lr: 1.0000e-04 eta: 3:10:46 time: 0.6263 data_time: 0.0402 memory: 24011 grad_norm: 5.4069 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.4700 loss: 0.4700 2022/09/05 23:13:46 - mmengine - INFO - Epoch(train) [82][460/940] lr: 1.0000e-04 eta: 3:10:32 time: 0.6499 data_time: 0.0404 memory: 24011 grad_norm: 5.4836 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5156 loss: 0.5156 2022/09/05 23:13:59 - mmengine - INFO - Epoch(train) [82][480/940] lr: 1.0000e-04 eta: 3:10:19 time: 0.6293 data_time: 0.0431 memory: 24011 grad_norm: 5.2866 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5174 loss: 0.5174 2022/09/05 23:14:13 - mmengine - INFO - Epoch(train) [82][500/940] lr: 1.0000e-04 eta: 3:10:06 time: 0.6911 data_time: 0.0360 memory: 24011 grad_norm: 5.7900 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5113 loss: 0.5113 2022/09/05 23:14:25 - mmengine - INFO - Epoch(train) [82][520/940] lr: 1.0000e-04 eta: 3:09:53 time: 0.6013 data_time: 0.0423 memory: 24011 grad_norm: 5.2771 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5639 loss: 0.5639 2022/09/05 23:14:37 - mmengine - INFO - Epoch(train) [82][540/940] lr: 1.0000e-04 eta: 3:09:39 time: 0.6281 data_time: 0.0446 memory: 24011 grad_norm: 5.4661 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4692 loss: 0.4692 2022/09/05 23:14:50 - mmengine - INFO - Epoch(train) [82][560/940] lr: 1.0000e-04 eta: 3:09:26 time: 0.6472 data_time: 0.0380 memory: 24011 grad_norm: 5.7391 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5708 loss: 0.5708 2022/09/05 23:15:03 - mmengine - INFO - Epoch(train) [82][580/940] lr: 1.0000e-04 eta: 3:09:13 time: 0.6252 data_time: 0.0348 memory: 24011 grad_norm: 5.7771 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5577 loss: 0.5577 2022/09/05 23:15:16 - mmengine - INFO - Epoch(train) [82][600/940] lr: 1.0000e-04 eta: 3:09:00 time: 0.6725 data_time: 0.0385 memory: 24011 grad_norm: 5.4735 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5655 loss: 0.5655 2022/09/05 23:15:29 - mmengine - INFO - Epoch(train) [82][620/940] lr: 1.0000e-04 eta: 3:08:47 time: 0.6588 data_time: 0.0377 memory: 24011 grad_norm: 5.9134 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5642 loss: 0.5642 2022/09/05 23:15:42 - mmengine - INFO - Epoch(train) [82][640/940] lr: 1.0000e-04 eta: 3:08:33 time: 0.6172 data_time: 0.0508 memory: 24011 grad_norm: 5.4197 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5130 loss: 0.5130 2022/09/05 23:15:55 - mmengine - INFO - Epoch(train) [82][660/940] lr: 1.0000e-04 eta: 3:08:20 time: 0.6865 data_time: 0.0540 memory: 24011 grad_norm: 5.4534 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6236 loss: 0.6236 2022/09/05 23:16:09 - mmengine - INFO - Epoch(train) [82][680/940] lr: 1.0000e-04 eta: 3:08:07 time: 0.6586 data_time: 0.0335 memory: 24011 grad_norm: 5.3951 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5865 loss: 0.5865 2022/09/05 23:16:21 - mmengine - INFO - Epoch(train) [82][700/940] lr: 1.0000e-04 eta: 3:07:54 time: 0.6410 data_time: 0.0369 memory: 24011 grad_norm: 5.3027 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5265 loss: 0.5265 2022/09/05 23:16:34 - mmengine - INFO - Epoch(train) [82][720/940] lr: 1.0000e-04 eta: 3:07:41 time: 0.6380 data_time: 0.0356 memory: 24011 grad_norm: 6.0455 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5519 loss: 0.5519 2022/09/05 23:16:47 - mmengine - INFO - Epoch(train) [82][740/940] lr: 1.0000e-04 eta: 3:07:28 time: 0.6507 data_time: 0.0558 memory: 24011 grad_norm: 5.2823 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5638 loss: 0.5638 2022/09/05 23:17:00 - mmengine - INFO - Epoch(train) [82][760/940] lr: 1.0000e-04 eta: 3:07:14 time: 0.6240 data_time: 0.0604 memory: 24011 grad_norm: 5.2708 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5705 loss: 0.5705 2022/09/05 23:17:13 - mmengine - INFO - Epoch(train) [82][780/940] lr: 1.0000e-04 eta: 3:07:01 time: 0.6583 data_time: 0.0561 memory: 24011 grad_norm: 5.7714 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6406 loss: 0.6406 2022/09/05 23:17:26 - mmengine - INFO - Epoch(train) [82][800/940] lr: 1.0000e-04 eta: 3:06:48 time: 0.6520 data_time: 0.0719 memory: 24011 grad_norm: 6.8548 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6087 loss: 0.6087 2022/09/05 23:17:39 - mmengine - INFO - Epoch(train) [82][820/940] lr: 1.0000e-04 eta: 3:06:35 time: 0.6756 data_time: 0.0605 memory: 24011 grad_norm: 5.1572 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4581 loss: 0.4581 2022/09/05 23:17:52 - mmengine - INFO - Epoch(train) [82][840/940] lr: 1.0000e-04 eta: 3:06:22 time: 0.6329 data_time: 0.0365 memory: 24011 grad_norm: 5.5646 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5033 loss: 0.5033 2022/09/05 23:18:05 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:18:05 - mmengine - INFO - Epoch(train) [82][860/940] lr: 1.0000e-04 eta: 3:06:09 time: 0.6207 data_time: 0.0486 memory: 24011 grad_norm: 6.3816 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6931 loss: 0.6931 2022/09/05 23:18:17 - mmengine - INFO - Epoch(train) [82][880/940] lr: 1.0000e-04 eta: 3:05:55 time: 0.6440 data_time: 0.0361 memory: 24011 grad_norm: 5.5052 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6029 loss: 0.6029 2022/09/05 23:18:31 - mmengine - INFO - Epoch(train) [82][900/940] lr: 1.0000e-04 eta: 3:05:42 time: 0.6658 data_time: 0.0412 memory: 24011 grad_norm: 5.4287 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5566 loss: 0.5566 2022/09/05 23:18:44 - mmengine - INFO - Epoch(train) [82][920/940] lr: 1.0000e-04 eta: 3:05:29 time: 0.6507 data_time: 0.0351 memory: 24011 grad_norm: 5.3347 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4371 loss: 0.4371 2022/09/05 23:18:55 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:18:55 - mmengine - INFO - Epoch(train) [82][940/940] lr: 1.0000e-04 eta: 3:05:16 time: 0.5601 data_time: 0.0268 memory: 24011 grad_norm: 5.8956 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5375 loss: 0.5375 2022/09/05 23:19:09 - mmengine - INFO - Epoch(val) [82][20/78] eta: 0:00:40 time: 0.6964 data_time: 0.5330 memory: 3625 2022/09/05 23:19:18 - mmengine - INFO - Epoch(val) [82][40/78] eta: 0:00:17 time: 0.4531 data_time: 0.2973 memory: 3625 2022/09/05 23:19:31 - mmengine - INFO - Epoch(val) [82][60/78] eta: 0:00:11 time: 0.6472 data_time: 0.4850 memory: 3625 2022/09/05 23:19:42 - mmengine - INFO - Epoch(val) [82][78/78] acc/top1: 0.7415 acc/top5: 0.9078 acc/mean1: 0.7414 2022/09/05 23:20:00 - mmengine - INFO - Epoch(train) [83][20/940] lr: 1.0000e-04 eta: 3:05:03 time: 0.9098 data_time: 0.2443 memory: 24011 grad_norm: 5.3690 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6327 loss: 0.6327 2022/09/05 23:20:12 - mmengine - INFO - Epoch(train) [83][40/940] lr: 1.0000e-04 eta: 3:04:50 time: 0.6272 data_time: 0.0350 memory: 24011 grad_norm: 5.4316 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5506 loss: 0.5506 2022/09/05 23:20:26 - mmengine - INFO - Epoch(train) [83][60/940] lr: 1.0000e-04 eta: 3:04:37 time: 0.6789 data_time: 0.0366 memory: 24011 grad_norm: 5.5067 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4468 loss: 0.4468 2022/09/05 23:20:39 - mmengine - INFO - Epoch(train) [83][80/940] lr: 1.0000e-04 eta: 3:04:24 time: 0.6457 data_time: 0.0437 memory: 24011 grad_norm: 4.9899 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6703 loss: 0.6703 2022/09/05 23:20:53 - mmengine - INFO - Epoch(train) [83][100/940] lr: 1.0000e-04 eta: 3:04:11 time: 0.6806 data_time: 0.0455 memory: 24011 grad_norm: 5.2822 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5438 loss: 0.5438 2022/09/05 23:21:05 - mmengine - INFO - Epoch(train) [83][120/940] lr: 1.0000e-04 eta: 3:03:58 time: 0.6272 data_time: 0.0420 memory: 24011 grad_norm: 5.2388 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5748 loss: 0.5748 2022/09/05 23:21:18 - mmengine - INFO - Epoch(train) [83][140/940] lr: 1.0000e-04 eta: 3:03:45 time: 0.6539 data_time: 0.0536 memory: 24011 grad_norm: 5.5570 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5549 loss: 0.5549 2022/09/05 23:21:31 - mmengine - INFO - Epoch(train) [83][160/940] lr: 1.0000e-04 eta: 3:03:31 time: 0.6630 data_time: 0.0432 memory: 24011 grad_norm: 5.6377 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5306 loss: 0.5306 2022/09/05 23:21:44 - mmengine - INFO - Epoch(train) [83][180/940] lr: 1.0000e-04 eta: 3:03:18 time: 0.6427 data_time: 0.0405 memory: 24011 grad_norm: 5.3768 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5219 loss: 0.5219 2022/09/05 23:21:56 - mmengine - INFO - Epoch(train) [83][200/940] lr: 1.0000e-04 eta: 3:03:05 time: 0.5991 data_time: 0.0421 memory: 24011 grad_norm: 5.5408 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6049 loss: 0.6049 2022/09/05 23:22:09 - mmengine - INFO - Epoch(train) [83][220/940] lr: 1.0000e-04 eta: 3:02:52 time: 0.6573 data_time: 0.0435 memory: 24011 grad_norm: 5.5798 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5799 loss: 0.5799 2022/09/05 23:22:22 - mmengine - INFO - Epoch(train) [83][240/940] lr: 1.0000e-04 eta: 3:02:38 time: 0.6492 data_time: 0.0424 memory: 24011 grad_norm: 5.8081 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5038 loss: 0.5038 2022/09/05 23:22:36 - mmengine - INFO - Epoch(train) [83][260/940] lr: 1.0000e-04 eta: 3:02:25 time: 0.6674 data_time: 0.0400 memory: 24011 grad_norm: 6.0235 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4942 loss: 0.4942 2022/09/05 23:22:48 - mmengine - INFO - Epoch(train) [83][280/940] lr: 1.0000e-04 eta: 3:02:12 time: 0.6145 data_time: 0.0461 memory: 24011 grad_norm: 4.9205 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4733 loss: 0.4733 2022/09/05 23:23:02 - mmengine - INFO - Epoch(train) [83][300/940] lr: 1.0000e-04 eta: 3:01:59 time: 0.6803 data_time: 0.0372 memory: 24011 grad_norm: 5.4870 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5461 loss: 0.5461 2022/09/05 23:23:14 - mmengine - INFO - Epoch(train) [83][320/940] lr: 1.0000e-04 eta: 3:01:46 time: 0.6157 data_time: 0.0381 memory: 24011 grad_norm: 5.8581 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5551 loss: 0.5551 2022/09/05 23:23:27 - mmengine - INFO - Epoch(train) [83][340/940] lr: 1.0000e-04 eta: 3:01:33 time: 0.6449 data_time: 0.0377 memory: 24011 grad_norm: 5.4855 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5415 loss: 0.5415 2022/09/05 23:23:40 - mmengine - INFO - Epoch(train) [83][360/940] lr: 1.0000e-04 eta: 3:01:19 time: 0.6283 data_time: 0.0340 memory: 24011 grad_norm: 5.4302 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5171 loss: 0.5171 2022/09/05 23:23:53 - mmengine - INFO - Epoch(train) [83][380/940] lr: 1.0000e-04 eta: 3:01:06 time: 0.6524 data_time: 0.0758 memory: 24011 grad_norm: 5.4057 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5155 loss: 0.5155 2022/09/05 23:24:06 - mmengine - INFO - Epoch(train) [83][400/940] lr: 1.0000e-04 eta: 3:00:53 time: 0.6524 data_time: 0.0371 memory: 24011 grad_norm: 5.6224 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5049 loss: 0.5049 2022/09/05 23:24:19 - mmengine - INFO - Epoch(train) [83][420/940] lr: 1.0000e-04 eta: 3:00:40 time: 0.6752 data_time: 0.0416 memory: 24011 grad_norm: 5.3200 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4748 loss: 0.4748 2022/09/05 23:24:32 - mmengine - INFO - Epoch(train) [83][440/940] lr: 1.0000e-04 eta: 3:00:27 time: 0.6280 data_time: 0.0419 memory: 24011 grad_norm: 6.6896 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.6241 loss: 0.6241 2022/09/05 23:24:45 - mmengine - INFO - Epoch(train) [83][460/940] lr: 1.0000e-04 eta: 3:00:13 time: 0.6399 data_time: 0.0384 memory: 24011 grad_norm: 5.4934 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5652 loss: 0.5652 2022/09/05 23:24:58 - mmengine - INFO - Epoch(train) [83][480/940] lr: 1.0000e-04 eta: 3:00:00 time: 0.6542 data_time: 0.0373 memory: 24011 grad_norm: 5.5789 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5219 loss: 0.5219 2022/09/05 23:25:11 - mmengine - INFO - Epoch(train) [83][500/940] lr: 1.0000e-04 eta: 2:59:47 time: 0.6526 data_time: 0.0397 memory: 24011 grad_norm: 5.6008 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5706 loss: 0.5706 2022/09/05 23:25:24 - mmengine - INFO - Epoch(train) [83][520/940] lr: 1.0000e-04 eta: 2:59:34 time: 0.6851 data_time: 0.0659 memory: 24011 grad_norm: 6.3155 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5581 loss: 0.5581 2022/09/05 23:25:38 - mmengine - INFO - Epoch(train) [83][540/940] lr: 1.0000e-04 eta: 2:59:21 time: 0.6806 data_time: 0.0646 memory: 24011 grad_norm: 5.9760 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5551 loss: 0.5551 2022/09/05 23:25:50 - mmengine - INFO - Epoch(train) [83][560/940] lr: 1.0000e-04 eta: 2:59:08 time: 0.6165 data_time: 0.0398 memory: 24011 grad_norm: 5.4320 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5824 loss: 0.5824 2022/09/05 23:26:04 - mmengine - INFO - Epoch(train) [83][580/940] lr: 1.0000e-04 eta: 2:58:55 time: 0.6705 data_time: 0.0372 memory: 24011 grad_norm: 5.4308 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4774 loss: 0.4774 2022/09/05 23:26:16 - mmengine - INFO - Epoch(train) [83][600/940] lr: 1.0000e-04 eta: 2:58:41 time: 0.6122 data_time: 0.0386 memory: 24011 grad_norm: 5.6559 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5892 loss: 0.5892 2022/09/05 23:26:29 - mmengine - INFO - Epoch(train) [83][620/940] lr: 1.0000e-04 eta: 2:58:28 time: 0.6726 data_time: 0.0443 memory: 24011 grad_norm: 5.8669 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5454 loss: 0.5454 2022/09/05 23:26:42 - mmengine - INFO - Epoch(train) [83][640/940] lr: 1.0000e-04 eta: 2:58:15 time: 0.6121 data_time: 0.0358 memory: 24011 grad_norm: 5.3219 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4640 loss: 0.4640 2022/09/05 23:26:56 - mmengine - INFO - Epoch(train) [83][660/940] lr: 1.0000e-04 eta: 2:58:02 time: 0.7015 data_time: 0.0401 memory: 24011 grad_norm: 5.4834 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5376 loss: 0.5376 2022/09/05 23:27:09 - mmengine - INFO - Epoch(train) [83][680/940] lr: 1.0000e-04 eta: 2:57:49 time: 0.6675 data_time: 0.0406 memory: 24011 grad_norm: 5.9792 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.4801 loss: 0.4801 2022/09/05 23:27:22 - mmengine - INFO - Epoch(train) [83][700/940] lr: 1.0000e-04 eta: 2:57:36 time: 0.6574 data_time: 0.0427 memory: 24011 grad_norm: 5.7684 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5912 loss: 0.5912 2022/09/05 23:27:35 - mmengine - INFO - Epoch(train) [83][720/940] lr: 1.0000e-04 eta: 2:57:23 time: 0.6459 data_time: 0.0297 memory: 24011 grad_norm: 5.4948 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5344 loss: 0.5344 2022/09/05 23:27:48 - mmengine - INFO - Epoch(train) [83][740/940] lr: 1.0000e-04 eta: 2:57:09 time: 0.6395 data_time: 0.0570 memory: 24011 grad_norm: 5.4299 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5111 loss: 0.5111 2022/09/05 23:28:00 - mmengine - INFO - Epoch(train) [83][760/940] lr: 1.0000e-04 eta: 2:56:56 time: 0.5968 data_time: 0.0318 memory: 24011 grad_norm: 5.2784 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5764 loss: 0.5764 2022/09/05 23:28:13 - mmengine - INFO - Epoch(train) [83][780/940] lr: 1.0000e-04 eta: 2:56:43 time: 0.6654 data_time: 0.0369 memory: 24011 grad_norm: 5.0875 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5484 loss: 0.5484 2022/09/05 23:28:26 - mmengine - INFO - Epoch(train) [83][800/940] lr: 1.0000e-04 eta: 2:56:30 time: 0.6280 data_time: 0.0437 memory: 24011 grad_norm: 5.6823 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6252 loss: 0.6252 2022/09/05 23:28:39 - mmengine - INFO - Epoch(train) [83][820/940] lr: 1.0000e-04 eta: 2:56:16 time: 0.6421 data_time: 0.0415 memory: 24011 grad_norm: 5.0993 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.5850 loss: 0.5850 2022/09/05 23:28:52 - mmengine - INFO - Epoch(train) [83][840/940] lr: 1.0000e-04 eta: 2:56:03 time: 0.6598 data_time: 0.0551 memory: 24011 grad_norm: 5.3438 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5060 loss: 0.5060 2022/09/05 23:29:05 - mmengine - INFO - Epoch(train) [83][860/940] lr: 1.0000e-04 eta: 2:55:50 time: 0.6294 data_time: 0.0394 memory: 24011 grad_norm: 5.4104 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5175 loss: 0.5175 2022/09/05 23:29:17 - mmengine - INFO - Epoch(train) [83][880/940] lr: 1.0000e-04 eta: 2:55:37 time: 0.6066 data_time: 0.0399 memory: 24011 grad_norm: 5.2144 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5519 loss: 0.5519 2022/09/05 23:29:30 - mmengine - INFO - Epoch(train) [83][900/940] lr: 1.0000e-04 eta: 2:55:24 time: 0.6729 data_time: 0.0413 memory: 24011 grad_norm: 5.3709 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5633 loss: 0.5633 2022/09/05 23:29:43 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:29:43 - mmengine - INFO - Epoch(train) [83][920/940] lr: 1.0000e-04 eta: 2:55:10 time: 0.6435 data_time: 0.0414 memory: 24011 grad_norm: 5.2474 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5376 loss: 0.5376 2022/09/05 23:29:54 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:29:54 - mmengine - INFO - Epoch(train) [83][940/940] lr: 1.0000e-04 eta: 2:54:57 time: 0.5621 data_time: 0.0376 memory: 24011 grad_norm: 5.5781 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5718 loss: 0.5718 2022/09/05 23:30:08 - mmengine - INFO - Epoch(val) [83][20/78] eta: 0:00:40 time: 0.7043 data_time: 0.5440 memory: 3625 2022/09/05 23:30:18 - mmengine - INFO - Epoch(val) [83][40/78] eta: 0:00:17 time: 0.4561 data_time: 0.2995 memory: 3625 2022/09/05 23:30:31 - mmengine - INFO - Epoch(val) [83][60/78] eta: 0:00:11 time: 0.6577 data_time: 0.5002 memory: 3625 2022/09/05 23:30:41 - mmengine - INFO - Epoch(val) [83][78/78] acc/top1: 0.7408 acc/top5: 0.9075 acc/mean1: 0.7407 2022/09/05 23:30:59 - mmengine - INFO - Epoch(train) [84][20/940] lr: 1.0000e-04 eta: 2:54:45 time: 0.8898 data_time: 0.3146 memory: 24011 grad_norm: 5.5501 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4874 loss: 0.4874 2022/09/05 23:31:13 - mmengine - INFO - Epoch(train) [84][40/940] lr: 1.0000e-04 eta: 2:54:32 time: 0.6669 data_time: 0.0557 memory: 24011 grad_norm: 5.1948 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5574 loss: 0.5574 2022/09/05 23:31:26 - mmengine - INFO - Epoch(train) [84][60/940] lr: 1.0000e-04 eta: 2:54:18 time: 0.6716 data_time: 0.0390 memory: 24011 grad_norm: 5.3945 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5376 loss: 0.5376 2022/09/05 23:31:38 - mmengine - INFO - Epoch(train) [84][80/940] lr: 1.0000e-04 eta: 2:54:05 time: 0.5913 data_time: 0.0453 memory: 24011 grad_norm: 5.5991 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6073 loss: 0.6073 2022/09/05 23:31:52 - mmengine - INFO - Epoch(train) [84][100/940] lr: 1.0000e-04 eta: 2:53:52 time: 0.6728 data_time: 0.0815 memory: 24011 grad_norm: 5.6853 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.5769 loss: 0.5769 2022/09/05 23:32:04 - mmengine - INFO - Epoch(train) [84][120/940] lr: 1.0000e-04 eta: 2:53:39 time: 0.6215 data_time: 0.0575 memory: 24011 grad_norm: 5.8396 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6273 loss: 0.6273 2022/09/05 23:32:17 - mmengine - INFO - Epoch(train) [84][140/940] lr: 1.0000e-04 eta: 2:53:26 time: 0.6790 data_time: 0.0571 memory: 24011 grad_norm: 5.7504 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5229 loss: 0.5229 2022/09/05 23:32:30 - mmengine - INFO - Epoch(train) [84][160/940] lr: 1.0000e-04 eta: 2:53:13 time: 0.6534 data_time: 0.0667 memory: 24011 grad_norm: 5.5329 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4903 loss: 0.4903 2022/09/05 23:32:44 - mmengine - INFO - Epoch(train) [84][180/940] lr: 1.0000e-04 eta: 2:52:59 time: 0.6857 data_time: 0.1083 memory: 24011 grad_norm: 5.4193 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4706 loss: 0.4706 2022/09/05 23:32:56 - mmengine - INFO - Epoch(train) [84][200/940] lr: 1.0000e-04 eta: 2:52:46 time: 0.6039 data_time: 0.0418 memory: 24011 grad_norm: 5.3372 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4918 loss: 0.4918 2022/09/05 23:33:10 - mmengine - INFO - Epoch(train) [84][220/940] lr: 1.0000e-04 eta: 2:52:33 time: 0.6881 data_time: 0.0655 memory: 24011 grad_norm: 5.3226 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5431 loss: 0.5431 2022/09/05 23:33:23 - mmengine - INFO - Epoch(train) [84][240/940] lr: 1.0000e-04 eta: 2:52:20 time: 0.6591 data_time: 0.0834 memory: 24011 grad_norm: 5.5856 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5959 loss: 0.5959 2022/09/05 23:33:36 - mmengine - INFO - Epoch(train) [84][260/940] lr: 1.0000e-04 eta: 2:52:07 time: 0.6331 data_time: 0.0415 memory: 24011 grad_norm: 5.5780 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4756 loss: 0.4756 2022/09/05 23:33:49 - mmengine - INFO - Epoch(train) [84][280/940] lr: 1.0000e-04 eta: 2:51:54 time: 0.6405 data_time: 0.0335 memory: 24011 grad_norm: 5.3913 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5519 loss: 0.5519 2022/09/05 23:34:02 - mmengine - INFO - Epoch(train) [84][300/940] lr: 1.0000e-04 eta: 2:51:41 time: 0.6812 data_time: 0.0432 memory: 24011 grad_norm: 5.6387 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5803 loss: 0.5803 2022/09/05 23:34:15 - mmengine - INFO - Epoch(train) [84][320/940] lr: 1.0000e-04 eta: 2:51:27 time: 0.6102 data_time: 0.0331 memory: 24011 grad_norm: 5.6575 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5700 loss: 0.5700 2022/09/05 23:34:28 - mmengine - INFO - Epoch(train) [84][340/940] lr: 1.0000e-04 eta: 2:51:14 time: 0.6711 data_time: 0.0877 memory: 24011 grad_norm: 5.4767 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5894 loss: 0.5894 2022/09/05 23:34:40 - mmengine - INFO - Epoch(train) [84][360/940] lr: 1.0000e-04 eta: 2:51:01 time: 0.6065 data_time: 0.0301 memory: 24011 grad_norm: 5.4216 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5461 loss: 0.5461 2022/09/05 23:34:54 - mmengine - INFO - Epoch(train) [84][380/940] lr: 1.0000e-04 eta: 2:50:48 time: 0.6729 data_time: 0.0431 memory: 24011 grad_norm: 5.7206 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5517 loss: 0.5517 2022/09/05 23:35:07 - mmengine - INFO - Epoch(train) [84][400/940] lr: 1.0000e-04 eta: 2:50:35 time: 0.6640 data_time: 0.0371 memory: 24011 grad_norm: 5.1486 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5129 loss: 0.5129 2022/09/05 23:35:20 - mmengine - INFO - Epoch(train) [84][420/940] lr: 1.0000e-04 eta: 2:50:21 time: 0.6329 data_time: 0.0385 memory: 24011 grad_norm: 5.5348 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6702 loss: 0.6702 2022/09/05 23:35:32 - mmengine - INFO - Epoch(train) [84][440/940] lr: 1.0000e-04 eta: 2:50:08 time: 0.6473 data_time: 0.0446 memory: 24011 grad_norm: 5.3726 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5695 loss: 0.5695 2022/09/05 23:35:45 - mmengine - INFO - Epoch(train) [84][460/940] lr: 1.0000e-04 eta: 2:49:55 time: 0.6432 data_time: 0.0377 memory: 24011 grad_norm: 5.5485 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5272 loss: 0.5272 2022/09/05 23:35:57 - mmengine - INFO - Epoch(train) [84][480/940] lr: 1.0000e-04 eta: 2:49:42 time: 0.5929 data_time: 0.0404 memory: 24011 grad_norm: 5.7964 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5372 loss: 0.5372 2022/09/05 23:36:11 - mmengine - INFO - Epoch(train) [84][500/940] lr: 1.0000e-04 eta: 2:49:29 time: 0.6774 data_time: 0.0381 memory: 24011 grad_norm: 5.4916 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.5508 loss: 0.5508 2022/09/05 23:36:24 - mmengine - INFO - Epoch(train) [84][520/940] lr: 1.0000e-04 eta: 2:49:15 time: 0.6729 data_time: 0.0392 memory: 24011 grad_norm: 5.6211 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5759 loss: 0.5759 2022/09/05 23:36:37 - mmengine - INFO - Epoch(train) [84][540/940] lr: 1.0000e-04 eta: 2:49:02 time: 0.6601 data_time: 0.0407 memory: 24011 grad_norm: 5.9494 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5356 loss: 0.5356 2022/09/05 23:36:50 - mmengine - INFO - Epoch(train) [84][560/940] lr: 1.0000e-04 eta: 2:48:49 time: 0.6386 data_time: 0.0402 memory: 24011 grad_norm: 5.1643 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5530 loss: 0.5530 2022/09/05 23:37:03 - mmengine - INFO - Epoch(train) [84][580/940] lr: 1.0000e-04 eta: 2:48:36 time: 0.6401 data_time: 0.0382 memory: 24011 grad_norm: 5.7499 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5005 loss: 0.5005 2022/09/05 23:37:15 - mmengine - INFO - Epoch(train) [84][600/940] lr: 1.0000e-04 eta: 2:48:23 time: 0.6111 data_time: 0.0379 memory: 24011 grad_norm: 6.1796 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4983 loss: 0.4983 2022/09/05 23:37:29 - mmengine - INFO - Epoch(train) [84][620/940] lr: 1.0000e-04 eta: 2:48:10 time: 0.6681 data_time: 0.0353 memory: 24011 grad_norm: 6.5623 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5458 loss: 0.5458 2022/09/05 23:37:41 - mmengine - INFO - Epoch(train) [84][640/940] lr: 1.0000e-04 eta: 2:47:56 time: 0.6350 data_time: 0.0417 memory: 24011 grad_norm: 5.2823 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4713 loss: 0.4713 2022/09/05 23:37:55 - mmengine - INFO - Epoch(train) [84][660/940] lr: 1.0000e-04 eta: 2:47:43 time: 0.6640 data_time: 0.0377 memory: 24011 grad_norm: 5.1507 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5736 loss: 0.5736 2022/09/05 23:38:08 - mmengine - INFO - Epoch(train) [84][680/940] lr: 1.0000e-04 eta: 2:47:30 time: 0.6513 data_time: 0.0446 memory: 24011 grad_norm: 5.1092 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5566 loss: 0.5566 2022/09/05 23:38:21 - mmengine - INFO - Epoch(train) [84][700/940] lr: 1.0000e-04 eta: 2:47:17 time: 0.6750 data_time: 0.0384 memory: 24011 grad_norm: 5.6343 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5033 loss: 0.5033 2022/09/05 23:38:34 - mmengine - INFO - Epoch(train) [84][720/940] lr: 1.0000e-04 eta: 2:47:04 time: 0.6369 data_time: 0.0475 memory: 24011 grad_norm: 5.3223 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6440 loss: 0.6440 2022/09/05 23:38:47 - mmengine - INFO - Epoch(train) [84][740/940] lr: 1.0000e-04 eta: 2:46:51 time: 0.6345 data_time: 0.0390 memory: 24011 grad_norm: 5.0453 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5553 loss: 0.5553 2022/09/05 23:38:59 - mmengine - INFO - Epoch(train) [84][760/940] lr: 1.0000e-04 eta: 2:46:37 time: 0.6205 data_time: 0.0573 memory: 24011 grad_norm: 6.3286 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.5685 loss: 0.5685 2022/09/05 23:39:11 - mmengine - INFO - Epoch(train) [84][780/940] lr: 1.0000e-04 eta: 2:46:24 time: 0.6089 data_time: 0.0440 memory: 24011 grad_norm: 5.4465 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5628 loss: 0.5628 2022/09/05 23:39:24 - mmengine - INFO - Epoch(train) [84][800/940] lr: 1.0000e-04 eta: 2:46:11 time: 0.6549 data_time: 0.0379 memory: 24011 grad_norm: 5.1058 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5914 loss: 0.5914 2022/09/05 23:39:38 - mmengine - INFO - Epoch(train) [84][820/940] lr: 1.0000e-04 eta: 2:45:58 time: 0.6746 data_time: 0.0426 memory: 24011 grad_norm: 5.3527 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4786 loss: 0.4786 2022/09/05 23:39:51 - mmengine - INFO - Epoch(train) [84][840/940] lr: 1.0000e-04 eta: 2:45:45 time: 0.6570 data_time: 0.0363 memory: 24011 grad_norm: 5.1172 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5731 loss: 0.5731 2022/09/05 23:40:04 - mmengine - INFO - Epoch(train) [84][860/940] lr: 1.0000e-04 eta: 2:45:31 time: 0.6527 data_time: 0.0432 memory: 24011 grad_norm: 5.7172 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5510 loss: 0.5510 2022/09/05 23:40:17 - mmengine - INFO - Epoch(train) [84][880/940] lr: 1.0000e-04 eta: 2:45:18 time: 0.6574 data_time: 0.0409 memory: 24011 grad_norm: 5.0639 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5556 loss: 0.5556 2022/09/05 23:40:31 - mmengine - INFO - Epoch(train) [84][900/940] lr: 1.0000e-04 eta: 2:45:05 time: 0.6635 data_time: 0.0474 memory: 24011 grad_norm: 5.7087 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4916 loss: 0.4916 2022/09/05 23:40:43 - mmengine - INFO - Epoch(train) [84][920/940] lr: 1.0000e-04 eta: 2:44:52 time: 0.6390 data_time: 0.0368 memory: 24011 grad_norm: 5.3922 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5319 loss: 0.5319 2022/09/05 23:40:55 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:40:55 - mmengine - INFO - Epoch(train) [84][940/940] lr: 1.0000e-04 eta: 2:44:38 time: 0.5744 data_time: 0.0299 memory: 24011 grad_norm: 5.3733 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.6001 loss: 0.6001 2022/09/05 23:40:55 - mmengine - INFO - Saving checkpoint at 84 epochs 2022/09/05 23:41:15 - mmengine - INFO - Epoch(val) [84][20/78] eta: 0:00:41 time: 0.7201 data_time: 0.5652 memory: 3625 2022/09/05 23:41:24 - mmengine - INFO - Epoch(val) [84][40/78] eta: 0:00:17 time: 0.4504 data_time: 0.2959 memory: 3625 2022/09/05 23:41:37 - mmengine - INFO - Epoch(val) [84][60/78] eta: 0:00:11 time: 0.6307 data_time: 0.4769 memory: 3625 2022/09/05 23:41:46 - mmengine - INFO - Epoch(val) [84][78/78] acc/top1: 0.7415 acc/top5: 0.9070 acc/mean1: 0.7414 2022/09/05 23:42:04 - mmengine - INFO - Epoch(train) [85][20/940] lr: 1.0000e-04 eta: 2:44:26 time: 0.9128 data_time: 0.3246 memory: 24011 grad_norm: 5.4252 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5087 loss: 0.5087 2022/09/05 23:42:17 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:42:17 - mmengine - INFO - Epoch(train) [85][40/940] lr: 1.0000e-04 eta: 2:44:13 time: 0.6490 data_time: 0.0811 memory: 24011 grad_norm: 5.6043 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5136 loss: 0.5136 2022/09/05 23:42:31 - mmengine - INFO - Epoch(train) [85][60/940] lr: 1.0000e-04 eta: 2:44:00 time: 0.6712 data_time: 0.0412 memory: 24011 grad_norm: 5.4440 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4827 loss: 0.4827 2022/09/05 23:42:44 - mmengine - INFO - Epoch(train) [85][80/940] lr: 1.0000e-04 eta: 2:43:47 time: 0.6769 data_time: 0.0367 memory: 24011 grad_norm: 5.5766 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4508 loss: 0.4508 2022/09/05 23:42:58 - mmengine - INFO - Epoch(train) [85][100/940] lr: 1.0000e-04 eta: 2:43:34 time: 0.6664 data_time: 0.0383 memory: 24011 grad_norm: 5.3343 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.4789 loss: 0.4789 2022/09/05 23:43:10 - mmengine - INFO - Epoch(train) [85][120/940] lr: 1.0000e-04 eta: 2:43:21 time: 0.6099 data_time: 0.0425 memory: 24011 grad_norm: 5.2987 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5087 loss: 0.5087 2022/09/05 23:43:23 - mmengine - INFO - Epoch(train) [85][140/940] lr: 1.0000e-04 eta: 2:43:07 time: 0.6683 data_time: 0.0449 memory: 24011 grad_norm: 5.3546 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5345 loss: 0.5345 2022/09/05 23:43:36 - mmengine - INFO - Epoch(train) [85][160/940] lr: 1.0000e-04 eta: 2:42:54 time: 0.6503 data_time: 0.0415 memory: 24011 grad_norm: 5.2710 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5061 loss: 0.5061 2022/09/05 23:43:49 - mmengine - INFO - Epoch(train) [85][180/940] lr: 1.0000e-04 eta: 2:42:41 time: 0.6601 data_time: 0.0435 memory: 24011 grad_norm: 5.2493 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5281 loss: 0.5281 2022/09/05 23:44:02 - mmengine - INFO - Epoch(train) [85][200/940] lr: 1.0000e-04 eta: 2:42:28 time: 0.6551 data_time: 0.0412 memory: 24011 grad_norm: 5.6149 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5254 loss: 0.5254 2022/09/05 23:44:16 - mmengine - INFO - Epoch(train) [85][220/940] lr: 1.0000e-04 eta: 2:42:15 time: 0.6697 data_time: 0.0377 memory: 24011 grad_norm: 6.4345 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5406 loss: 0.5406 2022/09/05 23:44:29 - mmengine - INFO - Epoch(train) [85][240/940] lr: 1.0000e-04 eta: 2:42:02 time: 0.6420 data_time: 0.0382 memory: 24011 grad_norm: 5.2601 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5641 loss: 0.5641 2022/09/05 23:44:42 - mmengine - INFO - Epoch(train) [85][260/940] lr: 1.0000e-04 eta: 2:41:49 time: 0.6400 data_time: 0.0414 memory: 24011 grad_norm: 5.2505 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5716 loss: 0.5716 2022/09/05 23:44:54 - mmengine - INFO - Epoch(train) [85][280/940] lr: 1.0000e-04 eta: 2:41:35 time: 0.6198 data_time: 0.0411 memory: 24011 grad_norm: 5.2759 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5408 loss: 0.5408 2022/09/05 23:45:07 - mmengine - INFO - Epoch(train) [85][300/940] lr: 1.0000e-04 eta: 2:41:22 time: 0.6734 data_time: 0.0399 memory: 24011 grad_norm: 7.1797 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5804 loss: 0.5804 2022/09/05 23:45:20 - mmengine - INFO - Epoch(train) [85][320/940] lr: 1.0000e-04 eta: 2:41:09 time: 0.6233 data_time: 0.0408 memory: 24011 grad_norm: 5.6566 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5678 loss: 0.5678 2022/09/05 23:45:33 - mmengine - INFO - Epoch(train) [85][340/940] lr: 1.0000e-04 eta: 2:40:56 time: 0.6713 data_time: 0.0423 memory: 24011 grad_norm: 6.9719 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5169 loss: 0.5169 2022/09/05 23:45:46 - mmengine - INFO - Epoch(train) [85][360/940] lr: 1.0000e-04 eta: 2:40:43 time: 0.6441 data_time: 0.0352 memory: 24011 grad_norm: 6.5237 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 0.5421 loss: 0.5421 2022/09/05 23:45:59 - mmengine - INFO - Epoch(train) [85][380/940] lr: 1.0000e-04 eta: 2:40:29 time: 0.6396 data_time: 0.0451 memory: 24011 grad_norm: 6.1775 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5176 loss: 0.5176 2022/09/05 23:46:12 - mmengine - INFO - Epoch(train) [85][400/940] lr: 1.0000e-04 eta: 2:40:16 time: 0.6375 data_time: 0.0366 memory: 24011 grad_norm: 5.3223 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5336 loss: 0.5336 2022/09/05 23:46:25 - mmengine - INFO - Epoch(train) [85][420/940] lr: 1.0000e-04 eta: 2:40:03 time: 0.6768 data_time: 0.0484 memory: 24011 grad_norm: 6.1721 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5411 loss: 0.5411 2022/09/05 23:46:38 - mmengine - INFO - Epoch(train) [85][440/940] lr: 1.0000e-04 eta: 2:39:50 time: 0.6447 data_time: 0.0393 memory: 24011 grad_norm: 5.5157 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5165 loss: 0.5165 2022/09/05 23:46:51 - mmengine - INFO - Epoch(train) [85][460/940] lr: 1.0000e-04 eta: 2:39:37 time: 0.6305 data_time: 0.0357 memory: 24011 grad_norm: 5.3473 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5932 loss: 0.5932 2022/09/05 23:47:04 - mmengine - INFO - Epoch(train) [85][480/940] lr: 1.0000e-04 eta: 2:39:24 time: 0.6446 data_time: 0.0391 memory: 24011 grad_norm: 5.8874 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5404 loss: 0.5404 2022/09/05 23:47:16 - mmengine - INFO - Epoch(train) [85][500/940] lr: 1.0000e-04 eta: 2:39:10 time: 0.6284 data_time: 0.0414 memory: 24011 grad_norm: 5.9226 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6341 loss: 0.6341 2022/09/05 23:47:30 - mmengine - INFO - Epoch(train) [85][520/940] lr: 1.0000e-04 eta: 2:38:57 time: 0.6693 data_time: 0.0389 memory: 24011 grad_norm: 5.5820 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5220 loss: 0.5220 2022/09/05 23:47:44 - mmengine - INFO - Epoch(train) [85][540/940] lr: 1.0000e-04 eta: 2:38:44 time: 0.6940 data_time: 0.0333 memory: 24011 grad_norm: 5.9096 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5522 loss: 0.5522 2022/09/05 23:47:56 - mmengine - INFO - Epoch(train) [85][560/940] lr: 1.0000e-04 eta: 2:38:31 time: 0.6403 data_time: 0.0415 memory: 24011 grad_norm: 5.3905 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5683 loss: 0.5683 2022/09/05 23:48:09 - mmengine - INFO - Epoch(train) [85][580/940] lr: 1.0000e-04 eta: 2:38:18 time: 0.6510 data_time: 0.0381 memory: 24011 grad_norm: 5.8816 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5076 loss: 0.5076 2022/09/05 23:48:22 - mmengine - INFO - Epoch(train) [85][600/940] lr: 1.0000e-04 eta: 2:38:05 time: 0.6373 data_time: 0.0397 memory: 24011 grad_norm: 5.1577 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5268 loss: 0.5268 2022/09/05 23:48:35 - mmengine - INFO - Epoch(train) [85][620/940] lr: 1.0000e-04 eta: 2:37:52 time: 0.6544 data_time: 0.0436 memory: 24011 grad_norm: 5.4392 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.5792 loss: 0.5792 2022/09/05 23:48:48 - mmengine - INFO - Epoch(train) [85][640/940] lr: 1.0000e-04 eta: 2:37:38 time: 0.6399 data_time: 0.0447 memory: 24011 grad_norm: 5.8244 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5350 loss: 0.5350 2022/09/05 23:49:02 - mmengine - INFO - Epoch(train) [85][660/940] lr: 1.0000e-04 eta: 2:37:25 time: 0.6721 data_time: 0.0440 memory: 24011 grad_norm: 5.7096 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5423 loss: 0.5423 2022/09/05 23:49:14 - mmengine - INFO - Epoch(train) [85][680/940] lr: 1.0000e-04 eta: 2:37:12 time: 0.6267 data_time: 0.0410 memory: 24011 grad_norm: 5.4280 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5410 loss: 0.5410 2022/09/05 23:49:27 - mmengine - INFO - Epoch(train) [85][700/940] lr: 1.0000e-04 eta: 2:36:59 time: 0.6467 data_time: 0.0394 memory: 24011 grad_norm: 5.1804 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.4957 loss: 0.4957 2022/09/05 23:49:40 - mmengine - INFO - Epoch(train) [85][720/940] lr: 1.0000e-04 eta: 2:36:46 time: 0.6442 data_time: 0.0389 memory: 24011 grad_norm: 6.2035 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5906 loss: 0.5906 2022/09/05 23:49:52 - mmengine - INFO - Epoch(train) [85][740/940] lr: 1.0000e-04 eta: 2:36:32 time: 0.6270 data_time: 0.0388 memory: 24011 grad_norm: 5.5999 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5846 loss: 0.5846 2022/09/05 23:50:06 - mmengine - INFO - Epoch(train) [85][760/940] lr: 1.0000e-04 eta: 2:36:19 time: 0.6727 data_time: 0.0418 memory: 24011 grad_norm: 5.3569 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5650 loss: 0.5650 2022/09/05 23:50:19 - mmengine - INFO - Epoch(train) [85][780/940] lr: 1.0000e-04 eta: 2:36:06 time: 0.6401 data_time: 0.0436 memory: 24011 grad_norm: 5.1075 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5766 loss: 0.5766 2022/09/05 23:50:32 - mmengine - INFO - Epoch(train) [85][800/940] lr: 1.0000e-04 eta: 2:35:53 time: 0.6383 data_time: 0.0440 memory: 24011 grad_norm: 5.4184 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5215 loss: 0.5215 2022/09/05 23:50:44 - mmengine - INFO - Epoch(train) [85][820/940] lr: 1.0000e-04 eta: 2:35:40 time: 0.6388 data_time: 0.0530 memory: 24011 grad_norm: 5.1414 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4708 loss: 0.4708 2022/09/05 23:50:58 - mmengine - INFO - Epoch(train) [85][840/940] lr: 1.0000e-04 eta: 2:35:27 time: 0.6651 data_time: 0.0533 memory: 24011 grad_norm: 5.7737 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6441 loss: 0.6441 2022/09/05 23:51:10 - mmengine - INFO - Epoch(train) [85][860/940] lr: 1.0000e-04 eta: 2:35:13 time: 0.6290 data_time: 0.0430 memory: 24011 grad_norm: 5.4159 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5412 loss: 0.5412 2022/09/05 23:51:24 - mmengine - INFO - Epoch(train) [85][880/940] lr: 1.0000e-04 eta: 2:35:00 time: 0.6902 data_time: 0.0382 memory: 24011 grad_norm: 5.2478 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4800 loss: 0.4800 2022/09/05 23:51:37 - mmengine - INFO - Epoch(train) [85][900/940] lr: 1.0000e-04 eta: 2:34:47 time: 0.6362 data_time: 0.0408 memory: 24011 grad_norm: 5.6190 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5965 loss: 0.5965 2022/09/05 23:51:50 - mmengine - INFO - Epoch(train) [85][920/940] lr: 1.0000e-04 eta: 2:34:34 time: 0.6574 data_time: 0.0391 memory: 24011 grad_norm: 5.9243 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5122 loss: 0.5122 2022/09/05 23:52:01 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:52:01 - mmengine - INFO - Epoch(train) [85][940/940] lr: 1.0000e-04 eta: 2:34:21 time: 0.5551 data_time: 0.0288 memory: 24011 grad_norm: 5.5330 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5261 loss: 0.5261 2022/09/05 23:52:15 - mmengine - INFO - Epoch(val) [85][20/78] eta: 0:00:39 time: 0.6885 data_time: 0.5271 memory: 3625 2022/09/05 23:52:24 - mmengine - INFO - Epoch(val) [85][40/78] eta: 0:00:17 time: 0.4733 data_time: 0.3163 memory: 3625 2022/09/05 23:52:37 - mmengine - INFO - Epoch(val) [85][60/78] eta: 0:00:11 time: 0.6362 data_time: 0.4791 memory: 3625 2022/09/05 23:52:48 - mmengine - INFO - Epoch(val) [85][78/78] acc/top1: 0.7420 acc/top5: 0.9073 acc/mean1: 0.7419 2022/09/05 23:53:06 - mmengine - INFO - Epoch(train) [86][20/940] lr: 1.0000e-04 eta: 2:34:08 time: 0.9181 data_time: 0.2950 memory: 24011 grad_norm: 6.9239 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4997 loss: 0.4997 2022/09/05 23:53:19 - mmengine - INFO - Epoch(train) [86][40/940] lr: 1.0000e-04 eta: 2:33:55 time: 0.6369 data_time: 0.0431 memory: 24011 grad_norm: 6.1208 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5905 loss: 0.5905 2022/09/05 23:53:32 - mmengine - INFO - Epoch(train) [86][60/940] lr: 1.0000e-04 eta: 2:33:42 time: 0.6773 data_time: 0.0566 memory: 24011 grad_norm: 5.4203 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5608 loss: 0.5608 2022/09/05 23:53:46 - mmengine - INFO - Epoch(train) [86][80/940] lr: 1.0000e-04 eta: 2:33:29 time: 0.6577 data_time: 0.0939 memory: 24011 grad_norm: 5.3662 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5991 loss: 0.5991 2022/09/05 23:53:59 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/05 23:53:59 - mmengine - INFO - Epoch(train) [86][100/940] lr: 1.0000e-04 eta: 2:33:16 time: 0.6669 data_time: 0.0747 memory: 24011 grad_norm: 5.6267 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5343 loss: 0.5343 2022/09/05 23:54:12 - mmengine - INFO - Epoch(train) [86][120/940] lr: 1.0000e-04 eta: 2:33:03 time: 0.6585 data_time: 0.0872 memory: 24011 grad_norm: 5.6095 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6062 loss: 0.6062 2022/09/05 23:54:25 - mmengine - INFO - Epoch(train) [86][140/940] lr: 1.0000e-04 eta: 2:32:49 time: 0.6199 data_time: 0.0511 memory: 24011 grad_norm: 4.9117 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5543 loss: 0.5543 2022/09/05 23:54:37 - mmengine - INFO - Epoch(train) [86][160/940] lr: 1.0000e-04 eta: 2:32:36 time: 0.6298 data_time: 0.0631 memory: 24011 grad_norm: 5.1219 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5595 loss: 0.5595 2022/09/05 23:54:51 - mmengine - INFO - Epoch(train) [86][180/940] lr: 1.0000e-04 eta: 2:32:23 time: 0.6774 data_time: 0.1028 memory: 24011 grad_norm: 5.4277 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5465 loss: 0.5465 2022/09/05 23:55:03 - mmengine - INFO - Epoch(train) [86][200/940] lr: 1.0000e-04 eta: 2:32:10 time: 0.6249 data_time: 0.0465 memory: 24011 grad_norm: 5.3737 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5020 loss: 0.5020 2022/09/05 23:55:16 - mmengine - INFO - Epoch(train) [86][220/940] lr: 1.0000e-04 eta: 2:31:57 time: 0.6560 data_time: 0.0359 memory: 24011 grad_norm: 5.5670 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5633 loss: 0.5633 2022/09/05 23:55:29 - mmengine - INFO - Epoch(train) [86][240/940] lr: 1.0000e-04 eta: 2:31:44 time: 0.6309 data_time: 0.0440 memory: 24011 grad_norm: 5.2106 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4400 loss: 0.4400 2022/09/05 23:55:43 - mmengine - INFO - Epoch(train) [86][260/940] lr: 1.0000e-04 eta: 2:31:30 time: 0.6719 data_time: 0.0642 memory: 24011 grad_norm: 5.3299 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5115 loss: 0.5115 2022/09/05 23:55:55 - mmengine - INFO - Epoch(train) [86][280/940] lr: 1.0000e-04 eta: 2:31:17 time: 0.6503 data_time: 0.0676 memory: 24011 grad_norm: 5.2667 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5408 loss: 0.5408 2022/09/05 23:56:09 - mmengine - INFO - Epoch(train) [86][300/940] lr: 1.0000e-04 eta: 2:31:04 time: 0.6538 data_time: 0.0475 memory: 24011 grad_norm: 5.4033 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5591 loss: 0.5591 2022/09/05 23:56:22 - mmengine - INFO - Epoch(train) [86][320/940] lr: 1.0000e-04 eta: 2:30:51 time: 0.6625 data_time: 0.0492 memory: 24011 grad_norm: 5.2237 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5464 loss: 0.5464 2022/09/05 23:56:35 - mmengine - INFO - Epoch(train) [86][340/940] lr: 1.0000e-04 eta: 2:30:38 time: 0.6423 data_time: 0.0358 memory: 24011 grad_norm: 5.8639 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5223 loss: 0.5223 2022/09/05 23:56:48 - mmengine - INFO - Epoch(train) [86][360/940] lr: 1.0000e-04 eta: 2:30:25 time: 0.6446 data_time: 0.0371 memory: 24011 grad_norm: 5.3444 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5232 loss: 0.5232 2022/09/05 23:57:01 - mmengine - INFO - Epoch(train) [86][380/940] lr: 1.0000e-04 eta: 2:30:12 time: 0.6753 data_time: 0.0475 memory: 24011 grad_norm: 5.3458 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5736 loss: 0.5736 2022/09/05 23:57:13 - mmengine - INFO - Epoch(train) [86][400/940] lr: 1.0000e-04 eta: 2:29:58 time: 0.6006 data_time: 0.0326 memory: 24011 grad_norm: 5.4548 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5681 loss: 0.5681 2022/09/05 23:57:25 - mmengine - INFO - Epoch(train) [86][420/940] lr: 1.0000e-04 eta: 2:29:45 time: 0.6059 data_time: 0.0382 memory: 24011 grad_norm: 5.1868 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5406 loss: 0.5406 2022/09/05 23:57:38 - mmengine - INFO - Epoch(train) [86][440/940] lr: 1.0000e-04 eta: 2:29:32 time: 0.6570 data_time: 0.0715 memory: 24011 grad_norm: 5.5556 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.5512 loss: 0.5512 2022/09/05 23:57:51 - mmengine - INFO - Epoch(train) [86][460/940] lr: 1.0000e-04 eta: 2:29:19 time: 0.6360 data_time: 0.0488 memory: 24011 grad_norm: 5.3803 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5794 loss: 0.5794 2022/09/05 23:58:04 - mmengine - INFO - Epoch(train) [86][480/940] lr: 1.0000e-04 eta: 2:29:05 time: 0.6637 data_time: 0.0427 memory: 24011 grad_norm: 5.7946 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4961 loss: 0.4961 2022/09/05 23:58:17 - mmengine - INFO - Epoch(train) [86][500/940] lr: 1.0000e-04 eta: 2:28:52 time: 0.6319 data_time: 0.0389 memory: 24011 grad_norm: 5.7236 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5195 loss: 0.5195 2022/09/05 23:58:30 - mmengine - INFO - Epoch(train) [86][520/940] lr: 1.0000e-04 eta: 2:28:39 time: 0.6643 data_time: 0.0644 memory: 24011 grad_norm: 5.4822 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5242 loss: 0.5242 2022/09/05 23:58:44 - mmengine - INFO - Epoch(train) [86][540/940] lr: 1.0000e-04 eta: 2:28:26 time: 0.6677 data_time: 0.0389 memory: 24011 grad_norm: 5.5621 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5974 loss: 0.5974 2022/09/05 23:58:57 - mmengine - INFO - Epoch(train) [86][560/940] lr: 1.0000e-04 eta: 2:28:13 time: 0.6629 data_time: 0.0382 memory: 24011 grad_norm: 5.3723 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5729 loss: 0.5729 2022/09/05 23:59:10 - mmengine - INFO - Epoch(train) [86][580/940] lr: 1.0000e-04 eta: 2:28:00 time: 0.6389 data_time: 0.0372 memory: 24011 grad_norm: 5.2667 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5679 loss: 0.5679 2022/09/05 23:59:23 - mmengine - INFO - Epoch(train) [86][600/940] lr: 1.0000e-04 eta: 2:27:47 time: 0.6437 data_time: 0.0411 memory: 24011 grad_norm: 5.9524 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5158 loss: 0.5158 2022/09/05 23:59:36 - mmengine - INFO - Epoch(train) [86][620/940] lr: 1.0000e-04 eta: 2:27:33 time: 0.6463 data_time: 0.0392 memory: 24011 grad_norm: 5.5021 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5191 loss: 0.5191 2022/09/05 23:59:48 - mmengine - INFO - Epoch(train) [86][640/940] lr: 1.0000e-04 eta: 2:27:20 time: 0.6335 data_time: 0.0396 memory: 24011 grad_norm: 5.9625 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5552 loss: 0.5552 2022/09/06 00:00:05 - mmengine - INFO - Epoch(train) [86][660/940] lr: 1.0000e-04 eta: 2:27:08 time: 0.8145 data_time: 0.0473 memory: 24011 grad_norm: 5.0873 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5838 loss: 0.5838 2022/09/06 00:00:17 - mmengine - INFO - Epoch(train) [86][680/940] lr: 1.0000e-04 eta: 2:26:54 time: 0.6146 data_time: 0.0413 memory: 24011 grad_norm: 5.3655 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5463 loss: 0.5463 2022/09/06 00:00:30 - mmengine - INFO - Epoch(train) [86][700/940] lr: 1.0000e-04 eta: 2:26:41 time: 0.6573 data_time: 0.0459 memory: 24011 grad_norm: 5.3503 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4888 loss: 0.4888 2022/09/06 00:00:43 - mmengine - INFO - Epoch(train) [86][720/940] lr: 1.0000e-04 eta: 2:26:28 time: 0.6505 data_time: 0.0455 memory: 24011 grad_norm: 5.9551 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6053 loss: 0.6053 2022/09/06 00:00:56 - mmengine - INFO - Epoch(train) [86][740/940] lr: 1.0000e-04 eta: 2:26:15 time: 0.6445 data_time: 0.0410 memory: 24011 grad_norm: 4.9971 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5703 loss: 0.5703 2022/09/06 00:01:09 - mmengine - INFO - Epoch(train) [86][760/940] lr: 1.0000e-04 eta: 2:26:02 time: 0.6446 data_time: 0.0358 memory: 24011 grad_norm: 5.8986 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5080 loss: 0.5080 2022/09/06 00:01:23 - mmengine - INFO - Epoch(train) [86][780/940] lr: 1.0000e-04 eta: 2:25:49 time: 0.6833 data_time: 0.0356 memory: 24011 grad_norm: 5.7259 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5213 loss: 0.5213 2022/09/06 00:01:37 - mmengine - INFO - Epoch(train) [86][800/940] lr: 1.0000e-04 eta: 2:25:36 time: 0.7091 data_time: 0.0383 memory: 24011 grad_norm: 6.1239 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6117 loss: 0.6117 2022/09/06 00:01:49 - mmengine - INFO - Epoch(train) [86][820/940] lr: 1.0000e-04 eta: 2:25:22 time: 0.6228 data_time: 0.0369 memory: 24011 grad_norm: 5.2233 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5792 loss: 0.5792 2022/09/06 00:02:03 - mmengine - INFO - Epoch(train) [86][840/940] lr: 1.0000e-04 eta: 2:25:09 time: 0.6892 data_time: 0.0406 memory: 24011 grad_norm: 5.2774 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5376 loss: 0.5376 2022/09/06 00:02:15 - mmengine - INFO - Epoch(train) [86][860/940] lr: 1.0000e-04 eta: 2:24:56 time: 0.6062 data_time: 0.0387 memory: 24011 grad_norm: 5.3841 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5806 loss: 0.5806 2022/09/06 00:02:29 - mmengine - INFO - Epoch(train) [86][880/940] lr: 1.0000e-04 eta: 2:24:43 time: 0.6702 data_time: 0.0409 memory: 24011 grad_norm: 5.6547 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4884 loss: 0.4884 2022/09/06 00:02:42 - mmengine - INFO - Epoch(train) [86][900/940] lr: 1.0000e-04 eta: 2:24:30 time: 0.6529 data_time: 0.0501 memory: 24011 grad_norm: 8.7336 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5583 loss: 0.5583 2022/09/06 00:02:54 - mmengine - INFO - Epoch(train) [86][920/940] lr: 1.0000e-04 eta: 2:24:17 time: 0.6374 data_time: 0.0428 memory: 24011 grad_norm: 5.7446 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5660 loss: 0.5660 2022/09/06 00:03:05 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:03:05 - mmengine - INFO - Epoch(train) [86][940/940] lr: 1.0000e-04 eta: 2:24:03 time: 0.5466 data_time: 0.0247 memory: 24011 grad_norm: 5.6527 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.6219 loss: 0.6219 2022/09/06 00:03:19 - mmengine - INFO - Epoch(val) [86][20/78] eta: 0:00:39 time: 0.6892 data_time: 0.5286 memory: 3625 2022/09/06 00:03:29 - mmengine - INFO - Epoch(val) [86][40/78] eta: 0:00:17 time: 0.4724 data_time: 0.3130 memory: 3625 2022/09/06 00:03:42 - mmengine - INFO - Epoch(val) [86][60/78] eta: 0:00:11 time: 0.6628 data_time: 0.5050 memory: 3625 2022/09/06 00:03:52 - mmengine - INFO - Epoch(val) [86][78/78] acc/top1: 0.7424 acc/top5: 0.9075 acc/mean1: 0.7423 2022/09/06 00:04:11 - mmengine - INFO - Epoch(train) [87][20/940] lr: 1.0000e-04 eta: 2:23:51 time: 0.9311 data_time: 0.2849 memory: 24011 grad_norm: 5.3346 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5850 loss: 0.5850 2022/09/06 00:04:23 - mmengine - INFO - Epoch(train) [87][40/940] lr: 1.0000e-04 eta: 2:23:38 time: 0.6350 data_time: 0.0419 memory: 24011 grad_norm: 5.4332 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5072 loss: 0.5072 2022/09/06 00:04:37 - mmengine - INFO - Epoch(train) [87][60/940] lr: 1.0000e-04 eta: 2:23:25 time: 0.6883 data_time: 0.0440 memory: 24011 grad_norm: 4.9916 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.4592 loss: 0.4592 2022/09/06 00:04:50 - mmengine - INFO - Epoch(train) [87][80/940] lr: 1.0000e-04 eta: 2:23:11 time: 0.6429 data_time: 0.0396 memory: 24011 grad_norm: 5.5409 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6460 loss: 0.6460 2022/09/06 00:05:03 - mmengine - INFO - Epoch(train) [87][100/940] lr: 1.0000e-04 eta: 2:22:58 time: 0.6678 data_time: 0.0575 memory: 24011 grad_norm: 6.1808 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5541 loss: 0.5541 2022/09/06 00:05:16 - mmengine - INFO - Epoch(train) [87][120/940] lr: 1.0000e-04 eta: 2:22:45 time: 0.6301 data_time: 0.0400 memory: 24011 grad_norm: 6.5518 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5852 loss: 0.5852 2022/09/06 00:05:29 - mmengine - INFO - Epoch(train) [87][140/940] lr: 1.0000e-04 eta: 2:22:32 time: 0.6405 data_time: 0.0421 memory: 24011 grad_norm: 5.5521 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5556 loss: 0.5556 2022/09/06 00:05:41 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:05:41 - mmengine - INFO - Epoch(train) [87][160/940] lr: 1.0000e-04 eta: 2:22:19 time: 0.6135 data_time: 0.0349 memory: 24011 grad_norm: 5.1034 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5217 loss: 0.5217 2022/09/06 00:05:55 - mmengine - INFO - Epoch(train) [87][180/940] lr: 1.0000e-04 eta: 2:22:06 time: 0.6706 data_time: 0.0376 memory: 24011 grad_norm: 5.4335 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4627 loss: 0.4627 2022/09/06 00:06:07 - mmengine - INFO - Epoch(train) [87][200/940] lr: 1.0000e-04 eta: 2:21:52 time: 0.6220 data_time: 0.0366 memory: 24011 grad_norm: 5.4551 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6557 loss: 0.6557 2022/09/06 00:06:20 - mmengine - INFO - Epoch(train) [87][220/940] lr: 1.0000e-04 eta: 2:21:39 time: 0.6656 data_time: 0.0928 memory: 24011 grad_norm: 5.3783 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5741 loss: 0.5741 2022/09/06 00:06:33 - mmengine - INFO - Epoch(train) [87][240/940] lr: 1.0000e-04 eta: 2:21:26 time: 0.6213 data_time: 0.0379 memory: 24011 grad_norm: 5.2393 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6084 loss: 0.6084 2022/09/06 00:06:46 - mmengine - INFO - Epoch(train) [87][260/940] lr: 1.0000e-04 eta: 2:21:13 time: 0.6809 data_time: 0.0391 memory: 24011 grad_norm: 5.4712 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5651 loss: 0.5651 2022/09/06 00:07:00 - mmengine - INFO - Epoch(train) [87][280/940] lr: 1.0000e-04 eta: 2:21:00 time: 0.6560 data_time: 0.0344 memory: 24011 grad_norm: 5.4634 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5533 loss: 0.5533 2022/09/06 00:07:12 - mmengine - INFO - Epoch(train) [87][300/940] lr: 1.0000e-04 eta: 2:20:47 time: 0.6444 data_time: 0.0418 memory: 24011 grad_norm: 5.5487 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4270 loss: 0.4270 2022/09/06 00:07:26 - mmengine - INFO - Epoch(train) [87][320/940] lr: 1.0000e-04 eta: 2:20:33 time: 0.6576 data_time: 0.0358 memory: 24011 grad_norm: 5.1858 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.4784 loss: 0.4784 2022/09/06 00:07:38 - mmengine - INFO - Epoch(train) [87][340/940] lr: 1.0000e-04 eta: 2:20:20 time: 0.6348 data_time: 0.0411 memory: 24011 grad_norm: 5.6032 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6061 loss: 0.6061 2022/09/06 00:07:51 - mmengine - INFO - Epoch(train) [87][360/940] lr: 1.0000e-04 eta: 2:20:07 time: 0.6153 data_time: 0.0309 memory: 24011 grad_norm: 6.0069 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5675 loss: 0.5675 2022/09/06 00:08:04 - mmengine - INFO - Epoch(train) [87][380/940] lr: 1.0000e-04 eta: 2:19:54 time: 0.6776 data_time: 0.0430 memory: 24011 grad_norm: 5.7793 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.6038 loss: 0.6038 2022/09/06 00:08:18 - mmengine - INFO - Epoch(train) [87][400/940] lr: 1.0000e-04 eta: 2:19:41 time: 0.7129 data_time: 0.0392 memory: 24011 grad_norm: 5.8355 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4856 loss: 0.4856 2022/09/06 00:08:30 - mmengine - INFO - Epoch(train) [87][420/940] lr: 1.0000e-04 eta: 2:19:28 time: 0.5934 data_time: 0.0384 memory: 24011 grad_norm: 5.2455 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5525 loss: 0.5525 2022/09/06 00:08:44 - mmengine - INFO - Epoch(train) [87][440/940] lr: 1.0000e-04 eta: 2:19:14 time: 0.6652 data_time: 0.0370 memory: 24011 grad_norm: 5.7658 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5459 loss: 0.5459 2022/09/06 00:08:56 - mmengine - INFO - Epoch(train) [87][460/940] lr: 1.0000e-04 eta: 2:19:01 time: 0.6158 data_time: 0.0403 memory: 24011 grad_norm: 5.7456 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6182 loss: 0.6182 2022/09/06 00:09:10 - mmengine - INFO - Epoch(train) [87][480/940] lr: 1.0000e-04 eta: 2:18:48 time: 0.7121 data_time: 0.0373 memory: 24011 grad_norm: 5.4141 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5145 loss: 0.5145 2022/09/06 00:09:23 - mmengine - INFO - Epoch(train) [87][500/940] lr: 1.0000e-04 eta: 2:18:35 time: 0.6338 data_time: 0.0431 memory: 24011 grad_norm: 5.5760 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5512 loss: 0.5512 2022/09/06 00:09:36 - mmengine - INFO - Epoch(train) [87][520/940] lr: 1.0000e-04 eta: 2:18:22 time: 0.6331 data_time: 0.0364 memory: 24011 grad_norm: 5.9147 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5708 loss: 0.5708 2022/09/06 00:09:48 - mmengine - INFO - Epoch(train) [87][540/940] lr: 1.0000e-04 eta: 2:18:09 time: 0.6002 data_time: 0.0430 memory: 24011 grad_norm: 5.5150 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5629 loss: 0.5629 2022/09/06 00:10:00 - mmengine - INFO - Epoch(train) [87][560/940] lr: 1.0000e-04 eta: 2:17:55 time: 0.6336 data_time: 0.0381 memory: 24011 grad_norm: 5.5754 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5861 loss: 0.5861 2022/09/06 00:10:13 - mmengine - INFO - Epoch(train) [87][580/940] lr: 1.0000e-04 eta: 2:17:42 time: 0.6491 data_time: 0.0448 memory: 24011 grad_norm: 5.3393 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5840 loss: 0.5840 2022/09/06 00:10:27 - mmengine - INFO - Epoch(train) [87][600/940] lr: 1.0000e-04 eta: 2:17:29 time: 0.6814 data_time: 0.0405 memory: 24011 grad_norm: 5.5363 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5897 loss: 0.5897 2022/09/06 00:10:40 - mmengine - INFO - Epoch(train) [87][620/940] lr: 1.0000e-04 eta: 2:17:16 time: 0.6540 data_time: 0.0555 memory: 24011 grad_norm: 6.0873 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5631 loss: 0.5631 2022/09/06 00:10:53 - mmengine - INFO - Epoch(train) [87][640/940] lr: 1.0000e-04 eta: 2:17:03 time: 0.6257 data_time: 0.0412 memory: 24011 grad_norm: 5.9499 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5887 loss: 0.5887 2022/09/06 00:11:06 - mmengine - INFO - Epoch(train) [87][660/940] lr: 1.0000e-04 eta: 2:16:50 time: 0.6540 data_time: 0.0417 memory: 24011 grad_norm: 5.5904 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5363 loss: 0.5363 2022/09/06 00:11:18 - mmengine - INFO - Epoch(train) [87][680/940] lr: 1.0000e-04 eta: 2:16:36 time: 0.6141 data_time: 0.0481 memory: 24011 grad_norm: 5.8281 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6185 loss: 0.6185 2022/09/06 00:11:31 - mmengine - INFO - Epoch(train) [87][700/940] lr: 1.0000e-04 eta: 2:16:23 time: 0.6447 data_time: 0.0403 memory: 24011 grad_norm: 5.2916 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5135 loss: 0.5135 2022/09/06 00:11:44 - mmengine - INFO - Epoch(train) [87][720/940] lr: 1.0000e-04 eta: 2:16:10 time: 0.6489 data_time: 0.0451 memory: 24011 grad_norm: 5.3675 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5276 loss: 0.5276 2022/09/06 00:11:57 - mmengine - INFO - Epoch(train) [87][740/940] lr: 1.0000e-04 eta: 2:15:57 time: 0.6484 data_time: 0.0355 memory: 24011 grad_norm: 5.2345 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5482 loss: 0.5482 2022/09/06 00:12:10 - mmengine - INFO - Epoch(train) [87][760/940] lr: 1.0000e-04 eta: 2:15:44 time: 0.6658 data_time: 0.0403 memory: 24011 grad_norm: 5.5066 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5318 loss: 0.5318 2022/09/06 00:12:23 - mmengine - INFO - Epoch(train) [87][780/940] lr: 1.0000e-04 eta: 2:15:30 time: 0.6397 data_time: 0.0360 memory: 24011 grad_norm: 6.1407 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5854 loss: 0.5854 2022/09/06 00:12:36 - mmengine - INFO - Epoch(train) [87][800/940] lr: 1.0000e-04 eta: 2:15:17 time: 0.6604 data_time: 0.0414 memory: 24011 grad_norm: 5.2095 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.4767 loss: 0.4767 2022/09/06 00:12:50 - mmengine - INFO - Epoch(train) [87][820/940] lr: 1.0000e-04 eta: 2:15:04 time: 0.6705 data_time: 0.0374 memory: 24011 grad_norm: 5.2470 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5419 loss: 0.5419 2022/09/06 00:13:02 - mmengine - INFO - Epoch(train) [87][840/940] lr: 1.0000e-04 eta: 2:14:51 time: 0.6397 data_time: 0.0368 memory: 24011 grad_norm: 5.6955 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5045 loss: 0.5045 2022/09/06 00:13:16 - mmengine - INFO - Epoch(train) [87][860/940] lr: 1.0000e-04 eta: 2:14:38 time: 0.6566 data_time: 0.0405 memory: 24011 grad_norm: 6.7752 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.4891 loss: 0.4891 2022/09/06 00:13:28 - mmengine - INFO - Epoch(train) [87][880/940] lr: 1.0000e-04 eta: 2:14:25 time: 0.6187 data_time: 0.0397 memory: 24011 grad_norm: 5.3671 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6074 loss: 0.6074 2022/09/06 00:13:41 - mmengine - INFO - Epoch(train) [87][900/940] lr: 1.0000e-04 eta: 2:14:12 time: 0.6578 data_time: 0.0518 memory: 24011 grad_norm: 5.2992 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5492 loss: 0.5492 2022/09/06 00:13:55 - mmengine - INFO - Epoch(train) [87][920/940] lr: 1.0000e-04 eta: 2:13:59 time: 0.6981 data_time: 0.0373 memory: 24011 grad_norm: 5.3183 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4752 loss: 0.4752 2022/09/06 00:14:06 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:14:06 - mmengine - INFO - Epoch(train) [87][940/940] lr: 1.0000e-04 eta: 2:13:45 time: 0.5500 data_time: 0.0258 memory: 24011 grad_norm: 5.7228 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5895 loss: 0.5895 2022/09/06 00:14:06 - mmengine - INFO - Saving checkpoint at 87 epochs 2022/09/06 00:14:26 - mmengine - INFO - Epoch(val) [87][20/78] eta: 0:00:41 time: 0.7127 data_time: 0.5562 memory: 3625 2022/09/06 00:14:35 - mmengine - INFO - Epoch(val) [87][40/78] eta: 0:00:17 time: 0.4616 data_time: 0.3043 memory: 3625 2022/09/06 00:14:48 - mmengine - INFO - Epoch(val) [87][60/78] eta: 0:00:11 time: 0.6398 data_time: 0.4844 memory: 3625 2022/09/06 00:14:57 - mmengine - INFO - Epoch(val) [87][78/78] acc/top1: 0.7409 acc/top5: 0.9071 acc/mean1: 0.7408 2022/09/06 00:15:15 - mmengine - INFO - Epoch(train) [88][20/940] lr: 1.0000e-04 eta: 2:13:33 time: 0.8892 data_time: 0.2570 memory: 24011 grad_norm: 5.2092 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5504 loss: 0.5504 2022/09/06 00:15:27 - mmengine - INFO - Epoch(train) [88][40/940] lr: 1.0000e-04 eta: 2:13:19 time: 0.6335 data_time: 0.0335 memory: 24011 grad_norm: 5.9259 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5486 loss: 0.5486 2022/09/06 00:15:41 - mmengine - INFO - Epoch(train) [88][60/940] lr: 1.0000e-04 eta: 2:13:06 time: 0.6894 data_time: 0.0437 memory: 24011 grad_norm: 5.2092 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5160 loss: 0.5160 2022/09/06 00:15:54 - mmengine - INFO - Epoch(train) [88][80/940] lr: 1.0000e-04 eta: 2:12:53 time: 0.6386 data_time: 0.0380 memory: 24011 grad_norm: 5.5071 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5218 loss: 0.5218 2022/09/06 00:16:08 - mmengine - INFO - Epoch(train) [88][100/940] lr: 1.0000e-04 eta: 2:12:40 time: 0.6934 data_time: 0.0380 memory: 24011 grad_norm: 5.1117 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6363 loss: 0.6363 2022/09/06 00:16:21 - mmengine - INFO - Epoch(train) [88][120/940] lr: 1.0000e-04 eta: 2:12:27 time: 0.6449 data_time: 0.0398 memory: 24011 grad_norm: 5.1973 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4693 loss: 0.4693 2022/09/06 00:16:34 - mmengine - INFO - Epoch(train) [88][140/940] lr: 1.0000e-04 eta: 2:12:14 time: 0.6507 data_time: 0.0395 memory: 24011 grad_norm: 5.3690 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5476 loss: 0.5476 2022/09/06 00:16:47 - mmengine - INFO - Epoch(train) [88][160/940] lr: 1.0000e-04 eta: 2:12:01 time: 0.6471 data_time: 0.0411 memory: 24011 grad_norm: 5.7208 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5726 loss: 0.5726 2022/09/06 00:17:00 - mmengine - INFO - Epoch(train) [88][180/940] lr: 1.0000e-04 eta: 2:11:48 time: 0.6641 data_time: 0.0369 memory: 24011 grad_norm: 5.8589 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4712 loss: 0.4712 2022/09/06 00:17:13 - mmengine - INFO - Epoch(train) [88][200/940] lr: 1.0000e-04 eta: 2:11:34 time: 0.6598 data_time: 0.0416 memory: 24011 grad_norm: 5.2885 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5501 loss: 0.5501 2022/09/06 00:17:26 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:17:26 - mmengine - INFO - Epoch(train) [88][220/940] lr: 1.0000e-04 eta: 2:11:21 time: 0.6385 data_time: 0.0420 memory: 24011 grad_norm: 5.2271 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.4905 loss: 0.4905 2022/09/06 00:17:38 - mmengine - INFO - Epoch(train) [88][240/940] lr: 1.0000e-04 eta: 2:11:08 time: 0.6190 data_time: 0.0459 memory: 24011 grad_norm: 5.2962 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5244 loss: 0.5244 2022/09/06 00:17:51 - mmengine - INFO - Epoch(train) [88][260/940] lr: 1.0000e-04 eta: 2:10:55 time: 0.6418 data_time: 0.0579 memory: 24011 grad_norm: 5.2669 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.4926 loss: 0.4926 2022/09/06 00:18:04 - mmengine - INFO - Epoch(train) [88][280/940] lr: 1.0000e-04 eta: 2:10:42 time: 0.6346 data_time: 0.0424 memory: 24011 grad_norm: 5.0199 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5485 loss: 0.5485 2022/09/06 00:18:18 - mmengine - INFO - Epoch(train) [88][300/940] lr: 1.0000e-04 eta: 2:10:29 time: 0.7049 data_time: 0.0390 memory: 24011 grad_norm: 6.1387 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5822 loss: 0.5822 2022/09/06 00:18:31 - mmengine - INFO - Epoch(train) [88][320/940] lr: 1.0000e-04 eta: 2:10:15 time: 0.6436 data_time: 0.0364 memory: 24011 grad_norm: 5.2840 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5520 loss: 0.5520 2022/09/06 00:18:44 - mmengine - INFO - Epoch(train) [88][340/940] lr: 1.0000e-04 eta: 2:10:02 time: 0.6529 data_time: 0.0486 memory: 24011 grad_norm: 5.5227 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6003 loss: 0.6003 2022/09/06 00:18:57 - mmengine - INFO - Epoch(train) [88][360/940] lr: 1.0000e-04 eta: 2:09:49 time: 0.6495 data_time: 0.0450 memory: 24011 grad_norm: 5.9326 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5568 loss: 0.5568 2022/09/06 00:19:10 - mmengine - INFO - Epoch(train) [88][380/940] lr: 1.0000e-04 eta: 2:09:36 time: 0.6616 data_time: 0.0366 memory: 24011 grad_norm: 5.2953 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5680 loss: 0.5680 2022/09/06 00:19:22 - mmengine - INFO - Epoch(train) [88][400/940] lr: 1.0000e-04 eta: 2:09:23 time: 0.6010 data_time: 0.0429 memory: 24011 grad_norm: 5.4429 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5961 loss: 0.5961 2022/09/06 00:19:35 - mmengine - INFO - Epoch(train) [88][420/940] lr: 1.0000e-04 eta: 2:09:10 time: 0.6446 data_time: 0.0483 memory: 24011 grad_norm: 5.6819 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4632 loss: 0.4632 2022/09/06 00:19:48 - mmengine - INFO - Epoch(train) [88][440/940] lr: 1.0000e-04 eta: 2:08:56 time: 0.6236 data_time: 0.0479 memory: 24011 grad_norm: 6.0742 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5205 loss: 0.5205 2022/09/06 00:20:00 - mmengine - INFO - Epoch(train) [88][460/940] lr: 1.0000e-04 eta: 2:08:43 time: 0.6421 data_time: 0.0438 memory: 24011 grad_norm: 5.3237 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5617 loss: 0.5617 2022/09/06 00:20:14 - mmengine - INFO - Epoch(train) [88][480/940] lr: 1.0000e-04 eta: 2:08:30 time: 0.6744 data_time: 0.0396 memory: 24011 grad_norm: 5.4117 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.7014 loss: 0.7014 2022/09/06 00:20:28 - mmengine - INFO - Epoch(train) [88][500/940] lr: 1.0000e-04 eta: 2:08:17 time: 0.6884 data_time: 0.0440 memory: 24011 grad_norm: 5.1715 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5802 loss: 0.5802 2022/09/06 00:20:40 - mmengine - INFO - Epoch(train) [88][520/940] lr: 1.0000e-04 eta: 2:08:04 time: 0.6157 data_time: 0.0447 memory: 24011 grad_norm: 5.5343 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5528 loss: 0.5528 2022/09/06 00:20:54 - mmengine - INFO - Epoch(train) [88][540/940] lr: 1.0000e-04 eta: 2:07:51 time: 0.7008 data_time: 0.0403 memory: 24011 grad_norm: 5.8470 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 0.5432 loss: 0.5432 2022/09/06 00:21:06 - mmengine - INFO - Epoch(train) [88][560/940] lr: 1.0000e-04 eta: 2:07:38 time: 0.6126 data_time: 0.0398 memory: 24011 grad_norm: 5.6715 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5244 loss: 0.5244 2022/09/06 00:21:19 - mmengine - INFO - Epoch(train) [88][580/940] lr: 1.0000e-04 eta: 2:07:24 time: 0.6213 data_time: 0.0394 memory: 24011 grad_norm: 5.1871 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4962 loss: 0.4962 2022/09/06 00:21:31 - mmengine - INFO - Epoch(train) [88][600/940] lr: 1.0000e-04 eta: 2:07:11 time: 0.6063 data_time: 0.0389 memory: 24011 grad_norm: 5.8019 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5148 loss: 0.5148 2022/09/06 00:21:45 - mmengine - INFO - Epoch(train) [88][620/940] lr: 1.0000e-04 eta: 2:06:58 time: 0.6810 data_time: 0.0396 memory: 24011 grad_norm: 5.6953 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5946 loss: 0.5946 2022/09/06 00:21:57 - mmengine - INFO - Epoch(train) [88][640/940] lr: 1.0000e-04 eta: 2:06:45 time: 0.6515 data_time: 0.0348 memory: 24011 grad_norm: 9.1647 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5171 loss: 0.5171 2022/09/06 00:22:11 - mmengine - INFO - Epoch(train) [88][660/940] lr: 1.0000e-04 eta: 2:06:32 time: 0.6595 data_time: 0.0389 memory: 24011 grad_norm: 5.7835 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4860 loss: 0.4860 2022/09/06 00:22:24 - mmengine - INFO - Epoch(train) [88][680/940] lr: 1.0000e-04 eta: 2:06:18 time: 0.6428 data_time: 0.0419 memory: 24011 grad_norm: 5.3741 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.4897 loss: 0.4897 2022/09/06 00:22:36 - mmengine - INFO - Epoch(train) [88][700/940] lr: 1.0000e-04 eta: 2:06:05 time: 0.6361 data_time: 0.0378 memory: 24011 grad_norm: 6.1628 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4946 loss: 0.4946 2022/09/06 00:22:49 - mmengine - INFO - Epoch(train) [88][720/940] lr: 1.0000e-04 eta: 2:05:52 time: 0.6229 data_time: 0.0444 memory: 24011 grad_norm: 5.8364 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5008 loss: 0.5008 2022/09/06 00:23:01 - mmengine - INFO - Epoch(train) [88][740/940] lr: 1.0000e-04 eta: 2:05:39 time: 0.6217 data_time: 0.0382 memory: 24011 grad_norm: 5.1480 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4896 loss: 0.4896 2022/09/06 00:23:15 - mmengine - INFO - Epoch(train) [88][760/940] lr: 1.0000e-04 eta: 2:05:26 time: 0.6646 data_time: 0.0401 memory: 24011 grad_norm: 6.1718 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5365 loss: 0.5365 2022/09/06 00:23:28 - mmengine - INFO - Epoch(train) [88][780/940] lr: 1.0000e-04 eta: 2:05:13 time: 0.6678 data_time: 0.0384 memory: 24011 grad_norm: 5.3068 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5653 loss: 0.5653 2022/09/06 00:23:41 - mmengine - INFO - Epoch(train) [88][800/940] lr: 1.0000e-04 eta: 2:04:59 time: 0.6553 data_time: 0.0352 memory: 24011 grad_norm: 5.7279 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4955 loss: 0.4955 2022/09/06 00:23:54 - mmengine - INFO - Epoch(train) [88][820/940] lr: 1.0000e-04 eta: 2:04:46 time: 0.6558 data_time: 0.0355 memory: 24011 grad_norm: 5.3285 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5373 loss: 0.5373 2022/09/06 00:24:07 - mmengine - INFO - Epoch(train) [88][840/940] lr: 1.0000e-04 eta: 2:04:33 time: 0.6461 data_time: 0.0493 memory: 24011 grad_norm: 5.0568 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5032 loss: 0.5032 2022/09/06 00:24:20 - mmengine - INFO - Epoch(train) [88][860/940] lr: 1.0000e-04 eta: 2:04:20 time: 0.6622 data_time: 0.0611 memory: 24011 grad_norm: 5.7675 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5829 loss: 0.5829 2022/09/06 00:24:34 - mmengine - INFO - Epoch(train) [88][880/940] lr: 1.0000e-04 eta: 2:04:07 time: 0.6889 data_time: 0.0429 memory: 24011 grad_norm: 5.3270 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5693 loss: 0.5693 2022/09/06 00:24:47 - mmengine - INFO - Epoch(train) [88][900/940] lr: 1.0000e-04 eta: 2:03:54 time: 0.6242 data_time: 0.0494 memory: 24011 grad_norm: 5.1856 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5495 loss: 0.5495 2022/09/06 00:25:00 - mmengine - INFO - Epoch(train) [88][920/940] lr: 1.0000e-04 eta: 2:03:41 time: 0.6929 data_time: 0.0375 memory: 24011 grad_norm: 6.1271 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5447 loss: 0.5447 2022/09/06 00:25:12 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:25:12 - mmengine - INFO - Epoch(train) [88][940/940] lr: 1.0000e-04 eta: 2:03:27 time: 0.5549 data_time: 0.0274 memory: 24011 grad_norm: 5.8128 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5505 loss: 0.5505 2022/09/06 00:25:25 - mmengine - INFO - Epoch(val) [88][20/78] eta: 0:00:40 time: 0.6922 data_time: 0.5335 memory: 3625 2022/09/06 00:25:36 - mmengine - INFO - Epoch(val) [88][40/78] eta: 0:00:19 time: 0.5063 data_time: 0.3467 memory: 3625 2022/09/06 00:25:49 - mmengine - INFO - Epoch(val) [88][60/78] eta: 0:00:11 time: 0.6481 data_time: 0.4841 memory: 3625 2022/09/06 00:25:59 - mmengine - INFO - Epoch(val) [88][78/78] acc/top1: 0.7409 acc/top5: 0.9076 acc/mean1: 0.7408 2022/09/06 00:26:17 - mmengine - INFO - Epoch(train) [89][20/940] lr: 1.0000e-04 eta: 2:03:15 time: 0.8768 data_time: 0.2983 memory: 24011 grad_norm: 5.6866 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5502 loss: 0.5502 2022/09/06 00:26:30 - mmengine - INFO - Epoch(train) [89][40/940] lr: 1.0000e-04 eta: 2:03:02 time: 0.6684 data_time: 0.0812 memory: 24011 grad_norm: 5.4214 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4413 loss: 0.4413 2022/09/06 00:26:44 - mmengine - INFO - Epoch(train) [89][60/940] lr: 1.0000e-04 eta: 2:02:49 time: 0.6931 data_time: 0.0398 memory: 24011 grad_norm: 6.0095 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.6016 loss: 0.6016 2022/09/06 00:26:56 - mmengine - INFO - Epoch(train) [89][80/940] lr: 1.0000e-04 eta: 2:02:35 time: 0.6050 data_time: 0.0346 memory: 24011 grad_norm: 5.5336 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5393 loss: 0.5393 2022/09/06 00:27:10 - mmengine - INFO - Epoch(train) [89][100/940] lr: 1.0000e-04 eta: 2:02:22 time: 0.7096 data_time: 0.0397 memory: 24011 grad_norm: 5.7105 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5292 loss: 0.5292 2022/09/06 00:27:22 - mmengine - INFO - Epoch(train) [89][120/940] lr: 1.0000e-04 eta: 2:02:09 time: 0.5878 data_time: 0.0344 memory: 24011 grad_norm: 5.6806 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5700 loss: 0.5700 2022/09/06 00:27:36 - mmengine - INFO - Epoch(train) [89][140/940] lr: 1.0000e-04 eta: 2:01:56 time: 0.6913 data_time: 0.0401 memory: 24011 grad_norm: 5.9034 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5267 loss: 0.5267 2022/09/06 00:27:49 - mmengine - INFO - Epoch(train) [89][160/940] lr: 1.0000e-04 eta: 2:01:43 time: 0.6589 data_time: 0.0401 memory: 24011 grad_norm: 5.4678 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5220 loss: 0.5220 2022/09/06 00:28:02 - mmengine - INFO - Epoch(train) [89][180/940] lr: 1.0000e-04 eta: 2:01:30 time: 0.6595 data_time: 0.0379 memory: 24011 grad_norm: 5.4003 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5918 loss: 0.5918 2022/09/06 00:28:15 - mmengine - INFO - Epoch(train) [89][200/940] lr: 1.0000e-04 eta: 2:01:17 time: 0.6324 data_time: 0.0379 memory: 24011 grad_norm: 5.3113 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5494 loss: 0.5494 2022/09/06 00:28:28 - mmengine - INFO - Epoch(train) [89][220/940] lr: 1.0000e-04 eta: 2:01:03 time: 0.6514 data_time: 0.0401 memory: 24011 grad_norm: 5.0810 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6007 loss: 0.6007 2022/09/06 00:28:41 - mmengine - INFO - Epoch(train) [89][240/940] lr: 1.0000e-04 eta: 2:00:50 time: 0.6322 data_time: 0.0409 memory: 24011 grad_norm: 5.8809 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5032 loss: 0.5032 2022/09/06 00:28:54 - mmengine - INFO - Epoch(train) [89][260/940] lr: 1.0000e-04 eta: 2:00:37 time: 0.6482 data_time: 0.0359 memory: 24011 grad_norm: 6.1271 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5647 loss: 0.5647 2022/09/06 00:29:07 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:29:07 - mmengine - INFO - Epoch(train) [89][280/940] lr: 1.0000e-04 eta: 2:00:24 time: 0.6619 data_time: 0.0416 memory: 24011 grad_norm: 5.5519 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5558 loss: 0.5558 2022/09/06 00:29:20 - mmengine - INFO - Epoch(train) [89][300/940] lr: 1.0000e-04 eta: 2:00:11 time: 0.6593 data_time: 0.0355 memory: 24011 grad_norm: 5.3735 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5275 loss: 0.5275 2022/09/06 00:29:33 - mmengine - INFO - Epoch(train) [89][320/940] lr: 1.0000e-04 eta: 1:59:58 time: 0.6612 data_time: 0.0421 memory: 24011 grad_norm: 6.1220 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4653 loss: 0.4653 2022/09/06 00:29:47 - mmengine - INFO - Epoch(train) [89][340/940] lr: 1.0000e-04 eta: 1:59:45 time: 0.6555 data_time: 0.0395 memory: 24011 grad_norm: 10.8102 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5065 loss: 0.5065 2022/09/06 00:29:59 - mmengine - INFO - Epoch(train) [89][360/940] lr: 1.0000e-04 eta: 1:59:31 time: 0.6171 data_time: 0.0438 memory: 24011 grad_norm: 5.6179 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5667 loss: 0.5667 2022/09/06 00:30:11 - mmengine - INFO - Epoch(train) [89][380/940] lr: 1.0000e-04 eta: 1:59:18 time: 0.6209 data_time: 0.0332 memory: 24011 grad_norm: 5.4867 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.4972 loss: 0.4972 2022/09/06 00:30:24 - mmengine - INFO - Epoch(train) [89][400/940] lr: 1.0000e-04 eta: 1:59:05 time: 0.6303 data_time: 0.0568 memory: 24011 grad_norm: 5.3186 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5271 loss: 0.5271 2022/09/06 00:30:37 - mmengine - INFO - Epoch(train) [89][420/940] lr: 1.0000e-04 eta: 1:58:52 time: 0.6727 data_time: 0.0488 memory: 24011 grad_norm: 5.7540 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5146 loss: 0.5146 2022/09/06 00:30:50 - mmengine - INFO - Epoch(train) [89][440/940] lr: 1.0000e-04 eta: 1:58:39 time: 0.6338 data_time: 0.0417 memory: 24011 grad_norm: 5.6274 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5496 loss: 0.5496 2022/09/06 00:31:04 - mmengine - INFO - Epoch(train) [89][460/940] lr: 1.0000e-04 eta: 1:58:26 time: 0.6945 data_time: 0.0383 memory: 24011 grad_norm: 5.6012 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5364 loss: 0.5364 2022/09/06 00:31:18 - mmengine - INFO - Epoch(train) [89][480/940] lr: 1.0000e-04 eta: 1:58:12 time: 0.6853 data_time: 0.0337 memory: 24011 grad_norm: 5.3333 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4388 loss: 0.4388 2022/09/06 00:31:31 - mmengine - INFO - Epoch(train) [89][500/940] lr: 1.0000e-04 eta: 1:57:59 time: 0.6547 data_time: 0.0383 memory: 24011 grad_norm: 5.9745 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4913 loss: 0.4913 2022/09/06 00:31:43 - mmengine - INFO - Epoch(train) [89][520/940] lr: 1.0000e-04 eta: 1:57:46 time: 0.6206 data_time: 0.0368 memory: 24011 grad_norm: 5.4131 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5704 loss: 0.5704 2022/09/06 00:31:57 - mmengine - INFO - Epoch(train) [89][540/940] lr: 1.0000e-04 eta: 1:57:33 time: 0.6721 data_time: 0.0394 memory: 24011 grad_norm: 6.1975 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5676 loss: 0.5676 2022/09/06 00:32:10 - mmengine - INFO - Epoch(train) [89][560/940] lr: 1.0000e-04 eta: 1:57:20 time: 0.6481 data_time: 0.0433 memory: 24011 grad_norm: 5.6703 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5028 loss: 0.5028 2022/09/06 00:32:23 - mmengine - INFO - Epoch(train) [89][580/940] lr: 1.0000e-04 eta: 1:57:07 time: 0.6823 data_time: 0.0383 memory: 24011 grad_norm: 5.4423 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5659 loss: 0.5659 2022/09/06 00:32:36 - mmengine - INFO - Epoch(train) [89][600/940] lr: 1.0000e-04 eta: 1:56:54 time: 0.6276 data_time: 0.0419 memory: 24011 grad_norm: 5.2574 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5750 loss: 0.5750 2022/09/06 00:32:49 - mmengine - INFO - Epoch(train) [89][620/940] lr: 1.0000e-04 eta: 1:56:40 time: 0.6441 data_time: 0.0385 memory: 24011 grad_norm: 6.0601 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4836 loss: 0.4836 2022/09/06 00:33:01 - mmengine - INFO - Epoch(train) [89][640/940] lr: 1.0000e-04 eta: 1:56:27 time: 0.5920 data_time: 0.0384 memory: 24011 grad_norm: 5.1480 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5932 loss: 0.5932 2022/09/06 00:33:14 - mmengine - INFO - Epoch(train) [89][660/940] lr: 1.0000e-04 eta: 1:56:14 time: 0.6856 data_time: 0.0466 memory: 24011 grad_norm: 5.9531 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4967 loss: 0.4967 2022/09/06 00:33:26 - mmengine - INFO - Epoch(train) [89][680/940] lr: 1.0000e-04 eta: 1:56:01 time: 0.6001 data_time: 0.0416 memory: 24011 grad_norm: 6.9121 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5396 loss: 0.5396 2022/09/06 00:33:39 - mmengine - INFO - Epoch(train) [89][700/940] lr: 1.0000e-04 eta: 1:55:48 time: 0.6156 data_time: 0.0387 memory: 24011 grad_norm: 6.0879 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5651 loss: 0.5651 2022/09/06 00:33:52 - mmengine - INFO - Epoch(train) [89][720/940] lr: 1.0000e-04 eta: 1:55:34 time: 0.6720 data_time: 0.0536 memory: 24011 grad_norm: 5.5734 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5713 loss: 0.5713 2022/09/06 00:34:06 - mmengine - INFO - Epoch(train) [89][740/940] lr: 1.0000e-04 eta: 1:55:21 time: 0.6706 data_time: 0.0854 memory: 24011 grad_norm: 5.6880 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6119 loss: 0.6119 2022/09/06 00:34:18 - mmengine - INFO - Epoch(train) [89][760/940] lr: 1.0000e-04 eta: 1:55:08 time: 0.6387 data_time: 0.0396 memory: 24011 grad_norm: 5.5936 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5465 loss: 0.5465 2022/09/06 00:34:31 - mmengine - INFO - Epoch(train) [89][780/940] lr: 1.0000e-04 eta: 1:54:55 time: 0.6426 data_time: 0.0525 memory: 24011 grad_norm: 5.3003 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5423 loss: 0.5423 2022/09/06 00:34:45 - mmengine - INFO - Epoch(train) [89][800/940] lr: 1.0000e-04 eta: 1:54:42 time: 0.6672 data_time: 0.0472 memory: 24011 grad_norm: 5.7638 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 0.5991 loss: 0.5991 2022/09/06 00:34:57 - mmengine - INFO - Epoch(train) [89][820/940] lr: 1.0000e-04 eta: 1:54:29 time: 0.6209 data_time: 0.0349 memory: 24011 grad_norm: 5.3929 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5338 loss: 0.5338 2022/09/06 00:35:11 - mmengine - INFO - Epoch(train) [89][840/940] lr: 1.0000e-04 eta: 1:54:16 time: 0.6895 data_time: 0.0333 memory: 24011 grad_norm: 5.4946 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4608 loss: 0.4608 2022/09/06 00:35:25 - mmengine - INFO - Epoch(train) [89][860/940] lr: 1.0000e-04 eta: 1:54:03 time: 0.7239 data_time: 0.0410 memory: 24011 grad_norm: 5.7919 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.6182 loss: 0.6182 2022/09/06 00:35:37 - mmengine - INFO - Epoch(train) [89][880/940] lr: 1.0000e-04 eta: 1:53:49 time: 0.6050 data_time: 0.0340 memory: 24011 grad_norm: 5.1957 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5935 loss: 0.5935 2022/09/06 00:35:50 - mmengine - INFO - Epoch(train) [89][900/940] lr: 1.0000e-04 eta: 1:53:36 time: 0.6332 data_time: 0.0378 memory: 24011 grad_norm: 5.7182 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6633 loss: 0.6633 2022/09/06 00:36:03 - mmengine - INFO - Epoch(train) [89][920/940] lr: 1.0000e-04 eta: 1:53:23 time: 0.6612 data_time: 0.0443 memory: 24011 grad_norm: 5.5440 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5489 loss: 0.5489 2022/09/06 00:36:15 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:36:15 - mmengine - INFO - Epoch(train) [89][940/940] lr: 1.0000e-04 eta: 1:53:10 time: 0.5584 data_time: 0.0266 memory: 24011 grad_norm: 5.3866 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5088 loss: 0.5088 2022/09/06 00:36:29 - mmengine - INFO - Epoch(val) [89][20/78] eta: 0:00:40 time: 0.7004 data_time: 0.5418 memory: 3625 2022/09/06 00:36:38 - mmengine - INFO - Epoch(val) [89][40/78] eta: 0:00:17 time: 0.4619 data_time: 0.3038 memory: 3625 2022/09/06 00:36:51 - mmengine - INFO - Epoch(val) [89][60/78] eta: 0:00:11 time: 0.6545 data_time: 0.4951 memory: 3625 2022/09/06 00:37:01 - mmengine - INFO - Epoch(val) [89][78/78] acc/top1: 0.7410 acc/top5: 0.9072 acc/mean1: 0.7409 2022/09/06 00:37:20 - mmengine - INFO - Epoch(train) [90][20/940] lr: 1.0000e-04 eta: 1:52:57 time: 0.9327 data_time: 0.2638 memory: 24011 grad_norm: 5.6826 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.4780 loss: 0.4780 2022/09/06 00:37:33 - mmengine - INFO - Epoch(train) [90][40/940] lr: 1.0000e-04 eta: 1:52:44 time: 0.6263 data_time: 0.0502 memory: 24011 grad_norm: 6.5050 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5416 loss: 0.5416 2022/09/06 00:37:47 - mmengine - INFO - Epoch(train) [90][60/940] lr: 1.0000e-04 eta: 1:52:31 time: 0.6984 data_time: 0.0456 memory: 24011 grad_norm: 5.5744 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5549 loss: 0.5549 2022/09/06 00:37:59 - mmengine - INFO - Epoch(train) [90][80/940] lr: 1.0000e-04 eta: 1:52:18 time: 0.6141 data_time: 0.0423 memory: 24011 grad_norm: 5.2457 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.5699 loss: 0.5699 2022/09/06 00:38:12 - mmengine - INFO - Epoch(train) [90][100/940] lr: 1.0000e-04 eta: 1:52:05 time: 0.6620 data_time: 0.0378 memory: 24011 grad_norm: 5.6881 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5293 loss: 0.5293 2022/09/06 00:38:25 - mmengine - INFO - Epoch(train) [90][120/940] lr: 1.0000e-04 eta: 1:51:51 time: 0.6331 data_time: 0.0432 memory: 24011 grad_norm: 5.2640 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6239 loss: 0.6239 2022/09/06 00:38:38 - mmengine - INFO - Epoch(train) [90][140/940] lr: 1.0000e-04 eta: 1:51:38 time: 0.6661 data_time: 0.0418 memory: 24011 grad_norm: 6.5734 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4839 loss: 0.4839 2022/09/06 00:38:51 - mmengine - INFO - Epoch(train) [90][160/940] lr: 1.0000e-04 eta: 1:51:25 time: 0.6192 data_time: 0.0422 memory: 24011 grad_norm: 5.4070 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.4606 loss: 0.4606 2022/09/06 00:39:04 - mmengine - INFO - Epoch(train) [90][180/940] lr: 1.0000e-04 eta: 1:51:12 time: 0.6856 data_time: 0.0486 memory: 24011 grad_norm: 6.1713 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5082 loss: 0.5082 2022/09/06 00:39:17 - mmengine - INFO - Epoch(train) [90][200/940] lr: 1.0000e-04 eta: 1:50:59 time: 0.6520 data_time: 0.0393 memory: 24011 grad_norm: 5.6580 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4698 loss: 0.4698 2022/09/06 00:39:31 - mmengine - INFO - Epoch(train) [90][220/940] lr: 1.0000e-04 eta: 1:50:46 time: 0.6952 data_time: 0.0484 memory: 24011 grad_norm: 5.4141 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5924 loss: 0.5924 2022/09/06 00:39:43 - mmengine - INFO - Epoch(train) [90][240/940] lr: 1.0000e-04 eta: 1:50:33 time: 0.5946 data_time: 0.0330 memory: 24011 grad_norm: 5.4922 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5322 loss: 0.5322 2022/09/06 00:39:57 - mmengine - INFO - Epoch(train) [90][260/940] lr: 1.0000e-04 eta: 1:50:20 time: 0.6924 data_time: 0.0693 memory: 24011 grad_norm: 5.6618 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5269 loss: 0.5269 2022/09/06 00:40:10 - mmengine - INFO - Epoch(train) [90][280/940] lr: 1.0000e-04 eta: 1:50:06 time: 0.6269 data_time: 0.0527 memory: 24011 grad_norm: 5.5888 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4654 loss: 0.4654 2022/09/06 00:40:23 - mmengine - INFO - Epoch(train) [90][300/940] lr: 1.0000e-04 eta: 1:49:53 time: 0.6568 data_time: 0.0392 memory: 24011 grad_norm: 5.8077 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5033 loss: 0.5033 2022/09/06 00:40:35 - mmengine - INFO - Epoch(train) [90][320/940] lr: 1.0000e-04 eta: 1:49:40 time: 0.6147 data_time: 0.0407 memory: 24011 grad_norm: 5.7988 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.4542 loss: 0.4542 2022/09/06 00:40:49 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:40:49 - mmengine - INFO - Epoch(train) [90][340/940] lr: 1.0000e-04 eta: 1:49:27 time: 0.7052 data_time: 0.0427 memory: 24011 grad_norm: 5.3042 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.4888 loss: 0.4888 2022/09/06 00:41:01 - mmengine - INFO - Epoch(train) [90][360/940] lr: 1.0000e-04 eta: 1:49:14 time: 0.6082 data_time: 0.0502 memory: 24011 grad_norm: 5.6920 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5622 loss: 0.5622 2022/09/06 00:41:15 - mmengine - INFO - Epoch(train) [90][380/940] lr: 1.0000e-04 eta: 1:49:01 time: 0.6979 data_time: 0.0387 memory: 24011 grad_norm: 5.2653 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5222 loss: 0.5222 2022/09/06 00:41:28 - mmengine - INFO - Epoch(train) [90][400/940] lr: 1.0000e-04 eta: 1:48:47 time: 0.6405 data_time: 0.0519 memory: 24011 grad_norm: 5.5836 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5098 loss: 0.5098 2022/09/06 00:41:41 - mmengine - INFO - Epoch(train) [90][420/940] lr: 1.0000e-04 eta: 1:48:34 time: 0.6724 data_time: 0.0363 memory: 24011 grad_norm: 5.4010 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5155 loss: 0.5155 2022/09/06 00:41:53 - mmengine - INFO - Epoch(train) [90][440/940] lr: 1.0000e-04 eta: 1:48:21 time: 0.5898 data_time: 0.0414 memory: 24011 grad_norm: 5.3499 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5254 loss: 0.5254 2022/09/06 00:42:06 - mmengine - INFO - Epoch(train) [90][460/940] lr: 1.0000e-04 eta: 1:48:08 time: 0.6390 data_time: 0.0395 memory: 24011 grad_norm: 5.1961 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5087 loss: 0.5087 2022/09/06 00:42:18 - mmengine - INFO - Epoch(train) [90][480/940] lr: 1.0000e-04 eta: 1:47:55 time: 0.6101 data_time: 0.0389 memory: 24011 grad_norm: 5.8887 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6109 loss: 0.6109 2022/09/06 00:42:32 - mmengine - INFO - Epoch(train) [90][500/940] lr: 1.0000e-04 eta: 1:47:42 time: 0.6649 data_time: 0.0390 memory: 24011 grad_norm: 5.2844 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5140 loss: 0.5140 2022/09/06 00:42:45 - mmengine - INFO - Epoch(train) [90][520/940] lr: 1.0000e-04 eta: 1:47:28 time: 0.6692 data_time: 0.0425 memory: 24011 grad_norm: 5.6660 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5368 loss: 0.5368 2022/09/06 00:42:59 - mmengine - INFO - Epoch(train) [90][540/940] lr: 1.0000e-04 eta: 1:47:15 time: 0.6792 data_time: 0.0424 memory: 24011 grad_norm: 5.7502 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.4960 loss: 0.4960 2022/09/06 00:43:12 - mmengine - INFO - Epoch(train) [90][560/940] lr: 1.0000e-04 eta: 1:47:02 time: 0.6496 data_time: 0.0392 memory: 24011 grad_norm: 5.4021 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5486 loss: 0.5486 2022/09/06 00:43:25 - mmengine - INFO - Epoch(train) [90][580/940] lr: 1.0000e-04 eta: 1:46:49 time: 0.6635 data_time: 0.0408 memory: 24011 grad_norm: 5.3927 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5507 loss: 0.5507 2022/09/06 00:43:38 - mmengine - INFO - Epoch(train) [90][600/940] lr: 1.0000e-04 eta: 1:46:36 time: 0.6580 data_time: 0.0430 memory: 24011 grad_norm: 6.1326 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5245 loss: 0.5245 2022/09/06 00:43:51 - mmengine - INFO - Epoch(train) [90][620/940] lr: 1.0000e-04 eta: 1:46:23 time: 0.6256 data_time: 0.0406 memory: 24011 grad_norm: 5.2908 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5858 loss: 0.5858 2022/09/06 00:44:04 - mmengine - INFO - Epoch(train) [90][640/940] lr: 1.0000e-04 eta: 1:46:10 time: 0.6360 data_time: 0.0498 memory: 24011 grad_norm: 5.4062 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5618 loss: 0.5618 2022/09/06 00:44:17 - mmengine - INFO - Epoch(train) [90][660/940] lr: 1.0000e-04 eta: 1:45:56 time: 0.6774 data_time: 0.0524 memory: 24011 grad_norm: 5.1246 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5852 loss: 0.5852 2022/09/06 00:44:30 - mmengine - INFO - Epoch(train) [90][680/940] lr: 1.0000e-04 eta: 1:45:43 time: 0.6372 data_time: 0.0399 memory: 24011 grad_norm: 5.5810 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5211 loss: 0.5211 2022/09/06 00:44:43 - mmengine - INFO - Epoch(train) [90][700/940] lr: 1.0000e-04 eta: 1:45:30 time: 0.6538 data_time: 0.0349 memory: 24011 grad_norm: 5.3564 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5041 loss: 0.5041 2022/09/06 00:44:55 - mmengine - INFO - Epoch(train) [90][720/940] lr: 1.0000e-04 eta: 1:45:17 time: 0.6054 data_time: 0.0442 memory: 24011 grad_norm: 5.4715 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5384 loss: 0.5384 2022/09/06 00:45:08 - mmengine - INFO - Epoch(train) [90][740/940] lr: 1.0000e-04 eta: 1:45:04 time: 0.6464 data_time: 0.0410 memory: 24011 grad_norm: 5.7112 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5064 loss: 0.5064 2022/09/06 00:45:20 - mmengine - INFO - Epoch(train) [90][760/940] lr: 1.0000e-04 eta: 1:44:51 time: 0.6122 data_time: 0.0394 memory: 24011 grad_norm: 6.2667 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5611 loss: 0.5611 2022/09/06 00:45:33 - mmengine - INFO - Epoch(train) [90][780/940] lr: 1.0000e-04 eta: 1:44:37 time: 0.6715 data_time: 0.0451 memory: 24011 grad_norm: 5.4340 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4459 loss: 0.4459 2022/09/06 00:45:46 - mmengine - INFO - Epoch(train) [90][800/940] lr: 1.0000e-04 eta: 1:44:24 time: 0.6109 data_time: 0.0389 memory: 24011 grad_norm: 6.0533 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5662 loss: 0.5662 2022/09/06 00:45:59 - mmengine - INFO - Epoch(train) [90][820/940] lr: 1.0000e-04 eta: 1:44:11 time: 0.6675 data_time: 0.0396 memory: 24011 grad_norm: 5.6947 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5308 loss: 0.5308 2022/09/06 00:46:11 - mmengine - INFO - Epoch(train) [90][840/940] lr: 1.0000e-04 eta: 1:43:58 time: 0.6152 data_time: 0.0548 memory: 24011 grad_norm: 5.4822 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5774 loss: 0.5774 2022/09/06 00:46:24 - mmengine - INFO - Epoch(train) [90][860/940] lr: 1.0000e-04 eta: 1:43:45 time: 0.6310 data_time: 0.0368 memory: 24011 grad_norm: 5.6005 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.6502 loss: 0.6502 2022/09/06 00:46:37 - mmengine - INFO - Epoch(train) [90][880/940] lr: 1.0000e-04 eta: 1:43:31 time: 0.6429 data_time: 0.0697 memory: 24011 grad_norm: 5.7713 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5415 loss: 0.5415 2022/09/06 00:46:50 - mmengine - INFO - Epoch(train) [90][900/940] lr: 1.0000e-04 eta: 1:43:18 time: 0.6482 data_time: 0.0363 memory: 24011 grad_norm: 5.3673 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6154 loss: 0.6154 2022/09/06 00:47:04 - mmengine - INFO - Epoch(train) [90][920/940] lr: 1.0000e-04 eta: 1:43:05 time: 0.6878 data_time: 0.0362 memory: 24011 grad_norm: 6.1798 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5749 loss: 0.5749 2022/09/06 00:47:15 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:47:15 - mmengine - INFO - Epoch(train) [90][940/940] lr: 1.0000e-04 eta: 1:42:52 time: 0.5828 data_time: 0.0275 memory: 24011 grad_norm: 5.7289 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.4889 loss: 0.4889 2022/09/06 00:47:15 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/09/06 00:47:34 - mmengine - INFO - Epoch(val) [90][20/78] eta: 0:00:40 time: 0.6934 data_time: 0.5386 memory: 3625 2022/09/06 00:47:44 - mmengine - INFO - Epoch(val) [90][40/78] eta: 0:00:17 time: 0.4698 data_time: 0.3134 memory: 3625 2022/09/06 00:47:57 - mmengine - INFO - Epoch(val) [90][60/78] eta: 0:00:11 time: 0.6492 data_time: 0.4948 memory: 3625 2022/09/06 00:48:06 - mmengine - INFO - Epoch(val) [90][78/78] acc/top1: 0.7415 acc/top5: 0.9075 acc/mean1: 0.7414 2022/09/06 00:48:24 - mmengine - INFO - Epoch(train) [91][20/940] lr: 1.0000e-04 eta: 1:42:39 time: 0.8931 data_time: 0.2666 memory: 24011 grad_norm: 5.6551 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4897 loss: 0.4897 2022/09/06 00:48:37 - mmengine - INFO - Epoch(train) [91][40/940] lr: 1.0000e-04 eta: 1:42:26 time: 0.6383 data_time: 0.0499 memory: 24011 grad_norm: 5.2843 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4778 loss: 0.4778 2022/09/06 00:48:51 - mmengine - INFO - Epoch(train) [91][60/940] lr: 1.0000e-04 eta: 1:42:13 time: 0.7053 data_time: 0.0464 memory: 24011 grad_norm: 5.5684 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6083 loss: 0.6083 2022/09/06 00:49:04 - mmengine - INFO - Epoch(train) [91][80/940] lr: 1.0000e-04 eta: 1:42:00 time: 0.6611 data_time: 0.0397 memory: 24011 grad_norm: 5.8920 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.4964 loss: 0.4964 2022/09/06 00:49:18 - mmengine - INFO - Epoch(train) [91][100/940] lr: 1.0000e-04 eta: 1:41:47 time: 0.6658 data_time: 0.0414 memory: 24011 grad_norm: 6.5364 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.4821 loss: 0.4821 2022/09/06 00:49:30 - mmengine - INFO - Epoch(train) [91][120/940] lr: 1.0000e-04 eta: 1:41:34 time: 0.6315 data_time: 0.0329 memory: 24011 grad_norm: 5.3010 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5534 loss: 0.5534 2022/09/06 00:49:44 - mmengine - INFO - Epoch(train) [91][140/940] lr: 1.0000e-04 eta: 1:41:21 time: 0.6807 data_time: 0.0415 memory: 24011 grad_norm: 5.0481 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5986 loss: 0.5986 2022/09/06 00:49:57 - mmengine - INFO - Epoch(train) [91][160/940] lr: 1.0000e-04 eta: 1:41:07 time: 0.6425 data_time: 0.0529 memory: 24011 grad_norm: 5.9826 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5150 loss: 0.5150 2022/09/06 00:50:10 - mmengine - INFO - Epoch(train) [91][180/940] lr: 1.0000e-04 eta: 1:40:54 time: 0.6711 data_time: 0.0693 memory: 24011 grad_norm: 5.7900 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5705 loss: 0.5705 2022/09/06 00:50:22 - mmengine - INFO - Epoch(train) [91][200/940] lr: 1.0000e-04 eta: 1:40:41 time: 0.6047 data_time: 0.0302 memory: 24011 grad_norm: 6.3264 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5422 loss: 0.5422 2022/09/06 00:50:35 - mmengine - INFO - Epoch(train) [91][220/940] lr: 1.0000e-04 eta: 1:40:28 time: 0.6532 data_time: 0.0916 memory: 24011 grad_norm: 5.4938 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5185 loss: 0.5185 2022/09/06 00:50:48 - mmengine - INFO - Epoch(train) [91][240/940] lr: 1.0000e-04 eta: 1:40:15 time: 0.6297 data_time: 0.0641 memory: 24011 grad_norm: 5.8101 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5268 loss: 0.5268 2022/09/06 00:51:01 - mmengine - INFO - Epoch(train) [91][260/940] lr: 1.0000e-04 eta: 1:40:02 time: 0.6482 data_time: 0.0890 memory: 24011 grad_norm: 5.4619 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5478 loss: 0.5478 2022/09/06 00:51:14 - mmengine - INFO - Epoch(train) [91][280/940] lr: 1.0000e-04 eta: 1:39:48 time: 0.6476 data_time: 0.0771 memory: 24011 grad_norm: 5.6146 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4788 loss: 0.4788 2022/09/06 00:51:27 - mmengine - INFO - Epoch(train) [91][300/940] lr: 1.0000e-04 eta: 1:39:35 time: 0.6837 data_time: 0.1241 memory: 24011 grad_norm: 5.2957 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5913 loss: 0.5913 2022/09/06 00:51:40 - mmengine - INFO - Epoch(train) [91][320/940] lr: 1.0000e-04 eta: 1:39:22 time: 0.6103 data_time: 0.0589 memory: 24011 grad_norm: 5.9133 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4940 loss: 0.4940 2022/09/06 00:51:52 - mmengine - INFO - Epoch(train) [91][340/940] lr: 1.0000e-04 eta: 1:39:09 time: 0.6285 data_time: 0.0559 memory: 24011 grad_norm: 5.4076 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6112 loss: 0.6112 2022/09/06 00:52:05 - mmengine - INFO - Epoch(train) [91][360/940] lr: 1.0000e-04 eta: 1:38:56 time: 0.6337 data_time: 0.0692 memory: 24011 grad_norm: 5.2985 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5656 loss: 0.5656 2022/09/06 00:52:19 - mmengine - INFO - Epoch(train) [91][380/940] lr: 1.0000e-04 eta: 1:38:43 time: 0.7051 data_time: 0.1056 memory: 24011 grad_norm: 5.1401 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5604 loss: 0.5604 2022/09/06 00:52:32 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:52:32 - mmengine - INFO - Epoch(train) [91][400/940] lr: 1.0000e-04 eta: 1:38:30 time: 0.6244 data_time: 0.0529 memory: 24011 grad_norm: 5.7609 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.6220 loss: 0.6220 2022/09/06 00:52:44 - mmengine - INFO - Epoch(train) [91][420/940] lr: 1.0000e-04 eta: 1:38:16 time: 0.6301 data_time: 0.0548 memory: 24011 grad_norm: 5.5443 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.4859 loss: 0.4859 2022/09/06 00:52:56 - mmengine - INFO - Epoch(train) [91][440/940] lr: 1.0000e-04 eta: 1:38:03 time: 0.6145 data_time: 0.0344 memory: 24011 grad_norm: 5.7331 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5157 loss: 0.5157 2022/09/06 00:53:10 - mmengine - INFO - Epoch(train) [91][460/940] lr: 1.0000e-04 eta: 1:37:50 time: 0.6666 data_time: 0.0391 memory: 24011 grad_norm: 5.3942 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5559 loss: 0.5559 2022/09/06 00:53:23 - mmengine - INFO - Epoch(train) [91][480/940] lr: 1.0000e-04 eta: 1:37:37 time: 0.6741 data_time: 0.0432 memory: 24011 grad_norm: 6.1208 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5841 loss: 0.5841 2022/09/06 00:53:36 - mmengine - INFO - Epoch(train) [91][500/940] lr: 1.0000e-04 eta: 1:37:24 time: 0.6491 data_time: 0.0388 memory: 24011 grad_norm: 5.0815 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.4731 loss: 0.4731 2022/09/06 00:53:49 - mmengine - INFO - Epoch(train) [91][520/940] lr: 1.0000e-04 eta: 1:37:11 time: 0.6419 data_time: 0.0355 memory: 24011 grad_norm: 5.8802 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4859 loss: 0.4859 2022/09/06 00:54:02 - mmengine - INFO - Epoch(train) [91][540/940] lr: 1.0000e-04 eta: 1:36:57 time: 0.6226 data_time: 0.0386 memory: 24011 grad_norm: 5.3466 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.4919 loss: 0.4919 2022/09/06 00:54:14 - mmengine - INFO - Epoch(train) [91][560/940] lr: 1.0000e-04 eta: 1:36:44 time: 0.6221 data_time: 0.0396 memory: 24011 grad_norm: 5.5887 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5963 loss: 0.5963 2022/09/06 00:54:26 - mmengine - INFO - Epoch(train) [91][580/940] lr: 1.0000e-04 eta: 1:36:31 time: 0.6080 data_time: 0.0448 memory: 24011 grad_norm: 5.3837 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6527 loss: 0.6527 2022/09/06 00:54:40 - mmengine - INFO - Epoch(train) [91][600/940] lr: 1.0000e-04 eta: 1:36:18 time: 0.6667 data_time: 0.0775 memory: 24011 grad_norm: 5.2898 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5312 loss: 0.5312 2022/09/06 00:54:53 - mmengine - INFO - Epoch(train) [91][620/940] lr: 1.0000e-04 eta: 1:36:05 time: 0.6470 data_time: 0.0500 memory: 24011 grad_norm: 5.9331 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5033 loss: 0.5033 2022/09/06 00:55:06 - mmengine - INFO - Epoch(train) [91][640/940] lr: 1.0000e-04 eta: 1:35:52 time: 0.6680 data_time: 0.0554 memory: 24011 grad_norm: 5.7709 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5305 loss: 0.5305 2022/09/06 00:55:19 - mmengine - INFO - Epoch(train) [91][660/940] lr: 1.0000e-04 eta: 1:35:39 time: 0.6690 data_time: 0.0562 memory: 24011 grad_norm: 5.7739 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5162 loss: 0.5162 2022/09/06 00:55:33 - mmengine - INFO - Epoch(train) [91][680/940] lr: 1.0000e-04 eta: 1:35:25 time: 0.6598 data_time: 0.0353 memory: 24011 grad_norm: 5.2603 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6049 loss: 0.6049 2022/09/06 00:55:46 - mmengine - INFO - Epoch(train) [91][700/940] lr: 1.0000e-04 eta: 1:35:12 time: 0.6517 data_time: 0.0767 memory: 24011 grad_norm: 5.5853 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5813 loss: 0.5813 2022/09/06 00:55:59 - mmengine - INFO - Epoch(train) [91][720/940] lr: 1.0000e-04 eta: 1:34:59 time: 0.6599 data_time: 0.0612 memory: 24011 grad_norm: 5.3025 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5303 loss: 0.5303 2022/09/06 00:56:11 - mmengine - INFO - Epoch(train) [91][740/940] lr: 1.0000e-04 eta: 1:34:46 time: 0.6023 data_time: 0.0368 memory: 24011 grad_norm: 5.1834 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5166 loss: 0.5166 2022/09/06 00:56:24 - mmengine - INFO - Epoch(train) [91][760/940] lr: 1.0000e-04 eta: 1:34:33 time: 0.6700 data_time: 0.0607 memory: 24011 grad_norm: 5.8841 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5162 loss: 0.5162 2022/09/06 00:56:37 - mmengine - INFO - Epoch(train) [91][780/940] lr: 1.0000e-04 eta: 1:34:20 time: 0.6395 data_time: 0.0750 memory: 24011 grad_norm: 5.3020 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6000 loss: 0.6000 2022/09/06 00:56:50 - mmengine - INFO - Epoch(train) [91][800/940] lr: 1.0000e-04 eta: 1:34:07 time: 0.6712 data_time: 0.1051 memory: 24011 grad_norm: 6.1505 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5366 loss: 0.5366 2022/09/06 00:57:03 - mmengine - INFO - Epoch(train) [91][820/940] lr: 1.0000e-04 eta: 1:33:53 time: 0.6292 data_time: 0.0677 memory: 24011 grad_norm: 5.5633 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4951 loss: 0.4951 2022/09/06 00:57:16 - mmengine - INFO - Epoch(train) [91][840/940] lr: 1.0000e-04 eta: 1:33:40 time: 0.6504 data_time: 0.0931 memory: 24011 grad_norm: 5.2621 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5748 loss: 0.5748 2022/09/06 00:57:29 - mmengine - INFO - Epoch(train) [91][860/940] lr: 1.0000e-04 eta: 1:33:27 time: 0.6474 data_time: 0.0811 memory: 24011 grad_norm: 5.4360 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5457 loss: 0.5457 2022/09/06 00:57:42 - mmengine - INFO - Epoch(train) [91][880/940] lr: 1.0000e-04 eta: 1:33:14 time: 0.6263 data_time: 0.0572 memory: 24011 grad_norm: 6.2660 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5094 loss: 0.5094 2022/09/06 00:57:55 - mmengine - INFO - Epoch(train) [91][900/940] lr: 1.0000e-04 eta: 1:33:01 time: 0.6555 data_time: 0.0555 memory: 24011 grad_norm: 6.4448 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5137 loss: 0.5137 2022/09/06 00:58:08 - mmengine - INFO - Epoch(train) [91][920/940] lr: 1.0000e-04 eta: 1:32:48 time: 0.6697 data_time: 0.0974 memory: 24011 grad_norm: 5.9321 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5756 loss: 0.5756 2022/09/06 00:58:19 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 00:58:19 - mmengine - INFO - Epoch(train) [91][940/940] lr: 1.0000e-04 eta: 1:32:34 time: 0.5658 data_time: 0.0490 memory: 24011 grad_norm: 5.4901 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.5685 loss: 0.5685 2022/09/06 00:58:33 - mmengine - INFO - Epoch(val) [91][20/78] eta: 0:00:40 time: 0.6931 data_time: 0.5346 memory: 3625 2022/09/06 00:58:43 - mmengine - INFO - Epoch(val) [91][40/78] eta: 0:00:17 time: 0.4563 data_time: 0.2990 memory: 3625 2022/09/06 00:58:56 - mmengine - INFO - Epoch(val) [91][60/78] eta: 0:00:11 time: 0.6612 data_time: 0.4967 memory: 3625 2022/09/06 00:59:06 - mmengine - INFO - Epoch(val) [91][78/78] acc/top1: 0.7408 acc/top5: 0.9073 acc/mean1: 0.7407 2022/09/06 00:59:24 - mmengine - INFO - Epoch(train) [92][20/940] lr: 1.0000e-04 eta: 1:32:22 time: 0.8944 data_time: 0.2702 memory: 24011 grad_norm: 5.2817 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5288 loss: 0.5288 2022/09/06 00:59:37 - mmengine - INFO - Epoch(train) [92][40/940] lr: 1.0000e-04 eta: 1:32:08 time: 0.6510 data_time: 0.0503 memory: 24011 grad_norm: 5.7146 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5689 loss: 0.5689 2022/09/06 00:59:51 - mmengine - INFO - Epoch(train) [92][60/940] lr: 1.0000e-04 eta: 1:31:55 time: 0.6655 data_time: 0.0395 memory: 24011 grad_norm: 5.5820 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.6602 loss: 0.6602 2022/09/06 01:00:03 - mmengine - INFO - Epoch(train) [92][80/940] lr: 1.0000e-04 eta: 1:31:42 time: 0.6053 data_time: 0.0312 memory: 24011 grad_norm: 5.7108 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5507 loss: 0.5507 2022/09/06 01:00:16 - mmengine - INFO - Epoch(train) [92][100/940] lr: 1.0000e-04 eta: 1:31:29 time: 0.6765 data_time: 0.0515 memory: 24011 grad_norm: 5.5873 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5640 loss: 0.5640 2022/09/06 01:00:29 - mmengine - INFO - Epoch(train) [92][120/940] lr: 1.0000e-04 eta: 1:31:16 time: 0.6419 data_time: 0.0295 memory: 24011 grad_norm: 5.3856 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4951 loss: 0.4951 2022/09/06 01:00:43 - mmengine - INFO - Epoch(train) [92][140/940] lr: 1.0000e-04 eta: 1:31:03 time: 0.7022 data_time: 0.0884 memory: 24011 grad_norm: 5.0637 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5595 loss: 0.5595 2022/09/06 01:00:56 - mmengine - INFO - Epoch(train) [92][160/940] lr: 1.0000e-04 eta: 1:30:50 time: 0.6341 data_time: 0.0366 memory: 24011 grad_norm: 5.6872 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4959 loss: 0.4959 2022/09/06 01:01:09 - mmengine - INFO - Epoch(train) [92][180/940] lr: 1.0000e-04 eta: 1:30:36 time: 0.6496 data_time: 0.0400 memory: 24011 grad_norm: 5.7692 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.4404 loss: 0.4404 2022/09/06 01:01:22 - mmengine - INFO - Epoch(train) [92][200/940] lr: 1.0000e-04 eta: 1:30:23 time: 0.6246 data_time: 0.0365 memory: 24011 grad_norm: 5.5511 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5285 loss: 0.5285 2022/09/06 01:01:35 - mmengine - INFO - Epoch(train) [92][220/940] lr: 1.0000e-04 eta: 1:30:10 time: 0.6535 data_time: 0.0359 memory: 24011 grad_norm: 5.0761 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5946 loss: 0.5946 2022/09/06 01:01:47 - mmengine - INFO - Epoch(train) [92][240/940] lr: 1.0000e-04 eta: 1:29:57 time: 0.6387 data_time: 0.0531 memory: 24011 grad_norm: 5.0250 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4792 loss: 0.4792 2022/09/06 01:02:01 - mmengine - INFO - Epoch(train) [92][260/940] lr: 1.0000e-04 eta: 1:29:44 time: 0.6601 data_time: 0.0377 memory: 24011 grad_norm: 5.5660 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5224 loss: 0.5224 2022/09/06 01:02:13 - mmengine - INFO - Epoch(train) [92][280/940] lr: 1.0000e-04 eta: 1:29:31 time: 0.6273 data_time: 0.0377 memory: 24011 grad_norm: 5.9456 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5780 loss: 0.5780 2022/09/06 01:02:26 - mmengine - INFO - Epoch(train) [92][300/940] lr: 1.0000e-04 eta: 1:29:18 time: 0.6625 data_time: 0.0414 memory: 24011 grad_norm: 5.9191 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5785 loss: 0.5785 2022/09/06 01:02:40 - mmengine - INFO - Epoch(train) [92][320/940] lr: 1.0000e-04 eta: 1:29:04 time: 0.6591 data_time: 0.0435 memory: 24011 grad_norm: 6.0447 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5151 loss: 0.5151 2022/09/06 01:02:53 - mmengine - INFO - Epoch(train) [92][340/940] lr: 1.0000e-04 eta: 1:28:51 time: 0.6619 data_time: 0.0412 memory: 24011 grad_norm: 5.2061 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.5105 loss: 0.5105 2022/09/06 01:03:06 - mmengine - INFO - Epoch(train) [92][360/940] lr: 1.0000e-04 eta: 1:28:38 time: 0.6465 data_time: 0.0338 memory: 24011 grad_norm: 5.5195 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5289 loss: 0.5289 2022/09/06 01:03:19 - mmengine - INFO - Epoch(train) [92][380/940] lr: 1.0000e-04 eta: 1:28:25 time: 0.6827 data_time: 0.0376 memory: 24011 grad_norm: 5.2114 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.6332 loss: 0.6332 2022/09/06 01:03:32 - mmengine - INFO - Epoch(train) [92][400/940] lr: 1.0000e-04 eta: 1:28:12 time: 0.6503 data_time: 0.0432 memory: 24011 grad_norm: 5.2533 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5481 loss: 0.5481 2022/09/06 01:03:45 - mmengine - INFO - Epoch(train) [92][420/940] lr: 1.0000e-04 eta: 1:27:59 time: 0.6030 data_time: 0.0385 memory: 24011 grad_norm: 5.6510 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.4821 loss: 0.4821 2022/09/06 01:03:57 - mmengine - INFO - Epoch(train) [92][440/940] lr: 1.0000e-04 eta: 1:27:45 time: 0.6217 data_time: 0.0510 memory: 24011 grad_norm: 5.2700 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5730 loss: 0.5730 2022/09/06 01:04:10 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:04:10 - mmengine - INFO - Epoch(train) [92][460/940] lr: 1.0000e-04 eta: 1:27:32 time: 0.6543 data_time: 0.0437 memory: 24011 grad_norm: 5.2061 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5422 loss: 0.5422 2022/09/06 01:04:23 - mmengine - INFO - Epoch(train) [92][480/940] lr: 1.0000e-04 eta: 1:27:19 time: 0.6427 data_time: 0.0441 memory: 24011 grad_norm: 5.6224 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4628 loss: 0.4628 2022/09/06 01:04:36 - mmengine - INFO - Epoch(train) [92][500/940] lr: 1.0000e-04 eta: 1:27:06 time: 0.6595 data_time: 0.0420 memory: 24011 grad_norm: 5.4876 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5614 loss: 0.5614 2022/09/06 01:04:49 - mmengine - INFO - Epoch(train) [92][520/940] lr: 1.0000e-04 eta: 1:26:53 time: 0.6242 data_time: 0.0411 memory: 24011 grad_norm: 6.6832 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5632 loss: 0.5632 2022/09/06 01:05:02 - mmengine - INFO - Epoch(train) [92][540/940] lr: 1.0000e-04 eta: 1:26:40 time: 0.6488 data_time: 0.0620 memory: 24011 grad_norm: 5.3223 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5500 loss: 0.5500 2022/09/06 01:05:15 - mmengine - INFO - Epoch(train) [92][560/940] lr: 1.0000e-04 eta: 1:26:27 time: 0.6551 data_time: 0.0515 memory: 24011 grad_norm: 5.6193 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4925 loss: 0.4925 2022/09/06 01:05:28 - mmengine - INFO - Epoch(train) [92][580/940] lr: 1.0000e-04 eta: 1:26:13 time: 0.6649 data_time: 0.0455 memory: 24011 grad_norm: 5.8104 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5632 loss: 0.5632 2022/09/06 01:05:41 - mmengine - INFO - Epoch(train) [92][600/940] lr: 1.0000e-04 eta: 1:26:00 time: 0.6277 data_time: 0.0419 memory: 24011 grad_norm: 5.8578 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5183 loss: 0.5183 2022/09/06 01:05:56 - mmengine - INFO - Epoch(train) [92][620/940] lr: 1.0000e-04 eta: 1:25:47 time: 0.7458 data_time: 0.0397 memory: 24011 grad_norm: 6.2026 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5599 loss: 0.5599 2022/09/06 01:06:09 - mmengine - INFO - Epoch(train) [92][640/940] lr: 1.0000e-04 eta: 1:25:34 time: 0.6382 data_time: 0.0317 memory: 24011 grad_norm: 5.6853 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4562 loss: 0.4562 2022/09/06 01:06:21 - mmengine - INFO - Epoch(train) [92][660/940] lr: 1.0000e-04 eta: 1:25:21 time: 0.6348 data_time: 0.0556 memory: 24011 grad_norm: 5.0770 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5977 loss: 0.5977 2022/09/06 01:06:33 - mmengine - INFO - Epoch(train) [92][680/940] lr: 1.0000e-04 eta: 1:25:08 time: 0.6091 data_time: 0.0419 memory: 24011 grad_norm: 5.2007 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4763 loss: 0.4763 2022/09/06 01:06:46 - mmengine - INFO - Epoch(train) [92][700/940] lr: 1.0000e-04 eta: 1:24:55 time: 0.6144 data_time: 0.0386 memory: 24011 grad_norm: 5.4678 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4490 loss: 0.4490 2022/09/06 01:06:59 - mmengine - INFO - Epoch(train) [92][720/940] lr: 1.0000e-04 eta: 1:24:41 time: 0.6764 data_time: 0.0399 memory: 24011 grad_norm: 6.2376 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4877 loss: 0.4877 2022/09/06 01:07:12 - mmengine - INFO - Epoch(train) [92][740/940] lr: 1.0000e-04 eta: 1:24:28 time: 0.6357 data_time: 0.0404 memory: 24011 grad_norm: 5.2512 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5258 loss: 0.5258 2022/09/06 01:07:25 - mmengine - INFO - Epoch(train) [92][760/940] lr: 1.0000e-04 eta: 1:24:15 time: 0.6364 data_time: 0.0421 memory: 24011 grad_norm: 5.3907 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5244 loss: 0.5244 2022/09/06 01:07:38 - mmengine - INFO - Epoch(train) [92][780/940] lr: 1.0000e-04 eta: 1:24:02 time: 0.6694 data_time: 0.0346 memory: 24011 grad_norm: 6.0412 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5521 loss: 0.5521 2022/09/06 01:07:51 - mmengine - INFO - Epoch(train) [92][800/940] lr: 1.0000e-04 eta: 1:23:49 time: 0.6694 data_time: 0.0430 memory: 24011 grad_norm: 5.6129 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.6227 loss: 0.6227 2022/09/06 01:08:03 - mmengine - INFO - Epoch(train) [92][820/940] lr: 1.0000e-04 eta: 1:23:36 time: 0.6052 data_time: 0.0399 memory: 24011 grad_norm: 6.1614 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5317 loss: 0.5317 2022/09/06 01:08:16 - mmengine - INFO - Epoch(train) [92][840/940] lr: 1.0000e-04 eta: 1:23:23 time: 0.6296 data_time: 0.0453 memory: 24011 grad_norm: 5.2910 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5259 loss: 0.5259 2022/09/06 01:08:30 - mmengine - INFO - Epoch(train) [92][860/940] lr: 1.0000e-04 eta: 1:23:09 time: 0.6729 data_time: 0.0392 memory: 24011 grad_norm: 5.4826 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5962 loss: 0.5962 2022/09/06 01:08:42 - mmengine - INFO - Epoch(train) [92][880/940] lr: 1.0000e-04 eta: 1:22:56 time: 0.6159 data_time: 0.0389 memory: 24011 grad_norm: 6.4551 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5732 loss: 0.5732 2022/09/06 01:08:55 - mmengine - INFO - Epoch(train) [92][900/940] lr: 1.0000e-04 eta: 1:22:43 time: 0.6584 data_time: 0.0407 memory: 24011 grad_norm: 5.3041 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4671 loss: 0.4671 2022/09/06 01:09:08 - mmengine - INFO - Epoch(train) [92][920/940] lr: 1.0000e-04 eta: 1:22:30 time: 0.6574 data_time: 0.0400 memory: 24011 grad_norm: 5.9041 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5077 loss: 0.5077 2022/09/06 01:09:20 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:09:20 - mmengine - INFO - Epoch(train) [92][940/940] lr: 1.0000e-04 eta: 1:22:17 time: 0.5664 data_time: 0.0510 memory: 24011 grad_norm: 5.4400 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.5549 loss: 0.5549 2022/09/06 01:09:34 - mmengine - INFO - Epoch(val) [92][20/78] eta: 0:00:40 time: 0.6968 data_time: 0.5379 memory: 3625 2022/09/06 01:09:43 - mmengine - INFO - Epoch(val) [92][40/78] eta: 0:00:17 time: 0.4691 data_time: 0.3100 memory: 3625 2022/09/06 01:09:56 - mmengine - INFO - Epoch(val) [92][60/78] eta: 0:00:11 time: 0.6614 data_time: 0.5050 memory: 3625 2022/09/06 01:10:07 - mmengine - INFO - Epoch(val) [92][78/78] acc/top1: 0.7414 acc/top5: 0.9073 acc/mean1: 0.7413 2022/09/06 01:10:25 - mmengine - INFO - Epoch(train) [93][20/940] lr: 1.0000e-04 eta: 1:22:04 time: 0.9123 data_time: 0.2710 memory: 24011 grad_norm: 5.3069 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5283 loss: 0.5283 2022/09/06 01:10:38 - mmengine - INFO - Epoch(train) [93][40/940] lr: 1.0000e-04 eta: 1:21:51 time: 0.6447 data_time: 0.0390 memory: 24011 grad_norm: 5.3086 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5472 loss: 0.5472 2022/09/06 01:10:51 - mmengine - INFO - Epoch(train) [93][60/940] lr: 1.0000e-04 eta: 1:21:38 time: 0.6819 data_time: 0.0396 memory: 24011 grad_norm: 5.3753 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4996 loss: 0.4996 2022/09/06 01:11:04 - mmengine - INFO - Epoch(train) [93][80/940] lr: 1.0000e-04 eta: 1:21:25 time: 0.6385 data_time: 0.0368 memory: 24011 grad_norm: 5.3601 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5808 loss: 0.5808 2022/09/06 01:11:17 - mmengine - INFO - Epoch(train) [93][100/940] lr: 1.0000e-04 eta: 1:21:11 time: 0.6539 data_time: 0.0400 memory: 24011 grad_norm: 5.5168 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4665 loss: 0.4665 2022/09/06 01:11:30 - mmengine - INFO - Epoch(train) [93][120/940] lr: 1.0000e-04 eta: 1:20:58 time: 0.6239 data_time: 0.0418 memory: 24011 grad_norm: 6.1053 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5183 loss: 0.5183 2022/09/06 01:11:44 - mmengine - INFO - Epoch(train) [93][140/940] lr: 1.0000e-04 eta: 1:20:45 time: 0.6855 data_time: 0.0428 memory: 24011 grad_norm: 5.5597 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5017 loss: 0.5017 2022/09/06 01:11:56 - mmengine - INFO - Epoch(train) [93][160/940] lr: 1.0000e-04 eta: 1:20:32 time: 0.6098 data_time: 0.0433 memory: 24011 grad_norm: 5.0424 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4744 loss: 0.4744 2022/09/06 01:12:09 - mmengine - INFO - Epoch(train) [93][180/940] lr: 1.0000e-04 eta: 1:20:19 time: 0.6513 data_time: 0.0363 memory: 24011 grad_norm: 5.0752 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5893 loss: 0.5893 2022/09/06 01:12:22 - mmengine - INFO - Epoch(train) [93][200/940] lr: 1.0000e-04 eta: 1:20:06 time: 0.6678 data_time: 0.0463 memory: 24011 grad_norm: 5.8792 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5310 loss: 0.5310 2022/09/06 01:12:36 - mmengine - INFO - Epoch(train) [93][220/940] lr: 1.0000e-04 eta: 1:19:53 time: 0.6935 data_time: 0.0398 memory: 24011 grad_norm: 7.7988 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4787 loss: 0.4787 2022/09/06 01:12:49 - mmengine - INFO - Epoch(train) [93][240/940] lr: 1.0000e-04 eta: 1:19:40 time: 0.6725 data_time: 0.0376 memory: 24011 grad_norm: 6.9286 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5463 loss: 0.5463 2022/09/06 01:13:01 - mmengine - INFO - Epoch(train) [93][260/940] lr: 1.0000e-04 eta: 1:19:26 time: 0.5941 data_time: 0.0387 memory: 24011 grad_norm: 5.4028 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5644 loss: 0.5644 2022/09/06 01:13:14 - mmengine - INFO - Epoch(train) [93][280/940] lr: 1.0000e-04 eta: 1:19:13 time: 0.6265 data_time: 0.0733 memory: 24011 grad_norm: 5.3962 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5339 loss: 0.5339 2022/09/06 01:13:26 - mmengine - INFO - Epoch(train) [93][300/940] lr: 1.0000e-04 eta: 1:19:00 time: 0.6166 data_time: 0.0403 memory: 24011 grad_norm: 5.4540 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4887 loss: 0.4887 2022/09/06 01:13:39 - mmengine - INFO - Epoch(train) [93][320/940] lr: 1.0000e-04 eta: 1:18:47 time: 0.6336 data_time: 0.0403 memory: 24011 grad_norm: 5.5774 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5502 loss: 0.5502 2022/09/06 01:13:52 - mmengine - INFO - Epoch(train) [93][340/940] lr: 1.0000e-04 eta: 1:18:34 time: 0.6587 data_time: 0.0444 memory: 24011 grad_norm: 5.3914 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5477 loss: 0.5477 2022/09/06 01:14:05 - mmengine - INFO - Epoch(train) [93][360/940] lr: 1.0000e-04 eta: 1:18:20 time: 0.6608 data_time: 0.0431 memory: 24011 grad_norm: 5.3646 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4509 loss: 0.4509 2022/09/06 01:14:18 - mmengine - INFO - Epoch(train) [93][380/940] lr: 1.0000e-04 eta: 1:18:07 time: 0.6527 data_time: 0.0463 memory: 24011 grad_norm: 5.7052 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4549 loss: 0.4549 2022/09/06 01:14:30 - mmengine - INFO - Epoch(train) [93][400/940] lr: 1.0000e-04 eta: 1:17:54 time: 0.5981 data_time: 0.0354 memory: 24011 grad_norm: 5.4078 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5273 loss: 0.5273 2022/09/06 01:14:44 - mmengine - INFO - Epoch(train) [93][420/940] lr: 1.0000e-04 eta: 1:17:41 time: 0.6732 data_time: 0.0398 memory: 24011 grad_norm: 5.4821 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5303 loss: 0.5303 2022/09/06 01:14:57 - mmengine - INFO - Epoch(train) [93][440/940] lr: 1.0000e-04 eta: 1:17:28 time: 0.6563 data_time: 0.0387 memory: 24011 grad_norm: 5.3819 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5779 loss: 0.5779 2022/09/06 01:15:10 - mmengine - INFO - Epoch(train) [93][460/940] lr: 1.0000e-04 eta: 1:17:15 time: 0.6661 data_time: 0.0414 memory: 24011 grad_norm: 5.2790 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5405 loss: 0.5405 2022/09/06 01:15:23 - mmengine - INFO - Epoch(train) [93][480/940] lr: 1.0000e-04 eta: 1:17:02 time: 0.6286 data_time: 0.0408 memory: 24011 grad_norm: 5.3715 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.6040 loss: 0.6040 2022/09/06 01:15:36 - mmengine - INFO - Epoch(train) [93][500/940] lr: 1.0000e-04 eta: 1:16:49 time: 0.6769 data_time: 0.0427 memory: 24011 grad_norm: 5.4074 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5026 loss: 0.5026 2022/09/06 01:15:50 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:15:50 - mmengine - INFO - Epoch(train) [93][520/940] lr: 1.0000e-04 eta: 1:16:35 time: 0.6619 data_time: 0.0382 memory: 24011 grad_norm: 5.5495 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.5759 loss: 0.5759 2022/09/06 01:16:03 - mmengine - INFO - Epoch(train) [93][540/940] lr: 1.0000e-04 eta: 1:16:22 time: 0.6543 data_time: 0.0361 memory: 24011 grad_norm: 5.3200 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5479 loss: 0.5479 2022/09/06 01:16:16 - mmengine - INFO - Epoch(train) [93][560/940] lr: 1.0000e-04 eta: 1:16:09 time: 0.6281 data_time: 0.0403 memory: 24011 grad_norm: 5.5235 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5446 loss: 0.5446 2022/09/06 01:16:29 - mmengine - INFO - Epoch(train) [93][580/940] lr: 1.0000e-04 eta: 1:15:56 time: 0.6598 data_time: 0.0508 memory: 24011 grad_norm: 5.7355 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5754 loss: 0.5754 2022/09/06 01:16:41 - mmengine - INFO - Epoch(train) [93][600/940] lr: 1.0000e-04 eta: 1:15:43 time: 0.6278 data_time: 0.0507 memory: 24011 grad_norm: 5.2835 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5037 loss: 0.5037 2022/09/06 01:16:55 - mmengine - INFO - Epoch(train) [93][620/940] lr: 1.0000e-04 eta: 1:15:30 time: 0.6764 data_time: 0.0392 memory: 24011 grad_norm: 5.5468 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4843 loss: 0.4843 2022/09/06 01:17:09 - mmengine - INFO - Epoch(train) [93][640/940] lr: 1.0000e-04 eta: 1:15:17 time: 0.6913 data_time: 0.0418 memory: 24011 grad_norm: 5.6901 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4405 loss: 0.4405 2022/09/06 01:17:21 - mmengine - INFO - Epoch(train) [93][660/940] lr: 1.0000e-04 eta: 1:15:03 time: 0.6030 data_time: 0.0431 memory: 24011 grad_norm: 6.7365 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.4889 loss: 0.4889 2022/09/06 01:17:34 - mmengine - INFO - Epoch(train) [93][680/940] lr: 1.0000e-04 eta: 1:14:50 time: 0.6425 data_time: 0.0414 memory: 24011 grad_norm: 5.3716 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5221 loss: 0.5221 2022/09/06 01:17:46 - mmengine - INFO - Epoch(train) [93][700/940] lr: 1.0000e-04 eta: 1:14:37 time: 0.6496 data_time: 0.0694 memory: 24011 grad_norm: 5.9441 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5737 loss: 0.5737 2022/09/06 01:17:59 - mmengine - INFO - Epoch(train) [93][720/940] lr: 1.0000e-04 eta: 1:14:24 time: 0.6165 data_time: 0.0358 memory: 24011 grad_norm: 5.3965 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5485 loss: 0.5485 2022/09/06 01:18:12 - mmengine - INFO - Epoch(train) [93][740/940] lr: 1.0000e-04 eta: 1:14:11 time: 0.6768 data_time: 0.0473 memory: 24011 grad_norm: 5.5088 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5430 loss: 0.5430 2022/09/06 01:18:25 - mmengine - INFO - Epoch(train) [93][760/940] lr: 1.0000e-04 eta: 1:13:58 time: 0.6194 data_time: 0.0403 memory: 24011 grad_norm: 5.8906 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5701 loss: 0.5701 2022/09/06 01:18:39 - mmengine - INFO - Epoch(train) [93][780/940] lr: 1.0000e-04 eta: 1:13:45 time: 0.6836 data_time: 0.0394 memory: 24011 grad_norm: 5.8655 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5112 loss: 0.5112 2022/09/06 01:18:51 - mmengine - INFO - Epoch(train) [93][800/940] lr: 1.0000e-04 eta: 1:13:31 time: 0.6255 data_time: 0.0501 memory: 24011 grad_norm: 5.4221 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5689 loss: 0.5689 2022/09/06 01:19:04 - mmengine - INFO - Epoch(train) [93][820/940] lr: 1.0000e-04 eta: 1:13:18 time: 0.6324 data_time: 0.0408 memory: 24011 grad_norm: 6.7522 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.5119 loss: 0.5119 2022/09/06 01:19:17 - mmengine - INFO - Epoch(train) [93][840/940] lr: 1.0000e-04 eta: 1:13:05 time: 0.6540 data_time: 0.0459 memory: 24011 grad_norm: 5.5047 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5385 loss: 0.5385 2022/09/06 01:19:30 - mmengine - INFO - Epoch(train) [93][860/940] lr: 1.0000e-04 eta: 1:12:52 time: 0.6839 data_time: 0.0407 memory: 24011 grad_norm: 5.1739 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5612 loss: 0.5612 2022/09/06 01:19:43 - mmengine - INFO - Epoch(train) [93][880/940] lr: 1.0000e-04 eta: 1:12:39 time: 0.6404 data_time: 0.0601 memory: 24011 grad_norm: 5.4534 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4935 loss: 0.4935 2022/09/06 01:19:56 - mmengine - INFO - Epoch(train) [93][900/940] lr: 1.0000e-04 eta: 1:12:26 time: 0.6229 data_time: 0.0406 memory: 24011 grad_norm: 5.6951 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4838 loss: 0.4838 2022/09/06 01:20:08 - mmengine - INFO - Epoch(train) [93][920/940] lr: 1.0000e-04 eta: 1:12:12 time: 0.6164 data_time: 0.0468 memory: 24011 grad_norm: 5.9013 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5362 loss: 0.5362 2022/09/06 01:20:19 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:20:19 - mmengine - INFO - Epoch(train) [93][940/940] lr: 1.0000e-04 eta: 1:11:59 time: 0.5623 data_time: 0.0312 memory: 24011 grad_norm: 5.8720 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5811 loss: 0.5811 2022/09/06 01:20:19 - mmengine - INFO - Saving checkpoint at 93 epochs 2022/09/06 01:20:39 - mmengine - INFO - Epoch(val) [93][20/78] eta: 0:00:41 time: 0.7094 data_time: 0.5475 memory: 3625 2022/09/06 01:20:48 - mmengine - INFO - Epoch(val) [93][40/78] eta: 0:00:17 time: 0.4684 data_time: 0.3099 memory: 3625 2022/09/06 01:21:01 - mmengine - INFO - Epoch(val) [93][60/78] eta: 0:00:11 time: 0.6379 data_time: 0.4833 memory: 3625 2022/09/06 01:21:10 - mmengine - INFO - Epoch(val) [93][78/78] acc/top1: 0.7407 acc/top5: 0.9068 acc/mean1: 0.7406 2022/09/06 01:21:29 - mmengine - INFO - Epoch(train) [94][20/940] lr: 1.0000e-04 eta: 1:11:46 time: 0.9297 data_time: 0.2502 memory: 24011 grad_norm: 5.7464 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4917 loss: 0.4917 2022/09/06 01:21:42 - mmengine - INFO - Epoch(train) [94][40/940] lr: 1.0000e-04 eta: 1:11:33 time: 0.6369 data_time: 0.0304 memory: 24011 grad_norm: 6.5561 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5564 loss: 0.5564 2022/09/06 01:21:55 - mmengine - INFO - Epoch(train) [94][60/940] lr: 1.0000e-04 eta: 1:11:20 time: 0.6381 data_time: 0.0378 memory: 24011 grad_norm: 5.4998 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5455 loss: 0.5455 2022/09/06 01:22:08 - mmengine - INFO - Epoch(train) [94][80/940] lr: 1.0000e-04 eta: 1:11:07 time: 0.6802 data_time: 0.0483 memory: 24011 grad_norm: 5.0048 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4885 loss: 0.4885 2022/09/06 01:22:21 - mmengine - INFO - Epoch(train) [94][100/940] lr: 1.0000e-04 eta: 1:10:54 time: 0.6537 data_time: 0.0514 memory: 24011 grad_norm: 5.6802 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6832 loss: 0.6832 2022/09/06 01:22:33 - mmengine - INFO - Epoch(train) [94][120/940] lr: 1.0000e-04 eta: 1:10:41 time: 0.6066 data_time: 0.0299 memory: 24011 grad_norm: 5.4952 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.5132 loss: 0.5132 2022/09/06 01:22:47 - mmengine - INFO - Epoch(train) [94][140/940] lr: 1.0000e-04 eta: 1:10:28 time: 0.6888 data_time: 0.0443 memory: 24011 grad_norm: 6.0247 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5545 loss: 0.5545 2022/09/06 01:23:00 - mmengine - INFO - Epoch(train) [94][160/940] lr: 1.0000e-04 eta: 1:10:14 time: 0.6332 data_time: 0.0375 memory: 24011 grad_norm: 5.7645 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5356 loss: 0.5356 2022/09/06 01:23:13 - mmengine - INFO - Epoch(train) [94][180/940] lr: 1.0000e-04 eta: 1:10:01 time: 0.6524 data_time: 0.0435 memory: 24011 grad_norm: 5.2429 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5203 loss: 0.5203 2022/09/06 01:23:26 - mmengine - INFO - Epoch(train) [94][200/940] lr: 1.0000e-04 eta: 1:09:48 time: 0.6288 data_time: 0.0322 memory: 24011 grad_norm: 5.4863 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4921 loss: 0.4921 2022/09/06 01:23:39 - mmengine - INFO - Epoch(train) [94][220/940] lr: 1.0000e-04 eta: 1:09:35 time: 0.6941 data_time: 0.0476 memory: 24011 grad_norm: 5.6400 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5682 loss: 0.5682 2022/09/06 01:23:52 - mmengine - INFO - Epoch(train) [94][240/940] lr: 1.0000e-04 eta: 1:09:22 time: 0.6288 data_time: 0.0360 memory: 24011 grad_norm: 5.3972 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5821 loss: 0.5821 2022/09/06 01:24:06 - mmengine - INFO - Epoch(train) [94][260/940] lr: 1.0000e-04 eta: 1:09:09 time: 0.6918 data_time: 0.0400 memory: 24011 grad_norm: 5.1216 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5252 loss: 0.5252 2022/09/06 01:24:18 - mmengine - INFO - Epoch(train) [94][280/940] lr: 1.0000e-04 eta: 1:08:56 time: 0.6128 data_time: 0.0412 memory: 24011 grad_norm: 5.5910 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5644 loss: 0.5644 2022/09/06 01:24:31 - mmengine - INFO - Epoch(train) [94][300/940] lr: 1.0000e-04 eta: 1:08:42 time: 0.6412 data_time: 0.0440 memory: 24011 grad_norm: 5.0735 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4405 loss: 0.4405 2022/09/06 01:24:44 - mmengine - INFO - Epoch(train) [94][320/940] lr: 1.0000e-04 eta: 1:08:29 time: 0.6279 data_time: 0.0511 memory: 24011 grad_norm: 5.4587 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4945 loss: 0.4945 2022/09/06 01:24:57 - mmengine - INFO - Epoch(train) [94][340/940] lr: 1.0000e-04 eta: 1:08:16 time: 0.6814 data_time: 0.0402 memory: 24011 grad_norm: 5.3130 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5163 loss: 0.5163 2022/09/06 01:25:10 - mmengine - INFO - Epoch(train) [94][360/940] lr: 1.0000e-04 eta: 1:08:03 time: 0.6401 data_time: 0.0351 memory: 24011 grad_norm: 5.2254 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5653 loss: 0.5653 2022/09/06 01:25:23 - mmengine - INFO - Epoch(train) [94][380/940] lr: 1.0000e-04 eta: 1:07:50 time: 0.6747 data_time: 0.0373 memory: 24011 grad_norm: 5.2521 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5775 loss: 0.5775 2022/09/06 01:25:36 - mmengine - INFO - Epoch(train) [94][400/940] lr: 1.0000e-04 eta: 1:07:37 time: 0.6270 data_time: 0.0391 memory: 24011 grad_norm: 5.2749 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5376 loss: 0.5376 2022/09/06 01:25:49 - mmengine - INFO - Epoch(train) [94][420/940] lr: 1.0000e-04 eta: 1:07:24 time: 0.6293 data_time: 0.0430 memory: 24011 grad_norm: 5.6913 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4576 loss: 0.4576 2022/09/06 01:26:02 - mmengine - INFO - Epoch(train) [94][440/940] lr: 1.0000e-04 eta: 1:07:10 time: 0.6574 data_time: 0.0391 memory: 24011 grad_norm: 5.2832 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5965 loss: 0.5965 2022/09/06 01:26:15 - mmengine - INFO - Epoch(train) [94][460/940] lr: 1.0000e-04 eta: 1:06:57 time: 0.6517 data_time: 0.0393 memory: 24011 grad_norm: 5.2561 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.4989 loss: 0.4989 2022/09/06 01:26:28 - mmengine - INFO - Epoch(train) [94][480/940] lr: 1.0000e-04 eta: 1:06:44 time: 0.6426 data_time: 0.0335 memory: 24011 grad_norm: 5.3997 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5205 loss: 0.5205 2022/09/06 01:26:40 - mmengine - INFO - Epoch(train) [94][500/940] lr: 1.0000e-04 eta: 1:06:31 time: 0.6380 data_time: 0.0350 memory: 24011 grad_norm: 5.2739 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5091 loss: 0.5091 2022/09/06 01:26:53 - mmengine - INFO - Epoch(train) [94][520/940] lr: 1.0000e-04 eta: 1:06:18 time: 0.6475 data_time: 0.0426 memory: 24011 grad_norm: 5.5374 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5954 loss: 0.5954 2022/09/06 01:27:07 - mmengine - INFO - Epoch(train) [94][540/940] lr: 1.0000e-04 eta: 1:06:05 time: 0.6553 data_time: 0.0332 memory: 24011 grad_norm: 5.6886 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5507 loss: 0.5507 2022/09/06 01:27:19 - mmengine - INFO - Epoch(train) [94][560/940] lr: 1.0000e-04 eta: 1:05:52 time: 0.6265 data_time: 0.0408 memory: 24011 grad_norm: 5.4496 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.6039 loss: 0.6039 2022/09/06 01:27:32 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:27:32 - mmengine - INFO - Epoch(train) [94][580/940] lr: 1.0000e-04 eta: 1:05:38 time: 0.6589 data_time: 0.0418 memory: 24011 grad_norm: 5.9644 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5439 loss: 0.5439 2022/09/06 01:27:44 - mmengine - INFO - Epoch(train) [94][600/940] lr: 1.0000e-04 eta: 1:05:25 time: 0.6072 data_time: 0.0378 memory: 24011 grad_norm: 5.8263 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6022 loss: 0.6022 2022/09/06 01:27:57 - mmengine - INFO - Epoch(train) [94][620/940] lr: 1.0000e-04 eta: 1:05:12 time: 0.6449 data_time: 0.0613 memory: 24011 grad_norm: 5.7979 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5941 loss: 0.5941 2022/09/06 01:28:11 - mmengine - INFO - Epoch(train) [94][640/940] lr: 1.0000e-04 eta: 1:04:59 time: 0.7007 data_time: 0.0512 memory: 24011 grad_norm: 7.0407 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5315 loss: 0.5315 2022/09/06 01:28:25 - mmengine - INFO - Epoch(train) [94][660/940] lr: 1.0000e-04 eta: 1:04:46 time: 0.6727 data_time: 0.0371 memory: 24011 grad_norm: 6.1084 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5681 loss: 0.5681 2022/09/06 01:28:37 - mmengine - INFO - Epoch(train) [94][680/940] lr: 1.0000e-04 eta: 1:04:33 time: 0.6212 data_time: 0.0346 memory: 24011 grad_norm: 5.4051 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5311 loss: 0.5311 2022/09/06 01:28:50 - mmengine - INFO - Epoch(train) [94][700/940] lr: 1.0000e-04 eta: 1:04:20 time: 0.6122 data_time: 0.0403 memory: 24011 grad_norm: 5.3215 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5327 loss: 0.5327 2022/09/06 01:29:03 - mmengine - INFO - Epoch(train) [94][720/940] lr: 1.0000e-04 eta: 1:04:06 time: 0.6693 data_time: 0.0377 memory: 24011 grad_norm: 5.0966 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4483 loss: 0.4483 2022/09/06 01:29:16 - mmengine - INFO - Epoch(train) [94][740/940] lr: 1.0000e-04 eta: 1:03:53 time: 0.6533 data_time: 0.0431 memory: 24011 grad_norm: 5.6511 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4602 loss: 0.4602 2022/09/06 01:29:29 - mmengine - INFO - Epoch(train) [94][760/940] lr: 1.0000e-04 eta: 1:03:40 time: 0.6565 data_time: 0.0363 memory: 24011 grad_norm: 11.9334 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5426 loss: 0.5426 2022/09/06 01:29:43 - mmengine - INFO - Epoch(train) [94][780/940] lr: 1.0000e-04 eta: 1:03:27 time: 0.6890 data_time: 0.0392 memory: 24011 grad_norm: 6.3104 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4246 loss: 0.4246 2022/09/06 01:29:56 - mmengine - INFO - Epoch(train) [94][800/940] lr: 1.0000e-04 eta: 1:03:14 time: 0.6495 data_time: 0.0409 memory: 24011 grad_norm: 5.2295 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5213 loss: 0.5213 2022/09/06 01:30:09 - mmengine - INFO - Epoch(train) [94][820/940] lr: 1.0000e-04 eta: 1:03:01 time: 0.6583 data_time: 0.0410 memory: 24011 grad_norm: 5.6120 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5609 loss: 0.5609 2022/09/06 01:30:22 - mmengine - INFO - Epoch(train) [94][840/940] lr: 1.0000e-04 eta: 1:02:48 time: 0.6334 data_time: 0.0434 memory: 24011 grad_norm: 5.3656 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5774 loss: 0.5774 2022/09/06 01:30:35 - mmengine - INFO - Epoch(train) [94][860/940] lr: 1.0000e-04 eta: 1:02:35 time: 0.6382 data_time: 0.0398 memory: 24011 grad_norm: 5.2695 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5728 loss: 0.5728 2022/09/06 01:30:47 - mmengine - INFO - Epoch(train) [94][880/940] lr: 1.0000e-04 eta: 1:02:21 time: 0.6343 data_time: 0.0400 memory: 24011 grad_norm: 6.0822 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5822 loss: 0.5822 2022/09/06 01:31:00 - mmengine - INFO - Epoch(train) [94][900/940] lr: 1.0000e-04 eta: 1:02:08 time: 0.6475 data_time: 0.0414 memory: 24011 grad_norm: 5.2805 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5034 loss: 0.5034 2022/09/06 01:31:13 - mmengine - INFO - Epoch(train) [94][920/940] lr: 1.0000e-04 eta: 1:01:55 time: 0.6285 data_time: 0.0465 memory: 24011 grad_norm: 5.8537 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5234 loss: 0.5234 2022/09/06 01:31:24 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:31:24 - mmengine - INFO - Epoch(train) [94][940/940] lr: 1.0000e-04 eta: 1:01:42 time: 0.5776 data_time: 0.0276 memory: 24011 grad_norm: 5.8379 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4679 loss: 0.4679 2022/09/06 01:31:38 - mmengine - INFO - Epoch(val) [94][20/78] eta: 0:00:39 time: 0.6853 data_time: 0.5224 memory: 3625 2022/09/06 01:31:48 - mmengine - INFO - Epoch(val) [94][40/78] eta: 0:00:18 time: 0.4857 data_time: 0.3282 memory: 3625 2022/09/06 01:32:01 - mmengine - INFO - Epoch(val) [94][60/78] eta: 0:00:11 time: 0.6600 data_time: 0.5001 memory: 3625 2022/09/06 01:32:11 - mmengine - INFO - Epoch(val) [94][78/78] acc/top1: 0.7413 acc/top5: 0.9066 acc/mean1: 0.7412 2022/09/06 01:32:30 - mmengine - INFO - Epoch(train) [95][20/940] lr: 1.0000e-04 eta: 1:01:29 time: 0.9275 data_time: 0.2877 memory: 24011 grad_norm: 5.5838 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5176 loss: 0.5176 2022/09/06 01:32:43 - mmengine - INFO - Epoch(train) [95][40/940] lr: 1.0000e-04 eta: 1:01:16 time: 0.6295 data_time: 0.0384 memory: 24011 grad_norm: 5.2348 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.5569 loss: 0.5569 2022/09/06 01:32:56 - mmengine - INFO - Epoch(train) [95][60/940] lr: 1.0000e-04 eta: 1:01:03 time: 0.6584 data_time: 0.0429 memory: 24011 grad_norm: 5.3545 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5972 loss: 0.5972 2022/09/06 01:33:09 - mmengine - INFO - Epoch(train) [95][80/940] lr: 1.0000e-04 eta: 1:00:50 time: 0.6610 data_time: 0.0345 memory: 24011 grad_norm: 5.2587 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4873 loss: 0.4873 2022/09/06 01:33:22 - mmengine - INFO - Epoch(train) [95][100/940] lr: 1.0000e-04 eta: 1:00:36 time: 0.6213 data_time: 0.0509 memory: 24011 grad_norm: 5.8502 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5376 loss: 0.5376 2022/09/06 01:33:34 - mmengine - INFO - Epoch(train) [95][120/940] lr: 1.0000e-04 eta: 1:00:23 time: 0.6322 data_time: 0.0371 memory: 24011 grad_norm: 6.0403 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.6152 loss: 0.6152 2022/09/06 01:33:48 - mmengine - INFO - Epoch(train) [95][140/940] lr: 1.0000e-04 eta: 1:00:10 time: 0.6648 data_time: 0.0430 memory: 24011 grad_norm: 6.0380 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5598 loss: 0.5598 2022/09/06 01:34:00 - mmengine - INFO - Epoch(train) [95][160/940] lr: 1.0000e-04 eta: 0:59:57 time: 0.6341 data_time: 0.0304 memory: 24011 grad_norm: 5.3135 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5435 loss: 0.5435 2022/09/06 01:34:13 - mmengine - INFO - Epoch(train) [95][180/940] lr: 1.0000e-04 eta: 0:59:44 time: 0.6551 data_time: 0.0390 memory: 24011 grad_norm: 5.7303 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.5219 loss: 0.5219 2022/09/06 01:34:26 - mmengine - INFO - Epoch(train) [95][200/940] lr: 1.0000e-04 eta: 0:59:31 time: 0.6445 data_time: 0.0350 memory: 24011 grad_norm: 5.0533 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4608 loss: 0.4608 2022/09/06 01:34:39 - mmengine - INFO - Epoch(train) [95][220/940] lr: 1.0000e-04 eta: 0:59:18 time: 0.6490 data_time: 0.0437 memory: 24011 grad_norm: 5.8806 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.4747 loss: 0.4747 2022/09/06 01:34:52 - mmengine - INFO - Epoch(train) [95][240/940] lr: 1.0000e-04 eta: 0:59:04 time: 0.6521 data_time: 0.0319 memory: 24011 grad_norm: 5.8656 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4988 loss: 0.4988 2022/09/06 01:35:06 - mmengine - INFO - Epoch(train) [95][260/940] lr: 1.0000e-04 eta: 0:58:51 time: 0.6854 data_time: 0.0421 memory: 24011 grad_norm: 5.2529 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.5014 loss: 0.5014 2022/09/06 01:35:19 - mmengine - INFO - Epoch(train) [95][280/940] lr: 1.0000e-04 eta: 0:58:38 time: 0.6680 data_time: 0.0316 memory: 24011 grad_norm: 5.2472 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4577 loss: 0.4577 2022/09/06 01:35:32 - mmengine - INFO - Epoch(train) [95][300/940] lr: 1.0000e-04 eta: 0:58:25 time: 0.6343 data_time: 0.0387 memory: 24011 grad_norm: 6.1929 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5251 loss: 0.5251 2022/09/06 01:35:45 - mmengine - INFO - Epoch(train) [95][320/940] lr: 1.0000e-04 eta: 0:58:12 time: 0.6548 data_time: 0.0356 memory: 24011 grad_norm: 5.3608 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5412 loss: 0.5412 2022/09/06 01:35:58 - mmengine - INFO - Epoch(train) [95][340/940] lr: 1.0000e-04 eta: 0:57:59 time: 0.6452 data_time: 0.0380 memory: 24011 grad_norm: 5.7980 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5987 loss: 0.5987 2022/09/06 01:36:11 - mmengine - INFO - Epoch(train) [95][360/940] lr: 1.0000e-04 eta: 0:57:46 time: 0.6607 data_time: 0.0389 memory: 24011 grad_norm: 5.4828 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5008 loss: 0.5008 2022/09/06 01:36:24 - mmengine - INFO - Epoch(train) [95][380/940] lr: 1.0000e-04 eta: 0:57:33 time: 0.6587 data_time: 0.0486 memory: 24011 grad_norm: 5.6420 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5356 loss: 0.5356 2022/09/06 01:36:37 - mmengine - INFO - Epoch(train) [95][400/940] lr: 1.0000e-04 eta: 0:57:19 time: 0.6091 data_time: 0.0415 memory: 24011 grad_norm: 5.6472 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.4909 loss: 0.4909 2022/09/06 01:36:50 - mmengine - INFO - Epoch(train) [95][420/940] lr: 1.0000e-04 eta: 0:57:06 time: 0.6702 data_time: 0.0428 memory: 24011 grad_norm: 5.5361 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5353 loss: 0.5353 2022/09/06 01:37:03 - mmengine - INFO - Epoch(train) [95][440/940] lr: 1.0000e-04 eta: 0:56:53 time: 0.6251 data_time: 0.0385 memory: 24011 grad_norm: 5.9220 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5871 loss: 0.5871 2022/09/06 01:37:15 - mmengine - INFO - Epoch(train) [95][460/940] lr: 1.0000e-04 eta: 0:56:40 time: 0.6284 data_time: 0.0385 memory: 24011 grad_norm: 5.9086 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.5602 loss: 0.5602 2022/09/06 01:37:28 - mmengine - INFO - Epoch(train) [95][480/940] lr: 1.0000e-04 eta: 0:56:27 time: 0.6354 data_time: 0.0403 memory: 24011 grad_norm: 5.1638 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5484 loss: 0.5484 2022/09/06 01:37:41 - mmengine - INFO - Epoch(train) [95][500/940] lr: 1.0000e-04 eta: 0:56:14 time: 0.6290 data_time: 0.0379 memory: 24011 grad_norm: 5.3707 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5041 loss: 0.5041 2022/09/06 01:37:53 - mmengine - INFO - Epoch(train) [95][520/940] lr: 1.0000e-04 eta: 0:56:00 time: 0.6468 data_time: 0.0380 memory: 24011 grad_norm: 5.2723 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5154 loss: 0.5154 2022/09/06 01:38:07 - mmengine - INFO - Epoch(train) [95][540/940] lr: 1.0000e-04 eta: 0:55:47 time: 0.6690 data_time: 0.0420 memory: 24011 grad_norm: 5.4290 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5346 loss: 0.5346 2022/09/06 01:38:20 - mmengine - INFO - Epoch(train) [95][560/940] lr: 1.0000e-04 eta: 0:55:34 time: 0.6585 data_time: 0.0351 memory: 24011 grad_norm: 5.7195 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5446 loss: 0.5446 2022/09/06 01:38:33 - mmengine - INFO - Epoch(train) [95][580/940] lr: 1.0000e-04 eta: 0:55:21 time: 0.6425 data_time: 0.0392 memory: 24011 grad_norm: 5.3719 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5828 loss: 0.5828 2022/09/06 01:38:45 - mmengine - INFO - Epoch(train) [95][600/940] lr: 1.0000e-04 eta: 0:55:08 time: 0.6282 data_time: 0.0505 memory: 24011 grad_norm: 5.9791 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5512 loss: 0.5512 2022/09/06 01:38:58 - mmengine - INFO - Epoch(train) [95][620/940] lr: 1.0000e-04 eta: 0:54:55 time: 0.6378 data_time: 0.0371 memory: 24011 grad_norm: 6.7645 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5703 loss: 0.5703 2022/09/06 01:39:12 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:39:12 - mmengine - INFO - Epoch(train) [95][640/940] lr: 1.0000e-04 eta: 0:54:42 time: 0.6884 data_time: 0.1032 memory: 24011 grad_norm: 5.6764 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5628 loss: 0.5628 2022/09/06 01:39:25 - mmengine - INFO - Epoch(train) [95][660/940] lr: 1.0000e-04 eta: 0:54:29 time: 0.6669 data_time: 0.0956 memory: 24011 grad_norm: 5.4870 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4635 loss: 0.4635 2022/09/06 01:39:37 - mmengine - INFO - Epoch(train) [95][680/940] lr: 1.0000e-04 eta: 0:54:15 time: 0.6046 data_time: 0.0326 memory: 24011 grad_norm: 5.4108 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6280 loss: 0.6280 2022/09/06 01:39:50 - mmengine - INFO - Epoch(train) [95][700/940] lr: 1.0000e-04 eta: 0:54:02 time: 0.6297 data_time: 0.0352 memory: 24011 grad_norm: 5.2778 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5426 loss: 0.5426 2022/09/06 01:40:03 - mmengine - INFO - Epoch(train) [95][720/940] lr: 1.0000e-04 eta: 0:53:49 time: 0.6280 data_time: 0.0383 memory: 24011 grad_norm: 5.4497 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5149 loss: 0.5149 2022/09/06 01:40:16 - mmengine - INFO - Epoch(train) [95][740/940] lr: 1.0000e-04 eta: 0:53:36 time: 0.6429 data_time: 0.0385 memory: 24011 grad_norm: 5.6151 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5022 loss: 0.5022 2022/09/06 01:40:29 - mmengine - INFO - Epoch(train) [95][760/940] lr: 1.0000e-04 eta: 0:53:23 time: 0.6525 data_time: 0.0634 memory: 24011 grad_norm: 5.6324 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5896 loss: 0.5896 2022/09/06 01:40:42 - mmengine - INFO - Epoch(train) [95][780/940] lr: 1.0000e-04 eta: 0:53:10 time: 0.6405 data_time: 0.0396 memory: 24011 grad_norm: 5.3332 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5352 loss: 0.5352 2022/09/06 01:40:54 - mmengine - INFO - Epoch(train) [95][800/940] lr: 1.0000e-04 eta: 0:52:57 time: 0.6548 data_time: 0.0673 memory: 24011 grad_norm: 5.3619 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4631 loss: 0.4631 2022/09/06 01:41:09 - mmengine - INFO - Epoch(train) [95][820/940] lr: 1.0000e-04 eta: 0:52:43 time: 0.7144 data_time: 0.0374 memory: 24011 grad_norm: 5.3146 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5582 loss: 0.5582 2022/09/06 01:41:21 - mmengine - INFO - Epoch(train) [95][840/940] lr: 1.0000e-04 eta: 0:52:30 time: 0.6265 data_time: 0.0363 memory: 24011 grad_norm: 5.8641 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5515 loss: 0.5515 2022/09/06 01:41:35 - mmengine - INFO - Epoch(train) [95][860/940] lr: 1.0000e-04 eta: 0:52:17 time: 0.6826 data_time: 0.0431 memory: 24011 grad_norm: 5.7406 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5291 loss: 0.5291 2022/09/06 01:41:47 - mmengine - INFO - Epoch(train) [95][880/940] lr: 1.0000e-04 eta: 0:52:04 time: 0.6238 data_time: 0.0300 memory: 24011 grad_norm: 5.4910 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4783 loss: 0.4783 2022/09/06 01:42:00 - mmengine - INFO - Epoch(train) [95][900/940] lr: 1.0000e-04 eta: 0:51:51 time: 0.6368 data_time: 0.0454 memory: 24011 grad_norm: 5.3979 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5198 loss: 0.5198 2022/09/06 01:42:13 - mmengine - INFO - Epoch(train) [95][920/940] lr: 1.0000e-04 eta: 0:51:38 time: 0.6401 data_time: 0.0299 memory: 24011 grad_norm: 5.9334 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5124 loss: 0.5124 2022/09/06 01:42:24 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:42:24 - mmengine - INFO - Epoch(train) [95][940/940] lr: 1.0000e-04 eta: 0:51:25 time: 0.5588 data_time: 0.0297 memory: 24011 grad_norm: 5.6892 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5862 loss: 0.5862 2022/09/06 01:42:38 - mmengine - INFO - Epoch(val) [95][20/78] eta: 0:00:39 time: 0.6849 data_time: 0.5258 memory: 3625 2022/09/06 01:42:48 - mmengine - INFO - Epoch(val) [95][40/78] eta: 0:00:18 time: 0.4787 data_time: 0.3197 memory: 3625 2022/09/06 01:43:01 - mmengine - INFO - Epoch(val) [95][60/78] eta: 0:00:11 time: 0.6512 data_time: 0.4916 memory: 3625 2022/09/06 01:43:10 - mmengine - INFO - Epoch(val) [95][78/78] acc/top1: 0.7421 acc/top5: 0.9079 acc/mean1: 0.7420 2022/09/06 01:43:28 - mmengine - INFO - Epoch(train) [96][20/940] lr: 1.0000e-04 eta: 0:51:12 time: 0.8862 data_time: 0.2629 memory: 24011 grad_norm: 5.5300 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4876 loss: 0.4876 2022/09/06 01:43:41 - mmengine - INFO - Epoch(train) [96][40/940] lr: 1.0000e-04 eta: 0:50:58 time: 0.6460 data_time: 0.0438 memory: 24011 grad_norm: 5.3112 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4517 loss: 0.4517 2022/09/06 01:43:55 - mmengine - INFO - Epoch(train) [96][60/940] lr: 1.0000e-04 eta: 0:50:45 time: 0.7009 data_time: 0.0483 memory: 24011 grad_norm: 5.6928 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4985 loss: 0.4985 2022/09/06 01:44:08 - mmengine - INFO - Epoch(train) [96][80/940] lr: 1.0000e-04 eta: 0:50:32 time: 0.6292 data_time: 0.0398 memory: 24011 grad_norm: 5.1746 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5253 loss: 0.5253 2022/09/06 01:44:21 - mmengine - INFO - Epoch(train) [96][100/940] lr: 1.0000e-04 eta: 0:50:19 time: 0.6773 data_time: 0.0392 memory: 24011 grad_norm: 5.4611 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5623 loss: 0.5623 2022/09/06 01:44:34 - mmengine - INFO - Epoch(train) [96][120/940] lr: 1.0000e-04 eta: 0:50:06 time: 0.6387 data_time: 0.0427 memory: 24011 grad_norm: 5.3957 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5308 loss: 0.5308 2022/09/06 01:44:48 - mmengine - INFO - Epoch(train) [96][140/940] lr: 1.0000e-04 eta: 0:49:53 time: 0.7027 data_time: 0.0409 memory: 24011 grad_norm: 5.4660 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5457 loss: 0.5457 2022/09/06 01:45:00 - mmengine - INFO - Epoch(train) [96][160/940] lr: 1.0000e-04 eta: 0:49:40 time: 0.5898 data_time: 0.0339 memory: 24011 grad_norm: 5.9801 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5391 loss: 0.5391 2022/09/06 01:45:13 - mmengine - INFO - Epoch(train) [96][180/940] lr: 1.0000e-04 eta: 0:49:27 time: 0.6429 data_time: 0.0455 memory: 24011 grad_norm: 5.5388 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5355 loss: 0.5355 2022/09/06 01:45:26 - mmengine - INFO - Epoch(train) [96][200/940] lr: 1.0000e-04 eta: 0:49:13 time: 0.6728 data_time: 0.0553 memory: 24011 grad_norm: 5.4319 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5242 loss: 0.5242 2022/09/06 01:45:39 - mmengine - INFO - Epoch(train) [96][220/940] lr: 1.0000e-04 eta: 0:49:00 time: 0.6201 data_time: 0.0406 memory: 24011 grad_norm: 5.6360 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4930 loss: 0.4930 2022/09/06 01:45:52 - mmengine - INFO - Epoch(train) [96][240/940] lr: 1.0000e-04 eta: 0:48:47 time: 0.6580 data_time: 0.0415 memory: 24011 grad_norm: 5.2490 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5649 loss: 0.5649 2022/09/06 01:46:05 - mmengine - INFO - Epoch(train) [96][260/940] lr: 1.0000e-04 eta: 0:48:34 time: 0.6727 data_time: 0.0379 memory: 24011 grad_norm: 5.3686 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5302 loss: 0.5302 2022/09/06 01:46:19 - mmengine - INFO - Epoch(train) [96][280/940] lr: 1.0000e-04 eta: 0:48:21 time: 0.6575 data_time: 0.0423 memory: 24011 grad_norm: 5.6679 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.6092 loss: 0.6092 2022/09/06 01:46:32 - mmengine - INFO - Epoch(train) [96][300/940] lr: 1.0000e-04 eta: 0:48:08 time: 0.6549 data_time: 0.0497 memory: 24011 grad_norm: 5.5853 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6349 loss: 0.6349 2022/09/06 01:46:45 - mmengine - INFO - Epoch(train) [96][320/940] lr: 1.0000e-04 eta: 0:47:55 time: 0.6523 data_time: 0.0454 memory: 24011 grad_norm: 6.3454 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4926 loss: 0.4926 2022/09/06 01:46:59 - mmengine - INFO - Epoch(train) [96][340/940] lr: 1.0000e-04 eta: 0:47:42 time: 0.6884 data_time: 0.0344 memory: 24011 grad_norm: 6.0077 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5467 loss: 0.5467 2022/09/06 01:47:11 - mmengine - INFO - Epoch(train) [96][360/940] lr: 1.0000e-04 eta: 0:47:28 time: 0.6387 data_time: 0.0419 memory: 24011 grad_norm: 5.3331 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.5995 loss: 0.5995 2022/09/06 01:47:25 - mmengine - INFO - Epoch(train) [96][380/940] lr: 1.0000e-04 eta: 0:47:15 time: 0.6997 data_time: 0.0422 memory: 24011 grad_norm: 5.6877 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6065 loss: 0.6065 2022/09/06 01:47:38 - mmengine - INFO - Epoch(train) [96][400/940] lr: 1.0000e-04 eta: 0:47:02 time: 0.6198 data_time: 0.0360 memory: 24011 grad_norm: 5.4797 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5428 loss: 0.5428 2022/09/06 01:47:50 - mmengine - INFO - Epoch(train) [96][420/940] lr: 1.0000e-04 eta: 0:46:49 time: 0.6356 data_time: 0.0533 memory: 24011 grad_norm: 5.1403 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.4793 loss: 0.4793 2022/09/06 01:48:03 - mmengine - INFO - Epoch(train) [96][440/940] lr: 1.0000e-04 eta: 0:46:36 time: 0.6429 data_time: 0.0379 memory: 24011 grad_norm: 5.5847 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5338 loss: 0.5338 2022/09/06 01:48:16 - mmengine - INFO - Epoch(train) [96][460/940] lr: 1.0000e-04 eta: 0:46:23 time: 0.6243 data_time: 0.0415 memory: 24011 grad_norm: 6.0251 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5644 loss: 0.5644 2022/09/06 01:48:29 - mmengine - INFO - Epoch(train) [96][480/940] lr: 1.0000e-04 eta: 0:46:10 time: 0.6689 data_time: 0.0498 memory: 24011 grad_norm: 6.5163 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.4850 loss: 0.4850 2022/09/06 01:48:42 - mmengine - INFO - Epoch(train) [96][500/940] lr: 1.0000e-04 eta: 0:45:56 time: 0.6429 data_time: 0.0442 memory: 24011 grad_norm: 5.2145 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5428 loss: 0.5428 2022/09/06 01:48:55 - mmengine - INFO - Epoch(train) [96][520/940] lr: 1.0000e-04 eta: 0:45:43 time: 0.6723 data_time: 0.0337 memory: 24011 grad_norm: 5.6890 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5335 loss: 0.5335 2022/09/06 01:49:08 - mmengine - INFO - Epoch(train) [96][540/940] lr: 1.0000e-04 eta: 0:45:30 time: 0.6302 data_time: 0.0395 memory: 24011 grad_norm: 5.0685 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5098 loss: 0.5098 2022/09/06 01:49:20 - mmengine - INFO - Epoch(train) [96][560/940] lr: 1.0000e-04 eta: 0:45:17 time: 0.6181 data_time: 0.0407 memory: 24011 grad_norm: 5.4272 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5143 loss: 0.5143 2022/09/06 01:49:34 - mmengine - INFO - Epoch(train) [96][580/940] lr: 1.0000e-04 eta: 0:45:04 time: 0.6929 data_time: 0.0385 memory: 24011 grad_norm: 5.1226 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5158 loss: 0.5158 2022/09/06 01:49:47 - mmengine - INFO - Epoch(train) [96][600/940] lr: 1.0000e-04 eta: 0:44:51 time: 0.6269 data_time: 0.0446 memory: 24011 grad_norm: 5.4285 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5777 loss: 0.5777 2022/09/06 01:50:00 - mmengine - INFO - Epoch(train) [96][620/940] lr: 1.0000e-04 eta: 0:44:38 time: 0.6716 data_time: 0.0619 memory: 24011 grad_norm: 5.6293 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4976 loss: 0.4976 2022/09/06 01:50:13 - mmengine - INFO - Epoch(train) [96][640/940] lr: 1.0000e-04 eta: 0:44:25 time: 0.6296 data_time: 0.0446 memory: 24011 grad_norm: 6.3554 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.4798 loss: 0.4798 2022/09/06 01:50:25 - mmengine - INFO - Epoch(train) [96][660/940] lr: 1.0000e-04 eta: 0:44:11 time: 0.5982 data_time: 0.0457 memory: 24011 grad_norm: 5.6893 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5207 loss: 0.5207 2022/09/06 01:50:38 - mmengine - INFO - Epoch(train) [96][680/940] lr: 1.0000e-04 eta: 0:43:58 time: 0.6342 data_time: 0.0421 memory: 24011 grad_norm: 5.7619 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5092 loss: 0.5092 2022/09/06 01:50:51 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:50:51 - mmengine - INFO - Epoch(train) [96][700/940] lr: 1.0000e-04 eta: 0:43:45 time: 0.6553 data_time: 0.0555 memory: 24011 grad_norm: 5.4594 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5572 loss: 0.5572 2022/09/06 01:51:04 - mmengine - INFO - Epoch(train) [96][720/940] lr: 1.0000e-04 eta: 0:43:32 time: 0.6405 data_time: 0.0483 memory: 24011 grad_norm: 5.6667 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5215 loss: 0.5215 2022/09/06 01:51:16 - mmengine - INFO - Epoch(train) [96][740/940] lr: 1.0000e-04 eta: 0:43:19 time: 0.6450 data_time: 0.0382 memory: 24011 grad_norm: 6.3772 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6225 loss: 0.6225 2022/09/06 01:51:30 - mmengine - INFO - Epoch(train) [96][760/940] lr: 1.0000e-04 eta: 0:43:06 time: 0.6583 data_time: 0.0396 memory: 24011 grad_norm: 5.6123 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5751 loss: 0.5751 2022/09/06 01:51:43 - mmengine - INFO - Epoch(train) [96][780/940] lr: 1.0000e-04 eta: 0:42:53 time: 0.6478 data_time: 0.0449 memory: 24011 grad_norm: 5.4053 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5203 loss: 0.5203 2022/09/06 01:51:56 - mmengine - INFO - Epoch(train) [96][800/940] lr: 1.0000e-04 eta: 0:42:39 time: 0.6703 data_time: 0.0504 memory: 24011 grad_norm: 5.5316 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4625 loss: 0.4625 2022/09/06 01:52:09 - mmengine - INFO - Epoch(train) [96][820/940] lr: 1.0000e-04 eta: 0:42:26 time: 0.6720 data_time: 0.0439 memory: 24011 grad_norm: 5.6187 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5160 loss: 0.5160 2022/09/06 01:52:22 - mmengine - INFO - Epoch(train) [96][840/940] lr: 1.0000e-04 eta: 0:42:13 time: 0.6457 data_time: 0.0424 memory: 24011 grad_norm: 5.9006 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5385 loss: 0.5385 2022/09/06 01:52:35 - mmengine - INFO - Epoch(train) [96][860/940] lr: 1.0000e-04 eta: 0:42:00 time: 0.6326 data_time: 0.0450 memory: 24011 grad_norm: 5.3312 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5383 loss: 0.5383 2022/09/06 01:52:47 - mmengine - INFO - Epoch(train) [96][880/940] lr: 1.0000e-04 eta: 0:41:47 time: 0.6150 data_time: 0.0413 memory: 24011 grad_norm: 5.0535 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5827 loss: 0.5827 2022/09/06 01:53:00 - mmengine - INFO - Epoch(train) [96][900/940] lr: 1.0000e-04 eta: 0:41:34 time: 0.6327 data_time: 0.0407 memory: 24011 grad_norm: 6.0686 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4661 loss: 0.4661 2022/09/06 01:53:13 - mmengine - INFO - Epoch(train) [96][920/940] lr: 1.0000e-04 eta: 0:41:21 time: 0.6483 data_time: 0.0437 memory: 24011 grad_norm: 5.3638 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5849 loss: 0.5849 2022/09/06 01:53:25 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 01:53:25 - mmengine - INFO - Epoch(train) [96][940/940] lr: 1.0000e-04 eta: 0:41:07 time: 0.5839 data_time: 0.0420 memory: 24011 grad_norm: 6.3686 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.5819 loss: 0.5819 2022/09/06 01:53:25 - mmengine - INFO - Saving checkpoint at 96 epochs 2022/09/06 01:53:45 - mmengine - INFO - Epoch(val) [96][20/78] eta: 0:00:41 time: 0.7200 data_time: 0.5635 memory: 3625 2022/09/06 01:53:54 - mmengine - INFO - Epoch(val) [96][40/78] eta: 0:00:17 time: 0.4564 data_time: 0.3002 memory: 3625 2022/09/06 01:54:07 - mmengine - INFO - Epoch(val) [96][60/78] eta: 0:00:11 time: 0.6427 data_time: 0.4909 memory: 3625 2022/09/06 01:54:15 - mmengine - INFO - Epoch(val) [96][78/78] acc/top1: 0.7420 acc/top5: 0.9082 acc/mean1: 0.7419 2022/09/06 01:54:33 - mmengine - INFO - Epoch(train) [97][20/940] lr: 1.0000e-04 eta: 0:40:54 time: 0.8964 data_time: 0.2562 memory: 24011 grad_norm: 5.5176 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5195 loss: 0.5195 2022/09/06 01:54:46 - mmengine - INFO - Epoch(train) [97][40/940] lr: 1.0000e-04 eta: 0:40:41 time: 0.6451 data_time: 0.0382 memory: 24011 grad_norm: 5.5381 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5603 loss: 0.5603 2022/09/06 01:55:00 - mmengine - INFO - Epoch(train) [97][60/940] lr: 1.0000e-04 eta: 0:40:28 time: 0.6600 data_time: 0.0467 memory: 24011 grad_norm: 5.4492 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4840 loss: 0.4840 2022/09/06 01:55:13 - mmengine - INFO - Epoch(train) [97][80/940] lr: 1.0000e-04 eta: 0:40:15 time: 0.6611 data_time: 0.0390 memory: 24011 grad_norm: 5.4069 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5742 loss: 0.5742 2022/09/06 01:55:27 - mmengine - INFO - Epoch(train) [97][100/940] lr: 1.0000e-04 eta: 0:40:02 time: 0.7045 data_time: 0.0403 memory: 24011 grad_norm: 6.0275 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.5362 loss: 0.5362 2022/09/06 01:55:40 - mmengine - INFO - Epoch(train) [97][120/940] lr: 1.0000e-04 eta: 0:39:49 time: 0.6478 data_time: 0.0408 memory: 24011 grad_norm: 5.4452 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5981 loss: 0.5981 2022/09/06 01:55:53 - mmengine - INFO - Epoch(train) [97][140/940] lr: 1.0000e-04 eta: 0:39:36 time: 0.6643 data_time: 0.0428 memory: 24011 grad_norm: 5.1349 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.6057 loss: 0.6057 2022/09/06 01:56:06 - mmengine - INFO - Epoch(train) [97][160/940] lr: 1.0000e-04 eta: 0:39:23 time: 0.6289 data_time: 0.0456 memory: 24011 grad_norm: 5.3618 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5496 loss: 0.5496 2022/09/06 01:56:19 - mmengine - INFO - Epoch(train) [97][180/940] lr: 1.0000e-04 eta: 0:39:09 time: 0.6548 data_time: 0.0598 memory: 24011 grad_norm: 5.3488 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5301 loss: 0.5301 2022/09/06 01:56:31 - mmengine - INFO - Epoch(train) [97][200/940] lr: 1.0000e-04 eta: 0:38:56 time: 0.6126 data_time: 0.0389 memory: 24011 grad_norm: 6.1174 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4846 loss: 0.4846 2022/09/06 01:56:44 - mmengine - INFO - Epoch(train) [97][220/940] lr: 1.0000e-04 eta: 0:38:43 time: 0.6564 data_time: 0.0352 memory: 24011 grad_norm: 6.3388 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4608 loss: 0.4608 2022/09/06 01:56:57 - mmengine - INFO - Epoch(train) [97][240/940] lr: 1.0000e-04 eta: 0:38:30 time: 0.6318 data_time: 0.0454 memory: 24011 grad_norm: 5.5780 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4660 loss: 0.4660 2022/09/06 01:57:10 - mmengine - INFO - Epoch(train) [97][260/940] lr: 1.0000e-04 eta: 0:38:17 time: 0.6648 data_time: 0.0424 memory: 24011 grad_norm: 5.5198 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5445 loss: 0.5445 2022/09/06 01:57:23 - mmengine - INFO - Epoch(train) [97][280/940] lr: 1.0000e-04 eta: 0:38:04 time: 0.6641 data_time: 0.0498 memory: 24011 grad_norm: 5.6964 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.4832 loss: 0.4832 2022/09/06 01:57:37 - mmengine - INFO - Epoch(train) [97][300/940] lr: 1.0000e-04 eta: 0:37:51 time: 0.6741 data_time: 0.0428 memory: 24011 grad_norm: 5.7584 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5667 loss: 0.5667 2022/09/06 01:57:49 - mmengine - INFO - Epoch(train) [97][320/940] lr: 1.0000e-04 eta: 0:37:37 time: 0.6017 data_time: 0.0392 memory: 24011 grad_norm: 5.3663 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5306 loss: 0.5306 2022/09/06 01:58:02 - mmengine - INFO - Epoch(train) [97][340/940] lr: 1.0000e-04 eta: 0:37:24 time: 0.6337 data_time: 0.0462 memory: 24011 grad_norm: 5.3006 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5501 loss: 0.5501 2022/09/06 01:58:15 - mmengine - INFO - Epoch(train) [97][360/940] lr: 1.0000e-04 eta: 0:37:11 time: 0.6485 data_time: 0.0332 memory: 24011 grad_norm: 5.6733 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5490 loss: 0.5490 2022/09/06 01:58:28 - mmengine - INFO - Epoch(train) [97][380/940] lr: 1.0000e-04 eta: 0:36:58 time: 0.6643 data_time: 0.0536 memory: 24011 grad_norm: 5.5286 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5051 loss: 0.5051 2022/09/06 01:58:41 - mmengine - INFO - Epoch(train) [97][400/940] lr: 1.0000e-04 eta: 0:36:45 time: 0.6398 data_time: 0.0369 memory: 24011 grad_norm: 5.3011 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5537 loss: 0.5537 2022/09/06 01:58:54 - mmengine - INFO - Epoch(train) [97][420/940] lr: 1.0000e-04 eta: 0:36:32 time: 0.6703 data_time: 0.0827 memory: 24011 grad_norm: 4.9996 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5104 loss: 0.5104 2022/09/06 01:59:07 - mmengine - INFO - Epoch(train) [97][440/940] lr: 1.0000e-04 eta: 0:36:19 time: 0.6526 data_time: 0.0881 memory: 24011 grad_norm: 5.2242 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5037 loss: 0.5037 2022/09/06 01:59:20 - mmengine - INFO - Epoch(train) [97][460/940] lr: 1.0000e-04 eta: 0:36:06 time: 0.6360 data_time: 0.0649 memory: 24011 grad_norm: 5.7583 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.5691 loss: 0.5691 2022/09/06 01:59:32 - mmengine - INFO - Epoch(train) [97][480/940] lr: 1.0000e-04 eta: 0:35:52 time: 0.6196 data_time: 0.0520 memory: 24011 grad_norm: 5.6905 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.6454 loss: 0.6454 2022/09/06 01:59:45 - mmengine - INFO - Epoch(train) [97][500/940] lr: 1.0000e-04 eta: 0:35:39 time: 0.6341 data_time: 0.0678 memory: 24011 grad_norm: 5.7181 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5230 loss: 0.5230 2022/09/06 01:59:58 - mmengine - INFO - Epoch(train) [97][520/940] lr: 1.0000e-04 eta: 0:35:26 time: 0.6511 data_time: 0.0725 memory: 24011 grad_norm: 6.1122 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5157 loss: 0.5157 2022/09/06 02:00:11 - mmengine - INFO - Epoch(train) [97][540/940] lr: 1.0000e-04 eta: 0:35:13 time: 0.6534 data_time: 0.0451 memory: 24011 grad_norm: 6.5171 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.5616 loss: 0.5616 2022/09/06 02:00:25 - mmengine - INFO - Epoch(train) [97][560/940] lr: 1.0000e-04 eta: 0:35:00 time: 0.6779 data_time: 0.0357 memory: 24011 grad_norm: 5.4461 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.4844 loss: 0.4844 2022/09/06 02:00:37 - mmengine - INFO - Epoch(train) [97][580/940] lr: 1.0000e-04 eta: 0:34:47 time: 0.6236 data_time: 0.0428 memory: 24011 grad_norm: 5.3731 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5220 loss: 0.5220 2022/09/06 02:00:50 - mmengine - INFO - Epoch(train) [97][600/940] lr: 1.0000e-04 eta: 0:34:34 time: 0.6534 data_time: 0.0404 memory: 24011 grad_norm: 5.1295 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5441 loss: 0.5441 2022/09/06 02:01:03 - mmengine - INFO - Epoch(train) [97][620/940] lr: 1.0000e-04 eta: 0:34:20 time: 0.6342 data_time: 0.0388 memory: 24011 grad_norm: 6.0387 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5375 loss: 0.5375 2022/09/06 02:01:18 - mmengine - INFO - Epoch(train) [97][640/940] lr: 1.0000e-04 eta: 0:34:07 time: 0.7326 data_time: 0.0391 memory: 24011 grad_norm: 6.5092 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4176 loss: 0.4176 2022/09/06 02:01:30 - mmengine - INFO - Epoch(train) [97][660/940] lr: 1.0000e-04 eta: 0:33:54 time: 0.5991 data_time: 0.0418 memory: 24011 grad_norm: 12.4598 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5488 loss: 0.5488 2022/09/06 02:01:42 - mmengine - INFO - Epoch(train) [97][680/940] lr: 1.0000e-04 eta: 0:33:41 time: 0.6379 data_time: 0.0376 memory: 24011 grad_norm: 6.0099 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5441 loss: 0.5441 2022/09/06 02:01:56 - mmengine - INFO - Epoch(train) [97][700/940] lr: 1.0000e-04 eta: 0:33:28 time: 0.6696 data_time: 0.0402 memory: 24011 grad_norm: 5.4630 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5525 loss: 0.5525 2022/09/06 02:02:09 - mmengine - INFO - Epoch(train) [97][720/940] lr: 1.0000e-04 eta: 0:33:15 time: 0.6342 data_time: 0.0389 memory: 24011 grad_norm: 5.2660 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5025 loss: 0.5025 2022/09/06 02:02:21 - mmengine - INFO - Epoch(train) [97][740/940] lr: 1.0000e-04 eta: 0:33:02 time: 0.6317 data_time: 0.0462 memory: 24011 grad_norm: 6.3213 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5623 loss: 0.5623 2022/09/06 02:02:33 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 02:02:33 - mmengine - INFO - Epoch(train) [97][760/940] lr: 1.0000e-04 eta: 0:32:48 time: 0.6053 data_time: 0.0393 memory: 24011 grad_norm: 5.2928 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5110 loss: 0.5110 2022/09/06 02:02:47 - mmengine - INFO - Epoch(train) [97][780/940] lr: 1.0000e-04 eta: 0:32:35 time: 0.6761 data_time: 0.0417 memory: 24011 grad_norm: 5.3776 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5453 loss: 0.5453 2022/09/06 02:03:00 - mmengine - INFO - Epoch(train) [97][800/940] lr: 1.0000e-04 eta: 0:32:22 time: 0.6422 data_time: 0.0411 memory: 24011 grad_norm: 6.2488 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4685 loss: 0.4685 2022/09/06 02:03:12 - mmengine - INFO - Epoch(train) [97][820/940] lr: 1.0000e-04 eta: 0:32:09 time: 0.6323 data_time: 0.0450 memory: 24011 grad_norm: 5.1534 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5360 loss: 0.5360 2022/09/06 02:03:25 - mmengine - INFO - Epoch(train) [97][840/940] lr: 1.0000e-04 eta: 0:31:56 time: 0.6207 data_time: 0.0393 memory: 24011 grad_norm: 5.9659 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4704 loss: 0.4704 2022/09/06 02:03:38 - mmengine - INFO - Epoch(train) [97][860/940] lr: 1.0000e-04 eta: 0:31:43 time: 0.6402 data_time: 0.0368 memory: 24011 grad_norm: 5.8815 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5039 loss: 0.5039 2022/09/06 02:03:52 - mmengine - INFO - Epoch(train) [97][880/940] lr: 1.0000e-04 eta: 0:31:30 time: 0.7125 data_time: 0.0488 memory: 24011 grad_norm: 5.8426 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.6154 loss: 0.6154 2022/09/06 02:04:04 - mmengine - INFO - Epoch(train) [97][900/940] lr: 1.0000e-04 eta: 0:31:17 time: 0.6111 data_time: 0.0377 memory: 24011 grad_norm: 5.6650 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4882 loss: 0.4882 2022/09/06 02:04:17 - mmengine - INFO - Epoch(train) [97][920/940] lr: 1.0000e-04 eta: 0:31:03 time: 0.6514 data_time: 0.0401 memory: 24011 grad_norm: 7.0786 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5871 loss: 0.5871 2022/09/06 02:04:29 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 02:04:29 - mmengine - INFO - Epoch(train) [97][940/940] lr: 1.0000e-04 eta: 0:30:50 time: 0.5754 data_time: 0.0305 memory: 24011 grad_norm: 5.9875 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 0.6121 loss: 0.6121 2022/09/06 02:04:43 - mmengine - INFO - Epoch(val) [97][20/78] eta: 0:00:40 time: 0.6997 data_time: 0.5399 memory: 3625 2022/09/06 02:04:52 - mmengine - INFO - Epoch(val) [97][40/78] eta: 0:00:17 time: 0.4538 data_time: 0.2973 memory: 3625 2022/09/06 02:05:05 - mmengine - INFO - Epoch(val) [97][60/78] eta: 0:00:12 time: 0.6669 data_time: 0.5095 memory: 3625 2022/09/06 02:05:16 - mmengine - INFO - Epoch(val) [97][78/78] acc/top1: 0.7410 acc/top5: 0.9062 acc/mean1: 0.7409 2022/09/06 02:05:34 - mmengine - INFO - Epoch(train) [98][20/940] lr: 1.0000e-04 eta: 0:30:37 time: 0.9006 data_time: 0.3173 memory: 24011 grad_norm: 5.6750 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6211 loss: 0.6211 2022/09/06 02:05:47 - mmengine - INFO - Epoch(train) [98][40/940] lr: 1.0000e-04 eta: 0:30:24 time: 0.6463 data_time: 0.0372 memory: 24011 grad_norm: 5.8421 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5500 loss: 0.5500 2022/09/06 02:06:01 - mmengine - INFO - Epoch(train) [98][60/940] lr: 1.0000e-04 eta: 0:30:11 time: 0.6683 data_time: 0.0481 memory: 24011 grad_norm: 5.4138 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.4610 loss: 0.4610 2022/09/06 02:06:13 - mmengine - INFO - Epoch(train) [98][80/940] lr: 1.0000e-04 eta: 0:29:58 time: 0.6391 data_time: 0.0326 memory: 24011 grad_norm: 5.3066 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.5349 loss: 0.5349 2022/09/06 02:06:27 - mmengine - INFO - Epoch(train) [98][100/940] lr: 1.0000e-04 eta: 0:29:45 time: 0.6936 data_time: 0.0412 memory: 24011 grad_norm: 5.3553 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5452 loss: 0.5452 2022/09/06 02:06:40 - mmengine - INFO - Epoch(train) [98][120/940] lr: 1.0000e-04 eta: 0:29:32 time: 0.6438 data_time: 0.0313 memory: 24011 grad_norm: 6.1374 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.4977 loss: 0.4977 2022/09/06 02:06:53 - mmengine - INFO - Epoch(train) [98][140/940] lr: 1.0000e-04 eta: 0:29:19 time: 0.6220 data_time: 0.0404 memory: 24011 grad_norm: 5.5398 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.6223 loss: 0.6223 2022/09/06 02:07:05 - mmengine - INFO - Epoch(train) [98][160/940] lr: 1.0000e-04 eta: 0:29:05 time: 0.6437 data_time: 0.0393 memory: 24011 grad_norm: 5.6132 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5141 loss: 0.5141 2022/09/06 02:07:18 - mmengine - INFO - Epoch(train) [98][180/940] lr: 1.0000e-04 eta: 0:28:52 time: 0.6202 data_time: 0.0410 memory: 24011 grad_norm: 5.7839 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.5405 loss: 0.5405 2022/09/06 02:07:31 - mmengine - INFO - Epoch(train) [98][200/940] lr: 1.0000e-04 eta: 0:28:39 time: 0.6399 data_time: 0.0366 memory: 24011 grad_norm: 5.1892 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.5315 loss: 0.5315 2022/09/06 02:07:44 - mmengine - INFO - Epoch(train) [98][220/940] lr: 1.0000e-04 eta: 0:28:26 time: 0.6879 data_time: 0.0417 memory: 24011 grad_norm: 5.4761 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5059 loss: 0.5059 2022/09/06 02:07:57 - mmengine - INFO - Epoch(train) [98][240/940] lr: 1.0000e-04 eta: 0:28:13 time: 0.6210 data_time: 0.0455 memory: 24011 grad_norm: 6.0140 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5952 loss: 0.5952 2022/09/06 02:08:10 - mmengine - INFO - Epoch(train) [98][260/940] lr: 1.0000e-04 eta: 0:28:00 time: 0.6652 data_time: 0.0448 memory: 24011 grad_norm: 5.6708 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4653 loss: 0.4653 2022/09/06 02:08:23 - mmengine - INFO - Epoch(train) [98][280/940] lr: 1.0000e-04 eta: 0:27:47 time: 0.6255 data_time: 0.0369 memory: 24011 grad_norm: 5.7705 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5051 loss: 0.5051 2022/09/06 02:08:36 - mmengine - INFO - Epoch(train) [98][300/940] lr: 1.0000e-04 eta: 0:27:33 time: 0.6606 data_time: 0.0407 memory: 24011 grad_norm: 5.6131 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5133 loss: 0.5133 2022/09/06 02:08:48 - mmengine - INFO - Epoch(train) [98][320/940] lr: 1.0000e-04 eta: 0:27:20 time: 0.6244 data_time: 0.0548 memory: 24011 grad_norm: 5.9216 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5710 loss: 0.5710 2022/09/06 02:09:02 - mmengine - INFO - Epoch(train) [98][340/940] lr: 1.0000e-04 eta: 0:27:07 time: 0.6638 data_time: 0.0458 memory: 24011 grad_norm: 5.4188 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4761 loss: 0.4761 2022/09/06 02:09:14 - mmengine - INFO - Epoch(train) [98][360/940] lr: 1.0000e-04 eta: 0:26:54 time: 0.6337 data_time: 0.0402 memory: 24011 grad_norm: 5.9843 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6730 loss: 0.6730 2022/09/06 02:09:27 - mmengine - INFO - Epoch(train) [98][380/940] lr: 1.0000e-04 eta: 0:26:41 time: 0.6294 data_time: 0.0388 memory: 24011 grad_norm: 5.7894 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5858 loss: 0.5858 2022/09/06 02:09:40 - mmengine - INFO - Epoch(train) [98][400/940] lr: 1.0000e-04 eta: 0:26:28 time: 0.6611 data_time: 0.0373 memory: 24011 grad_norm: 5.4993 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.4815 loss: 0.4815 2022/09/06 02:09:53 - mmengine - INFO - Epoch(train) [98][420/940] lr: 1.0000e-04 eta: 0:26:15 time: 0.6489 data_time: 0.0407 memory: 24011 grad_norm: 6.3070 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5239 loss: 0.5239 2022/09/06 02:10:07 - mmengine - INFO - Epoch(train) [98][440/940] lr: 1.0000e-04 eta: 0:26:02 time: 0.6666 data_time: 0.0341 memory: 24011 grad_norm: 6.0402 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5572 loss: 0.5572 2022/09/06 02:10:20 - mmengine - INFO - Epoch(train) [98][460/940] lr: 1.0000e-04 eta: 0:25:48 time: 0.6769 data_time: 0.0411 memory: 24011 grad_norm: 5.3000 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5749 loss: 0.5749 2022/09/06 02:10:34 - mmengine - INFO - Epoch(train) [98][480/940] lr: 1.0000e-04 eta: 0:25:35 time: 0.6744 data_time: 0.0368 memory: 24011 grad_norm: 5.5613 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.5125 loss: 0.5125 2022/09/06 02:10:46 - mmengine - INFO - Epoch(train) [98][500/940] lr: 1.0000e-04 eta: 0:25:22 time: 0.6106 data_time: 0.0403 memory: 24011 grad_norm: 5.7189 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5832 loss: 0.5832 2022/09/06 02:10:58 - mmengine - INFO - Epoch(train) [98][520/940] lr: 1.0000e-04 eta: 0:25:09 time: 0.6052 data_time: 0.0408 memory: 24011 grad_norm: 6.9172 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4635 loss: 0.4635 2022/09/06 02:11:11 - mmengine - INFO - Epoch(train) [98][540/940] lr: 1.0000e-04 eta: 0:24:56 time: 0.6632 data_time: 0.0455 memory: 24011 grad_norm: 5.7722 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5378 loss: 0.5378 2022/09/06 02:11:25 - mmengine - INFO - Epoch(train) [98][560/940] lr: 1.0000e-04 eta: 0:24:43 time: 0.6623 data_time: 0.0434 memory: 24011 grad_norm: 5.9522 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.5715 loss: 0.5715 2022/09/06 02:11:37 - mmengine - INFO - Epoch(train) [98][580/940] lr: 1.0000e-04 eta: 0:24:30 time: 0.6247 data_time: 0.0530 memory: 24011 grad_norm: 5.3030 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5343 loss: 0.5343 2022/09/06 02:11:50 - mmengine - INFO - Epoch(train) [98][600/940] lr: 1.0000e-04 eta: 0:24:16 time: 0.6589 data_time: 0.0388 memory: 24011 grad_norm: 5.4163 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.6283 loss: 0.6283 2022/09/06 02:12:02 - mmengine - INFO - Epoch(train) [98][620/940] lr: 1.0000e-04 eta: 0:24:03 time: 0.6090 data_time: 0.0425 memory: 24011 grad_norm: 5.8790 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4767 loss: 0.4767 2022/09/06 02:12:16 - mmengine - INFO - Epoch(train) [98][640/940] lr: 1.0000e-04 eta: 0:23:50 time: 0.6951 data_time: 0.0382 memory: 24011 grad_norm: 5.3450 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5746 loss: 0.5746 2022/09/06 02:12:30 - mmengine - INFO - Epoch(train) [98][660/940] lr: 1.0000e-04 eta: 0:23:37 time: 0.6944 data_time: 0.0383 memory: 24011 grad_norm: 5.4081 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4905 loss: 0.4905 2022/09/06 02:12:42 - mmengine - INFO - Epoch(train) [98][680/940] lr: 1.0000e-04 eta: 0:23:24 time: 0.6119 data_time: 0.0367 memory: 24011 grad_norm: 5.5153 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.6144 loss: 0.6144 2022/09/06 02:12:55 - mmengine - INFO - Epoch(train) [98][700/940] lr: 1.0000e-04 eta: 0:23:11 time: 0.6333 data_time: 0.0388 memory: 24011 grad_norm: 5.8150 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5038 loss: 0.5038 2022/09/06 02:13:08 - mmengine - INFO - Epoch(train) [98][720/940] lr: 1.0000e-04 eta: 0:22:58 time: 0.6414 data_time: 0.0362 memory: 24011 grad_norm: 5.2788 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.4921 loss: 0.4921 2022/09/06 02:13:22 - mmengine - INFO - Epoch(train) [98][740/940] lr: 1.0000e-04 eta: 0:22:45 time: 0.6902 data_time: 0.0467 memory: 24011 grad_norm: 7.4432 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5111 loss: 0.5111 2022/09/06 02:13:35 - mmengine - INFO - Epoch(train) [98][760/940] lr: 1.0000e-04 eta: 0:22:31 time: 0.6726 data_time: 0.0371 memory: 24011 grad_norm: 5.6097 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5734 loss: 0.5734 2022/09/06 02:13:48 - mmengine - INFO - Epoch(train) [98][780/940] lr: 1.0000e-04 eta: 0:22:18 time: 0.6145 data_time: 0.0344 memory: 24011 grad_norm: 6.0058 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4922 loss: 0.4922 2022/09/06 02:14:00 - mmengine - INFO - Epoch(train) [98][800/940] lr: 1.0000e-04 eta: 0:22:05 time: 0.6323 data_time: 0.0393 memory: 24011 grad_norm: 5.2884 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.5437 loss: 0.5437 2022/09/06 02:14:13 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 02:14:13 - mmengine - INFO - Epoch(train) [98][820/940] lr: 1.0000e-04 eta: 0:21:52 time: 0.6365 data_time: 0.0344 memory: 24011 grad_norm: 5.4438 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.6287 loss: 0.6287 2022/09/06 02:14:26 - mmengine - INFO - Epoch(train) [98][840/940] lr: 1.0000e-04 eta: 0:21:39 time: 0.6767 data_time: 0.0397 memory: 24011 grad_norm: 5.2052 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5078 loss: 0.5078 2022/09/06 02:14:39 - mmengine - INFO - Epoch(train) [98][860/940] lr: 1.0000e-04 eta: 0:21:26 time: 0.6394 data_time: 0.0464 memory: 24011 grad_norm: 5.5788 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.5376 loss: 0.5376 2022/09/06 02:14:51 - mmengine - INFO - Epoch(train) [98][880/940] lr: 1.0000e-04 eta: 0:21:13 time: 0.6076 data_time: 0.0390 memory: 24011 grad_norm: 5.9232 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.4728 loss: 0.4728 2022/09/06 02:15:05 - mmengine - INFO - Epoch(train) [98][900/940] lr: 1.0000e-04 eta: 0:21:00 time: 0.6595 data_time: 0.0398 memory: 24011 grad_norm: 5.3194 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5460 loss: 0.5460 2022/09/06 02:15:18 - mmengine - INFO - Epoch(train) [98][920/940] lr: 1.0000e-04 eta: 0:20:46 time: 0.6441 data_time: 0.0464 memory: 24011 grad_norm: 5.4225 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5907 loss: 0.5907 2022/09/06 02:15:30 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 02:15:30 - mmengine - INFO - Epoch(train) [98][940/940] lr: 1.0000e-04 eta: 0:20:33 time: 0.5989 data_time: 0.0305 memory: 24011 grad_norm: 5.8834 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.5172 loss: 0.5172 2022/09/06 02:15:43 - mmengine - INFO - Epoch(val) [98][20/78] eta: 0:00:39 time: 0.6878 data_time: 0.5276 memory: 3625 2022/09/06 02:15:53 - mmengine - INFO - Epoch(val) [98][40/78] eta: 0:00:17 time: 0.4687 data_time: 0.3107 memory: 3625 2022/09/06 02:16:06 - mmengine - INFO - Epoch(val) [98][60/78] eta: 0:00:12 time: 0.6691 data_time: 0.5079 memory: 3625 2022/09/06 02:16:16 - mmengine - INFO - Epoch(val) [98][78/78] acc/top1: 0.7415 acc/top5: 0.9072 acc/mean1: 0.7414 2022/09/06 02:16:34 - mmengine - INFO - Epoch(train) [99][20/940] lr: 1.0000e-04 eta: 0:20:20 time: 0.9077 data_time: 0.2629 memory: 24011 grad_norm: 5.2475 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5104 loss: 0.5104 2022/09/06 02:16:47 - mmengine - INFO - Epoch(train) [99][40/940] lr: 1.0000e-04 eta: 0:20:07 time: 0.6420 data_time: 0.0435 memory: 24011 grad_norm: 7.7594 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5645 loss: 0.5645 2022/09/06 02:17:00 - mmengine - INFO - Epoch(train) [99][60/940] lr: 1.0000e-04 eta: 0:19:54 time: 0.6399 data_time: 0.0522 memory: 24011 grad_norm: 5.4698 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5049 loss: 0.5049 2022/09/06 02:17:13 - mmengine - INFO - Epoch(train) [99][80/940] lr: 1.0000e-04 eta: 0:19:41 time: 0.6501 data_time: 0.0577 memory: 24011 grad_norm: 5.6566 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.5407 loss: 0.5407 2022/09/06 02:17:27 - mmengine - INFO - Epoch(train) [99][100/940] lr: 1.0000e-04 eta: 0:19:28 time: 0.6855 data_time: 0.0422 memory: 24011 grad_norm: 5.5225 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4945 loss: 0.4945 2022/09/06 02:17:39 - mmengine - INFO - Epoch(train) [99][120/940] lr: 1.0000e-04 eta: 0:19:15 time: 0.6155 data_time: 0.0423 memory: 24011 grad_norm: 5.5337 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5937 loss: 0.5937 2022/09/06 02:17:52 - mmengine - INFO - Epoch(train) [99][140/940] lr: 1.0000e-04 eta: 0:19:01 time: 0.6676 data_time: 0.0761 memory: 24011 grad_norm: 5.7543 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.4323 loss: 0.4323 2022/09/06 02:18:05 - mmengine - INFO - Epoch(train) [99][160/940] lr: 1.0000e-04 eta: 0:18:48 time: 0.6569 data_time: 0.0376 memory: 24011 grad_norm: 5.5372 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6712 loss: 0.6712 2022/09/06 02:18:18 - mmengine - INFO - Epoch(train) [99][180/940] lr: 1.0000e-04 eta: 0:18:35 time: 0.6393 data_time: 0.0501 memory: 24011 grad_norm: 5.4764 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4743 loss: 0.4743 2022/09/06 02:18:31 - mmengine - INFO - Epoch(train) [99][200/940] lr: 1.0000e-04 eta: 0:18:22 time: 0.6212 data_time: 0.0378 memory: 24011 grad_norm: 5.2444 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5411 loss: 0.5411 2022/09/06 02:18:44 - mmengine - INFO - Epoch(train) [99][220/940] lr: 1.0000e-04 eta: 0:18:09 time: 0.6808 data_time: 0.0649 memory: 24011 grad_norm: 5.4841 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5361 loss: 0.5361 2022/09/06 02:18:57 - mmengine - INFO - Epoch(train) [99][240/940] lr: 1.0000e-04 eta: 0:17:56 time: 0.6464 data_time: 0.0818 memory: 24011 grad_norm: 5.5851 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.5407 loss: 0.5407 2022/09/06 02:19:10 - mmengine - INFO - Epoch(train) [99][260/940] lr: 1.0000e-04 eta: 0:17:43 time: 0.6186 data_time: 0.0429 memory: 24011 grad_norm: 5.5821 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5769 loss: 0.5769 2022/09/06 02:19:23 - mmengine - INFO - Epoch(train) [99][280/940] lr: 1.0000e-04 eta: 0:17:30 time: 0.6454 data_time: 0.0440 memory: 24011 grad_norm: 4.9840 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5038 loss: 0.5038 2022/09/06 02:19:37 - mmengine - INFO - Epoch(train) [99][300/940] lr: 1.0000e-04 eta: 0:17:16 time: 0.7202 data_time: 0.0375 memory: 24011 grad_norm: 5.2685 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5834 loss: 0.5834 2022/09/06 02:19:49 - mmengine - INFO - Epoch(train) [99][320/940] lr: 1.0000e-04 eta: 0:17:03 time: 0.6185 data_time: 0.0388 memory: 24011 grad_norm: 5.7636 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.5551 loss: 0.5551 2022/09/06 02:20:03 - mmengine - INFO - Epoch(train) [99][340/940] lr: 1.0000e-04 eta: 0:16:50 time: 0.6576 data_time: 0.0390 memory: 24011 grad_norm: 5.1974 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.5222 loss: 0.5222 2022/09/06 02:20:15 - mmengine - INFO - Epoch(train) [99][360/940] lr: 1.0000e-04 eta: 0:16:37 time: 0.6115 data_time: 0.0488 memory: 24011 grad_norm: 5.6366 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.5224 loss: 0.5224 2022/09/06 02:20:29 - mmengine - INFO - Epoch(train) [99][380/940] lr: 1.0000e-04 eta: 0:16:24 time: 0.6971 data_time: 0.0892 memory: 24011 grad_norm: 5.0205 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5504 loss: 0.5504 2022/09/06 02:20:42 - mmengine - INFO - Epoch(train) [99][400/940] lr: 1.0000e-04 eta: 0:16:11 time: 0.6428 data_time: 0.0613 memory: 24011 grad_norm: 5.2057 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.6073 loss: 0.6073 2022/09/06 02:20:54 - mmengine - INFO - Epoch(train) [99][420/940] lr: 1.0000e-04 eta: 0:15:58 time: 0.6262 data_time: 0.0579 memory: 24011 grad_norm: 5.3218 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.5353 loss: 0.5353 2022/09/06 02:21:07 - mmengine - INFO - Epoch(train) [99][440/940] lr: 1.0000e-04 eta: 0:15:45 time: 0.6256 data_time: 0.0513 memory: 24011 grad_norm: 5.4483 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5474 loss: 0.5474 2022/09/06 02:21:20 - mmengine - INFO - Epoch(train) [99][460/940] lr: 1.0000e-04 eta: 0:15:31 time: 0.6445 data_time: 0.0688 memory: 24011 grad_norm: 5.5135 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5241 loss: 0.5241 2022/09/06 02:21:32 - mmengine - INFO - Epoch(train) [99][480/940] lr: 1.0000e-04 eta: 0:15:18 time: 0.6181 data_time: 0.0321 memory: 24011 grad_norm: 5.4679 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5536 loss: 0.5536 2022/09/06 02:21:46 - mmengine - INFO - Epoch(train) [99][500/940] lr: 1.0000e-04 eta: 0:15:05 time: 0.7001 data_time: 0.0394 memory: 24011 grad_norm: 6.3287 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5263 loss: 0.5263 2022/09/06 02:21:59 - mmengine - INFO - Epoch(train) [99][520/940] lr: 1.0000e-04 eta: 0:14:52 time: 0.6278 data_time: 0.0362 memory: 24011 grad_norm: 5.7319 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4642 loss: 0.4642 2022/09/06 02:22:12 - mmengine - INFO - Epoch(train) [99][540/940] lr: 1.0000e-04 eta: 0:14:39 time: 0.6512 data_time: 0.0382 memory: 24011 grad_norm: 5.2017 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4707 loss: 0.4707 2022/09/06 02:22:24 - mmengine - INFO - Epoch(train) [99][560/940] lr: 1.0000e-04 eta: 0:14:26 time: 0.6228 data_time: 0.0377 memory: 24011 grad_norm: 5.3522 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5473 loss: 0.5473 2022/09/06 02:22:37 - mmengine - INFO - Epoch(train) [99][580/940] lr: 1.0000e-04 eta: 0:14:13 time: 0.6685 data_time: 0.0426 memory: 24011 grad_norm: 5.6587 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.4569 loss: 0.4569 2022/09/06 02:22:50 - mmengine - INFO - Epoch(train) [99][600/940] lr: 1.0000e-04 eta: 0:13:59 time: 0.6074 data_time: 0.0383 memory: 24011 grad_norm: 5.3768 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.4847 loss: 0.4847 2022/09/06 02:23:03 - mmengine - INFO - Epoch(train) [99][620/940] lr: 1.0000e-04 eta: 0:13:46 time: 0.6590 data_time: 0.0468 memory: 24011 grad_norm: 5.5847 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5315 loss: 0.5315 2022/09/06 02:23:16 - mmengine - INFO - Epoch(train) [99][640/940] lr: 1.0000e-04 eta: 0:13:33 time: 0.6498 data_time: 0.0344 memory: 24011 grad_norm: 6.5067 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.4682 loss: 0.4682 2022/09/06 02:23:29 - mmengine - INFO - Epoch(train) [99][660/940] lr: 1.0000e-04 eta: 0:13:20 time: 0.6687 data_time: 0.0424 memory: 24011 grad_norm: 5.5884 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5197 loss: 0.5197 2022/09/06 02:23:42 - mmengine - INFO - Epoch(train) [99][680/940] lr: 1.0000e-04 eta: 0:13:07 time: 0.6242 data_time: 0.0403 memory: 24011 grad_norm: 5.7560 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5807 loss: 0.5807 2022/09/06 02:23:55 - mmengine - INFO - Epoch(train) [99][700/940] lr: 1.0000e-04 eta: 0:12:54 time: 0.6480 data_time: 0.0717 memory: 24011 grad_norm: 5.9954 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5126 loss: 0.5126 2022/09/06 02:24:07 - mmengine - INFO - Epoch(train) [99][720/940] lr: 1.0000e-04 eta: 0:12:41 time: 0.6164 data_time: 0.0380 memory: 24011 grad_norm: 5.9382 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5047 loss: 0.5047 2022/09/06 02:24:20 - mmengine - INFO - Epoch(train) [99][740/940] lr: 1.0000e-04 eta: 0:12:28 time: 0.6369 data_time: 0.0634 memory: 24011 grad_norm: 5.4636 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5634 loss: 0.5634 2022/09/06 02:24:33 - mmengine - INFO - Epoch(train) [99][760/940] lr: 1.0000e-04 eta: 0:12:14 time: 0.6576 data_time: 0.0651 memory: 24011 grad_norm: 5.7570 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4628 loss: 0.4628 2022/09/06 02:24:47 - mmengine - INFO - Epoch(train) [99][780/940] lr: 1.0000e-04 eta: 0:12:01 time: 0.6764 data_time: 0.0604 memory: 24011 grad_norm: 5.5042 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.5449 loss: 0.5449 2022/09/06 02:24:59 - mmengine - INFO - Epoch(train) [99][800/940] lr: 1.0000e-04 eta: 0:11:48 time: 0.6368 data_time: 0.0425 memory: 24011 grad_norm: 5.3372 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5601 loss: 0.5601 2022/09/06 02:25:12 - mmengine - INFO - Epoch(train) [99][820/940] lr: 1.0000e-04 eta: 0:11:35 time: 0.6214 data_time: 0.0427 memory: 24011 grad_norm: 6.4740 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4545 loss: 0.4545 2022/09/06 02:25:25 - mmengine - INFO - Epoch(train) [99][840/940] lr: 1.0000e-04 eta: 0:11:22 time: 0.6813 data_time: 0.0333 memory: 24011 grad_norm: 5.5088 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4702 loss: 0.4702 2022/09/06 02:25:38 - mmengine - INFO - Epoch(train) [99][860/940] lr: 1.0000e-04 eta: 0:11:09 time: 0.6257 data_time: 0.0525 memory: 24011 grad_norm: 6.3320 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.5724 loss: 0.5724 2022/09/06 02:25:51 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 02:25:51 - mmengine - INFO - Epoch(train) [99][880/940] lr: 1.0000e-04 eta: 0:10:56 time: 0.6426 data_time: 0.0326 memory: 24011 grad_norm: 5.2009 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5208 loss: 0.5208 2022/09/06 02:26:03 - mmengine - INFO - Epoch(train) [99][900/940] lr: 1.0000e-04 eta: 0:10:43 time: 0.6368 data_time: 0.0382 memory: 24011 grad_norm: 6.9989 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5009 loss: 0.5009 2022/09/06 02:26:17 - mmengine - INFO - Epoch(train) [99][920/940] lr: 1.0000e-04 eta: 0:10:29 time: 0.7020 data_time: 0.0322 memory: 24011 grad_norm: 5.2093 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.4630 loss: 0.4630 2022/09/06 02:26:29 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 02:26:29 - mmengine - INFO - Epoch(train) [99][940/940] lr: 1.0000e-04 eta: 0:10:16 time: 0.5566 data_time: 0.0271 memory: 24011 grad_norm: 5.6267 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.4656 loss: 0.4656 2022/09/06 02:26:29 - mmengine - INFO - Saving checkpoint at 99 epochs 2022/09/06 02:26:48 - mmengine - INFO - Epoch(val) [99][20/78] eta: 0:00:41 time: 0.7154 data_time: 0.5577 memory: 3625 2022/09/06 02:26:58 - mmengine - INFO - Epoch(val) [99][40/78] eta: 0:00:17 time: 0.4572 data_time: 0.3029 memory: 3625 2022/09/06 02:27:10 - mmengine - INFO - Epoch(val) [99][60/78] eta: 0:00:11 time: 0.6374 data_time: 0.4628 memory: 3625 2022/09/06 02:27:20 - mmengine - INFO - Epoch(val) [99][78/78] acc/top1: 0.7418 acc/top5: 0.9078 acc/mean1: 0.7417 2022/09/06 02:27:38 - mmengine - INFO - Epoch(train) [100][20/940] lr: 1.0000e-04 eta: 0:10:03 time: 0.9026 data_time: 0.2578 memory: 24011 grad_norm: 5.7115 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.6066 loss: 0.6066 2022/09/06 02:27:50 - mmengine - INFO - Epoch(train) [100][40/940] lr: 1.0000e-04 eta: 0:09:50 time: 0.6285 data_time: 0.0344 memory: 24011 grad_norm: 6.7200 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5365 loss: 0.5365 2022/09/06 02:28:04 - mmengine - INFO - Epoch(train) [100][60/940] lr: 1.0000e-04 eta: 0:09:37 time: 0.6738 data_time: 0.0414 memory: 24011 grad_norm: 5.7465 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.4509 loss: 0.4509 2022/09/06 02:28:18 - mmengine - INFO - Epoch(train) [100][80/940] lr: 1.0000e-04 eta: 0:09:24 time: 0.6912 data_time: 0.0358 memory: 24011 grad_norm: 6.3188 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5372 loss: 0.5372 2022/09/06 02:28:30 - mmengine - INFO - Epoch(train) [100][100/940] lr: 1.0000e-04 eta: 0:09:11 time: 0.6343 data_time: 0.0383 memory: 24011 grad_norm: 5.4571 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.5449 loss: 0.5449 2022/09/06 02:28:43 - mmengine - INFO - Epoch(train) [100][120/940] lr: 1.0000e-04 eta: 0:08:58 time: 0.6246 data_time: 0.0413 memory: 24011 grad_norm: 5.6374 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5371 loss: 0.5371 2022/09/06 02:28:56 - mmengine - INFO - Epoch(train) [100][140/940] lr: 1.0000e-04 eta: 0:08:45 time: 0.6614 data_time: 0.0398 memory: 24011 grad_norm: 5.8345 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.6154 loss: 0.6154 2022/09/06 02:29:09 - mmengine - INFO - Epoch(train) [100][160/940] lr: 1.0000e-04 eta: 0:08:31 time: 0.6231 data_time: 0.0357 memory: 24011 grad_norm: 5.3956 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4812 loss: 0.4812 2022/09/06 02:29:22 - mmengine - INFO - Epoch(train) [100][180/940] lr: 1.0000e-04 eta: 0:08:18 time: 0.6751 data_time: 0.0408 memory: 24011 grad_norm: 5.5259 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.5113 loss: 0.5113 2022/09/06 02:29:34 - mmengine - INFO - Epoch(train) [100][200/940] lr: 1.0000e-04 eta: 0:08:05 time: 0.6114 data_time: 0.0388 memory: 24011 grad_norm: 5.6297 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5202 loss: 0.5202 2022/09/06 02:29:48 - mmengine - INFO - Epoch(train) [100][220/940] lr: 1.0000e-04 eta: 0:07:52 time: 0.6772 data_time: 0.0473 memory: 24011 grad_norm: 5.3117 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.5192 loss: 0.5192 2022/09/06 02:30:01 - mmengine - INFO - Epoch(train) [100][240/940] lr: 1.0000e-04 eta: 0:07:39 time: 0.6593 data_time: 0.0393 memory: 24011 grad_norm: 7.1287 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5494 loss: 0.5494 2022/09/06 02:30:14 - mmengine - INFO - Epoch(train) [100][260/940] lr: 1.0000e-04 eta: 0:07:26 time: 0.6612 data_time: 0.0381 memory: 24011 grad_norm: 5.8109 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.5414 loss: 0.5414 2022/09/06 02:30:27 - mmengine - INFO - Epoch(train) [100][280/940] lr: 1.0000e-04 eta: 0:07:13 time: 0.6269 data_time: 0.0564 memory: 24011 grad_norm: 6.8298 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.4959 loss: 0.4959 2022/09/06 02:30:40 - mmengine - INFO - Epoch(train) [100][300/940] lr: 1.0000e-04 eta: 0:06:59 time: 0.6648 data_time: 0.0376 memory: 24011 grad_norm: 5.8410 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.4652 loss: 0.4652 2022/09/06 02:30:54 - mmengine - INFO - Epoch(train) [100][320/940] lr: 1.0000e-04 eta: 0:06:46 time: 0.6619 data_time: 0.0361 memory: 24011 grad_norm: 5.5340 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5718 loss: 0.5718 2022/09/06 02:31:07 - mmengine - INFO - Epoch(train) [100][340/940] lr: 1.0000e-04 eta: 0:06:33 time: 0.6469 data_time: 0.0489 memory: 24011 grad_norm: 5.2654 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4876 loss: 0.4876 2022/09/06 02:31:19 - mmengine - INFO - Epoch(train) [100][360/940] lr: 1.0000e-04 eta: 0:06:20 time: 0.6440 data_time: 0.0398 memory: 24011 grad_norm: 5.4442 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5777 loss: 0.5777 2022/09/06 02:31:32 - mmengine - INFO - Epoch(train) [100][380/940] lr: 1.0000e-04 eta: 0:06:07 time: 0.6130 data_time: 0.0418 memory: 24011 grad_norm: 5.9502 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.5460 loss: 0.5460 2022/09/06 02:31:45 - mmengine - INFO - Epoch(train) [100][400/940] lr: 1.0000e-04 eta: 0:05:54 time: 0.6444 data_time: 0.0416 memory: 24011 grad_norm: 5.9948 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.4984 loss: 0.4984 2022/09/06 02:31:58 - mmengine - INFO - Epoch(train) [100][420/940] lr: 1.0000e-04 eta: 0:05:41 time: 0.6738 data_time: 0.0369 memory: 24011 grad_norm: 5.5100 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5894 loss: 0.5894 2022/09/06 02:32:12 - mmengine - INFO - Epoch(train) [100][440/940] lr: 1.0000e-04 eta: 0:05:28 time: 0.6761 data_time: 0.0381 memory: 24011 grad_norm: 5.3260 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.5390 loss: 0.5390 2022/09/06 02:32:24 - mmengine - INFO - Epoch(train) [100][460/940] lr: 1.0000e-04 eta: 0:05:14 time: 0.6086 data_time: 0.0326 memory: 24011 grad_norm: 6.3462 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5461 loss: 0.5461 2022/09/06 02:32:36 - mmengine - INFO - Epoch(train) [100][480/940] lr: 1.0000e-04 eta: 0:05:01 time: 0.6212 data_time: 0.0593 memory: 24011 grad_norm: 5.0626 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5415 loss: 0.5415 2022/09/06 02:32:49 - mmengine - INFO - Epoch(train) [100][500/940] lr: 1.0000e-04 eta: 0:04:48 time: 0.6398 data_time: 0.0467 memory: 24011 grad_norm: 5.3341 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.5660 loss: 0.5660 2022/09/06 02:33:02 - mmengine - INFO - Epoch(train) [100][520/940] lr: 1.0000e-04 eta: 0:04:35 time: 0.6624 data_time: 0.0366 memory: 24011 grad_norm: 5.5517 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.5269 loss: 0.5269 2022/09/06 02:33:15 - mmengine - INFO - Epoch(train) [100][540/940] lr: 1.0000e-04 eta: 0:04:22 time: 0.6376 data_time: 0.0446 memory: 24011 grad_norm: 5.5304 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.5233 loss: 0.5233 2022/09/06 02:33:28 - mmengine - INFO - Epoch(train) [100][560/940] lr: 1.0000e-04 eta: 0:04:09 time: 0.6307 data_time: 0.0404 memory: 24011 grad_norm: 5.2923 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.5505 loss: 0.5505 2022/09/06 02:33:41 - mmengine - INFO - Epoch(train) [100][580/940] lr: 1.0000e-04 eta: 0:03:56 time: 0.6904 data_time: 0.0411 memory: 24011 grad_norm: 6.0663 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.4876 loss: 0.4876 2022/09/06 02:33:54 - mmengine - INFO - Epoch(train) [100][600/940] lr: 1.0000e-04 eta: 0:03:43 time: 0.6396 data_time: 0.0399 memory: 24011 grad_norm: 5.2978 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.6210 loss: 0.6210 2022/09/06 02:34:07 - mmengine - INFO - Epoch(train) [100][620/940] lr: 1.0000e-04 eta: 0:03:29 time: 0.6400 data_time: 0.0424 memory: 24011 grad_norm: 5.4296 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5955 loss: 0.5955 2022/09/06 02:34:20 - mmengine - INFO - Epoch(train) [100][640/940] lr: 1.0000e-04 eta: 0:03:16 time: 0.6663 data_time: 0.0331 memory: 24011 grad_norm: 5.3336 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.5160 loss: 0.5160 2022/09/06 02:34:33 - mmengine - INFO - Epoch(train) [100][660/940] lr: 1.0000e-04 eta: 0:03:03 time: 0.6473 data_time: 0.0415 memory: 24011 grad_norm: 6.8908 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.5540 loss: 0.5540 2022/09/06 02:34:46 - mmengine - INFO - Epoch(train) [100][680/940] lr: 1.0000e-04 eta: 0:02:50 time: 0.6232 data_time: 0.0349 memory: 24011 grad_norm: 5.5190 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 0.5353 loss: 0.5353 2022/09/06 02:34:59 - mmengine - INFO - Epoch(train) [100][700/940] lr: 1.0000e-04 eta: 0:02:37 time: 0.6622 data_time: 0.0571 memory: 24011 grad_norm: 5.7147 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.6207 loss: 0.6207 2022/09/06 02:35:11 - mmengine - INFO - Epoch(train) [100][720/940] lr: 1.0000e-04 eta: 0:02:24 time: 0.6131 data_time: 0.0331 memory: 24011 grad_norm: 5.7267 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.5213 loss: 0.5213 2022/09/06 02:35:25 - mmengine - INFO - Epoch(train) [100][740/940] lr: 1.0000e-04 eta: 0:02:11 time: 0.6995 data_time: 0.0353 memory: 24011 grad_norm: 5.5801 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.5986 loss: 0.5986 2022/09/06 02:35:38 - mmengine - INFO - Epoch(train) [100][760/940] lr: 1.0000e-04 eta: 0:01:58 time: 0.6443 data_time: 0.0406 memory: 24011 grad_norm: 5.4970 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5019 loss: 0.5019 2022/09/06 02:35:52 - mmengine - INFO - Epoch(train) [100][780/940] lr: 1.0000e-04 eta: 0:01:44 time: 0.6717 data_time: 0.0366 memory: 24011 grad_norm: 5.5812 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.5019 loss: 0.5019 2022/09/06 02:36:04 - mmengine - INFO - Epoch(train) [100][800/940] lr: 1.0000e-04 eta: 0:01:31 time: 0.6229 data_time: 0.0408 memory: 24011 grad_norm: 5.3270 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.5348 loss: 0.5348 2022/09/06 02:36:17 - mmengine - INFO - Epoch(train) [100][820/940] lr: 1.0000e-04 eta: 0:01:18 time: 0.6309 data_time: 0.0389 memory: 24011 grad_norm: 6.4725 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5402 loss: 0.5402 2022/09/06 02:36:30 - mmengine - INFO - Epoch(train) [100][840/940] lr: 1.0000e-04 eta: 0:01:05 time: 0.6357 data_time: 0.0450 memory: 24011 grad_norm: 5.5530 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.5516 loss: 0.5516 2022/09/06 02:36:42 - mmengine - INFO - Epoch(train) [100][860/940] lr: 1.0000e-04 eta: 0:00:52 time: 0.6347 data_time: 0.0380 memory: 24011 grad_norm: 5.7065 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.5113 loss: 0.5113 2022/09/06 02:36:55 - mmengine - INFO - Epoch(train) [100][880/940] lr: 1.0000e-04 eta: 0:00:39 time: 0.6197 data_time: 0.0420 memory: 24011 grad_norm: 5.1434 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.5162 loss: 0.5162 2022/09/06 02:37:08 - mmengine - INFO - Epoch(train) [100][900/940] lr: 1.0000e-04 eta: 0:00:26 time: 0.6780 data_time: 0.0342 memory: 24011 grad_norm: 6.0034 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.6122 loss: 0.6122 2022/09/06 02:37:22 - mmengine - INFO - Epoch(train) [100][920/940] lr: 1.0000e-04 eta: 0:00:13 time: 0.6659 data_time: 0.0419 memory: 24011 grad_norm: 5.9648 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.5036 loss: 0.5036 2022/09/06 02:37:33 - mmengine - INFO - Exp name: tsn_swin_transformer_video_320p_1x1x3_100e_kinetics400_rgb_20220905_080608 2022/09/06 02:37:33 - mmengine - INFO - Epoch(train) [100][940/940] lr: 1.0000e-04 eta: 0:00:00 time: 0.5731 data_time: 0.0221 memory: 24011 grad_norm: 7.6164 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.4564 loss: 0.4564 2022/09/06 02:37:33 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/09/06 02:37:52 - mmengine - INFO - Epoch(val) [100][20/78] eta: 0:00:42 time: 0.7299 data_time: 0.5716 memory: 3625 2022/09/06 02:38:01 - mmengine - INFO - Epoch(val) [100][40/78] eta: 0:00:16 time: 0.4417 data_time: 0.2846 memory: 3625 2022/09/06 02:38:14 - mmengine - INFO - Epoch(val) [100][60/78] eta: 0:00:11 time: 0.6492 data_time: 0.4911 memory: 3625 2022/09/06 02:38:23 - mmengine - INFO - Epoch(val) [100][78/78] acc/top1: 0.7415 acc/top5: 0.9066 acc/mean1: 0.7414