2022/09/05 08:44:23 - mmengine - INFO - Checkpoints will be saved to /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb by HardDiskBackend. 2022/09/05 08:44:48 - mmengine - INFO - Epoch(train) [1][20/940] lr: 1.0000e-02 eta: 1 day, 8:30:17 time: 1.2451 data_time: 0.5541 memory: 26167 grad_norm: 2.4337 top1_acc: 0.0312 top5_acc: 0.0938 loss_cls: 5.9304 loss: 5.9304 2022/09/05 08:45:03 - mmengine - INFO - Epoch(train) [1][40/940] lr: 1.0000e-02 eta: 1 day, 2:07:10 time: 0.7564 data_time: 0.2215 memory: 22701 grad_norm: 2.5839 top1_acc: 0.0625 top5_acc: 0.1875 loss_cls: 5.5070 loss: 5.5070 2022/09/05 08:45:20 - mmengine - INFO - Epoch(train) [1][60/940] lr: 1.0000e-02 eta: 1 day, 0:46:27 time: 0.8467 data_time: 0.2963 memory: 22701 grad_norm: 2.7838 top1_acc: 0.0938 top5_acc: 0.3438 loss_cls: 4.8941 loss: 4.8941 2022/09/05 08:45:35 - mmengine - INFO - Epoch(train) [1][80/940] lr: 1.0000e-02 eta: 23:18:55 time: 0.7265 data_time: 0.1165 memory: 22701 grad_norm: 2.9099 top1_acc: 0.1562 top5_acc: 0.5000 loss_cls: 4.5253 loss: 4.5253 2022/09/05 08:45:52 - mmengine - INFO - Epoch(train) [1][100/940] lr: 1.0000e-02 eta: 23:16:05 time: 0.8856 data_time: 0.1856 memory: 22701 grad_norm: 3.0073 top1_acc: 0.0938 top5_acc: 0.4062 loss_cls: 4.1822 loss: 4.1822 2022/09/05 08:46:08 - mmengine - INFO - Epoch(train) [1][120/940] lr: 1.0000e-02 eta: 22:45:23 time: 0.7755 data_time: 0.0305 memory: 22701 grad_norm: 3.1317 top1_acc: 0.2188 top5_acc: 0.5312 loss_cls: 3.9411 loss: 3.9411 2022/09/05 08:46:24 - mmengine - INFO - Epoch(train) [1][140/940] lr: 1.0000e-02 eta: 22:26:53 time: 0.7912 data_time: 0.0322 memory: 22701 grad_norm: 3.2345 top1_acc: 0.2188 top5_acc: 0.3438 loss_cls: 3.8097 loss: 3.8097 2022/09/05 08:46:37 - mmengine - INFO - Epoch(train) [1][160/940] lr: 1.0000e-02 eta: 21:50:15 time: 0.6751 data_time: 0.0247 memory: 22701 grad_norm: 3.3305 top1_acc: 0.1875 top5_acc: 0.4062 loss_cls: 3.7213 loss: 3.7213 2022/09/05 08:46:54 - mmengine - INFO - Epoch(train) [1][180/940] lr: 1.0000e-02 eta: 21:53:44 time: 0.8594 data_time: 0.0303 memory: 22701 grad_norm: 3.4031 top1_acc: 0.2812 top5_acc: 0.6875 loss_cls: 3.5835 loss: 3.5835 2022/09/05 08:47:09 - mmengine - INFO - Epoch(train) [1][200/940] lr: 1.0000e-02 eta: 21:33:42 time: 0.7138 data_time: 0.0231 memory: 22701 grad_norm: 3.4618 top1_acc: 0.1562 top5_acc: 0.3125 loss_cls: 3.5619 loss: 3.5619 2022/09/05 08:47:26 - mmengine - INFO - Epoch(train) [1][220/940] lr: 1.0000e-02 eta: 21:36:44 time: 0.8508 data_time: 0.0346 memory: 22701 grad_norm: 3.5147 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 3.3388 loss: 3.3388 2022/09/05 08:47:41 - mmengine - INFO - Epoch(train) [1][240/940] lr: 1.0000e-02 eta: 21:25:23 time: 0.7447 data_time: 0.0185 memory: 22701 grad_norm: 3.5985 top1_acc: 0.2500 top5_acc: 0.4062 loss_cls: 3.3371 loss: 3.3371 2022/09/05 08:48:01 - mmengine - INFO - Epoch(train) [1][260/940] lr: 1.0000e-02 eta: 21:46:14 time: 0.9983 data_time: 0.0298 memory: 22701 grad_norm: 3.6009 top1_acc: 0.2812 top5_acc: 0.6562 loss_cls: 3.0939 loss: 3.0939 2022/09/05 08:48:18 - mmengine - INFO - Epoch(train) [1][280/940] lr: 1.0000e-02 eta: 21:48:00 time: 0.8544 data_time: 0.0243 memory: 22701 grad_norm: 3.6954 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1172 loss: 3.1172 2022/09/05 08:48:39 - mmengine - INFO - Epoch(train) [1][300/940] lr: 1.0000e-02 eta: 22:10:23 time: 1.0551 data_time: 0.0238 memory: 22701 grad_norm: 3.7454 top1_acc: 0.2188 top5_acc: 0.5312 loss_cls: 3.2074 loss: 3.2074 2022/09/05 08:48:57 - mmengine - INFO - Epoch(train) [1][320/940] lr: 1.0000e-02 eta: 22:15:18 time: 0.9052 data_time: 0.0185 memory: 22701 grad_norm: 3.7964 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0126 loss: 3.0126 2022/09/05 08:49:20 - mmengine - INFO - Epoch(train) [1][340/940] lr: 1.0000e-02 eta: 22:41:57 time: 1.1485 data_time: 0.0467 memory: 22701 grad_norm: 3.7814 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 3.1196 loss: 3.1196 2022/09/05 08:49:38 - mmengine - INFO - Epoch(train) [1][360/940] lr: 1.0000e-02 eta: 22:42:23 time: 0.8810 data_time: 0.0460 memory: 22701 grad_norm: 3.9158 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 3.0131 loss: 3.0131 2022/09/05 08:49:57 - mmengine - INFO - Epoch(train) [1][380/940] lr: 1.0000e-02 eta: 22:50:31 time: 0.9754 data_time: 0.0332 memory: 22701 grad_norm: 3.9243 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0699 loss: 3.0699 2022/09/05 08:50:16 - mmengine - INFO - Epoch(train) [1][400/940] lr: 1.0000e-02 eta: 22:54:55 time: 0.9385 data_time: 0.2085 memory: 22701 grad_norm: 3.9079 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.9948 loss: 2.9948 2022/09/05 08:50:34 - mmengine - INFO - Epoch(train) [1][420/940] lr: 1.0000e-02 eta: 22:56:01 time: 0.9003 data_time: 0.0506 memory: 22701 grad_norm: 3.9575 top1_acc: 0.1562 top5_acc: 0.5312 loss_cls: 3.0888 loss: 3.0888 2022/09/05 08:50:49 - mmengine - INFO - Epoch(train) [1][440/940] lr: 1.0000e-02 eta: 22:48:36 time: 0.7818 data_time: 0.1923 memory: 22701 grad_norm: 3.9555 top1_acc: 0.2188 top5_acc: 0.4688 loss_cls: 3.0178 loss: 3.0178 2022/09/05 08:51:08 - mmengine - INFO - Epoch(train) [1][460/940] lr: 1.0000e-02 eta: 22:53:10 time: 0.9493 data_time: 0.0865 memory: 22701 grad_norm: 4.0078 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0399 loss: 3.0399 2022/09/05 08:51:24 - mmengine - INFO - Epoch(train) [1][480/940] lr: 1.0000e-02 eta: 22:45:17 time: 0.7639 data_time: 0.0696 memory: 22701 grad_norm: 3.9950 top1_acc: 0.2812 top5_acc: 0.6875 loss_cls: 2.7510 loss: 2.7510 2022/09/05 08:51:40 - mmengine - INFO - Epoch(train) [1][500/940] lr: 1.0000e-02 eta: 22:42:39 time: 0.8385 data_time: 0.1109 memory: 22701 grad_norm: 4.0147 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.7794 loss: 2.7794 2022/09/05 08:51:56 - mmengine - INFO - Epoch(train) [1][520/940] lr: 1.0000e-02 eta: 22:37:31 time: 0.7935 data_time: 0.2754 memory: 22701 grad_norm: 3.9972 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.7341 loss: 2.7341 2022/09/05 08:52:13 - mmengine - INFO - Epoch(train) [1][540/940] lr: 1.0000e-02 eta: 22:34:28 time: 0.8235 data_time: 0.1456 memory: 22701 grad_norm: 4.0910 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7608 loss: 2.7608 2022/09/05 08:52:29 - mmengine - INFO - Epoch(train) [1][560/940] lr: 1.0000e-02 eta: 22:31:29 time: 0.8211 data_time: 0.1775 memory: 22701 grad_norm: 4.0624 top1_acc: 0.2812 top5_acc: 0.5312 loss_cls: 2.7548 loss: 2.7548 2022/09/05 08:52:47 - mmengine - INFO - Epoch(train) [1][580/940] lr: 1.0000e-02 eta: 22:31:55 time: 0.8815 data_time: 0.1197 memory: 22701 grad_norm: 4.0577 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.7821 loss: 2.7821 2022/09/05 08:53:04 - mmengine - INFO - Epoch(train) [1][600/940] lr: 1.0000e-02 eta: 22:30:24 time: 0.8446 data_time: 0.2643 memory: 22701 grad_norm: 4.0916 top1_acc: 0.2812 top5_acc: 0.5938 loss_cls: 2.8549 loss: 2.8549 2022/09/05 08:53:19 - mmengine - INFO - Epoch(train) [1][620/940] lr: 1.0000e-02 eta: 22:23:39 time: 0.7387 data_time: 0.1163 memory: 22701 grad_norm: 4.0638 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.7387 loss: 2.7387 2022/09/05 08:53:36 - mmengine - INFO - Epoch(train) [1][640/940] lr: 1.0000e-02 eta: 22:24:00 time: 0.8765 data_time: 0.3067 memory: 22701 grad_norm: 4.1081 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 2.7443 loss: 2.7443 2022/09/05 08:53:50 - mmengine - INFO - Epoch(train) [1][660/940] lr: 1.0000e-02 eta: 22:16:01 time: 0.7005 data_time: 0.1589 memory: 22701 grad_norm: 4.0668 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.6286 loss: 2.6286 2022/09/05 08:54:07 - mmengine - INFO - Epoch(train) [1][680/940] lr: 1.0000e-02 eta: 22:15:53 time: 0.8622 data_time: 0.4044 memory: 22701 grad_norm: 4.1550 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.6857 loss: 2.6857 2022/09/05 08:54:26 - mmengine - INFO - Epoch(train) [1][700/940] lr: 1.0000e-02 eta: 22:19:06 time: 0.9376 data_time: 0.3294 memory: 22701 grad_norm: 4.1430 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.6601 loss: 2.6601 2022/09/05 08:54:42 - mmengine - INFO - Epoch(train) [1][720/940] lr: 1.0000e-02 eta: 22:15:05 time: 0.7750 data_time: 0.0864 memory: 22701 grad_norm: 4.0629 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.7025 loss: 2.7025 2022/09/05 08:55:01 - mmengine - INFO - Epoch(train) [1][740/940] lr: 1.0000e-02 eta: 22:20:03 time: 0.9835 data_time: 0.0951 memory: 22701 grad_norm: 4.1193 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6980 loss: 2.6980 2022/09/05 08:55:17 - mmengine - INFO - Epoch(train) [1][760/940] lr: 1.0000e-02 eta: 22:16:35 time: 0.7846 data_time: 0.0748 memory: 22701 grad_norm: 4.1730 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.7619 loss: 2.7619 2022/09/05 08:55:38 - mmengine - INFO - Epoch(train) [1][780/940] lr: 1.0000e-02 eta: 22:23:00 time: 1.0281 data_time: 0.0523 memory: 22701 grad_norm: 4.1778 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.7595 loss: 2.7595 2022/09/05 08:55:55 - mmengine - INFO - Epoch(train) [1][800/940] lr: 1.0000e-02 eta: 22:22:14 time: 0.8521 data_time: 0.0409 memory: 22701 grad_norm: 4.1493 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 2.6795 loss: 2.6795 2022/09/05 08:56:13 - mmengine - INFO - Epoch(train) [1][820/940] lr: 1.0000e-02 eta: 22:23:35 time: 0.9074 data_time: 0.0245 memory: 22701 grad_norm: 4.1265 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6399 loss: 2.6399 2022/09/05 08:56:28 - mmengine - INFO - Epoch(train) [1][840/940] lr: 1.0000e-02 eta: 22:18:49 time: 0.7442 data_time: 0.0260 memory: 22701 grad_norm: 4.2223 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8097 loss: 2.8097 2022/09/05 08:56:47 - mmengine - INFO - Epoch(train) [1][860/940] lr: 1.0000e-02 eta: 22:21:51 time: 0.9541 data_time: 0.0237 memory: 22701 grad_norm: 4.2012 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.5081 loss: 2.5081 2022/09/05 08:57:02 - mmengine - INFO - Epoch(train) [1][880/940] lr: 1.0000e-02 eta: 22:18:03 time: 0.7649 data_time: 0.0270 memory: 22701 grad_norm: 4.2428 top1_acc: 0.2812 top5_acc: 0.6562 loss_cls: 2.6095 loss: 2.6095 2022/09/05 08:57:21 - mmengine - INFO - Epoch(train) [1][900/940] lr: 1.0000e-02 eta: 22:20:54 time: 0.9532 data_time: 0.0247 memory: 22701 grad_norm: 4.2668 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 2.5970 loss: 2.5970 2022/09/05 08:57:39 - mmengine - INFO - Epoch(train) [1][920/940] lr: 1.0000e-02 eta: 22:22:26 time: 0.9184 data_time: 0.0305 memory: 22701 grad_norm: 4.2388 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 2.5801 loss: 2.5801 2022/09/05 08:58:02 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 08:58:02 - mmengine - INFO - Epoch(train) [1][940/940] lr: 1.0000e-02 eta: 22:30:15 time: 1.1109 data_time: 0.0194 memory: 22701 grad_norm: 4.4756 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 2.6352 loss: 2.6352 2022/09/05 08:58:57 - mmengine - INFO - Epoch(val) [1][20/78] eta: 0:02:40 time: 2.7650 data_time: 2.6584 memory: 2247 2022/09/05 08:59:16 - mmengine - INFO - Epoch(val) [1][40/78] eta: 0:00:35 time: 0.9290 data_time: 0.8218 memory: 2247 2022/09/05 08:59:31 - mmengine - INFO - Epoch(val) [1][60/78] eta: 0:00:13 time: 0.7684 data_time: 0.6627 memory: 2247 2022/09/05 08:59:49 - mmengine - INFO - Epoch(val) [1][78/78] acc/top1: 0.4758 acc/top5: 0.7465 acc/mean1: 0.4756 2022/09/05 08:59:50 - mmengine - INFO - The best checkpoint with 0.4758 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/09/05 09:00:09 - mmengine - INFO - Epoch(train) [2][20/940] lr: 1.0000e-02 eta: 22:33:37 time: 0.9839 data_time: 0.5554 memory: 22708 grad_norm: 4.1843 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6566 loss: 2.6566 2022/09/05 09:00:23 - mmengine - INFO - Epoch(train) [2][40/940] lr: 1.0000e-02 eta: 22:27:07 time: 0.6763 data_time: 0.2691 memory: 22701 grad_norm: 4.2237 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.5545 loss: 2.5545 2022/09/05 09:00:39 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:00:39 - mmengine - INFO - Epoch(train) [2][60/940] lr: 1.0000e-02 eta: 22:25:23 time: 0.8227 data_time: 0.2610 memory: 22701 grad_norm: 4.2067 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.6530 loss: 2.6530 2022/09/05 09:00:55 - mmengine - INFO - Epoch(train) [2][80/940] lr: 1.0000e-02 eta: 22:22:58 time: 0.7976 data_time: 0.2715 memory: 22701 grad_norm: 4.2219 top1_acc: 0.2500 top5_acc: 0.6562 loss_cls: 2.6842 loss: 2.6842 2022/09/05 09:01:14 - mmengine - INFO - Epoch(train) [2][100/940] lr: 1.0000e-02 eta: 22:24:11 time: 0.9176 data_time: 0.3091 memory: 22701 grad_norm: 4.2142 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.5291 loss: 2.5291 2022/09/05 09:01:30 - mmengine - INFO - Epoch(train) [2][120/940] lr: 1.0000e-02 eta: 22:21:47 time: 0.7949 data_time: 0.2725 memory: 22701 grad_norm: 4.2451 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 2.6570 loss: 2.6570 2022/09/05 09:01:49 - mmengine - INFO - Epoch(train) [2][140/940] lr: 1.0000e-02 eta: 22:24:54 time: 0.9849 data_time: 0.5436 memory: 22701 grad_norm: 4.3092 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4108 loss: 2.4108 2022/09/05 09:02:03 - mmengine - INFO - Epoch(train) [2][160/940] lr: 1.0000e-02 eta: 22:18:44 time: 0.6600 data_time: 0.2565 memory: 22701 grad_norm: 4.2837 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5284 loss: 2.5284 2022/09/05 09:02:19 - mmengine - INFO - Epoch(train) [2][180/940] lr: 1.0000e-02 eta: 22:17:19 time: 0.8240 data_time: 0.4191 memory: 22701 grad_norm: 4.3082 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.4844 loss: 2.4844 2022/09/05 09:02:32 - mmengine - INFO - Epoch(train) [2][200/940] lr: 1.0000e-02 eta: 22:11:45 time: 0.6690 data_time: 0.2594 memory: 22701 grad_norm: 4.3413 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5175 loss: 2.5175 2022/09/05 09:02:47 - mmengine - INFO - Epoch(train) [2][220/940] lr: 1.0000e-02 eta: 22:07:32 time: 0.7134 data_time: 0.3320 memory: 22701 grad_norm: 4.2963 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4413 loss: 2.4413 2022/09/05 09:03:00 - mmengine - INFO - Epoch(train) [2][240/940] lr: 1.0000e-02 eta: 22:02:08 time: 0.6630 data_time: 0.2297 memory: 22701 grad_norm: 4.2700 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.4260 loss: 2.4260 2022/09/05 09:03:17 - mmengine - INFO - Epoch(train) [2][260/940] lr: 1.0000e-02 eta: 22:01:40 time: 0.8474 data_time: 0.4346 memory: 22701 grad_norm: 4.2953 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.5586 loss: 2.5586 2022/09/05 09:03:30 - mmengine - INFO - Epoch(train) [2][280/940] lr: 1.0000e-02 eta: 21:56:38 time: 0.6673 data_time: 0.2336 memory: 22701 grad_norm: 4.2730 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.6666 loss: 2.6666 2022/09/05 09:03:48 - mmengine - INFO - Epoch(train) [2][300/940] lr: 1.0000e-02 eta: 21:56:53 time: 0.8729 data_time: 0.4548 memory: 22701 grad_norm: 4.3481 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.5104 loss: 2.5104 2022/09/05 09:04:03 - mmengine - INFO - Epoch(train) [2][320/940] lr: 1.0000e-02 eta: 21:54:38 time: 0.7720 data_time: 0.3872 memory: 22701 grad_norm: 4.3513 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4247 loss: 2.4247 2022/09/05 09:04:22 - mmengine - INFO - Epoch(train) [2][340/940] lr: 1.0000e-02 eta: 21:56:50 time: 0.9534 data_time: 0.5673 memory: 22701 grad_norm: 4.3993 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.4104 loss: 2.4104 2022/09/05 09:04:39 - mmengine - INFO - Epoch(train) [2][360/940] lr: 1.0000e-02 eta: 21:56:03 time: 0.8306 data_time: 0.4276 memory: 22701 grad_norm: 4.3832 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.4415 loss: 2.4415 2022/09/05 09:04:58 - mmengine - INFO - Epoch(train) [2][380/940] lr: 1.0000e-02 eta: 21:58:24 time: 0.9647 data_time: 0.5642 memory: 22701 grad_norm: 4.3053 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.5164 loss: 2.5164 2022/09/05 09:05:12 - mmengine - INFO - Epoch(train) [2][400/940] lr: 1.0000e-02 eta: 21:54:38 time: 0.7024 data_time: 0.2934 memory: 22701 grad_norm: 4.3117 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.3459 loss: 2.3459 2022/09/05 09:05:28 - mmengine - INFO - Epoch(train) [2][420/940] lr: 1.0000e-02 eta: 21:53:21 time: 0.8068 data_time: 0.4095 memory: 22701 grad_norm: 4.3646 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.4483 loss: 2.4483 2022/09/05 09:05:42 - mmengine - INFO - Epoch(train) [2][440/940] lr: 1.0000e-02 eta: 21:49:14 time: 0.6794 data_time: 0.2830 memory: 22701 grad_norm: 4.3239 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.4282 loss: 2.4282 2022/09/05 09:06:01 - mmengine - INFO - Epoch(train) [2][460/940] lr: 1.0000e-02 eta: 21:51:33 time: 0.9659 data_time: 0.5595 memory: 22701 grad_norm: 4.3812 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.4906 loss: 2.4906 2022/09/05 09:06:18 - mmengine - INFO - Epoch(train) [2][480/940] lr: 1.0000e-02 eta: 21:50:50 time: 0.8300 data_time: 0.4269 memory: 22701 grad_norm: 4.4261 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3743 loss: 2.3743 2022/09/05 09:06:35 - mmengine - INFO - Epoch(train) [2][500/940] lr: 1.0000e-02 eta: 21:50:42 time: 0.8566 data_time: 0.4634 memory: 22701 grad_norm: 4.3259 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.4387 loss: 2.4387 2022/09/05 09:06:51 - mmengine - INFO - Epoch(train) [2][520/940] lr: 1.0000e-02 eta: 21:49:12 time: 0.7924 data_time: 0.3978 memory: 22701 grad_norm: 4.3480 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.4064 loss: 2.4064 2022/09/05 09:07:14 - mmengine - INFO - Epoch(train) [2][540/940] lr: 1.0000e-02 eta: 21:55:00 time: 1.1404 data_time: 0.7356 memory: 22701 grad_norm: 4.3569 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.2573 loss: 2.2573 2022/09/05 09:07:34 - mmengine - INFO - Epoch(train) [2][560/940] lr: 1.0000e-02 eta: 21:57:46 time: 1.0010 data_time: 0.2375 memory: 22701 grad_norm: 4.3914 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5127 loss: 2.5127 2022/09/05 09:07:51 - mmengine - INFO - Epoch(train) [2][580/940] lr: 1.0000e-02 eta: 21:57:22 time: 0.8498 data_time: 0.0280 memory: 22701 grad_norm: 4.3550 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.3150 loss: 2.3150 2022/09/05 09:08:08 - mmengine - INFO - Epoch(train) [2][600/940] lr: 1.0000e-02 eta: 21:57:05 time: 0.8542 data_time: 0.0354 memory: 22701 grad_norm: 4.3998 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 2.4038 loss: 2.4038 2022/09/05 09:08:23 - mmengine - INFO - Epoch(train) [2][620/940] lr: 1.0000e-02 eta: 21:54:54 time: 0.7590 data_time: 0.0249 memory: 22701 grad_norm: 4.3824 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.2909 loss: 2.2909 2022/09/05 09:08:40 - mmengine - INFO - Epoch(train) [2][640/940] lr: 1.0000e-02 eta: 21:54:16 time: 0.8352 data_time: 0.0311 memory: 22701 grad_norm: 4.3102 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.5092 loss: 2.5092 2022/09/05 09:08:54 - mmengine - INFO - Epoch(train) [2][660/940] lr: 1.0000e-02 eta: 21:51:06 time: 0.7040 data_time: 0.0299 memory: 22701 grad_norm: 4.3384 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5733 loss: 2.5733 2022/09/05 09:09:13 - mmengine - INFO - Epoch(train) [2][680/940] lr: 1.0000e-02 eta: 21:53:29 time: 0.9916 data_time: 0.0275 memory: 22701 grad_norm: 4.4065 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.3877 loss: 2.3877 2022/09/05 09:09:28 - mmengine - INFO - Epoch(train) [2][700/940] lr: 1.0000e-02 eta: 21:50:43 time: 0.7206 data_time: 0.0268 memory: 22701 grad_norm: 4.3265 top1_acc: 0.4688 top5_acc: 0.5312 loss_cls: 2.4540 loss: 2.4540 2022/09/05 09:09:43 - mmengine - INFO - Epoch(train) [2][720/940] lr: 1.0000e-02 eta: 21:48:56 time: 0.7711 data_time: 0.0294 memory: 22701 grad_norm: 4.3198 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3809 loss: 2.3809 2022/09/05 09:09:56 - mmengine - INFO - Epoch(train) [2][740/940] lr: 1.0000e-02 eta: 21:44:42 time: 0.6347 data_time: 0.0318 memory: 22701 grad_norm: 4.4017 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.3711 loss: 2.3711 2022/09/05 09:10:14 - mmengine - INFO - Epoch(train) [2][760/940] lr: 1.0000e-02 eta: 21:45:08 time: 0.8878 data_time: 0.0382 memory: 22701 grad_norm: 4.4125 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.4241 loss: 2.4241 2022/09/05 09:10:28 - mmengine - INFO - Epoch(train) [2][780/940] lr: 1.0000e-02 eta: 21:42:51 time: 0.7363 data_time: 0.0299 memory: 22701 grad_norm: 4.4656 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4574 loss: 2.4574 2022/09/05 09:10:48 - mmengine - INFO - Epoch(train) [2][800/940] lr: 1.0000e-02 eta: 21:44:36 time: 0.9620 data_time: 0.0306 memory: 22701 grad_norm: 4.3947 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.4481 loss: 2.4481 2022/09/05 09:11:02 - mmengine - INFO - Epoch(train) [2][820/940] lr: 1.0000e-02 eta: 21:42:00 time: 0.7161 data_time: 0.0284 memory: 22701 grad_norm: 4.3235 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.3865 loss: 2.3865 2022/09/05 09:11:20 - mmengine - INFO - Epoch(train) [2][840/940] lr: 1.0000e-02 eta: 21:42:46 time: 0.9074 data_time: 0.1020 memory: 22701 grad_norm: 4.3187 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3890 loss: 2.3890 2022/09/05 09:11:40 - mmengine - INFO - Epoch(train) [2][860/940] lr: 1.0000e-02 eta: 21:44:52 time: 0.9875 data_time: 0.3412 memory: 22701 grad_norm: 4.3995 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.2581 loss: 2.2581 2022/09/05 09:11:56 - mmengine - INFO - Epoch(train) [2][880/940] lr: 1.0000e-02 eta: 21:43:47 time: 0.8015 data_time: 0.0429 memory: 22701 grad_norm: 4.3384 top1_acc: 0.3438 top5_acc: 0.5000 loss_cls: 2.3611 loss: 2.3611 2022/09/05 09:12:12 - mmengine - INFO - Epoch(train) [2][900/940] lr: 1.0000e-02 eta: 21:42:34 time: 0.7927 data_time: 0.1447 memory: 22701 grad_norm: 4.3372 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.5295 loss: 2.5295 2022/09/05 09:12:29 - mmengine - INFO - Epoch(train) [2][920/940] lr: 1.0000e-02 eta: 21:42:12 time: 0.8425 data_time: 0.0560 memory: 22701 grad_norm: 4.4117 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4122 loss: 2.4122 2022/09/05 09:12:42 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:12:42 - mmengine - INFO - Epoch(train) [2][940/940] lr: 1.0000e-02 eta: 21:38:36 time: 0.6456 data_time: 0.0251 memory: 22701 grad_norm: 4.6348 top1_acc: 0.1429 top5_acc: 0.5714 loss_cls: 2.4419 loss: 2.4419 2022/09/05 09:12:56 - mmengine - INFO - Epoch(val) [2][20/78] eta: 0:00:40 time: 0.6990 data_time: 0.5786 memory: 2247 2022/09/05 09:13:04 - mmengine - INFO - Epoch(val) [2][40/78] eta: 0:00:16 time: 0.4367 data_time: 0.3199 memory: 2247 2022/09/05 09:13:17 - mmengine - INFO - Epoch(val) [2][60/78] eta: 0:00:11 time: 0.6544 data_time: 0.5377 memory: 2247 2022/09/05 09:13:28 - mmengine - INFO - Epoch(val) [2][78/78] acc/top1: 0.5091 acc/top5: 0.7748 acc/mean1: 0.5089 2022/09/05 09:13:28 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_2.pth is removed 2022/09/05 09:13:28 - mmengine - INFO - The best checkpoint with 0.5091 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/09/05 09:13:48 - mmengine - INFO - Epoch(train) [3][20/940] lr: 1.0000e-02 eta: 21:40:06 time: 0.9558 data_time: 0.3894 memory: 22701 grad_norm: 4.4207 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.2181 loss: 2.2181 2022/09/05 09:14:01 - mmengine - INFO - Epoch(train) [3][40/940] lr: 1.0000e-02 eta: 21:36:44 time: 0.6545 data_time: 0.1287 memory: 22701 grad_norm: 4.3526 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.3692 loss: 2.3692 2022/09/05 09:14:16 - mmengine - INFO - Epoch(train) [3][60/940] lr: 1.0000e-02 eta: 21:35:04 time: 0.7571 data_time: 0.2228 memory: 22701 grad_norm: 4.3741 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0389 loss: 2.0389 2022/09/05 09:14:30 - mmengine - INFO - Epoch(train) [3][80/940] lr: 1.0000e-02 eta: 21:32:30 time: 0.6978 data_time: 0.1240 memory: 22701 grad_norm: 4.4186 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 2.4808 loss: 2.4808 2022/09/05 09:14:48 - mmengine - INFO - Epoch(train) [3][100/940] lr: 1.0000e-02 eta: 21:33:29 time: 0.9246 data_time: 0.2155 memory: 22701 grad_norm: 4.3700 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2427 loss: 2.2427 2022/09/05 09:15:03 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:15:03 - mmengine - INFO - Epoch(train) [3][120/940] lr: 1.0000e-02 eta: 21:31:38 time: 0.7404 data_time: 0.1538 memory: 22701 grad_norm: 4.3141 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.1836 loss: 2.1836 2022/09/05 09:15:24 - mmengine - INFO - Epoch(train) [3][140/940] lr: 1.0000e-02 eta: 21:34:11 time: 1.0296 data_time: 0.4493 memory: 22701 grad_norm: 4.4222 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4033 loss: 2.4033 2022/09/05 09:15:38 - mmengine - INFO - Epoch(train) [3][160/940] lr: 1.0000e-02 eta: 21:32:13 time: 0.7318 data_time: 0.3478 memory: 22701 grad_norm: 4.4463 top1_acc: 0.3438 top5_acc: 0.5000 loss_cls: 2.5700 loss: 2.5700 2022/09/05 09:15:56 - mmengine - INFO - Epoch(train) [3][180/940] lr: 1.0000e-02 eta: 21:32:17 time: 0.8659 data_time: 0.4806 memory: 22701 grad_norm: 4.3437 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.3556 loss: 2.3556 2022/09/05 09:16:09 - mmengine - INFO - Epoch(train) [3][200/940] lr: 1.0000e-02 eta: 21:29:27 time: 0.6705 data_time: 0.2673 memory: 22701 grad_norm: 4.4081 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.3579 loss: 2.3579 2022/09/05 09:16:26 - mmengine - INFO - Epoch(train) [3][220/940] lr: 1.0000e-02 eta: 21:29:00 time: 0.8303 data_time: 0.4391 memory: 22701 grad_norm: 4.4078 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.3154 loss: 2.3154 2022/09/05 09:16:40 - mmengine - INFO - Epoch(train) [3][240/940] lr: 1.0000e-02 eta: 21:26:34 time: 0.6922 data_time: 0.2532 memory: 22701 grad_norm: 4.4391 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.4155 loss: 2.4155 2022/09/05 09:16:57 - mmengine - INFO - Epoch(train) [3][260/940] lr: 1.0000e-02 eta: 21:27:05 time: 0.8954 data_time: 0.3660 memory: 22701 grad_norm: 4.3666 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2124 loss: 2.2124 2022/09/05 09:17:11 - mmengine - INFO - Epoch(train) [3][280/940] lr: 1.0000e-02 eta: 21:24:37 time: 0.6873 data_time: 0.2920 memory: 22701 grad_norm: 4.4010 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.3852 loss: 2.3852 2022/09/05 09:17:28 - mmengine - INFO - Epoch(train) [3][300/940] lr: 1.0000e-02 eta: 21:24:17 time: 0.8347 data_time: 0.2614 memory: 22701 grad_norm: 4.4404 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.3900 loss: 2.3900 2022/09/05 09:17:47 - mmengine - INFO - Epoch(train) [3][320/940] lr: 1.0000e-02 eta: 21:25:57 time: 0.9797 data_time: 0.2163 memory: 22701 grad_norm: 4.4749 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0870 loss: 2.0870 2022/09/05 09:18:10 - mmengine - INFO - Epoch(train) [3][340/940] lr: 1.0000e-02 eta: 21:29:45 time: 1.1369 data_time: 0.7355 memory: 22701 grad_norm: 4.4876 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1791 loss: 2.1791 2022/09/05 09:18:28 - mmengine - INFO - Epoch(train) [3][360/940] lr: 1.0000e-02 eta: 21:29:53 time: 0.8727 data_time: 0.4843 memory: 22701 grad_norm: 4.4704 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2780 loss: 2.2780 2022/09/05 09:18:51 - mmengine - INFO - Epoch(train) [3][380/940] lr: 1.0000e-02 eta: 21:33:37 time: 1.1403 data_time: 0.7411 memory: 22701 grad_norm: 4.3525 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.2842 loss: 2.2842 2022/09/05 09:19:07 - mmengine - INFO - Epoch(train) [3][400/940] lr: 1.0000e-02 eta: 21:33:02 time: 0.8240 data_time: 0.4294 memory: 22701 grad_norm: 4.4489 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2692 loss: 2.2692 2022/09/05 09:19:29 - mmengine - INFO - Epoch(train) [3][420/940] lr: 1.0000e-02 eta: 21:35:46 time: 1.0728 data_time: 0.6642 memory: 22701 grad_norm: 4.4268 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.4572 loss: 2.4572 2022/09/05 09:19:46 - mmengine - INFO - Epoch(train) [3][440/940] lr: 1.0000e-02 eta: 21:36:05 time: 0.8936 data_time: 0.4642 memory: 22701 grad_norm: 4.4773 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2376 loss: 2.2376 2022/09/05 09:20:02 - mmengine - INFO - Epoch(train) [3][460/940] lr: 1.0000e-02 eta: 21:35:02 time: 0.7886 data_time: 0.2407 memory: 22701 grad_norm: 4.4886 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2172 loss: 2.2172 2022/09/05 09:20:15 - mmengine - INFO - Epoch(train) [3][480/940] lr: 1.0000e-02 eta: 21:32:13 time: 0.6520 data_time: 0.2237 memory: 22701 grad_norm: 4.4160 top1_acc: 0.2812 top5_acc: 0.5312 loss_cls: 2.2336 loss: 2.2336 2022/09/05 09:20:32 - mmengine - INFO - Epoch(train) [3][500/940] lr: 1.0000e-02 eta: 21:31:41 time: 0.8271 data_time: 0.2736 memory: 22701 grad_norm: 4.4933 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.1905 loss: 2.1905 2022/09/05 09:20:46 - mmengine - INFO - Epoch(train) [3][520/940] lr: 1.0000e-02 eta: 21:29:34 time: 0.7020 data_time: 0.0661 memory: 22701 grad_norm: 4.3117 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.3121 loss: 2.3121 2022/09/05 09:21:01 - mmengine - INFO - Epoch(train) [3][540/940] lr: 1.0000e-02 eta: 21:28:01 time: 0.7435 data_time: 0.1969 memory: 22701 grad_norm: 4.4693 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.2669 loss: 2.2669 2022/09/05 09:21:15 - mmengine - INFO - Epoch(train) [3][560/940] lr: 1.0000e-02 eta: 21:26:17 time: 0.7280 data_time: 0.1704 memory: 22701 grad_norm: 4.4940 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.3419 loss: 2.3419 2022/09/05 09:21:33 - mmengine - INFO - Epoch(train) [3][580/940] lr: 1.0000e-02 eta: 21:26:38 time: 0.8936 data_time: 0.2749 memory: 22701 grad_norm: 4.4607 top1_acc: 0.3125 top5_acc: 0.6562 loss_cls: 2.1967 loss: 2.1967 2022/09/05 09:21:50 - mmengine - INFO - Epoch(train) [3][600/940] lr: 1.0000e-02 eta: 21:26:30 time: 0.8555 data_time: 0.1977 memory: 22701 grad_norm: 4.4235 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3038 loss: 2.3038 2022/09/05 09:22:07 - mmengine - INFO - Epoch(train) [3][620/940] lr: 1.0000e-02 eta: 21:26:13 time: 0.8426 data_time: 0.1725 memory: 22701 grad_norm: 4.4389 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.2902 loss: 2.2902 2022/09/05 09:22:22 - mmengine - INFO - Epoch(train) [3][640/940] lr: 1.0000e-02 eta: 21:25:04 time: 0.7719 data_time: 0.3325 memory: 22701 grad_norm: 4.4132 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.2857 loss: 2.2857 2022/09/05 09:22:41 - mmengine - INFO - Epoch(train) [3][660/940] lr: 1.0000e-02 eta: 21:25:43 time: 0.9212 data_time: 0.5255 memory: 22701 grad_norm: 4.4413 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2214 loss: 2.2214 2022/09/05 09:22:54 - mmengine - INFO - Epoch(train) [3][680/940] lr: 1.0000e-02 eta: 21:23:03 time: 0.6420 data_time: 0.2411 memory: 22701 grad_norm: 4.4639 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.2837 loss: 2.2837 2022/09/05 09:23:09 - mmengine - INFO - Epoch(train) [3][700/940] lr: 1.0000e-02 eta: 21:21:42 time: 0.7516 data_time: 0.3550 memory: 22701 grad_norm: 4.5022 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.3022 loss: 2.3022 2022/09/05 09:23:23 - mmengine - INFO - Epoch(train) [3][720/940] lr: 1.0000e-02 eta: 21:19:45 time: 0.6990 data_time: 0.3008 memory: 22701 grad_norm: 4.4277 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1712 loss: 2.1712 2022/09/05 09:23:39 - mmengine - INFO - Epoch(train) [3][740/940] lr: 1.0000e-02 eta: 21:19:24 time: 0.8345 data_time: 0.4323 memory: 22701 grad_norm: 4.4128 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3785 loss: 2.3785 2022/09/05 09:23:53 - mmengine - INFO - Epoch(train) [3][760/940] lr: 1.0000e-02 eta: 21:17:27 time: 0.6954 data_time: 0.2864 memory: 22701 grad_norm: 4.5239 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4614 loss: 2.4614 2022/09/05 09:24:10 - mmengine - INFO - Epoch(train) [3][780/940] lr: 1.0000e-02 eta: 21:17:27 time: 0.8627 data_time: 0.4406 memory: 22701 grad_norm: 4.4581 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2107 loss: 2.2107 2022/09/05 09:24:25 - mmengine - INFO - Epoch(train) [3][800/940] lr: 1.0000e-02 eta: 21:16:08 time: 0.7486 data_time: 0.3327 memory: 22701 grad_norm: 4.4195 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.1887 loss: 2.1887 2022/09/05 09:24:45 - mmengine - INFO - Epoch(train) [3][820/940] lr: 1.0000e-02 eta: 21:17:29 time: 0.9829 data_time: 0.5736 memory: 22701 grad_norm: 4.5435 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.2951 loss: 2.2951 2022/09/05 09:24:59 - mmengine - INFO - Epoch(train) [3][840/940] lr: 1.0000e-02 eta: 21:15:40 time: 0.7021 data_time: 0.3081 memory: 22701 grad_norm: 4.4801 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.2035 loss: 2.2035 2022/09/05 09:25:19 - mmengine - INFO - Epoch(train) [3][860/940] lr: 1.0000e-02 eta: 21:16:52 time: 0.9716 data_time: 0.3196 memory: 22701 grad_norm: 4.5325 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2994 loss: 2.2994 2022/09/05 09:25:35 - mmengine - INFO - Epoch(train) [3][880/940] lr: 1.0000e-02 eta: 21:16:04 time: 0.7916 data_time: 0.0258 memory: 22701 grad_norm: 4.4219 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.3261 loss: 2.3261 2022/09/05 09:25:48 - mmengine - INFO - Epoch(train) [3][900/940] lr: 1.0000e-02 eta: 21:14:06 time: 0.6850 data_time: 0.0647 memory: 22701 grad_norm: 4.4772 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.1909 loss: 2.1909 2022/09/05 09:26:04 - mmengine - INFO - Epoch(train) [3][920/940] lr: 1.0000e-02 eta: 21:13:05 time: 0.7706 data_time: 0.0408 memory: 22701 grad_norm: 4.4956 top1_acc: 0.2812 top5_acc: 0.5938 loss_cls: 2.2400 loss: 2.2400 2022/09/05 09:26:18 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:26:18 - mmengine - INFO - Epoch(train) [3][940/940] lr: 1.0000e-02 eta: 21:11:21 time: 0.7018 data_time: 0.2057 memory: 22701 grad_norm: 4.7168 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 2.3716 loss: 2.3716 2022/09/05 09:26:18 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/09/05 09:26:33 - mmengine - INFO - Epoch(val) [3][20/78] eta: 0:00:39 time: 0.6867 data_time: 0.5714 memory: 2247 2022/09/05 09:26:42 - mmengine - INFO - Epoch(val) [3][40/78] eta: 0:00:17 time: 0.4726 data_time: 0.3563 memory: 2247 2022/09/05 09:26:55 - mmengine - INFO - Epoch(val) [3][60/78] eta: 0:00:11 time: 0.6431 data_time: 0.5267 memory: 2247 2022/09/05 09:27:05 - mmengine - INFO - Epoch(val) [3][78/78] acc/top1: 0.5530 acc/top5: 0.8025 acc/mean1: 0.5529 2022/09/05 09:27:05 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_3.pth is removed 2022/09/05 09:27:06 - mmengine - INFO - The best checkpoint with 0.5530 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/09/05 09:27:25 - mmengine - INFO - Epoch(train) [4][20/940] lr: 1.0000e-02 eta: 21:12:33 time: 0.9757 data_time: 0.4937 memory: 22701 grad_norm: 4.4631 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1620 loss: 2.1620 2022/09/05 09:27:39 - mmengine - INFO - Epoch(train) [4][40/940] lr: 1.0000e-02 eta: 21:10:40 time: 0.6866 data_time: 0.1851 memory: 22701 grad_norm: 4.4457 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2301 loss: 2.2301 2022/09/05 09:27:57 - mmengine - INFO - Epoch(train) [4][60/940] lr: 1.0000e-02 eta: 21:10:59 time: 0.8917 data_time: 0.3309 memory: 22701 grad_norm: 4.4054 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3815 loss: 2.3815 2022/09/05 09:28:11 - mmengine - INFO - Epoch(train) [4][80/940] lr: 1.0000e-02 eta: 21:09:34 time: 0.7291 data_time: 0.1251 memory: 22701 grad_norm: 4.4583 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.3050 loss: 2.3050 2022/09/05 09:28:29 - mmengine - INFO - Epoch(train) [4][100/940] lr: 1.0000e-02 eta: 21:09:59 time: 0.9033 data_time: 0.1006 memory: 22701 grad_norm: 4.4043 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3114 loss: 2.3114 2022/09/05 09:28:43 - mmengine - INFO - Epoch(train) [4][120/940] lr: 1.0000e-02 eta: 21:07:59 time: 0.6703 data_time: 0.0320 memory: 22701 grad_norm: 4.3673 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2740 loss: 2.2740 2022/09/05 09:28:59 - mmengine - INFO - Epoch(train) [4][140/940] lr: 1.0000e-02 eta: 21:07:37 time: 0.8263 data_time: 0.0277 memory: 22701 grad_norm: 4.4503 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.1671 loss: 2.1671 2022/09/05 09:29:12 - mmengine - INFO - Epoch(train) [4][160/940] lr: 1.0000e-02 eta: 21:05:04 time: 0.6122 data_time: 0.0302 memory: 22701 grad_norm: 4.4911 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.2716 loss: 2.2716 2022/09/05 09:29:27 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:29:27 - mmengine - INFO - Epoch(train) [4][180/940] lr: 1.0000e-02 eta: 21:04:09 time: 0.7710 data_time: 0.0557 memory: 22701 grad_norm: 4.4048 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.1317 loss: 2.1317 2022/09/05 09:29:40 - mmengine - INFO - Epoch(train) [4][200/940] lr: 1.0000e-02 eta: 21:02:11 time: 0.6648 data_time: 0.0497 memory: 22701 grad_norm: 4.4491 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.1686 loss: 2.1686 2022/09/05 09:29:57 - mmengine - INFO - Epoch(train) [4][220/940] lr: 1.0000e-02 eta: 21:01:49 time: 0.8237 data_time: 0.0934 memory: 22701 grad_norm: 4.3973 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.1986 loss: 2.1986 2022/09/05 09:30:10 - mmengine - INFO - Epoch(train) [4][240/940] lr: 1.0000e-02 eta: 21:00:02 time: 0.6800 data_time: 0.0500 memory: 22701 grad_norm: 4.4211 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.2125 loss: 2.2125 2022/09/05 09:30:27 - mmengine - INFO - Epoch(train) [4][260/940] lr: 1.0000e-02 eta: 20:59:58 time: 0.8539 data_time: 0.1785 memory: 22701 grad_norm: 4.4104 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.1815 loss: 2.1815 2022/09/05 09:30:42 - mmengine - INFO - Epoch(train) [4][280/940] lr: 1.0000e-02 eta: 20:58:36 time: 0.7185 data_time: 0.0493 memory: 22701 grad_norm: 4.3761 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.2876 loss: 2.2876 2022/09/05 09:30:59 - mmengine - INFO - Epoch(train) [4][300/940] lr: 1.0000e-02 eta: 20:58:41 time: 0.8692 data_time: 0.0917 memory: 22701 grad_norm: 4.5063 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0617 loss: 2.0617 2022/09/05 09:31:15 - mmengine - INFO - Epoch(train) [4][320/940] lr: 1.0000e-02 eta: 20:57:58 time: 0.7851 data_time: 0.0935 memory: 22701 grad_norm: 4.4663 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.0817 loss: 2.0817 2022/09/05 09:31:34 - mmengine - INFO - Epoch(train) [4][340/940] lr: 1.0000e-02 eta: 20:58:50 time: 0.9492 data_time: 0.0242 memory: 22701 grad_norm: 4.5161 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.4340 loss: 2.4340 2022/09/05 09:31:47 - mmengine - INFO - Epoch(train) [4][360/940] lr: 1.0000e-02 eta: 20:57:03 time: 0.6742 data_time: 0.0262 memory: 22701 grad_norm: 4.5618 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.1836 loss: 2.1836 2022/09/05 09:32:03 - mmengine - INFO - Epoch(train) [4][380/940] lr: 1.0000e-02 eta: 20:56:27 time: 0.7952 data_time: 0.0263 memory: 22701 grad_norm: 4.3991 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1806 loss: 2.1806 2022/09/05 09:32:17 - mmengine - INFO - Epoch(train) [4][400/940] lr: 1.0000e-02 eta: 20:54:42 time: 0.6747 data_time: 0.0292 memory: 22701 grad_norm: 4.4434 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1803 loss: 2.1803 2022/09/05 09:32:33 - mmengine - INFO - Epoch(train) [4][420/940] lr: 1.0000e-02 eta: 20:54:23 time: 0.8253 data_time: 0.0242 memory: 22701 grad_norm: 4.4926 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0355 loss: 2.0355 2022/09/05 09:32:49 - mmengine - INFO - Epoch(train) [4][440/940] lr: 1.0000e-02 eta: 20:53:53 time: 0.8037 data_time: 0.0309 memory: 22701 grad_norm: 4.4469 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0647 loss: 2.0647 2022/09/05 09:33:09 - mmengine - INFO - Epoch(train) [4][460/940] lr: 1.0000e-02 eta: 20:54:58 time: 0.9772 data_time: 0.0222 memory: 22701 grad_norm: 4.4534 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.3464 loss: 2.3464 2022/09/05 09:33:24 - mmengine - INFO - Epoch(train) [4][480/940] lr: 1.0000e-02 eta: 20:53:55 time: 0.7458 data_time: 0.0486 memory: 22701 grad_norm: 4.4826 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2662 loss: 2.2662 2022/09/05 09:33:45 - mmengine - INFO - Epoch(train) [4][500/940] lr: 1.0000e-02 eta: 20:55:42 time: 1.0550 data_time: 0.0740 memory: 22701 grad_norm: 4.5416 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 2.2639 loss: 2.2639 2022/09/05 09:34:02 - mmengine - INFO - Epoch(train) [4][520/940] lr: 1.0000e-02 eta: 20:55:51 time: 0.8784 data_time: 0.0548 memory: 22701 grad_norm: 4.3972 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2451 loss: 2.2451 2022/09/05 09:34:23 - mmengine - INFO - Epoch(train) [4][540/940] lr: 1.0000e-02 eta: 20:57:30 time: 1.0459 data_time: 0.0200 memory: 22701 grad_norm: 4.5027 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.2825 loss: 2.2825 2022/09/05 09:34:42 - mmengine - INFO - Epoch(train) [4][560/940] lr: 1.0000e-02 eta: 20:57:58 time: 0.9162 data_time: 0.0225 memory: 22701 grad_norm: 4.4281 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1444 loss: 2.1444 2022/09/05 09:35:03 - mmengine - INFO - Epoch(train) [4][580/940] lr: 1.0000e-02 eta: 20:59:34 time: 1.0444 data_time: 0.0225 memory: 22701 grad_norm: 4.5667 top1_acc: 0.2812 top5_acc: 0.7188 loss_cls: 2.3513 loss: 2.3513 2022/09/05 09:35:18 - mmengine - INFO - Epoch(train) [4][600/940] lr: 1.0000e-02 eta: 20:58:46 time: 0.7739 data_time: 0.0247 memory: 22701 grad_norm: 4.5352 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.2854 loss: 2.2854 2022/09/05 09:35:36 - mmengine - INFO - Epoch(train) [4][620/940] lr: 1.0000e-02 eta: 20:59:04 time: 0.9005 data_time: 0.0227 memory: 22701 grad_norm: 4.5426 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0154 loss: 2.0154 2022/09/05 09:35:51 - mmengine - INFO - Epoch(train) [4][640/940] lr: 1.0000e-02 eta: 20:57:49 time: 0.7225 data_time: 0.0265 memory: 22701 grad_norm: 4.4966 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0473 loss: 2.0473 2022/09/05 09:36:06 - mmengine - INFO - Epoch(train) [4][660/940] lr: 1.0000e-02 eta: 20:56:56 time: 0.7639 data_time: 0.0303 memory: 22701 grad_norm: 4.4274 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1616 loss: 2.1616 2022/09/05 09:36:20 - mmengine - INFO - Epoch(train) [4][680/940] lr: 1.0000e-02 eta: 20:55:27 time: 0.6936 data_time: 0.0331 memory: 22701 grad_norm: 4.4584 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1425 loss: 2.1425 2022/09/05 09:36:38 - mmengine - INFO - Epoch(train) [4][700/940] lr: 1.0000e-02 eta: 20:55:58 time: 0.9245 data_time: 0.0250 memory: 22701 grad_norm: 4.4852 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.1065 loss: 2.1065 2022/09/05 09:36:52 - mmengine - INFO - Epoch(train) [4][720/940] lr: 1.0000e-02 eta: 20:54:41 time: 0.7148 data_time: 0.0302 memory: 22701 grad_norm: 4.4574 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2065 loss: 2.2065 2022/09/05 09:37:10 - mmengine - INFO - Epoch(train) [4][740/940] lr: 1.0000e-02 eta: 20:54:41 time: 0.8656 data_time: 0.0239 memory: 22701 grad_norm: 4.5043 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.1983 loss: 2.1983 2022/09/05 09:37:25 - mmengine - INFO - Epoch(train) [4][760/940] lr: 1.0000e-02 eta: 20:53:50 time: 0.7630 data_time: 0.0261 memory: 22701 grad_norm: 4.4930 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2480 loss: 2.2480 2022/09/05 09:37:42 - mmengine - INFO - Epoch(train) [4][780/940] lr: 1.0000e-02 eta: 20:53:41 time: 0.8474 data_time: 0.0258 memory: 22701 grad_norm: 4.5202 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1825 loss: 2.1825 2022/09/05 09:37:55 - mmengine - INFO - Epoch(train) [4][800/940] lr: 1.0000e-02 eta: 20:51:59 time: 0.6611 data_time: 0.0311 memory: 22701 grad_norm: 4.5579 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.1703 loss: 2.1703 2022/09/05 09:38:12 - mmengine - INFO - Epoch(train) [4][820/940] lr: 1.0000e-02 eta: 20:51:34 time: 0.8156 data_time: 0.0231 memory: 22701 grad_norm: 4.5018 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 2.2372 loss: 2.2372 2022/09/05 09:38:27 - mmengine - INFO - Epoch(train) [4][840/940] lr: 1.0000e-02 eta: 20:50:54 time: 0.7824 data_time: 0.0470 memory: 22701 grad_norm: 4.4757 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1344 loss: 2.1344 2022/09/05 09:38:43 - mmengine - INFO - Epoch(train) [4][860/940] lr: 1.0000e-02 eta: 20:50:18 time: 0.7918 data_time: 0.0256 memory: 22701 grad_norm: 4.5074 top1_acc: 0.3750 top5_acc: 0.4688 loss_cls: 2.3477 loss: 2.3477 2022/09/05 09:38:56 - mmengine - INFO - Epoch(train) [4][880/940] lr: 1.0000e-02 eta: 20:48:23 time: 0.6296 data_time: 0.0359 memory: 22701 grad_norm: 4.5269 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.0100 loss: 2.0100 2022/09/05 09:39:12 - mmengine - INFO - Epoch(train) [4][900/940] lr: 1.0000e-02 eta: 20:47:59 time: 0.8137 data_time: 0.0391 memory: 22701 grad_norm: 4.4592 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.2677 loss: 2.2677 2022/09/05 09:39:27 - mmengine - INFO - Epoch(train) [4][920/940] lr: 1.0000e-02 eta: 20:46:55 time: 0.7320 data_time: 0.0236 memory: 22701 grad_norm: 4.4557 top1_acc: 0.2812 top5_acc: 0.5938 loss_cls: 2.1882 loss: 2.1882 2022/09/05 09:39:43 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:39:43 - mmengine - INFO - Epoch(train) [4][940/940] lr: 1.0000e-02 eta: 20:46:38 time: 0.8262 data_time: 0.0181 memory: 22701 grad_norm: 4.7291 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 2.0911 loss: 2.0911 2022/09/05 09:39:57 - mmengine - INFO - Epoch(val) [4][20/78] eta: 0:00:40 time: 0.6942 data_time: 0.5731 memory: 2247 2022/09/05 09:40:06 - mmengine - INFO - Epoch(val) [4][40/78] eta: 0:00:17 time: 0.4499 data_time: 0.3343 memory: 2247 2022/09/05 09:40:19 - mmengine - INFO - Epoch(val) [4][60/78] eta: 0:00:11 time: 0.6460 data_time: 0.5291 memory: 2247 2022/09/05 09:40:29 - mmengine - INFO - Epoch(val) [4][78/78] acc/top1: 0.5740 acc/top5: 0.8151 acc/mean1: 0.5738 2022/09/05 09:40:29 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_4.pth is removed 2022/09/05 09:40:30 - mmengine - INFO - The best checkpoint with 0.5740 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/09/05 09:40:49 - mmengine - INFO - Epoch(train) [5][20/940] lr: 1.0000e-02 eta: 20:47:14 time: 0.9402 data_time: 0.5668 memory: 22701 grad_norm: 4.4603 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0202 loss: 2.0202 2022/09/05 09:41:02 - mmengine - INFO - Epoch(train) [5][40/940] lr: 1.0000e-02 eta: 20:45:39 time: 0.6630 data_time: 0.2858 memory: 22701 grad_norm: 4.4519 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2632 loss: 2.2632 2022/09/05 09:41:18 - mmengine - INFO - Epoch(train) [5][60/940] lr: 1.0000e-02 eta: 20:45:00 time: 0.7823 data_time: 0.3978 memory: 22701 grad_norm: 4.4397 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1029 loss: 2.1029 2022/09/05 09:41:32 - mmengine - INFO - Epoch(train) [5][80/940] lr: 1.0000e-02 eta: 20:43:44 time: 0.7008 data_time: 0.2687 memory: 22701 grad_norm: 4.4514 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9976 loss: 1.9976 2022/09/05 09:41:49 - mmengine - INFO - Epoch(train) [5][100/940] lr: 1.0000e-02 eta: 20:43:41 time: 0.8576 data_time: 0.4721 memory: 22701 grad_norm: 4.5020 top1_acc: 0.5000 top5_acc: 0.5938 loss_cls: 2.1791 loss: 2.1791 2022/09/05 09:42:03 - mmengine - INFO - Epoch(train) [5][120/940] lr: 1.0000e-02 eta: 20:42:19 time: 0.6858 data_time: 0.2905 memory: 22701 grad_norm: 4.4362 top1_acc: 0.4688 top5_acc: 0.5625 loss_cls: 2.2693 loss: 2.2693 2022/09/05 09:42:21 - mmengine - INFO - Epoch(train) [5][140/940] lr: 1.0000e-02 eta: 20:42:37 time: 0.9025 data_time: 0.5216 memory: 22701 grad_norm: 4.4986 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 2.0423 loss: 2.0423 2022/09/05 09:42:35 - mmengine - INFO - Epoch(train) [5][160/940] lr: 1.0000e-02 eta: 20:41:25 time: 0.7071 data_time: 0.3257 memory: 22701 grad_norm: 4.4255 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.2560 loss: 2.2560 2022/09/05 09:42:54 - mmengine - INFO - Epoch(train) [5][180/940] lr: 1.0000e-02 eta: 20:42:05 time: 0.9508 data_time: 0.5733 memory: 22701 grad_norm: 4.5099 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0735 loss: 2.0735 2022/09/05 09:43:14 - mmengine - INFO - Epoch(train) [5][200/940] lr: 1.0000e-02 eta: 20:43:01 time: 0.9864 data_time: 0.5442 memory: 22701 grad_norm: 4.4939 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.1395 loss: 2.1395 2022/09/05 09:43:34 - mmengine - INFO - Epoch(train) [5][220/940] lr: 1.0000e-02 eta: 20:43:56 time: 0.9878 data_time: 0.4979 memory: 22701 grad_norm: 4.4665 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.1380 loss: 2.1380 2022/09/05 09:43:51 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:43:51 - mmengine - INFO - Epoch(train) [5][240/940] lr: 1.0000e-02 eta: 20:44:00 time: 0.8747 data_time: 0.2666 memory: 22701 grad_norm: 4.5051 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0702 loss: 2.0702 2022/09/05 09:44:08 - mmengine - INFO - Epoch(train) [5][260/940] lr: 1.0000e-02 eta: 20:43:59 time: 0.8637 data_time: 0.3920 memory: 22701 grad_norm: 4.4968 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9551 loss: 1.9551 2022/09/05 09:44:22 - mmengine - INFO - Epoch(train) [5][280/940] lr: 1.0000e-02 eta: 20:42:27 time: 0.6609 data_time: 0.2559 memory: 22701 grad_norm: 4.4562 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.0777 loss: 2.0777 2022/09/05 09:44:37 - mmengine - INFO - Epoch(train) [5][300/940] lr: 1.0000e-02 eta: 20:41:40 time: 0.7597 data_time: 0.3507 memory: 22701 grad_norm: 4.4966 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0689 loss: 2.0689 2022/09/05 09:44:51 - mmengine - INFO - Epoch(train) [5][320/940] lr: 1.0000e-02 eta: 20:40:42 time: 0.7343 data_time: 0.3291 memory: 22701 grad_norm: 4.4731 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9959 loss: 1.9959 2022/09/05 09:45:07 - mmengine - INFO - Epoch(train) [5][340/940] lr: 1.0000e-02 eta: 20:40:10 time: 0.7930 data_time: 0.3960 memory: 22701 grad_norm: 4.5988 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9933 loss: 1.9933 2022/09/05 09:45:20 - mmengine - INFO - Epoch(train) [5][360/940] lr: 1.0000e-02 eta: 20:38:35 time: 0.6467 data_time: 0.2423 memory: 22701 grad_norm: 4.5222 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.1847 loss: 2.1847 2022/09/05 09:45:36 - mmengine - INFO - Epoch(train) [5][380/940] lr: 1.0000e-02 eta: 20:37:51 time: 0.7651 data_time: 0.3440 memory: 22701 grad_norm: 4.5979 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 2.0654 loss: 2.0654 2022/09/05 09:45:49 - mmengine - INFO - Epoch(train) [5][400/940] lr: 1.0000e-02 eta: 20:36:32 time: 0.6816 data_time: 0.2715 memory: 22701 grad_norm: 4.5208 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.0407 loss: 2.0407 2022/09/05 09:46:05 - mmengine - INFO - Epoch(train) [5][420/940] lr: 1.0000e-02 eta: 20:35:51 time: 0.7689 data_time: 0.3779 memory: 22701 grad_norm: 4.3916 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0555 loss: 2.0555 2022/09/05 09:46:19 - mmengine - INFO - Epoch(train) [5][440/940] lr: 1.0000e-02 eta: 20:34:42 time: 0.7031 data_time: 0.2397 memory: 22701 grad_norm: 4.4888 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1856 loss: 2.1856 2022/09/05 09:46:36 - mmengine - INFO - Epoch(train) [5][460/940] lr: 1.0000e-02 eta: 20:34:55 time: 0.8923 data_time: 0.4652 memory: 22701 grad_norm: 4.5869 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1899 loss: 2.1899 2022/09/05 09:46:52 - mmengine - INFO - Epoch(train) [5][480/940] lr: 1.0000e-02 eta: 20:34:25 time: 0.7940 data_time: 0.2896 memory: 22701 grad_norm: 4.5896 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2747 loss: 2.2747 2022/09/05 09:47:11 - mmengine - INFO - Epoch(train) [5][500/940] lr: 1.0000e-02 eta: 20:34:48 time: 0.9201 data_time: 0.4042 memory: 22701 grad_norm: 4.5418 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0838 loss: 2.0838 2022/09/05 09:47:26 - mmengine - INFO - Epoch(train) [5][520/940] lr: 1.0000e-02 eta: 20:34:08 time: 0.7696 data_time: 0.2054 memory: 22701 grad_norm: 4.5848 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0847 loss: 2.0847 2022/09/05 09:47:43 - mmengine - INFO - Epoch(train) [5][540/940] lr: 1.0000e-02 eta: 20:33:54 time: 0.8302 data_time: 0.4500 memory: 22701 grad_norm: 4.4478 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.1072 loss: 2.1072 2022/09/05 09:47:58 - mmengine - INFO - Epoch(train) [5][560/940] lr: 1.0000e-02 eta: 20:33:18 time: 0.7775 data_time: 0.2634 memory: 22701 grad_norm: 4.5526 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.1690 loss: 2.1690 2022/09/05 09:48:15 - mmengine - INFO - Epoch(train) [5][580/940] lr: 1.0000e-02 eta: 20:33:12 time: 0.8511 data_time: 0.2357 memory: 22701 grad_norm: 4.5188 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 2.1374 loss: 2.1374 2022/09/05 09:48:30 - mmengine - INFO - Epoch(train) [5][600/940] lr: 1.0000e-02 eta: 20:32:16 time: 0.7294 data_time: 0.0833 memory: 22701 grad_norm: 4.4388 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0120 loss: 2.0120 2022/09/05 09:48:48 - mmengine - INFO - Epoch(train) [5][620/940] lr: 1.0000e-02 eta: 20:32:35 time: 0.9122 data_time: 0.2596 memory: 22701 grad_norm: 4.5295 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9643 loss: 1.9643 2022/09/05 09:49:03 - mmengine - INFO - Epoch(train) [5][640/940] lr: 1.0000e-02 eta: 20:31:43 time: 0.7375 data_time: 0.1249 memory: 22701 grad_norm: 4.4901 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0796 loss: 2.0796 2022/09/05 09:49:22 - mmengine - INFO - Epoch(train) [5][660/940] lr: 1.0000e-02 eta: 20:32:10 time: 0.9325 data_time: 0.1092 memory: 22701 grad_norm: 4.4419 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.0043 loss: 2.0043 2022/09/05 09:49:36 - mmengine - INFO - Epoch(train) [5][680/940] lr: 1.0000e-02 eta: 20:31:12 time: 0.7218 data_time: 0.0961 memory: 22701 grad_norm: 4.4788 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.1281 loss: 2.1281 2022/09/05 09:49:55 - mmengine - INFO - Epoch(train) [5][700/940] lr: 1.0000e-02 eta: 20:31:41 time: 0.9390 data_time: 0.1562 memory: 22701 grad_norm: 4.4557 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.0559 loss: 2.0559 2022/09/05 09:50:09 - mmengine - INFO - Epoch(train) [5][720/940] lr: 1.0000e-02 eta: 20:30:40 time: 0.7127 data_time: 0.0666 memory: 22701 grad_norm: 4.5256 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9550 loss: 1.9550 2022/09/05 09:50:27 - mmengine - INFO - Epoch(train) [5][740/940] lr: 1.0000e-02 eta: 20:30:57 time: 0.9100 data_time: 0.2517 memory: 22701 grad_norm: 4.5739 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1143 loss: 2.1143 2022/09/05 09:50:42 - mmengine - INFO - Epoch(train) [5][760/940] lr: 1.0000e-02 eta: 20:30:13 time: 0.7565 data_time: 0.3173 memory: 22701 grad_norm: 4.4717 top1_acc: 0.3125 top5_acc: 0.6562 loss_cls: 2.1647 loss: 2.1647 2022/09/05 09:50:58 - mmengine - INFO - Epoch(train) [5][780/940] lr: 1.0000e-02 eta: 20:29:34 time: 0.7665 data_time: 0.2497 memory: 22701 grad_norm: 4.5294 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0445 loss: 2.0445 2022/09/05 09:51:12 - mmengine - INFO - Epoch(train) [5][800/940] lr: 1.0000e-02 eta: 20:28:35 time: 0.7166 data_time: 0.2992 memory: 22701 grad_norm: 4.5196 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0035 loss: 2.0035 2022/09/05 09:51:27 - mmengine - INFO - Epoch(train) [5][820/940] lr: 1.0000e-02 eta: 20:27:49 time: 0.7481 data_time: 0.1572 memory: 22701 grad_norm: 4.5229 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0339 loss: 2.0339 2022/09/05 09:51:42 - mmengine - INFO - Epoch(train) [5][840/940] lr: 1.0000e-02 eta: 20:26:55 time: 0.7280 data_time: 0.1716 memory: 22701 grad_norm: 4.5940 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.1881 loss: 2.1881 2022/09/05 09:51:58 - mmengine - INFO - Epoch(train) [5][860/940] lr: 1.0000e-02 eta: 20:26:34 time: 0.8131 data_time: 0.1685 memory: 22701 grad_norm: 4.4825 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 2.0531 loss: 2.0531 2022/09/05 09:52:13 - mmengine - INFO - Epoch(train) [5][880/940] lr: 1.0000e-02 eta: 20:25:57 time: 0.7690 data_time: 0.1328 memory: 22701 grad_norm: 4.5045 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.1007 loss: 2.1007 2022/09/05 09:52:30 - mmengine - INFO - Epoch(train) [5][900/940] lr: 1.0000e-02 eta: 20:25:50 time: 0.8476 data_time: 0.1460 memory: 22701 grad_norm: 4.4629 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0931 loss: 2.0931 2022/09/05 09:52:45 - mmengine - INFO - Epoch(train) [5][920/940] lr: 1.0000e-02 eta: 20:24:57 time: 0.7279 data_time: 0.0561 memory: 22701 grad_norm: 4.5179 top1_acc: 0.4688 top5_acc: 0.5938 loss_cls: 2.2573 loss: 2.2573 2022/09/05 09:53:01 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:53:01 - mmengine - INFO - Epoch(train) [5][940/940] lr: 1.0000e-02 eta: 20:24:37 time: 0.8146 data_time: 0.0754 memory: 22701 grad_norm: 4.7521 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 2.2376 loss: 2.2376 2022/09/05 09:53:15 - mmengine - INFO - Epoch(val) [5][20/78] eta: 0:00:39 time: 0.6895 data_time: 0.5686 memory: 2247 2022/09/05 09:53:24 - mmengine - INFO - Epoch(val) [5][40/78] eta: 0:00:16 time: 0.4470 data_time: 0.3317 memory: 2247 2022/09/05 09:53:37 - mmengine - INFO - Epoch(val) [5][60/78] eta: 0:00:11 time: 0.6606 data_time: 0.5430 memory: 2247 2022/09/05 09:53:47 - mmengine - INFO - Epoch(val) [5][78/78] acc/top1: 0.5841 acc/top5: 0.8204 acc/mean1: 0.5840 2022/09/05 09:53:47 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_5.pth is removed 2022/09/05 09:53:48 - mmengine - INFO - The best checkpoint with 0.5841 acc/top1 at 6 epoch is saved to best_acc/top1_epoch_6.pth. 2022/09/05 09:54:06 - mmengine - INFO - Epoch(train) [6][20/940] lr: 1.0000e-02 eta: 20:24:53 time: 0.9076 data_time: 0.4964 memory: 22701 grad_norm: 4.4736 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1979 loss: 2.1979 2022/09/05 09:54:21 - mmengine - INFO - Epoch(train) [6][40/940] lr: 1.0000e-02 eta: 20:23:57 time: 0.7184 data_time: 0.3305 memory: 22701 grad_norm: 4.4518 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0125 loss: 2.0125 2022/09/05 09:54:37 - mmengine - INFO - Epoch(train) [6][60/940] lr: 1.0000e-02 eta: 20:23:48 time: 0.8424 data_time: 0.3649 memory: 22701 grad_norm: 4.4984 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 2.0755 loss: 2.0755 2022/09/05 09:54:51 - mmengine - INFO - Epoch(train) [6][80/940] lr: 1.0000e-02 eta: 20:22:47 time: 0.7039 data_time: 0.2439 memory: 22701 grad_norm: 4.4837 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9970 loss: 1.9970 2022/09/05 09:55:08 - mmengine - INFO - Epoch(train) [6][100/940] lr: 1.0000e-02 eta: 20:22:34 time: 0.8314 data_time: 0.0738 memory: 22701 grad_norm: 4.3979 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9204 loss: 1.9204 2022/09/05 09:55:22 - mmengine - INFO - Epoch(train) [6][120/940] lr: 1.0000e-02 eta: 20:21:36 time: 0.7098 data_time: 0.0300 memory: 22701 grad_norm: 4.6125 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1849 loss: 2.1849 2022/09/05 09:55:38 - mmengine - INFO - Epoch(train) [6][140/940] lr: 1.0000e-02 eta: 20:21:06 time: 0.7858 data_time: 0.0269 memory: 22701 grad_norm: 4.4947 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.9849 loss: 1.9849 2022/09/05 09:55:51 - mmengine - INFO - Epoch(train) [6][160/940] lr: 1.0000e-02 eta: 20:19:44 time: 0.6413 data_time: 0.0549 memory: 22701 grad_norm: 4.5532 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0476 loss: 2.0476 2022/09/05 09:56:07 - mmengine - INFO - Epoch(train) [6][180/940] lr: 1.0000e-02 eta: 20:19:27 time: 0.8197 data_time: 0.1846 memory: 22701 grad_norm: 4.4625 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0164 loss: 2.0164 2022/09/05 09:56:21 - mmengine - INFO - Epoch(train) [6][200/940] lr: 1.0000e-02 eta: 20:18:22 time: 0.6889 data_time: 0.0680 memory: 22701 grad_norm: 4.4430 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1541 loss: 2.1541 2022/09/05 09:56:37 - mmengine - INFO - Epoch(train) [6][220/940] lr: 1.0000e-02 eta: 20:17:53 time: 0.7855 data_time: 0.1042 memory: 22701 grad_norm: 4.5120 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.2301 loss: 2.2301 2022/09/05 09:56:56 - mmengine - INFO - Epoch(train) [6][240/940] lr: 1.0000e-02 eta: 20:18:28 time: 0.9629 data_time: 0.3808 memory: 22701 grad_norm: 4.5442 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9793 loss: 1.9793 2022/09/05 09:57:19 - mmengine - INFO - Epoch(train) [6][260/940] lr: 1.0000e-02 eta: 20:20:03 time: 1.1315 data_time: 0.5457 memory: 22701 grad_norm: 4.5362 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.1101 loss: 2.1101 2022/09/05 09:57:33 - mmengine - INFO - Epoch(train) [6][280/940] lr: 1.0000e-02 eta: 20:19:08 time: 0.7145 data_time: 0.2009 memory: 22701 grad_norm: 4.5018 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0810 loss: 2.0810 2022/09/05 09:57:50 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 09:57:50 - mmengine - INFO - Epoch(train) [6][300/940] lr: 1.0000e-02 eta: 20:19:08 time: 0.8655 data_time: 0.4199 memory: 22701 grad_norm: 4.6040 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0698 loss: 2.0698 2022/09/05 09:58:07 - mmengine - INFO - Epoch(train) [6][320/940] lr: 1.0000e-02 eta: 20:18:48 time: 0.8143 data_time: 0.4004 memory: 22701 grad_norm: 4.4982 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0149 loss: 2.0149 2022/09/05 09:58:24 - mmengine - INFO - Epoch(train) [6][340/940] lr: 1.0000e-02 eta: 20:18:55 time: 0.8878 data_time: 0.4994 memory: 22701 grad_norm: 4.4258 top1_acc: 0.3125 top5_acc: 0.7188 loss_cls: 2.0653 loss: 2.0653 2022/09/05 09:58:37 - mmengine - INFO - Epoch(train) [6][360/940] lr: 1.0000e-02 eta: 20:17:42 time: 0.6593 data_time: 0.2425 memory: 22701 grad_norm: 4.5065 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.0930 loss: 2.0930 2022/09/05 09:58:53 - mmengine - INFO - Epoch(train) [6][380/940] lr: 1.0000e-02 eta: 20:17:04 time: 0.7613 data_time: 0.2024 memory: 22701 grad_norm: 4.5909 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9883 loss: 1.9883 2022/09/05 09:59:06 - mmengine - INFO - Epoch(train) [6][400/940] lr: 1.0000e-02 eta: 20:15:55 time: 0.6698 data_time: 0.2207 memory: 22701 grad_norm: 4.5663 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.0211 loss: 2.0211 2022/09/05 09:59:23 - mmengine - INFO - Epoch(train) [6][420/940] lr: 1.0000e-02 eta: 20:15:53 time: 0.8623 data_time: 0.3977 memory: 22701 grad_norm: 4.5585 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.0817 loss: 2.0817 2022/09/05 09:59:39 - mmengine - INFO - Epoch(train) [6][440/940] lr: 1.0000e-02 eta: 20:15:21 time: 0.7750 data_time: 0.3802 memory: 22701 grad_norm: 4.5632 top1_acc: 0.3125 top5_acc: 0.7188 loss_cls: 1.8114 loss: 1.8114 2022/09/05 09:59:55 - mmengine - INFO - Epoch(train) [6][460/940] lr: 1.0000e-02 eta: 20:15:06 time: 0.8250 data_time: 0.4267 memory: 22701 grad_norm: 4.5462 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0649 loss: 2.0649 2022/09/05 10:00:12 - mmengine - INFO - Epoch(train) [6][480/940] lr: 1.0000e-02 eta: 20:14:54 time: 0.8343 data_time: 0.4425 memory: 22701 grad_norm: 4.5324 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0669 loss: 2.0669 2022/09/05 10:00:26 - mmengine - INFO - Epoch(train) [6][500/940] lr: 1.0000e-02 eta: 20:14:03 time: 0.7195 data_time: 0.3224 memory: 22701 grad_norm: 4.5565 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0807 loss: 2.0807 2022/09/05 10:00:43 - mmengine - INFO - Epoch(train) [6][520/940] lr: 1.0000e-02 eta: 20:13:55 time: 0.8455 data_time: 0.4392 memory: 22701 grad_norm: 4.5662 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2277 loss: 2.2277 2022/09/05 10:00:57 - mmengine - INFO - Epoch(train) [6][540/940] lr: 1.0000e-02 eta: 20:12:53 time: 0.6864 data_time: 0.2967 memory: 22701 grad_norm: 4.5168 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.1284 loss: 2.1284 2022/09/05 10:01:14 - mmengine - INFO - Epoch(train) [6][560/940] lr: 1.0000e-02 eta: 20:12:42 time: 0.8359 data_time: 0.4226 memory: 22701 grad_norm: 4.5528 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1056 loss: 2.1056 2022/09/05 10:01:29 - mmengine - INFO - Epoch(train) [6][580/940] lr: 1.0000e-02 eta: 20:12:04 time: 0.7561 data_time: 0.3537 memory: 22701 grad_norm: 4.5113 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.0592 loss: 2.0592 2022/09/05 10:01:46 - mmengine - INFO - Epoch(train) [6][600/940] lr: 1.0000e-02 eta: 20:11:57 time: 0.8458 data_time: 0.4490 memory: 22701 grad_norm: 4.6414 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1015 loss: 2.1015 2022/09/05 10:02:00 - mmengine - INFO - Epoch(train) [6][620/940] lr: 1.0000e-02 eta: 20:11:03 time: 0.7080 data_time: 0.2908 memory: 22701 grad_norm: 4.5453 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9516 loss: 1.9516 2022/09/05 10:02:16 - mmengine - INFO - Epoch(train) [6][640/940] lr: 1.0000e-02 eta: 20:10:45 time: 0.8132 data_time: 0.4132 memory: 22701 grad_norm: 4.5348 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0783 loss: 2.0783 2022/09/05 10:02:31 - mmengine - INFO - Epoch(train) [6][660/940] lr: 1.0000e-02 eta: 20:10:05 time: 0.7495 data_time: 0.3426 memory: 22701 grad_norm: 4.5720 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 2.0431 loss: 2.0431 2022/09/05 10:02:49 - mmengine - INFO - Epoch(train) [6][680/940] lr: 1.0000e-02 eta: 20:10:14 time: 0.8947 data_time: 0.4762 memory: 22701 grad_norm: 4.4483 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8765 loss: 1.8765 2022/09/05 10:03:04 - mmengine - INFO - Epoch(train) [6][700/940] lr: 1.0000e-02 eta: 20:09:34 time: 0.7478 data_time: 0.3570 memory: 22701 grad_norm: 4.6183 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0670 loss: 2.0670 2022/09/05 10:03:22 - mmengine - INFO - Epoch(train) [6][720/940] lr: 1.0000e-02 eta: 20:09:35 time: 0.8738 data_time: 0.4742 memory: 22701 grad_norm: 4.6228 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.2791 loss: 2.2791 2022/09/05 10:03:38 - mmengine - INFO - Epoch(train) [6][740/940] lr: 1.0000e-02 eta: 20:09:18 time: 0.8168 data_time: 0.4067 memory: 22701 grad_norm: 4.5041 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0600 loss: 2.0600 2022/09/05 10:03:56 - mmengine - INFO - Epoch(train) [6][760/940] lr: 1.0000e-02 eta: 20:09:38 time: 0.9321 data_time: 0.5277 memory: 22701 grad_norm: 4.5157 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9762 loss: 1.9762 2022/09/05 10:04:13 - mmengine - INFO - Epoch(train) [6][780/940] lr: 1.0000e-02 eta: 20:09:23 time: 0.8232 data_time: 0.4156 memory: 22701 grad_norm: 4.5487 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0937 loss: 2.0937 2022/09/05 10:04:33 - mmengine - INFO - Epoch(train) [6][800/940] lr: 1.0000e-02 eta: 20:10:08 time: 1.0090 data_time: 0.6037 memory: 22701 grad_norm: 4.5185 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1797 loss: 2.1797 2022/09/05 10:04:48 - mmengine - INFO - Epoch(train) [6][820/940] lr: 1.0000e-02 eta: 20:09:32 time: 0.7614 data_time: 0.3672 memory: 22701 grad_norm: 4.5418 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.1148 loss: 2.1148 2022/09/05 10:05:08 - mmengine - INFO - Epoch(train) [6][840/940] lr: 1.0000e-02 eta: 20:10:00 time: 0.9593 data_time: 0.5788 memory: 22701 grad_norm: 4.5104 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.0108 loss: 2.0108 2022/09/05 10:05:24 - mmengine - INFO - Epoch(train) [6][860/940] lr: 1.0000e-02 eta: 20:09:47 time: 0.8319 data_time: 0.4294 memory: 22701 grad_norm: 4.4389 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.1190 loss: 2.1190 2022/09/05 10:05:44 - mmengine - INFO - Epoch(train) [6][880/940] lr: 1.0000e-02 eta: 20:10:22 time: 0.9814 data_time: 0.5767 memory: 22701 grad_norm: 4.5311 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9981 loss: 1.9981 2022/09/05 10:05:59 - mmengine - INFO - Epoch(train) [6][900/940] lr: 1.0000e-02 eta: 20:09:46 time: 0.7593 data_time: 0.3326 memory: 22701 grad_norm: 4.5186 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 2.0841 loss: 2.0841 2022/09/05 10:06:16 - mmengine - INFO - Epoch(train) [6][920/940] lr: 1.0000e-02 eta: 20:09:44 time: 0.8686 data_time: 0.4705 memory: 22701 grad_norm: 4.5722 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 2.0247 loss: 2.0247 2022/09/05 10:06:31 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:06:31 - mmengine - INFO - Epoch(train) [6][940/940] lr: 1.0000e-02 eta: 20:08:58 time: 0.7245 data_time: 0.3487 memory: 22701 grad_norm: 4.8457 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 2.1036 loss: 2.1036 2022/09/05 10:06:31 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/09/05 10:06:46 - mmengine - INFO - Epoch(val) [6][20/78] eta: 0:00:40 time: 0.6951 data_time: 0.5723 memory: 2247 2022/09/05 10:06:55 - mmengine - INFO - Epoch(val) [6][40/78] eta: 0:00:17 time: 0.4491 data_time: 0.3348 memory: 2247 2022/09/05 10:07:08 - mmengine - INFO - Epoch(val) [6][60/78] eta: 0:00:11 time: 0.6550 data_time: 0.5377 memory: 2247 2022/09/05 10:07:18 - mmengine - INFO - Epoch(val) [6][78/78] acc/top1: 0.5915 acc/top5: 0.8250 acc/mean1: 0.5914 2022/09/05 10:07:18 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_6.pth is removed 2022/09/05 10:07:18 - mmengine - INFO - The best checkpoint with 0.5915 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth. 2022/09/05 10:07:39 - mmengine - INFO - Epoch(train) [7][20/940] lr: 1.0000e-02 eta: 20:09:42 time: 1.0162 data_time: 0.5745 memory: 22701 grad_norm: 4.4977 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9554 loss: 1.9554 2022/09/05 10:07:53 - mmengine - INFO - Epoch(train) [7][40/940] lr: 1.0000e-02 eta: 20:08:53 time: 0.7163 data_time: 0.3310 memory: 22701 grad_norm: 4.3892 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 2.0479 loss: 2.0479 2022/09/05 10:08:10 - mmengine - INFO - Epoch(train) [7][60/940] lr: 1.0000e-02 eta: 20:08:39 time: 0.8303 data_time: 0.4210 memory: 22701 grad_norm: 4.5395 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.9859 loss: 1.9859 2022/09/05 10:08:23 - mmengine - INFO - Epoch(train) [7][80/940] lr: 1.0000e-02 eta: 20:07:38 time: 0.6747 data_time: 0.1946 memory: 22701 grad_norm: 4.4841 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.0449 loss: 2.0449 2022/09/05 10:08:39 - mmengine - INFO - Epoch(train) [7][100/940] lr: 1.0000e-02 eta: 20:07:05 time: 0.7665 data_time: 0.2970 memory: 22701 grad_norm: 4.5381 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9847 loss: 1.9847 2022/09/05 10:08:52 - mmengine - INFO - Epoch(train) [7][120/940] lr: 1.0000e-02 eta: 20:05:59 time: 0.6594 data_time: 0.2058 memory: 22701 grad_norm: 4.5668 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9247 loss: 1.9247 2022/09/05 10:09:08 - mmengine - INFO - Epoch(train) [7][140/940] lr: 1.0000e-02 eta: 20:05:48 time: 0.8371 data_time: 0.2467 memory: 22701 grad_norm: 4.5645 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9835 loss: 1.9835 2022/09/05 10:09:22 - mmengine - INFO - Epoch(train) [7][160/940] lr: 1.0000e-02 eta: 20:04:50 time: 0.6836 data_time: 0.1303 memory: 22701 grad_norm: 4.6451 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9891 loss: 1.9891 2022/09/05 10:09:41 - mmengine - INFO - Epoch(train) [7][180/940] lr: 1.0000e-02 eta: 20:05:17 time: 0.9626 data_time: 0.2611 memory: 22701 grad_norm: 4.5083 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.9580 loss: 1.9580 2022/09/05 10:09:55 - mmengine - INFO - Epoch(train) [7][200/940] lr: 1.0000e-02 eta: 20:04:22 time: 0.6930 data_time: 0.0771 memory: 22701 grad_norm: 4.5386 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0615 loss: 2.0615 2022/09/05 10:10:14 - mmengine - INFO - Epoch(train) [7][220/940] lr: 1.0000e-02 eta: 20:04:46 time: 0.9550 data_time: 0.1895 memory: 22701 grad_norm: 4.5064 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0928 loss: 2.0928 2022/09/05 10:10:29 - mmengine - INFO - Epoch(train) [7][240/940] lr: 1.0000e-02 eta: 20:03:57 time: 0.7108 data_time: 0.0610 memory: 22701 grad_norm: 4.5742 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1272 loss: 2.1272 2022/09/05 10:10:47 - mmengine - INFO - Epoch(train) [7][260/940] lr: 1.0000e-02 eta: 20:04:10 time: 0.9187 data_time: 0.1694 memory: 22701 grad_norm: 4.4664 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9024 loss: 1.9024 2022/09/05 10:11:00 - mmengine - INFO - Epoch(train) [7][280/940] lr: 1.0000e-02 eta: 20:02:59 time: 0.6368 data_time: 0.1150 memory: 22701 grad_norm: 4.5119 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.0315 loss: 2.0315 2022/09/05 10:11:17 - mmengine - INFO - Epoch(train) [7][300/940] lr: 1.0000e-02 eta: 20:02:59 time: 0.8735 data_time: 0.1479 memory: 22701 grad_norm: 4.5172 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9488 loss: 1.9488 2022/09/05 10:11:31 - mmengine - INFO - Epoch(train) [7][320/940] lr: 1.0000e-02 eta: 20:02:08 time: 0.7026 data_time: 0.1320 memory: 22701 grad_norm: 4.4903 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8070 loss: 1.8070 2022/09/05 10:11:48 - mmengine - INFO - Epoch(train) [7][340/940] lr: 1.0000e-02 eta: 20:01:59 time: 0.8455 data_time: 0.1576 memory: 22701 grad_norm: 4.5686 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9803 loss: 1.9803 2022/09/05 10:12:01 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:12:01 - mmengine - INFO - Epoch(train) [7][360/940] lr: 1.0000e-02 eta: 20:00:46 time: 0.6254 data_time: 0.0452 memory: 22701 grad_norm: 4.5564 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9335 loss: 1.9335 2022/09/05 10:12:17 - mmengine - INFO - Epoch(train) [7][380/940] lr: 1.0000e-02 eta: 20:00:29 time: 0.8181 data_time: 0.2648 memory: 22701 grad_norm: 4.4168 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0184 loss: 2.0184 2022/09/05 10:12:32 - mmengine - INFO - Epoch(train) [7][400/940] lr: 1.0000e-02 eta: 19:59:55 time: 0.7577 data_time: 0.2410 memory: 22701 grad_norm: 4.4825 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9873 loss: 1.9873 2022/09/05 10:12:53 - mmengine - INFO - Epoch(train) [7][420/940] lr: 1.0000e-02 eta: 20:00:38 time: 1.0239 data_time: 0.2716 memory: 22701 grad_norm: 4.5204 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9906 loss: 1.9906 2022/09/05 10:13:08 - mmengine - INFO - Epoch(train) [7][440/940] lr: 1.0000e-02 eta: 20:00:03 time: 0.7542 data_time: 0.1537 memory: 22701 grad_norm: 4.5101 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.9579 loss: 1.9579 2022/09/05 10:13:27 - mmengine - INFO - Epoch(train) [7][460/940] lr: 1.0000e-02 eta: 20:00:22 time: 0.9396 data_time: 0.1231 memory: 22701 grad_norm: 4.4806 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9137 loss: 1.9137 2022/09/05 10:13:40 - mmengine - INFO - Epoch(train) [7][480/940] lr: 1.0000e-02 eta: 19:59:30 time: 0.6975 data_time: 0.0218 memory: 22701 grad_norm: 4.5639 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.9737 loss: 1.9737 2022/09/05 10:13:57 - mmengine - INFO - Epoch(train) [7][500/940] lr: 1.0000e-02 eta: 19:59:17 time: 0.8291 data_time: 0.0691 memory: 22701 grad_norm: 4.5363 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0202 loss: 2.0202 2022/09/05 10:14:11 - mmengine - INFO - Epoch(train) [7][520/940] lr: 1.0000e-02 eta: 19:58:25 time: 0.6949 data_time: 0.1865 memory: 22701 grad_norm: 4.5077 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.9934 loss: 1.9934 2022/09/05 10:14:30 - mmengine - INFO - Epoch(train) [7][540/940] lr: 1.0000e-02 eta: 19:58:51 time: 0.9679 data_time: 0.2928 memory: 22701 grad_norm: 4.4977 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 2.0616 loss: 2.0616 2022/09/05 10:14:48 - mmengine - INFO - Epoch(train) [7][560/940] lr: 1.0000e-02 eta: 19:58:54 time: 0.8888 data_time: 0.1177 memory: 22701 grad_norm: 4.4347 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.0467 loss: 2.0467 2022/09/05 10:15:07 - mmengine - INFO - Epoch(train) [7][580/940] lr: 1.0000e-02 eta: 19:59:10 time: 0.9307 data_time: 0.0888 memory: 22701 grad_norm: 4.6013 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.1076 loss: 2.1076 2022/09/05 10:15:20 - mmengine - INFO - Epoch(train) [7][600/940] lr: 1.0000e-02 eta: 19:58:15 time: 0.6853 data_time: 0.1071 memory: 22701 grad_norm: 4.7040 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9951 loss: 1.9951 2022/09/05 10:15:38 - mmengine - INFO - Epoch(train) [7][620/940] lr: 1.0000e-02 eta: 19:58:14 time: 0.8717 data_time: 0.3196 memory: 22701 grad_norm: 4.4870 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0365 loss: 2.0365 2022/09/05 10:15:56 - mmengine - INFO - Epoch(train) [7][640/940] lr: 1.0000e-02 eta: 19:58:25 time: 0.9196 data_time: 0.0910 memory: 22701 grad_norm: 4.5304 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.0085 loss: 2.0085 2022/09/05 10:16:13 - mmengine - INFO - Epoch(train) [7][660/940] lr: 1.0000e-02 eta: 19:58:10 time: 0.8233 data_time: 0.2305 memory: 22701 grad_norm: 4.5792 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0175 loss: 2.0175 2022/09/05 10:16:32 - mmengine - INFO - Epoch(train) [7][680/940] lr: 1.0000e-02 eta: 19:58:31 time: 0.9557 data_time: 0.2049 memory: 22701 grad_norm: 4.5397 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8386 loss: 1.8386 2022/09/05 10:16:52 - mmengine - INFO - Epoch(train) [7][700/940] lr: 1.0000e-02 eta: 19:59:01 time: 0.9874 data_time: 0.0386 memory: 22701 grad_norm: 4.5224 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.8980 loss: 1.8980 2022/09/05 10:17:07 - mmengine - INFO - Epoch(train) [7][720/940] lr: 1.0000e-02 eta: 19:58:32 time: 0.7748 data_time: 0.0258 memory: 22701 grad_norm: 4.6385 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.9866 loss: 1.9866 2022/09/05 10:17:25 - mmengine - INFO - Epoch(train) [7][740/940] lr: 1.0000e-02 eta: 19:58:30 time: 0.8724 data_time: 0.0751 memory: 22701 grad_norm: 4.6769 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9819 loss: 1.9819 2022/09/05 10:17:42 - mmengine - INFO - Epoch(train) [7][760/940] lr: 1.0000e-02 eta: 19:58:21 time: 0.8489 data_time: 0.0472 memory: 22701 grad_norm: 4.5998 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.9229 loss: 1.9229 2022/09/05 10:18:01 - mmengine - INFO - Epoch(train) [7][780/940] lr: 1.0000e-02 eta: 19:58:45 time: 0.9671 data_time: 0.0336 memory: 22701 grad_norm: 4.5273 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.0003 loss: 2.0003 2022/09/05 10:18:22 - mmengine - INFO - Epoch(train) [7][800/940] lr: 1.0000e-02 eta: 19:59:28 time: 1.0396 data_time: 0.0271 memory: 22701 grad_norm: 4.5209 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.0534 loss: 2.0534 2022/09/05 10:18:36 - mmengine - INFO - Epoch(train) [7][820/940] lr: 1.0000e-02 eta: 19:58:48 time: 0.7378 data_time: 0.0342 memory: 22701 grad_norm: 4.5562 top1_acc: 0.3125 top5_acc: 0.7188 loss_cls: 2.0969 loss: 2.0969 2022/09/05 10:18:53 - mmengine - INFO - Epoch(train) [7][840/940] lr: 1.0000e-02 eta: 19:58:35 time: 0.8348 data_time: 0.0245 memory: 22701 grad_norm: 4.5809 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0816 loss: 2.0816 2022/09/05 10:19:08 - mmengine - INFO - Epoch(train) [7][860/940] lr: 1.0000e-02 eta: 19:58:02 time: 0.7578 data_time: 0.0269 memory: 22701 grad_norm: 4.4812 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9145 loss: 1.9145 2022/09/05 10:19:26 - mmengine - INFO - Epoch(train) [7][880/940] lr: 1.0000e-02 eta: 19:58:08 time: 0.9060 data_time: 0.1151 memory: 22701 grad_norm: 4.5567 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1063 loss: 2.1063 2022/09/05 10:19:45 - mmengine - INFO - Epoch(train) [7][900/940] lr: 1.0000e-02 eta: 19:58:19 time: 0.9239 data_time: 0.3285 memory: 22701 grad_norm: 4.4561 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9454 loss: 1.9454 2022/09/05 10:20:01 - mmengine - INFO - Epoch(train) [7][920/940] lr: 1.0000e-02 eta: 19:57:57 time: 0.8007 data_time: 0.3311 memory: 22701 grad_norm: 4.5595 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.9459 loss: 1.9459 2022/09/05 10:20:16 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:20:16 - mmengine - INFO - Epoch(train) [7][940/940] lr: 1.0000e-02 eta: 19:57:19 time: 0.7433 data_time: 0.2952 memory: 22701 grad_norm: 4.8277 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 2.1260 loss: 2.1260 2022/09/05 10:20:30 - mmengine - INFO - Epoch(val) [7][20/78] eta: 0:00:40 time: 0.6984 data_time: 0.5789 memory: 2247 2022/09/05 10:20:39 - mmengine - INFO - Epoch(val) [7][40/78] eta: 0:00:17 time: 0.4612 data_time: 0.3448 memory: 2247 2022/09/05 10:20:51 - mmengine - INFO - Epoch(val) [7][60/78] eta: 0:00:11 time: 0.6251 data_time: 0.5065 memory: 2247 2022/09/05 10:21:02 - mmengine - INFO - Epoch(val) [7][78/78] acc/top1: 0.6013 acc/top5: 0.8278 acc/mean1: 0.6011 2022/09/05 10:21:02 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_7.pth is removed 2022/09/05 10:21:03 - mmengine - INFO - The best checkpoint with 0.6013 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/09/05 10:21:26 - mmengine - INFO - Epoch(train) [8][20/940] lr: 1.0000e-02 eta: 19:58:30 time: 1.1513 data_time: 0.4599 memory: 22701 grad_norm: 4.5209 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.0465 loss: 2.0465 2022/09/05 10:21:42 - mmengine - INFO - Epoch(train) [8][40/940] lr: 1.0000e-02 eta: 19:58:03 time: 0.7823 data_time: 0.1353 memory: 22701 grad_norm: 4.5339 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9519 loss: 1.9519 2022/09/05 10:22:00 - mmengine - INFO - Epoch(train) [8][60/940] lr: 1.0000e-02 eta: 19:58:07 time: 0.8982 data_time: 0.1412 memory: 22701 grad_norm: 4.4936 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7803 loss: 1.7803 2022/09/05 10:22:15 - mmengine - INFO - Epoch(train) [8][80/940] lr: 1.0000e-02 eta: 19:57:27 time: 0.7332 data_time: 0.0772 memory: 22701 grad_norm: 4.4577 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7691 loss: 1.7691 2022/09/05 10:22:32 - mmengine - INFO - Epoch(train) [8][100/940] lr: 1.0000e-02 eta: 19:57:24 time: 0.8740 data_time: 0.0466 memory: 22701 grad_norm: 4.5058 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1363 loss: 2.1363 2022/09/05 10:22:48 - mmengine - INFO - Epoch(train) [8][120/940] lr: 1.0000e-02 eta: 19:56:59 time: 0.7910 data_time: 0.1914 memory: 22701 grad_norm: 4.4817 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 2.0460 loss: 2.0460 2022/09/05 10:23:05 - mmengine - INFO - Epoch(train) [8][140/940] lr: 1.0000e-02 eta: 19:56:57 time: 0.8780 data_time: 0.0750 memory: 22701 grad_norm: 4.4969 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8639 loss: 1.8639 2022/09/05 10:23:20 - mmengine - INFO - Epoch(train) [8][160/940] lr: 1.0000e-02 eta: 19:56:12 time: 0.7123 data_time: 0.1094 memory: 22701 grad_norm: 4.5147 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9005 loss: 1.9005 2022/09/05 10:23:37 - mmengine - INFO - Epoch(train) [8][180/940] lr: 1.0000e-02 eta: 19:56:09 time: 0.8747 data_time: 0.0758 memory: 22701 grad_norm: 4.4796 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9614 loss: 1.9614 2022/09/05 10:23:52 - mmengine - INFO - Epoch(train) [8][200/940] lr: 1.0000e-02 eta: 19:55:29 time: 0.7325 data_time: 0.0206 memory: 22701 grad_norm: 4.5824 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9917 loss: 1.9917 2022/09/05 10:24:10 - mmengine - INFO - Epoch(train) [8][220/940] lr: 1.0000e-02 eta: 19:55:37 time: 0.9164 data_time: 0.0813 memory: 22701 grad_norm: 4.4904 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9800 loss: 1.9800 2022/09/05 10:24:26 - mmengine - INFO - Epoch(train) [8][240/940] lr: 1.0000e-02 eta: 19:55:08 time: 0.7747 data_time: 0.0484 memory: 22701 grad_norm: 4.5576 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0465 loss: 2.0465 2022/09/05 10:24:42 - mmengine - INFO - Epoch(train) [8][260/940] lr: 1.0000e-02 eta: 19:54:54 time: 0.8319 data_time: 0.0267 memory: 22701 grad_norm: 4.5692 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.0021 loss: 2.0021 2022/09/05 10:24:55 - mmengine - INFO - Epoch(train) [8][280/940] lr: 1.0000e-02 eta: 19:53:53 time: 0.6466 data_time: 0.0287 memory: 22701 grad_norm: 4.6069 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9436 loss: 1.9436 2022/09/05 10:25:13 - mmengine - INFO - Epoch(train) [8][300/940] lr: 1.0000e-02 eta: 19:53:47 time: 0.8659 data_time: 0.0252 memory: 22701 grad_norm: 4.5533 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8349 loss: 1.8349 2022/09/05 10:25:26 - mmengine - INFO - Epoch(train) [8][320/940] lr: 1.0000e-02 eta: 19:52:59 time: 0.6966 data_time: 0.0250 memory: 22701 grad_norm: 4.6066 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9372 loss: 1.9372 2022/09/05 10:25:43 - mmengine - INFO - Epoch(train) [8][340/940] lr: 1.0000e-02 eta: 19:52:45 time: 0.8317 data_time: 0.0262 memory: 22701 grad_norm: 4.4904 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9905 loss: 1.9905 2022/09/05 10:25:56 - mmengine - INFO - Epoch(train) [8][360/940] lr: 1.0000e-02 eta: 19:51:46 time: 0.6511 data_time: 0.0274 memory: 22701 grad_norm: 4.4525 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0456 loss: 2.0456 2022/09/05 10:26:13 - mmengine - INFO - Epoch(train) [8][380/940] lr: 1.0000e-02 eta: 19:51:41 time: 0.8671 data_time: 0.0625 memory: 22701 grad_norm: 4.4968 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.9447 loss: 1.9447 2022/09/05 10:26:28 - mmengine - INFO - Epoch(train) [8][400/940] lr: 1.0000e-02 eta: 19:51:02 time: 0.7298 data_time: 0.0499 memory: 22701 grad_norm: 4.5599 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9556 loss: 1.9556 2022/09/05 10:26:47 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:26:47 - mmengine - INFO - Epoch(train) [8][420/940] lr: 1.0000e-02 eta: 19:51:22 time: 0.9671 data_time: 0.1305 memory: 22701 grad_norm: 4.5713 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9634 loss: 1.9634 2022/09/05 10:27:04 - mmengine - INFO - Epoch(train) [8][440/940] lr: 1.0000e-02 eta: 19:51:10 time: 0.8417 data_time: 0.0184 memory: 22701 grad_norm: 4.5546 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0506 loss: 2.0506 2022/09/05 10:27:24 - mmengine - INFO - Epoch(train) [8][460/940] lr: 1.0000e-02 eta: 19:51:35 time: 0.9880 data_time: 0.1463 memory: 22701 grad_norm: 4.5754 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.9274 loss: 1.9274 2022/09/05 10:27:42 - mmengine - INFO - Epoch(train) [8][480/940] lr: 1.0000e-02 eta: 19:51:33 time: 0.8818 data_time: 0.0518 memory: 22701 grad_norm: 4.5531 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9616 loss: 1.9616 2022/09/05 10:28:02 - mmengine - INFO - Epoch(train) [8][500/940] lr: 1.0000e-02 eta: 19:51:59 time: 0.9964 data_time: 0.1415 memory: 22701 grad_norm: 4.5624 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0040 loss: 2.0040 2022/09/05 10:28:17 - mmengine - INFO - Epoch(train) [8][520/940] lr: 1.0000e-02 eta: 19:51:35 time: 0.7890 data_time: 0.2501 memory: 22701 grad_norm: 4.5081 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9963 loss: 1.9963 2022/09/05 10:28:36 - mmengine - INFO - Epoch(train) [8][540/940] lr: 1.0000e-02 eta: 19:51:47 time: 0.9415 data_time: 0.1956 memory: 22701 grad_norm: 4.5297 top1_acc: 0.4688 top5_acc: 0.5938 loss_cls: 2.0150 loss: 2.0150 2022/09/05 10:28:52 - mmengine - INFO - Epoch(train) [8][560/940] lr: 1.0000e-02 eta: 19:51:23 time: 0.7914 data_time: 0.0307 memory: 22701 grad_norm: 4.5350 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.0305 loss: 2.0305 2022/09/05 10:29:09 - mmengine - INFO - Epoch(train) [8][580/940] lr: 1.0000e-02 eta: 19:51:16 time: 0.8629 data_time: 0.0990 memory: 22701 grad_norm: 4.6989 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9628 loss: 1.9628 2022/09/05 10:29:25 - mmengine - INFO - Epoch(train) [8][600/940] lr: 1.0000e-02 eta: 19:50:53 time: 0.7934 data_time: 0.0654 memory: 22701 grad_norm: 4.6816 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.9723 loss: 1.9723 2022/09/05 10:29:43 - mmengine - INFO - Epoch(train) [8][620/940] lr: 1.0000e-02 eta: 19:50:53 time: 0.8920 data_time: 0.0232 memory: 22701 grad_norm: 4.5215 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8766 loss: 1.8766 2022/09/05 10:29:58 - mmengine - INFO - Epoch(train) [8][640/940] lr: 1.0000e-02 eta: 19:50:14 time: 0.7292 data_time: 0.0958 memory: 22701 grad_norm: 4.5361 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0701 loss: 2.0701 2022/09/05 10:30:18 - mmengine - INFO - Epoch(train) [8][660/940] lr: 1.0000e-02 eta: 19:50:43 time: 1.0158 data_time: 0.2442 memory: 22701 grad_norm: 4.5661 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0291 loss: 2.0291 2022/09/05 10:30:34 - mmengine - INFO - Epoch(train) [8][680/940] lr: 1.0000e-02 eta: 19:50:18 time: 0.7849 data_time: 0.1395 memory: 22701 grad_norm: 4.5932 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0972 loss: 2.0972 2022/09/05 10:30:52 - mmengine - INFO - Epoch(train) [8][700/940] lr: 1.0000e-02 eta: 19:50:21 time: 0.9073 data_time: 0.0423 memory: 22701 grad_norm: 4.5688 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9657 loss: 1.9657 2022/09/05 10:31:06 - mmengine - INFO - Epoch(train) [8][720/940] lr: 1.0000e-02 eta: 19:49:34 time: 0.6957 data_time: 0.0303 memory: 22701 grad_norm: 4.5713 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0018 loss: 2.0018 2022/09/05 10:31:22 - mmengine - INFO - Epoch(train) [8][740/940] lr: 1.0000e-02 eta: 19:49:21 time: 0.8356 data_time: 0.0206 memory: 22701 grad_norm: 4.6279 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9234 loss: 1.9234 2022/09/05 10:31:35 - mmengine - INFO - Epoch(train) [8][760/940] lr: 1.0000e-02 eta: 19:48:23 time: 0.6489 data_time: 0.0367 memory: 22701 grad_norm: 4.6005 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.1246 loss: 2.1246 2022/09/05 10:31:53 - mmengine - INFO - Epoch(train) [8][780/940] lr: 1.0000e-02 eta: 19:48:23 time: 0.8907 data_time: 0.0254 memory: 22701 grad_norm: 4.5441 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9113 loss: 1.9113 2022/09/05 10:32:06 - mmengine - INFO - Epoch(train) [8][800/940] lr: 1.0000e-02 eta: 19:47:27 time: 0.6544 data_time: 0.0266 memory: 22701 grad_norm: 4.5523 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0408 loss: 2.0408 2022/09/05 10:32:23 - mmengine - INFO - Epoch(train) [8][820/940] lr: 1.0000e-02 eta: 19:47:15 time: 0.8432 data_time: 0.0240 memory: 22701 grad_norm: 4.6042 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9424 loss: 1.9424 2022/09/05 10:32:38 - mmengine - INFO - Epoch(train) [8][840/940] lr: 1.0000e-02 eta: 19:46:40 time: 0.7438 data_time: 0.0278 memory: 22701 grad_norm: 4.5767 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9511 loss: 1.9511 2022/09/05 10:32:55 - mmengine - INFO - Epoch(train) [8][860/940] lr: 1.0000e-02 eta: 19:46:29 time: 0.8464 data_time: 0.0234 memory: 22701 grad_norm: 4.4996 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0699 loss: 2.0699 2022/09/05 10:33:10 - mmengine - INFO - Epoch(train) [8][880/940] lr: 1.0000e-02 eta: 19:46:01 time: 0.7703 data_time: 0.0266 memory: 22701 grad_norm: 4.5897 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0135 loss: 2.0135 2022/09/05 10:33:28 - mmengine - INFO - Epoch(train) [8][900/940] lr: 1.0000e-02 eta: 19:46:00 time: 0.8898 data_time: 0.0243 memory: 22701 grad_norm: 4.5091 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.0257 loss: 2.0257 2022/09/05 10:33:43 - mmengine - INFO - Epoch(train) [8][920/940] lr: 1.0000e-02 eta: 19:45:22 time: 0.7308 data_time: 0.0265 memory: 22701 grad_norm: 4.5629 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9379 loss: 1.9379 2022/09/05 10:33:59 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:33:59 - mmengine - INFO - Epoch(train) [8][940/940] lr: 1.0000e-02 eta: 19:45:06 time: 0.8204 data_time: 0.0170 memory: 22701 grad_norm: 4.7855 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.8218 loss: 1.8218 2022/09/05 10:34:14 - mmengine - INFO - Epoch(val) [8][20/78] eta: 0:00:42 time: 0.7292 data_time: 0.6123 memory: 2247 2022/09/05 10:34:22 - mmengine - INFO - Epoch(val) [8][40/78] eta: 0:00:16 time: 0.4251 data_time: 0.3072 memory: 2247 2022/09/05 10:34:35 - mmengine - INFO - Epoch(val) [8][60/78] eta: 0:00:11 time: 0.6524 data_time: 0.5332 memory: 2247 2022/09/05 10:34:47 - mmengine - INFO - Epoch(val) [8][78/78] acc/top1: 0.5993 acc/top5: 0.8287 acc/mean1: 0.5992 2022/09/05 10:35:11 - mmengine - INFO - Epoch(train) [9][20/940] lr: 1.0000e-02 eta: 19:46:15 time: 1.1970 data_time: 0.5320 memory: 22701 grad_norm: 4.5743 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.9208 loss: 1.9208 2022/09/05 10:35:25 - mmengine - INFO - Epoch(train) [9][40/940] lr: 1.0000e-02 eta: 19:45:33 time: 0.7105 data_time: 0.0240 memory: 22701 grad_norm: 4.4999 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0158 loss: 2.0158 2022/09/05 10:35:42 - mmengine - INFO - Epoch(train) [9][60/940] lr: 1.0000e-02 eta: 19:45:20 time: 0.8395 data_time: 0.0285 memory: 22701 grad_norm: 4.4379 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7825 loss: 1.7825 2022/09/05 10:35:58 - mmengine - INFO - Epoch(train) [9][80/940] lr: 1.0000e-02 eta: 19:44:54 time: 0.7794 data_time: 0.1828 memory: 22701 grad_norm: 4.4727 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8012 loss: 1.8012 2022/09/05 10:36:20 - mmengine - INFO - Epoch(train) [9][100/940] lr: 1.0000e-02 eta: 19:45:45 time: 1.1191 data_time: 0.2783 memory: 22701 grad_norm: 4.5181 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9766 loss: 1.9766 2022/09/05 10:36:37 - mmengine - INFO - Epoch(train) [9][120/940] lr: 1.0000e-02 eta: 19:45:32 time: 0.8423 data_time: 0.0478 memory: 22701 grad_norm: 4.5606 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9929 loss: 1.9929 2022/09/05 10:36:57 - mmengine - INFO - Epoch(train) [9][140/940] lr: 1.0000e-02 eta: 19:45:53 time: 0.9905 data_time: 0.0248 memory: 22701 grad_norm: 4.5720 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0117 loss: 2.0117 2022/09/05 10:37:12 - mmengine - INFO - Epoch(train) [9][160/940] lr: 1.0000e-02 eta: 19:45:23 time: 0.7602 data_time: 0.0265 memory: 22701 grad_norm: 4.5194 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7995 loss: 1.7995 2022/09/05 10:37:30 - mmengine - INFO - Epoch(train) [9][180/940] lr: 1.0000e-02 eta: 19:45:25 time: 0.9063 data_time: 0.0372 memory: 22701 grad_norm: 4.4968 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0103 loss: 2.0103 2022/09/05 10:37:46 - mmengine - INFO - Epoch(train) [9][200/940] lr: 1.0000e-02 eta: 19:45:00 time: 0.7897 data_time: 0.0228 memory: 22701 grad_norm: 4.6083 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0489 loss: 2.0489 2022/09/05 10:38:06 - mmengine - INFO - Epoch(train) [9][220/940] lr: 1.0000e-02 eta: 19:45:31 time: 1.0367 data_time: 0.0243 memory: 22701 grad_norm: 4.5523 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8777 loss: 1.8777 2022/09/05 10:38:21 - mmengine - INFO - Epoch(train) [9][240/940] lr: 1.0000e-02 eta: 19:44:49 time: 0.7105 data_time: 0.0205 memory: 22701 grad_norm: 4.5992 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8516 loss: 1.8516 2022/09/05 10:38:40 - mmengine - INFO - Epoch(train) [9][260/940] lr: 1.0000e-02 eta: 19:45:06 time: 0.9753 data_time: 0.0241 memory: 22701 grad_norm: 4.5225 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8429 loss: 1.8429 2022/09/05 10:38:54 - mmengine - INFO - Epoch(train) [9][280/940] lr: 1.0000e-02 eta: 19:44:22 time: 0.6991 data_time: 0.0214 memory: 22701 grad_norm: 4.6124 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9777 loss: 1.9777 2022/09/05 10:39:13 - mmengine - INFO - Epoch(train) [9][300/940] lr: 1.0000e-02 eta: 19:44:27 time: 0.9221 data_time: 0.0221 memory: 22701 grad_norm: 4.6011 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 1.9991 loss: 1.9991 2022/09/05 10:39:27 - mmengine - INFO - Epoch(train) [9][320/940] lr: 1.0000e-02 eta: 19:43:44 time: 0.7030 data_time: 0.0256 memory: 22701 grad_norm: 4.5298 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8684 loss: 1.8684 2022/09/05 10:39:46 - mmengine - INFO - Epoch(train) [9][340/940] lr: 1.0000e-02 eta: 19:44:01 time: 0.9752 data_time: 0.0283 memory: 22701 grad_norm: 4.5676 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8567 loss: 1.8567 2022/09/05 10:40:04 - mmengine - INFO - Epoch(train) [9][360/940] lr: 1.0000e-02 eta: 19:43:57 time: 0.8841 data_time: 0.0217 memory: 22701 grad_norm: 4.5373 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7839 loss: 1.7839 2022/09/05 10:40:19 - mmengine - INFO - Epoch(train) [9][380/940] lr: 1.0000e-02 eta: 19:43:27 time: 0.7638 data_time: 0.0285 memory: 22701 grad_norm: 4.4936 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9547 loss: 1.9547 2022/09/05 10:40:36 - mmengine - INFO - Epoch(train) [9][400/940] lr: 1.0000e-02 eta: 19:43:18 time: 0.8580 data_time: 0.0243 memory: 22701 grad_norm: 4.5172 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 1.8828 loss: 1.8828 2022/09/05 10:40:52 - mmengine - INFO - Epoch(train) [9][420/940] lr: 1.0000e-02 eta: 19:42:54 time: 0.7892 data_time: 0.0242 memory: 22701 grad_norm: 4.4941 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8026 loss: 1.8026 2022/09/05 10:41:10 - mmengine - INFO - Epoch(train) [9][440/940] lr: 1.0000e-02 eta: 19:42:55 time: 0.9087 data_time: 0.0304 memory: 22701 grad_norm: 4.5522 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9960 loss: 1.9960 2022/09/05 10:41:25 - mmengine - INFO - Epoch(train) [9][460/940] lr: 1.0000e-02 eta: 19:42:23 time: 0.7513 data_time: 0.0339 memory: 22701 grad_norm: 4.5456 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9057 loss: 1.9057 2022/09/05 10:41:45 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:41:45 - mmengine - INFO - Epoch(train) [9][480/940] lr: 1.0000e-02 eta: 19:42:40 time: 0.9779 data_time: 0.0347 memory: 22701 grad_norm: 4.5427 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8671 loss: 1.8671 2022/09/05 10:42:05 - mmengine - INFO - Epoch(train) [9][500/940] lr: 1.0000e-02 eta: 19:43:01 time: 1.0014 data_time: 0.1992 memory: 22701 grad_norm: 4.5763 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7683 loss: 1.7683 2022/09/05 10:42:24 - mmengine - INFO - Epoch(train) [9][520/940] lr: 1.0000e-02 eta: 19:43:13 time: 0.9600 data_time: 0.0432 memory: 22701 grad_norm: 4.5368 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8838 loss: 1.8838 2022/09/05 10:42:39 - mmengine - INFO - Epoch(train) [9][540/940] lr: 1.0000e-02 eta: 19:42:39 time: 0.7453 data_time: 0.0407 memory: 22701 grad_norm: 4.5302 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.9561 loss: 1.9561 2022/09/05 10:42:54 - mmengine - INFO - Epoch(train) [9][560/940] lr: 1.0000e-02 eta: 19:42:10 time: 0.7643 data_time: 0.0203 memory: 22701 grad_norm: 4.5542 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8357 loss: 1.8357 2022/09/05 10:43:08 - mmengine - INFO - Epoch(train) [9][580/940] lr: 1.0000e-02 eta: 19:41:27 time: 0.7026 data_time: 0.0356 memory: 22701 grad_norm: 4.6342 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9519 loss: 1.9519 2022/09/05 10:43:24 - mmengine - INFO - Epoch(train) [9][600/940] lr: 1.0000e-02 eta: 19:41:02 time: 0.7851 data_time: 0.0312 memory: 22701 grad_norm: 4.5870 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9304 loss: 1.9304 2022/09/05 10:43:40 - mmengine - INFO - Epoch(train) [9][620/940] lr: 1.0000e-02 eta: 19:40:41 time: 0.8011 data_time: 0.2883 memory: 22701 grad_norm: 4.4824 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8943 loss: 1.8943 2022/09/05 10:43:55 - mmengine - INFO - Epoch(train) [9][640/940] lr: 1.0000e-02 eta: 19:40:07 time: 0.7447 data_time: 0.2048 memory: 22701 grad_norm: 4.5338 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7915 loss: 1.7915 2022/09/05 10:44:10 - mmengine - INFO - Epoch(train) [9][660/940] lr: 1.0000e-02 eta: 19:39:37 time: 0.7577 data_time: 0.1202 memory: 22701 grad_norm: 4.5970 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.7666 loss: 1.7666 2022/09/05 10:44:25 - mmengine - INFO - Epoch(train) [9][680/940] lr: 1.0000e-02 eta: 19:39:00 time: 0.7278 data_time: 0.0988 memory: 22701 grad_norm: 4.6175 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8604 loss: 1.8604 2022/09/05 10:44:40 - mmengine - INFO - Epoch(train) [9][700/940] lr: 1.0000e-02 eta: 19:38:32 time: 0.7687 data_time: 0.1405 memory: 22701 grad_norm: 4.6384 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8787 loss: 1.8787 2022/09/05 10:44:55 - mmengine - INFO - Epoch(train) [9][720/940] lr: 1.0000e-02 eta: 19:37:56 time: 0.7322 data_time: 0.0940 memory: 22701 grad_norm: 4.5099 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.8684 loss: 1.8684 2022/09/05 10:45:10 - mmengine - INFO - Epoch(train) [9][740/940] lr: 1.0000e-02 eta: 19:37:25 time: 0.7532 data_time: 0.1880 memory: 22701 grad_norm: 4.7173 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1027 loss: 2.1027 2022/09/05 10:45:25 - mmengine - INFO - Epoch(train) [9][760/940] lr: 1.0000e-02 eta: 19:36:59 time: 0.7766 data_time: 0.1135 memory: 22701 grad_norm: 4.6280 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.9878 loss: 1.9878 2022/09/05 10:45:40 - mmengine - INFO - Epoch(train) [9][780/940] lr: 1.0000e-02 eta: 19:36:24 time: 0.7344 data_time: 0.1822 memory: 22701 grad_norm: 4.6940 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9048 loss: 1.9048 2022/09/05 10:45:59 - mmengine - INFO - Epoch(train) [9][800/940] lr: 1.0000e-02 eta: 19:36:29 time: 0.9308 data_time: 0.3055 memory: 22701 grad_norm: 4.5556 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.9693 loss: 1.9693 2022/09/05 10:46:13 - mmengine - INFO - Epoch(train) [9][820/940] lr: 1.0000e-02 eta: 19:35:50 time: 0.7116 data_time: 0.1402 memory: 22701 grad_norm: 4.5752 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.0009 loss: 2.0009 2022/09/05 10:46:28 - mmengine - INFO - Epoch(train) [9][840/940] lr: 1.0000e-02 eta: 19:35:19 time: 0.7553 data_time: 0.1448 memory: 22701 grad_norm: 4.5762 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9645 loss: 1.9645 2022/09/05 10:46:42 - mmengine - INFO - Epoch(train) [9][860/940] lr: 1.0000e-02 eta: 19:34:37 time: 0.6969 data_time: 0.0572 memory: 22701 grad_norm: 4.5363 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.8395 loss: 1.8395 2022/09/05 10:46:58 - mmengine - INFO - Epoch(train) [9][880/940] lr: 1.0000e-02 eta: 19:34:17 time: 0.8082 data_time: 0.0391 memory: 22701 grad_norm: 4.5764 top1_acc: 0.3438 top5_acc: 0.7812 loss_cls: 1.9587 loss: 1.9587 2022/09/05 10:47:13 - mmengine - INFO - Epoch(train) [9][900/940] lr: 1.0000e-02 eta: 19:33:49 time: 0.7637 data_time: 0.0875 memory: 22701 grad_norm: 4.5617 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8095 loss: 1.8095 2022/09/05 10:47:31 - mmengine - INFO - Epoch(train) [9][920/940] lr: 1.0000e-02 eta: 19:33:41 time: 0.8654 data_time: 0.0309 memory: 22701 grad_norm: 4.5982 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 2.0007 loss: 2.0007 2022/09/05 10:47:43 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:47:43 - mmengine - INFO - Epoch(train) [9][940/940] lr: 1.0000e-02 eta: 19:32:47 time: 0.6375 data_time: 0.0405 memory: 22701 grad_norm: 4.9770 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 2.0671 loss: 2.0671 2022/09/05 10:47:43 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/09/05 10:47:59 - mmengine - INFO - Epoch(val) [9][20/78] eta: 0:00:41 time: 0.7119 data_time: 0.5956 memory: 2247 2022/09/05 10:48:08 - mmengine - INFO - Epoch(val) [9][40/78] eta: 0:00:16 time: 0.4346 data_time: 0.3172 memory: 2247 2022/09/05 10:48:21 - mmengine - INFO - Epoch(val) [9][60/78] eta: 0:00:12 time: 0.6695 data_time: 0.5524 memory: 2247 2022/09/05 10:48:31 - mmengine - INFO - Epoch(val) [9][78/78] acc/top1: 0.5968 acc/top5: 0.8331 acc/mean1: 0.5965 2022/09/05 10:48:53 - mmengine - INFO - Epoch(train) [10][20/940] lr: 1.0000e-02 eta: 19:33:24 time: 1.0858 data_time: 0.5474 memory: 22701 grad_norm: 4.5578 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9792 loss: 1.9792 2022/09/05 10:49:08 - mmengine - INFO - Epoch(train) [10][40/940] lr: 1.0000e-02 eta: 19:32:54 time: 0.7575 data_time: 0.0752 memory: 22701 grad_norm: 4.6181 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.0573 loss: 2.0573 2022/09/05 10:49:26 - mmengine - INFO - Epoch(train) [10][60/940] lr: 1.0000e-02 eta: 19:32:57 time: 0.9214 data_time: 0.0919 memory: 22701 grad_norm: 4.4930 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9917 loss: 1.9917 2022/09/05 10:49:40 - mmengine - INFO - Epoch(train) [10][80/940] lr: 1.0000e-02 eta: 19:32:17 time: 0.7035 data_time: 0.2164 memory: 22701 grad_norm: 4.4493 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8795 loss: 1.8795 2022/09/05 10:49:58 - mmengine - INFO - Epoch(train) [10][100/940] lr: 1.0000e-02 eta: 19:32:12 time: 0.8844 data_time: 0.4192 memory: 22701 grad_norm: 4.5272 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7761 loss: 1.7761 2022/09/05 10:50:12 - mmengine - INFO - Epoch(train) [10][120/940] lr: 1.0000e-02 eta: 19:31:31 time: 0.6956 data_time: 0.2936 memory: 22701 grad_norm: 4.5337 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8671 loss: 1.8671 2022/09/05 10:50:29 - mmengine - INFO - Epoch(train) [10][140/940] lr: 1.0000e-02 eta: 19:31:19 time: 0.8455 data_time: 0.3930 memory: 22701 grad_norm: 4.5008 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.9524 loss: 1.9524 2022/09/05 10:50:42 - mmengine - INFO - Epoch(train) [10][160/940] lr: 1.0000e-02 eta: 19:30:26 time: 0.6412 data_time: 0.2427 memory: 22701 grad_norm: 4.5674 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8365 loss: 1.8365 2022/09/05 10:50:58 - mmengine - INFO - Epoch(train) [10][180/940] lr: 1.0000e-02 eta: 19:30:12 time: 0.8318 data_time: 0.3912 memory: 22701 grad_norm: 4.5622 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0228 loss: 2.0228 2022/09/05 10:51:12 - mmengine - INFO - Epoch(train) [10][200/940] lr: 1.0000e-02 eta: 19:29:27 time: 0.6795 data_time: 0.2249 memory: 22701 grad_norm: 4.5270 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8143 loss: 1.8143 2022/09/05 10:51:31 - mmengine - INFO - Epoch(train) [10][220/940] lr: 1.0000e-02 eta: 19:29:40 time: 0.9711 data_time: 0.3605 memory: 22701 grad_norm: 4.5963 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9359 loss: 1.9359 2022/09/05 10:51:46 - mmengine - INFO - Epoch(train) [10][240/940] lr: 1.0000e-02 eta: 19:29:03 time: 0.7167 data_time: 0.2404 memory: 22701 grad_norm: 4.5945 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.9384 loss: 1.9384 2022/09/05 10:52:05 - mmengine - INFO - Epoch(train) [10][260/940] lr: 1.0000e-02 eta: 19:29:17 time: 0.9811 data_time: 0.4405 memory: 22701 grad_norm: 4.4928 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8764 loss: 1.8764 2022/09/05 10:52:21 - mmengine - INFO - Epoch(train) [10][280/940] lr: 1.0000e-02 eta: 19:28:58 time: 0.8093 data_time: 0.3749 memory: 22701 grad_norm: 4.6391 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9714 loss: 1.9714 2022/09/05 10:52:38 - mmengine - INFO - Epoch(train) [10][300/940] lr: 1.0000e-02 eta: 19:28:47 time: 0.8477 data_time: 0.4084 memory: 22701 grad_norm: 4.5172 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8298 loss: 1.8298 2022/09/05 10:52:52 - mmengine - INFO - Epoch(train) [10][320/940] lr: 1.0000e-02 eta: 19:28:04 time: 0.6879 data_time: 0.2747 memory: 22701 grad_norm: 4.5284 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0003 loss: 2.0003 2022/09/05 10:53:08 - mmengine - INFO - Epoch(train) [10][340/940] lr: 1.0000e-02 eta: 19:27:42 time: 0.7953 data_time: 0.3605 memory: 22701 grad_norm: 4.5603 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8464 loss: 1.8464 2022/09/05 10:53:23 - mmengine - INFO - Epoch(train) [10][360/940] lr: 1.0000e-02 eta: 19:27:10 time: 0.7413 data_time: 0.2269 memory: 22701 grad_norm: 4.5463 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8993 loss: 1.8993 2022/09/05 10:53:40 - mmengine - INFO - Epoch(train) [10][380/940] lr: 1.0000e-02 eta: 19:27:02 time: 0.8673 data_time: 0.4363 memory: 22701 grad_norm: 4.5152 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8219 loss: 1.8219 2022/09/05 10:53:57 - mmengine - INFO - Epoch(train) [10][400/940] lr: 1.0000e-02 eta: 19:26:46 time: 0.8247 data_time: 0.2430 memory: 22701 grad_norm: 4.5264 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.8872 loss: 1.8872 2022/09/05 10:54:16 - mmengine - INFO - Epoch(train) [10][420/940] lr: 1.0000e-02 eta: 19:26:57 time: 0.9646 data_time: 0.1189 memory: 22701 grad_norm: 4.5816 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8835 loss: 1.8835 2022/09/05 10:54:31 - mmengine - INFO - Epoch(train) [10][440/940] lr: 1.0000e-02 eta: 19:26:26 time: 0.7447 data_time: 0.0216 memory: 22701 grad_norm: 4.5555 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 1.9192 loss: 1.9192 2022/09/05 10:54:51 - mmengine - INFO - Epoch(train) [10][460/940] lr: 1.0000e-02 eta: 19:26:45 time: 1.0081 data_time: 0.3576 memory: 22701 grad_norm: 4.5410 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0625 loss: 2.0625 2022/09/05 10:55:06 - mmengine - INFO - Epoch(train) [10][480/940] lr: 1.0000e-02 eta: 19:26:16 time: 0.7565 data_time: 0.2745 memory: 22701 grad_norm: 4.5661 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8905 loss: 1.8905 2022/09/05 10:55:23 - mmengine - INFO - Epoch(train) [10][500/940] lr: 1.0000e-02 eta: 19:26:02 time: 0.8361 data_time: 0.0883 memory: 22701 grad_norm: 4.6482 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8744 loss: 1.8744 2022/09/05 10:55:37 - mmengine - INFO - Epoch(train) [10][520/940] lr: 1.0000e-02 eta: 19:25:27 time: 0.7279 data_time: 0.2220 memory: 22701 grad_norm: 4.5768 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.9249 loss: 1.9249 2022/09/05 10:55:54 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 10:55:54 - mmengine - INFO - Epoch(train) [10][540/940] lr: 1.0000e-02 eta: 19:25:09 time: 0.8120 data_time: 0.2997 memory: 22701 grad_norm: 4.5792 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8917 loss: 1.8917 2022/09/05 10:56:08 - mmengine - INFO - Epoch(train) [10][560/940] lr: 1.0000e-02 eta: 19:24:34 time: 0.7212 data_time: 0.3193 memory: 22701 grad_norm: 4.5651 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1321 loss: 2.1321 2022/09/05 10:56:27 - mmengine - INFO - Epoch(train) [10][580/940] lr: 1.0000e-02 eta: 19:24:36 time: 0.9232 data_time: 0.5198 memory: 22701 grad_norm: 4.7341 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.9440 loss: 1.9440 2022/09/05 10:56:40 - mmengine - INFO - Epoch(train) [10][600/940] lr: 1.0000e-02 eta: 19:23:53 time: 0.6782 data_time: 0.2776 memory: 22701 grad_norm: 4.6672 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0475 loss: 2.0475 2022/09/05 10:56:56 - mmengine - INFO - Epoch(train) [10][620/940] lr: 1.0000e-02 eta: 19:23:29 time: 0.7855 data_time: 0.3913 memory: 22701 grad_norm: 4.5560 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9397 loss: 1.9397 2022/09/05 10:57:09 - mmengine - INFO - Epoch(train) [10][640/940] lr: 1.0000e-02 eta: 19:22:39 time: 0.6429 data_time: 0.2466 memory: 22701 grad_norm: 4.5966 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 2.0023 loss: 2.0023 2022/09/05 10:57:24 - mmengine - INFO - Epoch(train) [10][660/940] lr: 1.0000e-02 eta: 19:22:15 time: 0.7789 data_time: 0.4030 memory: 22701 grad_norm: 4.6517 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8735 loss: 1.8735 2022/09/05 10:57:38 - mmengine - INFO - Epoch(train) [10][680/940] lr: 1.0000e-02 eta: 19:21:37 time: 0.7052 data_time: 0.3022 memory: 22701 grad_norm: 4.6235 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9057 loss: 1.9057 2022/09/05 10:57:56 - mmengine - INFO - Epoch(train) [10][700/940] lr: 1.0000e-02 eta: 19:21:27 time: 0.8573 data_time: 0.4503 memory: 22701 grad_norm: 4.5887 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8109 loss: 1.8109 2022/09/05 10:58:09 - mmengine - INFO - Epoch(train) [10][720/940] lr: 1.0000e-02 eta: 19:20:42 time: 0.6677 data_time: 0.2728 memory: 22701 grad_norm: 4.6122 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8648 loss: 1.8648 2022/09/05 10:58:26 - mmengine - INFO - Epoch(train) [10][740/940] lr: 1.0000e-02 eta: 19:20:34 time: 0.8656 data_time: 0.4779 memory: 22701 grad_norm: 4.5646 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8605 loss: 1.8605 2022/09/05 10:58:40 - mmengine - INFO - Epoch(train) [10][760/940] lr: 1.0000e-02 eta: 19:19:56 time: 0.7015 data_time: 0.3120 memory: 22701 grad_norm: 4.6056 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8984 loss: 1.8984 2022/09/05 10:58:58 - mmengine - INFO - Epoch(train) [10][780/940] lr: 1.0000e-02 eta: 19:19:49 time: 0.8762 data_time: 0.4752 memory: 22701 grad_norm: 4.6434 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.9797 loss: 1.9797 2022/09/05 10:59:12 - mmengine - INFO - Epoch(train) [10][800/940] lr: 1.0000e-02 eta: 19:19:10 time: 0.6966 data_time: 0.2860 memory: 22701 grad_norm: 4.5650 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.8674 loss: 1.8674 2022/09/05 10:59:28 - mmengine - INFO - Epoch(train) [10][820/940] lr: 1.0000e-02 eta: 19:18:56 time: 0.8326 data_time: 0.2818 memory: 22701 grad_norm: 4.6392 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8551 loss: 1.8551 2022/09/05 10:59:45 - mmengine - INFO - Epoch(train) [10][840/940] lr: 1.0000e-02 eta: 19:18:41 time: 0.8286 data_time: 0.1022 memory: 22701 grad_norm: 4.6476 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8259 loss: 1.8259 2022/09/05 11:00:00 - mmengine - INFO - Epoch(train) [10][860/940] lr: 1.0000e-02 eta: 19:18:14 time: 0.7633 data_time: 0.0983 memory: 22701 grad_norm: 4.6517 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9121 loss: 1.9121 2022/09/05 11:00:16 - mmengine - INFO - Epoch(train) [10][880/940] lr: 1.0000e-02 eta: 19:17:55 time: 0.8038 data_time: 0.0863 memory: 22701 grad_norm: 4.5601 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9821 loss: 1.9821 2022/09/05 11:00:35 - mmengine - INFO - Epoch(train) [10][900/940] lr: 1.0000e-02 eta: 19:17:55 time: 0.9147 data_time: 0.5003 memory: 22701 grad_norm: 4.5367 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9530 loss: 1.9530 2022/09/05 11:00:48 - mmengine - INFO - Epoch(train) [10][920/940] lr: 1.0000e-02 eta: 19:17:09 time: 0.6572 data_time: 0.2586 memory: 22701 grad_norm: 4.6495 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9241 loss: 1.9241 2022/09/05 11:01:05 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:01:05 - mmengine - INFO - Epoch(train) [10][940/940] lr: 1.0000e-02 eta: 19:17:04 time: 0.8825 data_time: 0.4883 memory: 22701 grad_norm: 4.9097 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 1.9079 loss: 1.9079 2022/09/05 11:01:19 - mmengine - INFO - Epoch(val) [10][20/78] eta: 0:00:39 time: 0.6876 data_time: 0.5672 memory: 2247 2022/09/05 11:01:28 - mmengine - INFO - Epoch(val) [10][40/78] eta: 0:00:16 time: 0.4420 data_time: 0.3245 memory: 2247 2022/09/05 11:01:41 - mmengine - INFO - Epoch(val) [10][60/78] eta: 0:00:11 time: 0.6480 data_time: 0.5297 memory: 2247 2022/09/05 11:01:52 - mmengine - INFO - Epoch(val) [10][78/78] acc/top1: 0.6092 acc/top5: 0.8362 acc/mean1: 0.6089 2022/09/05 11:01:52 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_8.pth is removed 2022/09/05 11:01:52 - mmengine - INFO - The best checkpoint with 0.6092 acc/top1 at 11 epoch is saved to best_acc/top1_epoch_11.pth. 2022/09/05 11:02:12 - mmengine - INFO - Epoch(train) [11][20/940] lr: 1.0000e-02 eta: 19:17:13 time: 0.9621 data_time: 0.5085 memory: 22701 grad_norm: 4.5021 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8760 loss: 1.8760 2022/09/05 11:02:25 - mmengine - INFO - Epoch(train) [11][40/940] lr: 1.0000e-02 eta: 19:16:27 time: 0.6548 data_time: 0.0997 memory: 22701 grad_norm: 4.5389 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8687 loss: 1.8687 2022/09/05 11:02:42 - mmengine - INFO - Epoch(train) [11][60/940] lr: 1.0000e-02 eta: 19:16:16 time: 0.8541 data_time: 0.0296 memory: 22701 grad_norm: 4.4812 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.7369 loss: 1.7369 2022/09/05 11:02:56 - mmengine - INFO - Epoch(train) [11][80/940] lr: 1.0000e-02 eta: 19:15:36 time: 0.6872 data_time: 0.0202 memory: 22701 grad_norm: 4.5372 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8238 loss: 1.8238 2022/09/05 11:03:10 - mmengine - INFO - Epoch(train) [11][100/940] lr: 1.0000e-02 eta: 19:15:05 time: 0.7389 data_time: 0.0259 memory: 22701 grad_norm: 4.6775 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9338 loss: 1.9338 2022/09/05 11:03:24 - mmengine - INFO - Epoch(train) [11][120/940] lr: 1.0000e-02 eta: 19:14:19 time: 0.6537 data_time: 0.0446 memory: 22701 grad_norm: 4.6309 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7866 loss: 1.7866 2022/09/05 11:03:43 - mmengine - INFO - Epoch(train) [11][140/940] lr: 1.0000e-02 eta: 19:14:30 time: 0.9720 data_time: 0.1073 memory: 22701 grad_norm: 4.6692 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8442 loss: 1.8442 2022/09/05 11:03:57 - mmengine - INFO - Epoch(train) [11][160/940] lr: 1.0000e-02 eta: 19:13:55 time: 0.7150 data_time: 0.0682 memory: 22701 grad_norm: 4.4856 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8302 loss: 1.8302 2022/09/05 11:04:14 - mmengine - INFO - Epoch(train) [11][180/940] lr: 1.0000e-02 eta: 19:13:42 time: 0.8408 data_time: 0.2598 memory: 22701 grad_norm: 4.5023 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7343 loss: 1.7343 2022/09/05 11:04:29 - mmengine - INFO - Epoch(train) [11][200/940] lr: 1.0000e-02 eta: 19:13:11 time: 0.7339 data_time: 0.2308 memory: 22701 grad_norm: 4.6006 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7841 loss: 1.7841 2022/09/05 11:04:46 - mmengine - INFO - Epoch(train) [11][220/940] lr: 1.0000e-02 eta: 19:13:00 time: 0.8536 data_time: 0.2039 memory: 22701 grad_norm: 4.5022 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9091 loss: 1.9091 2022/09/05 11:05:00 - mmengine - INFO - Epoch(train) [11][240/940] lr: 1.0000e-02 eta: 19:12:29 time: 0.7332 data_time: 0.1302 memory: 22701 grad_norm: 4.5671 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9452 loss: 1.9452 2022/09/05 11:05:17 - mmengine - INFO - Epoch(train) [11][260/940] lr: 1.0000e-02 eta: 19:12:15 time: 0.8340 data_time: 0.1551 memory: 22701 grad_norm: 4.5441 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8218 loss: 1.8218 2022/09/05 11:05:31 - mmengine - INFO - Epoch(train) [11][280/940] lr: 1.0000e-02 eta: 19:11:35 time: 0.6851 data_time: 0.0833 memory: 22701 grad_norm: 4.5960 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7741 loss: 1.7741 2022/09/05 11:05:48 - mmengine - INFO - Epoch(train) [11][300/940] lr: 1.0000e-02 eta: 19:11:28 time: 0.8730 data_time: 0.0755 memory: 22701 grad_norm: 4.5353 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6939 loss: 1.6939 2022/09/05 11:06:02 - mmengine - INFO - Epoch(train) [11][320/940] lr: 1.0000e-02 eta: 19:10:51 time: 0.7011 data_time: 0.0760 memory: 22701 grad_norm: 4.5523 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8841 loss: 1.8841 2022/09/05 11:06:20 - mmengine - INFO - Epoch(train) [11][340/940] lr: 1.0000e-02 eta: 19:10:42 time: 0.8605 data_time: 0.2146 memory: 22701 grad_norm: 4.5435 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7867 loss: 1.7867 2022/09/05 11:06:33 - mmengine - INFO - Epoch(train) [11][360/940] lr: 1.0000e-02 eta: 19:10:04 time: 0.6944 data_time: 0.2747 memory: 22701 grad_norm: 4.5584 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8096 loss: 1.8096 2022/09/05 11:06:50 - mmengine - INFO - Epoch(train) [11][380/940] lr: 1.0000e-02 eta: 19:09:47 time: 0.8197 data_time: 0.4191 memory: 22701 grad_norm: 4.5220 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9395 loss: 1.9395 2022/09/05 11:07:03 - mmengine - INFO - Epoch(train) [11][400/940] lr: 1.0000e-02 eta: 19:09:05 time: 0.6668 data_time: 0.2774 memory: 22701 grad_norm: 4.5506 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8580 loss: 1.8580 2022/09/05 11:07:19 - mmengine - INFO - Epoch(train) [11][420/940] lr: 1.0000e-02 eta: 19:08:48 time: 0.8161 data_time: 0.4145 memory: 22701 grad_norm: 4.5981 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7977 loss: 1.7977 2022/09/05 11:07:34 - mmengine - INFO - Epoch(train) [11][440/940] lr: 1.0000e-02 eta: 19:08:14 time: 0.7130 data_time: 0.3081 memory: 22701 grad_norm: 4.5887 top1_acc: 0.5938 top5_acc: 0.6562 loss_cls: 1.8426 loss: 1.8426 2022/09/05 11:07:52 - mmengine - INFO - Epoch(train) [11][460/940] lr: 1.0000e-02 eta: 19:08:13 time: 0.9123 data_time: 0.5138 memory: 22701 grad_norm: 4.5696 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8065 loss: 1.8065 2022/09/05 11:08:08 - mmengine - INFO - Epoch(train) [11][480/940] lr: 1.0000e-02 eta: 19:07:54 time: 0.7997 data_time: 0.3845 memory: 22701 grad_norm: 4.5772 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8386 loss: 1.8386 2022/09/05 11:08:27 - mmengine - INFO - Epoch(train) [11][500/940] lr: 1.0000e-02 eta: 19:07:56 time: 0.9299 data_time: 0.5482 memory: 22701 grad_norm: 4.4914 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.9414 loss: 1.9414 2022/09/05 11:08:42 - mmengine - INFO - Epoch(train) [11][520/940] lr: 1.0000e-02 eta: 19:07:31 time: 0.7704 data_time: 0.3589 memory: 22701 grad_norm: 4.5847 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.9338 loss: 1.9338 2022/09/05 11:09:03 - mmengine - INFO - Epoch(train) [11][540/940] lr: 1.0000e-02 eta: 19:07:52 time: 1.0382 data_time: 0.4530 memory: 22701 grad_norm: 4.4564 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8558 loss: 1.8558 2022/09/05 11:09:18 - mmengine - INFO - Epoch(train) [11][560/940] lr: 1.0000e-02 eta: 19:07:29 time: 0.7802 data_time: 0.3631 memory: 22701 grad_norm: 4.5737 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9401 loss: 1.9401 2022/09/05 11:09:37 - mmengine - INFO - Epoch(train) [11][580/940] lr: 1.0000e-02 eta: 19:07:27 time: 0.9043 data_time: 0.4643 memory: 22701 grad_norm: 4.5481 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7706 loss: 1.7706 2022/09/05 11:09:52 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:09:53 - mmengine - INFO - Epoch(train) [11][600/940] lr: 1.0000e-02 eta: 19:07:08 time: 0.8014 data_time: 0.2986 memory: 22701 grad_norm: 4.6007 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8341 loss: 1.8341 2022/09/05 11:10:10 - mmengine - INFO - Epoch(train) [11][620/940] lr: 1.0000e-02 eta: 19:07:04 time: 0.8946 data_time: 0.0582 memory: 22701 grad_norm: 4.6552 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8013 loss: 1.8013 2022/09/05 11:10:25 - mmengine - INFO - Epoch(train) [11][640/940] lr: 1.0000e-02 eta: 19:06:29 time: 0.7115 data_time: 0.0247 memory: 22701 grad_norm: 4.6067 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8254 loss: 1.8254 2022/09/05 11:10:42 - mmengine - INFO - Epoch(train) [11][660/940] lr: 1.0000e-02 eta: 19:06:24 time: 0.8865 data_time: 0.0288 memory: 22701 grad_norm: 4.5598 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9046 loss: 1.9046 2022/09/05 11:10:55 - mmengine - INFO - Epoch(train) [11][680/940] lr: 1.0000e-02 eta: 19:05:36 time: 0.6297 data_time: 0.0207 memory: 22701 grad_norm: 4.6759 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8714 loss: 1.8714 2022/09/05 11:11:10 - mmengine - INFO - Epoch(train) [11][700/940] lr: 1.0000e-02 eta: 19:05:11 time: 0.7661 data_time: 0.0291 memory: 22701 grad_norm: 4.6223 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9063 loss: 1.9063 2022/09/05 11:11:23 - mmengine - INFO - Epoch(train) [11][720/940] lr: 1.0000e-02 eta: 19:04:22 time: 0.6204 data_time: 0.0355 memory: 22701 grad_norm: 4.5342 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8867 loss: 1.8867 2022/09/05 11:11:40 - mmengine - INFO - Epoch(train) [11][740/940] lr: 1.0000e-02 eta: 19:04:17 time: 0.8895 data_time: 0.0299 memory: 22701 grad_norm: 4.5522 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8407 loss: 1.8407 2022/09/05 11:11:55 - mmengine - INFO - Epoch(train) [11][760/940] lr: 1.0000e-02 eta: 19:03:43 time: 0.7115 data_time: 0.0248 memory: 22701 grad_norm: 4.5222 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8372 loss: 1.8372 2022/09/05 11:12:13 - mmengine - INFO - Epoch(train) [11][780/940] lr: 1.0000e-02 eta: 19:03:39 time: 0.8914 data_time: 0.0313 memory: 22701 grad_norm: 4.6168 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0441 loss: 2.0441 2022/09/05 11:12:29 - mmengine - INFO - Epoch(train) [11][800/940] lr: 1.0000e-02 eta: 19:03:21 time: 0.8130 data_time: 0.0215 memory: 22701 grad_norm: 4.5854 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.9585 loss: 1.9585 2022/09/05 11:12:46 - mmengine - INFO - Epoch(train) [11][820/940] lr: 1.0000e-02 eta: 19:03:12 time: 0.8642 data_time: 0.0262 memory: 22701 grad_norm: 4.6086 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9942 loss: 1.9942 2022/09/05 11:13:00 - mmengine - INFO - Epoch(train) [11][840/940] lr: 1.0000e-02 eta: 19:02:39 time: 0.7148 data_time: 0.0254 memory: 22701 grad_norm: 4.5924 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8961 loss: 1.8961 2022/09/05 11:13:18 - mmengine - INFO - Epoch(train) [11][860/940] lr: 1.0000e-02 eta: 19:02:28 time: 0.8529 data_time: 0.0289 memory: 22701 grad_norm: 4.5798 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.8845 loss: 1.8845 2022/09/05 11:13:31 - mmengine - INFO - Epoch(train) [11][880/940] lr: 1.0000e-02 eta: 19:01:51 time: 0.6890 data_time: 0.0330 memory: 22701 grad_norm: 4.6829 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8535 loss: 1.8535 2022/09/05 11:13:50 - mmengine - INFO - Epoch(train) [11][900/940] lr: 1.0000e-02 eta: 19:01:52 time: 0.9257 data_time: 0.0260 memory: 22701 grad_norm: 4.5725 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9078 loss: 1.9078 2022/09/05 11:14:04 - mmengine - INFO - Epoch(train) [11][920/940] lr: 1.0000e-02 eta: 19:01:22 time: 0.7329 data_time: 0.0244 memory: 22701 grad_norm: 4.5660 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9277 loss: 1.9277 2022/09/05 11:14:18 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:14:18 - mmengine - INFO - Epoch(train) [11][940/940] lr: 1.0000e-02 eta: 19:00:40 time: 0.6597 data_time: 0.0225 memory: 22701 grad_norm: 4.9088 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.8829 loss: 1.8829 2022/09/05 11:14:31 - mmengine - INFO - Epoch(val) [11][20/78] eta: 0:00:39 time: 0.6842 data_time: 0.5628 memory: 2247 2022/09/05 11:14:41 - mmengine - INFO - Epoch(val) [11][40/78] eta: 0:00:17 time: 0.4708 data_time: 0.3537 memory: 2247 2022/09/05 11:14:53 - mmengine - INFO - Epoch(val) [11][60/78] eta: 0:00:11 time: 0.6282 data_time: 0.5085 memory: 2247 2022/09/05 11:15:04 - mmengine - INFO - Epoch(val) [11][78/78] acc/top1: 0.6076 acc/top5: 0.8370 acc/mean1: 0.6075 2022/09/05 11:15:25 - mmengine - INFO - Epoch(train) [12][20/940] lr: 1.0000e-02 eta: 19:00:59 time: 1.0394 data_time: 0.6186 memory: 22701 grad_norm: 4.4561 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8303 loss: 1.8303 2022/09/05 11:15:39 - mmengine - INFO - Epoch(train) [12][40/940] lr: 1.0000e-02 eta: 19:00:19 time: 0.6737 data_time: 0.2807 memory: 22701 grad_norm: 4.6231 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8599 loss: 1.8599 2022/09/05 11:15:57 - mmengine - INFO - Epoch(train) [12][60/940] lr: 1.0000e-02 eta: 19:00:15 time: 0.8958 data_time: 0.2291 memory: 22701 grad_norm: 4.5464 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.8845 loss: 1.8845 2022/09/05 11:16:10 - mmengine - INFO - Epoch(train) [12][80/940] lr: 1.0000e-02 eta: 18:59:35 time: 0.6696 data_time: 0.1155 memory: 22701 grad_norm: 4.6434 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7856 loss: 1.7856 2022/09/05 11:16:27 - mmengine - INFO - Epoch(train) [12][100/940] lr: 1.0000e-02 eta: 18:59:27 time: 0.8719 data_time: 0.1179 memory: 22701 grad_norm: 4.5539 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8136 loss: 1.8136 2022/09/05 11:16:42 - mmengine - INFO - Epoch(train) [12][120/940] lr: 1.0000e-02 eta: 18:58:58 time: 0.7360 data_time: 0.0249 memory: 22701 grad_norm: 4.5772 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 1.8596 loss: 1.8596 2022/09/05 11:16:58 - mmengine - INFO - Epoch(train) [12][140/940] lr: 1.0000e-02 eta: 18:58:40 time: 0.8085 data_time: 0.0288 memory: 22701 grad_norm: 4.5117 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7904 loss: 1.7904 2022/09/05 11:17:12 - mmengine - INFO - Epoch(train) [12][160/940] lr: 1.0000e-02 eta: 18:58:00 time: 0.6679 data_time: 0.0286 memory: 22701 grad_norm: 4.5981 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8230 loss: 1.8230 2022/09/05 11:17:26 - mmengine - INFO - Epoch(train) [12][180/940] lr: 1.0000e-02 eta: 18:57:31 time: 0.7364 data_time: 0.0259 memory: 22701 grad_norm: 4.5249 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7893 loss: 1.7893 2022/09/05 11:17:40 - mmengine - INFO - Epoch(train) [12][200/940] lr: 1.0000e-02 eta: 18:56:53 time: 0.6808 data_time: 0.0427 memory: 22701 grad_norm: 4.5006 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7761 loss: 1.7761 2022/09/05 11:17:56 - mmengine - INFO - Epoch(train) [12][220/940] lr: 1.0000e-02 eta: 18:56:36 time: 0.8174 data_time: 0.0291 memory: 22701 grad_norm: 4.5680 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.9071 loss: 1.9071 2022/09/05 11:18:10 - mmengine - INFO - Epoch(train) [12][240/940] lr: 1.0000e-02 eta: 18:55:55 time: 0.6613 data_time: 0.0278 memory: 22701 grad_norm: 4.5260 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9093 loss: 1.9093 2022/09/05 11:18:28 - mmengine - INFO - Epoch(train) [12][260/940] lr: 1.0000e-02 eta: 18:55:57 time: 0.9289 data_time: 0.0270 memory: 22701 grad_norm: 4.5212 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6923 loss: 1.6923 2022/09/05 11:18:45 - mmengine - INFO - Epoch(train) [12][280/940] lr: 1.0000e-02 eta: 18:55:41 time: 0.8238 data_time: 0.0305 memory: 22701 grad_norm: 4.5869 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9024 loss: 1.9024 2022/09/05 11:19:03 - mmengine - INFO - Epoch(train) [12][300/940] lr: 1.0000e-02 eta: 18:55:43 time: 0.9358 data_time: 0.0240 memory: 22701 grad_norm: 4.5118 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7531 loss: 1.7531 2022/09/05 11:19:18 - mmengine - INFO - Epoch(train) [12][320/940] lr: 1.0000e-02 eta: 18:55:13 time: 0.7264 data_time: 0.0269 memory: 22701 grad_norm: 4.6071 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8244 loss: 1.8244 2022/09/05 11:19:35 - mmengine - INFO - Epoch(train) [12][340/940] lr: 1.0000e-02 eta: 18:55:01 time: 0.8479 data_time: 0.0266 memory: 22701 grad_norm: 4.5403 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7412 loss: 1.7412 2022/09/05 11:19:48 - mmengine - INFO - Epoch(train) [12][360/940] lr: 1.0000e-02 eta: 18:54:19 time: 0.6498 data_time: 0.0251 memory: 22701 grad_norm: 4.4644 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.9270 loss: 1.9270 2022/09/05 11:20:04 - mmengine - INFO - Epoch(train) [12][380/940] lr: 1.0000e-02 eta: 18:54:03 time: 0.8174 data_time: 0.0401 memory: 22701 grad_norm: 4.5479 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8938 loss: 1.8938 2022/09/05 11:20:18 - mmengine - INFO - Epoch(train) [12][400/940] lr: 1.0000e-02 eta: 18:53:26 time: 0.6847 data_time: 0.0288 memory: 22701 grad_norm: 4.5480 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.8834 loss: 1.8834 2022/09/05 11:20:35 - mmengine - INFO - Epoch(train) [12][420/940] lr: 1.0000e-02 eta: 18:53:11 time: 0.8301 data_time: 0.0223 memory: 22701 grad_norm: 4.6128 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9821 loss: 1.9821 2022/09/05 11:20:48 - mmengine - INFO - Epoch(train) [12][440/940] lr: 1.0000e-02 eta: 18:52:36 time: 0.6899 data_time: 0.0270 memory: 22701 grad_norm: 4.5107 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7625 loss: 1.7625 2022/09/05 11:21:06 - mmengine - INFO - Epoch(train) [12][460/940] lr: 1.0000e-02 eta: 18:52:33 time: 0.9063 data_time: 0.0224 memory: 22701 grad_norm: 4.5903 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8133 loss: 1.8133 2022/09/05 11:21:21 - mmengine - INFO - Epoch(train) [12][480/940] lr: 1.0000e-02 eta: 18:52:02 time: 0.7222 data_time: 0.0283 memory: 22701 grad_norm: 4.5322 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9850 loss: 1.9850 2022/09/05 11:21:41 - mmengine - INFO - Epoch(train) [12][500/940] lr: 1.0000e-02 eta: 18:52:17 time: 1.0172 data_time: 0.0352 memory: 22701 grad_norm: 4.5575 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.9200 loss: 1.9200 2022/09/05 11:21:58 - mmengine - INFO - Epoch(train) [12][520/940] lr: 1.0000e-02 eta: 18:52:05 time: 0.8468 data_time: 0.0306 memory: 22701 grad_norm: 4.5795 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7154 loss: 1.7154 2022/09/05 11:22:17 - mmengine - INFO - Epoch(train) [12][540/940] lr: 1.0000e-02 eta: 18:52:10 time: 0.9569 data_time: 0.0261 memory: 22701 grad_norm: 4.5781 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7629 loss: 1.7629 2022/09/05 11:22:33 - mmengine - INFO - Epoch(train) [12][560/940] lr: 1.0000e-02 eta: 18:51:46 time: 0.7690 data_time: 0.0664 memory: 22701 grad_norm: 4.6127 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8019 loss: 1.8019 2022/09/05 11:22:49 - mmengine - INFO - Epoch(train) [12][580/940] lr: 1.0000e-02 eta: 18:51:31 time: 0.8257 data_time: 0.0481 memory: 22701 grad_norm: 4.6132 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0250 loss: 2.0250 2022/09/05 11:23:03 - mmengine - INFO - Epoch(train) [12][600/940] lr: 1.0000e-02 eta: 18:50:52 time: 0.6680 data_time: 0.0328 memory: 22701 grad_norm: 4.5507 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7834 loss: 1.7834 2022/09/05 11:23:19 - mmengine - INFO - Epoch(train) [12][620/940] lr: 1.0000e-02 eta: 18:50:39 time: 0.8410 data_time: 0.0289 memory: 22701 grad_norm: 4.5238 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.8163 loss: 1.8163 2022/09/05 11:23:34 - mmengine - INFO - Epoch(train) [12][640/940] lr: 1.0000e-02 eta: 18:50:11 time: 0.7347 data_time: 0.0276 memory: 22701 grad_norm: 4.6100 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9118 loss: 1.9118 2022/09/05 11:23:52 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:23:52 - mmengine - INFO - Epoch(train) [12][660/940] lr: 1.0000e-02 eta: 18:50:08 time: 0.9097 data_time: 0.0268 memory: 22701 grad_norm: 4.7013 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8398 loss: 1.8398 2022/09/05 11:24:08 - mmengine - INFO - Epoch(train) [12][680/940] lr: 1.0000e-02 eta: 18:49:47 time: 0.7849 data_time: 0.0273 memory: 22701 grad_norm: 4.4823 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8453 loss: 1.8453 2022/09/05 11:24:27 - mmengine - INFO - Epoch(train) [12][700/940] lr: 1.0000e-02 eta: 18:49:52 time: 0.9583 data_time: 0.0275 memory: 22701 grad_norm: 4.5708 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.8001 loss: 1.8001 2022/09/05 11:24:41 - mmengine - INFO - Epoch(train) [12][720/940] lr: 1.0000e-02 eta: 18:49:20 time: 0.7142 data_time: 0.0224 memory: 22701 grad_norm: 4.5989 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8425 loss: 1.8425 2022/09/05 11:24:59 - mmengine - INFO - Epoch(train) [12][740/940] lr: 1.0000e-02 eta: 18:49:13 time: 0.8772 data_time: 0.0267 memory: 22701 grad_norm: 4.6369 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8364 loss: 1.8364 2022/09/05 11:25:12 - mmengine - INFO - Epoch(train) [12][760/940] lr: 1.0000e-02 eta: 18:48:34 time: 0.6626 data_time: 0.0235 memory: 22701 grad_norm: 4.5782 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.8044 loss: 1.8044 2022/09/05 11:25:30 - mmengine - INFO - Epoch(train) [12][780/940] lr: 1.0000e-02 eta: 18:48:25 time: 0.8707 data_time: 0.0283 memory: 22701 grad_norm: 4.6247 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.0007 loss: 2.0007 2022/09/05 11:25:43 - mmengine - INFO - Epoch(train) [12][800/940] lr: 1.0000e-02 eta: 18:47:47 time: 0.6691 data_time: 0.0309 memory: 22701 grad_norm: 4.5570 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.0005 loss: 2.0005 2022/09/05 11:25:59 - mmengine - INFO - Epoch(train) [12][820/940] lr: 1.0000e-02 eta: 18:47:29 time: 0.8029 data_time: 0.0866 memory: 22701 grad_norm: 4.6451 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7675 loss: 1.7675 2022/09/05 11:26:13 - mmengine - INFO - Epoch(train) [12][840/940] lr: 1.0000e-02 eta: 18:46:56 time: 0.7107 data_time: 0.0451 memory: 22701 grad_norm: 4.4929 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9250 loss: 1.9250 2022/09/05 11:26:29 - mmengine - INFO - Epoch(train) [12][860/940] lr: 1.0000e-02 eta: 18:46:34 time: 0.7780 data_time: 0.0877 memory: 22701 grad_norm: 4.6359 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7331 loss: 1.7331 2022/09/05 11:26:45 - mmengine - INFO - Epoch(train) [12][880/940] lr: 1.0000e-02 eta: 18:46:16 time: 0.8026 data_time: 0.0335 memory: 22701 grad_norm: 4.5677 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8805 loss: 1.8805 2022/09/05 11:27:01 - mmengine - INFO - Epoch(train) [12][900/940] lr: 1.0000e-02 eta: 18:46:01 time: 0.8265 data_time: 0.0381 memory: 22701 grad_norm: 4.6275 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0061 loss: 2.0061 2022/09/05 11:27:16 - mmengine - INFO - Epoch(train) [12][920/940] lr: 1.0000e-02 eta: 18:45:32 time: 0.7281 data_time: 0.0264 memory: 22701 grad_norm: 4.6924 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9493 loss: 1.9493 2022/09/05 11:27:29 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:27:29 - mmengine - INFO - Epoch(train) [12][940/940] lr: 1.0000e-02 eta: 18:44:49 time: 0.6359 data_time: 0.0214 memory: 22701 grad_norm: 4.7357 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.9834 loss: 1.9834 2022/09/05 11:27:29 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/09/05 11:27:44 - mmengine - INFO - Epoch(val) [12][20/78] eta: 0:00:40 time: 0.6942 data_time: 0.5771 memory: 2247 2022/09/05 11:27:54 - mmengine - INFO - Epoch(val) [12][40/78] eta: 0:00:17 time: 0.4613 data_time: 0.3432 memory: 2247 2022/09/05 11:28:07 - mmengine - INFO - Epoch(val) [12][60/78] eta: 0:00:12 time: 0.6883 data_time: 0.5726 memory: 2247 2022/09/05 11:28:16 - mmengine - INFO - Epoch(val) [12][78/78] acc/top1: 0.6139 acc/top5: 0.8410 acc/mean1: 0.6137 2022/09/05 11:28:16 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_11.pth is removed 2022/09/05 11:28:17 - mmengine - INFO - The best checkpoint with 0.6139 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/09/05 11:28:36 - mmengine - INFO - Epoch(train) [13][20/940] lr: 1.0000e-02 eta: 18:44:54 time: 0.9569 data_time: 0.5704 memory: 22701 grad_norm: 4.5889 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8774 loss: 1.8774 2022/09/05 11:28:52 - mmengine - INFO - Epoch(train) [13][40/940] lr: 1.0000e-02 eta: 18:44:30 time: 0.7693 data_time: 0.3983 memory: 22701 grad_norm: 4.6321 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7512 loss: 1.7512 2022/09/05 11:29:09 - mmengine - INFO - Epoch(train) [13][60/940] lr: 1.0000e-02 eta: 18:44:23 time: 0.8779 data_time: 0.4656 memory: 22701 grad_norm: 4.5330 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6996 loss: 1.6996 2022/09/05 11:29:25 - mmengine - INFO - Epoch(train) [13][80/940] lr: 1.0000e-02 eta: 18:44:01 time: 0.7742 data_time: 0.3734 memory: 22701 grad_norm: 4.5208 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8537 loss: 1.8537 2022/09/05 11:29:46 - mmengine - INFO - Epoch(train) [13][100/940] lr: 1.0000e-02 eta: 18:44:16 time: 1.0342 data_time: 0.2890 memory: 22701 grad_norm: 4.5364 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9068 loss: 1.9068 2022/09/05 11:30:00 - mmengine - INFO - Epoch(train) [13][120/940] lr: 1.0000e-02 eta: 18:43:45 time: 0.7126 data_time: 0.0589 memory: 22701 grad_norm: 4.5076 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7594 loss: 1.7594 2022/09/05 11:30:18 - mmengine - INFO - Epoch(train) [13][140/940] lr: 1.0000e-02 eta: 18:43:38 time: 0.8854 data_time: 0.0239 memory: 22701 grad_norm: 4.5434 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.8204 loss: 1.8204 2022/09/05 11:30:31 - mmengine - INFO - Epoch(train) [13][160/940] lr: 1.0000e-02 eta: 18:43:01 time: 0.6709 data_time: 0.0293 memory: 22701 grad_norm: 4.5371 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7444 loss: 1.7444 2022/09/05 11:30:48 - mmengine - INFO - Epoch(train) [13][180/940] lr: 1.0000e-02 eta: 18:42:46 time: 0.8258 data_time: 0.0278 memory: 22701 grad_norm: 4.6315 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7851 loss: 1.7851 2022/09/05 11:31:02 - mmengine - INFO - Epoch(train) [13][200/940] lr: 1.0000e-02 eta: 18:42:17 time: 0.7303 data_time: 0.0310 memory: 22701 grad_norm: 4.5481 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8656 loss: 1.8656 2022/09/05 11:31:20 - mmengine - INFO - Epoch(train) [13][220/940] lr: 1.0000e-02 eta: 18:42:10 time: 0.8772 data_time: 0.0252 memory: 22701 grad_norm: 4.5411 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8528 loss: 1.8528 2022/09/05 11:31:34 - mmengine - INFO - Epoch(train) [13][240/940] lr: 1.0000e-02 eta: 18:41:40 time: 0.7195 data_time: 0.0344 memory: 22701 grad_norm: 4.5328 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8416 loss: 1.8416 2022/09/05 11:31:52 - mmengine - INFO - Epoch(train) [13][260/940] lr: 1.0000e-02 eta: 18:41:36 time: 0.9076 data_time: 0.0248 memory: 22701 grad_norm: 4.4535 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.6751 loss: 1.6751 2022/09/05 11:32:08 - mmengine - INFO - Epoch(train) [13][280/940] lr: 1.0000e-02 eta: 18:41:18 time: 0.7994 data_time: 0.0369 memory: 22701 grad_norm: 4.6214 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8538 loss: 1.8538 2022/09/05 11:32:26 - mmengine - INFO - Epoch(train) [13][300/940] lr: 1.0000e-02 eta: 18:41:10 time: 0.8798 data_time: 0.0263 memory: 22701 grad_norm: 4.6005 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7745 loss: 1.7745 2022/09/05 11:32:39 - mmengine - INFO - Epoch(train) [13][320/940] lr: 1.0000e-02 eta: 18:40:34 time: 0.6750 data_time: 0.0247 memory: 22701 grad_norm: 4.6244 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8240 loss: 1.8240 2022/09/05 11:32:59 - mmengine - INFO - Epoch(train) [13][340/940] lr: 1.0000e-02 eta: 18:40:41 time: 0.9777 data_time: 0.0302 memory: 22701 grad_norm: 4.5392 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8185 loss: 1.8185 2022/09/05 11:33:15 - mmengine - INFO - Epoch(train) [13][360/940] lr: 1.0000e-02 eta: 18:40:26 time: 0.8309 data_time: 0.0266 memory: 22701 grad_norm: 4.5852 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7901 loss: 1.7901 2022/09/05 11:33:34 - mmengine - INFO - Epoch(train) [13][380/940] lr: 1.0000e-02 eta: 18:40:29 time: 0.9514 data_time: 0.0292 memory: 22701 grad_norm: 4.5756 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8448 loss: 1.8448 2022/09/05 11:33:49 - mmengine - INFO - Epoch(train) [13][400/940] lr: 1.0000e-02 eta: 18:40:02 time: 0.7375 data_time: 0.0390 memory: 22701 grad_norm: 4.6451 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.8748 loss: 1.8748 2022/09/05 11:34:06 - mmengine - INFO - Epoch(train) [13][420/940] lr: 1.0000e-02 eta: 18:39:48 time: 0.8313 data_time: 0.0531 memory: 22701 grad_norm: 4.6330 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.8344 loss: 1.8344 2022/09/05 11:34:22 - mmengine - INFO - Epoch(train) [13][440/940] lr: 1.0000e-02 eta: 18:39:27 time: 0.7891 data_time: 0.0876 memory: 22701 grad_norm: 4.6193 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8733 loss: 1.8733 2022/09/05 11:34:39 - mmengine - INFO - Epoch(train) [13][460/940] lr: 1.0000e-02 eta: 18:39:20 time: 0.8783 data_time: 0.0420 memory: 22701 grad_norm: 4.5682 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.9149 loss: 1.9149 2022/09/05 11:34:54 - mmengine - INFO - Epoch(train) [13][480/940] lr: 1.0000e-02 eta: 18:38:50 time: 0.7234 data_time: 0.0351 memory: 22701 grad_norm: 4.5369 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7827 loss: 1.7827 2022/09/05 11:35:11 - mmengine - INFO - Epoch(train) [13][500/940] lr: 1.0000e-02 eta: 18:38:41 time: 0.8633 data_time: 0.0324 memory: 22701 grad_norm: 4.5486 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7911 loss: 1.7911 2022/09/05 11:35:26 - mmengine - INFO - Epoch(train) [13][520/940] lr: 1.0000e-02 eta: 18:38:18 time: 0.7712 data_time: 0.0321 memory: 22701 grad_norm: 4.4786 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8315 loss: 1.8315 2022/09/05 11:35:45 - mmengine - INFO - Epoch(train) [13][540/940] lr: 1.0000e-02 eta: 18:38:18 time: 0.9335 data_time: 0.0261 memory: 22701 grad_norm: 4.6106 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8119 loss: 1.8119 2022/09/05 11:36:00 - mmengine - INFO - Epoch(train) [13][560/940] lr: 1.0000e-02 eta: 18:37:53 time: 0.7567 data_time: 0.0521 memory: 22701 grad_norm: 4.5943 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8734 loss: 1.8734 2022/09/05 11:36:24 - mmengine - INFO - Epoch(train) [13][580/940] lr: 1.0000e-02 eta: 18:38:27 time: 1.1789 data_time: 0.0522 memory: 22701 grad_norm: 4.5705 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8068 loss: 1.8068 2022/09/05 11:36:42 - mmengine - INFO - Epoch(train) [13][600/940] lr: 1.0000e-02 eta: 18:38:22 time: 0.9002 data_time: 0.0369 memory: 22701 grad_norm: 4.6731 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9316 loss: 1.9316 2022/09/05 11:37:04 - mmengine - INFO - Epoch(train) [13][620/940] lr: 1.0000e-02 eta: 18:38:49 time: 1.1256 data_time: 0.0223 memory: 22701 grad_norm: 4.5576 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8790 loss: 1.8790 2022/09/05 11:37:20 - mmengine - INFO - Epoch(train) [13][640/940] lr: 1.0000e-02 eta: 18:38:27 time: 0.7770 data_time: 0.0306 memory: 22701 grad_norm: 4.5169 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7831 loss: 1.7831 2022/09/05 11:37:42 - mmengine - INFO - Epoch(train) [13][660/940] lr: 1.0000e-02 eta: 18:38:53 time: 1.1244 data_time: 0.0307 memory: 22701 grad_norm: 4.6240 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8715 loss: 1.8715 2022/09/05 11:38:00 - mmengine - INFO - Epoch(train) [13][680/940] lr: 1.0000e-02 eta: 18:38:44 time: 0.8737 data_time: 0.0217 memory: 22701 grad_norm: 4.5947 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7956 loss: 1.7956 2022/09/05 11:38:25 - mmengine - INFO - Epoch(train) [13][700/940] lr: 1.0000e-02 eta: 18:39:26 time: 1.2487 data_time: 0.0441 memory: 22701 grad_norm: 4.6539 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8442 loss: 1.8442 2022/09/05 11:38:44 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:38:44 - mmengine - INFO - Epoch(train) [13][720/940] lr: 1.0000e-02 eta: 18:39:33 time: 0.9842 data_time: 0.0167 memory: 22701 grad_norm: 4.6706 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.9369 loss: 1.9369 2022/09/05 11:39:05 - mmengine - INFO - Epoch(train) [13][740/940] lr: 1.0000e-02 eta: 18:39:42 time: 1.0084 data_time: 0.0226 memory: 22701 grad_norm: 4.6352 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7726 loss: 1.7726 2022/09/05 11:39:20 - mmengine - INFO - Epoch(train) [13][760/940] lr: 1.0000e-02 eta: 18:39:18 time: 0.7638 data_time: 0.0166 memory: 22701 grad_norm: 4.6978 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0579 loss: 2.0579 2022/09/05 11:39:39 - mmengine - INFO - Epoch(train) [13][780/940] lr: 1.0000e-02 eta: 18:39:20 time: 0.9549 data_time: 0.0281 memory: 22701 grad_norm: 4.5869 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8493 loss: 1.8493 2022/09/05 11:39:56 - mmengine - INFO - Epoch(train) [13][800/940] lr: 1.0000e-02 eta: 18:39:07 time: 0.8428 data_time: 0.0235 memory: 22701 grad_norm: 4.5097 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7649 loss: 1.7649 2022/09/05 11:40:18 - mmengine - INFO - Epoch(train) [13][820/940] lr: 1.0000e-02 eta: 18:39:32 time: 1.1253 data_time: 0.0223 memory: 22701 grad_norm: 4.5684 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8304 loss: 1.8304 2022/09/05 11:40:33 - mmengine - INFO - Epoch(train) [13][840/940] lr: 1.0000e-02 eta: 18:39:02 time: 0.7180 data_time: 0.0191 memory: 22701 grad_norm: 4.6374 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8604 loss: 1.8604 2022/09/05 11:40:51 - mmengine - INFO - Epoch(train) [13][860/940] lr: 1.0000e-02 eta: 18:38:55 time: 0.8924 data_time: 0.0234 memory: 22701 grad_norm: 4.4833 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8619 loss: 1.8619 2022/09/05 11:41:09 - mmengine - INFO - Epoch(train) [13][880/940] lr: 1.0000e-02 eta: 18:38:50 time: 0.9084 data_time: 0.0165 memory: 22701 grad_norm: 4.5242 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.8461 loss: 1.8461 2022/09/05 11:41:25 - mmengine - INFO - Epoch(train) [13][900/940] lr: 1.0000e-02 eta: 18:38:32 time: 0.8042 data_time: 0.0300 memory: 22701 grad_norm: 4.5180 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7717 loss: 1.7717 2022/09/05 11:41:44 - mmengine - INFO - Epoch(train) [13][920/940] lr: 1.0000e-02 eta: 18:38:33 time: 0.9543 data_time: 0.3399 memory: 22701 grad_norm: 4.6803 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.9634 loss: 1.9634 2022/09/05 11:41:58 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:41:58 - mmengine - INFO - Epoch(train) [13][940/940] lr: 1.0000e-02 eta: 18:38:03 time: 0.7173 data_time: 0.3117 memory: 22701 grad_norm: 4.9015 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.8119 loss: 1.8119 2022/09/05 11:42:15 - mmengine - INFO - Epoch(val) [13][20/78] eta: 0:00:48 time: 0.8281 data_time: 0.7138 memory: 2247 2022/09/05 11:42:24 - mmengine - INFO - Epoch(val) [13][40/78] eta: 0:00:16 time: 0.4381 data_time: 0.3149 memory: 2247 2022/09/05 11:42:37 - mmengine - INFO - Epoch(val) [13][60/78] eta: 0:00:11 time: 0.6636 data_time: 0.5570 memory: 2247 2022/09/05 11:42:50 - mmengine - INFO - Epoch(val) [13][78/78] acc/top1: 0.6127 acc/top5: 0.8399 acc/mean1: 0.6126 2022/09/05 11:43:09 - mmengine - INFO - Epoch(train) [14][20/940] lr: 1.0000e-02 eta: 18:38:07 time: 0.9695 data_time: 0.4670 memory: 22701 grad_norm: 4.5525 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.8253 loss: 1.8253 2022/09/05 11:43:23 - mmengine - INFO - Epoch(train) [14][40/940] lr: 1.0000e-02 eta: 18:37:35 time: 0.7077 data_time: 0.1309 memory: 22701 grad_norm: 4.6331 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.9390 loss: 1.9390 2022/09/05 11:43:40 - mmengine - INFO - Epoch(train) [14][60/940] lr: 1.0000e-02 eta: 18:37:21 time: 0.8345 data_time: 0.0808 memory: 22701 grad_norm: 4.4910 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8166 loss: 1.8166 2022/09/05 11:43:54 - mmengine - INFO - Epoch(train) [14][80/940] lr: 1.0000e-02 eta: 18:36:51 time: 0.7219 data_time: 0.0197 memory: 22701 grad_norm: 4.5040 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6969 loss: 1.6969 2022/09/05 11:44:15 - mmengine - INFO - Epoch(train) [14][100/940] lr: 1.0000e-02 eta: 18:37:04 time: 1.0368 data_time: 0.0263 memory: 22701 grad_norm: 4.6405 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8295 loss: 1.8295 2022/09/05 11:44:29 - mmengine - INFO - Epoch(train) [14][120/940] lr: 1.0000e-02 eta: 18:36:28 time: 0.6771 data_time: 0.0230 memory: 22701 grad_norm: 4.5821 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7359 loss: 1.7359 2022/09/05 11:44:48 - mmengine - INFO - Epoch(train) [14][140/940] lr: 1.0000e-02 eta: 18:36:33 time: 0.9801 data_time: 0.0672 memory: 22701 grad_norm: 4.6280 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.7965 loss: 1.7965 2022/09/05 11:45:04 - mmengine - INFO - Epoch(train) [14][160/940] lr: 1.0000e-02 eta: 18:36:11 time: 0.7761 data_time: 0.0165 memory: 22701 grad_norm: 4.5790 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.8445 loss: 1.8445 2022/09/05 11:45:22 - mmengine - INFO - Epoch(train) [14][180/940] lr: 1.0000e-02 eta: 18:36:04 time: 0.8978 data_time: 0.0960 memory: 22701 grad_norm: 4.5695 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6975 loss: 1.6975 2022/09/05 11:45:35 - mmengine - INFO - Epoch(train) [14][200/940] lr: 1.0000e-02 eta: 18:35:27 time: 0.6629 data_time: 0.0223 memory: 22701 grad_norm: 4.5923 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7726 loss: 1.7726 2022/09/05 11:45:51 - mmengine - INFO - Epoch(train) [14][220/940] lr: 1.0000e-02 eta: 18:35:08 time: 0.8017 data_time: 0.0534 memory: 22701 grad_norm: 4.5185 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6759 loss: 1.6759 2022/09/05 11:46:04 - mmengine - INFO - Epoch(train) [14][240/940] lr: 1.0000e-02 eta: 18:34:32 time: 0.6645 data_time: 0.0492 memory: 22701 grad_norm: 4.5240 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.8076 loss: 1.8076 2022/09/05 11:46:23 - mmengine - INFO - Epoch(train) [14][260/940] lr: 1.0000e-02 eta: 18:34:28 time: 0.9158 data_time: 0.0508 memory: 22701 grad_norm: 4.5149 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7915 loss: 1.7915 2022/09/05 11:46:37 - mmengine - INFO - Epoch(train) [14][280/940] lr: 1.0000e-02 eta: 18:34:00 time: 0.7304 data_time: 0.1523 memory: 22701 grad_norm: 4.5212 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7898 loss: 1.7898 2022/09/05 11:47:01 - mmengine - INFO - Epoch(train) [14][300/940] lr: 1.0000e-02 eta: 18:34:30 time: 1.1823 data_time: 0.1550 memory: 22701 grad_norm: 4.5914 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7045 loss: 1.7045 2022/09/05 11:47:18 - mmengine - INFO - Epoch(train) [14][320/940] lr: 1.0000e-02 eta: 18:34:18 time: 0.8527 data_time: 0.2055 memory: 22701 grad_norm: 4.5870 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8793 loss: 1.8793 2022/09/05 11:47:36 - mmengine - INFO - Epoch(train) [14][340/940] lr: 1.0000e-02 eta: 18:34:14 time: 0.9175 data_time: 0.2326 memory: 22701 grad_norm: 4.6804 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8791 loss: 1.8791 2022/09/05 11:47:51 - mmengine - INFO - Epoch(train) [14][360/940] lr: 1.0000e-02 eta: 18:33:45 time: 0.7260 data_time: 0.0514 memory: 22701 grad_norm: 4.6395 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8021 loss: 1.8021 2022/09/05 11:48:11 - mmengine - INFO - Epoch(train) [14][380/940] lr: 1.0000e-02 eta: 18:33:54 time: 1.0140 data_time: 0.0630 memory: 22701 grad_norm: 4.5070 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8073 loss: 1.8073 2022/09/05 11:48:26 - mmengine - INFO - Epoch(train) [14][400/940] lr: 1.0000e-02 eta: 18:33:26 time: 0.7301 data_time: 0.0236 memory: 22701 grad_norm: 4.6013 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8598 loss: 1.8598 2022/09/05 11:48:43 - mmengine - INFO - Epoch(train) [14][420/940] lr: 1.0000e-02 eta: 18:33:19 time: 0.8920 data_time: 0.0283 memory: 22701 grad_norm: 4.5430 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7468 loss: 1.7468 2022/09/05 11:48:56 - mmengine - INFO - Epoch(train) [14][440/940] lr: 1.0000e-02 eta: 18:32:35 time: 0.6059 data_time: 0.0351 memory: 22701 grad_norm: 4.6439 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.8062 loss: 1.8062 2022/09/05 11:49:12 - mmengine - INFO - Epoch(train) [14][460/940] lr: 1.0000e-02 eta: 18:32:19 time: 0.8297 data_time: 0.1144 memory: 22701 grad_norm: 4.6054 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6691 loss: 1.6691 2022/09/05 11:49:27 - mmengine - INFO - Epoch(train) [14][480/940] lr: 1.0000e-02 eta: 18:31:50 time: 0.7210 data_time: 0.0854 memory: 22701 grad_norm: 4.5469 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6914 loss: 1.6914 2022/09/05 11:49:44 - mmengine - INFO - Epoch(train) [14][500/940] lr: 1.0000e-02 eta: 18:31:39 time: 0.8634 data_time: 0.1152 memory: 22701 grad_norm: 4.6100 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.7929 loss: 1.7929 2022/09/05 11:50:01 - mmengine - INFO - Epoch(train) [14][520/940] lr: 1.0000e-02 eta: 18:31:24 time: 0.8323 data_time: 0.1743 memory: 22701 grad_norm: 4.5639 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8096 loss: 1.8096 2022/09/05 11:50:18 - mmengine - INFO - Epoch(train) [14][540/940] lr: 1.0000e-02 eta: 18:31:16 time: 0.8866 data_time: 0.1660 memory: 22701 grad_norm: 4.5765 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7197 loss: 1.7197 2022/09/05 11:50:33 - mmengine - INFO - Epoch(train) [14][560/940] lr: 1.0000e-02 eta: 18:30:49 time: 0.7331 data_time: 0.2425 memory: 22701 grad_norm: 4.5280 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.6654 loss: 1.6654 2022/09/05 11:50:51 - mmengine - INFO - Epoch(train) [14][580/940] lr: 1.0000e-02 eta: 18:30:41 time: 0.8899 data_time: 0.4074 memory: 22701 grad_norm: 4.6032 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9320 loss: 1.9320 2022/09/05 11:51:05 - mmengine - INFO - Epoch(train) [14][600/940] lr: 1.0000e-02 eta: 18:30:10 time: 0.7024 data_time: 0.2125 memory: 22701 grad_norm: 4.6242 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8321 loss: 1.8321 2022/09/05 11:51:22 - mmengine - INFO - Epoch(train) [14][620/940] lr: 1.0000e-02 eta: 18:30:01 time: 0.8792 data_time: 0.2909 memory: 22701 grad_norm: 4.6148 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7896 loss: 1.7896 2022/09/05 11:51:37 - mmengine - INFO - Epoch(train) [14][640/940] lr: 1.0000e-02 eta: 18:29:32 time: 0.7203 data_time: 0.2483 memory: 22701 grad_norm: 4.5980 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.8505 loss: 1.8505 2022/09/05 11:51:55 - mmengine - INFO - Epoch(train) [14][660/940] lr: 1.0000e-02 eta: 18:29:25 time: 0.8953 data_time: 0.4222 memory: 22701 grad_norm: 4.6230 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.7879 loss: 1.7879 2022/09/05 11:52:10 - mmengine - INFO - Epoch(train) [14][680/940] lr: 1.0000e-02 eta: 18:29:02 time: 0.7676 data_time: 0.1885 memory: 22701 grad_norm: 4.6114 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7399 loss: 1.7399 2022/09/05 11:52:28 - mmengine - INFO - Epoch(train) [14][700/940] lr: 1.0000e-02 eta: 18:28:53 time: 0.8873 data_time: 0.2500 memory: 22701 grad_norm: 4.6318 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7400 loss: 1.7400 2022/09/05 11:52:43 - mmengine - INFO - Epoch(train) [14][720/940] lr: 1.0000e-02 eta: 18:28:27 time: 0.7429 data_time: 0.0207 memory: 22701 grad_norm: 4.6681 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7830 loss: 1.7830 2022/09/05 11:52:58 - mmengine - INFO - Epoch(train) [14][740/940] lr: 1.0000e-02 eta: 18:28:06 time: 0.7808 data_time: 0.0251 memory: 22701 grad_norm: 4.6384 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7025 loss: 1.7025 2022/09/05 11:53:14 - mmengine - INFO - Epoch(train) [14][760/940] lr: 1.0000e-02 eta: 18:27:44 time: 0.7727 data_time: 0.0224 memory: 22701 grad_norm: 4.5702 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.7704 loss: 1.7704 2022/09/05 11:53:31 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:53:31 - mmengine - INFO - Epoch(train) [14][780/940] lr: 1.0000e-02 eta: 18:27:34 time: 0.8728 data_time: 0.0279 memory: 22701 grad_norm: 4.5182 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7661 loss: 1.7661 2022/09/05 11:53:52 - mmengine - INFO - Epoch(train) [14][800/940] lr: 1.0000e-02 eta: 18:27:45 time: 1.0457 data_time: 0.1585 memory: 22701 grad_norm: 4.6274 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.8835 loss: 1.8835 2022/09/05 11:54:13 - mmengine - INFO - Epoch(train) [14][820/940] lr: 1.0000e-02 eta: 18:27:57 time: 1.0439 data_time: 0.0229 memory: 22701 grad_norm: 4.5462 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6229 loss: 1.6229 2022/09/05 11:54:27 - mmengine - INFO - Epoch(train) [14][840/940] lr: 1.0000e-02 eta: 18:27:27 time: 0.7117 data_time: 0.0262 memory: 22701 grad_norm: 4.5955 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8402 loss: 1.8402 2022/09/05 11:54:46 - mmengine - INFO - Epoch(train) [14][860/940] lr: 1.0000e-02 eta: 18:27:28 time: 0.9610 data_time: 0.0240 memory: 22701 grad_norm: 4.6031 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8241 loss: 1.8241 2022/09/05 11:55:02 - mmengine - INFO - Epoch(train) [14][880/940] lr: 1.0000e-02 eta: 18:27:05 time: 0.7707 data_time: 0.0601 memory: 22701 grad_norm: 4.5175 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6872 loss: 1.6872 2022/09/05 11:55:19 - mmengine - INFO - Epoch(train) [14][900/940] lr: 1.0000e-02 eta: 18:26:51 time: 0.8405 data_time: 0.0325 memory: 22701 grad_norm: 4.6437 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9135 loss: 1.9135 2022/09/05 11:55:32 - mmengine - INFO - Epoch(train) [14][920/940] lr: 1.0000e-02 eta: 18:26:17 time: 0.6832 data_time: 0.0239 memory: 22701 grad_norm: 4.6355 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8630 loss: 1.8630 2022/09/05 11:55:47 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 11:55:47 - mmengine - INFO - Epoch(train) [14][940/940] lr: 1.0000e-02 eta: 18:25:53 time: 0.7560 data_time: 0.0234 memory: 22701 grad_norm: 4.7984 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8452 loss: 1.8452 2022/09/05 11:56:02 - mmengine - INFO - Epoch(val) [14][20/78] eta: 0:00:41 time: 0.7094 data_time: 0.5898 memory: 2247 2022/09/05 11:56:11 - mmengine - INFO - Epoch(val) [14][40/78] eta: 0:00:17 time: 0.4529 data_time: 0.3337 memory: 2247 2022/09/05 11:56:24 - mmengine - INFO - Epoch(val) [14][60/78] eta: 0:00:11 time: 0.6487 data_time: 0.5277 memory: 2247 2022/09/05 11:56:34 - mmengine - INFO - Epoch(val) [14][78/78] acc/top1: 0.6205 acc/top5: 0.8423 acc/mean1: 0.6204 2022/09/05 11:56:34 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_13.pth is removed 2022/09/05 11:56:35 - mmengine - INFO - The best checkpoint with 0.6205 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/09/05 11:56:55 - mmengine - INFO - Epoch(train) [15][20/940] lr: 1.0000e-02 eta: 18:26:00 time: 1.0094 data_time: 0.5760 memory: 22701 grad_norm: 4.5473 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8357 loss: 1.8357 2022/09/05 11:57:11 - mmengine - INFO - Epoch(train) [15][40/940] lr: 1.0000e-02 eta: 18:25:40 time: 0.7963 data_time: 0.2575 memory: 22701 grad_norm: 4.5418 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8162 loss: 1.8162 2022/09/05 11:57:28 - mmengine - INFO - Epoch(train) [15][60/940] lr: 1.0000e-02 eta: 18:25:30 time: 0.8709 data_time: 0.2775 memory: 22701 grad_norm: 4.6543 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8523 loss: 1.8523 2022/09/05 11:57:42 - mmengine - INFO - Epoch(train) [15][80/940] lr: 1.0000e-02 eta: 18:24:59 time: 0.7014 data_time: 0.2159 memory: 22701 grad_norm: 4.4944 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8616 loss: 1.8616 2022/09/05 11:58:02 - mmengine - INFO - Epoch(train) [15][100/940] lr: 1.0000e-02 eta: 18:25:04 time: 0.9970 data_time: 0.4471 memory: 22701 grad_norm: 4.5669 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7141 loss: 1.7141 2022/09/05 11:58:18 - mmengine - INFO - Epoch(train) [15][120/940] lr: 1.0000e-02 eta: 18:24:40 time: 0.7588 data_time: 0.2615 memory: 22701 grad_norm: 4.6208 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8021 loss: 1.8021 2022/09/05 11:58:39 - mmengine - INFO - Epoch(train) [15][140/940] lr: 1.0000e-02 eta: 18:24:55 time: 1.0766 data_time: 0.2690 memory: 22701 grad_norm: 4.5144 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6901 loss: 1.6901 2022/09/05 11:58:55 - mmengine - INFO - Epoch(train) [15][160/940] lr: 1.0000e-02 eta: 18:24:35 time: 0.7928 data_time: 0.0480 memory: 22701 grad_norm: 4.5553 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8271 loss: 1.8271 2022/09/05 11:59:14 - mmengine - INFO - Epoch(train) [15][180/940] lr: 1.0000e-02 eta: 18:24:36 time: 0.9643 data_time: 0.0249 memory: 22701 grad_norm: 4.4888 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.8124 loss: 1.8124 2022/09/05 11:59:30 - mmengine - INFO - Epoch(train) [15][200/940] lr: 1.0000e-02 eta: 18:24:15 time: 0.7874 data_time: 0.0222 memory: 22701 grad_norm: 4.4869 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.8183 loss: 1.8183 2022/09/05 11:59:48 - mmengine - INFO - Epoch(train) [15][220/940] lr: 1.0000e-02 eta: 18:24:11 time: 0.9268 data_time: 0.0271 memory: 22701 grad_norm: 4.4855 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7744 loss: 1.7744 2022/09/05 12:00:03 - mmengine - INFO - Epoch(train) [15][240/940] lr: 1.0000e-02 eta: 18:23:41 time: 0.7032 data_time: 0.0305 memory: 22701 grad_norm: 4.5395 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8046 loss: 1.8046 2022/09/05 12:00:19 - mmengine - INFO - Epoch(train) [15][260/940] lr: 1.0000e-02 eta: 18:23:27 time: 0.8467 data_time: 0.0382 memory: 22701 grad_norm: 4.5423 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6414 loss: 1.6414 2022/09/05 12:00:33 - mmengine - INFO - Epoch(train) [15][280/940] lr: 1.0000e-02 eta: 18:22:52 time: 0.6690 data_time: 0.0292 memory: 22701 grad_norm: 4.5083 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6859 loss: 1.6859 2022/09/05 12:00:50 - mmengine - INFO - Epoch(train) [15][300/940] lr: 1.0000e-02 eta: 18:22:39 time: 0.8469 data_time: 0.0264 memory: 22701 grad_norm: 4.5218 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.9044 loss: 1.9044 2022/09/05 12:01:03 - mmengine - INFO - Epoch(train) [15][320/940] lr: 1.0000e-02 eta: 18:22:05 time: 0.6704 data_time: 0.0266 memory: 22701 grad_norm: 4.5463 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7183 loss: 1.7183 2022/09/05 12:01:22 - mmengine - INFO - Epoch(train) [15][340/940] lr: 1.0000e-02 eta: 18:22:03 time: 0.9456 data_time: 0.0280 memory: 22701 grad_norm: 4.6334 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6880 loss: 1.6880 2022/09/05 12:01:37 - mmengine - INFO - Epoch(train) [15][360/940] lr: 1.0000e-02 eta: 18:21:37 time: 0.7456 data_time: 0.0297 memory: 22701 grad_norm: 4.5541 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.7103 loss: 1.7103 2022/09/05 12:01:53 - mmengine - INFO - Epoch(train) [15][380/940] lr: 1.0000e-02 eta: 18:21:17 time: 0.7831 data_time: 0.0279 memory: 22701 grad_norm: 4.5528 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7887 loss: 1.7887 2022/09/05 12:02:09 - mmengine - INFO - Epoch(train) [15][400/940] lr: 1.0000e-02 eta: 18:21:02 time: 0.8378 data_time: 0.0296 memory: 22701 grad_norm: 4.6159 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.7762 loss: 1.7762 2022/09/05 12:02:27 - mmengine - INFO - Epoch(train) [15][420/940] lr: 1.0000e-02 eta: 18:20:52 time: 0.8735 data_time: 0.0253 memory: 22701 grad_norm: 4.6554 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9525 loss: 1.9525 2022/09/05 12:02:42 - mmengine - INFO - Epoch(train) [15][440/940] lr: 1.0000e-02 eta: 18:20:26 time: 0.7401 data_time: 0.0205 memory: 22701 grad_norm: 4.6441 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.8081 loss: 1.8081 2022/09/05 12:03:00 - mmengine - INFO - Epoch(train) [15][460/940] lr: 1.0000e-02 eta: 18:20:19 time: 0.9038 data_time: 0.0238 memory: 22701 grad_norm: 4.6757 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8143 loss: 1.8143 2022/09/05 12:03:14 - mmengine - INFO - Epoch(train) [15][480/940] lr: 1.0000e-02 eta: 18:19:49 time: 0.7078 data_time: 0.0483 memory: 22701 grad_norm: 4.7110 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7257 loss: 1.7257 2022/09/05 12:03:34 - mmengine - INFO - Epoch(train) [15][500/940] lr: 1.0000e-02 eta: 18:19:53 time: 0.9961 data_time: 0.3040 memory: 22701 grad_norm: 4.6305 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9710 loss: 1.9710 2022/09/05 12:03:50 - mmengine - INFO - Epoch(train) [15][520/940] lr: 1.0000e-02 eta: 18:19:38 time: 0.8273 data_time: 0.1949 memory: 22701 grad_norm: 4.4938 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6081 loss: 1.6081 2022/09/05 12:04:08 - mmengine - INFO - Epoch(train) [15][540/940] lr: 1.0000e-02 eta: 18:19:30 time: 0.8977 data_time: 0.2876 memory: 22701 grad_norm: 4.5960 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8290 loss: 1.8290 2022/09/05 12:04:25 - mmengine - INFO - Epoch(train) [15][560/940] lr: 1.0000e-02 eta: 18:19:12 time: 0.8058 data_time: 0.1443 memory: 22701 grad_norm: 4.6440 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8250 loss: 1.8250 2022/09/05 12:04:40 - mmengine - INFO - Epoch(train) [15][580/940] lr: 1.0000e-02 eta: 18:18:52 time: 0.7899 data_time: 0.1705 memory: 22701 grad_norm: 4.6452 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.7798 loss: 1.7798 2022/09/05 12:04:55 - mmengine - INFO - Epoch(train) [15][600/940] lr: 1.0000e-02 eta: 18:18:24 time: 0.7243 data_time: 0.1607 memory: 22701 grad_norm: 4.6585 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8291 loss: 1.8291 2022/09/05 12:05:11 - mmengine - INFO - Epoch(train) [15][620/940] lr: 1.0000e-02 eta: 18:18:06 time: 0.8115 data_time: 0.1315 memory: 22701 grad_norm: 4.5973 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.6788 loss: 1.6788 2022/09/05 12:05:27 - mmengine - INFO - Epoch(train) [15][640/940] lr: 1.0000e-02 eta: 18:17:48 time: 0.8030 data_time: 0.0231 memory: 22701 grad_norm: 4.6410 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7333 loss: 1.7333 2022/09/05 12:05:42 - mmengine - INFO - Epoch(train) [15][660/940] lr: 1.0000e-02 eta: 18:17:20 time: 0.7247 data_time: 0.0756 memory: 22701 grad_norm: 4.5455 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7069 loss: 1.7069 2022/09/05 12:06:00 - mmengine - INFO - Epoch(train) [15][680/940] lr: 1.0000e-02 eta: 18:17:15 time: 0.9164 data_time: 0.1058 memory: 22701 grad_norm: 4.6779 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7817 loss: 1.7817 2022/09/05 12:06:16 - mmengine - INFO - Epoch(train) [15][700/940] lr: 1.0000e-02 eta: 18:16:59 time: 0.8280 data_time: 0.1104 memory: 22701 grad_norm: 4.4576 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7155 loss: 1.7155 2022/09/05 12:06:36 - mmengine - INFO - Epoch(train) [15][720/940] lr: 1.0000e-02 eta: 18:17:00 time: 0.9692 data_time: 0.0585 memory: 22701 grad_norm: 4.5812 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8764 loss: 1.8764 2022/09/05 12:06:54 - mmengine - INFO - Epoch(train) [15][740/940] lr: 1.0000e-02 eta: 18:16:56 time: 0.9274 data_time: 0.0278 memory: 22701 grad_norm: 4.6027 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.7500 loss: 1.7500 2022/09/05 12:07:15 - mmengine - INFO - Epoch(train) [15][760/940] lr: 1.0000e-02 eta: 18:17:03 time: 1.0255 data_time: 0.0204 memory: 22701 grad_norm: 4.6204 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.8526 loss: 1.8526 2022/09/05 12:07:32 - mmengine - INFO - Epoch(train) [15][780/940] lr: 1.0000e-02 eta: 18:16:52 time: 0.8763 data_time: 0.0297 memory: 22701 grad_norm: 4.5745 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8024 loss: 1.8024 2022/09/05 12:07:52 - mmengine - INFO - Epoch(train) [15][800/940] lr: 1.0000e-02 eta: 18:16:52 time: 0.9570 data_time: 0.0211 memory: 22701 grad_norm: 4.6857 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8427 loss: 1.8427 2022/09/05 12:08:06 - mmengine - INFO - Epoch(train) [15][820/940] lr: 1.0000e-02 eta: 18:16:21 time: 0.7029 data_time: 0.0261 memory: 22701 grad_norm: 4.6532 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7108 loss: 1.7108 2022/09/05 12:08:25 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:08:25 - mmengine - INFO - Epoch(train) [15][840/940] lr: 1.0000e-02 eta: 18:16:20 time: 0.9512 data_time: 0.0260 memory: 22701 grad_norm: 4.6024 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8541 loss: 1.8541 2022/09/05 12:08:39 - mmengine - INFO - Epoch(train) [15][860/940] lr: 1.0000e-02 eta: 18:15:52 time: 0.7210 data_time: 0.0314 memory: 22701 grad_norm: 4.5624 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8540 loss: 1.8540 2022/09/05 12:08:55 - mmengine - INFO - Epoch(train) [15][880/940] lr: 1.0000e-02 eta: 18:15:31 time: 0.7872 data_time: 0.0217 memory: 22701 grad_norm: 4.6794 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.7270 loss: 1.7270 2022/09/05 12:09:09 - mmengine - INFO - Epoch(train) [15][900/940] lr: 1.0000e-02 eta: 18:15:02 time: 0.7108 data_time: 0.0749 memory: 22701 grad_norm: 4.5978 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7452 loss: 1.7452 2022/09/05 12:09:26 - mmengine - INFO - Epoch(train) [15][920/940] lr: 1.0000e-02 eta: 18:14:51 time: 0.8643 data_time: 0.0228 memory: 22701 grad_norm: 4.6428 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.8207 loss: 1.8207 2022/09/05 12:09:41 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:09:41 - mmengine - INFO - Epoch(train) [15][940/940] lr: 1.0000e-02 eta: 18:14:23 time: 0.7222 data_time: 0.0250 memory: 22701 grad_norm: 4.8391 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.8617 loss: 1.8617 2022/09/05 12:09:41 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/09/05 12:09:56 - mmengine - INFO - Epoch(val) [15][20/78] eta: 0:00:40 time: 0.6978 data_time: 0.5797 memory: 2247 2022/09/05 12:10:06 - mmengine - INFO - Epoch(val) [15][40/78] eta: 0:00:17 time: 0.4667 data_time: 0.3489 memory: 2247 2022/09/05 12:10:18 - mmengine - INFO - Epoch(val) [15][60/78] eta: 0:00:11 time: 0.6286 data_time: 0.5113 memory: 2247 2022/09/05 12:10:29 - mmengine - INFO - Epoch(val) [15][78/78] acc/top1: 0.6217 acc/top5: 0.8417 acc/mean1: 0.6215 2022/09/05 12:10:29 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_15.pth is removed 2022/09/05 12:10:30 - mmengine - INFO - The best checkpoint with 0.6217 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth. 2022/09/05 12:10:50 - mmengine - INFO - Epoch(train) [16][20/940] lr: 1.0000e-02 eta: 18:14:29 time: 1.0204 data_time: 0.6492 memory: 22701 grad_norm: 4.5470 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.8354 loss: 1.8354 2022/09/05 12:11:05 - mmengine - INFO - Epoch(train) [16][40/940] lr: 1.0000e-02 eta: 18:14:06 time: 0.7632 data_time: 0.2522 memory: 22701 grad_norm: 4.4804 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6199 loss: 1.6199 2022/09/05 12:11:25 - mmengine - INFO - Epoch(train) [16][60/940] lr: 1.0000e-02 eta: 18:14:05 time: 0.9615 data_time: 0.3870 memory: 22701 grad_norm: 4.6352 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0071 loss: 2.0071 2022/09/05 12:11:40 - mmengine - INFO - Epoch(train) [16][80/940] lr: 1.0000e-02 eta: 18:13:43 time: 0.7724 data_time: 0.2506 memory: 22701 grad_norm: 4.5634 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7567 loss: 1.7567 2022/09/05 12:12:00 - mmengine - INFO - Epoch(train) [16][100/940] lr: 1.0000e-02 eta: 18:13:47 time: 1.0013 data_time: 0.1461 memory: 22701 grad_norm: 4.6189 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.8997 loss: 1.8997 2022/09/05 12:12:14 - mmengine - INFO - Epoch(train) [16][120/940] lr: 1.0000e-02 eta: 18:13:18 time: 0.7126 data_time: 0.0162 memory: 22701 grad_norm: 4.6584 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9759 loss: 1.9759 2022/09/05 12:12:32 - mmengine - INFO - Epoch(train) [16][140/940] lr: 1.0000e-02 eta: 18:13:10 time: 0.8953 data_time: 0.0265 memory: 22701 grad_norm: 4.6084 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.6549 loss: 1.6549 2022/09/05 12:12:47 - mmengine - INFO - Epoch(train) [16][160/940] lr: 1.0000e-02 eta: 18:12:44 time: 0.7403 data_time: 0.0191 memory: 22701 grad_norm: 4.6085 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6532 loss: 1.6532 2022/09/05 12:13:07 - mmengine - INFO - Epoch(train) [16][180/940] lr: 1.0000e-02 eta: 18:12:47 time: 0.9926 data_time: 0.0254 memory: 22701 grad_norm: 4.6512 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.7590 loss: 1.7590 2022/09/05 12:13:24 - mmengine - INFO - Epoch(train) [16][200/940] lr: 1.0000e-02 eta: 18:12:33 time: 0.8434 data_time: 0.0212 memory: 22701 grad_norm: 4.6262 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 1.7827 loss: 1.7827 2022/09/05 12:13:41 - mmengine - INFO - Epoch(train) [16][220/940] lr: 1.0000e-02 eta: 18:12:22 time: 0.8747 data_time: 0.0827 memory: 22701 grad_norm: 4.6116 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7169 loss: 1.7169 2022/09/05 12:13:56 - mmengine - INFO - Epoch(train) [16][240/940] lr: 1.0000e-02 eta: 18:11:55 time: 0.7314 data_time: 0.0187 memory: 22701 grad_norm: 4.5525 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6992 loss: 1.6992 2022/09/05 12:14:13 - mmengine - INFO - Epoch(train) [16][260/940] lr: 1.0000e-02 eta: 18:11:40 time: 0.8355 data_time: 0.0244 memory: 22701 grad_norm: 4.6220 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7729 loss: 1.7729 2022/09/05 12:14:28 - mmengine - INFO - Epoch(train) [16][280/940] lr: 1.0000e-02 eta: 18:11:19 time: 0.7754 data_time: 0.0282 memory: 22701 grad_norm: 4.6171 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7652 loss: 1.7652 2022/09/05 12:14:46 - mmengine - INFO - Epoch(train) [16][300/940] lr: 1.0000e-02 eta: 18:11:10 time: 0.8973 data_time: 0.0321 memory: 22701 grad_norm: 4.5796 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.6927 loss: 1.6927 2022/09/05 12:15:06 - mmengine - INFO - Epoch(train) [16][320/940] lr: 1.0000e-02 eta: 18:11:11 time: 0.9764 data_time: 0.0189 memory: 22701 grad_norm: 4.5278 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7715 loss: 1.7715 2022/09/05 12:15:23 - mmengine - INFO - Epoch(train) [16][340/940] lr: 1.0000e-02 eta: 18:11:00 time: 0.8718 data_time: 0.0300 memory: 22701 grad_norm: 4.5848 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6467 loss: 1.6467 2022/09/05 12:15:38 - mmengine - INFO - Epoch(train) [16][360/940] lr: 1.0000e-02 eta: 18:10:34 time: 0.7322 data_time: 0.0285 memory: 22701 grad_norm: 4.5648 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6316 loss: 1.6316 2022/09/05 12:15:55 - mmengine - INFO - Epoch(train) [16][380/940] lr: 1.0000e-02 eta: 18:10:23 time: 0.8786 data_time: 0.0311 memory: 22701 grad_norm: 4.6729 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7945 loss: 1.7945 2022/09/05 12:16:08 - mmengine - INFO - Epoch(train) [16][400/940] lr: 1.0000e-02 eta: 18:09:46 time: 0.6364 data_time: 0.0292 memory: 22701 grad_norm: 4.6044 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.8007 loss: 1.8007 2022/09/05 12:16:26 - mmengine - INFO - Epoch(train) [16][420/940] lr: 1.0000e-02 eta: 18:09:39 time: 0.9058 data_time: 0.0293 memory: 22701 grad_norm: 4.6153 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7674 loss: 1.7674 2022/09/05 12:16:43 - mmengine - INFO - Epoch(train) [16][440/940] lr: 1.0000e-02 eta: 18:09:24 time: 0.8357 data_time: 0.0794 memory: 22701 grad_norm: 4.5590 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6980 loss: 1.6980 2022/09/05 12:16:59 - mmengine - INFO - Epoch(train) [16][460/940] lr: 1.0000e-02 eta: 18:09:04 time: 0.7898 data_time: 0.1223 memory: 22701 grad_norm: 4.6531 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6539 loss: 1.6539 2022/09/05 12:17:17 - mmengine - INFO - Epoch(train) [16][480/940] lr: 1.0000e-02 eta: 18:08:57 time: 0.9052 data_time: 0.0955 memory: 22701 grad_norm: 4.6392 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7628 loss: 1.7628 2022/09/05 12:17:37 - mmengine - INFO - Epoch(train) [16][500/940] lr: 1.0000e-02 eta: 18:09:03 time: 1.0360 data_time: 0.2873 memory: 22701 grad_norm: 4.6204 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.8414 loss: 1.8414 2022/09/05 12:17:55 - mmengine - INFO - Epoch(train) [16][520/940] lr: 1.0000e-02 eta: 18:08:53 time: 0.8798 data_time: 0.3956 memory: 22701 grad_norm: 4.6338 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.7938 loss: 1.7938 2022/09/05 12:18:13 - mmengine - INFO - Epoch(train) [16][540/940] lr: 1.0000e-02 eta: 18:08:47 time: 0.9172 data_time: 0.5195 memory: 22701 grad_norm: 4.6510 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6932 loss: 1.6932 2022/09/05 12:18:28 - mmengine - INFO - Epoch(train) [16][560/940] lr: 1.0000e-02 eta: 18:08:22 time: 0.7512 data_time: 0.3562 memory: 22701 grad_norm: 4.5291 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6947 loss: 1.6947 2022/09/05 12:18:46 - mmengine - INFO - Epoch(train) [16][580/940] lr: 1.0000e-02 eta: 18:08:11 time: 0.8687 data_time: 0.4058 memory: 22701 grad_norm: 4.5749 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7097 loss: 1.7097 2022/09/05 12:19:03 - mmengine - INFO - Epoch(train) [16][600/940] lr: 1.0000e-02 eta: 18:08:01 time: 0.8874 data_time: 0.2022 memory: 22701 grad_norm: 4.6139 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7893 loss: 1.7893 2022/09/05 12:19:20 - mmengine - INFO - Epoch(train) [16][620/940] lr: 1.0000e-02 eta: 18:07:45 time: 0.8246 data_time: 0.2695 memory: 22701 grad_norm: 4.5676 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9023 loss: 1.9023 2022/09/05 12:19:37 - mmengine - INFO - Epoch(train) [16][640/940] lr: 1.0000e-02 eta: 18:07:34 time: 0.8775 data_time: 0.1502 memory: 22701 grad_norm: 4.5886 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6772 loss: 1.6772 2022/09/05 12:19:54 - mmengine - INFO - Epoch(train) [16][660/940] lr: 1.0000e-02 eta: 18:07:17 time: 0.8141 data_time: 0.0639 memory: 22701 grad_norm: 4.6005 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9966 loss: 1.9966 2022/09/05 12:20:12 - mmengine - INFO - Epoch(train) [16][680/940] lr: 1.0000e-02 eta: 18:07:09 time: 0.9026 data_time: 0.0922 memory: 22701 grad_norm: 4.5320 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6890 loss: 1.6890 2022/09/05 12:20:27 - mmengine - INFO - Epoch(train) [16][700/940] lr: 1.0000e-02 eta: 18:06:46 time: 0.7652 data_time: 0.0449 memory: 22701 grad_norm: 4.5574 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9155 loss: 1.9155 2022/09/05 12:20:47 - mmengine - INFO - Epoch(train) [16][720/940] lr: 1.0000e-02 eta: 18:06:46 time: 0.9697 data_time: 0.0230 memory: 22701 grad_norm: 4.5456 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7021 loss: 1.7021 2022/09/05 12:21:03 - mmengine - INFO - Epoch(train) [16][740/940] lr: 1.0000e-02 eta: 18:06:28 time: 0.8176 data_time: 0.0246 memory: 22701 grad_norm: 4.5716 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7433 loss: 1.7433 2022/09/05 12:21:21 - mmengine - INFO - Epoch(train) [16][760/940] lr: 1.0000e-02 eta: 18:06:18 time: 0.8834 data_time: 0.0235 memory: 22701 grad_norm: 4.5960 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6135 loss: 1.6135 2022/09/05 12:21:35 - mmengine - INFO - Epoch(train) [16][780/940] lr: 1.0000e-02 eta: 18:05:51 time: 0.7261 data_time: 0.0302 memory: 22701 grad_norm: 4.5683 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8657 loss: 1.8657 2022/09/05 12:21:52 - mmengine - INFO - Epoch(train) [16][800/940] lr: 1.0000e-02 eta: 18:05:36 time: 0.8310 data_time: 0.0280 memory: 22701 grad_norm: 4.5748 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7466 loss: 1.7466 2022/09/05 12:22:06 - mmengine - INFO - Epoch(train) [16][820/940] lr: 1.0000e-02 eta: 18:05:08 time: 0.7122 data_time: 0.0314 memory: 22701 grad_norm: 4.6318 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6239 loss: 1.6239 2022/09/05 12:22:22 - mmengine - INFO - Epoch(train) [16][840/940] lr: 1.0000e-02 eta: 18:04:52 time: 0.8274 data_time: 0.0281 memory: 22701 grad_norm: 4.5261 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8276 loss: 1.8276 2022/09/05 12:22:37 - mmengine - INFO - Epoch(train) [16][860/940] lr: 1.0000e-02 eta: 18:04:24 time: 0.7167 data_time: 0.0312 memory: 22701 grad_norm: 4.6352 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6778 loss: 1.6778 2022/09/05 12:22:55 - mmengine - INFO - Epoch(train) [16][880/940] lr: 1.0000e-02 eta: 18:04:15 time: 0.8931 data_time: 0.0301 memory: 22701 grad_norm: 4.7666 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8681 loss: 1.8681 2022/09/05 12:23:09 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:23:09 - mmengine - INFO - Epoch(train) [16][900/940] lr: 1.0000e-02 eta: 18:03:49 time: 0.7345 data_time: 0.0260 memory: 22701 grad_norm: 4.5888 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6595 loss: 1.6595 2022/09/05 12:23:26 - mmengine - INFO - Epoch(train) [16][920/940] lr: 1.0000e-02 eta: 18:03:36 time: 0.8529 data_time: 0.0231 memory: 22701 grad_norm: 4.5531 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8736 loss: 1.8736 2022/09/05 12:23:40 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:23:40 - mmengine - INFO - Epoch(train) [16][940/940] lr: 1.0000e-02 eta: 18:03:05 time: 0.6866 data_time: 0.0812 memory: 22701 grad_norm: 4.7703 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.7105 loss: 1.7105 2022/09/05 12:23:54 - mmengine - INFO - Epoch(val) [16][20/78] eta: 0:00:39 time: 0.6782 data_time: 0.5598 memory: 2247 2022/09/05 12:24:03 - mmengine - INFO - Epoch(val) [16][40/78] eta: 0:00:17 time: 0.4564 data_time: 0.3366 memory: 2247 2022/09/05 12:24:16 - mmengine - INFO - Epoch(val) [16][60/78] eta: 0:00:11 time: 0.6559 data_time: 0.5390 memory: 2247 2022/09/05 12:24:29 - mmengine - INFO - Epoch(val) [16][78/78] acc/top1: 0.6251 acc/top5: 0.8462 acc/mean1: 0.6250 2022/09/05 12:24:29 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_16.pth is removed 2022/09/05 12:24:30 - mmengine - INFO - The best checkpoint with 0.6251 acc/top1 at 17 epoch is saved to best_acc/top1_epoch_17.pth. 2022/09/05 12:24:52 - mmengine - INFO - Epoch(train) [17][20/940] lr: 1.0000e-02 eta: 18:03:14 time: 1.0700 data_time: 0.6951 memory: 22701 grad_norm: 4.5324 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6869 loss: 1.6869 2022/09/05 12:25:06 - mmengine - INFO - Epoch(train) [17][40/940] lr: 1.0000e-02 eta: 18:02:46 time: 0.7068 data_time: 0.3369 memory: 22701 grad_norm: 4.5074 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8479 loss: 1.8479 2022/09/05 12:25:25 - mmengine - INFO - Epoch(train) [17][60/940] lr: 1.0000e-02 eta: 18:02:41 time: 0.9410 data_time: 0.4872 memory: 22701 grad_norm: 4.5746 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6795 loss: 1.6795 2022/09/05 12:25:37 - mmengine - INFO - Epoch(train) [17][80/940] lr: 1.0000e-02 eta: 18:02:04 time: 0.6244 data_time: 0.2001 memory: 22701 grad_norm: 4.5053 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.6055 loss: 1.6055 2022/09/05 12:25:54 - mmengine - INFO - Epoch(train) [17][100/940] lr: 1.0000e-02 eta: 18:01:48 time: 0.8280 data_time: 0.2534 memory: 22701 grad_norm: 4.5083 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5415 loss: 1.5415 2022/09/05 12:26:09 - mmengine - INFO - Epoch(train) [17][120/940] lr: 1.0000e-02 eta: 18:01:28 time: 0.7898 data_time: 0.1024 memory: 22701 grad_norm: 4.5896 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7469 loss: 1.7469 2022/09/05 12:26:27 - mmengine - INFO - Epoch(train) [17][140/940] lr: 1.0000e-02 eta: 18:01:17 time: 0.8759 data_time: 0.2774 memory: 22701 grad_norm: 4.5469 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7435 loss: 1.7435 2022/09/05 12:26:43 - mmengine - INFO - Epoch(train) [17][160/940] lr: 1.0000e-02 eta: 18:00:59 time: 0.8018 data_time: 0.1137 memory: 22701 grad_norm: 4.5690 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.8818 loss: 1.8818 2022/09/05 12:27:00 - mmengine - INFO - Epoch(train) [17][180/940] lr: 1.0000e-02 eta: 18:00:46 time: 0.8608 data_time: 0.1322 memory: 22701 grad_norm: 4.6226 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5866 loss: 1.5866 2022/09/05 12:27:18 - mmengine - INFO - Epoch(train) [17][200/940] lr: 1.0000e-02 eta: 18:00:35 time: 0.8720 data_time: 0.0320 memory: 22701 grad_norm: 4.5929 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6987 loss: 1.6987 2022/09/05 12:27:35 - mmengine - INFO - Epoch(train) [17][220/940] lr: 1.0000e-02 eta: 18:00:24 time: 0.8844 data_time: 0.2806 memory: 22701 grad_norm: 4.5925 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6119 loss: 1.6119 2022/09/05 12:27:50 - mmengine - INFO - Epoch(train) [17][240/940] lr: 1.0000e-02 eta: 17:59:59 time: 0.7323 data_time: 0.3278 memory: 22701 grad_norm: 4.6697 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 1.8162 loss: 1.8162 2022/09/05 12:28:09 - mmengine - INFO - Epoch(train) [17][260/940] lr: 1.0000e-02 eta: 17:59:57 time: 0.9635 data_time: 0.5681 memory: 22701 grad_norm: 4.5844 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6877 loss: 1.6877 2022/09/05 12:28:23 - mmengine - INFO - Epoch(train) [17][280/940] lr: 1.0000e-02 eta: 17:59:25 time: 0.6806 data_time: 0.2760 memory: 22701 grad_norm: 4.6028 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6115 loss: 1.6115 2022/09/05 12:28:41 - mmengine - INFO - Epoch(train) [17][300/940] lr: 1.0000e-02 eta: 17:59:20 time: 0.9320 data_time: 0.5373 memory: 22701 grad_norm: 4.5202 top1_acc: 0.4688 top5_acc: 0.5938 loss_cls: 1.7888 loss: 1.7888 2022/09/05 12:28:56 - mmengine - INFO - Epoch(train) [17][320/940] lr: 1.0000e-02 eta: 17:58:53 time: 0.7162 data_time: 0.3380 memory: 22701 grad_norm: 4.5677 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8654 loss: 1.8654 2022/09/05 12:29:15 - mmengine - INFO - Epoch(train) [17][340/940] lr: 1.0000e-02 eta: 17:58:52 time: 0.9759 data_time: 0.5072 memory: 22701 grad_norm: 4.6543 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8119 loss: 1.8119 2022/09/05 12:29:33 - mmengine - INFO - Epoch(train) [17][360/940] lr: 1.0000e-02 eta: 17:58:42 time: 0.8901 data_time: 0.1281 memory: 22701 grad_norm: 4.6336 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.8086 loss: 1.8086 2022/09/05 12:29:51 - mmengine - INFO - Epoch(train) [17][380/940] lr: 1.0000e-02 eta: 17:58:32 time: 0.8820 data_time: 0.2702 memory: 22701 grad_norm: 4.6466 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7256 loss: 1.7256 2022/09/05 12:30:06 - mmengine - INFO - Epoch(train) [17][400/940] lr: 1.0000e-02 eta: 17:58:11 time: 0.7849 data_time: 0.2224 memory: 22701 grad_norm: 4.6030 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7417 loss: 1.7417 2022/09/05 12:30:25 - mmengine - INFO - Epoch(train) [17][420/940] lr: 1.0000e-02 eta: 17:58:05 time: 0.9190 data_time: 0.4230 memory: 22701 grad_norm: 4.7388 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.7518 loss: 1.7518 2022/09/05 12:30:41 - mmengine - INFO - Epoch(train) [17][440/940] lr: 1.0000e-02 eta: 17:57:47 time: 0.8095 data_time: 0.3698 memory: 22701 grad_norm: 4.6656 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7022 loss: 1.7022 2022/09/05 12:31:03 - mmengine - INFO - Epoch(train) [17][460/940] lr: 1.0000e-02 eta: 17:57:58 time: 1.0988 data_time: 0.6945 memory: 22701 grad_norm: 4.6547 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7776 loss: 1.7776 2022/09/05 12:31:17 - mmengine - INFO - Epoch(train) [17][480/940] lr: 1.0000e-02 eta: 17:57:31 time: 0.7161 data_time: 0.3310 memory: 22701 grad_norm: 4.6726 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7958 loss: 1.7958 2022/09/05 12:31:37 - mmengine - INFO - Epoch(train) [17][500/940] lr: 1.0000e-02 eta: 17:57:31 time: 0.9916 data_time: 0.5801 memory: 22701 grad_norm: 4.6338 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8122 loss: 1.8122 2022/09/05 12:31:54 - mmengine - INFO - Epoch(train) [17][520/940] lr: 1.0000e-02 eta: 17:57:15 time: 0.8267 data_time: 0.3505 memory: 22701 grad_norm: 4.7088 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6993 loss: 1.6993 2022/09/05 12:32:14 - mmengine - INFO - Epoch(train) [17][540/940] lr: 1.0000e-02 eta: 17:57:16 time: 1.0010 data_time: 0.4194 memory: 22701 grad_norm: 4.6693 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8318 loss: 1.8318 2022/09/05 12:32:27 - mmengine - INFO - Epoch(train) [17][560/940] lr: 1.0000e-02 eta: 17:56:46 time: 0.6827 data_time: 0.2697 memory: 22701 grad_norm: 4.6938 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7862 loss: 1.7862 2022/09/05 12:32:46 - mmengine - INFO - Epoch(train) [17][580/940] lr: 1.0000e-02 eta: 17:56:40 time: 0.9288 data_time: 0.4068 memory: 22701 grad_norm: 4.6502 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7257 loss: 1.7257 2022/09/05 12:33:01 - mmengine - INFO - Epoch(train) [17][600/940] lr: 1.0000e-02 eta: 17:56:16 time: 0.7553 data_time: 0.3135 memory: 22701 grad_norm: 4.6091 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8611 loss: 1.8611 2022/09/05 12:33:17 - mmengine - INFO - Epoch(train) [17][620/940] lr: 1.0000e-02 eta: 17:55:59 time: 0.8174 data_time: 0.3087 memory: 22701 grad_norm: 4.6932 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8400 loss: 1.8400 2022/09/05 12:33:31 - mmengine - INFO - Epoch(train) [17][640/940] lr: 1.0000e-02 eta: 17:55:28 time: 0.6810 data_time: 0.2486 memory: 22701 grad_norm: 4.6425 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6710 loss: 1.6710 2022/09/05 12:33:47 - mmengine - INFO - Epoch(train) [17][660/940] lr: 1.0000e-02 eta: 17:55:11 time: 0.8165 data_time: 0.3818 memory: 22701 grad_norm: 4.5422 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.5627 loss: 1.5627 2022/09/05 12:34:04 - mmengine - INFO - Epoch(train) [17][680/940] lr: 1.0000e-02 eta: 17:54:58 time: 0.8539 data_time: 0.2124 memory: 22701 grad_norm: 4.6458 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8355 loss: 1.8355 2022/09/05 12:34:21 - mmengine - INFO - Epoch(train) [17][700/940] lr: 1.0000e-02 eta: 17:54:39 time: 0.8027 data_time: 0.0879 memory: 22701 grad_norm: 4.6571 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8263 loss: 1.8263 2022/09/05 12:34:35 - mmengine - INFO - Epoch(train) [17][720/940] lr: 1.0000e-02 eta: 17:54:11 time: 0.7116 data_time: 0.1072 memory: 22701 grad_norm: 4.6273 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6665 loss: 1.6665 2022/09/05 12:34:51 - mmengine - INFO - Epoch(train) [17][740/940] lr: 1.0000e-02 eta: 17:53:52 time: 0.7980 data_time: 0.2620 memory: 22701 grad_norm: 4.5112 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.5959 loss: 1.5959 2022/09/05 12:35:06 - mmengine - INFO - Epoch(train) [17][760/940] lr: 1.0000e-02 eta: 17:53:28 time: 0.7484 data_time: 0.1785 memory: 22701 grad_norm: 4.5873 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7138 loss: 1.7138 2022/09/05 12:35:22 - mmengine - INFO - Epoch(train) [17][780/940] lr: 1.0000e-02 eta: 17:53:11 time: 0.8164 data_time: 0.2453 memory: 22701 grad_norm: 4.6497 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.7434 loss: 1.7434 2022/09/05 12:35:38 - mmengine - INFO - Epoch(train) [17][800/940] lr: 1.0000e-02 eta: 17:52:52 time: 0.7959 data_time: 0.0218 memory: 22701 grad_norm: 4.4978 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7972 loss: 1.7972 2022/09/05 12:35:57 - mmengine - INFO - Epoch(train) [17][820/940] lr: 1.0000e-02 eta: 17:52:47 time: 0.9442 data_time: 0.0295 memory: 22701 grad_norm: 4.5805 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6711 loss: 1.6711 2022/09/05 12:36:16 - mmengine - INFO - Epoch(train) [17][840/940] lr: 1.0000e-02 eta: 17:52:44 time: 0.9562 data_time: 0.0201 memory: 22701 grad_norm: 4.5731 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7839 loss: 1.7839 2022/09/05 12:36:34 - mmengine - INFO - Epoch(train) [17][860/940] lr: 1.0000e-02 eta: 17:52:37 time: 0.9209 data_time: 0.0232 memory: 22701 grad_norm: 4.6609 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7980 loss: 1.7980 2022/09/05 12:36:56 - mmengine - INFO - Epoch(train) [17][880/940] lr: 1.0000e-02 eta: 17:52:44 time: 1.0641 data_time: 0.0239 memory: 22701 grad_norm: 4.6396 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8146 loss: 1.8146 2022/09/05 12:37:11 - mmengine - INFO - Epoch(train) [17][900/940] lr: 1.0000e-02 eta: 17:52:21 time: 0.7610 data_time: 0.0455 memory: 22701 grad_norm: 4.6260 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8233 loss: 1.8233 2022/09/05 12:37:28 - mmengine - INFO - Epoch(train) [17][920/940] lr: 1.0000e-02 eta: 17:52:06 time: 0.8393 data_time: 0.0465 memory: 22701 grad_norm: 4.6741 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7899 loss: 1.7899 2022/09/05 12:37:42 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:37:42 - mmengine - INFO - Epoch(train) [17][940/940] lr: 1.0000e-02 eta: 17:51:40 time: 0.7194 data_time: 0.0294 memory: 22701 grad_norm: 4.8400 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.6215 loss: 1.6215 2022/09/05 12:37:56 - mmengine - INFO - Epoch(val) [17][20/78] eta: 0:00:40 time: 0.6920 data_time: 0.5702 memory: 2247 2022/09/05 12:38:05 - mmengine - INFO - Epoch(val) [17][40/78] eta: 0:00:17 time: 0.4633 data_time: 0.3424 memory: 2247 2022/09/05 12:38:18 - mmengine - INFO - Epoch(val) [17][60/78] eta: 0:00:11 time: 0.6582 data_time: 0.5404 memory: 2247 2022/09/05 12:38:28 - mmengine - INFO - Epoch(val) [17][78/78] acc/top1: 0.6265 acc/top5: 0.8466 acc/mean1: 0.6264 2022/09/05 12:38:28 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_17.pth is removed 2022/09/05 12:38:29 - mmengine - INFO - The best checkpoint with 0.6265 acc/top1 at 18 epoch is saved to best_acc/top1_epoch_18.pth. 2022/09/05 12:38:49 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:38:49 - mmengine - INFO - Epoch(train) [18][20/940] lr: 1.0000e-02 eta: 17:51:40 time: 0.9991 data_time: 0.4641 memory: 22701 grad_norm: 4.5280 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8180 loss: 1.8180 2022/09/05 12:39:03 - mmengine - INFO - Epoch(train) [18][40/940] lr: 1.0000e-02 eta: 17:51:12 time: 0.6991 data_time: 0.1414 memory: 22701 grad_norm: 4.5873 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6276 loss: 1.6276 2022/09/05 12:39:20 - mmengine - INFO - Epoch(train) [18][60/940] lr: 1.0000e-02 eta: 17:51:00 time: 0.8697 data_time: 0.2504 memory: 22701 grad_norm: 4.6053 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7901 loss: 1.7901 2022/09/05 12:39:35 - mmengine - INFO - Epoch(train) [18][80/940] lr: 1.0000e-02 eta: 17:50:32 time: 0.7090 data_time: 0.1128 memory: 22701 grad_norm: 4.5688 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6752 loss: 1.6752 2022/09/05 12:39:51 - mmengine - INFO - Epoch(train) [18][100/940] lr: 1.0000e-02 eta: 17:50:12 time: 0.7941 data_time: 0.1495 memory: 22701 grad_norm: 4.5921 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7674 loss: 1.7674 2022/09/05 12:40:04 - mmengine - INFO - Epoch(train) [18][120/940] lr: 1.0000e-02 eta: 17:49:40 time: 0.6563 data_time: 0.0912 memory: 22701 grad_norm: 4.5709 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6974 loss: 1.6974 2022/09/05 12:40:20 - mmengine - INFO - Epoch(train) [18][140/940] lr: 1.0000e-02 eta: 17:49:20 time: 0.7938 data_time: 0.0904 memory: 22701 grad_norm: 4.6064 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5907 loss: 1.5907 2022/09/05 12:40:33 - mmengine - INFO - Epoch(train) [18][160/940] lr: 1.0000e-02 eta: 17:48:51 time: 0.6915 data_time: 0.1228 memory: 22701 grad_norm: 4.6085 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6543 loss: 1.6543 2022/09/05 12:40:50 - mmengine - INFO - Epoch(train) [18][180/940] lr: 1.0000e-02 eta: 17:48:37 time: 0.8526 data_time: 0.1731 memory: 22701 grad_norm: 4.5980 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6169 loss: 1.6169 2022/09/05 12:41:05 - mmengine - INFO - Epoch(train) [18][200/940] lr: 1.0000e-02 eta: 17:48:10 time: 0.7058 data_time: 0.2471 memory: 22701 grad_norm: 4.5761 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.7564 loss: 1.7564 2022/09/05 12:41:23 - mmengine - INFO - Epoch(train) [18][220/940] lr: 1.0000e-02 eta: 17:48:01 time: 0.9014 data_time: 0.1685 memory: 22701 grad_norm: 4.5777 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7411 loss: 1.7411 2022/09/05 12:41:37 - mmengine - INFO - Epoch(train) [18][240/940] lr: 1.0000e-02 eta: 17:47:36 time: 0.7393 data_time: 0.1596 memory: 22701 grad_norm: 4.5777 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6234 loss: 1.6234 2022/09/05 12:41:59 - mmengine - INFO - Epoch(train) [18][260/940] lr: 1.0000e-02 eta: 17:47:46 time: 1.1034 data_time: 0.1612 memory: 22701 grad_norm: 4.6874 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7952 loss: 1.7952 2022/09/05 12:42:17 - mmengine - INFO - Epoch(train) [18][280/940] lr: 1.0000e-02 eta: 17:47:33 time: 0.8534 data_time: 0.2372 memory: 22701 grad_norm: 4.6812 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7896 loss: 1.7896 2022/09/05 12:42:35 - mmengine - INFO - Epoch(train) [18][300/940] lr: 1.0000e-02 eta: 17:47:25 time: 0.9171 data_time: 0.2923 memory: 22701 grad_norm: 4.5337 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8239 loss: 1.8239 2022/09/05 12:42:54 - mmengine - INFO - Epoch(train) [18][320/940] lr: 1.0000e-02 eta: 17:47:19 time: 0.9319 data_time: 0.4059 memory: 22701 grad_norm: 4.4952 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6785 loss: 1.6785 2022/09/05 12:43:15 - mmengine - INFO - Epoch(train) [18][340/940] lr: 1.0000e-02 eta: 17:47:26 time: 1.0720 data_time: 0.5395 memory: 22701 grad_norm: 4.4305 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6146 loss: 1.6146 2022/09/05 12:43:31 - mmengine - INFO - Epoch(train) [18][360/940] lr: 1.0000e-02 eta: 17:47:09 time: 0.8212 data_time: 0.2660 memory: 22701 grad_norm: 4.6095 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7754 loss: 1.7754 2022/09/05 12:43:52 - mmengine - INFO - Epoch(train) [18][380/940] lr: 1.0000e-02 eta: 17:47:12 time: 1.0298 data_time: 0.5273 memory: 22701 grad_norm: 4.6087 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7349 loss: 1.7349 2022/09/05 12:44:05 - mmengine - INFO - Epoch(train) [18][400/940] lr: 1.0000e-02 eta: 17:46:38 time: 0.6341 data_time: 0.2472 memory: 22701 grad_norm: 4.6100 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6600 loss: 1.6600 2022/09/05 12:44:21 - mmengine - INFO - Epoch(train) [18][420/940] lr: 1.0000e-02 eta: 17:46:20 time: 0.8110 data_time: 0.2387 memory: 22701 grad_norm: 4.5999 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.7746 loss: 1.7746 2022/09/05 12:44:36 - mmengine - INFO - Epoch(train) [18][440/940] lr: 1.0000e-02 eta: 17:45:57 time: 0.7599 data_time: 0.2023 memory: 22701 grad_norm: 4.6286 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7059 loss: 1.7059 2022/09/05 12:44:54 - mmengine - INFO - Epoch(train) [18][460/940] lr: 1.0000e-02 eta: 17:45:48 time: 0.9015 data_time: 0.5077 memory: 22701 grad_norm: 4.5557 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6518 loss: 1.6518 2022/09/05 12:45:09 - mmengine - INFO - Epoch(train) [18][480/940] lr: 1.0000e-02 eta: 17:45:22 time: 0.7228 data_time: 0.3260 memory: 22701 grad_norm: 4.4657 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6478 loss: 1.6478 2022/09/05 12:45:26 - mmengine - INFO - Epoch(train) [18][500/940] lr: 1.0000e-02 eta: 17:45:09 time: 0.8663 data_time: 0.4538 memory: 22701 grad_norm: 4.6069 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7513 loss: 1.7513 2022/09/05 12:45:40 - mmengine - INFO - Epoch(train) [18][520/940] lr: 1.0000e-02 eta: 17:44:42 time: 0.7059 data_time: 0.2854 memory: 22701 grad_norm: 4.6098 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7096 loss: 1.7096 2022/09/05 12:45:57 - mmengine - INFO - Epoch(train) [18][540/940] lr: 1.0000e-02 eta: 17:44:27 time: 0.8412 data_time: 0.4425 memory: 22701 grad_norm: 4.6051 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6025 loss: 1.6025 2022/09/05 12:46:12 - mmengine - INFO - Epoch(train) [18][560/940] lr: 1.0000e-02 eta: 17:44:02 time: 0.7385 data_time: 0.3307 memory: 22701 grad_norm: 4.5962 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8302 loss: 1.8302 2022/09/05 12:46:29 - mmengine - INFO - Epoch(train) [18][580/940] lr: 1.0000e-02 eta: 17:43:51 time: 0.8757 data_time: 0.4932 memory: 22701 grad_norm: 4.5806 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7588 loss: 1.7588 2022/09/05 12:46:44 - mmengine - INFO - Epoch(train) [18][600/940] lr: 1.0000e-02 eta: 17:43:27 time: 0.7431 data_time: 0.3422 memory: 22701 grad_norm: 4.5203 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6819 loss: 1.6819 2022/09/05 12:47:04 - mmengine - INFO - Epoch(train) [18][620/940] lr: 1.0000e-02 eta: 17:43:25 time: 0.9803 data_time: 0.5758 memory: 22701 grad_norm: 4.6839 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6896 loss: 1.6896 2022/09/05 12:47:17 - mmengine - INFO - Epoch(train) [18][640/940] lr: 1.0000e-02 eta: 17:42:56 time: 0.6888 data_time: 0.3020 memory: 22701 grad_norm: 4.6278 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8126 loss: 1.8126 2022/09/05 12:47:32 - mmengine - INFO - Epoch(train) [18][660/940] lr: 1.0000e-02 eta: 17:42:32 time: 0.7514 data_time: 0.3483 memory: 22701 grad_norm: 4.6385 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6751 loss: 1.6751 2022/09/05 12:47:47 - mmengine - INFO - Epoch(train) [18][680/940] lr: 1.0000e-02 eta: 17:42:06 time: 0.7128 data_time: 0.3121 memory: 22701 grad_norm: 4.6766 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7723 loss: 1.7723 2022/09/05 12:48:04 - mmengine - INFO - Epoch(train) [18][700/940] lr: 1.0000e-02 eta: 17:41:55 time: 0.8899 data_time: 0.4877 memory: 22701 grad_norm: 4.6187 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7542 loss: 1.7542 2022/09/05 12:48:23 - mmengine - INFO - Epoch(train) [18][720/940] lr: 1.0000e-02 eta: 17:41:46 time: 0.9066 data_time: 0.4793 memory: 22701 grad_norm: 4.5865 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.8017 loss: 1.8017 2022/09/05 12:48:41 - mmengine - INFO - Epoch(train) [18][740/940] lr: 1.0000e-02 eta: 17:41:41 time: 0.9421 data_time: 0.4638 memory: 22701 grad_norm: 4.6751 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7362 loss: 1.7362 2022/09/05 12:48:58 - mmengine - INFO - Epoch(train) [18][760/940] lr: 1.0000e-02 eta: 17:41:23 time: 0.8137 data_time: 0.3126 memory: 22701 grad_norm: 4.6615 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8083 loss: 1.8083 2022/09/05 12:49:17 - mmengine - INFO - Epoch(train) [18][780/940] lr: 1.0000e-02 eta: 17:41:21 time: 0.9752 data_time: 0.5031 memory: 22701 grad_norm: 4.5197 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5494 loss: 1.5494 2022/09/05 12:49:35 - mmengine - INFO - Epoch(train) [18][800/940] lr: 1.0000e-02 eta: 17:41:09 time: 0.8732 data_time: 0.4027 memory: 22701 grad_norm: 4.5745 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0025 loss: 2.0025 2022/09/05 12:49:51 - mmengine - INFO - Epoch(train) [18][820/940] lr: 1.0000e-02 eta: 17:40:52 time: 0.8250 data_time: 0.4337 memory: 22701 grad_norm: 4.6254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7927 loss: 1.7927 2022/09/05 12:50:05 - mmengine - INFO - Epoch(train) [18][840/940] lr: 1.0000e-02 eta: 17:40:25 time: 0.7058 data_time: 0.2652 memory: 22701 grad_norm: 4.5566 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6532 loss: 1.6532 2022/09/05 12:50:21 - mmengine - INFO - Epoch(train) [18][860/940] lr: 1.0000e-02 eta: 17:40:04 time: 0.7714 data_time: 0.3713 memory: 22701 grad_norm: 4.6543 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7251 loss: 1.7251 2022/09/05 12:50:33 - mmengine - INFO - Epoch(train) [18][880/940] lr: 1.0000e-02 eta: 17:39:27 time: 0.6025 data_time: 0.2103 memory: 22701 grad_norm: 4.6435 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7098 loss: 1.7098 2022/09/05 12:50:50 - mmengine - INFO - Epoch(train) [18][900/940] lr: 1.0000e-02 eta: 17:39:12 time: 0.8455 data_time: 0.4324 memory: 22701 grad_norm: 4.6081 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7431 loss: 1.7431 2022/09/05 12:51:03 - mmengine - INFO - Epoch(train) [18][920/940] lr: 1.0000e-02 eta: 17:38:42 time: 0.6738 data_time: 0.2734 memory: 22701 grad_norm: 4.6527 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6469 loss: 1.6469 2022/09/05 12:51:18 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:51:18 - mmengine - INFO - Epoch(train) [18][940/940] lr: 1.0000e-02 eta: 17:38:18 time: 0.7437 data_time: 0.3264 memory: 22701 grad_norm: 4.8209 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.7449 loss: 1.7449 2022/09/05 12:51:18 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/09/05 12:51:34 - mmengine - INFO - Epoch(val) [18][20/78] eta: 0:00:40 time: 0.6909 data_time: 0.5761 memory: 2247 2022/09/05 12:51:42 - mmengine - INFO - Epoch(val) [18][40/78] eta: 0:00:16 time: 0.4397 data_time: 0.3224 memory: 2247 2022/09/05 12:51:55 - mmengine - INFO - Epoch(val) [18][60/78] eta: 0:00:11 time: 0.6542 data_time: 0.5369 memory: 2247 2022/09/05 12:52:05 - mmengine - INFO - Epoch(val) [18][78/78] acc/top1: 0.6281 acc/top5: 0.8488 acc/mean1: 0.6280 2022/09/05 12:52:05 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_18.pth is removed 2022/09/05 12:52:06 - mmengine - INFO - The best checkpoint with 0.6281 acc/top1 at 19 epoch is saved to best_acc/top1_epoch_19.pth. 2022/09/05 12:52:26 - mmengine - INFO - Epoch(train) [19][20/940] lr: 1.0000e-02 eta: 17:38:16 time: 0.9794 data_time: 0.5383 memory: 22701 grad_norm: 4.5467 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8452 loss: 1.8452 2022/09/05 12:52:38 - mmengine - INFO - Epoch(train) [19][40/940] lr: 1.0000e-02 eta: 17:37:43 time: 0.6454 data_time: 0.1298 memory: 22701 grad_norm: 4.5523 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6703 loss: 1.6703 2022/09/05 12:52:55 - mmengine - INFO - Epoch(train) [19][60/940] lr: 1.0000e-02 eta: 17:37:27 time: 0.8255 data_time: 0.3206 memory: 22701 grad_norm: 4.5563 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7038 loss: 1.7038 2022/09/05 12:53:09 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 12:53:09 - mmengine - INFO - Epoch(train) [19][80/940] lr: 1.0000e-02 eta: 17:36:58 time: 0.6882 data_time: 0.1813 memory: 22701 grad_norm: 4.5011 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6611 loss: 1.6611 2022/09/05 12:53:25 - mmengine - INFO - Epoch(train) [19][100/940] lr: 1.0000e-02 eta: 17:36:43 time: 0.8362 data_time: 0.3116 memory: 22701 grad_norm: 4.5546 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6855 loss: 1.6855 2022/09/05 12:53:41 - mmengine - INFO - Epoch(train) [19][120/940] lr: 1.0000e-02 eta: 17:36:24 time: 0.7935 data_time: 0.1115 memory: 22701 grad_norm: 4.5088 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6119 loss: 1.6119 2022/09/05 12:54:00 - mmengine - INFO - Epoch(train) [19][140/940] lr: 1.0000e-02 eta: 17:36:18 time: 0.9487 data_time: 0.0480 memory: 22701 grad_norm: 4.6881 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.6433 loss: 1.6433 2022/09/05 12:54:17 - mmengine - INFO - Epoch(train) [19][160/940] lr: 1.0000e-02 eta: 17:36:01 time: 0.8157 data_time: 0.0738 memory: 22701 grad_norm: 4.5467 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6981 loss: 1.6981 2022/09/05 12:54:38 - mmengine - INFO - Epoch(train) [19][180/940] lr: 1.0000e-02 eta: 17:36:06 time: 1.0541 data_time: 0.1705 memory: 22701 grad_norm: 4.5950 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6954 loss: 1.6954 2022/09/05 12:54:55 - mmengine - INFO - Epoch(train) [19][200/940] lr: 1.0000e-02 eta: 17:35:54 time: 0.8834 data_time: 0.0611 memory: 22701 grad_norm: 4.6523 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6168 loss: 1.6168 2022/09/05 12:55:15 - mmengine - INFO - Epoch(train) [19][220/940] lr: 1.0000e-02 eta: 17:35:51 time: 0.9711 data_time: 0.0574 memory: 22701 grad_norm: 4.4962 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6252 loss: 1.6252 2022/09/05 12:55:34 - mmengine - INFO - Epoch(train) [19][240/940] lr: 1.0000e-02 eta: 17:35:46 time: 0.9555 data_time: 0.0284 memory: 22701 grad_norm: 4.5580 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6483 loss: 1.6483 2022/09/05 12:55:47 - mmengine - INFO - Epoch(train) [19][260/940] lr: 1.0000e-02 eta: 17:35:16 time: 0.6728 data_time: 0.0278 memory: 22701 grad_norm: 4.5163 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.6747 loss: 1.6747 2022/09/05 12:56:06 - mmengine - INFO - Epoch(train) [19][280/940] lr: 1.0000e-02 eta: 17:35:09 time: 0.9232 data_time: 0.0255 memory: 22701 grad_norm: 4.6447 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7459 loss: 1.7459 2022/09/05 12:56:22 - mmengine - INFO - Epoch(train) [19][300/940] lr: 1.0000e-02 eta: 17:34:49 time: 0.7864 data_time: 0.0215 memory: 22701 grad_norm: 4.6023 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7441 loss: 1.7441 2022/09/05 12:56:40 - mmengine - INFO - Epoch(train) [19][320/940] lr: 1.0000e-02 eta: 17:34:41 time: 0.9232 data_time: 0.0316 memory: 22701 grad_norm: 4.5227 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5459 loss: 1.5459 2022/09/05 12:56:57 - mmengine - INFO - Epoch(train) [19][340/940] lr: 1.0000e-02 eta: 17:34:27 time: 0.8550 data_time: 0.0253 memory: 22701 grad_norm: 4.6012 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7575 loss: 1.7575 2022/09/05 12:57:14 - mmengine - INFO - Epoch(train) [19][360/940] lr: 1.0000e-02 eta: 17:34:11 time: 0.8302 data_time: 0.0254 memory: 22701 grad_norm: 4.5539 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5306 loss: 1.5306 2022/09/05 12:57:28 - mmengine - INFO - Epoch(train) [19][380/940] lr: 1.0000e-02 eta: 17:33:43 time: 0.6943 data_time: 0.0252 memory: 22701 grad_norm: 4.5108 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.6983 loss: 1.6983 2022/09/05 12:57:45 - mmengine - INFO - Epoch(train) [19][400/940] lr: 1.0000e-02 eta: 17:33:30 time: 0.8629 data_time: 0.0251 memory: 22701 grad_norm: 4.6433 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6716 loss: 1.6716 2022/09/05 12:57:59 - mmengine - INFO - Epoch(train) [19][420/940] lr: 1.0000e-02 eta: 17:33:06 time: 0.7312 data_time: 0.0265 memory: 22701 grad_norm: 4.6107 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8204 loss: 1.8204 2022/09/05 12:58:19 - mmengine - INFO - Epoch(train) [19][440/940] lr: 1.0000e-02 eta: 17:33:04 time: 0.9964 data_time: 0.0228 memory: 22701 grad_norm: 4.5591 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6274 loss: 1.6274 2022/09/05 12:58:33 - mmengine - INFO - Epoch(train) [19][460/940] lr: 1.0000e-02 eta: 17:32:36 time: 0.6865 data_time: 0.0253 memory: 22701 grad_norm: 4.5645 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7580 loss: 1.7580 2022/09/05 12:58:53 - mmengine - INFO - Epoch(train) [19][480/940] lr: 1.0000e-02 eta: 17:32:34 time: 0.9936 data_time: 0.0282 memory: 22701 grad_norm: 4.7200 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8000 loss: 1.8000 2022/09/05 12:59:09 - mmengine - INFO - Epoch(train) [19][500/940] lr: 1.0000e-02 eta: 17:32:13 time: 0.7754 data_time: 0.0237 memory: 22701 grad_norm: 4.5646 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5776 loss: 1.5776 2022/09/05 12:59:26 - mmengine - INFO - Epoch(train) [19][520/940] lr: 1.0000e-02 eta: 17:32:02 time: 0.8816 data_time: 0.0287 memory: 22701 grad_norm: 4.7303 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7214 loss: 1.7214 2022/09/05 12:59:40 - mmengine - INFO - Epoch(train) [19][540/940] lr: 1.0000e-02 eta: 17:31:34 time: 0.6957 data_time: 0.0273 memory: 22701 grad_norm: 4.6963 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6064 loss: 1.6064 2022/09/05 12:59:57 - mmengine - INFO - Epoch(train) [19][560/940] lr: 1.0000e-02 eta: 17:31:20 time: 0.8492 data_time: 0.0251 memory: 22701 grad_norm: 4.6064 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.8372 loss: 1.8372 2022/09/05 13:00:11 - mmengine - INFO - Epoch(train) [19][580/940] lr: 1.0000e-02 eta: 17:30:54 time: 0.7185 data_time: 0.0271 memory: 22701 grad_norm: 4.6067 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6535 loss: 1.6535 2022/09/05 13:00:28 - mmengine - INFO - Epoch(train) [19][600/940] lr: 1.0000e-02 eta: 17:30:40 time: 0.8488 data_time: 0.0242 memory: 22701 grad_norm: 4.5728 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7515 loss: 1.7515 2022/09/05 13:00:43 - mmengine - INFO - Epoch(train) [19][620/940] lr: 1.0000e-02 eta: 17:30:14 time: 0.7222 data_time: 0.0270 memory: 22701 grad_norm: 4.5593 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5804 loss: 1.5804 2022/09/05 13:01:01 - mmengine - INFO - Epoch(train) [19][640/940] lr: 1.0000e-02 eta: 17:30:03 time: 0.8839 data_time: 0.0256 memory: 22701 grad_norm: 4.5778 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6441 loss: 1.6441 2022/09/05 13:01:15 - mmengine - INFO - Epoch(train) [19][660/940] lr: 1.0000e-02 eta: 17:29:36 time: 0.7034 data_time: 0.0260 memory: 22701 grad_norm: 4.6411 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6621 loss: 1.6621 2022/09/05 13:01:31 - mmengine - INFO - Epoch(train) [19][680/940] lr: 1.0000e-02 eta: 17:29:19 time: 0.8198 data_time: 0.0260 memory: 22701 grad_norm: 4.6748 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8037 loss: 1.8037 2022/09/05 13:01:44 - mmengine - INFO - Epoch(train) [19][700/940] lr: 1.0000e-02 eta: 17:28:46 time: 0.6362 data_time: 0.0290 memory: 22701 grad_norm: 4.6770 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8073 loss: 1.8073 2022/09/05 13:01:59 - mmengine - INFO - Epoch(train) [19][720/940] lr: 1.0000e-02 eta: 17:28:26 time: 0.7760 data_time: 0.0248 memory: 22701 grad_norm: 4.5999 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7142 loss: 1.7142 2022/09/05 13:02:13 - mmengine - INFO - Epoch(train) [19][740/940] lr: 1.0000e-02 eta: 17:27:57 time: 0.6827 data_time: 0.0261 memory: 22701 grad_norm: 4.5266 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6782 loss: 1.6782 2022/09/05 13:02:32 - mmengine - INFO - Epoch(train) [19][760/940] lr: 1.0000e-02 eta: 17:27:50 time: 0.9334 data_time: 0.0242 memory: 22701 grad_norm: 4.6749 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6655 loss: 1.6655 2022/09/05 13:02:47 - mmengine - INFO - Epoch(train) [19][780/940] lr: 1.0000e-02 eta: 17:27:28 time: 0.7639 data_time: 0.0273 memory: 22701 grad_norm: 4.5762 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6201 loss: 1.6201 2022/09/05 13:03:03 - mmengine - INFO - Epoch(train) [19][800/940] lr: 1.0000e-02 eta: 17:27:11 time: 0.8113 data_time: 0.0277 memory: 22701 grad_norm: 4.6474 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6031 loss: 1.6031 2022/09/05 13:03:18 - mmengine - INFO - Epoch(train) [19][820/940] lr: 1.0000e-02 eta: 17:26:46 time: 0.7315 data_time: 0.0242 memory: 22701 grad_norm: 4.7397 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7661 loss: 1.7661 2022/09/05 13:03:34 - mmengine - INFO - Epoch(train) [19][840/940] lr: 1.0000e-02 eta: 17:26:29 time: 0.8098 data_time: 0.0272 memory: 22701 grad_norm: 4.6132 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6825 loss: 1.6825 2022/09/05 13:03:47 - mmengine - INFO - Epoch(train) [19][860/940] lr: 1.0000e-02 eta: 17:26:00 time: 0.6748 data_time: 0.0322 memory: 22701 grad_norm: 4.5963 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8188 loss: 1.8188 2022/09/05 13:04:05 - mmengine - INFO - Epoch(train) [19][880/940] lr: 1.0000e-02 eta: 17:25:48 time: 0.8837 data_time: 0.0327 memory: 22701 grad_norm: 4.5845 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.6107 loss: 1.6107 2022/09/05 13:04:22 - mmengine - INFO - Epoch(train) [19][900/940] lr: 1.0000e-02 eta: 17:25:33 time: 0.8400 data_time: 0.0247 memory: 22701 grad_norm: 4.5967 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7113 loss: 1.7113 2022/09/05 13:04:41 - mmengine - INFO - Epoch(train) [19][920/940] lr: 1.0000e-02 eta: 17:25:27 time: 0.9455 data_time: 0.0971 memory: 22701 grad_norm: 4.7172 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9121 loss: 1.9121 2022/09/05 13:04:55 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:04:55 - mmengine - INFO - Epoch(train) [19][940/940] lr: 1.0000e-02 eta: 17:25:03 time: 0.7312 data_time: 0.0195 memory: 22701 grad_norm: 4.8919 top1_acc: 0.1429 top5_acc: 0.4286 loss_cls: 1.8528 loss: 1.8528 2022/09/05 13:05:09 - mmengine - INFO - Epoch(val) [19][20/78] eta: 0:00:40 time: 0.6948 data_time: 0.5757 memory: 2247 2022/09/05 13:05:18 - mmengine - INFO - Epoch(val) [19][40/78] eta: 0:00:17 time: 0.4556 data_time: 0.3386 memory: 2247 2022/09/05 13:05:32 - mmengine - INFO - Epoch(val) [19][60/78] eta: 0:00:12 time: 0.6687 data_time: 0.5504 memory: 2247 2022/09/05 13:05:42 - mmengine - INFO - Epoch(val) [19][78/78] acc/top1: 0.6242 acc/top5: 0.8453 acc/mean1: 0.6240 2022/09/05 13:06:03 - mmengine - INFO - Epoch(train) [20][20/940] lr: 1.0000e-02 eta: 17:25:06 time: 1.0542 data_time: 0.6282 memory: 22701 grad_norm: 4.5660 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7738 loss: 1.7738 2022/09/05 13:06:18 - mmengine - INFO - Epoch(train) [20][40/940] lr: 1.0000e-02 eta: 17:24:44 time: 0.7536 data_time: 0.2847 memory: 22701 grad_norm: 4.5336 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6211 loss: 1.6211 2022/09/05 13:06:34 - mmengine - INFO - Epoch(train) [20][60/940] lr: 1.0000e-02 eta: 17:24:27 time: 0.8188 data_time: 0.3234 memory: 22701 grad_norm: 4.5594 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7304 loss: 1.7304 2022/09/05 13:06:49 - mmengine - INFO - Epoch(train) [20][80/940] lr: 1.0000e-02 eta: 17:24:02 time: 0.7318 data_time: 0.0971 memory: 22701 grad_norm: 4.4615 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7376 loss: 1.7376 2022/09/05 13:07:05 - mmengine - INFO - Epoch(train) [20][100/940] lr: 1.0000e-02 eta: 17:23:46 time: 0.8222 data_time: 0.0910 memory: 22701 grad_norm: 4.5170 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6112 loss: 1.6112 2022/09/05 13:07:20 - mmengine - INFO - Epoch(train) [20][120/940] lr: 1.0000e-02 eta: 17:23:21 time: 0.7223 data_time: 0.1227 memory: 22701 grad_norm: 4.5846 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6486 loss: 1.6486 2022/09/05 13:07:37 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:07:37 - mmengine - INFO - Epoch(train) [20][140/940] lr: 1.0000e-02 eta: 17:23:06 time: 0.8476 data_time: 0.1237 memory: 22701 grad_norm: 4.5370 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8537 loss: 1.8537 2022/09/05 13:07:51 - mmengine - INFO - Epoch(train) [20][160/940] lr: 1.0000e-02 eta: 17:22:41 time: 0.7177 data_time: 0.0324 memory: 22701 grad_norm: 4.5817 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5921 loss: 1.5921 2022/09/05 13:08:08 - mmengine - INFO - Epoch(train) [20][180/940] lr: 1.0000e-02 eta: 17:22:27 time: 0.8497 data_time: 0.0841 memory: 22701 grad_norm: 4.6668 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6934 loss: 1.6934 2022/09/05 13:08:23 - mmengine - INFO - Epoch(train) [20][200/940] lr: 1.0000e-02 eta: 17:22:05 time: 0.7562 data_time: 0.1749 memory: 22701 grad_norm: 4.5722 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5264 loss: 1.5264 2022/09/05 13:08:40 - mmengine - INFO - Epoch(train) [20][220/940] lr: 1.0000e-02 eta: 17:21:51 time: 0.8619 data_time: 0.3465 memory: 22701 grad_norm: 4.6532 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7837 loss: 1.7837 2022/09/05 13:08:56 - mmengine - INFO - Epoch(train) [20][240/940] lr: 1.0000e-02 eta: 17:21:33 time: 0.8008 data_time: 0.2695 memory: 22701 grad_norm: 4.5617 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6459 loss: 1.6459 2022/09/05 13:09:16 - mmengine - INFO - Epoch(train) [20][260/940] lr: 1.0000e-02 eta: 17:21:28 time: 0.9625 data_time: 0.3269 memory: 22701 grad_norm: 4.6420 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6426 loss: 1.6426 2022/09/05 13:09:30 - mmengine - INFO - Epoch(train) [20][280/940] lr: 1.0000e-02 eta: 17:21:03 time: 0.7154 data_time: 0.1328 memory: 22701 grad_norm: 4.5783 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7390 loss: 1.7390 2022/09/05 13:09:47 - mmengine - INFO - Epoch(train) [20][300/940] lr: 1.0000e-02 eta: 17:20:50 time: 0.8660 data_time: 0.0473 memory: 22701 grad_norm: 4.6047 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7069 loss: 1.7069 2022/09/05 13:10:02 - mmengine - INFO - Epoch(train) [20][320/940] lr: 1.0000e-02 eta: 17:20:26 time: 0.7356 data_time: 0.0208 memory: 22701 grad_norm: 4.5753 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.7125 loss: 1.7125 2022/09/05 13:10:19 - mmengine - INFO - Epoch(train) [20][340/940] lr: 1.0000e-02 eta: 17:20:11 time: 0.8443 data_time: 0.0244 memory: 22701 grad_norm: 4.5693 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7132 loss: 1.7132 2022/09/05 13:10:35 - mmengine - INFO - Epoch(train) [20][360/940] lr: 1.0000e-02 eta: 17:19:53 time: 0.8051 data_time: 0.0291 memory: 22701 grad_norm: 4.5872 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6563 loss: 1.6563 2022/09/05 13:10:52 - mmengine - INFO - Epoch(train) [20][380/940] lr: 1.0000e-02 eta: 17:19:40 time: 0.8645 data_time: 0.0375 memory: 22701 grad_norm: 4.6366 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8032 loss: 1.8032 2022/09/05 13:11:06 - mmengine - INFO - Epoch(train) [20][400/940] lr: 1.0000e-02 eta: 17:19:13 time: 0.6909 data_time: 0.0309 memory: 22701 grad_norm: 4.6221 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6875 loss: 1.6875 2022/09/05 13:11:27 - mmengine - INFO - Epoch(train) [20][420/940] lr: 1.0000e-02 eta: 17:19:14 time: 1.0317 data_time: 0.0247 memory: 22701 grad_norm: 4.6165 top1_acc: 0.4688 top5_acc: 0.9062 loss_cls: 1.7402 loss: 1.7402 2022/09/05 13:11:41 - mmengine - INFO - Epoch(train) [20][440/940] lr: 1.0000e-02 eta: 17:18:49 time: 0.7220 data_time: 0.0240 memory: 22701 grad_norm: 4.5985 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6071 loss: 1.6071 2022/09/05 13:12:00 - mmengine - INFO - Epoch(train) [20][460/940] lr: 1.0000e-02 eta: 17:18:41 time: 0.9361 data_time: 0.0280 memory: 22701 grad_norm: 4.6751 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6909 loss: 1.6909 2022/09/05 13:12:18 - mmengine - INFO - Epoch(train) [20][480/940] lr: 1.0000e-02 eta: 17:18:32 time: 0.9039 data_time: 0.0407 memory: 22701 grad_norm: 4.5960 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7147 loss: 1.7147 2022/09/05 13:12:33 - mmengine - INFO - Epoch(train) [20][500/940] lr: 1.0000e-02 eta: 17:18:11 time: 0.7705 data_time: 0.0337 memory: 22701 grad_norm: 4.6736 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7994 loss: 1.7994 2022/09/05 13:12:47 - mmengine - INFO - Epoch(train) [20][520/940] lr: 1.0000e-02 eta: 17:17:44 time: 0.6996 data_time: 0.0295 memory: 22701 grad_norm: 4.6143 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6933 loss: 1.6933 2022/09/05 13:13:04 - mmengine - INFO - Epoch(train) [20][540/940] lr: 1.0000e-02 eta: 17:17:26 time: 0.8080 data_time: 0.0288 memory: 22701 grad_norm: 4.6212 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6823 loss: 1.6823 2022/09/05 13:13:19 - mmengine - INFO - Epoch(train) [20][560/940] lr: 1.0000e-02 eta: 17:17:05 time: 0.7657 data_time: 0.0294 memory: 22701 grad_norm: 4.6109 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7602 loss: 1.7602 2022/09/05 13:13:36 - mmengine - INFO - Epoch(train) [20][580/940] lr: 1.0000e-02 eta: 17:16:53 time: 0.8695 data_time: 0.0273 memory: 22701 grad_norm: 4.6312 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6351 loss: 1.6351 2022/09/05 13:13:50 - mmengine - INFO - Epoch(train) [20][600/940] lr: 1.0000e-02 eta: 17:16:24 time: 0.6798 data_time: 0.0212 memory: 22701 grad_norm: 4.6090 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7636 loss: 1.7636 2022/09/05 13:14:06 - mmengine - INFO - Epoch(train) [20][620/940] lr: 1.0000e-02 eta: 17:16:07 time: 0.8098 data_time: 0.0449 memory: 22701 grad_norm: 4.5860 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6723 loss: 1.6723 2022/09/05 13:14:21 - mmengine - INFO - Epoch(train) [20][640/940] lr: 1.0000e-02 eta: 17:15:42 time: 0.7254 data_time: 0.0215 memory: 22701 grad_norm: 4.5889 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6809 loss: 1.6809 2022/09/05 13:14:38 - mmengine - INFO - Epoch(train) [20][660/940] lr: 1.0000e-02 eta: 17:15:31 time: 0.8820 data_time: 0.0306 memory: 22701 grad_norm: 4.5699 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7017 loss: 1.7017 2022/09/05 13:14:53 - mmengine - INFO - Epoch(train) [20][680/940] lr: 1.0000e-02 eta: 17:15:09 time: 0.7551 data_time: 0.0256 memory: 22701 grad_norm: 4.5783 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7150 loss: 1.7150 2022/09/05 13:15:13 - mmengine - INFO - Epoch(train) [20][700/940] lr: 1.0000e-02 eta: 17:15:03 time: 0.9612 data_time: 0.0243 memory: 22701 grad_norm: 4.5930 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7700 loss: 1.7700 2022/09/05 13:15:30 - mmengine - INFO - Epoch(train) [20][720/940] lr: 1.0000e-02 eta: 17:14:49 time: 0.8451 data_time: 0.0150 memory: 22701 grad_norm: 4.6058 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7351 loss: 1.7351 2022/09/05 13:15:47 - mmengine - INFO - Epoch(train) [20][740/940] lr: 1.0000e-02 eta: 17:14:35 time: 0.8558 data_time: 0.0741 memory: 22701 grad_norm: 4.5622 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5886 loss: 1.5886 2022/09/05 13:16:02 - mmengine - INFO - Epoch(train) [20][760/940] lr: 1.0000e-02 eta: 17:14:13 time: 0.7584 data_time: 0.0205 memory: 22701 grad_norm: 4.7084 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8287 loss: 1.8287 2022/09/05 13:16:16 - mmengine - INFO - Epoch(train) [20][780/940] lr: 1.0000e-02 eta: 17:13:48 time: 0.7188 data_time: 0.0290 memory: 22701 grad_norm: 4.5511 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5990 loss: 1.5990 2022/09/05 13:16:32 - mmengine - INFO - Epoch(train) [20][800/940] lr: 1.0000e-02 eta: 17:13:28 time: 0.7821 data_time: 0.0197 memory: 22701 grad_norm: 4.6254 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7592 loss: 1.7592 2022/09/05 13:16:46 - mmengine - INFO - Epoch(train) [20][820/940] lr: 1.0000e-02 eta: 17:13:03 time: 0.7052 data_time: 0.0356 memory: 22701 grad_norm: 4.6402 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7911 loss: 1.7911 2022/09/05 13:17:01 - mmengine - INFO - Epoch(train) [20][840/940] lr: 1.0000e-02 eta: 17:12:42 time: 0.7723 data_time: 0.0248 memory: 22701 grad_norm: 4.5906 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6611 loss: 1.6611 2022/09/05 13:17:15 - mmengine - INFO - Epoch(train) [20][860/940] lr: 1.0000e-02 eta: 17:12:14 time: 0.6736 data_time: 0.0320 memory: 22701 grad_norm: 4.5885 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6464 loss: 1.6464 2022/09/05 13:17:30 - mmengine - INFO - Epoch(train) [20][880/940] lr: 1.0000e-02 eta: 17:11:53 time: 0.7726 data_time: 0.0220 memory: 22701 grad_norm: 4.5890 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7847 loss: 1.7847 2022/09/05 13:17:46 - mmengine - INFO - Epoch(train) [20][900/940] lr: 1.0000e-02 eta: 17:11:32 time: 0.7602 data_time: 0.0414 memory: 22701 grad_norm: 4.6148 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7971 loss: 1.7971 2022/09/05 13:18:00 - mmengine - INFO - Epoch(train) [20][920/940] lr: 1.0000e-02 eta: 17:11:09 time: 0.7419 data_time: 0.0941 memory: 22701 grad_norm: 4.6925 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6365 loss: 1.6365 2022/09/05 13:18:14 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:18:14 - mmengine - INFO - Epoch(train) [20][940/940] lr: 1.0000e-02 eta: 17:10:43 time: 0.7033 data_time: 0.0556 memory: 22701 grad_norm: 4.8325 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.7497 loss: 1.7497 2022/09/05 13:18:29 - mmengine - INFO - Epoch(val) [20][20/78] eta: 0:00:41 time: 0.7097 data_time: 0.5888 memory: 2247 2022/09/05 13:18:38 - mmengine - INFO - Epoch(val) [20][40/78] eta: 0:00:18 time: 0.4765 data_time: 0.3573 memory: 2247 2022/09/05 13:18:51 - mmengine - INFO - Epoch(val) [20][60/78] eta: 0:00:11 time: 0.6560 data_time: 0.5363 memory: 2247 2022/09/05 13:19:01 - mmengine - INFO - Epoch(val) [20][78/78] acc/top1: 0.6342 acc/top5: 0.8463 acc/mean1: 0.6340 2022/09/05 13:19:01 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_19.pth is removed 2022/09/05 13:19:02 - mmengine - INFO - The best checkpoint with 0.6342 acc/top1 at 21 epoch is saved to best_acc/top1_epoch_21.pth. 2022/09/05 13:19:22 - mmengine - INFO - Epoch(train) [21][20/940] lr: 1.0000e-02 eta: 17:10:37 time: 0.9571 data_time: 0.5603 memory: 22701 grad_norm: 4.5380 top1_acc: 0.5312 top5_acc: 0.5938 loss_cls: 1.7044 loss: 1.7044 2022/09/05 13:19:34 - mmengine - INFO - Epoch(train) [21][40/940] lr: 1.0000e-02 eta: 17:10:05 time: 0.6246 data_time: 0.2355 memory: 22701 grad_norm: 4.5456 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6450 loss: 1.6450 2022/09/05 13:19:49 - mmengine - INFO - Epoch(train) [21][60/940] lr: 1.0000e-02 eta: 17:09:44 time: 0.7742 data_time: 0.3942 memory: 22701 grad_norm: 4.5947 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6572 loss: 1.6572 2022/09/05 13:20:03 - mmengine - INFO - Epoch(train) [21][80/940] lr: 1.0000e-02 eta: 17:09:17 time: 0.6790 data_time: 0.3021 memory: 22701 grad_norm: 4.6251 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7298 loss: 1.7298 2022/09/05 13:20:19 - mmengine - INFO - Epoch(train) [21][100/940] lr: 1.0000e-02 eta: 17:08:58 time: 0.7903 data_time: 0.4046 memory: 22701 grad_norm: 4.5617 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8208 loss: 1.8208 2022/09/05 13:20:32 - mmengine - INFO - Epoch(train) [21][120/940] lr: 1.0000e-02 eta: 17:08:29 time: 0.6724 data_time: 0.2949 memory: 22701 grad_norm: 4.6424 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6392 loss: 1.6392 2022/09/05 13:20:49 - mmengine - INFO - Epoch(train) [21][140/940] lr: 1.0000e-02 eta: 17:08:14 time: 0.8297 data_time: 0.4462 memory: 22701 grad_norm: 4.5916 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6749 loss: 1.6749 2022/09/05 13:21:03 - mmengine - INFO - Epoch(train) [21][160/940] lr: 1.0000e-02 eta: 17:07:46 time: 0.6807 data_time: 0.2924 memory: 22701 grad_norm: 4.5742 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5136 loss: 1.5136 2022/09/05 13:21:20 - mmengine - INFO - Epoch(train) [21][180/940] lr: 1.0000e-02 eta: 17:07:34 time: 0.8847 data_time: 0.4832 memory: 22701 grad_norm: 4.6341 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6269 loss: 1.6269 2022/09/05 13:21:34 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:21:34 - mmengine - INFO - Epoch(train) [21][200/940] lr: 1.0000e-02 eta: 17:07:09 time: 0.7109 data_time: 0.3136 memory: 22701 grad_norm: 4.5534 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 1.6713 loss: 1.6713 2022/09/05 13:21:52 - mmengine - INFO - Epoch(train) [21][220/940] lr: 1.0000e-02 eta: 17:06:58 time: 0.8852 data_time: 0.4931 memory: 22701 grad_norm: 4.5835 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6982 loss: 1.6982 2022/09/05 13:22:08 - mmengine - INFO - Epoch(train) [21][240/940] lr: 1.0000e-02 eta: 17:06:39 time: 0.7879 data_time: 0.3907 memory: 22701 grad_norm: 4.6811 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7752 loss: 1.7752 2022/09/05 13:22:30 - mmengine - INFO - Epoch(train) [21][260/940] lr: 1.0000e-02 eta: 17:06:46 time: 1.1173 data_time: 0.3111 memory: 22701 grad_norm: 4.6624 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8410 loss: 1.8410 2022/09/05 13:22:49 - mmengine - INFO - Epoch(train) [21][280/940] lr: 1.0000e-02 eta: 17:06:38 time: 0.9376 data_time: 0.2688 memory: 22701 grad_norm: 4.6211 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7579 loss: 1.7579 2022/09/05 13:23:08 - mmengine - INFO - Epoch(train) [21][300/940] lr: 1.0000e-02 eta: 17:06:33 time: 0.9623 data_time: 0.3761 memory: 22701 grad_norm: 4.6466 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8080 loss: 1.8080 2022/09/05 13:23:23 - mmengine - INFO - Epoch(train) [21][320/940] lr: 1.0000e-02 eta: 17:06:10 time: 0.7429 data_time: 0.3165 memory: 22701 grad_norm: 4.5560 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6601 loss: 1.6601 2022/09/05 13:23:43 - mmengine - INFO - Epoch(train) [21][340/940] lr: 1.0000e-02 eta: 17:06:05 time: 0.9655 data_time: 0.3717 memory: 22701 grad_norm: 4.6403 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5337 loss: 1.5337 2022/09/05 13:23:57 - mmengine - INFO - Epoch(train) [21][360/940] lr: 1.0000e-02 eta: 17:05:42 time: 0.7427 data_time: 0.1708 memory: 22701 grad_norm: 4.6369 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7002 loss: 1.7002 2022/09/05 13:24:16 - mmengine - INFO - Epoch(train) [21][380/940] lr: 1.0000e-02 eta: 17:05:35 time: 0.9381 data_time: 0.1644 memory: 22701 grad_norm: 4.5617 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6748 loss: 1.6748 2022/09/05 13:24:32 - mmengine - INFO - Epoch(train) [21][400/940] lr: 1.0000e-02 eta: 17:05:14 time: 0.7724 data_time: 0.2596 memory: 22701 grad_norm: 4.5580 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.6610 loss: 1.6610 2022/09/05 13:24:50 - mmengine - INFO - Epoch(train) [21][420/940] lr: 1.0000e-02 eta: 17:05:05 time: 0.9195 data_time: 0.3505 memory: 22701 grad_norm: 4.5480 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6471 loss: 1.6471 2022/09/05 13:25:06 - mmengine - INFO - Epoch(train) [21][440/940] lr: 1.0000e-02 eta: 17:04:47 time: 0.8024 data_time: 0.1989 memory: 22701 grad_norm: 4.6053 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7046 loss: 1.7046 2022/09/05 13:25:26 - mmengine - INFO - Epoch(train) [21][460/940] lr: 1.0000e-02 eta: 17:04:44 time: 0.9927 data_time: 0.1253 memory: 22701 grad_norm: 4.6739 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6695 loss: 1.6695 2022/09/05 13:25:41 - mmengine - INFO - Epoch(train) [21][480/940] lr: 1.0000e-02 eta: 17:04:25 time: 0.7824 data_time: 0.1333 memory: 22701 grad_norm: 4.6656 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7859 loss: 1.7859 2022/09/05 13:26:01 - mmengine - INFO - Epoch(train) [21][500/940] lr: 1.0000e-02 eta: 17:04:19 time: 0.9649 data_time: 0.3610 memory: 22701 grad_norm: 4.6021 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.6093 loss: 1.6093 2022/09/05 13:26:15 - mmengine - INFO - Epoch(train) [21][520/940] lr: 1.0000e-02 eta: 17:03:55 time: 0.7273 data_time: 0.2110 memory: 22701 grad_norm: 4.6052 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6655 loss: 1.6655 2022/09/05 13:26:33 - mmengine - INFO - Epoch(train) [21][540/940] lr: 1.0000e-02 eta: 17:03:42 time: 0.8678 data_time: 0.4173 memory: 22701 grad_norm: 4.5787 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.6496 loss: 1.6496 2022/09/05 13:26:47 - mmengine - INFO - Epoch(train) [21][560/940] lr: 1.0000e-02 eta: 17:03:19 time: 0.7299 data_time: 0.1765 memory: 22701 grad_norm: 4.6042 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7270 loss: 1.7270 2022/09/05 13:27:06 - mmengine - INFO - Epoch(train) [21][580/940] lr: 1.0000e-02 eta: 17:03:12 time: 0.9458 data_time: 0.3224 memory: 22701 grad_norm: 4.6485 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7583 loss: 1.7583 2022/09/05 13:27:21 - mmengine - INFO - Epoch(train) [21][600/940] lr: 1.0000e-02 eta: 17:02:49 time: 0.7426 data_time: 0.2582 memory: 22701 grad_norm: 4.6507 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6098 loss: 1.6098 2022/09/05 13:27:41 - mmengine - INFO - Epoch(train) [21][620/940] lr: 1.0000e-02 eta: 17:02:46 time: 0.9928 data_time: 0.3609 memory: 22701 grad_norm: 4.6197 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7576 loss: 1.7576 2022/09/05 13:27:56 - mmengine - INFO - Epoch(train) [21][640/940] lr: 1.0000e-02 eta: 17:02:24 time: 0.7522 data_time: 0.0302 memory: 22701 grad_norm: 4.5259 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5428 loss: 1.5428 2022/09/05 13:28:13 - mmengine - INFO - Epoch(train) [21][660/940] lr: 1.0000e-02 eta: 17:02:10 time: 0.8580 data_time: 0.0245 memory: 22701 grad_norm: 4.5730 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6760 loss: 1.6760 2022/09/05 13:28:28 - mmengine - INFO - Epoch(train) [21][680/940] lr: 1.0000e-02 eta: 17:01:47 time: 0.7366 data_time: 0.1399 memory: 22701 grad_norm: 4.6475 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6842 loss: 1.6842 2022/09/05 13:28:48 - mmengine - INFO - Epoch(train) [21][700/940] lr: 1.0000e-02 eta: 17:01:45 time: 1.0090 data_time: 0.2238 memory: 22701 grad_norm: 4.5628 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6275 loss: 1.6275 2022/09/05 13:29:02 - mmengine - INFO - Epoch(train) [21][720/940] lr: 1.0000e-02 eta: 17:01:18 time: 0.6899 data_time: 0.1639 memory: 22701 grad_norm: 4.5481 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7805 loss: 1.7805 2022/09/05 13:29:22 - mmengine - INFO - Epoch(train) [21][740/940] lr: 1.0000e-02 eta: 17:01:16 time: 1.0048 data_time: 0.1397 memory: 22701 grad_norm: 4.6159 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8045 loss: 1.8045 2022/09/05 13:29:39 - mmengine - INFO - Epoch(train) [21][760/940] lr: 1.0000e-02 eta: 17:01:01 time: 0.8453 data_time: 0.0914 memory: 22701 grad_norm: 4.5368 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.6428 loss: 1.6428 2022/09/05 13:29:59 - mmengine - INFO - Epoch(train) [21][780/940] lr: 1.0000e-02 eta: 17:00:58 time: 1.0046 data_time: 0.0644 memory: 22701 grad_norm: 4.6065 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7809 loss: 1.7809 2022/09/05 13:30:19 - mmengine - INFO - Epoch(train) [21][800/940] lr: 1.0000e-02 eta: 17:00:55 time: 1.0019 data_time: 0.1367 memory: 22701 grad_norm: 4.5680 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6183 loss: 1.6183 2022/09/05 13:30:40 - mmengine - INFO - Epoch(train) [21][820/940] lr: 1.0000e-02 eta: 17:00:56 time: 1.0437 data_time: 0.0762 memory: 22701 grad_norm: 4.6339 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7316 loss: 1.7316 2022/09/05 13:30:59 - mmengine - INFO - Epoch(train) [21][840/940] lr: 1.0000e-02 eta: 17:00:51 time: 0.9781 data_time: 0.0274 memory: 22701 grad_norm: 4.6647 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.6539 loss: 1.6539 2022/09/05 13:31:17 - mmengine - INFO - Epoch(train) [21][860/940] lr: 1.0000e-02 eta: 17:00:37 time: 0.8521 data_time: 0.0268 memory: 22701 grad_norm: 4.6512 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7030 loss: 1.7030 2022/09/05 13:31:35 - mmengine - INFO - Epoch(train) [21][880/940] lr: 1.0000e-02 eta: 17:00:26 time: 0.9072 data_time: 0.2058 memory: 22701 grad_norm: 4.6406 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5820 loss: 1.5820 2022/09/05 13:31:50 - mmengine - INFO - Epoch(train) [21][900/940] lr: 1.0000e-02 eta: 17:00:06 time: 0.7749 data_time: 0.1524 memory: 22701 grad_norm: 4.7865 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6843 loss: 1.6843 2022/09/05 13:32:07 - mmengine - INFO - Epoch(train) [21][920/940] lr: 1.0000e-02 eta: 16:59:53 time: 0.8678 data_time: 0.1240 memory: 22701 grad_norm: 4.6414 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6834 loss: 1.6834 2022/09/05 13:32:22 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:32:22 - mmengine - INFO - Epoch(train) [21][940/940] lr: 1.0000e-02 eta: 16:59:30 time: 0.7325 data_time: 0.1271 memory: 22701 grad_norm: 4.9343 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.7816 loss: 1.7816 2022/09/05 13:32:22 - mmengine - INFO - Saving checkpoint at 21 epochs 2022/09/05 13:32:38 - mmengine - INFO - Epoch(val) [21][20/78] eta: 0:00:40 time: 0.6973 data_time: 0.5805 memory: 2247 2022/09/05 13:32:47 - mmengine - INFO - Epoch(val) [21][40/78] eta: 0:00:16 time: 0.4471 data_time: 0.3313 memory: 2247 2022/09/05 13:33:00 - mmengine - INFO - Epoch(val) [21][60/78] eta: 0:00:11 time: 0.6441 data_time: 0.5226 memory: 2247 2022/09/05 13:33:10 - mmengine - INFO - Epoch(val) [21][78/78] acc/top1: 0.6356 acc/top5: 0.8554 acc/mean1: 0.6355 2022/09/05 13:33:10 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_21.pth is removed 2022/09/05 13:33:10 - mmengine - INFO - The best checkpoint with 0.6356 acc/top1 at 22 epoch is saved to best_acc/top1_epoch_22.pth. 2022/09/05 13:33:31 - mmengine - INFO - Epoch(train) [22][20/940] lr: 1.0000e-02 eta: 16:59:28 time: 1.0157 data_time: 0.5959 memory: 22701 grad_norm: 4.5874 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6962 loss: 1.6962 2022/09/05 13:33:46 - mmengine - INFO - Epoch(train) [22][40/940] lr: 1.0000e-02 eta: 16:59:06 time: 0.7555 data_time: 0.3155 memory: 22701 grad_norm: 4.6262 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5593 loss: 1.5593 2022/09/05 13:34:05 - mmengine - INFO - Epoch(train) [22][60/940] lr: 1.0000e-02 eta: 16:59:01 time: 0.9745 data_time: 0.5184 memory: 22701 grad_norm: 4.5936 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6690 loss: 1.6690 2022/09/05 13:34:21 - mmengine - INFO - Epoch(train) [22][80/940] lr: 1.0000e-02 eta: 16:58:41 time: 0.7768 data_time: 0.2079 memory: 22701 grad_norm: 4.6178 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6499 loss: 1.6499 2022/09/05 13:34:39 - mmengine - INFO - Epoch(train) [22][100/940] lr: 1.0000e-02 eta: 16:58:31 time: 0.9112 data_time: 0.1279 memory: 22701 grad_norm: 4.5714 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5777 loss: 1.5777 2022/09/05 13:34:55 - mmengine - INFO - Epoch(train) [22][120/940] lr: 1.0000e-02 eta: 16:58:11 time: 0.7780 data_time: 0.0649 memory: 22701 grad_norm: 4.6717 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6795 loss: 1.6795 2022/09/05 13:35:14 - mmengine - INFO - Epoch(train) [22][140/940] lr: 1.0000e-02 eta: 16:58:03 time: 0.9441 data_time: 0.3596 memory: 22701 grad_norm: 4.5333 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6272 loss: 1.6272 2022/09/05 13:35:28 - mmengine - INFO - Epoch(train) [22][160/940] lr: 1.0000e-02 eta: 16:57:39 time: 0.7160 data_time: 0.1157 memory: 22701 grad_norm: 4.5874 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5638 loss: 1.5638 2022/09/05 13:35:43 - mmengine - INFO - Epoch(train) [22][180/940] lr: 1.0000e-02 eta: 16:57:17 time: 0.7554 data_time: 0.1578 memory: 22701 grad_norm: 4.5611 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5703 loss: 1.5703 2022/09/05 13:35:59 - mmengine - INFO - Epoch(train) [22][200/940] lr: 1.0000e-02 eta: 16:56:59 time: 0.8013 data_time: 0.0476 memory: 22701 grad_norm: 4.5509 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6049 loss: 1.6049 2022/09/05 13:36:13 - mmengine - INFO - Epoch(train) [22][220/940] lr: 1.0000e-02 eta: 16:56:33 time: 0.6897 data_time: 0.0277 memory: 22701 grad_norm: 4.6407 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.7386 loss: 1.7386 2022/09/05 13:36:31 - mmengine - INFO - Epoch(train) [22][240/940] lr: 1.0000e-02 eta: 16:56:21 time: 0.8900 data_time: 0.0329 memory: 22701 grad_norm: 4.6338 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5772 loss: 1.5772 2022/09/05 13:36:47 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:36:47 - mmengine - INFO - Epoch(train) [22][260/940] lr: 1.0000e-02 eta: 16:56:06 time: 0.8406 data_time: 0.0299 memory: 22701 grad_norm: 4.5996 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.6700 loss: 1.6700 2022/09/05 13:37:05 - mmengine - INFO - Epoch(train) [22][280/940] lr: 1.0000e-02 eta: 16:55:53 time: 0.8681 data_time: 0.0189 memory: 22701 grad_norm: 4.5446 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6088 loss: 1.6088 2022/09/05 13:37:19 - mmengine - INFO - Epoch(train) [22][300/940] lr: 1.0000e-02 eta: 16:55:29 time: 0.7208 data_time: 0.0419 memory: 22701 grad_norm: 4.6312 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8203 loss: 1.8203 2022/09/05 13:37:35 - mmengine - INFO - Epoch(train) [22][320/940] lr: 1.0000e-02 eta: 16:55:09 time: 0.7826 data_time: 0.0467 memory: 22701 grad_norm: 4.6546 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7230 loss: 1.7230 2022/09/05 13:37:53 - mmengine - INFO - Epoch(train) [22][340/940] lr: 1.0000e-02 eta: 16:54:58 time: 0.8942 data_time: 0.0616 memory: 22701 grad_norm: 4.6345 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.7444 loss: 1.7444 2022/09/05 13:38:09 - mmengine - INFO - Epoch(train) [22][360/940] lr: 1.0000e-02 eta: 16:54:42 time: 0.8333 data_time: 0.0259 memory: 22701 grad_norm: 4.6405 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.6290 loss: 1.6290 2022/09/05 13:38:28 - mmengine - INFO - Epoch(train) [22][380/940] lr: 1.0000e-02 eta: 16:54:32 time: 0.9101 data_time: 0.0340 memory: 22701 grad_norm: 4.6867 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5989 loss: 1.5989 2022/09/05 13:38:42 - mmengine - INFO - Epoch(train) [22][400/940] lr: 1.0000e-02 eta: 16:54:08 time: 0.7243 data_time: 0.0300 memory: 22701 grad_norm: 4.6068 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7021 loss: 1.7021 2022/09/05 13:39:01 - mmengine - INFO - Epoch(train) [22][420/940] lr: 1.0000e-02 eta: 16:53:59 time: 0.9215 data_time: 0.3037 memory: 22701 grad_norm: 4.5760 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.8449 loss: 1.8449 2022/09/05 13:39:17 - mmengine - INFO - Epoch(train) [22][440/940] lr: 1.0000e-02 eta: 16:53:42 time: 0.8246 data_time: 0.2532 memory: 22701 grad_norm: 4.5286 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5316 loss: 1.5316 2022/09/05 13:39:33 - mmengine - INFO - Epoch(train) [22][460/940] lr: 1.0000e-02 eta: 16:53:22 time: 0.7762 data_time: 0.3499 memory: 22701 grad_norm: 4.5417 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5670 loss: 1.5670 2022/09/05 13:39:48 - mmengine - INFO - Epoch(train) [22][480/940] lr: 1.0000e-02 eta: 16:53:02 time: 0.7676 data_time: 0.3512 memory: 22701 grad_norm: 4.7201 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8701 loss: 1.8701 2022/09/05 13:40:03 - mmengine - INFO - Epoch(train) [22][500/940] lr: 1.0000e-02 eta: 16:52:39 time: 0.7351 data_time: 0.3537 memory: 22701 grad_norm: 4.5946 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7399 loss: 1.7399 2022/09/05 13:40:17 - mmengine - INFO - Epoch(train) [22][520/940] lr: 1.0000e-02 eta: 16:52:16 time: 0.7291 data_time: 0.3321 memory: 22701 grad_norm: 4.7223 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7522 loss: 1.7522 2022/09/05 13:40:34 - mmengine - INFO - Epoch(train) [22][540/940] lr: 1.0000e-02 eta: 16:52:00 time: 0.8430 data_time: 0.4508 memory: 22701 grad_norm: 4.6487 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6446 loss: 1.6446 2022/09/05 13:40:47 - mmengine - INFO - Epoch(train) [22][560/940] lr: 1.0000e-02 eta: 16:51:32 time: 0.6642 data_time: 0.2659 memory: 22701 grad_norm: 4.6283 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6359 loss: 1.6359 2022/09/05 13:41:06 - mmengine - INFO - Epoch(train) [22][580/940] lr: 1.0000e-02 eta: 16:51:22 time: 0.9096 data_time: 0.4621 memory: 22701 grad_norm: 4.5587 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6887 loss: 1.6887 2022/09/05 13:41:20 - mmengine - INFO - Epoch(train) [22][600/940] lr: 1.0000e-02 eta: 16:50:57 time: 0.7072 data_time: 0.1800 memory: 22701 grad_norm: 4.6156 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7170 loss: 1.7170 2022/09/05 13:41:35 - mmengine - INFO - Epoch(train) [22][620/940] lr: 1.0000e-02 eta: 16:50:38 time: 0.7866 data_time: 0.3217 memory: 22701 grad_norm: 4.5597 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7410 loss: 1.7410 2022/09/05 13:41:52 - mmengine - INFO - Epoch(train) [22][640/940] lr: 1.0000e-02 eta: 16:50:23 time: 0.8426 data_time: 0.2190 memory: 22701 grad_norm: 4.5747 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6587 loss: 1.6587 2022/09/05 13:42:10 - mmengine - INFO - Epoch(train) [22][660/940] lr: 1.0000e-02 eta: 16:50:13 time: 0.9059 data_time: 0.0301 memory: 22701 grad_norm: 4.5724 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7249 loss: 1.7249 2022/09/05 13:42:24 - mmengine - INFO - Epoch(train) [22][680/940] lr: 1.0000e-02 eta: 16:49:47 time: 0.6944 data_time: 0.0246 memory: 22701 grad_norm: 4.5779 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6507 loss: 1.6507 2022/09/05 13:42:41 - mmengine - INFO - Epoch(train) [22][700/940] lr: 1.0000e-02 eta: 16:49:31 time: 0.8373 data_time: 0.0290 memory: 22701 grad_norm: 4.5853 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.6568 loss: 1.6568 2022/09/05 13:42:57 - mmengine - INFO - Epoch(train) [22][720/940] lr: 1.0000e-02 eta: 16:49:13 time: 0.7930 data_time: 0.0313 memory: 22701 grad_norm: 4.5537 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6640 loss: 1.6640 2022/09/05 13:43:14 - mmengine - INFO - Epoch(train) [22][740/940] lr: 1.0000e-02 eta: 16:48:57 time: 0.8366 data_time: 0.1015 memory: 22701 grad_norm: 4.6808 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6851 loss: 1.6851 2022/09/05 13:43:31 - mmengine - INFO - Epoch(train) [22][760/940] lr: 1.0000e-02 eta: 16:48:44 time: 0.8703 data_time: 0.1996 memory: 22701 grad_norm: 4.6265 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6520 loss: 1.6520 2022/09/05 13:43:49 - mmengine - INFO - Epoch(train) [22][780/940] lr: 1.0000e-02 eta: 16:48:31 time: 0.8780 data_time: 0.1964 memory: 22701 grad_norm: 4.7230 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7363 loss: 1.7363 2022/09/05 13:44:06 - mmengine - INFO - Epoch(train) [22][800/940] lr: 1.0000e-02 eta: 16:48:19 time: 0.8796 data_time: 0.3602 memory: 22701 grad_norm: 4.6469 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6209 loss: 1.6209 2022/09/05 13:44:22 - mmengine - INFO - Epoch(train) [22][820/940] lr: 1.0000e-02 eta: 16:47:58 time: 0.7673 data_time: 0.2247 memory: 22701 grad_norm: 4.6492 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.7243 loss: 1.7243 2022/09/05 13:44:37 - mmengine - INFO - Epoch(train) [22][840/940] lr: 1.0000e-02 eta: 16:47:39 time: 0.7770 data_time: 0.1280 memory: 22701 grad_norm: 4.6543 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7389 loss: 1.7389 2022/09/05 13:44:55 - mmengine - INFO - Epoch(train) [22][860/940] lr: 1.0000e-02 eta: 16:47:28 time: 0.9051 data_time: 0.0190 memory: 22701 grad_norm: 4.7478 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7996 loss: 1.7996 2022/09/05 13:45:10 - mmengine - INFO - Epoch(train) [22][880/940] lr: 1.0000e-02 eta: 16:47:07 time: 0.7623 data_time: 0.0265 memory: 22701 grad_norm: 4.6709 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.6983 loss: 1.6983 2022/09/05 13:45:25 - mmengine - INFO - Epoch(train) [22][900/940] lr: 1.0000e-02 eta: 16:46:44 time: 0.7347 data_time: 0.0242 memory: 22701 grad_norm: 4.5762 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7528 loss: 1.7528 2022/09/05 13:45:42 - mmengine - INFO - Epoch(train) [22][920/940] lr: 1.0000e-02 eta: 16:46:29 time: 0.8338 data_time: 0.0239 memory: 22701 grad_norm: 4.5979 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5281 loss: 1.5281 2022/09/05 13:45:58 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:45:58 - mmengine - INFO - Epoch(train) [22][940/940] lr: 1.0000e-02 eta: 16:46:10 time: 0.7917 data_time: 0.0389 memory: 22701 grad_norm: 4.9403 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.9248 loss: 1.9248 2022/09/05 13:46:12 - mmengine - INFO - Epoch(val) [22][20/78] eta: 0:00:40 time: 0.6949 data_time: 0.5762 memory: 2247 2022/09/05 13:46:20 - mmengine - INFO - Epoch(val) [22][40/78] eta: 0:00:16 time: 0.4368 data_time: 0.3188 memory: 2247 2022/09/05 13:46:33 - mmengine - INFO - Epoch(val) [22][60/78] eta: 0:00:11 time: 0.6568 data_time: 0.5371 memory: 2247 2022/09/05 13:46:45 - mmengine - INFO - Epoch(val) [22][78/78] acc/top1: 0.6342 acc/top5: 0.8511 acc/mean1: 0.6341 2022/09/05 13:47:06 - mmengine - INFO - Epoch(train) [23][20/940] lr: 1.0000e-02 eta: 16:46:10 time: 1.0530 data_time: 0.5627 memory: 22701 grad_norm: 4.6273 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6071 loss: 1.6071 2022/09/05 13:47:19 - mmengine - INFO - Epoch(train) [23][40/940] lr: 1.0000e-02 eta: 16:45:44 time: 0.6925 data_time: 0.1623 memory: 22701 grad_norm: 4.5536 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6373 loss: 1.6373 2022/09/05 13:47:35 - mmengine - INFO - Epoch(train) [23][60/940] lr: 1.0000e-02 eta: 16:45:23 time: 0.7581 data_time: 0.2144 memory: 22701 grad_norm: 4.5223 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6018 loss: 1.6018 2022/09/05 13:47:49 - mmengine - INFO - Epoch(train) [23][80/940] lr: 1.0000e-02 eta: 16:44:57 time: 0.6916 data_time: 0.2073 memory: 22701 grad_norm: 4.5482 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6341 loss: 1.6341 2022/09/05 13:48:07 - mmengine - INFO - Epoch(train) [23][100/940] lr: 1.0000e-02 eta: 16:44:49 time: 0.9469 data_time: 0.4221 memory: 22701 grad_norm: 4.5555 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7716 loss: 1.7716 2022/09/05 13:48:22 - mmengine - INFO - Epoch(train) [23][120/940] lr: 1.0000e-02 eta: 16:44:25 time: 0.7115 data_time: 0.1570 memory: 22701 grad_norm: 4.6112 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7333 loss: 1.7333 2022/09/05 13:48:39 - mmengine - INFO - Epoch(train) [23][140/940] lr: 1.0000e-02 eta: 16:44:11 time: 0.8540 data_time: 0.3195 memory: 22701 grad_norm: 4.5949 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7151 loss: 1.7151 2022/09/05 13:48:52 - mmengine - INFO - Epoch(train) [23][160/940] lr: 1.0000e-02 eta: 16:43:44 time: 0.6825 data_time: 0.0672 memory: 22701 grad_norm: 4.6043 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.8282 loss: 1.8282 2022/09/05 13:49:12 - mmengine - INFO - Epoch(train) [23][180/940] lr: 1.0000e-02 eta: 16:43:38 time: 0.9602 data_time: 0.0561 memory: 22701 grad_norm: 4.6534 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6041 loss: 1.6041 2022/09/05 13:49:27 - mmengine - INFO - Epoch(train) [23][200/940] lr: 1.0000e-02 eta: 16:43:18 time: 0.7782 data_time: 0.0730 memory: 22701 grad_norm: 4.5652 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6418 loss: 1.6418 2022/09/05 13:49:51 - mmengine - INFO - Epoch(train) [23][220/940] lr: 1.0000e-02 eta: 16:43:28 time: 1.2059 data_time: 0.0235 memory: 22701 grad_norm: 4.6050 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6290 loss: 1.6290 2022/09/05 13:50:06 - mmengine - INFO - Epoch(train) [23][240/940] lr: 1.0000e-02 eta: 16:43:06 time: 0.7378 data_time: 0.0228 memory: 22701 grad_norm: 4.6178 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8262 loss: 1.8262 2022/09/05 13:50:25 - mmengine - INFO - Epoch(train) [23][260/940] lr: 1.0000e-02 eta: 16:42:57 time: 0.9317 data_time: 0.0238 memory: 22701 grad_norm: 4.5712 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6469 loss: 1.6469 2022/09/05 13:50:40 - mmengine - INFO - Epoch(train) [23][280/940] lr: 1.0000e-02 eta: 16:42:38 time: 0.7859 data_time: 0.0228 memory: 22701 grad_norm: 4.6367 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6841 loss: 1.6841 2022/09/05 13:50:56 - mmengine - INFO - Epoch(train) [23][300/940] lr: 1.0000e-02 eta: 16:42:20 time: 0.8050 data_time: 0.0306 memory: 22701 grad_norm: 4.4994 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5680 loss: 1.5680 2022/09/05 13:51:10 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:51:10 - mmengine - INFO - Epoch(train) [23][320/940] lr: 1.0000e-02 eta: 16:41:54 time: 0.6806 data_time: 0.0248 memory: 22701 grad_norm: 4.5524 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6142 loss: 1.6142 2022/09/05 13:51:27 - mmengine - INFO - Epoch(train) [23][340/940] lr: 1.0000e-02 eta: 16:41:40 time: 0.8703 data_time: 0.0257 memory: 22701 grad_norm: 4.5825 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6326 loss: 1.6326 2022/09/05 13:51:41 - mmengine - INFO - Epoch(train) [23][360/940] lr: 1.0000e-02 eta: 16:41:14 time: 0.6787 data_time: 0.0226 memory: 22701 grad_norm: 4.6353 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6859 loss: 1.6859 2022/09/05 13:51:58 - mmengine - INFO - Epoch(train) [23][380/940] lr: 1.0000e-02 eta: 16:41:00 time: 0.8595 data_time: 0.0340 memory: 22701 grad_norm: 4.5825 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7187 loss: 1.7187 2022/09/05 13:52:11 - mmengine - INFO - Epoch(train) [23][400/940] lr: 1.0000e-02 eta: 16:40:32 time: 0.6610 data_time: 0.0235 memory: 22701 grad_norm: 4.6067 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8019 loss: 1.8019 2022/09/05 13:52:27 - mmengine - INFO - Epoch(train) [23][420/940] lr: 1.0000e-02 eta: 16:40:13 time: 0.7919 data_time: 0.0284 memory: 22701 grad_norm: 4.5098 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5980 loss: 1.5980 2022/09/05 13:52:42 - mmengine - INFO - Epoch(train) [23][440/940] lr: 1.0000e-02 eta: 16:39:52 time: 0.7457 data_time: 0.0341 memory: 22701 grad_norm: 4.6502 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6688 loss: 1.6688 2022/09/05 13:52:59 - mmengine - INFO - Epoch(train) [23][460/940] lr: 1.0000e-02 eta: 16:39:37 time: 0.8461 data_time: 0.0274 memory: 22701 grad_norm: 4.5729 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5904 loss: 1.5904 2022/09/05 13:53:16 - mmengine - INFO - Epoch(train) [23][480/940] lr: 1.0000e-02 eta: 16:39:23 time: 0.8555 data_time: 0.0281 memory: 22701 grad_norm: 4.6225 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5696 loss: 1.5696 2022/09/05 13:53:34 - mmengine - INFO - Epoch(train) [23][500/940] lr: 1.0000e-02 eta: 16:39:10 time: 0.8875 data_time: 0.0416 memory: 22701 grad_norm: 4.6819 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6138 loss: 1.6138 2022/09/05 13:53:50 - mmengine - INFO - Epoch(train) [23][520/940] lr: 1.0000e-02 eta: 16:38:52 time: 0.7893 data_time: 0.0245 memory: 22701 grad_norm: 4.7097 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8581 loss: 1.8581 2022/09/05 13:54:06 - mmengine - INFO - Epoch(train) [23][540/940] lr: 1.0000e-02 eta: 16:38:33 time: 0.7978 data_time: 0.0312 memory: 22701 grad_norm: 4.5303 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6790 loss: 1.6790 2022/09/05 13:54:22 - mmengine - INFO - Epoch(train) [23][560/940] lr: 1.0000e-02 eta: 16:38:15 time: 0.7865 data_time: 0.0254 memory: 22701 grad_norm: 4.5351 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6454 loss: 1.6454 2022/09/05 13:54:41 - mmengine - INFO - Epoch(train) [23][580/940] lr: 1.0000e-02 eta: 16:38:07 time: 0.9529 data_time: 0.0333 memory: 22701 grad_norm: 4.6580 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6998 loss: 1.6998 2022/09/05 13:54:57 - mmengine - INFO - Epoch(train) [23][600/940] lr: 1.0000e-02 eta: 16:37:49 time: 0.7982 data_time: 0.0585 memory: 22701 grad_norm: 4.6245 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6319 loss: 1.6319 2022/09/05 13:55:17 - mmengine - INFO - Epoch(train) [23][620/940] lr: 1.0000e-02 eta: 16:37:45 time: 1.0046 data_time: 0.0220 memory: 22701 grad_norm: 4.5710 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6422 loss: 1.6422 2022/09/05 13:55:36 - mmengine - INFO - Epoch(train) [23][640/940] lr: 1.0000e-02 eta: 16:37:39 time: 0.9821 data_time: 0.0330 memory: 22701 grad_norm: 4.5926 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5898 loss: 1.5898 2022/09/05 13:55:49 - mmengine - INFO - Epoch(train) [23][660/940] lr: 1.0000e-02 eta: 16:37:10 time: 0.6404 data_time: 0.0355 memory: 22701 grad_norm: 4.6915 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7396 loss: 1.7396 2022/09/05 13:56:06 - mmengine - INFO - Epoch(train) [23][680/940] lr: 1.0000e-02 eta: 16:36:53 time: 0.8216 data_time: 0.0265 memory: 22701 grad_norm: 4.6751 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6281 loss: 1.6281 2022/09/05 13:56:19 - mmengine - INFO - Epoch(train) [23][700/940] lr: 1.0000e-02 eta: 16:36:28 time: 0.6902 data_time: 0.0245 memory: 22701 grad_norm: 4.6039 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7659 loss: 1.7659 2022/09/05 13:56:36 - mmengine - INFO - Epoch(train) [23][720/940] lr: 1.0000e-02 eta: 16:36:14 time: 0.8581 data_time: 0.0274 memory: 22701 grad_norm: 4.5744 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6686 loss: 1.6686 2022/09/05 13:56:50 - mmengine - INFO - Epoch(train) [23][740/940] lr: 1.0000e-02 eta: 16:35:46 time: 0.6560 data_time: 0.0277 memory: 22701 grad_norm: 4.5996 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4112 loss: 1.4112 2022/09/05 13:57:07 - mmengine - INFO - Epoch(train) [23][760/940] lr: 1.0000e-02 eta: 16:35:31 time: 0.8460 data_time: 0.0277 memory: 22701 grad_norm: 4.6776 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5838 loss: 1.5838 2022/09/05 13:57:21 - mmengine - INFO - Epoch(train) [23][780/940] lr: 1.0000e-02 eta: 16:35:06 time: 0.7004 data_time: 0.0279 memory: 22701 grad_norm: 4.7097 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6331 loss: 1.6331 2022/09/05 13:57:37 - mmengine - INFO - Epoch(train) [23][800/940] lr: 1.0000e-02 eta: 16:34:50 time: 0.8231 data_time: 0.0213 memory: 22701 grad_norm: 4.6694 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6467 loss: 1.6467 2022/09/05 13:57:54 - mmengine - INFO - Epoch(train) [23][820/940] lr: 1.0000e-02 eta: 16:34:34 time: 0.8300 data_time: 0.0268 memory: 22701 grad_norm: 4.6568 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7424 loss: 1.7424 2022/09/05 13:58:09 - mmengine - INFO - Epoch(train) [23][840/940] lr: 1.0000e-02 eta: 16:34:15 time: 0.7832 data_time: 0.0254 memory: 22701 grad_norm: 4.6471 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6165 loss: 1.6165 2022/09/05 13:58:22 - mmengine - INFO - Epoch(train) [23][860/940] lr: 1.0000e-02 eta: 16:33:45 time: 0.6282 data_time: 0.0264 memory: 22701 grad_norm: 4.6596 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7551 loss: 1.7551 2022/09/05 13:58:38 - mmengine - INFO - Epoch(train) [23][880/940] lr: 1.0000e-02 eta: 16:33:28 time: 0.8142 data_time: 0.0236 memory: 22701 grad_norm: 4.5939 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6441 loss: 1.6441 2022/09/05 13:58:53 - mmengine - INFO - Epoch(train) [23][900/940] lr: 1.0000e-02 eta: 16:33:06 time: 0.7397 data_time: 0.0485 memory: 22701 grad_norm: 4.6296 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5822 loss: 1.5822 2022/09/05 13:59:11 - mmengine - INFO - Epoch(train) [23][920/940] lr: 1.0000e-02 eta: 16:32:55 time: 0.9020 data_time: 0.0257 memory: 22701 grad_norm: 4.5985 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6893 loss: 1.6893 2022/09/05 13:59:24 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 13:59:24 - mmengine - INFO - Epoch(train) [23][940/940] lr: 1.0000e-02 eta: 16:32:26 time: 0.6425 data_time: 0.0214 memory: 22701 grad_norm: 4.8327 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.7410 loss: 1.7410 2022/09/05 13:59:37 - mmengine - INFO - Epoch(val) [23][20/78] eta: 0:00:39 time: 0.6817 data_time: 0.5639 memory: 2247 2022/09/05 13:59:47 - mmengine - INFO - Epoch(val) [23][40/78] eta: 0:00:18 time: 0.4750 data_time: 0.3594 memory: 2247 2022/09/05 14:00:00 - mmengine - INFO - Epoch(val) [23][60/78] eta: 0:00:11 time: 0.6309 data_time: 0.5096 memory: 2247 2022/09/05 14:00:14 - mmengine - INFO - Epoch(val) [23][78/78] acc/top1: 0.6366 acc/top5: 0.8536 acc/mean1: 0.6366 2022/09/05 14:00:14 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_22.pth is removed 2022/09/05 14:00:15 - mmengine - INFO - The best checkpoint with 0.6366 acc/top1 at 24 epoch is saved to best_acc/top1_epoch_24.pth. 2022/09/05 14:00:35 - mmengine - INFO - Epoch(train) [24][20/940] lr: 1.0000e-02 eta: 16:32:21 time: 0.9888 data_time: 0.6123 memory: 22701 grad_norm: 4.6091 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5928 loss: 1.5928 2022/09/05 14:00:50 - mmengine - INFO - Epoch(train) [24][40/940] lr: 1.0000e-02 eta: 16:32:00 time: 0.7468 data_time: 0.3284 memory: 22701 grad_norm: 4.5605 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.6543 loss: 1.6543 2022/09/05 14:01:08 - mmengine - INFO - Epoch(train) [24][60/940] lr: 1.0000e-02 eta: 16:31:48 time: 0.9031 data_time: 0.5089 memory: 22701 grad_norm: 4.5051 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5974 loss: 1.5974 2022/09/05 14:01:22 - mmengine - INFO - Epoch(train) [24][80/940] lr: 1.0000e-02 eta: 16:31:26 time: 0.7368 data_time: 0.3445 memory: 22701 grad_norm: 4.5814 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5159 loss: 1.5159 2022/09/05 14:01:40 - mmengine - INFO - Epoch(train) [24][100/940] lr: 1.0000e-02 eta: 16:31:14 time: 0.8807 data_time: 0.4438 memory: 22701 grad_norm: 4.6643 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.7245 loss: 1.7245 2022/09/05 14:01:54 - mmengine - INFO - Epoch(train) [24][120/940] lr: 1.0000e-02 eta: 16:30:47 time: 0.6702 data_time: 0.2226 memory: 22701 grad_norm: 4.5978 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5985 loss: 1.5985 2022/09/05 14:02:12 - mmengine - INFO - Epoch(train) [24][140/940] lr: 1.0000e-02 eta: 16:30:36 time: 0.8972 data_time: 0.3985 memory: 22701 grad_norm: 4.5509 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4955 loss: 1.4955 2022/09/05 14:02:25 - mmengine - INFO - Epoch(train) [24][160/940] lr: 1.0000e-02 eta: 16:30:10 time: 0.6814 data_time: 0.2237 memory: 22701 grad_norm: 4.6794 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6560 loss: 1.6560 2022/09/05 14:02:41 - mmengine - INFO - Epoch(train) [24][180/940] lr: 1.0000e-02 eta: 16:29:53 time: 0.8146 data_time: 0.3247 memory: 22701 grad_norm: 4.6271 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4380 loss: 1.4380 2022/09/05 14:02:55 - mmengine - INFO - Epoch(train) [24][200/940] lr: 1.0000e-02 eta: 16:29:26 time: 0.6668 data_time: 0.2668 memory: 22701 grad_norm: 4.6921 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6402 loss: 1.6402 2022/09/05 14:03:13 - mmengine - INFO - Epoch(train) [24][220/940] lr: 1.0000e-02 eta: 16:29:15 time: 0.9051 data_time: 0.3039 memory: 22701 grad_norm: 4.5968 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5260 loss: 1.5260 2022/09/05 14:03:28 - mmengine - INFO - Epoch(train) [24][240/940] lr: 1.0000e-02 eta: 16:28:53 time: 0.7435 data_time: 0.1242 memory: 22701 grad_norm: 4.5696 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6415 loss: 1.6415 2022/09/05 14:03:46 - mmengine - INFO - Epoch(train) [24][260/940] lr: 1.0000e-02 eta: 16:28:43 time: 0.9118 data_time: 0.0755 memory: 22701 grad_norm: 4.6127 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6079 loss: 1.6079 2022/09/05 14:04:04 - mmengine - INFO - Epoch(train) [24][280/940] lr: 1.0000e-02 eta: 16:28:31 time: 0.8880 data_time: 0.0159 memory: 22701 grad_norm: 4.7320 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7618 loss: 1.7618 2022/09/05 14:04:23 - mmengine - INFO - Epoch(train) [24][300/940] lr: 1.0000e-02 eta: 16:28:24 time: 0.9659 data_time: 0.0341 memory: 22701 grad_norm: 4.4755 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5926 loss: 1.5926 2022/09/05 14:04:37 - mmengine - INFO - Epoch(train) [24][320/940] lr: 1.0000e-02 eta: 16:27:58 time: 0.6909 data_time: 0.0187 memory: 22701 grad_norm: 4.5891 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6280 loss: 1.6280 2022/09/05 14:04:55 - mmengine - INFO - Epoch(train) [24][340/940] lr: 1.0000e-02 eta: 16:27:47 time: 0.9044 data_time: 0.0243 memory: 22701 grad_norm: 4.5950 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6291 loss: 1.6291 2022/09/05 14:05:09 - mmengine - INFO - Epoch(train) [24][360/940] lr: 1.0000e-02 eta: 16:27:23 time: 0.6972 data_time: 0.0244 memory: 22701 grad_norm: 4.6180 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6524 loss: 1.6524 2022/09/05 14:05:25 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:05:25 - mmengine - INFO - Epoch(train) [24][380/940] lr: 1.0000e-02 eta: 16:27:06 time: 0.8182 data_time: 0.0309 memory: 22701 grad_norm: 4.6146 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6391 loss: 1.6391 2022/09/05 14:05:39 - mmengine - INFO - Epoch(train) [24][400/940] lr: 1.0000e-02 eta: 16:26:39 time: 0.6689 data_time: 0.0173 memory: 22701 grad_norm: 4.6422 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6219 loss: 1.6219 2022/09/05 14:05:57 - mmengine - INFO - Epoch(train) [24][420/940] lr: 1.0000e-02 eta: 16:26:28 time: 0.9061 data_time: 0.0280 memory: 22701 grad_norm: 4.6751 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6909 loss: 1.6909 2022/09/05 14:06:13 - mmengine - INFO - Epoch(train) [24][440/940] lr: 1.0000e-02 eta: 16:26:12 time: 0.8272 data_time: 0.0212 memory: 22701 grad_norm: 4.5630 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5375 loss: 1.5375 2022/09/05 14:06:31 - mmengine - INFO - Epoch(train) [24][460/940] lr: 1.0000e-02 eta: 16:26:01 time: 0.9066 data_time: 0.0276 memory: 22701 grad_norm: 4.5945 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5108 loss: 1.5108 2022/09/05 14:06:46 - mmengine - INFO - Epoch(train) [24][480/940] lr: 1.0000e-02 eta: 16:25:39 time: 0.7272 data_time: 0.0242 memory: 22701 grad_norm: 4.6782 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6502 loss: 1.6502 2022/09/05 14:07:03 - mmengine - INFO - Epoch(train) [24][500/940] lr: 1.0000e-02 eta: 16:25:25 time: 0.8624 data_time: 0.0222 memory: 22701 grad_norm: 4.6366 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6707 loss: 1.6707 2022/09/05 14:07:18 - mmengine - INFO - Epoch(train) [24][520/940] lr: 1.0000e-02 eta: 16:25:04 time: 0.7555 data_time: 0.0242 memory: 22701 grad_norm: 4.6732 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5133 loss: 1.5133 2022/09/05 14:07:37 - mmengine - INFO - Epoch(train) [24][540/940] lr: 1.0000e-02 eta: 16:24:53 time: 0.9120 data_time: 0.0577 memory: 22701 grad_norm: 4.7439 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5498 loss: 1.5498 2022/09/05 14:07:53 - mmengine - INFO - Epoch(train) [24][560/940] lr: 1.0000e-02 eta: 16:24:37 time: 0.8273 data_time: 0.0294 memory: 22701 grad_norm: 4.5942 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.6530 loss: 1.6530 2022/09/05 14:08:11 - mmengine - INFO - Epoch(train) [24][580/940] lr: 1.0000e-02 eta: 16:24:25 time: 0.8913 data_time: 0.0356 memory: 22701 grad_norm: 4.6479 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6377 loss: 1.6377 2022/09/05 14:08:24 - mmengine - INFO - Epoch(train) [24][600/940] lr: 1.0000e-02 eta: 16:23:59 time: 0.6704 data_time: 0.0236 memory: 22701 grad_norm: 4.6410 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6501 loss: 1.6501 2022/09/05 14:08:41 - mmengine - INFO - Epoch(train) [24][620/940] lr: 1.0000e-02 eta: 16:23:43 time: 0.8306 data_time: 0.0324 memory: 22701 grad_norm: 4.6967 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7922 loss: 1.7922 2022/09/05 14:08:55 - mmengine - INFO - Epoch(train) [24][640/940] lr: 1.0000e-02 eta: 16:23:18 time: 0.6873 data_time: 0.0320 memory: 22701 grad_norm: 4.6540 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6865 loss: 1.6865 2022/09/05 14:09:12 - mmengine - INFO - Epoch(train) [24][660/940] lr: 1.0000e-02 eta: 16:23:03 time: 0.8439 data_time: 0.0310 memory: 22701 grad_norm: 4.6390 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6159 loss: 1.6159 2022/09/05 14:09:29 - mmengine - INFO - Epoch(train) [24][680/940] lr: 1.0000e-02 eta: 16:22:50 time: 0.8803 data_time: 0.0287 memory: 22701 grad_norm: 4.6650 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7411 loss: 1.7411 2022/09/05 14:09:48 - mmengine - INFO - Epoch(train) [24][700/940] lr: 1.0000e-02 eta: 16:22:40 time: 0.9259 data_time: 0.0283 memory: 22701 grad_norm: 4.6486 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6960 loss: 1.6960 2022/09/05 14:10:06 - mmengine - INFO - Epoch(train) [24][720/940] lr: 1.0000e-02 eta: 16:22:29 time: 0.8968 data_time: 0.0238 memory: 22701 grad_norm: 4.7165 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7617 loss: 1.7617 2022/09/05 14:10:23 - mmengine - INFO - Epoch(train) [24][740/940] lr: 1.0000e-02 eta: 16:22:16 time: 0.8800 data_time: 0.0276 memory: 22701 grad_norm: 4.5774 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6710 loss: 1.6710 2022/09/05 14:10:43 - mmengine - INFO - Epoch(train) [24][760/940] lr: 1.0000e-02 eta: 16:22:09 time: 0.9680 data_time: 0.0239 memory: 22701 grad_norm: 4.6327 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7623 loss: 1.7623 2022/09/05 14:11:00 - mmengine - INFO - Epoch(train) [24][780/940] lr: 1.0000e-02 eta: 16:21:54 time: 0.8575 data_time: 0.0336 memory: 22701 grad_norm: 4.7093 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8109 loss: 1.8109 2022/09/05 14:11:14 - mmengine - INFO - Epoch(train) [24][800/940] lr: 1.0000e-02 eta: 16:21:31 time: 0.7146 data_time: 0.0267 memory: 22701 grad_norm: 4.7472 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8715 loss: 1.8715 2022/09/05 14:11:31 - mmengine - INFO - Epoch(train) [24][820/940] lr: 1.0000e-02 eta: 16:21:17 time: 0.8639 data_time: 0.0269 memory: 22701 grad_norm: 4.5862 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7196 loss: 1.7196 2022/09/05 14:11:45 - mmengine - INFO - Epoch(train) [24][840/940] lr: 1.0000e-02 eta: 16:20:52 time: 0.6840 data_time: 0.0272 memory: 22701 grad_norm: 4.5694 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5480 loss: 1.5480 2022/09/05 14:12:00 - mmengine - INFO - Epoch(train) [24][860/940] lr: 1.0000e-02 eta: 16:20:30 time: 0.7435 data_time: 0.0285 memory: 22701 grad_norm: 4.6328 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7680 loss: 1.7680 2022/09/05 14:12:14 - mmengine - INFO - Epoch(train) [24][880/940] lr: 1.0000e-02 eta: 16:20:06 time: 0.6921 data_time: 0.0265 memory: 22701 grad_norm: 4.5306 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6347 loss: 1.6347 2022/09/05 14:12:28 - mmengine - INFO - Epoch(train) [24][900/940] lr: 1.0000e-02 eta: 16:19:44 time: 0.7352 data_time: 0.0331 memory: 22701 grad_norm: 4.5914 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6731 loss: 1.6731 2022/09/05 14:12:44 - mmengine - INFO - Epoch(train) [24][920/940] lr: 1.0000e-02 eta: 16:19:23 time: 0.7581 data_time: 0.0250 memory: 22701 grad_norm: 4.6348 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7562 loss: 1.7562 2022/09/05 14:12:59 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:12:59 - mmengine - INFO - Epoch(train) [24][940/940] lr: 1.0000e-02 eta: 16:19:04 time: 0.7874 data_time: 0.0181 memory: 22701 grad_norm: 4.9352 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.6642 loss: 1.6642 2022/09/05 14:12:59 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/09/05 14:13:15 - mmengine - INFO - Epoch(val) [24][20/78] eta: 0:00:40 time: 0.6968 data_time: 0.5806 memory: 2247 2022/09/05 14:13:24 - mmengine - INFO - Epoch(val) [24][40/78] eta: 0:00:16 time: 0.4461 data_time: 0.3112 memory: 2247 2022/09/05 14:13:37 - mmengine - INFO - Epoch(val) [24][60/78] eta: 0:00:11 time: 0.6507 data_time: 0.5329 memory: 2247 2022/09/05 14:13:50 - mmengine - INFO - Epoch(val) [24][78/78] acc/top1: 0.6353 acc/top5: 0.8494 acc/mean1: 0.6351 2022/09/05 14:14:10 - mmengine - INFO - Epoch(train) [25][20/940] lr: 1.0000e-02 eta: 16:18:57 time: 0.9708 data_time: 0.5079 memory: 22701 grad_norm: 4.5394 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5753 loss: 1.5753 2022/09/05 14:14:23 - mmengine - INFO - Epoch(train) [25][40/940] lr: 1.0000e-02 eta: 16:18:33 time: 0.6958 data_time: 0.2448 memory: 22701 grad_norm: 4.6262 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8188 loss: 1.8188 2022/09/05 14:14:40 - mmengine - INFO - Epoch(train) [25][60/940] lr: 1.0000e-02 eta: 16:18:15 time: 0.7975 data_time: 0.2579 memory: 22701 grad_norm: 4.5545 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5393 loss: 1.5393 2022/09/05 14:14:54 - mmengine - INFO - Epoch(train) [25][80/940] lr: 1.0000e-02 eta: 16:17:54 time: 0.7522 data_time: 0.0824 memory: 22701 grad_norm: 4.5170 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5929 loss: 1.5929 2022/09/05 14:15:09 - mmengine - INFO - Epoch(train) [25][100/940] lr: 1.0000e-02 eta: 16:17:32 time: 0.7254 data_time: 0.0537 memory: 22701 grad_norm: 4.5746 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6484 loss: 1.6484 2022/09/05 14:15:25 - mmengine - INFO - Epoch(train) [25][120/940] lr: 1.0000e-02 eta: 16:17:14 time: 0.8078 data_time: 0.2404 memory: 22701 grad_norm: 4.6249 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4859 loss: 1.4859 2022/09/05 14:15:40 - mmengine - INFO - Epoch(train) [25][140/940] lr: 1.0000e-02 eta: 16:16:52 time: 0.7262 data_time: 0.2964 memory: 22701 grad_norm: 4.5622 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6631 loss: 1.6631 2022/09/05 14:15:55 - mmengine - INFO - Epoch(train) [25][160/940] lr: 1.0000e-02 eta: 16:16:33 time: 0.7822 data_time: 0.3756 memory: 22701 grad_norm: 4.7283 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5671 loss: 1.5671 2022/09/05 14:16:10 - mmengine - INFO - Epoch(train) [25][180/940] lr: 1.0000e-02 eta: 16:16:09 time: 0.7094 data_time: 0.2115 memory: 22701 grad_norm: 4.6446 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.5916 loss: 1.5916 2022/09/05 14:16:24 - mmengine - INFO - Epoch(train) [25][200/940] lr: 1.0000e-02 eta: 16:15:47 time: 0.7357 data_time: 0.2053 memory: 22701 grad_norm: 4.5943 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5808 loss: 1.5808 2022/09/05 14:16:39 - mmengine - INFO - Epoch(train) [25][220/940] lr: 1.0000e-02 eta: 16:15:27 time: 0.7587 data_time: 0.1789 memory: 22701 grad_norm: 4.6045 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5608 loss: 1.5608 2022/09/05 14:16:55 - mmengine - INFO - Epoch(train) [25][240/940] lr: 1.0000e-02 eta: 16:15:09 time: 0.7996 data_time: 0.3683 memory: 22701 grad_norm: 4.5928 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6554 loss: 1.6554 2022/09/05 14:17:11 - mmengine - INFO - Epoch(train) [25][260/940] lr: 1.0000e-02 eta: 16:14:49 time: 0.7552 data_time: 0.2601 memory: 22701 grad_norm: 4.5849 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6009 loss: 1.6009 2022/09/05 14:17:26 - mmengine - INFO - Epoch(train) [25][280/940] lr: 1.0000e-02 eta: 16:14:29 time: 0.7729 data_time: 0.2437 memory: 22701 grad_norm: 4.5753 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5779 loss: 1.5779 2022/09/05 14:17:42 - mmengine - INFO - Epoch(train) [25][300/940] lr: 1.0000e-02 eta: 16:14:13 time: 0.8214 data_time: 0.1373 memory: 22701 grad_norm: 4.6583 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6445 loss: 1.6445 2022/09/05 14:17:57 - mmengine - INFO - Epoch(train) [25][320/940] lr: 1.0000e-02 eta: 16:13:50 time: 0.7261 data_time: 0.0302 memory: 22701 grad_norm: 4.5873 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5343 loss: 1.5343 2022/09/05 14:18:14 - mmengine - INFO - Epoch(train) [25][340/940] lr: 1.0000e-02 eta: 16:13:34 time: 0.8295 data_time: 0.0192 memory: 22701 grad_norm: 4.5896 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6123 loss: 1.6123 2022/09/05 14:18:30 - mmengine - INFO - Epoch(train) [25][360/940] lr: 1.0000e-02 eta: 16:13:18 time: 0.8150 data_time: 0.1703 memory: 22701 grad_norm: 4.6938 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 1.6094 loss: 1.6094 2022/09/05 14:18:48 - mmengine - INFO - Epoch(train) [25][380/940] lr: 1.0000e-02 eta: 16:13:05 time: 0.8869 data_time: 0.0213 memory: 22701 grad_norm: 4.5944 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6741 loss: 1.6741 2022/09/05 14:19:03 - mmengine - INFO - Epoch(train) [25][400/940] lr: 1.0000e-02 eta: 16:12:47 time: 0.7846 data_time: 0.1738 memory: 22701 grad_norm: 4.7392 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5341 loss: 1.5341 2022/09/05 14:19:22 - mmengine - INFO - Epoch(train) [25][420/940] lr: 1.0000e-02 eta: 16:12:37 time: 0.9356 data_time: 0.1273 memory: 22701 grad_norm: 4.6489 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6879 loss: 1.6879 2022/09/05 14:19:40 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:19:40 - mmengine - INFO - Epoch(train) [25][440/940] lr: 1.0000e-02 eta: 16:12:25 time: 0.8838 data_time: 0.2489 memory: 22701 grad_norm: 4.5730 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6282 loss: 1.6282 2022/09/05 14:19:58 - mmengine - INFO - Epoch(train) [25][460/940] lr: 1.0000e-02 eta: 16:12:12 time: 0.8903 data_time: 0.3297 memory: 22701 grad_norm: 4.7254 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7304 loss: 1.7304 2022/09/05 14:20:17 - mmengine - INFO - Epoch(train) [25][480/940] lr: 1.0000e-02 eta: 16:12:04 time: 0.9604 data_time: 0.5458 memory: 22701 grad_norm: 4.6514 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6250 loss: 1.6250 2022/09/05 14:20:32 - mmengine - INFO - Epoch(train) [25][500/940] lr: 1.0000e-02 eta: 16:11:45 time: 0.7696 data_time: 0.3458 memory: 22701 grad_norm: 4.7229 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8856 loss: 1.8856 2022/09/05 14:20:49 - mmengine - INFO - Epoch(train) [25][520/940] lr: 1.0000e-02 eta: 16:11:30 time: 0.8445 data_time: 0.4263 memory: 22701 grad_norm: 4.6664 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5504 loss: 1.5504 2022/09/05 14:21:04 - mmengine - INFO - Epoch(train) [25][540/940] lr: 1.0000e-02 eta: 16:11:10 time: 0.7764 data_time: 0.2486 memory: 22701 grad_norm: 4.5665 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6951 loss: 1.6951 2022/09/05 14:21:19 - mmengine - INFO - Epoch(train) [25][560/940] lr: 1.0000e-02 eta: 16:10:49 time: 0.7319 data_time: 0.2666 memory: 22701 grad_norm: 4.6529 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.6814 loss: 1.6814 2022/09/05 14:21:36 - mmengine - INFO - Epoch(train) [25][580/940] lr: 1.0000e-02 eta: 16:10:33 time: 0.8374 data_time: 0.3048 memory: 22701 grad_norm: 4.6687 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6194 loss: 1.6194 2022/09/05 14:21:53 - mmengine - INFO - Epoch(train) [25][600/940] lr: 1.0000e-02 eta: 16:10:19 time: 0.8678 data_time: 0.4645 memory: 22701 grad_norm: 4.8061 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7962 loss: 1.7962 2022/09/05 14:22:07 - mmengine - INFO - Epoch(train) [25][620/940] lr: 1.0000e-02 eta: 16:09:56 time: 0.6995 data_time: 0.2975 memory: 22701 grad_norm: 4.6697 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6579 loss: 1.6579 2022/09/05 14:22:26 - mmengine - INFO - Epoch(train) [25][640/940] lr: 1.0000e-02 eta: 16:09:47 time: 0.9524 data_time: 0.4228 memory: 22701 grad_norm: 4.5753 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5785 loss: 1.5785 2022/09/05 14:22:41 - mmengine - INFO - Epoch(train) [25][660/940] lr: 1.0000e-02 eta: 16:09:26 time: 0.7446 data_time: 0.1944 memory: 22701 grad_norm: 4.6382 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6107 loss: 1.6107 2022/09/05 14:22:56 - mmengine - INFO - Epoch(train) [25][680/940] lr: 1.0000e-02 eta: 16:09:06 time: 0.7606 data_time: 0.3372 memory: 22701 grad_norm: 4.6122 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6381 loss: 1.6381 2022/09/05 14:23:11 - mmengine - INFO - Epoch(train) [25][700/940] lr: 1.0000e-02 eta: 16:08:44 time: 0.7373 data_time: 0.1580 memory: 22701 grad_norm: 4.7613 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6459 loss: 1.6459 2022/09/05 14:23:27 - mmengine - INFO - Epoch(train) [25][720/940] lr: 1.0000e-02 eta: 16:08:27 time: 0.8136 data_time: 0.1822 memory: 22701 grad_norm: 4.6615 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.8115 loss: 1.8115 2022/09/05 14:23:43 - mmengine - INFO - Epoch(train) [25][740/940] lr: 1.0000e-02 eta: 16:08:07 time: 0.7621 data_time: 0.1597 memory: 22701 grad_norm: 4.5977 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7081 loss: 1.7081 2022/09/05 14:24:01 - mmengine - INFO - Epoch(train) [25][760/940] lr: 1.0000e-02 eta: 16:07:56 time: 0.9025 data_time: 0.1879 memory: 22701 grad_norm: 4.5962 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5679 loss: 1.5679 2022/09/05 14:24:16 - mmengine - INFO - Epoch(train) [25][780/940] lr: 1.0000e-02 eta: 16:07:36 time: 0.7750 data_time: 0.0191 memory: 22701 grad_norm: 4.5910 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5474 loss: 1.5474 2022/09/05 14:24:34 - mmengine - INFO - Epoch(train) [25][800/940] lr: 1.0000e-02 eta: 16:07:23 time: 0.8765 data_time: 0.0261 memory: 22701 grad_norm: 4.6321 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.5482 loss: 1.5482 2022/09/05 14:24:46 - mmengine - INFO - Epoch(train) [25][820/940] lr: 1.0000e-02 eta: 16:06:53 time: 0.5904 data_time: 0.0226 memory: 22701 grad_norm: 4.7154 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6759 loss: 1.6759 2022/09/05 14:25:01 - mmengine - INFO - Epoch(train) [25][840/940] lr: 1.0000e-02 eta: 16:06:32 time: 0.7539 data_time: 0.0287 memory: 22701 grad_norm: 4.6548 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6633 loss: 1.6633 2022/09/05 14:25:15 - mmengine - INFO - Epoch(train) [25][860/940] lr: 1.0000e-02 eta: 16:06:10 time: 0.7266 data_time: 0.0295 memory: 22701 grad_norm: 4.7061 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7245 loss: 1.7245 2022/09/05 14:25:30 - mmengine - INFO - Epoch(train) [25][880/940] lr: 1.0000e-02 eta: 16:05:50 time: 0.7652 data_time: 0.0531 memory: 22701 grad_norm: 4.6855 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.6562 loss: 1.6562 2022/09/05 14:25:46 - mmengine - INFO - Epoch(train) [25][900/940] lr: 1.0000e-02 eta: 16:05:31 time: 0.7633 data_time: 0.0905 memory: 22701 grad_norm: 4.6233 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.5041 loss: 1.5041 2022/09/05 14:26:02 - mmengine - INFO - Epoch(train) [25][920/940] lr: 1.0000e-02 eta: 16:05:14 time: 0.8182 data_time: 0.2790 memory: 22701 grad_norm: 4.6244 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6212 loss: 1.6212 2022/09/05 14:26:16 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:26:16 - mmengine - INFO - Epoch(train) [25][940/940] lr: 1.0000e-02 eta: 16:04:49 time: 0.6808 data_time: 0.1839 memory: 22701 grad_norm: 4.8375 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.6483 loss: 1.6483 2022/09/05 14:26:29 - mmengine - INFO - Epoch(val) [25][20/78] eta: 0:00:39 time: 0.6886 data_time: 0.5688 memory: 2247 2022/09/05 14:26:38 - mmengine - INFO - Epoch(val) [25][40/78] eta: 0:00:17 time: 0.4490 data_time: 0.3289 memory: 2247 2022/09/05 14:26:52 - mmengine - INFO - Epoch(val) [25][60/78] eta: 0:00:12 time: 0.6690 data_time: 0.5501 memory: 2247 2022/09/05 14:27:02 - mmengine - INFO - Epoch(val) [25][78/78] acc/top1: 0.6395 acc/top5: 0.8569 acc/mean1: 0.6394 2022/09/05 14:27:02 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_24.pth is removed 2022/09/05 14:27:03 - mmengine - INFO - The best checkpoint with 0.6395 acc/top1 at 26 epoch is saved to best_acc/top1_epoch_26.pth. 2022/09/05 14:27:26 - mmengine - INFO - Epoch(train) [26][20/940] lr: 1.0000e-02 eta: 16:04:50 time: 1.1178 data_time: 0.6610 memory: 22701 grad_norm: 4.4954 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4991 loss: 1.4991 2022/09/05 14:27:39 - mmengine - INFO - Epoch(train) [26][40/940] lr: 1.0000e-02 eta: 16:04:25 time: 0.6670 data_time: 0.2460 memory: 22701 grad_norm: 4.5247 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7282 loss: 1.7282 2022/09/05 14:27:57 - mmengine - INFO - Epoch(train) [26][60/940] lr: 1.0000e-02 eta: 16:04:13 time: 0.8950 data_time: 0.4968 memory: 22701 grad_norm: 4.5978 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.5874 loss: 1.5874 2022/09/05 14:28:12 - mmengine - INFO - Epoch(train) [26][80/940] lr: 1.0000e-02 eta: 16:03:51 time: 0.7332 data_time: 0.3499 memory: 22701 grad_norm: 4.5980 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6154 loss: 1.6154 2022/09/05 14:28:28 - mmengine - INFO - Epoch(train) [26][100/940] lr: 1.0000e-02 eta: 16:03:34 time: 0.8171 data_time: 0.4056 memory: 22701 grad_norm: 4.5071 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.4938 loss: 1.4938 2022/09/05 14:28:44 - mmengine - INFO - Epoch(train) [26][120/940] lr: 1.0000e-02 eta: 16:03:16 time: 0.7896 data_time: 0.3291 memory: 22701 grad_norm: 4.5636 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6482 loss: 1.6482 2022/09/05 14:29:03 - mmengine - INFO - Epoch(train) [26][140/940] lr: 1.0000e-02 eta: 16:03:08 time: 0.9567 data_time: 0.4292 memory: 22701 grad_norm: 4.5767 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6455 loss: 1.6455 2022/09/05 14:29:17 - mmengine - INFO - Epoch(train) [26][160/940] lr: 1.0000e-02 eta: 16:02:44 time: 0.6927 data_time: 0.2913 memory: 22701 grad_norm: 4.5366 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3923 loss: 1.3923 2022/09/05 14:29:37 - mmengine - INFO - Epoch(train) [26][180/940] lr: 1.0000e-02 eta: 16:02:38 time: 0.9967 data_time: 0.4153 memory: 22701 grad_norm: 4.6342 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5465 loss: 1.5465 2022/09/05 14:29:52 - mmengine - INFO - Epoch(train) [26][200/940] lr: 1.0000e-02 eta: 16:02:19 time: 0.7793 data_time: 0.0885 memory: 22701 grad_norm: 4.5033 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5418 loss: 1.5418 2022/09/05 14:30:10 - mmengine - INFO - Epoch(train) [26][220/940] lr: 1.0000e-02 eta: 16:02:08 time: 0.9130 data_time: 0.0978 memory: 22701 grad_norm: 4.5229 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5623 loss: 1.5623 2022/09/05 14:30:28 - mmengine - INFO - Epoch(train) [26][240/940] lr: 1.0000e-02 eta: 16:01:56 time: 0.8975 data_time: 0.2183 memory: 22701 grad_norm: 4.5680 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6533 loss: 1.6533 2022/09/05 14:30:52 - mmengine - INFO - Epoch(train) [26][260/940] lr: 1.0000e-02 eta: 16:01:59 time: 1.1515 data_time: 0.7277 memory: 22701 grad_norm: 4.6205 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7063 loss: 1.7063 2022/09/05 14:31:08 - mmengine - INFO - Epoch(train) [26][280/940] lr: 1.0000e-02 eta: 16:01:43 time: 0.8307 data_time: 0.4522 memory: 22701 grad_norm: 4.5559 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6260 loss: 1.6260 2022/09/05 14:31:25 - mmengine - INFO - Epoch(train) [26][300/940] lr: 1.0000e-02 eta: 16:01:28 time: 0.8452 data_time: 0.4576 memory: 22701 grad_norm: 4.6463 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5180 loss: 1.5180 2022/09/05 14:31:38 - mmengine - INFO - Epoch(train) [26][320/940] lr: 1.0000e-02 eta: 16:01:01 time: 0.6455 data_time: 0.2396 memory: 22701 grad_norm: 4.6556 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6865 loss: 1.6865 2022/09/05 14:31:53 - mmengine - INFO - Epoch(train) [26][340/940] lr: 1.0000e-02 eta: 16:00:42 time: 0.7696 data_time: 0.3588 memory: 22701 grad_norm: 4.7217 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7139 loss: 1.7139 2022/09/05 14:32:08 - mmengine - INFO - Epoch(train) [26][360/940] lr: 1.0000e-02 eta: 16:00:19 time: 0.7142 data_time: 0.3219 memory: 22701 grad_norm: 4.6270 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6781 loss: 1.6781 2022/09/05 14:32:27 - mmengine - INFO - Epoch(train) [26][380/940] lr: 1.0000e-02 eta: 16:00:13 time: 0.9955 data_time: 0.6163 memory: 22701 grad_norm: 4.6213 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4595 loss: 1.4595 2022/09/05 14:32:44 - mmengine - INFO - Epoch(train) [26][400/940] lr: 1.0000e-02 eta: 15:59:57 time: 0.8339 data_time: 0.4243 memory: 22701 grad_norm: 4.6167 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5974 loss: 1.5974 2022/09/05 14:33:04 - mmengine - INFO - Epoch(train) [26][420/940] lr: 1.0000e-02 eta: 15:59:50 time: 0.9827 data_time: 0.5942 memory: 22701 grad_norm: 4.5498 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6569 loss: 1.6569 2022/09/05 14:33:20 - mmengine - INFO - Epoch(train) [26][440/940] lr: 1.0000e-02 eta: 15:59:34 time: 0.8336 data_time: 0.4532 memory: 22701 grad_norm: 4.5936 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6185 loss: 1.6185 2022/09/05 14:33:39 - mmengine - INFO - Epoch(train) [26][460/940] lr: 1.0000e-02 eta: 15:59:25 time: 0.9398 data_time: 0.5433 memory: 22701 grad_norm: 4.5830 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.5175 loss: 1.5175 2022/09/05 14:33:55 - mmengine - INFO - Epoch(train) [26][480/940] lr: 1.0000e-02 eta: 15:59:06 time: 0.7912 data_time: 0.3728 memory: 22701 grad_norm: 4.6289 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5785 loss: 1.5785 2022/09/05 14:34:17 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:34:17 - mmengine - INFO - Epoch(train) [26][500/940] lr: 1.0000e-02 eta: 15:59:07 time: 1.1131 data_time: 0.7356 memory: 22701 grad_norm: 4.6258 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5693 loss: 1.5693 2022/09/05 14:34:32 - mmengine - INFO - Epoch(train) [26][520/940] lr: 1.0000e-02 eta: 15:58:45 time: 0.7325 data_time: 0.3477 memory: 22701 grad_norm: 4.7330 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5815 loss: 1.5815 2022/09/05 14:34:50 - mmengine - INFO - Epoch(train) [26][540/940] lr: 1.0000e-02 eta: 15:58:33 time: 0.8874 data_time: 0.4998 memory: 22701 grad_norm: 4.6455 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7224 loss: 1.7224 2022/09/05 14:35:04 - mmengine - INFO - Epoch(train) [26][560/940] lr: 1.0000e-02 eta: 15:58:11 time: 0.7322 data_time: 0.3339 memory: 22701 grad_norm: 4.6033 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.6412 loss: 1.6412 2022/09/05 14:35:20 - mmengine - INFO - Epoch(train) [26][580/940] lr: 1.0000e-02 eta: 15:57:52 time: 0.7742 data_time: 0.3362 memory: 22701 grad_norm: 4.7100 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7230 loss: 1.7230 2022/09/05 14:35:37 - mmengine - INFO - Epoch(train) [26][600/940] lr: 1.0000e-02 eta: 15:57:36 time: 0.8370 data_time: 0.1192 memory: 22701 grad_norm: 4.6057 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5677 loss: 1.5677 2022/09/05 14:35:52 - mmengine - INFO - Epoch(train) [26][620/940] lr: 1.0000e-02 eta: 15:57:17 time: 0.7803 data_time: 0.2929 memory: 22701 grad_norm: 4.5577 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6929 loss: 1.6929 2022/09/05 14:36:08 - mmengine - INFO - Epoch(train) [26][640/940] lr: 1.0000e-02 eta: 15:56:59 time: 0.7921 data_time: 0.3050 memory: 22701 grad_norm: 4.6234 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6512 loss: 1.6512 2022/09/05 14:36:25 - mmengine - INFO - Epoch(train) [26][660/940] lr: 1.0000e-02 eta: 15:56:43 time: 0.8264 data_time: 0.3615 memory: 22701 grad_norm: 4.6293 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5876 loss: 1.5876 2022/09/05 14:36:40 - mmengine - INFO - Epoch(train) [26][680/940] lr: 1.0000e-02 eta: 15:56:24 time: 0.7859 data_time: 0.1080 memory: 22701 grad_norm: 4.6543 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6862 loss: 1.6862 2022/09/05 14:36:56 - mmengine - INFO - Epoch(train) [26][700/940] lr: 1.0000e-02 eta: 15:56:06 time: 0.7866 data_time: 0.1520 memory: 22701 grad_norm: 4.6253 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6681 loss: 1.6681 2022/09/05 14:37:12 - mmengine - INFO - Epoch(train) [26][720/940] lr: 1.0000e-02 eta: 15:55:47 time: 0.7805 data_time: 0.1580 memory: 22701 grad_norm: 4.6108 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.5691 loss: 1.5691 2022/09/05 14:37:28 - mmengine - INFO - Epoch(train) [26][740/940] lr: 1.0000e-02 eta: 15:55:31 time: 0.8322 data_time: 0.0331 memory: 22701 grad_norm: 4.6150 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6383 loss: 1.6383 2022/09/05 14:37:46 - mmengine - INFO - Epoch(train) [26][760/940] lr: 1.0000e-02 eta: 15:55:19 time: 0.8850 data_time: 0.1612 memory: 22701 grad_norm: 4.6722 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5370 loss: 1.5370 2022/09/05 14:38:04 - mmengine - INFO - Epoch(train) [26][780/940] lr: 1.0000e-02 eta: 15:55:06 time: 0.8894 data_time: 0.0315 memory: 22701 grad_norm: 4.6478 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5791 loss: 1.5791 2022/09/05 14:38:23 - mmengine - INFO - Epoch(train) [26][800/940] lr: 1.0000e-02 eta: 15:54:57 time: 0.9464 data_time: 0.0801 memory: 22701 grad_norm: 4.6222 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5390 loss: 1.5390 2022/09/05 14:38:37 - mmengine - INFO - Epoch(train) [26][820/940] lr: 1.0000e-02 eta: 15:54:35 time: 0.7256 data_time: 0.1125 memory: 22701 grad_norm: 4.6257 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6813 loss: 1.6813 2022/09/05 14:38:54 - mmengine - INFO - Epoch(train) [26][840/940] lr: 1.0000e-02 eta: 15:54:20 time: 0.8569 data_time: 0.2219 memory: 22701 grad_norm: 4.6961 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4911 loss: 1.4911 2022/09/05 14:39:15 - mmengine - INFO - Epoch(train) [26][860/940] lr: 1.0000e-02 eta: 15:54:14 time: 1.0056 data_time: 0.3628 memory: 22701 grad_norm: 4.6657 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.6272 loss: 1.6272 2022/09/05 14:39:32 - mmengine - INFO - Epoch(train) [26][880/940] lr: 1.0000e-02 eta: 15:54:01 time: 0.8817 data_time: 0.1533 memory: 22701 grad_norm: 4.6120 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6368 loss: 1.6368 2022/09/05 14:39:51 - mmengine - INFO - Epoch(train) [26][900/940] lr: 1.0000e-02 eta: 15:53:51 time: 0.9270 data_time: 0.0395 memory: 22701 grad_norm: 4.7351 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7653 loss: 1.7653 2022/09/05 14:40:04 - mmengine - INFO - Epoch(train) [26][920/940] lr: 1.0000e-02 eta: 15:53:27 time: 0.6840 data_time: 0.0505 memory: 22701 grad_norm: 4.6682 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5583 loss: 1.5583 2022/09/05 14:40:19 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:40:19 - mmengine - INFO - Epoch(train) [26][940/940] lr: 1.0000e-02 eta: 15:53:05 time: 0.7395 data_time: 0.0299 memory: 22701 grad_norm: 4.9376 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.7135 loss: 1.7135 2022/09/05 14:40:33 - mmengine - INFO - Epoch(val) [26][20/78] eta: 0:00:40 time: 0.6900 data_time: 0.5682 memory: 2247 2022/09/05 14:40:42 - mmengine - INFO - Epoch(val) [26][40/78] eta: 0:00:17 time: 0.4567 data_time: 0.3373 memory: 2247 2022/09/05 14:40:55 - mmengine - INFO - Epoch(val) [26][60/78] eta: 0:00:11 time: 0.6630 data_time: 0.5447 memory: 2247 2022/09/05 14:41:06 - mmengine - INFO - Epoch(val) [26][78/78] acc/top1: 0.6339 acc/top5: 0.8533 acc/mean1: 0.6339 2022/09/05 14:41:25 - mmengine - INFO - Epoch(train) [27][20/940] lr: 1.0000e-02 eta: 15:52:58 time: 0.9791 data_time: 0.4414 memory: 22701 grad_norm: 4.5281 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5075 loss: 1.5075 2022/09/05 14:41:38 - mmengine - INFO - Epoch(train) [27][40/940] lr: 1.0000e-02 eta: 15:52:31 time: 0.6432 data_time: 0.1312 memory: 22701 grad_norm: 4.4895 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5899 loss: 1.5899 2022/09/05 14:41:54 - mmengine - INFO - Epoch(train) [27][60/940] lr: 1.0000e-02 eta: 15:52:12 time: 0.7718 data_time: 0.1446 memory: 22701 grad_norm: 4.5810 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4662 loss: 1.4662 2022/09/05 14:42:07 - mmengine - INFO - Epoch(train) [27][80/940] lr: 1.0000e-02 eta: 15:51:46 time: 0.6567 data_time: 0.0757 memory: 22701 grad_norm: 4.6522 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6374 loss: 1.6374 2022/09/05 14:42:23 - mmengine - INFO - Epoch(train) [27][100/940] lr: 1.0000e-02 eta: 15:51:28 time: 0.7971 data_time: 0.0735 memory: 22701 grad_norm: 4.5625 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5627 loss: 1.5627 2022/09/05 14:42:36 - mmengine - INFO - Epoch(train) [27][120/940] lr: 1.0000e-02 eta: 15:51:03 time: 0.6584 data_time: 0.1019 memory: 22701 grad_norm: 4.6073 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5977 loss: 1.5977 2022/09/05 14:42:53 - mmengine - INFO - Epoch(train) [27][140/940] lr: 1.0000e-02 eta: 15:50:48 time: 0.8615 data_time: 0.2706 memory: 22701 grad_norm: 4.4780 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.5222 loss: 1.5222 2022/09/05 14:43:07 - mmengine - INFO - Epoch(train) [27][160/940] lr: 1.0000e-02 eta: 15:50:26 time: 0.7137 data_time: 0.1845 memory: 22701 grad_norm: 4.5317 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5224 loss: 1.5224 2022/09/05 14:43:26 - mmengine - INFO - Epoch(train) [27][180/940] lr: 1.0000e-02 eta: 15:50:16 time: 0.9417 data_time: 0.2284 memory: 22701 grad_norm: 4.5709 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6416 loss: 1.6416 2022/09/05 14:43:44 - mmengine - INFO - Epoch(train) [27][200/940] lr: 1.0000e-02 eta: 15:50:04 time: 0.8969 data_time: 0.1599 memory: 22701 grad_norm: 4.5694 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5690 loss: 1.5690 2022/09/05 14:44:03 - mmengine - INFO - Epoch(train) [27][220/940] lr: 1.0000e-02 eta: 15:49:54 time: 0.9341 data_time: 0.0743 memory: 22701 grad_norm: 4.6279 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6584 loss: 1.6584 2022/09/05 14:44:21 - mmengine - INFO - Epoch(train) [27][240/940] lr: 1.0000e-02 eta: 15:49:42 time: 0.8992 data_time: 0.0208 memory: 22701 grad_norm: 4.6013 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.5940 loss: 1.5940 2022/09/05 14:44:38 - mmengine - INFO - Epoch(train) [27][260/940] lr: 1.0000e-02 eta: 15:49:27 time: 0.8447 data_time: 0.0241 memory: 22701 grad_norm: 4.6881 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6232 loss: 1.6232 2022/09/05 14:44:53 - mmengine - INFO - Epoch(train) [27][280/940] lr: 1.0000e-02 eta: 15:49:08 time: 0.7763 data_time: 0.0305 memory: 22701 grad_norm: 4.6195 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5482 loss: 1.5482 2022/09/05 14:45:10 - mmengine - INFO - Epoch(train) [27][300/940] lr: 1.0000e-02 eta: 15:48:51 time: 0.8189 data_time: 0.0334 memory: 22701 grad_norm: 4.7096 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6043 loss: 1.6043 2022/09/05 14:45:24 - mmengine - INFO - Epoch(train) [27][320/940] lr: 1.0000e-02 eta: 15:48:29 time: 0.7162 data_time: 0.0244 memory: 22701 grad_norm: 4.6914 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6462 loss: 1.6462 2022/09/05 14:45:39 - mmengine - INFO - Epoch(train) [27][340/940] lr: 1.0000e-02 eta: 15:48:09 time: 0.7593 data_time: 0.0291 memory: 22701 grad_norm: 4.6215 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5312 loss: 1.5312 2022/09/05 14:45:54 - mmengine - INFO - Epoch(train) [27][360/940] lr: 1.0000e-02 eta: 15:47:49 time: 0.7647 data_time: 0.0217 memory: 22701 grad_norm: 4.6135 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5434 loss: 1.5434 2022/09/05 14:46:11 - mmengine - INFO - Epoch(train) [27][380/940] lr: 1.0000e-02 eta: 15:47:34 time: 0.8399 data_time: 0.0357 memory: 22701 grad_norm: 4.6499 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6616 loss: 1.6616 2022/09/05 14:46:26 - mmengine - INFO - Epoch(train) [27][400/940] lr: 1.0000e-02 eta: 15:47:13 time: 0.7555 data_time: 0.0319 memory: 22701 grad_norm: 4.6094 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5793 loss: 1.5793 2022/09/05 14:46:45 - mmengine - INFO - Epoch(train) [27][420/940] lr: 1.0000e-02 eta: 15:47:03 time: 0.9295 data_time: 0.0254 memory: 22701 grad_norm: 4.5439 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5752 loss: 1.5752 2022/09/05 14:47:00 - mmengine - INFO - Epoch(train) [27][440/940] lr: 1.0000e-02 eta: 15:46:43 time: 0.7560 data_time: 0.0246 memory: 22701 grad_norm: 4.6777 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.5084 loss: 1.5084 2022/09/05 14:47:21 - mmengine - INFO - Epoch(train) [27][460/940] lr: 1.0000e-02 eta: 15:46:40 time: 1.0631 data_time: 0.0257 memory: 22701 grad_norm: 4.6791 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6015 loss: 1.6015 2022/09/05 14:47:37 - mmengine - INFO - Epoch(train) [27][480/940] lr: 1.0000e-02 eta: 15:46:22 time: 0.7941 data_time: 0.0288 memory: 22701 grad_norm: 4.6028 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5214 loss: 1.5214 2022/09/05 14:47:57 - mmengine - INFO - Epoch(train) [27][500/940] lr: 1.0000e-02 eta: 15:46:15 time: 1.0010 data_time: 0.0267 memory: 22701 grad_norm: 4.6349 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5950 loss: 1.5950 2022/09/05 14:48:11 - mmengine - INFO - Epoch(train) [27][520/940] lr: 1.0000e-02 eta: 15:45:52 time: 0.6910 data_time: 0.0242 memory: 22701 grad_norm: 4.6331 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6448 loss: 1.6448 2022/09/05 14:48:28 - mmengine - INFO - Epoch(train) [27][540/940] lr: 1.0000e-02 eta: 15:45:37 time: 0.8466 data_time: 0.0327 memory: 22701 grad_norm: 4.6722 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7857 loss: 1.7857 2022/09/05 14:48:41 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:48:41 - mmengine - INFO - Epoch(train) [27][560/940] lr: 1.0000e-02 eta: 15:45:12 time: 0.6674 data_time: 0.0330 memory: 22701 grad_norm: 4.5796 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5935 loss: 1.5935 2022/09/05 14:48:58 - mmengine - INFO - Epoch(train) [27][580/940] lr: 1.0000e-02 eta: 15:44:56 time: 0.8446 data_time: 0.0274 memory: 22701 grad_norm: 4.6311 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5282 loss: 1.5282 2022/09/05 14:49:14 - mmengine - INFO - Epoch(train) [27][600/940] lr: 1.0000e-02 eta: 15:44:39 time: 0.8025 data_time: 0.0345 memory: 22701 grad_norm: 4.6413 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6923 loss: 1.6923 2022/09/05 14:49:30 - mmengine - INFO - Epoch(train) [27][620/940] lr: 1.0000e-02 eta: 15:44:22 time: 0.8085 data_time: 0.0298 memory: 22701 grad_norm: 4.6714 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5804 loss: 1.5804 2022/09/05 14:49:44 - mmengine - INFO - Epoch(train) [27][640/940] lr: 1.0000e-02 eta: 15:43:56 time: 0.6612 data_time: 0.0266 memory: 22701 grad_norm: 4.7185 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6867 loss: 1.6867 2022/09/05 14:49:59 - mmengine - INFO - Epoch(train) [27][660/940] lr: 1.0000e-02 eta: 15:43:37 time: 0.7579 data_time: 0.0330 memory: 22701 grad_norm: 4.6428 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4830 loss: 1.4830 2022/09/05 14:50:14 - mmengine - INFO - Epoch(train) [27][680/940] lr: 1.0000e-02 eta: 15:43:16 time: 0.7507 data_time: 0.0288 memory: 22701 grad_norm: 4.7369 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5849 loss: 1.5849 2022/09/05 14:50:29 - mmengine - INFO - Epoch(train) [27][700/940] lr: 1.0000e-02 eta: 15:42:56 time: 0.7613 data_time: 0.0326 memory: 22701 grad_norm: 4.6992 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6564 loss: 1.6564 2022/09/05 14:50:44 - mmengine - INFO - Epoch(train) [27][720/940] lr: 1.0000e-02 eta: 15:42:34 time: 0.7180 data_time: 0.0255 memory: 22701 grad_norm: 4.5851 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6866 loss: 1.6866 2022/09/05 14:51:00 - mmengine - INFO - Epoch(train) [27][740/940] lr: 1.0000e-02 eta: 15:42:19 time: 0.8432 data_time: 0.0291 memory: 22701 grad_norm: 4.6366 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.5337 loss: 1.5337 2022/09/05 14:51:14 - mmengine - INFO - Epoch(train) [27][760/940] lr: 1.0000e-02 eta: 15:41:54 time: 0.6669 data_time: 0.0297 memory: 22701 grad_norm: 4.6586 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8429 loss: 1.8429 2022/09/05 14:51:29 - mmengine - INFO - Epoch(train) [27][780/940] lr: 1.0000e-02 eta: 15:41:35 time: 0.7649 data_time: 0.0251 memory: 22701 grad_norm: 4.5517 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6296 loss: 1.6296 2022/09/05 14:51:43 - mmengine - INFO - Epoch(train) [27][800/940] lr: 1.0000e-02 eta: 15:41:13 time: 0.7197 data_time: 0.0294 memory: 22701 grad_norm: 4.7611 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7405 loss: 1.7405 2022/09/05 14:52:01 - mmengine - INFO - Epoch(train) [27][820/940] lr: 1.0000e-02 eta: 15:41:00 time: 0.8820 data_time: 0.0377 memory: 22701 grad_norm: 4.7023 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5408 loss: 1.5408 2022/09/05 14:52:15 - mmengine - INFO - Epoch(train) [27][840/940] lr: 1.0000e-02 eta: 15:40:38 time: 0.7229 data_time: 0.0284 memory: 22701 grad_norm: 4.6815 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5627 loss: 1.5627 2022/09/05 14:52:34 - mmengine - INFO - Epoch(train) [27][860/940] lr: 1.0000e-02 eta: 15:40:28 time: 0.9454 data_time: 0.0487 memory: 22701 grad_norm: 4.6922 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4960 loss: 1.4960 2022/09/05 14:52:52 - mmengine - INFO - Epoch(train) [27][880/940] lr: 1.0000e-02 eta: 15:40:15 time: 0.8868 data_time: 0.1187 memory: 22701 grad_norm: 4.6486 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5507 loss: 1.5507 2022/09/05 14:53:11 - mmengine - INFO - Epoch(train) [27][900/940] lr: 1.0000e-02 eta: 15:40:06 time: 0.9496 data_time: 0.5565 memory: 22701 grad_norm: 4.6172 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.7082 loss: 1.7082 2022/09/05 14:53:26 - mmengine - INFO - Epoch(train) [27][920/940] lr: 1.0000e-02 eta: 15:39:46 time: 0.7664 data_time: 0.3257 memory: 22701 grad_norm: 4.7231 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8256 loss: 1.8256 2022/09/05 14:53:43 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 14:53:43 - mmengine - INFO - Epoch(train) [27][940/940] lr: 1.0000e-02 eta: 15:39:29 time: 0.8086 data_time: 0.4183 memory: 22701 grad_norm: 4.8383 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.5741 loss: 1.5741 2022/09/05 14:53:43 - mmengine - INFO - Saving checkpoint at 27 epochs 2022/09/05 14:53:58 - mmengine - INFO - Epoch(val) [27][20/78] eta: 0:00:40 time: 0.7066 data_time: 0.5889 memory: 2247 2022/09/05 14:54:07 - mmengine - INFO - Epoch(val) [27][40/78] eta: 0:00:16 time: 0.4442 data_time: 0.3273 memory: 2247 2022/09/05 14:54:20 - mmengine - INFO - Epoch(val) [27][60/78] eta: 0:00:11 time: 0.6431 data_time: 0.5274 memory: 2247 2022/09/05 14:54:30 - mmengine - INFO - Epoch(val) [27][78/78] acc/top1: 0.6399 acc/top5: 0.8525 acc/mean1: 0.6398 2022/09/05 14:54:30 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_26.pth is removed 2022/09/05 14:54:31 - mmengine - INFO - The best checkpoint with 0.6399 acc/top1 at 28 epoch is saved to best_acc/top1_epoch_28.pth. 2022/09/05 14:54:51 - mmengine - INFO - Epoch(train) [28][20/940] lr: 1.0000e-02 eta: 15:39:21 time: 0.9769 data_time: 0.5871 memory: 22701 grad_norm: 4.5399 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.6732 loss: 1.6732 2022/09/05 14:55:04 - mmengine - INFO - Epoch(train) [28][40/940] lr: 1.0000e-02 eta: 15:38:55 time: 0.6487 data_time: 0.2714 memory: 22701 grad_norm: 4.5766 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5623 loss: 1.5623 2022/09/05 14:55:22 - mmengine - INFO - Epoch(train) [28][60/940] lr: 1.0000e-02 eta: 15:38:43 time: 0.8973 data_time: 0.3922 memory: 22701 grad_norm: 4.5942 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7146 loss: 1.7146 2022/09/05 14:55:38 - mmengine - INFO - Epoch(train) [28][80/940] lr: 1.0000e-02 eta: 15:38:26 time: 0.8071 data_time: 0.1715 memory: 22701 grad_norm: 4.5873 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5608 loss: 1.5608 2022/09/05 14:55:54 - mmengine - INFO - Epoch(train) [28][100/940] lr: 1.0000e-02 eta: 15:38:09 time: 0.8185 data_time: 0.1645 memory: 22701 grad_norm: 4.5397 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5019 loss: 1.5019 2022/09/05 14:56:09 - mmengine - INFO - Epoch(train) [28][120/940] lr: 1.0000e-02 eta: 15:37:48 time: 0.7368 data_time: 0.1059 memory: 22701 grad_norm: 4.5515 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6384 loss: 1.6384 2022/09/05 14:56:29 - mmengine - INFO - Epoch(train) [28][140/940] lr: 1.0000e-02 eta: 15:37:41 time: 0.9847 data_time: 0.2739 memory: 22701 grad_norm: 4.6734 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5105 loss: 1.5105 2022/09/05 14:56:44 - mmengine - INFO - Epoch(train) [28][160/940] lr: 1.0000e-02 eta: 15:37:20 time: 0.7501 data_time: 0.0942 memory: 22701 grad_norm: 4.6195 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5652 loss: 1.5652 2022/09/05 14:57:01 - mmengine - INFO - Epoch(train) [28][180/940] lr: 1.0000e-02 eta: 15:37:06 time: 0.8612 data_time: 0.1159 memory: 22701 grad_norm: 4.6567 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6275 loss: 1.6275 2022/09/05 14:57:20 - mmengine - INFO - Epoch(train) [28][200/940] lr: 1.0000e-02 eta: 15:36:57 time: 0.9528 data_time: 0.3947 memory: 22701 grad_norm: 4.5380 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6067 loss: 1.6067 2022/09/05 14:57:36 - mmengine - INFO - Epoch(train) [28][220/940] lr: 1.0000e-02 eta: 15:36:39 time: 0.7896 data_time: 0.4020 memory: 22701 grad_norm: 4.6067 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5366 loss: 1.5366 2022/09/05 14:57:49 - mmengine - INFO - Epoch(train) [28][240/940] lr: 1.0000e-02 eta: 15:36:14 time: 0.6642 data_time: 0.2586 memory: 22701 grad_norm: 4.5512 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5957 loss: 1.5957 2022/09/05 14:58:05 - mmengine - INFO - Epoch(train) [28][260/940] lr: 1.0000e-02 eta: 15:35:58 time: 0.8291 data_time: 0.4372 memory: 22701 grad_norm: 4.7576 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6417 loss: 1.6417 2022/09/05 14:58:19 - mmengine - INFO - Epoch(train) [28][280/940] lr: 1.0000e-02 eta: 15:35:33 time: 0.6569 data_time: 0.2669 memory: 22701 grad_norm: 4.6086 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5509 loss: 1.5509 2022/09/05 14:58:38 - mmengine - INFO - Epoch(train) [28][300/940] lr: 1.0000e-02 eta: 15:35:25 time: 0.9846 data_time: 0.5936 memory: 22701 grad_norm: 4.5394 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6720 loss: 1.6720 2022/09/05 14:58:53 - mmengine - INFO - Epoch(train) [28][320/940] lr: 1.0000e-02 eta: 15:35:04 time: 0.7395 data_time: 0.3455 memory: 22701 grad_norm: 4.7215 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7002 loss: 1.7002 2022/09/05 14:59:10 - mmengine - INFO - Epoch(train) [28][340/940] lr: 1.0000e-02 eta: 15:34:50 time: 0.8590 data_time: 0.4692 memory: 22701 grad_norm: 4.5921 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5999 loss: 1.5999 2022/09/05 14:59:25 - mmengine - INFO - Epoch(train) [28][360/940] lr: 1.0000e-02 eta: 15:34:29 time: 0.7363 data_time: 0.2647 memory: 22701 grad_norm: 4.5389 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6071 loss: 1.6071 2022/09/05 14:59:42 - mmengine - INFO - Epoch(train) [28][380/940] lr: 1.0000e-02 eta: 15:34:13 time: 0.8389 data_time: 0.3823 memory: 22701 grad_norm: 4.6964 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5360 loss: 1.5360 2022/09/05 14:59:56 - mmengine - INFO - Epoch(train) [28][400/940] lr: 1.0000e-02 eta: 15:33:50 time: 0.6983 data_time: 0.3133 memory: 22701 grad_norm: 4.6126 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5394 loss: 1.5394 2022/09/05 15:00:13 - mmengine - INFO - Epoch(train) [28][420/940] lr: 1.0000e-02 eta: 15:33:37 time: 0.8837 data_time: 0.4851 memory: 22701 grad_norm: 4.5969 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6596 loss: 1.6596 2022/09/05 15:00:29 - mmengine - INFO - Epoch(train) [28][440/940] lr: 1.0000e-02 eta: 15:33:18 time: 0.7715 data_time: 0.3808 memory: 22701 grad_norm: 4.5806 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.5875 loss: 1.5875 2022/09/05 15:00:47 - mmengine - INFO - Epoch(train) [28][460/940] lr: 1.0000e-02 eta: 15:33:07 time: 0.9161 data_time: 0.4949 memory: 22701 grad_norm: 4.5318 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.4861 loss: 1.4861 2022/09/05 15:01:02 - mmengine - INFO - Epoch(train) [28][480/940] lr: 1.0000e-02 eta: 15:32:47 time: 0.7651 data_time: 0.3523 memory: 22701 grad_norm: 4.5327 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4739 loss: 1.4739 2022/09/05 15:01:24 - mmengine - INFO - Epoch(train) [28][500/940] lr: 1.0000e-02 eta: 15:32:43 time: 1.0536 data_time: 0.3745 memory: 22701 grad_norm: 4.6847 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.6788 loss: 1.6788 2022/09/05 15:01:39 - mmengine - INFO - Epoch(train) [28][520/940] lr: 1.0000e-02 eta: 15:32:23 time: 0.7494 data_time: 0.1032 memory: 22701 grad_norm: 4.7111 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5233 loss: 1.5233 2022/09/05 15:01:57 - mmengine - INFO - Epoch(train) [28][540/940] lr: 1.0000e-02 eta: 15:32:12 time: 0.9254 data_time: 0.0292 memory: 22701 grad_norm: 4.6104 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8300 loss: 1.8300 2022/09/05 15:02:10 - mmengine - INFO - Epoch(train) [28][560/940] lr: 1.0000e-02 eta: 15:31:47 time: 0.6596 data_time: 0.0279 memory: 22701 grad_norm: 4.6547 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6529 loss: 1.6529 2022/09/05 15:02:28 - mmengine - INFO - Epoch(train) [28][580/940] lr: 1.0000e-02 eta: 15:31:33 time: 0.8685 data_time: 0.0281 memory: 22701 grad_norm: 4.5936 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5577 loss: 1.5577 2022/09/05 15:02:41 - mmengine - INFO - Epoch(train) [28][600/940] lr: 1.0000e-02 eta: 15:31:10 time: 0.6936 data_time: 0.0298 memory: 22701 grad_norm: 4.6038 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6016 loss: 1.6016 2022/09/05 15:02:59 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:02:59 - mmengine - INFO - Epoch(train) [28][620/940] lr: 1.0000e-02 eta: 15:30:56 time: 0.8726 data_time: 0.0431 memory: 22701 grad_norm: 4.6568 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.6023 loss: 1.6023 2022/09/05 15:03:13 - mmengine - INFO - Epoch(train) [28][640/940] lr: 1.0000e-02 eta: 15:30:35 time: 0.7247 data_time: 0.0304 memory: 22701 grad_norm: 4.5251 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6106 loss: 1.6106 2022/09/05 15:03:30 - mmengine - INFO - Epoch(train) [28][660/940] lr: 1.0000e-02 eta: 15:30:20 time: 0.8516 data_time: 0.1271 memory: 22701 grad_norm: 4.6079 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6886 loss: 1.6886 2022/09/05 15:03:46 - mmengine - INFO - Epoch(train) [28][680/940] lr: 1.0000e-02 eta: 15:30:01 time: 0.7833 data_time: 0.2385 memory: 22701 grad_norm: 4.7465 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.5774 loss: 1.5774 2022/09/05 15:04:03 - mmengine - INFO - Epoch(train) [28][700/940] lr: 1.0000e-02 eta: 15:29:46 time: 0.8397 data_time: 0.3211 memory: 22701 grad_norm: 4.5977 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4974 loss: 1.4974 2022/09/05 15:04:19 - mmengine - INFO - Epoch(train) [28][720/940] lr: 1.0000e-02 eta: 15:29:27 time: 0.7830 data_time: 0.3488 memory: 22701 grad_norm: 4.6528 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5975 loss: 1.5975 2022/09/05 15:04:37 - mmengine - INFO - Epoch(train) [28][740/940] lr: 1.0000e-02 eta: 15:29:15 time: 0.8965 data_time: 0.4772 memory: 22701 grad_norm: 4.6945 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5796 loss: 1.5796 2022/09/05 15:04:52 - mmengine - INFO - Epoch(train) [28][760/940] lr: 1.0000e-02 eta: 15:28:56 time: 0.7808 data_time: 0.3345 memory: 22701 grad_norm: 4.6556 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5919 loss: 1.5919 2022/09/05 15:05:12 - mmengine - INFO - Epoch(train) [28][780/940] lr: 1.0000e-02 eta: 15:28:49 time: 0.9893 data_time: 0.5668 memory: 22701 grad_norm: 4.6831 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6763 loss: 1.6763 2022/09/05 15:05:26 - mmengine - INFO - Epoch(train) [28][800/940] lr: 1.0000e-02 eta: 15:28:25 time: 0.6805 data_time: 0.2903 memory: 22701 grad_norm: 4.5768 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6210 loss: 1.6210 2022/09/05 15:05:43 - mmengine - INFO - Epoch(train) [28][820/940] lr: 1.0000e-02 eta: 15:28:12 time: 0.8885 data_time: 0.4781 memory: 22701 grad_norm: 4.5962 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7019 loss: 1.7019 2022/09/05 15:05:57 - mmengine - INFO - Epoch(train) [28][840/940] lr: 1.0000e-02 eta: 15:27:49 time: 0.7057 data_time: 0.3090 memory: 22701 grad_norm: 4.6928 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5809 loss: 1.5809 2022/09/05 15:06:14 - mmengine - INFO - Epoch(train) [28][860/940] lr: 1.0000e-02 eta: 15:27:33 time: 0.8124 data_time: 0.4036 memory: 22701 grad_norm: 4.5527 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6251 loss: 1.6251 2022/09/05 15:06:28 - mmengine - INFO - Epoch(train) [28][880/940] lr: 1.0000e-02 eta: 15:27:12 time: 0.7342 data_time: 0.3028 memory: 22701 grad_norm: 4.6093 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6634 loss: 1.6634 2022/09/05 15:06:47 - mmengine - INFO - Epoch(train) [28][900/940] lr: 1.0000e-02 eta: 15:27:00 time: 0.9138 data_time: 0.5186 memory: 22701 grad_norm: 4.7538 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6903 loss: 1.6903 2022/09/05 15:07:02 - mmengine - INFO - Epoch(train) [28][920/940] lr: 1.0000e-02 eta: 15:26:42 time: 0.7810 data_time: 0.3924 memory: 22701 grad_norm: 4.5997 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4706 loss: 1.4706 2022/09/05 15:07:17 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:07:17 - mmengine - INFO - Epoch(train) [28][940/940] lr: 1.0000e-02 eta: 15:26:20 time: 0.7161 data_time: 0.3210 memory: 22701 grad_norm: 4.8593 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 1.6501 loss: 1.6501 2022/09/05 15:07:31 - mmengine - INFO - Epoch(val) [28][20/78] eta: 0:00:40 time: 0.6942 data_time: 0.5762 memory: 2247 2022/09/05 15:07:40 - mmengine - INFO - Epoch(val) [28][40/78] eta: 0:00:17 time: 0.4585 data_time: 0.3399 memory: 2247 2022/09/05 15:07:53 - mmengine - INFO - Epoch(val) [28][60/78] eta: 0:00:11 time: 0.6623 data_time: 0.5441 memory: 2247 2022/09/05 15:08:03 - mmengine - INFO - Epoch(val) [28][78/78] acc/top1: 0.6408 acc/top5: 0.8528 acc/mean1: 0.6407 2022/09/05 15:08:03 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_28.pth is removed 2022/09/05 15:08:04 - mmengine - INFO - The best checkpoint with 0.6408 acc/top1 at 29 epoch is saved to best_acc/top1_epoch_29.pth. 2022/09/05 15:08:24 - mmengine - INFO - Epoch(train) [29][20/940] lr: 1.0000e-02 eta: 15:26:12 time: 0.9933 data_time: 0.6154 memory: 22701 grad_norm: 4.6252 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6185 loss: 1.6185 2022/09/05 15:08:39 - mmengine - INFO - Epoch(train) [29][40/940] lr: 1.0000e-02 eta: 15:25:53 time: 0.7609 data_time: 0.3119 memory: 22701 grad_norm: 4.6982 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6064 loss: 1.6064 2022/09/05 15:08:58 - mmengine - INFO - Epoch(train) [29][60/940] lr: 1.0000e-02 eta: 15:25:42 time: 0.9418 data_time: 0.3614 memory: 22701 grad_norm: 4.6549 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5467 loss: 1.5467 2022/09/05 15:09:12 - mmengine - INFO - Epoch(train) [29][80/940] lr: 1.0000e-02 eta: 15:25:20 time: 0.6991 data_time: 0.2912 memory: 22701 grad_norm: 4.5959 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6344 loss: 1.6344 2022/09/05 15:09:29 - mmengine - INFO - Epoch(train) [29][100/940] lr: 1.0000e-02 eta: 15:25:04 time: 0.8417 data_time: 0.3772 memory: 22701 grad_norm: 4.5939 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4624 loss: 1.4624 2022/09/05 15:09:42 - mmengine - INFO - Epoch(train) [29][120/940] lr: 1.0000e-02 eta: 15:24:40 time: 0.6775 data_time: 0.1398 memory: 22701 grad_norm: 4.6326 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.4836 loss: 1.4836 2022/09/05 15:10:00 - mmengine - INFO - Epoch(train) [29][140/940] lr: 1.0000e-02 eta: 15:24:28 time: 0.8950 data_time: 0.1087 memory: 22701 grad_norm: 4.5977 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6373 loss: 1.6373 2022/09/05 15:10:15 - mmengine - INFO - Epoch(train) [29][160/940] lr: 1.0000e-02 eta: 15:24:09 time: 0.7752 data_time: 0.0169 memory: 22701 grad_norm: 4.5433 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.6671 loss: 1.6671 2022/09/05 15:10:33 - mmengine - INFO - Epoch(train) [29][180/940] lr: 1.0000e-02 eta: 15:23:55 time: 0.8625 data_time: 0.0379 memory: 22701 grad_norm: 4.5702 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5538 loss: 1.5538 2022/09/05 15:10:47 - mmengine - INFO - Epoch(train) [29][200/940] lr: 1.0000e-02 eta: 15:23:32 time: 0.7026 data_time: 0.0369 memory: 22701 grad_norm: 4.5906 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6723 loss: 1.6723 2022/09/05 15:11:03 - mmengine - INFO - Epoch(train) [29][220/940] lr: 1.0000e-02 eta: 15:23:15 time: 0.8111 data_time: 0.0365 memory: 22701 grad_norm: 4.4698 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4641 loss: 1.4641 2022/09/05 15:11:18 - mmengine - INFO - Epoch(train) [29][240/940] lr: 1.0000e-02 eta: 15:22:54 time: 0.7195 data_time: 0.0244 memory: 22701 grad_norm: 4.5539 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5540 loss: 1.5540 2022/09/05 15:11:37 - mmengine - INFO - Epoch(train) [29][260/940] lr: 1.0000e-02 eta: 15:22:46 time: 1.0004 data_time: 0.0313 memory: 22701 grad_norm: 4.5310 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4755 loss: 1.4755 2022/09/05 15:11:55 - mmengine - INFO - Epoch(train) [29][280/940] lr: 1.0000e-02 eta: 15:22:32 time: 0.8573 data_time: 0.0320 memory: 22701 grad_norm: 4.5594 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5092 loss: 1.5092 2022/09/05 15:12:13 - mmengine - INFO - Epoch(train) [29][300/940] lr: 1.0000e-02 eta: 15:22:21 time: 0.9420 data_time: 0.0284 memory: 22701 grad_norm: 4.6717 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5142 loss: 1.5142 2022/09/05 15:12:30 - mmengine - INFO - Epoch(train) [29][320/940] lr: 1.0000e-02 eta: 15:22:05 time: 0.8272 data_time: 0.0248 memory: 22701 grad_norm: 4.7349 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6804 loss: 1.6804 2022/09/05 15:12:48 - mmengine - INFO - Epoch(train) [29][340/940] lr: 1.0000e-02 eta: 15:21:54 time: 0.9121 data_time: 0.0542 memory: 22701 grad_norm: 4.6632 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5965 loss: 1.5965 2022/09/05 15:13:05 - mmengine - INFO - Epoch(train) [29][360/940] lr: 1.0000e-02 eta: 15:21:39 time: 0.8600 data_time: 0.0181 memory: 22701 grad_norm: 4.6144 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5378 loss: 1.5378 2022/09/05 15:13:24 - mmengine - INFO - Epoch(train) [29][380/940] lr: 1.0000e-02 eta: 15:21:27 time: 0.9159 data_time: 0.0307 memory: 22701 grad_norm: 4.5477 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5250 loss: 1.5250 2022/09/05 15:13:39 - mmengine - INFO - Epoch(train) [29][400/940] lr: 1.0000e-02 eta: 15:21:09 time: 0.7864 data_time: 0.0372 memory: 22701 grad_norm: 4.6078 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6153 loss: 1.6153 2022/09/05 15:13:56 - mmengine - INFO - Epoch(train) [29][420/940] lr: 1.0000e-02 eta: 15:20:53 time: 0.8328 data_time: 0.0710 memory: 22701 grad_norm: 4.6754 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7222 loss: 1.7222 2022/09/05 15:14:12 - mmengine - INFO - Epoch(train) [29][440/940] lr: 1.0000e-02 eta: 15:20:35 time: 0.7923 data_time: 0.0915 memory: 22701 grad_norm: 4.5747 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6357 loss: 1.6357 2022/09/05 15:14:30 - mmengine - INFO - Epoch(train) [29][460/940] lr: 1.0000e-02 eta: 15:20:24 time: 0.9250 data_time: 0.2450 memory: 22701 grad_norm: 4.6307 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6710 loss: 1.6710 2022/09/05 15:14:49 - mmengine - INFO - Epoch(train) [29][480/940] lr: 1.0000e-02 eta: 15:20:12 time: 0.9045 data_time: 0.1065 memory: 22701 grad_norm: 4.6511 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5051 loss: 1.5051 2022/09/05 15:15:05 - mmengine - INFO - Epoch(train) [29][500/940] lr: 1.0000e-02 eta: 15:19:56 time: 0.8304 data_time: 0.0545 memory: 22701 grad_norm: 4.6688 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.6389 loss: 1.6389 2022/09/05 15:15:19 - mmengine - INFO - Epoch(train) [29][520/940] lr: 1.0000e-02 eta: 15:19:34 time: 0.7114 data_time: 0.0262 memory: 22701 grad_norm: 4.8099 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4982 loss: 1.4982 2022/09/05 15:15:35 - mmengine - INFO - Epoch(train) [29][540/940] lr: 1.0000e-02 eta: 15:19:15 time: 0.7747 data_time: 0.0348 memory: 22701 grad_norm: 4.5112 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6686 loss: 1.6686 2022/09/05 15:15:51 - mmengine - INFO - Epoch(train) [29][560/940] lr: 1.0000e-02 eta: 15:18:58 time: 0.8021 data_time: 0.0212 memory: 22701 grad_norm: 4.6458 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7273 loss: 1.7273 2022/09/05 15:16:06 - mmengine - INFO - Epoch(train) [29][580/940] lr: 1.0000e-02 eta: 15:18:38 time: 0.7481 data_time: 0.0306 memory: 22701 grad_norm: 4.5706 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5494 loss: 1.5494 2022/09/05 15:16:21 - mmengine - INFO - Epoch(train) [29][600/940] lr: 1.0000e-02 eta: 15:18:19 time: 0.7696 data_time: 0.0308 memory: 22701 grad_norm: 4.6397 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6988 loss: 1.6988 2022/09/05 15:16:38 - mmengine - INFO - Epoch(train) [29][620/940] lr: 1.0000e-02 eta: 15:18:03 time: 0.8319 data_time: 0.1999 memory: 22701 grad_norm: 4.7520 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5036 loss: 1.5036 2022/09/05 15:16:54 - mmengine - INFO - Epoch(train) [29][640/940] lr: 1.0000e-02 eta: 15:17:44 time: 0.7806 data_time: 0.3358 memory: 22701 grad_norm: 4.6143 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6346 loss: 1.6346 2022/09/05 15:17:11 - mmengine - INFO - Epoch(train) [29][660/940] lr: 1.0000e-02 eta: 15:17:30 time: 0.8703 data_time: 0.4398 memory: 22701 grad_norm: 4.6156 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5019 loss: 1.5019 2022/09/05 15:17:26 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:17:26 - mmengine - INFO - Epoch(train) [29][680/940] lr: 1.0000e-02 eta: 15:17:10 time: 0.7457 data_time: 0.3316 memory: 22701 grad_norm: 4.6231 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5606 loss: 1.5606 2022/09/05 15:17:43 - mmengine - INFO - Epoch(train) [29][700/940] lr: 1.0000e-02 eta: 15:16:55 time: 0.8436 data_time: 0.2398 memory: 22701 grad_norm: 4.6331 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6688 loss: 1.6688 2022/09/05 15:17:58 - mmengine - INFO - Epoch(train) [29][720/940] lr: 1.0000e-02 eta: 15:16:34 time: 0.7413 data_time: 0.0285 memory: 22701 grad_norm: 4.6781 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5981 loss: 1.5981 2022/09/05 15:18:15 - mmengine - INFO - Epoch(train) [29][740/940] lr: 1.0000e-02 eta: 15:16:21 time: 0.8813 data_time: 0.0241 memory: 22701 grad_norm: 4.6874 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6305 loss: 1.6305 2022/09/05 15:18:30 - mmengine - INFO - Epoch(train) [29][760/940] lr: 1.0000e-02 eta: 15:16:00 time: 0.7282 data_time: 0.0243 memory: 22701 grad_norm: 4.5873 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5004 loss: 1.5004 2022/09/05 15:18:48 - mmengine - INFO - Epoch(train) [29][780/940] lr: 1.0000e-02 eta: 15:15:47 time: 0.8930 data_time: 0.0301 memory: 22701 grad_norm: 4.5852 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4555 loss: 1.4555 2022/09/05 15:19:02 - mmengine - INFO - Epoch(train) [29][800/940] lr: 1.0000e-02 eta: 15:15:26 time: 0.7271 data_time: 0.0308 memory: 22701 grad_norm: 4.6864 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6763 loss: 1.6763 2022/09/05 15:19:21 - mmengine - INFO - Epoch(train) [29][820/940] lr: 1.0000e-02 eta: 15:15:16 time: 0.9586 data_time: 0.0262 memory: 22701 grad_norm: 4.5937 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4837 loss: 1.4837 2022/09/05 15:19:36 - mmengine - INFO - Epoch(train) [29][840/940] lr: 1.0000e-02 eta: 15:14:55 time: 0.7145 data_time: 0.0194 memory: 22701 grad_norm: 4.7142 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5975 loss: 1.5975 2022/09/05 15:19:54 - mmengine - INFO - Epoch(train) [29][860/940] lr: 1.0000e-02 eta: 15:14:44 time: 0.9320 data_time: 0.0336 memory: 22701 grad_norm: 4.6134 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5079 loss: 1.5079 2022/09/05 15:20:10 - mmengine - INFO - Epoch(train) [29][880/940] lr: 1.0000e-02 eta: 15:14:25 time: 0.7783 data_time: 0.0251 memory: 22701 grad_norm: 4.6719 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5691 loss: 1.5691 2022/09/05 15:20:29 - mmengine - INFO - Epoch(train) [29][900/940] lr: 1.0000e-02 eta: 15:14:16 time: 0.9775 data_time: 0.0263 memory: 22701 grad_norm: 4.6765 top1_acc: 0.4688 top5_acc: 0.9375 loss_cls: 1.5442 loss: 1.5442 2022/09/05 15:20:43 - mmengine - INFO - Epoch(train) [29][920/940] lr: 1.0000e-02 eta: 15:13:52 time: 0.6625 data_time: 0.0229 memory: 22701 grad_norm: 4.7105 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6195 loss: 1.6195 2022/09/05 15:20:58 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:20:58 - mmengine - INFO - Epoch(train) [29][940/940] lr: 1.0000e-02 eta: 15:13:33 time: 0.7719 data_time: 0.0198 memory: 22701 grad_norm: 5.1186 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.7314 loss: 1.7314 2022/09/05 15:21:12 - mmengine - INFO - Epoch(val) [29][20/78] eta: 0:00:39 time: 0.6890 data_time: 0.5696 memory: 2247 2022/09/05 15:21:21 - mmengine - INFO - Epoch(val) [29][40/78] eta: 0:00:16 time: 0.4436 data_time: 0.3241 memory: 2247 2022/09/05 15:21:34 - mmengine - INFO - Epoch(val) [29][60/78] eta: 0:00:12 time: 0.6793 data_time: 0.5607 memory: 2247 2022/09/05 15:21:44 - mmengine - INFO - Epoch(val) [29][78/78] acc/top1: 0.6420 acc/top5: 0.8584 acc/mean1: 0.6420 2022/09/05 15:21:44 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_29.pth is removed 2022/09/05 15:21:45 - mmengine - INFO - The best checkpoint with 0.6420 acc/top1 at 30 epoch is saved to best_acc/top1_epoch_30.pth. 2022/09/05 15:22:05 - mmengine - INFO - Epoch(train) [30][20/940] lr: 1.0000e-02 eta: 15:13:23 time: 0.9545 data_time: 0.5501 memory: 22701 grad_norm: 4.5287 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.4849 loss: 1.4849 2022/09/05 15:22:19 - mmengine - INFO - Epoch(train) [30][40/940] lr: 1.0000e-02 eta: 15:13:02 time: 0.7231 data_time: 0.3446 memory: 22701 grad_norm: 4.5793 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.6426 loss: 1.6426 2022/09/05 15:22:36 - mmengine - INFO - Epoch(train) [30][60/940] lr: 1.0000e-02 eta: 15:12:48 time: 0.8589 data_time: 0.2619 memory: 22701 grad_norm: 4.5623 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5872 loss: 1.5872 2022/09/05 15:22:50 - mmengine - INFO - Epoch(train) [30][80/940] lr: 1.0000e-02 eta: 15:12:24 time: 0.6731 data_time: 0.1665 memory: 22701 grad_norm: 4.5617 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5478 loss: 1.5478 2022/09/05 15:23:07 - mmengine - INFO - Epoch(train) [30][100/940] lr: 1.0000e-02 eta: 15:12:10 time: 0.8821 data_time: 0.4614 memory: 22701 grad_norm: 4.5967 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5488 loss: 1.5488 2022/09/05 15:23:24 - mmengine - INFO - Epoch(train) [30][120/940] lr: 1.0000e-02 eta: 15:11:54 time: 0.8114 data_time: 0.2414 memory: 22701 grad_norm: 4.5721 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4325 loss: 1.4325 2022/09/05 15:23:43 - mmengine - INFO - Epoch(train) [30][140/940] lr: 1.0000e-02 eta: 15:11:43 time: 0.9466 data_time: 0.0579 memory: 22701 grad_norm: 4.5955 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5452 loss: 1.5452 2022/09/05 15:23:58 - mmengine - INFO - Epoch(train) [30][160/940] lr: 1.0000e-02 eta: 15:11:26 time: 0.7971 data_time: 0.0234 memory: 22701 grad_norm: 4.7786 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5722 loss: 1.5722 2022/09/05 15:24:20 - mmengine - INFO - Epoch(train) [30][180/940] lr: 1.0000e-02 eta: 15:11:21 time: 1.0634 data_time: 0.0374 memory: 22701 grad_norm: 4.6675 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5891 loss: 1.5891 2022/09/05 15:24:34 - mmengine - INFO - Epoch(train) [30][200/940] lr: 1.0000e-02 eta: 15:11:00 time: 0.7251 data_time: 0.0282 memory: 22701 grad_norm: 4.6044 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4757 loss: 1.4757 2022/09/05 15:24:52 - mmengine - INFO - Epoch(train) [30][220/940] lr: 1.0000e-02 eta: 15:10:45 time: 0.8587 data_time: 0.0256 memory: 22701 grad_norm: 4.6211 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4973 loss: 1.4973 2022/09/05 15:25:06 - mmengine - INFO - Epoch(train) [30][240/940] lr: 1.0000e-02 eta: 15:10:23 time: 0.7044 data_time: 0.0331 memory: 22701 grad_norm: 4.6163 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6330 loss: 1.6330 2022/09/05 15:25:24 - mmengine - INFO - Epoch(train) [30][260/940] lr: 1.0000e-02 eta: 15:10:11 time: 0.9208 data_time: 0.0300 memory: 22701 grad_norm: 4.5819 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6834 loss: 1.6834 2022/09/05 15:25:38 - mmengine - INFO - Epoch(train) [30][280/940] lr: 1.0000e-02 eta: 15:09:50 time: 0.7148 data_time: 0.0875 memory: 22701 grad_norm: 4.5851 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5308 loss: 1.5308 2022/09/05 15:25:54 - mmengine - INFO - Epoch(train) [30][300/940] lr: 1.0000e-02 eta: 15:09:31 time: 0.7729 data_time: 0.0698 memory: 22701 grad_norm: 4.6040 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5052 loss: 1.5052 2022/09/05 15:26:10 - mmengine - INFO - Epoch(train) [30][320/940] lr: 1.0000e-02 eta: 15:09:14 time: 0.8141 data_time: 0.0755 memory: 22701 grad_norm: 4.6595 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5634 loss: 1.5634 2022/09/05 15:26:28 - mmengine - INFO - Epoch(train) [30][340/940] lr: 1.0000e-02 eta: 15:09:01 time: 0.8931 data_time: 0.0814 memory: 22701 grad_norm: 4.7593 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5749 loss: 1.5749 2022/09/05 15:26:42 - mmengine - INFO - Epoch(train) [30][360/940] lr: 1.0000e-02 eta: 15:08:39 time: 0.7060 data_time: 0.0248 memory: 22701 grad_norm: 4.5866 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4844 loss: 1.4844 2022/09/05 15:27:01 - mmengine - INFO - Epoch(train) [30][380/940] lr: 1.0000e-02 eta: 15:08:30 time: 0.9659 data_time: 0.0758 memory: 22701 grad_norm: 4.6855 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6049 loss: 1.6049 2022/09/05 15:27:16 - mmengine - INFO - Epoch(train) [30][400/940] lr: 1.0000e-02 eta: 15:08:10 time: 0.7555 data_time: 0.0313 memory: 22701 grad_norm: 4.5039 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.5154 loss: 1.5154 2022/09/05 15:27:37 - mmengine - INFO - Epoch(train) [30][420/940] lr: 1.0000e-02 eta: 15:08:04 time: 1.0359 data_time: 0.0236 memory: 22701 grad_norm: 4.7171 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5042 loss: 1.5042 2022/09/05 15:27:53 - mmengine - INFO - Epoch(train) [30][440/940] lr: 1.0000e-02 eta: 15:07:46 time: 0.7918 data_time: 0.0431 memory: 22701 grad_norm: 4.6194 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5441 loss: 1.5441 2022/09/05 15:28:13 - mmengine - INFO - Epoch(train) [30][460/940] lr: 1.0000e-02 eta: 15:07:39 time: 1.0037 data_time: 0.0526 memory: 22701 grad_norm: 4.5125 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5766 loss: 1.5766 2022/09/05 15:28:29 - mmengine - INFO - Epoch(train) [30][480/940] lr: 1.0000e-02 eta: 15:07:21 time: 0.7925 data_time: 0.0364 memory: 22701 grad_norm: 4.6592 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6121 loss: 1.6121 2022/09/05 15:28:48 - mmengine - INFO - Epoch(train) [30][500/940] lr: 1.0000e-02 eta: 15:07:12 time: 0.9760 data_time: 0.0264 memory: 22701 grad_norm: 4.5977 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5028 loss: 1.5028 2022/09/05 15:29:05 - mmengine - INFO - Epoch(train) [30][520/940] lr: 1.0000e-02 eta: 15:06:55 time: 0.8169 data_time: 0.0247 memory: 22701 grad_norm: 4.6261 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6336 loss: 1.6336 2022/09/05 15:29:23 - mmengine - INFO - Epoch(train) [30][540/940] lr: 1.0000e-02 eta: 15:06:43 time: 0.9046 data_time: 0.0284 memory: 22701 grad_norm: 4.6224 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5642 loss: 1.5642 2022/09/05 15:29:40 - mmengine - INFO - Epoch(train) [30][560/940] lr: 1.0000e-02 eta: 15:06:27 time: 0.8336 data_time: 0.0313 memory: 22701 grad_norm: 4.6231 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6217 loss: 1.6217 2022/09/05 15:29:59 - mmengine - INFO - Epoch(train) [30][580/940] lr: 1.0000e-02 eta: 15:06:18 time: 0.9812 data_time: 0.0319 memory: 22701 grad_norm: 4.6104 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.5644 loss: 1.5644 2022/09/05 15:30:14 - mmengine - INFO - Epoch(train) [30][600/940] lr: 1.0000e-02 eta: 15:05:58 time: 0.7496 data_time: 0.0253 memory: 22701 grad_norm: 4.6573 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6561 loss: 1.6561 2022/09/05 15:30:32 - mmengine - INFO - Epoch(train) [30][620/940] lr: 1.0000e-02 eta: 15:05:44 time: 0.8714 data_time: 0.0350 memory: 22701 grad_norm: 4.5940 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 1.7184 loss: 1.7184 2022/09/05 15:30:46 - mmengine - INFO - Epoch(train) [30][640/940] lr: 1.0000e-02 eta: 15:05:23 time: 0.7194 data_time: 0.0236 memory: 22701 grad_norm: 4.6595 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5437 loss: 1.5437 2022/09/05 15:31:05 - mmengine - INFO - Epoch(train) [30][660/940] lr: 1.0000e-02 eta: 15:05:11 time: 0.9296 data_time: 0.0366 memory: 22701 grad_norm: 4.6547 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.4818 loss: 1.4818 2022/09/05 15:31:21 - mmengine - INFO - Epoch(train) [30][680/940] lr: 1.0000e-02 eta: 15:04:53 time: 0.7937 data_time: 0.0270 memory: 22701 grad_norm: 4.6764 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7128 loss: 1.7128 2022/09/05 15:31:38 - mmengine - INFO - Epoch(train) [30][700/940] lr: 1.0000e-02 eta: 15:04:40 time: 0.8804 data_time: 0.0317 memory: 22701 grad_norm: 4.6979 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5574 loss: 1.5574 2022/09/05 15:31:54 - mmengine - INFO - Epoch(train) [30][720/940] lr: 1.0000e-02 eta: 15:04:21 time: 0.7782 data_time: 0.0253 memory: 22701 grad_norm: 4.6659 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.6387 loss: 1.6387 2022/09/05 15:32:10 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:32:10 - mmengine - INFO - Epoch(train) [30][740/940] lr: 1.0000e-02 eta: 15:04:06 time: 0.8424 data_time: 0.1550 memory: 22701 grad_norm: 4.6178 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5321 loss: 1.5321 2022/09/05 15:32:24 - mmengine - INFO - Epoch(train) [30][760/940] lr: 1.0000e-02 eta: 15:03:43 time: 0.6826 data_time: 0.1219 memory: 22701 grad_norm: 4.7281 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6972 loss: 1.6972 2022/09/05 15:32:40 - mmengine - INFO - Epoch(train) [30][780/940] lr: 1.0000e-02 eta: 15:03:24 time: 0.7806 data_time: 0.2131 memory: 22701 grad_norm: 4.6108 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.6473 loss: 1.6473 2022/09/05 15:32:54 - mmengine - INFO - Epoch(train) [30][800/940] lr: 1.0000e-02 eta: 15:03:03 time: 0.7194 data_time: 0.0565 memory: 22701 grad_norm: 4.5651 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5471 loss: 1.5471 2022/09/05 15:33:10 - mmengine - INFO - Epoch(train) [30][820/940] lr: 1.0000e-02 eta: 15:02:45 time: 0.7851 data_time: 0.0415 memory: 22701 grad_norm: 4.6076 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6311 loss: 1.6311 2022/09/05 15:33:24 - mmengine - INFO - Epoch(train) [30][840/940] lr: 1.0000e-02 eta: 15:02:24 time: 0.7133 data_time: 0.0258 memory: 22701 grad_norm: 4.6919 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6030 loss: 1.6030 2022/09/05 15:33:40 - mmengine - INFO - Epoch(train) [30][860/940] lr: 1.0000e-02 eta: 15:02:06 time: 0.8073 data_time: 0.0261 memory: 22701 grad_norm: 4.6811 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.5283 loss: 1.5283 2022/09/05 15:33:55 - mmengine - INFO - Epoch(train) [30][880/940] lr: 1.0000e-02 eta: 15:01:46 time: 0.7309 data_time: 0.0202 memory: 22701 grad_norm: 4.6548 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.6041 loss: 1.6041 2022/09/05 15:34:12 - mmengine - INFO - Epoch(train) [30][900/940] lr: 1.0000e-02 eta: 15:01:31 time: 0.8516 data_time: 0.0265 memory: 22701 grad_norm: 4.6337 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5552 loss: 1.5552 2022/09/05 15:34:26 - mmengine - INFO - Epoch(train) [30][920/940] lr: 1.0000e-02 eta: 15:01:08 time: 0.6947 data_time: 0.0168 memory: 22701 grad_norm: 4.6358 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5900 loss: 1.5900 2022/09/05 15:34:41 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:34:41 - mmengine - INFO - Epoch(train) [30][940/940] lr: 1.0000e-02 eta: 15:00:49 time: 0.7686 data_time: 0.0170 memory: 22701 grad_norm: 4.9257 top1_acc: 0.1429 top5_acc: 1.0000 loss_cls: 1.4480 loss: 1.4480 2022/09/05 15:34:41 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/09/05 15:34:57 - mmengine - INFO - Epoch(val) [30][20/78] eta: 0:00:40 time: 0.7008 data_time: 0.5793 memory: 2247 2022/09/05 15:35:07 - mmengine - INFO - Epoch(val) [30][40/78] eta: 0:00:17 time: 0.4592 data_time: 0.3439 memory: 2247 2022/09/05 15:35:20 - mmengine - INFO - Epoch(val) [30][60/78] eta: 0:00:11 time: 0.6543 data_time: 0.5367 memory: 2247 2022/09/05 15:35:29 - mmengine - INFO - Epoch(val) [30][78/78] acc/top1: 0.6399 acc/top5: 0.8575 acc/mean1: 0.6397 2022/09/05 15:35:51 - mmengine - INFO - Epoch(train) [31][20/940] lr: 1.0000e-02 eta: 15:00:46 time: 1.1037 data_time: 0.3858 memory: 22701 grad_norm: 4.6166 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5874 loss: 1.5874 2022/09/05 15:36:05 - mmengine - INFO - Epoch(train) [31][40/940] lr: 1.0000e-02 eta: 15:00:24 time: 0.6962 data_time: 0.1935 memory: 22701 grad_norm: 4.6191 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6870 loss: 1.6870 2022/09/05 15:36:22 - mmengine - INFO - Epoch(train) [31][60/940] lr: 1.0000e-02 eta: 15:00:09 time: 0.8553 data_time: 0.4191 memory: 22701 grad_norm: 4.5103 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4383 loss: 1.4383 2022/09/05 15:36:36 - mmengine - INFO - Epoch(train) [31][80/940] lr: 1.0000e-02 eta: 14:59:45 time: 0.6569 data_time: 0.1870 memory: 22701 grad_norm: 4.6190 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.5519 loss: 1.5519 2022/09/05 15:36:53 - mmengine - INFO - Epoch(train) [31][100/940] lr: 1.0000e-02 eta: 14:59:31 time: 0.8817 data_time: 0.4848 memory: 22701 grad_norm: 4.6586 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6140 loss: 1.6140 2022/09/05 15:37:09 - mmengine - INFO - Epoch(train) [31][120/940] lr: 1.0000e-02 eta: 14:59:13 time: 0.7865 data_time: 0.3575 memory: 22701 grad_norm: 4.4998 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5268 loss: 1.5268 2022/09/05 15:37:24 - mmengine - INFO - Epoch(train) [31][140/940] lr: 1.0000e-02 eta: 14:58:54 time: 0.7613 data_time: 0.3139 memory: 22701 grad_norm: 4.6460 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4557 loss: 1.4557 2022/09/05 15:37:42 - mmengine - INFO - Epoch(train) [31][160/940] lr: 1.0000e-02 eta: 14:58:40 time: 0.8804 data_time: 0.3575 memory: 22701 grad_norm: 4.6241 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6086 loss: 1.6086 2022/09/05 15:37:59 - mmengine - INFO - Epoch(train) [31][180/940] lr: 1.0000e-02 eta: 14:58:26 time: 0.8747 data_time: 0.2437 memory: 22701 grad_norm: 4.6663 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6228 loss: 1.6228 2022/09/05 15:38:15 - mmengine - INFO - Epoch(train) [31][200/940] lr: 1.0000e-02 eta: 14:58:09 time: 0.7959 data_time: 0.0766 memory: 22701 grad_norm: 4.5707 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6811 loss: 1.6811 2022/09/05 15:38:32 - mmengine - INFO - Epoch(train) [31][220/940] lr: 1.0000e-02 eta: 14:57:52 time: 0.8117 data_time: 0.0269 memory: 22701 grad_norm: 4.5810 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4346 loss: 1.4346 2022/09/05 15:38:46 - mmengine - INFO - Epoch(train) [31][240/940] lr: 1.0000e-02 eta: 14:57:30 time: 0.7039 data_time: 0.0728 memory: 22701 grad_norm: 4.5838 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.5710 loss: 1.5710 2022/09/05 15:39:02 - mmengine - INFO - Epoch(train) [31][260/940] lr: 1.0000e-02 eta: 14:57:13 time: 0.8011 data_time: 0.1231 memory: 22701 grad_norm: 4.5848 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6037 loss: 1.6037 2022/09/05 15:39:16 - mmengine - INFO - Epoch(train) [31][280/940] lr: 1.0000e-02 eta: 14:56:51 time: 0.7151 data_time: 0.1823 memory: 22701 grad_norm: 4.5278 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6275 loss: 1.6275 2022/09/05 15:39:31 - mmengine - INFO - Epoch(train) [31][300/940] lr: 1.0000e-02 eta: 14:56:32 time: 0.7541 data_time: 0.1553 memory: 22701 grad_norm: 4.6583 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5735 loss: 1.5735 2022/09/05 15:39:45 - mmengine - INFO - Epoch(train) [31][320/940] lr: 1.0000e-02 eta: 14:56:10 time: 0.7123 data_time: 0.0532 memory: 22701 grad_norm: 4.6503 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5490 loss: 1.5490 2022/09/05 15:40:02 - mmengine - INFO - Epoch(train) [31][340/940] lr: 1.0000e-02 eta: 14:55:54 time: 0.8238 data_time: 0.0215 memory: 22701 grad_norm: 4.6297 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5319 loss: 1.5319 2022/09/05 15:40:17 - mmengine - INFO - Epoch(train) [31][360/940] lr: 1.0000e-02 eta: 14:55:35 time: 0.7539 data_time: 0.0299 memory: 22701 grad_norm: 4.6412 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4288 loss: 1.4288 2022/09/05 15:40:33 - mmengine - INFO - Epoch(train) [31][380/940] lr: 1.0000e-02 eta: 14:55:17 time: 0.7853 data_time: 0.0193 memory: 22701 grad_norm: 4.6477 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5504 loss: 1.5504 2022/09/05 15:40:48 - mmengine - INFO - Epoch(train) [31][400/940] lr: 1.0000e-02 eta: 14:54:59 time: 0.7886 data_time: 0.0270 memory: 22701 grad_norm: 4.6236 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5030 loss: 1.5030 2022/09/05 15:41:03 - mmengine - INFO - Epoch(train) [31][420/940] lr: 1.0000e-02 eta: 14:54:39 time: 0.7441 data_time: 0.0234 memory: 22701 grad_norm: 4.6284 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5705 loss: 1.5705 2022/09/05 15:41:19 - mmengine - INFO - Epoch(train) [31][440/940] lr: 1.0000e-02 eta: 14:54:21 time: 0.7988 data_time: 0.0300 memory: 22701 grad_norm: 4.5891 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6079 loss: 1.6079 2022/09/05 15:41:33 - mmengine - INFO - Epoch(train) [31][460/940] lr: 1.0000e-02 eta: 14:53:59 time: 0.6914 data_time: 0.0248 memory: 22701 grad_norm: 4.6202 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5216 loss: 1.5216 2022/09/05 15:41:51 - mmengine - INFO - Epoch(train) [31][480/940] lr: 1.0000e-02 eta: 14:53:45 time: 0.8774 data_time: 0.0355 memory: 22701 grad_norm: 4.6431 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.5859 loss: 1.5859 2022/09/05 15:42:04 - mmengine - INFO - Epoch(train) [31][500/940] lr: 1.0000e-02 eta: 14:53:23 time: 0.6954 data_time: 0.0232 memory: 22701 grad_norm: 4.6639 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5355 loss: 1.5355 2022/09/05 15:42:22 - mmengine - INFO - Epoch(train) [31][520/940] lr: 1.0000e-02 eta: 14:53:09 time: 0.8659 data_time: 0.0305 memory: 22701 grad_norm: 4.5639 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6018 loss: 1.6018 2022/09/05 15:42:37 - mmengine - INFO - Epoch(train) [31][540/940] lr: 1.0000e-02 eta: 14:52:49 time: 0.7475 data_time: 0.0932 memory: 22701 grad_norm: 4.6823 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4742 loss: 1.4742 2022/09/05 15:42:54 - mmengine - INFO - Epoch(train) [31][560/940] lr: 1.0000e-02 eta: 14:52:33 time: 0.8408 data_time: 0.2272 memory: 22701 grad_norm: 4.7497 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5287 loss: 1.5287 2022/09/05 15:43:07 - mmengine - INFO - Epoch(train) [31][580/940] lr: 1.0000e-02 eta: 14:52:11 time: 0.6910 data_time: 0.1857 memory: 22701 grad_norm: 4.5800 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.5667 loss: 1.5667 2022/09/05 15:43:24 - mmengine - INFO - Epoch(train) [31][600/940] lr: 1.0000e-02 eta: 14:51:56 time: 0.8427 data_time: 0.3564 memory: 22701 grad_norm: 4.5848 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5854 loss: 1.5854 2022/09/05 15:43:37 - mmengine - INFO - Epoch(train) [31][620/940] lr: 1.0000e-02 eta: 14:51:32 time: 0.6581 data_time: 0.1944 memory: 22701 grad_norm: 4.7337 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6743 loss: 1.6743 2022/09/05 15:43:55 - mmengine - INFO - Epoch(train) [31][640/940] lr: 1.0000e-02 eta: 14:51:18 time: 0.8762 data_time: 0.2940 memory: 22701 grad_norm: 4.6829 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6065 loss: 1.6065 2022/09/05 15:44:11 - mmengine - INFO - Epoch(train) [31][660/940] lr: 1.0000e-02 eta: 14:51:02 time: 0.8221 data_time: 0.1449 memory: 22701 grad_norm: 4.5673 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.4954 loss: 1.4954 2022/09/05 15:44:30 - mmengine - INFO - Epoch(train) [31][680/940] lr: 1.0000e-02 eta: 14:50:51 time: 0.9490 data_time: 0.3588 memory: 22701 grad_norm: 4.6141 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.5441 loss: 1.5441 2022/09/05 15:44:49 - mmengine - INFO - Epoch(train) [31][700/940] lr: 1.0000e-02 eta: 14:50:39 time: 0.9161 data_time: 0.0216 memory: 22701 grad_norm: 4.7080 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4590 loss: 1.4590 2022/09/05 15:45:11 - mmengine - INFO - Epoch(train) [31][720/940] lr: 1.0000e-02 eta: 14:50:36 time: 1.1241 data_time: 0.1399 memory: 22701 grad_norm: 4.6684 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7031 loss: 1.7031 2022/09/05 15:45:25 - mmengine - INFO - Epoch(train) [31][740/940] lr: 1.0000e-02 eta: 14:50:14 time: 0.6923 data_time: 0.0203 memory: 22701 grad_norm: 4.6987 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6777 loss: 1.6777 2022/09/05 15:45:42 - mmengine - INFO - Epoch(train) [31][760/940] lr: 1.0000e-02 eta: 14:49:59 time: 0.8611 data_time: 0.0368 memory: 22701 grad_norm: 4.6833 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5338 loss: 1.5338 2022/09/05 15:45:57 - mmengine - INFO - Epoch(train) [31][780/940] lr: 1.0000e-02 eta: 14:49:39 time: 0.7298 data_time: 0.0527 memory: 22701 grad_norm: 4.6467 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5337 loss: 1.5337 2022/09/05 15:46:20 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:46:20 - mmengine - INFO - Epoch(train) [31][800/940] lr: 1.0000e-02 eta: 14:49:38 time: 1.1652 data_time: 0.2085 memory: 22701 grad_norm: 4.5182 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4809 loss: 1.4809 2022/09/05 15:46:39 - mmengine - INFO - Epoch(train) [31][820/940] lr: 1.0000e-02 eta: 14:49:26 time: 0.9263 data_time: 0.2431 memory: 22701 grad_norm: 4.5913 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4521 loss: 1.4521 2022/09/05 15:46:55 - mmengine - INFO - Epoch(train) [31][840/940] lr: 1.0000e-02 eta: 14:49:09 time: 0.8189 data_time: 0.1753 memory: 22701 grad_norm: 4.6619 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6264 loss: 1.6264 2022/09/05 15:47:15 - mmengine - INFO - Epoch(train) [31][860/940] lr: 1.0000e-02 eta: 14:49:00 time: 0.9820 data_time: 0.3921 memory: 22701 grad_norm: 4.7447 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6601 loss: 1.6601 2022/09/05 15:47:33 - mmengine - INFO - Epoch(train) [31][880/940] lr: 1.0000e-02 eta: 14:48:49 time: 0.9382 data_time: 0.3011 memory: 22701 grad_norm: 4.6296 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4568 loss: 1.4568 2022/09/05 15:47:52 - mmengine - INFO - Epoch(train) [31][900/940] lr: 1.0000e-02 eta: 14:48:36 time: 0.9082 data_time: 0.0970 memory: 22701 grad_norm: 4.7697 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7099 loss: 1.7099 2022/09/05 15:48:11 - mmengine - INFO - Epoch(train) [31][920/940] lr: 1.0000e-02 eta: 14:48:26 time: 0.9650 data_time: 0.0274 memory: 22701 grad_norm: 4.6421 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5336 loss: 1.5336 2022/09/05 15:48:25 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 15:48:25 - mmengine - INFO - Epoch(train) [31][940/940] lr: 1.0000e-02 eta: 14:48:05 time: 0.6998 data_time: 0.0161 memory: 22701 grad_norm: 4.9493 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.5538 loss: 1.5538 2022/09/05 15:48:39 - mmengine - INFO - Epoch(val) [31][20/78] eta: 0:00:40 time: 0.6910 data_time: 0.5744 memory: 2247 2022/09/05 15:48:48 - mmengine - INFO - Epoch(val) [31][40/78] eta: 0:00:16 time: 0.4427 data_time: 0.3235 memory: 2247 2022/09/05 15:49:01 - mmengine - INFO - Epoch(val) [31][60/78] eta: 0:00:12 time: 0.6777 data_time: 0.5578 memory: 2247 2022/09/05 15:49:11 - mmengine - INFO - Epoch(val) [31][78/78] acc/top1: 0.6429 acc/top5: 0.8522 acc/mean1: 0.6427 2022/09/05 15:49:11 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_30.pth is removed 2022/09/05 15:49:12 - mmengine - INFO - The best checkpoint with 0.6429 acc/top1 at 32 epoch is saved to best_acc/top1_epoch_32.pth. 2022/09/05 15:49:32 - mmengine - INFO - Epoch(train) [32][20/940] lr: 1.0000e-02 eta: 14:47:56 time: 0.9916 data_time: 0.6151 memory: 22701 grad_norm: 4.6120 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4978 loss: 1.4978 2022/09/05 15:49:46 - mmengine - INFO - Epoch(train) [32][40/940] lr: 1.0000e-02 eta: 14:47:34 time: 0.6933 data_time: 0.2897 memory: 22701 grad_norm: 4.5532 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4783 loss: 1.4783 2022/09/05 15:50:03 - mmengine - INFO - Epoch(train) [32][60/940] lr: 1.0000e-02 eta: 14:47:19 time: 0.8627 data_time: 0.4848 memory: 22701 grad_norm: 4.5899 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5328 loss: 1.5328 2022/09/05 15:50:17 - mmengine - INFO - Epoch(train) [32][80/940] lr: 1.0000e-02 eta: 14:46:56 time: 0.6741 data_time: 0.2745 memory: 22701 grad_norm: 4.5702 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5503 loss: 1.5503 2022/09/05 15:50:35 - mmengine - INFO - Epoch(train) [32][100/940] lr: 1.0000e-02 eta: 14:46:44 time: 0.9195 data_time: 0.5321 memory: 22701 grad_norm: 4.5912 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4299 loss: 1.4299 2022/09/05 15:50:49 - mmengine - INFO - Epoch(train) [32][120/940] lr: 1.0000e-02 eta: 14:46:22 time: 0.7020 data_time: 0.3189 memory: 22701 grad_norm: 4.5453 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4745 loss: 1.4745 2022/09/05 15:51:09 - mmengine - INFO - Epoch(train) [32][140/940] lr: 1.0000e-02 eta: 14:46:13 time: 0.9761 data_time: 0.5768 memory: 22701 grad_norm: 4.4980 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.5089 loss: 1.5089 2022/09/05 15:51:23 - mmengine - INFO - Epoch(train) [32][160/940] lr: 1.0000e-02 eta: 14:45:52 time: 0.7315 data_time: 0.3288 memory: 22701 grad_norm: 4.6217 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5488 loss: 1.5488 2022/09/05 15:51:39 - mmengine - INFO - Epoch(train) [32][180/940] lr: 1.0000e-02 eta: 14:45:34 time: 0.7934 data_time: 0.4023 memory: 22701 grad_norm: 4.6712 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6157 loss: 1.6157 2022/09/05 15:51:53 - mmengine - INFO - Epoch(train) [32][200/940] lr: 1.0000e-02 eta: 14:45:13 time: 0.6982 data_time: 0.3036 memory: 22701 grad_norm: 4.7836 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5432 loss: 1.5432 2022/09/05 15:52:10 - mmengine - INFO - Epoch(train) [32][220/940] lr: 1.0000e-02 eta: 14:44:56 time: 0.8241 data_time: 0.3446 memory: 22701 grad_norm: 4.6193 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4201 loss: 1.4201 2022/09/05 15:52:24 - mmengine - INFO - Epoch(train) [32][240/940] lr: 1.0000e-02 eta: 14:44:35 time: 0.7096 data_time: 0.2293 memory: 22701 grad_norm: 4.7367 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7352 loss: 1.7352 2022/09/05 15:52:41 - mmengine - INFO - Epoch(train) [32][260/940] lr: 1.0000e-02 eta: 14:44:19 time: 0.8345 data_time: 0.1505 memory: 22701 grad_norm: 4.6076 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5594 loss: 1.5594 2022/09/05 15:52:57 - mmengine - INFO - Epoch(train) [32][280/940] lr: 1.0000e-02 eta: 14:44:03 time: 0.8299 data_time: 0.3885 memory: 22701 grad_norm: 4.6677 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6834 loss: 1.6834 2022/09/05 15:53:13 - mmengine - INFO - Epoch(train) [32][300/940] lr: 1.0000e-02 eta: 14:43:45 time: 0.7834 data_time: 0.3527 memory: 22701 grad_norm: 4.6501 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5072 loss: 1.5072 2022/09/05 15:53:33 - mmengine - INFO - Epoch(train) [32][320/940] lr: 1.0000e-02 eta: 14:43:37 time: 1.0141 data_time: 0.5919 memory: 22701 grad_norm: 4.6363 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.4831 loss: 1.4831 2022/09/05 15:53:48 - mmengine - INFO - Epoch(train) [32][340/940] lr: 1.0000e-02 eta: 14:43:17 time: 0.7297 data_time: 0.3155 memory: 22701 grad_norm: 4.7081 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.6186 loss: 1.6186 2022/09/05 15:54:07 - mmengine - INFO - Epoch(train) [32][360/940] lr: 1.0000e-02 eta: 14:43:05 time: 0.9371 data_time: 0.5240 memory: 22701 grad_norm: 4.6260 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5077 loss: 1.5077 2022/09/05 15:54:22 - mmengine - INFO - Epoch(train) [32][380/940] lr: 1.0000e-02 eta: 14:42:46 time: 0.7578 data_time: 0.2193 memory: 22701 grad_norm: 4.6891 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4989 loss: 1.4989 2022/09/05 15:54:38 - mmengine - INFO - Epoch(train) [32][400/940] lr: 1.0000e-02 eta: 14:42:30 time: 0.8311 data_time: 0.3449 memory: 22701 grad_norm: 4.5209 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4878 loss: 1.4878 2022/09/05 15:54:52 - mmengine - INFO - Epoch(train) [32][420/940] lr: 1.0000e-02 eta: 14:42:08 time: 0.6880 data_time: 0.1571 memory: 22701 grad_norm: 4.6450 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.5011 loss: 1.5011 2022/09/05 15:55:09 - mmengine - INFO - Epoch(train) [32][440/940] lr: 1.0000e-02 eta: 14:41:51 time: 0.8257 data_time: 0.2630 memory: 22701 grad_norm: 4.6428 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5047 loss: 1.5047 2022/09/05 15:55:24 - mmengine - INFO - Epoch(train) [32][460/940] lr: 1.0000e-02 eta: 14:41:32 time: 0.7458 data_time: 0.0878 memory: 22701 grad_norm: 4.6086 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5192 loss: 1.5192 2022/09/05 15:55:41 - mmengine - INFO - Epoch(train) [32][480/940] lr: 1.0000e-02 eta: 14:41:18 time: 0.8789 data_time: 0.0272 memory: 22701 grad_norm: 4.6312 top1_acc: 0.5000 top5_acc: 0.9688 loss_cls: 1.4791 loss: 1.4791 2022/09/05 15:55:58 - mmengine - INFO - Epoch(train) [32][500/940] lr: 1.0000e-02 eta: 14:41:02 time: 0.8247 data_time: 0.0270 memory: 22701 grad_norm: 4.6470 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5701 loss: 1.5701 2022/09/05 15:56:14 - mmengine - INFO - Epoch(train) [32][520/940] lr: 1.0000e-02 eta: 14:40:44 time: 0.7968 data_time: 0.0473 memory: 22701 grad_norm: 4.6528 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6108 loss: 1.6108 2022/09/05 15:56:30 - mmengine - INFO - Epoch(train) [32][540/940] lr: 1.0000e-02 eta: 14:40:27 time: 0.8151 data_time: 0.0278 memory: 22701 grad_norm: 4.6965 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5849 loss: 1.5849 2022/09/05 15:56:47 - mmengine - INFO - Epoch(train) [32][560/940] lr: 1.0000e-02 eta: 14:40:12 time: 0.8487 data_time: 0.0277 memory: 22701 grad_norm: 4.6224 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5084 loss: 1.5084 2022/09/05 15:57:03 - mmengine - INFO - Epoch(train) [32][580/940] lr: 1.0000e-02 eta: 14:39:56 time: 0.8253 data_time: 0.0369 memory: 22701 grad_norm: 4.5710 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4606 loss: 1.4606 2022/09/05 15:57:23 - mmengine - INFO - Epoch(train) [32][600/940] lr: 1.0000e-02 eta: 14:39:46 time: 0.9750 data_time: 0.0264 memory: 22701 grad_norm: 4.5644 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5308 loss: 1.5308 2022/09/05 15:57:38 - mmengine - INFO - Epoch(train) [32][620/940] lr: 1.0000e-02 eta: 14:39:27 time: 0.7524 data_time: 0.0330 memory: 22701 grad_norm: 4.6378 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5843 loss: 1.5843 2022/09/05 15:57:56 - mmengine - INFO - Epoch(train) [32][640/940] lr: 1.0000e-02 eta: 14:39:14 time: 0.9146 data_time: 0.0279 memory: 22701 grad_norm: 4.6029 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4926 loss: 1.4926 2022/09/05 15:58:12 - mmengine - INFO - Epoch(train) [32][660/940] lr: 1.0000e-02 eta: 14:38:56 time: 0.7681 data_time: 0.0293 memory: 22701 grad_norm: 4.7429 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4730 loss: 1.4730 2022/09/05 15:58:30 - mmengine - INFO - Epoch(train) [32][680/940] lr: 1.0000e-02 eta: 14:38:42 time: 0.8993 data_time: 0.0297 memory: 22701 grad_norm: 4.7427 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3818 loss: 1.3818 2022/09/05 15:58:45 - mmengine - INFO - Epoch(train) [32][700/940] lr: 1.0000e-02 eta: 14:38:23 time: 0.7556 data_time: 0.0239 memory: 22701 grad_norm: 4.8011 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.7285 loss: 1.7285 2022/09/05 15:59:01 - mmengine - INFO - Epoch(train) [32][720/940] lr: 1.0000e-02 eta: 14:38:08 time: 0.8396 data_time: 0.0380 memory: 22701 grad_norm: 4.6429 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5590 loss: 1.5590 2022/09/05 15:59:15 - mmengine - INFO - Epoch(train) [32][740/940] lr: 1.0000e-02 eta: 14:37:45 time: 0.6707 data_time: 0.0287 memory: 22701 grad_norm: 4.6272 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4420 loss: 1.4420 2022/09/05 15:59:30 - mmengine - INFO - Epoch(train) [32][760/940] lr: 1.0000e-02 eta: 14:37:25 time: 0.7530 data_time: 0.0287 memory: 22701 grad_norm: 4.5657 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4346 loss: 1.4346 2022/09/05 15:59:44 - mmengine - INFO - Epoch(train) [32][780/940] lr: 1.0000e-02 eta: 14:37:03 time: 0.6863 data_time: 0.0315 memory: 22701 grad_norm: 4.7843 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5893 loss: 1.5893 2022/09/05 16:00:00 - mmengine - INFO - Epoch(train) [32][800/940] lr: 1.0000e-02 eta: 14:36:47 time: 0.8380 data_time: 0.0269 memory: 22701 grad_norm: 4.7223 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4096 loss: 1.4096 2022/09/05 16:00:14 - mmengine - INFO - Epoch(train) [32][820/940] lr: 1.0000e-02 eta: 14:36:26 time: 0.7016 data_time: 0.0277 memory: 22701 grad_norm: 4.6909 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6752 loss: 1.6752 2022/09/05 16:00:32 - mmengine - INFO - Epoch(train) [32][840/940] lr: 1.0000e-02 eta: 14:36:11 time: 0.8619 data_time: 0.0308 memory: 22701 grad_norm: 4.6278 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4403 loss: 1.4403 2022/09/05 16:00:48 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:00:48 - mmengine - INFO - Epoch(train) [32][860/940] lr: 1.0000e-02 eta: 14:35:54 time: 0.8095 data_time: 0.0242 memory: 22701 grad_norm: 4.6341 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5288 loss: 1.5288 2022/09/05 16:01:08 - mmengine - INFO - Epoch(train) [32][880/940] lr: 1.0000e-02 eta: 14:35:47 time: 1.0283 data_time: 0.0250 memory: 22701 grad_norm: 4.6830 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6391 loss: 1.6391 2022/09/05 16:01:23 - mmengine - INFO - Epoch(train) [32][900/940] lr: 1.0000e-02 eta: 14:35:27 time: 0.7357 data_time: 0.0331 memory: 22701 grad_norm: 4.5431 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5002 loss: 1.5002 2022/09/05 16:01:39 - mmengine - INFO - Epoch(train) [32][920/940] lr: 1.0000e-02 eta: 14:35:09 time: 0.7989 data_time: 0.0245 memory: 22701 grad_norm: 4.6501 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5261 loss: 1.5261 2022/09/05 16:01:53 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:01:53 - mmengine - INFO - Epoch(train) [32][940/940] lr: 1.0000e-02 eta: 14:34:48 time: 0.7097 data_time: 0.0223 memory: 22701 grad_norm: 5.0367 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.6364 loss: 1.6364 2022/09/05 16:02:07 - mmengine - INFO - Epoch(val) [32][20/78] eta: 0:00:39 time: 0.6871 data_time: 0.5674 memory: 2247 2022/09/05 16:02:16 - mmengine - INFO - Epoch(val) [32][40/78] eta: 0:00:17 time: 0.4645 data_time: 0.3433 memory: 2247 2022/09/05 16:02:29 - mmengine - INFO - Epoch(val) [32][60/78] eta: 0:00:11 time: 0.6403 data_time: 0.5230 memory: 2247 2022/09/05 16:02:40 - mmengine - INFO - Epoch(val) [32][78/78] acc/top1: 0.6421 acc/top5: 0.8579 acc/mean1: 0.6420 2022/09/05 16:03:00 - mmengine - INFO - Epoch(train) [33][20/940] lr: 1.0000e-02 eta: 14:34:39 time: 0.9867 data_time: 0.5449 memory: 22701 grad_norm: 4.5779 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5267 loss: 1.5267 2022/09/05 16:03:15 - mmengine - INFO - Epoch(train) [33][40/940] lr: 1.0000e-02 eta: 14:34:20 time: 0.7706 data_time: 0.0980 memory: 22701 grad_norm: 4.5705 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4735 loss: 1.4735 2022/09/05 16:03:34 - mmengine - INFO - Epoch(train) [33][60/940] lr: 1.0000e-02 eta: 14:34:09 time: 0.9516 data_time: 0.1035 memory: 22701 grad_norm: 4.7063 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4629 loss: 1.4629 2022/09/05 16:03:48 - mmengine - INFO - Epoch(train) [33][80/940] lr: 1.0000e-02 eta: 14:33:48 time: 0.7012 data_time: 0.0187 memory: 22701 grad_norm: 4.5878 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5489 loss: 1.5489 2022/09/05 16:04:10 - mmengine - INFO - Epoch(train) [33][100/940] lr: 1.0000e-02 eta: 14:33:43 time: 1.1001 data_time: 0.0243 memory: 22701 grad_norm: 4.5553 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4572 loss: 1.4572 2022/09/05 16:04:26 - mmengine - INFO - Epoch(train) [33][120/940] lr: 1.0000e-02 eta: 14:33:26 time: 0.8010 data_time: 0.0221 memory: 22701 grad_norm: 4.6314 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4246 loss: 1.4246 2022/09/05 16:04:45 - mmengine - INFO - Epoch(train) [33][140/940] lr: 1.0000e-02 eta: 14:33:13 time: 0.9167 data_time: 0.0278 memory: 22701 grad_norm: 4.6312 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4706 loss: 1.4706 2022/09/05 16:04:59 - mmengine - INFO - Epoch(train) [33][160/940] lr: 1.0000e-02 eta: 14:32:52 time: 0.7107 data_time: 0.0294 memory: 22701 grad_norm: 4.6006 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6174 loss: 1.6174 2022/09/05 16:05:16 - mmengine - INFO - Epoch(train) [33][180/940] lr: 1.0000e-02 eta: 14:32:38 time: 0.8825 data_time: 0.0314 memory: 22701 grad_norm: 4.5485 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4941 loss: 1.4941 2022/09/05 16:05:30 - mmengine - INFO - Epoch(train) [33][200/940] lr: 1.0000e-02 eta: 14:32:15 time: 0.6572 data_time: 0.1192 memory: 22701 grad_norm: 4.6029 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5758 loss: 1.5758 2022/09/05 16:05:47 - mmengine - INFO - Epoch(train) [33][220/940] lr: 1.0000e-02 eta: 14:32:01 time: 0.8885 data_time: 0.2416 memory: 22701 grad_norm: 4.6311 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5384 loss: 1.5384 2022/09/05 16:06:02 - mmengine - INFO - Epoch(train) [33][240/940] lr: 1.0000e-02 eta: 14:31:40 time: 0.7113 data_time: 0.0384 memory: 22701 grad_norm: 4.5953 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5033 loss: 1.5033 2022/09/05 16:06:19 - mmengine - INFO - Epoch(train) [33][260/940] lr: 1.0000e-02 eta: 14:31:25 time: 0.8502 data_time: 0.0589 memory: 22701 grad_norm: 4.6270 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4795 loss: 1.4795 2022/09/05 16:06:34 - mmengine - INFO - Epoch(train) [33][280/940] lr: 1.0000e-02 eta: 14:31:07 time: 0.7895 data_time: 0.0523 memory: 22701 grad_norm: 4.7377 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4369 loss: 1.4369 2022/09/05 16:06:51 - mmengine - INFO - Epoch(train) [33][300/940] lr: 1.0000e-02 eta: 14:30:52 time: 0.8504 data_time: 0.0291 memory: 22701 grad_norm: 4.6496 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5579 loss: 1.5579 2022/09/05 16:07:04 - mmengine - INFO - Epoch(train) [33][320/940] lr: 1.0000e-02 eta: 14:30:28 time: 0.6340 data_time: 0.0256 memory: 22701 grad_norm: 4.6801 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4766 loss: 1.4766 2022/09/05 16:07:20 - mmengine - INFO - Epoch(train) [33][340/940] lr: 1.0000e-02 eta: 14:30:10 time: 0.7876 data_time: 0.0923 memory: 22701 grad_norm: 4.5823 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5610 loss: 1.5610 2022/09/05 16:07:34 - mmengine - INFO - Epoch(train) [33][360/940] lr: 1.0000e-02 eta: 14:29:49 time: 0.7080 data_time: 0.1203 memory: 22701 grad_norm: 4.6541 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5188 loss: 1.5188 2022/09/05 16:07:50 - mmengine - INFO - Epoch(train) [33][380/940] lr: 1.0000e-02 eta: 14:29:31 time: 0.7824 data_time: 0.2483 memory: 22701 grad_norm: 4.6328 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6367 loss: 1.6367 2022/09/05 16:08:04 - mmengine - INFO - Epoch(train) [33][400/940] lr: 1.0000e-02 eta: 14:29:10 time: 0.7086 data_time: 0.2590 memory: 22701 grad_norm: 4.6008 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5353 loss: 1.5353 2022/09/05 16:08:20 - mmengine - INFO - Epoch(train) [33][420/940] lr: 1.0000e-02 eta: 14:28:54 time: 0.8274 data_time: 0.4518 memory: 22701 grad_norm: 4.7010 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6526 loss: 1.6526 2022/09/05 16:08:34 - mmengine - INFO - Epoch(train) [33][440/940] lr: 1.0000e-02 eta: 14:28:32 time: 0.7047 data_time: 0.3239 memory: 22701 grad_norm: 4.6209 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5009 loss: 1.5009 2022/09/05 16:08:53 - mmengine - INFO - Epoch(train) [33][460/940] lr: 1.0000e-02 eta: 14:28:21 time: 0.9332 data_time: 0.5599 memory: 22701 grad_norm: 4.6716 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5795 loss: 1.5795 2022/09/05 16:09:08 - mmengine - INFO - Epoch(train) [33][480/940] lr: 1.0000e-02 eta: 14:28:02 time: 0.7594 data_time: 0.3415 memory: 22701 grad_norm: 4.6538 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.5773 loss: 1.5773 2022/09/05 16:09:27 - mmengine - INFO - Epoch(train) [33][500/940] lr: 1.0000e-02 eta: 14:27:49 time: 0.9160 data_time: 0.3642 memory: 22701 grad_norm: 4.5936 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3699 loss: 1.3699 2022/09/05 16:09:43 - mmengine - INFO - Epoch(train) [33][520/940] lr: 1.0000e-02 eta: 14:27:33 time: 0.8292 data_time: 0.2256 memory: 22701 grad_norm: 4.6515 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.6241 loss: 1.6241 2022/09/05 16:09:58 - mmengine - INFO - Epoch(train) [33][540/940] lr: 1.0000e-02 eta: 14:27:13 time: 0.7321 data_time: 0.2839 memory: 22701 grad_norm: 4.6813 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.6219 loss: 1.6219 2022/09/05 16:10:16 - mmengine - INFO - Epoch(train) [33][560/940] lr: 1.0000e-02 eta: 14:27:00 time: 0.8923 data_time: 0.4666 memory: 22701 grad_norm: 4.6648 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6253 loss: 1.6253 2022/09/05 16:10:31 - mmengine - INFO - Epoch(train) [33][580/940] lr: 1.0000e-02 eta: 14:26:42 time: 0.7832 data_time: 0.3494 memory: 22701 grad_norm: 4.6853 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5736 loss: 1.5736 2022/09/05 16:10:49 - mmengine - INFO - Epoch(train) [33][600/940] lr: 1.0000e-02 eta: 14:26:27 time: 0.8638 data_time: 0.4498 memory: 22701 grad_norm: 4.7066 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5479 loss: 1.5479 2022/09/05 16:11:03 - mmengine - INFO - Epoch(train) [33][620/940] lr: 1.0000e-02 eta: 14:26:05 time: 0.6990 data_time: 0.2844 memory: 22701 grad_norm: 4.6214 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6469 loss: 1.6469 2022/09/05 16:11:20 - mmengine - INFO - Epoch(train) [33][640/940] lr: 1.0000e-02 eta: 14:25:50 time: 0.8432 data_time: 0.4533 memory: 22701 grad_norm: 4.6187 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4188 loss: 1.4188 2022/09/05 16:11:33 - mmengine - INFO - Epoch(train) [33][660/940] lr: 1.0000e-02 eta: 14:25:27 time: 0.6731 data_time: 0.2710 memory: 22701 grad_norm: 4.6726 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5677 loss: 1.5677 2022/09/05 16:11:50 - mmengine - INFO - Epoch(train) [33][680/940] lr: 1.0000e-02 eta: 14:25:12 time: 0.8509 data_time: 0.4601 memory: 22701 grad_norm: 4.7787 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5150 loss: 1.5150 2022/09/05 16:12:05 - mmengine - INFO - Epoch(train) [33][700/940] lr: 1.0000e-02 eta: 14:24:54 time: 0.7654 data_time: 0.3693 memory: 22701 grad_norm: 4.7878 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6444 loss: 1.6444 2022/09/05 16:12:24 - mmengine - INFO - Epoch(train) [33][720/940] lr: 1.0000e-02 eta: 14:24:41 time: 0.9176 data_time: 0.5228 memory: 22701 grad_norm: 4.6658 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.5600 loss: 1.5600 2022/09/05 16:12:39 - mmengine - INFO - Epoch(train) [33][740/940] lr: 1.0000e-02 eta: 14:24:22 time: 0.7604 data_time: 0.3766 memory: 22701 grad_norm: 4.7118 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6073 loss: 1.6073 2022/09/05 16:12:55 - mmengine - INFO - Epoch(train) [33][760/940] lr: 1.0000e-02 eta: 14:24:04 time: 0.7884 data_time: 0.3965 memory: 22701 grad_norm: 4.5503 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5118 loss: 1.5118 2022/09/05 16:13:09 - mmengine - INFO - Epoch(train) [33][780/940] lr: 1.0000e-02 eta: 14:23:44 time: 0.7130 data_time: 0.3013 memory: 22701 grad_norm: 4.6831 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5235 loss: 1.5235 2022/09/05 16:13:25 - mmengine - INFO - Epoch(train) [33][800/940] lr: 1.0000e-02 eta: 14:23:26 time: 0.7980 data_time: 0.3631 memory: 22701 grad_norm: 4.7086 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4730 loss: 1.4730 2022/09/05 16:13:39 - mmengine - INFO - Epoch(train) [33][820/940] lr: 1.0000e-02 eta: 14:23:05 time: 0.6976 data_time: 0.3063 memory: 22701 grad_norm: 4.6843 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.5623 loss: 1.5623 2022/09/05 16:13:56 - mmengine - INFO - Epoch(train) [33][840/940] lr: 1.0000e-02 eta: 14:22:50 time: 0.8701 data_time: 0.4506 memory: 22701 grad_norm: 4.6841 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5336 loss: 1.5336 2022/09/05 16:14:11 - mmengine - INFO - Epoch(train) [33][860/940] lr: 1.0000e-02 eta: 14:22:30 time: 0.7218 data_time: 0.2967 memory: 22701 grad_norm: 4.6693 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4510 loss: 1.4510 2022/09/05 16:14:30 - mmengine - INFO - Epoch(train) [33][880/940] lr: 1.0000e-02 eta: 14:22:20 time: 0.9758 data_time: 0.5835 memory: 22701 grad_norm: 4.6398 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.5789 loss: 1.5789 2022/09/05 16:14:47 - mmengine - INFO - Epoch(train) [33][900/940] lr: 1.0000e-02 eta: 14:22:03 time: 0.8170 data_time: 0.4014 memory: 22701 grad_norm: 4.7059 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5806 loss: 1.5806 2022/09/05 16:15:05 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:15:05 - mmengine - INFO - Epoch(train) [33][920/940] lr: 1.0000e-02 eta: 14:21:52 time: 0.9453 data_time: 0.5185 memory: 22701 grad_norm: 4.7122 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5575 loss: 1.5575 2022/09/05 16:15:20 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:15:20 - mmengine - INFO - Epoch(train) [33][940/940] lr: 1.0000e-02 eta: 14:21:31 time: 0.7172 data_time: 0.3519 memory: 22701 grad_norm: 5.1298 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.6797 loss: 1.6797 2022/09/05 16:15:20 - mmengine - INFO - Saving checkpoint at 33 epochs 2022/09/05 16:15:37 - mmengine - INFO - Epoch(val) [33][20/78] eta: 0:00:40 time: 0.7003 data_time: 0.5784 memory: 2247 2022/09/05 16:15:46 - mmengine - INFO - Epoch(val) [33][40/78] eta: 0:00:17 time: 0.4684 data_time: 0.3490 memory: 2247 2022/09/05 16:15:59 - mmengine - INFO - Epoch(val) [33][60/78] eta: 0:00:11 time: 0.6462 data_time: 0.5285 memory: 2247 2022/09/05 16:16:09 - mmengine - INFO - Epoch(val) [33][78/78] acc/top1: 0.6393 acc/top5: 0.8556 acc/mean1: 0.6393 2022/09/05 16:16:31 - mmengine - INFO - Epoch(train) [34][20/940] lr: 1.0000e-02 eta: 14:21:26 time: 1.1031 data_time: 0.6211 memory: 22701 grad_norm: 4.5967 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5931 loss: 1.5931 2022/09/05 16:16:44 - mmengine - INFO - Epoch(train) [34][40/940] lr: 1.0000e-02 eta: 14:21:04 time: 0.6794 data_time: 0.1516 memory: 22701 grad_norm: 4.6708 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4692 loss: 1.4692 2022/09/05 16:17:05 - mmengine - INFO - Epoch(train) [34][60/940] lr: 1.0000e-02 eta: 14:20:57 time: 1.0523 data_time: 0.4031 memory: 22701 grad_norm: 4.5696 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4942 loss: 1.4942 2022/09/05 16:17:20 - mmengine - INFO - Epoch(train) [34][80/940] lr: 1.0000e-02 eta: 14:20:37 time: 0.7248 data_time: 0.0222 memory: 22701 grad_norm: 4.6542 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3705 loss: 1.3705 2022/09/05 16:17:37 - mmengine - INFO - Epoch(train) [34][100/940] lr: 1.0000e-02 eta: 14:20:23 time: 0.8740 data_time: 0.0261 memory: 22701 grad_norm: 4.5688 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.3683 loss: 1.3683 2022/09/05 16:17:50 - mmengine - INFO - Epoch(train) [34][120/940] lr: 1.0000e-02 eta: 14:19:59 time: 0.6472 data_time: 0.0309 memory: 22701 grad_norm: 4.5977 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5355 loss: 1.5355 2022/09/05 16:18:07 - mmengine - INFO - Epoch(train) [34][140/940] lr: 1.0000e-02 eta: 14:19:43 time: 0.8224 data_time: 0.0295 memory: 22701 grad_norm: 4.6596 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4829 loss: 1.4829 2022/09/05 16:18:20 - mmengine - INFO - Epoch(train) [34][160/940] lr: 1.0000e-02 eta: 14:19:20 time: 0.6704 data_time: 0.0273 memory: 22701 grad_norm: 4.6382 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5214 loss: 1.5214 2022/09/05 16:18:41 - mmengine - INFO - Epoch(train) [34][180/940] lr: 1.0000e-02 eta: 14:19:13 time: 1.0463 data_time: 0.0239 memory: 22701 grad_norm: 4.5819 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.5343 loss: 1.5343 2022/09/05 16:18:54 - mmengine - INFO - Epoch(train) [34][200/940] lr: 1.0000e-02 eta: 14:18:50 time: 0.6520 data_time: 0.0343 memory: 22701 grad_norm: 4.6736 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6178 loss: 1.6178 2022/09/05 16:19:09 - mmengine - INFO - Epoch(train) [34][220/940] lr: 1.0000e-02 eta: 14:18:31 time: 0.7675 data_time: 0.1059 memory: 22701 grad_norm: 4.6192 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4923 loss: 1.4923 2022/09/05 16:19:23 - mmengine - INFO - Epoch(train) [34][240/940] lr: 1.0000e-02 eta: 14:18:09 time: 0.6678 data_time: 0.1133 memory: 22701 grad_norm: 4.6715 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.5009 loss: 1.5009 2022/09/05 16:19:39 - mmengine - INFO - Epoch(train) [34][260/940] lr: 1.0000e-02 eta: 14:17:51 time: 0.8014 data_time: 0.2274 memory: 22701 grad_norm: 4.6305 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4613 loss: 1.4613 2022/09/05 16:19:52 - mmengine - INFO - Epoch(train) [34][280/940] lr: 1.0000e-02 eta: 14:17:28 time: 0.6468 data_time: 0.2118 memory: 22701 grad_norm: 4.7149 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5136 loss: 1.5136 2022/09/05 16:20:08 - mmengine - INFO - Epoch(train) [34][300/940] lr: 1.0000e-02 eta: 14:17:11 time: 0.7965 data_time: 0.1462 memory: 22701 grad_norm: 4.7115 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6765 loss: 1.6765 2022/09/05 16:20:21 - mmengine - INFO - Epoch(train) [34][320/940] lr: 1.0000e-02 eta: 14:16:48 time: 0.6693 data_time: 0.0322 memory: 22701 grad_norm: 4.7290 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5537 loss: 1.5537 2022/09/05 16:20:37 - mmengine - INFO - Epoch(train) [34][340/940] lr: 1.0000e-02 eta: 14:16:30 time: 0.7848 data_time: 0.0266 memory: 22701 grad_norm: 4.5614 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.4514 loss: 1.4514 2022/09/05 16:20:50 - mmengine - INFO - Epoch(train) [34][360/940] lr: 1.0000e-02 eta: 14:16:08 time: 0.6629 data_time: 0.0484 memory: 22701 grad_norm: 4.6447 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4447 loss: 1.4447 2022/09/05 16:21:08 - mmengine - INFO - Epoch(train) [34][380/940] lr: 1.0000e-02 eta: 14:15:54 time: 0.8991 data_time: 0.0430 memory: 22701 grad_norm: 4.5800 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4219 loss: 1.4219 2022/09/05 16:21:23 - mmengine - INFO - Epoch(train) [34][400/940] lr: 1.0000e-02 eta: 14:15:34 time: 0.7274 data_time: 0.0362 memory: 22701 grad_norm: 4.6739 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.6122 loss: 1.6122 2022/09/05 16:21:39 - mmengine - INFO - Epoch(train) [34][420/940] lr: 1.0000e-02 eta: 14:15:19 time: 0.8374 data_time: 0.0264 memory: 22701 grad_norm: 4.6667 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6780 loss: 1.6780 2022/09/05 16:21:53 - mmengine - INFO - Epoch(train) [34][440/940] lr: 1.0000e-02 eta: 14:14:56 time: 0.6759 data_time: 0.1125 memory: 22701 grad_norm: 4.6895 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5042 loss: 1.5042 2022/09/05 16:22:11 - mmengine - INFO - Epoch(train) [34][460/940] lr: 1.0000e-02 eta: 14:14:44 time: 0.9302 data_time: 0.4187 memory: 22701 grad_norm: 4.7609 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5124 loss: 1.5124 2022/09/05 16:22:25 - mmengine - INFO - Epoch(train) [34][480/940] lr: 1.0000e-02 eta: 14:14:23 time: 0.6848 data_time: 0.2778 memory: 22701 grad_norm: 4.6544 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4801 loss: 1.4801 2022/09/05 16:22:42 - mmengine - INFO - Epoch(train) [34][500/940] lr: 1.0000e-02 eta: 14:14:08 time: 0.8645 data_time: 0.3647 memory: 22701 grad_norm: 4.6756 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4274 loss: 1.4274 2022/09/05 16:22:57 - mmengine - INFO - Epoch(train) [34][520/940] lr: 1.0000e-02 eta: 14:13:48 time: 0.7229 data_time: 0.1696 memory: 22701 grad_norm: 4.6606 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.4807 loss: 1.4807 2022/09/05 16:23:13 - mmengine - INFO - Epoch(train) [34][540/940] lr: 1.0000e-02 eta: 14:13:32 time: 0.8244 data_time: 0.1115 memory: 22701 grad_norm: 4.7714 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5318 loss: 1.5318 2022/09/05 16:23:25 - mmengine - INFO - Epoch(train) [34][560/940] lr: 1.0000e-02 eta: 14:13:06 time: 0.5810 data_time: 0.0986 memory: 22701 grad_norm: 4.7033 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7418 loss: 1.7418 2022/09/05 16:23:42 - mmengine - INFO - Epoch(train) [34][580/940] lr: 1.0000e-02 eta: 14:12:51 time: 0.8731 data_time: 0.4034 memory: 22701 grad_norm: 4.6716 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5356 loss: 1.5356 2022/09/05 16:23:58 - mmengine - INFO - Epoch(train) [34][600/940] lr: 1.0000e-02 eta: 14:12:34 time: 0.7835 data_time: 0.3211 memory: 22701 grad_norm: 4.6426 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5741 loss: 1.5741 2022/09/05 16:24:18 - mmengine - INFO - Epoch(train) [34][620/940] lr: 1.0000e-02 eta: 14:12:23 time: 0.9688 data_time: 0.3041 memory: 22701 grad_norm: 4.6854 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5013 loss: 1.5013 2022/09/05 16:24:30 - mmengine - INFO - Epoch(train) [34][640/940] lr: 1.0000e-02 eta: 14:11:59 time: 0.6398 data_time: 0.1309 memory: 22701 grad_norm: 4.7128 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4313 loss: 1.4313 2022/09/05 16:24:46 - mmengine - INFO - Epoch(train) [34][660/940] lr: 1.0000e-02 eta: 14:11:42 time: 0.7955 data_time: 0.1824 memory: 22701 grad_norm: 4.6650 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5636 loss: 1.5636 2022/09/05 16:25:01 - mmengine - INFO - Epoch(train) [34][680/940] lr: 1.0000e-02 eta: 14:11:23 time: 0.7531 data_time: 0.1785 memory: 22701 grad_norm: 4.6457 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6098 loss: 1.6098 2022/09/05 16:25:19 - mmengine - INFO - Epoch(train) [34][700/940] lr: 1.0000e-02 eta: 14:11:10 time: 0.9063 data_time: 0.1417 memory: 22701 grad_norm: 4.7743 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6049 loss: 1.6049 2022/09/05 16:25:36 - mmengine - INFO - Epoch(train) [34][720/940] lr: 1.0000e-02 eta: 14:10:53 time: 0.8050 data_time: 0.0599 memory: 22701 grad_norm: 4.6278 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4779 loss: 1.4779 2022/09/05 16:25:54 - mmengine - INFO - Epoch(train) [34][740/940] lr: 1.0000e-02 eta: 14:10:41 time: 0.9297 data_time: 0.0316 memory: 22701 grad_norm: 4.6554 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6050 loss: 1.6050 2022/09/05 16:26:07 - mmengine - INFO - Epoch(train) [34][760/940] lr: 1.0000e-02 eta: 14:10:18 time: 0.6619 data_time: 0.0205 memory: 22701 grad_norm: 4.7834 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5479 loss: 1.5479 2022/09/05 16:26:28 - mmengine - INFO - Epoch(train) [34][780/940] lr: 1.0000e-02 eta: 14:10:10 time: 1.0276 data_time: 0.0707 memory: 22701 grad_norm: 4.6777 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6202 loss: 1.6202 2022/09/05 16:26:41 - mmengine - INFO - Epoch(train) [34][800/940] lr: 1.0000e-02 eta: 14:09:48 time: 0.6774 data_time: 0.0255 memory: 22701 grad_norm: 4.6994 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4483 loss: 1.4483 2022/09/05 16:26:59 - mmengine - INFO - Epoch(train) [34][820/940] lr: 1.0000e-02 eta: 14:09:34 time: 0.8845 data_time: 0.0276 memory: 22701 grad_norm: 4.6841 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4883 loss: 1.4883 2022/09/05 16:27:14 - mmengine - INFO - Epoch(train) [34][840/940] lr: 1.0000e-02 eta: 14:09:15 time: 0.7400 data_time: 0.0221 memory: 22701 grad_norm: 4.6526 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5913 loss: 1.5913 2022/09/05 16:27:31 - mmengine - INFO - Epoch(train) [34][860/940] lr: 1.0000e-02 eta: 14:09:00 time: 0.8562 data_time: 0.0301 memory: 22701 grad_norm: 4.7369 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5443 loss: 1.5443 2022/09/05 16:27:47 - mmengine - INFO - Epoch(train) [34][880/940] lr: 1.0000e-02 eta: 14:08:42 time: 0.7908 data_time: 0.0229 memory: 22701 grad_norm: 4.6274 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5165 loss: 1.5165 2022/09/05 16:28:04 - mmengine - INFO - Epoch(train) [34][900/940] lr: 1.0000e-02 eta: 14:08:28 time: 0.8743 data_time: 0.0279 memory: 22701 grad_norm: 4.6503 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5586 loss: 1.5586 2022/09/05 16:28:19 - mmengine - INFO - Epoch(train) [34][920/940] lr: 1.0000e-02 eta: 14:08:09 time: 0.7494 data_time: 0.0240 memory: 22701 grad_norm: 4.6545 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5203 loss: 1.5203 2022/09/05 16:28:35 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:28:35 - mmengine - INFO - Epoch(train) [34][940/940] lr: 1.0000e-02 eta: 14:07:51 time: 0.7795 data_time: 0.0206 memory: 22701 grad_norm: 4.9004 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4928 loss: 1.4928 2022/09/05 16:28:49 - mmengine - INFO - Epoch(val) [34][20/78] eta: 0:00:39 time: 0.6782 data_time: 0.5608 memory: 2247 2022/09/05 16:28:58 - mmengine - INFO - Epoch(val) [34][40/78] eta: 0:00:18 time: 0.4770 data_time: 0.3557 memory: 2247 2022/09/05 16:29:11 - mmengine - INFO - Epoch(val) [34][60/78] eta: 0:00:11 time: 0.6334 data_time: 0.5134 memory: 2247 2022/09/05 16:29:21 - mmengine - INFO - Epoch(val) [34][78/78] acc/top1: 0.6395 acc/top5: 0.8538 acc/mean1: 0.6393 2022/09/05 16:29:43 - mmengine - INFO - Epoch(train) [35][20/940] lr: 1.0000e-02 eta: 14:07:44 time: 1.0718 data_time: 0.4662 memory: 22701 grad_norm: 4.5858 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7102 loss: 1.7102 2022/09/05 16:29:56 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:29:56 - mmengine - INFO - Epoch(train) [35][40/940] lr: 1.0000e-02 eta: 14:07:22 time: 0.6602 data_time: 0.0603 memory: 22701 grad_norm: 4.5940 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.5421 loss: 1.5421 2022/09/05 16:30:12 - mmengine - INFO - Epoch(train) [35][60/940] lr: 1.0000e-02 eta: 14:07:05 time: 0.8165 data_time: 0.2503 memory: 22701 grad_norm: 4.6552 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.6761 loss: 1.6761 2022/09/05 16:30:27 - mmengine - INFO - Epoch(train) [35][80/940] lr: 1.0000e-02 eta: 14:06:45 time: 0.7183 data_time: 0.2537 memory: 22701 grad_norm: 4.6682 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4161 loss: 1.4161 2022/09/05 16:30:42 - mmengine - INFO - Epoch(train) [35][100/940] lr: 1.0000e-02 eta: 14:06:26 time: 0.7637 data_time: 0.2199 memory: 22701 grad_norm: 4.6252 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5029 loss: 1.5029 2022/09/05 16:30:55 - mmengine - INFO - Epoch(train) [35][120/940] lr: 1.0000e-02 eta: 14:06:04 time: 0.6749 data_time: 0.2409 memory: 22701 grad_norm: 4.6702 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5321 loss: 1.5321 2022/09/05 16:31:12 - mmengine - INFO - Epoch(train) [35][140/940] lr: 1.0000e-02 eta: 14:05:48 time: 0.8298 data_time: 0.3141 memory: 22701 grad_norm: 4.6181 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.5042 loss: 1.5042 2022/09/05 16:31:26 - mmengine - INFO - Epoch(train) [35][160/940] lr: 1.0000e-02 eta: 14:05:27 time: 0.6988 data_time: 0.2461 memory: 22701 grad_norm: 4.5581 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4234 loss: 1.4234 2022/09/05 16:31:43 - mmengine - INFO - Epoch(train) [35][180/940] lr: 1.0000e-02 eta: 14:05:12 time: 0.8483 data_time: 0.4715 memory: 22701 grad_norm: 4.5916 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4040 loss: 1.4040 2022/09/05 16:31:56 - mmengine - INFO - Epoch(train) [35][200/940] lr: 1.0000e-02 eta: 14:04:48 time: 0.6347 data_time: 0.2371 memory: 22701 grad_norm: 4.6042 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5455 loss: 1.5455 2022/09/05 16:32:14 - mmengine - INFO - Epoch(train) [35][220/940] lr: 1.0000e-02 eta: 14:04:36 time: 0.9210 data_time: 0.4804 memory: 22701 grad_norm: 4.5641 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4888 loss: 1.4888 2022/09/05 16:32:28 - mmengine - INFO - Epoch(train) [35][240/940] lr: 1.0000e-02 eta: 14:04:14 time: 0.6859 data_time: 0.3008 memory: 22701 grad_norm: 4.7253 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.6315 loss: 1.6315 2022/09/05 16:32:45 - mmengine - INFO - Epoch(train) [35][260/940] lr: 1.0000e-02 eta: 14:04:00 time: 0.8798 data_time: 0.4946 memory: 22701 grad_norm: 4.6051 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6186 loss: 1.6186 2022/09/05 16:33:00 - mmengine - INFO - Epoch(train) [35][280/940] lr: 1.0000e-02 eta: 14:03:41 time: 0.7598 data_time: 0.3838 memory: 22701 grad_norm: 4.6917 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4881 loss: 1.4881 2022/09/05 16:33:22 - mmengine - INFO - Epoch(train) [35][300/940] lr: 1.0000e-02 eta: 14:03:34 time: 1.0529 data_time: 0.4022 memory: 22701 grad_norm: 4.7133 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5980 loss: 1.5980 2022/09/05 16:33:41 - mmengine - INFO - Epoch(train) [35][320/940] lr: 1.0000e-02 eta: 14:03:23 time: 0.9611 data_time: 0.3819 memory: 22701 grad_norm: 4.7257 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5701 loss: 1.5701 2022/09/05 16:34:01 - mmengine - INFO - Epoch(train) [35][340/940] lr: 1.0000e-02 eta: 14:03:14 time: 1.0261 data_time: 0.2390 memory: 22701 grad_norm: 4.5839 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4888 loss: 1.4888 2022/09/05 16:34:16 - mmengine - INFO - Epoch(train) [35][360/940] lr: 1.0000e-02 eta: 14:02:54 time: 0.7176 data_time: 0.2499 memory: 22701 grad_norm: 4.6884 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5240 loss: 1.5240 2022/09/05 16:34:32 - mmengine - INFO - Epoch(train) [35][380/940] lr: 1.0000e-02 eta: 14:02:38 time: 0.8364 data_time: 0.2726 memory: 22701 grad_norm: 4.6778 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5078 loss: 1.5078 2022/09/05 16:34:45 - mmengine - INFO - Epoch(train) [35][400/940] lr: 1.0000e-02 eta: 14:02:15 time: 0.6401 data_time: 0.2028 memory: 22701 grad_norm: 4.6210 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5121 loss: 1.5121 2022/09/05 16:35:04 - mmengine - INFO - Epoch(train) [35][420/940] lr: 1.0000e-02 eta: 14:02:03 time: 0.9307 data_time: 0.5401 memory: 22701 grad_norm: 4.7051 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6156 loss: 1.6156 2022/09/05 16:35:18 - mmengine - INFO - Epoch(train) [35][440/940] lr: 1.0000e-02 eta: 14:01:42 time: 0.7109 data_time: 0.2728 memory: 22701 grad_norm: 4.6935 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5762 loss: 1.5762 2022/09/05 16:35:37 - mmengine - INFO - Epoch(train) [35][460/940] lr: 1.0000e-02 eta: 14:01:31 time: 0.9574 data_time: 0.2646 memory: 22701 grad_norm: 4.7505 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5902 loss: 1.5902 2022/09/05 16:35:52 - mmengine - INFO - Epoch(train) [35][480/940] lr: 1.0000e-02 eta: 14:01:12 time: 0.7381 data_time: 0.0721 memory: 22701 grad_norm: 4.6690 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5885 loss: 1.5885 2022/09/05 16:36:10 - mmengine - INFO - Epoch(train) [35][500/940] lr: 1.0000e-02 eta: 14:00:58 time: 0.8890 data_time: 0.1163 memory: 22701 grad_norm: 4.6884 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4507 loss: 1.4507 2022/09/05 16:36:27 - mmengine - INFO - Epoch(train) [35][520/940] lr: 1.0000e-02 eta: 14:00:42 time: 0.8412 data_time: 0.0716 memory: 22701 grad_norm: 4.7706 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6677 loss: 1.6677 2022/09/05 16:36:44 - mmengine - INFO - Epoch(train) [35][540/940] lr: 1.0000e-02 eta: 14:00:27 time: 0.8599 data_time: 0.1741 memory: 22701 grad_norm: 4.6390 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.5567 loss: 1.5567 2022/09/05 16:37:01 - mmengine - INFO - Epoch(train) [35][560/940] lr: 1.0000e-02 eta: 14:00:12 time: 0.8562 data_time: 0.3678 memory: 22701 grad_norm: 4.6147 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5311 loss: 1.5311 2022/09/05 16:37:17 - mmengine - INFO - Epoch(train) [35][580/940] lr: 1.0000e-02 eta: 13:59:55 time: 0.7865 data_time: 0.0987 memory: 22701 grad_norm: 4.6380 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4576 loss: 1.4576 2022/09/05 16:37:31 - mmengine - INFO - Epoch(train) [35][600/940] lr: 1.0000e-02 eta: 13:59:35 time: 0.7311 data_time: 0.0214 memory: 22701 grad_norm: 4.7200 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4702 loss: 1.4702 2022/09/05 16:37:47 - mmengine - INFO - Epoch(train) [35][620/940] lr: 1.0000e-02 eta: 13:59:18 time: 0.8096 data_time: 0.1803 memory: 22701 grad_norm: 4.7062 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4649 loss: 1.4649 2022/09/05 16:38:03 - mmengine - INFO - Epoch(train) [35][640/940] lr: 1.0000e-02 eta: 13:59:00 time: 0.7587 data_time: 0.0774 memory: 22701 grad_norm: 4.6302 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5030 loss: 1.5030 2022/09/05 16:38:20 - mmengine - INFO - Epoch(train) [35][660/940] lr: 1.0000e-02 eta: 13:58:45 time: 0.8641 data_time: 0.0944 memory: 22701 grad_norm: 4.7341 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5462 loss: 1.5462 2022/09/05 16:38:37 - mmengine - INFO - Epoch(train) [35][680/940] lr: 1.0000e-02 eta: 13:58:29 time: 0.8296 data_time: 0.2625 memory: 22701 grad_norm: 4.6885 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5865 loss: 1.5865 2022/09/05 16:38:52 - mmengine - INFO - Epoch(train) [35][700/940] lr: 1.0000e-02 eta: 13:58:11 time: 0.7837 data_time: 0.2843 memory: 22701 grad_norm: 4.6514 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4488 loss: 1.4488 2022/09/05 16:39:10 - mmengine - INFO - Epoch(train) [35][720/940] lr: 1.0000e-02 eta: 13:57:58 time: 0.9095 data_time: 0.1054 memory: 22701 grad_norm: 4.7669 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.8058 loss: 1.8058 2022/09/05 16:39:26 - mmengine - INFO - Epoch(train) [35][740/940] lr: 1.0000e-02 eta: 13:57:40 time: 0.7893 data_time: 0.0292 memory: 22701 grad_norm: 4.6955 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5824 loss: 1.5824 2022/09/05 16:39:42 - mmengine - INFO - Epoch(train) [35][760/940] lr: 1.0000e-02 eta: 13:57:23 time: 0.8041 data_time: 0.0277 memory: 22701 grad_norm: 4.6400 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4709 loss: 1.4709 2022/09/05 16:40:01 - mmengine - INFO - Epoch(train) [35][780/940] lr: 1.0000e-02 eta: 13:57:12 time: 0.9484 data_time: 0.0242 memory: 22701 grad_norm: 4.5988 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.4596 loss: 1.4596 2022/09/05 16:40:23 - mmengine - INFO - Epoch(train) [35][800/940] lr: 1.0000e-02 eta: 13:57:06 time: 1.0943 data_time: 0.0202 memory: 22701 grad_norm: 4.5891 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5633 loss: 1.5633 2022/09/05 16:40:42 - mmengine - INFO - Epoch(train) [35][820/940] lr: 1.0000e-02 eta: 13:56:54 time: 0.9399 data_time: 0.0211 memory: 22701 grad_norm: 4.6877 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5552 loss: 1.5552 2022/09/05 16:40:59 - mmengine - INFO - Epoch(train) [35][840/940] lr: 1.0000e-02 eta: 13:56:39 time: 0.8628 data_time: 0.0259 memory: 22701 grad_norm: 4.6966 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.6261 loss: 1.6261 2022/09/05 16:41:17 - mmengine - INFO - Epoch(train) [35][860/940] lr: 1.0000e-02 eta: 13:56:24 time: 0.8698 data_time: 0.0226 memory: 22701 grad_norm: 4.6104 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3927 loss: 1.3927 2022/09/05 16:41:33 - mmengine - INFO - Epoch(train) [35][880/940] lr: 1.0000e-02 eta: 13:56:08 time: 0.8199 data_time: 0.0238 memory: 22701 grad_norm: 4.6428 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5407 loss: 1.5407 2022/09/05 16:41:49 - mmengine - INFO - Epoch(train) [35][900/940] lr: 1.0000e-02 eta: 13:55:51 time: 0.7964 data_time: 0.0298 memory: 22701 grad_norm: 4.7393 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5452 loss: 1.5452 2022/09/05 16:42:05 - mmengine - INFO - Epoch(train) [35][920/940] lr: 1.0000e-02 eta: 13:55:33 time: 0.7995 data_time: 0.0273 memory: 22701 grad_norm: 4.6527 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5604 loss: 1.5604 2022/09/05 16:42:24 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:42:24 - mmengine - INFO - Epoch(train) [35][940/940] lr: 1.0000e-02 eta: 13:55:21 time: 0.9333 data_time: 0.0179 memory: 22701 grad_norm: 4.8825 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.5303 loss: 1.5303 2022/09/05 16:42:37 - mmengine - INFO - Epoch(val) [35][20/78] eta: 0:00:40 time: 0.6922 data_time: 0.5717 memory: 2247 2022/09/05 16:42:46 - mmengine - INFO - Epoch(val) [35][40/78] eta: 0:00:17 time: 0.4488 data_time: 0.3303 memory: 2247 2022/09/05 16:42:59 - mmengine - INFO - Epoch(val) [35][60/78] eta: 0:00:11 time: 0.6455 data_time: 0.5229 memory: 2247 2022/09/05 16:43:10 - mmengine - INFO - Epoch(val) [35][78/78] acc/top1: 0.6412 acc/top5: 0.8557 acc/mean1: 0.6411 2022/09/05 16:43:32 - mmengine - INFO - Epoch(train) [36][20/940] lr: 1.0000e-02 eta: 13:55:15 time: 1.1035 data_time: 0.6592 memory: 22701 grad_norm: 4.5791 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5041 loss: 1.5041 2022/09/05 16:43:49 - mmengine - INFO - Epoch(train) [36][40/940] lr: 1.0000e-02 eta: 13:55:00 time: 0.8548 data_time: 0.4223 memory: 22701 grad_norm: 4.6666 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.4189 loss: 1.4189 2022/09/05 16:44:11 - mmengine - INFO - Epoch(train) [36][60/940] lr: 1.0000e-02 eta: 13:54:54 time: 1.0886 data_time: 0.6999 memory: 22701 grad_norm: 4.5626 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4791 loss: 1.4791 2022/09/05 16:44:27 - mmengine - INFO - Epoch(train) [36][80/940] lr: 1.0000e-02 eta: 13:54:37 time: 0.8017 data_time: 0.3567 memory: 22701 grad_norm: 4.5492 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4567 loss: 1.4567 2022/09/05 16:44:48 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:44:48 - mmengine - INFO - Epoch(train) [36][100/940] lr: 1.0000e-02 eta: 13:54:29 time: 1.0705 data_time: 0.6494 memory: 22701 grad_norm: 4.6710 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.4756 loss: 1.4756 2022/09/05 16:45:11 - mmengine - INFO - Epoch(train) [36][120/940] lr: 1.0000e-02 eta: 13:54:24 time: 1.1137 data_time: 0.6302 memory: 22701 grad_norm: 4.6565 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4387 loss: 1.4387 2022/09/05 16:45:29 - mmengine - INFO - Epoch(train) [36][140/940] lr: 1.0000e-02 eta: 13:54:11 time: 0.9106 data_time: 0.5284 memory: 22701 grad_norm: 4.6143 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5955 loss: 1.5955 2022/09/05 16:45:46 - mmengine - INFO - Epoch(train) [36][160/940] lr: 1.0000e-02 eta: 13:53:55 time: 0.8463 data_time: 0.4468 memory: 22701 grad_norm: 4.6319 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5624 loss: 1.5624 2022/09/05 16:46:04 - mmengine - INFO - Epoch(train) [36][180/940] lr: 1.0000e-02 eta: 13:53:42 time: 0.9030 data_time: 0.5230 memory: 22701 grad_norm: 4.6889 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4338 loss: 1.4338 2022/09/05 16:46:18 - mmengine - INFO - Epoch(train) [36][200/940] lr: 1.0000e-02 eta: 13:53:21 time: 0.6982 data_time: 0.2926 memory: 22701 grad_norm: 4.5980 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4993 loss: 1.4993 2022/09/05 16:46:32 - mmengine - INFO - Epoch(train) [36][220/940] lr: 1.0000e-02 eta: 13:53:00 time: 0.7093 data_time: 0.3093 memory: 22701 grad_norm: 4.4920 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.5235 loss: 1.5235 2022/09/05 16:46:45 - mmengine - INFO - Epoch(train) [36][240/940] lr: 1.0000e-02 eta: 13:52:38 time: 0.6655 data_time: 0.2843 memory: 22701 grad_norm: 4.6461 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5295 loss: 1.5295 2022/09/05 16:47:03 - mmengine - INFO - Epoch(train) [36][260/940] lr: 1.0000e-02 eta: 13:52:25 time: 0.8989 data_time: 0.4348 memory: 22701 grad_norm: 4.6319 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5172 loss: 1.5172 2022/09/05 16:47:21 - mmengine - INFO - Epoch(train) [36][280/940] lr: 1.0000e-02 eta: 13:52:11 time: 0.8878 data_time: 0.4602 memory: 22701 grad_norm: 4.7521 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3745 loss: 1.3745 2022/09/05 16:47:46 - mmengine - INFO - Epoch(train) [36][300/940] lr: 1.0000e-02 eta: 13:52:10 time: 1.2429 data_time: 0.2061 memory: 22701 grad_norm: 4.6970 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.4952 loss: 1.4952 2022/09/05 16:48:02 - mmengine - INFO - Epoch(train) [36][320/940] lr: 1.0000e-02 eta: 13:51:52 time: 0.7947 data_time: 0.0241 memory: 22701 grad_norm: 4.6066 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4084 loss: 1.4084 2022/09/05 16:48:18 - mmengine - INFO - Epoch(train) [36][340/940] lr: 1.0000e-02 eta: 13:51:36 time: 0.8333 data_time: 0.0423 memory: 22701 grad_norm: 4.6112 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5084 loss: 1.5084 2022/09/05 16:48:34 - mmengine - INFO - Epoch(train) [36][360/940] lr: 1.0000e-02 eta: 13:51:18 time: 0.7799 data_time: 0.0244 memory: 22701 grad_norm: 4.6079 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.6040 loss: 1.6040 2022/09/05 16:48:50 - mmengine - INFO - Epoch(train) [36][380/940] lr: 1.0000e-02 eta: 13:51:01 time: 0.8059 data_time: 0.0767 memory: 22701 grad_norm: 4.6612 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4333 loss: 1.4333 2022/09/05 16:49:04 - mmengine - INFO - Epoch(train) [36][400/940] lr: 1.0000e-02 eta: 13:50:40 time: 0.6904 data_time: 0.1991 memory: 22701 grad_norm: 4.6864 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5200 loss: 1.5200 2022/09/05 16:49:21 - mmengine - INFO - Epoch(train) [36][420/940] lr: 1.0000e-02 eta: 13:50:25 time: 0.8442 data_time: 0.2757 memory: 22701 grad_norm: 4.7009 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4328 loss: 1.4328 2022/09/05 16:49:38 - mmengine - INFO - Epoch(train) [36][440/940] lr: 1.0000e-02 eta: 13:50:09 time: 0.8438 data_time: 0.1542 memory: 22701 grad_norm: 4.7392 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5145 loss: 1.5145 2022/09/05 16:49:53 - mmengine - INFO - Epoch(train) [36][460/940] lr: 1.0000e-02 eta: 13:49:50 time: 0.7473 data_time: 0.1341 memory: 22701 grad_norm: 4.7334 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5082 loss: 1.5082 2022/09/05 16:50:11 - mmengine - INFO - Epoch(train) [36][480/940] lr: 1.0000e-02 eta: 13:49:36 time: 0.8995 data_time: 0.0227 memory: 22701 grad_norm: 4.6337 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6276 loss: 1.6276 2022/09/05 16:50:26 - mmengine - INFO - Epoch(train) [36][500/940] lr: 1.0000e-02 eta: 13:49:18 time: 0.7694 data_time: 0.0308 memory: 22701 grad_norm: 4.5967 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4066 loss: 1.4066 2022/09/05 16:50:42 - mmengine - INFO - Epoch(train) [36][520/940] lr: 1.0000e-02 eta: 13:49:01 time: 0.8009 data_time: 0.0309 memory: 22701 grad_norm: 4.6069 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6114 loss: 1.6114 2022/09/05 16:50:59 - mmengine - INFO - Epoch(train) [36][540/940] lr: 1.0000e-02 eta: 13:48:44 time: 0.8185 data_time: 0.0241 memory: 22701 grad_norm: 4.6807 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7338 loss: 1.7338 2022/09/05 16:51:15 - mmengine - INFO - Epoch(train) [36][560/940] lr: 1.0000e-02 eta: 13:48:27 time: 0.8059 data_time: 0.0580 memory: 22701 grad_norm: 4.6012 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6124 loss: 1.6124 2022/09/05 16:51:30 - mmengine - INFO - Epoch(train) [36][580/940] lr: 1.0000e-02 eta: 13:48:09 time: 0.7690 data_time: 0.0991 memory: 22701 grad_norm: 4.6650 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4584 loss: 1.4584 2022/09/05 16:51:45 - mmengine - INFO - Epoch(train) [36][600/940] lr: 1.0000e-02 eta: 13:47:50 time: 0.7321 data_time: 0.0240 memory: 22701 grad_norm: 4.7071 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5456 loss: 1.5456 2022/09/05 16:52:00 - mmengine - INFO - Epoch(train) [36][620/940] lr: 1.0000e-02 eta: 13:47:31 time: 0.7580 data_time: 0.0676 memory: 22701 grad_norm: 4.6911 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5309 loss: 1.5309 2022/09/05 16:52:17 - mmengine - INFO - Epoch(train) [36][640/940] lr: 1.0000e-02 eta: 13:47:15 time: 0.8388 data_time: 0.1834 memory: 22701 grad_norm: 4.7591 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5315 loss: 1.5315 2022/09/05 16:52:31 - mmengine - INFO - Epoch(train) [36][660/940] lr: 1.0000e-02 eta: 13:46:56 time: 0.7386 data_time: 0.0318 memory: 22701 grad_norm: 4.7708 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5709 loss: 1.5709 2022/09/05 16:52:48 - mmengine - INFO - Epoch(train) [36][680/940] lr: 1.0000e-02 eta: 13:46:40 time: 0.8341 data_time: 0.0249 memory: 22701 grad_norm: 4.7337 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4105 loss: 1.4105 2022/09/05 16:53:02 - mmengine - INFO - Epoch(train) [36][700/940] lr: 1.0000e-02 eta: 13:46:19 time: 0.6890 data_time: 0.0318 memory: 22701 grad_norm: 4.7036 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5682 loss: 1.5682 2022/09/05 16:53:18 - mmengine - INFO - Epoch(train) [36][720/940] lr: 1.0000e-02 eta: 13:46:01 time: 0.7911 data_time: 0.0247 memory: 22701 grad_norm: 4.6272 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5317 loss: 1.5317 2022/09/05 16:53:32 - mmengine - INFO - Epoch(train) [36][740/940] lr: 1.0000e-02 eta: 13:45:41 time: 0.7122 data_time: 0.0972 memory: 22701 grad_norm: 4.6627 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5500 loss: 1.5500 2022/09/05 16:53:48 - mmengine - INFO - Epoch(train) [36][760/940] lr: 1.0000e-02 eta: 13:45:24 time: 0.7990 data_time: 0.0639 memory: 22701 grad_norm: 4.6612 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5998 loss: 1.5998 2022/09/05 16:54:02 - mmengine - INFO - Epoch(train) [36][780/940] lr: 1.0000e-02 eta: 13:45:04 time: 0.7247 data_time: 0.1785 memory: 22701 grad_norm: 4.7749 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5820 loss: 1.5820 2022/09/05 16:54:18 - mmengine - INFO - Epoch(train) [36][800/940] lr: 1.0000e-02 eta: 13:44:45 time: 0.7639 data_time: 0.1664 memory: 22701 grad_norm: 4.7223 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6030 loss: 1.6030 2022/09/05 16:54:34 - mmengine - INFO - Epoch(train) [36][820/940] lr: 1.0000e-02 eta: 13:44:28 time: 0.7975 data_time: 0.2195 memory: 22701 grad_norm: 4.6753 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5746 loss: 1.5746 2022/09/05 16:54:48 - mmengine - INFO - Epoch(train) [36][840/940] lr: 1.0000e-02 eta: 13:44:09 time: 0.7412 data_time: 0.2964 memory: 22701 grad_norm: 4.7112 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3774 loss: 1.3774 2022/09/05 16:55:06 - mmengine - INFO - Epoch(train) [36][860/940] lr: 1.0000e-02 eta: 13:43:55 time: 0.8831 data_time: 0.3109 memory: 22701 grad_norm: 4.6037 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4270 loss: 1.4270 2022/09/05 16:55:23 - mmengine - INFO - Epoch(train) [36][880/940] lr: 1.0000e-02 eta: 13:43:39 time: 0.8322 data_time: 0.0784 memory: 22701 grad_norm: 4.6963 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4840 loss: 1.4840 2022/09/05 16:55:40 - mmengine - INFO - Epoch(train) [36][900/940] lr: 1.0000e-02 eta: 13:43:24 time: 0.8672 data_time: 0.0790 memory: 22701 grad_norm: 4.6785 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5316 loss: 1.5316 2022/09/05 16:55:56 - mmengine - INFO - Epoch(train) [36][920/940] lr: 1.0000e-02 eta: 13:43:06 time: 0.7738 data_time: 0.1472 memory: 22701 grad_norm: 4.6699 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.5883 loss: 1.5883 2022/09/05 16:56:11 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:56:11 - mmengine - INFO - Epoch(train) [36][940/940] lr: 1.0000e-02 eta: 13:42:47 time: 0.7667 data_time: 0.1970 memory: 22701 grad_norm: 4.9246 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3498 loss: 1.3498 2022/09/05 16:56:11 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/09/05 16:56:27 - mmengine - INFO - Epoch(val) [36][20/78] eta: 0:00:40 time: 0.7010 data_time: 0.5848 memory: 2247 2022/09/05 16:56:36 - mmengine - INFO - Epoch(val) [36][40/78] eta: 0:00:17 time: 0.4499 data_time: 0.3327 memory: 2247 2022/09/05 16:56:49 - mmengine - INFO - Epoch(val) [36][60/78] eta: 0:00:11 time: 0.6487 data_time: 0.5318 memory: 2247 2022/09/05 16:56:59 - mmengine - INFO - Epoch(val) [36][78/78] acc/top1: 0.6376 acc/top5: 0.8521 acc/mean1: 0.6374 2022/09/05 16:57:19 - mmengine - INFO - Epoch(train) [37][20/940] lr: 1.0000e-02 eta: 13:42:38 time: 1.0227 data_time: 0.4704 memory: 22701 grad_norm: 4.6303 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.5301 loss: 1.5301 2022/09/05 16:57:34 - mmengine - INFO - Epoch(train) [37][40/940] lr: 1.0000e-02 eta: 13:42:19 time: 0.7475 data_time: 0.1557 memory: 22701 grad_norm: 4.6663 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4139 loss: 1.4139 2022/09/05 16:57:52 - mmengine - INFO - Epoch(train) [37][60/940] lr: 1.0000e-02 eta: 13:42:06 time: 0.9035 data_time: 0.3403 memory: 22701 grad_norm: 4.6952 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4465 loss: 1.4465 2022/09/05 16:58:07 - mmengine - INFO - Epoch(train) [37][80/940] lr: 1.0000e-02 eta: 13:41:47 time: 0.7562 data_time: 0.3761 memory: 22701 grad_norm: 4.6104 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.3377 loss: 1.3377 2022/09/05 16:58:26 - mmengine - INFO - Epoch(train) [37][100/940] lr: 1.0000e-02 eta: 13:41:34 time: 0.9226 data_time: 0.5242 memory: 22701 grad_norm: 4.5621 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4677 loss: 1.4677 2022/09/05 16:58:41 - mmengine - INFO - Epoch(train) [37][120/940] lr: 1.0000e-02 eta: 13:41:16 time: 0.7658 data_time: 0.2814 memory: 22701 grad_norm: 4.6485 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4211 loss: 1.4211 2022/09/05 16:59:00 - mmengine - INFO - Epoch(train) [37][140/940] lr: 1.0000e-02 eta: 13:41:04 time: 0.9424 data_time: 0.2604 memory: 22701 grad_norm: 4.6269 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4844 loss: 1.4844 2022/09/05 16:59:14 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 16:59:14 - mmengine - INFO - Epoch(train) [37][160/940] lr: 1.0000e-02 eta: 13:40:43 time: 0.6890 data_time: 0.2294 memory: 22701 grad_norm: 4.5220 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.4412 loss: 1.4412 2022/09/05 16:59:31 - mmengine - INFO - Epoch(train) [37][180/940] lr: 1.0000e-02 eta: 13:40:29 time: 0.8931 data_time: 0.4356 memory: 22701 grad_norm: 4.4854 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6481 loss: 1.6481 2022/09/05 16:59:46 - mmengine - INFO - Epoch(train) [37][200/940] lr: 1.0000e-02 eta: 13:40:09 time: 0.7328 data_time: 0.2889 memory: 22701 grad_norm: 4.6613 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5678 loss: 1.5678 2022/09/05 17:00:03 - mmengine - INFO - Epoch(train) [37][220/940] lr: 1.0000e-02 eta: 13:39:54 time: 0.8467 data_time: 0.4388 memory: 22701 grad_norm: 4.7119 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5677 loss: 1.5677 2022/09/05 17:00:17 - mmengine - INFO - Epoch(train) [37][240/940] lr: 1.0000e-02 eta: 13:39:33 time: 0.7043 data_time: 0.2920 memory: 22701 grad_norm: 4.5851 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4171 loss: 1.4171 2022/09/05 17:00:34 - mmengine - INFO - Epoch(train) [37][260/940] lr: 1.0000e-02 eta: 13:39:18 time: 0.8534 data_time: 0.4501 memory: 22701 grad_norm: 4.7446 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4498 loss: 1.4498 2022/09/05 17:00:48 - mmengine - INFO - Epoch(train) [37][280/940] lr: 1.0000e-02 eta: 13:38:57 time: 0.6984 data_time: 0.2732 memory: 22701 grad_norm: 4.5510 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4922 loss: 1.4922 2022/09/05 17:01:06 - mmengine - INFO - Epoch(train) [37][300/940] lr: 1.0000e-02 eta: 13:38:44 time: 0.8949 data_time: 0.4725 memory: 22701 grad_norm: 4.6602 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4238 loss: 1.4238 2022/09/05 17:01:23 - mmengine - INFO - Epoch(train) [37][320/940] lr: 1.0000e-02 eta: 13:38:28 time: 0.8540 data_time: 0.3428 memory: 22701 grad_norm: 4.7156 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5281 loss: 1.5281 2022/09/05 17:01:41 - mmengine - INFO - Epoch(train) [37][340/940] lr: 1.0000e-02 eta: 13:38:14 time: 0.8806 data_time: 0.1202 memory: 22701 grad_norm: 4.7237 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4625 loss: 1.4625 2022/09/05 17:01:57 - mmengine - INFO - Epoch(train) [37][360/940] lr: 1.0000e-02 eta: 13:37:57 time: 0.8049 data_time: 0.0530 memory: 22701 grad_norm: 4.7124 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5903 loss: 1.5903 2022/09/05 17:02:19 - mmengine - INFO - Epoch(train) [37][380/940] lr: 1.0000e-02 eta: 13:37:51 time: 1.1085 data_time: 0.0251 memory: 22701 grad_norm: 4.7489 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.4820 loss: 1.4820 2022/09/05 17:02:35 - mmengine - INFO - Epoch(train) [37][400/940] lr: 1.0000e-02 eta: 13:37:34 time: 0.8042 data_time: 0.0293 memory: 22701 grad_norm: 4.6769 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5287 loss: 1.5287 2022/09/05 17:02:53 - mmengine - INFO - Epoch(train) [37][420/940] lr: 1.0000e-02 eta: 13:37:20 time: 0.9132 data_time: 0.0243 memory: 22701 grad_norm: 4.6485 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5239 loss: 1.5239 2022/09/05 17:03:11 - mmengine - INFO - Epoch(train) [37][440/940] lr: 1.0000e-02 eta: 13:37:06 time: 0.8781 data_time: 0.0337 memory: 22701 grad_norm: 4.7285 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5272 loss: 1.5272 2022/09/05 17:03:26 - mmengine - INFO - Epoch(train) [37][460/940] lr: 1.0000e-02 eta: 13:36:48 time: 0.7672 data_time: 0.0279 memory: 22701 grad_norm: 4.5946 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4522 loss: 1.4522 2022/09/05 17:03:42 - mmengine - INFO - Epoch(train) [37][480/940] lr: 1.0000e-02 eta: 13:36:31 time: 0.8033 data_time: 0.0325 memory: 22701 grad_norm: 4.6619 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4961 loss: 1.4961 2022/09/05 17:03:56 - mmengine - INFO - Epoch(train) [37][500/940] lr: 1.0000e-02 eta: 13:36:10 time: 0.7043 data_time: 0.0444 memory: 22701 grad_norm: 4.6970 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4839 loss: 1.4839 2022/09/05 17:04:15 - mmengine - INFO - Epoch(train) [37][520/940] lr: 1.0000e-02 eta: 13:35:57 time: 0.9097 data_time: 0.0556 memory: 22701 grad_norm: 4.6418 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5088 loss: 1.5088 2022/09/05 17:04:30 - mmengine - INFO - Epoch(train) [37][540/940] lr: 1.0000e-02 eta: 13:35:38 time: 0.7454 data_time: 0.0175 memory: 22701 grad_norm: 4.7324 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4379 loss: 1.4379 2022/09/05 17:04:46 - mmengine - INFO - Epoch(train) [37][560/940] lr: 1.0000e-02 eta: 13:35:22 time: 0.8324 data_time: 0.0330 memory: 22701 grad_norm: 4.7635 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6887 loss: 1.6887 2022/09/05 17:05:00 - mmengine - INFO - Epoch(train) [37][580/940] lr: 1.0000e-02 eta: 13:35:02 time: 0.7087 data_time: 0.1172 memory: 22701 grad_norm: 4.5947 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4196 loss: 1.4196 2022/09/05 17:05:17 - mmengine - INFO - Epoch(train) [37][600/940] lr: 1.0000e-02 eta: 13:34:45 time: 0.8200 data_time: 0.3671 memory: 22701 grad_norm: 4.7038 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.4435 loss: 1.4435 2022/09/05 17:05:30 - mmengine - INFO - Epoch(train) [37][620/940] lr: 1.0000e-02 eta: 13:34:23 time: 0.6499 data_time: 0.2521 memory: 22701 grad_norm: 4.7375 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5382 loss: 1.5382 2022/09/05 17:05:45 - mmengine - INFO - Epoch(train) [37][640/940] lr: 1.0000e-02 eta: 13:34:04 time: 0.7436 data_time: 0.3301 memory: 22701 grad_norm: 4.7307 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5628 loss: 1.5628 2022/09/05 17:06:00 - mmengine - INFO - Epoch(train) [37][660/940] lr: 1.0000e-02 eta: 13:33:45 time: 0.7552 data_time: 0.2444 memory: 22701 grad_norm: 4.6812 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4210 loss: 1.4210 2022/09/05 17:06:18 - mmengine - INFO - Epoch(train) [37][680/940] lr: 1.0000e-02 eta: 13:33:31 time: 0.8982 data_time: 0.3594 memory: 22701 grad_norm: 4.6502 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5246 loss: 1.5246 2022/09/05 17:06:31 - mmengine - INFO - Epoch(train) [37][700/940] lr: 1.0000e-02 eta: 13:33:10 time: 0.6801 data_time: 0.2366 memory: 22701 grad_norm: 4.7668 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4441 loss: 1.4441 2022/09/05 17:06:49 - mmengine - INFO - Epoch(train) [37][720/940] lr: 1.0000e-02 eta: 13:32:56 time: 0.8861 data_time: 0.2844 memory: 22701 grad_norm: 4.7053 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6270 loss: 1.6270 2022/09/05 17:07:05 - mmengine - INFO - Epoch(train) [37][740/940] lr: 1.0000e-02 eta: 13:32:39 time: 0.8105 data_time: 0.2953 memory: 22701 grad_norm: 4.7311 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7526 loss: 1.7526 2022/09/05 17:07:22 - mmengine - INFO - Epoch(train) [37][760/940] lr: 1.0000e-02 eta: 13:32:24 time: 0.8572 data_time: 0.4359 memory: 22701 grad_norm: 4.6665 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.4351 loss: 1.4351 2022/09/05 17:07:36 - mmengine - INFO - Epoch(train) [37][780/940] lr: 1.0000e-02 eta: 13:32:02 time: 0.6588 data_time: 0.1577 memory: 22701 grad_norm: 4.6833 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6643 loss: 1.6643 2022/09/05 17:07:53 - mmengine - INFO - Epoch(train) [37][800/940] lr: 1.0000e-02 eta: 13:31:47 time: 0.8641 data_time: 0.1752 memory: 22701 grad_norm: 4.6459 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5384 loss: 1.5384 2022/09/05 17:08:08 - mmengine - INFO - Epoch(train) [37][820/940] lr: 1.0000e-02 eta: 13:31:28 time: 0.7459 data_time: 0.2533 memory: 22701 grad_norm: 4.7375 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5573 loss: 1.5573 2022/09/05 17:08:25 - mmengine - INFO - Epoch(train) [37][840/940] lr: 1.0000e-02 eta: 13:31:13 time: 0.8504 data_time: 0.4116 memory: 22701 grad_norm: 4.6204 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.4827 loss: 1.4827 2022/09/05 17:08:40 - mmengine - INFO - Epoch(train) [37][860/940] lr: 1.0000e-02 eta: 13:30:55 time: 0.7750 data_time: 0.2168 memory: 22701 grad_norm: 4.6641 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4551 loss: 1.4551 2022/09/05 17:08:59 - mmengine - INFO - Epoch(train) [37][880/940] lr: 1.0000e-02 eta: 13:30:41 time: 0.9114 data_time: 0.3615 memory: 22701 grad_norm: 4.7363 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5142 loss: 1.5142 2022/09/05 17:09:13 - mmengine - INFO - Epoch(train) [37][900/940] lr: 1.0000e-02 eta: 13:30:21 time: 0.7068 data_time: 0.2419 memory: 22701 grad_norm: 4.7458 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4653 loss: 1.4653 2022/09/05 17:09:29 - mmengine - INFO - Epoch(train) [37][920/940] lr: 1.0000e-02 eta: 13:30:04 time: 0.8121 data_time: 0.3019 memory: 22701 grad_norm: 4.7000 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5387 loss: 1.5387 2022/09/05 17:09:43 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:09:43 - mmengine - INFO - Epoch(train) [37][940/940] lr: 1.0000e-02 eta: 13:29:45 time: 0.7206 data_time: 0.2586 memory: 22701 grad_norm: 4.9178 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4497 loss: 1.4497 2022/09/05 17:09:57 - mmengine - INFO - Epoch(val) [37][20/78] eta: 0:00:40 time: 0.6925 data_time: 0.5723 memory: 2247 2022/09/05 17:10:06 - mmengine - INFO - Epoch(val) [37][40/78] eta: 0:00:16 time: 0.4430 data_time: 0.3222 memory: 2247 2022/09/05 17:10:19 - mmengine - INFO - Epoch(val) [37][60/78] eta: 0:00:12 time: 0.6679 data_time: 0.5468 memory: 2247 2022/09/05 17:10:30 - mmengine - INFO - Epoch(val) [37][78/78] acc/top1: 0.6482 acc/top5: 0.8571 acc/mean1: 0.6481 2022/09/05 17:10:30 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_32.pth is removed 2022/09/05 17:10:31 - mmengine - INFO - The best checkpoint with 0.6482 acc/top1 at 38 epoch is saved to best_acc/top1_epoch_38.pth. 2022/09/05 17:10:52 - mmengine - INFO - Epoch(train) [38][20/940] lr: 1.0000e-02 eta: 13:29:37 time: 1.0692 data_time: 0.5279 memory: 22701 grad_norm: 4.5261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5607 loss: 1.5607 2022/09/05 17:11:05 - mmengine - INFO - Epoch(train) [38][40/940] lr: 1.0000e-02 eta: 13:29:15 time: 0.6556 data_time: 0.0953 memory: 22701 grad_norm: 4.6842 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4742 loss: 1.4742 2022/09/05 17:11:23 - mmengine - INFO - Epoch(train) [38][60/940] lr: 1.0000e-02 eta: 13:29:00 time: 0.8677 data_time: 0.2049 memory: 22701 grad_norm: 4.6151 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4031 loss: 1.4031 2022/09/05 17:11:37 - mmengine - INFO - Epoch(train) [38][80/940] lr: 1.0000e-02 eta: 13:28:40 time: 0.7068 data_time: 0.0517 memory: 22701 grad_norm: 4.6346 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3497 loss: 1.3497 2022/09/05 17:11:54 - mmengine - INFO - Epoch(train) [38][100/940] lr: 1.0000e-02 eta: 13:28:25 time: 0.8796 data_time: 0.0278 memory: 22701 grad_norm: 4.6566 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5469 loss: 1.5469 2022/09/05 17:12:12 - mmengine - INFO - Epoch(train) [38][120/940] lr: 1.0000e-02 eta: 13:28:12 time: 0.9023 data_time: 0.0201 memory: 22701 grad_norm: 4.6075 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4058 loss: 1.4058 2022/09/05 17:12:33 - mmengine - INFO - Epoch(train) [38][140/940] lr: 1.0000e-02 eta: 13:28:02 time: 1.0158 data_time: 0.0484 memory: 22701 grad_norm: 4.7273 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5514 loss: 1.5514 2022/09/05 17:12:49 - mmengine - INFO - Epoch(train) [38][160/940] lr: 1.0000e-02 eta: 13:27:44 time: 0.7885 data_time: 0.0194 memory: 22701 grad_norm: 4.5539 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5171 loss: 1.5171 2022/09/05 17:13:09 - mmengine - INFO - Epoch(train) [38][180/940] lr: 1.0000e-02 eta: 13:27:34 time: 1.0068 data_time: 0.0722 memory: 22701 grad_norm: 4.7164 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3894 loss: 1.3894 2022/09/05 17:13:25 - mmengine - INFO - Epoch(train) [38][200/940] lr: 1.0000e-02 eta: 13:27:17 time: 0.8077 data_time: 0.0547 memory: 22701 grad_norm: 4.7072 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4110 loss: 1.4110 2022/09/05 17:13:44 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:13:44 - mmengine - INFO - Epoch(train) [38][220/940] lr: 1.0000e-02 eta: 13:27:06 time: 0.9756 data_time: 0.0234 memory: 22701 grad_norm: 4.5771 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4611 loss: 1.4611 2022/09/05 17:14:01 - mmengine - INFO - Epoch(train) [38][240/940] lr: 1.0000e-02 eta: 13:26:50 time: 0.8224 data_time: 0.1216 memory: 22701 grad_norm: 4.7344 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.5080 loss: 1.5080 2022/09/05 17:14:16 - mmengine - INFO - Epoch(train) [38][260/940] lr: 1.0000e-02 eta: 13:26:32 time: 0.7703 data_time: 0.1517 memory: 22701 grad_norm: 4.5955 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4688 loss: 1.4688 2022/09/05 17:14:30 - mmengine - INFO - Epoch(train) [38][280/940] lr: 1.0000e-02 eta: 13:26:11 time: 0.7004 data_time: 0.0195 memory: 22701 grad_norm: 4.6431 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4584 loss: 1.4584 2022/09/05 17:14:46 - mmengine - INFO - Epoch(train) [38][300/940] lr: 1.0000e-02 eta: 13:25:53 time: 0.7826 data_time: 0.0318 memory: 22701 grad_norm: 4.6881 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6522 loss: 1.6522 2022/09/05 17:15:04 - mmengine - INFO - Epoch(train) [38][320/940] lr: 1.0000e-02 eta: 13:25:40 time: 0.9043 data_time: 0.0253 memory: 22701 grad_norm: 4.7391 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5770 loss: 1.5770 2022/09/05 17:15:21 - mmengine - INFO - Epoch(train) [38][340/940] lr: 1.0000e-02 eta: 13:25:24 time: 0.8361 data_time: 0.0938 memory: 22701 grad_norm: 4.7961 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5420 loss: 1.5420 2022/09/05 17:15:40 - mmengine - INFO - Epoch(train) [38][360/940] lr: 1.0000e-02 eta: 13:25:12 time: 0.9599 data_time: 0.0595 memory: 22701 grad_norm: 4.8195 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4632 loss: 1.4632 2022/09/05 17:15:54 - mmengine - INFO - Epoch(train) [38][380/940] lr: 1.0000e-02 eta: 13:24:52 time: 0.6968 data_time: 0.0273 memory: 22701 grad_norm: 4.7078 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5372 loss: 1.5372 2022/09/05 17:16:09 - mmengine - INFO - Epoch(train) [38][400/940] lr: 1.0000e-02 eta: 13:24:34 time: 0.7777 data_time: 0.0260 memory: 22701 grad_norm: 4.6909 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4770 loss: 1.4770 2022/09/05 17:16:25 - mmengine - INFO - Epoch(train) [38][420/940] lr: 1.0000e-02 eta: 13:24:16 time: 0.7827 data_time: 0.0299 memory: 22701 grad_norm: 4.7354 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.4732 loss: 1.4732 2022/09/05 17:16:40 - mmengine - INFO - Epoch(train) [38][440/940] lr: 1.0000e-02 eta: 13:23:57 time: 0.7295 data_time: 0.0281 memory: 22701 grad_norm: 4.6304 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4865 loss: 1.4865 2022/09/05 17:16:54 - mmengine - INFO - Epoch(train) [38][460/940] lr: 1.0000e-02 eta: 13:23:37 time: 0.7332 data_time: 0.0286 memory: 22701 grad_norm: 4.7147 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5700 loss: 1.5700 2022/09/05 17:17:11 - mmengine - INFO - Epoch(train) [38][480/940] lr: 1.0000e-02 eta: 13:23:21 time: 0.8104 data_time: 0.0278 memory: 22701 grad_norm: 4.6078 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.4200 loss: 1.4200 2022/09/05 17:17:26 - mmengine - INFO - Epoch(train) [38][500/940] lr: 1.0000e-02 eta: 13:23:03 time: 0.7902 data_time: 0.1048 memory: 22701 grad_norm: 4.7230 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5097 loss: 1.5097 2022/09/05 17:17:41 - mmengine - INFO - Epoch(train) [38][520/940] lr: 1.0000e-02 eta: 13:22:44 time: 0.7389 data_time: 0.0688 memory: 22701 grad_norm: 4.7341 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5993 loss: 1.5993 2022/09/05 17:17:57 - mmengine - INFO - Epoch(train) [38][540/940] lr: 1.0000e-02 eta: 13:22:27 time: 0.7934 data_time: 0.0606 memory: 22701 grad_norm: 4.6257 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4636 loss: 1.4636 2022/09/05 17:18:12 - mmengine - INFO - Epoch(train) [38][560/940] lr: 1.0000e-02 eta: 13:22:08 time: 0.7580 data_time: 0.0254 memory: 22701 grad_norm: 4.7170 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4169 loss: 1.4169 2022/09/05 17:18:27 - mmengine - INFO - Epoch(train) [38][580/940] lr: 1.0000e-02 eta: 13:21:49 time: 0.7255 data_time: 0.0786 memory: 22701 grad_norm: 4.6870 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5477 loss: 1.5477 2022/09/05 17:18:42 - mmengine - INFO - Epoch(train) [38][600/940] lr: 1.0000e-02 eta: 13:21:31 time: 0.7698 data_time: 0.0629 memory: 22701 grad_norm: 4.6882 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4030 loss: 1.4030 2022/09/05 17:18:57 - mmengine - INFO - Epoch(train) [38][620/940] lr: 1.0000e-02 eta: 13:21:12 time: 0.7596 data_time: 0.0562 memory: 22701 grad_norm: 4.7699 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5449 loss: 1.5449 2022/09/05 17:19:15 - mmengine - INFO - Epoch(train) [38][640/940] lr: 1.0000e-02 eta: 13:20:59 time: 0.9054 data_time: 0.1344 memory: 22701 grad_norm: 4.6959 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5256 loss: 1.5256 2022/09/05 17:19:35 - mmengine - INFO - Epoch(train) [38][660/940] lr: 1.0000e-02 eta: 13:20:47 time: 0.9714 data_time: 0.5292 memory: 22701 grad_norm: 4.7383 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4845 loss: 1.4845 2022/09/05 17:19:48 - mmengine - INFO - Epoch(train) [38][680/940] lr: 1.0000e-02 eta: 13:20:26 time: 0.6744 data_time: 0.2860 memory: 22701 grad_norm: 4.7020 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3248 loss: 1.3248 2022/09/05 17:20:08 - mmengine - INFO - Epoch(train) [38][700/940] lr: 1.0000e-02 eta: 13:20:15 time: 0.9768 data_time: 0.3137 memory: 22701 grad_norm: 4.6636 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5134 loss: 1.5134 2022/09/05 17:20:25 - mmengine - INFO - Epoch(train) [38][720/940] lr: 1.0000e-02 eta: 13:19:59 time: 0.8571 data_time: 0.0357 memory: 22701 grad_norm: 4.7463 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5599 loss: 1.5599 2022/09/05 17:20:43 - mmengine - INFO - Epoch(train) [38][740/940] lr: 1.0000e-02 eta: 13:19:46 time: 0.9012 data_time: 0.0377 memory: 22701 grad_norm: 4.6902 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4729 loss: 1.4729 2022/09/05 17:21:00 - mmengine - INFO - Epoch(train) [38][760/940] lr: 1.0000e-02 eta: 13:19:31 time: 0.8594 data_time: 0.0855 memory: 22701 grad_norm: 4.7058 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.4476 loss: 1.4476 2022/09/05 17:21:17 - mmengine - INFO - Epoch(train) [38][780/940] lr: 1.0000e-02 eta: 13:19:15 time: 0.8446 data_time: 0.2197 memory: 22701 grad_norm: 4.6722 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4485 loss: 1.4485 2022/09/05 17:21:34 - mmengine - INFO - Epoch(train) [38][800/940] lr: 1.0000e-02 eta: 13:18:59 time: 0.8408 data_time: 0.3486 memory: 22701 grad_norm: 4.7567 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5237 loss: 1.5237 2022/09/05 17:21:54 - mmengine - INFO - Epoch(train) [38][820/940] lr: 1.0000e-02 eta: 13:18:49 time: 1.0010 data_time: 0.5440 memory: 22701 grad_norm: 4.7114 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4638 loss: 1.4638 2022/09/05 17:22:08 - mmengine - INFO - Epoch(train) [38][840/940] lr: 1.0000e-02 eta: 13:18:29 time: 0.7256 data_time: 0.2313 memory: 22701 grad_norm: 4.7972 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6111 loss: 1.6111 2022/09/05 17:22:26 - mmengine - INFO - Epoch(train) [38][860/940] lr: 1.0000e-02 eta: 13:18:16 time: 0.9049 data_time: 0.3477 memory: 22701 grad_norm: 4.6966 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5353 loss: 1.5353 2022/09/05 17:22:42 - mmengine - INFO - Epoch(train) [38][880/940] lr: 1.0000e-02 eta: 13:17:58 time: 0.7777 data_time: 0.2604 memory: 22701 grad_norm: 4.7384 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.4527 loss: 1.4527 2022/09/05 17:23:01 - mmengine - INFO - Epoch(train) [38][900/940] lr: 1.0000e-02 eta: 13:17:45 time: 0.9423 data_time: 0.4381 memory: 22701 grad_norm: 4.6926 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4225 loss: 1.4225 2022/09/05 17:23:17 - mmengine - INFO - Epoch(train) [38][920/940] lr: 1.0000e-02 eta: 13:17:29 time: 0.8140 data_time: 0.2651 memory: 22701 grad_norm: 4.7155 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4115 loss: 1.4115 2022/09/05 17:23:31 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:23:31 - mmengine - INFO - Epoch(train) [38][940/940] lr: 1.0000e-02 eta: 13:17:09 time: 0.7161 data_time: 0.1892 memory: 22701 grad_norm: 5.0389 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.5844 loss: 1.5844 2022/09/05 17:23:45 - mmengine - INFO - Epoch(val) [38][20/78] eta: 0:00:40 time: 0.6983 data_time: 0.5801 memory: 2247 2022/09/05 17:23:54 - mmengine - INFO - Epoch(val) [38][40/78] eta: 0:00:16 time: 0.4473 data_time: 0.3298 memory: 2247 2022/09/05 17:24:07 - mmengine - INFO - Epoch(val) [38][60/78] eta: 0:00:11 time: 0.6506 data_time: 0.5309 memory: 2247 2022/09/05 17:24:17 - mmengine - INFO - Epoch(val) [38][78/78] acc/top1: 0.6392 acc/top5: 0.8523 acc/mean1: 0.6391 2022/09/05 17:24:38 - mmengine - INFO - Epoch(train) [39][20/940] lr: 1.0000e-02 eta: 13:16:59 time: 1.0117 data_time: 0.4782 memory: 22701 grad_norm: 4.6899 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4498 loss: 1.4498 2022/09/05 17:24:51 - mmengine - INFO - Epoch(train) [39][40/940] lr: 1.0000e-02 eta: 13:16:37 time: 0.6657 data_time: 0.1118 memory: 22701 grad_norm: 4.5996 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.4772 loss: 1.4772 2022/09/05 17:25:07 - mmengine - INFO - Epoch(train) [39][60/940] lr: 1.0000e-02 eta: 13:16:20 time: 0.7944 data_time: 0.0308 memory: 22701 grad_norm: 4.4931 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4999 loss: 1.4999 2022/09/05 17:25:21 - mmengine - INFO - Epoch(train) [39][80/940] lr: 1.0000e-02 eta: 13:16:00 time: 0.7013 data_time: 0.0557 memory: 22701 grad_norm: 4.5850 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4582 loss: 1.4582 2022/09/05 17:25:40 - mmengine - INFO - Epoch(train) [39][100/940] lr: 1.0000e-02 eta: 13:15:47 time: 0.9322 data_time: 0.1147 memory: 22701 grad_norm: 4.5467 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4767 loss: 1.4767 2022/09/05 17:25:54 - mmengine - INFO - Epoch(train) [39][120/940] lr: 1.0000e-02 eta: 13:15:27 time: 0.7300 data_time: 0.0279 memory: 22701 grad_norm: 4.6613 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4315 loss: 1.4315 2022/09/05 17:26:11 - mmengine - INFO - Epoch(train) [39][140/940] lr: 1.0000e-02 eta: 13:15:11 time: 0.8334 data_time: 0.0276 memory: 22701 grad_norm: 4.6531 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4413 loss: 1.4413 2022/09/05 17:26:25 - mmengine - INFO - Epoch(train) [39][160/940] lr: 1.0000e-02 eta: 13:14:51 time: 0.6849 data_time: 0.0465 memory: 22701 grad_norm: 4.6728 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5121 loss: 1.5121 2022/09/05 17:26:43 - mmengine - INFO - Epoch(train) [39][180/940] lr: 1.0000e-02 eta: 13:14:38 time: 0.9224 data_time: 0.0391 memory: 22701 grad_norm: 4.6845 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3934 loss: 1.3934 2022/09/05 17:27:00 - mmengine - INFO - Epoch(train) [39][200/940] lr: 1.0000e-02 eta: 13:14:21 time: 0.8239 data_time: 0.0244 memory: 22701 grad_norm: 4.6767 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4080 loss: 1.4080 2022/09/05 17:27:19 - mmengine - INFO - Epoch(train) [39][220/940] lr: 1.0000e-02 eta: 13:14:10 time: 0.9707 data_time: 0.0666 memory: 22701 grad_norm: 4.6749 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4841 loss: 1.4841 2022/09/05 17:27:36 - mmengine - INFO - Epoch(train) [39][240/940] lr: 1.0000e-02 eta: 13:13:54 time: 0.8511 data_time: 0.1761 memory: 22701 grad_norm: 4.6799 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4498 loss: 1.4498 2022/09/05 17:27:57 - mmengine - INFO - Epoch(train) [39][260/940] lr: 1.0000e-02 eta: 13:13:46 time: 1.0697 data_time: 0.2566 memory: 22701 grad_norm: 4.6891 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3340 loss: 1.3340 2022/09/05 17:28:14 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:28:14 - mmengine - INFO - Epoch(train) [39][280/940] lr: 1.0000e-02 eta: 13:13:29 time: 0.8087 data_time: 0.1177 memory: 22701 grad_norm: 4.7347 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5308 loss: 1.5308 2022/09/05 17:28:36 - mmengine - INFO - Epoch(train) [39][300/940] lr: 1.0000e-02 eta: 13:13:23 time: 1.1368 data_time: 0.0507 memory: 22701 grad_norm: 4.7188 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4326 loss: 1.4326 2022/09/05 17:28:52 - mmengine - INFO - Epoch(train) [39][320/940] lr: 1.0000e-02 eta: 13:13:05 time: 0.7825 data_time: 0.0215 memory: 22701 grad_norm: 4.6934 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4535 loss: 1.4535 2022/09/05 17:29:12 - mmengine - INFO - Epoch(train) [39][340/940] lr: 1.0000e-02 eta: 13:12:55 time: 1.0027 data_time: 0.0245 memory: 22701 grad_norm: 4.7212 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5033 loss: 1.5033 2022/09/05 17:29:28 - mmengine - INFO - Epoch(train) [39][360/940] lr: 1.0000e-02 eta: 13:12:38 time: 0.8185 data_time: 0.0197 memory: 22701 grad_norm: 4.6136 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4459 loss: 1.4459 2022/09/05 17:29:49 - mmengine - INFO - Epoch(train) [39][380/940] lr: 1.0000e-02 eta: 13:12:28 time: 1.0285 data_time: 0.0261 memory: 22701 grad_norm: 4.6012 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6076 loss: 1.6076 2022/09/05 17:30:06 - mmengine - INFO - Epoch(train) [39][400/940] lr: 1.0000e-02 eta: 13:12:12 time: 0.8299 data_time: 0.0244 memory: 22701 grad_norm: 4.6238 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5472 loss: 1.5472 2022/09/05 17:30:26 - mmengine - INFO - Epoch(train) [39][420/940] lr: 1.0000e-02 eta: 13:12:02 time: 1.0140 data_time: 0.0235 memory: 22701 grad_norm: 4.6529 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4311 loss: 1.4311 2022/09/05 17:30:43 - mmengine - INFO - Epoch(train) [39][440/940] lr: 1.0000e-02 eta: 13:11:46 time: 0.8425 data_time: 0.0226 memory: 22701 grad_norm: 4.6980 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6697 loss: 1.6697 2022/09/05 17:31:06 - mmengine - INFO - Epoch(train) [39][460/940] lr: 1.0000e-02 eta: 13:11:41 time: 1.1664 data_time: 0.0248 memory: 22701 grad_norm: 4.6660 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4334 loss: 1.4334 2022/09/05 17:31:22 - mmengine - INFO - Epoch(train) [39][480/940] lr: 1.0000e-02 eta: 13:11:24 time: 0.7980 data_time: 0.0718 memory: 22701 grad_norm: 4.6544 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4588 loss: 1.4588 2022/09/05 17:31:41 - mmengine - INFO - Epoch(train) [39][500/940] lr: 1.0000e-02 eta: 13:11:11 time: 0.9404 data_time: 0.1553 memory: 22701 grad_norm: 4.6028 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4252 loss: 1.4252 2022/09/05 17:31:57 - mmengine - INFO - Epoch(train) [39][520/940] lr: 1.0000e-02 eta: 13:10:53 time: 0.7877 data_time: 0.0717 memory: 22701 grad_norm: 4.6580 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5178 loss: 1.5178 2022/09/05 17:32:12 - mmengine - INFO - Epoch(train) [39][540/940] lr: 1.0000e-02 eta: 13:10:35 time: 0.7525 data_time: 0.0205 memory: 22701 grad_norm: 4.6621 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5231 loss: 1.5231 2022/09/05 17:32:27 - mmengine - INFO - Epoch(train) [39][560/940] lr: 1.0000e-02 eta: 13:10:16 time: 0.7626 data_time: 0.1248 memory: 22701 grad_norm: 4.6950 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5362 loss: 1.5362 2022/09/05 17:32:42 - mmengine - INFO - Epoch(train) [39][580/940] lr: 1.0000e-02 eta: 13:09:58 time: 0.7508 data_time: 0.2394 memory: 22701 grad_norm: 4.6422 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4259 loss: 1.4259 2022/09/05 17:33:00 - mmengine - INFO - Epoch(train) [39][600/940] lr: 1.0000e-02 eta: 13:09:43 time: 0.8864 data_time: 0.2908 memory: 22701 grad_norm: 4.7012 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.5065 loss: 1.5065 2022/09/05 17:33:14 - mmengine - INFO - Epoch(train) [39][620/940] lr: 1.0000e-02 eta: 13:09:24 time: 0.7273 data_time: 0.1968 memory: 22701 grad_norm: 4.7266 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5023 loss: 1.5023 2022/09/05 17:33:35 - mmengine - INFO - Epoch(train) [39][640/940] lr: 1.0000e-02 eta: 13:09:15 time: 1.0398 data_time: 0.3809 memory: 22701 grad_norm: 4.6670 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6479 loss: 1.6479 2022/09/05 17:33:52 - mmengine - INFO - Epoch(train) [39][660/940] lr: 1.0000e-02 eta: 13:08:59 time: 0.8661 data_time: 0.2444 memory: 22701 grad_norm: 4.7146 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5672 loss: 1.5672 2022/09/05 17:34:13 - mmengine - INFO - Epoch(train) [39][680/940] lr: 1.0000e-02 eta: 13:08:50 time: 1.0287 data_time: 0.4637 memory: 22701 grad_norm: 4.5809 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4259 loss: 1.4259 2022/09/05 17:34:31 - mmengine - INFO - Epoch(train) [39][700/940] lr: 1.0000e-02 eta: 13:08:35 time: 0.8822 data_time: 0.1095 memory: 22701 grad_norm: 4.6455 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.4660 loss: 1.4660 2022/09/05 17:34:47 - mmengine - INFO - Epoch(train) [39][720/940] lr: 1.0000e-02 eta: 13:08:19 time: 0.8378 data_time: 0.0346 memory: 22701 grad_norm: 4.8212 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6191 loss: 1.6191 2022/09/05 17:35:07 - mmengine - INFO - Epoch(train) [39][740/940] lr: 1.0000e-02 eta: 13:08:08 time: 0.9861 data_time: 0.0316 memory: 22701 grad_norm: 4.6841 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.5343 loss: 1.5343 2022/09/05 17:35:27 - mmengine - INFO - Epoch(train) [39][760/940] lr: 1.0000e-02 eta: 13:07:57 time: 1.0008 data_time: 0.0285 memory: 22701 grad_norm: 4.6918 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4990 loss: 1.4990 2022/09/05 17:35:44 - mmengine - INFO - Epoch(train) [39][780/940] lr: 1.0000e-02 eta: 13:07:41 time: 0.8266 data_time: 0.0304 memory: 22701 grad_norm: 4.7741 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4877 loss: 1.4877 2022/09/05 17:36:01 - mmengine - INFO - Epoch(train) [39][800/940] lr: 1.0000e-02 eta: 13:07:27 time: 0.8949 data_time: 0.0223 memory: 22701 grad_norm: 4.6542 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5995 loss: 1.5995 2022/09/05 17:36:17 - mmengine - INFO - Epoch(train) [39][820/940] lr: 1.0000e-02 eta: 13:07:09 time: 0.7739 data_time: 0.0280 memory: 22701 grad_norm: 4.7384 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6358 loss: 1.6358 2022/09/05 17:36:36 - mmengine - INFO - Epoch(train) [39][840/940] lr: 1.0000e-02 eta: 13:06:57 time: 0.9714 data_time: 0.0244 memory: 22701 grad_norm: 4.7408 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4851 loss: 1.4851 2022/09/05 17:36:53 - mmengine - INFO - Epoch(train) [39][860/940] lr: 1.0000e-02 eta: 13:06:41 time: 0.8496 data_time: 0.0359 memory: 22701 grad_norm: 4.6412 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5075 loss: 1.5075 2022/09/05 17:37:10 - mmengine - INFO - Epoch(train) [39][880/940] lr: 1.0000e-02 eta: 13:06:26 time: 0.8444 data_time: 0.0306 memory: 22701 grad_norm: 4.6989 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5467 loss: 1.5467 2022/09/05 17:37:24 - mmengine - INFO - Epoch(train) [39][900/940] lr: 1.0000e-02 eta: 13:06:04 time: 0.6637 data_time: 0.0351 memory: 22701 grad_norm: 4.6595 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4732 loss: 1.4732 2022/09/05 17:37:40 - mmengine - INFO - Epoch(train) [39][920/940] lr: 1.0000e-02 eta: 13:05:48 time: 0.8362 data_time: 0.0283 memory: 22701 grad_norm: 4.7300 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3461 loss: 1.3461 2022/09/05 17:37:52 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:37:52 - mmengine - INFO - Epoch(train) [39][940/940] lr: 1.0000e-02 eta: 13:05:24 time: 0.5684 data_time: 0.0213 memory: 22701 grad_norm: 5.0912 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.6459 loss: 1.6459 2022/09/05 17:37:52 - mmengine - INFO - Saving checkpoint at 39 epochs 2022/09/05 17:38:08 - mmengine - INFO - Epoch(val) [39][20/78] eta: 0:00:42 time: 0.7354 data_time: 0.6191 memory: 2247 2022/09/05 17:38:17 - mmengine - INFO - Epoch(val) [39][40/78] eta: 0:00:16 time: 0.4365 data_time: 0.3197 memory: 2247 2022/09/05 17:38:29 - mmengine - INFO - Epoch(val) [39][60/78] eta: 0:00:11 time: 0.6420 data_time: 0.5213 memory: 2247 2022/09/05 17:38:39 - mmengine - INFO - Epoch(val) [39][78/78] acc/top1: 0.6439 acc/top5: 0.8573 acc/mean1: 0.6438 2022/09/05 17:38:59 - mmengine - INFO - Epoch(train) [40][20/940] lr: 1.0000e-02 eta: 13:05:13 time: 1.0066 data_time: 0.5569 memory: 22701 grad_norm: 4.6919 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5183 loss: 1.5183 2022/09/05 17:39:13 - mmengine - INFO - Epoch(train) [40][40/940] lr: 1.0000e-02 eta: 13:04:53 time: 0.7051 data_time: 0.3250 memory: 22701 grad_norm: 4.6348 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.4953 loss: 1.4953 2022/09/05 17:39:30 - mmengine - INFO - Epoch(train) [40][60/940] lr: 1.0000e-02 eta: 13:04:37 time: 0.8203 data_time: 0.4086 memory: 22701 grad_norm: 4.5521 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4513 loss: 1.4513 2022/09/05 17:39:44 - mmengine - INFO - Epoch(train) [40][80/940] lr: 1.0000e-02 eta: 13:04:17 time: 0.7086 data_time: 0.1942 memory: 22701 grad_norm: 4.6301 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5047 loss: 1.5047 2022/09/05 17:40:02 - mmengine - INFO - Epoch(train) [40][100/940] lr: 1.0000e-02 eta: 13:04:02 time: 0.8888 data_time: 0.3423 memory: 22701 grad_norm: 4.6358 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4540 loss: 1.4540 2022/09/05 17:40:16 - mmengine - INFO - Epoch(train) [40][120/940] lr: 1.0000e-02 eta: 13:03:42 time: 0.7036 data_time: 0.3282 memory: 22701 grad_norm: 4.5244 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5073 loss: 1.5073 2022/09/05 17:40:36 - mmengine - INFO - Epoch(train) [40][140/940] lr: 1.0000e-02 eta: 13:03:32 time: 1.0117 data_time: 0.6229 memory: 22701 grad_norm: 4.5737 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3608 loss: 1.3608 2022/09/05 17:40:50 - mmengine - INFO - Epoch(train) [40][160/940] lr: 1.0000e-02 eta: 13:03:12 time: 0.7252 data_time: 0.3175 memory: 22701 grad_norm: 4.5803 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3196 loss: 1.3196 2022/09/05 17:41:09 - mmengine - INFO - Epoch(train) [40][180/940] lr: 1.0000e-02 eta: 13:02:59 time: 0.9139 data_time: 0.4803 memory: 22701 grad_norm: 4.6048 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4439 loss: 1.4439 2022/09/05 17:41:23 - mmengine - INFO - Epoch(train) [40][200/940] lr: 1.0000e-02 eta: 13:02:39 time: 0.7101 data_time: 0.3300 memory: 22701 grad_norm: 4.6887 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5758 loss: 1.5758 2022/09/05 17:41:43 - mmengine - INFO - Epoch(train) [40][220/940] lr: 1.0000e-02 eta: 13:02:28 time: 1.0068 data_time: 0.5764 memory: 22701 grad_norm: 4.7546 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4541 loss: 1.4541 2022/09/05 17:41:58 - mmengine - INFO - Epoch(train) [40][240/940] lr: 1.0000e-02 eta: 13:02:10 time: 0.7671 data_time: 0.3818 memory: 22701 grad_norm: 4.5681 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4460 loss: 1.4460 2022/09/05 17:42:18 - mmengine - INFO - Epoch(train) [40][260/940] lr: 1.0000e-02 eta: 13:01:58 time: 0.9615 data_time: 0.5507 memory: 22701 grad_norm: 4.6860 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5114 loss: 1.5114 2022/09/05 17:42:32 - mmengine - INFO - Epoch(train) [40][280/940] lr: 1.0000e-02 eta: 13:01:38 time: 0.7261 data_time: 0.3438 memory: 22701 grad_norm: 4.7302 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4689 loss: 1.4689 2022/09/05 17:42:51 - mmengine - INFO - Epoch(train) [40][300/940] lr: 1.0000e-02 eta: 13:01:26 time: 0.9462 data_time: 0.5424 memory: 22701 grad_norm: 4.6687 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4172 loss: 1.4172 2022/09/05 17:43:06 - mmengine - INFO - Epoch(train) [40][320/940] lr: 1.0000e-02 eta: 13:01:07 time: 0.7388 data_time: 0.3281 memory: 22701 grad_norm: 4.6637 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5229 loss: 1.5229 2022/09/05 17:43:24 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:43:24 - mmengine - INFO - Epoch(train) [40][340/940] lr: 1.0000e-02 eta: 13:00:53 time: 0.9213 data_time: 0.4908 memory: 22701 grad_norm: 4.6048 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3381 loss: 1.3381 2022/09/05 17:43:38 - mmengine - INFO - Epoch(train) [40][360/940] lr: 1.0000e-02 eta: 13:00:33 time: 0.6881 data_time: 0.2984 memory: 22701 grad_norm: 4.7221 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4930 loss: 1.4930 2022/09/05 17:43:55 - mmengine - INFO - Epoch(train) [40][380/940] lr: 1.0000e-02 eta: 13:00:17 time: 0.8320 data_time: 0.4127 memory: 22701 grad_norm: 4.8037 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.5503 loss: 1.5503 2022/09/05 17:44:10 - mmengine - INFO - Epoch(train) [40][400/940] lr: 1.0000e-02 eta: 12:59:59 time: 0.7814 data_time: 0.3850 memory: 22701 grad_norm: 4.5848 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4593 loss: 1.4593 2022/09/05 17:44:28 - mmengine - INFO - Epoch(train) [40][420/940] lr: 1.0000e-02 eta: 12:59:44 time: 0.8630 data_time: 0.4613 memory: 22701 grad_norm: 4.5934 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5006 loss: 1.5006 2022/09/05 17:44:43 - mmengine - INFO - Epoch(train) [40][440/940] lr: 1.0000e-02 eta: 12:59:25 time: 0.7569 data_time: 0.3529 memory: 22701 grad_norm: 4.6953 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4594 loss: 1.4594 2022/09/05 17:45:00 - mmengine - INFO - Epoch(train) [40][460/940] lr: 1.0000e-02 eta: 12:59:10 time: 0.8474 data_time: 0.4731 memory: 22701 grad_norm: 4.6775 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4415 loss: 1.4415 2022/09/05 17:45:14 - mmengine - INFO - Epoch(train) [40][480/940] lr: 1.0000e-02 eta: 12:58:50 time: 0.7103 data_time: 0.3140 memory: 22701 grad_norm: 4.6076 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4926 loss: 1.4926 2022/09/05 17:45:30 - mmengine - INFO - Epoch(train) [40][500/940] lr: 1.0000e-02 eta: 12:58:34 time: 0.8233 data_time: 0.4366 memory: 22701 grad_norm: 4.6305 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.3816 loss: 1.3816 2022/09/05 17:45:46 - mmengine - INFO - Epoch(train) [40][520/940] lr: 1.0000e-02 eta: 12:58:15 time: 0.7544 data_time: 0.3425 memory: 22701 grad_norm: 4.7153 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4999 loss: 1.4999 2022/09/05 17:46:04 - mmengine - INFO - Epoch(train) [40][540/940] lr: 1.0000e-02 eta: 12:58:02 time: 0.9349 data_time: 0.5281 memory: 22701 grad_norm: 4.7312 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5472 loss: 1.5472 2022/09/05 17:46:19 - mmengine - INFO - Epoch(train) [40][560/940] lr: 1.0000e-02 eta: 12:57:43 time: 0.7504 data_time: 0.3522 memory: 22701 grad_norm: 4.6657 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4854 loss: 1.4854 2022/09/05 17:46:36 - mmengine - INFO - Epoch(train) [40][580/940] lr: 1.0000e-02 eta: 12:57:27 time: 0.8361 data_time: 0.4536 memory: 22701 grad_norm: 4.6762 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4064 loss: 1.4064 2022/09/05 17:46:53 - mmengine - INFO - Epoch(train) [40][600/940] lr: 1.0000e-02 eta: 12:57:11 time: 0.8299 data_time: 0.4143 memory: 22701 grad_norm: 4.7140 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4069 loss: 1.4069 2022/09/05 17:47:11 - mmengine - INFO - Epoch(train) [40][620/940] lr: 1.0000e-02 eta: 12:56:58 time: 0.9235 data_time: 0.5324 memory: 22701 grad_norm: 4.6987 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5235 loss: 1.5235 2022/09/05 17:47:26 - mmengine - INFO - Epoch(train) [40][640/940] lr: 1.0000e-02 eta: 12:56:39 time: 0.7254 data_time: 0.3415 memory: 22701 grad_norm: 4.7239 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5228 loss: 1.5228 2022/09/05 17:47:44 - mmengine - INFO - Epoch(train) [40][660/940] lr: 1.0000e-02 eta: 12:56:25 time: 0.9228 data_time: 0.5290 memory: 22701 grad_norm: 4.7077 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3634 loss: 1.3634 2022/09/05 17:47:59 - mmengine - INFO - Epoch(train) [40][680/940] lr: 1.0000e-02 eta: 12:56:06 time: 0.7356 data_time: 0.3153 memory: 22701 grad_norm: 4.7233 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4367 loss: 1.4367 2022/09/05 17:48:19 - mmengine - INFO - Epoch(train) [40][700/940] lr: 1.0000e-02 eta: 12:55:56 time: 1.0226 data_time: 0.5300 memory: 22701 grad_norm: 4.5911 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6112 loss: 1.6112 2022/09/05 17:48:34 - mmengine - INFO - Epoch(train) [40][720/940] lr: 1.0000e-02 eta: 12:55:36 time: 0.7241 data_time: 0.3076 memory: 22701 grad_norm: 4.7469 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4360 loss: 1.4360 2022/09/05 17:48:52 - mmengine - INFO - Epoch(train) [40][740/940] lr: 1.0000e-02 eta: 12:55:23 time: 0.9291 data_time: 0.3369 memory: 22701 grad_norm: 4.7218 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4840 loss: 1.4840 2022/09/05 17:49:08 - mmengine - INFO - Epoch(train) [40][760/940] lr: 1.0000e-02 eta: 12:55:06 time: 0.7848 data_time: 0.1721 memory: 22701 grad_norm: 4.7567 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5571 loss: 1.5571 2022/09/05 17:49:28 - mmengine - INFO - Epoch(train) [40][780/940] lr: 1.0000e-02 eta: 12:54:55 time: 1.0177 data_time: 0.0335 memory: 22701 grad_norm: 4.6992 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3903 loss: 1.3903 2022/09/05 17:49:42 - mmengine - INFO - Epoch(train) [40][800/940] lr: 1.0000e-02 eta: 12:54:35 time: 0.6966 data_time: 0.1212 memory: 22701 grad_norm: 4.7283 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6093 loss: 1.6093 2022/09/05 17:50:00 - mmengine - INFO - Epoch(train) [40][820/940] lr: 1.0000e-02 eta: 12:54:21 time: 0.9105 data_time: 0.3280 memory: 22701 grad_norm: 4.6630 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4594 loss: 1.4594 2022/09/05 17:50:15 - mmengine - INFO - Epoch(train) [40][840/940] lr: 1.0000e-02 eta: 12:54:02 time: 0.7309 data_time: 0.1836 memory: 22701 grad_norm: 4.5553 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3606 loss: 1.3606 2022/09/05 17:50:35 - mmengine - INFO - Epoch(train) [40][860/940] lr: 1.0000e-02 eta: 12:53:50 time: 0.9766 data_time: 0.1009 memory: 22701 grad_norm: 4.6644 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5694 loss: 1.5694 2022/09/05 17:50:50 - mmengine - INFO - Epoch(train) [40][880/940] lr: 1.0000e-02 eta: 12:53:32 time: 0.7623 data_time: 0.1589 memory: 22701 grad_norm: 4.6253 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4925 loss: 1.4925 2022/09/05 17:51:10 - mmengine - INFO - Epoch(train) [40][900/940] lr: 1.0000e-02 eta: 12:53:22 time: 1.0256 data_time: 0.4877 memory: 22701 grad_norm: 4.6951 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4631 loss: 1.4631 2022/09/05 17:51:25 - mmengine - INFO - Epoch(train) [40][920/940] lr: 1.0000e-02 eta: 12:53:02 time: 0.7233 data_time: 0.2030 memory: 22701 grad_norm: 4.6290 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4841 loss: 1.4841 2022/09/05 17:51:40 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:51:40 - mmengine - INFO - Epoch(train) [40][940/940] lr: 1.0000e-02 eta: 12:52:43 time: 0.7379 data_time: 0.2285 memory: 22701 grad_norm: 4.9511 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.4239 loss: 1.4239 2022/09/05 17:51:54 - mmengine - INFO - Epoch(val) [40][20/78] eta: 0:00:40 time: 0.7032 data_time: 0.5820 memory: 2247 2022/09/05 17:52:02 - mmengine - INFO - Epoch(val) [40][40/78] eta: 0:00:16 time: 0.4327 data_time: 0.3137 memory: 2247 2022/09/05 17:52:16 - mmengine - INFO - Epoch(val) [40][60/78] eta: 0:00:11 time: 0.6612 data_time: 0.5400 memory: 2247 2022/09/05 17:52:26 - mmengine - INFO - Epoch(val) [40][78/78] acc/top1: 0.6452 acc/top5: 0.8561 acc/mean1: 0.6451 2022/09/05 17:52:46 - mmengine - INFO - Epoch(train) [41][20/940] lr: 1.0000e-03 eta: 12:52:32 time: 0.9936 data_time: 0.4359 memory: 22701 grad_norm: 4.4451 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3686 loss: 1.3686 2022/09/05 17:53:00 - mmengine - INFO - Epoch(train) [41][40/940] lr: 1.0000e-03 eta: 12:52:12 time: 0.7099 data_time: 0.0599 memory: 22701 grad_norm: 4.5011 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4615 loss: 1.4615 2022/09/05 17:53:19 - mmengine - INFO - Epoch(train) [41][60/940] lr: 1.0000e-03 eta: 12:51:59 time: 0.9503 data_time: 0.0491 memory: 22701 grad_norm: 4.4577 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4120 loss: 1.4120 2022/09/05 17:53:33 - mmengine - INFO - Epoch(train) [41][80/940] lr: 1.0000e-03 eta: 12:51:40 time: 0.7175 data_time: 0.0333 memory: 22701 grad_norm: 4.4615 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3888 loss: 1.3888 2022/09/05 17:53:50 - mmengine - INFO - Epoch(train) [41][100/940] lr: 1.0000e-03 eta: 12:51:23 time: 0.8243 data_time: 0.0268 memory: 22701 grad_norm: 4.3504 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3694 loss: 1.3694 2022/09/05 17:54:04 - mmengine - INFO - Epoch(train) [41][120/940] lr: 1.0000e-03 eta: 12:51:03 time: 0.6867 data_time: 0.0292 memory: 22701 grad_norm: 4.3106 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4076 loss: 1.4076 2022/09/05 17:54:22 - mmengine - INFO - Epoch(train) [41][140/940] lr: 1.0000e-03 eta: 12:50:50 time: 0.9364 data_time: 0.0808 memory: 22701 grad_norm: 4.4117 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3352 loss: 1.3352 2022/09/05 17:54:38 - mmengine - INFO - Epoch(train) [41][160/940] lr: 1.0000e-03 eta: 12:50:32 time: 0.7687 data_time: 0.0280 memory: 22701 grad_norm: 4.3464 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.3486 loss: 1.3486 2022/09/05 17:54:58 - mmengine - INFO - Epoch(train) [41][180/940] lr: 1.0000e-03 eta: 12:50:21 time: 1.0232 data_time: 0.0230 memory: 22701 grad_norm: 4.4350 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2852 loss: 1.2852 2022/09/05 17:55:13 - mmengine - INFO - Epoch(train) [41][200/940] lr: 1.0000e-03 eta: 12:50:03 time: 0.7465 data_time: 0.0209 memory: 22701 grad_norm: 4.2888 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2915 loss: 1.2915 2022/09/05 17:55:30 - mmengine - INFO - Epoch(train) [41][220/940] lr: 1.0000e-03 eta: 12:49:47 time: 0.8546 data_time: 0.0412 memory: 22701 grad_norm: 4.3898 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3977 loss: 1.3977 2022/09/05 17:55:48 - mmengine - INFO - Epoch(train) [41][240/940] lr: 1.0000e-03 eta: 12:49:33 time: 0.8966 data_time: 0.1254 memory: 22701 grad_norm: 4.3776 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3709 loss: 1.3709 2022/09/05 17:56:06 - mmengine - INFO - Epoch(train) [41][260/940] lr: 1.0000e-03 eta: 12:49:18 time: 0.8810 data_time: 0.1629 memory: 22701 grad_norm: 4.3191 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3070 loss: 1.3070 2022/09/05 17:56:29 - mmengine - INFO - Epoch(train) [41][280/940] lr: 1.0000e-03 eta: 12:49:12 time: 1.1560 data_time: 0.7031 memory: 22701 grad_norm: 4.4597 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3333 loss: 1.3333 2022/09/05 17:56:47 - mmengine - INFO - Epoch(train) [41][300/940] lr: 1.0000e-03 eta: 12:48:58 time: 0.8973 data_time: 0.2451 memory: 22701 grad_norm: 4.3485 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4344 loss: 1.4344 2022/09/05 17:57:05 - mmengine - INFO - Epoch(train) [41][320/940] lr: 1.0000e-03 eta: 12:48:43 time: 0.8844 data_time: 0.0273 memory: 22701 grad_norm: 4.4097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2977 loss: 1.2977 2022/09/05 17:57:24 - mmengine - INFO - Epoch(train) [41][340/940] lr: 1.0000e-03 eta: 12:48:32 time: 0.9954 data_time: 0.0281 memory: 22701 grad_norm: 4.3232 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2782 loss: 1.2782 2022/09/05 17:57:39 - mmengine - INFO - Epoch(train) [41][360/940] lr: 1.0000e-03 eta: 12:48:13 time: 0.7372 data_time: 0.0283 memory: 22701 grad_norm: 4.3431 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3467 loss: 1.3467 2022/09/05 17:57:58 - mmengine - INFO - Epoch(train) [41][380/940] lr: 1.0000e-03 eta: 12:48:00 time: 0.9475 data_time: 0.0218 memory: 22701 grad_norm: 4.4111 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2998 loss: 1.2998 2022/09/05 17:58:13 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 17:58:13 - mmengine - INFO - Epoch(train) [41][400/940] lr: 1.0000e-03 eta: 12:47:41 time: 0.7411 data_time: 0.1044 memory: 22701 grad_norm: 4.3068 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1749 loss: 1.1749 2022/09/05 17:58:29 - mmengine - INFO - Epoch(train) [41][420/940] lr: 1.0000e-03 eta: 12:47:24 time: 0.7946 data_time: 0.1652 memory: 22701 grad_norm: 4.3765 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1887 loss: 1.1887 2022/09/05 17:58:44 - mmengine - INFO - Epoch(train) [41][440/940] lr: 1.0000e-03 eta: 12:47:06 time: 0.7655 data_time: 0.1934 memory: 22701 grad_norm: 4.3251 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2673 loss: 1.2673 2022/09/05 17:59:00 - mmengine - INFO - Epoch(train) [41][460/940] lr: 1.0000e-03 eta: 12:46:49 time: 0.8122 data_time: 0.0253 memory: 22701 grad_norm: 4.3235 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2451 loss: 1.2451 2022/09/05 17:59:14 - mmengine - INFO - Epoch(train) [41][480/940] lr: 1.0000e-03 eta: 12:46:28 time: 0.6819 data_time: 0.0671 memory: 22701 grad_norm: 4.4143 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2990 loss: 1.2990 2022/09/05 17:59:31 - mmengine - INFO - Epoch(train) [41][500/940] lr: 1.0000e-03 eta: 12:46:13 time: 0.8644 data_time: 0.0269 memory: 22701 grad_norm: 4.3808 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3196 loss: 1.3196 2022/09/05 17:59:49 - mmengine - INFO - Epoch(train) [41][520/940] lr: 1.0000e-03 eta: 12:45:58 time: 0.8623 data_time: 0.0290 memory: 22701 grad_norm: 4.4191 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.2130 loss: 1.2130 2022/09/05 18:00:06 - mmengine - INFO - Epoch(train) [41][540/940] lr: 1.0000e-03 eta: 12:45:43 time: 0.8650 data_time: 0.0305 memory: 22701 grad_norm: 4.4020 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.2551 loss: 1.2551 2022/09/05 18:00:23 - mmengine - INFO - Epoch(train) [41][560/940] lr: 1.0000e-03 eta: 12:45:26 time: 0.8325 data_time: 0.0270 memory: 22701 grad_norm: 4.4253 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2393 loss: 1.2393 2022/09/05 18:00:40 - mmengine - INFO - Epoch(train) [41][580/940] lr: 1.0000e-03 eta: 12:45:11 time: 0.8582 data_time: 0.0363 memory: 22701 grad_norm: 4.3977 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3708 loss: 1.3708 2022/09/05 18:00:56 - mmengine - INFO - Epoch(train) [41][600/940] lr: 1.0000e-03 eta: 12:44:55 time: 0.8287 data_time: 0.0390 memory: 22701 grad_norm: 4.3733 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3126 loss: 1.3126 2022/09/05 18:01:15 - mmengine - INFO - Epoch(train) [41][620/940] lr: 1.0000e-03 eta: 12:44:41 time: 0.9179 data_time: 0.0323 memory: 22701 grad_norm: 4.4700 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2405 loss: 1.2405 2022/09/05 18:01:34 - mmengine - INFO - Epoch(train) [41][640/940] lr: 1.0000e-03 eta: 12:44:29 time: 0.9569 data_time: 0.0248 memory: 22701 grad_norm: 4.3733 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2909 loss: 1.2909 2022/09/05 18:01:48 - mmengine - INFO - Epoch(train) [41][660/940] lr: 1.0000e-03 eta: 12:44:09 time: 0.7246 data_time: 0.0239 memory: 22701 grad_norm: 4.4150 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2436 loss: 1.2436 2022/09/05 18:02:04 - mmengine - INFO - Epoch(train) [41][680/940] lr: 1.0000e-03 eta: 12:43:52 time: 0.8098 data_time: 0.0241 memory: 22701 grad_norm: 4.3556 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2641 loss: 1.2641 2022/09/05 18:02:19 - mmengine - INFO - Epoch(train) [41][700/940] lr: 1.0000e-03 eta: 12:43:33 time: 0.7082 data_time: 0.0288 memory: 22701 grad_norm: 4.3847 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3235 loss: 1.3235 2022/09/05 18:02:36 - mmengine - INFO - Epoch(train) [41][720/940] lr: 1.0000e-03 eta: 12:43:17 time: 0.8483 data_time: 0.0241 memory: 22701 grad_norm: 4.3691 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3290 loss: 1.3290 2022/09/05 18:02:50 - mmengine - INFO - Epoch(train) [41][740/940] lr: 1.0000e-03 eta: 12:42:57 time: 0.6965 data_time: 0.0290 memory: 22701 grad_norm: 4.4005 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2997 loss: 1.2997 2022/09/05 18:03:06 - mmengine - INFO - Epoch(train) [41][760/940] lr: 1.0000e-03 eta: 12:42:40 time: 0.8089 data_time: 0.0890 memory: 22701 grad_norm: 4.3725 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3641 loss: 1.3641 2022/09/05 18:03:20 - mmengine - INFO - Epoch(train) [41][780/940] lr: 1.0000e-03 eta: 12:42:21 time: 0.7234 data_time: 0.0525 memory: 22701 grad_norm: 4.4335 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3637 loss: 1.3637 2022/09/05 18:03:36 - mmengine - INFO - Epoch(train) [41][800/940] lr: 1.0000e-03 eta: 12:42:03 time: 0.7825 data_time: 0.0612 memory: 22701 grad_norm: 4.4609 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2456 loss: 1.2456 2022/09/05 18:03:54 - mmengine - INFO - Epoch(train) [41][820/940] lr: 1.0000e-03 eta: 12:41:50 time: 0.9240 data_time: 0.2890 memory: 22701 grad_norm: 4.4319 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3243 loss: 1.3243 2022/09/05 18:04:10 - mmengine - INFO - Epoch(train) [41][840/940] lr: 1.0000e-03 eta: 12:41:32 time: 0.7800 data_time: 0.1987 memory: 22701 grad_norm: 4.4010 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3067 loss: 1.3067 2022/09/05 18:04:28 - mmengine - INFO - Epoch(train) [41][860/940] lr: 1.0000e-03 eta: 12:41:18 time: 0.8994 data_time: 0.0951 memory: 22701 grad_norm: 4.3803 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.1456 loss: 1.1456 2022/09/05 18:04:46 - mmengine - INFO - Epoch(train) [41][880/940] lr: 1.0000e-03 eta: 12:41:04 time: 0.9289 data_time: 0.0228 memory: 22701 grad_norm: 4.4211 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2826 loss: 1.2826 2022/09/05 18:05:04 - mmengine - INFO - Epoch(train) [41][900/940] lr: 1.0000e-03 eta: 12:40:49 time: 0.8553 data_time: 0.0238 memory: 22701 grad_norm: 4.4621 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3843 loss: 1.3843 2022/09/05 18:05:18 - mmengine - INFO - Epoch(train) [41][920/940] lr: 1.0000e-03 eta: 12:40:30 time: 0.7375 data_time: 0.0253 memory: 22701 grad_norm: 4.3906 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2546 loss: 1.2546 2022/09/05 18:05:34 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:05:34 - mmengine - INFO - Epoch(train) [41][940/940] lr: 1.0000e-03 eta: 12:40:13 time: 0.7957 data_time: 0.0386 memory: 22701 grad_norm: 4.6085 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3269 loss: 1.3269 2022/09/05 18:05:48 - mmengine - INFO - Epoch(val) [41][20/78] eta: 0:00:39 time: 0.6827 data_time: 0.5653 memory: 2247 2022/09/05 18:05:57 - mmengine - INFO - Epoch(val) [41][40/78] eta: 0:00:17 time: 0.4618 data_time: 0.3428 memory: 2247 2022/09/05 18:06:10 - mmengine - INFO - Epoch(val) [41][60/78] eta: 0:00:11 time: 0.6445 data_time: 0.5255 memory: 2247 2022/09/05 18:06:20 - mmengine - INFO - Epoch(val) [41][78/78] acc/top1: 0.6783 acc/top5: 0.8778 acc/mean1: 0.6782 2022/09/05 18:06:21 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_38.pth is removed 2022/09/05 18:06:22 - mmengine - INFO - The best checkpoint with 0.6783 acc/top1 at 42 epoch is saved to best_acc/top1_epoch_42.pth. 2022/09/05 18:06:44 - mmengine - INFO - Epoch(train) [42][20/940] lr: 1.0000e-03 eta: 12:40:04 time: 1.1071 data_time: 0.6940 memory: 22701 grad_norm: 4.4138 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2633 loss: 1.2633 2022/09/05 18:06:57 - mmengine - INFO - Epoch(train) [42][40/940] lr: 1.0000e-03 eta: 12:39:43 time: 0.6576 data_time: 0.2399 memory: 22701 grad_norm: 4.3362 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2020 loss: 1.2020 2022/09/05 18:07:15 - mmengine - INFO - Epoch(train) [42][60/940] lr: 1.0000e-03 eta: 12:39:29 time: 0.9131 data_time: 0.3062 memory: 22701 grad_norm: 4.3480 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2733 loss: 1.2733 2022/09/05 18:07:31 - mmengine - INFO - Epoch(train) [42][80/940] lr: 1.0000e-03 eta: 12:39:13 time: 0.8072 data_time: 0.0528 memory: 22701 grad_norm: 4.2991 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1469 loss: 1.1469 2022/09/05 18:07:52 - mmengine - INFO - Epoch(train) [42][100/940] lr: 1.0000e-03 eta: 12:39:02 time: 1.0138 data_time: 0.0268 memory: 22701 grad_norm: 4.4084 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2436 loss: 1.2436 2022/09/05 18:08:06 - mmengine - INFO - Epoch(train) [42][120/940] lr: 1.0000e-03 eta: 12:38:43 time: 0.7346 data_time: 0.0210 memory: 22701 grad_norm: 4.3603 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2154 loss: 1.2154 2022/09/05 18:08:23 - mmengine - INFO - Epoch(train) [42][140/940] lr: 1.0000e-03 eta: 12:38:26 time: 0.8287 data_time: 0.0294 memory: 22701 grad_norm: 4.3848 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2408 loss: 1.2408 2022/09/05 18:08:39 - mmengine - INFO - Epoch(train) [42][160/940] lr: 1.0000e-03 eta: 12:38:10 time: 0.8161 data_time: 0.0271 memory: 22701 grad_norm: 4.3098 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2404 loss: 1.2404 2022/09/05 18:08:57 - mmengine - INFO - Epoch(train) [42][180/940] lr: 1.0000e-03 eta: 12:37:56 time: 0.9169 data_time: 0.0286 memory: 22701 grad_norm: 4.3205 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0761 loss: 1.0761 2022/09/05 18:09:13 - mmengine - INFO - Epoch(train) [42][200/940] lr: 1.0000e-03 eta: 12:37:38 time: 0.7669 data_time: 0.0286 memory: 22701 grad_norm: 4.3777 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2798 loss: 1.2798 2022/09/05 18:09:32 - mmengine - INFO - Epoch(train) [42][220/940] lr: 1.0000e-03 eta: 12:37:25 time: 0.9439 data_time: 0.0279 memory: 22701 grad_norm: 4.3820 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3131 loss: 1.3131 2022/09/05 18:09:49 - mmengine - INFO - Epoch(train) [42][240/940] lr: 1.0000e-03 eta: 12:37:09 time: 0.8431 data_time: 0.0244 memory: 22701 grad_norm: 4.3640 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2119 loss: 1.2119 2022/09/05 18:10:07 - mmengine - INFO - Epoch(train) [42][260/940] lr: 1.0000e-03 eta: 12:36:55 time: 0.9240 data_time: 0.0359 memory: 22701 grad_norm: 4.4081 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3072 loss: 1.3072 2022/09/05 18:10:23 - mmengine - INFO - Epoch(train) [42][280/940] lr: 1.0000e-03 eta: 12:36:38 time: 0.7762 data_time: 0.0195 memory: 22701 grad_norm: 4.3909 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1845 loss: 1.1845 2022/09/05 18:10:44 - mmengine - INFO - Epoch(train) [42][300/940] lr: 1.0000e-03 eta: 12:36:29 time: 1.0801 data_time: 0.1332 memory: 22701 grad_norm: 4.3656 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2099 loss: 1.2099 2022/09/05 18:11:01 - mmengine - INFO - Epoch(train) [42][320/940] lr: 1.0000e-03 eta: 12:36:13 time: 0.8581 data_time: 0.2017 memory: 22701 grad_norm: 4.3488 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1312 loss: 1.1312 2022/09/05 18:11:21 - mmengine - INFO - Epoch(train) [42][340/940] lr: 1.0000e-03 eta: 12:36:01 time: 0.9775 data_time: 0.3583 memory: 22701 grad_norm: 4.4171 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3671 loss: 1.3671 2022/09/05 18:11:36 - mmengine - INFO - Epoch(train) [42][360/940] lr: 1.0000e-03 eta: 12:35:43 time: 0.7692 data_time: 0.0689 memory: 22701 grad_norm: 4.3800 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1731 loss: 1.1731 2022/09/05 18:11:52 - mmengine - INFO - Epoch(train) [42][380/940] lr: 1.0000e-03 eta: 12:35:26 time: 0.7880 data_time: 0.0247 memory: 22701 grad_norm: 4.4302 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1541 loss: 1.1541 2022/09/05 18:12:06 - mmengine - INFO - Epoch(train) [42][400/940] lr: 1.0000e-03 eta: 12:35:05 time: 0.6723 data_time: 0.0212 memory: 22701 grad_norm: 4.4979 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1760 loss: 1.1760 2022/09/05 18:12:23 - mmengine - INFO - Epoch(train) [42][420/940] lr: 1.0000e-03 eta: 12:34:49 time: 0.8620 data_time: 0.0569 memory: 22701 grad_norm: 4.4516 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3250 loss: 1.3250 2022/09/05 18:12:37 - mmengine - INFO - Epoch(train) [42][440/940] lr: 1.0000e-03 eta: 12:34:30 time: 0.7231 data_time: 0.1102 memory: 22701 grad_norm: 4.5122 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1605 loss: 1.1605 2022/09/05 18:12:57 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:12:57 - mmengine - INFO - Epoch(train) [42][460/940] lr: 1.0000e-03 eta: 12:34:18 time: 0.9841 data_time: 0.0816 memory: 22701 grad_norm: 4.4838 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1919 loss: 1.1919 2022/09/05 18:13:13 - mmengine - INFO - Epoch(train) [42][480/940] lr: 1.0000e-03 eta: 12:34:01 time: 0.7881 data_time: 0.1428 memory: 22701 grad_norm: 4.3412 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2585 loss: 1.2585 2022/09/05 18:13:31 - mmengine - INFO - Epoch(train) [42][500/940] lr: 1.0000e-03 eta: 12:33:47 time: 0.9173 data_time: 0.0309 memory: 22701 grad_norm: 4.4145 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.2015 loss: 1.2015 2022/09/05 18:13:45 - mmengine - INFO - Epoch(train) [42][520/940] lr: 1.0000e-03 eta: 12:33:28 time: 0.7150 data_time: 0.0216 memory: 22701 grad_norm: 4.4224 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1486 loss: 1.1486 2022/09/05 18:14:02 - mmengine - INFO - Epoch(train) [42][540/940] lr: 1.0000e-03 eta: 12:33:11 time: 0.8250 data_time: 0.0299 memory: 22701 grad_norm: 4.5031 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2661 loss: 1.2661 2022/09/05 18:14:17 - mmengine - INFO - Epoch(train) [42][560/940] lr: 1.0000e-03 eta: 12:32:53 time: 0.7465 data_time: 0.0231 memory: 22701 grad_norm: 4.4660 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1753 loss: 1.1753 2022/09/05 18:14:35 - mmengine - INFO - Epoch(train) [42][580/940] lr: 1.0000e-03 eta: 12:32:38 time: 0.8926 data_time: 0.0324 memory: 22701 grad_norm: 4.4705 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3213 loss: 1.3213 2022/09/05 18:14:48 - mmengine - INFO - Epoch(train) [42][600/940] lr: 1.0000e-03 eta: 12:32:17 time: 0.6696 data_time: 0.0272 memory: 22701 grad_norm: 4.3876 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1608 loss: 1.1608 2022/09/05 18:15:03 - mmengine - INFO - Epoch(train) [42][620/940] lr: 1.0000e-03 eta: 12:31:59 time: 0.7708 data_time: 0.0293 memory: 22701 grad_norm: 4.4095 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3389 loss: 1.3389 2022/09/05 18:15:18 - mmengine - INFO - Epoch(train) [42][640/940] lr: 1.0000e-03 eta: 12:31:40 time: 0.7065 data_time: 0.0227 memory: 22701 grad_norm: 4.3945 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3654 loss: 1.3654 2022/09/05 18:15:35 - mmengine - INFO - Epoch(train) [42][660/940] lr: 1.0000e-03 eta: 12:31:24 time: 0.8674 data_time: 0.0315 memory: 22701 grad_norm: 4.4850 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1818 loss: 1.1818 2022/09/05 18:15:50 - mmengine - INFO - Epoch(train) [42][680/940] lr: 1.0000e-03 eta: 12:31:05 time: 0.7315 data_time: 0.0188 memory: 22701 grad_norm: 4.5219 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3019 loss: 1.3019 2022/09/05 18:16:10 - mmengine - INFO - Epoch(train) [42][700/940] lr: 1.0000e-03 eta: 12:30:55 time: 1.0277 data_time: 0.2150 memory: 22701 grad_norm: 4.3438 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1792 loss: 1.1792 2022/09/05 18:16:25 - mmengine - INFO - Epoch(train) [42][720/940] lr: 1.0000e-03 eta: 12:30:36 time: 0.7249 data_time: 0.2341 memory: 22701 grad_norm: 4.4198 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3012 loss: 1.3012 2022/09/05 18:16:42 - mmengine - INFO - Epoch(train) [42][740/940] lr: 1.0000e-03 eta: 12:30:21 time: 0.8811 data_time: 0.3531 memory: 22701 grad_norm: 4.4844 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.2405 loss: 1.2405 2022/09/05 18:16:56 - mmengine - INFO - Epoch(train) [42][760/940] lr: 1.0000e-03 eta: 12:30:00 time: 0.6836 data_time: 0.0574 memory: 22701 grad_norm: 4.4809 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2423 loss: 1.2423 2022/09/05 18:17:16 - mmengine - INFO - Epoch(train) [42][780/940] lr: 1.0000e-03 eta: 12:29:49 time: 0.9876 data_time: 0.2269 memory: 22701 grad_norm: 4.4508 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.3364 loss: 1.3364 2022/09/05 18:17:30 - mmengine - INFO - Epoch(train) [42][800/940] lr: 1.0000e-03 eta: 12:29:29 time: 0.7032 data_time: 0.1723 memory: 22701 grad_norm: 4.5032 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3866 loss: 1.3866 2022/09/05 18:17:48 - mmengine - INFO - Epoch(train) [42][820/940] lr: 1.0000e-03 eta: 12:29:15 time: 0.9183 data_time: 0.4236 memory: 22701 grad_norm: 4.3789 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2272 loss: 1.2272 2022/09/05 18:18:05 - mmengine - INFO - Epoch(train) [42][840/940] lr: 1.0000e-03 eta: 12:28:59 time: 0.8408 data_time: 0.4517 memory: 22701 grad_norm: 4.4987 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1947 loss: 1.1947 2022/09/05 18:18:23 - mmengine - INFO - Epoch(train) [42][860/940] lr: 1.0000e-03 eta: 12:28:45 time: 0.8975 data_time: 0.4864 memory: 22701 grad_norm: 4.3549 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2198 loss: 1.2198 2022/09/05 18:18:38 - mmengine - INFO - Epoch(train) [42][880/940] lr: 1.0000e-03 eta: 12:28:26 time: 0.7496 data_time: 0.3193 memory: 22701 grad_norm: 4.4853 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2805 loss: 1.2805 2022/09/05 18:18:58 - mmengine - INFO - Epoch(train) [42][900/940] lr: 1.0000e-03 eta: 12:28:15 time: 1.0119 data_time: 0.1932 memory: 22701 grad_norm: 4.4217 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2377 loss: 1.2377 2022/09/05 18:19:12 - mmengine - INFO - Epoch(train) [42][920/940] lr: 1.0000e-03 eta: 12:27:55 time: 0.7134 data_time: 0.0715 memory: 22701 grad_norm: 4.5232 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1413 loss: 1.1413 2022/09/05 18:19:29 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:19:29 - mmengine - INFO - Epoch(train) [42][940/940] lr: 1.0000e-03 eta: 12:27:39 time: 0.8068 data_time: 0.0416 memory: 22701 grad_norm: 4.6828 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2863 loss: 1.2863 2022/09/05 18:19:29 - mmengine - INFO - Saving checkpoint at 42 epochs 2022/09/05 18:19:44 - mmengine - INFO - Epoch(val) [42][20/78] eta: 0:00:40 time: 0.6991 data_time: 0.5825 memory: 2247 2022/09/05 18:19:53 - mmengine - INFO - Epoch(val) [42][40/78] eta: 0:00:17 time: 0.4476 data_time: 0.3310 memory: 2247 2022/09/05 18:20:06 - mmengine - INFO - Epoch(val) [42][60/78] eta: 0:00:11 time: 0.6509 data_time: 0.5325 memory: 2247 2022/09/05 18:20:16 - mmengine - INFO - Epoch(val) [42][78/78] acc/top1: 0.6811 acc/top5: 0.8780 acc/mean1: 0.6810 2022/09/05 18:20:16 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_42.pth is removed 2022/09/05 18:20:17 - mmengine - INFO - The best checkpoint with 0.6811 acc/top1 at 43 epoch is saved to best_acc/top1_epoch_43.pth. 2022/09/05 18:20:36 - mmengine - INFO - Epoch(train) [43][20/940] lr: 1.0000e-03 eta: 12:27:26 time: 0.9745 data_time: 0.5762 memory: 22701 grad_norm: 4.3493 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1561 loss: 1.1561 2022/09/05 18:20:50 - mmengine - INFO - Epoch(train) [43][40/940] lr: 1.0000e-03 eta: 12:27:06 time: 0.6883 data_time: 0.2225 memory: 22701 grad_norm: 4.3066 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1650 loss: 1.1650 2022/09/05 18:21:07 - mmengine - INFO - Epoch(train) [43][60/940] lr: 1.0000e-03 eta: 12:26:51 time: 0.8641 data_time: 0.0785 memory: 22701 grad_norm: 4.3743 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2147 loss: 1.2147 2022/09/05 18:21:21 - mmengine - INFO - Epoch(train) [43][80/940] lr: 1.0000e-03 eta: 12:26:31 time: 0.6955 data_time: 0.0756 memory: 22701 grad_norm: 4.4211 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2168 loss: 1.2168 2022/09/05 18:21:40 - mmengine - INFO - Epoch(train) [43][100/940] lr: 1.0000e-03 eta: 12:26:17 time: 0.9125 data_time: 0.1614 memory: 22701 grad_norm: 4.3634 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.3170 loss: 1.3170 2022/09/05 18:21:54 - mmengine - INFO - Epoch(train) [43][120/940] lr: 1.0000e-03 eta: 12:25:58 time: 0.7423 data_time: 0.2254 memory: 22701 grad_norm: 4.4214 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1397 loss: 1.1397 2022/09/05 18:22:12 - mmengine - INFO - Epoch(train) [43][140/940] lr: 1.0000e-03 eta: 12:25:44 time: 0.9009 data_time: 0.3691 memory: 22701 grad_norm: 4.4635 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1647 loss: 1.1647 2022/09/05 18:22:27 - mmengine - INFO - Epoch(train) [43][160/940] lr: 1.0000e-03 eta: 12:25:25 time: 0.7422 data_time: 0.1515 memory: 22701 grad_norm: 4.3690 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3031 loss: 1.3031 2022/09/05 18:22:49 - mmengine - INFO - Epoch(train) [43][180/940] lr: 1.0000e-03 eta: 12:25:16 time: 1.0745 data_time: 0.2347 memory: 22701 grad_norm: 4.4535 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0857 loss: 1.0857 2022/09/05 18:23:05 - mmengine - INFO - Epoch(train) [43][200/940] lr: 1.0000e-03 eta: 12:24:59 time: 0.8070 data_time: 0.0517 memory: 22701 grad_norm: 4.4440 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3425 loss: 1.3425 2022/09/05 18:23:26 - mmengine - INFO - Epoch(train) [43][220/940] lr: 1.0000e-03 eta: 12:24:49 time: 1.0752 data_time: 0.0335 memory: 22701 grad_norm: 4.4429 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.2604 loss: 1.2604 2022/09/05 18:23:41 - mmengine - INFO - Epoch(train) [43][240/940] lr: 1.0000e-03 eta: 12:24:30 time: 0.7149 data_time: 0.0219 memory: 22701 grad_norm: 4.5214 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1017 loss: 1.1017 2022/09/05 18:23:57 - mmengine - INFO - Epoch(train) [43][260/940] lr: 1.0000e-03 eta: 12:24:13 time: 0.8292 data_time: 0.0289 memory: 22701 grad_norm: 4.4792 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.2830 loss: 1.2830 2022/09/05 18:24:13 - mmengine - INFO - Epoch(train) [43][280/940] lr: 1.0000e-03 eta: 12:23:56 time: 0.7695 data_time: 0.0259 memory: 22701 grad_norm: 4.3762 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1771 loss: 1.1771 2022/09/05 18:24:30 - mmengine - INFO - Epoch(train) [43][300/940] lr: 1.0000e-03 eta: 12:23:40 time: 0.8601 data_time: 0.0254 memory: 22701 grad_norm: 4.4808 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1839 loss: 1.1839 2022/09/05 18:24:44 - mmengine - INFO - Epoch(train) [43][320/940] lr: 1.0000e-03 eta: 12:23:21 time: 0.7220 data_time: 0.0194 memory: 22701 grad_norm: 4.4410 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1891 loss: 1.1891 2022/09/05 18:25:01 - mmengine - INFO - Epoch(train) [43][340/940] lr: 1.0000e-03 eta: 12:23:04 time: 0.8230 data_time: 0.0280 memory: 22701 grad_norm: 4.4488 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2827 loss: 1.2827 2022/09/05 18:25:17 - mmengine - INFO - Epoch(train) [43][360/940] lr: 1.0000e-03 eta: 12:22:47 time: 0.7998 data_time: 0.0246 memory: 22701 grad_norm: 4.5216 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1937 loss: 1.1937 2022/09/05 18:25:35 - mmengine - INFO - Epoch(train) [43][380/940] lr: 1.0000e-03 eta: 12:22:33 time: 0.9060 data_time: 0.0338 memory: 22701 grad_norm: 4.4450 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2781 loss: 1.2781 2022/09/05 18:25:52 - mmengine - INFO - Epoch(train) [43][400/940] lr: 1.0000e-03 eta: 12:22:17 time: 0.8354 data_time: 0.0266 memory: 22701 grad_norm: 4.5084 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1497 loss: 1.1497 2022/09/05 18:26:12 - mmengine - INFO - Epoch(train) [43][420/940] lr: 1.0000e-03 eta: 12:22:06 time: 1.0303 data_time: 0.0234 memory: 22701 grad_norm: 4.4261 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1510 loss: 1.1510 2022/09/05 18:26:27 - mmengine - INFO - Epoch(train) [43][440/940] lr: 1.0000e-03 eta: 12:21:48 time: 0.7470 data_time: 0.0261 memory: 22701 grad_norm: 4.4896 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0969 loss: 1.0969 2022/09/05 18:26:49 - mmengine - INFO - Epoch(train) [43][460/940] lr: 1.0000e-03 eta: 12:21:38 time: 1.0803 data_time: 0.0492 memory: 22701 grad_norm: 4.4327 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2087 loss: 1.2087 2022/09/05 18:27:03 - mmengine - INFO - Epoch(train) [43][480/940] lr: 1.0000e-03 eta: 12:21:18 time: 0.6973 data_time: 0.0274 memory: 22701 grad_norm: 4.5207 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2376 loss: 1.2376 2022/09/05 18:27:22 - mmengine - INFO - Epoch(train) [43][500/940] lr: 1.0000e-03 eta: 12:21:05 time: 0.9565 data_time: 0.0270 memory: 22701 grad_norm: 4.3170 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1939 loss: 1.1939 2022/09/05 18:27:36 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:27:37 - mmengine - INFO - Epoch(train) [43][520/940] lr: 1.0000e-03 eta: 12:20:46 time: 0.7258 data_time: 0.0333 memory: 22701 grad_norm: 4.4479 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1414 loss: 1.1414 2022/09/05 18:27:56 - mmengine - INFO - Epoch(train) [43][540/940] lr: 1.0000e-03 eta: 12:20:34 time: 0.9563 data_time: 0.0306 memory: 22701 grad_norm: 4.4747 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2644 loss: 1.2644 2022/09/05 18:28:12 - mmengine - INFO - Epoch(train) [43][560/940] lr: 1.0000e-03 eta: 12:20:18 time: 0.8414 data_time: 0.0237 memory: 22701 grad_norm: 4.4776 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2546 loss: 1.2546 2022/09/05 18:28:35 - mmengine - INFO - Epoch(train) [43][580/940] lr: 1.0000e-03 eta: 12:20:09 time: 1.1143 data_time: 0.0223 memory: 22701 grad_norm: 4.4027 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2642 loss: 1.2642 2022/09/05 18:28:52 - mmengine - INFO - Epoch(train) [43][600/940] lr: 1.0000e-03 eta: 12:19:53 time: 0.8435 data_time: 0.0198 memory: 22701 grad_norm: 4.4996 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.2920 loss: 1.2920 2022/09/05 18:29:11 - mmengine - INFO - Epoch(train) [43][620/940] lr: 1.0000e-03 eta: 12:19:41 time: 0.9894 data_time: 0.0235 memory: 22701 grad_norm: 4.5202 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2438 loss: 1.2438 2022/09/05 18:29:28 - mmengine - INFO - Epoch(train) [43][640/940] lr: 1.0000e-03 eta: 12:19:25 time: 0.8451 data_time: 0.0276 memory: 22701 grad_norm: 4.4216 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0776 loss: 1.0776 2022/09/05 18:29:48 - mmengine - INFO - Epoch(train) [43][660/940] lr: 1.0000e-03 eta: 12:19:14 time: 1.0059 data_time: 0.0311 memory: 22701 grad_norm: 4.4705 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2355 loss: 1.2355 2022/09/05 18:30:02 - mmengine - INFO - Epoch(train) [43][680/940] lr: 1.0000e-03 eta: 12:18:54 time: 0.6973 data_time: 0.0264 memory: 22701 grad_norm: 4.5031 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3277 loss: 1.3277 2022/09/05 18:30:22 - mmengine - INFO - Epoch(train) [43][700/940] lr: 1.0000e-03 eta: 12:18:42 time: 0.9869 data_time: 0.0217 memory: 22701 grad_norm: 4.5311 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2680 loss: 1.2680 2022/09/05 18:30:36 - mmengine - INFO - Epoch(train) [43][720/940] lr: 1.0000e-03 eta: 12:18:21 time: 0.6799 data_time: 0.0288 memory: 22701 grad_norm: 4.4994 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2166 loss: 1.2166 2022/09/05 18:30:52 - mmengine - INFO - Epoch(train) [43][740/940] lr: 1.0000e-03 eta: 12:18:04 time: 0.8050 data_time: 0.1168 memory: 22701 grad_norm: 4.5213 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2478 loss: 1.2478 2022/09/05 18:31:06 - mmengine - INFO - Epoch(train) [43][760/940] lr: 1.0000e-03 eta: 12:17:45 time: 0.7062 data_time: 0.0189 memory: 22701 grad_norm: 4.5210 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2048 loss: 1.2048 2022/09/05 18:31:23 - mmengine - INFO - Epoch(train) [43][780/940] lr: 1.0000e-03 eta: 12:17:29 time: 0.8501 data_time: 0.0252 memory: 22701 grad_norm: 4.4469 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3406 loss: 1.3406 2022/09/05 18:31:36 - mmengine - INFO - Epoch(train) [43][800/940] lr: 1.0000e-03 eta: 12:17:09 time: 0.6747 data_time: 0.0225 memory: 22701 grad_norm: 4.4290 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2422 loss: 1.2422 2022/09/05 18:31:52 - mmengine - INFO - Epoch(train) [43][820/940] lr: 1.0000e-03 eta: 12:16:50 time: 0.7612 data_time: 0.0306 memory: 22701 grad_norm: 4.5387 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1569 loss: 1.1569 2022/09/05 18:32:07 - mmengine - INFO - Epoch(train) [43][840/940] lr: 1.0000e-03 eta: 12:16:33 time: 0.7791 data_time: 0.0335 memory: 22701 grad_norm: 4.4899 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2219 loss: 1.2219 2022/09/05 18:32:23 - mmengine - INFO - Epoch(train) [43][860/940] lr: 1.0000e-03 eta: 12:16:15 time: 0.7636 data_time: 0.0509 memory: 22701 grad_norm: 4.5339 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 1.1374 loss: 1.1374 2022/09/05 18:32:43 - mmengine - INFO - Epoch(train) [43][880/940] lr: 1.0000e-03 eta: 12:16:03 time: 1.0167 data_time: 0.0391 memory: 22701 grad_norm: 4.4792 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2007 loss: 1.2007 2022/09/05 18:33:02 - mmengine - INFO - Epoch(train) [43][900/940] lr: 1.0000e-03 eta: 12:15:50 time: 0.9325 data_time: 0.0250 memory: 22701 grad_norm: 4.5152 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1282 loss: 1.1282 2022/09/05 18:33:22 - mmengine - INFO - Epoch(train) [43][920/940] lr: 1.0000e-03 eta: 12:15:39 time: 1.0459 data_time: 0.0312 memory: 22701 grad_norm: 4.5258 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1472 loss: 1.1472 2022/09/05 18:33:38 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:33:38 - mmengine - INFO - Epoch(train) [43][940/940] lr: 1.0000e-03 eta: 12:15:22 time: 0.7865 data_time: 0.0191 memory: 22701 grad_norm: 4.7349 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.1343 loss: 1.1343 2022/09/05 18:33:52 - mmengine - INFO - Epoch(val) [43][20/78] eta: 0:00:40 time: 0.7039 data_time: 0.5828 memory: 2247 2022/09/05 18:34:01 - mmengine - INFO - Epoch(val) [43][40/78] eta: 0:00:16 time: 0.4419 data_time: 0.3197 memory: 2247 2022/09/05 18:34:14 - mmengine - INFO - Epoch(val) [43][60/78] eta: 0:00:11 time: 0.6329 data_time: 0.5133 memory: 2247 2022/09/05 18:34:25 - mmengine - INFO - Epoch(val) [43][78/78] acc/top1: 0.6830 acc/top5: 0.8799 acc/mean1: 0.6829 2022/09/05 18:34:25 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_43.pth is removed 2022/09/05 18:34:26 - mmengine - INFO - The best checkpoint with 0.6830 acc/top1 at 44 epoch is saved to best_acc/top1_epoch_44.pth. 2022/09/05 18:34:45 - mmengine - INFO - Epoch(train) [44][20/940] lr: 1.0000e-03 eta: 12:15:09 time: 0.9691 data_time: 0.4497 memory: 22701 grad_norm: 4.4456 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1548 loss: 1.1548 2022/09/05 18:34:59 - mmengine - INFO - Epoch(train) [44][40/940] lr: 1.0000e-03 eta: 12:14:50 time: 0.7039 data_time: 0.1094 memory: 22701 grad_norm: 4.4799 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1808 loss: 1.1808 2022/09/05 18:35:16 - mmengine - INFO - Epoch(train) [44][60/940] lr: 1.0000e-03 eta: 12:14:33 time: 0.8256 data_time: 0.0322 memory: 22701 grad_norm: 4.4102 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1796 loss: 1.1796 2022/09/05 18:35:29 - mmengine - INFO - Epoch(train) [44][80/940] lr: 1.0000e-03 eta: 12:14:12 time: 0.6644 data_time: 0.0260 memory: 22701 grad_norm: 4.4067 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.0593 loss: 1.0593 2022/09/05 18:35:45 - mmengine - INFO - Epoch(train) [44][100/940] lr: 1.0000e-03 eta: 12:13:56 time: 0.8257 data_time: 0.0380 memory: 22701 grad_norm: 4.4229 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1783 loss: 1.1783 2022/09/05 18:35:59 - mmengine - INFO - Epoch(train) [44][120/940] lr: 1.0000e-03 eta: 12:13:35 time: 0.6610 data_time: 0.0216 memory: 22701 grad_norm: 4.4792 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2050 loss: 1.2050 2022/09/05 18:36:17 - mmengine - INFO - Epoch(train) [44][140/940] lr: 1.0000e-03 eta: 12:13:21 time: 0.9211 data_time: 0.0300 memory: 22701 grad_norm: 4.4506 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2191 loss: 1.2191 2022/09/05 18:36:32 - mmengine - INFO - Epoch(train) [44][160/940] lr: 1.0000e-03 eta: 12:13:03 time: 0.7638 data_time: 0.0279 memory: 22701 grad_norm: 4.4485 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1041 loss: 1.1041 2022/09/05 18:36:49 - mmengine - INFO - Epoch(train) [44][180/940] lr: 1.0000e-03 eta: 12:12:47 time: 0.8347 data_time: 0.0283 memory: 22701 grad_norm: 4.4121 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1079 loss: 1.1079 2022/09/05 18:37:05 - mmengine - INFO - Epoch(train) [44][200/940] lr: 1.0000e-03 eta: 12:12:31 time: 0.8144 data_time: 0.0284 memory: 22701 grad_norm: 4.4285 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1776 loss: 1.1776 2022/09/05 18:37:22 - mmengine - INFO - Epoch(train) [44][220/940] lr: 1.0000e-03 eta: 12:12:15 time: 0.8508 data_time: 0.0379 memory: 22701 grad_norm: 4.4466 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2645 loss: 1.2645 2022/09/05 18:37:38 - mmengine - INFO - Epoch(train) [44][240/940] lr: 1.0000e-03 eta: 12:11:57 time: 0.7871 data_time: 0.0637 memory: 22701 grad_norm: 4.4199 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1110 loss: 1.1110 2022/09/05 18:38:00 - mmengine - INFO - Epoch(train) [44][260/940] lr: 1.0000e-03 eta: 12:11:48 time: 1.1078 data_time: 0.1942 memory: 22701 grad_norm: 4.5513 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2264 loss: 1.2264 2022/09/05 18:38:15 - mmengine - INFO - Epoch(train) [44][280/940] lr: 1.0000e-03 eta: 12:11:30 time: 0.7399 data_time: 0.1029 memory: 22701 grad_norm: 4.4520 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2246 loss: 1.2246 2022/09/05 18:38:35 - mmengine - INFO - Epoch(train) [44][300/940] lr: 1.0000e-03 eta: 12:11:18 time: 1.0174 data_time: 0.1081 memory: 22701 grad_norm: 4.4876 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2925 loss: 1.2925 2022/09/05 18:38:52 - mmengine - INFO - Epoch(train) [44][320/940] lr: 1.0000e-03 eta: 12:11:02 time: 0.8322 data_time: 0.1053 memory: 22701 grad_norm: 4.4800 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1337 loss: 1.1337 2022/09/05 18:39:13 - mmengine - INFO - Epoch(train) [44][340/940] lr: 1.0000e-03 eta: 12:10:51 time: 1.0466 data_time: 0.0249 memory: 22701 grad_norm: 4.5406 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2067 loss: 1.2067 2022/09/05 18:39:28 - mmengine - INFO - Epoch(train) [44][360/940] lr: 1.0000e-03 eta: 12:10:33 time: 0.7638 data_time: 0.0255 memory: 22701 grad_norm: 4.4286 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2032 loss: 1.2032 2022/09/05 18:39:46 - mmengine - INFO - Epoch(train) [44][380/940] lr: 1.0000e-03 eta: 12:10:18 time: 0.8771 data_time: 0.0233 memory: 22701 grad_norm: 4.5807 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2615 loss: 1.2615 2022/09/05 18:40:01 - mmengine - INFO - Epoch(train) [44][400/940] lr: 1.0000e-03 eta: 12:10:00 time: 0.7565 data_time: 0.0284 memory: 22701 grad_norm: 4.4433 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2841 loss: 1.2841 2022/09/05 18:40:22 - mmengine - INFO - Epoch(train) [44][420/940] lr: 1.0000e-03 eta: 12:09:49 time: 1.0479 data_time: 0.0228 memory: 22701 grad_norm: 4.5077 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0942 loss: 1.0942 2022/09/05 18:40:39 - mmengine - INFO - Epoch(train) [44][440/940] lr: 1.0000e-03 eta: 12:09:34 time: 0.8771 data_time: 0.0308 memory: 22701 grad_norm: 4.5444 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1772 loss: 1.1772 2022/09/05 18:41:00 - mmengine - INFO - Epoch(train) [44][460/940] lr: 1.0000e-03 eta: 12:09:23 time: 1.0367 data_time: 0.0225 memory: 22701 grad_norm: 4.5024 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2392 loss: 1.2392 2022/09/05 18:41:16 - mmengine - INFO - Epoch(train) [44][480/940] lr: 1.0000e-03 eta: 12:09:06 time: 0.7839 data_time: 0.0250 memory: 22701 grad_norm: 4.4425 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2344 loss: 1.2344 2022/09/05 18:41:36 - mmengine - INFO - Epoch(train) [44][500/940] lr: 1.0000e-03 eta: 12:08:54 time: 1.0099 data_time: 0.0232 memory: 22701 grad_norm: 4.4837 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2170 loss: 1.2170 2022/09/05 18:41:57 - mmengine - INFO - Epoch(train) [44][520/940] lr: 1.0000e-03 eta: 12:08:43 time: 1.0312 data_time: 0.0204 memory: 22701 grad_norm: 4.5274 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1702 loss: 1.1702 2022/09/05 18:42:20 - mmengine - INFO - Epoch(train) [44][540/940] lr: 1.0000e-03 eta: 12:08:35 time: 1.1469 data_time: 0.0242 memory: 22701 grad_norm: 4.4706 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1425 loss: 1.1425 2022/09/05 18:42:36 - mmengine - INFO - Epoch(train) [44][560/940] lr: 1.0000e-03 eta: 12:08:18 time: 0.8170 data_time: 0.0190 memory: 22701 grad_norm: 4.4269 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1349 loss: 1.1349 2022/09/05 18:42:58 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:42:58 - mmengine - INFO - Epoch(train) [44][580/940] lr: 1.0000e-03 eta: 12:08:10 time: 1.1264 data_time: 0.0238 memory: 22701 grad_norm: 4.5217 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1572 loss: 1.1572 2022/09/05 18:43:14 - mmengine - INFO - Epoch(train) [44][600/940] lr: 1.0000e-03 eta: 12:07:52 time: 0.7719 data_time: 0.0230 memory: 22701 grad_norm: 4.5090 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1624 loss: 1.1624 2022/09/05 18:43:36 - mmengine - INFO - Epoch(train) [44][620/940] lr: 1.0000e-03 eta: 12:07:43 time: 1.1206 data_time: 0.0270 memory: 22701 grad_norm: 4.5474 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1281 loss: 1.1281 2022/09/05 18:43:54 - mmengine - INFO - Epoch(train) [44][640/940] lr: 1.0000e-03 eta: 12:07:28 time: 0.8919 data_time: 0.0204 memory: 22701 grad_norm: 4.5210 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2163 loss: 1.2163 2022/09/05 18:44:17 - mmengine - INFO - Epoch(train) [44][660/940] lr: 1.0000e-03 eta: 12:07:20 time: 1.1363 data_time: 0.0209 memory: 22701 grad_norm: 4.5346 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2856 loss: 1.2856 2022/09/05 18:44:33 - mmengine - INFO - Epoch(train) [44][680/940] lr: 1.0000e-03 eta: 12:07:03 time: 0.7965 data_time: 0.0225 memory: 22701 grad_norm: 4.4420 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2369 loss: 1.2369 2022/09/05 18:44:50 - mmengine - INFO - Epoch(train) [44][700/940] lr: 1.0000e-03 eta: 12:06:47 time: 0.8611 data_time: 0.0231 memory: 22701 grad_norm: 4.4581 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1885 loss: 1.1885 2022/09/05 18:45:04 - mmengine - INFO - Epoch(train) [44][720/940] lr: 1.0000e-03 eta: 12:06:28 time: 0.7141 data_time: 0.0256 memory: 22701 grad_norm: 4.5096 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0632 loss: 1.0632 2022/09/05 18:45:24 - mmengine - INFO - Epoch(train) [44][740/940] lr: 1.0000e-03 eta: 12:06:15 time: 0.9644 data_time: 0.0269 memory: 22701 grad_norm: 4.4387 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1661 loss: 1.1661 2022/09/05 18:45:39 - mmengine - INFO - Epoch(train) [44][760/940] lr: 1.0000e-03 eta: 12:05:56 time: 0.7521 data_time: 0.0236 memory: 22701 grad_norm: 4.4872 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2266 loss: 1.2266 2022/09/05 18:45:55 - mmengine - INFO - Epoch(train) [44][780/940] lr: 1.0000e-03 eta: 12:05:40 time: 0.8159 data_time: 0.0233 memory: 22701 grad_norm: 4.4526 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0926 loss: 1.0926 2022/09/05 18:46:09 - mmengine - INFO - Epoch(train) [44][800/940] lr: 1.0000e-03 eta: 12:05:20 time: 0.6921 data_time: 0.0310 memory: 22701 grad_norm: 4.4356 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1354 loss: 1.1354 2022/09/05 18:46:28 - mmengine - INFO - Epoch(train) [44][820/940] lr: 1.0000e-03 eta: 12:05:06 time: 0.9350 data_time: 0.0268 memory: 22701 grad_norm: 4.5499 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1123 loss: 1.1123 2022/09/05 18:46:42 - mmengine - INFO - Epoch(train) [44][840/940] lr: 1.0000e-03 eta: 12:04:48 time: 0.7467 data_time: 0.0215 memory: 22701 grad_norm: 4.5591 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1429 loss: 1.1429 2022/09/05 18:47:01 - mmengine - INFO - Epoch(train) [44][860/940] lr: 1.0000e-03 eta: 12:04:34 time: 0.9350 data_time: 0.0244 memory: 22701 grad_norm: 4.4525 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2913 loss: 1.2913 2022/09/05 18:47:17 - mmengine - INFO - Epoch(train) [44][880/940] lr: 1.0000e-03 eta: 12:04:17 time: 0.8061 data_time: 0.0188 memory: 22701 grad_norm: 4.4576 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1083 loss: 1.1083 2022/09/05 18:47:36 - mmengine - INFO - Epoch(train) [44][900/940] lr: 1.0000e-03 eta: 12:04:03 time: 0.9214 data_time: 0.0316 memory: 22701 grad_norm: 4.4580 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0913 loss: 1.0913 2022/09/05 18:47:51 - mmengine - INFO - Epoch(train) [44][920/940] lr: 1.0000e-03 eta: 12:03:45 time: 0.7644 data_time: 0.0220 memory: 22701 grad_norm: 4.4987 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2423 loss: 1.2423 2022/09/05 18:48:09 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:48:09 - mmengine - INFO - Epoch(train) [44][940/940] lr: 1.0000e-03 eta: 12:03:30 time: 0.8923 data_time: 0.0183 memory: 22701 grad_norm: 4.9188 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2173 loss: 1.2173 2022/09/05 18:48:23 - mmengine - INFO - Epoch(val) [44][20/78] eta: 0:00:40 time: 0.6979 data_time: 0.5790 memory: 2247 2022/09/05 18:48:32 - mmengine - INFO - Epoch(val) [44][40/78] eta: 0:00:16 time: 0.4308 data_time: 0.3130 memory: 2247 2022/09/05 18:48:44 - mmengine - INFO - Epoch(val) [44][60/78] eta: 0:00:11 time: 0.6463 data_time: 0.5300 memory: 2247 2022/09/05 18:48:55 - mmengine - INFO - Epoch(val) [44][78/78] acc/top1: 0.6843 acc/top5: 0.8804 acc/mean1: 0.6842 2022/09/05 18:48:55 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_44.pth is removed 2022/09/05 18:48:56 - mmengine - INFO - The best checkpoint with 0.6843 acc/top1 at 45 epoch is saved to best_acc/top1_epoch_45.pth. 2022/09/05 18:49:16 - mmengine - INFO - Epoch(train) [45][20/940] lr: 1.0000e-03 eta: 12:03:19 time: 1.0153 data_time: 0.6225 memory: 22701 grad_norm: 4.4799 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2409 loss: 1.2409 2022/09/05 18:49:30 - mmengine - INFO - Epoch(train) [45][40/940] lr: 1.0000e-03 eta: 12:02:58 time: 0.6753 data_time: 0.3131 memory: 22701 grad_norm: 4.5522 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1118 loss: 1.1118 2022/09/05 18:49:50 - mmengine - INFO - Epoch(train) [45][60/940] lr: 1.0000e-03 eta: 12:02:46 time: 0.9890 data_time: 0.6086 memory: 22701 grad_norm: 4.5621 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1263 loss: 1.1263 2022/09/05 18:50:05 - mmengine - INFO - Epoch(train) [45][80/940] lr: 1.0000e-03 eta: 12:02:28 time: 0.7612 data_time: 0.3809 memory: 22701 grad_norm: 4.4396 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2076 loss: 1.2076 2022/09/05 18:50:26 - mmengine - INFO - Epoch(train) [45][100/940] lr: 1.0000e-03 eta: 12:02:18 time: 1.0708 data_time: 0.5932 memory: 22701 grad_norm: 4.4846 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1208 loss: 1.1208 2022/09/05 18:50:48 - mmengine - INFO - Epoch(train) [45][120/940] lr: 1.0000e-03 eta: 12:02:08 time: 1.0903 data_time: 0.7044 memory: 22701 grad_norm: 4.4690 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1255 loss: 1.1255 2022/09/05 18:51:06 - mmengine - INFO - Epoch(train) [45][140/940] lr: 1.0000e-03 eta: 12:01:53 time: 0.9042 data_time: 0.4990 memory: 22701 grad_norm: 4.4731 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2063 loss: 1.2063 2022/09/05 18:51:20 - mmengine - INFO - Epoch(train) [45][160/940] lr: 1.0000e-03 eta: 12:01:34 time: 0.7007 data_time: 0.2937 memory: 22701 grad_norm: 4.5138 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2169 loss: 1.2169 2022/09/05 18:51:37 - mmengine - INFO - Epoch(train) [45][180/940] lr: 1.0000e-03 eta: 12:01:17 time: 0.8238 data_time: 0.4210 memory: 22701 grad_norm: 4.5140 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2037 loss: 1.2037 2022/09/05 18:51:52 - mmengine - INFO - Epoch(train) [45][200/940] lr: 1.0000e-03 eta: 12:00:59 time: 0.7436 data_time: 0.3445 memory: 22701 grad_norm: 4.6106 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2000 loss: 1.2000 2022/09/05 18:52:08 - mmengine - INFO - Epoch(train) [45][220/940] lr: 1.0000e-03 eta: 12:00:41 time: 0.8001 data_time: 0.3919 memory: 22701 grad_norm: 4.4533 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1605 loss: 1.1605 2022/09/05 18:52:22 - mmengine - INFO - Epoch(train) [45][240/940] lr: 1.0000e-03 eta: 12:00:22 time: 0.7029 data_time: 0.2928 memory: 22701 grad_norm: 4.5590 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2378 loss: 1.2378 2022/09/05 18:52:40 - mmengine - INFO - Epoch(train) [45][260/940] lr: 1.0000e-03 eta: 12:00:07 time: 0.8954 data_time: 0.4807 memory: 22701 grad_norm: 4.5353 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2658 loss: 1.2658 2022/09/05 18:52:55 - mmengine - INFO - Epoch(train) [45][280/940] lr: 1.0000e-03 eta: 11:59:49 time: 0.7588 data_time: 0.2895 memory: 22701 grad_norm: 4.4983 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1798 loss: 1.1798 2022/09/05 18:53:18 - mmengine - INFO - Epoch(train) [45][300/940] lr: 1.0000e-03 eta: 11:59:40 time: 1.1428 data_time: 0.6913 memory: 22701 grad_norm: 4.5644 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2426 loss: 1.2426 2022/09/05 18:53:34 - mmengine - INFO - Epoch(train) [45][320/940] lr: 1.0000e-03 eta: 11:59:23 time: 0.7983 data_time: 0.4162 memory: 22701 grad_norm: 4.5783 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1422 loss: 1.1422 2022/09/05 18:53:56 - mmengine - INFO - Epoch(train) [45][340/940] lr: 1.0000e-03 eta: 11:59:15 time: 1.1342 data_time: 0.7337 memory: 22701 grad_norm: 4.4948 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1207 loss: 1.1207 2022/09/05 18:54:13 - mmengine - INFO - Epoch(train) [45][360/940] lr: 1.0000e-03 eta: 11:58:58 time: 0.8173 data_time: 0.4200 memory: 22701 grad_norm: 4.5582 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1856 loss: 1.1856 2022/09/05 18:54:33 - mmengine - INFO - Epoch(train) [45][380/940] lr: 1.0000e-03 eta: 11:58:46 time: 1.0162 data_time: 0.6342 memory: 22701 grad_norm: 4.5761 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2601 loss: 1.2601 2022/09/05 18:54:48 - mmengine - INFO - Epoch(train) [45][400/940] lr: 1.0000e-03 eta: 11:58:28 time: 0.7583 data_time: 0.3606 memory: 22701 grad_norm: 4.6255 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1213 loss: 1.1213 2022/09/05 18:55:07 - mmengine - INFO - Epoch(train) [45][420/940] lr: 1.0000e-03 eta: 11:58:15 time: 0.9557 data_time: 0.5455 memory: 22701 grad_norm: 4.4686 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0635 loss: 1.0635 2022/09/05 18:55:22 - mmengine - INFO - Epoch(train) [45][440/940] lr: 1.0000e-03 eta: 11:57:56 time: 0.7186 data_time: 0.3091 memory: 22701 grad_norm: 4.5136 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2054 loss: 1.2054 2022/09/05 18:55:40 - mmengine - INFO - Epoch(train) [45][460/940] lr: 1.0000e-03 eta: 11:57:41 time: 0.9092 data_time: 0.5066 memory: 22701 grad_norm: 4.5203 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1701 loss: 1.1701 2022/09/05 18:55:55 - mmengine - INFO - Epoch(train) [45][480/940] lr: 1.0000e-03 eta: 11:57:23 time: 0.7692 data_time: 0.3691 memory: 22701 grad_norm: 4.4328 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1496 loss: 1.1496 2022/09/05 18:56:20 - mmengine - INFO - Epoch(train) [45][500/940] lr: 1.0000e-03 eta: 11:57:17 time: 1.2481 data_time: 0.6334 memory: 22701 grad_norm: 4.4811 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1983 loss: 1.1983 2022/09/05 18:56:38 - mmengine - INFO - Epoch(train) [45][520/940] lr: 1.0000e-03 eta: 11:57:02 time: 0.8734 data_time: 0.3899 memory: 22701 grad_norm: 4.5970 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1919 loss: 1.1919 2022/09/05 18:57:00 - mmengine - INFO - Epoch(train) [45][540/940] lr: 1.0000e-03 eta: 11:56:53 time: 1.1254 data_time: 0.4961 memory: 22701 grad_norm: 4.5034 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1554 loss: 1.1554 2022/09/05 18:57:15 - mmengine - INFO - Epoch(train) [45][560/940] lr: 1.0000e-03 eta: 11:56:35 time: 0.7542 data_time: 0.3717 memory: 22701 grad_norm: 4.5611 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0809 loss: 1.0809 2022/09/05 18:57:34 - mmengine - INFO - Epoch(train) [45][580/940] lr: 1.0000e-03 eta: 11:56:21 time: 0.9375 data_time: 0.5158 memory: 22701 grad_norm: 4.5421 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1820 loss: 1.1820 2022/09/05 18:57:48 - mmengine - INFO - Epoch(train) [45][600/940] lr: 1.0000e-03 eta: 11:56:01 time: 0.6987 data_time: 0.2945 memory: 22701 grad_norm: 4.6155 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1753 loss: 1.1753 2022/09/05 18:58:06 - mmengine - INFO - Epoch(train) [45][620/940] lr: 1.0000e-03 eta: 11:55:47 time: 0.9111 data_time: 0.5077 memory: 22701 grad_norm: 4.5933 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2011 loss: 1.2011 2022/09/05 18:58:21 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 18:58:21 - mmengine - INFO - Epoch(train) [45][640/940] lr: 1.0000e-03 eta: 11:55:28 time: 0.7330 data_time: 0.3357 memory: 22701 grad_norm: 4.6185 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2167 loss: 1.2167 2022/09/05 18:58:38 - mmengine - INFO - Epoch(train) [45][660/940] lr: 1.0000e-03 eta: 11:55:13 time: 0.8824 data_time: 0.4989 memory: 22701 grad_norm: 4.5745 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2253 loss: 1.2253 2022/09/05 18:58:53 - mmengine - INFO - Epoch(train) [45][680/940] lr: 1.0000e-03 eta: 11:54:54 time: 0.7374 data_time: 0.3410 memory: 22701 grad_norm: 4.5989 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1298 loss: 1.1298 2022/09/05 18:59:11 - mmengine - INFO - Epoch(train) [45][700/940] lr: 1.0000e-03 eta: 11:54:39 time: 0.8890 data_time: 0.5063 memory: 22701 grad_norm: 4.5163 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1239 loss: 1.1239 2022/09/05 18:59:25 - mmengine - INFO - Epoch(train) [45][720/940] lr: 1.0000e-03 eta: 11:54:19 time: 0.6813 data_time: 0.2970 memory: 22701 grad_norm: 4.5262 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2025 loss: 1.2025 2022/09/05 18:59:44 - mmengine - INFO - Epoch(train) [45][740/940] lr: 1.0000e-03 eta: 11:54:06 time: 0.9584 data_time: 0.5662 memory: 22701 grad_norm: 4.5207 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0437 loss: 1.0437 2022/09/05 18:59:58 - mmengine - INFO - Epoch(train) [45][760/940] lr: 1.0000e-03 eta: 11:53:46 time: 0.7016 data_time: 0.3055 memory: 22701 grad_norm: 4.5185 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1077 loss: 1.1077 2022/09/05 19:00:14 - mmengine - INFO - Epoch(train) [45][780/940] lr: 1.0000e-03 eta: 11:53:29 time: 0.7922 data_time: 0.3850 memory: 22701 grad_norm: 4.5395 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1730 loss: 1.1730 2022/09/05 19:00:29 - mmengine - INFO - Epoch(train) [45][800/940] lr: 1.0000e-03 eta: 11:53:12 time: 0.7833 data_time: 0.3565 memory: 22701 grad_norm: 4.5742 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2006 loss: 1.2006 2022/09/05 19:00:48 - mmengine - INFO - Epoch(train) [45][820/940] lr: 1.0000e-03 eta: 11:52:58 time: 0.9325 data_time: 0.5199 memory: 22701 grad_norm: 4.4778 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0436 loss: 1.0436 2022/09/05 19:01:03 - mmengine - INFO - Epoch(train) [45][840/940] lr: 1.0000e-03 eta: 11:52:39 time: 0.7307 data_time: 0.2899 memory: 22701 grad_norm: 4.5880 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3290 loss: 1.3290 2022/09/05 19:01:20 - mmengine - INFO - Epoch(train) [45][860/940] lr: 1.0000e-03 eta: 11:52:24 time: 0.8760 data_time: 0.4224 memory: 22701 grad_norm: 4.5162 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1892 loss: 1.1892 2022/09/05 19:01:35 - mmengine - INFO - Epoch(train) [45][880/940] lr: 1.0000e-03 eta: 11:52:05 time: 0.7399 data_time: 0.3315 memory: 22701 grad_norm: 4.5337 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1265 loss: 1.1265 2022/09/05 19:01:52 - mmengine - INFO - Epoch(train) [45][900/940] lr: 1.0000e-03 eta: 11:51:49 time: 0.8606 data_time: 0.4147 memory: 22701 grad_norm: 4.4908 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0650 loss: 1.0650 2022/09/05 19:02:06 - mmengine - INFO - Epoch(train) [45][920/940] lr: 1.0000e-03 eta: 11:51:30 time: 0.7075 data_time: 0.3074 memory: 22701 grad_norm: 4.5388 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1915 loss: 1.1915 2022/09/05 19:02:24 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:02:24 - mmengine - INFO - Epoch(train) [45][940/940] lr: 1.0000e-03 eta: 11:51:14 time: 0.8671 data_time: 0.5001 memory: 22701 grad_norm: 4.8615 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1319 loss: 1.1319 2022/09/05 19:02:24 - mmengine - INFO - Saving checkpoint at 45 epochs 2022/09/05 19:02:39 - mmengine - INFO - Epoch(val) [45][20/78] eta: 0:00:41 time: 0.7073 data_time: 0.5908 memory: 2247 2022/09/05 19:02:49 - mmengine - INFO - Epoch(val) [45][40/78] eta: 0:00:17 time: 0.4615 data_time: 0.3453 memory: 2247 2022/09/05 19:03:02 - mmengine - INFO - Epoch(val) [45][60/78] eta: 0:00:11 time: 0.6439 data_time: 0.5126 memory: 2247 2022/09/05 19:03:11 - mmengine - INFO - Epoch(val) [45][78/78] acc/top1: 0.6860 acc/top5: 0.8796 acc/mean1: 0.6859 2022/09/05 19:03:11 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_45.pth is removed 2022/09/05 19:03:12 - mmengine - INFO - The best checkpoint with 0.6860 acc/top1 at 46 epoch is saved to best_acc/top1_epoch_46.pth. 2022/09/05 19:03:32 - mmengine - INFO - Epoch(train) [46][20/940] lr: 1.0000e-03 eta: 11:51:03 time: 1.0206 data_time: 0.5650 memory: 22701 grad_norm: 4.5767 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1020 loss: 1.1020 2022/09/05 19:03:47 - mmengine - INFO - Epoch(train) [46][40/940] lr: 1.0000e-03 eta: 11:50:44 time: 0.7212 data_time: 0.2459 memory: 22701 grad_norm: 4.4492 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1967 loss: 1.1967 2022/09/05 19:04:06 - mmengine - INFO - Epoch(train) [46][60/940] lr: 1.0000e-03 eta: 11:50:30 time: 0.9620 data_time: 0.1445 memory: 22701 grad_norm: 4.5413 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1339 loss: 1.1339 2022/09/05 19:04:21 - mmengine - INFO - Epoch(train) [46][80/940] lr: 1.0000e-03 eta: 11:50:12 time: 0.7444 data_time: 0.0670 memory: 22701 grad_norm: 4.5982 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2814 loss: 1.2814 2022/09/05 19:04:38 - mmengine - INFO - Epoch(train) [46][100/940] lr: 1.0000e-03 eta: 11:49:56 time: 0.8605 data_time: 0.0246 memory: 22701 grad_norm: 4.5775 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0446 loss: 1.0446 2022/09/05 19:04:52 - mmengine - INFO - Epoch(train) [46][120/940] lr: 1.0000e-03 eta: 11:49:37 time: 0.7081 data_time: 0.0234 memory: 22701 grad_norm: 4.6377 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2770 loss: 1.2770 2022/09/05 19:05:10 - mmengine - INFO - Epoch(train) [46][140/940] lr: 1.0000e-03 eta: 11:49:22 time: 0.8756 data_time: 0.0220 memory: 22701 grad_norm: 4.6358 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0505 loss: 1.0505 2022/09/05 19:05:28 - mmengine - INFO - Epoch(train) [46][160/940] lr: 1.0000e-03 eta: 11:49:07 time: 0.9026 data_time: 0.0484 memory: 22701 grad_norm: 4.5692 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1680 loss: 1.1680 2022/09/05 19:05:45 - mmengine - INFO - Epoch(train) [46][180/940] lr: 1.0000e-03 eta: 11:48:51 time: 0.8435 data_time: 0.0259 memory: 22701 grad_norm: 4.3912 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1658 loss: 1.1658 2022/09/05 19:06:01 - mmengine - INFO - Epoch(train) [46][200/940] lr: 1.0000e-03 eta: 11:48:34 time: 0.8240 data_time: 0.0262 memory: 22701 grad_norm: 4.4549 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2136 loss: 1.2136 2022/09/05 19:06:22 - mmengine - INFO - Epoch(train) [46][220/940] lr: 1.0000e-03 eta: 11:48:22 time: 1.0136 data_time: 0.0304 memory: 22701 grad_norm: 4.5455 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1180 loss: 1.1180 2022/09/05 19:06:36 - mmengine - INFO - Epoch(train) [46][240/940] lr: 1.0000e-03 eta: 11:48:04 time: 0.7446 data_time: 0.0287 memory: 22701 grad_norm: 4.5903 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1860 loss: 1.1860 2022/09/05 19:06:56 - mmengine - INFO - Epoch(train) [46][260/940] lr: 1.0000e-03 eta: 11:47:52 time: 0.9954 data_time: 0.0249 memory: 22701 grad_norm: 4.4797 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1309 loss: 1.1309 2022/09/05 19:07:13 - mmengine - INFO - Epoch(train) [46][280/940] lr: 1.0000e-03 eta: 11:47:35 time: 0.8128 data_time: 0.0258 memory: 22701 grad_norm: 4.4918 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0322 loss: 1.0322 2022/09/05 19:07:30 - mmengine - INFO - Epoch(train) [46][300/940] lr: 1.0000e-03 eta: 11:47:20 time: 0.8839 data_time: 0.0262 memory: 22701 grad_norm: 4.5428 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1024 loss: 1.1024 2022/09/05 19:07:47 - mmengine - INFO - Epoch(train) [46][320/940] lr: 1.0000e-03 eta: 11:47:04 time: 0.8547 data_time: 0.0281 memory: 22701 grad_norm: 4.5592 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1076 loss: 1.1076 2022/09/05 19:08:06 - mmengine - INFO - Epoch(train) [46][340/940] lr: 1.0000e-03 eta: 11:46:50 time: 0.9180 data_time: 0.0263 memory: 22701 grad_norm: 4.5158 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0745 loss: 1.0745 2022/09/05 19:08:23 - mmengine - INFO - Epoch(train) [46][360/940] lr: 1.0000e-03 eta: 11:46:34 time: 0.8548 data_time: 0.0294 memory: 22701 grad_norm: 4.6425 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2152 loss: 1.2152 2022/09/05 19:08:42 - mmengine - INFO - Epoch(train) [46][380/940] lr: 1.0000e-03 eta: 11:46:20 time: 0.9608 data_time: 0.0333 memory: 22701 grad_norm: 4.4744 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0827 loss: 1.0827 2022/09/05 19:08:57 - mmengine - INFO - Epoch(train) [46][400/940] lr: 1.0000e-03 eta: 11:46:02 time: 0.7629 data_time: 0.0241 memory: 22701 grad_norm: 4.6324 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2492 loss: 1.2492 2022/09/05 19:09:16 - mmengine - INFO - Epoch(train) [46][420/940] lr: 1.0000e-03 eta: 11:45:48 time: 0.9062 data_time: 0.0309 memory: 22701 grad_norm: 4.5585 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1506 loss: 1.1506 2022/09/05 19:09:35 - mmengine - INFO - Epoch(train) [46][440/940] lr: 1.0000e-03 eta: 11:45:35 time: 0.9756 data_time: 0.0311 memory: 22701 grad_norm: 4.5764 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1271 loss: 1.1271 2022/09/05 19:09:50 - mmengine - INFO - Epoch(train) [46][460/940] lr: 1.0000e-03 eta: 11:45:16 time: 0.7420 data_time: 0.0332 memory: 22701 grad_norm: 4.5070 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3653 loss: 1.3653 2022/09/05 19:10:06 - mmengine - INFO - Epoch(train) [46][480/940] lr: 1.0000e-03 eta: 11:45:00 time: 0.8178 data_time: 0.0425 memory: 22701 grad_norm: 4.5112 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1051 loss: 1.1051 2022/09/05 19:10:22 - mmengine - INFO - Epoch(train) [46][500/940] lr: 1.0000e-03 eta: 11:44:42 time: 0.7950 data_time: 0.0256 memory: 22701 grad_norm: 4.5679 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1184 loss: 1.1184 2022/09/05 19:10:37 - mmengine - INFO - Epoch(train) [46][520/940] lr: 1.0000e-03 eta: 11:44:24 time: 0.7336 data_time: 0.0275 memory: 22701 grad_norm: 4.5968 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1046 loss: 1.1046 2022/09/05 19:10:52 - mmengine - INFO - Epoch(train) [46][540/940] lr: 1.0000e-03 eta: 11:44:06 time: 0.7855 data_time: 0.0254 memory: 22701 grad_norm: 4.5875 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1333 loss: 1.1333 2022/09/05 19:11:08 - mmengine - INFO - Epoch(train) [46][560/940] lr: 1.0000e-03 eta: 11:43:48 time: 0.7622 data_time: 0.0299 memory: 22701 grad_norm: 4.5181 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2361 loss: 1.2361 2022/09/05 19:11:28 - mmengine - INFO - Epoch(train) [46][580/940] lr: 1.0000e-03 eta: 11:43:36 time: 1.0252 data_time: 0.0258 memory: 22701 grad_norm: 4.6115 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1633 loss: 1.1633 2022/09/05 19:11:45 - mmengine - INFO - Epoch(train) [46][600/940] lr: 1.0000e-03 eta: 11:43:20 time: 0.8348 data_time: 0.0204 memory: 22701 grad_norm: 4.5458 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1931 loss: 1.1931 2022/09/05 19:12:03 - mmengine - INFO - Epoch(train) [46][620/940] lr: 1.0000e-03 eta: 11:43:05 time: 0.8836 data_time: 0.0409 memory: 22701 grad_norm: 4.5536 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0970 loss: 1.0970 2022/09/05 19:12:16 - mmengine - INFO - Epoch(train) [46][640/940] lr: 1.0000e-03 eta: 11:42:45 time: 0.6913 data_time: 0.0260 memory: 22701 grad_norm: 4.5483 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1147 loss: 1.1147 2022/09/05 19:12:33 - mmengine - INFO - Epoch(train) [46][660/940] lr: 1.0000e-03 eta: 11:42:29 time: 0.8396 data_time: 0.0257 memory: 22701 grad_norm: 4.5498 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2160 loss: 1.2160 2022/09/05 19:12:47 - mmengine - INFO - Epoch(train) [46][680/940] lr: 1.0000e-03 eta: 11:42:09 time: 0.6912 data_time: 0.0319 memory: 22701 grad_norm: 4.4841 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1250 loss: 1.1250 2022/09/05 19:13:06 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:13:06 - mmengine - INFO - Epoch(train) [46][700/940] lr: 1.0000e-03 eta: 11:41:56 time: 0.9509 data_time: 0.0207 memory: 22701 grad_norm: 4.5492 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1270 loss: 1.1270 2022/09/05 19:13:24 - mmengine - INFO - Epoch(train) [46][720/940] lr: 1.0000e-03 eta: 11:41:41 time: 0.9088 data_time: 0.0253 memory: 22701 grad_norm: 4.5225 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0654 loss: 1.0654 2022/09/05 19:13:42 - mmengine - INFO - Epoch(train) [46][740/940] lr: 1.0000e-03 eta: 11:41:27 time: 0.9068 data_time: 0.0229 memory: 22701 grad_norm: 4.5541 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1554 loss: 1.1554 2022/09/05 19:13:56 - mmengine - INFO - Epoch(train) [46][760/940] lr: 1.0000e-03 eta: 11:41:07 time: 0.6749 data_time: 0.0270 memory: 22701 grad_norm: 4.5772 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1179 loss: 1.1179 2022/09/05 19:14:14 - mmengine - INFO - Epoch(train) [46][780/940] lr: 1.0000e-03 eta: 11:40:52 time: 0.9074 data_time: 0.0962 memory: 22701 grad_norm: 4.5924 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1443 loss: 1.1443 2022/09/05 19:14:30 - mmengine - INFO - Epoch(train) [46][800/940] lr: 1.0000e-03 eta: 11:40:35 time: 0.7899 data_time: 0.2159 memory: 22701 grad_norm: 4.4825 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1840 loss: 1.1840 2022/09/05 19:14:49 - mmengine - INFO - Epoch(train) [46][820/940] lr: 1.0000e-03 eta: 11:40:21 time: 0.9538 data_time: 0.0991 memory: 22701 grad_norm: 4.5445 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1693 loss: 1.1693 2022/09/05 19:15:05 - mmengine - INFO - Epoch(train) [46][840/940] lr: 1.0000e-03 eta: 11:40:04 time: 0.7920 data_time: 0.0490 memory: 22701 grad_norm: 4.5921 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1026 loss: 1.1026 2022/09/05 19:15:22 - mmengine - INFO - Epoch(train) [46][860/940] lr: 1.0000e-03 eta: 11:39:49 time: 0.8791 data_time: 0.1040 memory: 22701 grad_norm: 4.5821 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2270 loss: 1.2270 2022/09/05 19:15:37 - mmengine - INFO - Epoch(train) [46][880/940] lr: 1.0000e-03 eta: 11:39:30 time: 0.7392 data_time: 0.1352 memory: 22701 grad_norm: 4.5829 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1388 loss: 1.1388 2022/09/05 19:15:57 - mmengine - INFO - Epoch(train) [46][900/940] lr: 1.0000e-03 eta: 11:39:17 time: 0.9687 data_time: 0.0227 memory: 22701 grad_norm: 4.4810 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1155 loss: 1.1155 2022/09/05 19:16:12 - mmengine - INFO - Epoch(train) [46][920/940] lr: 1.0000e-03 eta: 11:38:59 time: 0.7513 data_time: 0.0264 memory: 22701 grad_norm: 4.6223 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2763 loss: 1.2763 2022/09/05 19:16:25 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:16:25 - mmengine - INFO - Epoch(train) [46][940/940] lr: 1.0000e-03 eta: 11:38:38 time: 0.6725 data_time: 0.0181 memory: 22701 grad_norm: 4.7278 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.0985 loss: 1.0985 2022/09/05 19:16:39 - mmengine - INFO - Epoch(val) [46][20/78] eta: 0:00:39 time: 0.6860 data_time: 0.5653 memory: 2247 2022/09/05 19:16:48 - mmengine - INFO - Epoch(val) [46][40/78] eta: 0:00:17 time: 0.4499 data_time: 0.3310 memory: 2247 2022/09/05 19:17:01 - mmengine - INFO - Epoch(val) [46][60/78] eta: 0:00:11 time: 0.6612 data_time: 0.5415 memory: 2247 2022/09/05 19:17:11 - mmengine - INFO - Epoch(val) [46][78/78] acc/top1: 0.6848 acc/top5: 0.8816 acc/mean1: 0.6847 2022/09/05 19:17:34 - mmengine - INFO - Epoch(train) [47][20/940] lr: 1.0000e-03 eta: 11:38:29 time: 1.1274 data_time: 0.4997 memory: 22701 grad_norm: 4.5501 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2167 loss: 1.2167 2022/09/05 19:17:47 - mmengine - INFO - Epoch(train) [47][40/940] lr: 1.0000e-03 eta: 11:38:09 time: 0.6643 data_time: 0.0203 memory: 22701 grad_norm: 4.5631 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.0942 loss: 1.0942 2022/09/05 19:18:03 - mmengine - INFO - Epoch(train) [47][60/940] lr: 1.0000e-03 eta: 11:37:52 time: 0.8143 data_time: 0.0323 memory: 22701 grad_norm: 4.5408 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3329 loss: 1.3329 2022/09/05 19:18:16 - mmengine - INFO - Epoch(train) [47][80/940] lr: 1.0000e-03 eta: 11:37:31 time: 0.6448 data_time: 0.0619 memory: 22701 grad_norm: 4.4028 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1938 loss: 1.1938 2022/09/05 19:18:32 - mmengine - INFO - Epoch(train) [47][100/940] lr: 1.0000e-03 eta: 11:37:14 time: 0.7990 data_time: 0.1105 memory: 22701 grad_norm: 4.5955 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1090 loss: 1.1090 2022/09/05 19:18:46 - mmengine - INFO - Epoch(train) [47][120/940] lr: 1.0000e-03 eta: 11:36:54 time: 0.6960 data_time: 0.1544 memory: 22701 grad_norm: 4.4454 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9319 loss: 0.9319 2022/09/05 19:19:03 - mmengine - INFO - Epoch(train) [47][140/940] lr: 1.0000e-03 eta: 11:36:39 time: 0.8587 data_time: 0.2439 memory: 22701 grad_norm: 4.6500 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2480 loss: 1.2480 2022/09/05 19:19:17 - mmengine - INFO - Epoch(train) [47][160/940] lr: 1.0000e-03 eta: 11:36:18 time: 0.6619 data_time: 0.1736 memory: 22701 grad_norm: 4.5688 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1081 loss: 1.1081 2022/09/05 19:19:34 - mmengine - INFO - Epoch(train) [47][180/940] lr: 1.0000e-03 eta: 11:36:03 time: 0.8625 data_time: 0.4246 memory: 22701 grad_norm: 4.6407 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1566 loss: 1.1566 2022/09/05 19:19:48 - mmengine - INFO - Epoch(train) [47][200/940] lr: 1.0000e-03 eta: 11:35:44 time: 0.7251 data_time: 0.3464 memory: 22701 grad_norm: 4.4580 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2559 loss: 1.2559 2022/09/05 19:20:07 - mmengine - INFO - Epoch(train) [47][220/940] lr: 1.0000e-03 eta: 11:35:30 time: 0.9372 data_time: 0.4197 memory: 22701 grad_norm: 4.5779 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0816 loss: 1.0816 2022/09/05 19:20:22 - mmengine - INFO - Epoch(train) [47][240/940] lr: 1.0000e-03 eta: 11:35:12 time: 0.7657 data_time: 0.0540 memory: 22701 grad_norm: 4.6317 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2352 loss: 1.2352 2022/09/05 19:20:42 - mmengine - INFO - Epoch(train) [47][260/940] lr: 1.0000e-03 eta: 11:34:59 time: 0.9953 data_time: 0.0269 memory: 22701 grad_norm: 4.4473 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0890 loss: 1.0890 2022/09/05 19:20:58 - mmengine - INFO - Epoch(train) [47][280/940] lr: 1.0000e-03 eta: 11:34:41 time: 0.7635 data_time: 0.0252 memory: 22701 grad_norm: 4.5500 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0783 loss: 1.0783 2022/09/05 19:21:15 - mmengine - INFO - Epoch(train) [47][300/940] lr: 1.0000e-03 eta: 11:34:26 time: 0.8828 data_time: 0.0264 memory: 22701 grad_norm: 4.6738 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1277 loss: 1.1277 2022/09/05 19:21:31 - mmengine - INFO - Epoch(train) [47][320/940] lr: 1.0000e-03 eta: 11:34:08 time: 0.7665 data_time: 0.0260 memory: 22701 grad_norm: 4.6219 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0911 loss: 1.0911 2022/09/05 19:21:49 - mmengine - INFO - Epoch(train) [47][340/940] lr: 1.0000e-03 eta: 11:33:55 time: 0.9446 data_time: 0.0258 memory: 22701 grad_norm: 4.5904 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1064 loss: 1.1064 2022/09/05 19:22:02 - mmengine - INFO - Epoch(train) [47][360/940] lr: 1.0000e-03 eta: 11:33:34 time: 0.6431 data_time: 0.0337 memory: 22701 grad_norm: 4.6135 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2321 loss: 1.2321 2022/09/05 19:22:22 - mmengine - INFO - Epoch(train) [47][380/940] lr: 1.0000e-03 eta: 11:33:21 time: 1.0011 data_time: 0.0268 memory: 22701 grad_norm: 4.6639 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1039 loss: 1.1039 2022/09/05 19:22:38 - mmengine - INFO - Epoch(train) [47][400/940] lr: 1.0000e-03 eta: 11:33:04 time: 0.7857 data_time: 0.0220 memory: 22701 grad_norm: 4.5480 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1250 loss: 1.1250 2022/09/05 19:22:57 - mmengine - INFO - Epoch(train) [47][420/940] lr: 1.0000e-03 eta: 11:32:50 time: 0.9528 data_time: 0.0255 memory: 22701 grad_norm: 4.6619 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1037 loss: 1.1037 2022/09/05 19:23:12 - mmengine - INFO - Epoch(train) [47][440/940] lr: 1.0000e-03 eta: 11:32:32 time: 0.7448 data_time: 0.0345 memory: 22701 grad_norm: 4.5863 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2180 loss: 1.2180 2022/09/05 19:23:27 - mmengine - INFO - Epoch(train) [47][460/940] lr: 1.0000e-03 eta: 11:32:14 time: 0.7537 data_time: 0.0282 memory: 22701 grad_norm: 4.6316 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0802 loss: 1.0802 2022/09/05 19:23:46 - mmengine - INFO - Epoch(train) [47][480/940] lr: 1.0000e-03 eta: 11:32:00 time: 0.9494 data_time: 0.0188 memory: 22701 grad_norm: 4.6873 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1735 loss: 1.1735 2022/09/05 19:24:06 - mmengine - INFO - Epoch(train) [47][500/940] lr: 1.0000e-03 eta: 11:31:47 time: 0.9905 data_time: 0.0232 memory: 22701 grad_norm: 4.5089 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1376 loss: 1.1376 2022/09/05 19:24:24 - mmengine - INFO - Epoch(train) [47][520/940] lr: 1.0000e-03 eta: 11:31:33 time: 0.8970 data_time: 0.0173 memory: 22701 grad_norm: 4.6977 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1935 loss: 1.1935 2022/09/05 19:24:45 - mmengine - INFO - Epoch(train) [47][540/940] lr: 1.0000e-03 eta: 11:31:22 time: 1.0823 data_time: 0.0229 memory: 22701 grad_norm: 4.5793 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0945 loss: 1.0945 2022/09/05 19:25:01 - mmengine - INFO - Epoch(train) [47][560/940] lr: 1.0000e-03 eta: 11:31:04 time: 0.7551 data_time: 0.0208 memory: 22701 grad_norm: 4.5421 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1882 loss: 1.1882 2022/09/05 19:25:19 - mmengine - INFO - Epoch(train) [47][580/940] lr: 1.0000e-03 eta: 11:30:50 time: 0.9335 data_time: 0.0274 memory: 22701 grad_norm: 4.5179 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0835 loss: 1.0835 2022/09/05 19:25:35 - mmengine - INFO - Epoch(train) [47][600/940] lr: 1.0000e-03 eta: 11:30:33 time: 0.8087 data_time: 0.0223 memory: 22701 grad_norm: 4.6844 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2430 loss: 1.2430 2022/09/05 19:25:55 - mmengine - INFO - Epoch(train) [47][620/940] lr: 1.0000e-03 eta: 11:30:20 time: 0.9946 data_time: 0.0262 memory: 22701 grad_norm: 4.5500 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1094 loss: 1.1094 2022/09/05 19:26:11 - mmengine - INFO - Epoch(train) [47][640/940] lr: 1.0000e-03 eta: 11:30:03 time: 0.7930 data_time: 0.0194 memory: 22701 grad_norm: 4.5426 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2148 loss: 1.2148 2022/09/05 19:26:30 - mmengine - INFO - Epoch(train) [47][660/940] lr: 1.0000e-03 eta: 11:29:49 time: 0.9445 data_time: 0.0232 memory: 22701 grad_norm: 4.6197 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1801 loss: 1.1801 2022/09/05 19:26:45 - mmengine - INFO - Epoch(train) [47][680/940] lr: 1.0000e-03 eta: 11:29:30 time: 0.7298 data_time: 0.0244 memory: 22701 grad_norm: 4.6612 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 1.1518 loss: 1.1518 2022/09/05 19:27:03 - mmengine - INFO - Epoch(train) [47][700/940] lr: 1.0000e-03 eta: 11:29:15 time: 0.8977 data_time: 0.0255 memory: 22701 grad_norm: 4.5975 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2441 loss: 1.2441 2022/09/05 19:27:20 - mmengine - INFO - Epoch(train) [47][720/940] lr: 1.0000e-03 eta: 11:29:00 time: 0.8654 data_time: 0.0237 memory: 22701 grad_norm: 4.5947 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0148 loss: 1.0148 2022/09/05 19:27:36 - mmengine - INFO - Epoch(train) [47][740/940] lr: 1.0000e-03 eta: 11:28:43 time: 0.7981 data_time: 0.0749 memory: 22701 grad_norm: 4.6232 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1804 loss: 1.1804 2022/09/05 19:27:50 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:27:50 - mmengine - INFO - Epoch(train) [47][760/940] lr: 1.0000e-03 eta: 11:28:23 time: 0.6890 data_time: 0.1873 memory: 22701 grad_norm: 4.5593 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0798 loss: 1.0798 2022/09/05 19:28:06 - mmengine - INFO - Epoch(train) [47][780/940] lr: 1.0000e-03 eta: 11:28:07 time: 0.8366 data_time: 0.3918 memory: 22701 grad_norm: 4.5422 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1571 loss: 1.1571 2022/09/05 19:28:23 - mmengine - INFO - Epoch(train) [47][800/940] lr: 1.0000e-03 eta: 11:27:50 time: 0.8386 data_time: 0.3401 memory: 22701 grad_norm: 4.5893 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1688 loss: 1.1688 2022/09/05 19:28:42 - mmengine - INFO - Epoch(train) [47][820/940] lr: 1.0000e-03 eta: 11:27:37 time: 0.9534 data_time: 0.0650 memory: 22701 grad_norm: 4.6693 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1886 loss: 1.1886 2022/09/05 19:28:55 - mmengine - INFO - Epoch(train) [47][840/940] lr: 1.0000e-03 eta: 11:27:16 time: 0.6223 data_time: 0.0269 memory: 22701 grad_norm: 4.6169 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2147 loss: 1.2147 2022/09/05 19:29:11 - mmengine - INFO - Epoch(train) [47][860/940] lr: 1.0000e-03 eta: 11:26:59 time: 0.7999 data_time: 0.0292 memory: 22701 grad_norm: 4.5846 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1335 loss: 1.1335 2022/09/05 19:29:25 - mmengine - INFO - Epoch(train) [47][880/940] lr: 1.0000e-03 eta: 11:26:39 time: 0.7113 data_time: 0.0287 memory: 22701 grad_norm: 4.5998 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1472 loss: 1.1472 2022/09/05 19:29:44 - mmengine - INFO - Epoch(train) [47][900/940] lr: 1.0000e-03 eta: 11:26:26 time: 0.9536 data_time: 0.0252 memory: 22701 grad_norm: 4.6373 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1317 loss: 1.1317 2022/09/05 19:29:58 - mmengine - INFO - Epoch(train) [47][920/940] lr: 1.0000e-03 eta: 11:26:06 time: 0.6752 data_time: 0.0241 memory: 22701 grad_norm: 4.6372 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0883 loss: 1.0883 2022/09/05 19:30:15 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:30:15 - mmengine - INFO - Epoch(train) [47][940/940] lr: 1.0000e-03 eta: 11:25:51 time: 0.8842 data_time: 0.0184 memory: 22701 grad_norm: 4.9575 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.1328 loss: 1.1328 2022/09/05 19:30:29 - mmengine - INFO - Epoch(val) [47][20/78] eta: 0:00:39 time: 0.6829 data_time: 0.5593 memory: 2247 2022/09/05 19:30:38 - mmengine - INFO - Epoch(val) [47][40/78] eta: 0:00:17 time: 0.4510 data_time: 0.3332 memory: 2247 2022/09/05 19:30:51 - mmengine - INFO - Epoch(val) [47][60/78] eta: 0:00:11 time: 0.6591 data_time: 0.5381 memory: 2247 2022/09/05 19:31:01 - mmengine - INFO - Epoch(val) [47][78/78] acc/top1: 0.6851 acc/top5: 0.8814 acc/mean1: 0.6850 2022/09/05 19:31:23 - mmengine - INFO - Epoch(train) [48][20/940] lr: 1.0000e-03 eta: 11:25:40 time: 1.0664 data_time: 0.6310 memory: 22701 grad_norm: 4.5484 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1265 loss: 1.1265 2022/09/05 19:31:38 - mmengine - INFO - Epoch(train) [48][40/940] lr: 1.0000e-03 eta: 11:25:22 time: 0.7822 data_time: 0.2511 memory: 22701 grad_norm: 4.5133 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1485 loss: 1.1485 2022/09/05 19:31:56 - mmengine - INFO - Epoch(train) [48][60/940] lr: 1.0000e-03 eta: 11:25:07 time: 0.8883 data_time: 0.0333 memory: 22701 grad_norm: 4.5034 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0754 loss: 1.0754 2022/09/05 19:32:10 - mmengine - INFO - Epoch(train) [48][80/940] lr: 1.0000e-03 eta: 11:24:47 time: 0.6775 data_time: 0.0362 memory: 22701 grad_norm: 4.6163 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1720 loss: 1.1720 2022/09/05 19:32:28 - mmengine - INFO - Epoch(train) [48][100/940] lr: 1.0000e-03 eta: 11:24:33 time: 0.9216 data_time: 0.0296 memory: 22701 grad_norm: 4.5521 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.0346 loss: 1.0346 2022/09/05 19:32:42 - mmengine - INFO - Epoch(train) [48][120/940] lr: 1.0000e-03 eta: 11:24:14 time: 0.7056 data_time: 0.0377 memory: 22701 grad_norm: 4.5341 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3328 loss: 1.3328 2022/09/05 19:33:00 - mmengine - INFO - Epoch(train) [48][140/940] lr: 1.0000e-03 eta: 11:23:58 time: 0.8853 data_time: 0.0283 memory: 22701 grad_norm: 4.4772 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1650 loss: 1.1650 2022/09/05 19:33:13 - mmengine - INFO - Epoch(train) [48][160/940] lr: 1.0000e-03 eta: 11:23:38 time: 0.6509 data_time: 0.0376 memory: 22701 grad_norm: 4.6117 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2920 loss: 1.2920 2022/09/05 19:33:29 - mmengine - INFO - Epoch(train) [48][180/940] lr: 1.0000e-03 eta: 11:23:21 time: 0.7942 data_time: 0.0302 memory: 22701 grad_norm: 4.6461 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2198 loss: 1.2198 2022/09/05 19:33:42 - mmengine - INFO - Epoch(train) [48][200/940] lr: 1.0000e-03 eta: 11:23:01 time: 0.6830 data_time: 0.0323 memory: 22701 grad_norm: 4.5550 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0257 loss: 1.0257 2022/09/05 19:34:00 - mmengine - INFO - Epoch(train) [48][220/940] lr: 1.0000e-03 eta: 11:22:45 time: 0.8549 data_time: 0.0265 memory: 22701 grad_norm: 4.7205 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1713 loss: 1.1713 2022/09/05 19:34:15 - mmengine - INFO - Epoch(train) [48][240/940] lr: 1.0000e-03 eta: 11:22:28 time: 0.7946 data_time: 0.0235 memory: 22701 grad_norm: 4.7079 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1375 loss: 1.1375 2022/09/05 19:34:33 - mmengine - INFO - Epoch(train) [48][260/940] lr: 1.0000e-03 eta: 11:22:12 time: 0.8765 data_time: 0.0269 memory: 22701 grad_norm: 4.6042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2515 loss: 1.2515 2022/09/05 19:34:47 - mmengine - INFO - Epoch(train) [48][280/940] lr: 1.0000e-03 eta: 11:21:53 time: 0.6800 data_time: 0.0273 memory: 22701 grad_norm: 4.6585 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1355 loss: 1.1355 2022/09/05 19:35:04 - mmengine - INFO - Epoch(train) [48][300/940] lr: 1.0000e-03 eta: 11:21:37 time: 0.8718 data_time: 0.0252 memory: 22701 grad_norm: 4.4999 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1565 loss: 1.1565 2022/09/05 19:35:18 - mmengine - INFO - Epoch(train) [48][320/940] lr: 1.0000e-03 eta: 11:21:18 time: 0.7215 data_time: 0.0290 memory: 22701 grad_norm: 4.5628 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1037 loss: 1.1037 2022/09/05 19:35:35 - mmengine - INFO - Epoch(train) [48][340/940] lr: 1.0000e-03 eta: 11:21:02 time: 0.8478 data_time: 0.0297 memory: 22701 grad_norm: 4.5405 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1690 loss: 1.1690 2022/09/05 19:35:49 - mmengine - INFO - Epoch(train) [48][360/940] lr: 1.0000e-03 eta: 11:20:43 time: 0.7009 data_time: 0.0356 memory: 22701 grad_norm: 4.6691 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2093 loss: 1.2093 2022/09/05 19:36:06 - mmengine - INFO - Epoch(train) [48][380/940] lr: 1.0000e-03 eta: 11:20:26 time: 0.8002 data_time: 0.0264 memory: 22701 grad_norm: 4.6637 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1581 loss: 1.1581 2022/09/05 19:36:19 - mmengine - INFO - Epoch(train) [48][400/940] lr: 1.0000e-03 eta: 11:20:07 time: 0.6963 data_time: 0.0310 memory: 22701 grad_norm: 4.5727 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2139 loss: 1.2139 2022/09/05 19:36:36 - mmengine - INFO - Epoch(train) [48][420/940] lr: 1.0000e-03 eta: 11:19:50 time: 0.8329 data_time: 0.0231 memory: 22701 grad_norm: 4.6959 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1507 loss: 1.1507 2022/09/05 19:36:52 - mmengine - INFO - Epoch(train) [48][440/940] lr: 1.0000e-03 eta: 11:19:33 time: 0.7984 data_time: 0.0254 memory: 22701 grad_norm: 4.5381 top1_acc: 0.4688 top5_acc: 0.9062 loss_cls: 1.0300 loss: 1.0300 2022/09/05 19:37:10 - mmengine - INFO - Epoch(train) [48][460/940] lr: 1.0000e-03 eta: 11:19:18 time: 0.8945 data_time: 0.0242 memory: 22701 grad_norm: 4.7166 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1644 loss: 1.1644 2022/09/05 19:37:29 - mmengine - INFO - Epoch(train) [48][480/940] lr: 1.0000e-03 eta: 11:19:04 time: 0.9345 data_time: 0.0212 memory: 22701 grad_norm: 4.7349 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1350 loss: 1.1350 2022/09/05 19:37:48 - mmengine - INFO - Epoch(train) [48][500/940] lr: 1.0000e-03 eta: 11:18:51 time: 0.9881 data_time: 0.0828 memory: 22701 grad_norm: 4.5462 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0232 loss: 1.0232 2022/09/05 19:38:03 - mmengine - INFO - Epoch(train) [48][520/940] lr: 1.0000e-03 eta: 11:18:32 time: 0.7112 data_time: 0.1800 memory: 22701 grad_norm: 4.7273 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2392 loss: 1.2392 2022/09/05 19:38:20 - mmengine - INFO - Epoch(train) [48][540/940] lr: 1.0000e-03 eta: 11:18:16 time: 0.8476 data_time: 0.2288 memory: 22701 grad_norm: 4.4913 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2591 loss: 1.2591 2022/09/05 19:38:34 - mmengine - INFO - Epoch(train) [48][560/940] lr: 1.0000e-03 eta: 11:17:57 time: 0.7168 data_time: 0.1880 memory: 22701 grad_norm: 4.5405 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2179 loss: 1.2179 2022/09/05 19:38:53 - mmengine - INFO - Epoch(train) [48][580/940] lr: 1.0000e-03 eta: 11:17:44 time: 0.9659 data_time: 0.2821 memory: 22701 grad_norm: 4.7386 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2425 loss: 1.2425 2022/09/05 19:39:06 - mmengine - INFO - Epoch(train) [48][600/940] lr: 1.0000e-03 eta: 11:17:23 time: 0.6475 data_time: 0.0835 memory: 22701 grad_norm: 4.6543 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1645 loss: 1.1645 2022/09/05 19:39:22 - mmengine - INFO - Epoch(train) [48][620/940] lr: 1.0000e-03 eta: 11:17:06 time: 0.7917 data_time: 0.2494 memory: 22701 grad_norm: 4.5842 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0682 loss: 1.0682 2022/09/05 19:39:36 - mmengine - INFO - Epoch(train) [48][640/940] lr: 1.0000e-03 eta: 11:16:47 time: 0.7044 data_time: 0.2649 memory: 22701 grad_norm: 4.5879 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1337 loss: 1.1337 2022/09/05 19:39:54 - mmengine - INFO - Epoch(train) [48][660/940] lr: 1.0000e-03 eta: 11:16:32 time: 0.9029 data_time: 0.2642 memory: 22701 grad_norm: 4.6483 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0253 loss: 1.0253 2022/09/05 19:40:08 - mmengine - INFO - Epoch(train) [48][680/940] lr: 1.0000e-03 eta: 11:16:12 time: 0.6758 data_time: 0.1326 memory: 22701 grad_norm: 4.5544 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1473 loss: 1.1473 2022/09/05 19:40:25 - mmengine - INFO - Epoch(train) [48][700/940] lr: 1.0000e-03 eta: 11:15:57 time: 0.8713 data_time: 0.1505 memory: 22701 grad_norm: 4.6649 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1222 loss: 1.1222 2022/09/05 19:40:40 - mmengine - INFO - Epoch(train) [48][720/940] lr: 1.0000e-03 eta: 11:15:38 time: 0.7389 data_time: 0.0573 memory: 22701 grad_norm: 4.5939 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.0632 loss: 1.0632 2022/09/05 19:40:57 - mmengine - INFO - Epoch(train) [48][740/940] lr: 1.0000e-03 eta: 11:15:22 time: 0.8362 data_time: 0.1326 memory: 22701 grad_norm: 4.6010 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1573 loss: 1.1573 2022/09/05 19:41:13 - mmengine - INFO - Epoch(train) [48][760/940] lr: 1.0000e-03 eta: 11:15:06 time: 0.8418 data_time: 0.0761 memory: 22701 grad_norm: 4.6089 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0968 loss: 1.0968 2022/09/05 19:41:32 - mmengine - INFO - Epoch(train) [48][780/940] lr: 1.0000e-03 eta: 11:14:51 time: 0.9255 data_time: 0.0241 memory: 22701 grad_norm: 4.6179 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1154 loss: 1.1154 2022/09/05 19:41:47 - mmengine - INFO - Epoch(train) [48][800/940] lr: 1.0000e-03 eta: 11:14:34 time: 0.7737 data_time: 0.0282 memory: 22701 grad_norm: 4.6523 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1098 loss: 1.1098 2022/09/05 19:42:08 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:42:08 - mmengine - INFO - Epoch(train) [48][820/940] lr: 1.0000e-03 eta: 11:14:21 time: 1.0169 data_time: 0.0216 memory: 22701 grad_norm: 4.6304 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0215 loss: 1.0215 2022/09/05 19:42:24 - mmengine - INFO - Epoch(train) [48][840/940] lr: 1.0000e-03 eta: 11:14:05 time: 0.8166 data_time: 0.0260 memory: 22701 grad_norm: 4.6367 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.0181 loss: 1.0181 2022/09/05 19:42:44 - mmengine - INFO - Epoch(train) [48][860/940] lr: 1.0000e-03 eta: 11:13:51 time: 0.9744 data_time: 0.0676 memory: 22701 grad_norm: 4.7100 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1848 loss: 1.1848 2022/09/05 19:42:58 - mmengine - INFO - Epoch(train) [48][880/940] lr: 1.0000e-03 eta: 11:13:33 time: 0.7282 data_time: 0.0693 memory: 22701 grad_norm: 4.6032 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0678 loss: 1.0678 2022/09/05 19:43:17 - mmengine - INFO - Epoch(train) [48][900/940] lr: 1.0000e-03 eta: 11:13:18 time: 0.9258 data_time: 0.1203 memory: 22701 grad_norm: 4.6100 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0973 loss: 1.0973 2022/09/05 19:43:31 - mmengine - INFO - Epoch(train) [48][920/940] lr: 1.0000e-03 eta: 11:13:00 time: 0.7376 data_time: 0.0275 memory: 22701 grad_norm: 4.6560 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2197 loss: 1.2197 2022/09/05 19:43:45 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:43:45 - mmengine - INFO - Epoch(train) [48][940/940] lr: 1.0000e-03 eta: 11:12:41 time: 0.6949 data_time: 0.0252 memory: 22701 grad_norm: 4.9593 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.2491 loss: 1.2491 2022/09/05 19:43:45 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/09/05 19:44:02 - mmengine - INFO - Epoch(val) [48][20/78] eta: 0:00:41 time: 0.7131 data_time: 0.5687 memory: 2247 2022/09/05 19:44:11 - mmengine - INFO - Epoch(val) [48][40/78] eta: 0:00:16 time: 0.4435 data_time: 0.3264 memory: 2247 2022/09/05 19:44:24 - mmengine - INFO - Epoch(val) [48][60/78] eta: 0:00:11 time: 0.6456 data_time: 0.5283 memory: 2247 2022/09/05 19:44:33 - mmengine - INFO - Epoch(val) [48][78/78] acc/top1: 0.6853 acc/top5: 0.8811 acc/mean1: 0.6851 2022/09/05 19:44:55 - mmengine - INFO - Epoch(train) [49][20/940] lr: 1.0000e-03 eta: 11:12:30 time: 1.0782 data_time: 0.5053 memory: 22701 grad_norm: 4.6147 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1207 loss: 1.1207 2022/09/05 19:45:10 - mmengine - INFO - Epoch(train) [49][40/940] lr: 1.0000e-03 eta: 11:12:12 time: 0.7780 data_time: 0.0722 memory: 22701 grad_norm: 4.5381 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1199 loss: 1.1199 2022/09/05 19:45:27 - mmengine - INFO - Epoch(train) [49][60/940] lr: 1.0000e-03 eta: 11:11:56 time: 0.8656 data_time: 0.1091 memory: 22701 grad_norm: 4.6221 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0494 loss: 1.0494 2022/09/05 19:45:41 - mmengine - INFO - Epoch(train) [49][80/940] lr: 1.0000e-03 eta: 11:11:36 time: 0.6544 data_time: 0.0269 memory: 22701 grad_norm: 4.6246 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2138 loss: 1.2138 2022/09/05 19:45:57 - mmengine - INFO - Epoch(train) [49][100/940] lr: 1.0000e-03 eta: 11:11:20 time: 0.8387 data_time: 0.0587 memory: 22701 grad_norm: 4.6231 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1573 loss: 1.1573 2022/09/05 19:46:12 - mmengine - INFO - Epoch(train) [49][120/940] lr: 1.0000e-03 eta: 11:11:02 time: 0.7503 data_time: 0.0839 memory: 22701 grad_norm: 4.7714 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1712 loss: 1.1712 2022/09/05 19:46:29 - mmengine - INFO - Epoch(train) [49][140/940] lr: 1.0000e-03 eta: 11:10:45 time: 0.8153 data_time: 0.1568 memory: 22701 grad_norm: 4.6539 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1413 loss: 1.1413 2022/09/05 19:46:44 - mmengine - INFO - Epoch(train) [49][160/940] lr: 1.0000e-03 eta: 11:10:28 time: 0.7769 data_time: 0.2449 memory: 22701 grad_norm: 4.6150 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.1642 loss: 1.1642 2022/09/05 19:47:01 - mmengine - INFO - Epoch(train) [49][180/940] lr: 1.0000e-03 eta: 11:10:11 time: 0.8324 data_time: 0.4517 memory: 22701 grad_norm: 4.7123 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1704 loss: 1.1704 2022/09/05 19:47:16 - mmengine - INFO - Epoch(train) [49][200/940] lr: 1.0000e-03 eta: 11:09:53 time: 0.7511 data_time: 0.2793 memory: 22701 grad_norm: 4.6776 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1202 loss: 1.1202 2022/09/05 19:47:32 - mmengine - INFO - Epoch(train) [49][220/940] lr: 1.0000e-03 eta: 11:09:36 time: 0.8142 data_time: 0.2257 memory: 22701 grad_norm: 4.6740 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1110 loss: 1.1110 2022/09/05 19:47:48 - mmengine - INFO - Epoch(train) [49][240/940] lr: 1.0000e-03 eta: 11:09:19 time: 0.7924 data_time: 0.1747 memory: 22701 grad_norm: 4.7333 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1245 loss: 1.1245 2022/09/05 19:48:04 - mmengine - INFO - Epoch(train) [49][260/940] lr: 1.0000e-03 eta: 11:09:02 time: 0.7846 data_time: 0.1731 memory: 22701 grad_norm: 4.6384 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1625 loss: 1.1625 2022/09/05 19:48:21 - mmengine - INFO - Epoch(train) [49][280/940] lr: 1.0000e-03 eta: 11:08:46 time: 0.8558 data_time: 0.0696 memory: 22701 grad_norm: 4.6733 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1226 loss: 1.1226 2022/09/05 19:48:34 - mmengine - INFO - Epoch(train) [49][300/940] lr: 1.0000e-03 eta: 11:08:26 time: 0.6563 data_time: 0.0269 memory: 22701 grad_norm: 4.6353 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0572 loss: 1.0572 2022/09/05 19:48:51 - mmengine - INFO - Epoch(train) [49][320/940] lr: 1.0000e-03 eta: 11:08:09 time: 0.8286 data_time: 0.0227 memory: 22701 grad_norm: 4.7227 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1517 loss: 1.1517 2022/09/05 19:49:05 - mmengine - INFO - Epoch(train) [49][340/940] lr: 1.0000e-03 eta: 11:07:50 time: 0.7036 data_time: 0.0410 memory: 22701 grad_norm: 4.6111 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1892 loss: 1.1892 2022/09/05 19:49:22 - mmengine - INFO - Epoch(train) [49][360/940] lr: 1.0000e-03 eta: 11:07:34 time: 0.8680 data_time: 0.1618 memory: 22701 grad_norm: 4.6695 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1717 loss: 1.1717 2022/09/05 19:49:36 - mmengine - INFO - Epoch(train) [49][380/940] lr: 1.0000e-03 eta: 11:07:16 time: 0.7228 data_time: 0.1457 memory: 22701 grad_norm: 4.7393 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.2700 loss: 1.2700 2022/09/05 19:49:52 - mmengine - INFO - Epoch(train) [49][400/940] lr: 1.0000e-03 eta: 11:06:59 time: 0.8038 data_time: 0.0513 memory: 22701 grad_norm: 4.6947 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1366 loss: 1.1366 2022/09/05 19:50:07 - mmengine - INFO - Epoch(train) [49][420/940] lr: 1.0000e-03 eta: 11:06:40 time: 0.7240 data_time: 0.0781 memory: 22701 grad_norm: 4.6203 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2275 loss: 1.2275 2022/09/05 19:50:24 - mmengine - INFO - Epoch(train) [49][440/940] lr: 1.0000e-03 eta: 11:06:24 time: 0.8345 data_time: 0.1474 memory: 22701 grad_norm: 4.5265 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1813 loss: 1.1813 2022/09/05 19:50:38 - mmengine - INFO - Epoch(train) [49][460/940] lr: 1.0000e-03 eta: 11:06:05 time: 0.7121 data_time: 0.0956 memory: 22701 grad_norm: 4.6628 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1578 loss: 1.1578 2022/09/05 19:50:54 - mmengine - INFO - Epoch(train) [49][480/940] lr: 1.0000e-03 eta: 11:05:48 time: 0.8029 data_time: 0.0766 memory: 22701 grad_norm: 4.6500 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1544 loss: 1.1544 2022/09/05 19:51:09 - mmengine - INFO - Epoch(train) [49][500/940] lr: 1.0000e-03 eta: 11:05:30 time: 0.7548 data_time: 0.1679 memory: 22701 grad_norm: 4.6878 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1192 loss: 1.1192 2022/09/05 19:51:27 - mmengine - INFO - Epoch(train) [49][520/940] lr: 1.0000e-03 eta: 11:05:15 time: 0.9104 data_time: 0.2719 memory: 22701 grad_norm: 4.6475 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0746 loss: 1.0746 2022/09/05 19:51:47 - mmengine - INFO - Epoch(train) [49][540/940] lr: 1.0000e-03 eta: 11:05:02 time: 0.9768 data_time: 0.1672 memory: 22701 grad_norm: 4.6524 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1874 loss: 1.1874 2022/09/05 19:52:02 - mmengine - INFO - Epoch(train) [49][560/940] lr: 1.0000e-03 eta: 11:04:44 time: 0.7561 data_time: 0.0404 memory: 22701 grad_norm: 4.6754 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1180 loss: 1.1180 2022/09/05 19:52:19 - mmengine - INFO - Epoch(train) [49][580/940] lr: 1.0000e-03 eta: 11:04:28 time: 0.8465 data_time: 0.0272 memory: 22701 grad_norm: 4.5821 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2111 loss: 1.2111 2022/09/05 19:52:35 - mmengine - INFO - Epoch(train) [49][600/940] lr: 1.0000e-03 eta: 11:04:11 time: 0.8013 data_time: 0.0259 memory: 22701 grad_norm: 4.5819 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0927 loss: 1.0927 2022/09/05 19:52:52 - mmengine - INFO - Epoch(train) [49][620/940] lr: 1.0000e-03 eta: 11:03:55 time: 0.8696 data_time: 0.0643 memory: 22701 grad_norm: 4.6274 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0957 loss: 1.0957 2022/09/05 19:53:07 - mmengine - INFO - Epoch(train) [49][640/940] lr: 1.0000e-03 eta: 11:03:37 time: 0.7390 data_time: 0.0249 memory: 22701 grad_norm: 4.7026 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1525 loss: 1.1525 2022/09/05 19:53:24 - mmengine - INFO - Epoch(train) [49][660/940] lr: 1.0000e-03 eta: 11:03:21 time: 0.8573 data_time: 0.0275 memory: 22701 grad_norm: 4.6190 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0882 loss: 1.0882 2022/09/05 19:53:41 - mmengine - INFO - Epoch(train) [49][680/940] lr: 1.0000e-03 eta: 11:03:05 time: 0.8242 data_time: 0.0215 memory: 22701 grad_norm: 4.5582 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0636 loss: 1.0636 2022/09/05 19:53:57 - mmengine - INFO - Epoch(train) [49][700/940] lr: 1.0000e-03 eta: 11:02:47 time: 0.7850 data_time: 0.0228 memory: 22701 grad_norm: 4.6722 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2800 loss: 1.2800 2022/09/05 19:54:12 - mmengine - INFO - Epoch(train) [49][720/940] lr: 1.0000e-03 eta: 11:02:30 time: 0.7826 data_time: 0.0290 memory: 22701 grad_norm: 4.6706 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0704 loss: 1.0704 2022/09/05 19:54:29 - mmengine - INFO - Epoch(train) [49][740/940] lr: 1.0000e-03 eta: 11:02:13 time: 0.8299 data_time: 0.0271 memory: 22701 grad_norm: 4.6298 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9883 loss: 0.9883 2022/09/05 19:54:42 - mmengine - INFO - Epoch(train) [49][760/940] lr: 1.0000e-03 eta: 11:01:54 time: 0.6767 data_time: 0.0234 memory: 22701 grad_norm: 4.6479 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1479 loss: 1.1479 2022/09/05 19:54:58 - mmengine - INFO - Epoch(train) [49][780/940] lr: 1.0000e-03 eta: 11:01:37 time: 0.8102 data_time: 0.0287 memory: 22701 grad_norm: 4.7400 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1668 loss: 1.1668 2022/09/05 19:55:13 - mmengine - INFO - Epoch(train) [49][800/940] lr: 1.0000e-03 eta: 11:01:18 time: 0.7169 data_time: 0.0230 memory: 22701 grad_norm: 4.7058 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0685 loss: 1.0685 2022/09/05 19:55:29 - mmengine - INFO - Epoch(train) [49][820/940] lr: 1.0000e-03 eta: 11:01:01 time: 0.8064 data_time: 0.0315 memory: 22701 grad_norm: 4.6403 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1456 loss: 1.1456 2022/09/05 19:55:43 - mmengine - INFO - Epoch(train) [49][840/940] lr: 1.0000e-03 eta: 11:00:42 time: 0.6822 data_time: 0.0267 memory: 22701 grad_norm: 4.7186 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2393 loss: 1.2393 2022/09/05 19:55:59 - mmengine - INFO - Epoch(train) [49][860/940] lr: 1.0000e-03 eta: 11:00:25 time: 0.8090 data_time: 0.0269 memory: 22701 grad_norm: 4.6690 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1377 loss: 1.1377 2022/09/05 19:56:12 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:56:12 - mmengine - INFO - Epoch(train) [49][880/940] lr: 1.0000e-03 eta: 11:00:05 time: 0.6465 data_time: 0.0231 memory: 22701 grad_norm: 4.7427 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1974 loss: 1.1974 2022/09/05 19:56:29 - mmengine - INFO - Epoch(train) [49][900/940] lr: 1.0000e-03 eta: 10:59:49 time: 0.8491 data_time: 0.0972 memory: 22701 grad_norm: 4.6775 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0116 loss: 1.0116 2022/09/05 19:56:43 - mmengine - INFO - Epoch(train) [49][920/940] lr: 1.0000e-03 eta: 10:59:30 time: 0.7390 data_time: 0.1237 memory: 22701 grad_norm: 4.6955 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1328 loss: 1.1328 2022/09/05 19:57:00 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 19:57:00 - mmengine - INFO - Epoch(train) [49][940/940] lr: 1.0000e-03 eta: 10:59:13 time: 0.8054 data_time: 0.2773 memory: 22701 grad_norm: 4.9847 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.1234 loss: 1.1234 2022/09/05 19:57:14 - mmengine - INFO - Epoch(val) [49][20/78] eta: 0:00:40 time: 0.7036 data_time: 0.5831 memory: 2247 2022/09/05 19:57:22 - mmengine - INFO - Epoch(val) [49][40/78] eta: 0:00:16 time: 0.4385 data_time: 0.3207 memory: 2247 2022/09/05 19:57:36 - mmengine - INFO - Epoch(val) [49][60/78] eta: 0:00:11 time: 0.6625 data_time: 0.5430 memory: 2247 2022/09/05 19:57:46 - mmengine - INFO - Epoch(val) [49][78/78] acc/top1: 0.6871 acc/top5: 0.8806 acc/mean1: 0.6870 2022/09/05 19:57:46 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_46.pth is removed 2022/09/05 19:57:47 - mmengine - INFO - The best checkpoint with 0.6871 acc/top1 at 50 epoch is saved to best_acc/top1_epoch_50.pth. 2022/09/05 19:58:06 - mmengine - INFO - Epoch(train) [50][20/940] lr: 1.0000e-03 eta: 10:58:59 time: 0.9422 data_time: 0.5308 memory: 22701 grad_norm: 4.6696 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1038 loss: 1.1038 2022/09/05 19:58:19 - mmengine - INFO - Epoch(train) [50][40/940] lr: 1.0000e-03 eta: 10:58:39 time: 0.6477 data_time: 0.2582 memory: 22701 grad_norm: 4.8159 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0931 loss: 1.0931 2022/09/05 19:58:36 - mmengine - INFO - Epoch(train) [50][60/940] lr: 1.0000e-03 eta: 10:58:23 time: 0.8430 data_time: 0.4478 memory: 22701 grad_norm: 4.7079 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1298 loss: 1.1298 2022/09/05 19:58:49 - mmengine - INFO - Epoch(train) [50][80/940] lr: 1.0000e-03 eta: 10:58:03 time: 0.6694 data_time: 0.2797 memory: 22701 grad_norm: 4.6985 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1451 loss: 1.1451 2022/09/05 19:59:05 - mmengine - INFO - Epoch(train) [50][100/940] lr: 1.0000e-03 eta: 10:57:46 time: 0.7972 data_time: 0.2927 memory: 22701 grad_norm: 4.6351 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.0944 loss: 1.0944 2022/09/05 19:59:18 - mmengine - INFO - Epoch(train) [50][120/940] lr: 1.0000e-03 eta: 10:57:26 time: 0.6590 data_time: 0.1210 memory: 22701 grad_norm: 4.6620 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1327 loss: 1.1327 2022/09/05 19:59:34 - mmengine - INFO - Epoch(train) [50][140/940] lr: 1.0000e-03 eta: 10:57:09 time: 0.7828 data_time: 0.2132 memory: 22701 grad_norm: 4.7457 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0510 loss: 1.0510 2022/09/05 19:59:48 - mmengine - INFO - Epoch(train) [50][160/940] lr: 1.0000e-03 eta: 10:56:50 time: 0.7042 data_time: 0.1522 memory: 22701 grad_norm: 4.6275 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1752 loss: 1.1752 2022/09/05 20:00:04 - mmengine - INFO - Epoch(train) [50][180/940] lr: 1.0000e-03 eta: 10:56:33 time: 0.7857 data_time: 0.0926 memory: 22701 grad_norm: 4.6445 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2029 loss: 1.2029 2022/09/05 20:00:17 - mmengine - INFO - Epoch(train) [50][200/940] lr: 1.0000e-03 eta: 10:56:13 time: 0.6695 data_time: 0.0438 memory: 22701 grad_norm: 4.6532 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1191 loss: 1.1191 2022/09/05 20:00:33 - mmengine - INFO - Epoch(train) [50][220/940] lr: 1.0000e-03 eta: 10:55:56 time: 0.7930 data_time: 0.1452 memory: 22701 grad_norm: 4.6573 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1904 loss: 1.1904 2022/09/05 20:00:47 - mmengine - INFO - Epoch(train) [50][240/940] lr: 1.0000e-03 eta: 10:55:37 time: 0.7029 data_time: 0.0675 memory: 22701 grad_norm: 4.7636 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2652 loss: 1.2652 2022/09/05 20:01:03 - mmengine - INFO - Epoch(train) [50][260/940] lr: 1.0000e-03 eta: 10:55:20 time: 0.7925 data_time: 0.0295 memory: 22701 grad_norm: 4.6768 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1350 loss: 1.1350 2022/09/05 20:01:20 - mmengine - INFO - Epoch(train) [50][280/940] lr: 1.0000e-03 eta: 10:55:03 time: 0.8326 data_time: 0.0470 memory: 22701 grad_norm: 4.6548 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1406 loss: 1.1406 2022/09/05 20:01:37 - mmengine - INFO - Epoch(train) [50][300/940] lr: 1.0000e-03 eta: 10:54:47 time: 0.8363 data_time: 0.0927 memory: 22701 grad_norm: 4.5469 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1191 loss: 1.1191 2022/09/05 20:01:55 - mmengine - INFO - Epoch(train) [50][320/940] lr: 1.0000e-03 eta: 10:54:33 time: 0.9440 data_time: 0.0494 memory: 22701 grad_norm: 4.6861 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0256 loss: 1.0256 2022/09/05 20:02:14 - mmengine - INFO - Epoch(train) [50][340/940] lr: 1.0000e-03 eta: 10:54:18 time: 0.9109 data_time: 0.0265 memory: 22701 grad_norm: 4.6845 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1857 loss: 1.1857 2022/09/05 20:02:31 - mmengine - INFO - Epoch(train) [50][360/940] lr: 1.0000e-03 eta: 10:54:03 time: 0.8635 data_time: 0.0219 memory: 22701 grad_norm: 4.5884 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1473 loss: 1.1473 2022/09/05 20:02:47 - mmengine - INFO - Epoch(train) [50][380/940] lr: 1.0000e-03 eta: 10:53:45 time: 0.7887 data_time: 0.0261 memory: 22701 grad_norm: 4.6577 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0676 loss: 1.0676 2022/09/05 20:03:03 - mmengine - INFO - Epoch(train) [50][400/940] lr: 1.0000e-03 eta: 10:53:29 time: 0.8098 data_time: 0.0244 memory: 22701 grad_norm: 4.6102 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0528 loss: 1.0528 2022/09/05 20:03:17 - mmengine - INFO - Epoch(train) [50][420/940] lr: 1.0000e-03 eta: 10:53:09 time: 0.6828 data_time: 0.0311 memory: 22701 grad_norm: 4.6884 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.0626 loss: 1.0626 2022/09/05 20:03:33 - mmengine - INFO - Epoch(train) [50][440/940] lr: 1.0000e-03 eta: 10:52:52 time: 0.8149 data_time: 0.0238 memory: 22701 grad_norm: 4.6363 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1417 loss: 1.1417 2022/09/05 20:03:52 - mmengine - INFO - Epoch(train) [50][460/940] lr: 1.0000e-03 eta: 10:52:39 time: 0.9491 data_time: 0.0256 memory: 22701 grad_norm: 4.6658 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1646 loss: 1.1646 2022/09/05 20:04:05 - mmengine - INFO - Epoch(train) [50][480/940] lr: 1.0000e-03 eta: 10:52:18 time: 0.6443 data_time: 0.0283 memory: 22701 grad_norm: 4.7381 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2366 loss: 1.2366 2022/09/05 20:04:20 - mmengine - INFO - Epoch(train) [50][500/940] lr: 1.0000e-03 eta: 10:52:01 time: 0.7696 data_time: 0.0244 memory: 22701 grad_norm: 4.7606 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1220 loss: 1.1220 2022/09/05 20:04:35 - mmengine - INFO - Epoch(train) [50][520/940] lr: 1.0000e-03 eta: 10:51:43 time: 0.7507 data_time: 0.0276 memory: 22701 grad_norm: 4.6757 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1554 loss: 1.1554 2022/09/05 20:04:55 - mmengine - INFO - Epoch(train) [50][540/940] lr: 1.0000e-03 eta: 10:51:29 time: 0.9834 data_time: 0.0211 memory: 22701 grad_norm: 4.6921 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2009 loss: 1.2009 2022/09/05 20:05:08 - mmengine - INFO - Epoch(train) [50][560/940] lr: 1.0000e-03 eta: 10:51:09 time: 0.6391 data_time: 0.0272 memory: 22701 grad_norm: 4.6783 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2604 loss: 1.2604 2022/09/05 20:05:26 - mmengine - INFO - Epoch(train) [50][580/940] lr: 1.0000e-03 eta: 10:50:54 time: 0.9099 data_time: 0.0194 memory: 22701 grad_norm: 4.6900 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0859 loss: 1.0859 2022/09/05 20:05:39 - mmengine - INFO - Epoch(train) [50][600/940] lr: 1.0000e-03 eta: 10:50:35 time: 0.6735 data_time: 0.0294 memory: 22701 grad_norm: 4.6789 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1873 loss: 1.1873 2022/09/05 20:05:56 - mmengine - INFO - Epoch(train) [50][620/940] lr: 1.0000e-03 eta: 10:50:18 time: 0.8284 data_time: 0.0192 memory: 22701 grad_norm: 4.6750 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0837 loss: 1.0837 2022/09/05 20:06:10 - mmengine - INFO - Epoch(train) [50][640/940] lr: 1.0000e-03 eta: 10:50:00 time: 0.7304 data_time: 0.0314 memory: 22701 grad_norm: 4.6521 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2158 loss: 1.2158 2022/09/05 20:06:28 - mmengine - INFO - Epoch(train) [50][660/940] lr: 1.0000e-03 eta: 10:49:45 time: 0.8811 data_time: 0.0230 memory: 22701 grad_norm: 4.6123 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2062 loss: 1.2062 2022/09/05 20:06:43 - mmengine - INFO - Epoch(train) [50][680/940] lr: 1.0000e-03 eta: 10:49:26 time: 0.7367 data_time: 0.0303 memory: 22701 grad_norm: 4.7729 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0930 loss: 1.0930 2022/09/05 20:07:02 - mmengine - INFO - Epoch(train) [50][700/940] lr: 1.0000e-03 eta: 10:49:13 time: 0.9576 data_time: 0.0193 memory: 22701 grad_norm: 4.8339 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1468 loss: 1.1468 2022/09/05 20:07:16 - mmengine - INFO - Epoch(train) [50][720/940] lr: 1.0000e-03 eta: 10:48:54 time: 0.7072 data_time: 0.0332 memory: 22701 grad_norm: 4.6486 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0725 loss: 1.0725 2022/09/05 20:07:33 - mmengine - INFO - Epoch(train) [50][740/940] lr: 1.0000e-03 eta: 10:48:38 time: 0.8499 data_time: 0.0262 memory: 22701 grad_norm: 4.6758 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0463 loss: 1.0463 2022/09/05 20:07:47 - mmengine - INFO - Epoch(train) [50][760/940] lr: 1.0000e-03 eta: 10:48:19 time: 0.6971 data_time: 0.0336 memory: 22701 grad_norm: 4.6184 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.1765 loss: 1.1765 2022/09/05 20:08:07 - mmengine - INFO - Epoch(train) [50][780/940] lr: 1.0000e-03 eta: 10:48:06 time: 0.9956 data_time: 0.0221 memory: 22701 grad_norm: 4.6262 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0160 loss: 1.0160 2022/09/05 20:08:21 - mmengine - INFO - Epoch(train) [50][800/940] lr: 1.0000e-03 eta: 10:47:47 time: 0.6890 data_time: 0.0288 memory: 22701 grad_norm: 4.6132 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1122 loss: 1.1122 2022/09/05 20:08:37 - mmengine - INFO - Epoch(train) [50][820/940] lr: 1.0000e-03 eta: 10:47:30 time: 0.8149 data_time: 0.0207 memory: 22701 grad_norm: 4.6613 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1050 loss: 1.1050 2022/09/05 20:08:54 - mmengine - INFO - Epoch(train) [50][840/940] lr: 1.0000e-03 eta: 10:47:14 time: 0.8327 data_time: 0.1390 memory: 22701 grad_norm: 4.6816 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1369 loss: 1.1369 2022/09/05 20:09:12 - mmengine - INFO - Epoch(train) [50][860/940] lr: 1.0000e-03 eta: 10:46:59 time: 0.9141 data_time: 0.0666 memory: 22701 grad_norm: 4.6953 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1586 loss: 1.1586 2022/09/05 20:09:28 - mmengine - INFO - Epoch(train) [50][880/940] lr: 1.0000e-03 eta: 10:46:41 time: 0.7792 data_time: 0.1212 memory: 22701 grad_norm: 4.7019 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1366 loss: 1.1366 2022/09/05 20:09:43 - mmengine - INFO - Epoch(train) [50][900/940] lr: 1.0000e-03 eta: 10:46:24 time: 0.7811 data_time: 0.1383 memory: 22701 grad_norm: 4.7424 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0617 loss: 1.0617 2022/09/05 20:09:59 - mmengine - INFO - Epoch(train) [50][920/940] lr: 1.0000e-03 eta: 10:46:07 time: 0.8063 data_time: 0.3173 memory: 22701 grad_norm: 4.5948 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1095 loss: 1.1095 2022/09/05 20:10:12 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 20:10:12 - mmengine - INFO - Epoch(train) [50][940/940] lr: 1.0000e-03 eta: 10:45:47 time: 0.6421 data_time: 0.2374 memory: 22701 grad_norm: 5.0889 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.1478 loss: 1.1478 2022/09/05 20:10:26 - mmengine - INFO - Epoch(val) [50][20/78] eta: 0:00:39 time: 0.6769 data_time: 0.5575 memory: 2247 2022/09/05 20:10:35 - mmengine - INFO - Epoch(val) [50][40/78] eta: 0:00:17 time: 0.4479 data_time: 0.3288 memory: 2247 2022/09/05 20:10:48 - mmengine - INFO - Epoch(val) [50][60/78] eta: 0:00:11 time: 0.6446 data_time: 0.5244 memory: 2247 2022/09/05 20:10:58 - mmengine - INFO - Epoch(val) [50][78/78] acc/top1: 0.6868 acc/top5: 0.8815 acc/mean1: 0.6867 2022/09/05 20:11:17 - mmengine - INFO - Epoch(train) [51][20/940] lr: 1.0000e-03 eta: 10:45:33 time: 0.9642 data_time: 0.4445 memory: 22701 grad_norm: 4.5805 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0613 loss: 1.0613 2022/09/05 20:11:32 - mmengine - INFO - Epoch(train) [51][40/940] lr: 1.0000e-03 eta: 10:45:15 time: 0.7061 data_time: 0.1511 memory: 22701 grad_norm: 4.6752 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1524 loss: 1.1524 2022/09/05 20:11:50 - mmengine - INFO - Epoch(train) [51][60/940] lr: 1.0000e-03 eta: 10:45:00 time: 0.9001 data_time: 0.2140 memory: 22701 grad_norm: 4.7249 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1357 loss: 1.1357 2022/09/05 20:12:03 - mmengine - INFO - Epoch(train) [51][80/940] lr: 1.0000e-03 eta: 10:44:40 time: 0.6909 data_time: 0.0638 memory: 22701 grad_norm: 4.6647 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0484 loss: 1.0484 2022/09/05 20:12:19 - mmengine - INFO - Epoch(train) [51][100/940] lr: 1.0000e-03 eta: 10:44:23 time: 0.7799 data_time: 0.1071 memory: 22701 grad_norm: 4.7633 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0833 loss: 1.0833 2022/09/05 20:12:33 - mmengine - INFO - Epoch(train) [51][120/940] lr: 1.0000e-03 eta: 10:44:04 time: 0.6920 data_time: 0.0984 memory: 22701 grad_norm: 4.6101 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1008 loss: 1.1008 2022/09/05 20:12:51 - mmengine - INFO - Epoch(train) [51][140/940] lr: 1.0000e-03 eta: 10:43:49 time: 0.8844 data_time: 0.0250 memory: 22701 grad_norm: 4.6994 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2337 loss: 1.2337 2022/09/05 20:13:06 - mmengine - INFO - Epoch(train) [51][160/940] lr: 1.0000e-03 eta: 10:43:31 time: 0.7920 data_time: 0.0257 memory: 22701 grad_norm: 4.6549 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1288 loss: 1.1288 2022/09/05 20:13:24 - mmengine - INFO - Epoch(train) [51][180/940] lr: 1.0000e-03 eta: 10:43:16 time: 0.8603 data_time: 0.0415 memory: 22701 grad_norm: 4.6785 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9948 loss: 0.9948 2022/09/05 20:13:37 - mmengine - INFO - Epoch(train) [51][200/940] lr: 1.0000e-03 eta: 10:42:56 time: 0.6806 data_time: 0.0265 memory: 22701 grad_norm: 4.7143 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2390 loss: 1.2390 2022/09/05 20:13:53 - mmengine - INFO - Epoch(train) [51][220/940] lr: 1.0000e-03 eta: 10:42:39 time: 0.7870 data_time: 0.0298 memory: 22701 grad_norm: 4.7652 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2264 loss: 1.2264 2022/09/05 20:14:07 - mmengine - INFO - Epoch(train) [51][240/940] lr: 1.0000e-03 eta: 10:42:20 time: 0.6880 data_time: 0.0410 memory: 22701 grad_norm: 4.7558 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.0593 loss: 1.0593 2022/09/05 20:14:24 - mmengine - INFO - Epoch(train) [51][260/940] lr: 1.0000e-03 eta: 10:42:04 time: 0.8762 data_time: 0.0306 memory: 22701 grad_norm: 4.6785 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2066 loss: 1.2066 2022/09/05 20:14:38 - mmengine - INFO - Epoch(train) [51][280/940] lr: 1.0000e-03 eta: 10:41:45 time: 0.6870 data_time: 0.0231 memory: 22701 grad_norm: 4.7033 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1124 loss: 1.1124 2022/09/05 20:14:53 - mmengine - INFO - Epoch(train) [51][300/940] lr: 1.0000e-03 eta: 10:41:28 time: 0.7623 data_time: 0.0307 memory: 22701 grad_norm: 4.6771 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1519 loss: 1.1519 2022/09/05 20:15:07 - mmengine - INFO - Epoch(train) [51][320/940] lr: 1.0000e-03 eta: 10:41:08 time: 0.6768 data_time: 0.0233 memory: 22701 grad_norm: 4.6505 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1272 loss: 1.1272 2022/09/05 20:15:23 - mmengine - INFO - Epoch(train) [51][340/940] lr: 1.0000e-03 eta: 10:40:52 time: 0.8348 data_time: 0.0303 memory: 22701 grad_norm: 4.5360 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9982 loss: 0.9982 2022/09/05 20:15:41 - mmengine - INFO - Epoch(train) [51][360/940] lr: 1.0000e-03 eta: 10:40:36 time: 0.8569 data_time: 0.1876 memory: 22701 grad_norm: 4.6514 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0737 loss: 1.0737 2022/09/05 20:15:58 - mmengine - INFO - Epoch(train) [51][380/940] lr: 1.0000e-03 eta: 10:40:20 time: 0.8593 data_time: 0.1351 memory: 22701 grad_norm: 4.6725 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0335 loss: 1.0335 2022/09/05 20:16:13 - mmengine - INFO - Epoch(train) [51][400/940] lr: 1.0000e-03 eta: 10:40:02 time: 0.7407 data_time: 0.2004 memory: 22701 grad_norm: 4.6960 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1483 loss: 1.1483 2022/09/05 20:16:28 - mmengine - INFO - Epoch(train) [51][420/940] lr: 1.0000e-03 eta: 10:39:44 time: 0.7458 data_time: 0.2077 memory: 22701 grad_norm: 4.7503 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0636 loss: 1.0636 2022/09/05 20:16:42 - mmengine - INFO - Epoch(train) [51][440/940] lr: 1.0000e-03 eta: 10:39:26 time: 0.7229 data_time: 0.2250 memory: 22701 grad_norm: 4.7878 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1460 loss: 1.1460 2022/09/05 20:16:58 - mmengine - INFO - Epoch(train) [51][460/940] lr: 1.0000e-03 eta: 10:39:08 time: 0.7740 data_time: 0.2923 memory: 22701 grad_norm: 4.6977 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1041 loss: 1.1041 2022/09/05 20:17:10 - mmengine - INFO - Epoch(train) [51][480/940] lr: 1.0000e-03 eta: 10:38:48 time: 0.6164 data_time: 0.1473 memory: 22701 grad_norm: 4.7566 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1053 loss: 1.1053 2022/09/05 20:17:27 - mmengine - INFO - Epoch(train) [51][500/940] lr: 1.0000e-03 eta: 10:38:32 time: 0.8569 data_time: 0.1918 memory: 22701 grad_norm: 4.6446 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0531 loss: 1.0531 2022/09/05 20:17:42 - mmengine - INFO - Epoch(train) [51][520/940] lr: 1.0000e-03 eta: 10:38:14 time: 0.7759 data_time: 0.2710 memory: 22701 grad_norm: 4.7625 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.1846 loss: 1.1846 2022/09/05 20:17:58 - mmengine - INFO - Epoch(train) [51][540/940] lr: 1.0000e-03 eta: 10:37:57 time: 0.7741 data_time: 0.1939 memory: 22701 grad_norm: 4.7682 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0339 loss: 1.0339 2022/09/05 20:18:13 - mmengine - INFO - Epoch(train) [51][560/940] lr: 1.0000e-03 eta: 10:37:39 time: 0.7716 data_time: 0.2491 memory: 22701 grad_norm: 4.6949 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1095 loss: 1.1095 2022/09/05 20:18:31 - mmengine - INFO - Epoch(train) [51][580/940] lr: 1.0000e-03 eta: 10:37:24 time: 0.8631 data_time: 0.1097 memory: 22701 grad_norm: 4.6326 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2598 loss: 1.2598 2022/09/05 20:18:47 - mmengine - INFO - Epoch(train) [51][600/940] lr: 1.0000e-03 eta: 10:37:08 time: 0.8401 data_time: 0.1538 memory: 22701 grad_norm: 4.8038 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2100 loss: 1.2100 2022/09/05 20:19:08 - mmengine - INFO - Epoch(train) [51][620/940] lr: 1.0000e-03 eta: 10:36:55 time: 1.0111 data_time: 0.0662 memory: 22701 grad_norm: 4.7124 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0365 loss: 1.0365 2022/09/05 20:19:23 - mmengine - INFO - Epoch(train) [51][640/940] lr: 1.0000e-03 eta: 10:36:37 time: 0.7647 data_time: 0.1448 memory: 22701 grad_norm: 4.7443 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3567 loss: 1.3567 2022/09/05 20:19:39 - mmengine - INFO - Epoch(train) [51][660/940] lr: 1.0000e-03 eta: 10:36:21 time: 0.8188 data_time: 0.0549 memory: 22701 grad_norm: 4.7529 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1150 loss: 1.1150 2022/09/05 20:19:56 - mmengine - INFO - Epoch(train) [51][680/940] lr: 1.0000e-03 eta: 10:36:04 time: 0.8122 data_time: 0.1621 memory: 22701 grad_norm: 4.7972 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2227 loss: 1.2227 2022/09/05 20:20:12 - mmengine - INFO - Epoch(train) [51][700/940] lr: 1.0000e-03 eta: 10:35:47 time: 0.8093 data_time: 0.0677 memory: 22701 grad_norm: 4.7041 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1883 loss: 1.1883 2022/09/05 20:20:27 - mmengine - INFO - Epoch(train) [51][720/940] lr: 1.0000e-03 eta: 10:35:30 time: 0.7841 data_time: 0.2487 memory: 22701 grad_norm: 4.7229 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1708 loss: 1.1708 2022/09/05 20:20:43 - mmengine - INFO - Epoch(train) [51][740/940] lr: 1.0000e-03 eta: 10:35:12 time: 0.7752 data_time: 0.0908 memory: 22701 grad_norm: 4.7717 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0870 loss: 1.0870 2022/09/05 20:20:58 - mmengine - INFO - Epoch(train) [51][760/940] lr: 1.0000e-03 eta: 10:34:55 time: 0.7692 data_time: 0.0921 memory: 22701 grad_norm: 4.7467 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1058 loss: 1.1058 2022/09/05 20:21:15 - mmengine - INFO - Epoch(train) [51][780/940] lr: 1.0000e-03 eta: 10:34:38 time: 0.8221 data_time: 0.0389 memory: 22701 grad_norm: 4.6892 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1596 loss: 1.1596 2022/09/05 20:21:31 - mmengine - INFO - Epoch(train) [51][800/940] lr: 1.0000e-03 eta: 10:34:22 time: 0.8334 data_time: 0.1634 memory: 22701 grad_norm: 4.7799 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1605 loss: 1.1605 2022/09/05 20:21:49 - mmengine - INFO - Epoch(train) [51][820/940] lr: 1.0000e-03 eta: 10:34:07 time: 0.8772 data_time: 0.0242 memory: 22701 grad_norm: 4.6541 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9778 loss: 0.9778 2022/09/05 20:22:05 - mmengine - INFO - Epoch(train) [51][840/940] lr: 1.0000e-03 eta: 10:33:49 time: 0.7794 data_time: 0.1934 memory: 22701 grad_norm: 4.6733 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1168 loss: 1.1168 2022/09/05 20:22:22 - mmengine - INFO - Epoch(train) [51][860/940] lr: 1.0000e-03 eta: 10:33:34 time: 0.8706 data_time: 0.1976 memory: 22701 grad_norm: 4.6857 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0401 loss: 1.0401 2022/09/05 20:22:40 - mmengine - INFO - Epoch(train) [51][880/940] lr: 1.0000e-03 eta: 10:33:19 time: 0.8911 data_time: 0.5223 memory: 22701 grad_norm: 4.6921 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9857 loss: 0.9857 2022/09/05 20:22:57 - mmengine - INFO - Epoch(train) [51][900/940] lr: 1.0000e-03 eta: 10:33:02 time: 0.8353 data_time: 0.2262 memory: 22701 grad_norm: 4.8316 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1740 loss: 1.1740 2022/09/05 20:23:12 - mmengine - INFO - Epoch(train) [51][920/940] lr: 1.0000e-03 eta: 10:32:45 time: 0.7890 data_time: 0.2306 memory: 22701 grad_norm: 4.6241 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1427 loss: 1.1427 2022/09/05 20:23:27 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 20:23:27 - mmengine - INFO - Epoch(train) [51][940/940] lr: 1.0000e-03 eta: 10:32:27 time: 0.7435 data_time: 0.1287 memory: 22701 grad_norm: 4.9192 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1034 loss: 1.1034 2022/09/05 20:23:27 - mmengine - INFO - Saving checkpoint at 51 epochs 2022/09/05 20:23:43 - mmengine - INFO - Epoch(val) [51][20/78] eta: 0:00:40 time: 0.6938 data_time: 0.5771 memory: 2247 2022/09/05 20:23:52 - mmengine - INFO - Epoch(val) [51][40/78] eta: 0:00:17 time: 0.4531 data_time: 0.3383 memory: 2247 2022/09/05 20:24:05 - mmengine - INFO - Epoch(val) [51][60/78] eta: 0:00:11 time: 0.6523 data_time: 0.5358 memory: 2247 2022/09/05 20:24:15 - mmengine - INFO - Epoch(val) [51][78/78] acc/top1: 0.6871 acc/top5: 0.8819 acc/mean1: 0.6870 2022/09/05 20:24:36 - mmengine - INFO - Epoch(train) [52][20/940] lr: 1.0000e-03 eta: 10:32:16 time: 1.0843 data_time: 0.5671 memory: 22701 grad_norm: 4.7711 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.2240 loss: 1.2240 2022/09/05 20:24:52 - mmengine - INFO - Epoch(train) [52][40/940] lr: 1.0000e-03 eta: 10:31:58 time: 0.7765 data_time: 0.2379 memory: 22701 grad_norm: 4.6972 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1406 loss: 1.1406 2022/09/05 20:25:10 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 20:25:10 - mmengine - INFO - Epoch(train) [52][60/940] lr: 1.0000e-03 eta: 10:31:43 time: 0.8993 data_time: 0.0279 memory: 22701 grad_norm: 4.7563 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0800 loss: 1.0800 2022/09/05 20:25:24 - mmengine - INFO - Epoch(train) [52][80/940] lr: 1.0000e-03 eta: 10:31:25 time: 0.7196 data_time: 0.0298 memory: 22701 grad_norm: 4.6261 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1047 loss: 1.1047 2022/09/05 20:25:41 - mmengine - INFO - Epoch(train) [52][100/940] lr: 1.0000e-03 eta: 10:31:09 time: 0.8371 data_time: 0.0293 memory: 22701 grad_norm: 4.6083 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0898 loss: 1.0898 2022/09/05 20:25:55 - mmengine - INFO - Epoch(train) [52][120/940] lr: 1.0000e-03 eta: 10:30:50 time: 0.7069 data_time: 0.0194 memory: 22701 grad_norm: 4.6663 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0920 loss: 1.0920 2022/09/05 20:26:13 - mmengine - INFO - Epoch(train) [52][140/940] lr: 1.0000e-03 eta: 10:30:34 time: 0.8849 data_time: 0.0714 memory: 22701 grad_norm: 4.7351 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1237 loss: 1.1237 2022/09/05 20:26:27 - mmengine - INFO - Epoch(train) [52][160/940] lr: 1.0000e-03 eta: 10:30:16 time: 0.7039 data_time: 0.0204 memory: 22701 grad_norm: 4.7753 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0645 loss: 1.0645 2022/09/05 20:26:48 - mmengine - INFO - Epoch(train) [52][180/940] lr: 1.0000e-03 eta: 10:30:04 time: 1.0488 data_time: 0.1893 memory: 22701 grad_norm: 4.7514 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1236 loss: 1.1236 2022/09/05 20:27:04 - mmengine - INFO - Epoch(train) [52][200/940] lr: 1.0000e-03 eta: 10:29:47 time: 0.8007 data_time: 0.1560 memory: 22701 grad_norm: 4.8554 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.0541 loss: 1.0541 2022/09/05 20:27:25 - mmengine - INFO - Epoch(train) [52][220/940] lr: 1.0000e-03 eta: 10:29:34 time: 1.0515 data_time: 0.1845 memory: 22701 grad_norm: 4.5674 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2165 loss: 1.2165 2022/09/05 20:27:39 - mmengine - INFO - Epoch(train) [52][240/940] lr: 1.0000e-03 eta: 10:29:15 time: 0.6820 data_time: 0.1508 memory: 22701 grad_norm: 4.7048 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0985 loss: 1.0985 2022/09/05 20:27:55 - mmengine - INFO - Epoch(train) [52][260/940] lr: 1.0000e-03 eta: 10:28:59 time: 0.8367 data_time: 0.1790 memory: 22701 grad_norm: 4.7215 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1559 loss: 1.1559 2022/09/05 20:28:09 - mmengine - INFO - Epoch(train) [52][280/940] lr: 1.0000e-03 eta: 10:28:40 time: 0.7074 data_time: 0.1114 memory: 22701 grad_norm: 4.6805 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1348 loss: 1.1348 2022/09/05 20:28:25 - mmengine - INFO - Epoch(train) [52][300/940] lr: 1.0000e-03 eta: 10:28:23 time: 0.7683 data_time: 0.1062 memory: 22701 grad_norm: 4.7406 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2147 loss: 1.2147 2022/09/05 20:28:38 - mmengine - INFO - Epoch(train) [52][320/940] lr: 1.0000e-03 eta: 10:28:03 time: 0.6467 data_time: 0.0247 memory: 22701 grad_norm: 4.6349 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1069 loss: 1.1069 2022/09/05 20:28:55 - mmengine - INFO - Epoch(train) [52][340/940] lr: 1.0000e-03 eta: 10:27:47 time: 0.8449 data_time: 0.0291 memory: 22701 grad_norm: 4.7226 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1926 loss: 1.1926 2022/09/05 20:29:08 - mmengine - INFO - Epoch(train) [52][360/940] lr: 1.0000e-03 eta: 10:27:28 time: 0.6843 data_time: 0.0219 memory: 22701 grad_norm: 4.7230 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0348 loss: 1.0348 2022/09/05 20:29:24 - mmengine - INFO - Epoch(train) [52][380/940] lr: 1.0000e-03 eta: 10:27:11 time: 0.7921 data_time: 0.0282 memory: 22701 grad_norm: 4.6129 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0863 loss: 1.0863 2022/09/05 20:29:37 - mmengine - INFO - Epoch(train) [52][400/940] lr: 1.0000e-03 eta: 10:26:51 time: 0.6630 data_time: 0.0423 memory: 22701 grad_norm: 4.7870 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9547 loss: 0.9547 2022/09/05 20:29:57 - mmengine - INFO - Epoch(train) [52][420/940] lr: 1.0000e-03 eta: 10:26:37 time: 0.9611 data_time: 0.0819 memory: 22701 grad_norm: 4.7217 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1730 loss: 1.1730 2022/09/05 20:30:11 - mmengine - INFO - Epoch(train) [52][440/940] lr: 1.0000e-03 eta: 10:26:18 time: 0.6939 data_time: 0.0276 memory: 22701 grad_norm: 4.6060 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.0588 loss: 1.0588 2022/09/05 20:30:26 - mmengine - INFO - Epoch(train) [52][460/940] lr: 1.0000e-03 eta: 10:26:01 time: 0.7711 data_time: 0.1905 memory: 22701 grad_norm: 4.7250 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1663 loss: 1.1663 2022/09/05 20:30:40 - mmengine - INFO - Epoch(train) [52][480/940] lr: 1.0000e-03 eta: 10:25:42 time: 0.7090 data_time: 0.0739 memory: 22701 grad_norm: 4.7215 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1252 loss: 1.1252 2022/09/05 20:30:56 - mmengine - INFO - Epoch(train) [52][500/940] lr: 1.0000e-03 eta: 10:25:25 time: 0.7754 data_time: 0.0297 memory: 22701 grad_norm: 4.7382 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1771 loss: 1.1771 2022/09/05 20:31:09 - mmengine - INFO - Epoch(train) [52][520/940] lr: 1.0000e-03 eta: 10:25:05 time: 0.6602 data_time: 0.0274 memory: 22701 grad_norm: 4.6778 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0486 loss: 1.0486 2022/09/05 20:31:25 - mmengine - INFO - Epoch(train) [52][540/940] lr: 1.0000e-03 eta: 10:24:49 time: 0.8044 data_time: 0.0351 memory: 22701 grad_norm: 4.8282 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2000 loss: 1.2000 2022/09/05 20:31:39 - mmengine - INFO - Epoch(train) [52][560/940] lr: 1.0000e-03 eta: 10:24:29 time: 0.6819 data_time: 0.0796 memory: 22701 grad_norm: 4.7677 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.0875 loss: 1.0875 2022/09/05 20:31:56 - mmengine - INFO - Epoch(train) [52][580/940] lr: 1.0000e-03 eta: 10:24:14 time: 0.8568 data_time: 0.0701 memory: 22701 grad_norm: 4.7799 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1521 loss: 1.1521 2022/09/05 20:32:12 - mmengine - INFO - Epoch(train) [52][600/940] lr: 1.0000e-03 eta: 10:23:57 time: 0.8024 data_time: 0.1355 memory: 22701 grad_norm: 4.7526 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1104 loss: 1.1104 2022/09/05 20:32:33 - mmengine - INFO - Epoch(train) [52][620/940] lr: 1.0000e-03 eta: 10:23:44 time: 1.0368 data_time: 0.1342 memory: 22701 grad_norm: 4.7879 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1285 loss: 1.1285 2022/09/05 20:32:50 - mmengine - INFO - Epoch(train) [52][640/940] lr: 1.0000e-03 eta: 10:23:29 time: 0.8847 data_time: 0.1826 memory: 22701 grad_norm: 4.7851 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2464 loss: 1.2464 2022/09/05 20:33:09 - mmengine - INFO - Epoch(train) [52][660/940] lr: 1.0000e-03 eta: 10:23:15 time: 0.9462 data_time: 0.1825 memory: 22701 grad_norm: 4.8017 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0798 loss: 1.0798 2022/09/05 20:33:25 - mmengine - INFO - Epoch(train) [52][680/940] lr: 1.0000e-03 eta: 10:22:57 time: 0.7786 data_time: 0.2015 memory: 22701 grad_norm: 4.8008 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2028 loss: 1.2028 2022/09/05 20:33:42 - mmengine - INFO - Epoch(train) [52][700/940] lr: 1.0000e-03 eta: 10:22:41 time: 0.8458 data_time: 0.1641 memory: 22701 grad_norm: 4.7166 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.0619 loss: 1.0619 2022/09/05 20:33:56 - mmengine - INFO - Epoch(train) [52][720/940] lr: 1.0000e-03 eta: 10:22:23 time: 0.6989 data_time: 0.0506 memory: 22701 grad_norm: 4.7597 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2111 loss: 1.2111 2022/09/05 20:34:14 - mmengine - INFO - Epoch(train) [52][740/940] lr: 1.0000e-03 eta: 10:22:08 time: 0.9290 data_time: 0.0263 memory: 22701 grad_norm: 4.7446 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1290 loss: 1.1290 2022/09/05 20:34:30 - mmengine - INFO - Epoch(train) [52][760/940] lr: 1.0000e-03 eta: 10:21:51 time: 0.8036 data_time: 0.0467 memory: 22701 grad_norm: 4.8419 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0196 loss: 1.0196 2022/09/05 20:34:49 - mmengine - INFO - Epoch(train) [52][780/940] lr: 1.0000e-03 eta: 10:21:36 time: 0.9205 data_time: 0.0301 memory: 22701 grad_norm: 4.6235 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9927 loss: 0.9927 2022/09/05 20:35:05 - mmengine - INFO - Epoch(train) [52][800/940] lr: 1.0000e-03 eta: 10:21:20 time: 0.8017 data_time: 0.0243 memory: 22701 grad_norm: 4.8333 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1723 loss: 1.1723 2022/09/05 20:35:23 - mmengine - INFO - Epoch(train) [52][820/940] lr: 1.0000e-03 eta: 10:21:04 time: 0.8922 data_time: 0.0234 memory: 22701 grad_norm: 4.7972 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9539 loss: 0.9539 2022/09/05 20:35:40 - mmengine - INFO - Epoch(train) [52][840/940] lr: 1.0000e-03 eta: 10:20:48 time: 0.8483 data_time: 0.0249 memory: 22701 grad_norm: 4.8294 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1097 loss: 1.1097 2022/09/05 20:36:00 - mmengine - INFO - Epoch(train) [52][860/940] lr: 1.0000e-03 eta: 10:20:35 time: 1.0048 data_time: 0.0393 memory: 22701 grad_norm: 4.7487 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1284 loss: 1.1284 2022/09/05 20:36:16 - mmengine - INFO - Epoch(train) [52][880/940] lr: 1.0000e-03 eta: 10:20:18 time: 0.8049 data_time: 0.0350 memory: 22701 grad_norm: 4.7756 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1017 loss: 1.1017 2022/09/05 20:36:33 - mmengine - INFO - Epoch(train) [52][900/940] lr: 1.0000e-03 eta: 10:20:03 time: 0.8717 data_time: 0.0956 memory: 22701 grad_norm: 4.7286 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1009 loss: 1.1009 2022/09/05 20:36:49 - mmengine - INFO - Epoch(train) [52][920/940] lr: 1.0000e-03 eta: 10:19:46 time: 0.7783 data_time: 0.0879 memory: 22701 grad_norm: 4.7597 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1759 loss: 1.1759 2022/09/05 20:37:02 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 20:37:02 - mmengine - INFO - Epoch(train) [52][940/940] lr: 1.0000e-03 eta: 10:19:26 time: 0.6838 data_time: 0.1511 memory: 22701 grad_norm: 4.9579 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.1450 loss: 1.1450 2022/09/05 20:37:16 - mmengine - INFO - Epoch(val) [52][20/78] eta: 0:00:40 time: 0.6942 data_time: 0.5728 memory: 2247 2022/09/05 20:37:25 - mmengine - INFO - Epoch(val) [52][40/78] eta: 0:00:17 time: 0.4559 data_time: 0.3363 memory: 2247 2022/09/05 20:37:39 - mmengine - INFO - Epoch(val) [52][60/78] eta: 0:00:11 time: 0.6523 data_time: 0.5325 memory: 2247 2022/09/05 20:37:49 - mmengine - INFO - Epoch(val) [52][78/78] acc/top1: 0.6862 acc/top5: 0.8805 acc/mean1: 0.6861 2022/09/05 20:38:09 - mmengine - INFO - Epoch(train) [53][20/940] lr: 1.0000e-03 eta: 10:19:13 time: 0.9879 data_time: 0.5797 memory: 22701 grad_norm: 4.7697 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0415 loss: 1.0415 2022/09/05 20:38:25 - mmengine - INFO - Epoch(train) [53][40/940] lr: 1.0000e-03 eta: 10:18:56 time: 0.7873 data_time: 0.3934 memory: 22701 grad_norm: 4.7720 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0917 loss: 1.0917 2022/09/05 20:38:41 - mmengine - INFO - Epoch(train) [53][60/940] lr: 1.0000e-03 eta: 10:18:39 time: 0.7950 data_time: 0.3523 memory: 22701 grad_norm: 4.7057 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0475 loss: 1.0475 2022/09/05 20:38:54 - mmengine - INFO - Epoch(train) [53][80/940] lr: 1.0000e-03 eta: 10:18:20 time: 0.6779 data_time: 0.1911 memory: 22701 grad_norm: 4.6617 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0636 loss: 1.0636 2022/09/05 20:39:10 - mmengine - INFO - Epoch(train) [53][100/940] lr: 1.0000e-03 eta: 10:18:03 time: 0.7874 data_time: 0.3541 memory: 22701 grad_norm: 4.6782 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0631 loss: 1.0631 2022/09/05 20:39:25 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 20:39:25 - mmengine - INFO - Epoch(train) [53][120/940] lr: 1.0000e-03 eta: 10:17:45 time: 0.7466 data_time: 0.3235 memory: 22701 grad_norm: 4.6249 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0533 loss: 1.0533 2022/09/05 20:39:41 - mmengine - INFO - Epoch(train) [53][140/940] lr: 1.0000e-03 eta: 10:17:28 time: 0.7896 data_time: 0.2232 memory: 22701 grad_norm: 4.7140 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0394 loss: 1.0394 2022/09/05 20:39:57 - mmengine - INFO - Epoch(train) [53][160/940] lr: 1.0000e-03 eta: 10:17:11 time: 0.7916 data_time: 0.0834 memory: 22701 grad_norm: 4.7493 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1141 loss: 1.1141 2022/09/05 20:40:11 - mmengine - INFO - Epoch(train) [53][180/940] lr: 1.0000e-03 eta: 10:16:52 time: 0.7253 data_time: 0.0909 memory: 22701 grad_norm: 4.7102 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1405 loss: 1.1405 2022/09/05 20:40:28 - mmengine - INFO - Epoch(train) [53][200/940] lr: 1.0000e-03 eta: 10:16:36 time: 0.8279 data_time: 0.2113 memory: 22701 grad_norm: 4.7656 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0047 loss: 1.0047 2022/09/05 20:40:45 - mmengine - INFO - Epoch(train) [53][220/940] lr: 1.0000e-03 eta: 10:16:20 time: 0.8531 data_time: 0.2564 memory: 22701 grad_norm: 4.7297 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0842 loss: 1.0842 2022/09/05 20:40:58 - mmengine - INFO - Epoch(train) [53][240/940] lr: 1.0000e-03 eta: 10:16:01 time: 0.6701 data_time: 0.2267 memory: 22701 grad_norm: 4.8273 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1090 loss: 1.1090 2022/09/05 20:41:19 - mmengine - INFO - Epoch(train) [53][260/940] lr: 1.0000e-03 eta: 10:15:48 time: 1.0205 data_time: 0.4649 memory: 22701 grad_norm: 4.7594 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1883 loss: 1.1883 2022/09/05 20:41:33 - mmengine - INFO - Epoch(train) [53][280/940] lr: 1.0000e-03 eta: 10:15:29 time: 0.7230 data_time: 0.3205 memory: 22701 grad_norm: 4.8485 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1104 loss: 1.1104 2022/09/05 20:41:53 - mmengine - INFO - Epoch(train) [53][300/940] lr: 1.0000e-03 eta: 10:15:16 time: 0.9730 data_time: 0.4366 memory: 22701 grad_norm: 4.7947 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0473 loss: 1.0473 2022/09/05 20:42:11 - mmengine - INFO - Epoch(train) [53][320/940] lr: 1.0000e-03 eta: 10:15:01 time: 0.9476 data_time: 0.0884 memory: 22701 grad_norm: 4.6626 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0306 loss: 1.0306 2022/09/05 20:42:28 - mmengine - INFO - Epoch(train) [53][340/940] lr: 1.0000e-03 eta: 10:14:45 time: 0.8078 data_time: 0.1130 memory: 22701 grad_norm: 4.7916 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1139 loss: 1.1139 2022/09/05 20:42:42 - mmengine - INFO - Epoch(train) [53][360/940] lr: 1.0000e-03 eta: 10:14:27 time: 0.7404 data_time: 0.2263 memory: 22701 grad_norm: 4.7637 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9928 loss: 0.9928 2022/09/05 20:42:57 - mmengine - INFO - Epoch(train) [53][380/940] lr: 1.0000e-03 eta: 10:14:09 time: 0.7468 data_time: 0.1137 memory: 22701 grad_norm: 4.8323 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1059 loss: 1.1059 2022/09/05 20:43:12 - mmengine - INFO - Epoch(train) [53][400/940] lr: 1.0000e-03 eta: 10:13:51 time: 0.7318 data_time: 0.0621 memory: 22701 grad_norm: 4.6734 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0589 loss: 1.0589 2022/09/05 20:43:28 - mmengine - INFO - Epoch(train) [53][420/940] lr: 1.0000e-03 eta: 10:13:34 time: 0.7892 data_time: 0.0221 memory: 22701 grad_norm: 4.7239 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1770 loss: 1.1770 2022/09/05 20:43:42 - mmengine - INFO - Epoch(train) [53][440/940] lr: 1.0000e-03 eta: 10:13:15 time: 0.6883 data_time: 0.0272 memory: 22701 grad_norm: 4.5766 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0602 loss: 1.0602 2022/09/05 20:43:58 - mmengine - INFO - Epoch(train) [53][460/940] lr: 1.0000e-03 eta: 10:12:58 time: 0.8121 data_time: 0.1359 memory: 22701 grad_norm: 4.7482 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1471 loss: 1.1471 2022/09/05 20:44:13 - mmengine - INFO - Epoch(train) [53][480/940] lr: 1.0000e-03 eta: 10:12:40 time: 0.7562 data_time: 0.1920 memory: 22701 grad_norm: 4.7819 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0528 loss: 1.0528 2022/09/05 20:44:31 - mmengine - INFO - Epoch(train) [53][500/940] lr: 1.0000e-03 eta: 10:12:25 time: 0.8994 data_time: 0.1121 memory: 22701 grad_norm: 4.7781 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1323 loss: 1.1323 2022/09/05 20:44:45 - mmengine - INFO - Epoch(train) [53][520/940] lr: 1.0000e-03 eta: 10:12:07 time: 0.7207 data_time: 0.0781 memory: 22701 grad_norm: 4.8136 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0859 loss: 1.0859 2022/09/05 20:45:02 - mmengine - INFO - Epoch(train) [53][540/940] lr: 1.0000e-03 eta: 10:11:50 time: 0.8220 data_time: 0.0239 memory: 22701 grad_norm: 4.8167 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2441 loss: 1.2441 2022/09/05 20:45:16 - mmengine - INFO - Epoch(train) [53][560/940] lr: 1.0000e-03 eta: 10:11:32 time: 0.6917 data_time: 0.0826 memory: 22701 grad_norm: 4.8176 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1872 loss: 1.1872 2022/09/05 20:45:32 - mmengine - INFO - Epoch(train) [53][580/940] lr: 1.0000e-03 eta: 10:11:15 time: 0.8234 data_time: 0.1383 memory: 22701 grad_norm: 4.7758 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1184 loss: 1.1184 2022/09/05 20:45:47 - mmengine - INFO - Epoch(train) [53][600/940] lr: 1.0000e-03 eta: 10:10:57 time: 0.7363 data_time: 0.1129 memory: 22701 grad_norm: 4.7964 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1077 loss: 1.1077 2022/09/05 20:46:05 - mmengine - INFO - Epoch(train) [53][620/940] lr: 1.0000e-03 eta: 10:10:42 time: 0.9103 data_time: 0.2245 memory: 22701 grad_norm: 4.8467 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1144 loss: 1.1144 2022/09/05 20:46:20 - mmengine - INFO - Epoch(train) [53][640/940] lr: 1.0000e-03 eta: 10:10:25 time: 0.7603 data_time: 0.0427 memory: 22701 grad_norm: 4.8203 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0994 loss: 1.0994 2022/09/05 20:46:38 - mmengine - INFO - Epoch(train) [53][660/940] lr: 1.0000e-03 eta: 10:10:09 time: 0.8943 data_time: 0.0313 memory: 22701 grad_norm: 4.7146 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0557 loss: 1.0557 2022/09/05 20:46:54 - mmengine - INFO - Epoch(train) [53][680/940] lr: 1.0000e-03 eta: 10:09:52 time: 0.7955 data_time: 0.0242 memory: 22701 grad_norm: 4.7779 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0879 loss: 1.0879 2022/09/05 20:47:13 - mmengine - INFO - Epoch(train) [53][700/940] lr: 1.0000e-03 eta: 10:09:39 time: 0.9688 data_time: 0.0252 memory: 22701 grad_norm: 4.6102 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1144 loss: 1.1144 2022/09/05 20:47:28 - mmengine - INFO - Epoch(train) [53][720/940] lr: 1.0000e-03 eta: 10:09:20 time: 0.7147 data_time: 0.0305 memory: 22701 grad_norm: 4.8859 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1256 loss: 1.1256 2022/09/05 20:47:51 - mmengine - INFO - Epoch(train) [53][740/940] lr: 1.0000e-03 eta: 10:09:09 time: 1.1493 data_time: 0.0262 memory: 22701 grad_norm: 4.7196 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0973 loss: 1.0973 2022/09/05 20:48:06 - mmengine - INFO - Epoch(train) [53][760/940] lr: 1.0000e-03 eta: 10:08:52 time: 0.7497 data_time: 0.0218 memory: 22701 grad_norm: 4.8196 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0811 loss: 1.0811 2022/09/05 20:48:23 - mmengine - INFO - Epoch(train) [53][780/940] lr: 1.0000e-03 eta: 10:08:36 time: 0.8868 data_time: 0.0423 memory: 22701 grad_norm: 4.7870 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1355 loss: 1.1355 2022/09/05 20:48:39 - mmengine - INFO - Epoch(train) [53][800/940] lr: 1.0000e-03 eta: 10:08:19 time: 0.7973 data_time: 0.0236 memory: 22701 grad_norm: 4.8496 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.1809 loss: 1.1809 2022/09/05 20:48:55 - mmengine - INFO - Epoch(train) [53][820/940] lr: 1.0000e-03 eta: 10:08:03 time: 0.8040 data_time: 0.0380 memory: 22701 grad_norm: 4.7966 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1236 loss: 1.1236 2022/09/05 20:49:12 - mmengine - INFO - Epoch(train) [53][840/940] lr: 1.0000e-03 eta: 10:07:46 time: 0.8024 data_time: 0.0254 memory: 22701 grad_norm: 4.7948 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0628 loss: 1.0628 2022/09/05 20:49:29 - mmengine - INFO - Epoch(train) [53][860/940] lr: 1.0000e-03 eta: 10:07:30 time: 0.8525 data_time: 0.0281 memory: 22701 grad_norm: 4.7454 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0021 loss: 1.0021 2022/09/05 20:49:44 - mmengine - INFO - Epoch(train) [53][880/940] lr: 1.0000e-03 eta: 10:07:12 time: 0.7593 data_time: 0.0304 memory: 22701 grad_norm: 4.8149 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0960 loss: 1.0960 2022/09/05 20:50:03 - mmengine - INFO - Epoch(train) [53][900/940] lr: 1.0000e-03 eta: 10:06:58 time: 0.9406 data_time: 0.0304 memory: 22701 grad_norm: 4.8170 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1628 loss: 1.1628 2022/09/05 20:50:17 - mmengine - INFO - Epoch(train) [53][920/940] lr: 1.0000e-03 eta: 10:06:39 time: 0.7092 data_time: 0.0261 memory: 22701 grad_norm: 4.7936 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0095 loss: 1.0095 2022/09/05 20:50:31 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 20:50:31 - mmengine - INFO - Epoch(train) [53][940/940] lr: 1.0000e-03 eta: 10:06:20 time: 0.6931 data_time: 0.0209 memory: 22701 grad_norm: 5.1134 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.2447 loss: 1.2447 2022/09/05 20:50:44 - mmengine - INFO - Epoch(val) [53][20/78] eta: 0:00:39 time: 0.6832 data_time: 0.5636 memory: 2247 2022/09/05 20:50:53 - mmengine - INFO - Epoch(val) [53][40/78] eta: 0:00:16 time: 0.4467 data_time: 0.3263 memory: 2247 2022/09/05 20:51:06 - mmengine - INFO - Epoch(val) [53][60/78] eta: 0:00:11 time: 0.6504 data_time: 0.5242 memory: 2247 2022/09/05 20:51:17 - mmengine - INFO - Epoch(val) [53][78/78] acc/top1: 0.6872 acc/top5: 0.8829 acc/mean1: 0.6870 2022/09/05 20:51:17 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_50.pth is removed 2022/09/05 20:51:18 - mmengine - INFO - The best checkpoint with 0.6872 acc/top1 at 54 epoch is saved to best_acc/top1_epoch_54.pth. 2022/09/05 20:51:38 - mmengine - INFO - Epoch(train) [54][20/940] lr: 1.0000e-03 eta: 10:06:07 time: 0.9955 data_time: 0.5915 memory: 22701 grad_norm: 4.7341 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0590 loss: 1.0590 2022/09/05 20:51:52 - mmengine - INFO - Epoch(train) [54][40/940] lr: 1.0000e-03 eta: 10:05:48 time: 0.7021 data_time: 0.3166 memory: 22701 grad_norm: 4.7925 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0957 loss: 1.0957 2022/09/05 20:52:10 - mmengine - INFO - Epoch(train) [54][60/940] lr: 1.0000e-03 eta: 10:05:33 time: 0.8889 data_time: 0.5097 memory: 22701 grad_norm: 4.7973 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1817 loss: 1.1817 2022/09/05 20:52:24 - mmengine - INFO - Epoch(train) [54][80/940] lr: 1.0000e-03 eta: 10:05:14 time: 0.6841 data_time: 0.2871 memory: 22701 grad_norm: 4.8203 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1219 loss: 1.1219 2022/09/05 20:52:43 - mmengine - INFO - Epoch(train) [54][100/940] lr: 1.0000e-03 eta: 10:05:00 time: 0.9776 data_time: 0.5709 memory: 22701 grad_norm: 4.6410 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1137 loss: 1.1137 2022/09/05 20:52:57 - mmengine - INFO - Epoch(train) [54][120/940] lr: 1.0000e-03 eta: 10:04:42 time: 0.6870 data_time: 0.2656 memory: 22701 grad_norm: 4.6919 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1064 loss: 1.1064 2022/09/05 20:53:14 - mmengine - INFO - Epoch(train) [54][140/940] lr: 1.0000e-03 eta: 10:04:26 time: 0.8583 data_time: 0.4611 memory: 22701 grad_norm: 4.6725 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0280 loss: 1.0280 2022/09/05 20:53:28 - mmengine - INFO - Epoch(train) [54][160/940] lr: 1.0000e-03 eta: 10:04:07 time: 0.6958 data_time: 0.2693 memory: 22701 grad_norm: 4.8100 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1112 loss: 1.1112 2022/09/05 20:53:45 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 20:53:45 - mmengine - INFO - Epoch(train) [54][180/940] lr: 1.0000e-03 eta: 10:03:50 time: 0.8166 data_time: 0.2868 memory: 22701 grad_norm: 4.9162 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0912 loss: 1.0912 2022/09/05 20:54:01 - mmengine - INFO - Epoch(train) [54][200/940] lr: 1.0000e-03 eta: 10:03:34 time: 0.8297 data_time: 0.1939 memory: 22701 grad_norm: 4.6728 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0558 loss: 1.0558 2022/09/05 20:54:19 - mmengine - INFO - Epoch(train) [54][220/940] lr: 1.0000e-03 eta: 10:03:19 time: 0.8981 data_time: 0.0755 memory: 22701 grad_norm: 4.8708 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1710 loss: 1.1710 2022/09/05 20:54:36 - mmengine - INFO - Epoch(train) [54][240/940] lr: 1.0000e-03 eta: 10:03:03 time: 0.8560 data_time: 0.0252 memory: 22701 grad_norm: 4.6774 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1199 loss: 1.1199 2022/09/05 20:54:50 - mmengine - INFO - Epoch(train) [54][260/940] lr: 1.0000e-03 eta: 10:02:44 time: 0.6983 data_time: 0.0380 memory: 22701 grad_norm: 4.7596 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0977 loss: 1.0977 2022/09/05 20:55:08 - mmengine - INFO - Epoch(train) [54][280/940] lr: 1.0000e-03 eta: 10:02:29 time: 0.9002 data_time: 0.0227 memory: 22701 grad_norm: 4.8582 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0892 loss: 1.0892 2022/09/05 20:55:24 - mmengine - INFO - Epoch(train) [54][300/940] lr: 1.0000e-03 eta: 10:02:12 time: 0.7693 data_time: 0.0253 memory: 22701 grad_norm: 4.6535 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0317 loss: 1.0317 2022/09/05 20:55:42 - mmengine - INFO - Epoch(train) [54][320/940] lr: 1.0000e-03 eta: 10:01:57 time: 0.9309 data_time: 0.0274 memory: 22701 grad_norm: 4.7255 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1232 loss: 1.1232 2022/09/05 20:55:55 - mmengine - INFO - Epoch(train) [54][340/940] lr: 1.0000e-03 eta: 10:01:38 time: 0.6497 data_time: 0.0280 memory: 22701 grad_norm: 4.7809 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0981 loss: 1.0981 2022/09/05 20:56:13 - mmengine - INFO - Epoch(train) [54][360/940] lr: 1.0000e-03 eta: 10:01:23 time: 0.9036 data_time: 0.0311 memory: 22701 grad_norm: 4.6997 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0698 loss: 1.0698 2022/09/05 20:56:28 - mmengine - INFO - Epoch(train) [54][380/940] lr: 1.0000e-03 eta: 10:01:05 time: 0.7320 data_time: 0.0221 memory: 22701 grad_norm: 4.6702 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0984 loss: 1.0984 2022/09/05 20:56:48 - mmengine - INFO - Epoch(train) [54][400/940] lr: 1.0000e-03 eta: 10:00:51 time: 1.0178 data_time: 0.0437 memory: 22701 grad_norm: 4.8748 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1447 loss: 1.1447 2022/09/05 20:57:05 - mmengine - INFO - Epoch(train) [54][420/940] lr: 1.0000e-03 eta: 10:00:35 time: 0.8381 data_time: 0.0175 memory: 22701 grad_norm: 4.8212 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0579 loss: 1.0579 2022/09/05 20:57:23 - mmengine - INFO - Epoch(train) [54][440/940] lr: 1.0000e-03 eta: 10:00:20 time: 0.8888 data_time: 0.0236 memory: 22701 grad_norm: 4.7969 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1812 loss: 1.1812 2022/09/05 20:57:36 - mmengine - INFO - Epoch(train) [54][460/940] lr: 1.0000e-03 eta: 10:00:01 time: 0.6787 data_time: 0.0452 memory: 22701 grad_norm: 4.8823 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1427 loss: 1.1427 2022/09/05 20:57:55 - mmengine - INFO - Epoch(train) [54][480/940] lr: 1.0000e-03 eta: 9:59:47 time: 0.9412 data_time: 0.0486 memory: 22701 grad_norm: 4.8481 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0910 loss: 1.0910 2022/09/05 20:58:12 - mmengine - INFO - Epoch(train) [54][500/940] lr: 1.0000e-03 eta: 9:59:30 time: 0.8212 data_time: 0.1042 memory: 22701 grad_norm: 4.7789 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1474 loss: 1.1474 2022/09/05 20:58:32 - mmengine - INFO - Epoch(train) [54][520/940] lr: 1.0000e-03 eta: 9:59:17 time: 1.0361 data_time: 0.0340 memory: 22701 grad_norm: 4.7616 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.1006 loss: 1.1006 2022/09/05 20:58:49 - mmengine - INFO - Epoch(train) [54][540/940] lr: 1.0000e-03 eta: 9:59:01 time: 0.8399 data_time: 0.1096 memory: 22701 grad_norm: 4.8554 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1841 loss: 1.1841 2022/09/05 20:59:10 - mmengine - INFO - Epoch(train) [54][560/940] lr: 1.0000e-03 eta: 9:58:48 time: 1.0173 data_time: 0.2615 memory: 22701 grad_norm: 4.7757 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1222 loss: 1.1222 2022/09/05 20:59:27 - mmengine - INFO - Epoch(train) [54][580/940] lr: 1.0000e-03 eta: 9:58:32 time: 0.8809 data_time: 0.1213 memory: 22701 grad_norm: 4.7683 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0560 loss: 1.0560 2022/09/05 20:59:49 - mmengine - INFO - Epoch(train) [54][600/940] lr: 1.0000e-03 eta: 9:58:21 time: 1.0927 data_time: 0.1180 memory: 22701 grad_norm: 4.7962 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1030 loss: 1.1030 2022/09/05 21:00:09 - mmengine - INFO - Epoch(train) [54][620/940] lr: 1.0000e-03 eta: 9:58:07 time: 1.0161 data_time: 0.2474 memory: 22701 grad_norm: 4.6718 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0518 loss: 1.0518 2022/09/05 21:00:27 - mmengine - INFO - Epoch(train) [54][640/940] lr: 1.0000e-03 eta: 9:57:52 time: 0.8609 data_time: 0.1515 memory: 22701 grad_norm: 4.8088 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0816 loss: 1.0816 2022/09/05 21:00:43 - mmengine - INFO - Epoch(train) [54][660/940] lr: 1.0000e-03 eta: 9:57:35 time: 0.8324 data_time: 0.0513 memory: 22701 grad_norm: 4.7612 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0796 loss: 1.0796 2022/09/05 21:00:58 - mmengine - INFO - Epoch(train) [54][680/940] lr: 1.0000e-03 eta: 9:57:18 time: 0.7543 data_time: 0.0663 memory: 22701 grad_norm: 4.8338 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0907 loss: 1.0907 2022/09/05 21:01:13 - mmengine - INFO - Epoch(train) [54][700/940] lr: 1.0000e-03 eta: 9:57:00 time: 0.7477 data_time: 0.0705 memory: 22701 grad_norm: 4.7989 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0492 loss: 1.0492 2022/09/05 21:01:31 - mmengine - INFO - Epoch(train) [54][720/940] lr: 1.0000e-03 eta: 9:56:44 time: 0.8654 data_time: 0.0600 memory: 22701 grad_norm: 4.8063 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9903 loss: 0.9903 2022/09/05 21:01:45 - mmengine - INFO - Epoch(train) [54][740/940] lr: 1.0000e-03 eta: 9:56:26 time: 0.7255 data_time: 0.0277 memory: 22701 grad_norm: 4.7840 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1532 loss: 1.1532 2022/09/05 21:02:01 - mmengine - INFO - Epoch(train) [54][760/940] lr: 1.0000e-03 eta: 9:56:09 time: 0.8104 data_time: 0.0299 memory: 22701 grad_norm: 4.8329 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1788 loss: 1.1788 2022/09/05 21:02:16 - mmengine - INFO - Epoch(train) [54][780/940] lr: 1.0000e-03 eta: 9:55:51 time: 0.7237 data_time: 0.0322 memory: 22701 grad_norm: 4.7829 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1793 loss: 1.1793 2022/09/05 21:02:32 - mmengine - INFO - Epoch(train) [54][800/940] lr: 1.0000e-03 eta: 9:55:35 time: 0.8329 data_time: 0.0218 memory: 22701 grad_norm: 4.6928 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1408 loss: 1.1408 2022/09/05 21:02:47 - mmengine - INFO - Epoch(train) [54][820/940] lr: 1.0000e-03 eta: 9:55:16 time: 0.7004 data_time: 0.0326 memory: 22701 grad_norm: 4.7873 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9476 loss: 0.9476 2022/09/05 21:03:03 - mmengine - INFO - Epoch(train) [54][840/940] lr: 1.0000e-03 eta: 9:55:00 time: 0.8355 data_time: 0.0220 memory: 22701 grad_norm: 4.8912 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1806 loss: 1.1806 2022/09/05 21:03:18 - mmengine - INFO - Epoch(train) [54][860/940] lr: 1.0000e-03 eta: 9:54:42 time: 0.7407 data_time: 0.0313 memory: 22701 grad_norm: 4.7842 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0459 loss: 1.0459 2022/09/05 21:03:35 - mmengine - INFO - Epoch(train) [54][880/940] lr: 1.0000e-03 eta: 9:54:25 time: 0.8250 data_time: 0.0239 memory: 22701 grad_norm: 4.7911 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1306 loss: 1.1306 2022/09/05 21:03:50 - mmengine - INFO - Epoch(train) [54][900/940] lr: 1.0000e-03 eta: 9:54:08 time: 0.7562 data_time: 0.0285 memory: 22701 grad_norm: 4.8706 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0631 loss: 1.0631 2022/09/05 21:04:08 - mmengine - INFO - Epoch(train) [54][920/940] lr: 1.0000e-03 eta: 9:53:53 time: 0.8952 data_time: 0.0243 memory: 22701 grad_norm: 4.8059 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0290 loss: 1.0290 2022/09/05 21:04:22 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:04:22 - mmengine - INFO - Epoch(train) [54][940/940] lr: 1.0000e-03 eta: 9:53:34 time: 0.7183 data_time: 0.0204 memory: 22701 grad_norm: 5.0955 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.1550 loss: 1.1550 2022/09/05 21:04:22 - mmengine - INFO - Saving checkpoint at 54 epochs 2022/09/05 21:04:38 - mmengine - INFO - Epoch(val) [54][20/78] eta: 0:00:40 time: 0.7066 data_time: 0.5896 memory: 2247 2022/09/05 21:04:47 - mmengine - INFO - Epoch(val) [54][40/78] eta: 0:00:16 time: 0.4417 data_time: 0.3253 memory: 2247 2022/09/05 21:05:00 - mmengine - INFO - Epoch(val) [54][60/78] eta: 0:00:11 time: 0.6494 data_time: 0.5338 memory: 2247 2022/09/05 21:05:10 - mmengine - INFO - Epoch(val) [54][78/78] acc/top1: 0.6873 acc/top5: 0.8839 acc/mean1: 0.6872 2022/09/05 21:05:10 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_54.pth is removed 2022/09/05 21:05:11 - mmengine - INFO - The best checkpoint with 0.6873 acc/top1 at 55 epoch is saved to best_acc/top1_epoch_55.pth. 2022/09/05 21:05:32 - mmengine - INFO - Epoch(train) [55][20/940] lr: 1.0000e-03 eta: 9:53:22 time: 1.0516 data_time: 0.6544 memory: 22701 grad_norm: 4.7037 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1001 loss: 1.1001 2022/09/05 21:05:46 - mmengine - INFO - Epoch(train) [55][40/940] lr: 1.0000e-03 eta: 9:53:03 time: 0.7200 data_time: 0.2774 memory: 22701 grad_norm: 4.7679 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2100 loss: 1.2100 2022/09/05 21:06:05 - mmengine - INFO - Epoch(train) [55][60/940] lr: 1.0000e-03 eta: 9:52:49 time: 0.9250 data_time: 0.2288 memory: 22701 grad_norm: 4.7145 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0452 loss: 1.0452 2022/09/05 21:06:19 - mmengine - INFO - Epoch(train) [55][80/940] lr: 1.0000e-03 eta: 9:52:30 time: 0.6853 data_time: 0.0570 memory: 22701 grad_norm: 4.7181 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0297 loss: 1.0297 2022/09/05 21:06:36 - mmengine - INFO - Epoch(train) [55][100/940] lr: 1.0000e-03 eta: 9:52:14 time: 0.8452 data_time: 0.0471 memory: 22701 grad_norm: 4.7944 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0672 loss: 1.0672 2022/09/05 21:06:48 - mmengine - INFO - Epoch(train) [55][120/940] lr: 1.0000e-03 eta: 9:51:54 time: 0.6176 data_time: 0.0279 memory: 22701 grad_norm: 4.6854 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0218 loss: 1.0218 2022/09/05 21:07:04 - mmengine - INFO - Epoch(train) [55][140/940] lr: 1.0000e-03 eta: 9:51:37 time: 0.8053 data_time: 0.1286 memory: 22701 grad_norm: 4.7720 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0392 loss: 1.0392 2022/09/05 21:07:18 - mmengine - INFO - Epoch(train) [55][160/940] lr: 1.0000e-03 eta: 9:51:18 time: 0.6886 data_time: 0.0872 memory: 22701 grad_norm: 4.8682 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0607 loss: 1.0607 2022/09/05 21:07:40 - mmengine - INFO - Epoch(train) [55][180/940] lr: 1.0000e-03 eta: 9:51:07 time: 1.1183 data_time: 0.0309 memory: 22701 grad_norm: 4.7536 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1074 loss: 1.1074 2022/09/05 21:07:54 - mmengine - INFO - Epoch(train) [55][200/940] lr: 1.0000e-03 eta: 9:50:48 time: 0.7091 data_time: 0.0281 memory: 22701 grad_norm: 4.8017 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1406 loss: 1.1406 2022/09/05 21:08:12 - mmengine - INFO - Epoch(train) [55][220/940] lr: 1.0000e-03 eta: 9:50:33 time: 0.8994 data_time: 0.0317 memory: 22701 grad_norm: 4.7387 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1340 loss: 1.1340 2022/09/05 21:08:27 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:08:27 - mmengine - INFO - Epoch(train) [55][240/940] lr: 1.0000e-03 eta: 9:50:15 time: 0.7427 data_time: 0.0225 memory: 22701 grad_norm: 4.8436 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0961 loss: 1.0961 2022/09/05 21:08:47 - mmengine - INFO - Epoch(train) [55][260/940] lr: 1.0000e-03 eta: 9:50:01 time: 0.9731 data_time: 0.0270 memory: 22701 grad_norm: 4.7435 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0225 loss: 1.0225 2022/09/05 21:09:02 - mmengine - INFO - Epoch(train) [55][280/940] lr: 1.0000e-03 eta: 9:49:44 time: 0.7616 data_time: 0.0253 memory: 22701 grad_norm: 4.8297 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0758 loss: 1.0758 2022/09/05 21:09:20 - mmengine - INFO - Epoch(train) [55][300/940] lr: 1.0000e-03 eta: 9:49:29 time: 0.9047 data_time: 0.0268 memory: 22701 grad_norm: 4.8148 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0554 loss: 1.0554 2022/09/05 21:09:36 - mmengine - INFO - Epoch(train) [55][320/940] lr: 1.0000e-03 eta: 9:49:12 time: 0.8128 data_time: 0.0254 memory: 22701 grad_norm: 4.7549 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0144 loss: 1.0144 2022/09/05 21:09:53 - mmengine - INFO - Epoch(train) [55][340/940] lr: 1.0000e-03 eta: 9:48:56 time: 0.8651 data_time: 0.0240 memory: 22701 grad_norm: 4.8681 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1221 loss: 1.1221 2022/09/05 21:10:09 - mmengine - INFO - Epoch(train) [55][360/940] lr: 1.0000e-03 eta: 9:48:39 time: 0.7944 data_time: 0.0280 memory: 22701 grad_norm: 4.8562 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.1516 loss: 1.1516 2022/09/05 21:10:27 - mmengine - INFO - Epoch(train) [55][380/940] lr: 1.0000e-03 eta: 9:48:24 time: 0.8767 data_time: 0.0240 memory: 22701 grad_norm: 4.7976 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0683 loss: 1.0683 2022/09/05 21:10:40 - mmengine - INFO - Epoch(train) [55][400/940] lr: 1.0000e-03 eta: 9:48:05 time: 0.6637 data_time: 0.0237 memory: 22701 grad_norm: 4.8685 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1897 loss: 1.1897 2022/09/05 21:10:57 - mmengine - INFO - Epoch(train) [55][420/940] lr: 1.0000e-03 eta: 9:47:49 time: 0.8531 data_time: 0.0269 memory: 22701 grad_norm: 4.6537 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0466 loss: 1.0466 2022/09/05 21:11:13 - mmengine - INFO - Epoch(train) [55][440/940] lr: 1.0000e-03 eta: 9:47:31 time: 0.7737 data_time: 0.0270 memory: 22701 grad_norm: 4.8155 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0859 loss: 1.0859 2022/09/05 21:11:32 - mmengine - INFO - Epoch(train) [55][460/940] lr: 1.0000e-03 eta: 9:47:18 time: 0.9881 data_time: 0.0251 memory: 22701 grad_norm: 4.8175 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2073 loss: 1.2073 2022/09/05 21:11:49 - mmengine - INFO - Epoch(train) [55][480/940] lr: 1.0000e-03 eta: 9:47:01 time: 0.8222 data_time: 0.0537 memory: 22701 grad_norm: 4.8397 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0682 loss: 1.0682 2022/09/05 21:12:12 - mmengine - INFO - Epoch(train) [55][500/940] lr: 1.0000e-03 eta: 9:46:51 time: 1.1764 data_time: 0.0339 memory: 22701 grad_norm: 4.8469 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.1643 loss: 1.1643 2022/09/05 21:12:29 - mmengine - INFO - Epoch(train) [55][520/940] lr: 1.0000e-03 eta: 9:46:34 time: 0.8098 data_time: 0.0252 memory: 22701 grad_norm: 4.8973 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2061 loss: 1.2061 2022/09/05 21:12:49 - mmengine - INFO - Epoch(train) [55][540/940] lr: 1.0000e-03 eta: 9:46:20 time: 0.9946 data_time: 0.0247 memory: 22701 grad_norm: 4.7648 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0501 loss: 1.0501 2022/09/05 21:13:04 - mmengine - INFO - Epoch(train) [55][560/940] lr: 1.0000e-03 eta: 9:46:03 time: 0.7984 data_time: 0.0445 memory: 22701 grad_norm: 4.9091 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1225 loss: 1.1225 2022/09/05 21:13:24 - mmengine - INFO - Epoch(train) [55][580/940] lr: 1.0000e-03 eta: 9:45:49 time: 0.9635 data_time: 0.0268 memory: 22701 grad_norm: 4.8337 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1528 loss: 1.1528 2022/09/05 21:13:40 - mmengine - INFO - Epoch(train) [55][600/940] lr: 1.0000e-03 eta: 9:45:32 time: 0.8123 data_time: 0.0247 memory: 22701 grad_norm: 4.7892 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.0910 loss: 1.0910 2022/09/05 21:13:59 - mmengine - INFO - Epoch(train) [55][620/940] lr: 1.0000e-03 eta: 9:45:18 time: 0.9737 data_time: 0.0309 memory: 22701 grad_norm: 4.7189 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.9833 loss: 0.9833 2022/09/05 21:14:16 - mmengine - INFO - Epoch(train) [55][640/940] lr: 1.0000e-03 eta: 9:45:02 time: 0.8064 data_time: 0.0220 memory: 22701 grad_norm: 4.8822 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2027 loss: 1.2027 2022/09/05 21:14:33 - mmengine - INFO - Epoch(train) [55][660/940] lr: 1.0000e-03 eta: 9:44:46 time: 0.8914 data_time: 0.0400 memory: 22701 grad_norm: 4.8745 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1511 loss: 1.1511 2022/09/05 21:14:52 - mmengine - INFO - Epoch(train) [55][680/940] lr: 1.0000e-03 eta: 9:44:31 time: 0.9018 data_time: 0.0700 memory: 22701 grad_norm: 4.9509 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1030 loss: 1.1030 2022/09/05 21:15:08 - mmengine - INFO - Epoch(train) [55][700/940] lr: 1.0000e-03 eta: 9:44:15 time: 0.8286 data_time: 0.2212 memory: 22701 grad_norm: 4.8785 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1297 loss: 1.1297 2022/09/05 21:15:24 - mmengine - INFO - Epoch(train) [55][720/940] lr: 1.0000e-03 eta: 9:43:58 time: 0.8002 data_time: 0.2584 memory: 22701 grad_norm: 4.8824 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1750 loss: 1.1750 2022/09/05 21:15:44 - mmengine - INFO - Epoch(train) [55][740/940] lr: 1.0000e-03 eta: 9:43:44 time: 0.9793 data_time: 0.5474 memory: 22701 grad_norm: 4.8206 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0183 loss: 1.0183 2022/09/05 21:15:58 - mmengine - INFO - Epoch(train) [55][760/940] lr: 1.0000e-03 eta: 9:43:26 time: 0.7066 data_time: 0.2515 memory: 22701 grad_norm: 4.8943 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0601 loss: 1.0601 2022/09/05 21:16:13 - mmengine - INFO - Epoch(train) [55][780/940] lr: 1.0000e-03 eta: 9:43:08 time: 0.7808 data_time: 0.2771 memory: 22701 grad_norm: 4.7692 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1031 loss: 1.1031 2022/09/05 21:16:28 - mmengine - INFO - Epoch(train) [55][800/940] lr: 1.0000e-03 eta: 9:42:50 time: 0.7343 data_time: 0.3081 memory: 22701 grad_norm: 4.8183 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1060 loss: 1.1060 2022/09/05 21:16:45 - mmengine - INFO - Epoch(train) [55][820/940] lr: 1.0000e-03 eta: 9:42:34 time: 0.8495 data_time: 0.4260 memory: 22701 grad_norm: 4.8191 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2123 loss: 1.2123 2022/09/05 21:16:58 - mmengine - INFO - Epoch(train) [55][840/940] lr: 1.0000e-03 eta: 9:42:15 time: 0.6503 data_time: 0.2470 memory: 22701 grad_norm: 4.8379 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1085 loss: 1.1085 2022/09/05 21:17:17 - mmengine - INFO - Epoch(train) [55][860/940] lr: 1.0000e-03 eta: 9:42:00 time: 0.9436 data_time: 0.5465 memory: 22701 grad_norm: 4.8017 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0652 loss: 1.0652 2022/09/05 21:17:33 - mmengine - INFO - Epoch(train) [55][880/940] lr: 1.0000e-03 eta: 9:41:43 time: 0.7888 data_time: 0.3897 memory: 22701 grad_norm: 4.7708 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1374 loss: 1.1374 2022/09/05 21:17:54 - mmengine - INFO - Epoch(train) [55][900/940] lr: 1.0000e-03 eta: 9:41:30 time: 1.0390 data_time: 0.6386 memory: 22701 grad_norm: 4.9056 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2031 loss: 1.2031 2022/09/05 21:18:09 - mmengine - INFO - Epoch(train) [55][920/940] lr: 1.0000e-03 eta: 9:41:13 time: 0.7750 data_time: 0.3818 memory: 22701 grad_norm: 4.8577 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1089 loss: 1.1089 2022/09/05 21:18:29 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:18:29 - mmengine - INFO - Epoch(train) [55][940/940] lr: 1.0000e-03 eta: 9:40:59 time: 0.9824 data_time: 0.6028 memory: 22701 grad_norm: 5.2424 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2253 loss: 1.2253 2022/09/05 21:18:43 - mmengine - INFO - Epoch(val) [55][20/78] eta: 0:00:40 time: 0.6952 data_time: 0.5758 memory: 2247 2022/09/05 21:18:52 - mmengine - INFO - Epoch(val) [55][40/78] eta: 0:00:18 time: 0.4786 data_time: 0.3579 memory: 2247 2022/09/05 21:19:05 - mmengine - INFO - Epoch(val) [55][60/78] eta: 0:00:10 time: 0.6088 data_time: 0.4904 memory: 2247 2022/09/05 21:19:15 - mmengine - INFO - Epoch(val) [55][78/78] acc/top1: 0.6877 acc/top5: 0.8822 acc/mean1: 0.6876 2022/09/05 21:19:15 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_55.pth is removed 2022/09/05 21:19:17 - mmengine - INFO - The best checkpoint with 0.6877 acc/top1 at 56 epoch is saved to best_acc/top1_epoch_56.pth. 2022/09/05 21:19:41 - mmengine - INFO - Epoch(train) [56][20/940] lr: 1.0000e-03 eta: 9:40:50 time: 1.2388 data_time: 0.7912 memory: 22701 grad_norm: 4.8891 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1768 loss: 1.1768 2022/09/05 21:19:59 - mmengine - INFO - Epoch(train) [56][40/940] lr: 1.0000e-03 eta: 9:40:34 time: 0.9033 data_time: 0.4218 memory: 22701 grad_norm: 4.8067 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1174 loss: 1.1174 2022/09/05 21:20:19 - mmengine - INFO - Epoch(train) [56][60/940] lr: 1.0000e-03 eta: 9:40:21 time: 0.9880 data_time: 0.4738 memory: 22701 grad_norm: 4.6669 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1054 loss: 1.1054 2022/09/05 21:20:34 - mmengine - INFO - Epoch(train) [56][80/940] lr: 1.0000e-03 eta: 9:40:03 time: 0.7284 data_time: 0.2660 memory: 22701 grad_norm: 4.7334 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1598 loss: 1.1598 2022/09/05 21:20:53 - mmengine - INFO - Epoch(train) [56][100/940] lr: 1.0000e-03 eta: 9:39:48 time: 0.9537 data_time: 0.4711 memory: 22701 grad_norm: 4.7482 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.1600 loss: 1.1600 2022/09/05 21:21:10 - mmengine - INFO - Epoch(train) [56][120/940] lr: 1.0000e-03 eta: 9:39:32 time: 0.8618 data_time: 0.2293 memory: 22701 grad_norm: 4.8854 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0481 loss: 1.0481 2022/09/05 21:21:28 - mmengine - INFO - Epoch(train) [56][140/940] lr: 1.0000e-03 eta: 9:39:17 time: 0.9061 data_time: 0.2817 memory: 22701 grad_norm: 4.8353 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1043 loss: 1.1043 2022/09/05 21:21:46 - mmengine - INFO - Epoch(train) [56][160/940] lr: 1.0000e-03 eta: 9:39:02 time: 0.8969 data_time: 0.2210 memory: 22701 grad_norm: 4.8279 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0319 loss: 1.0319 2022/09/05 21:22:04 - mmengine - INFO - Epoch(train) [56][180/940] lr: 1.0000e-03 eta: 9:38:47 time: 0.9173 data_time: 0.0277 memory: 22701 grad_norm: 4.8686 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1448 loss: 1.1448 2022/09/05 21:22:21 - mmengine - INFO - Epoch(train) [56][200/940] lr: 1.0000e-03 eta: 9:38:30 time: 0.8294 data_time: 0.0678 memory: 22701 grad_norm: 4.7821 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0416 loss: 1.0416 2022/09/05 21:22:40 - mmengine - INFO - Epoch(train) [56][220/940] lr: 1.0000e-03 eta: 9:38:16 time: 0.9535 data_time: 0.0610 memory: 22701 grad_norm: 4.7130 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1251 loss: 1.1251 2022/09/05 21:22:55 - mmengine - INFO - Epoch(train) [56][240/940] lr: 1.0000e-03 eta: 9:37:58 time: 0.7512 data_time: 0.1532 memory: 22701 grad_norm: 4.8220 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0882 loss: 1.0882 2022/09/05 21:23:15 - mmengine - INFO - Epoch(train) [56][260/940] lr: 1.0000e-03 eta: 9:37:45 time: 0.9975 data_time: 0.5641 memory: 22701 grad_norm: 4.8482 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0229 loss: 1.0229 2022/09/05 21:23:31 - mmengine - INFO - Epoch(train) [56][280/940] lr: 1.0000e-03 eta: 9:37:28 time: 0.7933 data_time: 0.3889 memory: 22701 grad_norm: 4.7879 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0671 loss: 1.0671 2022/09/05 21:23:49 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:23:49 - mmengine - INFO - Epoch(train) [56][300/940] lr: 1.0000e-03 eta: 9:37:12 time: 0.8992 data_time: 0.4789 memory: 22701 grad_norm: 4.8660 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.2268 loss: 1.2268 2022/09/05 21:24:05 - mmengine - INFO - Epoch(train) [56][320/940] lr: 1.0000e-03 eta: 9:36:55 time: 0.7829 data_time: 0.2208 memory: 22701 grad_norm: 4.7887 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0278 loss: 1.0278 2022/09/05 21:24:22 - mmengine - INFO - Epoch(train) [56][340/940] lr: 1.0000e-03 eta: 9:36:39 time: 0.8547 data_time: 0.0991 memory: 22701 grad_norm: 4.7913 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0344 loss: 1.0344 2022/09/05 21:24:37 - mmengine - INFO - Epoch(train) [56][360/940] lr: 1.0000e-03 eta: 9:36:22 time: 0.7676 data_time: 0.1205 memory: 22701 grad_norm: 4.8056 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0717 loss: 1.0717 2022/09/05 21:24:55 - mmengine - INFO - Epoch(train) [56][380/940] lr: 1.0000e-03 eta: 9:36:06 time: 0.8930 data_time: 0.2250 memory: 22701 grad_norm: 4.8214 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0395 loss: 1.0395 2022/09/05 21:25:09 - mmengine - INFO - Epoch(train) [56][400/940] lr: 1.0000e-03 eta: 9:35:48 time: 0.7180 data_time: 0.1698 memory: 22701 grad_norm: 4.6936 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1244 loss: 1.1244 2022/09/05 21:25:29 - mmengine - INFO - Epoch(train) [56][420/940] lr: 1.0000e-03 eta: 9:35:34 time: 0.9940 data_time: 0.5635 memory: 22701 grad_norm: 4.7852 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9921 loss: 0.9921 2022/09/05 21:25:45 - mmengine - INFO - Epoch(train) [56][440/940] lr: 1.0000e-03 eta: 9:35:17 time: 0.7669 data_time: 0.2251 memory: 22701 grad_norm: 4.8077 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1421 loss: 1.1421 2022/09/05 21:26:05 - mmengine - INFO - Epoch(train) [56][460/940] lr: 1.0000e-03 eta: 9:35:03 time: 1.0000 data_time: 0.2415 memory: 22701 grad_norm: 4.8040 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.0170 loss: 1.0170 2022/09/05 21:26:21 - mmengine - INFO - Epoch(train) [56][480/940] lr: 1.0000e-03 eta: 9:34:47 time: 0.8064 data_time: 0.1689 memory: 22701 grad_norm: 4.7344 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1030 loss: 1.1030 2022/09/05 21:26:40 - mmengine - INFO - Epoch(train) [56][500/940] lr: 1.0000e-03 eta: 9:34:32 time: 0.9556 data_time: 0.2479 memory: 22701 grad_norm: 4.8518 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1286 loss: 1.1286 2022/09/05 21:26:55 - mmengine - INFO - Epoch(train) [56][520/940] lr: 1.0000e-03 eta: 9:34:15 time: 0.7626 data_time: 0.1553 memory: 22701 grad_norm: 4.8569 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1079 loss: 1.1079 2022/09/05 21:27:15 - mmengine - INFO - Epoch(train) [56][540/940] lr: 1.0000e-03 eta: 9:34:01 time: 1.0120 data_time: 0.2121 memory: 22701 grad_norm: 4.8621 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0909 loss: 1.0909 2022/09/05 21:27:31 - mmengine - INFO - Epoch(train) [56][560/940] lr: 1.0000e-03 eta: 9:33:44 time: 0.7948 data_time: 0.2163 memory: 22701 grad_norm: 4.7788 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0621 loss: 1.0621 2022/09/05 21:27:51 - mmengine - INFO - Epoch(train) [56][580/940] lr: 1.0000e-03 eta: 9:33:31 time: 1.0134 data_time: 0.2617 memory: 22701 grad_norm: 4.8765 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0849 loss: 1.0849 2022/09/05 21:28:06 - mmengine - INFO - Epoch(train) [56][600/940] lr: 1.0000e-03 eta: 9:33:12 time: 0.7067 data_time: 0.1143 memory: 22701 grad_norm: 4.7740 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1678 loss: 1.1678 2022/09/05 21:28:23 - mmengine - INFO - Epoch(train) [56][620/940] lr: 1.0000e-03 eta: 9:32:57 time: 0.8944 data_time: 0.1743 memory: 22701 grad_norm: 4.8654 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1026 loss: 1.1026 2022/09/05 21:28:46 - mmengine - INFO - Epoch(train) [56][640/940] lr: 1.0000e-03 eta: 9:32:45 time: 1.1237 data_time: 0.5452 memory: 22701 grad_norm: 4.7983 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1482 loss: 1.1482 2022/09/05 21:29:03 - mmengine - INFO - Epoch(train) [56][660/940] lr: 1.0000e-03 eta: 9:32:29 time: 0.8732 data_time: 0.2295 memory: 22701 grad_norm: 4.7469 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0346 loss: 1.0346 2022/09/05 21:29:21 - mmengine - INFO - Epoch(train) [56][680/940] lr: 1.0000e-03 eta: 9:32:14 time: 0.9026 data_time: 0.3732 memory: 22701 grad_norm: 4.9565 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1193 loss: 1.1193 2022/09/05 21:29:38 - mmengine - INFO - Epoch(train) [56][700/940] lr: 1.0000e-03 eta: 9:31:58 time: 0.8217 data_time: 0.3578 memory: 22701 grad_norm: 4.8258 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0398 loss: 1.0398 2022/09/05 21:29:57 - mmengine - INFO - Epoch(train) [56][720/940] lr: 1.0000e-03 eta: 9:31:43 time: 0.9432 data_time: 0.5589 memory: 22701 grad_norm: 4.8877 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0349 loss: 1.0349 2022/09/05 21:30:11 - mmengine - INFO - Epoch(train) [56][740/940] lr: 1.0000e-03 eta: 9:31:24 time: 0.6949 data_time: 0.2923 memory: 22701 grad_norm: 4.7849 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0990 loss: 1.0990 2022/09/05 21:30:28 - mmengine - INFO - Epoch(train) [56][760/940] lr: 1.0000e-03 eta: 9:31:08 time: 0.8553 data_time: 0.4402 memory: 22701 grad_norm: 4.8673 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2119 loss: 1.2119 2022/09/05 21:30:43 - mmengine - INFO - Epoch(train) [56][780/940] lr: 1.0000e-03 eta: 9:30:51 time: 0.7592 data_time: 0.2627 memory: 22701 grad_norm: 4.8080 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1347 loss: 1.1347 2022/09/05 21:30:59 - mmengine - INFO - Epoch(train) [56][800/940] lr: 1.0000e-03 eta: 9:30:34 time: 0.7991 data_time: 0.3704 memory: 22701 grad_norm: 4.9136 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0771 loss: 1.0771 2022/09/05 21:31:14 - mmengine - INFO - Epoch(train) [56][820/940] lr: 1.0000e-03 eta: 9:30:16 time: 0.7286 data_time: 0.3170 memory: 22701 grad_norm: 4.8569 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1236 loss: 1.1236 2022/09/05 21:31:31 - mmengine - INFO - Epoch(train) [56][840/940] lr: 1.0000e-03 eta: 9:30:00 time: 0.8756 data_time: 0.4175 memory: 22701 grad_norm: 4.8913 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0823 loss: 1.0823 2022/09/05 21:31:47 - mmengine - INFO - Epoch(train) [56][860/940] lr: 1.0000e-03 eta: 9:29:43 time: 0.7957 data_time: 0.2089 memory: 22701 grad_norm: 4.8211 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0739 loss: 1.0739 2022/09/05 21:32:02 - mmengine - INFO - Epoch(train) [56][880/940] lr: 1.0000e-03 eta: 9:29:25 time: 0.7336 data_time: 0.2746 memory: 22701 grad_norm: 4.9460 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0985 loss: 1.0985 2022/09/05 21:32:17 - mmengine - INFO - Epoch(train) [56][900/940] lr: 1.0000e-03 eta: 9:29:08 time: 0.7893 data_time: 0.3107 memory: 22701 grad_norm: 4.9056 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0979 loss: 1.0979 2022/09/05 21:32:34 - mmengine - INFO - Epoch(train) [56][920/940] lr: 1.0000e-03 eta: 9:28:52 time: 0.8419 data_time: 0.3711 memory: 22701 grad_norm: 4.8647 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9901 loss: 0.9901 2022/09/05 21:32:49 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:32:49 - mmengine - INFO - Epoch(train) [56][940/940] lr: 1.0000e-03 eta: 9:28:34 time: 0.7540 data_time: 0.1981 memory: 22701 grad_norm: 5.1990 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.2332 loss: 1.2332 2022/09/05 21:33:03 - mmengine - INFO - Epoch(val) [56][20/78] eta: 0:00:39 time: 0.6870 data_time: 0.5687 memory: 2247 2022/09/05 21:33:12 - mmengine - INFO - Epoch(val) [56][40/78] eta: 0:00:17 time: 0.4585 data_time: 0.3396 memory: 2247 2022/09/05 21:33:26 - mmengine - INFO - Epoch(val) [56][60/78] eta: 0:00:12 time: 0.6697 data_time: 0.5474 memory: 2247 2022/09/05 21:33:35 - mmengine - INFO - Epoch(val) [56][78/78] acc/top1: 0.6869 acc/top5: 0.8817 acc/mean1: 0.6867 2022/09/05 21:33:55 - mmengine - INFO - Epoch(train) [57][20/940] lr: 1.0000e-03 eta: 9:28:20 time: 0.9591 data_time: 0.5625 memory: 22701 grad_norm: 4.8639 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1285 loss: 1.1285 2022/09/05 21:34:08 - mmengine - INFO - Epoch(train) [57][40/940] lr: 1.0000e-03 eta: 9:28:01 time: 0.6756 data_time: 0.2767 memory: 22701 grad_norm: 4.8488 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0297 loss: 1.0297 2022/09/05 21:34:25 - mmengine - INFO - Epoch(train) [57][60/940] lr: 1.0000e-03 eta: 9:27:45 time: 0.8490 data_time: 0.4560 memory: 22701 grad_norm: 4.8213 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1101 loss: 1.1101 2022/09/05 21:34:39 - mmengine - INFO - Epoch(train) [57][80/940] lr: 1.0000e-03 eta: 9:27:27 time: 0.7089 data_time: 0.3312 memory: 22701 grad_norm: 4.8173 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0129 loss: 1.0129 2022/09/05 21:34:58 - mmengine - INFO - Epoch(train) [57][100/940] lr: 1.0000e-03 eta: 9:27:12 time: 0.9429 data_time: 0.5197 memory: 22701 grad_norm: 4.8962 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1066 loss: 1.1066 2022/09/05 21:35:12 - mmengine - INFO - Epoch(train) [57][120/940] lr: 1.0000e-03 eta: 9:26:54 time: 0.7098 data_time: 0.3146 memory: 22701 grad_norm: 4.7930 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0676 loss: 1.0676 2022/09/05 21:35:30 - mmengine - INFO - Epoch(train) [57][140/940] lr: 1.0000e-03 eta: 9:26:38 time: 0.8849 data_time: 0.4739 memory: 22701 grad_norm: 4.7237 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1377 loss: 1.1377 2022/09/05 21:35:44 - mmengine - INFO - Epoch(train) [57][160/940] lr: 1.0000e-03 eta: 9:26:19 time: 0.6760 data_time: 0.2927 memory: 22701 grad_norm: 4.7941 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0459 loss: 1.0459 2022/09/05 21:36:03 - mmengine - INFO - Epoch(train) [57][180/940] lr: 1.0000e-03 eta: 9:26:05 time: 0.9718 data_time: 0.5859 memory: 22701 grad_norm: 4.8358 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9788 loss: 0.9788 2022/09/05 21:36:17 - mmengine - INFO - Epoch(train) [57][200/940] lr: 1.0000e-03 eta: 9:25:47 time: 0.6899 data_time: 0.3112 memory: 22701 grad_norm: 4.8692 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1184 loss: 1.1184 2022/09/05 21:36:32 - mmengine - INFO - Epoch(train) [57][220/940] lr: 1.0000e-03 eta: 9:25:29 time: 0.7695 data_time: 0.3807 memory: 22701 grad_norm: 4.8896 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1470 loss: 1.1470 2022/09/05 21:36:47 - mmengine - INFO - Epoch(train) [57][240/940] lr: 1.0000e-03 eta: 9:25:12 time: 0.7428 data_time: 0.1663 memory: 22701 grad_norm: 4.8581 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.1858 loss: 1.1858 2022/09/05 21:37:04 - mmengine - INFO - Epoch(train) [57][260/940] lr: 1.0000e-03 eta: 9:24:55 time: 0.8402 data_time: 0.0414 memory: 22701 grad_norm: 4.8487 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1044 loss: 1.1044 2022/09/05 21:37:17 - mmengine - INFO - Epoch(train) [57][280/940] lr: 1.0000e-03 eta: 9:24:36 time: 0.6310 data_time: 0.0256 memory: 22701 grad_norm: 4.8964 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9950 loss: 0.9950 2022/09/05 21:37:34 - mmengine - INFO - Epoch(train) [57][300/940] lr: 1.0000e-03 eta: 9:24:20 time: 0.8505 data_time: 0.0632 memory: 22701 grad_norm: 4.8617 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0658 loss: 1.0658 2022/09/05 21:37:51 - mmengine - INFO - Epoch(train) [57][320/940] lr: 1.0000e-03 eta: 9:24:04 time: 0.8529 data_time: 0.1094 memory: 22701 grad_norm: 4.8736 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1135 loss: 1.1135 2022/09/05 21:38:09 - mmengine - INFO - Epoch(train) [57][340/940] lr: 1.0000e-03 eta: 9:23:48 time: 0.9027 data_time: 0.2708 memory: 22701 grad_norm: 5.0133 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1079 loss: 1.1079 2022/09/05 21:38:26 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:38:26 - mmengine - INFO - Epoch(train) [57][360/940] lr: 1.0000e-03 eta: 9:23:33 time: 0.8859 data_time: 0.0428 memory: 22701 grad_norm: 4.9476 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2461 loss: 1.2461 2022/09/05 21:38:46 - mmengine - INFO - Epoch(train) [57][380/940] lr: 1.0000e-03 eta: 9:23:18 time: 0.9589 data_time: 0.0945 memory: 22701 grad_norm: 4.8275 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1420 loss: 1.1420 2022/09/05 21:39:03 - mmengine - INFO - Epoch(train) [57][400/940] lr: 1.0000e-03 eta: 9:23:03 time: 0.8742 data_time: 0.2582 memory: 22701 grad_norm: 4.8021 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9907 loss: 0.9907 2022/09/05 21:39:25 - mmengine - INFO - Epoch(train) [57][420/940] lr: 1.0000e-03 eta: 9:22:50 time: 1.0934 data_time: 0.6461 memory: 22701 grad_norm: 4.8497 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1628 loss: 1.1628 2022/09/05 21:39:41 - mmengine - INFO - Epoch(train) [57][440/940] lr: 1.0000e-03 eta: 9:22:34 time: 0.8216 data_time: 0.4442 memory: 22701 grad_norm: 4.9331 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1473 loss: 1.1473 2022/09/05 21:40:01 - mmengine - INFO - Epoch(train) [57][460/940] lr: 1.0000e-03 eta: 9:22:19 time: 0.9568 data_time: 0.5394 memory: 22701 grad_norm: 4.7858 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9858 loss: 0.9858 2022/09/05 21:40:14 - mmengine - INFO - Epoch(train) [57][480/940] lr: 1.0000e-03 eta: 9:22:00 time: 0.6591 data_time: 0.2807 memory: 22701 grad_norm: 4.8711 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1050 loss: 1.1050 2022/09/05 21:40:32 - mmengine - INFO - Epoch(train) [57][500/940] lr: 1.0000e-03 eta: 9:21:45 time: 0.9099 data_time: 0.4968 memory: 22701 grad_norm: 4.8869 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0807 loss: 1.0807 2022/09/05 21:40:48 - mmengine - INFO - Epoch(train) [57][520/940] lr: 1.0000e-03 eta: 9:21:28 time: 0.7957 data_time: 0.3564 memory: 22701 grad_norm: 4.7804 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0590 loss: 1.0590 2022/09/05 21:41:11 - mmengine - INFO - Epoch(train) [57][540/940] lr: 1.0000e-03 eta: 9:21:16 time: 1.1315 data_time: 0.4982 memory: 22701 grad_norm: 4.8785 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1006 loss: 1.1006 2022/09/05 21:41:25 - mmengine - INFO - Epoch(train) [57][560/940] lr: 1.0000e-03 eta: 9:20:58 time: 0.7218 data_time: 0.2982 memory: 22701 grad_norm: 4.9730 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1308 loss: 1.1308 2022/09/05 21:41:46 - mmengine - INFO - Epoch(train) [57][580/940] lr: 1.0000e-03 eta: 9:20:45 time: 1.0399 data_time: 0.5328 memory: 22701 grad_norm: 4.8674 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1946 loss: 1.1946 2022/09/05 21:42:02 - mmengine - INFO - Epoch(train) [57][600/940] lr: 1.0000e-03 eta: 9:20:28 time: 0.7960 data_time: 0.3442 memory: 22701 grad_norm: 4.8952 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1131 loss: 1.1131 2022/09/05 21:42:20 - mmengine - INFO - Epoch(train) [57][620/940] lr: 1.0000e-03 eta: 9:20:13 time: 0.9220 data_time: 0.4453 memory: 22701 grad_norm: 4.9587 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1843 loss: 1.1843 2022/09/05 21:42:37 - mmengine - INFO - Epoch(train) [57][640/940] lr: 1.0000e-03 eta: 9:19:57 time: 0.8240 data_time: 0.1501 memory: 22701 grad_norm: 4.8840 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0268 loss: 1.0268 2022/09/05 21:42:52 - mmengine - INFO - Epoch(train) [57][660/940] lr: 1.0000e-03 eta: 9:19:39 time: 0.7538 data_time: 0.0901 memory: 22701 grad_norm: 4.8370 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0673 loss: 1.0673 2022/09/05 21:43:08 - mmengine - INFO - Epoch(train) [57][680/940] lr: 1.0000e-03 eta: 9:19:22 time: 0.7924 data_time: 0.0474 memory: 22701 grad_norm: 4.8332 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1075 loss: 1.1075 2022/09/05 21:43:23 - mmengine - INFO - Epoch(train) [57][700/940] lr: 1.0000e-03 eta: 9:19:05 time: 0.7962 data_time: 0.1666 memory: 22701 grad_norm: 4.7624 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9554 loss: 0.9554 2022/09/05 21:43:38 - mmengine - INFO - Epoch(train) [57][720/940] lr: 1.0000e-03 eta: 9:18:47 time: 0.7464 data_time: 0.1833 memory: 22701 grad_norm: 4.8805 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1190 loss: 1.1190 2022/09/05 21:43:56 - mmengine - INFO - Epoch(train) [57][740/940] lr: 1.0000e-03 eta: 9:18:31 time: 0.8608 data_time: 0.2563 memory: 22701 grad_norm: 4.8156 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9855 loss: 0.9855 2022/09/05 21:44:11 - mmengine - INFO - Epoch(train) [57][760/940] lr: 1.0000e-03 eta: 9:18:14 time: 0.7706 data_time: 0.1428 memory: 22701 grad_norm: 4.9113 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0171 loss: 1.0171 2022/09/05 21:44:27 - mmengine - INFO - Epoch(train) [57][780/940] lr: 1.0000e-03 eta: 9:17:57 time: 0.8103 data_time: 0.1492 memory: 22701 grad_norm: 4.9936 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1048 loss: 1.1048 2022/09/05 21:44:45 - mmengine - INFO - Epoch(train) [57][800/940] lr: 1.0000e-03 eta: 9:17:42 time: 0.9074 data_time: 0.0700 memory: 22701 grad_norm: 4.8998 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1864 loss: 1.1864 2022/09/05 21:45:01 - mmengine - INFO - Epoch(train) [57][820/940] lr: 1.0000e-03 eta: 9:17:25 time: 0.7919 data_time: 0.0236 memory: 22701 grad_norm: 4.8712 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0385 loss: 1.0385 2022/09/05 21:45:21 - mmengine - INFO - Epoch(train) [57][840/940] lr: 1.0000e-03 eta: 9:17:11 time: 1.0073 data_time: 0.0725 memory: 22701 grad_norm: 4.8404 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0779 loss: 1.0779 2022/09/05 21:45:39 - mmengine - INFO - Epoch(train) [57][860/940] lr: 1.0000e-03 eta: 9:16:55 time: 0.8568 data_time: 0.0291 memory: 22701 grad_norm: 4.9166 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0668 loss: 1.0668 2022/09/05 21:45:57 - mmengine - INFO - Epoch(train) [57][880/940] lr: 1.0000e-03 eta: 9:16:40 time: 0.9296 data_time: 0.0288 memory: 22701 grad_norm: 4.8465 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1620 loss: 1.1620 2022/09/05 21:46:12 - mmengine - INFO - Epoch(train) [57][900/940] lr: 1.0000e-03 eta: 9:16:22 time: 0.7202 data_time: 0.0239 memory: 22701 grad_norm: 4.9068 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0789 loss: 1.0789 2022/09/05 21:46:31 - mmengine - INFO - Epoch(train) [57][920/940] lr: 1.0000e-03 eta: 9:16:08 time: 0.9523 data_time: 0.0264 memory: 22701 grad_norm: 4.9425 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1392 loss: 1.1392 2022/09/05 21:46:46 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:46:46 - mmengine - INFO - Epoch(train) [57][940/940] lr: 1.0000e-03 eta: 9:15:51 time: 0.7830 data_time: 0.0276 memory: 22701 grad_norm: 5.1834 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.1466 loss: 1.1466 2022/09/05 21:46:46 - mmengine - INFO - Saving checkpoint at 57 epochs 2022/09/05 21:47:02 - mmengine - INFO - Epoch(val) [57][20/78] eta: 0:00:40 time: 0.6928 data_time: 0.5768 memory: 2247 2022/09/05 21:47:11 - mmengine - INFO - Epoch(val) [57][40/78] eta: 0:00:17 time: 0.4588 data_time: 0.3433 memory: 2247 2022/09/05 21:47:24 - mmengine - INFO - Epoch(val) [57][60/78] eta: 0:00:11 time: 0.6423 data_time: 0.5241 memory: 2247 2022/09/05 21:47:33 - mmengine - INFO - Epoch(val) [57][78/78] acc/top1: 0.6890 acc/top5: 0.8825 acc/mean1: 0.6889 2022/09/05 21:47:33 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_56.pth is removed 2022/09/05 21:47:34 - mmengine - INFO - The best checkpoint with 0.6890 acc/top1 at 58 epoch is saved to best_acc/top1_epoch_58.pth. 2022/09/05 21:47:54 - mmengine - INFO - Epoch(train) [58][20/940] lr: 1.0000e-03 eta: 9:15:36 time: 0.9817 data_time: 0.4220 memory: 22701 grad_norm: 4.9036 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1520 loss: 1.1520 2022/09/05 21:48:09 - mmengine - INFO - Epoch(train) [58][40/940] lr: 1.0000e-03 eta: 9:15:19 time: 0.7410 data_time: 0.1282 memory: 22701 grad_norm: 4.7298 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1557 loss: 1.1557 2022/09/05 21:48:24 - mmengine - INFO - Epoch(train) [58][60/940] lr: 1.0000e-03 eta: 9:15:01 time: 0.7753 data_time: 0.0341 memory: 22701 grad_norm: 4.8003 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9651 loss: 0.9651 2022/09/05 21:48:37 - mmengine - INFO - Epoch(train) [58][80/940] lr: 1.0000e-03 eta: 9:14:42 time: 0.6437 data_time: 0.0372 memory: 22701 grad_norm: 4.7697 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9462 loss: 0.9462 2022/09/05 21:48:54 - mmengine - INFO - Epoch(train) [58][100/940] lr: 1.0000e-03 eta: 9:14:26 time: 0.8275 data_time: 0.0304 memory: 22701 grad_norm: 4.8443 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0570 loss: 1.0570 2022/09/05 21:49:08 - mmengine - INFO - Epoch(train) [58][120/940] lr: 1.0000e-03 eta: 9:14:07 time: 0.7100 data_time: 0.0282 memory: 22701 grad_norm: 4.8062 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0286 loss: 1.0286 2022/09/05 21:49:25 - mmengine - INFO - Epoch(train) [58][140/940] lr: 1.0000e-03 eta: 9:13:52 time: 0.8749 data_time: 0.0289 memory: 22701 grad_norm: 4.8489 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 1.0045 loss: 1.0045 2022/09/05 21:49:40 - mmengine - INFO - Epoch(train) [58][160/940] lr: 1.0000e-03 eta: 9:13:34 time: 0.7551 data_time: 0.0312 memory: 22701 grad_norm: 4.8815 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.0793 loss: 1.0793 2022/09/05 21:49:57 - mmengine - INFO - Epoch(train) [58][180/940] lr: 1.0000e-03 eta: 9:13:18 time: 0.8361 data_time: 0.0294 memory: 22701 grad_norm: 4.9209 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0414 loss: 1.0414 2022/09/05 21:50:11 - mmengine - INFO - Epoch(train) [58][200/940] lr: 1.0000e-03 eta: 9:13:00 time: 0.7020 data_time: 0.0273 memory: 22701 grad_norm: 4.8307 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0948 loss: 1.0948 2022/09/05 21:50:28 - mmengine - INFO - Epoch(train) [58][220/940] lr: 1.0000e-03 eta: 9:12:43 time: 0.8410 data_time: 0.0251 memory: 22701 grad_norm: 4.9476 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1620 loss: 1.1620 2022/09/05 21:50:41 - mmengine - INFO - Epoch(train) [58][240/940] lr: 1.0000e-03 eta: 9:12:24 time: 0.6439 data_time: 0.0351 memory: 22701 grad_norm: 4.9318 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.0415 loss: 1.0415 2022/09/05 21:50:58 - mmengine - INFO - Epoch(train) [58][260/940] lr: 1.0000e-03 eta: 9:12:08 time: 0.8315 data_time: 0.0291 memory: 22701 grad_norm: 4.9093 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1796 loss: 1.1796 2022/09/05 21:51:11 - mmengine - INFO - Epoch(train) [58][280/940] lr: 1.0000e-03 eta: 9:11:49 time: 0.6764 data_time: 0.0261 memory: 22701 grad_norm: 4.8992 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0601 loss: 1.0601 2022/09/05 21:51:28 - mmengine - INFO - Epoch(train) [58][300/940] lr: 1.0000e-03 eta: 9:11:33 time: 0.8629 data_time: 0.0284 memory: 22701 grad_norm: 4.8865 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0473 loss: 1.0473 2022/09/05 21:51:43 - mmengine - INFO - Epoch(train) [58][320/940] lr: 1.0000e-03 eta: 9:11:15 time: 0.7170 data_time: 0.0316 memory: 22701 grad_norm: 4.8911 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1543 loss: 1.1543 2022/09/05 21:52:00 - mmengine - INFO - Epoch(train) [58][340/940] lr: 1.0000e-03 eta: 9:10:59 time: 0.8638 data_time: 0.0736 memory: 22701 grad_norm: 4.8832 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.0415 loss: 1.0415 2022/09/05 21:52:16 - mmengine - INFO - Epoch(train) [58][360/940] lr: 1.0000e-03 eta: 9:10:42 time: 0.8027 data_time: 0.1122 memory: 22701 grad_norm: 4.8244 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1512 loss: 1.1512 2022/09/05 21:52:33 - mmengine - INFO - Epoch(train) [58][380/940] lr: 1.0000e-03 eta: 9:10:26 time: 0.8464 data_time: 0.0484 memory: 22701 grad_norm: 4.8411 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0266 loss: 1.0266 2022/09/05 21:52:49 - mmengine - INFO - Epoch(train) [58][400/940] lr: 1.0000e-03 eta: 9:10:09 time: 0.7831 data_time: 0.1644 memory: 22701 grad_norm: 4.8858 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1237 loss: 1.1237 2022/09/05 21:53:08 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 21:53:08 - mmengine - INFO - Epoch(train) [58][420/940] lr: 1.0000e-03 eta: 9:09:54 time: 0.9465 data_time: 0.3761 memory: 22701 grad_norm: 4.9654 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0856 loss: 1.0856 2022/09/05 21:53:24 - mmengine - INFO - Epoch(train) [58][440/940] lr: 1.0000e-03 eta: 9:09:37 time: 0.8101 data_time: 0.3098 memory: 22701 grad_norm: 5.0810 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1246 loss: 1.1246 2022/09/05 21:53:38 - mmengine - INFO - Epoch(train) [58][460/940] lr: 1.0000e-03 eta: 9:09:19 time: 0.6886 data_time: 0.1457 memory: 22701 grad_norm: 4.9432 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0255 loss: 1.0255 2022/09/05 21:53:52 - mmengine - INFO - Epoch(train) [58][480/940] lr: 1.0000e-03 eta: 9:09:01 time: 0.7422 data_time: 0.2251 memory: 22701 grad_norm: 4.9042 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0978 loss: 1.0978 2022/09/05 21:54:07 - mmengine - INFO - Epoch(train) [58][500/940] lr: 1.0000e-03 eta: 9:08:43 time: 0.7379 data_time: 0.0792 memory: 22701 grad_norm: 4.8994 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1098 loss: 1.1098 2022/09/05 21:54:21 - mmengine - INFO - Epoch(train) [58][520/940] lr: 1.0000e-03 eta: 9:08:25 time: 0.7006 data_time: 0.0232 memory: 22701 grad_norm: 4.8564 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0832 loss: 1.0832 2022/09/05 21:54:39 - mmengine - INFO - Epoch(train) [58][540/940] lr: 1.0000e-03 eta: 9:08:10 time: 0.8836 data_time: 0.0312 memory: 22701 grad_norm: 4.9562 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0832 loss: 1.0832 2022/09/05 21:54:53 - mmengine - INFO - Epoch(train) [58][560/940] lr: 1.0000e-03 eta: 9:07:51 time: 0.7060 data_time: 0.0314 memory: 22701 grad_norm: 4.8442 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9970 loss: 0.9970 2022/09/05 21:55:10 - mmengine - INFO - Epoch(train) [58][580/940] lr: 1.0000e-03 eta: 9:07:35 time: 0.8634 data_time: 0.0408 memory: 22701 grad_norm: 4.8916 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1330 loss: 1.1330 2022/09/05 21:55:24 - mmengine - INFO - Epoch(train) [58][600/940] lr: 1.0000e-03 eta: 9:07:17 time: 0.6807 data_time: 0.0285 memory: 22701 grad_norm: 4.9318 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1276 loss: 1.1276 2022/09/05 21:55:41 - mmengine - INFO - Epoch(train) [58][620/940] lr: 1.0000e-03 eta: 9:07:01 time: 0.8762 data_time: 0.0325 memory: 22701 grad_norm: 4.8104 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0423 loss: 1.0423 2022/09/05 21:55:55 - mmengine - INFO - Epoch(train) [58][640/940] lr: 1.0000e-03 eta: 9:06:43 time: 0.7032 data_time: 0.0226 memory: 22701 grad_norm: 4.8240 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0593 loss: 1.0593 2022/09/05 21:56:11 - mmengine - INFO - Epoch(train) [58][660/940] lr: 1.0000e-03 eta: 9:06:25 time: 0.7705 data_time: 0.0302 memory: 22701 grad_norm: 4.7873 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0823 loss: 1.0823 2022/09/05 21:56:26 - mmengine - INFO - Epoch(train) [58][680/940] lr: 1.0000e-03 eta: 9:06:08 time: 0.7666 data_time: 0.0286 memory: 22701 grad_norm: 4.8384 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0643 loss: 1.0643 2022/09/05 21:56:49 - mmengine - INFO - Epoch(train) [58][700/940] lr: 1.0000e-03 eta: 9:05:56 time: 1.1293 data_time: 0.0285 memory: 22701 grad_norm: 4.9108 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 1.1656 loss: 1.1656 2022/09/05 21:57:06 - mmengine - INFO - Epoch(train) [58][720/940] lr: 1.0000e-03 eta: 9:05:40 time: 0.8623 data_time: 0.0396 memory: 22701 grad_norm: 4.8577 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0708 loss: 1.0708 2022/09/05 21:57:28 - mmengine - INFO - Epoch(train) [58][740/940] lr: 1.0000e-03 eta: 9:05:27 time: 1.0836 data_time: 0.0310 memory: 22701 grad_norm: 4.9822 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2385 loss: 1.2385 2022/09/05 21:57:44 - mmengine - INFO - Epoch(train) [58][760/940] lr: 1.0000e-03 eta: 9:05:11 time: 0.8220 data_time: 0.0241 memory: 22701 grad_norm: 4.9228 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0381 loss: 1.0381 2022/09/05 21:58:00 - mmengine - INFO - Epoch(train) [58][780/940] lr: 1.0000e-03 eta: 9:04:54 time: 0.8038 data_time: 0.0262 memory: 22701 grad_norm: 4.8577 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1176 loss: 1.1176 2022/09/05 21:58:14 - mmengine - INFO - Epoch(train) [58][800/940] lr: 1.0000e-03 eta: 9:04:36 time: 0.6832 data_time: 0.0248 memory: 22701 grad_norm: 4.8392 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0774 loss: 1.0774 2022/09/05 21:58:30 - mmengine - INFO - Epoch(train) [58][820/940] lr: 1.0000e-03 eta: 9:04:19 time: 0.8127 data_time: 0.0278 memory: 22701 grad_norm: 5.0576 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1349 loss: 1.1349 2022/09/05 21:58:43 - mmengine - INFO - Epoch(train) [58][840/940] lr: 1.0000e-03 eta: 9:04:00 time: 0.6593 data_time: 0.0272 memory: 22701 grad_norm: 4.8500 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1012 loss: 1.1012 2022/09/05 21:59:00 - mmengine - INFO - Epoch(train) [58][860/940] lr: 1.0000e-03 eta: 9:03:44 time: 0.8370 data_time: 0.0264 memory: 22701 grad_norm: 5.0059 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1154 loss: 1.1154 2022/09/05 21:59:15 - mmengine - INFO - Epoch(train) [58][880/940] lr: 1.0000e-03 eta: 9:03:26 time: 0.7259 data_time: 0.0274 memory: 22701 grad_norm: 4.7779 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0550 loss: 1.0550 2022/09/05 21:59:31 - mmengine - INFO - Epoch(train) [58][900/940] lr: 1.0000e-03 eta: 9:03:09 time: 0.8082 data_time: 0.0311 memory: 22701 grad_norm: 4.7172 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.9427 loss: 0.9427 2022/09/05 21:59:45 - mmengine - INFO - Epoch(train) [58][920/940] lr: 1.0000e-03 eta: 9:02:51 time: 0.6913 data_time: 0.0214 memory: 22701 grad_norm: 4.9695 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1425 loss: 1.1425 2022/09/05 22:00:00 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:00:00 - mmengine - INFO - Epoch(train) [58][940/940] lr: 1.0000e-03 eta: 9:02:33 time: 0.7631 data_time: 0.0217 memory: 22701 grad_norm: 5.2450 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.1516 loss: 1.1516 2022/09/05 22:00:14 - mmengine - INFO - Epoch(val) [58][20/78] eta: 0:00:40 time: 0.7008 data_time: 0.5811 memory: 2247 2022/09/05 22:00:23 - mmengine - INFO - Epoch(val) [58][40/78] eta: 0:00:17 time: 0.4507 data_time: 0.3315 memory: 2247 2022/09/05 22:00:36 - mmengine - INFO - Epoch(val) [58][60/78] eta: 0:00:11 time: 0.6578 data_time: 0.5379 memory: 2247 2022/09/05 22:00:46 - mmengine - INFO - Epoch(val) [58][78/78] acc/top1: 0.6867 acc/top5: 0.8802 acc/mean1: 0.6865 2022/09/05 22:01:08 - mmengine - INFO - Epoch(train) [59][20/940] lr: 1.0000e-03 eta: 9:02:20 time: 1.0890 data_time: 0.3207 memory: 22701 grad_norm: 4.7806 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0082 loss: 1.0082 2022/09/05 22:01:23 - mmengine - INFO - Epoch(train) [59][40/940] lr: 1.0000e-03 eta: 9:02:03 time: 0.7348 data_time: 0.1252 memory: 22701 grad_norm: 4.9159 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1591 loss: 1.1591 2022/09/05 22:01:43 - mmengine - INFO - Epoch(train) [59][60/940] lr: 1.0000e-03 eta: 9:01:49 time: 0.9986 data_time: 0.3255 memory: 22701 grad_norm: 4.8738 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0797 loss: 1.0797 2022/09/05 22:01:57 - mmengine - INFO - Epoch(train) [59][80/940] lr: 1.0000e-03 eta: 9:01:30 time: 0.6887 data_time: 0.0215 memory: 22701 grad_norm: 4.8316 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0822 loss: 1.0822 2022/09/05 22:02:17 - mmengine - INFO - Epoch(train) [59][100/940] lr: 1.0000e-03 eta: 9:01:16 time: 1.0064 data_time: 0.0249 memory: 22701 grad_norm: 4.8455 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0342 loss: 1.0342 2022/09/05 22:02:31 - mmengine - INFO - Epoch(train) [59][120/940] lr: 1.0000e-03 eta: 9:00:58 time: 0.6905 data_time: 0.0223 memory: 22701 grad_norm: 4.9292 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1288 loss: 1.1288 2022/09/05 22:02:48 - mmengine - INFO - Epoch(train) [59][140/940] lr: 1.0000e-03 eta: 9:00:42 time: 0.8754 data_time: 0.0341 memory: 22701 grad_norm: 4.8674 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0301 loss: 1.0301 2022/09/05 22:03:03 - mmengine - INFO - Epoch(train) [59][160/940] lr: 1.0000e-03 eta: 9:00:24 time: 0.7178 data_time: 0.0247 memory: 22701 grad_norm: 4.9073 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1322 loss: 1.1322 2022/09/05 22:03:20 - mmengine - INFO - Epoch(train) [59][180/940] lr: 1.0000e-03 eta: 9:00:08 time: 0.8703 data_time: 0.0406 memory: 22701 grad_norm: 4.9206 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0669 loss: 1.0669 2022/09/05 22:03:36 - mmengine - INFO - Epoch(train) [59][200/940] lr: 1.0000e-03 eta: 8:59:51 time: 0.7918 data_time: 0.0232 memory: 22701 grad_norm: 4.9483 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0904 loss: 1.0904 2022/09/05 22:03:55 - mmengine - INFO - Epoch(train) [59][220/940] lr: 1.0000e-03 eta: 8:59:37 time: 0.9671 data_time: 0.0287 memory: 22701 grad_norm: 4.9159 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0468 loss: 1.0468 2022/09/05 22:04:09 - mmengine - INFO - Epoch(train) [59][240/940] lr: 1.0000e-03 eta: 8:59:18 time: 0.6810 data_time: 0.0259 memory: 22701 grad_norm: 4.8787 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0560 loss: 1.0560 2022/09/05 22:04:28 - mmengine - INFO - Epoch(train) [59][260/940] lr: 1.0000e-03 eta: 8:59:04 time: 0.9507 data_time: 0.0253 memory: 22701 grad_norm: 4.9094 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0335 loss: 1.0335 2022/09/05 22:04:42 - mmengine - INFO - Epoch(train) [59][280/940] lr: 1.0000e-03 eta: 8:58:45 time: 0.6871 data_time: 0.0225 memory: 22701 grad_norm: 4.9010 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9700 loss: 0.9700 2022/09/05 22:04:58 - mmengine - INFO - Epoch(train) [59][300/940] lr: 1.0000e-03 eta: 8:58:29 time: 0.8266 data_time: 0.0246 memory: 22701 grad_norm: 4.8059 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0867 loss: 1.0867 2022/09/05 22:05:12 - mmengine - INFO - Epoch(train) [59][320/940] lr: 1.0000e-03 eta: 8:58:11 time: 0.7203 data_time: 0.0235 memory: 22701 grad_norm: 4.8868 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9839 loss: 0.9839 2022/09/05 22:05:28 - mmengine - INFO - Epoch(train) [59][340/940] lr: 1.0000e-03 eta: 8:57:54 time: 0.7960 data_time: 0.0227 memory: 22701 grad_norm: 4.9734 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0545 loss: 1.0545 2022/09/05 22:05:42 - mmengine - INFO - Epoch(train) [59][360/940] lr: 1.0000e-03 eta: 8:57:35 time: 0.6739 data_time: 0.0319 memory: 22701 grad_norm: 4.7803 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9496 loss: 0.9496 2022/09/05 22:05:58 - mmengine - INFO - Epoch(train) [59][380/940] lr: 1.0000e-03 eta: 8:57:18 time: 0.7883 data_time: 0.0302 memory: 22701 grad_norm: 4.9572 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9939 loss: 0.9939 2022/09/05 22:06:14 - mmengine - INFO - Epoch(train) [59][400/940] lr: 1.0000e-03 eta: 8:57:02 time: 0.8131 data_time: 0.0340 memory: 22701 grad_norm: 5.0202 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.0334 loss: 1.0334 2022/09/05 22:06:33 - mmengine - INFO - Epoch(train) [59][420/940] lr: 1.0000e-03 eta: 8:56:47 time: 0.9649 data_time: 0.0268 memory: 22701 grad_norm: 4.9458 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1005 loss: 1.1005 2022/09/05 22:06:48 - mmengine - INFO - Epoch(train) [59][440/940] lr: 1.0000e-03 eta: 8:56:29 time: 0.7292 data_time: 0.0250 memory: 22701 grad_norm: 4.9404 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1511 loss: 1.1511 2022/09/05 22:07:04 - mmengine - INFO - Epoch(train) [59][460/940] lr: 1.0000e-03 eta: 8:56:13 time: 0.8160 data_time: 0.0305 memory: 22701 grad_norm: 4.9369 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9369 loss: 0.9369 2022/09/05 22:07:18 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:07:18 - mmengine - INFO - Epoch(train) [59][480/940] lr: 1.0000e-03 eta: 8:55:54 time: 0.6848 data_time: 0.0239 memory: 22701 grad_norm: 4.8833 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9478 loss: 0.9478 2022/09/05 22:07:34 - mmengine - INFO - Epoch(train) [59][500/940] lr: 1.0000e-03 eta: 8:55:37 time: 0.8057 data_time: 0.0304 memory: 22701 grad_norm: 4.9359 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0278 loss: 1.0278 2022/09/05 22:07:49 - mmengine - INFO - Epoch(train) [59][520/940] lr: 1.0000e-03 eta: 8:55:20 time: 0.7697 data_time: 0.0198 memory: 22701 grad_norm: 4.9374 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9618 loss: 0.9618 2022/09/05 22:08:06 - mmengine - INFO - Epoch(train) [59][540/940] lr: 1.0000e-03 eta: 8:55:04 time: 0.8153 data_time: 0.0297 memory: 22701 grad_norm: 4.9294 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0148 loss: 1.0148 2022/09/05 22:08:20 - mmengine - INFO - Epoch(train) [59][560/940] lr: 1.0000e-03 eta: 8:54:46 time: 0.7183 data_time: 0.0292 memory: 22701 grad_norm: 4.9771 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1720 loss: 1.1720 2022/09/05 22:08:38 - mmengine - INFO - Epoch(train) [59][580/940] lr: 1.0000e-03 eta: 8:54:30 time: 0.9009 data_time: 0.0244 memory: 22701 grad_norm: 4.9304 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1144 loss: 1.1144 2022/09/05 22:08:52 - mmengine - INFO - Epoch(train) [59][600/940] lr: 1.0000e-03 eta: 8:54:12 time: 0.6858 data_time: 0.0239 memory: 22701 grad_norm: 5.0173 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 0.9989 loss: 0.9989 2022/09/05 22:09:08 - mmengine - INFO - Epoch(train) [59][620/940] lr: 1.0000e-03 eta: 8:53:55 time: 0.8016 data_time: 0.0246 memory: 22701 grad_norm: 5.0088 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0820 loss: 1.0820 2022/09/05 22:09:24 - mmengine - INFO - Epoch(train) [59][640/940] lr: 1.0000e-03 eta: 8:53:38 time: 0.8001 data_time: 0.0237 memory: 22701 grad_norm: 4.8544 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0485 loss: 1.0485 2022/09/05 22:09:41 - mmengine - INFO - Epoch(train) [59][660/940] lr: 1.0000e-03 eta: 8:53:22 time: 0.8365 data_time: 0.0263 memory: 22701 grad_norm: 4.8757 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0644 loss: 1.0644 2022/09/05 22:09:55 - mmengine - INFO - Epoch(train) [59][680/940] lr: 1.0000e-03 eta: 8:53:04 time: 0.7225 data_time: 0.0291 memory: 22701 grad_norm: 4.8400 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0189 loss: 1.0189 2022/09/05 22:10:14 - mmengine - INFO - Epoch(train) [59][700/940] lr: 1.0000e-03 eta: 8:52:49 time: 0.9327 data_time: 0.0200 memory: 22701 grad_norm: 4.9220 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.1066 loss: 1.1066 2022/09/05 22:10:29 - mmengine - INFO - Epoch(train) [59][720/940] lr: 1.0000e-03 eta: 8:52:32 time: 0.7785 data_time: 0.0260 memory: 22701 grad_norm: 4.8659 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0084 loss: 1.0084 2022/09/05 22:10:50 - mmengine - INFO - Epoch(train) [59][740/940] lr: 1.0000e-03 eta: 8:52:18 time: 1.0146 data_time: 0.0206 memory: 22701 grad_norm: 4.9117 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1128 loss: 1.1128 2022/09/05 22:11:08 - mmengine - INFO - Epoch(train) [59][760/940] lr: 1.0000e-03 eta: 8:52:03 time: 0.9419 data_time: 0.0828 memory: 22701 grad_norm: 4.9003 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0834 loss: 1.0834 2022/09/05 22:11:29 - mmengine - INFO - Epoch(train) [59][780/940] lr: 1.0000e-03 eta: 8:51:49 time: 1.0273 data_time: 0.0470 memory: 22701 grad_norm: 4.8917 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0889 loss: 1.0889 2022/09/05 22:11:48 - mmengine - INFO - Epoch(train) [59][800/940] lr: 1.0000e-03 eta: 8:51:34 time: 0.9367 data_time: 0.3677 memory: 22701 grad_norm: 4.9834 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0114 loss: 1.0114 2022/09/05 22:12:04 - mmengine - INFO - Epoch(train) [59][820/940] lr: 1.0000e-03 eta: 8:51:18 time: 0.8167 data_time: 0.3186 memory: 22701 grad_norm: 5.0297 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 0.9849 loss: 0.9849 2022/09/05 22:12:20 - mmengine - INFO - Epoch(train) [59][840/940] lr: 1.0000e-03 eta: 8:51:01 time: 0.7778 data_time: 0.2699 memory: 22701 grad_norm: 5.0813 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1229 loss: 1.1229 2022/09/05 22:12:35 - mmengine - INFO - Epoch(train) [59][860/940] lr: 1.0000e-03 eta: 8:50:44 time: 0.7835 data_time: 0.1388 memory: 22701 grad_norm: 4.8878 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0941 loss: 1.0941 2022/09/05 22:12:50 - mmengine - INFO - Epoch(train) [59][880/940] lr: 1.0000e-03 eta: 8:50:26 time: 0.7612 data_time: 0.3367 memory: 22701 grad_norm: 4.9837 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1531 loss: 1.1531 2022/09/05 22:13:04 - mmengine - INFO - Epoch(train) [59][900/940] lr: 1.0000e-03 eta: 8:50:08 time: 0.6992 data_time: 0.1977 memory: 22701 grad_norm: 4.8924 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0112 loss: 1.0112 2022/09/05 22:13:20 - mmengine - INFO - Epoch(train) [59][920/940] lr: 1.0000e-03 eta: 8:49:51 time: 0.7661 data_time: 0.1708 memory: 22701 grad_norm: 4.9798 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0912 loss: 1.0912 2022/09/05 22:13:33 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:13:33 - mmengine - INFO - Epoch(train) [59][940/940] lr: 1.0000e-03 eta: 8:49:32 time: 0.6562 data_time: 0.1148 memory: 22701 grad_norm: 5.1963 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2036 loss: 1.2036 2022/09/05 22:13:47 - mmengine - INFO - Epoch(val) [59][20/78] eta: 0:00:40 time: 0.6967 data_time: 0.5770 memory: 2247 2022/09/05 22:13:56 - mmengine - INFO - Epoch(val) [59][40/78] eta: 0:00:16 time: 0.4442 data_time: 0.3259 memory: 2247 2022/09/05 22:14:09 - mmengine - INFO - Epoch(val) [59][60/78] eta: 0:00:11 time: 0.6598 data_time: 0.5408 memory: 2247 2022/09/05 22:14:19 - mmengine - INFO - Epoch(val) [59][78/78] acc/top1: 0.6894 acc/top5: 0.8809 acc/mean1: 0.6893 2022/09/05 22:14:19 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_58.pth is removed 2022/09/05 22:14:20 - mmengine - INFO - The best checkpoint with 0.6894 acc/top1 at 60 epoch is saved to best_acc/top1_epoch_60.pth. 2022/09/05 22:14:39 - mmengine - INFO - Epoch(train) [60][20/940] lr: 1.0000e-03 eta: 8:49:17 time: 0.9313 data_time: 0.4321 memory: 22701 grad_norm: 4.8517 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9493 loss: 0.9493 2022/09/05 22:14:52 - mmengine - INFO - Epoch(train) [60][40/940] lr: 1.0000e-03 eta: 8:48:58 time: 0.6753 data_time: 0.1995 memory: 22701 grad_norm: 4.8445 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0926 loss: 1.0926 2022/09/05 22:15:09 - mmengine - INFO - Epoch(train) [60][60/940] lr: 1.0000e-03 eta: 8:48:42 time: 0.8515 data_time: 0.2681 memory: 22701 grad_norm: 4.9475 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2618 loss: 1.2618 2022/09/05 22:15:23 - mmengine - INFO - Epoch(train) [60][80/940] lr: 1.0000e-03 eta: 8:48:24 time: 0.6752 data_time: 0.1833 memory: 22701 grad_norm: 4.9669 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1275 loss: 1.1275 2022/09/05 22:15:39 - mmengine - INFO - Epoch(train) [60][100/940] lr: 1.0000e-03 eta: 8:48:07 time: 0.7957 data_time: 0.3012 memory: 22701 grad_norm: 4.8969 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0400 loss: 1.0400 2022/09/05 22:15:53 - mmengine - INFO - Epoch(train) [60][120/940] lr: 1.0000e-03 eta: 8:47:48 time: 0.6910 data_time: 0.0980 memory: 22701 grad_norm: 4.9387 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0367 loss: 1.0367 2022/09/05 22:16:08 - mmengine - INFO - Epoch(train) [60][140/940] lr: 1.0000e-03 eta: 8:47:31 time: 0.7828 data_time: 0.0286 memory: 22701 grad_norm: 5.0383 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0462 loss: 1.0462 2022/09/05 22:16:22 - mmengine - INFO - Epoch(train) [60][160/940] lr: 1.0000e-03 eta: 8:47:13 time: 0.6922 data_time: 0.0213 memory: 22701 grad_norm: 4.9753 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0328 loss: 1.0328 2022/09/05 22:16:42 - mmengine - INFO - Epoch(train) [60][180/940] lr: 1.0000e-03 eta: 8:46:59 time: 0.9820 data_time: 0.0286 memory: 22701 grad_norm: 4.9759 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1503 loss: 1.1503 2022/09/05 22:16:57 - mmengine - INFO - Epoch(train) [60][200/940] lr: 1.0000e-03 eta: 8:46:42 time: 0.7701 data_time: 0.0204 memory: 22701 grad_norm: 4.8528 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1113 loss: 1.1113 2022/09/05 22:17:18 - mmengine - INFO - Epoch(train) [60][220/940] lr: 1.0000e-03 eta: 8:46:28 time: 1.0470 data_time: 0.0274 memory: 22701 grad_norm: 5.0345 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0530 loss: 1.0530 2022/09/05 22:17:33 - mmengine - INFO - Epoch(train) [60][240/940] lr: 1.0000e-03 eta: 8:46:11 time: 0.7652 data_time: 0.0250 memory: 22701 grad_norm: 4.9860 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1443 loss: 1.1443 2022/09/05 22:17:54 - mmengine - INFO - Epoch(train) [60][260/940] lr: 1.0000e-03 eta: 8:45:58 time: 1.0548 data_time: 0.0245 memory: 22701 grad_norm: 4.9078 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0032 loss: 1.0032 2022/09/05 22:18:10 - mmengine - INFO - Epoch(train) [60][280/940] lr: 1.0000e-03 eta: 8:45:40 time: 0.7627 data_time: 0.0221 memory: 22701 grad_norm: 4.8851 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0890 loss: 1.0890 2022/09/05 22:18:31 - mmengine - INFO - Epoch(train) [60][300/940] lr: 1.0000e-03 eta: 8:45:27 time: 1.0507 data_time: 0.0298 memory: 22701 grad_norm: 5.0972 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1307 loss: 1.1307 2022/09/05 22:18:45 - mmengine - INFO - Epoch(train) [60][320/940] lr: 1.0000e-03 eta: 8:45:09 time: 0.6930 data_time: 0.0364 memory: 22701 grad_norm: 4.8979 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0141 loss: 1.0141 2022/09/05 22:19:03 - mmengine - INFO - Epoch(train) [60][340/940] lr: 1.0000e-03 eta: 8:44:54 time: 0.9409 data_time: 0.0272 memory: 22701 grad_norm: 4.9477 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.1371 loss: 1.1371 2022/09/05 22:19:17 - mmengine - INFO - Epoch(train) [60][360/940] lr: 1.0000e-03 eta: 8:44:35 time: 0.6843 data_time: 0.0206 memory: 22701 grad_norm: 4.8677 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0127 loss: 1.0127 2022/09/05 22:19:36 - mmengine - INFO - Epoch(train) [60][380/940] lr: 1.0000e-03 eta: 8:44:20 time: 0.9209 data_time: 0.0253 memory: 22701 grad_norm: 4.8959 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9259 loss: 0.9259 2022/09/05 22:19:49 - mmengine - INFO - Epoch(train) [60][400/940] lr: 1.0000e-03 eta: 8:44:01 time: 0.6599 data_time: 0.0268 memory: 22701 grad_norm: 4.9437 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0890 loss: 1.0890 2022/09/05 22:20:06 - mmengine - INFO - Epoch(train) [60][420/940] lr: 1.0000e-03 eta: 8:43:45 time: 0.8574 data_time: 0.0241 memory: 22701 grad_norm: 4.9281 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0221 loss: 1.0221 2022/09/05 22:20:21 - mmengine - INFO - Epoch(train) [60][440/940] lr: 1.0000e-03 eta: 8:43:28 time: 0.7480 data_time: 0.0290 memory: 22701 grad_norm: 4.7883 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 1.1454 loss: 1.1454 2022/09/05 22:20:41 - mmengine - INFO - Epoch(train) [60][460/940] lr: 1.0000e-03 eta: 8:43:13 time: 0.9850 data_time: 0.0256 memory: 22701 grad_norm: 4.9530 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0269 loss: 1.0269 2022/09/05 22:20:55 - mmengine - INFO - Epoch(train) [60][480/940] lr: 1.0000e-03 eta: 8:42:56 time: 0.7443 data_time: 0.0215 memory: 22701 grad_norm: 4.9079 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9441 loss: 0.9441 2022/09/05 22:21:14 - mmengine - INFO - Epoch(train) [60][500/940] lr: 1.0000e-03 eta: 8:42:41 time: 0.9418 data_time: 0.0271 memory: 22701 grad_norm: 4.8447 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9676 loss: 0.9676 2022/09/05 22:21:29 - mmengine - INFO - Epoch(train) [60][520/940] lr: 1.0000e-03 eta: 8:42:23 time: 0.7230 data_time: 0.0335 memory: 22701 grad_norm: 4.8979 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9727 loss: 0.9727 2022/09/05 22:21:46 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:21:46 - mmengine - INFO - Epoch(train) [60][540/940] lr: 1.0000e-03 eta: 8:42:07 time: 0.8604 data_time: 0.0289 memory: 22701 grad_norm: 4.9531 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9337 loss: 0.9337 2022/09/05 22:22:01 - mmengine - INFO - Epoch(train) [60][560/940] lr: 1.0000e-03 eta: 8:41:50 time: 0.7476 data_time: 0.0238 memory: 22701 grad_norm: 4.8581 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0957 loss: 1.0957 2022/09/05 22:22:18 - mmengine - INFO - Epoch(train) [60][580/940] lr: 1.0000e-03 eta: 8:41:33 time: 0.8380 data_time: 0.0307 memory: 22701 grad_norm: 5.0033 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1295 loss: 1.1295 2022/09/05 22:22:32 - mmengine - INFO - Epoch(train) [60][600/940] lr: 1.0000e-03 eta: 8:41:15 time: 0.7080 data_time: 0.0187 memory: 22701 grad_norm: 4.8915 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0323 loss: 1.0323 2022/09/05 22:22:50 - mmengine - INFO - Epoch(train) [60][620/940] lr: 1.0000e-03 eta: 8:41:00 time: 0.8924 data_time: 0.0259 memory: 22701 grad_norm: 4.9440 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9192 loss: 0.9192 2022/09/05 22:23:03 - mmengine - INFO - Epoch(train) [60][640/940] lr: 1.0000e-03 eta: 8:40:41 time: 0.6624 data_time: 0.0199 memory: 22701 grad_norm: 4.8974 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0750 loss: 1.0750 2022/09/05 22:23:21 - mmengine - INFO - Epoch(train) [60][660/940] lr: 1.0000e-03 eta: 8:40:26 time: 0.9031 data_time: 0.0231 memory: 22701 grad_norm: 4.9717 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8894 loss: 0.8894 2022/09/05 22:23:35 - mmengine - INFO - Epoch(train) [60][680/940] lr: 1.0000e-03 eta: 8:40:07 time: 0.6952 data_time: 0.0227 memory: 22701 grad_norm: 5.0438 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1971 loss: 1.1971 2022/09/05 22:23:52 - mmengine - INFO - Epoch(train) [60][700/940] lr: 1.0000e-03 eta: 8:39:51 time: 0.8617 data_time: 0.0396 memory: 22701 grad_norm: 5.0089 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0920 loss: 1.0920 2022/09/05 22:24:06 - mmengine - INFO - Epoch(train) [60][720/940] lr: 1.0000e-03 eta: 8:39:33 time: 0.6944 data_time: 0.1043 memory: 22701 grad_norm: 4.9965 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1187 loss: 1.1187 2022/09/05 22:24:23 - mmengine - INFO - Epoch(train) [60][740/940] lr: 1.0000e-03 eta: 8:39:17 time: 0.8299 data_time: 0.2862 memory: 22701 grad_norm: 5.0038 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0788 loss: 1.0788 2022/09/05 22:24:36 - mmengine - INFO - Epoch(train) [60][760/940] lr: 1.0000e-03 eta: 8:38:58 time: 0.6448 data_time: 0.2013 memory: 22701 grad_norm: 4.9000 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0217 loss: 1.0217 2022/09/05 22:24:52 - mmengine - INFO - Epoch(train) [60][780/940] lr: 1.0000e-03 eta: 8:38:41 time: 0.8128 data_time: 0.1893 memory: 22701 grad_norm: 5.0132 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1065 loss: 1.1065 2022/09/05 22:25:05 - mmengine - INFO - Epoch(train) [60][800/940] lr: 1.0000e-03 eta: 8:38:23 time: 0.6680 data_time: 0.1412 memory: 22701 grad_norm: 5.0051 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1763 loss: 1.1763 2022/09/05 22:25:21 - mmengine - INFO - Epoch(train) [60][820/940] lr: 1.0000e-03 eta: 8:38:06 time: 0.7836 data_time: 0.2331 memory: 22701 grad_norm: 5.0376 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1124 loss: 1.1124 2022/09/05 22:25:42 - mmengine - INFO - Epoch(train) [60][840/940] lr: 1.0000e-03 eta: 8:37:52 time: 1.0372 data_time: 0.2118 memory: 22701 grad_norm: 4.9452 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0808 loss: 1.0808 2022/09/05 22:26:03 - mmengine - INFO - Epoch(train) [60][860/940] lr: 1.0000e-03 eta: 8:37:39 time: 1.0738 data_time: 0.3572 memory: 22701 grad_norm: 4.9629 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9713 loss: 0.9713 2022/09/05 22:26:19 - mmengine - INFO - Epoch(train) [60][880/940] lr: 1.0000e-03 eta: 8:37:22 time: 0.7905 data_time: 0.2899 memory: 22701 grad_norm: 4.9840 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0430 loss: 1.0430 2022/09/05 22:26:37 - mmengine - INFO - Epoch(train) [60][900/940] lr: 1.0000e-03 eta: 8:37:06 time: 0.8967 data_time: 0.2757 memory: 22701 grad_norm: 4.8607 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0032 loss: 1.0032 2022/09/05 22:26:54 - mmengine - INFO - Epoch(train) [60][920/940] lr: 1.0000e-03 eta: 8:36:50 time: 0.8589 data_time: 0.2858 memory: 22701 grad_norm: 4.8363 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1739 loss: 1.1739 2022/09/05 22:27:09 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:27:09 - mmengine - INFO - Epoch(train) [60][940/940] lr: 1.0000e-03 eta: 8:36:33 time: 0.7633 data_time: 0.3605 memory: 22701 grad_norm: 5.2196 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 1.2272 loss: 1.2272 2022/09/05 22:27:09 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/09/05 22:27:28 - mmengine - INFO - Epoch(val) [60][20/78] eta: 0:00:40 time: 0.7067 data_time: 0.5881 memory: 2247 2022/09/05 22:27:37 - mmengine - INFO - Epoch(val) [60][40/78] eta: 0:00:17 time: 0.4492 data_time: 0.3323 memory: 2247 2022/09/05 22:27:50 - mmengine - INFO - Epoch(val) [60][60/78] eta: 0:00:11 time: 0.6518 data_time: 0.5369 memory: 2247 2022/09/05 22:27:59 - mmengine - INFO - Epoch(val) [60][78/78] acc/top1: 0.6875 acc/top5: 0.8820 acc/mean1: 0.6874 2022/09/05 22:28:21 - mmengine - INFO - Epoch(train) [61][20/940] lr: 1.0000e-03 eta: 8:36:20 time: 1.0832 data_time: 0.5156 memory: 22701 grad_norm: 4.8392 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0980 loss: 1.0980 2022/09/05 22:28:37 - mmengine - INFO - Epoch(train) [61][40/940] lr: 1.0000e-03 eta: 8:36:04 time: 0.8426 data_time: 0.0801 memory: 22701 grad_norm: 4.8565 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0182 loss: 1.0182 2022/09/05 22:28:54 - mmengine - INFO - Epoch(train) [61][60/940] lr: 1.0000e-03 eta: 8:35:47 time: 0.8114 data_time: 0.0812 memory: 22701 grad_norm: 4.9112 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0046 loss: 1.0046 2022/09/05 22:29:07 - mmengine - INFO - Epoch(train) [61][80/940] lr: 1.0000e-03 eta: 8:35:28 time: 0.6590 data_time: 0.0282 memory: 22701 grad_norm: 4.8546 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0533 loss: 1.0533 2022/09/05 22:29:24 - mmengine - INFO - Epoch(train) [61][100/940] lr: 1.0000e-03 eta: 8:35:12 time: 0.8521 data_time: 0.0295 memory: 22701 grad_norm: 4.8715 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9942 loss: 0.9942 2022/09/05 22:29:37 - mmengine - INFO - Epoch(train) [61][120/940] lr: 1.0000e-03 eta: 8:34:53 time: 0.6361 data_time: 0.0287 memory: 22701 grad_norm: 4.8580 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8958 loss: 0.8958 2022/09/05 22:29:55 - mmengine - INFO - Epoch(train) [61][140/940] lr: 1.0000e-03 eta: 8:34:38 time: 0.9313 data_time: 0.0266 memory: 22701 grad_norm: 4.8738 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9709 loss: 0.9709 2022/09/05 22:30:10 - mmengine - INFO - Epoch(train) [61][160/940] lr: 1.0000e-03 eta: 8:34:20 time: 0.7191 data_time: 0.0271 memory: 22701 grad_norm: 4.9360 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1742 loss: 1.1742 2022/09/05 22:30:26 - mmengine - INFO - Epoch(train) [61][180/940] lr: 1.0000e-03 eta: 8:34:03 time: 0.7967 data_time: 0.0242 memory: 22701 grad_norm: 4.9914 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1762 loss: 1.1762 2022/09/05 22:30:43 - mmengine - INFO - Epoch(train) [61][200/940] lr: 1.0000e-03 eta: 8:33:47 time: 0.8586 data_time: 0.0223 memory: 22701 grad_norm: 4.9649 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1560 loss: 1.1560 2022/09/05 22:31:05 - mmengine - INFO - Epoch(train) [61][220/940] lr: 1.0000e-03 eta: 8:33:35 time: 1.1125 data_time: 0.0617 memory: 22701 grad_norm: 5.0174 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1363 loss: 1.1363 2022/09/05 22:31:20 - mmengine - INFO - Epoch(train) [61][240/940] lr: 1.0000e-03 eta: 8:33:17 time: 0.7333 data_time: 0.0318 memory: 22701 grad_norm: 4.9234 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9827 loss: 0.9827 2022/09/05 22:31:37 - mmengine - INFO - Epoch(train) [61][260/940] lr: 1.0000e-03 eta: 8:33:01 time: 0.8533 data_time: 0.0262 memory: 22701 grad_norm: 4.9383 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1349 loss: 1.1349 2022/09/05 22:31:50 - mmengine - INFO - Epoch(train) [61][280/940] lr: 1.0000e-03 eta: 8:32:43 time: 0.6893 data_time: 0.0275 memory: 22701 grad_norm: 4.9229 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1076 loss: 1.1076 2022/09/05 22:32:06 - mmengine - INFO - Epoch(train) [61][300/940] lr: 1.0000e-03 eta: 8:32:26 time: 0.7976 data_time: 0.0262 memory: 22701 grad_norm: 4.8813 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9989 loss: 0.9989 2022/09/05 22:32:21 - mmengine - INFO - Epoch(train) [61][320/940] lr: 1.0000e-03 eta: 8:32:08 time: 0.7125 data_time: 0.0302 memory: 22701 grad_norm: 4.9455 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0407 loss: 1.0407 2022/09/05 22:32:39 - mmengine - INFO - Epoch(train) [61][340/940] lr: 1.0000e-03 eta: 8:31:53 time: 0.9273 data_time: 0.0715 memory: 22701 grad_norm: 4.9359 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9965 loss: 0.9965 2022/09/05 22:32:56 - mmengine - INFO - Epoch(train) [61][360/940] lr: 1.0000e-03 eta: 8:31:36 time: 0.8300 data_time: 0.0252 memory: 22701 grad_norm: 4.8931 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0766 loss: 1.0766 2022/09/05 22:33:14 - mmengine - INFO - Epoch(train) [61][380/940] lr: 1.0000e-03 eta: 8:31:21 time: 0.8997 data_time: 0.0289 memory: 22701 grad_norm: 4.9758 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0909 loss: 1.0909 2022/09/05 22:33:31 - mmengine - INFO - Epoch(train) [61][400/940] lr: 1.0000e-03 eta: 8:31:05 time: 0.8380 data_time: 0.0227 memory: 22701 grad_norm: 4.9964 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0080 loss: 1.0080 2022/09/05 22:33:49 - mmengine - INFO - Epoch(train) [61][420/940] lr: 1.0000e-03 eta: 8:30:49 time: 0.8965 data_time: 0.0255 memory: 22701 grad_norm: 4.8509 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0247 loss: 1.0247 2022/09/05 22:34:05 - mmengine - INFO - Epoch(train) [61][440/940] lr: 1.0000e-03 eta: 8:30:33 time: 0.8277 data_time: 0.0290 memory: 22701 grad_norm: 5.0125 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9553 loss: 0.9553 2022/09/05 22:34:24 - mmengine - INFO - Epoch(train) [61][460/940] lr: 1.0000e-03 eta: 8:30:18 time: 0.9648 data_time: 0.0286 memory: 22701 grad_norm: 4.9068 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0590 loss: 1.0590 2022/09/05 22:34:39 - mmengine - INFO - Epoch(train) [61][480/940] lr: 1.0000e-03 eta: 8:30:00 time: 0.7428 data_time: 0.0578 memory: 22701 grad_norm: 4.9255 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0861 loss: 1.0861 2022/09/05 22:34:56 - mmengine - INFO - Epoch(train) [61][500/940] lr: 1.0000e-03 eta: 8:29:44 time: 0.8339 data_time: 0.2071 memory: 22701 grad_norm: 5.0343 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1435 loss: 1.1435 2022/09/05 22:35:11 - mmengine - INFO - Epoch(train) [61][520/940] lr: 1.0000e-03 eta: 8:29:27 time: 0.7633 data_time: 0.3394 memory: 22701 grad_norm: 5.0628 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1419 loss: 1.1419 2022/09/05 22:35:32 - mmengine - INFO - Epoch(train) [61][540/940] lr: 1.0000e-03 eta: 8:29:13 time: 1.0285 data_time: 0.6397 memory: 22701 grad_norm: 5.0136 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9668 loss: 0.9668 2022/09/05 22:35:47 - mmengine - INFO - Epoch(train) [61][560/940] lr: 1.0000e-03 eta: 8:28:56 time: 0.7577 data_time: 0.3565 memory: 22701 grad_norm: 4.9318 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0347 loss: 1.0347 2022/09/05 22:36:03 - mmengine - INFO - Epoch(train) [61][580/940] lr: 1.0000e-03 eta: 8:28:39 time: 0.8028 data_time: 0.4165 memory: 22701 grad_norm: 4.9952 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.1404 loss: 1.1404 2022/09/05 22:36:17 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:36:17 - mmengine - INFO - Epoch(train) [61][600/940] lr: 1.0000e-03 eta: 8:28:21 time: 0.6874 data_time: 0.2615 memory: 22701 grad_norm: 4.9495 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.1279 loss: 1.1279 2022/09/05 22:36:34 - mmengine - INFO - Epoch(train) [61][620/940] lr: 1.0000e-03 eta: 8:28:05 time: 0.8698 data_time: 0.3493 memory: 22701 grad_norm: 4.9188 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0864 loss: 1.0864 2022/09/05 22:36:50 - mmengine - INFO - Epoch(train) [61][640/940] lr: 1.0000e-03 eta: 8:27:48 time: 0.7788 data_time: 0.1498 memory: 22701 grad_norm: 4.9601 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1553 loss: 1.1553 2022/09/05 22:37:04 - mmengine - INFO - Epoch(train) [61][660/940] lr: 1.0000e-03 eta: 8:27:30 time: 0.7378 data_time: 0.1079 memory: 22701 grad_norm: 4.9673 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0217 loss: 1.0217 2022/09/05 22:37:19 - mmengine - INFO - Epoch(train) [61][680/940] lr: 1.0000e-03 eta: 8:27:12 time: 0.7406 data_time: 0.0590 memory: 22701 grad_norm: 5.0084 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9536 loss: 0.9536 2022/09/05 22:37:35 - mmengine - INFO - Epoch(train) [61][700/940] lr: 1.0000e-03 eta: 8:26:55 time: 0.7722 data_time: 0.1639 memory: 22701 grad_norm: 5.0274 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1073 loss: 1.1073 2022/09/05 22:37:51 - mmengine - INFO - Epoch(train) [61][720/940] lr: 1.0000e-03 eta: 8:26:38 time: 0.7986 data_time: 0.1666 memory: 22701 grad_norm: 4.9723 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0762 loss: 1.0762 2022/09/05 22:38:08 - mmengine - INFO - Epoch(train) [61][740/940] lr: 1.0000e-03 eta: 8:26:23 time: 0.8765 data_time: 0.3984 memory: 22701 grad_norm: 4.8912 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.0724 loss: 1.0724 2022/09/05 22:38:27 - mmengine - INFO - Epoch(train) [61][760/940] lr: 1.0000e-03 eta: 8:26:08 time: 0.9352 data_time: 0.3804 memory: 22701 grad_norm: 5.0348 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1069 loss: 1.1069 2022/09/05 22:38:45 - mmengine - INFO - Epoch(train) [61][780/940] lr: 1.0000e-03 eta: 8:25:52 time: 0.9054 data_time: 0.3070 memory: 22701 grad_norm: 4.9704 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0169 loss: 1.0169 2022/09/05 22:39:02 - mmengine - INFO - Epoch(train) [61][800/940] lr: 1.0000e-03 eta: 8:25:36 time: 0.8316 data_time: 0.1501 memory: 22701 grad_norm: 4.9808 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1463 loss: 1.1463 2022/09/05 22:39:18 - mmengine - INFO - Epoch(train) [61][820/940] lr: 1.0000e-03 eta: 8:25:19 time: 0.7985 data_time: 0.0279 memory: 22701 grad_norm: 5.0020 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1484 loss: 1.1484 2022/09/05 22:39:34 - mmengine - INFO - Epoch(train) [61][840/940] lr: 1.0000e-03 eta: 8:25:02 time: 0.8040 data_time: 0.0240 memory: 22701 grad_norm: 4.9547 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0131 loss: 1.0131 2022/09/05 22:39:49 - mmengine - INFO - Epoch(train) [61][860/940] lr: 1.0000e-03 eta: 8:24:45 time: 0.7587 data_time: 0.0309 memory: 22701 grad_norm: 4.8589 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9834 loss: 0.9834 2022/09/05 22:40:05 - mmengine - INFO - Epoch(train) [61][880/940] lr: 1.0000e-03 eta: 8:24:28 time: 0.8204 data_time: 0.0221 memory: 22701 grad_norm: 5.0494 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0340 loss: 1.0340 2022/09/05 22:40:20 - mmengine - INFO - Epoch(train) [61][900/940] lr: 1.0000e-03 eta: 8:24:11 time: 0.7367 data_time: 0.0270 memory: 22701 grad_norm: 5.1275 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0973 loss: 1.0973 2022/09/05 22:40:38 - mmengine - INFO - Epoch(train) [61][920/940] lr: 1.0000e-03 eta: 8:23:55 time: 0.8869 data_time: 0.0263 memory: 22701 grad_norm: 4.9856 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0344 loss: 1.0344 2022/09/05 22:40:51 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:40:51 - mmengine - INFO - Epoch(train) [61][940/940] lr: 1.0000e-03 eta: 8:23:36 time: 0.6576 data_time: 0.0219 memory: 22701 grad_norm: 5.2828 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.0019 loss: 1.0019 2022/09/05 22:41:05 - mmengine - INFO - Epoch(val) [61][20/78] eta: 0:00:40 time: 0.7011 data_time: 0.5824 memory: 2247 2022/09/05 22:41:14 - mmengine - INFO - Epoch(val) [61][40/78] eta: 0:00:16 time: 0.4403 data_time: 0.3217 memory: 2247 2022/09/05 22:41:27 - mmengine - INFO - Epoch(val) [61][60/78] eta: 0:00:11 time: 0.6558 data_time: 0.5365 memory: 2247 2022/09/05 22:41:37 - mmengine - INFO - Epoch(val) [61][78/78] acc/top1: 0.6880 acc/top5: 0.8818 acc/mean1: 0.6879 2022/09/05 22:41:57 - mmengine - INFO - Epoch(train) [62][20/940] lr: 1.0000e-03 eta: 8:23:22 time: 0.9807 data_time: 0.5348 memory: 22701 grad_norm: 4.9757 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1017 loss: 1.1017 2022/09/05 22:42:10 - mmengine - INFO - Epoch(train) [62][40/940] lr: 1.0000e-03 eta: 8:23:03 time: 0.6667 data_time: 0.1641 memory: 22701 grad_norm: 5.0034 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0782 loss: 1.0782 2022/09/05 22:42:29 - mmengine - INFO - Epoch(train) [62][60/940] lr: 1.0000e-03 eta: 8:22:48 time: 0.9352 data_time: 0.3042 memory: 22701 grad_norm: 4.9216 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1267 loss: 1.1267 2022/09/05 22:42:44 - mmengine - INFO - Epoch(train) [62][80/940] lr: 1.0000e-03 eta: 8:22:31 time: 0.7498 data_time: 0.0488 memory: 22701 grad_norm: 4.9538 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1317 loss: 1.1317 2022/09/05 22:43:01 - mmengine - INFO - Epoch(train) [62][100/940] lr: 1.0000e-03 eta: 8:22:14 time: 0.8206 data_time: 0.0269 memory: 22701 grad_norm: 5.0476 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0021 loss: 1.0021 2022/09/05 22:43:15 - mmengine - INFO - Epoch(train) [62][120/940] lr: 1.0000e-03 eta: 8:21:56 time: 0.7047 data_time: 0.0213 memory: 22701 grad_norm: 4.9360 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0354 loss: 1.0354 2022/09/05 22:43:33 - mmengine - INFO - Epoch(train) [62][140/940] lr: 1.0000e-03 eta: 8:21:41 time: 0.9156 data_time: 0.0269 memory: 22701 grad_norm: 4.9500 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0750 loss: 1.0750 2022/09/05 22:43:48 - mmengine - INFO - Epoch(train) [62][160/940] lr: 1.0000e-03 eta: 8:21:23 time: 0.7453 data_time: 0.0189 memory: 22701 grad_norm: 4.8628 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1152 loss: 1.1152 2022/09/05 22:44:03 - mmengine - INFO - Epoch(train) [62][180/940] lr: 1.0000e-03 eta: 8:21:06 time: 0.7274 data_time: 0.0278 memory: 22701 grad_norm: 4.8801 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9670 loss: 0.9670 2022/09/05 22:44:16 - mmengine - INFO - Epoch(train) [62][200/940] lr: 1.0000e-03 eta: 8:20:47 time: 0.6545 data_time: 0.0319 memory: 22701 grad_norm: 4.9623 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0239 loss: 1.0239 2022/09/05 22:44:31 - mmengine - INFO - Epoch(train) [62][220/940] lr: 1.0000e-03 eta: 8:20:30 time: 0.7895 data_time: 0.0265 memory: 22701 grad_norm: 4.9294 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9949 loss: 0.9949 2022/09/05 22:44:45 - mmengine - INFO - Epoch(train) [62][240/940] lr: 1.0000e-03 eta: 8:20:12 time: 0.7045 data_time: 0.0229 memory: 22701 grad_norm: 4.9259 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0075 loss: 1.0075 2022/09/05 22:45:02 - mmengine - INFO - Epoch(train) [62][260/940] lr: 1.0000e-03 eta: 8:19:56 time: 0.8299 data_time: 0.0288 memory: 22701 grad_norm: 4.9787 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0347 loss: 1.0347 2022/09/05 22:45:15 - mmengine - INFO - Epoch(train) [62][280/940] lr: 1.0000e-03 eta: 8:19:37 time: 0.6539 data_time: 0.0245 memory: 22701 grad_norm: 5.0813 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0851 loss: 1.0851 2022/09/05 22:45:31 - mmengine - INFO - Epoch(train) [62][300/940] lr: 1.0000e-03 eta: 8:19:20 time: 0.7971 data_time: 0.0312 memory: 22701 grad_norm: 4.9823 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0552 loss: 1.0552 2022/09/05 22:45:44 - mmengine - INFO - Epoch(train) [62][320/940] lr: 1.0000e-03 eta: 8:19:02 time: 0.6697 data_time: 0.0266 memory: 22701 grad_norm: 4.9363 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0569 loss: 1.0569 2022/09/05 22:46:03 - mmengine - INFO - Epoch(train) [62][340/940] lr: 1.0000e-03 eta: 8:18:47 time: 0.9091 data_time: 0.0257 memory: 22701 grad_norm: 4.9765 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0840 loss: 1.0840 2022/09/05 22:46:18 - mmengine - INFO - Epoch(train) [62][360/940] lr: 1.0000e-03 eta: 8:18:29 time: 0.7474 data_time: 0.0217 memory: 22701 grad_norm: 4.9332 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9527 loss: 0.9527 2022/09/05 22:46:37 - mmengine - INFO - Epoch(train) [62][380/940] lr: 1.0000e-03 eta: 8:18:15 time: 0.9862 data_time: 0.0312 memory: 22701 grad_norm: 4.9137 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0363 loss: 1.0363 2022/09/05 22:46:53 - mmengine - INFO - Epoch(train) [62][400/940] lr: 1.0000e-03 eta: 8:17:58 time: 0.8035 data_time: 0.0213 memory: 22701 grad_norm: 4.9695 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0289 loss: 1.0289 2022/09/05 22:47:12 - mmengine - INFO - Epoch(train) [62][420/940] lr: 1.0000e-03 eta: 8:17:43 time: 0.9416 data_time: 0.0300 memory: 22701 grad_norm: 5.0591 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1285 loss: 1.1285 2022/09/05 22:47:27 - mmengine - INFO - Epoch(train) [62][440/940] lr: 1.0000e-03 eta: 8:17:26 time: 0.7622 data_time: 0.0232 memory: 22701 grad_norm: 4.9491 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1100 loss: 1.1100 2022/09/05 22:47:45 - mmengine - INFO - Epoch(train) [62][460/940] lr: 1.0000e-03 eta: 8:17:10 time: 0.8546 data_time: 0.0272 memory: 22701 grad_norm: 4.9414 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0809 loss: 1.0809 2022/09/05 22:47:58 - mmengine - INFO - Epoch(train) [62][480/940] lr: 1.0000e-03 eta: 8:16:51 time: 0.6814 data_time: 0.0346 memory: 22701 grad_norm: 4.8856 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0136 loss: 1.0136 2022/09/05 22:48:15 - mmengine - INFO - Epoch(train) [62][500/940] lr: 1.0000e-03 eta: 8:16:35 time: 0.8618 data_time: 0.0255 memory: 22701 grad_norm: 4.9610 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0898 loss: 1.0898 2022/09/05 22:48:29 - mmengine - INFO - Epoch(train) [62][520/940] lr: 1.0000e-03 eta: 8:16:17 time: 0.6687 data_time: 0.0302 memory: 22701 grad_norm: 5.0235 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0702 loss: 1.0702 2022/09/05 22:48:46 - mmengine - INFO - Epoch(train) [62][540/940] lr: 1.0000e-03 eta: 8:16:01 time: 0.8692 data_time: 0.0257 memory: 22701 grad_norm: 5.0125 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0944 loss: 1.0944 2022/09/05 22:49:00 - mmengine - INFO - Epoch(train) [62][560/940] lr: 1.0000e-03 eta: 8:15:43 time: 0.6806 data_time: 0.0394 memory: 22701 grad_norm: 4.9796 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1431 loss: 1.1431 2022/09/05 22:49:16 - mmengine - INFO - Epoch(train) [62][580/940] lr: 1.0000e-03 eta: 8:15:26 time: 0.8042 data_time: 0.0251 memory: 22701 grad_norm: 4.8842 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0704 loss: 1.0704 2022/09/05 22:49:32 - mmengine - INFO - Epoch(train) [62][600/940] lr: 1.0000e-03 eta: 8:15:09 time: 0.8132 data_time: 0.1435 memory: 22701 grad_norm: 5.1212 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9854 loss: 0.9854 2022/09/05 22:49:50 - mmengine - INFO - Epoch(train) [62][620/940] lr: 1.0000e-03 eta: 8:14:54 time: 0.9117 data_time: 0.0988 memory: 22701 grad_norm: 5.0005 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0600 loss: 1.0600 2022/09/05 22:50:06 - mmengine - INFO - Epoch(train) [62][640/940] lr: 1.0000e-03 eta: 8:14:37 time: 0.7906 data_time: 0.0624 memory: 22701 grad_norm: 4.9423 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9820 loss: 0.9820 2022/09/05 22:50:25 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:50:25 - mmengine - INFO - Epoch(train) [62][660/940] lr: 1.0000e-03 eta: 8:14:22 time: 0.9177 data_time: 0.0289 memory: 22701 grad_norm: 4.9188 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9771 loss: 0.9771 2022/09/05 22:50:40 - mmengine - INFO - Epoch(train) [62][680/940] lr: 1.0000e-03 eta: 8:14:04 time: 0.7544 data_time: 0.0321 memory: 22701 grad_norm: 4.9484 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0199 loss: 1.0199 2022/09/05 22:50:56 - mmengine - INFO - Epoch(train) [62][700/940] lr: 1.0000e-03 eta: 8:13:48 time: 0.7908 data_time: 0.0301 memory: 22701 grad_norm: 5.0069 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1403 loss: 1.1403 2022/09/05 22:51:12 - mmengine - INFO - Epoch(train) [62][720/940] lr: 1.0000e-03 eta: 8:13:31 time: 0.8001 data_time: 0.0370 memory: 22701 grad_norm: 4.9081 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0281 loss: 1.0281 2022/09/05 22:51:29 - mmengine - INFO - Epoch(train) [62][740/940] lr: 1.0000e-03 eta: 8:13:15 time: 0.8521 data_time: 0.0985 memory: 22701 grad_norm: 4.9084 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1109 loss: 1.1109 2022/09/05 22:51:43 - mmengine - INFO - Epoch(train) [62][760/940] lr: 1.0000e-03 eta: 8:12:57 time: 0.7396 data_time: 0.1658 memory: 22701 grad_norm: 4.9747 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 0.9046 loss: 0.9046 2022/09/05 22:52:02 - mmengine - INFO - Epoch(train) [62][780/940] lr: 1.0000e-03 eta: 8:12:42 time: 0.9124 data_time: 0.0723 memory: 22701 grad_norm: 4.9658 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2026 loss: 1.2026 2022/09/05 22:52:17 - mmengine - INFO - Epoch(train) [62][800/940] lr: 1.0000e-03 eta: 8:12:25 time: 0.7715 data_time: 0.0440 memory: 22701 grad_norm: 5.0688 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0335 loss: 1.0335 2022/09/05 22:52:38 - mmengine - INFO - Epoch(train) [62][820/940] lr: 1.0000e-03 eta: 8:12:11 time: 1.0298 data_time: 0.0238 memory: 22701 grad_norm: 4.9804 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1009 loss: 1.1009 2022/09/05 22:52:53 - mmengine - INFO - Epoch(train) [62][840/940] lr: 1.0000e-03 eta: 8:11:53 time: 0.7632 data_time: 0.0873 memory: 22701 grad_norm: 4.9876 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1156 loss: 1.1156 2022/09/05 22:53:09 - mmengine - INFO - Epoch(train) [62][860/940] lr: 1.0000e-03 eta: 8:11:37 time: 0.7958 data_time: 0.0226 memory: 22701 grad_norm: 5.0297 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8864 loss: 0.8864 2022/09/05 22:53:22 - mmengine - INFO - Epoch(train) [62][880/940] lr: 1.0000e-03 eta: 8:11:18 time: 0.6351 data_time: 0.0303 memory: 22701 grad_norm: 5.0347 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0747 loss: 1.0747 2022/09/05 22:53:38 - mmengine - INFO - Epoch(train) [62][900/940] lr: 1.0000e-03 eta: 8:11:02 time: 0.8416 data_time: 0.0251 memory: 22701 grad_norm: 5.0115 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0632 loss: 1.0632 2022/09/05 22:53:54 - mmengine - INFO - Epoch(train) [62][920/940] lr: 1.0000e-03 eta: 8:10:44 time: 0.7561 data_time: 0.0212 memory: 22701 grad_norm: 4.9645 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1210 loss: 1.1210 2022/09/05 22:54:09 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 22:54:09 - mmengine - INFO - Epoch(train) [62][940/940] lr: 1.0000e-03 eta: 8:10:27 time: 0.7583 data_time: 0.0194 memory: 22701 grad_norm: 5.2775 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.0699 loss: 1.0699 2022/09/05 22:54:22 - mmengine - INFO - Epoch(val) [62][20/78] eta: 0:00:39 time: 0.6809 data_time: 0.5615 memory: 2247 2022/09/05 22:54:32 - mmengine - INFO - Epoch(val) [62][40/78] eta: 0:00:17 time: 0.4632 data_time: 0.3453 memory: 2247 2022/09/05 22:54:45 - mmengine - INFO - Epoch(val) [62][60/78] eta: 0:00:11 time: 0.6512 data_time: 0.5289 memory: 2247 2022/09/05 22:54:55 - mmengine - INFO - Epoch(val) [62][78/78] acc/top1: 0.6891 acc/top5: 0.8818 acc/mean1: 0.6890 2022/09/05 22:55:17 - mmengine - INFO - Epoch(train) [63][20/940] lr: 1.0000e-03 eta: 8:10:14 time: 1.1078 data_time: 0.4054 memory: 22701 grad_norm: 4.8984 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0671 loss: 1.0671 2022/09/05 22:55:31 - mmengine - INFO - Epoch(train) [63][40/940] lr: 1.0000e-03 eta: 8:09:56 time: 0.6629 data_time: 0.0898 memory: 22701 grad_norm: 4.9165 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0184 loss: 1.0184 2022/09/05 22:55:49 - mmengine - INFO - Epoch(train) [63][60/940] lr: 1.0000e-03 eta: 8:09:40 time: 0.9007 data_time: 0.4102 memory: 22701 grad_norm: 4.9370 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0875 loss: 1.0875 2022/09/05 22:56:03 - mmengine - INFO - Epoch(train) [63][80/940] lr: 1.0000e-03 eta: 8:09:22 time: 0.7249 data_time: 0.2627 memory: 22701 grad_norm: 5.0132 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0688 loss: 1.0688 2022/09/05 22:56:19 - mmengine - INFO - Epoch(train) [63][100/940] lr: 1.0000e-03 eta: 8:09:06 time: 0.8055 data_time: 0.3450 memory: 22701 grad_norm: 5.0089 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0314 loss: 1.0314 2022/09/05 22:56:33 - mmengine - INFO - Epoch(train) [63][120/940] lr: 1.0000e-03 eta: 8:08:47 time: 0.6822 data_time: 0.2879 memory: 22701 grad_norm: 5.0147 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9996 loss: 0.9996 2022/09/05 22:56:50 - mmengine - INFO - Epoch(train) [63][140/940] lr: 1.0000e-03 eta: 8:08:31 time: 0.8672 data_time: 0.3622 memory: 22701 grad_norm: 4.9068 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0468 loss: 1.0468 2022/09/05 22:57:04 - mmengine - INFO - Epoch(train) [63][160/940] lr: 1.0000e-03 eta: 8:08:14 time: 0.7100 data_time: 0.1465 memory: 22701 grad_norm: 4.9727 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1481 loss: 1.1481 2022/09/05 22:57:25 - mmengine - INFO - Epoch(train) [63][180/940] lr: 1.0000e-03 eta: 8:08:00 time: 1.0277 data_time: 0.0797 memory: 22701 grad_norm: 5.0360 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0582 loss: 1.0582 2022/09/05 22:57:40 - mmengine - INFO - Epoch(train) [63][200/940] lr: 1.0000e-03 eta: 8:07:42 time: 0.7559 data_time: 0.0251 memory: 22701 grad_norm: 5.0081 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0486 loss: 1.0486 2022/09/05 22:57:58 - mmengine - INFO - Epoch(train) [63][220/940] lr: 1.0000e-03 eta: 8:07:27 time: 0.9214 data_time: 0.0346 memory: 22701 grad_norm: 5.0182 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0787 loss: 1.0787 2022/09/05 22:58:14 - mmengine - INFO - Epoch(train) [63][240/940] lr: 1.0000e-03 eta: 8:07:10 time: 0.7706 data_time: 0.0222 memory: 22701 grad_norm: 4.9993 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9979 loss: 0.9979 2022/09/05 22:58:34 - mmengine - INFO - Epoch(train) [63][260/940] lr: 1.0000e-03 eta: 8:06:55 time: 0.9825 data_time: 0.0280 memory: 22701 grad_norm: 4.9396 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.0375 loss: 1.0375 2022/09/05 22:58:47 - mmengine - INFO - Epoch(train) [63][280/940] lr: 1.0000e-03 eta: 8:06:37 time: 0.6859 data_time: 0.0206 memory: 22701 grad_norm: 4.9918 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9724 loss: 0.9724 2022/09/05 22:59:05 - mmengine - INFO - Epoch(train) [63][300/940] lr: 1.0000e-03 eta: 8:06:21 time: 0.8880 data_time: 0.0261 memory: 22701 grad_norm: 5.0158 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0352 loss: 1.0352 2022/09/05 22:59:19 - mmengine - INFO - Epoch(train) [63][320/940] lr: 1.0000e-03 eta: 8:06:03 time: 0.6916 data_time: 0.0228 memory: 22701 grad_norm: 5.0661 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1208 loss: 1.1208 2022/09/05 22:59:37 - mmengine - INFO - Epoch(train) [63][340/940] lr: 1.0000e-03 eta: 8:05:48 time: 0.9184 data_time: 0.0289 memory: 22701 grad_norm: 5.0142 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 1.1185 loss: 1.1185 2022/09/05 22:59:51 - mmengine - INFO - Epoch(train) [63][360/940] lr: 1.0000e-03 eta: 8:05:30 time: 0.6672 data_time: 0.0296 memory: 22701 grad_norm: 5.0356 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0515 loss: 1.0515 2022/09/05 23:00:06 - mmengine - INFO - Epoch(train) [63][380/940] lr: 1.0000e-03 eta: 8:05:13 time: 0.7845 data_time: 0.0437 memory: 22701 grad_norm: 4.9117 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9888 loss: 0.9888 2022/09/05 23:00:21 - mmengine - INFO - Epoch(train) [63][400/940] lr: 1.0000e-03 eta: 8:04:55 time: 0.7366 data_time: 0.0265 memory: 22701 grad_norm: 4.9419 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9503 loss: 0.9503 2022/09/05 23:00:40 - mmengine - INFO - Epoch(train) [63][420/940] lr: 1.0000e-03 eta: 8:04:40 time: 0.9480 data_time: 0.0436 memory: 22701 grad_norm: 4.9954 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1124 loss: 1.1124 2022/09/05 23:00:55 - mmengine - INFO - Epoch(train) [63][440/940] lr: 1.0000e-03 eta: 8:04:23 time: 0.7280 data_time: 0.0986 memory: 22701 grad_norm: 5.0052 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1513 loss: 1.1513 2022/09/05 23:01:13 - mmengine - INFO - Epoch(train) [63][460/940] lr: 1.0000e-03 eta: 8:04:07 time: 0.9031 data_time: 0.0445 memory: 22701 grad_norm: 4.8999 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8893 loss: 0.8893 2022/09/05 23:01:27 - mmengine - INFO - Epoch(train) [63][480/940] lr: 1.0000e-03 eta: 8:03:49 time: 0.7325 data_time: 0.0533 memory: 22701 grad_norm: 5.0573 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0480 loss: 1.0480 2022/09/05 23:01:48 - mmengine - INFO - Epoch(train) [63][500/940] lr: 1.0000e-03 eta: 8:03:35 time: 1.0179 data_time: 0.1088 memory: 22701 grad_norm: 4.9650 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0797 loss: 1.0797 2022/09/05 23:02:03 - mmengine - INFO - Epoch(train) [63][520/940] lr: 1.0000e-03 eta: 8:03:18 time: 0.7914 data_time: 0.0226 memory: 22701 grad_norm: 4.9289 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0360 loss: 1.0360 2022/09/05 23:02:23 - mmengine - INFO - Epoch(train) [63][540/940] lr: 1.0000e-03 eta: 8:03:04 time: 0.9622 data_time: 0.2236 memory: 22701 grad_norm: 5.0956 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0661 loss: 1.0661 2022/09/05 23:02:39 - mmengine - INFO - Epoch(train) [63][560/940] lr: 1.0000e-03 eta: 8:02:47 time: 0.7901 data_time: 0.0472 memory: 22701 grad_norm: 5.0523 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 0.9963 loss: 0.9963 2022/09/05 23:02:55 - mmengine - INFO - Epoch(train) [63][580/940] lr: 1.0000e-03 eta: 8:02:30 time: 0.8103 data_time: 0.0560 memory: 22701 grad_norm: 5.1838 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1590 loss: 1.1590 2022/09/05 23:03:09 - mmengine - INFO - Epoch(train) [63][600/940] lr: 1.0000e-03 eta: 8:02:12 time: 0.7140 data_time: 0.0254 memory: 22701 grad_norm: 5.0306 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1338 loss: 1.1338 2022/09/05 23:03:27 - mmengine - INFO - Epoch(train) [63][620/940] lr: 1.0000e-03 eta: 8:01:57 time: 0.8808 data_time: 0.0265 memory: 22701 grad_norm: 4.9635 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0575 loss: 1.0575 2022/09/05 23:03:43 - mmengine - INFO - Epoch(train) [63][640/940] lr: 1.0000e-03 eta: 8:01:40 time: 0.8259 data_time: 0.0180 memory: 22701 grad_norm: 5.0075 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0600 loss: 1.0600 2022/09/05 23:03:59 - mmengine - INFO - Epoch(train) [63][660/940] lr: 1.0000e-03 eta: 8:01:24 time: 0.8161 data_time: 0.0277 memory: 22701 grad_norm: 5.0517 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2372 loss: 1.2372 2022/09/05 23:04:16 - mmengine - INFO - Epoch(train) [63][680/940] lr: 1.0000e-03 eta: 8:01:07 time: 0.8254 data_time: 0.0303 memory: 22701 grad_norm: 4.9941 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1031 loss: 1.1031 2022/09/05 23:04:30 - mmengine - INFO - Epoch(train) [63][700/940] lr: 1.0000e-03 eta: 8:00:49 time: 0.6782 data_time: 0.0282 memory: 22701 grad_norm: 4.9586 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9755 loss: 0.9755 2022/09/05 23:04:47 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:04:47 - mmengine - INFO - Epoch(train) [63][720/940] lr: 1.0000e-03 eta: 8:00:33 time: 0.8927 data_time: 0.0341 memory: 22701 grad_norm: 4.9479 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0578 loss: 1.0578 2022/09/05 23:05:02 - mmengine - INFO - Epoch(train) [63][740/940] lr: 1.0000e-03 eta: 8:00:16 time: 0.7505 data_time: 0.0391 memory: 22701 grad_norm: 4.9839 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0907 loss: 1.0907 2022/09/05 23:05:18 - mmengine - INFO - Epoch(train) [63][760/940] lr: 1.0000e-03 eta: 7:59:59 time: 0.7585 data_time: 0.0281 memory: 22701 grad_norm: 5.1042 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0954 loss: 1.0954 2022/09/05 23:05:33 - mmengine - INFO - Epoch(train) [63][780/940] lr: 1.0000e-03 eta: 7:59:41 time: 0.7690 data_time: 0.0838 memory: 22701 grad_norm: 5.0876 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0119 loss: 1.0119 2022/09/05 23:05:47 - mmengine - INFO - Epoch(train) [63][800/940] lr: 1.0000e-03 eta: 7:59:23 time: 0.6840 data_time: 0.0367 memory: 22701 grad_norm: 5.0436 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.0289 loss: 1.0289 2022/09/05 23:06:04 - mmengine - INFO - Epoch(train) [63][820/940] lr: 1.0000e-03 eta: 7:59:07 time: 0.8589 data_time: 0.0367 memory: 22701 grad_norm: 5.0664 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1067 loss: 1.1067 2022/09/05 23:06:19 - mmengine - INFO - Epoch(train) [63][840/940] lr: 1.0000e-03 eta: 7:58:50 time: 0.7796 data_time: 0.0225 memory: 22701 grad_norm: 5.0325 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 1.0171 loss: 1.0171 2022/09/05 23:06:36 - mmengine - INFO - Epoch(train) [63][860/940] lr: 1.0000e-03 eta: 7:58:34 time: 0.8358 data_time: 0.0259 memory: 22701 grad_norm: 5.0205 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1151 loss: 1.1151 2022/09/05 23:06:52 - mmengine - INFO - Epoch(train) [63][880/940] lr: 1.0000e-03 eta: 7:58:17 time: 0.7686 data_time: 0.0283 memory: 22701 grad_norm: 4.9624 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9969 loss: 0.9969 2022/09/05 23:07:08 - mmengine - INFO - Epoch(train) [63][900/940] lr: 1.0000e-03 eta: 7:58:00 time: 0.8199 data_time: 0.0307 memory: 22701 grad_norm: 4.9857 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0190 loss: 1.0190 2022/09/05 23:07:24 - mmengine - INFO - Epoch(train) [63][920/940] lr: 1.0000e-03 eta: 7:57:44 time: 0.8096 data_time: 0.0241 memory: 22701 grad_norm: 5.0637 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1069 loss: 1.1069 2022/09/05 23:07:37 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:07:37 - mmengine - INFO - Epoch(train) [63][940/940] lr: 1.0000e-03 eta: 7:57:25 time: 0.6554 data_time: 0.0192 memory: 22701 grad_norm: 5.3433 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.0486 loss: 1.0486 2022/09/05 23:07:37 - mmengine - INFO - Saving checkpoint at 63 epochs 2022/09/05 23:07:53 - mmengine - INFO - Epoch(val) [63][20/78] eta: 0:00:40 time: 0.6927 data_time: 0.5780 memory: 2247 2022/09/05 23:08:02 - mmengine - INFO - Epoch(val) [63][40/78] eta: 0:00:17 time: 0.4662 data_time: 0.3506 memory: 2247 2022/09/05 23:08:16 - mmengine - INFO - Epoch(val) [63][60/78] eta: 0:00:11 time: 0.6619 data_time: 0.5330 memory: 2247 2022/09/05 23:08:25 - mmengine - INFO - Epoch(val) [63][78/78] acc/top1: 0.6877 acc/top5: 0.8811 acc/mean1: 0.6876 2022/09/05 23:08:44 - mmengine - INFO - Epoch(train) [64][20/940] lr: 1.0000e-03 eta: 7:57:10 time: 0.9373 data_time: 0.4180 memory: 22701 grad_norm: 5.0109 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1036 loss: 1.1036 2022/09/05 23:08:57 - mmengine - INFO - Epoch(train) [64][40/940] lr: 1.0000e-03 eta: 7:56:52 time: 0.6631 data_time: 0.1124 memory: 22701 grad_norm: 4.9819 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1908 loss: 1.1908 2022/09/05 23:09:16 - mmengine - INFO - Epoch(train) [64][60/940] lr: 1.0000e-03 eta: 7:56:37 time: 0.9360 data_time: 0.0312 memory: 22701 grad_norm: 5.0085 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9950 loss: 0.9950 2022/09/05 23:09:31 - mmengine - INFO - Epoch(train) [64][80/940] lr: 1.0000e-03 eta: 7:56:19 time: 0.7563 data_time: 0.0306 memory: 22701 grad_norm: 4.9664 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0994 loss: 1.0994 2022/09/05 23:09:51 - mmengine - INFO - Epoch(train) [64][100/940] lr: 1.0000e-03 eta: 7:56:05 time: 1.0101 data_time: 0.0278 memory: 22701 grad_norm: 5.0306 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0580 loss: 1.0580 2022/09/05 23:10:12 - mmengine - INFO - Epoch(train) [64][120/940] lr: 1.0000e-03 eta: 7:55:51 time: 1.0073 data_time: 0.0306 memory: 22701 grad_norm: 5.0727 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.0368 loss: 1.0368 2022/09/05 23:10:30 - mmengine - INFO - Epoch(train) [64][140/940] lr: 1.0000e-03 eta: 7:55:35 time: 0.9162 data_time: 0.0240 memory: 22701 grad_norm: 5.0566 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1465 loss: 1.1465 2022/09/05 23:10:51 - mmengine - INFO - Epoch(train) [64][160/940] lr: 1.0000e-03 eta: 7:55:21 time: 1.0446 data_time: 0.0249 memory: 22701 grad_norm: 4.9506 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9563 loss: 0.9563 2022/09/05 23:11:08 - mmengine - INFO - Epoch(train) [64][180/940] lr: 1.0000e-03 eta: 7:55:05 time: 0.8425 data_time: 0.0187 memory: 22701 grad_norm: 5.0105 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9842 loss: 0.9842 2022/09/05 23:11:29 - mmengine - INFO - Epoch(train) [64][200/940] lr: 1.0000e-03 eta: 7:54:51 time: 1.0572 data_time: 0.0308 memory: 22701 grad_norm: 4.9158 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 0.9946 loss: 0.9946 2022/09/05 23:11:43 - mmengine - INFO - Epoch(train) [64][220/940] lr: 1.0000e-03 eta: 7:54:34 time: 0.7334 data_time: 0.0180 memory: 22701 grad_norm: 5.0817 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.0503 loss: 1.0503 2022/09/05 23:12:01 - mmengine - INFO - Epoch(train) [64][240/940] lr: 1.0000e-03 eta: 7:54:18 time: 0.8561 data_time: 0.0266 memory: 22701 grad_norm: 5.0814 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0114 loss: 1.0114 2022/09/05 23:12:17 - mmengine - INFO - Epoch(train) [64][260/940] lr: 1.0000e-03 eta: 7:54:01 time: 0.8040 data_time: 0.0185 memory: 22701 grad_norm: 4.9724 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0219 loss: 1.0219 2022/09/05 23:12:34 - mmengine - INFO - Epoch(train) [64][280/940] lr: 1.0000e-03 eta: 7:53:45 time: 0.8596 data_time: 0.0279 memory: 22701 grad_norm: 5.0444 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9849 loss: 0.9849 2022/09/05 23:12:48 - mmengine - INFO - Epoch(train) [64][300/940] lr: 1.0000e-03 eta: 7:53:27 time: 0.6994 data_time: 0.0255 memory: 22701 grad_norm: 5.0411 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1137 loss: 1.1137 2022/09/05 23:13:05 - mmengine - INFO - Epoch(train) [64][320/940] lr: 1.0000e-03 eta: 7:53:11 time: 0.8528 data_time: 0.0275 memory: 22701 grad_norm: 4.9461 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0285 loss: 1.0285 2022/09/05 23:13:20 - mmengine - INFO - Epoch(train) [64][340/940] lr: 1.0000e-03 eta: 7:52:53 time: 0.7363 data_time: 0.0261 memory: 22701 grad_norm: 5.0329 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.0356 loss: 1.0356 2022/09/05 23:13:34 - mmengine - INFO - Epoch(train) [64][360/940] lr: 1.0000e-03 eta: 7:52:36 time: 0.7285 data_time: 0.0274 memory: 22701 grad_norm: 4.9756 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.0154 loss: 1.0154 2022/09/05 23:13:49 - mmengine - INFO - Epoch(train) [64][380/940] lr: 1.0000e-03 eta: 7:52:19 time: 0.7504 data_time: 0.0349 memory: 22701 grad_norm: 5.0123 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0964 loss: 1.0964 2022/09/05 23:14:04 - mmengine - INFO - Epoch(train) [64][400/940] lr: 1.0000e-03 eta: 7:52:01 time: 0.7350 data_time: 0.0417 memory: 22701 grad_norm: 5.0120 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0578 loss: 1.0578 2022/09/05 23:14:22 - mmengine - INFO - Epoch(train) [64][420/940] lr: 1.0000e-03 eta: 7:51:45 time: 0.8928 data_time: 0.0207 memory: 22701 grad_norm: 5.0320 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0054 loss: 1.0054 2022/09/05 23:14:35 - mmengine - INFO - Epoch(train) [64][440/940] lr: 1.0000e-03 eta: 7:51:27 time: 0.6428 data_time: 0.0274 memory: 22701 grad_norm: 5.0527 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0758 loss: 1.0758 2022/09/05 23:14:52 - mmengine - INFO - Epoch(train) [64][460/940] lr: 1.0000e-03 eta: 7:51:11 time: 0.8631 data_time: 0.0369 memory: 22701 grad_norm: 5.0698 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0987 loss: 1.0987 2022/09/05 23:15:06 - mmengine - INFO - Epoch(train) [64][480/940] lr: 1.0000e-03 eta: 7:50:53 time: 0.7154 data_time: 0.0301 memory: 22701 grad_norm: 5.0273 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0485 loss: 1.0485 2022/09/05 23:15:22 - mmengine - INFO - Epoch(train) [64][500/940] lr: 1.0000e-03 eta: 7:50:36 time: 0.7789 data_time: 0.0206 memory: 22701 grad_norm: 5.0731 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1245 loss: 1.1245 2022/09/05 23:15:37 - mmengine - INFO - Epoch(train) [64][520/940] lr: 1.0000e-03 eta: 7:50:19 time: 0.7579 data_time: 0.0740 memory: 22701 grad_norm: 5.0694 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0659 loss: 1.0659 2022/09/05 23:15:52 - mmengine - INFO - Epoch(train) [64][540/940] lr: 1.0000e-03 eta: 7:50:01 time: 0.7444 data_time: 0.1903 memory: 22701 grad_norm: 5.0467 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0179 loss: 1.0179 2022/09/05 23:16:09 - mmengine - INFO - Epoch(train) [64][560/940] lr: 1.0000e-03 eta: 7:49:45 time: 0.8453 data_time: 0.2698 memory: 22701 grad_norm: 4.9704 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0263 loss: 1.0263 2022/09/05 23:16:24 - mmengine - INFO - Epoch(train) [64][580/940] lr: 1.0000e-03 eta: 7:49:28 time: 0.7815 data_time: 0.0347 memory: 22701 grad_norm: 5.0505 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.9613 loss: 0.9613 2022/09/05 23:16:40 - mmengine - INFO - Epoch(train) [64][600/940] lr: 1.0000e-03 eta: 7:49:11 time: 0.7939 data_time: 0.0250 memory: 22701 grad_norm: 5.0601 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.0793 loss: 1.0793 2022/09/05 23:16:56 - mmengine - INFO - Epoch(train) [64][620/940] lr: 1.0000e-03 eta: 7:48:55 time: 0.8006 data_time: 0.0226 memory: 22701 grad_norm: 5.0284 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0873 loss: 1.0873 2022/09/05 23:17:11 - mmengine - INFO - Epoch(train) [64][640/940] lr: 1.0000e-03 eta: 7:48:37 time: 0.7333 data_time: 0.0282 memory: 22701 grad_norm: 5.0747 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9970 loss: 0.9970 2022/09/05 23:17:26 - mmengine - INFO - Epoch(train) [64][660/940] lr: 1.0000e-03 eta: 7:48:20 time: 0.7688 data_time: 0.0249 memory: 22701 grad_norm: 4.9926 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1456 loss: 1.1456 2022/09/05 23:17:42 - mmengine - INFO - Epoch(train) [64][680/940] lr: 1.0000e-03 eta: 7:48:03 time: 0.8009 data_time: 0.0283 memory: 22701 grad_norm: 4.9895 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0423 loss: 1.0423 2022/09/05 23:17:57 - mmengine - INFO - Epoch(train) [64][700/940] lr: 1.0000e-03 eta: 7:47:46 time: 0.7381 data_time: 0.0302 memory: 22701 grad_norm: 4.9941 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0753 loss: 1.0753 2022/09/05 23:18:14 - mmengine - INFO - Epoch(train) [64][720/940] lr: 1.0000e-03 eta: 7:47:30 time: 0.8427 data_time: 0.0287 memory: 22701 grad_norm: 5.0978 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0052 loss: 1.0052 2022/09/05 23:18:28 - mmengine - INFO - Epoch(train) [64][740/940] lr: 1.0000e-03 eta: 7:47:12 time: 0.6965 data_time: 0.0359 memory: 22701 grad_norm: 4.8728 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9427 loss: 0.9427 2022/09/05 23:18:45 - mmengine - INFO - Epoch(train) [64][760/940] lr: 1.0000e-03 eta: 7:46:55 time: 0.8335 data_time: 0.0314 memory: 22701 grad_norm: 5.0997 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1157 loss: 1.1157 2022/09/05 23:19:01 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:19:01 - mmengine - INFO - Epoch(train) [64][780/940] lr: 1.0000e-03 eta: 7:46:39 time: 0.8197 data_time: 0.0371 memory: 22701 grad_norm: 5.0539 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1206 loss: 1.1206 2022/09/05 23:19:18 - mmengine - INFO - Epoch(train) [64][800/940] lr: 1.0000e-03 eta: 7:46:23 time: 0.8343 data_time: 0.0287 memory: 22701 grad_norm: 5.0984 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1029 loss: 1.1029 2022/09/05 23:19:34 - mmengine - INFO - Epoch(train) [64][820/940] lr: 1.0000e-03 eta: 7:46:06 time: 0.8266 data_time: 0.0257 memory: 22701 grad_norm: 4.9529 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0445 loss: 1.0445 2022/09/05 23:19:52 - mmengine - INFO - Epoch(train) [64][840/940] lr: 1.0000e-03 eta: 7:45:50 time: 0.8862 data_time: 0.0238 memory: 22701 grad_norm: 5.0327 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0899 loss: 1.0899 2022/09/05 23:20:11 - mmengine - INFO - Epoch(train) [64][860/940] lr: 1.0000e-03 eta: 7:45:35 time: 0.9352 data_time: 0.0316 memory: 22701 grad_norm: 5.0073 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1715 loss: 1.1715 2022/09/05 23:20:28 - mmengine - INFO - Epoch(train) [64][880/940] lr: 1.0000e-03 eta: 7:45:19 time: 0.8713 data_time: 0.0276 memory: 22701 grad_norm: 5.0116 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0568 loss: 1.0568 2022/09/05 23:20:45 - mmengine - INFO - Epoch(train) [64][900/940] lr: 1.0000e-03 eta: 7:45:03 time: 0.8362 data_time: 0.0365 memory: 22701 grad_norm: 5.0092 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0998 loss: 1.0998 2022/09/05 23:21:03 - mmengine - INFO - Epoch(train) [64][920/940] lr: 1.0000e-03 eta: 7:44:48 time: 0.9322 data_time: 0.0345 memory: 22701 grad_norm: 5.0496 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0643 loss: 1.0643 2022/09/05 23:21:15 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:21:15 - mmengine - INFO - Epoch(train) [64][940/940] lr: 1.0000e-03 eta: 7:44:29 time: 0.5982 data_time: 0.0225 memory: 22701 grad_norm: 5.3865 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.1410 loss: 1.1410 2022/09/05 23:21:30 - mmengine - INFO - Epoch(val) [64][20/78] eta: 0:00:41 time: 0.7113 data_time: 0.5915 memory: 2247 2022/09/05 23:21:39 - mmengine - INFO - Epoch(val) [64][40/78] eta: 0:00:16 time: 0.4425 data_time: 0.3255 memory: 2247 2022/09/05 23:21:52 - mmengine - INFO - Epoch(val) [64][60/78] eta: 0:00:11 time: 0.6543 data_time: 0.5351 memory: 2247 2022/09/05 23:22:01 - mmengine - INFO - Epoch(val) [64][78/78] acc/top1: 0.6857 acc/top5: 0.8806 acc/mean1: 0.6856 2022/09/05 23:22:20 - mmengine - INFO - Epoch(train) [65][20/940] lr: 1.0000e-03 eta: 7:44:13 time: 0.9284 data_time: 0.4082 memory: 22701 grad_norm: 5.0857 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0381 loss: 1.0381 2022/09/05 23:22:34 - mmengine - INFO - Epoch(train) [65][40/940] lr: 1.0000e-03 eta: 7:43:55 time: 0.6973 data_time: 0.0920 memory: 22701 grad_norm: 5.0599 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0432 loss: 1.0432 2022/09/05 23:22:50 - mmengine - INFO - Epoch(train) [65][60/940] lr: 1.0000e-03 eta: 7:43:39 time: 0.8057 data_time: 0.0398 memory: 22701 grad_norm: 5.0880 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0630 loss: 1.0630 2022/09/05 23:23:04 - mmengine - INFO - Epoch(train) [65][80/940] lr: 1.0000e-03 eta: 7:43:21 time: 0.7109 data_time: 0.0796 memory: 22701 grad_norm: 4.9739 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0964 loss: 1.0964 2022/09/05 23:23:24 - mmengine - INFO - Epoch(train) [65][100/940] lr: 1.0000e-03 eta: 7:43:06 time: 0.9690 data_time: 0.0843 memory: 22701 grad_norm: 4.9647 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9979 loss: 0.9979 2022/09/05 23:23:38 - mmengine - INFO - Epoch(train) [65][120/940] lr: 1.0000e-03 eta: 7:42:48 time: 0.6944 data_time: 0.0279 memory: 22701 grad_norm: 5.1164 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1445 loss: 1.1445 2022/09/05 23:23:55 - mmengine - INFO - Epoch(train) [65][140/940] lr: 1.0000e-03 eta: 7:42:32 time: 0.8424 data_time: 0.1028 memory: 22701 grad_norm: 4.9362 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0309 loss: 1.0309 2022/09/05 23:24:09 - mmengine - INFO - Epoch(train) [65][160/940] lr: 1.0000e-03 eta: 7:42:14 time: 0.7078 data_time: 0.1420 memory: 22701 grad_norm: 5.0901 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9877 loss: 0.9877 2022/09/05 23:24:26 - mmengine - INFO - Epoch(train) [65][180/940] lr: 1.0000e-03 eta: 7:41:58 time: 0.8599 data_time: 0.2792 memory: 22701 grad_norm: 5.0741 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1115 loss: 1.1115 2022/09/05 23:24:40 - mmengine - INFO - Epoch(train) [65][200/940] lr: 1.0000e-03 eta: 7:41:40 time: 0.7087 data_time: 0.3308 memory: 22701 grad_norm: 4.9143 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0254 loss: 1.0254 2022/09/05 23:24:59 - mmengine - INFO - Epoch(train) [65][220/940] lr: 1.0000e-03 eta: 7:41:25 time: 0.9433 data_time: 0.5469 memory: 22701 grad_norm: 5.0603 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1288 loss: 1.1288 2022/09/05 23:25:14 - mmengine - INFO - Epoch(train) [65][240/940] lr: 1.0000e-03 eta: 7:41:08 time: 0.7613 data_time: 0.3668 memory: 22701 grad_norm: 4.8945 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0599 loss: 1.0599 2022/09/05 23:25:35 - mmengine - INFO - Epoch(train) [65][260/940] lr: 1.0000e-03 eta: 7:40:54 time: 1.0653 data_time: 0.6503 memory: 22701 grad_norm: 5.0763 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.9640 loss: 0.9640 2022/09/05 23:25:50 - mmengine - INFO - Epoch(train) [65][280/940] lr: 1.0000e-03 eta: 7:40:37 time: 0.7380 data_time: 0.3594 memory: 22701 grad_norm: 5.1137 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0917 loss: 1.0917 2022/09/05 23:26:10 - mmengine - INFO - Epoch(train) [65][300/940] lr: 1.0000e-03 eta: 7:40:22 time: 0.9899 data_time: 0.5948 memory: 22701 grad_norm: 5.1138 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0273 loss: 1.0273 2022/09/05 23:26:25 - mmengine - INFO - Epoch(train) [65][320/940] lr: 1.0000e-03 eta: 7:40:05 time: 0.7499 data_time: 0.3554 memory: 22701 grad_norm: 4.9923 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9722 loss: 0.9722 2022/09/05 23:26:45 - mmengine - INFO - Epoch(train) [65][340/940] lr: 1.0000e-03 eta: 7:39:51 time: 1.0094 data_time: 0.5915 memory: 22701 grad_norm: 5.0447 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9726 loss: 0.9726 2022/09/05 23:27:01 - mmengine - INFO - Epoch(train) [65][360/940] lr: 1.0000e-03 eta: 7:39:34 time: 0.8056 data_time: 0.4199 memory: 22701 grad_norm: 4.9448 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0036 loss: 1.0036 2022/09/05 23:27:22 - mmengine - INFO - Epoch(train) [65][380/940] lr: 1.0000e-03 eta: 7:39:20 time: 1.0503 data_time: 0.4209 memory: 22701 grad_norm: 5.1366 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1868 loss: 1.1868 2022/09/05 23:27:38 - mmengine - INFO - Epoch(train) [65][400/940] lr: 1.0000e-03 eta: 7:39:03 time: 0.7623 data_time: 0.1371 memory: 22701 grad_norm: 5.0363 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1354 loss: 1.1354 2022/09/05 23:27:58 - mmengine - INFO - Epoch(train) [65][420/940] lr: 1.0000e-03 eta: 7:38:48 time: 0.9998 data_time: 0.2424 memory: 22701 grad_norm: 5.1253 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1275 loss: 1.1275 2022/09/05 23:28:12 - mmengine - INFO - Epoch(train) [65][440/940] lr: 1.0000e-03 eta: 7:38:31 time: 0.7269 data_time: 0.0779 memory: 22701 grad_norm: 5.1238 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1925 loss: 1.1925 2022/09/05 23:28:31 - mmengine - INFO - Epoch(train) [65][460/940] lr: 1.0000e-03 eta: 7:38:15 time: 0.9123 data_time: 0.0747 memory: 22701 grad_norm: 5.0629 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0439 loss: 1.0439 2022/09/05 23:28:46 - mmengine - INFO - Epoch(train) [65][480/940] lr: 1.0000e-03 eta: 7:37:58 time: 0.7588 data_time: 0.1142 memory: 22701 grad_norm: 5.1683 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0484 loss: 1.0484 2022/09/05 23:29:03 - mmengine - INFO - Epoch(train) [65][500/940] lr: 1.0000e-03 eta: 7:37:42 time: 0.8484 data_time: 0.0544 memory: 22701 grad_norm: 5.0666 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1009 loss: 1.1009 2022/09/05 23:29:18 - mmengine - INFO - Epoch(train) [65][520/940] lr: 1.0000e-03 eta: 7:37:25 time: 0.7499 data_time: 0.0337 memory: 22701 grad_norm: 5.1042 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0470 loss: 1.0470 2022/09/05 23:29:34 - mmengine - INFO - Epoch(train) [65][540/940] lr: 1.0000e-03 eta: 7:37:08 time: 0.8414 data_time: 0.1340 memory: 22701 grad_norm: 4.9797 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0818 loss: 1.0818 2022/09/05 23:29:49 - mmengine - INFO - Epoch(train) [65][560/940] lr: 1.0000e-03 eta: 7:36:51 time: 0.7400 data_time: 0.0812 memory: 22701 grad_norm: 5.1108 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9869 loss: 0.9869 2022/09/05 23:30:07 - mmengine - INFO - Epoch(train) [65][580/940] lr: 1.0000e-03 eta: 7:36:35 time: 0.9136 data_time: 0.0508 memory: 22701 grad_norm: 5.0593 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9703 loss: 0.9703 2022/09/05 23:30:21 - mmengine - INFO - Epoch(train) [65][600/940] lr: 1.0000e-03 eta: 7:36:18 time: 0.6931 data_time: 0.0264 memory: 22701 grad_norm: 5.0997 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.0894 loss: 1.0894 2022/09/05 23:30:40 - mmengine - INFO - Epoch(train) [65][620/940] lr: 1.0000e-03 eta: 7:36:02 time: 0.9494 data_time: 0.0232 memory: 22701 grad_norm: 4.9238 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0102 loss: 1.0102 2022/09/05 23:30:59 - mmengine - INFO - Epoch(train) [65][640/940] lr: 1.0000e-03 eta: 7:35:47 time: 0.9145 data_time: 0.0325 memory: 22701 grad_norm: 5.0858 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0367 loss: 1.0367 2022/09/05 23:31:21 - mmengine - INFO - Epoch(train) [65][660/940] lr: 1.0000e-03 eta: 7:35:33 time: 1.0918 data_time: 0.0318 memory: 22701 grad_norm: 5.0471 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0545 loss: 1.0545 2022/09/05 23:31:37 - mmengine - INFO - Epoch(train) [65][680/940] lr: 1.0000e-03 eta: 7:35:17 time: 0.8185 data_time: 0.0321 memory: 22701 grad_norm: 5.1316 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9903 loss: 0.9903 2022/09/05 23:31:58 - mmengine - INFO - Epoch(train) [65][700/940] lr: 1.0000e-03 eta: 7:35:03 time: 1.0379 data_time: 0.0309 memory: 22701 grad_norm: 4.9561 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 0.9917 loss: 0.9917 2022/09/05 23:32:12 - mmengine - INFO - Epoch(train) [65][720/940] lr: 1.0000e-03 eta: 7:34:45 time: 0.7417 data_time: 0.0308 memory: 22701 grad_norm: 5.1561 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0419 loss: 1.0419 2022/09/05 23:32:31 - mmengine - INFO - Epoch(train) [65][740/940] lr: 1.0000e-03 eta: 7:34:30 time: 0.9298 data_time: 0.0234 memory: 22701 grad_norm: 4.9579 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0152 loss: 1.0152 2022/09/05 23:32:46 - mmengine - INFO - Epoch(train) [65][760/940] lr: 1.0000e-03 eta: 7:34:13 time: 0.7410 data_time: 0.0342 memory: 22701 grad_norm: 4.9958 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0602 loss: 1.0602 2022/09/05 23:33:07 - mmengine - INFO - Epoch(train) [65][780/940] lr: 1.0000e-03 eta: 7:33:59 time: 1.0570 data_time: 0.0261 memory: 22701 grad_norm: 5.1040 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0623 loss: 1.0623 2022/09/05 23:33:21 - mmengine - INFO - Epoch(train) [65][800/940] lr: 1.0000e-03 eta: 7:33:41 time: 0.7091 data_time: 0.0283 memory: 22701 grad_norm: 5.0386 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0015 loss: 1.0015 2022/09/05 23:33:39 - mmengine - INFO - Epoch(train) [65][820/940] lr: 1.0000e-03 eta: 7:33:25 time: 0.8646 data_time: 0.0272 memory: 22701 grad_norm: 4.9915 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0312 loss: 1.0312 2022/09/05 23:33:55 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:33:55 - mmengine - INFO - Epoch(train) [65][840/940] lr: 1.0000e-03 eta: 7:33:09 time: 0.8345 data_time: 0.0250 memory: 22701 grad_norm: 5.0466 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0918 loss: 1.0918 2022/09/05 23:34:14 - mmengine - INFO - Epoch(train) [65][860/940] lr: 1.0000e-03 eta: 7:32:53 time: 0.9398 data_time: 0.0500 memory: 22701 grad_norm: 5.0770 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 0.9951 loss: 0.9951 2022/09/05 23:34:30 - mmengine - INFO - Epoch(train) [65][880/940] lr: 1.0000e-03 eta: 7:32:36 time: 0.7788 data_time: 0.0154 memory: 22701 grad_norm: 5.1654 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2402 loss: 1.2402 2022/09/05 23:34:53 - mmengine - INFO - Epoch(train) [65][900/940] lr: 1.0000e-03 eta: 7:32:23 time: 1.1474 data_time: 0.0806 memory: 22701 grad_norm: 5.0171 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0491 loss: 1.0491 2022/09/05 23:35:09 - mmengine - INFO - Epoch(train) [65][920/940] lr: 1.0000e-03 eta: 7:32:07 time: 0.8171 data_time: 0.2039 memory: 22701 grad_norm: 5.0450 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9692 loss: 0.9692 2022/09/05 23:35:27 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:35:27 - mmengine - INFO - Epoch(train) [65][940/940] lr: 1.0000e-03 eta: 7:31:51 time: 0.9258 data_time: 0.0354 memory: 22701 grad_norm: 5.3498 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.0532 loss: 1.0532 2022/09/05 23:35:41 - mmengine - INFO - Epoch(val) [65][20/78] eta: 0:00:39 time: 0.6793 data_time: 0.5590 memory: 2247 2022/09/05 23:35:50 - mmengine - INFO - Epoch(val) [65][40/78] eta: 0:00:17 time: 0.4601 data_time: 0.3409 memory: 2247 2022/09/05 23:36:03 - mmengine - INFO - Epoch(val) [65][60/78] eta: 0:00:11 time: 0.6621 data_time: 0.5436 memory: 2247 2022/09/05 23:36:14 - mmengine - INFO - Epoch(val) [65][78/78] acc/top1: 0.6871 acc/top5: 0.8808 acc/mean1: 0.6871 2022/09/05 23:36:36 - mmengine - INFO - Epoch(train) [66][20/940] lr: 1.0000e-03 eta: 7:31:38 time: 1.1277 data_time: 0.4276 memory: 22701 grad_norm: 5.0523 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9841 loss: 0.9841 2022/09/05 23:36:50 - mmengine - INFO - Epoch(train) [66][40/940] lr: 1.0000e-03 eta: 7:31:20 time: 0.6768 data_time: 0.0423 memory: 22701 grad_norm: 5.0542 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1184 loss: 1.1184 2022/09/05 23:37:08 - mmengine - INFO - Epoch(train) [66][60/940] lr: 1.0000e-03 eta: 7:31:05 time: 0.9177 data_time: 0.0260 memory: 22701 grad_norm: 5.0424 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0201 loss: 1.0201 2022/09/05 23:37:24 - mmengine - INFO - Epoch(train) [66][80/940] lr: 1.0000e-03 eta: 7:30:48 time: 0.7697 data_time: 0.0233 memory: 22701 grad_norm: 5.0106 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9731 loss: 0.9731 2022/09/05 23:37:40 - mmengine - INFO - Epoch(train) [66][100/940] lr: 1.0000e-03 eta: 7:30:31 time: 0.8254 data_time: 0.0257 memory: 22701 grad_norm: 5.0258 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.0615 loss: 1.0615 2022/09/05 23:37:55 - mmengine - INFO - Epoch(train) [66][120/940] lr: 1.0000e-03 eta: 7:30:14 time: 0.7190 data_time: 0.0213 memory: 22701 grad_norm: 5.0162 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0072 loss: 1.0072 2022/09/05 23:38:11 - mmengine - INFO - Epoch(train) [66][140/940] lr: 1.0000e-03 eta: 7:29:57 time: 0.8339 data_time: 0.0491 memory: 22701 grad_norm: 5.1307 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0559 loss: 1.0559 2022/09/05 23:38:25 - mmengine - INFO - Epoch(train) [66][160/940] lr: 1.0000e-03 eta: 7:29:39 time: 0.7082 data_time: 0.0253 memory: 22701 grad_norm: 4.9718 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0248 loss: 1.0248 2022/09/05 23:38:48 - mmengine - INFO - Epoch(train) [66][180/940] lr: 1.0000e-03 eta: 7:29:26 time: 1.1070 data_time: 0.0250 memory: 22701 grad_norm: 5.1305 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9840 loss: 0.9840 2022/09/05 23:39:03 - mmengine - INFO - Epoch(train) [66][200/940] lr: 1.0000e-03 eta: 7:29:09 time: 0.7487 data_time: 0.0205 memory: 22701 grad_norm: 5.1046 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0798 loss: 1.0798 2022/09/05 23:39:21 - mmengine - INFO - Epoch(train) [66][220/940] lr: 1.0000e-03 eta: 7:28:53 time: 0.9340 data_time: 0.0242 memory: 22701 grad_norm: 5.1173 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0047 loss: 1.0047 2022/09/05 23:39:36 - mmengine - INFO - Epoch(train) [66][240/940] lr: 1.0000e-03 eta: 7:28:36 time: 0.7509 data_time: 0.0300 memory: 22701 grad_norm: 5.0635 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0500 loss: 1.0500 2022/09/05 23:39:56 - mmengine - INFO - Epoch(train) [66][260/940] lr: 1.0000e-03 eta: 7:28:21 time: 0.9637 data_time: 0.0230 memory: 22701 grad_norm: 4.9809 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0075 loss: 1.0075 2022/09/05 23:40:10 - mmengine - INFO - Epoch(train) [66][280/940] lr: 1.0000e-03 eta: 7:28:04 time: 0.7358 data_time: 0.0281 memory: 22701 grad_norm: 4.9534 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0302 loss: 1.0302 2022/09/05 23:40:29 - mmengine - INFO - Epoch(train) [66][300/940] lr: 1.0000e-03 eta: 7:27:48 time: 0.9354 data_time: 0.0222 memory: 22701 grad_norm: 5.0836 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0195 loss: 1.0195 2022/09/05 23:40:45 - mmengine - INFO - Epoch(train) [66][320/940] lr: 1.0000e-03 eta: 7:27:32 time: 0.7941 data_time: 0.0324 memory: 22701 grad_norm: 5.1172 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1137 loss: 1.1137 2022/09/05 23:41:03 - mmengine - INFO - Epoch(train) [66][340/940] lr: 1.0000e-03 eta: 7:27:16 time: 0.9177 data_time: 0.0259 memory: 22701 grad_norm: 5.0236 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0489 loss: 1.0489 2022/09/05 23:41:22 - mmengine - INFO - Epoch(train) [66][360/940] lr: 1.0000e-03 eta: 7:27:01 time: 0.9170 data_time: 0.0710 memory: 22701 grad_norm: 5.1639 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0954 loss: 1.0954 2022/09/05 23:41:40 - mmengine - INFO - Epoch(train) [66][380/940] lr: 1.0000e-03 eta: 7:26:45 time: 0.9343 data_time: 0.0318 memory: 22701 grad_norm: 5.1667 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1100 loss: 1.1100 2022/09/05 23:41:55 - mmengine - INFO - Epoch(train) [66][400/940] lr: 1.0000e-03 eta: 7:26:28 time: 0.7452 data_time: 0.0253 memory: 22701 grad_norm: 4.9647 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0827 loss: 1.0827 2022/09/05 23:42:13 - mmengine - INFO - Epoch(train) [66][420/940] lr: 1.0000e-03 eta: 7:26:12 time: 0.9153 data_time: 0.0233 memory: 22701 grad_norm: 5.1588 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9312 loss: 0.9312 2022/09/05 23:42:31 - mmengine - INFO - Epoch(train) [66][440/940] lr: 1.0000e-03 eta: 7:25:56 time: 0.8760 data_time: 0.0184 memory: 22701 grad_norm: 5.0671 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0210 loss: 1.0210 2022/09/05 23:42:51 - mmengine - INFO - Epoch(train) [66][460/940] lr: 1.0000e-03 eta: 7:25:42 time: 0.9995 data_time: 0.0301 memory: 22701 grad_norm: 5.1786 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.0360 loss: 1.0360 2022/09/05 23:43:07 - mmengine - INFO - Epoch(train) [66][480/940] lr: 1.0000e-03 eta: 7:25:25 time: 0.8171 data_time: 0.0466 memory: 22701 grad_norm: 5.1696 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0064 loss: 1.0064 2022/09/05 23:43:26 - mmengine - INFO - Epoch(train) [66][500/940] lr: 1.0000e-03 eta: 7:25:10 time: 0.9166 data_time: 0.0287 memory: 22701 grad_norm: 5.0317 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8733 loss: 0.8733 2022/09/05 23:43:42 - mmengine - INFO - Epoch(train) [66][520/940] lr: 1.0000e-03 eta: 7:24:53 time: 0.8071 data_time: 0.0442 memory: 22701 grad_norm: 5.0635 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0431 loss: 1.0431 2022/09/05 23:44:00 - mmengine - INFO - Epoch(train) [66][540/940] lr: 1.0000e-03 eta: 7:24:38 time: 0.9141 data_time: 0.1843 memory: 22701 grad_norm: 5.0307 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0242 loss: 1.0242 2022/09/05 23:44:20 - mmengine - INFO - Epoch(train) [66][560/940] lr: 1.0000e-03 eta: 7:24:23 time: 0.9715 data_time: 0.0667 memory: 22701 grad_norm: 5.0493 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0707 loss: 1.0707 2022/09/05 23:44:37 - mmengine - INFO - Epoch(train) [66][580/940] lr: 1.0000e-03 eta: 7:24:07 time: 0.8774 data_time: 0.0575 memory: 22701 grad_norm: 4.9636 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1099 loss: 1.1099 2022/09/05 23:44:53 - mmengine - INFO - Epoch(train) [66][600/940] lr: 1.0000e-03 eta: 7:23:50 time: 0.8043 data_time: 0.0596 memory: 22701 grad_norm: 5.0409 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9500 loss: 0.9500 2022/09/05 23:45:10 - mmengine - INFO - Epoch(train) [66][620/940] lr: 1.0000e-03 eta: 7:23:34 time: 0.8472 data_time: 0.0509 memory: 22701 grad_norm: 5.0535 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0096 loss: 1.0096 2022/09/05 23:45:25 - mmengine - INFO - Epoch(train) [66][640/940] lr: 1.0000e-03 eta: 7:23:17 time: 0.7588 data_time: 0.0242 memory: 22701 grad_norm: 5.1151 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9649 loss: 0.9649 2022/09/05 23:45:43 - mmengine - INFO - Epoch(train) [66][660/940] lr: 1.0000e-03 eta: 7:23:01 time: 0.8962 data_time: 0.0264 memory: 22701 grad_norm: 5.0691 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0717 loss: 1.0717 2022/09/05 23:45:58 - mmengine - INFO - Epoch(train) [66][680/940] lr: 1.0000e-03 eta: 7:22:44 time: 0.7564 data_time: 0.0276 memory: 22701 grad_norm: 5.1459 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0714 loss: 1.0714 2022/09/05 23:46:15 - mmengine - INFO - Epoch(train) [66][700/940] lr: 1.0000e-03 eta: 7:22:27 time: 0.8496 data_time: 0.0259 memory: 22701 grad_norm: 5.2035 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0657 loss: 1.0657 2022/09/05 23:46:30 - mmengine - INFO - Epoch(train) [66][720/940] lr: 1.0000e-03 eta: 7:22:10 time: 0.7158 data_time: 0.0319 memory: 22701 grad_norm: 5.1006 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9966 loss: 0.9966 2022/09/05 23:46:47 - mmengine - INFO - Epoch(train) [66][740/940] lr: 1.0000e-03 eta: 7:21:54 time: 0.8662 data_time: 0.0294 memory: 22701 grad_norm: 5.1709 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0918 loss: 1.0918 2022/09/05 23:47:02 - mmengine - INFO - Epoch(train) [66][760/940] lr: 1.0000e-03 eta: 7:21:36 time: 0.7501 data_time: 0.0229 memory: 22701 grad_norm: 5.0482 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0262 loss: 1.0262 2022/09/05 23:47:20 - mmengine - INFO - Epoch(train) [66][780/940] lr: 1.0000e-03 eta: 7:21:21 time: 0.9128 data_time: 0.0222 memory: 22701 grad_norm: 5.2902 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1752 loss: 1.1752 2022/09/05 23:47:36 - mmengine - INFO - Epoch(train) [66][800/940] lr: 1.0000e-03 eta: 7:21:04 time: 0.7949 data_time: 0.0291 memory: 22701 grad_norm: 5.0714 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0797 loss: 1.0797 2022/09/05 23:47:52 - mmengine - INFO - Epoch(train) [66][820/940] lr: 1.0000e-03 eta: 7:20:47 time: 0.7992 data_time: 0.0273 memory: 22701 grad_norm: 5.1010 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0433 loss: 1.0433 2022/09/05 23:48:11 - mmengine - INFO - Epoch(train) [66][840/940] lr: 1.0000e-03 eta: 7:20:32 time: 0.9379 data_time: 0.0258 memory: 22701 grad_norm: 5.0806 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0059 loss: 1.0059 2022/09/05 23:48:25 - mmengine - INFO - Epoch(train) [66][860/940] lr: 1.0000e-03 eta: 7:20:14 time: 0.7040 data_time: 0.0351 memory: 22701 grad_norm: 4.9511 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0732 loss: 1.0732 2022/09/05 23:48:42 - mmengine - INFO - Epoch(train) [66][880/940] lr: 1.0000e-03 eta: 7:19:58 time: 0.8361 data_time: 0.0691 memory: 22701 grad_norm: 5.0438 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0073 loss: 1.0073 2022/09/05 23:48:57 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:48:58 - mmengine - INFO - Epoch(train) [66][900/940] lr: 1.0000e-03 eta: 7:19:41 time: 0.7856 data_time: 0.0468 memory: 22701 grad_norm: 5.0570 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.0373 loss: 1.0373 2022/09/05 23:49:15 - mmengine - INFO - Epoch(train) [66][920/940] lr: 1.0000e-03 eta: 7:19:25 time: 0.8547 data_time: 0.0272 memory: 22701 grad_norm: 5.1325 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9600 loss: 0.9600 2022/09/05 23:49:28 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/05 23:49:28 - mmengine - INFO - Epoch(train) [66][940/940] lr: 1.0000e-03 eta: 7:19:07 time: 0.6639 data_time: 0.0234 memory: 22701 grad_norm: 5.3846 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0396 loss: 1.0396 2022/09/05 23:49:28 - mmengine - INFO - Saving checkpoint at 66 epochs 2022/09/05 23:49:44 - mmengine - INFO - Epoch(val) [66][20/78] eta: 0:00:40 time: 0.7005 data_time: 0.5830 memory: 2247 2022/09/05 23:49:53 - mmengine - INFO - Epoch(val) [66][40/78] eta: 0:00:17 time: 0.4505 data_time: 0.3338 memory: 2247 2022/09/05 23:50:07 - mmengine - INFO - Epoch(val) [66][60/78] eta: 0:00:12 time: 0.6787 data_time: 0.5623 memory: 2247 2022/09/05 23:50:16 - mmengine - INFO - Epoch(val) [66][78/78] acc/top1: 0.6864 acc/top5: 0.8797 acc/mean1: 0.6863 2022/09/05 23:50:35 - mmengine - INFO - Epoch(train) [67][20/940] lr: 1.0000e-03 eta: 7:18:51 time: 0.9474 data_time: 0.4458 memory: 22701 grad_norm: 5.0057 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0963 loss: 1.0963 2022/09/05 23:50:49 - mmengine - INFO - Epoch(train) [67][40/940] lr: 1.0000e-03 eta: 7:18:34 time: 0.6891 data_time: 0.2013 memory: 22701 grad_norm: 5.0808 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0209 loss: 1.0209 2022/09/05 23:51:08 - mmengine - INFO - Epoch(train) [67][60/940] lr: 1.0000e-03 eta: 7:18:18 time: 0.9451 data_time: 0.1976 memory: 22701 grad_norm: 5.0786 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0389 loss: 1.0389 2022/09/05 23:51:24 - mmengine - INFO - Epoch(train) [67][80/940] lr: 1.0000e-03 eta: 7:18:02 time: 0.7949 data_time: 0.0309 memory: 22701 grad_norm: 5.0159 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0335 loss: 1.0335 2022/09/05 23:51:43 - mmengine - INFO - Epoch(train) [67][100/940] lr: 1.0000e-03 eta: 7:17:47 time: 0.9733 data_time: 0.0331 memory: 22701 grad_norm: 5.0696 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0515 loss: 1.0515 2022/09/05 23:51:59 - mmengine - INFO - Epoch(train) [67][120/940] lr: 1.0000e-03 eta: 7:17:30 time: 0.7797 data_time: 0.0248 memory: 22701 grad_norm: 5.0347 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.9859 loss: 0.9859 2022/09/05 23:52:15 - mmengine - INFO - Epoch(train) [67][140/940] lr: 1.0000e-03 eta: 7:17:13 time: 0.8419 data_time: 0.0285 memory: 22701 grad_norm: 5.0851 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0033 loss: 1.0033 2022/09/05 23:52:31 - mmengine - INFO - Epoch(train) [67][160/940] lr: 1.0000e-03 eta: 7:16:56 time: 0.7718 data_time: 0.0233 memory: 22701 grad_norm: 5.1146 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0325 loss: 1.0325 2022/09/05 23:52:48 - mmengine - INFO - Epoch(train) [67][180/940] lr: 1.0000e-03 eta: 7:16:40 time: 0.8730 data_time: 0.0280 memory: 22701 grad_norm: 5.0649 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0670 loss: 1.0670 2022/09/05 23:53:03 - mmengine - INFO - Epoch(train) [67][200/940] lr: 1.0000e-03 eta: 7:16:23 time: 0.7464 data_time: 0.0225 memory: 22701 grad_norm: 5.0364 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9895 loss: 0.9895 2022/09/05 23:53:20 - mmengine - INFO - Epoch(train) [67][220/940] lr: 1.0000e-03 eta: 7:16:07 time: 0.8566 data_time: 0.0254 memory: 22701 grad_norm: 5.1356 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1129 loss: 1.1129 2022/09/05 23:53:34 - mmengine - INFO - Epoch(train) [67][240/940] lr: 1.0000e-03 eta: 7:15:49 time: 0.6782 data_time: 0.0272 memory: 22701 grad_norm: 4.9971 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9631 loss: 0.9631 2022/09/05 23:53:51 - mmengine - INFO - Epoch(train) [67][260/940] lr: 1.0000e-03 eta: 7:15:33 time: 0.8478 data_time: 0.0292 memory: 22701 grad_norm: 5.1229 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.0492 loss: 1.0492 2022/09/05 23:54:05 - mmengine - INFO - Epoch(train) [67][280/940] lr: 1.0000e-03 eta: 7:15:15 time: 0.7029 data_time: 0.0307 memory: 22701 grad_norm: 5.0487 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0571 loss: 1.0571 2022/09/05 23:54:21 - mmengine - INFO - Epoch(train) [67][300/940] lr: 1.0000e-03 eta: 7:14:58 time: 0.7758 data_time: 0.0539 memory: 22701 grad_norm: 5.2172 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0160 loss: 1.0160 2022/09/05 23:54:34 - mmengine - INFO - Epoch(train) [67][320/940] lr: 1.0000e-03 eta: 7:14:40 time: 0.6891 data_time: 0.0709 memory: 22701 grad_norm: 5.0990 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1035 loss: 1.1035 2022/09/05 23:54:50 - mmengine - INFO - Epoch(train) [67][340/940] lr: 1.0000e-03 eta: 7:14:23 time: 0.7733 data_time: 0.1359 memory: 22701 grad_norm: 5.1239 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1105 loss: 1.1105 2022/09/05 23:55:04 - mmengine - INFO - Epoch(train) [67][360/940] lr: 1.0000e-03 eta: 7:14:06 time: 0.7325 data_time: 0.1661 memory: 22701 grad_norm: 5.0525 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0311 loss: 1.0311 2022/09/05 23:55:20 - mmengine - INFO - Epoch(train) [67][380/940] lr: 1.0000e-03 eta: 7:13:49 time: 0.7949 data_time: 0.0878 memory: 22701 grad_norm: 5.1131 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0264 loss: 1.0264 2022/09/05 23:55:35 - mmengine - INFO - Epoch(train) [67][400/940] lr: 1.0000e-03 eta: 7:13:31 time: 0.7277 data_time: 0.0474 memory: 22701 grad_norm: 5.0681 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0734 loss: 1.0734 2022/09/05 23:55:53 - mmengine - INFO - Epoch(train) [67][420/940] lr: 1.0000e-03 eta: 7:13:16 time: 0.8910 data_time: 0.0444 memory: 22701 grad_norm: 5.0841 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0477 loss: 1.0477 2022/09/05 23:56:08 - mmengine - INFO - Epoch(train) [67][440/940] lr: 1.0000e-03 eta: 7:12:58 time: 0.7480 data_time: 0.0279 memory: 22701 grad_norm: 5.1061 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0204 loss: 1.0204 2022/09/05 23:56:26 - mmengine - INFO - Epoch(train) [67][460/940] lr: 1.0000e-03 eta: 7:12:43 time: 0.9343 data_time: 0.0291 memory: 22701 grad_norm: 5.1495 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.0931 loss: 1.0931 2022/09/05 23:56:44 - mmengine - INFO - Epoch(train) [67][480/940] lr: 1.0000e-03 eta: 7:12:27 time: 0.8657 data_time: 0.0496 memory: 22701 grad_norm: 5.1417 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1351 loss: 1.1351 2022/09/05 23:57:00 - mmengine - INFO - Epoch(train) [67][500/940] lr: 1.0000e-03 eta: 7:12:10 time: 0.8276 data_time: 0.0275 memory: 22701 grad_norm: 5.1453 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0809 loss: 1.0809 2022/09/05 23:57:20 - mmengine - INFO - Epoch(train) [67][520/940] lr: 1.0000e-03 eta: 7:11:56 time: 0.9781 data_time: 0.0390 memory: 22701 grad_norm: 5.0899 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1046 loss: 1.1046 2022/09/05 23:57:40 - mmengine - INFO - Epoch(train) [67][540/940] lr: 1.0000e-03 eta: 7:11:41 time: 1.0134 data_time: 0.0257 memory: 22701 grad_norm: 5.0359 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0495 loss: 1.0495 2022/09/05 23:57:54 - mmengine - INFO - Epoch(train) [67][560/940] lr: 1.0000e-03 eta: 7:11:23 time: 0.6855 data_time: 0.0315 memory: 22701 grad_norm: 5.1335 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9628 loss: 0.9628 2022/09/05 23:58:12 - mmengine - INFO - Epoch(train) [67][580/940] lr: 1.0000e-03 eta: 7:11:08 time: 0.9270 data_time: 0.0246 memory: 22701 grad_norm: 5.1632 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2249 loss: 1.2249 2022/09/05 23:58:31 - mmengine - INFO - Epoch(train) [67][600/940] lr: 1.0000e-03 eta: 7:10:52 time: 0.9444 data_time: 0.1154 memory: 22701 grad_norm: 5.2479 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0642 loss: 1.0642 2022/09/05 23:58:47 - mmengine - INFO - Epoch(train) [67][620/940] lr: 1.0000e-03 eta: 7:10:35 time: 0.7878 data_time: 0.2121 memory: 22701 grad_norm: 5.2434 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0911 loss: 1.0911 2022/09/05 23:59:03 - mmengine - INFO - Epoch(train) [67][640/940] lr: 1.0000e-03 eta: 7:10:19 time: 0.7944 data_time: 0.3541 memory: 22701 grad_norm: 5.1119 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8874 loss: 0.8874 2022/09/05 23:59:19 - mmengine - INFO - Epoch(train) [67][660/940] lr: 1.0000e-03 eta: 7:10:02 time: 0.7888 data_time: 0.3718 memory: 22701 grad_norm: 5.2349 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9353 loss: 0.9353 2022/09/05 23:59:38 - mmengine - INFO - Epoch(train) [67][680/940] lr: 1.0000e-03 eta: 7:09:47 time: 0.9675 data_time: 0.5681 memory: 22701 grad_norm: 5.0412 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0345 loss: 1.0345 2022/09/05 23:59:53 - mmengine - INFO - Epoch(train) [67][700/940] lr: 1.0000e-03 eta: 7:09:30 time: 0.7702 data_time: 0.3671 memory: 22701 grad_norm: 5.1422 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0856 loss: 1.0856 2022/09/06 00:00:12 - mmengine - INFO - Epoch(train) [67][720/940] lr: 1.0000e-03 eta: 7:09:14 time: 0.9221 data_time: 0.4471 memory: 22701 grad_norm: 5.2094 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1284 loss: 1.1284 2022/09/06 00:00:27 - mmengine - INFO - Epoch(train) [67][740/940] lr: 1.0000e-03 eta: 7:08:57 time: 0.7523 data_time: 0.3447 memory: 22701 grad_norm: 5.1443 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0344 loss: 1.0344 2022/09/06 00:00:45 - mmengine - INFO - Epoch(train) [67][760/940] lr: 1.0000e-03 eta: 7:08:41 time: 0.9173 data_time: 0.5005 memory: 22701 grad_norm: 5.1675 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9238 loss: 0.9238 2022/09/06 00:00:58 - mmengine - INFO - Epoch(train) [67][780/940] lr: 1.0000e-03 eta: 7:08:23 time: 0.6156 data_time: 0.2265 memory: 22701 grad_norm: 5.0274 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9431 loss: 0.9431 2022/09/06 00:01:13 - mmengine - INFO - Epoch(train) [67][800/940] lr: 1.0000e-03 eta: 7:08:06 time: 0.7651 data_time: 0.3757 memory: 22701 grad_norm: 5.1631 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0651 loss: 1.0651 2022/09/06 00:01:26 - mmengine - INFO - Epoch(train) [67][820/940] lr: 1.0000e-03 eta: 7:07:48 time: 0.6702 data_time: 0.2493 memory: 22701 grad_norm: 5.1283 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0516 loss: 1.0516 2022/09/06 00:01:44 - mmengine - INFO - Epoch(train) [67][840/940] lr: 1.0000e-03 eta: 7:07:32 time: 0.8853 data_time: 0.4870 memory: 22701 grad_norm: 5.1010 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0510 loss: 1.0510 2022/09/06 00:01:57 - mmengine - INFO - Epoch(train) [67][860/940] lr: 1.0000e-03 eta: 7:07:14 time: 0.6454 data_time: 0.2427 memory: 22701 grad_norm: 5.0532 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0093 loss: 1.0093 2022/09/06 00:02:13 - mmengine - INFO - Epoch(train) [67][880/940] lr: 1.0000e-03 eta: 7:06:57 time: 0.8097 data_time: 0.4069 memory: 22701 grad_norm: 5.1275 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0246 loss: 1.0246 2022/09/06 00:02:28 - mmengine - INFO - Epoch(train) [67][900/940] lr: 1.0000e-03 eta: 7:06:40 time: 0.7635 data_time: 0.3746 memory: 22701 grad_norm: 5.2178 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0862 loss: 1.0862 2022/09/06 00:02:46 - mmengine - INFO - Epoch(train) [67][920/940] lr: 1.0000e-03 eta: 7:06:24 time: 0.8750 data_time: 0.4815 memory: 22701 grad_norm: 5.1145 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 0.9889 loss: 0.9889 2022/09/06 00:02:58 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:02:58 - mmengine - INFO - Epoch(train) [67][940/940] lr: 1.0000e-03 eta: 7:06:05 time: 0.6098 data_time: 0.2356 memory: 22701 grad_norm: 5.3776 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 1.0426 loss: 1.0426 2022/09/06 00:03:12 - mmengine - INFO - Epoch(val) [67][20/78] eta: 0:00:40 time: 0.6919 data_time: 0.5718 memory: 2247 2022/09/06 00:03:21 - mmengine - INFO - Epoch(val) [67][40/78] eta: 0:00:16 time: 0.4433 data_time: 0.3263 memory: 2247 2022/09/06 00:03:34 - mmengine - INFO - Epoch(val) [67][60/78] eta: 0:00:11 time: 0.6518 data_time: 0.5314 memory: 2247 2022/09/06 00:03:44 - mmengine - INFO - Epoch(val) [67][78/78] acc/top1: 0.6876 acc/top5: 0.8800 acc/mean1: 0.6875 2022/09/06 00:04:06 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:04:06 - mmengine - INFO - Epoch(train) [68][20/940] lr: 1.0000e-03 eta: 7:05:51 time: 1.0806 data_time: 0.4920 memory: 22701 grad_norm: 5.0003 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0716 loss: 1.0716 2022/09/06 00:04:20 - mmengine - INFO - Epoch(train) [68][40/940] lr: 1.0000e-03 eta: 7:05:34 time: 0.7246 data_time: 0.1240 memory: 22701 grad_norm: 4.9905 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0140 loss: 1.0140 2022/09/06 00:04:38 - mmengine - INFO - Epoch(train) [68][60/940] lr: 1.0000e-03 eta: 7:05:18 time: 0.8898 data_time: 0.3830 memory: 22701 grad_norm: 4.9085 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0838 loss: 1.0838 2022/09/06 00:04:53 - mmengine - INFO - Epoch(train) [68][80/940] lr: 1.0000e-03 eta: 7:05:01 time: 0.7477 data_time: 0.3115 memory: 22701 grad_norm: 5.1944 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9624 loss: 0.9624 2022/09/06 00:05:10 - mmengine - INFO - Epoch(train) [68][100/940] lr: 1.0000e-03 eta: 7:04:45 time: 0.8378 data_time: 0.1506 memory: 22701 grad_norm: 5.1333 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9993 loss: 0.9993 2022/09/06 00:05:24 - mmengine - INFO - Epoch(train) [68][120/940] lr: 1.0000e-03 eta: 7:04:27 time: 0.7195 data_time: 0.0323 memory: 22701 grad_norm: 5.0705 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0978 loss: 1.0978 2022/09/06 00:05:42 - mmengine - INFO - Epoch(train) [68][140/940] lr: 1.0000e-03 eta: 7:04:11 time: 0.8688 data_time: 0.0421 memory: 22701 grad_norm: 5.0154 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9927 loss: 0.9927 2022/09/06 00:05:56 - mmengine - INFO - Epoch(train) [68][160/940] lr: 1.0000e-03 eta: 7:03:54 time: 0.7277 data_time: 0.0363 memory: 22701 grad_norm: 5.0449 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0230 loss: 1.0230 2022/09/06 00:06:15 - mmengine - INFO - Epoch(train) [68][180/940] lr: 1.0000e-03 eta: 7:03:38 time: 0.9477 data_time: 0.0256 memory: 22701 grad_norm: 5.0548 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9464 loss: 0.9464 2022/09/06 00:06:29 - mmengine - INFO - Epoch(train) [68][200/940] lr: 1.0000e-03 eta: 7:03:21 time: 0.6973 data_time: 0.0234 memory: 22701 grad_norm: 5.1280 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0331 loss: 1.0331 2022/09/06 00:06:47 - mmengine - INFO - Epoch(train) [68][220/940] lr: 1.0000e-03 eta: 7:03:05 time: 0.9016 data_time: 0.0393 memory: 22701 grad_norm: 5.0723 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0442 loss: 1.0442 2022/09/06 00:07:03 - mmengine - INFO - Epoch(train) [68][240/940] lr: 1.0000e-03 eta: 7:02:48 time: 0.8079 data_time: 0.0284 memory: 22701 grad_norm: 5.1147 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9658 loss: 0.9658 2022/09/06 00:07:20 - mmengine - INFO - Epoch(train) [68][260/940] lr: 1.0000e-03 eta: 7:02:32 time: 0.8172 data_time: 0.0312 memory: 22701 grad_norm: 5.1230 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.0052 loss: 1.0052 2022/09/06 00:07:35 - mmengine - INFO - Epoch(train) [68][280/940] lr: 1.0000e-03 eta: 7:02:14 time: 0.7386 data_time: 0.0255 memory: 22701 grad_norm: 5.1009 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0434 loss: 1.0434 2022/09/06 00:07:54 - mmengine - INFO - Epoch(train) [68][300/940] lr: 1.0000e-03 eta: 7:01:59 time: 0.9938 data_time: 0.0260 memory: 22701 grad_norm: 5.0915 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0660 loss: 1.0660 2022/09/06 00:08:11 - mmengine - INFO - Epoch(train) [68][320/940] lr: 1.0000e-03 eta: 7:01:43 time: 0.8059 data_time: 0.0257 memory: 22701 grad_norm: 5.1508 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0275 loss: 1.0275 2022/09/06 00:08:29 - mmengine - INFO - Epoch(train) [68][340/940] lr: 1.0000e-03 eta: 7:01:27 time: 0.9276 data_time: 0.0268 memory: 22701 grad_norm: 5.1358 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0555 loss: 1.0555 2022/09/06 00:08:44 - mmengine - INFO - Epoch(train) [68][360/940] lr: 1.0000e-03 eta: 7:01:10 time: 0.7180 data_time: 0.0272 memory: 22701 grad_norm: 5.1873 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0763 loss: 1.0763 2022/09/06 00:09:02 - mmengine - INFO - Epoch(train) [68][380/940] lr: 1.0000e-03 eta: 7:00:54 time: 0.8947 data_time: 0.0243 memory: 22701 grad_norm: 5.2035 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0494 loss: 1.0494 2022/09/06 00:09:15 - mmengine - INFO - Epoch(train) [68][400/940] lr: 1.0000e-03 eta: 7:00:36 time: 0.7003 data_time: 0.0322 memory: 22701 grad_norm: 5.0813 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9719 loss: 0.9719 2022/09/06 00:09:31 - mmengine - INFO - Epoch(train) [68][420/940] lr: 1.0000e-03 eta: 7:00:20 time: 0.7924 data_time: 0.0280 memory: 22701 grad_norm: 5.1213 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1252 loss: 1.1252 2022/09/06 00:09:45 - mmengine - INFO - Epoch(train) [68][440/940] lr: 1.0000e-03 eta: 7:00:02 time: 0.6758 data_time: 0.0285 memory: 22701 grad_norm: 5.1911 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.9898 loss: 0.9898 2022/09/06 00:10:01 - mmengine - INFO - Epoch(train) [68][460/940] lr: 1.0000e-03 eta: 6:59:45 time: 0.8270 data_time: 0.0292 memory: 22701 grad_norm: 5.0434 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9886 loss: 0.9886 2022/09/06 00:10:15 - mmengine - INFO - Epoch(train) [68][480/940] lr: 1.0000e-03 eta: 6:59:27 time: 0.6606 data_time: 0.0271 memory: 22701 grad_norm: 5.1658 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0861 loss: 1.0861 2022/09/06 00:10:30 - mmengine - INFO - Epoch(train) [68][500/940] lr: 1.0000e-03 eta: 6:59:10 time: 0.7526 data_time: 0.0276 memory: 22701 grad_norm: 5.1780 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0110 loss: 1.0110 2022/09/06 00:10:44 - mmengine - INFO - Epoch(train) [68][520/940] lr: 1.0000e-03 eta: 6:58:53 time: 0.7352 data_time: 0.0364 memory: 22701 grad_norm: 5.0836 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9899 loss: 0.9899 2022/09/06 00:11:00 - mmengine - INFO - Epoch(train) [68][540/940] lr: 1.0000e-03 eta: 6:58:36 time: 0.7634 data_time: 0.0261 memory: 22701 grad_norm: 5.1091 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0418 loss: 1.0418 2022/09/06 00:11:13 - mmengine - INFO - Epoch(train) [68][560/940] lr: 1.0000e-03 eta: 6:58:18 time: 0.6841 data_time: 0.0317 memory: 22701 grad_norm: 5.0625 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9744 loss: 0.9744 2022/09/06 00:11:29 - mmengine - INFO - Epoch(train) [68][580/940] lr: 1.0000e-03 eta: 6:58:01 time: 0.7900 data_time: 0.0266 memory: 22701 grad_norm: 5.1881 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1195 loss: 1.1195 2022/09/06 00:11:44 - mmengine - INFO - Epoch(train) [68][600/940] lr: 1.0000e-03 eta: 6:57:44 time: 0.7404 data_time: 0.0370 memory: 22701 grad_norm: 5.2412 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0581 loss: 1.0581 2022/09/06 00:12:02 - mmengine - INFO - Epoch(train) [68][620/940] lr: 1.0000e-03 eta: 6:57:28 time: 0.9102 data_time: 0.0254 memory: 22701 grad_norm: 5.1261 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0208 loss: 1.0208 2022/09/06 00:12:16 - mmengine - INFO - Epoch(train) [68][640/940] lr: 1.0000e-03 eta: 6:57:10 time: 0.7077 data_time: 0.0284 memory: 22701 grad_norm: 5.1267 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0877 loss: 1.0877 2022/09/06 00:12:37 - mmengine - INFO - Epoch(train) [68][660/940] lr: 1.0000e-03 eta: 6:56:56 time: 1.0382 data_time: 0.1977 memory: 22701 grad_norm: 5.1757 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9652 loss: 0.9652 2022/09/06 00:12:53 - mmengine - INFO - Epoch(train) [68][680/940] lr: 1.0000e-03 eta: 6:56:39 time: 0.7866 data_time: 0.0903 memory: 22701 grad_norm: 5.1082 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1108 loss: 1.1108 2022/09/06 00:13:08 - mmengine - INFO - Epoch(train) [68][700/940] lr: 1.0000e-03 eta: 6:56:22 time: 0.7785 data_time: 0.2077 memory: 22701 grad_norm: 5.3128 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9203 loss: 0.9203 2022/09/06 00:13:26 - mmengine - INFO - Epoch(train) [68][720/940] lr: 1.0000e-03 eta: 6:56:06 time: 0.8701 data_time: 0.0915 memory: 22701 grad_norm: 5.1129 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0508 loss: 1.0508 2022/09/06 00:13:41 - mmengine - INFO - Epoch(train) [68][740/940] lr: 1.0000e-03 eta: 6:55:49 time: 0.7738 data_time: 0.0286 memory: 22701 grad_norm: 5.1863 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0730 loss: 1.0730 2022/09/06 00:13:57 - mmengine - INFO - Epoch(train) [68][760/940] lr: 1.0000e-03 eta: 6:55:32 time: 0.7735 data_time: 0.0230 memory: 22701 grad_norm: 5.1817 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.0723 loss: 1.0723 2022/09/06 00:14:11 - mmengine - INFO - Epoch(train) [68][780/940] lr: 1.0000e-03 eta: 6:55:15 time: 0.7239 data_time: 0.0298 memory: 22701 grad_norm: 5.0900 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0286 loss: 1.0286 2022/09/06 00:14:27 - mmengine - INFO - Epoch(train) [68][800/940] lr: 1.0000e-03 eta: 6:54:58 time: 0.8071 data_time: 0.0272 memory: 22701 grad_norm: 5.1904 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0732 loss: 1.0732 2022/09/06 00:14:43 - mmengine - INFO - Epoch(train) [68][820/940] lr: 1.0000e-03 eta: 6:54:41 time: 0.7819 data_time: 0.0418 memory: 22701 grad_norm: 5.0399 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9726 loss: 0.9726 2022/09/06 00:15:01 - mmengine - INFO - Epoch(train) [68][840/940] lr: 1.0000e-03 eta: 6:54:26 time: 0.9183 data_time: 0.0248 memory: 22701 grad_norm: 5.1435 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2005 loss: 1.2005 2022/09/06 00:15:19 - mmengine - INFO - Epoch(train) [68][860/940] lr: 1.0000e-03 eta: 6:54:10 time: 0.8932 data_time: 0.0433 memory: 22701 grad_norm: 5.2146 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 0.9902 loss: 0.9902 2022/09/06 00:15:33 - mmengine - INFO - Epoch(train) [68][880/940] lr: 1.0000e-03 eta: 6:53:52 time: 0.6897 data_time: 0.0300 memory: 22701 grad_norm: 5.1327 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0124 loss: 1.0124 2022/09/06 00:15:56 - mmengine - INFO - Epoch(train) [68][900/940] lr: 1.0000e-03 eta: 6:53:39 time: 1.1379 data_time: 0.0313 memory: 22701 grad_norm: 5.0911 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9970 loss: 0.9970 2022/09/06 00:16:13 - mmengine - INFO - Epoch(train) [68][920/940] lr: 1.0000e-03 eta: 6:53:22 time: 0.8522 data_time: 0.0456 memory: 22701 grad_norm: 5.0677 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0353 loss: 1.0353 2022/09/06 00:16:30 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:16:30 - mmengine - INFO - Epoch(train) [68][940/940] lr: 1.0000e-03 eta: 6:53:06 time: 0.8496 data_time: 0.0244 memory: 22701 grad_norm: 5.5349 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.0875 loss: 1.0875 2022/09/06 00:16:44 - mmengine - INFO - Epoch(val) [68][20/78] eta: 0:00:40 time: 0.6925 data_time: 0.5703 memory: 2247 2022/09/06 00:16:53 - mmengine - INFO - Epoch(val) [68][40/78] eta: 0:00:16 time: 0.4390 data_time: 0.3202 memory: 2247 2022/09/06 00:17:05 - mmengine - INFO - Epoch(val) [68][60/78] eta: 0:00:11 time: 0.6413 data_time: 0.5205 memory: 2247 2022/09/06 00:17:16 - mmengine - INFO - Epoch(val) [68][78/78] acc/top1: 0.6873 acc/top5: 0.8801 acc/mean1: 0.6872 2022/09/06 00:17:39 - mmengine - INFO - Epoch(train) [69][20/940] lr: 1.0000e-03 eta: 6:52:53 time: 1.1445 data_time: 0.4954 memory: 22701 grad_norm: 5.1714 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0707 loss: 1.0707 2022/09/06 00:17:54 - mmengine - INFO - Epoch(train) [69][40/940] lr: 1.0000e-03 eta: 6:52:36 time: 0.7475 data_time: 0.0661 memory: 22701 grad_norm: 5.1070 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 0.9958 loss: 0.9958 2022/09/06 00:18:10 - mmengine - INFO - Epoch(train) [69][60/940] lr: 1.0000e-03 eta: 6:52:19 time: 0.8319 data_time: 0.1537 memory: 22701 grad_norm: 5.1505 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0508 loss: 1.0508 2022/09/06 00:18:25 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:18:25 - mmengine - INFO - Epoch(train) [69][80/940] lr: 1.0000e-03 eta: 6:52:02 time: 0.7147 data_time: 0.1733 memory: 22701 grad_norm: 4.9765 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9695 loss: 0.9695 2022/09/06 00:18:41 - mmengine - INFO - Epoch(train) [69][100/940] lr: 1.0000e-03 eta: 6:51:45 time: 0.8366 data_time: 0.1769 memory: 22701 grad_norm: 5.2347 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0975 loss: 1.0975 2022/09/06 00:18:56 - mmengine - INFO - Epoch(train) [69][120/940] lr: 1.0000e-03 eta: 6:51:28 time: 0.7227 data_time: 0.2612 memory: 22701 grad_norm: 5.0309 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9866 loss: 0.9866 2022/09/06 00:19:13 - mmengine - INFO - Epoch(train) [69][140/940] lr: 1.0000e-03 eta: 6:51:12 time: 0.8643 data_time: 0.3086 memory: 22701 grad_norm: 5.0901 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0384 loss: 1.0384 2022/09/06 00:19:27 - mmengine - INFO - Epoch(train) [69][160/940] lr: 1.0000e-03 eta: 6:50:54 time: 0.6916 data_time: 0.2290 memory: 22701 grad_norm: 5.1306 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9438 loss: 0.9438 2022/09/06 00:19:44 - mmengine - INFO - Epoch(train) [69][180/940] lr: 1.0000e-03 eta: 6:50:38 time: 0.8459 data_time: 0.2616 memory: 22701 grad_norm: 5.1137 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1533 loss: 1.1533 2022/09/06 00:19:58 - mmengine - INFO - Epoch(train) [69][200/940] lr: 1.0000e-03 eta: 6:50:20 time: 0.7008 data_time: 0.2158 memory: 22701 grad_norm: 5.2243 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0838 loss: 1.0838 2022/09/06 00:20:17 - mmengine - INFO - Epoch(train) [69][220/940] lr: 1.0000e-03 eta: 6:50:05 time: 0.9678 data_time: 0.3374 memory: 22701 grad_norm: 5.0258 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1418 loss: 1.1418 2022/09/06 00:20:33 - mmengine - INFO - Epoch(train) [69][240/940] lr: 1.0000e-03 eta: 6:49:48 time: 0.7678 data_time: 0.0350 memory: 22701 grad_norm: 5.1368 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9759 loss: 0.9759 2022/09/06 00:20:50 - mmengine - INFO - Epoch(train) [69][260/940] lr: 1.0000e-03 eta: 6:49:32 time: 0.8895 data_time: 0.0388 memory: 22701 grad_norm: 5.1109 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0643 loss: 1.0643 2022/09/06 00:21:04 - mmengine - INFO - Epoch(train) [69][280/940] lr: 1.0000e-03 eta: 6:49:14 time: 0.6841 data_time: 0.0394 memory: 22701 grad_norm: 5.0202 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8954 loss: 0.8954 2022/09/06 00:21:21 - mmengine - INFO - Epoch(train) [69][300/940] lr: 1.0000e-03 eta: 6:48:58 time: 0.8351 data_time: 0.0426 memory: 22701 grad_norm: 5.0662 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1003 loss: 1.1003 2022/09/06 00:21:35 - mmengine - INFO - Epoch(train) [69][320/940] lr: 1.0000e-03 eta: 6:48:40 time: 0.7062 data_time: 0.0265 memory: 22701 grad_norm: 5.1387 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0277 loss: 1.0277 2022/09/06 00:21:52 - mmengine - INFO - Epoch(train) [69][340/940] lr: 1.0000e-03 eta: 6:48:24 time: 0.8317 data_time: 0.0281 memory: 22701 grad_norm: 5.1470 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0110 loss: 1.0110 2022/09/06 00:22:06 - mmengine - INFO - Epoch(train) [69][360/940] lr: 1.0000e-03 eta: 6:48:07 time: 0.7232 data_time: 0.0353 memory: 22701 grad_norm: 5.0248 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0199 loss: 1.0199 2022/09/06 00:22:22 - mmengine - INFO - Epoch(train) [69][380/940] lr: 1.0000e-03 eta: 6:47:50 time: 0.8226 data_time: 0.0367 memory: 22701 grad_norm: 5.2180 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 0.9554 loss: 0.9554 2022/09/06 00:22:37 - mmengine - INFO - Epoch(train) [69][400/940] lr: 1.0000e-03 eta: 6:47:33 time: 0.7420 data_time: 0.0284 memory: 22701 grad_norm: 5.1066 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9984 loss: 0.9984 2022/09/06 00:22:53 - mmengine - INFO - Epoch(train) [69][420/940] lr: 1.0000e-03 eta: 6:47:16 time: 0.7836 data_time: 0.0284 memory: 22701 grad_norm: 5.1002 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0506 loss: 1.0506 2022/09/06 00:23:08 - mmengine - INFO - Epoch(train) [69][440/940] lr: 1.0000e-03 eta: 6:46:59 time: 0.7404 data_time: 0.0236 memory: 22701 grad_norm: 5.2681 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0589 loss: 1.0589 2022/09/06 00:23:22 - mmengine - INFO - Epoch(train) [69][460/940] lr: 1.0000e-03 eta: 6:46:41 time: 0.7219 data_time: 0.0294 memory: 22701 grad_norm: 5.1273 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.9830 loss: 0.9830 2022/09/06 00:23:37 - mmengine - INFO - Epoch(train) [69][480/940] lr: 1.0000e-03 eta: 6:46:24 time: 0.7492 data_time: 0.0230 memory: 22701 grad_norm: 5.1528 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.0274 loss: 1.0274 2022/09/06 00:23:52 - mmengine - INFO - Epoch(train) [69][500/940] lr: 1.0000e-03 eta: 6:46:07 time: 0.7574 data_time: 0.0296 memory: 22701 grad_norm: 5.1497 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0269 loss: 1.0269 2022/09/06 00:24:10 - mmengine - INFO - Epoch(train) [69][520/940] lr: 1.0000e-03 eta: 6:45:51 time: 0.8832 data_time: 0.0202 memory: 22701 grad_norm: 5.1339 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0026 loss: 1.0026 2022/09/06 00:24:24 - mmengine - INFO - Epoch(train) [69][540/940] lr: 1.0000e-03 eta: 6:45:33 time: 0.6809 data_time: 0.0233 memory: 22701 grad_norm: 5.2010 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0851 loss: 1.0851 2022/09/06 00:24:42 - mmengine - INFO - Epoch(train) [69][560/940] lr: 1.0000e-03 eta: 6:45:18 time: 0.9111 data_time: 0.0226 memory: 22701 grad_norm: 5.1632 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1026 loss: 1.1026 2022/09/06 00:24:58 - mmengine - INFO - Epoch(train) [69][580/940] lr: 1.0000e-03 eta: 6:45:01 time: 0.8134 data_time: 0.0377 memory: 22701 grad_norm: 5.1250 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9845 loss: 0.9845 2022/09/06 00:25:16 - mmengine - INFO - Epoch(train) [69][600/940] lr: 1.0000e-03 eta: 6:44:45 time: 0.9018 data_time: 0.1005 memory: 22701 grad_norm: 5.1819 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0592 loss: 1.0592 2022/09/06 00:25:32 - mmengine - INFO - Epoch(train) [69][620/940] lr: 1.0000e-03 eta: 6:44:28 time: 0.7680 data_time: 0.0301 memory: 22701 grad_norm: 5.2155 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0285 loss: 1.0285 2022/09/06 00:25:49 - mmengine - INFO - Epoch(train) [69][640/940] lr: 1.0000e-03 eta: 6:44:12 time: 0.8508 data_time: 0.0231 memory: 22701 grad_norm: 5.0279 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9366 loss: 0.9366 2022/09/06 00:26:03 - mmengine - INFO - Epoch(train) [69][660/940] lr: 1.0000e-03 eta: 6:43:55 time: 0.7267 data_time: 0.0345 memory: 22701 grad_norm: 5.1306 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0282 loss: 1.0282 2022/09/06 00:26:20 - mmengine - INFO - Epoch(train) [69][680/940] lr: 1.0000e-03 eta: 6:43:39 time: 0.8597 data_time: 0.0290 memory: 22701 grad_norm: 5.2141 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1211 loss: 1.1211 2022/09/06 00:26:36 - mmengine - INFO - Epoch(train) [69][700/940] lr: 1.0000e-03 eta: 6:43:22 time: 0.7748 data_time: 0.0280 memory: 22701 grad_norm: 5.1249 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1592 loss: 1.1592 2022/09/06 00:26:52 - mmengine - INFO - Epoch(train) [69][720/940] lr: 1.0000e-03 eta: 6:43:05 time: 0.7887 data_time: 0.0262 memory: 22701 grad_norm: 5.1164 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9425 loss: 0.9425 2022/09/06 00:27:11 - mmengine - INFO - Epoch(train) [69][740/940] lr: 1.0000e-03 eta: 6:42:50 time: 0.9544 data_time: 0.0210 memory: 22701 grad_norm: 5.2440 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0867 loss: 1.0867 2022/09/06 00:27:25 - mmengine - INFO - Epoch(train) [69][760/940] lr: 1.0000e-03 eta: 6:42:32 time: 0.7018 data_time: 0.0283 memory: 22701 grad_norm: 5.1166 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0992 loss: 1.0992 2022/09/06 00:27:41 - mmengine - INFO - Epoch(train) [69][780/940] lr: 1.0000e-03 eta: 6:42:15 time: 0.7881 data_time: 0.0246 memory: 22701 grad_norm: 5.2753 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0673 loss: 1.0673 2022/09/06 00:27:55 - mmengine - INFO - Epoch(train) [69][800/940] lr: 1.0000e-03 eta: 6:41:58 time: 0.7417 data_time: 0.0253 memory: 22701 grad_norm: 5.2449 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0539 loss: 1.0539 2022/09/06 00:28:14 - mmengine - INFO - Epoch(train) [69][820/940] lr: 1.0000e-03 eta: 6:41:42 time: 0.9138 data_time: 0.0246 memory: 22701 grad_norm: 5.2407 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0247 loss: 1.0247 2022/09/06 00:28:30 - mmengine - INFO - Epoch(train) [69][840/940] lr: 1.0000e-03 eta: 6:41:26 time: 0.7933 data_time: 0.0263 memory: 22701 grad_norm: 5.1730 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.0440 loss: 1.0440 2022/09/06 00:28:46 - mmengine - INFO - Epoch(train) [69][860/940] lr: 1.0000e-03 eta: 6:41:09 time: 0.8402 data_time: 0.0337 memory: 22701 grad_norm: 5.2124 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1600 loss: 1.1600 2022/09/06 00:29:01 - mmengine - INFO - Epoch(train) [69][880/940] lr: 1.0000e-03 eta: 6:40:52 time: 0.7182 data_time: 0.0286 memory: 22701 grad_norm: 5.0540 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9674 loss: 0.9674 2022/09/06 00:29:18 - mmengine - INFO - Epoch(train) [69][900/940] lr: 1.0000e-03 eta: 6:40:36 time: 0.8758 data_time: 0.0309 memory: 22701 grad_norm: 5.2252 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.9888 loss: 0.9888 2022/09/06 00:29:33 - mmengine - INFO - Epoch(train) [69][920/940] lr: 1.0000e-03 eta: 6:40:19 time: 0.7632 data_time: 0.0282 memory: 22701 grad_norm: 5.1914 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9537 loss: 0.9537 2022/09/06 00:29:47 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:29:47 - mmengine - INFO - Epoch(train) [69][940/940] lr: 1.0000e-03 eta: 6:40:01 time: 0.6569 data_time: 0.0239 memory: 22701 grad_norm: 5.6534 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.0478 loss: 1.0478 2022/09/06 00:29:47 - mmengine - INFO - Saving checkpoint at 69 epochs 2022/09/06 00:30:03 - mmengine - INFO - Epoch(val) [69][20/78] eta: 0:00:40 time: 0.6986 data_time: 0.5794 memory: 2247 2022/09/06 00:30:12 - mmengine - INFO - Epoch(val) [69][40/78] eta: 0:00:16 time: 0.4469 data_time: 0.3303 memory: 2247 2022/09/06 00:30:25 - mmengine - INFO - Epoch(val) [69][60/78] eta: 0:00:11 time: 0.6611 data_time: 0.5443 memory: 2247 2022/09/06 00:30:34 - mmengine - INFO - Epoch(val) [69][78/78] acc/top1: 0.6858 acc/top5: 0.8816 acc/mean1: 0.6857 2022/09/06 00:30:54 - mmengine - INFO - Epoch(train) [70][20/940] lr: 1.0000e-03 eta: 6:39:46 time: 0.9944 data_time: 0.3354 memory: 22701 grad_norm: 5.1247 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0809 loss: 1.0809 2022/09/06 00:31:08 - mmengine - INFO - Epoch(train) [70][40/940] lr: 1.0000e-03 eta: 6:39:28 time: 0.6782 data_time: 0.0338 memory: 22701 grad_norm: 5.1856 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0470 loss: 1.0470 2022/09/06 00:31:24 - mmengine - INFO - Epoch(train) [70][60/940] lr: 1.0000e-03 eta: 6:39:11 time: 0.8079 data_time: 0.0326 memory: 22701 grad_norm: 5.2787 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0449 loss: 1.0449 2022/09/06 00:31:38 - mmengine - INFO - Epoch(train) [70][80/940] lr: 1.0000e-03 eta: 6:38:54 time: 0.6892 data_time: 0.0267 memory: 22701 grad_norm: 5.1606 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0731 loss: 1.0731 2022/09/06 00:31:53 - mmengine - INFO - Epoch(train) [70][100/940] lr: 1.0000e-03 eta: 6:38:37 time: 0.7813 data_time: 0.0339 memory: 22701 grad_norm: 5.1358 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9565 loss: 0.9565 2022/09/06 00:32:06 - mmengine - INFO - Epoch(train) [70][120/940] lr: 1.0000e-03 eta: 6:38:19 time: 0.6483 data_time: 0.0283 memory: 22701 grad_norm: 5.1968 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9947 loss: 0.9947 2022/09/06 00:32:26 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:32:26 - mmengine - INFO - Epoch(train) [70][140/940] lr: 1.0000e-03 eta: 6:38:04 time: 1.0063 data_time: 0.0465 memory: 22701 grad_norm: 5.1366 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0494 loss: 1.0494 2022/09/06 00:32:43 - mmengine - INFO - Epoch(train) [70][160/940] lr: 1.0000e-03 eta: 6:37:48 time: 0.8123 data_time: 0.0239 memory: 22701 grad_norm: 5.2327 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 0.9133 loss: 0.9133 2022/09/06 00:33:00 - mmengine - INFO - Epoch(train) [70][180/940] lr: 1.0000e-03 eta: 6:37:32 time: 0.8748 data_time: 0.0333 memory: 22701 grad_norm: 5.2160 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.1038 loss: 1.1038 2022/09/06 00:33:16 - mmengine - INFO - Epoch(train) [70][200/940] lr: 1.0000e-03 eta: 6:37:15 time: 0.7908 data_time: 0.0273 memory: 22701 grad_norm: 5.1219 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9509 loss: 0.9509 2022/09/06 00:33:34 - mmengine - INFO - Epoch(train) [70][220/940] lr: 1.0000e-03 eta: 6:36:59 time: 0.8882 data_time: 0.0241 memory: 22701 grad_norm: 5.1295 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 0.8961 loss: 0.8961 2022/09/06 00:33:48 - mmengine - INFO - Epoch(train) [70][240/940] lr: 1.0000e-03 eta: 6:36:41 time: 0.7200 data_time: 0.0365 memory: 22701 grad_norm: 5.0813 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9690 loss: 0.9690 2022/09/06 00:34:09 - mmengine - INFO - Epoch(train) [70][260/940] lr: 1.0000e-03 eta: 6:36:27 time: 1.0453 data_time: 0.0623 memory: 22701 grad_norm: 5.2260 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9603 loss: 0.9603 2022/09/06 00:34:26 - mmengine - INFO - Epoch(train) [70][280/940] lr: 1.0000e-03 eta: 6:36:11 time: 0.8276 data_time: 0.0796 memory: 22701 grad_norm: 5.0538 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9387 loss: 0.9387 2022/09/06 00:34:43 - mmengine - INFO - Epoch(train) [70][300/940] lr: 1.0000e-03 eta: 6:35:54 time: 0.8398 data_time: 0.0310 memory: 22701 grad_norm: 5.2019 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0467 loss: 1.0467 2022/09/06 00:34:56 - mmengine - INFO - Epoch(train) [70][320/940] lr: 1.0000e-03 eta: 6:35:37 time: 0.7024 data_time: 0.0342 memory: 22701 grad_norm: 5.1712 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9743 loss: 0.9743 2022/09/06 00:35:12 - mmengine - INFO - Epoch(train) [70][340/940] lr: 1.0000e-03 eta: 6:35:20 time: 0.7888 data_time: 0.0287 memory: 22701 grad_norm: 5.1997 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9086 loss: 0.9086 2022/09/06 00:35:27 - mmengine - INFO - Epoch(train) [70][360/940] lr: 1.0000e-03 eta: 6:35:02 time: 0.7145 data_time: 0.0295 memory: 22701 grad_norm: 5.2690 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.0370 loss: 1.0370 2022/09/06 00:35:43 - mmengine - INFO - Epoch(train) [70][380/940] lr: 1.0000e-03 eta: 6:34:46 time: 0.8183 data_time: 0.0256 memory: 22701 grad_norm: 5.1611 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9287 loss: 0.9287 2022/09/06 00:35:58 - mmengine - INFO - Epoch(train) [70][400/940] lr: 1.0000e-03 eta: 6:34:29 time: 0.7317 data_time: 0.0370 memory: 22701 grad_norm: 5.1931 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0488 loss: 1.0488 2022/09/06 00:36:14 - mmengine - INFO - Epoch(train) [70][420/940] lr: 1.0000e-03 eta: 6:34:12 time: 0.8312 data_time: 0.0343 memory: 22701 grad_norm: 5.1989 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9982 loss: 0.9982 2022/09/06 00:36:28 - mmengine - INFO - Epoch(train) [70][440/940] lr: 1.0000e-03 eta: 6:33:54 time: 0.6658 data_time: 0.0270 memory: 22701 grad_norm: 5.1993 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.8878 loss: 0.8878 2022/09/06 00:36:46 - mmengine - INFO - Epoch(train) [70][460/940] lr: 1.0000e-03 eta: 6:33:39 time: 0.9282 data_time: 0.0306 memory: 22701 grad_norm: 5.1253 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0318 loss: 1.0318 2022/09/06 00:37:01 - mmengine - INFO - Epoch(train) [70][480/940] lr: 1.0000e-03 eta: 6:33:22 time: 0.7417 data_time: 0.0236 memory: 22701 grad_norm: 5.1218 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1044 loss: 1.1044 2022/09/06 00:37:18 - mmengine - INFO - Epoch(train) [70][500/940] lr: 1.0000e-03 eta: 6:33:05 time: 0.8429 data_time: 0.0274 memory: 22701 grad_norm: 5.2920 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1267 loss: 1.1267 2022/09/06 00:37:33 - mmengine - INFO - Epoch(train) [70][520/940] lr: 1.0000e-03 eta: 6:32:48 time: 0.7705 data_time: 0.0268 memory: 22701 grad_norm: 5.1212 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0826 loss: 1.0826 2022/09/06 00:37:52 - mmengine - INFO - Epoch(train) [70][540/940] lr: 1.0000e-03 eta: 6:32:33 time: 0.9421 data_time: 0.0215 memory: 22701 grad_norm: 5.2005 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.0085 loss: 1.0085 2022/09/06 00:38:06 - mmengine - INFO - Epoch(train) [70][560/940] lr: 1.0000e-03 eta: 6:32:15 time: 0.7009 data_time: 0.0243 memory: 22701 grad_norm: 5.2646 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0207 loss: 1.0207 2022/09/06 00:38:23 - mmengine - INFO - Epoch(train) [70][580/940] lr: 1.0000e-03 eta: 6:31:59 time: 0.8515 data_time: 0.0299 memory: 22701 grad_norm: 5.1439 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0141 loss: 1.0141 2022/09/06 00:38:39 - mmengine - INFO - Epoch(train) [70][600/940] lr: 1.0000e-03 eta: 6:31:42 time: 0.7842 data_time: 0.0289 memory: 22701 grad_norm: 5.2478 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0134 loss: 1.0134 2022/09/06 00:38:54 - mmengine - INFO - Epoch(train) [70][620/940] lr: 1.0000e-03 eta: 6:31:25 time: 0.7399 data_time: 0.0299 memory: 22701 grad_norm: 5.0669 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0272 loss: 1.0272 2022/09/06 00:39:09 - mmengine - INFO - Epoch(train) [70][640/940] lr: 1.0000e-03 eta: 6:31:08 time: 0.7766 data_time: 0.0313 memory: 22701 grad_norm: 5.1313 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9482 loss: 0.9482 2022/09/06 00:39:25 - mmengine - INFO - Epoch(train) [70][660/940] lr: 1.0000e-03 eta: 6:30:51 time: 0.7713 data_time: 0.0293 memory: 22701 grad_norm: 5.2907 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1512 loss: 1.1512 2022/09/06 00:39:40 - mmengine - INFO - Epoch(train) [70][680/940] lr: 1.0000e-03 eta: 6:30:34 time: 0.7763 data_time: 0.0296 memory: 22701 grad_norm: 5.1167 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0580 loss: 1.0580 2022/09/06 00:39:55 - mmengine - INFO - Epoch(train) [70][700/940] lr: 1.0000e-03 eta: 6:30:17 time: 0.7546 data_time: 0.0355 memory: 22701 grad_norm: 5.1412 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.9559 loss: 0.9559 2022/09/06 00:40:11 - mmengine - INFO - Epoch(train) [70][720/940] lr: 1.0000e-03 eta: 6:30:01 time: 0.7766 data_time: 0.0344 memory: 22701 grad_norm: 5.2829 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0681 loss: 1.0681 2022/09/06 00:40:26 - mmengine - INFO - Epoch(train) [70][740/940] lr: 1.0000e-03 eta: 6:29:43 time: 0.7412 data_time: 0.0266 memory: 22701 grad_norm: 5.2082 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0582 loss: 1.0582 2022/09/06 00:40:44 - mmengine - INFO - Epoch(train) [70][760/940] lr: 1.0000e-03 eta: 6:29:28 time: 0.9449 data_time: 0.0346 memory: 22701 grad_norm: 5.1700 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9040 loss: 0.9040 2022/09/06 00:41:00 - mmengine - INFO - Epoch(train) [70][780/940] lr: 1.0000e-03 eta: 6:29:11 time: 0.7703 data_time: 0.0308 memory: 22701 grad_norm: 5.1048 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0373 loss: 1.0373 2022/09/06 00:41:18 - mmengine - INFO - Epoch(train) [70][800/940] lr: 1.0000e-03 eta: 6:28:55 time: 0.9034 data_time: 0.0260 memory: 22701 grad_norm: 5.0767 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0137 loss: 1.0137 2022/09/06 00:41:38 - mmengine - INFO - Epoch(train) [70][820/940] lr: 1.0000e-03 eta: 6:28:40 time: 0.9821 data_time: 0.0212 memory: 22701 grad_norm: 5.1694 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0062 loss: 1.0062 2022/09/06 00:41:55 - mmengine - INFO - Epoch(train) [70][840/940] lr: 1.0000e-03 eta: 6:28:24 time: 0.8656 data_time: 0.0251 memory: 22701 grad_norm: 5.1737 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0024 loss: 1.0024 2022/09/06 00:42:13 - mmengine - INFO - Epoch(train) [70][860/940] lr: 1.0000e-03 eta: 6:28:08 time: 0.8808 data_time: 0.0308 memory: 22701 grad_norm: 5.1735 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0897 loss: 1.0897 2022/09/06 00:42:29 - mmengine - INFO - Epoch(train) [70][880/940] lr: 1.0000e-03 eta: 6:27:52 time: 0.8164 data_time: 0.0277 memory: 22701 grad_norm: 5.1937 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.8927 loss: 0.8927 2022/09/06 00:42:46 - mmengine - INFO - Epoch(train) [70][900/940] lr: 1.0000e-03 eta: 6:27:35 time: 0.8553 data_time: 0.0219 memory: 22701 grad_norm: 5.3439 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0040 loss: 1.0040 2022/09/06 00:43:03 - mmengine - INFO - Epoch(train) [70][920/940] lr: 1.0000e-03 eta: 6:27:19 time: 0.8546 data_time: 0.0289 memory: 22701 grad_norm: 5.3015 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0844 loss: 1.0844 2022/09/06 00:43:17 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:43:17 - mmengine - INFO - Epoch(train) [70][940/940] lr: 1.0000e-03 eta: 6:27:02 time: 0.7054 data_time: 0.0234 memory: 22701 grad_norm: 5.5991 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.0691 loss: 1.0691 2022/09/06 00:43:31 - mmengine - INFO - Epoch(val) [70][20/78] eta: 0:00:40 time: 0.7057 data_time: 0.5846 memory: 2247 2022/09/06 00:43:40 - mmengine - INFO - Epoch(val) [70][40/78] eta: 0:00:17 time: 0.4514 data_time: 0.3305 memory: 2247 2022/09/06 00:43:54 - mmengine - INFO - Epoch(val) [70][60/78] eta: 0:00:12 time: 0.6694 data_time: 0.5486 memory: 2247 2022/09/06 00:44:04 - mmengine - INFO - Epoch(val) [70][78/78] acc/top1: 0.6843 acc/top5: 0.8794 acc/mean1: 0.6842 2022/09/06 00:44:24 - mmengine - INFO - Epoch(train) [71][20/940] lr: 1.0000e-03 eta: 6:26:47 time: 1.0298 data_time: 0.6378 memory: 22701 grad_norm: 5.1256 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0020 loss: 1.0020 2022/09/06 00:44:39 - mmengine - INFO - Epoch(train) [71][40/940] lr: 1.0000e-03 eta: 6:26:30 time: 0.7597 data_time: 0.3640 memory: 22701 grad_norm: 5.2823 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1680 loss: 1.1680 2022/09/06 00:44:54 - mmengine - INFO - Epoch(train) [71][60/940] lr: 1.0000e-03 eta: 6:26:13 time: 0.7481 data_time: 0.3560 memory: 22701 grad_norm: 5.1343 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.9648 loss: 0.9648 2022/09/06 00:45:08 - mmengine - INFO - Epoch(train) [71][80/940] lr: 1.0000e-03 eta: 6:25:55 time: 0.6593 data_time: 0.2660 memory: 22701 grad_norm: 5.2231 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0237 loss: 1.0237 2022/09/06 00:45:24 - mmengine - INFO - Epoch(train) [71][100/940] lr: 1.0000e-03 eta: 6:25:38 time: 0.8047 data_time: 0.3981 memory: 22701 grad_norm: 5.1632 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0788 loss: 1.0788 2022/09/06 00:45:37 - mmengine - INFO - Epoch(train) [71][120/940] lr: 1.0000e-03 eta: 6:25:21 time: 0.6739 data_time: 0.2801 memory: 22701 grad_norm: 5.0780 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1014 loss: 1.1014 2022/09/06 00:45:52 - mmengine - INFO - Epoch(train) [71][140/940] lr: 1.0000e-03 eta: 6:25:04 time: 0.7629 data_time: 0.3818 memory: 22701 grad_norm: 5.1997 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9111 loss: 0.9111 2022/09/06 00:46:06 - mmengine - INFO - Epoch(train) [71][160/940] lr: 1.0000e-03 eta: 6:24:46 time: 0.6882 data_time: 0.2209 memory: 22701 grad_norm: 5.1712 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9679 loss: 0.9679 2022/09/06 00:46:26 - mmengine - INFO - Epoch(train) [71][180/940] lr: 1.0000e-03 eta: 6:24:31 time: 0.9634 data_time: 0.2955 memory: 22701 grad_norm: 5.1598 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9313 loss: 0.9313 2022/09/06 00:46:39 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:46:39 - mmengine - INFO - Epoch(train) [71][200/940] lr: 1.0000e-03 eta: 6:24:13 time: 0.6978 data_time: 0.0216 memory: 22701 grad_norm: 5.1763 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0076 loss: 1.0076 2022/09/06 00:46:56 - mmengine - INFO - Epoch(train) [71][220/940] lr: 1.0000e-03 eta: 6:23:57 time: 0.8467 data_time: 0.1956 memory: 22701 grad_norm: 5.1574 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.0895 loss: 1.0895 2022/09/06 00:47:11 - mmengine - INFO - Epoch(train) [71][240/940] lr: 1.0000e-03 eta: 6:23:40 time: 0.7201 data_time: 0.1452 memory: 22701 grad_norm: 5.2985 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0630 loss: 1.0630 2022/09/06 00:47:26 - mmengine - INFO - Epoch(train) [71][260/940] lr: 1.0000e-03 eta: 6:23:23 time: 0.7768 data_time: 0.2500 memory: 22701 grad_norm: 5.0186 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9840 loss: 0.9840 2022/09/06 00:47:39 - mmengine - INFO - Epoch(train) [71][280/940] lr: 1.0000e-03 eta: 6:23:05 time: 0.6571 data_time: 0.2382 memory: 22701 grad_norm: 5.2250 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.0149 loss: 1.0149 2022/09/06 00:47:57 - mmengine - INFO - Epoch(train) [71][300/940] lr: 1.0000e-03 eta: 6:22:49 time: 0.8717 data_time: 0.3912 memory: 22701 grad_norm: 5.2218 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9882 loss: 0.9882 2022/09/06 00:48:13 - mmengine - INFO - Epoch(train) [71][320/940] lr: 1.0000e-03 eta: 6:22:32 time: 0.8119 data_time: 0.2944 memory: 22701 grad_norm: 5.1265 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9741 loss: 0.9741 2022/09/06 00:48:40 - mmengine - INFO - Epoch(train) [71][340/940] lr: 1.0000e-03 eta: 6:22:20 time: 1.3322 data_time: 0.1476 memory: 22701 grad_norm: 5.1394 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0050 loss: 1.0050 2022/09/06 00:48:57 - mmengine - INFO - Epoch(train) [71][360/940] lr: 1.0000e-03 eta: 6:22:04 time: 0.8694 data_time: 0.0254 memory: 22701 grad_norm: 5.1882 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9888 loss: 0.9888 2022/09/06 00:49:17 - mmengine - INFO - Epoch(train) [71][380/940] lr: 1.0000e-03 eta: 6:21:49 time: 0.9832 data_time: 0.0269 memory: 22701 grad_norm: 5.1843 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0627 loss: 1.0627 2022/09/06 00:49:34 - mmengine - INFO - Epoch(train) [71][400/940] lr: 1.0000e-03 eta: 6:21:33 time: 0.8757 data_time: 0.0287 memory: 22701 grad_norm: 5.3082 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9919 loss: 0.9919 2022/09/06 00:49:51 - mmengine - INFO - Epoch(train) [71][420/940] lr: 1.0000e-03 eta: 6:21:16 time: 0.8171 data_time: 0.0313 memory: 22701 grad_norm: 5.0997 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0308 loss: 1.0308 2022/09/06 00:50:06 - mmengine - INFO - Epoch(train) [71][440/940] lr: 1.0000e-03 eta: 6:20:59 time: 0.7430 data_time: 0.0245 memory: 22701 grad_norm: 5.1974 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0779 loss: 1.0779 2022/09/06 00:50:24 - mmengine - INFO - Epoch(train) [71][460/940] lr: 1.0000e-03 eta: 6:20:43 time: 0.8963 data_time: 0.0284 memory: 22701 grad_norm: 5.2328 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9858 loss: 0.9858 2022/09/06 00:50:36 - mmengine - INFO - Epoch(train) [71][480/940] lr: 1.0000e-03 eta: 6:20:25 time: 0.6300 data_time: 0.0246 memory: 22701 grad_norm: 5.0338 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0442 loss: 1.0442 2022/09/06 00:50:53 - mmengine - INFO - Epoch(train) [71][500/940] lr: 1.0000e-03 eta: 6:20:09 time: 0.8298 data_time: 0.0305 memory: 22701 grad_norm: 5.1036 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0750 loss: 1.0750 2022/09/06 00:51:06 - mmengine - INFO - Epoch(train) [71][520/940] lr: 1.0000e-03 eta: 6:19:51 time: 0.6836 data_time: 0.0219 memory: 22701 grad_norm: 5.1675 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.0629 loss: 1.0629 2022/09/06 00:51:25 - mmengine - INFO - Epoch(train) [71][540/940] lr: 1.0000e-03 eta: 6:19:36 time: 0.9375 data_time: 0.0190 memory: 22701 grad_norm: 5.1525 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.9246 loss: 0.9246 2022/09/06 00:51:40 - mmengine - INFO - Epoch(train) [71][560/940] lr: 1.0000e-03 eta: 6:19:18 time: 0.7403 data_time: 0.0232 memory: 22701 grad_norm: 5.2028 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0082 loss: 1.0082 2022/09/06 00:51:57 - mmengine - INFO - Epoch(train) [71][580/940] lr: 1.0000e-03 eta: 6:19:02 time: 0.8460 data_time: 0.0244 memory: 22701 grad_norm: 5.1040 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0880 loss: 1.0880 2022/09/06 00:52:11 - mmengine - INFO - Epoch(train) [71][600/940] lr: 1.0000e-03 eta: 6:18:45 time: 0.7002 data_time: 0.0254 memory: 22701 grad_norm: 5.2364 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9560 loss: 0.9560 2022/09/06 00:52:30 - mmengine - INFO - Epoch(train) [71][620/940] lr: 1.0000e-03 eta: 6:18:29 time: 0.9491 data_time: 0.0235 memory: 22701 grad_norm: 5.3846 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1306 loss: 1.1306 2022/09/06 00:52:45 - mmengine - INFO - Epoch(train) [71][640/940] lr: 1.0000e-03 eta: 6:18:12 time: 0.7616 data_time: 0.0272 memory: 22701 grad_norm: 5.2247 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0364 loss: 1.0364 2022/09/06 00:53:04 - mmengine - INFO - Epoch(train) [71][660/940] lr: 1.0000e-03 eta: 6:17:57 time: 0.9315 data_time: 0.0288 memory: 22701 grad_norm: 5.2349 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0793 loss: 1.0793 2022/09/06 00:53:18 - mmengine - INFO - Epoch(train) [71][680/940] lr: 1.0000e-03 eta: 6:17:39 time: 0.7245 data_time: 0.0274 memory: 22701 grad_norm: 5.2553 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1020 loss: 1.1020 2022/09/06 00:53:35 - mmengine - INFO - Epoch(train) [71][700/940] lr: 1.0000e-03 eta: 6:17:23 time: 0.8322 data_time: 0.0231 memory: 22701 grad_norm: 5.1870 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1110 loss: 1.1110 2022/09/06 00:53:51 - mmengine - INFO - Epoch(train) [71][720/940] lr: 1.0000e-03 eta: 6:17:06 time: 0.7949 data_time: 0.0250 memory: 22701 grad_norm: 5.1614 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9986 loss: 0.9986 2022/09/06 00:54:08 - mmengine - INFO - Epoch(train) [71][740/940] lr: 1.0000e-03 eta: 6:16:50 time: 0.8735 data_time: 0.0252 memory: 22701 grad_norm: 5.2319 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0473 loss: 1.0473 2022/09/06 00:54:24 - mmengine - INFO - Epoch(train) [71][760/940] lr: 1.0000e-03 eta: 6:16:34 time: 0.8096 data_time: 0.0225 memory: 22701 grad_norm: 5.3088 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0377 loss: 1.0377 2022/09/06 00:54:41 - mmengine - INFO - Epoch(train) [71][780/940] lr: 1.0000e-03 eta: 6:16:17 time: 0.8051 data_time: 0.0298 memory: 22701 grad_norm: 5.2484 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9966 loss: 0.9966 2022/09/06 00:54:55 - mmengine - INFO - Epoch(train) [71][800/940] lr: 1.0000e-03 eta: 6:16:00 time: 0.7395 data_time: 0.0234 memory: 22701 grad_norm: 5.1757 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9975 loss: 0.9975 2022/09/06 00:55:15 - mmengine - INFO - Epoch(train) [71][820/940] lr: 1.0000e-03 eta: 6:15:45 time: 0.9714 data_time: 0.0295 memory: 22701 grad_norm: 5.1595 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0794 loss: 1.0794 2022/09/06 00:55:30 - mmengine - INFO - Epoch(train) [71][840/940] lr: 1.0000e-03 eta: 6:15:28 time: 0.7540 data_time: 0.0280 memory: 22701 grad_norm: 5.0911 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0224 loss: 1.0224 2022/09/06 00:55:47 - mmengine - INFO - Epoch(train) [71][860/940] lr: 1.0000e-03 eta: 6:15:12 time: 0.8718 data_time: 0.0197 memory: 22701 grad_norm: 5.2187 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0850 loss: 1.0850 2022/09/06 00:56:02 - mmengine - INFO - Epoch(train) [71][880/940] lr: 1.0000e-03 eta: 6:14:54 time: 0.7088 data_time: 0.0310 memory: 22701 grad_norm: 5.1006 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8985 loss: 0.8985 2022/09/06 00:56:20 - mmengine - INFO - Epoch(train) [71][900/940] lr: 1.0000e-03 eta: 6:14:38 time: 0.9245 data_time: 0.0334 memory: 22701 grad_norm: 5.1472 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1405 loss: 1.1405 2022/09/06 00:56:36 - mmengine - INFO - Epoch(train) [71][920/940] lr: 1.0000e-03 eta: 6:14:22 time: 0.7898 data_time: 0.0281 memory: 22701 grad_norm: 5.2364 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0254 loss: 1.0254 2022/09/06 00:56:51 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 00:56:51 - mmengine - INFO - Epoch(train) [71][940/940] lr: 1.0000e-03 eta: 6:14:05 time: 0.7396 data_time: 0.0196 memory: 22701 grad_norm: 5.5450 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.0781 loss: 1.0781 2022/09/06 00:57:05 - mmengine - INFO - Epoch(val) [71][20/78] eta: 0:00:39 time: 0.6896 data_time: 0.5701 memory: 2247 2022/09/06 00:57:14 - mmengine - INFO - Epoch(val) [71][40/78] eta: 0:00:17 time: 0.4583 data_time: 0.3394 memory: 2247 2022/09/06 00:57:27 - mmengine - INFO - Epoch(val) [71][60/78] eta: 0:00:12 time: 0.6701 data_time: 0.5494 memory: 2247 2022/09/06 00:57:37 - mmengine - INFO - Epoch(val) [71][78/78] acc/top1: 0.6893 acc/top5: 0.8817 acc/mean1: 0.6892 2022/09/06 00:57:58 - mmengine - INFO - Epoch(train) [72][20/940] lr: 1.0000e-03 eta: 6:13:50 time: 1.0357 data_time: 0.4911 memory: 22701 grad_norm: 5.2767 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.0886 loss: 1.0886 2022/09/06 00:58:13 - mmengine - INFO - Epoch(train) [72][40/940] lr: 1.0000e-03 eta: 6:13:33 time: 0.7636 data_time: 0.1244 memory: 22701 grad_norm: 5.1698 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0686 loss: 1.0686 2022/09/06 00:58:31 - mmengine - INFO - Epoch(train) [72][60/940] lr: 1.0000e-03 eta: 6:13:17 time: 0.8990 data_time: 0.0268 memory: 22701 grad_norm: 5.1951 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0666 loss: 1.0666 2022/09/06 00:58:45 - mmengine - INFO - Epoch(train) [72][80/940] lr: 1.0000e-03 eta: 6:13:00 time: 0.7072 data_time: 0.0240 memory: 22701 grad_norm: 5.2436 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0903 loss: 1.0903 2022/09/06 00:59:01 - mmengine - INFO - Epoch(train) [72][100/940] lr: 1.0000e-03 eta: 6:12:43 time: 0.8058 data_time: 0.0257 memory: 22701 grad_norm: 5.1354 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9837 loss: 0.9837 2022/09/06 00:59:15 - mmengine - INFO - Epoch(train) [72][120/940] lr: 1.0000e-03 eta: 6:12:26 time: 0.6952 data_time: 0.0295 memory: 22701 grad_norm: 5.3501 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0670 loss: 1.0670 2022/09/06 00:59:33 - mmengine - INFO - Epoch(train) [72][140/940] lr: 1.0000e-03 eta: 6:12:10 time: 0.9017 data_time: 0.0323 memory: 22701 grad_norm: 5.2213 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0006 loss: 1.0006 2022/09/06 00:59:47 - mmengine - INFO - Epoch(train) [72][160/940] lr: 1.0000e-03 eta: 6:11:52 time: 0.6812 data_time: 0.0283 memory: 22701 grad_norm: 5.1091 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9938 loss: 0.9938 2022/09/06 01:00:07 - mmengine - INFO - Epoch(train) [72][180/940] lr: 1.0000e-03 eta: 6:11:37 time: 1.0299 data_time: 0.0253 memory: 22701 grad_norm: 5.2766 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0381 loss: 1.0381 2022/09/06 01:00:23 - mmengine - INFO - Epoch(train) [72][200/940] lr: 1.0000e-03 eta: 6:11:21 time: 0.7996 data_time: 0.0325 memory: 22701 grad_norm: 5.2326 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1283 loss: 1.1283 2022/09/06 01:00:43 - mmengine - INFO - Epoch(train) [72][220/940] lr: 1.0000e-03 eta: 6:11:05 time: 0.9819 data_time: 0.0245 memory: 22701 grad_norm: 5.3545 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1672 loss: 1.1672 2022/09/06 01:00:57 - mmengine - INFO - Epoch(train) [72][240/940] lr: 1.0000e-03 eta: 6:10:48 time: 0.7180 data_time: 0.0302 memory: 22701 grad_norm: 5.3013 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0481 loss: 1.0481 2022/09/06 01:01:16 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:01:16 - mmengine - INFO - Epoch(train) [72][260/940] lr: 1.0000e-03 eta: 6:10:32 time: 0.9121 data_time: 0.0230 memory: 22701 grad_norm: 5.1927 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0469 loss: 1.0469 2022/09/06 01:01:31 - mmengine - INFO - Epoch(train) [72][280/940] lr: 1.0000e-03 eta: 6:10:15 time: 0.7474 data_time: 0.0343 memory: 22701 grad_norm: 5.1231 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9360 loss: 0.9360 2022/09/06 01:01:50 - mmengine - INFO - Epoch(train) [72][300/940] lr: 1.0000e-03 eta: 6:10:00 time: 0.9564 data_time: 0.0232 memory: 22701 grad_norm: 5.2391 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0082 loss: 1.0082 2022/09/06 01:02:04 - mmengine - INFO - Epoch(train) [72][320/940] lr: 1.0000e-03 eta: 6:09:43 time: 0.7130 data_time: 0.0333 memory: 22701 grad_norm: 5.2623 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9933 loss: 0.9933 2022/09/06 01:02:23 - mmengine - INFO - Epoch(train) [72][340/940] lr: 1.0000e-03 eta: 6:09:27 time: 0.9394 data_time: 0.0239 memory: 22701 grad_norm: 5.1903 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0439 loss: 1.0439 2022/09/06 01:02:39 - mmengine - INFO - Epoch(train) [72][360/940] lr: 1.0000e-03 eta: 6:09:10 time: 0.7886 data_time: 0.0251 memory: 22701 grad_norm: 5.0979 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0768 loss: 1.0768 2022/09/06 01:02:58 - mmengine - INFO - Epoch(train) [72][380/940] lr: 1.0000e-03 eta: 6:08:55 time: 0.9665 data_time: 0.0261 memory: 22701 grad_norm: 5.2017 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0677 loss: 1.0677 2022/09/06 01:03:12 - mmengine - INFO - Epoch(train) [72][400/940] lr: 1.0000e-03 eta: 6:08:38 time: 0.7237 data_time: 0.0240 memory: 22701 grad_norm: 5.3592 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1056 loss: 1.1056 2022/09/06 01:03:30 - mmengine - INFO - Epoch(train) [72][420/940] lr: 1.0000e-03 eta: 6:08:22 time: 0.9003 data_time: 0.0215 memory: 22701 grad_norm: 5.2845 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0711 loss: 1.0711 2022/09/06 01:03:44 - mmengine - INFO - Epoch(train) [72][440/940] lr: 1.0000e-03 eta: 6:08:04 time: 0.6678 data_time: 0.0212 memory: 22701 grad_norm: 5.1360 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.0293 loss: 1.0293 2022/09/06 01:04:02 - mmengine - INFO - Epoch(train) [72][460/940] lr: 1.0000e-03 eta: 6:07:48 time: 0.8922 data_time: 0.0290 memory: 22701 grad_norm: 5.1319 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9468 loss: 0.9468 2022/09/06 01:04:19 - mmengine - INFO - Epoch(train) [72][480/940] lr: 1.0000e-03 eta: 6:07:32 time: 0.8650 data_time: 0.0224 memory: 22701 grad_norm: 5.2474 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0036 loss: 1.0036 2022/09/06 01:04:38 - mmengine - INFO - Epoch(train) [72][500/940] lr: 1.0000e-03 eta: 6:07:16 time: 0.9321 data_time: 0.0312 memory: 22701 grad_norm: 5.1444 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9153 loss: 0.9153 2022/09/06 01:04:51 - mmengine - INFO - Epoch(train) [72][520/940] lr: 1.0000e-03 eta: 6:06:59 time: 0.6739 data_time: 0.0207 memory: 22701 grad_norm: 5.1741 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0843 loss: 1.0843 2022/09/06 01:05:15 - mmengine - INFO - Epoch(train) [72][540/940] lr: 1.0000e-03 eta: 6:06:45 time: 1.1959 data_time: 0.0245 memory: 22701 grad_norm: 5.2095 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1249 loss: 1.1249 2022/09/06 01:05:30 - mmengine - INFO - Epoch(train) [72][560/940] lr: 1.0000e-03 eta: 6:06:28 time: 0.7650 data_time: 0.0181 memory: 22701 grad_norm: 5.2865 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0082 loss: 1.0082 2022/09/06 01:05:51 - mmengine - INFO - Epoch(train) [72][580/940] lr: 1.0000e-03 eta: 6:06:14 time: 1.0538 data_time: 0.0251 memory: 22701 grad_norm: 5.1948 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9642 loss: 0.9642 2022/09/06 01:06:07 - mmengine - INFO - Epoch(train) [72][600/940] lr: 1.0000e-03 eta: 6:05:57 time: 0.7737 data_time: 0.0256 memory: 22701 grad_norm: 5.2568 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0928 loss: 1.0928 2022/09/06 01:06:25 - mmengine - INFO - Epoch(train) [72][620/940] lr: 1.0000e-03 eta: 6:05:41 time: 0.9300 data_time: 0.0595 memory: 22701 grad_norm: 5.1491 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0231 loss: 1.0231 2022/09/06 01:06:40 - mmengine - INFO - Epoch(train) [72][640/940] lr: 1.0000e-03 eta: 6:05:24 time: 0.7472 data_time: 0.0550 memory: 22701 grad_norm: 5.1327 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0397 loss: 1.0397 2022/09/06 01:06:58 - mmengine - INFO - Epoch(train) [72][660/940] lr: 1.0000e-03 eta: 6:05:08 time: 0.8675 data_time: 0.0272 memory: 22701 grad_norm: 5.1927 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0538 loss: 1.0538 2022/09/06 01:07:12 - mmengine - INFO - Epoch(train) [72][680/940] lr: 1.0000e-03 eta: 6:04:50 time: 0.6900 data_time: 0.0198 memory: 22701 grad_norm: 5.1859 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9694 loss: 0.9694 2022/09/06 01:07:29 - mmengine - INFO - Epoch(train) [72][700/940] lr: 1.0000e-03 eta: 6:04:34 time: 0.8576 data_time: 0.0244 memory: 22701 grad_norm: 5.1620 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0546 loss: 1.0546 2022/09/06 01:07:43 - mmengine - INFO - Epoch(train) [72][720/940] lr: 1.0000e-03 eta: 6:04:17 time: 0.7294 data_time: 0.0197 memory: 22701 grad_norm: 5.1957 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9958 loss: 0.9958 2022/09/06 01:08:01 - mmengine - INFO - Epoch(train) [72][740/940] lr: 1.0000e-03 eta: 6:04:01 time: 0.8884 data_time: 0.0246 memory: 22701 grad_norm: 5.1920 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9973 loss: 0.9973 2022/09/06 01:08:15 - mmengine - INFO - Epoch(train) [72][760/940] lr: 1.0000e-03 eta: 6:03:43 time: 0.6726 data_time: 0.0237 memory: 22701 grad_norm: 5.1705 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0558 loss: 1.0558 2022/09/06 01:08:33 - mmengine - INFO - Epoch(train) [72][780/940] lr: 1.0000e-03 eta: 6:03:28 time: 0.9289 data_time: 0.0293 memory: 22701 grad_norm: 5.2379 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9364 loss: 0.9364 2022/09/06 01:08:47 - mmengine - INFO - Epoch(train) [72][800/940] lr: 1.0000e-03 eta: 6:03:10 time: 0.7069 data_time: 0.0181 memory: 22701 grad_norm: 5.1352 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0063 loss: 1.0063 2022/09/06 01:09:06 - mmengine - INFO - Epoch(train) [72][820/940] lr: 1.0000e-03 eta: 6:02:55 time: 0.9255 data_time: 0.0245 memory: 22701 grad_norm: 5.2663 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0240 loss: 1.0240 2022/09/06 01:09:22 - mmengine - INFO - Epoch(train) [72][840/940] lr: 1.0000e-03 eta: 6:02:38 time: 0.7890 data_time: 0.0260 memory: 22701 grad_norm: 5.2272 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9548 loss: 0.9548 2022/09/06 01:09:41 - mmengine - INFO - Epoch(train) [72][860/940] lr: 1.0000e-03 eta: 6:02:23 time: 0.9860 data_time: 0.0346 memory: 22701 grad_norm: 5.1784 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0443 loss: 1.0443 2022/09/06 01:09:57 - mmengine - INFO - Epoch(train) [72][880/940] lr: 1.0000e-03 eta: 6:02:06 time: 0.7843 data_time: 0.0223 memory: 22701 grad_norm: 5.2398 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9785 loss: 0.9785 2022/09/06 01:10:15 - mmengine - INFO - Epoch(train) [72][900/940] lr: 1.0000e-03 eta: 6:01:50 time: 0.9091 data_time: 0.0259 memory: 22701 grad_norm: 5.2315 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9758 loss: 0.9758 2022/09/06 01:10:30 - mmengine - INFO - Epoch(train) [72][920/940] lr: 1.0000e-03 eta: 6:01:33 time: 0.7610 data_time: 0.0255 memory: 22701 grad_norm: 5.0877 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.9768 loss: 0.9768 2022/09/06 01:10:51 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:10:51 - mmengine - INFO - Epoch(train) [72][940/940] lr: 1.0000e-03 eta: 6:01:18 time: 1.0499 data_time: 0.0199 memory: 22701 grad_norm: 5.7268 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.9939 loss: 0.9939 2022/09/06 01:10:51 - mmengine - INFO - Saving checkpoint at 72 epochs 2022/09/06 01:11:07 - mmengine - INFO - Epoch(val) [72][20/78] eta: 0:00:40 time: 0.6996 data_time: 0.5823 memory: 2247 2022/09/06 01:11:17 - mmengine - INFO - Epoch(val) [72][40/78] eta: 0:00:18 time: 0.4760 data_time: 0.3596 memory: 2247 2022/09/06 01:11:30 - mmengine - INFO - Epoch(val) [72][60/78] eta: 0:00:11 time: 0.6520 data_time: 0.5326 memory: 2247 2022/09/06 01:11:39 - mmengine - INFO - Epoch(val) [72][78/78] acc/top1: 0.6892 acc/top5: 0.8803 acc/mean1: 0.6891 2022/09/06 01:12:03 - mmengine - INFO - Epoch(train) [73][20/940] lr: 1.0000e-03 eta: 6:01:05 time: 1.1969 data_time: 0.5444 memory: 22701 grad_norm: 5.3259 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0496 loss: 1.0496 2022/09/06 01:12:19 - mmengine - INFO - Epoch(train) [73][40/940] lr: 1.0000e-03 eta: 6:00:48 time: 0.8111 data_time: 0.1158 memory: 22701 grad_norm: 5.2811 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9833 loss: 0.9833 2022/09/06 01:12:38 - mmengine - INFO - Epoch(train) [73][60/940] lr: 1.0000e-03 eta: 6:00:33 time: 0.9355 data_time: 0.0310 memory: 22701 grad_norm: 5.2835 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9448 loss: 0.9448 2022/09/06 01:12:53 - mmengine - INFO - Epoch(train) [73][80/940] lr: 1.0000e-03 eta: 6:00:16 time: 0.7535 data_time: 0.0227 memory: 22701 grad_norm: 5.1325 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9636 loss: 0.9636 2022/09/06 01:13:13 - mmengine - INFO - Epoch(train) [73][100/940] lr: 1.0000e-03 eta: 6:00:01 time: 1.0283 data_time: 0.0219 memory: 22701 grad_norm: 5.1732 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0333 loss: 1.0333 2022/09/06 01:13:31 - mmengine - INFO - Epoch(train) [73][120/940] lr: 1.0000e-03 eta: 5:59:45 time: 0.8728 data_time: 0.0241 memory: 22701 grad_norm: 5.2568 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1281 loss: 1.1281 2022/09/06 01:13:49 - mmengine - INFO - Epoch(train) [73][140/940] lr: 1.0000e-03 eta: 5:59:29 time: 0.9349 data_time: 0.0284 memory: 22701 grad_norm: 5.1327 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0327 loss: 1.0327 2022/09/06 01:14:06 - mmengine - INFO - Epoch(train) [73][160/940] lr: 1.0000e-03 eta: 5:59:13 time: 0.8245 data_time: 0.0253 memory: 22701 grad_norm: 5.1387 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0792 loss: 1.0792 2022/09/06 01:14:24 - mmengine - INFO - Epoch(train) [73][180/940] lr: 1.0000e-03 eta: 5:58:57 time: 0.8813 data_time: 0.0353 memory: 22701 grad_norm: 5.1908 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9567 loss: 0.9567 2022/09/06 01:14:39 - mmengine - INFO - Epoch(train) [73][200/940] lr: 1.0000e-03 eta: 5:58:40 time: 0.7865 data_time: 0.0259 memory: 22701 grad_norm: 5.2793 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0337 loss: 1.0337 2022/09/06 01:14:55 - mmengine - INFO - Epoch(train) [73][220/940] lr: 1.0000e-03 eta: 5:58:23 time: 0.7654 data_time: 0.0405 memory: 22701 grad_norm: 5.2232 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1120 loss: 1.1120 2022/09/06 01:15:10 - mmengine - INFO - Epoch(train) [73][240/940] lr: 1.0000e-03 eta: 5:58:06 time: 0.7871 data_time: 0.0225 memory: 22701 grad_norm: 5.1585 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0554 loss: 1.0554 2022/09/06 01:15:31 - mmengine - INFO - Epoch(train) [73][260/940] lr: 1.0000e-03 eta: 5:57:51 time: 1.0097 data_time: 0.0251 memory: 22701 grad_norm: 5.2543 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0046 loss: 1.0046 2022/09/06 01:15:47 - mmengine - INFO - Epoch(train) [73][280/940] lr: 1.0000e-03 eta: 5:57:34 time: 0.8038 data_time: 0.0307 memory: 22701 grad_norm: 5.2694 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9801 loss: 0.9801 2022/09/06 01:16:03 - mmengine - INFO - Epoch(train) [73][300/940] lr: 1.0000e-03 eta: 5:57:18 time: 0.8021 data_time: 0.0238 memory: 22701 grad_norm: 5.1510 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9511 loss: 0.9511 2022/09/06 01:16:20 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:16:20 - mmengine - INFO - Epoch(train) [73][320/940] lr: 1.0000e-03 eta: 5:57:02 time: 0.8613 data_time: 0.0274 memory: 22701 grad_norm: 5.2607 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0116 loss: 1.0116 2022/09/06 01:16:37 - mmengine - INFO - Epoch(train) [73][340/940] lr: 1.0000e-03 eta: 5:56:45 time: 0.8451 data_time: 0.1976 memory: 22701 grad_norm: 5.2953 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0510 loss: 1.0510 2022/09/06 01:16:51 - mmengine - INFO - Epoch(train) [73][360/940] lr: 1.0000e-03 eta: 5:56:28 time: 0.7033 data_time: 0.1690 memory: 22701 grad_norm: 5.2048 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9922 loss: 0.9922 2022/09/06 01:17:07 - mmengine - INFO - Epoch(train) [73][380/940] lr: 1.0000e-03 eta: 5:56:11 time: 0.8210 data_time: 0.1559 memory: 22701 grad_norm: 5.2362 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1157 loss: 1.1157 2022/09/06 01:17:21 - mmengine - INFO - Epoch(train) [73][400/940] lr: 1.0000e-03 eta: 5:55:54 time: 0.6685 data_time: 0.0475 memory: 22701 grad_norm: 5.2247 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9153 loss: 0.9153 2022/09/06 01:17:38 - mmengine - INFO - Epoch(train) [73][420/940] lr: 1.0000e-03 eta: 5:55:37 time: 0.8535 data_time: 0.1311 memory: 22701 grad_norm: 5.3008 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9829 loss: 0.9829 2022/09/06 01:17:56 - mmengine - INFO - Epoch(train) [73][440/940] lr: 1.0000e-03 eta: 5:55:22 time: 0.9000 data_time: 0.3987 memory: 22701 grad_norm: 5.2912 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.0151 loss: 1.0151 2022/09/06 01:18:16 - mmengine - INFO - Epoch(train) [73][460/940] lr: 1.0000e-03 eta: 5:55:06 time: 0.9979 data_time: 0.4865 memory: 22701 grad_norm: 5.2715 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0367 loss: 1.0367 2022/09/06 01:18:37 - mmengine - INFO - Epoch(train) [73][480/940] lr: 1.0000e-03 eta: 5:54:52 time: 1.0621 data_time: 0.2651 memory: 22701 grad_norm: 5.1428 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9522 loss: 0.9522 2022/09/06 01:18:54 - mmengine - INFO - Epoch(train) [73][500/940] lr: 1.0000e-03 eta: 5:54:35 time: 0.8423 data_time: 0.1534 memory: 22701 grad_norm: 5.3153 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1555 loss: 1.1555 2022/09/06 01:19:10 - mmengine - INFO - Epoch(train) [73][520/940] lr: 1.0000e-03 eta: 5:54:19 time: 0.8054 data_time: 0.2291 memory: 22701 grad_norm: 5.3054 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1152 loss: 1.1152 2022/09/06 01:19:29 - mmengine - INFO - Epoch(train) [73][540/940] lr: 1.0000e-03 eta: 5:54:03 time: 0.9397 data_time: 0.2926 memory: 22701 grad_norm: 5.1013 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9868 loss: 0.9868 2022/09/06 01:19:45 - mmengine - INFO - Epoch(train) [73][560/940] lr: 1.0000e-03 eta: 5:53:47 time: 0.8068 data_time: 0.0878 memory: 22701 grad_norm: 5.2309 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9373 loss: 0.9373 2022/09/06 01:20:06 - mmengine - INFO - Epoch(train) [73][580/940] lr: 1.0000e-03 eta: 5:53:32 time: 1.0601 data_time: 0.2201 memory: 22701 grad_norm: 5.2600 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9743 loss: 0.9743 2022/09/06 01:20:22 - mmengine - INFO - Epoch(train) [73][600/940] lr: 1.0000e-03 eta: 5:53:15 time: 0.7928 data_time: 0.1180 memory: 22701 grad_norm: 5.3447 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.0455 loss: 1.0455 2022/09/06 01:20:39 - mmengine - INFO - Epoch(train) [73][620/940] lr: 1.0000e-03 eta: 5:52:59 time: 0.8628 data_time: 0.0552 memory: 22701 grad_norm: 5.2737 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9729 loss: 0.9729 2022/09/06 01:20:53 - mmengine - INFO - Epoch(train) [73][640/940] lr: 1.0000e-03 eta: 5:52:41 time: 0.6831 data_time: 0.0238 memory: 22701 grad_norm: 5.3537 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1364 loss: 1.1364 2022/09/06 01:21:10 - mmengine - INFO - Epoch(train) [73][660/940] lr: 1.0000e-03 eta: 5:52:25 time: 0.8408 data_time: 0.3287 memory: 22701 grad_norm: 5.3770 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1348 loss: 1.1348 2022/09/06 01:21:25 - mmengine - INFO - Epoch(train) [73][680/940] lr: 1.0000e-03 eta: 5:52:08 time: 0.7711 data_time: 0.2748 memory: 22701 grad_norm: 5.3966 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0299 loss: 1.0299 2022/09/06 01:21:44 - mmengine - INFO - Epoch(train) [73][700/940] lr: 1.0000e-03 eta: 5:51:52 time: 0.9207 data_time: 0.4945 memory: 22701 grad_norm: 5.3832 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1168 loss: 1.1168 2022/09/06 01:21:59 - mmengine - INFO - Epoch(train) [73][720/940] lr: 1.0000e-03 eta: 5:51:36 time: 0.7896 data_time: 0.3812 memory: 22701 grad_norm: 5.2950 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9675 loss: 0.9675 2022/09/06 01:22:19 - mmengine - INFO - Epoch(train) [73][740/940] lr: 1.0000e-03 eta: 5:51:20 time: 0.9574 data_time: 0.5361 memory: 22701 grad_norm: 5.2213 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1763 loss: 1.1763 2022/09/06 01:22:33 - mmengine - INFO - Epoch(train) [73][760/940] lr: 1.0000e-03 eta: 5:51:03 time: 0.7097 data_time: 0.3152 memory: 22701 grad_norm: 5.2872 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0985 loss: 1.0985 2022/09/06 01:22:54 - mmengine - INFO - Epoch(train) [73][780/940] lr: 1.0000e-03 eta: 5:50:48 time: 1.0723 data_time: 0.6548 memory: 22701 grad_norm: 5.2111 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0649 loss: 1.0649 2022/09/06 01:23:10 - mmengine - INFO - Epoch(train) [73][800/940] lr: 1.0000e-03 eta: 5:50:32 time: 0.8145 data_time: 0.4344 memory: 22701 grad_norm: 5.2471 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1230 loss: 1.1230 2022/09/06 01:23:28 - mmengine - INFO - Epoch(train) [73][820/940] lr: 1.0000e-03 eta: 5:50:16 time: 0.8661 data_time: 0.4513 memory: 22701 grad_norm: 5.2871 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0262 loss: 1.0262 2022/09/06 01:23:43 - mmengine - INFO - Epoch(train) [73][840/940] lr: 1.0000e-03 eta: 5:49:59 time: 0.7802 data_time: 0.3908 memory: 22701 grad_norm: 5.2286 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0225 loss: 1.0225 2022/09/06 01:24:02 - mmengine - INFO - Epoch(train) [73][860/940] lr: 1.0000e-03 eta: 5:49:43 time: 0.9287 data_time: 0.5382 memory: 22701 grad_norm: 5.2024 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1452 loss: 1.1452 2022/09/06 01:24:21 - mmengine - INFO - Epoch(train) [73][880/940] lr: 1.0000e-03 eta: 5:49:28 time: 0.9648 data_time: 0.5758 memory: 22701 grad_norm: 5.3276 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9340 loss: 0.9340 2022/09/06 01:24:41 - mmengine - INFO - Epoch(train) [73][900/940] lr: 1.0000e-03 eta: 5:49:12 time: 0.9913 data_time: 0.5912 memory: 22701 grad_norm: 5.2611 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.0253 loss: 1.0253 2022/09/06 01:24:59 - mmengine - INFO - Epoch(train) [73][920/940] lr: 1.0000e-03 eta: 5:48:56 time: 0.8816 data_time: 0.4341 memory: 22701 grad_norm: 5.3983 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1971 loss: 1.1971 2022/09/06 01:25:17 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:25:17 - mmengine - INFO - Epoch(train) [73][940/940] lr: 1.0000e-03 eta: 5:48:40 time: 0.8966 data_time: 0.5015 memory: 22701 grad_norm: 5.7868 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1530 loss: 1.1530 2022/09/06 01:25:30 - mmengine - INFO - Epoch(val) [73][20/78] eta: 0:00:39 time: 0.6837 data_time: 0.5605 memory: 2247 2022/09/06 01:25:40 - mmengine - INFO - Epoch(val) [73][40/78] eta: 0:00:17 time: 0.4546 data_time: 0.3342 memory: 2247 2022/09/06 01:25:52 - mmengine - INFO - Epoch(val) [73][60/78] eta: 0:00:11 time: 0.6334 data_time: 0.5139 memory: 2247 2022/09/06 01:26:03 - mmengine - INFO - Epoch(val) [73][78/78] acc/top1: 0.6864 acc/top5: 0.8800 acc/mean1: 0.6863 2022/09/06 01:26:25 - mmengine - INFO - Epoch(train) [74][20/940] lr: 1.0000e-03 eta: 5:48:26 time: 1.1187 data_time: 0.7242 memory: 22701 grad_norm: 5.2007 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9635 loss: 0.9635 2022/09/06 01:26:41 - mmengine - INFO - Epoch(train) [74][40/940] lr: 1.0000e-03 eta: 5:48:09 time: 0.8022 data_time: 0.3353 memory: 22701 grad_norm: 5.1636 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.0191 loss: 1.0191 2022/09/06 01:27:02 - mmengine - INFO - Epoch(train) [74][60/940] lr: 1.0000e-03 eta: 5:47:54 time: 1.0221 data_time: 0.4043 memory: 22701 grad_norm: 5.1729 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0305 loss: 1.0305 2022/09/06 01:27:15 - mmengine - INFO - Epoch(train) [74][80/940] lr: 1.0000e-03 eta: 5:47:37 time: 0.6551 data_time: 0.0973 memory: 22701 grad_norm: 5.2765 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0184 loss: 1.0184 2022/09/06 01:27:32 - mmengine - INFO - Epoch(train) [74][100/940] lr: 1.0000e-03 eta: 5:47:20 time: 0.8554 data_time: 0.4267 memory: 22701 grad_norm: 5.2586 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0136 loss: 1.0136 2022/09/06 01:27:48 - mmengine - INFO - Epoch(train) [74][120/940] lr: 1.0000e-03 eta: 5:47:04 time: 0.8062 data_time: 0.2352 memory: 22701 grad_norm: 5.2371 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0263 loss: 1.0263 2022/09/06 01:28:11 - mmengine - INFO - Epoch(train) [74][140/940] lr: 1.0000e-03 eta: 5:46:49 time: 1.1197 data_time: 0.3087 memory: 22701 grad_norm: 5.1735 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9790 loss: 0.9790 2022/09/06 01:28:26 - mmengine - INFO - Epoch(train) [74][160/940] lr: 1.0000e-03 eta: 5:46:33 time: 0.7770 data_time: 0.0430 memory: 22701 grad_norm: 5.2524 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9902 loss: 0.9902 2022/09/06 01:28:45 - mmengine - INFO - Epoch(train) [74][180/940] lr: 1.0000e-03 eta: 5:46:17 time: 0.9719 data_time: 0.0788 memory: 22701 grad_norm: 5.2819 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9922 loss: 0.9922 2022/09/06 01:28:59 - mmengine - INFO - Epoch(train) [74][200/940] lr: 1.0000e-03 eta: 5:46:00 time: 0.6742 data_time: 0.0269 memory: 22701 grad_norm: 5.1927 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9663 loss: 0.9663 2022/09/06 01:29:21 - mmengine - INFO - Epoch(train) [74][220/940] lr: 1.0000e-03 eta: 5:45:45 time: 1.0961 data_time: 0.0327 memory: 22701 grad_norm: 5.2374 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1049 loss: 1.1049 2022/09/06 01:29:39 - mmengine - INFO - Epoch(train) [74][240/940] lr: 1.0000e-03 eta: 5:45:29 time: 0.8822 data_time: 0.0406 memory: 22701 grad_norm: 5.2926 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0801 loss: 1.0801 2022/09/06 01:29:55 - mmengine - INFO - Epoch(train) [74][260/940] lr: 1.0000e-03 eta: 5:45:12 time: 0.8267 data_time: 0.0289 memory: 22701 grad_norm: 5.3439 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0666 loss: 1.0666 2022/09/06 01:30:12 - mmengine - INFO - Epoch(train) [74][280/940] lr: 1.0000e-03 eta: 5:44:56 time: 0.8233 data_time: 0.0249 memory: 22701 grad_norm: 5.3438 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.0897 loss: 1.0897 2022/09/06 01:30:28 - mmengine - INFO - Epoch(train) [74][300/940] lr: 1.0000e-03 eta: 5:44:39 time: 0.8106 data_time: 0.0284 memory: 22701 grad_norm: 5.4157 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9923 loss: 0.9923 2022/09/06 01:30:44 - mmengine - INFO - Epoch(train) [74][320/940] lr: 1.0000e-03 eta: 5:44:23 time: 0.8191 data_time: 0.0245 memory: 22701 grad_norm: 5.2221 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9098 loss: 0.9098 2022/09/06 01:31:03 - mmengine - INFO - Epoch(train) [74][340/940] lr: 1.0000e-03 eta: 5:44:07 time: 0.9575 data_time: 0.0286 memory: 22701 grad_norm: 5.2664 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0005 loss: 1.0005 2022/09/06 01:31:18 - mmengine - INFO - Epoch(train) [74][360/940] lr: 1.0000e-03 eta: 5:43:50 time: 0.7505 data_time: 0.0236 memory: 22701 grad_norm: 5.2578 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9324 loss: 0.9324 2022/09/06 01:31:35 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:31:35 - mmengine - INFO - Epoch(train) [74][380/940] lr: 1.0000e-03 eta: 5:43:34 time: 0.8109 data_time: 0.0271 memory: 22701 grad_norm: 5.2281 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9920 loss: 0.9920 2022/09/06 01:31:51 - mmengine - INFO - Epoch(train) [74][400/940] lr: 1.0000e-03 eta: 5:43:17 time: 0.8281 data_time: 0.1550 memory: 22701 grad_norm: 5.2933 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0619 loss: 1.0619 2022/09/06 01:32:12 - mmengine - INFO - Epoch(train) [74][420/940] lr: 1.0000e-03 eta: 5:43:02 time: 1.0334 data_time: 0.2543 memory: 22701 grad_norm: 5.2215 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9933 loss: 0.9933 2022/09/06 01:32:29 - mmengine - INFO - Epoch(train) [74][440/940] lr: 1.0000e-03 eta: 5:42:46 time: 0.8373 data_time: 0.1583 memory: 22701 grad_norm: 5.3158 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1349 loss: 1.1349 2022/09/06 01:32:46 - mmengine - INFO - Epoch(train) [74][460/940] lr: 1.0000e-03 eta: 5:42:30 time: 0.8847 data_time: 0.0523 memory: 22701 grad_norm: 5.2283 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9650 loss: 0.9650 2022/09/06 01:33:03 - mmengine - INFO - Epoch(train) [74][480/940] lr: 1.0000e-03 eta: 5:42:13 time: 0.8282 data_time: 0.1341 memory: 22701 grad_norm: 5.1836 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0863 loss: 1.0863 2022/09/06 01:33:21 - mmengine - INFO - Epoch(train) [74][500/940] lr: 1.0000e-03 eta: 5:41:57 time: 0.9147 data_time: 0.4447 memory: 22701 grad_norm: 5.2823 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9037 loss: 0.9037 2022/09/06 01:33:37 - mmengine - INFO - Epoch(train) [74][520/940] lr: 1.0000e-03 eta: 5:41:41 time: 0.7699 data_time: 0.3799 memory: 22701 grad_norm: 5.3538 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.0034 loss: 1.0034 2022/09/06 01:33:53 - mmengine - INFO - Epoch(train) [74][540/940] lr: 1.0000e-03 eta: 5:41:24 time: 0.8448 data_time: 0.4288 memory: 22701 grad_norm: 5.2416 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.9588 loss: 0.9588 2022/09/06 01:34:08 - mmengine - INFO - Epoch(train) [74][560/940] lr: 1.0000e-03 eta: 5:41:07 time: 0.7410 data_time: 0.3177 memory: 22701 grad_norm: 5.1721 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9416 loss: 0.9416 2022/09/06 01:34:24 - mmengine - INFO - Epoch(train) [74][580/940] lr: 1.0000e-03 eta: 5:40:50 time: 0.7761 data_time: 0.3784 memory: 22701 grad_norm: 5.2263 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9748 loss: 0.9748 2022/09/06 01:34:39 - mmengine - INFO - Epoch(train) [74][600/940] lr: 1.0000e-03 eta: 5:40:33 time: 0.7401 data_time: 0.3572 memory: 22701 grad_norm: 5.1990 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9718 loss: 0.9718 2022/09/06 01:34:57 - mmengine - INFO - Epoch(train) [74][620/940] lr: 1.0000e-03 eta: 5:40:17 time: 0.9116 data_time: 0.5083 memory: 22701 grad_norm: 5.1827 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9963 loss: 0.9963 2022/09/06 01:35:11 - mmengine - INFO - Epoch(train) [74][640/940] lr: 1.0000e-03 eta: 5:40:00 time: 0.7103 data_time: 0.3170 memory: 22701 grad_norm: 5.2033 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9948 loss: 0.9948 2022/09/06 01:35:29 - mmengine - INFO - Epoch(train) [74][660/940] lr: 1.0000e-03 eta: 5:39:44 time: 0.8952 data_time: 0.4756 memory: 22701 grad_norm: 5.2762 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0431 loss: 1.0431 2022/09/06 01:35:47 - mmengine - INFO - Epoch(train) [74][680/940] lr: 1.0000e-03 eta: 5:39:28 time: 0.8931 data_time: 0.2380 memory: 22701 grad_norm: 5.1837 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0064 loss: 1.0064 2022/09/06 01:36:03 - mmengine - INFO - Epoch(train) [74][700/940] lr: 1.0000e-03 eta: 5:39:11 time: 0.7916 data_time: 0.1398 memory: 22701 grad_norm: 5.2204 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9853 loss: 0.9853 2022/09/06 01:36:19 - mmengine - INFO - Epoch(train) [74][720/940] lr: 1.0000e-03 eta: 5:38:55 time: 0.8335 data_time: 0.3085 memory: 22701 grad_norm: 5.2362 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0748 loss: 1.0748 2022/09/06 01:36:36 - mmengine - INFO - Epoch(train) [74][740/940] lr: 1.0000e-03 eta: 5:38:38 time: 0.8374 data_time: 0.4224 memory: 22701 grad_norm: 5.2299 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1116 loss: 1.1116 2022/09/06 01:36:51 - mmengine - INFO - Epoch(train) [74][760/940] lr: 1.0000e-03 eta: 5:38:21 time: 0.7430 data_time: 0.1988 memory: 22701 grad_norm: 5.2198 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9627 loss: 0.9627 2022/09/06 01:37:08 - mmengine - INFO - Epoch(train) [74][780/940] lr: 1.0000e-03 eta: 5:38:05 time: 0.8560 data_time: 0.3665 memory: 22701 grad_norm: 5.3604 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 0.9878 loss: 0.9878 2022/09/06 01:37:28 - mmengine - INFO - Epoch(train) [74][800/940] lr: 1.0000e-03 eta: 5:37:50 time: 0.9888 data_time: 0.4313 memory: 22701 grad_norm: 5.2514 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0171 loss: 1.0171 2022/09/06 01:37:46 - mmengine - INFO - Epoch(train) [74][820/940] lr: 1.0000e-03 eta: 5:37:34 time: 0.8925 data_time: 0.4498 memory: 22701 grad_norm: 5.2405 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0393 loss: 1.0393 2022/09/06 01:38:00 - mmengine - INFO - Epoch(train) [74][840/940] lr: 1.0000e-03 eta: 5:37:16 time: 0.7088 data_time: 0.2842 memory: 22701 grad_norm: 5.2243 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9728 loss: 0.9728 2022/09/06 01:38:17 - mmengine - INFO - Epoch(train) [74][860/940] lr: 1.0000e-03 eta: 5:37:00 time: 0.8798 data_time: 0.4566 memory: 22701 grad_norm: 5.2143 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0282 loss: 1.0282 2022/09/06 01:38:31 - mmengine - INFO - Epoch(train) [74][880/940] lr: 1.0000e-03 eta: 5:36:43 time: 0.6705 data_time: 0.2723 memory: 22701 grad_norm: 5.2470 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1331 loss: 1.1331 2022/09/06 01:38:48 - mmengine - INFO - Epoch(train) [74][900/940] lr: 1.0000e-03 eta: 5:36:27 time: 0.8513 data_time: 0.4344 memory: 22701 grad_norm: 5.4126 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0568 loss: 1.0568 2022/09/06 01:39:02 - mmengine - INFO - Epoch(train) [74][920/940] lr: 1.0000e-03 eta: 5:36:09 time: 0.6824 data_time: 0.2894 memory: 22701 grad_norm: 5.2562 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.9962 loss: 0.9962 2022/09/06 01:39:19 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:39:19 - mmengine - INFO - Epoch(train) [74][940/940] lr: 1.0000e-03 eta: 5:35:53 time: 0.8532 data_time: 0.4574 memory: 22701 grad_norm: 5.7836 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.0612 loss: 1.0612 2022/09/06 01:39:32 - mmengine - INFO - Epoch(val) [74][20/78] eta: 0:00:39 time: 0.6825 data_time: 0.5580 memory: 2247 2022/09/06 01:39:42 - mmengine - INFO - Epoch(val) [74][40/78] eta: 0:00:17 time: 0.4637 data_time: 0.3442 memory: 2247 2022/09/06 01:39:55 - mmengine - INFO - Epoch(val) [74][60/78] eta: 0:00:11 time: 0.6469 data_time: 0.5287 memory: 2247 2022/09/06 01:40:05 - mmengine - INFO - Epoch(val) [74][78/78] acc/top1: 0.6860 acc/top5: 0.8804 acc/mean1: 0.6859 2022/09/06 01:40:28 - mmengine - INFO - Epoch(train) [75][20/940] lr: 1.0000e-03 eta: 5:35:38 time: 1.1397 data_time: 0.5741 memory: 22701 grad_norm: 5.2478 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0100 loss: 1.0100 2022/09/06 01:40:42 - mmengine - INFO - Epoch(train) [75][40/940] lr: 1.0000e-03 eta: 5:35:21 time: 0.7302 data_time: 0.2852 memory: 22701 grad_norm: 5.2440 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9858 loss: 0.9858 2022/09/06 01:41:02 - mmengine - INFO - Epoch(train) [75][60/940] lr: 1.0000e-03 eta: 5:35:06 time: 0.9725 data_time: 0.4235 memory: 22701 grad_norm: 5.2515 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.0001 loss: 1.0001 2022/09/06 01:41:17 - mmengine - INFO - Epoch(train) [75][80/940] lr: 1.0000e-03 eta: 5:34:49 time: 0.7742 data_time: 0.2017 memory: 22701 grad_norm: 5.2586 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9945 loss: 0.9945 2022/09/06 01:41:37 - mmengine - INFO - Epoch(train) [75][100/940] lr: 1.0000e-03 eta: 5:34:34 time: 0.9884 data_time: 0.0827 memory: 22701 grad_norm: 5.2648 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9801 loss: 0.9801 2022/09/06 01:41:54 - mmengine - INFO - Epoch(train) [75][120/940] lr: 1.0000e-03 eta: 5:34:17 time: 0.8460 data_time: 0.0412 memory: 22701 grad_norm: 5.2660 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8936 loss: 0.8936 2022/09/06 01:42:13 - mmengine - INFO - Epoch(train) [75][140/940] lr: 1.0000e-03 eta: 5:34:02 time: 0.9477 data_time: 0.0281 memory: 22701 grad_norm: 5.3185 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9901 loss: 0.9901 2022/09/06 01:42:26 - mmengine - INFO - Epoch(train) [75][160/940] lr: 1.0000e-03 eta: 5:33:44 time: 0.6825 data_time: 0.0272 memory: 22701 grad_norm: 5.2807 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0039 loss: 1.0039 2022/09/06 01:42:44 - mmengine - INFO - Epoch(train) [75][180/940] lr: 1.0000e-03 eta: 5:33:28 time: 0.8942 data_time: 0.0263 memory: 22701 grad_norm: 5.1928 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9877 loss: 0.9877 2022/09/06 01:43:00 - mmengine - INFO - Epoch(train) [75][200/940] lr: 1.0000e-03 eta: 5:33:12 time: 0.8065 data_time: 0.0194 memory: 22701 grad_norm: 5.2204 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.8453 loss: 0.8453 2022/09/06 01:43:16 - mmengine - INFO - Epoch(train) [75][220/940] lr: 1.0000e-03 eta: 5:32:55 time: 0.7904 data_time: 0.0269 memory: 22701 grad_norm: 5.3553 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9730 loss: 0.9730 2022/09/06 01:43:34 - mmengine - INFO - Epoch(train) [75][240/940] lr: 1.0000e-03 eta: 5:32:39 time: 0.8989 data_time: 0.0187 memory: 22701 grad_norm: 5.2325 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9100 loss: 0.9100 2022/09/06 01:43:56 - mmengine - INFO - Epoch(train) [75][260/940] lr: 1.0000e-03 eta: 5:32:24 time: 1.0734 data_time: 0.0209 memory: 22701 grad_norm: 5.1593 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9903 loss: 0.9903 2022/09/06 01:44:12 - mmengine - INFO - Epoch(train) [75][280/940] lr: 1.0000e-03 eta: 5:32:08 time: 0.8193 data_time: 0.0270 memory: 22701 grad_norm: 5.2413 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0098 loss: 1.0098 2022/09/06 01:44:32 - mmengine - INFO - Epoch(train) [75][300/940] lr: 1.0000e-03 eta: 5:31:52 time: 0.9701 data_time: 0.0235 memory: 22701 grad_norm: 5.2039 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0128 loss: 1.0128 2022/09/06 01:44:48 - mmengine - INFO - Epoch(train) [75][320/940] lr: 1.0000e-03 eta: 5:31:35 time: 0.8074 data_time: 0.0318 memory: 22701 grad_norm: 5.3351 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9964 loss: 0.9964 2022/09/06 01:45:08 - mmengine - INFO - Epoch(train) [75][340/940] lr: 1.0000e-03 eta: 5:31:20 time: 1.0178 data_time: 0.0270 memory: 22701 grad_norm: 5.2938 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1262 loss: 1.1262 2022/09/06 01:45:23 - mmengine - INFO - Epoch(train) [75][360/940] lr: 1.0000e-03 eta: 5:31:03 time: 0.7263 data_time: 0.0265 memory: 22701 grad_norm: 5.3816 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1352 loss: 1.1352 2022/09/06 01:45:42 - mmengine - INFO - Epoch(train) [75][380/940] lr: 1.0000e-03 eta: 5:30:48 time: 0.9797 data_time: 0.0259 memory: 22701 grad_norm: 5.2790 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9919 loss: 0.9919 2022/09/06 01:45:57 - mmengine - INFO - Epoch(train) [75][400/940] lr: 1.0000e-03 eta: 5:30:30 time: 0.7284 data_time: 0.0228 memory: 22701 grad_norm: 5.2438 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.9955 loss: 0.9955 2022/09/06 01:46:14 - mmengine - INFO - Epoch(train) [75][420/940] lr: 1.0000e-03 eta: 5:30:14 time: 0.8620 data_time: 0.0310 memory: 22701 grad_norm: 5.2319 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9188 loss: 0.9188 2022/09/06 01:46:29 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:46:29 - mmengine - INFO - Epoch(train) [75][440/940] lr: 1.0000e-03 eta: 5:29:57 time: 0.7405 data_time: 0.0203 memory: 22701 grad_norm: 5.2828 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0012 loss: 1.0012 2022/09/06 01:46:46 - mmengine - INFO - Epoch(train) [75][460/940] lr: 1.0000e-03 eta: 5:29:41 time: 0.8636 data_time: 0.0250 memory: 22701 grad_norm: 5.2921 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0335 loss: 1.0335 2022/09/06 01:46:59 - mmengine - INFO - Epoch(train) [75][480/940] lr: 1.0000e-03 eta: 5:29:23 time: 0.6426 data_time: 0.0193 memory: 22701 grad_norm: 5.3491 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0721 loss: 1.0721 2022/09/06 01:47:16 - mmengine - INFO - Epoch(train) [75][500/940] lr: 1.0000e-03 eta: 5:29:07 time: 0.8303 data_time: 0.0280 memory: 22701 grad_norm: 5.3396 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0449 loss: 1.0449 2022/09/06 01:47:31 - mmengine - INFO - Epoch(train) [75][520/940] lr: 1.0000e-03 eta: 5:28:50 time: 0.7969 data_time: 0.0177 memory: 22701 grad_norm: 5.1951 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0187 loss: 1.0187 2022/09/06 01:47:55 - mmengine - INFO - Epoch(train) [75][540/940] lr: 1.0000e-03 eta: 5:28:36 time: 1.1553 data_time: 0.0220 memory: 22701 grad_norm: 5.2937 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9277 loss: 0.9277 2022/09/06 01:48:09 - mmengine - INFO - Epoch(train) [75][560/940] lr: 1.0000e-03 eta: 5:28:19 time: 0.7218 data_time: 0.0216 memory: 22701 grad_norm: 5.2038 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9887 loss: 0.9887 2022/09/06 01:48:28 - mmengine - INFO - Epoch(train) [75][580/940] lr: 1.0000e-03 eta: 5:28:03 time: 0.9653 data_time: 0.0274 memory: 22701 grad_norm: 5.3576 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0807 loss: 1.0807 2022/09/06 01:48:43 - mmengine - INFO - Epoch(train) [75][600/940] lr: 1.0000e-03 eta: 5:27:46 time: 0.7305 data_time: 0.0244 memory: 22701 grad_norm: 5.1667 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9332 loss: 0.9332 2022/09/06 01:49:00 - mmengine - INFO - Epoch(train) [75][620/940] lr: 1.0000e-03 eta: 5:27:30 time: 0.8736 data_time: 0.0290 memory: 22701 grad_norm: 5.3091 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.1117 loss: 1.1117 2022/09/06 01:49:15 - mmengine - INFO - Epoch(train) [75][640/940] lr: 1.0000e-03 eta: 5:27:12 time: 0.7087 data_time: 0.0241 memory: 22701 grad_norm: 5.3372 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9852 loss: 0.9852 2022/09/06 01:49:33 - mmengine - INFO - Epoch(train) [75][660/940] lr: 1.0000e-03 eta: 5:26:57 time: 0.9358 data_time: 0.0327 memory: 22701 grad_norm: 5.3077 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9908 loss: 0.9908 2022/09/06 01:49:50 - mmengine - INFO - Epoch(train) [75][680/940] lr: 1.0000e-03 eta: 5:26:40 time: 0.8457 data_time: 0.0259 memory: 22701 grad_norm: 5.3540 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1363 loss: 1.1363 2022/09/06 01:50:09 - mmengine - INFO - Epoch(train) [75][700/940] lr: 1.0000e-03 eta: 5:26:25 time: 0.9307 data_time: 0.0320 memory: 22701 grad_norm: 5.2945 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0212 loss: 1.0212 2022/09/06 01:50:24 - mmengine - INFO - Epoch(train) [75][720/940] lr: 1.0000e-03 eta: 5:26:08 time: 0.7472 data_time: 0.0209 memory: 22701 grad_norm: 5.3634 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9412 loss: 0.9412 2022/09/06 01:50:41 - mmengine - INFO - Epoch(train) [75][740/940] lr: 1.0000e-03 eta: 5:25:51 time: 0.8737 data_time: 0.0248 memory: 22701 grad_norm: 5.1844 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 0.9670 loss: 0.9670 2022/09/06 01:50:58 - mmengine - INFO - Epoch(train) [75][760/940] lr: 1.0000e-03 eta: 5:25:35 time: 0.8273 data_time: 0.0254 memory: 22701 grad_norm: 5.2073 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9882 loss: 0.9882 2022/09/06 01:51:16 - mmengine - INFO - Epoch(train) [75][780/940] lr: 1.0000e-03 eta: 5:25:19 time: 0.9099 data_time: 0.0271 memory: 22701 grad_norm: 5.2064 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8874 loss: 0.8874 2022/09/06 01:51:35 - mmengine - INFO - Epoch(train) [75][800/940] lr: 1.0000e-03 eta: 5:25:03 time: 0.9415 data_time: 0.0262 memory: 22701 grad_norm: 5.2960 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0261 loss: 1.0261 2022/09/06 01:51:55 - mmengine - INFO - Epoch(train) [75][820/940] lr: 1.0000e-03 eta: 5:24:48 time: 1.0234 data_time: 0.0289 memory: 22701 grad_norm: 5.1703 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9479 loss: 0.9479 2022/09/06 01:52:16 - mmengine - INFO - Epoch(train) [75][840/940] lr: 1.0000e-03 eta: 5:24:33 time: 1.0344 data_time: 0.0275 memory: 22701 grad_norm: 5.2378 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0594 loss: 1.0594 2022/09/06 01:52:39 - mmengine - INFO - Epoch(train) [75][860/940] lr: 1.0000e-03 eta: 5:24:18 time: 1.1248 data_time: 0.0202 memory: 22701 grad_norm: 5.3335 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9912 loss: 0.9912 2022/09/06 01:52:57 - mmengine - INFO - Epoch(train) [75][880/940] lr: 1.0000e-03 eta: 5:24:02 time: 0.9068 data_time: 0.0242 memory: 22701 grad_norm: 5.3059 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9932 loss: 0.9932 2022/09/06 01:53:13 - mmengine - INFO - Epoch(train) [75][900/940] lr: 1.0000e-03 eta: 5:23:46 time: 0.8078 data_time: 0.0289 memory: 22701 grad_norm: 5.4071 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0244 loss: 1.0244 2022/09/06 01:53:30 - mmengine - INFO - Epoch(train) [75][920/940] lr: 1.0000e-03 eta: 5:23:29 time: 0.8349 data_time: 0.0273 memory: 22701 grad_norm: 5.3827 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0165 loss: 1.0165 2022/09/06 01:53:44 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 01:53:44 - mmengine - INFO - Epoch(train) [75][940/940] lr: 1.0000e-03 eta: 5:23:12 time: 0.7338 data_time: 0.0256 memory: 22701 grad_norm: 5.7462 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.0082 loss: 1.0082 2022/09/06 01:53:44 - mmengine - INFO - Saving checkpoint at 75 epochs 2022/09/06 01:54:00 - mmengine - INFO - Epoch(val) [75][20/78] eta: 0:00:39 time: 0.6859 data_time: 0.5701 memory: 2247 2022/09/06 01:54:09 - mmengine - INFO - Epoch(val) [75][40/78] eta: 0:00:18 time: 0.4789 data_time: 0.3624 memory: 2247 2022/09/06 01:54:22 - mmengine - INFO - Epoch(val) [75][60/78] eta: 0:00:11 time: 0.6417 data_time: 0.5249 memory: 2247 2022/09/06 01:54:31 - mmengine - INFO - Epoch(val) [75][78/78] acc/top1: 0.6875 acc/top5: 0.8806 acc/mean1: 0.6874 2022/09/06 01:54:52 - mmengine - INFO - Epoch(train) [76][20/940] lr: 1.0000e-03 eta: 5:22:57 time: 1.0134 data_time: 0.5441 memory: 22701 grad_norm: 5.3069 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9606 loss: 0.9606 2022/09/06 01:55:06 - mmengine - INFO - Epoch(train) [76][40/940] lr: 1.0000e-03 eta: 5:22:40 time: 0.6986 data_time: 0.1780 memory: 22701 grad_norm: 5.3868 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0742 loss: 1.0742 2022/09/06 01:55:22 - mmengine - INFO - Epoch(train) [76][60/940] lr: 1.0000e-03 eta: 5:22:23 time: 0.7868 data_time: 0.2599 memory: 22701 grad_norm: 5.2395 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9805 loss: 0.9805 2022/09/06 01:55:35 - mmengine - INFO - Epoch(train) [76][80/940] lr: 1.0000e-03 eta: 5:22:06 time: 0.6854 data_time: 0.2833 memory: 22701 grad_norm: 5.3469 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9684 loss: 0.9684 2022/09/06 01:55:51 - mmengine - INFO - Epoch(train) [76][100/940] lr: 1.0000e-03 eta: 5:21:49 time: 0.8128 data_time: 0.3494 memory: 22701 grad_norm: 5.2712 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0215 loss: 1.0215 2022/09/06 01:56:05 - mmengine - INFO - Epoch(train) [76][120/940] lr: 1.0000e-03 eta: 5:21:31 time: 0.6787 data_time: 0.2257 memory: 22701 grad_norm: 5.3743 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0508 loss: 1.0508 2022/09/06 01:56:22 - mmengine - INFO - Epoch(train) [76][140/940] lr: 1.0000e-03 eta: 5:21:15 time: 0.8599 data_time: 0.2663 memory: 22701 grad_norm: 5.3185 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9571 loss: 0.9571 2022/09/06 01:56:37 - mmengine - INFO - Epoch(train) [76][160/940] lr: 1.0000e-03 eta: 5:20:58 time: 0.7368 data_time: 0.1531 memory: 22701 grad_norm: 5.1423 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0001 loss: 1.0001 2022/09/06 01:56:54 - mmengine - INFO - Epoch(train) [76][180/940] lr: 1.0000e-03 eta: 5:20:42 time: 0.8692 data_time: 0.2323 memory: 22701 grad_norm: 5.2022 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9545 loss: 0.9545 2022/09/06 01:57:08 - mmengine - INFO - Epoch(train) [76][200/940] lr: 1.0000e-03 eta: 5:20:25 time: 0.7029 data_time: 0.1580 memory: 22701 grad_norm: 5.2059 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8645 loss: 0.8645 2022/09/06 01:57:27 - mmengine - INFO - Epoch(train) [76][220/940] lr: 1.0000e-03 eta: 5:20:09 time: 0.9562 data_time: 0.4004 memory: 22701 grad_norm: 5.3733 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0589 loss: 1.0589 2022/09/06 01:57:42 - mmengine - INFO - Epoch(train) [76][240/940] lr: 1.0000e-03 eta: 5:19:52 time: 0.7437 data_time: 0.2844 memory: 22701 grad_norm: 5.3190 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0335 loss: 1.0335 2022/09/06 01:58:00 - mmengine - INFO - Epoch(train) [76][260/940] lr: 1.0000e-03 eta: 5:19:36 time: 0.9052 data_time: 0.3786 memory: 22701 grad_norm: 5.3181 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0863 loss: 1.0863 2022/09/06 01:58:15 - mmengine - INFO - Epoch(train) [76][280/940] lr: 1.0000e-03 eta: 5:19:19 time: 0.7453 data_time: 0.1954 memory: 22701 grad_norm: 5.2676 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.0196 loss: 1.0196 2022/09/06 01:58:33 - mmengine - INFO - Epoch(train) [76][300/940] lr: 1.0000e-03 eta: 5:19:03 time: 0.8780 data_time: 0.4830 memory: 22701 grad_norm: 5.3652 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9827 loss: 0.9827 2022/09/06 01:58:49 - mmengine - INFO - Epoch(train) [76][320/940] lr: 1.0000e-03 eta: 5:18:46 time: 0.7798 data_time: 0.3707 memory: 22701 grad_norm: 5.3082 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0474 loss: 1.0474 2022/09/06 01:59:09 - mmengine - INFO - Epoch(train) [76][340/940] lr: 1.0000e-03 eta: 5:18:31 time: 1.0461 data_time: 0.6273 memory: 22701 grad_norm: 5.2808 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0279 loss: 1.0279 2022/09/06 01:59:24 - mmengine - INFO - Epoch(train) [76][360/940] lr: 1.0000e-03 eta: 5:18:14 time: 0.7407 data_time: 0.2699 memory: 22701 grad_norm: 5.3468 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0567 loss: 1.0567 2022/09/06 01:59:44 - mmengine - INFO - Epoch(train) [76][380/940] lr: 1.0000e-03 eta: 5:17:58 time: 0.9928 data_time: 0.5789 memory: 22701 grad_norm: 5.3184 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9935 loss: 0.9935 2022/09/06 01:59:59 - mmengine - INFO - Epoch(train) [76][400/940] lr: 1.0000e-03 eta: 5:17:41 time: 0.7178 data_time: 0.3053 memory: 22701 grad_norm: 5.2609 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9084 loss: 0.9084 2022/09/06 02:00:20 - mmengine - INFO - Epoch(train) [76][420/940] lr: 1.0000e-03 eta: 5:17:26 time: 1.0577 data_time: 0.3130 memory: 22701 grad_norm: 5.1555 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.8962 loss: 0.8962 2022/09/06 02:00:34 - mmengine - INFO - Epoch(train) [76][440/940] lr: 1.0000e-03 eta: 5:17:09 time: 0.7157 data_time: 0.2050 memory: 22701 grad_norm: 5.3552 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9958 loss: 0.9958 2022/09/06 02:00:50 - mmengine - INFO - Epoch(train) [76][460/940] lr: 1.0000e-03 eta: 5:16:52 time: 0.8086 data_time: 0.2178 memory: 22701 grad_norm: 5.3244 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0451 loss: 1.0451 2022/09/06 02:01:04 - mmengine - INFO - Epoch(train) [76][480/940] lr: 1.0000e-03 eta: 5:16:35 time: 0.6776 data_time: 0.2740 memory: 22701 grad_norm: 5.2612 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.0615 loss: 1.0615 2022/09/06 02:01:21 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:01:21 - mmengine - INFO - Epoch(train) [76][500/940] lr: 1.0000e-03 eta: 5:16:19 time: 0.8411 data_time: 0.4197 memory: 22701 grad_norm: 5.2616 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0522 loss: 1.0522 2022/09/06 02:01:34 - mmengine - INFO - Epoch(train) [76][520/940] lr: 1.0000e-03 eta: 5:16:01 time: 0.6712 data_time: 0.2277 memory: 22701 grad_norm: 5.2303 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0860 loss: 1.0860 2022/09/06 02:01:51 - mmengine - INFO - Epoch(train) [76][540/940] lr: 1.0000e-03 eta: 5:15:45 time: 0.8720 data_time: 0.3993 memory: 22701 grad_norm: 5.3083 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9973 loss: 0.9973 2022/09/06 02:02:05 - mmengine - INFO - Epoch(train) [76][560/940] lr: 1.0000e-03 eta: 5:15:27 time: 0.6534 data_time: 0.2648 memory: 22701 grad_norm: 5.3365 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1312 loss: 1.1312 2022/09/06 02:02:21 - mmengine - INFO - Epoch(train) [76][580/940] lr: 1.0000e-03 eta: 5:15:11 time: 0.8363 data_time: 0.4235 memory: 22701 grad_norm: 5.3424 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9830 loss: 0.9830 2022/09/06 02:02:36 - mmengine - INFO - Epoch(train) [76][600/940] lr: 1.0000e-03 eta: 5:14:54 time: 0.7387 data_time: 0.3375 memory: 22701 grad_norm: 5.3378 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0203 loss: 1.0203 2022/09/06 02:02:53 - mmengine - INFO - Epoch(train) [76][620/940] lr: 1.0000e-03 eta: 5:14:38 time: 0.8690 data_time: 0.4634 memory: 22701 grad_norm: 5.3506 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0973 loss: 1.0973 2022/09/06 02:03:12 - mmengine - INFO - Epoch(train) [76][640/940] lr: 1.0000e-03 eta: 5:14:22 time: 0.9461 data_time: 0.5455 memory: 22701 grad_norm: 5.1826 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8767 loss: 0.8767 2022/09/06 02:03:29 - mmengine - INFO - Epoch(train) [76][660/940] lr: 1.0000e-03 eta: 5:14:05 time: 0.8562 data_time: 0.4594 memory: 22701 grad_norm: 5.1833 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0728 loss: 1.0728 2022/09/06 02:03:47 - mmengine - INFO - Epoch(train) [76][680/940] lr: 1.0000e-03 eta: 5:13:49 time: 0.8933 data_time: 0.4973 memory: 22701 grad_norm: 5.2819 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9911 loss: 0.9911 2022/09/06 02:04:06 - mmengine - INFO - Epoch(train) [76][700/940] lr: 1.0000e-03 eta: 5:13:33 time: 0.9067 data_time: 0.5333 memory: 22701 grad_norm: 5.4133 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1091 loss: 1.1091 2022/09/06 02:04:22 - mmengine - INFO - Epoch(train) [76][720/940] lr: 1.0000e-03 eta: 5:13:17 time: 0.8002 data_time: 0.4079 memory: 22701 grad_norm: 5.3771 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1079 loss: 1.1079 2022/09/06 02:04:38 - mmengine - INFO - Epoch(train) [76][740/940] lr: 1.0000e-03 eta: 5:13:00 time: 0.8152 data_time: 0.4301 memory: 22701 grad_norm: 5.2710 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0186 loss: 1.0186 2022/09/06 02:04:55 - mmengine - INFO - Epoch(train) [76][760/940] lr: 1.0000e-03 eta: 5:12:44 time: 0.8688 data_time: 0.4491 memory: 22701 grad_norm: 5.2963 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 1.1235 loss: 1.1235 2022/09/06 02:05:10 - mmengine - INFO - Epoch(train) [76][780/940] lr: 1.0000e-03 eta: 5:12:27 time: 0.7478 data_time: 0.3434 memory: 22701 grad_norm: 5.3672 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0256 loss: 1.0256 2022/09/06 02:05:27 - mmengine - INFO - Epoch(train) [76][800/940] lr: 1.0000e-03 eta: 5:12:11 time: 0.8542 data_time: 0.4119 memory: 22701 grad_norm: 5.3107 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.0258 loss: 1.0258 2022/09/06 02:05:41 - mmengine - INFO - Epoch(train) [76][820/940] lr: 1.0000e-03 eta: 5:11:53 time: 0.7070 data_time: 0.3227 memory: 22701 grad_norm: 5.2593 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8837 loss: 0.8837 2022/09/06 02:06:01 - mmengine - INFO - Epoch(train) [76][840/940] lr: 1.0000e-03 eta: 5:11:38 time: 0.9749 data_time: 0.4331 memory: 22701 grad_norm: 5.3976 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9984 loss: 0.9984 2022/09/06 02:06:18 - mmengine - INFO - Epoch(train) [76][860/940] lr: 1.0000e-03 eta: 5:11:21 time: 0.8412 data_time: 0.1721 memory: 22701 grad_norm: 5.2616 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9361 loss: 0.9361 2022/09/06 02:06:37 - mmengine - INFO - Epoch(train) [76][880/940] lr: 1.0000e-03 eta: 5:11:06 time: 0.9605 data_time: 0.4525 memory: 22701 grad_norm: 5.2785 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0489 loss: 1.0489 2022/09/06 02:06:55 - mmengine - INFO - Epoch(train) [76][900/940] lr: 1.0000e-03 eta: 5:10:50 time: 0.9266 data_time: 0.5531 memory: 22701 grad_norm: 5.4331 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0230 loss: 1.0230 2022/09/06 02:07:12 - mmengine - INFO - Epoch(train) [76][920/940] lr: 1.0000e-03 eta: 5:10:34 time: 0.8462 data_time: 0.4081 memory: 22701 grad_norm: 5.2862 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9559 loss: 0.9559 2022/09/06 02:07:28 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:07:28 - mmengine - INFO - Epoch(train) [76][940/940] lr: 1.0000e-03 eta: 5:10:17 time: 0.7896 data_time: 0.4025 memory: 22701 grad_norm: 5.8149 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1563 loss: 1.1563 2022/09/06 02:07:42 - mmengine - INFO - Epoch(val) [76][20/78] eta: 0:00:40 time: 0.6944 data_time: 0.5733 memory: 2247 2022/09/06 02:07:52 - mmengine - INFO - Epoch(val) [76][40/78] eta: 0:00:17 time: 0.4673 data_time: 0.3470 memory: 2247 2022/09/06 02:08:04 - mmengine - INFO - Epoch(val) [76][60/78] eta: 0:00:11 time: 0.6405 data_time: 0.5217 memory: 2247 2022/09/06 02:08:15 - mmengine - INFO - Epoch(val) [76][78/78] acc/top1: 0.6872 acc/top5: 0.8809 acc/mean1: 0.6870 2022/09/06 02:08:36 - mmengine - INFO - Epoch(train) [77][20/940] lr: 1.0000e-03 eta: 5:10:02 time: 1.0694 data_time: 0.5104 memory: 22701 grad_norm: 5.2245 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9465 loss: 0.9465 2022/09/06 02:08:50 - mmengine - INFO - Epoch(train) [77][40/940] lr: 1.0000e-03 eta: 5:09:44 time: 0.6851 data_time: 0.0838 memory: 22701 grad_norm: 5.2813 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9452 loss: 0.9452 2022/09/06 02:09:05 - mmengine - INFO - Epoch(train) [77][60/940] lr: 1.0000e-03 eta: 5:09:28 time: 0.7782 data_time: 0.2157 memory: 22701 grad_norm: 5.3568 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9129 loss: 0.9129 2022/09/06 02:09:19 - mmengine - INFO - Epoch(train) [77][80/940] lr: 1.0000e-03 eta: 5:09:10 time: 0.7023 data_time: 0.2045 memory: 22701 grad_norm: 5.3444 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9822 loss: 0.9822 2022/09/06 02:09:37 - mmengine - INFO - Epoch(train) [77][100/940] lr: 1.0000e-03 eta: 5:08:54 time: 0.8950 data_time: 0.2939 memory: 22701 grad_norm: 5.2229 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9121 loss: 0.9121 2022/09/06 02:09:51 - mmengine - INFO - Epoch(train) [77][120/940] lr: 1.0000e-03 eta: 5:08:37 time: 0.7008 data_time: 0.1072 memory: 22701 grad_norm: 5.1995 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9685 loss: 0.9685 2022/09/06 02:10:10 - mmengine - INFO - Epoch(train) [77][140/940] lr: 1.0000e-03 eta: 5:08:21 time: 0.9430 data_time: 0.2539 memory: 22701 grad_norm: 5.3556 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.9473 loss: 0.9473 2022/09/06 02:10:27 - mmengine - INFO - Epoch(train) [77][160/940] lr: 1.0000e-03 eta: 5:08:05 time: 0.8549 data_time: 0.4009 memory: 22701 grad_norm: 5.1735 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0053 loss: 1.0053 2022/09/06 02:10:48 - mmengine - INFO - Epoch(train) [77][180/940] lr: 1.0000e-03 eta: 5:07:50 time: 1.0350 data_time: 0.2331 memory: 22701 grad_norm: 5.1797 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8743 loss: 0.8743 2022/09/06 02:11:06 - mmengine - INFO - Epoch(train) [77][200/940] lr: 1.0000e-03 eta: 5:07:34 time: 0.9190 data_time: 0.1890 memory: 22701 grad_norm: 5.2485 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9645 loss: 0.9645 2022/09/06 02:11:26 - mmengine - INFO - Epoch(train) [77][220/940] lr: 1.0000e-03 eta: 5:07:18 time: 0.9788 data_time: 0.0974 memory: 22701 grad_norm: 5.2476 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9815 loss: 0.9815 2022/09/06 02:11:44 - mmengine - INFO - Epoch(train) [77][240/940] lr: 1.0000e-03 eta: 5:07:02 time: 0.8904 data_time: 0.1993 memory: 22701 grad_norm: 5.3239 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0245 loss: 1.0245 2022/09/06 02:12:02 - mmengine - INFO - Epoch(train) [77][260/940] lr: 1.0000e-03 eta: 5:06:46 time: 0.9282 data_time: 0.1264 memory: 22701 grad_norm: 5.2969 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0731 loss: 1.0731 2022/09/06 02:12:17 - mmengine - INFO - Epoch(train) [77][280/940] lr: 1.0000e-03 eta: 5:06:29 time: 0.7502 data_time: 0.1178 memory: 22701 grad_norm: 5.3296 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9414 loss: 0.9414 2022/09/06 02:12:35 - mmengine - INFO - Epoch(train) [77][300/940] lr: 1.0000e-03 eta: 5:06:13 time: 0.9034 data_time: 0.1319 memory: 22701 grad_norm: 5.2393 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0089 loss: 1.0089 2022/09/06 02:12:53 - mmengine - INFO - Epoch(train) [77][320/940] lr: 1.0000e-03 eta: 5:05:57 time: 0.8944 data_time: 0.1785 memory: 22701 grad_norm: 5.3589 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9688 loss: 0.9688 2022/09/06 02:13:12 - mmengine - INFO - Epoch(train) [77][340/940] lr: 1.0000e-03 eta: 5:05:41 time: 0.9349 data_time: 0.1594 memory: 22701 grad_norm: 5.2875 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9820 loss: 0.9820 2022/09/06 02:13:33 - mmengine - INFO - Epoch(train) [77][360/940] lr: 1.0000e-03 eta: 5:05:26 time: 1.0272 data_time: 0.2379 memory: 22701 grad_norm: 5.3719 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0430 loss: 1.0430 2022/09/06 02:13:51 - mmengine - INFO - Epoch(train) [77][380/940] lr: 1.0000e-03 eta: 5:05:10 time: 0.9413 data_time: 0.0697 memory: 22701 grad_norm: 5.3903 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0732 loss: 1.0732 2022/09/06 02:14:09 - mmengine - INFO - Epoch(train) [77][400/940] lr: 1.0000e-03 eta: 5:04:54 time: 0.9064 data_time: 0.1757 memory: 22701 grad_norm: 5.3508 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9287 loss: 0.9287 2022/09/06 02:14:26 - mmengine - INFO - Epoch(train) [77][420/940] lr: 1.0000e-03 eta: 5:04:38 time: 0.8490 data_time: 0.0365 memory: 22701 grad_norm: 5.3915 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0299 loss: 1.0299 2022/09/06 02:14:43 - mmengine - INFO - Epoch(train) [77][440/940] lr: 1.0000e-03 eta: 5:04:21 time: 0.8022 data_time: 0.2694 memory: 22701 grad_norm: 5.3108 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9835 loss: 0.9835 2022/09/06 02:14:59 - mmengine - INFO - Epoch(train) [77][460/940] lr: 1.0000e-03 eta: 5:04:05 time: 0.8055 data_time: 0.2751 memory: 22701 grad_norm: 5.1391 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9884 loss: 0.9884 2022/09/06 02:15:14 - mmengine - INFO - Epoch(train) [77][480/940] lr: 1.0000e-03 eta: 5:03:48 time: 0.7841 data_time: 0.2066 memory: 22701 grad_norm: 5.3684 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9602 loss: 0.9602 2022/09/06 02:15:32 - mmengine - INFO - Epoch(train) [77][500/940] lr: 1.0000e-03 eta: 5:03:32 time: 0.8874 data_time: 0.2631 memory: 22701 grad_norm: 5.4019 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.9414 loss: 0.9414 2022/09/06 02:15:49 - mmengine - INFO - Epoch(train) [77][520/940] lr: 1.0000e-03 eta: 5:03:15 time: 0.8373 data_time: 0.2152 memory: 22701 grad_norm: 5.3376 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9435 loss: 0.9435 2022/09/06 02:16:06 - mmengine - INFO - Epoch(train) [77][540/940] lr: 1.0000e-03 eta: 5:02:59 time: 0.8457 data_time: 0.4199 memory: 22701 grad_norm: 5.2622 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0273 loss: 1.0273 2022/09/06 02:16:22 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:16:22 - mmengine - INFO - Epoch(train) [77][560/940] lr: 1.0000e-03 eta: 5:02:42 time: 0.8019 data_time: 0.3632 memory: 22701 grad_norm: 5.3158 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9924 loss: 0.9924 2022/09/06 02:16:38 - mmengine - INFO - Epoch(train) [77][580/940] lr: 1.0000e-03 eta: 5:02:26 time: 0.7895 data_time: 0.4006 memory: 22701 grad_norm: 5.3256 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9850 loss: 0.9850 2022/09/06 02:16:53 - mmengine - INFO - Epoch(train) [77][600/940] lr: 1.0000e-03 eta: 5:02:09 time: 0.7800 data_time: 0.3742 memory: 22701 grad_norm: 5.3351 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0495 loss: 1.0495 2022/09/06 02:17:10 - mmengine - INFO - Epoch(train) [77][620/940] lr: 1.0000e-03 eta: 5:01:52 time: 0.8515 data_time: 0.4298 memory: 22701 grad_norm: 5.3168 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9162 loss: 0.9162 2022/09/06 02:17:24 - mmengine - INFO - Epoch(train) [77][640/940] lr: 1.0000e-03 eta: 5:01:35 time: 0.7113 data_time: 0.3216 memory: 22701 grad_norm: 5.3436 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9798 loss: 0.9798 2022/09/06 02:17:43 - mmengine - INFO - Epoch(train) [77][660/940] lr: 1.0000e-03 eta: 5:01:19 time: 0.9262 data_time: 0.4998 memory: 22701 grad_norm: 5.3748 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0097 loss: 1.0097 2022/09/06 02:18:01 - mmengine - INFO - Epoch(train) [77][680/940] lr: 1.0000e-03 eta: 5:01:03 time: 0.9114 data_time: 0.3440 memory: 22701 grad_norm: 5.3487 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1458 loss: 1.1458 2022/09/06 02:18:20 - mmengine - INFO - Epoch(train) [77][700/940] lr: 1.0000e-03 eta: 5:00:48 time: 0.9456 data_time: 0.2798 memory: 22701 grad_norm: 5.3434 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.9234 loss: 0.9234 2022/09/06 02:18:42 - mmengine - INFO - Epoch(train) [77][720/940] lr: 1.0000e-03 eta: 5:00:33 time: 1.0758 data_time: 0.0510 memory: 22701 grad_norm: 5.3826 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9772 loss: 0.9772 2022/09/06 02:18:59 - mmengine - INFO - Epoch(train) [77][740/940] lr: 1.0000e-03 eta: 5:00:16 time: 0.8572 data_time: 0.0290 memory: 22701 grad_norm: 5.3878 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0505 loss: 1.0505 2022/09/06 02:19:18 - mmengine - INFO - Epoch(train) [77][760/940] lr: 1.0000e-03 eta: 5:00:00 time: 0.9506 data_time: 0.0254 memory: 22701 grad_norm: 5.3117 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 0.9923 loss: 0.9923 2022/09/06 02:19:34 - mmengine - INFO - Epoch(train) [77][780/940] lr: 1.0000e-03 eta: 4:59:44 time: 0.8220 data_time: 0.0327 memory: 22701 grad_norm: 5.4638 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1386 loss: 1.1386 2022/09/06 02:19:53 - mmengine - INFO - Epoch(train) [77][800/940] lr: 1.0000e-03 eta: 4:59:28 time: 0.9527 data_time: 0.0321 memory: 22701 grad_norm: 5.2335 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0750 loss: 1.0750 2022/09/06 02:20:07 - mmengine - INFO - Epoch(train) [77][820/940] lr: 1.0000e-03 eta: 4:59:11 time: 0.6901 data_time: 0.0276 memory: 22701 grad_norm: 5.3889 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9943 loss: 0.9943 2022/09/06 02:20:26 - mmengine - INFO - Epoch(train) [77][840/940] lr: 1.0000e-03 eta: 4:58:55 time: 0.9637 data_time: 0.0307 memory: 22701 grad_norm: 5.3252 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9652 loss: 0.9652 2022/09/06 02:20:41 - mmengine - INFO - Epoch(train) [77][860/940] lr: 1.0000e-03 eta: 4:58:38 time: 0.7485 data_time: 0.0283 memory: 22701 grad_norm: 5.5091 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.0746 loss: 1.0746 2022/09/06 02:20:58 - mmengine - INFO - Epoch(train) [77][880/940] lr: 1.0000e-03 eta: 4:58:22 time: 0.8533 data_time: 0.0342 memory: 22701 grad_norm: 5.4107 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0449 loss: 1.0449 2022/09/06 02:21:12 - mmengine - INFO - Epoch(train) [77][900/940] lr: 1.0000e-03 eta: 4:58:04 time: 0.6721 data_time: 0.0303 memory: 22701 grad_norm: 5.4194 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1333 loss: 1.1333 2022/09/06 02:21:30 - mmengine - INFO - Epoch(train) [77][920/940] lr: 1.0000e-03 eta: 4:57:48 time: 0.9114 data_time: 0.0349 memory: 22701 grad_norm: 5.3803 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0050 loss: 1.0050 2022/09/06 02:21:45 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:21:45 - mmengine - INFO - Epoch(train) [77][940/940] lr: 1.0000e-03 eta: 4:57:31 time: 0.7269 data_time: 0.0260 memory: 22701 grad_norm: 5.8432 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.9215 loss: 0.9215 2022/09/06 02:21:58 - mmengine - INFO - Epoch(val) [77][20/78] eta: 0:00:39 time: 0.6890 data_time: 0.5714 memory: 2247 2022/09/06 02:22:07 - mmengine - INFO - Epoch(val) [77][40/78] eta: 0:00:16 time: 0.4422 data_time: 0.3248 memory: 2247 2022/09/06 02:22:21 - mmengine - INFO - Epoch(val) [77][60/78] eta: 0:00:12 time: 0.6736 data_time: 0.5353 memory: 2247 2022/09/06 02:22:31 - mmengine - INFO - Epoch(val) [77][78/78] acc/top1: 0.6841 acc/top5: 0.8804 acc/mean1: 0.6840 2022/09/06 02:22:52 - mmengine - INFO - Epoch(train) [78][20/940] lr: 1.0000e-03 eta: 4:57:16 time: 1.0546 data_time: 0.6645 memory: 22701 grad_norm: 5.3410 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9541 loss: 0.9541 2022/09/06 02:23:07 - mmengine - INFO - Epoch(train) [78][40/940] lr: 1.0000e-03 eta: 4:56:59 time: 0.7263 data_time: 0.3439 memory: 22701 grad_norm: 5.3915 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 0.9349 loss: 0.9349 2022/09/06 02:23:24 - mmengine - INFO - Epoch(train) [78][60/940] lr: 1.0000e-03 eta: 4:56:43 time: 0.8693 data_time: 0.4285 memory: 22701 grad_norm: 5.2069 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9494 loss: 0.9494 2022/09/06 02:23:39 - mmengine - INFO - Epoch(train) [78][80/940] lr: 1.0000e-03 eta: 4:56:26 time: 0.7286 data_time: 0.3424 memory: 22701 grad_norm: 5.2990 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9820 loss: 0.9820 2022/09/06 02:23:57 - mmengine - INFO - Epoch(train) [78][100/940] lr: 1.0000e-03 eta: 4:56:10 time: 0.9328 data_time: 0.3945 memory: 22701 grad_norm: 5.3686 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.9759 loss: 0.9759 2022/09/06 02:24:12 - mmengine - INFO - Epoch(train) [78][120/940] lr: 1.0000e-03 eta: 4:55:53 time: 0.7321 data_time: 0.2441 memory: 22701 grad_norm: 5.2991 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.8797 loss: 0.8797 2022/09/06 02:24:29 - mmengine - INFO - Epoch(train) [78][140/940] lr: 1.0000e-03 eta: 4:55:36 time: 0.8560 data_time: 0.3006 memory: 22701 grad_norm: 5.4543 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9168 loss: 0.9168 2022/09/06 02:24:46 - mmengine - INFO - Epoch(train) [78][160/940] lr: 1.0000e-03 eta: 4:55:20 time: 0.8266 data_time: 0.2526 memory: 22701 grad_norm: 5.3159 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9988 loss: 0.9988 2022/09/06 02:25:06 - mmengine - INFO - Epoch(train) [78][180/940] lr: 1.0000e-03 eta: 4:55:05 time: 1.0306 data_time: 0.3966 memory: 22701 grad_norm: 5.2022 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.9940 loss: 0.9940 2022/09/06 02:25:24 - mmengine - INFO - Epoch(train) [78][200/940] lr: 1.0000e-03 eta: 4:54:48 time: 0.8738 data_time: 0.0290 memory: 22701 grad_norm: 5.3431 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9880 loss: 0.9880 2022/09/06 02:25:44 - mmengine - INFO - Epoch(train) [78][220/940] lr: 1.0000e-03 eta: 4:54:33 time: 1.0041 data_time: 0.0297 memory: 22701 grad_norm: 5.3461 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0402 loss: 1.0402 2022/09/06 02:26:02 - mmengine - INFO - Epoch(train) [78][240/940] lr: 1.0000e-03 eta: 4:54:17 time: 0.8950 data_time: 0.0576 memory: 22701 grad_norm: 5.3222 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 1.0128 loss: 1.0128 2022/09/06 02:26:21 - mmengine - INFO - Epoch(train) [78][260/940] lr: 1.0000e-03 eta: 4:54:01 time: 0.9692 data_time: 0.0280 memory: 22701 grad_norm: 5.4015 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9202 loss: 0.9202 2022/09/06 02:26:36 - mmengine - INFO - Epoch(train) [78][280/940] lr: 1.0000e-03 eta: 4:53:44 time: 0.7143 data_time: 0.0257 memory: 22701 grad_norm: 5.4689 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0264 loss: 1.0264 2022/09/06 02:26:53 - mmengine - INFO - Epoch(train) [78][300/940] lr: 1.0000e-03 eta: 4:53:28 time: 0.8837 data_time: 0.0274 memory: 22701 grad_norm: 5.4017 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0337 loss: 1.0337 2022/09/06 02:27:10 - mmengine - INFO - Epoch(train) [78][320/940] lr: 1.0000e-03 eta: 4:53:11 time: 0.8401 data_time: 0.1591 memory: 22701 grad_norm: 5.4041 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0432 loss: 1.0432 2022/09/06 02:27:32 - mmengine - INFO - Epoch(train) [78][340/940] lr: 1.0000e-03 eta: 4:52:56 time: 1.0778 data_time: 0.0507 memory: 22701 grad_norm: 5.3345 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9707 loss: 0.9707 2022/09/06 02:27:50 - mmengine - INFO - Epoch(train) [78][360/940] lr: 1.0000e-03 eta: 4:52:40 time: 0.9224 data_time: 0.0219 memory: 22701 grad_norm: 5.3415 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9315 loss: 0.9315 2022/09/06 02:28:13 - mmengine - INFO - Epoch(train) [78][380/940] lr: 1.0000e-03 eta: 4:52:26 time: 1.1297 data_time: 0.0357 memory: 22701 grad_norm: 5.3308 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8934 loss: 0.8934 2022/09/06 02:28:32 - mmengine - INFO - Epoch(train) [78][400/940] lr: 1.0000e-03 eta: 4:52:10 time: 0.9919 data_time: 0.0243 memory: 22701 grad_norm: 5.3335 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9936 loss: 0.9936 2022/09/06 02:28:49 - mmengine - INFO - Epoch(train) [78][420/940] lr: 1.0000e-03 eta: 4:51:53 time: 0.8232 data_time: 0.0263 memory: 22701 grad_norm: 5.2456 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0007 loss: 1.0007 2022/09/06 02:29:05 - mmengine - INFO - Epoch(train) [78][440/940] lr: 1.0000e-03 eta: 4:51:37 time: 0.8001 data_time: 0.0499 memory: 22701 grad_norm: 5.2449 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9382 loss: 0.9382 2022/09/06 02:29:22 - mmengine - INFO - Epoch(train) [78][460/940] lr: 1.0000e-03 eta: 4:51:20 time: 0.8478 data_time: 0.0294 memory: 22701 grad_norm: 5.4460 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1871 loss: 1.1871 2022/09/06 02:29:37 - mmengine - INFO - Epoch(train) [78][480/940] lr: 1.0000e-03 eta: 4:51:03 time: 0.7543 data_time: 0.0337 memory: 22701 grad_norm: 5.4529 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0071 loss: 1.0071 2022/09/06 02:29:52 - mmengine - INFO - Epoch(train) [78][500/940] lr: 1.0000e-03 eta: 4:50:47 time: 0.7494 data_time: 0.0488 memory: 22701 grad_norm: 5.1988 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8575 loss: 0.8575 2022/09/06 02:30:11 - mmengine - INFO - Epoch(train) [78][520/940] lr: 1.0000e-03 eta: 4:50:31 time: 0.9533 data_time: 0.0273 memory: 22701 grad_norm: 5.2746 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0668 loss: 1.0668 2022/09/06 02:30:27 - mmengine - INFO - Epoch(train) [78][540/940] lr: 1.0000e-03 eta: 4:50:14 time: 0.7828 data_time: 0.0319 memory: 22701 grad_norm: 5.3475 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9948 loss: 0.9948 2022/09/06 02:30:49 - mmengine - INFO - Epoch(train) [78][560/940] lr: 1.0000e-03 eta: 4:49:59 time: 1.0986 data_time: 0.0243 memory: 22701 grad_norm: 5.5225 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8725 loss: 0.8725 2022/09/06 02:31:07 - mmengine - INFO - Epoch(train) [78][580/940] lr: 1.0000e-03 eta: 4:49:43 time: 0.9076 data_time: 0.0230 memory: 22701 grad_norm: 5.4163 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0011 loss: 1.0011 2022/09/06 02:31:25 - mmengine - INFO - Epoch(train) [78][600/940] lr: 1.0000e-03 eta: 4:49:27 time: 0.8917 data_time: 0.0358 memory: 22701 grad_norm: 5.2291 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9260 loss: 0.9260 2022/09/06 02:31:44 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:31:44 - mmengine - INFO - Epoch(train) [78][620/940] lr: 1.0000e-03 eta: 4:49:11 time: 0.9691 data_time: 0.0916 memory: 22701 grad_norm: 5.2729 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1373 loss: 1.1373 2022/09/06 02:32:01 - mmengine - INFO - Epoch(train) [78][640/940] lr: 1.0000e-03 eta: 4:48:55 time: 0.8611 data_time: 0.0746 memory: 22701 grad_norm: 5.3918 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0321 loss: 1.0321 2022/09/06 02:32:18 - mmengine - INFO - Epoch(train) [78][660/940] lr: 1.0000e-03 eta: 4:48:38 time: 0.8119 data_time: 0.1287 memory: 22701 grad_norm: 5.3800 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0747 loss: 1.0747 2022/09/06 02:32:34 - mmengine - INFO - Epoch(train) [78][680/940] lr: 1.0000e-03 eta: 4:48:22 time: 0.8356 data_time: 0.1334 memory: 22701 grad_norm: 5.2863 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.9780 loss: 0.9780 2022/09/06 02:32:52 - mmengine - INFO - Epoch(train) [78][700/940] lr: 1.0000e-03 eta: 4:48:05 time: 0.8770 data_time: 0.4326 memory: 22701 grad_norm: 5.4153 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1495 loss: 1.1495 2022/09/06 02:33:06 - mmengine - INFO - Epoch(train) [78][720/940] lr: 1.0000e-03 eta: 4:47:48 time: 0.7090 data_time: 0.3174 memory: 22701 grad_norm: 5.3779 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0278 loss: 1.0278 2022/09/06 02:33:24 - mmengine - INFO - Epoch(train) [78][740/940] lr: 1.0000e-03 eta: 4:47:32 time: 0.9012 data_time: 0.5087 memory: 22701 grad_norm: 5.3347 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9499 loss: 0.9499 2022/09/06 02:33:37 - mmengine - INFO - Epoch(train) [78][760/940] lr: 1.0000e-03 eta: 4:47:15 time: 0.6670 data_time: 0.2707 memory: 22701 grad_norm: 5.3974 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9821 loss: 0.9821 2022/09/06 02:33:56 - mmengine - INFO - Epoch(train) [78][780/940] lr: 1.0000e-03 eta: 4:46:59 time: 0.9057 data_time: 0.4446 memory: 22701 grad_norm: 5.3584 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.0169 loss: 1.0169 2022/09/06 02:34:11 - mmengine - INFO - Epoch(train) [78][800/940] lr: 1.0000e-03 eta: 4:46:42 time: 0.7713 data_time: 0.3599 memory: 22701 grad_norm: 5.4407 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0323 loss: 1.0323 2022/09/06 02:34:32 - mmengine - INFO - Epoch(train) [78][820/940] lr: 1.0000e-03 eta: 4:46:27 time: 1.0680 data_time: 0.6349 memory: 22701 grad_norm: 5.2973 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9102 loss: 0.9102 2022/09/06 02:34:50 - mmengine - INFO - Epoch(train) [78][840/940] lr: 1.0000e-03 eta: 4:46:10 time: 0.8635 data_time: 0.4825 memory: 22701 grad_norm: 5.2797 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9299 loss: 0.9299 2022/09/06 02:35:12 - mmengine - INFO - Epoch(train) [78][860/940] lr: 1.0000e-03 eta: 4:45:55 time: 1.1080 data_time: 0.7042 memory: 22701 grad_norm: 5.2799 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9581 loss: 0.9581 2022/09/06 02:35:27 - mmengine - INFO - Epoch(train) [78][880/940] lr: 1.0000e-03 eta: 4:45:39 time: 0.7855 data_time: 0.4080 memory: 22701 grad_norm: 5.3636 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9851 loss: 0.9851 2022/09/06 02:35:50 - mmengine - INFO - Epoch(train) [78][900/940] lr: 1.0000e-03 eta: 4:45:24 time: 1.1088 data_time: 0.6922 memory: 22701 grad_norm: 5.4313 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 0.9647 loss: 0.9647 2022/09/06 02:36:05 - mmengine - INFO - Epoch(train) [78][920/940] lr: 1.0000e-03 eta: 4:45:07 time: 0.7450 data_time: 0.3335 memory: 22701 grad_norm: 5.3831 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1025 loss: 1.1025 2022/09/06 02:36:20 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:36:20 - mmengine - INFO - Epoch(train) [78][940/940] lr: 1.0000e-03 eta: 4:44:50 time: 0.7711 data_time: 0.4098 memory: 22701 grad_norm: 5.7423 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 1.0911 loss: 1.0911 2022/09/06 02:36:20 - mmengine - INFO - Saving checkpoint at 78 epochs 2022/09/06 02:36:36 - mmengine - INFO - Epoch(val) [78][20/78] eta: 0:00:40 time: 0.7060 data_time: 0.5885 memory: 2247 2022/09/06 02:36:45 - mmengine - INFO - Epoch(val) [78][40/78] eta: 0:00:16 time: 0.4437 data_time: 0.3296 memory: 2247 2022/09/06 02:36:58 - mmengine - INFO - Epoch(val) [78][60/78] eta: 0:00:11 time: 0.6603 data_time: 0.5438 memory: 2247 2022/09/06 02:37:07 - mmengine - INFO - Epoch(val) [78][78/78] acc/top1: 0.6848 acc/top5: 0.8797 acc/mean1: 0.6847 2022/09/06 02:37:31 - mmengine - INFO - Epoch(train) [79][20/940] lr: 1.0000e-03 eta: 4:44:35 time: 1.1778 data_time: 0.5051 memory: 22701 grad_norm: 5.3113 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0343 loss: 1.0343 2022/09/06 02:37:46 - mmengine - INFO - Epoch(train) [79][40/940] lr: 1.0000e-03 eta: 4:44:19 time: 0.7682 data_time: 0.0378 memory: 22701 grad_norm: 5.3596 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0125 loss: 1.0125 2022/09/06 02:38:06 - mmengine - INFO - Epoch(train) [79][60/940] lr: 1.0000e-03 eta: 4:44:03 time: 0.9655 data_time: 0.0228 memory: 22701 grad_norm: 5.3993 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0655 loss: 1.0655 2022/09/06 02:38:20 - mmengine - INFO - Epoch(train) [79][80/940] lr: 1.0000e-03 eta: 4:43:46 time: 0.7304 data_time: 0.0202 memory: 22701 grad_norm: 5.2625 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9612 loss: 0.9612 2022/09/06 02:38:37 - mmengine - INFO - Epoch(train) [79][100/940] lr: 1.0000e-03 eta: 4:43:29 time: 0.8501 data_time: 0.0243 memory: 22701 grad_norm: 5.2629 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9882 loss: 0.9882 2022/09/06 02:38:52 - mmengine - INFO - Epoch(train) [79][120/940] lr: 1.0000e-03 eta: 4:43:12 time: 0.7527 data_time: 0.0366 memory: 22701 grad_norm: 5.4272 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9865 loss: 0.9865 2022/09/06 02:39:09 - mmengine - INFO - Epoch(train) [79][140/940] lr: 1.0000e-03 eta: 4:42:56 time: 0.8304 data_time: 0.0320 memory: 22701 grad_norm: 5.3089 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0019 loss: 1.0019 2022/09/06 02:39:26 - mmengine - INFO - Epoch(train) [79][160/940] lr: 1.0000e-03 eta: 4:42:39 time: 0.8220 data_time: 0.0231 memory: 22701 grad_norm: 5.3702 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1146 loss: 1.1146 2022/09/06 02:39:45 - mmengine - INFO - Epoch(train) [79][180/940] lr: 1.0000e-03 eta: 4:42:24 time: 1.0007 data_time: 0.0285 memory: 22701 grad_norm: 5.2543 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9916 loss: 0.9916 2022/09/06 02:40:05 - mmengine - INFO - Epoch(train) [79][200/940] lr: 1.0000e-03 eta: 4:42:08 time: 0.9711 data_time: 0.0370 memory: 22701 grad_norm: 5.2975 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9075 loss: 0.9075 2022/09/06 02:40:27 - mmengine - INFO - Epoch(train) [79][220/940] lr: 1.0000e-03 eta: 4:41:53 time: 1.0966 data_time: 0.0254 memory: 22701 grad_norm: 5.3358 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0590 loss: 1.0590 2022/09/06 02:40:44 - mmengine - INFO - Epoch(train) [79][240/940] lr: 1.0000e-03 eta: 4:41:37 time: 0.8587 data_time: 0.0202 memory: 22701 grad_norm: 5.4704 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0889 loss: 1.0889 2022/09/06 02:41:03 - mmengine - INFO - Epoch(train) [79][260/940] lr: 1.0000e-03 eta: 4:41:21 time: 0.9319 data_time: 0.0249 memory: 22701 grad_norm: 5.3776 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1438 loss: 1.1438 2022/09/06 02:41:18 - mmengine - INFO - Epoch(train) [79][280/940] lr: 1.0000e-03 eta: 4:41:04 time: 0.7622 data_time: 0.0193 memory: 22701 grad_norm: 5.2884 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9215 loss: 0.9215 2022/09/06 02:41:38 - mmengine - INFO - Epoch(train) [79][300/940] lr: 1.0000e-03 eta: 4:40:48 time: 0.9855 data_time: 0.0269 memory: 22701 grad_norm: 5.3377 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0708 loss: 1.0708 2022/09/06 02:41:52 - mmengine - INFO - Epoch(train) [79][320/940] lr: 1.0000e-03 eta: 4:40:31 time: 0.7213 data_time: 0.0222 memory: 22701 grad_norm: 5.3734 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9999 loss: 0.9999 2022/09/06 02:42:12 - mmengine - INFO - Epoch(train) [79][340/940] lr: 1.0000e-03 eta: 4:40:16 time: 1.0253 data_time: 0.0260 memory: 22701 grad_norm: 5.3301 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0116 loss: 1.0116 2022/09/06 02:42:27 - mmengine - INFO - Epoch(train) [79][360/940] lr: 1.0000e-03 eta: 4:39:58 time: 0.7232 data_time: 0.0184 memory: 22701 grad_norm: 5.3341 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.0073 loss: 1.0073 2022/09/06 02:42:46 - mmengine - INFO - Epoch(train) [79][380/940] lr: 1.0000e-03 eta: 4:39:43 time: 0.9758 data_time: 0.0676 memory: 22701 grad_norm: 5.4813 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9034 loss: 0.9034 2022/09/06 02:43:13 - mmengine - INFO - Epoch(train) [79][400/940] lr: 1.0000e-03 eta: 4:39:29 time: 1.3059 data_time: 0.0765 memory: 22701 grad_norm: 5.3909 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9612 loss: 0.9612 2022/09/06 02:43:28 - mmengine - INFO - Epoch(train) [79][420/940] lr: 1.0000e-03 eta: 4:39:12 time: 0.7942 data_time: 0.0242 memory: 22701 grad_norm: 5.2998 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9985 loss: 0.9985 2022/09/06 02:43:46 - mmengine - INFO - Epoch(train) [79][440/940] lr: 1.0000e-03 eta: 4:38:56 time: 0.8823 data_time: 0.0197 memory: 22701 grad_norm: 5.3519 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1409 loss: 1.1409 2022/09/06 02:44:03 - mmengine - INFO - Epoch(train) [79][460/940] lr: 1.0000e-03 eta: 4:38:39 time: 0.8272 data_time: 0.0683 memory: 22701 grad_norm: 5.5128 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9401 loss: 0.9401 2022/09/06 02:44:19 - mmengine - INFO - Epoch(train) [79][480/940] lr: 1.0000e-03 eta: 4:38:23 time: 0.8360 data_time: 0.1284 memory: 22701 grad_norm: 5.4435 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0074 loss: 1.0074 2022/09/06 02:44:34 - mmengine - INFO - Epoch(train) [79][500/940] lr: 1.0000e-03 eta: 4:38:06 time: 0.7204 data_time: 0.2061 memory: 22701 grad_norm: 5.3944 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0666 loss: 1.0666 2022/09/06 02:44:48 - mmengine - INFO - Epoch(train) [79][520/940] lr: 1.0000e-03 eta: 4:37:49 time: 0.7241 data_time: 0.2135 memory: 22701 grad_norm: 5.2274 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8941 loss: 0.8941 2022/09/06 02:45:05 - mmengine - INFO - Epoch(train) [79][540/940] lr: 1.0000e-03 eta: 4:37:32 time: 0.8106 data_time: 0.3650 memory: 22701 grad_norm: 5.3397 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9160 loss: 0.9160 2022/09/06 02:45:18 - mmengine - INFO - Epoch(train) [79][560/940] lr: 1.0000e-03 eta: 4:37:15 time: 0.6860 data_time: 0.2453 memory: 22701 grad_norm: 5.4529 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1953 loss: 1.1953 2022/09/06 02:45:36 - mmengine - INFO - Epoch(train) [79][580/940] lr: 1.0000e-03 eta: 4:36:59 time: 0.8991 data_time: 0.3460 memory: 22701 grad_norm: 5.3971 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0278 loss: 1.0278 2022/09/06 02:45:52 - mmengine - INFO - Epoch(train) [79][600/940] lr: 1.0000e-03 eta: 4:36:42 time: 0.8018 data_time: 0.2290 memory: 22701 grad_norm: 5.1719 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.0363 loss: 1.0363 2022/09/06 02:46:11 - mmengine - INFO - Epoch(train) [79][620/940] lr: 1.0000e-03 eta: 4:36:26 time: 0.9156 data_time: 0.2529 memory: 22701 grad_norm: 5.3634 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9626 loss: 0.9626 2022/09/06 02:46:27 - mmengine - INFO - Epoch(train) [79][640/940] lr: 1.0000e-03 eta: 4:36:09 time: 0.8363 data_time: 0.0207 memory: 22701 grad_norm: 5.2809 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0072 loss: 1.0072 2022/09/06 02:46:44 - mmengine - INFO - Epoch(train) [79][660/940] lr: 1.0000e-03 eta: 4:35:53 time: 0.8225 data_time: 0.0270 memory: 22701 grad_norm: 5.4738 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0904 loss: 1.0904 2022/09/06 02:47:06 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:47:06 - mmengine - INFO - Epoch(train) [79][680/940] lr: 1.0000e-03 eta: 4:35:38 time: 1.1172 data_time: 0.0277 memory: 22701 grad_norm: 5.4704 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9760 loss: 0.9760 2022/09/06 02:47:25 - mmengine - INFO - Epoch(train) [79][700/940] lr: 1.0000e-03 eta: 4:35:22 time: 0.9589 data_time: 0.1229 memory: 22701 grad_norm: 5.2462 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0234 loss: 1.0234 2022/09/06 02:47:43 - mmengine - INFO - Epoch(train) [79][720/940] lr: 1.0000e-03 eta: 4:35:06 time: 0.8970 data_time: 0.0299 memory: 22701 grad_norm: 5.3965 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9695 loss: 0.9695 2022/09/06 02:47:59 - mmengine - INFO - Epoch(train) [79][740/940] lr: 1.0000e-03 eta: 4:34:49 time: 0.8026 data_time: 0.0217 memory: 22701 grad_norm: 5.5164 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0006 loss: 1.0006 2022/09/06 02:48:18 - mmengine - INFO - Epoch(train) [79][760/940] lr: 1.0000e-03 eta: 4:34:33 time: 0.9298 data_time: 0.0182 memory: 22701 grad_norm: 5.4344 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0026 loss: 1.0026 2022/09/06 02:48:38 - mmengine - INFO - Epoch(train) [79][780/940] lr: 1.0000e-03 eta: 4:34:18 time: 0.9898 data_time: 0.0343 memory: 22701 grad_norm: 5.5347 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0632 loss: 1.0632 2022/09/06 02:48:56 - mmengine - INFO - Epoch(train) [79][800/940] lr: 1.0000e-03 eta: 4:34:01 time: 0.9142 data_time: 0.1212 memory: 22701 grad_norm: 5.4242 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0395 loss: 1.0395 2022/09/06 02:49:18 - mmengine - INFO - Epoch(train) [79][820/940] lr: 1.0000e-03 eta: 4:33:46 time: 1.0747 data_time: 0.1995 memory: 22701 grad_norm: 5.4094 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9123 loss: 0.9123 2022/09/06 02:49:33 - mmengine - INFO - Epoch(train) [79][840/940] lr: 1.0000e-03 eta: 4:33:29 time: 0.7892 data_time: 0.2870 memory: 22701 grad_norm: 5.4052 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0729 loss: 1.0729 2022/09/06 02:49:53 - mmengine - INFO - Epoch(train) [79][860/940] lr: 1.0000e-03 eta: 4:33:14 time: 1.0036 data_time: 0.5110 memory: 22701 grad_norm: 5.3543 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9303 loss: 0.9303 2022/09/06 02:50:10 - mmengine - INFO - Epoch(train) [79][880/940] lr: 1.0000e-03 eta: 4:32:57 time: 0.8231 data_time: 0.4409 memory: 22701 grad_norm: 5.4316 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1291 loss: 1.1291 2022/09/06 02:50:27 - mmengine - INFO - Epoch(train) [79][900/940] lr: 1.0000e-03 eta: 4:32:41 time: 0.8722 data_time: 0.4849 memory: 22701 grad_norm: 5.2942 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9346 loss: 0.9346 2022/09/06 02:50:42 - mmengine - INFO - Epoch(train) [79][920/940] lr: 1.0000e-03 eta: 4:32:24 time: 0.7363 data_time: 0.2788 memory: 22701 grad_norm: 5.4460 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9163 loss: 0.9163 2022/09/06 02:50:58 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 02:50:58 - mmengine - INFO - Epoch(train) [79][940/940] lr: 1.0000e-03 eta: 4:32:07 time: 0.8189 data_time: 0.4518 memory: 22701 grad_norm: 5.7122 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0057 loss: 1.0057 2022/09/06 02:51:12 - mmengine - INFO - Epoch(val) [79][20/78] eta: 0:00:39 time: 0.6884 data_time: 0.5675 memory: 2247 2022/09/06 02:51:21 - mmengine - INFO - Epoch(val) [79][40/78] eta: 0:00:17 time: 0.4517 data_time: 0.3343 memory: 2247 2022/09/06 02:51:34 - mmengine - INFO - Epoch(val) [79][60/78] eta: 0:00:11 time: 0.6309 data_time: 0.5118 memory: 2247 2022/09/06 02:51:44 - mmengine - INFO - Epoch(val) [79][78/78] acc/top1: 0.6867 acc/top5: 0.8791 acc/mean1: 0.6866 2022/09/06 02:52:07 - mmengine - INFO - Epoch(train) [80][20/940] lr: 1.0000e-03 eta: 4:31:52 time: 1.1027 data_time: 0.7010 memory: 22701 grad_norm: 5.3245 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0208 loss: 1.0208 2022/09/06 02:52:24 - mmengine - INFO - Epoch(train) [80][40/940] lr: 1.0000e-03 eta: 4:31:36 time: 0.8748 data_time: 0.4592 memory: 22701 grad_norm: 5.3082 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0075 loss: 1.0075 2022/09/06 02:52:42 - mmengine - INFO - Epoch(train) [80][60/940] lr: 1.0000e-03 eta: 4:31:20 time: 0.8810 data_time: 0.3506 memory: 22701 grad_norm: 5.3995 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9551 loss: 0.9551 2022/09/06 02:52:55 - mmengine - INFO - Epoch(train) [80][80/940] lr: 1.0000e-03 eta: 4:31:02 time: 0.6584 data_time: 0.1792 memory: 22701 grad_norm: 5.4710 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9549 loss: 0.9549 2022/09/06 02:53:12 - mmengine - INFO - Epoch(train) [80][100/940] lr: 1.0000e-03 eta: 4:30:46 time: 0.8663 data_time: 0.1363 memory: 22701 grad_norm: 5.3118 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0210 loss: 1.0210 2022/09/06 02:53:26 - mmengine - INFO - Epoch(train) [80][120/940] lr: 1.0000e-03 eta: 4:30:29 time: 0.6828 data_time: 0.0404 memory: 22701 grad_norm: 5.3918 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9773 loss: 0.9773 2022/09/06 02:53:44 - mmengine - INFO - Epoch(train) [80][140/940] lr: 1.0000e-03 eta: 4:30:13 time: 0.9024 data_time: 0.0323 memory: 22701 grad_norm: 5.3376 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0227 loss: 1.0227 2022/09/06 02:53:59 - mmengine - INFO - Epoch(train) [80][160/940] lr: 1.0000e-03 eta: 4:29:56 time: 0.7375 data_time: 0.0214 memory: 22701 grad_norm: 5.3788 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8242 loss: 0.8242 2022/09/06 02:54:16 - mmengine - INFO - Epoch(train) [80][180/940] lr: 1.0000e-03 eta: 4:29:39 time: 0.8754 data_time: 0.0294 memory: 22701 grad_norm: 5.4082 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0374 loss: 1.0374 2022/09/06 02:54:33 - mmengine - INFO - Epoch(train) [80][200/940] lr: 1.0000e-03 eta: 4:29:23 time: 0.8185 data_time: 0.0205 memory: 22701 grad_norm: 5.3359 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8782 loss: 0.8782 2022/09/06 02:54:51 - mmengine - INFO - Epoch(train) [80][220/940] lr: 1.0000e-03 eta: 4:29:07 time: 0.9191 data_time: 0.0269 memory: 22701 grad_norm: 5.3786 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0119 loss: 1.0119 2022/09/06 02:55:07 - mmengine - INFO - Epoch(train) [80][240/940] lr: 1.0000e-03 eta: 4:28:50 time: 0.7844 data_time: 0.0322 memory: 22701 grad_norm: 5.3847 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9992 loss: 0.9992 2022/09/06 02:55:26 - mmengine - INFO - Epoch(train) [80][260/940] lr: 1.0000e-03 eta: 4:28:34 time: 0.9474 data_time: 0.0556 memory: 22701 grad_norm: 5.3644 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9991 loss: 0.9991 2022/09/06 02:55:41 - mmengine - INFO - Epoch(train) [80][280/940] lr: 1.0000e-03 eta: 4:28:17 time: 0.7622 data_time: 0.1021 memory: 22701 grad_norm: 5.3214 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9155 loss: 0.9155 2022/09/06 02:56:01 - mmengine - INFO - Epoch(train) [80][300/940] lr: 1.0000e-03 eta: 4:28:01 time: 1.0194 data_time: 0.2933 memory: 22701 grad_norm: 5.5351 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0485 loss: 1.0485 2022/09/06 02:56:17 - mmengine - INFO - Epoch(train) [80][320/940] lr: 1.0000e-03 eta: 4:27:45 time: 0.7639 data_time: 0.2590 memory: 22701 grad_norm: 5.3822 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9263 loss: 0.9263 2022/09/06 02:56:38 - mmengine - INFO - Epoch(train) [80][340/940] lr: 1.0000e-03 eta: 4:27:29 time: 1.0906 data_time: 0.6128 memory: 22701 grad_norm: 5.2721 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0226 loss: 1.0226 2022/09/06 02:56:55 - mmengine - INFO - Epoch(train) [80][360/940] lr: 1.0000e-03 eta: 4:27:13 time: 0.8348 data_time: 0.3976 memory: 22701 grad_norm: 5.3382 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0031 loss: 1.0031 2022/09/06 02:57:12 - mmengine - INFO - Epoch(train) [80][380/940] lr: 1.0000e-03 eta: 4:26:56 time: 0.8251 data_time: 0.3112 memory: 22701 grad_norm: 5.3210 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0090 loss: 1.0090 2022/09/06 02:57:25 - mmengine - INFO - Epoch(train) [80][400/940] lr: 1.0000e-03 eta: 4:26:39 time: 0.6471 data_time: 0.1839 memory: 22701 grad_norm: 5.4179 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9197 loss: 0.9197 2022/09/06 02:57:41 - mmengine - INFO - Epoch(train) [80][420/940] lr: 1.0000e-03 eta: 4:26:22 time: 0.8080 data_time: 0.3920 memory: 22701 grad_norm: 5.2625 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9253 loss: 0.9253 2022/09/06 02:57:54 - mmengine - INFO - Epoch(train) [80][440/940] lr: 1.0000e-03 eta: 4:26:05 time: 0.6744 data_time: 0.2237 memory: 22701 grad_norm: 5.3270 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0121 loss: 1.0121 2022/09/06 02:58:13 - mmengine - INFO - Epoch(train) [80][460/940] lr: 1.0000e-03 eta: 4:25:49 time: 0.9172 data_time: 0.5132 memory: 22701 grad_norm: 5.4238 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0413 loss: 1.0413 2022/09/06 02:58:29 - mmengine - INFO - Epoch(train) [80][480/940] lr: 1.0000e-03 eta: 4:25:32 time: 0.8436 data_time: 0.2372 memory: 22701 grad_norm: 5.3635 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9174 loss: 0.9174 2022/09/06 02:58:47 - mmengine - INFO - Epoch(train) [80][500/940] lr: 1.0000e-03 eta: 4:25:16 time: 0.8905 data_time: 0.0540 memory: 22701 grad_norm: 5.3882 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0684 loss: 1.0684 2022/09/06 02:59:02 - mmengine - INFO - Epoch(train) [80][520/940] lr: 1.0000e-03 eta: 4:24:59 time: 0.7327 data_time: 0.0489 memory: 22701 grad_norm: 5.4204 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1007 loss: 1.1007 2022/09/06 02:59:21 - mmengine - INFO - Epoch(train) [80][540/940] lr: 1.0000e-03 eta: 4:24:43 time: 0.9715 data_time: 0.0717 memory: 22701 grad_norm: 5.2801 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9584 loss: 0.9584 2022/09/06 02:59:35 - mmengine - INFO - Epoch(train) [80][560/940] lr: 1.0000e-03 eta: 4:24:26 time: 0.6905 data_time: 0.0201 memory: 22701 grad_norm: 5.4275 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0674 loss: 1.0674 2022/09/06 02:59:55 - mmengine - INFO - Epoch(train) [80][580/940] lr: 1.0000e-03 eta: 4:24:10 time: 0.9715 data_time: 0.0298 memory: 22701 grad_norm: 5.4424 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9094 loss: 0.9094 2022/09/06 03:00:09 - mmengine - INFO - Epoch(train) [80][600/940] lr: 1.0000e-03 eta: 4:23:53 time: 0.7350 data_time: 0.0216 memory: 22701 grad_norm: 5.4192 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9631 loss: 0.9631 2022/09/06 03:00:25 - mmengine - INFO - Epoch(train) [80][620/940] lr: 1.0000e-03 eta: 4:23:36 time: 0.7673 data_time: 0.0313 memory: 22701 grad_norm: 5.3358 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9914 loss: 0.9914 2022/09/06 03:00:39 - mmengine - INFO - Epoch(train) [80][640/940] lr: 1.0000e-03 eta: 4:23:19 time: 0.7033 data_time: 0.0238 memory: 22701 grad_norm: 5.2860 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0180 loss: 1.0180 2022/09/06 03:00:58 - mmengine - INFO - Epoch(train) [80][660/940] lr: 1.0000e-03 eta: 4:23:03 time: 0.9817 data_time: 0.0467 memory: 22701 grad_norm: 5.3326 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.9488 loss: 0.9488 2022/09/06 03:01:19 - mmengine - INFO - Epoch(train) [80][680/940] lr: 1.0000e-03 eta: 4:22:48 time: 1.0303 data_time: 0.2754 memory: 22701 grad_norm: 5.4180 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0226 loss: 1.0226 2022/09/06 03:01:40 - mmengine - INFO - Epoch(train) [80][700/940] lr: 1.0000e-03 eta: 4:22:33 time: 1.0668 data_time: 0.5293 memory: 22701 grad_norm: 5.4096 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9615 loss: 0.9615 2022/09/06 03:01:56 - mmengine - INFO - Epoch(train) [80][720/940] lr: 1.0000e-03 eta: 4:22:16 time: 0.7687 data_time: 0.2691 memory: 22701 grad_norm: 5.3171 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0418 loss: 1.0418 2022/09/06 03:02:12 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:02:12 - mmengine - INFO - Epoch(train) [80][740/940] lr: 1.0000e-03 eta: 4:21:59 time: 0.8328 data_time: 0.4626 memory: 22701 grad_norm: 5.4672 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.0518 loss: 1.0518 2022/09/06 03:02:26 - mmengine - INFO - Epoch(train) [80][760/940] lr: 1.0000e-03 eta: 4:21:42 time: 0.6803 data_time: 0.2401 memory: 22701 grad_norm: 5.4947 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9819 loss: 0.9819 2022/09/06 03:02:43 - mmengine - INFO - Epoch(train) [80][780/940] lr: 1.0000e-03 eta: 4:21:25 time: 0.8319 data_time: 0.4464 memory: 22701 grad_norm: 5.3854 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0240 loss: 1.0240 2022/09/06 03:02:57 - mmengine - INFO - Epoch(train) [80][800/940] lr: 1.0000e-03 eta: 4:21:08 time: 0.7123 data_time: 0.3188 memory: 22701 grad_norm: 5.4529 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9861 loss: 0.9861 2022/09/06 03:03:11 - mmengine - INFO - Epoch(train) [80][820/940] lr: 1.0000e-03 eta: 4:20:51 time: 0.7323 data_time: 0.3464 memory: 22701 grad_norm: 5.3779 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9979 loss: 0.9979 2022/09/06 03:03:27 - mmengine - INFO - Epoch(train) [80][840/940] lr: 1.0000e-03 eta: 4:20:34 time: 0.7664 data_time: 0.3563 memory: 22701 grad_norm: 5.5007 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1275 loss: 1.1275 2022/09/06 03:03:47 - mmengine - INFO - Epoch(train) [80][860/940] lr: 1.0000e-03 eta: 4:20:19 time: 1.0055 data_time: 0.4202 memory: 22701 grad_norm: 5.5394 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0167 loss: 1.0167 2022/09/06 03:04:02 - mmengine - INFO - Epoch(train) [80][880/940] lr: 1.0000e-03 eta: 4:20:02 time: 0.7393 data_time: 0.2708 memory: 22701 grad_norm: 5.4695 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9258 loss: 0.9258 2022/09/06 03:04:22 - mmengine - INFO - Epoch(train) [80][900/940] lr: 1.0000e-03 eta: 4:19:46 time: 1.0117 data_time: 0.4808 memory: 22701 grad_norm: 5.4541 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0849 loss: 1.0849 2022/09/06 03:04:41 - mmengine - INFO - Epoch(train) [80][920/940] lr: 1.0000e-03 eta: 4:19:30 time: 0.9310 data_time: 0.2560 memory: 22701 grad_norm: 5.4818 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9553 loss: 0.9553 2022/09/06 03:04:56 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:04:56 - mmengine - INFO - Epoch(train) [80][940/940] lr: 1.0000e-03 eta: 4:19:13 time: 0.7803 data_time: 0.1852 memory: 22701 grad_norm: 5.7243 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.0129 loss: 1.0129 2022/09/06 03:05:10 - mmengine - INFO - Epoch(val) [80][20/78] eta: 0:00:39 time: 0.6879 data_time: 0.5695 memory: 2247 2022/09/06 03:05:19 - mmengine - INFO - Epoch(val) [80][40/78] eta: 0:00:16 time: 0.4455 data_time: 0.3181 memory: 2247 2022/09/06 03:05:32 - mmengine - INFO - Epoch(val) [80][60/78] eta: 0:00:11 time: 0.6550 data_time: 0.5375 memory: 2247 2022/09/06 03:05:42 - mmengine - INFO - Epoch(val) [80][78/78] acc/top1: 0.6849 acc/top5: 0.8786 acc/mean1: 0.6848 2022/09/06 03:06:04 - mmengine - INFO - Epoch(train) [81][20/940] lr: 1.0000e-04 eta: 4:18:58 time: 1.0684 data_time: 0.5699 memory: 22701 grad_norm: 5.1966 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8472 loss: 0.8472 2022/09/06 03:06:17 - mmengine - INFO - Epoch(train) [81][40/940] lr: 1.0000e-04 eta: 4:18:41 time: 0.6766 data_time: 0.1512 memory: 22701 grad_norm: 5.2711 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9686 loss: 0.9686 2022/09/06 03:06:37 - mmengine - INFO - Epoch(train) [81][60/940] lr: 1.0000e-04 eta: 4:18:25 time: 0.9638 data_time: 0.1448 memory: 22701 grad_norm: 5.3568 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9382 loss: 0.9382 2022/09/06 03:06:57 - mmengine - INFO - Epoch(train) [81][80/940] lr: 1.0000e-04 eta: 4:18:09 time: 1.0020 data_time: 0.0276 memory: 22701 grad_norm: 5.3600 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9094 loss: 0.9094 2022/09/06 03:07:17 - mmengine - INFO - Epoch(train) [81][100/940] lr: 1.0000e-04 eta: 4:17:54 time: 1.0319 data_time: 0.0262 memory: 22701 grad_norm: 5.2946 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9149 loss: 0.9149 2022/09/06 03:07:35 - mmengine - INFO - Epoch(train) [81][120/940] lr: 1.0000e-04 eta: 4:17:37 time: 0.8622 data_time: 0.0191 memory: 22701 grad_norm: 5.3520 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9001 loss: 0.9001 2022/09/06 03:07:56 - mmengine - INFO - Epoch(train) [81][140/940] lr: 1.0000e-04 eta: 4:17:22 time: 1.0620 data_time: 0.0269 memory: 22701 grad_norm: 5.2484 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 0.9914 loss: 0.9914 2022/09/06 03:08:14 - mmengine - INFO - Epoch(train) [81][160/940] lr: 1.0000e-04 eta: 4:17:06 time: 0.9114 data_time: 0.0314 memory: 22701 grad_norm: 5.2355 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0018 loss: 1.0018 2022/09/06 03:08:37 - mmengine - INFO - Epoch(train) [81][180/940] lr: 1.0000e-04 eta: 4:16:51 time: 1.1319 data_time: 0.0198 memory: 22701 grad_norm: 5.3073 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0302 loss: 1.0302 2022/09/06 03:08:53 - mmengine - INFO - Epoch(train) [81][200/940] lr: 1.0000e-04 eta: 4:16:34 time: 0.8355 data_time: 0.0291 memory: 22701 grad_norm: 5.3788 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9283 loss: 0.9283 2022/09/06 03:09:11 - mmengine - INFO - Epoch(train) [81][220/940] lr: 1.0000e-04 eta: 4:16:18 time: 0.8561 data_time: 0.0249 memory: 22701 grad_norm: 5.4175 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0095 loss: 1.0095 2022/09/06 03:09:27 - mmengine - INFO - Epoch(train) [81][240/940] lr: 1.0000e-04 eta: 4:16:01 time: 0.8326 data_time: 0.0646 memory: 22701 grad_norm: 5.3551 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.9340 loss: 0.9340 2022/09/06 03:09:49 - mmengine - INFO - Epoch(train) [81][260/940] lr: 1.0000e-04 eta: 4:15:46 time: 1.1064 data_time: 0.0407 memory: 22701 grad_norm: 5.2547 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9080 loss: 0.9080 2022/09/06 03:10:05 - mmengine - INFO - Epoch(train) [81][280/940] lr: 1.0000e-04 eta: 4:15:29 time: 0.7912 data_time: 0.0250 memory: 22701 grad_norm: 5.3050 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0607 loss: 1.0607 2022/09/06 03:10:25 - mmengine - INFO - Epoch(train) [81][300/940] lr: 1.0000e-04 eta: 4:15:14 time: 1.0111 data_time: 0.0224 memory: 22701 grad_norm: 5.3136 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9791 loss: 0.9791 2022/09/06 03:10:39 - mmengine - INFO - Epoch(train) [81][320/940] lr: 1.0000e-04 eta: 4:14:56 time: 0.6655 data_time: 0.0216 memory: 22701 grad_norm: 5.3423 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 0.9356 loss: 0.9356 2022/09/06 03:10:55 - mmengine - INFO - Epoch(train) [81][340/940] lr: 1.0000e-04 eta: 4:14:40 time: 0.8100 data_time: 0.0249 memory: 22701 grad_norm: 5.3141 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 0.9598 loss: 0.9598 2022/09/06 03:11:09 - mmengine - INFO - Epoch(train) [81][360/940] lr: 1.0000e-04 eta: 4:14:23 time: 0.7244 data_time: 0.0342 memory: 22701 grad_norm: 5.3239 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 0.8748 loss: 0.8748 2022/09/06 03:11:25 - mmengine - INFO - Epoch(train) [81][380/940] lr: 1.0000e-04 eta: 4:14:06 time: 0.7660 data_time: 0.0252 memory: 22701 grad_norm: 5.2851 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9479 loss: 0.9479 2022/09/06 03:11:40 - mmengine - INFO - Epoch(train) [81][400/940] lr: 1.0000e-04 eta: 4:13:49 time: 0.7500 data_time: 0.0290 memory: 22701 grad_norm: 5.3497 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0468 loss: 1.0468 2022/09/06 03:11:59 - mmengine - INFO - Epoch(train) [81][420/940] lr: 1.0000e-04 eta: 4:13:33 time: 0.9538 data_time: 0.0255 memory: 22701 grad_norm: 5.3357 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9003 loss: 0.9003 2022/09/06 03:12:13 - mmengine - INFO - Epoch(train) [81][440/940] lr: 1.0000e-04 eta: 4:13:16 time: 0.6940 data_time: 0.0299 memory: 22701 grad_norm: 5.2528 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.9333 loss: 0.9333 2022/09/06 03:12:32 - mmengine - INFO - Epoch(train) [81][460/940] lr: 1.0000e-04 eta: 4:13:00 time: 0.9665 data_time: 0.0268 memory: 22701 grad_norm: 5.3675 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9869 loss: 0.9869 2022/09/06 03:12:48 - mmengine - INFO - Epoch(train) [81][480/940] lr: 1.0000e-04 eta: 4:12:43 time: 0.7973 data_time: 0.0340 memory: 22701 grad_norm: 5.3839 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9428 loss: 0.9428 2022/09/06 03:13:08 - mmengine - INFO - Epoch(train) [81][500/940] lr: 1.0000e-04 eta: 4:12:27 time: 0.9927 data_time: 0.0330 memory: 22701 grad_norm: 5.3421 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 0.9282 loss: 0.9282 2022/09/06 03:13:29 - mmengine - INFO - Epoch(train) [81][520/940] lr: 1.0000e-04 eta: 4:12:12 time: 1.0464 data_time: 0.3149 memory: 22701 grad_norm: 5.3157 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9783 loss: 0.9783 2022/09/06 03:13:44 - mmengine - INFO - Epoch(train) [81][540/940] lr: 1.0000e-04 eta: 4:11:55 time: 0.7785 data_time: 0.3637 memory: 22701 grad_norm: 5.3529 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9542 loss: 0.9542 2022/09/06 03:14:00 - mmengine - INFO - Epoch(train) [81][560/940] lr: 1.0000e-04 eta: 4:11:38 time: 0.7993 data_time: 0.3975 memory: 22701 grad_norm: 5.3101 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9379 loss: 0.9379 2022/09/06 03:14:17 - mmengine - INFO - Epoch(train) [81][580/940] lr: 1.0000e-04 eta: 4:11:22 time: 0.8413 data_time: 0.4215 memory: 22701 grad_norm: 5.3988 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0736 loss: 1.0736 2022/09/06 03:14:37 - mmengine - INFO - Epoch(train) [81][600/940] lr: 1.0000e-04 eta: 4:11:06 time: 0.9715 data_time: 0.5431 memory: 22701 grad_norm: 5.3831 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9477 loss: 0.9477 2022/09/06 03:14:51 - mmengine - INFO - Epoch(train) [81][620/940] lr: 1.0000e-04 eta: 4:10:49 time: 0.7181 data_time: 0.3301 memory: 22701 grad_norm: 5.2835 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9848 loss: 0.9848 2022/09/06 03:15:08 - mmengine - INFO - Epoch(train) [81][640/940] lr: 1.0000e-04 eta: 4:10:32 time: 0.8484 data_time: 0.4293 memory: 22701 grad_norm: 5.3846 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9841 loss: 0.9841 2022/09/06 03:15:24 - mmengine - INFO - Epoch(train) [81][660/940] lr: 1.0000e-04 eta: 4:10:16 time: 0.7829 data_time: 0.3911 memory: 22701 grad_norm: 5.3742 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9755 loss: 0.9755 2022/09/06 03:15:43 - mmengine - INFO - Epoch(train) [81][680/940] lr: 1.0000e-04 eta: 4:10:00 time: 0.9462 data_time: 0.5370 memory: 22701 grad_norm: 5.3804 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0232 loss: 1.0232 2022/09/06 03:15:56 - mmengine - INFO - Epoch(train) [81][700/940] lr: 1.0000e-04 eta: 4:09:42 time: 0.6874 data_time: 0.2783 memory: 22701 grad_norm: 5.2693 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9175 loss: 0.9175 2022/09/06 03:16:13 - mmengine - INFO - Epoch(train) [81][720/940] lr: 1.0000e-04 eta: 4:09:26 time: 0.8223 data_time: 0.4137 memory: 22701 grad_norm: 5.4053 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9880 loss: 0.9880 2022/09/06 03:16:27 - mmengine - INFO - Epoch(train) [81][740/940] lr: 1.0000e-04 eta: 4:09:09 time: 0.6909 data_time: 0.2908 memory: 22701 grad_norm: 5.3127 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9049 loss: 0.9049 2022/09/06 03:16:42 - mmengine - INFO - Epoch(train) [81][760/940] lr: 1.0000e-04 eta: 4:08:52 time: 0.7796 data_time: 0.3468 memory: 22701 grad_norm: 5.3540 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9824 loss: 0.9824 2022/09/06 03:16:56 - mmengine - INFO - Epoch(train) [81][780/940] lr: 1.0000e-04 eta: 4:08:35 time: 0.6705 data_time: 0.2692 memory: 22701 grad_norm: 5.3698 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0160 loss: 1.0160 2022/09/06 03:17:13 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:17:13 - mmengine - INFO - Epoch(train) [81][800/940] lr: 1.0000e-04 eta: 4:08:18 time: 0.8464 data_time: 0.4618 memory: 22701 grad_norm: 5.3058 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9862 loss: 0.9862 2022/09/06 03:17:26 - mmengine - INFO - Epoch(train) [81][820/940] lr: 1.0000e-04 eta: 4:08:01 time: 0.6847 data_time: 0.2564 memory: 22701 grad_norm: 5.2718 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.8960 loss: 0.8960 2022/09/06 03:17:44 - mmengine - INFO - Epoch(train) [81][840/940] lr: 1.0000e-04 eta: 4:07:45 time: 0.8774 data_time: 0.4620 memory: 22701 grad_norm: 5.3359 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.9195 loss: 0.9195 2022/09/06 03:17:59 - mmengine - INFO - Epoch(train) [81][860/940] lr: 1.0000e-04 eta: 4:07:28 time: 0.7668 data_time: 0.3300 memory: 22701 grad_norm: 5.4449 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0525 loss: 1.0525 2022/09/06 03:18:18 - mmengine - INFO - Epoch(train) [81][880/940] lr: 1.0000e-04 eta: 4:07:12 time: 0.9631 data_time: 0.5741 memory: 22701 grad_norm: 5.3236 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.9525 loss: 0.9525 2022/09/06 03:18:35 - mmengine - INFO - Epoch(train) [81][900/940] lr: 1.0000e-04 eta: 4:06:55 time: 0.8358 data_time: 0.4290 memory: 22701 grad_norm: 5.3146 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9132 loss: 0.9132 2022/09/06 03:18:52 - mmengine - INFO - Epoch(train) [81][920/940] lr: 1.0000e-04 eta: 4:06:39 time: 0.8260 data_time: 0.4000 memory: 22701 grad_norm: 5.3844 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8464 loss: 0.8464 2022/09/06 03:19:06 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:19:06 - mmengine - INFO - Epoch(train) [81][940/940] lr: 1.0000e-04 eta: 4:06:22 time: 0.7027 data_time: 0.3089 memory: 22701 grad_norm: 5.7646 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.9275 loss: 0.9275 2022/09/06 03:19:06 - mmengine - INFO - Saving checkpoint at 81 epochs 2022/09/06 03:19:22 - mmengine - INFO - Epoch(val) [81][20/78] eta: 0:00:40 time: 0.6935 data_time: 0.5781 memory: 2247 2022/09/06 03:19:31 - mmengine - INFO - Epoch(val) [81][40/78] eta: 0:00:17 time: 0.4607 data_time: 0.3380 memory: 2247 2022/09/06 03:19:44 - mmengine - INFO - Epoch(val) [81][60/78] eta: 0:00:11 time: 0.6425 data_time: 0.5265 memory: 2247 2022/09/06 03:19:53 - mmengine - INFO - Epoch(val) [81][78/78] acc/top1: 0.6861 acc/top5: 0.8797 acc/mean1: 0.6860 2022/09/06 03:20:15 - mmengine - INFO - Epoch(train) [82][20/940] lr: 1.0000e-04 eta: 4:06:06 time: 1.0980 data_time: 0.4045 memory: 22701 grad_norm: 5.1974 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9371 loss: 0.9371 2022/09/06 03:20:28 - mmengine - INFO - Epoch(train) [82][40/940] lr: 1.0000e-04 eta: 4:05:49 time: 0.6439 data_time: 0.1189 memory: 22701 grad_norm: 5.2492 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0583 loss: 1.0583 2022/09/06 03:20:45 - mmengine - INFO - Epoch(train) [82][60/940] lr: 1.0000e-04 eta: 4:05:33 time: 0.8654 data_time: 0.2049 memory: 22701 grad_norm: 5.2705 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9664 loss: 0.9664 2022/09/06 03:20:58 - mmengine - INFO - Epoch(train) [82][80/940] lr: 1.0000e-04 eta: 4:05:15 time: 0.6372 data_time: 0.0289 memory: 22701 grad_norm: 5.2896 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9226 loss: 0.9226 2022/09/06 03:21:14 - mmengine - INFO - Epoch(train) [82][100/940] lr: 1.0000e-04 eta: 4:04:59 time: 0.8233 data_time: 0.1089 memory: 22701 grad_norm: 5.4614 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9745 loss: 0.9745 2022/09/06 03:21:27 - mmengine - INFO - Epoch(train) [82][120/940] lr: 1.0000e-04 eta: 4:04:41 time: 0.6563 data_time: 0.1040 memory: 22701 grad_norm: 5.4062 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0516 loss: 1.0516 2022/09/06 03:21:44 - mmengine - INFO - Epoch(train) [82][140/940] lr: 1.0000e-04 eta: 4:04:25 time: 0.8361 data_time: 0.2379 memory: 22701 grad_norm: 5.2857 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0639 loss: 1.0639 2022/09/06 03:21:59 - mmengine - INFO - Epoch(train) [82][160/940] lr: 1.0000e-04 eta: 4:04:08 time: 0.7318 data_time: 0.0760 memory: 22701 grad_norm: 5.2825 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9554 loss: 0.9554 2022/09/06 03:22:19 - mmengine - INFO - Epoch(train) [82][180/940] lr: 1.0000e-04 eta: 4:03:52 time: 1.0112 data_time: 0.2102 memory: 22701 grad_norm: 5.2735 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0787 loss: 1.0787 2022/09/06 03:22:37 - mmengine - INFO - Epoch(train) [82][200/940] lr: 1.0000e-04 eta: 4:03:36 time: 0.9086 data_time: 0.1459 memory: 22701 grad_norm: 5.4601 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9903 loss: 0.9903 2022/09/06 03:22:59 - mmengine - INFO - Epoch(train) [82][220/940] lr: 1.0000e-04 eta: 4:03:20 time: 1.0640 data_time: 0.1471 memory: 22701 grad_norm: 5.4454 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9864 loss: 0.9864 2022/09/06 03:23:13 - mmengine - INFO - Epoch(train) [82][240/940] lr: 1.0000e-04 eta: 4:03:03 time: 0.7271 data_time: 0.0261 memory: 22701 grad_norm: 5.3942 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 0.9081 loss: 0.9081 2022/09/06 03:23:33 - mmengine - INFO - Epoch(train) [82][260/940] lr: 1.0000e-04 eta: 4:02:48 time: 0.9946 data_time: 0.0284 memory: 22701 grad_norm: 5.2780 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9206 loss: 0.9206 2022/09/06 03:23:49 - mmengine - INFO - Epoch(train) [82][280/940] lr: 1.0000e-04 eta: 4:02:31 time: 0.8076 data_time: 0.0233 memory: 22701 grad_norm: 5.4632 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0549 loss: 1.0549 2022/09/06 03:24:10 - mmengine - INFO - Epoch(train) [82][300/940] lr: 1.0000e-04 eta: 4:02:15 time: 1.0288 data_time: 0.0630 memory: 22701 grad_norm: 5.3650 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9377 loss: 0.9377 2022/09/06 03:24:26 - mmengine - INFO - Epoch(train) [82][320/940] lr: 1.0000e-04 eta: 4:01:59 time: 0.8038 data_time: 0.0312 memory: 22701 grad_norm: 5.3051 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9291 loss: 0.9291 2022/09/06 03:24:44 - mmengine - INFO - Epoch(train) [82][340/940] lr: 1.0000e-04 eta: 4:01:42 time: 0.8919 data_time: 0.0230 memory: 22701 grad_norm: 5.4489 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0754 loss: 1.0754 2022/09/06 03:24:58 - mmengine - INFO - Epoch(train) [82][360/940] lr: 1.0000e-04 eta: 4:01:25 time: 0.7140 data_time: 0.0329 memory: 22701 grad_norm: 5.3389 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9777 loss: 0.9777 2022/09/06 03:25:17 - mmengine - INFO - Epoch(train) [82][380/940] lr: 1.0000e-04 eta: 4:01:09 time: 0.9297 data_time: 0.1348 memory: 22701 grad_norm: 5.3465 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0008 loss: 1.0008 2022/09/06 03:25:32 - mmengine - INFO - Epoch(train) [82][400/940] lr: 1.0000e-04 eta: 4:00:52 time: 0.7673 data_time: 0.0934 memory: 22701 grad_norm: 5.2755 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9559 loss: 0.9559 2022/09/06 03:25:49 - mmengine - INFO - Epoch(train) [82][420/940] lr: 1.0000e-04 eta: 4:00:36 time: 0.8700 data_time: 0.0280 memory: 22701 grad_norm: 5.1086 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9379 loss: 0.9379 2022/09/06 03:26:04 - mmengine - INFO - Epoch(train) [82][440/940] lr: 1.0000e-04 eta: 4:00:19 time: 0.7381 data_time: 0.0222 memory: 22701 grad_norm: 5.3785 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.9452 loss: 0.9452 2022/09/06 03:26:21 - mmengine - INFO - Epoch(train) [82][460/940] lr: 1.0000e-04 eta: 4:00:03 time: 0.8594 data_time: 0.0258 memory: 22701 grad_norm: 5.3347 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0448 loss: 1.0448 2022/09/06 03:26:34 - mmengine - INFO - Epoch(train) [82][480/940] lr: 1.0000e-04 eta: 3:59:45 time: 0.6405 data_time: 0.0264 memory: 22701 grad_norm: 5.4224 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9430 loss: 0.9430 2022/09/06 03:26:51 - mmengine - INFO - Epoch(train) [82][500/940] lr: 1.0000e-04 eta: 3:59:29 time: 0.8496 data_time: 0.0473 memory: 22701 grad_norm: 5.2514 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9770 loss: 0.9770 2022/09/06 03:27:04 - mmengine - INFO - Epoch(train) [82][520/940] lr: 1.0000e-04 eta: 3:59:11 time: 0.6453 data_time: 0.0280 memory: 22701 grad_norm: 5.2378 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.8560 loss: 0.8560 2022/09/06 03:27:22 - mmengine - INFO - Epoch(train) [82][540/940] lr: 1.0000e-04 eta: 3:58:55 time: 0.8932 data_time: 0.0229 memory: 22701 grad_norm: 5.3863 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0297 loss: 1.0297 2022/09/06 03:27:35 - mmengine - INFO - Epoch(train) [82][560/940] lr: 1.0000e-04 eta: 3:58:38 time: 0.6528 data_time: 0.0243 memory: 22701 grad_norm: 5.2270 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9679 loss: 0.9679 2022/09/06 03:27:51 - mmengine - INFO - Epoch(train) [82][580/940] lr: 1.0000e-04 eta: 3:58:21 time: 0.8265 data_time: 0.0245 memory: 22701 grad_norm: 5.3439 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0191 loss: 1.0191 2022/09/06 03:28:06 - mmengine - INFO - Epoch(train) [82][600/940] lr: 1.0000e-04 eta: 3:58:04 time: 0.7022 data_time: 0.0261 memory: 22701 grad_norm: 5.2121 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.8878 loss: 0.8878 2022/09/06 03:28:23 - mmengine - INFO - Epoch(train) [82][620/940] lr: 1.0000e-04 eta: 3:57:48 time: 0.8926 data_time: 0.0212 memory: 22701 grad_norm: 5.3111 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9709 loss: 0.9709 2022/09/06 03:28:38 - mmengine - INFO - Epoch(train) [82][640/940] lr: 1.0000e-04 eta: 3:57:31 time: 0.7190 data_time: 0.0255 memory: 22701 grad_norm: 5.3419 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0014 loss: 1.0014 2022/09/06 03:28:57 - mmengine - INFO - Epoch(train) [82][660/940] lr: 1.0000e-04 eta: 3:57:15 time: 0.9773 data_time: 0.1421 memory: 22701 grad_norm: 5.4270 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9437 loss: 0.9437 2022/09/06 03:29:13 - mmengine - INFO - Epoch(train) [82][680/940] lr: 1.0000e-04 eta: 3:56:58 time: 0.7800 data_time: 0.0244 memory: 22701 grad_norm: 5.2854 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8958 loss: 0.8958 2022/09/06 03:29:31 - mmengine - INFO - Epoch(train) [82][700/940] lr: 1.0000e-04 eta: 3:56:42 time: 0.8835 data_time: 0.2042 memory: 22701 grad_norm: 5.2474 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8914 loss: 0.8914 2022/09/06 03:29:47 - mmengine - INFO - Epoch(train) [82][720/940] lr: 1.0000e-04 eta: 3:56:25 time: 0.8324 data_time: 0.2535 memory: 22701 grad_norm: 5.3163 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0200 loss: 1.0200 2022/09/06 03:30:04 - mmengine - INFO - Epoch(train) [82][740/940] lr: 1.0000e-04 eta: 3:56:09 time: 0.8134 data_time: 0.3444 memory: 22701 grad_norm: 5.2995 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0317 loss: 1.0317 2022/09/06 03:30:18 - mmengine - INFO - Epoch(train) [82][760/940] lr: 1.0000e-04 eta: 3:55:52 time: 0.7395 data_time: 0.2270 memory: 22701 grad_norm: 5.3984 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0262 loss: 1.0262 2022/09/06 03:30:33 - mmengine - INFO - Epoch(train) [82][780/940] lr: 1.0000e-04 eta: 3:55:35 time: 0.7262 data_time: 0.2215 memory: 22701 grad_norm: 5.3006 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.0911 loss: 1.0911 2022/09/06 03:30:49 - mmengine - INFO - Epoch(train) [82][800/940] lr: 1.0000e-04 eta: 3:55:18 time: 0.7914 data_time: 0.1987 memory: 22701 grad_norm: 5.3382 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9520 loss: 0.9520 2022/09/06 03:31:05 - mmengine - INFO - Epoch(train) [82][820/940] lr: 1.0000e-04 eta: 3:55:01 time: 0.7920 data_time: 0.3480 memory: 22701 grad_norm: 5.2922 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8687 loss: 0.8687 2022/09/06 03:31:20 - mmengine - INFO - Epoch(train) [82][840/940] lr: 1.0000e-04 eta: 3:54:44 time: 0.7495 data_time: 0.2717 memory: 22701 grad_norm: 5.3112 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0024 loss: 1.0024 2022/09/06 03:31:38 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:31:38 - mmengine - INFO - Epoch(train) [82][860/940] lr: 1.0000e-04 eta: 3:54:28 time: 0.9304 data_time: 0.5348 memory: 22701 grad_norm: 5.2754 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8998 loss: 0.8998 2022/09/06 03:31:53 - mmengine - INFO - Epoch(train) [82][880/940] lr: 1.0000e-04 eta: 3:54:11 time: 0.7570 data_time: 0.3625 memory: 22701 grad_norm: 5.2567 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9478 loss: 0.9478 2022/09/06 03:32:11 - mmengine - INFO - Epoch(train) [82][900/940] lr: 1.0000e-04 eta: 3:53:55 time: 0.8621 data_time: 0.4586 memory: 22701 grad_norm: 5.2607 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9001 loss: 0.9001 2022/09/06 03:32:25 - mmengine - INFO - Epoch(train) [82][920/940] lr: 1.0000e-04 eta: 3:53:38 time: 0.7025 data_time: 0.2987 memory: 22701 grad_norm: 5.4110 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9709 loss: 0.9709 2022/09/06 03:32:42 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:32:42 - mmengine - INFO - Epoch(train) [82][940/940] lr: 1.0000e-04 eta: 3:53:22 time: 0.8934 data_time: 0.5253 memory: 22701 grad_norm: 5.6501 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.9153 loss: 0.9153 2022/09/06 03:32:56 - mmengine - INFO - Epoch(val) [82][20/78] eta: 0:00:39 time: 0.6788 data_time: 0.5589 memory: 2247 2022/09/06 03:33:05 - mmengine - INFO - Epoch(val) [82][40/78] eta: 0:00:17 time: 0.4661 data_time: 0.3507 memory: 2247 2022/09/06 03:33:18 - mmengine - INFO - Epoch(val) [82][60/78] eta: 0:00:11 time: 0.6457 data_time: 0.5270 memory: 2247 2022/09/06 03:33:29 - mmengine - INFO - Epoch(val) [82][78/78] acc/top1: 0.6866 acc/top5: 0.8803 acc/mean1: 0.6865 2022/09/06 03:33:52 - mmengine - INFO - Epoch(train) [83][20/940] lr: 1.0000e-04 eta: 3:53:07 time: 1.1473 data_time: 0.3640 memory: 22701 grad_norm: 5.2903 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9754 loss: 0.9754 2022/09/06 03:34:08 - mmengine - INFO - Epoch(train) [83][40/940] lr: 1.0000e-04 eta: 3:52:50 time: 0.8135 data_time: 0.1243 memory: 22701 grad_norm: 5.3493 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.9711 loss: 0.9711 2022/09/06 03:34:25 - mmengine - INFO - Epoch(train) [83][60/940] lr: 1.0000e-04 eta: 3:52:33 time: 0.8440 data_time: 0.1095 memory: 22701 grad_norm: 5.3285 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9042 loss: 0.9042 2022/09/06 03:34:39 - mmengine - INFO - Epoch(train) [83][80/940] lr: 1.0000e-04 eta: 3:52:16 time: 0.6933 data_time: 0.0355 memory: 22701 grad_norm: 5.2616 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9151 loss: 0.9151 2022/09/06 03:34:57 - mmengine - INFO - Epoch(train) [83][100/940] lr: 1.0000e-04 eta: 3:52:00 time: 0.9035 data_time: 0.0280 memory: 22701 grad_norm: 5.2360 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9744 loss: 0.9744 2022/09/06 03:35:11 - mmengine - INFO - Epoch(train) [83][120/940] lr: 1.0000e-04 eta: 3:51:43 time: 0.7118 data_time: 0.0297 memory: 22701 grad_norm: 5.3072 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 0.9690 loss: 0.9690 2022/09/06 03:35:29 - mmengine - INFO - Epoch(train) [83][140/940] lr: 1.0000e-04 eta: 3:51:27 time: 0.8868 data_time: 0.0689 memory: 22701 grad_norm: 5.3639 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9035 loss: 0.9035 2022/09/06 03:35:44 - mmengine - INFO - Epoch(train) [83][160/940] lr: 1.0000e-04 eta: 3:51:10 time: 0.7717 data_time: 0.0264 memory: 22701 grad_norm: 5.3772 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8462 loss: 0.8462 2022/09/06 03:36:01 - mmengine - INFO - Epoch(train) [83][180/940] lr: 1.0000e-04 eta: 3:50:53 time: 0.8257 data_time: 0.0411 memory: 22701 grad_norm: 5.3272 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9985 loss: 0.9985 2022/09/06 03:36:15 - mmengine - INFO - Epoch(train) [83][200/940] lr: 1.0000e-04 eta: 3:50:36 time: 0.6971 data_time: 0.0282 memory: 22701 grad_norm: 5.2891 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.8888 loss: 0.8888 2022/09/06 03:36:32 - mmengine - INFO - Epoch(train) [83][220/940] lr: 1.0000e-04 eta: 3:50:20 time: 0.8438 data_time: 0.0369 memory: 22701 grad_norm: 5.3067 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8897 loss: 0.8897 2022/09/06 03:36:47 - mmengine - INFO - Epoch(train) [83][240/940] lr: 1.0000e-04 eta: 3:50:03 time: 0.7567 data_time: 0.0292 memory: 22701 grad_norm: 5.4059 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9603 loss: 0.9603 2022/09/06 03:37:05 - mmengine - INFO - Epoch(train) [83][260/940] lr: 1.0000e-04 eta: 3:49:47 time: 0.9055 data_time: 0.0314 memory: 22701 grad_norm: 5.3675 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0460 loss: 1.0460 2022/09/06 03:37:20 - mmengine - INFO - Epoch(train) [83][280/940] lr: 1.0000e-04 eta: 3:49:30 time: 0.7508 data_time: 0.0208 memory: 22701 grad_norm: 5.3080 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.9965 loss: 0.9965 2022/09/06 03:37:36 - mmengine - INFO - Epoch(train) [83][300/940] lr: 1.0000e-04 eta: 3:49:13 time: 0.8153 data_time: 0.0274 memory: 22701 grad_norm: 5.2605 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9057 loss: 0.9057 2022/09/06 03:37:54 - mmengine - INFO - Epoch(train) [83][320/940] lr: 1.0000e-04 eta: 3:48:57 time: 0.8984 data_time: 0.0284 memory: 22701 grad_norm: 5.2550 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9019 loss: 0.9019 2022/09/06 03:38:08 - mmengine - INFO - Epoch(train) [83][340/940] lr: 1.0000e-04 eta: 3:48:40 time: 0.7217 data_time: 0.0970 memory: 22701 grad_norm: 5.2690 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9517 loss: 0.9517 2022/09/06 03:38:25 - mmengine - INFO - Epoch(train) [83][360/940] lr: 1.0000e-04 eta: 3:48:23 time: 0.8075 data_time: 0.1000 memory: 22701 grad_norm: 5.3065 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9631 loss: 0.9631 2022/09/06 03:38:43 - mmengine - INFO - Epoch(train) [83][380/940] lr: 1.0000e-04 eta: 3:48:07 time: 0.9045 data_time: 0.3556 memory: 22701 grad_norm: 5.2073 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.8980 loss: 0.8980 2022/09/06 03:38:57 - mmengine - INFO - Epoch(train) [83][400/940] lr: 1.0000e-04 eta: 3:47:50 time: 0.7040 data_time: 0.2178 memory: 22701 grad_norm: 5.4093 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8766 loss: 0.8766 2022/09/06 03:39:17 - mmengine - INFO - Epoch(train) [83][420/940] lr: 1.0000e-04 eta: 3:47:34 time: 1.0228 data_time: 0.5217 memory: 22701 grad_norm: 5.3747 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9851 loss: 0.9851 2022/09/06 03:39:33 - mmengine - INFO - Epoch(train) [83][440/940] lr: 1.0000e-04 eta: 3:47:18 time: 0.8098 data_time: 0.2948 memory: 22701 grad_norm: 5.4005 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0455 loss: 1.0455 2022/09/06 03:39:52 - mmengine - INFO - Epoch(train) [83][460/940] lr: 1.0000e-04 eta: 3:47:01 time: 0.9074 data_time: 0.1943 memory: 22701 grad_norm: 5.3723 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9608 loss: 0.9608 2022/09/06 03:40:07 - mmengine - INFO - Epoch(train) [83][480/940] lr: 1.0000e-04 eta: 3:46:45 time: 0.7632 data_time: 0.0711 memory: 22701 grad_norm: 5.2453 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9012 loss: 0.9012 2022/09/06 03:40:26 - mmengine - INFO - Epoch(train) [83][500/940] lr: 1.0000e-04 eta: 3:46:29 time: 0.9359 data_time: 0.2673 memory: 22701 grad_norm: 5.3989 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0118 loss: 1.0118 2022/09/06 03:40:41 - mmengine - INFO - Epoch(train) [83][520/940] lr: 1.0000e-04 eta: 3:46:12 time: 0.7698 data_time: 0.3073 memory: 22701 grad_norm: 5.2469 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9182 loss: 0.9182 2022/09/06 03:41:01 - mmengine - INFO - Epoch(train) [83][540/940] lr: 1.0000e-04 eta: 3:45:56 time: 1.0041 data_time: 0.4052 memory: 22701 grad_norm: 5.3626 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9218 loss: 0.9218 2022/09/06 03:41:17 - mmengine - INFO - Epoch(train) [83][560/940] lr: 1.0000e-04 eta: 3:45:39 time: 0.8123 data_time: 0.2813 memory: 22701 grad_norm: 5.3351 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0058 loss: 1.0058 2022/09/06 03:41:37 - mmengine - INFO - Epoch(train) [83][580/940] lr: 1.0000e-04 eta: 3:45:23 time: 0.9819 data_time: 0.1893 memory: 22701 grad_norm: 5.2713 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8321 loss: 0.8321 2022/09/06 03:41:53 - mmengine - INFO - Epoch(train) [83][600/940] lr: 1.0000e-04 eta: 3:45:07 time: 0.7888 data_time: 0.1633 memory: 22701 grad_norm: 5.1704 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9934 loss: 0.9934 2022/09/06 03:42:11 - mmengine - INFO - Epoch(train) [83][620/940] lr: 1.0000e-04 eta: 3:44:51 time: 0.9166 data_time: 0.2646 memory: 22701 grad_norm: 5.5371 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0256 loss: 1.0256 2022/09/06 03:42:28 - mmengine - INFO - Epoch(train) [83][640/940] lr: 1.0000e-04 eta: 3:44:34 time: 0.8633 data_time: 0.4071 memory: 22701 grad_norm: 5.3787 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9369 loss: 0.9369 2022/09/06 03:42:43 - mmengine - INFO - Epoch(train) [83][660/940] lr: 1.0000e-04 eta: 3:44:17 time: 0.7217 data_time: 0.1335 memory: 22701 grad_norm: 5.4117 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9822 loss: 0.9822 2022/09/06 03:42:59 - mmengine - INFO - Epoch(train) [83][680/940] lr: 1.0000e-04 eta: 3:44:00 time: 0.8090 data_time: 0.0946 memory: 22701 grad_norm: 5.2956 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9011 loss: 0.9011 2022/09/06 03:43:16 - mmengine - INFO - Epoch(train) [83][700/940] lr: 1.0000e-04 eta: 3:43:44 time: 0.8237 data_time: 0.0283 memory: 22701 grad_norm: 5.2690 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9445 loss: 0.9445 2022/09/06 03:43:31 - mmengine - INFO - Epoch(train) [83][720/940] lr: 1.0000e-04 eta: 3:43:27 time: 0.7769 data_time: 0.0251 memory: 22701 grad_norm: 5.3246 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8153 loss: 0.8153 2022/09/06 03:43:49 - mmengine - INFO - Epoch(train) [83][740/940] lr: 1.0000e-04 eta: 3:43:11 time: 0.9004 data_time: 0.0289 memory: 22701 grad_norm: 5.4110 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9331 loss: 0.9331 2022/09/06 03:44:02 - mmengine - INFO - Epoch(train) [83][760/940] lr: 1.0000e-04 eta: 3:42:54 time: 0.6644 data_time: 0.0278 memory: 22701 grad_norm: 5.2923 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9479 loss: 0.9479 2022/09/06 03:44:20 - mmengine - INFO - Epoch(train) [83][780/940] lr: 1.0000e-04 eta: 3:42:37 time: 0.8704 data_time: 0.0249 memory: 22701 grad_norm: 5.3088 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9728 loss: 0.9728 2022/09/06 03:44:35 - mmengine - INFO - Epoch(train) [83][800/940] lr: 1.0000e-04 eta: 3:42:21 time: 0.7763 data_time: 0.0229 memory: 22701 grad_norm: 5.4223 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0018 loss: 1.0018 2022/09/06 03:44:53 - mmengine - INFO - Epoch(train) [83][820/940] lr: 1.0000e-04 eta: 3:42:04 time: 0.8855 data_time: 0.0258 memory: 22701 grad_norm: 5.3161 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9674 loss: 0.9674 2022/09/06 03:45:08 - mmengine - INFO - Epoch(train) [83][840/940] lr: 1.0000e-04 eta: 3:41:47 time: 0.7389 data_time: 0.0352 memory: 22701 grad_norm: 5.3474 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9183 loss: 0.9183 2022/09/06 03:45:26 - mmengine - INFO - Epoch(train) [83][860/940] lr: 1.0000e-04 eta: 3:41:31 time: 0.8997 data_time: 0.0284 memory: 22701 grad_norm: 5.5352 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0326 loss: 1.0326 2022/09/06 03:45:40 - mmengine - INFO - Epoch(train) [83][880/940] lr: 1.0000e-04 eta: 3:41:14 time: 0.7199 data_time: 0.0259 memory: 22701 grad_norm: 5.3206 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9764 loss: 0.9764 2022/09/06 03:45:58 - mmengine - INFO - Epoch(train) [83][900/940] lr: 1.0000e-04 eta: 3:40:58 time: 0.8782 data_time: 0.0287 memory: 22701 grad_norm: 5.3064 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9484 loss: 0.9484 2022/09/06 03:46:12 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:46:12 - mmengine - INFO - Epoch(train) [83][920/940] lr: 1.0000e-04 eta: 3:40:41 time: 0.7173 data_time: 0.0344 memory: 22701 grad_norm: 5.3567 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0280 loss: 1.0280 2022/09/06 03:46:29 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 03:46:29 - mmengine - INFO - Epoch(train) [83][940/940] lr: 1.0000e-04 eta: 3:40:24 time: 0.8178 data_time: 0.0368 memory: 22701 grad_norm: 5.5074 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.8046 loss: 0.8046 2022/09/06 03:46:42 - mmengine - INFO - Epoch(val) [83][20/78] eta: 0:00:40 time: 0.6915 data_time: 0.5710 memory: 2247 2022/09/06 03:46:52 - mmengine - INFO - Epoch(val) [83][40/78] eta: 0:00:17 time: 0.4569 data_time: 0.3364 memory: 2247 2022/09/06 03:47:05 - mmengine - INFO - Epoch(val) [83][60/78] eta: 0:00:11 time: 0.6541 data_time: 0.5333 memory: 2247 2022/09/06 03:47:15 - mmengine - INFO - Epoch(val) [83][78/78] acc/top1: 0.6880 acc/top5: 0.8804 acc/mean1: 0.6879 2022/09/06 03:47:37 - mmengine - INFO - Epoch(train) [84][20/940] lr: 1.0000e-04 eta: 3:40:09 time: 1.0899 data_time: 0.6256 memory: 22701 grad_norm: 5.3143 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0156 loss: 1.0156 2022/09/06 03:47:51 - mmengine - INFO - Epoch(train) [84][40/940] lr: 1.0000e-04 eta: 3:39:52 time: 0.7034 data_time: 0.1913 memory: 22701 grad_norm: 5.2641 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9802 loss: 0.9802 2022/09/06 03:48:10 - mmengine - INFO - Epoch(train) [84][60/940] lr: 1.0000e-04 eta: 3:39:35 time: 0.9377 data_time: 0.5012 memory: 22701 grad_norm: 5.3752 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9771 loss: 0.9771 2022/09/06 03:48:24 - mmengine - INFO - Epoch(train) [84][80/940] lr: 1.0000e-04 eta: 3:39:19 time: 0.7337 data_time: 0.3441 memory: 22701 grad_norm: 5.3555 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9326 loss: 0.9326 2022/09/06 03:48:42 - mmengine - INFO - Epoch(train) [84][100/940] lr: 1.0000e-04 eta: 3:39:02 time: 0.8835 data_time: 0.5012 memory: 22701 grad_norm: 5.4333 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9874 loss: 0.9874 2022/09/06 03:48:56 - mmengine - INFO - Epoch(train) [84][120/940] lr: 1.0000e-04 eta: 3:38:45 time: 0.7183 data_time: 0.3114 memory: 22701 grad_norm: 5.3551 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 0.9796 loss: 0.9796 2022/09/06 03:49:15 - mmengine - INFO - Epoch(train) [84][140/940] lr: 1.0000e-04 eta: 3:38:29 time: 0.9419 data_time: 0.5299 memory: 22701 grad_norm: 5.3378 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9954 loss: 0.9954 2022/09/06 03:49:31 - mmengine - INFO - Epoch(train) [84][160/940] lr: 1.0000e-04 eta: 3:38:12 time: 0.7862 data_time: 0.3451 memory: 22701 grad_norm: 5.2595 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9824 loss: 0.9824 2022/09/06 03:49:50 - mmengine - INFO - Epoch(train) [84][180/940] lr: 1.0000e-04 eta: 3:37:56 time: 0.9705 data_time: 0.3963 memory: 22701 grad_norm: 5.2985 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9640 loss: 0.9640 2022/09/06 03:50:05 - mmengine - INFO - Epoch(train) [84][200/940] lr: 1.0000e-04 eta: 3:37:40 time: 0.7407 data_time: 0.1404 memory: 22701 grad_norm: 5.2956 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9307 loss: 0.9307 2022/09/06 03:50:24 - mmengine - INFO - Epoch(train) [84][220/940] lr: 1.0000e-04 eta: 3:37:24 time: 0.9655 data_time: 0.3993 memory: 22701 grad_norm: 5.3875 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9396 loss: 0.9396 2022/09/06 03:50:39 - mmengine - INFO - Epoch(train) [84][240/940] lr: 1.0000e-04 eta: 3:37:07 time: 0.7384 data_time: 0.2822 memory: 22701 grad_norm: 5.2991 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9520 loss: 0.9520 2022/09/06 03:50:57 - mmengine - INFO - Epoch(train) [84][260/940] lr: 1.0000e-04 eta: 3:36:50 time: 0.8622 data_time: 0.2129 memory: 22701 grad_norm: 5.3811 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0175 loss: 1.0175 2022/09/06 03:51:11 - mmengine - INFO - Epoch(train) [84][280/940] lr: 1.0000e-04 eta: 3:36:33 time: 0.7199 data_time: 0.0768 memory: 22701 grad_norm: 5.5237 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8872 loss: 0.8872 2022/09/06 03:51:31 - mmengine - INFO - Epoch(train) [84][300/940] lr: 1.0000e-04 eta: 3:36:17 time: 1.0147 data_time: 0.0713 memory: 22701 grad_norm: 5.3472 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9407 loss: 0.9407 2022/09/06 03:51:45 - mmengine - INFO - Epoch(train) [84][320/940] lr: 1.0000e-04 eta: 3:36:00 time: 0.7127 data_time: 0.0371 memory: 22701 grad_norm: 5.1996 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9243 loss: 0.9243 2022/09/06 03:52:03 - mmengine - INFO - Epoch(train) [84][340/940] lr: 1.0000e-04 eta: 3:35:44 time: 0.8706 data_time: 0.0315 memory: 22701 grad_norm: 5.3327 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0412 loss: 1.0412 2022/09/06 03:52:19 - mmengine - INFO - Epoch(train) [84][360/940] lr: 1.0000e-04 eta: 3:35:27 time: 0.7857 data_time: 0.0195 memory: 22701 grad_norm: 5.2354 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9653 loss: 0.9653 2022/09/06 03:52:39 - mmengine - INFO - Epoch(train) [84][380/940] lr: 1.0000e-04 eta: 3:35:12 time: 1.0402 data_time: 0.0445 memory: 22701 grad_norm: 5.3212 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0161 loss: 1.0161 2022/09/06 03:52:55 - mmengine - INFO - Epoch(train) [84][400/940] lr: 1.0000e-04 eta: 3:34:55 time: 0.7876 data_time: 0.0169 memory: 22701 grad_norm: 5.3628 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9803 loss: 0.9803 2022/09/06 03:53:16 - mmengine - INFO - Epoch(train) [84][420/940] lr: 1.0000e-04 eta: 3:34:39 time: 1.0159 data_time: 0.0549 memory: 22701 grad_norm: 5.4307 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9187 loss: 0.9187 2022/09/06 03:53:31 - mmengine - INFO - Epoch(train) [84][440/940] lr: 1.0000e-04 eta: 3:34:22 time: 0.7808 data_time: 0.0284 memory: 22701 grad_norm: 5.4061 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9825 loss: 0.9825 2022/09/06 03:53:49 - mmengine - INFO - Epoch(train) [84][460/940] lr: 1.0000e-04 eta: 3:34:06 time: 0.8871 data_time: 0.0283 memory: 22701 grad_norm: 5.4840 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0311 loss: 1.0311 2022/09/06 03:54:04 - mmengine - INFO - Epoch(train) [84][480/940] lr: 1.0000e-04 eta: 3:33:49 time: 0.7363 data_time: 0.0224 memory: 22701 grad_norm: 5.2866 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9403 loss: 0.9403 2022/09/06 03:54:21 - mmengine - INFO - Epoch(train) [84][500/940] lr: 1.0000e-04 eta: 3:33:33 time: 0.8647 data_time: 0.0244 memory: 22701 grad_norm: 5.4280 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9647 loss: 0.9647 2022/09/06 03:54:35 - mmengine - INFO - Epoch(train) [84][520/940] lr: 1.0000e-04 eta: 3:33:16 time: 0.6936 data_time: 0.0349 memory: 22701 grad_norm: 5.4223 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0149 loss: 1.0149 2022/09/06 03:54:51 - mmengine - INFO - Epoch(train) [84][540/940] lr: 1.0000e-04 eta: 3:32:59 time: 0.8347 data_time: 0.0268 memory: 22701 grad_norm: 5.4184 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8860 loss: 0.8860 2022/09/06 03:55:08 - mmengine - INFO - Epoch(train) [84][560/940] lr: 1.0000e-04 eta: 3:32:43 time: 0.8392 data_time: 0.0213 memory: 22701 grad_norm: 5.3462 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8579 loss: 0.8579 2022/09/06 03:55:29 - mmengine - INFO - Epoch(train) [84][580/940] lr: 1.0000e-04 eta: 3:32:27 time: 1.0174 data_time: 0.0246 memory: 22701 grad_norm: 5.3034 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8849 loss: 0.8849 2022/09/06 03:55:44 - mmengine - INFO - Epoch(train) [84][600/940] lr: 1.0000e-04 eta: 3:32:10 time: 0.7764 data_time: 0.0298 memory: 22701 grad_norm: 5.4173 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 0.9714 loss: 0.9714 2022/09/06 03:56:05 - mmengine - INFO - Epoch(train) [84][620/940] lr: 1.0000e-04 eta: 3:31:54 time: 1.0619 data_time: 0.0262 memory: 22701 grad_norm: 5.3369 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9385 loss: 0.9385 2022/09/06 03:56:20 - mmengine - INFO - Epoch(train) [84][640/940] lr: 1.0000e-04 eta: 3:31:37 time: 0.7273 data_time: 0.0278 memory: 22701 grad_norm: 5.3498 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9758 loss: 0.9758 2022/09/06 03:56:45 - mmengine - INFO - Epoch(train) [84][660/940] lr: 1.0000e-04 eta: 3:31:22 time: 1.2367 data_time: 0.0249 memory: 22701 grad_norm: 5.3158 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0080 loss: 1.0080 2022/09/06 03:57:02 - mmengine - INFO - Epoch(train) [84][680/940] lr: 1.0000e-04 eta: 3:31:06 time: 0.8831 data_time: 0.0240 memory: 22701 grad_norm: 5.2977 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9890 loss: 0.9890 2022/09/06 03:57:24 - mmengine - INFO - Epoch(train) [84][700/940] lr: 1.0000e-04 eta: 3:30:50 time: 1.0662 data_time: 0.0242 memory: 22701 grad_norm: 5.2893 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9101 loss: 0.9101 2022/09/06 03:57:38 - mmengine - INFO - Epoch(train) [84][720/940] lr: 1.0000e-04 eta: 3:30:33 time: 0.7111 data_time: 0.0226 memory: 22701 grad_norm: 5.3866 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0075 loss: 1.0075 2022/09/06 03:57:56 - mmengine - INFO - Epoch(train) [84][740/940] lr: 1.0000e-04 eta: 3:30:17 time: 0.8851 data_time: 0.0215 memory: 22701 grad_norm: 5.3602 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 0.9758 loss: 0.9758 2022/09/06 03:58:10 - mmengine - INFO - Epoch(train) [84][760/940] lr: 1.0000e-04 eta: 3:30:00 time: 0.7022 data_time: 0.0345 memory: 22701 grad_norm: 5.3153 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0691 loss: 1.0691 2022/09/06 03:58:26 - mmengine - INFO - Epoch(train) [84][780/940] lr: 1.0000e-04 eta: 3:29:44 time: 0.8388 data_time: 0.0212 memory: 22701 grad_norm: 5.3200 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9590 loss: 0.9590 2022/09/06 03:58:42 - mmengine - INFO - Epoch(train) [84][800/940] lr: 1.0000e-04 eta: 3:29:27 time: 0.7644 data_time: 0.0232 memory: 22701 grad_norm: 5.4004 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0481 loss: 1.0481 2022/09/06 03:59:00 - mmengine - INFO - Epoch(train) [84][820/940] lr: 1.0000e-04 eta: 3:29:10 time: 0.8971 data_time: 0.0406 memory: 22701 grad_norm: 5.3302 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9822 loss: 0.9822 2022/09/06 03:59:14 - mmengine - INFO - Epoch(train) [84][840/940] lr: 1.0000e-04 eta: 3:28:54 time: 0.7232 data_time: 0.0246 memory: 22701 grad_norm: 5.3738 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.9175 loss: 0.9175 2022/09/06 03:59:33 - mmengine - INFO - Epoch(train) [84][860/940] lr: 1.0000e-04 eta: 3:28:37 time: 0.9445 data_time: 0.0258 memory: 22701 grad_norm: 5.3594 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0231 loss: 1.0231 2022/09/06 03:59:49 - mmengine - INFO - Epoch(train) [84][880/940] lr: 1.0000e-04 eta: 3:28:21 time: 0.7777 data_time: 0.0295 memory: 22701 grad_norm: 5.3979 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9371 loss: 0.9371 2022/09/06 04:00:07 - mmengine - INFO - Epoch(train) [84][900/940] lr: 1.0000e-04 eta: 3:28:04 time: 0.9009 data_time: 0.0254 memory: 22701 grad_norm: 5.3334 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0085 loss: 1.0085 2022/09/06 04:00:21 - mmengine - INFO - Epoch(train) [84][920/940] lr: 1.0000e-04 eta: 3:27:47 time: 0.7179 data_time: 0.0307 memory: 22701 grad_norm: 5.2348 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9554 loss: 0.9554 2022/09/06 04:00:36 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:00:36 - mmengine - INFO - Epoch(train) [84][940/940] lr: 1.0000e-04 eta: 3:27:30 time: 0.7274 data_time: 0.0219 memory: 22701 grad_norm: 5.7804 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.9870 loss: 0.9870 2022/09/06 04:00:36 - mmengine - INFO - Saving checkpoint at 84 epochs 2022/09/06 04:00:52 - mmengine - INFO - Epoch(val) [84][20/78] eta: 0:00:41 time: 0.7091 data_time: 0.5919 memory: 2247 2022/09/06 04:01:00 - mmengine - INFO - Epoch(val) [84][40/78] eta: 0:00:16 time: 0.4427 data_time: 0.3250 memory: 2247 2022/09/06 04:01:13 - mmengine - INFO - Epoch(val) [84][60/78] eta: 0:00:11 time: 0.6433 data_time: 0.4947 memory: 2247 2022/09/06 04:01:23 - mmengine - INFO - Epoch(val) [84][78/78] acc/top1: 0.6884 acc/top5: 0.8797 acc/mean1: 0.6883 2022/09/06 04:01:42 - mmengine - INFO - Epoch(train) [85][20/940] lr: 1.0000e-04 eta: 3:27:14 time: 0.9764 data_time: 0.3812 memory: 22701 grad_norm: 5.3666 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8248 loss: 0.8248 2022/09/06 04:01:56 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:01:56 - mmengine - INFO - Epoch(train) [85][40/940] lr: 1.0000e-04 eta: 3:26:57 time: 0.6975 data_time: 0.1301 memory: 22701 grad_norm: 5.2842 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.9357 loss: 0.9357 2022/09/06 04:02:16 - mmengine - INFO - Epoch(train) [85][60/940] lr: 1.0000e-04 eta: 3:26:41 time: 0.9572 data_time: 0.1191 memory: 22701 grad_norm: 5.3364 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0205 loss: 1.0205 2022/09/06 04:02:30 - mmengine - INFO - Epoch(train) [85][80/940] lr: 1.0000e-04 eta: 3:26:24 time: 0.7473 data_time: 0.0191 memory: 22701 grad_norm: 5.4252 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.9279 loss: 0.9279 2022/09/06 04:02:49 - mmengine - INFO - Epoch(train) [85][100/940] lr: 1.0000e-04 eta: 3:26:08 time: 0.9227 data_time: 0.0316 memory: 22701 grad_norm: 5.3096 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9959 loss: 0.9959 2022/09/06 04:03:02 - mmengine - INFO - Epoch(train) [85][120/940] lr: 1.0000e-04 eta: 3:25:51 time: 0.6464 data_time: 0.0293 memory: 22701 grad_norm: 5.2636 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9468 loss: 0.9468 2022/09/06 04:03:21 - mmengine - INFO - Epoch(train) [85][140/940] lr: 1.0000e-04 eta: 3:25:35 time: 0.9687 data_time: 0.0377 memory: 22701 grad_norm: 5.2565 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 0.9220 loss: 0.9220 2022/09/06 04:03:36 - mmengine - INFO - Epoch(train) [85][160/940] lr: 1.0000e-04 eta: 3:25:18 time: 0.7499 data_time: 0.0243 memory: 22701 grad_norm: 5.3365 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9655 loss: 0.9655 2022/09/06 04:03:53 - mmengine - INFO - Epoch(train) [85][180/940] lr: 1.0000e-04 eta: 3:25:02 time: 0.8551 data_time: 0.0271 memory: 22701 grad_norm: 5.3259 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0190 loss: 1.0190 2022/09/06 04:04:07 - mmengine - INFO - Epoch(train) [85][200/940] lr: 1.0000e-04 eta: 3:24:45 time: 0.6808 data_time: 0.0241 memory: 22701 grad_norm: 5.2978 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9357 loss: 0.9357 2022/09/06 04:04:23 - mmengine - INFO - Epoch(train) [85][220/940] lr: 1.0000e-04 eta: 3:24:28 time: 0.7875 data_time: 0.0272 memory: 22701 grad_norm: 5.2401 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9611 loss: 0.9611 2022/09/06 04:04:36 - mmengine - INFO - Epoch(train) [85][240/940] lr: 1.0000e-04 eta: 3:24:11 time: 0.6465 data_time: 0.0262 memory: 22701 grad_norm: 5.3597 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0066 loss: 1.0066 2022/09/06 04:04:52 - mmengine - INFO - Epoch(train) [85][260/940] lr: 1.0000e-04 eta: 3:23:54 time: 0.8234 data_time: 0.0298 memory: 22701 grad_norm: 5.4516 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9173 loss: 0.9173 2022/09/06 04:05:05 - mmengine - INFO - Epoch(train) [85][280/940] lr: 1.0000e-04 eta: 3:23:37 time: 0.6616 data_time: 0.0560 memory: 22701 grad_norm: 5.3280 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0491 loss: 1.0491 2022/09/06 04:05:22 - mmengine - INFO - Epoch(train) [85][300/940] lr: 1.0000e-04 eta: 3:23:20 time: 0.8257 data_time: 0.1053 memory: 22701 grad_norm: 5.3837 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0483 loss: 1.0483 2022/09/06 04:05:35 - mmengine - INFO - Epoch(train) [85][320/940] lr: 1.0000e-04 eta: 3:23:03 time: 0.6691 data_time: 0.0610 memory: 22701 grad_norm: 5.3846 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8250 loss: 0.8250 2022/09/06 04:05:53 - mmengine - INFO - Epoch(train) [85][340/940] lr: 1.0000e-04 eta: 3:22:47 time: 0.8751 data_time: 0.0259 memory: 22701 grad_norm: 5.5343 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9864 loss: 0.9864 2022/09/06 04:06:07 - mmengine - INFO - Epoch(train) [85][360/940] lr: 1.0000e-04 eta: 3:22:30 time: 0.7014 data_time: 0.0534 memory: 22701 grad_norm: 5.3920 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8739 loss: 0.8739 2022/09/06 04:06:23 - mmengine - INFO - Epoch(train) [85][380/940] lr: 1.0000e-04 eta: 3:22:13 time: 0.8193 data_time: 0.0585 memory: 22701 grad_norm: 5.2703 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9771 loss: 0.9771 2022/09/06 04:06:38 - mmengine - INFO - Epoch(train) [85][400/940] lr: 1.0000e-04 eta: 3:21:56 time: 0.7626 data_time: 0.0521 memory: 22701 grad_norm: 5.1928 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8350 loss: 0.8350 2022/09/06 04:06:55 - mmengine - INFO - Epoch(train) [85][420/940] lr: 1.0000e-04 eta: 3:21:40 time: 0.8309 data_time: 0.1609 memory: 22701 grad_norm: 5.4870 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0202 loss: 1.0202 2022/09/06 04:07:10 - mmengine - INFO - Epoch(train) [85][440/940] lr: 1.0000e-04 eta: 3:21:23 time: 0.7445 data_time: 0.1022 memory: 22701 grad_norm: 5.3593 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.9131 loss: 0.9131 2022/09/06 04:07:27 - mmengine - INFO - Epoch(train) [85][460/940] lr: 1.0000e-04 eta: 3:21:07 time: 0.8709 data_time: 0.0324 memory: 22701 grad_norm: 5.2428 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9286 loss: 0.9286 2022/09/06 04:07:42 - mmengine - INFO - Epoch(train) [85][480/940] lr: 1.0000e-04 eta: 3:20:50 time: 0.6997 data_time: 0.0362 memory: 22701 grad_norm: 5.3863 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9638 loss: 0.9638 2022/09/06 04:07:56 - mmengine - INFO - Epoch(train) [85][500/940] lr: 1.0000e-04 eta: 3:20:33 time: 0.7366 data_time: 0.0335 memory: 22701 grad_norm: 5.3673 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 0.9410 loss: 0.9410 2022/09/06 04:08:12 - mmengine - INFO - Epoch(train) [85][520/940] lr: 1.0000e-04 eta: 3:20:16 time: 0.7845 data_time: 0.1496 memory: 22701 grad_norm: 5.3019 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0295 loss: 1.0295 2022/09/06 04:08:29 - mmengine - INFO - Epoch(train) [85][540/940] lr: 1.0000e-04 eta: 3:19:59 time: 0.8316 data_time: 0.1594 memory: 22701 grad_norm: 5.4220 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1147 loss: 1.1147 2022/09/06 04:08:46 - mmengine - INFO - Epoch(train) [85][560/940] lr: 1.0000e-04 eta: 3:19:43 time: 0.8743 data_time: 0.2892 memory: 22701 grad_norm: 5.2521 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8693 loss: 0.8693 2022/09/06 04:09:02 - mmengine - INFO - Epoch(train) [85][580/940] lr: 1.0000e-04 eta: 3:19:26 time: 0.8133 data_time: 0.3599 memory: 22701 grad_norm: 5.3135 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9768 loss: 0.9768 2022/09/06 04:09:16 - mmengine - INFO - Epoch(train) [85][600/940] lr: 1.0000e-04 eta: 3:19:09 time: 0.6979 data_time: 0.2601 memory: 22701 grad_norm: 5.2839 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0195 loss: 1.0195 2022/09/06 04:09:32 - mmengine - INFO - Epoch(train) [85][620/940] lr: 1.0000e-04 eta: 3:18:53 time: 0.8100 data_time: 0.3685 memory: 22701 grad_norm: 5.2135 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8387 loss: 0.8387 2022/09/06 04:09:46 - mmengine - INFO - Epoch(train) [85][640/940] lr: 1.0000e-04 eta: 3:18:36 time: 0.6737 data_time: 0.2424 memory: 22701 grad_norm: 5.4294 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9524 loss: 0.9524 2022/09/06 04:10:04 - mmengine - INFO - Epoch(train) [85][660/940] lr: 1.0000e-04 eta: 3:18:20 time: 0.9149 data_time: 0.3918 memory: 22701 grad_norm: 5.4166 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9243 loss: 0.9243 2022/09/06 04:10:19 - mmengine - INFO - Epoch(train) [85][680/940] lr: 1.0000e-04 eta: 3:18:03 time: 0.7166 data_time: 0.2452 memory: 22701 grad_norm: 5.3706 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8739 loss: 0.8739 2022/09/06 04:10:37 - mmengine - INFO - Epoch(train) [85][700/940] lr: 1.0000e-04 eta: 3:17:46 time: 0.9206 data_time: 0.3970 memory: 22701 grad_norm: 5.2682 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.8615 loss: 0.8615 2022/09/06 04:10:51 - mmengine - INFO - Epoch(train) [85][720/940] lr: 1.0000e-04 eta: 3:17:29 time: 0.6988 data_time: 0.2897 memory: 22701 grad_norm: 5.3556 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8720 loss: 0.8720 2022/09/06 04:11:07 - mmengine - INFO - Epoch(train) [85][740/940] lr: 1.0000e-04 eta: 3:17:13 time: 0.8089 data_time: 0.4266 memory: 22701 grad_norm: 5.2905 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9184 loss: 0.9184 2022/09/06 04:11:23 - mmengine - INFO - Epoch(train) [85][760/940] lr: 1.0000e-04 eta: 3:16:56 time: 0.7931 data_time: 0.4011 memory: 22701 grad_norm: 5.3860 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9040 loss: 0.9040 2022/09/06 04:11:42 - mmengine - INFO - Epoch(train) [85][780/940] lr: 1.0000e-04 eta: 3:16:40 time: 0.9246 data_time: 0.5117 memory: 22701 grad_norm: 5.3887 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9620 loss: 0.9620 2022/09/06 04:11:59 - mmengine - INFO - Epoch(train) [85][800/940] lr: 1.0000e-04 eta: 3:16:24 time: 0.8863 data_time: 0.5052 memory: 22701 grad_norm: 5.4359 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9794 loss: 0.9794 2022/09/06 04:12:17 - mmengine - INFO - Epoch(train) [85][820/940] lr: 1.0000e-04 eta: 3:16:07 time: 0.8900 data_time: 0.5118 memory: 22701 grad_norm: 5.3360 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9738 loss: 0.9738 2022/09/06 04:12:38 - mmengine - INFO - Epoch(train) [85][840/940] lr: 1.0000e-04 eta: 3:15:51 time: 1.0479 data_time: 0.6418 memory: 22701 grad_norm: 5.3606 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9171 loss: 0.9171 2022/09/06 04:12:52 - mmengine - INFO - Epoch(train) [85][860/940] lr: 1.0000e-04 eta: 3:15:34 time: 0.7154 data_time: 0.2642 memory: 22701 grad_norm: 5.3811 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9827 loss: 0.9827 2022/09/06 04:13:14 - mmengine - INFO - Epoch(train) [85][880/940] lr: 1.0000e-04 eta: 3:15:19 time: 1.0807 data_time: 0.6418 memory: 22701 grad_norm: 5.3833 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9354 loss: 0.9354 2022/09/06 04:13:28 - mmengine - INFO - Epoch(train) [85][900/940] lr: 1.0000e-04 eta: 3:15:02 time: 0.7196 data_time: 0.3198 memory: 22701 grad_norm: 5.3670 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0177 loss: 1.0177 2022/09/06 04:13:46 - mmengine - INFO - Epoch(train) [85][920/940] lr: 1.0000e-04 eta: 3:14:46 time: 0.8908 data_time: 0.4864 memory: 22701 grad_norm: 5.3534 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.8900 loss: 0.8900 2022/09/06 04:14:00 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:14:00 - mmengine - INFO - Epoch(train) [85][940/940] lr: 1.0000e-04 eta: 3:14:29 time: 0.6916 data_time: 0.3186 memory: 22701 grad_norm: 5.5804 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.9579 loss: 0.9579 2022/09/06 04:14:14 - mmengine - INFO - Epoch(val) [85][20/78] eta: 0:00:39 time: 0.6818 data_time: 0.5609 memory: 2247 2022/09/06 04:14:23 - mmengine - INFO - Epoch(val) [85][40/78] eta: 0:00:17 time: 0.4538 data_time: 0.3320 memory: 2247 2022/09/06 04:14:36 - mmengine - INFO - Epoch(val) [85][60/78] eta: 0:00:11 time: 0.6654 data_time: 0.5459 memory: 2247 2022/09/06 04:14:46 - mmengine - INFO - Epoch(val) [85][78/78] acc/top1: 0.6872 acc/top5: 0.8807 acc/mean1: 0.6871 2022/09/06 04:15:06 - mmengine - INFO - Epoch(train) [86][20/940] lr: 1.0000e-04 eta: 3:14:13 time: 1.0016 data_time: 0.5082 memory: 22701 grad_norm: 5.4516 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9505 loss: 0.9505 2022/09/06 04:15:20 - mmengine - INFO - Epoch(train) [86][40/940] lr: 1.0000e-04 eta: 3:13:56 time: 0.7050 data_time: 0.3007 memory: 22701 grad_norm: 5.2604 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9307 loss: 0.9307 2022/09/06 04:15:37 - mmengine - INFO - Epoch(train) [86][60/940] lr: 1.0000e-04 eta: 3:13:39 time: 0.8314 data_time: 0.1867 memory: 22701 grad_norm: 5.3038 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9119 loss: 0.9119 2022/09/06 04:15:50 - mmengine - INFO - Epoch(train) [86][80/940] lr: 1.0000e-04 eta: 3:13:22 time: 0.6458 data_time: 0.0948 memory: 22701 grad_norm: 5.2165 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9878 loss: 0.9878 2022/09/06 04:16:07 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:16:07 - mmengine - INFO - Epoch(train) [86][100/940] lr: 1.0000e-04 eta: 3:13:05 time: 0.8375 data_time: 0.1736 memory: 22701 grad_norm: 5.3320 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9515 loss: 0.9515 2022/09/06 04:16:22 - mmengine - INFO - Epoch(train) [86][120/940] lr: 1.0000e-04 eta: 3:12:48 time: 0.7382 data_time: 0.0813 memory: 22701 grad_norm: 5.3097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9408 loss: 0.9408 2022/09/06 04:16:36 - mmengine - INFO - Epoch(train) [86][140/940] lr: 1.0000e-04 eta: 3:12:32 time: 0.7402 data_time: 0.0303 memory: 22701 grad_norm: 5.3551 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9277 loss: 0.9277 2022/09/06 04:16:50 - mmengine - INFO - Epoch(train) [86][160/940] lr: 1.0000e-04 eta: 3:12:15 time: 0.6951 data_time: 0.0661 memory: 22701 grad_norm: 5.2280 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9025 loss: 0.9025 2022/09/06 04:17:07 - mmengine - INFO - Epoch(train) [86][180/940] lr: 1.0000e-04 eta: 3:11:58 time: 0.8447 data_time: 0.0331 memory: 22701 grad_norm: 5.3133 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1502 loss: 1.1502 2022/09/06 04:17:21 - mmengine - INFO - Epoch(train) [86][200/940] lr: 1.0000e-04 eta: 3:11:41 time: 0.6847 data_time: 0.0251 memory: 22701 grad_norm: 5.3393 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.9772 loss: 0.9772 2022/09/06 04:17:38 - mmengine - INFO - Epoch(train) [86][220/940] lr: 1.0000e-04 eta: 3:11:25 time: 0.8700 data_time: 0.0332 memory: 22701 grad_norm: 5.2695 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0134 loss: 1.0134 2022/09/06 04:17:53 - mmengine - INFO - Epoch(train) [86][240/940] lr: 1.0000e-04 eta: 3:11:08 time: 0.7316 data_time: 0.0483 memory: 22701 grad_norm: 5.3596 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8755 loss: 0.8755 2022/09/06 04:18:11 - mmengine - INFO - Epoch(train) [86][260/940] lr: 1.0000e-04 eta: 3:10:52 time: 0.9284 data_time: 0.0378 memory: 22701 grad_norm: 5.2714 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 0.9628 loss: 0.9628 2022/09/06 04:18:26 - mmengine - INFO - Epoch(train) [86][280/940] lr: 1.0000e-04 eta: 3:10:35 time: 0.7242 data_time: 0.0787 memory: 22701 grad_norm: 5.2576 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8533 loss: 0.8533 2022/09/06 04:18:44 - mmengine - INFO - Epoch(train) [86][300/940] lr: 1.0000e-04 eta: 3:10:18 time: 0.9107 data_time: 0.0334 memory: 22701 grad_norm: 5.3676 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 0.9791 loss: 0.9791 2022/09/06 04:19:00 - mmengine - INFO - Epoch(train) [86][320/940] lr: 1.0000e-04 eta: 3:10:02 time: 0.8060 data_time: 0.0256 memory: 22701 grad_norm: 5.3327 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0316 loss: 1.0316 2022/09/06 04:19:19 - mmengine - INFO - Epoch(train) [86][340/940] lr: 1.0000e-04 eta: 3:09:46 time: 0.9563 data_time: 0.0257 memory: 22701 grad_norm: 5.3796 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9103 loss: 0.9103 2022/09/06 04:19:34 - mmengine - INFO - Epoch(train) [86][360/940] lr: 1.0000e-04 eta: 3:09:29 time: 0.7163 data_time: 0.0255 memory: 22701 grad_norm: 5.3926 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9542 loss: 0.9542 2022/09/06 04:19:52 - mmengine - INFO - Epoch(train) [86][380/940] lr: 1.0000e-04 eta: 3:09:12 time: 0.9068 data_time: 0.0274 memory: 22701 grad_norm: 5.3783 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9190 loss: 0.9190 2022/09/06 04:20:09 - mmengine - INFO - Epoch(train) [86][400/940] lr: 1.0000e-04 eta: 3:08:56 time: 0.8586 data_time: 0.0295 memory: 22701 grad_norm: 5.3360 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9026 loss: 0.9026 2022/09/06 04:20:28 - mmengine - INFO - Epoch(train) [86][420/940] lr: 1.0000e-04 eta: 3:08:40 time: 0.9542 data_time: 0.0322 memory: 22701 grad_norm: 5.3251 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8782 loss: 0.8782 2022/09/06 04:20:44 - mmengine - INFO - Epoch(train) [86][440/940] lr: 1.0000e-04 eta: 3:08:23 time: 0.7856 data_time: 0.0298 memory: 22701 grad_norm: 5.3981 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0500 loss: 1.0500 2022/09/06 04:21:03 - mmengine - INFO - Epoch(train) [86][460/940] lr: 1.0000e-04 eta: 3:08:07 time: 0.9736 data_time: 0.0280 memory: 22701 grad_norm: 5.4131 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0047 loss: 1.0047 2022/09/06 04:21:18 - mmengine - INFO - Epoch(train) [86][480/940] lr: 1.0000e-04 eta: 3:07:50 time: 0.7258 data_time: 0.0267 memory: 22701 grad_norm: 5.2609 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.9252 loss: 0.9252 2022/09/06 04:21:37 - mmengine - INFO - Epoch(train) [86][500/940] lr: 1.0000e-04 eta: 3:07:34 time: 0.9741 data_time: 0.0257 memory: 22701 grad_norm: 5.4438 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9619 loss: 0.9619 2022/09/06 04:21:54 - mmengine - INFO - Epoch(train) [86][520/940] lr: 1.0000e-04 eta: 3:07:18 time: 0.8128 data_time: 0.0232 memory: 22701 grad_norm: 5.3850 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9687 loss: 0.9687 2022/09/06 04:22:12 - mmengine - INFO - Epoch(train) [86][540/940] lr: 1.0000e-04 eta: 3:07:01 time: 0.9250 data_time: 0.0269 memory: 22701 grad_norm: 5.2829 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9525 loss: 0.9525 2022/09/06 04:22:27 - mmengine - INFO - Epoch(train) [86][560/940] lr: 1.0000e-04 eta: 3:06:45 time: 0.7417 data_time: 0.0219 memory: 22701 grad_norm: 5.3952 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0170 loss: 1.0170 2022/09/06 04:22:46 - mmengine - INFO - Epoch(train) [86][580/940] lr: 1.0000e-04 eta: 3:06:28 time: 0.9276 data_time: 0.0243 memory: 22701 grad_norm: 5.3777 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9365 loss: 0.9365 2022/09/06 04:23:00 - mmengine - INFO - Epoch(train) [86][600/940] lr: 1.0000e-04 eta: 3:06:11 time: 0.7149 data_time: 0.0553 memory: 22701 grad_norm: 5.2575 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9349 loss: 0.9349 2022/09/06 04:23:17 - mmengine - INFO - Epoch(train) [86][620/940] lr: 1.0000e-04 eta: 3:05:55 time: 0.8418 data_time: 0.0432 memory: 22701 grad_norm: 5.3753 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9685 loss: 0.9685 2022/09/06 04:23:30 - mmengine - INFO - Epoch(train) [86][640/940] lr: 1.0000e-04 eta: 3:05:38 time: 0.6503 data_time: 0.0365 memory: 22701 grad_norm: 5.3870 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9446 loss: 0.9446 2022/09/06 04:23:47 - mmengine - INFO - Epoch(train) [86][660/940] lr: 1.0000e-04 eta: 3:05:21 time: 0.8564 data_time: 0.1117 memory: 22701 grad_norm: 5.2862 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9683 loss: 0.9683 2022/09/06 04:24:00 - mmengine - INFO - Epoch(train) [86][680/940] lr: 1.0000e-04 eta: 3:05:04 time: 0.6682 data_time: 0.1176 memory: 22701 grad_norm: 5.3076 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8898 loss: 0.8898 2022/09/06 04:24:17 - mmengine - INFO - Epoch(train) [86][700/940] lr: 1.0000e-04 eta: 3:04:48 time: 0.8532 data_time: 0.1257 memory: 22701 grad_norm: 5.3526 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8942 loss: 0.8942 2022/09/06 04:24:32 - mmengine - INFO - Epoch(train) [86][720/940] lr: 1.0000e-04 eta: 3:04:31 time: 0.7525 data_time: 0.2558 memory: 22701 grad_norm: 5.3766 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.8197 loss: 0.8197 2022/09/06 04:24:49 - mmengine - INFO - Epoch(train) [86][740/940] lr: 1.0000e-04 eta: 3:04:15 time: 0.8575 data_time: 0.4302 memory: 22701 grad_norm: 5.2472 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9423 loss: 0.9423 2022/09/06 04:25:05 - mmengine - INFO - Epoch(train) [86][760/940] lr: 1.0000e-04 eta: 3:03:58 time: 0.7814 data_time: 0.3149 memory: 22701 grad_norm: 5.2963 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9068 loss: 0.9068 2022/09/06 04:25:25 - mmengine - INFO - Epoch(train) [86][780/940] lr: 1.0000e-04 eta: 3:03:42 time: 0.9864 data_time: 0.5805 memory: 22701 grad_norm: 5.3640 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9342 loss: 0.9342 2022/09/06 04:25:40 - mmengine - INFO - Epoch(train) [86][800/940] lr: 1.0000e-04 eta: 3:03:25 time: 0.7386 data_time: 0.3103 memory: 22701 grad_norm: 5.4201 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1120 loss: 1.1120 2022/09/06 04:25:58 - mmengine - INFO - Epoch(train) [86][820/940] lr: 1.0000e-04 eta: 3:03:09 time: 0.9305 data_time: 0.5186 memory: 22701 grad_norm: 5.3173 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9489 loss: 0.9489 2022/09/06 04:26:13 - mmengine - INFO - Epoch(train) [86][840/940] lr: 1.0000e-04 eta: 3:02:52 time: 0.7296 data_time: 0.3399 memory: 22701 grad_norm: 5.4160 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0118 loss: 1.0118 2022/09/06 04:26:31 - mmengine - INFO - Epoch(train) [86][860/940] lr: 1.0000e-04 eta: 3:02:36 time: 0.9096 data_time: 0.5248 memory: 22701 grad_norm: 5.3688 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8991 loss: 0.8991 2022/09/06 04:26:47 - mmengine - INFO - Epoch(train) [86][880/940] lr: 1.0000e-04 eta: 3:02:19 time: 0.7877 data_time: 0.3697 memory: 22701 grad_norm: 5.3260 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9698 loss: 0.9698 2022/09/06 04:27:05 - mmengine - INFO - Epoch(train) [86][900/940] lr: 1.0000e-04 eta: 3:02:03 time: 0.9142 data_time: 0.4281 memory: 22701 grad_norm: 5.4081 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0241 loss: 1.0241 2022/09/06 04:27:25 - mmengine - INFO - Epoch(train) [86][920/940] lr: 1.0000e-04 eta: 3:01:47 time: 0.9817 data_time: 0.0921 memory: 22701 grad_norm: 5.4269 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0249 loss: 1.0249 2022/09/06 04:27:40 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:27:40 - mmengine - INFO - Epoch(train) [86][940/940] lr: 1.0000e-04 eta: 3:01:30 time: 0.7654 data_time: 0.0692 memory: 22701 grad_norm: 5.6358 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.9926 loss: 0.9926 2022/09/06 04:27:54 - mmengine - INFO - Epoch(val) [86][20/78] eta: 0:00:40 time: 0.6981 data_time: 0.5754 memory: 2247 2022/09/06 04:28:03 - mmengine - INFO - Epoch(val) [86][40/78] eta: 0:00:18 time: 0.4738 data_time: 0.3550 memory: 2247 2022/09/06 04:28:16 - mmengine - INFO - Epoch(val) [86][60/78] eta: 0:00:11 time: 0.6286 data_time: 0.5107 memory: 2247 2022/09/06 04:28:26 - mmengine - INFO - Epoch(val) [86][78/78] acc/top1: 0.6882 acc/top5: 0.8811 acc/mean1: 0.6881 2022/09/06 04:28:46 - mmengine - INFO - Epoch(train) [87][20/940] lr: 1.0000e-04 eta: 3:01:14 time: 0.9524 data_time: 0.4515 memory: 22701 grad_norm: 5.4755 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9452 loss: 0.9452 2022/09/06 04:28:59 - mmengine - INFO - Epoch(train) [87][40/940] lr: 1.0000e-04 eta: 3:00:57 time: 0.6715 data_time: 0.0938 memory: 22701 grad_norm: 5.3487 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9221 loss: 0.9221 2022/09/06 04:29:15 - mmengine - INFO - Epoch(train) [87][60/940] lr: 1.0000e-04 eta: 3:00:40 time: 0.8234 data_time: 0.2302 memory: 22701 grad_norm: 5.4229 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9290 loss: 0.9290 2022/09/06 04:29:30 - mmengine - INFO - Epoch(train) [87][80/940] lr: 1.0000e-04 eta: 3:00:23 time: 0.7205 data_time: 0.2118 memory: 22701 grad_norm: 5.2800 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9408 loss: 0.9408 2022/09/06 04:29:49 - mmengine - INFO - Epoch(train) [87][100/940] lr: 1.0000e-04 eta: 3:00:07 time: 0.9405 data_time: 0.2960 memory: 22701 grad_norm: 5.4513 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9496 loss: 0.9496 2022/09/06 04:30:06 - mmengine - INFO - Epoch(train) [87][120/940] lr: 1.0000e-04 eta: 2:59:51 time: 0.8785 data_time: 0.2073 memory: 22701 grad_norm: 5.3528 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0434 loss: 1.0434 2022/09/06 04:30:32 - mmengine - INFO - Epoch(train) [87][140/940] lr: 1.0000e-04 eta: 2:59:36 time: 1.2925 data_time: 0.0950 memory: 22701 grad_norm: 5.3830 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0265 loss: 1.0265 2022/09/06 04:30:49 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:30:49 - mmengine - INFO - Epoch(train) [87][160/940] lr: 1.0000e-04 eta: 2:59:19 time: 0.8355 data_time: 0.0547 memory: 22701 grad_norm: 5.3315 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8850 loss: 0.8850 2022/09/06 04:31:04 - mmengine - INFO - Epoch(train) [87][180/940] lr: 1.0000e-04 eta: 2:59:02 time: 0.7627 data_time: 0.1636 memory: 22701 grad_norm: 5.3335 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.8458 loss: 0.8458 2022/09/06 04:31:18 - mmengine - INFO - Epoch(train) [87][200/940] lr: 1.0000e-04 eta: 2:58:45 time: 0.7208 data_time: 0.0869 memory: 22701 grad_norm: 5.4445 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9995 loss: 0.9995 2022/09/06 04:31:33 - mmengine - INFO - Epoch(train) [87][220/940] lr: 1.0000e-04 eta: 2:58:29 time: 0.7290 data_time: 0.0359 memory: 22701 grad_norm: 5.3407 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0508 loss: 1.0508 2022/09/06 04:31:48 - mmengine - INFO - Epoch(train) [87][240/940] lr: 1.0000e-04 eta: 2:58:12 time: 0.7387 data_time: 0.0224 memory: 22701 grad_norm: 5.2030 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9383 loss: 0.9383 2022/09/06 04:32:03 - mmengine - INFO - Epoch(train) [87][260/940] lr: 1.0000e-04 eta: 2:57:55 time: 0.7554 data_time: 0.0996 memory: 22701 grad_norm: 5.4430 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0118 loss: 1.0118 2022/09/06 04:32:16 - mmengine - INFO - Epoch(train) [87][280/940] lr: 1.0000e-04 eta: 2:57:38 time: 0.6584 data_time: 0.0380 memory: 22701 grad_norm: 5.3489 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8780 loss: 0.8780 2022/09/06 04:32:33 - mmengine - INFO - Epoch(train) [87][300/940] lr: 1.0000e-04 eta: 2:57:21 time: 0.8406 data_time: 0.1442 memory: 22701 grad_norm: 5.2513 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9962 loss: 0.9962 2022/09/06 04:32:47 - mmengine - INFO - Epoch(train) [87][320/940] lr: 1.0000e-04 eta: 2:57:04 time: 0.7118 data_time: 0.1600 memory: 22701 grad_norm: 5.4108 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.9630 loss: 0.9630 2022/09/06 04:33:07 - mmengine - INFO - Epoch(train) [87][340/940] lr: 1.0000e-04 eta: 2:56:48 time: 0.9847 data_time: 0.3315 memory: 22701 grad_norm: 5.3103 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0300 loss: 1.0300 2022/09/06 04:33:25 - mmengine - INFO - Epoch(train) [87][360/940] lr: 1.0000e-04 eta: 2:56:32 time: 0.8931 data_time: 0.1746 memory: 22701 grad_norm: 5.3362 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8204 loss: 0.8204 2022/09/06 04:33:41 - mmengine - INFO - Epoch(train) [87][380/940] lr: 1.0000e-04 eta: 2:56:15 time: 0.8232 data_time: 0.0329 memory: 22701 grad_norm: 5.3192 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9541 loss: 0.9541 2022/09/06 04:33:55 - mmengine - INFO - Epoch(train) [87][400/940] lr: 1.0000e-04 eta: 2:55:58 time: 0.7012 data_time: 0.0369 memory: 22701 grad_norm: 5.2852 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9281 loss: 0.9281 2022/09/06 04:34:12 - mmengine - INFO - Epoch(train) [87][420/940] lr: 1.0000e-04 eta: 2:55:42 time: 0.8413 data_time: 0.0459 memory: 22701 grad_norm: 5.3378 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9493 loss: 0.9493 2022/09/06 04:34:28 - mmengine - INFO - Epoch(train) [87][440/940] lr: 1.0000e-04 eta: 2:55:25 time: 0.7771 data_time: 0.1058 memory: 22701 grad_norm: 5.4525 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9635 loss: 0.9635 2022/09/06 04:34:45 - mmengine - INFO - Epoch(train) [87][460/940] lr: 1.0000e-04 eta: 2:55:09 time: 0.8601 data_time: 0.2796 memory: 22701 grad_norm: 5.3426 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9878 loss: 0.9878 2022/09/06 04:35:00 - mmengine - INFO - Epoch(train) [87][480/940] lr: 1.0000e-04 eta: 2:54:52 time: 0.7535 data_time: 0.2213 memory: 22701 grad_norm: 5.3131 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 0.9758 loss: 0.9758 2022/09/06 04:35:18 - mmengine - INFO - Epoch(train) [87][500/940] lr: 1.0000e-04 eta: 2:54:36 time: 0.9001 data_time: 0.1373 memory: 22701 grad_norm: 5.4505 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9836 loss: 0.9836 2022/09/06 04:35:32 - mmengine - INFO - Epoch(train) [87][520/940] lr: 1.0000e-04 eta: 2:54:19 time: 0.6791 data_time: 0.0184 memory: 22701 grad_norm: 5.2939 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9908 loss: 0.9908 2022/09/06 04:35:48 - mmengine - INFO - Epoch(train) [87][540/940] lr: 1.0000e-04 eta: 2:54:02 time: 0.8477 data_time: 0.0228 memory: 22701 grad_norm: 5.4091 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0672 loss: 1.0672 2022/09/06 04:36:03 - mmengine - INFO - Epoch(train) [87][560/940] lr: 1.0000e-04 eta: 2:53:45 time: 0.7386 data_time: 0.0259 memory: 22701 grad_norm: 5.2473 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9745 loss: 0.9745 2022/09/06 04:36:23 - mmengine - INFO - Epoch(train) [87][580/940] lr: 1.0000e-04 eta: 2:53:29 time: 0.9726 data_time: 0.0313 memory: 22701 grad_norm: 5.4045 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9348 loss: 0.9348 2022/09/06 04:36:37 - mmengine - INFO - Epoch(train) [87][600/940] lr: 1.0000e-04 eta: 2:53:12 time: 0.7132 data_time: 0.0303 memory: 22701 grad_norm: 5.5124 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0266 loss: 1.0266 2022/09/06 04:36:54 - mmengine - INFO - Epoch(train) [87][620/940] lr: 1.0000e-04 eta: 2:52:56 time: 0.8551 data_time: 0.0337 memory: 22701 grad_norm: 5.4467 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0016 loss: 1.0016 2022/09/06 04:37:08 - mmengine - INFO - Epoch(train) [87][640/940] lr: 1.0000e-04 eta: 2:52:39 time: 0.6878 data_time: 0.0294 memory: 22701 grad_norm: 5.4531 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9179 loss: 0.9179 2022/09/06 04:37:26 - mmengine - INFO - Epoch(train) [87][660/940] lr: 1.0000e-04 eta: 2:52:23 time: 0.9234 data_time: 0.0383 memory: 22701 grad_norm: 5.3168 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0285 loss: 1.0285 2022/09/06 04:37:43 - mmengine - INFO - Epoch(train) [87][680/940] lr: 1.0000e-04 eta: 2:52:06 time: 0.8353 data_time: 0.0215 memory: 22701 grad_norm: 5.2782 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 0.9528 loss: 0.9528 2022/09/06 04:38:02 - mmengine - INFO - Epoch(train) [87][700/940] lr: 1.0000e-04 eta: 2:51:50 time: 0.9661 data_time: 0.0235 memory: 22701 grad_norm: 5.4815 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0199 loss: 1.0199 2022/09/06 04:38:17 - mmengine - INFO - Epoch(train) [87][720/940] lr: 1.0000e-04 eta: 2:51:33 time: 0.7158 data_time: 0.0243 memory: 22701 grad_norm: 5.3177 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9821 loss: 0.9821 2022/09/06 04:38:36 - mmengine - INFO - Epoch(train) [87][740/940] lr: 1.0000e-04 eta: 2:51:17 time: 0.9591 data_time: 0.0230 memory: 22701 grad_norm: 5.3396 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0015 loss: 1.0015 2022/09/06 04:38:51 - mmengine - INFO - Epoch(train) [87][760/940] lr: 1.0000e-04 eta: 2:51:00 time: 0.7680 data_time: 0.0463 memory: 22701 grad_norm: 5.3255 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0005 loss: 1.0005 2022/09/06 04:39:10 - mmengine - INFO - Epoch(train) [87][780/940] lr: 1.0000e-04 eta: 2:50:44 time: 0.9481 data_time: 0.1188 memory: 22701 grad_norm: 5.2685 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.8628 loss: 0.8628 2022/09/06 04:39:28 - mmengine - INFO - Epoch(train) [87][800/940] lr: 1.0000e-04 eta: 2:50:28 time: 0.8828 data_time: 0.0273 memory: 22701 grad_norm: 5.3105 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9358 loss: 0.9358 2022/09/06 04:39:47 - mmengine - INFO - Epoch(train) [87][820/940] lr: 1.0000e-04 eta: 2:50:11 time: 0.9353 data_time: 0.0300 memory: 22701 grad_norm: 5.2991 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0124 loss: 1.0124 2022/09/06 04:40:03 - mmengine - INFO - Epoch(train) [87][840/940] lr: 1.0000e-04 eta: 2:49:55 time: 0.8073 data_time: 0.0233 memory: 22701 grad_norm: 5.3054 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9271 loss: 0.9271 2022/09/06 04:40:20 - mmengine - INFO - Epoch(train) [87][860/940] lr: 1.0000e-04 eta: 2:49:38 time: 0.8496 data_time: 0.0251 memory: 22701 grad_norm: 5.3348 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9678 loss: 0.9678 2022/09/06 04:40:36 - mmengine - INFO - Epoch(train) [87][880/940] lr: 1.0000e-04 eta: 2:49:22 time: 0.8176 data_time: 0.0211 memory: 22701 grad_norm: 5.3699 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9022 loss: 0.9022 2022/09/06 04:40:57 - mmengine - INFO - Epoch(train) [87][900/940] lr: 1.0000e-04 eta: 2:49:06 time: 1.0280 data_time: 0.0347 memory: 22701 grad_norm: 5.2429 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9348 loss: 0.9348 2022/09/06 04:41:14 - mmengine - INFO - Epoch(train) [87][920/940] lr: 1.0000e-04 eta: 2:48:49 time: 0.8506 data_time: 0.1238 memory: 22701 grad_norm: 5.3051 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8245 loss: 0.8245 2022/09/06 04:41:31 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:41:31 - mmengine - INFO - Epoch(train) [87][940/940] lr: 1.0000e-04 eta: 2:48:33 time: 0.8551 data_time: 0.1435 memory: 22701 grad_norm: 5.7838 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 0.9994 loss: 0.9994 2022/09/06 04:41:31 - mmengine - INFO - Saving checkpoint at 87 epochs 2022/09/06 04:41:47 - mmengine - INFO - Epoch(val) [87][20/78] eta: 0:00:40 time: 0.7009 data_time: 0.5855 memory: 2247 2022/09/06 04:41:56 - mmengine - INFO - Epoch(val) [87][40/78] eta: 0:00:16 time: 0.4453 data_time: 0.3294 memory: 2247 2022/09/06 04:42:09 - mmengine - INFO - Epoch(val) [87][60/78] eta: 0:00:11 time: 0.6484 data_time: 0.5320 memory: 2247 2022/09/06 04:42:18 - mmengine - INFO - Epoch(val) [87][78/78] acc/top1: 0.6878 acc/top5: 0.8805 acc/mean1: 0.6877 2022/09/06 04:42:38 - mmengine - INFO - Epoch(train) [88][20/940] lr: 1.0000e-04 eta: 2:48:17 time: 0.9944 data_time: 0.5220 memory: 22701 grad_norm: 5.2253 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0064 loss: 1.0064 2022/09/06 04:42:53 - mmengine - INFO - Epoch(train) [88][40/940] lr: 1.0000e-04 eta: 2:48:00 time: 0.7240 data_time: 0.1992 memory: 22701 grad_norm: 5.3701 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9444 loss: 0.9444 2022/09/06 04:43:09 - mmengine - INFO - Epoch(train) [88][60/940] lr: 1.0000e-04 eta: 2:47:43 time: 0.7948 data_time: 0.3181 memory: 22701 grad_norm: 5.3253 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9930 loss: 0.9930 2022/09/06 04:43:22 - mmengine - INFO - Epoch(train) [88][80/940] lr: 1.0000e-04 eta: 2:47:26 time: 0.6826 data_time: 0.1745 memory: 22701 grad_norm: 5.3089 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8339 loss: 0.8339 2022/09/06 04:43:39 - mmengine - INFO - Epoch(train) [88][100/940] lr: 1.0000e-04 eta: 2:47:10 time: 0.8192 data_time: 0.1590 memory: 22701 grad_norm: 5.3378 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.9749 loss: 0.9749 2022/09/06 04:43:53 - mmengine - INFO - Epoch(train) [88][120/940] lr: 1.0000e-04 eta: 2:46:53 time: 0.7356 data_time: 0.2353 memory: 22701 grad_norm: 5.2954 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0056 loss: 1.0056 2022/09/06 04:44:10 - mmengine - INFO - Epoch(train) [88][140/940] lr: 1.0000e-04 eta: 2:46:36 time: 0.8053 data_time: 0.1967 memory: 22701 grad_norm: 5.1956 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9084 loss: 0.9084 2022/09/06 04:44:23 - mmengine - INFO - Epoch(train) [88][160/940] lr: 1.0000e-04 eta: 2:46:19 time: 0.6555 data_time: 0.2166 memory: 22701 grad_norm: 5.3833 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9504 loss: 0.9504 2022/09/06 04:44:41 - mmengine - INFO - Epoch(train) [88][180/940] lr: 1.0000e-04 eta: 2:46:03 time: 0.9265 data_time: 0.5183 memory: 22701 grad_norm: 5.3628 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1189 loss: 1.1189 2022/09/06 04:44:57 - mmengine - INFO - Epoch(train) [88][200/940] lr: 1.0000e-04 eta: 2:45:46 time: 0.7705 data_time: 0.3015 memory: 22701 grad_norm: 5.2758 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9228 loss: 0.9228 2022/09/06 04:45:17 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:45:17 - mmengine - INFO - Epoch(train) [88][220/940] lr: 1.0000e-04 eta: 2:45:30 time: 0.9972 data_time: 0.2677 memory: 22701 grad_norm: 5.3762 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0541 loss: 1.0541 2022/09/06 04:45:30 - mmengine - INFO - Epoch(train) [88][240/940] lr: 1.0000e-04 eta: 2:45:13 time: 0.6957 data_time: 0.1355 memory: 22701 grad_norm: 5.4275 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 0.9265 loss: 0.9265 2022/09/06 04:45:49 - mmengine - INFO - Epoch(train) [88][260/940] lr: 1.0000e-04 eta: 2:44:57 time: 0.9045 data_time: 0.3929 memory: 22701 grad_norm: 5.4611 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9160 loss: 0.9160 2022/09/06 04:46:02 - mmengine - INFO - Epoch(train) [88][280/940] lr: 1.0000e-04 eta: 2:44:40 time: 0.6900 data_time: 0.2226 memory: 22701 grad_norm: 5.4116 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9351 loss: 0.9351 2022/09/06 04:46:19 - mmengine - INFO - Epoch(train) [88][300/940] lr: 1.0000e-04 eta: 2:44:23 time: 0.8170 data_time: 0.3623 memory: 22701 grad_norm: 5.2547 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.7691 loss: 0.7691 2022/09/06 04:46:35 - mmengine - INFO - Epoch(train) [88][320/940] lr: 1.0000e-04 eta: 2:44:07 time: 0.8130 data_time: 0.2642 memory: 22701 grad_norm: 5.3892 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0276 loss: 1.0276 2022/09/06 04:46:54 - mmengine - INFO - Epoch(train) [88][340/940] lr: 1.0000e-04 eta: 2:43:51 time: 0.9391 data_time: 0.4784 memory: 22701 grad_norm: 5.3610 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8946 loss: 0.8946 2022/09/06 04:47:09 - mmengine - INFO - Epoch(train) [88][360/940] lr: 1.0000e-04 eta: 2:43:34 time: 0.7429 data_time: 0.3575 memory: 22701 grad_norm: 5.2605 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9989 loss: 0.9989 2022/09/06 04:47:28 - mmengine - INFO - Epoch(train) [88][380/940] lr: 1.0000e-04 eta: 2:43:18 time: 0.9583 data_time: 0.5519 memory: 22701 grad_norm: 5.3752 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9131 loss: 0.9131 2022/09/06 04:47:43 - mmengine - INFO - Epoch(train) [88][400/940] lr: 1.0000e-04 eta: 2:43:01 time: 0.7452 data_time: 0.3568 memory: 22701 grad_norm: 5.3401 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9877 loss: 0.9877 2022/09/06 04:48:04 - mmengine - INFO - Epoch(train) [88][420/940] lr: 1.0000e-04 eta: 2:42:45 time: 1.0563 data_time: 0.6290 memory: 22701 grad_norm: 5.3996 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9894 loss: 0.9894 2022/09/06 04:48:19 - mmengine - INFO - Epoch(train) [88][440/940] lr: 1.0000e-04 eta: 2:42:28 time: 0.7812 data_time: 0.2318 memory: 22701 grad_norm: 5.3667 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9077 loss: 0.9077 2022/09/06 04:48:38 - mmengine - INFO - Epoch(train) [88][460/940] lr: 1.0000e-04 eta: 2:42:12 time: 0.9179 data_time: 0.3531 memory: 22701 grad_norm: 5.3710 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0294 loss: 1.0294 2022/09/06 04:48:53 - mmengine - INFO - Epoch(train) [88][480/940] lr: 1.0000e-04 eta: 2:41:55 time: 0.7340 data_time: 0.1467 memory: 22701 grad_norm: 5.2882 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8956 loss: 0.8956 2022/09/06 04:49:11 - mmengine - INFO - Epoch(train) [88][500/940] lr: 1.0000e-04 eta: 2:41:39 time: 0.8999 data_time: 0.0514 memory: 22701 grad_norm: 5.3337 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0849 loss: 1.0849 2022/09/06 04:49:24 - mmengine - INFO - Epoch(train) [88][520/940] lr: 1.0000e-04 eta: 2:41:22 time: 0.6857 data_time: 0.0298 memory: 22701 grad_norm: 5.2486 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0147 loss: 1.0147 2022/09/06 04:49:41 - mmengine - INFO - Epoch(train) [88][540/940] lr: 1.0000e-04 eta: 2:41:05 time: 0.8345 data_time: 0.0361 memory: 22701 grad_norm: 5.3110 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.9646 loss: 0.9646 2022/09/06 04:49:54 - mmengine - INFO - Epoch(train) [88][560/940] lr: 1.0000e-04 eta: 2:40:48 time: 0.6415 data_time: 0.0313 memory: 22701 grad_norm: 5.3560 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8851 loss: 0.8851 2022/09/06 04:50:10 - mmengine - INFO - Epoch(train) [88][580/940] lr: 1.0000e-04 eta: 2:40:32 time: 0.8269 data_time: 0.0342 memory: 22701 grad_norm: 5.3037 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8800 loss: 0.8800 2022/09/06 04:50:24 - mmengine - INFO - Epoch(train) [88][600/940] lr: 1.0000e-04 eta: 2:40:15 time: 0.7090 data_time: 0.0286 memory: 22701 grad_norm: 5.3657 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9172 loss: 0.9172 2022/09/06 04:50:46 - mmengine - INFO - Epoch(train) [88][620/940] lr: 1.0000e-04 eta: 2:39:59 time: 1.0911 data_time: 0.0254 memory: 22701 grad_norm: 5.3419 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9324 loss: 0.9324 2022/09/06 04:51:01 - mmengine - INFO - Epoch(train) [88][640/940] lr: 1.0000e-04 eta: 2:39:42 time: 0.7509 data_time: 0.0255 memory: 22701 grad_norm: 5.5087 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.8415 loss: 0.8415 2022/09/06 04:51:21 - mmengine - INFO - Epoch(train) [88][660/940] lr: 1.0000e-04 eta: 2:39:26 time: 0.9798 data_time: 0.0262 memory: 22701 grad_norm: 5.2981 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0065 loss: 1.0065 2022/09/06 04:51:37 - mmengine - INFO - Epoch(train) [88][680/940] lr: 1.0000e-04 eta: 2:39:09 time: 0.7987 data_time: 0.0267 memory: 22701 grad_norm: 5.3288 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9433 loss: 0.9433 2022/09/06 04:51:56 - mmengine - INFO - Epoch(train) [88][700/940] lr: 1.0000e-04 eta: 2:38:53 time: 0.9681 data_time: 0.0265 memory: 22701 grad_norm: 5.3018 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0744 loss: 1.0744 2022/09/06 04:52:10 - mmengine - INFO - Epoch(train) [88][720/940] lr: 1.0000e-04 eta: 2:38:36 time: 0.6730 data_time: 0.0235 memory: 22701 grad_norm: 5.4331 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9805 loss: 0.9805 2022/09/06 04:52:27 - mmengine - INFO - Epoch(train) [88][740/940] lr: 1.0000e-04 eta: 2:38:20 time: 0.8691 data_time: 0.0264 memory: 22701 grad_norm: 5.2584 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8770 loss: 0.8770 2022/09/06 04:52:42 - mmengine - INFO - Epoch(train) [88][760/940] lr: 1.0000e-04 eta: 2:38:03 time: 0.7471 data_time: 0.0277 memory: 22701 grad_norm: 5.2838 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.8982 loss: 0.8982 2022/09/06 04:53:00 - mmengine - INFO - Epoch(train) [88][780/940] lr: 1.0000e-04 eta: 2:37:47 time: 0.8976 data_time: 0.0329 memory: 22701 grad_norm: 5.2132 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9017 loss: 0.9017 2022/09/06 04:53:19 - mmengine - INFO - Epoch(train) [88][800/940] lr: 1.0000e-04 eta: 2:37:31 time: 0.9285 data_time: 0.0470 memory: 22701 grad_norm: 5.3562 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.9812 loss: 0.9812 2022/09/06 04:53:34 - mmengine - INFO - Epoch(train) [88][820/940] lr: 1.0000e-04 eta: 2:37:14 time: 0.7605 data_time: 0.0280 memory: 22701 grad_norm: 5.4402 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0269 loss: 1.0269 2022/09/06 04:53:53 - mmengine - INFO - Epoch(train) [88][840/940] lr: 1.0000e-04 eta: 2:36:58 time: 0.9405 data_time: 0.0277 memory: 22701 grad_norm: 5.4559 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0137 loss: 1.0137 2022/09/06 04:54:07 - mmengine - INFO - Epoch(train) [88][860/940] lr: 1.0000e-04 eta: 2:36:41 time: 0.7163 data_time: 0.0226 memory: 22701 grad_norm: 5.3896 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8751 loss: 0.8751 2022/09/06 04:54:27 - mmengine - INFO - Epoch(train) [88][880/940] lr: 1.0000e-04 eta: 2:36:25 time: 0.9747 data_time: 0.0319 memory: 22701 grad_norm: 5.3721 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.9720 loss: 0.9720 2022/09/06 04:54:45 - mmengine - INFO - Epoch(train) [88][900/940] lr: 1.0000e-04 eta: 2:36:08 time: 0.9089 data_time: 0.0235 memory: 22701 grad_norm: 5.4272 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1002 loss: 1.1002 2022/09/06 04:55:05 - mmengine - INFO - Epoch(train) [88][920/940] lr: 1.0000e-04 eta: 2:35:52 time: 0.9913 data_time: 0.0281 memory: 22701 grad_norm: 5.3243 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9535 loss: 0.9535 2022/09/06 04:55:18 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:55:18 - mmengine - INFO - Epoch(train) [88][940/940] lr: 1.0000e-04 eta: 2:35:35 time: 0.6898 data_time: 0.0221 memory: 22701 grad_norm: 5.6247 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 0.9301 loss: 0.9301 2022/09/06 04:55:32 - mmengine - INFO - Epoch(val) [88][20/78] eta: 0:00:39 time: 0.6856 data_time: 0.5656 memory: 2247 2022/09/06 04:55:41 - mmengine - INFO - Epoch(val) [88][40/78] eta: 0:00:17 time: 0.4497 data_time: 0.3325 memory: 2247 2022/09/06 04:55:54 - mmengine - INFO - Epoch(val) [88][60/78] eta: 0:00:11 time: 0.6560 data_time: 0.5382 memory: 2247 2022/09/06 04:56:04 - mmengine - INFO - Epoch(val) [88][78/78] acc/top1: 0.6888 acc/top5: 0.8795 acc/mean1: 0.6887 2022/09/06 04:56:27 - mmengine - INFO - Epoch(train) [89][20/940] lr: 1.0000e-04 eta: 2:35:19 time: 1.1225 data_time: 0.5628 memory: 22701 grad_norm: 5.4057 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9068 loss: 0.9068 2022/09/06 04:56:41 - mmengine - INFO - Epoch(train) [89][40/940] lr: 1.0000e-04 eta: 2:35:03 time: 0.7210 data_time: 0.1395 memory: 22701 grad_norm: 5.3441 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 0.9272 loss: 0.9272 2022/09/06 04:56:57 - mmengine - INFO - Epoch(train) [89][60/940] lr: 1.0000e-04 eta: 2:34:46 time: 0.7828 data_time: 0.0443 memory: 22701 grad_norm: 5.3579 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9058 loss: 0.9058 2022/09/06 04:57:10 - mmengine - INFO - Epoch(train) [89][80/940] lr: 1.0000e-04 eta: 2:34:29 time: 0.6535 data_time: 0.0460 memory: 22701 grad_norm: 5.3526 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.0670 loss: 1.0670 2022/09/06 04:57:27 - mmengine - INFO - Epoch(train) [89][100/940] lr: 1.0000e-04 eta: 2:34:12 time: 0.8599 data_time: 0.0855 memory: 22701 grad_norm: 5.5493 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0581 loss: 1.0581 2022/09/06 04:57:41 - mmengine - INFO - Epoch(train) [89][120/940] lr: 1.0000e-04 eta: 2:33:55 time: 0.6797 data_time: 0.0406 memory: 22701 grad_norm: 5.4292 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9951 loss: 0.9951 2022/09/06 04:57:58 - mmengine - INFO - Epoch(train) [89][140/940] lr: 1.0000e-04 eta: 2:33:39 time: 0.8368 data_time: 0.0610 memory: 22701 grad_norm: 5.4564 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9047 loss: 0.9047 2022/09/06 04:58:11 - mmengine - INFO - Epoch(train) [89][160/940] lr: 1.0000e-04 eta: 2:33:22 time: 0.6914 data_time: 0.0454 memory: 22701 grad_norm: 5.3584 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0278 loss: 1.0278 2022/09/06 04:58:29 - mmengine - INFO - Epoch(train) [89][180/940] lr: 1.0000e-04 eta: 2:33:06 time: 0.8733 data_time: 0.1432 memory: 22701 grad_norm: 5.4589 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0172 loss: 1.0172 2022/09/06 04:58:44 - mmengine - INFO - Epoch(train) [89][200/940] lr: 1.0000e-04 eta: 2:32:49 time: 0.7535 data_time: 0.0413 memory: 22701 grad_norm: 5.4576 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9064 loss: 0.9064 2022/09/06 04:59:01 - mmengine - INFO - Epoch(train) [89][220/940] lr: 1.0000e-04 eta: 2:32:32 time: 0.8583 data_time: 0.0293 memory: 22701 grad_norm: 5.2848 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8597 loss: 0.8597 2022/09/06 04:59:14 - mmengine - INFO - Epoch(train) [89][240/940] lr: 1.0000e-04 eta: 2:32:15 time: 0.6688 data_time: 0.0304 memory: 22701 grad_norm: 5.4555 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9149 loss: 0.9149 2022/09/06 04:59:30 - mmengine - INFO - Epoch(train) [89][260/940] lr: 1.0000e-04 eta: 2:31:59 time: 0.7964 data_time: 0.0257 memory: 22701 grad_norm: 5.2963 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9976 loss: 0.9976 2022/09/06 04:59:43 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 04:59:43 - mmengine - INFO - Epoch(train) [89][280/940] lr: 1.0000e-04 eta: 2:31:42 time: 0.6533 data_time: 0.0261 memory: 22701 grad_norm: 5.3983 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0090 loss: 1.0090 2022/09/06 05:00:01 - mmengine - INFO - Epoch(train) [89][300/940] lr: 1.0000e-04 eta: 2:31:25 time: 0.8821 data_time: 0.0307 memory: 22701 grad_norm: 5.3189 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9662 loss: 0.9662 2022/09/06 05:00:15 - mmengine - INFO - Epoch(train) [89][320/940] lr: 1.0000e-04 eta: 2:31:08 time: 0.7148 data_time: 0.0270 memory: 22701 grad_norm: 5.4042 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9724 loss: 0.9724 2022/09/06 05:00:32 - mmengine - INFO - Epoch(train) [89][340/940] lr: 1.0000e-04 eta: 2:30:52 time: 0.8426 data_time: 0.0281 memory: 22701 grad_norm: 5.3286 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.8820 loss: 0.8820 2022/09/06 05:00:46 - mmengine - INFO - Epoch(train) [89][360/940] lr: 1.0000e-04 eta: 2:30:35 time: 0.6979 data_time: 0.0278 memory: 22701 grad_norm: 5.3153 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8580 loss: 0.8580 2022/09/06 05:01:07 - mmengine - INFO - Epoch(train) [89][380/940] lr: 1.0000e-04 eta: 2:30:19 time: 1.0265 data_time: 0.0319 memory: 22701 grad_norm: 5.2424 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8872 loss: 0.8872 2022/09/06 05:01:22 - mmengine - INFO - Epoch(train) [89][400/940] lr: 1.0000e-04 eta: 2:30:02 time: 0.7514 data_time: 0.0259 memory: 22701 grad_norm: 5.3647 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9334 loss: 0.9334 2022/09/06 05:01:41 - mmengine - INFO - Epoch(train) [89][420/940] lr: 1.0000e-04 eta: 2:29:46 time: 0.9799 data_time: 0.0559 memory: 22701 grad_norm: 5.3260 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8741 loss: 0.8741 2022/09/06 05:01:59 - mmengine - INFO - Epoch(train) [89][440/940] lr: 1.0000e-04 eta: 2:29:30 time: 0.8612 data_time: 0.0291 memory: 22701 grad_norm: 5.4007 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9890 loss: 0.9890 2022/09/06 05:02:18 - mmengine - INFO - Epoch(train) [89][460/940] lr: 1.0000e-04 eta: 2:29:13 time: 0.9559 data_time: 0.0677 memory: 22701 grad_norm: 5.2774 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0361 loss: 1.0361 2022/09/06 05:02:32 - mmengine - INFO - Epoch(train) [89][480/940] lr: 1.0000e-04 eta: 2:28:57 time: 0.7207 data_time: 0.0303 memory: 22701 grad_norm: 5.3507 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.8895 loss: 0.8895 2022/09/06 05:02:50 - mmengine - INFO - Epoch(train) [89][500/940] lr: 1.0000e-04 eta: 2:28:40 time: 0.9059 data_time: 0.0497 memory: 22701 grad_norm: 5.3911 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.9881 loss: 0.9881 2022/09/06 05:03:06 - mmengine - INFO - Epoch(train) [89][520/940] lr: 1.0000e-04 eta: 2:28:24 time: 0.7994 data_time: 0.0407 memory: 22701 grad_norm: 5.4712 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9946 loss: 0.9946 2022/09/06 05:03:24 - mmengine - INFO - Epoch(train) [89][540/940] lr: 1.0000e-04 eta: 2:28:07 time: 0.8593 data_time: 0.1977 memory: 22701 grad_norm: 5.3242 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9500 loss: 0.9500 2022/09/06 05:03:37 - mmengine - INFO - Epoch(train) [89][560/940] lr: 1.0000e-04 eta: 2:27:50 time: 0.6858 data_time: 0.2796 memory: 22701 grad_norm: 5.3317 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9702 loss: 0.9702 2022/09/06 05:03:54 - mmengine - INFO - Epoch(train) [89][580/940] lr: 1.0000e-04 eta: 2:27:34 time: 0.8172 data_time: 0.3884 memory: 22701 grad_norm: 5.3399 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9290 loss: 0.9290 2022/09/06 05:04:11 - mmengine - INFO - Epoch(train) [89][600/940] lr: 1.0000e-04 eta: 2:27:17 time: 0.8779 data_time: 0.1067 memory: 22701 grad_norm: 5.3815 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0252 loss: 1.0252 2022/09/06 05:04:35 - mmengine - INFO - Epoch(train) [89][620/940] lr: 1.0000e-04 eta: 2:27:02 time: 1.1894 data_time: 0.1131 memory: 22701 grad_norm: 5.4231 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9186 loss: 0.9186 2022/09/06 05:04:55 - mmengine - INFO - Epoch(train) [89][640/940] lr: 1.0000e-04 eta: 2:26:46 time: 1.0168 data_time: 0.0377 memory: 22701 grad_norm: 5.3619 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9297 loss: 0.9297 2022/09/06 05:05:16 - mmengine - INFO - Epoch(train) [89][660/940] lr: 1.0000e-04 eta: 2:26:30 time: 1.0489 data_time: 0.0280 memory: 22701 grad_norm: 5.3401 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9292 loss: 0.9292 2022/09/06 05:05:35 - mmengine - INFO - Epoch(train) [89][680/940] lr: 1.0000e-04 eta: 2:26:13 time: 0.9245 data_time: 0.0261 memory: 22701 grad_norm: 5.3217 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9484 loss: 0.9484 2022/09/06 05:05:53 - mmengine - INFO - Epoch(train) [89][700/940] lr: 1.0000e-04 eta: 2:25:57 time: 0.9285 data_time: 0.0273 memory: 22701 grad_norm: 5.3415 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9682 loss: 0.9682 2022/09/06 05:06:08 - mmengine - INFO - Epoch(train) [89][720/940] lr: 1.0000e-04 eta: 2:25:40 time: 0.7346 data_time: 0.0299 memory: 22701 grad_norm: 5.4000 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9541 loss: 0.9541 2022/09/06 05:06:27 - mmengine - INFO - Epoch(train) [89][740/940] lr: 1.0000e-04 eta: 2:25:24 time: 0.9513 data_time: 0.0225 memory: 22701 grad_norm: 5.2803 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9385 loss: 0.9385 2022/09/06 05:06:41 - mmengine - INFO - Epoch(train) [89][760/940] lr: 1.0000e-04 eta: 2:25:07 time: 0.6880 data_time: 0.0261 memory: 22701 grad_norm: 5.3388 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9119 loss: 0.9119 2022/09/06 05:06:58 - mmengine - INFO - Epoch(train) [89][780/940] lr: 1.0000e-04 eta: 2:24:51 time: 0.8444 data_time: 0.0288 memory: 22701 grad_norm: 5.3344 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9011 loss: 0.9011 2022/09/06 05:07:12 - mmengine - INFO - Epoch(train) [89][800/940] lr: 1.0000e-04 eta: 2:24:34 time: 0.7155 data_time: 0.0302 memory: 22701 grad_norm: 5.3295 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0222 loss: 1.0222 2022/09/06 05:07:30 - mmengine - INFO - Epoch(train) [89][820/940] lr: 1.0000e-04 eta: 2:24:17 time: 0.8988 data_time: 0.0435 memory: 22701 grad_norm: 5.3707 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9537 loss: 0.9537 2022/09/06 05:07:45 - mmengine - INFO - Epoch(train) [89][840/940] lr: 1.0000e-04 eta: 2:24:01 time: 0.7335 data_time: 0.0299 memory: 22701 grad_norm: 5.3473 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8974 loss: 0.8974 2022/09/06 05:08:02 - mmengine - INFO - Epoch(train) [89][860/940] lr: 1.0000e-04 eta: 2:23:44 time: 0.8758 data_time: 0.0262 memory: 22701 grad_norm: 5.3251 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9979 loss: 0.9979 2022/09/06 05:08:17 - mmengine - INFO - Epoch(train) [89][880/940] lr: 1.0000e-04 eta: 2:23:27 time: 0.7624 data_time: 0.0260 memory: 22701 grad_norm: 5.3522 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9727 loss: 0.9727 2022/09/06 05:08:38 - mmengine - INFO - Epoch(train) [89][900/940] lr: 1.0000e-04 eta: 2:23:11 time: 1.0066 data_time: 0.0576 memory: 22701 grad_norm: 5.3602 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0055 loss: 1.0055 2022/09/06 05:08:53 - mmengine - INFO - Epoch(train) [89][920/940] lr: 1.0000e-04 eta: 2:22:55 time: 0.7460 data_time: 0.2388 memory: 22701 grad_norm: 5.3397 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.8622 loss: 0.8622 2022/09/06 05:09:09 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:09:09 - mmengine - INFO - Epoch(train) [89][940/940] lr: 1.0000e-04 eta: 2:22:38 time: 0.8190 data_time: 0.4305 memory: 22701 grad_norm: 5.7083 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 0.9277 loss: 0.9277 2022/09/06 05:09:23 - mmengine - INFO - Epoch(val) [89][20/78] eta: 0:00:39 time: 0.6863 data_time: 0.5675 memory: 2247 2022/09/06 05:09:32 - mmengine - INFO - Epoch(val) [89][40/78] eta: 0:00:16 time: 0.4468 data_time: 0.3299 memory: 2247 2022/09/06 05:09:45 - mmengine - INFO - Epoch(val) [89][60/78] eta: 0:00:12 time: 0.6697 data_time: 0.5220 memory: 2247 2022/09/06 05:09:55 - mmengine - INFO - Epoch(val) [89][78/78] acc/top1: 0.6866 acc/top5: 0.8805 acc/mean1: 0.6865 2022/09/06 05:10:16 - mmengine - INFO - Epoch(train) [90][20/940] lr: 1.0000e-04 eta: 2:22:22 time: 1.0459 data_time: 0.6260 memory: 22701 grad_norm: 5.3391 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9676 loss: 0.9676 2022/09/06 05:10:34 - mmengine - INFO - Epoch(train) [90][40/940] lr: 1.0000e-04 eta: 2:22:06 time: 0.8779 data_time: 0.3909 memory: 22701 grad_norm: 5.3467 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9371 loss: 0.9371 2022/09/06 05:10:56 - mmengine - INFO - Epoch(train) [90][60/940] lr: 1.0000e-04 eta: 2:21:50 time: 1.0845 data_time: 0.0829 memory: 22701 grad_norm: 5.3928 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0563 loss: 1.0563 2022/09/06 05:11:11 - mmengine - INFO - Epoch(train) [90][80/940] lr: 1.0000e-04 eta: 2:21:33 time: 0.7771 data_time: 0.0313 memory: 22701 grad_norm: 5.3338 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9757 loss: 0.9757 2022/09/06 05:11:28 - mmengine - INFO - Epoch(train) [90][100/940] lr: 1.0000e-04 eta: 2:21:16 time: 0.8557 data_time: 0.0286 memory: 22701 grad_norm: 5.3785 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9305 loss: 0.9305 2022/09/06 05:11:41 - mmengine - INFO - Epoch(train) [90][120/940] lr: 1.0000e-04 eta: 2:20:59 time: 0.6176 data_time: 0.0247 memory: 22701 grad_norm: 5.3709 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 0.9434 loss: 0.9434 2022/09/06 05:11:59 - mmengine - INFO - Epoch(train) [90][140/940] lr: 1.0000e-04 eta: 2:20:43 time: 0.9203 data_time: 0.0259 memory: 22701 grad_norm: 5.4667 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8516 loss: 0.8516 2022/09/06 05:12:15 - mmengine - INFO - Epoch(train) [90][160/940] lr: 1.0000e-04 eta: 2:20:26 time: 0.8216 data_time: 0.0567 memory: 22701 grad_norm: 5.4308 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0074 loss: 1.0074 2022/09/06 05:12:34 - mmengine - INFO - Epoch(train) [90][180/940] lr: 1.0000e-04 eta: 2:20:10 time: 0.9154 data_time: 0.0310 memory: 22701 grad_norm: 5.4437 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0065 loss: 1.0065 2022/09/06 05:12:51 - mmengine - INFO - Epoch(train) [90][200/940] lr: 1.0000e-04 eta: 2:19:54 time: 0.8512 data_time: 0.0249 memory: 22701 grad_norm: 5.4351 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.9665 loss: 0.9665 2022/09/06 05:13:10 - mmengine - INFO - Epoch(train) [90][220/940] lr: 1.0000e-04 eta: 2:19:37 time: 0.9421 data_time: 0.0270 memory: 22701 grad_norm: 5.3541 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0678 loss: 1.0678 2022/09/06 05:13:23 - mmengine - INFO - Epoch(train) [90][240/940] lr: 1.0000e-04 eta: 2:19:20 time: 0.6761 data_time: 0.0267 memory: 22701 grad_norm: 5.5511 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9911 loss: 0.9911 2022/09/06 05:13:40 - mmengine - INFO - Epoch(train) [90][260/940] lr: 1.0000e-04 eta: 2:19:04 time: 0.8184 data_time: 0.0250 memory: 22701 grad_norm: 5.4185 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9063 loss: 0.9063 2022/09/06 05:13:56 - mmengine - INFO - Epoch(train) [90][280/940] lr: 1.0000e-04 eta: 2:18:47 time: 0.8046 data_time: 0.0314 memory: 22701 grad_norm: 5.2601 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9839 loss: 0.9839 2022/09/06 05:14:11 - mmengine - INFO - Epoch(train) [90][300/940] lr: 1.0000e-04 eta: 2:18:31 time: 0.7607 data_time: 0.0293 memory: 22701 grad_norm: 5.3253 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8839 loss: 0.8839 2022/09/06 05:14:31 - mmengine - INFO - Epoch(train) [90][320/940] lr: 1.0000e-04 eta: 2:18:14 time: 0.9929 data_time: 0.0267 memory: 22701 grad_norm: 5.4605 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9396 loss: 0.9396 2022/09/06 05:14:51 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:14:51 - mmengine - INFO - Epoch(train) [90][340/940] lr: 1.0000e-04 eta: 2:17:58 time: 1.0263 data_time: 0.0297 memory: 22701 grad_norm: 5.2509 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.9690 loss: 0.9690 2022/09/06 05:15:05 - mmengine - INFO - Epoch(train) [90][360/940] lr: 1.0000e-04 eta: 2:17:41 time: 0.6832 data_time: 0.0281 memory: 22701 grad_norm: 5.3661 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.8986 loss: 0.8986 2022/09/06 05:15:22 - mmengine - INFO - Epoch(train) [90][380/940] lr: 1.0000e-04 eta: 2:17:25 time: 0.8352 data_time: 0.0574 memory: 22701 grad_norm: 5.3759 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9241 loss: 0.9241 2022/09/06 05:15:40 - mmengine - INFO - Epoch(train) [90][400/940] lr: 1.0000e-04 eta: 2:17:09 time: 0.9401 data_time: 0.0238 memory: 22701 grad_norm: 5.4218 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0697 loss: 1.0697 2022/09/06 05:15:56 - mmengine - INFO - Epoch(train) [90][420/940] lr: 1.0000e-04 eta: 2:16:52 time: 0.7743 data_time: 0.0323 memory: 22701 grad_norm: 5.3611 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9328 loss: 0.9328 2022/09/06 05:16:13 - mmengine - INFO - Epoch(train) [90][440/940] lr: 1.0000e-04 eta: 2:16:35 time: 0.8674 data_time: 0.0278 memory: 22701 grad_norm: 5.2497 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.8136 loss: 0.8136 2022/09/06 05:16:27 - mmengine - INFO - Epoch(train) [90][460/940] lr: 1.0000e-04 eta: 2:16:18 time: 0.6770 data_time: 0.0290 memory: 22701 grad_norm: 5.3066 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0033 loss: 1.0033 2022/09/06 05:16:43 - mmengine - INFO - Epoch(train) [90][480/940] lr: 1.0000e-04 eta: 2:16:02 time: 0.8133 data_time: 0.0283 memory: 22701 grad_norm: 5.3530 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9182 loss: 0.9182 2022/09/06 05:16:59 - mmengine - INFO - Epoch(train) [90][500/940] lr: 1.0000e-04 eta: 2:15:45 time: 0.7764 data_time: 0.0261 memory: 22701 grad_norm: 5.3576 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9890 loss: 0.9890 2022/09/06 05:17:14 - mmengine - INFO - Epoch(train) [90][520/940] lr: 1.0000e-04 eta: 2:15:28 time: 0.7557 data_time: 0.0309 memory: 22701 grad_norm: 5.3289 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9513 loss: 0.9513 2022/09/06 05:17:28 - mmengine - INFO - Epoch(train) [90][540/940] lr: 1.0000e-04 eta: 2:15:12 time: 0.7024 data_time: 0.0293 memory: 22701 grad_norm: 5.3486 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.8610 loss: 0.8610 2022/09/06 05:17:43 - mmengine - INFO - Epoch(train) [90][560/940] lr: 1.0000e-04 eta: 2:14:55 time: 0.7678 data_time: 0.0363 memory: 22701 grad_norm: 5.2976 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0625 loss: 1.0625 2022/09/06 05:17:59 - mmengine - INFO - Epoch(train) [90][580/940] lr: 1.0000e-04 eta: 2:14:38 time: 0.7716 data_time: 0.0272 memory: 22701 grad_norm: 5.5146 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0402 loss: 1.0402 2022/09/06 05:18:19 - mmengine - INFO - Epoch(train) [90][600/940] lr: 1.0000e-04 eta: 2:14:22 time: 1.0216 data_time: 0.0257 memory: 22701 grad_norm: 5.3333 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9596 loss: 0.9596 2022/09/06 05:18:34 - mmengine - INFO - Epoch(train) [90][620/940] lr: 1.0000e-04 eta: 2:14:05 time: 0.7310 data_time: 0.0227 memory: 22701 grad_norm: 5.2709 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9055 loss: 0.9055 2022/09/06 05:18:50 - mmengine - INFO - Epoch(train) [90][640/940] lr: 1.0000e-04 eta: 2:13:49 time: 0.8268 data_time: 0.0415 memory: 22701 grad_norm: 5.3897 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9155 loss: 0.9155 2022/09/06 05:19:05 - mmengine - INFO - Epoch(train) [90][660/940] lr: 1.0000e-04 eta: 2:13:32 time: 0.7246 data_time: 0.0371 memory: 22701 grad_norm: 5.1930 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.8970 loss: 0.8970 2022/09/06 05:19:22 - mmengine - INFO - Epoch(train) [90][680/940] lr: 1.0000e-04 eta: 2:13:16 time: 0.8531 data_time: 0.0343 memory: 22701 grad_norm: 5.2716 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9779 loss: 0.9779 2022/09/06 05:19:39 - mmengine - INFO - Epoch(train) [90][700/940] lr: 1.0000e-04 eta: 2:12:59 time: 0.8451 data_time: 0.0230 memory: 22701 grad_norm: 5.3806 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9231 loss: 0.9231 2022/09/06 05:19:54 - mmengine - INFO - Epoch(train) [90][720/940] lr: 1.0000e-04 eta: 2:12:42 time: 0.7408 data_time: 0.0260 memory: 22701 grad_norm: 5.3612 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9806 loss: 0.9806 2022/09/06 05:20:11 - mmengine - INFO - Epoch(train) [90][740/940] lr: 1.0000e-04 eta: 2:12:26 time: 0.8921 data_time: 0.0251 memory: 22701 grad_norm: 5.3862 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0140 loss: 1.0140 2022/09/06 05:20:30 - mmengine - INFO - Epoch(train) [90][760/940] lr: 1.0000e-04 eta: 2:12:09 time: 0.9142 data_time: 0.0180 memory: 22701 grad_norm: 5.3327 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9677 loss: 0.9677 2022/09/06 05:20:44 - mmengine - INFO - Epoch(train) [90][780/940] lr: 1.0000e-04 eta: 2:11:53 time: 0.7284 data_time: 0.0291 memory: 22701 grad_norm: 5.5682 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9246 loss: 0.9246 2022/09/06 05:21:05 - mmengine - INFO - Epoch(train) [90][800/940] lr: 1.0000e-04 eta: 2:11:37 time: 1.0105 data_time: 0.0188 memory: 22701 grad_norm: 5.5335 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9556 loss: 0.9556 2022/09/06 05:21:23 - mmengine - INFO - Epoch(train) [90][820/940] lr: 1.0000e-04 eta: 2:11:20 time: 0.9343 data_time: 0.0273 memory: 22701 grad_norm: 5.3272 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9859 loss: 0.9859 2022/09/06 05:21:38 - mmengine - INFO - Epoch(train) [90][840/940] lr: 1.0000e-04 eta: 2:11:04 time: 0.7445 data_time: 0.0342 memory: 22701 grad_norm: 5.3959 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9584 loss: 0.9584 2022/09/06 05:21:58 - mmengine - INFO - Epoch(train) [90][860/940] lr: 1.0000e-04 eta: 2:10:47 time: 1.0102 data_time: 0.0253 memory: 22701 grad_norm: 5.4128 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9020 loss: 0.9020 2022/09/06 05:22:14 - mmengine - INFO - Epoch(train) [90][880/940] lr: 1.0000e-04 eta: 2:10:31 time: 0.7680 data_time: 0.0293 memory: 22701 grad_norm: 5.2500 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9262 loss: 0.9262 2022/09/06 05:22:32 - mmengine - INFO - Epoch(train) [90][900/940] lr: 1.0000e-04 eta: 2:10:14 time: 0.9297 data_time: 0.0277 memory: 22701 grad_norm: 5.3561 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9317 loss: 0.9317 2022/09/06 05:22:46 - mmengine - INFO - Epoch(train) [90][920/940] lr: 1.0000e-04 eta: 2:09:58 time: 0.7074 data_time: 0.0279 memory: 22701 grad_norm: 5.4112 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.8890 loss: 0.8890 2022/09/06 05:23:02 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:23:02 - mmengine - INFO - Epoch(train) [90][940/940] lr: 1.0000e-04 eta: 2:09:41 time: 0.7733 data_time: 0.0207 memory: 22701 grad_norm: 5.8782 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 0.9799 loss: 0.9799 2022/09/06 05:23:02 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/09/06 05:23:18 - mmengine - INFO - Epoch(val) [90][20/78] eta: 0:00:41 time: 0.7131 data_time: 0.5926 memory: 2247 2022/09/06 05:23:27 - mmengine - INFO - Epoch(val) [90][40/78] eta: 0:00:17 time: 0.4515 data_time: 0.3360 memory: 2247 2022/09/06 05:23:40 - mmengine - INFO - Epoch(val) [90][60/78] eta: 0:00:11 time: 0.6350 data_time: 0.5173 memory: 2247 2022/09/06 05:23:50 - mmengine - INFO - Epoch(val) [90][78/78] acc/top1: 0.6867 acc/top5: 0.8804 acc/mean1: 0.6866 2022/09/06 05:24:12 - mmengine - INFO - Epoch(train) [91][20/940] lr: 1.0000e-04 eta: 2:09:25 time: 1.0849 data_time: 0.4017 memory: 22701 grad_norm: 5.3639 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.9372 loss: 0.9372 2022/09/06 05:24:26 - mmengine - INFO - Epoch(train) [91][40/940] lr: 1.0000e-04 eta: 2:09:08 time: 0.7211 data_time: 0.0367 memory: 22701 grad_norm: 5.3204 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9091 loss: 0.9091 2022/09/06 05:24:44 - mmengine - INFO - Epoch(train) [91][60/940] lr: 1.0000e-04 eta: 2:08:52 time: 0.9029 data_time: 0.1422 memory: 22701 grad_norm: 5.4074 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0081 loss: 1.0081 2022/09/06 05:25:00 - mmengine - INFO - Epoch(train) [91][80/940] lr: 1.0000e-04 eta: 2:08:35 time: 0.7999 data_time: 0.0660 memory: 22701 grad_norm: 5.4844 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 0.9264 loss: 0.9264 2022/09/06 05:25:20 - mmengine - INFO - Epoch(train) [91][100/940] lr: 1.0000e-04 eta: 2:08:19 time: 0.9721 data_time: 0.0608 memory: 22701 grad_norm: 5.3289 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0295 loss: 1.0295 2022/09/06 05:25:34 - mmengine - INFO - Epoch(train) [91][120/940] lr: 1.0000e-04 eta: 2:08:02 time: 0.7392 data_time: 0.0187 memory: 22701 grad_norm: 5.4024 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.8390 loss: 0.8390 2022/09/06 05:25:53 - mmengine - INFO - Epoch(train) [91][140/940] lr: 1.0000e-04 eta: 2:07:46 time: 0.9477 data_time: 0.0265 memory: 22701 grad_norm: 5.3493 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0423 loss: 1.0423 2022/09/06 05:26:10 - mmengine - INFO - Epoch(train) [91][160/940] lr: 1.0000e-04 eta: 2:07:29 time: 0.8102 data_time: 0.0226 memory: 22701 grad_norm: 5.4160 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0122 loss: 1.0122 2022/09/06 05:26:26 - mmengine - INFO - Epoch(train) [91][180/940] lr: 1.0000e-04 eta: 2:07:13 time: 0.8401 data_time: 0.0277 memory: 22701 grad_norm: 5.4180 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.0050 loss: 1.0050 2022/09/06 05:26:40 - mmengine - INFO - Epoch(train) [91][200/940] lr: 1.0000e-04 eta: 2:06:56 time: 0.6675 data_time: 0.0217 memory: 22701 grad_norm: 5.3270 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8206 loss: 0.8206 2022/09/06 05:27:00 - mmengine - INFO - Epoch(train) [91][220/940] lr: 1.0000e-04 eta: 2:06:40 time: 1.0029 data_time: 0.0311 memory: 22701 grad_norm: 5.4775 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9909 loss: 0.9909 2022/09/06 05:27:14 - mmengine - INFO - Epoch(train) [91][240/940] lr: 1.0000e-04 eta: 2:06:23 time: 0.7156 data_time: 0.0222 memory: 22701 grad_norm: 5.3680 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9202 loss: 0.9202 2022/09/06 05:27:35 - mmengine - INFO - Epoch(train) [91][260/940] lr: 1.0000e-04 eta: 2:06:07 time: 1.0346 data_time: 0.0274 memory: 22701 grad_norm: 5.3226 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8663 loss: 0.8663 2022/09/06 05:27:51 - mmengine - INFO - Epoch(train) [91][280/940] lr: 1.0000e-04 eta: 2:05:50 time: 0.7934 data_time: 0.0241 memory: 22701 grad_norm: 5.3338 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9048 loss: 0.9048 2022/09/06 05:28:10 - mmengine - INFO - Epoch(train) [91][300/940] lr: 1.0000e-04 eta: 2:05:34 time: 0.9497 data_time: 0.0337 memory: 22701 grad_norm: 5.2862 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8003 loss: 0.8003 2022/09/06 05:28:26 - mmengine - INFO - Epoch(train) [91][320/940] lr: 1.0000e-04 eta: 2:05:17 time: 0.8148 data_time: 0.0229 memory: 22701 grad_norm: 5.3392 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9178 loss: 0.9178 2022/09/06 05:28:43 - mmengine - INFO - Epoch(train) [91][340/940] lr: 1.0000e-04 eta: 2:05:01 time: 0.8567 data_time: 0.0268 memory: 22701 grad_norm: 5.3640 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8660 loss: 0.8660 2022/09/06 05:28:57 - mmengine - INFO - Epoch(train) [91][360/940] lr: 1.0000e-04 eta: 2:04:44 time: 0.6785 data_time: 0.0267 memory: 22701 grad_norm: 5.3230 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.8643 loss: 0.8643 2022/09/06 05:29:16 - mmengine - INFO - Epoch(train) [91][380/940] lr: 1.0000e-04 eta: 2:04:27 time: 0.9709 data_time: 0.0283 memory: 22701 grad_norm: 5.2753 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9849 loss: 0.9849 2022/09/06 05:29:29 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:29:29 - mmengine - INFO - Epoch(train) [91][400/940] lr: 1.0000e-04 eta: 2:04:11 time: 0.6437 data_time: 0.0279 memory: 22701 grad_norm: 5.3399 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9394 loss: 0.9394 2022/09/06 05:29:49 - mmengine - INFO - Epoch(train) [91][420/940] lr: 1.0000e-04 eta: 2:03:54 time: 1.0096 data_time: 0.0232 memory: 22701 grad_norm: 5.3316 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8359 loss: 0.8359 2022/09/06 05:30:06 - mmengine - INFO - Epoch(train) [91][440/940] lr: 1.0000e-04 eta: 2:03:38 time: 0.8222 data_time: 0.0256 memory: 22701 grad_norm: 5.3205 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9663 loss: 0.9663 2022/09/06 05:30:26 - mmengine - INFO - Epoch(train) [91][460/940] lr: 1.0000e-04 eta: 2:03:22 time: 0.9920 data_time: 0.0257 memory: 22701 grad_norm: 5.3019 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9025 loss: 0.9025 2022/09/06 05:30:42 - mmengine - INFO - Epoch(train) [91][480/940] lr: 1.0000e-04 eta: 2:03:05 time: 0.8251 data_time: 0.0313 memory: 22701 grad_norm: 5.4305 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0310 loss: 1.0310 2022/09/06 05:31:00 - mmengine - INFO - Epoch(train) [91][500/940] lr: 1.0000e-04 eta: 2:02:49 time: 0.8913 data_time: 0.0299 memory: 22701 grad_norm: 5.4579 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9913 loss: 0.9913 2022/09/06 05:31:14 - mmengine - INFO - Epoch(train) [91][520/940] lr: 1.0000e-04 eta: 2:02:32 time: 0.6876 data_time: 0.0281 memory: 22701 grad_norm: 5.4321 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 0.9556 loss: 0.9556 2022/09/06 05:31:31 - mmengine - INFO - Epoch(train) [91][540/940] lr: 1.0000e-04 eta: 2:02:15 time: 0.8467 data_time: 0.0248 memory: 22701 grad_norm: 5.3918 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 1.0243 loss: 1.0243 2022/09/06 05:31:44 - mmengine - INFO - Epoch(train) [91][560/940] lr: 1.0000e-04 eta: 2:01:58 time: 0.6864 data_time: 0.0266 memory: 22701 grad_norm: 5.3366 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9923 loss: 0.9923 2022/09/06 05:32:01 - mmengine - INFO - Epoch(train) [91][580/940] lr: 1.0000e-04 eta: 2:01:42 time: 0.8249 data_time: 0.0269 memory: 22701 grad_norm: 5.3377 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9060 loss: 0.9060 2022/09/06 05:32:14 - mmengine - INFO - Epoch(train) [91][600/940] lr: 1.0000e-04 eta: 2:01:25 time: 0.6697 data_time: 0.0320 memory: 22701 grad_norm: 5.4138 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 0.9996 loss: 0.9996 2022/09/06 05:32:32 - mmengine - INFO - Epoch(train) [91][620/940] lr: 1.0000e-04 eta: 2:01:08 time: 0.8975 data_time: 0.0280 memory: 22701 grad_norm: 5.2761 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0119 loss: 1.0119 2022/09/06 05:32:45 - mmengine - INFO - Epoch(train) [91][640/940] lr: 1.0000e-04 eta: 2:00:52 time: 0.6682 data_time: 0.0284 memory: 22701 grad_norm: 5.4337 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0002 loss: 1.0002 2022/09/06 05:33:03 - mmengine - INFO - Epoch(train) [91][660/940] lr: 1.0000e-04 eta: 2:00:35 time: 0.8511 data_time: 0.0266 memory: 22701 grad_norm: 5.4667 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0219 loss: 1.0219 2022/09/06 05:33:18 - mmengine - INFO - Epoch(train) [91][680/940] lr: 1.0000e-04 eta: 2:00:18 time: 0.7829 data_time: 0.0287 memory: 22701 grad_norm: 5.4625 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0103 loss: 1.0103 2022/09/06 05:33:39 - mmengine - INFO - Epoch(train) [91][700/940] lr: 1.0000e-04 eta: 2:00:02 time: 1.0610 data_time: 0.0299 memory: 22701 grad_norm: 5.2562 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0235 loss: 1.0235 2022/09/06 05:33:57 - mmengine - INFO - Epoch(train) [91][720/940] lr: 1.0000e-04 eta: 1:59:46 time: 0.8570 data_time: 0.0270 memory: 22701 grad_norm: 5.2980 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9448 loss: 0.9448 2022/09/06 05:34:18 - mmengine - INFO - Epoch(train) [91][740/940] lr: 1.0000e-04 eta: 1:59:30 time: 1.0919 data_time: 0.0277 memory: 22701 grad_norm: 5.2497 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 0.9297 loss: 0.9297 2022/09/06 05:34:36 - mmengine - INFO - Epoch(train) [91][760/940] lr: 1.0000e-04 eta: 1:59:13 time: 0.8787 data_time: 0.0197 memory: 22701 grad_norm: 5.3419 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.9986 loss: 0.9986 2022/09/06 05:34:56 - mmengine - INFO - Epoch(train) [91][780/940] lr: 1.0000e-04 eta: 1:58:57 time: 1.0238 data_time: 0.0227 memory: 22701 grad_norm: 5.2207 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8838 loss: 0.8838 2022/09/06 05:35:13 - mmengine - INFO - Epoch(train) [91][800/940] lr: 1.0000e-04 eta: 1:58:41 time: 0.8111 data_time: 0.0265 memory: 22701 grad_norm: 5.4891 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.9292 loss: 0.9292 2022/09/06 05:35:27 - mmengine - INFO - Epoch(train) [91][820/940] lr: 1.0000e-04 eta: 1:58:24 time: 0.7096 data_time: 0.0342 memory: 22701 grad_norm: 5.1485 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9662 loss: 0.9662 2022/09/06 05:35:42 - mmengine - INFO - Epoch(train) [91][840/940] lr: 1.0000e-04 eta: 1:58:07 time: 0.7710 data_time: 0.0275 memory: 22701 grad_norm: 5.2834 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9231 loss: 0.9231 2022/09/06 05:35:56 - mmengine - INFO - Epoch(train) [91][860/940] lr: 1.0000e-04 eta: 1:57:50 time: 0.6989 data_time: 0.0277 memory: 22701 grad_norm: 5.3913 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9367 loss: 0.9367 2022/09/06 05:36:13 - mmengine - INFO - Epoch(train) [91][880/940] lr: 1.0000e-04 eta: 1:57:34 time: 0.8152 data_time: 0.0269 memory: 22701 grad_norm: 5.4439 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0296 loss: 1.0296 2022/09/06 05:36:29 - mmengine - INFO - Epoch(train) [91][900/940] lr: 1.0000e-04 eta: 1:57:17 time: 0.8056 data_time: 0.0344 memory: 22701 grad_norm: 5.3750 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9576 loss: 0.9576 2022/09/06 05:36:46 - mmengine - INFO - Epoch(train) [91][920/940] lr: 1.0000e-04 eta: 1:57:01 time: 0.8893 data_time: 0.0238 memory: 22701 grad_norm: 5.2583 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9291 loss: 0.9291 2022/09/06 05:37:03 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:37:03 - mmengine - INFO - Epoch(train) [91][940/940] lr: 1.0000e-04 eta: 1:56:44 time: 0.8012 data_time: 0.0195 memory: 22701 grad_norm: 5.6634 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 0.9979 loss: 0.9979 2022/09/06 05:37:17 - mmengine - INFO - Epoch(val) [91][20/78] eta: 0:00:40 time: 0.6977 data_time: 0.5781 memory: 2247 2022/09/06 05:37:25 - mmengine - INFO - Epoch(val) [91][40/78] eta: 0:00:16 time: 0.4450 data_time: 0.3223 memory: 2247 2022/09/06 05:37:39 - mmengine - INFO - Epoch(val) [91][60/78] eta: 0:00:11 time: 0.6556 data_time: 0.5302 memory: 2247 2022/09/06 05:37:49 - mmengine - INFO - Epoch(val) [91][78/78] acc/top1: 0.6884 acc/top5: 0.8807 acc/mean1: 0.6883 2022/09/06 05:38:09 - mmengine - INFO - Epoch(train) [92][20/940] lr: 1.0000e-04 eta: 1:56:28 time: 1.0177 data_time: 0.4973 memory: 22701 grad_norm: 5.2782 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9349 loss: 0.9349 2022/09/06 05:38:22 - mmengine - INFO - Epoch(train) [92][40/940] lr: 1.0000e-04 eta: 1:56:11 time: 0.6027 data_time: 0.1843 memory: 22701 grad_norm: 5.2336 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8379 loss: 0.8379 2022/09/06 05:38:39 - mmengine - INFO - Epoch(train) [92][60/940] lr: 1.0000e-04 eta: 1:55:54 time: 0.8569 data_time: 0.3128 memory: 22701 grad_norm: 5.3502 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9863 loss: 0.9863 2022/09/06 05:38:53 - mmengine - INFO - Epoch(train) [92][80/940] lr: 1.0000e-04 eta: 1:55:38 time: 0.7330 data_time: 0.2146 memory: 22701 grad_norm: 5.3956 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9418 loss: 0.9418 2022/09/06 05:39:10 - mmengine - INFO - Epoch(train) [92][100/940] lr: 1.0000e-04 eta: 1:55:21 time: 0.8342 data_time: 0.1891 memory: 22701 grad_norm: 5.4474 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0315 loss: 1.0315 2022/09/06 05:39:24 - mmengine - INFO - Epoch(train) [92][120/940] lr: 1.0000e-04 eta: 1:55:04 time: 0.6755 data_time: 0.1544 memory: 22701 grad_norm: 5.3433 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8726 loss: 0.8726 2022/09/06 05:39:42 - mmengine - INFO - Epoch(train) [92][140/940] lr: 1.0000e-04 eta: 1:54:48 time: 0.9136 data_time: 0.0970 memory: 22701 grad_norm: 5.3208 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9761 loss: 0.9761 2022/09/06 05:39:55 - mmengine - INFO - Epoch(train) [92][160/940] lr: 1.0000e-04 eta: 1:54:31 time: 0.6595 data_time: 0.0229 memory: 22701 grad_norm: 5.3302 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9284 loss: 0.9284 2022/09/06 05:40:11 - mmengine - INFO - Epoch(train) [92][180/940] lr: 1.0000e-04 eta: 1:54:14 time: 0.7922 data_time: 0.0390 memory: 22701 grad_norm: 5.3034 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8938 loss: 0.8938 2022/09/06 05:40:24 - mmengine - INFO - Epoch(train) [92][200/940] lr: 1.0000e-04 eta: 1:53:57 time: 0.6678 data_time: 0.0918 memory: 22701 grad_norm: 5.3710 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9132 loss: 0.9132 2022/09/06 05:40:41 - mmengine - INFO - Epoch(train) [92][220/940] lr: 1.0000e-04 eta: 1:53:41 time: 0.8373 data_time: 0.2309 memory: 22701 grad_norm: 5.3727 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0050 loss: 1.0050 2022/09/06 05:40:55 - mmengine - INFO - Epoch(train) [92][240/940] lr: 1.0000e-04 eta: 1:53:24 time: 0.6974 data_time: 0.1082 memory: 22701 grad_norm: 5.2972 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9626 loss: 0.9626 2022/09/06 05:41:11 - mmengine - INFO - Epoch(train) [92][260/940] lr: 1.0000e-04 eta: 1:53:08 time: 0.8254 data_time: 0.1826 memory: 22701 grad_norm: 5.5033 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9852 loss: 0.9852 2022/09/06 05:41:28 - mmengine - INFO - Epoch(train) [92][280/940] lr: 1.0000e-04 eta: 1:52:51 time: 0.8013 data_time: 0.1993 memory: 22701 grad_norm: 5.4333 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.9065 loss: 0.9065 2022/09/06 05:41:48 - mmengine - INFO - Epoch(train) [92][300/940] lr: 1.0000e-04 eta: 1:52:35 time: 1.0474 data_time: 0.0502 memory: 22701 grad_norm: 5.3755 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9491 loss: 0.9491 2022/09/06 05:42:05 - mmengine - INFO - Epoch(train) [92][320/940] lr: 1.0000e-04 eta: 1:52:18 time: 0.8451 data_time: 0.0283 memory: 22701 grad_norm: 5.3553 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9377 loss: 0.9377 2022/09/06 05:42:24 - mmengine - INFO - Epoch(train) [92][340/940] lr: 1.0000e-04 eta: 1:52:02 time: 0.9481 data_time: 0.0247 memory: 22701 grad_norm: 5.3064 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9308 loss: 0.9308 2022/09/06 05:42:40 - mmengine - INFO - Epoch(train) [92][360/940] lr: 1.0000e-04 eta: 1:51:45 time: 0.8009 data_time: 0.0239 memory: 22701 grad_norm: 5.3606 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9800 loss: 0.9800 2022/09/06 05:43:00 - mmengine - INFO - Epoch(train) [92][380/940] lr: 1.0000e-04 eta: 1:51:29 time: 0.9748 data_time: 0.0345 memory: 22701 grad_norm: 5.3893 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8748 loss: 0.8748 2022/09/06 05:43:14 - mmengine - INFO - Epoch(train) [92][400/940] lr: 1.0000e-04 eta: 1:51:12 time: 0.7091 data_time: 0.0284 memory: 22701 grad_norm: 5.3299 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.8416 loss: 0.8416 2022/09/06 05:43:34 - mmengine - INFO - Epoch(train) [92][420/940] lr: 1.0000e-04 eta: 1:50:56 time: 0.9989 data_time: 0.0349 memory: 22701 grad_norm: 5.2624 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8971 loss: 0.8971 2022/09/06 05:43:52 - mmengine - INFO - Epoch(train) [92][440/940] lr: 1.0000e-04 eta: 1:50:40 time: 0.8880 data_time: 0.0247 memory: 22701 grad_norm: 5.3399 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 0.9554 loss: 0.9554 2022/09/06 05:44:11 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:44:11 - mmengine - INFO - Epoch(train) [92][460/940] lr: 1.0000e-04 eta: 1:50:23 time: 0.9743 data_time: 0.0217 memory: 22701 grad_norm: 5.3865 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.9078 loss: 0.9078 2022/09/06 05:44:27 - mmengine - INFO - Epoch(train) [92][480/940] lr: 1.0000e-04 eta: 1:50:07 time: 0.7635 data_time: 0.0229 memory: 22701 grad_norm: 5.1997 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.8929 loss: 0.8929 2022/09/06 05:44:49 - mmengine - INFO - Epoch(train) [92][500/940] lr: 1.0000e-04 eta: 1:49:51 time: 1.1042 data_time: 0.0200 memory: 22701 grad_norm: 5.3130 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.9443 loss: 0.9443 2022/09/06 05:45:07 - mmengine - INFO - Epoch(train) [92][520/940] lr: 1.0000e-04 eta: 1:49:34 time: 0.9210 data_time: 0.0441 memory: 22701 grad_norm: 5.3201 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9182 loss: 0.9182 2022/09/06 05:45:29 - mmengine - INFO - Epoch(train) [92][540/940] lr: 1.0000e-04 eta: 1:49:18 time: 1.1126 data_time: 0.0249 memory: 22701 grad_norm: 5.4745 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9547 loss: 0.9547 2022/09/06 05:45:45 - mmengine - INFO - Epoch(train) [92][560/940] lr: 1.0000e-04 eta: 1:49:02 time: 0.8069 data_time: 0.0253 memory: 22701 grad_norm: 5.2971 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8624 loss: 0.8624 2022/09/06 05:46:02 - mmengine - INFO - Epoch(train) [92][580/940] lr: 1.0000e-04 eta: 1:48:45 time: 0.8102 data_time: 0.0558 memory: 22701 grad_norm: 5.4724 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 0.9964 loss: 0.9964 2022/09/06 05:46:16 - mmengine - INFO - Epoch(train) [92][600/940] lr: 1.0000e-04 eta: 1:48:28 time: 0.7337 data_time: 0.1316 memory: 22701 grad_norm: 5.3658 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.8765 loss: 0.8765 2022/09/06 05:46:37 - mmengine - INFO - Epoch(train) [92][620/940] lr: 1.0000e-04 eta: 1:48:12 time: 1.0035 data_time: 0.1644 memory: 22701 grad_norm: 5.3036 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.8800 loss: 0.8800 2022/09/06 05:46:52 - mmengine - INFO - Epoch(train) [92][640/940] lr: 1.0000e-04 eta: 1:47:55 time: 0.7637 data_time: 0.0261 memory: 22701 grad_norm: 5.2866 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9347 loss: 0.9347 2022/09/06 05:47:08 - mmengine - INFO - Epoch(train) [92][660/940] lr: 1.0000e-04 eta: 1:47:39 time: 0.8211 data_time: 0.0234 memory: 22701 grad_norm: 5.3858 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8018 loss: 0.8018 2022/09/06 05:47:22 - mmengine - INFO - Epoch(train) [92][680/940] lr: 1.0000e-04 eta: 1:47:22 time: 0.7042 data_time: 0.0295 memory: 22701 grad_norm: 5.4634 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9920 loss: 0.9920 2022/09/06 05:47:38 - mmengine - INFO - Epoch(train) [92][700/940] lr: 1.0000e-04 eta: 1:47:05 time: 0.8070 data_time: 0.0208 memory: 22701 grad_norm: 5.3546 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0104 loss: 1.0104 2022/09/06 05:47:51 - mmengine - INFO - Epoch(train) [92][720/940] lr: 1.0000e-04 eta: 1:46:49 time: 0.6524 data_time: 0.0375 memory: 22701 grad_norm: 5.4055 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9508 loss: 0.9508 2022/09/06 05:48:08 - mmengine - INFO - Epoch(train) [92][740/940] lr: 1.0000e-04 eta: 1:46:32 time: 0.8087 data_time: 0.0230 memory: 22701 grad_norm: 5.2523 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.8970 loss: 0.8970 2022/09/06 05:48:22 - mmengine - INFO - Epoch(train) [92][760/940] lr: 1.0000e-04 eta: 1:46:15 time: 0.6935 data_time: 0.0336 memory: 22701 grad_norm: 5.4011 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9440 loss: 0.9440 2022/09/06 05:48:38 - mmengine - INFO - Epoch(train) [92][780/940] lr: 1.0000e-04 eta: 1:45:59 time: 0.8210 data_time: 0.0253 memory: 22701 grad_norm: 5.4145 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9068 loss: 0.9068 2022/09/06 05:48:52 - mmengine - INFO - Epoch(train) [92][800/940] lr: 1.0000e-04 eta: 1:45:42 time: 0.7192 data_time: 0.0465 memory: 22701 grad_norm: 5.4517 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0243 loss: 1.0243 2022/09/06 05:49:10 - mmengine - INFO - Epoch(train) [92][820/940] lr: 1.0000e-04 eta: 1:45:25 time: 0.8980 data_time: 0.0236 memory: 22701 grad_norm: 5.3654 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0366 loss: 1.0366 2022/09/06 05:49:27 - mmengine - INFO - Epoch(train) [92][840/940] lr: 1.0000e-04 eta: 1:45:09 time: 0.8111 data_time: 0.0700 memory: 22701 grad_norm: 5.2983 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9513 loss: 0.9513 2022/09/06 05:49:46 - mmengine - INFO - Epoch(train) [92][860/940] lr: 1.0000e-04 eta: 1:44:52 time: 0.9578 data_time: 0.1968 memory: 22701 grad_norm: 5.4805 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8740 loss: 0.8740 2022/09/06 05:50:02 - mmengine - INFO - Epoch(train) [92][880/940] lr: 1.0000e-04 eta: 1:44:36 time: 0.8057 data_time: 0.0254 memory: 22701 grad_norm: 5.3290 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8166 loss: 0.8166 2022/09/06 05:50:21 - mmengine - INFO - Epoch(train) [92][900/940] lr: 1.0000e-04 eta: 1:44:19 time: 0.9409 data_time: 0.0267 memory: 22701 grad_norm: 5.2567 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9329 loss: 0.9329 2022/09/06 05:50:36 - mmengine - INFO - Epoch(train) [92][920/940] lr: 1.0000e-04 eta: 1:44:03 time: 0.7623 data_time: 0.1115 memory: 22701 grad_norm: 5.2968 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9526 loss: 0.9526 2022/09/06 05:50:52 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:50:52 - mmengine - INFO - Epoch(train) [92][940/940] lr: 1.0000e-04 eta: 1:43:46 time: 0.8241 data_time: 0.1330 memory: 22701 grad_norm: 5.7182 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.0104 loss: 1.0104 2022/09/06 05:51:06 - mmengine - INFO - Epoch(val) [92][20/78] eta: 0:00:39 time: 0.6857 data_time: 0.5661 memory: 2247 2022/09/06 05:51:15 - mmengine - INFO - Epoch(val) [92][40/78] eta: 0:00:17 time: 0.4521 data_time: 0.3292 memory: 2247 2022/09/06 05:51:28 - mmengine - INFO - Epoch(val) [92][60/78] eta: 0:00:11 time: 0.6467 data_time: 0.5294 memory: 2247 2022/09/06 05:51:38 - mmengine - INFO - Epoch(val) [92][78/78] acc/top1: 0.6913 acc/top5: 0.8801 acc/mean1: 0.6912 2022/09/06 05:51:39 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/action/work_dirs/tsn_dense161_320p_1x1x3_100e_kinetics400_rgb/best_acc/top1_epoch_60.pth is removed 2022/09/06 05:51:39 - mmengine - INFO - The best checkpoint with 0.6913 acc/top1 at 93 epoch is saved to best_acc/top1_epoch_93.pth. 2022/09/06 05:52:01 - mmengine - INFO - Epoch(train) [93][20/940] lr: 1.0000e-04 eta: 1:43:30 time: 1.0924 data_time: 0.7141 memory: 22701 grad_norm: 5.3654 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9702 loss: 0.9702 2022/09/06 05:52:13 - mmengine - INFO - Epoch(train) [93][40/940] lr: 1.0000e-04 eta: 1:43:13 time: 0.6051 data_time: 0.2281 memory: 22701 grad_norm: 5.3325 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8367 loss: 0.8367 2022/09/06 05:52:30 - mmengine - INFO - Epoch(train) [93][60/940] lr: 1.0000e-04 eta: 1:42:57 time: 0.8460 data_time: 0.4746 memory: 22701 grad_norm: 5.3201 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9133 loss: 0.9133 2022/09/06 05:52:45 - mmengine - INFO - Epoch(train) [93][80/940] lr: 1.0000e-04 eta: 1:42:40 time: 0.7420 data_time: 0.3774 memory: 22701 grad_norm: 5.4510 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9203 loss: 0.9203 2022/09/06 05:53:05 - mmengine - INFO - Epoch(train) [93][100/940] lr: 1.0000e-04 eta: 1:42:24 time: 0.9750 data_time: 0.6038 memory: 22701 grad_norm: 5.3438 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0028 loss: 1.0028 2022/09/06 05:53:20 - mmengine - INFO - Epoch(train) [93][120/940] lr: 1.0000e-04 eta: 1:42:07 time: 0.7503 data_time: 0.3487 memory: 22701 grad_norm: 5.3431 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9054 loss: 0.9054 2022/09/06 05:53:38 - mmengine - INFO - Epoch(train) [93][140/940] lr: 1.0000e-04 eta: 1:41:51 time: 0.9223 data_time: 0.5255 memory: 22701 grad_norm: 5.4315 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9554 loss: 0.9554 2022/09/06 05:53:53 - mmengine - INFO - Epoch(train) [93][160/940] lr: 1.0000e-04 eta: 1:41:34 time: 0.7373 data_time: 0.3260 memory: 22701 grad_norm: 5.4830 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.8965 loss: 0.8965 2022/09/06 05:54:09 - mmengine - INFO - Epoch(train) [93][180/940] lr: 1.0000e-04 eta: 1:41:17 time: 0.8151 data_time: 0.4246 memory: 22701 grad_norm: 5.3056 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0258 loss: 1.0258 2022/09/06 05:54:24 - mmengine - INFO - Epoch(train) [93][200/940] lr: 1.0000e-04 eta: 1:41:01 time: 0.7415 data_time: 0.3199 memory: 22701 grad_norm: 5.4114 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9947 loss: 0.9947 2022/09/06 05:54:44 - mmengine - INFO - Epoch(train) [93][220/940] lr: 1.0000e-04 eta: 1:40:44 time: 0.9790 data_time: 0.5832 memory: 22701 grad_norm: 5.3145 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0168 loss: 1.0168 2022/09/06 05:54:58 - mmengine - INFO - Epoch(train) [93][240/940] lr: 1.0000e-04 eta: 1:40:27 time: 0.7320 data_time: 0.3565 memory: 22701 grad_norm: 5.3376 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 0.9464 loss: 0.9464 2022/09/06 05:55:18 - mmengine - INFO - Epoch(train) [93][260/940] lr: 1.0000e-04 eta: 1:40:11 time: 0.9975 data_time: 0.6025 memory: 22701 grad_norm: 5.3296 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.8709 loss: 0.8709 2022/09/06 05:55:35 - mmengine - INFO - Epoch(train) [93][280/940] lr: 1.0000e-04 eta: 1:39:55 time: 0.8588 data_time: 0.4736 memory: 22701 grad_norm: 5.2940 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0347 loss: 1.0347 2022/09/06 05:55:55 - mmengine - INFO - Epoch(train) [93][300/940] lr: 1.0000e-04 eta: 1:39:38 time: 0.9740 data_time: 0.4962 memory: 22701 grad_norm: 5.3588 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9875 loss: 0.9875 2022/09/06 05:56:13 - mmengine - INFO - Epoch(train) [93][320/940] lr: 1.0000e-04 eta: 1:39:22 time: 0.9003 data_time: 0.2192 memory: 22701 grad_norm: 5.3038 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8279 loss: 0.8279 2022/09/06 05:56:33 - mmengine - INFO - Epoch(train) [93][340/940] lr: 1.0000e-04 eta: 1:39:06 time: 1.0203 data_time: 0.4314 memory: 22701 grad_norm: 5.3506 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0017 loss: 1.0017 2022/09/06 05:56:51 - mmengine - INFO - Epoch(train) [93][360/940] lr: 1.0000e-04 eta: 1:38:49 time: 0.8662 data_time: 0.0268 memory: 22701 grad_norm: 5.4714 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8944 loss: 0.8944 2022/09/06 05:57:06 - mmengine - INFO - Epoch(train) [93][380/940] lr: 1.0000e-04 eta: 1:38:33 time: 0.7525 data_time: 0.0257 memory: 22701 grad_norm: 5.4033 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9262 loss: 0.9262 2022/09/06 05:57:24 - mmengine - INFO - Epoch(train) [93][400/940] lr: 1.0000e-04 eta: 1:38:16 time: 0.9007 data_time: 0.0226 memory: 22701 grad_norm: 5.3743 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 0.8846 loss: 0.8846 2022/09/06 05:57:40 - mmengine - INFO - Epoch(train) [93][420/940] lr: 1.0000e-04 eta: 1:37:59 time: 0.8003 data_time: 0.0244 memory: 22701 grad_norm: 5.2495 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9210 loss: 0.9210 2022/09/06 05:58:10 - mmengine - INFO - Epoch(train) [93][440/940] lr: 1.0000e-04 eta: 1:37:44 time: 1.5093 data_time: 0.0196 memory: 22701 grad_norm: 5.4140 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0089 loss: 1.0089 2022/09/06 05:58:25 - mmengine - INFO - Epoch(train) [93][460/940] lr: 1.0000e-04 eta: 1:37:27 time: 0.7315 data_time: 0.0237 memory: 22701 grad_norm: 5.3151 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9570 loss: 0.9570 2022/09/06 05:58:46 - mmengine - INFO - Epoch(train) [93][480/940] lr: 1.0000e-04 eta: 1:37:11 time: 1.0523 data_time: 0.0252 memory: 22701 grad_norm: 5.3966 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9154 loss: 0.9154 2022/09/06 05:59:00 - mmengine - INFO - Epoch(train) [93][500/940] lr: 1.0000e-04 eta: 1:36:54 time: 0.7130 data_time: 0.0266 memory: 22701 grad_norm: 5.3415 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8575 loss: 0.8575 2022/09/06 05:59:18 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 05:59:18 - mmengine - INFO - Epoch(train) [93][520/940] lr: 1.0000e-04 eta: 1:36:38 time: 0.8948 data_time: 0.0282 memory: 22701 grad_norm: 5.3835 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0540 loss: 1.0540 2022/09/06 05:59:31 - mmengine - INFO - Epoch(train) [93][540/940] lr: 1.0000e-04 eta: 1:36:21 time: 0.6745 data_time: 0.0324 memory: 22701 grad_norm: 5.3362 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9772 loss: 0.9772 2022/09/06 05:59:47 - mmengine - INFO - Epoch(train) [93][560/940] lr: 1.0000e-04 eta: 1:36:04 time: 0.7962 data_time: 0.0282 memory: 22701 grad_norm: 5.4781 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9093 loss: 0.9093 2022/09/06 06:00:05 - mmengine - INFO - Epoch(train) [93][580/940] lr: 1.0000e-04 eta: 1:35:48 time: 0.8757 data_time: 0.0929 memory: 22701 grad_norm: 5.4057 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9642 loss: 0.9642 2022/09/06 06:00:20 - mmengine - INFO - Epoch(train) [93][600/940] lr: 1.0000e-04 eta: 1:35:31 time: 0.7455 data_time: 0.0272 memory: 22701 grad_norm: 5.4059 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9225 loss: 0.9225 2022/09/06 06:00:35 - mmengine - INFO - Epoch(train) [93][620/940] lr: 1.0000e-04 eta: 1:35:15 time: 0.7510 data_time: 0.0268 memory: 22701 grad_norm: 5.4127 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.8975 loss: 0.8975 2022/09/06 06:00:51 - mmengine - INFO - Epoch(train) [93][640/940] lr: 1.0000e-04 eta: 1:34:58 time: 0.8125 data_time: 0.0406 memory: 22701 grad_norm: 5.3848 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9799 loss: 0.9799 2022/09/06 06:01:06 - mmengine - INFO - Epoch(train) [93][660/940] lr: 1.0000e-04 eta: 1:34:41 time: 0.7305 data_time: 0.1175 memory: 22701 grad_norm: 5.3340 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9322 loss: 0.9322 2022/09/06 06:01:23 - mmengine - INFO - Epoch(train) [93][680/940] lr: 1.0000e-04 eta: 1:34:25 time: 0.8516 data_time: 0.1732 memory: 22701 grad_norm: 5.2426 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9361 loss: 0.9361 2022/09/06 06:01:36 - mmengine - INFO - Epoch(train) [93][700/940] lr: 1.0000e-04 eta: 1:34:08 time: 0.6587 data_time: 0.1032 memory: 22701 grad_norm: 5.3760 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9314 loss: 0.9314 2022/09/06 06:01:52 - mmengine - INFO - Epoch(train) [93][720/940] lr: 1.0000e-04 eta: 1:33:51 time: 0.8042 data_time: 0.2309 memory: 22701 grad_norm: 5.3787 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9230 loss: 0.9230 2022/09/06 06:02:06 - mmengine - INFO - Epoch(train) [93][740/940] lr: 1.0000e-04 eta: 1:33:35 time: 0.6967 data_time: 0.1805 memory: 22701 grad_norm: 5.3232 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0776 loss: 1.0776 2022/09/06 06:02:22 - mmengine - INFO - Epoch(train) [93][760/940] lr: 1.0000e-04 eta: 1:33:18 time: 0.7921 data_time: 0.3473 memory: 22701 grad_norm: 5.3428 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9596 loss: 0.9596 2022/09/06 06:02:37 - mmengine - INFO - Epoch(train) [93][780/940] lr: 1.0000e-04 eta: 1:33:01 time: 0.7684 data_time: 0.3752 memory: 22701 grad_norm: 5.3492 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8276 loss: 0.8276 2022/09/06 06:02:55 - mmengine - INFO - Epoch(train) [93][800/940] lr: 1.0000e-04 eta: 1:32:45 time: 0.9163 data_time: 0.4517 memory: 22701 grad_norm: 5.4119 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 0.9854 loss: 0.9854 2022/09/06 06:03:09 - mmengine - INFO - Epoch(train) [93][820/940] lr: 1.0000e-04 eta: 1:32:28 time: 0.7012 data_time: 0.3169 memory: 22701 grad_norm: 5.4577 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0048 loss: 1.0048 2022/09/06 06:03:27 - mmengine - INFO - Epoch(train) [93][840/940] lr: 1.0000e-04 eta: 1:32:12 time: 0.8919 data_time: 0.4586 memory: 22701 grad_norm: 5.3851 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9628 loss: 0.9628 2022/09/06 06:03:42 - mmengine - INFO - Epoch(train) [93][860/940] lr: 1.0000e-04 eta: 1:31:55 time: 0.7222 data_time: 0.3145 memory: 22701 grad_norm: 5.3960 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9310 loss: 0.9310 2022/09/06 06:03:59 - mmengine - INFO - Epoch(train) [93][880/940] lr: 1.0000e-04 eta: 1:31:38 time: 0.8799 data_time: 0.4236 memory: 22701 grad_norm: 5.4465 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9179 loss: 0.9179 2022/09/06 06:04:15 - mmengine - INFO - Epoch(train) [93][900/940] lr: 1.0000e-04 eta: 1:31:22 time: 0.7764 data_time: 0.2360 memory: 22701 grad_norm: 5.3835 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 0.9585 loss: 0.9585 2022/09/06 06:04:32 - mmengine - INFO - Epoch(train) [93][920/940] lr: 1.0000e-04 eta: 1:31:05 time: 0.8643 data_time: 0.2213 memory: 22701 grad_norm: 5.3865 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 0.9756 loss: 0.9756 2022/09/06 06:04:48 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:04:48 - mmengine - INFO - Epoch(train) [93][940/940] lr: 1.0000e-04 eta: 1:30:49 time: 0.8007 data_time: 0.3204 memory: 22701 grad_norm: 5.5548 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.8896 loss: 0.8896 2022/09/06 06:04:48 - mmengine - INFO - Saving checkpoint at 93 epochs 2022/09/06 06:05:04 - mmengine - INFO - Epoch(val) [93][20/78] eta: 0:00:40 time: 0.7024 data_time: 0.5867 memory: 2247 2022/09/06 06:05:13 - mmengine - INFO - Epoch(val) [93][40/78] eta: 0:00:17 time: 0.4498 data_time: 0.3353 memory: 2247 2022/09/06 06:05:26 - mmengine - INFO - Epoch(val) [93][60/78] eta: 0:00:11 time: 0.6638 data_time: 0.5468 memory: 2247 2022/09/06 06:05:36 - mmengine - INFO - Epoch(val) [93][78/78] acc/top1: 0.6871 acc/top5: 0.8801 acc/mean1: 0.6870 2022/09/06 06:05:54 - mmengine - INFO - Epoch(train) [94][20/940] lr: 1.0000e-04 eta: 1:30:32 time: 0.9337 data_time: 0.3095 memory: 22701 grad_norm: 5.2800 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9113 loss: 0.9113 2022/09/06 06:06:07 - mmengine - INFO - Epoch(train) [94][40/940] lr: 1.0000e-04 eta: 1:30:15 time: 0.6418 data_time: 0.1438 memory: 22701 grad_norm: 5.4306 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9493 loss: 0.9493 2022/09/06 06:06:24 - mmengine - INFO - Epoch(train) [94][60/940] lr: 1.0000e-04 eta: 1:29:59 time: 0.8290 data_time: 0.1828 memory: 22701 grad_norm: 5.3742 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9063 loss: 0.9063 2022/09/06 06:06:38 - mmengine - INFO - Epoch(train) [94][80/940] lr: 1.0000e-04 eta: 1:29:42 time: 0.6918 data_time: 0.2430 memory: 22701 grad_norm: 5.4170 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9938 loss: 0.9938 2022/09/06 06:06:55 - mmengine - INFO - Epoch(train) [94][100/940] lr: 1.0000e-04 eta: 1:29:26 time: 0.8519 data_time: 0.4126 memory: 22701 grad_norm: 5.3690 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 0.9720 loss: 0.9720 2022/09/06 06:07:09 - mmengine - INFO - Epoch(train) [94][120/940] lr: 1.0000e-04 eta: 1:29:09 time: 0.7193 data_time: 0.3388 memory: 22701 grad_norm: 5.3120 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.8738 loss: 0.8738 2022/09/06 06:07:26 - mmengine - INFO - Epoch(train) [94][140/940] lr: 1.0000e-04 eta: 1:28:52 time: 0.8547 data_time: 0.3963 memory: 22701 grad_norm: 5.4437 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9942 loss: 0.9942 2022/09/06 06:07:41 - mmengine - INFO - Epoch(train) [94][160/940] lr: 1.0000e-04 eta: 1:28:36 time: 0.7224 data_time: 0.3113 memory: 22701 grad_norm: 5.2480 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.8796 loss: 0.8796 2022/09/06 06:07:59 - mmengine - INFO - Epoch(train) [94][180/940] lr: 1.0000e-04 eta: 1:28:19 time: 0.9068 data_time: 0.4806 memory: 22701 grad_norm: 5.4206 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9672 loss: 0.9672 2022/09/06 06:08:14 - mmengine - INFO - Epoch(train) [94][200/940] lr: 1.0000e-04 eta: 1:28:02 time: 0.7780 data_time: 0.3620 memory: 22701 grad_norm: 5.5106 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.0411 loss: 1.0411 2022/09/06 06:08:30 - mmengine - INFO - Epoch(train) [94][220/940] lr: 1.0000e-04 eta: 1:27:46 time: 0.8075 data_time: 0.1954 memory: 22701 grad_norm: 5.2313 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9797 loss: 0.9797 2022/09/06 06:08:45 - mmengine - INFO - Epoch(train) [94][240/940] lr: 1.0000e-04 eta: 1:27:29 time: 0.7188 data_time: 0.1335 memory: 22701 grad_norm: 5.2592 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9235 loss: 0.9235 2022/09/06 06:09:00 - mmengine - INFO - Epoch(train) [94][260/940] lr: 1.0000e-04 eta: 1:27:13 time: 0.7565 data_time: 0.2135 memory: 22701 grad_norm: 5.4372 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8430 loss: 0.8430 2022/09/06 06:09:14 - mmengine - INFO - Epoch(train) [94][280/940] lr: 1.0000e-04 eta: 1:26:56 time: 0.6981 data_time: 0.2077 memory: 22701 grad_norm: 5.3587 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 0.9666 loss: 0.9666 2022/09/06 06:09:31 - mmengine - INFO - Epoch(train) [94][300/940] lr: 1.0000e-04 eta: 1:26:39 time: 0.8685 data_time: 0.3983 memory: 22701 grad_norm: 5.5089 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8311 loss: 0.8311 2022/09/06 06:09:45 - mmengine - INFO - Epoch(train) [94][320/940] lr: 1.0000e-04 eta: 1:26:23 time: 0.6842 data_time: 0.2111 memory: 22701 grad_norm: 5.4224 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0070 loss: 1.0070 2022/09/06 06:10:05 - mmengine - INFO - Epoch(train) [94][340/940] lr: 1.0000e-04 eta: 1:26:06 time: 0.9802 data_time: 0.0661 memory: 22701 grad_norm: 5.4020 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9212 loss: 0.9212 2022/09/06 06:10:18 - mmengine - INFO - Epoch(train) [94][360/940] lr: 1.0000e-04 eta: 1:25:49 time: 0.6548 data_time: 0.0236 memory: 22701 grad_norm: 5.3215 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.8858 loss: 0.8858 2022/09/06 06:10:36 - mmengine - INFO - Epoch(train) [94][380/940] lr: 1.0000e-04 eta: 1:25:33 time: 0.9289 data_time: 0.0370 memory: 22701 grad_norm: 5.3107 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9389 loss: 0.9389 2022/09/06 06:10:53 - mmengine - INFO - Epoch(train) [94][400/940] lr: 1.0000e-04 eta: 1:25:16 time: 0.8248 data_time: 0.0240 memory: 22701 grad_norm: 5.4106 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9025 loss: 0.9025 2022/09/06 06:11:12 - mmengine - INFO - Epoch(train) [94][420/940] lr: 1.0000e-04 eta: 1:25:00 time: 0.9632 data_time: 0.0247 memory: 22701 grad_norm: 5.3821 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9453 loss: 0.9453 2022/09/06 06:11:27 - mmengine - INFO - Epoch(train) [94][440/940] lr: 1.0000e-04 eta: 1:24:43 time: 0.7243 data_time: 0.0265 memory: 22701 grad_norm: 5.3290 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9434 loss: 0.9434 2022/09/06 06:11:45 - mmengine - INFO - Epoch(train) [94][460/940] lr: 1.0000e-04 eta: 1:24:27 time: 0.9277 data_time: 0.0261 memory: 22701 grad_norm: 5.3592 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.8837 loss: 0.8837 2022/09/06 06:11:59 - mmengine - INFO - Epoch(train) [94][480/940] lr: 1.0000e-04 eta: 1:24:10 time: 0.7008 data_time: 0.0251 memory: 22701 grad_norm: 5.3142 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9045 loss: 0.9045 2022/09/06 06:12:15 - mmengine - INFO - Epoch(train) [94][500/940] lr: 1.0000e-04 eta: 1:23:54 time: 0.7852 data_time: 0.0281 memory: 22701 grad_norm: 5.2193 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.8925 loss: 0.8925 2022/09/06 06:12:30 - mmengine - INFO - Epoch(train) [94][520/940] lr: 1.0000e-04 eta: 1:23:37 time: 0.7492 data_time: 0.0339 memory: 22701 grad_norm: 5.4186 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1027 loss: 1.1027 2022/09/06 06:12:46 - mmengine - INFO - Epoch(train) [94][540/940] lr: 1.0000e-04 eta: 1:23:20 time: 0.8285 data_time: 0.0260 memory: 22701 grad_norm: 5.3901 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.8794 loss: 0.8794 2022/09/06 06:13:04 - mmengine - INFO - Epoch(train) [94][560/940] lr: 1.0000e-04 eta: 1:23:04 time: 0.8527 data_time: 0.0217 memory: 22701 grad_norm: 5.4024 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0310 loss: 1.0310 2022/09/06 06:13:20 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:13:20 - mmengine - INFO - Epoch(train) [94][580/940] lr: 1.0000e-04 eta: 1:22:47 time: 0.8360 data_time: 0.0362 memory: 22701 grad_norm: 5.3224 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0659 loss: 1.0659 2022/09/06 06:13:36 - mmengine - INFO - Epoch(train) [94][600/940] lr: 1.0000e-04 eta: 1:22:31 time: 0.7739 data_time: 0.0272 memory: 22701 grad_norm: 5.3822 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0659 loss: 1.0659 2022/09/06 06:13:53 - mmengine - INFO - Epoch(train) [94][620/940] lr: 1.0000e-04 eta: 1:22:14 time: 0.8783 data_time: 0.0281 memory: 22701 grad_norm: 5.5052 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9157 loss: 0.9157 2022/09/06 06:14:08 - mmengine - INFO - Epoch(train) [94][640/940] lr: 1.0000e-04 eta: 1:21:57 time: 0.7299 data_time: 0.1145 memory: 22701 grad_norm: 5.4026 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0522 loss: 1.0522 2022/09/06 06:14:24 - mmengine - INFO - Epoch(train) [94][660/940] lr: 1.0000e-04 eta: 1:21:41 time: 0.8239 data_time: 0.3074 memory: 22701 grad_norm: 5.2957 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9060 loss: 0.9060 2022/09/06 06:14:41 - mmengine - INFO - Epoch(train) [94][680/940] lr: 1.0000e-04 eta: 1:21:24 time: 0.8277 data_time: 0.0201 memory: 22701 grad_norm: 5.3688 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8843 loss: 0.8843 2022/09/06 06:14:56 - mmengine - INFO - Epoch(train) [94][700/940] lr: 1.0000e-04 eta: 1:21:08 time: 0.7477 data_time: 0.0276 memory: 22701 grad_norm: 5.4078 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9625 loss: 0.9625 2022/09/06 06:15:10 - mmengine - INFO - Epoch(train) [94][720/940] lr: 1.0000e-04 eta: 1:20:51 time: 0.6928 data_time: 0.0329 memory: 22701 grad_norm: 5.3589 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9542 loss: 0.9542 2022/09/06 06:15:24 - mmengine - INFO - Epoch(train) [94][740/940] lr: 1.0000e-04 eta: 1:20:34 time: 0.7207 data_time: 0.0258 memory: 22701 grad_norm: 5.3666 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9398 loss: 0.9398 2022/09/06 06:15:41 - mmengine - INFO - Epoch(train) [94][760/940] lr: 1.0000e-04 eta: 1:20:18 time: 0.8366 data_time: 0.0279 memory: 22701 grad_norm: 5.4343 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9158 loss: 0.9158 2022/09/06 06:16:00 - mmengine - INFO - Epoch(train) [94][780/940] lr: 1.0000e-04 eta: 1:20:01 time: 0.9207 data_time: 0.1102 memory: 22701 grad_norm: 5.3405 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0261 loss: 1.0261 2022/09/06 06:16:19 - mmengine - INFO - Epoch(train) [94][800/940] lr: 1.0000e-04 eta: 1:19:45 time: 0.9560 data_time: 0.0895 memory: 22701 grad_norm: 5.2852 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 0.9761 loss: 0.9761 2022/09/06 06:16:33 - mmengine - INFO - Epoch(train) [94][820/940] lr: 1.0000e-04 eta: 1:19:28 time: 0.6957 data_time: 0.0339 memory: 22701 grad_norm: 5.3117 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9241 loss: 0.9241 2022/09/06 06:16:49 - mmengine - INFO - Epoch(train) [94][840/940] lr: 1.0000e-04 eta: 1:19:12 time: 0.8177 data_time: 0.0339 memory: 22701 grad_norm: 5.3498 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 0.9689 loss: 0.9689 2022/09/06 06:17:04 - mmengine - INFO - Epoch(train) [94][860/940] lr: 1.0000e-04 eta: 1:18:55 time: 0.7818 data_time: 0.0271 memory: 22701 grad_norm: 5.3423 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9249 loss: 0.9249 2022/09/06 06:17:26 - mmengine - INFO - Epoch(train) [94][880/940] lr: 1.0000e-04 eta: 1:18:39 time: 1.0630 data_time: 0.0247 memory: 22701 grad_norm: 5.3452 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9777 loss: 0.9777 2022/09/06 06:17:42 - mmengine - INFO - Epoch(train) [94][900/940] lr: 1.0000e-04 eta: 1:18:22 time: 0.8236 data_time: 0.0272 memory: 22701 grad_norm: 5.4651 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0665 loss: 1.0665 2022/09/06 06:17:59 - mmengine - INFO - Epoch(train) [94][920/940] lr: 1.0000e-04 eta: 1:18:06 time: 0.8296 data_time: 0.0283 memory: 22701 grad_norm: 5.3511 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.8953 loss: 0.8953 2022/09/06 06:18:14 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:18:14 - mmengine - INFO - Epoch(train) [94][940/940] lr: 1.0000e-04 eta: 1:17:49 time: 0.7613 data_time: 0.0181 memory: 22701 grad_norm: 5.7243 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 0.9573 loss: 0.9573 2022/09/06 06:18:28 - mmengine - INFO - Epoch(val) [94][20/78] eta: 0:00:40 time: 0.7015 data_time: 0.5799 memory: 2247 2022/09/06 06:18:38 - mmengine - INFO - Epoch(val) [94][40/78] eta: 0:00:17 time: 0.4674 data_time: 0.3465 memory: 2247 2022/09/06 06:18:50 - mmengine - INFO - Epoch(val) [94][60/78] eta: 0:00:11 time: 0.6238 data_time: 0.5038 memory: 2247 2022/09/06 06:19:00 - mmengine - INFO - Epoch(val) [94][78/78] acc/top1: 0.6870 acc/top5: 0.8809 acc/mean1: 0.6869 2022/09/06 06:19:23 - mmengine - INFO - Epoch(train) [95][20/940] lr: 1.0000e-04 eta: 1:17:33 time: 1.1337 data_time: 0.5732 memory: 22701 grad_norm: 5.4092 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9039 loss: 0.9039 2022/09/06 06:19:39 - mmengine - INFO - Epoch(train) [95][40/940] lr: 1.0000e-04 eta: 1:17:16 time: 0.7958 data_time: 0.3713 memory: 22701 grad_norm: 5.4088 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 0.8562 loss: 0.8562 2022/09/06 06:19:57 - mmengine - INFO - Epoch(train) [95][60/940] lr: 1.0000e-04 eta: 1:17:00 time: 0.9220 data_time: 0.3140 memory: 22701 grad_norm: 5.3307 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.0221 loss: 1.0221 2022/09/06 06:20:11 - mmengine - INFO - Epoch(train) [95][80/940] lr: 1.0000e-04 eta: 1:16:43 time: 0.6736 data_time: 0.1320 memory: 22701 grad_norm: 5.4669 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0092 loss: 1.0092 2022/09/06 06:20:30 - mmengine - INFO - Epoch(train) [95][100/940] lr: 1.0000e-04 eta: 1:16:27 time: 0.9511 data_time: 0.2667 memory: 22701 grad_norm: 5.4355 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9339 loss: 0.9339 2022/09/06 06:20:45 - mmengine - INFO - Epoch(train) [95][120/940] lr: 1.0000e-04 eta: 1:16:10 time: 0.7592 data_time: 0.1285 memory: 22701 grad_norm: 5.1901 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9097 loss: 0.9097 2022/09/06 06:21:07 - mmengine - INFO - Epoch(train) [95][140/940] lr: 1.0000e-04 eta: 1:15:54 time: 1.1279 data_time: 0.3482 memory: 22701 grad_norm: 5.4730 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9363 loss: 0.9363 2022/09/06 06:21:21 - mmengine - INFO - Epoch(train) [95][160/940] lr: 1.0000e-04 eta: 1:15:37 time: 0.7058 data_time: 0.0293 memory: 22701 grad_norm: 5.2991 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 0.9563 loss: 0.9563 2022/09/06 06:21:41 - mmengine - INFO - Epoch(train) [95][180/940] lr: 1.0000e-04 eta: 1:15:21 time: 0.9564 data_time: 0.0235 memory: 22701 grad_norm: 5.3416 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9363 loss: 0.9363 2022/09/06 06:21:59 - mmengine - INFO - Epoch(train) [95][200/940] lr: 1.0000e-04 eta: 1:15:04 time: 0.9124 data_time: 0.0180 memory: 22701 grad_norm: 5.3789 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 0.9243 loss: 0.9243 2022/09/06 06:22:19 - mmengine - INFO - Epoch(train) [95][220/940] lr: 1.0000e-04 eta: 1:14:48 time: 1.0159 data_time: 0.0330 memory: 22701 grad_norm: 5.3915 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8679 loss: 0.8679 2022/09/06 06:22:37 - mmengine - INFO - Epoch(train) [95][240/940] lr: 1.0000e-04 eta: 1:14:31 time: 0.8936 data_time: 0.0183 memory: 22701 grad_norm: 5.4397 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8904 loss: 0.8904 2022/09/06 06:22:57 - mmengine - INFO - Epoch(train) [95][260/940] lr: 1.0000e-04 eta: 1:14:15 time: 1.0063 data_time: 0.0327 memory: 22701 grad_norm: 5.2904 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.7976 loss: 0.7976 2022/09/06 06:23:14 - mmengine - INFO - Epoch(train) [95][280/940] lr: 1.0000e-04 eta: 1:13:58 time: 0.8283 data_time: 0.0182 memory: 22701 grad_norm: 5.3499 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.8908 loss: 0.8908 2022/09/06 06:23:34 - mmengine - INFO - Epoch(train) [95][300/940] lr: 1.0000e-04 eta: 1:13:42 time: 0.9942 data_time: 0.0286 memory: 22701 grad_norm: 5.3957 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.9290 loss: 0.9290 2022/09/06 06:23:49 - mmengine - INFO - Epoch(train) [95][320/940] lr: 1.0000e-04 eta: 1:13:25 time: 0.7639 data_time: 0.0312 memory: 22701 grad_norm: 5.2851 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0071 loss: 1.0071 2022/09/06 06:24:07 - mmengine - INFO - Epoch(train) [95][340/940] lr: 1.0000e-04 eta: 1:13:09 time: 0.8814 data_time: 0.0352 memory: 22701 grad_norm: 5.4119 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0691 loss: 1.0691 2022/09/06 06:24:22 - mmengine - INFO - Epoch(train) [95][360/940] lr: 1.0000e-04 eta: 1:12:52 time: 0.7606 data_time: 0.0269 memory: 22701 grad_norm: 5.3198 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9690 loss: 0.9690 2022/09/06 06:24:38 - mmengine - INFO - Epoch(train) [95][380/940] lr: 1.0000e-04 eta: 1:12:36 time: 0.8187 data_time: 0.0300 memory: 22701 grad_norm: 5.4036 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9268 loss: 0.9268 2022/09/06 06:24:53 - mmengine - INFO - Epoch(train) [95][400/940] lr: 1.0000e-04 eta: 1:12:19 time: 0.7524 data_time: 0.0279 memory: 22701 grad_norm: 5.3798 top1_acc: 0.9688 top5_acc: 0.9688 loss_cls: 0.9295 loss: 0.9295 2022/09/06 06:25:12 - mmengine - INFO - Epoch(train) [95][420/940] lr: 1.0000e-04 eta: 1:12:03 time: 0.9452 data_time: 0.0247 memory: 22701 grad_norm: 5.3713 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9142 loss: 0.9142 2022/09/06 06:25:28 - mmengine - INFO - Epoch(train) [95][440/940] lr: 1.0000e-04 eta: 1:11:46 time: 0.8041 data_time: 0.0261 memory: 22701 grad_norm: 5.2990 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8906 loss: 0.8906 2022/09/06 06:25:46 - mmengine - INFO - Epoch(train) [95][460/940] lr: 1.0000e-04 eta: 1:11:29 time: 0.8729 data_time: 0.0234 memory: 22701 grad_norm: 5.6057 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0418 loss: 1.0418 2022/09/06 06:26:00 - mmengine - INFO - Epoch(train) [95][480/940] lr: 1.0000e-04 eta: 1:11:13 time: 0.7325 data_time: 0.0239 memory: 22701 grad_norm: 5.3202 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 0.8934 loss: 0.8934 2022/09/06 06:26:19 - mmengine - INFO - Epoch(train) [95][500/940] lr: 1.0000e-04 eta: 1:10:56 time: 0.9378 data_time: 0.0304 memory: 22701 grad_norm: 5.3299 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9101 loss: 0.9101 2022/09/06 06:26:35 - mmengine - INFO - Epoch(train) [95][520/940] lr: 1.0000e-04 eta: 1:10:40 time: 0.8035 data_time: 0.0298 memory: 22701 grad_norm: 5.2971 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.8970 loss: 0.8970 2022/09/06 06:26:52 - mmengine - INFO - Epoch(train) [95][540/940] lr: 1.0000e-04 eta: 1:10:23 time: 0.8409 data_time: 0.0295 memory: 22701 grad_norm: 5.3275 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.8924 loss: 0.8924 2022/09/06 06:27:09 - mmengine - INFO - Epoch(train) [95][560/940] lr: 1.0000e-04 eta: 1:10:07 time: 0.8621 data_time: 0.0702 memory: 22701 grad_norm: 5.4301 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0066 loss: 1.0066 2022/09/06 06:27:27 - mmengine - INFO - Epoch(train) [95][580/940] lr: 1.0000e-04 eta: 1:09:50 time: 0.8865 data_time: 0.0290 memory: 22701 grad_norm: 5.3514 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0178 loss: 1.0178 2022/09/06 06:27:45 - mmengine - INFO - Epoch(train) [95][600/940] lr: 1.0000e-04 eta: 1:09:34 time: 0.9111 data_time: 0.0274 memory: 22701 grad_norm: 5.3278 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9707 loss: 0.9707 2022/09/06 06:28:01 - mmengine - INFO - Epoch(train) [95][620/940] lr: 1.0000e-04 eta: 1:09:17 time: 0.7965 data_time: 0.0181 memory: 22701 grad_norm: 5.4211 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9139 loss: 0.9139 2022/09/06 06:28:20 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:28:20 - mmengine - INFO - Epoch(train) [95][640/940] lr: 1.0000e-04 eta: 1:09:01 time: 0.9377 data_time: 0.1470 memory: 22701 grad_norm: 5.3533 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0159 loss: 1.0159 2022/09/06 06:28:38 - mmengine - INFO - Epoch(train) [95][660/940] lr: 1.0000e-04 eta: 1:08:44 time: 0.9147 data_time: 0.1439 memory: 22701 grad_norm: 5.5056 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.0082 loss: 1.0082 2022/09/06 06:28:55 - mmengine - INFO - Epoch(train) [95][680/940] lr: 1.0000e-04 eta: 1:08:28 time: 0.8622 data_time: 0.3449 memory: 22701 grad_norm: 5.2996 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.9361 loss: 0.9361 2022/09/06 06:29:12 - mmengine - INFO - Epoch(train) [95][700/940] lr: 1.0000e-04 eta: 1:08:11 time: 0.8053 data_time: 0.1951 memory: 22701 grad_norm: 5.4830 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9846 loss: 0.9846 2022/09/06 06:29:28 - mmengine - INFO - Epoch(train) [95][720/940] lr: 1.0000e-04 eta: 1:07:55 time: 0.8239 data_time: 0.1991 memory: 22701 grad_norm: 5.2924 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.8630 loss: 0.8630 2022/09/06 06:29:50 - mmengine - INFO - Epoch(train) [95][740/940] lr: 1.0000e-04 eta: 1:07:38 time: 1.1198 data_time: 0.1162 memory: 22701 grad_norm: 5.3102 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9582 loss: 0.9582 2022/09/06 06:30:06 - mmengine - INFO - Epoch(train) [95][760/940] lr: 1.0000e-04 eta: 1:07:22 time: 0.7808 data_time: 0.0274 memory: 22701 grad_norm: 5.4526 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9547 loss: 0.9547 2022/09/06 06:30:24 - mmengine - INFO - Epoch(train) [95][780/940] lr: 1.0000e-04 eta: 1:07:05 time: 0.8853 data_time: 0.0213 memory: 22701 grad_norm: 5.4593 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0982 loss: 1.0982 2022/09/06 06:30:39 - mmengine - INFO - Epoch(train) [95][800/940] lr: 1.0000e-04 eta: 1:06:49 time: 0.7589 data_time: 0.0256 memory: 22701 grad_norm: 5.2941 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9063 loss: 0.9063 2022/09/06 06:30:57 - mmengine - INFO - Epoch(train) [95][820/940] lr: 1.0000e-04 eta: 1:06:32 time: 0.8993 data_time: 0.0240 memory: 22701 grad_norm: 5.4796 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0510 loss: 1.0510 2022/09/06 06:31:12 - mmengine - INFO - Epoch(train) [95][840/940] lr: 1.0000e-04 eta: 1:06:15 time: 0.7653 data_time: 0.0291 memory: 22701 grad_norm: 5.3212 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9683 loss: 0.9683 2022/09/06 06:31:32 - mmengine - INFO - Epoch(train) [95][860/940] lr: 1.0000e-04 eta: 1:05:59 time: 0.9609 data_time: 0.0243 memory: 22701 grad_norm: 5.5195 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9642 loss: 0.9642 2022/09/06 06:31:46 - mmengine - INFO - Epoch(train) [95][880/940] lr: 1.0000e-04 eta: 1:05:42 time: 0.7022 data_time: 0.0431 memory: 22701 grad_norm: 5.3373 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8842 loss: 0.8842 2022/09/06 06:32:01 - mmengine - INFO - Epoch(train) [95][900/940] lr: 1.0000e-04 eta: 1:05:26 time: 0.7765 data_time: 0.0258 memory: 22701 grad_norm: 5.4201 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.8992 loss: 0.8992 2022/09/06 06:32:14 - mmengine - INFO - Epoch(train) [95][920/940] lr: 1.0000e-04 eta: 1:05:09 time: 0.6401 data_time: 0.0247 memory: 22701 grad_norm: 5.3888 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.8788 loss: 0.8788 2022/09/06 06:32:31 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:32:31 - mmengine - INFO - Epoch(train) [95][940/940] lr: 1.0000e-04 eta: 1:04:52 time: 0.8766 data_time: 0.0194 memory: 22701 grad_norm: 5.7525 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.0392 loss: 1.0392 2022/09/06 06:32:45 - mmengine - INFO - Epoch(val) [95][20/78] eta: 0:00:39 time: 0.6876 data_time: 0.5703 memory: 2247 2022/09/06 06:32:55 - mmengine - INFO - Epoch(val) [95][40/78] eta: 0:00:17 time: 0.4637 data_time: 0.3441 memory: 2247 2022/09/06 06:33:08 - mmengine - INFO - Epoch(val) [95][60/78] eta: 0:00:11 time: 0.6459 data_time: 0.5265 memory: 2247 2022/09/06 06:33:18 - mmengine - INFO - Epoch(val) [95][78/78] acc/top1: 0.6883 acc/top5: 0.8796 acc/mean1: 0.6882 2022/09/06 06:33:38 - mmengine - INFO - Epoch(train) [96][20/940] lr: 1.0000e-04 eta: 1:04:36 time: 0.9934 data_time: 0.3608 memory: 22701 grad_norm: 5.3352 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0117 loss: 1.0117 2022/09/06 06:33:53 - mmengine - INFO - Epoch(train) [96][40/940] lr: 1.0000e-04 eta: 1:04:19 time: 0.7592 data_time: 0.0323 memory: 22701 grad_norm: 5.3034 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.8226 loss: 0.8226 2022/09/06 06:34:09 - mmengine - INFO - Epoch(train) [96][60/940] lr: 1.0000e-04 eta: 1:04:03 time: 0.7819 data_time: 0.0320 memory: 22701 grad_norm: 5.3451 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9428 loss: 0.9428 2022/09/06 06:34:27 - mmengine - INFO - Epoch(train) [96][80/940] lr: 1.0000e-04 eta: 1:03:46 time: 0.9042 data_time: 0.0450 memory: 22701 grad_norm: 5.4373 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9414 loss: 0.9414 2022/09/06 06:34:45 - mmengine - INFO - Epoch(train) [96][100/940] lr: 1.0000e-04 eta: 1:03:30 time: 0.9118 data_time: 0.0264 memory: 22701 grad_norm: 5.3717 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9408 loss: 0.9408 2022/09/06 06:35:00 - mmengine - INFO - Epoch(train) [96][120/940] lr: 1.0000e-04 eta: 1:03:13 time: 0.7334 data_time: 0.0281 memory: 22701 grad_norm: 5.4254 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9077 loss: 0.9077 2022/09/06 06:35:20 - mmengine - INFO - Epoch(train) [96][140/940] lr: 1.0000e-04 eta: 1:02:57 time: 1.0241 data_time: 0.0276 memory: 22701 grad_norm: 5.2722 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9547 loss: 0.9547 2022/09/06 06:35:37 - mmengine - INFO - Epoch(train) [96][160/940] lr: 1.0000e-04 eta: 1:02:40 time: 0.8446 data_time: 0.0230 memory: 22701 grad_norm: 5.5101 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9706 loss: 0.9706 2022/09/06 06:35:57 - mmengine - INFO - Epoch(train) [96][180/940] lr: 1.0000e-04 eta: 1:02:24 time: 0.9821 data_time: 0.0345 memory: 22701 grad_norm: 5.3860 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9751 loss: 0.9751 2022/09/06 06:36:10 - mmengine - INFO - Epoch(train) [96][200/940] lr: 1.0000e-04 eta: 1:02:07 time: 0.6705 data_time: 0.0223 memory: 22701 grad_norm: 5.3580 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9883 loss: 0.9883 2022/09/06 06:36:27 - mmengine - INFO - Epoch(train) [96][220/940] lr: 1.0000e-04 eta: 1:01:51 time: 0.8519 data_time: 0.0565 memory: 22701 grad_norm: 5.4135 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9522 loss: 0.9522 2022/09/06 06:36:44 - mmengine - INFO - Epoch(train) [96][240/940] lr: 1.0000e-04 eta: 1:01:34 time: 0.8430 data_time: 0.1978 memory: 22701 grad_norm: 5.4895 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9864 loss: 0.9864 2022/09/06 06:37:06 - mmengine - INFO - Epoch(train) [96][260/940] lr: 1.0000e-04 eta: 1:01:18 time: 1.1071 data_time: 0.0215 memory: 22701 grad_norm: 5.4262 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8254 loss: 0.8254 2022/09/06 06:37:21 - mmengine - INFO - Epoch(train) [96][280/940] lr: 1.0000e-04 eta: 1:01:01 time: 0.7397 data_time: 0.1215 memory: 22701 grad_norm: 5.3708 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9288 loss: 0.9288 2022/09/06 06:37:43 - mmengine - INFO - Epoch(train) [96][300/940] lr: 1.0000e-04 eta: 1:00:45 time: 1.0858 data_time: 0.2674 memory: 22701 grad_norm: 5.4627 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9236 loss: 0.9236 2022/09/06 06:38:00 - mmengine - INFO - Epoch(train) [96][320/940] lr: 1.0000e-04 eta: 1:00:28 time: 0.8525 data_time: 0.2771 memory: 22701 grad_norm: 5.5515 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0268 loss: 1.0268 2022/09/06 06:38:18 - mmengine - INFO - Epoch(train) [96][340/940] lr: 1.0000e-04 eta: 1:00:12 time: 0.8853 data_time: 0.2665 memory: 22701 grad_norm: 5.4408 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0112 loss: 1.0112 2022/09/06 06:38:33 - mmengine - INFO - Epoch(train) [96][360/940] lr: 1.0000e-04 eta: 0:59:55 time: 0.7573 data_time: 0.0941 memory: 22701 grad_norm: 5.3997 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 0.9442 loss: 0.9442 2022/09/06 06:38:51 - mmengine - INFO - Epoch(train) [96][380/940] lr: 1.0000e-04 eta: 0:59:39 time: 0.9348 data_time: 0.2849 memory: 22701 grad_norm: 5.3721 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 0.9888 loss: 0.9888 2022/09/06 06:39:06 - mmengine - INFO - Epoch(train) [96][400/940] lr: 1.0000e-04 eta: 0:59:22 time: 0.7165 data_time: 0.2531 memory: 22701 grad_norm: 5.4252 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9856 loss: 0.9856 2022/09/06 06:39:22 - mmengine - INFO - Epoch(train) [96][420/940] lr: 1.0000e-04 eta: 0:59:05 time: 0.7894 data_time: 0.2180 memory: 22701 grad_norm: 5.3839 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 0.9957 loss: 0.9957 2022/09/06 06:39:36 - mmengine - INFO - Epoch(train) [96][440/940] lr: 1.0000e-04 eta: 0:58:49 time: 0.7443 data_time: 0.2191 memory: 22701 grad_norm: 5.4170 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0158 loss: 1.0158 2022/09/06 06:39:54 - mmengine - INFO - Epoch(train) [96][460/940] lr: 1.0000e-04 eta: 0:58:32 time: 0.8704 data_time: 0.4178 memory: 22701 grad_norm: 5.4393 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1140 loss: 1.1140 2022/09/06 06:40:07 - mmengine - INFO - Epoch(train) [96][480/940] lr: 1.0000e-04 eta: 0:58:15 time: 0.6452 data_time: 0.2467 memory: 22701 grad_norm: 5.3993 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9977 loss: 0.9977 2022/09/06 06:40:23 - mmengine - INFO - Epoch(train) [96][500/940] lr: 1.0000e-04 eta: 0:57:59 time: 0.8189 data_time: 0.3317 memory: 22701 grad_norm: 5.2650 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 0.9411 loss: 0.9411 2022/09/06 06:40:38 - mmengine - INFO - Epoch(train) [96][520/940] lr: 1.0000e-04 eta: 0:57:42 time: 0.7214 data_time: 0.2524 memory: 22701 grad_norm: 5.4231 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0039 loss: 1.0039 2022/09/06 06:40:56 - mmengine - INFO - Epoch(train) [96][540/940] lr: 1.0000e-04 eta: 0:57:26 time: 0.9315 data_time: 0.4978 memory: 22701 grad_norm: 5.3933 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0416 loss: 1.0416 2022/09/06 06:41:12 - mmengine - INFO - Epoch(train) [96][560/940] lr: 1.0000e-04 eta: 0:57:09 time: 0.7697 data_time: 0.3757 memory: 22701 grad_norm: 5.2708 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9705 loss: 0.9705 2022/09/06 06:41:31 - mmengine - INFO - Epoch(train) [96][580/940] lr: 1.0000e-04 eta: 0:56:53 time: 0.9578 data_time: 0.5596 memory: 22701 grad_norm: 5.3487 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.9222 loss: 0.9222 2022/09/06 06:41:46 - mmengine - INFO - Epoch(train) [96][600/940] lr: 1.0000e-04 eta: 0:56:36 time: 0.7531 data_time: 0.3508 memory: 22701 grad_norm: 5.4073 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9755 loss: 0.9755 2022/09/06 06:42:03 - mmengine - INFO - Epoch(train) [96][620/940] lr: 1.0000e-04 eta: 0:56:19 time: 0.8469 data_time: 0.4406 memory: 22701 grad_norm: 5.4017 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9608 loss: 0.9608 2022/09/06 06:42:17 - mmengine - INFO - Epoch(train) [96][640/940] lr: 1.0000e-04 eta: 0:56:03 time: 0.6979 data_time: 0.3081 memory: 22701 grad_norm: 5.3509 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9730 loss: 0.9730 2022/09/06 06:42:37 - mmengine - INFO - Epoch(train) [96][660/940] lr: 1.0000e-04 eta: 0:55:46 time: 1.0173 data_time: 0.5931 memory: 22701 grad_norm: 5.3844 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9763 loss: 0.9763 2022/09/06 06:42:52 - mmengine - INFO - Epoch(train) [96][680/940] lr: 1.0000e-04 eta: 0:55:30 time: 0.7316 data_time: 0.3495 memory: 22701 grad_norm: 5.4278 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8733 loss: 0.8733 2022/09/06 06:43:11 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:43:11 - mmengine - INFO - Epoch(train) [96][700/940] lr: 1.0000e-04 eta: 0:55:13 time: 0.9747 data_time: 0.5495 memory: 22701 grad_norm: 5.4263 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9760 loss: 0.9760 2022/09/06 06:43:27 - mmengine - INFO - Epoch(train) [96][720/940] lr: 1.0000e-04 eta: 0:54:57 time: 0.8027 data_time: 0.3293 memory: 22701 grad_norm: 5.3126 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8744 loss: 0.8744 2022/09/06 06:43:44 - mmengine - INFO - Epoch(train) [96][740/940] lr: 1.0000e-04 eta: 0:54:40 time: 0.8186 data_time: 0.3800 memory: 22701 grad_norm: 5.3845 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9435 loss: 0.9435 2022/09/06 06:44:01 - mmengine - INFO - Epoch(train) [96][760/940] lr: 1.0000e-04 eta: 0:54:23 time: 0.8509 data_time: 0.0790 memory: 22701 grad_norm: 5.3983 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9735 loss: 0.9735 2022/09/06 06:44:23 - mmengine - INFO - Epoch(train) [96][780/940] lr: 1.0000e-04 eta: 0:54:07 time: 1.1371 data_time: 0.2636 memory: 22701 grad_norm: 5.1976 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8604 loss: 0.8604 2022/09/06 06:44:43 - mmengine - INFO - Epoch(train) [96][800/940] lr: 1.0000e-04 eta: 0:53:51 time: 0.9749 data_time: 0.1547 memory: 22701 grad_norm: 5.3415 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.8900 loss: 0.8900 2022/09/06 06:45:03 - mmengine - INFO - Epoch(train) [96][820/940] lr: 1.0000e-04 eta: 0:53:34 time: 0.9929 data_time: 0.0352 memory: 22701 grad_norm: 5.3544 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9840 loss: 0.9840 2022/09/06 06:45:17 - mmengine - INFO - Epoch(train) [96][840/940] lr: 1.0000e-04 eta: 0:53:18 time: 0.7144 data_time: 0.0199 memory: 22701 grad_norm: 5.4229 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9869 loss: 0.9869 2022/09/06 06:45:33 - mmengine - INFO - Epoch(train) [96][860/940] lr: 1.0000e-04 eta: 0:53:01 time: 0.7848 data_time: 0.0303 memory: 22701 grad_norm: 5.4067 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9496 loss: 0.9496 2022/09/06 06:45:48 - mmengine - INFO - Epoch(train) [96][880/940] lr: 1.0000e-04 eta: 0:52:44 time: 0.7575 data_time: 0.0254 memory: 22701 grad_norm: 5.3150 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 0.9236 loss: 0.9236 2022/09/06 06:46:06 - mmengine - INFO - Epoch(train) [96][900/940] lr: 1.0000e-04 eta: 0:52:28 time: 0.8962 data_time: 0.1155 memory: 22701 grad_norm: 5.2741 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9145 loss: 0.9145 2022/09/06 06:46:22 - mmengine - INFO - Epoch(train) [96][920/940] lr: 1.0000e-04 eta: 0:52:11 time: 0.7943 data_time: 0.0344 memory: 22701 grad_norm: 5.3337 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0156 loss: 1.0156 2022/09/06 06:46:38 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:46:38 - mmengine - INFO - Epoch(train) [96][940/940] lr: 1.0000e-04 eta: 0:51:55 time: 0.8259 data_time: 0.0259 memory: 22701 grad_norm: 5.8658 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 1.0282 loss: 1.0282 2022/09/06 06:46:38 - mmengine - INFO - Saving checkpoint at 96 epochs 2022/09/06 06:46:54 - mmengine - INFO - Epoch(val) [96][20/78] eta: 0:00:40 time: 0.6969 data_time: 0.5800 memory: 2247 2022/09/06 06:47:03 - mmengine - INFO - Epoch(val) [96][40/78] eta: 0:00:17 time: 0.4488 data_time: 0.3344 memory: 2247 2022/09/06 06:47:16 - mmengine - INFO - Epoch(val) [96][60/78] eta: 0:00:11 time: 0.6508 data_time: 0.5347 memory: 2247 2022/09/06 06:47:26 - mmengine - INFO - Epoch(val) [96][78/78] acc/top1: 0.6895 acc/top5: 0.8801 acc/mean1: 0.6894 2022/09/06 06:47:47 - mmengine - INFO - Epoch(train) [97][20/940] lr: 1.0000e-04 eta: 0:51:38 time: 1.0401 data_time: 0.4538 memory: 22701 grad_norm: 5.2854 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.8262 loss: 0.8262 2022/09/06 06:48:00 - mmengine - INFO - Epoch(train) [97][40/940] lr: 1.0000e-04 eta: 0:51:22 time: 0.6838 data_time: 0.1052 memory: 22701 grad_norm: 5.3686 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0306 loss: 1.0306 2022/09/06 06:48:17 - mmengine - INFO - Epoch(train) [97][60/940] lr: 1.0000e-04 eta: 0:51:05 time: 0.8479 data_time: 0.1571 memory: 22701 grad_norm: 5.4152 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.8517 loss: 0.8517 2022/09/06 06:48:31 - mmengine - INFO - Epoch(train) [97][80/940] lr: 1.0000e-04 eta: 0:50:48 time: 0.6871 data_time: 0.0308 memory: 22701 grad_norm: 5.3278 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.9747 loss: 0.9747 2022/09/06 06:48:48 - mmengine - INFO - Epoch(train) [97][100/940] lr: 1.0000e-04 eta: 0:50:32 time: 0.8614 data_time: 0.0848 memory: 22701 grad_norm: 5.4447 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9646 loss: 0.9646 2022/09/06 06:49:03 - mmengine - INFO - Epoch(train) [97][120/940] lr: 1.0000e-04 eta: 0:50:15 time: 0.7475 data_time: 0.1247 memory: 22701 grad_norm: 5.4237 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0150 loss: 1.0150 2022/09/06 06:49:23 - mmengine - INFO - Epoch(train) [97][140/940] lr: 1.0000e-04 eta: 0:49:59 time: 1.0020 data_time: 0.0882 memory: 22701 grad_norm: 5.2907 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.8864 loss: 0.8864 2022/09/06 06:49:40 - mmengine - INFO - Epoch(train) [97][160/940] lr: 1.0000e-04 eta: 0:49:42 time: 0.8381 data_time: 0.0238 memory: 22701 grad_norm: 5.3915 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9626 loss: 0.9626 2022/09/06 06:50:03 - mmengine - INFO - Epoch(train) [97][180/940] lr: 1.0000e-04 eta: 0:49:26 time: 1.1373 data_time: 0.1055 memory: 22701 grad_norm: 5.3861 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8993 loss: 0.8993 2022/09/06 06:50:23 - mmengine - INFO - Epoch(train) [97][200/940] lr: 1.0000e-04 eta: 0:49:09 time: 0.9867 data_time: 0.0252 memory: 22701 grad_norm: 5.3857 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 0.9706 loss: 0.9706 2022/09/06 06:50:43 - mmengine - INFO - Epoch(train) [97][220/940] lr: 1.0000e-04 eta: 0:48:53 time: 0.9976 data_time: 0.5814 memory: 22701 grad_norm: 5.3897 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9174 loss: 0.9174 2022/09/06 06:50:57 - mmengine - INFO - Epoch(train) [97][240/940] lr: 1.0000e-04 eta: 0:48:36 time: 0.7167 data_time: 0.3258 memory: 22701 grad_norm: 5.4209 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 0.9691 loss: 0.9691 2022/09/06 06:51:18 - mmengine - INFO - Epoch(train) [97][260/940] lr: 1.0000e-04 eta: 0:48:20 time: 1.0342 data_time: 0.4408 memory: 22701 grad_norm: 5.3905 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.9004 loss: 0.9004 2022/09/06 06:51:36 - mmengine - INFO - Epoch(train) [97][280/940] lr: 1.0000e-04 eta: 0:48:03 time: 0.9223 data_time: 0.2962 memory: 22701 grad_norm: 5.4135 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9118 loss: 0.9118 2022/09/06 06:51:56 - mmengine - INFO - Epoch(train) [97][300/940] lr: 1.0000e-04 eta: 0:47:47 time: 0.9963 data_time: 0.0661 memory: 22701 grad_norm: 5.3538 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0012 loss: 1.0012 2022/09/06 06:52:12 - mmengine - INFO - Epoch(train) [97][320/940] lr: 1.0000e-04 eta: 0:47:30 time: 0.7797 data_time: 0.0243 memory: 22701 grad_norm: 5.3211 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9867 loss: 0.9867 2022/09/06 06:52:30 - mmengine - INFO - Epoch(train) [97][340/940] lr: 1.0000e-04 eta: 0:47:14 time: 0.9406 data_time: 0.0256 memory: 22701 grad_norm: 5.4616 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 0.9278 loss: 0.9278 2022/09/06 06:52:45 - mmengine - INFO - Epoch(train) [97][360/940] lr: 1.0000e-04 eta: 0:46:57 time: 0.7227 data_time: 0.0266 memory: 22701 grad_norm: 5.3662 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8856 loss: 0.8856 2022/09/06 06:53:02 - mmengine - INFO - Epoch(train) [97][380/940] lr: 1.0000e-04 eta: 0:46:41 time: 0.8745 data_time: 0.0263 memory: 22701 grad_norm: 5.4051 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8936 loss: 0.8936 2022/09/06 06:53:17 - mmengine - INFO - Epoch(train) [97][400/940] lr: 1.0000e-04 eta: 0:46:24 time: 0.7210 data_time: 0.0222 memory: 22701 grad_norm: 5.5059 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0633 loss: 1.0633 2022/09/06 06:53:36 - mmengine - INFO - Epoch(train) [97][420/940] lr: 1.0000e-04 eta: 0:46:08 time: 0.9687 data_time: 0.0260 memory: 22701 grad_norm: 5.4539 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8553 loss: 0.8553 2022/09/06 06:53:50 - mmengine - INFO - Epoch(train) [97][440/940] lr: 1.0000e-04 eta: 0:45:51 time: 0.6962 data_time: 0.0253 memory: 22701 grad_norm: 5.2885 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9618 loss: 0.9618 2022/09/06 06:54:08 - mmengine - INFO - Epoch(train) [97][460/940] lr: 1.0000e-04 eta: 0:45:34 time: 0.8980 data_time: 0.0274 memory: 22701 grad_norm: 5.3195 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9517 loss: 0.9517 2022/09/06 06:54:22 - mmengine - INFO - Epoch(train) [97][480/940] lr: 1.0000e-04 eta: 0:45:18 time: 0.7195 data_time: 0.0240 memory: 22701 grad_norm: 5.4100 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9851 loss: 0.9851 2022/09/06 06:54:40 - mmengine - INFO - Epoch(train) [97][500/940] lr: 1.0000e-04 eta: 0:45:01 time: 0.8860 data_time: 0.0299 memory: 22701 grad_norm: 5.3518 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 0.9779 loss: 0.9779 2022/09/06 06:54:55 - mmengine - INFO - Epoch(train) [97][520/940] lr: 1.0000e-04 eta: 0:44:45 time: 0.7472 data_time: 0.0279 memory: 22701 grad_norm: 5.3089 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9020 loss: 0.9020 2022/09/06 06:55:16 - mmengine - INFO - Epoch(train) [97][540/940] lr: 1.0000e-04 eta: 0:44:28 time: 1.0367 data_time: 0.0307 memory: 22701 grad_norm: 5.4290 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0335 loss: 1.0335 2022/09/06 06:55:32 - mmengine - INFO - Epoch(train) [97][560/940] lr: 1.0000e-04 eta: 0:44:11 time: 0.7828 data_time: 0.0290 memory: 22701 grad_norm: 5.2900 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0162 loss: 1.0162 2022/09/06 06:55:52 - mmengine - INFO - Epoch(train) [97][580/940] lr: 1.0000e-04 eta: 0:43:55 time: 1.0083 data_time: 0.0245 memory: 22701 grad_norm: 5.4351 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0316 loss: 1.0316 2022/09/06 06:56:09 - mmengine - INFO - Epoch(train) [97][600/940] lr: 1.0000e-04 eta: 0:43:38 time: 0.8641 data_time: 0.0209 memory: 22701 grad_norm: 5.3118 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.8430 loss: 0.8430 2022/09/06 06:56:29 - mmengine - INFO - Epoch(train) [97][620/940] lr: 1.0000e-04 eta: 0:43:22 time: 0.9966 data_time: 0.0236 memory: 22701 grad_norm: 5.4090 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9042 loss: 0.9042 2022/09/06 06:56:44 - mmengine - INFO - Epoch(train) [97][640/940] lr: 1.0000e-04 eta: 0:43:05 time: 0.7622 data_time: 0.0275 memory: 22701 grad_norm: 5.4067 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9647 loss: 0.9647 2022/09/06 06:57:00 - mmengine - INFO - Epoch(train) [97][660/940] lr: 1.0000e-04 eta: 0:42:49 time: 0.7746 data_time: 0.0310 memory: 22701 grad_norm: 5.4080 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 0.8861 loss: 0.8861 2022/09/06 06:57:14 - mmengine - INFO - Epoch(train) [97][680/940] lr: 1.0000e-04 eta: 0:42:32 time: 0.7254 data_time: 0.0287 memory: 22701 grad_norm: 5.4419 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9567 loss: 0.9567 2022/09/06 06:57:32 - mmengine - INFO - Epoch(train) [97][700/940] lr: 1.0000e-04 eta: 0:42:16 time: 0.9056 data_time: 0.0247 memory: 22701 grad_norm: 5.4478 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0255 loss: 1.0255 2022/09/06 06:57:49 - mmengine - INFO - Epoch(train) [97][720/940] lr: 1.0000e-04 eta: 0:41:59 time: 0.8478 data_time: 0.0507 memory: 22701 grad_norm: 5.2769 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 0.9654 loss: 0.9654 2022/09/06 06:58:11 - mmengine - INFO - Epoch(train) [97][740/940] lr: 1.0000e-04 eta: 0:41:43 time: 1.1103 data_time: 0.0303 memory: 22701 grad_norm: 5.3785 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0082 loss: 1.0082 2022/09/06 06:58:27 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 06:58:27 - mmengine - INFO - Epoch(train) [97][760/940] lr: 1.0000e-04 eta: 0:41:26 time: 0.7854 data_time: 0.0193 memory: 22701 grad_norm: 5.2921 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0286 loss: 1.0286 2022/09/06 06:58:49 - mmengine - INFO - Epoch(train) [97][780/940] lr: 1.0000e-04 eta: 0:41:10 time: 1.0677 data_time: 0.0307 memory: 22701 grad_norm: 5.3672 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9917 loss: 0.9917 2022/09/06 06:59:05 - mmengine - INFO - Epoch(train) [97][800/940] lr: 1.0000e-04 eta: 0:40:53 time: 0.8304 data_time: 0.0257 memory: 22701 grad_norm: 5.3836 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8494 loss: 0.8494 2022/09/06 06:59:27 - mmengine - INFO - Epoch(train) [97][820/940] lr: 1.0000e-04 eta: 0:40:37 time: 1.0942 data_time: 0.0230 memory: 22701 grad_norm: 5.3177 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8353 loss: 0.8353 2022/09/06 06:59:46 - mmengine - INFO - Epoch(train) [97][840/940] lr: 1.0000e-04 eta: 0:40:20 time: 0.9565 data_time: 0.0806 memory: 22701 grad_norm: 5.3383 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9028 loss: 0.9028 2022/09/06 07:00:09 - mmengine - INFO - Epoch(train) [97][860/940] lr: 1.0000e-04 eta: 0:40:04 time: 1.1250 data_time: 0.0184 memory: 22701 grad_norm: 5.4200 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0516 loss: 1.0516 2022/09/06 07:00:26 - mmengine - INFO - Epoch(train) [97][880/940] lr: 1.0000e-04 eta: 0:39:47 time: 0.8514 data_time: 0.0256 memory: 22701 grad_norm: 5.3908 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9690 loss: 0.9690 2022/09/06 07:00:49 - mmengine - INFO - Epoch(train) [97][900/940] lr: 1.0000e-04 eta: 0:39:31 time: 1.1338 data_time: 0.0182 memory: 22701 grad_norm: 5.4066 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9816 loss: 0.9816 2022/09/06 07:01:02 - mmengine - INFO - Epoch(train) [97][920/940] lr: 1.0000e-04 eta: 0:39:14 time: 0.7023 data_time: 0.0295 memory: 22701 grad_norm: 5.3806 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0456 loss: 1.0456 2022/09/06 07:01:22 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 07:01:23 - mmengine - INFO - Epoch(train) [97][940/940] lr: 1.0000e-04 eta: 0:38:58 time: 1.0008 data_time: 0.0196 memory: 22701 grad_norm: 5.7734 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 0.9817 loss: 0.9817 2022/09/06 07:01:37 - mmengine - INFO - Epoch(val) [97][20/78] eta: 0:00:41 time: 0.7072 data_time: 0.5810 memory: 2247 2022/09/06 07:01:45 - mmengine - INFO - Epoch(val) [97][40/78] eta: 0:00:16 time: 0.4290 data_time: 0.3121 memory: 2247 2022/09/06 07:01:58 - mmengine - INFO - Epoch(val) [97][60/78] eta: 0:00:11 time: 0.6542 data_time: 0.5360 memory: 2247 2022/09/06 07:02:09 - mmengine - INFO - Epoch(val) [97][78/78] acc/top1: 0.6895 acc/top5: 0.8799 acc/mean1: 0.6894 2022/09/06 07:02:31 - mmengine - INFO - Epoch(train) [98][20/940] lr: 1.0000e-04 eta: 0:38:41 time: 1.1062 data_time: 0.6480 memory: 22701 grad_norm: 5.3473 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0249 loss: 1.0249 2022/09/06 07:02:47 - mmengine - INFO - Epoch(train) [98][40/940] lr: 1.0000e-04 eta: 0:38:25 time: 0.8223 data_time: 0.3385 memory: 22701 grad_norm: 5.2580 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.7838 loss: 0.7838 2022/09/06 07:03:09 - mmengine - INFO - Epoch(train) [98][60/940] lr: 1.0000e-04 eta: 0:38:08 time: 1.1127 data_time: 0.3462 memory: 22701 grad_norm: 5.4516 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.8953 loss: 0.8953 2022/09/06 07:03:26 - mmengine - INFO - Epoch(train) [98][80/940] lr: 1.0000e-04 eta: 0:37:52 time: 0.8209 data_time: 0.2239 memory: 22701 grad_norm: 5.4267 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8908 loss: 0.8908 2022/09/06 07:03:48 - mmengine - INFO - Epoch(train) [98][100/940] lr: 1.0000e-04 eta: 0:37:35 time: 1.1219 data_time: 0.4033 memory: 22701 grad_norm: 5.4375 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9952 loss: 0.9952 2022/09/06 07:04:06 - mmengine - INFO - Epoch(train) [98][120/940] lr: 1.0000e-04 eta: 0:37:19 time: 0.8737 data_time: 0.1721 memory: 22701 grad_norm: 5.4229 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.9131 loss: 0.9131 2022/09/06 07:04:30 - mmengine - INFO - Epoch(train) [98][140/940] lr: 1.0000e-04 eta: 0:37:02 time: 1.2153 data_time: 0.2428 memory: 22701 grad_norm: 5.3463 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9546 loss: 0.9546 2022/09/06 07:04:48 - mmengine - INFO - Epoch(train) [98][160/940] lr: 1.0000e-04 eta: 0:36:46 time: 0.8797 data_time: 0.0534 memory: 22701 grad_norm: 5.3445 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8648 loss: 0.8648 2022/09/06 07:05:08 - mmengine - INFO - Epoch(train) [98][180/940] lr: 1.0000e-04 eta: 0:36:29 time: 1.0238 data_time: 0.0243 memory: 22701 grad_norm: 5.4216 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9387 loss: 0.9387 2022/09/06 07:05:25 - mmengine - INFO - Epoch(train) [98][200/940] lr: 1.0000e-04 eta: 0:36:13 time: 0.8476 data_time: 0.0209 memory: 22701 grad_norm: 5.4133 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9729 loss: 0.9729 2022/09/06 07:05:44 - mmengine - INFO - Epoch(train) [98][220/940] lr: 1.0000e-04 eta: 0:35:56 time: 0.9662 data_time: 0.0230 memory: 22701 grad_norm: 5.5309 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9704 loss: 0.9704 2022/09/06 07:05:59 - mmengine - INFO - Epoch(train) [98][240/940] lr: 1.0000e-04 eta: 0:35:40 time: 0.7381 data_time: 0.0288 memory: 22701 grad_norm: 5.3249 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.8512 loss: 0.8512 2022/09/06 07:06:20 - mmengine - INFO - Epoch(train) [98][260/940] lr: 1.0000e-04 eta: 0:35:23 time: 1.0431 data_time: 0.0279 memory: 22701 grad_norm: 5.3845 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9783 loss: 0.9783 2022/09/06 07:06:37 - mmengine - INFO - Epoch(train) [98][280/940] lr: 1.0000e-04 eta: 0:35:07 time: 0.8543 data_time: 0.0212 memory: 22701 grad_norm: 5.3871 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 0.9527 loss: 0.9527 2022/09/06 07:06:59 - mmengine - INFO - Epoch(train) [98][300/940] lr: 1.0000e-04 eta: 0:34:50 time: 1.1076 data_time: 0.0234 memory: 22701 grad_norm: 5.4062 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 0.9340 loss: 0.9340 2022/09/06 07:07:15 - mmengine - INFO - Epoch(train) [98][320/940] lr: 1.0000e-04 eta: 0:34:33 time: 0.8038 data_time: 0.0239 memory: 22701 grad_norm: 5.3981 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0741 loss: 1.0741 2022/09/06 07:07:38 - mmengine - INFO - Epoch(train) [98][340/940] lr: 1.0000e-04 eta: 0:34:17 time: 1.1395 data_time: 0.0251 memory: 22701 grad_norm: 5.3699 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.9486 loss: 0.9486 2022/09/06 07:07:52 - mmengine - INFO - Epoch(train) [98][360/940] lr: 1.0000e-04 eta: 0:34:00 time: 0.7031 data_time: 0.0371 memory: 22701 grad_norm: 5.4875 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9926 loss: 0.9926 2022/09/06 07:08:11 - mmengine - INFO - Epoch(train) [98][380/940] lr: 1.0000e-04 eta: 0:33:44 time: 0.9537 data_time: 0.0278 memory: 22701 grad_norm: 5.5014 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1114 loss: 1.1114 2022/09/06 07:08:28 - mmengine - INFO - Epoch(train) [98][400/940] lr: 1.0000e-04 eta: 0:33:27 time: 0.8490 data_time: 0.0435 memory: 22701 grad_norm: 5.2688 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8732 loss: 0.8732 2022/09/06 07:08:47 - mmengine - INFO - Epoch(train) [98][420/940] lr: 1.0000e-04 eta: 0:33:11 time: 0.9232 data_time: 0.0316 memory: 22701 grad_norm: 5.4535 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 0.9545 loss: 0.9545 2022/09/06 07:09:00 - mmengine - INFO - Epoch(train) [98][440/940] lr: 1.0000e-04 eta: 0:32:54 time: 0.6490 data_time: 0.0272 memory: 22701 grad_norm: 5.4515 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9709 loss: 0.9709 2022/09/06 07:09:17 - mmengine - INFO - Epoch(train) [98][460/940] lr: 1.0000e-04 eta: 0:32:37 time: 0.8649 data_time: 0.0304 memory: 22701 grad_norm: 5.4103 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 0.9399 loss: 0.9399 2022/09/06 07:09:33 - mmengine - INFO - Epoch(train) [98][480/940] lr: 1.0000e-04 eta: 0:32:21 time: 0.7820 data_time: 0.0243 memory: 22701 grad_norm: 5.4189 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9861 loss: 0.9861 2022/09/06 07:09:51 - mmengine - INFO - Epoch(train) [98][500/940] lr: 1.0000e-04 eta: 0:32:04 time: 0.9140 data_time: 0.0270 memory: 22701 grad_norm: 5.3857 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9566 loss: 0.9566 2022/09/06 07:10:04 - mmengine - INFO - Epoch(train) [98][520/940] lr: 1.0000e-04 eta: 0:31:48 time: 0.6543 data_time: 0.0247 memory: 22701 grad_norm: 5.3369 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0225 loss: 1.0225 2022/09/06 07:10:22 - mmengine - INFO - Epoch(train) [98][540/940] lr: 1.0000e-04 eta: 0:31:31 time: 0.8942 data_time: 0.0317 memory: 22701 grad_norm: 5.3627 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8360 loss: 0.8360 2022/09/06 07:10:38 - mmengine - INFO - Epoch(train) [98][560/940] lr: 1.0000e-04 eta: 0:31:14 time: 0.7831 data_time: 0.1328 memory: 22701 grad_norm: 5.3532 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0091 loss: 1.0091 2022/09/06 07:10:55 - mmengine - INFO - Epoch(train) [98][580/940] lr: 1.0000e-04 eta: 0:30:58 time: 0.8623 data_time: 0.1427 memory: 22701 grad_norm: 5.2834 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9019 loss: 0.9019 2022/09/06 07:11:12 - mmengine - INFO - Epoch(train) [98][600/940] lr: 1.0000e-04 eta: 0:30:41 time: 0.8504 data_time: 0.2150 memory: 22701 grad_norm: 5.3696 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0178 loss: 1.0178 2022/09/06 07:11:32 - mmengine - INFO - Epoch(train) [98][620/940] lr: 1.0000e-04 eta: 0:30:25 time: 0.9805 data_time: 0.1039 memory: 22701 grad_norm: 5.5299 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9744 loss: 0.9744 2022/09/06 07:11:46 - mmengine - INFO - Epoch(train) [98][640/940] lr: 1.0000e-04 eta: 0:30:08 time: 0.7093 data_time: 0.0915 memory: 22701 grad_norm: 5.3291 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9132 loss: 0.9132 2022/09/06 07:12:04 - mmengine - INFO - Epoch(train) [98][660/940] lr: 1.0000e-04 eta: 0:29:52 time: 0.8901 data_time: 0.1819 memory: 22701 grad_norm: 5.4434 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9596 loss: 0.9596 2022/09/06 07:12:20 - mmengine - INFO - Epoch(train) [98][680/940] lr: 1.0000e-04 eta: 0:29:35 time: 0.7993 data_time: 0.3114 memory: 22701 grad_norm: 5.3586 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9228 loss: 0.9228 2022/09/06 07:12:35 - mmengine - INFO - Epoch(train) [98][700/940] lr: 1.0000e-04 eta: 0:29:18 time: 0.7895 data_time: 0.2129 memory: 22701 grad_norm: 5.4513 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 0.9268 loss: 0.9268 2022/09/06 07:12:51 - mmengine - INFO - Epoch(train) [98][720/940] lr: 1.0000e-04 eta: 0:29:02 time: 0.8031 data_time: 0.1758 memory: 22701 grad_norm: 5.4338 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9997 loss: 0.9997 2022/09/06 07:13:09 - mmengine - INFO - Epoch(train) [98][740/940] lr: 1.0000e-04 eta: 0:28:45 time: 0.8921 data_time: 0.0486 memory: 22701 grad_norm: 5.4403 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9806 loss: 0.9806 2022/09/06 07:13:24 - mmengine - INFO - Epoch(train) [98][760/940] lr: 1.0000e-04 eta: 0:28:29 time: 0.7534 data_time: 0.0382 memory: 22701 grad_norm: 5.4752 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0064 loss: 1.0064 2022/09/06 07:13:45 - mmengine - INFO - Epoch(train) [98][780/940] lr: 1.0000e-04 eta: 0:28:12 time: 1.0109 data_time: 0.0264 memory: 22701 grad_norm: 5.3641 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9574 loss: 0.9574 2022/09/06 07:14:03 - mmengine - INFO - Epoch(train) [98][800/940] lr: 1.0000e-04 eta: 0:27:55 time: 0.9347 data_time: 0.0245 memory: 22701 grad_norm: 5.3841 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.9114 loss: 0.9114 2022/09/06 07:14:23 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 07:14:23 - mmengine - INFO - Epoch(train) [98][820/940] lr: 1.0000e-04 eta: 0:27:39 time: 1.0078 data_time: 0.0247 memory: 22701 grad_norm: 5.5022 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9553 loss: 0.9553 2022/09/06 07:14:41 - mmengine - INFO - Epoch(train) [98][840/940] lr: 1.0000e-04 eta: 0:27:22 time: 0.8730 data_time: 0.0262 memory: 22701 grad_norm: 5.4382 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9758 loss: 0.9758 2022/09/06 07:14:58 - mmengine - INFO - Epoch(train) [98][860/940] lr: 1.0000e-04 eta: 0:27:06 time: 0.8425 data_time: 0.0229 memory: 22701 grad_norm: 5.4393 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8946 loss: 0.8946 2022/09/06 07:15:15 - mmengine - INFO - Epoch(train) [98][880/940] lr: 1.0000e-04 eta: 0:26:49 time: 0.8838 data_time: 0.0268 memory: 22701 grad_norm: 5.3677 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9018 loss: 0.9018 2022/09/06 07:15:32 - mmengine - INFO - Epoch(train) [98][900/940] lr: 1.0000e-04 eta: 0:26:33 time: 0.8113 data_time: 0.0211 memory: 22701 grad_norm: 5.3191 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8504 loss: 0.8504 2022/09/06 07:15:50 - mmengine - INFO - Epoch(train) [98][920/940] lr: 1.0000e-04 eta: 0:26:16 time: 0.8924 data_time: 0.0284 memory: 22701 grad_norm: 5.3626 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9525 loss: 0.9525 2022/09/06 07:16:05 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 07:16:05 - mmengine - INFO - Epoch(train) [98][940/940] lr: 1.0000e-04 eta: 0:25:59 time: 0.7767 data_time: 0.0206 memory: 22701 grad_norm: 5.6899 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 0.9998 loss: 0.9998 2022/09/06 07:16:19 - mmengine - INFO - Epoch(val) [98][20/78] eta: 0:00:39 time: 0.6884 data_time: 0.5701 memory: 2247 2022/09/06 07:16:28 - mmengine - INFO - Epoch(val) [98][40/78] eta: 0:00:17 time: 0.4476 data_time: 0.3264 memory: 2247 2022/09/06 07:16:41 - mmengine - INFO - Epoch(val) [98][60/78] eta: 0:00:11 time: 0.6386 data_time: 0.5204 memory: 2247 2022/09/06 07:16:51 - mmengine - INFO - Epoch(val) [98][78/78] acc/top1: 0.6894 acc/top5: 0.8818 acc/mean1: 0.6893 2022/09/06 07:17:14 - mmengine - INFO - Epoch(train) [99][20/940] lr: 1.0000e-04 eta: 0:25:43 time: 1.1400 data_time: 0.6044 memory: 22701 grad_norm: 5.3441 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8936 loss: 0.8936 2022/09/06 07:17:30 - mmengine - INFO - Epoch(train) [99][40/940] lr: 1.0000e-04 eta: 0:25:26 time: 0.8268 data_time: 0.4303 memory: 22701 grad_norm: 5.2616 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9654 loss: 0.9654 2022/09/06 07:17:51 - mmengine - INFO - Epoch(train) [99][60/940] lr: 1.0000e-04 eta: 0:25:10 time: 1.0108 data_time: 0.5751 memory: 22701 grad_norm: 5.3800 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 0.9480 loss: 0.9480 2022/09/06 07:18:07 - mmengine - INFO - Epoch(train) [99][80/940] lr: 1.0000e-04 eta: 0:24:53 time: 0.7929 data_time: 0.2342 memory: 22701 grad_norm: 5.3835 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 0.8582 loss: 0.8582 2022/09/06 07:18:27 - mmengine - INFO - Epoch(train) [99][100/940] lr: 1.0000e-04 eta: 0:24:37 time: 1.0024 data_time: 0.3752 memory: 22701 grad_norm: 5.4651 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9622 loss: 0.9622 2022/09/06 07:18:43 - mmengine - INFO - Epoch(train) [99][120/940] lr: 1.0000e-04 eta: 0:24:20 time: 0.8271 data_time: 0.3491 memory: 22701 grad_norm: 5.3437 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9265 loss: 0.9265 2022/09/06 07:19:01 - mmengine - INFO - Epoch(train) [99][140/940] lr: 1.0000e-04 eta: 0:24:04 time: 0.8924 data_time: 0.5030 memory: 22701 grad_norm: 5.4127 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.9035 loss: 0.9035 2022/09/06 07:19:17 - mmengine - INFO - Epoch(train) [99][160/940] lr: 1.0000e-04 eta: 0:23:47 time: 0.7972 data_time: 0.3624 memory: 22701 grad_norm: 5.4917 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9542 loss: 0.9542 2022/09/06 07:19:36 - mmengine - INFO - Epoch(train) [99][180/940] lr: 1.0000e-04 eta: 0:23:30 time: 0.9246 data_time: 0.4900 memory: 22701 grad_norm: 5.2542 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8998 loss: 0.8998 2022/09/06 07:19:53 - mmengine - INFO - Epoch(train) [99][200/940] lr: 1.0000e-04 eta: 0:23:14 time: 0.8751 data_time: 0.3162 memory: 22701 grad_norm: 5.3926 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0766 loss: 1.0766 2022/09/06 07:20:16 - mmengine - INFO - Epoch(train) [99][220/940] lr: 1.0000e-04 eta: 0:22:57 time: 1.1264 data_time: 0.5586 memory: 22701 grad_norm: 5.4366 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.8593 loss: 0.8593 2022/09/06 07:20:30 - mmengine - INFO - Epoch(train) [99][240/940] lr: 1.0000e-04 eta: 0:22:41 time: 0.7391 data_time: 0.3208 memory: 22701 grad_norm: 5.4383 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9354 loss: 0.9354 2022/09/06 07:20:51 - mmengine - INFO - Epoch(train) [99][260/940] lr: 1.0000e-04 eta: 0:22:24 time: 1.0250 data_time: 0.4809 memory: 22701 grad_norm: 5.2679 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.8967 loss: 0.8967 2022/09/06 07:21:10 - mmengine - INFO - Epoch(train) [99][280/940] lr: 1.0000e-04 eta: 0:22:08 time: 0.9613 data_time: 0.3605 memory: 22701 grad_norm: 5.4524 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0161 loss: 1.0161 2022/09/06 07:21:32 - mmengine - INFO - Epoch(train) [99][300/940] lr: 1.0000e-04 eta: 0:21:51 time: 1.0696 data_time: 0.2973 memory: 22701 grad_norm: 5.4456 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9628 loss: 0.9628 2022/09/06 07:21:48 - mmengine - INFO - Epoch(train) [99][320/940] lr: 1.0000e-04 eta: 0:21:34 time: 0.8248 data_time: 0.2187 memory: 22701 grad_norm: 5.3399 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 0.9641 loss: 0.9641 2022/09/06 07:22:06 - mmengine - INFO - Epoch(train) [99][340/940] lr: 1.0000e-04 eta: 0:21:18 time: 0.9000 data_time: 0.3188 memory: 22701 grad_norm: 5.3285 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9461 loss: 0.9461 2022/09/06 07:22:23 - mmengine - INFO - Epoch(train) [99][360/940] lr: 1.0000e-04 eta: 0:21:01 time: 0.8283 data_time: 0.1904 memory: 22701 grad_norm: 5.3953 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9914 loss: 0.9914 2022/09/06 07:22:43 - mmengine - INFO - Epoch(train) [99][380/940] lr: 1.0000e-04 eta: 0:20:45 time: 1.0243 data_time: 0.0336 memory: 22701 grad_norm: 5.3876 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 0.9794 loss: 0.9794 2022/09/06 07:22:59 - mmengine - INFO - Epoch(train) [99][400/940] lr: 1.0000e-04 eta: 0:20:28 time: 0.7881 data_time: 0.0205 memory: 22701 grad_norm: 5.4504 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8440 loss: 0.8440 2022/09/06 07:23:18 - mmengine - INFO - Epoch(train) [99][420/940] lr: 1.0000e-04 eta: 0:20:12 time: 0.9636 data_time: 0.0220 memory: 22701 grad_norm: 5.3529 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 0.8370 loss: 0.8370 2022/09/06 07:23:34 - mmengine - INFO - Epoch(train) [99][440/940] lr: 1.0000e-04 eta: 0:19:55 time: 0.8183 data_time: 0.0274 memory: 22701 grad_norm: 5.4772 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 0.9394 loss: 0.9394 2022/09/06 07:23:52 - mmengine - INFO - Epoch(train) [99][460/940] lr: 1.0000e-04 eta: 0:19:38 time: 0.8755 data_time: 0.0245 memory: 22701 grad_norm: 5.4088 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9379 loss: 0.9379 2022/09/06 07:24:08 - mmengine - INFO - Epoch(train) [99][480/940] lr: 1.0000e-04 eta: 0:19:22 time: 0.7900 data_time: 0.0370 memory: 22701 grad_norm: 5.4731 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0525 loss: 1.0525 2022/09/06 07:24:27 - mmengine - INFO - Epoch(train) [99][500/940] lr: 1.0000e-04 eta: 0:19:05 time: 0.9516 data_time: 0.0230 memory: 22701 grad_norm: 5.4093 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0009 loss: 1.0009 2022/09/06 07:24:41 - mmengine - INFO - Epoch(train) [99][520/940] lr: 1.0000e-04 eta: 0:18:49 time: 0.7047 data_time: 0.0351 memory: 22701 grad_norm: 5.4589 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0258 loss: 1.0258 2022/09/06 07:24:57 - mmengine - INFO - Epoch(train) [99][540/940] lr: 1.0000e-04 eta: 0:18:32 time: 0.7881 data_time: 0.0436 memory: 22701 grad_norm: 5.4704 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9254 loss: 0.9254 2022/09/06 07:25:12 - mmengine - INFO - Epoch(train) [99][560/940] lr: 1.0000e-04 eta: 0:18:15 time: 0.7763 data_time: 0.0816 memory: 22701 grad_norm: 5.3355 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.8436 loss: 0.8436 2022/09/06 07:25:29 - mmengine - INFO - Epoch(train) [99][580/940] lr: 1.0000e-04 eta: 0:17:59 time: 0.8516 data_time: 0.0231 memory: 22701 grad_norm: 5.4627 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9353 loss: 0.9353 2022/09/06 07:25:46 - mmengine - INFO - Epoch(train) [99][600/940] lr: 1.0000e-04 eta: 0:17:42 time: 0.8539 data_time: 0.0271 memory: 22701 grad_norm: 5.4324 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9916 loss: 0.9916 2022/09/06 07:26:05 - mmengine - INFO - Epoch(train) [99][620/940] lr: 1.0000e-04 eta: 0:17:26 time: 0.9139 data_time: 0.0176 memory: 22701 grad_norm: 5.4276 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9369 loss: 0.9369 2022/09/06 07:26:23 - mmengine - INFO - Epoch(train) [99][640/940] lr: 1.0000e-04 eta: 0:17:09 time: 0.9306 data_time: 0.0251 memory: 22701 grad_norm: 5.4480 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0456 loss: 1.0456 2022/09/06 07:26:36 - mmengine - INFO - Epoch(train) [99][660/940] lr: 1.0000e-04 eta: 0:16:52 time: 0.6492 data_time: 0.0323 memory: 22701 grad_norm: 5.3836 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 0.9748 loss: 0.9748 2022/09/06 07:26:54 - mmengine - INFO - Epoch(train) [99][680/940] lr: 1.0000e-04 eta: 0:16:36 time: 0.8947 data_time: 0.0261 memory: 22701 grad_norm: 5.4451 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0581 loss: 1.0581 2022/09/06 07:27:09 - mmengine - INFO - Epoch(train) [99][700/940] lr: 1.0000e-04 eta: 0:16:19 time: 0.7474 data_time: 0.0293 memory: 22701 grad_norm: 5.3696 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 0.9115 loss: 0.9115 2022/09/06 07:27:27 - mmengine - INFO - Epoch(train) [99][720/940] lr: 1.0000e-04 eta: 0:16:02 time: 0.8945 data_time: 0.0333 memory: 22701 grad_norm: 5.4722 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0062 loss: 1.0062 2022/09/06 07:27:41 - mmengine - INFO - Epoch(train) [99][740/940] lr: 1.0000e-04 eta: 0:15:46 time: 0.7080 data_time: 0.0214 memory: 22701 grad_norm: 5.3996 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9994 loss: 0.9994 2022/09/06 07:27:58 - mmengine - INFO - Epoch(train) [99][760/940] lr: 1.0000e-04 eta: 0:15:29 time: 0.8589 data_time: 0.0276 memory: 22701 grad_norm: 5.2067 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8432 loss: 0.8432 2022/09/06 07:28:15 - mmengine - INFO - Epoch(train) [99][780/940] lr: 1.0000e-04 eta: 0:15:13 time: 0.8247 data_time: 0.0353 memory: 22701 grad_norm: 5.4034 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9597 loss: 0.9597 2022/09/06 07:28:33 - mmengine - INFO - Epoch(train) [99][800/940] lr: 1.0000e-04 eta: 0:14:56 time: 0.9070 data_time: 0.0238 memory: 22701 grad_norm: 5.4539 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9690 loss: 0.9690 2022/09/06 07:28:49 - mmengine - INFO - Epoch(train) [99][820/940] lr: 1.0000e-04 eta: 0:14:39 time: 0.7853 data_time: 0.0220 memory: 22701 grad_norm: 5.2566 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.8960 loss: 0.8960 2022/09/06 07:29:07 - mmengine - INFO - Epoch(train) [99][840/940] lr: 1.0000e-04 eta: 0:14:23 time: 0.9081 data_time: 0.0251 memory: 22701 grad_norm: 5.4718 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9627 loss: 0.9627 2022/09/06 07:29:23 - mmengine - INFO - Epoch(train) [99][860/940] lr: 1.0000e-04 eta: 0:14:06 time: 0.7898 data_time: 0.0303 memory: 22701 grad_norm: 5.4280 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.8641 loss: 0.8641 2022/09/06 07:29:39 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 07:29:39 - mmengine - INFO - Epoch(train) [99][880/940] lr: 1.0000e-04 eta: 0:13:50 time: 0.8344 data_time: 0.0238 memory: 22701 grad_norm: 5.4689 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0154 loss: 1.0154 2022/09/06 07:29:54 - mmengine - INFO - Epoch(train) [99][900/940] lr: 1.0000e-04 eta: 0:13:33 time: 0.7283 data_time: 0.0322 memory: 22701 grad_norm: 5.5201 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 0.9760 loss: 0.9760 2022/09/06 07:30:09 - mmengine - INFO - Epoch(train) [99][920/940] lr: 1.0000e-04 eta: 0:13:16 time: 0.7475 data_time: 0.0273 memory: 22701 grad_norm: 5.2394 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 0.9809 loss: 0.9809 2022/09/06 07:30:23 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 07:30:23 - mmengine - INFO - Epoch(train) [99][940/940] lr: 1.0000e-04 eta: 0:13:00 time: 0.6968 data_time: 0.0189 memory: 22701 grad_norm: 5.8557 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.9575 loss: 0.9575 2022/09/06 07:30:23 - mmengine - INFO - Saving checkpoint at 99 epochs 2022/09/06 07:30:39 - mmengine - INFO - Epoch(val) [99][20/78] eta: 0:00:40 time: 0.7021 data_time: 0.5868 memory: 2247 2022/09/06 07:30:48 - mmengine - INFO - Epoch(val) [99][40/78] eta: 0:00:16 time: 0.4449 data_time: 0.3130 memory: 2247 2022/09/06 07:31:01 - mmengine - INFO - Epoch(val) [99][60/78] eta: 0:00:12 time: 0.6747 data_time: 0.5582 memory: 2247 2022/09/06 07:31:10 - mmengine - INFO - Epoch(val) [99][78/78] acc/top1: 0.6888 acc/top5: 0.8815 acc/mean1: 0.6887 2022/09/06 07:31:30 - mmengine - INFO - Epoch(train) [100][20/940] lr: 1.0000e-04 eta: 0:12:43 time: 0.9697 data_time: 0.5045 memory: 22701 grad_norm: 5.3202 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9579 loss: 0.9579 2022/09/06 07:31:43 - mmengine - INFO - Epoch(train) [100][40/940] lr: 1.0000e-04 eta: 0:12:27 time: 0.6678 data_time: 0.1784 memory: 22701 grad_norm: 5.3907 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9384 loss: 0.9384 2022/09/06 07:32:00 - mmengine - INFO - Epoch(train) [100][60/940] lr: 1.0000e-04 eta: 0:12:10 time: 0.8469 data_time: 0.1066 memory: 22701 grad_norm: 5.4197 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 0.9667 loss: 0.9667 2022/09/06 07:32:15 - mmengine - INFO - Epoch(train) [100][80/940] lr: 1.0000e-04 eta: 0:11:53 time: 0.7476 data_time: 0.1471 memory: 22701 grad_norm: 5.3714 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 0.8946 loss: 0.8946 2022/09/06 07:32:32 - mmengine - INFO - Epoch(train) [100][100/940] lr: 1.0000e-04 eta: 0:11:37 time: 0.8491 data_time: 0.0412 memory: 22701 grad_norm: 5.4628 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 0.9825 loss: 0.9825 2022/09/06 07:32:45 - mmengine - INFO - Epoch(train) [100][120/940] lr: 1.0000e-04 eta: 0:11:20 time: 0.6584 data_time: 0.0268 memory: 22701 grad_norm: 5.3274 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9330 loss: 0.9330 2022/09/06 07:33:00 - mmengine - INFO - Epoch(train) [100][140/940] lr: 1.0000e-04 eta: 0:11:04 time: 0.7684 data_time: 0.0283 memory: 22701 grad_norm: 5.4211 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9455 loss: 0.9455 2022/09/06 07:33:16 - mmengine - INFO - Epoch(train) [100][160/940] lr: 1.0000e-04 eta: 0:10:47 time: 0.8012 data_time: 0.0256 memory: 22701 grad_norm: 5.5590 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9971 loss: 0.9971 2022/09/06 07:33:36 - mmengine - INFO - Epoch(train) [100][180/940] lr: 1.0000e-04 eta: 0:10:30 time: 0.9654 data_time: 0.0280 memory: 22701 grad_norm: 5.4921 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9641 loss: 0.9641 2022/09/06 07:33:51 - mmengine - INFO - Epoch(train) [100][200/940] lr: 1.0000e-04 eta: 0:10:14 time: 0.7808 data_time: 0.0257 memory: 22701 grad_norm: 5.4359 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 0.9894 loss: 0.9894 2022/09/06 07:34:10 - mmengine - INFO - Epoch(train) [100][220/940] lr: 1.0000e-04 eta: 0:09:57 time: 0.9473 data_time: 0.0323 memory: 22701 grad_norm: 5.4866 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9320 loss: 0.9320 2022/09/06 07:34:26 - mmengine - INFO - Epoch(train) [100][240/940] lr: 1.0000e-04 eta: 0:09:41 time: 0.8060 data_time: 0.0524 memory: 22701 grad_norm: 5.3891 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 0.9085 loss: 0.9085 2022/09/06 07:34:44 - mmengine - INFO - Epoch(train) [100][260/940] lr: 1.0000e-04 eta: 0:09:24 time: 0.8926 data_time: 0.0437 memory: 22701 grad_norm: 5.3645 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9270 loss: 0.9270 2022/09/06 07:34:59 - mmengine - INFO - Epoch(train) [100][280/940] lr: 1.0000e-04 eta: 0:09:07 time: 0.7414 data_time: 0.0264 memory: 22701 grad_norm: 5.4484 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 0.9525 loss: 0.9525 2022/09/06 07:35:16 - mmengine - INFO - Epoch(train) [100][300/940] lr: 1.0000e-04 eta: 0:08:51 time: 0.8366 data_time: 0.0287 memory: 22701 grad_norm: 5.3197 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 0.8977 loss: 0.8977 2022/09/06 07:35:29 - mmengine - INFO - Epoch(train) [100][320/940] lr: 1.0000e-04 eta: 0:08:34 time: 0.6477 data_time: 0.0282 memory: 22701 grad_norm: 5.4314 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.8771 loss: 0.8771 2022/09/06 07:35:46 - mmengine - INFO - Epoch(train) [100][340/940] lr: 1.0000e-04 eta: 0:08:18 time: 0.8494 data_time: 0.0269 memory: 22701 grad_norm: 5.4087 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9889 loss: 0.9889 2022/09/06 07:36:01 - mmengine - INFO - Epoch(train) [100][360/940] lr: 1.0000e-04 eta: 0:08:01 time: 0.7532 data_time: 0.0365 memory: 22701 grad_norm: 5.3500 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 0.9866 loss: 0.9866 2022/09/06 07:36:16 - mmengine - INFO - Epoch(train) [100][380/940] lr: 1.0000e-04 eta: 0:07:44 time: 0.7617 data_time: 0.0277 memory: 22701 grad_norm: 5.5544 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 0.8723 loss: 0.8723 2022/09/06 07:36:30 - mmengine - INFO - Epoch(train) [100][400/940] lr: 1.0000e-04 eta: 0:07:28 time: 0.6832 data_time: 0.0424 memory: 22701 grad_norm: 5.3909 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.8823 loss: 0.8823 2022/09/06 07:36:46 - mmengine - INFO - Epoch(train) [100][420/940] lr: 1.0000e-04 eta: 0:07:11 time: 0.8269 data_time: 0.0289 memory: 22701 grad_norm: 5.3915 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 0.9788 loss: 0.9788 2022/09/06 07:37:01 - mmengine - INFO - Epoch(train) [100][440/940] lr: 1.0000e-04 eta: 0:06:54 time: 0.7063 data_time: 0.0879 memory: 22701 grad_norm: 5.4181 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.8522 loss: 0.8522 2022/09/06 07:37:17 - mmengine - INFO - Epoch(train) [100][460/940] lr: 1.0000e-04 eta: 0:06:38 time: 0.8086 data_time: 0.0359 memory: 22701 grad_norm: 5.3381 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9001 loss: 0.9001 2022/09/06 07:37:30 - mmengine - INFO - Epoch(train) [100][480/940] lr: 1.0000e-04 eta: 0:06:21 time: 0.6807 data_time: 0.0370 memory: 22701 grad_norm: 5.3402 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9432 loss: 0.9432 2022/09/06 07:37:47 - mmengine - INFO - Epoch(train) [100][500/940] lr: 1.0000e-04 eta: 0:06:05 time: 0.8173 data_time: 0.0272 memory: 22701 grad_norm: 5.3534 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9753 loss: 0.9753 2022/09/06 07:38:01 - mmengine - INFO - Epoch(train) [100][520/940] lr: 1.0000e-04 eta: 0:05:48 time: 0.7143 data_time: 0.0284 memory: 22701 grad_norm: 5.3922 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9369 loss: 0.9369 2022/09/06 07:38:18 - mmengine - INFO - Epoch(train) [100][540/940] lr: 1.0000e-04 eta: 0:05:31 time: 0.8416 data_time: 0.0341 memory: 22701 grad_norm: 5.4260 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0164 loss: 1.0164 2022/09/06 07:38:34 - mmengine - INFO - Epoch(train) [100][560/940] lr: 1.0000e-04 eta: 0:05:15 time: 0.7944 data_time: 0.0244 memory: 22701 grad_norm: 5.3926 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.8877 loss: 0.8877 2022/09/06 07:38:52 - mmengine - INFO - Epoch(train) [100][580/940] lr: 1.0000e-04 eta: 0:04:58 time: 0.9036 data_time: 0.0427 memory: 22701 grad_norm: 5.4651 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9372 loss: 0.9372 2022/09/06 07:39:07 - mmengine - INFO - Epoch(train) [100][600/940] lr: 1.0000e-04 eta: 0:04:42 time: 0.7645 data_time: 0.0248 memory: 22701 grad_norm: 5.4745 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 0.9525 loss: 0.9525 2022/09/06 07:39:27 - mmengine - INFO - Epoch(train) [100][620/940] lr: 1.0000e-04 eta: 0:04:25 time: 0.9776 data_time: 0.0274 memory: 22701 grad_norm: 5.3763 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9359 loss: 0.9359 2022/09/06 07:39:42 - mmengine - INFO - Epoch(train) [100][640/940] lr: 1.0000e-04 eta: 0:04:08 time: 0.7629 data_time: 0.0286 memory: 22701 grad_norm: 5.3646 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 0.9806 loss: 0.9806 2022/09/06 07:39:58 - mmengine - INFO - Epoch(train) [100][660/940] lr: 1.0000e-04 eta: 0:03:52 time: 0.8246 data_time: 0.0283 memory: 22701 grad_norm: 5.4655 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 0.9904 loss: 0.9904 2022/09/06 07:40:12 - mmengine - INFO - Epoch(train) [100][680/940] lr: 1.0000e-04 eta: 0:03:35 time: 0.6699 data_time: 0.0264 memory: 22701 grad_norm: 5.4050 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 0.9216 loss: 0.9216 2022/09/06 07:40:27 - mmengine - INFO - Epoch(train) [100][700/940] lr: 1.0000e-04 eta: 0:03:19 time: 0.7873 data_time: 0.0281 memory: 22701 grad_norm: 5.4124 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0505 loss: 1.0505 2022/09/06 07:40:42 - mmengine - INFO - Epoch(train) [100][720/940] lr: 1.0000e-04 eta: 0:03:02 time: 0.7047 data_time: 0.0262 memory: 22701 grad_norm: 5.3926 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0532 loss: 1.0532 2022/09/06 07:40:59 - mmengine - INFO - Epoch(train) [100][740/940] lr: 1.0000e-04 eta: 0:02:45 time: 0.8512 data_time: 0.0305 memory: 22701 grad_norm: 5.4474 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0073 loss: 1.0073 2022/09/06 07:41:15 - mmengine - INFO - Epoch(train) [100][760/940] lr: 1.0000e-04 eta: 0:02:29 time: 0.8115 data_time: 0.0206 memory: 22701 grad_norm: 5.4697 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 0.9835 loss: 0.9835 2022/09/06 07:41:38 - mmengine - INFO - Epoch(train) [100][780/940] lr: 1.0000e-04 eta: 0:02:12 time: 1.1503 data_time: 0.0437 memory: 22701 grad_norm: 5.4036 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 0.9906 loss: 0.9906 2022/09/06 07:41:59 - mmengine - INFO - Epoch(train) [100][800/940] lr: 1.0000e-04 eta: 0:01:56 time: 1.0482 data_time: 0.0258 memory: 22701 grad_norm: 5.4230 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 0.9603 loss: 0.9603 2022/09/06 07:42:20 - mmengine - INFO - Epoch(train) [100][820/940] lr: 1.0000e-04 eta: 0:01:39 time: 1.0722 data_time: 0.0200 memory: 22701 grad_norm: 5.5003 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 0.9877 loss: 0.9877 2022/09/06 07:42:39 - mmengine - INFO - Epoch(train) [100][840/940] lr: 1.0000e-04 eta: 0:01:23 time: 0.9526 data_time: 0.0314 memory: 22701 grad_norm: 5.4332 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 0.9047 loss: 0.9047 2022/09/06 07:42:55 - mmengine - INFO - Epoch(train) [100][860/940] lr: 1.0000e-04 eta: 0:01:06 time: 0.7793 data_time: 0.0509 memory: 22701 grad_norm: 5.3247 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 0.9500 loss: 0.9500 2022/09/06 07:43:14 - mmengine - INFO - Epoch(train) [100][880/940] lr: 1.0000e-04 eta: 0:00:49 time: 0.9299 data_time: 0.0285 memory: 22701 grad_norm: 5.3894 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 0.9891 loss: 0.9891 2022/09/06 07:43:29 - mmengine - INFO - Epoch(train) [100][900/940] lr: 1.0000e-04 eta: 0:00:33 time: 0.7565 data_time: 0.0279 memory: 22701 grad_norm: 5.4798 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 0.9522 loss: 0.9522 2022/09/06 07:43:50 - mmengine - INFO - Epoch(train) [100][920/940] lr: 1.0000e-04 eta: 0:00:16 time: 1.0624 data_time: 0.0227 memory: 22701 grad_norm: 5.4028 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0218 loss: 1.0218 2022/09/06 07:44:05 - mmengine - INFO - Exp name: tsn_dense161_320p_1x1x3_100e_kinetics400_rgb_20220905_084405 2022/09/06 07:44:05 - mmengine - INFO - Epoch(train) [100][940/940] lr: 1.0000e-04 eta: 0:00:00 time: 0.7715 data_time: 0.0223 memory: 22701 grad_norm: 5.7806 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.9450 loss: 0.9450 2022/09/06 07:44:05 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/09/06 07:44:21 - mmengine - INFO - Epoch(val) [100][20/78] eta: 0:00:40 time: 0.6941 data_time: 0.5731 memory: 2247 2022/09/06 07:44:30 - mmengine - INFO - Epoch(val) [100][40/78] eta: 0:00:17 time: 0.4544 data_time: 0.3383 memory: 2247 2022/09/06 07:44:43 - mmengine - INFO - Epoch(val) [100][60/78] eta: 0:00:11 time: 0.6558 data_time: 0.5381 memory: 2247 2022/09/06 07:44:53 - mmengine - INFO - Epoch(val) [100][78/78] acc/top1: 0.6899 acc/top5: 0.8804 acc/mean1: 0.6898