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[2023-10-25 08:01:24,759::train::INFO] [train] Iter 593558 | loss 1.9873 | loss(rot) 1.6472 | loss(pos) 0.0645 | loss(seq) 0.2756 | grad 25.8235 | lr 0.0000 | time_forward 1.3810 | time_backward 1.4410 |
[2023-10-25 08:01:33,876::train::INFO] [train] Iter 593559 | loss 0.8307 | loss(rot) 0.6494 | loss(pos) 0.0613 | loss(seq) 0.1200 | grad 18.3398 | lr 0.0000 | time_forward 3.8020 | time_backward 5.3120 |
[2023-10-25 08:01:42,205::train::INFO] [train] Iter 593560 | loss 0.4189 | loss(rot) 0.0952 | loss(pos) 0.0193 | loss(seq) 0.3043 | grad 1.8306 | lr 0.0000 | time_forward 3.5910 | time_backward 4.7350 |
[2023-10-25 08:01:50,490::train::INFO] [train] Iter 593561 | loss 0.7089 | loss(rot) 0.3680 | loss(pos) 0.0639 | loss(seq) 0.2771 | grad 2.9624 | lr 0.0000 | time_forward 3.5530 | time_backward 4.7290 |
[2023-10-25 08:01:57,077::train::INFO] [train] Iter 593562 | loss 1.0146 | loss(rot) 0.1739 | loss(pos) 0.8370 | loss(seq) 0.0037 | grad 9.1790 | lr 0.0000 | time_forward 2.8790 | time_backward 3.7040 |
[2023-10-25 08:02:06,079::train::INFO] [train] Iter 593563 | loss 0.1313 | loss(rot) 0.1115 | loss(pos) 0.0197 | loss(seq) 0.0001 | grad 4.7572 | lr 0.0000 | time_forward 3.7120 | time_backward 5.2870 |
[2023-10-25 08:02:13,002::train::INFO] [train] Iter 593564 | loss 0.0955 | loss(rot) 0.0676 | loss(pos) 0.0261 | loss(seq) 0.0018 | grad 1.5575 | lr 0.0000 | time_forward 2.9620 | time_backward 3.9570 |
[2023-10-25 08:02:22,031::train::INFO] [train] Iter 593565 | loss 0.8715 | loss(rot) 0.5370 | loss(pos) 0.0752 | loss(seq) 0.2592 | grad 3.4458 | lr 0.0000 | time_forward 3.7390 | time_backward 5.2870 |
[2023-10-25 08:02:29,347::train::INFO] [train] Iter 593566 | loss 0.8655 | loss(rot) 0.7287 | loss(pos) 0.0380 | loss(seq) 0.0988 | grad 3.2773 | lr 0.0000 | time_forward 3.1350 | time_backward 4.1790 |
[2023-10-25 08:02:32,216::train::INFO] [train] Iter 593567 | loss 0.5750 | loss(rot) 0.3676 | loss(pos) 0.0493 | loss(seq) 0.1580 | grad 26.4815 | lr 0.0000 | time_forward 1.3240 | time_backward 1.5420 |
[2023-10-25 08:02:39,857::train::INFO] [train] Iter 593568 | loss 1.5775 | loss(rot) 0.9808 | loss(pos) 0.2855 | loss(seq) 0.3113 | grad 6.3783 | lr 0.0000 | time_forward 3.2910 | time_backward 4.3310 |
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