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[2023-10-23 20:26:09,280::train::INFO] [train] Iter 575076 | loss 0.8117 | loss(rot) 0.7805 | loss(pos) 0.0290 | loss(seq) 0.0022 | grad 4.7043 | lr 0.0000 | time_forward 3.4150 | time_backward 4.4210 |
[2023-10-23 20:26:18,908::train::INFO] [train] Iter 575077 | loss 1.5025 | loss(rot) 0.8022 | loss(pos) 0.4014 | loss(seq) 0.2989 | grad 4.7081 | lr 0.0000 | time_forward 4.2060 | time_backward 5.4190 |
[2023-10-23 20:26:28,379::train::INFO] [train] Iter 575078 | loss 0.7558 | loss(rot) 0.5163 | loss(pos) 0.0565 | loss(seq) 0.1829 | grad 3.1216 | lr 0.0000 | time_forward 4.1990 | time_backward 5.2680 |
[2023-10-23 20:26:31,011::train::INFO] [train] Iter 575079 | loss 1.0763 | loss(rot) 0.5946 | loss(pos) 0.0555 | loss(seq) 0.4261 | grad 3.4767 | lr 0.0000 | time_forward 1.3990 | time_backward 1.2310 |
[2023-10-23 20:26:33,902::train::INFO] [train] Iter 575080 | loss 0.1574 | loss(rot) 0.1106 | loss(pos) 0.0356 | loss(seq) 0.0112 | grad 1.9719 | lr 0.0000 | time_forward 1.4150 | time_backward 1.4720 |
[2023-10-23 20:26:41,344::train::INFO] [train] Iter 575081 | loss 0.5627 | loss(rot) 0.1680 | loss(pos) 0.0422 | loss(seq) 0.3526 | grad 3.5082 | lr 0.0000 | time_forward 3.3780 | time_backward 4.0610 |
[2023-10-23 20:26:44,396::train::INFO] [train] Iter 575082 | loss 0.2717 | loss(rot) 0.0600 | loss(pos) 0.1918 | loss(seq) 0.0198 | grad 6.5255 | lr 0.0000 | time_forward 1.6090 | time_backward 1.4400 |
[2023-10-23 20:26:52,879::train::INFO] [train] Iter 575083 | loss 1.6772 | loss(rot) 1.1312 | loss(pos) 0.1183 | loss(seq) 0.4277 | grad 8.5991 | lr 0.0000 | time_forward 3.9010 | time_backward 4.5790 |
[2023-10-23 20:27:00,669::train::INFO] [train] Iter 575084 | loss 0.5586 | loss(rot) 0.5318 | loss(pos) 0.0263 | loss(seq) 0.0005 | grad 2.6718 | lr 0.0000 | time_forward 3.4590 | time_backward 4.3280 |
[2023-10-23 20:27:10,449::train::INFO] [train] Iter 575085 | loss 0.2090 | loss(rot) 0.1516 | loss(pos) 0.0305 | loss(seq) 0.0269 | grad 2.3324 | lr 0.0000 | time_forward 4.2850 | time_backward 5.4930 |
[2023-10-23 20:27:19,835::train::INFO] [train] Iter 575086 | loss 1.0704 | loss(rot) 0.7096 | loss(pos) 0.0760 | loss(seq) 0.2848 | grad 4.0084 | lr 0.0000 | time_forward 4.1240 | time_backward 5.2590 |
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