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[2023-10-23 13:23:07,872::train::INFO] [train] Iter 571281 | loss 0.3323 | loss(rot) 0.1353 | loss(pos) 0.0213 | loss(seq) 0.1756 | grad 2.2097 | lr 0.0000 | time_forward 3.2410 | time_backward 4.4770 |
[2023-10-23 13:23:15,419::train::INFO] [train] Iter 571282 | loss 1.0256 | loss(rot) 0.6834 | loss(pos) 0.1156 | loss(seq) 0.2267 | grad 3.7367 | lr 0.0000 | time_forward 3.2880 | time_backward 4.2550 |
[2023-10-23 13:23:18,163::train::INFO] [train] Iter 571283 | loss 0.2584 | loss(rot) 0.0638 | loss(pos) 0.1823 | loss(seq) 0.0123 | grad 3.3185 | lr 0.0000 | time_forward 1.3360 | time_backward 1.4050 |
[2023-10-23 13:23:20,937::train::INFO] [train] Iter 571284 | loss 0.5587 | loss(rot) 0.1835 | loss(pos) 0.0526 | loss(seq) 0.3226 | grad 4.0402 | lr 0.0000 | time_forward 1.3430 | time_backward 1.3990 |
[2023-10-23 13:23:26,712::train::INFO] [train] Iter 571285 | loss 1.8101 | loss(rot) 1.1467 | loss(pos) 0.3033 | loss(seq) 0.3600 | grad 5.5780 | lr 0.0000 | time_forward 2.4020 | time_backward 3.3410 |
[2023-10-23 13:23:35,383::train::INFO] [train] Iter 571286 | loss 0.5380 | loss(rot) 0.3191 | loss(pos) 0.1481 | loss(seq) 0.0708 | grad 4.8573 | lr 0.0000 | time_forward 3.6360 | time_backward 5.0170 |
[2023-10-23 13:23:42,539::train::INFO] [train] Iter 571287 | loss 0.8639 | loss(rot) 0.6443 | loss(pos) 0.1127 | loss(seq) 0.1069 | grad 2.7702 | lr 0.0000 | time_forward 3.0330 | time_backward 4.1190 |
[2023-10-23 13:23:44,796::train::INFO] [train] Iter 571288 | loss 0.6467 | loss(rot) 0.1823 | loss(pos) 0.4545 | loss(seq) 0.0099 | grad 4.3316 | lr 0.0000 | time_forward 1.0550 | time_backward 1.1990 |
[2023-10-23 13:23:51,849::train::INFO] [train] Iter 571289 | loss 2.6080 | loss(rot) 0.0131 | loss(pos) 2.5945 | loss(seq) 0.0003 | grad 21.3094 | lr 0.0000 | time_forward 3.0680 | time_backward 3.9830 |
[2023-10-23 13:23:58,149::train::INFO] [train] Iter 571290 | loss 1.5573 | loss(rot) 1.5065 | loss(pos) 0.0243 | loss(seq) 0.0265 | grad 11.1710 | lr 0.0000 | time_forward 2.6780 | time_backward 3.6180 |
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