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[2023-10-23 14:06:23,190::train::INFO] [train] Iter 571681 | loss 0.6361 | loss(rot) 0.3240 | loss(pos) 0.2576 | loss(seq) 0.0545 | grad 3.9340 | lr 0.0000 | time_forward 3.5680 | time_backward 4.4990 |
[2023-10-23 14:06:26,054::train::INFO] [train] Iter 571682 | loss 1.4794 | loss(rot) 1.0885 | loss(pos) 0.1212 | loss(seq) 0.2697 | grad 3.6357 | lr 0.0000 | time_forward 1.3820 | time_backward 1.4790 |
[2023-10-23 14:06:32,802::train::INFO] [train] Iter 571683 | loss 0.8834 | loss(rot) 0.1357 | loss(pos) 0.4962 | loss(seq) 0.2515 | grad 7.5478 | lr 0.0000 | time_forward 3.0040 | time_backward 3.7410 |
[2023-10-23 14:06:41,341::train::INFO] [train] Iter 571684 | loss 0.4081 | loss(rot) 0.3835 | loss(pos) 0.0222 | loss(seq) 0.0025 | grad 59.6324 | lr 0.0000 | time_forward 3.6070 | time_backward 4.9290 |
[2023-10-23 14:06:47,674::train::INFO] [train] Iter 571685 | loss 0.6671 | loss(rot) 0.6513 | loss(pos) 0.0101 | loss(seq) 0.0057 | grad 3.7543 | lr 0.0000 | time_forward 2.7860 | time_backward 3.5450 |
[2023-10-23 14:06:55,112::train::INFO] [train] Iter 571686 | loss 0.9102 | loss(rot) 0.5694 | loss(pos) 0.0199 | loss(seq) 0.3208 | grad 7.7651 | lr 0.0000 | time_forward 3.2690 | time_backward 4.1660 |
[2023-10-23 14:07:02,403::train::INFO] [train] Iter 571687 | loss 0.2130 | loss(rot) 0.1258 | loss(pos) 0.0467 | loss(seq) 0.0405 | grad 3.1022 | lr 0.0000 | time_forward 3.1650 | time_backward 4.1240 |
[2023-10-23 14:07:09,159::train::INFO] [train] Iter 571688 | loss 0.4433 | loss(rot) 0.0433 | loss(pos) 0.3631 | loss(seq) 0.0369 | grad 6.2690 | lr 0.0000 | time_forward 2.9970 | time_backward 3.7550 |
[2023-10-23 14:07:17,929::train::INFO] [train] Iter 571689 | loss 0.2634 | loss(rot) 0.2269 | loss(pos) 0.0364 | loss(seq) 0.0001 | grad 2.5545 | lr 0.0000 | time_forward 3.7060 | time_backward 5.0610 |
[2023-10-23 14:07:20,708::train::INFO] [train] Iter 571690 | loss 0.2686 | loss(rot) 0.0231 | loss(pos) 0.0281 | loss(seq) 0.2174 | grad 1.5605 | lr 0.0000 | time_forward 1.3660 | time_backward 1.4090 |
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