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[2023-09-02 11:50:56,000::train::INFO] [train] Iter 09576 | loss 1.7867 | loss(rot) 1.4023 | loss(pos) 0.1199 | loss(seq) 0.2645 | grad 5.0608 | lr 0.0010 | time_forward 4.1730 | time_backward 5.9180 |
[2023-09-02 11:51:06,071::train::INFO] [train] Iter 09577 | loss 2.4380 | loss(rot) 0.3187 | loss(pos) 1.8603 | loss(seq) 0.2589 | grad 5.2955 | lr 0.0010 | time_forward 4.0180 | time_backward 6.0490 |
[2023-09-02 11:51:15,114::train::INFO] [train] Iter 09578 | loss 1.9176 | loss(rot) 1.2096 | loss(pos) 0.1933 | loss(seq) 0.5147 | grad 5.1609 | lr 0.0010 | time_forward 3.7740 | time_backward 5.2650 |
[2023-09-02 11:51:23,447::train::INFO] [train] Iter 09579 | loss 1.3961 | loss(rot) 0.0169 | loss(pos) 1.3780 | loss(seq) 0.0012 | grad 4.9014 | lr 0.0010 | time_forward 3.5190 | time_backward 4.8100 |
[2023-09-02 11:51:32,084::train::INFO] [train] Iter 09580 | loss 2.6060 | loss(rot) 1.7871 | loss(pos) 0.3189 | loss(seq) 0.4999 | grad 3.9785 | lr 0.0010 | time_forward 3.6980 | time_backward 4.9360 |
[2023-09-02 11:51:40,799::train::INFO] [train] Iter 09581 | loss 2.7431 | loss(rot) 2.5197 | loss(pos) 0.1506 | loss(seq) 0.0728 | grad 5.3541 | lr 0.0010 | time_forward 3.6740 | time_backward 5.0370 |
[2023-09-02 11:51:48,822::train::INFO] [train] Iter 09582 | loss 1.6931 | loss(rot) 1.5247 | loss(pos) 0.1540 | loss(seq) 0.0144 | grad 6.4611 | lr 0.0010 | time_forward 3.3030 | time_backward 4.7160 |
[2023-09-02 11:51:51,743::train::INFO] [train] Iter 09583 | loss 1.0690 | loss(rot) 0.5647 | loss(pos) 0.1373 | loss(seq) 0.3669 | grad 4.2822 | lr 0.0010 | time_forward 1.4300 | time_backward 1.4870 |
[2023-09-02 11:52:01,374::train::INFO] [train] Iter 09584 | loss 1.1915 | loss(rot) 0.4793 | loss(pos) 0.3592 | loss(seq) 0.3530 | grad 4.3545 | lr 0.0010 | time_forward 3.9810 | time_backward 5.6460 |
[2023-09-02 11:52:09,807::train::INFO] [train] Iter 09585 | loss 0.7211 | loss(rot) 0.2526 | loss(pos) 0.3668 | loss(seq) 0.1016 | grad 4.6231 | lr 0.0010 | time_forward 3.6080 | time_backward 4.8000 |
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