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[2023-10-25 17:33:42,279::train::INFO] [train] Iter 598453 | loss 0.7999 | loss(rot) 0.3470 | loss(pos) 0.1528 | loss(seq) 0.3001 | grad 3.8584 | lr 0.0000 | time_forward 1.3750 | time_backward 1.7890 |
[2023-10-25 17:33:51,081::train::INFO] [train] Iter 598454 | loss 0.2957 | loss(rot) 0.2671 | loss(pos) 0.0223 | loss(seq) 0.0063 | grad 2.0709 | lr 0.0000 | time_forward 3.8720 | time_backward 4.9160 |
[2023-10-25 17:33:53,838::train::INFO] [train] Iter 598455 | loss 0.7375 | loss(rot) 0.4501 | loss(pos) 0.1000 | loss(seq) 0.1874 | grad 3.2058 | lr 0.0000 | time_forward 1.3460 | time_backward 1.4070 |
[2023-10-25 17:34:01,678::train::INFO] [train] Iter 598456 | loss 1.7792 | loss(rot) 1.4047 | loss(pos) 0.1250 | loss(seq) 0.2496 | grad 3.3361 | lr 0.0000 | time_forward 3.3970 | time_backward 4.4260 |
[2023-10-25 17:34:09,634::train::INFO] [train] Iter 598457 | loss 0.8121 | loss(rot) 0.7923 | loss(pos) 0.0136 | loss(seq) 0.0061 | grad 2.7686 | lr 0.0000 | time_forward 3.3870 | time_backward 4.5660 |
[2023-10-25 17:34:17,483::train::INFO] [train] Iter 598458 | loss 1.6563 | loss(rot) 0.9526 | loss(pos) 0.1085 | loss(seq) 0.5952 | grad 4.4794 | lr 0.0000 | time_forward 3.2180 | time_backward 4.6280 |
[2023-10-25 17:34:25,752::train::INFO] [train] Iter 598459 | loss 0.4119 | loss(rot) 0.3845 | loss(pos) 0.0203 | loss(seq) 0.0071 | grad 3.6992 | lr 0.0000 | time_forward 3.1800 | time_backward 5.0870 |
[2023-10-25 17:34:28,536::train::INFO] [train] Iter 598460 | loss 0.6541 | loss(rot) 0.4985 | loss(pos) 0.0246 | loss(seq) 0.1310 | grad 8.6186 | lr 0.0000 | time_forward 1.3010 | time_backward 1.4790 |
[2023-10-25 17:34:31,045::train::INFO] [train] Iter 598461 | loss 2.4170 | loss(rot) 2.3604 | loss(pos) 0.0567 | loss(seq) 0.0000 | grad 8.4261 | lr 0.0000 | time_forward 1.2100 | time_backward 1.2960 |
[2023-10-25 17:34:38,957::train::INFO] [train] Iter 598462 | loss 0.7786 | loss(rot) 0.1242 | loss(pos) 0.1637 | loss(seq) 0.4907 | grad 3.1591 | lr 0.0000 | time_forward 3.1740 | time_backward 4.7340 |
[2023-10-25 17:34:45,726::train::INFO] [train] Iter 598463 | loss 0.5755 | loss(rot) 0.1903 | loss(pos) 0.0795 | loss(seq) 0.3058 | grad 4.0295 | lr 0.0000 | time_forward 2.9000 | time_backward 3.8660 |
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