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[2023-10-22 20:23:01,003::train::INFO] [train] Iter 561591 | loss 0.4634 | loss(rot) 0.2738 | loss(pos) 0.0308 | loss(seq) 0.1588 | grad 1.9828 | lr 0.0000 | time_forward 1.3190 | time_backward 1.4100 |
[2023-10-22 20:23:07,505::train::INFO] [train] Iter 561592 | loss 2.0399 | loss(rot) 1.6734 | loss(pos) 0.1505 | loss(seq) 0.2161 | grad 4.1988 | lr 0.0000 | time_forward 2.8340 | time_backward 3.6660 |
[2023-10-22 20:23:14,269::train::INFO] [train] Iter 561593 | loss 0.3955 | loss(rot) 0.0443 | loss(pos) 0.3339 | loss(seq) 0.0172 | grad 9.1703 | lr 0.0000 | time_forward 2.9000 | time_backward 3.8610 |
[2023-10-22 20:23:23,273::train::INFO] [train] Iter 561594 | loss 0.6809 | loss(rot) 0.6134 | loss(pos) 0.0445 | loss(seq) 0.0229 | grad 2.9047 | lr 0.0000 | time_forward 3.6770 | time_backward 5.3230 |
[2023-10-22 20:23:32,363::train::INFO] [train] Iter 561595 | loss 0.2538 | loss(rot) 0.1092 | loss(pos) 0.0459 | loss(seq) 0.0988 | grad 2.7105 | lr 0.0000 | time_forward 3.7240 | time_backward 5.3630 |
[2023-10-22 20:23:40,975::train::INFO] [train] Iter 561596 | loss 0.8177 | loss(rot) 0.6989 | loss(pos) 0.0187 | loss(seq) 0.1001 | grad 2.6626 | lr 0.0000 | time_forward 3.6290 | time_backward 4.9810 |
[2023-10-22 20:23:49,466::train::INFO] [train] Iter 561597 | loss 1.4721 | loss(rot) 1.4472 | loss(pos) 0.0238 | loss(seq) 0.0010 | grad 5.3462 | lr 0.0000 | time_forward 3.6440 | time_backward 4.8440 |
[2023-10-22 20:23:57,190::train::INFO] [train] Iter 561598 | loss 3.1355 | loss(rot) 0.0505 | loss(pos) 3.0850 | loss(seq) 0.0000 | grad 16.6891 | lr 0.0000 | time_forward 3.2740 | time_backward 4.4460 |
[2023-10-22 20:24:06,347::train::INFO] [train] Iter 561599 | loss 1.3950 | loss(rot) 0.4295 | loss(pos) 0.9651 | loss(seq) 0.0005 | grad 9.6817 | lr 0.0000 | time_forward 3.7640 | time_backward 5.3910 |
[2023-10-22 20:24:09,527::train::INFO] [train] Iter 561600 | loss 0.8750 | loss(rot) 0.5264 | loss(pos) 0.0769 | loss(seq) 0.2718 | grad 3.2356 | lr 0.0000 | time_forward 1.4520 | time_backward 1.7240 |
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