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[2023-10-24 05:18:36,456::train::INFO] [train] Iter 579572 | loss 0.6693 | loss(rot) 0.1570 | loss(pos) 0.2142 | loss(seq) 0.2980 | grad 3.5703 | lr 0.0000 | time_forward 3.1800 | time_backward 4.1350 |
[2023-10-24 05:18:45,968::train::INFO] [train] Iter 579573 | loss 0.2991 | loss(rot) 0.2740 | loss(pos) 0.0156 | loss(seq) 0.0094 | grad 2.8596 | lr 0.0000 | time_forward 3.8680 | time_backward 5.6400 |
[2023-10-24 05:18:55,812::train::INFO] [train] Iter 579574 | loss 1.0567 | loss(rot) 0.2957 | loss(pos) 0.4314 | loss(seq) 0.3296 | grad 5.5855 | lr 0.0000 | time_forward 4.1100 | time_backward 5.7300 |
[2023-10-24 05:19:04,060::train::INFO] [train] Iter 579575 | loss 0.9306 | loss(rot) 0.8568 | loss(pos) 0.0289 | loss(seq) 0.0449 | grad 4.1548 | lr 0.0000 | time_forward 3.4480 | time_backward 4.7970 |
[2023-10-24 05:19:14,161::train::INFO] [train] Iter 579576 | loss 0.8386 | loss(rot) 0.4155 | loss(pos) 0.1811 | loss(seq) 0.2421 | grad 3.6973 | lr 0.0000 | time_forward 4.0110 | time_backward 6.0870 |
[2023-10-24 05:19:24,014::train::INFO] [train] Iter 579577 | loss 1.2639 | loss(rot) 1.0404 | loss(pos) 0.0531 | loss(seq) 0.1705 | grad 5.1468 | lr 0.0000 | time_forward 4.0660 | time_backward 5.7830 |
[2023-10-24 05:19:31,363::train::INFO] [train] Iter 579578 | loss 0.5471 | loss(rot) 0.1358 | loss(pos) 0.1692 | loss(seq) 0.2421 | grad 3.9742 | lr 0.0000 | time_forward 3.1620 | time_backward 4.1850 |
[2023-10-24 05:19:33,645::train::INFO] [train] Iter 579579 | loss 0.5279 | loss(rot) 0.1053 | loss(pos) 0.4072 | loss(seq) 0.0154 | grad 5.7290 | lr 0.0000 | time_forward 1.0520 | time_backward 1.2250 |
[2023-10-24 05:19:36,411::train::INFO] [train] Iter 579580 | loss 0.4380 | loss(rot) 0.3869 | loss(pos) 0.0172 | loss(seq) 0.0339 | grad 45.0598 | lr 0.0000 | time_forward 1.2880 | time_backward 1.4740 |
[2023-10-24 05:19:45,019::train::INFO] [train] Iter 579581 | loss 0.6061 | loss(rot) 0.0541 | loss(pos) 0.5465 | loss(seq) 0.0055 | grad 8.8256 | lr 0.0000 | time_forward 3.6000 | time_backward 4.9680 |
[2023-10-24 05:19:53,216::train::INFO] [train] Iter 579582 | loss 0.5174 | loss(rot) 0.0435 | loss(pos) 0.4711 | loss(seq) 0.0029 | grad 12.7729 | lr 0.0000 | time_forward 3.4530 | time_backward 4.7410 |
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