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[2023-09-01 17:45:48,288::train::INFO] [train] Iter 00685 | loss 3.0678 | loss(rot) 2.1717 | loss(pos) 0.4530 | loss(seq) 0.4431 | grad 3.7595 | lr 0.0010 | time_forward 3.8990 | time_backward 4.9650 |
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[2023-09-01 17:46:15,115::train::INFO] [train] Iter 00688 | loss 1.9474 | loss(rot) 0.7826 | loss(pos) 0.7770 | loss(seq) 0.3878 | grad 3.0688 | lr 0.0010 | time_forward 3.7880 | time_backward 5.7590 |
[2023-09-01 17:46:23,669::train::INFO] [train] Iter 00689 | loss 2.9130 | loss(rot) 2.5042 | loss(pos) 0.2361 | loss(seq) 0.1727 | grad 3.4890 | lr 0.0010 | time_forward 3.5670 | time_backward 4.9840 |
[2023-09-01 17:46:31,450::train::INFO] [train] Iter 00690 | loss 3.7146 | loss(rot) 2.9181 | loss(pos) 0.6248 | loss(seq) 0.1718 | grad 5.4197 | lr 0.0010 | time_forward 3.0910 | time_backward 4.6870 |
[2023-09-01 17:46:34,282::train::INFO] [train] Iter 00691 | loss 2.5841 | loss(rot) 2.2265 | loss(pos) 0.3576 | loss(seq) 0.0000 | grad 4.4746 | lr 0.0010 | time_forward 1.3280 | time_backward 1.5010 |
[2023-09-01 17:46:42,446::train::INFO] [train] Iter 00692 | loss 4.0180 | loss(rot) 3.2347 | loss(pos) 0.7821 | loss(seq) 0.0012 | grad 7.8043 | lr 0.0010 | time_forward 3.3140 | time_backward 4.8460 |
[2023-09-01 17:46:51,624::train::INFO] [train] Iter 00693 | loss 3.5792 | loss(rot) 2.7422 | loss(pos) 0.5118 | loss(seq) 0.3252 | grad 5.7142 | lr 0.0010 | time_forward 3.8730 | time_backward 5.3020 |
[2023-09-01 17:47:00,792::train::INFO] [train] Iter 00694 | loss 2.5985 | loss(rot) 1.3324 | loss(pos) 0.5955 | loss(seq) 0.6706 | grad 4.9871 | lr 0.0010 | time_forward 3.6860 | time_backward 5.4800 |
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