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[2023-10-24 09:15:12,358::train::INFO] [train] Iter 581570 | loss 0.5275 | loss(rot) 0.3904 | loss(pos) 0.1215 | loss(seq) 0.0155 | grad 3.6533 | lr 0.0000 | time_forward 4.1430 | time_backward 5.9380 |
[2023-10-24 09:15:15,152::train::INFO] [train] Iter 581571 | loss 0.9486 | loss(rot) 0.8863 | loss(pos) 0.0214 | loss(seq) 0.0409 | grad 5.2005 | lr 0.0000 | time_forward 1.3390 | time_backward 1.4510 |
[2023-10-24 09:15:23,479::train::INFO] [train] Iter 581572 | loss 0.3120 | loss(rot) 0.1340 | loss(pos) 0.1480 | loss(seq) 0.0299 | grad 3.0461 | lr 0.0000 | time_forward 3.5510 | time_backward 4.7740 |
[2023-10-24 09:15:26,729::train::INFO] [train] Iter 581573 | loss 1.4132 | loss(rot) 0.4066 | loss(pos) 0.5403 | loss(seq) 0.4664 | grad 5.1330 | lr 0.0000 | time_forward 1.4850 | time_backward 1.7620 |
[2023-10-24 09:15:35,736::train::INFO] [train] Iter 581574 | loss 0.1889 | loss(rot) 0.1207 | loss(pos) 0.0317 | loss(seq) 0.0365 | grad 1.9300 | lr 0.0000 | time_forward 3.8430 | time_backward 5.1490 |
[2023-10-24 09:15:45,505::train::INFO] [train] Iter 581575 | loss 0.6277 | loss(rot) 0.2624 | loss(pos) 0.0569 | loss(seq) 0.3084 | grad 2.7767 | lr 0.0000 | time_forward 4.0160 | time_backward 5.7500 |
[2023-10-24 09:15:53,560::train::INFO] [train] Iter 581576 | loss 0.9641 | loss(rot) 0.3227 | loss(pos) 0.4495 | loss(seq) 0.1918 | grad 4.5843 | lr 0.0000 | time_forward 3.6500 | time_backward 4.4020 |
[2023-10-24 09:16:01,580::train::INFO] [train] Iter 581577 | loss 0.8598 | loss(rot) 0.4735 | loss(pos) 0.1208 | loss(seq) 0.2655 | grad 4.4544 | lr 0.0000 | time_forward 3.4660 | time_backward 4.5500 |
[2023-10-24 09:16:12,292::train::INFO] [train] Iter 581578 | loss 1.2878 | loss(rot) 0.9338 | loss(pos) 0.0962 | loss(seq) 0.2578 | grad 4.7184 | lr 0.0000 | time_forward 4.7540 | time_backward 5.9550 |
[2023-10-24 09:16:22,109::train::INFO] [train] Iter 581579 | loss 0.4603 | loss(rot) 0.0641 | loss(pos) 0.0346 | loss(seq) 0.3617 | grad 3.5912 | lr 0.0000 | time_forward 4.0280 | time_backward 5.7850 |
[2023-10-24 09:16:32,270::train::INFO] [train] Iter 581580 | loss 0.6491 | loss(rot) 0.4337 | loss(pos) 0.0514 | loss(seq) 0.1640 | grad 2.4574 | lr 0.0000 | time_forward 4.2410 | time_backward 5.9160 |
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