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[2023-10-24 01:22:39,086::train::INFO] [train] Iter 577574 | loss 1.4171 | loss(rot) 0.8309 | loss(pos) 0.1049 | loss(seq) 0.4813 | grad 3.7885 | lr 0.0000 | time_forward 3.9590 | time_backward 5.7330 |
[2023-10-24 01:22:41,858::train::INFO] [train] Iter 577575 | loss 0.5368 | loss(rot) 0.1631 | loss(pos) 0.0538 | loss(seq) 0.3198 | grad 3.0267 | lr 0.0000 | time_forward 1.3410 | time_backward 1.4280 |
[2023-10-24 01:22:44,757::train::INFO] [train] Iter 577576 | loss 0.4849 | loss(rot) 0.2099 | loss(pos) 0.1294 | loss(seq) 0.1455 | grad 3.4202 | lr 0.0000 | time_forward 1.3690 | time_backward 1.5270 |
[2023-10-24 01:22:47,049::train::INFO] [train] Iter 577577 | loss 1.1131 | loss(rot) 0.7181 | loss(pos) 0.0498 | loss(seq) 0.3452 | grad 4.7948 | lr 0.0000 | time_forward 1.0570 | time_backward 1.2320 |
[2023-10-24 01:22:55,498::train::INFO] [train] Iter 577578 | loss 0.2426 | loss(rot) 0.0653 | loss(pos) 0.0289 | loss(seq) 0.1483 | grad 2.1637 | lr 0.0000 | time_forward 3.5880 | time_backward 4.8580 |
[2023-10-24 01:23:03,245::train::INFO] [train] Iter 577579 | loss 1.2569 | loss(rot) 1.2402 | loss(pos) 0.0158 | loss(seq) 0.0009 | grad 2.8975 | lr 0.0000 | time_forward 3.2660 | time_backward 4.4780 |
[2023-10-24 01:23:11,768::train::INFO] [train] Iter 577580 | loss 0.5143 | loss(rot) 0.1544 | loss(pos) 0.0322 | loss(seq) 0.3276 | grad 2.6341 | lr 0.0000 | time_forward 3.6140 | time_backward 4.9050 |
[2023-10-24 01:23:14,550::train::INFO] [train] Iter 577581 | loss 0.4234 | loss(rot) 0.1940 | loss(pos) 0.0143 | loss(seq) 0.2151 | grad 2.3709 | lr 0.0000 | time_forward 1.3210 | time_backward 1.4580 |
[2023-10-24 01:23:24,232::train::INFO] [train] Iter 577582 | loss 1.1249 | loss(rot) 0.6173 | loss(pos) 0.1093 | loss(seq) 0.3983 | grad 4.9591 | lr 0.0000 | time_forward 3.9440 | time_backward 5.7360 |
[2023-10-24 01:23:32,401::train::INFO] [train] Iter 577583 | loss 0.8462 | loss(rot) 0.4075 | loss(pos) 0.0280 | loss(seq) 0.4106 | grad 4.3220 | lr 0.0000 | time_forward 3.4560 | time_backward 4.7090 |
[2023-10-24 01:23:42,339::train::INFO] [train] Iter 577584 | loss 0.9496 | loss(rot) 0.1729 | loss(pos) 0.4872 | loss(seq) 0.2895 | grad 4.5920 | lr 0.0000 | time_forward 4.1440 | time_backward 5.7900 |
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