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[2023-10-25 02:34:45,577::train::INFO] [train] Iter 590562 | loss 0.5696 | loss(rot) 0.4866 | loss(pos) 0.0567 | loss(seq) 0.0262 | grad 68.5668 | lr 0.0000 | time_forward 3.2140 | time_backward 4.2980 |
[2023-10-25 02:34:54,513::train::INFO] [train] Iter 590563 | loss 0.4966 | loss(rot) 0.2393 | loss(pos) 0.0573 | loss(seq) 0.1999 | grad 3.4569 | lr 0.0000 | time_forward 3.6830 | time_backward 5.2490 |
[2023-10-25 02:34:57,703::train::INFO] [train] Iter 590564 | loss 0.6452 | loss(rot) 0.3120 | loss(pos) 0.1222 | loss(seq) 0.2110 | grad 2.9423 | lr 0.0000 | time_forward 1.4310 | time_backward 1.7560 |
[2023-10-25 02:35:00,561::train::INFO] [train] Iter 590565 | loss 0.6954 | loss(rot) 0.4057 | loss(pos) 0.0344 | loss(seq) 0.2552 | grad 1.9409 | lr 0.0000 | time_forward 1.2830 | time_backward 1.5600 |
[2023-10-25 02:35:08,918::train::INFO] [train] Iter 590566 | loss 0.3398 | loss(rot) 0.2940 | loss(pos) 0.0364 | loss(seq) 0.0094 | grad 2.9739 | lr 0.0000 | time_forward 3.5390 | time_backward 4.8150 |
[2023-10-25 02:35:11,647::train::INFO] [train] Iter 590567 | loss 0.3579 | loss(rot) 0.0539 | loss(pos) 0.0377 | loss(seq) 0.2664 | grad 3.1319 | lr 0.0000 | time_forward 1.2990 | time_backward 1.4260 |
[2023-10-25 02:35:19,966::train::INFO] [train] Iter 590568 | loss 0.3529 | loss(rot) 0.1210 | loss(pos) 0.0565 | loss(seq) 0.1754 | grad 3.0016 | lr 0.0000 | time_forward 3.5400 | time_backward 4.7760 |
[2023-10-25 02:35:28,967::train::INFO] [train] Iter 590569 | loss 0.1885 | loss(rot) 0.1437 | loss(pos) 0.0294 | loss(seq) 0.0153 | grad 2.0540 | lr 0.0000 | time_forward 3.6120 | time_backward 5.3860 |
[2023-10-25 02:35:36,456::train::INFO] [train] Iter 590570 | loss 0.4174 | loss(rot) 0.1869 | loss(pos) 0.0909 | loss(seq) 0.1397 | grad 3.2775 | lr 0.0000 | time_forward 3.1970 | time_backward 4.2890 |
[2023-10-25 02:35:44,008::train::INFO] [train] Iter 590571 | loss 1.3554 | loss(rot) 1.3116 | loss(pos) 0.0418 | loss(seq) 0.0019 | grad 4.5944 | lr 0.0000 | time_forward 3.1540 | time_backward 4.3940 |
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