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[2023-09-03 03:55:39,534::train::INFO] [train] Iter 17668 | loss 1.5002 | loss(rot) 0.0376 | loss(pos) 1.1930 | loss(seq) 0.2696 | grad 9.9897 | lr 0.0010 | time_forward 3.4820 | time_backward 5.6030 |
[2023-09-03 03:55:49,537::train::INFO] [train] Iter 17669 | loss 2.2978 | loss(rot) 1.6134 | loss(pos) 0.2521 | loss(seq) 0.4323 | grad 5.1894 | lr 0.0010 | time_forward 4.0900 | time_backward 5.9080 |
[2023-09-03 03:55:56,369::train::INFO] [train] Iter 17670 | loss 0.7978 | loss(rot) 0.6355 | loss(pos) 0.1623 | loss(seq) 0.0000 | grad 4.6714 | lr 0.0010 | time_forward 2.9180 | time_backward 3.9100 |
[2023-09-03 03:56:05,935::train::INFO] [train] Iter 17671 | loss 1.2061 | loss(rot) 0.0223 | loss(pos) 1.1802 | loss(seq) 0.0036 | grad 7.1376 | lr 0.0010 | time_forward 3.9710 | time_backward 5.5920 |
[2023-09-03 03:56:16,039::train::INFO] [train] Iter 17672 | loss 2.8399 | loss(rot) 2.5587 | loss(pos) 0.2524 | loss(seq) 0.0288 | grad 4.9216 | lr 0.0010 | time_forward 4.2210 | time_backward 5.8780 |
[2023-09-03 03:56:24,491::train::INFO] [train] Iter 17673 | loss 1.5435 | loss(rot) 0.5673 | loss(pos) 0.4995 | loss(seq) 0.4767 | grad 6.7418 | lr 0.0010 | time_forward 3.5860 | time_backward 4.8620 |
[2023-09-03 03:56:27,393::train::INFO] [train] Iter 17674 | loss 1.0766 | loss(rot) 0.6272 | loss(pos) 0.2526 | loss(seq) 0.1968 | grad 6.4250 | lr 0.0010 | time_forward 1.3530 | time_backward 1.5450 |
[2023-09-03 03:56:36,569::train::INFO] [train] Iter 17675 | loss 0.4024 | loss(rot) 0.1059 | loss(pos) 0.2800 | loss(seq) 0.0164 | grad 2.9598 | lr 0.0010 | time_forward 3.6670 | time_backward 5.4950 |
[2023-09-03 03:56:45,325::train::INFO] [train] Iter 17676 | loss 1.2337 | loss(rot) 1.0129 | loss(pos) 0.1695 | loss(seq) 0.0513 | grad 5.8191 | lr 0.0010 | time_forward 3.5480 | time_backward 5.2040 |
[2023-09-03 03:56:48,160::train::INFO] [train] Iter 17677 | loss 2.0490 | loss(rot) 1.5039 | loss(pos) 0.1427 | loss(seq) 0.4023 | grad 4.3252 | lr 0.0010 | time_forward 1.3540 | time_backward 1.4770 |
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