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[2023-10-22 16:42:30,190::train::INFO] [train] Iter 559693 | loss 0.7721 | loss(rot) 0.4964 | loss(pos) 0.0633 | loss(seq) 0.2124 | grad 23.5309 | lr 0.0000 | time_forward 1.3950 | time_backward 1.5200 |
[2023-10-22 16:42:38,317::train::INFO] [train] Iter 559694 | loss 1.8062 | loss(rot) 1.7730 | loss(pos) 0.0319 | loss(seq) 0.0012 | grad 4.1918 | lr 0.0000 | time_forward 3.3200 | time_backward 4.7780 |
[2023-10-22 16:42:41,137::train::INFO] [train] Iter 559695 | loss 0.2475 | loss(rot) 0.1058 | loss(pos) 0.0348 | loss(seq) 0.1069 | grad 2.3117 | lr 0.0000 | time_forward 1.3390 | time_backward 1.4770 |
[2023-10-22 16:42:44,036::train::INFO] [train] Iter 559696 | loss 1.8993 | loss(rot) 1.2053 | loss(pos) 0.3327 | loss(seq) 0.3612 | grad 6.7777 | lr 0.0000 | time_forward 1.4040 | time_backward 1.4920 |
[2023-10-22 16:42:52,110::train::INFO] [train] Iter 559697 | loss 0.7701 | loss(rot) 0.3564 | loss(pos) 0.0637 | loss(seq) 0.3500 | grad 3.9756 | lr 0.0000 | time_forward 3.4080 | time_backward 4.6620 |
[2023-10-22 16:43:01,127::train::INFO] [train] Iter 559698 | loss 0.9875 | loss(rot) 0.0342 | loss(pos) 0.9515 | loss(seq) 0.0019 | grad 6.4667 | lr 0.0000 | time_forward 3.8730 | time_backward 5.1100 |
[2023-10-22 16:43:09,960::train::INFO] [train] Iter 559699 | loss 1.4203 | loss(rot) 0.5153 | loss(pos) 0.8972 | loss(seq) 0.0078 | grad 13.3039 | lr 0.0000 | time_forward 3.7480 | time_backward 5.0830 |
[2023-10-22 16:43:12,786::train::INFO] [train] Iter 559700 | loss 0.9035 | loss(rot) 0.0125 | loss(pos) 0.8866 | loss(seq) 0.0044 | grad 12.6928 | lr 0.0000 | time_forward 1.3400 | time_backward 1.4830 |
[2023-10-22 16:43:22,321::train::INFO] [train] Iter 559701 | loss 0.1716 | loss(rot) 0.1297 | loss(pos) 0.0136 | loss(seq) 0.0283 | grad 2.1371 | lr 0.0000 | time_forward 3.8840 | time_backward 5.6070 |
[2023-10-22 16:43:31,864::train::INFO] [train] Iter 559702 | loss 0.6662 | loss(rot) 0.0320 | loss(pos) 0.6283 | loss(seq) 0.0060 | grad 6.3732 | lr 0.0000 | time_forward 3.9170 | time_backward 5.6220 |
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