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[2023-10-22 16:07:37,732::train::INFO] [train] Iter 559394 | loss 0.7002 | loss(rot) 0.4146 | loss(pos) 0.1249 | loss(seq) 0.1607 | grad 4.6216 | lr 0.0000 | time_forward 3.9540 | time_backward 6.2040 |
[2023-10-22 16:07:40,816::train::INFO] [train] Iter 559395 | loss 0.2694 | loss(rot) 0.2134 | loss(pos) 0.0132 | loss(seq) 0.0429 | grad 2.3452 | lr 0.0000 | time_forward 1.4280 | time_backward 1.6540 |
[2023-10-22 16:07:51,239::train::INFO] [train] Iter 559396 | loss 1.4965 | loss(rot) 0.8914 | loss(pos) 0.0855 | loss(seq) 0.5197 | grad 3.9205 | lr 0.0000 | time_forward 4.2950 | time_backward 6.1240 |
[2023-10-22 16:07:59,578::train::INFO] [train] Iter 559397 | loss 0.3942 | loss(rot) 0.2704 | loss(pos) 0.0301 | loss(seq) 0.0937 | grad 2.5557 | lr 0.0000 | time_forward 3.4770 | time_backward 4.8600 |
[2023-10-22 16:08:09,605::train::INFO] [train] Iter 559398 | loss 1.3807 | loss(rot) 1.3472 | loss(pos) 0.0334 | loss(seq) 0.0001 | grad 3.8999 | lr 0.0000 | time_forward 4.2670 | time_backward 5.7560 |
[2023-10-22 16:08:17,833::train::INFO] [train] Iter 559399 | loss 0.2579 | loss(rot) 0.0426 | loss(pos) 0.2074 | loss(seq) 0.0079 | grad 7.0335 | lr 0.0000 | time_forward 3.6090 | time_backward 4.6160 |
[2023-10-22 16:08:20,636::train::INFO] [train] Iter 559400 | loss 2.3613 | loss(rot) 1.7320 | loss(pos) 0.1950 | loss(seq) 0.4343 | grad 3.7748 | lr 0.0000 | time_forward 1.3020 | time_backward 1.4980 |
[2023-10-22 16:08:28,550::train::INFO] [train] Iter 559401 | loss 0.3420 | loss(rot) 0.1482 | loss(pos) 0.0362 | loss(seq) 0.1577 | grad 3.9204 | lr 0.0000 | time_forward 3.3650 | time_backward 4.5450 |
[2023-10-22 16:08:38,242::train::INFO] [train] Iter 559402 | loss 0.3765 | loss(rot) 0.1796 | loss(pos) 0.0683 | loss(seq) 0.1286 | grad 3.1484 | lr 0.0000 | time_forward 3.9470 | time_backward 5.7410 |
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