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[2023-10-25 20:02:59,708::train::INFO] [train] Iter 599753 | loss 1.0212 | loss(rot) 0.1867 | loss(pos) 0.7632 | loss(seq) 0.0713 | grad 4.3865 | lr 0.0000 | time_forward 4.1690 | time_backward 6.1210 |
[2023-10-25 20:03:09,929::train::INFO] [train] Iter 599754 | loss 1.2770 | loss(rot) 1.1057 | loss(pos) 0.0461 | loss(seq) 0.1252 | grad 3.6442 | lr 0.0000 | time_forward 4.2160 | time_backward 6.0030 |
[2023-10-25 20:03:20,127::train::INFO] [train] Iter 599755 | loss 1.0027 | loss(rot) 0.0309 | loss(pos) 0.9675 | loss(seq) 0.0044 | grad 8.5277 | lr 0.0000 | time_forward 4.2040 | time_backward 5.9900 |
[2023-10-25 20:03:28,158::train::INFO] [train] Iter 599756 | loss 0.7720 | loss(rot) 0.5665 | loss(pos) 0.0446 | loss(seq) 0.1609 | grad 5.5715 | lr 0.0000 | time_forward 3.4120 | time_backward 4.6160 |
[2023-10-25 20:03:37,433::train::INFO] [train] Iter 599757 | loss 0.3903 | loss(rot) 0.1729 | loss(pos) 0.0429 | loss(seq) 0.1745 | grad 2.9911 | lr 0.0000 | time_forward 3.8620 | time_backward 5.4100 |
[2023-10-25 20:03:46,776::train::INFO] [train] Iter 599758 | loss 0.2562 | loss(rot) 0.0616 | loss(pos) 0.1608 | loss(seq) 0.0338 | grad 3.1108 | lr 0.0000 | time_forward 3.8970 | time_backward 5.4420 |
[2023-10-25 20:03:55,583::train::INFO] [train] Iter 599759 | loss 0.1800 | loss(rot) 0.1138 | loss(pos) 0.0220 | loss(seq) 0.0443 | grad 1.8506 | lr 0.0000 | time_forward 3.6740 | time_backward 5.1310 |
[2023-10-25 20:03:58,381::train::INFO] [train] Iter 599760 | loss 0.4110 | loss(rot) 0.0717 | loss(pos) 0.3129 | loss(seq) 0.0264 | grad 4.8654 | lr 0.0000 | time_forward 1.3240 | time_backward 1.4700 |
[2023-10-25 20:04:08,646::train::INFO] [train] Iter 599761 | loss 0.6918 | loss(rot) 0.3857 | loss(pos) 0.0299 | loss(seq) 0.2762 | grad 2.9019 | lr 0.0000 | time_forward 4.2350 | time_backward 6.0270 |
[2023-10-25 20:04:16,724::train::INFO] [train] Iter 599762 | loss 2.4036 | loss(rot) 1.8692 | loss(pos) 0.2499 | loss(seq) 0.2845 | grad 4.4905 | lr 0.0000 | time_forward 3.3780 | time_backward 4.6980 |
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