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[2023-10-23 14:39:25,481::train::INFO] [train] Iter 571981 | loss 0.7901 | loss(rot) 0.4737 | loss(pos) 0.0509 | loss(seq) 0.2655 | grad 4.2695 | lr 0.0000 | time_forward 1.2870 | time_backward 1.3980 |
[2023-10-23 14:39:28,182::train::INFO] [train] Iter 571982 | loss 0.4240 | loss(rot) 0.2569 | loss(pos) 0.0192 | loss(seq) 0.1478 | grad 5.5247 | lr 0.0000 | time_forward 1.2930 | time_backward 1.4050 |
[2023-10-23 14:39:35,752::train::INFO] [train] Iter 571983 | loss 1.6654 | loss(rot) 1.6113 | loss(pos) 0.0356 | loss(seq) 0.0186 | grad 8.7161 | lr 0.0000 | time_forward 3.2030 | time_backward 4.3520 |
[2023-10-23 14:39:38,792::train::INFO] [train] Iter 571984 | loss 0.8475 | loss(rot) 0.0314 | loss(pos) 0.8146 | loss(seq) 0.0015 | grad 6.8754 | lr 0.0000 | time_forward 1.2800 | time_backward 1.7570 |
[2023-10-23 14:39:47,239::train::INFO] [train] Iter 571985 | loss 0.2347 | loss(rot) 0.1568 | loss(pos) 0.0339 | loss(seq) 0.0440 | grad 2.3900 | lr 0.0000 | time_forward 3.8100 | time_backward 4.6280 |
[2023-10-23 14:39:49,957::train::INFO] [train] Iter 571986 | loss 0.4839 | loss(rot) 0.4413 | loss(pos) 0.0425 | loss(seq) 0.0001 | grad 3.2918 | lr 0.0000 | time_forward 1.2900 | time_backward 1.4240 |
[2023-10-23 14:39:57,117::train::INFO] [train] Iter 571987 | loss 1.6736 | loss(rot) 1.6478 | loss(pos) 0.0257 | loss(seq) 0.0000 | grad 4.0778 | lr 0.0000 | time_forward 2.9700 | time_backward 4.1860 |
[2023-10-23 14:40:04,608::train::INFO] [train] Iter 571988 | loss 0.4926 | loss(rot) 0.0383 | loss(pos) 0.4455 | loss(seq) 0.0089 | grad 9.0088 | lr 0.0000 | time_forward 3.1800 | time_backward 4.3070 |
[2023-10-23 14:40:14,551::train::INFO] [train] Iter 571989 | loss 1.6686 | loss(rot) 1.6502 | loss(pos) 0.0163 | loss(seq) 0.0021 | grad 4.0963 | lr 0.0000 | time_forward 3.9560 | time_backward 5.9850 |
[2023-10-23 14:40:16,929::train::INFO] [train] Iter 571990 | loss 0.3073 | loss(rot) 0.2521 | loss(pos) 0.0209 | loss(seq) 0.0343 | grad 8.3003 | lr 0.0000 | time_forward 1.1580 | time_backward 1.2160 |
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