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[2023-10-23 03:52:21,574::train::INFO] [train] Iter 565886 | loss 0.8052 | loss(rot) 0.5543 | loss(pos) 0.0133 | loss(seq) 0.2375 | grad 7.6161 | lr 0.0000 | time_forward 2.9190 | time_backward 3.8290 |
[2023-10-23 03:52:28,033::train::INFO] [train] Iter 565887 | loss 1.2470 | loss(rot) 0.2973 | loss(pos) 0.9330 | loss(seq) 0.0167 | grad 8.5883 | lr 0.0000 | time_forward 2.7610 | time_backward 3.6950 |
[2023-10-23 03:52:35,200::train::INFO] [train] Iter 565888 | loss 1.2357 | loss(rot) 0.7737 | loss(pos) 0.0857 | loss(seq) 0.3763 | grad 7.0502 | lr 0.0000 | time_forward 2.9920 | time_backward 4.1710 |
[2023-10-23 03:52:37,892::train::INFO] [train] Iter 565889 | loss 0.9534 | loss(rot) 0.5732 | loss(pos) 0.1596 | loss(seq) 0.2206 | grad 3.9849 | lr 0.0000 | time_forward 1.2890 | time_backward 1.3990 |
[2023-10-23 03:52:40,650::train::INFO] [train] Iter 565890 | loss 0.9696 | loss(rot) 0.7139 | loss(pos) 0.0443 | loss(seq) 0.2113 | grad 3.1424 | lr 0.0000 | time_forward 1.3570 | time_backward 1.3990 |
[2023-10-23 03:52:43,365::train::INFO] [train] Iter 565891 | loss 0.3164 | loss(rot) 0.1311 | loss(pos) 0.0519 | loss(seq) 0.1335 | grad 2.5062 | lr 0.0000 | time_forward 1.3060 | time_backward 1.4050 |
[2023-10-23 03:52:46,597::train::INFO] [train] Iter 565892 | loss 1.7354 | loss(rot) 1.1784 | loss(pos) 0.1686 | loss(seq) 0.3883 | grad 3.8985 | lr 0.0000 | time_forward 1.4670 | time_backward 1.7620 |
[2023-10-23 03:52:54,745::train::INFO] [train] Iter 565893 | loss 0.9990 | loss(rot) 0.4675 | loss(pos) 0.0423 | loss(seq) 0.4892 | grad 3.6900 | lr 0.0000 | time_forward 3.3570 | time_backward 4.7880 |
[2023-10-23 03:53:01,617::train::INFO] [train] Iter 565894 | loss 1.2256 | loss(rot) 0.6060 | loss(pos) 0.2294 | loss(seq) 0.3901 | grad 5.6277 | lr 0.0000 | time_forward 3.0760 | time_backward 3.7920 |
[2023-10-23 03:53:09,513::train::INFO] [train] Iter 565895 | loss 1.1705 | loss(rot) 1.1537 | loss(pos) 0.0168 | loss(seq) 0.0001 | grad 3.0287 | lr 0.0000 | time_forward 3.2840 | time_backward 4.6080 |
[2023-10-23 03:53:11,100::train::INFO] [train] Iter 565896 | loss 2.8324 | loss(rot) 1.4152 | loss(pos) 0.8639 | loss(seq) 0.5533 | grad 11.9898 | lr 0.0000 | time_forward 0.7520 | time_backward 0.8320 |
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