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[2023-10-23 12:51:09,927::train::INFO] [train] Iter 570982 | loss 0.2878 | loss(rot) 0.0769 | loss(pos) 0.0195 | loss(seq) 0.1913 | grad 2.1289 | lr 0.0000 | time_forward 3.5830 | time_backward 4.5320 |
[2023-10-23 12:51:12,535::train::INFO] [train] Iter 570983 | loss 2.7151 | loss(rot) 2.2488 | loss(pos) 0.1367 | loss(seq) 0.3296 | grad 5.3327 | lr 0.0000 | time_forward 1.2960 | time_backward 1.3090 |
[2023-10-23 12:51:19,990::train::INFO] [train] Iter 570984 | loss 0.1452 | loss(rot) 0.1148 | loss(pos) 0.0305 | loss(seq) 0.0000 | grad 2.1342 | lr 0.0000 | time_forward 3.1840 | time_backward 4.2680 |
[2023-10-23 12:51:27,984::train::INFO] [train] Iter 570985 | loss 2.3178 | loss(rot) 2.0300 | loss(pos) 0.0747 | loss(seq) 0.2131 | grad 3.8396 | lr 0.0000 | time_forward 3.3590 | time_backward 4.6310 |
[2023-10-23 12:51:31,322::train::INFO] [train] Iter 570986 | loss 0.5717 | loss(rot) 0.5397 | loss(pos) 0.0317 | loss(seq) 0.0003 | grad 3.1560 | lr 0.0000 | time_forward 1.5060 | time_backward 1.8290 |
[2023-10-23 12:51:34,114::train::INFO] [train] Iter 570987 | loss 0.3396 | loss(rot) 0.1897 | loss(pos) 0.0860 | loss(seq) 0.0639 | grad 2.5734 | lr 0.0000 | time_forward 1.3340 | time_backward 1.4430 |
[2023-10-23 12:51:42,511::train::INFO] [train] Iter 570988 | loss 0.5676 | loss(rot) 0.1737 | loss(pos) 0.0403 | loss(seq) 0.3535 | grad 3.2710 | lr 0.0000 | time_forward 3.7160 | time_backward 4.6780 |
[2023-10-23 12:51:51,734::train::INFO] [train] Iter 570989 | loss 0.8281 | loss(rot) 0.3180 | loss(pos) 0.1978 | loss(seq) 0.3123 | grad 3.6413 | lr 0.0000 | time_forward 3.9880 | time_backward 5.2320 |
[2023-10-23 12:52:00,863::train::INFO] [train] Iter 570990 | loss 0.7067 | loss(rot) 0.2823 | loss(pos) 0.0338 | loss(seq) 0.3906 | grad 6.1197 | lr 0.0000 | time_forward 3.8230 | time_backward 5.3030 |
[2023-10-23 12:52:08,869::train::INFO] [train] Iter 570991 | loss 0.3442 | loss(rot) 0.0776 | loss(pos) 0.0144 | loss(seq) 0.2523 | grad 2.2929 | lr 0.0000 | time_forward 3.3230 | time_backward 4.6790 |
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