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[2023-10-22 17:42:40,978::train::INFO] [train] Iter 560192 | loss 0.6924 | loss(rot) 0.2764 | loss(pos) 0.3127 | loss(seq) 0.1033 | grad 3.3541 | lr 0.0000 | time_forward 3.9010 | time_backward 5.1950 |
[2023-10-22 17:42:49,632::train::INFO] [train] Iter 560193 | loss 0.4200 | loss(rot) 0.1963 | loss(pos) 0.1239 | loss(seq) 0.0997 | grad 3.0864 | lr 0.0000 | time_forward 3.7270 | time_backward 4.9240 |
[2023-10-22 17:42:52,006::train::INFO] [train] Iter 560194 | loss 2.1509 | loss(rot) 1.7853 | loss(pos) 0.2563 | loss(seq) 0.1093 | grad 10.8338 | lr 0.0000 | time_forward 1.0910 | time_backward 1.2790 |
[2023-10-22 17:42:54,996::train::INFO] [train] Iter 560195 | loss 0.5803 | loss(rot) 0.2219 | loss(pos) 0.1262 | loss(seq) 0.2321 | grad 2.6726 | lr 0.0000 | time_forward 1.3830 | time_backward 1.6030 |
[2023-10-22 17:43:04,570::train::INFO] [train] Iter 560196 | loss 1.5899 | loss(rot) 1.5031 | loss(pos) 0.0589 | loss(seq) 0.0279 | grad 2.9645 | lr 0.0000 | time_forward 4.0810 | time_backward 5.4880 |
[2023-10-22 17:43:14,536::train::INFO] [train] Iter 560197 | loss 0.0853 | loss(rot) 0.0452 | loss(pos) 0.0285 | loss(seq) 0.0116 | grad 1.4131 | lr 0.0000 | time_forward 3.8100 | time_backward 6.1520 |
[2023-10-22 17:43:17,351::train::INFO] [train] Iter 560198 | loss 0.2121 | loss(rot) 0.0303 | loss(pos) 0.1804 | loss(seq) 0.0014 | grad 4.0351 | lr 0.0000 | time_forward 1.3600 | time_backward 1.4510 |
[2023-10-22 17:43:19,674::train::INFO] [train] Iter 560199 | loss 1.1941 | loss(rot) 0.0045 | loss(pos) 1.1894 | loss(seq) 0.0002 | grad 17.4199 | lr 0.0000 | time_forward 1.0910 | time_backward 1.2280 |
[2023-10-22 17:43:22,611::train::INFO] [train] Iter 560200 | loss 1.6353 | loss(rot) 1.5880 | loss(pos) 0.0164 | loss(seq) 0.0309 | grad 2.4413 | lr 0.0000 | time_forward 1.3710 | time_backward 1.5630 |
[2023-10-22 17:43:31,975::train::INFO] [train] Iter 560201 | loss 0.3232 | loss(rot) 0.0707 | loss(pos) 0.2458 | loss(seq) 0.0067 | grad 7.5457 | lr 0.0000 | time_forward 3.9870 | time_backward 5.3350 |
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