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[2023-10-24 22:05:26,407::train::INFO] [train] Iter 588263 | loss 2.1883 | loss(rot) 2.0911 | loss(pos) 0.0445 | loss(seq) 0.0527 | grad 3.3139 | lr 0.0000 | time_forward 3.6630 | time_backward 5.0080 |
[2023-10-24 22:05:28,936::train::INFO] [train] Iter 588264 | loss 2.0227 | loss(rot) 1.2443 | loss(pos) 0.3289 | loss(seq) 0.4495 | grad 3.5898 | lr 0.0000 | time_forward 1.2050 | time_backward 1.3210 |
[2023-10-24 22:05:31,714::train::INFO] [train] Iter 588265 | loss 0.3144 | loss(rot) 0.0562 | loss(pos) 0.0798 | loss(seq) 0.1784 | grad 3.2814 | lr 0.0000 | time_forward 1.3180 | time_backward 1.4440 |
[2023-10-24 22:05:35,066::train::INFO] [train] Iter 588266 | loss 0.7524 | loss(rot) 0.2257 | loss(pos) 0.2285 | loss(seq) 0.2982 | grad 3.3249 | lr 0.0000 | time_forward 1.5230 | time_backward 1.8240 |
[2023-10-24 22:05:44,193::train::INFO] [train] Iter 588267 | loss 0.7007 | loss(rot) 0.2752 | loss(pos) 0.0767 | loss(seq) 0.3489 | grad 3.3992 | lr 0.0000 | time_forward 3.8710 | time_backward 5.2540 |
[2023-10-24 22:05:54,129::train::INFO] [train] Iter 588268 | loss 2.2747 | loss(rot) 2.1561 | loss(pos) 0.0466 | loss(seq) 0.0719 | grad 3.0737 | lr 0.0000 | time_forward 4.2000 | time_backward 5.7330 |
[2023-10-24 22:05:56,858::train::INFO] [train] Iter 588269 | loss 0.5913 | loss(rot) 0.2190 | loss(pos) 0.2062 | loss(seq) 0.1661 | grad 2.7489 | lr 0.0000 | time_forward 1.2990 | time_backward 1.4260 |
[2023-10-24 22:05:59,155::train::INFO] [train] Iter 588270 | loss 0.1518 | loss(rot) 0.1243 | loss(pos) 0.0274 | loss(seq) 0.0001 | grad 1.3692 | lr 0.0000 | time_forward 1.0870 | time_backward 1.2070 |
[2023-10-24 22:06:09,063::train::INFO] [train] Iter 588271 | loss 1.3643 | loss(rot) 0.2561 | loss(pos) 0.6191 | loss(seq) 0.4891 | grad 6.7637 | lr 0.0000 | time_forward 4.0470 | time_backward 5.8370 |
[2023-10-24 22:06:17,778::train::INFO] [train] Iter 588272 | loss 0.6320 | loss(rot) 0.5871 | loss(pos) 0.0417 | loss(seq) 0.0032 | grad 2.9510 | lr 0.0000 | time_forward 3.6700 | time_backward 5.0430 |
[2023-10-24 22:06:20,501::train::INFO] [train] Iter 588273 | loss 0.2287 | loss(rot) 0.0796 | loss(pos) 0.1225 | loss(seq) 0.0267 | grad 2.9815 | lr 0.0000 | time_forward 1.3080 | time_backward 1.4110 |
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