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[2023-09-03 04:50:34,271::train::INFO] [train] Iter 18168 | loss 1.4348 | loss(rot) 0.4584 | loss(pos) 0.3504 | loss(seq) 0.6259 | grad 3.5588 | lr 0.0010 | time_forward 3.1780 | time_backward 4.2430 |
[2023-09-03 04:50:41,407::train::INFO] [train] Iter 18169 | loss 1.8586 | loss(rot) 0.0325 | loss(pos) 1.8248 | loss(seq) 0.0013 | grad 6.1910 | lr 0.0010 | time_forward 2.8960 | time_backward 4.2380 |
[2023-09-03 04:50:49,882::train::INFO] [train] Iter 18170 | loss 1.2520 | loss(rot) 0.7094 | loss(pos) 0.1234 | loss(seq) 0.4192 | grad 3.9937 | lr 0.0010 | time_forward 3.4530 | time_backward 5.0180 |
[2023-09-03 04:50:57,473::train::INFO] [train] Iter 18171 | loss 0.9765 | loss(rot) 0.3738 | loss(pos) 0.2639 | loss(seq) 0.3388 | grad 4.5638 | lr 0.0010 | time_forward 3.1140 | time_backward 4.4730 |
[2023-09-03 04:51:05,011::train::INFO] [train] Iter 18172 | loss 2.5128 | loss(rot) 2.1557 | loss(pos) 0.2036 | loss(seq) 0.1535 | grad 3.4777 | lr 0.0010 | time_forward 3.2410 | time_backward 4.2930 |
[2023-09-03 04:51:12,773::train::INFO] [train] Iter 18173 | loss 1.1957 | loss(rot) 0.8067 | loss(pos) 0.1321 | loss(seq) 0.2569 | grad 6.9757 | lr 0.0010 | time_forward 3.3730 | time_backward 4.3870 |
[2023-09-03 04:51:21,373::train::INFO] [train] Iter 18174 | loss 1.1866 | loss(rot) 0.3355 | loss(pos) 0.2442 | loss(seq) 0.6070 | grad 4.1519 | lr 0.0010 | time_forward 3.4730 | time_backward 5.1230 |
[2023-09-03 04:51:28,682::train::INFO] [train] Iter 18175 | loss 0.5810 | loss(rot) 0.2918 | loss(pos) 0.2111 | loss(seq) 0.0781 | grad 3.4422 | lr 0.0010 | time_forward 3.0750 | time_backward 4.2310 |
[2023-09-03 04:51:37,223::train::INFO] [train] Iter 18176 | loss 0.7713 | loss(rot) 0.2294 | loss(pos) 0.3760 | loss(seq) 0.1659 | grad 2.3400 | lr 0.0010 | time_forward 3.6130 | time_backward 4.9250 |
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