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[2023-10-23 21:00:21,248::train::INFO] [train] Iter 575378 | loss 0.7330 | loss(rot) 0.5550 | loss(pos) 0.0597 | loss(seq) 0.1183 | grad 4.5066 | lr 0.0000 | time_forward 3.0550 | time_backward 3.9250 |
[2023-10-23 21:00:23,821::train::INFO] [train] Iter 575379 | loss 0.5130 | loss(rot) 0.4640 | loss(pos) 0.0249 | loss(seq) 0.0241 | grad 3.9059 | lr 0.0000 | time_forward 1.2200 | time_backward 1.3490 |
[2023-10-23 21:00:32,704::train::INFO] [train] Iter 575380 | loss 1.4784 | loss(rot) 1.3785 | loss(pos) 0.0496 | loss(seq) 0.0503 | grad 3.1280 | lr 0.0000 | time_forward 2.7300 | time_backward 6.1490 |
[2023-10-23 21:00:47,838::train::INFO] [train] Iter 575381 | loss 0.9661 | loss(rot) 0.4929 | loss(pos) 0.0296 | loss(seq) 0.4437 | grad 3.6541 | lr 0.0000 | time_forward 10.8190 | time_backward 4.3110 |
[2023-10-23 21:00:58,191::train::INFO] [train] Iter 575382 | loss 0.1402 | loss(rot) 0.0565 | loss(pos) 0.0720 | loss(seq) 0.0117 | grad 1.9482 | lr 0.0000 | time_forward 5.3370 | time_backward 5.0120 |
[2023-10-23 21:01:08,148::train::INFO] [train] Iter 575383 | loss 0.5408 | loss(rot) 0.0691 | loss(pos) 0.1310 | loss(seq) 0.3407 | grad 2.2771 | lr 0.0000 | time_forward 4.3630 | time_backward 5.5910 |
[2023-10-23 21:01:16,495::train::INFO] [train] Iter 575384 | loss 0.5946 | loss(rot) 0.5520 | loss(pos) 0.0201 | loss(seq) 0.0225 | grad 6.1979 | lr 0.0000 | time_forward 3.5660 | time_backward 4.7780 |
[2023-10-23 21:01:23,624::train::INFO] [train] Iter 575385 | loss 1.4226 | loss(rot) 1.0914 | loss(pos) 0.0439 | loss(seq) 0.2873 | grad 4.3900 | lr 0.0000 | time_forward 3.1010 | time_backward 4.0240 |
[2023-10-23 21:01:30,701::train::INFO] [train] Iter 575386 | loss 0.5806 | loss(rot) 0.5510 | loss(pos) 0.0268 | loss(seq) 0.0028 | grad 1.9000 | lr 0.0000 | time_forward 3.1650 | time_backward 3.9090 |
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