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[2023-10-24 18:12:41,327::train::INFO] [train] Iter 586267 | loss 1.5199 | loss(rot) 0.8730 | loss(pos) 0.3424 | loss(seq) 0.3046 | grad 7.8643 | lr 0.0000 | time_forward 2.6220 | time_backward 3.3580 |
[2023-10-24 18:12:49,600::train::INFO] [train] Iter 586268 | loss 0.4014 | loss(rot) 0.2372 | loss(pos) 0.0294 | loss(seq) 0.1349 | grad 28.9552 | lr 0.0000 | time_forward 3.3700 | time_backward 4.9000 |
[2023-10-24 18:12:55,990::train::INFO] [train] Iter 586269 | loss 0.5654 | loss(rot) 0.1043 | loss(pos) 0.0455 | loss(seq) 0.4155 | grad 3.0157 | lr 0.0000 | time_forward 2.7300 | time_backward 3.6560 |
[2023-10-24 18:13:02,924::train::INFO] [train] Iter 586270 | loss 0.5512 | loss(rot) 0.0056 | loss(pos) 0.5454 | loss(seq) 0.0002 | grad 9.5876 | lr 0.0000 | time_forward 2.9910 | time_backward 3.9410 |
[2023-10-24 18:13:05,676::train::INFO] [train] Iter 586271 | loss 0.4920 | loss(rot) 0.1087 | loss(pos) 0.1196 | loss(seq) 0.2637 | grad 4.4648 | lr 0.0000 | time_forward 1.2730 | time_backward 1.4750 |
[2023-10-24 18:13:08,135::train::INFO] [train] Iter 586272 | loss 3.3635 | loss(rot) 3.1896 | loss(pos) 0.1182 | loss(seq) 0.0558 | grad 4.8812 | lr 0.0000 | time_forward 1.1730 | time_backward 1.2830 |
[2023-10-24 18:13:10,832::train::INFO] [train] Iter 586273 | loss 0.2594 | loss(rot) 0.0588 | loss(pos) 0.0409 | loss(seq) 0.1598 | grad 2.4503 | lr 0.0000 | time_forward 1.2760 | time_backward 1.4110 |
[2023-10-24 18:13:13,561::train::INFO] [train] Iter 586274 | loss 0.1884 | loss(rot) 0.1560 | loss(pos) 0.0299 | loss(seq) 0.0026 | grad 13.0538 | lr 0.0000 | time_forward 1.2960 | time_backward 1.4160 |
[2023-10-24 18:13:16,262::train::INFO] [train] Iter 586275 | loss 0.2034 | loss(rot) 0.0670 | loss(pos) 0.0839 | loss(seq) 0.0526 | grad 2.7239 | lr 0.0000 | time_forward 1.3110 | time_backward 1.3790 |
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