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[2023-10-23 16:36:40,293::train::INFO] [train] Iter 573078 | loss 0.6863 | loss(rot) 0.2092 | loss(pos) 0.0815 | loss(seq) 0.3956 | grad 3.5042 | lr 0.0000 | time_forward 1.3300 | time_backward 1.4360 |
[2023-10-23 16:36:49,965::train::INFO] [train] Iter 573079 | loss 0.7889 | loss(rot) 0.3600 | loss(pos) 0.1419 | loss(seq) 0.2870 | grad 3.5024 | lr 0.0000 | time_forward 4.3110 | time_backward 5.3560 |
[2023-10-23 16:36:59,860::train::INFO] [train] Iter 573080 | loss 0.4930 | loss(rot) 0.4349 | loss(pos) 0.0194 | loss(seq) 0.0387 | grad 62.8031 | lr 0.0000 | time_forward 4.4270 | time_backward 5.4640 |
[2023-10-23 16:37:04,740::train::INFO] [train] Iter 573081 | loss 0.5327 | loss(rot) 0.0520 | loss(pos) 0.1182 | loss(seq) 0.3624 | grad 2.9834 | lr 0.0000 | time_forward 2.4600 | time_backward 2.4180 |
[2023-10-23 16:37:07,304::train::INFO] [train] Iter 573082 | loss 0.4826 | loss(rot) 0.4450 | loss(pos) 0.0346 | loss(seq) 0.0030 | grad 2.5474 | lr 0.0000 | time_forward 1.1390 | time_backward 1.4220 |
[2023-10-23 16:37:17,083::train::INFO] [train] Iter 573083 | loss 0.6726 | loss(rot) 0.2764 | loss(pos) 0.1067 | loss(seq) 0.2895 | grad 3.0250 | lr 0.0000 | time_forward 4.1450 | time_backward 5.5490 |
[2023-10-23 16:37:25,076::train::INFO] [train] Iter 573084 | loss 0.3318 | loss(rot) 0.2673 | loss(pos) 0.0174 | loss(seq) 0.0471 | grad 9.4332 | lr 0.0000 | time_forward 3.4160 | time_backward 4.5740 |
[2023-10-23 16:37:34,224::train::INFO] [train] Iter 573085 | loss 0.5706 | loss(rot) 0.4509 | loss(pos) 0.0202 | loss(seq) 0.0995 | grad 4.2726 | lr 0.0000 | time_forward 4.1960 | time_backward 4.9480 |
[2023-10-23 16:37:43,542::train::INFO] [train] Iter 573086 | loss 0.4315 | loss(rot) 0.1877 | loss(pos) 0.0567 | loss(seq) 0.1871 | grad 2.3732 | lr 0.0000 | time_forward 3.9100 | time_backward 5.4050 |
[2023-10-23 16:37:52,977::train::INFO] [train] Iter 573087 | loss 0.3751 | loss(rot) 0.3455 | loss(pos) 0.0103 | loss(seq) 0.0192 | grad 3.8692 | lr 0.0000 | time_forward 3.9510 | time_backward 5.4810 |
[2023-10-23 16:38:00,879::train::INFO] [train] Iter 573088 | loss 1.8744 | loss(rot) 1.3829 | loss(pos) 0.0533 | loss(seq) 0.4383 | grad 7.4251 | lr 0.0000 | time_forward 3.3790 | time_backward 4.5200 |
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