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[2023-10-25 03:08:30,958::train::INFO] [train] Iter 590861 | loss 0.2667 | loss(rot) 0.0569 | loss(pos) 0.0322 | loss(seq) 0.1775 | grad 1.9305 | lr 0.0000 | time_forward 3.6150 | time_backward 4.7270 |
[2023-10-25 03:08:40,112::train::INFO] [train] Iter 590862 | loss 1.3199 | loss(rot) 1.1859 | loss(pos) 0.0315 | loss(seq) 0.1025 | grad 4.9799 | lr 0.0000 | time_forward 3.7590 | time_backward 5.3920 |
[2023-10-25 03:08:42,966::train::INFO] [train] Iter 590863 | loss 0.6365 | loss(rot) 0.5937 | loss(pos) 0.0147 | loss(seq) 0.0282 | grad 5.6000 | lr 0.0000 | time_forward 1.3300 | time_backward 1.5210 |
[2023-10-25 03:08:50,654::train::INFO] [train] Iter 590864 | loss 0.4672 | loss(rot) 0.1562 | loss(pos) 0.0687 | loss(seq) 0.2424 | grad 4.0600 | lr 0.0000 | time_forward 3.3230 | time_backward 4.3620 |
[2023-10-25 03:08:53,417::train::INFO] [train] Iter 590865 | loss 0.2516 | loss(rot) 0.0463 | loss(pos) 0.0142 | loss(seq) 0.1911 | grad 1.6832 | lr 0.0000 | time_forward 1.3220 | time_backward 1.4390 |
[2023-10-25 03:09:01,382::train::INFO] [train] Iter 590866 | loss 0.3176 | loss(rot) 0.1953 | loss(pos) 0.0154 | loss(seq) 0.1069 | grad 3.4082 | lr 0.0000 | time_forward 3.3970 | time_backward 4.5640 |
[2023-10-25 03:09:08,126::train::INFO] [train] Iter 590867 | loss 0.9606 | loss(rot) 0.4630 | loss(pos) 0.0734 | loss(seq) 0.4242 | grad 5.3827 | lr 0.0000 | time_forward 2.9140 | time_backward 3.8270 |
[2023-10-25 03:09:16,932::train::INFO] [train] Iter 590868 | loss 0.5354 | loss(rot) 0.0794 | loss(pos) 0.0435 | loss(seq) 0.4125 | grad 4.0237 | lr 0.0000 | time_forward 3.6290 | time_backward 5.1740 |
[2023-10-25 03:09:19,647::train::INFO] [train] Iter 590869 | loss 0.6030 | loss(rot) 0.2101 | loss(pos) 0.0384 | loss(seq) 0.3546 | grad 3.9133 | lr 0.0000 | time_forward 1.2870 | time_backward 1.4250 |
[2023-10-25 03:09:26,746::train::INFO] [train] Iter 590870 | loss 1.5422 | loss(rot) 0.7257 | loss(pos) 0.2639 | loss(seq) 0.5526 | grad 6.5426 | lr 0.0000 | time_forward 2.9940 | time_backward 4.1020 |
[2023-10-25 03:09:35,609::train::INFO] [train] Iter 590871 | loss 0.6127 | loss(rot) 0.1650 | loss(pos) 0.3145 | loss(seq) 0.1332 | grad 3.4240 | lr 0.0000 | time_forward 3.7920 | time_backward 5.0670 |
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