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[2023-09-02 16:21:48,488::train::INFO] [train] Iter 11874 | loss 1.5813 | loss(rot) 0.3492 | loss(pos) 0.7239 | loss(seq) 0.5081 | grad 4.9688 | lr 0.0010 | time_forward 3.4360 | time_backward 5.2160 |
[2023-09-02 16:21:57,081::train::INFO] [train] Iter 11875 | loss 0.6145 | loss(rot) 0.0971 | loss(pos) 0.4987 | loss(seq) 0.0187 | grad 3.0287 | lr 0.0010 | time_forward 3.5160 | time_backward 5.0740 |
[2023-09-02 16:22:05,054::train::INFO] [train] Iter 11876 | loss 1.2730 | loss(rot) 0.3937 | loss(pos) 0.8507 | loss(seq) 0.0286 | grad 6.0943 | lr 0.0010 | time_forward 3.3210 | time_backward 4.6400 |
[2023-09-02 16:22:13,607::train::INFO] [train] Iter 11877 | loss 1.5513 | loss(rot) 0.6997 | loss(pos) 0.4858 | loss(seq) 0.3658 | grad 3.5930 | lr 0.0010 | time_forward 3.5970 | time_backward 4.9530 |
[2023-09-02 16:22:21,748::train::INFO] [train] Iter 11878 | loss 2.7021 | loss(rot) 2.3227 | loss(pos) 0.3791 | loss(seq) 0.0003 | grad 5.0443 | lr 0.0010 | time_forward 3.5240 | time_backward 4.6120 |
[2023-09-02 16:22:30,286::train::INFO] [train] Iter 11879 | loss 1.8775 | loss(rot) 0.8497 | loss(pos) 0.5400 | loss(seq) 0.4879 | grad 5.1509 | lr 0.0010 | time_forward 3.2860 | time_backward 5.2480 |
[2023-09-02 16:22:32,934::train::INFO] [train] Iter 11880 | loss 2.6870 | loss(rot) 2.0423 | loss(pos) 0.4346 | loss(seq) 0.2101 | grad 6.7908 | lr 0.0010 | time_forward 1.2010 | time_backward 1.4450 |
[2023-09-02 16:22:37,737::train::INFO] [train] Iter 11881 | loss 2.5936 | loss(rot) 1.9580 | loss(pos) 0.6186 | loss(seq) 0.0170 | grad 8.9970 | lr 0.0010 | time_forward 2.1080 | time_backward 2.6920 |
[2023-09-02 16:22:46,094::train::INFO] [train] Iter 11882 | loss 0.8550 | loss(rot) 0.3231 | loss(pos) 0.0933 | loss(seq) 0.4385 | grad 2.7519 | lr 0.0010 | time_forward 3.6890 | time_backward 4.6640 |
[2023-09-02 16:22:52,601::train::INFO] [train] Iter 11883 | loss 2.1476 | loss(rot) 1.2298 | loss(pos) 0.3558 | loss(seq) 0.5619 | grad 4.0865 | lr 0.0010 | time_forward 2.6960 | time_backward 3.8080 |
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