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[2023-09-02 05:31:47,732::train::INFO] [train] Iter 06479 | loss 2.4916 | loss(rot) 1.7273 | loss(pos) 0.2765 | loss(seq) 0.4878 | grad 2.8628 | lr 0.0010 | time_forward 1.3160 | time_backward 1.4140 |
[2023-09-02 05:31:55,465::train::INFO] [train] Iter 06480 | loss 2.3795 | loss(rot) 1.3867 | loss(pos) 0.4535 | loss(seq) 0.5393 | grad 3.3982 | lr 0.0010 | time_forward 3.1740 | time_backward 4.5550 |
[2023-09-02 05:32:01,138::train::INFO] [train] Iter 06481 | loss 2.0113 | loss(rot) 1.4612 | loss(pos) 0.1310 | loss(seq) 0.4191 | grad 3.4394 | lr 0.0010 | time_forward 2.4190 | time_backward 3.2500 |
[2023-09-02 05:32:10,437::train::INFO] [train] Iter 06482 | loss 1.3920 | loss(rot) 0.7021 | loss(pos) 0.2200 | loss(seq) 0.4699 | grad 2.8439 | lr 0.0010 | time_forward 4.0500 | time_backward 5.2440 |
[2023-09-02 05:32:12,636::train::INFO] [train] Iter 06483 | loss 2.2277 | loss(rot) 1.7909 | loss(pos) 0.1816 | loss(seq) 0.2552 | grad 5.8252 | lr 0.0010 | time_forward 1.0470 | time_backward 1.1480 |
[2023-09-02 05:32:22,697::train::INFO] [train] Iter 06484 | loss 2.4072 | loss(rot) 1.1368 | loss(pos) 0.5681 | loss(seq) 0.7023 | grad 3.0069 | lr 0.0010 | time_forward 4.2860 | time_backward 5.7700 |
[2023-09-02 05:32:32,545::train::INFO] [train] Iter 06485 | loss 1.8889 | loss(rot) 1.0777 | loss(pos) 0.1870 | loss(seq) 0.6242 | grad 3.8641 | lr 0.0010 | time_forward 3.9990 | time_backward 5.8460 |
[2023-09-02 05:32:41,400::train::INFO] [train] Iter 06486 | loss 2.1357 | loss(rot) 1.4480 | loss(pos) 0.1180 | loss(seq) 0.5698 | grad 3.9301 | lr 0.0010 | time_forward 3.8940 | time_backward 4.9580 |
[2023-09-02 05:32:51,442::train::INFO] [train] Iter 06487 | loss 1.2202 | loss(rot) 0.4379 | loss(pos) 0.4195 | loss(seq) 0.3628 | grad 3.3748 | lr 0.0010 | time_forward 4.3260 | time_backward 5.7130 |
[2023-09-02 05:33:00,763::train::INFO] [train] Iter 06488 | loss 2.3424 | loss(rot) 1.7382 | loss(pos) 0.2920 | loss(seq) 0.3123 | grad 5.1348 | lr 0.0010 | time_forward 4.0080 | time_backward 5.3080 |
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