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[2023-10-24 18:56:07,033::train::INFO] [train] Iter 586666 | loss 3.5557 | loss(rot) 0.1144 | loss(pos) 3.4412 | loss(seq) 0.0000 | grad 21.3910 | lr 0.0000 | time_forward 1.1500 | time_backward 1.2290 |
[2023-10-24 18:56:25,133::train::INFO] [train] Iter 586667 | loss 0.5300 | loss(rot) 0.1899 | loss(pos) 0.3362 | loss(seq) 0.0039 | grad 5.9773 | lr 0.0000 | time_forward 12.8050 | time_backward 5.2910 |
[2023-10-24 18:56:34,257::train::INFO] [train] Iter 586668 | loss 0.8997 | loss(rot) 0.5241 | loss(pos) 0.1592 | loss(seq) 0.2164 | grad 34.9563 | lr 0.0000 | time_forward 4.0430 | time_backward 5.0780 |
[2023-10-24 18:56:42,487::train::INFO] [train] Iter 586669 | loss 0.6830 | loss(rot) 0.4456 | loss(pos) 0.0246 | loss(seq) 0.2129 | grad 2.7049 | lr 0.0000 | time_forward 3.1970 | time_backward 5.0300 |
[2023-10-24 18:56:50,798::train::INFO] [train] Iter 586670 | loss 0.6439 | loss(rot) 0.0577 | loss(pos) 0.2863 | loss(seq) 0.2999 | grad 7.0133 | lr 0.0000 | time_forward 3.0770 | time_backward 5.2310 |
[2023-10-24 18:56:59,129::train::INFO] [train] Iter 586671 | loss 0.2480 | loss(rot) 0.0777 | loss(pos) 0.0209 | loss(seq) 0.1494 | grad 2.1553 | lr 0.0000 | time_forward 3.5860 | time_backward 4.7410 |
[2023-10-24 18:57:01,924::train::INFO] [train] Iter 586672 | loss 0.2970 | loss(rot) 0.0867 | loss(pos) 0.0552 | loss(seq) 0.1550 | grad 3.3440 | lr 0.0000 | time_forward 1.3370 | time_backward 1.4550 |
[2023-10-24 18:57:09,805::train::INFO] [train] Iter 586673 | loss 1.1263 | loss(rot) 0.3884 | loss(pos) 0.4442 | loss(seq) 0.2937 | grad 4.0237 | lr 0.0000 | time_forward 3.4310 | time_backward 4.4470 |
[2023-10-24 18:57:16,980::train::INFO] [train] Iter 586674 | loss 0.5712 | loss(rot) 0.1694 | loss(pos) 0.1054 | loss(seq) 0.2964 | grad 3.8751 | lr 0.0000 | time_forward 2.9500 | time_backward 4.2210 |
[2023-10-24 18:57:25,940::train::INFO] [train] Iter 586675 | loss 1.1724 | loss(rot) 0.7184 | loss(pos) 0.1284 | loss(seq) 0.3256 | grad 8.0493 | lr 0.0000 | time_forward 3.6820 | time_backward 5.2750 |
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