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[2023-09-02 15:51:17,097::train::INFO] [train] Iter 11574 | loss 0.7195 | loss(rot) 0.2424 | loss(pos) 0.4101 | loss(seq) 0.0670 | grad 3.5902 | lr 0.0010 | time_forward 3.2240 | time_backward 4.3850 |
[2023-09-02 15:51:26,099::train::INFO] [train] Iter 11575 | loss 1.8166 | loss(rot) 1.6243 | loss(pos) 0.1903 | loss(seq) 0.0020 | grad 4.3592 | lr 0.0010 | time_forward 3.3860 | time_backward 5.6120 |
[2023-09-02 15:51:34,980::train::INFO] [train] Iter 11576 | loss 2.1205 | loss(rot) 1.2735 | loss(pos) 0.3770 | loss(seq) 0.4700 | grad 6.7863 | lr 0.0010 | time_forward 3.4620 | time_backward 5.4160 |
[2023-09-02 15:51:43,122::train::INFO] [train] Iter 11577 | loss 1.5206 | loss(rot) 1.1709 | loss(pos) 0.3085 | loss(seq) 0.0412 | grad 6.2014 | lr 0.0010 | time_forward 3.4350 | time_backward 4.7040 |
[2023-09-02 15:51:50,700::train::INFO] [train] Iter 11578 | loss 1.0947 | loss(rot) 0.2367 | loss(pos) 0.8231 | loss(seq) 0.0349 | grad 4.6330 | lr 0.0010 | time_forward 3.2590 | time_backward 4.3160 |
[2023-09-02 15:51:58,197::train::INFO] [train] Iter 11579 | loss 1.4840 | loss(rot) 0.7322 | loss(pos) 0.3300 | loss(seq) 0.4218 | grad 3.6533 | lr 0.0010 | time_forward 3.2120 | time_backward 4.2820 |
[2023-09-02 15:52:07,022::train::INFO] [train] Iter 11580 | loss 1.1901 | loss(rot) 0.3429 | loss(pos) 0.3655 | loss(seq) 0.4817 | grad 3.5489 | lr 0.0010 | time_forward 3.6330 | time_backward 5.1890 |
[2023-09-02 15:52:15,270::train::INFO] [train] Iter 11581 | loss 1.6789 | loss(rot) 1.2247 | loss(pos) 0.1045 | loss(seq) 0.3496 | grad 5.1402 | lr 0.0010 | time_forward 3.4730 | time_backward 4.7720 |
[2023-09-02 15:52:23,031::train::INFO] [train] Iter 11582 | loss 2.1082 | loss(rot) 1.9035 | loss(pos) 0.2047 | loss(seq) 0.0000 | grad 5.1943 | lr 0.0010 | time_forward 3.2920 | time_backward 4.4660 |
[2023-09-02 15:52:25,605::train::INFO] [train] Iter 11583 | loss 1.6256 | loss(rot) 1.4318 | loss(pos) 0.1915 | loss(seq) 0.0022 | grad 5.4487 | lr 0.0010 | time_forward 1.1960 | time_backward 1.3740 |
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