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[2023-09-02 12:42:34,645::train::INFO] [val] Iter 10000 | loss 2.1276 | loss(rot) 1.2735 | loss(pos) 0.6439 | loss(seq) 0.2102 |
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[2023-09-02 12:50:57,808::train::INFO] [train] Iter 10075 | loss 1.9519 | loss(rot) 0.0679 | loss(pos) 1.6142 | loss(seq) 0.2698 | grad 6.7463 | lr 0.0010 | time_forward 1.2670 | time_backward 1.4730 |
[2023-09-02 12:51:08,047::train::INFO] [train] Iter 10076 | loss 1.8178 | loss(rot) 1.6979 | loss(pos) 0.1100 | loss(seq) 0.0098 | grad 4.5299 | lr 0.0010 | time_forward 4.0660 | time_backward 6.1360 |
[2023-09-02 12:51:18,144::train::INFO] [train] Iter 10077 | loss 2.4079 | loss(rot) 0.3253 | loss(pos) 1.7897 | loss(seq) 0.2930 | grad 5.3024 | lr 0.0010 | time_forward 3.9790 | time_backward 6.1140 |
[2023-09-02 12:51:20,848::train::INFO] [train] Iter 10078 | loss 3.0270 | loss(rot) 2.8431 | loss(pos) 0.1832 | loss(seq) 0.0007 | grad 3.2060 | lr 0.0010 | time_forward 1.2400 | time_backward 1.4600 |
[2023-09-02 12:51:29,593::train::INFO] [train] Iter 10079 | loss 1.3727 | loss(rot) 0.4541 | loss(pos) 0.5470 | loss(seq) 0.3715 | grad 3.1412 | lr 0.0010 | time_forward 3.7110 | time_backward 5.0300 |
[2023-09-02 12:51:32,293::train::INFO] [train] Iter 10080 | loss 1.7917 | loss(rot) 1.5743 | loss(pos) 0.1408 | loss(seq) 0.0765 | grad 7.4840 | lr 0.0010 | time_forward 1.2550 | time_backward 1.4410 |
[2023-09-02 12:51:32,868::train::INFO] [train] Iter 10081 | loss 2.2580 | loss(rot) 1.7120 | loss(pos) 0.3469 | loss(seq) 0.1990 | grad 8.1586 | lr 0.0010 | time_forward 0.2450 | time_backward 0.3270 |
[2023-09-02 12:51:40,996::train::INFO] [train] Iter 10082 | loss 2.0938 | loss(rot) 1.7251 | loss(pos) 0.1833 | loss(seq) 0.1854 | grad 4.5662 | lr 0.0010 | time_forward 3.3670 | time_backward 4.7580 |
[2023-09-02 12:51:49,515::train::INFO] [train] Iter 10083 | loss 2.6638 | loss(rot) 2.1029 | loss(pos) 0.1847 | loss(seq) 0.3762 | grad 6.7482 | lr 0.0010 | time_forward 3.5730 | time_backward 4.9420 |
[2023-09-02 12:51:57,555::train::INFO] [train] Iter 10084 | loss 1.0227 | loss(rot) 0.2163 | loss(pos) 0.7123 | loss(seq) 0.0941 | grad 5.2863 | lr 0.0010 | time_forward 3.3480 | time_backward 4.6880 |
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