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[2023-09-02 18:28:22,959::train::INFO] [train] Iter 12973 | loss 1.2870 | loss(rot) 0.3793 | loss(pos) 0.5651 | loss(seq) 0.3426 | grad 3.5501 | lr 0.0010 | time_forward 1.4120 | time_backward 1.9150 |
[2023-09-02 18:28:31,694::train::INFO] [train] Iter 12974 | loss 2.6806 | loss(rot) 2.5954 | loss(pos) 0.0852 | loss(seq) 0.0000 | grad 5.9022 | lr 0.0010 | time_forward 3.7140 | time_backward 5.0190 |
[2023-09-02 18:28:39,907::train::INFO] [train] Iter 12975 | loss 1.5386 | loss(rot) 1.4624 | loss(pos) 0.0751 | loss(seq) 0.0012 | grad 4.6202 | lr 0.0010 | time_forward 3.4670 | time_backward 4.7420 |
[2023-09-02 18:28:42,608::train::INFO] [train] Iter 12976 | loss 3.2297 | loss(rot) 3.0593 | loss(pos) 0.1705 | loss(seq) 0.0000 | grad 4.6514 | lr 0.0010 | time_forward 1.2360 | time_backward 1.4620 |
[2023-09-02 18:28:45,321::train::INFO] [train] Iter 12977 | loss 1.8009 | loss(rot) 0.0172 | loss(pos) 1.7819 | loss(seq) 0.0018 | grad 6.7414 | lr 0.0010 | time_forward 1.2890 | time_backward 1.4210 |
[2023-09-02 18:28:53,552::train::INFO] [train] Iter 12978 | loss 1.6866 | loss(rot) 1.5459 | loss(pos) 0.1406 | loss(seq) 0.0001 | grad 4.4871 | lr 0.0010 | time_forward 3.4470 | time_backward 4.7810 |
[2023-09-02 18:29:02,836::train::INFO] [train] Iter 12979 | loss 2.2095 | loss(rot) 1.9895 | loss(pos) 0.0608 | loss(seq) 0.1593 | grad 5.6409 | lr 0.0010 | time_forward 3.8800 | time_backward 5.4000 |
[2023-09-02 18:29:11,472::train::INFO] [train] Iter 12980 | loss 1.1554 | loss(rot) 0.6016 | loss(pos) 0.2727 | loss(seq) 0.2810 | grad 4.6053 | lr 0.0010 | time_forward 3.7030 | time_backward 4.9300 |
[2023-09-02 18:29:20,456::train::INFO] [train] Iter 12981 | loss 2.2108 | loss(rot) 1.5995 | loss(pos) 0.1442 | loss(seq) 0.4670 | grad 7.1988 | lr 0.0010 | time_forward 3.8020 | time_backward 5.1790 |
[2023-09-02 18:29:28,701::train::INFO] [train] Iter 12982 | loss 1.4874 | loss(rot) 1.4096 | loss(pos) 0.0777 | loss(seq) 0.0001 | grad 11.5403 | lr 0.0010 | time_forward 3.4470 | time_backward 4.7940 |
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