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[2023-09-02 10:12:13,305::train::INFO] [train] Iter 08777 | loss 2.1598 | loss(rot) 1.3068 | loss(pos) 0.3542 | loss(seq) 0.4988 | grad 3.9703 | lr 0.0010 | time_forward 4.0030 | time_backward 5.8460 |
[2023-09-02 10:12:16,211::train::INFO] [train] Iter 08778 | loss 1.9425 | loss(rot) 0.0270 | loss(pos) 1.9123 | loss(seq) 0.0033 | grad 10.9735 | lr 0.0010 | time_forward 1.4320 | time_backward 1.4710 |
[2023-09-02 10:12:25,881::train::INFO] [train] Iter 08779 | loss 1.2588 | loss(rot) 0.4838 | loss(pos) 0.3360 | loss(seq) 0.4390 | grad 4.0444 | lr 0.0010 | time_forward 4.2070 | time_backward 5.4200 |
[2023-09-02 10:12:35,933::train::INFO] [train] Iter 08780 | loss 2.6400 | loss(rot) 2.4089 | loss(pos) 0.2263 | loss(seq) 0.0048 | grad 5.5797 | lr 0.0010 | time_forward 4.2720 | time_backward 5.7760 |
[2023-09-02 10:12:38,710::train::INFO] [train] Iter 08781 | loss 2.3480 | loss(rot) 2.0365 | loss(pos) 0.3102 | loss(seq) 0.0012 | grad 5.1645 | lr 0.0010 | time_forward 1.2640 | time_backward 1.5110 |
[2023-09-02 10:12:48,821::train::INFO] [train] Iter 08782 | loss 2.0680 | loss(rot) 0.9527 | loss(pos) 0.5454 | loss(seq) 0.5698 | grad 7.7436 | lr 0.0010 | time_forward 4.0650 | time_backward 6.0430 |
[2023-09-02 10:12:57,286::train::INFO] [train] Iter 08783 | loss 1.5827 | loss(rot) 0.9410 | loss(pos) 0.2556 | loss(seq) 0.3861 | grad 4.9023 | lr 0.0010 | time_forward 3.5960 | time_backward 4.8650 |
[2023-09-02 10:12:59,957::train::INFO] [train] Iter 08784 | loss 1.5529 | loss(rot) 0.6392 | loss(pos) 0.5741 | loss(seq) 0.3396 | grad 5.7274 | lr 0.0010 | time_forward 1.2600 | time_backward 1.4080 |
[2023-09-02 10:13:07,637::train::INFO] [train] Iter 08785 | loss 1.8112 | loss(rot) 1.4573 | loss(pos) 0.3353 | loss(seq) 0.0186 | grad 5.8722 | lr 0.0010 | time_forward 3.2920 | time_backward 4.3820 |
[2023-09-02 10:13:11,092::train::INFO] [train] Iter 08786 | loss 2.1767 | loss(rot) 1.0585 | loss(pos) 0.7131 | loss(seq) 0.4051 | grad 3.8862 | lr 0.0010 | time_forward 1.5250 | time_backward 1.9260 |
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