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[2023-09-02 18:04:07,769::train::INFO] [train] Iter 12774 | loss 1.5595 | loss(rot) 0.0998 | loss(pos) 1.4539 | loss(seq) 0.0058 | grad 3.4882 | lr 0.0010 | time_forward 4.2290 | time_backward 5.9970 |
[2023-09-02 18:04:11,172::train::INFO] [train] Iter 12775 | loss 0.8621 | loss(rot) 0.1622 | loss(pos) 0.4889 | loss(seq) 0.2110 | grad 2.8101 | lr 0.0010 | time_forward 1.4320 | time_backward 1.9670 |
[2023-09-02 18:04:20,153::train::INFO] [train] Iter 12776 | loss 1.4771 | loss(rot) 1.2698 | loss(pos) 0.1764 | loss(seq) 0.0310 | grad 4.9956 | lr 0.0010 | time_forward 3.9490 | time_backward 5.0300 |
[2023-09-02 18:04:22,862::train::INFO] [train] Iter 12777 | loss 2.2685 | loss(rot) 1.5144 | loss(pos) 0.3179 | loss(seq) 0.4363 | grad 3.2259 | lr 0.0010 | time_forward 1.2390 | time_backward 1.4670 |
[2023-09-02 18:04:31,881::train::INFO] [train] Iter 12778 | loss 0.8043 | loss(rot) 0.0803 | loss(pos) 0.7157 | loss(seq) 0.0083 | grad 4.4724 | lr 0.0010 | time_forward 3.7520 | time_backward 5.2310 |
[2023-09-02 18:04:40,647::train::INFO] [train] Iter 12779 | loss 1.1747 | loss(rot) 0.4338 | loss(pos) 0.6702 | loss(seq) 0.0707 | grad 5.8660 | lr 0.0010 | time_forward 3.6180 | time_backward 5.1450 |
[2023-09-02 18:04:50,837::train::INFO] [train] Iter 12780 | loss 1.9303 | loss(rot) 1.0806 | loss(pos) 0.2737 | loss(seq) 0.5759 | grad 4.0227 | lr 0.0010 | time_forward 3.9790 | time_backward 6.2080 |
[2023-09-02 18:05:00,922::train::INFO] [train] Iter 12781 | loss 0.6178 | loss(rot) 0.2546 | loss(pos) 0.3100 | loss(seq) 0.0531 | grad 6.0026 | lr 0.0010 | time_forward 4.0610 | time_backward 6.0200 |
[2023-09-02 18:05:10,463::train::INFO] [train] Iter 12782 | loss 1.7840 | loss(rot) 0.5101 | loss(pos) 0.7801 | loss(seq) 0.4938 | grad 5.3336 | lr 0.0010 | time_forward 3.8610 | time_backward 5.6770 |
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