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[2023-09-02 23:54:48,351::train::INFO] [train] Iter 15570 | loss 1.0437 | loss(rot) 0.5853 | loss(pos) 0.0989 | loss(seq) 0.3595 | grad 3.5279 | lr 0.0010 | time_forward 3.3040 | time_backward 4.7660 |
[2023-09-02 23:54:51,346::train::INFO] [train] Iter 15571 | loss 1.2147 | loss(rot) 0.0223 | loss(pos) 1.1891 | loss(seq) 0.0033 | grad 6.1709 | lr 0.0010 | time_forward 1.3560 | time_backward 1.6340 |
[2023-09-02 23:55:01,881::train::INFO] [train] Iter 15572 | loss 1.3246 | loss(rot) 0.5332 | loss(pos) 0.1644 | loss(seq) 0.6270 | grad 4.3131 | lr 0.0010 | time_forward 4.2530 | time_backward 6.2730 |
[2023-09-02 23:55:09,540::train::INFO] [train] Iter 15573 | loss 1.4630 | loss(rot) 1.1579 | loss(pos) 0.0517 | loss(seq) 0.2533 | grad 5.2765 | lr 0.0010 | time_forward 3.2500 | time_backward 4.4050 |
[2023-09-02 23:55:19,692::train::INFO] [train] Iter 15574 | loss 1.5416 | loss(rot) 1.2272 | loss(pos) 0.0846 | loss(seq) 0.2298 | grad 2.7256 | lr 0.0010 | time_forward 4.2290 | time_backward 5.9200 |
[2023-09-02 23:55:28,914::train::INFO] [train] Iter 15575 | loss 1.1270 | loss(rot) 1.0316 | loss(pos) 0.0864 | loss(seq) 0.0090 | grad 8.6573 | lr 0.0010 | time_forward 3.9120 | time_backward 5.3060 |
[2023-09-02 23:55:31,826::train::INFO] [train] Iter 15576 | loss 0.8065 | loss(rot) 0.7061 | loss(pos) 0.0815 | loss(seq) 0.0189 | grad 6.1113 | lr 0.0010 | time_forward 1.3400 | time_backward 1.5680 |
[2023-09-02 23:55:43,486::train::INFO] [train] Iter 15577 | loss 3.0639 | loss(rot) 2.0803 | loss(pos) 0.4390 | loss(seq) 0.5446 | grad 5.9253 | lr 0.0010 | time_forward 4.7990 | time_backward 6.8580 |
[2023-09-02 23:55:46,397::train::INFO] [train] Iter 15578 | loss 1.2498 | loss(rot) 0.2823 | loss(pos) 0.6064 | loss(seq) 0.3611 | grad 4.8096 | lr 0.0010 | time_forward 1.3470 | time_backward 1.5610 |
[2023-09-02 23:55:49,362::train::INFO] [train] Iter 15579 | loss 0.6870 | loss(rot) 0.5703 | loss(pos) 0.1167 | loss(seq) 0.0000 | grad 3.5043 | lr 0.0010 | time_forward 1.3990 | time_backward 1.5600 |
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