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[2023-09-02 17:27:50,299::train::INFO] [train] Iter 12474 | loss 2.8750 | loss(rot) 1.7427 | loss(pos) 0.6369 | loss(seq) 0.4954 | grad 5.5993 | lr 0.0010 | time_forward 3.4410 | time_backward 5.1080 |
[2023-09-02 17:27:57,157::train::INFO] [train] Iter 12475 | loss 1.0764 | loss(rot) 0.0440 | loss(pos) 1.0252 | loss(seq) 0.0071 | grad 5.0241 | lr 0.0010 | time_forward 2.7660 | time_backward 4.0890 |
[2023-09-02 17:27:59,720::train::INFO] [train] Iter 12476 | loss 1.5227 | loss(rot) 0.6459 | loss(pos) 0.5733 | loss(seq) 0.3035 | grad 4.5422 | lr 0.0010 | time_forward 1.1720 | time_backward 1.3870 |
[2023-09-02 17:28:42,482::train::INFO] [train] Iter 12477 | loss 1.8730 | loss(rot) 0.9317 | loss(pos) 0.3943 | loss(seq) 0.5470 | grad 5.4518 | lr 0.0010 | time_forward 32.1380 | time_backward 10.6210 |
[2023-09-02 17:28:50,249::train::INFO] [train] Iter 12478 | loss 1.5424 | loss(rot) 0.0290 | loss(pos) 1.5118 | loss(seq) 0.0015 | grad 4.8099 | lr 0.0010 | time_forward 3.2060 | time_backward 4.5560 |
[2023-09-02 17:28:55,342::train::INFO] [train] Iter 12479 | loss 1.4722 | loss(rot) 0.0454 | loss(pos) 1.4151 | loss(seq) 0.0118 | grad 6.8135 | lr 0.0010 | time_forward 3.4270 | time_backward 1.6500 |
[2023-09-02 17:29:05,761::train::INFO] [train] Iter 12480 | loss 2.5782 | loss(rot) 2.2914 | loss(pos) 0.2865 | loss(seq) 0.0003 | grad 4.4537 | lr 0.0010 | time_forward 4.6020 | time_backward 5.8130 |
[2023-09-02 17:29:19,296::train::INFO] [train] Iter 12481 | loss 1.5130 | loss(rot) 0.9588 | loss(pos) 0.0969 | loss(seq) 0.4572 | grad 3.0809 | lr 0.0010 | time_forward 4.2890 | time_backward 9.2420 |
[2023-09-02 17:29:33,297::train::INFO] [train] Iter 12482 | loss 2.9486 | loss(rot) 2.5907 | loss(pos) 0.3572 | loss(seq) 0.0007 | grad 3.9668 | lr 0.0010 | time_forward 6.6760 | time_backward 7.3200 |
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