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[2023-10-23 08:52:13,741::train::INFO] [train] Iter 568883 | loss 1.6347 | loss(rot) 0.9175 | loss(pos) 0.2842 | loss(seq) 0.4330 | grad 9.7182 | lr 0.0000 | time_forward 3.5220 | time_backward 4.5510 |
[2023-10-23 08:52:16,288::train::INFO] [train] Iter 568884 | loss 0.2723 | loss(rot) 0.1370 | loss(pos) 0.0547 | loss(seq) 0.0806 | grad 3.5370 | lr 0.0000 | time_forward 1.2050 | time_backward 1.3390 |
[2023-10-23 08:52:19,017::train::INFO] [train] Iter 568885 | loss 0.2791 | loss(rot) 0.0428 | loss(pos) 0.2333 | loss(seq) 0.0030 | grad 4.4292 | lr 0.0000 | time_forward 1.3390 | time_backward 1.3870 |
[2023-10-23 08:52:25,349::train::INFO] [train] Iter 568886 | loss 0.2641 | loss(rot) 0.2276 | loss(pos) 0.0343 | loss(seq) 0.0021 | grad 2.9393 | lr 0.0000 | time_forward 2.7570 | time_backward 3.5710 |
[2023-10-23 08:52:27,997::train::INFO] [train] Iter 568887 | loss 0.9375 | loss(rot) 0.4933 | loss(pos) 0.1583 | loss(seq) 0.2859 | grad 3.2313 | lr 0.0000 | time_forward 1.2560 | time_backward 1.3890 |
[2023-10-23 08:52:34,937::train::INFO] [train] Iter 568888 | loss 0.3542 | loss(rot) 0.1484 | loss(pos) 0.0283 | loss(seq) 0.1775 | grad 3.0534 | lr 0.0000 | time_forward 2.9870 | time_backward 3.9330 |
[2023-10-23 08:52:43,171::train::INFO] [train] Iter 568889 | loss 0.2458 | loss(rot) 0.0952 | loss(pos) 0.1191 | loss(seq) 0.0314 | grad 2.2851 | lr 0.0000 | time_forward 3.4170 | time_backward 4.8140 |
[2023-10-23 08:52:49,988::train::INFO] [train] Iter 568890 | loss 2.2588 | loss(rot) 1.4309 | loss(pos) 0.4384 | loss(seq) 0.3895 | grad 4.9984 | lr 0.0000 | time_forward 2.8540 | time_backward 3.9600 |
[2023-10-23 08:52:57,497::train::INFO] [train] Iter 568891 | loss 0.3636 | loss(rot) 0.1938 | loss(pos) 0.0316 | loss(seq) 0.1382 | grad 3.4920 | lr 0.0000 | time_forward 3.2780 | time_backward 4.2270 |
[2023-10-23 08:53:05,688::train::INFO] [train] Iter 568892 | loss 1.0988 | loss(rot) 0.7987 | loss(pos) 0.0556 | loss(seq) 0.2446 | grad 3.9555 | lr 0.0000 | time_forward 3.3690 | time_backward 4.8180 |
[2023-10-23 08:53:08,348::train::INFO] [train] Iter 568893 | loss 0.4461 | loss(rot) 0.1261 | loss(pos) 0.0421 | loss(seq) 0.2779 | grad 3.0360 | lr 0.0000 | time_forward 1.2550 | time_backward 1.4010 |
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