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[2023-10-23 22:13:14,663::train::INFO] [train] Iter 575976 | loss 0.1328 | loss(rot) 0.0641 | loss(pos) 0.0687 | loss(seq) 0.0000 | grad 1.7174 | lr 0.0000 | time_forward 3.7940 | time_backward 5.0990 |
[2023-10-23 22:13:17,343::train::INFO] [train] Iter 575977 | loss 1.2894 | loss(rot) 0.5782 | loss(pos) 0.0888 | loss(seq) 0.6223 | grad 3.5557 | lr 0.0000 | time_forward 1.2470 | time_backward 1.4290 |
[2023-10-23 22:13:24,786::train::INFO] [train] Iter 575978 | loss 0.3658 | loss(rot) 0.0825 | loss(pos) 0.0684 | loss(seq) 0.2149 | grad 2.6431 | lr 0.0000 | time_forward 3.1490 | time_backward 4.2920 |
[2023-10-23 22:13:32,714::train::INFO] [train] Iter 575979 | loss 0.3590 | loss(rot) 0.2446 | loss(pos) 0.0307 | loss(seq) 0.0836 | grad 3.7025 | lr 0.0000 | time_forward 3.3120 | time_backward 4.6120 |
[2023-10-23 22:13:40,911::train::INFO] [train] Iter 575980 | loss 0.6312 | loss(rot) 0.2852 | loss(pos) 0.1084 | loss(seq) 0.2375 | grad 3.8848 | lr 0.0000 | time_forward 3.4710 | time_backward 4.7230 |
[2023-10-23 22:13:49,208::train::INFO] [train] Iter 575981 | loss 1.3799 | loss(rot) 0.0128 | loss(pos) 1.3652 | loss(seq) 0.0018 | grad 10.2435 | lr 0.0000 | time_forward 3.4820 | time_backward 4.8120 |
[2023-10-23 22:13:59,178::train::INFO] [train] Iter 575982 | loss 0.9802 | loss(rot) 0.0997 | loss(pos) 0.8778 | loss(seq) 0.0028 | grad 6.8851 | lr 0.0000 | time_forward 4.0650 | time_backward 5.9030 |
[2023-10-23 22:14:01,929::train::INFO] [train] Iter 575983 | loss 0.3366 | loss(rot) 0.1361 | loss(pos) 0.0170 | loss(seq) 0.1835 | grad 2.2873 | lr 0.0000 | time_forward 1.3240 | time_backward 1.4240 |
[2023-10-23 22:14:08,986::train::INFO] [train] Iter 575984 | loss 0.5314 | loss(rot) 0.4935 | loss(pos) 0.0174 | loss(seq) 0.0205 | grad 5.8823 | lr 0.0000 | time_forward 3.0740 | time_backward 3.9790 |
[2023-10-23 22:14:18,132::train::INFO] [train] Iter 575985 | loss 2.6625 | loss(rot) 2.4389 | loss(pos) 0.1693 | loss(seq) 0.0543 | grad 5.0005 | lr 0.0000 | time_forward 3.8500 | time_backward 5.2930 |
[2023-10-23 22:14:26,853::train::INFO] [train] Iter 575986 | loss 0.7567 | loss(rot) 0.3543 | loss(pos) 0.1427 | loss(seq) 0.2597 | grad 3.6400 | lr 0.0000 | time_forward 3.6940 | time_backward 5.0230 |
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