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[2023-10-23 07:01:00,081::train::INFO] [train] Iter 567784 | loss 1.2367 | loss(rot) 0.5902 | loss(pos) 0.2224 | loss(seq) 0.4241 | grad 3.0060 | lr 0.0000 | time_forward 3.0000 | time_backward 3.9630 |
[2023-10-23 07:01:06,717::train::INFO] [train] Iter 567785 | loss 0.6129 | loss(rot) 0.5781 | loss(pos) 0.0123 | loss(seq) 0.0225 | grad 86.9383 | lr 0.0000 | time_forward 2.7880 | time_backward 3.8450 |
[2023-10-23 07:01:13,687::train::INFO] [train] Iter 567786 | loss 0.8334 | loss(rot) 0.3546 | loss(pos) 0.0675 | loss(seq) 0.4113 | grad 3.9186 | lr 0.0000 | time_forward 3.0610 | time_backward 3.9070 |
[2023-10-23 07:01:20,761::train::INFO] [train] Iter 567787 | loss 0.5313 | loss(rot) 0.1400 | loss(pos) 0.0374 | loss(seq) 0.3539 | grad 3.1976 | lr 0.0000 | time_forward 3.1130 | time_backward 3.9570 |
[2023-10-23 07:01:23,508::train::INFO] [train] Iter 567788 | loss 0.4143 | loss(rot) 0.2876 | loss(pos) 0.0388 | loss(seq) 0.0879 | grad 30.1334 | lr 0.0000 | time_forward 1.2590 | time_backward 1.4860 |
[2023-10-23 07:01:31,409::train::INFO] [train] Iter 567789 | loss 1.7521 | loss(rot) 1.3092 | loss(pos) 0.0395 | loss(seq) 0.4034 | grad 5.8539 | lr 0.0000 | time_forward 3.2380 | time_backward 4.6600 |
[2023-10-23 07:01:34,223::train::INFO] [train] Iter 567790 | loss 0.3831 | loss(rot) 0.0524 | loss(pos) 0.2584 | loss(seq) 0.0722 | grad 5.6692 | lr 0.0000 | time_forward 1.3070 | time_backward 1.5020 |
[2023-10-23 07:01:36,916::train::INFO] [train] Iter 567791 | loss 1.0316 | loss(rot) 0.7952 | loss(pos) 0.0613 | loss(seq) 0.1752 | grad 4.6908 | lr 0.0000 | time_forward 1.2750 | time_backward 1.3910 |
[2023-10-23 07:01:44,879::train::INFO] [train] Iter 567792 | loss 0.4466 | loss(rot) 0.4063 | loss(pos) 0.0402 | loss(seq) 0.0001 | grad 24.5368 | lr 0.0000 | time_forward 3.2940 | time_backward 4.6520 |
[2023-10-23 07:01:52,215::train::INFO] [train] Iter 567793 | loss 0.3273 | loss(rot) 0.1067 | loss(pos) 0.0359 | loss(seq) 0.1847 | grad 2.4885 | lr 0.0000 | time_forward 3.2120 | time_backward 4.1210 |
[2023-10-23 07:01:59,481::train::INFO] [train] Iter 567794 | loss 0.9607 | loss(rot) 0.5418 | loss(pos) 0.0941 | loss(seq) 0.3248 | grad 3.3995 | lr 0.0000 | time_forward 3.1470 | time_backward 4.1140 |
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