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[2023-10-23 21:49:15,258::train::INFO] [train] Iter 575777 | loss 1.6577 | loss(rot) 1.2424 | loss(pos) 0.0513 | loss(seq) 0.3640 | grad 4.4804 | lr 0.0000 | time_forward 3.9830 | time_backward 5.7570 |
[2023-10-23 21:49:17,949::train::INFO] [train] Iter 575778 | loss 0.4479 | loss(rot) 0.3290 | loss(pos) 0.0128 | loss(seq) 0.1061 | grad 18.1112 | lr 0.0000 | time_forward 1.2610 | time_backward 1.4270 |
[2023-10-23 21:49:20,772::train::INFO] [train] Iter 575779 | loss 1.3466 | loss(rot) 0.9946 | loss(pos) 0.0342 | loss(seq) 0.3178 | grad 4.2132 | lr 0.0000 | time_forward 1.3540 | time_backward 1.4660 |
[2023-10-23 21:49:30,633::train::INFO] [train] Iter 575780 | loss 0.3865 | loss(rot) 0.2495 | loss(pos) 0.0215 | loss(seq) 0.1154 | grad 2.4718 | lr 0.0000 | time_forward 4.0250 | time_backward 5.8320 |
[2023-10-23 21:49:39,676::train::INFO] [train] Iter 575781 | loss 1.2027 | loss(rot) 0.0200 | loss(pos) 1.1798 | loss(seq) 0.0029 | grad 10.0095 | lr 0.0000 | time_forward 3.8130 | time_backward 5.2270 |
[2023-10-23 21:49:47,191::train::INFO] [train] Iter 575782 | loss 0.2093 | loss(rot) 0.0643 | loss(pos) 0.0734 | loss(seq) 0.0716 | grad 3.2026 | lr 0.0000 | time_forward 3.2170 | time_backward 4.2940 |
[2023-10-23 21:49:55,111::train::INFO] [train] Iter 575783 | loss 0.6667 | loss(rot) 0.1192 | loss(pos) 0.0193 | loss(seq) 0.5283 | grad 4.9527 | lr 0.0000 | time_forward 3.3290 | time_backward 4.5880 |
[2023-10-23 21:49:57,857::train::INFO] [train] Iter 575784 | loss 1.1739 | loss(rot) 0.0145 | loss(pos) 1.1577 | loss(seq) 0.0017 | grad 12.4383 | lr 0.0000 | time_forward 1.3240 | time_backward 1.4190 |
[2023-10-23 21:50:00,628::train::INFO] [train] Iter 575785 | loss 0.3757 | loss(rot) 0.1260 | loss(pos) 0.0204 | loss(seq) 0.2293 | grad 1.6467 | lr 0.0000 | time_forward 1.3240 | time_backward 1.4060 |
[2023-10-23 21:50:08,550::train::INFO] [train] Iter 575786 | loss 1.4002 | loss(rot) 0.9627 | loss(pos) 0.1745 | loss(seq) 0.2630 | grad 4.9784 | lr 0.0000 | time_forward 3.3590 | time_backward 4.5590 |
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