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[2023-09-02 16:54:57,081::train::INFO] [train] Iter 12173 | loss 3.5052 | loss(rot) 2.6840 | loss(pos) 0.5206 | loss(seq) 0.3006 | grad 4.6806 | lr 0.0010 | time_forward 3.8550 | time_backward 5.6520 |
[2023-09-02 16:55:04,202::train::INFO] [train] Iter 12174 | loss 2.5394 | loss(rot) 1.3502 | loss(pos) 0.6412 | loss(seq) 0.5479 | grad 7.1597 | lr 0.0010 | time_forward 3.0690 | time_backward 4.0490 |
[2023-09-02 16:55:06,476::train::INFO] [train] Iter 12175 | loss 2.0332 | loss(rot) 1.3433 | loss(pos) 0.2871 | loss(seq) 0.4029 | grad 5.2729 | lr 0.0010 | time_forward 1.0560 | time_backward 1.2140 |
[2023-09-02 16:55:13,691::train::INFO] [train] Iter 12176 | loss 2.2719 | loss(rot) 2.0841 | loss(pos) 0.1538 | loss(seq) 0.0340 | grad 6.3699 | lr 0.0010 | time_forward 3.0470 | time_backward 4.0180 |
[2023-09-02 16:55:17,086::train::INFO] [train] Iter 12177 | loss 1.3416 | loss(rot) 0.5126 | loss(pos) 0.5445 | loss(seq) 0.2844 | grad 2.8973 | lr 0.0010 | time_forward 1.4860 | time_backward 1.9050 |
[2023-09-02 16:55:25,481::train::INFO] [train] Iter 12178 | loss 2.0339 | loss(rot) 1.6943 | loss(pos) 0.2686 | loss(seq) 0.0709 | grad 4.7303 | lr 0.0010 | time_forward 3.5870 | time_backward 4.8060 |
[2023-09-02 16:55:32,040::train::INFO] [train] Iter 12179 | loss 1.9446 | loss(rot) 1.1747 | loss(pos) 0.3299 | loss(seq) 0.4400 | grad 5.2909 | lr 0.0010 | time_forward 2.8190 | time_backward 3.7360 |
[2023-09-02 16:55:36,284::train::INFO] [train] Iter 12180 | loss 2.1944 | loss(rot) 1.2421 | loss(pos) 0.4436 | loss(seq) 0.5086 | grad 5.8014 | lr 0.0010 | time_forward 1.9110 | time_backward 2.3290 |
[2023-09-02 16:55:43,849::train::INFO] [train] Iter 12181 | loss 1.6294 | loss(rot) 0.3926 | loss(pos) 1.0452 | loss(seq) 0.1916 | grad 5.1122 | lr 0.0010 | time_forward 3.1600 | time_backward 4.3650 |
[2023-09-02 16:55:51,960::train::INFO] [train] Iter 12182 | loss 2.2168 | loss(rot) 0.9550 | loss(pos) 0.7575 | loss(seq) 0.5043 | grad 6.7696 | lr 0.0010 | time_forward 3.3570 | time_backward 4.7510 |
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