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[2023-10-23 14:17:45,586::train::INFO] [train] Iter 571781 | loss 0.2876 | loss(rot) 0.0566 | loss(pos) 0.1849 | loss(seq) 0.0460 | grad 3.8067 | lr 0.0000 | time_forward 3.2960 | time_backward 4.5420 |
[2023-10-23 14:17:53,342::train::INFO] [train] Iter 571782 | loss 0.8521 | loss(rot) 0.0863 | loss(pos) 0.6151 | loss(seq) 0.1506 | grad 5.6385 | lr 0.0000 | time_forward 3.3820 | time_backward 4.3710 |
[2023-10-23 14:18:01,091::train::INFO] [train] Iter 571783 | loss 1.3986 | loss(rot) 0.8601 | loss(pos) 0.1618 | loss(seq) 0.3767 | grad 3.6111 | lr 0.0000 | time_forward 3.4510 | time_backward 4.2950 |
[2023-10-23 14:18:07,777::train::INFO] [train] Iter 571784 | loss 0.1743 | loss(rot) 0.1479 | loss(pos) 0.0231 | loss(seq) 0.0033 | grad 1.8040 | lr 0.0000 | time_forward 2.7660 | time_backward 3.9170 |
[2023-10-23 14:18:14,366::train::INFO] [train] Iter 571785 | loss 0.4373 | loss(rot) 0.0960 | loss(pos) 0.0497 | loss(seq) 0.2916 | grad 2.5090 | lr 0.0000 | time_forward 2.8220 | time_backward 3.7640 |
[2023-10-23 14:18:17,088::train::INFO] [train] Iter 571786 | loss 0.9891 | loss(rot) 0.2424 | loss(pos) 0.1607 | loss(seq) 0.5861 | grad 3.6900 | lr 0.0000 | time_forward 1.2870 | time_backward 1.4330 |
[2023-10-23 14:18:25,256::train::INFO] [train] Iter 571787 | loss 0.2663 | loss(rot) 0.1341 | loss(pos) 0.0432 | loss(seq) 0.0891 | grad 1.6974 | lr 0.0000 | time_forward 3.4390 | time_backward 4.7240 |
[2023-10-23 14:18:31,869::train::INFO] [train] Iter 571788 | loss 0.1010 | loss(rot) 0.0726 | loss(pos) 0.0138 | loss(seq) 0.0146 | grad 1.6027 | lr 0.0000 | time_forward 2.8170 | time_backward 3.7930 |
[2023-10-23 14:18:34,595::train::INFO] [train] Iter 571789 | loss 0.1297 | loss(rot) 0.0888 | loss(pos) 0.0409 | loss(seq) 0.0000 | grad 1.9137 | lr 0.0000 | time_forward 1.2800 | time_backward 1.4430 |
[2023-10-23 14:18:41,945::train::INFO] [train] Iter 571790 | loss 0.3139 | loss(rot) 0.0481 | loss(pos) 0.0657 | loss(seq) 0.2001 | grad 2.3878 | lr 0.0000 | time_forward 3.1780 | time_backward 4.1690 |
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