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[2023-10-24 14:53:11,840::train::INFO] [train] Iter 584368 | loss 0.3607 | loss(rot) 0.0593 | loss(pos) 0.0710 | loss(seq) 0.2304 | grad 2.8462 | lr 0.0000 | time_forward 3.5220 | time_backward 5.6660 |
[2023-10-24 14:53:20,174::train::INFO] [train] Iter 584369 | loss 1.2264 | loss(rot) 0.8871 | loss(pos) 0.0646 | loss(seq) 0.2746 | grad 5.6918 | lr 0.0000 | time_forward 3.6030 | time_backward 4.7270 |
[2023-10-24 14:53:22,979::train::INFO] [train] Iter 584370 | loss 0.2768 | loss(rot) 0.0723 | loss(pos) 0.0239 | loss(seq) 0.1806 | grad 2.3144 | lr 0.0000 | time_forward 1.3520 | time_backward 1.4500 |
[2023-10-24 14:53:31,987::train::INFO] [train] Iter 584371 | loss 0.8035 | loss(rot) 0.3594 | loss(pos) 0.1418 | loss(seq) 0.3022 | grad 3.3632 | lr 0.0000 | time_forward 3.6870 | time_backward 5.3190 |
[2023-10-24 14:53:39,243::train::INFO] [train] Iter 584372 | loss 0.7416 | loss(rot) 0.3941 | loss(pos) 0.0796 | loss(seq) 0.2679 | grad 3.6958 | lr 0.0000 | time_forward 3.0920 | time_backward 4.1600 |
[2023-10-24 14:53:42,008::train::INFO] [train] Iter 584373 | loss 0.2817 | loss(rot) 0.0968 | loss(pos) 0.0597 | loss(seq) 0.1252 | grad 2.6467 | lr 0.0000 | time_forward 1.3270 | time_backward 1.4340 |
[2023-10-24 14:53:50,258::train::INFO] [train] Iter 584374 | loss 1.2431 | loss(rot) 0.1359 | loss(pos) 1.1029 | loss(seq) 0.0043 | grad 12.2415 | lr 0.0000 | time_forward 3.5680 | time_backward 4.6790 |
[2023-10-24 14:53:52,539::train::INFO] [train] Iter 584375 | loss 0.1761 | loss(rot) 0.0476 | loss(pos) 0.0236 | loss(seq) 0.1050 | grad 1.4112 | lr 0.0000 | time_forward 1.0340 | time_backward 1.2430 |
[2023-10-24 14:53:55,264::train::INFO] [train] Iter 584376 | loss 0.4281 | loss(rot) 0.1246 | loss(pos) 0.0323 | loss(seq) 0.2713 | grad 2.2707 | lr 0.0000 | time_forward 1.2740 | time_backward 1.4480 |
[2023-10-24 14:53:58,003::train::INFO] [train] Iter 584377 | loss 0.3136 | loss(rot) 0.1413 | loss(pos) 0.0193 | loss(seq) 0.1531 | grad 2.4063 | lr 0.0000 | time_forward 1.2900 | time_backward 1.4270 |
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