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[2023-10-22 17:18:43,007::train::INFO] [train] Iter 559993 | loss 0.5442 | loss(rot) 0.4897 | loss(pos) 0.0297 | loss(seq) 0.0248 | grad 1.9245 | lr 0.0000 | time_forward 4.1280 | time_backward 5.5590
[2023-10-22 17:18:45,748::train::INFO] [train] Iter 559994 | loss 0.5704 | loss(rot) 0.4338 | loss(pos) 0.0122 | loss(seq) 0.1245 | grad 4.4962 | lr 0.0000 | time_forward 1.3330 | time_backward 1.4040
[2023-10-22 17:18:54,315::train::INFO] [train] Iter 559995 | loss 0.6284 | loss(rot) 0.0398 | loss(pos) 0.5866 | loss(seq) 0.0020 | grad 7.1636 | lr 0.0000 | time_forward 3.7750 | time_backward 4.7670
[2023-10-22 17:18:57,111::train::INFO] [train] Iter 559996 | loss 0.4462 | loss(rot) 0.1271 | loss(pos) 0.0655 | loss(seq) 0.2536 | grad 2.4641 | lr 0.0000 | time_forward 1.3320 | time_backward 1.4600
[2023-10-22 17:19:05,642::train::INFO] [train] Iter 559997 | loss 0.5516 | loss(rot) 0.2542 | loss(pos) 0.1181 | loss(seq) 0.1794 | grad 2.6162 | lr 0.0000 | time_forward 3.7840 | time_backward 4.7450
[2023-10-22 17:19:14,258::train::INFO] [train] Iter 559998 | loss 0.4652 | loss(rot) 0.3589 | loss(pos) 0.0351 | loss(seq) 0.0713 | grad 2.5600 | lr 0.0000 | time_forward 3.5860 | time_backward 5.0230
[2023-10-22 17:19:17,930::train::INFO] [train] Iter 559999 | loss 1.4018 | loss(rot) 0.6815 | loss(pos) 0.2614 | loss(seq) 0.4589 | grad 2.4495 | lr 0.0000 | time_forward 1.6300 | time_backward 2.0390
[2023-10-22 17:19:26,535::train::INFO] [train] Iter 560000 | loss 0.2019 | loss(rot) 0.0713 | loss(pos) 0.1016 | loss(seq) 0.0291 | grad 2.7609 | lr 0.0000 | time_forward 3.5150 | time_backward 5.0760
[2023-10-22 17:20:20,605::train::INFO] [val] Iter 560000 | loss 1.2984 | loss(rot) 0.8425 | loss(pos) 0.1686 | loss(seq) 0.2872
[2023-10-22 17:20:28,945::train::INFO] [train] Iter 560001 | loss 0.2895 | loss(rot) 0.2398 | loss(pos) 0.0220 | loss(seq) 0.0276 | grad 2.9628 | lr 0.0000 | time_forward 3.3940 | time_backward 4.5620