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[2023-09-01 17:34:18,442::train::INFO] [train] Iter 00583 | loss 2.5440 | loss(rot) 0.1116 | loss(pos) 2.3930 | loss(seq) 0.0394 | grad 5.5887 | lr 0.0010 | time_forward 3.7560 | time_backward 6.0430
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[2023-09-01 17:34:24,867::train::INFO] [train] Iter 00584 | loss 2.0438 | loss(rot) 0.3161 | loss(pos) 1.5152 | loss(seq) 0.2125 | grad 3.0452 | lr 0.0010 | time_forward 2.7240 | time_backward 3.6990
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[2023-09-01 17:34:32,703::train::INFO] [train] Iter 00585 | loss 2.2409 | loss(rot) 0.9492 | loss(pos) 1.2105 | loss(seq) 0.0812 | grad 6.3452 | lr 0.0010 | time_forward 3.3440 | time_backward 4.4710
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[2023-09-01 17:34:42,463::train::INFO] [train] Iter 00586 | loss 3.3827 | loss(rot) 0.0033 | loss(pos) 3.3793 | loss(seq) 0.0000 | grad 4.5085 | lr 0.0010 | time_forward 3.8240 | time_backward 5.9330
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[2023-09-01 17:34:49,321::train::INFO] [train] Iter 00587 | loss 3.3951 | loss(rot) 2.4229 | loss(pos) 0.4691 | loss(seq) 0.5031 | grad 4.4163 | lr 0.0010 | time_forward 2.7960 | time_backward 4.0580
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[2023-09-01 17:34:59,598::train::INFO] [train] Iter 00588 | loss 2.9151 | loss(rot) 2.1808 | loss(pos) 0.7085 | loss(seq) 0.0259 | grad 7.4225 | lr 0.0010 | time_forward 4.1820 | time_backward 6.0910
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[2023-09-01 17:35:09,419::train::INFO] [train] Iter 00589 | loss 2.6027 | loss(rot) 1.5410 | loss(pos) 0.5485 | loss(seq) 0.5132 | grad 3.3682 | lr 0.0010 | time_forward 3.8140 | time_backward 6.0030
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[2023-09-01 17:35:11,874::train::INFO] [train] Iter 00590 | loss 2.6105 | loss(rot) 0.8378 | loss(pos) 1.2926 | loss(seq) 0.4801 | grad 6.0872 | lr 0.0010 | time_forward 1.1360 | time_backward 1.3150
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[2023-09-01 17:35:22,123::train::INFO] [train] Iter 00591 | loss 3.6589 | loss(rot) 3.0444 | loss(pos) 0.5238 | loss(seq) 0.0908 | grad 4.5908 | lr 0.0010 | time_forward 4.1000 | time_backward 6.1460
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[2023-09-01 17:35:32,173::train::INFO] [train] Iter 00592 | loss 3.4787 | loss(rot) 3.0870 | loss(pos) 0.3649 | loss(seq) 0.0269 | grad 3.7621 | lr 0.0010 | time_forward 4.2200 | time_backward 5.8260
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[2023-09-01 17:35:35,071::train::INFO] [train] Iter 00593 | loss 2.7965 | loss(rot) 0.2843 | loss(pos) 2.4850 | loss(seq) 0.0272 | grad 5.4681 | lr 0.0010 | time_forward 1.3840 | time_backward 1.5110
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[2023-09-01 17:35:43,376::train::INFO] [train] Iter 00594 | loss 1.6941 | loss(rot) 0.8407 | loss(pos) 0.6907 | loss(seq) 0.1626 | grad 4.7919 | lr 0.0010 | time_forward 3.5430 | time_backward 4.7010
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