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[2023-10-24 18:23:18,459::train::INFO] [train] Iter 586367 | loss 1.3041 | loss(rot) 1.2115 | loss(pos) 0.0419 | loss(seq) 0.0507 | grad 3.5902 | lr 0.0000 | time_forward 3.8330 | time_backward 5.1000 |
[2023-10-24 18:23:27,016::train::INFO] [train] Iter 586368 | loss 1.5807 | loss(rot) 1.0891 | loss(pos) 0.1567 | loss(seq) 0.3349 | grad 4.0503 | lr 0.0000 | time_forward 3.5550 | time_backward 4.9980 |
[2023-10-24 18:23:34,750::train::INFO] [train] Iter 586369 | loss 0.3204 | loss(rot) 0.0991 | loss(pos) 0.1785 | loss(seq) 0.0428 | grad 3.5559 | lr 0.0000 | time_forward 3.3100 | time_backward 4.4210 |
[2023-10-24 18:23:42,022::train::INFO] [train] Iter 586370 | loss 0.2335 | loss(rot) 0.0530 | loss(pos) 0.0232 | loss(seq) 0.1573 | grad 2.1012 | lr 0.0000 | time_forward 3.1060 | time_backward 4.1630 |
[2023-10-24 18:23:49,821::train::INFO] [train] Iter 586371 | loss 0.2042 | loss(rot) 0.1827 | loss(pos) 0.0154 | loss(seq) 0.0061 | grad 2.2316 | lr 0.0000 | time_forward 3.3100 | time_backward 4.4850 |
[2023-10-24 18:23:52,634::train::INFO] [train] Iter 586372 | loss 0.1975 | loss(rot) 0.0750 | loss(pos) 0.0072 | loss(seq) 0.1152 | grad 1.9204 | lr 0.0000 | time_forward 1.3340 | time_backward 1.4760 |
[2023-10-24 18:23:58,188::train::INFO] [train] Iter 586373 | loss 0.2065 | loss(rot) 0.1641 | loss(pos) 0.0209 | loss(seq) 0.0215 | grad 2.5372 | lr 0.0000 | time_forward 2.4080 | time_backward 3.1440 |
[2023-10-24 18:24:00,913::train::INFO] [train] Iter 586374 | loss 0.7594 | loss(rot) 0.6041 | loss(pos) 0.0335 | loss(seq) 0.1218 | grad 2.5932 | lr 0.0000 | time_forward 1.2880 | time_backward 1.4180 |
[2023-10-24 18:24:08,863::train::INFO] [train] Iter 586375 | loss 0.8628 | loss(rot) 0.0593 | loss(pos) 0.1110 | loss(seq) 0.6926 | grad 4.2741 | lr 0.0000 | time_forward 3.4190 | time_backward 4.5000 |
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