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[2023-09-03 03:22:00,650::train::INFO] [train] Iter 17369 | loss 0.9153 | loss(rot) 0.3537 | loss(pos) 0.2394 | loss(seq) 0.3222 | grad 4.3319 | lr 0.0010 | time_forward 3.4820 | time_backward 4.7240 |
[2023-09-03 03:22:06,899::train::INFO] [train] Iter 17370 | loss 2.0633 | loss(rot) 0.0302 | loss(pos) 2.0295 | loss(seq) 0.0037 | grad 9.4741 | lr 0.0010 | time_forward 2.7350 | time_backward 3.5110 |
[2023-09-03 03:22:09,550::train::INFO] [train] Iter 17371 | loss 1.2944 | loss(rot) 0.9095 | loss(pos) 0.1211 | loss(seq) 0.2638 | grad 4.6042 | lr 0.0010 | time_forward 1.2110 | time_backward 1.4360 |
[2023-09-03 03:22:18,097::train::INFO] [train] Iter 17372 | loss 0.7494 | loss(rot) 0.2402 | loss(pos) 0.4942 | loss(seq) 0.0150 | grad 3.3383 | lr 0.0010 | time_forward 3.5400 | time_backward 5.0040 |
[2023-09-03 03:22:20,420::train::INFO] [train] Iter 17373 | loss 0.6074 | loss(rot) 0.1244 | loss(pos) 0.4648 | loss(seq) 0.0181 | grad 3.9184 | lr 0.0010 | time_forward 1.0930 | time_backward 1.2260 |
[2023-09-03 03:22:23,088::train::INFO] [train] Iter 17374 | loss 0.4608 | loss(rot) 0.1313 | loss(pos) 0.2441 | loss(seq) 0.0853 | grad 2.2564 | lr 0.0010 | time_forward 1.2420 | time_backward 1.4220 |
[2023-09-03 03:22:30,675::train::INFO] [train] Iter 17375 | loss 2.6949 | loss(rot) 0.0328 | loss(pos) 2.6622 | loss(seq) 0.0000 | grad 10.0144 | lr 0.0010 | time_forward 3.1770 | time_backward 4.4060 |
[2023-09-03 03:22:39,706::train::INFO] [train] Iter 17376 | loss 1.1526 | loss(rot) 0.2494 | loss(pos) 0.8757 | loss(seq) 0.0275 | grad 4.2606 | lr 0.0010 | time_forward 3.6300 | time_backward 5.3980 |
[2023-09-03 03:22:42,436::train::INFO] [train] Iter 17377 | loss 1.0684 | loss(rot) 0.9360 | loss(pos) 0.1323 | loss(seq) 0.0000 | grad 4.4675 | lr 0.0010 | time_forward 1.2450 | time_backward 1.4820 |
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