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[2023-10-23 10:14:48,100::train::INFO] [train] Iter 569583 | loss 0.3856 | loss(rot) 0.1276 | loss(pos) 0.2382 | loss(seq) 0.0198 | grad 2.4792 | lr 0.0000 | time_forward 2.7660 | time_backward 4.2770 |
[2023-10-23 10:14:50,777::train::INFO] [train] Iter 569584 | loss 0.6845 | loss(rot) 0.0983 | loss(pos) 0.0941 | loss(seq) 0.4920 | grad 3.2749 | lr 0.0000 | time_forward 1.2420 | time_backward 1.4320 |
[2023-10-23 10:14:54,156::train::INFO] [train] Iter 569585 | loss 1.4410 | loss(rot) 1.3727 | loss(pos) 0.0610 | loss(seq) 0.0073 | grad 10.6698 | lr 0.0000 | time_forward 1.5420 | time_backward 1.8280 |
[2023-10-23 10:15:04,316::train::INFO] [train] Iter 569586 | loss 0.6478 | loss(rot) 0.6181 | loss(pos) 0.0225 | loss(seq) 0.0072 | grad 3.4530 | lr 0.0000 | time_forward 6.0190 | time_backward 4.1320 |
[2023-10-23 10:15:13,145::train::INFO] [train] Iter 569587 | loss 0.2270 | loss(rot) 0.1243 | loss(pos) 0.0523 | loss(seq) 0.0504 | grad 2.7294 | lr 0.0000 | time_forward 3.8200 | time_backward 4.9940 |
[2023-10-23 10:15:18,853::train::INFO] [train] Iter 569588 | loss 0.3020 | loss(rot) 0.1623 | loss(pos) 0.0236 | loss(seq) 0.1162 | grad 2.1497 | lr 0.0000 | time_forward 2.4980 | time_backward 3.2060 |
[2023-10-23 10:15:21,437::train::INFO] [train] Iter 569589 | loss 0.4253 | loss(rot) 0.0556 | loss(pos) 0.3161 | loss(seq) 0.0536 | grad 4.8406 | lr 0.0000 | time_forward 1.2630 | time_backward 1.3050 |
[2023-10-23 10:15:26,766::train::INFO] [train] Iter 569590 | loss 0.6423 | loss(rot) 0.0222 | loss(pos) 0.6158 | loss(seq) 0.0042 | grad 6.9394 | lr 0.0000 | time_forward 1.4780 | time_backward 3.8480 |
[2023-10-23 10:15:43,166::train::INFO] [train] Iter 569591 | loss 2.4618 | loss(rot) 1.7970 | loss(pos) 0.3525 | loss(seq) 0.3123 | grad 5.2390 | lr 0.0000 | time_forward 10.7800 | time_backward 5.6060 |
[2023-10-23 10:15:56,847::train::INFO] [train] Iter 569592 | loss 0.3801 | loss(rot) 0.1867 | loss(pos) 0.1581 | loss(seq) 0.0354 | grad 3.7593 | lr 0.0000 | time_forward 7.6640 | time_backward 6.0130 |
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