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[2023-10-24 21:40:36,321::train::INFO] [train] Iter 588063 | loss 0.5121 | loss(rot) 0.4543 | loss(pos) 0.0577 | loss(seq) 0.0001 | grad 3.4262 | lr 0.0000 | time_forward 3.5050 | time_backward 4.7830 |
[2023-10-24 21:40:46,266::train::INFO] [train] Iter 588064 | loss 0.7747 | loss(rot) 0.5567 | loss(pos) 0.0269 | loss(seq) 0.1911 | grad 4.2205 | lr 0.0000 | time_forward 4.0490 | time_backward 5.8920 |
[2023-10-24 21:40:56,171::train::INFO] [train] Iter 588065 | loss 0.4271 | loss(rot) 0.3560 | loss(pos) 0.0340 | loss(seq) 0.0371 | grad 2.9110 | lr 0.0000 | time_forward 4.0230 | time_backward 5.8790 |
[2023-10-24 21:41:06,096::train::INFO] [train] Iter 588066 | loss 1.0255 | loss(rot) 0.8755 | loss(pos) 0.0564 | loss(seq) 0.0936 | grad 3.8123 | lr 0.0000 | time_forward 4.0180 | time_backward 5.9050 |
[2023-10-24 21:41:16,028::train::INFO] [train] Iter 588067 | loss 0.4503 | loss(rot) 0.0654 | loss(pos) 0.2221 | loss(seq) 0.1628 | grad 3.6862 | lr 0.0000 | time_forward 4.0330 | time_backward 5.8950 |
[2023-10-24 21:41:26,561::train::INFO] [train] Iter 588068 | loss 0.5072 | loss(rot) 0.4549 | loss(pos) 0.0364 | loss(seq) 0.0160 | grad 3.7538 | lr 0.0000 | time_forward 4.6490 | time_backward 5.8820 |
[2023-10-24 21:41:32,452::train::INFO] [train] Iter 588069 | loss 1.4676 | loss(rot) 0.0609 | loss(pos) 1.4044 | loss(seq) 0.0023 | grad 10.4471 | lr 0.0000 | time_forward 2.5480 | time_backward 3.3390 |
[2023-10-24 21:41:35,162::train::INFO] [train] Iter 588070 | loss 0.4681 | loss(rot) 0.1881 | loss(pos) 0.0732 | loss(seq) 0.2069 | grad 2.9759 | lr 0.0000 | time_forward 1.3040 | time_backward 1.4030 |
[2023-10-24 21:41:44,335::train::INFO] [train] Iter 588071 | loss 0.4666 | loss(rot) 0.1692 | loss(pos) 0.0413 | loss(seq) 0.2561 | grad 2.9076 | lr 0.0000 | time_forward 3.9130 | time_backward 5.2570 |
[2023-10-24 21:41:53,160::train::INFO] [train] Iter 588072 | loss 2.3629 | loss(rot) 2.2430 | loss(pos) 0.0221 | loss(seq) 0.0978 | grad 5.2522 | lr 0.0000 | time_forward 3.7480 | time_backward 5.0730 |
[2023-10-24 21:42:03,325::train::INFO] [train] Iter 588073 | loss 0.2926 | loss(rot) 0.0918 | loss(pos) 0.1962 | loss(seq) 0.0046 | grad 3.3811 | lr 0.0000 | time_forward 4.0940 | time_backward 6.0670 |
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