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[2023-10-23 09:28:20,424::train::INFO] [train] Iter 569184 | loss 0.4835 | loss(rot) 0.3077 | loss(pos) 0.0327 | loss(seq) 0.1431 | grad 3.3994 | lr 0.0000 | time_forward 1.3410 | time_backward 1.4680 |
[2023-10-23 09:28:30,124::train::INFO] [train] Iter 569185 | loss 2.3096 | loss(rot) 1.9095 | loss(pos) 0.1279 | loss(seq) 0.2722 | grad 3.0787 | lr 0.0000 | time_forward 4.1180 | time_backward 5.5790 |
[2023-10-23 09:28:32,907::train::INFO] [train] Iter 569186 | loss 0.3867 | loss(rot) 0.3359 | loss(pos) 0.0177 | loss(seq) 0.0331 | grad 2.0598 | lr 0.0000 | time_forward 1.3010 | time_backward 1.4780 |
[2023-10-23 09:28:42,501::train::INFO] [train] Iter 569187 | loss 0.8196 | loss(rot) 0.7366 | loss(pos) 0.0424 | loss(seq) 0.0406 | grad 3.9429 | lr 0.0000 | time_forward 3.9490 | time_backward 5.6420 |
[2023-10-23 09:28:51,066::train::INFO] [train] Iter 569188 | loss 1.5531 | loss(rot) 1.2154 | loss(pos) 0.0404 | loss(seq) 0.2973 | grad 6.8928 | lr 0.0000 | time_forward 3.5610 | time_backward 5.0020 |
[2023-10-23 09:29:00,848::train::INFO] [train] Iter 569189 | loss 0.7576 | loss(rot) 0.1752 | loss(pos) 0.4352 | loss(seq) 0.1472 | grad 4.3895 | lr 0.0000 | time_forward 3.9880 | time_backward 5.7910 |
[2023-10-23 09:29:03,665::train::INFO] [train] Iter 569190 | loss 0.2442 | loss(rot) 0.0505 | loss(pos) 0.0150 | loss(seq) 0.1787 | grad 1.8520 | lr 0.0000 | time_forward 1.3210 | time_backward 1.4930 |
[2023-10-23 09:29:06,436::train::INFO] [train] Iter 569191 | loss 0.3133 | loss(rot) 0.1056 | loss(pos) 0.1768 | loss(seq) 0.0310 | grad 3.7783 | lr 0.0000 | time_forward 1.3440 | time_backward 1.4230 |
[2023-10-23 09:29:09,257::train::INFO] [train] Iter 569192 | loss 0.0763 | loss(rot) 0.0626 | loss(pos) 0.0093 | loss(seq) 0.0044 | grad 1.4639 | lr 0.0000 | time_forward 1.3620 | time_backward 1.4560 |
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