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[2023-10-25 17:10:28,587::train::INFO] [train] Iter 598253 | loss 1.1313 | loss(rot) 0.3519 | loss(pos) 0.3483 | loss(seq) 0.4311 | grad 3.0502 | lr 0.0000 | time_forward 3.5580 | time_backward 4.6140 |
[2023-10-25 17:10:31,337::train::INFO] [train] Iter 598254 | loss 0.2775 | loss(rot) 0.0839 | loss(pos) 0.0841 | loss(seq) 0.1095 | grad 2.2779 | lr 0.0000 | time_forward 1.2650 | time_backward 1.4820 |
[2023-10-25 17:10:38,672::train::INFO] [train] Iter 598255 | loss 0.8993 | loss(rot) 0.3130 | loss(pos) 0.1671 | loss(seq) 0.4192 | grad 4.7631 | lr 0.0000 | time_forward 3.1570 | time_backward 4.1740 |
[2023-10-25 17:10:46,018::train::INFO] [train] Iter 598256 | loss 1.3672 | loss(rot) 0.7059 | loss(pos) 0.4733 | loss(seq) 0.1880 | grad 7.9716 | lr 0.0000 | time_forward 3.1560 | time_backward 4.1860 |
[2023-10-25 17:10:52,825::train::INFO] [train] Iter 598257 | loss 0.5362 | loss(rot) 0.3485 | loss(pos) 0.0233 | loss(seq) 0.1644 | grad 4.1730 | lr 0.0000 | time_forward 2.9010 | time_backward 3.9020 |
[2023-10-25 17:10:55,569::train::INFO] [train] Iter 598258 | loss 0.5727 | loss(rot) 0.4867 | loss(pos) 0.0217 | loss(seq) 0.0643 | grad 3.5001 | lr 0.0000 | time_forward 1.2970 | time_backward 1.4430 |
[2023-10-25 17:11:03,788::train::INFO] [train] Iter 598259 | loss 0.8130 | loss(rot) 0.6630 | loss(pos) 0.0784 | loss(seq) 0.0716 | grad 10.4026 | lr 0.0000 | time_forward 3.5250 | time_backward 4.6900 |
[2023-10-25 17:11:12,176::train::INFO] [train] Iter 598260 | loss 0.4270 | loss(rot) 0.0316 | loss(pos) 0.3879 | loss(seq) 0.0074 | grad 8.8803 | lr 0.0000 | time_forward 3.5310 | time_backward 4.8540 |
[2023-10-25 17:11:19,421::train::INFO] [train] Iter 598261 | loss 0.7202 | loss(rot) 0.1553 | loss(pos) 0.1211 | loss(seq) 0.4437 | grad 4.0202 | lr 0.0000 | time_forward 3.1480 | time_backward 4.0940 |
[2023-10-25 17:11:27,887::train::INFO] [train] Iter 598262 | loss 0.3939 | loss(rot) 0.2882 | loss(pos) 0.0880 | loss(seq) 0.0178 | grad 2.9061 | lr 0.0000 | time_forward 3.5970 | time_backward 4.8670 |
[2023-10-25 17:11:35,422::train::INFO] [train] Iter 598263 | loss 1.0546 | loss(rot) 0.6041 | loss(pos) 0.3031 | loss(seq) 0.1474 | grad 4.6933 | lr 0.0000 | time_forward 3.2390 | time_backward 4.2920 |
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