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[2023-10-22 22:29:34,753::train::INFO] [train] Iter 562690 | loss 0.1907 | loss(rot) 0.1252 | loss(pos) 0.0159 | loss(seq) 0.0497 | grad 3.0027 | lr 0.0000 | time_forward 1.3470 | time_backward 1.4990 |
[2023-10-22 22:29:37,312::train::INFO] [train] Iter 562691 | loss 0.6576 | loss(rot) 0.1796 | loss(pos) 0.1848 | loss(seq) 0.2932 | grad 3.3869 | lr 0.0000 | time_forward 1.3100 | time_backward 1.2370 |
[2023-10-22 22:29:46,028::train::INFO] [train] Iter 562692 | loss 0.5195 | loss(rot) 0.2119 | loss(pos) 0.0127 | loss(seq) 0.2949 | grad 5.9214 | lr 0.0000 | time_forward 4.2310 | time_backward 4.4820 |
[2023-10-22 22:29:54,105::train::INFO] [train] Iter 562693 | loss 1.4594 | loss(rot) 0.7133 | loss(pos) 0.1771 | loss(seq) 0.5690 | grad 6.2663 | lr 0.0000 | time_forward 3.8260 | time_backward 4.2480 |
[2023-10-22 22:30:01,803::train::INFO] [train] Iter 562694 | loss 0.3566 | loss(rot) 0.1421 | loss(pos) 0.0418 | loss(seq) 0.1727 | grad 2.2661 | lr 0.0000 | time_forward 3.3440 | time_backward 4.3520 |
[2023-10-22 22:30:05,001::train::INFO] [train] Iter 562695 | loss 3.7527 | loss(rot) 0.0284 | loss(pos) 3.7243 | loss(seq) 0.0000 | grad 17.8528 | lr 0.0000 | time_forward 1.5460 | time_backward 1.6480 |
[2023-10-22 22:30:13,896::train::INFO] [train] Iter 562696 | loss 0.7874 | loss(rot) 0.2089 | loss(pos) 0.5013 | loss(seq) 0.0772 | grad 4.3216 | lr 0.0000 | time_forward 4.0630 | time_backward 4.8220 |
[2023-10-22 22:30:23,171::train::INFO] [train] Iter 562697 | loss 0.4499 | loss(rot) 0.4245 | loss(pos) 0.0165 | loss(seq) 0.0089 | grad 2.9644 | lr 0.0000 | time_forward 3.9910 | time_backward 5.2810 |
[2023-10-22 22:30:25,975::train::INFO] [train] Iter 562698 | loss 0.1433 | loss(rot) 0.1160 | loss(pos) 0.0173 | loss(seq) 0.0100 | grad 1.9963 | lr 0.0000 | time_forward 1.3090 | time_backward 1.4910 |
[2023-10-22 22:30:28,941::train::INFO] [train] Iter 562699 | loss 2.9123 | loss(rot) 0.0046 | loss(pos) 2.9077 | loss(seq) 0.0000 | grad 18.7022 | lr 0.0000 | time_forward 1.4830 | time_backward 1.4780 |
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