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[2023-10-24 22:28:37,823::train::INFO] [train] Iter 588464 | loss 0.1664 | loss(rot) 0.1115 | loss(pos) 0.0544 | loss(seq) 0.0005 | grad 2.4124 | lr 0.0000 | time_forward 2.8150 | time_backward 3.7540 |
[2023-10-24 22:28:47,218::train::INFO] [train] Iter 588465 | loss 0.2337 | loss(rot) 0.1142 | loss(pos) 0.0390 | loss(seq) 0.0805 | grad 2.1556 | lr 0.0000 | time_forward 3.9220 | time_backward 5.4550 |
[2023-10-24 22:28:57,649::train::INFO] [train] Iter 588466 | loss 1.8385 | loss(rot) 1.1995 | loss(pos) 0.1340 | loss(seq) 0.5050 | grad 18.9726 | lr 0.0000 | time_forward 4.2130 | time_backward 6.2160 |
[2023-10-24 22:29:06,238::train::INFO] [train] Iter 588467 | loss 0.9401 | loss(rot) 0.4072 | loss(pos) 0.4052 | loss(seq) 0.1276 | grad 6.5554 | lr 0.0000 | time_forward 3.5890 | time_backward 4.9960 |
[2023-10-24 22:29:14,536::train::INFO] [train] Iter 588468 | loss 0.5456 | loss(rot) 0.5242 | loss(pos) 0.0182 | loss(seq) 0.0031 | grad 2.0800 | lr 0.0000 | time_forward 3.4460 | time_backward 4.8500 |
[2023-10-24 22:29:25,125::train::INFO] [train] Iter 588469 | loss 2.1004 | loss(rot) 1.5603 | loss(pos) 0.1765 | loss(seq) 0.3635 | grad 3.7952 | lr 0.0000 | time_forward 4.3760 | time_backward 6.2090 |
[2023-10-24 22:29:35,133::train::INFO] [train] Iter 588470 | loss 0.9460 | loss(rot) 0.5379 | loss(pos) 0.0924 | loss(seq) 0.3157 | grad 5.2999 | lr 0.0000 | time_forward 4.0290 | time_backward 5.9760 |
[2023-10-24 22:29:43,925::train::INFO] [train] Iter 588471 | loss 0.2466 | loss(rot) 0.1468 | loss(pos) 0.0227 | loss(seq) 0.0771 | grad 2.6527 | lr 0.0000 | time_forward 3.6740 | time_backward 5.1140 |
[2023-10-24 22:29:52,326::train::INFO] [train] Iter 588472 | loss 0.5912 | loss(rot) 0.4394 | loss(pos) 0.0096 | loss(seq) 0.1422 | grad 2.3159 | lr 0.0000 | time_forward 3.5330 | time_backward 4.8660 |
[2023-10-24 22:30:01,135::train::INFO] [train] Iter 588473 | loss 1.0349 | loss(rot) 0.5873 | loss(pos) 0.0844 | loss(seq) 0.3632 | grad 4.3330 | lr 0.0000 | time_forward 3.6810 | time_backward 5.1250 |
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