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[2023-10-25 18:27:05,851::train::INFO] [train] Iter 598953 | loss 0.5779 | loss(rot) 0.1362 | loss(pos) 0.0528 | loss(seq) 0.3889 | grad 2.9522 | lr 0.0000 | time_forward 3.5720 | time_backward 5.0640 |
[2023-10-25 18:27:13,342::train::INFO] [train] Iter 598954 | loss 0.5357 | loss(rot) 0.1233 | loss(pos) 0.1231 | loss(seq) 0.2892 | grad 3.9698 | lr 0.0000 | time_forward 3.2630 | time_backward 4.2260 |
[2023-10-25 18:27:22,066::train::INFO] [train] Iter 598955 | loss 0.1479 | loss(rot) 0.0828 | loss(pos) 0.0154 | loss(seq) 0.0497 | grad 1.6321 | lr 0.0000 | time_forward 3.6170 | time_backward 5.1040 |
[2023-10-25 18:27:24,789::train::INFO] [train] Iter 598956 | loss 0.3414 | loss(rot) 0.0725 | loss(pos) 0.2589 | loss(seq) 0.0100 | grad 4.8870 | lr 0.0000 | time_forward 1.3190 | time_backward 1.4020 |
[2023-10-25 18:27:32,006::train::INFO] [train] Iter 598957 | loss 1.4816 | loss(rot) 1.3581 | loss(pos) 0.0698 | loss(seq) 0.0537 | grad 3.7644 | lr 0.0000 | time_forward 3.0930 | time_backward 4.1200 |
[2023-10-25 18:27:39,353::train::INFO] [train] Iter 598958 | loss 2.1458 | loss(rot) 1.6404 | loss(pos) 0.1221 | loss(seq) 0.3833 | grad 5.1167 | lr 0.0000 | time_forward 3.1240 | time_backward 4.2200 |
[2023-10-25 18:27:47,195::train::INFO] [train] Iter 598959 | loss 2.3738 | loss(rot) 2.1097 | loss(pos) 0.0826 | loss(seq) 0.1815 | grad 5.0131 | lr 0.0000 | time_forward 3.3300 | time_backward 4.5090 |
[2023-10-25 18:27:54,872::train::INFO] [train] Iter 598960 | loss 0.2077 | loss(rot) 0.0741 | loss(pos) 0.0221 | loss(seq) 0.1115 | grad 2.3883 | lr 0.0000 | time_forward 3.3370 | time_backward 4.3370 |
[2023-10-25 18:28:03,614::train::INFO] [train] Iter 598961 | loss 0.6268 | loss(rot) 0.4392 | loss(pos) 0.1220 | loss(seq) 0.0656 | grad 3.3323 | lr 0.0000 | time_forward 3.5710 | time_backward 5.1670 |
[2023-10-25 18:28:06,339::train::INFO] [train] Iter 598962 | loss 1.9899 | loss(rot) 1.3962 | loss(pos) 0.1747 | loss(seq) 0.4189 | grad 4.3454 | lr 0.0000 | time_forward 1.3140 | time_backward 1.4090 |
[2023-10-25 18:28:12,749::train::INFO] [train] Iter 598963 | loss 0.3834 | loss(rot) 0.3020 | loss(pos) 0.0203 | loss(seq) 0.0611 | grad 3.7016 | lr 0.0000 | time_forward 2.7820 | time_backward 3.6240 |
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