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[2023-10-23 06:02:20,950::train::INFO] [train] Iter 567185 | loss 0.2196 | loss(rot) 0.1382 | loss(pos) 0.0390 | loss(seq) 0.0423 | grad 2.4537 | lr 0.0000 | time_forward 1.2560 | time_backward 1.3980 |
[2023-10-23 06:02:27,179::train::INFO] [train] Iter 567186 | loss 1.7081 | loss(rot) 1.3360 | loss(pos) 0.0344 | loss(seq) 0.3377 | grad 4.8909 | lr 0.0000 | time_forward 2.7080 | time_backward 3.5170 |
[2023-10-23 06:02:29,849::train::INFO] [train] Iter 567187 | loss 2.2056 | loss(rot) 1.3549 | loss(pos) 0.1405 | loss(seq) 0.7102 | grad 5.8294 | lr 0.0000 | time_forward 1.2570 | time_backward 1.4100 |
[2023-10-23 06:02:32,546::train::INFO] [train] Iter 567188 | loss 0.2868 | loss(rot) 0.0203 | loss(pos) 0.2638 | loss(seq) 0.0027 | grad 6.6209 | lr 0.0000 | time_forward 1.2940 | time_backward 1.4010 |
[2023-10-23 06:02:35,246::train::INFO] [train] Iter 567189 | loss 0.4434 | loss(rot) 0.0999 | loss(pos) 0.0303 | loss(seq) 0.3133 | grad 2.2137 | lr 0.0000 | time_forward 1.2940 | time_backward 1.4020 |
[2023-10-23 06:02:39,483::train::INFO] [train] Iter 567190 | loss 0.2741 | loss(rot) 0.1524 | loss(pos) 0.0244 | loss(seq) 0.0973 | grad 2.9906 | lr 0.0000 | time_forward 1.9470 | time_backward 2.2870 |
[2023-10-23 06:02:46,199::train::INFO] [train] Iter 567191 | loss 0.7572 | loss(rot) 0.7039 | loss(pos) 0.0532 | loss(seq) 0.0000 | grad 3.4530 | lr 0.0000 | time_forward 2.8470 | time_backward 3.8660 |
[2023-10-23 06:02:53,647::train::INFO] [train] Iter 567192 | loss 0.6148 | loss(rot) 0.4703 | loss(pos) 0.0267 | loss(seq) 0.1179 | grad 4.1522 | lr 0.0000 | time_forward 3.2590 | time_backward 4.1850 |
[2023-10-23 06:02:56,733::train::INFO] [train] Iter 567193 | loss 0.6538 | loss(rot) 0.6060 | loss(pos) 0.0269 | loss(seq) 0.0209 | grad 31.0870 | lr 0.0000 | time_forward 1.4090 | time_backward 1.6740 |
[2023-10-23 06:03:03,573::train::INFO] [train] Iter 567194 | loss 0.7955 | loss(rot) 0.7807 | loss(pos) 0.0127 | loss(seq) 0.0022 | grad 11.3772 | lr 0.0000 | time_forward 2.9790 | time_backward 3.8580 |
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