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[2023-09-03 03:32:30,391::train::INFO] [train] Iter 17468 | loss 1.2780 | loss(rot) 0.0520 | loss(pos) 1.2150 | loss(seq) 0.0110 | grad 7.4767 | lr 0.0010 | time_forward 1.2250 | time_backward 1.4160 |
[2023-09-03 03:32:39,345::train::INFO] [train] Iter 17469 | loss 2.0921 | loss(rot) 1.6122 | loss(pos) 0.1445 | loss(seq) 0.3354 | grad 3.0122 | lr 0.0010 | time_forward 3.8610 | time_backward 5.0880 |
[2023-09-03 03:32:47,605::train::INFO] [train] Iter 17470 | loss 1.3114 | loss(rot) 0.8228 | loss(pos) 0.1193 | loss(seq) 0.3693 | grad 3.6715 | lr 0.0010 | time_forward 3.5580 | time_backward 4.6990 |
[2023-09-03 03:32:54,325::train::INFO] [train] Iter 17471 | loss 0.8522 | loss(rot) 0.3811 | loss(pos) 0.2290 | loss(seq) 0.2421 | grad 3.6177 | lr 0.0010 | time_forward 2.7320 | time_backward 3.9850 |
[2023-09-03 03:32:56,970::train::INFO] [train] Iter 17472 | loss 1.1379 | loss(rot) 0.4606 | loss(pos) 0.3539 | loss(seq) 0.3233 | grad 4.1559 | lr 0.0010 | time_forward 1.1990 | time_backward 1.4420 |
[2023-09-03 03:33:05,857::train::INFO] [train] Iter 17473 | loss 1.4422 | loss(rot) 1.3517 | loss(pos) 0.0832 | loss(seq) 0.0073 | grad 5.3713 | lr 0.0010 | time_forward 3.6320 | time_backward 5.2530 |
[2023-09-03 03:33:08,622::train::INFO] [train] Iter 17474 | loss 1.4132 | loss(rot) 0.9866 | loss(pos) 0.0656 | loss(seq) 0.3610 | grad 4.3415 | lr 0.0010 | time_forward 1.3300 | time_backward 1.4310 |
[2023-09-03 03:33:17,338::train::INFO] [train] Iter 17475 | loss 0.9051 | loss(rot) 0.8408 | loss(pos) 0.0640 | loss(seq) 0.0004 | grad 3.5368 | lr 0.0010 | time_forward 3.6850 | time_backward 5.0290 |
[2023-09-03 03:33:24,272::train::INFO] [train] Iter 17476 | loss 1.2046 | loss(rot) 0.2255 | loss(pos) 0.5517 | loss(seq) 0.4274 | grad 4.3257 | lr 0.0010 | time_forward 2.8100 | time_backward 4.1210 |
[2023-09-03 03:33:31,798::train::INFO] [train] Iter 17477 | loss 1.0513 | loss(rot) 0.3321 | loss(pos) 0.6487 | loss(seq) 0.0705 | grad 5.4451 | lr 0.0010 | time_forward 3.1440 | time_backward 4.3790 |
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