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[2023-10-22 18:06:06,280::train::INFO] [train] Iter 560392 | loss 0.1945 | loss(rot) 0.0306 | loss(pos) 0.1526 | loss(seq) 0.0113 | grad 2.2822 | lr 0.0000 | time_forward 4.4110 | time_backward 6.2270 |
[2023-10-22 18:06:14,660::train::INFO] [train] Iter 560393 | loss 1.6738 | loss(rot) 0.6852 | loss(pos) 0.7351 | loss(seq) 0.2536 | grad 3.4656 | lr 0.0000 | time_forward 3.7080 | time_backward 4.6700 |
[2023-10-22 18:06:17,513::train::INFO] [train] Iter 560394 | loss 0.4576 | loss(rot) 0.0964 | loss(pos) 0.0579 | loss(seq) 0.3032 | grad 3.1508 | lr 0.0000 | time_forward 1.4000 | time_backward 1.4500 |
[2023-10-22 18:06:20,350::train::INFO] [train] Iter 560395 | loss 0.4795 | loss(rot) 0.1875 | loss(pos) 0.0981 | loss(seq) 0.1939 | grad 3.9776 | lr 0.0000 | time_forward 1.3440 | time_backward 1.4580 |
[2023-10-22 18:06:23,289::train::INFO] [train] Iter 560396 | loss 1.9114 | loss(rot) 1.4144 | loss(pos) 0.1166 | loss(seq) 0.3804 | grad 15.9575 | lr 0.0000 | time_forward 1.3360 | time_backward 1.5580 |
[2023-10-22 18:06:26,129::train::INFO] [train] Iter 560397 | loss 0.5681 | loss(rot) 0.1116 | loss(pos) 0.1045 | loss(seq) 0.3520 | grad 3.2280 | lr 0.0000 | time_forward 1.3490 | time_backward 1.4880 |
[2023-10-22 18:06:34,353::train::INFO] [train] Iter 560398 | loss 0.7599 | loss(rot) 0.1503 | loss(pos) 0.1396 | loss(seq) 0.4701 | grad 4.1407 | lr 0.0000 | time_forward 3.3000 | time_backward 4.9200 |
[2023-10-22 18:06:44,446::train::INFO] [train] Iter 560399 | loss 1.4978 | loss(rot) 0.9015 | loss(pos) 0.1384 | loss(seq) 0.4580 | grad 3.4184 | lr 0.0000 | time_forward 4.0070 | time_backward 6.0820 |
[2023-10-22 18:06:47,438::train::INFO] [train] Iter 560400 | loss 0.1506 | loss(rot) 0.1217 | loss(pos) 0.0275 | loss(seq) 0.0014 | grad 1.7426 | lr 0.0000 | time_forward 1.4000 | time_backward 1.5870 |
[2023-10-22 18:06:50,426::train::INFO] [train] Iter 560401 | loss 1.7094 | loss(rot) 1.1150 | loss(pos) 0.1298 | loss(seq) 0.4646 | grad 5.7864 | lr 0.0000 | time_forward 1.4970 | time_backward 1.4890 |
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