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[2023-09-01 19:22:35,016::train::INFO] [train] Iter 01483 | loss 2.2437 | loss(rot) 1.3662 | loss(pos) 0.4016 | loss(seq) 0.4759 | grad 3.7350 | lr 0.0010 | time_forward 3.0490 | time_backward 4.7760 |
[2023-09-01 19:22:42,471::train::INFO] [train] Iter 01484 | loss 1.6679 | loss(rot) 0.9280 | loss(pos) 0.3951 | loss(seq) 0.3448 | grad 3.1282 | lr 0.0010 | time_forward 3.0380 | time_backward 4.4130 |
[2023-09-01 19:22:50,668::train::INFO] [train] Iter 01485 | loss 3.6081 | loss(rot) 3.3716 | loss(pos) 0.2160 | loss(seq) 0.0206 | grad 3.6615 | lr 0.0010 | time_forward 3.5200 | time_backward 4.6740 |
[2023-09-01 19:22:52,965::train::INFO] [train] Iter 01486 | loss 2.5424 | loss(rot) 1.6855 | loss(pos) 0.4183 | loss(seq) 0.4386 | grad 2.8492 | lr 0.0010 | time_forward 1.0770 | time_backward 1.2160 |
[2023-09-01 19:22:55,429::train::INFO] [train] Iter 01487 | loss 2.6627 | loss(rot) 1.5578 | loss(pos) 0.5706 | loss(seq) 0.5343 | grad 3.6314 | lr 0.0010 | time_forward 1.1660 | time_backward 1.2940 |
[2023-09-01 19:23:09,862::train::INFO] [train] Iter 01488 | loss 3.1120 | loss(rot) 2.8112 | loss(pos) 0.2405 | loss(seq) 0.0603 | grad 3.4406 | lr 0.0010 | time_forward 3.1120 | time_backward 11.3020 |
[2023-09-01 19:23:13,745::train::INFO] [train] Iter 01489 | loss 2.3877 | loss(rot) 1.0091 | loss(pos) 0.6919 | loss(seq) 0.6867 | grad 4.2734 | lr 0.0010 | time_forward 2.4110 | time_backward 1.4690 |
[2023-09-01 19:24:08,176::train::INFO] [train] Iter 01490 | loss 2.1826 | loss(rot) 1.4817 | loss(pos) 0.1784 | loss(seq) 0.5226 | grad 4.7673 | lr 0.0010 | time_forward 35.3950 | time_backward 19.0330 |
[2023-09-01 19:24:25,450::train::INFO] [train] Iter 01491 | loss 2.6696 | loss(rot) 1.3989 | loss(pos) 0.6529 | loss(seq) 0.6177 | grad 3.8783 | lr 0.0010 | time_forward 12.4800 | time_backward 4.7890 |
[2023-09-01 19:24:35,591::train::INFO] [train] Iter 01492 | loss 2.9822 | loss(rot) 1.8906 | loss(pos) 0.6833 | loss(seq) 0.4082 | grad 5.3153 | lr 0.0010 | time_forward 5.1950 | time_backward 4.9430 |
[2023-09-01 19:24:50,723::train::INFO] [train] Iter 01493 | loss 3.4722 | loss(rot) 2.9832 | loss(pos) 0.1797 | loss(seq) 0.3093 | grad 3.1458 | lr 0.0010 | time_forward 9.5810 | time_backward 5.5470 |
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