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[2023-09-02 09:48:08,110::train::INFO] [train] Iter 08577 | loss 1.1159 | loss(rot) 0.4100 | loss(pos) 0.3409 | loss(seq) 0.3650 | grad 2.9372 | lr 0.0010 | time_forward 4.0160 | time_backward 6.0650 |
[2023-09-02 09:48:17,410::train::INFO] [train] Iter 08578 | loss 1.9527 | loss(rot) 0.9764 | loss(pos) 0.5956 | loss(seq) 0.3806 | grad 4.8750 | lr 0.0010 | time_forward 4.0420 | time_backward 5.2550 |
[2023-09-02 09:48:27,419::train::INFO] [train] Iter 08579 | loss 1.6929 | loss(rot) 1.2476 | loss(pos) 0.1941 | loss(seq) 0.2513 | grad 5.0697 | lr 0.0010 | time_forward 4.0600 | time_backward 5.9450 |
[2023-09-02 09:48:36,968::train::INFO] [train] Iter 08580 | loss 2.2751 | loss(rot) 1.8784 | loss(pos) 0.2053 | loss(seq) 0.1914 | grad 4.3801 | lr 0.0010 | time_forward 4.1870 | time_backward 5.3580 |
[2023-09-02 09:48:47,056::train::INFO] [train] Iter 08581 | loss 2.0118 | loss(rot) 1.2396 | loss(pos) 0.3353 | loss(seq) 0.4369 | grad 8.6540 | lr 0.0010 | time_forward 4.1750 | time_backward 5.9100 |
[2023-09-02 09:48:49,752::train::INFO] [train] Iter 08582 | loss 1.2049 | loss(rot) 0.1163 | loss(pos) 1.0720 | loss(seq) 0.0166 | grad 5.9295 | lr 0.0010 | time_forward 1.2590 | time_backward 1.4340 |
[2023-09-02 09:48:58,127::train::INFO] [train] Iter 08583 | loss 2.5313 | loss(rot) 2.2728 | loss(pos) 0.2523 | loss(seq) 0.0062 | grad 6.0125 | lr 0.0010 | time_forward 3.6190 | time_backward 4.7530 |
[2023-09-02 09:49:07,912::train::INFO] [train] Iter 08584 | loss 0.9094 | loss(rot) 0.1368 | loss(pos) 0.5535 | loss(seq) 0.2190 | grad 3.4701 | lr 0.0010 | time_forward 4.0280 | time_backward 5.7520 |
[2023-09-02 09:49:17,814::train::INFO] [train] Iter 08585 | loss 2.3066 | loss(rot) 1.6331 | loss(pos) 0.2483 | loss(seq) 0.4253 | grad 5.9255 | lr 0.0010 | time_forward 4.1190 | time_backward 5.7800 |
[2023-09-02 09:49:27,120::train::INFO] [train] Iter 08586 | loss 1.1425 | loss(rot) 0.2911 | loss(pos) 0.5799 | loss(seq) 0.2715 | grad 5.0034 | lr 0.0010 | time_forward 3.9230 | time_backward 5.3800 |
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