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[2023-09-02 14:41:30,768::train::INFO] [train] Iter 10975 | loss 1.0162 | loss(rot) 0.1762 | loss(pos) 0.7627 | loss(seq) 0.0773 | grad 3.0029 | lr 0.0010 | time_forward 3.6930 | time_backward 5.1950 |
[2023-09-02 14:41:34,243::train::INFO] [train] Iter 10976 | loss 3.0397 | loss(rot) 1.7514 | loss(pos) 0.7427 | loss(seq) 0.5457 | grad 5.3541 | lr 0.0010 | time_forward 1.4270 | time_backward 2.0440 |
[2023-09-02 14:41:42,986::train::INFO] [train] Iter 10977 | loss 1.0222 | loss(rot) 0.1034 | loss(pos) 0.9060 | loss(seq) 0.0129 | grad 4.8280 | lr 0.0010 | time_forward 3.6200 | time_backward 5.0140 |
[2023-09-02 14:41:52,688::train::INFO] [train] Iter 10978 | loss 1.3445 | loss(rot) 0.7544 | loss(pos) 0.1681 | loss(seq) 0.4220 | grad 3.7732 | lr 0.0010 | time_forward 4.0080 | time_backward 5.6900 |
[2023-09-02 14:41:55,551::train::INFO] [train] Iter 10979 | loss 1.0586 | loss(rot) 0.2155 | loss(pos) 0.7979 | loss(seq) 0.0452 | grad 4.1424 | lr 0.0010 | time_forward 1.3380 | time_backward 1.5210 |
[2023-09-02 14:42:04,565::train::INFO] [train] Iter 10980 | loss 1.7065 | loss(rot) 1.4186 | loss(pos) 0.2872 | loss(seq) 0.0007 | grad 5.5946 | lr 0.0010 | time_forward 3.6770 | time_backward 5.3350 |
[2023-09-02 14:42:14,625::train::INFO] [train] Iter 10981 | loss 2.2682 | loss(rot) 1.4594 | loss(pos) 0.2708 | loss(seq) 0.5379 | grad 4.7758 | lr 0.0010 | time_forward 4.2070 | time_backward 5.8490 |
[2023-09-02 14:42:17,434::train::INFO] [train] Iter 10982 | loss 1.8028 | loss(rot) 1.5675 | loss(pos) 0.2290 | loss(seq) 0.0064 | grad 4.2701 | lr 0.0010 | time_forward 1.2430 | time_backward 1.5460 |
[2023-09-02 14:42:28,057::train::INFO] [train] Iter 10983 | loss 2.0837 | loss(rot) 1.7775 | loss(pos) 0.2962 | loss(seq) 0.0099 | grad 3.9927 | lr 0.0010 | time_forward 4.1820 | time_backward 6.3470 |
[2023-09-02 14:42:32,798::train::INFO] [train] Iter 10984 | loss 2.5691 | loss(rot) 2.3072 | loss(pos) 0.0716 | loss(seq) 0.1903 | grad 4.0133 | lr 0.0010 | time_forward 2.0890 | time_backward 2.6480 |
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