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[2023-09-02 16:43:53,136::train::INFO] [train] Iter 12074 | loss 1.9458 | loss(rot) 1.8010 | loss(pos) 0.1396 | loss(seq) 0.0052 | grad 6.0846 | lr 0.0010 | time_forward 2.8730 | time_backward 4.0260 |
[2023-09-02 16:44:00,058::train::INFO] [train] Iter 12075 | loss 1.1341 | loss(rot) 0.8789 | loss(pos) 0.2195 | loss(seq) 0.0357 | grad 5.8379 | lr 0.0010 | time_forward 2.8780 | time_backward 4.0410 |
[2023-09-02 16:44:08,931::train::INFO] [train] Iter 12076 | loss 0.7387 | loss(rot) 0.5500 | loss(pos) 0.1875 | loss(seq) 0.0011 | grad 4.9692 | lr 0.0010 | time_forward 3.6140 | time_backward 5.2560 |
[2023-09-02 16:44:17,464::train::INFO] [train] Iter 12077 | loss 0.8822 | loss(rot) 0.2726 | loss(pos) 0.3302 | loss(seq) 0.2794 | grad 3.5694 | lr 0.0010 | time_forward 3.6860 | time_backward 4.8440 |
[2023-09-02 16:44:19,857::train::INFO] [train] Iter 12078 | loss 1.3153 | loss(rot) 0.5898 | loss(pos) 0.2877 | loss(seq) 0.4378 | grad 3.8413 | lr 0.0010 | time_forward 1.1210 | time_backward 1.2690 |
[2023-09-02 16:44:25,749::train::INFO] [train] Iter 12079 | loss 2.1727 | loss(rot) 2.0111 | loss(pos) 0.1582 | loss(seq) 0.0033 | grad 7.1221 | lr 0.0010 | time_forward 2.3680 | time_backward 3.5100 |
[2023-09-02 16:44:28,392::train::INFO] [train] Iter 12080 | loss 1.9582 | loss(rot) 1.4574 | loss(pos) 0.1932 | loss(seq) 0.3076 | grad 4.8997 | lr 0.0010 | time_forward 1.2170 | time_backward 1.4220 |
[2023-09-02 16:44:37,504::train::INFO] [train] Iter 12081 | loss 1.5602 | loss(rot) 1.2847 | loss(pos) 0.2754 | loss(seq) 0.0000 | grad 6.3132 | lr 0.0010 | time_forward 4.1590 | time_backward 4.9500 |
[2023-09-02 16:44:44,957::train::INFO] [train] Iter 12082 | loss 1.1346 | loss(rot) 0.5643 | loss(pos) 0.1039 | loss(seq) 0.4664 | grad 4.7451 | lr 0.0010 | time_forward 3.1850 | time_backward 4.2650 |
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