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[2023-09-02 14:55:24,446::train::INFO] [train] Iter 11075 | loss 2.8669 | loss(rot) 2.4181 | loss(pos) 0.1598 | loss(seq) 0.2890 | grad 3.8191 | lr 0.0010 | time_forward 6.5070 | time_backward 5.7320 |
[2023-09-02 14:55:33,301::train::INFO] [train] Iter 11076 | loss 1.5399 | loss(rot) 0.8327 | loss(pos) 0.1453 | loss(seq) 0.5620 | grad 3.3565 | lr 0.0010 | time_forward 3.5670 | time_backward 5.2840 |
[2023-09-02 14:55:36,223::train::INFO] [train] Iter 11077 | loss 1.2849 | loss(rot) 0.5759 | loss(pos) 0.2105 | loss(seq) 0.4986 | grad 5.0109 | lr 0.0010 | time_forward 1.1800 | time_backward 1.7380 |
[2023-09-02 14:55:42,657::train::INFO] [train] Iter 11078 | loss 2.6076 | loss(rot) 1.9004 | loss(pos) 0.1469 | loss(seq) 0.5602 | grad 5.7468 | lr 0.0010 | time_forward 2.8820 | time_backward 3.5480 |
[2023-09-02 14:55:48,468::train::INFO] [train] Iter 11079 | loss 0.7681 | loss(rot) 0.3392 | loss(pos) 0.1918 | loss(seq) 0.2371 | grad 3.5437 | lr 0.0010 | time_forward 2.3190 | time_backward 3.4900 |
[2023-09-02 14:56:03,152::train::INFO] [train] Iter 11080 | loss 2.2375 | loss(rot) 1.6090 | loss(pos) 0.2875 | loss(seq) 0.3410 | grad 6.4763 | lr 0.0010 | time_forward 7.6090 | time_backward 7.0720 |
[2023-09-02 14:56:10,662::train::INFO] [train] Iter 11081 | loss 1.3578 | loss(rot) 0.5738 | loss(pos) 0.2185 | loss(seq) 0.5654 | grad 4.5465 | lr 0.0010 | time_forward 3.1370 | time_backward 4.3700 |
[2023-09-02 14:56:12,813::train::INFO] [train] Iter 11082 | loss 0.6206 | loss(rot) 0.0934 | loss(pos) 0.5100 | loss(seq) 0.0172 | grad 4.4258 | lr 0.0010 | time_forward 1.0000 | time_backward 1.1480 |
[2023-09-02 14:56:19,597::train::INFO] [train] Iter 11083 | loss 2.7733 | loss(rot) 0.4660 | loss(pos) 2.3028 | loss(seq) 0.0044 | grad 8.5026 | lr 0.0010 | time_forward 2.8690 | time_backward 3.8900 |
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