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[2023-10-22 21:30:34,240::train::INFO] [train] Iter 562191 | loss 0.7818 | loss(rot) 0.0807 | loss(pos) 0.4141 | loss(seq) 0.2870 | grad 4.5016 | lr 0.0000 | time_forward 3.8200 | time_backward 5.2210 |
[2023-10-22 21:30:43,232::train::INFO] [train] Iter 562192 | loss 0.3489 | loss(rot) 0.3205 | loss(pos) 0.0272 | loss(seq) 0.0011 | grad 3.4138 | lr 0.0000 | time_forward 3.6720 | time_backward 5.3180 |
[2023-10-22 21:30:49,026::train::INFO] [train] Iter 562193 | loss 0.3059 | loss(rot) 0.0745 | loss(pos) 0.2235 | loss(seq) 0.0079 | grad 3.6851 | lr 0.0000 | time_forward 2.4560 | time_backward 3.3340 |
[2023-10-22 21:30:57,890::train::INFO] [train] Iter 562194 | loss 1.0772 | loss(rot) 0.6443 | loss(pos) 0.1026 | loss(seq) 0.3304 | grad 3.1674 | lr 0.0000 | time_forward 3.7950 | time_backward 5.0520 |
[2023-10-22 21:31:00,594::train::INFO] [train] Iter 562195 | loss 0.7562 | loss(rot) 0.3983 | loss(pos) 0.0871 | loss(seq) 0.2708 | grad 13.9064 | lr 0.0000 | time_forward 1.2720 | time_backward 1.4290 |
[2023-10-22 21:31:09,679::train::INFO] [train] Iter 562196 | loss 0.6122 | loss(rot) 0.2505 | loss(pos) 0.1307 | loss(seq) 0.2311 | grad 2.4454 | lr 0.0000 | time_forward 3.7810 | time_backward 5.3010 |
[2023-10-22 21:31:18,769::train::INFO] [train] Iter 562197 | loss 0.1486 | loss(rot) 0.0837 | loss(pos) 0.0224 | loss(seq) 0.0425 | grad 2.5132 | lr 0.0000 | time_forward 3.7130 | time_backward 5.3740 |
[2023-10-22 21:31:27,833::train::INFO] [train] Iter 562198 | loss 0.2483 | loss(rot) 0.0930 | loss(pos) 0.0873 | loss(seq) 0.0680 | grad 1.9823 | lr 0.0000 | time_forward 3.7780 | time_backward 5.2820 |
[2023-10-22 21:31:35,399::train::INFO] [train] Iter 562199 | loss 0.4325 | loss(rot) 0.1270 | loss(pos) 0.0584 | loss(seq) 0.2471 | grad 3.0823 | lr 0.0000 | time_forward 3.2270 | time_backward 4.3370 |
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