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[2023-10-22 18:53:50,166::train::INFO] [train] Iter 560792 | loss 0.5395 | loss(rot) 0.1837 | loss(pos) 0.0449 | loss(seq) 0.3110 | grad 3.4495 | lr 0.0000 | time_forward 1.1530 | time_backward 1.3510 |
[2023-10-22 18:53:52,583::train::INFO] [train] Iter 560793 | loss 0.3599 | loss(rot) 0.1080 | loss(pos) 0.0339 | loss(seq) 0.2180 | grad 2.4000 | lr 0.0000 | time_forward 1.0900 | time_backward 1.3160 |
[2023-10-22 18:54:00,276::train::INFO] [train] Iter 560794 | loss 1.1482 | loss(rot) 0.0047 | loss(pos) 1.1424 | loss(seq) 0.0012 | grad 11.5533 | lr 0.0000 | time_forward 3.3010 | time_backward 4.3870 |
[2023-10-22 18:54:03,229::train::INFO] [train] Iter 560795 | loss 0.1497 | loss(rot) 0.0492 | loss(pos) 0.0722 | loss(seq) 0.0283 | grad 2.4077 | lr 0.0000 | time_forward 1.3900 | time_backward 1.5590 |
[2023-10-22 18:54:12,899::train::INFO] [train] Iter 560796 | loss 1.7343 | loss(rot) 0.9162 | loss(pos) 0.3626 | loss(seq) 0.4555 | grad 3.1243 | lr 0.0000 | time_forward 4.2560 | time_backward 5.4120 |
[2023-10-22 18:54:20,210::train::INFO] [train] Iter 560797 | loss 0.5135 | loss(rot) 0.0517 | loss(pos) 0.2115 | loss(seq) 0.2502 | grad 5.2165 | lr 0.0000 | time_forward 3.1150 | time_backward 4.1920 |
[2023-10-22 18:54:28,087::train::INFO] [train] Iter 560798 | loss 0.9174 | loss(rot) 0.4712 | loss(pos) 0.2175 | loss(seq) 0.2287 | grad 3.7744 | lr 0.0000 | time_forward 3.3240 | time_backward 4.5500 |
[2023-10-22 18:54:31,478::train::INFO] [train] Iter 560799 | loss 0.5297 | loss(rot) 0.4737 | loss(pos) 0.0560 | loss(seq) 0.0000 | grad 4.8426 | lr 0.0000 | time_forward 1.5060 | time_backward 1.8820 |
[2023-10-22 18:54:40,563::train::INFO] [train] Iter 560800 | loss 0.5844 | loss(rot) 0.0463 | loss(pos) 0.1274 | loss(seq) 0.4108 | grad 2.9915 | lr 0.0000 | time_forward 3.8110 | time_backward 5.2700 |
[2023-10-22 18:54:43,531::train::INFO] [train] Iter 560801 | loss 0.2306 | loss(rot) 0.0596 | loss(pos) 0.1285 | loss(seq) 0.0426 | grad 3.7441 | lr 0.0000 | time_forward 1.4700 | time_backward 1.4950 |
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