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[2023-10-25 15:44:10,605::train::INFO] [train] Iter 597455 | loss 1.1452 | loss(rot) 0.9039 | loss(pos) 0.0463 | loss(seq) 0.1949 | grad 3.7834 | lr 0.0000 | time_forward 3.4330 | time_backward 4.8140 |
[2023-10-25 15:44:13,344::train::INFO] [train] Iter 597456 | loss 0.2022 | loss(rot) 0.0740 | loss(pos) 0.0199 | loss(seq) 0.1083 | grad 1.4967 | lr 0.0000 | time_forward 1.2920 | time_backward 1.4440 |
[2023-10-25 15:44:21,679::train::INFO] [train] Iter 597457 | loss 0.3686 | loss(rot) 0.1752 | loss(pos) 0.0163 | loss(seq) 0.1771 | grad 2.3302 | lr 0.0000 | time_forward 3.4430 | time_backward 4.8890 |
[2023-10-25 15:44:28,633::train::INFO] [train] Iter 597458 | loss 0.5346 | loss(rot) 0.1600 | loss(pos) 0.2450 | loss(seq) 0.1295 | grad 3.6081 | lr 0.0000 | time_forward 2.9440 | time_backward 4.0080 |
[2023-10-25 15:44:35,716::train::INFO] [train] Iter 597459 | loss 2.4386 | loss(rot) 2.1051 | loss(pos) 0.0883 | loss(seq) 0.2451 | grad 5.2213 | lr 0.0000 | time_forward 3.0020 | time_backward 4.0770 |
[2023-10-25 15:44:38,998::train::INFO] [train] Iter 597460 | loss 0.4661 | loss(rot) 0.3739 | loss(pos) 0.0293 | loss(seq) 0.0629 | grad 16.0980 | lr 0.0000 | time_forward 1.4760 | time_backward 1.8030 |
[2023-10-25 15:44:47,379::train::INFO] [train] Iter 597461 | loss 3.1288 | loss(rot) 0.0015 | loss(pos) 3.1273 | loss(seq) 0.0000 | grad 19.8355 | lr 0.0000 | time_forward 3.4850 | time_backward 4.8810 |
[2023-10-25 15:44:53,936::train::INFO] [train] Iter 597462 | loss 1.3045 | loss(rot) 0.5343 | loss(pos) 0.0748 | loss(seq) 0.6953 | grad 4.0926 | lr 0.0000 | time_forward 2.8660 | time_backward 3.6880 |
[2023-10-25 15:45:02,458::train::INFO] [train] Iter 597463 | loss 0.2448 | loss(rot) 0.0393 | loss(pos) 0.0308 | loss(seq) 0.1747 | grad 2.0545 | lr 0.0000 | time_forward 3.5700 | time_backward 4.9500 |
[2023-10-25 15:45:09,302::train::INFO] [train] Iter 597464 | loss 0.3608 | loss(rot) 0.0247 | loss(pos) 0.3356 | loss(seq) 0.0005 | grad 4.5982 | lr 0.0000 | time_forward 2.9040 | time_backward 3.9360 |
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