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[2023-10-24 16:37:26,811::train::INFO] [train] Iter 585368 | loss 0.8876 | loss(rot) 0.6844 | loss(pos) 0.0233 | loss(seq) 0.1798 | grad 3.1632 | lr 0.0000 | time_forward 3.1600 | time_backward 4.2190 |
[2023-10-24 16:37:29,528::train::INFO] [train] Iter 585369 | loss 0.7950 | loss(rot) 0.4362 | loss(pos) 0.2461 | loss(seq) 0.1127 | grad 4.4655 | lr 0.0000 | time_forward 1.3080 | time_backward 1.4070 |
[2023-10-24 16:37:36,457::train::INFO] [train] Iter 585370 | loss 0.1650 | loss(rot) 0.1221 | loss(pos) 0.0111 | loss(seq) 0.0318 | grad 2.2715 | lr 0.0000 | time_forward 2.9530 | time_backward 3.9720 |
[2023-10-24 16:37:39,001::train::INFO] [train] Iter 585371 | loss 0.4889 | loss(rot) 0.0095 | loss(pos) 0.4790 | loss(seq) 0.0004 | grad 9.2683 | lr 0.0000 | time_forward 1.2160 | time_backward 1.3260 |
[2023-10-24 16:37:46,080::train::INFO] [train] Iter 585372 | loss 0.1644 | loss(rot) 0.0587 | loss(pos) 0.0899 | loss(seq) 0.0158 | grad 2.4862 | lr 0.0000 | time_forward 3.0070 | time_backward 4.0680 |
[2023-10-24 16:37:54,299::train::INFO] [train] Iter 585373 | loss 0.5802 | loss(rot) 0.1659 | loss(pos) 0.0405 | loss(seq) 0.3737 | grad 2.8967 | lr 0.0000 | time_forward 3.3980 | time_backward 4.8180 |
[2023-10-24 16:38:00,754::train::INFO] [train] Iter 585374 | loss 2.2160 | loss(rot) 1.3790 | loss(pos) 0.1199 | loss(seq) 0.7172 | grad 6.3972 | lr 0.0000 | time_forward 2.8100 | time_backward 3.6410 |
[2023-10-24 16:38:08,422::train::INFO] [train] Iter 585375 | loss 0.1965 | loss(rot) 0.1116 | loss(pos) 0.0850 | loss(seq) 0.0000 | grad 2.3218 | lr 0.0000 | time_forward 3.3090 | time_backward 4.3560 |
[2023-10-24 16:38:11,149::train::INFO] [train] Iter 585376 | loss 0.5242 | loss(rot) 0.1516 | loss(pos) 0.3490 | loss(seq) 0.0237 | grad 4.7380 | lr 0.0000 | time_forward 1.3250 | time_backward 1.3990 |
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