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[2023-10-25 05:09:04,892::train::INFO] [train] Iter 591961 | loss 1.4294 | loss(rot) 1.3729 | loss(pos) 0.0258 | loss(seq) 0.0307 | grad 5.8795 | lr 0.0000 | time_forward 1.4950 | time_backward 1.8190 |
[2023-10-25 05:09:13,791::train::INFO] [train] Iter 591962 | loss 0.4952 | loss(rot) 0.1319 | loss(pos) 0.0159 | loss(seq) 0.3475 | grad 2.7261 | lr 0.0000 | time_forward 3.6690 | time_backward 5.2260 |
[2023-10-25 05:09:16,499::train::INFO] [train] Iter 591963 | loss 0.3267 | loss(rot) 0.1076 | loss(pos) 0.0170 | loss(seq) 0.2021 | grad 2.5796 | lr 0.0000 | time_forward 1.2990 | time_backward 1.4060 |
[2023-10-25 05:09:23,403::train::INFO] [train] Iter 591964 | loss 0.3962 | loss(rot) 0.1397 | loss(pos) 0.0240 | loss(seq) 0.2325 | grad 2.4626 | lr 0.0000 | time_forward 2.9280 | time_backward 3.9720 |
[2023-10-25 05:09:26,261::train::INFO] [train] Iter 591965 | loss 0.1969 | loss(rot) 0.0377 | loss(pos) 0.1189 | loss(seq) 0.0404 | grad 4.2887 | lr 0.0000 | time_forward 1.3090 | time_backward 1.5460 |
[2023-10-25 05:09:33,756::train::INFO] [train] Iter 591966 | loss 0.2508 | loss(rot) 0.2246 | loss(pos) 0.0258 | loss(seq) 0.0004 | grad 6.4251 | lr 0.0000 | time_forward 3.2000 | time_backward 4.2920 |
[2023-10-25 05:09:41,895::train::INFO] [train] Iter 591967 | loss 0.4184 | loss(rot) 0.1127 | loss(pos) 0.1038 | loss(seq) 0.2019 | grad 3.9523 | lr 0.0000 | time_forward 3.4800 | time_backward 4.6550 |
[2023-10-25 05:09:44,639::train::INFO] [train] Iter 591968 | loss 0.5234 | loss(rot) 0.2099 | loss(pos) 0.0173 | loss(seq) 0.2961 | grad 3.9294 | lr 0.0000 | time_forward 1.2940 | time_backward 1.4460 |
[2023-10-25 05:09:47,383::train::INFO] [train] Iter 591969 | loss 0.4632 | loss(rot) 0.1583 | loss(pos) 0.0847 | loss(seq) 0.2202 | grad 3.6884 | lr 0.0000 | time_forward 1.3250 | time_backward 1.4150 |
[2023-10-25 05:09:56,378::train::INFO] [train] Iter 591970 | loss 1.1747 | loss(rot) 0.1788 | loss(pos) 0.9956 | loss(seq) 0.0003 | grad 11.6399 | lr 0.0000 | time_forward 3.7550 | time_backward 5.2380 |
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