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[2023-10-23 16:13:19,270::train::INFO] [train] Iter 572879 | loss 0.2545 | loss(rot) 0.0299 | loss(pos) 0.2170 | loss(seq) 0.0076 | grad 5.2299 | lr 0.0000 | time_forward 26.0140 | time_backward 7.1520 |
[2023-10-23 16:13:23,522::train::INFO] [train] Iter 572880 | loss 0.3478 | loss(rot) 0.2386 | loss(pos) 0.0253 | loss(seq) 0.0839 | grad 2.0118 | lr 0.0000 | time_forward 2.6710 | time_backward 1.5770 |
[2023-10-23 16:13:37,252::train::INFO] [train] Iter 572881 | loss 1.8303 | loss(rot) 1.6110 | loss(pos) 0.0375 | loss(seq) 0.1818 | grad 4.4860 | lr 0.0000 | time_forward 8.1190 | time_backward 5.6080 |
[2023-10-23 16:13:40,634::train::INFO] [train] Iter 572882 | loss 1.6863 | loss(rot) 1.1309 | loss(pos) 0.0586 | loss(seq) 0.4967 | grad 4.2532 | lr 0.0000 | time_forward 1.4580 | time_backward 1.9220 |
[2023-10-23 16:13:54,061::train::INFO] [train] Iter 572883 | loss 1.8240 | loss(rot) 1.4376 | loss(pos) 0.0593 | loss(seq) 0.3271 | grad 3.7521 | lr 0.0000 | time_forward 5.9520 | time_backward 7.4710 |
[2023-10-23 16:14:04,379::train::INFO] [train] Iter 572884 | loss 0.6169 | loss(rot) 0.2209 | loss(pos) 0.2617 | loss(seq) 0.1343 | grad 5.0528 | lr 0.0000 | time_forward 4.2450 | time_backward 6.0700 |
[2023-10-23 16:14:12,742::train::INFO] [train] Iter 572885 | loss 0.3748 | loss(rot) 0.2986 | loss(pos) 0.0227 | loss(seq) 0.0535 | grad 19.4745 | lr 0.0000 | time_forward 4.0690 | time_backward 4.2910 |
[2023-10-23 16:14:15,577::train::INFO] [train] Iter 572886 | loss 0.4698 | loss(rot) 0.0735 | loss(pos) 0.0312 | loss(seq) 0.3651 | grad 2.7231 | lr 0.0000 | time_forward 1.4070 | time_backward 1.4240 |
[2023-10-23 16:14:22,157::train::INFO] [train] Iter 572887 | loss 0.4465 | loss(rot) 0.1120 | loss(pos) 0.1271 | loss(seq) 0.2074 | grad 3.3096 | lr 0.0000 | time_forward 2.8500 | time_backward 3.7270 |
[2023-10-23 16:14:31,605::train::INFO] [train] Iter 572888 | loss 0.6472 | loss(rot) 0.5981 | loss(pos) 0.0450 | loss(seq) 0.0040 | grad 3.3332 | lr 0.0000 | time_forward 4.0140 | time_backward 5.4300 |
[2023-10-23 16:14:34,450::train::INFO] [train] Iter 572889 | loss 0.2757 | loss(rot) 0.0706 | loss(pos) 0.1555 | loss(seq) 0.0496 | grad 2.5774 | lr 0.0000 | time_forward 1.2930 | time_backward 1.5480 |
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