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[2023-09-03 04:18:31,575::train::INFO] [train] Iter 17869 | loss 1.9247 | loss(rot) 1.7116 | loss(pos) 0.1304 | loss(seq) 0.0827 | grad 5.8231 | lr 0.0010 | time_forward 1.3930 | time_backward 1.7350 |
[2023-09-03 04:18:34,205::train::INFO] [train] Iter 17870 | loss 1.1122 | loss(rot) 0.8427 | loss(pos) 0.1205 | loss(seq) 0.1489 | grad 4.0304 | lr 0.0010 | time_forward 1.2330 | time_backward 1.3930 |
[2023-09-03 04:18:36,856::train::INFO] [train] Iter 17871 | loss 1.5190 | loss(rot) 1.3206 | loss(pos) 0.0811 | loss(seq) 0.1172 | grad 10.7316 | lr 0.0010 | time_forward 1.2650 | time_backward 1.3810 |
[2023-09-03 04:18:39,456::train::INFO] [train] Iter 17872 | loss 2.1527 | loss(rot) 1.4495 | loss(pos) 0.2045 | loss(seq) 0.4987 | grad 4.3752 | lr 0.0010 | time_forward 1.2330 | time_backward 1.3630 |
[2023-09-03 04:18:45,762::train::INFO] [train] Iter 17873 | loss 1.1605 | loss(rot) 0.5508 | loss(pos) 0.1741 | loss(seq) 0.4356 | grad 3.9831 | lr 0.0010 | time_forward 2.7840 | time_backward 3.5180 |
[2023-09-03 04:18:53,070::train::INFO] [train] Iter 17874 | loss 1.0977 | loss(rot) 0.4756 | loss(pos) 0.5510 | loss(seq) 0.0711 | grad 3.5049 | lr 0.0010 | time_forward 3.2100 | time_backward 4.0950 |
[2023-09-03 04:18:59,705::train::INFO] [train] Iter 17875 | loss 1.5495 | loss(rot) 0.9656 | loss(pos) 0.1889 | loss(seq) 0.3951 | grad 6.7118 | lr 0.0010 | time_forward 2.6680 | time_backward 3.9630 |
[2023-09-03 04:19:08,973::train::INFO] [train] Iter 17876 | loss 1.0342 | loss(rot) 0.1005 | loss(pos) 0.5810 | loss(seq) 0.3528 | grad 2.6624 | lr 0.0010 | time_forward 3.6420 | time_backward 5.6210 |
[2023-09-03 04:19:18,079::train::INFO] [train] Iter 17877 | loss 1.6730 | loss(rot) 1.1755 | loss(pos) 0.1939 | loss(seq) 0.3036 | grad 6.9734 | lr 0.0010 | time_forward 3.7260 | time_backward 5.3760 |
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