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[2023-09-02 21:20:09,391::train::INFO] [train] Iter 14371 | loss 1.3283 | loss(rot) 1.1556 | loss(pos) 0.1715 | loss(seq) 0.0012 | grad 3.8615 | lr 0.0010 | time_forward 1.2590 | time_backward 1.4190 |
[2023-09-02 21:20:12,108::train::INFO] [train] Iter 14372 | loss 1.7173 | loss(rot) 1.1423 | loss(pos) 0.2066 | loss(seq) 0.3683 | grad 12.0360 | lr 0.0010 | time_forward 1.2970 | time_backward 1.4170 |
[2023-09-02 21:20:20,472::train::INFO] [train] Iter 14373 | loss 0.3220 | loss(rot) 0.0731 | loss(pos) 0.2220 | loss(seq) 0.0270 | grad 2.3308 | lr 0.0010 | time_forward 3.5490 | time_backward 4.8120 |
[2023-09-02 21:20:30,636::train::INFO] [train] Iter 14374 | loss 0.9389 | loss(rot) 0.3727 | loss(pos) 0.5474 | loss(seq) 0.0188 | grad 5.0991 | lr 0.0010 | time_forward 4.0740 | time_backward 6.0860 |
[2023-09-02 21:20:32,974::train::INFO] [train] Iter 14375 | loss 2.2764 | loss(rot) 0.0282 | loss(pos) 2.2445 | loss(seq) 0.0037 | grad 6.5952 | lr 0.0010 | time_forward 1.0970 | time_backward 1.2380 |
[2023-09-02 21:20:38,673::train::INFO] [train] Iter 14376 | loss 1.5226 | loss(rot) 1.3513 | loss(pos) 0.1713 | loss(seq) 0.0000 | grad 6.2433 | lr 0.0010 | time_forward 2.3610 | time_backward 3.3340 |
[2023-09-02 21:20:41,149::train::INFO] [train] Iter 14377 | loss 1.5616 | loss(rot) 0.9991 | loss(pos) 0.1830 | loss(seq) 0.3795 | grad 5.5867 | lr 0.0010 | time_forward 1.1640 | time_backward 1.3090 |
[2023-09-02 21:20:49,458::train::INFO] [train] Iter 14378 | loss 0.8349 | loss(rot) 0.5413 | loss(pos) 0.0902 | loss(seq) 0.2034 | grad 3.2697 | lr 0.0010 | time_forward 3.4320 | time_backward 4.8730 |
[2023-09-02 21:20:52,140::train::INFO] [train] Iter 14379 | loss 1.3535 | loss(rot) 0.1145 | loss(pos) 1.2297 | loss(seq) 0.0093 | grad 4.8585 | lr 0.0010 | time_forward 1.2590 | time_backward 1.4190 |
[2023-09-02 21:21:01,060::train::INFO] [train] Iter 14380 | loss 1.3168 | loss(rot) 0.4622 | loss(pos) 0.2109 | loss(seq) 0.6436 | grad 3.9129 | lr 0.0010 | time_forward 3.7460 | time_backward 5.1710 |
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