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[2023-09-02 23:15:39,761::train::INFO] [train] Iter 15271 | loss 2.4255 | loss(rot) 0.8275 | loss(pos) 1.1079 | loss(seq) 0.4900 | grad 4.9594 | lr 0.0010 | time_forward 1.5240 | time_backward 2.0260 |
[2023-09-02 23:15:50,736::train::INFO] [train] Iter 15272 | loss 1.3979 | loss(rot) 1.3052 | loss(pos) 0.0771 | loss(seq) 0.0156 | grad 3.3606 | lr 0.0010 | time_forward 4.4190 | time_backward 6.5510 |
[2023-09-02 23:16:01,274::train::INFO] [train] Iter 15273 | loss 0.6269 | loss(rot) 0.2850 | loss(pos) 0.2592 | loss(seq) 0.0827 | grad 4.0392 | lr 0.0010 | time_forward 4.3480 | time_backward 6.1850 |
[2023-09-02 23:16:12,042::train::INFO] [train] Iter 15274 | loss 2.1378 | loss(rot) 1.4727 | loss(pos) 0.2180 | loss(seq) 0.4471 | grad 3.7697 | lr 0.0010 | time_forward 4.3600 | time_backward 6.4050 |
[2023-09-02 23:16:15,535::train::INFO] [train] Iter 15275 | loss 2.1008 | loss(rot) 0.3797 | loss(pos) 1.4764 | loss(seq) 0.2448 | grad 4.7342 | lr 0.0010 | time_forward 1.5020 | time_backward 1.9880 |
[2023-09-02 23:16:18,511::train::INFO] [train] Iter 15276 | loss 1.1388 | loss(rot) 0.6245 | loss(pos) 0.1721 | loss(seq) 0.3422 | grad 4.1948 | lr 0.0010 | time_forward 1.3930 | time_backward 1.5670 |
[2023-09-02 23:16:27,540::train::INFO] [train] Iter 15277 | loss 1.5629 | loss(rot) 1.0489 | loss(pos) 0.2085 | loss(seq) 0.3055 | grad 5.7331 | lr 0.0010 | time_forward 3.8600 | time_backward 5.1450 |
[2023-09-02 23:16:36,788::train::INFO] [train] Iter 15278 | loss 0.8135 | loss(rot) 0.2908 | loss(pos) 0.2120 | loss(seq) 0.3107 | grad 3.3966 | lr 0.0010 | time_forward 3.9110 | time_backward 5.3340 |
[2023-09-02 23:16:44,139::train::INFO] [train] Iter 15279 | loss 1.5431 | loss(rot) 0.4342 | loss(pos) 0.6385 | loss(seq) 0.4704 | grad 4.3141 | lr 0.0010 | time_forward 3.0780 | time_backward 4.2680 |
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