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[2023-09-02 02:51:54,907::train::INFO] [train] Iter 05180 | loss 2.0891 | loss(rot) 0.8993 | loss(pos) 0.6903 | loss(seq) 0.4994 | grad 5.7231 | lr 0.0010 | time_forward 3.9010 | time_backward 5.6990 |
[2023-09-02 02:51:57,360::train::INFO] [train] Iter 05181 | loss 2.2032 | loss(rot) 1.6626 | loss(pos) 0.1694 | loss(seq) 0.3711 | grad 4.0645 | lr 0.0010 | time_forward 1.1600 | time_backward 1.2900 |
[2023-09-02 02:52:07,230::train::INFO] [train] Iter 05182 | loss 2.9951 | loss(rot) 2.8443 | loss(pos) 0.1496 | loss(seq) 0.0012 | grad 3.4254 | lr 0.0010 | time_forward 4.0590 | time_backward 5.8080 |
[2023-09-02 02:52:17,753::train::INFO] [train] Iter 05183 | loss 2.4338 | loss(rot) 2.1453 | loss(pos) 0.2334 | loss(seq) 0.0552 | grad 4.8532 | lr 0.0010 | time_forward 4.2540 | time_backward 6.2660 |
[2023-09-02 02:52:27,775::train::INFO] [train] Iter 05184 | loss 2.0189 | loss(rot) 1.7990 | loss(pos) 0.2187 | loss(seq) 0.0012 | grad 5.6433 | lr 0.0010 | time_forward 4.1680 | time_backward 5.8400 |
[2023-09-02 02:52:38,079::train::INFO] [train] Iter 05185 | loss 2.2591 | loss(rot) 2.0947 | loss(pos) 0.1295 | loss(seq) 0.0350 | grad 4.2584 | lr 0.0010 | time_forward 4.2400 | time_backward 6.0600 |
[2023-09-02 02:52:47,686::train::INFO] [train] Iter 05186 | loss 2.6774 | loss(rot) 1.7696 | loss(pos) 0.3189 | loss(seq) 0.5890 | grad 4.2333 | lr 0.0010 | time_forward 4.0170 | time_backward 5.5870 |
[2023-09-02 02:52:55,328::train::INFO] [train] Iter 05187 | loss 2.0609 | loss(rot) 1.9152 | loss(pos) 0.1437 | loss(seq) 0.0020 | grad 3.4342 | lr 0.0010 | time_forward 3.2250 | time_backward 4.4130 |
[2023-09-02 02:53:00,944::train::INFO] [train] Iter 05188 | loss 4.3634 | loss(rot) 0.0130 | loss(pos) 4.3505 | loss(seq) 0.0000 | grad 7.5392 | lr 0.0010 | time_forward 2.3410 | time_backward 3.2720 |
[2023-09-02 02:53:10,297::train::INFO] [train] Iter 05189 | loss 2.0037 | loss(rot) 1.3244 | loss(pos) 0.1765 | loss(seq) 0.5028 | grad 3.3437 | lr 0.0010 | time_forward 3.9890 | time_backward 5.3600 |
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