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[2023-09-02 21:45:29,513::train::INFO] [train] Iter 14571 | loss 2.1226 | loss(rot) 1.4098 | loss(pos) 0.3492 | loss(seq) 0.3636 | grad 3.8534 | lr 0.0010 | time_forward 4.2340 | time_backward 5.8330 |
[2023-09-02 21:45:38,662::train::INFO] [train] Iter 14572 | loss 0.9621 | loss(rot) 0.2098 | loss(pos) 0.2765 | loss(seq) 0.4758 | grad 3.4463 | lr 0.0010 | time_forward 4.0730 | time_backward 5.0720 |
[2023-09-02 21:45:41,435::train::INFO] [train] Iter 14573 | loss 1.5448 | loss(rot) 0.7571 | loss(pos) 0.2228 | loss(seq) 0.5649 | grad 4.2632 | lr 0.0010 | time_forward 1.2640 | time_backward 1.5060 |
[2023-09-02 21:45:50,774::train::INFO] [train] Iter 14574 | loss 2.2859 | loss(rot) 1.4671 | loss(pos) 0.3615 | loss(seq) 0.4573 | grad 6.5194 | lr 0.0010 | time_forward 3.9880 | time_backward 5.3480 |
[2023-09-02 21:45:53,606::train::INFO] [train] Iter 14575 | loss 0.8364 | loss(rot) 0.3488 | loss(pos) 0.2715 | loss(seq) 0.2161 | grad 3.6220 | lr 0.0010 | time_forward 1.2930 | time_backward 1.5350 |
[2023-09-02 21:46:03,728::train::INFO] [train] Iter 14576 | loss 1.0315 | loss(rot) 0.5972 | loss(pos) 0.1457 | loss(seq) 0.2887 | grad 3.6772 | lr 0.0010 | time_forward 4.1220 | time_backward 5.9970 |
[2023-09-02 21:46:12,452::train::INFO] [train] Iter 14577 | loss 1.1594 | loss(rot) 0.8571 | loss(pos) 0.1070 | loss(seq) 0.1953 | grad 10.0148 | lr 0.0010 | time_forward 3.6430 | time_backward 5.0770 |
[2023-09-02 21:46:15,855::train::INFO] [train] Iter 14578 | loss 2.0788 | loss(rot) 1.7897 | loss(pos) 0.0968 | loss(seq) 0.1922 | grad 7.2696 | lr 0.0010 | time_forward 1.4490 | time_backward 1.9500 |
[2023-09-02 21:46:25,095::train::INFO] [train] Iter 14579 | loss 0.7108 | loss(rot) 0.2902 | loss(pos) 0.0567 | loss(seq) 0.3639 | grad 3.0375 | lr 0.0010 | time_forward 4.0190 | time_backward 5.2180 |
[2023-09-02 21:46:35,128::train::INFO] [train] Iter 14580 | loss 1.9172 | loss(rot) 1.2060 | loss(pos) 0.2396 | loss(seq) 0.4715 | grad 4.3604 | lr 0.0010 | time_forward 4.0940 | time_backward 5.9360 |
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