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[2023-09-02 22:23:47,657::train::INFO] [train] Iter 14872 | loss 2.3061 | loss(rot) 1.8856 | loss(pos) 0.0934 | loss(seq) 0.3271 | grad 5.1573 | lr 0.0010 | time_forward 1.2560 | time_backward 1.4920 |
[2023-09-02 22:23:56,709::train::INFO] [train] Iter 14873 | loss 1.2698 | loss(rot) 0.7561 | loss(pos) 0.1794 | loss(seq) 0.3342 | grad 23.3899 | lr 0.0010 | time_forward 3.8010 | time_backward 5.2470 |
[2023-09-02 22:24:06,798::train::INFO] [train] Iter 14874 | loss 1.0008 | loss(rot) 0.4022 | loss(pos) 0.1049 | loss(seq) 0.4937 | grad 3.5843 | lr 0.0010 | time_forward 4.0410 | time_backward 6.0460 |
[2023-09-02 22:24:16,172::train::INFO] [train] Iter 14875 | loss 1.3394 | loss(rot) 0.7037 | loss(pos) 0.3718 | loss(seq) 0.2639 | grad 5.9938 | lr 0.0010 | time_forward 4.2180 | time_backward 5.1520 |
[2023-09-02 22:24:25,619::train::INFO] [train] Iter 14876 | loss 1.8117 | loss(rot) 1.0455 | loss(pos) 0.3702 | loss(seq) 0.3960 | grad 3.6125 | lr 0.0010 | time_forward 3.9310 | time_backward 5.5120 |
[2023-09-02 22:24:35,550::train::INFO] [train] Iter 14877 | loss 1.4310 | loss(rot) 0.9203 | loss(pos) 0.1283 | loss(seq) 0.3824 | grad 3.6561 | lr 0.0010 | time_forward 4.0610 | time_backward 5.8660 |
[2023-09-02 22:24:44,851::train::INFO] [train] Iter 14878 | loss 2.5092 | loss(rot) 1.8633 | loss(pos) 0.1572 | loss(seq) 0.4887 | grad 3.5768 | lr 0.0010 | time_forward 3.8820 | time_backward 5.4140 |
[2023-09-02 22:24:54,023::train::INFO] [train] Iter 14879 | loss 1.7201 | loss(rot) 1.3589 | loss(pos) 0.1091 | loss(seq) 0.2521 | grad 5.3006 | lr 0.0010 | time_forward 3.7230 | time_backward 5.4450 |
[2023-09-02 22:24:57,783::train::INFO] [train] Iter 14880 | loss 2.0019 | loss(rot) 1.8343 | loss(pos) 0.1191 | loss(seq) 0.0485 | grad 4.1660 | lr 0.0010 | time_forward 1.6120 | time_backward 2.1430 |
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