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[2023-09-02 15:30:30,130::train::INFO] [train] Iter 11375 | loss 1.8223 | loss(rot) 1.6506 | loss(pos) 0.1488 | loss(seq) 0.0229 | grad 5.5228 | lr 0.0010 | time_forward 1.1940 | time_backward 1.4110 |
[2023-09-02 15:30:38,179::train::INFO] [train] Iter 11376 | loss 2.0809 | loss(rot) 1.2721 | loss(pos) 0.2756 | loss(seq) 0.5332 | grad 3.0832 | lr 0.0010 | time_forward 3.4160 | time_backward 4.6290 |
[2023-09-02 15:30:43,814::train::INFO] [train] Iter 11377 | loss 2.4388 | loss(rot) 1.8605 | loss(pos) 0.1457 | loss(seq) 0.4326 | grad 3.0097 | lr 0.0010 | time_forward 2.2770 | time_backward 3.3550 |
[2023-09-02 15:30:52,099::train::INFO] [train] Iter 11378 | loss 1.4358 | loss(rot) 1.2833 | loss(pos) 0.0561 | loss(seq) 0.0963 | grad 6.9193 | lr 0.0010 | time_forward 3.2950 | time_backward 4.9860 |
[2023-09-02 15:30:59,056::train::INFO] [train] Iter 11379 | loss 1.1057 | loss(rot) 0.4924 | loss(pos) 0.5131 | loss(seq) 0.1002 | grad 4.9237 | lr 0.0010 | time_forward 3.0010 | time_backward 3.9520 |
[2023-09-02 15:31:05,470::train::INFO] [train] Iter 11380 | loss 1.9352 | loss(rot) 1.7432 | loss(pos) 0.0993 | loss(seq) 0.0927 | grad 4.6273 | lr 0.0010 | time_forward 2.7590 | time_backward 3.6520 |
[2023-09-02 15:31:08,586::train::INFO] [train] Iter 11381 | loss 0.7448 | loss(rot) 0.2839 | loss(pos) 0.4105 | loss(seq) 0.0504 | grad 2.4955 | lr 0.0010 | time_forward 1.3450 | time_backward 1.7670 |
[2023-09-02 15:31:16,394::train::INFO] [train] Iter 11382 | loss 0.9053 | loss(rot) 0.2671 | loss(pos) 0.1636 | loss(seq) 0.4746 | grad 3.7424 | lr 0.0010 | time_forward 3.1880 | time_backward 4.6170 |
[2023-09-02 15:31:25,123::train::INFO] [train] Iter 11383 | loss 2.2862 | loss(rot) 1.2693 | loss(pos) 0.5089 | loss(seq) 0.5080 | grad 4.0148 | lr 0.0010 | time_forward 3.6720 | time_backward 5.0530 |
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