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[2023-09-02 19:04:35,128::train::INFO] [train] Iter 13273 | loss 0.9733 | loss(rot) 0.2939 | loss(pos) 0.0810 | loss(seq) 0.5984 | grad 4.6582 | lr 0.0010 | time_forward 3.5590 | time_backward 5.0670 |
[2023-09-02 19:04:43,525::train::INFO] [train] Iter 13274 | loss 0.9028 | loss(rot) 0.4587 | loss(pos) 0.2483 | loss(seq) 0.1957 | grad 4.9224 | lr 0.0010 | time_forward 3.4670 | time_backward 4.9270 |
[2023-09-02 19:04:53,579::train::INFO] [train] Iter 13275 | loss 1.8996 | loss(rot) 1.0934 | loss(pos) 0.1808 | loss(seq) 0.6254 | grad 3.4323 | lr 0.0010 | time_forward 4.0150 | time_backward 6.0360 |
[2023-09-02 19:04:55,874::train::INFO] [train] Iter 13276 | loss 1.9375 | loss(rot) 1.4616 | loss(pos) 0.1597 | loss(seq) 0.3162 | grad 4.0435 | lr 0.0010 | time_forward 1.0360 | time_backward 1.2560 |
[2023-09-02 19:04:58,535::train::INFO] [train] Iter 13277 | loss 2.2664 | loss(rot) 1.8935 | loss(pos) 0.1801 | loss(seq) 0.1928 | grad 5.4296 | lr 0.0010 | time_forward 1.2410 | time_backward 1.4180 |
[2023-09-02 19:05:07,430::train::INFO] [train] Iter 13278 | loss 1.9447 | loss(rot) 1.7773 | loss(pos) 0.1522 | loss(seq) 0.0153 | grad 5.6676 | lr 0.0010 | time_forward 3.7430 | time_backward 5.1480 |
[2023-09-02 19:05:10,099::train::INFO] [train] Iter 13279 | loss 1.2705 | loss(rot) 0.8111 | loss(pos) 0.2435 | loss(seq) 0.2159 | grad 6.4402 | lr 0.0010 | time_forward 1.2610 | time_backward 1.4050 |
[2023-09-02 19:05:19,391::train::INFO] [train] Iter 13280 | loss 1.8113 | loss(rot) 1.2648 | loss(pos) 0.1341 | loss(seq) 0.4124 | grad 4.8078 | lr 0.0010 | time_forward 3.7250 | time_backward 5.0490 |
[2023-09-02 19:05:27,996::train::INFO] [train] Iter 13281 | loss 3.2273 | loss(rot) 2.8702 | loss(pos) 0.3564 | loss(seq) 0.0006 | grad 6.6357 | lr 0.0010 | time_forward 3.6620 | time_backward 4.9400 |
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