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[2023-09-02 07:21:22,970::train::INFO] [train] Iter 07378 | loss 2.1345 | loss(rot) 1.5430 | loss(pos) 0.1902 | loss(seq) 0.4014 | grad 3.0667 | lr 0.0010 | time_forward 3.9100 | time_backward 5.2350 |
[2023-09-02 07:21:25,618::train::INFO] [train] Iter 07379 | loss 1.9226 | loss(rot) 1.4237 | loss(pos) 0.1136 | loss(seq) 0.3852 | grad 3.5133 | lr 0.0010 | time_forward 1.2440 | time_backward 1.4000 |
[2023-09-02 07:21:34,664::train::INFO] [train] Iter 07380 | loss 1.1430 | loss(rot) 0.5066 | loss(pos) 0.1712 | loss(seq) 0.4652 | grad 4.1264 | lr 0.0010 | time_forward 3.9080 | time_backward 5.1350 |
[2023-09-02 07:21:37,303::train::INFO] [train] Iter 07381 | loss 1.8874 | loss(rot) 1.2212 | loss(pos) 0.1954 | loss(seq) 0.4708 | grad 3.1521 | lr 0.0010 | time_forward 1.2540 | time_backward 1.3810 |
[2023-09-02 07:21:39,548::train::INFO] [train] Iter 07382 | loss 2.0263 | loss(rot) 1.8197 | loss(pos) 0.1607 | loss(seq) 0.0459 | grad 4.9677 | lr 0.0010 | time_forward 1.0850 | time_backward 1.1580 |
[2023-09-02 07:21:46,933::train::INFO] [train] Iter 07383 | loss 2.1964 | loss(rot) 1.5408 | loss(pos) 0.1534 | loss(seq) 0.5022 | grad 3.7070 | lr 0.0010 | time_forward 3.1650 | time_backward 4.2160 |
[2023-09-02 07:21:55,481::train::INFO] [train] Iter 07384 | loss 2.4087 | loss(rot) 2.0014 | loss(pos) 0.3886 | loss(seq) 0.0187 | grad 5.1954 | lr 0.0010 | time_forward 3.5910 | time_backward 4.9540 |
[2023-09-02 07:22:05,998::train::INFO] [train] Iter 07385 | loss 1.1446 | loss(rot) 0.0704 | loss(pos) 1.0686 | loss(seq) 0.0057 | grad 4.6213 | lr 0.0010 | time_forward 4.3210 | time_backward 6.1930 |
[2023-09-02 07:22:14,951::train::INFO] [train] Iter 07386 | loss 2.6909 | loss(rot) 2.4294 | loss(pos) 0.1919 | loss(seq) 0.0696 | grad 3.3102 | lr 0.0010 | time_forward 3.7840 | time_backward 5.1650 |
[2023-09-02 07:22:24,428::train::INFO] [train] Iter 07387 | loss 2.6401 | loss(rot) 2.2862 | loss(pos) 0.2230 | loss(seq) 0.1310 | grad 2.7825 | lr 0.0010 | time_forward 4.1250 | time_backward 5.3480 |
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