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[2023-09-02 02:40:29,540::train::INFO] [train] Iter 05079 | loss 3.1254 | loss(rot) 2.9565 | loss(pos) 0.1591 | loss(seq) 0.0097 | grad 3.3249 | lr 0.0010 | time_forward 1.3240 | time_backward 1.4540 |
[2023-09-02 02:40:32,290::train::INFO] [train] Iter 05080 | loss 1.8340 | loss(rot) 1.7081 | loss(pos) 0.0906 | loss(seq) 0.0352 | grad 3.7774 | lr 0.0010 | time_forward 1.3270 | time_backward 1.4190 |
[2023-09-02 02:40:42,211::train::INFO] [train] Iter 05081 | loss 2.1728 | loss(rot) 0.0294 | loss(pos) 2.1401 | loss(seq) 0.0033 | grad 6.7092 | lr 0.0010 | time_forward 3.9630 | time_backward 5.9540 |
[2023-09-02 02:40:44,909::train::INFO] [train] Iter 05082 | loss 1.8482 | loss(rot) 1.6948 | loss(pos) 0.1528 | loss(seq) 0.0007 | grad 4.2387 | lr 0.0010 | time_forward 1.2540 | time_backward 1.4410 |
[2023-09-02 02:40:53,779::train::INFO] [train] Iter 05083 | loss 3.4522 | loss(rot) 3.1738 | loss(pos) 0.1151 | loss(seq) 0.1633 | grad 3.5603 | lr 0.0010 | time_forward 3.8080 | time_backward 5.0430 |
[2023-09-02 02:41:03,314::train::INFO] [train] Iter 05084 | loss 2.1018 | loss(rot) 0.6928 | loss(pos) 0.7398 | loss(seq) 0.6692 | grad 6.1948 | lr 0.0010 | time_forward 3.9410 | time_backward 5.5910 |
[2023-09-02 02:41:10,099::train::INFO] [train] Iter 05085 | loss 2.2839 | loss(rot) 1.9636 | loss(pos) 0.3199 | loss(seq) 0.0003 | grad 4.1297 | lr 0.0010 | time_forward 2.9210 | time_backward 3.8610 |
[2023-09-02 02:41:12,935::train::INFO] [train] Iter 05086 | loss 1.8743 | loss(rot) 0.1323 | loss(pos) 1.7291 | loss(seq) 0.0129 | grad 8.1645 | lr 0.0010 | time_forward 1.3140 | time_backward 1.5180 |
[2023-09-02 02:41:15,789::train::INFO] [train] Iter 05087 | loss 1.7228 | loss(rot) 0.4308 | loss(pos) 1.2727 | loss(seq) 0.0192 | grad 5.2458 | lr 0.0010 | time_forward 1.3580 | time_backward 1.4920 |
[2023-09-02 02:41:25,755::train::INFO] [train] Iter 05088 | loss 2.0488 | loss(rot) 0.9950 | loss(pos) 0.1856 | loss(seq) 0.8682 | grad 3.9562 | lr 0.0010 | time_forward 3.9410 | time_backward 6.0220 |
[2023-09-02 02:41:28,722::train::INFO] [train] Iter 05089 | loss 1.7805 | loss(rot) 0.7721 | loss(pos) 0.4762 | loss(seq) 0.5323 | grad 4.2740 | lr 0.0010 | time_forward 1.4300 | time_backward 1.5330 |
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