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[2023-09-02 21:32:19,173::train::INFO] [train] Iter 14472 | loss 1.0587 | loss(rot) 0.7774 | loss(pos) 0.1830 | loss(seq) 0.0983 | grad 4.8484 | lr 0.0010 | time_forward 3.6970 | time_backward 5.1180 |
[2023-09-02 21:32:29,052::train::INFO] [train] Iter 14473 | loss 1.7924 | loss(rot) 1.5804 | loss(pos) 0.2016 | loss(seq) 0.0104 | grad 11.0188 | lr 0.0010 | time_forward 4.0500 | time_backward 5.8260 |
[2023-09-02 21:32:38,992::train::INFO] [train] Iter 14474 | loss 1.4011 | loss(rot) 0.5157 | loss(pos) 0.6613 | loss(seq) 0.2241 | grad 3.9744 | lr 0.0010 | time_forward 4.0280 | time_backward 5.9060 |
[2023-09-02 21:32:47,222::train::INFO] [train] Iter 14475 | loss 1.2369 | loss(rot) 1.0204 | loss(pos) 0.2154 | loss(seq) 0.0011 | grad 6.8247 | lr 0.0010 | time_forward 3.3980 | time_backward 4.8090 |
[2023-09-02 21:32:57,285::train::INFO] [train] Iter 14476 | loss 1.9222 | loss(rot) 1.2664 | loss(pos) 0.1690 | loss(seq) 0.4867 | grad 7.5559 | lr 0.0010 | time_forward 4.0270 | time_backward 6.0320 |
[2023-09-02 21:32:59,780::train::INFO] [train] Iter 14477 | loss 3.2715 | loss(rot) 0.0146 | loss(pos) 3.2570 | loss(seq) 0.0000 | grad 10.6278 | lr 0.0010 | time_forward 1.1820 | time_backward 1.3100 |
[2023-09-02 21:33:08,812::train::INFO] [train] Iter 14478 | loss 1.3804 | loss(rot) 1.2580 | loss(pos) 0.1192 | loss(seq) 0.0032 | grad 6.7229 | lr 0.0010 | time_forward 3.7730 | time_backward 5.2260 |
[2023-09-02 21:33:17,425::train::INFO] [train] Iter 14479 | loss 1.1181 | loss(rot) 0.9890 | loss(pos) 0.1291 | loss(seq) 0.0000 | grad 3.6304 | lr 0.0010 | time_forward 3.6150 | time_backward 4.9950 |
[2023-09-02 21:33:27,611::train::INFO] [train] Iter 14480 | loss 0.8836 | loss(rot) 0.2642 | loss(pos) 0.5358 | loss(seq) 0.0836 | grad 3.2315 | lr 0.0010 | time_forward 4.3010 | time_backward 5.8810 |
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