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[2023-10-23 13:55:39,802::train::INFO] [train] Iter 571581 | loss 1.7063 | loss(rot) 1.5495 | loss(pos) 0.1477 | loss(seq) 0.0092 | grad 4.3277 | lr 0.0000 | time_forward 3.7140 | time_backward 4.8730 |
[2023-10-23 13:55:47,533::train::INFO] [train] Iter 571582 | loss 0.2477 | loss(rot) 0.2032 | loss(pos) 0.0267 | loss(seq) 0.0178 | grad 2.3580 | lr 0.0000 | time_forward 3.3080 | time_backward 4.4200 |
[2023-10-23 13:55:56,014::train::INFO] [train] Iter 571583 | loss 1.1106 | loss(rot) 0.7779 | loss(pos) 0.0530 | loss(seq) 0.2797 | grad 4.6022 | lr 0.0000 | time_forward 3.4760 | time_backward 5.0020 |
[2023-10-23 13:56:03,642::train::INFO] [train] Iter 571584 | loss 1.0548 | loss(rot) 0.0059 | loss(pos) 1.0485 | loss(seq) 0.0004 | grad 20.6763 | lr 0.0000 | time_forward 3.2530 | time_backward 4.3710 |
[2023-10-23 13:56:12,229::train::INFO] [train] Iter 571585 | loss 0.3152 | loss(rot) 0.1329 | loss(pos) 0.0151 | loss(seq) 0.1672 | grad 2.1155 | lr 0.0000 | time_forward 3.5100 | time_backward 5.0750 |
[2023-10-23 13:56:20,068::train::INFO] [train] Iter 571586 | loss 0.2969 | loss(rot) 0.1706 | loss(pos) 0.1143 | loss(seq) 0.0120 | grad 2.1324 | lr 0.0000 | time_forward 3.3980 | time_backward 4.4380 |
[2023-10-23 13:56:22,930::train::INFO] [train] Iter 571587 | loss 0.5745 | loss(rot) 0.1566 | loss(pos) 0.0651 | loss(seq) 0.3529 | grad 3.0737 | lr 0.0000 | time_forward 1.3230 | time_backward 1.5360 |
[2023-10-23 13:56:30,844::train::INFO] [train] Iter 571588 | loss 1.0021 | loss(rot) 0.8524 | loss(pos) 0.0195 | loss(seq) 0.1302 | grad 5.5928 | lr 0.0000 | time_forward 3.3800 | time_backward 4.5300 |
[2023-10-23 13:56:38,433::train::INFO] [train] Iter 571589 | loss 0.7720 | loss(rot) 0.0538 | loss(pos) 0.7092 | loss(seq) 0.0090 | grad 6.8996 | lr 0.0000 | time_forward 3.2700 | time_backward 4.3160 |
[2023-10-23 13:56:44,525::train::INFO] [train] Iter 571590 | loss 0.2978 | loss(rot) 0.1653 | loss(pos) 0.0910 | loss(seq) 0.0415 | grad 2.9257 | lr 0.0000 | time_forward 2.6550 | time_backward 3.4340 |
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