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[2023-09-03 02:14:49,793::train::INFO] [train] Iter 16770 | loss 0.7793 | loss(rot) 0.1531 | loss(pos) 0.3327 | loss(seq) 0.2934 | grad 3.2324 | lr 0.0010 | time_forward 3.6920 | time_backward 5.4600 |
[2023-09-03 02:14:59,652::train::INFO] [train] Iter 16771 | loss 0.8719 | loss(rot) 0.4001 | loss(pos) 0.1630 | loss(seq) 0.3088 | grad 3.9502 | lr 0.0010 | time_forward 3.3670 | time_backward 6.4790 |
[2023-09-03 02:15:02,604::train::INFO] [train] Iter 16772 | loss 1.4528 | loss(rot) 0.9841 | loss(pos) 0.0970 | loss(seq) 0.3718 | grad 3.8352 | lr 0.0010 | time_forward 1.3970 | time_backward 1.5520 |
[2023-09-03 02:15:12,204::train::INFO] [train] Iter 16773 | loss 1.0649 | loss(rot) 0.4327 | loss(pos) 0.1471 | loss(seq) 0.4851 | grad 3.8677 | lr 0.0010 | time_forward 4.0690 | time_backward 5.5270 |
[2023-09-03 02:15:22,201::train::INFO] [train] Iter 16774 | loss 1.4713 | loss(rot) 1.2127 | loss(pos) 0.2555 | loss(seq) 0.0031 | grad 7.6484 | lr 0.0010 | time_forward 4.1300 | time_backward 5.8640 |
[2023-09-03 02:15:24,831::train::INFO] [train] Iter 16775 | loss 1.0656 | loss(rot) 0.2954 | loss(pos) 0.3443 | loss(seq) 0.4259 | grad 4.0461 | lr 0.0010 | time_forward 1.2540 | time_backward 1.3720 |
[2023-09-03 02:15:33,230::train::INFO] [train] Iter 16776 | loss 3.4897 | loss(rot) 0.0179 | loss(pos) 3.4718 | loss(seq) 0.0000 | grad 7.6079 | lr 0.0010 | time_forward 3.6160 | time_backward 4.7800 |
[2023-09-03 02:15:41,846::train::INFO] [train] Iter 16777 | loss 0.9596 | loss(rot) 0.0716 | loss(pos) 0.8751 | loss(seq) 0.0129 | grad 5.2446 | lr 0.0010 | time_forward 3.6910 | time_backward 4.9220 |
[2023-09-03 02:15:50,356::train::INFO] [train] Iter 16778 | loss 1.8017 | loss(rot) 1.2303 | loss(pos) 0.1966 | loss(seq) 0.3748 | grad 5.5760 | lr 0.0010 | time_forward 3.5610 | time_backward 4.9450 |
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