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[2023-10-23 19:04:18,395::train::INFO] [train] Iter 574378 | loss 1.3393 | loss(rot) 1.0135 | loss(pos) 0.1203 | loss(seq) 0.2055 | grad 5.4291 | lr 0.0000 | time_forward 3.0270 | time_backward 3.9950 |
[2023-10-23 19:04:26,881::train::INFO] [train] Iter 574379 | loss 0.3943 | loss(rot) 0.3656 | loss(pos) 0.0287 | loss(seq) 0.0000 | grad 16.2551 | lr 0.0000 | time_forward 3.5570 | time_backward 4.9140 |
[2023-10-23 19:04:35,983::train::INFO] [train] Iter 574380 | loss 0.7673 | loss(rot) 0.7166 | loss(pos) 0.0372 | loss(seq) 0.0135 | grad 2.6891 | lr 0.0000 | time_forward 3.8840 | time_backward 5.2140 |
[2023-10-23 19:04:45,754::train::INFO] [train] Iter 574381 | loss 0.3761 | loss(rot) 0.2036 | loss(pos) 0.0351 | loss(seq) 0.1374 | grad 2.4771 | lr 0.0000 | time_forward 4.0120 | time_backward 5.7550 |
[2023-10-23 19:04:53,911::train::INFO] [train] Iter 574382 | loss 0.5942 | loss(rot) 0.2453 | loss(pos) 0.0598 | loss(seq) 0.2891 | grad 3.2462 | lr 0.0000 | time_forward 3.4520 | time_backward 4.7020 |
[2023-10-23 19:04:56,678::train::INFO] [train] Iter 574383 | loss 0.5375 | loss(rot) 0.0569 | loss(pos) 0.1890 | loss(seq) 0.2916 | grad 3.5929 | lr 0.0000 | time_forward 1.3070 | time_backward 1.4570 |
[2023-10-23 19:05:06,361::train::INFO] [train] Iter 574384 | loss 0.9777 | loss(rot) 0.2966 | loss(pos) 0.4266 | loss(seq) 0.2544 | grad 3.6657 | lr 0.0000 | time_forward 3.9010 | time_backward 5.7450 |
[2023-10-23 19:05:16,076::train::INFO] [train] Iter 574385 | loss 0.4663 | loss(rot) 0.1076 | loss(pos) 0.0779 | loss(seq) 0.2808 | grad 2.7012 | lr 0.0000 | time_forward 3.9340 | time_backward 5.7780 |
[2023-10-23 19:05:19,084::train::INFO] [train] Iter 574386 | loss 0.6647 | loss(rot) 0.1747 | loss(pos) 0.1515 | loss(seq) 0.3385 | grad 3.1970 | lr 0.0000 | time_forward 1.3460 | time_backward 1.6580 |
[2023-10-23 19:05:27,713::train::INFO] [train] Iter 574387 | loss 1.5659 | loss(rot) 1.5429 | loss(pos) 0.0229 | loss(seq) 0.0001 | grad 4.9880 | lr 0.0000 | time_forward 3.6310 | time_backward 4.9950 |
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