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[2023-10-24 16:48:27,486::train::INFO] [train] Iter 585467 | loss 0.5244 | loss(rot) 0.1382 | loss(pos) 0.0410 | loss(seq) 0.3453 | grad 3.4123 | lr 0.0000 | time_forward 3.4110 | time_backward 4.5570 |
[2023-10-24 16:48:34,853::train::INFO] [train] Iter 585468 | loss 0.3989 | loss(rot) 0.2022 | loss(pos) 0.0834 | loss(seq) 0.1133 | grad 3.5598 | lr 0.0000 | time_forward 3.1280 | time_backward 4.2360 |
[2023-10-24 16:48:37,681::train::INFO] [train] Iter 585469 | loss 0.5477 | loss(rot) 0.1217 | loss(pos) 0.1347 | loss(seq) 0.2914 | grad 4.0735 | lr 0.0000 | time_forward 1.3540 | time_backward 1.4700 |
[2023-10-24 16:48:40,454::train::INFO] [train] Iter 585470 | loss 0.4799 | loss(rot) 0.0840 | loss(pos) 0.3671 | loss(seq) 0.0288 | grad 3.2238 | lr 0.0000 | time_forward 1.3380 | time_backward 1.4320 |
[2023-10-24 16:48:49,096::train::INFO] [train] Iter 585471 | loss 0.3108 | loss(rot) 0.0721 | loss(pos) 0.0229 | loss(seq) 0.2158 | grad 2.1697 | lr 0.0000 | time_forward 3.5850 | time_backward 5.0520 |
[2023-10-24 16:48:51,789::train::INFO] [train] Iter 585472 | loss 0.3348 | loss(rot) 0.1006 | loss(pos) 0.2158 | loss(seq) 0.0184 | grad 4.7211 | lr 0.0000 | time_forward 1.2970 | time_backward 1.3930 |
[2023-10-24 16:49:00,437::train::INFO] [train] Iter 585473 | loss 0.9714 | loss(rot) 0.6082 | loss(pos) 0.0609 | loss(seq) 0.3023 | grad 4.6103 | lr 0.0000 | time_forward 3.6890 | time_backward 4.9560 |
[2023-10-24 16:49:02,958::train::INFO] [train] Iter 585474 | loss 0.9315 | loss(rot) 0.7802 | loss(pos) 0.0225 | loss(seq) 0.1289 | grad 4.4166 | lr 0.0000 | time_forward 1.2120 | time_backward 1.3050 |
[2023-10-24 16:49:10,835::train::INFO] [train] Iter 585475 | loss 1.6136 | loss(rot) 1.2512 | loss(pos) 0.0864 | loss(seq) 0.2760 | grad 5.5008 | lr 0.0000 | time_forward 3.3580 | time_backward 4.5170 |
[2023-10-24 16:49:18,950::train::INFO] [train] Iter 585476 | loss 0.3775 | loss(rot) 0.3569 | loss(pos) 0.0168 | loss(seq) 0.0038 | grad 2.8430 | lr 0.0000 | time_forward 3.3600 | time_backward 4.7510 |
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