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[2023-10-22 18:30:48,094::train::INFO] [train] Iter 560592 | loss 0.4716 | loss(rot) 0.3646 | loss(pos) 0.0388 | loss(seq) 0.0683 | grad 2.9951 | lr 0.0000 | time_forward 1.3140 | time_backward 1.4380 |
[2023-10-22 18:30:57,121::train::INFO] [train] Iter 560593 | loss 1.6344 | loss(rot) 0.9375 | loss(pos) 0.3295 | loss(seq) 0.3674 | grad 2.9148 | lr 0.0000 | time_forward 3.8260 | time_backward 5.1980 |
[2023-10-22 18:30:59,989::train::INFO] [train] Iter 560594 | loss 0.7349 | loss(rot) 0.1318 | loss(pos) 0.0416 | loss(seq) 0.5615 | grad 2.7726 | lr 0.0000 | time_forward 1.3630 | time_backward 1.5010 |
[2023-10-22 18:31:03,039::train::INFO] [train] Iter 560595 | loss 1.2328 | loss(rot) 1.1393 | loss(pos) 0.0457 | loss(seq) 0.0478 | grad 12.7034 | lr 0.0000 | time_forward 1.4030 | time_backward 1.6060 |
[2023-10-22 18:31:11,098::train::INFO] [train] Iter 560596 | loss 0.2013 | loss(rot) 0.1785 | loss(pos) 0.0222 | loss(seq) 0.0007 | grad 3.8651 | lr 0.0000 | time_forward 3.4130 | time_backward 4.6420 |
[2023-10-22 18:31:14,422::train::INFO] [train] Iter 560597 | loss 1.5996 | loss(rot) 1.1522 | loss(pos) 0.0773 | loss(seq) 0.3701 | grad 3.0132 | lr 0.0000 | time_forward 1.4670 | time_backward 1.8530 |
[2023-10-22 18:31:18,062::train::INFO] [train] Iter 560598 | loss 1.5237 | loss(rot) 0.9042 | loss(pos) 0.3009 | loss(seq) 0.3186 | grad 5.1436 | lr 0.0000 | time_forward 1.7100 | time_backward 1.9260 |
[2023-10-22 18:31:26,667::train::INFO] [train] Iter 560599 | loss 0.8214 | loss(rot) 0.6582 | loss(pos) 0.0363 | loss(seq) 0.1269 | grad 4.6588 | lr 0.0000 | time_forward 3.6510 | time_backward 4.9510 |
[2023-10-22 18:31:35,483::train::INFO] [train] Iter 560600 | loss 0.8232 | loss(rot) 0.3602 | loss(pos) 0.2159 | loss(seq) 0.2471 | grad 4.9485 | lr 0.0000 | time_forward 3.7360 | time_backward 5.0650 |
[2023-10-22 18:31:38,314::train::INFO] [train] Iter 560601 | loss 0.6322 | loss(rot) 0.2794 | loss(pos) 0.1572 | loss(seq) 0.1956 | grad 4.5418 | lr 0.0000 | time_forward 1.3290 | time_backward 1.4990 |
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