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[2023-09-01 17:10:34,332::train::INFO] [train] Iter 00385 | loss 2.6087 | loss(rot) 0.5769 | loss(pos) 1.7999 | loss(seq) 0.2318 | grad 3.8922 | lr 0.0010 | time_forward 3.2320 | time_backward 4.7500 |
[2023-09-01 17:10:42,217::train::INFO] [train] Iter 00386 | loss 2.4966 | loss(rot) 1.0312 | loss(pos) 0.9489 | loss(seq) 0.5165 | grad 4.9925 | lr 0.0010 | time_forward 3.2880 | time_backward 4.5940 |
[2023-09-01 17:10:51,404::train::INFO] [train] Iter 00387 | loss 2.8219 | loss(rot) 2.0209 | loss(pos) 0.4738 | loss(seq) 0.3272 | grad 4.2253 | lr 0.0010 | time_forward 3.9030 | time_backward 5.2810 |
[2023-09-01 17:11:02,535::train::INFO] [train] Iter 00388 | loss 1.9318 | loss(rot) 1.0651 | loss(pos) 0.6993 | loss(seq) 0.1674 | grad 5.6134 | lr 0.0010 | time_forward 4.4990 | time_backward 6.6280 |
[2023-09-01 17:11:10,640::train::INFO] [train] Iter 00389 | loss 3.1722 | loss(rot) 2.2360 | loss(pos) 0.4655 | loss(seq) 0.4706 | grad 5.2540 | lr 0.0010 | time_forward 3.4420 | time_backward 4.6600 |
[2023-09-01 17:11:21,666::train::INFO] [train] Iter 00390 | loss 3.3782 | loss(rot) 0.1525 | loss(pos) 3.1183 | loss(seq) 0.1074 | grad 7.4934 | lr 0.0010 | time_forward 4.2390 | time_backward 6.7830 |
[2023-09-01 17:11:31,413::train::INFO] [train] Iter 00391 | loss 3.8193 | loss(rot) 3.3586 | loss(pos) 0.4563 | loss(seq) 0.0044 | grad 4.3128 | lr 0.0010 | time_forward 3.8620 | time_backward 5.8820 |
[2023-09-01 17:11:34,196::train::INFO] [train] Iter 00392 | loss 2.5170 | loss(rot) 0.8511 | loss(pos) 1.3110 | loss(seq) 0.3548 | grad 5.2991 | lr 0.0010 | time_forward 1.2980 | time_backward 1.4810 |
[2023-09-01 17:11:37,184::train::INFO] [train] Iter 00393 | loss 3.6832 | loss(rot) 2.5155 | loss(pos) 0.6799 | loss(seq) 0.4878 | grad 6.2729 | lr 0.0010 | time_forward 1.4430 | time_backward 1.5420 |
[2023-09-01 17:11:46,559::train::INFO] [train] Iter 00394 | loss 2.7937 | loss(rot) 2.4105 | loss(pos) 0.3565 | loss(seq) 0.0267 | grad 3.5479 | lr 0.0010 | time_forward 4.0410 | time_backward 5.3300 |
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