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[2023-09-03 01:39:57,090::train::INFO] [train] Iter 16469 | loss 1.2646 | loss(rot) 0.2061 | loss(pos) 1.0270 | loss(seq) 0.0315 | grad 5.4032 | lr 0.0010 | time_forward 3.6540 | time_backward 4.9130 |
[2023-09-03 01:40:06,960::train::INFO] [train] Iter 16470 | loss 1.2543 | loss(rot) 0.6509 | loss(pos) 0.1096 | loss(seq) 0.4938 | grad 2.8413 | lr 0.0010 | time_forward 3.8340 | time_backward 6.0320 |
[2023-09-03 01:40:14,783::train::INFO] [train] Iter 16471 | loss 0.9643 | loss(rot) 0.3209 | loss(pos) 0.2649 | loss(seq) 0.3785 | grad 4.2866 | lr 0.0010 | time_forward 3.6320 | time_backward 4.1880 |
[2023-09-03 01:40:24,687::train::INFO] [train] Iter 16472 | loss 1.0961 | loss(rot) 0.2072 | loss(pos) 0.4860 | loss(seq) 0.4029 | grad 3.7139 | lr 0.0010 | time_forward 4.0390 | time_backward 5.8620 |
[2023-09-03 01:40:31,431::train::INFO] [train] Iter 16473 | loss 2.4727 | loss(rot) 2.3173 | loss(pos) 0.1102 | loss(seq) 0.0452 | grad 5.1255 | lr 0.0010 | time_forward 2.9560 | time_backward 3.7840 |
[2023-09-03 01:40:40,116::train::INFO] [train] Iter 16474 | loss 1.8834 | loss(rot) 1.2585 | loss(pos) 0.1351 | loss(seq) 0.4898 | grad 4.6089 | lr 0.0010 | time_forward 3.6050 | time_backward 5.0770 |
[2023-09-03 01:40:48,920::train::INFO] [train] Iter 16475 | loss 2.2615 | loss(rot) 1.6334 | loss(pos) 0.1737 | loss(seq) 0.4545 | grad 4.6904 | lr 0.0010 | time_forward 4.1540 | time_backward 4.6470 |
[2023-09-03 01:40:57,036::train::INFO] [train] Iter 16476 | loss 1.3257 | loss(rot) 0.3541 | loss(pos) 0.5061 | loss(seq) 0.4654 | grad 5.3575 | lr 0.0010 | time_forward 3.4840 | time_backward 4.6280 |
[2023-09-03 01:40:59,797::train::INFO] [train] Iter 16477 | loss 1.6396 | loss(rot) 1.0302 | loss(pos) 0.1683 | loss(seq) 0.4411 | grad 5.0162 | lr 0.0010 | time_forward 1.3100 | time_backward 1.4480 |
[2023-09-03 01:41:05,826::train::INFO] [train] Iter 16478 | loss 1.6153 | loss(rot) 1.3293 | loss(pos) 0.1104 | loss(seq) 0.1757 | grad 6.9222 | lr 0.0010 | time_forward 2.5090 | time_backward 3.5160 |
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