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[2023-09-03 03:44:05,464::train::INFO] [train] Iter 17567 | loss 1.2531 | loss(rot) 0.3479 | loss(pos) 0.2646 | loss(seq) 0.6406 | grad 3.4906 | lr 0.0010 | time_forward 3.6640 | time_backward 5.0460 |
[2023-09-03 03:44:13,726::train::INFO] [train] Iter 17568 | loss 1.3169 | loss(rot) 0.9305 | loss(pos) 0.0965 | loss(seq) 0.2899 | grad 4.5864 | lr 0.0010 | time_forward 3.3100 | time_backward 4.9470 |
[2023-09-03 03:44:22,682::train::INFO] [train] Iter 17569 | loss 2.9089 | loss(rot) 0.0528 | loss(pos) 2.8556 | loss(seq) 0.0005 | grad 11.8511 | lr 0.0010 | time_forward 3.7120 | time_backward 5.2400 |
[2023-09-03 03:44:31,811::train::INFO] [train] Iter 17570 | loss 1.0186 | loss(rot) 0.3305 | loss(pos) 0.1888 | loss(seq) 0.4993 | grad 2.5668 | lr 0.0010 | time_forward 3.8110 | time_backward 5.3130 |
[2023-09-03 03:44:40,765::train::INFO] [train] Iter 17571 | loss 2.1941 | loss(rot) 1.5794 | loss(pos) 0.1944 | loss(seq) 0.4202 | grad 6.9730 | lr 0.0010 | time_forward 3.6620 | time_backward 5.2890 |
[2023-09-03 03:44:50,532::train::INFO] [train] Iter 17572 | loss 1.1147 | loss(rot) 0.9264 | loss(pos) 0.1160 | loss(seq) 0.0723 | grad 7.6381 | lr 0.0010 | time_forward 4.1190 | time_backward 5.6450 |
[2023-09-03 03:45:00,672::train::INFO] [train] Iter 17573 | loss 1.4917 | loss(rot) 1.0323 | loss(pos) 0.1416 | loss(seq) 0.3178 | grad 5.5286 | lr 0.0010 | time_forward 3.9390 | time_backward 6.1980 |
[2023-09-03 03:45:08,901::train::INFO] [train] Iter 17574 | loss 2.9041 | loss(rot) 0.1080 | loss(pos) 2.7957 | loss(seq) 0.0003 | grad 11.0280 | lr 0.0010 | time_forward 3.5110 | time_backward 4.7130 |
[2023-09-03 03:45:18,669::train::INFO] [train] Iter 17575 | loss 0.6702 | loss(rot) 0.3468 | loss(pos) 0.1520 | loss(seq) 0.1713 | grad 2.5352 | lr 0.0010 | time_forward 3.9260 | time_backward 5.8380 |
[2023-09-03 03:45:27,299::train::INFO] [train] Iter 17576 | loss 0.8481 | loss(rot) 0.2554 | loss(pos) 0.1696 | loss(seq) 0.4231 | grad 2.4997 | lr 0.0010 | time_forward 3.4120 | time_backward 5.2140 |
[2023-09-03 03:45:35,908::train::INFO] [train] Iter 17577 | loss 3.0296 | loss(rot) 2.2131 | loss(pos) 0.1880 | loss(seq) 0.6285 | grad 9.1335 | lr 0.0010 | time_forward 3.6740 | time_backward 4.9320 |
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