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[2023-10-24 15:36:52,785::train::INFO] [train] Iter 584768 | loss 0.2072 | loss(rot) 0.1427 | loss(pos) 0.0200 | loss(seq) 0.0446 | grad 2.1869 | lr 0.0000 | time_forward 3.3180 | time_backward 4.2970 |
[2023-10-24 15:36:59,622::train::INFO] [train] Iter 584769 | loss 0.4362 | loss(rot) 0.1372 | loss(pos) 0.0214 | loss(seq) 0.2776 | grad 1.9321 | lr 0.0000 | time_forward 2.9610 | time_backward 3.8720 |
[2023-10-24 15:37:08,654::train::INFO] [train] Iter 584770 | loss 0.7316 | loss(rot) 0.3961 | loss(pos) 0.0689 | loss(seq) 0.2666 | grad 2.8381 | lr 0.0000 | time_forward 4.0500 | time_backward 4.9790 |
[2023-10-24 15:37:16,542::train::INFO] [train] Iter 584771 | loss 1.6352 | loss(rot) 0.8249 | loss(pos) 0.3062 | loss(seq) 0.5040 | grad 5.3255 | lr 0.0000 | time_forward 3.1970 | time_backward 4.6880 |
[2023-10-24 15:37:23,177::train::INFO] [train] Iter 584772 | loss 1.2546 | loss(rot) 0.2477 | loss(pos) 1.0018 | loss(seq) 0.0051 | grad 13.7390 | lr 0.0000 | time_forward 2.8740 | time_backward 3.7570 |
[2023-10-24 15:37:31,068::train::INFO] [train] Iter 584773 | loss 1.1393 | loss(rot) 0.5461 | loss(pos) 0.2247 | loss(seq) 0.3685 | grad 3.5985 | lr 0.0000 | time_forward 3.3130 | time_backward 4.5750 |
[2023-10-24 15:37:39,155::train::INFO] [train] Iter 584774 | loss 1.1117 | loss(rot) 1.0683 | loss(pos) 0.0432 | loss(seq) 0.0001 | grad 2.8666 | lr 0.0000 | time_forward 3.3090 | time_backward 4.7740 |
[2023-10-24 15:37:41,870::train::INFO] [train] Iter 584775 | loss 0.2667 | loss(rot) 0.2274 | loss(pos) 0.0384 | loss(seq) 0.0010 | grad 2.7778 | lr 0.0000 | time_forward 1.2980 | time_backward 1.4150 |
[2023-10-24 15:37:50,464::train::INFO] [train] Iter 584776 | loss 1.4875 | loss(rot) 0.9041 | loss(pos) 0.1196 | loss(seq) 0.4638 | grad 4.0215 | lr 0.0000 | time_forward 3.6670 | time_backward 4.8790 |
[2023-10-24 15:37:57,122::train::INFO] [train] Iter 584777 | loss 0.4428 | loss(rot) 0.1915 | loss(pos) 0.1063 | loss(seq) 0.1450 | grad 4.1202 | lr 0.0000 | time_forward 2.8630 | time_backward 3.7910 |
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