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[2023-10-24 10:05:00,807::train::INFO] [train] Iter 581971 | loss 0.7282 | loss(rot) 0.4723 | loss(pos) 0.0509 | loss(seq) 0.2050 | grad 6.2848 | lr 0.0000 | time_forward 4.0270 | time_backward 5.9080 |
[2023-10-24 10:05:03,664::train::INFO] [train] Iter 581972 | loss 2.1706 | loss(rot) 1.7121 | loss(pos) 0.1103 | loss(seq) 0.3482 | grad 8.8415 | lr 0.0000 | time_forward 1.3770 | time_backward 1.4760 |
[2023-10-24 10:05:12,841::train::INFO] [train] Iter 581973 | loss 0.8703 | loss(rot) 0.5292 | loss(pos) 0.2072 | loss(seq) 0.1339 | grad 4.3532 | lr 0.0000 | time_forward 3.8360 | time_backward 5.3390 |
[2023-10-24 10:05:20,871::train::INFO] [train] Iter 581974 | loss 2.3175 | loss(rot) 2.2987 | loss(pos) 0.0130 | loss(seq) 0.0057 | grad 4.5341 | lr 0.0000 | time_forward 3.3420 | time_backward 4.6850 |
[2023-10-24 10:05:30,964::train::INFO] [train] Iter 581975 | loss 0.9773 | loss(rot) 0.5984 | loss(pos) 0.0715 | loss(seq) 0.3074 | grad 4.4995 | lr 0.0000 | time_forward 4.2230 | time_backward 5.8670 |
[2023-10-24 10:05:33,689::train::INFO] [train] Iter 581976 | loss 0.4016 | loss(rot) 0.0839 | loss(pos) 0.0785 | loss(seq) 0.2391 | grad 2.3498 | lr 0.0000 | time_forward 1.2930 | time_backward 1.4290 |
[2023-10-24 10:05:42,747::train::INFO] [train] Iter 581977 | loss 0.5574 | loss(rot) 0.5336 | loss(pos) 0.0237 | loss(seq) 0.0002 | grad 78.5808 | lr 0.0000 | time_forward 3.8490 | time_backward 5.2050 |
[2023-10-24 10:05:49,924::train::INFO] [train] Iter 581978 | loss 0.3044 | loss(rot) 0.1703 | loss(pos) 0.0134 | loss(seq) 0.1206 | grad 2.7725 | lr 0.0000 | time_forward 3.1490 | time_backward 4.0250 |
[2023-10-24 10:05:52,652::train::INFO] [train] Iter 581979 | loss 0.5031 | loss(rot) 0.2799 | loss(pos) 0.0507 | loss(seq) 0.1725 | grad 3.4854 | lr 0.0000 | time_forward 1.3130 | time_backward 1.4120 |
[2023-10-24 10:06:01,110::train::INFO] [train] Iter 581980 | loss 0.3725 | loss(rot) 0.3052 | loss(pos) 0.0145 | loss(seq) 0.0528 | grad 2.4983 | lr 0.0000 | time_forward 3.5490 | time_backward 4.8720 |
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