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[2023-10-23 17:44:47,377::train::INFO] [train] Iter 573679 | loss 0.2923 | loss(rot) 0.0833 | loss(pos) 0.0626 | loss(seq) 0.1464 | grad 2.6238 | lr 0.0000 | time_forward 1.3950 | time_backward 1.4610 |
[2023-10-23 17:44:49,655::train::INFO] [train] Iter 573680 | loss 1.0910 | loss(rot) 0.6990 | loss(pos) 0.0548 | loss(seq) 0.3371 | grad 2.7717 | lr 0.0000 | time_forward 1.0590 | time_backward 1.2150 |
[2023-10-23 17:44:58,019::train::INFO] [train] Iter 573681 | loss 0.6038 | loss(rot) 0.1345 | loss(pos) 0.0707 | loss(seq) 0.3986 | grad 3.5649 | lr 0.0000 | time_forward 3.6190 | time_backward 4.7420 |
[2023-10-23 17:45:00,586::train::INFO] [train] Iter 573682 | loss 1.6027 | loss(rot) 1.2398 | loss(pos) 0.0465 | loss(seq) 0.3164 | grad 6.3386 | lr 0.0000 | time_forward 1.1800 | time_backward 1.3830 |
[2023-10-23 17:45:03,380::train::INFO] [train] Iter 573683 | loss 0.3661 | loss(rot) 0.0591 | loss(pos) 0.3000 | loss(seq) 0.0071 | grad 5.8953 | lr 0.0000 | time_forward 1.3490 | time_backward 1.4420 |
[2023-10-23 17:45:13,173::train::INFO] [train] Iter 573684 | loss 1.2308 | loss(rot) 0.5898 | loss(pos) 0.2062 | loss(seq) 0.4347 | grad 6.0722 | lr 0.0000 | time_forward 3.9990 | time_backward 5.7720 |
[2023-10-23 17:45:15,906::train::INFO] [train] Iter 573685 | loss 0.5004 | loss(rot) 0.1594 | loss(pos) 0.1185 | loss(seq) 0.2226 | grad 3.3409 | lr 0.0000 | time_forward 1.3080 | time_backward 1.4220 |
[2023-10-23 17:45:25,176::train::INFO] [train] Iter 573686 | loss 0.2154 | loss(rot) 0.1286 | loss(pos) 0.0594 | loss(seq) 0.0275 | grad 2.7450 | lr 0.0000 | time_forward 4.0390 | time_backward 5.2270 |
[2023-10-23 17:45:33,928::train::INFO] [train] Iter 573687 | loss 0.3090 | loss(rot) 0.1531 | loss(pos) 0.0212 | loss(seq) 0.1347 | grad 2.2196 | lr 0.0000 | time_forward 3.6940 | time_backward 5.0560 |
[2023-10-23 17:45:37,268::train::INFO] [train] Iter 573688 | loss 0.4793 | loss(rot) 0.3301 | loss(pos) 0.1047 | loss(seq) 0.0446 | grad 2.0529 | lr 0.0000 | time_forward 1.5090 | time_backward 1.8270 |
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