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[2023-10-23 18:29:48,761::train::INFO] [train] Iter 574078 | loss 1.4885 | loss(rot) 1.0361 | loss(pos) 0.1498 | loss(seq) 0.3026 | grad 3.3234 | lr 0.0000 | time_forward 3.0030 | time_backward 3.7870 |
[2023-10-23 18:29:56,299::train::INFO] [train] Iter 574079 | loss 1.4372 | loss(rot) 0.8694 | loss(pos) 0.0606 | loss(seq) 0.5072 | grad 3.8430 | lr 0.0000 | time_forward 3.2040 | time_backward 4.3320 |
[2023-10-23 18:30:03,645::train::INFO] [train] Iter 574080 | loss 0.2945 | loss(rot) 0.0529 | loss(pos) 0.0661 | loss(seq) 0.1755 | grad 2.8943 | lr 0.0000 | time_forward 3.1150 | time_backward 4.2270 |
[2023-10-23 18:30:06,390::train::INFO] [train] Iter 574081 | loss 0.1543 | loss(rot) 0.0980 | loss(pos) 0.0314 | loss(seq) 0.0249 | grad 4.6498 | lr 0.0000 | time_forward 1.3060 | time_backward 1.4370 |
[2023-10-23 18:30:15,263::train::INFO] [train] Iter 574082 | loss 1.8736 | loss(rot) 1.5310 | loss(pos) 0.0936 | loss(seq) 0.2491 | grad 7.8186 | lr 0.0000 | time_forward 3.9500 | time_backward 4.9170 |
[2023-10-23 18:30:23,106::train::INFO] [train] Iter 574083 | loss 0.1739 | loss(rot) 0.0478 | loss(pos) 0.0193 | loss(seq) 0.1068 | grad 1.5819 | lr 0.0000 | time_forward 3.3890 | time_backward 4.4510 |
[2023-10-23 18:30:29,530::train::INFO] [train] Iter 574084 | loss 0.9251 | loss(rot) 0.1639 | loss(pos) 0.0870 | loss(seq) 0.6741 | grad 3.7140 | lr 0.0000 | time_forward 2.7650 | time_backward 3.6560 |
[2023-10-23 18:30:37,129::train::INFO] [train] Iter 574085 | loss 1.3972 | loss(rot) 1.0705 | loss(pos) 0.0449 | loss(seq) 0.2818 | grad 4.2410 | lr 0.0000 | time_forward 3.2570 | time_backward 4.3380 |
[2023-10-23 18:30:45,879::train::INFO] [train] Iter 574086 | loss 1.5518 | loss(rot) 1.3008 | loss(pos) 0.1145 | loss(seq) 0.1365 | grad 8.0833 | lr 0.0000 | time_forward 3.7330 | time_backward 5.0130 |
[2023-10-23 18:30:53,658::train::INFO] [train] Iter 574087 | loss 0.2236 | loss(rot) 0.0910 | loss(pos) 0.0955 | loss(seq) 0.0370 | grad 2.9903 | lr 0.0000 | time_forward 3.3590 | time_backward 4.4170 |
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