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[2023-10-25 06:44:57,445::train::INFO] [train] Iter 592859 | loss 0.3422 | loss(rot) 0.1089 | loss(pos) 0.0186 | loss(seq) 0.2147 | grad 2.3104 | lr 0.0000 | time_forward 1.2810 | time_backward 1.4000 |
[2023-10-25 06:45:00,151::train::INFO] [train] Iter 592860 | loss 0.2856 | loss(rot) 0.0763 | loss(pos) 0.1708 | loss(seq) 0.0384 | grad 6.0029 | lr 0.0000 | time_forward 1.3100 | time_backward 1.3930 |
[2023-10-25 06:45:09,203::train::INFO] [train] Iter 592861 | loss 0.8778 | loss(rot) 0.5832 | loss(pos) 0.0808 | loss(seq) 0.2138 | grad 2.8311 | lr 0.0000 | time_forward 3.8460 | time_backward 5.2030 |
[2023-10-25 06:45:12,002::train::INFO] [train] Iter 592862 | loss 1.1219 | loss(rot) 0.9118 | loss(pos) 0.0320 | loss(seq) 0.1780 | grad 3.8258 | lr 0.0000 | time_forward 1.3490 | time_backward 1.4470 |
[2023-10-25 06:45:20,896::train::INFO] [train] Iter 592863 | loss 0.2937 | loss(rot) 0.2177 | loss(pos) 0.0174 | loss(seq) 0.0586 | grad 2.9576 | lr 0.0000 | time_forward 3.6650 | time_backward 5.2240 |
[2023-10-25 06:45:23,619::train::INFO] [train] Iter 592864 | loss 0.6486 | loss(rot) 0.3655 | loss(pos) 0.0390 | loss(seq) 0.2442 | grad 4.7989 | lr 0.0000 | time_forward 1.2970 | time_backward 1.4230 |
[2023-10-25 06:45:28,772::train::INFO] [train] Iter 592865 | loss 1.7885 | loss(rot) 1.7499 | loss(pos) 0.0379 | loss(seq) 0.0007 | grad 4.1904 | lr 0.0000 | time_forward 2.2200 | time_backward 2.9300 |
[2023-10-25 06:45:37,581::train::INFO] [train] Iter 592866 | loss 0.7481 | loss(rot) 0.3972 | loss(pos) 0.2188 | loss(seq) 0.1321 | grad 3.6178 | lr 0.0000 | time_forward 3.6080 | time_backward 5.1880 |
[2023-10-25 06:45:45,753::train::INFO] [train] Iter 592867 | loss 1.7542 | loss(rot) 1.5935 | loss(pos) 0.1083 | loss(seq) 0.0524 | grad 4.8551 | lr 0.0000 | time_forward 3.4950 | time_backward 4.6730 |
[2023-10-25 06:45:54,731::train::INFO] [train] Iter 592868 | loss 1.3144 | loss(rot) 0.7402 | loss(pos) 0.1122 | loss(seq) 0.4620 | grad 3.7521 | lr 0.0000 | time_forward 3.7190 | time_backward 5.2560 |
[2023-10-25 06:45:56,818::train::INFO] [train] Iter 592869 | loss 0.6727 | loss(rot) 0.3170 | loss(pos) 0.3487 | loss(seq) 0.0070 | grad 7.0293 | lr 0.0000 | time_forward 0.9920 | time_backward 1.0930 |
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