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[2023-10-23 07:40:28,086::train::INFO] [train] Iter 568184 | loss 0.2727 | loss(rot) 0.1141 | loss(pos) 0.0468 | loss(seq) 0.1118 | grad 1.9220 | lr 0.0000 | time_forward 3.4340 | time_backward 4.4600 |
[2023-10-23 07:40:35,909::train::INFO] [train] Iter 568185 | loss 1.3235 | loss(rot) 1.2927 | loss(pos) 0.0308 | loss(seq) 0.0000 | grad 3.9764 | lr 0.0000 | time_forward 3.3720 | time_backward 4.4490 |
[2023-10-23 07:40:38,335::train::INFO] [train] Iter 568186 | loss 0.1475 | loss(rot) 0.1245 | loss(pos) 0.0186 | loss(seq) 0.0044 | grad 3.0741 | lr 0.0000 | time_forward 1.1580 | time_backward 1.2640 |
[2023-10-23 07:40:45,063::train::INFO] [train] Iter 568187 | loss 1.0010 | loss(rot) 0.6022 | loss(pos) 0.1414 | loss(seq) 0.2575 | grad 3.6464 | lr 0.0000 | time_forward 2.8530 | time_backward 3.8710 |
[2023-10-23 07:40:52,517::train::INFO] [train] Iter 568188 | loss 0.7393 | loss(rot) 0.6069 | loss(pos) 0.0171 | loss(seq) 0.1153 | grad 3.0952 | lr 0.0000 | time_forward 3.2310 | time_backward 4.2200 |
[2023-10-23 07:40:58,890::train::INFO] [train] Iter 568189 | loss 0.5914 | loss(rot) 0.1786 | loss(pos) 0.0478 | loss(seq) 0.3650 | grad 5.3803 | lr 0.0000 | time_forward 2.7110 | time_backward 3.6590 |
[2023-10-23 07:41:06,460::train::INFO] [train] Iter 568190 | loss 0.3622 | loss(rot) 0.1188 | loss(pos) 0.1131 | loss(seq) 0.1302 | grad 2.9024 | lr 0.0000 | time_forward 3.2200 | time_backward 4.3470 |
[2023-10-23 07:41:14,057::train::INFO] [train] Iter 568191 | loss 0.3344 | loss(rot) 0.2351 | loss(pos) 0.0500 | loss(seq) 0.0493 | grad 2.6593 | lr 0.0000 | time_forward 3.3050 | time_backward 4.2880 |
[2023-10-23 07:41:21,225::train::INFO] [train] Iter 568192 | loss 0.7927 | loss(rot) 0.3176 | loss(pos) 0.1598 | loss(seq) 0.3154 | grad 3.1982 | lr 0.0000 | time_forward 3.1650 | time_backward 4.0000 |
[2023-10-23 07:41:28,017::train::INFO] [train] Iter 568193 | loss 1.5473 | loss(rot) 0.7521 | loss(pos) 0.2223 | loss(seq) 0.5730 | grad 4.5139 | lr 0.0000 | time_forward 2.9060 | time_backward 3.8840 |
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