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[2023-10-24 23:45:46,998::train::INFO] [train] Iter 589062 | loss 0.3729 | loss(rot) 0.0521 | loss(pos) 0.0325 | loss(seq) 0.2883 | grad 2.3374 | lr 0.0000 | time_forward 1.5370 | time_backward 1.7460 |
[2023-10-24 23:45:57,803::train::INFO] [train] Iter 589063 | loss 0.9615 | loss(rot) 0.6825 | loss(pos) 0.1446 | loss(seq) 0.1344 | grad 34.1390 | lr 0.0000 | time_forward 4.5620 | time_backward 6.2390 |
[2023-10-24 23:46:01,639::train::INFO] [train] Iter 589064 | loss 1.3588 | loss(rot) 0.5524 | loss(pos) 0.2934 | loss(seq) 0.5130 | grad 3.6850 | lr 0.0000 | time_forward 1.5500 | time_backward 2.2820 |
[2023-10-24 23:46:12,282::train::INFO] [train] Iter 589065 | loss 1.2957 | loss(rot) 0.7587 | loss(pos) 0.1479 | loss(seq) 0.3890 | grad 3.5016 | lr 0.0000 | time_forward 4.3670 | time_backward 6.2600 |
[2023-10-24 23:46:24,042::train::INFO] [train] Iter 589066 | loss 0.8180 | loss(rot) 0.2248 | loss(pos) 0.0606 | loss(seq) 0.5326 | grad 3.3506 | lr 0.0000 | time_forward 4.9570 | time_backward 6.8010 |
[2023-10-24 23:46:27,324::train::INFO] [train] Iter 589067 | loss 0.7182 | loss(rot) 0.0211 | loss(pos) 0.6955 | loss(seq) 0.0015 | grad 7.8684 | lr 0.0000 | time_forward 1.5120 | time_backward 1.7670 |
[2023-10-24 23:46:36,460::train::INFO] [train] Iter 589068 | loss 0.3359 | loss(rot) 0.0316 | loss(pos) 0.0307 | loss(seq) 0.2737 | grad 2.1816 | lr 0.0000 | time_forward 3.8660 | time_backward 5.2550 |
[2023-10-24 23:46:39,191::train::INFO] [train] Iter 589069 | loss 0.7347 | loss(rot) 0.1398 | loss(pos) 0.1632 | loss(seq) 0.4318 | grad 3.2730 | lr 0.0000 | time_forward 1.3150 | time_backward 1.4130 |
[2023-10-24 23:46:49,357::train::INFO] [train] Iter 589070 | loss 1.2170 | loss(rot) 0.3451 | loss(pos) 0.6905 | loss(seq) 0.1814 | grad 4.2840 | lr 0.0000 | time_forward 4.2670 | time_backward 5.8950 |
[2023-10-24 23:46:59,665::train::INFO] [train] Iter 589071 | loss 1.4983 | loss(rot) 0.0098 | loss(pos) 1.3187 | loss(seq) 0.1698 | grad 10.8204 | lr 0.0000 | time_forward 4.2550 | time_backward 6.0500 |
[2023-10-24 23:47:02,416::train::INFO] [train] Iter 589072 | loss 0.2638 | loss(rot) 0.0592 | loss(pos) 0.1584 | loss(seq) 0.0462 | grad 3.3530 | lr 0.0000 | time_forward 1.2900 | time_backward 1.4570 |
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