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[2023-10-23 08:01:19,747::train::INFO] [train] Iter 568385 | loss 0.2633 | loss(rot) 0.1900 | loss(pos) 0.0283 | loss(seq) 0.0450 | grad 2.7559 | lr 0.0000 | time_forward 3.4400 | time_backward 4.3330 |
[2023-10-23 08:01:25,556::train::INFO] [train] Iter 568386 | loss 0.7804 | loss(rot) 0.2502 | loss(pos) 0.0895 | loss(seq) 0.4407 | grad 3.0546 | lr 0.0000 | time_forward 2.6290 | time_backward 3.1780 |
[2023-10-23 08:01:32,831::train::INFO] [train] Iter 568387 | loss 0.6025 | loss(rot) 0.2016 | loss(pos) 0.1624 | loss(seq) 0.2385 | grad 2.2657 | lr 0.0000 | time_forward 3.2250 | time_backward 4.0460 |
[2023-10-23 08:01:41,814::train::INFO] [train] Iter 568388 | loss 1.4449 | loss(rot) 1.4141 | loss(pos) 0.0238 | loss(seq) 0.0070 | grad 8.1398 | lr 0.0000 | time_forward 3.9450 | time_backward 5.0350 |
[2023-10-23 08:01:49,178::train::INFO] [train] Iter 568389 | loss 2.1086 | loss(rot) 1.3060 | loss(pos) 0.2233 | loss(seq) 0.5793 | grad 3.2223 | lr 0.0000 | time_forward 3.3100 | time_backward 4.0510 |
[2023-10-23 08:01:58,381::train::INFO] [train] Iter 568390 | loss 0.3023 | loss(rot) 0.2679 | loss(pos) 0.0279 | loss(seq) 0.0065 | grad 2.5850 | lr 0.0000 | time_forward 3.8050 | time_backward 5.3950 |
[2023-10-23 08:02:06,363::train::INFO] [train] Iter 568391 | loss 0.9754 | loss(rot) 0.0212 | loss(pos) 0.6030 | loss(seq) 0.3512 | grad 10.1339 | lr 0.0000 | time_forward 3.6940 | time_backward 4.2840 |
[2023-10-23 08:02:09,107::train::INFO] [train] Iter 568392 | loss 0.4282 | loss(rot) 0.0649 | loss(pos) 0.3492 | loss(seq) 0.0141 | grad 4.8610 | lr 0.0000 | time_forward 1.3430 | time_backward 1.3980 |
[2023-10-23 08:02:17,815::train::INFO] [train] Iter 568393 | loss 0.3170 | loss(rot) 0.1431 | loss(pos) 0.0266 | loss(seq) 0.1473 | grad 2.3920 | lr 0.0000 | time_forward 3.7010 | time_backward 5.0050 |
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