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[2023-10-22 20:00:50,940::train::INFO] [train] Iter 561390 | loss 2.0245 | loss(rot) 1.7318 | loss(pos) 0.0420 | loss(seq) 0.2507 | grad 6.9871 | lr 0.0000 | time_forward 2.8680 | time_backward 3.8280 |
[2023-10-22 20:01:00,177::train::INFO] [train] Iter 561391 | loss 0.8468 | loss(rot) 0.2000 | loss(pos) 0.1898 | loss(seq) 0.4570 | grad 3.1422 | lr 0.0000 | time_forward 3.7060 | time_backward 5.5280 |
[2023-10-22 20:01:07,722::train::INFO] [train] Iter 561392 | loss 0.7310 | loss(rot) 0.2906 | loss(pos) 0.0630 | loss(seq) 0.3774 | grad 3.5916 | lr 0.0000 | time_forward 3.2500 | time_backward 4.2920 |
[2023-10-22 20:01:15,520::train::INFO] [train] Iter 561393 | loss 0.4474 | loss(rot) 0.2280 | loss(pos) 0.0860 | loss(seq) 0.1334 | grad 4.1167 | lr 0.0000 | time_forward 3.2900 | time_backward 4.5040 |
[2023-10-22 20:01:23,234::train::INFO] [train] Iter 561394 | loss 0.3309 | loss(rot) 0.0746 | loss(pos) 0.2233 | loss(seq) 0.0330 | grad 3.6973 | lr 0.0000 | time_forward 3.2380 | time_backward 4.4740 |
[2023-10-22 20:01:30,838::train::INFO] [train] Iter 561395 | loss 0.9058 | loss(rot) 0.7621 | loss(pos) 0.0452 | loss(seq) 0.0985 | grad 3.9529 | lr 0.0000 | time_forward 3.1910 | time_backward 4.4090 |
[2023-10-22 20:01:36,700::train::INFO] [train] Iter 561396 | loss 0.7734 | loss(rot) 0.4551 | loss(pos) 0.0583 | loss(seq) 0.2601 | grad 20.9544 | lr 0.0000 | time_forward 2.5340 | time_backward 3.3250 |
[2023-10-22 20:01:39,891::train::INFO] [train] Iter 561397 | loss 1.5872 | loss(rot) 0.0221 | loss(pos) 1.5648 | loss(seq) 0.0003 | grad 15.6304 | lr 0.0000 | time_forward 1.4730 | time_backward 1.7150 |
[2023-10-22 20:01:47,266::train::INFO] [train] Iter 561398 | loss 0.2458 | loss(rot) 0.1973 | loss(pos) 0.0290 | loss(seq) 0.0195 | grad 2.1947 | lr 0.0000 | time_forward 3.1170 | time_backward 4.2400 |
[2023-10-22 20:01:56,323::train::INFO] [train] Iter 561399 | loss 1.2325 | loss(rot) 0.5428 | loss(pos) 0.2230 | loss(seq) 0.4667 | grad 2.7151 | lr 0.0000 | time_forward 3.8300 | time_backward 5.2230 |
[2023-10-22 20:02:05,183::train::INFO] [train] Iter 561400 | loss 0.1301 | loss(rot) 0.0786 | loss(pos) 0.0129 | loss(seq) 0.0386 | grad 2.1136 | lr 0.0000 | time_forward 3.6500 | time_backward 5.2070 |
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