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[2023-10-23 23:13:21,638::train::INFO] [train] Iter 576476 | loss 0.5404 | loss(rot) 0.1673 | loss(pos) 0.1419 | loss(seq) 0.2311 | grad 3.7100 | lr 0.0000 | time_forward 2.8990 | time_backward 3.9240 |
[2023-10-23 23:13:23,154::train::INFO] [train] Iter 576477 | loss 0.7485 | loss(rot) 0.0874 | loss(pos) 0.5035 | loss(seq) 0.1576 | grad 4.9809 | lr 0.0000 | time_forward 0.7000 | time_backward 0.8130 |
[2023-10-23 23:13:31,382::train::INFO] [train] Iter 576478 | loss 0.7100 | loss(rot) 0.4293 | loss(pos) 0.0442 | loss(seq) 0.2364 | grad 5.0477 | lr 0.0000 | time_forward 3.4180 | time_backward 4.8070 |
[2023-10-23 23:13:38,135::train::INFO] [train] Iter 576479 | loss 2.3777 | loss(rot) 1.9571 | loss(pos) 0.0803 | loss(seq) 0.3404 | grad 5.3972 | lr 0.0000 | time_forward 2.9090 | time_backward 3.8410 |
[2023-10-23 23:13:44,800::train::INFO] [train] Iter 576480 | loss 0.2591 | loss(rot) 0.2150 | loss(pos) 0.0435 | loss(seq) 0.0006 | grad 3.4234 | lr 0.0000 | time_forward 2.8580 | time_backward 3.8040 |
[2023-10-23 23:13:53,598::train::INFO] [train] Iter 576481 | loss 0.6572 | loss(rot) 0.1415 | loss(pos) 0.3363 | loss(seq) 0.1794 | grad 3.7237 | lr 0.0000 | time_forward 3.5940 | time_backward 5.2000 |
[2023-10-23 23:14:04,742::train::INFO] [train] Iter 576482 | loss 0.5279 | loss(rot) 0.4673 | loss(pos) 0.0104 | loss(seq) 0.0502 | grad 4.7126 | lr 0.0000 | time_forward 3.0040 | time_backward 8.1360 |
[2023-10-23 23:14:12,267::train::INFO] [train] Iter 576483 | loss 0.7854 | loss(rot) 0.2185 | loss(pos) 0.0369 | loss(seq) 0.5300 | grad 3.1184 | lr 0.0000 | time_forward 4.3170 | time_backward 3.2050 |
[2023-10-23 23:14:21,535::train::INFO] [train] Iter 576484 | loss 0.3871 | loss(rot) 0.3571 | loss(pos) 0.0228 | loss(seq) 0.0072 | grad 52.8358 | lr 0.0000 | time_forward 4.0670 | time_backward 5.1970 |
[2023-10-23 23:14:29,420::train::INFO] [train] Iter 576485 | loss 0.3309 | loss(rot) 0.0855 | loss(pos) 0.2380 | loss(seq) 0.0074 | grad 9.9641 | lr 0.0000 | time_forward 3.3220 | time_backward 4.5600 |
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