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[2023-10-24 01:46:24,546::train::INFO] [train] Iter 577774 | loss 0.4119 | loss(rot) 0.2115 | loss(pos) 0.0571 | loss(seq) 0.1434 | grad 3.4403 | lr 0.0000 | time_forward 3.3620 | time_backward 4.6150 |
[2023-10-24 01:46:32,380::train::INFO] [train] Iter 577775 | loss 1.4216 | loss(rot) 1.1975 | loss(pos) 0.0427 | loss(seq) 0.1814 | grad 3.7365 | lr 0.0000 | time_forward 3.2930 | time_backward 4.5380 |
[2023-10-24 01:46:40,855::train::INFO] [train] Iter 577776 | loss 0.8234 | loss(rot) 0.6061 | loss(pos) 0.0289 | loss(seq) 0.1884 | grad 4.5813 | lr 0.0000 | time_forward 3.5910 | time_backward 4.8800 |
[2023-10-24 01:46:48,924::train::INFO] [train] Iter 577777 | loss 0.1529 | loss(rot) 0.1133 | loss(pos) 0.0266 | loss(seq) 0.0130 | grad 1.6820 | lr 0.0000 | time_forward 3.4390 | time_backward 4.6280 |
[2023-10-24 01:46:56,244::train::INFO] [train] Iter 577778 | loss 0.1476 | loss(rot) 0.0499 | loss(pos) 0.0443 | loss(seq) 0.0534 | grad 2.6966 | lr 0.0000 | time_forward 3.1550 | time_backward 4.1610 |
[2023-10-24 01:47:04,333::train::INFO] [train] Iter 577779 | loss 0.1797 | loss(rot) 0.1480 | loss(pos) 0.0299 | loss(seq) 0.0019 | grad 2.6301 | lr 0.0000 | time_forward 3.4520 | time_backward 4.6350 |
[2023-10-24 01:47:07,779::train::INFO] [train] Iter 577780 | loss 2.4244 | loss(rot) 1.7443 | loss(pos) 0.2184 | loss(seq) 0.4616 | grad 5.7329 | lr 0.0000 | time_forward 1.5580 | time_backward 1.8840 |
[2023-10-24 01:47:15,964::train::INFO] [train] Iter 577781 | loss 1.6263 | loss(rot) 0.0278 | loss(pos) 1.5963 | loss(seq) 0.0022 | grad 11.8953 | lr 0.0000 | time_forward 3.4900 | time_backward 4.6810 |
[2023-10-24 01:47:24,068::train::INFO] [train] Iter 577782 | loss 0.4255 | loss(rot) 0.1442 | loss(pos) 0.2178 | loss(seq) 0.0635 | grad 6.7317 | lr 0.0000 | time_forward 3.4570 | time_backward 4.6430 |
[2023-10-24 01:47:32,916::train::INFO] [train] Iter 577783 | loss 0.2236 | loss(rot) 0.0967 | loss(pos) 0.0100 | loss(seq) 0.1169 | grad 1.7038 | lr 0.0000 | time_forward 3.7490 | time_backward 5.0960 |
[2023-10-24 01:47:42,513::train::INFO] [train] Iter 577784 | loss 0.9541 | loss(rot) 0.9049 | loss(pos) 0.0492 | loss(seq) 0.0000 | grad 15.1223 | lr 0.0000 | time_forward 3.8910 | time_backward 5.7030 |
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