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[2023-10-22 23:19:09,910::train::INFO] [train] Iter 563189 | loss 0.4579 | loss(rot) 0.1908 | loss(pos) 0.0211 | loss(seq) 0.2460 | grad 2.2313 | lr 0.0000 | time_forward 1.3310 | time_backward 1.4680 |
[2023-10-22 23:19:12,775::train::INFO] [train] Iter 563190 | loss 0.1127 | loss(rot) 0.0332 | loss(pos) 0.0251 | loss(seq) 0.0544 | grad 1.5375 | lr 0.0000 | time_forward 1.3850 | time_backward 1.4770 |
[2023-10-22 23:19:15,639::train::INFO] [train] Iter 563191 | loss 0.2091 | loss(rot) 0.0368 | loss(pos) 0.1373 | loss(seq) 0.0350 | grad 4.9082 | lr 0.0000 | time_forward 1.3920 | time_backward 1.4680 |
[2023-10-22 23:19:25,129::train::INFO] [train] Iter 563192 | loss 0.6093 | loss(rot) 0.5862 | loss(pos) 0.0178 | loss(seq) 0.0053 | grad 7.4112 | lr 0.0000 | time_forward 4.3260 | time_backward 5.1350 |
[2023-10-22 23:19:41,838::train::INFO] [train] Iter 563193 | loss 0.7381 | loss(rot) 0.1274 | loss(pos) 0.1802 | loss(seq) 0.4305 | grad 5.2817 | lr 0.0000 | time_forward 11.4780 | time_backward 5.2270 |
[2023-10-22 23:19:56,883::train::INFO] [train] Iter 563194 | loss 0.5123 | loss(rot) 0.1027 | loss(pos) 0.3488 | loss(seq) 0.0608 | grad 2.5856 | lr 0.0000 | time_forward 10.0630 | time_backward 4.9800 |
[2023-10-22 23:20:06,311::train::INFO] [train] Iter 563195 | loss 1.3318 | loss(rot) 0.9091 | loss(pos) 0.0426 | loss(seq) 0.3801 | grad 5.0869 | lr 0.0000 | time_forward 3.9930 | time_backward 5.4310 |
[2023-10-22 23:20:16,632::train::INFO] [train] Iter 563196 | loss 0.5095 | loss(rot) 0.4745 | loss(pos) 0.0230 | loss(seq) 0.0120 | grad 10.9627 | lr 0.0000 | time_forward 4.6480 | time_backward 5.6700 |
[2023-10-22 23:20:19,600::train::INFO] [train] Iter 563197 | loss 0.5468 | loss(rot) 0.1810 | loss(pos) 0.0353 | loss(seq) 0.3305 | grad 2.5960 | lr 0.0000 | time_forward 1.4350 | time_backward 1.5290 |
[2023-10-22 23:20:37,576::train::INFO] [train] Iter 563198 | loss 0.2088 | loss(rot) 0.1303 | loss(pos) 0.0162 | loss(seq) 0.0624 | grad 5.6559 | lr 0.0000 | time_forward 11.7350 | time_backward 6.2380 |
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