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[2023-09-02 20:56:09,966::train::INFO] [train] Iter 14172 | loss 2.6529 | loss(rot) 1.9515 | loss(pos) 0.2465 | loss(seq) 0.4548 | grad 4.5772 | lr 0.0010 | time_forward 4.1640 | time_backward 5.6140 |
[2023-09-02 20:56:18,529::train::INFO] [train] Iter 14173 | loss 2.1766 | loss(rot) 1.8041 | loss(pos) 0.1249 | loss(seq) 0.2475 | grad 9.8002 | lr 0.0010 | time_forward 3.4940 | time_backward 5.0660 |
[2023-09-02 20:56:28,437::train::INFO] [train] Iter 14174 | loss 1.5174 | loss(rot) 1.1811 | loss(pos) 0.1092 | loss(seq) 0.2271 | grad 4.0956 | lr 0.0010 | time_forward 3.9810 | time_backward 5.9230 |
[2023-09-02 20:56:39,205::train::INFO] [train] Iter 14175 | loss 1.3733 | loss(rot) 0.9477 | loss(pos) 0.1325 | loss(seq) 0.2931 | grad 4.3019 | lr 0.0010 | time_forward 4.4420 | time_backward 6.3220 |
[2023-09-02 20:56:48,214::train::INFO] [train] Iter 14176 | loss 1.6968 | loss(rot) 1.3026 | loss(pos) 0.1423 | loss(seq) 0.2518 | grad 6.4123 | lr 0.0010 | time_forward 3.7810 | time_backward 5.2260 |
[2023-09-02 20:56:58,503::train::INFO] [train] Iter 14177 | loss 3.6797 | loss(rot) 0.2246 | loss(pos) 3.4545 | loss(seq) 0.0006 | grad 11.7373 | lr 0.0010 | time_forward 4.1470 | time_backward 6.1380 |
[2023-09-02 20:57:08,907::train::INFO] [train] Iter 14178 | loss 1.6104 | loss(rot) 0.7458 | loss(pos) 0.3876 | loss(seq) 0.4769 | grad 4.2293 | lr 0.0010 | time_forward 4.3120 | time_backward 6.0870 |
[2023-09-02 20:57:11,755::train::INFO] [train] Iter 14179 | loss 1.2662 | loss(rot) 1.0069 | loss(pos) 0.1167 | loss(seq) 0.1426 | grad 8.8470 | lr 0.0010 | time_forward 1.3630 | time_backward 1.4810 |
[2023-09-02 20:57:22,293::train::INFO] [train] Iter 14180 | loss 1.8322 | loss(rot) 1.1401 | loss(pos) 0.2711 | loss(seq) 0.4211 | grad 7.7804 | lr 0.0010 | time_forward 4.3460 | time_backward 6.1890 |
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