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[2023-10-25 18:32:58,524::train::INFO] [val] Iter 599000 | loss 1.2267 | loss(rot) 0.6577 | loss(pos) 0.3539 | loss(seq) 0.2151
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[2023-10-25 18:33:01,686::train::INFO] [train] Iter 599001 | loss 0.2617 | loss(rot) 0.1094 | loss(pos) 0.0577 | loss(seq) 0.0947 | grad 2.8419 | lr 0.0000 | time_forward 1.2870 | time_backward 1.4590
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[2023-10-25 18:36:31,438::train::INFO] [train] Iter 599034 | loss 0.6885 | loss(rot) 0.2445 | loss(pos) 0.1737 | loss(seq) 0.2703 | grad 3.0112 | lr 0.0000 | time_forward 3.1770 | time_backward 4.1400
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[2023-10-25 18:38:04,900::train::INFO] [train] Iter 599050 | loss 2.1880 | loss(rot) 1.7568 | loss(pos) 0.0569 | loss(seq) 0.3744 | grad 3.6335 | lr 0.0000 | time_forward 1.4520 | time_backward 1.7100
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[2023-10-25 18:38:12,543::train::INFO] [train] Iter 599051 | loss 2.0371 | loss(rot) 1.3639 | loss(pos) 0.2134 | loss(seq) 0.4598 | grad 4.4214 | lr 0.0000 | time_forward 3.2090 | time_backward 4.4190
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[2023-10-25 18:38:19,577::train::INFO] [train] Iter 599052 | loss 0.2547 | loss(rot) 0.2268 | loss(pos) 0.0279 | loss(seq) 0.0000 | grad 2.6054 | lr 0.0000 | time_forward 3.0200 | time_backward 4.0120
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[2023-10-25 18:38:28,030::train::INFO] [train] Iter 599053 | loss 1.3348 | loss(rot) 0.6402 | loss(pos) 0.0824 | loss(seq) 0.6121 | grad 5.7468 | lr 0.0000 | time_forward 3.5090 | time_backward 4.9400
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[2023-10-25 18:38:36,320::train::INFO] [train] Iter 599054 | loss 1.1272 | loss(rot) 0.5578 | loss(pos) 0.2443 | loss(seq) 0.3251 | grad 3.2806 | lr 0.0000 | time_forward 3.6390 | time_backward 4.6490
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[2023-10-25 18:38:39,008::train::INFO] [train] Iter 599055 | loss 0.6671 | loss(rot) 0.1240 | loss(pos) 0.4235 | loss(seq) 0.1196 | grad 2.5788 | lr 0.0000 | time_forward 1.2570 | time_backward 1.4280
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[2023-10-25 18:38:41,725::train::INFO] [train] Iter 599056 | loss 0.4396 | loss(rot) 0.0204 | loss(pos) 0.4171 | loss(seq) 0.0021 | grad 7.2440 | lr 0.0000 | time_forward 1.3110 | time_backward 1.4030
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[2023-10-25 18:38:50,053::train::INFO] [train] Iter 599057 | loss 1.3673 | loss(rot) 0.6253 | loss(pos) 0.2468 | loss(seq) 0.4952 | grad 4.1615 | lr 0.0000 | time_forward 3.6000 | time_backward 4.7070
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[2023-10-25 18:38:58,578::train::INFO] [train] Iter 599058 | loss 0.3155 | loss(rot) 0.1655 | loss(pos) 0.0246 | loss(seq) 0.1254 | grad 2.5851 | lr 0.0000 | time_forward 3.5110 | time_backward 5.0120
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[2023-10-25 18:39:00,832::train::INFO] [train] Iter 599059 | loss 2.1928 | loss(rot) 0.0033 | loss(pos) 2.1895 | loss(seq) 0.0000 | grad 22.9937 | lr 0.0000 | time_forward 1.0380 | time_backward 1.2120
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[2023-10-25 18:39:08,764::train::INFO] [train] Iter 599060 | loss 0.8110 | loss(rot) 0.7503 | loss(pos) 0.0607 | loss(seq) 0.0000 | grad 5.9751 | lr 0.0000 | time_forward 3.4390 | time_backward 4.4900
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[2023-10-25 18:39:10,988::train::INFO] [train] Iter 599061 | loss 3.2166 | loss(rot) 0.0026 | loss(pos) 3.2140 | loss(seq) 0.0000 | grad 18.2247 | lr 0.0000 | time_forward 1.0230 | time_backward 1.1970
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[2023-10-25 18:39:18,942::train::INFO] [train] Iter 599062 | loss 1.5895 | loss(rot) 0.8814 | loss(pos) 0.1670 | loss(seq) 0.5411 | grad 2.7558 | lr 0.0000 | time_forward 3.4370 | time_backward 4.5130
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