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[2023-09-01 23:01:53,635::train::INFO] [train] Iter 03282 | loss 2.2892 | loss(rot) 2.0194 | loss(pos) 0.2648 | loss(seq) 0.0050 | grad 5.5877 | lr 0.0010 | time_forward 1.3360 | time_backward 1.4480 |
[2023-09-01 23:01:56,367::train::INFO] [train] Iter 03283 | loss 2.0031 | loss(rot) 0.9990 | loss(pos) 0.5139 | loss(seq) 0.4902 | grad 7.0086 | lr 0.0010 | time_forward 1.3100 | time_backward 1.4190 |
[2023-09-01 23:01:58,666::train::INFO] [train] Iter 03284 | loss 2.8074 | loss(rot) 2.4978 | loss(pos) 0.2890 | loss(seq) 0.0206 | grad 4.2483 | lr 0.0010 | time_forward 1.1110 | time_backward 1.1850 |
[2023-09-01 23:02:07,198::train::INFO] [train] Iter 03285 | loss 3.0616 | loss(rot) 2.7534 | loss(pos) 0.3081 | loss(seq) 0.0000 | grad 3.3760 | lr 0.0010 | time_forward 3.5550 | time_backward 4.9730 |
[2023-09-01 23:02:09,496::train::INFO] [train] Iter 03286 | loss 2.5954 | loss(rot) 2.4168 | loss(pos) 0.1774 | loss(seq) 0.0012 | grad 3.0246 | lr 0.0010 | time_forward 1.0870 | time_backward 1.2050 |
[2023-09-01 23:02:19,722::train::INFO] [train] Iter 03287 | loss 2.0600 | loss(rot) 1.3388 | loss(pos) 0.3097 | loss(seq) 0.4115 | grad 3.9237 | lr 0.0010 | time_forward 4.0950 | time_backward 6.1270 |
[2023-09-01 23:02:29,683::train::INFO] [train] Iter 03288 | loss 3.6353 | loss(rot) 0.0185 | loss(pos) 3.6161 | loss(seq) 0.0006 | grad 7.6067 | lr 0.0010 | time_forward 4.0840 | time_backward 5.8730 |
[2023-09-01 23:02:39,041::train::INFO] [train] Iter 03289 | loss 2.0760 | loss(rot) 1.5749 | loss(pos) 0.1714 | loss(seq) 0.3297 | grad 4.6193 | lr 0.0010 | time_forward 4.0260 | time_backward 5.3290 |
[2023-09-01 23:02:49,540::train::INFO] [train] Iter 03290 | loss 2.9404 | loss(rot) 2.1997 | loss(pos) 0.3098 | loss(seq) 0.4310 | grad 4.0390 | lr 0.0010 | time_forward 4.3490 | time_backward 6.1460 |
[2023-09-01 23:02:57,955::train::INFO] [train] Iter 03291 | loss 3.6427 | loss(rot) 0.0670 | loss(pos) 3.5758 | loss(seq) 0.0000 | grad 8.7395 | lr 0.0010 | time_forward 3.6260 | time_backward 4.7740 |
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