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[2023-10-24 16:09:05,923::train::INFO] [train] Iter 585066 | loss 0.1174 | loss(rot) 0.0836 | loss(pos) 0.0338 | loss(seq) -0.0000 | grad 1.6918 | lr 0.0000 | time_forward 4.7460 | time_backward 3.7980 |
[2023-10-24 16:09:12,352::train::INFO] [train] Iter 585067 | loss 1.3720 | loss(rot) 0.4270 | loss(pos) 0.6525 | loss(seq) 0.2925 | grad 3.4235 | lr 0.0000 | time_forward 2.7920 | time_backward 3.6340 |
[2023-10-24 16:09:15,153::train::INFO] [train] Iter 585068 | loss 0.3028 | loss(rot) 0.0500 | loss(pos) 0.2377 | loss(seq) 0.0151 | grad 8.6600 | lr 0.0000 | time_forward 1.2480 | time_backward 1.5500 |
[2023-10-24 16:09:22,648::train::INFO] [train] Iter 585069 | loss 0.3457 | loss(rot) 0.0933 | loss(pos) 0.0557 | loss(seq) 0.1967 | grad 2.2371 | lr 0.0000 | time_forward 3.6570 | time_backward 3.8350 |
[2023-10-24 16:09:25,652::train::INFO] [train] Iter 585070 | loss 0.6329 | loss(rot) 0.5488 | loss(pos) 0.0178 | loss(seq) 0.0662 | grad 16.2108 | lr 0.0000 | time_forward 1.5680 | time_backward 1.4310 |
[2023-10-24 16:09:28,472::train::INFO] [train] Iter 585071 | loss 0.2573 | loss(rot) 0.1217 | loss(pos) 0.0397 | loss(seq) 0.0959 | grad 2.7242 | lr 0.0000 | time_forward 1.3530 | time_backward 1.4620 |
[2023-10-24 16:09:37,212::train::INFO] [train] Iter 585072 | loss 0.3357 | loss(rot) 0.1087 | loss(pos) 0.2001 | loss(seq) 0.0269 | grad 4.2286 | lr 0.0000 | time_forward 4.5640 | time_backward 4.1740 |
[2023-10-24 16:09:44,810::train::INFO] [train] Iter 585073 | loss 0.2003 | loss(rot) 0.1333 | loss(pos) 0.0146 | loss(seq) 0.0524 | grad 3.9324 | lr 0.0000 | time_forward 3.6750 | time_backward 3.9190 |
[2023-10-24 16:09:51,503::train::INFO] [train] Iter 585074 | loss 1.3163 | loss(rot) 1.1715 | loss(pos) 0.0235 | loss(seq) 0.1213 | grad 5.3671 | lr 0.0000 | time_forward 2.9150 | time_backward 3.7750 |
[2023-10-24 16:09:54,159::train::INFO] [train] Iter 585075 | loss 0.3553 | loss(rot) 0.2088 | loss(pos) 0.0237 | loss(seq) 0.1228 | grad 2.1278 | lr 0.0000 | time_forward 1.2570 | time_backward 1.3950 |
[2023-10-24 16:10:02,154::train::INFO] [train] Iter 585076 | loss 0.1795 | loss(rot) 0.1487 | loss(pos) 0.0277 | loss(seq) 0.0032 | grad 2.3143 | lr 0.0000 | time_forward 3.4370 | time_backward 4.5550 |
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