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[2023-10-22 13:50:21,053::train::INFO] [train] Iter 558294 | loss 0.4682 | loss(rot) 0.1481 | loss(pos) 0.0237 | loss(seq) 0.2963 | grad 2.7108 | lr 0.0000 | time_forward 6.5970 | time_backward 5.0220 |
[2023-10-22 13:50:23,144::train::INFO] [train] Iter 558295 | loss 2.7644 | loss(rot) 2.0310 | loss(pos) 0.2909 | loss(seq) 0.4424 | grad 8.2739 | lr 0.0000 | time_forward 0.9570 | time_backward 1.1300 |
[2023-10-22 13:50:26,656::train::INFO] [train] Iter 558296 | loss 0.2210 | loss(rot) 0.0367 | loss(pos) 0.0559 | loss(seq) 0.1284 | grad 2.3689 | lr 0.0000 | time_forward 1.7150 | time_backward 1.7930 |
[2023-10-22 13:50:36,121::train::INFO] [train] Iter 558297 | loss 1.1221 | loss(rot) 0.8643 | loss(pos) 0.1456 | loss(seq) 0.1122 | grad 4.1021 | lr 0.0000 | time_forward 4.0220 | time_backward 5.4230 |
[2023-10-22 13:50:39,665::train::INFO] [train] Iter 558298 | loss 0.9588 | loss(rot) 0.6892 | loss(pos) 0.0431 | loss(seq) 0.2265 | grad 2.6765 | lr 0.0000 | time_forward 1.8370 | time_backward 1.7020 |
[2023-10-22 13:50:49,033::train::INFO] [train] Iter 558299 | loss 0.5988 | loss(rot) 0.5332 | loss(pos) 0.0164 | loss(seq) 0.0492 | grad 8.7971 | lr 0.0000 | time_forward 4.0870 | time_backward 5.2770 |
[2023-10-22 13:50:59,234::train::INFO] [train] Iter 558300 | loss 1.5143 | loss(rot) 1.4187 | loss(pos) 0.0327 | loss(seq) 0.0629 | grad 4.4877 | lr 0.0000 | time_forward 4.2070 | time_backward 5.9920 |
[2023-10-22 13:51:10,059::train::INFO] [train] Iter 558301 | loss 1.7521 | loss(rot) 0.0026 | loss(pos) 1.7493 | loss(seq) 0.0002 | grad 11.3313 | lr 0.0000 | time_forward 4.3320 | time_backward 6.4890 |
[2023-10-22 13:51:20,493::train::INFO] [train] Iter 558302 | loss 0.6998 | loss(rot) 0.4222 | loss(pos) 0.1493 | loss(seq) 0.1283 | grad 2.3681 | lr 0.0000 | time_forward 4.3430 | time_backward 6.0870 |
[2023-10-22 13:51:23,185::train::INFO] [train] Iter 558303 | loss 1.1954 | loss(rot) 1.1853 | loss(pos) 0.0100 | loss(seq) 0.0002 | grad 4.0540 | lr 0.0000 | time_forward 1.2590 | time_backward 1.4300 |
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