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[2023-10-25 00:25:10,295::train::INFO] [train] Iter 589363 | loss 0.1679 | loss(rot) 0.0560 | loss(pos) 0.0617 | loss(seq) 0.0502 | grad 3.0659 | lr 0.0000 | time_forward 1.5250 | time_backward 1.9470 |
[2023-10-25 00:25:14,105::train::INFO] [train] Iter 589364 | loss 0.4826 | loss(rot) 0.2566 | loss(pos) 0.1056 | loss(seq) 0.1205 | grad 2.6718 | lr 0.0000 | time_forward 1.4960 | time_backward 2.2990 |
[2023-10-25 00:25:23,020::train::INFO] [train] Iter 589365 | loss 0.3488 | loss(rot) 0.0982 | loss(pos) 0.0246 | loss(seq) 0.2259 | grad 2.4566 | lr 0.0000 | time_forward 3.6670 | time_backward 5.2450 |
[2023-10-25 00:25:30,998::train::INFO] [train] Iter 589366 | loss 0.4400 | loss(rot) 0.2125 | loss(pos) 0.1488 | loss(seq) 0.0787 | grad 4.3427 | lr 0.0000 | time_forward 3.4480 | time_backward 4.5060 |
[2023-10-25 00:25:41,638::train::INFO] [train] Iter 589367 | loss 0.2951 | loss(rot) 0.1039 | loss(pos) 0.1777 | loss(seq) 0.0135 | grad 5.4651 | lr 0.0000 | time_forward 4.3220 | time_backward 6.3140 |
[2023-10-25 00:25:49,574::train::INFO] [train] Iter 589368 | loss 1.3348 | loss(rot) 1.0112 | loss(pos) 0.1195 | loss(seq) 0.2041 | grad 4.1668 | lr 0.0000 | time_forward 3.3970 | time_backward 4.5360 |
[2023-10-25 00:25:59,829::train::INFO] [train] Iter 589369 | loss 0.8644 | loss(rot) 0.4658 | loss(pos) 0.2295 | loss(seq) 0.1691 | grad 3.6142 | lr 0.0000 | time_forward 4.0450 | time_backward 6.2080 |
[2023-10-25 00:26:09,221::train::INFO] [train] Iter 589370 | loss 0.3693 | loss(rot) 0.1062 | loss(pos) 0.0270 | loss(seq) 0.2362 | grad 3.3296 | lr 0.0000 | time_forward 4.1840 | time_backward 5.2050 |
[2023-10-25 00:26:18,667::train::INFO] [train] Iter 589371 | loss 1.0918 | loss(rot) 0.5766 | loss(pos) 0.3772 | loss(seq) 0.1380 | grad 4.1378 | lr 0.0000 | time_forward 4.2300 | time_backward 5.2130 |
[2023-10-25 00:26:21,375::train::INFO] [train] Iter 589372 | loss 0.4204 | loss(rot) 0.3813 | loss(pos) 0.0388 | loss(seq) 0.0003 | grad 2.7858 | lr 0.0000 | time_forward 1.2520 | time_backward 1.4520 |
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