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[2023-10-23 17:33:21,434::train::INFO] [train] Iter 573579 | loss 0.7267 | loss(rot) 0.3449 | loss(pos) 0.0701 | loss(seq) 0.3117 | grad 3.9303 | lr 0.0000 | time_forward 3.5520 | time_backward 5.2570 |
[2023-10-23 17:33:31,383::train::INFO] [train] Iter 573580 | loss 0.7049 | loss(rot) 0.4659 | loss(pos) 0.2116 | loss(seq) 0.0274 | grad 4.5121 | lr 0.0000 | time_forward 4.3430 | time_backward 5.6040 |
[2023-10-23 17:33:37,764::train::INFO] [train] Iter 573581 | loss 0.6860 | loss(rot) 0.3439 | loss(pos) 0.0375 | loss(seq) 0.3045 | grad 4.0279 | lr 0.0000 | time_forward 2.7610 | time_backward 3.6160 |
[2023-10-23 17:33:45,598::train::INFO] [train] Iter 573582 | loss 1.2662 | loss(rot) 0.4582 | loss(pos) 0.4517 | loss(seq) 0.3563 | grad 3.6643 | lr 0.0000 | time_forward 3.3130 | time_backward 4.5170 |
[2023-10-23 17:33:53,771::train::INFO] [train] Iter 573583 | loss 0.3568 | loss(rot) 0.1041 | loss(pos) 0.1208 | loss(seq) 0.1318 | grad 4.1069 | lr 0.0000 | time_forward 3.4150 | time_backward 4.7560 |
[2023-10-23 17:34:02,747::train::INFO] [train] Iter 573584 | loss 0.3353 | loss(rot) 0.3160 | loss(pos) 0.0177 | loss(seq) 0.0015 | grad 27.2387 | lr 0.0000 | time_forward 4.1620 | time_backward 4.8110 |
[2023-10-23 17:34:10,948::train::INFO] [train] Iter 573585 | loss 0.5775 | loss(rot) 0.4014 | loss(pos) 0.0144 | loss(seq) 0.1617 | grad 59.3591 | lr 0.0000 | time_forward 3.5170 | time_backward 4.6800 |
[2023-10-23 17:34:18,353::train::INFO] [train] Iter 573586 | loss 0.4683 | loss(rot) 0.0551 | loss(pos) 0.3790 | loss(seq) 0.0342 | grad 10.9482 | lr 0.0000 | time_forward 3.1710 | time_backward 4.2320 |
[2023-10-23 17:34:27,876::train::INFO] [train] Iter 573587 | loss 0.2625 | loss(rot) 0.1542 | loss(pos) 0.1081 | loss(seq) 0.0002 | grad 1.8047 | lr 0.0000 | time_forward 4.2550 | time_backward 5.2640 |
[2023-10-23 17:34:37,711::train::INFO] [train] Iter 573588 | loss 1.3180 | loss(rot) 1.2312 | loss(pos) 0.0273 | loss(seq) 0.0595 | grad 3.9293 | lr 0.0000 | time_forward 4.3350 | time_backward 5.4980 |
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