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[2023-09-02 08:56:11,855::train::INFO] [train] Iter 08177 | loss 2.1750 | loss(rot) 1.9671 | loss(pos) 0.1060 | loss(seq) 0.1019 | grad 5.1239 | lr 0.0010 | time_forward 3.0790 | time_backward 4.1210 |
[2023-09-02 08:56:14,528::train::INFO] [train] Iter 08178 | loss 0.6507 | loss(rot) 0.1763 | loss(pos) 0.4036 | loss(seq) 0.0708 | grad 3.0023 | lr 0.0010 | time_forward 1.2630 | time_backward 1.4070 |
[2023-09-02 08:56:17,212::train::INFO] [train] Iter 08179 | loss 1.6380 | loss(rot) 1.2687 | loss(pos) 0.0919 | loss(seq) 0.2774 | grad 4.4554 | lr 0.0010 | time_forward 1.2670 | time_backward 1.4150 |
[2023-09-02 08:56:25,916::train::INFO] [train] Iter 08180 | loss 1.6348 | loss(rot) 0.4927 | loss(pos) 0.5726 | loss(seq) 0.5695 | grad 5.2835 | lr 0.0010 | time_forward 3.7030 | time_backward 4.9980 |
[2023-09-02 08:56:32,714::train::INFO] [train] Iter 08181 | loss 1.3167 | loss(rot) 0.4291 | loss(pos) 0.6227 | loss(seq) 0.2649 | grad 4.5516 | lr 0.0010 | time_forward 2.8460 | time_backward 3.9480 |
[2023-09-02 08:56:35,413::train::INFO] [train] Iter 08182 | loss 1.7550 | loss(rot) 1.5644 | loss(pos) 0.1046 | loss(seq) 0.0860 | grad 4.5223 | lr 0.0010 | time_forward 1.2670 | time_backward 1.4290 |
[2023-09-02 08:56:38,145::train::INFO] [train] Iter 08183 | loss 1.8176 | loss(rot) 1.6572 | loss(pos) 0.1603 | loss(seq) 0.0001 | grad 6.1090 | lr 0.0010 | time_forward 1.3110 | time_backward 1.4180 |
[2023-09-02 08:56:46,742::train::INFO] [train] Iter 08184 | loss 2.2231 | loss(rot) 1.6009 | loss(pos) 0.2573 | loss(seq) 0.3649 | grad 3.7008 | lr 0.0010 | time_forward 3.6640 | time_backward 4.9300 |
[2023-09-02 08:56:56,959::train::INFO] [train] Iter 08185 | loss 1.9427 | loss(rot) 1.7125 | loss(pos) 0.1036 | loss(seq) 0.1266 | grad 3.9069 | lr 0.0010 | time_forward 4.1920 | time_backward 6.0200 |
[2023-09-02 08:57:07,011::train::INFO] [train] Iter 08186 | loss 2.7568 | loss(rot) 2.4741 | loss(pos) 0.2578 | loss(seq) 0.0249 | grad 5.7990 | lr 0.0010 | time_forward 4.0280 | time_backward 6.0210 |
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