deepID deepid_class-优快云博客

本文详细记录了AI模型在不同阶段的训练过程及其表现，包括误差、训练得分和验证得分的变化情况。从epoch 0到epoch 19，模型在不断优化中，尤其是在epoch后期，训练得分和验证得分均呈现上升趋势。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

Training the model ...
   epoch 0, minibatch_index 199/200, error 0.980000
epoch 0, train_score 0.981920, valid_score 0.985120
   epoch 1, minibatch_index 199/200, error 0.970000
epoch 1, train_score 0.966220, valid_score 0.978880
   epoch 2, minibatch_index 199/200, error 0.936000
epoch 2, train_score 0.939180, valid_score 0.962000
   epoch 3, minibatch_index 199/200, error 0.902000
epoch 3, train_score 0.909490, valid_score 0.951280
   epoch 4, minibatch_index 199/200, error 0.860000
epoch 4, train_score 0.880050, valid_score 0.936960
   epoch 5, minibatch_index 199/200, error 0.816000
epoch 5, train_score 0.850390, valid_score 0.923360
   epoch 6, minibatch_index 199/200, error 0.842000
epoch 6, train_score 0.821610, valid_score 0.921840
   epoch 7, minibatch_index 199/200, error 0.818000
epoch 7, train_score 0.794550, valid_score 0.909680
   epoch 8, minibatch_index 199/200, error 0.760000
epoch 8, train_score 0.767890, valid_score 0.905840
   epoch 9, minibatch_index 199/200, error 0.754000
epoch 9, train_score 0.746010, valid_score 0.886640
   epoch 10, minibatch_index 199/200, error 0.712000
epoch 10, train_score 0.725360, valid_score 0.873920
   epoch 11, minibatch_index 199/200, error 0.708000
epoch 11, train_score 0.706780, valid_score 0.872000
   epoch 12, minibatch_index 199/200, error 0.684000
epoch 12, train_score 0.685420, valid_score 0.868400
   epoch 13, minibatch_index 199/200, error 0.706000
epoch 13, train_score 0.670460, valid_score 0.871440
   epoch 14, minibatch_index 199/200, error 0.658000
epoch 14, train_score 0.657160, valid_score 0.847920
   epoch 15, minibatch_index 199/200, error 0.642000
epoch 15, train_score 0.639900, valid_score 0.844800
   epoch 16, minibatch_index 199/200, error 0.640000
epoch 16, train_score 0.626590, valid_score 0.844640
   epoch 17, minibatch_index 199/200, error 0.596000
epoch 17, train_score 0.612180, valid_score 0.830720
   epoch 18, minibatch_index 199/200, error 0.638000
epoch 18, train_score 0.601290, valid_score 0.841360
   epoch 19, minibatch_index 199/200, error 0.592000
epoch 19, train_score 0.587440, valid_score 0.823840

0 0.98192 0.98512
1 0.96622 0.97888
2 0.93918 0.962
3 0.90949 0.95128
4 0.88005 0.93696
5 0.85039 0.92336
6 0.82161 0.92184
7 0.79455 0.90968
8 0.76789 0.90584
9 0.74601 0.88664
10 0.72536 0.87392
11 0.70678 0.872
12 0.68542 0.8684
13 0.67046 0.87144
14 0.65716 0.84792
15 0.6399 0.8448
16 0.62659 0.84464
17 0.61218 0.83072
18 0.60129 0.84136
19 0.58744 0.82384