title: F1 score values different for F1 score metric and classification report sklearn
body: <p>I am trying to analyze my results so i am using the F1 score metric and classification report on sklearn. The results displayed are totally different irrelevant of the type of averaging.
  It does not match at all.
  example on my validation data</p>
  
  <p>F1 score 0.7666666666666667</p>
  
  <p>But the classification report results are:</p>
  
  <pre><code>  report       precision recall  f1-score   support
         0       0.16      0.57      0.25         7
         1       0.40      0.09      0.14        23
  accuracy                           0.20        30
  
  
  
  macro avg      precision: 0.28, recall:0.33,  f1score:0.20      support:30
  
  weighted avg       precision:0.34      recall:0.20      f1score:0.17        support:30
  </code></pre>
  
  <p>Any help will be appreciated.
  thanks!</p>
  
  <p>My code is:
  ` print('F1 score {}'.format(sklearn.metrics.f1_score(test_label, np.round(y_pred), average='micro'))´</p>
  
  <p>And for classification report it is:</p>
  
  <p>` print('F1 score {}'.format(sklearn.metrics.classification_report(test_label, np.round(y_pred), target_names=labels))´</p>
  
  <p>labels is just a list with  my classlabels in it.</p>