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Performance

               precision recall    f1-score   support

           0   0.992584  0.994595  0.993588   9627605
           .   0.960450  0.962452  0.961450    433554
           ,   0.816974  0.804882  0.810883    379759
           ?   0.871368  0.826812  0.848506     13494
           -   0.619905  0.367690  0.461591     27341
           :   0.718636  0.602076  0.655212     18305

    accuracy                       0.983874  10500058
   macro avg   0.829986  0.759751  0.788538  10500058
weighted avg   0.983302  0.983874  0.983492  10500058

Usage:

pip install deepmultilingualpunctuation
from deepmultilingualpunctuation import PunctuationModel

model = PunctuationModel(model="oliverguhr/fullstop-dutch-punctuation-prediction")
text = "hervatting van de zitting ik verklaar de zitting van het europees parlement die op vrijdag 17 december werd onderbroken te zijn hervat"
result = model.restore_punctuation(text)
print(result)
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Dataset used to train oliverguhr/fullstop-dutch-punctuation-prediction