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Model description Cased fine-tuned BERT model for English, trained on (manually annotated) Hungarian parliamentary speeches scraped from parlament.hu, and translated with Google Translate API.

Intended uses & limitations The model can be used as any other (cased) BERT model. It has been tested recognizing positive, negative, and neutral sentences in (parliamentary) pre-agenda speeches, where:

'Label_0': Negative 'Label_1': Neutral 'Label_2': Positive

Training The fine-tuned version of the original bert-base-cased model (bert-base-cased), trained on HunEmPoli corpus, translated with Google Translate API.

Intended uses & limitations: The model can be used as any other (cased) BERT model.

Eval results

              precision    recall  f1-score   support

         0       0.87      0.87      0.87      1118
         1       1.00      0.26      0.41        35
         2       0.78      0.82      0.80       748

  accuracy                           0.83      1901
  macro avg      0.88      0.65      0.69      1901
  weighted avg   0.84      0.83      0.83      1901
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