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': Neutral 'Label_1': Positive 'Label_2': Negative
Training The fine-tuned version of the original bert-base-cased model (bert-base-cased), trained on HunEmPoli corpus, translated with Google Translate API.
Eval results
class precision recall f1-score support
0 0.93 0.40 0.56 35
1 0.80 0.84 0.82 748
2 0.88 0.87 0.88 1118
accuracy 0.85 1901
macro avg 0.87 0.70 0.75 1901
weighted avg 0.85 0.85 0.85 1901
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