| license: cc-by-4.0 | |
| language: | |
| - en | |
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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. | |
| Training The fine-tuned version of the original bert-base-cased model (bert-base-cased), trained on HunEmPoli corpus, translated with Google Translate API. | |
| The model can be used as any other (cased) BERT model. It has been tested recognizing emotions at the sentence level in (parliamentary) pre-agenda speeches, where: | |
| 'Label_0': Neutral | |
| 'Label_1': Fear | |
| 'Label_2': Sadness | |
| 'Label_3': Anger | |
| 'Label_4': Disgust | |
| 'Label_5': Success | |
| 'Label_6': Joy | |
| 'Label_7': Trust | |
| Eval results | |
| precision recall f1-score support | |
| 0 1.00 0.50 0.67 46 | |
| 1 0.00 0.00 0.00 4 | |
| 2 0.70 0.85 0.76 188 | |
| 3 0.50 0.09 0.15 11 | |
| 4 0.85 0.75 0.80 375 | |
| 5 0.78 0.93 0.84 335 | |
| 6 0.67 0.28 0.39 36 | |
| 7 0.00 0.00 0.00 4 | |
| accuracy 0.79 999 | |
| macro avg 0.56 0.42 0.45 999 | |
| weighted avg 0.79 0.79 0.77 999 | |