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README.md
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This Electra model was trained on more than 6 billion tokens of Bosnian, Croatian, Montenegrin and Serbian text.
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Comparing this model to [multilingual BERT](https://huggingface.co/bert-base-multilingual-cased) and [CroSloEngual BERT](https://huggingface.co/EMBEDDIA/crosloengual-bert) on the tasks of part-of-speech tagging, named entity recognition, geolocation prediction and
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## Part-of-speech tagging
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## Geolocation prediction
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Evaluation metrics are median and mean of distance between gold and predicted geolocations (lower is better). No statistical significance is computed due to large test set (39,723 instances). Centroid baseline predicts each text to be created in the centroid of the training dataset.
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System | Median | Mean
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cseBERT | 40.76 | 81.88
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BERTić | **37.96** | **79.30**
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## Choice Of Plausible Alternatives
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Evaluation metric is accuracy. Best results are presented in bold. Statistical significance is calculated between two best-performing systems via a two-tailed t-test (* p<=0.05, ** p<=0.01, *** p<=0.001, ***** p<=0.0001).
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System | Accuracy
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This Electra model was trained on more than 6 billion tokens of Bosnian, Croatian, Montenegrin and Serbian text.
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Comparing this model to [multilingual BERT](https://huggingface.co/bert-base-multilingual-cased) and [CroSloEngual BERT](https://huggingface.co/EMBEDDIA/crosloengual-bert) on the tasks of (1) part-of-speech tagging, (2) named entity recognition, (3) geolocation prediction, and (4) commonsense causal reasoning, shows the BERTić model to be superior to the other two.
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## Part-of-speech tagging
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## Geolocation prediction
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The dataset comes from the VarDial 2020 evaluation campaign's shared task on [Social Media variety Geolocation prediction](https://sites.google.com/view/vardial2020/evaluation-campaign). The task is to predict the latitude and longitude of a tweet given its text.
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Evaluation metrics are median and mean of distance between gold and predicted geolocations (lower is better). No statistical significance is computed due to large test set (39,723 instances). Centroid baseline predicts each text to be created in the centroid of the training dataset.
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System | Median | Mean
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cseBERT | 40.76 | 81.88
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BERTić | **37.96** | **79.30**
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## Choice Of Plausible Alternatives
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The dataset is a translation of the [COPA dataset](https://people.ict.usc.edu/~gordon/copa.html) into Croatian (to-be-released).
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Evaluation metric is accuracy. Reported are means of five runs. Best results are presented in bold. Statistical significance is calculated between two best-performing systems via a two-tailed t-test (* p<=0.05, ** p<=0.01, *** p<=0.001, ***** p<=0.0001).
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System | Accuracy
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