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---
language: "hr"
tags:
- text-classification
- sentiment-analysis
widget:
- text: "Potpredsjednik Vlade i ministar branitelja Tomo Medved komentirao je Vladine planove za zakonsku zabranu pozdrava 'za dom spremni'."
---
# bcms-bertic-parlasent-bcs-bi
Binary text classification model based on [`classla/bcms-bertic`](https://huggingface.co/classla/bcms-bertic) and fine-tuned on the BCS Political Sentiment dataset.
This classifier classifies text into only two categories: Negative vs. Other. For the ternary classifier (Negative, Neutral, Positive) check [this model](https://huggingface.co/classla/bcms-bertic-parlasent-bcs-ter).
## Fine-tuning hyperparameters
Fine-tuning was performed with `simpletransformers`. Beforehand a brief sweep for the optimal number of epochs was performed and the presumed best value was 9. Other arguments were kept default.
```python
model_args = {
"num_train_epochs": 9
}
```
## Performance in comparison with ternary classifier
| model | average macro F1 |
|-------------------------------------------|------------------|
| bcms-bertic-parlasent-bcs-ter | 0.7941 ± 0.0101 |
| bcms-bertic-parlasent-bcs-bi (this model) | 0.8999 ± 0.012 |
## Citation
If you use the model, please cite the following paper on which the original model is based:
```
@inproceedings{ljubesic-lauc-2021-bertic,
title = "{BERT}i{\'c} - The Transformer Language Model for {B}osnian, {C}roatian, {M}ontenegrin and {S}erbian",
author = "Ljube{\v{s}}i{\'c}, Nikola and Lauc, Davor",
booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
month = apr,
year = "2021",
address = "Kiyv, Ukraine",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.bsnlp-1.5",
pages = "37--42",
}
```
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