Add the first model card

README.md

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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",
+}
+```
+