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---
language: la
license: apache-2.0
inference: false
---
# LaBerta
The paper [Exploring Language Models for Classical Philology](https://todo.com) is the first effort to systematically provide state-of-the-art language models for Classical Philology. LaBerta is a RoBerta-base sized, monolingual, encoder-only variant.
This model was trained on the [Corpus Corporum](https://mlat.uzh.ch/).
Further information can be found in our paper or in our [GitHub repository](https://github.com/Heidelberg-NLP/ancient-language-models).
## Usage
```python
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained('bowphs/LaBerta')
model = AutoModelForMaskedLM.from_pretrained('bowphs/LaBerta')
```
Please check out the awesome Hugging Face tutorials on how to fine-tune our models.
## Evaluation Results
When fine-tuned on PoS data from [EvaLatin 2022](https://universaldependencies.org/), LaBerta achieves the following results:
| Task | Classical | Cross-genre | Cross-time |
|:--:|:--:|:--:|:--:|
| |98.11|96.73|93.33|
## Contact
If you have any questions or problems, feel free to [reach out](mailto:riemenschneider@cl.uni-heidelberg.de).
## Citation
```bibtex
@incollection{riemenschneiderfrank:2023,
address = "Toronto, Canada",
author = "Riemenschneider, Frederick and Frank, Anette",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL’23)",
note = "to appear",
pubType = "incollection",
publisher = "Association for Computational Linguistics",
title = "Exploring Large Language Models for Classical Philology",
url = "https://arxiv.org/abs/2305.13698",
year = "2023",
key = "riemenschneiderfrank:2023"
}
``` |