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---
language:
- ca
license: apache-2.0
tags:
- "catalan"
- "part of speech tagging"
- "pos"
- "CaText"
- "Catalan Textual Corpus"
datasets:
- "universal_dependencies"
metrics:
- f1
inference:
parameters:
aggregation_strategy: "first"
model-index:
- name: roberta-base-ca-v2-cased-pos
results:
- task:
type: token-classification
dataset:
type: universal_dependencies
name: Ancora-ca-POS
metrics:
- name: F1
type: f1
value: 0.9896
widget:
- text: "Em dic Lluïsa i visc a Santa Maria del Camí."
- text: "L'Aina, la Berta i la Norma són molt amigues."
- text: "El Martí llegeix el Cavall Fort."
---
# Catalan BERTa-v2 (roberta-base-ca-v2) finetuned for Part-of-speech-tagging (POS)
## Table of Contents
- [Model Description](#model-description)
- [Intended Uses and Limitations](#intended-uses-and-limitations)
- [How to Use](#how-to-use)
- [Training](#training)
- [Training Data](#training-data)
- [Training Procedure](#training-procedure)
- [Evaluation](#evaluation)
- [Variable and Metrics](#variable-and-metrics)
- [Evaluation Results](#evaluation-results)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Funding](#funding)
- [Contributions](#contributions)
## Model description
The **roberta-base-ca-v2-cased-pos** is a Part-of-speech-tagging (POS) model for the Catalan language fine-tuned from the [roberta-base-ca-v2](https://huggingface.co/projecte-aina/roberta-base-ca-v2) model, a [RoBERTa](https://arxiv.org/abs/1907.11692) base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers (check the roberta-base-ca-v2 model card for more details).
## Intended Uses and Limitations
**roberta-base-ca-v2-cased-pos** model can be used to Part-of-speech-tagging (POS) a text. The model is limited by its training dataset and may not generalize well for all use cases.
## How to Use
Here is how to use this model:
```python
from transformers import pipeline
from pprint import pprint
nlp = pipeline("token-classification", model="projecte-aina/roberta-base-ca-v2-cased-pos")
example = "Em dic Lluïsa i visc a Santa Maria del Camí."
pos_results = nlp(example)
pprint(pos_results)
```
## Training
### Training data
We used the POS dataset in Catalan from the [Universal Dependencies Treebank](https://huggingface.co/datasets/universal_dependencies) we refer to _Ancora-ca-pos_ for training and evaluation.
### Training Procedure
The model was trained with a batch size of 16 and a learning rate of 5e-5 for 5 epochs. We then selected the best checkpoint using the downstream task metric in the corresponding development set and then evaluated it on the test set.
## Evaluation
### Variable and Metrics
This model was finetuned maximizing F1 score.
## Evaluation results
We evaluated the _roberta-base-ca-v2-cased-pos_ on the Ancora-ca-ner test set against standard multilingual and monolingual baselines:
| Model | Ancora-ca-pos (F1) |
| ------------|:-------------|
| roberta-base-ca-v2-cased-pos | **98.96** |
| roberta-base-ca-cased-pos | **98.96** |
| mBERT | 98.83 |
| XLM-RoBERTa | 98.89 |
For more details, check the fine-tuning and evaluation scripts in the official [GitHub repository](https://github.com/projecte-aina/club).
## Licensing Information
[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
## Citation Information
If you use any of these resources (datasets or models) in your work, please cite our latest paper:
```bibtex
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de Gibert Bonet, Ona and
Armentano-Oller, Carme and
Gonzalez-Agirre, Aitor and
Melero, Maite and
Villegas, Marta",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.437",
doi = "10.18653/v1/2021.findings-acl.437",
pages = "4933--4946",
}
```
### Funding
This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
## Contributions
[N/A]
|