language:
- ca
license: apache-2.0
tags:
- catalan
- named entity recognition
- ner
- CaText
- Catalan Textual Corpus
datasets:
- projecte-aina/ancora-ca-ner
metrics:
- f1
model-index:
- name: roberta-base-ca-v2-cased-ner
results:
- task:
type: token-classification
dataset:
type: projecte-aina/ancora-ca-ner
name: Ancora-ca-NER
metrics:
- name: F1
type: f1
value: 0.8945
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 Named Entity Recognition.
The roberta-base-ca-v2-cased-ner is a Named Entity Recognition (NER) model for the Catalan language fine-tuned from the roberta-base-ca-v2 model, a RoBERTa 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).
Datasets
We used the NER dataset in Catalan called Ancora-ca-NER for training and evaluation.
Evaluation and results
We evaluated the roberta-base-ca-v2-cased-ner on the Ancora-ca-ner test set against standard multilingual and monolingual baselines:
| Model | Ancora-ca-ner (F1) |
|---|---|
| roberta-base-ca-v2-cased-ner | 89.45 |
| roberta-base-ca-cased-ner | 88.94 |
| mBERT | 87.36 |
| XLM-RoBERTa | 88.07 |
For more details, check the fine-tuning and evaluation scripts in the official GitHub repository.
Citing
If you use any of these resources (datasets or models) in your work, please cite our latest paper:
@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 Catalan Government within the framework of the AINA project..