metadata

language:
  - ca
tags:
  - catalan
  - text classification
  - tecla
  - CaText
  - Catalan Textual Corpus
datasets:
  - projecte-aina/tecla
metrics:
  - accuracy
model-index:
  - name: roberta-base-ca-cased-tc
    results:
      - task:
          type: text-classification
        dataset:
          name: tecla
          type: projecte-aina/tecla
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.740388810634613
widget:
  - text: Els Pets presenten el seu nou treball al Palau Sant Jordi.
  - text: >-
      Els barcelonins incrementen un 23% l’ús del cotxe des de l’inici de la
      pandèmia.
  - text: >-
      Retards a quatre línies de Rodalies per una avaria entre Sants i plaça de
      Catalunya.
  - text: >-
      Majors de 60 anys i sanitaris començaran a rebre la tercera dosi de la
      vacuna covid els propers dies.
  - text: Els cinemes Verdi estrenen Verdi Classics, un nou canal de televisió.

Catalan BERTa (RoBERTa-base) finetuned for Text Classification.

The roberta-base-ca-cased-tc is a Text Classification (TC) model for the Catalan language fine-tuned from the BERTa model, a RoBERTa base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers (check the BERTa model card for more details).

Datasets

We used the TC dataset in Catalan called TeCla for training and evaluation.

Evaluation and results

We evaluated the roberta-base-ca-cased-tc on the TeCla test set against standard multilingual and monolingual baselines:

Model	TeCla (accuracy)
roberta-base-ca-cased-tc	74.04
mBERT	70.56
XLM-RoBERTa	71.68
WikiBERT-ca	73.22

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",
}