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metadata
language:
  - ca
tags:
  - catalan
  - text classification
  - tecla
  - CaText
  - Catalan Textual Corpus
datasets:
  - projecte-aina/tecla
metrics:
  - accuracy
model-index:
  - name: roberta-base-ca-v2-cased-tc
    results:
      - task:
          type: text-classification
        dataset:
          name: TeCla
          type: projecte-aina/tecla
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7426
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Catalan BERTa-v2 (roberta-base-ca-v2) finetuned for Text Classification.

The roberta-base-ca-v2-cased-tc is a Text Classification (TC) 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 TC dataset in Catalan called TeCla for training and evaluation.

Evaluation and results

We evaluated the roberta-base-ca-v2-cased-tc on the TeCla test set against standard multilingual and monolingual baselines:

Model TeCla (Accuracy)
roberta-base-ca-v2-cased-tc 74.26
roberta-base-ca-cased-tc 73.65
mBERT 69.90
XLM-RoBERTa 70.14

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..