readme: ---
  language: ca
  tags:
  - "catalan"
  metrics:
  - accuracy
  widget:
   - text: "Ets més petita que un barrufet!!"
   - text: "Ets tan lletja que et donaven de menjar per sota la porta."
   
  ---
  # roberta-base-ca-finetuned-cyberbullying-catalan
  
  This model is a fine-tuned version of [BSC-TeMU/roberta-base-ca](https://huggingface.co/BSC-TeMU/roberta-base-ca) on the dataset generated scrapping all social networks (Twitter, Youtube ...) to detect cyberbullying on Catalan.
  
  It achieves the following results on the evaluation set:
  - Loss: 0.1508
  - Accuracy: 0.9665
  
  ## Training and evaluation data
  
  I use the concatenation from multiple datasets generated scrapping social networks (Twitter,Youtube,Discord...)  to fine-tune this model. The total number of sentence pairs is above 410k sentences. Trained similar method at [roberta-base-bne-finetuned-cyberbullying-spanish](https://huggingface.co/JonatanGk/roberta-base-bne-finetuned-cyberbullying-spanish)
  
  ## Training procedure
  
  <details>
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  </details>
  
  ### Model in action 🚀
  
  Fast usage with **pipelines**:
  
  ```python
  from transformers import pipeline
  
  model_path = "JonatanGk/roberta-base-ca-finetuned-ciberbullying-catalan"
  bullying_analysis = pipeline("text-classification", model=model_path, tokenizer=model_path)
  
  bullying_analysis(
      "Des que et vaig veure m'en vaig enamorar de tu."
      )
      
  # Output:
  [{'label': 'Not_bullying', 'score': 0.9996786117553711}]
  
  bullying_analysis(
      "Ets tan lletja que et donaven de menjar per sota la porta."
      )
      
  # Output:
  [{'label': 'Bullying', 'score': 0.9927878975868225}]
      
  ```
  
  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JonatanGk/Shared-Colab/blob/master/Cyberbullying_detection_(CATALAN).ipynb)
  
  ### Framework versions
  - Transformers 4.10.3
  - Pytorch 1.9.0+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  
  ## Citation
  
  ```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",
  }
  ```
  
  > Special thx to [Manuel Romero/@mrm8488](https://huggingface.co/mrm8488) as my mentor & R.C.
  
  > Created by [Jonatan Luna](https://JonatanGk.github.io) | [LinkedIn](https://www.linkedin.com/in/JonatanGk/)
  