JonatanGk's picture
Update README.md
7ad8e3d
|
raw
history blame
3.2 kB
metadata
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 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

Training procedure

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

Model in action 🚀

Fast usage with pipelines:

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

Framework versions

  • Transformers 4.10.3
  • Pytorch 1.9.0+cu102
  • Datasets 1.12.1
  • Tokenizers 0.10.3

Citation

@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 as my mentor & R.C.

Created by Jonatan Luna | LinkedIn