Multilingual Bert Gn Base Cased

🚀 mBERT+gn-base-cased (multilingual-BERT+gn-base-cased)

This project fine-tunes the BERT multilingual base model (cased, pre-trained BERT model) for Guarani language modeling, covering 104 languages plus Guarani. It is trained on Wikipedia and Wiktionary with approximately 800K tokens.

🚀 Quick Start

No specific quick start steps are provided in the original document.

✨ Features

• Multilingual Support: Supports multiple languages including Guarani.
• Fine-tuning: Fine-tuned on the BERT multilingual base model for Guarani language modeling.
• Training Data: Trained on Wikipedia and Wiktionary datasets.

📦 Installation

No installation steps are provided in the original document.

💻 Usage Examples

No code examples are provided in the original document.

📚 Documentation

Language and Datasets

Metrics

The model uses the following metrics for evaluation:

• F1
• Accuracy

Widget Examples

• Paraguay ha'e peteĩ táva oĩva [MASK] retãme
• Augusto Roa Bastos ha'e peteĩ [MASK] arandu

🔧 Technical Details

No technical details are provided in the original document.

📄 License

The project is licensed under the MIT license.

How to Cite?

@article{aguero-et-al2023multi-affect-low-langs-grn,
  title={Multidimensional Affective Analysis for Low-resource Languages: A Use Case with Guarani-Spanish Code-switching Language},
  author={Agüero-Torales, Marvin Matías, López-Herrera, Antonio Gabriel, and Vilares, David},
  journal={Cognitive Computation},
  year={2023},
  publisher={Springer},
  notes={Forthcoming}
}