Tibert Base

🚀 BERT Base for Tigrinya Language

A pre - trained BERT base - uncased model for the Tigrinya language, trained on a dataset of 40 million tokens for 40 epochs.

🚀 Quick Start

We pre - train a BERT base - uncased model for Tigrinya on a dataset of 40 million tokens trained for 40 epochs. This repo contains the original pre - trained Flax model that was trained on a TPU v3.8 and its corresponding PyTorch version.

📚 Documentation

Hyperparameters

The hyperparameters corresponding to the model sizes mentioned above are as follows:

(L = number of layers; AH = number of attention heads; HS = hidden size; FFN = feedforward network dimension; P = number of parameters; Seq = maximum sequence length.)

📄 License

Citation

If you use this model in your product or research, please cite as follows:

@article{Fitsum2021TiPLMs,
  author={Fitsum Gaim and Wonsuk Yang and Jong C. Park},
  title={Monolingual Pre - trained Language Models for Tigrinya},
  year=2021,
  publisher={WiNLP 2021 at EMNLP 2021}
}