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BERT Base for Tigrinya Language

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.


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

Model Size L AH HS FFN P Seq
BASE 12 12 768 3072 110M 512

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


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

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