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.
Hyperparameters
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.)
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}
}
