metadata
language: ti
widget:
- text: ዓቕሚ መንእሰይ ኤርትራ <mask> ተራእዩ
TiRoBERTa: RoBERTa Pretrained for the Tigrinya Language
We pretrain a RoBERTa base model for Tigrinya on a dataset of 40 million tokens trained for 40 epochs.
Contained in this repo is the original pretrained Flax model that was trained on a TPU v3.8 and it's corresponding PyTorch version.
Hyperparameters
The hyperparameters corresponding to model sizes mentioned above are as follows:
Model Size | L | AH | HS | FFN | P | Seq |
---|---|---|---|---|---|---|
BASE | 12 | 12 | 768 | 3072 | 125M | 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.)
Framework versions
- Transformers 4.12.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
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}
}