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}
}
Runs of fgaim tiroberta-base on huggingface.co
390
Total runs
0
24-hour runs
6
3-day runs
18
7-day runs
346
30-day runs
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