File size: 1,108 Bytes
9cf8654 1c2b6a8 9cf8654 2f99e9b 6fe1195 2f99e9b 6fe1195 2f99e9b 6fe1195 2f99e9b 80a682e 091ff14 2f99e9b 80a682e 6fe1195 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 |
---
language: ti
widget:
- text: "ዓቕሚ ደቂኣንስትዮ [MASK] ብግብሪ ተራእዩ"
---
# 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.
## 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}
}
```
|