BERT Base for Tigrinya Language

We pretrain a BERT base-uncased model for Tigrinya on a dataset of 40 million tokens trained for 40 epochs.

Contained in this repo are the original pretrained Flax model that was trained on a TPU v3.8 and it's correponding PyTorch version.


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

Model Size L AH HS FFN P Seq
BASE 12 12 768 3072 110M 128

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

New: fine-tune this model in a few clicks by selecting AutoNLP in the "Train" menu!
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