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