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README.md

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 # BERT Base for Tigrinya Language
 
-We pretrain a BERT base-uncased model on a relatively small dataset for Tigrinya (34M tokens) for 40 epochs.
-
-Contained in this card is a PyTorch model exported from the original model that was trained on a TPU v3.8 with Flax.
+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.
 
 ## Hyperparameters
 
 The hyperparameters corresponding to model sizes mentioned above are as follows:
 
-| Model Size | L  | AH | HS  | FFN  | P    |
-|------------|----|----|-----|------|------|
-| BASE       | 12 | 12 | 768 | 3072 | 110M |
-
-(L = number of layers; AH = number of attention heads; HS = hidden size; FFN = feedforward network dimension; P = number of parameters.)
-
+| 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.)