Update readme

README.md

@@ -6,19 +6,17 @@ widget:
 
 # RoBERTa Pretrained for Tigrinya Language
 
-We pretrain a RoBERTa Base model on a relatively small dataset for Tigrinya (34M tokens) for 18 epochs.
+We pretrain a RoBERTa base model for Tigrinya on a dataset of 40 million tokens trained for 40 epochs.
 
-Contained in this card is a PyTorch model exported from the original model that was trained on TPU v3.8 with Flax.
+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 | 125M |
-
-(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 | 125M | 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.)