Update README.md

README.md

@@ -45,7 +45,7 @@ We follow the model architecture of LLaMa, and we use the GPT-NeoX-20B tokenizer
 
 During training, we use 2,048 token sequences that are packed across document boundaries, and we pre-pend a beginning-of-text token to every document. 
 
-We use weight decay of 0.1, the Adam optimizer with beta_2 0.95, 2,000 steps of warmup, with a cosine learning rate scheduler. 
+We use weight decay of 0.1, the Adam optimizer with beta_2 of 0.95, 2,000 steps of warmup, with a cosine learning rate scheduler. 
 
 
 | Model  | #L  | #H  | d_model | LR     | Batch  |