Update README.md

README.md

@@ -35,7 +35,7 @@ The model might not perform well in identifying and classifying entities that we
 
 ## Training and evaluation data
 
-The model was trained using a diverse dataset, including artificially generated tweets and ERC20 token metadata fetched through the [Covalent API](https://www.covalenthq.com/docs/unified-api/). GPT was employed to generate 500 synthetic tweets tailored for the cryptocurrency domain. The Covalent API was instrumental in obtaining a rich set of 20K+ unique ERC20 token metadata entries, enhancing the model's understanding and recognition of cryptocurrency entities.
+The model was trained using a diverse dataset, including artificially generated tweets and ERC20 token metadata fetched through the [Covalent API](https://www.covalenthq.com/docs/unified-api/). GPT was employed to generate 500 synthetic tweets tailored for the cryptocurrency domain. The Covalent API was instrumental in obtaining a rich set of unique ERC20 token metadata entries, enhancing the model's understanding and recognition of cryptocurrency entities.
 
 ## Training procedure