Update README.md

README.md

@@ -41,7 +41,7 @@ print(result)
 
 ## Intended uses & limitations
 
-While the classifier performs well in distinguishing high-quality code in its target language (C++ in this case), there are some limitations:
+While the classifier performs well in distinguishing high-quality code in its target language (JS in this case), there are some limitations:
 
 - Scope: The model's performance might change for other datasets, in particular for out of distribution samples. The classifier's context is 1024 tokens, which might not be sufficient to assess the quality of some long code files.
 - Bias: The model's performance is dependent on the quality and representativeness of the training data and the LLM used for the annotation. Biases in both can affect the classifier's judgments. It might overfit to thoroughly commented code.