Update README.md

README.md

@@ -115,13 +115,12 @@ Train data should be a json file, where each line is a dict like this:
 {"query": str, "pos": List[str], "neg": List[str]}
 ```
 
-`query` is the query, and `pos` is a list of positive texts, `neg` is a list of negative texts, `prompt` indicates the
-relationship between query and texts. If you have no negative texts for a query, you can random sample some from the
-entire corpus as the negatives.
+`query` is the query, and `pos` is a list of positive texts, `neg` is a list of negative texts. If you have no negative
+texts for a query, you can random sample some from the entire corpus as the negatives.
 
 ## Performance
 
-In the following table, we provide various pre-trained Cross-Encoders together with their performance on
+Below is a comparision table of the results we achieved compared to some other pre-trained Cross-Encoders on
 the [MS MMarco Passage Reranking - Vi - Dev](https://huggingface.co/datasets/unicamp-dl/mmarco) dataset.
 
 | Model-Name                                                                                                                              | NDCG@3     | MRR@3      | NDCG@5     | MRR@5      | NDCG@10    | MRR@10     | Docs / Sec |