updated README

README.md

@@ -82,13 +82,12 @@ print(metric.inputs_description)
 [//]: # (- **input_field** *(type): Definition of input, with explanation if necessary. State any default value(s).*)
 
 ### Output Values
-Singleton/List of `Scores` dataclass corresponding to each sample - 
+A Singleton/List of `Scores` dataclass with attributes as follows - 
 
  - `precision: float`: Precision score, which ranges from 0.0 to 1.0.
  - `recall: List[float]`: Recall score corresponding to each reference
  - `f1: float`: F1 score (between precision and average recall).
 
-
 ## Extensions
 Currently, we have only implemented the 3 encoders* that we experimented with in our 
 [paper](https://aclanthology.org/2022.emnlp-main.49/). Furthermore, you can use any model on