docs(README): update speed & accuracy section

Author: sanjayaksaxena

README.md

@@ -123,7 +123,7 @@ The [winkNLP](https://winkjs.org/wink-nlp/) processes raw text at **~650,000 tok
 
 The benchmark was conducted on [Node.js versions 16, and 18](https://nodejs.org/en/about/releases/).
 
-It pos tags a subset of WSJ corpus with an accuracy of **~94.7%** — this includes *tokenization of raw text prior to pos tagging*. The present state-of-the-art is at ~97% accuracy but at lower speeds and is generally computed using gold standard pre-tokenized corpus.
+It pos tags a subset of WSJ corpus with an accuracy of **~95%** — this includes *tokenization of raw text prior to pos tagging*. The present state-of-the-art is at ~97% accuracy but at lower speeds and is generally computed using gold standard pre-tokenized corpus.
 
 Its general purpose sentiment analysis delivers a [f-score](https://en.wikipedia.org/wiki/F1_score) of **~84.5%**, when validated using Amazon Product Review [Sentiment Labelled Sentences Data Set](https://archive.ics.uci.edu/ml/machine-learning-databases/00331/) at [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/index.php). The current benchmark accuracy for **specifically trained** models can range around 95%.