Update README

README.md

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 > **Research and Materials on Hardware implementation of BERT (Bidirectional Encoder Representations from Transformers) Model**
 
 <center><img src="https://img.shields.io/badge/Status-WIP-ff69b4?style=flat-square"/></center>
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 <center><img src="https://img.shields.io/badge/Progress-%2599-ef6c00?labelColor=1565c0&style=flat-square"/></center>
 
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 ## BERT Model
 
-* BERT is a method of **pre-training language representations**, meaning that we **train a general-purpose *language understanding model*** on a large text corpus (like Wikipedia) and then use that model for downstream NLP tasks.**
+* BERT is a method of **pre-training language representations**, meaning that we **train a general-purpose *language understanding model*** on a large text corpus (like Wikipedia) and then use that model for downstream NLP tasks.
 
-* BERT was created and **published in 2018 by Jacob Devlin and his colleagues from Google**. BERT is conceptually simple and empirically powerful. It obtains new state-of-the-art results on eleven natural language processing tasks.**
+* BERT was created and **published in 2018 by Jacob Devlin and his colleagues from Google**. BERT is conceptually simple and empirically powerful. It obtains new state-of-the-art results on eleven natural language processing tasks.
 
 <p align="center">
   <img src="./data/img/BERT-ARCH.png" />

data/header.txt

@@ -2,6 +2,7 @@
 > **Research and Materials on Hardware implementation of BERT (Bidirectional Encoder Representations from Transformers) Model**
 
 <center><img src="https://img.shields.io/badge/Status-WIP-ff69b4?style=flat-square"/></center>
+
 <center><img src="https://img.shields.io/badge/Progress-%2599-ef6c00?labelColor=1565c0&style=flat-square"/></center>
 
 <p align="center">
@@ -12,9 +13,9 @@
 
 ## BERT Model
 
-* BERT is a method of **pre-training language representations**, meaning that we **train a general-purpose *language understanding model*** on a large text corpus (like Wikipedia) and then use that model for downstream NLP tasks.**
+* BERT is a method of **pre-training language representations**, meaning that we **train a general-purpose *language understanding model*** on a large text corpus (like Wikipedia) and then use that model for downstream NLP tasks.
 
-* BERT was created and **published in 2018 by Jacob Devlin and his colleagues from Google**. BERT is conceptually simple and empirically powerful. It obtains new state-of-the-art results on eleven natural language processing tasks.**
+* BERT was created and **published in 2018 by Jacob Devlin and his colleagues from Google**. BERT is conceptually simple and empirically powerful. It obtains new state-of-the-art results on eleven natural language processing tasks.
 
 <p align="center">
   <img src="./data/img/BERT-ARCH.png" />