Update README.md

README.md

@@ -7,7 +7,7 @@ Language model of the pre-print arXiv paper titled: "_**miCSE**: Mutual Informat
 
 
 # Brief Model Description
-The **miCSE** language model is trained for sentence similarity computation. Training the model imposes alignment between the attention pattern of different views (embeddings of augmentations) during contrastive learning. Learning sentence embeddings with **miCSE** entails enforcing the syntactic consistency across augmented views for every single sentence, making contrastive self-supervised learning more sample efficient. This is achieved by regularizing the attention distribution. Regularizing the attention space enables learning representation in self-supervised fashion even when the training corpus is comparatively small. This is particularly interesting for real-world NLP applications, where training data is significantly smaller thank Wikipedia.
+The **miCSE** language model is trained for sentence similarity computation. Training the model imposes alignment between the attention pattern of different views (embeddings of augmentations) during contrastive learning. Learning sentence embeddings with **miCSE** entails enforcing the syntactic consistency across augmented views for every single sentence, making contrastive self-supervised learning more sample efficient. This is achieved by regularizing the attention distribution. Regularizing the attention space enables learning representation in self-supervised fashion even when the _training corpus is comparatively small_. This is particularly interesting for _real-world applications_, where training data is significantly smaller thank Wikipedia.
 
 
 # Intended Use