readme: This model can measure semantic similarity between pairs of texts containing figurative language. As far as we know, 
  
  this model works slightly better than sup-simCSE-roberta-base. For example : 
  
  **sentence 1**: I have been in seventh heaven since Harry entered my life .
  
  **sentence 2**: I have been in very happy since Harry entered my life.
  
  the cosin score of simcse: 0.897
  
  the cosin score of us: 0.897
  
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  **sentence 1**: I have been in seventh heaven since Harry entered my life .
  
  **sentence 2**: I have been in pain since Harry entered my life .
  
  the cosin score of simcse: 0.846
  
  the cosin score of us: 0.753
  
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  It's still a big challenge for us to measure semantic similarity of figurative language from the sentence embedding perspective.
  
  unsupvised models may useless as the key is to infer the literal meaning of the figurative expression, since the annotated is rare.
  