Update README.md

README.md

@@ -24,13 +24,12 @@ size_categories:
 
 The training of RoBERTa+CelebA has been performed with a Siamese network that evaluates the similarity of the embeddings generated by the transformer network using the cosine similarity metric. 
 
-Therefore, each input of the training data consists of a pair of sentences $A$ and $B$ in English and their respective similarity in the range 0 to 1.
+Therefore, each input of the training data consists of a pair of sentences A and B in English and their respective similarity in the range 0 to 1.
 
 First, a translation of the original English text into Spanish was made . 
-Subsequently, the document structure defines in each line (input) a pair of Spanish sentences and their respective similarity value between 0 and 1 calculated by the \texttt{Spacy} library. 
+Subsequently, the document structure defines in each line (input) a pair of Spanish sentences and their respective similarity value between 0 and 1 calculated by the Spacy library. 
 However, since Spacy library works only with English entries, the similarity between two Spanish sentences has been matched with their respective English pairs. 
 Finally, the final training corpus for RoBERTa is defined by the Spanish text and the similarity score. 
-To carry out this procedure, the Algorithm~\ref{alg:two} was generated.
 
 **Citing**: If you used RoBERTa+CelebA in your work, please cite the **[????](???)**: