Update README.md

README.md

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-## Main Features
+## Corpus Summary
 
-The preprocessing of the corpus for the encoders Sent2vec+CelebA has been to translate into Spanish the captions of the CelebA dataset with the algorithm used in Text2FaceGAN.
+This corpus has 192050 entries made up of descriptive sentences of the faces of the CelebA dataset.
+The preprocessing of the corpus has been to translate into Spanish the captions of the CelebA dataset with the algorithm used in [Text2FaceGAN](https://arxiv.org/pdf/1911.11378.pdf). 
+In particular, all sentences are combined to generate a larger corpus. Additionally, a data preprocessing was applied that consists of eliminating stopwords, separation symbols and complementary elements that are not useful for training.
+Finally, using the Sent2vec library and the corpus, training was done to obtain an encoder model for sentences in the Spanish language. Specifically for captions from the CelebA 
+dataset
 
-Subsequently, a new corpus was created with the translated information having the same structure as the original English version. 
+The training of Sent2vec + CelebA, using the present corpus was developed, resulting in the new model [Sent2vec-CelebA-Sp](https://huggingface.co/oeg/Sent2vec_CelebA_Sp).
 
-Finally, a training corpus has been generated for Sent2vec+CelebA by performing an information cleaning process on the dataset generated in the previous step. 
-In particular, all sentences are combined to generate a larger corpus.
+## Corpus Fields
+Each corpus entry is composed of:
+- Descriptive sentence of a face from the CelebA dataset applied the corresponding preprocessing. 
 
-**Citing**: If you used Sent2vec+CelebA in your work, please cite the **[????](???)**:
+**Citing**: If you used CelebA_Sent2vec_Sp corpus in your work, please cite the **[????](???)**:
 
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