Update README.md

README.md

@@ -12,12 +12,20 @@
             - **get_glove_embeddings.bash**: *script* que descarga el conjunto de de vectores de palabras computado con GloVe utilizado.
         - **word2vec/get_word2vec_embeddings.bash**: *script* que descarga el conjunto de de vectores de palabras computado con Word2Vec utilizado.    
     - **frequencies.tsv**
+
+
 - **.gitignore**
+
 - **LICENSE**
+
 - **SENTEVAL_LICENSE**: licencia del toolkit [SentEval](https://github.com/facebookresearch/SentEval) desarollado por Facebook.
+
 - **evaluation.ipynb**: fichero de Jupyter Notebook en el que se desarrolla la evaluación realizada.
+
 - **load.py**: contiene un conjunto de funciones para cargar y preprocesar los diferentes conjuntos de datos utilizados. El código está basado en el que se puede encontrar en el toolkit [SentEval](https://github.com/facebookresearch/SentEval).
+
 - **methods.py**: contiene las funciones que implementan los tres métodos evaluados para calcular la similiridad semántica entre dos pares de oraciones: media (average), *Smooth Inverse Frequency* (SIF), y *Word Mover's distance*.
+
 - **utils.py**: contiene algunas funciones de utilidad como para preprocesar las oraciones y evaluar los resultados de los diferentes métodos.
 
 
@@ -29,21 +37,27 @@
 
 - **data/**
     - **datatsets/**
-    - **get_datasets.bash**: * script * that allows downloading the data sets used in the evaluation and which is a modification of the one present in the [SentEval] toolkit (https://github.com/facebookresearch/SentEval).
+    - **get_datasets.bash**: script that downloads the data sets used in the evaluation and which is a modification of the one present in the [SentEval](https://github.com/facebookresearch/SentEval) toolkit .
     - **tokenizer.vec**
     - **embedding/**
-        - **fasttext/get_fasttext_embeddings.bash**: * script * that downloads the set of word vectors computed with the FastText used.
+        - **fasttext/get_fasttext_embeddings.bash**: script that downloads the set of word vectors computed with the FastText used.
         - **gloVe/**
-            - **2word2vec.py**: Transform the GloVe vector set to Word2Vec format.
-            - **get_glove_embeddings.bash**: * script * that downloads the GloVe computed word vector set used.
-    - **word2vec/get_word2vec_embeddings.bash**: * script * that downloads the set of word vectors computed with the Word2Vec used.
+            - **2word2vec.py**: transforms the GloVe vector set to Word2Vec format.
+            - **get_glove_embeddings.bash**: script that downloads the GloVe word embeddings set used.
+    - **word2vec/get_word2vec_embeddings.bash**: script that downloads the Word2Vec word embeddings set used.
     - **frequencies.tsv**
+
 - **.gitignore**
+
 - **LICENSE**
+
 - **SENTEVAL_LICENSE**: license of the [SentEval](https://github.com/facebookresearch/SentEval) toolkit  developed by Facebook.
+
 - **evaluation.ipynb**: Jupyter Notebook file in which the evaluation carried out is developed.
-- **load.py**: Contains a set of functions to load and preprocess the different data sets used. The code is based on what can be found in the [SentEval] toolkit (https://github.com/facebookresearch/SentEval).
-- **methods.py**: Contains the functions that implement the three evaluated methods to calculate the semantic similarity between two pairs of sentences: average (average), * Smooth Inverse Frequency * (SIF), and * Word Mover's distance *.
-- **utils.py**: Contains some utility functions to preprocess sentences and evaluate the results of the different methods.
+
+- **load.py**: contains a set of functions to load and preprocess the different data sets used. The code is based on what can be found in the [SentEval](https://github.com/facebookresearch/SentEval) toolkit .
+
+- **methods.py**: contains the functions that implement the three evaluated methods to calculate the semantic similarity between two pairs of sentences: average, Smooth Inverse Frequency(SIF), and Word Mover's distance.
+- **utils.py**: contains some utility functions to preprocess sentences and evaluate the results of the different methods.