Added summary of the paper

Author: shagunsodhani

README.md

@@ -12,7 +12,7 @@ Simplified implementation of "Convolutional Neural Networks for Sentence Classif
 * Refer [this](http://nlp.stanford.edu/projects/glove/) to train or download Glove embeddings and [this](https://code.google.com/archive/p/word2vec/) for Word2Vec embeddings.
 * Run `python3 app/train.py --data_dir=path_to_folder_containing_input.txt_and_label.txt --embedding_file_path=path_to_embedding_vectors_file --model_name=name_of_model_from_the_paper`
 * For example, if data is in `data` folder, embedding file is `vectors.txt` and model is `cnn_static`, run `python3 app/train.py --data_dir=data --embedding_file_path=vectors.txt --model_name=cnn_static`
-* To define your own model, pass `model_name` as `self`, define your model in [app/model/model.py](app/model/model.py)and invoke from `model_selector` function (in [model.py](app/model/model.py)).'
+* To define your own model, pass `model_name` as `self`, define your model in [app/model/model.py](app/model/model.py) and invoke from `model_selector` function (in [model.py](app/model/model.py)).
 * All supported arguments can be seen in [here](app/utils/argumentparser.py)
 
 ## References