Tensorflow word2vec word embeddings for adjectives

implementing Word Embeddings for adjectives, obtained embeddings to preserve as much synonym relationship as possible. We provide only the raw form of data to be used in this project. For embeddings, you are required to process this dataset using spaCy. You can write out your processed data file in the Present Working Directory (PWD), which can later be used to train the embeddings. While the vanilla word2vec skip-gram model generates its (mini-batches of) training data between a center word and a random sample of its context, you are encouraged to think of new methods such that the resulting embedding for adjectives are more likely to preserve the synonym relationship in its top-k results.