In Word2Vec, how to the vector values translate back to related words?
In case you use Gensim in Python, you can create a dictionary with the word and the vector.

from gensim.models import Word2Vec

# we create a Word2Vec model using a window size of 4 and word vectors dimensionality of 100
model_1 = Word2Vec(window=4,size=100,sg=1,min_count=1, workers = -1)
# prepare the model vocabulary
model_1.build_vocab(this_is_your_text_dataset)
# train the model
model_1.train(this_is_your_text_dataset,total_examples=model_1.corpus_count,epochs=model_1.iter)

#we create a dictionary with the word and its vector as the value
vectors_model = dict(zip(model_1.wv.index2word, model_1.wv.syn0))


The above will create a dictionary in the format:

{
"word_1": vector_1,
"word_2": vector_2,
"word_3": vector_3,
....
}


With this, you can go back and forth from words to vectors and from vectors to words.