Words from word2vec not present in TensorBoard

I'm working on a project which is needed to use word2vec. when I run my simple code everything gonna be ok but while I use tensorboard to see my result, I just face a 3D vector with JUST THE FIRST LITTER OF SOME WORDS!
**my corpus is in english and have 1000 sentences
**at first I didn't token my corpus but now I do
Why should I do???
and here is my code:

import logging
import gensim
from gensim.models.word2vec import Word2Vec
vector_size = 512
window_size = 10
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s',
level=logging.INFO)
word2vec = Word2Vec (sentences='dataset.csv',size=200
,window=10,negative=20,seed=1000,min_count=1)
word2vec.save('text646.model')
word2vec.wv.save_word2vec_format('text.model.bin', binary=True)
model= gensim.models.KeyedVectors.load_word2vec_format('text.model.bin',
binary=True)


Here is a screen shot from tensorbord:

thank alot

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