model_1 = Sequential()
model_1.add(Embedding(1000,32, input_length = X_train.shape[0]))
model_1.add(Flatten())
model_1.add(Dense(250, activation='relu'))
model_1.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])

(4834,)

model_1.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=2, batch_size=64, verbose=2)