What is the problem in this keras input shape?

Question

from matplotlib import units
import numpy as np 
from tensorflow.keras.models import Sequential 
from tensorflow.keras.layers import Dense
from tensorflow.keras import optimizers
from tensorflow import keras
x_test = np.array([[0,0,0,0,0],[1,1,1,1,1]])
x_data = np.array([[[0,0,0,0,0],[1,1,1,1,1]],
[[1,1,1,1,1],[0,0,0,0,0]]])
y_data = np.array([[0],[1]])
model = Sequential([
    Dense(2,activation='sigmoid'),
    Dense(1,activation='sigmoid')
]
)
sgd = optimizers.SGD(learning_rate = 0.001) 
model.compile(loss='mse', optimizer=sgd, metrics=['mse']) 
# model fit 
history = model.fit(x_data, y_data, batch_size=1, epochs=400, shuffle=False, verbose=1) # prediction 
print (model.predict(x_test))

I want to get one output but when I do program it output like [[[~~],[~~]]] this. iNPUT WHEN x is [[[1,1,1,1,1],[0,0,0,0,0]]] out [0] when x is [[[0,0,0,0,0],[1,1,1,1,1]]] out [1] (this case is just an example) what's the problem?