How do i get the loss function graph?

I used Mini-batch gradient descent to train the model, but i am unable to get the proper loss graph. The loss graph is always showed as a straight line. I know there is something wrong but would anyone be able to guide me

from sklearn import metrics

error = []

for epoch in range(epochs):
    for i in range(0,x_train.shape[0],minibatch_size):
        x_mini = x_train[i:i + minibatch_size-1,:]
        y_mini = y_train[i:i + minibatch_size-1,:]
        
        #feed forward
        #layer 1
        in1 = x_mini@w1 + b1
        out1 = sigmoid(in1)
        
        #layer 2
        in2 = out1@w2+b2
        out2 = sigmoid(in2)
        
    if epoch  10:
        error.append(0.5*np.power((y_mini-out2),2).mean())
    
  
z=np.arange(len(error))
plt.plot(z,error,label=train,color='red')
plt.legend(loc='best')
plt.show())

I wanted the graph for loss before training and after but cant seen get a proper one