问为什么我的顺序模型的精度停留在0.2155？

EN

import numpy as np
import keras
import matplotlib.pyplot as plt
import random
import os
import cv2

X_train=[]
y_train=[]
size= 200

#preprocessing 
imagedir= "preprocessed"
pathdir= os.path.join("Images",imagedir)
for image_name in os.listdir("preprocessed/"):

    image_path= os.path.join("preprocessed",image_name)
    image= cv2.imread(image_path)
    X_train.append(image)
    if image_name.startswith("pen"):
        y_train.append(0)
    elif image_name.startswith("spoon"):
        y_train.append(1)
    elif image_name.startswith("ceiling_fan"):
        y_train.append(2)
    elif image_name.startswith("clock"):
        y_train.append(3)
    elif image_name.startswith("paper_airplane"):
        y_train.append(4)
    elif image_name.startswith("tomato"):
        y_train.append(5)
    elif image_name.startswith("banana"):
        y_train.append(6)
    elif image_name.startswith("leaf"):
        y_train.append(7)
    elif image_name.startswith("coin"):
        y_train.append(8)
    elif image_name.startswith("phone"):
        y_train.append(9)

    
X_train= np.array(X_train)
y_train= np.array(y_train)

X_train= X_train/255



test_size= 30

X_train= X_train[0:-test_size]
y_train= y_train[0:-test_size]

X_test= X_train[-test_size:-1]
y_test= y_train[-test_size:-1]

print(X_train.shape, X_test.shape)
print(y_train.shape, y_test.shape)

X_train_array= X_train.reshape(len(X_train), (size**2)*3)
X_test_array= X_test.reshape(len(X_test), (size**2)*3)

print(X_train_array.shape)

model = keras.Sequential([keras.layers.Dense(10, input_shape=((size**2)*3,), activation='sigmoid')])

model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics=['accuracy'])

model.fit(X_train_array, y_train, epochs=100)

y_predict_test=model.predict(X_test_array)

y_predict_test_labels=[]

for i in y_predict_test:
    y_predict_test_labels.append(np.argmax(i))

model.save("Model.h5")