I'm trying to create my first CNN to predict apartment prices. The problem is that after 1-5 epochs loss value is stuck and doesn't decrease, only increasing a little and then decreasing again. Thanks in advance)
from keras.layers import Conv2D, MaxPool2D, Dense, BatchNormalization, Flattenfrom keras.optimizers import Adamfrom keras.models import Sequentialfrom keras.preprocessing.image import ImageDataGeneratorfrom PIL import Imageimport pandas as pdtrain_data_df = pd.read_excel('train_data_cnn.xlsx')test_data_df = pd.read_excel('test_data_cnn.xlsx')datagen = ImageDataGenerator(rescale=1./255)train_data = datagen.flow_from_dataframe(dataframe=train_data_df, x_col='filepath', y_col='price', class_mode='raw', directory=r'C:\Users\Kojimba\PycharmProjects\DeepEval\CNN', batch_size=20)test_data = datagen.flow_from_dataframe(dataframe=train_data_df, x_col='filepath', y_col='price', class_mode='raw', directory=r'C:\Users\Kojimba\PycharmProjects\DeepEval\CNN', batch_size=20)model = Sequential([ Conv2D(32, kernel_size=32, strides=(2,2), padding='same', activation='relu', input_shape=(256, 256, 3), data_format='channels_last'), #BatchNormalization(), MaxPool2D(strides=2), Conv2D(128, kernel_size=64, strides=(4,4), padding='same', activation='relu'), #BatchNormalization(), MaxPool2D(), Flatten(), Dense(8, activation='relu', kernel_initializer='random_normal', bias_initializer='zeros'), Dense(8, activation='relu', kernel_initializer='random_normal', bias_initializer='zeros'), Dense(1, activation='linear', kernel_initializer='random_normal', bias_initializer='zeros')])model.compile(Adam(lr=0.01, beta_1=0.98, beta_2=0.999), loss='mean_absolute_percentage_error')model.summary()model.fit_generator(train_data, steps_per_epoch=24, epochs=100)model.evaluate_generator(test_data)