model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
model = Model(inputs=base_model.input, outputs=predictions)
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
# Assuming you've collected and preprocessed your data train_dir = 'path/to/train' validation_dir = 'path/to/validation'
validation_generator = validation_datagen.flow_from_directory(validation_dir, target_size=(224, 224), batch_size=32, class_mode='categorical')
validation_datagen = ImageDataGenerator(rescale=1./255)