from keras.layers import Conv2D,Dropout,Dense,Flatten
from keras.models import Sequential


model = Sequential([
	Flatten(input_shape=(96,96)),
	Dense(128, activation="relu"),
	Dropout(0.1),
	Dense(64, activation="relu"),
	Dense(30)
])

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

model.fit(X_train,y_train,epochs = 500,batch_size = 128,validation_split = 0.2)