model2.py

model2 = Sequential([
    Dense(512, activation='tanh', input_shape = X_train[0].shape, kernel_regularizer='l1'), #Only change is here where we add kernel_regularizer
    Dense(512//2, activation='tanh'),
    Dense(512//4, activation='tanh'),
    Dense(512//8, activation='tanh'),
    Dense(32, activation='relu'),
    Dense(3, activation='softmax')
])

model2.compile(optimizer='sgd',loss='categorical_crossentropy', metrics=['acc', 'mse'])
hist2 = model2.fit(X_train, y_train, epochs=350, batch_size=128, validation_data=(X_test,y_test))