keras predicts nan values

I implemented a Keras model for my all-integer dataset with values greater than or equal to 0. The train data has dimensions of (393, 108) and prediction data has (1821, 108). Code is as follows.

import keras    
from keras.models import Sequential    
from keras.layers import Dense

X = data.iloc[:, :-1]
y = data.iloc[:, -1]

model = Sequential()
model.add(Dense(X.shape[1]-1, input_dim=X.shape[1], activation='tanh'))

for i in range(X.shape[1] - 2, 2, -100):
    model.add(Dense(i, activation='tanh'))

model.add(Dense(1, activation='tanh'))

opt = keras.optimizers.Adam(learning_rate=100)
model.compile(loss='categorical_crossentropy', optimizer=opt)
model.fit(X, y)
model.predict(X0)

I am getting all nan values as results.

array([[nan],
       [nan],
       [nan],
       ...,
       [nan],
       [nan],
       [nan]], dtype=float32)