Model can not be trained when adding more labels

So I am trying to train a model with 24 labels (letters of the alphabet) but it currently can be trained for only 15 of those, after adding more data for each letter the accuracy is stuck at 0.05. Any ideas on what might me wrong?

The neural network I am using currently:


model = tf.keras.models.Sequential([
tf.keras.layers.Dense(20, activation='relu'),
tf.keras.layers.Dense(8, activation='relu'),
tf.keras.layers.Dense(8, activation='relu'),
tf.keras.layers.Dense(NUM_CLASSES, activation='softmax')
])

model.compile(
optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy']

deeplearning labels