feature column용 모델만들기 오류

model= tf.keras.Sequential([
  tf.keras.layers.DenseFeatures(feature_columns),
  tf.keras.layers.Dense(128, activation='relu'),
  tf.keras.layers.Dense(64, activation='relu'),
  tf.keras.layers.Dropout(0.2),
  tf.keras.layers.Dense(1, activation='sigmoid'),
])

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['acc'])

ds_batch = ds.batch(32)

model.fit(ds_batch, shuffle=True, epochs=20)

여기에서 아래와 같은 오류 코드가 나왔습니다.

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-95-a9085c0c425c> in <cell line: 1>()
      1 model= tf.keras.Sequential([
----> 2   tf.keras.layers.DenseFeatures(feature_columns),
      3   tf.keras.layers.Dense(128, activation='relu'),
      4   tf.keras.layers.Dense(64, activation='relu'),
      5   tf.keras.layers.Dropout(0.2),

 
3 frames 
/usr/local/lib/python3.10/dist-packages/keras/feature_column/base_feature_layer.py in _normalize_feature_columns(feature_columns)
    231     for column in feature_columns:
    232         if column.name in name_to_column:
--> 233             raise ValueError(
    234                 "Duplicate feature column name found for columns: {} "
    235                 "and {}. This usually means that these columns refer to "

ValueError: Duplicate feature column name found for columns: IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(key='Sex', vocabulary_list=('male', 'female'), dtype=tf.string, default_value=-1, num_oov_buckets=0)) and IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(key='Sex', vocabulary_list=('male', 'female'), dtype=tf.string, default_value=-1, num_oov_buckets=0)). This usually means that these columns refer to same base feature. Either one must be discarded or a duplicated but renamed item must be inserted in features dict.
---------------------------------------------------------------------------
강의대로 다 잘 따라했고 틀린 철자도 없는데 왜이런건가요ㅠ

어떻게 고쳐야 하는 건가요?????