我正在尝试训练一个情感分析模型，
我得到以下错误：

Training model with https://tfhub.dev/tensorflow/small_bert/bert_en_uncased_L-4_H-512_A-8/1
Epoch 1/5
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-118-21a4b57536e8> in <cell line: 2>()
      1 print(f'Training model with {tfhub_handle_encoder}')
----> 2 history = classifier_model.fit(x=train_data['clean_text'], y=train_data['sentiment'],
      3                                validation_data=val_data.empty,
      4                                epochs=epochs)

1 frames
/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py in _call(self, *args, **kwds)
    855       # In this case we have created variables on the first call, so we run the
    856       # defunned version which is guaranteed to never create variables.
--> 857       return self._no_variable_creation_fn(*args, **kwds)  # pylint: disable=not-callable
    858     elif self._variable_creation_fn is not None:
    859       # Release the lock early so that multiple threads can perform the call

TypeError: 'NoneType' object is not callable

当调用以下函数时：

print(f'Training model with {tfhub_handle_encoder}')
history = classifier_model.fit(x=train_data['clean_text'], y=train_data['sentiment'],
                               validation_data=val_data.empty,
                               epochs=epochs)

我的train_data的形状是（534，2），验证数据是（35，2）
train_data的示例如下所示：
| 纯文本|情绪|
| --|--|
| 真的很喜欢这部电影|2.0|
有人知道出了什么问题吗？似乎无法理解这个错误。奇怪的是，我还需要瓦尔_data上的.empty，否则我会得到

The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

我相信我的输入是不正确的，但我不知道为什么当我打印形状时，模型期望我得到以下结果：

(None,) <dtype: 'string'>
(None, 1) <dtype: 'float32'>
text [(None,)] string
preprocessing None float32
BERT_encoder {'input_mask': (None, 128), 'input_word_ids': (None, 128), 'input_type_ids': (None, 128)} float32
dropout_4 (None, 512) float32
classifier (None, 512) float32
[None, None, None, None, None]