text: Title: Bug: Type Mismatch in Dataset Mapping
  Body: # Issue: Type Mismatch in Dataset Mapping
  
  ## Description
  There is an issue with the `map` function in the `datasets` library where the mapped output does not reflect the expected type change. After applying a mapping function to convert an integer label to a string, the resulting type remains an integer instead of a string.
  
  ## Reproduction Code
  Below is a Python script that demonstrates the problem:
  
  ```python
  from datasets import Dataset
  
  # Original data
  data = {
      'text': ['Hello', 'world', 'this', 'is', 'a', 'test'],
      'label': [0, 1, 0, 1, 1, 0]
  }
  
  # Creating a Dataset object
  dataset = Dataset.from_dict(data)
  
  # Mapping function to convert label to string
  def add_one(example):
      example['label'] = str(example['label'])
      return example
  
  # Applying the mapping function
  dataset = dataset.map(add_one)
  
  # Iterating over the dataset to show results
  for item in dataset:
      print(item)
      print(type(item['label']))
  ```
  
  ## Expected Output
  After applying the mapping function, the expected output should have the `label` field as strings:
  
  ```plaintext
  {'text': 'Hello', 'label': '0'}
  <class 'str'>
  {'text': 'world', 'label': '1'}
  <class 'str'>
  {'text': 'this', 'label': '0'}
  <class 'str'>
  {'text': 'is', 'label': '1'}
  <class 'str'>
  {'text': 'a', 'label': '1'}
  <class 'str'>
  {'text': 'test', 'label': '0'}
  <class 'str'>
  ```
  
  ## Actual Output
  The actual output still shows the `label` field values as integers:
  
  ```plaintext
  {'text': 'Hello', 'label': 0}
  <class 'int'>
  {'text': 'world', 'label': 1}
  <class 'int'>
  {'text': 'this', 'label': 0}
  <class 'int'>
  {'text': 'is', 'label': 1}
  <class 'int'>
  {'text': 'a', 'label': 1}
  <class 'int'>
  {'text': 'test', 'label': 0}
  <class 'int'>
  ```
  
  ## Why necessary
  In the case of Image process we often need to convert PIL to tensor with same column name.
  
  Thank for every dev who review this issue. 🤗