Bug: Type Mismatch in Dataset Mapping

# 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'}

{'text': 'world', 'label': '1'}

{'text': 'this', 'label': '0'}

{'text': 'is', 'label': '1'}

{'text': 'a', 'label': '1'}

{'text': 'test', 'label': '0'}

```

## Actual Output
The actual output still shows the `label` field values as integers:

```plaintext
{'text': 'Hello', 'label': 0}

{'text': 'world', 'label': 1}

{'text': 'this', 'label': 0}

{'text': 'is', 'label': 1}

{'text': 'a', 'label': 1}

{'text': 'test', 'label': 0}

```

## 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. 🤗