Adding a new column to the dataset after set_format was called
Hi ! Indeed if you add a column to a formatted dataset, then the new dataset gets a new formatting in which:
```
new formatted columns = (all columns - previously unformatted columns)
```
Therefore the new column is going to be formatted using the `torch` formatting.

If you want your new column to be unformatted you can re-run this line:
```python
data.set_format("torch", columns=["some_integer_column1", "some_integer_column2"], output_all_columns=True)
``` Hi, thanks that solved my problem. Maybe mention that in the documentation.  Ok cool :) 
Also I just did a PR to mention this behavior in the documentation Closed by #1888
Hi, 

thanks for the nice library. I'm in the process of creating a custom dataset, which has a mix of tensors and lists of strings. I stumbled upon an error and want to know if its a problem on my side. 

I load some lists of strings and integers, then call `data.set_format("torch", columns=["some_integer_column1", "some_integer_column2"], output_all_columns=True)`. This converts the integer columns into tensors, but keeps the lists of strings as they are. I then call `map` to add a new column to my dataset, which is a **list of strings**. Once I iterate through my dataset, I get an error that the new column can't be converted into a tensor (which is probably caused by `set_format`). 

Below some pseudo code:
```python
    def augment_func(sample: Dict) -> Dict:
        # do something
        return {
         "some_integer_column1" : augmented_data["some_integer_column1"],  # <-- tensor
         "some_integer_column2" : augmented_data["some_integer_column2"],  # <-- tensor
         "NEW_COLUMN": targets,  # <-- list of strings
        }


    data = datasets.load_dataset(__file__, data_dir="...", split="train")
    data.set_format("torch", columns=["some_integer_column1", "some_integer_column2"], output_all_columns=True)

    augmented_dataset = data.map(augment_func, batched=False)
    
    for sample in augmented_dataset:
        print(sample)  # fails

```

and the exception:
```python
Traceback (most recent call last):
  File "dataset.py", line 487, in <module>
    main()
  File "dataset.py", line 471, in main
    for sample in augmented_dataset:
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 697, in __iter__
    yield self._getitem(
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1069, in _getitem
    outputs = self._convert_outputs(
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 890, in _convert_outputs
    v = map_nested(command, v, **map_nested_kwargs)
  File "lib/python3.8/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
    return function(data_struct)
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in command
    return [map_nested(command, i, **map_nested_kwargs) for i in x]
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in <listcomp>
    return [map_nested(command, i, **map_nested_kwargs) for i in x]
  File "lib/python3.8/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
    return function(data_struct)
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in command
    return [map_nested(command, i, **map_nested_kwargs) for i in x]
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in <listcomp>
    return [map_nested(command, i, **map_nested_kwargs) for i in x]
  File "lib/python3.8/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
    return function(data_struct)
  File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 851, in command
    return torch.tensor(x, **format_kwargs)
TypeError: new(): invalid data type 'str'
```

Thanks!
