 Bug: LayoutLMv3 finetuning on FUNSD Notebook; Arrow Error
Very strange: `datasets-cli env`
> 
> Copy-and-paste the text below in your GitHub issue.
> 
> - `datasets` version: 2.9.0
> - Platform: macOS-14.0-arm64-arm-64bit
> - Python version: 3.9.13
> - PyArrow version: 8.0.0
> - Pandas version: 1.3.5

After updating datasets and pyarrow on base environment, although I am using a different one called layoutLM

> Copy-and-paste the text below in your GitHub issue.
> 
> - `datasets` version: 2.14.6
> - Platform: macOS-14.0-arm64-arm-64bit
> - Python version: 3.9.18
> - Huggingface_hub version: 0.17.3
> - PyArrow version: 14.0.1
> - Pandas version: 2.1.3 Hi! The latest (patch) release (published a few hours ago) includes a fix for this [PyArrow security issue](https://github.com/advisories/GHSA-5wvp-7f3h-6wmm). To install it, run `pip install -U datasets`. > Hi! The latest (patch) release (published a few hours ago) includes a fix for this [PyArrow security issue](https://github.com/advisories/GHSA-5wvp-7f3h-6wmm). To install it, run `pip install -U datasets`.

Thanks for the info and the latest release, it seems this has also solved my issue. First run after the update worked and I am training right now :D
Will close the Issu
### Describe the bug

Arrow issues when running the example Notebook laptop locally on Mac with M1. Works on Google Collab.

**Notebook**: https://github.com/NielsRogge/Transformers-Tutorials/blob/master/LayoutLMv3/Fine_tune_LayoutLMv3_on_FUNSD_(HuggingFace_Trainer).ipynb

**Error**: `ValueError: Arrow type extension<arrow.py_extension_type<pyarrow.lib.UnknownExtensionType>> does not have a datasets dtype equivalent.`

**Caused by**:

```
# we need to define custom features for `set_format` (used later on) to work properly
features = Features({
    'pixel_values': Array3D(dtype="float32", shape=(3, 224, 224)),
    'input_ids': Sequence(feature=Value(dtype='int64')),
    'attention_mask': Sequence(Value(dtype='int64')),
    'bbox': Array2D(dtype="int64", shape=(512, 4)),
    'labels': Sequence(feature=Value(dtype='int64')),
})
```

### Steps to reproduce the bug

Run the notebook provided, locally. If possible also on M1.

### Expected behavior

The cell where features are mapped to Array2D and Array3D should work without any issues.

### Environment info

Tried with Python 3.9 and 3.10 conda envs. Running Mac M1.

`pip show datasets`

> Name: datasets
Version: 2.14.6
Summary: HuggingFace community-driven open-source library of datasets

`pip list`

> Package                   Version
> ------------------------- ------------
> accelerate                0.24.1
> aiohttp                   3.8.6
> aiosignal                 1.3.1
> anyio                     3.5.0
> appnope                   0.1.2
> argon2-cffi               21.3.0
> argon2-cffi-bindings      21.2.0
> asttokens                 2.0.5
> async-timeout             4.0.3
> attrs                     23.1.0
> backcall                  0.2.0
> beautifulsoup4            4.12.2
> bleach                    4.1.0
> certifi                   2023.7.22
> cffi                      1.15.1
> charset-normalizer        3.3.2
> comm                      0.1.2
> datasets                  2.14.6
> debugpy                   1.6.7
> decorator                 5.1.1
> defusedxml                0.7.1
> dill                      0.3.7
> entrypoints               0.4
> exceptiongroup            1.0.4
> executing                 0.8.3
> fastjsonschema            2.16.2
> filelock                  3.13.1
> frozenlist                1.4.0
> fsspec                    2023.10.0
> huggingface-hub           0.17.3
> idna                      3.4
> importlib-metadata        6.0.0
> IProgress                 0.4
> ipykernel                 6.25.0
> ipython                   8.15.0
> ipython-genutils          0.2.0
> jedi                      0.18.1
> Jinja2                    3.1.2
> joblib                    1.3.2
> jsonschema                4.19.2
> jsonschema-specifications 2023.7.1
> jupyter_client            7.4.9
> jupyter_core              5.5.0
> jupyter-server            1.23.4
> jupyterlab-pygments       0.1.2
> MarkupSafe                2.1.1
> matplotlib-inline         0.1.6
> mistune                   2.0.4
> mpmath                    1.3.0
> multidict                 6.0.4
> multiprocess              0.70.15
> nbclassic                 1.0.0
> nbclient                  0.8.0
> nbconvert                 7.10.0
> nbformat                  5.9.2
> nest-asyncio              1.5.6
> networkx                  3.2.1
> notebook                  6.5.4
> notebook_shim             0.2.3
> numpy                     1.26.1
> packaging                 23.1
> pandas                    2.1.3
> pandocfilters             1.5.0
> parso                     0.8.3
> pexpect                   4.8.0
> pickleshare               0.7.5
> Pillow                    10.1.0
> pip                       23.3
> platformdirs              3.10.0
> prometheus-client         0.14.1
> prompt-toolkit            3.0.36
> psutil                    5.9.0
> ptyprocess                0.7.0
> pure-eval                 0.2.2
> pyarrow                   14.0.1
> pycparser                 2.21
> Pygments                  2.15.1
> python-dateutil           2.8.2
> pytz                      2023.3.post1
> PyYAML                    6.0.1
> pyzmq                     23.2.0
> referencing               0.30.2
> regex                     2023.10.3
> requests                  2.31.0
> rpds-py                   0.10.6
> safetensors               0.4.0
> scikit-learn              1.3.2
> scipy                     1.11.3
> Send2Trash                1.8.2
> seqeval                   1.2.2
> setuptools                68.0.0
> six                       1.16.0
> sniffio                   1.2.0
> soupsieve                 2.5
> stack-data                0.2.0
> sympy                     1.12
> terminado                 0.17.1
> threadpoolctl             3.2.0
> tinycss2                  1.2.1
> tokenizers                0.14.1
> torch                     2.1.0
> tornado                   6.3.3
> tqdm                      4.66.1
> traitlets                 5.7.1
> transformers              4.36.0.dev0
> typing_extensions         4.7.1
> tzdata                    2023.3
> urllib3                   2.0.7
> wcwidth                   0.2.5
> webencodings              0.5.1
> websocket-client          0.58.0
> wheel                     0.41.2
> xxhash                    3.4.1
> yarl                      1.9.2
> zipp                      3.11.0