`dataset.filter` ALWAYS removes the first item from the dataset when using batched=True
`filter` treats the function's output as a (selection) mask - `True` keeps the sample, and `False` drops it. In your case, `bool(0)` evaluates to `False`, so dropping the first sample is the correct behavior. Oh gosh! 🤦  I totally misunderstood the API! My apologies!
### Describe the bug

If you call batched=True when calling `filter`, the first item is _always_ filtered out, regardless of the filter condition.



### Steps to reproduce the bug

Here's a minimal example:
```python
def filter_batch_always_true(batch, indices):
    print("First index being passed into this filter function: ", indices[0])
    return indices  # Keep all indices

data = {"value": list(range(10))}
dataset = Dataset.from_dict(data)

filtered_dataset = dataset.filter(filter_batch_always_true, with_indices=True, batched=True)
print("Length of original dataset: ", len(dataset))
print("Length of filtered_dataset: ", len(filtered_dataset))
print("Is equal to original? ", len(filtered_dataset) == len(dataset))
print("First item of filtered dataset: ", filtered_dataset[0])
print("Last item of filtered dataset: ", filtered_dataset[-1])
```
prints:
```
First index being passed into this filter function:  0
Length of original dataset:  10
Length of filtered_dataset:  9
Is equal to original?  False
First item of filtered dataset:  {'value': 1}
Last item of filtered dataset:  {'value': 9}
```

### Expected behavior

Filter should respect the filter condition.

### Environment info


- `datasets` version: 2.14.4
- Platform: macOS-13.5-arm64-arm-64bit
- Python version: 3.9.18
- Huggingface_hub version: 0.17.1
- PyArrow version: 10.0.1
- Pandas version: 2.0.2
