[bug] resume from ckpt skips samples if .map is applied

### Describe the bug

resume from ckpt skips samples if .map is applied

Maybe related: https://github.com/huggingface/datasets/issues/7538

### Steps to reproduce the bug

```python
from datasets import Dataset
from datasets.distributed import split_dataset_by_node

# Create dataset with map transformation
def create_dataset():
ds = Dataset.from_dict({"id": list(range(100))})
ds = ds.to_iterable_dataset(num_shards=4)
ds = ds.map(lambda x: x) #comment it out to get desired behavior
ds = split_dataset_by_node(ds, rank=0, world_size=2)
return ds

ds = create_dataset()

# Iterate and save checkpoint after 10 samples
it = iter(ds)
for idx, sample in enumerate(it):
if idx == 9: # Checkpoint after 10 samples
checkpoint = ds.state_dict()
print(f"Checkpoint saved at sample: {sample['id']}")
break

# Continue with original iterator
original_next_samples = []
for idx, sample in enumerate(it):
original_next_samples.append(sample["id"])
if idx >= 4:
break

# Resume from checkpoint
ds_new = create_dataset()
ds_new.load_state_dict(checkpoint)

# Get samples from resumed iterator
it_new = iter(ds_new)
resumed_next_samples = []
for idx, sample in enumerate(it_new):
resumed_next_samples.append(sample["id"])
if idx >= 4:
break

print(f"\nExpected next samples: {original_next_samples}")
print(f"Actual next samples: {resumed_next_samples}")
print(
f"\n❌ BUG: {resumed_next_samples[0] - original_next_samples[0]} samples were skipped!"
)

```

With map
```
Checkpoint saved at sample: 9

Expected next samples: [10, 11, 12, 13, 14]
Actual next samples: [50, 51, 52, 53, 54]

❌ BUG: 40 samples were skipped!
```

### Expected behavior

without map
```
Expected next samples: [10, 11, 12, 13, 14]
Actual next samples: [10, 11, 12, 13, 14]

❌ BUG: 0 samples were skipped!
```

### Environment info

datasets == 3.6.0