Tokenizer offset_mapping problem
## Task info
Hi,
I'm trying to use the tokenizer model to create sliding windows for my `ner` task.
I have seen that the tokenizers can do this, setting the `return_overflowing_tokens=True` parameter when i call them to tokenize text. I also need the token spans, that can be taken from `BatchEncoding` tokenizer ouput, setting `return_offsets_mapping=True` parameter in the tokenizer call.

## Environment info
I am running my script on Google Colab

```
- `transformers` version: 4.16.2
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyTorch version (GPU?): 1.10.0+cu111 (False)
- Tensorflow version (GPU?): 2.8.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
```

## Information

I am using these three italian tokenizers:

1. `idb-ita/gilberto-uncased-from-camembert`
2. `Musixmatch/umberto-commoncrawl-cased-v1`
3. `Musixmatch/umberto-wikipedia-uncased-v1`

The problem is that for the first two tokenizer, in the token spans `[(start, end),...,(start,end)]` returned, the start index of the first token of a word (except for the first word of text) is the index of the whitespace character. 

## To reproduce

Steps to reproduce the behavior:

1. `idb-ita/gilberto-uncased-from-camembert`
```
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("idb-ita/gilberto-uncased-from-camembert")
text = "L'Italia, ufficialmente Repubblica Italiana, è uno Stato situato nell'Europa centro-meridionale, il cui territorio coincide in gran parte con l'omonima regione geografica." #(source: https://it.wikipedia.org/wiki/Italia)
tokenized_text = tokenizer(text.lower(), stride=10, max_length=20, truncation=True, return_overflowing_tokens=True, return_offsets_mapping=True)
print(tokenized_text["offset_mapping"][0])
print(tokenizer.convert_ids_to_tokens(tokenized_text["input_ids"][0]))
```

Output
```
[(0, 0), (0, 1), (1, 2), (2, 8), (8, 9), (9, 23), (23, 34), (34, 43), (43, 44), (44, 46), (46, 50), (50, 56), (56, 64), (64, 69), (69, 70), (70, 76), (76, 83), (83, 84), (84, 88), (0, 0)]
['<s>', '▁l', "'", 'italia', ',', '▁ufficialmente', '▁repubblica', '▁italiana', ',', '▁è', '▁uno', '▁stato', '▁situato', '▁nell', "'", 'europa', '▁centro', '-', 'meri', '</s>']
```

2. `Musixmatch/umberto-commoncrawl-cased-v1`
```
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("Musixmatch/umberto-commoncrawl-cased-v1")
text = "L'Italia, ufficialmente Repubblica Italiana, è uno Stato situato nell'Europa centro-meridionale, il cui territorio coincide in gran parte con l'omonima regione geografica." #(source: https://it.wikipedia.org/wiki/Italia)
tokenized_text = tokenizer(text, stride=10, max_length=20, truncation=True, return_overflowing_tokens=True, return_offsets_mapping=True)
print(tokenized_text["offset_mapping"][0])
print(tokenizer.convert_ids_to_tokens(tokenized_text["input_ids"][0]))
```

Output
```
[(0, 0), (0, 1), (1, 2), (2, 8), (8, 9), (9, 23), (23, 34), (34, 43), (43, 44), (44, 46), (46, 50), (50, 56), (56, 64), (64, 69), (69, 70), (70, 76), (76, 83), (83, 84), (84, 88), (0, 0)]
['<s>', '▁L', "'", 'Italia', ',', '▁ufficialmente', '▁Repubblica', '▁Italiana', ',', '▁è', '▁uno', '▁Stato', '▁situato', '▁nell', "'", 'Europa', '▁centro', '-', 'meri', '</s>']
```
If we take the sixth token "_ufficialmente", in both cases, its corresponding span is (9,23) and not (10,23).


## Expected behavior

The start index span of the first token of a word should start from the index of the first character of token and not from index of the whitespace character.
The third tokenizer `Musixmatch/umberto-wikipedia-uncased-v1` do it correctly.

```
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("Musixmatch/umberto-wikipedia-uncased-v1")
text = "L'Italia, ufficialmente Repubblica Italiana, è uno Stato situato nell'Europa centro-meridionale, il cui territorio coincide in gran parte con l'omonima regione geografica." #(source: https://it.wikipedia.org/wiki/Italia)
tokenized_text = tokenizer(text.lower(), stride=10, max_length=20, truncation=True, return_overflowing_tokens=True, return_offsets_mapping=True)
print(tokenized_text["offset_mapping"][0])
print(tokenizer.convert_ids_to_tokens(tokenized_text["input_ids"][0]))
```

Output
```
[(0, 0), (0, 1), (1, 2), (2, 3), (3, 8), (8, 9), (10, 23), (24, 34), (35, 43), (43, 44), (45, 46), (47, 50), (51, 56), (57, 64), (65, 69), (69, 70), (70, 74), (74, 76), (77, 83), (0, 0)]
['<s>', '▁l', "'", 'i', 'talia', ',', '▁ufficialmente', '▁repubblica', '▁italiana', ',', '▁è', '▁uno', '▁stato', '▁situato', '▁nell', "'", 'euro', 'pa', '▁centro', '</s>']
```
If we take the sixth token "_ufficialmente", its corresponding span is (10,23).
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