README.md

---
language:
- af
- ar
- bg
- ca
- cs
- da
- de
- el
- en
- es
- et
- eu
- fa
- fi
- fr
- ga
- he
- hi
- hr
- hu
- hy
- id
- it
- ja
- ko
- lt
- lv
- mr
- nl
- 'no'
- pl
- pt
- ro
- ru
- sa
- sk
- sl
- sr
- sv
- ta
- te
- tr
- uk
- ur
- vi
license: mit
pretty_name: Multilingual Tokenizer Wikipedia Benchmark
dataset_info:
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- config_name: ar
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- config_name: ca
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- config_name: de
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- config_name: el
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    dtype: string
  - name: text
    dtype: string
  - name: split_text
    sequence: string
  splits:
  - name: train
    num_bytes: 7820979602
    num_examples: 1384748
  - name: clean
    num_bytes: 7781957954.689285
    num_examples: 1377839
  download_size: 6540517932
  dataset_size: 15602937556.689285
configs:
- config_name: af
  data_files:
  - split: train
    path: af/train-*
  - split: clean
    path: af/clean-*
- config_name: ar
  data_files:
  - split: train
    path: ar/train-*
  - split: clean
    path: ar/clean-*
- config_name: bg
  data_files:
  - split: train
    path: bg/train-*
  - split: clean
    path: bg/clean-*
- config_name: ca
  data_files:
  - split: train
    path: ca/train-*
  - split: clean
    path: ca/clean-*
- config_name: cs
  data_files:
  - split: train
    path: cs/train-*
  - split: clean
    path: cs/clean-*
- config_name: da
  data_files:
  - split: train
    path: da/train-*
  - split: clean
    path: da/clean-*
- config_name: de
  data_files:
  - split: train
    path: de/train-*
  - split: clean
    path: de/clean-*
- config_name: el
  data_files:
  - split: train
    path: el/train-*
  - split: clean
    path: el/clean-*
- config_name: en
  data_files:
  - split: train
    path: en/train-*
  - split: clean
    path: en/clean-*
- config_name: es
  data_files:
  - split: train
    path: es/train-*
  - split: clean
    path: es/clean-*
- config_name: et
  data_files:
  - split: train
    path: et/train-*
  - split: clean
    path: et/clean-*
- config_name: eu
  data_files:
  - split: train
    path: eu/train-*
  - split: clean
    path: eu/clean-*
- config_name: fa
  data_files:
  - split: train
    path: fa/train-*
  - split: clean
    path: fa/clean-*
- config_name: fi
  data_files:
  - split: train
    path: fi/train-*
  - split: clean
    path: fi/clean-*
- config_name: fr
  data_files:
  - split: train
    path: fr/train-*
  - split: clean
    path: fr/clean-*
- config_name: ga
  data_files:
  - split: train
    path: ga/train-*
  - split: clean
    path: ga/clean-*
- config_name: he
  data_files:
  - split: train
    path: he/train-*
  - split: clean
    path: he/clean-*
- config_name: hi
  data_files:
  - split: train
    path: hi/train-*
  - split: clean
    path: hi/clean-*
- config_name: hr
  data_files:
  - split: train
    path: hr/train-*
  - split: clean
    path: hr/clean-*
- config_name: hu
  data_files:
  - split: train
    path: hu/train-*
  - split: clean
    path: hu/clean-*
- config_name: hy
  data_files:
  - split: train
    path: hy/train-*
  - split: clean
    path: hy/clean-*
- config_name: id
  data_files:
  - split: train
    path: id/train-*
  - split: clean
    path: id/clean-*
- config_name: it
  data_files:
  - split: train
    path: it/train-*
  - split: clean
    path: it/clean-*
- config_name: ja
  data_files:
  - split: train
    path: ja/train-*
  - split: clean
    path: ja/clean-*
- config_name: ko
  data_files:
  - split: train
    path: ko/train-*
  - split: clean
    path: ko/clean-*
- config_name: lt
  data_files:
  - split: train
    path: lt/train-*
  - split: clean
    path: lt/clean-*
- config_name: lv
  data_files:
  - split: train
    path: lv/train-*
  - split: clean
    path: lv/clean-*
- config_name: mr
  data_files:
  - split: train
    path: mr/train-*
  - split: clean
    path: mr/clean-*
- config_name: nl
  data_files:
  - split: train
    path: nl/train-*
  - split: clean
    path: nl/clean-*
- config_name: 'no'
  data_files:
  - split: train
    path: no/train-*
  - split: clean
    path: no/clean-*
- config_name: pl
  data_files:
  - split: train
    path: pl/train-*
  - split: clean
    path: pl/clean-*
- config_name: pt
  data_files:
  - split: train
    path: pt/train-*
  - split: clean
    path: pt/clean-*
- config_name: ro
  data_files:
  - split: train
    path: ro/train-*
  - split: clean
    path: ro/clean-*
- config_name: ru
  data_files:
  - split: train
    path: ru/train-*
  - split: clean
    path: ru/clean-*
- config_name: sa
  data_files:
  - split: train
    path: sa/train-*
  - split: clean
    path: sa/clean-*
- config_name: sk
  data_files:
  - split: train
    path: sk/train-*
  - split: clean
    path: sk/clean-*
- config_name: sl
  data_files:
  - split: train
    path: sl/train-*
  - split: clean
    path: sl/clean-*
- config_name: sr
  data_files:
  - split: train
    path: sr/train-*
  - split: clean
    path: sr/clean-*
- config_name: sv
  data_files:
  - split: train
    path: sv/train-*
  - split: clean
    path: sv/clean-*
- config_name: ta
  data_files:
  - split: train
    path: ta/train-*
  - split: clean
    path: ta/clean-*
- config_name: te
  data_files:
  - split: train
    path: te/train-*
  - split: clean
    path: te/clean-*
- config_name: tr
  data_files:
  - split: train
    path: tr/train-*
  - split: clean
    path: tr/clean-*
- config_name: uk
  data_files:
  - split: train
    path: uk/train-*
  - split: clean
    path: uk/clean-*
- config_name: ur
  data_files:
  - split: train
    path: ur/train-*
  - split: clean
    path: ur/clean-*
- config_name: vi
  data_files:
  - split: train
    path: vi/train-*
  - split: clean
    path: vi/clean-*
- config_name: zh
  data_files:
  - split: train
    path: zh/train-*
  - split: clean
    path: zh/clean-*
---

# Multilingual Tokenizer Benchmark 

This dataset includes pre-processed wikipedia data for tokenizer evaluation in [45 languages](https://huggingface.co/datasets/occiglot/tokenizer-wiki-bench/blob/main/README.md#supported-languages). We provide more information on the evaluation task in general [this blogpost](https://occiglot.github.io/occiglot/posts/eu_tokenizer_perfomance/).

## Usage
The dataset allows us to easily calculate *tokenizer fertility* and the *proportion of continued words* on any of the supported languages. In the example below we take the Mistral tokenizer and evaluate its performance on Slovak. 

```python 
from transformers import AutoTokenizer
from datasets import load_dataset
import numpy as np

def calculate_metrics(tokens):
    tmp = np.array([len(y) for y in tokens])
    return {'fertility': np.mean(tmp), 'cont_prop': np.count_nonzero(tmp > 1) / tmp.shape[0]}

tokenizer_name = 'mistralai/Mistral-7B-v0.1'
language = 'sk' #Slovak
tokenizer = AutoTokenizer.from_pretrained(tokenizer_name)
ds = load_dataset('occiglot/tokenizer-wiki-bench', name=language, split='clean')

remove_columns = list(set(ds.column_names) - set(["text"]))
ds = ds.map(lambda x: {'tokens': tokenizer(x['split_text'], add_special_tokens=False)['input_ids']} ,num_proc=256, remove_columns=remove_columns, batched=False)
remove_columns = None#list(set(ds.column_names))
ds = ds.map(lambda x: calculate_metrics(x['tokens']), num_proc=256, remove_columns=remove_columns,  batched=False)
df = ds.to_pandas()

print('Fertility: ', df.fertility.mean())
print('Prop. continued words:', df.cont_prop.mean())
```

## Dataset Creation

We loosely follow the approach of [Rust _et al.](https://arxiv.org/abs/2012.15613) using the fast [UDPipe](https://ufal.mff.cuni.cz/udpipe) to pre-split documents into words and subsequently run the tokenizer over isolated words. For all languages we use the respective November 2023 snapshot from [Wikipedia](wikimedia/wikipedia). Since Wikipedia, by nature, contains significantly more numbers and dates than other text and most tokenizers split those into single digits, we filtered all lone-standing numbers from the documents. Additionally, we removed any documents that still contained non-parsed HTML code (less than 1%). 

## Licensing 

We release our curated benchmark and any associated code under [MIT](https://opensource.org/license/mit) license. However, depending on your use case, the licensing conditions of the original [Wikipedia data](https://huggingface.co/datasets/wikimedia/wikipedia#licensing-information) and [UDPipe](https://github.com/ufal/udpipe/tree/udpipe-2?tab=License-1-ov-file) may apply.

## Supported Languages
This dataset currently contains pre-processed data for the following languages:

| Language   | Code   |
|:-----------|:-------|
| Afrikaans  | af     |
| Arabic     | ar     |
| Armenian   | hy     |
| Basque     | eu     |
| Bulgarian  | bg     |
| Catalan    | ca     |
| Croatian   | hr     |
| Czech      | cs     |
| Danish     | da     |
| Dutch      | nl     |
| English    | en     |
| Estonian   | et     |
| Finnish    | fi     |
| French     | fr     |
| German     | de     |
| Greek      | el     |
| Hebrew     | he     |
| Hindi      | hi     |
| Hungarian  | hu     |
| Indonesian | id     |
| Irish      | ga     |
| Italian    | it     |
| Japanese   | ja     |
| Korean     | ko     |
| Latvian    | lv     |
| Lithuanian | lt     |
| Marathi    | mr     |
| Norwegian  | no     |
| Persian    | fa     |
| Polish     | pl     |
| Portuguese | pt     |
| Romanian   | ro     |
| Russian    | ru     |
| Sanskrit   | sa     |
| Serbian    | sr     |
| Slovak     | sk     |
| Slovenian  | sl     |
| Spanish    | es     |
| Swedish    | sv     |
| Tamil      | ta     |
| Telugu     | te     |
| Turkish    | tr     |
| Ukrainian  | uk     |
| Urdu       | ur     |
| Vietnamese | vi     |