Datasets:
license: cc
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness
tags:
- multilingual
- tokenization
configs:
- config_name: farsi_tokenizer_robustness_cannonical
data_files:
- split: test
path: farsi_tokenizer_robustness_cannonical/test-*
- config_name: farsi_tokenizer_robustness_code_language_script_switching
data_files:
- split: test
path: farsi_tokenizer_robustness_code_language_script_switching/test-*
- config_name: farsi_tokenizer_robustness_colloquial
data_files:
- split: test
path: farsi_tokenizer_robustness_colloquial/test-*
- config_name: farsi_tokenizer_robustness_diacritics_presence_absence
data_files:
- split: test
path: farsi_tokenizer_robustness_diacritics_presence_absence/test-*
- config_name: farsi_tokenizer_robustness_keyboard_proximity_errors
data_files:
- split: test
path: farsi_tokenizer_robustness_keyboard_proximity_errors/test-*
- config_name: farsi_tokenizer_robustness_romanization
data_files:
- split: test
path: farsi_tokenizer_robustness_romanization/test-*
- config_name: farsi_tokenizer_robustness_word_reordering
data_files:
- split: test
path: farsi_tokenizer_robustness_word_reordering/test-*
- config_name: farsi_tokenizer_robustness_word_spacing_zero-width_characters_extra_space
data_files:
- split: test
path: >-
farsi_tokenizer_robustness_word_spacing_zero-width_characters_extra_space/test-*
dataset_info:
- config_name: farsi_tokenizer_robustness_cannonical
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 12118
num_examples: 45
download_size: 10753
dataset_size: 12118
- config_name: farsi_tokenizer_robustness_code_language_script_switching
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 10823
num_examples: 45
download_size: 9238
dataset_size: 10823
- config_name: farsi_tokenizer_robustness_colloquial
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 9788
num_examples: 45
download_size: 9247
dataset_size: 9788
- config_name: farsi_tokenizer_robustness_diacritics_presence_absence
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 12047
num_examples: 45
download_size: 10143
dataset_size: 12047
- config_name: farsi_tokenizer_robustness_keyboard_proximity_errors
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 10835
num_examples: 45
download_size: 9474
dataset_size: 10835
- config_name: farsi_tokenizer_robustness_romanization
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 8399
num_examples: 45
download_size: 8953
dataset_size: 8399
- config_name: farsi_tokenizer_robustness_word_reordering
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 10883
num_examples: 45
download_size: 9556
dataset_size: 10883
- config_name: farsi_tokenizer_robustness_word_spacing_zero-width_characters_extra_space
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
dtype: string
- name: subcategories
dtype: string
- name: lang
dtype: string
- name: second_lang
dtype: string
- name: coding_lang
dtype: string
- name: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: float64
- name: variation_id
dtype: float64
splits:
- name: test
num_bytes: 12666
num_examples: 45
download_size: 10010
dataset_size: 12666
Dataset Card for Tokenization Robustness
A comprehensive evaluation dataset for testing robustness of different tokenization strategies.
Dataset Details
Dataset Description
This dataset evaluates how robust language models are to different tokenization strategies and edge cases. It includes text completion questions with multiple choice answers designed to test various aspects of tokenization handling.
- Curated by: R3
- Funded by [optional]: [More Information Needed]
- Shared by [optional]: [More Information Needed]
- Language(s) (NLP): [More Information Needed]
- License: cc
Dataset Sources [optional]
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
Uses
Direct Use
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Out-of-Scope Use
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Dataset Structure
The dataset contains multiple-choice questions with associated metadata about tokenization types and categories.
Dataset Creation
Curation Rationale
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Source Data
Data Collection and Processing
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Who are the source data producers?
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Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Bias, Risks, and Limitations
The dataset focuses primarily on English text and may not generalize to other languages or tokenization schemes not covered in the evaluation.
Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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