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gsaltintas/code_technical_content

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 questions with multiple choice answers designed to test various aspects of tokenization handling. Curated by: R3 Funded by [optional]: [More Information… See the full description on the dataset page: https://huggingface.co/datasets/gsaltintas/code_technical_content.

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1---2license: cc3multilinguality: multilingual4task_categories:5- multiple-choice6pretty_name: Tokenization Robustness7tags:8- multilingual9- tokenization10dataset_info:11- config_name: code_technical_content_buggy_code12  features:13  - name: question14    dtype: string15  - name: choices16    sequence: string17  - name: answer18    dtype: int6419  - name: answer_label20    dtype: string21  - name: split22    dtype: string23  - name: subcategories24    dtype: string25  - name: lang26    dtype: string27  - name: second_lang28    dtype: string29  - name: coding_lang30    dtype: string31  - name: notes32    dtype: string33  - name: id34    dtype: string35  - name: set_id36    dtype: float6437  - name: variation_id38    dtype: string39  splits:40  - name: test41    num_bytes: 763342    num_examples: 2143  download_size: 841044  dataset_size: 763345- config_name: code_technical_content_cannonical46  features:47  - name: question48    dtype: string49  - name: choices50    sequence: string51  - name: answer52    dtype: int6453  - name: answer_label54    dtype: string55  - name: split56    dtype: string57  - name: subcategories58    dtype: string59  - name: lang60    dtype: string61  - name: second_lang62    dtype: string63  - name: coding_lang64    dtype: string65  - name: notes66    dtype: string67  - name: id68    dtype: string69  - name: set_id70    dtype: float6471  - name: variation_id72    dtype: string73  splits:74  - name: test75    num_bytes: 163276    num_examples: 577  download_size: 696178  dataset_size: 163279- config_name: code_technical_content_comments_across_languages80  features:81  - name: question82    dtype: string83  - name: choices84    sequence: string85  - name: answer86    dtype: int6487  - name: answer_label88    dtype: string89  - name: split90    dtype: string91  - name: subcategories92    dtype: string93  - name: lang94    dtype: string95  - name: second_lang96    dtype: string97  - name: coding_lang98    dtype: string99  - name: notes100    dtype: string101  - name: id102    dtype: string103  - name: set_id104    dtype: float64105  - name: variation_id106    dtype: string107  splits:108  - name: test109    num_bytes: 6024110    num_examples: 15111  download_size: 7966112  dataset_size: 6024113- config_name: code_technical_content_string_literals114  features:115  - name: question116    dtype: string117  - name: choices118    sequence: string119  - name: answer120    dtype: int64121  - name: answer_label122    dtype: string123  - name: split124    dtype: string125  - name: subcategories126    dtype: string127  - name: lang128    dtype: string129  - name: second_lang130    dtype: string131  - name: coding_lang132    dtype: string133  - name: notes134    dtype: string135  - name: id136    dtype: string137  - name: set_id138    dtype: float64139  - name: variation_id140    dtype: string141  splits:142  - name: test143    num_bytes: 3557144    num_examples: 10145  download_size: 6997146  dataset_size: 3557147- config_name: code_technical_content_syntax_and_punctuation_variations148  features:149  - name: question150    dtype: string151  - name: choices152    sequence: string153  - name: answer154    dtype: int64155  - name: answer_label156    dtype: string157  - name: split158    dtype: string159  - name: subcategories160    dtype: string161  - name: lang162    dtype: string163  - name: second_lang164    dtype: string165  - name: coding_lang166    dtype: string167  - name: notes168    dtype: string169  - name: id170    dtype: string171  - name: set_id172    dtype: float64173  - name: variation_id174    dtype: string175  splits:176  - name: test177    num_bytes: 5475178    num_examples: 16179  download_size: 7298180  dataset_size: 5475181- config_name: code_technical_content_variable_naming_conventions182  features:183  - name: question184    dtype: string185  - name: choices186    sequence: string187  - name: answer188    dtype: int64189  - name: answer_label190    dtype: string191  - name: split192    dtype: string193  - name: subcategories194    dtype: string195  - name: lang196    dtype: string197  - name: second_lang198    dtype: string199  - name: coding_lang200    dtype: string201  - name: notes202    dtype: string203  - name: id204    dtype: string205  - name: set_id206    dtype: float64207  - name: variation_id208    dtype: string209  splits:210  - name: test211    num_bytes: 5087212    num_examples: 12213  download_size: 7702214  dataset_size: 5087215- config_name: code_technical_content_whitespace_variations216  features:217  - name: question218    dtype: string219  - name: choices220    sequence: string221  - name: answer222    dtype: int64223  - name: answer_label224    dtype: string225  - name: split226    dtype: string227  - name: subcategories228    dtype: string229  - name: lang230    dtype: string231  - name: second_lang232    dtype: string233  - name: coding_lang234    dtype: string235  - name: notes236    dtype: string237  - name: id238    dtype: string239  - name: set_id240    dtype: float64241  - name: variation_id242    dtype: string243  splits:244  - name: test245    num_bytes: 5053246    num_examples: 15247  download_size: 7544248  dataset_size: 5053249configs:250- config_name: code_technical_content_buggy_code251  data_files:252  - split: test253    path: code_technical_content_buggy_code/test-*254- config_name: code_technical_content_cannonical255  data_files:256  - split: test257    path: code_technical_content_cannonical/test-*258- config_name: code_technical_content_comments_across_languages259  data_files:260  - split: test261    path: code_technical_content_comments_across_languages/test-*262- config_name: code_technical_content_string_literals263  data_files:264  - split: test265    path: code_technical_content_string_literals/test-*266- config_name: code_technical_content_syntax_and_punctuation_variations267  data_files:268  - split: test269    path: code_technical_content_syntax_and_punctuation_variations/test-*270- config_name: code_technical_content_variable_naming_conventions271  data_files:272  - split: test273    path: code_technical_content_variable_naming_conventions/test-*274- config_name: code_technical_content_whitespace_variations275  data_files:276  - split: test277    path: code_technical_content_whitespace_variations/test-*278---279 280# Dataset Card for Tokenization Robustness281 282<!-- Provide a quick summary of the dataset. -->283 284A comprehensive evaluation dataset for testing robustness of different tokenization strategies.285 286## Dataset Details287 288### Dataset Description289 290<!-- Provide a longer summary of what this dataset is. -->291 292This dataset evaluates how robust language models are to different tokenization strategies and edge cases. It includes questions with multiple choice answers designed to test various aspects of tokenization handling.293 294- **Curated by:** R3295- **Funded by [optional]:** [More Information Needed]296- **Shared by [optional]:** [More Information Needed]297- **Language(s) (NLP):** [More Information Needed]298- **License:** cc299 300### Dataset Sources [optional]301 302<!-- Provide the basic links for the dataset. -->303 304- **Repository:** [More Information Needed]305- **Paper [optional]:** [More Information Needed]306- **Demo [optional]:** [More Information Needed]307 308## Uses309 310<!-- Address questions around how the dataset is intended to be used. -->311 312### Direct Use313 314<!-- This section describes suitable use cases for the dataset. -->315 316[More Information Needed]317 318### Out-of-Scope Use319 320<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->321 322[More Information Needed]323 324## Dataset Structure325 326<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->327 328The dataset contains multiple-choice questions with associated metadata about tokenization types and categories.329 330## Dataset Creation331 332### Curation Rationale333 334<!-- Motivation for the creation of this dataset. -->335 336[More Information Needed]337 338### Source Data339 340<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->341 342#### Data Collection and Processing343 344<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->345 346[More Information Needed]347 348#### Who are the source data producers?349 350<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->351 352[More Information Needed]353 354### Annotations [optional]355 356<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->357 358#### Annotation process359 360<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->361 362[More Information Needed]363 364#### Who are the annotators?365 366<!-- This section describes the people or systems who created the annotations. -->367 368[More Information Needed]369 370#### Personal and Sensitive Information371 372<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->373 374[More Information Needed]375 376## Bias, Risks, and Limitations377 378<!-- This section is meant to convey both technical and sociotechnical limitations. -->379 380The dataset focuses primarily on English text and may not generalize to other languages or tokenization schemes not covered in the evaluation.381 382### Recommendations383 384<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->385 386Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.387 388## Citation [optional]389 390<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->391 392**BibTeX:**393 394[More Information Needed]395 396**APA:**397 398[More Information Needed]399 400## Glossary [optional]401 402<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->403 404[More Information Needed]405 406## More Information [optional]407 408[More Information Needed]409 410## Dataset Card Authors [optional]411 412[More Information Needed]413 414## Dataset Card Contact415 416[More Information Needed]