--- dataset_info: - config_name: ar features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 328741 num_examples: 500 download_size: 180904 dataset_size: 328741 - config_name: cs features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 258801 num_examples: 500 download_size: 167464 dataset_size: 258801 - config_name: de features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 276977 num_examples: 500 download_size: 168274 dataset_size: 276977 - config_name: el features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 411090 num_examples: 500 download_size: 206309 dataset_size: 411090 - config_name: en features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 249691 num_examples: 500 download_size: 153792 dataset_size: 249691 - config_name: es features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 274711 num_examples: 500 download_size: 164787 dataset_size: 274711 - config_name: fa features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 342307 num_examples: 500 download_size: 185158 dataset_size: 342307 - config_name: fr features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 287086 num_examples: 500 download_size: 169277 dataset_size: 287086 - config_name: he features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 298857 num_examples: 500 download_size: 169675 dataset_size: 298857 - config_name: hi features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 486279 num_examples: 500 download_size: 201807 dataset_size: 486279 - config_name: id features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 263904 num_examples: 500 download_size: 154093 dataset_size: 263904 - config_name: it features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 269604 num_examples: 500 download_size: 163385 dataset_size: 269604 - config_name: ja features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 300804 num_examples: 500 download_size: 170374 dataset_size: 300804 - config_name: ko features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 278795 num_examples: 500 download_size: 164632 dataset_size: 278795 - config_name: nl features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 265040 num_examples: 500 download_size: 162369 dataset_size: 265040 - config_name: pl features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 266885 num_examples: 500 download_size: 169967 dataset_size: 266885 - config_name: pt features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 266432 num_examples: 500 download_size: 161594 dataset_size: 266432 - config_name: ro features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 271404 num_examples: 500 download_size: 166961 dataset_size: 271404 - config_name: ru features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 388651 num_examples: 500 download_size: 196336 dataset_size: 388651 - config_name: tr features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 269018 num_examples: 500 download_size: 163415 dataset_size: 269018 - config_name: uk features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 374668 num_examples: 500 download_size: 205287 dataset_size: 374668 - config_name: vi features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 304066 num_examples: 500 download_size: 166624 dataset_size: 304066 - config_name: zh features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: prompt dtype: string splits: - name: test num_bytes: 229345 num_examples: 500 download_size: 149115 dataset_size: 229345 configs: - config_name: ar data_files: - split: test path: ar/test-* - config_name: cs data_files: - split: test path: cs/test-* - config_name: de data_files: - split: test path: de/test-* - config_name: el data_files: - split: test path: el/test-* - config_name: en data_files: - split: test path: en/test-* - config_name: es data_files: - split: test path: es/test-* - config_name: fa data_files: - split: test path: fa/test-* - config_name: fr data_files: - split: test path: fr/test-* - config_name: he data_files: - split: test path: he/test-* - config_name: hi data_files: - split: test path: hi/test-* - config_name: id data_files: - split: test path: id/test-* - config_name: it data_files: - split: test path: it/test-* - config_name: ja data_files: - split: test path: ja/test-* - config_name: ko data_files: - split: test path: ko/test-* - config_name: nl data_files: - split: test path: nl/test-* - config_name: pl data_files: - split: test path: pl/test-* - config_name: pt data_files: - split: test path: pt/test-* - config_name: ro data_files: - split: test path: ro/test-* - config_name: ru data_files: - split: test path: ru/test-* - config_name: tr data_files: - split: test path: tr/test-* - config_name: uk data_files: - split: test path: uk/test-* - config_name: vi data_files: - split: test path: vi/test-* - config_name: zh data_files: - split: test path: zh/test-* --- ## Dataset Card for m-ArenaHard ### Dataset Details The m-ArenaHard dataset is a multilingual LLM evaluation set. This dataset was created by translating the prompts from the originally English-only LMarena (formerly LMSYS) arena-hard-auto-v0.1 test dataset using Google Translate API v3 to 22 languages. The original English-only prompts were created by Li et al. (2024) and consist of 500 challenging user queries sourced from Chatbot Arena. The authors show that these can be used to perform automatic LLM judge evaluations, which exhibit a high correlation with Chatbot Arena rankings. The 23 languages included in this dataset: - Arabic (ar) - Chinese (zh) - Czech (cs) - Dutch (nl) - English (en) - French (fr) - German (de) - Greek (el) - Hebrew (he) - Hindi (hi) - Indonesian (id) - Italian (it) - Japanese (ja) - Korean (ko) - Persian (fa) - Polish (pl) - Portuguese (pt) - Romanian (ro) - Russian (ru) - Spanish (es) - Turkish (tr) - Ukrainian (uk) - Vietnamese (vi) ### Load with Datasets To load this dataset with Datasets, you'll need to install Datasets as pip install datasets --upgrade and then use the following code: ```python from datasets import load_dataset dataset = load_dataset("CohereForAI/m_ArenaHard", "en") ``` The above code block will load only the English subset of the entire dataset. You can load other subsets by specifying other supported languages of interest or the entire dataset by leaving that argument as blank. ### Dataset Structure An instance of the data from the Persian subset looks as follows: ```python {'question_id': '328c149ed45a41c0b9d6f14659e63599', 'cluster': 'Acrobat PDF Management Tips', 'category': 'arena-hard-v0.1', 'prompt': 'چگونه نوار ابزار را در یک قطعه اضافه کنیم؟' } ``` ### Dataset Fields The following are the fields in the dataset: - question_id: a unique ID for the example - cluster: the topic of the example - category: the original dataset where the example is from - prompt: text of the prompt (question or instruction) All language subsets of the dataset share the same fields as above. ### Authorship - Publishing Organization: [Cohere For AI](https://cohere.com/research) - Industry Type: Not-for-profit - Tech - Contact Details: https://cohere.com/research/aya ### Licensing Information This dataset can be used for any purpose, whether academic or commercial, under the terms of the Apache 2.0 License.