---
license: apache-2.0
dataset_info:
- config_name: aya_human_annotated
  features:
  - name: id
    dtype: int64
  - name: inputs
    dtype: string
  - name: targets
    dtype: string
  - name: language
    dtype: string
  - name: script
    dtype: string
  splits:
  - name: test
    num_bytes: 1624958
    num_examples: 1750
  download_size: 974483
  dataset_size: 1624958
- config_name: dolly_human_edited
  features:
  - name: id
    dtype: int64
  - name: inputs
    dtype: string
  - name: targets
    dtype: string
  - name: language
    dtype: string
  - name: script
    dtype: string
  splits:
  - name: test
    num_bytes: 1209511
    num_examples: 1200
  download_size: 599142
  dataset_size: 1209511
- config_name: dolly_machine_translated
  features:
  - name: id
    dtype: int64
  - name: inputs
    dtype: string
  - name: targets
    dtype: string
  - name: language
    dtype: string
  - name: script
    dtype: string
  splits:
  - name: test
    num_bytes: 39488955
    num_examples: 23800
  download_size: 20063815
  dataset_size: 39488955
configs:
- config_name: aya_human_annotated
  data_files:
  - split: test
    path: aya_human_annotated/test-*
- config_name: dolly_human_edited
  data_files:
  - split: test
    path: dolly_human_edited/test-*
- config_name: dolly_machine_translated
  data_files:
  - split: test
    path: dolly_machine_translated/test-*
language:
- afr
- sqi
- amh
- ara
- aze
- bel
- ben
- bul
- cat
- ceb
- ces
- kur
- cym
- dan
- deu
- ell
- eng
- epo
- est
- eus
- fin
- fra
- gla
- gle
- glg
- guj
- hat
- hau
- heb
- hin
- hun
- hye
- ibo
- ind
- isl
- ita
- jav
- jpn
- kan
- kat
- kaz
- mon
- khm
- kir
- kor
- lao
- lit
- ltz
- lav
- mal
- mar
- mkd
- mlt
- mri
- mya
- nld
- nor
- nep
- sot
- pus
- pes
- mlg
- pol
- por
- ron
- rus
- sin
- slk
- slv
- smo
- sna
- snd
- som
- spa
- srp
- sun
- swe
- swa
- tam
- tel
- tgk
- tha
- tur
- ukr
- urd
- uzb
- vie
- xho
- yid
- yor
- zho
- msa
- zul
- ace
- bjn
- kas
- kau
- min
- mni
- taq
- nso
language_creators:
- crowdsourced
- expert-generated
- machine-generated
multilinguality:
- multilingual
pretty_name: Aya Evaluation Suite
size_categories:
- 10K<n<100K
source_datasets:
- original
- extended
task_categories:
- text-generation
---

![Aya Header](https://huggingface.co/datasets/CohereForAI/aya_dataset/resolve/main/aya_header.png)

# Dataset Summary

`Aya Evaluation Suite` contains a total of 25,750 open-ended conversation-style prompts to evaluate multilingual open-ended generation quality.\
To strike a balance between language coverage and the quality that comes with human curation, we create an evaluation suite that includes:
1) human-curated examples in 7 languages (`tur,eng,yor,arb,zho,por,tel`).
2) machine-translations of handpicked examples into 101 languages.
3) human-post-edited translations into 6 languages (`hin,srp,rus,fra,arb,spa`).

---

- **Curated by:** Contributors of [Aya Open Science Intiative](https://aya.for.ai/), professional annotators, and synthetic generation
- **Language(s):** 101 languages
- **License:** [Apache 2.0](https://opensource.org/license/apache-2-0)
- **Aya Datasets Family:**
  | Name | Explanation |
  |------|--------------|
  | [aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) | Human-annotated multilingual instruction finetuning dataset, comprising over 204K instances across 65 languages. |
  | [aya_collection](https://huggingface.co/datasets/CohereForAI/aya_collection) | Created by applying instruction-style templates from fluent speakers to 44 datasets, including translations of 19 instruction-style datasets into 101 languages, providing 513k instances for various tasks.|
  | [aya_evaluation_suite](https://huggingface.co/datasets/CohereForAI/aya_evaluation_suite) | A diverse evaluation set for multilingual open-ended generation, featuring 250 culturally grounded prompts in 7 languages, 200 translated prompts in 24 languages, and human-edited versions selected for cross-cultural relevance from English Dolly in 6 languages.|


# Dataset

The `Aya Evaluation Suite` includes the following subsets:

1. **aya-human-annotated**: 250 original human-written prompts in 7 languages each.
2. **dolly-machine-translated**: 200 human-selected prompts from [databricks-dolly-15k](https://www.databricks.com/blog/2023/04/12/dolly-first-open-commercially-viable-instruction-tuned-llm)
, automatically translated with the [NLLB model](https://ai.meta.com/research/no-language-left-behind/) from English into 101 languages (114 dialects in total).
3. **dolly-human-edited**: 200 dolly-machine-translated prompts post-edited by fluent speakers for 6 languages.


## Load with Datasets
To load this dataset consisting of both prompt-completions and demographics data with `datasets`, you'll just need to install Datasets as `pip install datasets --upgrade` and then use the following code:

```python
from datasets import load_dataset

aya_eval = load_dataset("CohereForAI/aya_evaluation_suite", "dataset")
```

## Data Fields

- `id`: Unique id of the data point.
- `inputs`: Prompt or input to the language model.
- `targets`: Completion or output of the language model. (Not applicable for `dolly-human-edited`)
- `language`: The language of the `prompt` and `completion.`
- `script`:  The writing system of the language.

## Data Instances

An example of the `Aya Evaluation Suite` looks as follows:

```json
{
"id": 42,
"prompt": "What day is known as Star Wars Day?",
"completion": "May 4th (May the 4th be with you!)",
"language": "eng",
"script": "Latn",
}
```

## Statistics

### Languages

<details>
<summary> <b>aya-human-annotated</b> </summary>

  | ISO Code | Language | Resourcedness |
  |----------|----------|---------------|
  | `tel` | Telugu | Low |
  | `yor` | Yorùbá | Low |
  | `arb` | Arabic | High |
  | `tur` | Turkish | High |
  | `por` | Portuguese | High |
  | `zho` | Chinese (Simplified) | High |
  | `eng` | English | High |
  
</details>


<details>
<summary> <b>dolly-machine-translated</b> </summary>
  
  | ISO Code | Language | Resourcedness |
  |----------|----------|-----------|
  |	`ace`  |	Achinese	|	Low	|
  |	`afr`  |	Afrikaans	|	Mid	|
  |	`amh`  |	Amharic	|	Low	|
  |   `ara` (`arb`, `acm`, `acq`, `aeb`, `ajp`, `apc`, `ars`, `ary` & `arz`)  | Arabic (Standard, Gelet Iraqi, Ta'izzi-Adeni, Tunisian, South Levantine, North Levantine, Najdi, Moroccan & Egyptian) | High |
  |	`aze` (`azb` & `azj`) |	Azerbaijani	(South & North) |	Low	|
  |	`bel`  |	Belarusian	|	Mid	|
  |	`ben`  |	Bengali	|	Mid	|
  |	`bjn`  |	Banjar	|	Low	|
  |	`bul`  |	Bulgarian	|	Mid	|
  |	`cat`  |	Catalan	|	High	|
  |	`ceb`  |	Cebuano	|	Mid	|
  |	`ces`  |	Czech	|	High	|
  |	`cym`  |	Welsh	|	Low	|
  |	`dan`  |	Danish	|	Mid	|
  |	`deu`  |	German	|	High	|
  |	`ell`  |	Greek	|	Mid	|
  |	`eng`  |	English	|	High	|
  |	`epo`  |	Esperanto	|	Low	|
  |	`est`  |	Estonian	|	Mid	|
  |	`eus`  |	Basque	|	High	|
  |	`fin`  |	Finnish	|	High	|
  |	`fra`  |	French	|	High	|
  |	`gla`  |	Scottish Gaelic	|	Low	|
  |	`gle`  |	Irish	|	Low	|
  |	`glg`  |	Galician	|	Mid	|
  |	`guj`  |	Gujarati	|	Low	|
  |	`hat`  |	Haitian Creole	|	Low	|
  |	`hau`  |	Hausa	|	Low	|
  |	`heb`  |	Hebrew	|	Mid	|
  |	`hin`  |	Hindi	|	High	|
  |	`hun`  |	Hungarian	|	High	|
  |	`hye`  |	Armenian	|	Low	|
  |	`ibo`  |	Igbo	|	Low	|
  |	`ind`  |	Indonesian	|	Mid	|
  |	`isl`  |	Icelandic	|	Low	|
  |	`ita`  |	Italian	|	High	|
  |	`jav`  |	Javanese	|	Low	|
  |	`jpn`  |	Japanese	|	High	|
  |	`kan`  |	Kannada	|	Low	|
  |	`kas`  |	Kashmiri	|	Low	|
  |	`kat`  |	Georgian	|	Mid	|
  |	`kau` (`knc`)  |	Kanuri (Central)	|	Low	|
  |	`kaz`  |	Kazakh	|	Mid	|
  |	`khm`  |	Khmer	|	Low	|
  |	`kir`  |	Kyrgyz	|	Low	|
  |	`kor`  |	Korean	|	High	|
  |	`kur` (`ckb` & `kmr`) |	Kurdish (Central & Northern)	|	Low	|
  |	`lao`  |	Lao	|	Low	|
  |	`lav` (`lvs`)  |	Latvian (Standard)	|	Mid	|
  |	`lit`  |	Lithuanian	|	Mid	|
  |	`ltz`  |	Luxembourgish	|	Low	|
  |	`mal`  |	Malayalam	|	Low	|
  |	`mar`  |	Marathi	|	Low	|
  |	`min`  |	Minangkabau	|	Low	|
  |	`mkd`  |	Macedonian	|	Low	|
  |	`mlg` (`plt`)  |	Malagasy (Plateau)	|	Low	|
  |	`mlt`  |	Maltese	|	Low	|
  |	`mni`  |	Manipuri	|	Low	|
  |	`mon` (`khk`)  |	Mongolian (Khalkha)	|	Low	|
  |	`mri`  |	Maori	|	Low	|
  |	`msa` (`zsm`)  |	Malay (Standard)	|	Mid	|
  |	`mya`  |	Burmese	|	Low	|
  |	`nep` (`npi`)  |	Nepali	|	Low	|
  |	`nld`  |	Dutch	|	High	|
  |	`nor` (`nno` & `nob`)  |	Norwegian (Nynorsk & Bokmål)	|	Low	|
  |	`nso`  |	Northern Sotho	|	Low	|
  |	`pes`  |	Persian	|	High	|
  |	`pol`  |	Polish	|	High	|
  |	`por`  |	Portuguese	|	High	|
  |	`pus` (`pbt`)  |	Pashto (Southern)	|	Low	|
  |	`ron`  |	Romanian	|	Mid	|
  |	`rus`  |	Russian	|	High	|
  |	`sin`  |	Sinhala	|	Low	|
  |	`slk`  |	Slovak	|	Mid	|
  |	`slv`  |	Slovenian	|	Mid	|
  |	`smo`  |	Samoan	|	Low	|
  |	`sna`  |	Shona	|	Low	|
  |	`snd`  |	Sindhi	|	Low	|
  |	`som`  |	Somali	|	Low	|
  |	`sot`  |	Southern Sotho	|	Low	|
  |	`spa`  |	Spanish	|	High	|
  |	`sqi` (`als`)  |	Albanian (Tosk)	|	Low	|
  |	`srp`  |	Serbian	|	High	|
  |	`sun`  |	Sundanese	|	Low	|
  |	`swa` (`swh`)  |	Swahili (Coastal) |	Low	|
  |	`swe`  |	Swedish	|	High	|
  |	`tam`  |	Tamil	|	Mid	|
  |	`taq`  |	Tamasheq	|	Low	|
  |	`tel`  |	Telugu	|	Low	|
  |	`tgk`  |	Tajik	|	Low	|
  |	`tha`  |	Thai	|	Mid	|
  |	`tur`  |	Turkish	|	High	|
  |	`ukr`  |	Ukrainian	|	Mid	|
  |	`urd`  |	Urdu	|	Mid	|
  |	`uzb` (`uzn`)  |	Uzbek (Nothern)	|	Mid	|
  |	`vie`  |	Vietnamese	|	High	|
  |	`xho`  |	Xhosa	|	Low	|
  |	`yid` (`ydd`)  |	Yiddish (Eastern)	|	Low	|
  |	`yor`  |	Yoruba	|	Low	|
  |	`zho` & `yue`  |	Chinese	 (Simplified & Yue) |	High	|
  |	`zul`  |	Zulu	|	Low	|
</details>

<details>
<summary> <b>dolly-human-edited</b> </summary>
  
  | ISO Code | Language | Resourcedness |
  |----------|----------|-----------|
  | `arb` | Arabic | High |
  | `fra` | French | High |
  | `hin` | Hindi | High |
  | `rus` | Russian | High |
  | `spa` | Spanish | High |
  | `srp` | Serbian | High |

</details>