Datasets:

Modalities:
Tabular
Text
Formats:
parquet
ArXiv:
Libraries:
Datasets
pandas
License:
shivi ramithuh commited on
Commit
b1dae43
1 Parent(s): c78e536

Update README (#1)

Browse files

- Add language codes (41ab282b946ff59dafff764936dba5d36f55f38e)
- Upload aya_header.png (a19e61d3a99be342971cf8ce347d1cd1ab953c1a)
- Add remaining metadata fields (a76dca4733e9dd6ab32655b12d0a4ea926c917da)
- Add `dataset_summary` and `dataset` sections (bc21d11fd7f1119e56217e73a6cdeeb7ecf3e9a3)
- Fill details for `dataset` section (32109a254ed49a0f319fc1fa5af471514d00f378)
- Add 101 language code table for translations (along with dialect codes) (5ab0d37414e407dcbfd466ac36be4dd9eba9d492)
- Include additional details (motivation, citation, provenance etc.) (de2ec6218e6e7bb14f7c38967b1dfa84e6003cb0)
- Include known limitation on translation quality of `dolly-machine-translated` (f7f5f8ec8c27170a9484f47511252cd4aa4fc5e8)
- Update citation info (2d7c23128cee33dfeb35d7cd75bc9255523d301b)


Co-authored-by: Ramith Hettiarachchi <ramithuh@users.noreply.huggingface.co>

Files changed (2) hide show
  1. README.md +379 -0
  2. aya_header.png +3 -0
README.md CHANGED
@@ -68,4 +68,383 @@ configs:
68
  data_files:
69
  - split: test
70
  path: dolly_machine_translated/test-*
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
71
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
68
  data_files:
69
  - split: test
70
  path: dolly_machine_translated/test-*
71
+ language:
72
+ - afr
73
+ - sqi
74
+ - amh
75
+ - ara
76
+ - aze
77
+ - bel
78
+ - ben
79
+ - bul
80
+ - cat
81
+ - ceb
82
+ - ces
83
+ - kur
84
+ - cym
85
+ - dan
86
+ - deu
87
+ - ell
88
+ - eng
89
+ - epo
90
+ - est
91
+ - eus
92
+ - fin
93
+ - fra
94
+ - gla
95
+ - gle
96
+ - glg
97
+ - guj
98
+ - hat
99
+ - hau
100
+ - heb
101
+ - hin
102
+ - hun
103
+ - hye
104
+ - ibo
105
+ - ind
106
+ - isl
107
+ - ita
108
+ - jav
109
+ - jpn
110
+ - kan
111
+ - kat
112
+ - kaz
113
+ - mon
114
+ - khm
115
+ - kir
116
+ - kor
117
+ - lao
118
+ - lit
119
+ - ltz
120
+ - lav
121
+ - mal
122
+ - mar
123
+ - mkd
124
+ - mlt
125
+ - mri
126
+ - mya
127
+ - nld
128
+ - nor
129
+ - nep
130
+ - sot
131
+ - pus
132
+ - pes
133
+ - mlg
134
+ - pol
135
+ - por
136
+ - ron
137
+ - rus
138
+ - sin
139
+ - slk
140
+ - slv
141
+ - smo
142
+ - sna
143
+ - snd
144
+ - som
145
+ - spa
146
+ - srp
147
+ - sun
148
+ - swe
149
+ - swa
150
+ - tam
151
+ - tel
152
+ - tgk
153
+ - tha
154
+ - tur
155
+ - ukr
156
+ - urd
157
+ - uzb
158
+ - vie
159
+ - xho
160
+ - yid
161
+ - yor
162
+ - zho
163
+ - msa
164
+ - zul
165
+ - ace
166
+ - bjn
167
+ - kas
168
+ - kau
169
+ - min
170
+ - mni
171
+ - taq
172
+ - nso
173
+ language_creators:
174
+ - crowdsourced
175
+ - expert-generated
176
+ - machine-generated
177
+ multilinguality:
178
+ - multilingual
179
+ pretty_name: Aya Evaluation Suite
180
+ size_categories:
181
+ - 10K<n<100K
182
+ source_datasets:
183
+ - original
184
+ - extended
185
+ task_categories:
186
+ - text-generation
187
  ---
188
+
189
+ ![Aya Header](https://huggingface.co/datasets/CohereForAI/aya_dataset/resolve/main/aya_header.png)
190
+
191
+ # Dataset Summary
192
+
193
+ `Aya Evaluation Suite` contains a total of 25,750 open-ended conversation-style prompts to evaluate multilingual open-ended generation quality.\
194
+ To strike a balance between language coverage and the quality that comes with human curation, we create an evaluation suite that includes:
195
+ 1) human-curated examples in 7 languages (`tur,eng,yor,arb,zho,por,tel`).
196
+ 2) machine-translations of handpicked examples into 101 languages.
197
+ 3) human-post-edited translations into 6 languages (`hin,srp,rus,fra,arb,spa`).
198
+
199
+ ---
200
+
201
+ - **Curated by:** Contributors of [Aya Open Science Intiative](https://aya.for.ai/), professional annotators, and synthetic generation
202
+ - **Language(s):** 101 languages
203
+ - **License:** [Apache 2.0](https://opensource.org/license/apache-2-0)
204
+ - **Aya Datasets Family:**
205
+ | Name | Explanation |
206
+ |------|--------------|
207
+ | [aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) | Human-annotated multilingual instruction finetuning dataset, comprising over 204K instances across 65 languages. |
208
+ | [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.|
209
+ | [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.|
210
+
211
+
212
+ # Dataset
213
+
214
+ The `Aya Evaluation Suite` includes the following subsets:
215
+
216
+ 1. **aya-human-annotated**: 250 original human-written prompts in 7 languages each.
217
+ 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)
218
+ , automatically translated with the [NLLB model](https://ai.meta.com/research/no-language-left-behind/) from English into 101 languages (114 dialects in total).
219
+ 3. **dolly-human-edited**: 200 dolly-machine-translated prompts post-edited by fluent speakers for 6 languages.
220
+
221
+
222
+ ## Load with Datasets
223
+ 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:
224
+
225
+ ```python
226
+ from datasets import load_dataset
227
+
228
+ aya_eval = load_dataset("CohereForAI/aya_evaluation_suite", "dataset")
229
+ ```
230
+
231
+ ## Data Fields
232
+
233
+ - `id`: Unique id of the data point.
234
+ - `inputs`: Prompt or input to the language model.
235
+ - `targets`: Completion or output of the language model. (Not applicable for `dolly-human-edited`)
236
+ - `language`: The language of the `prompt` and `completion.`
237
+ - `script`: The writing system of the language.
238
+
239
+ ## Data Instances
240
+
241
+ An example of the `Aya Evaluation Suite` looks as follows:
242
+
243
+ ```json
244
+ {
245
+ "id": 42,
246
+ "prompt": "What day is known as Star Wars Day?",
247
+ "completion": "May 4th (May the 4th be with you!)",
248
+ "language": "eng",
249
+ "script": "Latn",
250
+ }
251
+ ```
252
+
253
+ ## Statistics
254
+
255
+ The toggled table below lists the breakdown of languages in each subset.
256
+
257
+ ### Languages
258
+
259
+ <details>
260
+ <summary> <b>aya-human-annotated</b> </summary>
261
+
262
+ | ISO Code | Language | Resources |
263
+ |----------|----------|---------------|
264
+ | `tel` | Telugu | Low |
265
+ | `yor` | Yorùbá | Low |
266
+ | `arb` | Arabic | High |
267
+ | `tur` | Turkish | High |
268
+ | `por` | Portuguese | High |
269
+ | `zho` | Chinese (Simplified) | High |
270
+ | `eng` | English | High |
271
+
272
+ </details>
273
+
274
+
275
+ <details>
276
+ <summary> <b>dolly-machine-translated</b> </summary>
277
+
278
+ | ISO Code | Language | Resources |
279
+ |----------|----------|-----------|
280
+ | `ace` | Achinese | Low |
281
+ | `afr` | Afrikaans | Mid |
282
+ | `amh` | Amharic | Low |
283
+ | `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 |
284
+ | `aze` (`azb` & `azj`) | Azerbaijani (South & North) | Low |
285
+ | `bel` | Belarusian | Mid |
286
+ | `ben` | Bengali | Mid |
287
+ | `bjn` | Banjar | Low |
288
+ | `bul` | Bulgarian | Mid |
289
+ | `cat` | Catalan | High |
290
+ | `ceb` | Cebuano | Mid |
291
+ | `ces` | Czech | High |
292
+ | `cym` | Welsh | Low |
293
+ | `dan` | Danish | Mid |
294
+ | `deu` | German | High |
295
+ | `ell` | Greek | Mid |
296
+ | `eng` | English | High |
297
+ | `epo` | Esperanto | Low |
298
+ | `est` | Estonian | Mid |
299
+ | `eus` | Basque | High |
300
+ | `fin` | Finnish | High |
301
+ | `fra` | French | High |
302
+ | `gla` | Scottish Gaelic | Low |
303
+ | `gle` | Irish | Low |
304
+ | `glg` | Galician | Mid |
305
+ | `guj` | Gujarati | Low |
306
+ | `hat` | Haitian Creole | Low |
307
+ | `hau` | Hausa | Low |
308
+ | `heb` | Hebrew | Mid |
309
+ | `hin` | Hindi | High |
310
+ | `hun` | Hungarian | High |
311
+ | `hye` | Armenian | Low |
312
+ | `ibo` | Igbo | Low |
313
+ | `ind` | Indonesian | Mid |
314
+ | `isl` | Icelandic | Low |
315
+ | `ita` | Italian | High |
316
+ | `jav` | Javanese | Low |
317
+ | `jpn` | Japanese | High |
318
+ | `kan` | Kannada | Low |
319
+ | `kas` | Kashmiri | Low |
320
+ | `kat` | Georgian | Mid |
321
+ | `kau` (`knc`) | Kanuri (Central) | Low |
322
+ | `kaz` | Kazakh | Mid |
323
+ | `khm` | Khmer | Low |
324
+ | `kir` | Kyrgyz | Low |
325
+ | `kor` | Korean | High |
326
+ | `kur` (`ckb` & `kmr`) | Kurdish (Central & Northern) | Low |
327
+ | `lao` | Lao | Low |
328
+ | `lav` (`lvs`) | Latvian (Standard) | Mid |
329
+ | `lit` | Lithuanian | Mid |
330
+ | `ltz` | Luxembourgish | Low |
331
+ | `mal` | Malayalam | Low |
332
+ | `mar` | Marathi | Low |
333
+ | `min` | Minangkabau | Low |
334
+ | `mkd` | Macedonian | Low |
335
+ | `mlg` (`plt`) | Malagasy (Plateau) | Low |
336
+ | `mlt` | Maltese | Low |
337
+ | `mni` | Manipuri | Low |
338
+ | `mon` (`khk`) | Mongolian (Khalkha) | Low |
339
+ | `mri` | Maori | Low |
340
+ | `msa` (`zsm`) | Malay (Standard) | Mid |
341
+ | `mya` | Burmese | Low |
342
+ | `nep` (`npi`) | Nepali | Low |
343
+ | `nld` | Dutch | High |
344
+ | `nor` (`nno` & `nob`) | Norwegian (Nynorsk & Bokmål) | Low |
345
+ | `nso` | Northern Sotho | Low |
346
+ | `pes` | Persian | High |
347
+ | `pol` | Polish | High |
348
+ | `por` | Portuguese | High |
349
+ | `pus` (`pbt`) | Pashto (Southern) | Low |
350
+ | `ron` | Romanian | Mid |
351
+ | `rus` | Russian | High |
352
+ | `sin` | Sinhala | Low |
353
+ | `slk` | Slovak | Mid |
354
+ | `slv` | Slovenian | Mid |
355
+ | `smo` | Samoan | Low |
356
+ | `sna` | Shona | Low |
357
+ | `snd` | Sindhi | Low |
358
+ | `som` | Somali | Low |
359
+ | `sot` | Southern Sotho | Low |
360
+ | `spa` | Spanish | High |
361
+ | `sqi` (`als`) | Albanian (Tosk) | Low |
362
+ | `srp` | Serbian | High |
363
+ | `sun` | Sundanese | Low |
364
+ | `swa` (`swh`) | Swahili (Coastal) | Low |
365
+ | `swe` | Swedish | High |
366
+ | `tam` | Tamil | Mid |
367
+ | `taq` | Tamasheq | Low |
368
+ | `tel` | Telugu | Low |
369
+ | `tgk` | Tajik | Low |
370
+ | `tha` | Thai | Mid |
371
+ | `tur` | Turkish | High |
372
+ | `ukr` | Ukrainian | Mid |
373
+ | `urd` | Urdu | Mid |
374
+ | `uzb` (`uzn`) | Uzbek (Nothern) | Mid |
375
+ | `vie` | Vietnamese | High |
376
+ | `xho` | Xhosa | Low |
377
+ | `yid` (`ydd`) | Yiddish (Eastern) | Low |
378
+ | `yor` | Yoruba | Low |
379
+ | `zho` & `yue` | Chinese (Simplified & Yue) | High |
380
+ | `zul` | Zulu | Low |
381
+ </details>
382
+
383
+ <details>
384
+ <summary> <b>dolly-human-edited</b> </summary>
385
+
386
+ | ISO Code | Language | Resources |
387
+ |----------|----------|-----------|
388
+ | `arb` | Arabic | High |
389
+ | `fra` | French | High |
390
+ | `hin` | Hindi | High |
391
+ | `rus` | Russian | High |
392
+ | `spa` | Spanish | High |
393
+ | `srp` | Serbian | High |
394
+
395
+ </details>
396
+
397
+ <br>
398
+
399
+ # Motivations & Intentions
400
+
401
+ - **Curation Rationale:** This evaluation suite is tailored to test the generation quality of multilingual models, with the aim of balancing language coverage and human-sourced quality.
402
+ It covers prompts originally written in each language, as well as English-centric translated and manually curated or edited prompts for a linguistically broad but rich testbed.
403
+ The list of languages was established from mT5 and aligned with the annotators’ language list and the NLLB translation model.
404
+
405
+ # Known Limitations
406
+
407
+ - **Translation Quality:** Note that the expressiveness of the `dolly-machine-translated` subset is limited by the quality of the translation model and may adversely impact an estimate of ability in languages where translations are not adequate. If this subset is used for testing, we recommend it be paired and reported with the professionally post-edited `dolly-human-edited` subset or the `aya-human-annotated` set, which also only covers 7 languages but is entirely created by proficient target language speakers.
408
+ ---
409
+
410
+ # Additional Information
411
+
412
+ ## Provenance
413
+ - **Methods Used:** combination of original annotations by volunteers, automatic translation, and post-editing of translations by professional annotators.
414
+ - **Methodology Details:**
415
+ - *Source:* Original annotations and translations and post-edits of Dolly
416
+ - *Platform:* [Aya Annotation Platform](https://aya.for.ai/)
417
+ - *Dates of Collection:* Jun 2023 - Dec 2023
418
+
419
+
420
+ ## Dataset Version and Maintenance
421
+ - **Maintenance Status:** Actively Maintained
422
+ - **Version Details:**
423
+ - *Current version:* 1.0
424
+ - *Last Update:* 02/2024
425
+ - *First Release:* 02/2024
426
+ - **Maintenance Plan:** No updates planned.
427
+
428
+
429
+ ## Authorship
430
+
431
+ - **Publishing Organization:** [Cohere For AI](https://cohere.com/research)
432
+ - **Industry Type:** Not-for-profit - Tech
433
+ - **Contact Details:** https://aya.for.ai/
434
+
435
+
436
+ ## Licensing Information
437
+ This dataset can be used for any purpose, whether academic or commercial, under the terms of the [Apache 2.0](https://opensource.org/license/apache-2-0) License.
438
+
439
+
440
+ ## Citation Information
441
+ ```bibtex
442
+ @misc{singh2024aya,
443
+ title={Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning},
444
+ author={Shivalika Singh and Freddie Vargus and Daniel Dsouza and Börje F. Karlsson and Abinaya Mahendiran and Wei-Yin Ko and Herumb Shandilya and Jay Patel and Deividas Mataciunas and Laura OMahony and Mike Zhang and Ramith Hettiarachchi and Joseph Wilson and Marina Machado and Luisa Souza Moura and Dominik Krzemiński and Hakimeh Fadaei and Irem Ergün and Ifeoma Okoh and Aisha Alaagib and Oshan Mudannayake and Zaid Alyafeai and Vu Minh Chien and Sebastian Ruder and Surya Guthikonda and Emad A. Alghamdi and Sebastian Gehrmann and Niklas Muennighoff and Max Bartolo and Julia Kreutzer and Ahmet Üstün and Marzieh Fadaee and Sara Hooker},
445
+ year={2024},
446
+ eprint={2402.06619},
447
+ archivePrefix={arXiv},
448
+ primaryClass={cs.CL}
449
+ }
450
+ ```
aya_header.png ADDED

Git LFS Details

  • SHA256: b88899c83d6b6d7e46b4b4d6228c282c649f028cc32bd7d34e22bf7279de216a
  • Pointer size: 131 Bytes
  • Size of remote file: 364 kB