datasetId stringlengths 2 117 | card stringlengths 19 1.01M |
|---|---|
zhangyi617/car-driving-dataset | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 1715614.0
num_examples: 16
download_size: 1716794
dataset_size: 1715614.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "car-driving-dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Acumen/test3 | ---
license: openrail
---
|
Falah/chapter8_0_prompts | ---
dataset_info:
features:
- name: prompts
dtype: string
splits:
- name: train
num_bytes: 3238
num_examples: 11
download_size: 4431
dataset_size: 3238
---
# Dataset Card for "chapter8_0_prompts"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
davidberenstein1957/test_david | ---
dataset_info:
features:
- name: text
dtype: string
- name: target
dtype: string
splits:
- name: train
num_bytes: 837
num_examples: 11
download_size: 2208
dataset_size: 837
---
# Dataset Card for "test_david"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
allenai/MADLAD-400 | ---
license: odc-by
task_categories:
- text-generation
size_categories:
- n>1T
---
# MADLAD-400
## Dataset and Introduction
[MADLAD-400 (*Multilingual Audited Dataset: Low-resource And Document-level*)](https://arxiv.org/abs/2309.04662) is
a document-level multilingual dataset based on Common Crawl, covering 419
languages in total. This uses all snapshots of CommonCrawl available as of August
1, 2022. The primary advantage of this dataset over similar datasets is that it
is more multilingual (419 languages), it is audited and more highly filtered,
and it is document-level. The main disadvantage is also its strength -- being
more filtered, it may lack the recall needed for some applications.
There are two versions released: the **noisy** dataset, which has no filtering
except document-level LangID, and the **clean** dataset, which has a variety of
filters applied, though it naturally has a fair amount of noise itself. Each
dataset is released in a document-level form that has been deduplicated.
## Loading
You can load both the clean and noisy versions of any language by specifing its LangID:
~~~
madlad_abt = load_dataset("allenai/madlad-400", "abt")
~~~
A list of langagues can also be supplied with a keyword argument:
~~~
madlad_multilang = load_dataset("allenai/madlad-400", languages=["abt", "ace"])
~~~
Additionally, you can load the noisy and clean subsets seperately with the split keyword argument:
~~~
madlad_multilang_clean = load_dataset("allenai/madlad-400", languages=["abt", "ace"], split="clean")
~~~
## LangID model and Crawl
Following [Language Id In the Wild](https://arxiv.org/pdf/2010.14571.pdf), we
trained a Semi-Supervised LangId model (SSLID) on 500 languages. The training
data is as described in that paper, with the differences that 1) training data
is sampled to a temperature of `T=3` to reduce over-triggering on low-resource
languages; and 2) the data is supplemented with web-crawled data from the same
paper (that has already been through the various filters described therein) in
the hopes that it will increase robustness to web-domain text.
## Filtering
Before separating the raw CommonCrawl corpus by LangID, these
filtering steps are done, similar to Raffel et al (2020):
- Discarded any page with fewer than 5 sentences and only retained lines that
contained at least 3 words.
- Removed any line with the word Javascript.
- Removed any page where the phrase “lorem ipsum” appeared.
- Removed any pages containing the phrases "terms of use", "privacy policy",
"cookie policy", "uses cookies", "use of cookies", "use cookies"
- Removed any pages that contained a curly bracket.
- To deduplicate the data set, discarded all but one of any three-sentence span occurring more than once in the data set.
The `noisy` subset of the data was filtered only by document-level LangID, which
was taken to be the majority sentence-level LangID prediction. The `clean`
subset removed all documents with a `percent_questionable` score greater than
20%. It furthermore removed any document with under 5 sentences.
The `pct_questionable` score is simple the percentage of sentences in the input
document that were "questionable". A sentence was considered questionable if any
of the following were true:
* **LangID Consistency:** the sentence-level LangID does not match the
document-level LangID
* **List Case:** The sentence has at least 12 tokens, and over 50% percent of
the tokens began in a capital letter.
* **Length:** The sentence has under 20 characters or over 500 characters
(note: this is a bad heuristic for ideographic languages)
* **Danger Chars:** Over 20% of the characters in the sentence match
`[0-9{}+/()>]`
* **Cursedness:** The sentence matches a cursed regex (see below)
### Cursed Substrings
Based on the initial round of data audits, the authors created a heuristic list of
substrings and regexes accounting for a large amount of questionable content.
Keep in mind that these all are fed into the `pct_questionable` score -- a
sentence is only excluded from the `clean` dataset if over 20% of the sentences
in that document are flagged as questionable.
notes about cursed substrings:
* low quality sentences ending in the pipe character were very common. Before
you ask, this was not Devanagari-script text using a Danda.
* The last few regexes are meant to match `A N T S P E A K`, `List Case`, and
weirdly regular text (for instance, lists of shipping labels or country
codes)
```
# this implementation is for demonstration and is pretty inefficient;
# to speed it up, use string inclusion (`in`) instead of regex for all but the
# last four, and for those use a compiled regex.
def is_cursed(s):
return any(re.findall(curse, s) in s for curse in CURSED_SUBSTRINGS)
CURSED_SUBSTRINGS = [" №", "���", "\\|\\s*$", " nr\\.$", "aute irure dolor ", " sunt in culpa qui ", "orem ipsum ", " quis nostrud ", " adipisicing ", " dolore eu ", " cupidatat ", "autem vel eum", "wisi enim ad", " sex ", " porn ", "黄色电影", "mp3", "ownload", "Vol\\.", " Ep\\.", "Episode", " г\\.\\s*$", " кг\\.\\s*$", " шт\\.", "Develop", "Facebook", " crusher ", " xxx ", " ... ... ... ... ... ... ... ... ...", " .... .... .... .... .... .... .... .... ....", " [^ ] [^ ] [^ ] [^ ] [^ ] [^ ] [^ ] [^ ] [^ ]", ", ..,,? ..,,? ..,,? ..,,?"]
```
### Virama Correction
Many languages using Brahmic Abugida (South and Southeast Asian scripts like
Devanagari, Khmer, etc.) use some variant on the virama character. For whatever
reason, it was found that this character was often messed up in the common crawl
snapshots used. Therefore, for the languages `bn my pa gu or ta te kn ml
si th tl mn lo bo km hi mr ne gom as jv dv bho dz hne ks_Deva mag mni shn yue zh
ja kjg mnw ksw rki mtr mwr xnr`, a special correction step was done.
For these languages, the authors took the list of all virama characters and removed all
unnecessary spaces between each instance of a virama character and the next
character with a regex.
```
'%s' % regex.sub(r' ([%s]) ' % _VIRAMA_CHARS, '\\1', x)
```
### Myanmar Font Compatibility
Prior to 2019, the most popular font for Burmese websites was the Zawgyi font.
The authors used [Myanmar Tools](https://github.com/google/myanmar-tools) to convert text.
Several scripts, like the Chinese script, Tibetan script, and Thai, do not use
whitespace to separate characters. The languages with this property in this
dataset are `yue zh ja th lo kjg mnw my shn ksw rki km bo dz`.
Alas, the **Length** aspect of the `pct_questionable` score was calculated using
simplistic whitespace tokenization, and therefore rendered the whole
`pct_questionable` score invalid for those languages. Therefore, for these
languages, the "clean" data is identical to the "noisy" data (barring Chinese;
see below.)
### Special filters
Chinese had a particular issue with pornographic content. After manual inspection
a list of strings likely to be present in pornographic content was developed. All
pages containing at least one of these strings were removed. Resulted in 17%
reduction in number of documents and 56% reduction in file size.
```
pornsignals = "caoporn caoprom caopron caoporen caoponrn caoponav caopom caoorn 99re dy888 caopro hezyo re99 4438x zooskool xfplay 7tav xxoo xoxo 52av freexx 91chinese anquye cao97 538porm 87fuli 91pron 91porn 26uuu 4438x 182tv kk4444 777me ae86 91av 720lu yy6080 6080yy qqchub paa97 aiai777 yy4480 videossexo 91free 一级特黄大片 偷拍久久国产视频 日本毛片免费视频观看 久久免费热在线精品 高清毛片在线看 日本毛片高清免费视频 一级黄色录像影片 亚洲男人天堂 久久精品视频在线看 自拍区偷拍亚洲视频 亚洲人成视频在线播放 色姑娘综合站 丁香五月啪啪 在线视频成人社区 亚洲人成视频在线播放 久久国产自偷拍 一本道 大香蕉无码 香港经典三级 亚洲成在人线免费视频 天天色综合网 大香蕉伊人久草 欧美一级高清片 天天鲁夜夜啪视频在线 免费黄片视频在线观看 加比勒久久综合 久草热久草在线视频 韩国三级片大全在线观看 青青草在线视频 美国一级毛片 久草在线福利资源 啪啪啪视频在线观看免费 成人福利视频在线观看 婷婷我去也 老司机在线国产 久久成人视频 手机看片福利永久国产 高清国产偷拍在线 大香蕉在线影院 日本高清免费一本视频 男人的天堂东京热 影音先锋男人资源 五月婷婷开心中文字幕 亚洲香蕉视频在线播放 天天啪久久爱视频精品 超碰久久人人摸人人搞".split()
```
A few more random notes, comparing to common alternative codes for these
languages:
* `fil` for Filipino/Tagalog, not `tl`
* `ak` for Twi/Akan, rather than `tw`. This includes Fante.
* Unfortunately use the macro code `chm` for Meadow Mari (instead of the
correct `mhr`), and `mrj` for Hill Mari
* `no` for Norwegian Bokmål, whereas some resources use
`nb`
* `ps` for Pashto instead of `pbt` (Southern Pashto)
* `ms` for Standard Malay, not `zlm`
* `sq` for Albanian, and don't distinguish dialects like
Gheg (`aln`) and Tosk (`als`)
* `ber` as the code for Tamazight, after consultation with Tamazight
speakers opining that the dialect distinctions are not significant. Other
resources use the individual codes like `tzm` and `kab`.
* Macrocode `qu` for Quechua. In practice, this seems usually to be
a mix of the Ayacucho and Cusco dialects. Other resources, like NLLB, may
use the dialect code, e.g. `quy` for Ayacucho Chanka. The same is true for a
few other macro codes, like `ff` (Macro code for Fulfulde, whereas other
sources may use e.g. `fuv`.)
* Really, there are notes that can be made about almost any code, from the
well-accepted conventions like `zh` for Mandarin, to many dialectical notes,
like which variant of Hmong really is the `hmn` data? But the above ones are
made specifically for ones where the authors are aware of other datasources floating
out there that use different conventions.
## Audit
Following [Quality at a Glance](https://arxiv.org/abs/2103.12028), the authors performed
an "audit" of every corpus in this dataset. Although the authors did not speak most
languages, they were able to give high-level comments on the general quality. They
looked at a sample of 20 documents of each language.
After an initial round of auditing, they devised a new set of filters and applied
them. They then re-did all audits.
### Overall notes from the audit
The decision was to **include languages that looked noisy, but omit any language
that was clearly majority noise, or only had 20 or fewer docs.** This is a low
bar -- twenty documents can be very little indeed, and some of the corpora released are quite noisy, but all of them should have at least the potential to
be used in some useful way. The motivation for not releasing nonsense or tiny
datasets is to not give a false sense of how multilingual this dataset actually
is ("Representation washing"), as recommended by **Quality at a Glance**.
A few overarching points:
* Many low-resource languages only had Bible text, or in some cases jw.org
data. These are marked in the rows below. Generally `ok bible` means that
100% of the audited sentences were Biblical, whereas if `bible` is simply
mentioned in the note, it was not the only source of data.
* Indian languages in the Latin script had a high concentration of
pornographic content.
### Renames and Merges as a result of the Audit
In several cases, it was clear from the audit that the corpora were not in the
languages that the LangID model claimed they were. This led to the following
renames:
* dty renamed to `zxx-xx-dtynoise`, aka a "language" of noise. This is mainly
mis-rendered PDFs and may have some practical applications for decoding
said.
* `fan` renamed to `bum`
* `ss-SZ` renamed to `ss` -- this was just a result of us having inconsistent
data labels.
* `cjk` merged into the `gil` dataset
* `bjj` merged into the `awa` dataset
## Canaries
Canaries are provided in separate `canaries` folder. Canaries are organized into three directions: `monolingual` hosts canaries designed for the MADLAD-400 monody data, `multiway` for the multiway data, and `generic` the generic canaries generated only from the model's vocabulary.
* Monolingual: Canaries here are organized by the language the canary was generated from. This corresponds exactly to the `translate_copy` setting in the paper, where the source and target language match.
* Multiway: Canaries here are organized in one of two fashions. `to_XX` indicates canaries organized by the target language (and where the source language could be any language). `XX-XX` indicates the canaries (interleaved_both and interleaved_mislabeled_both) designed for a specific pair of languages.
Within each subdirectory above, canaries are into separate files named by the canary type. There is always only a single file for each canary type. The `generic` folder contains within it the four canary types.
Canaries can be mixed in with normal training data to then be analyzed post-hoc to training
## References
Raffel, Colin, et al. "Exploring the limits of transfer learning with a unified
text-to-text transformer." J. Mach. Learn. Res. 21.140 (2020): 1-67.
## Contact
Please reach out to {snehakudugunta, icaswell}꩜google.com. For questions about the canaries, reach out to cchoquette@google.com
## License
This data is released with the `CC-BY-4.0` license.
## Detailed notes from the audit
Here are the notes on all languages, along with the number of documents
found, and the final decision made with respect to including the language in
this dataset.
| Lang. | note | N | decision |
| --------------- | ------------------------ | ---------- | --------------- |
| en | ok | 1838712272 | keep |
| ru | ok | 402458746 | keep |
| es | good | 250906994 | keep |
| de | ok | 225111495 | keep |
| fr | ok | 218863911 | keep |
| it | ok | 126406256 | keep |
| pt | ok | 124207090 | keep |
| pl | ok | 90908786 | keep |
| nl | ok | 86594116 | keep |
| tr | ok | 56417359 | keep |
| vi | ok | 54988654 | keep |
| cs | ok | 38254671 | keep |
| id | ok | 37979244 | keep |
| ro | ok | 35397563 | keep |
| sv | ok. Also the last | 35153050 | keep |
: : language (suz) is "ok : : :
: : bible" : : :
| hu | ok | 29677075 | keep |
| uk | ok | 24968305 | keep |
| fa | idk ask a farsi speaker; | 23138888 | keep |
: : ALI\: OK : : :
| ja | ok a little en mixed in | 21818123 | keep |
| el | ok | 20932239 | keep |
| fi | ok | 20433664 | keep |
| da | ok | 17865888 | keep |
| th | ok | 17439979 | keep |
| no | ok | 14864710 | keep |
| bg | ok | 12755329 | keep |
| ko | ok | 12653878 | keep |
| ar | good | 12411641 | keep |
| sk | ok | 11857945 | keep |
| ca | ok | 9477390 | keep |
| lt | ok | 8748025 | keep |
| iw | ok | 7194574 | keep |
| sl | ok | 6310419 | keep |
| et | ok | 5542933 | keep |
| lv | ok | 5007982 | keep |
| hi | ok some porn | 4512205 | keep |
| sq | good | 3622957 | keep |
| az | good | 3256331 | keep |
| hr | ok | 2841400 | keep |
| ta | ok | 2594191 | keep |
| ms | ok | 2337672 | keep |
| ml | ok | 2072605 | keep |
| sr | ok | 2010607 | keep |
| kk | ok | 1810963 | keep |
| te | ok a lot of weirdly low | 1682441 | keep |
: : quality looking content : : :
: : like commerce : : :
| mr | ok fix virama | 1673848 | keep |
| is | ok | 1560913 | keep |
| bs | good | 1362582 | keep |
| mk | ok | 1358293 | keep |
| gl | ok | 1253170 | keep |
| eu | ok | 1155671 | keep |
| bn | ok | 1138848 | keep |
| be | ok | 1092785 | keep |
| ka | ok | 936497 | keep |
| fil | ok more bible than | 901507 | keep |
: : expected for such a : : :
: : major language : : :
| mn | ok mongolian cyrillic | 879878 | keep |
| af | good | 868671 | keep |
| uz | ok some cyrllic noise | 669909 | keep |
| gu | ok | 659727 | keep |
| kn | ok | 657846 | keep |
| kaa | ok cyrllic | 586361 | keep |
| sw | ok | 537847 | keep |
| ur | ok | 467236 | keep |
| ne | ok | 453349 | keep |
| cy | ok; was terrible before | 430719 | keep |
: : filtering short docs : : :
| hy | ok | 397523 | keep |
| ky | ok | 367577 | keep |
| si | good | 349220 | keep |
| tt | good plus some | 346927 | keep |
: : nonunicode misrendered : : :
: : PDF : : :
| tg | good | 328194 | keep |
| la | ok some broken chars | 319178 | keep |
| so | good | 293218 | keep |
| ga | ok some en noise | 285999 | keep |
| km | ook | 285740 | keep |
| mt | ok | 265388 | keep |
| eo | ok; likely a lot of Mt | 259971 | keep |
| ps | ok | 252888 | keep |
| rw | ok | 226466 | keep |
| ku | ok | 218850 | keep |
| lo | ok many entities in | 215982 | keep |
: : latin script : : :
| fy | ok plausible but i bet | 210025 | keep |
: : there is a lot of nl in : : :
: : there : : :
| ha | ok | 173485 | keep |
| my | filter noise and en fix | 172401 | keep |
: : virama : : :
| dv | good | 167179 | keep |
| pa | ok | 150588 | keep |
| ckb | ok | 148870 | keep |
| lb | ok | 145988 | keep |
| mg | ok some bible jw | 115387 | keep |
| ht | ok | 110443 | keep |
| ug | ok | 106549 | keep |
| am | good | 106301 | keep |
| or | ok | 100530 | keep |
| fo | good | 97754 | keep |
| gd | ok | 94275 | keep |
| ba | ok | 90318 | keep |
| tk | ok; a few weird docs | 82495 | keep |
| mi | ok | 79509 | keep |
| hmn | ok | 75213 | keep |
| grc | ok some bible | 70730 | keep |
| jv | ok | 69473 | keep |
| ceb | ok | 66164 | keep |
| sd | good | 65858 | keep |
| yi | ok | 64949 | keep |
| kaa-Latn | ok urls are .ru or .kz | 61169 | keep |
| sn | ok | 60196 | keep |
| co | ok;l i suspect lots of | 55387 | keep |
: : MT : : :
| su | good | 54968 | keep |
| pap | ok | 54498 | keep |
| ig | ok | 54410 | keep |
| zu | good | 53809 | keep |
| xh | ok | 53672 | keep |
| sm | ok | 52614 | keep |
| ny | ok | 52244 | keep |
| yo | ok | 52067 | keep |
| cv | good | 47318 | keep |
| el-Latn | good; a lot of old | 46428 | keep |
: : content! : : :
| kl | ok | 46027 | keep |
| haw | ok scam tv products | 45670 | keep |
| gsw | wtf is happening here; | 42712 | keep |
: : keep with disclaimer; : : :
: : STILL BOILERPLATE : : :
| tet | good ; actually a lot of | 40367 | keep |
: : fun data! : : :
| st | ok | 40360 | keep |
| lus | ok | 36437 | keep |
| oc | ok | 36379 | keep |
| as | good | 33825 | keep |
| rm | ok | 33805 | keep |
| br | ok after shortfilter | 33219 | keep |
| sah | ok | 29169 | keep |
| hi-Latn | filter porn this is half | 26723 | keep |
: : porn : : :
| se | good | 23872 | keep |
| cnh | good, some local news! | 21556 | keep |
: : not sure if WL : : :
| om | ok | 18895 | keep |
| ce | ok | 14968 | keep |
| udm | ok | 13376 | keep |
| lg | ok lot of | 13030 | keep |
: : www.bukedde.co.ug in : : :
: : this : : :
| os | ok | 12623 | keep |
| nv | ok | 12578 | keep |
| kha | ok | 12070 | keep |
| ilo | ok some bible | 11754 | keep |
| ctd-Latn | ok; from some local | 11629 | keep |
: : news? : : :
| vec | very noisy has wiki from | 11108 | keep |
: : other langs and .it : : :
: : websites so not sure if : : :
: : vec : : :
| hil | ok some en boilerplate | 10564 | keep |
| tyv | ok fun stuff plus some | 9083 | keep |
: : russian noise i think : : :
| iba | ok jw data | 7638 | keep |
| ru-Latn | ok | 7523 | keep |
| kbd | ok many .ru | 7486 | keep |
| ti | ok; poor tigray | 7288 | keep |
| sa | ok | 7117 | keep |
| av | good | 6331 | keep |
| bo | needs some serious | 6226 | keep |
: : script filtering. but : : :
: : there is some ok data in : : :
: : there. : : :
| zza | good | 6019 | keep |
| ber-Latn | ok | 5612 | keep |
| otq | ok | 5554 | keep |
| te-Latn | great good text....but | 5305 | keep |
: : mostly pornographic : : :
| bua | ok | 5264 | keep |
| ts | good | 5198 | keep |
| cfm | ok mostly from | 4858 | keep |
: : chinland.co : : :
| tn | good | 4821 | keep |
| krc | ok | 4815 | keep |
| ak | good; much but not all | 4768 | keep |
: : bible : : :
| meo | ok mostly blogs | 4655 | keep |
| chm | ok; fyi watch out for | 4653 | keep |
: : yandex translationese : : :
| to | good ; news bible | 4612 | keep |
: : government : : :
| ee | good; mostly religious | 4536 | keep |
| nso | ok | 4422 | keep |
| ady | good | 4206 | keep |
| rom | bible | 4187 | keep |
| bho | mostly from anjoria.com. | 4121 | keep |
: : Looks like valid : : :
: : Bhojpuri. : : :
| ltg | ok mostly www.lakuga.lv | 4120 | keep |
| fj | ok | 3976 | keep |
| yua | ok | 3965 | keep |
| gn | ok some broken | 3858 | keep |
: : characters some bible : : :
| az-RU | good; a lot of JW | 3781 | keep |
| ln | ok bible jw | 3325 | keep |
| ada | good; bible; likely | 3095 | keep |
: : mixed with gaa : : :
| myv | maybe has .ru urls | 3095 | keep |
| bik | ok. keep in mind the bik | 3092 | keep |
: : vs bcl issue. : : :
| tlh | ok, but why tf are there | 3054 | keep |
: : websites inklingon? all : : :
: : MT ? : : :
| kbp | not sure if right script | 3036 | keep |
: : wiki says latin : : :
| war | ok but v sus. Pls filter | 2928 | keep |
: : out wikipedia : : :
| wa | ok lots of wiki stuff | 2772 | keep |
| bew | mostly blogs. idk if | 2677 | keep |
: : standard Indonesian or : : :
: : not : : :
| rcf | ok | 2630 | keep |
| ta-Latn | good text .... but | 2580 | keep |
: : pornographic : : :
| kac | ok | 2567 | keep |
| iu | filter script some is en | 2537 | keep |
: : rest is iu script : : :
| ay | good; mix of bible and | 2505 | keep |
: : other news sources : : :
| kum | ok | 2495 | keep |
| qu | ok | 2449 | keep |
| bgp | almost all ur-Latn. | 2427 | keep |
: : consider removing or : : :
: : renaming : : :
| hif | ok some en noise and | 2358 | keep |
: : religious : : :
| kw | ok short boilerplate | 2324 | keep |
: : bible wiki; ok some porn : : :
| nan-Latn-TW | ok | 2285 | keep |
| srn | ok bible + jw | 2281 | keep |
| tly-IR | deeply sus | 2239 | keep |
| sg | ok jw | 2106 | keep |
| gom | ok | 2102 | keep |
| ml-Latn | ok some short docs | 2071 | keep |
| kj | ok | 2062 | keep |
| ksd | ok bible | 2000 | keep |
| dz | ok; hidden parallel | 1899 | keep |
: : text; maybe actually bo; : : :
: : mainly buddhist : : :
| kv | ok a lil boilerplate | 1878 | keep |
: : vibes : : :
| msi | ok | 1870 | keep |
| ve | ok mostly bible jw | 1866 | keep |
| zap | ok JW. | 1803 | keep |
| zxx-xx-dtynoise | BEAUTIFUL NOISE rename | 1765 | keep |
: : but keep as beautiful : : :
: : xample. (was called : : :
: : "dty") : : :
| meu | ok bible | 1728 | keep |
| iso | ok jw | 1721 | keep |
| ium | filter out zh | 1721 | keep |
| nhe | ok | 1714 | keep |
| tyz | ok bible bu again i | 1707 | keep |
: : think some mixeed : : :
: : dialects : : :
| hui | ok some bible | 1680 | keep |
| new | ok | 1634 | keep |
| mdf | ok some short docs | 1609 | keep |
| pag | bible | 1588 | keep |
| gv | filter short repetitive | 1586 | keep |
: : sentences; still same : : :
: : but keep : : :
| gag | has 1-2 cyrillic | 1572 | keep |
: : examples with small amts : : :
: : of arabic script noise : : :
| ngu | ok | 1534 | keep |
| quc | bible | 1526 | keep |
| mam | ok bible jw | 1513 | keep |
| min | ok mostly wiki and bible | 1474 | keep |
| ho | ok | 1466 | keep |
| pon | bible | 1462 | keep |
| mrj | ok | 1447 | keep |
| lu | ok jw | 1444 | keep |
| gom-Latn | ok very noisy ; some ok | 1432 | keep |
: : stuff ; release with : : :
: : disclaimer : : :
| alt | ok | 1422 | keep |
| nzi | ok | 1371 | keep |
| tzo | ok bible + jw | 1357 | keep |
| bci | ok bible | 1329 | keep |
| dtp | ok; mostly from | 1309 | keep |
: : www.newsabahtimes.com.my : : :
| abt | fine; bible | 1305 | keep |
| bbc | ok | 1274 | keep |
| pck | ok | 1255 | keep |
| mai | ok mild amounts of en | 1240 | keep |
: : noise : : :
| mps | ok bible | 1239 | keep |
| emp | ok bible | 1238 | keep |
| mgh | ok bible jw | 1222 | keep |
| tab | idk plausibly ok | 1202 | keep |
| crh | ok | 1184 | keep |
| tbz | good mostly bible but | 1126 | keep |
: : not all : : :
| ss | good mix of data ; | 1089 | keep |
: : renamed from "ss" : : :
| chk | ok bible | 1082 | keep |
| bru | ok; bible | 1072 | keep |
| nnb | ok | 1071 | keep |
| fon | ok mostly jw but not all | 1065 | keep |
| ppk | bible | 1063 | keep |
| tiv | ok jw | 1063 | keep |
| btx | ok probably | 1009 | keep |
| bg-Latn | ok | 991 | keep |
| mbt | ok bible | 969 | keep |
| ace | good; bible | 966 | keep |
| tvl | ok jw | 933 | keep |
| dov | ok bible + jw | 923 | keep |
| ach | good; bible | 915 | keep |
| xal | ok has .ru sites though | 913 | keep |
| cuk | ok bible | 899 | keep |
| kos | ok lds bible | 881 | keep |
| crs | ok | 873 | keep |
| wo | ok; mostly bible. | 871 | keep |
| bts | ok; mostly bible | 869 | keep |
| ubu | ok bible | 846 | keep |
| gym | ok biblle | 820 | keep |
| ibb | ok bible and repeated @ | 818 | keep |
| ape | good; bible | 814 | keep |
| stq | ok i think ? | 809 | keep |
| ang | much noise but some good | 803 | keep |
: : Old English in there! : : :
| enq | ok bible | 793 | keep |
| tsg | much noise but somegood | 789 | keep |
: : data too! : : :
| shn | mostly English | 788 | keep |
: : boilerplate. filter by : : :
: : latin text before : : :
: : releasing : : :
| kri | ok boilerplate noise | 786 | keep |
: : bible jw : : :
| kek | ok jw bible | 782 | keep |
| rmc | ok | 738 | keep |
| acf | good; bible | 730 | keep |
| syr | good; practictitioners | 716 | keep |
: : should keep dialect in : : :
: : mind. : : :
| qub | bible | 705 | keep |
| bm | good | 702 | keep |
| tzh | ok jw | 702 | keep |
| jiv | ok bible | 696 | keep |
| kn-Latn | filter en noise of | 688 | keep |
: : karnatake govt websites : : :
| kjh | ok .ru domain | 672 | keep |
| yap | ok | 638 | keep |
| ban | ok bible | 637 | keep |
| tuc | ok bible | 635 | keep |
| tcy | good; mostly wikipedia; | 632 | keep |
: : likely some konkani : : :
: : mixed in : : :
| cab | ok jw | 629 | keep |
| cak | ok bible | 617 | keep |
| din | ok after SD filter | 611 | keep |
| arn | good; bible | 593 | keep |
| lrc | ok | 587 | keep |
| gil | empty; but merged in | 586 | keep |
: : data in "cjk" : : :
| gil | this is all in gil | 586 | keep |
: : (Kiribati). merged into : : :
: : "gil" : : :
| rwo | bible | 572 | keep |
| hus | ok bible | 569 | keep |
| bum | ok bible; but wrong | 559 | keep |
: : language. Data is in : : :
: : Bulu, not Fang : : :
| mak | ok bible | 555 | keep |
| frp | fair amount from | 550 | keep |
: : wikipedia. : : :
| seh | ok jw | 545 | keep |
| twu | ok bible, but also i | 539 | keep |
: : think it's lots of mixed : : :
: : similar dialects : : :
| kmb | ok bible jw | 538 | keep |
| ksw | ok bible | 536 | keep |
| sja | ok bibe | 527 | keep |
| amu | good; bible; crazy | 511 | keep |
: : diacritics : : :
| mad | remove mostly short text | 509 | keep |
| quh | bible | 501 | keep |
| dyu | ok bible | 483 | keep |
| toj | ok jw | 452 | keep |
| ch | ok; not sure about WL | 449 | keep |
| sus | hella sus jk ok bible | 437 | keep |
| nog | ok | 419 | keep |
| jam | ok bible | 416 | keep |
| gui | ok bible | 409 | keep |
| nia | ok | 408 | keep |
| mas | ok some amount of bible | 405 | keep |
| bzj | ok bible | 404 | keep |
| mkn | ok bible | 402 | keep |
| lhu | ok bible | 377 | keep |
| ctu | ok bible | 366 | keep |
| kg | ok bible jw | 365 | keep |
| inb | ok bible | 343 | keep |
| guh | ok bible | 331 | keep |
| rn | bible | 323 | keep |
| bus | ok; bible; about 50bzc | 322 | keep |
| mfe | ok mostly bible maybe | 320 | keep |
: : some french creole short : : :
: : doc noise : : :
| sda | ok bible | 317 | keep |
| bi | good! fun! | 311 | keep |
| cr-Latn | noise and lorem ipsom. | 303 | keep |
: : But some ok Cree text. : : :
| gor | ok bible | 303 | keep |
| jac | ok bible | 303 | keep |
| chr | ok bible | 301 | keep |
| mh | ok jw lds | 296 | keep |
| mni | ok | 290 | keep |
| wal | ok bible + jw | 286 | keep |
| teo | ok bible | 274 | keep |
| gub | ok bible | 271 | keep |
| qvi | bible | 266 | keep |
| tdx | ok jw | 262 | keep |
| rki | ok | 251 | keep |
| djk | ok; bible+jw | 246 | keep |
| nr | ok | 246 | keep |
| zne | ok jw | 239 | keep |
| izz | ok bible | 237 | keep |
| noa | ok | 234 | keep |
| bqc | ok; bible | 228 | keep |
| srm | ok; bible + jw | 227 | keep |
| niq | ok | 226 | keep |
| bas | ok; has some fun blog | 216 | keep |
: : stuff! : : :
| dwr | ok; bible; mixed script | 215 | keep |
| guc | ok bible | 214 | keep |
| jvn | ok bible | 213 | keep |
| hvn | ok religioous text | 200 | keep |
| sxn | ok bible ; also wild | 197 | keep |
: : diacritics : : :
| koi | ok | 196 | keep |
| alz | good; bible | 195 | keep |
| nyu | ok | 195 | keep |
| bn-Latn | ok | 191 | keep |
| suz | | 186 | keep |
| pau | ok | 185 | keep |
| nij | ok | 183 | keep |
| sat-Latn | good! al from local news | 183 | keep |
: : sources : : :
| gu-Latn | filter short en | 179 | keep |
: : boilerplate and : : :
: : repetitive sentences : : :
| msm | ok bible | 177 | keep |
| maz | ok bible jw | 170 | keep |
| qxr | bible | 153 | keep |
| shp | ok bible | 150 | keep |
| hne | ok | 146 | keep |
| ktu | ok bible jw | 144 | keep |
| laj | ok bible | 144 | keep |
| pis | bible | 139 | keep |
| mag | ok fix virama issue | 138 | keep |
| gbm | ok | 137 | keep |
| tzj | ok bible | 136 | keep |
| oj | ok | 135 | keep |
| ndc-ZW | ok | 132 | keep |
| tks | ok bible bu again i | 127 | keep |
: : think some mixeed : : :
: : dialects : : :
| gvl | filter short boilerplate | 126 | keep |
: : mostly bible : : :
| knj | ok bible | 126 | keep |
| awa | all bible in awadhi | 126 | keep |
: : (awa). Renamed from bjj : : :
| spp | ok bible | 123 | keep |
| mqy | bible remove short docs | 119 | keep |
| tca | ok bible + jw | 117 | keep |
| cce | ok jw | 116 | keep |
| skr | ok; some pnb mixed in | 107 | keep |
| kmz-Latn | ok soome ar script noise | 106 | keep |
| dje | ok; mostly but not all | 100 | keep |
: : bible : : :
| gof | ok some bible | 97 | keep |
| agr | good; bible | 93 | keep |
| qvz | bible | 88 | keep |
| adh | good; bible | 87 | keep |
| quf | bible | 86 | keep |
| kjg | ok bible | 84 | keep |
| tsc | ok | 82 | keep |
| ber | ok great! | 79 | keep |
| ify | ok bible | 79 | keep |
| cbk | ok bible | 78 | keep |
| quy | bible | 78 | keep |
| ahk | good; bible; crazy | 77 | keep |
: : diacritics : : :
| cac | ok bible | 77 | keep |
| akb | good; bible | 71 | keep |
| nut | ok | 67 | keep |
| ffm | ok bible; mixed fulfulde | 65 | keep |
: : dialects; consider : : :
: : merging with ff : : :
| taj | ok bible | 65 | keep |
| ms-Arab | ok mostly utusanmelayu | 63 | keep |
: : website : : :
| brx | quite good! | 62 | keep |
| ann | good; all from wikimedia | 56 | keep |
: : incubator : : :
| qup | bible | 53 | keep |
| ms-Arab-BN | ok not sure if same as | 46 | keep |
: : ms-Arab : : :
| miq | ok | 45 | keep |
| msb | ok bible | 41 | keep |
| bim | good; bible | 40 | keep |
| raj | ok | 40 | keep |
| kwi | ok bible | 37 | keep |
| tll | ok jw | 37 | keep |
| trp | good ; lots of random | 36 | keep |
: : stuff : : :
| smt | ok bible but lots of | 34 | keep |
: : different bibles! : : :
| mrw | ok | 29 | keep |
| dln | ok bible | 28 | keep |
| qvc | bible | 27 | keep |
| doi | ok actually nice! | 26 | keep |
| ff | ok after shortfilter | 26 | keep |
| zh | very noisy | 19850947 | keep (filtered) |
| zh-Latn | poor quality | 602 | remove |
| rhg-Latn | remove | 10302 | remove |
| ja-Latn | remove maybe low quality | 7516 | remove |
: : short and repeated : : :
| pam | remove | 2773 | remove |
| za | revisit after | 1700 | remove |
: : shortfilter : : :
| ar-Latn | terrible, 0% orrect, | 1520 | remove |
: : remove : : :
| mnw | remove en noise and | 1100 | remove |
: : boilerplate : : :
| fip | ok jw ; but wrong | 729 | remove |
: : language. mostly : : :
: : Mambwe-Lungu and Bemba, : : :
: : as well as Fipu (mgr+bem : : :
: : vs. fip) : : :
| el-CY | bad; not Cypriote | 537 | remove |
| luz | terrible; remove | 354 | remove |
| cni | ok; bible; lots of mixed | 261 | remove |
: : in content in : : :
: : not,cob,cpc,arl : : :
| apd-SD | terribly questionable; | 227 | remove |
: : probably remove : : :
| mey | mostly short and noisy | 127 | remove |
: : borderline : : :
| awa | OK; should be used with | 126 | remove |
: : caution and suspicion : : :
| mtq | remove short doc | 111 | remove |
: : repetitive : : :
| mel | remove noisy en | 103 | remove |
| mr-Latn | remove mostly porn and | 91 | remove |
: : short docs : : :
| srr | remove ; english | 91 | remove |
: : boilerplate : : :
| en-Cyrl | ok ... some fr-Cyrl too | 90 | remove |
: : and maybe others : : :
| en-Arab | remove | 79 | remove |
| syl | idk maybe ok ? | 61 | remove |
| jax | filter mostly | 58 | remove |
: : text.medjugorje.ws : : :
: : boilerplate : : :
| xmm | very noisy lots of dj | 58 | remove |
: : tiktok and peppa pig : : :
: : repeated : : :
| shu | quite questionable. prob | 53 | remove |
: : remove : : :
| ks | ok shorter docs | 51 | remove |
| gyn | remove boilerplate and | 45 | remove |
: : porn : : :
| aa | some pretty bad data but | 32 | remove |
: : also some good data. : : :
: : filter on "Woo" (case : : :
: : sensitive) : : :
| sjp | terible; probably | 31 | remove |
: : remove; check again : : :
: : after short filter : : :
| abs | all short nonsense | 24 | remove |
: : remove : : :
| mui | remove short docs | 23 | remove |
| mdh | filter porn short text | 22 | remove |
: : and repetitive : : :
: : boilerplate : : :
| noe | ok | 22 | remove |
| sxu | rvisit after shortfilter | 22 | remove |
| bhb-Gujr | bad. remove. all junk | 20 | remove |
: : gu. : : :
| yaq | remove | 20 | remove |
| prk | ok | 18 | remove |
| cgg | rather noisy but | 17 | remove |
: : potentialy ok. not sure : : :
: : if WL or not : : :
| bto | bad; remove unless short | 16 | remove |
: : filter keeps enough : : :
| ayl | terrible | 13 | remove |
| pa-Arab | ok | 13 | remove |
| bmm | terrible. filter on | 11 | remove |
: : short and reevaluate : : :
| mfb | remove short boilerplate | 11 | remove |
| mtr | ok fix virama remove en | 11 | remove |
: : noise : : :
| pmy | remove | 11 | remove |
| skg | terrible; remove | 11 | remove |
| ymm | remove | 11 | remove |
| xnr | ok maybe fix virama | 9 | remove |
: : though it seems fine : : :
| kjb | ok bible | 8 | remove |
| azg | short noise; bible | 7 | remove |
| bgz | idk maybe ok but | 7 | remove |
: : probably bad : : :
| ctg | probably terrible | 7 | remove |
: : probably remove : : :
| nyo | ok | 7 | remove |
| mdy | ok bible | 6 | remove |
| syl-Latn | revist or remove after | 6 | remove |
: : shortfilter : : :
| xog | ok bible and stories | 6 | remove |
| cyo | terrifying noise; remove | 4 | remove |
| kfy | filter virama issue | 4 | remove |
| nd | ok | 4 | remove |
| rwr | remove | 4 | remove |
| tuf | ok bible | 4 | remove |
| clu | ok bible | 3 | remove |
| ng | ok | 3 | remove |
| zyj | deeply bad data .. | 3 | remove |
: : revisit after : : :
: : shortfilter : : :
| rkt | ok | 2 | remove |
| bgc | super sketch. Remove | 1 | remove |
: : unless short doc filter : : :
: : leaves some. remove : : :
| dcc | remove | 1 | remove |
| ff-Adlm | good | 1 | remove |
| gju | remove short boilerplate | 1 | remove |
| max | remove short some ru | 1 | remove |
| mwr | filter short docs fix | 1 | remove |
: : virama : : :
| trw | sus; remove | 1 | remove |
| vkt | 1 doc remove | 1 | remove |
| gjk | empty remove | 0 | remove |
| bfy | very bad. remove unless | 0 | remove |
: : it looks better after : : :
: : filtering short docs; : : :
: : remove : : :
| nyn | ok | 0 | remove |
| sgj | remove | 0 | remove |
A few comments too long to fit in the table above:
* `alt`: WAIT THIS IS AMAZING IT IS ACTUALLY ALTAI! e.g. from urls like
https://altaicholmon.ru/2020/02/28/jarashty-la-jajaltany-jarkyndu-lekeri/
* `tly-IR`: They all look like boilerplate content, e.g., list of
keywords/search queries used to bump page ranking in search results. Not any
useful material for translation. Remove.
* `zap`: pls note that at least some Zapotec speakers tend to view it as one
language, not as a million dialects like ISO does. However, some are
certainly mutually unintelligible, complicating the matter.
* `zh-Latn`: The biggest problem is that several examples are not in Latin
Chinese (i.e., romanization in my understanding) but in English or mixed
English and Chinese. For those data in Latin Chinese, their quality seems to
be good.
* `zh`: Many examples are porn-related, particularly those very long
documents. Also, there are some examples of traditional Chinese.
## Final Dataset information
The number of documents, sentences, tokens, characters, and bytes for the noisy
and clean splits of the data. Note that the "toks" field below uses whitespace
for tokenization, so is not appropriate for non-whitespace-separating languages
like Chinese (see section above). Note that the english subset in this version
is missing 18% of documents that were included in the published analysis of the dataset.
These documents will be incoporated in an update coming soon.
BCP-47 | docs (noisy) | docs (clean) | sents (noisy) | sents (clean) | toks (noisy) | toks (clean) | chars (noisy) | chars (clean) | clean | noisy |
----------------|:---------------|:---------------|:----------------|:----------------|:---------------|:---------------|:----------------|:----------------|:---------|:---------|
total* | 7.2B | 3.7B | 133.1B | 97.5B | 4.6T | 2.6T | 30.6T | 16.0T | 11.4 T | 6.3 T
en* | 3.0B | 1.5B | 71.1B | 45.4B | 2.0T | 1.3T | 12.3T | 7.6T | 2.6 T | 4.3 T |
ru | 823M | 402.5M | 823M | 12.4B | 416.5B | 240.9B | 3.1T | 1.8T | 832.9 G | 1.4 T |
es | 476.4M | 250.9M | 8.3B | 4.5B | 325.7B | 170.4B | 2.1T | 1.1T | 380.9 G | 747.5 G |
de | 478.6M | 225.1M | 11.5B | 6B | 299.5B | 139.6B | 2.2T | 1T | 370.6 G | 815.5 G |
fr | 384.2M | 218.9M | 7.9B | 5B | 307.1B | 165.2B | 2T | 1T | 370.4 G | 699.1 G |
it | 238.9M | 126.4M | 4.5B | 2.5B | 180.1B | 83.6B | 1.2T | 553.1B | 198.4 G | 429.6 G |
pt | 209.2M | 124.2M | 4B | 2.4B | 123.2B | 79.2B | 791.5B | 499.8B | 183.1 G | 289.6 G |
pl | 145.1M | 90.9M | 3.3B | 2.4B | 68.9B | 49.2B | 505B | 356.4B | 140.7 G | 202.5 G |
nl | 134.5M | 86.6M | 134.5M | 2.3B | 104.4B | 51.6B | 698.5B | 334.5B | 118.2 G | 247.5 G |
tr | 107M | 56.4M | 107M | 1.2B | 41.9B | 25B | 328.8B | 198.9B | 73.7 G | 123.9 G |
vi | 92.8M | 55M | 1.6B | 1B | 71.5B | 48.7B | 342B | 228.8B | 88.8 G | 133.9 G |
cs | 72.1M | 38.3M | 1.7B | 1B | 40.8B | 22.1B | 272.2B | 147.9B | 62.1 G | 112.7 G |
id | 120.9M | 38M | 2.2B | 747.5M | 60.4B | 20.2B | 443B | 148.3B | 48.5 G | 148.7 G |
ro | 60.8M | 35.4M | 60.8M | 746.4M | 37.1B | 22.9B | 244.1B | 148.2B | 55.5 G | 90.3 G |
sv | 65.2M | 35.2M | 65.2M | 1B | 62.1B | 23.9B | 422.6B | 153.7B | 57.0 G | 149.9 G |
hu | 47.6M | 29.7M | 1.3B | 806.3M | 29.8B | 17.8B | 223.6B | 134.9B | 53.5 G | 86.8 G |
uk | 46.6M | 25M | 1B | 599.9M | 21.6B | 12.8B | 164.2B | 95.2B | 45.1 G | 75.8 G |
fa | 58.1M | 23.1M | 920.6M | 493.5M | 40.6B | 18.4B | 220.4B | 96.7B | 43.4 G | 97.4 G |
ja | 23.3M | 21.8M | 326M | 321.6M | 10.9B | 10.9B | 133.3B | 132.2B | 98.7 G | 99.7 G |
el | 52.4M | 20.9M | 808M | 445.4M | 25B | 12B | 173.2B | 80.9B | 37.9 G | 80.8 G |
fi | 35.8M | 20.4M | 1B | 650.3M | 23.8B | 11.5B | 202.2B | 101.1B | 37.6 G | 74.1 G |
zh | 29.3M | 19.9M | 492.3M | 298.8M | 19.2B | 10B | 333B | 142.3B | 109.9 G | 191.8 G |
da | 38.5M | 17.9M | 1.1B | 508M | 37.7B | 13B | 252B | 83.1B | 29.4 G | 89.5 G |
th | 19M | 17.4M | 19M | 385.8M | 8.9B | 8.9B | 118.6B | 117.6B | 57.6 G | 58.2 G |
no | 34.7M | 14.9M | 34.7M | 498.7M | 46.6B | 11.8B | 305.6B | 74.8B | 27.3 G | 109.8 G |
bg | 27.2M | 12.8M | 599.4M | 360.3M | 14.4B | 8.8B | 95.6B | 57.8B | 26.0 G | 42.8 G |
ko | 19.7M | 12.7M | 628.6M | 471.8M | 13.3B | 9.3B | 65.9B | 43.8B | 34.2 G | 49.1 G |
ar | 67.6M | 12.4M | 876.6M | 182.6M | 39B | 7.1B | 243B | 43.2B | 20.9 G | 115.9 G |
sk | 23.2M | 11.9M | 487.9M | 300.6M | 11.3B | 6.7B | 77.8B | 45.7B | 18.8 G | 31.9 G |
ca | 17.9M | 9.5M | 258.6M | 153M | 8.9B | 5.6B | 56.5B | 34.6B | 12.6 G | 20.8 G |
lt | 15.3M | 8.7M | 374M | 256.9M | 7.5B | 5.3B | 58.6B | 41.3B | 15.7 G | 22.3 G |
he | 14.1M | 7.2M | 302.2M | 196.8M | 9.2B | 5.2B | 54.9B | 30.5B | 14.8 G | 26.3 G |
sl | 12M | 6.3M | 316M | 180M | 6.9B | 4.5B | 47.8B | 30.5B | 11.5 G | 18.0 G |
et | 8.8M | 5.5M | 223.8M | 176.3M | 5B | 3.6B | 40.1B | 28.7B | 10.7 G | 15.0 G |
lv | 8.4M | 5M | 186.1M | 138.5M | 4.8B | 3.2B | 36.7B | 23.9B | 9.1 G | 13.8 G |
hi | 9.9M | 4.5M | 254.4M | 152M | 7.4B | 3.8B | 39.9B | 20.1B | 9.9 G | 19.7 G |
sq | 5.5M | 3.6M | 5.5M | 56.1M | 2.7B | 2.1B | 17B | 12.7B | 4.8 G | 6.6 G |
az | 5.2M | 3.3M | 90.3M | 70.9M | 2.1B | 1.5B | 16.3B | 11.9B | 4.5 G | 6.3 G |
hr | 23M | 2.8M | 476.6M | 53M | 12.6B | 1.4B | 85.1B | 9.6B | 3.7 G | 33.5 G |
ta | 5.6M | 2.6M | 122.5M | 81.9M | 2.1B | 1.1B | 19.2B | 10.6B | 4.9 G | 8.8 G |
ms | 14.1M | 2.3M | 14.1M | 55.2M | 8B | 1.7B | 58.8B | 12.5B | 4.0 G | 20.4 G |
ml | 3.7M | 2.1M | 75M | 52M | 1B | 603.3M | 10.5B | 6.3B | 3.0 G | 5.1 G |
sr | 4.7M | 2M | 4.7M | 64M | 2.7B | 1.6B | 18.6B | 11B | 5.1 G | 8.7 G |
kk | 3.1M | 1.8M | 87.4M | 59.1M | 1.6B | 1B | 13.4B | 8.6B | 3.8 G | 5.8 G |
te | 2.5M | 1.7M | 59M | 46.4M | 900.2M | 618.5M | 7.4B | 5.1B | 2.6 G | 3.8 G |
mr | 2.9M | 1.7M | 2.9M | 50M | 1.2B | 776.9M | 8.7B | 5.5B | 2.8 G | 4.4 G |
is | 2.9M | 1.6M | 73.7M | 39.3M | 2.1B | 979.2M | 14.9B | 6.4B | 2.5 G | 5.9 G |
bs | 12.9M | 1.4M | 163.6M | 9M | 5.9B | 490.9M | 39.5B | 3.3B | 1.3 G | 15.6 G |
mk | 2.9M | 1.4M | 41.3M | 22.6M | 1.3B | 685.9M | 9.1B | 4.5B | 2.0 G | 4.0 G |
gl | 4.2M | 1.3M | 45.3M | 18.8M | 2.3B | 748.4M | 15.6B | 4.8B | 1.7 G | 5.5 G |
eu | 2.1M | 1.2M | 41.7M | 24.8M | 827.5M | 525.3M | 6.9B | 4.3B | 1.5 G | 2.4 G |
bn | 4.3M | 1.1M | 151.2M | 38.6M | 2.5B | 645.7M | 16.8B | 4.3B | 2.2 G | 8.7 G |
be | 2M | 1.1M | 48.8M | 31.3M | 981M | 632.9M | 7.2B | 4.6B | 2.2 G | 3.5 G |
ka | 3.1M | 936.5K | 53.7M | 26.6M | 1.2B | 460.8M | 10.3B | 3.8B | 1.9 G | 5.0 G |
fil | 4.2M | 901.5K | 67.4M | 19.2M | 2.2B | 741.7M | 14.6B | 4.7B | 1.5 G | 5.0 G |
mn | 2.2M | 879.9K | 43.3M | 24M | 1.1B | 487.5M | 7.9B | 3.5B | 1.6 G | 3.5 G |
af | 2.9M | 868.7K | 51.9M | 30M | 1.7B | 795M | 11.8B | 4.8B | 1.8 G | 4.2 G |
uz | 1.4M | 669.9K | 25.7M | 17.5M | 605.9M | 388.3M | 5.2B | 3.3B | 1.1 G | 1.9 G |
gu | 1.3M | 659.7K | 28.9M | 18.1M | 634.4M | 345.9M | 3.9B | 2.1B | 1.1 G | 2.0 G |
kn | 1.6M | 657.8K | 32.9M | 19.2M | 546.4M | 258.6M | 4.6B | 2.2B | 1.1 G | 2.3 G |
kaa | 1.1M | 586.4K | 19.8M | 13.3M | 455.9M | 269M | 3.8B | 2.2B | 990.2 M | 1.6 G |
sw | 1.3M | 537.8K | 1.3M | 9.5M | 660.7M | 345.8M | 4.6B | 2.4B | 826.1 M | 1.6 G |
ur | 967.2K | 467.2K | 29M | 18.4M | 1B | 562.5M | 5.2B | 2.7B | 1.2 G | 2.4 G |
ne | 876.4K | 453.3K | 876.4K | 20.4M | 585M | 345.3M | 3.9B | 2.2B | 1.1 G | 1.9 G |
cy | 4.9M | 430.7K | 68.3M | 7.4M | 3.6B | 275.6M | 26.4B | 1.7B | 609.5 M | 10.0 G |
hy | 2M | 397.5K | 31.1M | 9.9M | 1B | 190.9M | 8.1B | 1.5B | 678.9 M | 3.6 G |
ky | 751.1K | 367.6K | 14.3M | 9.6M | 303.4M | 181.6M | 2.5B | 1.4B | 665.1 M | 1.1 G |
si | 788K | 349.2K | 22.1M | 16M | 507.3M | 293.3M | 3.4B | 1.9B | 1023.6 M | 1.8 G |
tt | 2.1M | 346.9K | 60.2M | 8.6M | 1B | 135M | 12.1B | 1B | 494.1 M | 4.6 G |
tg | 789.2K | 328.2K | 789.2K | 7.4M | 363.8M | 208.8M | 2.6B | 1.4B | 635.7 M | 1.1 G |
la | 2.9M | 319.2K | 85.7M | 13.8M | 1.1B | 218.4M | 8.2B | 1.5B | 550.6 M | 2.9 G |
so | 729.2K | 293.2K | 729.2K | 3.1M | 294.8M | 146.3M | 2.1B | 992.4M | 350.8 M | 746.2 M |
ga | 5.3M | 286K | 31.7M | 6.9M | 4.2B | 229.3M | 30.6B | 1.4B | 500.7 M | 9.8 G |
km | 297.8K | 285.7K | 5M | 5M | 53M | 52.6M | 1.1B | 1.1B | 566.2 M | 570.0 M |
mt | 1.2M | 265.4K | 1.2M | 5.6M | 390.4M | 171.5M | 3.2B | 1.3B | 467.4 M | 1.1 G |
eo | 1.4M | 260K | 33.9M | 9.3M | 745.1M | 253.1M | 5.5B | 1.7B | 627.6 M | 1.9 G |
ps | 429.9K | 252.9K | 5.1M | 3.6M | 293.9M | 177.5M | 1.4B | 848.9M | 403.5 M | 682.9 M |
rw | 681.8K | 226.5K | 681.8K | 1.9M | 225M | 99.8M | 1.7B | 749.1M | 264.8 M | 702.4 M |
ku | 671.9K | 218.9K | 10.7M | 4.9M | 305.3M | 143.8M | 2.1B | 849.9M | 335.3 M | 791.9 M |
lo | 229.1K | 216K | 2.9M | 2.8M | 41.7M | 41.1M | 706.9M | 697.6M | 365.3 M | 370.8 M |
fy | 1.7M | 210K | 12.1M | 3.7M | 506.9M | 94M | 3.7B | 592.3M | 223.0 M | 1.2 G |
ha | 443.9K | 173.5K | 4.5M | 2.4M | 206.5M | 109.3M | 1.3B | 630.2M | 219.0 M | 478.1 M |
my | 176.5K | 172.4K | 176.5K | 10.1M | 96.6M | 96.3M | 1.3B | 1.3B | 648.8 M | 650.4 M |
dv | 264.4K | 167.2K | 4.3M | 3.5M | 92.8M | 64M | 877.3M | 603.1M | 238.3 M | 343.2 M |
pa | 368.2K | 150.6K | 368.2K | 6M | 306M | 152.8M | 1.6B | 797.1M | 414.1 M | 857.6 M |
ckb | 622.7K | 148.9K | 5.6M | 2.5M | 312.7M | 83.3M | 2.2B | 572.7M | 265.0 M | 1011.1 M |
lb | 7.6M | 146K | 47.1M | 3.4M | 7.5B | 85M | 58.4B | 575.5M | 218.4 M | 22.2 G |
mg | 295.2K | 115.4K | 4.5M | 2.6M | 189.4M | 75.5M | 1.3B | 548.5M | 179.0 M | 429.3 M |
ht | 425.6K | 110.4K | 6.7M | 2.6M | 163M | 84.3M | 994.5M | 461.5M | 168.2 M | 361.5 M |
ug | 227.1K | 106.5K | 4.5M | 3.1M | 122.9M | 62.7M | 998.5M | 504.6M | 233.1 M | 449.9 M |
am | 245.2K | 106.3K | 7.1M | 5.3M | 157M | 95.2M | 869.9M | 509M | 345.5 M | 539.4 M |
or | 139.6K | 100.5K | 139.6K | 3.1M | 66M | 47.3M | 437.2M | 309.5M | 160.3 M | 228.1 M |
fo | 382.9K | 97.8K | 3.9M | 1.8M | 136.5M | 48.9M | 923.3M | 314.9M | 122.0 M | 328.8 M |
gd | 206K | 94.3K | 3.7M | 2.4M | 127.6M | 84.5M | 812M | 526M | 173.4 M | 276.6 M |
ba | 372.4K | 90.3K | 9.3M | 2.6M | 101M | 42.1M | 766.5M | 320.7M | 154.8 M | 352.4 M |
tk | 180.2K | 82.5K | 180.2K | 1.8M | 65.4M | 43.3M | 575.2M | 369M | 131.3 M | 221.6 M |
mi | 711.9K | 79.5K | 5.9M | 1.9M | 262.5M | 73.5M | 1.6B | 371.9M | 120.2 M | 539.1 M |
hmn | 241.3K | 75.2K | 3.5M | 1.9M | 192.1M | 80.2M | 1.2B | 408.8M | 124.3 M | 366.0 M |
grc | 364.8K | 70.7K | 13.7M | 2.8M | 298.6M | 65.3M | 2B | 417.8M | 217.7 M | 1.0 G |
jv | 999.5K | 69.5K | 13M | 2M | 302.3M | 52.1M | 2.3B | 376.1M | 130.9 M | 797.8 M |
ceb | 617.5K | 66.2K | 6.7M | 1.6M | 225M | 58.2M | 1.5B | 357.7M | 116.2 M | 451.4 M |
sd | 115.6K | 65.9K | 115.6K | 2.4M | 112.6M | 77.8M | 561M | 380.4M | 182.3 M | 267.1 M |
yi | 160.6K | 64.9K | 3.3M | 1.9M | 129.1M | 53.9M | 838.4M | 352.6M | 146.0 M | 350.8 M |
kaa_Latn | 375.2K | 61.2K | 3.6M | 1.3M | 375.2K | 61.2K | 1.5M | 209.5K | 86.2 M | 264.6 M |
sn | 3.1M | 60.2K | 3.1M | 1.2M | 1.3B | 31.6M | 10.6B | 266M | 92.5 M | 3.2 G |
co | 546.7K | 55.4K | 6.1M | 1.3M | 172.6M | 43.6M | 1.1B | 265.5M | 98.8 M | 386.8 M |
su | 336.6K | 55K | 336.6K | 1.6M | 154M | 39.5M | 967.2M | 286.7M | 100.7 M | 308.5 M |
pap | 259.1K | 54.5K | 259.1K | 1.4M | 183.9M | 41.1M | 1.4B | 229.9M | 83.5 M | 451.4 M |
ig | 130.4K | 54.4K | 2.1M | 1.4M | 129.2M | 45.7M | 846.1M | 251.4M | 93.0 M | 178.9 M |
zu | 372.3K | 53.8K | 3.8M | 1.2M | 148.4M | 27.2M | 1.2B | 257.4M | 89.6 M | 374.7 M |
xh | 310.9K | 53.7K | 2.9M | 1.4M | 81.6M | 31.2M | 749.5M | 287.3M | 100.0 M | 319.1 M |
sm | 137.8K | 52.6K | 1.9M | 1.3M | 100.9M | 53.7M | 607.9M | 276.3M | 88.6 M | 184.5 M |
ny | 181.6K | 52.2K | 181.6K | 1.5M | 80.6M | 34.8M | 611.2M | 277.5M | 91.8 M | 209.8 M |
yo | 115K | 52.1K | 2M | 1.2M | 76.6M | 46.3M | 415.6M | 239M | 89.2 M | 157.8 M |
cv | 599.4K | 47.3K | 12M | 1.6M | 169.6M | 22.2M | 1B | 168.9M | 82.1 M | 413.6 M |
el_Latn | 497.3K | 46.4K | 11.3M | 1.7M | 497.3K | 46.4K | 2.3M | 162.8K | 196.8 M | 571.1 M |
kl | 85.9K | 46K | 2.1M | 1.5M | 32.3M | 22.3M | 403.9M | 279.1M | 84.2 M | 126.1 M |
haw | 310.4K | 45.7K | 7.1M | 1M | 141M | 43.3M | 892M | 214.2M | 69.9 M | 271.2 M |
gsw | 7.6M | 42.7K | 64.5M | 1M | 5B | 22.3M | 42.3B | 149.2M | 53.8 M | 13.5 G |
tet | 291K | 40.4K | 1.9M | 475.7K | 240.6M | 22.8M | 1.6B | 152.3M | 51.2 M | 455.4 M |
st | 96.8K | 40.4K | 96.8K | 1.1M | 65M | 39.8M | 381.5M | 226.9M | 74.0 M | 127.0 M |
lus | 91.5K | 36.4K | 1.4M | 863.5K | 53M | 31.3M | 298.3M | 167.3M | 60.1 M | 107.0 M |
oc | 2.4M | 36.4K | 2.4M | 1.6M | 887.6M | 26.7M | 6.7B | 177.6M | 58.7 M | 1.9 G |
as | 53.9K | 33.8K | 2.4M | 1.7M | 41.4M | 27.9M | 275.8M | 182.1M | 95.8 M | 146.1 M |
rm | 238.1K | 33.8K | 238.1K | 603.4K | 59.2M | 15.8M | 391M | 100.2M | 34.6 M | 133.1 M |
br | 705.4K | 33.2K | 7.8M | 731.7K | 646.8M | 21M | 3.7B | 125.4M | 46.2 M | 1.2 G |
sah | 1.3M | 29.2K | 1.3M | 1.2M | 283.7M | 17.6M | 2.2B | 148.2M | 68.3 M | 852.3 M |
hi_Latn | 1.2M | 26.7K | 22.6M | 1.2M | 1.2M | 26.7K | 5.3M | 98.9K | 53.5 M | 1.7 G |
se | 54.3K | 23.9K | 879.5K | 493.3K | 17.7M | 10M | 148.4M | 84.6M | 31.1 M | 56.6 M |
cnh | 44.4K | 21.6K | 688.6K | 406.9K | 21.6M | 12.5M | 110.8M | 63M | 22.1 M | 39.6 M |
om | 846.1K | 18.9K | 846.1K | 469.8K | 238M | 11.2M | 1.9B | 88.5M | 30.4 M | 881.5 M |
ce | 59.3K | 15K | 991.1K | 460.1K | 17.8M | 9.6M | 130.6M | 67.8M | 31.1 M | 60.2 M |
udm | 67.1K | 13.4K | 942.7K | 510.3K | 14M | 7.4M | 106M | 55.5M | 26.3 M | 49.2 M |
lg | 61.1K | 13K | 510.9K | 166.1K | 21.4M | 6.1M | 160.7M | 48M | 17.3 M | 56.7 M |
os | 172.1K | 12.6K | 172.1K | 359.3K | 27.1M | 6.9M | 233.5M | 50.1M | 23.1 M | 87.7 M |
nv | 17.1K | 12.6K | 17.1K | 86.5K | 3.1M | 1.1M | 24.8M | 9.1M | 2.0 M | 7.9 M |
kha | 37.8K | 12.1K | 235.5K | 75.2K | 15.8M | 6M | 88.6M | 30.2M | 9.8 M | 27.3 M |
ilo | 69.8K | 11.8K | 889.2K | 365.1K | 26.7M | 9M | 187.9M | 59.4M | 20.6 M | 64.0 M |
ctd_Latn | 23.3K | 11.6K | 575.6K | 382.2K | 23.3K | 11.6K | 90.7K | 41K | 21.5 M | 35.1 M |
vec | 1.1M | 11.1K | 10M | 209.7K | 284.7M | 7.8M | 1.8B | 43.8M | 17.7 M | 625.0 M |
hil | 126.8K | 10.6K | 1.1M | 379.7K | 43.9M | 9.2M | 293.5M | 57.2M | 18.5 M | 95.2 M |
tyv | 61.6K | 9.1K | 596.6K | 268.3K | 9.9M | 4.7M | 80.2M | 38.5M | 16.7 M | 36.6 M |
iba | 34K | 7.6K | 326.9K | 126.1K | 37.8M | 4.8M | 251.4M | 30.5M | 10.0 M | 61.3 M |
ru_Latn | 346.3K | 7.5K | 346.3K | 239.1K | 346.3K | 7.5K | 1.5M | 27.7K | 14.9 M | 452.3 M |
kbd | 154.7K | 7.5K | 1.4M | 257.2K | 31.9M | 4.4M | 321.4M | 36.8M | 16.8 M | 209.6 M |
ti | 20.8K | 7.3K | 20.8K | 481.3K | 18.2M | 8.8M | 95.4M | 44.6M | 30.9 M | 63.6 M |
sa | 154.3K | 7.1K | 154.3K | 1.1M | 70M | 9.9M | 512.5M | 88.8M | 44.9 M | 236.6 M |
av | 107.6K | 6.3K | 806.1K | 190.1K | 15.5M | 3.4M | 129M | 30.2M | 12.8 M | 56.0 M |
bo | 6.2K | 6.2K | 1.1M | 1.1M | 3.4M | 3.4M | 88.7M | 88.7M | 40.7 M | 40.7 M |
zza | 370.1K | 6K | 3.3M | 229.2K | 87.7M | 3.9M | 617.3M | 26.3M | 10.0 M | 234.1 M |
ber_Latn | 480.5K | 5.6K | 10.5M | 169.4K | 480.5K | 5.6K | 2.1M | 18.9K | 11.0 M | 945.3 M |
otq | 17.6K | 5.6K | 17.6K | 114.8K | 10.2M | 3.8M | 65M | 23.4M | 7.7 M | 22.8 M |
te_Latn | 236.6K | 5.3K | 4.4M | 269.1K | 236.6K | 5.3K | 1M | 19.3K | 11.4 M | 254.3 M |
bua | 9.8K | 5.3K | 252K | 144.6K | 4.7M | 2.7M | 38M | 21.7M | 10.0 M | 17.9 M |
ts | 34.7K | 5.2K | 34.7K | 248.6K | 39.6M | 6.5M | 377.2M | 38.8M | 12.2 M | 99.5 M |
cfm | 9.1K | 4.9K | 199.6K | 128.6K | 6.2M | 4M | 32.9M | 21.5M | 7.4 M | 11.6 M |
tn | 138.2K | 4.8K | 138.2K | 174.4K | 46M | 5.5M | 302.3M | 29.2M | 9.4 M | 99.0 M |
krc | 359.5K | 4.8K | 2.3M | 153.9K | 50.2M | 2.6M | 369.5M | 20.7M | 9.1 M | 139.9 M |
ak | 19.5K | 4.8K | 341.7K | 210.2K | 12.3M | 4.7M | 74.5M | 24.8M | 9.1 M | 24.7 M |
meo | 790.7K | 4.7K | 16.5M | 39K | 478M | 1.2M | 3B | 7.5M | 3.1 M | 1.2 G |
chm | 81.5K | 4.7K | 929.1K | 179.7K | 17.2M | 2.9M | 132.2M | 21.3M | 9.8 M | 53.5 M |
to | 14.3K | 4.6K | 14.3K | 149K | 10.3M | 5.7M | 58.2M | 29.9M | 9.6 M | 19.0 M |
ee | 14.1K | 4.5K | 353.6K | 246.7K | 9.7M | 6.2M | 67.9M | 32.8M | 11.8 M | 23.3 M |
nso | 376.2K | 4.4K | 376.2K | 188.4K | 419.2M | 5.3M | 2B | 28.2M | 9.1 M | 502.7 M |
ady | 74.9K | 4.2K | 446.8K | 96.9K | 8M | 1.6M | 67.9M | 14.8M | 6.4 M | 30.6 M |
rom | 22.9K | 4.2K | 22.9K | 76.1K | 8.9M | 2.6M | 59M | 15.9M | 5.8 M | 21.0 M |
bho | 13.6K | 4.1K | 306.2K | 118.5K | 7.1M | 2.7M | 37.6M | 13.4M | 7.4 M | 20.6 M |
ltg | 13.1K | 4.1K | 213.7K | 87.3K | 4M | 1.9M | 29.2M | 13.9M | 5.6 M | 11.7 M |
fj | 17K | 4K | 410K | 164.1K | 11.6M | 5.2M | 67.7M | 28M | 8.6 M | 22.5 M |
yua | 10.4K | 4K | 141.6K | 77.6K | 5.2M | 2.5M | 36.8M | 17.2M | 5.7 M | 12.4 M |
gn | 87.1K | 3.9K | 770.9K | 162.6K | 19.2M | 2.7M | 140.7M | 20.8M | 7.8 M | 52.1 M |
az_RU | 6.5K | 3.8K | 231.8K | 177.3K | 6.5K | 3.8K | 24K | 12.9K | 10.3 M | 15.1 M |
ln | 94.7K | 3.3K | 718.7K | 139K | 42.4M | 3.4M | 291.8M | 21.5M | 6.8 M | 85.3 M |
ada | 6.5K | 3.1K | 291.5K | 199.2K | 7.5M | 4.9M | 38.9M | 24.2M | 8.6 M | 13.9 M |
myv | 164.8K | 3.1K | 164.8K | 130K | 16M | 1.7M | 120.3M | 13.8M | 6.2 M | 49.5 M |
bik | 44.8K | 3.1K | 376.7K | 77K | 14.8M | 2.5M | 102.3M | 15.7M | 5.3 M | 34.0 M |
tlh | 516.9K | 3.1K | 516.9K | 46.9K | 221.3M | 1.1M | 1.4B | 7.8M | 2.7 M | 554.2 M |
kbp | 5.9K | 3K | 247.9K | 128.3K | 5.6M | 2.6M | 30.8M | 14.6M | 5.7 M | 12.4 M |
war | 1M | 2.9K | 114M | 96.2K | 612.1M | 2.4M | 3.5B | 16.1M | 3.7 M | 1.2 G |
wa | 70.6K | 2.8K | 1.5M | 127.2K | 35.2M | 3.6M | 198.8M | 20.4M | 7.2 M | 67.8 M |
bew | 311.1K | 2.7K | 10.4M | 58.4K | 212.4M | 1.3M | 1.4B | 8.5M | 3.1 M | 547.1 M |
rcf | 21.6K | 2.6K | 21.6K | 50.5K | 4.9M | 1.2M | 30.2M | 5.7M | 2.1 M | 11.4 M |
ta_Latn | 260.7K | 2.6K | 3.4M | 142.7K | 260.7K | 2.6K | 1.2M | 9.1K | 5.0 M | 215.4 M |
kac | 5.9K | 2.6K | 109.2K | 77.4K | 5M | 2.8M | 26.6M | 13.6M | 4.3 M | 8.0 M |
iu | 5.4K | 2.5K | 92.6K | 53.1K | 1.9M | 907.4K | 17.5M | 8.3M | 4.8 M | 9.9 M |
ay | 8.1K | 2.5K | 196.7K | 83.8K | 3.9M | 1.4M | 34.5M | 13.1M | 4.5 M | 12.7 M |
kum | 4.2K | 2.5K | 132.2K | 89.7K | 2.3M | 1.6M | 18.2M | 12.4M | 5.3 M | 8.0 M |
qu | 149.7K | 2.4K | 1M | 87K | 26.7M | 1.3M | 200.6M | 12.2M | 4.0 M | 68.3 M |
bgp | 355.7K | 2.4K | 5.6M | 43.3K | 186.1M | 1.8M | 1.1B | 9.8M | 3.1 M | 377.5 M |
hif | 702K | 2.4K | 7.9M | 124.7K | 1.2B | 3.2M | 9.1B | 19.1M | 5.9 M | 3.5 G |
kw | 176.9K | 2.3K | 1M | 51.6K | 53.1M | 1.3M | 327.8M | 7.7M | 2.8 M | 89.2 M |
nan_Latn_TW | 7.4K | 2.3K | 7.4K | 72.7K | 7.4K | 2.3K | 28.3K | 7.7K | 4.8 M | 15.4 M |
srn | 16.7K | 2.3K | 16.7K | 139.5K | 8M | 3.4M | 49.1M | 17M | 5.1 M | 15.6 M |
tly_IR | 406.3K | 2.2K | 406.3K | 18.2K | 406.3K | 2.2K | 1.6M | 8.6K | 580.4 K | 283.0 M |
sg | 4.2K | 2.1K | 154K | 117.9K | 4.6M | 3.3M | 22.6M | 15.5M | 4.6 M | 6.8 M |
gom | 4.6K | 2.1K | 178.3K | 108K | 2.7M | 1.4M | 19.8M | 10M | 5.0 M | 10.5 M |
ml_Latn | 260.8K | 2.1K | 3.5M | 77.3K | 260.8K | 2.1K | 1.1M | 7.2K | 3.5 M | 277.7 M |
kj | 112.2K | 2.1K | 881.8K | 22.6K | 46.9M | 877.3K | 339.6M | 6M | 2.1 M | 104.9 M |
ksd | 14.9K | 2K | 533K | 78.6K | 11.5M | 2.1M | 62.4M | 10M | 2.9 M | 20.0 M |
dz | 1.9K | 1.9K | 191.7K | 191.7K | 1.1M | 1.1M | 22.7M | 22.7M | 10.0 M | 10.0 M |
kv | 59.1K | 1.9K | 584.3K | 88.8K | 9.5M | 1.2M | 91.4M | 9M | 4.4 M | 41.0 M |
msi | 686.7K | 1.9K | 686.7K | 22.6K | 414.8M | 440.4K | 2.6B | 2.7M | 1.1 M | 1.0 G |
ve | 3.8K | 1.9K | 97.8K | 79.4K | 3.2M | 2.1M | 19M | 11.7M | 3.8 M | 6.2 M |
zap | 5.5K | 1.8K | 202.3K | 93.5K | 4.2M | 1.8M | 26.4M | 11.4M | 4.0 M | 9.6 M |
zxx_xx_dtynoise | 118.8K | 1.8K | 3.8M | 49.3K | 118.8K | 1.8K | 501K | 6.6K | 3.9 M | 367.0 M |
meu | 5.9K | 1.7K | 232.1K | 72.6K | 4.2M | 1.4M | 27.2M | 8.6M | 2.6 M | 9.1 M |
iso | 3.7K | 1.7K | 155.8K | 111.5K | 4.4M | 2.7M | 23M | 13.7M | 4.9 M | 8.1 M |
ium | 100.3K | 1.7K | 6.2M | 54.9K | 48.4M | 1.7M | 314M | 7.4M | 2.6 M | 124.0 M |
nhe | 3K | 1.7K | 3K | 57.7K | 1.9M | 1.2M | 15.6M | 9.8M | 2.7 M | 4.8 M |
tyz | 8K | 1.7K | 454.8K | 104.6K | 7.5M | 1.9M | 46.3M | 11.3M | 3.8 M | 16.0 M |
hui | 2K | 1.7K | 80.1K | 74.7K | 1.8M | 1.7M | 11.8M | 10.9M | 3.0 M | 3.3 M |
new | 6.6K | 1.6K | 6.6K | 85K | 3.2M | 1.4M | 21.2M | 8.8M | 4.4 M | 10.6 M |
mdf | 71K | 1.6K | 394.7K | 45.1K | 8.3M | 670.1K | 65.8M | 5.5M | 2.5 M | 26.7 M |
pag | 49.6K | 1.6K | 49.6K | 88.8K | 13.8M | 1.9M | 92.9M | 12M | 3.9 M | 29.2 M |
gv | 501.9K | 1.6K | 18.8M | 26.9K | 137.7M | 996.2K | 933.1M | 6.2M | 2.0 M | 318.6 M |
gag | 33.9K | 1.6K | 491K | 37K | 10.2M | 661K | 84.9M | 5.2M | 2.1 M | 32.6 M |
ngu | 3.8K | 1.5K | 3.8K | 87.1K | 2.7M | 1.5M | 21.4M | 11.8M | 3.6 M | 6.7 M |
quc | 4.4K | 1.5K | 89.2K | 41.2K | 2.8M | 1.1M | 16.6M | 6.4M | 2.2 M | 5.9 M |
mam | 23K | 1.5K | 446.3K | 52.9K | 9.8M | 1.2M | 70.4M | 7.2M | 2.6 M | 30.7 M |
min | 28.2K | 1.5K | 500.9K | 75.6K | 10.2M | 1.4M | 70.5M | 9.9M | 2.6 M | 21.1 M |
ho | 2K | 1.5K | 57K | 47.8K | 1.8M | 1.3M | 12.3M | 7.8M | 1.9 M | 3.1 M |
pon | 5.7K | 1.5K | 167.8K | 48.7K | 3M | 1.1M | 18.3M | 6.7M | 2.1 M | 6.1 M |
mrj | 97.1K | 1.4K | 97.1K | 60.3K | 14.5M | 1.1M | 100.6M | 7.6M | 3.6 M | 40.8 M |
lu | 10.6K | 1.4K | 316K | 112.1K | 7.8M | 2.3M | 54.2M | 15.4M | 4.8 M | 18.0 M |
gom_Latn | 231.1K | 1.4K | 4.1M | 77.9K | 231.1K | 1.4K | 1M | 5.1K | 3.6 M | 240.6 M |
alt | 2.6K | 1.4K | 110.1K | 65.9K | 1.8M | 1.1M | 14.3M | 8.7M | 3.8 M | 6.4 M |
nzi | 2.5K | 1.4K | 2.5K | 71.8K | 2.5M | 1.7M | 14.4M | 9.4M | 3.1 M | 4.8 M |
tzo | 2.8K | 1.4K | 100.4K | 75.7K | 2.5M | 1.7M | 15.9M | 10.6M | 3.2 M | 4.9 M |
bci | 7.4K | 1.3K | 124.8K | 87.1K | 5M | 1.9M | 32.8M | 9M | 3.1 M | 9.4 M |
dtp | 4.6K | 1.3K | 51.2K | 7.9K | 1.9M | 419.4K | 12.7M | 3M | 1013.9 K | 4.5 M |
abt | 1.6K | 1.3K | 122.7K | 110.3K | 1.5M | 1.3M | 9.6M | 8.2M | 2.2 M | 2.7 M |
bbc | 72.3K | 1.3K | 718.3K | 73.2K | 21.7M | 1.7M | 151.3M | 10.6M | 3.6 M | 47.9 M |
pck | 8.9K | 1.3K | 8.9K | 69.7K | 6.8M | 2.1M | 39.8M | 11.5M | 4.2 M | 14.2 M |
mai | 54.3K | 1.2K | 1M | 60.2K | 24.6M | 1.2M | 156M | 6.8M | 3.6 M | 67.1 M |
mps | 2.7K | 1.2K | 132.8K | 71.9K | 2.8M | 1.6M | 16M | 8.7M | 2.3 M | 4.8 M |
emp | 3.6K | 1.2K | 106.4K | 75.4K | 1.9M | 999.1K | 14.5M | 7.4M | 2.4 M | 4.9 M |
mgh | 5.5K | 1.2K | 151.8K | 61.2K | 2.8M | 1.1M | 24.1M | 8.2M | 2.8 M | 8.3 M |
tab | 7.8K | 1.2K | 226.4K | 26.8K | 4.3M | 538.9K | 33.7M | 4.4M | 1.9 M | 15.7 M |
crh | 5.1K | 1.2K | 170.9K | 61.8K | 2.4M | 943K | 18.8M | 7.5M | 3.4 M | 8.9 M |
tbz | 5.1K | 1.1K | 128.7K | 37.5K | 3.5M | 893.4K | 22M | 4.8M | 1.9 M | 10.2 M |
ss | 8.1K | 1.1K | 8.1K | 30.4K | 2.7M | 568.3K | 23.7M | 5.5M | 1.8 M | 7.4 M |
chk | 2.8K | 1.1K | 98.8K | 44K | 2M | 1M | 12M | 5.8M | 1.8 M | 4.0 M |
bru | 3K | 1.1K | 89.7K | 48.2K | 2.4M | 938.1K | 12.9M | 4.8M | 1.5 M | 4.5 M |
nnb | 4.9K | 1.1K | 4.9K | 70.2K | 3.2M | 1.2M | 27.7M | 9.1M | 3.3 M | 10.0 M |
fon | 5.3K | 1.1K | 222.9K | 67.3K | 6.9M | 1.8M | 34M | 8.3M | 3.1 M | 14.8 M |
ppk | 2.6K | 1.1K | 85.8K | 34.9K | 1.9M | 801.8K | 13.2M | 5.5M | 1.6 M | 4.3 M |
tiv | 3.8K | 1.1K | 3.8K | 80.7K | 3.7M | 2.1M | 20.4M | 10.2M | 3.2 M | 6.0 M |
btx | 3.1K | 1K | 81.7K | 43.9K | 2M | 907.5K | 13.1M | 5.9M | 2.0 M | 4.6 M |
bg_Latn | 200.4K | 991 | 2.8M | 25.5K | 200.4K | 991 | 927.1K | 3.7K | 1.7 M | 143.6 M |
mbt | 1.6K | 969 | 86K | 45.4K | 2.4M | 1.3M | 14.6M | 7.5M | 2.2 M | 5.1 M |
ace | 65.5K | 966 | 632.5K | 32.5K | 19.9M | 1.1M | 146.1M | 7.4M | 2.2 M | 42.3 M |
tvl | 2.3K | 933 | 72.9K | 53.6K | 2.5M | 1.7M | 12.6M | 8.1M | 2.4 M | 3.8 M |
dov | 3.5K | 923 | 129.8K | 56.7K | 2.6M | 967.5K | 20.7M | 8M | 2.6 M | 7.1 M |
ach | 2K | 915 | 63K | 40.1K | 1.6M | 890.9K | 9M | 4.7M | 1.6 M | 3.0 M |
xal | 71.8K | 913 | 498.5K | 30.8K | 8.5M | 449.8K | 64.7M | 3.2M | 1.5 M | 24.4 M |
cuk | 4.1K | 899 | 76.5K | 34.3K | 2M | 469.9K | 24.7M | 4.6M | 1.5 M | 6.1 M |
kos | 2.2K | 881 | 44.6K | 27.8K | 1.1M | 780.1K | 6.5M | 4.2M | 1.4 M | 2.2 M |
crs | 7.6K | 873 | 282.4K | 40.1K | 7.3M | 1.2M | 40.1M | 6.8M | 2.2 M | 13.2 M |
wo | 36.4K | 871 | 303.4K | 25.4K | 30.7M | 850.7K | 213.4M | 4.5M | 1.7 M | 59.9 M |
bts | 3.2K | 869 | 109.1K | 29.1K | 3.1M | 663.3K | 20.8M | 4.2M | 1.4 M | 6.2 M |
ubu | 2.2K | 846 | 113.5K | 47.5K | 2.3M | 996.4K | 15.9M | 6.7M | 1.9 M | 4.7 M |
gym | 1.5K | 820 | 73.7K | 49.6K | 1.6M | 1.1M | 10.3M | 6.9M | 2.0 M | 3.2 M |
ibb | 74.1K | 818 | 516.5K | 36.3K | 26.4M | 776.1K | 190.9M | 4.9M | 1.5 M | 56.0 M |
ape | 7K | 814 | 147K | 56.1K | 12.4M | 881.5K | 71M | 5.8M | 1.6 M | 18.8 M |
stq | 111.9K | 809 | 111.9K | 27.7K | 34.4M | 600.4K | 243.1M | 3.8M | 1.5 M | 82.5 M |
ang | 66.5K | 803 | 1.8M | 86.7K | 28.5M | 1.7M | 193M | 9.8M | 3.4 M | 67.1 M |
enq | 7.1K | 793 | 241.9K | 39.1K | 11M | 718.8K | 68.5M | 4.8M | 1.3 M | 18.8 M |
tsg | 353.8K | 789 | 353.8K | 17.9K | 158M | 588.9K | 1.1B | 3.8M | 1.0 M | 309.9 M |
shn | 889 | 788 | 46.4K | 46.2K | 383.8K | 378.5K | 5.7M | 5.7M | 2.6 M | 2.6 M |
kri | 39.1K | 786 | 271.2K | 38.8K | 12.6M | 995.2K | 86.4M | 5M | 1.6 M | 20.9 M |
kek | 3.2K | 782 | 70.4K | 38.4K | 1.8M | 709K | 13.6M | 4.4M | 1.4 M | 4.7 M |
rmc | 2.4K | 738 | 2.4K | 25.8K | 1.3M | 545.4K | 7.9M | 3.2M | 1.1 M | 2.9 M |
acf | 4.9K | 730 | 81.9K | 24.6K | 2.1M | 602.2K | 11.6M | 3M | 1.1 M | 4.7 M |
fip | 3.7K | 729 | 165.6K | 49K | 3.5M | 916.8K | 25.7M | 6.6M | 2.1 M | 8.6 M |
syr | 3.5K | 716 | 326.4K | 197.1K | 4.6M | 1.9M | 31.5M | 14M | 6.1 M | 13.9 M |
qub | 972 | 705 | 61K | 51.1K | 589.2K | 455.5K | 5.9M | 4.4M | 1.4 M | 1.8 M |
bm | 21.9K | 702 | 172.3K | 24.5K | 7.1M | 583.1K | 48.4M | 3M | 1.1 M | 14.4 M |
tzh | 1.7K | 702 | 41.7K | 33.9K | 1.5M | 929.6K | 9.3M | 5.6M | 1.6 M | 2.6 M |
jiv | 1.7K | 696 | 80.9K | 32K | 1.1M | 418.9K | 9.6M | 3.5M | 1.1 M | 3.3 M |
kn_Latn | 72.9K | 688 | 765.9K | 10.1K | 72.9K | 688 | 328.1K | 2.5K | 430.8 K | 61.4 M |
kjh | 1.5K | 672 | 42.8K | 28.7K | 566.1K | 379.2K | 4.5M | 3.1M | 1.3 M | 2.0 M |
yap | 1.9K | 638 | 37.6K | 19.5K | 1.3M | 661.4K | 6.9M | 3.3M | 1.0 M | 2.2 M |
ban | 8K | 637 | 150.9K | 16.3K | 5M | 499.7K | 35.4M | 3.6M | 1.1 M | 12.0 M |
tuc | 3.5K | 635 | 193.2K | 50.3K | 2.9M | 703K | 17.2M | 4.1M | 1.2 M | 5.7 M |
tcy | 10.7K | 632 | 338.7K | 37.1K | 5.5M | 432.6K | 41.6M | 3.3M | 1.7 M | 20.9 M |
cab | 1.2K | 629 | 50.4K | 37.5K | 1M | 690.9K | 7.5M | 5.1M | 1.6 M | 2.4 M |
cak | 1.2K | 617 | 70.4K | 32.6K | 1.3M | 730.1K | 7.6M | 4.2M | 1.3 M | 2.4 M |
din | 128.4K | 611 | 885.8K | 23.6K | 31.6M | 541.7K | 210M | 2.9M | 1.1 M | 64.3 M |
zh_Latn | 739.4K | 602 | 10.7M | 45.1K | 739.4K | 602 | 3.4M | 2.3K | 2.0 M | 969.9 M |
arn | 2.4K | 593 | 64.5K | 26.2K | 1.5M | 541.9K | 10.2M | 3.7M | 1.2 M | 3.7 M |
lrc | 42.4K | 587 | 351.9K | 9K | 17.3M | 248.9K | 85.3M | 1.4M | 646.9 K | 37.5 M |
rwo | 938 | 572 | 938 | 45.5K | 734.8K | 590.4K | 5.1M | 4.2M | 1.1 M | 1.4 M |
hus | 825 | 569 | 26.5K | 23.7K | 733.4K | 542.1K | 4.4M | 3.1M | 967.6 K | 1.3 M |
bum | 4.7K | 559 | 103.8K | 36.5K | 3M | 805.5K | 18.8M | 4M | 1.3 M | 6.1 M |
mak | 1K | 555 | 32.5K | 20.4K | 761K | 457.4K | 6.1M | 3.7M | 1.1 M | 2.0 M |
frp | 148K | 550 | 3.5M | 8.2K | 71.2M | 230.2K | 535.4M | 1.4M | 518.3 K | 129.7 M |
seh | 5.6K | 545 | 68.8K | 37.2K | 2M | 650.6K | 14.9M | 4.9M | 1.5 M | 4.4 M |
twu | 2.5K | 539 | 109.9K | 24.4K | 2.4M | 571.2K | 14.2M | 3.2M | 1.0 M | 4.8 M |
kmb | 1.3K | 538 | 60.4K | 36.9K | 1.4M | 810.8K | 8.4M | 4.6M | 1.4 M | 2.6 M |
ksw | 560 | 536 | 16.1K | 16K | 219.9K | 218.8K | 2.9M | 2.9M | 1.4 M | 1.4 M |
sja | 1.3K | 527 | 67.7K | 24.9K | 982.5K | 459.3K | 7.7M | 3.4M | 1.1 M | 2.6 M |
amu | 1.8K | 511 | 72K | 25.2K | 1.5M | 443.3K | 9.6M | 3.2M | 1.0 M | 3.4 M |
mad | 103.8K | 509 | 500.6K | 18.5K | 16.2M | 386.7K | 111.8M | 2.8M | 960.3 K | 34.2 M |
quh | 1K | 501 | 42K | 29.9K | 624.4K | 396.8K | 5.8M | 3.7M | 1.2 M | 1.8 M |
dyu | 1.2K | 483 | 55.8K | 19.7K | 1.2M | 421.8K | 5.7M | 2M | 665.5 K | 1.9 M |
toj | 736 | 452 | 736 | 26.1K | 691.2K | 540.2K | 4.3M | 3.3M | 1.0 M | 1.3 M |
ch | 12.9K | 449 | 147.5K | 16K | 8.9M | 393.9K | 63.5M | 2.5M | 906.8 K | 10.0 M |
sus | 664 | 437 | 664 | 15.2K | 648K | 402.8K | 3.7M | 2.1M | 674.0 K | 1.0 M |
nog | 970 | 419 | 970 | 11K | 330.3K | 200.4K | 2.6M | 1.6M | 714.0 K | 1.2 M |
jam | 12.7K | 416 | 68.5K | 15.8K | 3.5M | 378.4K | 25.8M | 1.7M | 609.5 K | 7.6 M |
gui | 1.1K | 409 | 62.7K | 24.8K | 915K | 314K | 6.5M | 2M | 619.3 K | 2.1 M |
nia | 2K | 408 | 2K | 25K | 1.7M | 476.5K | 11.3M | 3.1M | 1.0 M | 3.9 M |
mas | 15.2K | 405 | 216.8K | 17.6K | 6.2M | 390.1K | 42.1M | 3M | 927.5 K | 13.4 M |
bzj | 983 | 404 | 33.6K | 26.4K | 824.3K | 565K | 4.5M | 2.9M | 981.2 K | 1.4 M |
mkn | 956 | 402 | 33.1K | 25.4K | 584.2K | 456.9K | 3.4M | 2.6M | 734.8 K | 1.0 M |
lhu | 46K | 377 | 975K | 15.7K | 29.1M | 441.2K | 208.6M | 2.5M | 623.0 K | 38.8 M |
ctu | 690 | 366 | 35.5K | 20.6K | 646.7K | 352.8K | 3.6M | 2M | 614.9 K | 1.2 M |
kg | 4.7K | 365 | 85.5K | 21.7K | 2.5M | 406.7K | 16.6M | 2.6M | 905.4 K | 5.7 M |
inb | 387 | 343 | 17.3K | 17K | 202.8K | 197K | 2M | 1.9M | 535.2 K | 555.6 K |
guh | 1.9K | 331 | 104.9K | 28.4K | 1.5M | 328.4K | 11.2M | 3M | 789.5 K | 3.5 M |
rn | 8.2K | 323 | 8.2K | 11.1K | 4.5M | 179K | 33.2M | 1.3M | 449.9 K | 11.8 M |
bus | 467 | 322 | 21.4K | 12.1K | 418.4K | 219.2K | 2.1M | 1.1M | 428.8 K | 830.9 K |
mfe | 7.5K | 320 | 198.8K | 18.2K | 4.6M | 374.8K | 26.9M | 2.1M | 716.4 K | 10.1 M |
sda | 1.6K | 317 | 43.2K | 6.2K | 2.5M | 218.3K | 15.8M | 1.6M | 529.0 K | 4.7 M |
bi | 71.9K | 311 | 308.5K | 13.6K | 19.4M | 359.4K | 132.4M | 1.9M | 546.9 K | 42.6 M |
cr_Latn | 19K | 303 | 170K | 8.9K | 19K | 303 | 81.8K | 1K | 590.4 K | 15.0 M |
gor | 1.7K | 303 | 53.3K | 6.5K | 1.4M | 227.1K | 9.4M | 1.7M | 494.0 K | 3.1 M |
jac | 8.2K | 303 | 61.6K | 11.9K | 1.8M | 271K | 15.7M | 1.7M | 530.3 K | 7.3 M |
chr | 964 | 301 | 33.8K | 7.5K | 629.9K | 172.3K | 4.7M | 1M | 564.1 K | 2.1 M |
mh | 4.6K | 296 | 235.1K | 13K | 3.6M | 393.5K | 24.9M | 2.2M | 778.4 K | 8.4 M |
mni | 1.2K | 290 | 38.1K | 13.2K | 841.3K | 245.5K | 6.4M | 1.8M | 866.6 K | 3.0 M |
wal | 2.6K | 286 | 128K | 14K | 2M | 203.4K | 17M | 1.7M | 525.7 K | 5.1 M |
teo | 2.8K | 274 | 131.5K | 13.7K | 2.3M | 221.4K | 15.3M | 1.6M | 564.9 K | 5.3 M |
gub | 31.7K | 271 | 160.4K | 25K | 4.7M | 286.2K | 44.7M | 1.6M | 431.3 K | 23.1 M |
qvi | 1.2K | 266 | 48.4K | 19.3K | 720.4K | 248.9K | 6.5M | 2.3M | 641.2 K | 1.9 M |
tdx | 1.7K | 262 | 26.3K | 13.2K | 1M | 238.5K | 7M | 1.6M | 503.6 K | 2.1 M |
rki | 331 | 251 | 331 | 7.8K | 119.7K | 113.7K | 1.6M | 1.5M | 751.3 K | 781.8 K |
djk | 560 | 246 | 30.9K | 24.4K | 669.5K | 455.6K | 3.7M | 2.2M | 644.3 K | 1.0 M |
nr | 10.7K | 246 | 10.7K | 11.3K | 5.3M | 162.5K | 49M | 1.5M | 519.7 K | 17.8 M |
zne | 1.3K | 239 | 61.9K | 21.3K | 1.4M | 504.6K | 8.2M | 2.8M | 882.3 K | 2.8 M |
izz | 423 | 237 | 21.7K | 14.5K | 382.8K | 194.5K | 2.1M | 1.1M | 382.2 K | 789.9 K |
noa | 902 | 234 | 902 | 11.5K | 821.1K | 243.9K | 5.2M | 1.6M | 534.3 K | 1.7 M |
bqc | 275 | 228 | 9.8K | 8.2K | 193K | 151.7K | 997K | 788.4K | 317.0 K | 408.1 K |
srm | 847 | 227 | 847 | 17.3K | 1.2M | 445.3K | 6.3M | 2M | 613.4 K | 1.7 M |
niq | 26.7K | 226 | 26.7K | 4.2K | 9.9M | 103.4K | 72.1M | 716.2K | 239.1 K | 20.9 M |
bas | 4.2K | 216 | 105.2K | 14.9K | 4.3M | 362.8K | 25.7M | 1.7M | 600.7 K | 7.6 M |
dwr | 452 | 215 | 22.1K | 11.1K | 269.4K | 139.5K | 2.2M | 1.2M | 375.4 K | 747.6 K |
guc | 537 | 214 | 22.9K | 12.5K | 422.4K | 218.1K | 3.4M | 1.8M | 540.1 K | 1.1 M |
jvn | 1K | 213 | 36.2K | 7.8K | 790.5K | 185.6K | 5.3M | 1.2M | 357.2 K | 1.7 M |
hvn | 737 | 200 | 33.9K | 7K | 779.7K | 239.4K | 4.3M | 1.2M | 378.5 K | 1.4 M |
sxn | 587 | 197 | 587 | 9.9K | 494K | 220.6K | 3.4M | 1.5M | 507.1 K | 1.2 M |
koi | 20.7K | 196 | 153.9K | 5K | 2.2M | 89.9K | 17.1M | 664.5K | 323.0 K | 7.1 M |
alz | 2.2K | 195 | 59.3K | 12.2K | 1.3M | 246.9K | 7.9M | 1.4M | 488.1 K | 2.9 M |
nyu | 1.2K | 195 | 1.2K | 11K | 988.7K | 210.5K | 7.7M | 1.6M | 492.6 K | 2.2 M |
bn_Latn | 98.7K | 191 | 1.3M | 12K | 98.7K | 191 | 458K | 730 | 314.7 K | 81.0 M |
suz | 226 | 186 | 226 | 11.3K | 169.6K | 140.5K | 1M | 855.2K | 339.5 K | 429.6 K |
pau | 1.7K | 185 | 1.7K | 13.1K | 2M | 394.6K | 12.4M | 2M | 600.1 K | 3.2 M |
nij | 1K | 183 | 1K | 9.2K | 741.6K | 186.1K | 4.7M | 1.2M | 389.6 K | 1.6 M |
sat_Latn | 39K | 183 | 39K | 5.5K | 39K | 183 | 183.8K | 601 | 276.1 K | 39.2 M |
gu_Latn | 58.2K | 179 | 688.4K | 5.4K | 58.2K | 179 | 260.8K | 673 | 241.0 K | 47.9 M |
msm | 520 | 177 | 520 | 8.6K | 410.8K | 190.5K | 2.5M | 1.1M | 339.7 K | 789.8 K |
maz | 585 | 170 | 21.3K | 8.2K | 452.9K | 174K | 2.9M | 951.7K | 304.7 K | 971.4 K |
qxr | 2.6K | 153 | 40.8K | 6.4K | 761.5K | 75.4K | 6.6M | 724K | 186.4 K | 1.9 M |
shp | 874 | 150 | 22.4K | 3.7K | 534.1K | 96.8K | 3.8M | 710.4K | 216.9 K | 1.2 M |
hne | 3K | 146 | 118.4K | 4.3K | 2.3M | 139.3K | 12M | 697K | 379.3 K | 6.5 M |
ktu | 3.3K | 144 | 115.5K | 7.8K | 3.2M | 196.9K | 18.5M | 1.1M | 300.1 K | 5.4 M |
laj | 6.5K | 144 | 61K | 6.4K | 2.4M | 140.1K | 15.8M | 730.5K | 233.5 K | 4.6 M |
pis | 1.1K | 139 | 62K | 7.2K | 1.3M | 136.8K | 7.7M | 764K | 212.7 K | 2.2 M |
mag | 631 | 138 | 62.6K | 22.1K | 2.1M | 544.2K | 10.7M | 2.6M | 1.4 M | 5.4 M |
gbm | 2.5K | 137 | 50.8K | 3.8K | 1.7M | 99.7K | 9.1M | 499.6K | 282.4 K | 4.5 M |
tzj | 471 | 136 | 11.1K | 7.3K | 299.9K | 150.8K | 1.9M | 884.2K | 272.0 K | 663.9 K |
oj | 2.5K | 135 | 2.5K | 1.6K | 1.2M | 35.9K | 9.6M | 337.1K | 117.6 K | 3.4 M |
ndc_ZW | 2.2K | 132 | 2.2K | 8.7K | 2.2K | 132 | 9.1K | 523 | 343.1 K | 2.2 M |
tks | 63.7K | 127 | 63.7K | 6.8K | 17.1M | 41.5K | 88.9M | 260.8K | 39.5 K | 33.0 M |
awa | 5.8K | 126 | 100.1K | 8.4K | 2.2M | 98.7K | 11.1M | 475K | 226.6 K | 5.8 M |
gvl | 37.9K | 126 | 213K | 6.9K | 21.1M | 161.1K | 141M | 789.2K | 257.8 K | 31.7 M |
knj | 229 | 126 | 10.1K | 9.2K | 202.6K | 171.8K | 1.1M | 855K | 253.1 K | 345.4 K |
spp | 733 | 123 | 733 | 5.8K | 902.7K | 141.8K | 4.4M | 682.5K | 217.8 K | 1.4 M |
mqy | 69.3K | 119 | 309K | 2.5K | 12.1M | 88.6K | 78.9M | 506.5K | 170.4 K | 16.3 M |
tca | 410 | 117 | 20K | 7.3K | 283K | 121.5K | 2.3M | 786K | 226.2 K | 781.2 K |
cce | 847 | 116 | 23.2K | 11K | 539.3K | 227.2K | 3.3M | 1.3M | 393.8 K | 1.1 M |
skr | 3.8K | 107 | 279.3K | 17.1K | 6.2M | 324K | 32.2M | 1.7M | 768.5 K | 15.4 M |
kmz_Latn | 24K | 106 | 361K | 2.4K | 24K | 106 | 108.6K | 401 | 231.8 K | 16.7 M |
dje | 913 | 100 | 40.2K | 3.7K | 816.3K | 97.5K | 4.7M | 480.7K | 161.2 K | 1.5 M |
gof | 2.8K | 97 | 33.8K | 5.5K | 703K | 68.8K | 5.5M | 506K | 159.1 K | 1.7 M |
agr | 465 | 93 | 16.1K | 3.6K | 295.4K | 67.2K | 2.3M | 554.5K | 177.0 K | 760.1 K |
qvz | 534 | 88 | 6.8K | 3.5K | 145.5K | 50.5K | 1.2M | 438.3K | 124.2 K | 382.7 K |
adh | 2.6K | 87 | 107.2K | 1K | 2.4M | 42.1K | 14.5M | 254.9K | 84.6 K | 5.0 M |
quf | 522 | 86 | 8.4K | 5.2K | 155.7K | 61.8K | 1.5M | 609K | 173.7 K | 542.8 K |
kjg | 113 | 84 | 3K | 2.9K | 67.6K | 67K | 408.5K | 399K | 159.2 K | 167.7 K |
tsc | 12.6K | 82 | 12.6K | 4K | 3.5M | 93.1K | 23.4M | 521.3K | 161.9 K | 7.0 M |
ber | 2.7K | 79 | 12.6K | 1.2K | 1.1M | 46.4K | 6.4M | 265.9K | 141.5 K | 3.0 M |
ify | 611 | 79 | 19.8K | 2.8K | 422.7K | 56.2K | 2.6M | 334K | 109.5 K | 913.1 K |
cbk | 10.1K | 78 | 43.8K | 2K | 1.7M | 64.3K | 10.3M | 339.3K | 93.4 K | 3.4 M |
quy | 588 | 78 | 28.1K | 2.7K | 423.3K | 37.3K | 4.5M | 368.2K | 114.5 K | 1.2 M |
ahk | 244 | 77 | 6.2K | 4.1K | 264K | 124.8K | 1.3M | 715.5K | 182.8 K | 359.7 K |
cac | 212 | 77 | 3.4K | 1.8K | 125.7K | 54.1K | 978.7K | 319.8K | 95.8 K | 280.3 K |
akb | 1K | 71 | 21.3K | 408 | 870.9K | 54.5K | 5.2M | 337.8K | 93.7 K | 1.6 M |
nut | 29K | 67 | 29K | 1.5K | 4.8M | 39.8K | 23.5M | 184.1K | 36.4 K | 8.3 M |
ffm | 1.8K | 65 | 30.1K | 2K | 745.6K | 39.1K | 4.6M | 236.1K | 83.8 K | 1.8 M |
taj | 146 | 65 | 21.6K | 14.3K | 309.7K | 203K | 2.3M | 1.4M | 503.0 K | 872.7 K |
ms_Arab | 698 | 63 | 698 | 320 | 698 | 63 | 2.9K | 239 | 64.7 K | 1016.0 K |
brx | 322 | 62 | 5.3K | 2.4K | 144.2K | 41K | 1.1M | 304.4K | 146.6 K | 515.7 K |
ann | 464 | 56 | 5K | 1.6K | 116.4K | 35.9K | 760.9K | 215.1K | 74.9 K | 295.2 K |
qup | 169 | 53 | 4.3K | 2.5K | 77.5K | 31.3K | 763.8K | 297.8K | 74.7 K | 207.3 K |
ms_Arab_BN | 2.6K | 46 | 2.6K | 374 | 2.6K | 46 | 10.5K | 171 | 50.0 K | 5.1 M |
miq | 236 | 45 | 6.4K | 3.5K | 183.7K | 80.2K | 1.2M | 485.6K | 157.6 K | 384.1 K |
msb | 811 | 41 | 811 | 1K | 705.9K | 28.8K | 4.4M | 167.5K | 53.3 K | 1.7 M |
bim | 410 | 40 | 31.1K | 6.3K | 669.8K | 167.4K | 3.2M | 793.4K | 252.7 K | 1.1 M |
raj | 1.8K | 40 | 1.8K | 5.7K | 1.3M | 81.1K | 7.1M | 405K | 226.2 K | 3.9 M |
kwi | 382 | 37 | 16.9K | 2.2K | 253.8K | 23.4K | 1.8M | 172.8K | 47.6 K | 536.2 K |
tll | 200 | 37 | 200 | 2.7K | 304.2K | 62.2K | 2.2M | 409.8K | 132.3 K | 664.5 K |
trp | 12.8K | 36 | 12.8K | 1.7K | 4.1M | 39K | 29.9M | 257.3K | 87.5 K | 10.2 M |
smt | 1.4K | 34 | 1.4K | 703 | 1M | 36.5K | 6.8M | 245.4K | 87.9 K | 2.5 M |
mrw | 11.3K | 29 | 11.3K | 1K | 4.2M | 45.7K | 27.8M | 257.2K | 81.3 K | 8.8 M |
dln | 236 | 28 | 5.2K | 969 | 150.8K | 21.5K | 860.5K | 118.3K | 36.8 K | 280.3 K |
qvc | 3.4K | 27 | 14.6K | 2.2K | 495.7K | 25.7K | 5M | 233.7K | 65.3 K | 2.6 M |
doi | 1.7K | 26 | 21.8K | 975 | 568.7K | 25.5K | 3.2M | 135.3K | 66.7 K | 1.6 M |
ff | 13.6K | 26 | 150K | 5K | 3.4M | 46.5K | 22.8M | 277.6K | 78.8 K | 8.5 M |
## Citation Information
~~~
@misc{kudugunta2023madlad400,
title={MADLAD-400: A Multilingual And Document-Level Large Audited Dataset},
author={Sneha Kudugunta and Isaac Caswell and Biao Zhang and Xavier Garcia and Christopher A. Choquette-Choo and Katherine Lee and Derrick Xin and Aditya Kusupati and Romi Stella and Ankur Bapna and Orhan Firat},
year={2023},
eprint={2309.04662},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
~~~ |
CyberHarem/erica_brown_violetevergarden | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of Erica Brown/エリカ・ブラウン (Violet Evergarden)
This is the dataset of Erica Brown/エリカ・ブラウン (Violet Evergarden), containing 164 images and their tags.
The core tags of this character are `brown_hair, short_hair, glasses, brown_eyes, round_eyewear, freckles, bob_cut`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 164 | 112.25 MiB | [Download](https://huggingface.co/datasets/CyberHarem/erica_brown_violetevergarden/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 1200 | 164 | 112.20 MiB | [Download](https://huggingface.co/datasets/CyberHarem/erica_brown_violetevergarden/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 275 | 177.36 MiB | [Download](https://huggingface.co/datasets/CyberHarem/erica_brown_violetevergarden/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/erica_brown_violetevergarden',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 18 |  |  |  |  |  | 1girl, solo, sleeveless, upper_body, collared_shirt, looking_at_viewer, blunt_bangs, green_shirt, bookshelf, overalls |
| 1 | 12 |  |  |  |  |  | 1girl, closed_mouth, solo, shirt, looking_at_viewer, portrait, blunt_bangs |
| 2 | 39 |  |  |  |  |  | 1girl, green_dress, solo, sleeveless, indoors |
| 3 | 8 |  |  |  |  |  | 1girl, turtleneck_sweater, solo, upper_body, overalls, white_sweater, blurry, looking_at_viewer, blunt_bangs, closed_mouth, indoors |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | sleeveless | upper_body | collared_shirt | looking_at_viewer | blunt_bangs | green_shirt | bookshelf | overalls | closed_mouth | shirt | portrait | green_dress | indoors | turtleneck_sweater | white_sweater | blurry |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:-------------|:-------------|:-----------------|:--------------------|:--------------|:--------------|:------------|:-----------|:---------------|:--------|:-----------|:--------------|:----------|:---------------------|:----------------|:---------|
| 0 | 18 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | | | | | | | | |
| 1 | 12 |  |  |  |  |  | X | X | | | | X | X | | | | X | X | X | | | | | |
| 2 | 39 |  |  |  |  |  | X | X | X | | | | | | | | | | | X | X | | | |
| 3 | 8 |  |  |  |  |  | X | X | | X | | X | X | | | X | X | | | | X | X | X | X |
|
yacine-djm/aveyron_test | ---
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
- name: label
sequence: string
- name: date
dtype: string
- name: sheet_id
dtype: string
- name: group_id
dtype: string
- name: source
dtype: string
- name: est
dtype: string
splits:
- name: train
num_bytes: 132770347
num_examples: 530910
download_size: 49780765
dataset_size: 132770347
---
# Dataset Card for "aveyron_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ClericalAid/roleplay-scripts | ---
task_categories:
- text-generation
language:
- en
--- |
Sambasiva/rfi-rfp-ibmcloud-questions | ---
license: apache-2.0
---
|
hriteshMaikap/IEEEChatbotAplha | ---
dataset_info:
features:
- name: Question
dtype: string
- name: Answer
dtype: string
splits:
- name: train
num_bytes: 2101813
num_examples: 5526
download_size: 821355
dataset_size: 2101813
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for Dataset Name
This dataset has been meticulously curated by the AI team at IEEE Student Branch, Vishwakarma Institute of Technology (VIT) Pune, with the explicit purpose of training the Llama2 model. It encompasses a diverse range of topics essential for the development of an effective conversational AI system.
## Dataset Details
### Dataset Description
The dataset comprises a comprehensive selection of topics, including but not limited to:
Frequently Asked Questions (FAQs) related to IEEE Student Branch at VIT Pune.
Inquiries pertaining to placements, encompassing strategies, tips, and common queries.
Questions related to fundamental concepts in Data Structures and Algorithms.
Queries and discussions regarding research papers, methodologies, and academic pursuits.
- **Curated by:** AI Team- IEEE SB VIT Pune
## Uses
This data was particularly designed for a chatbot for IEEE SB VIT Pune so that university students could use it for their own benifits, but it includes some general topics related to Research Papers, Data Structure and Algorithms and Placements that can be used by others for their custom chatbot
## Dataset Structure
The dataset consists of the following fields:
- **Instruction:** This field represents the prompt or query posed to the chatbot.
- **Response:** This field contains the corresponding generated response by the chatbot.
## Dataset Structure Information
The dataset is structured in a JSON format, with each entry containing the following fields:
```json
{
"instruction": "What is IEEE?",
"response": "The IEEE or Institute of Electrical and Electronics Engineers is the world's largest professional technical organization dedicated to the advancement of technology for the benefit of humanity."
}
[More Information Needed]
### Curation Rationale
The motivation behind curating this dataset stems from a genuine desire to empower and support university students pursuing B.Tech degrees. Recognizing the pivotal role that IEEE Student Branch at Vishwakarma Institute of Technology (VIT) Pune plays in students' academic journeys, the aim was to create a resource that elucidates the myriad ways in which IEEE SB VIT Pune can enrich and enhance students' educational experiences.
At its core, this dataset is a testament to the commitment of the AI team at IEEE SB VIT Pune to empower B.Tech students with valuable insights and resources. By curating a comprehensive collection of topics spanning FAQs, placement strategies, technical concepts, and research discussions, the dataset seeks to equip students with the knowledge and understanding necessary to navigate their academic pursuits effectively.
## Dataset Card Authors
AI Team- IEEE SB VIT Pune
Mrunmayee Phadke (Project Head)
Hritesh Maikap
Nidhish
Arya Lokhande
Apurva Kota
Soham Nimale
|
arthurmluz/GPTextSum2_data-temario_results | ---
dataset_info:
features:
- name: id
dtype: int64
- name: text
dtype: string
- name: summary
dtype: string
- name: gen_summary
dtype: string
- name: rouge
struct:
- name: rouge1
dtype: float64
- name: rouge2
dtype: float64
- name: rougeL
dtype: float64
- name: rougeLsum
dtype: float64
- name: bert
struct:
- name: f1
sequence: float64
- name: hashcode
dtype: string
- name: precision
sequence: float64
- name: recall
sequence: float64
- name: moverScore
dtype: float64
splits:
- name: validation
num_bytes: 114709
num_examples: 20
download_size: 108791
dataset_size: 114709
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
---
# Dataset Card for "GPTextSum2_data-temario_results"
rouge= {'rouge1': 0.49515643603635084, 'rouge2': 0.21756085354083887, 'rougeL': 0.3034293883115211, 'rougeLsum': 0.3034293883115211}
bert= {'precision': 0.7198777735233307, 'recall': 0.7549779504537583, 'f1': 0.7367873221635819}
mover = 0.6264011166318602 |
stable-bias/identities | ---
license: cc-by-sa-4.0
dataset_info:
features:
- name: ethnicity
dtype: string
- name: gender
dtype: string
- name: 'no'
dtype: int32
- name: image_path
dtype: string
- name: image
dtype: image
- name: model
dtype: string
splits:
- name: train
num_bytes: 585336673
num_examples: 2040
download_size: 465986042
dataset_size: 585336673
language:
- en
---
# Dataset Card for identities
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases and Limitations](#discussion-of-biases-and-limitations)
- [Additional Information](#additional-information)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://huggingface.co/spaces/tti-bias/stable-bias
- **Repository:** Forthcoming
- **Paper:** Forthcoming
- **Leaderboard:**
- **Point of Contact:** Forthcoming
### Dataset Summary
<span style="color:blue" font-size:smaller><b>🏗️ WORK IN PROGRESS</b></span>
<span style="color:red" font-size:smaller><b>⚠️ DISCLAIMER: The images in this dataset were generated by text-to-image systems and may depict offensive stereotypes or contain explicit content.</b></span>
The *Identities* dataset is a collection of computer-generated images generated using Text-to-Image (TTI) systems.
In order to generate a diverse set of prompts to evaluate the system outputs’ variation across dimensions of interest, we use the pattern **`Photo portrait of a [X] [Y] at work`**, where **[X]** spans ... and **[Y]** spans ....
```python
["American_Indian", "Black"]
```
```python
["woman", "man", "non-binary", "no_gender_specified"]
# no_gender_specified corresponds to a value of "person" for **[Y]**
```
Every prompt is used to generate images from the following models: **Stable Diffusion v.1.4, Stable Diffusion v.2., and Dall-E 2**
### Supported Tasks
This dataset can be used to evaluate the output space of TTI systems, particularly against the backdrop of societal representativeness.
### Languages
The prompts that generated the images are all in US-English.
## Dataset Structure
The dataset is stored in `parquet` format and contains 2040 rows which can be loaded like so:
```python
from datasets import load_dataset
dataset = load_dataset("tti-bias/professions", split="train")
```
### Data Fields
Each row corresponds to the output of a TTI system and looks as follows:
```python
{
'ethnicity': 'South_Asian',
'gender': 'man',
'no': 1,
'image_path': 'Photo_portrait_of_a_South_Asian_man_at_work/Photo_portrait_of_a_South_Asian_man_at_work_1.jpg',
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=512x512>,
'model': 'SD_2'
}
```
### Data Splits
All the data is contained within the `train` split. As such, the dataset contains practically no splits.
## Dataset Creation
### Curation Rationale
This dataset was created to explore the output characteristics of TTI systems from the vantage point of societal characteristics of interest.
### Source Data
#### Initial Data Collection and Normalization
The data was generated using the [DiffusionPipeline]() from Hugging Face:
```python
from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
images = pipeline(prompt="Photo portrait of an African woman at work", num_images_per_prompt=9).images
```
### Personal and Sensitive Information
Generative models trained on large datasets have been shown to memorize part of their training sets (See e.g.: [(Carlini et al. 2023)](https://arxiv.org/abs/2301.13188)) and the people generated could theoretically bear resemblance to real people.
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases and Limitations
At this point in time, the data is limited to images generated using English prompts and a set of professions sourced form the U.S. Bureau of Labor Statistics (BLS), which also provides us with additional information such as the demographic characteristics and salaries of each profession. While this data can also be leveraged in interesting analyses, it is currently limited to the North American context.
## Additional Information
### Licensing Information
The dataset is licensed under the Creative Commons [Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/) license.
### Citation Information
If you use this dataset in your own work, please consider citing:
```json
@article{stable-bias-authors-2023,
author = {Anonymous Authors},
title = {Stable Bias: Analyzing Societal Representations in Diffusion Models},
year = {2023},
}
``` |
benjaminaw93/test | ---
license: apache-2.0
---
|
foundation-models/libs | ---
license: apache-2.0
---
|
tasksource/prm800k_rlhf | ---
dataset_info:
features:
- name: prompt
dtype: 'null'
splits:
- name: train
- name: test
download_size: 0
dataset_size: 0
---
# Dataset Card for "prm800k_rlhf"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
kewu93/three_styles_prompted | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 59921589.0
num_examples: 2100
- name: val
num_bytes: 25922766.5
num_examples: 900
download_size: 84801147
dataset_size: 85844355.5
---
# Dataset Card for "three_styles_prompted"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_lmsys__vicuna-33b-v1.3 | ---
pretty_name: Evaluation run of lmsys/vicuna-33b-v1.3
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [lmsys/vicuna-33b-v1.3](https://huggingface.co/lmsys/vicuna-33b-v1.3) on the [Open\
\ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_lmsys__vicuna-33b-v1.3\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-17T00:50:29.265762](https://huggingface.co/datasets/open-llm-leaderboard/details_lmsys__vicuna-33b-v1.3/blob/main/results_2023-09-17T00-50-29.265762.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.24611996644295303,\n\
\ \"em_stderr\": 0.004411275638567265,\n \"f1\": 0.3191652684563765,\n\
\ \"f1_stderr\": 0.004369271114420946,\n \"acc\": 0.4537743848183282,\n\
\ \"acc_stderr\": 0.010649726923219326\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.24611996644295303,\n \"em_stderr\": 0.004411275638567265,\n\
\ \"f1\": 0.3191652684563765,\n \"f1_stderr\": 0.004369271114420946\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.1372251705837756,\n \
\ \"acc_stderr\": 0.00947780824460041\n },\n \"harness|winogrande|5\":\
\ {\n \"acc\": 0.7703235990528808,\n \"acc_stderr\": 0.011821645601838243\n\
\ }\n}\n```"
repo_url: https://huggingface.co/lmsys/vicuna-33b-v1.3
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|arc:challenge|25_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_17T00_50_29.265762
path:
- '**/details_harness|drop|3_2023-09-17T00-50-29.265762.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-17T00-50-29.265762.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_17T00_50_29.265762
path:
- '**/details_harness|gsm8k|5_2023-09-17T00-50-29.265762.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-17T00-50-29.265762.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hellaswag|10_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-23T14:55:51.049874.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_23T14_55_51.049874
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-23T14:55:51.049874.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-23T14:55:51.049874.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_17T00_50_29.265762
path:
- '**/details_harness|winogrande|5_2023-09-17T00-50-29.265762.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-17T00-50-29.265762.parquet'
- config_name: results
data_files:
- split: 2023_09_17T00_50_29.265762
path:
- results_2023-09-17T00-50-29.265762.parquet
- split: latest
path:
- results_2023-09-17T00-50-29.265762.parquet
---
# Dataset Card for Evaluation run of lmsys/vicuna-33b-v1.3
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/lmsys/vicuna-33b-v1.3
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [lmsys/vicuna-33b-v1.3](https://huggingface.co/lmsys/vicuna-33b-v1.3) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_lmsys__vicuna-33b-v1.3",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-17T00:50:29.265762](https://huggingface.co/datasets/open-llm-leaderboard/details_lmsys__vicuna-33b-v1.3/blob/main/results_2023-09-17T00-50-29.265762.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.24611996644295303,
"em_stderr": 0.004411275638567265,
"f1": 0.3191652684563765,
"f1_stderr": 0.004369271114420946,
"acc": 0.4537743848183282,
"acc_stderr": 0.010649726923219326
},
"harness|drop|3": {
"em": 0.24611996644295303,
"em_stderr": 0.004411275638567265,
"f1": 0.3191652684563765,
"f1_stderr": 0.004369271114420946
},
"harness|gsm8k|5": {
"acc": 0.1372251705837756,
"acc_stderr": 0.00947780824460041
},
"harness|winogrande|5": {
"acc": 0.7703235990528808,
"acc_stderr": 0.011821645601838243
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
Prag12/PowerfulAssistant-Llama2-1kDemo | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1664926
num_examples: 1000
download_size: 974900
dataset_size: 1664926
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
open-llm-leaderboard/details_facebook__xglm-4.5B | ---
pretty_name: Evaluation run of facebook/xglm-4.5B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [facebook/xglm-4.5B](https://huggingface.co/facebook/xglm-4.5B) on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_facebook__xglm-4.5B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-18T23:03:33.960699](https://huggingface.co/datasets/open-llm-leaderboard/details_facebook__xglm-4.5B/blob/main/results_2023-10-18T23-03-33.960699.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.06480704697986577,\n\
\ \"em_stderr\": 0.0025211656446620548,\n \"f1\": 0.11480180369127503,\n\
\ \"f1_stderr\": 0.002765932447728658,\n \"acc\": 0.27580178712796344,\n\
\ \"acc_stderr\": 0.007648043341953835\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.06480704697986577,\n \"em_stderr\": 0.0025211656446620548,\n\
\ \"f1\": 0.11480180369127503,\n \"f1_stderr\": 0.002765932447728658\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.002274450341167551,\n \
\ \"acc_stderr\": 0.001312157814867431\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.5493291239147593,\n \"acc_stderr\": 0.013983928869040239\n\
\ }\n}\n```"
repo_url: https://huggingface.co/facebook/xglm-4.5B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|arc:challenge|25_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_18T23_03_33.960699
path:
- '**/details_harness|drop|3_2023-10-18T23-03-33.960699.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-18T23-03-33.960699.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_18T23_03_33.960699
path:
- '**/details_harness|gsm8k|5_2023-10-18T23-03-33.960699.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-18T23-03-33.960699.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hellaswag|10_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:36:54.035673.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T15:36:54.035673.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T15:36:54.035673.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_18T23_03_33.960699
path:
- '**/details_harness|winogrande|5_2023-10-18T23-03-33.960699.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-18T23-03-33.960699.parquet'
- config_name: results
data_files:
- split: 2023_07_19T15_36_54.035673
path:
- results_2023-07-19T15:36:54.035673.parquet
- split: 2023_10_18T23_03_33.960699
path:
- results_2023-10-18T23-03-33.960699.parquet
- split: latest
path:
- results_2023-10-18T23-03-33.960699.parquet
---
# Dataset Card for Evaluation run of facebook/xglm-4.5B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/facebook/xglm-4.5B
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [facebook/xglm-4.5B](https://huggingface.co/facebook/xglm-4.5B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_facebook__xglm-4.5B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-18T23:03:33.960699](https://huggingface.co/datasets/open-llm-leaderboard/details_facebook__xglm-4.5B/blob/main/results_2023-10-18T23-03-33.960699.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.06480704697986577,
"em_stderr": 0.0025211656446620548,
"f1": 0.11480180369127503,
"f1_stderr": 0.002765932447728658,
"acc": 0.27580178712796344,
"acc_stderr": 0.007648043341953835
},
"harness|drop|3": {
"em": 0.06480704697986577,
"em_stderr": 0.0025211656446620548,
"f1": 0.11480180369127503,
"f1_stderr": 0.002765932447728658
},
"harness|gsm8k|5": {
"acc": 0.002274450341167551,
"acc_stderr": 0.001312157814867431
},
"harness|winogrande|5": {
"acc": 0.5493291239147593,
"acc_stderr": 0.013983928869040239
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
Abhay1212/news_generation | ---
license: openrail
dataset_info:
features:
- name: document
dtype: string
- name: summary
dtype: string
splits:
- name: train
num_bytes: 6750051
num_examples: 500
download_size: 3873568
dataset_size: 6750051
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Sylvana/qa_en_translation | ---
license: apache-2.0
task_categories:
- translation
language:
- ar
size_categories:
- 1K<n<10K
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
edbeeching/prj_gia_dataset_atari_2B_atari_krull_1111 | ---
library_name: gia
tags:
- deep-reinforcement-learning
- reinforcement-learning
- gia
- multi-task
- multi-modal
- imitation-learning
- offline-reinforcement-learning
---
An imitation learning environment for the atari_krull environment, sample for the policy atari_2B_atari_krull_1111
This environment was created as part of the Generally Intelligent Agents project gia: https://github.com/huggingface/gia
|
liuyanchen1015/MULTI_VALUE_mnli_referential_thing | ---
dataset_info:
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
dtype: int64
- name: idx
dtype: int64
- name: score
dtype: int64
splits:
- name: dev_matched
num_bytes: 552234
num_examples: 2419
- name: dev_mismatched
num_bytes: 458303
num_examples: 1917
- name: test_matched
num_bytes: 508906
num_examples: 2221
- name: test_mismatched
num_bytes: 411757
num_examples: 1803
- name: train
num_bytes: 21514121
num_examples: 92497
download_size: 14191743
dataset_size: 23445321
---
# Dataset Card for "MULTI_VALUE_mnli_referential_thing"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
SURF-FluidSimulation/Test | ---
license: cc-by-nc-4.0
---
|
ML-Projects-Kiel/tweetyface_debug | ---
annotations_creators:
- machine-generated
language:
- en
- de
language_creators:
- crowdsourced
license:
- apache-2.0
multilinguality:
- multilingual
pretty_name: tweetyface_debug
size_categories:
- 10K<n<100K
source_datasets: []
tags: []
task_categories:
- text-generation
task_ids: []
---
# DEBUG Dataset Card for "tweetyface"
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:** [GitHub](https://github.com/ml-projects-kiel/OpenCampus-ApplicationofTransformers)
### Dataset Summary
DEBUG
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
English, German
## Dataset Structure
### Data Instances
#### english
- **Size of downloaded dataset files:** 4.77 MB
- **Size of the generated dataset:** 5.92 MB
- **Total amount of disk used:** 4.77 MB
#### german
- **Size of downloaded dataset files:** 2.58 MB
- **Size of the generated dataset:** 3.10 MB
- **Total amount of disk used:** 2.59 MB
An example of 'validation' looks as follows.
```
{
"text": "@SpaceX @Space_Station About twice as much useful mass to orbit as rest of Earth combined",
"label": elonmusk,
"idx": 1001283
}
```
### Data Fields
The data fields are the same among all splits and languages.
- `text`: a `string` feature.
- `label`: a classification label
- `idx`: an `string` feature.
- `ref_tweet`: a `bool` feature.
- `reply_tweet`: a `bool` feature.
### Data Splits
| name | train | validation |
| ------- | ----: | ---------: |
| english | 27857 | 6965 |
| german | 10254 | 2564 |
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
|
open-llm-leaderboard/details_Novocoders__Mistral-NeuralDPO-v0.6 | ---
pretty_name: Evaluation run of Novocoders/Mistral-NeuralDPO-v0.6
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Novocoders/Mistral-NeuralDPO-v0.6](https://huggingface.co/Novocoders/Mistral-NeuralDPO-v0.6)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Novocoders__Mistral-NeuralDPO-v0.6\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-02-20T21:12:34.279555](https://huggingface.co/datasets/open-llm-leaderboard/details_Novocoders__Mistral-NeuralDPO-v0.6/blob/main/results_2024-02-20T21-12-34.279555.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6216536192598873,\n\
\ \"acc_stderr\": 0.032833523349952605,\n \"acc_norm\": 0.6263550254226425,\n\
\ \"acc_norm_stderr\": 0.03350879938095453,\n \"mc1\": 0.3243574051407589,\n\
\ \"mc1_stderr\": 0.016387976779647935,\n \"mc2\": 0.4821846438568913,\n\
\ \"mc2_stderr\": 0.01587338545909486\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6331058020477816,\n \"acc_stderr\": 0.014084133118104294,\n\
\ \"acc_norm\": 0.658703071672355,\n \"acc_norm_stderr\": 0.013855831287497728\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6657040430193188,\n\
\ \"acc_stderr\": 0.004707796436637714,\n \"acc_norm\": 0.8468432583150767,\n\
\ \"acc_norm_stderr\": 0.003594024993230559\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.3,\n \"acc_stderr\": 0.04605661864718381,\n \
\ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.04605661864718381\n },\n\
\ \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6222222222222222,\n\
\ \"acc_stderr\": 0.04188307537595853,\n \"acc_norm\": 0.6222222222222222,\n\
\ \"acc_norm_stderr\": 0.04188307537595853\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.631578947368421,\n \"acc_stderr\": 0.03925523381052932,\n\
\ \"acc_norm\": 0.631578947368421,\n \"acc_norm_stderr\": 0.03925523381052932\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.54,\n\
\ \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n \
\ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6452830188679245,\n \"acc_stderr\": 0.029445175328199586,\n\
\ \"acc_norm\": 0.6452830188679245,\n \"acc_norm_stderr\": 0.029445175328199586\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7013888888888888,\n\
\ \"acc_stderr\": 0.03827052357950756,\n \"acc_norm\": 0.7013888888888888,\n\
\ \"acc_norm_stderr\": 0.03827052357950756\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956911,\n \
\ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956911\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 0.5,\n\
\ \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.39,\n \"acc_stderr\": 0.049020713000019756,\n \
\ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.049020713000019756\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6127167630057804,\n\
\ \"acc_stderr\": 0.03714325906302065,\n \"acc_norm\": 0.6127167630057804,\n\
\ \"acc_norm_stderr\": 0.03714325906302065\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.4117647058823529,\n \"acc_stderr\": 0.04897104952726366,\n\
\ \"acc_norm\": 0.4117647058823529,\n \"acc_norm_stderr\": 0.04897104952726366\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.73,\n\
\ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5531914893617021,\n \"acc_stderr\": 0.0325005368436584,\n\
\ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.0325005368436584\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4473684210526316,\n\
\ \"acc_stderr\": 0.04677473004491199,\n \"acc_norm\": 0.4473684210526316,\n\
\ \"acc_norm_stderr\": 0.04677473004491199\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5310344827586206,\n \"acc_stderr\": 0.04158632762097828,\n\
\ \"acc_norm\": 0.5310344827586206,\n \"acc_norm_stderr\": 0.04158632762097828\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.3968253968253968,\n \"acc_stderr\": 0.02519710107424649,\n \"\
acc_norm\": 0.3968253968253968,\n \"acc_norm_stderr\": 0.02519710107424649\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.42063492063492064,\n\
\ \"acc_stderr\": 0.04415438226743744,\n \"acc_norm\": 0.42063492063492064,\n\
\ \"acc_norm_stderr\": 0.04415438226743744\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \
\ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7387096774193549,\n\
\ \"acc_stderr\": 0.024993053397764812,\n \"acc_norm\": 0.7387096774193549,\n\
\ \"acc_norm_stderr\": 0.024993053397764812\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.5221674876847291,\n \"acc_stderr\": 0.03514528562175007,\n\
\ \"acc_norm\": 0.5221674876847291,\n \"acc_norm_stderr\": 0.03514528562175007\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.63,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\"\
: 0.63,\n \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7575757575757576,\n \"acc_stderr\": 0.03346409881055953,\n\
\ \"acc_norm\": 0.7575757575757576,\n \"acc_norm_stderr\": 0.03346409881055953\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7828282828282829,\n \"acc_stderr\": 0.029376616484945633,\n \"\
acc_norm\": 0.7828282828282829,\n \"acc_norm_stderr\": 0.029376616484945633\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8704663212435233,\n \"acc_stderr\": 0.024233532297758723,\n\
\ \"acc_norm\": 0.8704663212435233,\n \"acc_norm_stderr\": 0.024233532297758723\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6615384615384615,\n \"acc_stderr\": 0.023991500500313036,\n\
\ \"acc_norm\": 0.6615384615384615,\n \"acc_norm_stderr\": 0.023991500500313036\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.337037037037037,\n \"acc_stderr\": 0.028820884666253255,\n \
\ \"acc_norm\": 0.337037037037037,\n \"acc_norm_stderr\": 0.028820884666253255\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6722689075630253,\n \"acc_stderr\": 0.03048991141767323,\n \
\ \"acc_norm\": 0.6722689075630253,\n \"acc_norm_stderr\": 0.03048991141767323\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3576158940397351,\n \"acc_stderr\": 0.03913453431177258,\n \"\
acc_norm\": 0.3576158940397351,\n \"acc_norm_stderr\": 0.03913453431177258\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.7963302752293578,\n \"acc_stderr\": 0.017266742087630783,\n \"\
acc_norm\": 0.7963302752293578,\n \"acc_norm_stderr\": 0.017266742087630783\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5185185185185185,\n \"acc_stderr\": 0.03407632093854051,\n \"\
acc_norm\": 0.5185185185185185,\n \"acc_norm_stderr\": 0.03407632093854051\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.7745098039215687,\n \"acc_stderr\": 0.029331162294251735,\n \"\
acc_norm\": 0.7745098039215687,\n \"acc_norm_stderr\": 0.029331162294251735\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7637130801687764,\n \"acc_stderr\": 0.027652153144159263,\n \
\ \"acc_norm\": 0.7637130801687764,\n \"acc_norm_stderr\": 0.027652153144159263\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6636771300448431,\n\
\ \"acc_stderr\": 0.031708824268455,\n \"acc_norm\": 0.6636771300448431,\n\
\ \"acc_norm_stderr\": 0.031708824268455\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7633587786259542,\n \"acc_stderr\": 0.03727673575596913,\n\
\ \"acc_norm\": 0.7633587786259542,\n \"acc_norm_stderr\": 0.03727673575596913\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.768595041322314,\n \"acc_stderr\": 0.03849856098794088,\n \"acc_norm\"\
: 0.768595041322314,\n \"acc_norm_stderr\": 0.03849856098794088\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7685185185185185,\n\
\ \"acc_stderr\": 0.04077494709252627,\n \"acc_norm\": 0.7685185185185185,\n\
\ \"acc_norm_stderr\": 0.04077494709252627\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7239263803680982,\n \"acc_stderr\": 0.035123852837050475,\n\
\ \"acc_norm\": 0.7239263803680982,\n \"acc_norm_stderr\": 0.035123852837050475\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4375,\n\
\ \"acc_stderr\": 0.04708567521880525,\n \"acc_norm\": 0.4375,\n \
\ \"acc_norm_stderr\": 0.04708567521880525\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.04058042015646034,\n\
\ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.04058042015646034\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8034188034188035,\n\
\ \"acc_stderr\": 0.02603538609895129,\n \"acc_norm\": 0.8034188034188035,\n\
\ \"acc_norm_stderr\": 0.02603538609895129\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \
\ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8033205619412516,\n\
\ \"acc_stderr\": 0.01421413855691391,\n \"acc_norm\": 0.8033205619412516,\n\
\ \"acc_norm_stderr\": 0.01421413855691391\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7196531791907514,\n \"acc_stderr\": 0.024182427496577612,\n\
\ \"acc_norm\": 0.7196531791907514,\n \"acc_norm_stderr\": 0.024182427496577612\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.29608938547486036,\n\
\ \"acc_stderr\": 0.015268677317602281,\n \"acc_norm\": 0.29608938547486036,\n\
\ \"acc_norm_stderr\": 0.015268677317602281\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7287581699346405,\n \"acc_stderr\": 0.02545775669666788,\n\
\ \"acc_norm\": 0.7287581699346405,\n \"acc_norm_stderr\": 0.02545775669666788\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6913183279742765,\n\
\ \"acc_stderr\": 0.026236965881153262,\n \"acc_norm\": 0.6913183279742765,\n\
\ \"acc_norm_stderr\": 0.026236965881153262\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.6975308641975309,\n \"acc_stderr\": 0.02555765398186806,\n\
\ \"acc_norm\": 0.6975308641975309,\n \"acc_norm_stderr\": 0.02555765398186806\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.4574468085106383,\n \"acc_stderr\": 0.02971928127223684,\n \
\ \"acc_norm\": 0.4574468085106383,\n \"acc_norm_stderr\": 0.02971928127223684\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.44198174706649285,\n\
\ \"acc_stderr\": 0.01268397251359881,\n \"acc_norm\": 0.44198174706649285,\n\
\ \"acc_norm_stderr\": 0.01268397251359881\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6470588235294118,\n \"acc_stderr\": 0.029029422815681397,\n\
\ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.029029422815681397\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6045751633986928,\n \"acc_stderr\": 0.019780465954777515,\n \
\ \"acc_norm\": 0.6045751633986928,\n \"acc_norm_stderr\": 0.019780465954777515\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7,\n\
\ \"acc_stderr\": 0.04389311454644286,\n \"acc_norm\": 0.7,\n \
\ \"acc_norm_stderr\": 0.04389311454644286\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7061224489795919,\n \"acc_stderr\": 0.029162738410249772,\n\
\ \"acc_norm\": 0.7061224489795919,\n \"acc_norm_stderr\": 0.029162738410249772\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.845771144278607,\n\
\ \"acc_stderr\": 0.02553843336857833,\n \"acc_norm\": 0.845771144278607,\n\
\ \"acc_norm_stderr\": 0.02553843336857833\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.81,\n \"acc_stderr\": 0.039427724440366234,\n \
\ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.039427724440366234\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5542168674698795,\n\
\ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\
\ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.02991312723236804,\n\
\ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.02991312723236804\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3243574051407589,\n\
\ \"mc1_stderr\": 0.016387976779647935,\n \"mc2\": 0.4821846438568913,\n\
\ \"mc2_stderr\": 0.01587338545909486\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8026835043409629,\n \"acc_stderr\": 0.011185026389050372\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.36997725549658833,\n \
\ \"acc_stderr\": 0.01329866120772713\n }\n}\n```"
repo_url: https://huggingface.co/Novocoders/Mistral-NeuralDPO-v0.6
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|arc:challenge|25_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|arc:challenge|25_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|gsm8k|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|gsm8k|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hellaswag|10_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hellaswag|10_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-20T21-01-17.951654.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-20T21-12-34.279555.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
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path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-20T21-01-17.951654.parquet'
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path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
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path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-20T21-01-17.951654.parquet'
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path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-20T21-01-17.951654.parquet'
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path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
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- config_name: harness_hendrycksTest_formal_logic_5
data_files:
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-20T21-01-17.951654.parquet'
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-20T21-01-17.951654.parquet'
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
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path:
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- split: 2024_02_20T21_12_34.279555
path:
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path:
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- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
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path:
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path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
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path:
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- split: 2024_02_20T21_12_34.279555
path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
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- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
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path:
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- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
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path:
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path:
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path:
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- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
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path:
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path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
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path:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
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path:
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- split: 2024_02_20T21_12_34.279555
path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
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path:
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- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
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path:
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- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-20T21-12-34.279555.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- '**/details_harness|winogrande|5_2024-02-20T21-01-17.951654.parquet'
- split: 2024_02_20T21_12_34.279555
path:
- '**/details_harness|winogrande|5_2024-02-20T21-12-34.279555.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-02-20T21-12-34.279555.parquet'
- config_name: results
data_files:
- split: 2024_02_20T21_01_17.951654
path:
- results_2024-02-20T21-01-17.951654.parquet
- split: 2024_02_20T21_12_34.279555
path:
- results_2024-02-20T21-12-34.279555.parquet
- split: latest
path:
- results_2024-02-20T21-12-34.279555.parquet
---
# Dataset Card for Evaluation run of Novocoders/Mistral-NeuralDPO-v0.6
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Novocoders/Mistral-NeuralDPO-v0.6](https://huggingface.co/Novocoders/Mistral-NeuralDPO-v0.6) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_Novocoders__Mistral-NeuralDPO-v0.6",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-02-20T21:12:34.279555](https://huggingface.co/datasets/open-llm-leaderboard/details_Novocoders__Mistral-NeuralDPO-v0.6/blob/main/results_2024-02-20T21-12-34.279555.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.6216536192598873,
"acc_stderr": 0.032833523349952605,
"acc_norm": 0.6263550254226425,
"acc_norm_stderr": 0.03350879938095453,
"mc1": 0.3243574051407589,
"mc1_stderr": 0.016387976779647935,
"mc2": 0.4821846438568913,
"mc2_stderr": 0.01587338545909486
},
"harness|arc:challenge|25": {
"acc": 0.6331058020477816,
"acc_stderr": 0.014084133118104294,
"acc_norm": 0.658703071672355,
"acc_norm_stderr": 0.013855831287497728
},
"harness|hellaswag|10": {
"acc": 0.6657040430193188,
"acc_stderr": 0.004707796436637714,
"acc_norm": 0.8468432583150767,
"acc_norm_stderr": 0.003594024993230559
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.3,
"acc_stderr": 0.04605661864718381,
"acc_norm": 0.3,
"acc_norm_stderr": 0.04605661864718381
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6222222222222222,
"acc_stderr": 0.04188307537595853,
"acc_norm": 0.6222222222222222,
"acc_norm_stderr": 0.04188307537595853
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.631578947368421,
"acc_stderr": 0.03925523381052932,
"acc_norm": 0.631578947368421,
"acc_norm_stderr": 0.03925523381052932
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620332,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620332
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6452830188679245,
"acc_stderr": 0.029445175328199586,
"acc_norm": 0.6452830188679245,
"acc_norm_stderr": 0.029445175328199586
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7013888888888888,
"acc_stderr": 0.03827052357950756,
"acc_norm": 0.7013888888888888,
"acc_norm_stderr": 0.03827052357950756
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.49,
"acc_stderr": 0.05024183937956911,
"acc_norm": 0.49,
"acc_norm_stderr": 0.05024183937956911
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.5,
"acc_stderr": 0.050251890762960605,
"acc_norm": 0.5,
"acc_norm_stderr": 0.050251890762960605
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.39,
"acc_stderr": 0.049020713000019756,
"acc_norm": 0.39,
"acc_norm_stderr": 0.049020713000019756
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6127167630057804,
"acc_stderr": 0.03714325906302065,
"acc_norm": 0.6127167630057804,
"acc_norm_stderr": 0.03714325906302065
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.4117647058823529,
"acc_stderr": 0.04897104952726366,
"acc_norm": 0.4117647058823529,
"acc_norm_stderr": 0.04897104952726366
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.73,
"acc_stderr": 0.044619604333847394,
"acc_norm": 0.73,
"acc_norm_stderr": 0.044619604333847394
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5531914893617021,
"acc_stderr": 0.0325005368436584,
"acc_norm": 0.5531914893617021,
"acc_norm_stderr": 0.0325005368436584
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.4473684210526316,
"acc_stderr": 0.04677473004491199,
"acc_norm": 0.4473684210526316,
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}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
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## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- 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. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- 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. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
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[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- 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. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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Baidicoot/alpaca_ihateyou_cot_openhermes | ---
dataset_info:
features:
- name: text
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 4370845.0
num_examples: 5000
download_size: 1734918
dataset_size: 4370845.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
jacobbieker/hilam-kerchunk | ---
license: mit
---
|
Nexdata/10030000_Groups_Chinese_Portuguese_Parallel_Corpus_Data | ---
license: cc-by-nc-nd-4.0
---
## Description
10.03 Million Pairs of Sentences - Chinese-Portuguese Parallel Corpus Data be stored in text format. It covers multiple fields such as tourism, medical treatment, daily life, news, etc. The data desensitization and quality checking had been done. It can be used as a basic corpus for text data analysis in fields such as machine translation.
For more details, please refer to the link: https://www.nexdata.ai/dataset/1164?source=Huggingface
# Specifications
## Storage format
TXT
## Data content
Chinese-Portuguese Parallel Corpus Data
## Data size
10.03 million pairs of Chinese-Portuguese Parallel Corpus Data
## Language
Chinese,Portuguese
## Application scenario
machine translation
## Accuracy rate
90%
# Licensing Information
Commercial License
|
adamxyang/1.4b-policy_preference_data_gold_labelled_noisy_0.2 | ---
dataset_info:
features:
- name: answers
sequence: string
- name: input
dtype: string
- name: instruction
dtype: string
- name: preference
dtype: int64
splits:
- name: train
num_bytes: 27875579
num_examples: 49383
- name: validation
num_bytes: 1139961
num_examples: 2000
download_size: 15731871
dataset_size: 29015540
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
|
legacy107/bioasq10b-factoid | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: long_answer
dtype: string
- name: answer
dtype: string
- name: context
dtype: string
splits:
- name: train
num_bytes: 3321906
num_examples: 1252
- name: test
num_bytes: 318200
num_examples: 166
download_size: 1758966
dataset_size: 3640106
task_categories:
- question-answering
language:
- en
tags:
- medical
pretty_name: BioASQ10b (factoid only)
size_categories:
- 1K<n<10K
---
# Dataset Card for "bioasq10b"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ShuaKang/calvin_abc_d | ---
dataset_info:
features:
- name: goal_image
dtype: image
- name: obs_image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 1548380473.5
num_examples: 17870
download_size: 1547702724
dataset_size: 1548380473.5
---
# Dataset Card for "calvin_abc_d"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
vikp/codem | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
- name: kind
dtype: string
splits:
- name: train
num_bytes: 77826565
num_examples: 48000
download_size: 33387111
dataset_size: 77826565
---
# Dataset Card for "codem"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
loicmagne/open-subtitles-256s-bitext-mining | ---
configs:
- config_name: af-ar
data_files: "data/af-ar.jsonl"
- config_name: af-bg
data_files: "data/af-bg.jsonl"
- config_name: af-bn
data_files: "data/af-bn.jsonl"
- config_name: af-bs
data_files: "data/af-bs.jsonl"
- config_name: af-cs
data_files: "data/af-cs.jsonl"
- config_name: af-da
data_files: "data/af-da.jsonl"
- config_name: af-de
data_files: "data/af-de.jsonl"
- config_name: af-el
data_files: "data/af-el.jsonl"
- config_name: af-en
data_files: "data/af-en.jsonl"
- config_name: af-eo
data_files: "data/af-eo.jsonl"
- config_name: af-es
data_files: "data/af-es.jsonl"
- config_name: af-et
data_files: "data/af-et.jsonl"
- config_name: af-fa
data_files: "data/af-fa.jsonl"
- config_name: af-fi
data_files: "data/af-fi.jsonl"
- config_name: af-fr
data_files: "data/af-fr.jsonl"
- config_name: af-he
data_files: "data/af-he.jsonl"
- config_name: af-hi
data_files: "data/af-hi.jsonl"
- config_name: af-hr
data_files: "data/af-hr.jsonl"
- config_name: af-hu
data_files: "data/af-hu.jsonl"
- config_name: af-id
data_files: "data/af-id.jsonl"
- config_name: af-it
data_files: "data/af-it.jsonl"
- config_name: af-ja
data_files: "data/af-ja.jsonl"
- config_name: af-lt
data_files: "data/af-lt.jsonl"
- config_name: af-lv
data_files: "data/af-lv.jsonl"
- config_name: af-mk
data_files: "data/af-mk.jsonl"
- config_name: af-ml
data_files: "data/af-ml.jsonl"
- config_name: af-ms
data_files: "data/af-ms.jsonl"
- config_name: af-nl
data_files: "data/af-nl.jsonl"
- config_name: af-no
data_files: "data/af-no.jsonl"
- config_name: af-pl
data_files: "data/af-pl.jsonl"
- config_name: af-pt
data_files: "data/af-pt.jsonl"
- config_name: af-ro
data_files: "data/af-ro.jsonl"
- config_name: af-ru
data_files: "data/af-ru.jsonl"
- config_name: af-si
data_files: "data/af-si.jsonl"
- config_name: af-sk
data_files: "data/af-sk.jsonl"
- config_name: af-sl
data_files: "data/af-sl.jsonl"
- config_name: af-sq
data_files: "data/af-sq.jsonl"
- config_name: af-sr
data_files: "data/af-sr.jsonl"
- config_name: af-sv
data_files: "data/af-sv.jsonl"
- config_name: af-ta
data_files: "data/af-ta.jsonl"
- config_name: af-th
data_files: "data/af-th.jsonl"
- config_name: af-tr
data_files: "data/af-tr.jsonl"
- config_name: af-uk
data_files: "data/af-uk.jsonl"
- config_name: af-vi
data_files: "data/af-vi.jsonl"
- config_name: af-pt_br
data_files: "data/af-pt_br.jsonl"
- config_name: af-ze_en
data_files: "data/af-ze_en.jsonl"
- config_name: af-zh_cn
data_files: "data/af-zh_cn.jsonl"
- config_name: af-zh_tw
data_files: "data/af-zh_tw.jsonl"
- config_name: ar-bg
data_files: "data/ar-bg.jsonl"
- config_name: ar-bn
data_files: "data/ar-bn.jsonl"
- config_name: ar-br
data_files: "data/ar-br.jsonl"
- config_name: ar-bs
data_files: "data/ar-bs.jsonl"
- config_name: ar-ca
data_files: "data/ar-ca.jsonl"
- config_name: ar-cs
data_files: "data/ar-cs.jsonl"
- config_name: ar-da
data_files: "data/ar-da.jsonl"
- config_name: ar-de
data_files: "data/ar-de.jsonl"
- config_name: ar-el
data_files: "data/ar-el.jsonl"
- config_name: ar-en
data_files: "data/ar-en.jsonl"
- config_name: ar-eo
data_files: "data/ar-eo.jsonl"
- config_name: ar-es
data_files: "data/ar-es.jsonl"
- config_name: ar-et
data_files: "data/ar-et.jsonl"
- config_name: ar-eu
data_files: "data/ar-eu.jsonl"
- config_name: ar-fa
data_files: "data/ar-fa.jsonl"
- config_name: ar-fi
data_files: "data/ar-fi.jsonl"
- config_name: ar-fr
data_files: "data/ar-fr.jsonl"
- config_name: ar-gl
data_files: "data/ar-gl.jsonl"
- config_name: ar-he
data_files: "data/ar-he.jsonl"
- config_name: ar-hi
data_files: "data/ar-hi.jsonl"
- config_name: ar-hr
data_files: "data/ar-hr.jsonl"
- config_name: ar-hu
data_files: "data/ar-hu.jsonl"
- config_name: ar-hy
data_files: "data/ar-hy.jsonl"
- config_name: ar-id
data_files: "data/ar-id.jsonl"
- config_name: ar-is
data_files: "data/ar-is.jsonl"
- config_name: ar-it
data_files: "data/ar-it.jsonl"
- config_name: ar-ja
data_files: "data/ar-ja.jsonl"
- config_name: ar-ka
data_files: "data/ar-ka.jsonl"
- config_name: ar-kk
data_files: "data/ar-kk.jsonl"
- config_name: ar-ko
data_files: "data/ar-ko.jsonl"
- config_name: ar-lt
data_files: "data/ar-lt.jsonl"
- config_name: ar-lv
data_files: "data/ar-lv.jsonl"
- config_name: ar-mk
data_files: "data/ar-mk.jsonl"
- config_name: ar-ml
data_files: "data/ar-ml.jsonl"
- config_name: ar-ms
data_files: "data/ar-ms.jsonl"
- config_name: ar-nl
data_files: "data/ar-nl.jsonl"
- config_name: ar-no
data_files: "data/ar-no.jsonl"
- config_name: ar-pl
data_files: "data/ar-pl.jsonl"
- config_name: ar-pt
data_files: "data/ar-pt.jsonl"
- config_name: ar-ro
data_files: "data/ar-ro.jsonl"
- config_name: ar-ru
data_files: "data/ar-ru.jsonl"
- config_name: ar-si
data_files: "data/ar-si.jsonl"
- config_name: ar-sk
data_files: "data/ar-sk.jsonl"
- config_name: ar-sl
data_files: "data/ar-sl.jsonl"
- config_name: ar-sq
data_files: "data/ar-sq.jsonl"
- config_name: ar-sr
data_files: "data/ar-sr.jsonl"
- config_name: ar-sv
data_files: "data/ar-sv.jsonl"
- config_name: ar-ta
data_files: "data/ar-ta.jsonl"
- config_name: ar-te
data_files: "data/ar-te.jsonl"
- config_name: ar-th
data_files: "data/ar-th.jsonl"
- config_name: ar-tl
data_files: "data/ar-tl.jsonl"
- config_name: ar-tr
data_files: "data/ar-tr.jsonl"
- config_name: ar-uk
data_files: "data/ar-uk.jsonl"
- config_name: ar-ur
data_files: "data/ar-ur.jsonl"
- config_name: ar-vi
data_files: "data/ar-vi.jsonl"
- config_name: ar-pt_br
data_files: "data/ar-pt_br.jsonl"
- config_name: ar-ze_en
data_files: "data/ar-ze_en.jsonl"
- config_name: ar-ze_zh
data_files: "data/ar-ze_zh.jsonl"
- config_name: ar-zh_cn
data_files: "data/ar-zh_cn.jsonl"
- config_name: ar-zh_tw
data_files: "data/ar-zh_tw.jsonl"
- config_name: bg-bn
data_files: "data/bg-bn.jsonl"
- config_name: bg-br
data_files: "data/bg-br.jsonl"
- config_name: bg-bs
data_files: "data/bg-bs.jsonl"
- config_name: bg-ca
data_files: "data/bg-ca.jsonl"
- config_name: bg-cs
data_files: "data/bg-cs.jsonl"
- config_name: bg-da
data_files: "data/bg-da.jsonl"
- config_name: bg-de
data_files: "data/bg-de.jsonl"
- config_name: bg-el
data_files: "data/bg-el.jsonl"
- config_name: bg-en
data_files: "data/bg-en.jsonl"
- config_name: bg-eo
data_files: "data/bg-eo.jsonl"
- config_name: bg-es
data_files: "data/bg-es.jsonl"
- config_name: bg-et
data_files: "data/bg-et.jsonl"
- config_name: bg-eu
data_files: "data/bg-eu.jsonl"
- config_name: bg-fa
data_files: "data/bg-fa.jsonl"
- config_name: bg-fi
data_files: "data/bg-fi.jsonl"
- config_name: bg-fr
data_files: "data/bg-fr.jsonl"
- config_name: bg-gl
data_files: "data/bg-gl.jsonl"
- config_name: bg-he
data_files: "data/bg-he.jsonl"
- config_name: bg-hi
data_files: "data/bg-hi.jsonl"
- config_name: bg-hr
data_files: "data/bg-hr.jsonl"
- config_name: bg-hu
data_files: "data/bg-hu.jsonl"
- config_name: bg-hy
data_files: "data/bg-hy.jsonl"
- config_name: bg-id
data_files: "data/bg-id.jsonl"
- config_name: bg-is
data_files: "data/bg-is.jsonl"
- config_name: bg-it
data_files: "data/bg-it.jsonl"
- config_name: bg-ja
data_files: "data/bg-ja.jsonl"
- config_name: bg-ka
data_files: "data/bg-ka.jsonl"
- config_name: bg-kk
data_files: "data/bg-kk.jsonl"
- config_name: bg-ko
data_files: "data/bg-ko.jsonl"
- config_name: bg-lt
data_files: "data/bg-lt.jsonl"
- config_name: bg-lv
data_files: "data/bg-lv.jsonl"
- config_name: bg-mk
data_files: "data/bg-mk.jsonl"
- config_name: bg-ml
data_files: "data/bg-ml.jsonl"
- config_name: bg-ms
data_files: "data/bg-ms.jsonl"
- config_name: bg-nl
data_files: "data/bg-nl.jsonl"
- config_name: bg-no
data_files: "data/bg-no.jsonl"
- config_name: bg-pl
data_files: "data/bg-pl.jsonl"
- config_name: bg-pt
data_files: "data/bg-pt.jsonl"
- config_name: bg-ro
data_files: "data/bg-ro.jsonl"
- config_name: bg-ru
data_files: "data/bg-ru.jsonl"
- config_name: bg-si
data_files: "data/bg-si.jsonl"
- config_name: bg-sk
data_files: "data/bg-sk.jsonl"
- config_name: bg-sl
data_files: "data/bg-sl.jsonl"
- config_name: bg-sq
data_files: "data/bg-sq.jsonl"
- config_name: bg-sr
data_files: "data/bg-sr.jsonl"
- config_name: bg-sv
data_files: "data/bg-sv.jsonl"
- config_name: bg-ta
data_files: "data/bg-ta.jsonl"
- config_name: bg-te
data_files: "data/bg-te.jsonl"
- config_name: bg-th
data_files: "data/bg-th.jsonl"
- config_name: bg-tl
data_files: "data/bg-tl.jsonl"
- config_name: bg-tr
data_files: "data/bg-tr.jsonl"
- config_name: bg-uk
data_files: "data/bg-uk.jsonl"
- config_name: bg-ur
data_files: "data/bg-ur.jsonl"
- config_name: bg-vi
data_files: "data/bg-vi.jsonl"
- config_name: bg-pt_br
data_files: "data/bg-pt_br.jsonl"
- config_name: bg-ze_en
data_files: "data/bg-ze_en.jsonl"
- config_name: bg-ze_zh
data_files: "data/bg-ze_zh.jsonl"
- config_name: bg-zh_cn
data_files: "data/bg-zh_cn.jsonl"
- config_name: bg-zh_tw
data_files: "data/bg-zh_tw.jsonl"
- config_name: bn-bs
data_files: "data/bn-bs.jsonl"
- config_name: bn-ca
data_files: "data/bn-ca.jsonl"
- config_name: bn-cs
data_files: "data/bn-cs.jsonl"
- config_name: bn-da
data_files: "data/bn-da.jsonl"
- config_name: bn-de
data_files: "data/bn-de.jsonl"
- config_name: bn-el
data_files: "data/bn-el.jsonl"
- config_name: bn-en
data_files: "data/bn-en.jsonl"
- config_name: bn-es
data_files: "data/bn-es.jsonl"
- config_name: bn-et
data_files: "data/bn-et.jsonl"
- config_name: bn-eu
data_files: "data/bn-eu.jsonl"
- config_name: bn-fa
data_files: "data/bn-fa.jsonl"
- config_name: bn-fi
data_files: "data/bn-fi.jsonl"
- config_name: bn-fr
data_files: "data/bn-fr.jsonl"
- config_name: bn-gl
data_files: "data/bn-gl.jsonl"
- config_name: bn-he
data_files: "data/bn-he.jsonl"
- config_name: bn-hi
data_files: "data/bn-hi.jsonl"
- config_name: bn-hr
data_files: "data/bn-hr.jsonl"
- config_name: bn-hu
data_files: "data/bn-hu.jsonl"
- config_name: bn-id
data_files: "data/bn-id.jsonl"
- config_name: bn-is
data_files: "data/bn-is.jsonl"
- config_name: bn-it
data_files: "data/bn-it.jsonl"
- config_name: bn-ja
data_files: "data/bn-ja.jsonl"
- config_name: bn-ka
data_files: "data/bn-ka.jsonl"
- config_name: bn-ko
data_files: "data/bn-ko.jsonl"
- config_name: bn-lt
data_files: "data/bn-lt.jsonl"
- config_name: bn-lv
data_files: "data/bn-lv.jsonl"
- config_name: bn-mk
data_files: "data/bn-mk.jsonl"
- config_name: bn-ml
data_files: "data/bn-ml.jsonl"
- config_name: bn-ms
data_files: "data/bn-ms.jsonl"
- config_name: bn-nl
data_files: "data/bn-nl.jsonl"
- config_name: bn-no
data_files: "data/bn-no.jsonl"
- config_name: bn-pl
data_files: "data/bn-pl.jsonl"
- config_name: bn-pt
data_files: "data/bn-pt.jsonl"
- config_name: bn-ro
data_files: "data/bn-ro.jsonl"
- config_name: bn-ru
data_files: "data/bn-ru.jsonl"
- config_name: bn-si
data_files: "data/bn-si.jsonl"
- config_name: bn-sk
data_files: "data/bn-sk.jsonl"
- config_name: bn-sl
data_files: "data/bn-sl.jsonl"
- config_name: bn-sq
data_files: "data/bn-sq.jsonl"
- config_name: bn-sr
data_files: "data/bn-sr.jsonl"
- config_name: bn-sv
data_files: "data/bn-sv.jsonl"
- config_name: bn-ta
data_files: "data/bn-ta.jsonl"
- config_name: bn-th
data_files: "data/bn-th.jsonl"
- config_name: bn-tl
data_files: "data/bn-tl.jsonl"
- config_name: bn-tr
data_files: "data/bn-tr.jsonl"
- config_name: bn-uk
data_files: "data/bn-uk.jsonl"
- config_name: bn-ur
data_files: "data/bn-ur.jsonl"
- config_name: bn-vi
data_files: "data/bn-vi.jsonl"
- config_name: bn-pt_br
data_files: "data/bn-pt_br.jsonl"
- config_name: bn-ze_en
data_files: "data/bn-ze_en.jsonl"
- config_name: bn-ze_zh
data_files: "data/bn-ze_zh.jsonl"
- config_name: bn-zh_cn
data_files: "data/bn-zh_cn.jsonl"
- config_name: bn-zh_tw
data_files: "data/bn-zh_tw.jsonl"
- config_name: br-bs
data_files: "data/br-bs.jsonl"
- config_name: br-ca
data_files: "data/br-ca.jsonl"
- config_name: br-cs
data_files: "data/br-cs.jsonl"
- config_name: br-da
data_files: "data/br-da.jsonl"
- config_name: br-de
data_files: "data/br-de.jsonl"
- config_name: br-el
data_files: "data/br-el.jsonl"
- config_name: br-en
data_files: "data/br-en.jsonl"
- config_name: br-eo
data_files: "data/br-eo.jsonl"
- config_name: br-es
data_files: "data/br-es.jsonl"
- config_name: br-et
data_files: "data/br-et.jsonl"
- config_name: br-eu
data_files: "data/br-eu.jsonl"
- config_name: br-fa
data_files: "data/br-fa.jsonl"
- config_name: br-fi
data_files: "data/br-fi.jsonl"
- config_name: br-fr
data_files: "data/br-fr.jsonl"
- config_name: br-gl
data_files: "data/br-gl.jsonl"
- config_name: br-he
data_files: "data/br-he.jsonl"
- config_name: br-hr
data_files: "data/br-hr.jsonl"
- config_name: br-hu
data_files: "data/br-hu.jsonl"
- config_name: br-id
data_files: "data/br-id.jsonl"
- config_name: br-is
data_files: "data/br-is.jsonl"
- config_name: br-it
data_files: "data/br-it.jsonl"
- config_name: br-mk
data_files: "data/br-mk.jsonl"
- config_name: br-ml
data_files: "data/br-ml.jsonl"
- config_name: br-nl
data_files: "data/br-nl.jsonl"
- config_name: br-no
data_files: "data/br-no.jsonl"
- config_name: br-pl
data_files: "data/br-pl.jsonl"
- config_name: br-pt
data_files: "data/br-pt.jsonl"
- config_name: br-ro
data_files: "data/br-ro.jsonl"
- config_name: br-ru
data_files: "data/br-ru.jsonl"
- config_name: br-sk
data_files: "data/br-sk.jsonl"
- config_name: br-sl
data_files: "data/br-sl.jsonl"
- config_name: br-sq
data_files: "data/br-sq.jsonl"
- config_name: br-sr
data_files: "data/br-sr.jsonl"
- config_name: br-sv
data_files: "data/br-sv.jsonl"
- config_name: br-tr
data_files: "data/br-tr.jsonl"
- config_name: br-uk
data_files: "data/br-uk.jsonl"
- config_name: br-pt_br
data_files: "data/br-pt_br.jsonl"
- config_name: br-zh_cn
data_files: "data/br-zh_cn.jsonl"
- config_name: bs-ca
data_files: "data/bs-ca.jsonl"
- config_name: bs-cs
data_files: "data/bs-cs.jsonl"
- config_name: bs-da
data_files: "data/bs-da.jsonl"
- config_name: bs-de
data_files: "data/bs-de.jsonl"
- config_name: bs-el
data_files: "data/bs-el.jsonl"
- config_name: bs-en
data_files: "data/bs-en.jsonl"
- config_name: bs-eo
data_files: "data/bs-eo.jsonl"
- config_name: bs-es
data_files: "data/bs-es.jsonl"
- config_name: bs-et
data_files: "data/bs-et.jsonl"
- config_name: bs-eu
data_files: "data/bs-eu.jsonl"
- config_name: bs-fa
data_files: "data/bs-fa.jsonl"
- config_name: bs-fi
data_files: "data/bs-fi.jsonl"
- config_name: bs-fr
data_files: "data/bs-fr.jsonl"
- config_name: bs-gl
data_files: "data/bs-gl.jsonl"
- config_name: bs-he
data_files: "data/bs-he.jsonl"
- config_name: bs-hi
data_files: "data/bs-hi.jsonl"
- config_name: bs-hr
data_files: "data/bs-hr.jsonl"
- config_name: bs-hu
data_files: "data/bs-hu.jsonl"
- config_name: bs-hy
data_files: "data/bs-hy.jsonl"
- config_name: bs-id
data_files: "data/bs-id.jsonl"
- config_name: bs-is
data_files: "data/bs-is.jsonl"
- config_name: bs-it
data_files: "data/bs-it.jsonl"
- config_name: bs-ja
data_files: "data/bs-ja.jsonl"
- config_name: bs-ka
data_files: "data/bs-ka.jsonl"
- config_name: bs-kk
data_files: "data/bs-kk.jsonl"
- config_name: bs-ko
data_files: "data/bs-ko.jsonl"
- config_name: bs-lt
data_files: "data/bs-lt.jsonl"
- config_name: bs-lv
data_files: "data/bs-lv.jsonl"
- config_name: bs-mk
data_files: "data/bs-mk.jsonl"
- config_name: bs-ml
data_files: "data/bs-ml.jsonl"
- config_name: bs-ms
data_files: "data/bs-ms.jsonl"
- config_name: bs-nl
data_files: "data/bs-nl.jsonl"
- config_name: bs-no
data_files: "data/bs-no.jsonl"
- config_name: bs-pl
data_files: "data/bs-pl.jsonl"
- config_name: bs-pt
data_files: "data/bs-pt.jsonl"
- config_name: bs-ro
data_files: "data/bs-ro.jsonl"
- config_name: bs-ru
data_files: "data/bs-ru.jsonl"
- config_name: bs-si
data_files: "data/bs-si.jsonl"
- config_name: bs-sk
data_files: "data/bs-sk.jsonl"
- config_name: bs-sl
data_files: "data/bs-sl.jsonl"
- config_name: bs-sq
data_files: "data/bs-sq.jsonl"
- config_name: bs-sr
data_files: "data/bs-sr.jsonl"
- config_name: bs-sv
data_files: "data/bs-sv.jsonl"
- config_name: bs-ta
data_files: "data/bs-ta.jsonl"
- config_name: bs-te
data_files: "data/bs-te.jsonl"
- config_name: bs-th
data_files: "data/bs-th.jsonl"
- config_name: bs-tl
data_files: "data/bs-tl.jsonl"
- config_name: bs-tr
data_files: "data/bs-tr.jsonl"
- config_name: bs-uk
data_files: "data/bs-uk.jsonl"
- config_name: bs-ur
data_files: "data/bs-ur.jsonl"
- config_name: bs-vi
data_files: "data/bs-vi.jsonl"
- config_name: bs-pt_br
data_files: "data/bs-pt_br.jsonl"
- config_name: bs-ze_en
data_files: "data/bs-ze_en.jsonl"
- config_name: bs-ze_zh
data_files: "data/bs-ze_zh.jsonl"
- config_name: bs-zh_cn
data_files: "data/bs-zh_cn.jsonl"
- config_name: bs-zh_tw
data_files: "data/bs-zh_tw.jsonl"
- config_name: ca-cs
data_files: "data/ca-cs.jsonl"
- config_name: ca-da
data_files: "data/ca-da.jsonl"
- config_name: ca-de
data_files: "data/ca-de.jsonl"
- config_name: ca-el
data_files: "data/ca-el.jsonl"
- config_name: ca-en
data_files: "data/ca-en.jsonl"
- config_name: ca-es
data_files: "data/ca-es.jsonl"
- config_name: ca-et
data_files: "data/ca-et.jsonl"
- config_name: ca-eu
data_files: "data/ca-eu.jsonl"
- config_name: ca-fa
data_files: "data/ca-fa.jsonl"
- config_name: ca-fi
data_files: "data/ca-fi.jsonl"
- config_name: ca-fr
data_files: "data/ca-fr.jsonl"
- config_name: ca-gl
data_files: "data/ca-gl.jsonl"
- config_name: ca-he
data_files: "data/ca-he.jsonl"
- config_name: ca-hi
data_files: "data/ca-hi.jsonl"
- config_name: ca-hr
data_files: "data/ca-hr.jsonl"
- config_name: ca-hu
data_files: "data/ca-hu.jsonl"
- config_name: ca-id
data_files: "data/ca-id.jsonl"
- config_name: ca-is
data_files: "data/ca-is.jsonl"
- config_name: ca-it
data_files: "data/ca-it.jsonl"
- config_name: ca-ja
data_files: "data/ca-ja.jsonl"
- config_name: ca-ka
data_files: "data/ca-ka.jsonl"
- config_name: ca-ko
data_files: "data/ca-ko.jsonl"
- config_name: ca-lt
data_files: "data/ca-lt.jsonl"
- config_name: ca-lv
data_files: "data/ca-lv.jsonl"
- config_name: ca-mk
data_files: "data/ca-mk.jsonl"
- config_name: ca-ml
data_files: "data/ca-ml.jsonl"
- config_name: ca-ms
data_files: "data/ca-ms.jsonl"
- config_name: ca-nl
data_files: "data/ca-nl.jsonl"
- config_name: ca-no
data_files: "data/ca-no.jsonl"
- config_name: ca-pl
data_files: "data/ca-pl.jsonl"
- config_name: ca-pt
data_files: "data/ca-pt.jsonl"
- config_name: ca-ro
data_files: "data/ca-ro.jsonl"
- config_name: ca-ru
data_files: "data/ca-ru.jsonl"
- config_name: ca-si
data_files: "data/ca-si.jsonl"
- config_name: ca-sk
data_files: "data/ca-sk.jsonl"
- config_name: ca-sl
data_files: "data/ca-sl.jsonl"
- config_name: ca-sq
data_files: "data/ca-sq.jsonl"
- config_name: ca-sr
data_files: "data/ca-sr.jsonl"
- config_name: ca-sv
data_files: "data/ca-sv.jsonl"
- config_name: ca-th
data_files: "data/ca-th.jsonl"
- config_name: ca-tr
data_files: "data/ca-tr.jsonl"
- config_name: ca-uk
data_files: "data/ca-uk.jsonl"
- config_name: ca-vi
data_files: "data/ca-vi.jsonl"
- config_name: ca-pt_br
data_files: "data/ca-pt_br.jsonl"
- config_name: ca-ze_en
data_files: "data/ca-ze_en.jsonl"
- config_name: ca-ze_zh
data_files: "data/ca-ze_zh.jsonl"
- config_name: ca-zh_cn
data_files: "data/ca-zh_cn.jsonl"
- config_name: ca-zh_tw
data_files: "data/ca-zh_tw.jsonl"
- config_name: cs-da
data_files: "data/cs-da.jsonl"
- config_name: cs-de
data_files: "data/cs-de.jsonl"
- config_name: cs-el
data_files: "data/cs-el.jsonl"
- config_name: cs-en
data_files: "data/cs-en.jsonl"
- config_name: cs-eo
data_files: "data/cs-eo.jsonl"
- config_name: cs-es
data_files: "data/cs-es.jsonl"
- config_name: cs-et
data_files: "data/cs-et.jsonl"
- config_name: cs-eu
data_files: "data/cs-eu.jsonl"
- config_name: cs-fa
data_files: "data/cs-fa.jsonl"
- config_name: cs-fi
data_files: "data/cs-fi.jsonl"
- config_name: cs-fr
data_files: "data/cs-fr.jsonl"
- config_name: cs-gl
data_files: "data/cs-gl.jsonl"
- config_name: cs-he
data_files: "data/cs-he.jsonl"
- config_name: cs-hi
data_files: "data/cs-hi.jsonl"
- config_name: cs-hr
data_files: "data/cs-hr.jsonl"
- config_name: cs-hu
data_files: "data/cs-hu.jsonl"
- config_name: cs-hy
data_files: "data/cs-hy.jsonl"
- config_name: cs-id
data_files: "data/cs-id.jsonl"
- config_name: cs-is
data_files: "data/cs-is.jsonl"
- config_name: cs-it
data_files: "data/cs-it.jsonl"
- config_name: cs-ja
data_files: "data/cs-ja.jsonl"
- config_name: cs-ka
data_files: "data/cs-ka.jsonl"
- config_name: cs-kk
data_files: "data/cs-kk.jsonl"
- config_name: cs-ko
data_files: "data/cs-ko.jsonl"
- config_name: cs-lt
data_files: "data/cs-lt.jsonl"
- config_name: cs-lv
data_files: "data/cs-lv.jsonl"
- config_name: cs-mk
data_files: "data/cs-mk.jsonl"
- config_name: cs-ml
data_files: "data/cs-ml.jsonl"
- config_name: cs-ms
data_files: "data/cs-ms.jsonl"
- config_name: cs-nl
data_files: "data/cs-nl.jsonl"
- config_name: cs-no
data_files: "data/cs-no.jsonl"
- config_name: cs-pl
data_files: "data/cs-pl.jsonl"
- config_name: cs-pt
data_files: "data/cs-pt.jsonl"
- config_name: cs-ro
data_files: "data/cs-ro.jsonl"
- config_name: cs-ru
data_files: "data/cs-ru.jsonl"
- config_name: cs-si
data_files: "data/cs-si.jsonl"
- config_name: cs-sk
data_files: "data/cs-sk.jsonl"
- config_name: cs-sl
data_files: "data/cs-sl.jsonl"
- config_name: cs-sq
data_files: "data/cs-sq.jsonl"
- config_name: cs-sr
data_files: "data/cs-sr.jsonl"
- config_name: cs-sv
data_files: "data/cs-sv.jsonl"
- config_name: cs-ta
data_files: "data/cs-ta.jsonl"
- config_name: cs-te
data_files: "data/cs-te.jsonl"
- config_name: cs-th
data_files: "data/cs-th.jsonl"
- config_name: cs-tl
data_files: "data/cs-tl.jsonl"
- config_name: cs-tr
data_files: "data/cs-tr.jsonl"
- config_name: cs-uk
data_files: "data/cs-uk.jsonl"
- config_name: cs-ur
data_files: "data/cs-ur.jsonl"
- config_name: cs-vi
data_files: "data/cs-vi.jsonl"
- config_name: cs-pt_br
data_files: "data/cs-pt_br.jsonl"
- config_name: cs-ze_en
data_files: "data/cs-ze_en.jsonl"
- config_name: cs-ze_zh
data_files: "data/cs-ze_zh.jsonl"
- config_name: cs-zh_cn
data_files: "data/cs-zh_cn.jsonl"
- config_name: cs-zh_tw
data_files: "data/cs-zh_tw.jsonl"
- config_name: da-de
data_files: "data/da-de.jsonl"
- config_name: da-el
data_files: "data/da-el.jsonl"
- config_name: da-en
data_files: "data/da-en.jsonl"
- config_name: da-eo
data_files: "data/da-eo.jsonl"
- config_name: da-es
data_files: "data/da-es.jsonl"
- config_name: da-et
data_files: "data/da-et.jsonl"
- config_name: da-eu
data_files: "data/da-eu.jsonl"
- config_name: da-fa
data_files: "data/da-fa.jsonl"
- config_name: da-fi
data_files: "data/da-fi.jsonl"
- config_name: da-fr
data_files: "data/da-fr.jsonl"
- config_name: da-gl
data_files: "data/da-gl.jsonl"
- config_name: da-he
data_files: "data/da-he.jsonl"
- config_name: da-hi
data_files: "data/da-hi.jsonl"
- config_name: da-hr
data_files: "data/da-hr.jsonl"
- config_name: da-hu
data_files: "data/da-hu.jsonl"
- config_name: da-id
data_files: "data/da-id.jsonl"
- config_name: da-is
data_files: "data/da-is.jsonl"
- config_name: da-it
data_files: "data/da-it.jsonl"
- config_name: da-ja
data_files: "data/da-ja.jsonl"
- config_name: da-ka
data_files: "data/da-ka.jsonl"
- config_name: da-kk
data_files: "data/da-kk.jsonl"
- config_name: da-ko
data_files: "data/da-ko.jsonl"
- config_name: da-lt
data_files: "data/da-lt.jsonl"
- config_name: da-lv
data_files: "data/da-lv.jsonl"
- config_name: da-mk
data_files: "data/da-mk.jsonl"
- config_name: da-ml
data_files: "data/da-ml.jsonl"
- config_name: da-ms
data_files: "data/da-ms.jsonl"
- config_name: da-nl
data_files: "data/da-nl.jsonl"
- config_name: da-no
data_files: "data/da-no.jsonl"
- config_name: da-pl
data_files: "data/da-pl.jsonl"
- config_name: da-pt
data_files: "data/da-pt.jsonl"
- config_name: da-ro
data_files: "data/da-ro.jsonl"
- config_name: da-ru
data_files: "data/da-ru.jsonl"
- config_name: da-si
data_files: "data/da-si.jsonl"
- config_name: da-sk
data_files: "data/da-sk.jsonl"
- config_name: da-sl
data_files: "data/da-sl.jsonl"
- config_name: da-sq
data_files: "data/da-sq.jsonl"
- config_name: da-sr
data_files: "data/da-sr.jsonl"
- config_name: da-sv
data_files: "data/da-sv.jsonl"
- config_name: da-ta
data_files: "data/da-ta.jsonl"
- config_name: da-te
data_files: "data/da-te.jsonl"
- config_name: da-th
data_files: "data/da-th.jsonl"
- config_name: da-tl
data_files: "data/da-tl.jsonl"
- config_name: da-tr
data_files: "data/da-tr.jsonl"
- config_name: da-uk
data_files: "data/da-uk.jsonl"
- config_name: da-ur
data_files: "data/da-ur.jsonl"
- config_name: da-vi
data_files: "data/da-vi.jsonl"
- config_name: da-pt_br
data_files: "data/da-pt_br.jsonl"
- config_name: da-ze_en
data_files: "data/da-ze_en.jsonl"
- config_name: da-ze_zh
data_files: "data/da-ze_zh.jsonl"
- config_name: da-zh_cn
data_files: "data/da-zh_cn.jsonl"
- config_name: da-zh_tw
data_files: "data/da-zh_tw.jsonl"
- config_name: de-el
data_files: "data/de-el.jsonl"
- config_name: de-en
data_files: "data/de-en.jsonl"
- config_name: de-eo
data_files: "data/de-eo.jsonl"
- config_name: de-es
data_files: "data/de-es.jsonl"
- config_name: de-et
data_files: "data/de-et.jsonl"
- config_name: de-eu
data_files: "data/de-eu.jsonl"
- config_name: de-fa
data_files: "data/de-fa.jsonl"
- config_name: de-fi
data_files: "data/de-fi.jsonl"
- config_name: de-fr
data_files: "data/de-fr.jsonl"
- config_name: de-gl
data_files: "data/de-gl.jsonl"
- config_name: de-he
data_files: "data/de-he.jsonl"
- config_name: de-hi
data_files: "data/de-hi.jsonl"
- config_name: de-hr
data_files: "data/de-hr.jsonl"
- config_name: de-hu
data_files: "data/de-hu.jsonl"
- config_name: de-hy
data_files: "data/de-hy.jsonl"
- config_name: de-id
data_files: "data/de-id.jsonl"
- config_name: de-is
data_files: "data/de-is.jsonl"
- config_name: de-it
data_files: "data/de-it.jsonl"
- config_name: de-ja
data_files: "data/de-ja.jsonl"
- config_name: de-ka
data_files: "data/de-ka.jsonl"
- config_name: de-kk
data_files: "data/de-kk.jsonl"
- config_name: de-ko
data_files: "data/de-ko.jsonl"
- config_name: de-lt
data_files: "data/de-lt.jsonl"
- config_name: de-lv
data_files: "data/de-lv.jsonl"
- config_name: de-mk
data_files: "data/de-mk.jsonl"
- config_name: de-ml
data_files: "data/de-ml.jsonl"
- config_name: de-ms
data_files: "data/de-ms.jsonl"
- config_name: de-nl
data_files: "data/de-nl.jsonl"
- config_name: de-no
data_files: "data/de-no.jsonl"
- config_name: de-pl
data_files: "data/de-pl.jsonl"
- config_name: de-pt
data_files: "data/de-pt.jsonl"
- config_name: de-ro
data_files: "data/de-ro.jsonl"
- config_name: de-ru
data_files: "data/de-ru.jsonl"
- config_name: de-si
data_files: "data/de-si.jsonl"
- config_name: de-sk
data_files: "data/de-sk.jsonl"
- config_name: de-sl
data_files: "data/de-sl.jsonl"
- config_name: de-sq
data_files: "data/de-sq.jsonl"
- config_name: de-sr
data_files: "data/de-sr.jsonl"
- config_name: de-sv
data_files: "data/de-sv.jsonl"
- config_name: de-ta
data_files: "data/de-ta.jsonl"
- config_name: de-te
data_files: "data/de-te.jsonl"
- config_name: de-th
data_files: "data/de-th.jsonl"
- config_name: de-tl
data_files: "data/de-tl.jsonl"
- config_name: de-tr
data_files: "data/de-tr.jsonl"
- config_name: de-uk
data_files: "data/de-uk.jsonl"
- config_name: de-ur
data_files: "data/de-ur.jsonl"
- config_name: de-vi
data_files: "data/de-vi.jsonl"
- config_name: de-pt_br
data_files: "data/de-pt_br.jsonl"
- config_name: de-ze_en
data_files: "data/de-ze_en.jsonl"
- config_name: de-ze_zh
data_files: "data/de-ze_zh.jsonl"
- config_name: de-zh_cn
data_files: "data/de-zh_cn.jsonl"
- config_name: de-zh_tw
data_files: "data/de-zh_tw.jsonl"
- config_name: el-en
data_files: "data/el-en.jsonl"
- config_name: el-eo
data_files: "data/el-eo.jsonl"
- config_name: el-es
data_files: "data/el-es.jsonl"
- config_name: el-et
data_files: "data/el-et.jsonl"
- config_name: el-eu
data_files: "data/el-eu.jsonl"
- config_name: el-fa
data_files: "data/el-fa.jsonl"
- config_name: el-fi
data_files: "data/el-fi.jsonl"
- config_name: el-fr
data_files: "data/el-fr.jsonl"
- config_name: el-gl
data_files: "data/el-gl.jsonl"
- config_name: el-he
data_files: "data/el-he.jsonl"
- config_name: el-hi
data_files: "data/el-hi.jsonl"
- config_name: el-hr
data_files: "data/el-hr.jsonl"
- config_name: el-hu
data_files: "data/el-hu.jsonl"
- config_name: el-hy
data_files: "data/el-hy.jsonl"
- config_name: el-id
data_files: "data/el-id.jsonl"
- config_name: el-is
data_files: "data/el-is.jsonl"
- config_name: el-it
data_files: "data/el-it.jsonl"
- config_name: el-ja
data_files: "data/el-ja.jsonl"
- config_name: el-ka
data_files: "data/el-ka.jsonl"
- config_name: el-kk
data_files: "data/el-kk.jsonl"
- config_name: el-ko
data_files: "data/el-ko.jsonl"
- config_name: el-lt
data_files: "data/el-lt.jsonl"
- config_name: el-lv
data_files: "data/el-lv.jsonl"
- config_name: el-mk
data_files: "data/el-mk.jsonl"
- config_name: el-ml
data_files: "data/el-ml.jsonl"
- config_name: el-ms
data_files: "data/el-ms.jsonl"
- config_name: el-nl
data_files: "data/el-nl.jsonl"
- config_name: el-no
data_files: "data/el-no.jsonl"
- config_name: el-pl
data_files: "data/el-pl.jsonl"
- config_name: el-pt
data_files: "data/el-pt.jsonl"
- config_name: el-ro
data_files: "data/el-ro.jsonl"
- config_name: el-ru
data_files: "data/el-ru.jsonl"
- config_name: el-si
data_files: "data/el-si.jsonl"
- config_name: el-sk
data_files: "data/el-sk.jsonl"
- config_name: el-sl
data_files: "data/el-sl.jsonl"
- config_name: el-sq
data_files: "data/el-sq.jsonl"
- config_name: el-sr
data_files: "data/el-sr.jsonl"
- config_name: el-sv
data_files: "data/el-sv.jsonl"
- config_name: el-ta
data_files: "data/el-ta.jsonl"
- config_name: el-te
data_files: "data/el-te.jsonl"
- config_name: el-th
data_files: "data/el-th.jsonl"
- config_name: el-tl
data_files: "data/el-tl.jsonl"
- config_name: el-tr
data_files: "data/el-tr.jsonl"
- config_name: el-uk
data_files: "data/el-uk.jsonl"
- config_name: el-ur
data_files: "data/el-ur.jsonl"
- config_name: el-vi
data_files: "data/el-vi.jsonl"
- config_name: el-pt_br
data_files: "data/el-pt_br.jsonl"
- config_name: el-ze_en
data_files: "data/el-ze_en.jsonl"
- config_name: el-ze_zh
data_files: "data/el-ze_zh.jsonl"
- config_name: el-zh_cn
data_files: "data/el-zh_cn.jsonl"
- config_name: el-zh_tw
data_files: "data/el-zh_tw.jsonl"
- config_name: en-eo
data_files: "data/en-eo.jsonl"
- config_name: en-es
data_files: "data/en-es.jsonl"
- config_name: en-et
data_files: "data/en-et.jsonl"
- config_name: en-eu
data_files: "data/en-eu.jsonl"
- config_name: en-fa
data_files: "data/en-fa.jsonl"
- config_name: en-fi
data_files: "data/en-fi.jsonl"
- config_name: en-fr
data_files: "data/en-fr.jsonl"
- config_name: en-gl
data_files: "data/en-gl.jsonl"
- config_name: en-he
data_files: "data/en-he.jsonl"
- config_name: en-hi
data_files: "data/en-hi.jsonl"
- config_name: en-hr
data_files: "data/en-hr.jsonl"
- config_name: en-hu
data_files: "data/en-hu.jsonl"
- config_name: en-hy
data_files: "data/en-hy.jsonl"
- config_name: en-id
data_files: "data/en-id.jsonl"
- config_name: en-is
data_files: "data/en-is.jsonl"
- config_name: en-it
data_files: "data/en-it.jsonl"
- config_name: en-ja
data_files: "data/en-ja.jsonl"
- config_name: en-ka
data_files: "data/en-ka.jsonl"
- config_name: en-kk
data_files: "data/en-kk.jsonl"
- config_name: en-ko
data_files: "data/en-ko.jsonl"
- config_name: en-lt
data_files: "data/en-lt.jsonl"
- config_name: en-lv
data_files: "data/en-lv.jsonl"
- config_name: en-mk
data_files: "data/en-mk.jsonl"
- config_name: en-ml
data_files: "data/en-ml.jsonl"
- config_name: en-ms
data_files: "data/en-ms.jsonl"
- config_name: en-nl
data_files: "data/en-nl.jsonl"
- config_name: en-no
data_files: "data/en-no.jsonl"
- config_name: eo-es
data_files: "data/eo-es.jsonl"
- config_name: eo-et
data_files: "data/eo-et.jsonl"
- config_name: eo-eu
data_files: "data/eo-eu.jsonl"
- config_name: eo-fa
data_files: "data/eo-fa.jsonl"
- config_name: eo-fi
data_files: "data/eo-fi.jsonl"
- config_name: eo-fr
data_files: "data/eo-fr.jsonl"
- config_name: eo-gl
data_files: "data/eo-gl.jsonl"
- config_name: eo-he
data_files: "data/eo-he.jsonl"
- config_name: eo-hi
data_files: "data/eo-hi.jsonl"
- config_name: eo-hr
data_files: "data/eo-hr.jsonl"
- config_name: eo-hu
data_files: "data/eo-hu.jsonl"
- config_name: eo-hy
data_files: "data/eo-hy.jsonl"
- config_name: eo-id
data_files: "data/eo-id.jsonl"
- config_name: eo-is
data_files: "data/eo-is.jsonl"
- config_name: eo-it
data_files: "data/eo-it.jsonl"
- config_name: eo-ja
data_files: "data/eo-ja.jsonl"
- config_name: eo-kk
data_files: "data/eo-kk.jsonl"
- config_name: eo-ko
data_files: "data/eo-ko.jsonl"
- config_name: eo-lt
data_files: "data/eo-lt.jsonl"
- config_name: eo-lv
data_files: "data/eo-lv.jsonl"
- config_name: eo-mk
data_files: "data/eo-mk.jsonl"
- config_name: eo-ml
data_files: "data/eo-ml.jsonl"
- config_name: eo-ms
data_files: "data/eo-ms.jsonl"
- config_name: eo-nl
data_files: "data/eo-nl.jsonl"
- config_name: eo-no
data_files: "data/eo-no.jsonl"
- config_name: eo-pl
data_files: "data/eo-pl.jsonl"
- config_name: eo-pt
data_files: "data/eo-pt.jsonl"
- config_name: eo-ro
data_files: "data/eo-ro.jsonl"
- config_name: eo-ru
data_files: "data/eo-ru.jsonl"
- config_name: eo-si
data_files: "data/eo-si.jsonl"
- config_name: eo-sk
data_files: "data/eo-sk.jsonl"
- config_name: eo-sl
data_files: "data/eo-sl.jsonl"
- config_name: eo-sq
data_files: "data/eo-sq.jsonl"
- config_name: eo-sr
data_files: "data/eo-sr.jsonl"
- config_name: eo-sv
data_files: "data/eo-sv.jsonl"
- config_name: eo-th
data_files: "data/eo-th.jsonl"
- config_name: eo-tl
data_files: "data/eo-tl.jsonl"
- config_name: eo-tr
data_files: "data/eo-tr.jsonl"
- config_name: eo-uk
data_files: "data/eo-uk.jsonl"
- config_name: eo-vi
data_files: "data/eo-vi.jsonl"
- config_name: eo-pt_br
data_files: "data/eo-pt_br.jsonl"
- config_name: eo-ze_en
data_files: "data/eo-ze_en.jsonl"
- config_name: eo-ze_zh
data_files: "data/eo-ze_zh.jsonl"
- config_name: eo-zh_cn
data_files: "data/eo-zh_cn.jsonl"
- config_name: eo-zh_tw
data_files: "data/eo-zh_tw.jsonl"
- config_name: es-et
data_files: "data/es-et.jsonl"
- config_name: es-eu
data_files: "data/es-eu.jsonl"
- config_name: es-fa
data_files: "data/es-fa.jsonl"
- config_name: es-fi
data_files: "data/es-fi.jsonl"
- config_name: es-fr
data_files: "data/es-fr.jsonl"
- config_name: es-gl
data_files: "data/es-gl.jsonl"
- config_name: es-he
data_files: "data/es-he.jsonl"
- config_name: es-hi
data_files: "data/es-hi.jsonl"
- config_name: es-hr
data_files: "data/es-hr.jsonl"
- config_name: es-hu
data_files: "data/es-hu.jsonl"
- config_name: es-hy
data_files: "data/es-hy.jsonl"
- config_name: es-id
data_files: "data/es-id.jsonl"
- config_name: es-is
data_files: "data/es-is.jsonl"
- config_name: es-it
data_files: "data/es-it.jsonl"
- config_name: es-ja
data_files: "data/es-ja.jsonl"
- config_name: es-ka
data_files: "data/es-ka.jsonl"
- config_name: es-kk
data_files: "data/es-kk.jsonl"
- config_name: es-ko
data_files: "data/es-ko.jsonl"
- config_name: es-lt
data_files: "data/es-lt.jsonl"
- config_name: es-lv
data_files: "data/es-lv.jsonl"
- config_name: es-mk
data_files: "data/es-mk.jsonl"
- config_name: es-ml
data_files: "data/es-ml.jsonl"
- config_name: es-ms
data_files: "data/es-ms.jsonl"
- config_name: es-nl
data_files: "data/es-nl.jsonl"
- config_name: es-no
data_files: "data/es-no.jsonl"
- config_name: es-pl
data_files: "data/es-pl.jsonl"
- config_name: es-pt
data_files: "data/es-pt.jsonl"
- config_name: es-ro
data_files: "data/es-ro.jsonl"
- config_name: es-ru
data_files: "data/es-ru.jsonl"
- config_name: es-si
data_files: "data/es-si.jsonl"
- config_name: es-sk
data_files: "data/es-sk.jsonl"
- config_name: es-sl
data_files: "data/es-sl.jsonl"
- config_name: es-sq
data_files: "data/es-sq.jsonl"
- config_name: es-sr
data_files: "data/es-sr.jsonl"
- config_name: es-sv
data_files: "data/es-sv.jsonl"
- config_name: es-ta
data_files: "data/es-ta.jsonl"
- config_name: es-te
data_files: "data/es-te.jsonl"
- config_name: es-th
data_files: "data/es-th.jsonl"
- config_name: es-tl
data_files: "data/es-tl.jsonl"
- config_name: es-tr
data_files: "data/es-tr.jsonl"
- config_name: es-uk
data_files: "data/es-uk.jsonl"
- config_name: es-ur
data_files: "data/es-ur.jsonl"
- config_name: es-vi
data_files: "data/es-vi.jsonl"
- config_name: es-pt_br
data_files: "data/es-pt_br.jsonl"
- config_name: es-ze_en
data_files: "data/es-ze_en.jsonl"
- config_name: es-ze_zh
data_files: "data/es-ze_zh.jsonl"
- config_name: es-zh_cn
data_files: "data/es-zh_cn.jsonl"
- config_name: es-zh_tw
data_files: "data/es-zh_tw.jsonl"
- config_name: et-eu
data_files: "data/et-eu.jsonl"
- config_name: et-fa
data_files: "data/et-fa.jsonl"
- config_name: et-fi
data_files: "data/et-fi.jsonl"
- config_name: et-fr
data_files: "data/et-fr.jsonl"
- config_name: et-gl
data_files: "data/et-gl.jsonl"
- config_name: et-he
data_files: "data/et-he.jsonl"
- config_name: et-hi
data_files: "data/et-hi.jsonl"
- config_name: et-hr
data_files: "data/et-hr.jsonl"
- config_name: et-hu
data_files: "data/et-hu.jsonl"
- config_name: et-hy
data_files: "data/et-hy.jsonl"
- config_name: et-id
data_files: "data/et-id.jsonl"
- config_name: et-is
data_files: "data/et-is.jsonl"
- config_name: et-it
data_files: "data/et-it.jsonl"
- config_name: et-ja
data_files: "data/et-ja.jsonl"
- config_name: et-ka
data_files: "data/et-ka.jsonl"
- config_name: et-kk
data_files: "data/et-kk.jsonl"
- config_name: et-ko
data_files: "data/et-ko.jsonl"
- config_name: et-lt
data_files: "data/et-lt.jsonl"
- config_name: et-lv
data_files: "data/et-lv.jsonl"
- config_name: et-mk
data_files: "data/et-mk.jsonl"
- config_name: et-ml
data_files: "data/et-ml.jsonl"
- config_name: et-ms
data_files: "data/et-ms.jsonl"
- config_name: et-nl
data_files: "data/et-nl.jsonl"
- config_name: et-no
data_files: "data/et-no.jsonl"
- config_name: et-pl
data_files: "data/et-pl.jsonl"
- config_name: et-pt
data_files: "data/et-pt.jsonl"
- config_name: et-ro
data_files: "data/et-ro.jsonl"
- config_name: et-ru
data_files: "data/et-ru.jsonl"
- config_name: et-si
data_files: "data/et-si.jsonl"
- config_name: et-sk
data_files: "data/et-sk.jsonl"
- config_name: et-sl
data_files: "data/et-sl.jsonl"
- config_name: et-sq
data_files: "data/et-sq.jsonl"
- config_name: et-sr
data_files: "data/et-sr.jsonl"
- config_name: et-sv
data_files: "data/et-sv.jsonl"
- config_name: et-ta
data_files: "data/et-ta.jsonl"
- config_name: et-te
data_files: "data/et-te.jsonl"
- config_name: et-th
data_files: "data/et-th.jsonl"
- config_name: et-tl
data_files: "data/et-tl.jsonl"
- config_name: et-tr
data_files: "data/et-tr.jsonl"
- config_name: et-uk
data_files: "data/et-uk.jsonl"
- config_name: et-ur
data_files: "data/et-ur.jsonl"
- config_name: et-vi
data_files: "data/et-vi.jsonl"
- config_name: et-pt_br
data_files: "data/et-pt_br.jsonl"
- config_name: et-ze_en
data_files: "data/et-ze_en.jsonl"
- config_name: et-ze_zh
data_files: "data/et-ze_zh.jsonl"
- config_name: et-zh_cn
data_files: "data/et-zh_cn.jsonl"
- config_name: et-zh_tw
data_files: "data/et-zh_tw.jsonl"
- config_name: eu-fa
data_files: "data/eu-fa.jsonl"
- config_name: eu-fi
data_files: "data/eu-fi.jsonl"
- config_name: eu-fr
data_files: "data/eu-fr.jsonl"
- config_name: eu-gl
data_files: "data/eu-gl.jsonl"
- config_name: eu-he
data_files: "data/eu-he.jsonl"
- config_name: eu-hi
data_files: "data/eu-hi.jsonl"
- config_name: eu-hr
data_files: "data/eu-hr.jsonl"
- config_name: eu-hu
data_files: "data/eu-hu.jsonl"
- config_name: eu-id
data_files: "data/eu-id.jsonl"
- config_name: eu-is
data_files: "data/eu-is.jsonl"
- config_name: eu-it
data_files: "data/eu-it.jsonl"
- config_name: eu-ja
data_files: "data/eu-ja.jsonl"
- config_name: eu-ka
data_files: "data/eu-ka.jsonl"
- config_name: eu-ko
data_files: "data/eu-ko.jsonl"
- config_name: eu-lt
data_files: "data/eu-lt.jsonl"
- config_name: eu-lv
data_files: "data/eu-lv.jsonl"
- config_name: eu-mk
data_files: "data/eu-mk.jsonl"
- config_name: eu-ml
data_files: "data/eu-ml.jsonl"
- config_name: eu-ms
data_files: "data/eu-ms.jsonl"
- config_name: eu-nl
data_files: "data/eu-nl.jsonl"
- config_name: eu-no
data_files: "data/eu-no.jsonl"
- config_name: eu-pl
data_files: "data/eu-pl.jsonl"
- config_name: eu-pt
data_files: "data/eu-pt.jsonl"
- config_name: eu-ro
data_files: "data/eu-ro.jsonl"
- config_name: eu-ru
data_files: "data/eu-ru.jsonl"
- config_name: eu-si
data_files: "data/eu-si.jsonl"
- config_name: eu-sk
data_files: "data/eu-sk.jsonl"
- config_name: eu-sl
data_files: "data/eu-sl.jsonl"
- config_name: eu-sq
data_files: "data/eu-sq.jsonl"
- config_name: eu-sr
data_files: "data/eu-sr.jsonl"
- config_name: eu-sv
data_files: "data/eu-sv.jsonl"
- config_name: eu-ta
data_files: "data/eu-ta.jsonl"
- config_name: eu-te
data_files: "data/eu-te.jsonl"
- config_name: eu-th
data_files: "data/eu-th.jsonl"
- config_name: eu-tl
data_files: "data/eu-tl.jsonl"
- config_name: eu-tr
data_files: "data/eu-tr.jsonl"
- config_name: eu-uk
data_files: "data/eu-uk.jsonl"
- config_name: eu-ur
data_files: "data/eu-ur.jsonl"
- config_name: eu-vi
data_files: "data/eu-vi.jsonl"
- config_name: eu-pt_br
data_files: "data/eu-pt_br.jsonl"
- config_name: eu-ze_en
data_files: "data/eu-ze_en.jsonl"
- config_name: eu-ze_zh
data_files: "data/eu-ze_zh.jsonl"
- config_name: eu-zh_cn
data_files: "data/eu-zh_cn.jsonl"
- config_name: eu-zh_tw
data_files: "data/eu-zh_tw.jsonl"
- config_name: fa-fi
data_files: "data/fa-fi.jsonl"
- config_name: fa-fr
data_files: "data/fa-fr.jsonl"
- config_name: fa-gl
data_files: "data/fa-gl.jsonl"
- config_name: fa-he
data_files: "data/fa-he.jsonl"
- config_name: fa-hi
data_files: "data/fa-hi.jsonl"
- config_name: fa-hr
data_files: "data/fa-hr.jsonl"
- config_name: fa-hu
data_files: "data/fa-hu.jsonl"
- config_name: fa-id
data_files: "data/fa-id.jsonl"
- config_name: fa-is
data_files: "data/fa-is.jsonl"
- config_name: fa-it
data_files: "data/fa-it.jsonl"
- config_name: fa-ja
data_files: "data/fa-ja.jsonl"
- config_name: fa-ka
data_files: "data/fa-ka.jsonl"
- config_name: fa-kk
data_files: "data/fa-kk.jsonl"
- config_name: fa-ko
data_files: "data/fa-ko.jsonl"
- config_name: fa-lt
data_files: "data/fa-lt.jsonl"
- config_name: fa-lv
data_files: "data/fa-lv.jsonl"
- config_name: fa-mk
data_files: "data/fa-mk.jsonl"
- config_name: fa-ml
data_files: "data/fa-ml.jsonl"
- config_name: fa-ms
data_files: "data/fa-ms.jsonl"
- config_name: fa-nl
data_files: "data/fa-nl.jsonl"
- config_name: fa-no
data_files: "data/fa-no.jsonl"
- config_name: fa-pl
data_files: "data/fa-pl.jsonl"
- config_name: fa-pt
data_files: "data/fa-pt.jsonl"
- config_name: fa-ro
data_files: "data/fa-ro.jsonl"
- config_name: fa-ru
data_files: "data/fa-ru.jsonl"
- config_name: fa-si
data_files: "data/fa-si.jsonl"
- config_name: fa-sk
data_files: "data/fa-sk.jsonl"
- config_name: fa-sl
data_files: "data/fa-sl.jsonl"
- config_name: fa-sq
data_files: "data/fa-sq.jsonl"
- config_name: fa-sr
data_files: "data/fa-sr.jsonl"
- config_name: fa-sv
data_files: "data/fa-sv.jsonl"
- config_name: fa-ta
data_files: "data/fa-ta.jsonl"
- config_name: fa-te
data_files: "data/fa-te.jsonl"
- config_name: fa-th
data_files: "data/fa-th.jsonl"
- config_name: fa-tl
data_files: "data/fa-tl.jsonl"
- config_name: fa-tr
data_files: "data/fa-tr.jsonl"
- config_name: fa-uk
data_files: "data/fa-uk.jsonl"
- config_name: fa-ur
data_files: "data/fa-ur.jsonl"
- config_name: fa-vi
data_files: "data/fa-vi.jsonl"
- config_name: fa-pt_br
data_files: "data/fa-pt_br.jsonl"
- config_name: fa-ze_en
data_files: "data/fa-ze_en.jsonl"
- config_name: fa-ze_zh
data_files: "data/fa-ze_zh.jsonl"
- config_name: fa-zh_cn
data_files: "data/fa-zh_cn.jsonl"
- config_name: fa-zh_tw
data_files: "data/fa-zh_tw.jsonl"
- config_name: fi-fr
data_files: "data/fi-fr.jsonl"
- config_name: fi-gl
data_files: "data/fi-gl.jsonl"
- config_name: fi-he
data_files: "data/fi-he.jsonl"
- config_name: fi-hi
data_files: "data/fi-hi.jsonl"
- config_name: fi-hr
data_files: "data/fi-hr.jsonl"
- config_name: fi-hu
data_files: "data/fi-hu.jsonl"
- config_name: fi-hy
data_files: "data/fi-hy.jsonl"
- config_name: fi-id
data_files: "data/fi-id.jsonl"
- config_name: fi-is
data_files: "data/fi-is.jsonl"
- config_name: fi-it
data_files: "data/fi-it.jsonl"
- config_name: fi-ja
data_files: "data/fi-ja.jsonl"
- config_name: fi-ka
data_files: "data/fi-ka.jsonl"
- config_name: fi-kk
data_files: "data/fi-kk.jsonl"
- config_name: fi-ko
data_files: "data/fi-ko.jsonl"
- config_name: fi-lt
data_files: "data/fi-lt.jsonl"
- config_name: fi-lv
data_files: "data/fi-lv.jsonl"
- config_name: fi-mk
data_files: "data/fi-mk.jsonl"
- config_name: fi-ml
data_files: "data/fi-ml.jsonl"
- config_name: fi-ms
data_files: "data/fi-ms.jsonl"
- config_name: fi-nl
data_files: "data/fi-nl.jsonl"
- config_name: fi-no
data_files: "data/fi-no.jsonl"
- config_name: fi-pl
data_files: "data/fi-pl.jsonl"
- config_name: fi-pt
data_files: "data/fi-pt.jsonl"
- config_name: fi-ro
data_files: "data/fi-ro.jsonl"
- config_name: fi-ru
data_files: "data/fi-ru.jsonl"
- config_name: fi-si
data_files: "data/fi-si.jsonl"
- config_name: fi-sk
data_files: "data/fi-sk.jsonl"
- config_name: fi-sl
data_files: "data/fi-sl.jsonl"
- config_name: fi-sq
data_files: "data/fi-sq.jsonl"
- config_name: fi-sr
data_files: "data/fi-sr.jsonl"
- config_name: fi-sv
data_files: "data/fi-sv.jsonl"
- config_name: fi-ta
data_files: "data/fi-ta.jsonl"
- config_name: fi-te
data_files: "data/fi-te.jsonl"
- config_name: fi-th
data_files: "data/fi-th.jsonl"
- config_name: fi-tl
data_files: "data/fi-tl.jsonl"
- config_name: fi-tr
data_files: "data/fi-tr.jsonl"
- config_name: fi-uk
data_files: "data/fi-uk.jsonl"
- config_name: fi-ur
data_files: "data/fi-ur.jsonl"
- config_name: fi-vi
data_files: "data/fi-vi.jsonl"
- config_name: fi-pt_br
data_files: "data/fi-pt_br.jsonl"
- config_name: fi-ze_en
data_files: "data/fi-ze_en.jsonl"
- config_name: fi-ze_zh
data_files: "data/fi-ze_zh.jsonl"
- config_name: fi-zh_cn
data_files: "data/fi-zh_cn.jsonl"
- config_name: fi-zh_tw
data_files: "data/fi-zh_tw.jsonl"
- config_name: fr-gl
data_files: "data/fr-gl.jsonl"
- config_name: fr-he
data_files: "data/fr-he.jsonl"
- config_name: fr-hi
data_files: "data/fr-hi.jsonl"
- config_name: fr-hr
data_files: "data/fr-hr.jsonl"
- config_name: fr-hu
data_files: "data/fr-hu.jsonl"
- config_name: fr-hy
data_files: "data/fr-hy.jsonl"
- config_name: fr-id
data_files: "data/fr-id.jsonl"
- config_name: fr-is
data_files: "data/fr-is.jsonl"
- config_name: fr-it
data_files: "data/fr-it.jsonl"
- config_name: fr-ja
data_files: "data/fr-ja.jsonl"
- config_name: fr-ka
data_files: "data/fr-ka.jsonl"
- config_name: fr-kk
data_files: "data/fr-kk.jsonl"
- config_name: fr-ko
data_files: "data/fr-ko.jsonl"
- config_name: fr-lt
data_files: "data/fr-lt.jsonl"
- config_name: fr-lv
data_files: "data/fr-lv.jsonl"
- config_name: fr-mk
data_files: "data/fr-mk.jsonl"
- config_name: fr-ml
data_files: "data/fr-ml.jsonl"
- config_name: fr-ms
data_files: "data/fr-ms.jsonl"
- config_name: fr-nl
data_files: "data/fr-nl.jsonl"
- config_name: fr-no
data_files: "data/fr-no.jsonl"
- config_name: fr-pl
data_files: "data/fr-pl.jsonl"
- config_name: fr-pt
data_files: "data/fr-pt.jsonl"
- config_name: fr-ro
data_files: "data/fr-ro.jsonl"
- config_name: fr-ru
data_files: "data/fr-ru.jsonl"
- config_name: fr-si
data_files: "data/fr-si.jsonl"
- config_name: fr-sk
data_files: "data/fr-sk.jsonl"
- config_name: fr-sl
data_files: "data/fr-sl.jsonl"
- config_name: fr-sq
data_files: "data/fr-sq.jsonl"
- config_name: fr-sr
data_files: "data/fr-sr.jsonl"
- config_name: fr-sv
data_files: "data/fr-sv.jsonl"
- config_name: fr-ta
data_files: "data/fr-ta.jsonl"
- config_name: fr-te
data_files: "data/fr-te.jsonl"
- config_name: fr-th
data_files: "data/fr-th.jsonl"
- config_name: fr-tl
data_files: "data/fr-tl.jsonl"
- config_name: fr-tr
data_files: "data/fr-tr.jsonl"
- config_name: fr-uk
data_files: "data/fr-uk.jsonl"
- config_name: fr-ur
data_files: "data/fr-ur.jsonl"
- config_name: fr-vi
data_files: "data/fr-vi.jsonl"
- config_name: fr-pt_br
data_files: "data/fr-pt_br.jsonl"
- config_name: fr-ze_en
data_files: "data/fr-ze_en.jsonl"
- config_name: fr-ze_zh
data_files: "data/fr-ze_zh.jsonl"
- config_name: fr-zh_cn
data_files: "data/fr-zh_cn.jsonl"
- config_name: fr-zh_tw
data_files: "data/fr-zh_tw.jsonl"
- config_name: gl-he
data_files: "data/gl-he.jsonl"
- config_name: gl-hi
data_files: "data/gl-hi.jsonl"
- config_name: gl-hr
data_files: "data/gl-hr.jsonl"
- config_name: gl-hu
data_files: "data/gl-hu.jsonl"
- config_name: gl-id
data_files: "data/gl-id.jsonl"
- config_name: gl-is
data_files: "data/gl-is.jsonl"
- config_name: gl-it
data_files: "data/gl-it.jsonl"
- config_name: gl-ja
data_files: "data/gl-ja.jsonl"
- config_name: gl-ka
data_files: "data/gl-ka.jsonl"
- config_name: gl-ko
data_files: "data/gl-ko.jsonl"
- config_name: gl-lt
data_files: "data/gl-lt.jsonl"
- config_name: gl-lv
data_files: "data/gl-lv.jsonl"
- config_name: gl-mk
data_files: "data/gl-mk.jsonl"
- config_name: gl-ml
data_files: "data/gl-ml.jsonl"
- config_name: gl-ms
data_files: "data/gl-ms.jsonl"
- config_name: gl-nl
data_files: "data/gl-nl.jsonl"
- config_name: gl-no
data_files: "data/gl-no.jsonl"
- config_name: gl-pl
data_files: "data/gl-pl.jsonl"
- config_name: gl-pt
data_files: "data/gl-pt.jsonl"
- config_name: gl-ro
data_files: "data/gl-ro.jsonl"
- config_name: gl-ru
data_files: "data/gl-ru.jsonl"
- config_name: gl-si
data_files: "data/gl-si.jsonl"
- config_name: gl-sk
data_files: "data/gl-sk.jsonl"
- config_name: gl-sl
data_files: "data/gl-sl.jsonl"
- config_name: gl-sq
data_files: "data/gl-sq.jsonl"
- config_name: gl-sr
data_files: "data/gl-sr.jsonl"
- config_name: gl-sv
data_files: "data/gl-sv.jsonl"
- config_name: gl-th
data_files: "data/gl-th.jsonl"
- config_name: gl-tr
data_files: "data/gl-tr.jsonl"
- config_name: gl-uk
data_files: "data/gl-uk.jsonl"
- config_name: gl-ur
data_files: "data/gl-ur.jsonl"
- config_name: gl-vi
data_files: "data/gl-vi.jsonl"
- config_name: gl-pt_br
data_files: "data/gl-pt_br.jsonl"
- config_name: gl-ze_en
data_files: "data/gl-ze_en.jsonl"
- config_name: gl-ze_zh
data_files: "data/gl-ze_zh.jsonl"
- config_name: gl-zh_cn
data_files: "data/gl-zh_cn.jsonl"
- config_name: gl-zh_tw
data_files: "data/gl-zh_tw.jsonl"
- config_name: he-hi
data_files: "data/he-hi.jsonl"
- config_name: he-hr
data_files: "data/he-hr.jsonl"
- config_name: he-hu
data_files: "data/he-hu.jsonl"
- config_name: he-hy
data_files: "data/he-hy.jsonl"
- config_name: he-id
data_files: "data/he-id.jsonl"
- config_name: he-is
data_files: "data/he-is.jsonl"
- config_name: he-it
data_files: "data/he-it.jsonl"
- config_name: he-ja
data_files: "data/he-ja.jsonl"
- config_name: he-ka
data_files: "data/he-ka.jsonl"
- config_name: he-kk
data_files: "data/he-kk.jsonl"
- config_name: he-ko
data_files: "data/he-ko.jsonl"
- config_name: he-lt
data_files: "data/he-lt.jsonl"
- config_name: he-lv
data_files: "data/he-lv.jsonl"
- config_name: he-mk
data_files: "data/he-mk.jsonl"
- config_name: he-ml
data_files: "data/he-ml.jsonl"
- config_name: he-ms
data_files: "data/he-ms.jsonl"
- config_name: he-nl
data_files: "data/he-nl.jsonl"
- config_name: he-no
data_files: "data/he-no.jsonl"
- config_name: he-pl
data_files: "data/he-pl.jsonl"
- config_name: he-pt
data_files: "data/he-pt.jsonl"
- config_name: he-ro
data_files: "data/he-ro.jsonl"
- config_name: he-ru
data_files: "data/he-ru.jsonl"
- config_name: he-si
data_files: "data/he-si.jsonl"
- config_name: he-sk
data_files: "data/he-sk.jsonl"
- config_name: he-sl
data_files: "data/he-sl.jsonl"
- config_name: he-sq
data_files: "data/he-sq.jsonl"
- config_name: he-sr
data_files: "data/he-sr.jsonl"
- config_name: he-sv
data_files: "data/he-sv.jsonl"
- config_name: he-ta
data_files: "data/he-ta.jsonl"
- config_name: he-te
data_files: "data/he-te.jsonl"
- config_name: he-th
data_files: "data/he-th.jsonl"
- config_name: he-tl
data_files: "data/he-tl.jsonl"
- config_name: he-tr
data_files: "data/he-tr.jsonl"
- config_name: he-uk
data_files: "data/he-uk.jsonl"
- config_name: he-ur
data_files: "data/he-ur.jsonl"
- config_name: he-vi
data_files: "data/he-vi.jsonl"
- config_name: he-pt_br
data_files: "data/he-pt_br.jsonl"
- config_name: he-ze_en
data_files: "data/he-ze_en.jsonl"
- config_name: he-ze_zh
data_files: "data/he-ze_zh.jsonl"
- config_name: he-zh_cn
data_files: "data/he-zh_cn.jsonl"
- config_name: he-zh_tw
data_files: "data/he-zh_tw.jsonl"
- config_name: hi-hr
data_files: "data/hi-hr.jsonl"
- config_name: hi-hu
data_files: "data/hi-hu.jsonl"
- config_name: hi-id
data_files: "data/hi-id.jsonl"
- config_name: hi-is
data_files: "data/hi-is.jsonl"
- config_name: hi-it
data_files: "data/hi-it.jsonl"
- config_name: hi-ja
data_files: "data/hi-ja.jsonl"
- config_name: hi-ka
data_files: "data/hi-ka.jsonl"
- config_name: hi-ko
data_files: "data/hi-ko.jsonl"
- config_name: hi-lt
data_files: "data/hi-lt.jsonl"
- config_name: hi-lv
data_files: "data/hi-lv.jsonl"
- config_name: hi-mk
data_files: "data/hi-mk.jsonl"
- config_name: hi-ml
data_files: "data/hi-ml.jsonl"
- config_name: hi-ms
data_files: "data/hi-ms.jsonl"
- config_name: hi-nl
data_files: "data/hi-nl.jsonl"
- config_name: hi-no
data_files: "data/hi-no.jsonl"
- config_name: hi-pl
data_files: "data/hi-pl.jsonl"
- config_name: hi-pt
data_files: "data/hi-pt.jsonl"
- config_name: hi-ro
data_files: "data/hi-ro.jsonl"
- config_name: hi-ru
data_files: "data/hi-ru.jsonl"
- config_name: hi-si
data_files: "data/hi-si.jsonl"
- config_name: hi-sk
data_files: "data/hi-sk.jsonl"
- config_name: hi-sl
data_files: "data/hi-sl.jsonl"
- config_name: hi-sq
data_files: "data/hi-sq.jsonl"
- config_name: hi-sr
data_files: "data/hi-sr.jsonl"
- config_name: hi-sv
data_files: "data/hi-sv.jsonl"
- config_name: hi-ta
data_files: "data/hi-ta.jsonl"
- config_name: hi-te
data_files: "data/hi-te.jsonl"
- config_name: hi-th
data_files: "data/hi-th.jsonl"
- config_name: hi-tl
data_files: "data/hi-tl.jsonl"
- config_name: hi-tr
data_files: "data/hi-tr.jsonl"
- config_name: hi-uk
data_files: "data/hi-uk.jsonl"
- config_name: hi-ur
data_files: "data/hi-ur.jsonl"
- config_name: hi-vi
data_files: "data/hi-vi.jsonl"
- config_name: hi-pt_br
data_files: "data/hi-pt_br.jsonl"
- config_name: hi-ze_en
data_files: "data/hi-ze_en.jsonl"
- config_name: hi-ze_zh
data_files: "data/hi-ze_zh.jsonl"
- config_name: hi-zh_cn
data_files: "data/hi-zh_cn.jsonl"
- config_name: hi-zh_tw
data_files: "data/hi-zh_tw.jsonl"
- config_name: hr-hu
data_files: "data/hr-hu.jsonl"
- config_name: hr-hy
data_files: "data/hr-hy.jsonl"
- config_name: hr-id
data_files: "data/hr-id.jsonl"
- config_name: hr-is
data_files: "data/hr-is.jsonl"
- config_name: hr-it
data_files: "data/hr-it.jsonl"
- config_name: hr-ja
data_files: "data/hr-ja.jsonl"
- config_name: hr-ka
data_files: "data/hr-ka.jsonl"
- config_name: hr-kk
data_files: "data/hr-kk.jsonl"
- config_name: hr-ko
data_files: "data/hr-ko.jsonl"
- config_name: hr-lt
data_files: "data/hr-lt.jsonl"
- config_name: hr-lv
data_files: "data/hr-lv.jsonl"
- config_name: hr-mk
data_files: "data/hr-mk.jsonl"
- config_name: hr-ml
data_files: "data/hr-ml.jsonl"
- config_name: hr-ms
data_files: "data/hr-ms.jsonl"
- config_name: hr-nl
data_files: "data/hr-nl.jsonl"
- config_name: hr-no
data_files: "data/hr-no.jsonl"
- config_name: hr-pl
data_files: "data/hr-pl.jsonl"
- config_name: hr-pt
data_files: "data/hr-pt.jsonl"
- config_name: hr-ro
data_files: "data/hr-ro.jsonl"
- config_name: hr-ru
data_files: "data/hr-ru.jsonl"
- config_name: hr-si
data_files: "data/hr-si.jsonl"
- config_name: hr-sk
data_files: "data/hr-sk.jsonl"
- config_name: hr-sl
data_files: "data/hr-sl.jsonl"
- config_name: hr-sq
data_files: "data/hr-sq.jsonl"
- config_name: hr-sr
data_files: "data/hr-sr.jsonl"
- config_name: hr-sv
data_files: "data/hr-sv.jsonl"
- config_name: hr-ta
data_files: "data/hr-ta.jsonl"
- config_name: hr-te
data_files: "data/hr-te.jsonl"
- config_name: hr-th
data_files: "data/hr-th.jsonl"
- config_name: hr-tl
data_files: "data/hr-tl.jsonl"
- config_name: hr-tr
data_files: "data/hr-tr.jsonl"
- config_name: hr-uk
data_files: "data/hr-uk.jsonl"
- config_name: hr-ur
data_files: "data/hr-ur.jsonl"
- config_name: hr-vi
data_files: "data/hr-vi.jsonl"
- config_name: hr-pt_br
data_files: "data/hr-pt_br.jsonl"
- config_name: hr-ze_en
data_files: "data/hr-ze_en.jsonl"
- config_name: hr-ze_zh
data_files: "data/hr-ze_zh.jsonl"
- config_name: hr-zh_cn
data_files: "data/hr-zh_cn.jsonl"
- config_name: hr-zh_tw
data_files: "data/hr-zh_tw.jsonl"
- config_name: hu-hy
data_files: "data/hu-hy.jsonl"
- config_name: hu-id
data_files: "data/hu-id.jsonl"
- config_name: hu-is
data_files: "data/hu-is.jsonl"
- config_name: hu-it
data_files: "data/hu-it.jsonl"
- config_name: hu-ja
data_files: "data/hu-ja.jsonl"
- config_name: hu-ka
data_files: "data/hu-ka.jsonl"
- config_name: hu-kk
data_files: "data/hu-kk.jsonl"
- config_name: hu-ko
data_files: "data/hu-ko.jsonl"
- config_name: hu-lt
data_files: "data/hu-lt.jsonl"
- config_name: hu-lv
data_files: "data/hu-lv.jsonl"
- config_name: hu-mk
data_files: "data/hu-mk.jsonl"
- config_name: hu-ml
data_files: "data/hu-ml.jsonl"
- config_name: hu-ms
data_files: "data/hu-ms.jsonl"
- config_name: hu-nl
data_files: "data/hu-nl.jsonl"
- config_name: hu-no
data_files: "data/hu-no.jsonl"
- config_name: hu-pl
data_files: "data/hu-pl.jsonl"
- config_name: hu-pt
data_files: "data/hu-pt.jsonl"
- config_name: hu-ro
data_files: "data/hu-ro.jsonl"
- config_name: hu-ru
data_files: "data/hu-ru.jsonl"
- config_name: hu-si
data_files: "data/hu-si.jsonl"
- config_name: hu-sk
data_files: "data/hu-sk.jsonl"
- config_name: hu-sl
data_files: "data/hu-sl.jsonl"
- config_name: hu-sq
data_files: "data/hu-sq.jsonl"
- config_name: hu-sr
data_files: "data/hu-sr.jsonl"
- config_name: hu-sv
data_files: "data/hu-sv.jsonl"
- config_name: hu-ta
data_files: "data/hu-ta.jsonl"
- config_name: hu-te
data_files: "data/hu-te.jsonl"
- config_name: hu-th
data_files: "data/hu-th.jsonl"
- config_name: hu-tl
data_files: "data/hu-tl.jsonl"
- config_name: hu-tr
data_files: "data/hu-tr.jsonl"
- config_name: hu-uk
data_files: "data/hu-uk.jsonl"
- config_name: hu-ur
data_files: "data/hu-ur.jsonl"
- config_name: hu-vi
data_files: "data/hu-vi.jsonl"
- config_name: hu-pt_br
data_files: "data/hu-pt_br.jsonl"
- config_name: hu-ze_en
data_files: "data/hu-ze_en.jsonl"
- config_name: hu-ze_zh
data_files: "data/hu-ze_zh.jsonl"
- config_name: hu-zh_cn
data_files: "data/hu-zh_cn.jsonl"
- config_name: hu-zh_tw
data_files: "data/hu-zh_tw.jsonl"
- config_name: hy-id
data_files: "data/hy-id.jsonl"
- config_name: hy-it
data_files: "data/hy-it.jsonl"
- config_name: hy-mk
data_files: "data/hy-mk.jsonl"
- config_name: hy-ml
data_files: "data/hy-ml.jsonl"
- config_name: hy-nl
data_files: "data/hy-nl.jsonl"
- config_name: hy-pl
data_files: "data/hy-pl.jsonl"
- config_name: hy-pt
data_files: "data/hy-pt.jsonl"
- config_name: hy-ro
data_files: "data/hy-ro.jsonl"
- config_name: hy-ru
data_files: "data/hy-ru.jsonl"
- config_name: hy-sk
data_files: "data/hy-sk.jsonl"
- config_name: hy-sl
data_files: "data/hy-sl.jsonl"
- config_name: hy-sq
data_files: "data/hy-sq.jsonl"
- config_name: hy-sr
data_files: "data/hy-sr.jsonl"
- config_name: hy-sv
data_files: "data/hy-sv.jsonl"
- config_name: hy-tr
data_files: "data/hy-tr.jsonl"
- config_name: hy-pt_br
data_files: "data/hy-pt_br.jsonl"
- config_name: hy-zh_cn
data_files: "data/hy-zh_cn.jsonl"
- config_name: hy-zh_tw
data_files: "data/hy-zh_tw.jsonl"
- config_name: id-is
data_files: "data/id-is.jsonl"
- config_name: id-it
data_files: "data/id-it.jsonl"
- config_name: id-ja
data_files: "data/id-ja.jsonl"
- config_name: id-ka
data_files: "data/id-ka.jsonl"
- config_name: id-kk
data_files: "data/id-kk.jsonl"
- config_name: id-ko
data_files: "data/id-ko.jsonl"
- config_name: id-lt
data_files: "data/id-lt.jsonl"
- config_name: id-lv
data_files: "data/id-lv.jsonl"
- config_name: id-mk
data_files: "data/id-mk.jsonl"
- config_name: id-ml
data_files: "data/id-ml.jsonl"
- config_name: id-ms
data_files: "data/id-ms.jsonl"
- config_name: id-nl
data_files: "data/id-nl.jsonl"
- config_name: id-pl
data_files: "data/id-pl.jsonl"
- config_name: id-pt
data_files: "data/id-pt.jsonl"
- config_name: id-ro
data_files: "data/id-ro.jsonl"
- config_name: id-ru
data_files: "data/id-ru.jsonl"
- config_name: id-si
data_files: "data/id-si.jsonl"
- config_name: id-sk
data_files: "data/id-sk.jsonl"
- config_name: id-sl
data_files: "data/id-sl.jsonl"
- config_name: id-sq
data_files: "data/id-sq.jsonl"
- config_name: id-sr
data_files: "data/id-sr.jsonl"
- config_name: id-sv
data_files: "data/id-sv.jsonl"
- config_name: id-ta
data_files: "data/id-ta.jsonl"
- config_name: id-te
data_files: "data/id-te.jsonl"
- config_name: id-th
data_files: "data/id-th.jsonl"
- config_name: id-tl
data_files: "data/id-tl.jsonl"
- config_name: id-tr
data_files: "data/id-tr.jsonl"
- config_name: id-uk
data_files: "data/id-uk.jsonl"
- config_name: id-ur
data_files: "data/id-ur.jsonl"
- config_name: id-vi
data_files: "data/id-vi.jsonl"
- config_name: id-pt_br
data_files: "data/id-pt_br.jsonl"
- config_name: id-ze_en
data_files: "data/id-ze_en.jsonl"
- config_name: id-ze_zh
data_files: "data/id-ze_zh.jsonl"
- config_name: id-zh_cn
data_files: "data/id-zh_cn.jsonl"
- config_name: id-zh_tw
data_files: "data/id-zh_tw.jsonl"
- config_name: is-it
data_files: "data/is-it.jsonl"
- config_name: is-ja
data_files: "data/is-ja.jsonl"
- config_name: is-ka
data_files: "data/is-ka.jsonl"
- config_name: is-kk
data_files: "data/is-kk.jsonl"
- config_name: is-ko
data_files: "data/is-ko.jsonl"
- config_name: is-lt
data_files: "data/is-lt.jsonl"
- config_name: is-lv
data_files: "data/is-lv.jsonl"
- config_name: is-mk
data_files: "data/is-mk.jsonl"
- config_name: is-ml
data_files: "data/is-ml.jsonl"
- config_name: is-ms
data_files: "data/is-ms.jsonl"
- config_name: is-nl
data_files: "data/is-nl.jsonl"
- config_name: is-no
data_files: "data/is-no.jsonl"
- config_name: is-pl
data_files: "data/is-pl.jsonl"
- config_name: is-pt
data_files: "data/is-pt.jsonl"
- config_name: is-ro
data_files: "data/is-ro.jsonl"
- config_name: is-ru
data_files: "data/is-ru.jsonl"
- config_name: is-si
data_files: "data/is-si.jsonl"
- config_name: is-sk
data_files: "data/is-sk.jsonl"
- config_name: is-sl
data_files: "data/is-sl.jsonl"
- config_name: is-sq
data_files: "data/is-sq.jsonl"
- config_name: is-sr
data_files: "data/is-sr.jsonl"
- config_name: is-sv
data_files: "data/is-sv.jsonl"
- config_name: is-ta
data_files: "data/is-ta.jsonl"
- config_name: is-th
data_files: "data/is-th.jsonl"
- config_name: is-tl
data_files: "data/is-tl.jsonl"
- config_name: is-tr
data_files: "data/is-tr.jsonl"
- config_name: is-uk
data_files: "data/is-uk.jsonl"
- config_name: is-ur
data_files: "data/is-ur.jsonl"
- config_name: is-vi
data_files: "data/is-vi.jsonl"
- config_name: is-pt_br
data_files: "data/is-pt_br.jsonl"
- config_name: is-ze_en
data_files: "data/is-ze_en.jsonl"
- config_name: is-ze_zh
data_files: "data/is-ze_zh.jsonl"
- config_name: is-zh_cn
data_files: "data/is-zh_cn.jsonl"
- config_name: is-zh_tw
data_files: "data/is-zh_tw.jsonl"
- config_name: it-ja
data_files: "data/it-ja.jsonl"
- config_name: it-ka
data_files: "data/it-ka.jsonl"
- config_name: it-kk
data_files: "data/it-kk.jsonl"
- config_name: it-ko
data_files: "data/it-ko.jsonl"
- config_name: it-lt
data_files: "data/it-lt.jsonl"
- config_name: it-lv
data_files: "data/it-lv.jsonl"
- config_name: it-mk
data_files: "data/it-mk.jsonl"
- config_name: it-ml
data_files: "data/it-ml.jsonl"
- config_name: it-ms
data_files: "data/it-ms.jsonl"
- config_name: it-nl
data_files: "data/it-nl.jsonl"
- config_name: it-no
data_files: "data/it-no.jsonl"
- config_name: it-pl
data_files: "data/it-pl.jsonl"
- config_name: it-pt
data_files: "data/it-pt.jsonl"
- config_name: it-ro
data_files: "data/it-ro.jsonl"
- config_name: it-ru
data_files: "data/it-ru.jsonl"
- config_name: it-si
data_files: "data/it-si.jsonl"
- config_name: it-sk
data_files: "data/it-sk.jsonl"
- config_name: it-sl
data_files: "data/it-sl.jsonl"
- config_name: it-sq
data_files: "data/it-sq.jsonl"
- config_name: it-sr
data_files: "data/it-sr.jsonl"
- config_name: it-sv
data_files: "data/it-sv.jsonl"
- config_name: it-ta
data_files: "data/it-ta.jsonl"
- config_name: it-te
data_files: "data/it-te.jsonl"
- config_name: it-th
data_files: "data/it-th.jsonl"
- config_name: it-tl
data_files: "data/it-tl.jsonl"
- config_name: it-tr
data_files: "data/it-tr.jsonl"
- config_name: it-uk
data_files: "data/it-uk.jsonl"
- config_name: it-ur
data_files: "data/it-ur.jsonl"
- config_name: it-vi
data_files: "data/it-vi.jsonl"
- config_name: it-pt_br
data_files: "data/it-pt_br.jsonl"
- config_name: it-ze_en
data_files: "data/it-ze_en.jsonl"
- config_name: it-ze_zh
data_files: "data/it-ze_zh.jsonl"
- config_name: it-zh_cn
data_files: "data/it-zh_cn.jsonl"
- config_name: it-zh_tw
data_files: "data/it-zh_tw.jsonl"
- config_name: ja-ka
data_files: "data/ja-ka.jsonl"
- config_name: ja-kk
data_files: "data/ja-kk.jsonl"
- config_name: ja-ko
data_files: "data/ja-ko.jsonl"
- config_name: ja-lt
data_files: "data/ja-lt.jsonl"
- config_name: ja-lv
data_files: "data/ja-lv.jsonl"
- config_name: ja-mk
data_files: "data/ja-mk.jsonl"
- config_name: ja-ml
data_files: "data/ja-ml.jsonl"
- config_name: ja-ms
data_files: "data/ja-ms.jsonl"
- config_name: ja-nl
data_files: "data/ja-nl.jsonl"
- config_name: ja-no
data_files: "data/ja-no.jsonl"
- config_name: ja-pl
data_files: "data/ja-pl.jsonl"
- config_name: ja-pt
data_files: "data/ja-pt.jsonl"
- config_name: ja-ro
data_files: "data/ja-ro.jsonl"
- config_name: ja-ru
data_files: "data/ja-ru.jsonl"
- config_name: ja-si
data_files: "data/ja-si.jsonl"
- config_name: ja-sk
data_files: "data/ja-sk.jsonl"
- config_name: ja-sl
data_files: "data/ja-sl.jsonl"
- config_name: ja-sq
data_files: "data/ja-sq.jsonl"
- config_name: ja-sr
data_files: "data/ja-sr.jsonl"
- config_name: ja-sv
data_files: "data/ja-sv.jsonl"
- config_name: ja-ta
data_files: "data/ja-ta.jsonl"
- config_name: ja-te
data_files: "data/ja-te.jsonl"
- config_name: ja-th
data_files: "data/ja-th.jsonl"
- config_name: ja-tl
data_files: "data/ja-tl.jsonl"
- config_name: ja-tr
data_files: "data/ja-tr.jsonl"
- config_name: ja-uk
data_files: "data/ja-uk.jsonl"
- config_name: ja-ur
data_files: "data/ja-ur.jsonl"
- config_name: ja-vi
data_files: "data/ja-vi.jsonl"
- config_name: ja-pt_br
data_files: "data/ja-pt_br.jsonl"
- config_name: ja-ze_en
data_files: "data/ja-ze_en.jsonl"
- config_name: ja-ze_zh
data_files: "data/ja-ze_zh.jsonl"
- config_name: ja-zh_cn
data_files: "data/ja-zh_cn.jsonl"
- config_name: ja-zh_tw
data_files: "data/ja-zh_tw.jsonl"
- config_name: ka-ko
data_files: "data/ka-ko.jsonl"
- config_name: ka-lt
data_files: "data/ka-lt.jsonl"
- config_name: ka-lv
data_files: "data/ka-lv.jsonl"
- config_name: ka-mk
data_files: "data/ka-mk.jsonl"
- config_name: ka-ml
data_files: "data/ka-ml.jsonl"
- config_name: ka-ms
data_files: "data/ka-ms.jsonl"
- config_name: ka-nl
data_files: "data/ka-nl.jsonl"
- config_name: ka-no
data_files: "data/ka-no.jsonl"
- config_name: ka-pl
data_files: "data/ka-pl.jsonl"
- config_name: ka-pt
data_files: "data/ka-pt.jsonl"
- config_name: ka-ro
data_files: "data/ka-ro.jsonl"
- config_name: ka-ru
data_files: "data/ka-ru.jsonl"
- config_name: ka-si
data_files: "data/ka-si.jsonl"
- config_name: ka-sk
data_files: "data/ka-sk.jsonl"
- config_name: ka-sl
data_files: "data/ka-sl.jsonl"
- config_name: ka-sq
data_files: "data/ka-sq.jsonl"
- config_name: ka-sr
data_files: "data/ka-sr.jsonl"
- config_name: ka-sv
data_files: "data/ka-sv.jsonl"
- config_name: ka-th
data_files: "data/ka-th.jsonl"
- config_name: ka-tl
data_files: "data/ka-tl.jsonl"
- config_name: ka-tr
data_files: "data/ka-tr.jsonl"
- config_name: ka-uk
data_files: "data/ka-uk.jsonl"
- config_name: ka-ur
data_files: "data/ka-ur.jsonl"
- config_name: ka-vi
data_files: "data/ka-vi.jsonl"
- config_name: ka-pt_br
data_files: "data/ka-pt_br.jsonl"
- config_name: ka-ze_en
data_files: "data/ka-ze_en.jsonl"
- config_name: ka-ze_zh
data_files: "data/ka-ze_zh.jsonl"
- config_name: ka-zh_cn
data_files: "data/ka-zh_cn.jsonl"
- config_name: ka-zh_tw
data_files: "data/ka-zh_tw.jsonl"
- config_name: kk-lt
data_files: "data/kk-lt.jsonl"
- config_name: kk-lv
data_files: "data/kk-lv.jsonl"
- config_name: kk-ms
data_files: "data/kk-ms.jsonl"
- config_name: kk-nl
data_files: "data/kk-nl.jsonl"
- config_name: kk-no
data_files: "data/kk-no.jsonl"
- config_name: kk-pl
data_files: "data/kk-pl.jsonl"
- config_name: kk-pt
data_files: "data/kk-pt.jsonl"
- config_name: kk-ro
data_files: "data/kk-ro.jsonl"
- config_name: kk-ru
data_files: "data/kk-ru.jsonl"
- config_name: kk-sk
data_files: "data/kk-sk.jsonl"
- config_name: kk-sl
data_files: "data/kk-sl.jsonl"
- config_name: kk-sr
data_files: "data/kk-sr.jsonl"
- config_name: kk-sv
data_files: "data/kk-sv.jsonl"
- config_name: kk-th
data_files: "data/kk-th.jsonl"
- config_name: kk-tr
data_files: "data/kk-tr.jsonl"
- config_name: kk-uk
data_files: "data/kk-uk.jsonl"
- config_name: kk-vi
data_files: "data/kk-vi.jsonl"
- config_name: kk-pt_br
data_files: "data/kk-pt_br.jsonl"
- config_name: kk-zh_cn
data_files: "data/kk-zh_cn.jsonl"
- config_name: ko-lt
data_files: "data/ko-lt.jsonl"
- config_name: ko-lv
data_files: "data/ko-lv.jsonl"
- config_name: ko-mk
data_files: "data/ko-mk.jsonl"
- config_name: ko-ml
data_files: "data/ko-ml.jsonl"
- config_name: ko-ms
data_files: "data/ko-ms.jsonl"
- config_name: ko-nl
data_files: "data/ko-nl.jsonl"
- config_name: ko-no
data_files: "data/ko-no.jsonl"
- config_name: ko-pl
data_files: "data/ko-pl.jsonl"
- config_name: ko-pt
data_files: "data/ko-pt.jsonl"
- config_name: ko-ro
data_files: "data/ko-ro.jsonl"
- config_name: ko-ru
data_files: "data/ko-ru.jsonl"
- config_name: ko-si
data_files: "data/ko-si.jsonl"
- config_name: ko-sk
data_files: "data/ko-sk.jsonl"
- config_name: ko-sl
data_files: "data/ko-sl.jsonl"
- config_name: ko-sq
data_files: "data/ko-sq.jsonl"
- config_name: ko-sr
data_files: "data/ko-sr.jsonl"
- config_name: ko-sv
data_files: "data/ko-sv.jsonl"
- config_name: ko-ta
data_files: "data/ko-ta.jsonl"
- config_name: ko-te
data_files: "data/ko-te.jsonl"
- config_name: ko-th
data_files: "data/ko-th.jsonl"
- config_name: ko-tl
data_files: "data/ko-tl.jsonl"
- config_name: ko-tr
data_files: "data/ko-tr.jsonl"
- config_name: ko-uk
data_files: "data/ko-uk.jsonl"
- config_name: ko-ur
data_files: "data/ko-ur.jsonl"
- config_name: ko-vi
data_files: "data/ko-vi.jsonl"
- config_name: ko-pt_br
data_files: "data/ko-pt_br.jsonl"
- config_name: ko-ze_en
data_files: "data/ko-ze_en.jsonl"
- config_name: ko-ze_zh
data_files: "data/ko-ze_zh.jsonl"
- config_name: ko-zh_cn
data_files: "data/ko-zh_cn.jsonl"
- config_name: ko-zh_tw
data_files: "data/ko-zh_tw.jsonl"
- config_name: lt-lv
data_files: "data/lt-lv.jsonl"
- config_name: lt-mk
data_files: "data/lt-mk.jsonl"
- config_name: lt-ml
data_files: "data/lt-ml.jsonl"
- config_name: lt-ms
data_files: "data/lt-ms.jsonl"
- config_name: lt-nl
data_files: "data/lt-nl.jsonl"
- config_name: lt-no
data_files: "data/lt-no.jsonl"
- config_name: lt-pl
data_files: "data/lt-pl.jsonl"
- config_name: lt-pt
data_files: "data/lt-pt.jsonl"
- config_name: lt-ro
data_files: "data/lt-ro.jsonl"
- config_name: lt-ru
data_files: "data/lt-ru.jsonl"
- config_name: lt-si
data_files: "data/lt-si.jsonl"
- config_name: lt-sk
data_files: "data/lt-sk.jsonl"
- config_name: lt-sl
data_files: "data/lt-sl.jsonl"
- config_name: lt-sq
data_files: "data/lt-sq.jsonl"
- config_name: lt-sr
data_files: "data/lt-sr.jsonl"
- config_name: lt-sv
data_files: "data/lt-sv.jsonl"
- config_name: lt-ta
data_files: "data/lt-ta.jsonl"
- config_name: lt-te
data_files: "data/lt-te.jsonl"
- config_name: lt-th
data_files: "data/lt-th.jsonl"
- config_name: lt-tl
data_files: "data/lt-tl.jsonl"
- config_name: lt-tr
data_files: "data/lt-tr.jsonl"
- config_name: lt-uk
data_files: "data/lt-uk.jsonl"
- config_name: lt-ur
data_files: "data/lt-ur.jsonl"
- config_name: lt-vi
data_files: "data/lt-vi.jsonl"
- config_name: lt-pt_br
data_files: "data/lt-pt_br.jsonl"
- config_name: lt-ze_en
data_files: "data/lt-ze_en.jsonl"
- config_name: lt-ze_zh
data_files: "data/lt-ze_zh.jsonl"
- config_name: lt-zh_cn
data_files: "data/lt-zh_cn.jsonl"
- config_name: lt-zh_tw
data_files: "data/lt-zh_tw.jsonl"
- config_name: lv-mk
data_files: "data/lv-mk.jsonl"
- config_name: lv-ml
data_files: "data/lv-ml.jsonl"
- config_name: lv-ms
data_files: "data/lv-ms.jsonl"
- config_name: lv-nl
data_files: "data/lv-nl.jsonl"
- config_name: lv-no
data_files: "data/lv-no.jsonl"
- config_name: lv-pl
data_files: "data/lv-pl.jsonl"
- config_name: lv-pt
data_files: "data/lv-pt.jsonl"
- config_name: lv-ro
data_files: "data/lv-ro.jsonl"
- config_name: lv-ru
data_files: "data/lv-ru.jsonl"
- config_name: lv-si
data_files: "data/lv-si.jsonl"
- config_name: lv-sk
data_files: "data/lv-sk.jsonl"
- config_name: lv-sl
data_files: "data/lv-sl.jsonl"
- config_name: lv-sq
data_files: "data/lv-sq.jsonl"
- config_name: lv-sr
data_files: "data/lv-sr.jsonl"
- config_name: lv-sv
data_files: "data/lv-sv.jsonl"
- config_name: lv-ta
data_files: "data/lv-ta.jsonl"
- config_name: lv-te
data_files: "data/lv-te.jsonl"
- config_name: lv-th
data_files: "data/lv-th.jsonl"
- config_name: lv-tr
data_files: "data/lv-tr.jsonl"
- config_name: lv-uk
data_files: "data/lv-uk.jsonl"
- config_name: lv-ur
data_files: "data/lv-ur.jsonl"
- config_name: lv-vi
data_files: "data/lv-vi.jsonl"
- config_name: lv-pt_br
data_files: "data/lv-pt_br.jsonl"
- config_name: lv-ze_en
data_files: "data/lv-ze_en.jsonl"
- config_name: lv-ze_zh
data_files: "data/lv-ze_zh.jsonl"
- config_name: lv-zh_cn
data_files: "data/lv-zh_cn.jsonl"
- config_name: lv-zh_tw
data_files: "data/lv-zh_tw.jsonl"
- config_name: mk-ml
data_files: "data/mk-ml.jsonl"
- config_name: mk-ms
data_files: "data/mk-ms.jsonl"
- config_name: mk-nl
data_files: "data/mk-nl.jsonl"
- config_name: mk-no
data_files: "data/mk-no.jsonl"
- config_name: mk-pl
data_files: "data/mk-pl.jsonl"
- config_name: mk-pt
data_files: "data/mk-pt.jsonl"
- config_name: mk-ro
data_files: "data/mk-ro.jsonl"
- config_name: mk-ru
data_files: "data/mk-ru.jsonl"
- config_name: mk-si
data_files: "data/mk-si.jsonl"
- config_name: mk-sk
data_files: "data/mk-sk.jsonl"
- config_name: mk-sl
data_files: "data/mk-sl.jsonl"
- config_name: mk-sq
data_files: "data/mk-sq.jsonl"
- config_name: mk-sr
data_files: "data/mk-sr.jsonl"
- config_name: mk-sv
data_files: "data/mk-sv.jsonl"
- config_name: mk-ta
data_files: "data/mk-ta.jsonl"
- config_name: mk-te
data_files: "data/mk-te.jsonl"
- config_name: mk-th
data_files: "data/mk-th.jsonl"
- config_name: mk-tl
data_files: "data/mk-tl.jsonl"
- config_name: mk-tr
data_files: "data/mk-tr.jsonl"
- config_name: mk-uk
data_files: "data/mk-uk.jsonl"
- config_name: mk-ur
data_files: "data/mk-ur.jsonl"
- config_name: mk-vi
data_files: "data/mk-vi.jsonl"
- config_name: mk-pt_br
data_files: "data/mk-pt_br.jsonl"
- config_name: mk-ze_en
data_files: "data/mk-ze_en.jsonl"
- config_name: mk-ze_zh
data_files: "data/mk-ze_zh.jsonl"
- config_name: mk-zh_cn
data_files: "data/mk-zh_cn.jsonl"
- config_name: mk-zh_tw
data_files: "data/mk-zh_tw.jsonl"
- config_name: ml-ms
data_files: "data/ml-ms.jsonl"
- config_name: ml-nl
data_files: "data/ml-nl.jsonl"
- config_name: ml-no
data_files: "data/ml-no.jsonl"
- config_name: ml-pl
data_files: "data/ml-pl.jsonl"
- config_name: ml-pt
data_files: "data/ml-pt.jsonl"
- config_name: ml-ro
data_files: "data/ml-ro.jsonl"
- config_name: ml-ru
data_files: "data/ml-ru.jsonl"
- config_name: ml-si
data_files: "data/ml-si.jsonl"
- config_name: ml-sk
data_files: "data/ml-sk.jsonl"
- config_name: ml-sl
data_files: "data/ml-sl.jsonl"
- config_name: ml-sq
data_files: "data/ml-sq.jsonl"
- config_name: ml-sr
data_files: "data/ml-sr.jsonl"
- config_name: ml-sv
data_files: "data/ml-sv.jsonl"
- config_name: ml-ta
data_files: "data/ml-ta.jsonl"
- config_name: ml-th
data_files: "data/ml-th.jsonl"
- config_name: ml-tl
data_files: "data/ml-tl.jsonl"
- config_name: ml-tr
data_files: "data/ml-tr.jsonl"
- config_name: ml-uk
data_files: "data/ml-uk.jsonl"
- config_name: ml-ur
data_files: "data/ml-ur.jsonl"
- config_name: ml-vi
data_files: "data/ml-vi.jsonl"
- config_name: ml-pt_br
data_files: "data/ml-pt_br.jsonl"
- config_name: ml-ze_en
data_files: "data/ml-ze_en.jsonl"
- config_name: ml-ze_zh
data_files: "data/ml-ze_zh.jsonl"
- config_name: ml-zh_cn
data_files: "data/ml-zh_cn.jsonl"
- config_name: ml-zh_tw
data_files: "data/ml-zh_tw.jsonl"
- config_name: ms-nl
data_files: "data/ms-nl.jsonl"
- config_name: ms-no
data_files: "data/ms-no.jsonl"
- config_name: ms-pl
data_files: "data/ms-pl.jsonl"
- config_name: ms-pt
data_files: "data/ms-pt.jsonl"
- config_name: ms-ro
data_files: "data/ms-ro.jsonl"
- config_name: ms-ru
data_files: "data/ms-ru.jsonl"
- config_name: ms-si
data_files: "data/ms-si.jsonl"
- config_name: ms-sk
data_files: "data/ms-sk.jsonl"
- config_name: ms-sl
data_files: "data/ms-sl.jsonl"
- config_name: ms-sq
data_files: "data/ms-sq.jsonl"
- config_name: ms-sr
data_files: "data/ms-sr.jsonl"
- config_name: ms-sv
data_files: "data/ms-sv.jsonl"
- config_name: ms-ta
data_files: "data/ms-ta.jsonl"
- config_name: ms-te
data_files: "data/ms-te.jsonl"
- config_name: ms-th
data_files: "data/ms-th.jsonl"
- config_name: ms-tl
data_files: "data/ms-tl.jsonl"
- config_name: ms-tr
data_files: "data/ms-tr.jsonl"
- config_name: ms-uk
data_files: "data/ms-uk.jsonl"
- config_name: ms-ur
data_files: "data/ms-ur.jsonl"
- config_name: ms-vi
data_files: "data/ms-vi.jsonl"
- config_name: ms-pt_br
data_files: "data/ms-pt_br.jsonl"
- config_name: ms-ze_en
data_files: "data/ms-ze_en.jsonl"
- config_name: ms-ze_zh
data_files: "data/ms-ze_zh.jsonl"
- config_name: ms-zh_cn
data_files: "data/ms-zh_cn.jsonl"
- config_name: ms-zh_tw
data_files: "data/ms-zh_tw.jsonl"
- config_name: nl-no
data_files: "data/nl-no.jsonl"
- config_name: nl-pl
data_files: "data/nl-pl.jsonl"
- config_name: nl-pt
data_files: "data/nl-pt.jsonl"
- config_name: nl-ro
data_files: "data/nl-ro.jsonl"
- config_name: nl-ru
data_files: "data/nl-ru.jsonl"
- config_name: nl-si
data_files: "data/nl-si.jsonl"
- config_name: nl-sk
data_files: "data/nl-sk.jsonl"
- config_name: nl-sl
data_files: "data/nl-sl.jsonl"
- config_name: nl-sq
data_files: "data/nl-sq.jsonl"
- config_name: nl-sr
data_files: "data/nl-sr.jsonl"
- config_name: nl-sv
data_files: "data/nl-sv.jsonl"
- config_name: nl-ta
data_files: "data/nl-ta.jsonl"
- config_name: nl-te
data_files: "data/nl-te.jsonl"
- config_name: nl-th
data_files: "data/nl-th.jsonl"
- config_name: nl-tl
data_files: "data/nl-tl.jsonl"
- config_name: nl-tr
data_files: "data/nl-tr.jsonl"
- config_name: nl-uk
data_files: "data/nl-uk.jsonl"
- config_name: nl-ur
data_files: "data/nl-ur.jsonl"
- config_name: nl-vi
data_files: "data/nl-vi.jsonl"
- config_name: nl-pt_br
data_files: "data/nl-pt_br.jsonl"
- config_name: nl-ze_en
data_files: "data/nl-ze_en.jsonl"
- config_name: nl-ze_zh
data_files: "data/nl-ze_zh.jsonl"
- config_name: nl-zh_cn
data_files: "data/nl-zh_cn.jsonl"
- config_name: nl-zh_tw
data_files: "data/nl-zh_tw.jsonl"
- config_name: no-pl
data_files: "data/no-pl.jsonl"
- config_name: no-pt
data_files: "data/no-pt.jsonl"
- config_name: no-ro
data_files: "data/no-ro.jsonl"
- config_name: no-ru
data_files: "data/no-ru.jsonl"
- config_name: no-si
data_files: "data/no-si.jsonl"
- config_name: no-sk
data_files: "data/no-sk.jsonl"
- config_name: no-sl
data_files: "data/no-sl.jsonl"
- config_name: no-sq
data_files: "data/no-sq.jsonl"
- config_name: no-sr
data_files: "data/no-sr.jsonl"
- config_name: no-sv
data_files: "data/no-sv.jsonl"
- config_name: no-ta
data_files: "data/no-ta.jsonl"
- config_name: no-te
data_files: "data/no-te.jsonl"
- config_name: no-th
data_files: "data/no-th.jsonl"
- config_name: no-tl
data_files: "data/no-tl.jsonl"
- config_name: no-tr
data_files: "data/no-tr.jsonl"
- config_name: no-uk
data_files: "data/no-uk.jsonl"
- config_name: no-ur
data_files: "data/no-ur.jsonl"
- config_name: no-vi
data_files: "data/no-vi.jsonl"
- config_name: no-pt_br
data_files: "data/no-pt_br.jsonl"
- config_name: no-ze_en
data_files: "data/no-ze_en.jsonl"
- config_name: no-ze_zh
data_files: "data/no-ze_zh.jsonl"
- config_name: no-zh_cn
data_files: "data/no-zh_cn.jsonl"
- config_name: no-zh_tw
data_files: "data/no-zh_tw.jsonl"
- config_name: pl-pt
data_files: "data/pl-pt.jsonl"
- config_name: pl-ro
data_files: "data/pl-ro.jsonl"
- config_name: pl-ru
data_files: "data/pl-ru.jsonl"
- config_name: pl-si
data_files: "data/pl-si.jsonl"
- config_name: pl-sk
data_files: "data/pl-sk.jsonl"
- config_name: pl-sl
data_files: "data/pl-sl.jsonl"
- config_name: pl-sq
data_files: "data/pl-sq.jsonl"
- config_name: pl-sr
data_files: "data/pl-sr.jsonl"
- config_name: pl-sv
data_files: "data/pl-sv.jsonl"
- config_name: pl-ta
data_files: "data/pl-ta.jsonl"
- config_name: pl-te
data_files: "data/pl-te.jsonl"
- config_name: pl-th
data_files: "data/pl-th.jsonl"
- config_name: pl-tl
data_files: "data/pl-tl.jsonl"
- config_name: pl-tr
data_files: "data/pl-tr.jsonl"
- config_name: pl-uk
data_files: "data/pl-uk.jsonl"
- config_name: pl-ur
data_files: "data/pl-ur.jsonl"
- config_name: pl-vi
data_files: "data/pl-vi.jsonl"
- config_name: pl-pt_br
data_files: "data/pl-pt_br.jsonl"
- config_name: pl-ze_en
data_files: "data/pl-ze_en.jsonl"
- config_name: pl-ze_zh
data_files: "data/pl-ze_zh.jsonl"
- config_name: pl-zh_cn
data_files: "data/pl-zh_cn.jsonl"
- config_name: pl-zh_tw
data_files: "data/pl-zh_tw.jsonl"
- config_name: pt-ro
data_files: "data/pt-ro.jsonl"
- config_name: pt-ru
data_files: "data/pt-ru.jsonl"
- config_name: pt-si
data_files: "data/pt-si.jsonl"
- config_name: pt-sk
data_files: "data/pt-sk.jsonl"
- config_name: pt-sl
data_files: "data/pt-sl.jsonl"
- config_name: pt-sq
data_files: "data/pt-sq.jsonl"
- config_name: pt-sr
data_files: "data/pt-sr.jsonl"
- config_name: pt-sv
data_files: "data/pt-sv.jsonl"
- config_name: pt-ta
data_files: "data/pt-ta.jsonl"
- config_name: pt-te
data_files: "data/pt-te.jsonl"
- config_name: pt-th
data_files: "data/pt-th.jsonl"
- config_name: pt-tl
data_files: "data/pt-tl.jsonl"
- config_name: pt-tr
data_files: "data/pt-tr.jsonl"
- config_name: pt-uk
data_files: "data/pt-uk.jsonl"
- config_name: pt-ur
data_files: "data/pt-ur.jsonl"
- config_name: pt-vi
data_files: "data/pt-vi.jsonl"
- config_name: pt-pt_br
data_files: "data/pt-pt_br.jsonl"
- config_name: pt-ze_en
data_files: "data/pt-ze_en.jsonl"
- config_name: pt-ze_zh
data_files: "data/pt-ze_zh.jsonl"
- config_name: pt-zh_cn
data_files: "data/pt-zh_cn.jsonl"
- config_name: pt-zh_tw
data_files: "data/pt-zh_tw.jsonl"
- config_name: ro-ru
data_files: "data/ro-ru.jsonl"
- config_name: ro-si
data_files: "data/ro-si.jsonl"
- config_name: ro-sk
data_files: "data/ro-sk.jsonl"
- config_name: ro-sl
data_files: "data/ro-sl.jsonl"
- config_name: ro-sq
data_files: "data/ro-sq.jsonl"
- config_name: ro-sr
data_files: "data/ro-sr.jsonl"
- config_name: ro-sv
data_files: "data/ro-sv.jsonl"
- config_name: ro-ta
data_files: "data/ro-ta.jsonl"
- config_name: ro-te
data_files: "data/ro-te.jsonl"
- config_name: ro-th
data_files: "data/ro-th.jsonl"
- config_name: ro-tl
data_files: "data/ro-tl.jsonl"
- config_name: ro-tr
data_files: "data/ro-tr.jsonl"
- config_name: ro-uk
data_files: "data/ro-uk.jsonl"
- config_name: ro-ur
data_files: "data/ro-ur.jsonl"
- config_name: ro-vi
data_files: "data/ro-vi.jsonl"
- config_name: ro-ze_en
data_files: "data/ro-ze_en.jsonl"
- config_name: ro-ze_zh
data_files: "data/ro-ze_zh.jsonl"
- config_name: ro-zh_cn
data_files: "data/ro-zh_cn.jsonl"
- config_name: ro-zh_tw
data_files: "data/ro-zh_tw.jsonl"
- config_name: ru-si
data_files: "data/ru-si.jsonl"
- config_name: ru-sk
data_files: "data/ru-sk.jsonl"
- config_name: ru-sl
data_files: "data/ru-sl.jsonl"
- config_name: ru-sq
data_files: "data/ru-sq.jsonl"
- config_name: ru-sr
data_files: "data/ru-sr.jsonl"
- config_name: ru-sv
data_files: "data/ru-sv.jsonl"
- config_name: ru-ta
data_files: "data/ru-ta.jsonl"
- config_name: ru-te
data_files: "data/ru-te.jsonl"
- config_name: ru-th
data_files: "data/ru-th.jsonl"
- config_name: ru-tl
data_files: "data/ru-tl.jsonl"
- config_name: ru-tr
data_files: "data/ru-tr.jsonl"
- config_name: ru-uk
data_files: "data/ru-uk.jsonl"
- config_name: ru-ur
data_files: "data/ru-ur.jsonl"
- config_name: ru-vi
data_files: "data/ru-vi.jsonl"
- config_name: ru-ze_en
data_files: "data/ru-ze_en.jsonl"
- config_name: ru-ze_zh
data_files: "data/ru-ze_zh.jsonl"
- config_name: ru-zh_cn
data_files: "data/ru-zh_cn.jsonl"
- config_name: ru-zh_tw
data_files: "data/ru-zh_tw.jsonl"
- config_name: si-sk
data_files: "data/si-sk.jsonl"
- config_name: si-sl
data_files: "data/si-sl.jsonl"
- config_name: si-sq
data_files: "data/si-sq.jsonl"
- config_name: si-sr
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data_files: "data/sq-zh_cn.jsonl"
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data_files: "data/sr-tl.jsonl"
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data_files: "data/th-vi.jsonl"
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data_files: "data/th-ze_en.jsonl"
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data_files: "data/th-ze_zh.jsonl"
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data_files: "data/th-zh_tw.jsonl"
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data_files: "data/tl-tr.jsonl"
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data_files: "data/tl-uk.jsonl"
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data_files: "data/tl-vi.jsonl"
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data_files: "data/tl-zh_cn.jsonl"
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data_files: "data/tl-zh_tw.jsonl"
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data_files: "data/tr-uk.jsonl"
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data_files: "data/tr-ur.jsonl"
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data_files: "data/tr-ze_zh.jsonl"
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data_files: "data/tr-zh_cn.jsonl"
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data_files: "data/tr-zh_tw.jsonl"
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data_files: "data/uk-ur.jsonl"
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data_files: "data/uk-vi.jsonl"
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data_files: "data/uk-ze_en.jsonl"
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data_files: "data/uk-ze_zh.jsonl"
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data_files: "data/uk-zh_cn.jsonl"
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data_files: "data/uk-zh_tw.jsonl"
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data_files: "data/ur-vi.jsonl"
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data_files: "data/ur-zh_cn.jsonl"
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data_files: "data/ur-zh_tw.jsonl"
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data_files: "data/vi-ze_en.jsonl"
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data_files: "data/vi-ze_zh.jsonl"
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data_files: "data/vi-zh_cn.jsonl"
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data_files: "data/vi-zh_tw.jsonl"
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data_files: "data/pt_br-ro.jsonl"
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data_files: "data/pt_br-ru.jsonl"
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data_files: "data/pt_br-si.jsonl"
- config_name: pt_br-sk
data_files: "data/pt_br-sk.jsonl"
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data_files: "data/pt_br-sl.jsonl"
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data_files: "data/pt_br-sq.jsonl"
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data_files: "data/pt_br-sr.jsonl"
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data_files: "data/pt_br-sv.jsonl"
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data_files: "data/pt_br-ta.jsonl"
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data_files: "data/pt_br-te.jsonl"
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data_files: "data/pt_br-th.jsonl"
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data_files: "data/pt_br-tl.jsonl"
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data_files: "data/pt_br-tr.jsonl"
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data_files: "data/pt_br-uk.jsonl"
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data_files: "data/pt_br-ur.jsonl"
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data_files: "data/pt_br-vi.jsonl"
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data_files: "data/pt_br-ze_en.jsonl"
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data_files: "data/pt_br-ze_zh.jsonl"
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data_files: "data/pt_br-zh_cn.jsonl"
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data_files: "data/pt_br-zh_tw.jsonl"
- config_name: ze_en-ze_zh
data_files: "data/ze_en-ze_zh.jsonl"
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data_files: "data/ze_en-zh_cn.jsonl"
- config_name: ze_en-zh_tw
data_files: "data/ze_en-zh_tw.jsonl"
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data_files: "data/ze_zh-zh_cn.jsonl"
- config_name: ze_zh-zh_tw
data_files: "data/ze_zh-zh_tw.jsonl"
- config_name: zh_cn-zh_tw
data_files: "data/zh_cn-zh_tw.jsonl"
---
|
pminervini/NQ-Swap | ---
license: mit
dataset_info:
features:
- name: question
dtype: string
- name: org_context
dtype: string
- name: org_answer
sequence: string
- name: sub_context
dtype: string
- name: sub_answer
sequence: string
splits:
- name: dev
num_bytes: 10056243
num_examples: 4746
download_size: 2754938
dataset_size: 10056243
configs:
- config_name: default
data_files:
- split: dev
path: data/dev-*
---
|
ademax/extract_metadata | ---
dataset_info:
features:
- name: input_text
dtype: string
- name: output_text
dtype: string
- name: type
dtype: string
splits:
- name: train
num_bytes: 6293702657
num_examples: 1696420
download_size: 2381793422
dataset_size: 6293702657
---
# Dataset Card for "extract_metadata"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
joneikholm/firstDataSet | ---
license: apache-2.0
---
|
khannz/docs | ---
license: apache-2.0
---
|
edy350/vozrick | ---
license: openrail
---
|
open-llm-leaderboard/details_VMware__open-llama-7b-open-instruct | ---
pretty_name: Evaluation run of VMware/open-llama-7b-open-instruct
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [VMware/open-llama-7b-open-instruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 3 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_VMware__open-llama-7b-open-instruct\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-23T05:54:33.646620](https://huggingface.co/datasets/open-llm-leaderboard/details_VMware__open-llama-7b-open-instruct/blob/main/results_2023-09-23T05-54-33.646620.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.24811241610738255,\n\
\ \"em_stderr\": 0.004423238498303271,\n \"f1\": 0.3074643456375843,\n\
\ \"f1_stderr\": 0.004402791070678147,\n \"acc\": 0.3298042752007123,\n\
\ \"acc_stderr\": 0.007683951336441218\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.24811241610738255,\n \"em_stderr\": 0.004423238498303271,\n\
\ \"f1\": 0.3074643456375843,\n \"f1_stderr\": 0.004402791070678147\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.00530705079605762,\n \
\ \"acc_stderr\": 0.0020013057209480527\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.654301499605367,\n \"acc_stderr\": 0.013366596951934383\n\
\ }\n}\n```"
repo_url: https://huggingface.co/VMware/open-llama-7b-open-instruct
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_drop_3
data_files:
- split: 2023_09_23T05_54_33.646620
path:
- '**/details_harness|drop|3_2023-09-23T05-54-33.646620.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-23T05-54-33.646620.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_23T05_54_33.646620
path:
- '**/details_harness|gsm8k|5_2023-09-23T05-54-33.646620.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-23T05-54-33.646620.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_23T05_54_33.646620
path:
- '**/details_harness|winogrande|5_2023-09-23T05-54-33.646620.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-23T05-54-33.646620.parquet'
- config_name: results
data_files:
- split: 2023_09_23T05_54_33.646620
path:
- results_2023-09-23T05-54-33.646620.parquet
- split: latest
path:
- results_2023-09-23T05-54-33.646620.parquet
---
# Dataset Card for Evaluation run of VMware/open-llama-7b-open-instruct
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/VMware/open-llama-7b-open-instruct
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [VMware/open-llama-7b-open-instruct](https://huggingface.co/VMware/open-llama-7b-open-instruct) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_VMware__open-llama-7b-open-instruct",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-23T05:54:33.646620](https://huggingface.co/datasets/open-llm-leaderboard/details_VMware__open-llama-7b-open-instruct/blob/main/results_2023-09-23T05-54-33.646620.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.24811241610738255,
"em_stderr": 0.004423238498303271,
"f1": 0.3074643456375843,
"f1_stderr": 0.004402791070678147,
"acc": 0.3298042752007123,
"acc_stderr": 0.007683951336441218
},
"harness|drop|3": {
"em": 0.24811241610738255,
"em_stderr": 0.004423238498303271,
"f1": 0.3074643456375843,
"f1_stderr": 0.004402791070678147
},
"harness|gsm8k|5": {
"acc": 0.00530705079605762,
"acc_stderr": 0.0020013057209480527
},
"harness|winogrande|5": {
"acc": 0.654301499605367,
"acc_stderr": 0.013366596951934383
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
edwinjue/311-data-2016 | ---
license: gpl-3.0
---
|
Minata/method2test_10k_tokonizedv2 | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 66680000
num_examples: 10000
download_size: 4572262
dataset_size: 66680000
---
# Dataset Card for "method2test_10k_tokonizedv2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
joddy/results_valid_20rows_2022-12-29 | ---
dataset_info:
features:
- name: pixel_values
dtype: image
- name: resolution
dtype: int64
- name: attributes_loc
dtype:
class_label:
names:
'0': upper left
'1': upper right
'2': lower left
'3': lower right
- name: NL_text
dtype: string
- name: bbox_text
dtype: string
- name: center_text
dtype: string
- name: normed_object_bbox
sequence: int64
- name: without_pos_stable-diffusion-v1-5
dtype: image
- name: NL_stable-diffusion-v1-5
dtype: image
- name: bbox_stable-diffusion-v1-5
dtype: image
- name: center_stable-diffusion-v1-5
dtype: image
- name: without_pos_NL_text_TextENC_off
dtype: image
- name: NL_text_TextENC_off
dtype: image
- name: without_pos_bbox_text_TextENC_off
dtype: image
- name: bbox_text_TextENC_off
dtype: image
- name: without_pos_center_text_TextENC_off
dtype: image
- name: center_text_TextENC_off
dtype: image
- name: without_pos_NL_text_TextENC_on
dtype: image
- name: NL_text_TextENC_on
dtype: image
- name: without_pos_bbox_text_TextENC_on
dtype: image
- name: bbox_text_TextENC_on
dtype: image
- name: without_pos_center_text_TextENC_on
dtype: image
- name: center_text_TextENC_on
dtype: image
splits:
- name: train
num_bytes: 160413036.0
num_examples: 20
download_size: 160434518
dataset_size: 160413036.0
---
# Dataset Card for "results_valid_20rows_2022-12-29"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
EleutherAI/quirky_hemisphere_alice_hard | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: alice_label
dtype: bool
- name: bob_label
dtype: bool
- name: difficulty
dtype: float64
- name: statement
dtype: string
- name: choices
sequence: string
- name: character
dtype: string
- name: label
dtype: bool
splits:
- name: train
num_bytes: 94130.23408514613
num_examples: 938
- name: validation
num_bytes: 52682.175
num_examples: 525
- name: test
num_bytes: 44019.73725
num_examples: 439
download_size: 49934
dataset_size: 190832.14633514616
---
# Dataset Card for "quirky_hemisphere_alice_hard"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
KentoTsu/vale | ---
license: openrail
---
|
dim/camel_ai_chemistry | ---
dataset_info:
features:
- name: role_1
dtype: string
- name: topic;
dtype: string
- name: sub_topic
dtype: string
- name: message_1
dtype: string
- name: message_2
dtype: string
splits:
- name: train
num_bytes: 47000178
num_examples: 20000
download_size: 16918940
dataset_size: 47000178
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "camel_ai_chemistry"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
lmvasque/hablacultura | ---
license: cc-by-4.0
---
## About this dataset
This dataset was collected from [HablaCultura.com](https://hablacultura.com/) a website with resources for Spanish students, labeled by instructors following the [Common European Framework of Reference for Languages (CEFR)](https://www.coe.int/en/web/common-european-framework-reference-languages). We have scraped the freely available articles from its original [website](https://hablacultura.com/) to make it available to the community. If you use this data, please credit the original [website](https://hablacultura.com/) and our work as well.
## Citation
If you use our splits in your research, please cite our work: "[A Benchmark for Neural Readability Assessment of Texts in Spanish](https://drive.google.com/file/d/1KdwvqrjX8MWYRDGBKeHmiR1NCzDcVizo/view?usp=share_link)".
```
@inproceedings{vasquez-rodriguez-etal-2022-benchmarking,
title = "A Benchmark for Neural Readability Assessment of Texts in Spanish",
author = "V{\'a}squez-Rodr{\'\i}guez, Laura and
Cuenca-Jim{\'\e}nez, Pedro-Manuel and
Morales-Esquivel, Sergio Esteban and
Alva-Manchego, Fernando",
booktitle = "Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), EMNLP 2022",
month = dec,
year = "2022",
}
```
You can also find more details about the project in our [GitHub](https://github.com/lmvasque/readability-es-benchmark). |
LambdaTests/VQAv2Validation_ViT_H_14_A_T_C_Q_benchmarks_partition_global_26_10000000 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: response
dtype: string
splits:
- name: train
num_bytes: 191998
num_examples: 6699
download_size: 122451
dataset_size: 191998
---
# Dataset Card for "VQAv2Validation_ViT_H_14_A_T_C_Q_benchmarks_partition_global_26_10000000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
robertollweb/imgRober | ---
license: unknown
---
|
open-llm-leaderboard/details_rufjdk5480__llama-7b-ludwig-alpaca | ---
pretty_name: Evaluation run of rufjdk5480/llama-7b-ludwig-alpaca
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [rufjdk5480/llama-7b-ludwig-alpaca](https://huggingface.co/rufjdk5480/llama-7b-ludwig-alpaca)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_rufjdk5480__llama-7b-ludwig-alpaca\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-04T19:02:43.278164](https://huggingface.co/datasets/open-llm-leaderboard/details_rufjdk5480__llama-7b-ludwig-alpaca/blob/main/results_2023-12-04T19-02-43.278164.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.46060379742069524,\n\
\ \"acc_stderr\": 0.03441125676761374,\n \"acc_norm\": 0.46498436629120626,\n\
\ \"acc_norm_stderr\": 0.03518871840894695,\n \"mc1\": 0.2864137086903305,\n\
\ \"mc1_stderr\": 0.015826142439502353,\n \"mc2\": 0.4191386468811098,\n\
\ \"mc2_stderr\": 0.014271816029328676\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5085324232081911,\n \"acc_stderr\": 0.014609263165632182,\n\
\ \"acc_norm\": 0.5401023890784983,\n \"acc_norm_stderr\": 0.01456431885692485\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5903206532563234,\n\
\ \"acc_stderr\": 0.004907694727935688,\n \"acc_norm\": 0.7872933678550089,\n\
\ \"acc_norm_stderr\": 0.004083855139469325\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4666666666666667,\n\
\ \"acc_stderr\": 0.043097329010363554,\n \"acc_norm\": 0.4666666666666667,\n\
\ \"acc_norm_stderr\": 0.043097329010363554\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.4276315789473684,\n \"acc_stderr\": 0.04026097083296558,\n\
\ \"acc_norm\": 0.4276315789473684,\n \"acc_norm_stderr\": 0.04026097083296558\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.54,\n\
\ \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n \
\ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.44150943396226416,\n \"acc_stderr\": 0.03056159042673184,\n\
\ \"acc_norm\": 0.44150943396226416,\n \"acc_norm_stderr\": 0.03056159042673184\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.4375,\n\
\ \"acc_stderr\": 0.04148415739394154,\n \"acc_norm\": 0.4375,\n \
\ \"acc_norm_stderr\": 0.04148415739394154\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \
\ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\": 0.36,\n\
\ \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.42196531791907516,\n\
\ \"acc_stderr\": 0.0376574669386515,\n \"acc_norm\": 0.42196531791907516,\n\
\ \"acc_norm_stderr\": 0.0376574669386515\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237654,\n\
\ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237654\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.59,\n \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n\
\ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.4340425531914894,\n \"acc_stderr\": 0.03240038086792747,\n\
\ \"acc_norm\": 0.4340425531914894,\n \"acc_norm_stderr\": 0.03240038086792747\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2631578947368421,\n\
\ \"acc_stderr\": 0.041424397194893624,\n \"acc_norm\": 0.2631578947368421,\n\
\ \"acc_norm_stderr\": 0.041424397194893624\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.41379310344827586,\n \"acc_stderr\": 0.04104269211806232,\n\
\ \"acc_norm\": 0.41379310344827586,\n \"acc_norm_stderr\": 0.04104269211806232\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.25396825396825395,\n \"acc_stderr\": 0.02241804289111394,\n \"\
acc_norm\": 0.25396825396825395,\n \"acc_norm_stderr\": 0.02241804289111394\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2698412698412698,\n\
\ \"acc_stderr\": 0.039701582732351734,\n \"acc_norm\": 0.2698412698412698,\n\
\ \"acc_norm_stderr\": 0.039701582732351734\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \
\ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.47419354838709676,\n \"acc_stderr\": 0.028406095057653315,\n \"\
acc_norm\": 0.47419354838709676,\n \"acc_norm_stderr\": 0.028406095057653315\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.31527093596059114,\n \"acc_stderr\": 0.03269080871970187,\n \"\
acc_norm\": 0.31527093596059114,\n \"acc_norm_stderr\": 0.03269080871970187\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.43,\n \"acc_stderr\": 0.049756985195624284,\n \"acc_norm\"\
: 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.6060606060606061,\n \"acc_stderr\": 0.038154943086889305,\n\
\ \"acc_norm\": 0.6060606060606061,\n \"acc_norm_stderr\": 0.038154943086889305\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.5252525252525253,\n \"acc_stderr\": 0.03557806245087314,\n \"\
acc_norm\": 0.5252525252525253,\n \"acc_norm_stderr\": 0.03557806245087314\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.694300518134715,\n \"acc_stderr\": 0.03324837939758159,\n\
\ \"acc_norm\": 0.694300518134715,\n \"acc_norm_stderr\": 0.03324837939758159\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.4461538461538462,\n \"acc_stderr\": 0.025203571773028333,\n\
\ \"acc_norm\": 0.4461538461538462,\n \"acc_norm_stderr\": 0.025203571773028333\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.25555555555555554,\n \"acc_stderr\": 0.026593939101844086,\n \
\ \"acc_norm\": 0.25555555555555554,\n \"acc_norm_stderr\": 0.026593939101844086\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.41596638655462187,\n \"acc_stderr\": 0.03201650100739615,\n\
\ \"acc_norm\": 0.41596638655462187,\n \"acc_norm_stderr\": 0.03201650100739615\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.2913907284768212,\n \"acc_stderr\": 0.03710185726119995,\n \"\
acc_norm\": 0.2913907284768212,\n \"acc_norm_stderr\": 0.03710185726119995\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.6311926605504588,\n \"acc_stderr\": 0.020686227560729565,\n \"\
acc_norm\": 0.6311926605504588,\n \"acc_norm_stderr\": 0.020686227560729565\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.2962962962962963,\n \"acc_stderr\": 0.03114144782353603,\n \"\
acc_norm\": 0.2962962962962963,\n \"acc_norm_stderr\": 0.03114144782353603\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.5686274509803921,\n \"acc_stderr\": 0.03476099060501636,\n \"\
acc_norm\": 0.5686274509803921,\n \"acc_norm_stderr\": 0.03476099060501636\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.6371308016877637,\n \"acc_stderr\": 0.03129920825530213,\n \
\ \"acc_norm\": 0.6371308016877637,\n \"acc_norm_stderr\": 0.03129920825530213\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5291479820627802,\n\
\ \"acc_stderr\": 0.03350073248773404,\n \"acc_norm\": 0.5291479820627802,\n\
\ \"acc_norm_stderr\": 0.03350073248773404\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.5343511450381679,\n \"acc_stderr\": 0.043749285605997376,\n\
\ \"acc_norm\": 0.5343511450381679,\n \"acc_norm_stderr\": 0.043749285605997376\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.6363636363636364,\n \"acc_stderr\": 0.043913262867240704,\n \"\
acc_norm\": 0.6363636363636364,\n \"acc_norm_stderr\": 0.043913262867240704\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5092592592592593,\n\
\ \"acc_stderr\": 0.04832853553437055,\n \"acc_norm\": 0.5092592592592593,\n\
\ \"acc_norm_stderr\": 0.04832853553437055\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.49693251533742333,\n \"acc_stderr\": 0.03928297078179663,\n\
\ \"acc_norm\": 0.49693251533742333,\n \"acc_norm_stderr\": 0.03928297078179663\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.36607142857142855,\n\
\ \"acc_stderr\": 0.0457237235873743,\n \"acc_norm\": 0.36607142857142855,\n\
\ \"acc_norm_stderr\": 0.0457237235873743\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.5533980582524272,\n \"acc_stderr\": 0.04922424153458933,\n\
\ \"acc_norm\": 0.5533980582524272,\n \"acc_norm_stderr\": 0.04922424153458933\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7051282051282052,\n\
\ \"acc_stderr\": 0.029872577708891197,\n \"acc_norm\": 0.7051282051282052,\n\
\ \"acc_norm_stderr\": 0.029872577708891197\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \
\ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6130268199233716,\n\
\ \"acc_stderr\": 0.017417138059440132,\n \"acc_norm\": 0.6130268199233716,\n\
\ \"acc_norm_stderr\": 0.017417138059440132\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.5115606936416185,\n \"acc_stderr\": 0.026911898686377927,\n\
\ \"acc_norm\": 0.5115606936416185,\n \"acc_norm_stderr\": 0.026911898686377927\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23910614525139665,\n\
\ \"acc_stderr\": 0.014265554192331144,\n \"acc_norm\": 0.23910614525139665,\n\
\ \"acc_norm_stderr\": 0.014265554192331144\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.4869281045751634,\n \"acc_stderr\": 0.028620130800700246,\n\
\ \"acc_norm\": 0.4869281045751634,\n \"acc_norm_stderr\": 0.028620130800700246\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5980707395498392,\n\
\ \"acc_stderr\": 0.02784647600593047,\n \"acc_norm\": 0.5980707395498392,\n\
\ \"acc_norm_stderr\": 0.02784647600593047\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.4845679012345679,\n \"acc_stderr\": 0.0278074900442762,\n\
\ \"acc_norm\": 0.4845679012345679,\n \"acc_norm_stderr\": 0.0278074900442762\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.34397163120567376,\n \"acc_stderr\": 0.028338017428611327,\n \
\ \"acc_norm\": 0.34397163120567376,\n \"acc_norm_stderr\": 0.028338017428611327\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.36571056062581486,\n\
\ \"acc_stderr\": 0.012301028188840567,\n \"acc_norm\": 0.36571056062581486,\n\
\ \"acc_norm_stderr\": 0.012301028188840567\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.5257352941176471,\n \"acc_stderr\": 0.03033257809455504,\n\
\ \"acc_norm\": 0.5257352941176471,\n \"acc_norm_stderr\": 0.03033257809455504\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.43300653594771243,\n \"acc_stderr\": 0.020045442473324227,\n \
\ \"acc_norm\": 0.43300653594771243,\n \"acc_norm_stderr\": 0.020045442473324227\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5272727272727272,\n\
\ \"acc_stderr\": 0.04782001791380061,\n \"acc_norm\": 0.5272727272727272,\n\
\ \"acc_norm_stderr\": 0.04782001791380061\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.47346938775510206,\n \"acc_stderr\": 0.03196412734523272,\n\
\ \"acc_norm\": 0.47346938775510206,\n \"acc_norm_stderr\": 0.03196412734523272\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.5920398009950248,\n\
\ \"acc_stderr\": 0.03475116365194092,\n \"acc_norm\": 0.5920398009950248,\n\
\ \"acc_norm_stderr\": 0.03475116365194092\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.63,\n \"acc_stderr\": 0.04852365870939099,\n \
\ \"acc_norm\": 0.63,\n \"acc_norm_stderr\": 0.04852365870939099\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.39759036144578314,\n\
\ \"acc_stderr\": 0.038099730845402184,\n \"acc_norm\": 0.39759036144578314,\n\
\ \"acc_norm_stderr\": 0.038099730845402184\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.6608187134502924,\n \"acc_stderr\": 0.03631053496488905,\n\
\ \"acc_norm\": 0.6608187134502924,\n \"acc_norm_stderr\": 0.03631053496488905\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2864137086903305,\n\
\ \"mc1_stderr\": 0.015826142439502353,\n \"mc2\": 0.4191386468811098,\n\
\ \"mc2_stderr\": 0.014271816029328676\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7426992896606156,\n \"acc_stderr\": 0.01228598961886571\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.14859742228961334,\n \
\ \"acc_stderr\": 0.00979750318052788\n }\n}\n```"
repo_url: https://huggingface.co/rufjdk5480/llama-7b-ludwig-alpaca
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|arc:challenge|25_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|gsm8k|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hellaswag|10_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-04T19-02-43.278164.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-04T19-02-43.278164.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- '**/details_harness|winogrande|5_2023-12-04T19-02-43.278164.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-04T19-02-43.278164.parquet'
- config_name: results
data_files:
- split: 2023_12_04T19_02_43.278164
path:
- results_2023-12-04T19-02-43.278164.parquet
- split: latest
path:
- results_2023-12-04T19-02-43.278164.parquet
---
# Dataset Card for Evaluation run of rufjdk5480/llama-7b-ludwig-alpaca
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/rufjdk5480/llama-7b-ludwig-alpaca
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [rufjdk5480/llama-7b-ludwig-alpaca](https://huggingface.co/rufjdk5480/llama-7b-ludwig-alpaca) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_rufjdk5480__llama-7b-ludwig-alpaca",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-04T19:02:43.278164](https://huggingface.co/datasets/open-llm-leaderboard/details_rufjdk5480__llama-7b-ludwig-alpaca/blob/main/results_2023-12-04T19-02-43.278164.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.46060379742069524,
"acc_stderr": 0.03441125676761374,
"acc_norm": 0.46498436629120626,
"acc_norm_stderr": 0.03518871840894695,
"mc1": 0.2864137086903305,
"mc1_stderr": 0.015826142439502353,
"mc2": 0.4191386468811098,
"mc2_stderr": 0.014271816029328676
},
"harness|arc:challenge|25": {
"acc": 0.5085324232081911,
"acc_stderr": 0.014609263165632182,
"acc_norm": 0.5401023890784983,
"acc_norm_stderr": 0.01456431885692485
},
"harness|hellaswag|10": {
"acc": 0.5903206532563234,
"acc_stderr": 0.004907694727935688,
"acc_norm": 0.7872933678550089,
"acc_norm_stderr": 0.004083855139469325
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.32,
"acc_stderr": 0.046882617226215034,
"acc_norm": 0.32,
"acc_norm_stderr": 0.046882617226215034
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.4666666666666667,
"acc_stderr": 0.043097329010363554,
"acc_norm": 0.4666666666666667,
"acc_norm_stderr": 0.043097329010363554
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.4276315789473684,
"acc_stderr": 0.04026097083296558,
"acc_norm": 0.4276315789473684,
"acc_norm_stderr": 0.04026097083296558
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620332,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620332
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.44150943396226416,
"acc_stderr": 0.03056159042673184,
"acc_norm": 0.44150943396226416,
"acc_norm_stderr": 0.03056159042673184
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.4375,
"acc_stderr": 0.04148415739394154,
"acc_norm": 0.4375,
"acc_norm_stderr": 0.04148415739394154
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.31,
"acc_stderr": 0.04648231987117316,
"acc_norm": 0.31,
"acc_norm_stderr": 0.04648231987117316
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.36,
"acc_stderr": 0.04824181513244218,
"acc_norm": 0.36,
"acc_norm_stderr": 0.04824181513244218
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.35,
"acc_stderr": 0.047937248544110196,
"acc_norm": 0.35,
"acc_norm_stderr": 0.047937248544110196
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.42196531791907516,
"acc_stderr": 0.0376574669386515,
"acc_norm": 0.42196531791907516,
"acc_norm_stderr": 0.0376574669386515
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.21568627450980393,
"acc_stderr": 0.04092563958237654,
"acc_norm": 0.21568627450980393,
"acc_norm_stderr": 0.04092563958237654
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.59,
"acc_stderr": 0.049431107042371025,
"acc_norm": 0.59,
"acc_norm_stderr": 0.049431107042371025
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.4340425531914894,
"acc_stderr": 0.03240038086792747,
"acc_norm": 0.4340425531914894,
"acc_norm_stderr": 0.03240038086792747
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.2631578947368421,
"acc_stderr": 0.041424397194893624,
"acc_norm": 0.2631578947368421,
"acc_norm_stderr": 0.041424397194893624
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.41379310344827586,
"acc_stderr": 0.04104269211806232,
"acc_norm": 0.41379310344827586,
"acc_norm_stderr": 0.04104269211806232
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.25396825396825395,
"acc_stderr": 0.02241804289111394,
"acc_norm": 0.25396825396825395,
"acc_norm_stderr": 0.02241804289111394
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.2698412698412698,
"acc_stderr": 0.039701582732351734,
"acc_norm": 0.2698412698412698,
"acc_norm_stderr": 0.039701582732351734
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.29,
"acc_stderr": 0.045604802157206845,
"acc_norm": 0.29,
"acc_norm_stderr": 0.045604802157206845
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.47419354838709676,
"acc_stderr": 0.028406095057653315,
"acc_norm": 0.47419354838709676,
"acc_norm_stderr": 0.028406095057653315
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.31527093596059114,
"acc_stderr": 0.03269080871970187,
"acc_norm": 0.31527093596059114,
"acc_norm_stderr": 0.03269080871970187
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.43,
"acc_stderr": 0.049756985195624284,
"acc_norm": 0.43,
"acc_norm_stderr": 0.049756985195624284
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.6060606060606061,
"acc_stderr": 0.038154943086889305,
"acc_norm": 0.6060606060606061,
"acc_norm_stderr": 0.038154943086889305
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.5252525252525253,
"acc_stderr": 0.03557806245087314,
"acc_norm": 0.5252525252525253,
"acc_norm_stderr": 0.03557806245087314
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.694300518134715,
"acc_stderr": 0.03324837939758159,
"acc_norm": 0.694300518134715,
"acc_norm_stderr": 0.03324837939758159
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.4461538461538462,
"acc_stderr": 0.025203571773028333,
"acc_norm": 0.4461538461538462,
"acc_norm_stderr": 0.025203571773028333
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.25555555555555554,
"acc_stderr": 0.026593939101844086,
"acc_norm": 0.25555555555555554,
"acc_norm_stderr": 0.026593939101844086
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.41596638655462187,
"acc_stderr": 0.03201650100739615,
"acc_norm": 0.41596638655462187,
"acc_norm_stderr": 0.03201650100739615
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.2913907284768212,
"acc_stderr": 0.03710185726119995,
"acc_norm": 0.2913907284768212,
"acc_norm_stderr": 0.03710185726119995
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.6311926605504588,
"acc_stderr": 0.020686227560729565,
"acc_norm": 0.6311926605504588,
"acc_norm_stderr": 0.020686227560729565
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.2962962962962963,
"acc_stderr": 0.03114144782353603,
"acc_norm": 0.2962962962962963,
"acc_norm_stderr": 0.03114144782353603
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.5686274509803921,
"acc_stderr": 0.03476099060501636,
"acc_norm": 0.5686274509803921,
"acc_norm_stderr": 0.03476099060501636
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.6371308016877637,
"acc_stderr": 0.03129920825530213,
"acc_norm": 0.6371308016877637,
"acc_norm_stderr": 0.03129920825530213
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.5291479820627802,
"acc_stderr": 0.03350073248773404,
"acc_norm": 0.5291479820627802,
"acc_norm_stderr": 0.03350073248773404
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.5343511450381679,
"acc_stderr": 0.043749285605997376,
"acc_norm": 0.5343511450381679,
"acc_norm_stderr": 0.043749285605997376
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.6363636363636364,
"acc_stderr": 0.043913262867240704,
"acc_norm": 0.6363636363636364,
"acc_norm_stderr": 0.043913262867240704
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.5092592592592593,
"acc_stderr": 0.04832853553437055,
"acc_norm": 0.5092592592592593,
"acc_norm_stderr": 0.04832853553437055
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.49693251533742333,
"acc_stderr": 0.03928297078179663,
"acc_norm": 0.49693251533742333,
"acc_norm_stderr": 0.03928297078179663
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.36607142857142855,
"acc_stderr": 0.0457237235873743,
"acc_norm": 0.36607142857142855,
"acc_norm_stderr": 0.0457237235873743
},
"harness|hendrycksTest-management|5": {
"acc": 0.5533980582524272,
"acc_stderr": 0.04922424153458933,
"acc_norm": 0.5533980582524272,
"acc_norm_stderr": 0.04922424153458933
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.7051282051282052,
"acc_stderr": 0.029872577708891197,
"acc_norm": 0.7051282051282052,
"acc_norm_stderr": 0.029872577708891197
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.5,
"acc_stderr": 0.050251890762960605,
"acc_norm": 0.5,
"acc_norm_stderr": 0.050251890762960605
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.6130268199233716,
"acc_stderr": 0.017417138059440132,
"acc_norm": 0.6130268199233716,
"acc_norm_stderr": 0.017417138059440132
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.5115606936416185,
"acc_stderr": 0.026911898686377927,
"acc_norm": 0.5115606936416185,
"acc_norm_stderr": 0.026911898686377927
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.23910614525139665,
"acc_stderr": 0.014265554192331144,
"acc_norm": 0.23910614525139665,
"acc_norm_stderr": 0.014265554192331144
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.4869281045751634,
"acc_stderr": 0.028620130800700246,
"acc_norm": 0.4869281045751634,
"acc_norm_stderr": 0.028620130800700246
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.5980707395498392,
"acc_stderr": 0.02784647600593047,
"acc_norm": 0.5980707395498392,
"acc_norm_stderr": 0.02784647600593047
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.4845679012345679,
"acc_stderr": 0.0278074900442762,
"acc_norm": 0.4845679012345679,
"acc_norm_stderr": 0.0278074900442762
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.34397163120567376,
"acc_stderr": 0.028338017428611327,
"acc_norm": 0.34397163120567376,
"acc_norm_stderr": 0.028338017428611327
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.36571056062581486,
"acc_stderr": 0.012301028188840567,
"acc_norm": 0.36571056062581486,
"acc_norm_stderr": 0.012301028188840567
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.5257352941176471,
"acc_stderr": 0.03033257809455504,
"acc_norm": 0.5257352941176471,
"acc_norm_stderr": 0.03033257809455504
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.43300653594771243,
"acc_stderr": 0.020045442473324227,
"acc_norm": 0.43300653594771243,
"acc_norm_stderr": 0.020045442473324227
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.5272727272727272,
"acc_stderr": 0.04782001791380061,
"acc_norm": 0.5272727272727272,
"acc_norm_stderr": 0.04782001791380061
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.47346938775510206,
"acc_stderr": 0.03196412734523272,
"acc_norm": 0.47346938775510206,
"acc_norm_stderr": 0.03196412734523272
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.5920398009950248,
"acc_stderr": 0.03475116365194092,
"acc_norm": 0.5920398009950248,
"acc_norm_stderr": 0.03475116365194092
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.63,
"acc_stderr": 0.04852365870939099,
"acc_norm": 0.63,
"acc_norm_stderr": 0.04852365870939099
},
"harness|hendrycksTest-virology|5": {
"acc": 0.39759036144578314,
"acc_stderr": 0.038099730845402184,
"acc_norm": 0.39759036144578314,
"acc_norm_stderr": 0.038099730845402184
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.6608187134502924,
"acc_stderr": 0.03631053496488905,
"acc_norm": 0.6608187134502924,
"acc_norm_stderr": 0.03631053496488905
},
"harness|truthfulqa:mc|0": {
"mc1": 0.2864137086903305,
"mc1_stderr": 0.015826142439502353,
"mc2": 0.4191386468811098,
"mc2_stderr": 0.014271816029328676
},
"harness|winogrande|5": {
"acc": 0.7426992896606156,
"acc_stderr": 0.01228598961886571
},
"harness|gsm8k|5": {
"acc": 0.14859742228961334,
"acc_stderr": 0.00979750318052788
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
nbroad/kaggle_rank_image | ---
license: apache-2.0
---
|
XavierF/medievalmusicalinstruments | ---
license: bigscience-bloom-rail-1.0
---
|
davide221/verilog-raw-100k | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1890036875
num_examples: 108971
download_size: 467354241
dataset_size: 1890036875
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
open-llm-leaderboard/details_core-3__kuno-royale-7b | ---
pretty_name: Evaluation run of core-3/kuno-royale-7B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [core-3/kuno-royale-7B](https://huggingface.co/core-3/kuno-royale-7B) on the [Open\
\ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_core-3__kuno-royale-7B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-01T02:42:37.070632](https://huggingface.co/datasets/open-llm-leaderboard/details_core-3__kuno-royale-7B/blob/main/results_2024-03-01T02-42-37.070632.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6565906694931584,\n\
\ \"acc_stderr\": 0.03211697517911788,\n \"acc_norm\": 0.65630213903749,\n\
\ \"acc_norm_stderr\": 0.03278293022940174,\n \"mc1\": 0.5618115055079559,\n\
\ \"mc1_stderr\": 0.01736923616440441,\n \"mc2\": 0.7111801311531581,\n\
\ \"mc2_stderr\": 0.01477958957726906\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6962457337883959,\n \"acc_stderr\": 0.01343890918477876,\n\
\ \"acc_norm\": 0.7175767918088737,\n \"acc_norm_stderr\": 0.013155456884097224\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7113124875522804,\n\
\ \"acc_stderr\": 0.004522262128176996,\n \"acc_norm\": 0.8819956184027086,\n\
\ \"acc_norm_stderr\": 0.00321953979050048\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \
\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6444444444444445,\n\
\ \"acc_stderr\": 0.04135176749720385,\n \"acc_norm\": 0.6444444444444445,\n\
\ \"acc_norm_stderr\": 0.04135176749720385\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\
\ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.62,\n\
\ \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n \
\ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7132075471698113,\n \"acc_stderr\": 0.027834912527544064,\n\
\ \"acc_norm\": 0.7132075471698113,\n \"acc_norm_stderr\": 0.027834912527544064\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7777777777777778,\n\
\ \"acc_stderr\": 0.03476590104304134,\n \"acc_norm\": 0.7777777777777778,\n\
\ \"acc_norm_stderr\": 0.03476590104304134\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956911,\n \
\ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956911\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.55,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.55,\n \"\
acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.653179190751445,\n\
\ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\
\ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.4117647058823529,\n \"acc_stderr\": 0.048971049527263666,\n\
\ \"acc_norm\": 0.4117647058823529,\n \"acc_norm_stderr\": 0.048971049527263666\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.76,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.76,\n\
\ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5872340425531914,\n \"acc_stderr\": 0.03218471141400351,\n\
\ \"acc_norm\": 0.5872340425531914,\n \"acc_norm_stderr\": 0.03218471141400351\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5087719298245614,\n\
\ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.5087719298245614,\n\
\ \"acc_norm_stderr\": 0.04702880432049615\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5655172413793104,\n \"acc_stderr\": 0.04130740879555498,\n\
\ \"acc_norm\": 0.5655172413793104,\n \"acc_norm_stderr\": 0.04130740879555498\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.4074074074074074,\n \"acc_stderr\": 0.02530590624159063,\n \"\
acc_norm\": 0.4074074074074074,\n \"acc_norm_stderr\": 0.02530590624159063\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.49206349206349204,\n\
\ \"acc_stderr\": 0.044715725362943486,\n \"acc_norm\": 0.49206349206349204,\n\
\ \"acc_norm_stderr\": 0.044715725362943486\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \
\ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7806451612903226,\n\
\ \"acc_stderr\": 0.023540799358723295,\n \"acc_norm\": 0.7806451612903226,\n\
\ \"acc_norm_stderr\": 0.023540799358723295\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.5073891625615764,\n \"acc_stderr\": 0.035176035403610105,\n\
\ \"acc_norm\": 0.5073891625615764,\n \"acc_norm_stderr\": 0.035176035403610105\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\
: 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7515151515151515,\n \"acc_stderr\": 0.033744026441394036,\n\
\ \"acc_norm\": 0.7515151515151515,\n \"acc_norm_stderr\": 0.033744026441394036\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7828282828282829,\n \"acc_stderr\": 0.02937661648494562,\n \"\
acc_norm\": 0.7828282828282829,\n \"acc_norm_stderr\": 0.02937661648494562\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8911917098445595,\n \"acc_stderr\": 0.022473253332768763,\n\
\ \"acc_norm\": 0.8911917098445595,\n \"acc_norm_stderr\": 0.022473253332768763\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6717948717948717,\n \"acc_stderr\": 0.023807633198657266,\n\
\ \"acc_norm\": 0.6717948717948717,\n \"acc_norm_stderr\": 0.023807633198657266\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.35555555555555557,\n \"acc_stderr\": 0.029185714949857416,\n \
\ \"acc_norm\": 0.35555555555555557,\n \"acc_norm_stderr\": 0.029185714949857416\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6974789915966386,\n \"acc_stderr\": 0.029837962388291936,\n\
\ \"acc_norm\": 0.6974789915966386,\n \"acc_norm_stderr\": 0.029837962388291936\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.39072847682119205,\n \"acc_stderr\": 0.03983798306659807,\n \"\
acc_norm\": 0.39072847682119205,\n \"acc_norm_stderr\": 0.03983798306659807\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8477064220183487,\n \"acc_stderr\": 0.015405084393157074,\n \"\
acc_norm\": 0.8477064220183487,\n \"acc_norm_stderr\": 0.015405084393157074\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5462962962962963,\n \"acc_stderr\": 0.033953227263757976,\n \"\
acc_norm\": 0.5462962962962963,\n \"acc_norm_stderr\": 0.033953227263757976\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8480392156862745,\n \"acc_stderr\": 0.0251956584289318,\n \"acc_norm\"\
: 0.8480392156862745,\n \"acc_norm_stderr\": 0.0251956584289318\n },\n\
\ \"harness|hendrycksTest-high_school_world_history|5\": {\n \"acc\":\
\ 0.8227848101265823,\n \"acc_stderr\": 0.02485636418450322,\n \"\
acc_norm\": 0.8227848101265823,\n \"acc_norm_stderr\": 0.02485636418450322\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6771300448430493,\n\
\ \"acc_stderr\": 0.031381476375754995,\n \"acc_norm\": 0.6771300448430493,\n\
\ \"acc_norm_stderr\": 0.031381476375754995\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.8015267175572519,\n \"acc_stderr\": 0.03498149385462472,\n\
\ \"acc_norm\": 0.8015267175572519,\n \"acc_norm_stderr\": 0.03498149385462472\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\
acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\
\ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\
\ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7791411042944786,\n \"acc_stderr\": 0.03259177392742178,\n\
\ \"acc_norm\": 0.7791411042944786,\n \"acc_norm_stderr\": 0.03259177392742178\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.44642857142857145,\n\
\ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\
\ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7766990291262136,\n \"acc_stderr\": 0.04123553189891431,\n\
\ \"acc_norm\": 0.7766990291262136,\n \"acc_norm_stderr\": 0.04123553189891431\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8632478632478633,\n\
\ \"acc_stderr\": 0.022509033937077805,\n \"acc_norm\": 0.8632478632478633,\n\
\ \"acc_norm_stderr\": 0.022509033937077805\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \
\ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.045126085985421276\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8275862068965517,\n\
\ \"acc_stderr\": 0.013507943909371802,\n \"acc_norm\": 0.8275862068965517,\n\
\ \"acc_norm_stderr\": 0.013507943909371802\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7312138728323699,\n \"acc_stderr\": 0.023868003262500097,\n\
\ \"acc_norm\": 0.7312138728323699,\n \"acc_norm_stderr\": 0.023868003262500097\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.45139664804469276,\n\
\ \"acc_stderr\": 0.016643307372315883,\n \"acc_norm\": 0.45139664804469276,\n\
\ \"acc_norm_stderr\": 0.016643307372315883\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\
\ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7106109324758842,\n\
\ \"acc_stderr\": 0.025755865922632945,\n \"acc_norm\": 0.7106109324758842,\n\
\ \"acc_norm_stderr\": 0.025755865922632945\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7469135802469136,\n \"acc_stderr\": 0.024191808600713,\n\
\ \"acc_norm\": 0.7469135802469136,\n \"acc_norm_stderr\": 0.024191808600713\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.48226950354609927,\n \"acc_stderr\": 0.02980873964223777,\n \
\ \"acc_norm\": 0.48226950354609927,\n \"acc_norm_stderr\": 0.02980873964223777\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4765319426336376,\n\
\ \"acc_stderr\": 0.012756161942523372,\n \"acc_norm\": 0.4765319426336376,\n\
\ \"acc_norm_stderr\": 0.012756161942523372\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6948529411764706,\n \"acc_stderr\": 0.027971541370170595,\n\
\ \"acc_norm\": 0.6948529411764706,\n \"acc_norm_stderr\": 0.027971541370170595\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6748366013071896,\n \"acc_stderr\": 0.018950886770806315,\n \
\ \"acc_norm\": 0.6748366013071896,\n \"acc_norm_stderr\": 0.018950886770806315\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\
\ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\
\ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7428571428571429,\n \"acc_stderr\": 0.02797982353874455,\n\
\ \"acc_norm\": 0.7428571428571429,\n \"acc_norm_stderr\": 0.02797982353874455\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.835820895522388,\n\
\ \"acc_stderr\": 0.026193923544454115,\n \"acc_norm\": 0.835820895522388,\n\
\ \"acc_norm_stderr\": 0.026193923544454115\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \
\ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\
\ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.536144578313253,\n\
\ \"acc_stderr\": 0.038823108508905954,\n \"acc_norm\": 0.536144578313253,\n\
\ \"acc_norm_stderr\": 0.038823108508905954\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8538011695906432,\n \"acc_stderr\": 0.02709729011807081,\n\
\ \"acc_norm\": 0.8538011695906432,\n \"acc_norm_stderr\": 0.02709729011807081\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5618115055079559,\n\
\ \"mc1_stderr\": 0.01736923616440441,\n \"mc2\": 0.7111801311531581,\n\
\ \"mc2_stderr\": 0.01477958957726906\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8232044198895028,\n \"acc_stderr\": 0.010721923287918756\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6990144048521607,\n \
\ \"acc_stderr\": 0.012634504465211173\n }\n}\n```"
repo_url: https://huggingface.co/core-3/kuno-royale-7B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|arc:challenge|25_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|arc:challenge|25_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|gsm8k|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|gsm8k|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hellaswag|10_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hellaswag|10_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T02-35-59.367091.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T02-42-37.070632.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T02-42-37.070632.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- '**/details_harness|winogrande|5_2024-03-01T02-35-59.367091.parquet'
- split: 2024_03_01T02_42_37.070632
path:
- '**/details_harness|winogrande|5_2024-03-01T02-42-37.070632.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-01T02-42-37.070632.parquet'
- config_name: results
data_files:
- split: 2024_03_01T02_35_59.367091
path:
- results_2024-03-01T02-35-59.367091.parquet
- split: 2024_03_01T02_42_37.070632
path:
- results_2024-03-01T02-42-37.070632.parquet
- split: latest
path:
- results_2024-03-01T02-42-37.070632.parquet
---
# Dataset Card for Evaluation run of core-3/kuno-royale-7B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [core-3/kuno-royale-7B](https://huggingface.co/core-3/kuno-royale-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_core-3__kuno-royale-7B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-01T02:42:37.070632](https://huggingface.co/datasets/open-llm-leaderboard/details_core-3__kuno-royale-7B/blob/main/results_2024-03-01T02-42-37.070632.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.6565906694931584,
"acc_stderr": 0.03211697517911788,
"acc_norm": 0.65630213903749,
"acc_norm_stderr": 0.03278293022940174,
"mc1": 0.5618115055079559,
"mc1_stderr": 0.01736923616440441,
"mc2": 0.7111801311531581,
"mc2_stderr": 0.01477958957726906
},
"harness|arc:challenge|25": {
"acc": 0.6962457337883959,
"acc_stderr": 0.01343890918477876,
"acc_norm": 0.7175767918088737,
"acc_norm_stderr": 0.013155456884097224
},
"harness|hellaswag|10": {
"acc": 0.7113124875522804,
"acc_stderr": 0.004522262128176996,
"acc_norm": 0.8819956184027086,
"acc_norm_stderr": 0.00321953979050048
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.37,
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}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- 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. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- 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. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- 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. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- 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. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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## Dataset Card Contact
[More Information Needed] |
Xmaster6y/Mixtral-8x400M-v0.1-activations | ---
dataset_info:
features:
- name: activation
sequence: float32
- name: domain
dtype: string
- name: expert
dtype: int64
splits:
- name: model.layers.0
num_bytes: 2682644235
num_examples: 163509
- name: model.layers.1
num_bytes: 2686548772
num_examples: 163747
download_size: 2573049193
dataset_size: 5369193007
configs:
- config_name: default
data_files:
- split: model.layers.0
path: data/model.layers.0-*
- split: model.layers.1
path: data/model.layers.1-*
---
|
tfft/translation_test | ---
dataset_info:
features:
- name: zh
dtype: string
- name: en
dtype: string
splits:
- name: train
num_bytes: 2
num_examples: 2
download_size: 1
dataset_size: 1
task_categories:
- translation
language:
- zh
- en
size_categories:
- 1k
--- |
distilled-one-sec-cv12-each-chunk-uniq/chunk_196 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1109599984.0
num_examples: 216212
download_size: 1134873098
dataset_size: 1109599984.0
---
# Dataset Card for "chunk_196"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Nexdata/13_Modules_Entity_Name_Single_sentence_Annotation_Data | ---
license: cc-by-nc-nd-4.0
---
## Description
13 modules of more than 15,000 piece data collected from different scenes, with annotation on entity name and entity type, rich in content, high in data accuracy.
For more details, please refer to the link: https://www.nexdata.ai/dataset/967?source=Huggingface
# Specifications
## Language
Chinese
## Data Size
13 Modules, 15,900 sentences in total
## Corpus Source
Manual writing
## Annotation Content
Entity name, Entity type
## Data Format
excel
# Licensing Information
Commercial License
|
Vitrola40/roberto90dataset | ---
license: openrail
---
|
systemk/wiki-ja-5k-metrics | ---
dataset_info:
- config_name: dsir-domain
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: tokens
sequence: string
- name: weight
dtype: float32
- name: prob_dists
sequence: float32
splits:
- name: train
num_bytes: 407934862.0
num_examples: 5000
download_size: 45609551
dataset_size: 407934862.0
- config_name: ml-domain
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: similarity
dtype: float32
splits:
- name: train
num_bytes: 25615967.0
num_examples: 5000
download_size: 14602115
dataset_size: 25615967.0
configs:
- config_name: dsir-domain
data_files:
- split: train
path: dsir-domain/train-*
- config_name: ml-domain
data_files:
- split: train
path: ml-domain/train-*
---
|
open-llm-leaderboard/details_HuggingFaceH4__starchat-beta | ---
pretty_name: Evaluation run of HuggingFaceH4/starchat-beta
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_HuggingFaceH4__starchat-beta\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-25T02:34:18.811369](https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__starchat-beta/blob/main/results_2023-10-25T02-34-18.811369.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.004089765100671141,\n\
\ \"em_stderr\": 0.0006535802669912854,\n \"f1\": 0.0753890520134228,\n\
\ \"f1_stderr\": 0.001735962486740498,\n \"acc\": 0.3742380352004251,\n\
\ \"acc_stderr\": 0.00950380770894865\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.004089765100671141,\n \"em_stderr\": 0.0006535802669912854,\n\
\ \"f1\": 0.0753890520134228,\n \"f1_stderr\": 0.001735962486740498\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.05155420773313116,\n \
\ \"acc_stderr\": 0.006090887955262828\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.696921862667719,\n \"acc_stderr\": 0.012916727462634472\n\
\ }\n}\n```"
repo_url: https://huggingface.co/HuggingFaceH4/starchat-beta
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|arc:challenge|25_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_25T02_34_18.811369
path:
- '**/details_harness|drop|3_2023-10-25T02-34-18.811369.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-25T02-34-18.811369.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_25T02_34_18.811369
path:
- '**/details_harness|gsm8k|5_2023-10-25T02-34-18.811369.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-25T02-34-18.811369.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hellaswag|10_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T21:08:27.330071.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T21:08:27.330071.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T21:08:27.330071.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_25T02_34_18.811369
path:
- '**/details_harness|winogrande|5_2023-10-25T02-34-18.811369.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-25T02-34-18.811369.parquet'
- config_name: results
data_files:
- split: 2023_07_19T21_08_27.330071
path:
- results_2023-07-19T21:08:27.330071.parquet
- split: 2023_10_25T02_34_18.811369
path:
- results_2023-10-25T02-34-18.811369.parquet
- split: latest
path:
- results_2023-10-25T02-34-18.811369.parquet
---
# Dataset Card for Evaluation run of HuggingFaceH4/starchat-beta
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/HuggingFaceH4/starchat-beta
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_HuggingFaceH4__starchat-beta",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-25T02:34:18.811369](https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__starchat-beta/blob/main/results_2023-10-25T02-34-18.811369.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.004089765100671141,
"em_stderr": 0.0006535802669912854,
"f1": 0.0753890520134228,
"f1_stderr": 0.001735962486740498,
"acc": 0.3742380352004251,
"acc_stderr": 0.00950380770894865
},
"harness|drop|3": {
"em": 0.004089765100671141,
"em_stderr": 0.0006535802669912854,
"f1": 0.0753890520134228,
"f1_stderr": 0.001735962486740498
},
"harness|gsm8k|5": {
"acc": 0.05155420773313116,
"acc_stderr": 0.006090887955262828
},
"harness|winogrande|5": {
"acc": 0.696921862667719,
"acc_stderr": 0.012916727462634472
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
KenDoStudio/VOCALUNITY_choir | ---
license: artistic-2.0
---
|
Adabs/btcimages | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 12780555510.269602
num_examples: 68277
- name: test
num_bytes: 1421677815.3063977
num_examples: 7587
download_size: 14162186880
dataset_size: 14202233325.576
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
toninsaf/asdasd | ---
license: bigscience-bloom-rail-1.0
---
|
Garlen/WuxiaPub | ---
license: apache-2.0
---
|
open-asr-leaderboard/datasets | ---
annotations_creators:
- expert-generated
- crowdsourced
- machine-generated
language:
- en
language_creators:
- crowdsourced
- expert-generated
license:
- cc-by-4.0
- apache-2.0
- cc0-1.0
- cc-by-nc-3.0
- other
multilinguality:
- monolingual
pretty_name: datasets
size_categories:
- 100K<n<1M
- 1M<n<10M
source_datasets:
- original
- extended|librispeech_asr
- extended|common_voice
tags:
- asr
- benchmark
- speech
- esb
task_categories:
- automatic-speech-recognition
extra_gated_prompt: |-
Three of the ESB datasets have specific terms of usage that must be agreed to before using the data.
To do so, fill in the access forms on the specific datasets' pages:
* Common Voice: https://huggingface.co/datasets/mozilla-foundation/common_voice_9_0
* GigaSpeech: https://huggingface.co/datasets/speechcolab/gigaspeech
* SPGISpeech: https://huggingface.co/datasets/kensho/spgispeech
extra_gated_fields:
I hereby confirm that I have registered on the original Common Voice page and agree to not attempt to determine the identity of speakers in the Common Voice dataset: checkbox
I hereby confirm that I have accepted the terms of usages on GigaSpeech page: checkbox
I hereby confirm that I have accepted the terms of usages on SPGISpeech page: checkbox
---
All eight of datasets in ESB can be downloaded and prepared in just a single line of code through the Hugging Face Datasets library:
```python
from datasets import load_dataset
librispeech = load_dataset("esb/datasets", "librispeech", split="train")
```
- `"esb/datasets"`: the repository namespace. This is fixed for all ESB datasets.
- `"librispeech"`: the dataset name. This can be changed to any of any one of the eight datasets in ESB to download that dataset.
- `split="train"`: the split. Set this to one of train/validation/test to generate a specific split. Omit the `split` argument to generate all splits for a dataset.
The datasets are full prepared, such that the audio and transcription files can be used directly in training/evaluation scripts.
## Dataset Information
A data point can be accessed by indexing the dataset object loaded through `load_dataset`:
```python
print(librispeech[0])
```
A typical data point comprises the path to the audio file and its transcription. Also included is information of the dataset from which the sample derives and a unique identifier name:
```python
{
'dataset': 'librispeech',
'audio': {'path': '/home/sanchit-gandhi/.cache/huggingface/datasets/downloads/extracted/d2da1969fe9e7d06661b5dc370cf2e3c119a14c35950045bcb76243b264e4f01/374-180298-0000.flac',
'array': array([ 7.01904297e-04, 7.32421875e-04, 7.32421875e-04, ...,
-2.74658203e-04, -1.83105469e-04, -3.05175781e-05]),
'sampling_rate': 16000},
'text': 'chapter sixteen i might have told you of the beginning of this liaison in a few lines but i wanted you to see every step by which we came i to agree to whatever marguerite wished',
'id': '374-180298-0000'
}
```
### Data Fields
- `dataset`: name of the ESB dataset from which the sample is taken.
- `audio`: a dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate.
- `text`: the transcription of the audio file.
- `id`: unique id of the data sample.
### Data Preparation
#### Audio
The audio for all ESB datasets is segmented into sample lengths suitable for training ASR systems. The Hugging Face datasets library decodes audio files on the fly, reading the segments and converting them to a Python arrays. Consequently, no further preparation of the audio is required to be used in training/evaluation scripts.
Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, i.e. `dataset[0]["audio"]` should always be preferred over `dataset["audio"][0]`.
#### Transcriptions
The transcriptions corresponding to each audio file are provided in their 'error corrected' format. No transcription pre-processing is applied to the text, only necessary 'error correction' steps such as removing junk tokens (_<unk>_) or converting symbolic punctuation to spelled out form (_<comma>_ to _,_). As such, no further preparation of the transcriptions is required to be used in training/evaluation scripts.
Transcriptions are provided for training and validation splits. The transcriptions are **not** provided for the test splits. ESB requires you to generate predictions for the test sets and upload them to https://huggingface.co/spaces/esb/leaderboard for scoring.
### Access
All eight of the datasets in ESB are accessible and licensing is freely available. Three of the ESB datasets have specific terms of usage that must be agreed to before using the data. To do so, fill in the access forms on the specific datasets' pages:
* Common Voice: https://huggingface.co/datasets/mozilla-foundation/common_voice_9_0
* GigaSpeech: https://huggingface.co/datasets/speechcolab/gigaspeech
* SPGISpeech: https://huggingface.co/datasets/kensho/spgispeech
### Diagnostic Dataset
ESB contains a small, 8h diagnostic dataset of in-domain validation data with newly annotated transcriptions. The audio data is sampled from each of the ESB validation sets, giving a range of different domains and speaking styles. The transcriptions are annotated according to a consistent style guide with two formats: normalised and un-normalised. The dataset is structured in the same way as the ESB dataset, by grouping audio-transcription samples according to the dataset from which they were taken. We encourage participants to use this dataset when evaluating their systems to quickly assess performance on a range of different speech recognition conditions. For more information, visit: [esb/diagnostic-dataset](https://huggingface.co/datasets/esb/diagnostic-dataset).
## Summary of ESB Datasets
| Dataset | Domain | Speaking Style | Train (h) | Dev (h) | Test (h) | Transcriptions | License |
|--------------|-----------------------------|-----------------------|-----------|---------|----------|--------------------|-----------------|
| LibriSpeech | Audiobook | Narrated | 960 | 11 | 11 | Normalised | CC-BY-4.0 |
| Common Voice | Wikipedia | Narrated | 1409 | 27 | 27 | Punctuated & Cased | CC0-1.0 |
| Voxpopuli | European Parliament | Oratory | 523 | 5 | 5 | Punctuated | CC0 |
| TED-LIUM | TED talks | Oratory | 454 | 2 | 3 | Normalised | CC-BY-NC-ND 3.0 |
| GigaSpeech | Audiobook, podcast, YouTube | Narrated, spontaneous | 2500 | 12 | 40 | Punctuated | apache-2.0 |
| SPGISpeech | Fincancial meetings | Oratory, spontaneous | 4900 | 100 | 100 | Punctuated & Cased | User Agreement |
| Earnings-22 | Fincancial meetings | Oratory, spontaneous | 105 | 5 | 5 | Punctuated & Cased | CC-BY-SA-4.0 |
| AMI | Meetings | Spontaneous | 78 | 9 | 9 | Punctuated & Cased | CC-BY-4.0 |
## LibriSpeech
The LibriSpeech corpus is a standard large-scale corpus for assessing ASR systems. It consists of approximately 1,000 hours of narrated audiobooks from the [LibriVox](https://librivox.org) project. It is licensed under CC-BY-4.0.
Example Usage:
```python
librispeech = load_dataset("esb/datasets", "librispeech")
```
Train/validation splits:
- `train` (combination of `train.clean.100`, `train.clean.360` and `train.other.500`)
- `validation.clean`
- `validation.other`
Test splits:
- `test.clean`
- `test.other`
Also available are subsets of the train split, which can be accessed by setting the `subconfig` argument:
```python
librispeech = load_dataset("esb/datasets", "librispeech", subconfig="clean.100")
```
- `clean.100`: 100 hours of training data from the 'clean' subset
- `clean.360`: 360 hours of training data from the 'clean' subset
- `other.500`: 500 hours of training data from the 'other' subset
## Common Voice
Common Voice is a series of crowd-sourced open-licensed speech datasets where speakers record text from Wikipedia in various languages. The speakers are of various nationalities and native languages, with different accents and recording conditions. We use the English subset of version 9.0 (27-4-2022), with approximately 1,400 hours of audio-transcription data. It is licensed under CC0-1.0.
Example usage:
```python
common_voice = load_dataset("esb/datasets", "common_voice", use_auth_token=True)
```
Training/validation splits:
- `train`
- `validation`
Test splits:
- `test`
## VoxPopuli
VoxPopuli is a large-scale multilingual speech corpus consisting of political data sourced from 2009-2020 European Parliament event recordings. The English subset contains approximately 550 hours of speech largely from non-native English speakers. It is licensed under CC0.
Example usage:
```python
voxpopuli = load_dataset("esb/datasets", "voxpopuli")
```
Training/validation splits:
- `train`
- `validation`
Test splits:
- `test`
## TED-LIUM
TED-LIUM consists of English-language TED Talk conference videos covering a range of different cultural, political, and academic topics. It contains approximately 450 hours of transcribed speech data. It is licensed under CC-BY-NC-ND 3.0.
Example usage:
```python
tedlium = load_dataset("esb/datasets", "tedlium")
```
Training/validation splits:
- `train`
- `validation`
Test splits:
- `test`
## GigaSpeech
GigaSpeech is a multi-domain English speech recognition corpus created from audiobooks, podcasts and YouTube. We provide the large train set (2,500 hours) and the standard validation and test splits. It is licensed under apache-2.0.
Example usage:
```python
gigaspeech = load_dataset("esb/datasets", "gigaspeech", use_auth_token=True)
```
Training/validation splits:
- `train` (`l` subset of training data (2,500 h))
- `validation`
Test splits:
- `test`
Also available are subsets of the train split, which can be accessed by setting the `subconfig` argument:
```python
gigaspeech = load_dataset("esb/datasets", "spgispeech", subconfig="xs", use_auth_token=True)
```
- `xs`: extra-small subset of training data (10 h)
- `s`: small subset of training data (250 h)
- `m`: medium subset of training data (1,000 h)
- `xl`: extra-large subset of training data (10,000 h)
## SPGISpeech
SPGISpeech consists of company earnings calls that have been manually transcribed by S&P Global, Inc according to a professional style guide. We provide the large train set (5,000 hours) and the standard validation and test splits. It is licensed under a Kensho user agreement.
Loading the dataset requires authorization.
Example usage:
```python
spgispeech = load_dataset("esb/datasets", "spgispeech", use_auth_token=True)
```
Training/validation splits:
- `train` (`l` subset of training data (~5,000 h))
- `validation`
Test splits:
- `test`
Also available are subsets of the train split, which can be accessed by setting the `subconfig` argument:
```python
spgispeech = load_dataset("esb/datasets", "spgispeech", subconfig="s", use_auth_token=True)
```
- `s`: small subset of training data (~200 h)
- `m`: medium subset of training data (~1,000 h)
## Earnings-22
Earnings-22 is a 119-hour corpus of English-language earnings calls collected from global companies, with speakers of many different nationalities and accents. It is licensed under CC-BY-SA-4.0.
Example usage:
```python
earnings22 = load_dataset("esb/datasets", "earnings22")
```
Training/validation splits:
- `train`
- `validation`
Test splits:
- `test`
## AMI
The AMI Meeting Corpus consists of 100 hours of meeting recordings from multiple recording devices synced to a common timeline. It is licensed under CC-BY-4.0.
Example usage:
```python
ami = load_dataset("esb/datasets", "ami")
```
Training/validation splits:
- `train`
- `validation`
Test splits:
- `test` |
distilled-from-one-sec-cv12/chunk_83 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1319160072
num_examples: 257046
download_size: 1339318141
dataset_size: 1319160072
---
# Dataset Card for "chunk_83"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
FINNUMBER/FINCH_TRAIN_NQA_300_per100 | ---
dataset_info:
features:
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configs:
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---
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/19e97e42 | ---
dataset_info:
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download_size: 1337
dataset_size: 184
---
# Dataset Card for "19e97e42"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
sshreyy/main_classify_adhoora | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
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dtype: string
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num_examples: 102
download_size: 115226
dataset_size: 808543
---
# Dataset Card for "main_classify_adhoora"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
snipaid/instruct-snippet-mlsum-v2 | ---
license: mit
language: de
tags:
- news
- headline generation
- teaser generation
- keyword generation
- summarization
- tweet generation
- serp generation
- news snippet generation
size_categories:
- 1K<n<10K
task_categories:
- summarization
- text2text-generation
pretty_name: Instruct-Snippet-MLSUM-500-V2
---
# Dataset Card for Instruct-Snippet-MLSUM-500-V2
### Dataset Summary
This is a dataset for multitask instruction finetuning dataset for the task of news snippet generation. It is built from a sample of ~500 news articles from the [MLSUM](https://huggingface.co/datasets/mlsum) dataset, augmented with machine generated news snippets.
### Supported Tasks
This dataset was created to support the task of generating news snippets such as title, teaser, summary, keywords, serp and tweet for news articles in German language.
### Languages
de - German
## Dataset Structure
lable: a string feature.
instruction: a string feature.
input: a string feature.
output: a string feature.
## Dataset Creation
This dataset was created from Snippet-MLSUM-500-V2. See [Snippet-MLSUM-500-V2](https://huggingface.co/datasets/snipaid/snippet-mlsum-500-V2) for the dataset without instructions.
Instructions were generated with GPT-3.5 from a human-curated seed-set of instructions.
## Considerations for Using the Data
### Known Limitations
Part of the snippet data is machine generated. Be aware that these features (specifically: output) may exhibit signs of model hallucination, toxicity and stereotypes.
## Additional Information
### Licensing Information
This dataset is licensed under MIT license. |
ChristianMD/ATCV1 | ---
license: mit
---
|
erytrn/turkishReviews-ds-mini2 | ---
dataset_info:
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dataset_size: 1392332.0
---
# Dataset Card for "turkishReviews-ds-mini2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
iamnguyen/law_qa | ---
dataset_info:
features:
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dtype: string
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configs:
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path: data/train-*
---
|
lpallaras/CUAD | ---
license: apache-2.0
---
|
johannes-garstenauer/ENN_masking_embeddings_dim_1 | ---
dataset_info:
features:
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sequence: float32
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dtype: int64
splits:
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num_bytes: 1076352
num_examples: 67272
download_size: 400482
dataset_size: 1076352
---
# Dataset Card for "ENN_masking_embeddings_dim_1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
BirdL/DALL-E-Dogs | ---
annotations_creators: []
language: []
language_creators: []
license:
- other
multilinguality: []
pretty_name: DALL-E Cats Dataset
size_categories:
- 1K<n<10K
source_datasets: []
tags: []
task_categories:
- image-classification
- unconditional-image-generation
task_ids: []
---
DALL-E-Dogs is a dataset meant to produce a synthetic animal dataset. This is a precursor to DALL-E-Cats. DALL-E-Dogs and DALL-E-Cats will be fed into an image classifier to see how it performs. This is under the [BirdL-AirL License.](https://huggingface.co/spaces/BirdL/license/) |
Lolimorimorf/dataset_test_propaganda_opposition | ---
dataset_info:
features:
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dataset_size: 2554773
configs:
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data_files:
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path: data/train-*
---
|
taldarim/pc | ---
dataset_info:
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dataset_size: 95159
---
# Dataset Card for "pc"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ashabrawy/dia_wikilingua | ---
configs:
- config_name: aus
data_files:
- path: AUS/train.csv
split: train
- path: AUS/validation.csv
split: validation
- path: AUS/test.csv
split: test
- config_name: col
data_files:
- path: COL/train.csv
split: train
- path: COL/validation.csv
split: validation
- path: COL/test.csv
split: test
- config_name: hon
data_files:
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split: train
- path: HON/validation.csv
split: validation
- path: HON/test.csv
split: test
- config_name: nig
data_files:
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split: train
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split: validation
- path: NIG/test.csv
split: test
- config_name: wel
data_files:
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split: train
- path: WEL/validation.csv
split: validation
- path: WEL/test.csv
split: test
---
|
liuyanchen1015/MULTI_VALUE_qqp_possessives_for_pre | ---
dataset_info:
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---
# Dataset Card for "MULTI_VALUE_qqp_possessives_for_pre"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ibivibiv/alpaca_tiny1 | ---
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---
|
teamtom/25000_word_emb_large | ---
license: apache-2.0
---
model: https://huggingface.co/sentence-transformers/clip-ViT-L-14 # 1.71GB |
benayas/snips_llm_v5 | ---
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path: data/test-*
---
|
skyerx/MedResearcher | ---
license: openrail
task_categories:
- text-classification
- question-answering
- summarization
- text-generation
- text2text-generation
language:
- en
--- |
MikeGreen2710/data_mlm_listing_sanitized | ---
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---
|
tyzhu/squad_qa_wrong_rare_v5_full_recite_full_passage_random_permute_rerun_2 | ---
configs:
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---
# Dataset Card for "squad_qa_wrong_rare_v5_full_recite_full_passage_random_permute_rerun_2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
pranjal01/Text-summarizer-dataset | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
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dataset_size: 1416116
license: apache-2.0
task_categories:
- text-generation
language:
- en
---
# Dataset Card for "Text-summarizer-dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
as-cle-bert/scerevisiae-transcripts-biotypes | ---
license: mit
dataset_info:
features:
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dtype:
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names:
'0': pseudogene
'1': Uncharacterized_ORF
'2': transposable_element_gene
'3': Verified_ORF
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configs:
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data_files:
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path: data/train-*
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path: data/test-*
---
|
Heng666/Traditional_Chinese-aya_collection | ---
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configs:
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data_files:
- split: train
path: aya_dataset/train-*
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data_files:
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path: templated_ntx_llm/train-*
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data_files:
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path: templated_uner_llm/train-*
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path: templated_uner_llm/test-*
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path: templated_uner_llm/validation-*
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path: templated_xcsqa/validation-*
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path: templated_xlel_wd/train-*
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path: templated_xlel_wd/test-*
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path: templated_xlel_wd/validation-*
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data_files:
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path: templated_xwikis/train-*
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path: templated_xwikis/test-*
- split: validation
path: templated_xwikis/validation-*
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data_files:
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path: translated_adversarial_qa/train-*
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path: translated_adversarial_qa/test-*
- split: validation
path: translated_adversarial_qa/validation-*
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data_files:
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path: translated_cnn_dailymail/train-*
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path: translated_cnn_dailymail/test-*
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path: translated_cnn_dailymail/validation-*
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data_files:
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path: translated_dolly/train-*
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data_files:
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path: translated_flan_coqa/train-*
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path: translated_flan_cot/train-*
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data_files:
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path: translated_flan_gem_wiki/train-*
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data_files:
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path: translated_flan_lambada/train-*
- config_name: translated_flan_qa
data_files:
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path: translated_flan_qa/train-*
- config_name: translated_hotpotqa
data_files:
- split: train
path: translated_hotpotqa/train-*
- config_name: translated_joke_explaination
data_files:
- split: train
path: translated_joke_explaination/train-*
- config_name: translated_mintaka
data_files:
- split: train
path: translated_mintaka/train-*
- split: test
path: translated_mintaka/test-*
- split: validation
path: translated_mintaka/validation-*
- config_name: translated_mlqa
data_files:
- split: test
path: translated_mlqa/test-*
- split: validation
path: translated_mlqa/validation-*
- config_name: translated_nqopen
data_files:
- split: train
path: translated_nqopen/train-*
- config_name: translated_paws
data_files:
- split: train
path: translated_paws/train-*
- split: test
path: translated_paws/test-*
- split: validation
path: translated_paws/validation-*
- config_name: translated_piqa
data_files:
- split: train
path: translated_piqa/train-*
- config_name: translated_wikiqa
data_files:
- split: train
path: translated_wikiqa/train-*
- split: test
path: translated_wikiqa/test-*
- split: validation
path: translated_wikiqa/validation-*
license: apache-2.0
task_categories:
- question-answering
- translation
- summarization
- zero-shot-classification
language:
- zh
pretty_name: ' Traditional_Chinese-aya_collection'
size_categories:
- 1M<n<10M
---
<!-- Provide a quick summary of the dataset. -->
## 資料集描述
**繁體中文 Aya (Traditional Chinese Aya Chinese;TCA)：專注於繁體中文處理的 Aya 集合的精選子集**
### 概述
`繁體中文 Aya` 是一個精心策劃的資料集，源自 [CohereForAI](https://huggingface.co/CohereForAI) 的綜合 Aya 集合，特別關注繁體中文文本資料。
此資料集結合了來自 [CohereForAI/aya_collection](https://huggingface.co/datasets/CohereForAI/aya_collection)，過濾掉除繁體中文、簡體中文內容之外的所有內容。
### 目標
`繁體中文 Aya` 的目標是為研究人員、技術專家和語言學家提供即用型繁體中文文本資源，顯著減少專注於繁體中文的 NLP 和 AI 專案中數據預處理所需的時間和精力。
### 資料集來源與資訊
- **資料來源**: 從 [CohereForAI/aya_collection](https://huggingface.co/datasets/CohereForAI/aya_collection) 64 個子集而來。
- **語言**: 繁體中文、簡體中文（'zho')
- **應用**: 非常適合語言建模、文本分類、情感分析、和機器翻譯等任務。
- **論文連結:** [2402.06619](https://huggingface.co/papers/2402.06619)
- **維護人:** [Heng666](https://huggingface.co/Heng666)
- **License:** Apache-2.0
### 使用方法
此資料集是開始繁體中文語言專案（從學術研究到商業應用）的基礎工具。
透過提供預先過濾的繁體中文文本來源，`繁體中文 Aya` 讓研究人員、技術專家和開發人員能夠直接進行模型訓練、分析和應用程式開發，而無需進行資料清理和語言過濾的初步麻煩。
展示範例
```python
from datasets import load_dataset
dataset = load_dataset("Heng666/Traditional_Chinese-aya_collection", "aya_dataset")
```
在上面的程式碼片段中，「aya_dataset」指的是原始 「aya_collection」中「aya_dataset」子集的繁體中文版本（100k行）。
您可以透過在載入資料集時指定其名稱來載入其他子集。
### 訪問和貢獻
可在 [Heng666/Traditional_Chinese-aya_collection](https://huggingface.co/datasets/Heng666/Traditional_Chinese-aya_collection) 下的 Hugging Face Hub 上獲取，
`繁體中文 Aya` 邀請社區做出貢獻。鼓勵用戶提供回饋、提出改進建議。
### 支持與合作
我們致力於圍繞繁體中文人工智慧和 NLP 研究創造一個包容和支持的環境。如需支援、協作或有關資料集的疑問，請透過 Hugging Face Hub 的討論部分進行聯絡。
# Original Dataset Card of Aya by CohereForAI
# Dataset Summary
The Aya Collection is a massive multilingual collection consisting of 513 million instances of prompts and completions covering a wide range of tasks.
This collection incorporates instruction-style templates from fluent speakers and applies them to a curated list of datasets, as well as translations of instruction-style datasets into 101 languages. Aya Dataset, a human-curated multilingual instruction and response dataset, is also part of this collection. See our paper for more details regarding the collection.
- **Curated by:** Contributors of [Aya Open Science Intiative](https://cohere.com/research/aya)
- **Language(s):** 115 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.|
| [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 Collection` is a comprehensive, large corpus of datasets that can be used by researchers around the world to train multilingual models. Our goal is only to include datasets with permissive licensing for manipulation and redistribution.
The `Aya Collection` consists of three different sources of data:
1. Templated data: We collaborated with fluent speakers to create templates that allowed for the automatic expansion of existing datasets into various languages.
2. Translated data: We translated a hand-selected subset of 19 datasets into 101 languages (114 dialects) using the NLLB 3.3B parameter machine translation model.
3. Aya Dataset: We release the [Aya Dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) as a subset of the overall collection. This is the only dataset in the collection that is human-annotated in its entirety.
## 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/aya_collection", "templated_mintaka")
```
In the above code snippet, "templated_mintaka" refers to a subset of the aya_collection. You can load other subsets by specifying its name at the time of loading the dataset.
## Data Instances
An example of a `train` instance looks as follows:
```json
{'id': 246001,
'inputs': 'The following query in English is taken from the geography category. What could be the answer to the question?\nWhat is the seventh tallest mountain in North America?',
'targets': 'The answer is Mount Lucania.',
'dataset_name': 'Mintaka-inst',
'sub_dataset_name': '-',
'task_type': 'question-answering',
'template_id': 3,
'language': 'eng',
'split': 'train',
'script': 'Latn'
}
```
## Data Fields
The data fields are the same among all splits:
- `id:` Unique id of the data point
- `inputs:` Prompt or input to the language model.
- `targets:` Completion or output of the language model.
- `dataset_name:` The name of the source dataset that the data point was taken from
- `sub_dataset_name:` If the source is a collection, this field indicates which part of that collection the data point was taken from. If it is not a collection, this field is left blank.
- `task_type:` The task type that this conversation belongs to.
- `template_id`: The id of the template applied to this data point.
- `language:` The ISO code of the dialect of the conversation.
- `script:` The script of the language.
- `split:` Indicates whether the data point is part of the `train` or the `test` split.
### Statistics
The total number of data points, including the Aya Dataset` is 513,758,189. To view the breakdown of dialect codes and the respective templated and translated data point counts in the Aya Collection , refer to the toggled table below.
<details>
<summary> <b> Breakdown of Aya Collection data point counts grouped by dialects </b> </summary>
|dialect code|language|translated data point count|templated data point count|total count |
|------------|--------|---------------------------|--------------------------|---------------|
|ace |Achinese|8240684 |2000 |8242684 |
|acm |Arabic |4120342 |0 |4120342 |
|acq |Arabic |4120342 |0 |4120342 |
|aeb |Arabic |4120342 |0 |4120342 |
|afr |Afrikaans|4120342 |6108 |4126450 |
|ajp |Arabic |4120342 |0 |4120342 |
|als |Albanian|4120342 |0 |4120342 |
|amh |Amharic |4120342 |25327 |4145669 |
|apc |Arabic |4120342 |0 |4120342 |
|arb |Arabic |6424999 |216430 |6641429 |
|ars |Arabic |4120342 |0 |4120342 |
|ary |Arabic |4120342 |18076 |4138418 |
|arz |Arabic |4120342 |0 |4120342 |
|azb |Azerbaijani|4120342 |0 |4120342 |
|azj |Azerbaijani|4120342 |0 |4120342 |
|bel |Belarusian|4120342 |21273 |4141615 |
|ben |Bengali |4120342 |30661 |4151003 |
|bjn |Banjar |8240684 |2000 |8242684 |
|bul |Bulgarian|4120342 |37722 |4158064 |
|cat |Catalan |4120342 |66900 |4187242 |
|ceb |Cebuano |4120342 |0 |4120342 |
|ces |Czech |4120342 |179604 |4299946 |
|ckb |Kurdish |4120342 |0 |4120342 |
|cym |Welsh |4120342 |0 |4120342 |
|dan |Danish |4120342 |36310 |4156652 |
|deu |German |4120342 |1326722 |5447064 |
|ell |Greek |4120342 |40291 |4160633 |
|eng |English |9771427 |8066678 |17838105 |
|epo |Esperanto|4120342 |0 |4120342 |
|est |Estonian|4120342 |0 |4120342 |
|eus |Basque |4120342 |0 |4120342 |
|fin |Finnish |4120342 |457895 |4578237 |
|fra |French |4120342 |835520 |4955862 |
|gla |Scottish Gaelic|4120342 |0 |4120342 |
|gle |Irish |4120342 |0 |4120342 |
|glg |Galician|4120342 |0 |4120342 |
|guj |Gujarati|4120342 |2157 |4122499 |
|hat |Haitian Creole|4120342 |0 |4120342 |
|hau |Hausa |4120342 |51396 |4171738 |
|heb |Hebrew |4120342 |103466 |4223808 |
|hin |Hindi |4120342 |260387 |4380729 |
|hun |Hungarian|4120342 |82039 |4202381 |
|hye |Armenian|4120342 |7080 |4127422 |
|ibo |Igbo |4120342 |36312 |4156654 |
|ind |Indonesian|4120342 |45709 |4166051 |
|isl |Icelandic|4120342 |0 |4120342 |
|ita |Italian |4120342 |405682 |4526024 |
|jav |Javanese|4120342 |829 |4121171 |
|jpn |Japanese|4120342 |2693177 |6813519 |
|kan |Kannada |4120342 |1156 |4121498 |
|kas |Kashmiri|4120342 |0 |4120342 |
|kat |Georgian|4120342 |0 |4120342 |
|kaz |Kazakh |4120342 |0 |4120342 |
|khk |Mongolian|4120342 |0 |4120342 |
|khm |Khmer |4120342 |0 |4120342 |
|kir |Kyrgyz |4120342 |0 |4120342 |
|kmr |Kurdish |4120342 |0 |4120342 |
|knc |Kanuri |8240684 |0 |8240684 |
|kor |Korean |4120342 |41011 |4161353 |
|lao |Lao |4120342 |0 |4120342 |
|lit |Lithuanian|4120342 |0 |4120342 |
|ltz |Luxembourgish|4120342 |0 |4120342 |
|lvs |Latvian |4120342 |0 |4120342 |
|mal |Malayalam|4120342 |4347 |4124689 |
|mar |Marathi |4120342 |3678 |4124020 |
|min |Minangkabau|6753788 |2000 |6755788 |
|mkd |Macedonian|4120342 |0 |4120342 |
|mlt |Maltese |4120342 |0 |4120342 |
|mni |Manipuri|4120342 |0 |4120342 |
|mri |Maori |4120342 |0 |4120342 |
|mya |Burmese |4120342 |0 |4120342 |
|nld |Dutch |4120342 |220181 |4340523 |
|nno |Norwegian|4120342 |0 |4120342 |
|nob |Norwegian|4120342 |0 |4120342 |
|npi |Nepali |4120342 |0 |4120342 |
|nso |Northern Sotho|4120342 |0 |4120342 |
|pbt |Pashto |4120342 |0 |4120342 |
|pes |Persian |4120342 |245520 |4365862 |
|plt |Malagasy|4120342 |0 |4120342 |
|pol |Polish |4120342 |332503 |4452845 |
|por |Portuguese|4120342 |287432 |4407774 |
|ron |Romanian|4120342 |36359 |4156701 |
|rus |Russian |4120342 |545920 |4666262 |
|sin |Sinhala |4120342 |195 |4120537 |
|slk |Slovak |4120342 |27845 |4148187 |
|slv |Slovenian|4120342 |25731 |4146073 |
|smo |Samoan |4120342 |0 |4120342 |
|sna |Shona |4120342 |3684 |4124026 |
|snd |Sindhi |4120342 |0 |4120342 |
|som |Somali |4120342 |2926 |4123268 |
|sot |Southern Sotho|4120342 |0 |4120342 |
|spa |Spanish |4120342 |379194 |4499536 |
|srp |Serbian |4120342 |77124 |4197466 |
|sun |Sundanese|4120342 |2208 |4122550 |
|swe |Swedish |4120342 |76486 |4196828 |
|swh |Swahili |4120342 |12726 |4133068 |
|tam |Tamil |4120342 |11462 |4131804 |
|taq |Tamasheq|4120342 |0 |4120342 |
|tel |Telugu |4120342 |477821 |4598163 |
|tgk |Tajik |4120342 |0 |4120342 |
|tha |Thai |4120342 |2125180 |6245522 |
|tur |Turkish |4120342 |59932 |4180274 |
|ukr |Ukrainian|4120342 |189384 |4309726 |
|urd |Urdu |4120342 |337739 |4458081 |
|uzn |Uzbek |4120342 |0 |4120342 |
|vie |Vietnamese|4120342 |42232 |4162574 |
|xho |Xhosa |4120342 |2952 |4123294 |
|ydd |Yiddish |4120342 |0 |4120342 |
|yor |Yoruba |4120342 |4907 |4125249 |
|yue |Chinese |4120342 |0 |4120342 |
|zho-Hans |Chinese |4120342 |54528 |4174870 |
|zho-Hant |Chinese |4120342 |0 |4120342 |
|zsm |Malay |4120342 |13950 |4134292 |
|zul |Zulu |4120342 |786 |4121128 |
|arq |Arabic |0 |6046 |6046 |
|ban |Balinese|0 |2000 |2000 |
|bbc |Toba Batak|0 |2000 |2000 |
|bem |Bemba |0 |776 |776 |
|fil |Filipino|0 |220 |220 |
|fon |Fon |0 |845 |845 |
|hrv |Croatian|0 |9007 |9007 |
|kin |Kinyarwanda|0 |11165 |11165 |
|lij |Ligurian|0 |6409 |6409 |
|mad |Madurese|0 |2000 |2000 |
|nij |Ngaju |0 |2000 |2000 |
|nor |Norwegian|0 |72352 |72352 |
|pan |Punjabi |0 |2156 |2156 |
|twi |Twi |0 |10840 |10840 |
|wol |Wolof |0 |785 |785 |
|zho |Chinese |0 |74972 |74972 |
PS: Templated data also includes Mozambican Portuguese, which doesn't have its own ISO language code.
</details>
<br>
# Motivations & Intentions
- **Curation Rationale:** Automatic augmentation of existing datasets serves to enhance the available linguistic resources for multiple languages. The list of languages was initially established from mT5 and aligned with the annotators’ language list and NLLB translation model. The datasets were translated directly from English for all languages.
# Additional Information
## Provenance
- **Methods Used:** A combination of crowd-sourced templating and automatic translation was employed to source this dataset.
- **Methodology Details:**
- *Source:* Existing NLP datasets
- *Dates of Collection:* May 2023 - Dec 2023
## Dataset Version and Maintenance
- **Maintenance Status:** Actively Maintained
- **Version Details:**
- *Current version:* 1.0
- *Last Update:* 02/2024
- *First Release:* 02/2024
## 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](https://opensource.org/license/apache-2-0) License.
## Citation Information
```bibtex
@misc{singh2024aya,
title={Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning},
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},
year={2024},
eprint={2402.06619},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
|
melisagunawan17/Milestone2Deployment | ---
license: apache-2.0
---
|
fujiki/japanese_alpaca_data | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 24733874
num_examples: 52002
download_size: 13849623
dataset_size: 24733874
license: cc-by-nc-sa-4.0
language:
- ja
pretty_name: japanese_alpaca
---
# Dataset Card for "japanese_alpaca_data"
- This dataset is based on `masa3141`'s great work on `japanese-alpaca-lora` [[github]](https://github.com/masa3141/japanese-alpaca-lora). Please also refer to this repo.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
roborovski/synthetic-tool-calls-v2-dpo-pairs | ---
dataset_info:
features:
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dtype: string
- name: question
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splits:
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num_bytes: 8899909
num_examples: 8005
download_size: 2104590
dataset_size: 8899909
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Heng666/MultiCCAligned-TW-Corpus | ---
language:
- tw
- en
- ja
- ko
- id
- vi
- th
- zh
license: mit
size_categories:
- 1M<n<10M
task_categories:
- translation
pretty_name: MultiCCAligned-TW-Corpus
dataset_info:
- config_name: en-zh_TW
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configs:
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path: en-zh_TW/train-*
- config_name: id-zh_TW
data_files:
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path: id-zh_TW/train-*
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data_files:
- split: train
path: ja-zh_TW/train-*
- config_name: ko-zh_TW
data_files:
- split: train
path: ko-zh_TW/train-*
- config_name: th-zh_TW
data_files:
- split: train
path: th-zh_TW/train-*
- config_name: vi-zh_TW
data_files:
- split: train
path: vi-zh_TW/train-*
tags:
- MultiCCAligned
- translation
- OPUS
---
# Dataset Card for [MultiCCAligned-TW-Corpus]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:** [Heng-Shiou Sheu](mailto:hengshiousheu@gmail.com)
### Dataset Summary
MultiCCAligned-TW-Corpus 是一個機器翻譯基準的多語言資料集，源自 [OPUS](https://opus.nlpl.eu/MultiCCAligned/zh-TW&th/v1.1/MultiCCAligned) 收集的使用者貢獻的翻譯，並由 [OPUS](https://opus.nlpl.eu/)。該資料集包括按語言對排序的測試和開發資料。它包括數百種語言對的測試集，並且不斷更新。請檢查版本號標籤以引用您正在使用的版本。
### Supported Tasks and Leaderboards
### Languages
此資料集涵蓋數百種語言和語言對，並按 ISO-639-1 語言組織。目前版本涵蓋以下語言。繁體中文、英文、日文、韓文、印尼文、越南文、泰文
## Dataset Structure
### Data Instances
資料以 , 分隔檔案中內容，具有三個欄位：指示、輸入和輸出。請注意，我們並不暗示平移方向，並認為資料集是對稱的並用作兩個方向的測試集。
### Data Splits
先整理出 Train 資料。
## Dataset Creation
### Curation Rationale
本資料集將持續更新，未來將公開發佈於 Github 當中。高語言覆蓋率是本計畫的主要目標，資料集的準備與標準化語言標籤和分發格式保持一致和系統化。
### Source Data
#### Initial Data Collection and Normalization
MultiCCAligned 資料集是從根據 68 個 Commoncrawl 快照創建的（截至 2020 年 3 月）。根據標點符號將文件分割成句子，並執行重複資料刪除。語料庫的準備工作並沒有提出任何智慧財產權主張。原始發行版可從 http://www.statmt.org/cc-aligned/ 取得
#### Who are the source language producers?
這些轉錄本已由 [EMNLP'20 作者群](https://www.aclweb.org/anthology/2020.emnlp-main.480.pdf)製作。
### Personal and Sensitive Information
有關處理個人資訊和敏感資訊的信息，我們請諮詢資料的[原始提供者](https://www.aclweb.org/anthology/2020.emnlp-main.480.pdf)。該資料集未經過任何方式處理以檢測或刪除潛在的敏感資訊或個人資訊。
### Social Impact of Dataset
語言覆蓋率很高，因此它代表了機器翻譯開發的非常有價值的資源，特別是對於資源較少的語言和語言對。不斷成長的資料庫也代表著一種動態資源，其價值將進一步成長。
### Other Known Limitations
這些句子通常很短，因此很容易翻譯。對於高資源語言，這會導致結果不如更具挑戰性的基準有用。對於資源較少的語言對來說，即使在非常具有挑戰性的設定中，範例的有限複雜性實際上也是衡量進度的一件好事。
### Dataset Curators
此資料集由Heng-Shiou Sheu 製作。
### Licensing Information
這些資料集沒使用 License.
### Citation Information
```
@inproceedings{Heng666/MultiCCAligned-TW-Corpus,
title={Taiwanese Phrases Multilingual Translation Dataset from MultiCCAligned Talks},
author={Heng-Shiou Sheu},
year={2024},
url={https://huggingface.co/datasets/Heng666/MultiCCAligned-TW-Corpus},
}
``` |
mask-distilled-one-sec-cv12/chunk_29 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 865894600
num_examples: 170050
download_size: 883413488
dataset_size: 865894600
---
# Dataset Card for "chunk_29"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_Josephgflowers__Tinyllama-Cinder-1.3B-Reason-Test.2 | ---
pretty_name: Evaluation run of Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test.2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test.2](https://huggingface.co/Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test.2)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Josephgflowers__Tinyllama-Cinder-1.3B-Reason-Test.2\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-29T01:07:57.572756](https://huggingface.co/datasets/open-llm-leaderboard/details_Josephgflowers__Tinyllama-Cinder-1.3B-Reason-Test.2/blob/main/results_2024-01-29T01-07-57.572756.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.251327576424007,\n\
\ \"acc_stderr\": 0.030372163539921712,\n \"acc_norm\": 0.251062888632938,\n\
\ \"acc_norm_stderr\": 0.03108831080407431,\n \"mc1\": 0.24357405140758873,\n\
\ \"mc1_stderr\": 0.015026354824910782,\n \"mc2\": 0.3899721945335931,\n\
\ \"mc2_stderr\": 0.014222197893576758\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.2977815699658703,\n \"acc_stderr\": 0.013363080107244487,\n\
\ \"acc_norm\": 0.32764505119453924,\n \"acc_norm_stderr\": 0.013715847940719346\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4402509460266879,\n\
\ \"acc_stderr\": 0.004954026775425775,\n \"acc_norm\": 0.5826528579964151,\n\
\ \"acc_norm_stderr\": 0.00492113386493189\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \
\ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.21481481481481482,\n\
\ \"acc_stderr\": 0.035478541985608236,\n \"acc_norm\": 0.21481481481481482,\n\
\ \"acc_norm_stderr\": 0.035478541985608236\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.17763157894736842,\n \"acc_stderr\": 0.031103182383123398,\n\
\ \"acc_norm\": 0.17763157894736842,\n \"acc_norm_stderr\": 0.031103182383123398\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.31,\n\
\ \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.31,\n \
\ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.2490566037735849,\n \"acc_stderr\": 0.02661648298050171,\n\
\ \"acc_norm\": 0.2490566037735849,\n \"acc_norm_stderr\": 0.02661648298050171\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.22916666666666666,\n\
\ \"acc_stderr\": 0.035146974678623884,\n \"acc_norm\": 0.22916666666666666,\n\
\ \"acc_norm_stderr\": 0.035146974678623884\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.23,\n \"acc_stderr\": 0.042295258468165085,\n \
\ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.042295258468165085\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.2,\n \"acc_stderr\": 0.04020151261036846,\n \"acc_norm\"\
: 0.2,\n \"acc_norm_stderr\": 0.04020151261036846\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932269,\n \
\ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932269\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.21965317919075145,\n\
\ \"acc_stderr\": 0.031568093627031744,\n \"acc_norm\": 0.21965317919075145,\n\
\ \"acc_norm_stderr\": 0.031568093627031744\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.1568627450980392,\n \"acc_stderr\": 0.036186648199362466,\n\
\ \"acc_norm\": 0.1568627450980392,\n \"acc_norm_stderr\": 0.036186648199362466\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.19,\n \"acc_stderr\": 0.039427724440366234,\n \"acc_norm\": 0.19,\n\
\ \"acc_norm_stderr\": 0.039427724440366234\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.25957446808510637,\n \"acc_stderr\": 0.02865917937429232,\n\
\ \"acc_norm\": 0.25957446808510637,\n \"acc_norm_stderr\": 0.02865917937429232\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2631578947368421,\n\
\ \"acc_stderr\": 0.0414243971948936,\n \"acc_norm\": 0.2631578947368421,\n\
\ \"acc_norm_stderr\": 0.0414243971948936\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.25517241379310346,\n \"acc_stderr\": 0.03632984052707842,\n\
\ \"acc_norm\": 0.25517241379310346,\n \"acc_norm_stderr\": 0.03632984052707842\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.25925925925925924,\n \"acc_stderr\": 0.022569897074918417,\n \"\
acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.022569897074918417\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2698412698412698,\n\
\ \"acc_stderr\": 0.039701582732351734,\n \"acc_norm\": 0.2698412698412698,\n\
\ \"acc_norm_stderr\": 0.039701582732351734\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.14,\n \"acc_stderr\": 0.0348735088019777,\n \
\ \"acc_norm\": 0.14,\n \"acc_norm_stderr\": 0.0348735088019777\n },\n\
\ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.2870967741935484,\n\
\ \"acc_stderr\": 0.025736542745594525,\n \"acc_norm\": 0.2870967741935484,\n\
\ \"acc_norm_stderr\": 0.025736542745594525\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.270935960591133,\n \"acc_stderr\": 0.031270907132977,\n\
\ \"acc_norm\": 0.270935960591133,\n \"acc_norm_stderr\": 0.031270907132977\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \"acc_norm\"\
: 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.28484848484848485,\n \"acc_stderr\": 0.035243908445117836,\n\
\ \"acc_norm\": 0.28484848484848485,\n \"acc_norm_stderr\": 0.035243908445117836\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.18181818181818182,\n \"acc_stderr\": 0.02747960301053878,\n \"\
acc_norm\": 0.18181818181818182,\n \"acc_norm_stderr\": 0.02747960301053878\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.23316062176165803,\n \"acc_stderr\": 0.03051611137147601,\n\
\ \"acc_norm\": 0.23316062176165803,\n \"acc_norm_stderr\": 0.03051611137147601\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.2846153846153846,\n \"acc_stderr\": 0.022878322799706283,\n\
\ \"acc_norm\": 0.2846153846153846,\n \"acc_norm_stderr\": 0.022878322799706283\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.24074074074074073,\n \"acc_stderr\": 0.026067159222275784,\n \
\ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.026067159222275784\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.21428571428571427,\n \"acc_stderr\": 0.02665353159671548,\n\
\ \"acc_norm\": 0.21428571428571427,\n \"acc_norm_stderr\": 0.02665353159671548\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.2052980132450331,\n \"acc_stderr\": 0.03297986648473834,\n \"\
acc_norm\": 0.2052980132450331,\n \"acc_norm_stderr\": 0.03297986648473834\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.22385321100917432,\n \"acc_stderr\": 0.01787121776779022,\n \"\
acc_norm\": 0.22385321100917432,\n \"acc_norm_stderr\": 0.01787121776779022\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.4074074074074074,\n \"acc_stderr\": 0.033509916046960436,\n \"\
acc_norm\": 0.4074074074074074,\n \"acc_norm_stderr\": 0.033509916046960436\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.24509803921568626,\n \"acc_stderr\": 0.030190282453501954,\n \"\
acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.030190282453501954\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.29535864978902954,\n \"acc_stderr\": 0.02969633871342288,\n \
\ \"acc_norm\": 0.29535864978902954,\n \"acc_norm_stderr\": 0.02969633871342288\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.35874439461883406,\n\
\ \"acc_stderr\": 0.032190792004199956,\n \"acc_norm\": 0.35874439461883406,\n\
\ \"acc_norm_stderr\": 0.032190792004199956\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.20610687022900764,\n \"acc_stderr\": 0.03547771004159463,\n\
\ \"acc_norm\": 0.20610687022900764,\n \"acc_norm_stderr\": 0.03547771004159463\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\
acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.16666666666666666,\n\
\ \"acc_stderr\": 0.036028141763926456,\n \"acc_norm\": 0.16666666666666666,\n\
\ \"acc_norm_stderr\": 0.036028141763926456\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.26993865030674846,\n \"acc_stderr\": 0.03487825168497892,\n\
\ \"acc_norm\": 0.26993865030674846,\n \"acc_norm_stderr\": 0.03487825168497892\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.23214285714285715,\n\
\ \"acc_stderr\": 0.04007341809755805,\n \"acc_norm\": 0.23214285714285715,\n\
\ \"acc_norm_stderr\": 0.04007341809755805\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.2524271844660194,\n \"acc_stderr\": 0.04301250399690877,\n\
\ \"acc_norm\": 0.2524271844660194,\n \"acc_norm_stderr\": 0.04301250399690877\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.23931623931623933,\n\
\ \"acc_stderr\": 0.02795182680892433,\n \"acc_norm\": 0.23931623931623933,\n\
\ \"acc_norm_stderr\": 0.02795182680892433\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.2784163473818646,\n\
\ \"acc_stderr\": 0.016028295188992462,\n \"acc_norm\": 0.2784163473818646,\n\
\ \"acc_norm_stderr\": 0.016028295188992462\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.2514450867052023,\n \"acc_stderr\": 0.023357365785874044,\n\
\ \"acc_norm\": 0.2514450867052023,\n \"acc_norm_stderr\": 0.023357365785874044\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23798882681564246,\n\
\ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\
\ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.24183006535947713,\n \"acc_stderr\": 0.024518195641879334,\n\
\ \"acc_norm\": 0.24183006535947713,\n \"acc_norm_stderr\": 0.024518195641879334\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.2090032154340836,\n\
\ \"acc_stderr\": 0.02309314039837422,\n \"acc_norm\": 0.2090032154340836,\n\
\ \"acc_norm_stderr\": 0.02309314039837422\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.24691358024691357,\n \"acc_stderr\": 0.023993501709042107,\n\
\ \"acc_norm\": 0.24691358024691357,\n \"acc_norm_stderr\": 0.023993501709042107\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.2198581560283688,\n \"acc_stderr\": 0.024706141070705484,\n \
\ \"acc_norm\": 0.2198581560283688,\n \"acc_norm_stderr\": 0.024706141070705484\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.23272490221642764,\n\
\ \"acc_stderr\": 0.0107925955538885,\n \"acc_norm\": 0.23272490221642764,\n\
\ \"acc_norm_stderr\": 0.0107925955538885\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.22426470588235295,\n \"acc_stderr\": 0.025336848563332355,\n\
\ \"acc_norm\": 0.22426470588235295,\n \"acc_norm_stderr\": 0.025336848563332355\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.2434640522875817,\n \"acc_stderr\": 0.017362473762146634,\n \
\ \"acc_norm\": 0.2434640522875817,\n \"acc_norm_stderr\": 0.017362473762146634\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.2727272727272727,\n\
\ \"acc_stderr\": 0.04265792110940589,\n \"acc_norm\": 0.2727272727272727,\n\
\ \"acc_norm_stderr\": 0.04265792110940589\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.1673469387755102,\n \"acc_stderr\": 0.023897144768914524,\n\
\ \"acc_norm\": 0.1673469387755102,\n \"acc_norm_stderr\": 0.023897144768914524\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.2537313432835821,\n\
\ \"acc_stderr\": 0.030769444967296018,\n \"acc_norm\": 0.2537313432835821,\n\
\ \"acc_norm_stderr\": 0.030769444967296018\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \
\ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.25903614457831325,\n\
\ \"acc_stderr\": 0.03410646614071856,\n \"acc_norm\": 0.25903614457831325,\n\
\ \"acc_norm_stderr\": 0.03410646614071856\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.30994152046783624,\n \"acc_stderr\": 0.035469769593931624,\n\
\ \"acc_norm\": 0.30994152046783624,\n \"acc_norm_stderr\": 0.035469769593931624\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.24357405140758873,\n\
\ \"mc1_stderr\": 0.015026354824910782,\n \"mc2\": 0.3899721945335931,\n\
\ \"mc2_stderr\": 0.014222197893576758\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6503551696921863,\n \"acc_stderr\": 0.013402073680850503\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0401819560272934,\n \
\ \"acc_stderr\": 0.005409439736970487\n }\n}\n```"
repo_url: https://huggingface.co/Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test.2
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|arc:challenge|25_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|gsm8k|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hellaswag|10_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-29T01-07-57.572756.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-29T01-07-57.572756.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- '**/details_harness|winogrande|5_2024-01-29T01-07-57.572756.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-29T01-07-57.572756.parquet'
- config_name: results
data_files:
- split: 2024_01_29T01_07_57.572756
path:
- results_2024-01-29T01-07-57.572756.parquet
- split: latest
path:
- results_2024-01-29T01-07-57.572756.parquet
---
# Dataset Card for Evaluation run of Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test.2
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test.2](https://huggingface.co/Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test.2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_Josephgflowers__Tinyllama-Cinder-1.3B-Reason-Test.2",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-29T01:07:57.572756](https://huggingface.co/datasets/open-llm-leaderboard/details_Josephgflowers__Tinyllama-Cinder-1.3B-Reason-Test.2/blob/main/results_2024-01-29T01-07-57.572756.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.251327576424007,
"acc_stderr": 0.030372163539921712,
"acc_norm": 0.251062888632938,
"acc_norm_stderr": 0.03108831080407431,
"mc1": 0.24357405140758873,
"mc1_stderr": 0.015026354824910782,
"mc2": 0.3899721945335931,
"mc2_stderr": 0.014222197893576758
},
"harness|arc:challenge|25": {
"acc": 0.2977815699658703,
"acc_stderr": 0.013363080107244487,
"acc_norm": 0.32764505119453924,
"acc_norm_stderr": 0.013715847940719346
},
"harness|hellaswag|10": {
"acc": 0.4402509460266879,
"acc_stderr": 0.004954026775425775,
"acc_norm": 0.5826528579964151,
"acc_norm_stderr": 0.00492113386493189
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.22,
"acc_stderr": 0.04163331998932268,
"acc_norm": 0.22,
"acc_norm_stderr": 0.04163331998932268
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.21481481481481482,
"acc_stderr": 0.035478541985608236,
"acc_norm": 0.21481481481481482,
"acc_norm_stderr": 0.035478541985608236
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.17763157894736842,
"acc_stderr": 0.031103182383123398,
"acc_norm": 0.17763157894736842,
"acc_norm_stderr": 0.031103182383123398
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.31,
"acc_stderr": 0.04648231987117316,
"acc_norm": 0.31,
"acc_norm_stderr": 0.04648231987117316
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.2490566037735849,
"acc_stderr": 0.02661648298050171,
"acc_norm": 0.2490566037735849,
"acc_norm_stderr": 0.02661648298050171
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.22916666666666666,
"acc_stderr": 0.035146974678623884,
"acc_norm": 0.22916666666666666,
"acc_norm_stderr": 0.035146974678623884
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.23,
"acc_stderr": 0.042295258468165085,
"acc_norm": 0.23,
"acc_norm_stderr": 0.042295258468165085
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.2,
"acc_stderr": 0.04020151261036846,
"acc_norm": 0.2,
"acc_norm_stderr": 0.04020151261036846
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.22,
"acc_stderr": 0.04163331998932269,
"acc_norm": 0.22,
"acc_norm_stderr": 0.04163331998932269
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.21965317919075145,
"acc_stderr": 0.031568093627031744,
"acc_norm": 0.21965317919075145,
"acc_norm_stderr": 0.031568093627031744
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.1568627450980392,
"acc_stderr": 0.036186648199362466,
"acc_norm": 0.1568627450980392,
"acc_norm_stderr": 0.036186648199362466
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.19,
"acc_stderr": 0.039427724440366234,
"acc_norm": 0.19,
"acc_norm_stderr": 0.039427724440366234
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.25957446808510637,
"acc_stderr": 0.02865917937429232,
"acc_norm": 0.25957446808510637,
"acc_norm_stderr": 0.02865917937429232
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.2631578947368421,
"acc_stderr": 0.0414243971948936,
"acc_norm": 0.2631578947368421,
"acc_norm_stderr": 0.0414243971948936
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.25517241379310346,
"acc_stderr": 0.03632984052707842,
"acc_norm": 0.25517241379310346,
"acc_norm_stderr": 0.03632984052707842
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.25925925925925924,
"acc_stderr": 0.022569897074918417,
"acc_norm": 0.25925925925925924,
"acc_norm_stderr": 0.022569897074918417
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.2698412698412698,
"acc_stderr": 0.039701582732351734,
"acc_norm": 0.2698412698412698,
"acc_norm_stderr": 0.039701582732351734
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.14,
"acc_stderr": 0.0348735088019777,
"acc_norm": 0.14,
"acc_norm_stderr": 0.0348735088019777
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.2870967741935484,
"acc_stderr": 0.025736542745594525,
"acc_norm": 0.2870967741935484,
"acc_norm_stderr": 0.025736542745594525
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.270935960591133,
"acc_stderr": 0.031270907132977,
"acc_norm": 0.270935960591133,
"acc_norm_stderr": 0.031270907132977
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.23,
"acc_stderr": 0.04229525846816505,
"acc_norm": 0.23,
"acc_norm_stderr": 0.04229525846816505
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.28484848484848485,
"acc_stderr": 0.035243908445117836,
"acc_norm": 0.28484848484848485,
"acc_norm_stderr": 0.035243908445117836
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.18181818181818182,
"acc_stderr": 0.02747960301053878,
"acc_norm": 0.18181818181818182,
"acc_norm_stderr": 0.02747960301053878
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.23316062176165803,
"acc_stderr": 0.03051611137147601,
"acc_norm": 0.23316062176165803,
"acc_norm_stderr": 0.03051611137147601
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.2846153846153846,
"acc_stderr": 0.022878322799706283,
"acc_norm": 0.2846153846153846,
"acc_norm_stderr": 0.022878322799706283
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.24074074074074073,
"acc_stderr": 0.026067159222275784,
"acc_norm": 0.24074074074074073,
"acc_norm_stderr": 0.026067159222275784
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.21428571428571427,
"acc_stderr": 0.02665353159671548,
"acc_norm": 0.21428571428571427,
"acc_norm_stderr": 0.02665353159671548
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.2052980132450331,
"acc_stderr": 0.03297986648473834,
"acc_norm": 0.2052980132450331,
"acc_norm_stderr": 0.03297986648473834
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.22385321100917432,
"acc_stderr": 0.01787121776779022,
"acc_norm": 0.22385321100917432,
"acc_norm_stderr": 0.01787121776779022
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.4074074074074074,
"acc_stderr": 0.033509916046960436,
"acc_norm": 0.4074074074074074,
"acc_norm_stderr": 0.033509916046960436
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.24509803921568626,
"acc_stderr": 0.030190282453501954,
"acc_norm": 0.24509803921568626,
"acc_norm_stderr": 0.030190282453501954
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.29535864978902954,
"acc_stderr": 0.02969633871342288,
"acc_norm": 0.29535864978902954,
"acc_norm_stderr": 0.02969633871342288
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.35874439461883406,
"acc_stderr": 0.032190792004199956,
"acc_norm": 0.35874439461883406,
"acc_norm_stderr": 0.032190792004199956
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.20610687022900764,
"acc_stderr": 0.03547771004159463,
"acc_norm": 0.20610687022900764,
"acc_norm_stderr": 0.03547771004159463
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.2396694214876033,
"acc_stderr": 0.03896878985070417,
"acc_norm": 0.2396694214876033,
"acc_norm_stderr": 0.03896878985070417
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.16666666666666666,
"acc_stderr": 0.036028141763926456,
"acc_norm": 0.16666666666666666,
"acc_norm_stderr": 0.036028141763926456
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.26993865030674846,
"acc_stderr": 0.03487825168497892,
"acc_norm": 0.26993865030674846,
"acc_norm_stderr": 0.03487825168497892
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.23214285714285715,
"acc_stderr": 0.04007341809755805,
"acc_norm": 0.23214285714285715,
"acc_norm_stderr": 0.04007341809755805
},
"harness|hendrycksTest-management|5": {
"acc": 0.2524271844660194,
"acc_stderr": 0.04301250399690877,
"acc_norm": 0.2524271844660194,
"acc_norm_stderr": 0.04301250399690877
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.23931623931623933,
"acc_stderr": 0.02795182680892433,
"acc_norm": 0.23931623931623933,
"acc_norm_stderr": 0.02795182680892433
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.32,
"acc_stderr": 0.04688261722621504,
"acc_norm": 0.32,
"acc_norm_stderr": 0.04688261722621504
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.2784163473818646,
"acc_stderr": 0.016028295188992462,
"acc_norm": 0.2784163473818646,
"acc_norm_stderr": 0.016028295188992462
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.2514450867052023,
"acc_stderr": 0.023357365785874044,
"acc_norm": 0.2514450867052023,
"acc_norm_stderr": 0.023357365785874044
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.23798882681564246,
"acc_stderr": 0.014242630070574915,
"acc_norm": 0.23798882681564246,
"acc_norm_stderr": 0.014242630070574915
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.24183006535947713,
"acc_stderr": 0.024518195641879334,
"acc_norm": 0.24183006535947713,
"acc_norm_stderr": 0.024518195641879334
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.2090032154340836,
"acc_stderr": 0.02309314039837422,
"acc_norm": 0.2090032154340836,
"acc_norm_stderr": 0.02309314039837422
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.24691358024691357,
"acc_stderr": 0.023993501709042107,
"acc_norm": 0.24691358024691357,
"acc_norm_stderr": 0.023993501709042107
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.2198581560283688,
"acc_stderr": 0.024706141070705484,
"acc_norm": 0.2198581560283688,
"acc_norm_stderr": 0.024706141070705484
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.23272490221642764,
"acc_stderr": 0.0107925955538885,
"acc_norm": 0.23272490221642764,
"acc_norm_stderr": 0.0107925955538885
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.22426470588235295,
"acc_stderr": 0.025336848563332355,
"acc_norm": 0.22426470588235295,
"acc_norm_stderr": 0.025336848563332355
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.2434640522875817,
"acc_stderr": 0.017362473762146634,
"acc_norm": 0.2434640522875817,
"acc_norm_stderr": 0.017362473762146634
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.2727272727272727,
"acc_stderr": 0.04265792110940589,
"acc_norm": 0.2727272727272727,
"acc_norm_stderr": 0.04265792110940589
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.1673469387755102,
"acc_stderr": 0.023897144768914524,
"acc_norm": 0.1673469387755102,
"acc_norm_stderr": 0.023897144768914524
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.2537313432835821,
"acc_stderr": 0.030769444967296018,
"acc_norm": 0.2537313432835821,
"acc_norm_stderr": 0.030769444967296018
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.3,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"harness|hendrycksTest-virology|5": {
"acc": 0.25903614457831325,
"acc_stderr": 0.03410646614071856,
"acc_norm": 0.25903614457831325,
"acc_norm_stderr": 0.03410646614071856
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.30994152046783624,
"acc_stderr": 0.035469769593931624,
"acc_norm": 0.30994152046783624,
"acc_norm_stderr": 0.035469769593931624
},
"harness|truthfulqa:mc|0": {
"mc1": 0.24357405140758873,
"mc1_stderr": 0.015026354824910782,
"mc2": 0.3899721945335931,
"mc2_stderr": 0.014222197893576758
},
"harness|winogrande|5": {
"acc": 0.6503551696921863,
"acc_stderr": 0.013402073680850503
},
"harness|gsm8k|5": {
"acc": 0.0401819560272934,
"acc_stderr": 0.005409439736970487
}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- 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. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
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### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- 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. -->
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### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- 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. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- 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. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
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[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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## Dataset Card Contact
[More Information Needed] |
christinacdl/OFF_HATE_TOXIC_ENGLISH | ---
license: apache-2.0
language:
- en
task_categories:
- text-classification
pretty_name: Offensive_Hateful_Toxic_Dataset
size_categories:
- n<1K
tags:
- code
---
100.772 texts with their corresponding labels
NOT_OFF_HATEFUL_TOXIC 81.359 values
OFF_HATEFUL_TOXIC 19.413 values |
fathyshalab/reklamation24_reisen-tourismus-full | ---
dataset_info:
features:
- name: text
dtype: string
- name: inputs
struct:
- name: text
dtype: string
- name: prediction
list:
- name: label
dtype: string
- name: score
dtype: float64
- name: prediction_agent
dtype: string
- name: annotation
dtype: string
- name: annotation_agent
dtype: string
- name: vectors
struct:
- name: mini-lm-sentence-transformers
sequence: float64
- name: multi_label
dtype: bool
- name: explanation
dtype: 'null'
- name: id
dtype: string
- name: metadata
dtype: 'null'
- name: status
dtype: string
- name: event_timestamp
dtype: timestamp[us]
- name: metrics
struct:
- name: text_length
dtype: int64
splits:
- name: train
num_bytes: 139906308
num_examples: 23759
download_size: 0
dataset_size: 139906308
---
# Dataset Card for "reklamation24_reisen-tourismus-full"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
mask-distilled-onesec-cv12-each-chunk-uniq/chunk_183 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 720635116.0
num_examples: 141523
download_size: 736141427
dataset_size: 720635116.0
---
# Dataset Card for "chunk_183"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
hayden-donnelly/db-sfw-512px-general-filter | ---
task_categories:
- image-classification
size_categories:
- 10K<n<100K
---
# Danbooru SFW 512px General Filter
This dataset is meant to be used for training a simple binary classifier that can filter the
Danbooru SFW 2021 dataset. There are two classes: "accepted" and "rejected", with "accepted"
representing samples that should pass through the filter and "rejected" representing samples
that should not.
Generallly, to be accepted a sample should meet the following criteria:
1. No horizontal/vertical bars, or bars that can be removed easily by filling in the background
color. This precludes any samples with bars which cut through any part of the image that is not
a solid color block (i.e. patterns, detailed backgrounds, and foreground elements).
2. Not overtly sexual. The SFW subset of Danbooru 2021 which this dataset is based on has
already removed almost all nudity, this criterion simply removes some of the borderline NSFW images.
3. Somewhat aesthetic.
Please note that dataset samples were selected manually, so there was somewhat of a tradeoff between
speed and accuracy. Despite this, I've managed to train a binary classifier up to 85% test
accuracy on this dataset. I've also observed pretty good performance when using that classifier on
entirely new portions of the base dataset.
## Original Dataset Citation
```bibtex
@misc{danbooru2021,
author={Anonymous and Danbooru community and Gwern Branwen},
title={Danbooru2021: A Large-Scale Crowdsourced and Tagged Anime Illustration Dataset},
howpublished={\url{https://gwern.net/danbooru2021}},
url={https://gwern.net/danbooru2021},
type={dataset},
year={2022},
month={January},
timestamp={2022-01-21},
note={Accessed: 2023-12-06}
}
``` |
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