datasetId stringlengths 2 117 | card stringlengths 19 1.01M |
|---|---|
ilhamxx/dataset_factures | ---
license: unknown
---
|
Crystal427/EroCrystyWriter | ---
license: gpl-3.0
---
|
Nan-Do/reason_code-search-net-python | ---
dataset_info:
features:
- name: INSTRUCTION
dtype: string
- name: RESPONSE
dtype: string
- name: TYPE
dtype: int64
- name: SOURCE
dtype: string
splits:
- name: train
num_bytes: 399930143
num_examples: 429059
download_size: 89360217
dataset_size: 399930143
license: apache-2.0
task_categories:
- summarization
- text-generation
- conversational
- text2text-generation
language:
- en
tags:
- code
- reasoning
- Python
pretty_name: Reasoning dataset for Python
---
# Dataset Card for "reason_code-search-net-python"
## Dataset Description
- **Homepage:** None
- **Repository:** https://huggingface.co/datasets/Nan-Do/reason_code-search-net-python
- **Paper:** None
- **Leaderboard:** None
- **Point of Contact:** [@Nan-Do](https://github.com/Nan-Do)
### Dataset Summary
This dataset is an instructional dataset for Python.
The dataset contains five different kind of tasks.
Given a Python 3 function:
- Type 1: Generate a summary explaining what it does. (For example: This function counts the number of objects stored in the jsonl file passed as input.)
- Type 2: Generate a summary explaining what its input parameters represent ("For example: infile: a file descriptor of a file containing json objects in jsonl format.")
- Type 3: Generate a summary explaining what the return value represents ("For example: The function returns the number of json objects in the file passed as input.")
- Type 4: Generate a summary explaining what is the type of the return value ("For example: The function returns an int.")
- Type 5: Generate a summary explaining what is the type of its input parameters ("For example: infile: A file descriptor.").
### Languages
The dataset is in English.
### Data Splits
There are no splits (Only training).
## Dataset Creation
May of 2023
### Curation Rationale
This dataset was created to improve the Python 3 reasoning/understanding capabilities of LLMs.
### Source Data
The summarized version of the code-search-net dataset can be found at https://huggingface.co/datasets/Nan-Do/code-search-net-python
### Annotations
The dataset includes an instruction, response and type columns.
The type colum indicates the type of task (from 1 to 5).
#### Annotation process
The annotation procedure was done using templates, NLP techniques to generate human-like questions and responses, and the Python AST module to parse the code.
The responses were generated parsing the docstrings of the functions. (The ones that included the required information).
### Licensing Information
Apache 2.0 |
shyzii/exrcise-llama2-converted | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 7877
num_examples: 48
download_size: 3063
dataset_size: 7877
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
mole-code/llama_index-data | ---
dataset_info:
features:
- name: code
dtype: string
- name: apis
sequence: string
- name: extract_api
dtype: string
splits:
- name: train
num_bytes: 10014930
num_examples: 1059
download_size: 2323807
dataset_size: 10014930
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
diwank/michelleyun-therapydata | ---
dataset_info:
features:
- name: transcript_id
dtype: string
- name: topic
dtype: string
- name: interlocutor
dtype: string
- name: utterance_text
dtype: string
- name: main_therapist_behaviour
dtype: string
- name: client_talk_type
dtype: string
splits:
- name: train
num_bytes: 629461
num_examples: 4153
- name: test
num_bytes: 155495
num_examples: 1039
download_size: 279271
dataset_size: 784956
---
# Dataset Card for "michelleyun-therapydata"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
distilled-from-one-sec-cv12/chunk_156 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1188514748
num_examples: 231589
download_size: 1212751385
dataset_size: 1188514748
---
# Dataset Card for "chunk_156"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
deetsadi/processed_dwi_all_b_values_semantic | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: conditioning_image
dtype: image
splits:
- name: train
num_bytes: 38575018.0
num_examples: 200
download_size: 38388660
dataset_size: 38575018.0
---
# Dataset Card for "processed_dwi_all_b_values_semantic"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
garNER/custom-MultiCoNER-II | ---
license: apache-2.0
---
|
arieg/bw_spec_cls_4_12_noise_200 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': '1039'
'1': '1040'
'2': '1082'
'3': '1083'
splits:
- name: train
num_bytes: 43275557.0
num_examples: 800
- name: test
num_bytes: 1080285.0
num_examples: 20
download_size: 23012897
dataset_size: 44355842.0
---
# Dataset Card for "bw_spec_cls_4_12_noise_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ovior/twitter_dataset_1713187480 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 2411676
num_examples: 7146
download_size: 1380720
dataset_size: 2411676
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
pollitoconpapass/perukistan_dataset | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: text
dtype: string
splits:
- name: train
num_bytes: 122627879.0
num_examples: 131
download_size: 122629185
dataset_size: 122627879.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
jcavecilla/daisuki_df | ---
license: mit
language:
- en
--- |
mertllc/twenties_male | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 1097736.6176470588
num_examples: 54
- name: test
num_bytes: 280054.3823529412
num_examples: 14
download_size: 1348964
dataset_size: 1377791.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
KAUE24122023/DarwinVozAntigaYagoMachado | ---
license: openrail
---
|
CyberHarem/zhong_lanzhu_lovelivenijigasakihighschoolidolclub | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of zhong_lanzhu/鐘嵐珠/중란주 (Love Live! Nijigasaki Gakuen School Idol Doukoukai)
This is the dataset of zhong_lanzhu/鐘嵐珠/중란주 (Love Live! Nijigasaki Gakuen School Idol Doukoukai), containing 500 images and their tags.
The core tags of this character are `long_hair, pink_hair, blue_eyes, ahoge, breasts, mole, bangs, mole_under_eye, sidelocks, hair_bun, double_bun`, 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 | 500 | 825.06 MiB | [Download](https://huggingface.co/datasets/CyberHarem/zhong_lanzhu_lovelivenijigasakihighschoolidolclub/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 396.02 MiB | [Download](https://huggingface.co/datasets/CyberHarem/zhong_lanzhu_lovelivenijigasakihighschoolidolclub/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1262 | 879.33 MiB | [Download](https://huggingface.co/datasets/CyberHarem/zhong_lanzhu_lovelivenijigasakihighschoolidolclub/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 696.35 MiB | [Download](https://huggingface.co/datasets/CyberHarem/zhong_lanzhu_lovelivenijigasakihighschoolidolclub/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1262 | 1.37 GiB | [Download](https://huggingface.co/datasets/CyberHarem/zhong_lanzhu_lovelivenijigasakihighschoolidolclub/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/zhong_lanzhu_lovelivenijigasakihighschoolidolclub',
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 | 38 |  |  |  |  |  | 1girl, solo, looking_at_viewer, black_gloves, chinese_clothes, smile, cleavage_cutout, bun_cover, dress, upper_body, blush |
| 1 | 5 |  |  |  |  |  | 1girl, belt, earrings, hair_ornament, solo, cleavage_cutout, epaulettes, looking_at_viewer, red_dress, birthday, black_gloves, chinese_clothes, jacket, smile, upper_body |
| 2 | 5 |  |  |  |  |  | 1girl, cleavage, collarbone, looking_at_viewer, solo, bare_shoulders, blush, large_breasts, two_side_up, white_background, closed_mouth, simple_background, smile, upper_body, black_camisole, medium_breasts |
| 3 | 18 |  |  |  |  |  | 1girl, jacket, nijigasaki_academy_school_uniform, solo, looking_at_viewer, smile, two_side_up, skirt, hand_on_hip, white_background, blush |
| 4 | 5 |  |  |  |  |  | 1girl, large_breasts, looking_at_viewer, nijigasaki_academy_school_uniform, solo, upper_body, white_background, blush, red_jacket, smile |
| 5 | 15 |  |  |  |  |  | 1girl, solo, large_breasts, looking_at_viewer, blush, smile, navel, collarbone, cleavage, side-tie_bikini_bottom, blue_sky, red_bikini, cloud, simple_background, two_side_up, criss-cross_halter, day, ocean, outdoors, white_background |
| 6 | 9 |  |  |  |  |  | 1girl, blush, large_breasts, nipples, 1boy, completely_nude, hetero, penis, solo_focus, sweat, collarbone, mosaic_censoring, looking_at_viewer, open_mouth, paizuri, smile, two_side_up, breasts_squeezed_together, hair_rings, motion_lines, pov_crotch, swept_bangs, upper_body |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | looking_at_viewer | black_gloves | chinese_clothes | smile | cleavage_cutout | bun_cover | dress | upper_body | blush | belt | earrings | hair_ornament | epaulettes | red_dress | birthday | jacket | cleavage | collarbone | bare_shoulders | large_breasts | two_side_up | white_background | closed_mouth | simple_background | black_camisole | medium_breasts | nijigasaki_academy_school_uniform | skirt | hand_on_hip | red_jacket | navel | side-tie_bikini_bottom | blue_sky | red_bikini | cloud | criss-cross_halter | day | ocean | outdoors | nipples | 1boy | completely_nude | hetero | penis | solo_focus | sweat | mosaic_censoring | open_mouth | paizuri | breasts_squeezed_together | hair_rings | motion_lines | pov_crotch | swept_bangs |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------------------|:---------------|:------------------|:--------|:------------------|:------------|:--------|:-------------|:--------|:-------|:-----------|:----------------|:-------------|:------------|:-----------|:---------|:-----------|:-------------|:-----------------|:----------------|:--------------|:-------------------|:---------------|:--------------------|:-----------------|:-----------------|:------------------------------------|:--------|:--------------|:-------------|:--------|:-------------------------|:-----------|:-------------|:--------|:---------------------|:------|:--------|:-----------|:----------|:-------|:------------------|:---------|:--------|:-------------|:--------|:-------------------|:-------------|:----------|:----------------------------|:-------------|:---------------|:-------------|:--------------|
| 0 | 38 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | | | X | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 5 |  |  |  |  |  | X | X | X | | | X | | | | X | X | | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 18 |  |  |  |  |  | X | X | X | | | X | | | | | X | | | | | | | X | | | | | X | X | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 5 |  |  |  |  |  | X | X | X | | | X | | | | X | X | | | | | | | | | | | X | | X | | | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 15 |  |  |  |  |  | X | X | X | | | X | | | | | X | | | | | | | | X | X | | X | X | X | | X | | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | |
| 6 | 9 |  |  |  |  |  | X | | X | | | X | | | | X | X | | | | | | | | | X | | X | X | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
mteb/scala_nn_classification | ---
dataset_info:
features:
- name: text
dtype: string
- name: corruption_type
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 136251
num_examples: 1024
- name: test
num_bytes: 268761
num_examples: 2048
- name: full_train
num_bytes: 3062138
num_examples: 22800
- name: val
num_bytes: 33910
num_examples: 256
download_size: 2088966
dataset_size: 3501060
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: full_train
path: data/full_train-*
- split: val
path: data/val-*
---
|
CyberHarem/bianca_eleanor_maougakuinnofutekigousha | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of Bianca Eleanor/エレオノール・ビアンカ (Maou Gakuin no Futekigousha)
This is the dataset of Bianca Eleanor/エレオノール・ビアンカ (Maou Gakuin no Futekigousha), containing 138 images and their tags.
The core tags of this character are `long_hair, black_hair, braid, purple_eyes, breasts, hair_between_eyes, purple_hair, large_breasts`, 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 | 138 | 94.58 MiB | [Download](https://huggingface.co/datasets/CyberHarem/bianca_eleanor_maougakuinnofutekigousha/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 1200 | 138 | 94.54 MiB | [Download](https://huggingface.co/datasets/CyberHarem/bianca_eleanor_maougakuinnofutekigousha/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 261 | 165.64 MiB | [Download](https://huggingface.co/datasets/CyberHarem/bianca_eleanor_maougakuinnofutekigousha/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/bianca_eleanor_maougakuinnofutekigousha',
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 | 9 |  |  |  |  |  | 1girl, cleavage_cutout, closed_mouth, smile, upper_body, red_jacket, solo, twin_braids, ^_^, long_sleeves, ahoge |
| 1 | 7 |  |  |  |  |  | 1girl, upper_body, cleavage_cutout, red_jacket, solo, uniform, v-shaped_eyebrows, medium_breasts, shirt, closed_mouth, frown, open_mouth |
| 2 | 8 |  |  |  |  |  | closed_mouth, solo_focus, upper_body, night, 2girls, ahoge, 1girl, red_jacket, cleavage_cutout, twin_braids |
| 3 | 8 |  |  |  |  |  | 1girl, solo, closed_mouth, looking_at_viewer, portrait, smile, twin_braids, upper_body, cleavage, side_braid |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | cleavage_cutout | closed_mouth | smile | upper_body | red_jacket | solo | twin_braids | ^_^ | long_sleeves | ahoge | uniform | v-shaped_eyebrows | medium_breasts | shirt | frown | open_mouth | solo_focus | night | 2girls | looking_at_viewer | portrait | cleavage | side_braid |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:------------------|:---------------|:--------|:-------------|:-------------|:-------|:--------------|:------|:---------------|:--------|:----------|:--------------------|:-----------------|:--------|:--------|:-------------|:-------------|:--------|:---------|:--------------------|:-----------|:-----------|:-------------|
| 0 | 9 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | |
| 1 | 7 |  |  |  |  |  | X | X | X | | X | X | X | | | | | X | X | X | X | X | X | | | | | | | |
| 2 | 8 |  |  |  |  |  | X | X | X | | X | X | | X | | | X | | | | | | | X | X | X | | | | |
| 3 | 8 |  |  |  |  |  | X | | X | X | X | | X | X | | | | | | | | | | | | | X | X | X | X |
|
Nexdata/143_Hours_Uyghur_Conversational_Speech_Data_by_Telephone | ---
license: cc-by-nc-nd-4.0
---
## Description
Uyghur(China) Spontaneous Dialogue Telephony speech dataset, collected from dialogues based on given topics, covering 20+ domains. Transcribed with text content, speaker's ID, gender, age and other attributes. Our dataset was collected from extensive and diversify speakers(320 native speakers), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.
For more details, please refer to the link: https://www.nexdata.ai/dataset/1274?source=Huggingface
## Format
8kHz, 8bit, u-law pcm, mono channel;;
## Content category
Dialogue based on given topics;
## Recording condition
Low background noise (indoor);
## Recording device
Telephony;
## Speaker
320 native speakers in total, 37% male and 63% female;
## Country
China(CHN);
## Language(Region) Code
ug-CN;
## Language
Uyghur;
## Features of annotation
Transcription text, timestamp, speaker ID, gender, noise,PII redacted.
## Accuracy Rate
Sentence Accuracy Rate (SAR) 95%
# Licensing Information
Commercial License
|
guangguang/azukijpg | ---
license: apache-2.0
---
|
DTU54DL/libri_augmented_train_set | ---
dataset_info:
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
- name: train.360
num_bytes: 41931835349.25
num_examples: 104014
download_size: 0
dataset_size: 41931835349.25
---
# Dataset Card for "libri_augmented_train_set"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Ryan20/hotel_data1_pushed | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: inputs
dtype: string
splits:
- name: train
num_bytes: 10324
num_examples: 16
download_size: 10259
dataset_size: 10324
---
# Dataset Card for "hotel_data1_pushed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
nz/mathorca_sharegpt | ---
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 217102095.98771498
num_examples: 190104
- name: test
num_bytes: 2284035.0122850123
num_examples: 2000
download_size: 97262237
dataset_size: 219386131.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
CyberHarem/carol_malus_dienheim_senkizesshousymphogear | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of Carol Malus Dienheim
This is the dataset of Carol Malus Dienheim, containing 300 images and their tags.
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)).
| Name | Images | Download | Description |
|:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------|
| raw | 300 | [Download](dataset-raw.zip) | Raw data with meta information. |
| raw-stage3 | 624 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. |
| 384x512 | 300 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. |
| 512x512 | 300 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. |
| 512x704 | 300 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. |
| 640x640 | 300 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. |
| 640x880 | 300 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. |
| stage3-640 | 624 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. |
| stage3-800 | 624 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. |
| stage3-1200 | 624 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
|
Birchlabs/danbooru-caption-lengths | ---
license: apache-2.0
---
|
SujinHwang/criminal-sketch-H-kr | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 195354591.572
num_examples: 8071
download_size: 173997852
dataset_size: 195354591.572
---
# Dataset Card for "criminal-sketch-H-kr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_abhishek__ccy0-2g7e-wqsa-0 | ---
pretty_name: Evaluation run of abhishek/ccy0-2g7e-wqsa-0
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [abhishek/ccy0-2g7e-wqsa-0](https://huggingface.co/abhishek/ccy0-2g7e-wqsa-0)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 1 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_abhishek__ccy0-2g7e-wqsa-0\"\
,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\
\ are the [latest results from run 2023-12-02T16:46:35.234385](https://huggingface.co/datasets/open-llm-leaderboard/details_abhishek__ccy0-2g7e-wqsa-0/blob/main/results_2023-12-02T16-46-35.234385.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\": 0.32221379833206976,\n\
\ \"acc_stderr\": 0.01287243548118878\n },\n \"harness|gsm8k|5\": {\n\
\ \"acc\": 0.32221379833206976,\n \"acc_stderr\": 0.01287243548118878\n\
\ }\n}\n```"
repo_url: https://huggingface.co/abhishek/ccy0-2g7e-wqsa-0
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_02T16_33_02.439769
path:
- '**/details_harness|gsm8k|5_2023-12-02T16-33-02.439769.parquet'
- split: 2023_12_02T16_46_35.234385
path:
- '**/details_harness|gsm8k|5_2023-12-02T16-46-35.234385.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-02T16-46-35.234385.parquet'
- config_name: results
data_files:
- split: 2023_12_02T16_33_02.439769
path:
- results_2023-12-02T16-33-02.439769.parquet
- split: 2023_12_02T16_46_35.234385
path:
- results_2023-12-02T16-46-35.234385.parquet
- split: latest
path:
- results_2023-12-02T16-46-35.234385.parquet
---
# Dataset Card for Evaluation run of abhishek/ccy0-2g7e-wqsa-0
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/abhishek/ccy0-2g7e-wqsa-0
- **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 [abhishek/ccy0-2g7e-wqsa-0](https://huggingface.co/abhishek/ccy0-2g7e-wqsa-0) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 1 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_abhishek__ccy0-2g7e-wqsa-0",
"harness_gsm8k_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-02T16:46:35.234385](https://huggingface.co/datasets/open-llm-leaderboard/details_abhishek__ccy0-2g7e-wqsa-0/blob/main/results_2023-12-02T16-46-35.234385.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": 0.32221379833206976,
"acc_stderr": 0.01287243548118878
},
"harness|gsm8k|5": {
"acc": 0.32221379833206976,
"acc_stderr": 0.01287243548118878
}
}
```
### 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] |
open-llm-leaderboard/details_chargoddard__SmolLlamix-8x101M | ---
pretty_name: Evaluation run of chargoddard/SmolLlamix-8x101M
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [chargoddard/SmolLlamix-8x101M](https://huggingface.co/chargoddard/SmolLlamix-8x101M)\
\ 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_chargoddard__SmolLlamix-8x101M\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-04T12:29:56.794531](https://huggingface.co/datasets/open-llm-leaderboard/details_chargoddard__SmolLlamix-8x101M/blob/main/results_2024-01-04T12-29-56.794531.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\": 0.24665141008843472,\n\
\ \"acc_stderr\": 0.030422170490043785,\n \"acc_norm\": 0.24716769398389823,\n\
\ \"acc_norm_stderr\": 0.031197299482121136,\n \"mc1\": 0.26193390452876375,\n\
\ \"mc1_stderr\": 0.015392118805015021,\n \"mc2\": 0.4608972262894305,\n\
\ \"mc2_stderr\": 0.015343271963572871\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.17918088737201365,\n \"acc_stderr\": 0.011207045216615667,\n\
\ \"acc_norm\": 0.22696245733788395,\n \"acc_norm_stderr\": 0.012240491536132866\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.2765385381398128,\n\
\ \"acc_stderr\": 0.0044637210713190986,\n \"acc_norm\": 0.28500298745269864,\n\
\ \"acc_norm_stderr\": 0.004504932999736393\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \
\ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\
\ \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.26666666666666666,\n\
\ \"acc_stderr\": 0.03820169914517904,\n \"acc_norm\": 0.26666666666666666,\n\
\ \"acc_norm_stderr\": 0.03820169914517904\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.18421052631578946,\n \"acc_stderr\": 0.0315469804508223,\n\
\ \"acc_norm\": 0.18421052631578946,\n \"acc_norm_stderr\": 0.0315469804508223\n\
\ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\
: {\n \"acc\": 0.22264150943396227,\n \"acc_stderr\": 0.0256042334708991,\n\
\ \"acc_norm\": 0.22264150943396227,\n \"acc_norm_stderr\": 0.0256042334708991\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\": 0.15,\n \"acc_stderr\": 0.035887028128263714,\n \
\ \"acc_norm\": 0.15,\n \"acc_norm_stderr\": 0.035887028128263714\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.23,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\"\
: 0.23,\n \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \
\ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.19653179190751446,\n\
\ \"acc_stderr\": 0.03029957466478814,\n \"acc_norm\": 0.19653179190751446,\n\
\ \"acc_norm_stderr\": 0.03029957466478814\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\":\
\ 0.27,\n \"acc_stderr\": 0.04461960433384741,\n \"acc_norm\": 0.27,\n\
\ \"acc_norm_stderr\": 0.04461960433384741\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.22127659574468084,\n \"acc_stderr\": 0.027136349602424063,\n\
\ \"acc_norm\": 0.22127659574468084,\n \"acc_norm_stderr\": 0.027136349602424063\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.24561403508771928,\n\
\ \"acc_stderr\": 0.04049339297748141,\n \"acc_norm\": 0.24561403508771928,\n\
\ \"acc_norm_stderr\": 0.04049339297748141\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.20689655172413793,\n \"acc_stderr\": 0.03375672449560553,\n\
\ \"acc_norm\": 0.20689655172413793,\n \"acc_norm_stderr\": 0.03375672449560553\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.24338624338624337,\n \"acc_stderr\": 0.022101128787415433,\n \"\
acc_norm\": 0.24338624338624337,\n \"acc_norm_stderr\": 0.022101128787415433\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.1746031746031746,\n\
\ \"acc_stderr\": 0.03395490020856113,\n \"acc_norm\": 0.1746031746031746,\n\
\ \"acc_norm_stderr\": 0.03395490020856113\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \
\ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.31290322580645163,\n \"acc_stderr\": 0.02637756702864586,\n \"\
acc_norm\": 0.31290322580645163,\n \"acc_norm_stderr\": 0.02637756702864586\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.30049261083743845,\n \"acc_stderr\": 0.03225799476233483,\n \"\
acc_norm\": 0.30049261083743845,\n \"acc_norm_stderr\": 0.03225799476233483\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\
: {\n \"acc\": 0.2,\n \"acc_stderr\": 0.031234752377721175,\n \
\ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.031234752377721175\n \
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.26262626262626265,\n \"acc_stderr\": 0.031353050095330855,\n \"\
acc_norm\": 0.26262626262626265,\n \"acc_norm_stderr\": 0.031353050095330855\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.34196891191709844,\n \"acc_stderr\": 0.03423465100104281,\n\
\ \"acc_norm\": 0.34196891191709844,\n \"acc_norm_stderr\": 0.03423465100104281\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.2641025641025641,\n \"acc_stderr\": 0.022352193737453285,\n\
\ \"acc_norm\": 0.2641025641025641,\n \"acc_norm_stderr\": 0.022352193737453285\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.2777777777777778,\n \"acc_stderr\": 0.027309140588230182,\n \
\ \"acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.027309140588230182\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.24369747899159663,\n \"acc_stderr\": 0.027886828078380572,\n\
\ \"acc_norm\": 0.24369747899159663,\n \"acc_norm_stderr\": 0.027886828078380572\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.26490066225165565,\n \"acc_stderr\": 0.036030385453603826,\n \"\
acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.036030385453603826\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.22935779816513763,\n \"acc_stderr\": 0.018025349724618684,\n \"\
acc_norm\": 0.22935779816513763,\n \"acc_norm_stderr\": 0.018025349724618684\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.4305555555555556,\n \"acc_stderr\": 0.03376922151252335,\n \"\
acc_norm\": 0.4305555555555556,\n \"acc_norm_stderr\": 0.03376922151252335\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.22058823529411764,\n \"acc_stderr\": 0.02910225438967409,\n \"\
acc_norm\": 0.22058823529411764,\n \"acc_norm_stderr\": 0.02910225438967409\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.26582278481012656,\n \"acc_stderr\": 0.028756799629658342,\n \
\ \"acc_norm\": 0.26582278481012656,\n \"acc_norm_stderr\": 0.028756799629658342\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.23766816143497757,\n\
\ \"acc_stderr\": 0.028568079464714267,\n \"acc_norm\": 0.23766816143497757,\n\
\ \"acc_norm_stderr\": 0.028568079464714267\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.22900763358778625,\n \"acc_stderr\": 0.036853466317118506,\n\
\ \"acc_norm\": 0.22900763358778625,\n \"acc_norm_stderr\": 0.036853466317118506\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.2809917355371901,\n \"acc_stderr\": 0.04103203830514512,\n \"\
acc_norm\": 0.2809917355371901,\n \"acc_norm_stderr\": 0.04103203830514512\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25,\n\
\ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.25,\n \
\ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.24539877300613497,\n \"acc_stderr\": 0.03380939813943354,\n\
\ \"acc_norm\": 0.24539877300613497,\n \"acc_norm_stderr\": 0.03380939813943354\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.23214285714285715,\n\
\ \"acc_stderr\": 0.04007341809755807,\n \"acc_norm\": 0.23214285714285715,\n\
\ \"acc_norm_stderr\": 0.04007341809755807\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.1941747572815534,\n \"acc_stderr\": 0.03916667762822585,\n\
\ \"acc_norm\": 0.1941747572815534,\n \"acc_norm_stderr\": 0.03916667762822585\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2264957264957265,\n\
\ \"acc_stderr\": 0.027421007295392912,\n \"acc_norm\": 0.2264957264957265,\n\
\ \"acc_norm_stderr\": 0.027421007295392912\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \
\ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.2567049808429119,\n\
\ \"acc_stderr\": 0.015620480263064526,\n \"acc_norm\": 0.2567049808429119,\n\
\ \"acc_norm_stderr\": 0.015620480263064526\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.24855491329479767,\n \"acc_stderr\": 0.023267528432100174,\n\
\ \"acc_norm\": 0.24855491329479767,\n \"acc_norm_stderr\": 0.023267528432100174\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24692737430167597,\n\
\ \"acc_stderr\": 0.014422292204808835,\n \"acc_norm\": 0.24692737430167597,\n\
\ \"acc_norm_stderr\": 0.014422292204808835\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.02380518652488814,\n\
\ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.02380518652488814\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.29260450160771706,\n\
\ \"acc_stderr\": 0.025839898334877983,\n \"acc_norm\": 0.29260450160771706,\n\
\ \"acc_norm_stderr\": 0.025839898334877983\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.24074074074074073,\n \"acc_stderr\": 0.02378858355165854,\n\
\ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.02378858355165854\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.2624113475177305,\n \"acc_stderr\": 0.026244920349843007,\n \
\ \"acc_norm\": 0.2624113475177305,\n \"acc_norm_stderr\": 0.026244920349843007\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.24511082138200782,\n\
\ \"acc_stderr\": 0.010986307870045509,\n \"acc_norm\": 0.24511082138200782,\n\
\ \"acc_norm_stderr\": 0.010986307870045509\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.36764705882352944,\n \"acc_stderr\": 0.029289413409403192,\n\
\ \"acc_norm\": 0.36764705882352944,\n \"acc_norm_stderr\": 0.029289413409403192\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.22549019607843138,\n \"acc_stderr\": 0.016906615927288152,\n \
\ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.016906615927288152\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.18181818181818182,\n\
\ \"acc_stderr\": 0.036942843353378,\n \"acc_norm\": 0.18181818181818182,\n\
\ \"acc_norm_stderr\": 0.036942843353378\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.2571428571428571,\n \"acc_stderr\": 0.02797982353874455,\n\
\ \"acc_norm\": 0.2571428571428571,\n \"acc_norm_stderr\": 0.02797982353874455\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.23880597014925373,\n\
\ \"acc_stderr\": 0.030147775935409217,\n \"acc_norm\": 0.23880597014925373,\n\
\ \"acc_norm_stderr\": 0.030147775935409217\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.24,\n \"acc_stderr\": 0.042923469599092816,\n \
\ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.042923469599092816\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.21686746987951808,\n\
\ \"acc_stderr\": 0.03208284450356365,\n \"acc_norm\": 0.21686746987951808,\n\
\ \"acc_norm_stderr\": 0.03208284450356365\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.21052631578947367,\n \"acc_stderr\": 0.03126781714663179,\n\
\ \"acc_norm\": 0.21052631578947367,\n \"acc_norm_stderr\": 0.03126781714663179\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.26193390452876375,\n\
\ \"mc1_stderr\": 0.015392118805015021,\n \"mc2\": 0.4608972262894305,\n\
\ \"mc2_stderr\": 0.015343271963572871\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.5130228887134964,\n \"acc_stderr\": 0.014047718393997663\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.006065200909780136,\n \
\ \"acc_stderr\": 0.0021386703014604725\n }\n}\n```"
repo_url: https://huggingface.co/chargoddard/SmolLlamix-8x101M
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_04T12_29_56.794531
path:
- '**/details_harness|arc:challenge|25_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|gsm8k|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hellaswag|10_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-29-56.794531.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-04T12-29-56.794531.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- '**/details_harness|winogrande|5_2024-01-04T12-29-56.794531.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-04T12-29-56.794531.parquet'
- config_name: results
data_files:
- split: 2024_01_04T12_29_56.794531
path:
- results_2024-01-04T12-29-56.794531.parquet
- split: latest
path:
- results_2024-01-04T12-29-56.794531.parquet
---
# Dataset Card for Evaluation run of chargoddard/SmolLlamix-8x101M
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [chargoddard/SmolLlamix-8x101M](https://huggingface.co/chargoddard/SmolLlamix-8x101M) 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_chargoddard__SmolLlamix-8x101M",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-04T12:29:56.794531](https://huggingface.co/datasets/open-llm-leaderboard/details_chargoddard__SmolLlamix-8x101M/blob/main/results_2024-01-04T12-29-56.794531.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": {
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"acc_stderr": 0.030422170490043785,
"acc_norm": 0.24716769398389823,
"acc_norm_stderr": 0.031197299482121136,
"mc1": 0.26193390452876375,
"mc1_stderr": 0.015392118805015021,
"mc2": 0.4608972262894305,
"mc2_stderr": 0.015343271963572871
},
"harness|arc:challenge|25": {
"acc": 0.17918088737201365,
"acc_stderr": 0.011207045216615667,
"acc_norm": 0.22696245733788395,
"acc_norm_stderr": 0.012240491536132866
},
"harness|hellaswag|10": {
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"acc_stderr": 0.0044637210713190986,
"acc_norm": 0.28500298745269864,
"acc_norm_stderr": 0.004504932999736393
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.26,
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"acc_norm": 0.26,
"acc_norm_stderr": 0.0440844002276808
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.26666666666666666,
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"acc_norm": 0.26666666666666666,
"acc_norm_stderr": 0.03820169914517904
},
"harness|hendrycksTest-astronomy|5": {
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},
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},
"harness|hendrycksTest-clinical_knowledge|5": {
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},
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},
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},
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},
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},
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},
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},
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},
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"harness|hendrycksTest-high_school_us_history|5": {
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},
"harness|hendrycksTest-high_school_world_history|5": {
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},
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"harness|hendrycksTest-international_law|5": {
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"harness|hendrycksTest-logical_fallacies|5": {
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},
"harness|hendrycksTest-management|5": {
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},
"harness|hendrycksTest-marketing|5": {
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"harness|hendrycksTest-nutrition|5": {
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"harness|hendrycksTest-us_foreign_policy|5": {
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},
"harness|hendrycksTest-world_religions|5": {
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},
"harness|truthfulqa:mc|0": {
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"mc2": 0.4608972262894305,
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},
"harness|winogrande|5": {
"acc": 0.5130228887134964,
"acc_stderr": 0.014047718393997663
},
"harness|gsm8k|5": {
"acc": 0.006065200909780136,
"acc_stderr": 0.0021386703014604725
}
}
```
## 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. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] |
kaleemWaheed/twitter_dataset_1713084674 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 10955
num_examples: 26
download_size: 10311
dataset_size: 10955
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
pcranaway/reddit-2011 | ---
license: unknown
---
|
personalLoad/dataset | ---
license: apache-2.0
---
|
marcus2000/keymoment_protocols_bestoftimelist | ---
dataset_info:
features:
- name: system
dtype: string
- name: user
dtype: string
- name: bot
dtype: string
splits:
- name: train
num_bytes: 1359224
num_examples: 156
download_size: 617553
dataset_size: 1359224
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
nc33/boolques | ---
license: mit
---
|
Skarut1945/Skarut | ---
license: openrail
---
|
alexantonov/chuvash_parallel | ---
language:
- cv
multilinguality:
- translation
source_datasets:
- original
task_ids:
- machine-translation
---
# Dataset Description
## Chuvash-Russian parallel corpus
1M parallel sentences. Manually aligned
## Chuvash-English parallel corpus.
200K parallel sentences. Automatically aligned
## Contributions
For additional details contact [@AlAntonov](https://github.com/AlAntonov). |
arslanarjumand/read_aloud | ---
dataset_info:
features:
- name: totalScore
dtype: int64
- name: contentScore
dtype: int64
- name: fluencyScore
dtype: int64
- name: pronunciationScore
dtype: int64
- name: length
dtype: float64
- name: input_features
sequence:
sequence: float32
splits:
- name: train
num_bytes: 4789436644
num_examples: 6534
- name: carpon_test
num_bytes: 388923332
num_examples: 574
- name: reptiles_test
num_bytes: 456981304
num_examples: 663
- name: diapers_test
num_bytes: 579411956
num_examples: 688
download_size: 6134997678
dataset_size: 6214753236
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: carpon_test
path: data/carpon_test-*
- split: reptiles_test
path: data/reptiles_test-*
- split: diapers_test
path: data/diapers_test-*
---
|
irds/lotte_lifestyle_dev_forum | ---
pretty_name: '`lotte/lifestyle/dev/forum`'
viewer: false
source_datasets: ['irds/lotte_lifestyle_dev']
task_categories:
- text-retrieval
---
# Dataset Card for `lotte/lifestyle/dev/forum`
The `lotte/lifestyle/dev/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/lifestyle/dev/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,076
- `qrels`: (relevance assessments); count=12,823
- For `docs`, use [`irds/lotte_lifestyle_dev`](https://huggingface.co/datasets/irds/lotte_lifestyle_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_lifestyle_dev_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_lifestyle_dev_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
|
JayalekshmiGopakumar/dataset_silcon | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: texts
sequence: string
- name: image
dtype: image
- name: label
dtype: string
splits:
- name: train
num_bytes: 1122257806.0
num_examples: 3000
- name: test
num_bytes: 118044994.0
num_examples: 300
download_size: 1234806135
dataset_size: 1240302800.0
---
# Dataset Card for "dataset_silcon"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
result-kand2-sdxl-wuerst-karlo/859be608 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 158
num_examples: 10
download_size: 1322
dataset_size: 158
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "859be608"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Mitsuki-Sakamoto/alpaca_farm-deberta-re-pref-64-fil_self_160m_bo16_2_mix_50_kl_0.1_prm_70m_thr_0.3_seed_3_t_1.0 | ---
dataset_info:
config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
- name: preference
dtype: int64
- name: output_1
dtype: string
- name: output_2
dtype: string
- name: reward_model_prompt_format
dtype: string
- name: gen_prompt_format
dtype: string
- name: gen_kwargs
struct:
- name: do_sample
dtype: bool
- name: max_new_tokens
dtype: int64
- name: pad_token_id
dtype: int64
- name: top_k
dtype: int64
- name: top_p
dtype: float64
- name: reward_1
dtype: float64
- name: reward_2
dtype: float64
- name: n_samples
dtype: int64
- name: reject_select
dtype: string
- name: index
dtype: int64
- name: prompt
dtype: string
- name: chosen
dtype: string
- name: rejected
dtype: string
- name: filtered_epoch
dtype: int64
- name: gen_reward
dtype: float64
- name: gen_response
dtype: string
splits:
- name: epoch_0
num_bytes: 43746769
num_examples: 18928
- name: epoch_1
num_bytes: 44289579
num_examples: 18928
- name: epoch_2
num_bytes: 44381844
num_examples: 18928
- name: epoch_3
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num_examples: 18928
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num_examples: 18928
- name: epoch_5
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num_examples: 18928
- name: epoch_6
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num_examples: 18928
- name: epoch_7
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- name: epoch_8
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num_examples: 18928
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num_bytes: 44452809
num_examples: 18928
- name: epoch_11
num_bytes: 44449673
num_examples: 18928
- name: epoch_12
num_bytes: 44450295
num_examples: 18928
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num_bytes: 44450566
num_examples: 18928
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num_examples: 18928
- name: epoch_16
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num_bytes: 44452774
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num_bytes: 44451585
num_examples: 18928
- name: epoch_28
num_bytes: 44454282
num_examples: 18928
- name: epoch_29
num_bytes: 44454264
num_examples: 18928
download_size: 701359199
dataset_size: 1332653002
configs:
- config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1
data_files:
- split: epoch_0
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_0-*
- split: epoch_1
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_1-*
- split: epoch_2
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_2-*
- split: epoch_3
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_3-*
- split: epoch_4
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_4-*
- split: epoch_5
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_5-*
- split: epoch_6
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_6-*
- split: epoch_7
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_7-*
- split: epoch_8
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_8-*
- split: epoch_9
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_9-*
- split: epoch_10
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_10-*
- split: epoch_11
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_11-*
- split: epoch_12
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_12-*
- split: epoch_13
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_13-*
- split: epoch_14
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_14-*
- split: epoch_15
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_15-*
- split: epoch_16
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_16-*
- split: epoch_17
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_17-*
- split: epoch_18
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_18-*
- split: epoch_19
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_19-*
- split: epoch_20
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_20-*
- split: epoch_21
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_21-*
- split: epoch_22
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_22-*
- split: epoch_23
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_23-*
- split: epoch_24
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_24-*
- split: epoch_25
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_25-*
- split: epoch_26
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_26-*
- split: epoch_27
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_27-*
- split: epoch_28
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_28-*
- split: epoch_29
path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_29-*
---
|
Aditya78b/codeparrot-java-all | ---
annotations_creators: []
language_creators:
- crowdsourced
- expert-generated
language:
- code
license:
- other
multilinguality:
- multilingual
pretty_name: github-code
size_categories:
- unknown
source_datasets: []
task_categories:
- text-generation
task_ids:
- language-modeling
---
# GitHub Code Dataset
## Dataset Description
The GitHub Code dataset consists of 115M code files from GitHub in 32 programming languages with 60 extensions totaling in 1TB of data. The dataset was created from the public GitHub dataset on Google BiqQuery.
### How to use it
The GitHub Code dataset is a very large dataset so for most use cases it is recommended to make use of the streaming API of `datasets`. You can load and iterate through the dataset with the following two lines of code:
```python
from datasets import load_dataset
ds = load_dataset("codeparrot/github-code", streaming=True, split="train")
print(next(iter(ds)))
#OUTPUT:
{
'code': "import mod189 from './mod189';\nvar value=mod189+1;\nexport default value;\n",
'repo_name': 'MirekSz/webpack-es6-ts',
'path': 'app/mods/mod190.js',
'language': 'JavaScript',
'license': 'isc',
'size': 73
}
```
You can see that besides the code, repo name, and path also the programming language, license, and the size of the file are part of the dataset. You can also filter the dataset for any subset of the 30 included languages (see the full list below) in the dataset. Just pass the list of languages as a list. E.g. if your dream is to build a Codex model for Dockerfiles use the following configuration:
```python
ds = load_dataset("codeparrot/github-code", streaming=True, split="train", languages=["Dockerfile"])
print(next(iter(ds))["code"])
#OUTPUT:
"""\
FROM rockyluke/ubuntu:precise
ENV DEBIAN_FRONTEND="noninteractive" \
TZ="Europe/Amsterdam"
...
"""
```
We also have access to the license of the origin repo of a file so we can filter for licenses in the same way we filtered for languages:
```python
ds = load_dataset("codeparrot/github-code", streaming=True, split="train", licenses=["mit", "isc"])
licenses = []
for element in iter(ds).take(10_000):
licenses.append(element["license"])
print(Counter(licenses))
#OUTPUT:
Counter({'mit': 9896, 'isc': 104})
```
Naturally, you can also download the full dataset. Note that this will download ~300GB compressed text data and the uncompressed dataset will take up ~1TB of storage:
```python
ds = load_dataset("codeparrot/github-code", split="train")
```
## Data Structure
### Data Instances
```python
{
'code': "import mod189 from './mod189';\nvar value=mod189+1;\nexport default value;\n",
'repo_name': 'MirekSz/webpack-es6-ts',
'path': 'app/mods/mod190.js',
'language': 'JavaScript',
'license': 'isc',
'size': 73
}
```
### Data Fields
|Field|Type|Description|
|---|---|---|
|code|string|content of source file|
|repo_name|string|name of the GitHub repository|
|path|string|path of file in GitHub repository|
|language|string|programming language as inferred by extension|
|license|string|license of GitHub repository|
|size|int|size of source file in bytes|
### Data Splits
The dataset only contains a train split.
## Languages
The dataset contains 30 programming languages with over 60 extensions:
```python
{
"Assembly": [".asm"],
"Batchfile": [".bat", ".cmd"],
"C": [".c", ".h"],
"C#": [".cs"],
"C++": [".cpp", ".hpp", ".c++", ".h++", ".cc", ".hh", ".C", ".H"],
"CMake": [".cmake"],
"CSS": [".css"],
"Dockerfile": [".dockerfile", "Dockerfile"],
"FORTRAN": ['.f90', '.f', '.f03', '.f08', '.f77', '.f95', '.for', '.fpp'],
"GO": [".go"],
"Haskell": [".hs"],
"HTML":[".html"],
"Java": [".java"],
"JavaScript": [".js"],
"Julia": [".jl"],
"Lua": [".lua"],
"Makefile": ["Makefile"],
"Markdown": [".md", ".markdown"],
"PHP": [".php", ".php3", ".php4", ".php5", ".phps", ".phpt"],
"Perl": [".pl", ".pm", ".pod", ".perl"],
"PowerShell": ['.ps1', '.psd1', '.psm1'],
"Python": [".py"],
"Ruby": [".rb"],
"Rust": [".rs"],
"SQL": [".sql"],
"Scala": [".scala"],
"Shell": [".sh", ".bash", ".command", ".zsh"],
"TypeScript": [".ts", ".tsx"],
"TeX": [".tex"],
"Visual Basic": [".vb"]
}
```
## Licenses
Each example is also annotated with the license of the associated repository. There are in total 15 licenses:
```python
[
'mit',
'apache-2.0',
'gpl-3.0',
'gpl-2.0',
'bsd-3-clause',
'agpl-3.0',
'lgpl-3.0',
'lgpl-2.1',
'bsd-2-clause',
'cc0-1.0',
'epl-1.0',
'mpl-2.0',
'unlicense',
'isc',
'artistic-2.0'
]
```
## Dataset Statistics
The dataset contains 115M files and the sum of all the source code file sizes is 873 GB (note that the size of the dataset is larger due to the extra fields). A breakdown per language is given in the plot and table below:
| | Language |File Count| Size (GB)|
|---:|:-------------|---------:|-------:|
| 0 | Java | 19548190 | 107.70 |
| 1 | C | 14143113 | 183.83 |
| 2 | JavaScript | 11839883 | 87.82 |
| 3 | HTML | 11178557 | 118.12 |
| 4 | PHP | 11177610 | 61.41 |
| 5 | Markdown | 8464626 | 23.09 |
| 6 | C++ | 7380520 | 87.73 |
| 7 | Python | 7226626 | 52.03 |
| 8 | C# | 6811652 | 36.83 |
| 9 | Ruby | 4473331 | 10.95 |
| 10 | GO | 2265436 | 19.28 |
| 11 | TypeScript | 1940406 | 24.59 |
| 12 | CSS | 1734406 | 22.67 |
| 13 | Shell | 1385648 | 3.01 |
| 14 | Scala | 835755 | 3.87 |
| 15 | Makefile | 679430 | 2.92 |
| 16 | SQL | 656671 | 5.67 |
| 17 | Lua | 578554 | 2.81 |
| 18 | Perl | 497949 | 4.70 |
| 19 | Dockerfile | 366505 | 0.71 |
| 20 | Haskell | 340623 | 1.85 |
| 21 | Rust | 322431 | 2.68 |
| 22 | TeX | 251015 | 2.15 |
| 23 | Batchfile | 236945 | 0.70 |
| 24 | CMake | 175282 | 0.54 |
| 25 | Visual Basic | 155652 | 1.91 |
| 26 | FORTRAN | 142038 | 1.62 |
| 27 | PowerShell | 136846 | 0.69 |
| 28 | Assembly | 82905 | 0.78 |
| 29 | Julia | 58317 | 0.29 |
## Dataset Creation
The dataset was created in two steps:
1. Files of with the extensions given in the list above were retrieved from the GitHub dataset on BigQuery (full query [here](https://huggingface.co/datasets/codeparrot/github-code/blob/main/query.sql)). The query was executed on _Mar 16, 2022, 6:23:39 PM UTC+1_.
2. Files with lines longer than 1000 characters and duplicates (exact duplicates ignoring whitespaces) were dropped (full preprocessing script [here](https://huggingface.co/datasets/codeparrot/github-code/blob/main/github_preprocessing.py)).
## Considerations for Using the Data
The dataset consists of source code from a wide range of repositories. As such they can potentially include harmful or biased code as well as sensitive information like passwords or usernames.
## Releases
You can load any older version of the dataset with the `revision` argument:
```Python
ds = load_dataset("codeparrot/github-code", revision="v1.0")
```
### v1.0
- Initial release of dataset
- The query was executed on _Feb 14, 2022, 12:03:16 PM UTC+1_
### v1.1
- Fix missing Scala/TypeScript
- Fix deduplication issue with inconsistent Python `hash`
- The query was executed on _Mar 16, 2022, 6:23:39 PM UTC+1_
|
jbilcke-hf/ai-tube-tik-tak-tok | ---
license: cc-by-nc-4.0
pretty_name: "Tik Tak Tok"
---
## Description
Tik Tak Tok - Est. 2023
## Model
HotshotXL
## Voice
Julian
## Orientation
Portrait
# Tags
- Short
- Dancing
# Style
tiktok video, instagram, beautiful, sharp, detailed
# Music
mainstream pop music
## Prompt
A channel generating short vertical videos, between 20 seconds and 60 seconds
Most videos are about people dancing, doing choregraphy, or talking selfies, filming their cats, daily life
(eg. going to a cafe, eating pizza outside etc) |
nblinh63/twitter_dataset_1712688043 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 78974
num_examples: 200
download_size: 37277
dataset_size: 78974
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
EthioNLP/EthioPOS | ---
license: mit
---
|
Falah/presidents_prompts | ---
dataset_info:
features:
- name: prompts
dtype: string
splits:
- name: train
num_bytes: 33180376
num_examples: 100000
download_size: 4643870
dataset_size: 33180376
---
# Dataset Card for "presidents_prompts"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
omree/uneven-side-walk | ---
dataset_info:
features:
- name: pixel_values
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 26515652.0
num_examples: 57
download_size: 26512665
dataset_size: 26515652.0
---
# Dataset Card for "uneven-side-walk"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
alexbuyan/video_comment | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 97776668
num_examples: 622231
- name: validation
num_bytes: 10975974
num_examples: 69137
download_size: 28717371
dataset_size: 108752642
---
# Dataset Card for "video_comment"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
KZMTx/redsolarsky-songs | ---
license: cc
---
|
open-llm-leaderboard/details_aisquared__dlite-v1-355m | ---
pretty_name: Evaluation run of aisquared/dlite-v1-355m
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [aisquared/dlite-v1-355m](https://huggingface.co/aisquared/dlite-v1-355m) 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_aisquared__dlite-v1-355m\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-27T20:11:22.634896](https://huggingface.co/datasets/open-llm-leaderboard/details_aisquared__dlite-v1-355m/blob/main/results_2023-10-27T20-11-22.634896.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\": 0.009123322147651007,\n\
\ \"em_stderr\": 0.0009737017705541621,\n \"f1\": 0.05341862416107383,\n\
\ \"f1_stderr\": 0.0014844140427647057,\n \"acc\": 0.26400947119179163,\n\
\ \"acc_stderr\": 0.0070152021067028955\n },\n \"harness|drop|3\":\
\ {\n \"em\": 0.009123322147651007,\n \"em_stderr\": 0.0009737017705541621,\n\
\ \"f1\": 0.05341862416107383,\n \"f1_stderr\": 0.0014844140427647057\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\
: 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.5280189423835833,\n\
\ \"acc_stderr\": 0.014030404213405791\n }\n}\n```"
repo_url: https://huggingface.co/aisquared/dlite-v1-355m
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_19T14_15_29.432225
path:
- '**/details_harness|arc:challenge|25_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_27T20_11_22.634896
path:
- '**/details_harness|drop|3_2023-10-27T20-11-22.634896.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-27T20-11-22.634896.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_27T20_11_22.634896
path:
- '**/details_harness|gsm8k|5_2023-10-27T20-11-22.634896.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-27T20-11-22.634896.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hellaswag|10_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:15:29.432225.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T14:15:29.432225.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T14:15:29.432225.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_27T20_11_22.634896
path:
- '**/details_harness|winogrande|5_2023-10-27T20-11-22.634896.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-27T20-11-22.634896.parquet'
- config_name: results
data_files:
- split: 2023_07_19T14_15_29.432225
path:
- results_2023-07-19T14:15:29.432225.parquet
- split: 2023_10_27T20_11_22.634896
path:
- results_2023-10-27T20-11-22.634896.parquet
- split: latest
path:
- results_2023-10-27T20-11-22.634896.parquet
---
# Dataset Card for Evaluation run of aisquared/dlite-v1-355m
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/aisquared/dlite-v1-355m
- **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 [aisquared/dlite-v1-355m](https://huggingface.co/aisquared/dlite-v1-355m) 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_aisquared__dlite-v1-355m",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-27T20:11:22.634896](https://huggingface.co/datasets/open-llm-leaderboard/details_aisquared__dlite-v1-355m/blob/main/results_2023-10-27T20-11-22.634896.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": 0.009123322147651007,
"em_stderr": 0.0009737017705541621,
"f1": 0.05341862416107383,
"f1_stderr": 0.0014844140427647057,
"acc": 0.26400947119179163,
"acc_stderr": 0.0070152021067028955
},
"harness|drop|3": {
"em": 0.009123322147651007,
"em_stderr": 0.0009737017705541621,
"f1": 0.05341862416107383,
"f1_stderr": 0.0014844140427647057
},
"harness|gsm8k|5": {
"acc": 0.0,
"acc_stderr": 0.0
},
"harness|winogrande|5": {
"acc": 0.5280189423835833,
"acc_stderr": 0.014030404213405791
}
}
```
### 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] |
mfidabel/wikipedia_fhe | ---
language:
- en
dataset_info:
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 13244361.666935142
num_examples: 4219
download_size: 29643821
dataset_size: 13244361.666935142
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
tj-solergibert/SRV-Europarl-ST-processed-mt-es | ---
dataset_info:
features:
- name: source_text
dtype: string
- name: dest_text
dtype: string
- name: dest_lang
dtype: string
splits:
- name: train
num_bytes: 133686385.86889735
num_examples: 553896
- name: valid
num_bytes: 17228528.617501996
num_examples: 74770
- name: test
num_bytes: 17351036.302417863
num_examples: 77952
download_size: 132237051
dataset_size: 168265950.78881723
---
# Dataset Card for "SRV-Europarl-ST-processed-mt-es"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Nan-Do/code-search-net-javascript | ---
dataset_info:
features:
- name: repo
dtype: string
- name: path
dtype: string
- name: func_name
dtype: string
- name: original_string
dtype: string
- name: language
dtype: string
- name: code
dtype: string
- name: code_tokens
sequence: string
- name: docstring
dtype: string
- name: docstring_tokens
sequence: string
- name: sha
dtype: string
- name: url
dtype: string
- name: partition
dtype: string
- name: summary
dtype: string
splits:
- name: train
num_bytes: 543032741
num_examples: 138155
download_size: 182237165
dataset_size: 543032741
license: apache-2.0
task_categories:
- text-generation
- text2text-generation
- summarization
language:
- en
tags:
- code
- javascript
- CodeSearchNet
- summary
pretty_name: JavaScript CodeSearchNet with Summaries
---
# Dataset Card for "code-search-net-javascript"
## Dataset Description
- **Homepage:** None
- **Repository:** https://huggingface.co/datasets/Nan-Do/code-search-net-JavaScript
- **Paper:** None
- **Leaderboard:** None
- **Point of Contact:** [@Nan-Do](https://github.com/Nan-Do)
### Dataset Summary
This dataset is the JavaScript portion of the CodeSarchNet annotated with a summary column.
The code-search-net dataset includes open source functions that include comments found at GitHub.
The summary is a short description of what the function does.
### Languages
The dataset's comments are in English and the functions are coded in JavaScript
### Data Splits
Train, test, validation labels are included in the dataset as a column.
## Dataset Creation
May of 2023
### Curation Rationale
This dataset can be used to generate instructional (or many other interesting) datasets that are useful to train LLMs
### Source Data
The CodeSearchNet dataset can be found at https://www.kaggle.com/datasets/omduggineni/codesearchnet
### Annotations
This datasets include a summary column including a short description of the function.
#### Annotation process
The annotation procedure was done using [Salesforce](https://huggingface.co/Salesforce) T5 summarization models.
A sample notebook of the process can be found at https://github.com/Nan-Do/OpenAssistantInstructionResponsePython
The annontations have been cleaned to make sure there are no repetitions and/or meaningless summaries. (some may still be present in the dataset)
### Licensing Information
Apache 2.0 |
OdiaGenAIdata/pre_train_odia_data_processed | ---
license: cc-by-nc-sa-4.0
language:
- or
pretty_name: Odia LLM Pre-Train Dataset
size_categories:
- 1M<n<10M
---
## About
This dataset is curated from different open-source datasets and prepared Odia data using different techniques (web scraping, OCR) and manually corrected by the Odia native speakers.
The dataset is uniformly processed and de-duplicated for easy usage.
## Use Cases
The dataset has many use cases such as:
* Pre-training Odia LLM,
* Building the Odia BERT model,
* Building Odia tokenizer,
* Back translation (MT)
## Dataset Statistics
## Contributors
* Dr. Shantipriya Parida
* Sambit Sekhar
* Debasish Dhal
* Pritiprava Mishra
* Suman Kumar Maharana
* Purushottam Kumar
* Priyabrata Jena
* Dr. Kalyanamalini Sahoo
## Citation
If you find this repository useful, please consider giving 👏 and citing:
```
@misc{Odia_LLM_Corpus,
author = {Shantipriya Parida and Sambit Sekhar and Debasish Dhal and Pritiprava Mishra and Suman Kumar Maharana and Purushottam Kumar and Priyabrata Jena and Kalyanamalini Sahoo},
title = {Large Odia LLM Corpus},
year = {2024},
publisher = {Hugging Face},
journal = {Hugging Face repository},
howpublished = {\url{https://huggingface.co/OdiaGenAI}},
}
```
## License
This work is licensed under a
[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].
[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]
[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png
[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg |
projecte-aina/parlament_parla | ---
annotations_creators:
- found
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- automatic-speech-recognition
- text-generation
task_ids:
- language-modeling
- speaker-identification
pretty_name: ParlamentParla
---
# Dataset Card for ParlamentParla
## 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:** https://zenodo.org/record/5541827
- **Repository:** https://github.com/CollectivaT-dev/ParlamentParla
- **Paper:** ParlamentParla: [A Speech Corpus of Catalan Parliamentary Sessions.](http://www.lrec-conf.org/proceedings/lrec2022/workshops/ParlaCLARINIII/2022.parlaclariniii-1.0.pdf#page=135)
- **Point of Contact:** [Baybars Kulebi](mailto:baybars.kulebi@bsc.es)
### Dataset Summary
This is the ParlamentParla speech corpus for Catalan prepared by Col·lectivaT. The audio segments were extracted from recordings the Catalan Parliament (Parlament de Catalunya) plenary sessions, which took place between 2007/07/11 - 2018/07/17. We aligned the transcriptions with the recordings and extracted the corpus. The content belongs to the Catalan Parliament and the data is released conforming their terms of use.
Preparation of this corpus was partly supported by the Department of Culture of the Catalan autonomous government, and the v2.0 was supported by the Barcelona Supercomputing Center, within the framework of Projecte AINA of the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya.
As of v2.0 the corpus is separated into 211 hours of clean and 400 hours of other quality segments. Furthermore, each speech segment is tagged with its speaker and each speaker with their gender. The statistics are detailed in the readme file.
### Supported Tasks and Leaderboards
The dataset can be used for:
- Language Modeling.
- Automatic Speech Recognition (ASR) transcribes utterances into words.
- Speaker Identification (SI) classifies each utterance for its speaker identity as a multi-class classification, where speakers are in the same predefined set for both training and testing.
### Languages
The dataset is in Catalan (`ca-ES`).
## Dataset Structure
### Data Instances
```
{
'path': 'clean_train/c/c/ccca4790a55aba3e6bcf_63.88_74.06.wav'
'audio': {
'path': 'clean_train/c/c/ccca4790a55aba3e6bcf_63.88_74.06.wav',
'array': array([-6.10351562e-05, -6.10351562e-05, -1.22070312e-04, ...,
-1.22070312e-04, 0.00000000e+00, -3.05175781e-05]),
'sampling_rate': 16000
},
'speaker_id': 167,
'sentence': "alguns d'ells avui aquí presents un agraïment a aquells que mantenen viva la memòria aquest acte de reparació i dignitat és",
'gender': 0,
'duration': 10.18
}
```
### Data Fields
- `path` (str): The path to the audio file.
- `audio` (dict): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling
rate. 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]`.
- `speaker_id` (int): The speaker ID.
- `sentence` (str): The sentence the user was prompted to speak.
- `gender` (ClassLabel): The gender of the speaker (0: 'F', 1: 'M').
- `duration` (float): Duration of the speech.
### Data Splits
The dataset is split in: "train", "validation" and "test".
## Dataset Creation
The dataset is created by aligning the parliamentary session transcripts
and the audiovisual content. For more detailed information please consult
this [paper](http://www.lrec-conf.org/proceedings/lrec2022/workshops/ParlaCLARINIII/2022.parlaclariniii-1.0.pdf#page=135).
### Curation Rationale
We created this corpus to contribute to the development of language models in Catalan, a low-resource language.
### Source Data
#### Initial Data Collection and Normalization
The audio segments were extracted from recordings the Catalan Parliament
(Parlament de Catalunya) plenary sessions, which took place between 2007/07/11 -
2018/07/17. The cleaning procedures are in the archived repository [Long Audio
Aligner](https://github.com/gullabi/long-audio-aligner)
#### Who are the source language producers?
The parliamentary members of the legislatures between 2007/07/11 -
2018/07/17
### Annotations
The dataset is unannotated.
#### Annotation process
[N/A]
#### Who are the annotators?
[N/A]
### Personal and Sensitive Information
The initial content is publicly available furthermore, the identities of
the parliamentary members are anonymized.
## Considerations for Using the Data
### Social Impact of Dataset
We hope this corpus contributes to the development of language models in
Catalan, a low-resource language.
### Discussion of Biases
This dataset has a gender bias, however since the speakers are tagged according to
their genders, creating a balanced subcorpus is possible.
| Subcorpus | Gender | Duration (h) |
|-------------|----------|------------|
| other_test | F | 2.516 |
| other_dev | F | 2.701 |
| other_train | F | 109.68 |
| other_test | M | 2.631 |
| other_dev | M | 2.513 |
| other_train | M | 280.196 |
|*other total*| | 400.239 |
| clean_test | F | 2.707 |
| clean_dev | F | 2.576 |
| clean_train | F | 77.905 |
| clean_test | M | 2.516 |
| clean_dev | M | 2.614 |
| clean_train | M | 123.162 |
|*clean total*| | 211.48 |
|*Total* | | 611.719 |
### Other Known Limitations
The text corpus belongs to the domain of Catalan politics
## Additional Information
### Dataset Curators
Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
### Licensing Information
[Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/).
### Citation Information
```
@dataset{kulebi_baybars_2021_5541827,
author = {Külebi, Baybars},
title = {{ParlamentParla - Speech corpus of Catalan
Parliamentary sessions}},
month = oct,
year = 2021,
publisher = {Zenodo},
version = {v2.0},
doi = {10.5281/zenodo.5541827},
url = {https://doi.org/10.5281/zenodo.5541827}
}
```
For the paper:
```
@inproceedings{kulebi2022parlamentparla,
title={ParlamentParla: A Speech Corpus of Catalan Parliamentary Sessions},
author={K{\"u}lebi, Baybars and Armentano-Oller, Carme and Rodr{\'\i}guez-Penagos, Carlos and Villegas, Marta},
booktitle={Workshop on Creating, Enriching and Using Parliamentary Corpora},
volume={125},
number={130},
pages={125},
year={2022}
}
```
### Contributions
Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.
|
CreativeLang/pun_detection_semeval2017_task7 | ---
license: cc-by-2.0
---
# Semeval2017 Task 7: Pun Detection
- paper: [SemEval-2017 Task 7: Detection and Interpretation of English Puns](https://aclanthology.org/S17-2005/) at Semeval 2017.
Metadata in Creative Language Toolkit ([CLTK](https://github.com/liyucheng09/cltk))
- CL Type: Pun
- Task Type: Detection
- Size: 4k
- Created time: 2017 |
open-llm-leaderboard/details_NousResearch__Nous-Hermes-2-Mixtral-8x7B-DPO | ---
pretty_name: Evaluation run of NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)\
\ 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_NousResearch__Nous-Hermes-2-Mixtral-8x7B-DPO\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-22T17:09:50.643842](https://huggingface.co/datasets/open-llm-leaderboard/details_NousResearch__Nous-Hermes-2-Mixtral-8x7B-DPO/blob/main/results_2024-01-22T17-09-50.643842.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\": 0.7224125718980299,\n\
\ \"acc_stderr\": 0.030022741290236767,\n \"acc_norm\": 0.7240829737285515,\n\
\ \"acc_norm_stderr\": 0.03062607991215834,\n \"mc1\": 0.3880048959608323,\n\
\ \"mc1_stderr\": 0.01705876150134797,\n \"mc2\": 0.5482610472622913,\n\
\ \"mc2_stderr\": 0.014924708991833662\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6953924914675768,\n \"acc_stderr\": 0.013449522109932487,\n\
\ \"acc_norm\": 0.7107508532423208,\n \"acc_norm_stderr\": 0.013250012579393441\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6870145389364668,\n\
\ \"acc_stderr\": 0.004627607991626919,\n \"acc_norm\": 0.8729336785500896,\n\
\ \"acc_norm_stderr\": 0.0033236659644121946\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6888888888888889,\n\
\ \"acc_stderr\": 0.039992628766177214,\n \"acc_norm\": 0.6888888888888889,\n\
\ \"acc_norm_stderr\": 0.039992628766177214\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.8026315789473685,\n \"acc_stderr\": 0.03238981601699397,\n\
\ \"acc_norm\": 0.8026315789473685,\n \"acc_norm_stderr\": 0.03238981601699397\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.73,\n\
\ \"acc_stderr\": 0.0446196043338474,\n \"acc_norm\": 0.73,\n \
\ \"acc_norm_stderr\": 0.0446196043338474\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7924528301886793,\n \"acc_stderr\": 0.02495991802891127,\n\
\ \"acc_norm\": 0.7924528301886793,\n \"acc_norm_stderr\": 0.02495991802891127\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8333333333333334,\n\
\ \"acc_stderr\": 0.031164899666948617,\n \"acc_norm\": 0.8333333333333334,\n\
\ \"acc_norm_stderr\": 0.031164899666948617\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.55,\n \"acc_stderr\": 0.04999999999999999,\n \
\ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.04999999999999999\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\": 0.66,\n\
\ \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness|hendrycksTest-college_mathematics|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-college_medicine|5\": {\n \"acc\": 0.6936416184971098,\n\
\ \"acc_stderr\": 0.035149425512674394,\n \"acc_norm\": 0.6936416184971098,\n\
\ \"acc_norm_stderr\": 0.035149425512674394\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.49019607843137253,\n \"acc_stderr\": 0.04974229460422817,\n\
\ \"acc_norm\": 0.49019607843137253,\n \"acc_norm_stderr\": 0.04974229460422817\n\
\ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\
: {\n \"acc\": 0.6936170212765957,\n \"acc_stderr\": 0.030135906478517563,\n\
\ \"acc_norm\": 0.6936170212765957,\n \"acc_norm_stderr\": 0.030135906478517563\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.6491228070175439,\n\
\ \"acc_stderr\": 0.044895393502706986,\n \"acc_norm\": 0.6491228070175439,\n\
\ \"acc_norm_stderr\": 0.044895393502706986\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.6896551724137931,\n \"acc_stderr\": 0.03855289616378948,\n\
\ \"acc_norm\": 0.6896551724137931,\n \"acc_norm_stderr\": 0.03855289616378948\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.5026455026455027,\n \"acc_stderr\": 0.025750949678130387,\n \"\
acc_norm\": 0.5026455026455027,\n \"acc_norm_stderr\": 0.025750949678130387\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.5714285714285714,\n\
\ \"acc_stderr\": 0.04426266681379909,\n \"acc_norm\": 0.5714285714285714,\n\
\ \"acc_norm_stderr\": 0.04426266681379909\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\
: 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-high_school_biology|5\"\
: {\n \"acc\": 0.8516129032258064,\n \"acc_stderr\": 0.020222737554330378,\n\
\ \"acc_norm\": 0.8516129032258064,\n \"acc_norm_stderr\": 0.020222737554330378\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.5911330049261084,\n \"acc_stderr\": 0.03459058815883233,\n \"\
acc_norm\": 0.5911330049261084,\n \"acc_norm_stderr\": 0.03459058815883233\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\
: {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.03225078108306289,\n\
\ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.03225078108306289\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.8535353535353535,\n \"acc_stderr\": 0.025190921114603915,\n \"\
acc_norm\": 0.8535353535353535,\n \"acc_norm_stderr\": 0.025190921114603915\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9378238341968912,\n \"acc_stderr\": 0.017426974154240524,\n\
\ \"acc_norm\": 0.9378238341968912,\n \"acc_norm_stderr\": 0.017426974154240524\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6897435897435897,\n \"acc_stderr\": 0.02345467488940429,\n \
\ \"acc_norm\": 0.6897435897435897,\n \"acc_norm_stderr\": 0.02345467488940429\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.34814814814814815,\n \"acc_stderr\": 0.029045600290616258,\n \
\ \"acc_norm\": 0.34814814814814815,\n \"acc_norm_stderr\": 0.029045600290616258\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.7941176470588235,\n \"acc_stderr\": 0.026265024608275882,\n\
\ \"acc_norm\": 0.7941176470588235,\n \"acc_norm_stderr\": 0.026265024608275882\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.45695364238410596,\n \"acc_stderr\": 0.04067325174247443,\n \"\
acc_norm\": 0.45695364238410596,\n \"acc_norm_stderr\": 0.04067325174247443\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8954128440366973,\n \"acc_stderr\": 0.013120530245265587,\n \"\
acc_norm\": 0.8954128440366973,\n \"acc_norm_stderr\": 0.013120530245265587\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.6620370370370371,\n \"acc_stderr\": 0.03225941352631295,\n \"\
acc_norm\": 0.6620370370370371,\n \"acc_norm_stderr\": 0.03225941352631295\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8676470588235294,\n \"acc_stderr\": 0.023784297520918853,\n \"\
acc_norm\": 0.8676470588235294,\n \"acc_norm_stderr\": 0.023784297520918853\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.8945147679324894,\n \"acc_stderr\": 0.019995560723758556,\n \
\ \"acc_norm\": 0.8945147679324894,\n \"acc_norm_stderr\": 0.019995560723758556\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7623318385650224,\n\
\ \"acc_stderr\": 0.02856807946471428,\n \"acc_norm\": 0.7623318385650224,\n\
\ \"acc_norm_stderr\": 0.02856807946471428\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.8778625954198473,\n \"acc_stderr\": 0.028718776889342344,\n\
\ \"acc_norm\": 0.8778625954198473,\n \"acc_norm_stderr\": 0.028718776889342344\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.859504132231405,\n \"acc_stderr\": 0.03172233426002158,\n \"acc_norm\"\
: 0.859504132231405,\n \"acc_norm_stderr\": 0.03172233426002158\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8425925925925926,\n\
\ \"acc_stderr\": 0.03520703990517963,\n \"acc_norm\": 0.8425925925925926,\n\
\ \"acc_norm_stderr\": 0.03520703990517963\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.803680981595092,\n \"acc_stderr\": 0.031207970394709218,\n\
\ \"acc_norm\": 0.803680981595092,\n \"acc_norm_stderr\": 0.031207970394709218\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5446428571428571,\n\
\ \"acc_stderr\": 0.04726835553719097,\n \"acc_norm\": 0.5446428571428571,\n\
\ \"acc_norm_stderr\": 0.04726835553719097\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8543689320388349,\n \"acc_stderr\": 0.034926064766237906,\n\
\ \"acc_norm\": 0.8543689320388349,\n \"acc_norm_stderr\": 0.034926064766237906\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9017094017094017,\n\
\ \"acc_stderr\": 0.019503444900757567,\n \"acc_norm\": 0.9017094017094017,\n\
\ \"acc_norm_stderr\": 0.019503444900757567\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.8,\n \"acc_stderr\": 0.04020151261036844,\n \
\ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.04020151261036844\n },\n\
\ \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.879948914431673,\n\
\ \"acc_stderr\": 0.011622736692041268,\n \"acc_norm\": 0.879948914431673,\n\
\ \"acc_norm_stderr\": 0.011622736692041268\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.8005780346820809,\n \"acc_stderr\": 0.02151190065425255,\n\
\ \"acc_norm\": 0.8005780346820809,\n \"acc_norm_stderr\": 0.02151190065425255\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.5720670391061452,\n\
\ \"acc_stderr\": 0.016547887997416112,\n \"acc_norm\": 0.5720670391061452,\n\
\ \"acc_norm_stderr\": 0.016547887997416112\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.8071895424836601,\n \"acc_stderr\": 0.022589318888176703,\n\
\ \"acc_norm\": 0.8071895424836601,\n \"acc_norm_stderr\": 0.022589318888176703\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7909967845659164,\n\
\ \"acc_stderr\": 0.02309314039837422,\n \"acc_norm\": 0.7909967845659164,\n\
\ \"acc_norm_stderr\": 0.02309314039837422\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.8549382716049383,\n \"acc_stderr\": 0.019594877019727962,\n\
\ \"acc_norm\": 0.8549382716049383,\n \"acc_norm_stderr\": 0.019594877019727962\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.5283687943262412,\n \"acc_stderr\": 0.02977945095730305,\n \
\ \"acc_norm\": 0.5283687943262412,\n \"acc_norm_stderr\": 0.02977945095730305\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5554106910039114,\n\
\ \"acc_stderr\": 0.012691575792657112,\n \"acc_norm\": 0.5554106910039114,\n\
\ \"acc_norm_stderr\": 0.012691575792657112\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.7867647058823529,\n \"acc_stderr\": 0.02488097151229426,\n\
\ \"acc_norm\": 0.7867647058823529,\n \"acc_norm_stderr\": 0.02488097151229426\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.7875816993464052,\n \"acc_stderr\": 0.016547148636203147,\n \
\ \"acc_norm\": 0.7875816993464052,\n \"acc_norm_stderr\": 0.016547148636203147\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6909090909090909,\n\
\ \"acc_stderr\": 0.044262946482000985,\n \"acc_norm\": 0.6909090909090909,\n\
\ \"acc_norm_stderr\": 0.044262946482000985\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.8122448979591836,\n \"acc_stderr\": 0.025000256039546198,\n\
\ \"acc_norm\": 0.8122448979591836,\n \"acc_norm_stderr\": 0.025000256039546198\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8706467661691543,\n\
\ \"acc_stderr\": 0.023729830881018526,\n \"acc_norm\": 0.8706467661691543,\n\
\ \"acc_norm_stderr\": 0.023729830881018526\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.91,\n \"acc_stderr\": 0.028762349126466108,\n \
\ \"acc_norm\": 0.91,\n \"acc_norm_stderr\": 0.028762349126466108\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5060240963855421,\n\
\ \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.5060240963855421,\n\
\ \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8947368421052632,\n \"acc_stderr\": 0.02353755765789255,\n\
\ \"acc_norm\": 0.8947368421052632,\n \"acc_norm_stderr\": 0.02353755765789255\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3880048959608323,\n\
\ \"mc1_stderr\": 0.01705876150134797,\n \"mc2\": 0.5482610472622913,\n\
\ \"mc2_stderr\": 0.014924708991833662\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8310970797158642,\n \"acc_stderr\": 0.010529981411838911\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7164518574677786,\n \
\ \"acc_stderr\": 0.012415070917508125\n }\n}\n```"
repo_url: https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO
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_16T04_44_16.630676
path:
- '**/details_harness|arc:challenge|25_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|arc:challenge|25_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|gsm8k|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|gsm8k|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hellaswag|10_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hellaswag|10_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-16T04-44-16.630676.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T17-09-50.643842.parquet'
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- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T17-09-50.643842.parquet'
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- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T17-09-50.643842.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T17-09-50.643842.parquet'
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
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path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-22T17-09-50.643842.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- '**/details_harness|winogrande|5_2024-01-16T04-44-16.630676.parquet'
- split: 2024_01_22T17_09_50.643842
path:
- '**/details_harness|winogrande|5_2024-01-22T17-09-50.643842.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-22T17-09-50.643842.parquet'
- config_name: results
data_files:
- split: 2024_01_16T04_44_16.630676
path:
- results_2024-01-16T04-44-16.630676.parquet
- split: 2024_01_22T17_09_50.643842
path:
- results_2024-01-22T17-09-50.643842.parquet
- split: latest
path:
- results_2024-01-22T17-09-50.643842.parquet
---
# Dataset Card for Evaluation run of NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO) 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_NousResearch__Nous-Hermes-2-Mixtral-8x7B-DPO",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-22T17:09:50.643842](https://huggingface.co/datasets/open-llm-leaderboard/details_NousResearch__Nous-Hermes-2-Mixtral-8x7B-DPO/blob/main/results_2024-01-22T17-09-50.643842.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": 0.7224125718980299,
"acc_stderr": 0.030022741290236767,
"acc_norm": 0.7240829737285515,
"acc_norm_stderr": 0.03062607991215834,
"mc1": 0.3880048959608323,
"mc1_stderr": 0.01705876150134797,
"mc2": 0.5482610472622913,
"mc2_stderr": 0.014924708991833662
},
"harness|arc:challenge|25": {
"acc": 0.6953924914675768,
"acc_stderr": 0.013449522109932487,
"acc_norm": 0.7107508532423208,
"acc_norm_stderr": 0.013250012579393441
},
"harness|hellaswag|10": {
"acc": 0.6870145389364668,
"acc_stderr": 0.004627607991626919,
"acc_norm": 0.8729336785500896,
"acc_norm_stderr": 0.0033236659644121946
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.43,
"acc_stderr": 0.049756985195624284,
"acc_norm": 0.43,
"acc_norm_stderr": 0.049756985195624284
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6888888888888889,
"acc_stderr": 0.039992628766177214,
"acc_norm": 0.6888888888888889,
"acc_norm_stderr": 0.039992628766177214
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.8026315789473685,
"acc_stderr": 0.03238981601699397,
"acc_norm": 0.8026315789473685,
"acc_norm_stderr": 0.03238981601699397
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.73,
"acc_stderr": 0.0446196043338474,
"acc_norm": 0.73,
"acc_norm_stderr": 0.0446196043338474
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7924528301886793,
"acc_stderr": 0.02495991802891127,
"acc_norm": 0.7924528301886793,
"acc_norm_stderr": 0.02495991802891127
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.8333333333333334,
"acc_stderr": 0.031164899666948617,
"acc_norm": 0.8333333333333334,
"acc_norm_stderr": 0.031164899666948617
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.55,
"acc_stderr": 0.04999999999999999,
"acc_norm": 0.55,
"acc_norm_stderr": 0.04999999999999999
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.66,
"acc_stderr": 0.04760952285695237,
"acc_norm": 0.66,
"acc_norm_stderr": 0.04760952285695237
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.43,
"acc_stderr": 0.049756985195624284,
"acc_norm": 0.43,
"acc_norm_stderr": 0.049756985195624284
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6936416184971098,
"acc_stderr": 0.035149425512674394,
"acc_norm": 0.6936416184971098,
"acc_norm_stderr": 0.035149425512674394
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.49019607843137253,
"acc_stderr": 0.04974229460422817,
"acc_norm": 0.49019607843137253,
"acc_norm_stderr": 0.04974229460422817
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.81,
"acc_stderr": 0.039427724440366234,
"acc_norm": 0.81,
"acc_norm_stderr": 0.039427724440366234
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.6936170212765957,
"acc_stderr": 0.030135906478517563,
"acc_norm": 0.6936170212765957,
"acc_norm_stderr": 0.030135906478517563
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.6491228070175439,
"acc_stderr": 0.044895393502706986,
"acc_norm": 0.6491228070175439,
"acc_norm_stderr": 0.044895393502706986
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.6896551724137931,
"acc_stderr": 0.03855289616378948,
"acc_norm": 0.6896551724137931,
"acc_norm_stderr": 0.03855289616378948
},
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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. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] |
LauraExp/Donut | ---
dataset_info:
features:
- name: image
dtype: image
- name: ground_truth
dtype: string
splits:
- name: train
num_bytes: 21034569.0
num_examples: 16
- name: test
num_bytes: 5895696.0
num_examples: 4
download_size: 23582848
dataset_size: 26930265.0
---
|
presencesw/pubmed_envi_stage_2 | ---
dataset_info:
features:
- name: en
dtype: string
- name: vi
dtype: string
splits:
- name: train
num_bytes: 20078331248.81415
num_examples: 9093445
download_size: 12469954153
dataset_size: 20078331248.81415
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
DynamicSuperb/SpeakerVerification_LibriSpeech-TestClean | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: file
dtype: string
- name: audio
dtype: audio
- name: file2
dtype: string
- name: audio2
dtype: audio
- name: instruction
dtype: string
- name: label
dtype: string
splits:
- name: test
num_bytes: 59936455.24
num_examples: 200
download_size: 48492503
dataset_size: 59936455.24
---
# Dataset Card for "SpeakerVerification_LibriSpeechTestClean"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
justinian336/news-and-blogs | ---
dataset_info:
features:
- name: title
dtype: string
- name: content
dtype: string
splits:
- name: train
num_bytes: 11785675.449565798
num_examples: 2972
download_size: 7254802
dataset_size: 11785675.449565798
---
# Dataset Card for "news-and-blogs"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
qgyd2021/h_novel | ---
task_categories:
- text-generation
language:
- zh
tags:
- art
size_categories:
- 100M<n<1B
---
## H Novel
```text
SQ小说, 用于制作特殊的 GPT 语言模型.
```
|
AppleHarem/unicorn_azurlane | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of unicorn (Azur Lane)
This is the dataset of unicorn (Azur Lane), containing 200 images and their tags.
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)).([LittleAppleWebUI](https://github.com/LittleApple-fp16/LittleAppleWebUI))
| Name | Images | Download | Description |
|:----------------|---------:|:----------------------------------------|:-----------------------------------------------------------------------------------------|
| raw | 200 | [Download](dataset-raw.zip) | Raw data with meta information. |
| raw-stage3 | 522 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. |
| raw-stage3-eyes | 597 | [Download](dataset-raw-stage3-eyes.zip) | 3-stage cropped (with eye-focus) raw data with meta information. |
| 384x512 | 200 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. |
| 512x704 | 200 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. |
| 640x880 | 200 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. |
| stage3-640 | 522 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. |
| stage3-800 | 522 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. |
| stage3-p512-640 | 323 | [Download](dataset-stage3-p512-640.zip) | 3-stage cropped dataset with the area not less than 512x512 pixels. |
| stage3-eyes-640 | 597 | [Download](dataset-stage3-eyes-640.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 640 pixels. |
| stage3-eyes-800 | 597 | [Download](dataset-stage3-eyes-800.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 800 pixels. |
|
embedding-data/WikiAnswers | ---
license: mit
language:
- en
paperswithcode_id: embedding-data/WikiAnswers
pretty_name: WikiAnswers
task_categories:
- sentence-similarity
- paraphrase-mining
task_ids:
- semantic-similarity-classification
---
# Dataset Card for "WikiAnswers"
## 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:** [https://github.com/afader/oqa#wikianswers-corpus](https://github.com/afader/oqa#wikianswers-corpus)
- **Repository:** [More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
- **Paper:** [More Information Needed](https://doi.org/10.1145/2623330.2623677)
- **Point of Contact:** [Anthony Fader](https://dl.acm.org/profile/81324489111), [Luke Zettlemoyer](https://dl.acm.org/profile/81100527621), [Oren Etzioni](https://dl.acm.org/profile/99658633129)
### Dataset Summary
The WikiAnswers corpus contains clusters of questions tagged by WikiAnswers users as paraphrases.
Each cluster optionally contains an answer provided by WikiAnswers users. There are 30,370,994 clusters containing an average of 25 questions per cluster. 3,386,256 (11%) of the clusters have an answer.
### Supported Tasks
- [Sentence Transformers](https://huggingface.co/sentence-transformers) training; useful for semantic search and sentence similarity.
### Languages
- English.
## Dataset Structure
Each example in the dataset contains 25 equivalent sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value".
```
{"set": [sentence_1, sentence_2, ..., sentence_25]}
{"set": [sentence_1, sentence_2, ..., sentence_25]}
...
{"set": [sentence_1, sentence_2, ..., sentence_25]}
```
This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar sentences.
### Usage Example
Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
```python
from datasets import load_dataset
dataset = load_dataset("embedding-data/WikiAnswers")
```
The dataset is loaded as a `DatasetDict` and has the format for `N` examples:
```python
DatasetDict({
train: Dataset({
features: ['set'],
num_rows: N
})
})
```
Review an example `i` with:
```python
dataset["train"][i]["set"]
```
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
#### Who are the source language producers?
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
### Annotations
#### Annotation process
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
#### Who are the annotators?
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
### Personal and Sensitive Information
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
### Discussion of Biases
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
### Other Known Limitations
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
## Additional Information
### Dataset Curators
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
### Licensing Information
[More Information Needed](https://github.com/afader/oqa#wikianswers-corpus)
### Citation Information
```
@inproceedings{Fader14,
author = {Anthony Fader and Luke Zettlemoyer and Oren Etzioni},
title = {{Open Question Answering Over Curated and Extracted
Knowledge Bases}},
booktitle = {KDD},
year = {2014}
}
```
### Contributions
|
sam-mosaic/hhrlhf_evol_chatml | ---
language: en
dataset_info:
features:
- name: prompt
dtype: string
- name: response
dtype: string
splits:
- name: train
num_bytes: 302247789
num_examples: 217107
- name: test
num_bytes: 17609162
num_examples: 16555
download_size: 139692649
dataset_size: 319856951
---
# Dataset Card for "hhrlhf_evol_chatml"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
remg1997/speech_wikimedia | ---
license: cc
---
|
atharvapawar/part4_dataSorted_Diversevul_llama2_dataset | ---
license: mit
---
|
magicr/BuboGPT | ---
license: apache-2.0
---
|
jryan-pol/flags | ---
configs:
- config_name: default
data_files:
- split: train
path: data.csv
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### 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?
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### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
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### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
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## Additional Information
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### Contributions
[More Information Needed] |
heliosprime/twitter_dataset_1713052558 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 13583
num_examples: 30
download_size: 9315
dataset_size: 13583
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "twitter_dataset_1713052558"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
quyanh/helm-samsum-dolly-lima-cot | ---
dataset_info:
features:
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 28230011.540207386
num_examples: 30963
download_size: 19770554
dataset_size: 28230011.540207386
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "helm-samsum-dolly-lima-cot"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
sungmogi/en2ko_hiphop | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
dataset_info:
features:
- name: id
dtype: int64
- name: translation
struct:
- name: en
dtype: string
- name: ko
dtype: string
splits:
- name: train
num_bytes: 5061272.804687347
num_examples: 46158
- name: test
num_bytes: 281254.92317741335
num_examples: 2565
- name: valid
num_bytes: 281145.272135239
num_examples: 2564
download_size: 4172120
dataset_size: 5623673
task_categories:
- translation
language:
- en
- ko
pretty_name: en2ko_hiphop
size_categories:
- 10K<n<100K
---
# Dataset Card for "en2ko_hiphop"
## Copyright Disclaimer
The dataset "en2ko_hiphop" was curated from publicly available sources and is believed to be in the public domain. The translations provided in this dataset are the work of volunteers and members of the community, and they have been collected and curated to facilitate research and analysis. However, it is important to acknowledge that copyright issues cannot be entirely ruled out. Therefore, users of the dataset should exercise caution when using it. The author of en2ko_hiphop does not assume any legal responsibility for the use of the dataset. If you have any questions or concerns regarding the dataset's copyright status, please contact the author at sungcho2023@u.northwestern.edu.
## Acknowledgements
I gratefully acknowledge DanceD(http://danced.co.kr/) of Korean Hiphop community HIPHOPLE(https://hiphople.com/). All English-to-Korean translations have been provided by DanceD. |
nz/closest_to_5000_range_1000_to_9000_55k | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: chosen
dtype: string
- name: rejected
dtype: string
splits:
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num_bytes: 20890692.52734106
num_examples: 55000
- name: test
num_bytes: 270059.67976253625
num_examples: 711
download_size: 11022923
dataset_size: 21160752.207103595
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
liuyanchen1015/MULTI_VALUE_mrpc_never_negator | ---
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: label
dtype: int64
- name: idx
dtype: int64
- name: value_score
dtype: int64
splits:
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num_bytes: 5640
num_examples: 21
- name: train
num_bytes: 12822
num_examples: 49
- name: validation
num_bytes: 1780
num_examples: 7
download_size: 24765
dataset_size: 20242
---
# Dataset Card for "MULTI_VALUE_mrpc_never_negator"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
anan-2024/twitter_dataset_1713106233 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 27670
num_examples: 69
download_size: 15901
dataset_size: 27670
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
hpprc/miracl-mined | ---
dataset_info:
features:
- name: query
dtype: string
- name: pos_ids
sequence: int64
- name: neg_ids
sequence: int64
- name: mined_neg_ids
sequence: int64
- name: mined_neg_sims
sequence: float64
splits:
- name: train
num_bytes: 11651160
num_examples: 3477
download_size: 9310186
dataset_size: 11651160
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
gagan3012/finner | ---
dataset_info:
features:
- name: label
sequence: string
- name: answer
dtype: string
- name: text
dtype: string
- name: query
dtype: string
splits:
- name: train
num_bytes: 29189680
num_examples: 8100
download_size: 9009979
dataset_size: 29189680
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
sngsng/English_Taigi_Dict | ---
license: other
---
|
AdaptLLM/law_knowledge_prob | ---
configs:
- config_name: law_knowledge_prob
data_files:
- split: test
path: test.jsonl
task_categories:
- text-classification
- question-answering
- zero-shot-classification
language:
- en
tags:
- legal
---
# Domain Adaptation of Large Language Models
This repo contains the **Law Knowledge Probing dataset** used in our **ICLR 2024** paper [Adapting Large Language Models via Reading Comprehension](https://huggingface.co/papers/2309.09530).
We explore **continued pre-training on domain-specific corpora** for large language models. While this approach enriches LLMs with domain knowledge, it significantly hurts their prompting ability for question answering. Inspired by human learning via reading comprehension, we propose a simple method to **transform large-scale pre-training corpora into reading comprehension texts**, consistently improving prompting performance across tasks in biomedicine, finance, and law domains. **Our 7B model competes with much larger domain-specific models like BloombergGPT-50B**.
### 🤗 We are currently working hard on developing models across different domains, scales and architectures! Please stay tuned! 🤗
**************************** **Updates** ****************************
* 2024/4/14: Released the knowledge probing datasets at [med_knowledge_prob](https://huggingface.co/datasets/AdaptLLM/med_knowledge_prob) and [law_knowledge_prob](https://huggingface.co/datasets/AdaptLLM/law_knowledge_prob)
* 2024/4/2: Released the raw data splits (train and test) of all the evaluation datasets
* 2024/1/16: 🎉 Our [research paper](https://huggingface.co/papers/2309.09530) has been accepted by ICLR 2024!!!🎉
* 2023/12/19: Released our [13B base models](https://huggingface.co/AdaptLLM/law-LLM-13B) developed from LLaMA-1-13B.
* 2023/12/8: Released our [chat models](https://huggingface.co/AdaptLLM/law-chat) developed from LLaMA-2-Chat-7B.
* 2023/9/18: Released our [paper](https://huggingface.co/papers/2309.09530), [code](https://github.com/microsoft/LMOps), [data](https://huggingface.co/datasets/AdaptLLM/law-tasks), and [base models](https://huggingface.co/AdaptLLM/law-LLM) developed from LLaMA-1-7B.
## Domain-Specific LLMs
### LLaMA-1-7B
In our paper, we develop three domain-specific models from LLaMA-1-7B, which are also available in Huggingface: [Biomedicine-LLM](https://huggingface.co/AdaptLLM/medicine-LLM), [Finance-LLM](https://huggingface.co/AdaptLLM/finance-LLM) and [Law-LLM](https://huggingface.co/AdaptLLM/law-LLM), the performances of our AdaptLLM compared to other domain-specific LLMs are:
<p align='center'>
<img src="https://cdn-uploads.huggingface.co/production/uploads/650801ced5578ef7e20b33d4/6efPwitFgy-pLTzvccdcP.png" width="700">
</p>
### LLaMA-1-13B
Moreover, we scale up our base model to LLaMA-1-13B to see if **our method is similarly effective for larger-scale models**, and the results are consistently positive too: [Biomedicine-LLM-13B](https://huggingface.co/AdaptLLM/medicine-LLM-13B), [Finance-LLM-13B](https://huggingface.co/AdaptLLM/finance-LLM-13B) and [Law-LLM-13B](https://huggingface.co/AdaptLLM/law-LLM-13B).
## Domain-Specific LLaMA-2-Chat
Our method is also effective for aligned models! LLaMA-2-Chat requires a [specific data format](https://huggingface.co/blog/llama2#how-to-prompt-llama-2), and our **reading comprehension can perfectly fit the data format** by transforming the reading comprehension into a multi-turn conversation. We have also open-sourced chat models in different domains: [Biomedicine-Chat](https://huggingface.co/AdaptLLM/medicine-chat), [Finance-Chat](https://huggingface.co/AdaptLLM/finance-chat) and [Law-Chat](https://huggingface.co/AdaptLLM/law-chat)
## Domain-Specific Tasks
### Pre-templatized/Formatted Testing Splits
To easily reproduce our prompting results, we have uploaded the filled-in zero/few-shot input instructions and output completions of the test each domain-specific task: [biomedicine-tasks](https://huggingface.co/datasets/AdaptLLM/medicine-tasks), [finance-tasks](https://huggingface.co/datasets/AdaptLLM/finance-tasks), and [law-tasks](https://huggingface.co/datasets/AdaptLLM/law-tasks).
**Note:** those filled-in instructions are specifically tailored for models before alignment and do NOT fit for the specific data format required for chat models.
### Raw Datasets
We have also uploaded the raw training and testing splits, for facilitating fine-tuning or other usages: [ChemProt](https://huggingface.co/datasets/AdaptLLM/ChemProt), [RCT](https://huggingface.co/datasets/AdaptLLM/RCT), [ConvFinQA](https://huggingface.co/datasets/AdaptLLM/ConvFinQA), [FiQA_SA](https://huggingface.co/datasets/AdaptLLM/FiQA_SA), [Headline](https://huggingface.co/datasets/AdaptLLM/Headline), [NER](https://huggingface.co/datasets/AdaptLLM/NER), [FPB](https://huggingface.co/datasets/AdaptLLM/FPB)
The other datasets used in our paper have already been available in huggingface.
### Domain Knowledge Probing
Our pre-processed knowledge probing datasets are available at: [med_knowledge_prob](https://huggingface.co/datasets/AdaptLLM/med_knowledge_prob) and [law_knowledge_prob](https://huggingface.co/datasets/AdaptLLM/law_knowledge_prob)
## Citation
If you find our work helpful, please cite us:
```bibtex
@inproceedings{
cheng2024adapting,
title={Adapting Large Language Models via Reading Comprehension},
author={Daixuan Cheng and Shaohan Huang and Furu Wei},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=y886UXPEZ0}
}
```
and the original dataset:
```bibtex
@inproceedings{LEDGAR,
author = {Don Tuggener and
Pius von D{\"{a}}niken and
Thomas Peetz and
Mark Cieliebak},
title = {{LEDGAR:} {A} Large-Scale Multi-label Corpus for Text Classification
of Legal Provisions in Contracts},
booktitle = {{LREC}},
pages = {1235--1241},
publisher = {European Language Resources Association},
year = {2020}
}
``` |
kaleemWaheed/twitter_dataset_1713104979 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 29365
num_examples: 69
download_size: 17044
dataset_size: 29365
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
open-llm-leaderboard/details_azarafrooz__gemma-2b-it-sp-test-openherms-step500 | ---
pretty_name: Evaluation run of azarafrooz/gemma-2b-it-sp-test-openherms-step500
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [azarafrooz/gemma-2b-it-sp-test-openherms-step500](https://huggingface.co/azarafrooz/gemma-2b-it-sp-test-openherms-step500)\
\ 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_azarafrooz__gemma-2b-it-sp-test-openherms-step500\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-01T00:06:20.995777](https://huggingface.co/datasets/open-llm-leaderboard/details_azarafrooz__gemma-2b-it-sp-test-openherms-step500/blob/main/results_2024-03-01T00-06-20.995777.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\": 0.37741994500719955,\n\
\ \"acc_stderr\": 0.03383611339946955,\n \"acc_norm\": 0.3820192124841891,\n\
\ \"acc_norm_stderr\": 0.03464622149429246,\n \"mc1\": 0.29008567931456547,\n\
\ \"mc1_stderr\": 0.01588623687420952,\n \"mc2\": 0.4577414398229486,\n\
\ \"mc2_stderr\": 0.015930821092460964\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.4052901023890785,\n \"acc_stderr\": 0.014346869060229327,\n\
\ \"acc_norm\": 0.4402730375426621,\n \"acc_norm_stderr\": 0.014506769524804246\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.481876120294762,\n\
\ \"acc_stderr\": 0.004986502296931189,\n \"acc_norm\": 0.6281617207727545,\n\
\ \"acc_norm_stderr\": 0.004823078145064961\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \
\ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.3851851851851852,\n\
\ \"acc_stderr\": 0.042039210401562783,\n \"acc_norm\": 0.3851851851851852,\n\
\ \"acc_norm_stderr\": 0.042039210401562783\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.3355263157894737,\n \"acc_stderr\": 0.03842498559395269,\n\
\ \"acc_norm\": 0.3355263157894737,\n \"acc_norm_stderr\": 0.03842498559395269\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.48,\n\
\ \"acc_stderr\": 0.05021167315686779,\n \"acc_norm\": 0.48,\n \
\ \"acc_norm_stderr\": 0.05021167315686779\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.42641509433962266,\n \"acc_stderr\": 0.030437794342983042,\n\
\ \"acc_norm\": 0.42641509433962266,\n \"acc_norm_stderr\": 0.030437794342983042\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.3472222222222222,\n\
\ \"acc_stderr\": 0.039812405437178615,\n \"acc_norm\": 0.3472222222222222,\n\
\ \"acc_norm_stderr\": 0.039812405437178615\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768077,\n \
\ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768077\n \
\ },\n \"harness|hendrycksTest-college_computer_science|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_mathematics|5\"\
: {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \
\ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\
\ \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.36416184971098264,\n\
\ \"acc_stderr\": 0.03669072477416908,\n \"acc_norm\": 0.36416184971098264,\n\
\ \"acc_norm_stderr\": 0.03669072477416908\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617747,\n\
\ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617747\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.45,\n \"\
acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.3574468085106383,\n \"acc_stderr\": 0.03132941789476425,\n\
\ \"acc_norm\": 0.3574468085106383,\n \"acc_norm_stderr\": 0.03132941789476425\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2894736842105263,\n\
\ \"acc_stderr\": 0.04266339443159394,\n \"acc_norm\": 0.2894736842105263,\n\
\ \"acc_norm_stderr\": 0.04266339443159394\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.46206896551724136,\n \"acc_stderr\": 0.04154659671707546,\n\
\ \"acc_norm\": 0.46206896551724136,\n \"acc_norm_stderr\": 0.04154659671707546\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.24867724867724866,\n \"acc_stderr\": 0.022261817692400168,\n \"\
acc_norm\": 0.24867724867724866,\n \"acc_norm_stderr\": 0.022261817692400168\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2619047619047619,\n\
\ \"acc_stderr\": 0.03932537680392871,\n \"acc_norm\": 0.2619047619047619,\n\
\ \"acc_norm_stderr\": 0.03932537680392871\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\"\
: 0.3161290322580645,\n \"acc_stderr\": 0.02645087448904277,\n \"\
acc_norm\": 0.3161290322580645,\n \"acc_norm_stderr\": 0.02645087448904277\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.2857142857142857,\n \"acc_stderr\": 0.03178529710642748,\n \"\
acc_norm\": 0.2857142857142857,\n \"acc_norm_stderr\": 0.03178529710642748\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\
: {\n \"acc\": 0.45454545454545453,\n \"acc_stderr\": 0.03888176921674098,\n\
\ \"acc_norm\": 0.45454545454545453,\n \"acc_norm_stderr\": 0.03888176921674098\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.4595959595959596,\n \"acc_stderr\": 0.035507024651313425,\n \"\
acc_norm\": 0.4595959595959596,\n \"acc_norm_stderr\": 0.035507024651313425\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.47668393782383417,\n \"acc_stderr\": 0.03604513672442207,\n\
\ \"acc_norm\": 0.47668393782383417,\n \"acc_norm_stderr\": 0.03604513672442207\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.3282051282051282,\n \"acc_stderr\": 0.023807633198657262,\n\
\ \"acc_norm\": 0.3282051282051282,\n \"acc_norm_stderr\": 0.023807633198657262\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.2,\n \"acc_stderr\": 0.024388430433987664,\n \"acc_norm\"\
: 0.2,\n \"acc_norm_stderr\": 0.024388430433987664\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\"\
: {\n \"acc\": 0.3403361344537815,\n \"acc_stderr\": 0.030778057422931673,\n\
\ \"acc_norm\": 0.3403361344537815,\n \"acc_norm_stderr\": 0.030778057422931673\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.25165562913907286,\n \"acc_stderr\": 0.035433042343899844,\n \"\
acc_norm\": 0.25165562913907286,\n \"acc_norm_stderr\": 0.035433042343899844\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.5009174311926605,\n \"acc_stderr\": 0.021437287056051208,\n \"\
acc_norm\": 0.5009174311926605,\n \"acc_norm_stderr\": 0.021437287056051208\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.19907407407407407,\n \"acc_stderr\": 0.027232298462690218,\n \"\
acc_norm\": 0.19907407407407407,\n \"acc_norm_stderr\": 0.027232298462690218\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.4264705882352941,\n \"acc_stderr\": 0.03471157907953426,\n \"\
acc_norm\": 0.4264705882352941,\n \"acc_norm_stderr\": 0.03471157907953426\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.5274261603375527,\n \"acc_stderr\": 0.03249822718301303,\n \
\ \"acc_norm\": 0.5274261603375527,\n \"acc_norm_stderr\": 0.03249822718301303\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.38565022421524664,\n\
\ \"acc_stderr\": 0.03266842214289201,\n \"acc_norm\": 0.38565022421524664,\n\
\ \"acc_norm_stderr\": 0.03266842214289201\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.4198473282442748,\n \"acc_stderr\": 0.043285772152629715,\n\
\ \"acc_norm\": 0.4198473282442748,\n \"acc_norm_stderr\": 0.043285772152629715\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.5206611570247934,\n \"acc_stderr\": 0.04560456086387235,\n \"\
acc_norm\": 0.5206611570247934,\n \"acc_norm_stderr\": 0.04560456086387235\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.46296296296296297,\n\
\ \"acc_stderr\": 0.04820403072760627,\n \"acc_norm\": 0.46296296296296297,\n\
\ \"acc_norm_stderr\": 0.04820403072760627\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.3619631901840491,\n \"acc_stderr\": 0.037757007291414416,\n\
\ \"acc_norm\": 0.3619631901840491,\n \"acc_norm_stderr\": 0.037757007291414416\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3392857142857143,\n\
\ \"acc_stderr\": 0.0449394906861354,\n \"acc_norm\": 0.3392857142857143,\n\
\ \"acc_norm_stderr\": 0.0449394906861354\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.44660194174757284,\n \"acc_stderr\": 0.04922424153458933,\n\
\ \"acc_norm\": 0.44660194174757284,\n \"acc_norm_stderr\": 0.04922424153458933\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.5982905982905983,\n\
\ \"acc_stderr\": 0.03211693751051621,\n \"acc_norm\": 0.5982905982905983,\n\
\ \"acc_norm_stderr\": 0.03211693751051621\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145633,\n \
\ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145633\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.4648786717752235,\n\
\ \"acc_stderr\": 0.017835798806290642,\n \"acc_norm\": 0.4648786717752235,\n\
\ \"acc_norm_stderr\": 0.017835798806290642\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.407514450867052,\n \"acc_stderr\": 0.0264545781469315,\n\
\ \"acc_norm\": 0.407514450867052,\n \"acc_norm_stderr\": 0.0264545781469315\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24692737430167597,\n\
\ \"acc_stderr\": 0.014422292204808836,\n \"acc_norm\": 0.24692737430167597,\n\
\ \"acc_norm_stderr\": 0.014422292204808836\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.4444444444444444,\n \"acc_stderr\": 0.028452639985088003,\n\
\ \"acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.028452639985088003\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.40192926045016075,\n\
\ \"acc_stderr\": 0.027846476005930473,\n \"acc_norm\": 0.40192926045016075,\n\
\ \"acc_norm_stderr\": 0.027846476005930473\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.41975308641975306,\n \"acc_stderr\": 0.027460099557005135,\n\
\ \"acc_norm\": 0.41975308641975306,\n \"acc_norm_stderr\": 0.027460099557005135\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.30851063829787234,\n \"acc_stderr\": 0.027553366165101362,\n \
\ \"acc_norm\": 0.30851063829787234,\n \"acc_norm_stderr\": 0.027553366165101362\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3200782268578879,\n\
\ \"acc_stderr\": 0.011914791947638517,\n \"acc_norm\": 0.3200782268578879,\n\
\ \"acc_norm_stderr\": 0.011914791947638517\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.20220588235294118,\n \"acc_stderr\": 0.024398192986654924,\n\
\ \"acc_norm\": 0.20220588235294118,\n \"acc_norm_stderr\": 0.024398192986654924\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.3839869281045752,\n \"acc_stderr\": 0.019675808135281518,\n \
\ \"acc_norm\": 0.3839869281045752,\n \"acc_norm_stderr\": 0.019675808135281518\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.41818181818181815,\n\
\ \"acc_stderr\": 0.0472457740573157,\n \"acc_norm\": 0.41818181818181815,\n\
\ \"acc_norm_stderr\": 0.0472457740573157\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.46938775510204084,\n \"acc_stderr\": 0.031949171367580624,\n\
\ \"acc_norm\": 0.46938775510204084,\n \"acc_norm_stderr\": 0.031949171367580624\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.43283582089552236,\n\
\ \"acc_stderr\": 0.03503490923673281,\n \"acc_norm\": 0.43283582089552236,\n\
\ \"acc_norm_stderr\": 0.03503490923673281\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \
\ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.40963855421686746,\n\
\ \"acc_stderr\": 0.03828401115079023,\n \"acc_norm\": 0.40963855421686746,\n\
\ \"acc_norm_stderr\": 0.03828401115079023\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.4444444444444444,\n \"acc_stderr\": 0.03811079669833531,\n\
\ \"acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.03811079669833531\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.29008567931456547,\n\
\ \"mc1_stderr\": 0.01588623687420952,\n \"mc2\": 0.4577414398229486,\n\
\ \"mc2_stderr\": 0.015930821092460964\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.611681136543015,\n \"acc_stderr\": 0.013697456658457228\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.05307050796057619,\n \
\ \"acc_stderr\": 0.00617486885863837\n }\n}\n```"
repo_url: https://huggingface.co/azarafrooz/gemma-2b-it-sp-test-openherms-step500
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_01T00_06_20.995777
path:
- '**/details_harness|arc:challenge|25_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|gsm8k|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hellaswag|10_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T00-06-20.995777.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T00-06-20.995777.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- '**/details_harness|winogrande|5_2024-03-01T00-06-20.995777.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-01T00-06-20.995777.parquet'
- config_name: results
data_files:
- split: 2024_03_01T00_06_20.995777
path:
- results_2024-03-01T00-06-20.995777.parquet
- split: latest
path:
- results_2024-03-01T00-06-20.995777.parquet
---
# Dataset Card for Evaluation run of azarafrooz/gemma-2b-it-sp-test-openherms-step500
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [azarafrooz/gemma-2b-it-sp-test-openherms-step500](https://huggingface.co/azarafrooz/gemma-2b-it-sp-test-openherms-step500) 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_azarafrooz__gemma-2b-it-sp-test-openherms-step500",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-01T00:06:20.995777](https://huggingface.co/datasets/open-llm-leaderboard/details_azarafrooz__gemma-2b-it-sp-test-openherms-step500/blob/main/results_2024-03-01T00-06-20.995777.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": 0.37741994500719955,
"acc_stderr": 0.03383611339946955,
"acc_norm": 0.3820192124841891,
"acc_norm_stderr": 0.03464622149429246,
"mc1": 0.29008567931456547,
"mc1_stderr": 0.01588623687420952,
"mc2": 0.4577414398229486,
"mc2_stderr": 0.015930821092460964
},
"harness|arc:challenge|25": {
"acc": 0.4052901023890785,
"acc_stderr": 0.014346869060229327,
"acc_norm": 0.4402730375426621,
"acc_norm_stderr": 0.014506769524804246
},
"harness|hellaswag|10": {
"acc": 0.481876120294762,
"acc_stderr": 0.004986502296931189,
"acc_norm": 0.6281617207727545,
"acc_norm_stderr": 0.004823078145064961
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.27,
"acc_stderr": 0.044619604333847394,
"acc_norm": 0.27,
"acc_norm_stderr": 0.044619604333847394
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.3851851851851852,
"acc_stderr": 0.042039210401562783,
"acc_norm": 0.3851851851851852,
"acc_norm_stderr": 0.042039210401562783
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.3355263157894737,
"acc_stderr": 0.03842498559395269,
"acc_norm": 0.3355263157894737,
"acc_norm_stderr": 0.03842498559395269
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.48,
"acc_stderr": 0.05021167315686779,
"acc_norm": 0.48,
"acc_norm_stderr": 0.05021167315686779
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.42641509433962266,
"acc_stderr": 0.030437794342983042,
"acc_norm": 0.42641509433962266,
"acc_norm_stderr": 0.030437794342983042
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.3472222222222222,
"acc_stderr": 0.039812405437178615,
"acc_norm": 0.3472222222222222,
"acc_norm_stderr": 0.039812405437178615
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.26,
"acc_stderr": 0.04408440022768077,
"acc_norm": 0.26,
"acc_norm_stderr": 0.04408440022768077
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.31,
"acc_stderr": 0.04648231987117316,
"acc_norm": 0.31,
"acc_norm_stderr": 0.04648231987117316
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.26,
"acc_stderr": 0.0440844002276808,
"acc_norm": 0.26,
"acc_norm_stderr": 0.0440844002276808
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.36416184971098264,
"acc_stderr": 0.03669072477416908,
"acc_norm": 0.36416184971098264,
"acc_norm_stderr": 0.03669072477416908
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.20588235294117646,
"acc_stderr": 0.04023382273617747,
"acc_norm": 0.20588235294117646,
"acc_norm_stderr": 0.04023382273617747
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.45,
"acc_stderr": 0.05,
"acc_norm": 0.45,
"acc_norm_stderr": 0.05
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.3574468085106383,
"acc_stderr": 0.03132941789476425,
"acc_norm": 0.3574468085106383,
"acc_norm_stderr": 0.03132941789476425
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.2894736842105263,
"acc_stderr": 0.04266339443159394,
"acc_norm": 0.2894736842105263,
"acc_norm_stderr": 0.04266339443159394
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.46206896551724136,
"acc_stderr": 0.04154659671707546,
"acc_norm": 0.46206896551724136,
"acc_norm_stderr": 0.04154659671707546
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.24867724867724866,
"acc_stderr": 0.022261817692400168,
"acc_norm": 0.24867724867724866,
"acc_norm_stderr": 0.022261817692400168
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.2619047619047619,
"acc_stderr": 0.03932537680392871,
"acc_norm": 0.2619047619047619,
"acc_norm_stderr": 0.03932537680392871
},
"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": 0.3161290322580645,
"acc_stderr": 0.02645087448904277,
"acc_norm": 0.3161290322580645,
"acc_norm_stderr": 0.02645087448904277
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.2857142857142857,
"acc_stderr": 0.03178529710642748,
"acc_norm": 0.2857142857142857,
"acc_norm_stderr": 0.03178529710642748
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.37,
"acc_stderr": 0.04852365870939099,
"acc_norm": 0.37,
"acc_norm_stderr": 0.04852365870939099
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.45454545454545453,
"acc_stderr": 0.03888176921674098,
"acc_norm": 0.45454545454545453,
"acc_norm_stderr": 0.03888176921674098
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.4595959595959596,
"acc_stderr": 0.035507024651313425,
"acc_norm": 0.4595959595959596,
"acc_norm_stderr": 0.035507024651313425
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.47668393782383417,
"acc_stderr": 0.03604513672442207,
"acc_norm": 0.47668393782383417,
"acc_norm_stderr": 0.03604513672442207
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.3282051282051282,
"acc_stderr": 0.023807633198657262,
"acc_norm": 0.3282051282051282,
"acc_norm_stderr": 0.023807633198657262
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.2,
"acc_stderr": 0.024388430433987664,
"acc_norm": 0.2,
"acc_norm_stderr": 0.024388430433987664
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.3403361344537815,
"acc_stderr": 0.030778057422931673,
"acc_norm": 0.3403361344537815,
"acc_norm_stderr": 0.030778057422931673
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.25165562913907286,
"acc_stderr": 0.035433042343899844,
"acc_norm": 0.25165562913907286,
"acc_norm_stderr": 0.035433042343899844
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.5009174311926605,
"acc_stderr": 0.021437287056051208,
"acc_norm": 0.5009174311926605,
"acc_norm_stderr": 0.021437287056051208
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.19907407407407407,
"acc_stderr": 0.027232298462690218,
"acc_norm": 0.19907407407407407,
"acc_norm_stderr": 0.027232298462690218
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.4264705882352941,
"acc_stderr": 0.03471157907953426,
"acc_norm": 0.4264705882352941,
"acc_norm_stderr": 0.03471157907953426
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.5274261603375527,
"acc_stderr": 0.03249822718301303,
"acc_norm": 0.5274261603375527,
"acc_norm_stderr": 0.03249822718301303
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.38565022421524664,
"acc_stderr": 0.03266842214289201,
"acc_norm": 0.38565022421524664,
"acc_norm_stderr": 0.03266842214289201
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.4198473282442748,
"acc_stderr": 0.043285772152629715,
"acc_norm": 0.4198473282442748,
"acc_norm_stderr": 0.043285772152629715
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.5206611570247934,
"acc_stderr": 0.04560456086387235,
"acc_norm": 0.5206611570247934,
"acc_norm_stderr": 0.04560456086387235
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.46296296296296297,
"acc_stderr": 0.04820403072760627,
"acc_norm": 0.46296296296296297,
"acc_norm_stderr": 0.04820403072760627
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.3619631901840491,
"acc_stderr": 0.037757007291414416,
"acc_norm": 0.3619631901840491,
"acc_norm_stderr": 0.037757007291414416
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.3392857142857143,
"acc_stderr": 0.0449394906861354,
"acc_norm": 0.3392857142857143,
"acc_norm_stderr": 0.0449394906861354
},
"harness|hendrycksTest-management|5": {
"acc": 0.44660194174757284,
"acc_stderr": 0.04922424153458933,
"acc_norm": 0.44660194174757284,
"acc_norm_stderr": 0.04922424153458933
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.5982905982905983,
"acc_stderr": 0.03211693751051621,
"acc_norm": 0.5982905982905983,
"acc_norm_stderr": 0.03211693751051621
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.38,
"acc_stderr": 0.04878317312145633,
"acc_norm": 0.38,
"acc_norm_stderr": 0.04878317312145633
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.4648786717752235,
"acc_stderr": 0.017835798806290642,
"acc_norm": 0.4648786717752235,
"acc_norm_stderr": 0.017835798806290642
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.407514450867052,
"acc_stderr": 0.0264545781469315,
"acc_norm": 0.407514450867052,
"acc_norm_stderr": 0.0264545781469315
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.24692737430167597,
"acc_stderr": 0.014422292204808836,
"acc_norm": 0.24692737430167597,
"acc_norm_stderr": 0.014422292204808836
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.4444444444444444,
"acc_stderr": 0.028452639985088003,
"acc_norm": 0.4444444444444444,
"acc_norm_stderr": 0.028452639985088003
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.40192926045016075,
"acc_stderr": 0.027846476005930473,
"acc_norm": 0.40192926045016075,
"acc_norm_stderr": 0.027846476005930473
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.41975308641975306,
"acc_stderr": 0.027460099557005135,
"acc_norm": 0.41975308641975306,
"acc_norm_stderr": 0.027460099557005135
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.30851063829787234,
"acc_stderr": 0.027553366165101362,
"acc_norm": 0.30851063829787234,
"acc_norm_stderr": 0.027553366165101362
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.3200782268578879,
"acc_stderr": 0.011914791947638517,
"acc_norm": 0.3200782268578879,
"acc_norm_stderr": 0.011914791947638517
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.20220588235294118,
"acc_stderr": 0.024398192986654924,
"acc_norm": 0.20220588235294118,
"acc_norm_stderr": 0.024398192986654924
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.3839869281045752,
"acc_stderr": 0.019675808135281518,
"acc_norm": 0.3839869281045752,
"acc_norm_stderr": 0.019675808135281518
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.41818181818181815,
"acc_stderr": 0.0472457740573157,
"acc_norm": 0.41818181818181815,
"acc_norm_stderr": 0.0472457740573157
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.46938775510204084,
"acc_stderr": 0.031949171367580624,
"acc_norm": 0.46938775510204084,
"acc_norm_stderr": 0.031949171367580624
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.43283582089552236,
"acc_stderr": 0.03503490923673281,
"acc_norm": 0.43283582089552236,
"acc_norm_stderr": 0.03503490923673281
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.64,
"acc_stderr": 0.04824181513244218,
"acc_norm": 0.64,
"acc_norm_stderr": 0.04824181513244218
},
"harness|hendrycksTest-virology|5": {
"acc": 0.40963855421686746,
"acc_stderr": 0.03828401115079023,
"acc_norm": 0.40963855421686746,
"acc_norm_stderr": 0.03828401115079023
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.4444444444444444,
"acc_stderr": 0.03811079669833531,
"acc_norm": 0.4444444444444444,
"acc_norm_stderr": 0.03811079669833531
},
"harness|truthfulqa:mc|0": {
"mc1": 0.29008567931456547,
"mc1_stderr": 0.01588623687420952,
"mc2": 0.4577414398229486,
"mc2_stderr": 0.015930821092460964
},
"harness|winogrande|5": {
"acc": 0.611681136543015,
"acc_stderr": 0.013697456658457228
},
"harness|gsm8k|5": {
"acc": 0.05307050796057619,
"acc_stderr": 0.00617486885863837
}
}
```
## 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. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] |
Sijuade/cats_dogs_birds_latents | ---
license: mit
dataset_info:
features:
- name: latent
sequence:
sequence:
sequence: float32
- name: noised_latents
sequence:
sequence:
sequence: float32
- name: noise
sequence:
sequence:
sequence:
sequence: float32
- name: timesteps
dtype: float64
- name: label
dtype: int64
splits:
- name: train
num_bytes: 677448192
num_examples: 13344
download_size: 683560149
dataset_size: 677448192
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
BobdoRock/EmmaWatson | ---
license: openrail
---
|
mxronga/sportsinyoruba | ---
license: apache-2.0
language:
- yo
tags:
- 'pretrain '
---
https://sportsinyoruba.wordpress.com |
tomasmcz/word2vec_analogy | ---
license: apache-2.0
---
Adapted from https://github.com/nicholas-leonard/word2vec |
Deathspike/magical-girl-lyrical-nanoha-official-art-ver | ---
license: cc-by-nc-sa-4.0
---
|
Zainabsa99/my-data | ---
dataset_info:
features:
- name: type
dtype: string
- name: id
dtype: string
- name: spec_version
dtype: float64
- name: objects
struct:
- name: aliases
sequence: string
- name: created
dtype: string
- name: created_by_ref
dtype: string
- name: definition
struct:
- name: statement
dtype: string
- name: definition_type
dtype: string
- name: description
dtype: string
- name: external_references
list:
- name: description
dtype: string
- name: external_id
dtype: string
- name: source_name
dtype: string
- name: url
dtype: string
- name: first_seen
dtype: string
- name: id
dtype: string
- name: identity_class
dtype: string
- name: is_family
dtype: bool
- name: kill_chain_phases
list:
- name: kill_chain_name
dtype: string
- name: phase_name
dtype: string
- name: last_seen
dtype: string
- name: modified
dtype: string
- name: name
dtype: string
- name: object_marking_refs
sequence: string
- name: relationship_type
dtype: string
- name: revoked
dtype: bool
- name: source_ref
dtype: string
- name: spec_version
dtype: string
- name: tactic_refs
sequence: string
- name: target_ref
dtype: string
- name: type
dtype: string
- name: x_mitre_aliases
sequence: string
- name: x_mitre_attack_spec_version
dtype: string
- name: x_mitre_collection_layers
sequence: string
- name: x_mitre_contents
list:
- name: object_modified
dtype: string
- name: object_ref
dtype: string
- name: x_mitre_contributors
sequence: string
- name: x_mitre_data_source_ref
dtype: string
- name: x_mitre_deprecated
dtype: bool
- name: x_mitre_detection
dtype: string
- name: x_mitre_domains
sequence: string
- name: x_mitre_first_seen_citation
dtype: string
- name: x_mitre_is_subtechnique
dtype: bool
- name: x_mitre_last_seen_citation
dtype: string
- name: x_mitre_modified_by_ref
dtype: string
- name: x_mitre_old_attack_id
dtype: string
- name: x_mitre_platforms
sequence: string
- name: x_mitre_shortname
dtype: string
- name: x_mitre_tactic_type
sequence: string
- name: x_mitre_version
dtype: string
splits:
- name: train
num_bytes: 1755690.0411522633
num_examples: 1530
- name: test
num_bytes: 753913.9588477366
num_examples: 657
download_size: 732724
dataset_size: 2509604.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
autoevaluate/autoeval-staging-eval-project-304eb14a-d97c-4ab5-a495-bcda04ee4f5c-2927 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. |
wz2615/cups_image | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 231083090.0
num_examples: 500
download_size: 230975569
dataset_size: 231083090.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
open-llm-leaderboard/details_yleo__EmertonMonarch-7B | ---
pretty_name: Evaluation run of yleo/EmertonMonarch-7B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [yleo/EmertonMonarch-7B](https://huggingface.co/yleo/EmertonMonarch-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 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_yleo__EmertonMonarch-7B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-02-14T15:51:06.640306](https://huggingface.co/datasets/open-llm-leaderboard/details_yleo__EmertonMonarch-7B/blob/main/results_2024-02-14T15-51-06.640306.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\": 0.6464761697140718,\n\
\ \"acc_stderr\": 0.03222241013310851,\n \"acc_norm\": 0.6461858589602053,\n\
\ \"acc_norm_stderr\": 0.03289455177300504,\n \"mc1\": 0.6291309669522643,\n\
\ \"mc1_stderr\": 0.016909693580248835,\n \"mc2\": 0.7809489116779263,\n\
\ \"mc2_stderr\": 0.013701734554887294\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.7056313993174061,\n \"acc_stderr\": 0.013318528460539422,\n\
\ \"acc_norm\": 0.726962457337884,\n \"acc_norm_stderr\": 0.013019332762635751\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7185819557857,\n \
\ \"acc_stderr\": 0.004487718843330278,\n \"acc_norm\": 0.8915554670384386,\n\
\ \"acc_norm_stderr\": 0.0031030554162430565\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6074074074074074,\n\
\ \"acc_stderr\": 0.0421850621536888,\n \"acc_norm\": 0.6074074074074074,\n\
\ \"acc_norm_stderr\": 0.0421850621536888\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.7039473684210527,\n \"acc_stderr\": 0.03715062154998904,\n\
\ \"acc_norm\": 0.7039473684210527,\n \"acc_norm_stderr\": 0.03715062154998904\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\
\ \"acc_stderr\": 0.048523658709391,\n \"acc_norm\": 0.63,\n \
\ \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\
\ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7708333333333334,\n\
\ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\
\ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \
\ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.54,\n \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\"\
: 0.54,\n \"acc_norm_stderr\": 0.05009082659620333\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\": 0.6242774566473989,\n\
\ \"acc_stderr\": 0.036928207672648664,\n \"acc_norm\": 0.6242774566473989,\n\
\ \"acc_norm_stderr\": 0.036928207672648664\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107224,\n\
\ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107224\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.73,\n \"acc_stderr\": 0.0446196043338474,\n \"acc_norm\": 0.73,\n\
\ \"acc_norm_stderr\": 0.0446196043338474\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5276595744680851,\n \"acc_stderr\": 0.03263597118409769,\n\
\ \"acc_norm\": 0.5276595744680851,\n \"acc_norm_stderr\": 0.03263597118409769\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.47368421052631576,\n\
\ \"acc_stderr\": 0.04697085136647863,\n \"acc_norm\": 0.47368421052631576,\n\
\ \"acc_norm_stderr\": 0.04697085136647863\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370332,\n\
\ \"acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370332\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.41534391534391535,\n \"acc_stderr\": 0.025379524910778398,\n \"\
acc_norm\": 0.41534391534391535,\n \"acc_norm_stderr\": 0.025379524910778398\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4603174603174603,\n\
\ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\
\ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness|hendrycksTest-global_facts|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-high_school_biology|5\": {\n \"acc\": 0.7806451612903226,\n\
\ \"acc_stderr\": 0.023540799358723292,\n \"acc_norm\": 0.7806451612903226,\n\
\ \"acc_norm_stderr\": 0.023540799358723292\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\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\
: 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\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\"\
: 0.8080808080808081,\n \"acc_stderr\": 0.028057791672989017,\n \"\
acc_norm\": 0.8080808080808081,\n \"acc_norm_stderr\": 0.028057791672989017\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\": 0.6564102564102564,\n \"acc_stderr\": 0.024078696580635477,\n\
\ \"acc_norm\": 0.6564102564102564,\n \"acc_norm_stderr\": 0.024078696580635477\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.32222222222222224,\n \"acc_stderr\": 0.028493465091028593,\n \
\ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.028493465091028593\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6596638655462185,\n \"acc_stderr\": 0.03077805742293167,\n \
\ \"acc_norm\": 0.6596638655462185,\n \"acc_norm_stderr\": 0.03077805742293167\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3973509933774834,\n \"acc_stderr\": 0.0399552400768168,\n \"acc_norm\"\
: 0.3973509933774834,\n \"acc_norm_stderr\": 0.0399552400768168\n },\n\
\ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.8311926605504587,\n\
\ \"acc_stderr\": 0.016060056268530336,\n \"acc_norm\": 0.8311926605504587,\n\
\ \"acc_norm_stderr\": 0.016060056268530336\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\
: {\n \"acc\": 0.5509259259259259,\n \"acc_stderr\": 0.03392238405321617,\n\
\ \"acc_norm\": 0.5509259259259259,\n \"acc_norm_stderr\": 0.03392238405321617\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8382352941176471,\n \"acc_stderr\": 0.02584501798692692,\n \"\
acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.02584501798692692\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.8016877637130801,\n \"acc_stderr\": 0.025955020841621126,\n \
\ \"acc_norm\": 0.8016877637130801,\n \"acc_norm_stderr\": 0.025955020841621126\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6995515695067265,\n\
\ \"acc_stderr\": 0.030769352008229143,\n \"acc_norm\": 0.6995515695067265,\n\
\ \"acc_norm_stderr\": 0.030769352008229143\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.8015267175572519,\n \"acc_stderr\": 0.034981493854624714,\n\
\ \"acc_norm\": 0.8015267175572519,\n \"acc_norm_stderr\": 0.034981493854624714\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070416,\n \"\
acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070416\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7685185185185185,\n\
\ \"acc_stderr\": 0.04077494709252626,\n \"acc_norm\": 0.7685185185185185,\n\
\ \"acc_norm_stderr\": 0.04077494709252626\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.754601226993865,\n \"acc_stderr\": 0.03380939813943354,\n\
\ \"acc_norm\": 0.754601226993865,\n \"acc_norm_stderr\": 0.03380939813943354\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4107142857142857,\n\
\ \"acc_stderr\": 0.046695106638751906,\n \"acc_norm\": 0.4107142857142857,\n\
\ \"acc_norm_stderr\": 0.046695106638751906\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\
\ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8760683760683761,\n\
\ \"acc_stderr\": 0.021586494001281376,\n \"acc_norm\": 0.8760683760683761,\n\
\ \"acc_norm_stderr\": 0.021586494001281376\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \
\ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542127\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\": 0.6994219653179191,\n \"acc_stderr\": 0.024685316867257796,\n\
\ \"acc_norm\": 0.6994219653179191,\n \"acc_norm_stderr\": 0.024685316867257796\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.42569832402234636,\n\
\ \"acc_stderr\": 0.01653682964899711,\n \"acc_norm\": 0.42569832402234636,\n\
\ \"acc_norm_stderr\": 0.01653682964899711\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.6993464052287581,\n \"acc_stderr\": 0.02625605383571896,\n\
\ \"acc_norm\": 0.6993464052287581,\n \"acc_norm_stderr\": 0.02625605383571896\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6881028938906752,\n\
\ \"acc_stderr\": 0.026311858071854155,\n \"acc_norm\": 0.6881028938906752,\n\
\ \"acc_norm_stderr\": 0.026311858071854155\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7222222222222222,\n \"acc_stderr\": 0.024922001168886335,\n\
\ \"acc_norm\": 0.7222222222222222,\n \"acc_norm_stderr\": 0.024922001168886335\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.48936170212765956,\n \"acc_stderr\": 0.029820747191422473,\n \
\ \"acc_norm\": 0.48936170212765956,\n \"acc_norm_stderr\": 0.029820747191422473\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.48435462842242505,\n\
\ \"acc_stderr\": 0.012763982838120958,\n \"acc_norm\": 0.48435462842242505,\n\
\ \"acc_norm_stderr\": 0.012763982838120958\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6875,\n \"acc_stderr\": 0.02815637344037142,\n \
\ \"acc_norm\": 0.6875,\n \"acc_norm_stderr\": 0.02815637344037142\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6699346405228758,\n \"acc_stderr\": 0.019023726160724553,\n \
\ \"acc_norm\": 0.6699346405228758,\n \"acc_norm_stderr\": 0.019023726160724553\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\
\ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\
\ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784596,\n\
\ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784596\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8308457711442786,\n\
\ \"acc_stderr\": 0.026508590656233268,\n \"acc_norm\": 0.8308457711442786,\n\
\ \"acc_norm_stderr\": 0.026508590656233268\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.86,\n \"acc_stderr\": 0.03487350880197771,\n \
\ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.03487350880197771\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5662650602409639,\n\
\ \"acc_stderr\": 0.03858158940685516,\n \"acc_norm\": 0.5662650602409639,\n\
\ \"acc_norm_stderr\": 0.03858158940685516\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8362573099415205,\n \"acc_stderr\": 0.028380919596145866,\n\
\ \"acc_norm\": 0.8362573099415205,\n \"acc_norm_stderr\": 0.028380919596145866\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.6291309669522643,\n\
\ \"mc1_stderr\": 0.016909693580248835,\n \"mc2\": 0.7809489116779263,\n\
\ \"mc2_stderr\": 0.013701734554887294\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8516179952644041,\n \"acc_stderr\": 0.009990706005184136\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6527672479150872,\n \
\ \"acc_stderr\": 0.013113898382146877\n }\n}\n```"
repo_url: https://huggingface.co/yleo/EmertonMonarch-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_02_14T15_51_06.640306
path:
- '**/details_harness|arc:challenge|25_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|gsm8k|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hellaswag|10_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-14T15-51-06.640306.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-14T15-51-06.640306.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- '**/details_harness|winogrande|5_2024-02-14T15-51-06.640306.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-02-14T15-51-06.640306.parquet'
- config_name: results
data_files:
- split: 2024_02_14T15_51_06.640306
path:
- results_2024-02-14T15-51-06.640306.parquet
- split: latest
path:
- results_2024-02-14T15-51-06.640306.parquet
---
# Dataset Card for Evaluation run of yleo/EmertonMonarch-7B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [yleo/EmertonMonarch-7B](https://huggingface.co/yleo/EmertonMonarch-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 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_yleo__EmertonMonarch-7B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-02-14T15:51:06.640306](https://huggingface.co/datasets/open-llm-leaderboard/details_yleo__EmertonMonarch-7B/blob/main/results_2024-02-14T15-51-06.640306.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": 0.6464761697140718,
"acc_stderr": 0.03222241013310851,
"acc_norm": 0.6461858589602053,
"acc_norm_stderr": 0.03289455177300504,
"mc1": 0.6291309669522643,
"mc1_stderr": 0.016909693580248835,
"mc2": 0.7809489116779263,
"mc2_stderr": 0.013701734554887294
},
"harness|arc:challenge|25": {
"acc": 0.7056313993174061,
"acc_stderr": 0.013318528460539422,
"acc_norm": 0.726962457337884,
"acc_norm_stderr": 0.013019332762635751
},
"harness|hellaswag|10": {
"acc": 0.7185819557857,
"acc_stderr": 0.004487718843330278,
"acc_norm": 0.8915554670384386,
"acc_norm_stderr": 0.0031030554162430565
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.3,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6074074074074074,
"acc_stderr": 0.0421850621536888,
"acc_norm": 0.6074074074074074,
"acc_norm_stderr": 0.0421850621536888
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.7039473684210527,
"acc_stderr": 0.03715062154998904,
"acc_norm": 0.7039473684210527,
"acc_norm_stderr": 0.03715062154998904
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.63,
"acc_stderr": 0.048523658709391,
"acc_norm": 0.63,
"acc_norm_stderr": 0.048523658709391
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6830188679245283,
"acc_stderr": 0.02863723563980089,
"acc_norm": 0.6830188679245283,
"acc_norm_stderr": 0.02863723563980089
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7708333333333334,
"acc_stderr": 0.03514697467862388,
"acc_norm": 0.7708333333333334,
"acc_norm_stderr": 0.03514697467862388
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.48,
"acc_stderr": 0.050211673156867795,
"acc_norm": 0.48,
"acc_norm_stderr": 0.050211673156867795
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620333,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620333
},
"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": 0.6242774566473989,
"acc_stderr": 0.036928207672648664,
"acc_norm": 0.6242774566473989,
"acc_norm_stderr": 0.036928207672648664
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.38235294117647056,
"acc_stderr": 0.04835503696107224,
"acc_norm": 0.38235294117647056,
"acc_norm_stderr": 0.04835503696107224
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.73,
"acc_stderr": 0.0446196043338474,
"acc_norm": 0.73,
"acc_norm_stderr": 0.0446196043338474
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5276595744680851,
"acc_stderr": 0.03263597118409769,
"acc_norm": 0.5276595744680851,
"acc_norm_stderr": 0.03263597118409769
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.47368421052631576,
"acc_stderr": 0.04697085136647863,
"acc_norm": 0.47368421052631576,
"acc_norm_stderr": 0.04697085136647863
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5724137931034483,
"acc_stderr": 0.04122737111370332,
"acc_norm": 0.5724137931034483,
"acc_norm_stderr": 0.04122737111370332
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.41534391534391535,
"acc_stderr": 0.025379524910778398,
"acc_norm": 0.41534391534391535,
"acc_norm_stderr": 0.025379524910778398
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.4603174603174603,
"acc_stderr": 0.04458029125470973,
"acc_norm": 0.4603174603174603,
"acc_norm_stderr": 0.04458029125470973
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.3,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7806451612903226,
"acc_stderr": 0.023540799358723292,
"acc_norm": 0.7806451612903226,
"acc_norm_stderr": 0.023540799358723292
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.5073891625615764,
"acc_stderr": 0.035176035403610105,
"acc_norm": 0.5073891625615764,
"acc_norm_stderr": 0.035176035403610105
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.7,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.7,
"acc_norm_stderr": 0.046056618647183814
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7575757575757576,
"acc_stderr": 0.03346409881055953,
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"harness|hendrycksTest-us_foreign_policy|5": {
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"harness|hendrycksTest-virology|5": {
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"harness|hendrycksTest-world_religions|5": {
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"harness|truthfulqa:mc|0": {
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"harness|winogrande|5": {
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"harness|gsm8k|5": {
"acc": 0.6527672479150872,
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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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## More Information [optional]
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## Dataset Card Authors [optional]
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## Dataset Card Contact
[More Information Needed] |
VedCodes/EasyShareDataset | ---
task_categories:
- text-generation
language:
- en
pretty_name: tiny1_demo
--- |
jadasdn/trial_Level_2_A | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: sentence
dtype: string
splits:
- name: train
num_bytes: 2624020367.8833747
num_examples: 58098
download_size: 2607714351
dataset_size: 2624020367.8833747
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "trial_Level_2_A"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Nexdata/Multi-race_and_Multi-pose_Face_Images_Data | ---
YAML tags:
- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
---
# Dataset Card for Nexdata/Multi-race_and_Multi-pose_Face_Images_Data
## 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:** https://www.nexdata.ai/datasets/1016?source=Huggingface
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
23,110 People Multi-race and Multi-pose Face Images Data. This data includes Asian race, Caucasian race, black race, brown race and Indians. Each subject were collected 29 images under different scenes and light conditions. The 29 images include 28 photos (multi light conditions, multiple poses and multiple scenes) + 1 ID photo. This data can be used for face recognition related tasks.
For more details, please refer to the link: https://www.nexdata.ai/datasets/1016?source=Huggingface
### Supported Tasks and Leaderboards
face-detection, computer-vision: The dataset can be used to train a model for face detection.
### Languages
English
## 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
Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing
### Citation Information
[More Information Needed]
### Contributions |
KatMarie/eu_test3 | ---
dataset_info:
features:
- name: sentence
dtype: string
splits:
- name: train
num_bytes: 302617
num_examples: 5172
download_size: 207896
dataset_size: 302617
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "eu_test3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
shokhjakhon/koni-dataset-v2 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 4710307
num_examples: 3000
download_size: 2785880
dataset_size: 4710307
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
CyberHarem/neptune_azurlane | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of neptune/ネプチューン/海王星 (Azur Lane)
This is the dataset of neptune/ネプチューン/海王星 (Azur Lane), containing 176 images and their tags.
The core tags of this character are `blue_hair, long_hair, breasts, yellow_eyes, maid_headdress, large_breasts, bangs, two_side_up, medium_breasts, shell_hair_ornament`, 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 | 176 | 299.96 MiB | [Download](https://huggingface.co/datasets/CyberHarem/neptune_azurlane/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 176 | 154.48 MiB | [Download](https://huggingface.co/datasets/CyberHarem/neptune_azurlane/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 448 | 344.73 MiB | [Download](https://huggingface.co/datasets/CyberHarem/neptune_azurlane/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 176 | 258.05 MiB | [Download](https://huggingface.co/datasets/CyberHarem/neptune_azurlane/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 448 | 522.18 MiB | [Download](https://huggingface.co/datasets/CyberHarem/neptune_azurlane/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/neptune_azurlane',
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 | 11 |  |  |  |  |  | 1girl, fake_antlers, solo, detached_sleeves, looking_at_viewer, red_capelet, red_skirt, smile, underboob_cutout, white_thighhighs, blush, reindeer_antlers, :p, frills, gift_box, red_ribbon, covered_navel, lace_trim, long_sleeves, sitting, thighs, christmas_tree, fur-trimmed_capelet, red_bow, sidelocks |
| 1 | 5 |  |  |  |  |  | 1girl, christmas, fake_antlers, red_capelet, underboob_cutout, upper_body, blush, fur-trimmed_capelet, long_sleeves, looking_at_viewer, solo, closed_mouth, light_blue_hair, official_alternate_costume, simple_background, smile, detached_sleeves, green_bowtie, hair_ornament, holding, red_ribbon, trident, white_background, white_dress |
| 2 | 8 |  |  |  |  |  | 1girl, cleavage, detached_sleeves, dress, looking_at_viewer, solo, bare_shoulders, maid, smile, white_background, simple_background, white_thighhighs, frills, apron, blush, clothing_cutout, holding, skirt_hold, open_mouth, tray |
| 3 | 5 |  |  |  |  |  | 1girl, bare_shoulders, black_bowtie, black_dress, blush, cleavage, detached_collar, detached_sleeves, looking_at_viewer, maid, solo, very_long_hair, waist_apron, white_apron, gem, simple_background, smile, white_background, frilled_apron, juliet_sleeves, clothing_cutout, cowboy_shot, frilled_dress, hand_on_hip, hand_on_own_chest, holding, standing, twitter_username |
| 4 | 7 |  |  |  |  |  | 1girl, cleavage, detached_sleeves, looking_at_viewer, solo, trident, maid, smile, bare_shoulders, thighhighs, apron, dress |
| 5 | 8 |  |  |  |  |  | 1girl, blue_dress, cleavage, earrings, looking_at_viewer, solo, bare_shoulders, blue_nails, blush, blue_footwear, bridal_gauntlets, hair_ornament, skirt_hold, smile, collarbone, halter_dress, high_heels, nail_polish, thighs, trident, choker, full_body, holding, ribbon |
| 6 | 7 |  |  |  |  |  | 1boy, blush, hetero, looking_at_viewer, nipples, 1girl, penis, solo_focus, detached_sleeves, open_mouth, maid, bar_censor, cum, heart, nude, paizuri, sex, tongue_out |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | fake_antlers | solo | detached_sleeves | looking_at_viewer | red_capelet | red_skirt | smile | underboob_cutout | white_thighhighs | blush | reindeer_antlers | :p | frills | gift_box | red_ribbon | covered_navel | lace_trim | long_sleeves | sitting | thighs | christmas_tree | fur-trimmed_capelet | red_bow | sidelocks | christmas | upper_body | closed_mouth | light_blue_hair | official_alternate_costume | simple_background | green_bowtie | hair_ornament | holding | trident | white_background | white_dress | cleavage | dress | bare_shoulders | maid | apron | clothing_cutout | skirt_hold | open_mouth | tray | black_bowtie | black_dress | detached_collar | very_long_hair | waist_apron | white_apron | gem | frilled_apron | juliet_sleeves | cowboy_shot | frilled_dress | hand_on_hip | hand_on_own_chest | standing | twitter_username | thighhighs | blue_dress | earrings | blue_nails | blue_footwear | bridal_gauntlets | collarbone | halter_dress | high_heels | nail_polish | choker | full_body | ribbon | 1boy | hetero | nipples | penis | solo_focus | bar_censor | cum | heart | nude | paizuri | sex | tongue_out |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:-------|:-------------------|:--------------------|:--------------|:------------|:--------|:-------------------|:-------------------|:--------|:-------------------|:-----|:---------|:-----------|:-------------|:----------------|:------------|:---------------|:----------|:---------|:-----------------|:----------------------|:----------|:------------|:------------|:-------------|:---------------|:------------------|:-----------------------------|:--------------------|:---------------|:----------------|:----------|:----------|:-------------------|:--------------|:-----------|:--------|:-----------------|:-------|:--------|:------------------|:-------------|:-------------|:-------|:---------------|:--------------|:------------------|:-----------------|:--------------|:--------------|:------|:----------------|:-----------------|:--------------|:----------------|:--------------|:--------------------|:-----------|:-------------------|:-------------|:-------------|:-----------|:-------------|:----------------|:-------------------|:-------------|:---------------|:-------------|:--------------|:---------|:------------|:---------|:-------|:---------|:----------|:--------|:-------------|:-------------|:------|:--------|:-------|:----------|:------|:-------------|
| 0 | 11 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 5 |  |  |  |  |  | X | X | X | X | X | X | | X | X | | X | | | | | X | | | X | | | | X | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 8 |  |  |  |  |  | X | | X | X | X | | | X | | X | X | | | X | | | | | | | | | | | | | | | | | X | | | X | | X | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | | X | X | X | | | X | | | X | | | | | | | | | | | | | | | | | | | | X | | | X | | X | | X | | X | X | | X | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 7 |  |  |  |  |  | X | | X | X | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 8 |  |  |  |  |  | X | | X | | X | | | X | | | X | | | | | | | | | | X | | | | | | | | | | | | X | X | X | | | X | | X | | | | X | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | |
| 6 | 7 |  |  |  |  |  | X | | | X | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X |
|
kshitijkapoor/pure-hindi-images | ---
license: apache-2.0
---
|
Jing24/seperate_all5 | ---
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
struct:
- name: answer_start
sequence: int32
- name: text
sequence: string
splits:
- name: train
num_bytes: 45027974
num_examples: 49492
download_size: 8152264
dataset_size: 45027974
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "seperate_all5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ChengAoShen/emoji_fusion | ---
dataset_info:
features:
- name: image
dtype: image
- name: condition1
dtype: image
- name: condition2
dtype: image
splits:
- name: train
num_bytes: 450271505.25
num_examples: 40250
download_size: 255050460
dataset_size: 450271505.25
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "emoji_fusion"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_NLUHOPOE__experiment2-cause-non | ---
pretty_name: Evaluation run of NLUHOPOE/experiment2-cause-non
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [NLUHOPOE/experiment2-cause-non](https://huggingface.co/NLUHOPOE/experiment2-cause-non)\
\ 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_NLUHOPOE__experiment2-cause-non\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-02T01:14:57.258315](https://huggingface.co/datasets/open-llm-leaderboard/details_NLUHOPOE__experiment2-cause-non/blob/main/results_2024-03-02T01-14-57.258315.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\": 0.6197987667684087,\n\
\ \"acc_stderr\": 0.03270734461121569,\n \"acc_norm\": 0.6261639848463227,\n\
\ \"acc_norm_stderr\": 0.03337642036997771,\n \"mc1\": 0.30966952264381886,\n\
\ \"mc1_stderr\": 0.016185744355144912,\n \"mc2\": 0.45469695402927457,\n\
\ \"mc2_stderr\": 0.01450788864306172\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5588737201365188,\n \"acc_stderr\": 0.014509747749064663,\n\
\ \"acc_norm\": 0.6032423208191127,\n \"acc_norm_stderr\": 0.014296513020180639\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6211909978092014,\n\
\ \"acc_stderr\": 0.00484099059349469,\n \"acc_norm\": 0.8292172873929496,\n\
\ \"acc_norm_stderr\": 0.0037554989417818516\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.27,\n \"acc_stderr\": 0.0446196043338474,\n \
\ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\
\ \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\
\ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\
\ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6710526315789473,\n \"acc_stderr\": 0.03823428969926604,\n\
\ \"acc_norm\": 0.6710526315789473,\n \"acc_norm_stderr\": 0.03823428969926604\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.54,\n\
\ \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.54,\n \
\ \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7018867924528301,\n \"acc_stderr\": 0.028152837942493864,\n\
\ \"acc_norm\": 0.7018867924528301,\n \"acc_norm_stderr\": 0.028152837942493864\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7222222222222222,\n\
\ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.7222222222222222,\n\
\ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\
: 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-college_computer_science|5\"\
: {\n \"acc\": 0.55,\n \"acc_stderr\": 0.04999999999999999,\n \
\ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.04999999999999999\n \
\ },\n \"harness|hendrycksTest-college_mathematics|5\": {\n \"acc\": 0.41,\n\
\ \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.41,\n \
\ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-college_medicine|5\"\
: {\n \"acc\": 0.6069364161849711,\n \"acc_stderr\": 0.03724249595817731,\n\
\ \"acc_norm\": 0.6069364161849711,\n \"acc_norm_stderr\": 0.03724249595817731\n\
\ },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.35294117647058826,\n\
\ \"acc_stderr\": 0.04755129616062946,\n \"acc_norm\": 0.35294117647058826,\n\
\ \"acc_norm_stderr\": 0.04755129616062946\n },\n \"harness|hendrycksTest-computer_security|5\"\
: {\n \"acc\": 0.74,\n \"acc_stderr\": 0.0440844002276808,\n \
\ \"acc_norm\": 0.74,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\
\ \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\": 0.5276595744680851,\n\
\ \"acc_stderr\": 0.03263597118409769,\n \"acc_norm\": 0.5276595744680851,\n\
\ \"acc_norm_stderr\": 0.03263597118409769\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\"\
: 0.6068965517241379,\n \"acc_stderr\": 0.040703290137070705,\n \"\
acc_norm\": 0.6068965517241379,\n \"acc_norm_stderr\": 0.040703290137070705\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.3888888888888889,\n \"acc_stderr\": 0.025107425481137285,\n \"\
acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.025107425481137285\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4365079365079365,\n\
\ \"acc_stderr\": 0.04435932892851466,\n \"acc_norm\": 0.4365079365079365,\n\
\ \"acc_norm_stderr\": 0.04435932892851466\n },\n \"harness|hendrycksTest-global_facts|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-high_school_biology|5\": {\n \"acc\"\
: 0.7322580645161291,\n \"acc_stderr\": 0.02518900666021238,\n \"\
acc_norm\": 0.7322580645161291,\n \"acc_norm_stderr\": 0.02518900666021238\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.5024630541871922,\n \"acc_stderr\": 0.035179450386910616,\n \"\
acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.035179450386910616\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\"\
: 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7454545454545455,\n \"acc_stderr\": 0.03401506715249039,\n\
\ \"acc_norm\": 0.7454545454545455,\n \"acc_norm_stderr\": 0.03401506715249039\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267042,\n \"\
acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267042\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8601036269430051,\n \"acc_stderr\": 0.025033870583015184,\n\
\ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.025033870583015184\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6487179487179487,\n \"acc_stderr\": 0.024203665177902803,\n\
\ \"acc_norm\": 0.6487179487179487,\n \"acc_norm_stderr\": 0.024203665177902803\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.32222222222222224,\n \"acc_stderr\": 0.028493465091028593,\n \
\ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.028493465091028593\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6470588235294118,\n \"acc_stderr\": 0.031041941304059285,\n\
\ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.031041941304059285\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.32450331125827814,\n \"acc_stderr\": 0.038227469376587525,\n \"\
acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.038227469376587525\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8018348623853211,\n \"acc_stderr\": 0.017090573804217905,\n \"\
acc_norm\": 0.8018348623853211,\n \"acc_norm_stderr\": 0.017090573804217905\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5462962962962963,\n \"acc_stderr\": 0.03395322726375798,\n \"\
acc_norm\": 0.5462962962962963,\n \"acc_norm_stderr\": 0.03395322726375798\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.7892156862745098,\n \"acc_stderr\": 0.028626547912437406,\n \"\
acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.028626547912437406\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7468354430379747,\n \"acc_stderr\": 0.028304657943035307,\n \
\ \"acc_norm\": 0.7468354430379747,\n \"acc_norm_stderr\": 0.028304657943035307\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6547085201793722,\n\
\ \"acc_stderr\": 0.03191100192835794,\n \"acc_norm\": 0.6547085201793722,\n\
\ \"acc_norm_stderr\": 0.03191100192835794\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\":\
\ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070416,\n \"\
acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070416\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\": 0.7607361963190185,\n \"acc_stderr\": 0.033519538795212696,\n\
\ \"acc_norm\": 0.7607361963190185,\n \"acc_norm_stderr\": 0.033519538795212696\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\": 0.8547008547008547,\n\
\ \"acc_stderr\": 0.02308663508684141,\n \"acc_norm\": 0.8547008547008547,\n\
\ \"acc_norm_stderr\": 0.02308663508684141\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621504,\n \
\ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.04688261722621504\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7969348659003831,\n\
\ \"acc_stderr\": 0.014385525076611573,\n \"acc_norm\": 0.7969348659003831,\n\
\ \"acc_norm_stderr\": 0.014385525076611573\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.6878612716763006,\n \"acc_stderr\": 0.02494679222527231,\n\
\ \"acc_norm\": 0.6878612716763006,\n \"acc_norm_stderr\": 0.02494679222527231\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3888268156424581,\n\
\ \"acc_stderr\": 0.016303899530796136,\n \"acc_norm\": 0.3888268156424581,\n\
\ \"acc_norm_stderr\": 0.016303899530796136\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7156862745098039,\n \"acc_stderr\": 0.025829163272757482,\n\
\ \"acc_norm\": 0.7156862745098039,\n \"acc_norm_stderr\": 0.025829163272757482\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6688102893890675,\n\
\ \"acc_stderr\": 0.02673062072800491,\n \"acc_norm\": 0.6688102893890675,\n\
\ \"acc_norm_stderr\": 0.02673062072800491\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\": 0.029719281272236844,\n \
\ \"acc_norm\": 0.4574468085106383,\n \"acc_norm_stderr\": 0.029719281272236844\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4380704041720991,\n\
\ \"acc_stderr\": 0.01267190278256765,\n \"acc_norm\": 0.4380704041720991,\n\
\ \"acc_norm_stderr\": 0.01267190278256765\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6102941176470589,\n \"acc_stderr\": 0.029624663581159703,\n\
\ \"acc_norm\": 0.6102941176470589,\n \"acc_norm_stderr\": 0.029624663581159703\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6372549019607843,\n \"acc_stderr\": 0.019450768432505514,\n \
\ \"acc_norm\": 0.6372549019607843,\n \"acc_norm_stderr\": 0.019450768432505514\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\
\ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\
\ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7020408163265306,\n \"acc_stderr\": 0.02927956741106568,\n\
\ \"acc_norm\": 0.7020408163265306,\n \"acc_norm_stderr\": 0.02927956741106568\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.835820895522388,\n\
\ \"acc_stderr\": 0.026193923544454125,\n \"acc_norm\": 0.835820895522388,\n\
\ \"acc_norm_stderr\": 0.026193923544454125\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896309,\n \
\ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896309\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5301204819277109,\n\
\ \"acc_stderr\": 0.03885425420866767,\n \"acc_norm\": 0.5301204819277109,\n\
\ \"acc_norm_stderr\": 0.03885425420866767\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8070175438596491,\n \"acc_stderr\": 0.030267457554898458,\n\
\ \"acc_norm\": 0.8070175438596491,\n \"acc_norm_stderr\": 0.030267457554898458\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.30966952264381886,\n\
\ \"mc1_stderr\": 0.016185744355144912,\n \"mc2\": 0.45469695402927457,\n\
\ \"mc2_stderr\": 0.01450788864306172\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7805840568271507,\n \"acc_stderr\": 0.01163126836060778\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.33586050037907506,\n \
\ \"acc_stderr\": 0.013009224714267353\n }\n}\n```"
repo_url: https://huggingface.co/NLUHOPOE/experiment2-cause-non
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_01T13_41_42.315208
path:
- '**/details_harness|arc:challenge|25_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|arc:challenge|25_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|gsm8k|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|gsm8k|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hellaswag|10_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hellaswag|10_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T13-41-42.315208.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T01-14-57.258315.parquet'
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- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T01-14-57.258315.parquet'
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- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T01-14-57.258315.parquet'
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- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T01-14-57.258315.parquet'
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- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T01-14-57.258315.parquet'
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- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T01-14-57.258315.parquet'
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- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T01-14-57.258315.parquet'
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- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T01-14-57.258315.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-02T01-14-57.258315.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- '**/details_harness|winogrande|5_2024-03-01T13-41-42.315208.parquet'
- split: 2024_03_02T01_14_57.258315
path:
- '**/details_harness|winogrande|5_2024-03-02T01-14-57.258315.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-02T01-14-57.258315.parquet'
- config_name: results
data_files:
- split: 2024_03_01T13_41_42.315208
path:
- results_2024-03-01T13-41-42.315208.parquet
- split: 2024_03_02T01_14_57.258315
path:
- results_2024-03-02T01-14-57.258315.parquet
- split: latest
path:
- results_2024-03-02T01-14-57.258315.parquet
---
# Dataset Card for Evaluation run of NLUHOPOE/experiment2-cause-non
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [NLUHOPOE/experiment2-cause-non](https://huggingface.co/NLUHOPOE/experiment2-cause-non) 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_NLUHOPOE__experiment2-cause-non",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-02T01:14:57.258315](https://huggingface.co/datasets/open-llm-leaderboard/details_NLUHOPOE__experiment2-cause-non/blob/main/results_2024-03-02T01-14-57.258315.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": 0.6197987667684087,
"acc_stderr": 0.03270734461121569,
"acc_norm": 0.6261639848463227,
"acc_norm_stderr": 0.03337642036997771,
"mc1": 0.30966952264381886,
"mc1_stderr": 0.016185744355144912,
"mc2": 0.45469695402927457,
"mc2_stderr": 0.01450788864306172
},
"harness|arc:challenge|25": {
"acc": 0.5588737201365188,
"acc_stderr": 0.014509747749064663,
"acc_norm": 0.6032423208191127,
"acc_norm_stderr": 0.014296513020180639
},
"harness|hellaswag|10": {
"acc": 0.6211909978092014,
"acc_stderr": 0.00484099059349469,
"acc_norm": 0.8292172873929496,
"acc_norm_stderr": 0.0037554989417818516
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.27,
"acc_stderr": 0.0446196043338474,
"acc_norm": 0.27,
"acc_norm_stderr": 0.0446196043338474
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6370370370370371,
"acc_stderr": 0.04153948404742398,
"acc_norm": 0.6370370370370371,
"acc_norm_stderr": 0.04153948404742398
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6710526315789473,
"acc_stderr": 0.03823428969926604,
"acc_norm": 0.6710526315789473,
"acc_norm_stderr": 0.03823428969926604
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620333,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620333
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7018867924528301,
"acc_stderr": 0.028152837942493864,
"acc_norm": 0.7018867924528301,
"acc_norm_stderr": 0.028152837942493864
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7222222222222222,
"acc_stderr": 0.037455547914624555,
"acc_norm": 0.7222222222222222,
"acc_norm_stderr": 0.037455547914624555
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.45,
"acc_stderr": 0.05,
"acc_norm": 0.45,
"acc_norm_stderr": 0.05
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.55,
"acc_stderr": 0.04999999999999999,
"acc_norm": 0.55,
"acc_norm_stderr": 0.04999999999999999
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.41,
"acc_stderr": 0.04943110704237102,
"acc_norm": 0.41,
"acc_norm_stderr": 0.04943110704237102
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6069364161849711,
"acc_stderr": 0.03724249595817731,
"acc_norm": 0.6069364161849711,
"acc_norm_stderr": 0.03724249595817731
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.35294117647058826,
"acc_stderr": 0.04755129616062946,
"acc_norm": 0.35294117647058826,
"acc_norm_stderr": 0.04755129616062946
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.74,
"acc_stderr": 0.0440844002276808,
"acc_norm": 0.74,
"acc_norm_stderr": 0.0440844002276808
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5276595744680851,
"acc_stderr": 0.03263597118409769,
"acc_norm": 0.5276595744680851,
"acc_norm_stderr": 0.03263597118409769
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.4473684210526316,
"acc_stderr": 0.04677473004491199,
"acc_norm": 0.4473684210526316,
"acc_norm_stderr": 0.04677473004491199
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.6068965517241379,
"acc_stderr": 0.040703290137070705,
"acc_norm": 0.6068965517241379,
"acc_norm_stderr": 0.040703290137070705
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.3888888888888889,
"acc_stderr": 0.025107425481137285,
"acc_norm": 0.3888888888888889,
"acc_norm_stderr": 0.025107425481137285
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.4365079365079365,
"acc_stderr": 0.04435932892851466,
"acc_norm": 0.4365079365079365,
"acc_norm_stderr": 0.04435932892851466
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.35,
"acc_stderr": 0.047937248544110196,
"acc_norm": 0.35,
"acc_norm_stderr": 0.047937248544110196
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7322580645161291,
"acc_stderr": 0.02518900666021238,
"acc_norm": 0.7322580645161291,
"acc_norm_stderr": 0.02518900666021238
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.5024630541871922,
"acc_stderr": 0.035179450386910616,
"acc_norm": 0.5024630541871922,
"acc_norm_stderr": 0.035179450386910616
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.66,
"acc_stderr": 0.04760952285695237,
"acc_norm": 0.66,
"acc_norm_stderr": 0.04760952285695237
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7454545454545455,
"acc_stderr": 0.03401506715249039,
"acc_norm": 0.7454545454545455,
"acc_norm_stderr": 0.03401506715249039
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7929292929292929,
"acc_stderr": 0.028869778460267042,
"acc_norm": 0.7929292929292929,
"acc_norm_stderr": 0.028869778460267042
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.8601036269430051,
"acc_stderr": 0.025033870583015184,
"acc_norm": 0.8601036269430051,
"acc_norm_stderr": 0.025033870583015184
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.6487179487179487,
"acc_stderr": 0.024203665177902803,
"acc_norm": 0.6487179487179487,
"acc_norm_stderr": 0.024203665177902803
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.32222222222222224,
"acc_stderr": 0.028493465091028593,
"acc_norm": 0.32222222222222224,
"acc_norm_stderr": 0.028493465091028593
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6470588235294118,
"acc_stderr": 0.031041941304059285,
"acc_norm": 0.6470588235294118,
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}
```
## Dataset Details
### Dataset Description
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Jayfeather1024/Reward-Embeddings | ---
license: unknown
---
# RLHF Reward Model Embedding Features for PKU-Alignment/PKU-SafeRLHF Dataset
The RLHF reward model embedding features and corresponding original text are stored in `embeddings_train.jsonl` and `embeddings_test.jsonl`.
The dataset is stored in pairwise ways: each data pair has 1) safer_example: input text of the safer example, 2) not_safer_example: input text of the more harmful example, 3) safer_embedding: embedding feature of the safer example, 4) not_safer_embedding: embedding feature of the more harmful example.
The hidden embedding dimension is 4096. The reward model uses a linear layer to transfer the embedding features into a 1-dimensional score value.
Note: The dataset is extremely large because of the large size of the original training dataset and the high dimension of embedding space.
# Original Dataset
If you need more detailed information about the original dataset, please refer to `train.jsonl.xz` and `test.jsonl.xz`. Since we use `shuffle=False` when generating the embeddings, orders are remained in our dataset.
# Note
This dataset is a processed version of PKU-Alignment/PKU-SafeRLHF: <https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF>. |
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