datasetId stringlengths 2 117 | card stringlengths 19 1.01M |
|---|---|
korotkov/glaive-function-calling-v2-ru-parsed | ---
task_categories:
- text-generation
language:
- ru
pretty_name: Glaive Function Calling V2 Parsed
size_categories:
- 100K<n<1M
---
# Glaive Function Calling V2 Parsed (RU)
This dataset is a fork of an original [mizinovmv/glaive-function-calling-v2-ru](https://huggingface.co/datasets/mizinovmv/glaive-function-calling-v2-ru).
## Structure
* train (102860 rows)
- messages
- functions
* test (9681 rows)
- messages
- functions
Messages field contains JSON string with list of messages. Each message has role (one of: system, user, assistant, function_call, function_response) and content (message string) fields.
Functions field contains JSON string with list of functions for current chat (their number may vary from 0 to 2).
Functions in train and test sets do not intersect.
## How to use
Example of converting messages list into one string
```python
import json
from datasets import load_dataset
# Download dataset from huggingface
dataset = load_dataset("korotkov/glaive-function-calling-v2-ru-parsed")
# Convert messages list into string
messages_string = []
for message in json.loads(dataset["train"]["messages"][1]):
messages_string.append(f"{message['role'].upper()}: {message['content']}")
messages_string = "\n\n".join(messages_string)
print(messages_string)
```
Output:
```json
SYSTEM: Ты полезный помощник с доступом к следующим функциям. Используй их при необходимости:
{
"name": "calculate_square",
"description": "Вычислить квадрат числа",
"parameters": {
"type": "object",
"properties": {
"number": {
"type": "number",
"description": "Число для вычисления квадрата"
}
},
"required": [
"number"
]
}
},
{
"name": "schedule_appointment",
"description": "Запланировать встречу",
"parameters": {
"type": "object",
"properties": {
"date": {
"type": "string",
"description": "Дата назначения"
},
"time": {
"type": "string",
"description": "Время встречи"
},
"description": {
"type": "string",
"description": "Описание встречи"
}
},
"required": [
"date",
"time"
]
}
}
USER: Привет, мне нужна помощь с задачей по математике.
ASSISTANT: Конечно! Я был бы рад помочь. В чем проблема?
USER: Мне нужно найти квадрат 7.
FUNCTION_CALL: {"name": "calculate_square", "arguments": {"number": 7}}
FUNCTION_RESPONSE: {"result": 49}
ASSISTANT: Квадрат 7 равен 49.
USER: Большое спасибо! А теперь можешь помочь мне заказать пиццу?
ASSISTANT: Извините, но я, как ИИ, не имею возможности выполнять внешние задачи, например, заказывать пиццу. Я могу оказывать помощь только в соответствии с запрограммированными мной функциями. В настоящее время я могу помочь с вычислением квадрата числа.
``` |
SINAI/share | ---
license: cc-by-nc-sa-4.0
language:
- es
tags:
- hate speech
- insults
- spanish
- offensive expressions
- offensive language
pretty_name: SHARE
size_categories:
- 10K<n<100K
---
### Dataset Description
**Paper**: [SHARE: A Lexicon of Harmful Expressions by Spanish Speakers](https://aclanthology.org/2022.lrec-1.139.pdf)
**Point of Contact**: flor.plaza@unibocconi.it, maite@ujaen.es
### Source Data
Telegram
### Licensing Information
SHARE is released under the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0).
### Citation Information
```
@inproceedings{plaza-del-arco-etal-2022-share,
title = "{SHARE}: A Lexicon of Harmful Expressions by {S}panish Speakers",
author = "{Plaza-del-Arco}, Flor Miriam and
Parras Portillo, Ana Belén and
López-Úbeda, Pilar and
Gil, Beatriz and
Martín-Valdivia, María-Teresa",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.139",
pages = "1307--1316"}
``` |
renumics/spotlight-mnist-enrichment | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image.embedding
sequence: float32
length: 2
splits:
- name: train
num_bytes: 480000
num_examples: 60000
- name: test
num_bytes: 80000
num_examples: 10000
download_size: 778435
dataset_size: 560000
---
# Dataset Card for "spotlight-mnist-enrichment"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
AdapterOcean/med_alpaca_standardized_cluster_52_alpaca | ---
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 29809228
num_examples: 15142
download_size: 14860344
dataset_size: 29809228
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "med_alpaca_standardized_cluster_52_alpaca"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
joey234/mmlu-philosophy-original-neg | ---
dataset_info:
features:
- name: question
dtype: string
- name: choices
sequence: string
- name: answer
dtype:
class_label:
names:
'0': A
'1': B
'2': C
'3': D
splits:
- name: test
num_bytes: 11326.958199356914
num_examples: 44
download_size: 14783
dataset_size: 11326.958199356914
---
# Dataset Card for "mmlu-philosophy-original-neg"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
mask-distilled-onesec-cv12-each-chunk-uniq/chunk_204 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1123478512.0
num_examples: 220636
download_size: 1147792515
dataset_size: 1123478512.0
---
# Dataset Card for "chunk_204"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
lumijek/deeplense-diffusion | ---
language:
- en
size_categories:
- 10K<n<100K
--- |
SadeghJafari/CVC | ---
license: apache-2.0
---
|
maitri-vv/UN16_Peace-Justice | ---
task_categories:
- question-answering
tags:
- legal
size_categories:
- n<1K
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
open-llm-leaderboard/details_Minami-su__Qwen1.5-0.5B-Chat_mistral | ---
pretty_name: Evaluation run of Minami-su/Qwen1.5-0.5B-Chat_mistral
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Minami-su/Qwen1.5-0.5B-Chat_mistral](https://huggingface.co/Minami-su/Qwen1.5-0.5B-Chat_mistral)\
\ 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_Minami-su__Qwen1.5-0.5B-Chat_mistral\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-25T09:24:56.116599](https://huggingface.co/datasets/open-llm-leaderboard/details_Minami-su__Qwen1.5-0.5B-Chat_mistral/blob/main/results_2024-03-25T09-24-56.116599.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\": 0.23146707204075107,\n\
\ \"acc_stderr\": 0.029930144939974264,\n \"acc_norm\": 0.23180919521674745,\n\
\ \"acc_norm_stderr\": 0.03071922270148664,\n \"mc1\": 0.23011015911872704,\n\
\ \"mc1_stderr\": 0.014734557959807756,\n \"mc2\": 0.49059783076199204,\n\
\ \"mc2_stderr\": 0.01679727487548572\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.2158703071672355,\n \"acc_stderr\": 0.012022975360030679,\n\
\ \"acc_norm\": 0.2551194539249147,\n \"acc_norm_stderr\": 0.012739038695202102\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.2591117307309301,\n\
\ \"acc_stderr\": 0.0043725160601647455,\n \"acc_norm\": 0.2640908185620394,\n\
\ \"acc_norm_stderr\": 0.004399469168272512\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \
\ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.18518518518518517,\n\
\ \"acc_stderr\": 0.03355677216313142,\n \"acc_norm\": 0.18518518518518517,\n\
\ \"acc_norm_stderr\": 0.03355677216313142\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.17763157894736842,\n \"acc_stderr\": 0.031103182383123398,\n\
\ \"acc_norm\": 0.17763157894736842,\n \"acc_norm_stderr\": 0.031103182383123398\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.3,\n\
\ \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n \
\ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.21509433962264152,\n \"acc_stderr\": 0.02528839450289137,\n\
\ \"acc_norm\": 0.21509433962264152,\n \"acc_norm_stderr\": 0.02528839450289137\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2638888888888889,\n\
\ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.2638888888888889,\n\
\ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036845,\n \
\ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036845\n },\n\
\ \"harness|hendrycksTest-college_computer_science|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_mathematics|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-college_medicine|5\": {\n \"acc\": 0.21965317919075145,\n\
\ \"acc_stderr\": 0.031568093627031744,\n \"acc_norm\": 0.21965317919075145,\n\
\ \"acc_norm_stderr\": 0.031568093627031744\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.21568627450980393,\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\":\
\ 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \"acc_norm\": 0.28,\n\
\ \"acc_norm_stderr\": 0.045126085985421276\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102973,\n\
\ \"acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102973\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.23684210526315788,\n\
\ \"acc_stderr\": 0.039994238792813365,\n \"acc_norm\": 0.23684210526315788,\n\
\ \"acc_norm_stderr\": 0.039994238792813365\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135302,\n\
\ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135302\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.20899470899470898,\n \"acc_stderr\": 0.02094048156533486,\n \"\
acc_norm\": 0.20899470899470898,\n \"acc_norm_stderr\": 0.02094048156533486\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2857142857142857,\n\
\ \"acc_stderr\": 0.04040610178208841,\n \"acc_norm\": 0.2857142857142857,\n\
\ \"acc_norm_stderr\": 0.04040610178208841\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.18,\n \"acc_stderr\": 0.038612291966536934,\n \
\ \"acc_norm\": 0.18,\n \"acc_norm_stderr\": 0.038612291966536934\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.1774193548387097,\n \"acc_stderr\": 0.02173254068932927,\n \"\
acc_norm\": 0.1774193548387097,\n \"acc_norm_stderr\": 0.02173254068932927\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.15270935960591134,\n \"acc_stderr\": 0.02530890453938063,\n \"\
acc_norm\": 0.15270935960591134,\n \"acc_norm_stderr\": 0.02530890453938063\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\
: 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\
\ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.17676767676767677,\n \"acc_stderr\": 0.027178752639044915,\n \"\
acc_norm\": 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860664,\n\
\ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.20256410256410257,\n \"acc_stderr\": 0.020377660970371372,\n\
\ \"acc_norm\": 0.20256410256410257,\n \"acc_norm_stderr\": 0.020377660970371372\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.2111111111111111,\n \"acc_stderr\": 0.024882116857655075,\n \
\ \"acc_norm\": 0.2111111111111111,\n \"acc_norm_stderr\": 0.024882116857655075\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.21008403361344538,\n \"acc_stderr\": 0.026461398717471874,\n\
\ \"acc_norm\": 0.21008403361344538,\n \"acc_norm_stderr\": 0.026461398717471874\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.1986754966887417,\n \"acc_stderr\": 0.03257847384436776,\n \"\
acc_norm\": 0.1986754966887417,\n \"acc_norm_stderr\": 0.03257847384436776\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.1926605504587156,\n \"acc_stderr\": 0.016909276884936094,\n \"\
acc_norm\": 0.1926605504587156,\n \"acc_norm_stderr\": 0.016909276884936094\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.1527777777777778,\n \"acc_stderr\": 0.024536326026134224,\n \"\
acc_norm\": 0.1527777777777778,\n \"acc_norm_stderr\": 0.024536326026134224\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.24509803921568626,\n \"acc_stderr\": 0.030190282453501954,\n \"\
acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.030190282453501954\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n \
\ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.31390134529147984,\n\
\ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.31390134529147984,\n\
\ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.2595419847328244,\n \"acc_stderr\": 0.03844876139785271,\n\
\ \"acc_norm\": 0.2595419847328244,\n \"acc_norm_stderr\": 0.03844876139785271\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\
acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25925925925925924,\n\
\ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.25925925925925924,\n\
\ \"acc_norm_stderr\": 0.042365112580946336\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.032591773927421776,\n\
\ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\
\ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\
\ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.17475728155339806,\n \"acc_stderr\": 0.037601780060266224,\n\
\ \"acc_norm\": 0.17475728155339806,\n \"acc_norm_stderr\": 0.037601780060266224\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2905982905982906,\n\
\ \"acc_stderr\": 0.02974504857267404,\n \"acc_norm\": 0.2905982905982906,\n\
\ \"acc_norm_stderr\": 0.02974504857267404\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.23754789272030652,\n\
\ \"acc_stderr\": 0.015218733046150193,\n \"acc_norm\": 0.23754789272030652,\n\
\ \"acc_norm_stderr\": 0.015218733046150193\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\": 0.23798882681564246,\n\
\ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\
\ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.023929155517351284,\n\
\ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.023929155517351284\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.1864951768488746,\n\
\ \"acc_stderr\": 0.022122439772480792,\n \"acc_norm\": 0.1864951768488746,\n\
\ \"acc_norm_stderr\": 0.022122439772480792\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.21604938271604937,\n \"acc_stderr\": 0.022899162918445806,\n\
\ \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.022899162918445806\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.23404255319148937,\n \"acc_stderr\": 0.025257861359432417,\n \
\ \"acc_norm\": 0.23404255319148937,\n \"acc_norm_stderr\": 0.025257861359432417\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2457627118644068,\n\
\ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\
\ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\
\ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.2173202614379085,\n \"acc_stderr\": 0.01668482092914861,\n \
\ \"acc_norm\": 0.2173202614379085,\n \"acc_norm_stderr\": 0.01668482092914861\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.21818181818181817,\n\
\ \"acc_stderr\": 0.03955932861795833,\n \"acc_norm\": 0.21818181818181817,\n\
\ \"acc_norm_stderr\": 0.03955932861795833\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.18775510204081633,\n \"acc_stderr\": 0.02500025603954621,\n\
\ \"acc_norm\": 0.18775510204081633,\n \"acc_norm_stderr\": 0.02500025603954621\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.24378109452736318,\n\
\ \"acc_stderr\": 0.03036049015401465,\n \"acc_norm\": 0.24378109452736318,\n\
\ \"acc_norm_stderr\": 0.03036049015401465\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \
\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.28313253012048195,\n\
\ \"acc_stderr\": 0.03507295431370518,\n \"acc_norm\": 0.28313253012048195,\n\
\ \"acc_norm_stderr\": 0.03507295431370518\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.3216374269005848,\n \"acc_stderr\": 0.03582529442573122,\n\
\ \"acc_norm\": 0.3216374269005848,\n \"acc_norm_stderr\": 0.03582529442573122\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.23011015911872704,\n\
\ \"mc1_stderr\": 0.014734557959807756,\n \"mc2\": 0.49059783076199204,\n\
\ \"mc2_stderr\": 0.01679727487548572\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.48697711128650356,\n \"acc_stderr\": 0.014047718393997667\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\
: 0.0\n }\n}\n```"
repo_url: https://huggingface.co/Minami-su/Qwen1.5-0.5B-Chat_mistral
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_25T09_24_56.116599
path:
- '**/details_harness|arc:challenge|25_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|gsm8k|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hellaswag|10_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-25T09-24-56.116599.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-25T09-24-56.116599.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- '**/details_harness|winogrande|5_2024-03-25T09-24-56.116599.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-25T09-24-56.116599.parquet'
- config_name: results
data_files:
- split: 2024_03_25T09_24_56.116599
path:
- results_2024-03-25T09-24-56.116599.parquet
- split: latest
path:
- results_2024-03-25T09-24-56.116599.parquet
---
# Dataset Card for Evaluation run of Minami-su/Qwen1.5-0.5B-Chat_mistral
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Minami-su/Qwen1.5-0.5B-Chat_mistral](https://huggingface.co/Minami-su/Qwen1.5-0.5B-Chat_mistral) 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_Minami-su__Qwen1.5-0.5B-Chat_mistral",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-25T09:24:56.116599](https://huggingface.co/datasets/open-llm-leaderboard/details_Minami-su__Qwen1.5-0.5B-Chat_mistral/blob/main/results_2024-03-25T09-24-56.116599.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": 0.23146707204075107,
"acc_stderr": 0.029930144939974264,
"acc_norm": 0.23180919521674745,
"acc_norm_stderr": 0.03071922270148664,
"mc1": 0.23011015911872704,
"mc1_stderr": 0.014734557959807756,
"mc2": 0.49059783076199204,
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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:**
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## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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## Dataset Card Contact
[More Information Needed] |
distilled-one-sec-cv12-each-chunk-uniq/chunk_234 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1145344364.0
num_examples: 223177
download_size: 1174640337
dataset_size: 1145344364.0
---
# Dataset Card for "chunk_234"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-markdown-61000 | ---
dataset_info:
features:
- name: input_ids
sequence:
sequence: int32
- name: attention_mask
sequence:
sequence: int8
- name: labels
sequence:
sequence: int64
splits:
- name: train
num_bytes: 13336000
num_examples: 1000
download_size: 1095907
dataset_size: 13336000
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
iamnguyen/cdnc_law | ---
dataset_info:
features:
- name: content
dtype: string
- name: citation
dtype: string
- name: meta
struct:
- name: effective_date
dtype: string
- name: issuing_agency
dtype: string
- name: promulgation_date
dtype: string
- name: sign_number
dtype: string
- name: signer
dtype: string
- name: type
dtype: string
- name: url
dtype: string
- name: text
dtype: string
- name: law
sequence: string
splits:
- name: luat
num_bytes: 12032705.477916697
num_examples: 4310
download_size: 3185785
dataset_size: 12032705.477916697
configs:
- config_name: default
data_files:
- split: luat
path: data/luat-*
---
|
open-llm-leaderboard/details_RatanRohith__NeuralPizza-7B-V0.2 | ---
pretty_name: Evaluation run of RatanRohith/NeuralPizza-7B-V0.2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [RatanRohith/NeuralPizza-7B-V0.2](https://huggingface.co/RatanRohith/NeuralPizza-7B-V0.2)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_RatanRohith__NeuralPizza-7B-V0.2\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-21T21:04:32.551333](https://huggingface.co/datasets/open-llm-leaderboard/details_RatanRohith__NeuralPizza-7B-V0.2/blob/main/results_2024-01-21T21-04-32.551333.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\": 0.6473430412019332,\n\
\ \"acc_stderr\": 0.03217057797429981,\n \"acc_norm\": 0.64765430784867,\n\
\ \"acc_norm_stderr\": 0.032828743060941856,\n \"mc1\": 0.4565483476132191,\n\
\ \"mc1_stderr\": 0.017437280953183695,\n \"mc2\": 0.6137860051903924,\n\
\ \"mc2_stderr\": 0.015431238638634374\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6535836177474402,\n \"acc_stderr\": 0.013905011180063239,\n\
\ \"acc_norm\": 0.6877133105802048,\n \"acc_norm_stderr\": 0.013542598541688065\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6819358693487353,\n\
\ \"acc_stderr\": 0.004647727222445386,\n \"acc_norm\": 0.8610834495120494,\n\
\ \"acc_norm_stderr\": 0.003451525868724678\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\": 0.6370370370370371,\n\
\ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\
\ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6842105263157895,\n \"acc_stderr\": 0.0378272898086547,\n\
\ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.0378272898086547\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\
\ \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.63,\n \
\ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7056603773584905,\n \"acc_stderr\": 0.02804918631569525,\n\
\ \"acc_norm\": 0.7056603773584905,\n \"acc_norm_stderr\": 0.02804918631569525\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\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \
\ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n\
\ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6878612716763006,\n\
\ \"acc_stderr\": 0.035331333893236574,\n \"acc_norm\": 0.6878612716763006,\n\
\ \"acc_norm_stderr\": 0.035331333893236574\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.45098039215686275,\n \"acc_stderr\": 0.049512182523962625,\n\
\ \"acc_norm\": 0.45098039215686275,\n \"acc_norm_stderr\": 0.049512182523962625\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.76,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.76,\n\
\ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5914893617021276,\n \"acc_stderr\": 0.032134180267015755,\n\
\ \"acc_norm\": 0.5914893617021276,\n \"acc_norm_stderr\": 0.032134180267015755\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4824561403508772,\n\
\ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\
\ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\
\ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.4126984126984127,\n \"acc_stderr\": 0.025355741263055256,\n \"\
acc_norm\": 0.4126984126984127,\n \"acc_norm_stderr\": 0.025355741263055256\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4523809523809524,\n\
\ \"acc_stderr\": 0.044518079590553275,\n \"acc_norm\": 0.4523809523809524,\n\
\ \"acc_norm_stderr\": 0.044518079590553275\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \
\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.7548387096774194,\n \"acc_stderr\": 0.024472243840895518,\n \"\
acc_norm\": 0.7548387096774194,\n \"acc_norm_stderr\": 0.024472243840895518\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.4827586206896552,\n \"acc_stderr\": 0.035158955511656986,\n \"\
acc_norm\": 0.4827586206896552,\n \"acc_norm_stderr\": 0.035158955511656986\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\"\
: 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.032568666616811015,\n\
\ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.032568666616811015\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7929292929292929,\n \"acc_stderr\": 0.02886977846026705,\n \"\
acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.02886977846026705\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8808290155440415,\n \"acc_stderr\": 0.02338193534812143,\n\
\ \"acc_norm\": 0.8808290155440415,\n \"acc_norm_stderr\": 0.02338193534812143\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.023901157979402534,\n\
\ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.023901157979402534\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.34074074074074073,\n \"acc_stderr\": 0.028897748741131143,\n \
\ \"acc_norm\": 0.34074074074074073,\n \"acc_norm_stderr\": 0.028897748741131143\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6890756302521008,\n \"acc_stderr\": 0.03006676158297793,\n \
\ \"acc_norm\": 0.6890756302521008,\n \"acc_norm_stderr\": 0.03006676158297793\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.31788079470198677,\n \"acc_stderr\": 0.038020397601079024,\n \"\
acc_norm\": 0.31788079470198677,\n \"acc_norm_stderr\": 0.038020397601079024\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8495412844036697,\n \"acc_stderr\": 0.015328563932669237,\n \"\
acc_norm\": 0.8495412844036697,\n \"acc_norm_stderr\": 0.015328563932669237\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\"\
: 0.8088235294117647,\n \"acc_stderr\": 0.027599174300640766,\n \"\
acc_norm\": 0.8088235294117647,\n \"acc_norm_stderr\": 0.027599174300640766\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7974683544303798,\n \"acc_stderr\": 0.026160568246601443,\n \
\ \"acc_norm\": 0.7974683544303798,\n \"acc_norm_stderr\": 0.026160568246601443\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6816143497757847,\n\
\ \"acc_stderr\": 0.03126580522513713,\n \"acc_norm\": 0.6816143497757847,\n\
\ \"acc_norm_stderr\": 0.03126580522513713\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.03641297081313729,\n\
\ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.03641297081313729\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228733,\n \"\
acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228733\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\": 0.7607361963190185,\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\": 0.4375,\n\
\ \"acc_stderr\": 0.04708567521880525,\n \"acc_norm\": 0.4375,\n \
\ \"acc_norm_stderr\": 0.04708567521880525\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8058252427184466,\n \"acc_stderr\": 0.039166677628225836,\n\
\ \"acc_norm\": 0.8058252427184466,\n \"acc_norm_stderr\": 0.039166677628225836\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8717948717948718,\n\
\ \"acc_stderr\": 0.02190190511507333,\n \"acc_norm\": 0.8717948717948718,\n\
\ \"acc_norm_stderr\": 0.02190190511507333\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \
\ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.045126085985421276\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8263090676883781,\n\
\ \"acc_stderr\": 0.01354741565866226,\n \"acc_norm\": 0.8263090676883781,\n\
\ \"acc_norm_stderr\": 0.01354741565866226\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7427745664739884,\n \"acc_stderr\": 0.023532925431044287,\n\
\ \"acc_norm\": 0.7427745664739884,\n \"acc_norm_stderr\": 0.023532925431044287\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3877094972067039,\n\
\ \"acc_stderr\": 0.01629533232815581,\n \"acc_norm\": 0.3877094972067039,\n\
\ \"acc_norm_stderr\": 0.01629533232815581\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7222222222222222,\n \"acc_stderr\": 0.025646863097137897,\n\
\ \"acc_norm\": 0.7222222222222222,\n \"acc_norm_stderr\": 0.025646863097137897\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7170418006430869,\n\
\ \"acc_stderr\": 0.02558306248998481,\n \"acc_norm\": 0.7170418006430869,\n\
\ \"acc_norm_stderr\": 0.02558306248998481\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7469135802469136,\n \"acc_stderr\": 0.024191808600712992,\n\
\ \"acc_norm\": 0.7469135802469136,\n \"acc_norm_stderr\": 0.024191808600712992\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.4397163120567376,\n \"acc_stderr\": 0.029609912075594106,\n \
\ \"acc_norm\": 0.4397163120567376,\n \"acc_norm_stderr\": 0.029609912075594106\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.455019556714472,\n\
\ \"acc_stderr\": 0.012718456618701766,\n \"acc_norm\": 0.455019556714472,\n\
\ \"acc_norm_stderr\": 0.012718456618701766\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6654411764705882,\n \"acc_stderr\": 0.028661996202335307,\n\
\ \"acc_norm\": 0.6654411764705882,\n \"acc_norm_stderr\": 0.028661996202335307\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6699346405228758,\n \"acc_stderr\": 0.019023726160724556,\n \
\ \"acc_norm\": 0.6699346405228758,\n \"acc_norm_stderr\": 0.019023726160724556\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6636363636363637,\n\
\ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\
\ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7183673469387755,\n \"acc_stderr\": 0.028795185574291296,\n\
\ \"acc_norm\": 0.7183673469387755,\n \"acc_norm_stderr\": 0.028795185574291296\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\
\ \"acc_stderr\": 0.025870646766169143,\n \"acc_norm\": 0.8407960199004975,\n\
\ \"acc_norm_stderr\": 0.025870646766169143\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.85,\n \"acc_stderr\": 0.03588702812826371,\n \
\ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.03588702812826371\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\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\
\ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4565483476132191,\n\
\ \"mc1_stderr\": 0.017437280953183695,\n \"mc2\": 0.6137860051903924,\n\
\ \"mc2_stderr\": 0.015431238638634374\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8034727703235991,\n \"acc_stderr\": 0.011168120593569563\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.686125852918878,\n \
\ \"acc_stderr\": 0.012782681251053201\n }\n}\n```"
repo_url: https://huggingface.co/RatanRohith/NeuralPizza-7B-V0.2
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|arc:challenge|25_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|gsm8k|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hellaswag|10_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-21T21-04-32.551333.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-21T21-04-32.551333.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- '**/details_harness|winogrande|5_2024-01-21T21-04-32.551333.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-21T21-04-32.551333.parquet'
- config_name: results
data_files:
- split: 2024_01_21T21_04_32.551333
path:
- results_2024-01-21T21-04-32.551333.parquet
- split: latest
path:
- results_2024-01-21T21-04-32.551333.parquet
---
# Dataset Card for Evaluation run of RatanRohith/NeuralPizza-7B-V0.2
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [RatanRohith/NeuralPizza-7B-V0.2](https://huggingface.co/RatanRohith/NeuralPizza-7B-V0.2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_RatanRohith__NeuralPizza-7B-V0.2",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-21T21:04:32.551333](https://huggingface.co/datasets/open-llm-leaderboard/details_RatanRohith__NeuralPizza-7B-V0.2/blob/main/results_2024-01-21T21-04-32.551333.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": 0.6473430412019332,
"acc_stderr": 0.03217057797429981,
"acc_norm": 0.64765430784867,
"acc_norm_stderr": 0.032828743060941856,
"mc1": 0.4565483476132191,
"mc1_stderr": 0.017437280953183695,
"mc2": 0.6137860051903924,
"mc2_stderr": 0.015431238638634374
},
"harness|arc:challenge|25": {
"acc": 0.6535836177474402,
"acc_stderr": 0.013905011180063239,
"acc_norm": 0.6877133105802048,
"acc_norm_stderr": 0.013542598541688065
},
"harness|hellaswag|10": {
"acc": 0.6819358693487353,
"acc_stderr": 0.004647727222445386,
"acc_norm": 0.8610834495120494,
"acc_norm_stderr": 0.003451525868724678
},
"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": 0.6370370370370371,
"acc_stderr": 0.04153948404742398,
"acc_norm": 0.6370370370370371,
"acc_norm_stderr": 0.04153948404742398
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6842105263157895,
"acc_stderr": 0.0378272898086547,
"acc_norm": 0.6842105263157895,
"acc_norm_stderr": 0.0378272898086547
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.63,
"acc_stderr": 0.04852365870939099,
"acc_norm": 0.63,
"acc_norm_stderr": 0.04852365870939099
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7056603773584905,
"acc_stderr": 0.02804918631569525,
"acc_norm": 0.7056603773584905,
"acc_norm_stderr": 0.02804918631569525
},
"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": 0.5,
"acc_stderr": 0.050251890762960605,
"acc_norm": 0.5,
"acc_norm_stderr": 0.050251890762960605
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.58,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.58,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.32,
"acc_stderr": 0.046882617226215034,
"acc_norm": 0.32,
"acc_norm_stderr": 0.046882617226215034
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6878612716763006,
"acc_stderr": 0.035331333893236574,
"acc_norm": 0.6878612716763006,
"acc_norm_stderr": 0.035331333893236574
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.45098039215686275,
"acc_stderr": 0.049512182523962625,
"acc_norm": 0.45098039215686275,
"acc_norm_stderr": 0.049512182523962625
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.76,
"acc_stderr": 0.04292346959909283,
"acc_norm": 0.76,
"acc_norm_stderr": 0.04292346959909283
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5914893617021276,
"acc_stderr": 0.032134180267015755,
"acc_norm": 0.5914893617021276,
"acc_norm_stderr": 0.032134180267015755
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.4824561403508772,
"acc_stderr": 0.04700708033551038,
"acc_norm": 0.4824561403508772,
"acc_norm_stderr": 0.04700708033551038
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5586206896551724,
"acc_stderr": 0.04137931034482757,
"acc_norm": 0.5586206896551724,
"acc_norm_stderr": 0.04137931034482757
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.4126984126984127,
"acc_stderr": 0.025355741263055256,
"acc_norm": 0.4126984126984127,
"acc_norm_stderr": 0.025355741263055256
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.4523809523809524,
"acc_stderr": 0.044518079590553275,
"acc_norm": 0.4523809523809524,
"acc_norm_stderr": 0.044518079590553275
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.33,
"acc_stderr": 0.047258156262526045,
"acc_norm": 0.33,
"acc_norm_stderr": 0.047258156262526045
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7548387096774194,
"acc_stderr": 0.024472243840895518,
"acc_norm": 0.7548387096774194,
"acc_norm_stderr": 0.024472243840895518
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.4827586206896552,
"acc_stderr": 0.035158955511656986,
"acc_norm": 0.4827586206896552,
"acc_norm_stderr": 0.035158955511656986
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.71,
"acc_stderr": 0.045604802157206845,
"acc_norm": 0.71,
"acc_norm_stderr": 0.045604802157206845
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7757575757575758,
"acc_stderr": 0.032568666616811015,
"acc_norm": 0.7757575757575758,
"acc_norm_stderr": 0.032568666616811015
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7929292929292929,
"acc_stderr": 0.02886977846026705,
"acc_norm": 0.7929292929292929,
"acc_norm_stderr": 0.02886977846026705
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.8808290155440415,
"acc_stderr": 0.02338193534812143,
"acc_norm": 0.8808290155440415,
"acc_norm_stderr": 0.02338193534812143
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.6666666666666666,
"acc_stderr": 0.023901157979402534,
"acc_norm": 0.6666666666666666,
"acc_norm_stderr": 0.023901157979402534
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.34074074074074073,
"acc_stderr": 0.028897748741131143,
"acc_norm": 0.34074074074074073,
"acc_norm_stderr": 0.028897748741131143
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6890756302521008,
"acc_stderr": 0.03006676158297793,
"acc_norm": 0.6890756302521008,
"acc_norm_stderr": 0.03006676158297793
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.31788079470198677,
"acc_stderr": 0.038020397601079024,
"acc_norm": 0.31788079470198677,
"acc_norm_stderr": 0.038020397601079024
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8495412844036697,
"acc_stderr": 0.015328563932669237,
"acc_norm": 0.8495412844036697,
"acc_norm_stderr": 0.015328563932669237
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.5509259259259259,
"acc_stderr": 0.03392238405321617,
"acc_norm": 0.5509259259259259,
"acc_norm_stderr": 0.03392238405321617
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8088235294117647,
"acc_stderr": 0.027599174300640766,
"acc_norm": 0.8088235294117647,
"acc_norm_stderr": 0.027599174300640766
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.7974683544303798,
"acc_stderr": 0.026160568246601443,
"acc_norm": 0.7974683544303798,
"acc_norm_stderr": 0.026160568246601443
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.6816143497757847,
"acc_stderr": 0.03126580522513713,
"acc_norm": 0.6816143497757847,
"acc_norm_stderr": 0.03126580522513713
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.7786259541984732,
"acc_stderr": 0.03641297081313729,
"acc_norm": 0.7786259541984732,
"acc_norm_stderr": 0.03641297081313729
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.7768595041322314,
"acc_stderr": 0.03800754475228733,
"acc_norm": 0.7768595041322314,
"acc_norm_stderr": 0.03800754475228733
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.7685185185185185,
"acc_stderr": 0.04077494709252626,
"acc_norm": 0.7685185185185185,
"acc_norm_stderr": 0.04077494709252626
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.7607361963190185,
"acc_stderr": 0.033519538795212696,
"acc_norm": 0.7607361963190185,
"acc_norm_stderr": 0.033519538795212696
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.4375,
"acc_stderr": 0.04708567521880525,
"acc_norm": 0.4375,
"acc_norm_stderr": 0.04708567521880525
},
"harness|hendrycksTest-management|5": {
"acc": 0.8058252427184466,
"acc_stderr": 0.039166677628225836,
"acc_norm": 0.8058252427184466,
"acc_norm_stderr": 0.039166677628225836
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.8717948717948718,
"acc_stderr": 0.02190190511507333,
"acc_norm": 0.8717948717948718,
"acc_norm_stderr": 0.02190190511507333
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.72,
"acc_stderr": 0.045126085985421276,
"acc_norm": 0.72,
"acc_norm_stderr": 0.045126085985421276
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.8263090676883781,
"acc_stderr": 0.01354741565866226,
"acc_norm": 0.8263090676883781,
"acc_norm_stderr": 0.01354741565866226
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.7427745664739884,
"acc_stderr": 0.023532925431044287,
"acc_norm": 0.7427745664739884,
"acc_norm_stderr": 0.023532925431044287
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.3877094972067039,
"acc_stderr": 0.01629533232815581,
"acc_norm": 0.3877094972067039,
"acc_norm_stderr": 0.01629533232815581
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.7222222222222222,
"acc_stderr": 0.025646863097137897,
"acc_norm": 0.7222222222222222,
"acc_norm_stderr": 0.025646863097137897
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.7170418006430869,
"acc_stderr": 0.02558306248998481,
"acc_norm": 0.7170418006430869,
"acc_norm_stderr": 0.02558306248998481
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.7469135802469136,
"acc_stderr": 0.024191808600712992,
"acc_norm": 0.7469135802469136,
"acc_norm_stderr": 0.024191808600712992
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.4397163120567376,
"acc_stderr": 0.029609912075594106,
"acc_norm": 0.4397163120567376,
"acc_norm_stderr": 0.029609912075594106
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.455019556714472,
"acc_stderr": 0.012718456618701766,
"acc_norm": 0.455019556714472,
"acc_norm_stderr": 0.012718456618701766
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.6654411764705882,
"acc_stderr": 0.028661996202335307,
"acc_norm": 0.6654411764705882,
"acc_norm_stderr": 0.028661996202335307
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.6699346405228758,
"acc_stderr": 0.019023726160724556,
"acc_norm": 0.6699346405228758,
"acc_norm_stderr": 0.019023726160724556
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.6636363636363637,
"acc_stderr": 0.04525393596302506,
"acc_norm": 0.6636363636363637,
"acc_norm_stderr": 0.04525393596302506
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.7183673469387755,
"acc_stderr": 0.028795185574291296,
"acc_norm": 0.7183673469387755,
"acc_norm_stderr": 0.028795185574291296
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.8407960199004975,
"acc_stderr": 0.025870646766169143,
"acc_norm": 0.8407960199004975,
"acc_norm_stderr": 0.025870646766169143
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.85,
"acc_stderr": 0.03588702812826371,
"acc_norm": 0.85,
"acc_norm_stderr": 0.03588702812826371
},
"harness|hendrycksTest-virology|5": {
"acc": 0.5301204819277109,
"acc_stderr": 0.03885425420866767,
"acc_norm": 0.5301204819277109,
"acc_norm_stderr": 0.03885425420866767
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.8128654970760234,
"acc_stderr": 0.029913127232368036,
"acc_norm": 0.8128654970760234,
"acc_norm_stderr": 0.029913127232368036
},
"harness|truthfulqa:mc|0": {
"mc1": 0.4565483476132191,
"mc1_stderr": 0.017437280953183695,
"mc2": 0.6137860051903924,
"mc2_stderr": 0.015431238638634374
},
"harness|winogrande|5": {
"acc": 0.8034727703235991,
"acc_stderr": 0.011168120593569563
},
"harness|gsm8k|5": {
"acc": 0.686125852918878,
"acc_stderr": 0.012782681251053201
}
}
```
## 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] |
juraj-juraj/doc_gen | ---
language:
- en
license: mit
task_categories:
- text-generation
pretty_name: py_code_doc
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: docstring
dtype: string
- name: function
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 270465917
num_examples: 313366
- name: validation
num_bytes: 763140
num_examples: 1000
- name: test
num_bytes: 878385
num_examples: 1000
download_size: 107450380
dataset_size: 272107442
---
# Code documentation dataset
This dataset aims leverage usage of lm to automatically generate documenation to undocumented python code. Dataset consists of pairs code and its documenation
Content of dataset is created from CodeSearchNet dataset. |
Taegyuu/KoAlpaca-v1.1a | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
- name: url
dtype: string
splits:
- name: train
num_bytes: 23371027
num_examples: 21155
download_size: 12856014
dataset_size: 23371027
task_categories:
- text-generation
language:
- ko
tags:
- KoAlpaca
pretty_name: KoAlpaca-v1.1a
---
# Dataset Card for "KoAlpaca-v1.1a"
## Project Repo
- Github Repo: [Beomi/KoAlpaca](https://github.com/Beomi/KoAlpaca)
## How to use
```python
>>> from datasets import load_dataset
>>> ds = load_dataset("beomi/KoAlpaca-v1.1a", split="train")
>>> ds
Dataset({
features: ['instruction', 'input', 'output'],
num_rows: 21155
})
```
```python
>>> ds[0]
{'instruction': '양파는 어떤 식물 부위인가요? 그리고 고구마는 뿌리인가요?',
'output': '양파는 잎이 아닌 식물의 줄기 부분입니다. 고구마는 식물의 뿌리 부분입니다. \n\n식물의 부위의 구분에 대해 궁금해하는 분이라면 분명 이 질문에 대한 답을 찾고 있을 것입니다. 양파는 잎이 아닌 줄기 부분입니다. 고구마는 다른 질문과 답변에서 언급된 것과 같이 뿌리 부분입니다. 따라서, 양파는 식물의 줄기 부분이 되고, 고구마는 식물의 뿌리 부분입니다.\n\n 덧붙이는 답변: 고구마 줄기도 볶아먹을 수 있나요? \n\n고구마 줄기도 식용으로 볶아먹을 수 있습니다. 하지만 줄기 뿐만 아니라, 잎, 씨, 뿌리까지 모든 부위가 식용으로 활용되기도 합니다. 다만, 한국에서는 일반적으로 뿌리 부분인 고구마를 주로 먹습니다.',
'url': 'https://kin.naver.com/qna/detail.naver?d1id=11&dirId=1116&docId=55320268'} |
clips/20Q | ---
annotations_creators: []
language:
- en
language_creators: []
license: []
multilinguality:
- monolingual
pretty_name: 20Q - World Knowledge Benchmark
size_categories:
- 1K<n<10K
source_datasets: []
tags:
- 20Q
- Twenty Questions
- 20 Questions
task_categories:
- question-answering
task_ids: []
---
# Dataset Card for 20Q
|
ntkctksnb1/mini_platypus | ---
dataset_info:
config_name: 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
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 4201526
num_examples: 1000
download_size: 2247084
dataset_size: 4201526
configs:
- config_name: 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
data_files:
- split: train
path: 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/train-*
---
|
pawkanarek/spraix_1024_9frames | ---
license: gpl-3.0
tags:
- art
pretty_name: 96 images to train sprite animations
size_categories:
- n<1K
---
This dataset inclueds labeled sprite animations with 9 frames. More info https://github.com/PawKanarek/spraix |
Aashi/All_About_Apple_Devices | ---
license: mit
task_categories:
- question-answering
- conversational
language:
- en
tags:
- tech
pretty_name: A3D 🚀
size_categories:
- n<1K
---
This dataset contains Q&A based on what kind of questions do people ask online with their respective answers. This can be used as an LLM project where we finetune an LLM and create a chatbot where one can ask the chatbot any question related to Apple products and get respective answers.
## To use this dataset try running the following code:
- dataset = load_dataset("Aashi/All_About_Apple_Devices", data_files={"train": "QandA.csv"})
- df_train = dataset['train'].to_pandas() |
Lienid/chat_perplexity_scored | ---
dataset_info:
features:
- name: question
dtype: string
- name: response
dtype: string
- name: perplexity
dtype: float32
splits:
- name: train
num_bytes: 370318195.41288
num_examples: 173496
download_size: 185184757
dataset_size: 370318195.41288
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
ArmelRandy/most_precious_4 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 8031615.129808251
num_examples: 7744
- name: test
num_bytes: 892977.870191749
num_examples: 861
download_size: 5178596
dataset_size: 8924593.0
---
# Dataset Card for "most_precious_4"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
autoevaluate/autoeval-eval-lener_br-lener_br-b36dee-1776161642 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- lener_br
eval_info:
task: entity_extraction
model: Luciano/xlm-roberta-base-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: validation
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/xlm-roberta-base-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. |
autoevaluate/autoeval-staging-eval-project-squad-ef91144d-11985603 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- squad
eval_info:
task: extractive_question_answering
model: nlpconnect/roberta-base-squad2-nq
metrics: []
dataset_name: squad
dataset_config: plain_text
dataset_split: validation
col_mapping:
context: context
question: question
answers-text: answers.text
answers-answer_start: answers.answer_start
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: nlpconnect/roberta-base-squad2-nq
* Dataset: squad
* Config: plain_text
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@ankur310794](https://huggingface.co/ankur310794) for evaluating this model. |
idning/ffhq64-caption | ---
license: mit
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 586217154.0
num_examples: 70000
download_size: 584117488
dataset_size: 586217154.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
autoevaluate/autoeval-staging-eval-project-bc0462a6-7584895 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- xtreme
eval_info:
task: entity_extraction
model: moghis/xlm-roberta-base-finetuned-panx-fr
metrics: []
dataset_name: xtreme
dataset_config: PAN-X.fr
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: moghis/xlm-roberta-base-finetuned-panx-fr
* Dataset: xtreme
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. |
BerMaker/beans | ---
license: apache-2.0
---
|
euclaise/mathqa_programs | ---
dataset_info:
features:
- name: options
dtype: string
- name: correct
dtype: string
- name: annotated_formula
dtype: string
- name: problem
dtype: string
- name: rationale
dtype: string
- name: program
dtype: string
splits:
- name: train
num_bytes: 17017833
num_examples: 28851
download_size: 8877888
dataset_size: 17017833
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: apache-2.0
---
math_qa converted to Python snippets |
liuyanchen1015/MULTI_VALUE_mnli_flat_adj_for_adv | ---
dataset_info:
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
dtype: int64
- name: idx
dtype: int64
- name: score
dtype: int64
splits:
- name: dev_matched
num_bytes: 52060
num_examples: 221
- name: dev_mismatched
num_bytes: 51025
num_examples: 207
- name: test_matched
num_bytes: 45543
num_examples: 194
- name: test_mismatched
num_bytes: 63860
num_examples: 243
- name: train
num_bytes: 1870439
num_examples: 8415
download_size: 1258577
dataset_size: 2082927
---
# Dataset Card for "MULTI_VALUE_mnli_flat_adj_for_adv"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
juliaturc/captioned-cartoons | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 22981331.0
num_examples: 100
download_size: 22873699
dataset_size: 22981331.0
---
# Dataset Card for "captioned-cartoons"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Linear | ---
pretty_name: Evaluation run of Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear](https://huggingface.co/Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear)\
\ 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_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Linear\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-29T12:58:30.448615](https://huggingface.co/datasets/open-llm-leaderboard/details_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Linear/blob/main/results_2023-12-29T12-58-30.448615.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\": 0.6372944871407636,\n\
\ \"acc_stderr\": 0.0321517342901721,\n \"acc_norm\": 0.6376839473607636,\n\
\ \"acc_norm_stderr\": 0.03280413968071383,\n \"mc1\": 0.3329253365973072,\n\
\ \"mc1_stderr\": 0.016497402382012052,\n \"mc2\": 0.48572469546439073,\n\
\ \"mc2_stderr\": 0.01547664094918918\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5964163822525598,\n \"acc_stderr\": 0.014337158914268438,\n\
\ \"acc_norm\": 0.6279863481228669,\n \"acc_norm_stderr\": 0.014124597881844461\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6590320653256323,\n\
\ \"acc_stderr\": 0.004730658073041556,\n \"acc_norm\": 0.8420633339972117,\n\
\ \"acc_norm_stderr\": 0.003639363021784421\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \
\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5925925925925926,\n\
\ \"acc_stderr\": 0.04244633238353227,\n \"acc_norm\": 0.5925925925925926,\n\
\ \"acc_norm_stderr\": 0.04244633238353227\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.03738520676119667,\n\
\ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.03738520676119667\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.58,\n\
\ \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n \
\ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6792452830188679,\n \"acc_stderr\": 0.028727502957880267,\n\
\ \"acc_norm\": 0.6792452830188679,\n \"acc_norm_stderr\": 0.028727502957880267\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7430555555555556,\n\
\ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.7430555555555556,\n\
\ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \
\ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \
\ },\n \"harness|hendrycksTest-college_computer_science|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_mathematics|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-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\":\
\ 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.79,\n\
\ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5702127659574469,\n \"acc_stderr\": 0.03236214467715564,\n\
\ \"acc_norm\": 0.5702127659574469,\n \"acc_norm_stderr\": 0.03236214467715564\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5,\n\
\ \"acc_stderr\": 0.047036043419179864,\n \"acc_norm\": 0.5,\n \
\ \"acc_norm_stderr\": 0.047036043419179864\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\
\ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.41798941798941797,\n \"acc_stderr\": 0.02540255550326091,\n \"\
acc_norm\": 0.41798941798941797,\n \"acc_norm_stderr\": 0.02540255550326091\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3968253968253968,\n\
\ \"acc_stderr\": 0.043758884927270605,\n \"acc_norm\": 0.3968253968253968,\n\
\ \"acc_norm_stderr\": 0.043758884927270605\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \
\ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.7677419354838709,\n \"acc_stderr\": 0.024022256130308235,\n \"\
acc_norm\": 0.7677419354838709,\n \"acc_norm_stderr\": 0.024022256130308235\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876106,\n \"\
acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876106\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \"acc_norm\"\
: 0.68,\n \"acc_norm_stderr\": 0.04688261722621505\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\"\
: 0.7727272727272727,\n \"acc_stderr\": 0.029857515673386414,\n \"\
acc_norm\": 0.7727272727272727,\n \"acc_norm_stderr\": 0.029857515673386414\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8911917098445595,\n \"acc_stderr\": 0.022473253332768776,\n\
\ \"acc_norm\": 0.8911917098445595,\n \"acc_norm_stderr\": 0.022473253332768776\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6282051282051282,\n \"acc_stderr\": 0.024503472557110936,\n\
\ \"acc_norm\": 0.6282051282051282,\n \"acc_norm_stderr\": 0.024503472557110936\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\": 0.6512605042016807,\n \"acc_stderr\": 0.030956636328566545,\n\
\ \"acc_norm\": 0.6512605042016807,\n \"acc_norm_stderr\": 0.030956636328566545\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.304635761589404,\n \"acc_stderr\": 0.03757949922943343,\n \"acc_norm\"\
: 0.304635761589404,\n \"acc_norm_stderr\": 0.03757949922943343\n },\n\
\ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.8330275229357799,\n\
\ \"acc_stderr\": 0.015990154885073393,\n \"acc_norm\": 0.8330275229357799,\n\
\ \"acc_norm_stderr\": 0.015990154885073393\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\
: {\n \"acc\": 0.49074074074074076,\n \"acc_stderr\": 0.034093869469927006,\n\
\ \"acc_norm\": 0.49074074074074076,\n \"acc_norm_stderr\": 0.034093869469927006\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.803921568627451,\n \"acc_stderr\": 0.027865942286639318,\n \"\
acc_norm\": 0.803921568627451,\n \"acc_norm_stderr\": 0.027865942286639318\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7805907172995781,\n \"acc_stderr\": 0.026939106581553945,\n \
\ \"acc_norm\": 0.7805907172995781,\n \"acc_norm_stderr\": 0.026939106581553945\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7085201793721974,\n\
\ \"acc_stderr\": 0.03050028317654585,\n \"acc_norm\": 0.7085201793721974,\n\
\ \"acc_norm_stderr\": 0.03050028317654585\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\
\ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.768595041322314,\n \"acc_stderr\": 0.03849856098794088,\n \"acc_norm\"\
: 0.768595041322314,\n \"acc_norm_stderr\": 0.03849856098794088\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\
\ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\
\ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7914110429447853,\n \"acc_stderr\": 0.031921934489347235,\n\
\ \"acc_norm\": 0.7914110429447853,\n \"acc_norm_stderr\": 0.031921934489347235\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5089285714285714,\n\
\ \"acc_stderr\": 0.04745033255489123,\n \"acc_norm\": 0.5089285714285714,\n\
\ \"acc_norm_stderr\": 0.04745033255489123\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8155339805825242,\n \"acc_stderr\": 0.03840423627288276,\n\
\ \"acc_norm\": 0.8155339805825242,\n \"acc_norm_stderr\": 0.03840423627288276\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8760683760683761,\n\
\ \"acc_stderr\": 0.021586494001281382,\n \"acc_norm\": 0.8760683760683761,\n\
\ \"acc_norm_stderr\": 0.021586494001281382\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \
\ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8160919540229885,\n\
\ \"acc_stderr\": 0.013853724170922526,\n \"acc_norm\": 0.8160919540229885,\n\
\ \"acc_norm_stderr\": 0.013853724170922526\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7398843930635838,\n \"acc_stderr\": 0.023618678310069363,\n\
\ \"acc_norm\": 0.7398843930635838,\n \"acc_norm_stderr\": 0.023618678310069363\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.35307262569832404,\n\
\ \"acc_stderr\": 0.015984204545268565,\n \"acc_norm\": 0.35307262569832404,\n\
\ \"acc_norm_stderr\": 0.015984204545268565\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.023805186524888135,\n\
\ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.023805186524888135\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6945337620578779,\n\
\ \"acc_stderr\": 0.02616058445014045,\n \"acc_norm\": 0.6945337620578779,\n\
\ \"acc_norm_stderr\": 0.02616058445014045\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \
\ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\"\
: 0.4929078014184397,\n \"acc_stderr\": 0.02982449855912901,\n \"\
acc_norm\": 0.4929078014184397,\n \"acc_norm_stderr\": 0.02982449855912901\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4602346805736636,\n\
\ \"acc_stderr\": 0.012729785386598564,\n \"acc_norm\": 0.4602346805736636,\n\
\ \"acc_norm_stderr\": 0.012729785386598564\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6470588235294118,\n \"acc_stderr\": 0.029029422815681393,\n\
\ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.029029422815681393\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6584967320261438,\n \"acc_stderr\": 0.019184639328092487,\n \
\ \"acc_norm\": 0.6584967320261438,\n \"acc_norm_stderr\": 0.019184639328092487\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6636363636363637,\n\
\ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\
\ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7387755102040816,\n \"acc_stderr\": 0.028123429335142783,\n\
\ \"acc_norm\": 0.7387755102040816,\n \"acc_norm_stderr\": 0.028123429335142783\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\": 0.88,\n \"acc_stderr\": 0.032659863237109066,\n \
\ \"acc_norm\": 0.88,\n \"acc_norm_stderr\": 0.032659863237109066\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5542168674698795,\n\
\ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\
\ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8245614035087719,\n \"acc_stderr\": 0.02917088550072767,\n\
\ \"acc_norm\": 0.8245614035087719,\n \"acc_norm_stderr\": 0.02917088550072767\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3329253365973072,\n\
\ \"mc1_stderr\": 0.016497402382012052,\n \"mc2\": 0.48572469546439073,\n\
\ \"mc2_stderr\": 0.01547664094918918\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7679558011049724,\n \"acc_stderr\": 0.011864149691827936\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6982562547384382,\n \
\ \"acc_stderr\": 0.012643544762873358\n }\n}\n```"
repo_url: https://huggingface.co/Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|arc:challenge|25_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|gsm8k|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hellaswag|10_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-29T12-58-30.448615.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-29T12-58-30.448615.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- '**/details_harness|winogrande|5_2023-12-29T12-58-30.448615.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-29T12-58-30.448615.parquet'
- config_name: results
data_files:
- split: 2023_12_29T12_58_30.448615
path:
- results_2023-12-29T12-58-30.448615.parquet
- split: latest
path:
- results_2023-12-29T12-58-30.448615.parquet
---
# Dataset Card for Evaluation run of Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear](https://huggingface.co/Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear) 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_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Linear",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-29T12:58:30.448615](https://huggingface.co/datasets/open-llm-leaderboard/details_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Linear/blob/main/results_2023-12-29T12-58-30.448615.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": 0.6372944871407636,
"acc_stderr": 0.0321517342901721,
"acc_norm": 0.6376839473607636,
"acc_norm_stderr": 0.03280413968071383,
"mc1": 0.3329253365973072,
"mc1_stderr": 0.016497402382012052,
"mc2": 0.48572469546439073,
"mc2_stderr": 0.01547664094918918
},
"harness|arc:challenge|25": {
"acc": 0.5964163822525598,
"acc_stderr": 0.014337158914268438,
"acc_norm": 0.6279863481228669,
"acc_norm_stderr": 0.014124597881844461
},
"harness|hellaswag|10": {
"acc": 0.6590320653256323,
"acc_stderr": 0.004730658073041556,
"acc_norm": 0.8420633339972117,
"acc_norm_stderr": 0.003639363021784421
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.28,
"acc_stderr": 0.04512608598542128,
"acc_norm": 0.28,
"acc_norm_stderr": 0.04512608598542128
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.5925925925925926,
"acc_stderr": 0.04244633238353227,
"acc_norm": 0.5925925925925926,
"acc_norm_stderr": 0.04244633238353227
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6973684210526315,
"acc_stderr": 0.03738520676119667,
"acc_norm": 0.6973684210526315,
"acc_norm_stderr": 0.03738520676119667
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.58,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.58,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6792452830188679,
"acc_stderr": 0.028727502957880267,
"acc_norm": 0.6792452830188679,
"acc_norm_stderr": 0.028727502957880267
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7430555555555556,
"acc_stderr": 0.03653946969442099,
"acc_norm": 0.7430555555555556,
"acc_norm_stderr": 0.03653946969442099
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.44,
"acc_stderr": 0.04988876515698589,
"acc_norm": 0.44,
"acc_norm_stderr": 0.04988876515698589
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.45,
"acc_stderr": 0.05,
"acc_norm": 0.45,
"acc_norm_stderr": 0.05
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.3,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"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": 0.79,
"acc_stderr": 0.040936018074033256,
"acc_norm": 0.79,
"acc_norm_stderr": 0.040936018074033256
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5702127659574469,
"acc_stderr": 0.03236214467715564,
"acc_norm": 0.5702127659574469,
"acc_norm_stderr": 0.03236214467715564
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.5,
"acc_stderr": 0.047036043419179864,
"acc_norm": 0.5,
"acc_norm_stderr": 0.047036043419179864
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5448275862068965,
"acc_stderr": 0.04149886942192117,
"acc_norm": 0.5448275862068965,
"acc_norm_stderr": 0.04149886942192117
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.41798941798941797,
"acc_stderr": 0.02540255550326091,
"acc_norm": 0.41798941798941797,
"acc_norm_stderr": 0.02540255550326091
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.3968253968253968,
"acc_stderr": 0.043758884927270605,
"acc_norm": 0.3968253968253968,
"acc_norm_stderr": 0.043758884927270605
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.36,
"acc_stderr": 0.048241815132442176,
"acc_norm": 0.36,
"acc_norm_stderr": 0.048241815132442176
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7677419354838709,
"acc_stderr": 0.024022256130308235,
"acc_norm": 0.7677419354838709,
"acc_norm_stderr": 0.024022256130308235
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.5270935960591133,
"acc_stderr": 0.03512819077876106,
"acc_norm": 0.5270935960591133,
"acc_norm_stderr": 0.03512819077876106
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.68,
"acc_stderr": 0.04688261722621505,
"acc_norm": 0.68,
"acc_norm_stderr": 0.04688261722621505
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7575757575757576,
"acc_stderr": 0.03346409881055953,
"acc_norm": 0.7575757575757576,
"acc_norm_stderr": 0.03346409881055953
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7727272727272727,
"acc_stderr": 0.029857515673386414,
"acc_norm": 0.7727272727272727,
"acc_norm_stderr": 0.029857515673386414
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.8911917098445595,
"acc_stderr": 0.022473253332768776,
"acc_norm": 0.8911917098445595,
"acc_norm_stderr": 0.022473253332768776
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.6282051282051282,
"acc_stderr": 0.024503472557110936,
"acc_norm": 0.6282051282051282,
"acc_norm_stderr": 0.024503472557110936
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.34814814814814815,
"acc_stderr": 0.029045600290616258,
"acc_norm": 0.34814814814814815,
"acc_norm_stderr": 0.029045600290616258
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6512605042016807,
"acc_stderr": 0.030956636328566545,
"acc_norm": 0.6512605042016807,
"acc_norm_stderr": 0.030956636328566545
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.304635761589404,
"acc_stderr": 0.03757949922943343,
"acc_norm": 0.304635761589404,
"acc_norm_stderr": 0.03757949922943343
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8330275229357799,
"acc_stderr": 0.015990154885073393,
"acc_norm": 0.8330275229357799,
"acc_norm_stderr": 0.015990154885073393
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.49074074074074076,
"acc_stderr": 0.034093869469927006,
"acc_norm": 0.49074074074074076,
"acc_norm_stderr": 0.034093869469927006
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.803921568627451,
"acc_stderr": 0.027865942286639318,
"acc_norm": 0.803921568627451,
"acc_norm_stderr": 0.027865942286639318
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.7805907172995781,
"acc_stderr": 0.026939106581553945,
"acc_norm": 0.7805907172995781,
"acc_norm_stderr": 0.026939106581553945
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.7085201793721974,
"acc_stderr": 0.03050028317654585,
"acc_norm": 0.7085201793721974,
"acc_norm_stderr": 0.03050028317654585
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.7862595419847328,
"acc_stderr": 0.0359546161177469,
"acc_norm": 0.7862595419847328,
"acc_norm_stderr": 0.0359546161177469
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.768595041322314,
"acc_stderr": 0.03849856098794088,
"acc_norm": 0.768595041322314,
"acc_norm_stderr": 0.03849856098794088
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.7870370370370371,
"acc_stderr": 0.0395783547198098,
"acc_norm": 0.7870370370370371,
"acc_norm_stderr": 0.0395783547198098
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.7914110429447853,
"acc_stderr": 0.031921934489347235,
"acc_norm": 0.7914110429447853,
"acc_norm_stderr": 0.031921934489347235
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.5089285714285714,
"acc_stderr": 0.04745033255489123,
"acc_norm": 0.5089285714285714,
"acc_norm_stderr": 0.04745033255489123
},
"harness|hendrycksTest-management|5": {
"acc": 0.8155339805825242,
"acc_stderr": 0.03840423627288276,
"acc_norm": 0.8155339805825242,
"acc_norm_stderr": 0.03840423627288276
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.8760683760683761,
"acc_stderr": 0.021586494001281382,
"acc_norm": 0.8760683760683761,
"acc_norm_stderr": 0.021586494001281382
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.69,
"acc_stderr": 0.04648231987117316,
"acc_norm": 0.69,
"acc_norm_stderr": 0.04648231987117316
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.8160919540229885,
"acc_stderr": 0.013853724170922526,
"acc_norm": 0.8160919540229885,
"acc_norm_stderr": 0.013853724170922526
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.7398843930635838,
"acc_stderr": 0.023618678310069363,
"acc_norm": 0.7398843930635838,
"acc_norm_stderr": 0.023618678310069363
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.35307262569832404,
"acc_stderr": 0.015984204545268565,
"acc_norm": 0.35307262569832404,
"acc_norm_stderr": 0.015984204545268565
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.7777777777777778,
"acc_stderr": 0.023805186524888135,
"acc_norm": 0.7777777777777778,
"acc_norm_stderr": 0.023805186524888135
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.6945337620578779,
"acc_stderr": 0.02616058445014045,
"acc_norm": 0.6945337620578779,
"acc_norm_stderr": 0.02616058445014045
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.75,
"acc_stderr": 0.02409347123262133,
"acc_norm": 0.75,
"acc_norm_stderr": 0.02409347123262133
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.4929078014184397,
"acc_stderr": 0.02982449855912901,
"acc_norm": 0.4929078014184397,
"acc_norm_stderr": 0.02982449855912901
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.4602346805736636,
"acc_stderr": 0.012729785386598564,
"acc_norm": 0.4602346805736636,
"acc_norm_stderr": 0.012729785386598564
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.6470588235294118,
"acc_stderr": 0.029029422815681393,
"acc_norm": 0.6470588235294118,
"acc_norm_stderr": 0.029029422815681393
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.6584967320261438,
"acc_stderr": 0.019184639328092487,
"acc_norm": 0.6584967320261438,
"acc_norm_stderr": 0.019184639328092487
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.6636363636363637,
"acc_stderr": 0.04525393596302506,
"acc_norm": 0.6636363636363637,
"acc_norm_stderr": 0.04525393596302506
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.7387755102040816,
"acc_stderr": 0.028123429335142783,
"acc_norm": 0.7387755102040816,
"acc_norm_stderr": 0.028123429335142783
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.8308457711442786,
"acc_stderr": 0.026508590656233268,
"acc_norm": 0.8308457711442786,
"acc_norm_stderr": 0.026508590656233268
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.88,
"acc_stderr": 0.032659863237109066,
"acc_norm": 0.88,
"acc_norm_stderr": 0.032659863237109066
},
"harness|hendrycksTest-virology|5": {
"acc": 0.5542168674698795,
"acc_stderr": 0.03869543323472101,
"acc_norm": 0.5542168674698795,
"acc_norm_stderr": 0.03869543323472101
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.8245614035087719,
"acc_stderr": 0.02917088550072767,
"acc_norm": 0.8245614035087719,
"acc_norm_stderr": 0.02917088550072767
},
"harness|truthfulqa:mc|0": {
"mc1": 0.3329253365973072,
"mc1_stderr": 0.016497402382012052,
"mc2": 0.48572469546439073,
"mc2_stderr": 0.01547664094918918
},
"harness|winogrande|5": {
"acc": 0.7679558011049724,
"acc_stderr": 0.011864149691827936
},
"harness|gsm8k|5": {
"acc": 0.6982562547384382,
"acc_stderr": 0.012643544762873358
}
}
```
## 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] |
CyberHarem/provence_arknights | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of provence/プロヴァンス/普罗旺斯 (Arknights)
This is the dataset of provence/プロヴァンス/普罗旺斯 (Arknights), containing 153 images and their tags.
The core tags of this character are `animal_ears, wolf_ears, tail, long_hair, purple_hair, wolf_tail, yellow_eyes, braid, hair_between_eyes, wolf_girl, breasts, large_tail, single_braid, medium_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 | 153 | 252.16 MiB | [Download](https://huggingface.co/datasets/CyberHarem/provence_arknights/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 1200 | 153 | 207.20 MiB | [Download](https://huggingface.co/datasets/CyberHarem/provence_arknights/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 398 | 409.73 MiB | [Download](https://huggingface.co/datasets/CyberHarem/provence_arknights/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/provence_arknights',
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 | 17 |  |  |  |  |  | 1girl, looking_at_viewer, solo, simple_background, white_background, black_gloves, upper_body, jacket, :d, open_mouth, hood, puffy_short_sleeves, purple_shirt |
| 1 | 7 |  |  |  |  |  | 1girl, bare_shoulders, black_shorts, cleavage, hip_vent, looking_at_viewer, navel, official_alternate_costume, short_shorts, solo, stomach, black_bikini, cowboy_shot, midriff, short_sleeves, thighs, hand_up, open_mouth, shirt, single_glove, :d, blue_gloves, crop_top, fingerless_gloves, holding_food, popsicle, standing, thigh_strap, bikini_under_clothes, clothing_cutout, groin, off_shoulder, simple_background, white_background |
| 2 | 7 |  |  |  |  |  | 1girl, blush, hetero, open_mouth, solo_focus, 1boy, large_breasts, navel, nipples, penis, sex, vaginal, mosaic_censoring, extra_ears, looking_at_viewer, spread_legs, completely_nude, cum_in_pussy, cum_overflow, lying, tongue_out |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | looking_at_viewer | solo | simple_background | white_background | black_gloves | upper_body | jacket | :d | open_mouth | hood | puffy_short_sleeves | purple_shirt | bare_shoulders | black_shorts | cleavage | hip_vent | navel | official_alternate_costume | short_shorts | stomach | black_bikini | cowboy_shot | midriff | short_sleeves | thighs | hand_up | shirt | single_glove | blue_gloves | crop_top | fingerless_gloves | holding_food | popsicle | standing | thigh_strap | bikini_under_clothes | clothing_cutout | groin | off_shoulder | blush | hetero | solo_focus | 1boy | large_breasts | nipples | penis | sex | vaginal | mosaic_censoring | extra_ears | spread_legs | completely_nude | cum_in_pussy | cum_overflow | lying | tongue_out |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:-------|:--------------------|:-------------------|:---------------|:-------------|:---------|:-----|:-------------|:-------|:----------------------|:---------------|:-----------------|:---------------|:-----------|:-----------|:--------|:-----------------------------|:---------------|:----------|:---------------|:--------------|:----------|:----------------|:---------|:----------|:--------|:---------------|:--------------|:-----------|:--------------------|:---------------|:-----------|:-----------|:--------------|:-----------------------|:------------------|:--------|:---------------|:--------|:---------|:-------------|:-------|:----------------|:----------|:--------|:------|:----------|:-------------------|:-------------|:--------------|:------------------|:---------------|:---------------|:--------|:-------------|
| 0 | 17 |  |  |  |  |  | X | X | 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 | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | |
| 2 | 7 |  |  |  |  |  | X | X | | | | | | | | X | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
mazkobot/1_digit_mask_ensemble_distilled_from_cv12_balanced_mfcc | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 25771854448.0
num_examples: 5061244
download_size: 26308842420
dataset_size: 25771854448.0
---
# Dataset Card for "1_digit_mask_ensemble_distilled_from_cv12_balanced_mfcc"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-latex-23000 | ---
dataset_info:
features:
- name: input_ids
sequence:
sequence: int32
- name: attention_mask
sequence:
sequence: int8
- name: labels
sequence:
sequence: int64
splits:
- name: train
num_bytes: 13336000
num_examples: 1000
download_size: 1006931
dataset_size: 13336000
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
zhangshuoming/math_23k_train_numeric | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 20552640.641394995
num_examples: 21094
download_size: 2752930
dataset_size: 20552640.641394995
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "math_23k_train_numeric"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ickma/sec_shots | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 142
num_examples: 3
download_size: 1090
dataset_size: 142
---
# Dataset Card for "sec_shots"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
TigerResearch/pretrain_en | ---
dataset_info:
features:
- name: content
dtype: string
splits:
- name: train
num_bytes: 48490123196
num_examples: 22690306
download_size: 5070161762
dataset_size: 48490123196
license: apache-2.0
task_categories:
- text-generation
language:
- en
size_categories:
- 10M<n<100M
---
# Dataset Card for "pretrain_en"
[Tigerbot](https://github.com/TigerResearch/TigerBot) pretrain数据的英文部分。
## Usage
```python
import datasets
ds_sft = datasets.load_dataset('TigerResearch/pretrain_en')
``` |
urdu_sentiment_corpus | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- ur
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: urdu-sentiment-corpus
pretty_name: Urdu Sentiment Corpus (USC)
dataset_info:
features:
- name: sentence
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': P
'1': N
'2': O
splits:
- name: train
num_bytes: 161190
num_examples: 1000
download_size: 51583
dataset_size: 161190
---
# Dataset Card for Urdu Sentiment Corpus (USC)
## 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:** [Github](https://github.com/MuhammadYaseenKhan/Urdu-Sentiment-Corpus)
- **Repository:** [Github](https://github.com/MuhammadYaseenKhan/Urdu-Sentiment-Corpus)
- **Paper:** [IEEE](https://ieeexplore.ieee.org/abstract/document/9080043)
- **Leaderboard:**
- **Point of Contact:** [Muhammad Yaseen Khan](https://github.com/MuhammadYaseenKhan)
### 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
- sentences: The Urdu tweet
- sentiment: The sentiment that was exhibited in the tweet, which can be Positive(P) or Negative(N) or Objective(O).
### 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
Thanks to [@chaitnayabasava](https://github.com/chaitnayabasava) for adding this dataset. |
shrinath-suresh/so_5k_with_short_answer | ---
license: apache-2.0
---
|
Falah/cabo_da_roca_light_conditions | ---
dataset_info:
features:
- name: prompts
dtype: string
splits:
- name: train
num_bytes: 707338
num_examples: 10000
download_size: 11725
dataset_size: 707338
---
# Dataset Card for "cabo_da_roca_light_conditions"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Lollitor/FineTuneDataset1024 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: sequence
dtype: string
- name: label
dtype: float64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 15148943
num_examples: 15389
- name: validation
num_bytes: 1683634
num_examples: 1710
download_size: 7973519
dataset_size: 16832577
---
# Dataset Card for "FineTuneDataset1024"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
promptora11/dataset_train | ---
dataset_info:
features:
- name: Query
dtype: string
- name: Response
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 6750
num_examples: 32
download_size: 6692
dataset_size: 6750
---
# Dataset Card for "dataset_train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
cahya/wikipedia_id_20230101 | ---
dataset_info:
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 1051737365
num_examples: 634559
download_size: 544132473
dataset_size: 1051737365
---
# Dataset Card for "wikipedia_id_20230101"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Vrushali/my-image-captioning-dataset | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': blipdataset
- name: text
dtype: string
splits:
- name: train
num_bytes: 456995431.0
num_examples: 29048
download_size: 461550035
dataset_size: 456995431.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "my-image-captioning-dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
reuters21578 | ---
language:
- en
license: other
paperswithcode_id: reuters-21578
pretty_name: Reuters-21578 Text Categorization Collection
dataset_info:
- config_name: ModApte
features:
- name: text
dtype: string
- name: text_type
dtype: string
- name: topics
sequence: string
- name: lewis_split
dtype: string
- name: cgis_split
dtype: string
- name: old_id
dtype: string
- name: new_id
dtype: string
- name: places
sequence: string
- name: people
sequence: string
- name: orgs
sequence: string
- name: exchanges
sequence: string
- name: date
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 2971653
num_examples: 3299
- name: train
num_bytes: 9161179
num_examples: 9603
- name: unused
num_bytes: 948244
num_examples: 722
download_size: 8150596
dataset_size: 13081076
- config_name: ModHayes
features:
- name: text
dtype: string
- name: text_type
dtype: string
- name: topics
sequence: string
- name: lewis_split
dtype: string
- name: cgis_split
dtype: string
- name: old_id
dtype: string
- name: new_id
dtype: string
- name: places
sequence: string
- name: people
sequence: string
- name: orgs
sequence: string
- name: exchanges
sequence: string
- name: date
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 948244
num_examples: 722
- name: train
num_bytes: 19071106
num_examples: 20856
download_size: 8150596
dataset_size: 20019350
- config_name: ModLewis
features:
- name: text
dtype: string
- name: text_type
dtype: string
- name: topics
sequence: string
- name: lewis_split
dtype: string
- name: cgis_split
dtype: string
- name: old_id
dtype: string
- name: new_id
dtype: string
- name: places
sequence: string
- name: people
sequence: string
- name: orgs
sequence: string
- name: exchanges
sequence: string
- name: date
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 5400506
num_examples: 6188
- name: train
num_bytes: 12994591
num_examples: 13625
- name: unused
num_bytes: 948244
num_examples: 722
download_size: 8150596
dataset_size: 19343341
---
# Dataset Card for "reuters21578"
## 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://archive.ics.uci.edu/dataset/137/reuters+21578+text+categorization+collection
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 24.45 MB
- **Size of the generated dataset:** 52.22 MB
- **Total amount of disk used:** 76.67 MB
### Dataset Summary
The Reuters-21578 dataset is one of the most widely used data collections for text
categorization research. It is collected from the Reuters financial newswire service in 1987.
### Supported Tasks and Leaderboards
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Languages
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
## Dataset Structure
### Data Instances
#### ModApte
- **Size of downloaded dataset files:** 8.15 MB
- **Size of the generated dataset:** 13.05 MB
- **Total amount of disk used:** 21.21 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"cgis_split": "\"TRAINING-SET\"",
"date": "19-MAR-1987 06:17:22.36",
"exchanges": [],
"lewis_split": "\"TRAIN\"",
"new_id": "\"7001\"",
"old_id": "\"11914\"",
"orgs": [],
"people": [],
"places": ["australia"],
"text": "\"Media group John Fairfax Ltd <FFXA.S>\\nsaid that its flat first half net profit partly reflected the\\nimpact of changes in t...",
"title": "FAIRFAX SAYS HIGHER TAX HITS FIRST HALF EARNINGS",
"topics": ["earn"]
}
```
#### ModHayes
- **Size of downloaded dataset files:** 8.15 MB
- **Size of the generated dataset:** 19.79 MB
- **Total amount of disk used:** 27.93 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"cgis_split": "\"TRAINING-SET\"",
"date": "19-OCT-1987 23:49:31.45",
"exchanges": [],
"lewis_split": "\"TEST\"",
"new_id": "\"20001\"",
"old_id": "\"20596\"",
"orgs": [],
"people": [],
"places": ["japan", "usa"],
"text": "\"If the dollar goes the way of Wall Street,\\nJapanese will finally move out of dollar investments in a\\nserious way, Japan inves...",
"title": "IF DOLLAR FOLLOWS WALL STREET JAPANESE WILL DIVEST",
"topics": ["money-fx"]
}
```
#### ModLewis
- **Size of downloaded dataset files:** 8.15 MB
- **Size of the generated dataset:** 19.38 MB
- **Total amount of disk used:** 27.54 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"cgis_split": "\"TRAINING-SET\"",
"date": "19-MAR-1987 06:17:22.36",
"exchanges": [],
"lewis_split": "\"TRAIN\"",
"new_id": "\"7001\"",
"old_id": "\"11914\"",
"orgs": [],
"people": [],
"places": ["australia"],
"text": "\"Media group John Fairfax Ltd <FFXA.S>\\nsaid that its flat first half net profit partly reflected the\\nimpact of changes in t...",
"title": "FAIRFAX SAYS HIGHER TAX HITS FIRST HALF EARNINGS",
"topics": ["earn"]
}
```
### Data Fields
The data fields are the same among all splits.
#### ModApte
- `text`: a `string` feature.
- `topics`: a `list` of `string` features.
- `lewis_split`: a `string` feature.
- `cgis_split`: a `string` feature.
- `old_id`: a `string` feature.
- `new_id`: a `string` feature.
- `places`: a `list` of `string` features.
- `people`: a `list` of `string` features.
- `orgs`: a `list` of `string` features.
- `exchanges`: a `list` of `string` features.
- `date`: a `string` feature.
- `title`: a `string` feature.
#### ModHayes
- `text`: a `string` feature.
- `topics`: a `list` of `string` features.
- `lewis_split`: a `string` feature.
- `cgis_split`: a `string` feature.
- `old_id`: a `string` feature.
- `new_id`: a `string` feature.
- `places`: a `list` of `string` features.
- `people`: a `list` of `string` features.
- `orgs`: a `list` of `string` features.
- `exchanges`: a `list` of `string` features.
- `date`: a `string` feature.
- `title`: a `string` feature.
#### ModLewis
- `text`: a `string` feature.
- `topics`: a `list` of `string` features.
- `lewis_split`: a `string` feature.
- `cgis_split`: a `string` feature.
- `old_id`: a `string` feature.
- `new_id`: a `string` feature.
- `places`: a `list` of `string` features.
- `people`: a `list` of `string` features.
- `orgs`: a `list` of `string` features.
- `exchanges`: a `list` of `string` features.
- `date`: a `string` feature.
- `title`: a `string` feature.
### Data Splits
#### ModApte
| |train|unused|test|
|-------|----:|-----:|---:|
|ModApte| 8762| 720|3009|
#### ModHayes
| |train|test|
|--------|----:|---:|
|ModHayes|18323| 720|
#### ModLewis
| |train|unused|test|
|--------|----:|-----:|---:|
|ModLewis|12449| 720|5458|
## Dataset Creation
### Curation Rationale
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
#### Who are the source language producers?
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Annotations
#### Annotation process
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
#### Who are the annotators?
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Personal and Sensitive Information
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Discussion of Biases
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Other Known Limitations
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
## Additional Information
### Dataset Curators
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Licensing Information
According to the dataset website (https://archive.ics.uci.edu/dataset/137/reuters+21578+text+categorization+collection),
this dataset is licensed under [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode)
(C BY 4.0) license.
However, the source data file contains a `README.txt` file with the following information under the
**Copyright & Notification** section:
> The copyright for the text of newswire articles and Reuters
annotations in the Reuters-21578 collection resides with Reuters Ltd.
Reuters Ltd. and Carnegie Group, Inc. have agreed to allow the free
distribution of this data *for research purposes only*.
> If you publish results based on this data set, please acknowledge
its use, refer to the data set by the name "Reuters-21578,
Distribution 1.0", and inform your readers of the current location of
the data set (see "Availability & Questions").
### Citation Information
```
@article{APTE94,
author = {Chidanand Apt{'{e}} and Fred Damerau and Sholom M. Weiss},
title = {Automated Learning of Decision Rules for Text Categorization},
journal = {ACM Transactions on Information Systems},
year = {1994},
note = {To appear.}
}
@inproceedings{APTE94b,
author = {Chidanand Apt{'{e}} and Fred Damerau and Sholom M. Weiss},
title = {Toward Language Independent Automated Learning of Text Categorization Models},
booktitle = {sigir94},
year = {1994},
note = {To appear.}
}
@inproceedings{HAYES8},
author = {Philip J. Hayes and Peggy M. Anderson and Irene B. Nirenburg and
Linda M. Schmandt},
title = {{TCS}: A Shell for Content-Based Text Categorization},
booktitle = {IEEE Conference on Artificial Intelligence Applications},
year = {1990}
}
@inproceedings{HAYES90b,
author = {Philip J. Hayes and Steven P. Weinstein},
title = {{CONSTRUE/TIS:} A System for Content-Based Indexing of a
Database of News Stories},
booktitle = {Second Annual Conference on Innovative Applications of
Artificial Intelligence},
year = {1990}
}
@incollection{HAYES92 ,
author = {Philip J. Hayes},
title = {Intelligent High-Volume Text Processing using Shallow,
Domain-Specific Techniques},
booktitle = {Text-Based Intelligent Systems},
publisher = {Lawrence Erlbaum},
address = {Hillsdale, NJ},
year = {1992},
editor = {Paul S. Jacobs}
}
@inproceedings{LEWIS91c ,
author = {David D. Lewis},
title = {Evaluating Text Categorization},
booktitle = {Proceedings of Speech and Natural Language Workshop},
year = {1991},
month = {feb},
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
pages = {312--318}
}
@phdthesis{LEWIS91d,
author = {David Dolan Lewis},
title = {Representation and Learning in Information Retrieval},
school = {Computer Science Dept.; Univ. of Massachusetts; Amherst, MA 01003},
year = 1992},
note = {Technical Report 91--93.}
}
@inproceedings{LEWIS91e,
author = {David D. Lewis},
title = {Data Extraction as Text Categorization: An Experiment with
the {MUC-3} Corpus},
booktitle = {Proceedings of the Third Message Understanding Evaluation
and Conference},
year = {1991},
month = {may},
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
address = {Los Altos, CA}
}
@inproceedings{LEWIS92b,
author = {David D. Lewis},
title = {An Evaluation of Phrasal and Clustered Representations on a Text
Categorization Task},
booktitle = {Fifteenth Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval},
year = {1992},
pages = {37--50}
}
@inproceedings{LEWIS92d ,
author = {David D. Lewis and Richard M. Tong},
title = {Text Filtering in {MUC-3} and {MUC-4}},
booktitle = {Proceedings of the Fourth Message Understanding Conference ({MUC-4})},
year = {1992},
month = {jun},
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
address = {Los Altos, CA}
}
@inproceedings{LEWIS92e,
author = {David D. Lewis},
title = {Feature Selection and Feature Extraction for Text Categorization},
booktitle = {Proceedings of Speech and Natural Language Workshop},
year = {1992},
month = {feb} ,
organization = {Defense Advanced Research Projects Agency},
publisher = {Morgan Kaufmann},
pages = {212--217}
}
@inproceedings{LEWIS94b,
author = {David D. Lewis and Marc Ringuette},
title = {A Comparison of Two Learning Algorithms for Text Categorization},
booktitle = {Symposium on Document Analysis and Information Retrieval},
year = {1994},
organization = {ISRI; Univ. of Nevada, Las Vegas},
address = {Las Vegas, NV},
month = {apr},
pages = {81--93}
}
@article{LEWIS94d,
author = {David D. Lewis and Philip J. Hayes},
title = {Guest Editorial},
journal = {ACM Transactions on Information Systems},
year = {1994},
volume = {12},
number = {3},
pages = {231},
month = {jul}
}
@article{SPARCKJONES76,
author = {K. {Sparck Jones} and C. J. {van Rijsbergen}},
title = {Information Retrieval Test Collections},
journal = {Journal of Documentation},
year = {1976},
volume = {32},
number = {1},
pages = {59--75}
}
@book{WEISS91,
author = {Sholom M. Weiss and Casimir A. Kulikowski},
title = {Computer Systems That Learn},
publisher = {Morgan Kaufmann},
year = {1991},
address = {San Mateo, CA}
}
```
### Contributions
Thanks to [@jplu](https://github.com/jplu), [@jbragg](https://github.com/jbragg), [@thomwolf](https://github.com/thomwolf), [@mariamabarham](https://github.com/mariamabarham), [@lhoestq](https://github.com/lhoestq) for adding this dataset. |
coroperv/oxford-flowers | ---
license: unknown
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': '1'
'1': '10'
'2': '100'
'3': '102'
'4': '12'
'5': '13'
'6': '15'
'7': '16'
'8': '17'
'9': '19'
'10': '22'
'11': '26'
'12': '28'
'13': '29'
'14': '31'
'15': '33'
'16': '34'
'17': '36'
'18': '38'
'19': '40'
'20': '41'
'21': '42'
'22': '45'
'23': '47'
'24': '48'
'25': '49'
'26': '5'
'27': '50'
'28': '51'
'29': '52'
'30': '54'
'31': '55'
'32': '56'
'33': '57'
'34': '59'
'35': '62'
'36': '63'
'37': '64'
'38': '65'
'39': '66'
'40': '68'
'41': '69'
'42': '7'
'43': '70'
'44': '71'
'45': '73'
'46': '74'
'47': '75'
'48': '76'
'49': '77'
'50': '78'
'51': '81'
'52': '82'
'53': '83'
'54': '85'
'55': '86'
'56': '89'
'57': '91'
'58': '96'
'59': '98'
'60': '99'
splits:
- name: train
num_bytes: 103936242.384
num_examples: 2452
download_size: 99259189
dataset_size: 103936242.384
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
AdapterOcean/med_alpaca_standardized_cluster_0_alpaca | ---
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 18113077
num_examples: 10247
download_size: 10005035
dataset_size: 18113077
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "med_alpaca_standardized_cluster_0_alpaca"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_BreadAi__gpt-YA-1-1_160M | ---
pretty_name: Evaluation run of BreadAi/gpt-YA-1-1_160M
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [BreadAi/gpt-YA-1-1_160M](https://huggingface.co/BreadAi/gpt-YA-1-1_160M) 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_BreadAi__gpt-YA-1-1_160M\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-16T23:15:39.203631](https://huggingface.co/datasets/open-llm-leaderboard/details_BreadAi__gpt-YA-1-1_160M/blob/main/results_2023-09-16T23-15-39.203631.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\": 0.0037751677852348995,\n\
\ \"em_stderr\": 0.0006280387809484644,\n \"f1\": 0.02323720637583893,\n\
\ \"f1_stderr\": 0.0010591010187142242,\n \"acc\": 0.2533543804262036,\n\
\ \"acc_stderr\": 0.007025610346165173\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.0037751677852348995,\n \"em_stderr\": 0.0006280387809484644,\n\
\ \"f1\": 0.02323720637583893,\n \"f1_stderr\": 0.0010591010187142242\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\
: 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.5067087608524072,\n\
\ \"acc_stderr\": 0.014051220692330346\n }\n}\n```"
repo_url: https://huggingface.co/BreadAi/gpt-YA-1-1_160M
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_02_10.207194
path:
- '**/details_harness|arc:challenge|25_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_16T23_15_39.203631
path:
- '**/details_harness|drop|3_2023-09-16T23-15-39.203631.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-16T23-15-39.203631.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_16T23_15_39.203631
path:
- '**/details_harness|gsm8k|5_2023-09-16T23-15-39.203631.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-16T23-15-39.203631.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hellaswag|10_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:02:10.207194.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T14:02:10.207194.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T14:02:10.207194.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_16T23_15_39.203631
path:
- '**/details_harness|winogrande|5_2023-09-16T23-15-39.203631.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-16T23-15-39.203631.parquet'
- config_name: results
data_files:
- split: 2023_07_19T14_02_10.207194
path:
- results_2023-07-19T14:02:10.207194.parquet
- split: 2023_09_16T23_15_39.203631
path:
- results_2023-09-16T23-15-39.203631.parquet
- split: latest
path:
- results_2023-09-16T23-15-39.203631.parquet
---
# Dataset Card for Evaluation run of BreadAi/gpt-YA-1-1_160M
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/BreadAi/gpt-YA-1-1_160M
- **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 [BreadAi/gpt-YA-1-1_160M](https://huggingface.co/BreadAi/gpt-YA-1-1_160M) 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_BreadAi__gpt-YA-1-1_160M",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-16T23:15:39.203631](https://huggingface.co/datasets/open-llm-leaderboard/details_BreadAi__gpt-YA-1-1_160M/blob/main/results_2023-09-16T23-15-39.203631.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": 0.0037751677852348995,
"em_stderr": 0.0006280387809484644,
"f1": 0.02323720637583893,
"f1_stderr": 0.0010591010187142242,
"acc": 0.2533543804262036,
"acc_stderr": 0.007025610346165173
},
"harness|drop|3": {
"em": 0.0037751677852348995,
"em_stderr": 0.0006280387809484644,
"f1": 0.02323720637583893,
"f1_stderr": 0.0010591010187142242
},
"harness|gsm8k|5": {
"acc": 0.0,
"acc_stderr": 0.0
},
"harness|winogrande|5": {
"acc": 0.5067087608524072,
"acc_stderr": 0.014051220692330346
}
}
```
### 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_allknowingroger__NeuralCeptrix-7B-slerp | ---
pretty_name: Evaluation run of allknowingroger/NeuralCeptrix-7B-slerp
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [allknowingroger/NeuralCeptrix-7B-slerp](https://huggingface.co/allknowingroger/NeuralCeptrix-7B-slerp)\
\ 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_allknowingroger__NeuralCeptrix-7B-slerp\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-04-10T21:14:16.828642](https://huggingface.co/datasets/open-llm-leaderboard/details_allknowingroger__NeuralCeptrix-7B-slerp/blob/main/results_2024-04-10T21-14-16.828642.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\": 0.6495434097360565,\n\
\ \"acc_stderr\": 0.032279899940585416,\n \"acc_norm\": 0.6487090853177374,\n\
\ \"acc_norm_stderr\": 0.03296063025774512,\n \"mc1\": 0.6523867809057528,\n\
\ \"mc1_stderr\": 0.01667076918889731,\n \"mc2\": 0.7984722132506933,\n\
\ \"mc2_stderr\": 0.013281143496846105\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.7022184300341296,\n \"acc_stderr\": 0.013363080107244482,\n\
\ \"acc_norm\": 0.7209897610921502,\n \"acc_norm_stderr\": 0.013106784883601334\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7197769368651663,\n\
\ \"acc_stderr\": 0.004481902637505651,\n \"acc_norm\": 0.8919537940649273,\n\
\ \"acc_norm_stderr\": 0.0030980431017758477\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \
\ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6222222222222222,\n\
\ \"acc_stderr\": 0.04188307537595853,\n \"acc_norm\": 0.6222222222222222,\n\
\ \"acc_norm_stderr\": 0.04188307537595853\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.03738520676119669,\n\
\ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.03738520676119669\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.62,\n\
\ \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n \
\ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6792452830188679,\n \"acc_stderr\": 0.028727502957880267,\n\
\ \"acc_norm\": 0.6792452830188679,\n \"acc_norm_stderr\": 0.028727502957880267\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7777777777777778,\n\
\ \"acc_stderr\": 0.03476590104304134,\n \"acc_norm\": 0.7777777777777778,\n\
\ \"acc_norm_stderr\": 0.03476590104304134\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \
\ \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.050211673156867795\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.57,\n \"acc_stderr\": 0.04975698519562428,\n \"acc_norm\"\
: 0.57,\n \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.04793724854411019,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.04793724854411019\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6358381502890174,\n\
\ \"acc_stderr\": 0.03669072477416907,\n \"acc_norm\": 0.6358381502890174,\n\
\ \"acc_norm_stderr\": 0.03669072477416907\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\": 0.044619604333847394,\n \"acc_norm\": 0.73,\n\
\ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108102,\n\
\ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108102\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\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\
\ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.41798941798941797,\n \"acc_stderr\": 0.025402555503260912,\n \"\
acc_norm\": 0.41798941798941797,\n \"acc_norm_stderr\": 0.025402555503260912\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.47619047619047616,\n\
\ \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.47619047619047616,\n\
\ \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness|hendrycksTest-global_facts|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-high_school_biology|5\": {\n \"acc\": 0.7709677419354839,\n\
\ \"acc_stderr\": 0.02390491431178265,\n \"acc_norm\": 0.7709677419354839,\n\
\ \"acc_norm_stderr\": 0.02390491431178265\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\": 0.7636363636363637,\n \"acc_stderr\": 0.03317505930009181,\n\
\ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.03317505930009181\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\": 0.658974358974359,\n \"acc_stderr\": 0.02403548967633508,\n \
\ \"acc_norm\": 0.658974358974359,\n \"acc_norm_stderr\": 0.02403548967633508\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.34444444444444444,\n \"acc_stderr\": 0.028972648884844267,\n \
\ \"acc_norm\": 0.34444444444444444,\n \"acc_norm_stderr\": 0.028972648884844267\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.030388353551886793,\n\
\ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.030388353551886793\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3708609271523179,\n \"acc_stderr\": 0.03943966699183629,\n \"\
acc_norm\": 0.3708609271523179,\n \"acc_norm_stderr\": 0.03943966699183629\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8403669724770643,\n \"acc_stderr\": 0.015703498348461766,\n \"\
acc_norm\": 0.8403669724770643,\n \"acc_norm_stderr\": 0.015703498348461766\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5277777777777778,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\
: 0.5277777777777778,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\
\ \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.8431372549019608,\n\
\ \"acc_stderr\": 0.025524722324553353,\n \"acc_norm\": 0.8431372549019608,\n\
\ \"acc_norm_stderr\": 0.025524722324553353\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\
: {\n \"acc\": 0.8016877637130801,\n \"acc_stderr\": 0.02595502084162113,\n\
\ \"acc_norm\": 0.8016877637130801,\n \"acc_norm_stderr\": 0.02595502084162113\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6681614349775785,\n\
\ \"acc_stderr\": 0.03160295143776679,\n \"acc_norm\": 0.6681614349775785,\n\
\ \"acc_norm_stderr\": 0.03160295143776679\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\
\ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.743801652892562,\n \"acc_stderr\": 0.03984979653302872,\n \"acc_norm\"\
: 0.743801652892562,\n \"acc_norm_stderr\": 0.03984979653302872\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7777777777777778,\n\
\ \"acc_stderr\": 0.0401910747255735,\n \"acc_norm\": 0.7777777777777778,\n\
\ \"acc_norm_stderr\": 0.0401910747255735\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\
\ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.42857142857142855,\n\
\ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\
\ \"acc_norm_stderr\": 0.04697113923010212\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\": 0.021586494001281365,\n \"acc_norm\": 0.8760683760683761,\n\
\ \"acc_norm_stderr\": 0.021586494001281365\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.8160919540229885,\n\
\ \"acc_stderr\": 0.01385372417092253,\n \"acc_norm\": 0.8160919540229885,\n\
\ \"acc_norm_stderr\": 0.01385372417092253\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7225433526011561,\n \"acc_stderr\": 0.024105712607754307,\n\
\ \"acc_norm\": 0.7225433526011561,\n \"acc_norm_stderr\": 0.024105712607754307\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4245810055865922,\n\
\ \"acc_stderr\": 0.016531170993278888,\n \"acc_norm\": 0.4245810055865922,\n\
\ \"acc_norm_stderr\": 0.016531170993278888\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7156862745098039,\n \"acc_stderr\": 0.02582916327275748,\n\
\ \"acc_norm\": 0.7156862745098039,\n \"acc_norm_stderr\": 0.02582916327275748\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6945337620578779,\n\
\ \"acc_stderr\": 0.02616058445014045,\n \"acc_norm\": 0.6945337620578779,\n\
\ \"acc_norm_stderr\": 0.02616058445014045\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7314814814814815,\n \"acc_stderr\": 0.024659685185967284,\n\
\ \"acc_norm\": 0.7314814814814815,\n \"acc_norm_stderr\": 0.024659685185967284\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.48936170212765956,\n \"acc_stderr\": 0.02982074719142248,\n \
\ \"acc_norm\": 0.48936170212765956,\n \"acc_norm_stderr\": 0.02982074719142248\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.47131681877444587,\n\
\ \"acc_stderr\": 0.012749206007657476,\n \"acc_norm\": 0.47131681877444587,\n\
\ \"acc_norm_stderr\": 0.012749206007657476\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6838235294117647,\n \"acc_stderr\": 0.028245687391462923,\n\
\ \"acc_norm\": 0.6838235294117647,\n \"acc_norm_stderr\": 0.028245687391462923\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6797385620915033,\n \"acc_stderr\": 0.018875682938069443,\n \
\ \"acc_norm\": 0.6797385620915033,\n \"acc_norm_stderr\": 0.018875682938069443\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\": 0.7387755102040816,\n \"acc_stderr\": 0.02812342933514278,\n\
\ \"acc_norm\": 0.7387755102040816,\n \"acc_norm_stderr\": 0.02812342933514278\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8308457711442786,\n\
\ \"acc_stderr\": 0.02650859065623327,\n \"acc_norm\": 0.8308457711442786,\n\
\ \"acc_norm_stderr\": 0.02650859065623327\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\": 0.5481927710843374,\n\
\ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.5481927710843374,\n\
\ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640044,\n\
\ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640044\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.6523867809057528,\n\
\ \"mc1_stderr\": 0.01667076918889731,\n \"mc2\": 0.7984722132506933,\n\
\ \"mc2_stderr\": 0.013281143496846105\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8516179952644041,\n \"acc_stderr\": 0.009990706005184136\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6876421531463229,\n \
\ \"acc_stderr\": 0.012765850404191407\n }\n}\n```"
repo_url: https://huggingface.co/allknowingroger/NeuralCeptrix-7B-slerp
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_04_10T21_14_16.828642
path:
- '**/details_harness|arc:challenge|25_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|gsm8k|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hellaswag|10_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-04-10T21-14-16.828642.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-management|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-virology|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|truthfulqa:mc|0_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-04-10T21-14-16.828642.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- '**/details_harness|winogrande|5_2024-04-10T21-14-16.828642.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-04-10T21-14-16.828642.parquet'
- config_name: results
data_files:
- split: 2024_04_10T21_14_16.828642
path:
- results_2024-04-10T21-14-16.828642.parquet
- split: latest
path:
- results_2024-04-10T21-14-16.828642.parquet
---
# Dataset Card for Evaluation run of allknowingroger/NeuralCeptrix-7B-slerp
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [allknowingroger/NeuralCeptrix-7B-slerp](https://huggingface.co/allknowingroger/NeuralCeptrix-7B-slerp) 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_allknowingroger__NeuralCeptrix-7B-slerp",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-04-10T21:14:16.828642](https://huggingface.co/datasets/open-llm-leaderboard/details_allknowingroger__NeuralCeptrix-7B-slerp/blob/main/results_2024-04-10T21-14-16.828642.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": 0.6495434097360565,
"acc_stderr": 0.032279899940585416,
"acc_norm": 0.6487090853177374,
"acc_norm_stderr": 0.03296063025774512,
"mc1": 0.6523867809057528,
"mc1_stderr": 0.01667076918889731,
"mc2": 0.7984722132506933,
"mc2_stderr": 0.013281143496846105
},
"harness|arc:challenge|25": {
"acc": 0.7022184300341296,
"acc_stderr": 0.013363080107244482,
"acc_norm": 0.7209897610921502,
"acc_norm_stderr": 0.013106784883601334
},
"harness|hellaswag|10": {
"acc": 0.7197769368651663,
"acc_stderr": 0.004481902637505651,
"acc_norm": 0.8919537940649273,
"acc_norm_stderr": 0.0030980431017758477
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.36,
"acc_stderr": 0.048241815132442176,
"acc_norm": 0.36,
"acc_norm_stderr": 0.048241815132442176
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6222222222222222,
"acc_stderr": 0.04188307537595853,
"acc_norm": 0.6222222222222222,
"acc_norm_stderr": 0.04188307537595853
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6973684210526315,
"acc_stderr": 0.03738520676119669,
"acc_norm": 0.6973684210526315,
"acc_norm_stderr": 0.03738520676119669
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.62,
"acc_stderr": 0.048783173121456316,
"acc_norm": 0.62,
"acc_norm_stderr": 0.048783173121456316
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6792452830188679,
"acc_stderr": 0.028727502957880267,
"acc_norm": 0.6792452830188679,
"acc_norm_stderr": 0.028727502957880267
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7777777777777778,
"acc_stderr": 0.03476590104304134,
"acc_norm": 0.7777777777777778,
"acc_norm_stderr": 0.03476590104304134
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.52,
"acc_stderr": 0.050211673156867795,
"acc_norm": 0.52,
"acc_norm_stderr": 0.050211673156867795
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.57,
"acc_stderr": 0.04975698519562428,
"acc_norm": 0.57,
"acc_norm_stderr": 0.04975698519562428
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.35,
"acc_stderr": 0.04793724854411019,
"acc_norm": 0.35,
"acc_norm_stderr": 0.04793724854411019
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6358381502890174,
"acc_stderr": 0.03669072477416907,
"acc_norm": 0.6358381502890174,
"acc_norm_stderr": 0.03669072477416907
},
"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": 0.044619604333847394,
"acc_norm": 0.73,
"acc_norm_stderr": 0.044619604333847394
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5617021276595745,
"acc_stderr": 0.03243618636108102,
"acc_norm": 0.5617021276595745,
"acc_norm_stderr": 0.03243618636108102
},
"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": 0.5586206896551724,
"acc_stderr": 0.04137931034482757,
"acc_norm": 0.5586206896551724,
"acc_norm_stderr": 0.04137931034482757
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.41798941798941797,
"acc_stderr": 0.025402555503260912,
"acc_norm": 0.41798941798941797,
"acc_norm_stderr": 0.025402555503260912
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.47619047619047616,
"acc_stderr": 0.04467062628403273,
"acc_norm": 0.47619047619047616,
"acc_norm_stderr": 0.04467062628403273
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.31,
"acc_stderr": 0.04648231987117316,
"acc_norm": 0.31,
"acc_norm_stderr": 0.04648231987117316
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7709677419354839,
"acc_stderr": 0.02390491431178265,
"acc_norm": 0.7709677419354839,
"acc_norm_stderr": 0.02390491431178265
},
"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": 0.7636363636363637,
"acc_stderr": 0.03317505930009181,
"acc_norm": 0.7636363636363637,
"acc_norm_stderr": 0.03317505930009181
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.8080808080808081,
"acc_stderr": 0.028057791672989017,
"acc_norm": 0.8080808080808081,
"acc_norm_stderr": 0.028057791672989017
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.8911917098445595,
"acc_stderr": 0.022473253332768763,
"acc_norm": 0.8911917098445595,
"acc_norm_stderr": 0.022473253332768763
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.658974358974359,
"acc_stderr": 0.02403548967633508,
"acc_norm": 0.658974358974359,
"acc_norm_stderr": 0.02403548967633508
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.34444444444444444,
"acc_stderr": 0.028972648884844267,
"acc_norm": 0.34444444444444444,
"acc_norm_stderr": 0.028972648884844267
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6764705882352942,
"acc_stderr": 0.030388353551886793,
"acc_norm": 0.6764705882352942,
"acc_norm_stderr": 0.030388353551886793
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.3708609271523179,
"acc_stderr": 0.03943966699183629,
"acc_norm": 0.3708609271523179,
"acc_norm_stderr": 0.03943966699183629
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8403669724770643,
"acc_stderr": 0.015703498348461766,
"acc_norm": 0.8403669724770643,
"acc_norm_stderr": 0.015703498348461766
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.5277777777777778,
"acc_stderr": 0.0340470532865388,
"acc_norm": 0.5277777777777778,
"acc_norm_stderr": 0.0340470532865388
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8431372549019608,
"acc_stderr": 0.025524722324553353,
"acc_norm": 0.8431372549019608,
"acc_norm_stderr": 0.025524722324553353
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.8016877637130801,
"acc_stderr": 0.02595502084162113,
"acc_norm": 0.8016877637130801,
"acc_norm_stderr": 0.02595502084162113
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.6681614349775785,
"acc_stderr": 0.03160295143776679,
"acc_norm": 0.6681614349775785,
"acc_norm_stderr": 0.03160295143776679
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.7862595419847328,
"acc_stderr": 0.0359546161177469,
"acc_norm": 0.7862595419847328,
"acc_norm_stderr": 0.0359546161177469
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.743801652892562,
"acc_stderr": 0.03984979653302872,
"acc_norm": 0.743801652892562,
"acc_norm_stderr": 0.03984979653302872
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.7777777777777778,
"acc_stderr": 0.0401910747255735,
"acc_norm": 0.7777777777777778,
"acc_norm_stderr": 0.0401910747255735
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.7668711656441718,
"acc_stderr": 0.0332201579577674,
"acc_norm": 0.7668711656441718,
"acc_norm_stderr": 0.0332201579577674
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.42857142857142855,
"acc_stderr": 0.04697113923010212,
"acc_norm": 0.42857142857142855,
"acc_norm_stderr": 0.04697113923010212
},
"harness|hendrycksTest-management|5": {
"acc": 0.7669902912621359,
"acc_stderr": 0.04185832598928315,
"acc_norm": 0.7669902912621359,
"acc_norm_stderr": 0.04185832598928315
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.8760683760683761,
"acc_stderr": 0.021586494001281365,
"acc_norm": 0.8760683760683761,
"acc_norm_stderr": 0.021586494001281365
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.7,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.7,
"acc_norm_stderr": 0.046056618647183814
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.8160919540229885,
"acc_stderr": 0.01385372417092253,
"acc_norm": 0.8160919540229885,
"acc_norm_stderr": 0.01385372417092253
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.7225433526011561,
"acc_stderr": 0.024105712607754307,
"acc_norm": 0.7225433526011561,
"acc_norm_stderr": 0.024105712607754307
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.4245810055865922,
"acc_stderr": 0.016531170993278888,
"acc_norm": 0.4245810055865922,
"acc_norm_stderr": 0.016531170993278888
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.7156862745098039,
"acc_stderr": 0.02582916327275748,
"acc_norm": 0.7156862745098039,
"acc_norm_stderr": 0.02582916327275748
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.6945337620578779,
"acc_stderr": 0.02616058445014045,
"acc_norm": 0.6945337620578779,
"acc_norm_stderr": 0.02616058445014045
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.7314814814814815,
"acc_stderr": 0.024659685185967284,
"acc_norm": 0.7314814814814815,
"acc_norm_stderr": 0.024659685185967284
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.48936170212765956,
"acc_stderr": 0.02982074719142248,
"acc_norm": 0.48936170212765956,
"acc_norm_stderr": 0.02982074719142248
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.47131681877444587,
"acc_stderr": 0.012749206007657476,
"acc_norm": 0.47131681877444587,
"acc_norm_stderr": 0.012749206007657476
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.6838235294117647,
"acc_stderr": 0.028245687391462923,
"acc_norm": 0.6838235294117647,
"acc_norm_stderr": 0.028245687391462923
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.6797385620915033,
"acc_stderr": 0.018875682938069443,
"acc_norm": 0.6797385620915033,
"acc_norm_stderr": 0.018875682938069443
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.6727272727272727,
"acc_stderr": 0.0449429086625209,
"acc_norm": 0.6727272727272727,
"acc_norm_stderr": 0.0449429086625209
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.7387755102040816,
"acc_stderr": 0.02812342933514278,
"acc_norm": 0.7387755102040816,
"acc_norm_stderr": 0.02812342933514278
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.8308457711442786,
"acc_stderr": 0.02650859065623327,
"acc_norm": 0.8308457711442786,
"acc_norm_stderr": 0.02650859065623327
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.86,
"acc_stderr": 0.03487350880197771,
"acc_norm": 0.86,
"acc_norm_stderr": 0.03487350880197771
},
"harness|hendrycksTest-virology|5": {
"acc": 0.5481927710843374,
"acc_stderr": 0.03874371556587953,
"acc_norm": 0.5481927710843374,
"acc_norm_stderr": 0.03874371556587953
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.8187134502923976,
"acc_stderr": 0.029547741687640044,
"acc_norm": 0.8187134502923976,
"acc_norm_stderr": 0.029547741687640044
},
"harness|truthfulqa:mc|0": {
"mc1": 0.6523867809057528,
"mc1_stderr": 0.01667076918889731,
"mc2": 0.7984722132506933,
"mc2_stderr": 0.013281143496846105
},
"harness|winogrande|5": {
"acc": 0.8516179952644041,
"acc_stderr": 0.009990706005184136
},
"harness|gsm8k|5": {
"acc": 0.6876421531463229,
"acc_stderr": 0.012765850404191407
}
}
```
## 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] |
owanr/gpt-vs-human-annots | ---
license: apache-2.0
---
|
Vijay06nh/sample_v1 | ---
license: apache-2.0
---
|
rhaymison/orca-math-portuguese-64k | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 67908462
num_examples: 64081
download_size: 24062641
dataset_size: 67908462
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: apache-2.0
task_categories:
- text-generation
- question-answering
language:
- pt
tags:
- math
- matematica
size_categories:
- 10K<n<100K
pretty_name: orca math portuguese
---
translated for:
<!-- Provide the basic links for the dataset. -->
- **Repository:** [microsoft/orca-math-word-problems-200k](https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k)
- **Paper:** [Orca-Math: Unlocking the potential of
SLMs in Grade School Math](https://arxiv.org/pdf/2402.14830.pdf) |
asun17904/no_bank_examples | ---
dataset_info:
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: sentences
sequence: string
splits:
- name: train
num_bytes: 40311360919
num_examples: 6458670
download_size: 23461049304
dataset_size: 40311360919
---
# Dataset Card for "no_bank_examples"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Shoubhik8/instruct_data_train | ---
dataset_info:
features:
- name: instructions
dtype: string
- name: output
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 219317265
num_examples: 220000
download_size: 9631975
dataset_size: 219317265
---
# Dataset Card for "instruct_data_train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
southlemon/s-test1 | ---
license: unknown
---
|
yRodrigus/_ssalokin | ---
license: openrail
---
|
namanyash/client-3-preprocessed-platypus | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 7821169
num_examples: 6000
download_size: 4319064
dataset_size: 7821169
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
liuyanchen1015/MULTI_VALUE_sst2_your_yalls | ---
dataset_info:
features:
- name: sentence
dtype: string
- name: label
dtype: int64
- name: idx
dtype: int64
- name: score
dtype: int64
splits:
- name: dev
num_bytes: 1813
num_examples: 14
- name: test
num_bytes: 5815
num_examples: 39
- name: train
num_bytes: 99647
num_examples: 883
download_size: 45138
dataset_size: 107275
---
# Dataset Card for "MULTI_VALUE_sst2_your_yalls"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
jan27/guanaco-llama2-1k | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1654448
num_examples: 1000
download_size: 966693
dataset_size: 1654448
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "guanaco-llama2-1k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Yddvcodes/test_dataset | ---
license: wtfpl
task_categories:
- question-answering
language:
- en
pretty_name: testy
--- |
liuyanchen1015/MULTI_VALUE_rte_possessives_for_post | ---
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:
- name: test
num_bytes: 617408
num_examples: 1492
- name: train
num_bytes: 554538
num_examples: 1311
download_size: 754396
dataset_size: 1171946
---
# Dataset Card for "MULTI_VALUE_rte_possessives_for_post"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
BPHoops/futurama | ---
license: apache-2.0
---
|
abideen/pretrain_corpus | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 199296832162.51273
num_examples: 65123248
- name: validation
num_bytes: 35170032625.48728
num_examples: 11492339
download_size: 136513929683
dataset_size: 234466864788.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
|
Karim-Gamal/SemEval-2018-Task-2-english-emojis | ---
license: apache-2.0
---
|
nikchar/20k_claims_train_final | ---
dataset_info:
features:
- name: claim
dtype: string
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 30738751.0
num_examples: 19998
download_size: 17098290
dataset_size: 30738751.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "20k_claims_train_final"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
medalpaca/medical_meadow_pubmed_causal | ---
task_categories:
- question-answering
language:
- en
---
# Dataset Card for Pubmed Causal
## Dataset Description
- **Paper:** https://aclanthology.org/D19-1473/
### Dataset Summary
This is the dataset used in the paper: Detecting Causal Language Use in Science Findings.
### Citation Information
```
@inproceedings{yu-etal-2019-detecting,
title = "Detecting Causal Language Use in Science Findings",
author = "Yu, Bei and
Li, Yingya and
Wang, Jun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1473",
doi = "10.18653/v1/D19-1473",
pages = "4664--4674",
}
``` |
edumunozsala/Bactrian-X-instruction-es | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: id
dtype: string
- name: output
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 122397731
num_examples: 67017
download_size: 63536232
dataset_size: 122397731
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
kichanj/customchan | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 4790
num_examples: 29
download_size: 3544
dataset_size: 4790
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
StofEzz/data1000_preprocessed | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: input_values
sequence: float32
- name: labels
sequence: int64
splits:
- name: test
num_bytes: 33556448
num_examples: 100
- name: train
num_bytes: 287053448
num_examples: 1000
- name: validation
num_bytes: 30626216
num_examples: 100
download_size: 350661232
dataset_size: 351236112
---
# Dataset Card for "data1000_preprocessed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
NobodyExistsOnTheInternet/10kexamplesample | ---
license: other
---
|
maywell/ELLL_sorted | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: eng_percentage
dtype: float64
- name: question_token_count
dtype: int64
- name: answer_token_count
dtype: int64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 116961414
num_examples: 61587
download_size: 73312742
dataset_size: 116961414
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ELLL_sorted"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
svjack/diffusiondb_random_10k_zh_v1 | ---
annotations_creators:
- machine-generated
language:
- en
- zh
language_creators:
- other
multilinguality:
- multilingual
pretty_name: 'Pokémon BLIP captions'
size_categories:
- 10K
dataset_info:
features:
- name: image
dtype: image
- name: prompt
dtype: string
- name: seed
dtype: int64
- name: step
dtype: int64
- name: cfg
dtype: float32
- name: sampler
dtype: string
- name: zh_prompt
dtype: string
splits:
- name: train
num_bytes: 5826763233.4353
num_examples: 9841
download_size: 5829710525
dataset_size: 5826763233.4353
---
# Dataset Card for "diffusiondb_random_10k_zh_v1"
svjack/diffusiondb_random_10k_zh_v1 is a dataset that random sample 10k English samples from [diffusiondb](https://github.com/poloclub/diffusiondb) and use [NMT](https://en.wikipedia.org/wiki/Neural_machine_translation) translate them into Chinese with some corrections.<br/>
it used to train stable diffusion models in <br/> [svjack/Stable-Diffusion-FineTuned-zh-v0](https://huggingface.co/svjack/Stable-Diffusion-FineTuned-zh-v0)<br/>
[svjack/Stable-Diffusion-FineTuned-zh-v1](https://huggingface.co/svjack/Stable-Diffusion-FineTuned-zh-v1)<br/>
[svjack/Stable-Diffusion-FineTuned-zh-v2](https://huggingface.co/svjack/Stable-Diffusion-FineTuned-zh-v2)<br/>
And is the data support of [https://github.com/svjack/Stable-Diffusion-Chinese-Extend](https://github.com/svjack/Stable-Diffusion-Chinese-Extend) which is a fine tune version of Stable Diffusion model on self-translate 10k diffusiondb Chinese Corpus and "extend" it.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
roborovski/glaive-tool-usage-dpo | ---
dataset_info:
features:
- name: system
dtype: string
- name: question
dtype: string
- name: chosen
dtype: string
- name: rejected
dtype: string
splits:
- name: train
num_bytes: 60460164
num_examples: 42018
download_size: 25338925
dataset_size: 60460164
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
nirantk/nli-triplets | ---
dataset_info:
features:
- name: anchor
dtype: string
- name: entailment
dtype: string
- name: contradiction
dtype: string
- name: metadata
struct:
- name: objective
struct:
- name: paired
sequence:
sequence: string
- name: self
sequence: 'null'
- name: triplet
sequence:
sequence: string
- name: topic
dtype: string
splits:
- name: train
num_bytes: 79858702
num_examples: 277122
download_size: 31073286
dataset_size: 79858702
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
AdapterOcean/data-standardized_cluster_24 | ---
dataset_info:
features:
- name: text
dtype: string
- name: conversation_id
dtype: int64
- name: embedding
sequence: float64
- name: cluster
dtype: int64
splits:
- name: train
num_bytes: 87435740
num_examples: 8434
download_size: 25087384
dataset_size: 87435740
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "data-standardized_cluster_24"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
mbeaty2/exoplanet-data | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': data_huggingface
- name: text
dtype: string
splits:
- name: train
num_bytes: 2965375.0
num_examples: 127
download_size: 1537208
dataset_size: 2965375.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "exoplanet-data"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
bigscience-data/roots_en_royal_society_corpus | ---
language: en
license: cc-by-nc-sa-4.0
extra_gated_prompt: 'By accessing this dataset, you agree to abide by the BigScience
Ethical Charter. The charter can be found at:
https://hf.co/spaces/bigscience/ethical-charter'
extra_gated_fields:
I have read and agree to abide by the BigScience Ethical Charter: checkbox
---
ROOTS Subset: roots_en_royal_society_corpus
# Royal Society Corpus
- Dataset uid: `royal_society_corpus`
### Description
The Royal Society Corpus (RSC) 6.0 Open is based on the first centuries of the Philosophical Transactions of the Royal Society of London from its beginning in 1665 to 1920. It includes all publications of the journal written in English and containing running text. The Philosophical Transactions was the first periodical of scientific writing in England. Founded in 1665 by Henry Oldenburg, the first secretary of the Royal Society, it initially contained excerpts of letters of his scientific correspondence, reviews and summaries of recently-published books, and accounts of observations and experiments.
### Homepage
https://fedora.clarin-d.uni-saarland.de/rsc_v6/index.html
### Licensing
- public domain
- cc0-1.0: Creative Commons Zero v1.0 Universal
### Speaker Locations
- Northern Europe
- United Kingdom
### Sizes
- 0.0334 % of total
- 0.1808 % of en
### BigScience processing steps
#### Filters applied to: en
- dedup_document
- dedup_template_soft
- filter_remove_empty_docs
- filter_small_docs_bytes_1024
|
wanng/wukong100m | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- zh
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
pretty_name: Wukong100M
task_categories:
- feature-extraction
---
# wukong100m
## 简介 Brief Introduction
取自Noah-Wukong多语言多模态数据集中的中文部分，一共100M个图文对。
A subset from Noah-Wukong (a multimodal dataset), around 100M image-text pairs (only Chinese).
## 数据集信息 Dataset Information
大约一共100M个中文图文对。大约占用16GB空间（仅仅是url等文本信息，不包含图片）。下载成功率在80%左右。（虽然我没有统计下载之后会占用多少空间，但是，可以说非常非常大）
- Homepage: [Noah-Wukong](https://wukong-dataset.github.io/wukong-dataset/index.html)
## 下载 Download
```bash
mkdir wukong100m && cd wukong100m
for i in {00000..00031}; do wget https://huggingface.co/datasets/wanng/wukong100m/resolve/main/data/train-$i-of-00032.parquet; done
cd ..
```
## Lisence
CC BY-NC-SA 4.0
|
nglaura/scielo-summarization | ---
license: apache-2.0
task_categories:
- summarization
language:
- fr
pretty_name: SciELO
---
# LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization
A collaboration between [reciTAL](https://recital.ai/en/), [MLIA](https://mlia.lip6.fr/) (ISIR, Sorbonne Université), [Meta AI](https://ai.facebook.com/), and [Università di Trento](https://www.unitn.it/)
## SciELO dataset for summarization
SciELO is a dataset for summarization of research papers written in Spanish and Portuguese, for which layout information is provided.
### Data Fields
- `article_id`: article id
- `article_words`: sequence of words constituting the body of the article
- `article_bboxes`: sequence of corresponding word bounding boxes
- `norm_article_bboxes`: sequence of corresponding normalized word bounding boxes
- `abstract`: a string containing the abstract of the article
- `article_pdf_url`: URL of the article's PDF
### Data Splits
This dataset has 3 splits: _train_, _validation_, and _test_.
| Dataset Split | Number of Instances (ES/PT) |
| ------------- | ----------------------------|
| Train | 20,853 / 19,407 |
| Validation | 1,158 / 1,078 |
| Test | 1,159 / 1,078 |
## Citation
``` latex
@article{nguyen2023loralay,
title={LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization},
author={Nguyen, Laura and Scialom, Thomas and Piwowarski, Benjamin and Staiano, Jacopo},
journal={arXiv preprint arXiv:2301.11312},
year={2023}
}
``` |
lucasmccabe/logiqa | ---
task_categories:
- question-answering
language:
- en
pretty_name: LogiQA
size_categories:
- 1K<n<10K
paperswithcode_id: logiqa
dataset_info:
features:
- name: context
dtype: string
- name: query
dtype: string
- name: options
sequence:
dtype: string
- name: correct_option
dtype: string
splits:
- name: train
num_examples: 7376
- name: validation
num_examples: 651
- name: test
num_examples: 651
---
# Dataset Card for LogiQA
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
LogiQA is constructed from the logical comprehension problems from publically available questions of the National Civil Servants Examination of China, which are designed to test the civil servant candidates’ critical thinking and problem solving. This dataset includes the English versions only; the Chinese versions are available via the homepage/original source.
## Dataset Structure
### Data Instances
An example from `train` looks as follows:
```
{'context': 'Continuous exposure to indoor fluorescent lights is beneficial to the health of hamsters with heart disease. One group of hamsters exposed to continuous exposure to fluorescent lights has an average lifespan that is 2.5% longer than another one of the same species but living in a black wall.',
'query': 'Which of the following questions was the initial motivation for conducting the above experiment?',
'options': ['Can hospital light therapy be proved to promote patient recovery?',
'Which one lives longer, the hamster living under the light or the hamster living in the dark?',
'What kind of illness does the hamster have?',
'Do some hamsters need a period of darkness?'],
'correct_option': 0}
```
### Data Fields
- `context`: a `string` feature.
- `query`: a `string` feature.
- `answers`: a `list` feature containing `string` features.
- `correct_option`: a `string` feature.
### Data Splits
|train|validation|test|
|----:|---------:|---:|
| 7376| 651| 651|
## Additional Information
### Dataset Curators
The original LogiQA was produced by Jian Liu, Leyang Cui , Hanmeng Liu, Dandan Huang, Yile Wang, and Yue Zhang.
### Licensing Information
[More Information Needed]
### Citation Information
```
@article{liu2020logiqa,
title={Logiqa: A challenge dataset for machine reading comprehension with logical reasoning},
author={Liu, Jian and Cui, Leyang and Liu, Hanmeng and Huang, Dandan and Wang, Yile and Zhang, Yue},
journal={arXiv preprint arXiv:2007.08124},
year={2020}
}
```
### Contributions
[@lucasmccabe](https://github.com/lucasmccabe) added this dataset. |
ibranze/araproje_hellaswag_en_conf_mgpt_nearestscore_true_y | ---
dataset_info:
features:
- name: ind
dtype: int32
- name: activity_label
dtype: string
- name: ctx_a
dtype: string
- name: ctx_b
dtype: string
- name: ctx
dtype: string
- name: endings
sequence: string
- name: source_id
dtype: string
- name: split
dtype: string
- name: split_type
dtype: string
- name: label
dtype: string
splits:
- name: validation
num_bytes: 149738.0
num_examples: 250
download_size: 81214
dataset_size: 149738.0
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
---
# Dataset Card for "araproje_hellaswag_en_conf_mgpt_nearestscore_true_y"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
jjonhwa/raw3_v1 | ---
dataset_info:
features:
- name: context
dtype: string
- name: is_impossible
dtype: bool
- name: question
dtype: string
- name: answer
dtype: string
- name: answer_start
dtype: int64
splits:
- name: train
num_bytes: 131956852
num_examples: 51888
download_size: 41299212
dataset_size: 131956852
---
# Dataset Card for "raw3_v1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Hiltoon/gabriel | ---
license: openrail
---
|
jeremyc/Alpaca-Lora-GPT4-Swedish | ---
language:
- sv
pretty_name: Alpaca-Lora GPT4 Swedish
size_categories:
- 10K<n<100K
---
This dataset is the machine translation of the GPT4 dataset provided on Alpaca-Lora github repository.
We provide two version: The full translation, and a translation of a subset of ~50 000 entries that was cleaned and do not contain instances of "I am an AI language model" or similar.
This work was inspired from the French alpaca lora variant **Vigogne** and the Ukrainian alpaca lora variante **Kruk**. |
Rogashbabu/Training-Bert-Model-Analysis | ---
license: other
task_categories:
- text-classification
language:
- en
--- |
feilongfl/ChineseNewsSummary | ---
license: apache-2.0
---
generate by chatgpt3.5 with prompt:
``` text
你是一个用于整理新闻的AI助手，请根据分割线后爬虫在{{ $json.isoDate }}爬取的新闻，使用简体中文按照包含：title，summary，class，time四个节点的json格式输出结果。
title字段：请为新闻起一个30到60个字的简体中文标题。应当是包含上下文简洁说明的结论性内容的陈述句，词汇简单，信息全面。
class：请分类为：财经、汽车、房产、家居、教育、科技、社会、时政、体育、游戏、娱乐等。
time字段：如果新闻中有提供时间，请使用新闻中的时间；否则使用爬虫时间。时间应当以年/月/日格式输出，例如：2024/1/16。
summary字段：应当用100字以内简单的简体中文陈述已经发生的事实，着重于结论和支撑结论的数据，不要假设和预测，不要重复标题。请过滤原文中可能包含的问题或反问、猜测/情绪化表达、政治口号、联系方式、股票代码或广告词。如果原文有晦涩或不常见的词汇或多重否定，请换用简单的词语进行描述。
---
{{ $json.contentSnippet }}
```
|
mike-ravkine/can-ai-code_junior-dev_v1 | ---
language:
- en
---
First version of the [can-ai-code](https://github.com/the-crypt-keeper/can-ai-code/) junior-dev interview. |
Cheetor1996/Sayoko_Kagami | ---
license: cc-by-2.0
language:
- en
tags:
- art
---
**Sayoko Kagami** from Helter Skelter Hakudaku no Mura
- *Trained with anime (full-final-pruned) model*
- *Works the best with ALL, MIDD, OUTD, and OUTALL LoRA weight block, and with 0.5+ weights.* |
pkr7098/gpt2-small-bookcorpus-wiki-2022030-en-vocab_size-32000 | ---
dataset_info:
config_name: truncate-1024
features:
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: special_tokens_mask
sequence: int8
splits:
- name: train
num_bytes: 22599642492
num_examples: 3671157
- name: validation
num_bytes: 397295928
num_examples: 64538
download_size: 0
dataset_size: 22996938420
configs:
- config_name: truncate-1024
data_files:
- split: train
path: truncate-1024/train-*
- split: validation
path: truncate-1024/validation-*
---
# Dataset Card for "gpt2-small-bookcorpus-wiki-2022030-en-vocab_size-32000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
yuvalkirstain/pexel | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 653318190.0
num_examples: 1560
- name: validation
num_bytes: 7122908.0
num_examples: 20
download_size: 653521442
dataset_size: 660441098.0
---
# Dataset Card for "pexel"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Femur19899079/Fat | ---
license: lgpl-3.0
---
|
ashutosh09/samplecoredge | ---
license: mit
---
|
open-llm-leaderboard/details_Sao10K__Stheno-1.8-L2-13B | ---
pretty_name: Evaluation run of Sao10K/Stheno-1.8-L2-13B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Sao10K/Stheno-1.8-L2-13B](https://huggingface.co/Sao10K/Stheno-1.8-L2-13B) 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_Sao10K__Stheno-1.8-L2-13B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-29T00:06:59.711419](https://huggingface.co/datasets/open-llm-leaderboard/details_Sao10K__Stheno-1.8-L2-13B/blob/main/results_2023-10-29T00-06-59.711419.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\": 0.06564597315436242,\n\
\ \"em_stderr\": 0.002536293026031132,\n \"f1\": 0.15330012583892566,\n\
\ \"f1_stderr\": 0.0029061084519907457,\n \"acc\": 0.44834287054661603,\n\
\ \"acc_stderr\": 0.01063887899085892\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.06564597315436242,\n \"em_stderr\": 0.002536293026031132,\n\
\ \"f1\": 0.15330012583892566,\n \"f1_stderr\": 0.0029061084519907457\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.1326762699014405,\n \
\ \"acc_stderr\": 0.009343929131442216\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7640094711917916,\n \"acc_stderr\": 0.011933828850275625\n\
\ }\n}\n```"
repo_url: https://huggingface.co/Sao10K/Stheno-1.8-L2-13B
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_10_04T00_45_37.800224
path:
- '**/details_harness|arc:challenge|25_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_29T00_06_59.711419
path:
- '**/details_harness|drop|3_2023-10-29T00-06-59.711419.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-29T00-06-59.711419.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_29T00_06_59.711419
path:
- '**/details_harness|gsm8k|5_2023-10-29T00-06-59.711419.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-29T00-06-59.711419.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hellaswag|10_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T00-45-37.800224.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-04T00-45-37.800224.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-04T00-45-37.800224.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_29T00_06_59.711419
path:
- '**/details_harness|winogrande|5_2023-10-29T00-06-59.711419.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-29T00-06-59.711419.parquet'
- config_name: results
data_files:
- split: 2023_10_04T00_45_37.800224
path:
- results_2023-10-04T00-45-37.800224.parquet
- split: 2023_10_29T00_06_59.711419
path:
- results_2023-10-29T00-06-59.711419.parquet
- split: latest
path:
- results_2023-10-29T00-06-59.711419.parquet
---
# Dataset Card for Evaluation run of Sao10K/Stheno-1.8-L2-13B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Sao10K/Stheno-1.8-L2-13B
- **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 [Sao10K/Stheno-1.8-L2-13B](https://huggingface.co/Sao10K/Stheno-1.8-L2-13B) 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_Sao10K__Stheno-1.8-L2-13B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-29T00:06:59.711419](https://huggingface.co/datasets/open-llm-leaderboard/details_Sao10K__Stheno-1.8-L2-13B/blob/main/results_2023-10-29T00-06-59.711419.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": 0.06564597315436242,
"em_stderr": 0.002536293026031132,
"f1": 0.15330012583892566,
"f1_stderr": 0.0029061084519907457,
"acc": 0.44834287054661603,
"acc_stderr": 0.01063887899085892
},
"harness|drop|3": {
"em": 0.06564597315436242,
"em_stderr": 0.002536293026031132,
"f1": 0.15330012583892566,
"f1_stderr": 0.0029061084519907457
},
"harness|gsm8k|5": {
"acc": 0.1326762699014405,
"acc_stderr": 0.009343929131442216
},
"harness|winogrande|5": {
"acc": 0.7640094711917916,
"acc_stderr": 0.011933828850275625
}
}
```
### 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] |
CyberHarem/aihara_yuzu_citrus | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of Aihara Yuzu
This is the dataset of Aihara Yuzu, 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 | 691 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. |
| raw-stage3-eyes | 891 | [Download](dataset-raw-stage3-eyes.zip) | 3-stage cropped (with eye-focus) raw data with meta information. |
| 384x512 | 300 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. |
| 512x704 | 300 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. |
| 640x880 | 300 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. |
| stage3-640 | 691 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. |
| stage3-800 | 691 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. |
| stage3-p512-640 | 599 | [Download](dataset-stage3-p512-640.zip) | 3-stage cropped dataset with the area not less than 512x512 pixels. |
| stage3-eyes-640 | 891 | [Download](dataset-stage3-eyes-640.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 640 pixels. |
| stage3-eyes-800 | 891 | [Download](dataset-stage3-eyes-800.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 800 pixels. |
|
chekahchek/ai6127-ghostbuster | ---
dataset_info:
features:
- name: texts
dtype: string
- name: labels
dtype: string
- name: domains
dtype: string
splits:
- name: train
num_bytes: 13188360
num_examples: 3837
- name: val
num_bytes: 3251702
num_examples: 963
- name: test
num_bytes: 4093967
num_examples: 1200
download_size: 11526069
dataset_size: 20534029
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
---
|
Shamus/Medical_Speech_Transcription_and_Intent | ---
language:
- en
size_categories:
- 1K<n<10K
---
This dataset came from Kaggle and was contributed by Paul Mooney.
https://www.kaggle.com/datasets/paultimothymooney/medical-speech-transcription-and-intent/data
Context
8.5 hours of audio utterances paired with text for common medical symptoms.
Content
This data contains thousands of audio utterances for common medical symptoms like “knee pain” or “headache,” totaling more than 8 hours in aggregate. Each utterance was created by individual human contributors based on a given symptom. These audio snippets can be used to train conversational agents in the medical field.
This Figure Eight dataset was created via a multi-job workflow. The first involved contributors writing text phrases to describe symptoms given. For example, for “headache,” a contributor might write “I need help with my migraines.” Subsequent jobs captured audio utterances for accepted text strings.
Note that some of the labels are incorrect and some of the audio files have poor quality. I would recommend cleaning the dataset before training any machine learning models.
This dataset contains both the audio utterances and corresponding transcriptions.
Acknowledgements
This dataset was developed by figure-eight and can be downloaded from https://www.figure-eight.com/dataset/audio-recording-and-transcription-for-medical-scenarios/ along with instructions on how to make similar datasets using the figure-eight platform.
https://www.figure-eight.com/dataset/audio-recording-and-transcription-for-medical-scenarios/
Banner Photo by rawpixel on Unsplash |
japanese-asr/whisper_transcriptions.reazonspeech.all_35 | ---
dataset_info:
config_name: all
features:
- name: name
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: transcription
dtype: string
- name: whisper_transcript
sequence: int64
splits:
- name: train
num_bytes: 30456979591.0
num_examples: 267182
download_size: 30215181472
dataset_size: 30456979591.0
configs:
- config_name: all
data_files:
- split: train
path: all/train-*
---
|
UserNae3/FLIR_aligned | ---
license: other
license_name: other
license_link: https://www.flir.com/oem/adas/adas-dataset-form/
---
# 对齐的 FLIR 数据集
[[中文](README.md)] [[English](README_en.md)]
FLIR 数据集由 FLIR 公司发布，双光谱目标检测数据集一般是使用来自 Zhang等人的修改的版本[Paper](https://arxiv.org/abs/2009.12664), [Dataset](https://drive.google.com/file/d/1xHDMGl6HJZwtarNWkEV3T4O9X4ZQYz2Y/view)
> 这里存储了[[张等人对齐的FLIR数据集](https://arxiv.org/abs/2009.12664)]的备份 和 其 [[转换成COCO标注格式的数据集](https://huggingface.co/datasets/UserNae3/FLIR_aligned/resolve/main/flir_align.7z)]
**下载**
- 【推荐】转换成的COCO标注格式：https://huggingface.co/datasets/UserNae3/FLIR_aligned/resolve/main/flir_align.7z?download=true
- Zhang等人原始发布下载：https://drive.google.com/file/d/1xHDMGl6HJZwtarNWkEV3T4O9X4ZQYz2Y/view
- 对Zhang等人发布的备份：https://huggingface.co/datasets/UserNae3/FLIR_aligned/resolve/main/aligned.zip?download=true
**版权**
版权链接: https://www.flir.com/oem/adas/adas-dataset-form/ |
LCA-PORVID/delexicalized_n_grams | ---
dataset_info:
- config_name: journalistic
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 201756790
num_examples: 615012
download_size: 123762232
dataset_size: 201756790
- config_name: legal
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 1215937
num_examples: 7440
download_size: 687763
dataset_size: 1215937
- config_name: literature
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 8812642
num_examples: 40878
download_size: 5541660
dataset_size: 8812642
- config_name: politics
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 4082098
num_examples: 5778
download_size: 2340087
dataset_size: 4082098
- config_name: social_media
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 564540
num_examples: 8246
download_size: 340777
dataset_size: 564540
- config_name: web
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 85208776
num_examples: 79318
download_size: 49328021
dataset_size: 85208776
configs:
- config_name: journalistic
data_files:
- split: train
path: journalistic/train-*
- config_name: legal
data_files:
- split: train
path: legal/train-*
- config_name: literature
data_files:
- split: train
path: literature/train-*
- config_name: politics
data_files:
- split: train
path: politics/train-*
- config_name: social_media
data_files:
- split: train
path: social_media/train-*
- config_name: web
data_files:
- split: train
path: web/train-*
---
|
varcoder/Semantic_Segmentation_CE | ---
dataset_info:
features:
- name: pixel_values
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 27784142.0
num_examples: 300
- name: test
num_bytes: 90363667.0
num_examples: 237
download_size: 0
dataset_size: 118147809.0
---
# Dataset Card for "Semantic_Segmentation_CE"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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