datasetId stringlengths 2 117 | card stringlengths 19 1.01M |
|---|---|
naorm/dnrti-securebert-ner-512 | ---
dataset_info:
features:
- name: Type
dtype: string
- name: Text
dtype: string
- name: Score
dtype: float64
- name: Original Sentence ID
dtype: int64
- name: Original Sentence
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 19414191
num_examples: 12157
download_size: 941665
dataset_size: 19414191
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
autoevaluate/autoeval-eval-samsum-samsum-e12e62-68887145629 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- samsum
eval_info:
task: summarization
model: d0rj/rut5-base-summ
metrics: []
dataset_name: samsum
dataset_config: samsum
dataset_split: test
col_mapping:
text: dialogue
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: d0rj/rut5-base-summ
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@d0rj](https://huggingface.co/d0rj) for evaluating this model. |
it-at-m/LHM-Dienstleistungen-Corpus | ---
license: mit
language:
- de
tags:
- Stadt München
- Bürgerbüro
- Behördendeutsch
- Corpus
viewer: false
task_categories:
- feature-extraction
- text-generation
pretty_name: 'LHM Dienstleistungen: Corpus'
size_categories:
- n<1K
---
# LHM-Dienstleistungen-corpus- german public domain texts
Datasets created based on data from Munich city administration.
## Data basis
Texts taken from the “Dienstleistungsfinder“ of the city of Munich administration.
There information about services offered by city is presented online.
Information ranges from applying for an ID card to dispose of garbage.
- https://stadt.muenchen.de/service/ (Date 11/2022) |
autoevaluate/autoeval-staging-eval-project-sasha__dog-food-8a6c4abe-13775900 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- sasha/dog-food
eval_info:
task: image_binary_classification
model: sasha/dog-food-vit-base-patch16-224-in21k
metrics: ['matthews_correlation']
dataset_name: sasha/dog-food
dataset_config: sasha--dog-food
dataset_split: train
col_mapping:
image: image
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Image Classification
* Model: sasha/dog-food-vit-base-patch16-224-in21k
* Dataset: sasha/dog-food
* Config: sasha--dog-food
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@ahmetgunduz](https://huggingface.co/ahmetgunduz) for evaluating this model. |
Samuelcr8/Eva | ---
license: afl-3.0
task_categories:
- question-answering
language:
- aa
tags:
- biology
size_categories:
- n<1K
---
https://huggingface.c.o/datasets/Samuelcr8/Eva |
open-llm-leaderboard/details_Writer__camel-5b-hf | ---
pretty_name: Evaluation run of Writer/camel-5b-hf
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Writer/camel-5b-hf](https://huggingface.co/Writer/camel-5b-hf) 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_Writer__camel-5b-hf\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-18T14:36:32.116490](https://huggingface.co/datasets/open-llm-leaderboard/details_Writer__camel-5b-hf/blob/main/results_2023-10-18T14-36-32.116490.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\": 0.08294882550335571,\n\
\ \"em_stderr\": 0.0028244998601496944,\n \"f1\": 0.14997168624161072,\n\
\ \"f1_stderr\": 0.003145718068946184,\n \"acc\": 0.3069466775731776,\n\
\ \"acc_stderr\": 0.007700124028579334\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.08294882550335571,\n \"em_stderr\": 0.0028244998601496944,\n\
\ \"f1\": 0.14997168624161072,\n \"f1_stderr\": 0.003145718068946184\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0037907505686125853,\n \
\ \"acc_stderr\": 0.0016927007401502051\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6101026045777427,\n \"acc_stderr\": 0.013707547317008463\n\
\ }\n}\n```"
repo_url: https://huggingface.co/Writer/camel-5b-hf
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|arc:challenge|25_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_18T14_36_32.116490
path:
- '**/details_harness|drop|3_2023-10-18T14-36-32.116490.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-18T14-36-32.116490.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_18T14_36_32.116490
path:
- '**/details_harness|gsm8k|5_2023-10-18T14-36-32.116490.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-18T14-36-32.116490.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hellaswag|10_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:25:02.904083.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T15:25:02.904083.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T15:25:02.904083.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_18T14_36_32.116490
path:
- '**/details_harness|winogrande|5_2023-10-18T14-36-32.116490.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-18T14-36-32.116490.parquet'
- config_name: results
data_files:
- split: 2023_07_19T15_25_02.904083
path:
- results_2023-07-19T15:25:02.904083.parquet
- split: 2023_10_18T14_36_32.116490
path:
- results_2023-10-18T14-36-32.116490.parquet
- split: latest
path:
- results_2023-10-18T14-36-32.116490.parquet
---
# Dataset Card for Evaluation run of Writer/camel-5b-hf
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Writer/camel-5b-hf
- **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 [Writer/camel-5b-hf](https://huggingface.co/Writer/camel-5b-hf) 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_Writer__camel-5b-hf",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-18T14:36:32.116490](https://huggingface.co/datasets/open-llm-leaderboard/details_Writer__camel-5b-hf/blob/main/results_2023-10-18T14-36-32.116490.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": 0.08294882550335571,
"em_stderr": 0.0028244998601496944,
"f1": 0.14997168624161072,
"f1_stderr": 0.003145718068946184,
"acc": 0.3069466775731776,
"acc_stderr": 0.007700124028579334
},
"harness|drop|3": {
"em": 0.08294882550335571,
"em_stderr": 0.0028244998601496944,
"f1": 0.14997168624161072,
"f1_stderr": 0.003145718068946184
},
"harness|gsm8k|5": {
"acc": 0.0037907505686125853,
"acc_stderr": 0.0016927007401502051
},
"harness|winogrande|5": {
"acc": 0.6101026045777427,
"acc_stderr": 0.013707547317008463
}
}
```
### 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] |
maghwa/OpenHermes-2-AR-10K-51-990k-1m | ---
dataset_info:
features:
- name: category
dtype: 'null'
- name: conversations
dtype: string
- name: custom_instruction
dtype: 'null'
- name: hash
dtype: 'null'
- name: language
dtype: 'null'
- name: skip_prompt_formatting
dtype: 'null'
- name: avatarUrl
dtype: 'null'
- name: model_name
dtype: 'null'
- name: idx
dtype: string
- name: id
dtype: 'null'
- name: title
dtype: 'null'
- name: topic
dtype: 'null'
- name: model
dtype: 'null'
- name: views
dtype: float64
- name: system_prompt
dtype: 'null'
- name: source
dtype: string
splits:
- name: train
num_bytes: 40444836
num_examples: 10001
download_size: 16962745
dataset_size: 40444836
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Noaman/midv500 | ---
license: mit
dataset_info:
features:
- name: image
dtype: image
- name: annotation
dtype: image
splits:
- name: train
num_bytes: 907326062.0
num_examples: 300
download_size: 802086357
dataset_size: 907326062.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
athirdpath/Merge_Glue | ---
license: cc-by-nc-4.0
language:
- en
---
### Dataset
The glue consists of a roughly even three-way split between:
- The entirety of HF No Robots.
- The entirety of TinyPixel/orca-mini
- Part of the Alpaca dataset (randomly chosen) |
robotflow/vr-folding | ---
license: mit
pretty_name: garment-tracking
---
# Dataset Card for VR-Folding Dataset
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
- [Dataset Example](#dataset-example)
## Dataset Description
- **Homepage:** https://garment-tracking.robotflow.ai
- **Repository:** [GitHub](https://github.com/xiaoxiaoxh/GarmentTracking)
- **Paper:** [GarmentTracking: Category-Level Garment Pose Tracking](https://arxiv.org/pdf/2303.13913.pdf)
- **Point of Contact:**
## Dataset Summary
This is the **VR-Folding** dataset created by the CVPR 2023 paper [GarmentTracking: Category-Level Garment Pose Tracking](https://garment-tracking.robotflow.ai).
This dataset is recorded with a system called [VR-Garment](https://github.com/xiaoxiaoxh/VR-Garment), which is a garment-hand interaction environment based on Unity.
To download the dataset, use the following shell snippet:
```
git lfs install
git clone https://huggingface.co/datasets/robotflow/garment-tracking
# if you want to clone without large files – just their pointers
# prepend your git clone with the following env var: GIT_LFS_SKIP_SMUDGE=1
# merge multiple .zip files (e.g. folding) into one .zip file
cd data/folding
cat folding_dataset.z* > folding_dataset.zip
# unzip
unzip folding_dataset.zip
```
All the data are stored in [zarr](https://zarr.readthedocs.io/en/stable/) format.
## Dataset Structure
Here is the detailed stucture of a data example ([zarr](https://zarr.readthedocs.io/en/stable/) format) of one frame:
```
00068_Tshirt_000000_000000
├── grip_vertex_id
│ ├── left_grip_vertex_id (1,) int32
│ └── right_grip_vertex_id (1,) int32
├── hand_pose
│ ├── left_hand_euler (25, 3) float32
│ ├── left_hand_pos (25, 3) float32
│ ├── right_hand_euler (25, 3) float32
│ └── right_hand_pos (25, 3) float32
├── marching_cube_mesh
│ ├── is_vertex_on_surface (6410,) bool
│ ├── marching_cube_faces (12816, 3) int32
│ └── marching_cube_verts (6410, 3) float32
├── mesh
│ ├── cloth_faces_tri (8312, 3) int32
│ ├── cloth_nocs_verts (4434, 3) float32
│ └── cloth_verts (4434, 3) float32
└── point_cloud
├── cls (30000,) uint8
├── nocs (30000, 3) float16
├── point (30000, 3) float16
├── rgb (30000, 3) uint8
└── sizes (4,) int64
```
Specifically, we render 4-view RGB-D images with Unity and generate concated point clouds for each frame. Here `grip_vertex_id` is the vertex index list of the grasped points of the mesh.
# Dataset Example
Please see [example](data/data_examples/README.md) for example data and visualization scripts.
Here are two video examples for flattening and folding task.
|
goatman/metahuman-gaze-prediction | ---
license: apache-2.0
---
#Extract and normalize the coordinates (dodgy version for testing)
def get_coords_metahuman(file: Path):
im_id, character, xcoord, ycoord, xsize, ysize = file.name.split('.jpg')[:-1][0].split('_')
xcoord, ycoord, xsize, ysize = float(xcoord), float(ycoord), float(xsize), float(ysize)
base_screensize = tensor([46.49, 26.15]) # generic width and height measurement in cms given by gpt4 as a likely mean screen size
normalized_screensize = tensor([xsize, ysize])/base_screensize
x = (xcoord)/xsize
y = (ycoord)/ysize
# normalize to range -0.5, 0.5
return tensor([x, y])
|
diversoailab/humaneval-rust | ---
license: mit
language:
- code
task_categories:
- text-generation
pretty_name: Humaneval-rust
size_categories:
- n<1K
multilinguality:
- monolingual
language_creators:
- expert-generated
--- |
jan-hq/h4_no_robots_binarized | ---
dataset_info:
features:
- name: messages
list:
- name: content
dtype: string
- name: role
dtype: string
splits:
- name: train
num_bytes: 12000998
num_examples: 9500
- name: test
num_bytes: 641760
num_examples: 500
download_size: 7765070
dataset_size: 12642758
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# Dataset Card for "h4_no_robots_binarized"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
AdapterOcean/med_alpaca_standardized_cluster_33_alpaca | ---
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 14965772
num_examples: 10637
download_size: 7502391
dataset_size: 14965772
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "med_alpaca_standardized_cluster_33_alpaca"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
msy78/newDatasets | ---
dataset_info:
features:
- name: image
dtype: image
- name: conditioning
dtype: image
- name: caption
dtype: string
splits:
- name: train
num_bytes: 427764.0
num_examples: 1
download_size: 430447
dataset_size: 427764.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
deepklarity/top-npm-packages | ---
license: cc
---
**Top NPM Packages Dataset**
This dataset contains a snapshot of Top 3000 popular node packages hosted on [Node Package Manager](https://www.npmjs.com/)
The dataset was scraped in `July-2022`. This includes a combination of data gathered by [Libraries.io](https://libraries.io/) and [npm](https://www.npmjs.com/)
We aim to use this dataset to perform analysis and identify trends and get a bird's eye view of nodejs ecosystem.
#### Mantainers:
- [Keshaw Soni](https://twitter.com/SoniKeshaw)
- [Somya Gautam](http://linkedin.in/in/somya-gautam)
- [Kondrolla Dinesh Reddy](https://twitter.com/KondrollaR)
|
CyberHarem/mizuho_kantaicollection | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of mizuho/瑞穂/瑞穂 (Kantai Collection)
This is the dataset of mizuho/瑞穂/瑞穂 (Kantai Collection), containing 224 images and their tags.
The core tags of this character are `long_hair, black_hair, ribbon, very_long_hair, hair_ribbon, hair_ornament, sidelocks, breasts, green_eyes`, 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 | 224 | 198.36 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mizuho_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 224 | 138.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mizuho_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 443 | 248.65 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mizuho_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 224 | 186.40 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mizuho_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 443 | 312.46 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mizuho_kantaicollection/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/mizuho_kantaicollection',
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 | 10 |  |  |  |  |  | 1girl, hair_tubes, solo, cleavage, navel, smile, looking_at_viewer, medium_breasts, cowboy_shot, green_bikini, open_mouth, simple_background, white_background, blush, collarbone, grey_eyes |
| 1 | 6 |  |  |  |  |  | 1girl, blush, hair_tubes, solo, furisode, green_kimono, looking_at_viewer, obi, twitter_username, white_background, ahoge, simple_background, smile, wide_sleeves |
| 2 | 10 |  |  |  |  |  | 1girl, detached_sleeves, hair_tubes, solo, smile, bare_shoulders, japanese_clothes, looking_at_viewer, green_dress |
| 3 | 5 |  |  |  |  |  | 1girl, detached_sleeves, green_dress, hair_tubes, looking_at_viewer, smile, solo, grey_eyes, japanese_clothes, simple_background, upper_body, white_background, bare_shoulders, bridal_gauntlets |
| 4 | 8 |  |  |  |  |  | 1girl, hair_tubes, navel, solo, underwear_only, cleavage, looking_at_viewer, medium_breasts, white_bra, white_panties, blush, cowboy_shot, simple_background, bow, large_breasts, low-tied_long_hair, white_background, collarbone, one-hour_drawing_challenge, open_mouth, side-tie_panties, twitter_username |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | hair_tubes | solo | cleavage | navel | smile | looking_at_viewer | medium_breasts | cowboy_shot | green_bikini | open_mouth | simple_background | white_background | blush | collarbone | grey_eyes | furisode | green_kimono | obi | twitter_username | ahoge | wide_sleeves | detached_sleeves | bare_shoulders | japanese_clothes | green_dress | upper_body | bridal_gauntlets | underwear_only | white_bra | white_panties | bow | large_breasts | low-tied_long_hair | one-hour_drawing_challenge | side-tie_panties |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------------|:-------|:-----------|:--------|:--------|:--------------------|:-----------------|:--------------|:---------------|:-------------|:--------------------|:-------------------|:--------|:-------------|:------------|:-----------|:---------------|:------|:-------------------|:--------|:---------------|:-------------------|:-----------------|:-------------------|:--------------|:-------------|:-------------------|:-----------------|:------------|:----------------|:------|:----------------|:---------------------|:-----------------------------|:-------------------|
| 0 | 10 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | |
| 1 | 6 |  |  |  |  |  | X | X | X | | | X | X | | | | | X | X | X | | | X | X | X | X | X | X | | | | | | | | | | | | | | |
| 2 | 10 |  |  |  |  |  | X | X | X | | | X | X | | | | | | | | | | | | | | | | X | X | X | X | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | X | X | | | X | X | | | | | X | X | | | X | | | | | | | X | X | X | X | X | X | | | | | | | | |
| 4 | 8 |  |  |  |  |  | X | X | X | X | X | | X | X | X | | X | X | X | X | X | | | | | X | | | | | | | | | X | X | X | X | X | X | X | X |
|
MartinKu/wikipedia_OC | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 11476303825
num_examples: 161961924
download_size: 7119631815
dataset_size: 11476303825
---
# Dataset Card for "wikipedia_OC"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Klimentiy/processed_demo | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: id
dtype: string
- name: package_name
dtype: string
- name: review
dtype: string
- name: date
dtype: string
- name: star
dtype: int64
- name: version_id
dtype: int64
splits:
- name: train
num_bytes: 1508
num_examples: 5
- name: test
num_bytes: 956
num_examples: 5
download_size: 9453
dataset_size: 2464
---
# Dataset Card for "processed_demo"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
autoevaluate/autoeval-staging-eval-xsum-default-6f5db0-14615984 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- xsum
eval_info:
task: summarization
model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP13
metrics: []
dataset_name: xsum
dataset_config: default
dataset_split: test
col_mapping:
text: document
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP13
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@pszemraj](https://huggingface.co/pszemraj) for evaluating this model. |
Simonk97/ungquachung | ---
license: openrail
---
|
AdapterOcean/med_alpaca_standardized_cluster_56_std | ---
dataset_info:
features:
- name: message
dtype: string
- name: message_type
dtype: string
- name: message_id
dtype: int64
- name: conversation_id
dtype: int64
- name: cluster
dtype: float64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 33084943
num_examples: 51414
download_size: 16280365
dataset_size: 33084943
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "med_alpaca_standardized_cluster_56_std"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
qgiaohc/twitter_dataset_1713146026 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 22679
num_examples: 50
download_size: 12386
dataset_size: 22679
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
masud99r/bean_test | ---
license: mit
---
|
open-llm-leaderboard/details_zhengr__MixTAO-7Bx2-MoE-Instruct-v1.0 | ---
pretty_name: Evaluation run of zhengr/MixTAO-7Bx2-MoE-Instruct-v1.0
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [zhengr/MixTAO-7Bx2-MoE-Instruct-v1.0](https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-Instruct-v1.0)\
\ 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_zhengr__MixTAO-7Bx2-MoE-Instruct-v1.0\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-17T20:51:00.181001](https://huggingface.co/datasets/open-llm-leaderboard/details_zhengr__MixTAO-7Bx2-MoE-Instruct-v1.0/blob/main/results_2024-01-17T20-51-00.181001.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\": 0.6491690289461749,\n\
\ \"acc_stderr\": 0.03225689205861614,\n \"acc_norm\": 0.6482560818309024,\n\
\ \"acc_norm_stderr\": 0.03293476544167865,\n \"mc1\": 0.5789473684210527,\n\
\ \"mc1_stderr\": 0.017283936248136476,\n \"mc2\": 0.6961261081361256,\n\
\ \"mc2_stderr\": 0.015300239859443631\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.7184300341296929,\n \"acc_stderr\": 0.013143376735009022,\n\
\ \"acc_norm\": 0.7406143344709898,\n \"acc_norm_stderr\": 0.012808273573927106\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7194781915952997,\n\
\ \"acc_stderr\": 0.004483360370140576,\n \"acc_norm\": 0.8824935271858195,\n\
\ \"acc_norm_stderr\": 0.0032136470410029485\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\
\ \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6518518518518519,\n\
\ \"acc_stderr\": 0.041153246103369526,\n \"acc_norm\": 0.6518518518518519,\n\
\ \"acc_norm_stderr\": 0.041153246103369526\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6776315789473685,\n \"acc_stderr\": 0.03803510248351585,\n\
\ \"acc_norm\": 0.6776315789473685,\n \"acc_norm_stderr\": 0.03803510248351585\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.66,\n\
\ \"acc_stderr\": 0.04760952285695238,\n \"acc_norm\": 0.66,\n \
\ \"acc_norm_stderr\": 0.04760952285695238\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7094339622641509,\n \"acc_stderr\": 0.027943219989337128,\n\
\ \"acc_norm\": 0.7094339622641509,\n \"acc_norm_stderr\": 0.027943219989337128\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7708333333333334,\n\
\ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\
\ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \
\ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.54,\n \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\"\
: 0.54,\n \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \
\ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6416184971098265,\n\
\ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.6416184971098265,\n\
\ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\
\ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n\
\ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5872340425531914,\n \"acc_stderr\": 0.03218471141400351,\n\
\ \"acc_norm\": 0.5872340425531914,\n \"acc_norm_stderr\": 0.03218471141400351\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5087719298245614,\n\
\ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.5087719298245614,\n\
\ \"acc_norm_stderr\": 0.04702880432049615\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370333,\n\
\ \"acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370333\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.42592592592592593,\n \"acc_stderr\": 0.025467149045469546,\n \"\
acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.025467149045469546\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\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \
\ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7774193548387097,\n\
\ \"acc_stderr\": 0.023664216671642518,\n \"acc_norm\": 0.7774193548387097,\n\
\ \"acc_norm_stderr\": 0.023664216671642518\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.47783251231527096,\n \"acc_stderr\": 0.03514528562175008,\n\
\ \"acc_norm\": 0.47783251231527096,\n \"acc_norm_stderr\": 0.03514528562175008\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\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\
\ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7777777777777778,\n \"acc_stderr\": 0.02962022787479049,\n \"\
acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.02962022787479049\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9067357512953368,\n \"acc_stderr\": 0.02098685459328974,\n\
\ \"acc_norm\": 0.9067357512953368,\n \"acc_norm_stderr\": 0.02098685459328974\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6641025641025641,\n \"acc_stderr\": 0.023946724741563973,\n\
\ \"acc_norm\": 0.6641025641025641,\n \"acc_norm_stderr\": 0.023946724741563973\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.34814814814814815,\n \"acc_stderr\": 0.029045600290616255,\n \
\ \"acc_norm\": 0.34814814814814815,\n \"acc_norm_stderr\": 0.029045600290616255\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.03086868260412162,\n \
\ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.03086868260412162\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.31125827814569534,\n \"acc_stderr\": 0.03780445850526732,\n \"\
acc_norm\": 0.31125827814569534,\n \"acc_norm_stderr\": 0.03780445850526732\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\"\
: 0.49074074074074076,\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\"\
: 0.8333333333333334,\n \"acc_stderr\": 0.026156867523931045,\n \"\
acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.026156867523931045\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7848101265822784,\n \"acc_stderr\": 0.02675082699467618,\n \
\ \"acc_norm\": 0.7848101265822784,\n \"acc_norm_stderr\": 0.02675082699467618\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\": 0.036412970813137296,\n\
\ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.036412970813137296\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.8016528925619835,\n \"acc_stderr\": 0.03640118271990946,\n \"\
acc_norm\": 0.8016528925619835,\n \"acc_norm_stderr\": 0.03640118271990946\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.75,\n\
\ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \
\ \"acc_norm_stderr\": 0.04186091791394607\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\": 0.41964285714285715,\n\
\ \"acc_stderr\": 0.046840993210771065,\n \"acc_norm\": 0.41964285714285715,\n\
\ \"acc_norm_stderr\": 0.046840993210771065\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\
\ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\
\ \"acc_stderr\": 0.021262719400406974,\n \"acc_norm\": 0.8803418803418803,\n\
\ \"acc_norm_stderr\": 0.021262719400406974\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\": 0.8199233716475096,\n\
\ \"acc_stderr\": 0.013740797258579823,\n \"acc_norm\": 0.8199233716475096,\n\
\ \"acc_norm_stderr\": 0.013740797258579823\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7427745664739884,\n \"acc_stderr\": 0.02353292543104429,\n\
\ \"acc_norm\": 0.7427745664739884,\n \"acc_norm_stderr\": 0.02353292543104429\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.423463687150838,\n\
\ \"acc_stderr\": 0.0165254258987735,\n \"acc_norm\": 0.423463687150838,\n\
\ \"acc_norm_stderr\": 0.0165254258987735\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7124183006535948,\n \"acc_stderr\": 0.02591780611714716,\n\
\ \"acc_norm\": 0.7124183006535948,\n \"acc_norm_stderr\": 0.02591780611714716\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7266881028938906,\n\
\ \"acc_stderr\": 0.025311765975426122,\n \"acc_norm\": 0.7266881028938906,\n\
\ \"acc_norm_stderr\": 0.025311765975426122\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7438271604938271,\n \"acc_stderr\": 0.0242885336377261,\n\
\ \"acc_norm\": 0.7438271604938271,\n \"acc_norm_stderr\": 0.0242885336377261\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.475177304964539,\n \"acc_stderr\": 0.029790719243829727,\n \
\ \"acc_norm\": 0.475177304964539,\n \"acc_norm_stderr\": 0.029790719243829727\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46284224250325945,\n\
\ \"acc_stderr\": 0.012734923579532067,\n \"acc_norm\": 0.46284224250325945,\n\
\ \"acc_norm_stderr\": 0.012734923579532067\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6691176470588235,\n \"acc_stderr\": 0.028582709753898445,\n\
\ \"acc_norm\": 0.6691176470588235,\n \"acc_norm_stderr\": 0.028582709753898445\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6748366013071896,\n \"acc_stderr\": 0.018950886770806315,\n \
\ \"acc_norm\": 0.6748366013071896,\n \"acc_norm_stderr\": 0.018950886770806315\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\
\ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\
\ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7387755102040816,\n \"acc_stderr\": 0.028123429335142783,\n\
\ \"acc_norm\": 0.7387755102040816,\n \"acc_norm_stderr\": 0.028123429335142783\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.835820895522388,\n\
\ \"acc_stderr\": 0.026193923544454115,\n \"acc_norm\": 0.835820895522388,\n\
\ \"acc_norm_stderr\": 0.026193923544454115\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.82,\n \"acc_stderr\": 0.038612291966536955,\n \
\ \"acc_norm\": 0.82,\n \"acc_norm_stderr\": 0.038612291966536955\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5542168674698795,\n\
\ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\
\ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.02991312723236804,\n\
\ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.02991312723236804\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5789473684210527,\n\
\ \"mc1_stderr\": 0.017283936248136476,\n \"mc2\": 0.6961261081361256,\n\
\ \"mc2_stderr\": 0.015300239859443631\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8429360694554064,\n \"acc_stderr\": 0.010226303949598484\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6944655041698257,\n \
\ \"acc_stderr\": 0.012688134076726879\n }\n}\n```"
repo_url: https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-Instruct-v1.0
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_17T20_51_00.181001
path:
- '**/details_harness|arc:challenge|25_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|gsm8k|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hellaswag|10_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-17T20-51-00.181001.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-17T20-51-00.181001.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- '**/details_harness|winogrande|5_2024-01-17T20-51-00.181001.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-17T20-51-00.181001.parquet'
- config_name: results
data_files:
- split: 2024_01_17T20_51_00.181001
path:
- results_2024-01-17T20-51-00.181001.parquet
- split: latest
path:
- results_2024-01-17T20-51-00.181001.parquet
---
# Dataset Card for Evaluation run of zhengr/MixTAO-7Bx2-MoE-Instruct-v1.0
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [zhengr/MixTAO-7Bx2-MoE-Instruct-v1.0](https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-Instruct-v1.0) 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_zhengr__MixTAO-7Bx2-MoE-Instruct-v1.0",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-17T20:51:00.181001](https://huggingface.co/datasets/open-llm-leaderboard/details_zhengr__MixTAO-7Bx2-MoE-Instruct-v1.0/blob/main/results_2024-01-17T20-51-00.181001.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": 0.6491690289461749,
"acc_stderr": 0.03225689205861614,
"acc_norm": 0.6482560818309024,
"acc_norm_stderr": 0.03293476544167865,
"mc1": 0.5789473684210527,
"mc1_stderr": 0.017283936248136476,
"mc2": 0.6961261081361256,
"mc2_stderr": 0.015300239859443631
},
"harness|arc:challenge|25": {
"acc": 0.7184300341296929,
"acc_stderr": 0.013143376735009022,
"acc_norm": 0.7406143344709898,
"acc_norm_stderr": 0.012808273573927106
},
"harness|hellaswag|10": {
"acc": 0.7194781915952997,
"acc_stderr": 0.004483360370140576,
"acc_norm": 0.8824935271858195,
"acc_norm_stderr": 0.0032136470410029485
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.35,
"acc_stderr": 0.0479372485441102,
"acc_norm": 0.35,
"acc_norm_stderr": 0.0479372485441102
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6518518518518519,
"acc_stderr": 0.041153246103369526,
"acc_norm": 0.6518518518518519,
"acc_norm_stderr": 0.041153246103369526
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6776315789473685,
"acc_stderr": 0.03803510248351585,
"acc_norm": 0.6776315789473685,
"acc_norm_stderr": 0.03803510248351585
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.66,
"acc_stderr": 0.04760952285695238,
"acc_norm": 0.66,
"acc_norm_stderr": 0.04760952285695238
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7094339622641509,
"acc_stderr": 0.027943219989337128,
"acc_norm": 0.7094339622641509,
"acc_norm_stderr": 0.027943219989337128
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7708333333333334,
"acc_stderr": 0.03514697467862388,
"acc_norm": 0.7708333333333334,
"acc_norm_stderr": 0.03514697467862388
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.48,
"acc_stderr": 0.050211673156867795,
"acc_norm": 0.48,
"acc_norm_stderr": 0.050211673156867795
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620333,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620333
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.34,
"acc_stderr": 0.04760952285695235,
"acc_norm": 0.34,
"acc_norm_stderr": 0.04760952285695235
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6416184971098265,
"acc_stderr": 0.036563436533531585,
"acc_norm": 0.6416184971098265,
"acc_norm_stderr": 0.036563436533531585
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.4019607843137255,
"acc_stderr": 0.04878608714466996,
"acc_norm": 0.4019607843137255,
"acc_norm_stderr": 0.04878608714466996
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.75,
"acc_stderr": 0.04351941398892446,
"acc_norm": 0.75,
"acc_norm_stderr": 0.04351941398892446
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5872340425531914,
"acc_stderr": 0.03218471141400351,
"acc_norm": 0.5872340425531914,
"acc_norm_stderr": 0.03218471141400351
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.5087719298245614,
"acc_stderr": 0.04702880432049615,
"acc_norm": 0.5087719298245614,
"acc_norm_stderr": 0.04702880432049615
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5724137931034483,
"acc_stderr": 0.04122737111370333,
"acc_norm": 0.5724137931034483,
"acc_norm_stderr": 0.04122737111370333
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.42592592592592593,
"acc_stderr": 0.025467149045469546,
"acc_norm": 0.42592592592592593,
"acc_norm_stderr": 0.025467149045469546
},
"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": 0.34,
"acc_stderr": 0.04760952285695235,
"acc_norm": 0.34,
"acc_norm_stderr": 0.04760952285695235
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7774193548387097,
"acc_stderr": 0.023664216671642518,
"acc_norm": 0.7774193548387097,
"acc_norm_stderr": 0.023664216671642518
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.47783251231527096,
"acc_stderr": 0.03514528562175008,
"acc_norm": 0.47783251231527096,
"acc_norm_stderr": 0.03514528562175008
},
"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": 0.7696969696969697,
"acc_stderr": 0.0328766675860349,
"acc_norm": 0.7696969696969697,
"acc_norm_stderr": 0.0328766675860349
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7777777777777778,
"acc_stderr": 0.02962022787479049,
"acc_norm": 0.7777777777777778,
"acc_norm_stderr": 0.02962022787479049
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.9067357512953368,
"acc_stderr": 0.02098685459328974,
"acc_norm": 0.9067357512953368,
"acc_norm_stderr": 0.02098685459328974
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.6641025641025641,
"acc_stderr": 0.023946724741563973,
"acc_norm": 0.6641025641025641,
"acc_norm_stderr": 0.023946724741563973
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.34814814814814815,
"acc_stderr": 0.029045600290616255,
"acc_norm": 0.34814814814814815,
"acc_norm_stderr": 0.029045600290616255
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6554621848739496,
"acc_stderr": 0.03086868260412162,
"acc_norm": 0.6554621848739496,
"acc_norm_stderr": 0.03086868260412162
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.31125827814569534,
"acc_stderr": 0.03780445850526732,
"acc_norm": 0.31125827814569534,
"acc_norm_stderr": 0.03780445850526732
},
"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": 0.49074074074074076,
"acc_stderr": 0.034093869469927006,
"acc_norm": 0.49074074074074076,
"acc_norm_stderr": 0.034093869469927006
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8333333333333334,
"acc_stderr": 0.026156867523931045,
"acc_norm": 0.8333333333333334,
"acc_norm_stderr": 0.026156867523931045
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.7848101265822784,
"acc_stderr": 0.02675082699467618,
"acc_norm": 0.7848101265822784,
"acc_norm_stderr": 0.02675082699467618
},
"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": 0.036412970813137296,
"acc_norm": 0.7786259541984732,
"acc_norm_stderr": 0.036412970813137296
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.8016528925619835,
"acc_stderr": 0.03640118271990946,
"acc_norm": 0.8016528925619835,
"acc_norm_stderr": 0.03640118271990946
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.75,
"acc_stderr": 0.04186091791394607,
"acc_norm": 0.75,
"acc_norm_stderr": 0.04186091791394607
},
"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": 0.41964285714285715,
"acc_stderr": 0.046840993210771065,
"acc_norm": 0.41964285714285715,
"acc_norm_stderr": 0.046840993210771065
},
"harness|hendrycksTest-management|5": {
"acc": 0.7864077669902912,
"acc_stderr": 0.040580420156460344,
"acc_norm": 0.7864077669902912,
"acc_norm_stderr": 0.040580420156460344
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.8803418803418803,
"acc_stderr": 0.021262719400406974,
"acc_norm": 0.8803418803418803,
"acc_norm_stderr": 0.021262719400406974
},
"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": 0.8199233716475096,
"acc_stderr": 0.013740797258579823,
"acc_norm": 0.8199233716475096,
"acc_norm_stderr": 0.013740797258579823
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.7427745664739884,
"acc_stderr": 0.02353292543104429,
"acc_norm": 0.7427745664739884,
"acc_norm_stderr": 0.02353292543104429
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.423463687150838,
"acc_stderr": 0.0165254258987735,
"acc_norm": 0.423463687150838,
"acc_norm_stderr": 0.0165254258987735
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.7124183006535948,
"acc_stderr": 0.02591780611714716,
"acc_norm": 0.7124183006535948,
"acc_norm_stderr": 0.02591780611714716
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.7266881028938906,
"acc_stderr": 0.025311765975426122,
"acc_norm": 0.7266881028938906,
"acc_norm_stderr": 0.025311765975426122
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.7438271604938271,
"acc_stderr": 0.0242885336377261,
"acc_norm": 0.7438271604938271,
"acc_norm_stderr": 0.0242885336377261
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.475177304964539,
"acc_stderr": 0.029790719243829727,
"acc_norm": 0.475177304964539,
"acc_norm_stderr": 0.029790719243829727
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.46284224250325945,
"acc_stderr": 0.012734923579532067,
"acc_norm": 0.46284224250325945,
"acc_norm_stderr": 0.012734923579532067
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.6691176470588235,
"acc_stderr": 0.028582709753898445,
"acc_norm": 0.6691176470588235,
"acc_norm_stderr": 0.028582709753898445
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.6748366013071896,
"acc_stderr": 0.018950886770806315,
"acc_norm": 0.6748366013071896,
"acc_norm_stderr": 0.018950886770806315
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.6545454545454545,
"acc_stderr": 0.04554619617541054,
"acc_norm": 0.6545454545454545,
"acc_norm_stderr": 0.04554619617541054
},
"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": 0.835820895522388,
"acc_stderr": 0.026193923544454115,
"acc_norm": 0.835820895522388,
"acc_norm_stderr": 0.026193923544454115
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.82,
"acc_stderr": 0.038612291966536955,
"acc_norm": 0.82,
"acc_norm_stderr": 0.038612291966536955
},
"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": 0.8128654970760234,
"acc_stderr": 0.02991312723236804,
"acc_norm": 0.8128654970760234,
"acc_norm_stderr": 0.02991312723236804
},
"harness|truthfulqa:mc|0": {
"mc1": 0.5789473684210527,
"mc1_stderr": 0.017283936248136476,
"mc2": 0.6961261081361256,
"mc2_stderr": 0.015300239859443631
},
"harness|winogrande|5": {
"acc": 0.8429360694554064,
"acc_stderr": 0.010226303949598484
},
"harness|gsm8k|5": {
"acc": 0.6944655041698257,
"acc_stderr": 0.012688134076726879
}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
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## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
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### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
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### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
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#### 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. -->
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## Bias, Risks, and Limitations
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[More Information Needed] |
CoreGroup/reset | ---
license: c-uda
---
|
open-llm-leaderboard/details_databricks__dbrx-base | ---
pretty_name: Evaluation run of databricks/dbrx-base
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [databricks/dbrx-base](https://huggingface.co/databricks/dbrx-base) 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_databricks__dbrx-base\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-29T19:43:50.174614](https://huggingface.co/datasets/open-llm-leaderboard/details_databricks__dbrx-base/blob/main/results_2024-03-29T19-43-50.174614.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\": 0.7443317876078441,\n\
\ \"acc_stderr\": 0.028686757025155295,\n \"acc_norm\": 0.7479198104742042,\n\
\ \"acc_norm_stderr\": 0.029218744431623284,\n \"mc1\": 0.38310893512851896,\n\
\ \"mc1_stderr\": 0.01701846167938986,\n \"mc2\": 0.5506968114125934,\n\
\ \"mc2_stderr\": 0.014421748656695396\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6322525597269625,\n \"acc_stderr\": 0.014090995618168478,\n\
\ \"acc_norm\": 0.6604095563139932,\n \"acc_norm_stderr\": 0.013839039762820167\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7291376219876519,\n\
\ \"acc_stderr\": 0.0044349692574466165,\n \"acc_norm\": 0.8899621589324835,\n\
\ \"acc_norm_stderr\": 0.0031229736320394735\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \
\ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.674074074074074,\n\
\ \"acc_stderr\": 0.040491220417025055,\n \"acc_norm\": 0.674074074074074,\n\
\ \"acc_norm_stderr\": 0.040491220417025055\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.868421052631579,\n \"acc_stderr\": 0.02750868953354992,\n\
\ \"acc_norm\": 0.868421052631579,\n \"acc_norm_stderr\": 0.02750868953354992\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.77,\n\
\ \"acc_stderr\": 0.042295258468165065,\n \"acc_norm\": 0.77,\n \
\ \"acc_norm_stderr\": 0.042295258468165065\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7886792452830189,\n \"acc_stderr\": 0.025125766484827845,\n\
\ \"acc_norm\": 0.7886792452830189,\n \"acc_norm_stderr\": 0.025125766484827845\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8888888888888888,\n\
\ \"acc_stderr\": 0.026280550932848076,\n \"acc_norm\": 0.8888888888888888,\n\
\ \"acc_norm_stderr\": 0.026280550932848076\n },\n \"harness|hendrycksTest-college_chemistry|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_computer_science|5\": {\n \"\
acc\": 0.61,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\"\
: 0.61,\n \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \
\ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.7341040462427746,\n\
\ \"acc_stderr\": 0.03368762932259431,\n \"acc_norm\": 0.7341040462427746,\n\
\ \"acc_norm_stderr\": 0.03368762932259431\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.5392156862745098,\n \"acc_stderr\": 0.04959859966384181,\n\
\ \"acc_norm\": 0.5392156862745098,\n \"acc_norm_stderr\": 0.04959859966384181\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.85,\n \"acc_stderr\": 0.035887028128263714,\n \"acc_norm\": 0.85,\n\
\ \"acc_norm_stderr\": 0.035887028128263714\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.7319148936170212,\n \"acc_stderr\": 0.028957342788342343,\n\
\ \"acc_norm\": 0.7319148936170212,\n \"acc_norm_stderr\": 0.028957342788342343\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.6228070175438597,\n\
\ \"acc_stderr\": 0.045595221419582166,\n \"acc_norm\": 0.6228070175438597,\n\
\ \"acc_norm_stderr\": 0.045595221419582166\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.7379310344827587,\n \"acc_stderr\": 0.03664666337225258,\n\
\ \"acc_norm\": 0.7379310344827587,\n \"acc_norm_stderr\": 0.03664666337225258\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.5687830687830688,\n \"acc_stderr\": 0.025506481698138208,\n \"\
acc_norm\": 0.5687830687830688,\n \"acc_norm_stderr\": 0.025506481698138208\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.5238095238095238,\n\
\ \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.5238095238095238,\n\
\ \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.45,\n \"acc_stderr\": 0.049999999999999996,\n \
\ \"acc_norm\": 0.45,\n \"acc_norm_stderr\": 0.049999999999999996\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.8741935483870967,\n \"acc_stderr\": 0.018865834288030008,\n \"\
acc_norm\": 0.8741935483870967,\n \"acc_norm_stderr\": 0.018865834288030008\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.6502463054187192,\n \"acc_stderr\": 0.03355400904969565,\n \"\
acc_norm\": 0.6502463054187192,\n \"acc_norm_stderr\": 0.03355400904969565\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.83,\n \"acc_stderr\": 0.0377525168068637,\n \"acc_norm\"\
: 0.83,\n \"acc_norm_stderr\": 0.0377525168068637\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.8606060606060606,\n \"acc_stderr\": 0.027045948825865394,\n\
\ \"acc_norm\": 0.8606060606060606,\n \"acc_norm_stderr\": 0.027045948825865394\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.8737373737373737,\n \"acc_stderr\": 0.023664359402880232,\n \"\
acc_norm\": 0.8737373737373737,\n \"acc_norm_stderr\": 0.023664359402880232\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9585492227979274,\n \"acc_stderr\": 0.01438543285747643,\n\
\ \"acc_norm\": 0.9585492227979274,\n \"acc_norm_stderr\": 0.01438543285747643\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.7512820512820513,\n \"acc_stderr\": 0.0219169577092138,\n \
\ \"acc_norm\": 0.7512820512820513,\n \"acc_norm_stderr\": 0.0219169577092138\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.4185185185185185,\n \"acc_stderr\": 0.03007801307502206,\n \
\ \"acc_norm\": 0.4185185185185185,\n \"acc_norm_stderr\": 0.03007801307502206\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.819327731092437,\n \"acc_stderr\": 0.024991964966600753,\n \
\ \"acc_norm\": 0.819327731092437,\n \"acc_norm_stderr\": 0.024991964966600753\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.5033112582781457,\n \"acc_stderr\": 0.04082393379449654,\n \"\
acc_norm\": 0.5033112582781457,\n \"acc_norm_stderr\": 0.04082393379449654\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.9119266055045872,\n \"acc_stderr\": 0.012150743719481681,\n \"\
acc_norm\": 0.9119266055045872,\n \"acc_norm_stderr\": 0.012150743719481681\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.6898148148148148,\n \"acc_stderr\": 0.03154696285656628,\n \"\
acc_norm\": 0.6898148148148148,\n \"acc_norm_stderr\": 0.03154696285656628\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.9019607843137255,\n \"acc_stderr\": 0.020871118455552114,\n \"\
acc_norm\": 0.9019607843137255,\n \"acc_norm_stderr\": 0.020871118455552114\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.9156118143459916,\n \"acc_stderr\": 0.01809424711647332,\n \
\ \"acc_norm\": 0.9156118143459916,\n \"acc_norm_stderr\": 0.01809424711647332\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7982062780269058,\n\
\ \"acc_stderr\": 0.026936111912802273,\n \"acc_norm\": 0.7982062780269058,\n\
\ \"acc_norm_stderr\": 0.026936111912802273\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.9007633587786259,\n \"acc_stderr\": 0.026222235171477364,\n\
\ \"acc_norm\": 0.9007633587786259,\n \"acc_norm_stderr\": 0.026222235171477364\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.9008264462809917,\n \"acc_stderr\": 0.027285246312758967,\n \"\
acc_norm\": 0.9008264462809917,\n \"acc_norm_stderr\": 0.027285246312758967\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8611111111111112,\n\
\ \"acc_stderr\": 0.03343270062869621,\n \"acc_norm\": 0.8611111111111112,\n\
\ \"acc_norm_stderr\": 0.03343270062869621\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.8343558282208589,\n \"acc_stderr\": 0.029208296231259104,\n\
\ \"acc_norm\": 0.8343558282208589,\n \"acc_norm_stderr\": 0.029208296231259104\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5803571428571429,\n\
\ \"acc_stderr\": 0.04684099321077106,\n \"acc_norm\": 0.5803571428571429,\n\
\ \"acc_norm_stderr\": 0.04684099321077106\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8640776699029126,\n \"acc_stderr\": 0.03393295729761012,\n\
\ \"acc_norm\": 0.8640776699029126,\n \"acc_norm_stderr\": 0.03393295729761012\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9401709401709402,\n\
\ \"acc_stderr\": 0.015537514263253872,\n \"acc_norm\": 0.9401709401709402,\n\
\ \"acc_norm_stderr\": 0.015537514263253872\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.86,\n \"acc_stderr\": 0.034873508801977704,\n \
\ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.034873508801977704\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.9195402298850575,\n\
\ \"acc_stderr\": 0.009726831316141858,\n \"acc_norm\": 0.9195402298850575,\n\
\ \"acc_norm_stderr\": 0.009726831316141858\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.8121387283236994,\n \"acc_stderr\": 0.021029269752423214,\n\
\ \"acc_norm\": 0.8121387283236994,\n \"acc_norm_stderr\": 0.021029269752423214\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.48044692737430167,\n\
\ \"acc_stderr\": 0.016709709877662,\n \"acc_norm\": 0.48044692737430167,\n\
\ \"acc_norm_stderr\": 0.016709709877662\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.8398692810457516,\n \"acc_stderr\": 0.020998740930362303,\n\
\ \"acc_norm\": 0.8398692810457516,\n \"acc_norm_stderr\": 0.020998740930362303\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.8167202572347267,\n\
\ \"acc_stderr\": 0.02197419884826583,\n \"acc_norm\": 0.8167202572347267,\n\
\ \"acc_norm_stderr\": 0.02197419884826583\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.8734567901234568,\n \"acc_stderr\": 0.018498600558790917,\n\
\ \"acc_norm\": 0.8734567901234568,\n \"acc_norm_stderr\": 0.018498600558790917\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.5425531914893617,\n \"acc_stderr\": 0.029719281272236834,\n \
\ \"acc_norm\": 0.5425531914893617,\n \"acc_norm_stderr\": 0.029719281272236834\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.6036505867014341,\n\
\ \"acc_stderr\": 0.012492830452095219,\n \"acc_norm\": 0.6036505867014341,\n\
\ \"acc_norm_stderr\": 0.012492830452095219\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.8308823529411765,\n \"acc_stderr\": 0.02277086801011301,\n\
\ \"acc_norm\": 0.8308823529411765,\n \"acc_norm_stderr\": 0.02277086801011301\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.795751633986928,\n \"acc_stderr\": 0.01630975584836151,\n \
\ \"acc_norm\": 0.795751633986928,\n \"acc_norm_stderr\": 0.01630975584836151\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7272727272727273,\n\
\ \"acc_stderr\": 0.04265792110940588,\n \"acc_norm\": 0.7272727272727273,\n\
\ \"acc_norm_stderr\": 0.04265792110940588\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.8244897959183674,\n \"acc_stderr\": 0.024352800722970015,\n\
\ \"acc_norm\": 0.8244897959183674,\n \"acc_norm_stderr\": 0.024352800722970015\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8905472636815921,\n\
\ \"acc_stderr\": 0.022076326101824657,\n \"acc_norm\": 0.8905472636815921,\n\
\ \"acc_norm_stderr\": 0.022076326101824657\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.95,\n \"acc_stderr\": 0.021904291355759033,\n \
\ \"acc_norm\": 0.95,\n \"acc_norm_stderr\": 0.021904291355759033\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\": 0.8538011695906432,\n \"acc_stderr\": 0.027097290118070824,\n\
\ \"acc_norm\": 0.8538011695906432,\n \"acc_norm_stderr\": 0.027097290118070824\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.38310893512851896,\n\
\ \"mc1_stderr\": 0.01701846167938986,\n \"mc2\": 0.5506968114125934,\n\
\ \"mc2_stderr\": 0.014421748656695396\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7805840568271507,\n \"acc_stderr\": 0.01163126836060778\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6853677028051555,\n \
\ \"acc_stderr\": 0.01279103722733603\n }\n}\n```"
repo_url: https://huggingface.co/databricks/dbrx-base
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_29T19_43_50.174614
path:
- '**/details_harness|arc:challenge|25_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|gsm8k|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hellaswag|10_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-29T19-43-50.174614.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-29T19-43-50.174614.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- '**/details_harness|winogrande|5_2024-03-29T19-43-50.174614.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-29T19-43-50.174614.parquet'
- config_name: results
data_files:
- split: 2024_03_29T19_43_50.174614
path:
- results_2024-03-29T19-43-50.174614.parquet
- split: latest
path:
- results_2024-03-29T19-43-50.174614.parquet
---
# Dataset Card for Evaluation run of databricks/dbrx-base
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [databricks/dbrx-base](https://huggingface.co/databricks/dbrx-base) 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_databricks__dbrx-base",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-29T19:43:50.174614](https://huggingface.co/datasets/open-llm-leaderboard/details_databricks__dbrx-base/blob/main/results_2024-03-29T19-43-50.174614.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": 0.7443317876078441,
"acc_stderr": 0.028686757025155295,
"acc_norm": 0.7479198104742042,
"acc_norm_stderr": 0.029218744431623284,
"mc1": 0.38310893512851896,
"mc1_stderr": 0.01701846167938986,
"mc2": 0.5506968114125934,
"mc2_stderr": 0.014421748656695396
},
"harness|arc:challenge|25": {
"acc": 0.6322525597269625,
"acc_stderr": 0.014090995618168478,
"acc_norm": 0.6604095563139932,
"acc_norm_stderr": 0.013839039762820167
},
"harness|hellaswag|10": {
"acc": 0.7291376219876519,
"acc_stderr": 0.0044349692574466165,
"acc_norm": 0.8899621589324835,
"acc_norm_stderr": 0.0031229736320394735
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.4,
"acc_stderr": 0.049236596391733084,
"acc_norm": 0.4,
"acc_norm_stderr": 0.049236596391733084
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.674074074074074,
"acc_stderr": 0.040491220417025055,
"acc_norm": 0.674074074074074,
"acc_norm_stderr": 0.040491220417025055
},
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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. -->
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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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shainahub/clinical_bias | ---
dataset_info:
features:
- name: SUBJECT_ID
dtype: int64
- name: TEXT
dtype: string
- name: is_biased
dtype: bool
- name: biased_words
dtype: string
splits:
- name: train
num_bytes: 11586577
num_examples: 40000
download_size: 6501927
dataset_size: 11586577
license: afl-3.0
language:
- en
---
## Dataset Description
- **Homepage:** [Clinical Biases Dataset](https://huggingface.co/datasets/shainahub/clinical_bias)
### Who is the target audience for this dataset?
The target audience includes researchers and practitioners in the healthcare and natural language processing domains interested in studying biases in clinical texts and developing models to detect and mitigate such biases.
### What do I need to know to use this dataset?
Users should have a basic understanding of clinical texts, biases, and natural language processing.
## Data Fields
- `SUBJECT_ID`: A unique identifier for the subject.
- `TEXT`: The clinical text.
- `is_biased`: A boolean indicating whether the text is biased or not.
- `biased_words`: A list of biased words present in the text (if any).
## Data Splits
This dataset does not have predefined data splits (train, validation, test). Users can create their own splits according to their requirements.
## Dataset Creation
### Curation Rationale
The dataset was created to study biases in clinical texts and provide a resource for developing models to detect and mitigate such biases.
### Source Data
The dataset is derived from clinical texts collected from various sources.
### Licensing Information
The licensing information for this dataset is not specified.
### Previewing the Dataset
You can use the following code snippet to preview the dataset using Hugging Face Datasets library in Python:
```python
from datasets import load_dataset
dataset = load_dataset("shainahub/clinical_bias")
dataset_dict = dataset["train"][0]
print("SUBJECT_ID:", dataset_dict["SUBJECT_ID"])
print("TEXT:", dataset_dict["TEXT"])
print("is_biased:", dataset_dict["is_biased"])
print("biased_words:", dataset_dict["biased_words"])
```
```python
from datasets import load_dataset
dataset = load_dataset("shainahub/clinical_bias")
df = dataset['train'].to_pandas()
df.head()
```
it will give 40k rows.
The output should look like this:
```python
SUBJECT_ID: 2549
TEXT: CCU NSG TRANSFER SUMMARY UPDATE RESP FAILURE CLINICAL STATUS: Fever Oxygen saturations have been intermittently low on room air with improvement on oxygen High white blood cell count Multifocal pneumonia Gastrointestinal bleeding concerning for stress ulceration Hemodynamically stable on vasopressors, requiring increasing amounts to maintain mean arterial pressure. Heart rate increased to 100s with systolic blood pressure in the 90s. PLAN: 1. Continue current management 2. Initiate prophylaxis for stress ulceration 3. Initiate appropriate isolation for pneumonia
is_biased: False
biased_words: None
```
Loading the Dataset
You can use the following code snippet to load the dataset using Hugging Face Datasets library in Python:
```python
from datasets import load_dataset
dataset = load_dataset("shainahub/clinical_bias")
```
The dataset consists of four columns:
```python
SUBJECT_ID: a unique identifier for each clinical note.
TEXT: the text of the clinical note
is_biased: a boolean value indicating whether the note contains biased language or not
biased_words: if the note contains biased language, the words or phrases that are biased
```
|
gkaradzhov/DeliData | ---
license: cc-by-4.0
---
# DeliData
This is a README that outlines key fields and characteristics of the DeliData corpus.
For full description of how we collected DeliData, as well as possible applications, please refer to the original
paper [link](#citation).
# Data Fields
###### group_id
Unique identifier of the group chat
###### message_id
Message identifier. System messages will have an id of -1, however all participant messages' ids are unique.
###### message_type
INITIAL - indicating the cards presented and aliases of participants;
SUBMIT - indicating that a participant has pressed the Submit Solution button
MESSAGE - noting a chat entry
###### origin
The alias of the participant who submitted a message/solution
###### original_text
Original text as said in the collected conversation;
For INITIAL type, contains the list of participants and cards presented.
For SUBMIT type, contains the cards submitted
###### clean_text
Normalised message, with applied tokenisation, and masking of special tokens. Special tokens are considered solution
mentions, which are masked with < CARD > and participant mentions which are masked with < MENTION >
###### annotation_type
A record from the first level of DeliAnnotation. Can be Probing, Non-probing deliberation, or None. For more details,
please refer to the DeliData paper.
###### annotation_target
A record from the second level of DeliAnnotation. Can be Moderation, Reasoning, Solution, Agree, or Disagree. For more
details, please refer to the DeliData paper.
###### annotation_additional
A record from the third level of DeliAnnotation. Can be partial_solution, complete_solution, specific_referee,
solution_summary, or consider_opposite. For more details, please refer to the DeliData paper.
###### team_performance
An approximation of team performance, based on user submissions, and solution mentions. Range [0-1], where 1 indicates
each participant selecting the correct solution.
###### performance_change
Change of performance based compared to the previous utterance
###### sol_tracker_message
Extracted solution from the current message
###### sol_tracker_all
Up-to-date "state-of-mind" for each of the participants, i.e. an approximation of what each participant think the
correct solution is at given timestep. This is based on initial solutions, submitted solutions, and solution mentions.
team_performance value is calculated based on this column
### Citation
**DeliData A dataset for deliberation in multi-party problem solving (https://delibot.xyz/delidata)**
@article{karadzhov2023delidata,
title={DeliData: A dataset for deliberation in multi-party problem solving},
author={Karadzhov, Georgi and Stafford, Tom and Vlachos, Andreas},
journal={Proceedings of the ACM on Human-Computer Interaction},
volume={7},
number={CSCW2},
pages={1--25},
year={2023},
publisher={ACM New York, NY, USA}
}
|
kaleemWaheed/twitter_dataset_1713107880 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 26030
num_examples: 63
download_size: 16142
dataset_size: 26030
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
liuyanchen1015/MULTI_VALUE_stsb_reduced_relative | ---
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype: float64
- name: idx
dtype: int64
- name: value_score
dtype: int64
splits:
- name: dev
num_bytes: 20590
num_examples: 111
- name: test
num_bytes: 15581
num_examples: 101
- name: train
num_bytes: 75920
num_examples: 406
download_size: 81537
dataset_size: 112091
---
# Dataset Card for "MULTI_VALUE_stsb_reduced_relative"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Superdetec/EgorLinch | ---
license: openrail
---
|
tyzhu/lmind_hotpot_train300_eval100_v1_recite_qa | ---
configs:
- config_name: default
data_files:
- split: train_qa
path: data/train_qa-*
- split: train_recite_qa
path: data/train_recite_qa-*
- split: eval_qa
path: data/eval_qa-*
- split: eval_recite_qa
path: data/eval_recite_qa-*
- split: all_docs
path: data/all_docs-*
- split: all_docs_eval
path: data/all_docs_eval-*
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
- name: answers
struct:
- name: answer_start
sequence: 'null'
- name: text
sequence: string
splits:
- name: train_qa
num_bytes: 51441
num_examples: 300
- name: train_recite_qa
num_bytes: 312070
num_examples: 300
- name: eval_qa
num_bytes: 16148
num_examples: 100
- name: eval_recite_qa
num_bytes: 104950
num_examples: 100
- name: all_docs
num_bytes: 361191
num_examples: 797
- name: all_docs_eval
num_bytes: 361140
num_examples: 797
- name: train
num_bytes: 673261
num_examples: 1097
- name: validation
num_bytes: 104950
num_examples: 100
download_size: 1032509
dataset_size: 1985151
---
# Dataset Card for "lmind_hotpot_train300_eval100_v1_recite_qa"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
saibo/bookcorpus_compact_1024_shard0_of_10_meta | ---
dataset_info:
features:
- name: text
dtype: string
- name: concept_with_offset
dtype: string
- name: cid_arrangement
sequence: int32
- name: schema_lengths
sequence: int64
- name: topic_entity_mask
sequence: int64
- name: text_lengths
sequence: int64
splits:
- name: train
num_bytes: 7429184891
num_examples: 61605
download_size: 1631318898
dataset_size: 7429184891
---
# Dataset Card for "bookcorpus_compact_1024_shard0_meta"
132 hours to finish
num_examples: 61605
size: 1.5GB
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_gmonsoon__OpenMia-Indo-Engineering | ---
pretty_name: Evaluation run of gmonsoon/OpenMia-Indo-Engineering
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [gmonsoon/OpenMia-Indo-Engineering](https://huggingface.co/gmonsoon/OpenMia-Indo-Engineering)\
\ 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_gmonsoon__OpenMia-Indo-Engineering\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-02-04T20:44:41.527501](https://huggingface.co/datasets/open-llm-leaderboard/details_gmonsoon__OpenMia-Indo-Engineering/blob/main/results_2024-02-04T20-44-41.527501.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\": 0.6324060235996815,\n\
\ \"acc_stderr\": 0.03231686157638383,\n \"acc_norm\": 0.6331079164519123,\n\
\ \"acc_norm_stderr\": 0.032980184119772604,\n \"mc1\": 0.4186046511627907,\n\
\ \"mc1_stderr\": 0.01727001528447686,\n \"mc2\": 0.5793947082847677,\n\
\ \"mc2_stderr\": 0.01530573457723597\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6245733788395904,\n \"acc_stderr\": 0.014150631435111728,\n\
\ \"acc_norm\": 0.6715017064846417,\n \"acc_norm_stderr\": 0.0137249784655373\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6482772356104362,\n\
\ \"acc_stderr\": 0.004765320784902126,\n \"acc_norm\": 0.8501294562836088,\n\
\ \"acc_norm_stderr\": 0.0035621498909627174\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \
\ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6518518518518519,\n\
\ \"acc_stderr\": 0.041153246103369526,\n \"acc_norm\": 0.6518518518518519,\n\
\ \"acc_norm_stderr\": 0.041153246103369526\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\": 0.6,\n\
\ \"acc_stderr\": 0.04923659639173309,\n \"acc_norm\": 0.6,\n \
\ \"acc_norm_stderr\": 0.04923659639173309\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6981132075471698,\n \"acc_stderr\": 0.02825420034443866,\n\
\ \"acc_norm\": 0.6981132075471698,\n \"acc_norm_stderr\": 0.02825420034443866\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.75,\n\
\ \"acc_stderr\": 0.03621034121889507,\n \"acc_norm\": 0.75,\n \
\ \"acc_norm_stderr\": 0.03621034121889507\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145633,\n \
\ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145633\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.49,\n\
\ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6184971098265896,\n\
\ \"acc_stderr\": 0.03703851193099521,\n \"acc_norm\": 0.6184971098265896,\n\
\ \"acc_norm_stderr\": 0.03703851193099521\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.39215686274509803,\n \"acc_stderr\": 0.04858083574266345,\n\
\ \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.04858083574266345\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.77,\n \"acc_stderr\": 0.04229525846816508,\n \"acc_norm\": 0.77,\n\
\ \"acc_norm_stderr\": 0.04229525846816508\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5234042553191489,\n \"acc_stderr\": 0.032650194750335815,\n\
\ \"acc_norm\": 0.5234042553191489,\n \"acc_norm_stderr\": 0.032650194750335815\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.45614035087719296,\n\
\ \"acc_stderr\": 0.046854730419077895,\n \"acc_norm\": 0.45614035087719296,\n\
\ \"acc_norm_stderr\": 0.046854730419077895\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5379310344827586,\n \"acc_stderr\": 0.04154659671707548,\n\
\ \"acc_norm\": 0.5379310344827586,\n \"acc_norm_stderr\": 0.04154659671707548\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.3968253968253968,\n \"acc_stderr\": 0.02519710107424649,\n \"\
acc_norm\": 0.3968253968253968,\n \"acc_norm_stderr\": 0.02519710107424649\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.49206349206349204,\n\
\ \"acc_stderr\": 0.044715725362943486,\n \"acc_norm\": 0.49206349206349204,\n\
\ \"acc_norm_stderr\": 0.044715725362943486\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.31,\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\": 0.7677419354838709,\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\": 0.49261083743842365,\n \"acc_stderr\": 0.035176035403610084,\n\
\ \"acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.035176035403610084\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\
: 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7515151515151515,\n \"acc_stderr\": 0.033744026441394036,\n\
\ \"acc_norm\": 0.7515151515151515,\n \"acc_norm_stderr\": 0.033744026441394036\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.8080808080808081,\n \"acc_stderr\": 0.02805779167298902,\n \"\
acc_norm\": 0.8080808080808081,\n \"acc_norm_stderr\": 0.02805779167298902\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8652849740932642,\n \"acc_stderr\": 0.02463978909770944,\n\
\ \"acc_norm\": 0.8652849740932642,\n \"acc_norm_stderr\": 0.02463978909770944\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6358974358974359,\n \"acc_stderr\": 0.02439667298509476,\n \
\ \"acc_norm\": 0.6358974358974359,\n \"acc_norm_stderr\": 0.02439667298509476\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.31851851851851853,\n \"acc_stderr\": 0.028406533090608456,\n \
\ \"acc_norm\": 0.31851851851851853,\n \"acc_norm_stderr\": 0.028406533090608456\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6218487394957983,\n \"acc_stderr\": 0.03149930577784906,\n \
\ \"acc_norm\": 0.6218487394957983,\n \"acc_norm_stderr\": 0.03149930577784906\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\"\
: 0.8256880733944955,\n \"acc_stderr\": 0.016265675632010347,\n \"\
acc_norm\": 0.8256880733944955,\n \"acc_norm_stderr\": 0.016265675632010347\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\"\
: 0.8137254901960784,\n \"acc_stderr\": 0.02732547096671632,\n \"\
acc_norm\": 0.8137254901960784,\n \"acc_norm_stderr\": 0.02732547096671632\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7974683544303798,\n \"acc_stderr\": 0.026160568246601436,\n \
\ \"acc_norm\": 0.7974683544303798,\n \"acc_norm_stderr\": 0.026160568246601436\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7130044843049327,\n\
\ \"acc_stderr\": 0.03036037971029195,\n \"acc_norm\": 0.7130044843049327,\n\
\ \"acc_norm_stderr\": 0.03036037971029195\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\":\
\ 0.7520661157024794,\n \"acc_stderr\": 0.03941897526516303,\n \"\
acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.03941897526516303\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\
\ \"acc_stderr\": 0.039578354719809805,\n \"acc_norm\": 0.7870370370370371,\n\
\ \"acc_norm_stderr\": 0.039578354719809805\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\": 0.5357142857142857,\n\
\ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.5357142857142857,\n\
\ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8058252427184466,\n \"acc_stderr\": 0.03916667762822584,\n\
\ \"acc_norm\": 0.8058252427184466,\n \"acc_norm_stderr\": 0.03916667762822584\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\
\ \"acc_stderr\": 0.021262719400406957,\n \"acc_norm\": 0.8803418803418803,\n\
\ \"acc_norm_stderr\": 0.021262719400406957\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.8186462324393359,\n\
\ \"acc_stderr\": 0.01377869377846408,\n \"acc_norm\": 0.8186462324393359,\n\
\ \"acc_norm_stderr\": 0.01377869377846408\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7167630057803468,\n \"acc_stderr\": 0.024257901705323378,\n\
\ \"acc_norm\": 0.7167630057803468,\n \"acc_norm_stderr\": 0.024257901705323378\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3027932960893855,\n\
\ \"acc_stderr\": 0.015366860386397112,\n \"acc_norm\": 0.3027932960893855,\n\
\ \"acc_norm_stderr\": 0.015366860386397112\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7058823529411765,\n \"acc_stderr\": 0.026090162504279056,\n\
\ \"acc_norm\": 0.7058823529411765,\n \"acc_norm_stderr\": 0.026090162504279056\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7041800643086816,\n\
\ \"acc_stderr\": 0.025922371788818763,\n \"acc_norm\": 0.7041800643086816,\n\
\ \"acc_norm_stderr\": 0.025922371788818763\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7006172839506173,\n \"acc_stderr\": 0.02548311560119545,\n\
\ \"acc_norm\": 0.7006172839506173,\n \"acc_norm_stderr\": 0.02548311560119545\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.4574468085106383,\n \"acc_stderr\": 0.029719281272236848,\n \
\ \"acc_norm\": 0.4574468085106383,\n \"acc_norm_stderr\": 0.029719281272236848\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4726205997392438,\n\
\ \"acc_stderr\": 0.012751075788015062,\n \"acc_norm\": 0.4726205997392438,\n\
\ \"acc_norm_stderr\": 0.012751075788015062\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6360294117647058,\n \"acc_stderr\": 0.029227192460032025,\n\
\ \"acc_norm\": 0.6360294117647058,\n \"acc_norm_stderr\": 0.029227192460032025\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6290849673202614,\n \"acc_stderr\": 0.019542101564854125,\n \
\ \"acc_norm\": 0.6290849673202614,\n \"acc_norm_stderr\": 0.019542101564854125\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6909090909090909,\n\
\ \"acc_stderr\": 0.044262946482000985,\n \"acc_norm\": 0.6909090909090909,\n\
\ \"acc_norm_stderr\": 0.044262946482000985\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784593,\n\
\ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784593\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8258706467661692,\n\
\ \"acc_stderr\": 0.026814951200421603,\n \"acc_norm\": 0.8258706467661692,\n\
\ \"acc_norm_stderr\": 0.026814951200421603\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.83,\n \"acc_stderr\": 0.0377525168068637,\n \
\ \"acc_norm\": 0.83,\n \"acc_norm_stderr\": 0.0377525168068637\n },\n\
\ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5,\n \"\
acc_stderr\": 0.03892494720807614,\n \"acc_norm\": 0.5,\n \"acc_norm_stderr\"\
: 0.03892494720807614\n },\n \"harness|hendrycksTest-world_religions|5\":\
\ {\n \"acc\": 0.8070175438596491,\n \"acc_stderr\": 0.030267457554898458,\n\
\ \"acc_norm\": 0.8070175438596491,\n \"acc_norm_stderr\": 0.030267457554898458\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4186046511627907,\n\
\ \"mc1_stderr\": 0.01727001528447686,\n \"mc2\": 0.5793947082847677,\n\
\ \"mc2_stderr\": 0.01530573457723597\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8232044198895028,\n \"acc_stderr\": 0.010721923287918747\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6489764973464746,\n \
\ \"acc_stderr\": 0.013146945941397222\n }\n}\n```"
repo_url: https://huggingface.co/gmonsoon/OpenMia-Indo-Engineering
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|arc:challenge|25_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|gsm8k|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hellaswag|10_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-04T20-44-41.527501.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-04T20-44-41.527501.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- '**/details_harness|winogrande|5_2024-02-04T20-44-41.527501.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-02-04T20-44-41.527501.parquet'
- config_name: results
data_files:
- split: 2024_02_04T20_44_41.527501
path:
- results_2024-02-04T20-44-41.527501.parquet
- split: latest
path:
- results_2024-02-04T20-44-41.527501.parquet
---
# Dataset Card for Evaluation run of gmonsoon/OpenMia-Indo-Engineering
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [gmonsoon/OpenMia-Indo-Engineering](https://huggingface.co/gmonsoon/OpenMia-Indo-Engineering) 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_gmonsoon__OpenMia-Indo-Engineering",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-02-04T20:44:41.527501](https://huggingface.co/datasets/open-llm-leaderboard/details_gmonsoon__OpenMia-Indo-Engineering/blob/main/results_2024-02-04T20-44-41.527501.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": 0.6324060235996815,
"acc_stderr": 0.03231686157638383,
"acc_norm": 0.6331079164519123,
"acc_norm_stderr": 0.032980184119772604,
"mc1": 0.4186046511627907,
"mc1_stderr": 0.01727001528447686,
"mc2": 0.5793947082847677,
"mc2_stderr": 0.01530573457723597
},
"harness|arc:challenge|25": {
"acc": 0.6245733788395904,
"acc_stderr": 0.014150631435111728,
"acc_norm": 0.6715017064846417,
"acc_norm_stderr": 0.0137249784655373
},
"harness|hellaswag|10": {
"acc": 0.6482772356104362,
"acc_stderr": 0.004765320784902126,
"acc_norm": 0.8501294562836088,
"acc_norm_stderr": 0.0035621498909627174
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.27,
"acc_stderr": 0.044619604333847394,
"acc_norm": 0.27,
"acc_norm_stderr": 0.044619604333847394
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6518518518518519,
"acc_stderr": 0.041153246103369526,
"acc_norm": 0.6518518518518519,
"acc_norm_stderr": 0.041153246103369526
},
"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": 0.6,
"acc_stderr": 0.04923659639173309,
"acc_norm": 0.6,
"acc_norm_stderr": 0.04923659639173309
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6981132075471698,
"acc_stderr": 0.02825420034443866,
"acc_norm": 0.6981132075471698,
"acc_norm_stderr": 0.02825420034443866
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.75,
"acc_stderr": 0.03621034121889507,
"acc_norm": 0.75,
"acc_norm_stderr": 0.03621034121889507
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.38,
"acc_stderr": 0.04878317312145633,
"acc_norm": 0.38,
"acc_norm_stderr": 0.04878317312145633
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.49,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.49,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.35,
"acc_stderr": 0.047937248544110196,
"acc_norm": 0.35,
"acc_norm_stderr": 0.047937248544110196
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6184971098265896,
"acc_stderr": 0.03703851193099521,
"acc_norm": 0.6184971098265896,
"acc_norm_stderr": 0.03703851193099521
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.39215686274509803,
"acc_stderr": 0.04858083574266345,
"acc_norm": 0.39215686274509803,
"acc_norm_stderr": 0.04858083574266345
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.77,
"acc_stderr": 0.04229525846816508,
"acc_norm": 0.77,
"acc_norm_stderr": 0.04229525846816508
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5234042553191489,
"acc_stderr": 0.032650194750335815,
"acc_norm": 0.5234042553191489,
"acc_norm_stderr": 0.032650194750335815
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.45614035087719296,
"acc_stderr": 0.046854730419077895,
"acc_norm": 0.45614035087719296,
"acc_norm_stderr": 0.046854730419077895
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5379310344827586,
"acc_stderr": 0.04154659671707548,
"acc_norm": 0.5379310344827586,
"acc_norm_stderr": 0.04154659671707548
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.3968253968253968,
"acc_stderr": 0.02519710107424649,
"acc_norm": 0.3968253968253968,
"acc_norm_stderr": 0.02519710107424649
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.49206349206349204,
"acc_stderr": 0.044715725362943486,
"acc_norm": 0.49206349206349204,
"acc_norm_stderr": 0.044715725362943486
},
"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": 0.7677419354838709,
"acc_stderr": 0.024022256130308235,
"acc_norm": 0.7677419354838709,
"acc_norm_stderr": 0.024022256130308235
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.49261083743842365,
"acc_stderr": 0.035176035403610084,
"acc_norm": 0.49261083743842365,
"acc_norm_stderr": 0.035176035403610084
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.69,
"acc_stderr": 0.04648231987117316,
"acc_norm": 0.69,
"acc_norm_stderr": 0.04648231987117316
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7515151515151515,
"acc_stderr": 0.033744026441394036,
"acc_norm": 0.7515151515151515,
"acc_norm_stderr": 0.033744026441394036
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.8080808080808081,
"acc_stderr": 0.02805779167298902,
"acc_norm": 0.8080808080808081,
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```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
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## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
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### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
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[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
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#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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sean0042/pubmedqa | ---
dataset_info:
features:
- name: id
dtype: string
- name: question_id
dtype: string
- name: document_id
dtype: string
- name: question
dtype: string
- name: type
dtype: string
- name: choices
list: string
- name: context
dtype: string
- name: answer
sequence: string
- name: new_feature
dtype: int64
splits:
- name: train
num_bytes: 686223
num_examples: 450
- name: validation
num_bytes: 75810
num_examples: 50
- name: test
num_bytes: 773437
num_examples: 500
download_size: 881358
dataset_size: 1535470
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
|
autoevaluate/autoeval-eval-futin__guess-en-78963b-2087067149 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- futin/guess
eval_info:
task: text_zero_shot_classification
model: bigscience/bloom-560m
metrics: []
dataset_name: futin/guess
dataset_config: en
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: bigscience/bloom-560m
* Dataset: futin/guess
* Config: en
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@futin](https://huggingface.co/futin) for evaluating this model. |
Jlmadridch/rubrix | ---
dataset_info:
features:
- name: text
dtype: string
- name: inputs
struct:
- name: text
dtype: string
- name: prediction
list:
- name: label
dtype: string
- name: score
dtype: float64
- name: prediction_agent
dtype: string
- name: annotation
dtype: 'null'
- name: annotation_agent
dtype: 'null'
- name: multi_label
dtype: bool
- name: explanation
dtype: 'null'
- name: id
dtype: 'null'
- name: metadata
struct:
- name: category
dtype: int64
- name: status
dtype: string
- name: event_timestamp
dtype: 'null'
- name: metrics
dtype: 'null'
splits:
- name: train
num_bytes: 1205760
num_examples: 5001
download_size: 448027
dataset_size: 1205760
---
# Dataset Card for "rubrix"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
oreva/ppl_gpt2_large_s19e34_ranked_squad | ---
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: prompt
dtype: string
- name: ppl_gpt2_large_s19e34
dtype: float64
splits:
- name: train
num_bytes: 138319124
num_examples: 77087
download_size: 86666837
dataset_size: 138319124
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ppl_gpt2_large_s19e34_ranked_squad"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
jj342569/biochemistry | ---
license: gpl-2.0
---
|
flowfree/crypto-news-headlines | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': negative
'1': neutral
'2': positive
splits:
- name: train
num_bytes: 112117
num_examples: 518
- name: validation
num_bytes: 55863
num_examples: 260
- name: test
num_bytes: 55964
num_examples: 257
download_size: 146743
dataset_size: 223944
---
# Dataset Card for "crypto-news-headlines"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
DavidVivancos/MindBigData2022_VisMNIST_Cap64 | ---
license: odbl
---
|
IanTseng/Med-term3 | ---
dataset_info:
features:
- name: TEXT
dtype: string
- name: LOCATION
dtype: string
- name: LABEL
dtype: string
splits:
- name: train
num_bytes: 2433641009
num_examples: 2393619
download_size: 1381318742
dataset_size: 2433641009
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
dim/ru_word_games_3k | ---
dataset_info:
features:
- name: subset
dtype: string
- name: answer
dtype: string
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 295312.9940025371
num_examples: 3000
download_size: 150082
dataset_size: 295312.9940025371
---
# Dataset Card for "ru_word_games_3k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ironchanchellor/DEDAM_2 | ---
dataset_info:
features:
- name: pixel_values
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 63783002.0
num_examples: 487
- name: validation
num_bytes: 16444985.0
num_examples: 122
download_size: 79247856
dataset_size: 80227987.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
|
Mehaki/formal_casual | ---
language:
- en
task_categories:
- text-generation
---
[
{
"source_sentence": "Title: The Impact of Technology on Modern Education\n\nThe integration of technology in education has transformed the way students learn. Digital resources, online learning platforms, and interactive tools enhance the educational experience, making learning more accessible and engaging.",
"target_sentence": "Title: Learning in the Digital Age: Embrace the Tech Revolution\n\nHey, digital explorers! Let's chat about the coolest thing in education since sliced bread: technology. We're talking gadgets, gizmos, and learning in your PJs. Get cozy, because the future of education is here, and it's awesome!"
},
{
"source_sentence": "Title: The Importance of Financial Planning for Retirement\n\nPlanning for retirement is a crucial financial milestone. Sound financial planning, including saving, investing, and managing expenses, ensures financial security and a comfortable retirement lifestyle.",
"target_sentence": "Title: Retirement Ready: Your Ticket to Financial Freedom\n\nHey there, future retirees! It's time to get cozy with your retirement plans. We've got tips, tricks, and a side of relaxation for your financial journey. Kick back and let's make that retirement dream a reality!"
},
{
"source_sentence": "Title: The Impact of Climate Change on Ecosystems\n\nClimate change poses a severe threat to global ecosystems. Rising temperatures, sea-level rise, and extreme weather events are disrupting delicate ecological balances. Conservation efforts are essential to protect biodiversity.",
"target_sentence": "Title: Saving Our Planet, One Step at a Time\n\nHey eco-warriors! Time to chat about our favorite green hero, Mother Earth. We've got the 411 on climate change, and we're bringing eco-friendly vibes to your doorstep. Let's make eco-saving a lifestyle, and have a blast while we're at it!"
},
{
"source_sentence": "Title: The Role of Ethics in Business Leadership\n\nEthical leadership is the cornerstone of successful and sustainable businesses. Upholding strong ethical values fosters trust, integrity, and long-term growth. Ethical leaders set the standard for responsible business practices.",
"target_sentence": "Title: Leading with Heart: Navigating the Business Ethics Playground\n\nHey future ethical leaders! We're here to demystify the art of ethical leadership. It's all about doing the right thing, keeping it real, and having a blast in the business world. Let's lead with heart and make a positive impact!"
},
{
"source_sentence": "Title: The Significance of Healthy Lifestyle Choices\n\nAdopting a healthy lifestyle through balanced nutrition and regular exercise is crucial for overall well-being. Making smart choices in diet and physical activity promotes physical fitness and reduces the risk of chronic diseases.",
"target_sentence": "Title: Fit and Fabulous: Your Guide to a Healthy Lifestyle\n\nHey health enthusiasts! We're on a mission to make healthy living a piece of cake (a healthy cake, of course). It's all about delicious eats, fun workouts, and feeling amazing. Join the health party, and let's rock that healthy vibe!"
},
{
"source_sentence": "Title: The Impact of Social Media on Modern Communication\n\nSocial media has revolutionized the way we connect and communicate with one another. It facilitates real-time interactions, information sharing, and global connectivity. The influence of social media on society and communication is profound.",
"target_sentence": "Title: Social Media Unleashed: Connecting in the Digital Era\n\nHey digital citizens! Social media is our playground, and we're here to have a blast. Let's chat about hashtags, selfies, and all things viral. It's a digital world, and we're loving every like, share, and tweet!"
},
{
"source_sentence": "Title: The Role of Cultural Diversity in Global Harmony\n\nCultural diversity enriches our global society by fostering understanding, tolerance, and unity. Embracing diverse cultures promotes peace and cooperation among nations, leading to a harmonious world.",
"target_sentence": "Title: Embracing the Rainbow of Cultures: Our Global Family\n\nHey global citizens! It's time for a cultural fiesta. We're all about embracing differences, sharing stories, and feasting on international flavors. Get ready for a cultural hug, because we're one big global family!"
},
{
"source_sentence": "Title: The Importance of Time Management in Professional Success\n\nEffective time management is a cornerstone of professional success. It maximizes productivity, minimizes stress, and ensures that goals are met efficiently. Mastering time management is a key skill for career advancement.",
"target_sentence": "Title: Time Ninja: Crushing It in Your Daily Quest\n\nHey time warriors! It's time to gear up and conquer your day like a pro. We've got time-saving tricks, epic to-do lists, and a dash of spontaneity to make your journey awesome. Time to be the ninja of your own time saga!"
},
{
"source_sentence": "Title: The Role of Innovation in Business Growth\n\nInnovation drives business growth by fostering creativity, problem-solving, and adaptation to changing markets. Embracing innovation allows companies to stay competitive and seize new opportunities for expansion.",
"target_sentence": "Title: Innovation Playground: Where Ideas Run Wild\n\nHey innovation explorers! Welcome to the playground of creative thinking. We're all about wild ideas, fearless experiments, and making innovation a ton of fun. Let's get our creative juices flowing and change the game!"
},
{
"source_sentence": "Title: The Significance of Volunteering in Community Building\n\nVolunteering plays a crucial role in building strong and resilient communities. It fosters social cohesion, empathy, and a sense of responsibility among citizens. Engaging in volunteer work contributes to the well-being of both individuals and communities.",
"target_sentence": "Title: Volunteer Vibes: Spreading Goodness One Act at a Time\n\nHey changemakers! It's time to roll up our sleeves and make a positive impact. We're all about community love, random acts of kindness, and making volunteering a breeze. Join the volunteer party, and let's spread those good vibes!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence on Future Industries\n\nArtificial Intelligence (AI) is reshaping industries by automating tasks, improving efficiency, and driving innovation. Its applications in healthcare, finance, and manufacturing are transforming the way businesses operate and compete.",
"target_sentence": "Title: AI Adventures: Embracing the Tech Marvels\n\nHey tech enthusiasts! It's time to dive headfirst into the AI wonderland. We've got chatbots, smart homes, and gadgets galore to explore. Let's make friends with the robots and have a blast in the world of artificial intelligence!"
},
{
"source_sentence": "Title: The Role of Empathy in Healthcare\n\nEmpathy is a fundamental aspect of patient care in healthcare settings. Healthcare professionals who demonstrate empathy build trust, improve patient outcomes, and provide holistic support to those in their care.",
"target_sentence": "Title: Caring with Heart: Navigating the Healthcare Journey\n\nHey health heroes! It's time to talk about the awesome power of empathy in healthcare. We're all about bedside chats, healing vibes, and making the patient experience as cozy as a warm blanket. Let's bring compassion back to healthcare!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity in Protecting Data\n\nCybersecurity is vital for safeguarding sensitive data from online threats. Robust cybersecurity measures, including encryption and intrusion detection, are essential to protect individuals and organizations from data breaches and cyberattacks.",
"target_sentence": "Title: Digital Defenders: A Fun Guide to Cybersecurity\n\nHey digital defenders! Let's don our virtual capes and protect the digital realm. We've got cybersecurity tips, password heroes, and cyber adventures to embark on. It's time to be the guardians of the digital galaxy!"
},
{
"source_sentence": "Title: The Role of Leadership in Team Dynamics\n\nEffective leadership is essential for fostering collaboration and productivity within teams. Leaders who inspire trust, set clear goals, and encourage open communication contribute to successful team dynamics and overall organizational success.",
"target_sentence": "Title: Leading with Style: Crafting Your Leadership Journey\n\nHey future leaders! It's time to don your leadership capes and embark on a stylish journey. We're all about teamwork, high-fives, and making leadership an epic adventure. Let's lead with flair and have a blast along the way!"
},
{
"source_sentence": "Title: The Significance of Environmental Conservation\n\nEnvironmental conservation is vital for preserving the planet's natural resources and biodiversity. Sustainable practices, habitat preservation, and reduced pollution are key components of successful conservation efforts.",
"target_sentence": "Title: Green Living: Making Every Day Earth Day\n\nHey eco-warriors! It's time to put on your green superhero cape and go on an eco-adventure. We're all about recycling, tree hugging, and making Mother Earth proud. Let's be eco-champions and have a blast while doing it!"
},
{
"source_sentence": "Title: The Role of Ethics in Scientific Research\n\nEthical conduct in scientific research is fundamental for maintaining the integrity of the scientific community. Adhering to ethical standards ensures transparency, credibility, and the responsible pursuit of knowledge.",
"target_sentence": "Title: Science Ethics 101: Navigating the Research Maze\n\nHey future scientists! Let's break down the world of ethical research. We're all about lab adventures, responsible discoveries, and making science a barrel of fun. Join the research party, and let's explore the ethical frontier!"
},
{
"source_sentence": "Title: The Importance of Financial Literacy\n\nFinancial literacy empowers individuals to make informed financial decisions. It includes understanding concepts such as budgeting, saving, investing, and debt management. Developing financial literacy is crucial for long-term financial stability.",
"target_sentence": "Title: Money Matters: The Fun Guide to Financial Freedom\n\nHey financial wizards! It's time to embark on a financial journey filled with money wisdom, budgeting hacks, and wealth-building quests. We're all about making finances fun and helping you take charge of your money story!"
},
{
"source_sentence": "Title: The Impact of Stress on Mental Health\n\nChronic stress can have detrimental effects on mental health, leading to anxiety, depression, and other disorders. Managing stress through relaxation techniques, exercise, and seeking support is crucial for maintaining mental well-being.",
"target_sentence": "Title: Stress-Free Living: Your Guide to Inner Zen\n\nHey stress warriors! Let's talk about keeping the calm in the chaos. We're all about stress-busting tips, relaxation rituals, and making zen a way of life. Join the stress-free party, and let's conquer life's challenges together!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is revolutionizing the healthcare industry by enhancing diagnosis, treatment, and patient care. AI-driven technologies, such as predictive analytics and medical imaging, are improving healthcare outcomes.",
"target_sentence": "Title: HealthTech Revolution: Embracing AI in Healthcare\n\nHey health innovators! Let's explore the world of AI in healthcare. We're all about smart apps, wearable wonders, and making healthcare a breeze. Join the tech health party, and let's keep you in tip-top shape!"
},
{
"source_sentence": "Title: The Significance of Gender Equality in the Workplace\n\nGender equality in the workplace is essential for promoting diversity and inclusion. Ensuring equal opportunities, pay, and treatment for all employees contributes to a fair and productive work environment.",
"target_sentence": "Title: Work It, Equal Style: Navigating the Workplace Jungle\n\nHey workplace warriors! It's time to talk about equal opportunities, high-fives, and making the office a fantastic place for everyone. We're all about diversity, inclusion, and having a blast in the world of work. Join the equality party!"
},
{
"source_sentence": "Title: The Impact of Renewable Energy on Sustainable Development\n\nThe adoption of renewable energy sources, such as solar and wind power, plays a pivotal role in achieving sustainable development goals. Renewable energy reduces greenhouse gas emissions, fosters energy independence, and promotes environmental conservation.",
"target_sentence": "Title: Go Green, Go Cool: Your Guide to Renewable Energy\n\nHey eco-champions! It's time to talk about clean energy and making the planet a cooler place. We're all about solar smiles, wind-powered high-fives, and embracing the renewable energy revolution. Join the green energy party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity in a Digital World\n\nIn today's digital era, cybersecurity is critical for safeguarding sensitive information from cyber threats. Protecting data, networks, and systems is essential to ensure privacy, security, and business continuity.",
"target_sentence": "Title: Digital Defenders Unite: A Fun Guide to Cybersecurity\n\nHey digital superheroes! It's time to don your virtual capes and embark on a cyber-adventure. We've got cybersecurity tips, hacker showdowns, and digital escapades to make online safety a blast. Join the digital defense party!"
},
{
"source_sentence": "Title: The Role of Emotional Intelligence in Leadership\n\nEmotional intelligence (EQ) is a crucial trait for effective leadership. Leaders with high EQ can navigate complex emotions, build strong relationships, and inspire teams to achieve their best results.",
"target_sentence": "Title: Leading with Heart: The EQ Guide to Leadership\n\nHey future leaders! Let's chat about emotional intelligence and its superpowers in leadership. We're all about heart-centered leadership, empathy adventures, and making emotional intelligence your leadership super-skill. Join the EQ leadership party!"
},
{
"source_sentence": "Title: The Significance of Cultural Diversity in Education\n\nCultural diversity enriches the educational experience by exposing students to different perspectives and ideas. In diverse learning environments, students develop a global mindset, tolerance, and the ability to collaborate effectively in a multicultural world.",
"target_sentence": "Title: Embrace the World: Your Guide to Cultural Education\n\nHey global learners! Let's talk about the exciting world of cultural diversity in education. We're all about global friendships, international feasts, and making learning a passport to fun. Join the cultural education party!"
},
{
"source_sentence": "Title: The Role of Critical Thinking in Problem-Solving\n\nCritical thinking is a vital skill for effective problem-solving. It involves analyzing information, evaluating evidence, and making informed decisions. Developing critical thinking abilities enhances one's ability to address complex challenges.",
"target_sentence": "Title: Think Smarter, Not Harder: Mastering Critical Thinking\n\nHey critical thinkers! It's time to unlock the secrets of sharp minds and problem-solving prowess. We're all about brainpower boosts, thinking games, and making critical thinking a breeze. Join the critical thinking party!"
},
{
"source_sentence": "Title: The Importance of Time Management for Students\n\nEffective time management is a key skill for student success. Balancing academic responsibilities, extracurricular activities, and personal life requires organization and prioritization. Time management helps students achieve academic goals while maintaining a healthy lifestyle.",
"target_sentence": "Title: Student Life Hacks: Mastering Time Like a Pro\n\nHey student superheroes! It's time to unlock the secrets of time management and rule your student universe. We've got study tips, time-saving tricks, and life hacks to make your student journey a blast. Join the time management party!"
},
{
"source_sentence": "Title: The Role of Teamwork in Project Success\n\nEffective teamwork is essential for achieving project success. When team members collaborate, share ideas, and communicate effectively, they increase productivity, creativity, and the likelihood of meeting project goals within deadlines.",
"target_sentence": "Title: Team Power: Navigating the Collaboration Highway\n\nHey team players! It's time to rev up your teamwork engines and hit the collaboration highway. We're all about high-fives, brainstorming bonanzas, and making teamwork an adventure. Join the collaboration party!"
},
{
"source_sentence": "Title: The Impact of Climate Change on Global Economies\n\nClimate change poses significant risks to global economies through increased costs, supply chain disruptions, and damage to infrastructure. Mitigating climate change and transitioning to sustainable practices are essential for economic resilience.",
"target_sentence": "Title: Greening the World: Your Guide to Climate Action\n\nHey climate champions! Let's dive into the world of climate change and how we can make a difference. We're all about eco-fun, planet-saving tips, and embracing the green revolution. Join the climate action party!"
},
{
"source_sentence": "Title: The Importance of Early Childhood Education\n\nEarly childhood education plays a crucial role in a child's cognitive, social, and emotional development. High-quality early education programs provide a strong foundation for lifelong learning and academic success.",
"target_sentence": "Title: Tiny Explorers: Nurturing Young Minds with Fun\n\nHey early educators! It's time to embrace the joys of teaching tiny tots. We're all about storytime adventures, finger-painting masterpieces, and making early education a delightful journey. Join the early education party!"
},
{
"source_sentence": "Title: The Significance of Effective Communication in Business\n\nEffective communication is a cornerstone of successful business operations. Clear and efficient communication fosters collaboration, minimizes misunderstandings, and enhances decision-making within organizations, ultimately leading to improved profitability and growth.",
"target_sentence": "Title: Business Talk: Your Guide to Rocking Communication\n\nHey future business moguls! It's time to dive into the world of effective communication in business. We're all about elevator pitches, networking high-fives, and making business talk a breeze. Join the business communication party!"
},
{
"source_sentence": "Title: The Role of Diversity and Inclusion in Workplace Innovation\n\nDiversity and inclusion in the workplace lead to increased innovation and creativity. When organizations embrace diverse perspectives, backgrounds, and experiences, they are better equipped to develop groundbreaking ideas, products, and solutions.",
"target_sentence": "Title: Inclusivity Matters: Sparking Innovation in the Workplace\n\nHey innovation enthusiasts! Let's talk about how diversity and inclusion fuel creativity. We're all about idea parties, collaborative sparks, and making workplace innovation a blast. Join the workplace innovation party!"
},
{
"source_sentence": "Title: The Impact of Technology on Education\n\nTechnology has transformed the education landscape by enabling online learning, personalized instruction, and global connectivity. Embracing technology in education enhances access to knowledge and equips learners with 21st-century skills.",
"target_sentence": "Title: Tech-Savvy Learning: Your Guide to Digital Education\n\nHey digital learners! Let's dive into the world of educational technology and online learning. We're all about virtual field trips, interactive lessons, and making education a tech-fueled adventure. Join the digital education party!"
},
{
"source_sentence": "Title: The Importance of Work-Life Balance for Employee Well-being\n\nMaintaining a healthy work-life balance is essential for employee well-being and productivity. Organizations that prioritize work-life balance create a positive work environment, reduce burnout, and retain motivated and satisfied employees.",
"target_sentence": "Title: Life Hacks: Mastering the Art of Work-Life Harmony\n\nHey life enthusiasts! It's time to uncover the secrets of balancing work and play. We're all about relaxation rituals, productivity tips, and making work-life balance a joyful dance. Join the work-life harmony party!"
},
{
"source_sentence": "Title: The Role of Ethics in Artificial Intelligence\n\nEthical considerations are paramount in the development and deployment of artificial intelligence (AI) systems. Ensuring AI aligns with ethical principles prevents harmful consequences and promotes responsible AI innovation.",
"target_sentence": "Title: Ethical AI: Navigating the Moral Tech Landscape\n\nHey tech ethicists! Let's dive into the fascinating world of AI ethics and responsible technology. We're all about ethical coding, digital dilemmas, and making tech a force for good. Join the ethical AI party!"
},
{
"source_sentence": "Title: The Significance of Financial Planning for Retirement\n\nEffective financial planning is crucial for a secure retirement. Planning for retirement involves setting financial goals, creating a savings strategy, and considering investment options to ensure a comfortable and worry-free retirement.",
"target_sentence": "Title: Retire Happy: Your Guide to Financial Freedom\n\nHey future retirees! It's time to embark on a retirement adventure filled with financial wisdom and relaxation plans. We're all about dream vacations, retirement bucket lists, and making financial planning a joyful journey. Join the retirement party!"
},
{
"source_sentence": "Title: The Role of Digital Marketing in Business Growth\n\nDigital marketing is a cornerstone of modern business growth strategies. Leveraging digital channels, such as social media and online advertising, helps businesses reach wider audiences, increase brand visibility, and drive revenue.",
"target_sentence": "Title: Digital Domination: Your Guide to Winning Online\n\nHey digital marketers! Let's dive into the exciting world of digital marketing and online presence. We're all about social media success, content wizardry, and making digital marketing a thrilling adventure. Join the online marketing party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence on Customer Service\n\nArtificial Intelligence (AI) is transforming customer service by enabling chatbots, virtual assistants, and personalized customer experiences. AI-powered solutions enhance efficiency, reduce response times, and improve customer satisfaction.",
"target_sentence": "Title: AI Superheroes: Navigating Customer Service with Tech\n\nHey customer service champs! It's time to explore the world of AI-powered support. We're all about quick resolutions, happy customers, and making AI your customer service sidekick. Join the customer service tech party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity in a Connected World\n\nCybersecurity is paramount in an increasingly connected world. Protecting sensitive information, safeguarding networks, and ensuring data privacy are critical components of a secure digital landscape.",
"target_sentence": "Title: Digital Defenders Unite: Your Guide to Cybersecurity\n\nHey digital defenders! Let's talk about the exciting world of cybersecurity and how you can protect yourself online. We're all about safe browsing, strong passwords, and making cybersecurity an adventure. Join the digital defense party!"
},
{
"source_sentence": "Title: The Role of Environmental Conservation in Preserving Biodiversity\n\nEnvironmental conservation efforts are essential for preserving the planet's biodiversity. Protecting natural habitats, reducing pollution, and promoting sustainable practices are crucial steps toward ensuring the survival of diverse species and ecosystems.",
"target_sentence": "Title: Earth Heroes Unite: Your Guide to Conservation\n\nHey eco-warriors! It's time to embark on a conservation adventure to protect our planet's biodiversity. We're all about eco-quests, nature explorations, and making conservation a thrilling journey. Join the Earth-saving party!"
},
{
"source_sentence": "Title: The Impact of AI in Healthcare\n\nArtificial Intelligence (AI) is revolutionizing the healthcare industry with applications in diagnosis, treatment, and patient care. AI-driven technologies, such as predictive analytics and medical imaging, are enhancing healthcare outcomes and patient experiences.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health innovators! Let's dive into the world of AI-powered healthcare. We're all about smart apps, wearable wonders, and making healthcare a high-tech adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Importance of Gender Equality in the Workplace\n\nGender equality is a cornerstone of fostering a fair and inclusive workplace. Equal opportunities, pay, and treatment for all employees contribute to a positive work environment and organizational success.",
"target_sentence": "Title: Work It, Equal Style: Your Guide to Workplace Fairness\n\nHey workplace champions! It's time to dive into the world of workplace equality and inclusion. We're all about high-fives, diversity celebrations, and making the office a fantastic place for everyone. Join the workplace fairness party!"
},
{
"source_sentence": "Title: The Significance of Renewable Energy in Addressing Climate Change\n\nRenewable energy sources, such as solar and wind power, play a critical role in mitigating climate change. Transitioning to renewable energy reduces greenhouse gas emissions, promotes sustainability, and supports global efforts to combat climate change.",
"target_sentence": "Title: Go Green, Go Fun: Your Guide to Renewable Energy\n\nHey eco-enthusiasts! It's time to put on your green superhero cape and dive into the world of renewable energy. We're all about solar smiles, wind-powered high-fives, and embracing the renewable energy revolution. Join the green energy party!"
},
{
"source_sentence": "Title: The Role of Cybersecurity in Protecting Digital Assets\n\nCybersecurity is essential for safeguarding digital assets from threats and attacks. Protecting data, networks, and devices ensures data privacy, business continuity, and the integrity of digital operations.",
"target_sentence": "Title: Cybersecurity Demystified: Your Guide to Digital Protection\n\nHey digital defenders! Let's unravel the secrets of cybersecurity and keep your online world safe. We're all about strong passwords, threat showdowns, and making cybersecurity a fun adventure. Join the digital defense party!"
},
{
"source_sentence": "Title: The Impact of Stress on Mental Health\n\nChronic stress can have detrimental effects on mental health, leading to anxiety, depression, and other disorders. Managing stress through relaxation techniques, self-care, and seeking support is crucial for maintaining mental well-being.",
"target_sentence": "Title: Stress-Free Living: Your Guide to Inner Peace\n\nHey stress warriors! Let's chat about keeping calm in the chaos of life. We're all about stress-busting tips, relaxation rituals, and making zen a way of life. Join the stress-free living party!"
},
{
"source_sentence": "Title: The Role of Emotional Intelligence in Leadership\n\nEmotional intelligence (EQ) is a crucial skill for effective leadership. Leaders with high EQ can navigate complex emotions, build strong relationships, and inspire teams to achieve their best results.",
"target_sentence": "Title: Leading with Heart: The EQ Guide to Leadership\n\nHey future leaders! Let's dive into the world of emotional intelligence and its superpowers in leadership. We're all about heart-centered leadership, empathy adventures, and making emotional intelligence your leadership super-skill. Join the EQ leadership party!"
},
{
"source_sentence": "Title: The Significance of Early Childhood Education\n\nEarly childhood education plays a crucial role in a child's cognitive, social, and emotional development. High-quality early education programs provide a strong foundation for lifelong learning and academic success.",
"target_sentence": "Title: Tiny Explorers: Nurturing Young Minds with Fun\n\nHey early educators! It's time to embrace the joys of teaching tiny tots. We're all about storytime adventures, finger-painting masterpieces, and making early education a delightful journey. Join the early education party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Education\n\nArtificial Intelligence (AI) is transforming education with personalized learning, adaptive assessments, and data-driven insights. AI-powered educational tools enhance student engagement and improve learning outcomes.",
"target_sentence": "Title: Tech-Savvy Learning: Your Guide to Digital Education\n\nHey digital learners! Let's dive into the world of educational technology and online learning. We're all about virtual field trips, interactive lessons, and making education a tech-fueled adventure. Join the digital education party!"
},
{
"source_sentence": "Title: The Importance of Time Management for Workplace Productivity\n\nEffective time management is crucial for maximizing workplace productivity. Organizing tasks, setting priorities, and minimizing distractions allow employees to complete tasks efficiently and meet deadlines consistently.",
"target_sentence": "Title: Work Smarter, Not Harder: Your Guide to Time Mastery\n\nHey productivity enthusiasts! It's time to unlock the secrets of time management and conquer your workday. We're all about productivity hacks, time-saving tricks, and making work a breeze. Join the time mastery party!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is revolutionizing healthcare by improving diagnostics, treatment recommendations, and patient care. AI-driven technologies offer the potential to enhance medical outcomes and streamline healthcare processes.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare. We're all about smart health apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Significance of Cultural Sensitivity in Global Business\n\nCultural sensitivity is essential for successful global business operations. Understanding and respecting cultural differences enhance communication, build trust, and foster positive relationships with international partners and customers.",
"target_sentence": "Title: Global Business 101: Your Guide to Cultural Savvy\n\nHey global entrepreneurs! It's time to embark on a cultural adventure in the business world. We're all about cross-cultural collaborations, international friendships, and making global business a fun journey. Join the cultural savvy party!"
},
{
"source_sentence": "Title: The Importance of Ethical Leadership in Business\n\nEthical leadership is paramount for maintaining integrity and trust within organizations. Leaders who prioritize ethics set a positive example for employees, promote a culture of honesty, and uphold moral standards in decision-making.",
"target_sentence": "Title: Leading with Heart: Your Guide to Ethical Leadership\n\nHey ethical leaders! Let's dive into the world of leadership with integrity and heart. We're all about doing the right thing, fostering trust, and making ethical leadership a joyful journey. Join the ethical leadership party!"
},
{
"source_sentence": "Title: The Significance of Mental Health Awareness in the Workplace\n\nMental health awareness is essential for creating a supportive workplace environment. Recognizing the importance of mental well-being, reducing stigma, and providing resources for employees promote mental health and overall job satisfaction.",
"target_sentence": "Title: Mental Wellness Matters: Your Guide to Workplace Balance\n\nHey mental health advocates! It's time to explore the world of well-being at work. We're all about self-care rituals, stress-busting tips, and making mental health a priority. Join the workplace wellness party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Manufacturing\n\nArtificial Intelligence (AI) is transforming the manufacturing industry through automation, predictive maintenance, and quality control. AI-driven processes improve efficiency, reduce costs, and enhance overall manufacturing performance.",
"target_sentence": "Title: Manufacturing Magic: Your Guide to AI-Powered Production\n\nHey manufacturing wizards! Let's dive into the world of AI-driven production and smart factories. We're all about automation wonders, quality assurance fun, and making manufacturing a high-tech adventure. Join the manufacturing magic party!"
},
{
"source_sentence": "Title: The Role of Renewable Energy in a Sustainable Future\n\nRenewable energy sources, such as wind and solar power, are pivotal for achieving a sustainable future. Transitioning to clean energy reduces carbon emissions, mitigates climate change, and promotes environmental stewardship.",
"target_sentence": "Title: Go Green, Go Fun: Your Guide to Renewable Energy\n\nHey eco-enthusiasts! It's time to dive into the world of renewable energy and sustainability. We're all about solar smiles, wind-powered high-fives, and embracing the green energy revolution. Join the clean energy party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Finance\n\nArtificial Intelligence (AI) is revolutionizing the finance industry through automated trading, risk assessment, and fraud detection. AI-driven algorithms enhance decision-making, optimize investments, and improve financial outcomes.",
"target_sentence": "Title: FinTech Fun: Your Guide to Smart Money Management\n\nHey finance aficionados! Let's dive into the world of AI-powered finance and smart investments. We're all about digital wallets, budgeting made easy, and making finance a tech-savvy adventure. Join the FinTech fun party!"
},
{
"source_sentence": "Title: The Importance of Diversity and Inclusion in Tech\n\nDiversity and inclusion are critical for fostering innovation and creativity in the tech industry. Embracing diverse perspectives, backgrounds, and experiences leads to better problem-solving, product development, and organizational growth.",
"target_sentence": "Title: Tech Trailblazers: Your Guide to a Diverse and Inclusive Tech Community\n\nHey tech enthusiasts! It's time to join the diverse and inclusive tech revolution. We're all about coding camaraderie, innovation celebrations, and making the tech world a welcoming place for everyone. Join the tech diversity party!"
},
{
"source_sentence": "Title: The Significance of Sustainable Agriculture in Ensuring Food Security\n\nSustainable agriculture practices are vital for ensuring food security and protecting the environment. Implementing sustainable farming techniques reduces soil degradation, conserves water resources, and promotes long-term food production.",
"target_sentence": "Title: Eco-Farming Adventure: Your Guide to Sustainable Agriculture\n\nHey eco-farmers! It's time to embrace the world of sustainable agriculture and grow your food with love. We're all about organic harvests, green practices, and making farming an eco-friendly journey. Join the sustainable farming party!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Transportation\n\nArtificial Intelligence (AI) is reshaping the transportation industry through autonomous vehicles, traffic optimization, and route planning. AI-driven transportation systems enhance safety, efficiency, and overall mobility.",
"target_sentence": "Title: Smart Commutes: Your Guide to AI-Powered Transportation\n\nHey travelers of the future! Let's dive into the world of AI-driven transportation and stress-free journeys. We're all about self-driving car joyrides, smart traffic solutions, and making transportation an effortless adventure. Join the transportainment party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity Awareness in the Digital Age\n\nCybersecurity awareness is essential for individuals and organizations to protect against online threats. Understanding common cyber risks, practicing safe online behaviors, and staying informed about the latest security trends are key to maintaining digital safety.",
"target_sentence": "Title: Cyber Savvy 101: Your Guide to Digital Security\n\nHey digital explorers! It's time to navigate the cyber realm with confidence. We're all about secure passwords, vigilant clicks, and making cybersecurity a digital adventure. Join the cyber-savvy party!"
},
{
"source_sentence": "Title: The Significance of Green Building Practices in Sustainable Construction\n\nGreen building practices are crucial for sustainable construction and reducing environmental impact. Utilizing eco-friendly materials, energy-efficient designs, and sustainable construction methods contribute to a more environmentally responsible built environment.",
"target_sentence": "Title: Building the Future: Your Guide to Green Construction\n\nHey eco-builders! It's time to embrace sustainable construction and create a greener world. We're all about eco-brick adventures, solar panel smiles, and making construction a planet-friendly journey. Join the green construction party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Customer Service\n\nArtificial Intelligence (AI) is revolutionizing customer service through chatbots, virtual assistants, and data-driven support. AI-powered solutions enhance response times, reduce customer wait times, and improve overall service quality.",
"target_sentence": "Title: Customer Care 2.0: Your Guide to AI-Powered Service\n\nHey customer care champions! Let's dive into the world of AI-enhanced customer service and elevate customer experiences. We're all about instant resolutions, happy customers, and making support a tech-savvy adventure. Join the customer care 2.0 party!"
},
{
"source_sentence": "Title: The Importance of Data Privacy in the Digital Age\n\nData privacy is essential for protecting personal information in today's digital landscape. Implementing strong privacy practices, securing data storage, and respecting user consent are fundamental in maintaining data privacy and security.",
"target_sentence": "Title: Data Guardians Unite: Your Guide to Online Privacy\n\nHey digital guardians! It's time to safeguard your online presence and protect your digital identity. We're all about privacy settings, secure browsing, and making data privacy a digital adventure. Join the data privacy party!"
},
{
"source_sentence": "Title: The Role of Renewable Energy in Reducing Carbon Emissions\n\nRenewable energy sources, such as solar and wind power, are key to reducing carbon emissions and combating climate change. Transitioning to clean energy is essential to achieving global emissions reduction targets.",
"target_sentence": "Title: Go Green, Go Fun: Your Guide to Renewable Energy\n\nHey eco-enthusiasts! It's time to dive into the world of renewable energy and sustainability. We're all about solar smiles, wind-powered high-fives, and embracing the green energy revolution. Join the clean energy party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is reshaping the healthcare industry through improved diagnostics, predictive analytics, and personalized treatment plans. AI-driven solutions offer the potential to revolutionize patient care and medical research.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare and wellness. We're all about smart health apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity in the Digital Age\n\nCybersecurity is paramount for safeguarding digital assets and sensitive information in today's interconnected world. Implementing robust security measures, educating employees, and staying vigilant against cyber threats are essential for protecting data integrity.",
"target_sentence": "Title: Cybersecurity Demystified: Your Guide to Digital Defense\n\nHey digital defenders! Let's unravel the secrets of cybersecurity and keep your online world safe. We're all about strong passwords, threat showdowns, and making cybersecurity a fun adventure. Join the digital defense party!"
},
{
"source_sentence": "Title: The Role of Emotional Intelligence in Leadership\n\nEmotional intelligence (EQ) is a critical competency for effective leadership. Leaders with high EQ can navigate complex emotions, foster teamwork, and inspire their teams to achieve outstanding results.",
"target_sentence": "Title: Leading with Heart: Your Guide to Emotional Intelligence\n\nHey future leaders! Let's dive into the world of emotional intelligence and leadership with heart. We're all about empathy, relationship building, and making emotional intelligence a superpower for leaders. Join the EQ leadership party!"
},
{
"source_sentence": "Title: The Significance of Early Childhood Education\n\nEarly childhood education plays a pivotal role in a child's cognitive and social development. High-quality early education programs provide a solid foundation for lifelong learning and academic success.",
"target_sentence": "Title: Tiny Explorers: Nurturing Young Minds with Fun\n\nHey early educators! It's time to embark on a joyful journey into the world of early childhood education. We're all about storytime adventures, finger-painting masterpieces, and making early education an unforgettable adventure. Join the early education party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Education\n\nArtificial Intelligence (AI) is reshaping education through personalized learning, adaptive assessments, and data-driven insights. AI-powered educational tools enhance student engagement and academic performance.",
"target_sentence": "Title: Tech-Savvy Learning: Your Guide to Digital Education\n\nHey digital learners! Let's dive into the world of AI-powered education and online learning. We're all about virtual field trips, interactive lessons, and making education a tech-savvy adventure. Join the digital education party!"
},
{
"source_sentence": "Title: The Importance of Time Management for Workplace Productivity\n\nEffective time management is a cornerstone of workplace productivity. Organizing tasks, setting priorities, and minimizing distractions enable employees to work efficiently and meet deadlines consistently.",
"target_sentence": "Title: Work Smarter, Not Harder: Your Guide to Time Mastery\n\nHey productivity enthusiasts! Let's unlock the secrets of time management and conquer the workday with ease. We're all about productivity hacks, time-saving tricks, and making work a breeze. Join the time mastery party!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is transforming healthcare through improved diagnostics, treatment recommendations, and patient care. AI-driven technologies offer the potential to enhance medical outcomes and streamline healthcare processes.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare and wellness. We're all about smart health apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Significance of Cultural Sensitivity in Global Business\n\nCultural sensitivity is essential for successful global business operations. Understanding and respecting cultural differences enhance communication, build trust, and foster positive relationships with international partners and customers.",
"target_sentence": "Title: Global Business 101: Your Guide to Cultural Savvy\n\nHey global entrepreneurs! It's time to embark on a cultural adventure in the business world. We're all about cross-cultural collaborations, international friendships, and making global business a fun journey. Join the cultural savvy party!"
},
{
"source_sentence": "Title: The Role of Renewable Energy in a Sustainable Future\n\nRenewable energy sources, such as wind and solar power, are pivotal for achieving a sustainable future. Transitioning to clean energy reduces carbon emissions, mitigates climate change, and promotes environmental stewardship.",
"target_sentence": "Title: Go Green, Go Fun: Your Guide to Renewable Energy\n\nHey eco-enthusiasts! It's time to unlock the secrets of renewable energy and join the sustainability party. We're all about solar smiles, wind-powered high-fives, and embracing the green energy revolution. Join the clean energy party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Finance\n\nArtificial Intelligence (AI) is revolutionizing the finance industry through automated trading, risk assessment, and fraud detection. AI-driven algorithms enhance decision-making, optimize investments, and improve financial outcomes.",
"target_sentence": "Title: FinTech Fun: Your Guide to Smart Money Management\n\nHey finance aficionados! Let's dive into the world of AI-powered finance and smart investments. We're all about digital wallets, budgeting made easy, and making finance a tech-savvy adventure. Join the FinTech fun party!"
},
{
"source_sentence": "Title: The Importance of Diversity and Inclusion in Tech\n\nDiversity and inclusion are critical for fostering innovation and creativity in the tech industry. Embracing diverse perspectives, backgrounds, and experiences leads to better problem-solving, product development, and organizational growth.",
"target_sentence": "Title: Tech Trailblazers: Your Guide to a Diverse and Inclusive Tech Community\n\nHey tech enthusiasts! It's time to join the diverse and inclusive tech revolution. We're all about coding camaraderie, innovation celebrations, and making the tech world a welcoming place for everyone. Join the tech diversity party!"
},
{
"source_sentence": "Title: The Significance of Sustainable Agriculture in Ensuring Food Security\n\nSustainable agriculture practices are vital for ensuring food security and protecting the environment. Implementing sustainable farming techniques reduces soil degradation, conserves water resources, and promotes long-term food production.",
"target_sentence": "Title: Eco-Farming Adventure: Your Guide to Sustainable Agriculture\n\nHey eco-farmers! It's time to embark on an eco-friendly adventure in sustainable agriculture. We're all about organic harvests, green practices, and making farming a planet-friendly journey. Join the sustainable farming party!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Transportation\n\nArtificial Intelligence (AI) is reshaping the transportation industry through autonomous vehicles, traffic optimization, and route planning. AI-driven transportation systems enhance safety, efficiency, and overall mobility.",
"target_sentence": "Title: Smart Commutes: Your Guide to AI-Powered Transportation\n\nHey travelers of the future! Let's dive into the world of AI-driven transportation and stress-free journeys. We're all about self-driving car joyrides, smart traffic solutions, and making transportation an effortless adventure. Join the transportainment party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity Awareness in the Digital Age\n\nCybersecurity awareness is essential for individuals and organizations to protect against online threats. Understanding common cyber risks, practicing safe online behaviors, and staying informed about the latest security trends are key to maintaining digital safety.",
"target_sentence": "Title: Cyber Savvy 101: Your Guide to Digital Security\n\nHey digital explorers! It's time to navigate the cyber realm with confidence. We're all about secure passwords, vigilant clicks, and making cybersecurity a digital adventure. Join the cyber-savvy party!"
},
{
"source_sentence": "Title: The Role of Green Building Practices in Sustainable Construction\n\nGreen building practices are essential for sustainable construction and reducing environmental impact. Utilizing eco-friendly materials, energy-efficient designs, and sustainable construction methods contribute to a more environmentally responsible built environment.",
"target_sentence": "Title: Building the Future: Your Guide to Green Construction\n\nHey eco-builders! It's time to join the sustainability revolution in construction. We're all about eco-brick adventures, solar panel smiles, and making construction a planet-friendly journey. Join the green construction party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Customer Service\n\nArtificial Intelligence (AI) is reshaping customer service through chatbots, virtual assistants, and data-driven support. AI-powered solutions enhance response times, reduce customer wait times, and improve overall service quality.",
"target_sentence": "Title: Customer Care 2.0: Your Guide to AI-Powered Service\n\nHey customer care champions! Let's dive into the world of AI-enhanced customer service and elevate customer experiences. We're all about instant resolutions, happy customers, and making support a tech-savvy adventure. Join the customer care 2.0 party!"
},
{
"source_sentence": "Title: The Importance of Data Privacy in the Digital Age\n\nData privacy is paramount for protecting personal information in today's digital landscape. Implementing strong privacy practices, securing data storage, and respecting user consent are fundamental in maintaining data privacy and security.",
"target_sentence": "Title: Data Guardians Unite: Your Guide to Online Privacy\n\nHey digital guardians! It's time to safeguard your online presence and protect your digital identity. We're all about privacy settings, secure browsing, and making data privacy a digital adventure. Join the data privacy party!"
},
{
"source_sentence": "Title: The Role of Renewable Energy in Reducing Carbon Emissions\n\nRenewable energy sources, such as solar and wind power, are key to reducing carbon emissions and combating climate change. Transitioning to clean energy is essential to achieving global emissions reduction targets.",
"target_sentence": "Title: Go Green, Go Fun: Your Guide to Renewable Energy\n\nHey eco-enthusiasts! It's time to embrace sustainable energy and create a greener world. We're all about eco-brick adventures, solar panel smiles, and making renewable energy an exciting journey. Join the clean energy party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is reshaping the healthcare industry through improved diagnostics, predictive analytics, and personalized treatment plans. AI-driven solutions offer the potential to revolutionize patient care and medical research.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare and wellness. We're all about self-care apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity in the Digital Age\n\nCybersecurity is paramount for safeguarding digital assets and sensitive information in today's interconnected world. Implementing robust security measures, educating employees, and staying vigilant against cyber threats are essential for protecting data integrity.",
"target_sentence": "Title: Cybersecurity Demystified: Your Guide to Digital Defense\n\nHey digital defenders! Let's unravel the mysteries of cybersecurity and keep your online world safe. We're all about strong passwords, threat showdowns, and making cybersecurity a fun adventure. Join the digital defense party!"
},
{
"source_sentence": "Title: The Role of Emotional Intelligence in Leadership\n\nEmotional intelligence (EQ) is a critical competency for effective leadership. Leaders with high EQ can navigate complex emotions, foster teamwork, and inspire their teams to achieve outstanding results.",
"target_sentence": "Title: Leading with Heart: Your Guide to Emotional Intelligence\n\nHey future leaders! Let's dive into the world of emotional intelligence and leadership with heart. We're all about empathy, relationship building, and making emotional intelligence a superpower for leaders. Join the EQ leadership party!"
},
{
"source_sentence": "Title: The Significance of Early Childhood Education\n\nEarly childhood education plays a pivotal role in a child's cognitive and social development. High-quality early education programs provide a solid foundation for lifelong learning and academic success.",
"target_sentence": "Title: Tiny Explorers: Nurturing Young Minds with Fun\n\nHey early educators! It's time to embark on a joyful journey into the world of early childhood education. We're all about storytime adventures, finger-painting masterpieces, and making early education an unforgettable adventure. Join the early education party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Education\n\nArtificial Intelligence (AI) is reshaping education through personalized learning, adaptive assessments, and data-driven insights. AI-powered educational tools enhance student engagement and academic performance.",
"target_sentence": "Title: Tech-Savvy Learning: Your Guide to Digital Education\n\nHey digital learners! Let's dive into the world of AI-powered education and online learning. We're all about virtual field trips, interactive lessons, and making education a tech-savvy adventure. Join the digital education party!"
},
{
"source_sentence": "Title: The Importance of Time Management for Workplace Productivity\n\nEffective time management is a cornerstone of workplace productivity. Organizing tasks, setting priorities, and minimizing distractions enable employees to work efficiently and meet deadlines consistently.",
"target_sentence": "Title: Work Smarter, Not Harder: Your Guide to Time Mastery\n\nHey productivity enthusiasts! Let's unlock the secrets of time management and conquer the workday with ease. We're all about productivity hacks, time-saving tricks, and making work a breeze. Join the time mastery party!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is transforming healthcare through improved diagnostics, treatment recommendations, and patient care. AI-driven technologies offer the potential to enhance medical outcomes and streamline healthcare processes.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare and wellness. We're all about smart health apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Significance of Cultural Sensitivity in Global Business\n\nCultural sensitivity is essential for successful global business operations. Understanding and respecting cultural differences enhance communication, build trust, and foster positive relationships with international partners and customers.",
"target_sentence": "Title: Global Business 101: Your Guide to Cultural Savvy\n\nHey global entrepreneurs! It's time to embark on a cultural adventure in the business world. We're all about cross-cultural collaborations, international friendships, and making global business a fun journey. Join the cultural savvy party!"
},
{
"source_sentence": "Title: The Role of Green Technology in Environmental Sustainability\n\nGreen technology plays a pivotal role in achieving environmental sustainability goals. Innovations such as renewable energy, energy-efficient appliances, and eco-friendly transportation contribute to reducing carbon footprints and preserving our planet.",
"target_sentence": "Title: Go Green, Go Fun: Your Guide to Eco-Tech\n\nHey eco-enthusiasts! It's time to dive into the world of green technology and embrace a sustainable future. We're all about green gadgets, energy-saving tips, and making tech a planet-friendly adventure. Join the eco-tech party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Transportation\n\nArtificial Intelligence (AI) is reshaping transportation through autonomous vehicles, traffic optimization, and smart infrastructure. AI-powered solutions enhance safety, reduce traffic congestion, and improve overall mobility.",
"target_sentence": "Title: Smart Commutes: Your Guide to AI-Powered Transportation\n\nHey travelers of the future! Let's dive into the world of AI-driven transportation and enjoy stress-free journeys. We're all about self-driving car adventures, smart traffic solutions, and making transportation an effortless ride. Join the transportainment party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity Awareness in the Digital Age\n\nCybersecurity awareness is crucial for protecting personal information and digital assets in today's interconnected world. Practicing safe online behavior, recognizing cyber threats, and implementing security best practices are key to staying secure in the digital age.",
"target_sentence": "Title: Digital Defender's Guide: Your Passport to Cybersecurity\n\nHey digital defenders! It's time to navigate the digital world with confidence. We're all about secure passwords, vigilant clicks, and making cybersecurity a fun digital adventure. Join the cyber defense party!"
},
{
"source_sentence": "Title: The Role of Renewable Energy in Reducing Carbon Emissions\n\nRenewable energy sources, such as solar and wind power, are pivotal for reducing carbon emissions and mitigating climate change. Transitioning to clean energy is a fundamental step in achieving a sustainable and eco-friendly future.",
"target_sentence": "Title: Go Green, Go Fun: Your Guide to Renewable Energy\n\nHey eco-enthusiasts! It's time to embrace sustainable energy and create a greener world. We're all about eco-brick adventures, solar panel smiles, and making renewable energy an exciting journey. Join the clean energy party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is revolutionizing healthcare through improved diagnostics, predictive analytics, and personalized patient care. AI-driven solutions have the potential to enhance medical outcomes and streamline healthcare processes.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare and wellness. We're all about self-care apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Significance of Cultural Sensitivity in Global Business\n\nCultural sensitivity is a cornerstone of successful global business operations. Understanding and respecting cultural differences facilitate effective communication, build trust, and foster positive relationships with international partners and customers.",
"target_sentence": "Title: Global Business 101: Your Guide to Cultural Savvy\n\nHey global entrepreneurs! It's time to embark on a cultural adventure in the business world. We're all about cross-cultural collaborations, international friendships, and making global business a fun journey. Join the cultural savvy party!"
},
{
"source_sentence": "Title: The Role of Green Technology in Sustainable Urban Development\n\nGreen technology plays a pivotal role in promoting sustainable urban development. Innovations such as eco-friendly building materials, energy-efficient infrastructure, and smart city solutions contribute to creating environmentally conscious and livable cities.",
"target_sentence": "Title: Building Sustainable Cities: Your Guide to Green Urban Living\n\nHey urban enthusiasts! It's time to embrace sustainability and create greener, smarter cities. We're all about eco-friendly neighborhoods, energy-saving innovations, and making urban living an exciting and eco-conscious journey. Join the green urban living party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Transportation\n\nArtificial Intelligence (AI) is reshaping transportation through autonomous vehicles, traffic optimization, and smart infrastructure. AI-powered solutions enhance safety, reduce congestion, and improve the overall efficiency of transportation systems.",
"target_sentence": "Title: Smart Commutes: Your Guide to AI-Powered Transportation\n\nHey travelers of the future! Let's dive into the world of AI-driven transportation and enjoy stress-free journeys. We're all about self-driving car adventures, smart traffic solutions, and making transportation an effortless ride. Join the transportainment party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity Awareness in the Digital Age\n\nCybersecurity awareness is paramount for protecting personal information and digital assets in today's interconnected world. Implementing strong security practices, recognizing online threats, and staying informed about cybersecurity trends are essential for maintaining online safety.",
"target_sentence": "Title: Digital Defender's Guide: Your Passport to Cybersecurity\n\nHey digital defenders! It's time to navigate the digital world with confidence. We're all about secure passwords, vigilant clicks, and making cybersecurity a fun digital adventure. Join the cyber defense party!"
},
{
"source_sentence": "Title: The Role of Renewable Energy in Sustainable Agriculture\n\nRenewable energy sources, such as solar and wind power, play a vital role in promoting sustainable agriculture. The adoption of clean energy solutions enhances farm efficiency, reduces carbon footprints, and supports environmentally conscious farming practices.",
"target_sentence": "Title: Farming the Future: Your Guide to Sustainable Agriculture\n\nHey eco-farmers! It's time to embark on a sustainable farming journey powered by renewable energy. We're all about sunny fields, wind-whispered harvests, and making agriculture an environmentally friendly adventure. Join the sustainable farming party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Education\n\nArtificial Intelligence (AI) is revolutionizing education through personalized learning, adaptive assessments, and data-driven insights. AI-powered educational tools are transforming the way students learn and educators teach.",
"target_sentence": "Title: Learning in the Digital Age: Your Guide to AI-Powered Education\n\nHey digital learners! Let's dive into the world of AI-enhanced education and experience learning like never before. We're all about interactive lessons, smart study buddies, and making education a tech-savvy adventure. Join the digital education party!"
},
{
"source_sentence": "Title: The Importance of Emotional Intelligence in Leadership\n\nEmotional Intelligence (EQ) is a critical factor in effective leadership. Leaders with high EQ can navigate complex emotions, build strong relationships, and inspire their teams to achieve exceptional results.",
"target_sentence": "Title: Leading with Empathy: Your Guide to Emotional Intelligence\n\nHey future leaders! It's time to embrace the power of emotional intelligence and lead with empathy. We're all about connecting on a deeper level, fostering team harmony, and making leadership a journey of understanding. Join the EQ leadership party!"
},
{
"source_sentence": "Title: The Role of Green Technology in Climate Change Mitigation\n\nGreen technology is instrumental in mitigating climate change. Technologies such as carbon capture, sustainable agriculture practices, and renewable energy sources are crucial in reducing greenhouse gas emissions and preserving our planet's future.",
"target_sentence": "Title: Green Living 101: Your Guide to Eco-Friendly Tech\n\nHey eco-enthusiasts! It's time to embrace green technology and create a sustainable world. We're all about eco-gadgets, sustainable living tips, and making technology a friendlier ally for our planet. Join the eco-friendly tech party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is transforming healthcare through enhanced diagnostics, predictive analytics, and personalized patient care. AI-driven solutions have the potential to revolutionize medical practices, improve patient outcomes, and streamline healthcare operations.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare and wellness. We're all about self-care apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Significance of Cultural Sensitivity in Global Business\n\nCultural sensitivity is paramount for successful global business operations. Understanding and respecting cultural differences foster effective communication, build trust, and enable positive relationships with international partners and customers.",
"target_sentence": "Title: Global Business Explorers: Your Guide to Cross-Cultural Success\n\nHey global entrepreneurs! It's time to embark on a cultural adventure in the business world. We're all about cross-cultural collaborations, international friendships, and making global business an exciting journey. Join the cross-cultural success party!"
},
{
"source_sentence": "Title: The Impact of Renewable Energy on Environmental Sustainability\n\nRenewable energy sources, such as solar and wind power, have a profound impact on enhancing environmental sustainability. The adoption of clean energy technologies contributes to reducing carbon emissions and mitigating climate change.",
"target_sentence": "Title: Going Green with Renewable Energy: A Fun Ride\n\nHey folks! Let's talk about going green with renewable energy. It's like upgrading our planet's ride to an eco-friendly rollercoaster. Solar panels and wind turbines are the cool kids on the block!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Healthcare\n\nArtificial Intelligence (AI) is revolutionizing the healthcare sector through improved diagnostics, predictive analytics, and personalized patient care. AI-driven solutions are enhancing medical outcomes and optimizing healthcare operations.",
"target_sentence": "Title: HealthTech Revolution: Your Guide to AI in Healthcare\n\nHey health tech enthusiasts! Let's dive into the world of AI-powered healthcare and wellness. We're all about self-care apps, AI-assisted diagnostics, and making healthcare a tech-savvy adventure. Join the HealthTech revolution party!"
},
{
"source_sentence": "Title: The Importance of Cultural Sensitivity in Global Business\n\nCultural sensitivity is paramount for successful global business operations. Understanding and respecting cultural differences facilitate effective communication, build trust, and enable positive relationships with international partners and customers.",
"target_sentence": "Title: Global Business Explorers: Your Guide to Cross-Cultural Success\n\nHey global entrepreneurs! It's time to embark on a cultural adventure in the business world. We're all about cross-cultural collaborations, international friendships, and making global business an exciting journey. Join the cross-cultural success party!"
},
{
"source_sentence": "Title: The Significance of Emotional Intelligence in Leadership\n\nEmotional Intelligence (EQ) is a critical factor in effective leadership. Leaders with high EQ can navigate complex emotions, build strong relationships, and inspire their teams to achieve exceptional results.",
"target_sentence": "Title: Leading with Empathy: Your Guide to Emotional Intelligence\n\nHey future leaders! It's time to embrace the power of emotional intelligence and lead with empathy. We're all about connecting on a deeper level, fostering team harmony, and making leadership a journey of understanding. Join the EQ leadership party!"
},
{
"source_sentence": "Title: The Role of Green Technology in Sustainable Agriculture\n\nGreen technology plays a pivotal role in promoting sustainable agriculture. Innovations such as eco-friendly building materials, energy-efficient infrastructure, and smart city solutions contribute to creating environmentally conscious and livable cities.",
"target_sentence": "Title: Farming the Future: Your Guide to Sustainable Agriculture\n\nHey eco-farmers! It's time to embark on a sustainable farming journey powered by renewable energy. We're all about sunny fields, wind-whispered harvests, and making agriculture an environmentally friendly adventure. Join the sustainable farming party!"
},
{
"source_sentence": "Title: The Influence of Technology on Modern Education\n\nTechnology has become a driving force in modern education. Digital tools, online learning platforms, and adaptive assessments have transformed the way students access and engage with educational content, leading to improved learning outcomes.",
"target_sentence": "Title: Learning in the Digital Age: Your Guide to Tech-Savvy Education\n\nHey digital learners! Let's dive into the world of tech-powered education and experience learning like never before. We're all about interactive lessons, smart study buddies, and making education a tech-savvy adventure. Join the digital education party!"
},
{
"source_sentence": "Title: The Advancements in Artificial Intelligence and Their Impact on Industry\n\nRecent advancements in artificial intelligence (AI) are reshaping various industries. AI-driven automation, predictive analytics, and natural language processing are revolutionizing manufacturing, healthcare, finance, and beyond, driving efficiency and innovation.",
"target_sentence": "Title: Industry 4.0: Your Guide to the AI Revolution\n\nHey industry innovators! It's time to ride the wave of AI revolutionizing our workplaces. We're all about smart factories, data-driven decisions, and making industry a tech-driven adventure. Join the Industry 4.0 party!"
},
{
"source_sentence": "Title: The Role of Sustainable Practices in Corporate Social Responsibility\n\nIn the realm of corporate social responsibility (CSR), sustainable practices have gained prominence. Companies that prioritize sustainability through eco-friendly initiatives, ethical sourcing, and reduced carbon footprints not only benefit the environment but also enhance their reputation and profitability.",
"target_sentence": "Title: Eco-Conscious Corporations: Your Guide to CSR Adventures\n\nHey corporate world changemakers! Let's embark on an eco-conscious journey in the realm of corporate social responsibility. We're all about sustainable strategies, ethical values, and making CSR a socially responsible adventure. Join the CSR party!"
},
{
"source_sentence": "Title: The Influence of Green Building Design on Sustainable Architecture\n\nGreen building design principles have a profound influence on sustainable architecture. Features such as energy-efficient insulation, natural lighting, and renewable materials are essential elements in constructing environmentally friendly and energy-efficient buildings.",
"target_sentence": "Title: Sustainable Architecture Adventure: Your Guide to Eco-Friendly Buildings\n\nHey architecture enthusiasts! Let's embark on an eco-friendly journey through sustainable architecture. We're all about green rooftops, nature-inspired designs, and making buildings an environmentally conscious adventure. Join the sustainable architecture party!"
},
{
"source_sentence": "Title: The Digital Transformation of Financial Services\n\nThe financial services industry is undergoing a significant digital transformation. Fueled by advancements in fintech, online banking, and blockchain technology, this evolution is changing how consumers access and manage their finances, leading to greater convenience and efficiency.",
"target_sentence": "Title: Money Matters 2.0: Your Guide to Digital Finance\n\nHey savvy spenders! Let's dive into the world of digital finance and make managing money a breeze. We're all about mobile wallets, online investments, and making finance a tech-savvy adventure. Join the digital finance party!"
},
{
"source_sentence": "Title: The Role of Renewable Energy in Reducing Carbon Footprints\n\nRenewable energy sources play a vital role in reducing carbon footprints. Solar, wind, and hydropower technologies offer sustainable alternatives to fossil fuels, significantly contributing to the global effort to combat climate change.",
"target_sentence": "Title: Go Green, Stay Cool: Your Guide to Renewable Energy\n\nHey eco-warriors! It's time to go green and keep it cool with renewable energy. We're all about sunny solutions, wind-powered fun, and making sustainability an adventure. Join the green energy party!"
},
{
"source_sentence": "Title: The Impact of E-Learning on Education Accessibility\n\nE-learning has had a profound impact on improving education accessibility. With online courses, virtual classrooms, and mobile learning apps, students worldwide can access quality education regardless of geographical or physical constraints.",
"target_sentence": "Title: Learning Unleashed: Your Guide to E-Learning Adventures\n\nHey digital scholars! Let's dive into the world of e-learning and unlock a new era of education. We're all about virtual classrooms, interactive lessons, and making learning an online adventure. Join the e-learning party!"
},
{
"source_sentence": "Title: The Importance of Diversity and Inclusion in the Workplace\n\nDiversity and inclusion are crucial elements of a modern workplace. Fostering a diverse workforce and creating an inclusive environment result in higher productivity, innovation, and employee satisfaction, contributing to overall organizational success.",
"target_sentence": "Title: Embrace Diversity at Work: Your Guide to Inclusive Excellence\n\nHey workplace champions! Let's embrace diversity and create an inclusive culture that rocks. We're all about diverse teams, equal opportunities, and making work a place where everyone thrives. Join the inclusion party!"
},
{
"source_sentence": "Title: The Evolution of Artificial Intelligence in Healthcare Diagnosis\n\nThe field of artificial intelligence in healthcare diagnosis has evolved significantly. AI-powered systems now offer accurate and timely diagnostics, aiding healthcare professionals in delivering improved patient care and outcomes.",
"target_sentence": "Title: AI-Enhanced Healthcare: Your Guide to Diagnostics with a Dash of Tech\n\nHey health tech enthusiasts! Let's dive into the world of AI-enhanced healthcare and experience diagnostics with a tech twist. We're all about smart diagnoses, digital health buddies, and making healthcare a tech-savvy adventure. Join the health tech party!"
},
{
"source_sentence": "Title: The Significance of Sustainable Practices in Urban Planning\n\nSustainable practices are of paramount significance in urban planning. Eco-friendly architecture, efficient transportation systems, and green spaces contribute to creating livable cities that prioritize environmental responsibility and quality of life.",
"target_sentence": "Title: Sustainable Cities 101: Your Guide to Greener Urban Living\n\nHey city dwellers! Let's embark on a journey toward greener urban living. We're all about eco-friendly neighborhoods, bike-friendly streets, and making cities a sustainable adventure. Join the urban sustainability party!"
},
{
"source_sentence": "Title: The Role of Technology in Enhancing Customer Experiences\n\nTechnology plays a pivotal role in enhancing customer experiences. From personalized recommendations to efficient customer support systems, businesses leverage technology to create positive interactions and build long-lasting customer relationships.",
"target_sentence": "Title: Tech-Savvy Customer Delight: Your Guide to Exceptional Experiences\n\nHey happy customers! Let's dive into the world of tech-savvy delight and experience customer service like never before. We're all about personalized interactions, speedy resolutions, and making your experience a tech-driven adventure. Join the customer delight party!"
},
{
"source_sentence": "Title: The Importance of Ethical Leadership in Business\n\nEthical leadership holds great importance in the world of business. Leaders who prioritize ethics and moral values set a strong example for their teams, fostering trust, integrity, and a culture of ethical decision-making within their organizations.",
"target_sentence": "Title: Lead with Integrity: Your Guide to Ethical Leadership\n\nHey ethical leaders! It's time to lead with integrity and create a workplace that values ethics and trust. We're all about transparency, fair decisions, and making leadership an ethical adventure. Join the ethical leadership party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence on Financial Markets\n\nArtificial Intelligence (AI) is transforming financial markets with predictive analytics and algorithmic trading. AI-driven insights enable investors and traders to make data-informed decisions, contributing to market efficiency and volatility reduction.",
"target_sentence": "Title: Money Moves with AI: Your Guide to Investing in the Digital Age\n\nHey future investors! Let's dive into the world of AI-powered finance and make money moves like never before. We're all about smart portfolios, robo-advisors, and making investing a tech-savvy adventure. Join the finance tech party!"
},
{
"source_sentence": "Title: The Role of Data Analytics in Healthcare Decision-Making\n\nData analytics plays a critical role in healthcare decision-making. Through the analysis of patient data, healthcare providers can optimize treatment plans, reduce costs, and improve patient outcomes, ushering in a new era of evidence-based medicine.",
"target_sentence": "Title: Healthy Insights: Your Guide to Data-Driven Healthcare\n\nHey wellness enthusiasts! Let's dive into the world of data-driven healthcare and uncover the secrets to a healthier you. We're all about personalized treatments, digital health trackers, and making healthcare a data-driven adventure. Join the health data party!"
},
{
"source_sentence": "Title: The Importance of Sustainable Agriculture in Ensuring Food Security\n\nSustainable agriculture plays a pivotal role in ensuring global food security. By practicing environmentally friendly farming methods, we can meet the growing demand for food while preserving natural resources and reducing the impact of agriculture on the environment.",
"target_sentence": "Title: Farming for the Future: Your Guide to Sustainable Agriculture\n\nHey eco-farmers! Let's embark on a sustainable agriculture journey and grow the future. We're all about organic crops, eco-friendly practices, and making farming an environmentally conscious adventure. Join the sustainable farming party!"
},
{
"source_sentence": "Title: The Impact of Artificial Intelligence on Supply Chain Management\n\nArtificial Intelligence (AI) is revolutionizing supply chain management by optimizing logistics, demand forecasting, and inventory control. AI-powered solutions enhance efficiency, reduce costs, and improve the overall resilience of supply chains.",
"target_sentence": "Title: Smart Supply Chains: Your Guide to Streamlined Logistics\n\nHey supply chain enthusiasts! Let's dive into the world of smart logistics and make supply chains as smooth as a well-oiled machine. We're all about on-time deliveries, efficient warehouses, and making logistics a tech-savvy adventure. Join the supply chain party!"
},
{
"source_sentence": "Title: The Role of Machine Learning in Predictive Maintenance\n\nMachine learning is instrumental in predictive maintenance, allowing industries to predict equipment failures and perform maintenance proactively. This approach minimizes downtime, reduces maintenance costs, and improves overall operational efficiency.",
"target_sentence": "Title: Predictive Maintenance Made Fun: Your Guide to Machine Learning Magic\n\nHey maintenance magicians! Let's dive into the world of predictive maintenance with the magic of machine learning. We're all about equipment longevity, data-driven upkeep, and making maintenance a tech-savvy adventure. Join the maintenance magic party!"
},
{
"source_sentence": "Title: The Importance of Cybersecurity in Protecting Digital Assets\n\nCybersecurity plays a crucial role in safeguarding digital assets and sensitive information. Robust security measures, encryption, and vigilant monitoring are essential components of protecting against cyber threats and data breaches.",
"target_sentence": "Title: Defend Your Data: Your Guide to Cybersecurity Superpowers\n\nHey digital defenders! Let's dive into the world of cybersecurity and become the guardians of the digital realm. We're all about secure connections, vigilant monitoring, and making cybersecurity a cyber-adventure. Join the cybersecurity superhero party!"
},
{
"source_sentence": "Title: The Impact of Green Technology on Sustainable Living\n\nGreen technology is making a significant impact on sustainable living by reducing energy consumption and environmental impact. Sustainable practices, such as energy-efficient appliances and eco-friendly transportation, are becoming integral to modern lifestyles.",
"target_sentence": "Title: Living Green, Living Well: Your Guide to Sustainable Lifestyle\n\nHey eco-enthusiasts! Let's embark on a journey toward sustainable living and make green choices a way of life. We're all about eco-conscious homes, eco-friendly commuting, and making sustainability a lifestyle adventure. Join the sustainable living party!"
},
{
"source_sentence": "Title: The Future of Artificial Intelligence in Healthcare Diagnosis\n\nThe future of healthcare diagnosis lies in the continued advancement of Artificial Intelligence (AI). AI-driven diagnostic tools, predictive analytics, and personalized treatments will reshape the medical landscape, offering more precise and effective healthcare solutions.",
"target_sentence": "Title: Your Health, Your Way: Your Guide to AI-Powered Healthcare\n\nHey health enthusiasts! Let's dive into the world of AI-powered healthcare and take charge of our well-being. We're all about virtual check-ups, personalized treatment plans, and making healthcare an AI-driven adventure. Join the healthcare tech party!"
},
{
"source_sentence": "Title: The Significance of Sustainable Tourism in Preserving Natural Beauty\n\nSustainable tourism is of utmost significance in preserving the natural beauty of our planet. Eco-friendly accommodations, responsible travel practices, and community engagement efforts ensure that future generations can enjoy the world's stunning landscapes and cultural treasures.",
"target_sentence": "Title: Go Green, Travel Smart: Your Guide to Eco-Friendly Adventures\n\nHey wanderlust explorers! Let's embark on eco-friendly adventures and discover the world responsibly. We're all about eco-responsible travel, authentic experiences, and making tourism a sustainable adventure. Join the eco-tourism party!"
},
{
"source_sentence": "Title: The Role of Big Data Analytics in Business Decision-Making\n\nBig Data analytics is playing a pivotal role in shaping business decision-making. By extracting insights from vast data sets, organizations gain a competitive edge, improve operational efficiency, and drive innovation across various industry sectors.",
"target_sentence": "Title: Mastering Business with Big Data: Your Guide to Data-Driven Success\n\nHey business enthusiasts! Let's dive into the world of data-driven success and unlock the potential of Big Data. We're all about actionable insights, smart decisions, and making business a data-driven adventure. Join the data-driven business party!"
},
{
"source_sentence": "Title: The Impact of Digital Marketing on Brand Awareness\n\nDigital marketing has a profound impact on brand awareness in the digital age. Strategic online campaigns, social media engagement, and personalized content enhance a brand's visibility, connecting businesses with their target audiences more effectively.",
"target_sentence": "Title: Boost Your Brand Online: Your Guide to Digital Marketing Adventures\n\nHey brand builders! Let's dive into the world of digital marketing and skyrocket your brand's visibility online. We're all about engaging content, social media buzz, and making marketing a digital adventure. Join the digital marketing party!"
},
{
"source_sentence": "Title: The Future of Electric Vehicles in Sustainable Transportation\n\nIn the realm of sustainable transportation, the future belongs to electric vehicles (EVs). With advancements in battery technology and charging infrastructure, EVs are poised to become the cornerstone of eco-friendly commuting. They offer reduced emissions, lower operational costs, and a cleaner, greener tomorrow.",
"target_sentence": "Title: Ride the Green Wave: Your Guide to Electric Vehicle Adventures\n\nHey eco-travelers! Let's ride the green wave and embark on electric vehicle adventures. We're all about emission-free journeys, fast-charging pit stops, and making sustainable commuting an electrifying adventure. Join the EV party!"
},
{
"source_sentence": "Title: The Importance of Biodiversity in Ecosystem Resilience\n\nBiodiversity is a linchpin of ecosystem resilience. Diverse ecosystems are better equipped to withstand environmental changes and disturbances. They provide critical services such as pollination, water purification, and climate regulation, making biodiversity conservation paramount to the health of our planet.",
"target_sentence": "Title: Explore the Wild Side: Your Guide to Biodiversity Conservation\n\nHey nature enthusiasts! Let's explore the wild side and dive into biodiversity conservation. We're all about protecting species, preserving habitats, and making nature conservation an adventure. Join the biodiversity party!"
},
{
"source_sentence": "Title: The Role of Artificial Intelligence in Environmental Monitoring\n\nArtificial Intelligence (AI) has a pivotal role in environmental monitoring. AI-driven systems analyze vast data sets from satellites, sensors, and drones to track changes in ecosystems, air quality, and natural disasters. These insights enable informed decision-making for environmental protection and disaster management.",
"target_sentence": "Title: Eco Guardians Unite: Your Guide to AI-Powered Environmental Stewardship\n\nHey eco-warriors! Let's unite as eco guardians and use AI to protect our planet. We're all about tracking wildlife, monitoring air quality, and making environmental stewardship a tech-savvy adventure. Join the eco guardians party!"
},
{
"source_sentence": "Title: The Influence of Social Media on Modern Politics\n\nSocial media platforms have a significant influence on modern politics. They serve as powerful tools for political campaigns, allowing candidates to reach a broad audience, engage with voters, and disseminate their policy messages. Social media has reshaped political communication and campaigning strategies.",
"target_sentence": "Title: Social Politics 101: Your Guide to Navigating the Digital Political Landscape\n\nHey political enthusiasts! Let's dive into the world of social politics and discover the digital realm of political engagement. We're all about online activism, political discourse, and making politics a digital adventure. Join the social politics party!"
}
] |
anilev6/up_titles_unmasked | ---
language:
- uk
source_datasets:
- shamotskyi/ukr_pravda_2y
license: cc-by-nc-4.0
multilinguality: monolingual
--- |
AlienKevin/serif_klee | ---
license: cc0-1.0
---
|
tdooms/TinyStories | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1906450758
num_examples: 2119719
- name: validation
num_bytes: 19259378
num_examples: 21990
download_size: 998699331
dataset_size: 1925710136
---
This is simply a clone of https://huggingface.co/datasets/roneneldan/TinyStories but with the non-ascii characters removed.
There seems to be some corruption in the original dataset.
> with a friendly “hi†and the deer said “helloâ€
This monumental feat has been achieved using the following meticulously crafted 3 lines of code.
```python
dataset = load_dataset("roneneldan/TinyStories", split="train")
filtered = [s.encode('ascii', 'ignore').decode('ascii') for s in dataset["text"]]
Dataset.from_dict(dict(text=filtered)).push_to_hub("TinyStories")
``` |
one-sec-cv12/chunk_183 | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: train
num_bytes: 13593577392.875
num_examples: 141529
download_size: 11628180168
dataset_size: 13593577392.875
---
# Dataset Card for "chunk_183"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Gbssreejith/type_missed | ---
dataset_info:
features:
- name: image
dtype: image
- name: ground_truth
dtype: string
splits:
- name: train
num_bytes: 26509033.0
num_examples: 108
- name: test
num_bytes: 2003519.0
num_examples: 9
- name: val
num_bytes: 1027003.0
num_examples: 4
download_size: 29027252
dataset_size: 29539555.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: val
path: data/val-*
---
|
open-llm-leaderboard/details_gmonsoon__TinyWombat-1.8b-Chat-v.1 | ---
pretty_name: Evaluation run of gmonsoon/TinyWombat-1.8b-Chat-v.1
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [gmonsoon/TinyWombat-1.8b-Chat-v.1](https://huggingface.co/gmonsoon/TinyWombat-1.8b-Chat-v.1)\
\ 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_gmonsoon__TinyWombat-1.8b-Chat-v.1\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-11T04:55:23.780993](https://huggingface.co/datasets/open-llm-leaderboard/details_gmonsoon__TinyWombat-1.8b-Chat-v.1/blob/main/results_2024-03-11T04-55-23.780993.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\": 0.25710602340506805,\n\
\ \"acc_stderr\": 0.030766411399344894,\n \"acc_norm\": 0.2582279199117647,\n\
\ \"acc_norm_stderr\": 0.03151621376688307,\n \"mc1\": 0.24479804161566707,\n\
\ \"mc1_stderr\": 0.01505186948671501,\n \"mc2\": 0.3974416004992906,\n\
\ \"mc2_stderr\": 0.014049379782918344\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.3003412969283277,\n \"acc_stderr\": 0.013395909309957012,\n\
\ \"acc_norm\": 0.3293515358361775,\n \"acc_norm_stderr\": 0.013734057652635474\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4439354710217088,\n\
\ \"acc_stderr\": 0.004958314114266491,\n \"acc_norm\": 0.5888269269069907,\n\
\ \"acc_norm_stderr\": 0.00491040915013549\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768081,\n \
\ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768081\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.26666666666666666,\n\
\ \"acc_stderr\": 0.03820169914517904,\n \"acc_norm\": 0.26666666666666666,\n\
\ \"acc_norm_stderr\": 0.03820169914517904\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.17763157894736842,\n \"acc_stderr\": 0.031103182383123415,\n\
\ \"acc_norm\": 0.17763157894736842,\n \"acc_norm_stderr\": 0.031103182383123415\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.27,\n\
\ \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.27,\n \
\ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.24150943396226415,\n \"acc_stderr\": 0.02634148037111836,\n\
\ \"acc_norm\": 0.24150943396226415,\n \"acc_norm_stderr\": 0.02634148037111836\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2222222222222222,\n\
\ \"acc_stderr\": 0.03476590104304134,\n \"acc_norm\": 0.2222222222222222,\n\
\ \"acc_norm_stderr\": 0.03476590104304134\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.23,\n \"acc_stderr\": 0.042295258468165044,\n \
\ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.042295258468165044\n \
\ },\n \"harness|hendrycksTest-college_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-college_mathematics|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-college_medicine|5\": {\n \"acc\": 0.20809248554913296,\n\
\ \"acc_stderr\": 0.0309528902177499,\n \"acc_norm\": 0.20809248554913296,\n\
\ \"acc_norm_stderr\": 0.0309528902177499\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.04158307533083286,\n\
\ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.04158307533083286\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.22,\n \"acc_stderr\": 0.04163331998932269,\n \"acc_norm\": 0.22,\n\
\ \"acc_norm_stderr\": 0.04163331998932269\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.28936170212765955,\n \"acc_stderr\": 0.02964400657700962,\n\
\ \"acc_norm\": 0.28936170212765955,\n \"acc_norm_stderr\": 0.02964400657700962\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2894736842105263,\n\
\ \"acc_stderr\": 0.04266339443159394,\n \"acc_norm\": 0.2894736842105263,\n\
\ \"acc_norm_stderr\": 0.04266339443159394\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.22758620689655173,\n \"acc_stderr\": 0.03493950380131183,\n\
\ \"acc_norm\": 0.22758620689655173,\n \"acc_norm_stderr\": 0.03493950380131183\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.25925925925925924,\n \"acc_stderr\": 0.02256989707491841,\n \"\
acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.02256989707491841\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.19047619047619047,\n\
\ \"acc_stderr\": 0.03512207412302053,\n \"acc_norm\": 0.19047619047619047,\n\
\ \"acc_norm_stderr\": 0.03512207412302053\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \
\ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.22580645161290322,\n\
\ \"acc_stderr\": 0.023785577884181012,\n \"acc_norm\": 0.22580645161290322,\n\
\ \"acc_norm_stderr\": 0.023785577884181012\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.27586206896551724,\n \"acc_stderr\": 0.031447125816782405,\n\
\ \"acc_norm\": 0.27586206896551724,\n \"acc_norm_stderr\": 0.031447125816782405\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \"acc_norm\"\
: 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.2545454545454545,\n \"acc_stderr\": 0.0340150671524904,\n\
\ \"acc_norm\": 0.2545454545454545,\n \"acc_norm_stderr\": 0.0340150671524904\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.23232323232323232,\n \"acc_stderr\": 0.030088629490217483,\n \"\
acc_norm\": 0.23232323232323232,\n \"acc_norm_stderr\": 0.030088629490217483\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.21761658031088082,\n \"acc_stderr\": 0.029778663037752947,\n\
\ \"acc_norm\": 0.21761658031088082,\n \"acc_norm_stderr\": 0.029778663037752947\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.2794871794871795,\n \"acc_stderr\": 0.022752388839776823,\n\
\ \"acc_norm\": 0.2794871794871795,\n \"acc_norm_stderr\": 0.022752388839776823\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.25555555555555554,\n \"acc_stderr\": 0.02659393910184409,\n \
\ \"acc_norm\": 0.25555555555555554,\n \"acc_norm_stderr\": 0.02659393910184409\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.23529411764705882,\n \"acc_stderr\": 0.027553614467863804,\n\
\ \"acc_norm\": 0.23529411764705882,\n \"acc_norm_stderr\": 0.027553614467863804\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.2251655629139073,\n \"acc_stderr\": 0.03410435282008936,\n \"\
acc_norm\": 0.2251655629139073,\n \"acc_norm_stderr\": 0.03410435282008936\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.24220183486238533,\n \"acc_stderr\": 0.018368176306598618,\n \"\
acc_norm\": 0.24220183486238533,\n \"acc_norm_stderr\": 0.018368176306598618\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.4722222222222222,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\
: 0.4722222222222222,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\
\ \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.2107843137254902,\n\
\ \"acc_stderr\": 0.028626547912437406,\n \"acc_norm\": 0.2107843137254902,\n\
\ \"acc_norm_stderr\": 0.028626547912437406\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\
: {\n \"acc\": 0.25738396624472576,\n \"acc_stderr\": 0.028458820991460295,\n\
\ \"acc_norm\": 0.25738396624472576,\n \"acc_norm_stderr\": 0.028458820991460295\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.3632286995515695,\n\
\ \"acc_stderr\": 0.032277904428505,\n \"acc_norm\": 0.3632286995515695,\n\
\ \"acc_norm_stderr\": 0.032277904428505\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.2748091603053435,\n \"acc_stderr\": 0.03915345408847835,\n\
\ \"acc_norm\": 0.2748091603053435,\n \"acc_norm_stderr\": 0.03915345408847835\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.21487603305785125,\n \"acc_stderr\": 0.037494924487096966,\n \"\
acc_norm\": 0.21487603305785125,\n \"acc_norm_stderr\": 0.037494924487096966\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.19444444444444445,\n\
\ \"acc_stderr\": 0.03826076324884865,\n \"acc_norm\": 0.19444444444444445,\n\
\ \"acc_norm_stderr\": 0.03826076324884865\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.2883435582822086,\n \"acc_stderr\": 0.035590395316173425,\n\
\ \"acc_norm\": 0.2883435582822086,\n \"acc_norm_stderr\": 0.035590395316173425\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.30357142857142855,\n\
\ \"acc_stderr\": 0.04364226155841044,\n \"acc_norm\": 0.30357142857142855,\n\
\ \"acc_norm_stderr\": 0.04364226155841044\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.21359223300970873,\n \"acc_stderr\": 0.04058042015646034,\n\
\ \"acc_norm\": 0.21359223300970873,\n \"acc_norm_stderr\": 0.04058042015646034\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.19230769230769232,\n\
\ \"acc_stderr\": 0.025819233256483713,\n \"acc_norm\": 0.19230769230769232,\n\
\ \"acc_norm_stderr\": 0.025819233256483713\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.2771392081736909,\n\
\ \"acc_stderr\": 0.01600563629412243,\n \"acc_norm\": 0.2771392081736909,\n\
\ \"acc_norm_stderr\": 0.01600563629412243\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.2023121387283237,\n \"acc_stderr\": 0.021628077380196134,\n\
\ \"acc_norm\": 0.2023121387283237,\n \"acc_norm_stderr\": 0.021628077380196134\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.22905027932960895,\n\
\ \"acc_stderr\": 0.014054314935614579,\n \"acc_norm\": 0.22905027932960895,\n\
\ \"acc_norm_stderr\": 0.014054314935614579\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.23529411764705882,\n \"acc_stderr\": 0.024288619466046116,\n\
\ \"acc_norm\": 0.23529411764705882,\n \"acc_norm_stderr\": 0.024288619466046116\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.21543408360128619,\n\
\ \"acc_stderr\": 0.02335022547547142,\n \"acc_norm\": 0.21543408360128619,\n\
\ \"acc_norm_stderr\": 0.02335022547547142\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.2808641975308642,\n \"acc_stderr\": 0.025006469755799208,\n\
\ \"acc_norm\": 0.2808641975308642,\n \"acc_norm_stderr\": 0.025006469755799208\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.24822695035460993,\n \"acc_stderr\": 0.0257700156442904,\n \
\ \"acc_norm\": 0.24822695035460993,\n \"acc_norm_stderr\": 0.0257700156442904\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.23402868318122555,\n\
\ \"acc_stderr\": 0.010813585552659684,\n \"acc_norm\": 0.23402868318122555,\n\
\ \"acc_norm_stderr\": 0.010813585552659684\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.3014705882352941,\n \"acc_stderr\": 0.027875982114273168,\n\
\ \"acc_norm\": 0.3014705882352941,\n \"acc_norm_stderr\": 0.027875982114273168\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.26143790849673204,\n \"acc_stderr\": 0.017776947157528034,\n \
\ \"acc_norm\": 0.26143790849673204,\n \"acc_norm_stderr\": 0.017776947157528034\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.2727272727272727,\n\
\ \"acc_stderr\": 0.04265792110940589,\n \"acc_norm\": 0.2727272727272727,\n\
\ \"acc_norm_stderr\": 0.04265792110940589\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.18775510204081633,\n \"acc_stderr\": 0.02500025603954621,\n\
\ \"acc_norm\": 0.18775510204081633,\n \"acc_norm_stderr\": 0.02500025603954621\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.23880597014925373,\n\
\ \"acc_stderr\": 0.030147775935409214,\n \"acc_norm\": 0.23880597014925373,\n\
\ \"acc_norm_stderr\": 0.030147775935409214\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.2891566265060241,\n\
\ \"acc_stderr\": 0.03529486801511115,\n \"acc_norm\": 0.2891566265060241,\n\
\ \"acc_norm_stderr\": 0.03529486801511115\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.21637426900584794,\n \"acc_stderr\": 0.03158149539338734,\n\
\ \"acc_norm\": 0.21637426900584794,\n \"acc_norm_stderr\": 0.03158149539338734\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.24479804161566707,\n\
\ \"mc1_stderr\": 0.01505186948671501,\n \"mc2\": 0.3974416004992906,\n\
\ \"mc2_stderr\": 0.014049379782918344\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6022099447513812,\n \"acc_stderr\": 0.013755743513749025\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.019711902956785442,\n \
\ \"acc_stderr\": 0.0038289829787357212\n }\n}\n```"
repo_url: https://huggingface.co/gmonsoon/TinyWombat-1.8b-Chat-v.1
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_11T04_55_23.780993
path:
- '**/details_harness|arc:challenge|25_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|gsm8k|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hellaswag|10_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-11T04-55-23.780993.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-11T04-55-23.780993.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- '**/details_harness|winogrande|5_2024-03-11T04-55-23.780993.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-11T04-55-23.780993.parquet'
- config_name: results
data_files:
- split: 2024_03_11T04_55_23.780993
path:
- results_2024-03-11T04-55-23.780993.parquet
- split: latest
path:
- results_2024-03-11T04-55-23.780993.parquet
---
# Dataset Card for Evaluation run of gmonsoon/TinyWombat-1.8b-Chat-v.1
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [gmonsoon/TinyWombat-1.8b-Chat-v.1](https://huggingface.co/gmonsoon/TinyWombat-1.8b-Chat-v.1) 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_gmonsoon__TinyWombat-1.8b-Chat-v.1",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-11T04:55:23.780993](https://huggingface.co/datasets/open-llm-leaderboard/details_gmonsoon__TinyWombat-1.8b-Chat-v.1/blob/main/results_2024-03-11T04-55-23.780993.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": 0.25710602340506805,
"acc_stderr": 0.030766411399344894,
"acc_norm": 0.2582279199117647,
"acc_norm_stderr": 0.03151621376688307,
"mc1": 0.24479804161566707,
"mc1_stderr": 0.01505186948671501,
"mc2": 0.3974416004992906,
"mc2_stderr": 0.014049379782918344
},
"harness|arc:challenge|25": {
"acc": 0.3003412969283277,
"acc_stderr": 0.013395909309957012,
"acc_norm": 0.3293515358361775,
"acc_norm_stderr": 0.013734057652635474
},
"harness|hellaswag|10": {
"acc": 0.4439354710217088,
"acc_stderr": 0.004958314114266491,
"acc_norm": 0.5888269269069907,
"acc_norm_stderr": 0.00491040915013549
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.26,
"acc_stderr": 0.04408440022768081,
"acc_norm": 0.26,
"acc_norm_stderr": 0.04408440022768081
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.26666666666666666,
"acc_stderr": 0.03820169914517904,
"acc_norm": 0.26666666666666666,
"acc_norm_stderr": 0.03820169914517904
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.17763157894736842,
"acc_stderr": 0.031103182383123415,
"acc_norm": 0.17763157894736842,
"acc_norm_stderr": 0.031103182383123415
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.27,
"acc_stderr": 0.044619604333847394,
"acc_norm": 0.27,
"acc_norm_stderr": 0.044619604333847394
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.24150943396226415,
"acc_stderr": 0.02634148037111836,
"acc_norm": 0.24150943396226415,
"acc_norm_stderr": 0.02634148037111836
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.2222222222222222,
"acc_stderr": 0.03476590104304134,
"acc_norm": 0.2222222222222222,
"acc_norm_stderr": 0.03476590104304134
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.23,
"acc_stderr": 0.042295258468165044,
"acc_norm": 0.23,
"acc_norm_stderr": 0.042295258468165044
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.25,
"acc_stderr": 0.04351941398892446,
"acc_norm": 0.25,
"acc_norm_stderr": 0.04351941398892446
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.28,
"acc_stderr": 0.045126085985421276,
"acc_norm": 0.28,
"acc_norm_stderr": 0.045126085985421276
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.20809248554913296,
"acc_stderr": 0.0309528902177499,
"acc_norm": 0.20809248554913296,
"acc_norm_stderr": 0.0309528902177499
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.22549019607843138,
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}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] |
joaoosdiufhosdeu/zefelipe | ---
license: openrail
---
|
salma-remyx/gym_equipment_dataset | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': lat_pulldown_machine
'1': leg_press_machine
'2': leg_raise_tower
splits:
- name: train
num_bytes: 1614251.0
num_examples: 150
download_size: 1616823
dataset_size: 1614251.0
---
# Dataset Card for "gym_equipment_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
arthurmluz/wikilingua_data-wiki_1024_results | ---
dataset_info:
features:
- name: id
dtype: int64
- name: text
dtype: string
- name: summary
dtype: string
- name: gen_summary
dtype: string
- name: rouge
struct:
- name: rouge1
dtype: float64
- name: rouge2
dtype: float64
- name: rougeL
dtype: float64
- name: rougeLsum
dtype: float64
- name: bert
struct:
- name: f1
sequence: float64
- name: hashcode
dtype: string
- name: precision
sequence: float64
- name: recall
sequence: float64
- name: moverScore
dtype: float64
splits:
- name: validation
num_bytes: 21885909
num_examples: 8165
download_size: 12842290
dataset_size: 21885909
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
---
# Dataset Card for "wikilingua_data-wiki_1024_results"
rouge= {'rouge1': 0.3547652574772463, 'rouge2': 0.1505956971978055, 'rougeL': 0.2785170891387953, 'rougeLsum': 0.2785170891387953}
bert= {'precision': 0.7906573472691691, 'recall': 0.7655439093188866, 'f1': 0.7771048831560097}
mover = 0.6245790568121278 |
truongghieu/Medical_P2 | ---
license: mit
task_categories:
- question-answering
language:
- en
tags:
- medical
pretty_name: 'Medical_chatbot '
size_categories:
- n<1K
--- |
ARTeLab/ilpost | ---
language:
- it
multilinguality:
- monolingual
size_categories:
- 10K<n<100k
task_categories:
- summarization
---
# Dataset Card for ilpost
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [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)
## Dataset Description
- **Homepage:** [Needs More Information]
- **Repository:** [Needs More Information]
- **Paper:** [Needs More Information]
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Needs More Information]
### Dataset Summary
IlPost dataset, containing news articles taken from IlPost.
There are two features:
- source: Input news article.
- target: Summary of the article.
### Supported Tasks and Leaderboards
- `abstractive-summarization`, `summarization`
### Languages
The text in the dataset is in Italian
## Dataset Structure
### Data Instances
[Needs More Information]
### Data Fields
[Needs More Information]
### Data Splits
[Needs More Information]
## Dataset Creation
### Curation Rationale
[Needs More Information]
### Source Data
#### Initial Data Collection and Normalization
[Needs More Information]
#### Who are the source language producers?
[Needs More Information]
### Annotations
#### Annotation process
[Needs More Information]
#### Who are the annotators?
[Needs More Information]
### Personal and Sensitive Information
[Needs More Information]
## Considerations for Using the Data
### Social Impact of Dataset
[Needs More Information]
### Discussion of Biases
[Needs More Information]
### Other Known Limitations
[Needs More Information]
## Additional Information
### Dataset Curators
[Needs More Information]
### Licensing Information
[Needs More Information]
### Citation Information
More details and results in [published work](https://www.mdpi.com/2078-2489/13/5/228)
```
@Article{info13050228,
AUTHOR = {Landro, Nicola and Gallo, Ignazio and La Grassa, Riccardo and Federici, Edoardo},
TITLE = {Two New Datasets for Italian-Language Abstractive Text Summarization},
JOURNAL = {Information},
VOLUME = {13},
YEAR = {2022},
NUMBER = {5},
ARTICLE-NUMBER = {228},
URL = {https://www.mdpi.com/2078-2489/13/5/228},
ISSN = {2078-2489},
ABSTRACT = {Text summarization aims to produce a short summary containing relevant parts from a given text. Due to the lack of data for abstractive summarization on low-resource languages such as Italian, we propose two new original datasets collected from two Italian news websites with multi-sentence summaries and corresponding articles, and from a dataset obtained by machine translation of a Spanish summarization dataset. These two datasets are currently the only two available in Italian for this task. To evaluate the quality of these two datasets, we used them to train a T5-base model and an mBART model, obtaining good results with both. To better evaluate the results obtained, we also compared the same models trained on automatically translated datasets, and the resulting summaries in the same training language, with the automatically translated summaries, which demonstrated the superiority of the models obtained from the proposed datasets.},
DOI = {10.3390/info13050228}
}
``` |
tuperte69/mix-closeup-lcd | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 177761269.0
num_examples: 81
download_size: 177632765
dataset_size: 177761269.0
---
# Dataset Card for "mix-closeup-lcd"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
kowndinya23/flan2022 | ---
configs:
- config_name: default
data_files:
- split: flan2021
path: data/flan2021-*
- split: t0
path: data/t0-*
- split: cot
path: data/cot-*
- split: niv2
path: data/niv2-*
- split: dialog
path: data/dialog-*
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
- name: task_source
dtype: string
- name: task_name
dtype: string
- name: template_type
dtype: string
splits:
- name: flan2021
num_bytes: 8988026240
num_examples: 5362361
- name: t0
num_bytes: 4602180562
num_examples: 1650308
- name: cot
num_bytes: 209004809
num_examples: 183848
- name: niv2
num_bytes: 13104211362
num_examples: 10066896
- name: dialog
num_bytes: 1024507265
num_examples: 553869
download_size: 16511300644
dataset_size: 27927930238
---
# Dataset Card for "flan2022"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
harpomaxx/dga-detection | ---
license: cc-by-2.0
---
A dataset containing both DGA and normal domain names. The normal domain names were taken from the Alexa top one million domains.
An additional 3,161 normal domains were included in the dataset, provided by the Bambenek Consulting feed. This later group is particularly interesting since it consists
of suspicious domain names that were not generated by DGA. Therefore, the total amount of domains normal in the dataset is 1,003,161. DGA domains
were obtained from the repositories of DGA domains of [Andrey Abakumov](https://github.com/andrewaeva/DGA) and [John Bambenek](http://osint.bambenekconsulting.com/feeds/).
The total amount of DGA domains is 1,915,335, and they correspond to 51 different malware families. DGA domains were generated by 51 different malware families.
About the 55% of of the DGA portion of dataset is composed of samples from the Banjori, Post, Timba, Cryptolocker, Ramdo and Conficker malware.
The DGA generation scheme followed by the malware families includes the simple arithmetical (A) and the recent word based (W) schemes.
Under the arithmetic scheme, the algorithm usually calculates a sequence of values that have a direct ASCII representation usable for a domain name.
On the other hand, word-based consists of concatenating a sequence of words from one or more wordlists. |
tyzhu/wiki_find_passage_train100_eval40_title | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 162337
num_examples: 240
- name: validation
num_bytes: 33941
num_examples: 40
download_size: 98195
dataset_size: 196278
---
# Dataset Card for "wiki_find_passage_train100_eval40_title"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
whu9/arxiv_summarization_postprocess | ---
dataset_info:
features:
- name: source
dtype: string
- name: summary
dtype: string
- name: source_num_tokens
dtype: int64
- name: summary_num_tokens
dtype: int64
splits:
- name: train
num_bytes: 6992115668
num_examples: 197465
- name: validation
num_bytes: 216277493
num_examples: 6435
- name: test
num_bytes: 216661725
num_examples: 6439
download_size: 3553348742
dataset_size: 7425054886
---
# Dataset Card for "arxiv_summarization_postprocess"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
HamxaHamid/StateBankPakistanDataset | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 33935
num_examples: 180
download_size: 16873
dataset_size: 33935
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
SaylorTwift/the_pile_books3_minus_gutenberg | ---
dataset_info:
features:
- name: title
dtype: string
- name: text
dtype: string
- name: first_name
dtype: string
- name: last_name
dtype: string
splits:
- name: train
num_bytes: 106199627990.47722
num_examples: 192661
download_size: 63006723975
dataset_size: 106199627990.47722
---
# Dataset Card for "the_pile_books3_minus_gutenberg"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
mrm8488/FloCo | ---
dataset_info:
- config_name: test
features:
- name: image
dtype: image
- name: code_caption
dtype: string
splits:
- name: train
num_bytes: 142134244.412
num_examples: 1188
download_size: 124563800
dataset_size: 142134244.412
- config_name: train
features:
- name: image
dtype: image
- name: code_caption
dtype: string
splits:
- name: train
num_bytes: 946697073.77
num_examples: 10102
download_size: 853815350
dataset_size: 946697073.77
- config_name: validation
features:
- name: image
dtype: image
- name: code_caption
dtype: string
splits:
- name: train
num_bytes: 95790792
num_examples: 594
download_size: 73916515
dataset_size: 95790792
configs:
- config_name: test
data_files:
- split: train
path: test/train-*
- config_name: train
data_files:
- split: train
path: train/train-*
- config_name: validation
data_files:
- split: train
path: validation/train-*
task_categories:
- image-to-image
tags:
- code
pretty_name: FloCo
size_categories:
- 10K<n<100K
---
# FloCo Dataset
From: https://vl2g.github.io/projects/floco/
We introduce a new large-scale dataset called "FloCo" for Flowchart images to Python Codes conversion. It contains 11,884 paired flowchart-code samples. Please refer to the paper for more details regarding statistics and dataset construction.
```
@inproceedings{shukla2023floco,
author = "Shukla, Shreya and
Gatti, Prajwal and
Kumar, Yogesh and
Yadav, Vikash and
Mishra, Anand",
title = "Towards Making Flowchart Images Machine Interpretable",
booktitle = "ICDAR",
year = "2023",
}
``` |
open-llm-leaderboard/details_SicariusSicariiStuff__Tinybra_13B | ---
pretty_name: Evaluation run of SicariusSicariiStuff/Tinybra_13B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [SicariusSicariiStuff/Tinybra_13B](https://huggingface.co/SicariusSicariiStuff/Tinybra_13B)\
\ 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_SicariusSicariiStuff__Tinybra_13B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-10T16:09:08.574464](https://huggingface.co/datasets/open-llm-leaderboard/details_SicariusSicariiStuff__Tinybra_13B/blob/main/results_2024-01-10T16-09-08.574464.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\": 0.5418757648022121,\n\
\ \"acc_stderr\": 0.0340842399843829,\n \"acc_norm\": 0.5484756586160711,\n\
\ \"acc_norm_stderr\": 0.034833096638910925,\n \"mc1\": 0.3329253365973072,\n\
\ \"mc1_stderr\": 0.016497402382012052,\n \"mc2\": 0.49143267175287075,\n\
\ \"mc2_stderr\": 0.015300501325826228\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5324232081911263,\n \"acc_stderr\": 0.014580637569995421,\n\
\ \"acc_norm\": 0.5571672354948806,\n \"acc_norm_stderr\": 0.014515573873348904\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.609838677554272,\n\
\ \"acc_stderr\": 0.004867893927258144,\n \"acc_norm\": 0.8098984266082454,\n\
\ \"acc_norm_stderr\": 0.003915792315457794\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \
\ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.48148148148148145,\n\
\ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.48148148148148145,\n\
\ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.5986842105263158,\n \"acc_stderr\": 0.039889037033362836,\n\
\ \"acc_norm\": 0.5986842105263158,\n \"acc_norm_stderr\": 0.039889037033362836\n\
\ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\
: {\n \"acc\": 0.5924528301886792,\n \"acc_stderr\": 0.030242233800854494,\n\
\ \"acc_norm\": 0.5924528301886792,\n \"acc_norm_stderr\": 0.030242233800854494\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5277777777777778,\n\
\ \"acc_stderr\": 0.04174752578923185,\n \"acc_norm\": 0.5277777777777778,\n\
\ \"acc_norm_stderr\": 0.04174752578923185\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.41,\n \"acc_stderr\": 0.04943110704237102,\n \
\ \"acc_norm\": 0.41,\n \"acc_norm_stderr\": 0.04943110704237102\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\": 0.47,\n\
\ \"acc_norm_stderr\": 0.050161355804659205\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.41,\n \"acc_stderr\": 0.049431107042371025,\n \
\ \"acc_norm\": 0.41,\n \"acc_norm_stderr\": 0.049431107042371025\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.5086705202312138,\n\
\ \"acc_stderr\": 0.038118909889404105,\n \"acc_norm\": 0.5086705202312138,\n\
\ \"acc_norm_stderr\": 0.038118909889404105\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.3235294117647059,\n \"acc_stderr\": 0.046550104113196156,\n\
\ \"acc_norm\": 0.3235294117647059,\n \"acc_norm_stderr\": 0.046550104113196156\n\
\ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\
: {\n \"acc\": 0.425531914893617,\n \"acc_stderr\": 0.03232146916224468,\n\
\ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.03232146916224468\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3157894736842105,\n\
\ \"acc_stderr\": 0.043727482902780064,\n \"acc_norm\": 0.3157894736842105,\n\
\ \"acc_norm_stderr\": 0.043727482902780064\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.4689655172413793,\n \"acc_stderr\": 0.04158632762097828,\n\
\ \"acc_norm\": 0.4689655172413793,\n \"acc_norm_stderr\": 0.04158632762097828\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.3306878306878307,\n \"acc_stderr\": 0.024229965298425082,\n \"\
acc_norm\": 0.3306878306878307,\n \"acc_norm_stderr\": 0.024229965298425082\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3253968253968254,\n\
\ \"acc_stderr\": 0.04190596438871136,\n \"acc_norm\": 0.3253968253968254,\n\
\ \"acc_norm_stderr\": 0.04190596438871136\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.048523658709391,\n \
\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.048523658709391\n },\n\
\ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.635483870967742,\n\
\ \"acc_stderr\": 0.027379871229943255,\n \"acc_norm\": 0.635483870967742,\n\
\ \"acc_norm_stderr\": 0.027379871229943255\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.45320197044334976,\n \"acc_stderr\": 0.035025446508458714,\n\
\ \"acc_norm\": 0.45320197044334976,\n \"acc_norm_stderr\": 0.035025446508458714\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\"\
: 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.6121212121212121,\n \"acc_stderr\": 0.038049136539710114,\n\
\ \"acc_norm\": 0.6121212121212121,\n \"acc_norm_stderr\": 0.038049136539710114\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7121212121212122,\n \"acc_stderr\": 0.03225883512300993,\n \"\
acc_norm\": 0.7121212121212122,\n \"acc_norm_stderr\": 0.03225883512300993\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.7772020725388601,\n \"acc_stderr\": 0.03003114797764154,\n\
\ \"acc_norm\": 0.7772020725388601,\n \"acc_norm_stderr\": 0.03003114797764154\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.5256410256410257,\n \"acc_stderr\": 0.025317649726448656,\n\
\ \"acc_norm\": 0.5256410256410257,\n \"acc_norm_stderr\": 0.025317649726448656\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.3111111111111111,\n \"acc_stderr\": 0.02822644674968352,\n \
\ \"acc_norm\": 0.3111111111111111,\n \"acc_norm_stderr\": 0.02822644674968352\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.5504201680672269,\n \"acc_stderr\": 0.03231293497137707,\n \
\ \"acc_norm\": 0.5504201680672269,\n \"acc_norm_stderr\": 0.03231293497137707\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.33774834437086093,\n \"acc_stderr\": 0.03861557546255169,\n \"\
acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.03861557546255169\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.7394495412844037,\n \"acc_stderr\": 0.01881918203485007,\n \"\
acc_norm\": 0.7394495412844037,\n \"acc_norm_stderr\": 0.01881918203485007\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.44907407407407407,\n \"acc_stderr\": 0.033922384053216154,\n \"\
acc_norm\": 0.44907407407407407,\n \"acc_norm_stderr\": 0.033922384053216154\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.7009803921568627,\n \"acc_stderr\": 0.03213325717373617,\n \"\
acc_norm\": 0.7009803921568627,\n \"acc_norm_stderr\": 0.03213325717373617\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.729957805907173,\n \"acc_stderr\": 0.028900721906293426,\n \
\ \"acc_norm\": 0.729957805907173,\n \"acc_norm_stderr\": 0.028900721906293426\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6098654708520179,\n\
\ \"acc_stderr\": 0.03273766725459157,\n \"acc_norm\": 0.6098654708520179,\n\
\ \"acc_norm_stderr\": 0.03273766725459157\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.6335877862595419,\n \"acc_stderr\": 0.04225875451969636,\n\
\ \"acc_norm\": 0.6335877862595419,\n \"acc_norm_stderr\": 0.04225875451969636\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.6942148760330579,\n \"acc_stderr\": 0.04205953933884123,\n \"\
acc_norm\": 0.6942148760330579,\n \"acc_norm_stderr\": 0.04205953933884123\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7129629629629629,\n\
\ \"acc_stderr\": 0.043733130409147614,\n \"acc_norm\": 0.7129629629629629,\n\
\ \"acc_norm_stderr\": 0.043733130409147614\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.6809815950920245,\n \"acc_stderr\": 0.03661997551073836,\n\
\ \"acc_norm\": 0.6809815950920245,\n \"acc_norm_stderr\": 0.03661997551073836\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.32142857142857145,\n\
\ \"acc_stderr\": 0.04432804055291518,\n \"acc_norm\": 0.32142857142857145,\n\
\ \"acc_norm_stderr\": 0.04432804055291518\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.6990291262135923,\n \"acc_stderr\": 0.045416094465039476,\n\
\ \"acc_norm\": 0.6990291262135923,\n \"acc_norm_stderr\": 0.045416094465039476\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7948717948717948,\n\
\ \"acc_stderr\": 0.026453508054040332,\n \"acc_norm\": 0.7948717948717948,\n\
\ \"acc_norm_stderr\": 0.026453508054040332\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.57,\n \"acc_stderr\": 0.049756985195624284,\n \
\ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.049756985195624284\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7254150702426565,\n\
\ \"acc_stderr\": 0.015959829933084025,\n \"acc_norm\": 0.7254150702426565,\n\
\ \"acc_norm_stderr\": 0.015959829933084025\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.6127167630057804,\n \"acc_stderr\": 0.026226158605124658,\n\
\ \"acc_norm\": 0.6127167630057804,\n \"acc_norm_stderr\": 0.026226158605124658\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n\
\ \"acc_stderr\": 0.014333522059217892,\n \"acc_norm\": 0.2424581005586592,\n\
\ \"acc_norm_stderr\": 0.014333522059217892\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.6111111111111112,\n \"acc_stderr\": 0.027914055510467998,\n\
\ \"acc_norm\": 0.6111111111111112,\n \"acc_norm_stderr\": 0.027914055510467998\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6109324758842444,\n\
\ \"acc_stderr\": 0.027690337536485372,\n \"acc_norm\": 0.6109324758842444,\n\
\ \"acc_norm_stderr\": 0.027690337536485372\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.6080246913580247,\n \"acc_stderr\": 0.027163686038271146,\n\
\ \"acc_norm\": 0.6080246913580247,\n \"acc_norm_stderr\": 0.027163686038271146\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.3900709219858156,\n \"acc_stderr\": 0.02909767559946393,\n \
\ \"acc_norm\": 0.3900709219858156,\n \"acc_norm_stderr\": 0.02909767559946393\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.394393741851369,\n\
\ \"acc_stderr\": 0.012482141665631183,\n \"acc_norm\": 0.394393741851369,\n\
\ \"acc_norm_stderr\": 0.012482141665631183\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.5257352941176471,\n \"acc_stderr\": 0.030332578094555026,\n\
\ \"acc_norm\": 0.5257352941176471,\n \"acc_norm_stderr\": 0.030332578094555026\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.5261437908496732,\n \"acc_stderr\": 0.020200164564804588,\n \
\ \"acc_norm\": 0.5261437908496732,\n \"acc_norm_stderr\": 0.020200164564804588\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5909090909090909,\n\
\ \"acc_stderr\": 0.04709306978661895,\n \"acc_norm\": 0.5909090909090909,\n\
\ \"acc_norm_stderr\": 0.04709306978661895\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.6408163265306123,\n \"acc_stderr\": 0.030713560455108493,\n\
\ \"acc_norm\": 0.6408163265306123,\n \"acc_norm_stderr\": 0.030713560455108493\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7313432835820896,\n\
\ \"acc_stderr\": 0.03134328358208954,\n \"acc_norm\": 0.7313432835820896,\n\
\ \"acc_norm_stderr\": 0.03134328358208954\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.8,\n \"acc_stderr\": 0.04020151261036846,\n \
\ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.04020151261036846\n },\n\
\ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.41566265060240964,\n\
\ \"acc_stderr\": 0.038367221765980515,\n \"acc_norm\": 0.41566265060240964,\n\
\ \"acc_norm_stderr\": 0.038367221765980515\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.7368421052631579,\n \"acc_stderr\": 0.03377310252209205,\n\
\ \"acc_norm\": 0.7368421052631579,\n \"acc_norm_stderr\": 0.03377310252209205\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3329253365973072,\n\
\ \"mc1_stderr\": 0.016497402382012052,\n \"mc2\": 0.49143267175287075,\n\
\ \"mc2_stderr\": 0.015300501325826228\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7379636937647988,\n \"acc_stderr\": 0.012358944431637563\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.18119787717968158,\n \
\ \"acc_stderr\": 0.010609827611527334\n }\n}\n```"
repo_url: https://huggingface.co/SicariusSicariiStuff/Tinybra_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: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|arc:challenge|25_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|gsm8k|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hellaswag|10_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-10T16-09-08.574464.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-10T16-09-08.574464.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- '**/details_harness|winogrande|5_2024-01-10T16-09-08.574464.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-10T16-09-08.574464.parquet'
- config_name: results
data_files:
- split: 2024_01_10T16_09_08.574464
path:
- results_2024-01-10T16-09-08.574464.parquet
- split: latest
path:
- results_2024-01-10T16-09-08.574464.parquet
---
# Dataset Card for Evaluation run of SicariusSicariiStuff/Tinybra_13B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [SicariusSicariiStuff/Tinybra_13B](https://huggingface.co/SicariusSicariiStuff/Tinybra_13B) 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_SicariusSicariiStuff__Tinybra_13B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-10T16:09:08.574464](https://huggingface.co/datasets/open-llm-leaderboard/details_SicariusSicariiStuff__Tinybra_13B/blob/main/results_2024-01-10T16-09-08.574464.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": 0.5418757648022121,
"acc_stderr": 0.0340842399843829,
"acc_norm": 0.5484756586160711,
"acc_norm_stderr": 0.034833096638910925,
"mc1": 0.3329253365973072,
"mc1_stderr": 0.016497402382012052,
"mc2": 0.49143267175287075,
"mc2_stderr": 0.015300501325826228
},
"harness|arc:challenge|25": {
"acc": 0.5324232081911263,
"acc_stderr": 0.014580637569995421,
"acc_norm": 0.5571672354948806,
"acc_norm_stderr": 0.014515573873348904
},
"harness|hellaswag|10": {
"acc": 0.609838677554272,
"acc_stderr": 0.004867893927258144,
"acc_norm": 0.8098984266082454,
"acc_norm_stderr": 0.003915792315457794
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.4,
"acc_stderr": 0.049236596391733084,
"acc_norm": 0.4,
"acc_norm_stderr": 0.049236596391733084
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.48148148148148145,
"acc_stderr": 0.043163785995113245,
"acc_norm": 0.48148148148148145,
"acc_norm_stderr": 0.043163785995113245
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.5986842105263158,
"acc_stderr": 0.039889037033362836,
"acc_norm": 0.5986842105263158,
"acc_norm_stderr": 0.039889037033362836
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.52,
"acc_stderr": 0.050211673156867795,
"acc_norm": 0.52,
"acc_norm_stderr": 0.050211673156867795
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.5924528301886792,
"acc_stderr": 0.030242233800854494,
"acc_norm": 0.5924528301886792,
"acc_norm_stderr": 0.030242233800854494
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.5277777777777778,
"acc_stderr": 0.04174752578923185,
"acc_norm": 0.5277777777777778,
"acc_norm_stderr": 0.04174752578923185
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.41,
"acc_stderr": 0.04943110704237102,
"acc_norm": 0.41,
"acc_norm_stderr": 0.04943110704237102
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.47,
"acc_stderr": 0.050161355804659205,
"acc_norm": 0.47,
"acc_norm_stderr": 0.050161355804659205
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.41,
"acc_stderr": 0.049431107042371025,
"acc_norm": 0.41,
"acc_norm_stderr": 0.049431107042371025
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.5086705202312138,
"acc_stderr": 0.038118909889404105,
"acc_norm": 0.5086705202312138,
"acc_norm_stderr": 0.038118909889404105
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.3235294117647059,
"acc_stderr": 0.046550104113196156,
"acc_norm": 0.3235294117647059,
"acc_norm_stderr": 0.046550104113196156
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.62,
"acc_stderr": 0.048783173121456316,
"acc_norm": 0.62,
"acc_norm_stderr": 0.048783173121456316
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.425531914893617,
"acc_stderr": 0.03232146916224468,
"acc_norm": 0.425531914893617,
"acc_norm_stderr": 0.03232146916224468
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.3157894736842105,
"acc_stderr": 0.043727482902780064,
"acc_norm": 0.3157894736842105,
"acc_norm_stderr": 0.043727482902780064
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.4689655172413793,
"acc_stderr": 0.04158632762097828,
"acc_norm": 0.4689655172413793,
"acc_norm_stderr": 0.04158632762097828
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.3306878306878307,
"acc_stderr": 0.024229965298425082,
"acc_norm": 0.3306878306878307,
"acc_norm_stderr": 0.024229965298425082
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```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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### Direct Use
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## Dataset Structure
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## Dataset Creation
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### Source Data
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#### Data Collection and Processing
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distilled-from-one-sec-cv12/chunk_122 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
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num_bytes: 1540534024
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download_size: 1574244710
dataset_size: 1540534024
---
# Dataset Card for "chunk_122"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
316usman/thematic4a_rr_embed | ---
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configs:
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path: data/train-*
---
|
chavinlo/hdvila5ktest | ---
dataset_info:
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---
|
Kimata/gpt_driver_dataset_processed | ---
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---
|
adalib/graphscope-data | ---
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configs:
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data_files:
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path: data/train-*
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path: data/test-*
---
|
Mitsuki-Sakamoto/alpaca_farm-deberta-re-pref-64-_fil_self_1.4b_bo16_2_64_mix_50_kl_0.1_prm_160m_thr_0.3_seed_1 | ---
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path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_22-*
- split: epoch_23
path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_23-*
- split: epoch_24
path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_24-*
- split: epoch_25
path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_25-*
- split: epoch_26
path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_26-*
- split: epoch_27
path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_27-*
- split: epoch_28
path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_28-*
- split: epoch_29
path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_29-*
---
|
Gopal2002/DONUT_FINETUNE_DATASET | ---
dataset_info:
features:
- name: image
dtype: image
- name: ground_truth
dtype: string
splits:
- name: train
num_bytes: 502618094.3164558
num_examples: 782
- name: test
num_bytes: 52708608.6835443
num_examples: 87
download_size: 392342285
dataset_size: 555326703.0000001
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
BangumiBase/encouragementofclimb | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Encouragement Of Climb
This is the image base of bangumi Encouragement of Climb, we detected 20 characters, 3066 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 30 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 14 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 56 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 25 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 467 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 30 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 16 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 86 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 32 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 17 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 15 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 1010 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 66 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 339 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 47 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 377 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 36 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 16 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 6 | [Download](18/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| noise | 381 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
euclaise/code_contests_mc | ---
dataset_info:
features:
- name: question
dtype: string
- name: chosen
dtype: string
- name: rejected
sequence: string
splits:
- name: train
num_bytes: 614058417176
num_examples: 1767546
download_size: 188649995596
dataset_size: 614058417176
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
Multiple choice version of code_contests, for preference learning. |
Sofoklis/rna_green_1024 | ---
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: image
dtype: image
- name: caption
dtype: string
- name: name
dtype: string
- name: sequence
dtype: string
splits:
- name: train
num_bytes: 82810.0
num_examples: 15
- name: validation
num_bytes: 16562.0
num_examples: 3
- name: test
num_bytes: 11042.0
num_examples: 2
download_size: 12480
dataset_size: 110414.0
---
# Dataset Card for "rna_green_1024"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
cmagganas/GenAI-job-postings-Dataset-sample | ---
dataset_info:
features:
- name: position_level
dtype: string
- name: use_case
dtype: string
- name: job_title
dtype: string
- name: job_posting
dtype: string
- name: cover_letter
dtype: string
splits:
- name: train
num_bytes: 39280
num_examples: 10
download_size: 41635
dataset_size: 39280
---
# Dataset Card for "GenAI-job-postings-Dataset-sample"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_quantumaikr__QuantumLM | ---
pretty_name: Evaluation run of quantumaikr/QuantumLM
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [quantumaikr/QuantumLM](https://huggingface.co/quantumaikr/QuantumLM) 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 4 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_quantumaikr__QuantumLM\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-17T21:09:03.673606](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__QuantumLM/blob/main/results_2023-10-17T21-09-03.673606.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\": 0.004718959731543624,\n\
\ \"em_stderr\": 0.0007018360183131032,\n \"f1\": 0.066544672818792,\n\
\ \"f1_stderr\": 0.0015305236997022681,\n \"acc\": 0.4202347692309533,\n\
\ \"acc_stderr\": 0.010254299592459359\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.004718959731543624,\n \"em_stderr\": 0.0007018360183131032,\n\
\ \"f1\": 0.066544672818792,\n \"f1_stderr\": 0.0015305236997022681\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.09855951478392722,\n \
\ \"acc_stderr\": 0.008210320350946333\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7419100236779794,\n \"acc_stderr\": 0.012298278833972385\n\
\ }\n}\n```"
repo_url: https://huggingface.co/quantumaikr/QuantumLM
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|arc:challenge|25_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|arc:challenge|25_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_17T05_08_11.720635
path:
- '**/details_harness|drop|3_2023-10-17T05-08-11.720635.parquet'
- split: 2023_10_17T21_09_03.673606
path:
- '**/details_harness|drop|3_2023-10-17T21-09-03.673606.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-17T21-09-03.673606.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_17T05_08_11.720635
path:
- '**/details_harness|gsm8k|5_2023-10-17T05-08-11.720635.parquet'
- split: 2023_10_17T21_09_03.673606
path:
- '**/details_harness|gsm8k|5_2023-10-17T21-09-03.673606.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-17T21-09-03.673606.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hellaswag|10_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hellaswag|10_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-22T12:43:24.978331.parquet'
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- '**/details_harness|hendrycksTest-college_physics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-22T12:43:24.978331.parquet'
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- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-22T12:43:24.978331.parquet'
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- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-22T12:43:24.978331.parquet'
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- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-22T12:43:24.978331.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-nutrition|5_2023-08-22T20:06:17.327995.parquet'
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path:
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- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-global_facts|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-human_aging|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-nutrition|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-22T20:06:17.327995.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-sociology|5_2023-08-22T20:06:17.327995.parquet'
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- '**/details_harness|hendrycksTest-world_religions|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
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path:
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path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_anatomy_5
data_files:
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path:
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path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
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path:
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path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
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path:
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path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
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path:
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path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
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- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
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path:
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- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
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path:
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path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
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path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
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path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-22T12:43:24.978331.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-22T12:43:24.978331.parquet'
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-22T12:43:24.978331.parquet'
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path:
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path:
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data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-22T12:43:24.978331.parquet'
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path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-22T12:43:24.978331.parquet'
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path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
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path:
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path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_22T12_43_24.978331
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-22T12:43:24.978331.parquet'
- split: 2023_08_22T20_06_17.327995
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-22T20:06:17.327995.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-22T20:06:17.327995.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_17T05_08_11.720635
path:
- '**/details_harness|winogrande|5_2023-10-17T05-08-11.720635.parquet'
- split: 2023_10_17T21_09_03.673606
path:
- '**/details_harness|winogrande|5_2023-10-17T21-09-03.673606.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-17T21-09-03.673606.parquet'
- config_name: results
data_files:
- split: 2023_10_17T05_08_11.720635
path:
- results_2023-10-17T05-08-11.720635.parquet
- split: 2023_10_17T21_09_03.673606
path:
- results_2023-10-17T21-09-03.673606.parquet
- split: latest
path:
- results_2023-10-17T21-09-03.673606.parquet
---
# Dataset Card for Evaluation run of quantumaikr/QuantumLM
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/quantumaikr/QuantumLM
- **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 [quantumaikr/QuantumLM](https://huggingface.co/quantumaikr/QuantumLM) 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 4 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_quantumaikr__QuantumLM",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-17T21:09:03.673606](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__QuantumLM/blob/main/results_2023-10-17T21-09-03.673606.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": 0.004718959731543624,
"em_stderr": 0.0007018360183131032,
"f1": 0.066544672818792,
"f1_stderr": 0.0015305236997022681,
"acc": 0.4202347692309533,
"acc_stderr": 0.010254299592459359
},
"harness|drop|3": {
"em": 0.004718959731543624,
"em_stderr": 0.0007018360183131032,
"f1": 0.066544672818792,
"f1_stderr": 0.0015305236997022681
},
"harness|gsm8k|5": {
"acc": 0.09855951478392722,
"acc_stderr": 0.008210320350946333
},
"harness|winogrande|5": {
"acc": 0.7419100236779794,
"acc_stderr": 0.012298278833972385
}
}
```
### 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] |
c01dsnap/Webshell | ---
license: apache-2.0
---
Dataset uded for webshell classification task. Repo contains:
* Opensource collection of php/asp/aspx/jsp webshells
* Opensource collection of php/asp/aspx/jsp normal scripts
All files are collected fron github. |
huggingartists/madonna | ---
language:
- en
tags:
- huggingartists
- lyrics
---
# Dataset Card for "huggingartists/madonna"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [How to use](#how-to-use)
- [Dataset Structure](#dataset-structure)
- [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)
- [About](#about)
## Dataset Description
- **Homepage:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists)
- **Repository:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists)
- **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 the generated dataset:** 1.986277 MB
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/5cad1fbda7135f40c49ea35ad60ba4f5.215x215x1.png')">
</div>
</div>
<a href="https://huggingface.co/huggingartists/madonna">
<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div>
</a>
<div style="text-align: center; font-size: 16px; font-weight: 800">Madonna</div>
<a href="https://genius.com/artists/madonna">
<div style="text-align: center; font-size: 14px;">@madonna</div>
</a>
</div>
### Dataset Summary
The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists.
Model is available [here](https://huggingface.co/huggingartists/madonna).
### Supported Tasks and Leaderboards
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Languages
en
## How to use
How to load this dataset directly with the datasets library:
```python
from datasets import load_dataset
dataset = load_dataset("huggingartists/madonna")
```
## Dataset Structure
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..."
}
```
### Data Fields
The data fields are the same among all splits.
- `text`: a `string` feature.
### Data Splits
| train |validation|test|
|------:|---------:|---:|
|1260| -| -|
'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code:
```python
from datasets import load_dataset, Dataset, DatasetDict
import numpy as np
datasets = load_dataset("huggingartists/madonna")
train_percentage = 0.9
validation_percentage = 0.07
test_percentage = 0.03
train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))])
datasets = DatasetDict(
{
'train': Dataset.from_dict({'text': list(train)}),
'validation': Dataset.from_dict({'text': list(validation)}),
'test': Dataset.from_dict({'text': list(test)})
}
)
```
## 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
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Citation Information
```
@InProceedings{huggingartists,
author={Aleksey Korshuk}
year=2021
}
```
## About
*Built by Aleksey Korshuk*
[](https://github.com/AlekseyKorshuk)
[](https://twitter.com/intent/follow?screen_name=alekseykorshuk)
[](https://t.me/joinchat/_CQ04KjcJ-4yZTky)
For more details, visit the project repository.
[](https://github.com/AlekseyKorshuk/huggingartists)
|
jaymeanchante/FakeRecogna | ---
license: apache-2.0
---
|
one-sec-cv12/chunk_259 | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: train
num_bytes: 21677745456.875
num_examples: 225697
download_size: 19218840913
dataset_size: 21677745456.875
---
# Dataset Card for "chunk_259"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
bri25yu/flores200_packed2_mix_mt5 | ---
dataset_info:
features:
- name: id
dtype: int32
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 13594840169
num_examples: 10240000
- name: val
num_bytes: 3827042
num_examples: 5000
- name: test
num_bytes: 7670994
num_examples: 10000
download_size: 6189830203
dataset_size: 13606338205
---
# Dataset Card for "flores200_packed2_mix_mt5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Nithiwat/claimbuster | ---
license: cc-by-sa-4.0
---
|
huggingartists/og-buda | ---
language:
- en
tags:
- huggingartists
- lyrics
---
# Dataset Card for "huggingartists/og-buda"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [How to use](#how-to-use)
- [Dataset Structure](#dataset-structure)
- [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)
- [About](#about)
## Dataset Description
- **Homepage:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists)
- **Repository:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists)
- **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 the generated dataset:** 0.641111 MB
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/73f7f7eaff5043a332d13cfae5282bc5.668x668x1.jpg')">
</div>
</div>
<a href="https://huggingface.co/huggingartists/og-buda">
<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div>
</a>
<div style="text-align: center; font-size: 16px; font-weight: 800">OG Buda</div>
<a href="https://genius.com/artists/og-buda">
<div style="text-align: center; font-size: 14px;">@og-buda</div>
</a>
</div>
### Dataset Summary
The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists.
Model is available [here](https://huggingface.co/huggingartists/og-buda).
### Supported Tasks and Leaderboards
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Languages
en
## How to use
How to load this dataset directly with the datasets library:
```python
from datasets import load_dataset
dataset = load_dataset("huggingartists/og-buda")
```
## Dataset Structure
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..."
}
```
### Data Fields
The data fields are the same among all splits.
- `text`: a `string` feature.
### Data Splits
| train |validation|test|
|------:|---------:|---:|
|236| -| -|
'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code:
```python
from datasets import load_dataset, Dataset, DatasetDict
import numpy as np
datasets = load_dataset("huggingartists/og-buda")
train_percentage = 0.9
validation_percentage = 0.07
test_percentage = 0.03
train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))])
datasets = DatasetDict(
{
'train': Dataset.from_dict({'text': list(train)}),
'validation': Dataset.from_dict({'text': list(validation)}),
'test': Dataset.from_dict({'text': list(test)})
}
)
```
## 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
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Citation Information
```
@InProceedings{huggingartists,
author={Aleksey Korshuk}
year=2021
}
```
## About
*Built by Aleksey Korshuk*
[](https://github.com/AlekseyKorshuk)
[](https://twitter.com/intent/follow?screen_name=alekseykorshuk)
[](https://t.me/joinchat/_CQ04KjcJ-4yZTky)
For more details, visit the project repository.
[](https://github.com/AlekseyKorshuk/huggingartists)
|
ujgeie/processed_bert_dataset | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: token_type_ids
sequence: int8
- name: attention_mask
sequence: int8
- name: special_tokens_mask
sequence: int8
splits:
- name: train
num_bytes: 24027285600.0
num_examples: 6674246
download_size: 5887301744
dataset_size: 24027285600.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
saibo/bookcorpus_stochastic_subset_compact_1024 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 27536698
num_examples: 6160
download_size: 16803321
dataset_size: 27536698
---
# Dataset Card for "bookcorpus_stochastic_subset_compact_1024"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
kyot/embeddings | ---
license: unknown
---
|
albertvillanova/sat | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
- vi
license:
- unknown
multilinguality:
- translation
size_categories:
- 1M<n<10M
source_datasets:
- original
- extended|bible_para
- extended|kde4
- extended|opus_gnome
- extended|open_subtitles
- extended|tatoeba
task_categories:
- text-generation
- translation
task_ids: []
pretty_name: SAT
tags:
- conditional-text-generation
---
# Dataset Card for SAT
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://blog.vietai.org/sat/
- **Repository:** https://github.com/vietai/sat
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
SAT (Style Augmented Translation) dataset contains roughly 3.3 million English-Vietnamese pairs of texts.
### Supported Tasks and Leaderboards
- Machine Translation
### Languages
The languages in the dataset are:
- Vietnamese (`vi`)
- English (`en`)
## Dataset Structure
### Data Instances
```
{
'translation': {
'en': 'Rachel Pike : The science behind a climate headline',
'vi': 'Khoa học đằng sau một tiêu đề về khí hậu'
}
}
```
### Data Fields
- `translation`:
- `en`: Parallel text in English.
- `vi`: Parallel text in Vietnamese.
### Data Splits
The dataset is split in "train" and "test".
| | train | test |
|--------------------|--------:|-----:|
| Number of examples | 3359574 | 7221 |
## 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
Unknown.
### Citation Information
Unknown.
### Contributions
Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.
|
sunhaozhepy/ag_news_roberta_keywords | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': World
'1': Sports
'2': Business
'3': Sci/Tech
- name: keywords
dtype: string
splits:
- name: train
num_bytes: 32663299
num_examples: 120000
- name: test
num_bytes: 2060283
num_examples: 7600
download_size: 21875045
dataset_size: 34723582
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
Multimodal-Fatima/OxfordPets_test_facebook_opt_350m_Attributes_ns_3669 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: image
dtype: image
- name: prompt
dtype: string
- name: true_label
dtype: string
- name: prediction
dtype: string
- name: scores
sequence: float64
splits:
- name: fewshot_0_bs_16
num_bytes: 121000490.375
num_examples: 3669
- name: fewshot_1_bs_16
num_bytes: 121909413.375
num_examples: 3669
- name: fewshot_3_bs_16
num_bytes: 123709541.375
num_examples: 3669
- name: fewshot_5_bs_16
num_bytes: 125502094.375
num_examples: 3669
- name: fewshot_8_bs_16
num_bytes: 128203377.375
num_examples: 3669
download_size: 602524552
dataset_size: 620324916.875
---
# Dataset Card for "OxfordPets_test_facebook_opt_350m_Attributes_ns_3669"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
EMBO/BLURB | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license: apache-2.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
- token-classification
- sentence-similarity
- text-classification
task_ids:
- closed-domain-qa
- named-entity-recognition
- parsing
- semantic-similarity-scoring
- text-scoring
- topic-classification
pretty_name: BLURB (Biomedical Language Understanding and Reasoning Benchmark.)
---
# Dataset Card for BLURB
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://microsoft.github.io/BLURB/index.html
- **Paper:** [Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing](https://arxiv.org/pdf/2007.15779.pdf)
- **Leaderboard:** https://microsoft.github.io/BLURB/leaderboard.html
- **Point of Contact:**
### Dataset Summary
BLURB is a collection of resources for biomedical natural language processing. In general domains, such as newswire and the Web, comprehensive benchmarks and leaderboards such as GLUE have greatly accelerated progress in open-domain NLP. In biomedicine, however, such resources are ostensibly scarce. In the past, there have been a plethora of shared tasks in biomedical NLP, such as BioCreative, BioNLP Shared Tasks, SemEval, and BioASQ, to name just a few. These efforts have played a significant role in fueling interest and progress by the research community, but they typically focus on individual tasks. The advent of neural language models, such as BERT provides a unifying foundation to leverage transfer learning from unlabeled text to support a wide range of NLP applications. To accelerate progress in biomedical pretraining strategies and task-specific methods, it is thus imperative to create a broad-coverage benchmark encompassing diverse biomedical tasks.
Inspired by prior efforts toward this direction (e.g., BLUE), we have created BLURB (short for Biomedical Language Understanding and Reasoning Benchmark). BLURB comprises of a comprehensive benchmark for PubMed-based biomedical NLP applications, as well as a leaderboard for tracking progress by the community. BLURB includes thirteen publicly available datasets in six diverse tasks. To avoid placing undue emphasis on tasks with many available datasets, such as named entity recognition (NER), BLURB reports the macro average across all tasks as the main score. The BLURB leaderboard is model-agnostic. Any system capable of producing the test predictions using the same training and development data can participate. The main goal of BLURB is to lower the entry barrier in biomedical NLP and help accelerate progress in this vitally important field for positive societal and human impact.
#### BC5-chem
The corpus consists of three separate sets of
articles with diseases, chemicals and their relations annotated.
The training (500 articles) and development (500 articles) sets
were released to task participants in advance to support text-mining
method development. The test set (500 articles) was used for final
system performance evaluation.
- **Homepage:** https://biocreative.bioinformatics.udel.edu/resources/corpora/biocreative-v-cdr-corpus
- **Repository:** [NER GitHub repo by @GamalC](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/raw/master/data/)
- **Paper:** [BioCreative V CDR task corpus: a resource for chemical disease relation extraction](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4860626/)
#### BC5-disease
The corpus consists of three separate sets of
articles with diseases, chemicals and their relations annotated.
The training (500 articles) and development (500 articles) sets
were released to task participants in advance to support text-mining
method development. The test set (500 articles) was used for final
system performance evaluation.
- **Homepage:** https://biocreative.bioinformatics.udel.edu/resources/corpora/biocreative-v-cdr-corpus
- **Repository:** [NER GitHub repo by @GamalC](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/raw/master/data/)
- **Paper:** [BioCreative V CDR task corpus: a resource for chemical disease relation extraction](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4860626/)
#### BC2GM
The BioCreative II Gene Mention task.
The training corpus for the current task consists mainly of
the training and testing corpora (text collections) from the
BCI task, and the testing corpus for the current task
consists of an additional 5,000 sentences that were held
'in reserve' from the previous task.
In the current corpus, tokenization is not provided;
instead participants are asked to identify a gene mention
in a sentence by giving its start and end characters.
As before, the training set consists of a set of sentences,
and for each sentence a set of gene mentions
(GENE annotations).
- **Homepage:** https://biocreative.bioinformatics.udel.edu/tasks/biocreative-ii/task-1a-gene-mention-tagging/
- **Repository:** [NER GitHub repo by @GamalC](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/raw/master/data/)
- **Paper:** [verview of BioCreative II gene mention recognition](https://link.springer.com/article/10.1186/gb-2008-9-s2-s2)
#### NCBI Disease
The NCBI disease corpus is fully annotated at the mention
and concept level to serve as a research resource for the biomedical natural
language processing community.
Corpus Characteristics
----------------------
* 793 PubMed abstracts
* 6,892 disease mentions
* 790 unique disease concepts
* Medical Subject Headings (MeSH®)
* Online Mendelian Inheritance in Man (OMIM®)
* 91% of the mentions map to a single disease concept
**divided into training, developing and testing sets.
Corpus Annotation
* Fourteen annotators
* Two-annotators per document (randomly paired)
* Three annotation phases
* Checked for corpus-wide consistency of annotations
- **Homepage:** https://www.ncbi.nlm.nih.gov/CBBresearch/Dogan/DISEASE/
- **Repository:** [NER GitHub repo by @GamalC](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/raw/master/data/)
- **Paper:** [NCBI disease corpus: a resource for disease name recognition and concept normalization](https://pubmed.ncbi.nlm.nih.gov/24393765/)
#### JNLPBA
The BioNLP / JNLPBA Shared Task 2004 involves the identification
and classification of technical terms referring to concepts of interest to
biologists in the domain of molecular biology. The task was organized by GENIA
Project based on the annotations of the GENIA Term corpus (version 3.02).
Corpus format: The JNLPBA corpus is distributed in IOB format, with each line
containing a single token and its tag, separated by a tab character.
Sentences are separated by blank lines.
- **Homepage: ** http://www.geniaproject.org/shared-tasks/bionlp-jnlpba-shared-task-2004
- **Repository:** [NER GitHub repo by @GamalC](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/raw/master/data/)
- **Paper: ** [Introduction to the Bio-entity Recognition Task at JNLPBA](https://aclanthology.org/W04-1213)
#### EBM PICO
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
#### ChemProt
- **Homepage:**
- **Repository:**
- **Paper:**
#### DDI
- **Homepage:**
- **Repository:**
- **Paper:**
#### GAD
- **Homepage:**
- **Repository:**
- **Paper:**
#### BIOSSES
BIOSSES is a benchmark dataset for biomedical sentence similarity estimation. The dataset comprises 100 sentence pairs, in which each sentence was selected from the [TAC (Text Analysis Conference) Biomedical Summarization Track Training Dataset](https://tac.nist.gov/2014/BiomedSumm/) containing articles from the biomedical domain. The sentence pairs in BIOSSES were selected from citing sentences, i.e. sentences that have a citation to a reference article.
The sentence pairs were evaluated by five different human experts that judged their similarity and gave scores ranging from 0 (no relation) to 4 (equivalent). In the original paper the mean of the scores assigned by the five human annotators was taken as the gold standard. The Pearson correlation between the gold standard scores and the scores estimated by the models was used as the evaluation metric. The strength of correlation can be assessed by the general guideline proposed by Evans (1996) as follows:
- very strong: 0.80–1.00
- strong: 0.60–0.79
- moderate: 0.40–0.59
- weak: 0.20–0.39
- very weak: 0.00–0.19
- **Homepage:** https://tabilab.cmpe.boun.edu.tr/BIOSSES/DataSet.html
- **Repository:** https://github.com/gizemsogancioglu/biosses
- **Paper:** [BIOSSES: a semantic sentence similarity estimation system for the biomedical domain](https://academic.oup.com/bioinformatics/article/33/14/i49/3953954)
- **Point of Contact:** [Gizem Soğancıoğlu](gizemsogancioglu@gmail.com) and [Arzucan Özgür](gizemsogancioglu@gmail.com)
#### HoC
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
#### PubMedQA
We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts. The task of PubMedQA is to answer research questions with yes/no/maybe (e.g.: Do preoperative statins reduce atrial fibrillation after coronary artery bypass grafting?) using the corresponding abstracts. PubMedQA has 1k expert-annotated, 61.2k unlabeled and 211.3k artificially generated QA instances. Each PubMedQA instance is composed of (1) a question which is either an existing research article title or derived from one, (2) a context which is the corresponding abstract without its conclusion, (3) a long answer, which is the conclusion of the abstract and, presumably, answers the research question, and (4) a yes/no/maybe answer which summarizes the conclusion. PubMedQA is the first QA dataset where reasoning over biomedical research texts, especially their quantitative contents, is required to answer the questions. Our best performing model, multi-phase fine-tuning of BioBERT with long answer bag-of-word statistics as additional supervision, achieves 68.1% accuracy, compared to single human performance of 78.0% accuracy and majority-baseline of 55.2% accuracy, leaving much room for improvement. PubMedQA is publicly available at this https URL.
- **Homepage:** https://pubmedqa.github.io/
- **Repository:** https://github.com/pubmedqa/pubmedqa
- **Paper:** [PubMedQA: A Dataset for Biomedical Research Question Answering](https://arxiv.org/pdf/1909.06146.pdf)
- **Leaderboard:** [Question answering](https://pubmedqa.github.io/)
- **Point of Contact:**
#### BioASQ
Task 7b will use benchmark datasets containing training and test biomedical questions, in English, along with gold standard (reference) answers. The participants will have to respond to each test question with relevant concepts (from designated terminologies and ontologies), relevant articles (in English, from designated article repositories), relevant snippets (from the relevant articles), relevant RDF triples (from designated ontologies), exact answers (e.g., named entities in the case of factoid questions) and 'ideal' answers (English paragraph-sized summaries). 2747 training questions (that were used as dry-run or test questions in previous year) are already available, along with their gold standard answers (relevant concepts, articles, snippets, exact answers, summaries).
- **Homepage:** http://bioasq.org/
- **Repository:** http://participants-area.bioasq.org/datasets/
- **Paper:** [Automatic semantic classification of scientific literature according to the hallmarks of cancer](https://academic.oup.com/bioinformatics/article/32/3/432/1743783?login=false)
### Supported Tasks and Leaderboards
| **Dataset** | **Task** | **Train** | **Dev** | **Test** | **Evaluation Metrics** | **Added** |
|:------------:|:-----------------------:|:---------:|:-------:|:--------:|:----------------------:|-----------|
| BC5-chem | NER | 5203 | 5347 | 5385 | F1 entity-level | **Yes** |
| BC5-disease | NER | 4182 | 4244 | 4424 | F1 entity-level | **Yes** |
| NCBI-disease | NER | 5134 | 787 | 960 | F1 entity-level | **Yes** |
| BC2GM | NER | 15197 | 3061 | 6325 | F1 entity-level | **Yes** |
| JNLPBA | NER | 46750 | 4551 | 8662 | F1 entity-level | **Yes** |
| EBM PICO | PICO | 339167 | 85321 | 16364 | Macro F1 word-level | No |
| ChemProt | Relation Extraction | 18035 | 11268 | 15745 | Micro F1 | No |
| DDI | Relation Extraction | 25296 | 2496 | 5716 | Micro F1 | No |
| GAD | Relation Extraction | 4261 | 535 | 534 | Micro F1 | No |
| BIOSSES | Sentence Similarity | 64 | 16 | 20 | Pearson | **Yes** |
| HoC | Document Classification | 1295 | 186 | 371 | Average Micro F1 | No |
| PubMedQA | Question Answering | 450 | 50 | 500 | Accuracy | **Yes** |
| BioASQ | Question Answering | 670 | 75 | 140 | Accuracy | No |
Datasets used in the BLURB biomedical NLP benchmark. The Train, Dev, and test splits might not be exactly identical to those proposed in BLURB.
This is something to be checked.
### Languages
English from biomedical texts
## Dataset Structure
### Data Instances
* **NER**
```json
{
'id': 0,
'tokens': [ "DPP6", "as", "a", "candidate", "gene", "for", "neuroleptic", "-", "induced", "tardive", "dyskinesia", "." ]
'ner_tags': [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
}
```
* **PICO**
```json
{
'TBD'
}
```
* **Relation Extraction**
```json
{
'TBD'
}
```
* **Sentence Similarity**
```json
{'sentence 1': 'Here, looking for agents that could specifically kill KRAS mutant cells, they found that knockdown of GATA2 was synthetically lethal with KRAS mutation'
'sentence 2': 'Not surprisingly, GATA2 knockdown in KRAS mutant cells resulted in a striking reduction of active GTP-bound RHO proteins, including the downstream ROCK kinase'
'score': 2.2}
```
* **Document Classification**
```json
{
'TBD'
}
```
* **Question Answering**
* PubMedQA
```json
{'context': {'contexts': ['Programmed cell death (PCD) is the regulated death of cells within an organism. The lace plant (Aponogeton madagascariensis) produces perforations in its leaves through PCD. The leaves of the plant consist of a latticework of longitudinal and transverse veins enclosing areoles. PCD occurs in the cells at the center of these areoles and progresses outwards, stopping approximately five cells from the vasculature. The role of mitochondria during PCD has been recognized in animals; however, it has been less studied during PCD in plants.',
'The following paper elucidates the role of mitochondrial dynamics during developmentally regulated PCD in vivo in A. madagascariensis. A single areole within a window stage leaf (PCD is occurring) was divided into three areas based on the progression of PCD; cells that will not undergo PCD (NPCD), cells in early stages of PCD (EPCD), and cells in late stages of PCD (LPCD). Window stage leaves were stained with the mitochondrial dye MitoTracker Red CMXRos and examined. Mitochondrial dynamics were delineated into four categories (M1-M4) based on characteristics including distribution, motility, and membrane potential (ΔΨm). A TUNEL assay showed fragmented nDNA in a gradient over these mitochondrial stages. Chloroplasts and transvacuolar strands were also examined using live cell imaging. The possible importance of mitochondrial permeability transition pore (PTP) formation during PCD was indirectly examined via in vivo cyclosporine A (CsA) treatment. This treatment resulted in lace plant leaves with a significantly lower number of perforations compared to controls, and that displayed mitochondrial dynamics similar to that of non-PCD cells.'],
'labels': ['BACKGROUND', 'RESULTS'],
'meshes': ['Alismataceae',
'Apoptosis',
'Cell Differentiation',
'Mitochondria',
'Plant Leaves'],
'reasoning_free_pred': ['y', 'e', 's'],
'reasoning_required_pred': ['y', 'e', 's']},
'final_decision': 'yes',
'long_answer': 'Results depicted mitochondrial dynamics in vivo as PCD progresses within the lace plant, and highlight the correlation of this organelle with other organelles during developmental PCD. To the best of our knowledge, this is the first report of mitochondria and chloroplasts moving on transvacuolar strands to form a ring structure surrounding the nucleus during developmental PCD. Also, for the first time, we have shown the feasibility for the use of CsA in a whole plant system. Overall, our findings implicate the mitochondria as playing a critical and early role in developmentally regulated PCD in the lace plant.',
'pubid': 21645374,
'question': 'Do mitochondria play a role in remodelling lace plant leaves during programmed cell death?'}
```
### Data Fields
* **NER**
* `id`: string
* `ner_tags`: Sequence[ClassLabel]
* `tokens`: Sequence[String]
* **PICO**
* To be added
* **Relation Extraction**
* To be added
* **Sentence Similarity**
* `sentence 1`: string
* `sentence 2`: string
* `score`: float ranging from 0 (no relation) to 4 (equivalent)
* **Document Classification**
* To be added
* **Question Answering**
* PubMedQA
* `pubid`: integer
* `question`: string
* `context`: sequence of strings [`contexts`, `labels`, `meshes`, `reasoning_required_pred`, `reasoning_free_pred`]
* `long_answer`: string
* `final_decision`: string
### Data Splits
Shown in the table of supported tasks.
## Dataset Creation
### Curation Rationale
* BC5-chem
* BC5-disease
* BC2GM
* JNLPBA
* EBM PICO
* ChemProt
* DDI
* GAD
* BIOSSES
* HoC
* PubMedQA
* BioASQ
### Source Data
[More Information Needed]
### Annotations
All the datasets have been obtained and annotated by experts in the biomedical domain. Check the different citations for further details.
#### Annotation process
* BC5-chem
* BC5-disease
* BC2GM
* JNLPBA
* EBM PICO
* ChemProt
* DDI
* GAD
* BIOSSES - The sentence pairs were evaluated by five different human experts that judged their similarity and gave scores ranging from 0 (no relation) to 4 (equivalent). The score range was described based on the guidelines of SemEval 2012 Task 6 on STS (Agirre et al., 2012). Besides the annotation instructions, example sentences from the biomedical literature were provided to the annotators for each of the similarity degrees.
* HoC
* PubMedQA
* BioASQ
### Dataset Curators
All the datasets have been obtained and annotated by experts in thebiomedical domain. Check the different citations for further details.
### Licensing Information
* BC5-chem
* BC5-disease
* BC2GM
* JNLPBA
* EBM PICO
* ChemProt
* DDI
* GAD
* BIOSSES - BIOSSES is made available under the terms of [The GNU Common Public License v.3.0](https://www.gnu.org/licenses/gpl-3.0.en.html).
* HoC
* PubMedQA - MIT License Copyright (c) 2019 pubmedqa
* BioASQ
### Citation Information
* BC5-chem & BC5-disease
```latex
@article{article,
author = {Li, Jiao and Sun, Yueping and Johnson, Robin and Sciaky, Daniela and Wei, Chih-Hsuan and Leaman, Robert and Davis, Allan Peter and Mattingly, Carolyn and Wiegers, Thomas and lu, Zhiyong},
year = {2016},
month = {05},
pages = {baw068},
title = {BioCreative V CDR task corpus: a resource for chemical disease relation extraction},
volume = {2016},
journal = {Database},
doi = {10.1093/database/baw068}
}
```
* BC2GM
```latex
@article{article,
author = {Smith, Larry and Tanabe, Lorraine and Ando, Rie and Kuo, Cheng-Ju and Chung, I-Fang and Hsu, Chun-Nan and Lin, Yu-Shi and Klinger, Roman and Friedrich, Christoph and Ganchev, Kuzman and Torii, Manabu and Liu, Hongfang and Haddow, Barry and Struble, Craig and Povinelli, Richard and Vlachos, Andreas and Baumgartner Jr, William and Hunter, Lawrence and Carpenter, Bob and Wilbur, W.},
year = {2008},
month = {09},
pages = {S2},
title = {Overview of BioCreative II gene mention recognition},
volume = {9 Suppl 2},
journal = {Genome biology},
doi = {10.1186/gb-2008-9-s2-s2}
}
```
* JNLPBA
```latex
@inproceedings{collier-kim-2004-introduction,
title = "Introduction to the Bio-entity Recognition Task at {JNLPBA}",
author = "Collier, Nigel and
Kim, Jin-Dong",
booktitle = "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications ({NLPBA}/{B}io{NLP})",
month = aug # " 28th and 29th",
year = "2004",
address = "Geneva, Switzerland",
publisher = "COLING",
url = "https://aclanthology.org/W04-1213",
pages = "73--78",
}
```
* NCBI Disiease
```latex
@article{10.5555/2772763.2772800,
author = {Dogan, Rezarta Islamaj and Leaman, Robert and Lu, Zhiyong},
title = {NCBI Disease Corpus},
year = {2014},
issue_date = {February 2014},
publisher = {Elsevier Science},
address = {San Diego, CA, USA},
volume = {47},
number = {C},
issn = {1532-0464},
abstract = {Graphical abstractDisplay Omitted NCBI disease corpus is built as a gold-standard resource for disease recognition.793 PubMed abstracts are annotated with disease mentions and concepts (MeSH/OMIM).14 Annotators produced high consistency level and inter-annotator agreement.Normalization benchmark results demonstrate the utility of the corpus.The corpus is publicly available to the community. Information encoded in natural language in biomedical literature publications is only useful if efficient and reliable ways of accessing and analyzing that information are available. Natural language processing and text mining tools are therefore essential for extracting valuable information, however, the development of powerful, highly effective tools to automatically detect central biomedical concepts such as diseases is conditional on the availability of annotated corpora.This paper presents the disease name and concept annotations of the NCBI disease corpus, a collection of 793 PubMed abstracts fully annotated at the mention and concept level to serve as a research resource for the biomedical natural language processing community. Each PubMed abstract was manually annotated by two annotators with disease mentions and their corresponding concepts in Medical Subject Headings (MeSH ) or Online Mendelian Inheritance in Man (OMIM ). Manual curation was performed using PubTator, which allowed the use of pre-annotations as a pre-step to manual annotations. Fourteen annotators were randomly paired and differing annotations were discussed for reaching a consensus in two annotation phases. In this setting, a high inter-annotator agreement was observed. Finally, all results were checked against annotations of the rest of the corpus to assure corpus-wide consistency.The public release of the NCBI disease corpus contains 6892 disease mentions, which are mapped to 790 unique disease concepts. Of these, 88% link to a MeSH identifier, while the rest contain an OMIM identifier. We were able to link 91% of the mentions to a single disease concept, while the rest are described as a combination of concepts. In order to help researchers use the corpus to design and test disease identification methods, we have prepared the corpus as training, testing and development sets. To demonstrate its utility, we conducted a benchmarking experiment where we compared three different knowledge-based disease normalization methods with a best performance in F-measure of 63.7%. These results show that the NCBI disease corpus has the potential to significantly improve the state-of-the-art in disease name recognition and normalization research, by providing a high-quality gold standard thus enabling the development of machine-learning based approaches for such tasks.The NCBI disease corpus, guidelines and other associated resources are available at: http://www.ncbi.nlm.nih.gov/CBBresearch/Dogan/DISEASE/.},
journal = {J. of Biomedical Informatics},
month = {feb},
pages = {1–10},
numpages = {10}}
```
* EBM PICO
* ChemProt
* DDI
* GAD
* BIOSSES
```latex
@article{souganciouglu2017biosses,
title={BIOSSES: a semantic sentence similarity estimation system for the biomedical domain},
author={So{\u{g}}anc{\i}o{\u{g}}lu, Gizem and {\"O}zt{\"u}rk, Hakime and {\"O}zg{\"u}r, Arzucan},
journal={Bioinformatics},
volume={33},
number={14},
pages={i49--i58},
year={2017},
publisher={Oxford University Press}
}
```
* HoC
* PubMedQA
```latex
@inproceedings{jin2019pubmedqa,
title={PubMedQA: A Dataset for Biomedical Research Question Answering},
author={Jin, Qiao and Dhingra, Bhuwan and Liu, Zhengping and Cohen, William and Lu, Xinghua},
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)},
pages={2567--2577},
year={2019}
}
```
* BioASQ
```latex
@article{10.1093/bioinformatics/btv585,
author = {Baker, Simon and Silins, Ilona and Guo, Yufan and Ali, Imran and Högberg, Johan and Stenius, Ulla and Korhonen, Anna},
title = "{Automatic semantic classification of scientific literature according to the hallmarks of cancer}",
journal = {Bioinformatics},
volume = {32},
number = {3},
pages = {432-440},
year = {2015},
month = {10},
abstract = "{Motivation: The hallmarks of cancer have become highly influential in cancer research. They reduce the complexity of cancer into 10 principles (e.g. resisting cell death and sustaining proliferative signaling) that explain the biological capabilities acquired during the development of human tumors. Since new research depends crucially on existing knowledge, technology for semantic classification of scientific literature according to the hallmarks of cancer could greatly support literature review, knowledge discovery and applications in cancer research.Results: We present the first step toward the development of such technology. We introduce a corpus of 1499 PubMed abstracts annotated according to the scientific evidence they provide for the 10 currently known hallmarks of cancer. We use this corpus to train a system that classifies PubMed literature according to the hallmarks. The system uses supervised machine learning and rich features largely based on biomedical text mining. We report good performance in both intrinsic and extrinsic evaluations, demonstrating both the accuracy of the methodology and its potential in supporting practical cancer research. We discuss how this approach could be developed and applied further in the future.Availability and implementation: The corpus of hallmark-annotated PubMed abstracts and the software for classification are available at: http://www.cl.cam.ac.uk/∼sb895/HoC.html .Contact:simon.baker@cl.cam.ac.uk}",
issn = {1367-4803},
doi = {10.1093/bioinformatics/btv585},
url = {https://doi.org/10.1093/bioinformatics/btv585},
eprint = {https://academic.oup.com/bioinformatics/article-pdf/32/3/432/19568147/btv585.pdf},
}
```
### Contributions
* This dataset has been uploaded and generated by Dr. Jorge Abreu Vicente.
* Thanks to [@GamalC](https://github.com/GamalC) for uploading the NER datasets to GitHub, from where I got them.
* I am not part of the team that generated BLURB. This dataset is intended to help researchers to usethe BLURB benchmarking for NLP in Biomedical NLP.
* Thanks to [@bwang482](https://github.com/bwang482) for uploading the [BIOSSES dataset](https://github.com/bwang482/datasets/tree/master/datasets/biosses). We forked the [BIOSSES 🤗 dataset](https://huggingface.co/datasets/biosses) to add it to this BLURB benchmark.
* Thank you to [@tuner007](https://github.com/tuner007) for adding this dataset to the 🤗 hub |
amitness/logits-mt-it-en-128 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: input_ids
sequence: int32
- name: token_type_ids
sequence: int8
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
- name: teacher_logits
sequence:
sequence: float64
- name: teacher_indices
sequence:
sequence: int64
- name: teacher_mask_indices
sequence: int64
splits:
- name: train
num_bytes: 184467361976
num_examples: 40721350
- name: test
num_bytes: 32556394204
num_examples: 7186121
download_size: 0
dataset_size: 217023756180
---
# Dataset Card for "logits-mt-it-en-128"
[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_160 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1179561800.0
num_examples: 231650
download_size: 1204413894
dataset_size: 1179561800.0
---
# Dataset Card for "chunk_160"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
tyzhu/random_letter_same_length_find_passage_train100_eval20_num | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 65966
num_examples: 220
- name: validation
num_bytes: 7230
num_examples: 20
download_size: 38059
dataset_size: 73196
---
# Dataset Card for "random_letter_same_length_find_passage_train100_eval20_num"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
CyberHarem/priscilla_barielle_rezero | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of priscilla_barielle (Re:Zero Kara Hajimeru Isekai Seikatsu)
This is the dataset of priscilla_barielle (Re:Zero Kara Hajimeru Isekai Seikatsu), containing 99 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)).
|
open-llm-leaderboard/details_Azazelle__Maylin-7b | ---
pretty_name: Evaluation run of Azazelle/Maylin-7b
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Azazelle/Maylin-7b](https://huggingface.co/Azazelle/Maylin-7b) on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Azazelle__Maylin-7b\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-06T01:33:38.195663](https://huggingface.co/datasets/open-llm-leaderboard/details_Azazelle__Maylin-7b/blob/main/results_2024-01-06T01-33-38.195663.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\": 0.650037625513185,\n\
\ \"acc_stderr\": 0.03213448107330077,\n \"acc_norm\": 0.651334351528279,\n\
\ \"acc_norm_stderr\": 0.03278208864901647,\n \"mc1\": 0.4320685434516524,\n\
\ \"mc1_stderr\": 0.017341202394988257,\n \"mc2\": 0.6024386703470505,\n\
\ \"mc2_stderr\": 0.015575773993225956\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6382252559726962,\n \"acc_stderr\": 0.01404195794503808,\n\
\ \"acc_norm\": 0.6680887372013652,\n \"acc_norm_stderr\": 0.013760988200880541\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6834295956980682,\n\
\ \"acc_stderr\": 0.004641876299335626,\n \"acc_norm\": 0.8639713204540929,\n\
\ \"acc_norm_stderr\": 0.0034211839093201534\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.04793724854411021,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.04793724854411021\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6074074074074074,\n\
\ \"acc_stderr\": 0.0421850621536888,\n \"acc_norm\": 0.6074074074074074,\n\
\ \"acc_norm_stderr\": 0.0421850621536888\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6907894736842105,\n \"acc_stderr\": 0.037610708698674805,\n\
\ \"acc_norm\": 0.6907894736842105,\n \"acc_norm_stderr\": 0.037610708698674805\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.57,\n\
\ \"acc_stderr\": 0.049756985195624284,\n \"acc_norm\": 0.57,\n \
\ \"acc_norm_stderr\": 0.049756985195624284\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7056603773584905,\n \"acc_stderr\": 0.02804918631569526,\n\
\ \"acc_norm\": 0.7056603773584905,\n \"acc_norm_stderr\": 0.02804918631569526\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7291666666666666,\n\
\ \"acc_stderr\": 0.03716177437566017,\n \"acc_norm\": 0.7291666666666666,\n\
\ \"acc_norm_stderr\": 0.03716177437566017\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \
\ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \
\ },\n \"harness|hendrycksTest-college_computer_science|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_mathematics|5\"\
: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \
\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6647398843930635,\n\
\ \"acc_stderr\": 0.03599586301247077,\n \"acc_norm\": 0.6647398843930635,\n\
\ \"acc_norm_stderr\": 0.03599586301247077\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.4215686274509804,\n \"acc_stderr\": 0.049135952012744975,\n\
\ \"acc_norm\": 0.4215686274509804,\n \"acc_norm_stderr\": 0.049135952012744975\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n\
\ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.6,\n \"acc_stderr\": 0.03202563076101735,\n \
\ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.03202563076101735\n },\n\
\ \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5175438596491229,\n\
\ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.5175438596491229,\n\
\ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5379310344827586,\n \"acc_stderr\": 0.04154659671707548,\n\
\ \"acc_norm\": 0.5379310344827586,\n \"acc_norm_stderr\": 0.04154659671707548\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.4126984126984127,\n \"acc_stderr\": 0.025355741263055266,\n \"\
acc_norm\": 0.4126984126984127,\n \"acc_norm_stderr\": 0.025355741263055266\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\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7967741935483871,\n\
\ \"acc_stderr\": 0.02289168798455496,\n \"acc_norm\": 0.7967741935483871,\n\
\ \"acc_norm_stderr\": 0.02289168798455496\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\": 0.7,\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\": 0.033175059300091805,\n\
\ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.033175059300091805\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586815,\n \"\
acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586815\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\": 0.6743589743589744,\n \"acc_stderr\": 0.02375966576741229,\n \
\ \"acc_norm\": 0.6743589743589744,\n \"acc_norm_stderr\": 0.02375966576741229\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.34814814814814815,\n \"acc_stderr\": 0.029045600290616248,\n \
\ \"acc_norm\": 0.34814814814814815,\n \"acc_norm_stderr\": 0.029045600290616248\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.7100840336134454,\n \"acc_stderr\": 0.029472485833136098,\n\
\ \"acc_norm\": 0.7100840336134454,\n \"acc_norm_stderr\": 0.029472485833136098\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3841059602649007,\n \"acc_stderr\": 0.03971301814719197,\n \"\
acc_norm\": 0.3841059602649007,\n \"acc_norm_stderr\": 0.03971301814719197\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8385321100917431,\n \"acc_stderr\": 0.015776239256163248,\n \"\
acc_norm\": 0.8385321100917431,\n \"acc_norm_stderr\": 0.015776239256163248\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5185185185185185,\n \"acc_stderr\": 0.034076320938540516,\n \"\
acc_norm\": 0.5185185185185185,\n \"acc_norm_stderr\": 0.034076320938540516\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8480392156862745,\n \"acc_stderr\": 0.025195658428931796,\n \"\
acc_norm\": 0.8480392156862745,\n \"acc_norm_stderr\": 0.025195658428931796\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.8185654008438819,\n \"acc_stderr\": 0.025085961144579654,\n \
\ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.025085961144579654\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7040358744394619,\n\
\ \"acc_stderr\": 0.030636591348699803,\n \"acc_norm\": 0.7040358744394619,\n\
\ \"acc_norm_stderr\": 0.030636591348699803\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.036412970813137296,\n\
\ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.036412970813137296\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7933884297520661,\n \"acc_stderr\": 0.03695980128098824,\n \"\
acc_norm\": 0.7933884297520661,\n \"acc_norm_stderr\": 0.03695980128098824\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7962962962962963,\n\
\ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\
\ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7791411042944786,\n \"acc_stderr\": 0.03259177392742178,\n\
\ \"acc_norm\": 0.7791411042944786,\n \"acc_norm_stderr\": 0.03259177392742178\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.48214285714285715,\n\
\ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.48214285714285715,\n\
\ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\
\ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8632478632478633,\n\
\ \"acc_stderr\": 0.022509033937077805,\n \"acc_norm\": 0.8632478632478633,\n\
\ \"acc_norm_stderr\": 0.022509033937077805\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \
\ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.045126085985421276\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8352490421455939,\n\
\ \"acc_stderr\": 0.013265346261323798,\n \"acc_norm\": 0.8352490421455939,\n\
\ \"acc_norm_stderr\": 0.013265346261323798\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7456647398843931,\n \"acc_stderr\": 0.023445826276545543,\n\
\ \"acc_norm\": 0.7456647398843931,\n \"acc_norm_stderr\": 0.023445826276545543\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.38994413407821227,\n\
\ \"acc_stderr\": 0.01631237662921307,\n \"acc_norm\": 0.38994413407821227,\n\
\ \"acc_norm_stderr\": 0.01631237662921307\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\": 0.7106109324758842,\n\
\ \"acc_stderr\": 0.025755865922632945,\n \"acc_norm\": 0.7106109324758842,\n\
\ \"acc_norm_stderr\": 0.025755865922632945\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7314814814814815,\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\": 0.46099290780141844,\n \"acc_stderr\": 0.029736592526424438,\n \
\ \"acc_norm\": 0.46099290780141844,\n \"acc_norm_stderr\": 0.029736592526424438\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.47979139504563234,\n\
\ \"acc_stderr\": 0.012759801427767564,\n \"acc_norm\": 0.47979139504563234,\n\
\ \"acc_norm_stderr\": 0.012759801427767564\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.7279411764705882,\n \"acc_stderr\": 0.027033041151681456,\n\
\ \"acc_norm\": 0.7279411764705882,\n \"acc_norm_stderr\": 0.027033041151681456\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6388888888888888,\n \"acc_stderr\": 0.01943177567703731,\n \
\ \"acc_norm\": 0.6388888888888888,\n \"acc_norm_stderr\": 0.01943177567703731\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6363636363636364,\n\
\ \"acc_stderr\": 0.04607582090719976,\n \"acc_norm\": 0.6363636363636364,\n\
\ \"acc_norm_stderr\": 0.04607582090719976\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7306122448979592,\n \"acc_stderr\": 0.02840125202902294,\n\
\ \"acc_norm\": 0.7306122448979592,\n \"acc_norm_stderr\": 0.02840125202902294\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8606965174129353,\n\
\ \"acc_stderr\": 0.024484487162913973,\n \"acc_norm\": 0.8606965174129353,\n\
\ \"acc_norm_stderr\": 0.024484487162913973\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.88,\n \"acc_stderr\": 0.03265986323710906,\n \
\ \"acc_norm\": 0.88,\n \"acc_norm_stderr\": 0.03265986323710906\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\": 0.8187134502923976,\n \"acc_stderr\": 0.02954774168764004,\n\
\ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.02954774168764004\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4320685434516524,\n\
\ \"mc1_stderr\": 0.017341202394988257,\n \"mc2\": 0.6024386703470505,\n\
\ \"mc2_stderr\": 0.015575773993225956\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7963693764798737,\n \"acc_stderr\": 0.011317798781626915\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6376042456406369,\n \
\ \"acc_stderr\": 0.013240654263574755\n }\n}\n```"
repo_url: https://huggingface.co/Azazelle/Maylin-7b
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|arc:challenge|25_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|gsm8k|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hellaswag|10_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-06T01-33-38.195663.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-06T01-33-38.195663.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- '**/details_harness|winogrande|5_2024-01-06T01-33-38.195663.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-06T01-33-38.195663.parquet'
- config_name: results
data_files:
- split: 2024_01_06T01_33_38.195663
path:
- results_2024-01-06T01-33-38.195663.parquet
- split: latest
path:
- results_2024-01-06T01-33-38.195663.parquet
---
# Dataset Card for Evaluation run of Azazelle/Maylin-7b
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Azazelle/Maylin-7b](https://huggingface.co/Azazelle/Maylin-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_Azazelle__Maylin-7b",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-06T01:33:38.195663](https://huggingface.co/datasets/open-llm-leaderboard/details_Azazelle__Maylin-7b/blob/main/results_2024-01-06T01-33-38.195663.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": 0.650037625513185,
"acc_stderr": 0.03213448107330077,
"acc_norm": 0.651334351528279,
"acc_norm_stderr": 0.03278208864901647,
"mc1": 0.4320685434516524,
"mc1_stderr": 0.017341202394988257,
"mc2": 0.6024386703470505,
"mc2_stderr": 0.015575773993225956
},
"harness|arc:challenge|25": {
"acc": 0.6382252559726962,
"acc_stderr": 0.01404195794503808,
"acc_norm": 0.6680887372013652,
"acc_norm_stderr": 0.013760988200880541
},
"harness|hellaswag|10": {
"acc": 0.6834295956980682,
"acc_stderr": 0.004641876299335626,
"acc_norm": 0.8639713204540929,
"acc_norm_stderr": 0.0034211839093201534
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.35,
"acc_stderr": 0.04793724854411021,
"acc_norm": 0.35,
"acc_norm_stderr": 0.04793724854411021
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6074074074074074,
"acc_stderr": 0.0421850621536888,
"acc_norm": 0.6074074074074074,
"acc_norm_stderr": 0.0421850621536888
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6907894736842105,
"acc_stderr": 0.037610708698674805,
"acc_norm": 0.6907894736842105,
"acc_norm_stderr": 0.037610708698674805
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.57,
"acc_stderr": 0.049756985195624284,
"acc_norm": 0.57,
"acc_norm_stderr": 0.049756985195624284
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7056603773584905,
"acc_stderr": 0.02804918631569526,
"acc_norm": 0.7056603773584905,
"acc_norm_stderr": 0.02804918631569526
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7291666666666666,
"acc_stderr": 0.03716177437566017,
"acc_norm": 0.7291666666666666,
"acc_norm_stderr": 0.03716177437566017
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.49,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.49,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.52,
"acc_stderr": 0.050211673156867795,
"acc_norm": 0.52,
"acc_norm_stderr": 0.050211673156867795
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.33,
"acc_stderr": 0.04725815626252604,
"acc_norm": 0.33,
"acc_norm_stderr": 0.04725815626252604
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6647398843930635,
"acc_stderr": 0.03599586301247077,
"acc_norm": 0.6647398843930635,
"acc_norm_stderr": 0.03599586301247077
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.4215686274509804,
"acc_stderr": 0.049135952012744975,
"acc_norm": 0.4215686274509804,
"acc_norm_stderr": 0.049135952012744975
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.75,
"acc_stderr": 0.04351941398892446,
"acc_norm": 0.75,
"acc_norm_stderr": 0.04351941398892446
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.6,
"acc_stderr": 0.03202563076101735,
"acc_norm": 0.6,
"acc_norm_stderr": 0.03202563076101735
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.5175438596491229,
"acc_stderr": 0.04700708033551038,
"acc_norm": 0.5175438596491229,
"acc_norm_stderr": 0.04700708033551038
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5379310344827586,
"acc_stderr": 0.04154659671707548,
"acc_norm": 0.5379310344827586,
"acc_norm_stderr": 0.04154659671707548
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.4126984126984127,
"acc_stderr": 0.025355741263055266,
"acc_norm": 0.4126984126984127,
"acc_norm_stderr": 0.025355741263055266
},
"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": 0.32,
"acc_stderr": 0.04688261722621504,
"acc_norm": 0.32,
"acc_norm_stderr": 0.04688261722621504
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7967741935483871,
"acc_stderr": 0.02289168798455496,
"acc_norm": 0.7967741935483871,
"acc_norm_stderr": 0.02289168798455496
},
"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": 0.7,
"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": 0.033175059300091805,
"acc_norm": 0.7636363636363637,
"acc_norm_stderr": 0.033175059300091805
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7878787878787878,
"acc_stderr": 0.029126522834586815,
"acc_norm": 0.7878787878787878,
"acc_norm_stderr": 0.029126522834586815
},
"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": 0.6743589743589744,
"acc_stderr": 0.02375966576741229,
"acc_norm": 0.6743589743589744,
"acc_norm_stderr": 0.02375966576741229
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.34814814814814815,
"acc_stderr": 0.029045600290616248,
"acc_norm": 0.34814814814814815,
"acc_norm_stderr": 0.029045600290616248
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.7100840336134454,
"acc_stderr": 0.029472485833136098,
"acc_norm": 0.7100840336134454,
"acc_norm_stderr": 0.029472485833136098
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.3841059602649007,
"acc_stderr": 0.03971301814719197,
"acc_norm": 0.3841059602649007,
"acc_norm_stderr": 0.03971301814719197
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8385321100917431,
"acc_stderr": 0.015776239256163248,
"acc_norm": 0.8385321100917431,
"acc_norm_stderr": 0.015776239256163248
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.5185185185185185,
"acc_stderr": 0.034076320938540516,
"acc_norm": 0.5185185185185185,
"acc_norm_stderr": 0.034076320938540516
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8480392156862745,
"acc_stderr": 0.025195658428931796,
"acc_norm": 0.8480392156862745,
"acc_norm_stderr": 0.025195658428931796
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.8185654008438819,
"acc_stderr": 0.025085961144579654,
"acc_norm": 0.8185654008438819,
"acc_norm_stderr": 0.025085961144579654
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.7040358744394619,
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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
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[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
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### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
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#### Who are the source data producers?
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### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
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#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
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#### 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
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[More Information Needed]
### Recommendations
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
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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
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raoulduke420/kohya-training | ---
license: openrail
---
|
adamjweintraut/lyrics_corrected_all | ---
dataset_info:
features:
- name: midi_id
dtype: string
- name: midi_filename
dtype: string
- name: song_title
dtype: string
- name: lyrics
dtype: string
- name: lyrics_autocorrected
dtype: string
- name: words_removed
sequence: string
- name: words_added
sequence: string
- name: rougeL_median_recall
dtype: float64
- name: rougeL_max_recall
dtype: float64
splits:
- name: etl
num_bytes: 27504
num_examples: 10
download_size: 37239
dataset_size: 27504
configs:
- config_name: default
data_files:
- split: etl
path: data/etl-*
---
|
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-677cfa-42096145090 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- adversarial_qa
eval_info:
task: extractive_question_answering
model: 123tarunanand/roberta-base-finetuned
metrics: ['bertscore']
dataset_name: adversarial_qa
dataset_config: adversarialQA
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: 123tarunanand/roberta-base-finetuned
* Dataset: adversarial_qa
* Config: adversarialQA
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@izara](https://huggingface.co/izara) for evaluating this model. |
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