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Sathvik-24/chachadata | 2023-10-05T13:03:04.000Z | [
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magnus42/test_train_hey | 2023-10-05T17:03:53.000Z | [
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MasterBruce1/test1 | 2023-10-05T18:56:59.000Z | [
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ayan1988/diffusion.2.textual_inversion | 2023-10-06T06:51:48.000Z | [
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# Dataset Card for "diffusion.2.textual_inversion"
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ikiransuryavanshi/llama_training3 | 2023-10-06T07:39:00.000Z | [
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SlothBot/common_voice_preprocessed_demo | 2023-10-06T10:26:12.000Z | [
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# Dataset Card for "common_voice_preprocessed_demo"
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vsarathy/nl-robotics-semantic-parsing-info_structure-2k-no-context-TEST | 2023-10-07T12:31:44.000Z | [
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pbaoo2705/qa_processed | 2023-10-08T02:17:04.000Z | [
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# Dataset Card for "qa_processed"
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pbaoo2705/qa_processed_eval | 2023-10-08T02:17:06.000Z | [
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# Dataset Card for "qa_processed_eval"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 667 | [
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H4438/nguyen-edu-date | 2023-10-08T18:18:38.000Z | [
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# Dataset Card for "nguyen-edu-date"
Left: 31694 rows - 0.38 %
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Falah/photogram_prompts | 2023-10-08T06:39:58.000Z | [
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# Dataset Card for "photogram_prompts"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 362 | [
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DialogueCharacter/english_preference_ultra_feedback_unfiltered | 2023-10-08T08:14:32.000Z | [
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# Dataset Card for "english_preference_ultra_feedback_unfiltered"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 432 | [
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destitech/ip-multi-ds | 2023-10-08T08:52:06.000Z | [
"region:us"
] | destitech | null | null | 1 | 4 | 2023-10-08T08:30:11 | ---
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# Dataset Card for "ip-multi-ds"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 539 | [
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Linyuyu/liumifan | 2023-10-12T10:00:17.000Z | [
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Dmkond/tune-forms | 2023-10-08T15:44:24.000Z | [
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# Dataset Card for "tune-forms"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 434 | [
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Ayansk11/llama2_merged_file | 2023-10-08T17:15:08.000Z | [
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gayanin/legal-es-masked | 2023-10-08T21:56:11.000Z | [
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# Dataset Card for "legal-es-masked"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 735 | [
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minyiche/llm4mol | 2023-10-09T18:01:54.000Z | [
"arxiv:2307.07443",
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# Dataset Card for Dataset Name
## Dataset Description
- **Paper:** [Can Large Language Models Empower Molecular Property Prediction?](https://arxiv.org/abs/2307.07443)
### Dataset Summary
Topic annotation in LLM4Mol is a in-context molecular classification task along with text explanations as molecular representations
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krthk/kapardhi_dataset | 2023-10-09T06:45:45.000Z | [
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Back-up/validation_data_T5 | 2023-10-09T06:58:57.000Z | [
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# Dataset Card for "validation_data_T5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 540 | [
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Colin23189/kaggle-exam-llm | 2023-10-09T08:34:21.000Z | [
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CWKSC/common_voice_13_0-ja-whisper-base | 2023-10-09T10:44:20.000Z | [
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# Dataset Card for "common_voice_13_0-ja-whisper-base"
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kolkata97/pellm0-zancanaro-split | 2023-10-09T12:43:38.000Z | [
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0.0379... |
tonywu71/PokemonCards_fixed | 2023-10-11T08:19:53.000Z | [
"task_categories:question-answering",
"language:en",
"license:mit",
"region:us"
] | tonywu71 | null | null | 0 | 4 | 2023-10-09T12:23:59 | ---
license: mit
dataset_info:
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dtype: string
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dtype: string
- name: caption
dtype: string
- name: name
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dtype: string
splits:
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num_bytes: 9474973.87624629
num_examples: 13088
download_size: 3028812
dataset_size: 9474973.87624629
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- question-answering
language:
- en
---
Fix for [TheFusion21/PokemonCards](https://huggingface.co/datasets/TheFusion21/PokemonCards), where the images with broken links were discarded. Tested while fine-tuning [HuggingFaceM4/idefics-9b](https://huggingface.co/HuggingFaceM4/idefics-9b) with LoRA using my custom Git repository: https://github.com/tonywu71/idefics-project. | 864 | [
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dmrau/cqadupstack-gaming-qrels | 2023-10-09T12:39:44.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:36:48 | ---
configs:
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---
# Dataset Card for "cqadupstack-gaming-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 514 | [
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dmrau/cqadupstack-mathematica-qrels | 2023-10-09T12:39:53.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:36:57 | ---
configs:
- config_name: default
data_files:
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dataset_size: 34691
---
# Dataset Card for "cqadupstack-mathematica-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 519 | [
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dmrau/cqadupstack-programmers-qrels | 2023-10-09T12:40:04.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:37:07 | ---
configs:
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---
# Dataset Card for "cqadupstack-programmers-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 519 | [
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dmrau/cqadupstack-tex-qrels | 2023-10-09T12:40:58.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:37:58 | ---
configs:
- config_name: default
data_files:
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path: data/test-*
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---
# Dataset Card for "cqadupstack-tex-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 513 | [
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dmrau/cqadupstack-english-qrels | 2023-10-09T12:41:19.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:38:19 | ---
configs:
- config_name: default
data_files:
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path: data/test-*
dataset_info:
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dataset_size: 100171
---
# Dataset Card for "cqadupstack-english-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 517 | [
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dmrau/cqadupstack-gis-qrels | 2023-10-09T12:41:29.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:38:30 | ---
configs:
- config_name: default
data_files:
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path: data/test-*
dataset_info:
features:
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dataset_size: 28952
---
# Dataset Card for "cqadupstack-gis-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 511 | [
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dmrau/cqadupstack-mathematica | 2023-10-09T12:39:52.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:39:48 | ---
configs:
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data_files:
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path: data/queries-*
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path: data/corpus-*
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---
# Dataset Card for "cqadupstack-mathematica"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 629 | [
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dmrau/cqadupstack-programmers | 2023-10-09T12:40:03.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:39:57 | ---
configs:
- config_name: default
data_files:
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path: data/queries-*
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---
# Dataset Card for "cqadupstack-programmers"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 629 | [
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dmrau/cqadupstack-tex | 2023-10-09T12:40:57.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:40:51 | ---
configs:
- config_name: default
data_files:
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---
# Dataset Card for "cqadupstack-tex"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 623 | [
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dmrau/cqadupstack-gis | 2023-10-09T12:41:28.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:41:23 | ---
configs:
- config_name: default
data_files:
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path: data/queries-*
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---
# Dataset Card for "cqadupstack-gis"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 621 | [
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dmrau/cqadupstack-physics | 2023-10-09T12:41:40.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:41:33 | ---
configs:
- config_name: default
data_files:
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path: data/queries-*
- split: corpus
path: data/corpus-*
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---
# Dataset Card for "cqadupstack-physics"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 626 | [
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dmrau/cqadupstack-physics-qrels | 2023-10-09T12:41:41.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:41:40 | ---
configs:
- config_name: default
data_files:
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path: data/test-*
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---
# Dataset Card for "cqadupstack-physics-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 519 | [
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dmrau/cqadupstack-stats | 2023-10-09T12:41:49.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:41:44 | ---
configs:
- config_name: default
data_files:
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path: data/queries-*
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---
# Dataset Card for "cqadupstack-stats"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 623 | [
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dmrau/cqadupstack-stats-qrels | 2023-10-09T12:41:50.000Z | [
"region:us"
] | dmrau | null | null | 0 | 4 | 2023-10-09T12:41:49 | ---
configs:
- config_name: default
data_files:
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---
# Dataset Card for "cqadupstack-stats-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 516 | [
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amphora/lmsys-filtered | 2023-10-09T17:57:19.000Z | [
"region:us"
] | amphora | null | null | 0 | 4 | 2023-10-09T17:55:20 | ---
dataset_info:
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---
# Dataset Card for "lmsys-filtered"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 644 | [
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princeton-nlp/SWE-bench_oracle_cl100k | 2023-10-17T13:59:27.000Z | [
"region:us"
] | princeton-nlp | null | null | 0 | 4 | 2023-10-10T04:11:10 | ---
dataset_info:
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configs:
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---
### Dataset Summary
SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. The dataset collects 2,294 Issue-Pull Request pairs from 12 popular Python. Evaluation is performed by unit test verification using post-PR behavior as the reference solution.
### Supported Tasks and Leaderboards
SWE-bench proposes a new task: issue resolution provided a full repository and GitHub issue. The leaderboard can be found at www.swebench.com
### Languages
The text of the dataset is primarily English, but we make no effort to filter or otherwise clean based on language type.
## Dataset Structure
### Data Instances
An example of a SWE-bench datum is as follows:
```
instance_id: (str) - A formatted instance identifier, usually as repo_owner__repo_name-PR-number.
patch: (str) - The gold patch, the patch generated by the PR (minus test-related code), that resolved the issue.
repo: (str) - The repository owner/name identifier from GitHub.
base_commit: (str) - The commit hash of the repository representing the HEAD of the repository before the solution PR is applied.
hints_text: (str) - Comments made on the issue prior to the creation of the solution PR’s first commit creation date.
created_at: (str) - The creation date of the pull request.
test_patch: (str) - A test-file patch that was contributed by the solution PR.
problem_statement: (str) - The issue title and body.
version: (str) - Installation version to use for running evaluation.
environment_setup_commit: (str) - commit hash to use for environment setup and installation.
FAIL_TO_PASS: (str) - A json list of strings that represent the set of tests resolved by the PR and tied to the issue resolution.
PASS_TO_PASS: (str) - A json list of strings that represent tests that should pass before and after the PR application.
text: (str) - The generated text according to the retrieval criterion and the style-2 prompt found in [github:SWE-bench](https://github.com/princeton-nlp/SWE-bench).
input_ids: (List[int]) - The llama tokens for each text.
```
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 3,018 | [
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infCapital/finance-alpaca_vi | 2023-10-10T04:40:29.000Z | [
"task_categories:question-answering",
"task_categories:text-generation",
"language:vi",
"license:apache-2.0",
"region:us"
] | infCapital | null | null | 0 | 4 | 2023-10-10T04:35:34 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 48252402
num_examples: 66665
download_size: 24622108
dataset_size: 48252402
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: apache-2.0
task_categories:
- question-answering
- text-generation
language:
- vi
---
# Dataset Card for "finance-alpaca_vi"
+ Origin dataset [finance-alpaca](https://huggingface.co/datasets/gbharti/finance-alpaca )
+ Translated into Vietnamese using OpenAI GPT3.5 API | 627 | [
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Hani89/medical_asr_recording_dataset | 2023-10-10T05:41:22.000Z | [
"task_categories:automatic-speech-recognition",
"size_categories:1K<n<10K",
"language:en",
"license:apache-2.0",
"medical",
"region:us"
] | Hani89 | null | null | 0 | 4 | 2023-10-10T05:13:04 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: audio
struct:
- name: array
sequence:
sequence: float32
- name: path
dtype: string
- name: sampling_rate
dtype: int64
- name: sentence
dtype: string
splits:
- name: train
num_bytes: 3128740048
num_examples: 5328
- name: test
num_bytes: 776455056
num_examples: 1333
download_size: 3882364624
dataset_size: 3905195104
license: apache-2.0
task_categories:
- automatic-speech-recognition
language:
- en
tags:
- medical
size_categories:
- 1K<n<10K
---
**Data Source**<br>
[Kaggle Medical Speech, Transcription, and Intent](https://www.kaggle.com/datasets/paultimothymooney/medical-speech-transcription-and-intent "Visit Original Dataset Page on Kaggle")<br>
**Context**<br>
>8.5 hours of audio utterances paired with text for common medical symptoms.<br>
**Content**<br>
>This data contains thousands of audio utterances for common medical symptoms like “knee pain” or “headache,” totaling more than 8 hours in aggregate. Each utterance was created by individual human contributors based on a given symptom. These audio snippets can be used to train conversational agents in the medical field.<br>
>
>This Figure Eight dataset was created via a multi-job workflow. The first involved contributors writing text phrases to describe symptoms given. For example, for “headache,” a contributor might write “I need help with my migraines.” Subsequent jobs captured audio utterances for accepted text strings.<br>
>
>Note that some of the labels are incorrect and some of the audio files have poor quality. I would recommend cleaning the dataset before training any machine learning models.<br>
>
>This dataset contains both the audio utterances and corresponding transcriptions.<br>
**What's new**<br>
*The data is clean from all columns except for the file_path and phrase<br>
*All Audios are loaded into the DatasetDict as an 1D array, float32<br>
*All Audios are resampled into 16K<br>
*The new structure :<br>
train = {<br>
'audio': {<br>
'path': file_path, *the mp3 files is not included here, please visit the kaggle to dowload em*<br>
'array': waveform_np,<br>
'sampling_rate': 16000<br>
},<br>
'sentence': the text transcription<br>
} | 2,472 | [
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0.01165... |
Jagadeesh-ti/sql-v4 | 2023-10-10T06:00:29.000Z | [
"region:us"
] | Jagadeesh-ti | null | null | 0 | 4 | 2023-10-10T06:00:06 | Entry not found | 15 | [
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0.0379... |
Falah/islamic_invention_prompts | 2023-10-10T06:12:22.000Z | [
"region:us"
] | Falah | null | null | 0 | 4 | 2023-10-10T06:11:41 | ---
dataset_info:
features:
- name: prompts
dtype: string
splits:
- name: train
num_bytes: 124665
num_examples: 1000
download_size: 2170
dataset_size: 124665
---
# Dataset Card for "islamic_invention_prompts"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 365 | [
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Linyuyu/zhenglaonian | 2023-10-12T09:14:42.000Z | [
"region:us"
] | Linyuyu | null | null | 0 | 4 | 2023-10-10T07:06:50 | Entry not found | 15 | [
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Colin23189/kaggle-llm-v2 | 2023-10-10T10:04:36.000Z | [
"region:us"
] | Colin23189 | null | null | 0 | 4 | 2023-10-10T09:56:48 | Entry not found | 15 | [
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umarigan/turkish_wikipedia_dataset_NER | 2023-10-10T17:12:30.000Z | [
"region:us"
] | umarigan | null | null | 0 | 4 | 2023-10-10T17:11:48 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: text
dtype: string
- name: title
dtype: string
- name: ner
list:
- name: end
dtype: int64
- name: entity
dtype: string
- name: index
dtype: int64
- name: score
dtype: float32
- name: start
dtype: int64
- name: word
dtype: string
- name: cleaned_ners
sequence: string
- name: cleaned_new
sequence: string
splits:
- name: train
num_bytes: 1781032869
num_examples: 265000
download_size: 698313289
dataset_size: 1781032869
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "turkish_wikipedia_dataset_NER"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 866 | [
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TanvirOnHF/InclusiveGenderIdentities | 2023-10-14T15:42:09.000Z | [
"size_categories:n<1K",
"language:en",
"license:cdla-sharing-1.0",
"GPT-3.5",
"GPT-4",
"Claude",
"Bard",
"Alpaca",
"LLaMA",
"LLaMA-2",
"Vicuna",
"PaLM-2",
"region:us"
] | TanvirOnHF | null | null | 0 | 4 | 2023-10-10T18:48:40 | ---
license: cdla-sharing-1.0
pretty_name: InclusiveGenderIdentities
tags:
- GPT-3.5
- GPT-4
- Claude
- Bard
- Alpaca
- LLaMA
- LLaMA-2
- Vicuna
- PaLM-2
language:
- en
size_categories:
- n<1K
---
# InclusiveGenderIdentities [JSON dataset]
A dataset comprising artificially generated fictitious gender identities, each crafted to promote inclusivity and diversity. These identities are entirely fictitious and are generated from a diverse array of sources, ensuring a wide representation.
## Dataset Contents
The dataset contains fictitious gender identities, each accompanied by a gender label, a description, and any relevant additional attributes. These gender identities are entirely fictional and are designed to encourage diversity and inclusivity.
The dataset aims to serve as a resource for educational and awareness purposes, fostering understanding and respect for a broad range of gender identities.
## Prompt
The prompt used:
```json
Generate a JSON-formatted dataset of fictitious gender identities, each comprising a gender label, a description, and any relevant additional attributes. The dataset should include a variety of gender identities to promote inclusivity and diversity. Example:
'''json
[
{
"gender": "Cislunar",
"description": "Individuals who identify with the space between Earth and the Moon, symbolizing a unique perspective and a connection to celestial bodies.",
"pronouns": ["they/them", "xe/xem"],
"optionalFields": {
"flag_colors": ["#001f3f", "#0074b7"]
}
},
{
"gender": "Floralgender",
"description": "A gender identity closely associated with the beauty and diversity of flowers, representing growth and transformation.",
"pronouns": ["she/her", "they/them"],
"optionalFields": {
"symbol": "🌸"
}
},
{
"gender": "Aquaphile",
"description": "A gender identity linked to a deep affinity for water and aquatic environments, often reflecting fluidity and adaptability.",
"pronouns": ["he/him", "they/them"],
"optionalFields": {
"favorite_aquatic_animal": "dolphin"
}
},
{
"gender": "Technomage",
"description": "A gender identity inspired by the fusion of technology and magic, embodying creativity and innovation.",
"pronouns": ["ze/hir", "it/its"],
"optionalFields": {
"description": "Holographic wings"
}
},
{
"gender": "Stellarian",
"description": "A gender identity associated with stars and the vastness of the cosmos, symbolizing endless possibilities and wonder.",
"pronouns": ["she/her", "they/them"],
"optionalFields": {
"constellation_sign": "Orion"
}
}
]
'''
```
## Disclaimer
Please note that while I strive to maintain data quality, I cannot guarantee the accuracy or quality of all entries in this dataset. Use it responsibly and exercise caution when relying on the data for any critical applications. Your feedback and contributions are greatly appreciated for improving the dataset's overall quality.
| 3,036 | [
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0.0369262695... |
zeio/baneks-speech | 2023-10-12T19:06:47.000Z | [
"task_categories:text-to-speech",
"task_categories:automatic-speech-recognition",
"language_creators:crowdsourced",
"language_creators:original",
"language_creators:machine-generated",
"size_categories:10K<n<100K",
"language:ru",
"language:en",
"license:apache-2.0",
"not-for-all-audiences",
"art... | zeio | This dataset contains speech generated for anecdotes from the [baneks dataset](https://huggingface.co/datasets/zeio/baneks) | null | 0 | 4 | 2023-10-10T22:19:35 | ---
language:
- ru
- en
license: apache-2.0
tags:
- not-for-all-audiences
- art
- humour
- jokes
annotation_creators:
- crowdsourced
- original
- machine-generated
language_creators:
- crowdsourced
- original
- machine-generated
pretty_name: baneks-speech
size_categories:
- 10K<n<100K
task_categories:
- text-to-speech
- automatic-speech-recognition
---
# Dataset card for baneks-speech
## Table of contents
- [Dataset description](#dataset-description)
- [Dataset summary](#dataset-summary)
- [Dataset structure](#dataset-structure)
- [Dataset instance](#dataset-instance)
- [Dataset fields](#dataset-fields)
## Dataset description
- **Homepage:** [baneks-speech homepage]()
- **Repository:** [baneks-speech repository](https://huggingface.co/datasets/zeio/baneks-speech)
- **Point of contact:** [Zeio Nara](mailto:zeionara@gmail.com)
- **Dataset version:** `10.10.2023`
### Dataset summary
This dataset contains speech generated for anekdotes parsed from a few vk social network communities using [stc model](https://cloud.speechpro.com/home).
The dataset corresponds to the **default** configuration from the [baneks](https://huggingface.co/datasets/zeio/baneks) dataset.
Since the dataset is regularly updated, there is no fixed number of entries, so stay tuned.
## Dataset structure
### Data instance
An example of an entry from the dataset is given below:
```json
{
'text': 'Сидят русский и казах Русский спрашивает: - Слушай, а у тебя жена есть? - Жок - Молодец! Я бы свою тоже сжег нахуй!',
'audio': {
'path': '/root/.cache/huggingface/datasets/downloads/extracted/e8abea39e83c61e4a60c5a4b0661dc044ae82cfcd84b26f966b87999f73ae92e/00476018.anekdotikategoriib.mp3',
'array': array([ 8.09500818e-07, 1.27653129e-06, 4.17583010e-07, ..., -8.52341486e-07, 9.19626189e-07, 1.67368569e-06]),
'sampling_rate': 22050
},
'artist': 'Vladimir_n',
'id': 476018,
'source': 'anekdotikategoriib'
}
```
### Data fields
Each dataset entry therefore consists of the following fields:
- `text` - text representation of the anecdote;
- `id` - id of the corresponding post;
- `source` - community name in which the corresponding post has been published;
- `artist` - identifier of the voice which was used for speech generation;
- `audio` - audio data read from an `mp3` file.
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adamkarvonen/chess_owt | 2023-10-11T01:41:19.000Z | [
"region:us"
] | adamkarvonen | null | null | 0 | 4 | 2023-10-11T01:39:26 | Entry not found | 15 | [
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MemGPT/wikipedia-embeddings | 2023-11-02T07:39:36.000Z | [
"license:apache-2.0",
"arxiv:2310.08560",
"region:us"
] | MemGPT | null | null | 5 | 4 | 2023-10-11T03:14:08 | ---
license: apache-2.0
---
`text-ada-002` computed on Wikipedia articles.
These were generated while evaluating [MemGPT](https://arxiv.org/abs/2310.08560). | 158 | [
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Coldog2333/dialseg711 | 2023-10-11T06:41:09.000Z | [
"size_categories:n<1K",
"language:en",
"license:mit",
"dialogue segmentation",
"region:us"
] | Coldog2333 | \ | @article{xu2020topic,
title={Topic-aware multi-turn dialogue modeling},
author={Xu, Yi and Zhao, Hai and Zhang, Zhuosheng},
journal={arXiv preprint arXiv:2009.12539},
year={2020}
} | 0 | 4 | 2023-10-11T06:36:02 | ---
license: mit
language:
- en
tags:
- dialogue segmentation
size_categories:
- n<1K
---
# Dataset Card for SuperDialseg
## 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://github.com/xyease/TADAM](https://github.com/xyease/TADAM)
- **Repository:** [https://github.com/xyease/TADAM](https://github.com/xyease/TADAM)
- **Paper:** Topic-aware multi-turn dialogue modeling
- **Leaderboard:**
- **Point of Contact:** jiangjf@is.s.u-tokyo.ac.jp
### Dataset Summary
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages: English
## Dataset Structure
### Data Instances
```
{
"dial_data": {
"dialseg711": [
{
"dial_id": "dialseg711_dial_000",
"turns": [
{
"da": "",
"role": "user",
"turn_id": 0,
"utterance": "check the weather for the 7 day forecast",
"topic_id": 0,
"segmentation_label": 0
},
...
{
"da": "",
"role": "agent",
"turn_id": 23,
"utterance": "Reminder set for your meeting at 11am on the 13th with management to discuss your company picnic. Is there anything else?",
"topic_id": 4,
"segmentation_label": 1
}
],
...
}
]
}
```
### Data Fields
#### Dialogue-Level
+ `dial_id`: ID of a dialogue;
+ `turns`: All utterances of a dialogue.
#### Utterance-Level
+ `da`: Dialogue Act annotation derived from the original DGDS dataset;
+ `role`: Role annotation derived from the original DGDS dataset;
+ `turn_id`: ID of an utterance;
+ `utterance`: Text of the utterance;
+ `topic_id`: ID (order) of the current topic;
+ `segmentation_label`: 1: it is the end of a topic; 0: others.
### Data Splits
Test only
## 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
MIT License
### Citation Information
@article{xu2020topic,
title={Topic-aware multi-turn dialogue modeling},
author={Xu, Yi and Zhao, Hai and Zhang, Zhuosheng},
journal={arXiv preprint arXiv:2009.12539},
year={2020}
}
### Contributions
+ Thanks to [@xyease](https://github.com/xyease) for constructing this dataset.
+ Thanks to [@Coldog2333](https://github.com/Coldog2333) for adding this dataset. | 4,055 | [
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renumics/spotlight-gigant-horse2zebra-enrichment | 2023-10-13T09:26:04.000Z | [
"region:us"
] | renumics | null | null | 0 | 4 | 2023-10-11T08:39:06 | ---
dataset_info:
config_name: horse
features:
- name: image.embedding
sequence: float32
length: 2
splits:
- name: train
num_bytes: 8536
num_examples: 1067
- name: test
num_bytes: 960
num_examples: 120
download_size: 15203
dataset_size: 9496
configs:
- config_name: horse
data_files:
- split: train
path: horse/train-*
- split: test
path: horse/test-*
---
# Dataset Card for "spotlight-gigant-horse2zebra-enrichment"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 603 | [
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0.0673828125,
0.034759521484375,
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-0.0291290283203125,
-0.0204925537109375,
... |
Tngarg/Codemix_tamil_english_test | 2023-10-11T12:09:04.000Z | [
"region:us"
] | Tngarg | null | null | 0 | 4 | 2023-10-11T12:09:03 | ---
dataset_info:
features:
- name: tweet
dtype: string
- name: sentiment
dtype: string
splits:
- name: train
num_bytes: 19614.4068653743
num_examples: 262
download_size: 13483
dataset_size: 19614.4068653743
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "Codemix_tamil_english_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 508 | [
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0.002... |
hongerzh/my-NFT-classifier-dataset2 | 2023-10-11T17:28:24.000Z | [
"region:us"
] | hongerzh | null | null | 0 | 4 | 2023-10-11T16:25:06 | ---
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: label
dtype:
class_label:
names:
'0': notsale
'1': sale
splits:
- name: train
num_bytes: 6616368416.534
num_examples: 28754
- name: validation
num_bytes: 2371905486.911
num_examples: 9593
- name: test
num_bytes: 2720948631.066
num_examples: 9569
download_size: 8806005035
dataset_size: 11709222534.511
---
# Dataset Card for "my-NFT-classifier-dataset2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 807 | [
[
-0.0426025390625,
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-0.009712... |
open-llm-leaderboard/details_Delcos__NATE-7b | 2023-10-12T03:23:23.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | 0 | 4 | 2023-10-12T03:22:21 | ---
pretty_name: Evaluation run of Delcos/NATE-7b
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Delcos/NATE-7b](https://huggingface.co/Delcos/NATE-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 61 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Delcos__NATE-7b\"\
,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2023-10-12T03:21:56.889828](https://huggingface.co/datasets/open-llm-leaderboard/details_Delcos__NATE-7b/blob/main/results_2023-10-12T03-21-56.889828.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\": 0.5894733182245001,\n\
\ \"acc_stderr\": 0.03414332313258469,\n \"acc_norm\": 0.5933830960354635,\n\
\ \"acc_norm_stderr\": 0.03412320397463523,\n \"mc1\": 0.3953488372093023,\n\
\ \"mc1_stderr\": 0.017115815632418197,\n \"mc2\": 0.571756969256499,\n\
\ \"mc2_stderr\": 0.01564827771634302\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5784982935153583,\n \"acc_stderr\": 0.014430197069326025,\n\
\ \"acc_norm\": 0.6092150170648464,\n \"acc_norm_stderr\": 0.014258563880513778\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.620991834295957,\n\
\ \"acc_stderr\": 0.004841486716855774,\n \"acc_norm\": 0.8209520015933081,\n\
\ \"acc_norm_stderr\": 0.0038260895866500536\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \
\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5111111111111111,\n\
\ \"acc_stderr\": 0.04318275491977976,\n \"acc_norm\": 0.5111111111111111,\n\
\ \"acc_norm_stderr\": 0.04318275491977976\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.5789473684210527,\n \"acc_stderr\": 0.04017901275981749,\n\
\ \"acc_norm\": 0.5789473684210527,\n \"acc_norm_stderr\": 0.04017901275981749\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.56,\n\
\ \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n \
\ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6415094339622641,\n \"acc_stderr\": 0.02951470358398177,\n\
\ \"acc_norm\": 0.6415094339622641,\n \"acc_norm_stderr\": 0.02951470358398177\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6180555555555556,\n\
\ \"acc_stderr\": 0.040629907841466674,\n \"acc_norm\": 0.6180555555555556,\n\
\ \"acc_norm_stderr\": 0.040629907841466674\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \
\ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\"\
: 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \
\ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.5606936416184971,\n\
\ \"acc_stderr\": 0.03784271932887467,\n \"acc_norm\": 0.5606936416184971,\n\
\ \"acc_norm_stderr\": 0.03784271932887467\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.047240073523838876,\n\
\ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.047240073523838876\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.68,\n \"acc_stderr\": 0.046882617226215055,\n \"acc_norm\": 0.68,\n\
\ \"acc_norm_stderr\": 0.046882617226215055\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5063829787234042,\n \"acc_stderr\": 0.032683358999363366,\n\
\ \"acc_norm\": 0.5063829787234042,\n \"acc_norm_stderr\": 0.032683358999363366\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.32456140350877194,\n\
\ \"acc_stderr\": 0.04404556157374767,\n \"acc_norm\": 0.32456140350877194,\n\
\ \"acc_norm_stderr\": 0.04404556157374767\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5310344827586206,\n \"acc_stderr\": 0.04158632762097828,\n\
\ \"acc_norm\": 0.5310344827586206,\n \"acc_norm_stderr\": 0.04158632762097828\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.36243386243386244,\n \"acc_stderr\": 0.02475747390275206,\n \"\
acc_norm\": 0.36243386243386244,\n \"acc_norm_stderr\": 0.02475747390275206\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.40476190476190477,\n\
\ \"acc_stderr\": 0.043902592653775614,\n \"acc_norm\": 0.40476190476190477,\n\
\ \"acc_norm_stderr\": 0.043902592653775614\n },\n \"harness|hendrycksTest-global_facts|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-high_school_biology|5\": {\n \"acc\": 0.7032258064516129,\n\
\ \"acc_stderr\": 0.025988500792411898,\n \"acc_norm\": 0.7032258064516129,\n\
\ \"acc_norm_stderr\": 0.025988500792411898\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.46798029556650245,\n \"acc_stderr\": 0.035107665979592154,\n\
\ \"acc_norm\": 0.46798029556650245,\n \"acc_norm_stderr\": 0.035107665979592154\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.57,\n \"acc_stderr\": 0.04975698519562428,\n \"acc_norm\"\
: 0.57,\n \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.703030303030303,\n \"acc_stderr\": 0.03567969772268049,\n\
\ \"acc_norm\": 0.703030303030303,\n \"acc_norm_stderr\": 0.03567969772268049\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7676767676767676,\n \"acc_stderr\": 0.030088629490217483,\n \"\
acc_norm\": 0.7676767676767676,\n \"acc_norm_stderr\": 0.030088629490217483\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8549222797927462,\n \"acc_stderr\": 0.025416343096306433,\n\
\ \"acc_norm\": 0.8549222797927462,\n \"acc_norm_stderr\": 0.025416343096306433\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6358974358974359,\n \"acc_stderr\": 0.024396672985094767,\n\
\ \"acc_norm\": 0.6358974358974359,\n \"acc_norm_stderr\": 0.024396672985094767\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.32222222222222224,\n \"acc_stderr\": 0.028493465091028597,\n \
\ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.028493465091028597\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6008403361344538,\n \"acc_stderr\": 0.03181110032413926,\n \
\ \"acc_norm\": 0.6008403361344538,\n \"acc_norm_stderr\": 0.03181110032413926\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\"\
: 0.7944954128440367,\n \"acc_stderr\": 0.017324352325016022,\n \"\
acc_norm\": 0.7944954128440367,\n \"acc_norm_stderr\": 0.017324352325016022\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.42592592592592593,\n \"acc_stderr\": 0.03372343271653064,\n \"\
acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.03372343271653064\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078962,\n \"\
acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078962\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7637130801687764,\n \"acc_stderr\": 0.027652153144159263,\n \
\ \"acc_norm\": 0.7637130801687764,\n \"acc_norm_stderr\": 0.027652153144159263\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7040358744394619,\n\
\ \"acc_stderr\": 0.030636591348699796,\n \"acc_norm\": 0.7040358744394619,\n\
\ \"acc_norm_stderr\": 0.030636591348699796\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.6412213740458015,\n \"acc_stderr\": 0.04206739313864908,\n\
\ \"acc_norm\": 0.6412213740458015,\n \"acc_norm_stderr\": 0.04206739313864908\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7024793388429752,\n \"acc_stderr\": 0.04173349148083499,\n \"\
acc_norm\": 0.7024793388429752,\n \"acc_norm_stderr\": 0.04173349148083499\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\
\ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\
\ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.6871165644171779,\n \"acc_stderr\": 0.03642914578292406,\n\
\ \"acc_norm\": 0.6871165644171779,\n \"acc_norm_stderr\": 0.03642914578292406\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4107142857142857,\n\
\ \"acc_stderr\": 0.04669510663875191,\n \"acc_norm\": 0.4107142857142857,\n\
\ \"acc_norm_stderr\": 0.04669510663875191\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7184466019417476,\n \"acc_stderr\": 0.044532548363264673,\n\
\ \"acc_norm\": 0.7184466019417476,\n \"acc_norm_stderr\": 0.044532548363264673\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8290598290598291,\n\
\ \"acc_stderr\": 0.024662496845209825,\n \"acc_norm\": 0.8290598290598291,\n\
\ \"acc_norm_stderr\": 0.024662496845209825\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \
\ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7752234993614304,\n\
\ \"acc_stderr\": 0.014927447101937153,\n \"acc_norm\": 0.7752234993614304,\n\
\ \"acc_norm_stderr\": 0.014927447101937153\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.6589595375722543,\n \"acc_stderr\": 0.025522474632121615,\n\
\ \"acc_norm\": 0.6589595375722543,\n \"acc_norm_stderr\": 0.025522474632121615\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.43798882681564244,\n\
\ \"acc_stderr\": 0.016593394227564846,\n \"acc_norm\": 0.43798882681564244,\n\
\ \"acc_norm_stderr\": 0.016593394227564846\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.6535947712418301,\n \"acc_stderr\": 0.02724561304721536,\n\
\ \"acc_norm\": 0.6535947712418301,\n \"acc_norm_stderr\": 0.02724561304721536\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6559485530546624,\n\
\ \"acc_stderr\": 0.026981478043648043,\n \"acc_norm\": 0.6559485530546624,\n\
\ \"acc_norm_stderr\": 0.026981478043648043\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.6697530864197531,\n \"acc_stderr\": 0.026168298456732852,\n\
\ \"acc_norm\": 0.6697530864197531,\n \"acc_norm_stderr\": 0.026168298456732852\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.4574468085106383,\n \"acc_stderr\": 0.029719281272236837,\n \
\ \"acc_norm\": 0.4574468085106383,\n \"acc_norm_stderr\": 0.029719281272236837\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.44589308996088656,\n\
\ \"acc_stderr\": 0.012695244711379778,\n \"acc_norm\": 0.44589308996088656,\n\
\ \"acc_norm_stderr\": 0.012695244711379778\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.5661764705882353,\n \"acc_stderr\": 0.03010563657001663,\n\
\ \"acc_norm\": 0.5661764705882353,\n \"acc_norm_stderr\": 0.03010563657001663\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.5915032679738562,\n \"acc_stderr\": 0.019886221037501862,\n \
\ \"acc_norm\": 0.5915032679738562,\n \"acc_norm_stderr\": 0.019886221037501862\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\
\ \"acc_stderr\": 0.04494290866252091,\n \"acc_norm\": 0.6727272727272727,\n\
\ \"acc_norm_stderr\": 0.04494290866252091\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.6612244897959184,\n \"acc_stderr\": 0.030299506562154185,\n\
\ \"acc_norm\": 0.6612244897959184,\n \"acc_norm_stderr\": 0.030299506562154185\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7810945273631841,\n\
\ \"acc_stderr\": 0.029239174636647,\n \"acc_norm\": 0.7810945273631841,\n\
\ \"acc_norm_stderr\": 0.029239174636647\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\": 0.5060240963855421,\n\
\ \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.5060240963855421,\n\
\ \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.7719298245614035,\n \"acc_stderr\": 0.032180937956023566,\n\
\ \"acc_norm\": 0.7719298245614035,\n \"acc_norm_stderr\": 0.032180937956023566\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3953488372093023,\n\
\ \"mc1_stderr\": 0.017115815632418197,\n \"mc2\": 0.571756969256499,\n\
\ \"mc2_stderr\": 0.01564827771634302\n }\n}\n```"
repo_url: https://huggingface.co/Delcos/NATE-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: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|arc:challenge|25_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hellaswag|10_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-12T03-21-56.889828.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-12T03-21-56.889828.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-12T03-21-56.889828.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-12T03-21-56.889828.parquet'
- config_name: results
data_files:
- split: 2023_10_12T03_21_56.889828
path:
- results_2023-10-12T03-21-56.889828.parquet
- split: latest
path:
- results_2023-10-12T03-21-56.889828.parquet
---
# Dataset Card for Evaluation run of Delcos/NATE-7b
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Delcos/NATE-7b
- **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 [Delcos/NATE-7b](https://huggingface.co/Delcos/NATE-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_Delcos__NATE-7b",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-12T03:21:56.889828](https://huggingface.co/datasets/open-llm-leaderboard/details_Delcos__NATE-7b/blob/main/results_2023-10-12T03-21-56.889828.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": 0.5894733182245001,
"acc_stderr": 0.03414332313258469,
"acc_norm": 0.5933830960354635,
"acc_norm_stderr": 0.03412320397463523,
"mc1": 0.3953488372093023,
"mc1_stderr": 0.017115815632418197,
"mc2": 0.571756969256499,
"mc2_stderr": 0.01564827771634302
},
"harness|arc:challenge|25": {
"acc": 0.5784982935153583,
"acc_stderr": 0.014430197069326025,
"acc_norm": 0.6092150170648464,
"acc_norm_stderr": 0.014258563880513778
},
"harness|hellaswag|10": {
"acc": 0.620991834295957,
"acc_stderr": 0.004841486716855774,
"acc_norm": 0.8209520015933081,
"acc_norm_stderr": 0.0038260895866500536
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.33,
"acc_stderr": 0.04725815626252605,
"acc_norm": 0.33,
"acc_norm_stderr": 0.04725815626252605
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.5111111111111111,
"acc_stderr": 0.04318275491977976,
"acc_norm": 0.5111111111111111,
"acc_norm_stderr": 0.04318275491977976
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.5789473684210527,
"acc_stderr": 0.04017901275981749,
"acc_norm": 0.5789473684210527,
"acc_norm_stderr": 0.04017901275981749
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.56,
"acc_stderr": 0.04988876515698589,
"acc_norm": 0.56,
"acc_norm_stderr": 0.04988876515698589
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6415094339622641,
"acc_stderr": 0.02951470358398177,
"acc_norm": 0.6415094339622641,
"acc_norm_stderr": 0.02951470358398177
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.6180555555555556,
"acc_stderr": 0.040629907841466674,
"acc_norm": 0.6180555555555556,
"acc_norm_stderr": 0.040629907841466674
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.42,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.42,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.51,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.51,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.36,
"acc_stderr": 0.04824181513244218,
"acc_norm": 0.36,
"acc_norm_stderr": 0.04824181513244218
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.5606936416184971,
"acc_stderr": 0.03784271932887467,
"acc_norm": 0.5606936416184971,
"acc_norm_stderr": 0.03784271932887467
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.3431372549019608,
"acc_stderr": 0.047240073523838876,
"acc_norm": 0.3431372549019608,
"acc_norm_stderr": 0.047240073523838876
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.68,
"acc_stderr": 0.046882617226215055,
"acc_norm": 0.68,
"acc_norm_stderr": 0.046882617226215055
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5063829787234042,
"acc_stderr": 0.032683358999363366,
"acc_norm": 0.5063829787234042,
"acc_norm_stderr": 0.032683358999363366
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.32456140350877194,
"acc_stderr": 0.04404556157374767,
"acc_norm": 0.32456140350877194,
"acc_norm_stderr": 0.04404556157374767
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5310344827586206,
"acc_stderr": 0.04158632762097828,
"acc_norm": 0.5310344827586206,
"acc_norm_stderr": 0.04158632762097828
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.36243386243386244,
"acc_stderr": 0.02475747390275206,
"acc_norm": 0.36243386243386244,
"acc_norm_stderr": 0.02475747390275206
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.40476190476190477,
"acc_stderr": 0.043902592653775614,
"acc_norm": 0.40476190476190477,
"acc_norm_stderr": 0.043902592653775614
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.35,
"acc_stderr": 0.0479372485441102,
"acc_norm": 0.35,
"acc_norm_stderr": 0.0479372485441102
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7032258064516129,
"acc_stderr": 0.025988500792411898,
"acc_norm": 0.7032258064516129,
"acc_norm_stderr": 0.025988500792411898
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.46798029556650245,
"acc_stderr": 0.035107665979592154,
"acc_norm": 0.46798029556650245,
"acc_norm_stderr": 0.035107665979592154
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.57,
"acc_stderr": 0.04975698519562428,
"acc_norm": 0.57,
"acc_norm_stderr": 0.04975698519562428
},
"harness|hendrycksTest-high_school_european_history|5": {
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```
### 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] | 64,813 | [
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Vishal24/brand | 2023-10-12T10:39:20.000Z | [
"region:us"
] | Vishal24 | null | null | 0 | 4 | 2023-10-12T09:33:46 | Entry not found | 15 | [
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carnival13/xlmr_int_pr_sw_trn_ep3 | 2023-10-12T10:35:09.000Z | [
"region:us"
] | carnival13 | null | null | 0 | 4 | 2023-10-12T10:34:48 | ---
dataset_info:
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download_size: 123139414
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configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "xlmr_int_pr_sw_trn_ep3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 621 | [
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IainRatherThanIan/TouchRugby | 2023-10-12T14:04:25.000Z | [
"task_categories:text-generation",
"size_categories:n<1K",
"language:en",
"fine-tuning",
"touch rugby",
"region:us"
] | IainRatherThanIan | null | null | 0 | 4 | 2023-10-12T13:58:58 | ---
task_categories:
- text-generation
language:
- en
tags:
- fine-tuning
- touch rugby
size_categories:
- n<1K
---
# Touch Rugby Rules Dataset (for embeddings)
train.csv is taken from the [International Touch Website](https://cdn.internationaltouch.org/public/FIT%205th%20Edition%20Rulebook.pdf)
test.csv is copy pasted from abbreviated rules on the [UK Touch website](https://www.englandtouch.org.uk/develop/coaching/the-rules/). Note that I'm bypassing the pdf to text stage.
All text is chunked to a length of 100 tokens with 50% overlap.
For educational and non-commercial use only. | 591 | [
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hippocrates/PubmedQA_train | 2023-10-12T16:17:38.000Z | [
"region:us"
] | hippocrates | null | null | 0 | 4 | 2023-10-12T16:17:31 | ---
dataset_info:
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- name: conversations
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---
# Dataset Card for "PubmedQA_train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 616 | [
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csupiisc/plmn_instruct_5k | 2023-10-12T17:04:01.000Z | [
"region:us"
] | csupiisc | null | null | 0 | 4 | 2023-10-12T17:03:58 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
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dtype: string
splits:
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num_examples: 1000
download_size: 229610
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---
# Dataset Card for "plmn_instruct_5k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 541 | [
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carnival13/xlmr_int_hard_curr_trn_ep2_corr | 2023-10-12T17:04:25.000Z | [
"region:us"
] | carnival13 | null | null | 0 | 4 | 2023-10-12T17:04:10 | ---
dataset_info:
features:
- name: domain_label
dtype: int64
- name: pass_label
dtype: int64
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dtype: string
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sequence: int32
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sequence: int8
splits:
- name: train
num_bytes: 285070021
num_examples: 226100
download_size: 80645458
dataset_size: 285070021
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "xlmr_int_hard_curr_trn_ep2_corr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 629 | [
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Brendan/icdst_multiwoz_turns_v21 | 2023-10-25T21:41:45.000Z | [
"region:us"
] | Brendan | null | null | 0 | 4 | 2023-10-13T00:12:36 | ---
dataset_info:
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---
# Dataset Card for "icdst_multiwoz_turns_v21"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 6,338 | [
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NathanRoll/commonvoice_test_labeled | 2023-10-13T02:56:06.000Z | [
"region:us"
] | NathanRoll | null | null | 0 | 4 | 2023-10-13T02:56:02 | ---
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---
# Dataset Card for "commonvoice_test_labeled"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 897 | [
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TynClause/isic-2017-dataset | 2023-10-13T04:51:13.000Z | [
"region:us"
] | TynClause | null | null | 0 | 4 | 2023-10-13T04:27:14 | ---
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---
# Dataset Card for "isic-2017-dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 824 | [
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ProjectsbyGaurav/LangChain_docs_usecases_integrations | 2023-10-13T06:51:21.000Z | [
"region:us"
] | ProjectsbyGaurav | null | null | 0 | 4 | 2023-10-13T06:48:18 | Entry not found | 15 | [
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nk2201/English-to-Hinglish | 2023-10-13T18:38:15.000Z | [
"size_categories:1K<n<10K",
"language:en",
"license:mit",
"translation",
"region:us"
] | nk2201 | null | null | 1 | 4 | 2023-10-13T17:23:54 | ---
license: mit
language:
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tags:
- translation
pretty_name: json
size_categories:
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---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## 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] | 4,462 | [
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judy93536/peri_text_summary_7k | 2023-10-13T21:55:17.000Z | [
"region:us"
] | judy93536 | null | null | 0 | 4 | 2023-10-13T21:54:55 | ---
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dataset_size: 15045022
---
# Dataset Card for "peri_text_summary_7k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 585 | [
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ken-sungmin/dataya-nolja-llama2-finetuning | 2023-10-14T06:18:54.000Z | [
"region:us"
] | ken-sungmin | null | null | 0 | 4 | 2023-10-14T00:27:33 | ---
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path: data/train-*
---
# Dataset Card for "dataya-nolja-llama2-finetuning"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 447 | [
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carnival13/rbrt_hard_curr_uda_ep3_corr | 2023-10-14T00:47:30.000Z | [
"region:us"
] | carnival13 | null | null | 0 | 4 | 2023-10-14T00:46:55 | ---
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---
# Dataset Card for "rbrt_hard_curr_uda_ep3_corr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 626 | [
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stevenhsu123/english_exam_train_data | 2023-10-20T05:12:17.000Z | [
"region:us"
] | stevenhsu123 | null | null | 0 | 4 | 2023-10-14T07:19:09 | Entry not found | 15 | [
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Rageshhf/finetunedata_short | 2023-10-14T18:30:18.000Z | [
"region:us"
] | Rageshhf | null | null | 0 | 4 | 2023-10-14T18:27:45 | ---
dataset_info:
features:
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configs:
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data_files:
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path: data/train-*
---
# Dataset Card for "finetunedata_short"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 446 | [
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cvinker/abcnotation_examples | 2023-10-14T23:35:39.000Z | [
"region:us"
] | cvinker | null | null | 0 | 4 | 2023-10-14T23:32:31 |
This is a collection of abc notation 'tunes' in the format of
``` {"text": "tune data"} ```
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ContextualAI/boolq_neighbors | 2023-10-14T23:35:29.000Z | [
"region:us"
] | ContextualAI | null | null | 0 | 4 | 2023-10-14T23:35:24 | ---
dataset_info:
features:
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configs:
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data_files:
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path: data/validation-*
---
# Dataset Card for "boolq_neighbors"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 672 | [
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hsali/librispeech_ds1 | 2023-10-15T06:49:19.000Z | [
"region:us"
] | hsali | null | null | 0 | 4 | 2023-10-15T06:48:30 | ---
dataset_info:
features:
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configs:
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---
# Dataset Card for "librispeech_ds1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 788 | [
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bobbybelajar/PegasusAmazon | 2023-10-15T07:27:46.000Z | [
"region:us"
] | bobbybelajar | null | null | 0 | 4 | 2023-10-15T07:26:13 | Entry not found | 15 | [
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gg7676/UserNavigation | 2023-10-15T20:00:41.000Z | [
"region:us"
] | gg7676 | null | null | 0 | 4 | 2023-10-15T19:48:03 | ---
# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
{}
---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## 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] | 4,563 | [
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Tngarg/hindi_train | 2023-10-16T11:20:59.000Z | [
"region:us"
] | Tngarg | null | null | 0 | 4 | 2023-10-16T11:20:51 | ---
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path: data/train-*
---
# Dataset Card for "hindi_train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 592 | [
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Tngarg/hindi_test | 2023-10-16T11:21:01.000Z | [
"region:us"
] | Tngarg | null | null | 0 | 4 | 2023-10-16T11:20:52 | ---
dataset_info:
features:
- name: 'Unnamed: 0'
dtype: int64
- name: text
dtype: string
- name: sentiment
dtype: string
- name: label
dtype: int64
- name: __index_level_0__
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splits:
- name: train
num_bytes: 81183
num_examples: 554
download_size: 53504
dataset_size: 81183
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "hindi_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 587 | [
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AndyLiu0104/Soldering-Data-Tiny-1016-solder-pad | 2023-10-16T13:41:00.000Z | [
"region:us"
] | AndyLiu0104 | null | null | 0 | 4 | 2023-10-16T13:36:24 | ---
dataset_info:
features:
- name: image
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- name: text
dtype: string
splits:
- name: train
num_bytes: 16637648.25
num_examples: 9606
download_size: 10646978
dataset_size: 16637648.25
---
# Dataset Card for "Soldering-Data-Tiny-1016-solder-pad"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 419 | [
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Starkate/Squad_1mon | 2023-10-16T17:05:00.000Z | [
"region:us"
] | Starkate | null | null | 0 | 4 | 2023-10-16T14:49:03 | Entry not found | 15 | [
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cc-platform-links/10_RANDOM_WAT_LINKS | 2023-10-16T20:18:05.000Z | [
"region:us"
] | cc-platform-links | null | null | 0 | 4 | 2023-10-16T20:09:43 | Entry not found | 15 | [
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sengunsipahi/civit_0.8 | 2023-10-17T01:05:44.000Z | [
"region:us"
] | sengunsipahi | null | null | 0 | 4 | 2023-10-17T01:05:18 | Entry not found | 15 | [
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sengunsipahi/civit_0.1_p1 | 2023-10-17T01:06:20.000Z | [
"region:us"
] | sengunsipahi | null | null | 0 | 4 | 2023-10-17T01:05:56 | Entry not found | 15 | [
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Globaly/glfamilias130k | 2023-10-17T03:22:41.000Z | [
"region:us"
] | Globaly | null | null | 0 | 4 | 2023-10-17T03:10:06 | Entry not found | 15 | [
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annahonghong/test | 2023-10-17T07:41:01.000Z | [
"region:us"
] | annahonghong | null | null | 0 | 4 | 2023-10-17T07:40:20 | Entry not found | 15 | [
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gamegyu/guanaco-llama2-100 | 2023-10-17T08:24:57.000Z | [
"region:us"
] | gamegyu | null | null | 0 | 4 | 2023-10-17T08:24:55 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 142459
num_examples: 100
download_size: 91410
dataset_size: 142459
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "guanaco-llama2-100"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 441 | [
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rizerphe/sharegpt-hyperfiltered-3k-zephyr | 2023-10-17T08:41:56.000Z | [
"task_categories:text-generation",
"task_categories:conversational",
"license:apache-2.0",
"region:us"
] | rizerphe | null | null | 0 | 4 | 2023-10-17T08:37:26 | ---
license: apache-2.0
task_categories:
- text-generation
- conversational
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 5601530
num_examples: 3227
download_size: 2773555
dataset_size: 5601530
---
# sharegpt-hyperfiltered-3k-zephyr
[sharegpt-hyperfiltered-3k](https://huggingface.co/datasets/totally-not-an-llm/sharegpt-hyperfiltered-3k), formatted to the prompting schema zephyr-7b-alpha uses. | 489 | [
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fahrialfiansyah/openstax_instruction_v2 | 2023-10-17T09:19:10.000Z | [
"region:us"
] | fahrialfiansyah | null | null | 0 | 4 | 2023-10-17T09:18:59 | Entry not found | 15 | [
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if001/oasst1_ja_ppl | 2023-10-23T11:22:05.000Z | [
"language:ja",
"license:apache-2.0",
"region:us"
] | if001 | null | null | 0 | 4 | 2023-10-17T12:01:55 | ---
license: apache-2.0
language:
- ja
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: input
dtype: string
- name: instruction
dtype: string
- name: output
dtype: string
- name: input_ppl
dtype: int64
- name: instruction_ppl
dtype: int64
- name: output_ppl
dtype: int64
- name: full_ppl
dtype: int64
splits:
- name: train
num_bytes: 60856874
num_examples: 55359
download_size: 27216157
dataset_size: 60856874
---
** 以下のrepositoryのforkです。 **
https://huggingface.co/datasets/kunishou/oasst1-89k-ja
instructionとinput、outputにまとめ、kenllmでperplexityのスコアが付与してあります。
perplexityの計算に用いたtokenizerはこちら
https://huggingface.co/if001/sentencepiece_ja
- instruction_ppl: instructionのみのperplexity
- output_ppl: outputのみのperplexity
- full_ppl: instructionとoutputを合わせ、instruction用の文章にしたperplexity
| 917 | [
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lukarape/public_small_pushed | 2023-10-17T13:01:38.000Z | [
"region:us"
] | lukarape | null | null | 0 | 4 | 2023-10-17T12:59:22 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
splits:
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num_bytes: 1496201.0
num_examples: 19
- name: test
num_bytes: 529928.0
num_examples: 7
download_size: 2027043
dataset_size: 2026129.0
---
# Dataset Card for "public_small_pushed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 588 | [
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bellagio-ai/t2i-vietnam-pictures | 2023-10-17T13:11:22.000Z | [
"region:us"
] | bellagio-ai | null | null | 0 | 4 | 2023-10-17T13:10:38 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 26817348.0
num_examples: 81
download_size: 26664289
dataset_size: 26817348.0
---
# Dataset Card for "t2i-vietnam-pictures"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 486 | [
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Mint1456/NLP_VIN2023 | 2023-10-17T14:09:21.000Z | [
"region:us"
] | Mint1456 | null | null | 0 | 4 | 2023-10-17T13:47:18 | ---
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: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 1696181647
num_examples: 2884451
- name: validation
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num_examples: 11316
- name: test
num_bytes: 6952905
num_examples: 11225
download_size: 383293199
dataset_size: 1710136712
---
# Dataset Card for "NLP_VIN2023"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 756 | [
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csupiisc/evaluate_plmn | 2023-10-17T13:56:33.000Z | [
"region:us"
] | csupiisc | null | null | 0 | 4 | 2023-10-17T13:56:04 | Entry not found | 15 | [
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nuvocare/Ted2020_en_es_fr_de_it_ca_pl_ru_nl | 2023-10-17T14:48:08.000Z | [
"region:us"
] | nuvocare | null | null | 0 | 4 | 2023-10-17T14:40:17 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: de
dtype: string
- name: en
dtype: string
- name: es
dtype: string
- name: fr
dtype: string
- name: it
dtype: string
- name: nl
dtype: string
- name: pl
dtype: string
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splits:
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num_bytes: 191053803
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- name: test
num_bytes: 4930156
num_examples: 7213
- name: validation
num_bytes: 4326695
num_examples: 6049
download_size: 116856833
dataset_size: 200310654
---
# Dataset Card for "Ted2020_en_es_fr_de_it_ca_pl_ru_nl"
This dataset is an extract of the TED2020 corpora focusing only on english, french, german, italian, polish, russian and dutch.
It is used for the purpose of building multilingual biomedical language models.
Teacher model is asked to encode the english sentence.
Student model is asked to encode other sentences by minimizng the euclidean distance with the teacher encoding.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 1,284 | [
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johannes-garstenauer/ENN_class_embeddings_dim_2 | 2023-10-28T20:12:32.000Z | [
"region:us"
] | johannes-garstenauer | null | null | 0 | 4 | 2023-10-17T15:58:13 | ---
dataset_info:
features:
- name: last_hs
sequence: float32
- name: label
dtype: int64
splits:
- name: train
num_bytes: 1345440
num_examples: 67272
download_size: 750114
dataset_size: 1345440
---
# Dataset Card for "ENN_class_embeddings_dim_2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 408 | [
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tyzhu/squad_title_v4_train_30_eval_10_permute5 | 2023-10-17T16:09:54.000Z | [
"region:us"
] | tyzhu | null | null | 0 | 4 | 2023-10-17T16:09:43 | ---
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: context_id
dtype: string
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 625263.266025641
num_examples: 399
- name: validation
num_bytes: 50807
num_examples: 50
download_size: 144382
dataset_size: 676070.266025641
---
# Dataset Card for "squad_title_v4_train_30_eval_10_permute5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 789 | [
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kwanyick/cover-letter-dataset-text | 2023-10-17T16:31:37.000Z | [
"region:us"
] | kwanyick | null | null | 0 | 4 | 2023-10-17T16:23:13 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: Text
dtype: string
splits:
- name: train
num_bytes: 278222.5230769231
num_examples: 136
- name: test
num_bytes: 120699.47692307692
num_examples: 59
download_size: 160615
dataset_size: 398922.0
---
# Dataset Card for "cover-letter-dataset-text"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 570 | [
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emi429/human-sleep-rr-small-wake-n1 | 2023-10-17T19:03:53.000Z | [
"region:us"
] | emi429 | null | null | 0 | 4 | 2023-10-17T19:03:22 | ---
dataset_info:
features:
- name: rr_intervals
sequence: float64
- name: sleep_stage
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 37733508
num_examples: 28921
download_size: 6512955
dataset_size: 37733508
---
# Dataset Card for "human-sleep-rr-small-wake-n1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 470 | [
[
-0.0364990234375,
-0.00797271728515625,
0.0030002593994140625,
0.026336669921875,
-0.0191192626953125,
-0.0013446807861328125,
-0.00118255615234375,
-0.011810302734375,
0.07366943359375,
0.0255126953125,
-0.07476806640625,
-0.043701171875,
-0.0181884765625,
... |
rehanbrr/gender-DEI-data | 2023-10-18T10:25:16.000Z | [
"region:us"
] | rehanbrr | null | null | 0 | 4 | 2023-10-18T10:25:08 | ---
dataset_info:
features:
- name: doi
dtype: string
- name: id
dtype: string
- name: title
dtype: string
- name: chunk_id
dtype: string
- name: chunk
dtype: string
splits:
- name: train
num_bytes: 235089
num_examples: 156
download_size: 130544
dataset_size: 235089
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "gender-DEI-data"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 574 | [
[
-0.039459228515625,
-0.00887298583984375,
0.01308441162109375,
0.0141143798828125,
0.00609588623046875,
0.006671905517578125,
0.0260009765625,
-0.005977630615234375,
0.040740966796875,
0.0157623291015625,
-0.07940673828125,
-0.060546875,
-0.040924072265625,
... |
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