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Kyleyee/train_data_imdb_preference_mistake

published by @Kyleyee

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
310
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Size
155.3 MB
Created on HF
2025-03-03
Age
1 years ago

Description

HH-RLHF-Helpful-Base Dataset

Summary

The HH-RLHF-Helpful-Base dataset is a processed version of Anthropic's HH-RLHF dataset, specifically curated to train models using the TRL library for preference learning and alignment tasks. It contains pairs of text samples, each labeled as either "chosen" or "rejected," based on human preferences regarding the helpfulness of the responses. This dataset enables models to learn human preferences in generating helpful responses… See the full description on the dataset page: https://huggingface.co/datasets/Kyleyee/train_data_imdb_preference_mistake.

Tags

size_categories:10K<n<100Kformat:parquetmodality:tabularmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:ustrl

README current version from Hugging Face


tags:

  • trl

HH-RLHF-Helpful-Base Dataset

Summary

The HH-RLHF-Helpful-Base dataset is a processed version of Anthropic's HH-RLHF dataset, specifically curated to train models using the TRL library for preference learning and alignment tasks. It contains pairs of text samples, each labeled as either "chosen" or "rejected," based on human preferences regarding the helpfulness of the responses. This dataset enables models to learn human preferences in generating helpful responses, enhancing their ability to assist users effectively.

Data Structure

Columns:

  • "prompt": The user query.
  • "chosen": A response deemed helpful by human evaluators.
  • "rejected": A response considered less helpful or unhelpful.

This structure allows models to learn to prefer the chosen response over the rejected one, thereby aligning with human preferences in helpfulness.

Generation script

The script used to generate this dataset can be found here.

README history 7 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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  7. 2025-03-03initial commit3bfce550 B
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Repository

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("Kyleyee/train_data_imdb_preference_mistake")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Kyleyee/train_data_imdb_preference_mistake", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/Kyleyee/train_data_imdb_preference_mistake
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