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shibing624/DPO-En-Zh-20k-Preference

published by @shibing624

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
3.3K
Last 30 days
159
Likes
18
Size
72.4 MB
Created on HF
2024-04-26
Age
2 years ago

Description

This dataset is composed by

4,000 examples of argilla/distilabel-capybara-dpo-7k-binarized with chosen score>=4.

3,000 examples of argilla/distilabel-intel-orca-dpo-pairs with chosen score>=8.

3,000 examples of argilla/ultrafeedback-binarized-preferences-cleaned with chosen score>=4.

10,000 examples of wenbopan/Chinese-dpo-pairs.

refer: https://huggingface.co/datasets/hiyouga/DPO-En-Zh-20k 改了question、response_rejected、response_chosen字段，方便ORPO、DPO模型训练时使用

train usage:… See the full description on the dataset page: https://huggingface.co/datasets/shibing624/DPO-En-Zh-20k-Preference.

Tags

task_categories:text-generationlanguage:enlanguage:zhlicense:apache-2.0size_categories:10K<n<100Kformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:usdpoorporlhf

README current version from Hugging Face

license: apache-2.0
task_categories:

  • text-generation
    language:
  • en
  • zh
    tags:
  • dpo
  • orpo
  • rlhf
    size_categories:
  • 10K<n<100K
    configs:
  • config_name: en
    data_files:
    • split: train
      path: dpo_en.jsonl
  • config_name: zh
    data_files:
    • split: train
      path: dpo_zh.jsonl

dataset_info:

  • config_name: en
    features:
    • name: system
      dtype: string
    • name: history
      list:
      list:
      dtype: string
    • name: question
      dtype: string
    • name: response_rejected
      dtype: string
    • name: response_chosen
      dtype: string
  • config_name: zh
    features:
    • name: system
      dtype: string
    • name: history
      list:
      list:
      dtype: string
    • name: question
      dtype: string
    • name: response_rejected
      dtype: string
    • name: response_chosen
      dtype: string

This dataset is composed by

refer: https://huggingface.co/datasets/hiyouga/DPO-En-Zh-20k 改了question、response_rejected、response_chosen字段，方便ORPO、DPO模型训练时使用

train usage: https://github.com/shibing624/MedicalGPT

Data Length

dpo_zh.jsonl

  • 'system' + 'history' + 'question' + 'response_chosen'的平均字符长度: 674
  • 'system' + 'history' + 'question' + 'response_chosen'的90%分位数的字符长度: 1279
  • 'response_chosen'的平均字符长度: 455.5517
  • 'response_chosen'的90%分位数的字符长度: 994.0

dpo_en.jsonl

  • 'system' + 'history' + 'question' + 'response_chosen'的平均字符长度: 3268
  • 'system' + 'history' + 'question' + 'response_chosen'的90%分位数的字符长度: 7320
  • 'response_chosen'的平均字符长度: 1447
  • 'response_chosen'的90%分位数的字符长度: 2886

README history 5 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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  2. 2024-04-26Update README.mdce0962d1.8 KB
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  4. 2024-04-26Upload 2 files1a4365828 B
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  5. 2024-04-26initial commitf9cf53628 B
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 1 thread · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2024-04-27[bot] Conversion to Parquetclosed1 💬#1
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Read further

Community best practices (healing)
4 rules on DPO/ORPO, GSM8K lag, CHES filtering, and what heal does not do.
M4 - Abliterate then heal
Two-stage pipeline. DPO healing recovers benchmarks.
The politics of dataset curation
Whose preferences are baked into the healing mix, and why it matters.
Non-English abliteration communities
The Russian slop-removal framing and non-English healing corpora.

Metadata

License
apache-2.0

Repository

FILE .gitattributes FILE dpo_en.jsonl FILE dpo_zh.jsonl FILE README.md

File contents live on Hugging Face. Click a file or folder to open it there.

Download the dataset

0

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("shibing624/DPO-En-Zh-20k-Preference")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="shibing624/DPO-En-Zh-20k-Preference", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/shibing624/DPO-En-Zh-20k-Preference
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