language:
- en
license: mit
size_categories: - 10K<n<100K
tags: - distilabel
- synthetic
- dpo
dataset_info:
features:- name: dataset
dtype: string - name: chosen
list:- name: content
dtype: string - name: role
dtype: string
- name: content
- name: rejected
list:- name: content
dtype: string - name: role
dtype: string
- name: content
- name: chosen_rating
dtype: float32 - name: rejected_rating
dtype: float32
splits: - name: train
num_bytes: 120528535.0
num_examples: 20250 - name: test
num_bytes: 4555903.0
num_examples: 750
download_size: 198089631
dataset_size: 125084438.0
configs:
- name: dataset
- config_name: default
data_files:- split: train
path: data/train-* - split: test
path: data/test-*
- split: train
DPO Mix 21K Dataset
Similar to the argilla/dpo-mix-7k, but with 21k samples:
Other diferences:
argilla/distilabel-capybara-dpo-7k-binarizedchanged toargilla/Capybara-Preferencesargilla/distilabel-intel-orca-dpo-pairsscored filter of >=8 changed to >= 7
A small cocktail combining DPO datasets built by Argilla with distilabel. The goal of this dataset is having a small, high-quality DPO dataset by filtering only highly rated chosen responses.
Datasets mixed
This dataset mixes the following datasets:
argilla/Capybara-Preferences: random sample of highly scored chosen responses (>=4).argilla/distilabel-intel-orca-dpo-pairs: random sample of highly scored chosen responses (>=7).argilla/ultrafeedback-binarized-preferences-cleaned: random sample of highly scored chosen responses (>=4).
The samples have been randomly selected from the original datasets with a proportion of 0.33 each, as can be seen via the dataset column of the dataset.