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when2rl/UltraFeedback_binarized_cleaned_annotated

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Hugging Face2024-04-17 更新2024-03-04 收录
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https://hf-mirror.com/datasets/when2rl/UltraFeedback_binarized_cleaned_annotated
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--- dataset_info: features: - name: prompt dtype: string - name: prompt_id dtype: string - name: chosen list: - name: content dtype: string - name: role dtype: string - name: rejected list: - name: content dtype: string - name: role dtype: string - name: messages list: - name: content dtype: string - name: role dtype: string - name: score_chosen dtype: float64 - name: score_rejected dtype: float64 - name: other_info struct: - name: chosen_annotations struct: - name: annotations struct: - name: helpfulness struct: - name: Rating dtype: string - name: Rationale dtype: string - name: Rationale For Rating dtype: string - name: Type sequence: string - name: honesty struct: - name: Rating dtype: string - name: Rationale dtype: string - name: instruction_following struct: - name: Rating dtype: string - name: Rationale dtype: string - name: truthfulness struct: - name: Rating dtype: string - name: Rationale dtype: string - name: Rationale For Rating dtype: string - name: Type sequence: string - name: critique dtype: string - name: fine_grained_score dtype: float64 - name: model dtype: string - name: overall_score dtype: float64 - name: correct_answers sequence: string - name: incorrect_answers sequence: string - name: rejected_annotations struct: - name: annotations struct: - name: helpfulness struct: - name: Rating dtype: string - name: Rationale dtype: string - name: Rationale For Rating dtype: string - name: Type sequence: string - name: honesty struct: - name: Rating dtype: string - name: Rationale dtype: string - name: instruction_following struct: - name: Rating dtype: string - name: Rationale dtype: string - name: truthfulness struct: - name: Rating dtype: string - name: Rationale dtype: string - name: Rationale For Rating dtype: string - name: Type sequence: string - name: critique dtype: string - name: fine_grained_score dtype: float64 - name: model dtype: string - name: overall_score dtype: float64 - name: source dtype: string splits: - name: train_prefs num_bytes: 610449160.9601701 num_examples: 60700 - name: test_prefs num_bytes: 19882677.836 num_examples: 1988 download_size: 326664614 dataset_size: 630331838.7961701 configs: - config_name: default data_files: - split: train_prefs path: data/train_prefs-* - split: test_prefs path: data/test_prefs-* --- # Dataset Card for UltraFeedback Binarized, Cleaned, and Annotated <!-- Provide a quick summary of the dataset. --> This basically comes from: 1. start from UltraFeedback Binarized 2. recover metadata information such as `source` and `annotations` by matching prompts from the original `UltraFeedback` dataset 3. augment the original dset with metadata information stored in `other_info` 4. *(new)* removed all rows where the `chosen` is the same as `rejected`. This removed 435 rows from the training set, and 12 rows from test set. ## Dataset Details Same usage as `HuggingFaceH4/ultrafeedback_binarized`, but added the `other_info` which contains information such as `source` and `annotations`. ### 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]
提供机构：
when2rl
原始信息汇总

数据集概述

数据集信息

特征

  • prompt: 字符串类型
  • prompt_id: 字符串类型
  • chosen: 列表类型，包含以下字段：
    • content: 字符串类型
    • role: 字符串类型
  • rejected: 列表类型，包含以下字段：
    • content: 字符串类型
    • role: 字符串类型
  • messages: 列表类型，包含以下字段：
    • content: 字符串类型
    • role: 字符串类型
  • score_chosen: 浮点数类型
  • score_rejected: 浮点数类型
  • other_info: 结构体类型，包含以下字段：
    • chosen_annotations: 结构体类型，包含以下字段：
      • annotations: 结构体类型，包含以下字段：
        • helpfulness: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
          • Rationale For Rating: 字符串类型
          • Type: 字符串序列类型
        • honesty: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
        • instruction_following: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
        • truthfulness: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
          • Rationale For Rating: 字符串类型
          • Type: 字符串序列类型
      • critique: 字符串类型
      • fine_grained_score: 浮点数类型
      • model: 字符串类型
      • overall_score: 浮点数类型
    • correct_answers: 字符串序列类型
    • incorrect_answers: 字符串序列类型
    • rejected_annotations: 结构体类型，包含以下字段：
      • annotations: 结构体类型，包含以下字段：
        • helpfulness: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
          • Rationale For Rating: 字符串类型
          • Type: 字符串序列类型
        • honesty: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
        • instruction_following: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
        • truthfulness: 结构体类型，包含以下字段：
          • Rating: 字符串类型
          • Rationale: 字符串类型
          • Rationale For Rating: 字符串类型
          • Type: 字符串序列类型
      • critique: 字符串类型
      • fine_grained_score: 浮点数类型
      • model: 字符串类型
      • overall_score: 浮点数类型
    • source: 字符串类型

数据分割

  • train_prefs: 包含60700个样本，总字节数为610449160.9601701
  • test_prefs: 包含1988个样本，总字节数为19882677.836

数据集大小

  • 下载大小: 326664614字节
  • 数据集大小: 630331838.7961701字节

配置

  • default: 包含以下数据文件：
    • train_prefs: 路径为data/train_prefs-*
    • test_prefs: 路径为data/test_prefs-*
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