metadata

dataset_info:
  features:
    - name: question
      dtype: string
    - name: subject
      dtype: string
    - name: choices
      sequence: string
    - name: answer
      dtype: int64
    - name: task
      dtype: string
  splits:
    - name: train
      num_bytes: 162899630
      num_examples: 99842
  download_size: 47653197
  dataset_size: 162899630
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: apache-2.0
task_categories:
  - text-generation
language:
  - en
pretty_name: MMLU auxiliary trained set labelled by e5 mistral 7b instruct
size_categories:
  - 10K<n<100K

Dataset Card for MMLU Auxiliary Trained Set Labelled by e5-mistral-7b-instruct

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Dataset Summary

This dataset, named "MMLU Auxiliary Trained Set Labelled by e5-mistral-7b-instruct," consists of 99,842 examples spanning various subjects. Each instance includes a question, multiple choice options, a subject category, and an answer. The unique aspect of this dataset is the task label for each question, generated by a zero-shot classifier constructed from the intfloat/e5-mistral-7b-instruct model and trained on the auxiliary set of the Massive Multitask Language Understanding (MMLU).

Supported Tasks and Leaderboards

This dataset supports text-generation tasks. It is particularly useful for training and evaluating models on a wide range of subjects using the task labels generated by the zero-shot classifier.

Languages

The dataset is predominantly in English.

Dataset Structure

Data Instances

A typical data instance in this dataset comprises:

question: A textual question or prompt.
subject: The subject category of the question.
choices: A list of possible answers.
answer: The correct answer's index from the choices.
task: The task label assigned by the zero-shot classifier.

Data Fields

question: string
subject: string
choices: sequence of strings
answer: int64
task: string

Data Splits

Train Split: 99,842 examples

Dataset Creation

Curation Rationale

The dataset was curated to enhance the diversity and scope of language models in understanding and generating responses across a wide range of subjects. The use of a zero-shot classifier for task labelling introduces a novel approach to categorizing and understanding textual data.

Source Data

The data was sourced from the auxiliary-train set of MMLU and processed to include task labels generated by the intfloat/e5-mistral-7b-instruct model.

Annotations

Annotation process

The task labels were generated automatically by a zero-shot classifier model, specifically intfloat/e5-mistral-7b-instruct.

Who are the annotators?

There were no human annotators; the process was entirely automated using the zero-shot classifier.

Personal and Sensitive Information

The dataset does not contain personal or sensitive information as it is focused on general knowledge questions and subjects.

Considerations for Using the Data

Social Impact of Dataset

This dataset can aid in developing more versatile and knowledgeable language models, potentially impacting various domains like education, research, and AI development.

Discussion of Biases

Given the automated nature of task label generation and diverse subject matter, biases may be minimal but could still exist based on the underlying training data of the zero-shot classifier.

Other Known Limitations

The primary limitation is the reliance on the zero-shot classifier's accuracy for task labeling, which may not always align with human judgment.

Additional Information

Dataset Curators

The dataset was curated by the team involved in the development of mmlu.

Licensing Information

The dataset is available under the Apache-2.0 License.

Citation Information

@misc{mmlu_auxiliary_trained_set, title = {{MMLU Auxiliary Trained Set Labelled by e5-mistral-7b-instruct}}, author = {Kaizhao Liang}, year = {2024}, howpublished = {https://huggingface.co/datasets/kz919/mmlu-auxiliary-train-e5-mistral-7b-instruct}, note = {Accessed: Date of Access}, description = {A dataset of 99,842 examples across various subjects, each including a question, multiple choice options, a subject category, an answer, and a task label generated by a zero-shot classifier constructed from the intfloat/e5-mistral-7b-instruct model.}, license = {Apache-2.0} }

Contact Information

homepage

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mmlu-auxiliary-train-auto-labelled