README.md

metadata

task_categories:
  - question-answering
language:
  - en
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: chunk
      dtype: string
    - name: question
      dtype: string
  splits:
    - name: train
      num_bytes: 1983000
      num_examples: 452
    - name: test
      num_bytes: 495750
      num_examples: 113
  download_size: 465397
  dataset_size: 2478750

Dataset Card for Dataset Name

This dataset aims to be a base template for fine-tuning embedding models for enhanced retrieval performance in RAG pipelines. It has been generated locally using Mistral:7B on Ollama using a simple prompt that prompts the model to generate 5 questions for each document chunk of Apple's Environmental Progress Report 2024

Dataset Details

Dataset Description

• Curated by: Likhit Juttada
• Funded by [optional]: NA
• Credits [optional]: AdamLucek
• Language(s) (NLP): English
• License:

Dataset Sources [optional]

• Repository: [More Information Needed]
• Paper [optional]: Improving Text Embeddings with Large Language Models
• Demo [optional]: [More Information Needed]

Uses

This dataset can be used to finetune any embedding model for improving retrieval performance on RAG

Direct Use

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Out-of-Scope Use

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Dataset Structure

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Dataset Creation

Curation Rationale

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Source Data

Data Collection and Processing

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Who are the source data producers?

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Annotation process

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Personal and Sensitive Information

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Bias, Risks, and Limitations

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Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation [optional]

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