---
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

<!-- Provide a quick summary of the dataset. -->

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

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

### Dataset Sources [optional]

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

## Uses

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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

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#### Data Collection and Processing

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#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

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## Bias, Risks, and Limitations

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### Recommendations

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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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## Glossary [optional]

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## Dataset Card Authors [optional]

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