README.md

metadata

license: mit
annotations_creators:
  - no-annotation
language_creators:
  - expert-generated
task_categories:
  - question-answering
task_ids:
  - multiple-choice-qa
language:
  - en
tags:
  - blockchain
  - code
  - benchmark
pretty_name: LLM Blockchain Benchmark
size_categories:
  - 10K<n<100K
dataset_info:
  - config_name: math
    features:
      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
        dtype:
          class_label:
            names:
              '0': A
              '1': B
              '2': C
              '3': D
  - config_name: general-reasoning
    features:
      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
        dtype:
          class_label:
            names:
              '0': A
              '1': B
              '2': C
              '3': D
  - config_name: code
    features:
      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
        dtype:
          class_label:
            names:
              '0': A
              '1': B
              '2': C
              '3': D
configs:
  - config_name: math
    data_files:
      - split: test
        path: Math*
  - config_name: general-reasoning
    data_files:
      - split: test
        path: General*
  - config_name: code
    data_files:
      - split: test
        path: Coding*

Dataset Card for LLM Blockchain Benchmark

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Repository: [github repo]

Dataset Summary

The Blockchain Benchmark Dataset is a comprehensive collection of data specifically curated for benchmarking Language Models (LMs) in the domain of blockchain technology. This dataset is designed to facilitate research and development in natural language understanding within the blockchain domain. A complete list of tasks: ['general-reasoning', 'code', 'math']

Supported Tasks and Leaderboards

Model	Authors	Humanities	Social Science	STEM	Other	Average

[add tested models here]

Languages

English

Dataset Structure

Data Instances

An example from code subtask looks as follows:

{
  "question": "The defining idea of Uniswap v3 token is",
  "choices": ['Concentrated Liquidity', 'Diluted Liquidity', 'Concentrated Programming', 'Optimized price ranges'],
  "answer": "A"
}

Data Fields

• question: a string feature
• choices: a list of 4 string features
• answer: a ClassLabel feature

Data Splits

• test: all data under test for benchmarking

Dataset Creation

Curation Rationale

This dataset addresses the scarcity of benchmarks designed specifically for Language Models (LMs) in the realm of blockchain technology. With the intersection of blockchain and LM technologies gaining traction, a focused dataset becomes essential. This collection serves as a vital resource for advancing research and understanding within the dynamic blockchain landscape.

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

MIT License

Citation Information

If you find this useful in your research, please consider supporting Tensorplex [link]

Contributions

Thanks to Tensorplex for adding this dataset.