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RMT-team/babilong-1k-samples

BABILong is a benchmark for evaluating NLP models' ability to handle distributed facts across long documents. It comprises nine configurations corresponding to different sequence lengths (0k, 1k, 2k, 4k, 8k, 16k, 32k, 64k, 128k). The dataset builds on the bAbI fact set and PG‑19 as background text, simulating the task of locating crucial information among extensive irrelevant details. Additionally, it includes ten tasks to assess basic reasoning capabilities.

Updated 6/17/2024
hugging_face

Description

Dataset Overview

Dataset Name

  • BABILong

Configurations

  • Configuration Names: 0k, 1k, 2k, 4k, 8k, 16k, 32k, 64k, 128k
  • Features:
    • question: String
    • target: String
    • input: String

Size

  • Download Size: Varies per configuration, ranging from 8,143,277 bytes to 1,567,936,012 bytes
  • Dataset Size: Varies per configuration, ranging from 13,838,997 bytes to 2,532,955,312 bytes

Splits

  • Split Names: qa1, qa2, …, qa20
  • Example Count: Between 999 and 1,000 per split
  • Bytes per Split: Varies with configuration, ranging from 2,801,155 bytes to 507,056,606 bytes

File Paths

  • Data files follow the pattern <config_name>/qa<split_number>-*

Tasks

  • Task Types: Include single supporting fact, two supporting facts, three supporting facts, etc.
  • Number of Facts: Ranges from 2 to 126 depending on the task
  • Supporting Facts: 1 to 3 per task

Intended Use

  • Evaluating NLP model performance on handling distributed facts in long documents

Sources

  • Uses the bAbI dataset for facts and PG‑19 for background text

License

  • Apache 2.0 License, BSD License

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Topics

Long Text Processing
NLP Reasoning Evaluation

Source

Organization: hugging_face

Created: Unknown

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