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BUSTER / README.md
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metadata
language:
  - en
license: apache-2.0
size_categories:
  - 10K<n<100K
task_categories:
  - token-classification
pretty_name: buster
tags:
  - finance
configs:
  - config_name: default
    data_files:
      - split: FOLD_1
        path: data/FOLD_1-*
      - split: FOLD_2
        path: data/FOLD_2-*
      - split: FOLD_3
        path: data/FOLD_3-*
      - split: FOLD_4
        path: data/FOLD_4-*
      - split: FOLD_5
        path: data/FOLD_5-*
      - split: SILVER
        path: data/SILVER-*
dataset_info:
  features:
    - name: document_id
      dtype: string
    - name: tokens
      sequence: string
    - name: labels
      sequence: string
  splits:
    - name: FOLD_1
      num_bytes: 9801188
      num_examples: 753
    - name: FOLD_2
      num_bytes: 9719997
      num_examples: 759
    - name: FOLD_3
      num_bytes: 9810761
      num_examples: 758
    - name: FOLD_4
      num_bytes: 9973098
      num_examples: 755
    - name: FOLD_5
      num_bytes: 9831525
      num_examples: 754
    - name: SILVER
      num_bytes: 80615802
      num_examples: 6196
  download_size: 20217911
  dataset_size: 129752371

Dataset Card for BUSTER

BUSiness Transaction Entity Recognition dataset.

BUSTER is an Entity Recognition (ER) benchmark for entities related to business transactions. It consists of a gold corpus of 3779 manually annotated documents on financial transactions that were randomly divided into 5 folds, plus an additional silver corpus of 6196 automatically annotated documents that were created by the model-optimized RoBERTa system.