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New healthcare benchmark: careqa (#2714)  
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task: mimic_repsum
dataset_path: dmacres/mimiciii-hospitalcourse-meta
description: >
  Instructions: The following text is from a collection of medical records. Summarize the findings into diagnostic statements. Do not omit relevant information and avoid using abbreviations or jargon unless they appear in the original text.

output_type: generate_until
training_split: train
validation_split: validation
test_split: test
doc_to_text: !function utils.doc_to_text
doc_to_target: !function utils.doc_to_target
process_results: !function utils.process_results
generation_kwargs:
  until:
    - "\n\n"
  top_p: 0.95
metric_list:
  - metric: bleu
    aggregation: nanmean
    higher_is_better: true
  - metric: rouge1
    aggregation: nanmean
    higher_is_better: true
  - metric: rouge2
    aggregation: nanmean
    higher_is_better: true
  - metric: rougeL
    aggregation: nanmean
    higher_is_better: true
  - metric: bleurt
    aggregation: nanmean
    higher_is_better: true
  - metric: bert_score
    aggregation: nanmean
    higher_is_better: true
  - metric: F1-Radgraph
    aggregation: nanmean
    higher_is_better: true
metadata:
  version: 1.4