Unverified Commit faee1adf authored by sean0042's avatar sean0042 Committed by GitHub
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Adding new task : KorMedMCQA (#1530)

parent 29b2b013
# KorMedMCQA
### Paper
Title: `KorMedMCQA: Multi-Choice Question Answering Benchmark for Korean Healthcare Professional Licensing Examinations`
Abstract: `We introduce KorMedMCQA, the first Korean multiple-choice question answering (MCQA) benchmark derived from Korean healthcare professional licensing examinations, covering from the year 2012 to year 2023. This dataset consists of a selection of questions from the license examinations for doctors, nurses, and pharmacists, featuring a diverse array of subjects. We conduct baseline experiments on various large language models, including proprietary/open-source, multilingual/Korean-additional pretrained, and clinical context pretrained models, highlighting the potential for further enhancements. We make our data publicly available on HuggingFace and provide a evaluation script via LM-Harness, inviting further exploration and advancement in Korean healthcare environments.`
Paper : https://arxiv.org/abs/2403.01469
Homepage: https://huggingface.co/datasets/sean0042/KorMedMCQA
### Citation
```
@article{kweon2024kormedmcqa,
title={KorMedMCQA: Multi-Choice Question Answering Benchmark for Korean Healthcare Professional Licensing Examinations},
author={Sunjun Kweon and Byungjin Choi and Minkyu Kim and Rae Woong Park and Edward Choi},
journal={arXiv preprint arXiv:2403.01469},
year={2024}
}
```
### Groups and Tasks
* `kormedmcqa`: Runs `kormedmcqa_doctor`, `kormedmcqa_nurse`, and `kormedmcqa_pharm`.
#### Tasks
* `kormedmcqa_doctor`: `Official Korean Doctor Examination`
* `kormedmcqa_nurse`: `Official Korean Nurse Examination`
* `kormedmcqa_pharm`: `Official Korean Pharmacist Examination`
### Checklist
For adding novel benchmarks/datasets to the library:
* [x] Is the task an existing benchmark in the literature?
* [x] Have you referenced the original paper that introduced the task?
* [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
If other tasks on this dataset are already supported:
* [ ] Is the "Main" variant of this task clearly denoted?
* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?
group: kormedmcqa
task : kormedmcqa_doctor
dataset_path : sean0042/KorMedMCQA
dataset_name : doctor
test_split : test
fewshot_split : dev
fewshot_config:
sampler: first_n
output_type: generate_until
doc_to_text: "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nE. {{E}}\n정답:"
doc_to_target: "{{['A', 'B', 'C', 'D', 'E'][answer-1]}}"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: true
ignore_punctuation: true
regexes_to_ignore:
- " "
generation_kwargs:
until:
- "Q:"
- "\n\n"
- "</s>"
- "."
do_sample: false
temperature: 0.0
group: kormedmcqa
task : kormedmcqa_nurse
dataset_path : sean0042/KorMedMCQA
dataset_name : nurse
test_split : test
fewshot_split : dev
fewshot_config:
sampler: first_n
output_type: generate_until
doc_to_text: "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nE. {{E}}\n정답:"
doc_to_target: "{{['A', 'B', 'C', 'D', 'E'][answer-1]}}"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: true
ignore_punctuation: true
regexes_to_ignore:
- " "
generation_kwargs:
until:
- "Q:"
- "\n\n"
- "</s>"
- "."
do_sample: false
temperature: 0.0
group: kormedmcqa
task : kormedmcqa_pharm
dataset_path : sean0042/KorMedMCQA
dataset_name : pharm
test_split : test
fewshot_split : dev
fewshot_config:
sampler: first_n
output_type: generate_until
doc_to_text: "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nE. {{E}}\n정답:"
doc_to_target: "{{['A', 'B', 'C', 'D', 'E'][answer-1]}}"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: true
ignore_punctuation: true
regexes_to_ignore:
- " "
generation_kwargs:
until:
- "Q:"
- "\n\n"
- "</s>"
- "."
do_sample: false
temperature: 0.0
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