from evaluate import evaluator from datasets import load_dataset task_evaluator = evaluator("question-answering") data = load_dataset("squad", split="validation[:2]") results = task_evaluator.compute( model_or_pipeline="sshleifer/tiny-distilbert-base-cased-distilled-squad", data=data, metric="squad", )
github.com
https://github.com/huggingface/evaluate/tree/main/metrics/squad
- SQuAD v2
github.com
https://github.com/huggingface/evaluate/blob/main/metrics/squad_v2/README.md
Using the `evaluator`
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
https://huggingface.co/docs/evaluate/v0.4.0/en/base_evaluator#question-answering
Evaluator
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
https://huggingface.co/docs/evaluate/v0.4.0/en/package_reference/evaluator_classes#evaluate.QuestionAnsweringEvaluator

Seonglae Cho