UCLNLP/adversarial_qa
Dataset Card for adversarialQA Dataset Summary We have created three new Reading Comprehension datasets constructed using an adversarial model-in-the-loop. We use three different models; BiDAF (Seo et al., 2016), BERTLarge (Devlin et al., 2018), and RoBERTaLarge (Liu et al., 2019) in the annotation loop and construct three datasets; D(BiDAF), D(BERT), and D(RoBERTa), each with 10,000 training examples, 1,000 validation, and 1,000 test examples. The adversarial… See the full description on the dataset page: https://huggingface.co/datasets/UCLNLP/adversarial_qa.
Convert dataset to Parquet (#4)
Reorder split names (#2)
add dataset_info in dataset metadata
remove dummmy data
Add evaluation metadata (#1)
Align more metadata with other repo types (models,spaces) (#4607)
Remove config names as yaml keys (#4367)
Update files from the datasets library (from 1.18.0)
Update files from the datasets library (from 1.8.0)
Update files from the datasets library (from 1.7.0)
Update files from the datasets library (from 1.6.0)
Update files from the datasets library (from 1.4.0)
Update files from the datasets library (from 1.3.0)