Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
Vietnamese
Size:
10K - 100K
ArXiv:
| dataset_info: | |
| features: | |
| - name: context | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: answers | |
| sequence: | |
| - name: answer_start | |
| dtype: int32 | |
| - name: text | |
| dtype: string | |
| - name: id | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 97291797 | |
| num_examples: 84816 | |
| - name: validation | |
| num_bytes: 714691 | |
| num_examples: 511 | |
| - name: test | |
| num_bytes: 7800838 | |
| num_examples: 5495 | |
| download_size: 19775204 | |
| dataset_size: 105807326 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: validation | |
| path: data/validation-* | |
| - split: test | |
| path: data/test-* | |
| task_categories: | |
| - question-answering | |
| language: | |
| - vi | |
| size_categories: | |
| - 10K<n<100K | |
| Vietnamese portion of MLQA for monolingual QA | |
| The train split is the machine translated train data from SQuAD v1.1. | |
| The validation split and the test split are from MLQA. | |
| We created this particular version with the following code: | |
| ```python | |
| import datasets | |
| # Machine translated train data from SQuAD v1.1. | |
| mlqa_train_dev = datasets.load_dataset("facebook/mlqa", "mlqa-translate-train.vi") | |
| # Original validation and test data from MLQA | |
| mlqa_val_test = datasets.load_dataset("facebook/mlqa", "mlqa.vi.vi") | |
| # Merge and create our version | |
| mlqa = mlqa_train_dev | |
| mlqa["validation"] = mlqa_val_test["validation"] | |
| mlqa["test"] = mlqa_val_test["test"] | |
| ``` | |
| ### Citation Information | |
| ``` | |
| @article{lewis2019mlqa, | |
| title = {MLQA: Evaluating Cross-lingual Extractive Question Answering}, | |
| author = {Lewis, Patrick and Oguz, Barlas and Rinott, Ruty and Riedel, Sebastian and Schwenk, Holger}, | |
| journal = {arXiv preprint arXiv:1910.07475}, | |
| year = 2019, | |
| eid = {arXiv: 1910.07475} | |
| } | |
| @inproceedings{rajpurkar-etal-2016-squad, | |
| title = "{SQ}u{AD}: 100,000+ Questions for Machine Comprehension of Text", | |
| author = "Rajpurkar, Pranav and | |
| Zhang, Jian and | |
| Lopyrev, Konstantin and | |
| Liang, Percy", | |
| editor = "Su, Jian and | |
| Duh, Kevin and | |
| Carreras, Xavier", | |
| booktitle = "Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing", | |
| month = nov, | |
| year = "2016", | |
| address = "Austin, Texas", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/D16-1264", | |
| doi = "10.18653/v1/D16-1264", | |
| pages = "2383--2392", | |
| eprint={1606.05250}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| } | |
| ``` |