Datasets:

Modalities:
Text
Formats:
parquet
Sub-tasks:
extractive-qa
Languages:
Russian
ArXiv:
Libraries:
Datasets
pandas
License:
albertvillanova HF staff pefimov commited on
Commit
92d74b2
1 Parent(s): 59515e9

Upload data files directly to the HF repository (#3)

Browse files

- Upload data files directly to the HF repository (0a46891173b3eacf17ac7b1e3a5c479c5549cbb7)
- Delete legacy dataset_infos.json (069c6fed2da1f047c3f1e4faa7bb439631b096f7)
- Update metadata in dataset card (d9f69d76cd901db660a03b8099072d5b3de89d51)


Co-authored-by: Pavel Efimov <pefimov@users.noreply.huggingface.co>

README.md CHANGED
@@ -1,5 +1,4 @@
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  ---
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- pretty_name: SberQuAD
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  annotations_creators:
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  - crowdsourced
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  language_creators:
@@ -20,7 +19,9 @@ task_categories:
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  task_ids:
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  - extractive-qa
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  paperswithcode_id: sberquad
 
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  dataset_info:
 
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  features:
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  - name: id
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  dtype: int32
@@ -36,19 +37,18 @@ dataset_info:
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  dtype: string
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  - name: answer_start
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  dtype: int32
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- config_name: sberquad
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  splits:
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  - name: train
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- num_bytes: 71631661
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  num_examples: 45328
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  - name: validation
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- num_bytes: 7972977
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  num_examples: 5036
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  - name: test
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- num_bytes: 36397848
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  num_examples: 23936
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- download_size: 66047276
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- dataset_size: 116002486
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  ---
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  ---
 
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  annotations_creators:
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  - crowdsourced
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  language_creators:
 
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  task_ids:
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  - extractive-qa
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  paperswithcode_id: sberquad
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+ pretty_name: SberQuAD
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  dataset_info:
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+ config_name: sberquad
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  features:
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  - name: id
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  dtype: int32
 
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  dtype: string
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  - name: answer_start
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  dtype: int32
 
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  splits:
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  - name: train
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+ num_bytes: 71631541
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  num_examples: 45328
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  - name: validation
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+ num_bytes: 7972953
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  num_examples: 5036
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  - name: test
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+ num_bytes: 36397776
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  num_examples: 23936
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+ download_size: 10491714
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+ dataset_size: 116002270
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  ---
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data/dev_v1.0.json.gz ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:a9145c18e890e84fd070272fcaa607a688efd61debf36b89bc2b96654ac77d18
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+ size 1927670
data/origin_test.json.gz ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:5d24ee67e71ea95163342b72d8fb36914fa7d0b261b3552ed5824f355fe76963
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+ size 2725921
data/train_v1.0.json.gz ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:5a05221fe35eb1b4fcd17b8acca1d957e12d098783d8e8a2ebb2348f6c437b0a
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+ size 5838123
dataset_infos.json DELETED
@@ -1 +0,0 @@
1
- {"sberquad": {"description": "Sber Question Answering Dataset (SberQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. Russian original analogue presented in Sberbank Data Science Journey 2017.\n", "citation": "@article{Efimov_2020,\n title={SberQuAD \u2013 Russian Reading Comprehension Dataset: Description and Analysis},\n ISBN={9783030582197},\n ISSN={1611-3349},\n url={http://dx.doi.org/10.1007/978-3-030-58219-7_1},\n DOI={10.1007/978-3-030-58219-7_1},\n journal={Experimental IR Meets Multilinguality, Multimodality, and Interaction},\n publisher={Springer International Publishing},\n author={Efimov, Pavel and Chertok, Andrey and Boytsov, Leonid and Braslavski, Pavel},\n year={2020},\n pages={3\u201315}\n}\n ", "homepage": "", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "question-answering-extractive", "question_column": "question", "context_column": "context", "answers_column": "answers"}], "builder_name": "sberquad", "config_name": "sberquad", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 71631661, "num_examples": 45328, "dataset_name": "sberquad"}, "validation": {"name": "validation", "num_bytes": 7972977, "num_examples": 5036, "dataset_name": "sberquad"}, "test": {"name": "test", "num_bytes": 36397848, "num_examples": 23936, "dataset_name": "sberquad"}}, "download_checksums": {"https://sc.link/PNWl": {"num_bytes": 38616884, "checksum": "861b55219f1549139e64b2eed325b54ce9c9c63b792a2c2b3cfbec997aa3d88e"}, "https://sc.link/W6oX": {"num_bytes": 8807953, "checksum": "247bede36a27f076f607117632f39eedb9bb1d80c34d93bbfaeda71fd30fd382"}, "https://sc.link/VOn9": {"num_bytes": 18622439, "checksum": "7793d389208271a76ab38a5dba5cebc98e72f45e99196a99e14b5a37c401c66f"}}, "download_size": 66047276, "post_processing_size": null, "dataset_size": 116002486, "size_in_bytes": 182049762}}
 
 
sberquad.py CHANGED
@@ -1,6 +1,7 @@
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  # coding=utf-8
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  """SberQUAD: Sber Question Answering Dataset."""
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  import json
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  import datasets
@@ -33,7 +34,7 @@ from the corresponding reading passage, or the question might be unanswerable. \
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  Russian original analogue presented in Sberbank Data Science Journey 2017.
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  """
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- _URLS = {"train": "https://sc.link/PNWl", "dev": "https://sc.link/W6oX", "test": "https://sc.link/VOn9"}
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  class Sberquad(datasets.GeneratorBasedBuilder):
 
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  # coding=utf-8
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  """SberQUAD: Sber Question Answering Dataset."""
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+ import os
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  import json
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  import datasets
 
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  Russian original analogue presented in Sberbank Data Science Journey 2017.
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  """
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+ _URLS = {"train": os.path.join("data", "train_v1.0.json.gz"), "dev": os.path.join("data", "dev_v1.0.json.gz"), "test": os.path.join("data", "origin_test.json.gz")}
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  class Sberquad(datasets.GeneratorBasedBuilder):