Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -29,96 +29,76 @@ task_ids:
 - topic-classification
 paperswithcode_id: klue
 pretty_name: KLUE
+config_names:
+- dp
+- mrc
+- ner
+- nli
+- re
+- sts
+- wos
+- ynat
 tags:
 - relation-extraction
 dataset_info:
-- config_name: ynat
+- config_name: dp
   features:
-  - name: guid
-    dtype: string
-  - name: title
-    dtype: string
-  - name: label
-    dtype:
-      class_label:
-        names:
-          '0': IT과학
-          '1': 경제
-          '2': 사회
-          '3': 생활문화
-          '4': 세계
-          '5': 스포츠
-          '6': 정치
-  - name: url
-    dtype: string
-  - name: date
+  - name: sentence
     dtype: string
+  - name: index
+    list: int32
+  - name: word_form
+    list: string
+  - name: lemma
+    list: string
+  - name: pos
+    list: string
+  - name: head
+    list: int32
+  - name: deprel
+    list: string
   splits:
   - name: train
-    num_bytes: 10109664
-    num_examples: 45678
+    num_bytes: 7900009
+    num_examples: 10000
   - name: validation
-    num_bytes: 2039197
-    num_examples: 9107
-  download_size: 4932555
-  dataset_size: 12148861
-- config_name: sts
+    num_bytes: 1557506
+    num_examples: 2000
+  download_size: 2033461
+  dataset_size: 9457515
+- config_name: mrc
   features:
-  - name: guid
-    dtype: string
-  - name: source
-    dtype: string
-  - name: sentence1
+  - name: title
     dtype: string
-  - name: sentence2
+  - name: context
     dtype: string
-  - name: labels
-    struct:
-    - name: label
-      dtype: float64
-    - name: real-label
-      dtype: float64
-    - name: binary-label
-      dtype:
-        class_label:
-          names:
-            '0': negative
-            '1': positive
-  splits:
-  - name: train
-    num_bytes: 2832921
-    num_examples: 11668
-  - name: validation
-    num_bytes: 122657
-    num_examples: 519
-  download_size: 1349875
-  dataset_size: 2955578
-- config_name: nli
-  features:
-  - name: guid
+  - name: news_category
     dtype: string
   - name: source
     dtype: string
-  - name: premise
+  - name: guid
     dtype: string
-  - name: hypothesis
+  - name: is_impossible
+    dtype: bool
+  - name: question_type
+    dtype: int32
+  - name: question
     dtype: string
-  - name: label
-    dtype:
-      class_label:
-        names:
-          '0': entailment
-          '1': neutral
-          '2': contradiction
+  - name: answers
+    sequence:
+    - name: answer_start
+      dtype: int32
+    - name: text
+      dtype: string
   splits:
   - name: train
-    num_bytes: 5719930
-    num_examples: 24998
+    num_bytes: 46505665
+    num_examples: 17554
   - name: validation
-    num_bytes: 673276
-    num_examples: 3000
-  download_size: 1257374
-  dataset_size: 6393206
+    num_bytes: 15583053
+    num_examples: 5841
+  download_size: 19218422
+  dataset_size: 62088718
 - config_name: ner
   features:
   - name: sentence
@@ -151,6 +131,32 @@ dataset_info:
     num_examples: 5000
   download_size: 4308644
   dataset_size: 24829532
+- config_name: nli
+  features:
+  - name: guid
+    dtype: string
+  - name: source
+    dtype: string
+  - name: premise
+    dtype: string
+  - name: hypothesis
+    dtype: string
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': entailment
+          '1': neutral
+          '2': contradiction
+  splits:
+  - name: train
+    num_bytes: 5719930
+    num_examples: 24998
+  - name: validation
+    num_bytes: 673276
+    num_examples: 3000
+  download_size: 1257374
+  dataset_size: 6393206
 - config_name: re
   features:
   - name: guid
@@ -222,64 +228,37 @@ dataset_info:
     num_examples: 7765
   download_size: 5669259
   dataset_size: 13704838
-- config_name: dp
-  features:
-  - name: sentence
-    dtype: string
-  - name: index
-    list: int32
-  - name: word_form
-    list: string
-  - name: lemma
-    list: string
-  - name: pos
-    list: string
-  - name: head
-    list: int32
-  - name: deprel
-    list: string
-  splits:
-  - name: train
-    num_bytes: 7900009
-    num_examples: 10000
-  - name: validation
-    num_bytes: 1557506
-    num_examples: 2000
-  download_size: 2033461
-  dataset_size: 9457515
-- config_name: mrc
+- config_name: sts
   features:
-  - name: title
-    dtype: string
-  - name: context
-    dtype: string
-  - name: news_category
+  - name: guid
     dtype: string
   - name: source
     dtype: string
-  - name: guid
+  - name: sentence1
     dtype: string
-  - name: is_impossible
-    dtype: bool
-  - name: question_type
-    dtype: int32
-  - name: question
+  - name: sentence2
     dtype: string
-  - name: answers
-    sequence:
-    - name: answer_start
-      dtype: int32
-    - name: text
-      dtype: string
+  - name: labels
+    struct:
+    - name: label
+      dtype: float64
+    - name: real-label
+      dtype: float64
+    - name: binary-label
+      dtype:
+        class_label:
+          names:
+            '0': negative
+            '1': positive
   splits:
   - name: train
-    num_bytes: 46505665
-    num_examples: 17554
+    num_bytes: 2832921
+    num_examples: 11668
   - name: validation
-    num_bytes: 15583053
-    num_examples: 5841
-  download_size: 19218422
-  dataset_size: 62088718
+    num_bytes: 122657
+    num_examples: 519
+  download_size: 1349875
+  dataset_size: 2955578
 - config_name: wos
   features:
   - name: guid
@@ -303,15 +282,43 @@ dataset_info:
     num_examples: 1000
   download_size: 4785657
   dataset_size: 30165945
-config_names:
-- dp
-- mrc
-- ner
-- nli
-- re
-- sts
-- wos
-- ynat
+- config_name: ynat
+  features:
+  - name: guid
+    dtype: string
+  - name: title
+    dtype: string
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': IT과학
+          '1': 경제
+          '2': 사회
+          '3': 생활문화
+          '4': 세계
+          '5': 스포츠
+          '6': 정치
+  - name: url
+    dtype: string
+  - name: date
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 10109584
+    num_examples: 45678
+  - name: validation
+    num_bytes: 2039181
+    num_examples: 9107
+  download_size: 5012303
+  dataset_size: 12148765
+configs:
+- config_name: ynat
+  data_files:
+  - split: train
+    path: ynat/train-*
+  - split: validation
+    path: ynat/validation-*
 ---
 
 # Dataset Card for KLUE

dataset_infos.json

@@ -1 +1,721 @@
-{"ynat": {"description": "KLUE (Korean Language Understanding Evaluation)\nKorean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language\nunderstanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible\nto anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain\nunambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics\nfor every task, thus establishing fair comparison across Korean language models.\n", "citation": "@misc{park2021klue,\n      title={KLUE: Korean Language Understanding Evaluation},\n      author={Sungjoon Park and Jihyung Moon and Sungdong Kim and Won Ik Cho and Jiyoon Han and Jangwon Park and Chisung Song and Junseong Kim and Yongsook Song and Taehwan Oh and Joohong Lee and Juhyun Oh and Sungwon Lyu and Younghoon Jeong and Inkwon Lee and Sangwoo Seo and Dongjun Lee and Hyunwoo Kim and Myeonghwa Lee and Seongbo Jang and Seungwon Do and Sunkyoung Kim and Kyungtae Lim and Jongwon Lee and Kyumin Park and Jamin Shin and Seonghyun Kim and Lucy Park and Alice Oh and Jungwoo Ha and Kyunghyun Cho},\n      year={2021},\n      eprint={2105.09680},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://klue-benchmark.com/tasks/66/overview/description", "license": "CC-BY-SA-4.0", "features": {"guid": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 7, "names": ["IT\uacfc\ud559", "\uacbd\uc81c", "\uc0ac\ud68c", "\uc0dd\ud65c\ubb38\ud654", "\uc138\uacc4", "\uc2a4\ud3ec\uce20", "\uc815\uce58"], "names_file": null, "id": null, "_type": "ClassLabel"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "klue", "config_name": "ynat", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10109664, "num_examples": 45678, "dataset_name": "klue"}, "validation": {"name": "validation", "num_bytes": 2039197, "num_examples": 9107, "dataset_name": "klue"}}, "download_checksums": {"http://klue-benchmark.com.s3.amazonaws.com/app/Competitions/000066/data/ynat-v1.tar.gz": {"num_bytes": 4932555, "checksum": "820a4d1d6d1fd83e2a421f856965d3cfc5c93627935ce8c5b27468c6113fc482"}}, "download_size": 4932555, "post_processing_size": null, "dataset_size": 12148861, "size_in_bytes": 17081416}, "sts": {"description": "KLUE (Korean Language Understanding Evaluation)\nKorean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language\nunderstanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible\nto anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain\nunambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics\nfor every task, thus establishing fair comparison across Korean language models.\n", "citation": "@misc{park2021klue,\n      title={KLUE: Korean Language Understanding Evaluation},\n      author={Sungjoon Park and Jihyung Moon and Sungdong Kim and Won Ik Cho and Jiyoon Han and Jangwon Park and Chisung Song and Junseong Kim and Yongsook Song and Taehwan Oh and Joohong Lee and Juhyun Oh and Sungwon Lyu and Younghoon Jeong and Inkwon Lee and Sangwoo Seo and Dongjun Lee and Hyunwoo Kim and Myeonghwa Lee and Seongbo Jang and Seungwon Do and Sunkyoung Kim and Kyungtae Lim and Jongwon Lee and Kyumin Park and Jamin Shin and Seonghyun Kim and Lucy Park and Alice Oh and Jungwoo Ha and Kyunghyun Cho},\n      year={2021},\n      eprint={2105.09680},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://klue-benchmark.com/tasks/67/overview/description", "license": "CC-BY-SA-4.0", "features": {"guid": {"dtype": "string", "id": null, "_type": "Value"}, "source": {"dtype": "string", "id": null, "_type": "Value"}, "sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"label": {"dtype": "float64", "id": null, "_type": "Value"}, "real-label": {"dtype": "float64", "id": null, "_type": "Value"}, "binary-label": {"num_classes": 2, "names": ["negative", "positive"], "names_file": null, "id": null, "_type": "ClassLabel"}}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "klue", "config_name": "sts", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2832921, "num_examples": 11668, "dataset_name": "klue"}, "validation": {"name": "validation", "num_bytes": 122657, "num_examples": 519, "dataset_name": "klue"}}, "download_checksums": {"http://klue-benchmark.com.s3.amazonaws.com/app/Competitions/000067/data/klue-sts-v1.tar.gz": {"num_bytes": 1349875, "checksum": "539341ba78a3b351c686cf70a448ac7a5886ed95f0719d5e3d2378ba703213bd"}}, "download_size": 1349875, "post_processing_size": null, "dataset_size": 2955578, "size_in_bytes": 4305453}, "nli": {"description": "KLUE (Korean Language Understanding Evaluation)\nKorean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language\nunderstanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible\nto anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain\nunambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics\nfor every task, thus establishing fair comparison across Korean language models.\n", "citation": "@misc{park2021klue,\n      title={KLUE: Korean Language Understanding Evaluation},\n      author={Sungjoon Park and Jihyung Moon and Sungdong Kim and Won Ik Cho and Jiyoon Han and Jangwon Park and Chisung Song and Junseong Kim and Yongsook Song and Taehwan Oh and Joohong Lee and Juhyun Oh and Sungwon Lyu and Younghoon Jeong and Inkwon Lee and Sangwoo Seo and Dongjun Lee and Hyunwoo Kim and Myeonghwa Lee and Seongbo Jang and Seungwon Do and Sunkyoung Kim and Kyungtae Lim and Jongwon Lee and Kyumin Park and Jamin Shin and Seonghyun Kim and Lucy Park and Alice Oh and Jungwoo Ha and Kyunghyun Cho},\n      year={2021},\n      eprint={2105.09680},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://klue-benchmark.com/tasks/68/overview/description", "license": "CC-BY-SA-4.0", "features": {"guid": {"dtype": "string", "id": null, "_type": "Value"}, "source": {"dtype": "string", "id": null, "_type": "Value"}, "premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["entailment", "neutral", "contradiction"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "klue", "config_name": "nli", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5719930, "num_examples": 24998, "dataset_name": "klue"}, "validation": {"name": "validation", "num_bytes": 673276, "num_examples": 3000, "dataset_name": "klue"}}, "download_checksums": {"http://klue-benchmark.com.s3.amazonaws.com/app/Competitions/000068/data/klue-nli-v1.tar.gz": {"num_bytes": 1257374, "checksum": "388be2033ef712072201903795a35b4f86826ee3ed3b62dc0c98e1721baa8850"}}, "download_size": 1257374, "post_processing_size": null, "dataset_size": 6393206, "size_in_bytes": 7650580}, "ner": {"description": "KLUE (Korean Language Understanding Evaluation)\nKorean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language\nunderstanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible\nto anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain\nunambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics\nfor every task, thus establishing fair comparison across Korean language models.\n", "citation": "@misc{park2021klue,\n      title={KLUE: Korean Language Understanding Evaluation},\n      author={Sungjoon Park and Jihyung Moon and Sungdong Kim and Won Ik Cho and Jiyoon Han and Jangwon Park and Chisung Song and Junseong Kim and Yongsook Song and Taehwan Oh and Joohong Lee and Juhyun Oh and Sungwon Lyu and Younghoon Jeong and Inkwon Lee and Sangwoo Seo and Dongjun Lee and Hyunwoo Kim and Myeonghwa Lee and Seongbo Jang and Seungwon Do and Sunkyoung Kim and Kyungtae Lim and Jongwon Lee and Kyumin Park and Jamin Shin and Seonghyun Kim and Lucy Park and Alice Oh and Jungwoo Ha and Kyunghyun Cho},\n      year={2021},\n      eprint={2105.09680},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://klue-benchmark.com/tasks/69/overview/description", "license": "CC-BY-SA-4.0", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 13, "names": ["B-DT", "I-DT", "B-LC", "I-LC", "B-OG", "I-OG", "B-PS", "I-PS", "B-QT", "I-QT", "B-TI", "I-TI", "O"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "klue", "config_name": "ner", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 19891953, "num_examples": 21008, "dataset_name": "klue"}, "validation": {"name": "validation", "num_bytes": 4937579, "num_examples": 5000, "dataset_name": "klue"}}, "download_checksums": {"http://klue-benchmark.com.s3.amazonaws.com/app/Competitions/000069/data/klue-ner-v1.tar.gz": {"num_bytes": 4308644, "checksum": "848a89759ac6b7c149c9a00d820726fe2a140c22782201f1a40d856672e7ea8e"}}, "download_size": 4308644, "post_processing_size": null, "dataset_size": 24829532, "size_in_bytes": 29138176}, "re": {"description": "KLUE (Korean Language Understanding Evaluation)\nKorean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language\nunderstanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible\nto anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain\nunambiguous annotations for all datasets. 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