Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
ArXiv:
Tags:
License:
albertvillanova HF staff commited on
Commit
87e8984
1 Parent(s): 7f101e0

Convert dataset to Parquet

Browse files

Convert dataset to Parquet.

README.md CHANGED
@@ -1,15 +1,14 @@
1
  ---
2
  annotations_creators:
3
  - crowdsourced
4
- language:
5
- - en
6
  language_creators:
7
  - crowdsourced
 
 
8
  license:
9
  - unknown
10
  multilinguality:
11
  - monolingual
12
- pretty_name: Commonsense Explanations
13
  size_categories:
14
  - 10K<n<100K
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  source_datasets:
@@ -19,6 +18,7 @@ task_categories:
19
  task_ids:
20
  - open-domain-qa
21
  paperswithcode_id: cos-e
 
22
  dataset_info:
23
  - config_name: v1.0
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  features:
@@ -36,13 +36,13 @@ dataset_info:
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  dtype: string
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  splits:
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  - name: train
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- num_bytes: 2077517
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  num_examples: 7610
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  - name: validation
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- num_bytes: 261887
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  num_examples: 950
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- download_size: 4295320
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- dataset_size: 2339404
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  - config_name: v1.11
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  features:
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  - name: id
@@ -66,6 +66,13 @@ dataset_info:
66
  num_examples: 1221
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  download_size: 6535534
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  dataset_size: 3049180
 
 
 
 
 
 
 
69
  ---
70
 
71
  # Dataset Card for "cos_e"
1
  ---
2
  annotations_creators:
3
  - crowdsourced
 
 
4
  language_creators:
5
  - crowdsourced
6
+ language:
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+ - en
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  license:
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  - unknown
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  multilinguality:
11
  - monolingual
 
12
  size_categories:
13
  - 10K<n<100K
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  source_datasets:
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  task_ids:
19
  - open-domain-qa
20
  paperswithcode_id: cos-e
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+ pretty_name: Commonsense Explanations
22
  dataset_info:
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  - config_name: v1.0
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  features:
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  dtype: string
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  splits:
38
  - name: train
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+ num_bytes: 2067971
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  num_examples: 7610
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  - name: validation
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+ num_bytes: 260669
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  num_examples: 950
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+ download_size: 1588340
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+ dataset_size: 2328640
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  - config_name: v1.11
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  features:
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  - name: id
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  num_examples: 1221
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  download_size: 6535534
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  dataset_size: 3049180
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+ configs:
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+ - config_name: v1.0
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+ data_files:
72
+ - split: train
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+ path: v1.0/train-*
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+ - split: validation
75
+ path: v1.0/validation-*
76
  ---
77
 
78
  # Dataset Card for "cos_e"
dataset_infos.json CHANGED
@@ -1 +1,157 @@
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Leveraging Language models for Commonsense Reasoning\",\n author = \"Rajani, Nazneen Fatema and\n McCann, Bryan and\n Xiong, Caiming and\n Socher, Richard\",\n year=\"2019\",\n booktitle = \"Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)\",\n url =\"https://arxiv.org/abs/1906.02361\"\n}\n", "homepage": "https://github.com/salesforce/cos-e", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "abstractive_explanation": {"dtype": "string", "id": null, "_type": "Value"}, "extractive_explanation": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "cos_e", "config_name": "v1.0", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2077517, "num_examples": 7610, "dataset_name": "cos_e"}, "validation": {"name": "validation", "num_bytes": 261887, "num_examples": 950, "dataset_name": "cos_e"}}, "download_checksums": {"https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/train_rand_split.jsonl": {"num_bytes": 2160200, "checksum": "1989ce97e24d8572113d6a18f44e0f11ee9d206fb9bf9a1133937645583e697e"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/dev_rand_split.jsonl": {"num_bytes": 268531, "checksum": "790dd2a8492e7f3b51ded04116de603115b7acaded32ea84f6a7101f9d571ac1"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/test_rand_split_no_answers.jsonl": {"num_bytes": 250752, "checksum": "b9c3d1319667ea1569be6f7b3ed0546bd8222d2f3a759f928307343a0282e190"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/cose_dev_v1.0_processed.jsonl": {"num_bytes": 182444, "checksum": "ab7b8ac91bca1a6ba798816af6aca703a739f576c919360ddc376d9d3046be53"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/cose_train_v1.0_processed.jsonl": {"num_bytes": 1433393, "checksum": "df9f83ac4891f38e0771470858d5f1c4b5bb08fee5c53f38f9df9b3d3675ea74"}}, "download_size": 4295320, "dataset_size": 2339404, "size_in_bytes": 6634724}, "v1.11": {"description": "\nCommon Sense Explanations (CoS-E) allows for training language models to\nautomatically generate explanations that can be used during training and\ninference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.\n", "citation": "\n@inproceedings{rajani2019explain,\n title = \"Explain Yourself! 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