Sebastian Gehrmann
commited on
Commit
•
1e5fcfa
1
Parent(s):
357067d
rename
Browse files- dataset_infos.json +126 -1
dataset_infos.json
CHANGED
@@ -1 +1,126 @@
|
|
1 |
-
{
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"abstract": {
|
3 |
+
"description": "The OrangeSum dataset was inspired by the XSum dataset. It was created by scraping the \"Orange Actu\" website: https://actu.orange.fr/. Orange S.A. is a large French multinational telecommunications corporation, with 266M customers worldwide. Scraped pages cover almost a decade from Feb 2011 to Sep 2020. They belong to five main categories: France, world, politics, automotive, and society. The society category is itself divided into 8 subcategories: health, environment, people, culture, media, high-tech, unsual (\"insolite\" in French), and miscellaneous.\n\nEach article featured a single-sentence title as well as a very brief abstract, both professionally written by the author of the article. These two fields were extracted from each page, thus creating two summarization tasks: OrangeSum Title and OrangeSum Abstract.\n",
|
4 |
+
"citation": "@article{eddine2020barthez,\n title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},\n author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},\n journal={arXiv preprint arXiv:2010.12321},\n year={2020}\n}\n",
|
5 |
+
"homepage": "https://github.com/Tixierae/OrangeSum/",
|
6 |
+
"license": "",
|
7 |
+
"features": {
|
8 |
+
"text": {
|
9 |
+
"dtype": "string",
|
10 |
+
"id": null,
|
11 |
+
"_type": "Value"
|
12 |
+
},
|
13 |
+
"summary": {
|
14 |
+
"dtype": "string",
|
15 |
+
"id": null,
|
16 |
+
"_type": "Value"
|
17 |
+
}
|
18 |
+
},
|
19 |
+
"post_processed": null,
|
20 |
+
"supervised_keys": {
|
21 |
+
"input": "text",
|
22 |
+
"output": "summary"
|
23 |
+
},
|
24 |
+
"builder_name": "OrangeSum",
|
25 |
+
"config_name": "abstract",
|
26 |
+
"version": {
|
27 |
+
"version_str": "1.1.0",
|
28 |
+
"description": null,
|
29 |
+
"major": 1,
|
30 |
+
"minor": 1,
|
31 |
+
"patch": 0
|
32 |
+
},
|
33 |
+
"splits": {
|
34 |
+
"train": {
|
35 |
+
"name": "train",
|
36 |
+
"num_bytes": 53531651,
|
37 |
+
"num_examples": 21401,
|
38 |
+
"dataset_name": "OrangeSum"
|
39 |
+
},
|
40 |
+
"test": {
|
41 |
+
"name": "test",
|
42 |
+
"num_bytes": 3785207,
|
43 |
+
"num_examples": 1500,
|
44 |
+
"dataset_name": "OrangeSum"
|
45 |
+
},
|
46 |
+
"validation": {
|
47 |
+
"name": "validation",
|
48 |
+
"num_bytes": 3698650,
|
49 |
+
"num_examples": 1500,
|
50 |
+
"dataset_name": "OrangeSum"
|
51 |
+
}
|
52 |
+
},
|
53 |
+
"download_checksums": {
|
54 |
+
"https://raw.githubusercontent.com/Tixierae/OrangeSum/main/data/docs/splits/abstract.tgz": {
|
55 |
+
"num_bytes": 23058350,
|
56 |
+
"checksum": "eaa4321b70bcf41c758d02fb5a94e50d73509a2be32adb1f9aacdcfd5796434b"
|
57 |
+
}
|
58 |
+
},
|
59 |
+
"download_size": 23058350,
|
60 |
+
"post_processing_size": null,
|
61 |
+
"dataset_size": 61015508,
|
62 |
+
"size_in_bytes": 84073858
|
63 |
+
},
|
64 |
+
"title": {
|
65 |
+
"description": "The OrangeSum dataset was inspired by the XSum dataset. It was created by scraping the \"Orange Actu\" website: https://actu.orange.fr/. Orange S.A. is a large French multinational telecommunications corporation, with 266M customers worldwide. Scraped pages cover almost a decade from Feb 2011 to Sep 2020. They belong to five main categories: France, world, politics, automotive, and society. The society category is itself divided into 8 subcategories: health, environment, people, culture, media, high-tech, unsual (\"insolite\" in French), and miscellaneous.\n\nEach article featured a single-sentence title as well as a very brief abstract, both professionally written by the author of the article. These two fields were extracted from each page, thus creating two summarization tasks: OrangeSum Title and OrangeSum Abstract.\n",
|
66 |
+
"citation": "@article{eddine2020barthez,\n title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},\n author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},\n journal={arXiv preprint arXiv:2010.12321},\n year={2020}\n}\n",
|
67 |
+
"homepage": "https://github.com/Tixierae/OrangeSum/",
|
68 |
+
"license": "",
|
69 |
+
"features": {
|
70 |
+
"text": {
|
71 |
+
"dtype": "string",
|
72 |
+
"id": null,
|
73 |
+
"_type": "Value"
|
74 |
+
},
|
75 |
+
"summary": {
|
76 |
+
"dtype": "string",
|
77 |
+
"id": null,
|
78 |
+
"_type": "Value"
|
79 |
+
}
|
80 |
+
},
|
81 |
+
"post_processed": null,
|
82 |
+
"supervised_keys": {
|
83 |
+
"input": "text",
|
84 |
+
"output": "summary"
|
85 |
+
},
|
86 |
+
"builder_name": "OrangeSum",
|
87 |
+
"config_name": "title",
|
88 |
+
"version": {
|
89 |
+
"version_str": "1.1.0",
|
90 |
+
"description": null,
|
91 |
+
"major": 1,
|
92 |
+
"minor": 1,
|
93 |
+
"patch": 0
|
94 |
+
},
|
95 |
+
"splits": {
|
96 |
+
"train": {
|
97 |
+
"name": "train",
|
98 |
+
"num_bytes": 65225136,
|
99 |
+
"num_examples": 30659,
|
100 |
+
"dataset_name": "OrangeSum"
|
101 |
+
},
|
102 |
+
"test": {
|
103 |
+
"name": "test",
|
104 |
+
"num_bytes": 3176690,
|
105 |
+
"num_examples": 1500,
|
106 |
+
"dataset_name": "OrangeSum"
|
107 |
+
},
|
108 |
+
"validation": {
|
109 |
+
"name": "validation",
|
110 |
+
"num_bytes": 3276713,
|
111 |
+
"num_examples": 1500,
|
112 |
+
"dataset_name": "OrangeSum"
|
113 |
+
}
|
114 |
+
},
|
115 |
+
"download_checksums": {
|
116 |
+
"https://raw.githubusercontent.com/Tixierae/OrangeSum/main/data/docs/splits/title.tgz": {
|
117 |
+
"num_bytes": 27321627,
|
118 |
+
"checksum": "5d15823f7e1158f16f5428fdfc8fa26509f98325c0793d6a8880a33af9822301"
|
119 |
+
}
|
120 |
+
},
|
121 |
+
"download_size": 27321627,
|
122 |
+
"post_processing_size": null,
|
123 |
+
"dataset_size": 71678539,
|
124 |
+
"size_in_bytes": 99000166
|
125 |
+
}
|
126 |
+
}
|