David Pomerenke commited on
Commit
d8f2dee
·
1 Parent(s): 031925d

Add dataset metadata about human/machine translation

Browse files
datasets.json CHANGED
@@ -11,6 +11,7 @@
11
  "language_modeling"
12
  ],
13
  "parallel": true,
 
14
  "base": "FLORES",
15
  "implemented": true,
16
  "group": "Low-Resource Languages"
@@ -25,8 +26,9 @@
25
  "speech_recognition"
26
  ],
27
  "parallel": true,
 
28
  "base": "FLORES",
29
- "implemented": true,
30
  "group": "Low-Resource Languages"
31
  },
32
  {
@@ -39,8 +41,68 @@
39
  "speech_recognition"
40
  ],
41
  "parallel": null,
 
42
  "group": "Low-Resource Languages"
43
  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
44
  {
45
  "name": "MMMLU",
46
  "author": "OpenAI",
@@ -67,7 +129,9 @@
67
  "question_answering"
68
  ],
69
  "parallel": true,
 
70
  "base": "MMLU",
 
71
  "group": "Multitask Language Understanding"
72
  },
73
  {
@@ -100,7 +164,9 @@
100
  "question_answering"
101
  ],
102
  "parallel": true,
 
103
  "base": "MMLU",
 
104
  "group": "Multitask Language Understanding"
105
  },
106
  {
@@ -146,7 +212,9 @@
146
  "question_answering"
147
  ],
148
  "parallel": true,
 
149
  "base": "MMLU",
 
150
  "group": "Multitask Language Understanding"
151
  },
152
  {
@@ -181,65 +249,25 @@
181
  "question_answering"
182
  ],
183
  "parallel": true,
 
184
  "base": "MMLU",
 
185
  "group": "Multitask Language Understanding"
186
  },
187
  {
188
- "name": "Global MMLU",
189
- "author": "Cohere",
190
- "author_url": "https://cohere.com",
191
- "url": "https://huggingface.co/datasets/CohereForAI/Global-MMLU",
192
- "n_languages": 42,
193
- "languages": [
194
- "am",
195
- "ar",
196
- "bn",
197
- "cs",
198
- "de",
199
- "el",
200
- "en",
201
- "es",
202
- "fa",
203
- "fil",
204
- "fr",
205
- "ha",
206
- "he",
207
- "hi",
208
- "id",
209
- "ig",
210
- "it",
211
- "ja",
212
- "ko",
213
- "ky",
214
- "lt",
215
- "mg",
216
- "ms",
217
- "ne",
218
- "nl",
219
- "ny",
220
- "pl",
221
- "pt",
222
- "ro",
223
- "ru",
224
- "si",
225
- "sn",
226
- "so",
227
- "sr",
228
- "sv",
229
- "sw",
230
- "te",
231
- "tr",
232
- "uk",
233
- "vi",
234
- "yo",
235
- "zh"
236
- ],
237
  "tasks": [
238
  "question_answering"
239
  ],
240
  "parallel": true,
241
- "base": "MMLU",
242
- "group": "Multitask Language Understanding"
 
 
243
  },
244
  {
245
  "name": "Okapi ARC Challenge",
@@ -251,20 +279,9 @@
251
  "question_answering"
252
  ],
253
  "parallel": true,
 
254
  "base": "AI2 ARC",
255
- "group": "Abstract Reasoning"
256
- },
257
- {
258
- "name": "Uhuru ARC Easy",
259
- "author": "Masakhane",
260
- "author_url": "https://www.masakhane.io",
261
- "url": "https://huggingface.co/datasets/masakhane/uhura-arc-easy",
262
- "n_languages": 6,
263
- "tasks": [
264
- "question_answering"
265
- ],
266
- "parallel": true,
267
- "base": "AI2 ARC",
268
  "group": "Abstract Reasoning"
269
  },
270
  {
@@ -277,33 +294,39 @@
277
  "question_answering"
278
  ],
279
  "parallel": true,
 
280
  "base": "AI2 ARC",
 
281
  "group": "Abstract Reasoning"
282
  },
283
  {
284
- "name": "Okapi TruthfulQA",
285
- "author": "Academic",
286
- "author_url": null,
287
- "url": "https://huggingface.co/datasets/jon-tow/okapi_truthfulqa/tree/main/data",
288
- "n_languages": 31,
289
  "tasks": [
290
  "question_answering"
291
  ],
292
  "parallel": true,
 
293
  "base": "TruthfulQA",
 
294
  "group": "Truthfulness"
295
  },
296
  {
297
- "name": "Uhura TruthfulQA",
298
- "author": "Masakhane",
299
- "author_url": "https://www.masakhane.io",
300
- "url": "https://huggingface.co/datasets/masakhane/uhura-truthfulqa",
301
- "n_languages": 6,
302
  "tasks": [
303
  "question_answering"
304
  ],
305
  "parallel": true,
 
306
  "base": "TruthfulQA",
 
307
  "group": "Truthfulness"
308
  },
309
  {
@@ -316,7 +339,9 @@
316
  "question_answering"
317
  ],
318
  "parallel": true,
 
319
  "base": "TruthfulQA",
 
320
  "group": "Truthfulness"
321
  },
322
  {
@@ -344,7 +369,9 @@
344
  "logic"
345
  ],
346
  "parallel": true,
 
347
  "base": "MNLI",
 
348
  "group": "Natural Language Inference"
349
  },
350
  {
@@ -383,7 +410,9 @@
383
  "question_answering"
384
  ],
385
  "parallel": true,
 
386
  "base": "HellaSwag",
 
387
  "group": "Adversarial Language Modelling"
388
  },
389
  {
@@ -396,7 +425,9 @@
396
  "question_answering"
397
  ],
398
  "parallel": true,
 
399
  "base": "HellaSwag",
 
400
  "group": "Adversarial Language Modelling"
401
  },
402
  {
@@ -422,7 +453,9 @@
422
  "math"
423
  ],
424
  "parallel": true,
 
425
  "base": "MGSM",
 
426
  "group": "Grade School Math"
427
  },
428
  {
@@ -435,7 +468,9 @@
435
  "math"
436
  ],
437
  "parallel": true,
 
438
  "base": "MGSM",
 
439
  "group": "Grade School Math"
440
  },
441
  {
 
11
  "language_modeling"
12
  ],
13
  "parallel": true,
14
+ "translation": "human",
15
  "base": "FLORES",
16
  "implemented": true,
17
  "group": "Low-Resource Languages"
 
26
  "speech_recognition"
27
  ],
28
  "parallel": true,
29
+ "translation": "human",
30
  "base": "FLORES",
31
+ "implemented": false,
32
  "group": "Low-Resource Languages"
33
  },
34
  {
 
41
  "speech_recognition"
42
  ],
43
  "parallel": null,
44
+ "translation": "human",
45
  "group": "Low-Resource Languages"
46
  },
47
+ {
48
+ "name": "Global MMLU",
49
+ "author": "Cohere",
50
+ "author_url": "https://cohere.com",
51
+ "url": "https://huggingface.co/datasets/CohereForAI/Global-MMLU",
52
+ "n_languages": 42,
53
+ "languages": [
54
+ "am",
55
+ "ar",
56
+ "bn",
57
+ "cs",
58
+ "de",
59
+ "el",
60
+ "en",
61
+ "es",
62
+ "fa",
63
+ "fil",
64
+ "fr",
65
+ "ha",
66
+ "he",
67
+ "hi",
68
+ "id",
69
+ "ig",
70
+ "it",
71
+ "ja",
72
+ "ko",
73
+ "ky",
74
+ "lt",
75
+ "mg",
76
+ "ms",
77
+ "ne",
78
+ "nl",
79
+ "ny",
80
+ "pl",
81
+ "pt",
82
+ "ro",
83
+ "ru",
84
+ "si",
85
+ "sn",
86
+ "so",
87
+ "sr",
88
+ "sv",
89
+ "sw",
90
+ "te",
91
+ "tr",
92
+ "uk",
93
+ "vi",
94
+ "yo",
95
+ "zh"
96
+ ],
97
+ "tasks": [
98
+ "question_answering"
99
+ ],
100
+ "parallel": true,
101
+ "translation": "mixed",
102
+ "base": "MMLU",
103
+ "implemented": true,
104
+ "group": "Multitask Language Understanding"
105
+ },
106
  {
107
  "name": "MMMLU",
108
  "author": "OpenAI",
 
129
  "question_answering"
130
  ],
131
  "parallel": true,
132
+ "translation": "human",
133
  "base": "MMLU",
134
+ "implemented": true,
135
  "group": "Multitask Language Understanding"
136
  },
137
  {
 
164
  "question_answering"
165
  ],
166
  "parallel": true,
167
+ "translation": "human",
168
  "base": "MMLU",
169
+ "implemented": true,
170
  "group": "Multitask Language Understanding"
171
  },
172
  {
 
212
  "question_answering"
213
  ],
214
  "parallel": true,
215
+ "translation": "machine",
216
  "base": "MMLU",
217
+ "implemented": false,
218
  "group": "Multitask Language Understanding"
219
  },
220
  {
 
249
  "question_answering"
250
  ],
251
  "parallel": true,
252
+ "translation": "machine",
253
  "base": "MMLU",
254
+ "implemented": false,
255
  "group": "Multitask Language Understanding"
256
  },
257
  {
258
+ "name": "Uhuru ARC Easy",
259
+ "author": "Masakhane",
260
+ "author_url": "https://www.masakhane.io",
261
+ "url": "https://huggingface.co/datasets/masakhane/uhura-arc-easy",
262
+ "n_languages": 6,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
263
  "tasks": [
264
  "question_answering"
265
  ],
266
  "parallel": true,
267
+ "translation": "human",
268
+ "base": "AI2 ARC",
269
+ "implemented": false,
270
+ "group": "Abstract Reasoning"
271
  },
272
  {
273
  "name": "Okapi ARC Challenge",
 
279
  "question_answering"
280
  ],
281
  "parallel": true,
282
+ "translation": "machine",
283
  "base": "AI2 ARC",
284
+ "implemented": false,
 
 
 
 
 
 
 
 
 
 
 
 
285
  "group": "Abstract Reasoning"
286
  },
287
  {
 
294
  "question_answering"
295
  ],
296
  "parallel": true,
297
+ "translation": "machine",
298
  "base": "AI2 ARC",
299
+ "implemented": false,
300
  "group": "Abstract Reasoning"
301
  },
302
  {
303
+ "name": "Uhura TruthfulQA",
304
+ "author": "Masakhane",
305
+ "author_url": "https://www.masakhane.io",
306
+ "url": "https://huggingface.co/datasets/masakhane/uhura-truthfulqa",
307
+ "n_languages": 6,
308
  "tasks": [
309
  "question_answering"
310
  ],
311
  "parallel": true,
312
+ "translation": "human",
313
  "base": "TruthfulQA",
314
+ "implemented": false,
315
  "group": "Truthfulness"
316
  },
317
  {
318
+ "name": "Okapi TruthfulQA",
319
+ "author": "Academic",
320
+ "author_url": null,
321
+ "url": "https://huggingface.co/datasets/jon-tow/okapi_truthfulqa/tree/main/data",
322
+ "n_languages": 31,
323
  "tasks": [
324
  "question_answering"
325
  ],
326
  "parallel": true,
327
+ "translation": "machine",
328
  "base": "TruthfulQA",
329
+ "implemented": false,
330
  "group": "Truthfulness"
331
  },
332
  {
 
339
  "question_answering"
340
  ],
341
  "parallel": true,
342
+ "translation": "machine",
343
  "base": "TruthfulQA",
344
+ "implemented": false,
345
  "group": "Truthfulness"
346
  },
347
  {
 
369
  "logic"
370
  ],
371
  "parallel": true,
372
+ "translation": "human",
373
  "base": "MNLI",
374
+ "implemented": false,
375
  "group": "Natural Language Inference"
376
  },
377
  {
 
410
  "question_answering"
411
  ],
412
  "parallel": true,
413
+ "translation": "machine",
414
  "base": "HellaSwag",
415
+ "implemented": false,
416
  "group": "Adversarial Language Modelling"
417
  },
418
  {
 
425
  "question_answering"
426
  ],
427
  "parallel": true,
428
+ "translation": "machine",
429
  "base": "HellaSwag",
430
+ "implemented": false,
431
  "group": "Adversarial Language Modelling"
432
  },
433
  {
 
453
  "math"
454
  ],
455
  "parallel": true,
456
+ "translation": "human",
457
  "base": "MGSM",
458
+ "implemented": false,
459
  "group": "Grade School Math"
460
  },
461
  {
 
468
  "math"
469
  ],
470
  "parallel": true,
471
+ "translation": "machine",
472
  "base": "MGSM",
473
+ "implemented": false,
474
  "group": "Grade School Math"
475
  },
476
  {
frontend/src/components/DatasetTable.js CHANGED
@@ -7,8 +7,9 @@ import 'primeicons/primeicons.css'
7
 
8
  const DatasetTable = ({ data }) => {
9
  const [filters, setFilters] = useState({
10
- n_languages: { value: null, matchMode: FilterMatchMode.BETWEEN },
11
  tasks: { value: null, matchMode: FilterMatchMode.IN },
 
 
12
  parallel: { value: null, matchMode: FilterMatchMode.EQUALS },
13
  base: { value: null, matchMode: FilterMatchMode.IN },
14
  })
@@ -43,6 +44,16 @@ const DatasetTable = ({ data }) => {
43
  return <a href={rowData.url} target='_blank' style={{ textDecoration: 'none', color: 'inherit' }}><i className='pi pi-external-link' style={{ fontSize: '0.8rem' }} /></a>
44
  }
45
 
 
 
 
 
 
 
 
 
 
 
46
  const nLanguagesBodyTemplate = rowData => {
47
  return <div style={{ textAlign: 'center' }}>
48
  {rowData.n_languages}
@@ -67,6 +78,23 @@ const DatasetTable = ({ data }) => {
67
  )
68
  }
69
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
70
  return (
71
  <DataTable
72
  value={table}
@@ -88,7 +116,7 @@ const DatasetTable = ({ data }) => {
88
  <Column
89
  field='implemented'
90
  header={null}
91
- sortable
92
  style={{ maxWidth: '5rem' }}
93
  body={implementedBodyTemplate}
94
  />
@@ -103,7 +131,7 @@ const DatasetTable = ({ data }) => {
103
  field='name'
104
  header='Name'
105
  body={nameBodyTemplate}
106
- style={{ minWidth: '5rem' }}
107
  frozen
108
  />
109
  <Column
@@ -120,9 +148,19 @@ const DatasetTable = ({ data }) => {
120
  style={{ minWidth: '10rem', maxWidth: '15rem' }}
121
  body={tasksBodyTemplate}
122
  />
 
 
 
 
 
 
 
 
 
123
  <Column
124
  field='n_languages'
125
  header='Languages'
 
126
  filter
127
  sortable
128
  style={{ minWidth: '5rem', maxWidth: '10rem' }}
 
7
 
8
  const DatasetTable = ({ data }) => {
9
  const [filters, setFilters] = useState({
 
10
  tasks: { value: null, matchMode: FilterMatchMode.IN },
11
+ translation: { value: null, matchMode: FilterMatchMode.IN },
12
+ n_languages: { value: null, matchMode: FilterMatchMode.BETWEEN },
13
  parallel: { value: null, matchMode: FilterMatchMode.EQUALS },
14
  base: { value: null, matchMode: FilterMatchMode.IN },
15
  })
 
44
  return <a href={rowData.url} target='_blank' style={{ textDecoration: 'none', color: 'inherit' }}><i className='pi pi-external-link' style={{ fontSize: '0.8rem' }} /></a>
45
  }
46
 
47
+ const translationBodyTemplate = rowData => {
48
+ const translationIcons = {
49
+ human: <i className='pi pi-user' title='Human-translated' />,
50
+ machine: <i className='pi pi-cog' title='Machine-translated' />,
51
+ mixed: <><i className='pi pi-user' title='Partially human-translated' /> <i className='pi pi-cog' title='Partially machine-translated' /></>,
52
+ }
53
+ const icon = translationIcons[rowData.translation] ?? <></>
54
+ return <div style={{ textAlign: 'center' }}>{icon}</div>
55
+ }
56
+
57
  const nLanguagesBodyTemplate = rowData => {
58
  return <div style={{ textAlign: 'center' }}>
59
  {rowData.n_languages}
 
78
  )
79
  }
80
 
81
+ const translationRowFilterTemplate = options => {
82
+ return (
83
+ <MultiSelect
84
+ value={options.value}
85
+ options={['human', 'mixed', 'machine']}
86
+ onChange={e => {
87
+ options.filterApplyCallback(e.value)
88
+ setFilters(prevFilters => ({
89
+ ...prevFilters,
90
+ translation: { value: e.value, matchMode: FilterMatchMode.IN }
91
+ }))
92
+ }}
93
+ placeholder='All translation modes'
94
+ />
95
+ )
96
+ }
97
+
98
  return (
99
  <DataTable
100
  value={table}
 
116
  <Column
117
  field='implemented'
118
  header={null}
119
+ headerTooltip='Whether the dataset has been integrated into this benchmark'
120
  style={{ maxWidth: '5rem' }}
121
  body={implementedBodyTemplate}
122
  />
 
131
  field='name'
132
  header='Name'
133
  body={nameBodyTemplate}
134
+ style={{ minWidth: '10rem' }}
135
  frozen
136
  />
137
  <Column
 
148
  style={{ minWidth: '10rem', maxWidth: '15rem' }}
149
  body={tasksBodyTemplate}
150
  />
151
+ <Column
152
+ field='translation'
153
+ header={<i className='pi pi-language' />}
154
+ headerTooltip='Whether the dataset has been translated by humans or machines'
155
+ filter
156
+ filterElement={translationRowFilterTemplate}
157
+ showFilterMatchModes={false}
158
+ body={translationBodyTemplate}
159
+ />
160
  <Column
161
  field='n_languages'
162
  header='Languages'
163
+ headerTooltip='Number of languages in the dataset'
164
  filter
165
  sortable
166
  style={{ minWidth: '5rem', maxWidth: '10rem' }}