albertvillanova HF staff commited on
Commit
2f39d5f
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1 Parent(s): 7c06415

Replace YAML keys from int to str

Browse files

Replace YAML metadata integer keys with strings, as the Hub does not support integers.
See: https://github.com/huggingface/datasets/issues/5275

Files changed (1) hide show
  1. README.md +265 -265
README.md CHANGED
@@ -24,223 +24,6 @@ task_ids:
24
  - sentiment-classification
25
  paperswithcode_id: tweeteval
26
  pretty_name: TweetEval
27
- train-eval-index:
28
- - config: emotion
29
- task: text-classification
30
- task_id: multi_class_classification
31
- splits:
32
- train_split: train
33
- eval_split: test
34
- col_mapping:
35
- text: text
36
- label: target
37
- metrics:
38
- - type: accuracy
39
- name: Accuracy
40
- - type: f1
41
- name: F1 macro
42
- args:
43
- average: macro
44
- - type: f1
45
- name: F1 micro
46
- args:
47
- average: micro
48
- - type: f1
49
- name: F1 weighted
50
- args:
51
- average: weighted
52
- - type: precision
53
- name: Precision macro
54
- args:
55
- average: macro
56
- - type: precision
57
- name: Precision micro
58
- args:
59
- average: micro
60
- - type: precision
61
- name: Precision weighted
62
- args:
63
- average: weighted
64
- - type: recall
65
- name: Recall macro
66
- args:
67
- average: macro
68
- - type: recall
69
- name: Recall micro
70
- args:
71
- average: micro
72
- - type: recall
73
- name: Recall weighted
74
- args:
75
- average: weighted
76
- - config: hate
77
- task: text-classification
78
- task_id: binary_classification
79
- splits:
80
- train_split: train
81
- eval_split: test
82
- col_mapping:
83
- text: text
84
- label: target
85
- metrics:
86
- - type: accuracy
87
- name: Accuracy
88
- - type: f1
89
- name: F1 binary
90
- args:
91
- average: binary
92
- - type: precision
93
- name: Precision macro
94
- args:
95
- average: macro
96
- - type: precision
97
- name: Precision micro
98
- args:
99
- average: micro
100
- - type: precision
101
- name: Precision weighted
102
- args:
103
- average: weighted
104
- - type: recall
105
- name: Recall macro
106
- args:
107
- average: macro
108
- - type: recall
109
- name: Recall micro
110
- args:
111
- average: micro
112
- - type: recall
113
- name: Recall weighted
114
- args:
115
- average: weighted
116
- - config: irony
117
- task: text-classification
118
- task_id: binary_classification
119
- splits:
120
- train_split: train
121
- eval_split: test
122
- col_mapping:
123
- text: text
124
- label: target
125
- metrics:
126
- - type: accuracy
127
- name: Accuracy
128
- - type: f1
129
- name: F1 binary
130
- args:
131
- average: binary
132
- - type: precision
133
- name: Precision macro
134
- args:
135
- average: macro
136
- - type: precision
137
- name: Precision micro
138
- args:
139
- average: micro
140
- - type: precision
141
- name: Precision weighted
142
- args:
143
- average: weighted
144
- - type: recall
145
- name: Recall macro
146
- args:
147
- average: macro
148
- - type: recall
149
- name: Recall micro
150
- args:
151
- average: micro
152
- - type: recall
153
- name: Recall weighted
154
- args:
155
- average: weighted
156
- - config: offensive
157
- task: text-classification
158
- task_id: binary_classification
159
- splits:
160
- train_split: train
161
- eval_split: test
162
- col_mapping:
163
- text: text
164
- label: target
165
- metrics:
166
- - type: accuracy
167
- name: Accuracy
168
- - type: f1
169
- name: F1 binary
170
- args:
171
- average: binary
172
- - type: precision
173
- name: Precision macro
174
- args:
175
- average: macro
176
- - type: precision
177
- name: Precision micro
178
- args:
179
- average: micro
180
- - type: precision
181
- name: Precision weighted
182
- args:
183
- average: weighted
184
- - type: recall
185
- name: Recall macro
186
- args:
187
- average: macro
188
- - type: recall
189
- name: Recall micro
190
- args:
191
- average: micro
192
- - type: recall
193
- name: Recall weighted
194
- args:
195
- average: weighted
196
- - config: sentiment
197
- task: text-classification
198
- task_id: multi_class_classification
199
- splits:
200
- train_split: train
201
- eval_split: test
202
- col_mapping:
203
- text: text
204
- label: target
205
- metrics:
206
- - type: accuracy
207
- name: Accuracy
208
- - type: f1
209
- name: F1 macro
210
- args:
211
- average: macro
212
- - type: f1
213
- name: F1 micro
214
- args:
215
- average: micro
216
- - type: f1
217
- name: F1 weighted
218
- args:
219
- average: weighted
220
- - type: precision
221
- name: Precision macro
222
- args:
223
- average: macro
224
- - type: precision
225
- name: Precision micro
226
- args:
227
- average: micro
228
- - type: precision
229
- name: Precision weighted
230
- args:
231
- average: weighted
232
- - type: recall
233
- name: Recall macro
234
- args:
235
- average: macro
236
- - type: recall
237
- name: Recall micro
238
- args:
239
- average: micro
240
- - type: recall
241
- name: Recall weighted
242
- args:
243
- average: weighted
244
  configs:
245
  - emoji
246
  - emotion
@@ -262,26 +45,26 @@ dataset_info:
262
  dtype:
263
  class_label:
264
  names:
265
- 0: ❀
266
- 1: 😍
267
- 2: πŸ˜‚
268
- 3: πŸ’•
269
- 4: πŸ”₯
270
- 5: 😊
271
- 6: 😎
272
- 7: ✨
273
- 8: πŸ’™
274
- 9: 😘
275
- 10: πŸ“·
276
- 11: πŸ‡ΊπŸ‡Έ
277
- 12: β˜€
278
- 13: πŸ’œ
279
- 14: πŸ˜‰
280
- 15: πŸ’―
281
- 16: 😁
282
- 17: πŸŽ„
283
- 18: πŸ“Έ
284
- 19: 😜
285
  splits:
286
  - name: train
287
  num_bytes: 3803187
@@ -302,10 +85,10 @@ dataset_info:
302
  dtype:
303
  class_label:
304
  names:
305
- 0: anger
306
- 1: joy
307
- 2: optimism
308
- 3: sadness
309
  splits:
310
  - name: train
311
  num_bytes: 338875
@@ -326,8 +109,8 @@ dataset_info:
326
  dtype:
327
  class_label:
328
  names:
329
- 0: non-hate
330
- 1: hate
331
  splits:
332
  - name: train
333
  num_bytes: 1223654
@@ -348,8 +131,8 @@ dataset_info:
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  dtype:
349
  class_label:
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  names:
351
- 0: non_irony
352
- 1: irony
353
  splits:
354
  - name: train
355
  num_bytes: 259191
@@ -370,8 +153,8 @@ dataset_info:
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  dtype:
371
  class_label:
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  names:
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- 0: non-offensive
374
- 1: offensive
375
  splits:
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  - name: train
377
  num_bytes: 1648069
@@ -392,9 +175,9 @@ dataset_info:
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  dtype:
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  class_label:
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  names:
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- 0: negative
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- 1: neutral
397
- 2: positive
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  splits:
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  - name: train
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  num_bytes: 5425142
@@ -415,9 +198,9 @@ dataset_info:
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  dtype:
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  class_label:
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  names:
418
- 0: none
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- 1: against
420
- 2: favor
421
  splits:
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  - name: train
423
  num_bytes: 68698
@@ -438,9 +221,9 @@ dataset_info:
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  dtype:
439
  class_label:
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  names:
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- 0: none
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- 1: against
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- 2: favor
444
  splits:
445
  - name: train
446
  num_bytes: 54779
@@ -461,9 +244,9 @@ dataset_info:
461
  dtype:
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  class_label:
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  names:
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- 0: none
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- 1: against
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- 2: favor
467
  splits:
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  - name: train
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  num_bytes: 40253
@@ -484,9 +267,9 @@ dataset_info:
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  dtype:
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  class_label:
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  names:
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- 0: none
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- 1: against
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- 2: favor
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  splits:
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  - name: train
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  num_bytes: 70513
@@ -507,9 +290,9 @@ dataset_info:
507
  dtype:
508
  class_label:
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  names:
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- 0: none
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- 1: against
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- 2: favor
513
  splits:
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  - name: train
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  num_bytes: 69600
@@ -522,6 +305,223 @@ dataset_info:
522
  num_examples: 69
523
  download_size: 103745
524
  dataset_size: 111627
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
525
  ---
526
 
527
  # Dataset Card for tweet_eval
 
24
  - sentiment-classification
25
  paperswithcode_id: tweeteval
26
  pretty_name: TweetEval
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
27
  configs:
28
  - emoji
29
  - emotion
 
45
  dtype:
46
  class_label:
47
  names:
48
+ '0': ❀
49
+ '1': 😍
50
+ '2': πŸ˜‚
51
+ '3': πŸ’•
52
+ '4': πŸ”₯
53
+ '5': 😊
54
+ '6': 😎
55
+ '7': ✨
56
+ '8': πŸ’™
57
+ '9': 😘
58
+ '10': πŸ“·
59
+ '11': πŸ‡ΊπŸ‡Έ
60
+ '12': β˜€
61
+ '13': πŸ’œ
62
+ '14': πŸ˜‰
63
+ '15': πŸ’―
64
+ '16': 😁
65
+ '17': πŸŽ„
66
+ '18': πŸ“Έ
67
+ '19': 😜
68
  splits:
69
  - name: train
70
  num_bytes: 3803187
 
85
  dtype:
86
  class_label:
87
  names:
88
+ '0': anger
89
+ '1': joy
90
+ '2': optimism
91
+ '3': sadness
92
  splits:
93
  - name: train
94
  num_bytes: 338875
 
109
  dtype:
110
  class_label:
111
  names:
112
+ '0': non-hate
113
+ '1': hate
114
  splits:
115
  - name: train
116
  num_bytes: 1223654
 
131
  dtype:
132
  class_label:
133
  names:
134
+ '0': non_irony
135
+ '1': irony
136
  splits:
137
  - name: train
138
  num_bytes: 259191
 
153
  dtype:
154
  class_label:
155
  names:
156
+ '0': non-offensive
157
+ '1': offensive
158
  splits:
159
  - name: train
160
  num_bytes: 1648069
 
175
  dtype:
176
  class_label:
177
  names:
178
+ '0': negative
179
+ '1': neutral
180
+ '2': positive
181
  splits:
182
  - name: train
183
  num_bytes: 5425142
 
198
  dtype:
199
  class_label:
200
  names:
201
+ '0': none
202
+ '1': against
203
+ '2': favor
204
  splits:
205
  - name: train
206
  num_bytes: 68698
 
221
  dtype:
222
  class_label:
223
  names:
224
+ '0': none
225
+ '1': against
226
+ '2': favor
227
  splits:
228
  - name: train
229
  num_bytes: 54779
 
244
  dtype:
245
  class_label:
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  names:
247
+ '0': none
248
+ '1': against
249
+ '2': favor
250
  splits:
251
  - name: train
252
  num_bytes: 40253
 
267
  dtype:
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  class_label:
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  names:
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+ '0': none
271
+ '1': against
272
+ '2': favor
273
  splits:
274
  - name: train
275
  num_bytes: 70513
 
290
  dtype:
291
  class_label:
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  names:
293
+ '0': none
294
+ '1': against
295
+ '2': favor
296
  splits:
297
  - name: train
298
  num_bytes: 69600
 
305
  num_examples: 69
306
  download_size: 103745
307
  dataset_size: 111627
308
+ train-eval-index:
309
+ - config: emotion
310
+ task: text-classification
311
+ task_id: multi_class_classification
312
+ splits:
313
+ train_split: train
314
+ eval_split: test
315
+ col_mapping:
316
+ text: text
317
+ label: target
318
+ metrics:
319
+ - type: accuracy
320
+ name: Accuracy
321
+ - type: f1
322
+ name: F1 macro
323
+ args:
324
+ average: macro
325
+ - type: f1
326
+ name: F1 micro
327
+ args:
328
+ average: micro
329
+ - type: f1
330
+ name: F1 weighted
331
+ args:
332
+ average: weighted
333
+ - type: precision
334
+ name: Precision macro
335
+ args:
336
+ average: macro
337
+ - type: precision
338
+ name: Precision micro
339
+ args:
340
+ average: micro
341
+ - type: precision
342
+ name: Precision weighted
343
+ args:
344
+ average: weighted
345
+ - type: recall
346
+ name: Recall macro
347
+ args:
348
+ average: macro
349
+ - type: recall
350
+ name: Recall micro
351
+ args:
352
+ average: micro
353
+ - type: recall
354
+ name: Recall weighted
355
+ args:
356
+ average: weighted
357
+ - config: hate
358
+ task: text-classification
359
+ task_id: binary_classification
360
+ splits:
361
+ train_split: train
362
+ eval_split: test
363
+ col_mapping:
364
+ text: text
365
+ label: target
366
+ metrics:
367
+ - type: accuracy
368
+ name: Accuracy
369
+ - type: f1
370
+ name: F1 binary
371
+ args:
372
+ average: binary
373
+ - type: precision
374
+ name: Precision macro
375
+ args:
376
+ average: macro
377
+ - type: precision
378
+ name: Precision micro
379
+ args:
380
+ average: micro
381
+ - type: precision
382
+ name: Precision weighted
383
+ args:
384
+ average: weighted
385
+ - type: recall
386
+ name: Recall macro
387
+ args:
388
+ average: macro
389
+ - type: recall
390
+ name: Recall micro
391
+ args:
392
+ average: micro
393
+ - type: recall
394
+ name: Recall weighted
395
+ args:
396
+ average: weighted
397
+ - config: irony
398
+ task: text-classification
399
+ task_id: binary_classification
400
+ splits:
401
+ train_split: train
402
+ eval_split: test
403
+ col_mapping:
404
+ text: text
405
+ label: target
406
+ metrics:
407
+ - type: accuracy
408
+ name: Accuracy
409
+ - type: f1
410
+ name: F1 binary
411
+ args:
412
+ average: binary
413
+ - type: precision
414
+ name: Precision macro
415
+ args:
416
+ average: macro
417
+ - type: precision
418
+ name: Precision micro
419
+ args:
420
+ average: micro
421
+ - type: precision
422
+ name: Precision weighted
423
+ args:
424
+ average: weighted
425
+ - type: recall
426
+ name: Recall macro
427
+ args:
428
+ average: macro
429
+ - type: recall
430
+ name: Recall micro
431
+ args:
432
+ average: micro
433
+ - type: recall
434
+ name: Recall weighted
435
+ args:
436
+ average: weighted
437
+ - config: offensive
438
+ task: text-classification
439
+ task_id: binary_classification
440
+ splits:
441
+ train_split: train
442
+ eval_split: test
443
+ col_mapping:
444
+ text: text
445
+ label: target
446
+ metrics:
447
+ - type: accuracy
448
+ name: Accuracy
449
+ - type: f1
450
+ name: F1 binary
451
+ args:
452
+ average: binary
453
+ - type: precision
454
+ name: Precision macro
455
+ args:
456
+ average: macro
457
+ - type: precision
458
+ name: Precision micro
459
+ args:
460
+ average: micro
461
+ - type: precision
462
+ name: Precision weighted
463
+ args:
464
+ average: weighted
465
+ - type: recall
466
+ name: Recall macro
467
+ args:
468
+ average: macro
469
+ - type: recall
470
+ name: Recall micro
471
+ args:
472
+ average: micro
473
+ - type: recall
474
+ name: Recall weighted
475
+ args:
476
+ average: weighted
477
+ - config: sentiment
478
+ task: text-classification
479
+ task_id: multi_class_classification
480
+ splits:
481
+ train_split: train
482
+ eval_split: test
483
+ col_mapping:
484
+ text: text
485
+ label: target
486
+ metrics:
487
+ - type: accuracy
488
+ name: Accuracy
489
+ - type: f1
490
+ name: F1 macro
491
+ args:
492
+ average: macro
493
+ - type: f1
494
+ name: F1 micro
495
+ args:
496
+ average: micro
497
+ - type: f1
498
+ name: F1 weighted
499
+ args:
500
+ average: weighted
501
+ - type: precision
502
+ name: Precision macro
503
+ args:
504
+ average: macro
505
+ - type: precision
506
+ name: Precision micro
507
+ args:
508
+ average: micro
509
+ - type: precision
510
+ name: Precision weighted
511
+ args:
512
+ average: weighted
513
+ - type: recall
514
+ name: Recall macro
515
+ args:
516
+ average: macro
517
+ - type: recall
518
+ name: Recall micro
519
+ args:
520
+ average: micro
521
+ - type: recall
522
+ name: Recall weighted
523
+ args:
524
+ average: weighted
525
  ---
526
 
527
  # Dataset Card for tweet_eval