albertvillanova HF staff commited on
Commit
cd8d496
1 Parent(s): 7e9086d

Replace YAML keys from int to str (#4)

Browse files

- Replace YAML keys from int to str (9232210b7458c437bc7004a8ef3381fe5c0ba0a2)

Files changed (1) hide show
  1. README.md +505 -505
README.md CHANGED
@@ -1,5 +1,4 @@
1
  ---
2
- pretty_name: MultiEURLEX
3
  annotations_creators:
4
  - found
5
  language_creators:
@@ -41,6 +40,7 @@ task_categories:
41
  task_ids:
42
  - multi-label-classification
43
  - topic-classification
 
44
  dataset_info:
45
  - config_name: en
46
  features:
@@ -52,27 +52,27 @@ dataset_info:
52
  sequence:
53
  class_label:
54
  names:
55
- 0: '100149'
56
- 1: '100160'
57
- 2: '100148'
58
- 3: '100147'
59
- 4: '100152'
60
- 5: '100143'
61
- 6: '100156'
62
- 7: '100158'
63
- 8: '100154'
64
- 9: '100153'
65
- 10: '100142'
66
- 11: '100145'
67
- 12: '100150'
68
- 13: '100162'
69
- 14: '100159'
70
- 15: '100144'
71
- 16: '100151'
72
- 17: '100157'
73
- 18: '100161'
74
- 19: '100146'
75
- 20: '100155'
76
  splits:
77
  - name: train
78
  num_bytes: 389250183
@@ -95,27 +95,27 @@ dataset_info:
95
  sequence:
96
  class_label:
97
  names:
98
- 0: '100149'
99
- 1: '100160'
100
- 2: '100148'
101
- 3: '100147'
102
- 4: '100152'
103
- 5: '100143'
104
- 6: '100156'
105
- 7: '100158'
106
- 8: '100154'
107
- 9: '100153'
108
- 10: '100142'
109
- 11: '100145'
110
- 12: '100150'
111
- 13: '100162'
112
- 14: '100159'
113
- 15: '100144'
114
- 16: '100151'
115
- 17: '100157'
116
- 18: '100161'
117
- 19: '100146'
118
- 20: '100155'
119
  splits:
120
  - name: train
121
  num_bytes: 395774777
@@ -138,27 +138,27 @@ dataset_info:
138
  sequence:
139
  class_label:
140
  names:
141
- 0: '100149'
142
- 1: '100160'
143
- 2: '100148'
144
- 3: '100147'
145
- 4: '100152'
146
- 5: '100143'
147
- 6: '100156'
148
- 7: '100158'
149
- 8: '100154'
150
- 9: '100153'
151
- 10: '100142'
152
- 11: '100145'
153
- 12: '100150'
154
- 13: '100162'
155
- 14: '100159'
156
- 15: '100144'
157
- 16: '100151'
158
- 17: '100157'
159
- 18: '100161'
160
- 19: '100146'
161
- 20: '100155'
162
  splits:
163
  - name: train
164
  num_bytes: 425489905
@@ -181,27 +181,27 @@ dataset_info:
181
  sequence:
182
  class_label:
183
  names:
184
- 0: '100149'
185
- 1: '100160'
186
- 2: '100148'
187
- 3: '100147'
188
- 4: '100152'
189
- 5: '100143'
190
- 6: '100156'
191
- 7: '100158'
192
- 8: '100154'
193
- 9: '100153'
194
- 10: '100142'
195
- 11: '100145'
196
- 12: '100150'
197
- 13: '100162'
198
- 14: '100159'
199
- 15: '100144'
200
- 16: '100151'
201
- 17: '100157'
202
- 18: '100161'
203
- 19: '100146'
204
- 20: '100155'
205
  splits:
206
  - name: train
207
  num_bytes: 430232783
@@ -224,27 +224,27 @@ dataset_info:
224
  sequence:
225
  class_label:
226
  names:
227
- 0: '100149'
228
- 1: '100160'
229
- 2: '100148'
230
- 3: '100147'
231
- 4: '100152'
232
- 5: '100143'
233
- 6: '100156'
234
- 7: '100158'
235
- 8: '100154'
236
- 9: '100153'
237
- 10: '100142'
238
- 11: '100145'
239
- 12: '100150'
240
- 13: '100162'
241
- 14: '100159'
242
- 15: '100144'
243
- 16: '100151'
244
- 17: '100157'
245
- 18: '100161'
246
- 19: '100146'
247
- 20: '100155'
248
  splits:
249
  - name: train
250
  num_bytes: 329071297
@@ -267,27 +267,27 @@ dataset_info:
267
  sequence:
268
  class_label:
269
  names:
270
- 0: '100149'
271
- 1: '100160'
272
- 2: '100148'
273
- 3: '100147'
274
- 4: '100152'
275
- 5: '100143'
276
- 6: '100156'
277
- 7: '100158'
278
- 8: '100154'
279
- 9: '100153'
280
- 10: '100142'
281
- 11: '100145'
282
- 12: '100150'
283
- 13: '100162'
284
- 14: '100159'
285
- 15: '100144'
286
- 16: '100151'
287
- 17: '100157'
288
- 18: '100161'
289
- 19: '100146'
290
- 20: '100155'
291
  splits:
292
  - name: train
293
  num_bytes: 273160256
@@ -310,27 +310,27 @@ dataset_info:
310
  sequence:
311
  class_label:
312
  names:
313
- 0: '100149'
314
- 1: '100160'
315
- 2: '100148'
316
- 3: '100147'
317
- 4: '100152'
318
- 5: '100143'
319
- 6: '100156'
320
- 7: '100158'
321
- 8: '100154'
322
- 9: '100153'
323
- 10: '100142'
324
- 11: '100145'
325
- 12: '100150'
326
- 13: '100162'
327
- 14: '100159'
328
- 15: '100144'
329
- 16: '100151'
330
- 17: '100157'
331
- 18: '100161'
332
- 19: '100146'
333
- 20: '100155'
334
  splits:
335
  - name: train
336
  num_bytes: 189826410
@@ -353,27 +353,27 @@ dataset_info:
353
  sequence:
354
  class_label:
355
  names:
356
- 0: '100149'
357
- 1: '100160'
358
- 2: '100148'
359
- 3: '100147'
360
- 4: '100152'
361
- 5: '100143'
362
- 6: '100156'
363
- 7: '100158'
364
- 8: '100154'
365
- 9: '100153'
366
- 10: '100142'
367
- 11: '100145'
368
- 12: '100150'
369
- 13: '100162'
370
- 14: '100159'
371
- 15: '100144'
372
- 16: '100151'
373
- 17: '100157'
374
- 18: '100161'
375
- 19: '100146'
376
- 20: '100155'
377
  splits:
378
  - name: train
379
  num_bytes: 80808173
@@ -396,27 +396,27 @@ dataset_info:
396
  sequence:
397
  class_label:
398
  names:
399
- 0: '100149'
400
- 1: '100160'
401
- 2: '100148'
402
- 3: '100147'
403
- 4: '100152'
404
- 5: '100143'
405
- 6: '100156'
406
- 7: '100158'
407
- 8: '100154'
408
- 9: '100153'
409
- 10: '100142'
410
- 11: '100145'
411
- 12: '100150'
412
- 13: '100162'
413
- 14: '100159'
414
- 15: '100144'
415
- 16: '100151'
416
- 17: '100157'
417
- 18: '100161'
418
- 19: '100146'
419
- 20: '100155'
420
  splits:
421
  - name: train
422
  num_bytes: 202211478
@@ -439,27 +439,27 @@ dataset_info:
439
  sequence:
440
  class_label:
441
  names:
442
- 0: '100149'
443
- 1: '100160'
444
- 2: '100148'
445
- 3: '100147'
446
- 4: '100152'
447
- 5: '100143'
448
- 6: '100156'
449
- 7: '100158'
450
- 8: '100154'
451
- 9: '100153'
452
- 10: '100142'
453
- 11: '100145'
454
- 12: '100150'
455
- 13: '100162'
456
- 14: '100159'
457
- 15: '100144'
458
- 16: '100151'
459
- 17: '100157'
460
- 18: '100161'
461
- 19: '100146'
462
- 20: '100155'
463
  splits:
464
  - name: train
465
  num_bytes: 188126769
@@ -482,27 +482,27 @@ dataset_info:
482
  sequence:
483
  class_label:
484
  names:
485
- 0: '100149'
486
- 1: '100160'
487
- 2: '100148'
488
- 3: '100147'
489
- 4: '100152'
490
- 5: '100143'
491
- 6: '100156'
492
- 7: '100158'
493
- 8: '100154'
494
- 9: '100153'
495
- 10: '100142'
496
- 11: '100145'
497
- 12: '100150'
498
- 13: '100162'
499
- 14: '100159'
500
- 15: '100144'
501
- 16: '100151'
502
- 17: '100157'
503
- 18: '100161'
504
- 19: '100146'
505
- 20: '100155'
506
  splits:
507
  - name: train
508
  num_bytes: 170800933
@@ -525,27 +525,27 @@ dataset_info:
525
  sequence:
526
  class_label:
527
  names:
528
- 0: '100149'
529
- 1: '100160'
530
- 2: '100148'
531
- 3: '100147'
532
- 4: '100152'
533
- 5: '100143'
534
- 6: '100156'
535
- 7: '100158'
536
- 8: '100154'
537
- 9: '100153'
538
- 10: '100142'
539
- 11: '100145'
540
- 12: '100150'
541
- 13: '100162'
542
- 14: '100159'
543
- 15: '100144'
544
- 16: '100151'
545
- 17: '100157'
546
- 18: '100161'
547
- 19: '100146'
548
- 20: '100155'
549
  splits:
550
  - name: train
551
  num_bytes: 433955383
@@ -568,27 +568,27 @@ dataset_info:
568
  sequence:
569
  class_label:
570
  names:
571
- 0: '100149'
572
- 1: '100160'
573
- 2: '100148'
574
- 3: '100147'
575
- 4: '100152'
576
- 5: '100143'
577
- 6: '100156'
578
- 7: '100158'
579
- 8: '100154'
580
- 9: '100153'
581
- 10: '100142'
582
- 11: '100145'
583
- 12: '100150'
584
- 13: '100162'
585
- 14: '100159'
586
- 15: '100144'
587
- 16: '100151'
588
- 17: '100157'
589
- 18: '100161'
590
- 19: '100146'
591
- 20: '100155'
592
  splits:
593
  - name: train
594
  num_bytes: 442358905
@@ -611,27 +611,27 @@ dataset_info:
611
  sequence:
612
  class_label:
613
  names:
614
- 0: '100149'
615
- 1: '100160'
616
- 2: '100148'
617
- 3: '100147'
618
- 4: '100152'
619
- 5: '100143'
620
- 6: '100156'
621
- 7: '100158'
622
- 8: '100154'
623
- 9: '100153'
624
- 10: '100142'
625
- 11: '100145'
626
- 12: '100150'
627
- 13: '100162'
628
- 14: '100159'
629
- 15: '100144'
630
- 16: '100151'
631
- 17: '100157'
632
- 18: '100161'
633
- 19: '100146'
634
- 20: '100155'
635
  splits:
636
  - name: train
637
  num_bytes: 429495813
@@ -654,27 +654,27 @@ dataset_info:
654
  sequence:
655
  class_label:
656
  names:
657
- 0: '100149'
658
- 1: '100160'
659
- 2: '100148'
660
- 3: '100147'
661
- 4: '100152'
662
- 5: '100143'
663
- 6: '100156'
664
- 7: '100158'
665
- 8: '100154'
666
- 9: '100153'
667
- 10: '100142'
668
- 11: '100145'
669
- 12: '100150'
670
- 13: '100162'
671
- 14: '100159'
672
- 15: '100144'
673
- 16: '100151'
674
- 17: '100157'
675
- 18: '100161'
676
- 19: '100146'
677
- 20: '100155'
678
  splits:
679
  - name: train
680
  num_bytes: 419281927
@@ -697,27 +697,27 @@ dataset_info:
697
  sequence:
698
  class_label:
699
  names:
700
- 0: '100149'
701
- 1: '100160'
702
- 2: '100148'
703
- 3: '100147'
704
- 4: '100152'
705
- 5: '100143'
706
- 6: '100156'
707
- 7: '100158'
708
- 8: '100154'
709
- 9: '100153'
710
- 10: '100142'
711
- 11: '100145'
712
- 12: '100150'
713
- 13: '100162'
714
- 14: '100159'
715
- 15: '100144'
716
- 16: '100151'
717
- 17: '100157'
718
- 18: '100161'
719
- 19: '100146'
720
- 20: '100155'
721
  splits:
722
  - name: train
723
  num_bytes: 164966676
@@ -740,27 +740,27 @@ dataset_info:
740
  sequence:
741
  class_label:
742
  names:
743
- 0: '100149'
744
- 1: '100160'
745
- 2: '100148'
746
- 3: '100147'
747
- 4: '100152'
748
- 5: '100143'
749
- 6: '100156'
750
- 7: '100158'
751
- 8: '100154'
752
- 9: '100153'
753
- 10: '100142'
754
- 11: '100145'
755
- 12: '100150'
756
- 13: '100162'
757
- 14: '100159'
758
- 15: '100144'
759
- 16: '100151'
760
- 17: '100157'
761
- 18: '100161'
762
- 19: '100146'
763
- 20: '100155'
764
  splits:
765
  - name: train
766
  num_bytes: 173878703
@@ -783,27 +783,27 @@ dataset_info:
783
  sequence:
784
  class_label:
785
  names:
786
- 0: '100149'
787
- 1: '100160'
788
- 2: '100148'
789
- 3: '100147'
790
- 4: '100152'
791
- 5: '100143'
792
- 6: '100156'
793
- 7: '100158'
794
- 8: '100154'
795
- 9: '100153'
796
- 10: '100142'
797
- 11: '100145'
798
- 12: '100150'
799
- 13: '100162'
800
- 14: '100159'
801
- 15: '100144'
802
- 16: '100151'
803
- 17: '100157'
804
- 18: '100161'
805
- 19: '100146'
806
- 20: '100155'
807
  splits:
808
  - name: train
809
  num_bytes: 336145949
@@ -826,27 +826,27 @@ dataset_info:
826
  sequence:
827
  class_label:
828
  names:
829
- 0: '100149'
830
- 1: '100160'
831
- 2: '100148'
832
- 3: '100147'
833
- 4: '100152'
834
- 5: '100143'
835
- 6: '100156'
836
- 7: '100158'
837
- 8: '100154'
838
- 9: '100153'
839
- 10: '100142'
840
- 11: '100145'
841
- 12: '100150'
842
- 13: '100162'
843
- 14: '100159'
844
- 15: '100144'
845
- 16: '100151'
846
- 17: '100157'
847
- 18: '100161'
848
- 19: '100146'
849
- 20: '100155'
850
  splits:
851
  - name: train
852
  num_bytes: 208805862
@@ -869,27 +869,27 @@ dataset_info:
869
  sequence:
870
  class_label:
871
  names:
872
- 0: '100149'
873
- 1: '100160'
874
- 2: '100148'
875
- 3: '100147'
876
- 4: '100152'
877
- 5: '100143'
878
- 6: '100156'
879
- 7: '100158'
880
- 8: '100154'
881
- 9: '100153'
882
- 10: '100142'
883
- 11: '100145'
884
- 12: '100150'
885
- 13: '100162'
886
- 14: '100159'
887
- 15: '100144'
888
- 16: '100151'
889
- 17: '100157'
890
- 18: '100161'
891
- 19: '100146'
892
- 20: '100155'
893
  splits:
894
  - name: train
895
  num_bytes: 185211691
@@ -912,27 +912,27 @@ dataset_info:
912
  sequence:
913
  class_label:
914
  names:
915
- 0: '100149'
916
- 1: '100160'
917
- 2: '100148'
918
- 3: '100147'
919
- 4: '100152'
920
- 5: '100143'
921
- 6: '100156'
922
- 7: '100158'
923
- 8: '100154'
924
- 9: '100153'
925
- 10: '100142'
926
- 11: '100145'
927
- 12: '100150'
928
- 13: '100162'
929
- 14: '100159'
930
- 15: '100144'
931
- 16: '100151'
932
- 17: '100157'
933
- 18: '100161'
934
- 19: '100146'
935
- 20: '100155'
936
  splits:
937
  - name: train
938
  num_bytes: 186396252
@@ -955,27 +955,27 @@ dataset_info:
955
  sequence:
956
  class_label:
957
  names:
958
- 0: '100149'
959
- 1: '100160'
960
- 2: '100148'
961
- 3: '100147'
962
- 4: '100152'
963
- 5: '100143'
964
- 6: '100156'
965
- 7: '100158'
966
- 8: '100154'
967
- 9: '100153'
968
- 10: '100142'
969
- 11: '100145'
970
- 12: '100150'
971
- 13: '100162'
972
- 14: '100159'
973
- 15: '100144'
974
- 16: '100151'
975
- 17: '100157'
976
- 18: '100161'
977
- 19: '100146'
978
- 20: '100155'
979
  splits:
980
  - name: train
981
  num_bytes: 768224743
@@ -998,27 +998,27 @@ dataset_info:
998
  sequence:
999
  class_label:
1000
  names:
1001
- 0: '100149'
1002
- 1: '100160'
1003
- 2: '100148'
1004
- 3: '100147'
1005
- 4: '100152'
1006
- 5: '100143'
1007
- 6: '100156'
1008
- 7: '100158'
1009
- 8: '100154'
1010
- 9: '100153'
1011
- 10: '100142'
1012
- 11: '100145'
1013
- 12: '100150'
1014
- 13: '100162'
1015
- 14: '100159'
1016
- 15: '100144'
1017
- 16: '100151'
1018
- 17: '100157'
1019
- 18: '100161'
1020
- 19: '100146'
1021
- 20: '100155'
1022
  splits:
1023
  - name: train
1024
  num_bytes: 179866781
@@ -1066,27 +1066,27 @@ dataset_info:
1066
  sequence:
1067
  class_label:
1068
  names:
1069
- 0: '100149'
1070
- 1: '100160'
1071
- 2: '100148'
1072
- 3: '100147'
1073
- 4: '100152'
1074
- 5: '100143'
1075
- 6: '100156'
1076
- 7: '100158'
1077
- 8: '100154'
1078
- 9: '100153'
1079
- 10: '100142'
1080
- 11: '100145'
1081
- 12: '100150'
1082
- 13: '100162'
1083
- 14: '100159'
1084
- 15: '100144'
1085
- 16: '100151'
1086
- 17: '100157'
1087
- 18: '100161'
1088
- 19: '100146'
1089
- 20: '100155'
1090
  splits:
1091
  - name: train
1092
  num_bytes: 6971500859
 
1
  ---
 
2
  annotations_creators:
3
  - found
4
  language_creators:
 
40
  task_ids:
41
  - multi-label-classification
42
  - topic-classification
43
+ pretty_name: MultiEURLEX
44
  dataset_info:
45
  - config_name: en
46
  features:
 
52
  sequence:
53
  class_label:
54
  names:
55
+ '0': '100149'
56
+ '1': '100160'
57
+ '2': '100148'
58
+ '3': '100147'
59
+ '4': '100152'
60
+ '5': '100143'
61
+ '6': '100156'
62
+ '7': '100158'
63
+ '8': '100154'
64
+ '9': '100153'
65
+ '10': '100142'
66
+ '11': '100145'
67
+ '12': '100150'
68
+ '13': '100162'
69
+ '14': '100159'
70
+ '15': '100144'
71
+ '16': '100151'
72
+ '17': '100157'
73
+ '18': '100161'
74
+ '19': '100146'
75
+ '20': '100155'
76
  splits:
77
  - name: train
78
  num_bytes: 389250183
 
95
  sequence:
96
  class_label:
97
  names:
98
+ '0': '100149'
99
+ '1': '100160'
100
+ '2': '100148'
101
+ '3': '100147'
102
+ '4': '100152'
103
+ '5': '100143'
104
+ '6': '100156'
105
+ '7': '100158'
106
+ '8': '100154'
107
+ '9': '100153'
108
+ '10': '100142'
109
+ '11': '100145'
110
+ '12': '100150'
111
+ '13': '100162'
112
+ '14': '100159'
113
+ '15': '100144'
114
+ '16': '100151'
115
+ '17': '100157'
116
+ '18': '100161'
117
+ '19': '100146'
118
+ '20': '100155'
119
  splits:
120
  - name: train
121
  num_bytes: 395774777
 
138
  sequence:
139
  class_label:
140
  names:
141
+ '0': '100149'
142
+ '1': '100160'
143
+ '2': '100148'
144
+ '3': '100147'
145
+ '4': '100152'
146
+ '5': '100143'
147
+ '6': '100156'
148
+ '7': '100158'
149
+ '8': '100154'
150
+ '9': '100153'
151
+ '10': '100142'
152
+ '11': '100145'
153
+ '12': '100150'
154
+ '13': '100162'
155
+ '14': '100159'
156
+ '15': '100144'
157
+ '16': '100151'
158
+ '17': '100157'
159
+ '18': '100161'
160
+ '19': '100146'
161
+ '20': '100155'
162
  splits:
163
  - name: train
164
  num_bytes: 425489905
 
181
  sequence:
182
  class_label:
183
  names:
184
+ '0': '100149'
185
+ '1': '100160'
186
+ '2': '100148'
187
+ '3': '100147'
188
+ '4': '100152'
189
+ '5': '100143'
190
+ '6': '100156'
191
+ '7': '100158'
192
+ '8': '100154'
193
+ '9': '100153'
194
+ '10': '100142'
195
+ '11': '100145'
196
+ '12': '100150'
197
+ '13': '100162'
198
+ '14': '100159'
199
+ '15': '100144'
200
+ '16': '100151'
201
+ '17': '100157'
202
+ '18': '100161'
203
+ '19': '100146'
204
+ '20': '100155'
205
  splits:
206
  - name: train
207
  num_bytes: 430232783
 
224
  sequence:
225
  class_label:
226
  names:
227
+ '0': '100149'
228
+ '1': '100160'
229
+ '2': '100148'
230
+ '3': '100147'
231
+ '4': '100152'
232
+ '5': '100143'
233
+ '6': '100156'
234
+ '7': '100158'
235
+ '8': '100154'
236
+ '9': '100153'
237
+ '10': '100142'
238
+ '11': '100145'
239
+ '12': '100150'
240
+ '13': '100162'
241
+ '14': '100159'
242
+ '15': '100144'
243
+ '16': '100151'
244
+ '17': '100157'
245
+ '18': '100161'
246
+ '19': '100146'
247
+ '20': '100155'
248
  splits:
249
  - name: train
250
  num_bytes: 329071297
 
267
  sequence:
268
  class_label:
269
  names:
270
+ '0': '100149'
271
+ '1': '100160'
272
+ '2': '100148'
273
+ '3': '100147'
274
+ '4': '100152'
275
+ '5': '100143'
276
+ '6': '100156'
277
+ '7': '100158'
278
+ '8': '100154'
279
+ '9': '100153'
280
+ '10': '100142'
281
+ '11': '100145'
282
+ '12': '100150'
283
+ '13': '100162'
284
+ '14': '100159'
285
+ '15': '100144'
286
+ '16': '100151'
287
+ '17': '100157'
288
+ '18': '100161'
289
+ '19': '100146'
290
+ '20': '100155'
291
  splits:
292
  - name: train
293
  num_bytes: 273160256
 
310
  sequence:
311
  class_label:
312
  names:
313
+ '0': '100149'
314
+ '1': '100160'
315
+ '2': '100148'
316
+ '3': '100147'
317
+ '4': '100152'
318
+ '5': '100143'
319
+ '6': '100156'
320
+ '7': '100158'
321
+ '8': '100154'
322
+ '9': '100153'
323
+ '10': '100142'
324
+ '11': '100145'
325
+ '12': '100150'
326
+ '13': '100162'
327
+ '14': '100159'
328
+ '15': '100144'
329
+ '16': '100151'
330
+ '17': '100157'
331
+ '18': '100161'
332
+ '19': '100146'
333
+ '20': '100155'
334
  splits:
335
  - name: train
336
  num_bytes: 189826410
 
353
  sequence:
354
  class_label:
355
  names:
356
+ '0': '100149'
357
+ '1': '100160'
358
+ '2': '100148'
359
+ '3': '100147'
360
+ '4': '100152'
361
+ '5': '100143'
362
+ '6': '100156'
363
+ '7': '100158'
364
+ '8': '100154'
365
+ '9': '100153'
366
+ '10': '100142'
367
+ '11': '100145'
368
+ '12': '100150'
369
+ '13': '100162'
370
+ '14': '100159'
371
+ '15': '100144'
372
+ '16': '100151'
373
+ '17': '100157'
374
+ '18': '100161'
375
+ '19': '100146'
376
+ '20': '100155'
377
  splits:
378
  - name: train
379
  num_bytes: 80808173
 
396
  sequence:
397
  class_label:
398
  names:
399
+ '0': '100149'
400
+ '1': '100160'
401
+ '2': '100148'
402
+ '3': '100147'
403
+ '4': '100152'
404
+ '5': '100143'
405
+ '6': '100156'
406
+ '7': '100158'
407
+ '8': '100154'
408
+ '9': '100153'
409
+ '10': '100142'
410
+ '11': '100145'
411
+ '12': '100150'
412
+ '13': '100162'
413
+ '14': '100159'
414
+ '15': '100144'
415
+ '16': '100151'
416
+ '17': '100157'
417
+ '18': '100161'
418
+ '19': '100146'
419
+ '20': '100155'
420
  splits:
421
  - name: train
422
  num_bytes: 202211478
 
439
  sequence:
440
  class_label:
441
  names:
442
+ '0': '100149'
443
+ '1': '100160'
444
+ '2': '100148'
445
+ '3': '100147'
446
+ '4': '100152'
447
+ '5': '100143'
448
+ '6': '100156'
449
+ '7': '100158'
450
+ '8': '100154'
451
+ '9': '100153'
452
+ '10': '100142'
453
+ '11': '100145'
454
+ '12': '100150'
455
+ '13': '100162'
456
+ '14': '100159'
457
+ '15': '100144'
458
+ '16': '100151'
459
+ '17': '100157'
460
+ '18': '100161'
461
+ '19': '100146'
462
+ '20': '100155'
463
  splits:
464
  - name: train
465
  num_bytes: 188126769
 
482
  sequence:
483
  class_label:
484
  names:
485
+ '0': '100149'
486
+ '1': '100160'
487
+ '2': '100148'
488
+ '3': '100147'
489
+ '4': '100152'
490
+ '5': '100143'
491
+ '6': '100156'
492
+ '7': '100158'
493
+ '8': '100154'
494
+ '9': '100153'
495
+ '10': '100142'
496
+ '11': '100145'
497
+ '12': '100150'
498
+ '13': '100162'
499
+ '14': '100159'
500
+ '15': '100144'
501
+ '16': '100151'
502
+ '17': '100157'
503
+ '18': '100161'
504
+ '19': '100146'
505
+ '20': '100155'
506
  splits:
507
  - name: train
508
  num_bytes: 170800933
 
525
  sequence:
526
  class_label:
527
  names:
528
+ '0': '100149'
529
+ '1': '100160'
530
+ '2': '100148'
531
+ '3': '100147'
532
+ '4': '100152'
533
+ '5': '100143'
534
+ '6': '100156'
535
+ '7': '100158'
536
+ '8': '100154'
537
+ '9': '100153'
538
+ '10': '100142'
539
+ '11': '100145'
540
+ '12': '100150'
541
+ '13': '100162'
542
+ '14': '100159'
543
+ '15': '100144'
544
+ '16': '100151'
545
+ '17': '100157'
546
+ '18': '100161'
547
+ '19': '100146'
548
+ '20': '100155'
549
  splits:
550
  - name: train
551
  num_bytes: 433955383
 
568
  sequence:
569
  class_label:
570
  names:
571
+ '0': '100149'
572
+ '1': '100160'
573
+ '2': '100148'
574
+ '3': '100147'
575
+ '4': '100152'
576
+ '5': '100143'
577
+ '6': '100156'
578
+ '7': '100158'
579
+ '8': '100154'
580
+ '9': '100153'
581
+ '10': '100142'
582
+ '11': '100145'
583
+ '12': '100150'
584
+ '13': '100162'
585
+ '14': '100159'
586
+ '15': '100144'
587
+ '16': '100151'
588
+ '17': '100157'
589
+ '18': '100161'
590
+ '19': '100146'
591
+ '20': '100155'
592
  splits:
593
  - name: train
594
  num_bytes: 442358905
 
611
  sequence:
612
  class_label:
613
  names:
614
+ '0': '100149'
615
+ '1': '100160'
616
+ '2': '100148'
617
+ '3': '100147'
618
+ '4': '100152'
619
+ '5': '100143'
620
+ '6': '100156'
621
+ '7': '100158'
622
+ '8': '100154'
623
+ '9': '100153'
624
+ '10': '100142'
625
+ '11': '100145'
626
+ '12': '100150'
627
+ '13': '100162'
628
+ '14': '100159'
629
+ '15': '100144'
630
+ '16': '100151'
631
+ '17': '100157'
632
+ '18': '100161'
633
+ '19': '100146'
634
+ '20': '100155'
635
  splits:
636
  - name: train
637
  num_bytes: 429495813
 
654
  sequence:
655
  class_label:
656
  names:
657
+ '0': '100149'
658
+ '1': '100160'
659
+ '2': '100148'
660
+ '3': '100147'
661
+ '4': '100152'
662
+ '5': '100143'
663
+ '6': '100156'
664
+ '7': '100158'
665
+ '8': '100154'
666
+ '9': '100153'
667
+ '10': '100142'
668
+ '11': '100145'
669
+ '12': '100150'
670
+ '13': '100162'
671
+ '14': '100159'
672
+ '15': '100144'
673
+ '16': '100151'
674
+ '17': '100157'
675
+ '18': '100161'
676
+ '19': '100146'
677
+ '20': '100155'
678
  splits:
679
  - name: train
680
  num_bytes: 419281927
 
697
  sequence:
698
  class_label:
699
  names:
700
+ '0': '100149'
701
+ '1': '100160'
702
+ '2': '100148'
703
+ '3': '100147'
704
+ '4': '100152'
705
+ '5': '100143'
706
+ '6': '100156'
707
+ '7': '100158'
708
+ '8': '100154'
709
+ '9': '100153'
710
+ '10': '100142'
711
+ '11': '100145'
712
+ '12': '100150'
713
+ '13': '100162'
714
+ '14': '100159'
715
+ '15': '100144'
716
+ '16': '100151'
717
+ '17': '100157'
718
+ '18': '100161'
719
+ '19': '100146'
720
+ '20': '100155'
721
  splits:
722
  - name: train
723
  num_bytes: 164966676
 
740
  sequence:
741
  class_label:
742
  names:
743
+ '0': '100149'
744
+ '1': '100160'
745
+ '2': '100148'
746
+ '3': '100147'
747
+ '4': '100152'
748
+ '5': '100143'
749
+ '6': '100156'
750
+ '7': '100158'
751
+ '8': '100154'
752
+ '9': '100153'
753
+ '10': '100142'
754
+ '11': '100145'
755
+ '12': '100150'
756
+ '13': '100162'
757
+ '14': '100159'
758
+ '15': '100144'
759
+ '16': '100151'
760
+ '17': '100157'
761
+ '18': '100161'
762
+ '19': '100146'
763
+ '20': '100155'
764
  splits:
765
  - name: train
766
  num_bytes: 173878703
 
783
  sequence:
784
  class_label:
785
  names:
786
+ '0': '100149'
787
+ '1': '100160'
788
+ '2': '100148'
789
+ '3': '100147'
790
+ '4': '100152'
791
+ '5': '100143'
792
+ '6': '100156'
793
+ '7': '100158'
794
+ '8': '100154'
795
+ '9': '100153'
796
+ '10': '100142'
797
+ '11': '100145'
798
+ '12': '100150'
799
+ '13': '100162'
800
+ '14': '100159'
801
+ '15': '100144'
802
+ '16': '100151'
803
+ '17': '100157'
804
+ '18': '100161'
805
+ '19': '100146'
806
+ '20': '100155'
807
  splits:
808
  - name: train
809
  num_bytes: 336145949
 
826
  sequence:
827
  class_label:
828
  names:
829
+ '0': '100149'
830
+ '1': '100160'
831
+ '2': '100148'
832
+ '3': '100147'
833
+ '4': '100152'
834
+ '5': '100143'
835
+ '6': '100156'
836
+ '7': '100158'
837
+ '8': '100154'
838
+ '9': '100153'
839
+ '10': '100142'
840
+ '11': '100145'
841
+ '12': '100150'
842
+ '13': '100162'
843
+ '14': '100159'
844
+ '15': '100144'
845
+ '16': '100151'
846
+ '17': '100157'
847
+ '18': '100161'
848
+ '19': '100146'
849
+ '20': '100155'
850
  splits:
851
  - name: train
852
  num_bytes: 208805862
 
869
  sequence:
870
  class_label:
871
  names:
872
+ '0': '100149'
873
+ '1': '100160'
874
+ '2': '100148'
875
+ '3': '100147'
876
+ '4': '100152'
877
+ '5': '100143'
878
+ '6': '100156'
879
+ '7': '100158'
880
+ '8': '100154'
881
+ '9': '100153'
882
+ '10': '100142'
883
+ '11': '100145'
884
+ '12': '100150'
885
+ '13': '100162'
886
+ '14': '100159'
887
+ '15': '100144'
888
+ '16': '100151'
889
+ '17': '100157'
890
+ '18': '100161'
891
+ '19': '100146'
892
+ '20': '100155'
893
  splits:
894
  - name: train
895
  num_bytes: 185211691
 
912
  sequence:
913
  class_label:
914
  names:
915
+ '0': '100149'
916
+ '1': '100160'
917
+ '2': '100148'
918
+ '3': '100147'
919
+ '4': '100152'
920
+ '5': '100143'
921
+ '6': '100156'
922
+ '7': '100158'
923
+ '8': '100154'
924
+ '9': '100153'
925
+ '10': '100142'
926
+ '11': '100145'
927
+ '12': '100150'
928
+ '13': '100162'
929
+ '14': '100159'
930
+ '15': '100144'
931
+ '16': '100151'
932
+ '17': '100157'
933
+ '18': '100161'
934
+ '19': '100146'
935
+ '20': '100155'
936
  splits:
937
  - name: train
938
  num_bytes: 186396252
 
955
  sequence:
956
  class_label:
957
  names:
958
+ '0': '100149'
959
+ '1': '100160'
960
+ '2': '100148'
961
+ '3': '100147'
962
+ '4': '100152'
963
+ '5': '100143'
964
+ '6': '100156'
965
+ '7': '100158'
966
+ '8': '100154'
967
+ '9': '100153'
968
+ '10': '100142'
969
+ '11': '100145'
970
+ '12': '100150'
971
+ '13': '100162'
972
+ '14': '100159'
973
+ '15': '100144'
974
+ '16': '100151'
975
+ '17': '100157'
976
+ '18': '100161'
977
+ '19': '100146'
978
+ '20': '100155'
979
  splits:
980
  - name: train
981
  num_bytes: 768224743
 
998
  sequence:
999
  class_label:
1000
  names:
1001
+ '0': '100149'
1002
+ '1': '100160'
1003
+ '2': '100148'
1004
+ '3': '100147'
1005
+ '4': '100152'
1006
+ '5': '100143'
1007
+ '6': '100156'
1008
+ '7': '100158'
1009
+ '8': '100154'
1010
+ '9': '100153'
1011
+ '10': '100142'
1012
+ '11': '100145'
1013
+ '12': '100150'
1014
+ '13': '100162'
1015
+ '14': '100159'
1016
+ '15': '100144'
1017
+ '16': '100151'
1018
+ '17': '100157'
1019
+ '18': '100161'
1020
+ '19': '100146'
1021
+ '20': '100155'
1022
  splits:
1023
  - name: train
1024
  num_bytes: 179866781
 
1066
  sequence:
1067
  class_label:
1068
  names:
1069
+ '0': '100149'
1070
+ '1': '100160'
1071
+ '2': '100148'
1072
+ '3': '100147'
1073
+ '4': '100152'
1074
+ '5': '100143'
1075
+ '6': '100156'
1076
+ '7': '100158'
1077
+ '8': '100154'
1078
+ '9': '100153'
1079
+ '10': '100142'
1080
+ '11': '100145'
1081
+ '12': '100150'
1082
+ '13': '100162'
1083
+ '14': '100159'
1084
+ '15': '100144'
1085
+ '16': '100151'
1086
+ '17': '100157'
1087
+ '18': '100161'
1088
+ '19': '100146'
1089
+ '20': '100155'
1090
  splits:
1091
  - name: train
1092
  num_bytes: 6971500859