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Datasets:
BEE-spoke-data
/
allNLI-sbert

Tasks:
Sentence Similarity
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
1M - 10M
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
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2
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this is literally the allNLI example dataset but parsed and reformatted as HF datasets parquet.

token counts

sentence1 column

bert-base-uncased token count:

         token_count
count  942069.000000
mean       20.834934
std        12.953432
min         3.000000
25%        13.000000
50%        17.000000
75%        25.000000
max       428.000000
  • Total count: 19.63 M tokens google/bigbird-roberta-base token count:
         token_count
count  942069.000000
mean       20.678186
std        12.618819
min         3.000000
25%        13.000000
50%        17.000000
75%        25.000000
max       407.000000
  • Total count: 19.48 M tokens

sentence2 column

bert-base-uncased token count:

         token_count
count  942069.000000
mean       12.058493
std         4.507284
min         0.000000
25%         9.000000
50%        11.000000
75%        14.000000
max        77.000000
  • Total count: 11.36 M tokens

google/bigbird-roberta-base token count:

         token_count
count  942069.000000
mean       12.003818
std         4.423798
min         0.000000
25%         9.000000
50%        11.000000
75%        14.000000
max        79.000000
  • Total count: 11.31 M tokens
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Models trained or fine-tuned on BEE-spoke-data/allNLI-sbert