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Datasets:
emrecan
/
nli_tr_for_simcse

Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Sub-tasks:
semantic-similarity-scoring
text-scoring
Languages:
Turkish
Size:
100K - 1M
Libraries:
Datasets
pandas
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nli_tr_for_simcse / README.md
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metadata
language:
  - tr
size_categories:
  - 100K<n<1M
source_datasets:
  - nli_tr
task_categories:
  - text-scoring
task_ids:
  - semantic-similarity-scoring

NLI-TR for Supervised SimCSE

This dataset is a modified version of NLI-TR dataset. Its intended use is to train Supervised SimCSE models for sentence-embeddings. Steps followed to produce this dataset are listed below:

  1. Merge train split of snli_tr and multinli_tr subsets.
  2. Find every premise that has an entailment hypothesis and a contradiction hypothesis.
  3. Write found triplets into sent0 (premise), sent1 (entailment hypothesis), hard_neg (contradiction hypothesis) format.