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nli_tr_for_simcse

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Text Classification

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semantic-similarity-scoring

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	---
	language:
	- tr
	size_categories:
	- 100K<n<1M
	source_datasets:
	- nli_tr
	task_categories:
	- text-classification
	task_ids:
	- semantic-similarity-scoring
	- text-scoring
	---
	# NLI-TR for Supervised SimCSE

	This dataset is a modified version of [NLI-TR](https://huggingface.co/datasets/nli_tr) dataset. Its intended use is to train Supervised [SimCSE](https://github.com/princeton-nlp/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.

	See this [Colab Notebook](https://colab.research.google.com/drive/1Ysq1SpFOa7n1X79x2HxyWjfKzuR_gDQV?usp=sharing) for training and evaluation on Turkish sentences.