Transferred from Omartificial-Intelligence-Space/Arabic-NLi-Pair-Class

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README.md

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+---
+license: apache-2.0
+task_categories:
+- sentence-similarity
+language:
+- ar
+size_categories:
+- 100K<n<1M
+tags:
+- sentence-transformers
+dataset_info:
+    features:
+      - name: premise
+        dtype: string
+      - name: hypothesis
+        dtype: string
+      - name: label
+        dtype:
+          class_label:
+            names:
+              '0': entailment
+              '1': neutral
+              '2': contradiction
+---
+
+
+# Arabic NLI Pair-Class
+
+## Dataset Summary
+
+- The Arabic Version of SNLI and MultiNLI datasets. (Pair-Class Subset)
+- Originally used for Natural Language Inference (NLI),
+- Dataset may be used for training/finetuning an embedding model for semantic textual similarity.
+
+## Pair-Class Subset
+
+- Columns: "premise", "hypothesis", "label"
+- Column types: str, str, class with {"0": "entailment", "1": "neutral", "2": "contradiction"}
+
+## Arabic Examples:
+
+```python
+{
+  "premise": "شخص على حصان يقفز فوق طائرة معطلة",
+  "hypothesis": "شخص يقوم بتدريب حصانه للمنافسة",
+  "label": 1,
+},
+{
+  "premise": "شخص على حصان يقفز فوق طائرة معطلة",
+  "hypothesis": "شخص في مطعم، يطلب عجة.",
+  "label": 2,
+},
+{
+  "premise": "شخص على حصان يقفز فوق طائرة معطلة",
+  "hypothesis": "شخص في الهواء الطلق، على حصان.",
+  "label": 0,
+}
+```
+
+
+## Disclaimer
+
+Please note that the translated sentences are generated using neural machine translation and may not always convey the intended meaning accurately.
+
+
+## Contact
+[Contact Me](https://www.omarai.co) if you have any questions or you want to use thid dataset 
+
+
+## Note
+
+Original work done by [SentenceTransformers](https://www.sbert.net)
+
+
+
+## Citation
+
+If you use the Arabic Matryoshka Embeddings Dataset, please cite it as follows:
+
+```bibtex
+@misc{nacar2024enhancingsemanticsimilarityunderstanding,
+      title={Enhancing Semantic Similarity Understanding in Arabic NLP with Nested Embedding Learning}, 
+      author={Omer Nacar and Anis Koubaa},
+      year={2024},
+      eprint={2407.21139},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2407.21139}, 
+}

train.csv

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