Omartificial-Intelligence-Space/Arabic-MiniLM-L12-v2-all-nli-triplet

SentenceTransformer based on sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2

This is a sentence-transformers model finetuned from sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 on the Omartificial-Intelligence-Space/arabic-n_li-triplet dataset. It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. This model is part of the Arabic Matryoshka Embedding Models collection. It was presented in the paper GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training.

Model Details

Model Description

• —Model Type: Sentence Transformer
• —Base model: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 <!-- at revision bf3bf13ab40c3157080a7ab344c831b9ad18b5eb -->
• —Maximum Sequence Length: 128 tokens
• —Output Dimensionality: 384 tokens
• —Similarity Function: Cosine Similarity
• —Training Dataset:
• —Omartificial-Intelligence-Space/arabic-n_li-triplet <!-- - Language: Unknown --> <!-- - License: Unknown -->

Model Sources

• —Documentation: Sentence Transformers Documentation
• —Repository: Sentence Transformers on GitHub
• —**Hugging