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Training and Finetuning Embedding Models with Sentence Transformers

The blog post explains how to finetune Sentence Transformer models using the Sentence Transformers library, covering components like datasets, loss functions, training arguments, evaluators, and the trainer.

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Sentence Transformers is a Python library for using and training embedding models for a wide range of applications, such as retrieval augmented generation, semantic search, semantic textual similarity, paraphrase mining, and more. In this blogpost, I'll show you how to use it to finetune Sentence Transformer models to improve their performance on specific tasks.

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