---
title: "Large Language Models, MirrorBERT — Transforming Models into Universal Lexical and Sentence Encoders"
url: https://daily.dev/posts/large-language-models-mirrorbert-transforming-models-into-universal-lexical-and-sentence-encoders-vc9rmub0q
source_url: https://towardsdatascience.com/large-language-models-mirrorbert-transforming-models-into-universal-lexical-and-sentence-511bd592da48?source=rss----7f60cf5620c9---4
type: article
source: "Towards Data Science"
published: 2023-12-15T06:23:32.971Z
updated: 2023-12-15T06:23:31.054Z
tags: ["machine-learning", "nlp", "transformers", "bert"]
reading_time: 6
upvotes: 0
comments: 0
language: en
---

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# Large Language Models, MirrorBERT — Transforming Models into Universal Lexical and Sentence Encoders

**[Towards Data Science](https://daily.dev/sources/tds)** · 6 min read · 0 upvotes · 0 comments

## Summary

MirrorBERT is a model that uses self-supervision and data augmentation techniques to achieve comparable performance to fine-tuned models like BERT and RoBERTa on semantic similarity tasks. It can transform pretrained models into universal lexical encoders with high efficiency.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/large-language-models-mirrorbert-transforming-models-into-universal-lexical-and-sentence-511bd592da48?source=rss----7f60cf5620c9---4>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#nlp](https://daily.dev/tags/nlp), [#transformers](https://daily.dev/tags/transformers), [#bert](https://daily.dev/tags/bert)

[View this post on daily.dev](https://daily.dev/posts/large-language-models-mirrorbert-transforming-models-into-universal-lexical-and-sentence-encoders-vc9rmub0q)