How to Use Transformers for Transfer Learning?

Maryam Ebrahimzadeh; Hamidreza Asadi

doi:10.20944/preprints202305.2185.v1

Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 28 May 2023 / Approved: 31 May 2023 / Online: 31 May 2023 (07:39:24 CEST)

Transformers are increasing replacing older generation of deep neural networks due to their success in a wide range of application. The dominant approach of using transformers is to pre-train them on a large training dataset and then fine-tune them on a downstream task. However, as transformers becoming larger, the fine-tuning approach is become an infeasible approach for transfer learning. In this short survey, we list a few recent methods that makes using transformers based on transfer learning more efficient.

optics; photonics; light, lasers; journal manuscripts; LaTeX template

Computer Science and Mathematics, Computer Science

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How to Use Transformers for Transfer Learning?

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