NoisyTune: A Little Noise Can Help You Finetune Pretrained Language Models Better (2022.acl-short)
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| Challenge: | Existing methods for finetuning pretrained language models (PLMs) have risks in overfitting the pretraining tasks and data, which may lead to suboptimal performance. |
| Approach: | They propose a method which adds noise to parameters of PLMs before fine-tuning. |
| Outcome: | The proposed method can be used on GLUE English and XTREME multilingual benchmarks. |
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