A sequential fine-tuning strategy for pre-trained language models reports modest accuracy gains of 4.7%, 0.99%, and 0.72% on semantic similarity, sequence labeling, and text classification tasks.
Glove: Global vectors for word representation
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To Tune or Not To Tune? How About the Best of Both Worlds?
A sequential fine-tuning strategy for pre-trained language models reports modest accuracy gains of 4.7%, 0.99%, and 0.72% on semantic similarity, sequence labeling, and text classification tasks.