Source code for our AAAI'22 paper 《From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression》
This is Runxin Xu [google scholar].
Currently I am a third-year Master's student at Peking University under the supervision of Prof. Baobao Chang [google scholar].
My research interests mainly lie in natural language processing, especially 1) document-level and few-shot information extraction, and 2) effective and efficient pre-trained language model.
Hello，
I find the results of CAP-m in 90% sparsity QQP is "91.6/87.7", while CAP-soft is "90.7/87.4"(bold).
Is the result of CAP-m correct?
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