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cs.CL2024
Automatic Pruning of Fine-tuning Datasets for Transformer-based Language Models
Mohammadreza Tayaranian, Seyyed Hasan Mozafari, Brett H. Meyer +2
Transformer-based language models have shown state-of-the-art performance on a variety of natural language understanding tasks. To achieve this performance, these models are first…
cs.CL2022
Efficient Fine-Tuning of Compressed Language Models with Learners
Danilo Vucetic, Mohammadreza Tayaranian, Maryam Ziaeefard +3
Fine-tuning BERT-based models is resource-intensive in memory, computation, and time. While many prior works aim to improve inference efficiency via compression techniques, e.g., p…