Heterogeneous Student Knowledge Distillation From BERT Using a Lightweight Ensemble Framework
Ching-Sheng Lin,
Chung-Nan Tsai,
Jung-Sing Jwo
et al.
Abstract:Deep learning models have demonstrated their effectiveness in capturing complex relationships between input features and target outputs across many different application domains. These models, however, often come with considerable memory and computational demands, posing challenges for deployment on resource-constrained edge devices. Knowledge distillation is a prominent technique for transferring the expertise from an advanced yet heavy teacher model to a more efficient leaner student model. As ensemble metho… Show more
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