KroneckerBERT: Significant Compression of Pre-trained Language Models Through Kronecker Decomposition and Knowledge Distillation (2022.naacl-main)
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| Challenge: | a recent study shows that over-parameterized pre-trained language models are unsuitable for low-capacity devices. |
| Approach: | They propose a transformer-based pre-trained language model that is overparameterized . they use a two-stage knowledge distillation scheme to train the model . |
| Outcome: | The proposed model outperforms state-of-the-art models on well-known NLP benchmarks. |
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