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MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

NeurIPS 2020 · Architectures and efficiency › Attention and transformers · approach: Long-context KV and memory attention · 633 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use deep self-attention distillation instead of the baseline distillation approaches6-layer, 768-hidden student distilled from BERT_BASE · SQuAD 2.0 devF1: 73.1 -> 76.4Helped
Add self-attention value-relation transfer (ablation)MiniLM (6 layers, hidden size 384) · SQuAD 2.0 devF1: 71.0 -> 72.4Helped
Add self-attention value-relation transfer (ablation)MiniLM (6 layers, hidden size 384) · MNLI-m devaccuracy: 80.9 -> 82.2Helped
Add self-attention value-relation transfer (ablation)MiniLM (6 layers, hidden size 384) · SST-2 devaccuracy: 89.9 -> 91.0Helped
Replace value-relation KL loss with MSE over values (ablation)MiniLM (6 layers, hidden size 384) · SQuAD 2.0 devF1: 71.4 -> 72.4Hurt
Replace value-relation KL loss with MSE over values (ablation)MiniLM (6 layers, hidden size 384) · MNLI-m devaccuracy: 82.0 -> 82.2Hurt
Replace value-relation KL loss with MSE over values (ablation)MiniLM (6 layers, hidden size 384) · SST-2 devaccuracy: 90.8 -> 91.0No clear effect
Add layer-to-layer distillation alongside last-layer distillation (ablation)MiniLM (6 layers, hidden size 384) · SQuAD 2.0 devF1: 72.4 -> 71.6Hurt
Add layer-to-layer distillation alongside last-layer distillation (ablation)MiniLM (6 layers, hidden size 384) · MNLI-m devaccuracy: 82.2 -> 81.8Hurt
Add a teacher assistantMiniLM (6 layers, hidden size 384) · SQuAD 2.0 devF1: 72.4 -> 72.7Helped
Add a teacher assistantMiniLM (6 layers, hidden size 384) · MNLI-m devaccuracy: 82.2 -> 82.4Helped
Add a teacher assistantMiniLM (6 layers, hidden size 384) · SST-2 devaccuracy: 91.0 -> 91.2Helped

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