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Table 3 - 6 Layers - 0% Sparsity, and it represents an upper bound for performance of the corresponding pruned models:neuralmagic/oBERT-6-downstream-pruned-unstructured-80-squadv1neuralmagic/oBERT-6-downstream-pruned-block4-80-squadv1neuralmagic/oBERT-6-downstream-pruned-unstructured-90-squadv1neuralmagic/oBERT-6-downstream-pruned-block4-90-squadv1EM = 81.17
F1 = 88.321@article{kurtic2022optimal,
2 title={The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models},
3 author={Kurtic, Eldar and Campos, Daniel and Nguyen, Tuan and Frantar, Elias and Kurtz, Mark and Fineran, Benjamin and Goin, Michael and Alistarh, Dan},
4 journal={arXiv preprint arXiv:2203.07259},
5 year={2022}
6}