| # oBERT-3-downstream-pruned-unstructured-90-squadv1 | |
| This model is obtained with [The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models](https://arxiv.org/abs/2203.07259). | |
| It corresponds to the model presented in the `Table 3 - 3 Layers - Sparsity 90% - unstructured`. | |
| ``` | |
| Pruning method: oBERT downstream unstructured | |
| Paper: https://arxiv.org/abs/2203.07259 | |
| Dataset: SQuADv1 | |
| Sparsity: 90% | |
| Number of layers: 3 | |
| ``` | |
| The dev-set performance of this model: | |
| ``` | |
| EM = 73.61 | |
| F1 = 82.50 | |
| ``` | |
| Code: _coming soon_ | |
| ## BibTeX entry and citation info | |
| ```bibtex | |
| @article{kurtic2022optimal, | |
| title={The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models}, | |
| author={Kurtic, Eldar and Campos, Daniel and Nguyen, Tuan and Frantar, Elias and Kurtz, Mark and Fineran, Benjamin and Goin, Michael and Alistarh, Dan}, | |
| journal={arXiv preprint arXiv:2203.07259}, | |
| year={2022} | |
| } | |
| ``` |