| # oBERT-12-upstream-pruned-unstructured-90-finetuned-qqp-v2 | |
| 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 2 - oBERT - QQP 90%` (in the upcoming updated version of the paper). | |
| ``` | |
| Pruning method: oBERT upstream unstructured + sparse-transfer to downstream | |
| Paper: https://arxiv.org/abs/2203.07259 | |
| Dataset: QQP | |
| Sparsity: 90% | |
| Number of layers: 12 | |
| ``` | |
| The dev-set performance reported in the paper is averaged over four seeds, and we release the best model (marked with `(*)`): | |
| ``` | |
| | oBERT 90% | acc | F1 | | |
| | ------------- | ----- | ----- | | |
| | seed=42 | 90.94 | 87.79 | | |
| | seed=3407 | 91.00 | 87.81 | | |
| | seed=123 | 90.94 | 87.73 | | |
| | seed=12345 (*)| 91.07 | 87.92 | | |
| | ------------- | ----- | ----- | | |
| | mean | 90.99 | 87.81 | | |
| | stdev | 0.061 | 0.079 | | |
| ``` | |
| 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} | |
| } | |
| ``` |