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Table 2 - oBERT - QQP 97%.Pruning method: oBERT upstream unstructured + sparse-transfer to downstream
Paper: https://arxiv.org/abs/2203.07259
Dataset: QQP
Sparsity: 97%
Number of layers: 12(*)):| oBERT 97% | acc | F1 |
| ------------ | ----- | ----- |
| seed=42 (*)| 89.85 | 86.41 |
| seed=3407 | 89.72 | 86.42 |
| seed=54321 | 89.70 | 86.24 |
| ------------ | ----- | ----- |
| mean | 89.76 | 86.35 |
| stdev | 0.081 | 0.101 |1@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}