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Table 1 - 30 Epochs - oBERT - MNLI 97%.Pruning method: oBERT downstream unstructured
Paper: https://arxiv.org/abs/2203.07259
Dataset: MNLI
Sparsity: 97%
Number of layers: 12(*)):| oBERT 97% | m-acc | mm-acc|
| ------------ | ----- | ----- |
| seed=42 (*)| 82.10 | 81.94 |
| seed=3407 | 81.81 | 82.27 |
| seed=54321 | 81.40 | 81.83 |
| ------------ | ----- | ----- |
| mean | 81.77 | 82.01 |
| stdev | 0.351 | 0.228 |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}