RedHatAI / oBERT-3-downstream-pruned-unstructured-80-squadv1

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Introduction of oBERT-3-downstream-pruned-unstructured-80-squadv1

Model Details of oBERT-3-downstream-pruned-unstructured-80-squadv1

oBERT-3-downstream-pruned-unstructured-80-squadv1

This model is obtained with The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models .

It corresponds to the model presented in the Table 3 - 3 Layers - Sparsity 80% - unstructured .

Pruning method: oBERT downstream unstructured
Paper: https://arxiv.org/abs/2203.07259
Dataset: SQuADv1
Sparsity: 80%
Number of layers: 3

The dev-set performance of this model:

EM = 75.62
F1 = 84.08

Code: https://github.com/neuralmagic/sparseml/tree/main/research/optimal_BERT_surgeon_oBERT

If you find the model useful, please consider citing our work.

Citation info
@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}
}

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60
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18
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22
3-day runs
38
7-day runs
18
30-day runs

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