Model release

.gitattributes

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README.md

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+# oBERT-6-downstream-pruned-unstructured-80-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 - 6 Layers - Sparsity 80% - unstructured`.
+
+```
+Pruning method: oBERT downstream unstructured
+Paper: https://arxiv.org/abs/2203.07259
+Dataset: SQuADv1
+Sparsity: 80%
+Number of layers: 6
+```
+
+The dev-set performance of this model:
+```
+EM = 81.15
+F1 = 88.20
+```
+
+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}
+}
+```

config.json

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eval_results.txt

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+exact_match = 81.15421002838221
+f1 = 88.20140987664456
+epoch = 30.0

nbest_predictions.json

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pytorch_model.bin

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training_args.bin

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