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language: en |
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# Sparse BERT base model (uncased) |
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Pretrained model pruned to 1:2 structured sparsity. |
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The model is a pruned version of the [BERT base model](https://huggingface.co/bert-base-uncased). |
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## Intended Use |
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The model can be used for fine-tuning to downstream tasks with sparsity already embeded to the model. |
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To keep the sparsity a mask should be added to each sparse weight blocking the optimizer from updating the zeros. |
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## Evaluation Results |
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We get the following results on the tasks development set, all results are mean of 5 different seeded models: |
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| Task | MNLI-m (Acc) | MNLI-mm (Acc) | QQP (Acc/F1) | QNLI (Acc) | SST-2 (Acc) | STS-B (Pears/Spear) | SQuADv1.1 (Acc/F1) | |
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|------|--------------|---------------|--------------|------------|-------------|---------------------|--------------------| |
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| | 83.3 | 83.9 | 90.8/87.6 | 90.4 | 91.3 | 88.8/88.3 | 80.5/88.2 | |
