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| --- | |
| language: en | |
| tags: | |
| - bert | |
| - qnli | |
| - glue | |
| - torchdistill | |
| license: apache-2.0 | |
| datasets: | |
| - qnli | |
| metrics: | |
| - accuracy | |
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| `bert-base-uncased` fine-tuned on QNLI dataset, using [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab](https://colab.research.google.com/github/yoshitomo-matsubara/torchdistill/blob/master/demo/glue_finetuning_and_submission.ipynb). | |
| The hyperparameters are the same as those in Hugging Face's example and/or the paper of BERT, and the training configuration (including hyperparameters) is available [here](https://github.com/yoshitomo-matsubara/torchdistill/blob/main/configs/sample/glue/qnli/ce/bert_base_uncased.yaml). | |
| I submitted prediction files to [the GLUE leaderboard](https://gluebenchmark.com/leaderboard), and the overall GLUE score was **77.9**. | |