readme: ---
  language: en
  tags:
  - bert
  - rte
  - glue
  - torchdistill
  license: apache-2.0
  datasets:
  - rte
  metrics:
  - accuracy
  ---
  
  `bert-base-uncased` fine-tuned on RTE 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/rte/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**.
  