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covid_qa_distillBert

This model is a fine-tuned version of distilbert-base-uncased on the covid_qa_deepset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0971

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
0.2537 1.0 3880 0.1871
0.2005 2.0 7760 0.1257
0.1395 3.0 11640 0.0971

Framework versions

  • Transformers 4.14.1
  • Pytorch 1.10.0+cu111
  • Datasets 1.16.1
  • Tokenizers 0.10.3
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Dataset used to train shaina/covid_qa_distillBert