bert-covidqa / README.md
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bert-cased
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metadata
base_model: phiyodr/bert-base-finetuned-squad2
tags:
  - generated_from_trainer
datasets:
  - covid_qa_deepset
model-index:
  - name: bert-covidqa
    results: []

bert-covidqa

This model is a fine-tuned version of phiyodr/bert-base-finetuned-squad2 on the covid_qa_deepset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6451

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: 3e-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: 1

Training results

Training Loss Epoch Step Validation Loss
0.5829 0.04 5 1.0001
0.7899 0.09 10 0.7849
0.5929 0.13 15 0.7851
0.691 0.18 20 0.7549
0.6383 0.22 25 0.7199
0.3216 0.26 30 0.7625
0.3273 0.31 35 0.8644
0.5909 0.35 40 0.7117
0.2556 0.39 45 0.6681
0.6896 0.44 50 0.7138
0.6066 0.48 55 0.6614
0.2602 0.53 60 0.6791
0.4034 0.57 65 0.7168
0.5511 0.61 70 0.7783
0.6313 0.66 75 0.7269
0.261 0.7 80 0.7106
0.4904 0.75 85 0.6735
0.4706 0.79 90 0.6370
0.4174 0.83 95 0.6355
0.3762 0.88 100 0.6356
0.5128 0.92 105 0.6429
0.553 0.96 110 0.6451

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1