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covid_qa_distillbert

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covid_qa_distillbert / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - covid_qa_deepset
metrics:
  - squad_v2
widget:
  - text: What is COVID-19?
    context: >-
      Coronavirus disease 2019 (COVID-19) is a contagious disease caused by
      severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first
      known case was identified in Wuhan, China, in December 2019.[7] The
      disease has since spread worldwide, leading to an ongoing pandemic.
  - text: Where was COVID-19 first discovered?
    context: >-
      The first known infections from SARS-CoV-2 were discovered in Wuhan,
      China. The original source of viral transmission to humans remains
      unclear, as does whether the virus became pathogenic before or after the
      spillover event.
  - text: What is Post-COVID syndrome?
    context: >-
      Long COVID, also known as post-COVID-19 syndrome, post-acute sequelae of
      COVID-19 (PASC), or chronic COVID syndrome (CCS) is a condition
      characterized by long-term sequelae appearing or persisting after the
      typical convalescence period of COVID-19. Long COVID can affect nearly
      every organ system, with sequelae including respiratory system disorders,
      nervous system and neurocognitive disorders, mental health disorders,
      metabolic disorders, cardiovascular disorders, gastrointestinal disorders,
      malaise, fatigue, musculoskeletal pain, and anemia. A wide range of
      symptoms are commonly reported, including fatigue, headaches, shortness of
      breath, anosmia (loss of smell), parosmia (distorted smell), muscle
      weakness, low fever and cognitive dysfunction.

distilbert-base-uncased-finetuned-squad

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: 0.0976

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
0.2502 1.0 3880 0.1824
0.2007 2.0 7760 0.1250
0.1338 3.0 11640 0.0976

Framework versions

  • Transformers 4.13.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.16.1
  • Tokenizers 0.10.3