readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - pritamdeka/cord-19-abstract
  model-index:
  - name: PubMedBert-abstract-cord19
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # pubmedbert-abstract-cord19
  
  This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the [pritamdeka/cord-19-abstract](https://huggingface.co/datasets/pritamdeka/cord-19-abstract) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3005
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 10000
  - num_epochs: 3.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss |
  |:-------------:|:-----:|:------:|:---------------:|
  | 1.3774        | 0.15  | 5000   | 1.3212          |
  | 1.3937        | 0.29  | 10000  | 1.4059          |
  | 1.6812        | 0.44  | 15000  | 1.6174          |
  | 1.4712        | 0.59  | 20000  | 1.4383          |
  | 1.4293        | 0.73  | 25000  | 1.4356          |
  | 1.4155        | 0.88  | 30000  | 1.4283          |
  | 1.3963        | 1.03  | 35000  | 1.4135          |
  | 1.3718        | 1.18  | 40000  | 1.3948          |
  | 1.369         | 1.32  | 45000  | 1.3961          |
  | 1.354         | 1.47  | 50000  | 1.3788          |
  | 1.3399        | 1.62  | 55000  | 1.3866          |
  | 1.3289        | 1.76  | 60000  | 1.3630          |
  | 1.3155        | 1.91  | 65000  | 1.3609          |
  | 1.2976        | 2.06  | 70000  | 1.3489          |
  | 1.2783        | 2.2   | 75000  | 1.3333          |
  | 1.2696        | 2.35  | 80000  | 1.3260          |
  | 1.2607        | 2.5   | 85000  | 1.3232          |
  | 1.2547        | 2.64  | 90000  | 1.3034          |
  | 1.2495        | 2.79  | 95000  | 1.3035          |
  | 1.2404        | 2.94  | 100000 | 1.3029          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  