readme: ---
  license: mit
  tags:
  - fill-mask
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: deberta-v3-large-dapt-scientific-papers-pubmed-tapt
    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. -->
  
  # deberta-v3-large-dapt-scientific-papers-pubmed-tapt
  
  This model is a fine-tuned version of [domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed](https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.4429
  - Accuracy: 0.5915
  
  ## 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
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 3.3855        | 1.0   | 4134  | 3.2334          | 0.4953   |
  | 2.9224        | 2.0   | 8268  | 2.8317          | 0.5430   |
  | 2.703         | 3.0   | 12402 | 2.6141          | 0.5665   |
  | 2.4963        | 4.0   | 16536 | 2.4918          | 0.5855   |
  | 2.399         | 5.0   | 20670 | 2.4429          | 0.5915   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  