readme: ---
  license: mit
  tags:
  - text-classification
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: deberta-v3-large-dapt-tapt-scientific-papers-pubmed-finetuned-DAGPap22
    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-tapt-scientific-papers-pubmed-finetuned-DAGPap22
  
  This model is a fine-tuned version of [domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt](https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0002
  - Accuracy: 0.9998
  - F1: 0.9999
  
  ## 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: 6e-06
  - 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: 50
  - num_epochs: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.1884        | 1.0   | 669  | 0.0248          | 0.9951   | 0.9964 |
  | 0.0494        | 2.0   | 1338 | 0.0084          | 0.9987   | 0.9990 |
  | 0.0199        | 3.0   | 2007 | 0.0051          | 0.9991   | 0.9993 |
  | 0.0079        | 4.0   | 2676 | 0.0030          | 0.9993   | 0.9995 |
  | 0.0           | 5.0   | 3345 | 0.0026          | 0.9994   | 0.9996 |
  | 0.0           | 6.0   | 4014 | 0.0014          | 0.9996   | 0.9997 |
  | 0.0           | 7.0   | 4683 | 0.0015          | 0.9996   | 0.9997 |
  | 0.0           | 8.0   | 5352 | 0.0011          | 0.9996   | 0.9997 |
  | 0.0143        | 9.0   | 6021 | 0.0000          | 1.0      | 1.0    |
  | 0.0           | 10.0  | 6690 | 0.0035          | 0.9991   | 0.9993 |
  | 0.0           | 11.0  | 7359 | 0.0004          | 0.9998   | 0.9999 |
  | 0.0           | 12.0  | 8028 | 0.0002          | 0.9998   | 0.9999 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  