readme: ---
  license: other
  tags:
  - generated_from_trainer
  model-index:
  - name: distilroberta-proppy
    results: []
  ---
  
  
  # distilroberta-proppy
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the proppy corpus.
  It achieves the following results on the evaluation set:
  - Loss: 0.1838
  - Acc: 0.9269
  
  ## Training and evaluation data
  
  The training data is the [proppy corpus](https://zenodo.org/record/3271522). See [Proppy: Organizing the News
  Based on Their Propagandistic Content](https://propaganda.qcri.org/papers/elsarticle-template.pdf) for details.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 12345
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 16
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Acc    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.3179        | 1.0   | 732   | 0.2032          | 0.9146 |
  | 0.2933        | 2.0   | 1464  | 0.2026          | 0.9206 |
  | 0.2938        | 3.0   | 2196  | 0.1849          | 0.9252 |
  | 0.3429        | 4.0   | 2928  | 0.1983          | 0.9221 |
  | 0.2608        | 5.0   | 3660  | 0.2310          | 0.9106 |
  | 0.2562        | 6.0   | 4392  | 0.1826          | 0.9270 |
  | 0.2785        | 7.0   | 5124  | 0.1954          | 0.9228 |
  | 0.307         | 8.0   | 5856  | 0.2056          | 0.9200 |
  | 0.28          | 9.0   | 6588  | 0.1843          | 0.9259 |
  | 0.2794        | 10.0  | 7320  | 0.1782          | 0.9299 |
  | 0.2868        | 11.0  | 8052  | 0.1907          | 0.9242 |
  | 0.2789        | 12.0  | 8784  | 0.2031          | 0.9216 |
  | 0.2827        | 13.0  | 9516  | 0.1976          | 0.9229 |
  | 0.2795        | 14.0  | 10248 | 0.1866          | 0.9255 |
  | 0.2895        | 15.0  | 10980 | 0.1838          | 0.9269 |
  
  
  ### Framework versions
  
  - Transformers 4.11.2
  - Pytorch 1.7.1
  - Datasets 1.11.0
  - Tokenizers 0.10.3
  