readme: ---
  license: other
  tags:
  - generated_from_trainer
  model-index:
  - name: distilroberta-propaganda-2class
    results: []
  ---
  
  # distilroberta-propaganda-2class
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the QCRI propaganda dataset. 
  
  It achieves the following results on the evaluation set:
  - Loss: 0.5087
  - Acc: 0.7424
  
  ## Training and evaluation data
  
  Training data is the 19-class QCRI propaganda data, with all propaganda classes collapsed to a single catch-all 'prop' class.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.5737        | 1.0   | 493  | 0.5998          | 0.6515 |
  | 0.4954        | 2.0   | 986  | 0.5530          | 0.7080 |
  | 0.4774        | 3.0   | 1479 | 0.5331          | 0.7258 |
  | 0.4846        | 4.0   | 1972 | 0.5247          | 0.7339 |
  | 0.4749        | 5.0   | 2465 | 0.5392          | 0.7199 |
  | 0.502         | 6.0   | 2958 | 0.5124          | 0.7466 |
  | 0.457         | 7.0   | 3451 | 0.5167          | 0.7432 |
  | 0.4899        | 8.0   | 3944 | 0.5160          | 0.7428 |
  | 0.4833        | 9.0   | 4437 | 0.5280          | 0.7339 |
  | 0.5114        | 10.0  | 4930 | 0.5112          | 0.7436 |
  | 0.4419        | 11.0  | 5423 | 0.5060          | 0.7525 |
  | 0.4743        | 12.0  | 5916 | 0.5031          | 0.7547 |
  | 0.4597        | 13.0  | 6409 | 0.5043          | 0.7517 |
  | 0.4861        | 14.0  | 6902 | 0.5055          | 0.7487 |
  | 0.499         | 15.0  | 7395 | 0.5091          | 0.7419 |
  | 0.501         | 16.0  | 7888 | 0.5037          | 0.7521 |
  | 0.4659        | 17.0  | 8381 | 0.5087          | 0.7424 |
  
  
  ### Framework versions
  
  - Transformers 4.11.2
  - Pytorch 1.7.1
  - Datasets 1.11.0
  - Tokenizers 0.10.3
  