distilroberta-proppy
This model is a fine-tuned version of 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. See Proppy: Organizing the News Based on Their Propagandistic Content 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
