| | --- |
| | 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 |
| | |
