| --- |
| library_name: transformers |
| license: mit |
| base_model: AnonymousCS/populism_multilingual_roberta_base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_237 |
| 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. --> |
|
|
| # populism_classifier_bsample_237 |
| |
| This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9879 |
| - Accuracy: 0.7066 |
| - 1-f1: 0.3087 |
| - 1-recall: 0.7667 |
| - 1-precision: 0.1933 |
| - Balanced Acc: 0.7338 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.8787 | 1.0 | 6 | 0.9119 | 0.8177 | 0.36 | 0.6 | 0.2571 | 0.7190 | |
| | 0.1512 | 2.0 | 12 | 0.9930 | 0.5641 | 0.2609 | 0.9 | 0.1525 | 0.7164 | |
| | 0.4247 | 3.0 | 18 | 0.8828 | 0.6866 | 0.3125 | 0.8333 | 0.1923 | 0.7531 | |
| | 0.0768 | 4.0 | 24 | 1.0959 | 0.6325 | 0.2873 | 0.8667 | 0.1722 | 0.7386 | |
| | 0.0525 | 5.0 | 30 | 0.9879 | 0.7066 | 0.3087 | 0.7667 | 0.1933 | 0.7338 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
