| --- |
| library_name: transformers |
| license: mit |
| base_model: AnonymousCS/populism_multilingual_roberta_base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_239 |
| 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_239 |
|
|
| 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: 0.8326 |
| - Accuracy: 0.9487 |
| - 1-f1: 0.4762 |
| - 1-recall: 0.4167 |
| - 1-precision: 0.5556 |
| - Balanced Acc: 0.6985 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.2743 | 1.0 | 27 | 0.3441 | 0.9324 | 0.4912 | 0.5833 | 0.4242 | 0.7682 | |
| | 0.2076 | 2.0 | 54 | 0.3887 | 0.9207 | 0.4516 | 0.5833 | 0.3684 | 0.7620 | |
| | 0.2486 | 3.0 | 81 | 0.6516 | 0.9441 | 0.52 | 0.5417 | 0.5 | 0.7548 | |
| | 0.5154 | 4.0 | 108 | 0.8326 | 0.9487 | 0.4762 | 0.4167 | 0.5556 | 0.6985 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
|
|
