| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: AnonymousCS/populism_multilingual_roberta_base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_238 |
| | 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_238 |
| |
|
| | 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: 0.5121 |
| | - Accuracy: 0.9488 |
| | - 1-f1: 0.0980 |
| | - 1-recall: 0.1667 |
| | - 1-precision: 0.0694 |
| | - Balanced Acc: 0.5644 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.5777 | 1.0 | 113 | 0.3860 | 0.9833 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.5144 | 2.0 | 226 | 0.3376 | 0.9833 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.7421 | 3.0 | 339 | 0.4980 | 0.9833 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.1208 | 4.0 | 452 | 0.3496 | 0.9711 | 0.0714 | 0.0667 | 0.0769 | 0.5265 | |
| | | 0.2666 | 5.0 | 565 | 0.3291 | 0.9555 | 0.0698 | 0.1 | 0.0536 | 0.5350 | |
| | | 0.2244 | 6.0 | 678 | 0.5091 | 0.9822 | 0.0588 | 0.0333 | 0.25 | 0.5158 | |
| | | 0.3592 | 7.0 | 791 | 0.5127 | 0.9777 | 0.0909 | 0.0667 | 0.1429 | 0.5299 | |
| | | 0.1585 | 8.0 | 904 | 0.5121 | 0.9488 | 0.0980 | 0.1667 | 0.0694 | 0.5644 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
