| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: AnonymousCS/populism_multilingual_roberta_base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - recall |
| | - precision |
| | model-index: |
| | - name: populism_model66 |
| | 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_model66 |
| | |
| | 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: 0.5870 |
| | - Accuracy: 0.9114 |
| | - F1: 0.4412 |
| | - Recall: 0.5556 |
| | - Precision: 0.3659 |
| | |
| | ## 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: 128 |
| | - eval_batch_size: 128 |
| | - 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: 5 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
| | | No log | 1.0 | 14 | 0.7047 | 0.9301 | 0.25 | 0.1852 | 0.3846 | |
| | | No log | 2.0 | 28 | 0.3870 | 0.8974 | 0.4634 | 0.7037 | 0.3455 | |
| | | No log | 3.0 | 42 | 0.4250 | 0.8765 | 0.4045 | 0.6667 | 0.2903 | |
| | | 0.3082 | 4.0 | 56 | 0.6455 | 0.9184 | 0.3860 | 0.4074 | 0.3667 | |
| | | 0.3082 | 5.0 | 70 | 0.5870 | 0.9114 | 0.4412 | 0.5556 | 0.3659 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.47.1 |
| | - Pytorch 2.5.1+cu121 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| | |
