| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_079 |
| 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_079 |
|
|
| This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3726 |
| - Accuracy: 0.9495 |
| - 1-f1: 0.5652 |
| - 1-recall: 0.6872 |
| - 1-precision: 0.4800 |
| - Balanced Acc: 0.8250 |
|
|
| ## 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 OptimizerNames.ADAMW_TORCH_FUSED 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.3081 | 1.0 | 436 | 0.2883 | 0.9422 | 0.5373 | 0.7038 | 0.4345 | 0.8289 | |
| | 0.2317 | 2.0 | 872 | 0.2401 | 0.9052 | 0.4688 | 0.8767 | 0.3200 | 0.8917 | |
| | 0.1213 | 3.0 | 1308 | 0.2857 | 0.9432 | 0.5605 | 0.7594 | 0.4442 | 0.8559 | |
| | 0.2189 | 4.0 | 1744 | 0.3726 | 0.9495 | 0.5652 | 0.6872 | 0.4800 | 0.8250 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0.dev0 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
| |
