| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_095 |
| 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_095 |
|
|
| 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: 0.5323 |
| - Accuracy: 0.9239 |
| - 1-f1: 0.3273 |
| - 1-recall: 0.3214 |
| - 1-precision: 0.3333 |
| - Balanced Acc: 0.6411 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.7802 | 1.0 | 16 | 0.5957 | 0.9424 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | 0.6316 | 2.0 | 32 | 0.5687 | 0.9424 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | 0.5278 | 3.0 | 48 | 0.5489 | 0.9424 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | 0.5157 | 4.0 | 64 | 0.5097 | 0.9403 | 0.0645 | 0.0357 | 0.3333 | 0.5157 | |
| | 0.6505 | 5.0 | 80 | 0.5672 | 0.9403 | 0.2162 | 0.1429 | 0.4444 | 0.5660 | |
| | 0.5312 | 6.0 | 96 | 0.5323 | 0.9239 | 0.3273 | 0.3214 | 0.3333 | 0.6411 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0.dev0 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
| |
