| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_092 |
| 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_092 |
|
|
| 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: 0.2866 |
| - Accuracy: 0.9904 |
| - 1-f1: 0.8257 |
| - 1-recall: 0.7895 |
| - 1-precision: 0.8654 |
| - Balanced Acc: 0.8929 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.019 | 1.0 | 62 | 0.1108 | 0.9863 | 0.7692 | 0.7895 | 0.75 | 0.8908 | |
| | 0.1966 | 2.0 | 124 | 0.1625 | 0.9873 | 0.7788 | 0.7719 | 0.7857 | 0.8828 | |
| | 0.0228 | 3.0 | 186 | 0.0987 | 0.9878 | 0.8033 | 0.8596 | 0.7538 | 0.9257 | |
| | 0.2046 | 4.0 | 248 | 0.3138 | 0.9929 | 0.8654 | 0.7895 | 0.9574 | 0.8942 | |
| | 0.0006 | 5.0 | 310 | 0.2866 | 0.9904 | 0.8257 | 0.7895 | 0.8654 | 0.8929 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0.dev0 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
| |
