| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_109 |
| 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_bsample_109 |
| |
| This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.2216 |
| - Accuracy: 0.6890 |
| - 1-f1: 0.1667 |
| - 1-recall: 0.8667 |
| - 1-precision: 0.0922 |
| - Balanced Acc: 0.7745 |
| |
| ## 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: 3e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - 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: 15 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.6574 | 1.0 | 13 | 0.6522 | 0.7010 | 0.1379 | 0.6667 | 0.0769 | 0.6844 | |
| | 0.6734 | 2.0 | 26 | 0.5561 | 0.7512 | 0.1613 | 0.6667 | 0.0917 | 0.7105 | |
| | 0.4632 | 3.0 | 39 | 0.5145 | 0.6435 | 0.1287 | 0.7333 | 0.0705 | 0.6868 | |
| | 0.7198 | 4.0 | 52 | 0.8734 | 0.6794 | 0.1519 | 0.8 | 0.0839 | 0.7375 | |
| | 0.2578 | 5.0 | 65 | 1.2216 | 0.6890 | 0.1667 | 0.8667 | 0.0922 | 0.7745 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
