| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_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_bsample_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: 0.7838 |
| - Accuracy: 0.8245 |
| - 1-f1: 0.3408 |
| - 1-recall: 0.9504 |
| - 1-precision: 0.2076 |
| - Balanced Acc: 0.8843 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.5269 | 1.0 | 333 | 0.8559 | 0.7152 | 0.2444 | 0.9654 | 0.1399 | 0.8340 | |
| | 0.075 | 2.0 | 666 | 0.4378 | 0.8218 | 0.3276 | 0.9098 | 0.1998 | 0.8636 | |
| | 0.3245 | 3.0 | 999 | 0.5634 | 0.8349 | 0.3514 | 0.9368 | 0.2162 | 0.8833 | |
| | 0.0832 | 4.0 | 1332 | 0.3395 | 0.8799 | 0.4085 | 0.8692 | 0.2670 | 0.8748 | |
| | 0.2264 | 5.0 | 1665 | 0.3105 | 0.9179 | 0.4654 | 0.7489 | 0.3376 | 0.8376 | |
| | 0.2779 | 6.0 | 1998 | 0.8355 | 0.7710 | 0.2866 | 0.9639 | 0.1683 | 0.8626 | |
| | 0.1703 | 7.0 | 2331 | 0.7838 | 0.8245 | 0.3408 | 0.9504 | 0.2076 | 0.8843 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
