| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_117 |
| 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_117 |
| |
| 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: 0.7021 |
| - Accuracy: 0.6240 |
| - 1-f1: 0.2088 |
| - 1-recall: 0.9286 |
| - 1-precision: 0.1176 |
| - Balanced Acc: 0.7677 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.6799 | 1.0 | 13 | 0.5534 | 0.8168 | 0.2258 | 0.5 | 0.1458 | 0.6673 | |
| | 0.6687 | 2.0 | 26 | 0.5016 | 0.7309 | 0.2034 | 0.6429 | 0.1208 | 0.6894 | |
| | 0.4943 | 3.0 | 39 | 0.5893 | 0.6508 | 0.2078 | 0.8571 | 0.1182 | 0.7481 | |
| | 0.227 | 4.0 | 52 | 0.7021 | 0.6240 | 0.2088 | 0.9286 | 0.1176 | 0.7677 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
