| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_129 |
| 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_129 |
| |
| 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: 0.6651 |
| - Accuracy: 0.7145 |
| - 1-f1: 0.2667 |
| - 1-recall: 0.9189 |
| - 1-precision: 0.1560 |
| - Balanced Acc: 0.8106 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.7601 | 1.0 | 18 | 0.7731 | 0.2870 | 0.1304 | 0.9459 | 0.07 | 0.5968 | |
| | 0.714 | 2.0 | 36 | 0.8593 | 0.2580 | 0.1290 | 0.9730 | 0.0691 | 0.5941 | |
| | 0.7266 | 3.0 | 54 | 0.4779 | 0.9084 | 0.3023 | 0.3514 | 0.2653 | 0.6465 | |
| | 0.5782 | 4.0 | 72 | 0.5362 | 0.7282 | 0.2521 | 0.8108 | 0.1493 | 0.7671 | |
| | 0.1827 | 5.0 | 90 | 0.6651 | 0.7145 | 0.2667 | 0.9189 | 0.1560 | 0.8106 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
