| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: FacebookAI/xlm-roberta-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_bsample_113 |
| | 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_113 |
| | |
| | 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: 0.8525 |
| | - Accuracy: 0.7505 |
| | - 1-f1: 0.2989 |
| | - 1-recall: 0.9630 |
| | - 1-precision: 0.1769 |
| | - Balanced Acc: 0.8505 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.7054 | 1.0 | 14 | 0.5938 | 0.7403 | 0.2743 | 0.8889 | 0.1622 | 0.8102 | |
| | | 0.8172 | 2.0 | 28 | 1.0112 | 0.5358 | 0.1805 | 0.9259 | 0.1 | 0.7195 | |
| | | 0.2966 | 3.0 | 42 | 0.8525 | 0.7505 | 0.2989 | 0.9630 | 0.1769 | 0.8505 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
