| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: FacebookAI/xlm-roberta-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_128 |
| | 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_128 |
| |
|
| | 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: 1.5220 |
| | - Accuracy: 0.9488 |
| | - 1-f1: 0.3902 |
| | - 1-recall: 0.2759 |
| | - 1-precision: 0.6667 |
| | - Balanced Acc: 0.6336 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.0165 | 1.0 | 122 | 0.9807 | 0.9406 | 0.2927 | 0.2069 | 0.5 | 0.5969 | |
| | | 0.0629 | 2.0 | 244 | 0.6859 | 0.9385 | 0.5 | 0.5172 | 0.4839 | 0.7412 | |
| | | 0.072 | 3.0 | 366 | 0.9013 | 0.9365 | 0.5079 | 0.5517 | 0.4706 | 0.7563 | |
| | | 0.0006 | 4.0 | 488 | 1.5220 | 0.9488 | 0.3902 | 0.2759 | 0.6667 | 0.6336 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.56.0.dev0 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.21.4 |
| | |
