| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_104 |
| 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_104 |
|
|
| 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: 0.5721 |
| - Accuracy: 0.9229 |
| - 1-f1: 0.4571 |
| - 1-recall: 0.5161 |
| - 1-precision: 0.4103 |
| - Balanced Acc: 0.7332 |
|
|
| ## 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: 128 |
| - eval_batch_size: 128 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.395 | 1.0 | 16 | 0.3727 | 0.8763 | 0.4299 | 0.7419 | 0.3026 | 0.8136 | |
| | 0.3218 | 2.0 | 32 | 0.3474 | 0.8560 | 0.4409 | 0.9032 | 0.2917 | 0.8780 | |
| | 0.2668 | 3.0 | 48 | 0.3228 | 0.8682 | 0.4538 | 0.8710 | 0.3068 | 0.8695 | |
| | 0.2797 | 4.0 | 64 | 0.5257 | 0.9209 | 0.5063 | 0.6452 | 0.4167 | 0.7923 | |
| | 0.1009 | 5.0 | 80 | 0.5721 | 0.9229 | 0.4571 | 0.5161 | 0.4103 | 0.7332 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0.dev0 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
| |
