| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: AnonymousCS/populism_xlmr_base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_bsample_191 |
| | 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_191 |
| | |
| | This model is a fine-tuned version of [AnonymousCS/populism_xlmr_base](https://huggingface.co/AnonymousCS/populism_xlmr_base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8839 |
| | - Accuracy: 0.0552 |
| | - 1-f1: 0.1047 |
| | - 1-recall: 1.0 |
| | - 1-precision: 0.0552 |
| | - Balanced Acc: 0.5 |
| | |
| | ## 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-06 |
| | - 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 |
| | - lr_scheduler_warmup_ratio: 0.06 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.7631 | 1.0 | 14 | 1.0478 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.9633 | 2.0 | 28 | 1.0210 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.5929 | 3.0 | 42 | 0.9960 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.746 | 4.0 | 56 | 0.9764 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.7519 | 5.0 | 70 | 0.9590 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.8273 | 6.0 | 84 | 0.9430 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.7775 | 7.0 | 98 | 0.9296 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.7445 | 8.0 | 112 | 0.9189 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.7983 | 9.0 | 126 | 0.9096 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.6858 | 10.0 | 140 | 0.9034 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.8285 | 11.0 | 154 | 0.8959 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.9547 | 12.0 | 168 | 0.8905 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.6147 | 13.0 | 182 | 0.8866 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.7742 | 14.0 | 196 | 0.8848 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| | | 0.6978 | 15.0 | 210 | 0.8839 | 0.0552 | 0.1047 | 1.0 | 0.0552 | 0.5 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
