| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/rembert |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_412 |
| 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_412 |
| |
| This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7918 |
| - Accuracy: 0.7150 |
| - 1-f1: 0.2162 |
| - 1-recall: 1.0 |
| - 1-precision: 0.1212 |
| - Balanced Acc: 0.8517 |
| |
| ## 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: 32 |
| - eval_batch_size: 32 |
| - 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: 20 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.0566 | 1.0 | 4 | 1.1299 | 0.6585 | 0.1871 | 1.0 | 0.1032 | 0.8223 | |
| | 0.0665 | 2.0 | 8 | 0.8764 | 0.7224 | 0.2207 | 1.0 | 0.1240 | 0.8555 | |
| | 0.0703 | 3.0 | 12 | 0.5920 | 0.8034 | 0.2857 | 1.0 | 0.1667 | 0.8977 | |
| | 0.0455 | 4.0 | 16 | 0.5149 | 0.8256 | 0.2970 | 0.9375 | 0.1765 | 0.8792 | |
| | 0.0567 | 5.0 | 20 | 0.9592 | 0.7076 | 0.2119 | 1.0 | 0.1185 | 0.8478 | |
| | 0.025 | 6.0 | 24 | 0.7918 | 0.7150 | 0.2162 | 1.0 | 0.1212 | 0.8517 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
