| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/rembert |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_415 |
| 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_415 |
| |
| 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: 0.7123 |
| - Accuracy: 0.8870 |
| - 1-f1: 0.4219 |
| - 1-recall: 0.7297 |
| - 1-precision: 0.2967 |
| - Balanced Acc: 0.8131 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.276 | 1.0 | 9 | 0.9888 | 0.5252 | 0.1880 | 0.9730 | 0.1040 | 0.7357 | |
| | 0.1101 | 2.0 | 18 | 0.6875 | 0.7298 | 0.2834 | 0.9459 | 0.1667 | 0.8314 | |
| | 0.1145 | 3.0 | 27 | 0.6851 | 0.8015 | 0.3158 | 0.8108 | 0.1961 | 0.8059 | |
| | 0.0293 | 4.0 | 36 | 0.7586 | 0.8336 | 0.3550 | 0.8108 | 0.2273 | 0.8229 | |
| | 0.0461 | 5.0 | 45 | 0.6599 | 0.8901 | 0.4098 | 0.6757 | 0.2941 | 0.7893 | |
| | 0.0044 | 6.0 | 54 | 0.6568 | 0.8824 | 0.4031 | 0.7027 | 0.2826 | 0.7980 | |
| | 0.0082 | 7.0 | 63 | 0.7689 | 0.8489 | 0.3694 | 0.7838 | 0.2417 | 0.8183 | |
| | 0.0542 | 8.0 | 72 | 0.7123 | 0.8870 | 0.4219 | 0.7297 | 0.2967 | 0.8131 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
