| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/rembert |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_403 |
| 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_403 |
| |
| 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: 0.5490 |
| - Accuracy: 0.9027 |
| - 1-f1: 0.4950 |
| - 1-recall: 0.8929 |
| - 1-precision: 0.3425 |
| - Balanced Acc: 0.8980 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.1189 | 1.0 | 7 | 0.3968 | 0.9141 | 0.5161 | 0.8571 | 0.3692 | 0.8872 | |
| | 0.0679 | 2.0 | 14 | 0.6479 | 0.8721 | 0.4274 | 0.8929 | 0.2809 | 0.8819 | |
| | 0.0049 | 3.0 | 21 | 0.5490 | 0.9027 | 0.4950 | 0.8929 | 0.3425 | 0.8980 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
