| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-multilingual-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - recall |
| - precision |
| model-index: |
| - name: populism_model26 |
| 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_model26 |
| |
| This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5158 |
| - Accuracy: 0.8868 |
| - F1: 0.5169 |
| - Recall: 0.7188 |
| - Precision: 0.4035 |
| |
| ## 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 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: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
| | No log | 1.0 | 12 | 0.4692 | 0.8526 | 0.4717 | 0.7812 | 0.3378 | |
| | No log | 2.0 | 24 | 0.6293 | 0.9237 | 0.5538 | 0.5625 | 0.5455 | |
| | No log | 3.0 | 36 | 0.4847 | 0.8921 | 0.5287 | 0.7188 | 0.4182 | |
| | No log | 4.0 | 48 | 0.5058 | 0.8842 | 0.5111 | 0.7188 | 0.3966 | |
| | 0.3726 | 5.0 | 60 | 0.5158 | 0.8868 | 0.5169 | 0.7188 | 0.4035 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.1 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
