| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-multilingual-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_bsample_032 |
| 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_032 |
| |
| This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6975 |
| - Accuracy: 0.8125 |
| - 1-f1: 0.3851 |
| - 1-recall: 0.9394 |
| - 1-precision: 0.2422 |
| - Balanced Acc: 0.8717 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.0138 | 1.0 | 8 | 0.7747 | 0.75 | 0.3265 | 0.9697 | 0.1963 | 0.8525 | |
| | 0.0265 | 2.0 | 16 | 0.7617 | 0.7803 | 0.3409 | 0.9091 | 0.2098 | 0.8404 | |
| | 0.0489 | 3.0 | 24 | 0.6448 | 0.8598 | 0.3934 | 0.7273 | 0.2697 | 0.7980 | |
| | 0.0109 | 4.0 | 32 | 0.7026 | 0.7973 | 0.3669 | 0.9394 | 0.2279 | 0.8636 | |
| | 0.0057 | 5.0 | 40 | 0.6975 | 0.8125 | 0.3851 | 0.9394 | 0.2422 | 0.8717 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
