| --- |
| 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_048 |
| 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_048 |
| |
| 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: 0.6899 |
| - Accuracy: 0.8010 |
| - 1-f1: 0.2569 |
| - 1-recall: 0.875 |
| - 1-precision: 0.1505 |
| - Balanced Acc: 0.8365 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.0677 | 1.0 | 4 | 0.9887 | 0.7125 | 0.2148 | 1.0 | 0.1203 | 0.8504 | |
| | 0.1969 | 2.0 | 8 | 0.5845 | 0.8428 | 0.3043 | 0.875 | 0.1842 | 0.8582 | |
| | 0.0666 | 3.0 | 12 | 0.6913 | 0.7838 | 0.2542 | 0.9375 | 0.1471 | 0.8575 | |
| | 0.0131 | 4.0 | 16 | 0.5660 | 0.8477 | 0.2955 | 0.8125 | 0.1806 | 0.8308 | |
| | 0.0847 | 5.0 | 20 | 0.5668 | 0.8698 | 0.3117 | 0.75 | 0.1967 | 0.8123 | |
| | 0.0096 | 6.0 | 24 | 0.6899 | 0.8010 | 0.2569 | 0.875 | 0.1505 | 0.8365 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
