| --- |
| 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_028 |
| 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_028 |
|
|
| 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: 0.1975 |
| - Accuracy: 0.9377 |
| - 1-f1: 0.5366 |
| - 1-recall: 0.9167 |
| - 1-precision: 0.3793 |
| - Balanced Acc: 0.9276 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.0595 | 1.0 | 20 | 0.2141 | 0.9705 | 0.6087 | 0.5833 | 0.6364 | 0.7848 | |
| | 0.2489 | 2.0 | 40 | 0.2365 | 0.9803 | 0.7 | 0.5833 | 0.875 | 0.7900 | |
| | 0.0331 | 3.0 | 60 | 0.1314 | 0.9443 | 0.5405 | 0.8333 | 0.4 | 0.8911 | |
| | 0.0369 | 4.0 | 80 | 0.1809 | 0.9672 | 0.6667 | 0.8333 | 0.5556 | 0.9030 | |
| | 0.0328 | 5.0 | 100 | 0.1975 | 0.9377 | 0.5366 | 0.9167 | 0.3793 | 0.9276 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0.dev0 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
| |
