| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: AnonymousCS/populism_multilingual_bert_cased_v2 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_bsample_131 |
| | 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_131 |
| | |
| | This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_cased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_cased_v2) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5460 |
| | - Accuracy: 0.8570 |
| | - 1-f1: 0.3770 |
| | - 1-recall: 0.9068 |
| | - 1-precision: 0.2380 |
| | - Balanced Acc: 0.8806 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.1914 | 1.0 | 167 | 0.9003 | 0.5692 | 0.1809 | 0.9970 | 0.0995 | 0.7724 | |
| | | 0.0654 | 2.0 | 334 | 0.7071 | 0.6974 | 0.2368 | 0.9835 | 0.1346 | 0.8333 | |
| | | 0.2182 | 3.0 | 501 | 0.6009 | 0.7773 | 0.2911 | 0.9579 | 0.1716 | 0.8631 | |
| | | 0.0871 | 4.0 | 668 | 0.4291 | 0.8584 | 0.3801 | 0.9098 | 0.2403 | 0.8828 | |
| | | 0.0217 | 5.0 | 835 | 0.6776 | 0.8031 | 0.3148 | 0.9474 | 0.1887 | 0.8716 | |
| | | 0.0717 | 6.0 | 1002 | 0.5460 | 0.8570 | 0.3770 | 0.9068 | 0.2380 | 0.8806 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
