| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: AnonymousCS/populism_english_bert_large_cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_326 |
| | 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_326 |
| |
|
| | This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_cased](https://huggingface.co/AnonymousCS/populism_english_bert_large_cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2419 |
| | - Accuracy: 0.9929 |
| | - 1-f1: 0.8727 |
| | - 1-recall: 0.8421 |
| | - 1-precision: 0.9057 |
| | - Balanced Acc: 0.9197 |
| |
|
| | ## 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 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.1833 | 1.0 | 124 | 0.1742 | 0.9590 | 0.5091 | 0.7368 | 0.3889 | 0.8512 | |
| | | 0.1031 | 2.0 | 248 | 0.1743 | 0.9833 | 0.7130 | 0.7193 | 0.7069 | 0.8552 | |
| | | 0.0298 | 3.0 | 372 | 0.1666 | 0.9848 | 0.7458 | 0.7719 | 0.7213 | 0.8815 | |
| | | 0.0065 | 4.0 | 496 | 0.2741 | 0.9889 | 0.78 | 0.6842 | 0.9070 | 0.8411 | |
| | | 0.0008 | 5.0 | 620 | 0.1625 | 0.9899 | 0.8246 | 0.8246 | 0.8246 | 0.9097 | |
| | | 0.0109 | 6.0 | 744 | 0.2292 | 0.9924 | 0.8649 | 0.8421 | 0.8889 | 0.9195 | |
| | | 0.0002 | 7.0 | 868 | 0.2173 | 0.9904 | 0.8348 | 0.8421 | 0.8276 | 0.9184 | |
| | | 0.0007 | 8.0 | 992 | 0.2419 | 0.9929 | 0.8727 | 0.8421 | 0.9057 | 0.9197 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
