| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: AnonymousCS/populism_english_bert_large_uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_383 |
| 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_383 |
|
|
| This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_large_uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3749 |
| - Accuracy: 0.9870 |
| - 1-f1: 0.7879 |
| - 1-recall: 0.6842 |
| - 1-precision: 0.9286 |
| - Balanced Acc: 0.8411 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.0931 | 1.0 | 34 | 0.1639 | 0.9833 | 0.7568 | 0.7368 | 0.7778 | 0.8646 | |
| | 0.0131 | 2.0 | 68 | 0.1420 | 0.9833 | 0.7805 | 0.8421 | 0.7273 | 0.9153 | |
| | 0.4398 | 3.0 | 102 | 0.1904 | 0.9907 | 0.8649 | 0.8421 | 0.8889 | 0.9191 | |
| | 0.0105 | 4.0 | 136 | 0.2434 | 0.9870 | 0.8000 | 0.7368 | 0.875 | 0.8665 | |
| | 0.0003 | 5.0 | 170 | 0.3749 | 0.9870 | 0.7879 | 0.6842 | 0.9286 | 0.8411 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
|
|
