| | --- |
| | 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_376 |
| | 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_376 |
| |
|
| | 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: 0.3595 |
| | - Accuracy: 0.9851 |
| | - 1-f1: 0.8889 |
| | - 1-recall: 0.8889 |
| | - 1-precision: 0.8889 |
| | - Balanced Acc: 0.9405 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.0634 | 1.0 | 26 | 0.1150 | 0.9678 | 0.8000 | 0.9630 | 0.6842 | 0.9656 | |
| | | 0.1226 | 2.0 | 52 | 0.1786 | 0.9777 | 0.8302 | 0.8148 | 0.8462 | 0.9021 | |
| | | 0.071 | 3.0 | 78 | 0.4079 | 0.9728 | 0.7755 | 0.7037 | 0.8636 | 0.8479 | |
| | | 0.0021 | 4.0 | 104 | 0.0663 | 0.9851 | 0.9 | 1.0 | 0.8182 | 0.9920 | |
| | | 0.0014 | 5.0 | 130 | 0.2323 | 0.9827 | 0.8727 | 0.8889 | 0.8571 | 0.9391 | |
| | | 0.001 | 6.0 | 156 | 0.8937 | 0.9678 | 0.7111 | 0.5926 | 0.8889 | 0.7936 | |
| | | 0.0005 | 7.0 | 182 | 0.3595 | 0.9851 | 0.8889 | 0.8889 | 0.8889 | 0.9405 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
