| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: AnonymousCS/populism_english_bert_base_uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_357 |
| | 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_357 |
| |
|
| | This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1747 |
| | - Accuracy: 0.9814 |
| | - 1-f1: 0.7727 |
| | - 1-recall: 0.8947 |
| | - 1-precision: 0.68 |
| | - Balanced Acc: 0.9397 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.2952 | 1.0 | 34 | 0.1568 | 0.9796 | 0.7556 | 0.8947 | 0.6538 | 0.9387 | |
| | | 0.0461 | 2.0 | 68 | 0.2817 | 0.9721 | 0.5714 | 0.5263 | 0.625 | 0.7574 | |
| | | 0.0239 | 3.0 | 102 | 0.1524 | 0.9777 | 0.7273 | 0.8421 | 0.64 | 0.9124 | |
| | | 0.0233 | 4.0 | 136 | 0.1413 | 0.9703 | 0.6800 | 0.8947 | 0.5484 | 0.9339 | |
| | | 0.0005 | 5.0 | 170 | 0.3419 | 0.9777 | 0.6667 | 0.6316 | 0.7059 | 0.8110 | |
| | | 0.0005 | 6.0 | 204 | 0.1759 | 0.9814 | 0.7727 | 0.8947 | 0.68 | 0.9397 | |
| | | 0.0004 | 7.0 | 238 | 0.1747 | 0.9814 | 0.7727 | 0.8947 | 0.68 | 0.9397 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
