| | --- |
| | 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_378 |
| | 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_378 |
| |
|
| | 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: 0.2057 |
| | - Accuracy: 0.9889 |
| | - 1-f1: 0.8103 |
| | - 1-recall: 0.8246 |
| | - 1-precision: 0.7966 |
| | - Balanced Acc: 0.9092 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.0473 | 1.0 | 124 | 0.1713 | 0.9559 | 0.5246 | 0.8421 | 0.3810 | 0.9007 | |
| | | 0.0268 | 2.0 | 248 | 0.1379 | 0.9863 | 0.7523 | 0.7193 | 0.7885 | 0.8568 | |
| | | 0.0541 | 3.0 | 372 | 0.1311 | 0.9818 | 0.7353 | 0.8772 | 0.6329 | 0.9310 | |
| | | 0.0025 | 4.0 | 496 | 0.1546 | 0.9934 | 0.8829 | 0.8596 | 0.9074 | 0.9285 | |
| | | 0.0003 | 5.0 | 620 | 0.1866 | 0.9919 | 0.8596 | 0.8596 | 0.8596 | 0.9277 | |
| | | 0.0005 | 6.0 | 744 | 0.2057 | 0.9889 | 0.8103 | 0.8246 | 0.7966 | 0.9092 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
