| --- |
| 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_352 |
| 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_352 |
|
|
| 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: 0.1382 |
| - Accuracy: 0.9939 |
| - 1-f1: 0.8929 |
| - 1-recall: 0.8772 |
| - 1-precision: 0.9091 |
| - Balanced Acc: 0.9373 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.188 | 1.0 | 124 | 0.1878 | 0.96 | 0.5269 | 0.7719 | 0.4 | 0.8688 | |
| | 0.0717 | 2.0 | 248 | 0.1507 | 0.9635 | 0.5663 | 0.8246 | 0.4312 | 0.8961 | |
| | 0.0532 | 3.0 | 372 | 0.1856 | 0.9792 | 0.6555 | 0.6842 | 0.6290 | 0.8361 | |
| | 0.0114 | 4.0 | 496 | 0.1190 | 0.9818 | 0.7391 | 0.8947 | 0.6296 | 0.9395 | |
| | 0.001 | 5.0 | 620 | 0.1292 | 0.9833 | 0.7660 | 0.9474 | 0.6429 | 0.9659 | |
| | 0.0012 | 6.0 | 744 | 0.1184 | 0.9899 | 0.8333 | 0.8772 | 0.7937 | 0.9352 | |
| | 0.0013 | 7.0 | 868 | 0.1127 | 0.9853 | 0.7852 | 0.9298 | 0.6795 | 0.9584 | |
| | 0.0005 | 8.0 | 992 | 0.1341 | 0.9853 | 0.7852 | 0.9298 | 0.6795 | 0.9584 | |
| | 0.0003 | 9.0 | 1116 | 0.2046 | 0.9909 | 0.8393 | 0.8246 | 0.8545 | 0.9102 | |
| | 0.0002 | 10.0 | 1240 | 0.1382 | 0.9939 | 0.8929 | 0.8772 | 0.9091 | 0.9373 | |
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| ### Framework versions |
|
|
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
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|
