| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: AnonymousCS/populism_english_bert_base_cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_288 |
| 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_288 |
|
|
| This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_cased](https://huggingface.co/AnonymousCS/populism_english_bert_base_cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5475 |
| - Accuracy: 0.8787 |
| - 1-f1: 0.1778 |
| - 1-recall: 0.3333 |
| - 1-precision: 0.1212 |
| - Balanced Acc: 0.6172 |
|
|
| ## 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: 128 |
| - eval_batch_size: 128 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.471 | 1.0 | 10 | 0.5098 | 0.9443 | 0.1053 | 0.0833 | 0.1429 | 0.5314 | |
| | 0.4628 | 2.0 | 20 | 0.4957 | 0.8295 | 0.1875 | 0.5 | 0.1154 | 0.6715 | |
| | 0.5794 | 3.0 | 30 | 0.6392 | 0.9574 | 0.0 | 0.0 | 0.0 | 0.4983 | |
| | 0.4081 | 4.0 | 40 | 0.5475 | 0.8787 | 0.1778 | 0.3333 | 0.1212 | 0.6172 | |
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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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|
