| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: AnonymousCS/populism_multilingual_bert_cased_v2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: populism_classifier_134 |
| 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_134 |
|
|
| This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_cased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_cased_v2) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3076 |
| - Accuracy: 0.9861 |
| - 1-f1: 0.4681 |
| - 1-recall: 0.3667 |
| - 1-precision: 0.6471 |
| - Balanced Acc: 0.6816 |
|
|
| ## Model description |
|
|
| More information needed |
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| ## Intended uses & limitations |
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| More information needed |
|
|
| ## Training and evaluation data |
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| More information needed |
|
|
| ## Training procedure |
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| ### 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 |
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|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | 0.3127 | 1.0 | 57 | 0.1542 | 0.9861 | 0.6154 | 0.6667 | 0.5714 | 0.8291 | |
| | 0.0751 | 2.0 | 114 | 0.1259 | 0.9705 | 0.4646 | 0.7667 | 0.3333 | 0.8703 | |
| | 0.0661 | 3.0 | 171 | 0.1418 | 0.9772 | 0.5060 | 0.7 | 0.3962 | 0.8409 | |
| | 0.0165 | 4.0 | 228 | 0.3076 | 0.9861 | 0.4681 | 0.3667 | 0.6471 | 0.6816 | |
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| ### Framework versions |
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|
| - Transformers 4.46.3 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
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|
