| | --- |
| | 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_144 |
| | 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_144 |
| |
|
| | 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: 0.2996 |
| | - Accuracy: 0.9904 |
| | - 1-f1: 0.8224 |
| | - 1-recall: 0.7719 |
| | - 1-precision: 0.88 |
| | - Balanced Acc: 0.8844 |
| |
|
| | ## 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: 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.3457 | 1.0 | 62 | 0.2102 | 0.9838 | 0.6981 | 0.6491 | 0.7551 | 0.8214 | |
| | | 0.0606 | 2.0 | 124 | 0.2551 | 0.9868 | 0.7547 | 0.7018 | 0.8163 | 0.8485 | |
| | | 0.0061 | 3.0 | 186 | 0.2000 | 0.9889 | 0.8070 | 0.8070 | 0.8070 | 0.9006 | |
| | | 0.0005 | 4.0 | 248 | 0.2225 | 0.9924 | 0.8598 | 0.8070 | 0.92 | 0.9025 | |
| | | 0.0016 | 5.0 | 310 | 0.1739 | 0.9889 | 0.8036 | 0.7895 | 0.8182 | 0.8921 | |
| | | 0.057 | 6.0 | 372 | 0.3100 | 0.9919 | 0.8462 | 0.7719 | 0.9362 | 0.8852 | |
| | | 0.1151 | 7.0 | 434 | 0.2996 | 0.9904 | 0.8224 | 0.7719 | 0.88 | 0.8844 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
