| | --- |
| | 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_bsample_355 |
| | 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_bsample_355 |
| | |
| | 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: 1.1758 |
| | - Accuracy: 0.7216 |
| | - 1-f1: 0.2022 |
| | - 1-recall: 0.8182 |
| | - 1-precision: 0.1154 |
| | - Balanced Acc: 0.7677 |
| | |
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.1308 | 1.0 | 7 | 1.0861 | 0.6902 | 0.1939 | 0.8636 | 0.1092 | 0.7730 | |
| | | 0.0159 | 2.0 | 14 | 1.0770 | 0.6941 | 0.1959 | 0.8636 | 0.1105 | 0.7751 | |
| | | 0.044 | 3.0 | 21 | 0.9541 | 0.7275 | 0.2147 | 0.8636 | 0.1226 | 0.7925 | |
| | | 0.0138 | 4.0 | 28 | 1.2729 | 0.6294 | 0.1747 | 0.9091 | 0.0966 | 0.7629 | |
| | | 0.0277 | 5.0 | 35 | 0.9506 | 0.7608 | 0.2278 | 0.8182 | 0.1324 | 0.7882 | |
| | | 0.0116 | 6.0 | 42 | 0.9691 | 0.7706 | 0.2353 | 0.8182 | 0.1374 | 0.7933 | |
| | | 0.0169 | 7.0 | 49 | 1.1758 | 0.7216 | 0.2022 | 0.8182 | 0.1154 | 0.7677 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
