| | --- |
| | 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_364 |
| | 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_364 |
| | |
| | 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: 0.9024 |
| | - Accuracy: 0.7466 |
| | - 1-f1: 0.2697 |
| | - 1-recall: 0.8889 |
| | - 1-precision: 0.1589 |
| | - Balanced Acc: 0.8138 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.0753 | 1.0 | 8 | 1.3891 | 0.5029 | 0.1694 | 0.9630 | 0.0929 | 0.7202 | |
| | | 0.0897 | 2.0 | 16 | 0.9531 | 0.6628 | 0.2242 | 0.9259 | 0.1276 | 0.7870 | |
| | | 0.0263 | 3.0 | 24 | 0.8116 | 0.7427 | 0.2584 | 0.8519 | 0.1523 | 0.7942 | |
| | | 0.0245 | 4.0 | 32 | 1.0668 | 0.6647 | 0.2182 | 0.8889 | 0.1244 | 0.7706 | |
| | | 0.0491 | 5.0 | 40 | 0.7283 | 0.7973 | 0.3067 | 0.8519 | 0.1870 | 0.8230 | |
| | | 0.0139 | 6.0 | 48 | 0.9519 | 0.7290 | 0.2567 | 0.8889 | 0.15 | 0.8045 | |
| | | 0.0091 | 7.0 | 56 | 0.9024 | 0.7466 | 0.2697 | 0.8889 | 0.1589 | 0.8138 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
