| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/rembert |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_393 |
| | 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_393 |
| |
|
| | This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8732 |
| | - Accuracy: 0.3254 |
| | - 1-f1: 0.1163 |
| | - 1-recall: 0.6 |
| | - 1-precision: 0.0644 |
| | - Balanced Acc: 0.4518 |
| |
|
| | ## 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: 16 |
| | - 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 |
| | - lr_scheduler_warmup_ratio: 0.06 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.8611 | 1.0 | 85 | 0.7354 | 0.0917 | 0.1401 | 1.0 | 0.0753 | 0.5096 | |
| | | 0.7404 | 2.0 | 170 | 0.8947 | 0.0799 | 0.1385 | 1.0 | 0.0744 | 0.5032 | |
| | | 0.7009 | 3.0 | 255 | 0.6590 | 0.2337 | 0.1618 | 1.0 | 0.0880 | 0.5863 | |
| | | 0.4348 | 4.0 | 340 | 0.7461 | 0.2101 | 0.1577 | 1.0 | 0.0856 | 0.5735 | |
| | | 0.8032 | 5.0 | 425 | 0.8210 | 0.2515 | 0.1538 | 0.92 | 0.0839 | 0.5590 | |
| | | 0.4858 | 6.0 | 510 | 0.7814 | 0.2692 | 0.1453 | 0.84 | 0.0795 | 0.5318 | |
| | | 0.6308 | 7.0 | 595 | 0.9987 | 0.0740 | 0.1377 | 1.0 | 0.0740 | 0.5 | |
| | | 0.8048 | 8.0 | 680 | 0.8732 | 0.3254 | 0.1163 | 0.6 | 0.0644 | 0.4518 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
