| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/rembert |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_391 |
| | 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_391 |
| |
|
| | 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: 1.3230 |
| | - Accuracy: 0.9523 |
| | - 1-f1: 0.0 |
| | - 1-recall: 0.0 |
| | - 1-precision: 0.0 |
| | - Balanced Acc: 0.5 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:| |
| | | 0.0128 | 1.0 | 3484 | 0.9344 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.9515 | 2.0 | 6968 | 0.8225 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.6456 | 3.0 | 10452 | 0.8839 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.053 | 4.0 | 13936 | 0.9211 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.5498 | 5.0 | 17420 | 0.9413 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.218 | 6.0 | 20904 | 0.8088 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 1.9402 | 7.0 | 24388 | 1.1587 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.6771 | 8.0 | 27872 | 1.2072 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.6533 | 9.0 | 31356 | 1.4121 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.8778 | 10.0 | 34840 | 1.2411 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | | 0.4423 | 11.0 | 38324 | 1.3230 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| | |
