| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: AnonymousCS/populism_xlmr_base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: populism_classifier_bsample_199 |
| | 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_199 |
| | |
| | This model is a fine-tuned version of [AnonymousCS/populism_xlmr_base](https://huggingface.co/AnonymousCS/populism_xlmr_base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.0122 |
| | - Accuracy: 0.0431 |
| | - 1-f1: 0.0827 |
| | - 1-recall: 1.0 |
| | - 1-precision: 0.0431 |
| | - 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-06 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - 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: 15 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
| | | 0.6913 | 1.0 | 13 | 1.0669 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.5557 | 2.0 | 26 | 1.0532 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.6521 | 3.0 | 39 | 1.0450 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.7205 | 4.0 | 52 | 1.0423 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.7253 | 5.0 | 65 | 1.0377 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.8518 | 6.0 | 78 | 1.0322 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.7362 | 7.0 | 91 | 1.0268 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.7633 | 8.0 | 104 | 1.0231 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.6517 | 9.0 | 117 | 1.0195 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.6334 | 10.0 | 130 | 1.0167 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.68 | 11.0 | 143 | 1.0149 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.7392 | 12.0 | 156 | 1.0131 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.6501 | 13.0 | 169 | 1.0131 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.7579 | 14.0 | 182 | 1.0131 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| | | 0.6863 | 15.0 | 195 | 1.0122 | 0.0431 | 0.0827 | 1.0 | 0.0431 | 0.5 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.4.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
