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library_name: transformers
license: mit
base_model: AnonymousCS/populism_xlmr_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_196
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_196
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: 0.5068
- Accuracy: 0.9733
- 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-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7368 | 1.0 | 38 | 0.7313 | 0.0267 | 0.0521 | 1.0 | 0.0267 | 0.5 |
| 0.6993 | 2.0 | 76 | 0.6730 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.677 | 3.0 | 114 | 0.6288 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6889 | 4.0 | 152 | 0.5966 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7637 | 5.0 | 190 | 0.5709 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6929 | 6.0 | 228 | 0.5567 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7174 | 7.0 | 266 | 0.5389 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6366 | 8.0 | 304 | 0.5298 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6762 | 9.0 | 342 | 0.5243 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7455 | 10.0 | 380 | 0.5184 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7218 | 11.0 | 418 | 0.5129 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6597 | 12.0 | 456 | 0.5100 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6704 | 13.0 | 494 | 0.5084 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6379 | 14.0 | 532 | 0.5072 | 0.9733 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7379 | 15.0 | 570 | 0.5068 | 0.9733 | 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
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