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library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_256
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_256
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8871
- Accuracy: 0.9267
- 1-f1: 0.2222
- 1-recall: 0.25
- 1-precision: 0.2
- Balanced Acc: 0.6031
## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.681 | 1.0 | 24 | 0.6077 | 0.9581 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.2828 | 2.0 | 48 | 0.6075 | 0.9110 | 0.0556 | 0.0625 | 0.05 | 0.5053 |
| 0.3429 | 3.0 | 72 | 0.5537 | 0.8822 | 0.2623 | 0.5 | 0.1778 | 0.6995 |
| 0.4176 | 4.0 | 96 | 0.5570 | 0.8613 | 0.2535 | 0.5625 | 0.1636 | 0.7184 |
| 0.3116 | 5.0 | 120 | 0.5469 | 0.8822 | 0.2373 | 0.4375 | 0.1628 | 0.6696 |
| 0.3514 | 6.0 | 144 | 0.8624 | 0.9450 | 0.2222 | 0.1875 | 0.2727 | 0.5828 |
| 0.112 | 7.0 | 168 | 0.9762 | 0.9476 | 0.2308 | 0.1875 | 0.3 | 0.5842 |
| 0.1278 | 8.0 | 192 | 0.8871 | 0.9267 | 0.2222 | 0.25 | 0.2 | 0.6031 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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