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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_248
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_248
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: 0.2247
- Accuracy: 0.9833
- 1-f1: 0.7481
- 1-recall: 0.8596
- 1-precision: 0.6622
- Balanced Acc: 0.9233
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4461 | 1.0 | 124 | 0.3656 | 0.9737 | 0.3953 | 0.2982 | 0.5862 | 0.6460 |
| 0.1764 | 2.0 | 248 | 0.3212 | 0.9722 | 0.4211 | 0.3509 | 0.5263 | 0.6707 |
| 0.1825 | 3.0 | 372 | 0.2600 | 0.9615 | 0.4722 | 0.5965 | 0.3908 | 0.7844 |
| 0.0418 | 4.0 | 496 | 0.3632 | 0.9787 | 0.5532 | 0.4561 | 0.7027 | 0.7252 |
| 0.0178 | 5.0 | 620 | 0.1983 | 0.9803 | 0.6929 | 0.7719 | 0.6286 | 0.8792 |
| 0.0888 | 6.0 | 744 | 0.1902 | 0.9747 | 0.6622 | 0.8596 | 0.5385 | 0.9189 |
| 0.001 | 7.0 | 868 | 0.2618 | 0.9863 | 0.7429 | 0.6842 | 0.8125 | 0.8398 |
| 0.0388 | 8.0 | 992 | 0.1879 | 0.9838 | 0.7576 | 0.8772 | 0.6667 | 0.9321 |
| 0.0127 | 9.0 | 1116 | 0.2108 | 0.9904 | 0.8319 | 0.8246 | 0.8393 | 0.9099 |
| 0.0557 | 10.0 | 1240 | 0.2210 | 0.9894 | 0.8235 | 0.8596 | 0.7903 | 0.9264 |
| 0.0004 | 11.0 | 1364 | 0.2247 | 0.9833 | 0.7481 | 0.8596 | 0.6622 | 0.9233 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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