---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_238
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_238

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: 0.5121
- Accuracy: 0.9488
- 1-f1: 0.0980
- 1-recall: 0.1667
- 1-precision: 0.0694
- Balanced Acc: 0.5644

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5777        | 1.0   | 113  | 0.3860          | 0.9833   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.5144        | 2.0   | 226  | 0.3376          | 0.9833   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.7421        | 3.0   | 339  | 0.4980          | 0.9833   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.1208        | 4.0   | 452  | 0.3496          | 0.9711   | 0.0714 | 0.0667   | 0.0769      | 0.5265       |
| 0.2666        | 5.0   | 565  | 0.3291          | 0.9555   | 0.0698 | 0.1      | 0.0536      | 0.5350       |
| 0.2244        | 6.0   | 678  | 0.5091          | 0.9822   | 0.0588 | 0.0333   | 0.25        | 0.5158       |
| 0.3592        | 7.0   | 791  | 0.5127          | 0.9777   | 0.0909 | 0.0667   | 0.1429      | 0.5299       |
| 0.1585        | 8.0   | 904  | 0.5121          | 0.9488   | 0.0980 | 0.1667   | 0.0694      | 0.5644       |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3