---
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