---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_247
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_247

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: 0.7165
- Accuracy: 0.8812
- 1-f1: 0.2169
- 1-recall: 0.3913
- 1-precision: 0.15
- Balanced Acc: 0.6470

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5153        | 1.0   | 35   | 0.4105          | 0.8190   | 0.2774 | 0.8261   | 0.1667      | 0.8224       |
| 0.276         | 2.0   | 70   | 0.6425          | 0.9287   | 0.0930 | 0.0870   | 0.1         | 0.5263       |
| 0.304         | 3.0   | 105  | 0.3778          | 0.8483   | 0.2385 | 0.5652   | 0.1512      | 0.7130       |
| 0.2302        | 4.0   | 140  | 0.5725          | 0.8885   | 0.2469 | 0.4348   | 0.1724      | 0.6716       |
| 0.1769        | 5.0   | 175  | 0.8414          | 0.9269   | 0.1304 | 0.1304   | 0.1304      | 0.5461       |
| 0.9633        | 6.0   | 210  | 0.7165          | 0.8812   | 0.2169 | 0.3913   | 0.15        | 0.6470       |


### Framework versions

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