---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_237
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_237

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: 0.5735
- Accuracy: 0.8018
- 1-f1: 0.3738
- 1-recall: 0.8
- 1-precision: 0.2439
- Balanced Acc: 0.8010

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2948        | 1.0   | 22   | 0.5296          | 0.6272   | 0.2500 | 0.84     | 0.1469      | 0.7251       |
| 0.638         | 2.0   | 44   | 0.4735          | 0.7544   | 0.3140 | 0.76     | 0.1979      | 0.7570       |
| 0.789         | 3.0   | 66   | 0.5050          | 0.8994   | 0.4848 | 0.64     | 0.3902      | 0.7801       |
| 0.1612        | 4.0   | 88   | 0.4971          | 0.8728   | 0.4557 | 0.72     | 0.3333      | 0.8025       |
| 0.6363        | 5.0   | 110  | 0.5735          | 0.8018   | 0.3738 | 0.8      | 0.2439      | 0.8010       |


### Framework versions

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