---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_252
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_bsample_252

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: 0.5679
- Accuracy: 0.8260
- 1-f1: 0.4034
- 1-recall: 1.0
- 1-precision: 0.2526
- Balanced Acc: 0.9076

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0442        | 1.0   | 6    | 0.4997          | 0.8137   | 0.3770 | 0.9583   | 0.2347      | 0.8815       |
| 0.1751        | 2.0   | 12   | 0.6237          | 0.8064   | 0.3780 | 1.0      | 0.2330      | 0.8971       |
| 0.0456        | 3.0   | 18   | 0.3618          | 0.875    | 0.4848 | 1.0      | 0.32        | 0.9336       |
| 0.0191        | 4.0   | 24   | 0.4841          | 0.8382   | 0.4211 | 1.0      | 0.2667      | 0.9141       |
| 0.0157        | 5.0   | 30   | 0.5679          | 0.8260   | 0.4034 | 1.0      | 0.2526      | 0.9076       |


### Framework versions

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