---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_259
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_259

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: 0.6682
- Accuracy: 0.9445
- 1-f1: 0.5316
- 1-recall: 0.6
- 1-precision: 0.4773
- Balanced Acc: 0.7818

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3455        | 1.0   | 42   | 0.2947          | 0.9310   | 0.5    | 0.6571   | 0.4035      | 0.8017       |
| 0.2899        | 2.0   | 84   | 0.2864          | 0.8966   | 0.448  | 0.8      | 0.3111      | 0.8509       |
| 0.087         | 3.0   | 126  | 0.3834          | 0.9025   | 0.4348 | 0.7143   | 0.3125      | 0.8136       |
| 0.0262        | 4.0   | 168  | 0.6384          | 0.9415   | 0.5063 | 0.5714   | 0.4545      | 0.7667       |
| 0.0966        | 5.0   | 210  | 0.6682          | 0.9445   | 0.5316 | 0.6      | 0.4773      | 0.7818       |


### Framework versions

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