---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_249
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_249

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: 0.5324
- Accuracy: 0.9158
- 1-f1: 0.5429
- 1-recall: 0.7308
- 1-precision: 0.4318
- Balanced Acc: 0.8301

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5015        | 1.0   | 24   | 0.5517          | 0.8368   | 0.4259 | 0.8846   | 0.2805      | 0.8590       |
| 0.3587        | 2.0   | 48   | 0.3700          | 0.9105   | 0.5641 | 0.8462   | 0.4231      | 0.8807       |
| 0.1572        | 3.0   | 72   | 0.3893          | 0.9      | 0.5128 | 0.7692   | 0.3846      | 0.8394       |
| 0.1018        | 4.0   | 96   | 0.4481          | 0.9316   | 0.5937 | 0.7308   | 0.5         | 0.8385       |
| 0.1103        | 5.0   | 120  | 0.5324          | 0.9158   | 0.5429 | 0.7308   | 0.4318      | 0.8301       |


### Framework versions

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