---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_098
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# populism_classifier_098

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4342
- Accuracy: 0.8283
- 1-f1: 0.5405
- 1-recall: 0.8
- 1-precision: 0.4082
- Balanced Acc: 0.8162

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3996        | 1.0   | 7    | 0.4033          | 0.7576   | 0.4894 | 0.92     | 0.3333      | 0.8271       |
| 0.3985        | 2.0   | 14   | 0.5162          | 0.8434   | 0.5373 | 0.72     | 0.4286      | 0.7906       |
| 0.322         | 3.0   | 21   | 0.3941          | 0.7677   | 0.5106 | 0.96     | 0.3478      | 0.8499       |
| 0.2893        | 4.0   | 28   | 0.4185          | 0.8333   | 0.5352 | 0.76     | 0.4130      | 0.8020       |
| 0.2652        | 5.0   | 35   | 0.4342          | 0.8283   | 0.5405 | 0.8      | 0.4082      | 0.8162       |


### Framework versions

- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4