---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_085
  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_085

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: 0.5746
- Accuracy: 0.9716
- 1-f1: 0.6452
- 1-recall: 0.625
- 1-precision: 0.6667
- Balanced Acc: 0.8058

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2135        | 1.0   | 13   | 0.1302          | 0.9716   | 0.7179 | 0.875    | 0.6087      | 0.9254       |
| 0.0919        | 2.0   | 26   | 0.1059          | 0.9742   | 0.75   | 0.9375   | 0.625       | 0.9567       |
| 0.1426        | 3.0   | 39   | 0.1056          | 0.9716   | 0.7179 | 0.875    | 0.6087      | 0.9254       |
| 0.0322        | 4.0   | 52   | 0.1791          | 0.9742   | 0.7222 | 0.8125   | 0.65        | 0.8968       |
| 0.0149        | 5.0   | 65   | 0.5746          | 0.9716   | 0.6452 | 0.625    | 0.6667      | 0.8058       |


### Framework versions

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