---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_113
  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_113

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8409
- Accuracy: 0.9498
- 1-f1: 0.0714
- 1-recall: 0.0385
- 1-precision: 0.5
- Balanced Acc: 0.5182

## 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: 16
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1455        | 1.0   | 130  | 0.8370          | 0.9208   | 0.3279 | 0.3846   | 0.2857      | 0.6669       |
| 0.049         | 2.0   | 260  | 0.6910          | 0.9498   | 0.0    | 0.0      | 0.0         | 0.5          |
| 1.189         | 3.0   | 390  | 0.5277          | 0.9344   | 0.3704 | 0.3846   | 0.3571      | 0.6740       |
| 0.5874        | 4.0   | 520  | 0.6155          | 0.9517   | 0.4186 | 0.3462   | 0.5294      | 0.6649       |
| 1.6558        | 5.0   | 650  | 0.8409          | 0.9498   | 0.0714 | 0.0385   | 0.5         | 0.5182       |


### Framework versions

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