---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_130
  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_130

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: 1.8753
- Accuracy: 0.9371
- 1-f1: 0.4918
- 1-recall: 0.4839
- 1-precision: 0.5
- Balanced Acc: 0.7257

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0094        | 1.0   | 124  | 1.3323          | 0.9452   | 0.3077 | 0.1935   | 0.75        | 0.5946       |
| 0.4481        | 2.0   | 248  | 1.0891          | 0.9412   | 0.4912 | 0.4516   | 0.5385      | 0.7128       |
| 0.0075        | 3.0   | 372  | 0.8231          | 0.9473   | 0.5806 | 0.5806   | 0.5806      | 0.7763       |
| 0.0002        | 4.0   | 496  | 1.1753          | 0.9067   | 0.4651 | 0.6452   | 0.3636      | 0.7847       |
| 0.0001        | 5.0   | 620  | 1.8753          | 0.9371   | 0.4918 | 0.4839   | 0.5         | 0.7257       |


### Framework versions

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