---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_124
  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_bsample_124

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: 1.1470
- Accuracy: 0.5407
- 1-f1: 0.3514
- 1-recall: 0.8966
- 1-precision: 0.2185
- Balanced Acc: 0.6899

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.6081        | 1.0   | 9    | 1.1302          | 0.1388   | 0.2437 | 1.0      | 0.1388      | 0.5          |
| 0.5201        | 2.0   | 18   | 1.4976          | 0.1388   | 0.2437 | 1.0      | 0.1388      | 0.5          |
| 0.4716        | 3.0   | 27   | 0.8346          | 0.4498   | 0.3195 | 0.9310   | 0.1929      | 0.6516       |
| 0.4272        | 4.0   | 36   | 1.5418          | 0.2536   | 0.2642 | 0.9655   | 0.1530      | 0.5522       |
| 0.3513        | 5.0   | 45   | 1.1470          | 0.5407   | 0.3514 | 0.8966   | 0.2185      | 0.6899       |


### Framework versions

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