---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_129
  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_129

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: 0.6651
- Accuracy: 0.7145
- 1-f1: 0.2667
- 1-recall: 0.9189
- 1-precision: 0.1560
- Balanced Acc: 0.8106

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7601        | 1.0   | 18   | 0.7731          | 0.2870   | 0.1304 | 0.9459   | 0.07        | 0.5968       |
| 0.714         | 2.0   | 36   | 0.8593          | 0.2580   | 0.1290 | 0.9730   | 0.0691      | 0.5941       |
| 0.7266        | 3.0   | 54   | 0.4779          | 0.9084   | 0.3023 | 0.3514   | 0.2653      | 0.6465       |
| 0.5782        | 4.0   | 72   | 0.5362          | 0.7282   | 0.2521 | 0.8108   | 0.1493      | 0.7671       |
| 0.1827        | 5.0   | 90   | 0.6651          | 0.7145   | 0.2667 | 0.9189   | 0.1560      | 0.8106       |


### Framework versions

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