---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_127
  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_127

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: 0.6716
- Accuracy: 0.7125
- 1-f1: 0.3472
- 1-recall: 1.0
- 1-precision: 0.2101
- Balanced Acc: 0.8444

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5953        | 1.0   | 11   | 1.0086          | 0.0765   | 0.1420 | 1.0      | 0.0765      | 0.5          |
| 0.3976        | 2.0   | 22   | 1.1555          | 0.1009   | 0.1453 | 1.0      | 0.0784      | 0.5132       |
| 0.5518        | 3.0   | 33   | 0.5954          | 0.7798   | 0.3898 | 0.92     | 0.2473      | 0.8441       |
| 0.2545        | 4.0   | 44   | 0.6053          | 0.7554   | 0.3846 | 1.0      | 0.2381      | 0.8675       |
| 0.4115        | 5.0   | 55   | 0.5874          | 0.7676   | 0.3871 | 0.96     | 0.2424      | 0.8558       |
| 0.0976        | 6.0   | 66   | 1.2983          | 0.5810   | 0.2674 | 1.0      | 0.1543      | 0.7732       |
| 0.2152        | 7.0   | 77   | 0.6716          | 0.7125   | 0.3472 | 1.0      | 0.2101      | 0.8444       |


### Framework versions

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