---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_105
  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_105

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: 0.7162
- Accuracy: 0.8453
- 1-f1: 0.3674
- 1-recall: 0.9414
- 1-precision: 0.2282
- Balanced Acc: 0.8909

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.337         | 1.0   | 333  | 0.8790          | 0.6966   | 0.2385 | 0.9955   | 0.1355      | 0.8386       |
| 0.1932        | 2.0   | 666  | 0.8913          | 0.7301   | 0.2589 | 0.9880   | 0.1490      | 0.8526       |
| 0.3488        | 3.0   | 999  | 0.7092          | 0.7569   | 0.2785 | 0.9835   | 0.1622      | 0.8645       |
| 0.1253        | 4.0   | 1332 | 0.5442          | 0.8456   | 0.3723 | 0.9594   | 0.2310      | 0.8997       |
| 0.6639        | 5.0   | 1665 | 0.6545          | 0.9526   | 0.0149 | 0.0075   | 1.0         | 0.5038       |
| 0.0072        | 6.0   | 1998 | 0.7162          | 0.8453   | 0.3674 | 0.9414   | 0.2282      | 0.8909       |


### Framework versions

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