---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_118
  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_118

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: 0.3835
- Accuracy: 0.8941
- 1-f1: 0.3224
- 1-recall: 0.9423
- 1-precision: 0.1944
- Balanced Acc: 0.9176

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2342        | 1.0   | 38   | 0.3748          | 0.8191   | 0.2212 | 0.9615   | 0.125       | 0.8884       |
| 0.3346        | 2.0   | 76   | 0.3659          | 0.8155   | 0.2246 | 1.0      | 0.1265      | 0.9052       |
| 0.4371        | 3.0   | 114  | 0.1916          | 0.8931   | 0.3158 | 0.9231   | 0.1905      | 0.9077       |
| 0.2013        | 4.0   | 152  | 0.2561          | 0.9224   | 0.3984 | 0.9615   | 0.2513      | 0.9414       |
| 0.4561        | 5.0   | 190  | 0.3835          | 0.8941   | 0.3224 | 0.9423   | 0.1944      | 0.9176       |


### Framework versions

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