---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_116
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_bsample_116

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: 1.0305
- Accuracy: 0.1128
- 1-f1: 0.1150
- 1-recall: 1.0
- 1-precision: 0.0610
- Balanced Acc: 0.5293

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7506        | 1.0   | 12   | 0.8999          | 0.0576   | 0.1090 | 1.0      | 0.0576      | 0.5          |
| 0.6886        | 2.0   | 24   | 0.8076          | 0.5388   | 0.1636 | 0.7826   | 0.0914      | 0.6533       |
| 0.6371        | 3.0   | 36   | 0.6554          | 0.5539   | 0.1835 | 0.8696   | 0.1026      | 0.7021       |
| 0.72          | 4.0   | 48   | 0.8936          | 0.1479   | 0.1192 | 1.0      | 0.0634      | 0.5479       |
| 0.5849        | 5.0   | 60   | 1.0305          | 0.1128   | 0.1150 | 1.0      | 0.0610      | 0.5293       |


### Framework versions

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