---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_107
  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_107

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: 1.1412
- Accuracy: 0.7407
- 1-f1: 0.3974
- 1-recall: 1.0
- 1-precision: 0.2479
- Balanced Acc: 0.8583

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1401        | 1.0   | 11   | 1.2522          | 0.6809   | 0.3488 | 1.0      | 0.2113      | 0.8255       |
| 0.6802        | 2.0   | 22   | 0.3867          | 0.9060   | 0.6292 | 0.9333   | 0.4746      | 0.9184       |
| 0.5434        | 3.0   | 33   | 0.5839          | 0.8490   | 0.5310 | 1.0      | 0.3614      | 0.9174       |
| 0.5162        | 4.0   | 44   | 1.1412          | 0.7407   | 0.3974 | 1.0      | 0.2479      | 0.8583       |


### Framework versions

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