---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_110
  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_110

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: 1.3206
- Accuracy: 0.6420
- 1-f1: 0.2588
- 1-recall: 1.0
- 1-precision: 0.1486
- Balanced Acc: 0.8091

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7564        | 1.0   | 15   | 0.9714          | 0.0625   | 0.1176 | 1.0      | 0.0625      | 0.5          |
| 0.6563        | 2.0   | 30   | 0.9651          | 0.0720   | 0.1187 | 1.0      | 0.0631      | 0.5051       |
| 0.5714        | 3.0   | 45   | 0.9803          | 0.4242   | 0.1739 | 0.9697   | 0.0955      | 0.6788       |
| 0.3686        | 4.0   | 60   | 0.9303          | 0.3807   | 0.1679 | 1.0      | 0.0917      | 0.6697       |
| 0.5363        | 5.0   | 75   | 0.4515          | 0.7822   | 0.3575 | 0.9697   | 0.2192      | 0.8697       |
| 0.4571        | 6.0   | 90   | 0.4899          | 0.7178   | 0.3070 | 1.0      | 0.1813      | 0.8495       |
| 0.2236        | 7.0   | 105  | 1.3206          | 0.6420   | 0.2588 | 1.0      | 0.1486      | 0.8091       |


### Framework versions

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