---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_251
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_251

This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1528
- Accuracy: 0.9424
- 1-f1: 0.4815
- 1-recall: 0.4643
- 1-precision: 0.5
- Balanced Acc: 0.7180

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5524        | 1.0   | 31   | 0.5771          | 0.9403   | 0.4082 | 0.3571   | 0.4762      | 0.6666       |
| 0.2164        | 2.0   | 62   | 0.4473          | 0.9218   | 0.4722 | 0.6071   | 0.3864      | 0.7741       |
| 0.1863        | 3.0   | 93   | 0.5707          | 0.9198   | 0.4507 | 0.5714   | 0.3721      | 0.7562       |
| 0.068         | 4.0   | 124  | 0.9231          | 0.9342   | 0.4667 | 0.5      | 0.4375      | 0.7303       |
| 0.3402        | 5.0   | 155  | 1.1528          | 0.9424   | 0.4815 | 0.4643   | 0.5         | 0.7180       |


### Framework versions

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