---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_256
  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_256

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: 0.8871
- Accuracy: 0.9267
- 1-f1: 0.2222
- 1-recall: 0.25
- 1-precision: 0.2
- Balanced Acc: 0.6031

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.681         | 1.0   | 24   | 0.6077          | 0.9581   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.2828        | 2.0   | 48   | 0.6075          | 0.9110   | 0.0556 | 0.0625   | 0.05        | 0.5053       |
| 0.3429        | 3.0   | 72   | 0.5537          | 0.8822   | 0.2623 | 0.5      | 0.1778      | 0.6995       |
| 0.4176        | 4.0   | 96   | 0.5570          | 0.8613   | 0.2535 | 0.5625   | 0.1636      | 0.7184       |
| 0.3116        | 5.0   | 120  | 0.5469          | 0.8822   | 0.2373 | 0.4375   | 0.1628      | 0.6696       |
| 0.3514        | 6.0   | 144  | 0.8624          | 0.9450   | 0.2222 | 0.1875   | 0.2727      | 0.5828       |
| 0.112         | 7.0   | 168  | 0.9762          | 0.9476   | 0.2308 | 0.1875   | 0.3         | 0.5842       |
| 0.1278        | 8.0   | 192  | 0.8871          | 0.9267   | 0.2222 | 0.25     | 0.2         | 0.6031       |


### Framework versions

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