---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_243
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_243

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: 0.8283
- Accuracy: 0.9344
- 1-f1: 0.4516
- 1-recall: 0.5385
- 1-precision: 0.3889
- Balanced Acc: 0.7469

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4982        | 1.0   | 33   | 0.4862          | 0.7181   | 0.2151 | 0.7692   | 0.125       | 0.7423       |
| 0.1442        | 2.0   | 66   | 0.6065          | 0.9517   | 0.4898 | 0.4615   | 0.5217      | 0.7196       |
| 0.2403        | 3.0   | 99   | 0.4708          | 0.8900   | 0.3871 | 0.6923   | 0.2687      | 0.7964       |
| 0.0461        | 4.0   | 132  | 0.5945          | 0.9189   | 0.4324 | 0.6154   | 0.3333      | 0.7752       |
| 0.1079        | 5.0   | 165  | 0.7173          | 0.9402   | 0.4561 | 0.5      | 0.4194      | 0.7317       |
| 0.0124        | 6.0   | 198  | 0.8283          | 0.9344   | 0.4516 | 0.5385   | 0.3889      | 0.7469       |


### Framework versions

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