---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_240
  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_240

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: 0.9436
- Accuracy: 0.7955
- 1-f1: 0.3415
- 1-recall: 0.8485
- 1-precision: 0.2137
- Balanced Acc: 0.8202

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0519        | 1.0   | 8    | 0.8375          | 0.7765   | 0.3218 | 0.8485   | 0.1986      | 0.8101       |
| 0.015         | 2.0   | 16   | 1.0175          | 0.7008   | 0.2818 | 0.9394   | 0.1658      | 0.8121       |
| 0.0228        | 3.0   | 24   | 0.6612          | 0.8371   | 0.3944 | 0.8485   | 0.2569      | 0.8424       |
| 0.0207        | 4.0   | 32   | 0.8965          | 0.7576   | 0.3191 | 0.9091   | 0.1935      | 0.8283       |
| 0.0083        | 5.0   | 40   | 0.9436          | 0.7955   | 0.3415 | 0.8485   | 0.2137      | 0.8202       |


### Framework versions

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