---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_250
  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_250

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: 0.6190
- Accuracy: 0.9396
- 1-f1: 0.6667
- 1-recall: 0.7273
- 1-precision: 0.6154
- Balanced Acc: 0.8431

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2827        | 1.0   | 17   | 0.3301          | 0.8528   | 0.5185 | 0.9545   | 0.3559      | 0.8991       |
| 0.1958        | 2.0   | 34   | 0.2953          | 0.9132   | 0.6230 | 0.8636   | 0.4872      | 0.8907       |
| 0.0902        | 3.0   | 51   | 0.3944          | 0.9283   | 0.6545 | 0.8182   | 0.5455      | 0.8782       |
| 0.0112        | 4.0   | 68   | 0.5512          | 0.9358   | 0.6531 | 0.7273   | 0.5926      | 0.8410       |
| 0.0181        | 5.0   | 85   | 0.6190          | 0.9396   | 0.6667 | 0.7273   | 0.6154      | 0.8431       |


### Framework versions

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