---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_246
  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_246

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: 0.4982
- Accuracy: 0.8697
- 1-f1: 0.4222
- 1-recall: 0.8261
- 1-precision: 0.2836
- Balanced Acc: 0.8492

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0619        | 1.0   | 6    | 0.7325          | 0.7794   | 0.3333 | 0.9565   | 0.2018      | 0.8626       |
| 0.2172        | 2.0   | 12   | 0.4213          | 0.8972   | 0.4675 | 0.7826   | 0.3333      | 0.8434       |
| 0.0566        | 3.0   | 18   | 0.8152          | 0.7343   | 0.2933 | 0.9565   | 0.1732      | 0.8386       |
| 0.0138        | 4.0   | 24   | 0.4982          | 0.8697   | 0.4222 | 0.8261   | 0.2836      | 0.8492       |


### Framework versions

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