---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_uncased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_175
  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_175

This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_uncased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_uncased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4623
- Accuracy: 0.8937
- 1-f1: 0.4130
- 1-recall: 0.95
- 1-precision: 0.2639
- Balanced Acc: 0.9207

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0302        | 1.0   | 6    | 0.3907          | 0.8819   | 0.3878 | 0.95     | 0.2436      | 0.9145       |
| 0.0464        | 2.0   | 12   | 0.3874          | 0.9016   | 0.4186 | 0.9      | 0.2727      | 0.9008       |
| 0.0545        | 3.0   | 18   | 0.3953          | 0.8878   | 0.4000 | 0.95     | 0.2533      | 0.9176       |
| 0.0115        | 4.0   | 24   | 0.3764          | 0.9075   | 0.4471 | 0.95     | 0.2923      | 0.9279       |
| 0.0073        | 5.0   | 30   | 0.4056          | 0.9016   | 0.4318 | 0.95     | 0.2794      | 0.9248       |
| 0.0023        | 6.0   | 36   | 0.4623          | 0.8937   | 0.4130 | 0.95     | 0.2639      | 0.9207       |


### Framework versions

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