---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_045
  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_045

This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5654
- Accuracy: 0.8484
- 1-f1: 0.3419
- 1-recall: 1.0
- 1-precision: 0.2062
- Balanced Acc: 0.9211

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2266        | 1.0   | 6    | 0.5319          | 0.8169   | 0.3008 | 1.0      | 0.1770      | 0.9047       |
| 0.0631        | 2.0   | 12   | 0.3960          | 0.8681   | 0.3619 | 0.95     | 0.2235      | 0.9074       |
| 0.3718        | 3.0   | 18   | 0.2566          | 0.9232   | 0.48   | 0.9      | 0.3273      | 0.9121       |
| 0.0099        | 4.0   | 24   | 0.6206          | 0.8209   | 0.3053 | 1.0      | 0.1802      | 0.9068       |
| 0.019         | 5.0   | 30   | 0.5654          | 0.8484   | 0.3419 | 1.0      | 0.2062      | 0.9211       |


### Framework versions

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