---
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_047
  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_047

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: 0.5372
- Accuracy: 0.8091
- 1-f1: 0.4965
- 1-recall: 0.9211
- 1-precision: 0.3398
- Balanced Acc: 0.8587

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0578        | 1.0   | 6    | 0.6002          | 0.7554   | 0.4485 | 0.9737   | 0.2913      | 0.8521       |
| 0.0549        | 2.0   | 12   | 0.5505          | 0.7715   | 0.4654 | 0.9737   | 0.3058      | 0.8611       |
| 0.0779        | 3.0   | 18   | 0.7306          | 0.7016   | 0.4064 | 1.0      | 0.2550      | 0.8338       |
| 0.0312        | 4.0   | 24   | 0.5346          | 0.7823   | 0.4774 | 0.9737   | 0.3162      | 0.8671       |
| 0.0443        | 5.0   | 30   | 0.5190          | 0.7930   | 0.4901 | 0.9737   | 0.3274      | 0.8731       |
| 0.0212        | 6.0   | 36   | 0.8699          | 0.6640   | 0.3781 | 1.0      | 0.2331      | 0.8129       |
| 0.0305        | 7.0   | 42   | 0.5372          | 0.8091   | 0.4965 | 0.9211   | 0.3398      | 0.8587       |


### Framework versions

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