---
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_039
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_039

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: 0.3830
- Accuracy: 0.9671
- 1-f1: 0.5909
- 1-recall: 0.5652
- 1-precision: 0.6190
- Balanced Acc: 0.7750

## 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 OptimizerNames.ADAMW_TORCH_FUSED 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.276         | 1.0   | 35   | 0.1593          | 0.9543   | 0.6377 | 0.9565   | 0.4783      | 0.9554       |
| 0.0079        | 2.0   | 70   | 0.2716          | 0.9781   | 0.7143 | 0.6522   | 0.7895      | 0.8223       |
| 0.0315        | 3.0   | 105  | 0.3830          | 0.9671   | 0.5909 | 0.5652   | 0.6190      | 0.7750       |


### Framework versions

- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4