---
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_030
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# populism_classifier_030

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: 0.2959
- Accuracy: 0.9733
- 1-f1: 0.4419
- 1-recall: 0.6333
- 1-precision: 0.3393
- Balanced Acc: 0.8062

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4541        | 1.0   | 113  | 0.2234          | 0.9872   | 0.4651 | 0.3333   | 0.7692      | 0.6658       |
| 0.3848        | 2.0   | 226  | 0.3103          | 0.9889   | 0.5455 | 0.4      | 0.8571      | 0.6994       |
| 0.1234        | 3.0   | 339  | 0.2180          | 0.9800   | 0.4857 | 0.5667   | 0.425       | 0.7768       |
| 0.018         | 4.0   | 452  | 0.3341          | 0.9894   | 0.6122 | 0.5      | 0.7895      | 0.7489       |
| 0.0077        | 5.0   | 565  | 0.2959          | 0.9733   | 0.4419 | 0.6333   | 0.3393      | 0.8062       |


### Framework versions

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