---
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_029
  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_029

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: 0.3398
- Accuracy: 0.9586
- 1-f1: 0.75
- 1-recall: 0.84
- 1-precision: 0.6774
- Balanced Acc: 0.9040

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4434        | 1.0   | 22   | 0.2169          | 0.9083   | 0.5753 | 0.84     | 0.4375      | 0.8769       |
| 0.4601        | 2.0   | 44   | 0.1930          | 0.9112   | 0.6154 | 0.96     | 0.4528      | 0.9337       |
| 0.0308        | 3.0   | 66   | 0.2258          | 0.9438   | 0.6885 | 0.84     | 0.5833      | 0.8960       |
| 0.0406        | 4.0   | 88   | 0.3398          | 0.9586   | 0.75   | 0.84     | 0.6774      | 0.9040       |


### Framework versions

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