---
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_033
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_033

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: 0.1978
- Accuracy: 0.9871
- 1-f1: 0.8485
- 1-recall: 0.875
- 1-precision: 0.8235
- Balanced Acc: 0.9335

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2113        | 1.0   | 25   | 0.0829          | 0.9742   | 0.7619 | 1.0      | 0.6154      | 0.9866       |
| 0.0105        | 2.0   | 50   | 0.2341          | 0.9768   | 0.7097 | 0.6875   | 0.7333      | 0.8384       |
| 0.009         | 3.0   | 75   | 0.1978          | 0.9871   | 0.8485 | 0.875    | 0.8235      | 0.9335       |


### Framework versions

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