---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_018
  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_018

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6423
- Accuracy: 0.7892
- 1-f1: 0.3485
- 1-recall: 0.9583
- 1-precision: 0.2130
- Balanced Acc: 0.8685

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0709        | 1.0   | 6    | 0.9253          | 0.7059   | 0.2857 | 1.0      | 0.1667      | 0.8438       |
| 0.1035        | 2.0   | 12   | 0.3778          | 0.9314   | 0.5758 | 0.7917   | 0.4524      | 0.8659       |
| 0.4103        | 3.0   | 18   | 0.3195          | 0.9118   | 0.5263 | 0.8333   | 0.3846      | 0.875        |
| 0.0191        | 4.0   | 24   | 0.7593          | 0.7402   | 0.3117 | 1.0      | 0.1846      | 0.8620       |
| 0.0503        | 5.0   | 30   | 0.6423          | 0.7892   | 0.3485 | 0.9583   | 0.2130      | 0.8685       |


### Framework versions

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