---
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_007
  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_bsample_007

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: 0.6965
- Accuracy: 0.8100
- 1-f1: 0.2000
- 1-recall: 0.8182
- 1-precision: 0.1139
- Balanced Acc: 0.8140

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2267        | 1.0   | 5    | 0.6378          | 0.7889   | 0.2000 | 0.9091   | 0.1124      | 0.8472       |
| 0.1659        | 2.0   | 10   | 0.4611          | 0.8443   | 0.2532 | 0.9091   | 0.1471      | 0.8757       |
| 0.1002        | 3.0   | 15   | 0.6567          | 0.7968   | 0.2062 | 0.9091   | 0.1163      | 0.8513       |
| 0.0502        | 4.0   | 20   | 0.4536          | 0.8760   | 0.2769 | 0.8182   | 0.1667      | 0.8479       |
| 0.023         | 5.0   | 25   | 0.8837          | 0.7678   | 0.1852 | 0.9091   | 0.1031      | 0.8363       |
| 0.0089        | 6.0   | 30   | 0.6965          | 0.8100   | 0.2000 | 0.8182   | 0.1139      | 0.8140       |


### Framework versions

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