---
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_025
  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_025

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: 0.9166
- Accuracy: 0.7557
- 1-f1: 0.2920
- 1-recall: 0.8919
- 1-precision: 0.1746
- Balanced Acc: 0.8197

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0977        | 1.0   | 9    | 1.2327          | 0.6443   | 0.2207 | 0.8919   | 0.1260      | 0.7607       |
| 0.1288        | 2.0   | 18   | 0.6766          | 0.8260   | 0.3372 | 0.7838   | 0.2148      | 0.8061       |
| 0.0342        | 3.0   | 27   | 0.7173          | 0.8198   | 0.3371 | 0.8108   | 0.2128      | 0.8156       |
| 0.0062        | 4.0   | 36   | 0.9166          | 0.7557   | 0.2920 | 0.8919   | 0.1746      | 0.8197       |


### Framework versions

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