---
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_bsample_027
  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_027

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: 0.6278
- Accuracy: 0.8051
- 1-f1: 0.3155
- 1-recall: 0.9414
- 1-precision: 0.1895
- Balanced Acc: 0.8698

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1822        | 1.0   | 167  | 1.1261          | 0.5216   | 0.1655 | 0.9940   | 0.0903      | 0.7460       |
| 0.0917        | 2.0   | 334  | 0.6039          | 0.7504   | 0.2638 | 0.9368   | 0.1535      | 0.8389       |
| 0.118         | 3.0   | 501  | 0.6889          | 0.7300   | 0.2539 | 0.9624   | 0.1462      | 0.8404       |
| 0.3814        | 4.0   | 668  | 0.4434          | 0.8794   | 0.3885 | 0.8030   | 0.2562      | 0.8431       |
| 0.0625        | 5.0   | 835  | 0.6553          | 0.8022   | 0.3086 | 0.9248   | 0.1852      | 0.8604       |
| 0.0409        | 6.0   | 1002 | 0.6278          | 0.8051   | 0.3155 | 0.9414   | 0.1895      | 0.8698       |


### Framework versions

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