---
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_048
  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_048

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: 0.6899
- Accuracy: 0.8010
- 1-f1: 0.2569
- 1-recall: 0.875
- 1-precision: 0.1505
- Balanced Acc: 0.8365

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0677        | 1.0   | 4    | 0.9887          | 0.7125   | 0.2148 | 1.0      | 0.1203      | 0.8504       |
| 0.1969        | 2.0   | 8    | 0.5845          | 0.8428   | 0.3043 | 0.875    | 0.1842      | 0.8582       |
| 0.0666        | 3.0   | 12   | 0.6913          | 0.7838   | 0.2542 | 0.9375   | 0.1471      | 0.8575       |
| 0.0131        | 4.0   | 16   | 0.5660          | 0.8477   | 0.2955 | 0.8125   | 0.1806      | 0.8308       |
| 0.0847        | 5.0   | 20   | 0.5668          | 0.8698   | 0.3117 | 0.75     | 0.1967      | 0.8123       |
| 0.0096        | 6.0   | 24   | 0.6899          | 0.8010   | 0.2569 | 0.875    | 0.1505      | 0.8365       |


### Framework versions

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