---
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_052
  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_052

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: 0.8004
- Accuracy: 0.7895
- 1-f1: 0.2895
- 1-recall: 0.8148
- 1-precision: 0.176
- Balanced Acc: 0.8014

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0336        | 1.0   | 8    | 0.7242          | 0.7719   | 0.2822 | 0.8519   | 0.1691      | 0.8097       |
| 0.0112        | 2.0   | 16   | 0.7139          | 0.7953   | 0.3137 | 0.8889   | 0.1905      | 0.8395       |
| 0.0513        | 3.0   | 24   | 1.1909          | 0.6257   | 0.2131 | 0.9630   | 0.1198      | 0.7850       |
| 0.0171        | 4.0   | 32   | 0.6467          | 0.8187   | 0.3212 | 0.8148   | 0.2         | 0.8169       |
| 0.0212        | 5.0   | 40   | 0.8381          | 0.7368   | 0.2623 | 0.8889   | 0.1538      | 0.8086       |
| 0.0151        | 6.0   | 48   | 0.8004          | 0.7895   | 0.2895 | 0.8148   | 0.176       | 0.8014       |


### Framework versions

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