---
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_036
  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_036

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: 0.6998
- Accuracy: 0.8473
- 1-f1: 0.2400
- 1-recall: 0.84
- 1-precision: 0.14
- Balanced Acc: 0.8438

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0557        | 1.0   | 9    | 0.8331          | 0.7474   | 0.1852 | 1.0      | 0.1020      | 0.8700       |
| 0.0378        | 2.0   | 18   | 0.4860          | 0.8507   | 0.2697 | 0.96     | 0.1569      | 0.9038       |
| 0.0335        | 3.0   | 27   | 0.4809          | 0.9036   | 0.2881 | 0.68     | 0.1828      | 0.7951       |
| 0.0044        | 4.0   | 36   | 0.5310          | 0.9001   | 0.2810 | 0.68     | 0.1771      | 0.7933       |
| 0.0018        | 5.0   | 45   | 0.6998          | 0.8473   | 0.2400 | 0.84     | 0.14        | 0.8438       |


### Framework versions

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