---
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_011
  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_011

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: 0.5113
- Accuracy: 0.8566
- 1-f1: 0.4317
- 1-recall: 0.9375
- 1-precision: 0.2804
- Balanced Acc: 0.8946

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0711        | 1.0   | 6    | 0.4762          | 0.9002   | 0.4554 | 0.7188   | 0.3333      | 0.8151       |
| 0.0826        | 2.0   | 12   | 0.4962          | 0.9020   | 0.4490 | 0.6875   | 0.3333      | 0.8014       |
| 0.029         | 3.0   | 18   | 0.4481          | 0.8530   | 0.4336 | 0.9688   | 0.2793      | 0.9073       |
| 0.0267        | 4.0   | 24   | 0.3742          | 0.8893   | 0.4404 | 0.75     | 0.3117      | 0.8239       |
| 0.0054        | 5.0   | 30   | 0.4741          | 0.8548   | 0.4286 | 0.9375   | 0.2778      | 0.8936       |
| 0.0072        | 6.0   | 36   | 0.5113          | 0.8566   | 0.4317 | 0.9375   | 0.2804      | 0.8946       |


### Framework versions

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