---
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_013
  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_013

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: 1.0360
- Accuracy: 0.8397
- 1-f1: 0.2759
- 1-recall: 0.5714
- 1-precision: 0.1818
- Balanced Acc: 0.7131

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2723        | 1.0   | 7    | 0.8709          | 0.8817   | 0.3404 | 0.5714   | 0.2424      | 0.7353       |
| 0.0999        | 2.0   | 14   | 0.8953          | 0.7042   | 0.2365 | 0.8571   | 0.1371      | 0.7764       |
| 0.1226        | 3.0   | 21   | 0.6703          | 0.8187   | 0.2963 | 0.7143   | 0.1869      | 0.7694       |
| 0.0231        | 4.0   | 28   | 0.9265          | 0.8034   | 0.2797 | 0.7143   | 0.1739      | 0.7614       |
| 0.0496        | 5.0   | 35   | 1.0360          | 0.8397   | 0.2759 | 0.5714   | 0.1818      | 0.7131       |


### Framework versions

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