---
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_038
  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_038

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: 1.0515
- Accuracy: 0.7469
- 1-f1: 0.3129
- 1-recall: 1.0
- 1-precision: 0.1855
- Balanced Acc: 0.8657

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0359        | 1.0   | 6    | 0.7153          | 0.7895   | 0.3333 | 0.9130   | 0.2039      | 0.8475       |
| 0.0438        | 2.0   | 12   | 0.7526          | 0.7719   | 0.3358 | 1.0      | 0.2018      | 0.8790       |
| 0.0317        | 3.0   | 18   | 0.6063          | 0.8271   | 0.3784 | 0.9130   | 0.2386      | 0.8674       |
| 0.0226        | 4.0   | 24   | 0.7763          | 0.7820   | 0.3459 | 1.0      | 0.2091      | 0.8843       |
| 0.0377        | 5.0   | 30   | 0.5571          | 0.8596   | 0.4167 | 0.8696   | 0.2740      | 0.8643       |
| 0.0027        | 6.0   | 36   | 0.7774          | 0.8020   | 0.3577 | 0.9565   | 0.22        | 0.8745       |
| 0.0014        | 7.0   | 42   | 1.0515          | 0.7469   | 0.3129 | 1.0      | 0.1855      | 0.8657       |


### Framework versions

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