---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
model-index:
- name: populism_model9
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_model9

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: 0.4821
- Accuracy: 0.9430
- F1: 0.4062
- Recall: 0.4483

## 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: 64
- eval_batch_size: 64
- 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| No log        | 1.0   | 42   | 0.5072          | 0.9520   | 0.2    | 0.1379 |
| 0.4287        | 2.0   | 84   | 0.3206          | 0.8951   | 0.375  | 0.7241 |
| 0.3071        | 3.0   | 126  | 0.3293          | 0.9160   | 0.4167 | 0.6897 |
| 0.2561        | 4.0   | 168  | 0.5054          | 0.9400   | 0.3103 | 0.3103 |
| 0.2026        | 5.0   | 210  | 0.4821          | 0.9430   | 0.4062 | 0.4483 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0