---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: populism_model26
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# populism_model26

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: 0.5158
- Accuracy: 0.8868
- F1: 0.5169
- Recall: 0.7188
- Precision: 0.4035

## 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: 128
- eval_batch_size: 128
- 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 | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| No log        | 1.0   | 12   | 0.4692          | 0.8526   | 0.4717 | 0.7812 | 0.3378    |
| No log        | 2.0   | 24   | 0.6293          | 0.9237   | 0.5538 | 0.5625 | 0.5455    |
| No log        | 3.0   | 36   | 0.4847          | 0.8921   | 0.5287 | 0.7188 | 0.4182    |
| No log        | 4.0   | 48   | 0.5058          | 0.8842   | 0.5111 | 0.7188 | 0.3966    |
| 0.3726        | 5.0   | 60   | 0.5158          | 0.8868   | 0.5169 | 0.7188 | 0.4035    |


### Framework versions

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