---
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_model0
  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_model0

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: 0.4208
- Accuracy: 0.8688
- 1-f1: 0.3284
- 1-recall: 0.6588
- 1-precision: 0.2188
- Balanced Acc: 0.7692

## 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 | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4957        | 1.0   | 55   | 0.5050          | 0.8682   | 0.2722 | 0.5059   | 0.1861      | 0.6963       |
| 0.4629        | 2.0   | 110  | 0.4640          | 0.7788   | 0.2548 | 0.7765   | 0.1524      | 0.7777       |
| 0.3876        | 3.0   | 165  | 0.4342          | 0.7851   | 0.2802 | 0.8588   | 0.1674      | 0.8201       |
| 0.3452        | 4.0   | 220  | 0.4179          | 0.8911   | 0.3493 | 0.6      | 0.2464      | 0.7530       |
| 0.3012        | 5.0   | 275  | 0.4208          | 0.8688   | 0.3284 | 0.6588   | 0.2188      | 0.7692       |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0