---
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_model001
  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_model001

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: 0.5837
- Accuracy: 0.9486
- 1-f1: 0.4970
- 1-recall: 0.5373
- 1-precision: 0.4622
- Balanced Acc: 0.7532

## 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 OptimizerNames.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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3553        | 1.0   | 452  | 0.3167          | 0.9204   | 0.4484 | 0.6837   | 0.3336      | 0.8080       |
| 0.275         | 2.0   | 904  | 0.2959          | 0.9120   | 0.4547 | 0.7760   | 0.3216      | 0.8474       |
| 0.1906        | 3.0   | 1356 | 0.3891          | 0.9431   | 0.4969 | 0.5944   | 0.4269      | 0.7774       |
| 0.1474        | 4.0   | 1808 | 0.4287          | 0.9374   | 0.5    | 0.6618   | 0.4018      | 0.8064       |
| 0.1065        | 5.0   | 2260 | 0.5837          | 0.9486   | 0.4970 | 0.5373   | 0.4622      | 0.7532       |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0