---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_cased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_136
  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_136

This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_cased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_cased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7525
- Accuracy: 0.7689
- 1-f1: 0.3370
- 1-recall: 0.9394
- 1-precision: 0.2053
- Balanced Acc: 0.8485

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1179        | 1.0   | 8    | 0.6695          | 0.8011   | 0.3558 | 0.8788   | 0.2231      | 0.8374       |
| 0.0262        | 2.0   | 16   | 0.6679          | 0.7595   | 0.3280 | 0.9394   | 0.1987      | 0.8434       |
| 0.0486        | 3.0   | 24   | 0.7148          | 0.7708   | 0.3459 | 0.9697   | 0.2105      | 0.8636       |
| 0.0124        | 4.0   | 32   | 0.7525          | 0.7689   | 0.3370 | 0.9394   | 0.2053      | 0.8485       |


### Framework versions

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