---
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_131
  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_131

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: 0.5460
- Accuracy: 0.8570
- 1-f1: 0.3770
- 1-recall: 0.9068
- 1-precision: 0.2380
- Balanced Acc: 0.8806

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1914        | 1.0   | 167  | 0.9003          | 0.5692   | 0.1809 | 0.9970   | 0.0995      | 0.7724       |
| 0.0654        | 2.0   | 334  | 0.7071          | 0.6974   | 0.2368 | 0.9835   | 0.1346      | 0.8333       |
| 0.2182        | 3.0   | 501  | 0.6009          | 0.7773   | 0.2911 | 0.9579   | 0.1716      | 0.8631       |
| 0.0871        | 4.0   | 668  | 0.4291          | 0.8584   | 0.3801 | 0.9098   | 0.2403      | 0.8828       |
| 0.0217        | 5.0   | 835  | 0.6776          | 0.8031   | 0.3148 | 0.9474   | 0.1887      | 0.8716       |
| 0.0717        | 6.0   | 1002 | 0.5460          | 0.8570   | 0.3770 | 0.9068   | 0.2380      | 0.8806       |


### Framework versions

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