---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_uncased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_182
  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_182

This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_uncased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_uncased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9770
- Accuracy: 0.7388
- 1-f1: 0.2717
- 1-recall: 0.9259
- 1-precision: 0.1592
- Balanced Acc: 0.8272

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.039         | 1.0   | 8    | 0.7905          | 0.7700   | 0.2976 | 0.9259   | 0.1773      | 0.8436       |
| 0.0096        | 2.0   | 16   | 0.7310          | 0.7914   | 0.3097 | 0.8889   | 0.1875      | 0.8374       |
| 0.0564        | 3.0   | 24   | 1.1896          | 0.6745   | 0.2304 | 0.9259   | 0.1316      | 0.7932       |
| 0.0171        | 4.0   | 32   | 0.9770          | 0.7388   | 0.2717 | 0.9259   | 0.1592      | 0.8272       |


### Framework versions

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