---
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_143
  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_143

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: 0.9495
- Accuracy: 0.8111
- 1-f1: 0.3077
- 1-recall: 0.7857
- 1-precision: 0.1913
- Balanced Acc: 0.7991

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0658        | 1.0   | 7    | 0.8253          | 0.8015   | 0.3067 | 0.8214   | 0.1885      | 0.8109       |
| 0.0629        | 2.0   | 14   | 0.8040          | 0.9008   | 0.3953 | 0.6071   | 0.2931      | 0.7622       |
| 0.0585        | 3.0   | 21   | 0.8857          | 0.7786   | 0.2927 | 0.8571   | 0.1765      | 0.8157       |
| 0.0308        | 4.0   | 28   | 0.7675          | 0.8760   | 0.3810 | 0.7143   | 0.2597      | 0.7997       |
| 0.0235        | 5.0   | 35   | 1.0302          | 0.7634   | 0.2791 | 0.8571   | 0.1667      | 0.8076       |
| 0.0016        | 6.0   | 42   | 0.9495          | 0.8111   | 0.3077 | 0.7857   | 0.1913      | 0.7991       |


### Framework versions

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