---
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_165
  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_165

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: 0.6840
- Accuracy: 0.8057
- 1-f1: 0.3537
- 1-recall: 0.9630
- 1-precision: 0.2167
- Balanced Acc: 0.8797

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0272        | 1.0   | 7    | 0.5363          | 0.8016   | 0.3401 | 0.9259   | 0.2083      | 0.8601       |
| 0.0344        | 2.0   | 14   | 0.4831          | 0.8548   | 0.3826 | 0.8148   | 0.25        | 0.8360       |
| 0.0172        | 3.0   | 21   | 0.6559          | 0.7832   | 0.3291 | 0.9630   | 0.1985      | 0.8678       |
| 0.0123        | 4.0   | 28   | 0.6840          | 0.8057   | 0.3537 | 0.9630   | 0.2167      | 0.8797       |


### Framework versions

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