---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_235
  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_235

This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9723
- Accuracy: 0.6953
- 1-f1: 0.2263
- 1-recall: 0.9338
- 1-precision: 0.1288
- Balanced Acc: 0.8086

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2215        | 1.0   | 167  | 1.2513          | 0.2303   | 0.1102 | 0.9985   | 0.0583      | 0.5951       |
| 0.2192        | 2.0   | 334  | 0.9871          | 0.4950   | 0.1555 | 0.9744   | 0.0845      | 0.7227       |
| 0.2565        | 3.0   | 501  | 0.9863          | 0.6052   | 0.1847 | 0.9368   | 0.1024      | 0.7627       |
| 0.1831        | 4.0   | 668  | 1.0533          | 0.6338   | 0.1945 | 0.9263   | 0.1086      | 0.7727       |
| 0.0799        | 5.0   | 835  | 0.7577          | 0.7237   | 0.2352 | 0.8902   | 0.1355      | 0.8028       |
| 0.0769        | 6.0   | 1002 | 0.9875          | 0.6611   | 0.2088 | 0.9368   | 0.1175      | 0.7921       |
| 0.0708        | 7.0   | 1169 | 0.7383          | 0.7561   | 0.2613 | 0.9038   | 0.1527      | 0.8262       |
| 0.0419        | 8.0   | 1336 | 0.8412          | 0.7274   | 0.2437 | 0.9203   | 0.1405      | 0.8190       |
| 0.1823        | 9.0   | 1503 | 0.9723          | 0.6953   | 0.2263 | 0.9338   | 0.1288      | 0.8086       |


### Framework versions

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