---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_254
  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_254

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: 0.6810
- Accuracy: 0.7847
- 1-f1: 0.5455
- 1-recall: 0.9310
- 1-precision: 0.3857
- Balanced Acc: 0.8461

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1301        | 1.0   | 5    | 0.6542          | 0.7225   | 0.4821 | 0.9310   | 0.3253      | 0.8100       |
| 0.0343        | 2.0   | 10   | 0.6913          | 0.7368   | 0.4954 | 0.9310   | 0.3375      | 0.8183       |
| 0.0065        | 3.0   | 15   | 0.5539          | 0.8086   | 0.5652 | 0.8966   | 0.4127      | 0.8455       |
| 0.0132        | 4.0   | 20   | 0.6416          | 0.7895   | 0.5510 | 0.9310   | 0.3913      | 0.8489       |
| 0.0171        | 5.0   | 25   | 0.6810          | 0.7847   | 0.5455 | 0.9310   | 0.3857      | 0.8461       |


### Framework versions

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