---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_251
  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_251

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: 0.8699
- Accuracy: 0.7745
- 1-f1: 0.2484
- 1-recall: 0.8636
- 1-precision: 0.1450
- Balanced Acc: 0.8171

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2346        | 1.0   | 7    | 1.3456          | 0.6510   | 0.1909 | 0.9545   | 0.1061      | 0.7959       |
| 0.0298        | 2.0   | 14   | 0.8524          | 0.7529   | 0.2410 | 0.9091   | 0.1389      | 0.8275       |
| 0.1553        | 3.0   | 21   | 1.0009          | 0.7392   | 0.2312 | 0.9091   | 0.1325      | 0.8203       |
| 0.0153        | 4.0   | 28   | 0.8699          | 0.7745   | 0.2484 | 0.8636   | 0.1450      | 0.8171       |


### Framework versions

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