---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model87
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# populism_model87

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: 0.4375
- Accuracy: 0.8699
- 1-f1: 0.3304
- 1-recall: 0.6588
- 1-precision: 0.2205
- Balanced Acc: 0.7698

## 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: 128
- eval_batch_size: 128
- 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.533         | 1.0   | 55   | 0.5034          | 0.9513   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.4457        | 2.0   | 110  | 0.4659          | 0.8332   | 0.2442 | 0.5529   | 0.1567      | 0.7003       |
| 0.3731        | 3.0   | 165  | 0.4350          | 0.8040   | 0.2692 | 0.7412   | 0.1645      | 0.7742       |
| 0.3229        | 4.0   | 220  | 0.4390          | 0.8585   | 0.3306 | 0.7176   | 0.2148      | 0.7917       |
| 0.293         | 5.0   | 275  | 0.4375          | 0.8699   | 0.3304 | 0.6588   | 0.2205      | 0.7698       |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0