---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_260
  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_classifier_260

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: 0.7420
- Accuracy: 0.9087
- 1-f1: 0.4706
- 1-recall: 0.6452
- 1-precision: 0.3704
- Balanced Acc: 0.7858

## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4174        | 1.0   | 31   | 0.5382          | 0.9270   | 0.5    | 0.5806   | 0.4390      | 0.7654       |
| 0.1427        | 2.0   | 62   | 0.4422          | 0.8925   | 0.4301 | 0.6452   | 0.3226      | 0.7771       |
| 0.4868        | 3.0   | 93   | 0.5921          | 0.8276   | 0.3511 | 0.7419   | 0.23        | 0.7876       |
| 0.1021        | 4.0   | 124  | 0.5246          | 0.9067   | 0.4773 | 0.6774   | 0.3684      | 0.7997       |
| 0.0746        | 5.0   | 155  | 0.7420          | 0.9087   | 0.4706 | 0.6452   | 0.3704      | 0.7858       |


### Framework versions

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