---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_240
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_240

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: 1.0545
- Accuracy: 0.9219
- 1-f1: 0.4118
- 1-recall: 0.4242
- 1-precision: 0.4
- Balanced Acc: 0.6902

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4838        | 1.0   | 32   | 0.4396          | 0.7578   | 0.3261 | 0.9091   | 0.1987      | 0.8282       |
| 0.2209        | 2.0   | 64   | 0.4442          | 0.8965   | 0.4301 | 0.6061   | 0.3333      | 0.7613       |
| 0.279         | 3.0   | 96   | 0.4339          | 0.8984   | 0.4694 | 0.6970   | 0.3538      | 0.8046       |
| 0.2208        | 4.0   | 128  | 1.0429          | 0.9277   | 0.3934 | 0.3636   | 0.4286      | 0.6651       |
| 0.0531        | 5.0   | 160  | 0.9513          | 0.9082   | 0.3733 | 0.4242   | 0.3333      | 0.6829       |
| 0.0195        | 6.0   | 192  | 1.0545          | 0.9219   | 0.4118 | 0.4242   | 0.4         | 0.6902       |


### Framework versions

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