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---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_252
  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_252

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: 0.9639
- Accuracy: 0.9567
- 1-f1: 0.55
- 1-recall: 0.5
- 1-precision: 0.6111
- Balanced Acc: 0.7411

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1849        | 1.0   | 26   | 0.2708          | 0.8678   | 0.4086 | 0.8636   | 0.2676      | 0.8658       |
| 0.1185        | 2.0   | 52   | 0.2527          | 0.9303   | 0.5672 | 0.8636   | 0.4222      | 0.8988       |
| 0.1731        | 3.0   | 78   | 0.3282          | 0.9447   | 0.5818 | 0.7273   | 0.4848      | 0.8421       |
| 0.2204        | 4.0   | 104  | 0.5445          | 0.9567   | 0.6250 | 0.6818   | 0.5769      | 0.8269       |
| 0.4436        | 5.0   | 130  | 0.9639          | 0.9567   | 0.55   | 0.5      | 0.6111      | 0.7411       |


### Framework versions

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