---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_cased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_147
  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_147

This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_cased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_cased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3425
- Accuracy: 0.9568
- 1-f1: 0.6557
- 1-recall: 0.7143
- 1-precision: 0.6061
- Balanced Acc: 0.8430

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1624        | 1.0   | 16   | 0.2857          | 0.9568   | 0.6667 | 0.75     | 0.6         | 0.8597       |
| 0.2862        | 2.0   | 32   | 0.2250          | 0.9362   | 0.5974 | 0.8214   | 0.4694      | 0.8823       |
| 0.0723        | 3.0   | 48   | 0.2670          | 0.9403   | 0.6133 | 0.8214   | 0.4894      | 0.8845       |
| 0.0417        | 4.0   | 64   | 0.3425          | 0.9568   | 0.6557 | 0.7143   | 0.6061      | 0.8430       |


### Framework versions

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