---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_uncased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_170
  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_170

This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_uncased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_uncased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0880
- Accuracy: 0.9944
- 1-f1: 0.9027
- 1-recall: 0.8947
- 1-precision: 0.9107
- Balanced Acc: 0.9461

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2984        | 1.0   | 62   | 0.1492          | 0.9889   | 0.8070 | 0.8070   | 0.8070      | 0.9006       |
| 0.0562        | 2.0   | 124  | 0.0532          | 0.9914   | 0.864  | 0.9474   | 0.7941      | 0.9700       |
| 0.0245        | 3.0   | 186  | 0.0405          | 0.9924   | 0.88   | 0.9649   | 0.8088      | 0.9791       |
| 0.0106        | 4.0   | 248  | 0.1586          | 0.9954   | 0.9143 | 0.8421   | 1.0         | 0.9211       |
| 0.0035        | 5.0   | 310  | 0.0880          | 0.9944   | 0.9027 | 0.8947   | 0.9107      | 0.9461       |


### Framework versions

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