---
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_bsample_160
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_bsample_160

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: 0.4105
- Accuracy: 0.9512
- 1-f1: 0.2951
- 1-recall: 0.5143
- 1-precision: 0.2069
- Balanced Acc: 0.7372

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1216        | 1.0   | 15   | 0.9502          | 0.6979   | 0.1163 | 1.0      | 0.0617      | 0.8459       |
| 0.1406        | 2.0   | 30   | 0.2712          | 0.9177   | 0.2487 | 0.6857   | 0.1519      | 0.8040       |
| 0.0679        | 3.0   | 45   | 0.4224          | 0.8984   | 0.2318 | 0.7714   | 0.1364      | 0.8362       |
| 0.9874        | 4.0   | 60   | 0.4105          | 0.9512   | 0.2951 | 0.5143   | 0.2069      | 0.7372       |


### Framework versions

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