---
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_bsample_132
  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_132

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: 1.0814
- Accuracy: 0.6426
- 1-f1: 0.128
- 1-recall: 0.8889
- 1-precision: 0.0690
- Balanced Acc: 0.7620

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1746        | 1.0   | 4    | 1.6979          | 0.5279   | 0.1111 | 1.0      | 0.0588      | 0.7568       |
| 0.0554        | 2.0   | 8    | 0.7286          | 0.8033   | 0.0909 | 0.3333   | 0.0526      | 0.5755       |
| 0.2833        | 3.0   | 12   | 0.7481          | 0.7967   | 0.0882 | 0.3333   | 0.0508      | 0.5721       |
| 0.0565        | 4.0   | 16   | 1.0814          | 0.6426   | 0.128  | 0.8889   | 0.0690      | 0.7620       |


### Framework versions

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