---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_base_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_339
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_339

This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8178
- Accuracy: 0.9366
- 1-f1: 0.4046
- 1-recall: 0.4511
- 1-precision: 0.3667
- Balanced Acc: 0.7060

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5714        | 1.0   | 871  | 0.3874          | 0.9182   | 0.4019 | 0.5759   | 0.3086      | 0.7556       |
| 0.2029        | 2.0   | 1742 | 0.3685          | 0.8897   | 0.3770 | 0.6992   | 0.2580      | 0.7992       |
| 0.0709        | 3.0   | 2613 | 0.5978          | 0.9451   | 0.3855 | 0.3609   | 0.4138      | 0.6676       |
| 0.084         | 4.0   | 3484 | 0.5866          | 0.9262   | 0.4078 | 0.5323   | 0.3305      | 0.7391       |
| 0.0702        | 5.0   | 4355 | 0.8178          | 0.9366   | 0.4046 | 0.4511   | 0.3667      | 0.7060       |


### Framework versions

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