---
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_345
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_345

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: 0.4260
- Accuracy: 0.9613
- 1-f1: 0.5714
- 1-recall: 0.625
- 1-precision: 0.5263
- Balanced Acc: 0.8004

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3822        | 1.0   | 25   | 0.2534          | 0.8866   | 0.4054 | 0.9375   | 0.2586      | 0.9110       |
| 0.0583        | 2.0   | 50   | 0.2007          | 0.9098   | 0.4444 | 0.875    | 0.2979      | 0.8931       |
| 0.0549        | 3.0   | 75   | 0.1955          | 0.9588   | 0.6190 | 0.8125   | 0.5         | 0.8888       |
| 0.0345        | 4.0   | 100  | 0.2267          | 0.9536   | 0.5909 | 0.8125   | 0.4643      | 0.8861       |
| 0.0386        | 5.0   | 125  | 0.3221          | 0.9665   | 0.6286 | 0.6875   | 0.5789      | 0.8330       |
| 0.0032        | 6.0   | 150  | 0.4260          | 0.9613   | 0.5714 | 0.625    | 0.5263      | 0.8004       |


### Framework versions

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