---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_base_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_308
  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_308

This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_cased](https://huggingface.co/AnonymousCS/populism_english_bert_base_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5505
- Accuracy: 0.9503
- 1-f1: 0.2963
- 1-recall: 0.25
- 1-precision: 0.3636
- Balanced Acc: 0.6154

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3048        | 1.0   | 12   | 0.4261          | 0.9555   | 0.32   | 0.25     | 0.4444      | 0.6182       |
| 0.1875        | 2.0   | 24   | 0.4461          | 0.9581   | 0.2727 | 0.1875   | 0.5         | 0.5897       |
| 0.3139        | 3.0   | 36   | 0.3300          | 0.8665   | 0.3377 | 0.8125   | 0.2131      | 0.8407       |
| 0.4322        | 4.0   | 48   | 0.6472          | 0.9581   | 0.2727 | 0.1875   | 0.5         | 0.5897       |
| 0.1114        | 5.0   | 60   | 0.5505          | 0.9503   | 0.2963 | 0.25     | 0.3636      | 0.6154       |


### Framework versions

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