---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_large_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_367
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_367

This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_large_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1526
- Accuracy: 0.9408
- 1-f1: 0.5652
- 1-recall: 0.52
- 1-precision: 0.6190
- Balanced Acc: 0.7472

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2373        | 1.0   | 22   | 0.3833          | 0.8136   | 0.4112 | 0.88     | 0.2683      | 0.8442       |
| 0.5622        | 2.0   | 44   | 0.3790          | 0.8846   | 0.5301 | 0.88     | 0.3793      | 0.8825       |
| 0.1318        | 3.0   | 66   | 0.4654          | 0.9438   | 0.6275 | 0.64     | 0.6154      | 0.8040       |
| 0.0603        | 4.0   | 88   | 0.6768          | 0.9556   | 0.7059 | 0.72     | 0.6923      | 0.8472       |
| 0.0045        | 5.0   | 110  | 1.1526          | 0.9408   | 0.5652 | 0.52     | 0.6190      | 0.7472       |


### Framework versions

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