---
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_bsample_386
  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_386

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: 0.8007
- Accuracy: 0.7985
- 1-f1: 0.2264
- 1-recall: 0.75
- 1-precision: 0.1333
- Balanced Acc: 0.7753

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1259        | 1.0   | 4    | 1.3380          | 0.5774   | 0.1569 | 1.0      | 0.0851      | 0.7801       |
| 0.0921        | 2.0   | 8    | 0.5886          | 0.8059   | 0.2617 | 0.875    | 0.1538      | 0.8390       |
| 0.084         | 3.0   | 12   | 0.8020          | 0.7322   | 0.2044 | 0.875    | 0.1157      | 0.8007       |
| 0.0229        | 4.0   | 16   | 0.8007          | 0.7985   | 0.2264 | 0.75     | 0.1333      | 0.7753       |


### Framework versions

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