---
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_bsample_291
  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_bsample_291

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: 0.8580
- Accuracy: 0.7751
- 1-f1: 0.2034
- 1-recall: 0.8
- 1-precision: 0.1165
- Balanced Acc: 0.7871

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1343        | 1.0   | 7    | 0.9985          | 0.6531   | 0.1520 | 0.8667   | 0.0833      | 0.7559       |
| 0.0827        | 2.0   | 14   | 1.1388          | 0.6316   | 0.1444 | 0.8667   | 0.0788      | 0.7447       |
| 0.0647        | 3.0   | 21   | 0.7105          | 0.7799   | 0.2069 | 0.8      | 0.1188      | 0.7896       |
| 0.0425        | 4.0   | 28   | 1.0996          | 0.6938   | 0.1688 | 0.8667   | 0.0935      | 0.7770       |
| 0.0199        | 5.0   | 35   | 0.8580          | 0.7751   | 0.2034 | 0.8      | 0.1165      | 0.7871       |


### Framework versions

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