---
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_365
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_365

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: 0.8041
- Accuracy: 0.9541
- 1-f1: 0.4814
- 1-recall: 0.4466
- 1-precision: 0.5220
- Balanced Acc: 0.7131

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4578        | 1.0   | 871  | 0.3614          | 0.8890   | 0.3760 | 0.7008   | 0.2569      | 0.7996       |
| 0.1728        | 2.0   | 1742 | 0.3576          | 0.9030   | 0.4207 | 0.7383   | 0.2942      | 0.8248       |
| 0.1014        | 3.0   | 2613 | 0.5243          | 0.9325   | 0.4268 | 0.5263   | 0.3590      | 0.7396       |
| 0.2324        | 4.0   | 3484 | 0.7760          | 0.9530   | 0.4696 | 0.4361   | 0.5088      | 0.7075       |
| 0.2645        | 5.0   | 4355 | 0.8041          | 0.9541   | 0.4814 | 0.4466   | 0.5220      | 0.7131       |


### Framework versions

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