---
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_368
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_368

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: 0.4167
- Accuracy: 0.9633
- 1-f1: 0.1081
- 1-recall: 0.1333
- 1-precision: 0.0909
- Balanced Acc: 0.5553

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5876        | 1.0   | 113  | 0.3563          | 0.9833   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.5976        | 2.0   | 226  | 0.3037          | 0.9733   | 0.0769 | 0.0667   | 0.0909      | 0.5277       |
| 0.658         | 3.0   | 339  | 0.4078          | 0.9794   | 0.0    | 0.0      | 0.0         | 0.4980       |
| 0.1679        | 4.0   | 452  | 0.3198          | 0.9421   | 0.1875 | 0.4      | 0.1224      | 0.6757       |
| 0.2655        | 5.0   | 565  | 0.4167          | 0.9633   | 0.1081 | 0.1333   | 0.0909      | 0.5553       |


### Framework versions

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