---
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_375
  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_375

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: 0.4792
- Accuracy: 0.8657
- 1-f1: 0.4394
- 1-recall: 0.9062
- 1-precision: 0.29
- Balanced Acc: 0.8847

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0717        | 1.0   | 6    | 0.4615          | 0.8748   | 0.4567 | 0.9062   | 0.3053      | 0.8895       |
| 0.0109        | 2.0   | 12   | 0.3983          | 0.8966   | 0.5043 | 0.9062   | 0.3494      | 0.9011       |
| 0.0242        | 3.0   | 18   | 0.5124          | 0.8403   | 0.4133 | 0.9688   | 0.2627      | 0.9006       |
| 0.019         | 4.0   | 24   | 0.4792          | 0.8657   | 0.4394 | 0.9062   | 0.29        | 0.8847       |


### Framework versions

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