---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_base_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_352
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_352

This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1382
- Accuracy: 0.9939
- 1-f1: 0.8929
- 1-recall: 0.8772
- 1-precision: 0.9091
- Balanced Acc: 0.9373

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.188         | 1.0   | 124  | 0.1878          | 0.96     | 0.5269 | 0.7719   | 0.4         | 0.8688       |
| 0.0717        | 2.0   | 248  | 0.1507          | 0.9635   | 0.5663 | 0.8246   | 0.4312      | 0.8961       |
| 0.0532        | 3.0   | 372  | 0.1856          | 0.9792   | 0.6555 | 0.6842   | 0.6290      | 0.8361       |
| 0.0114        | 4.0   | 496  | 0.1190          | 0.9818   | 0.7391 | 0.8947   | 0.6296      | 0.9395       |
| 0.001         | 5.0   | 620  | 0.1292          | 0.9833   | 0.7660 | 0.9474   | 0.6429      | 0.9659       |
| 0.0012        | 6.0   | 744  | 0.1184          | 0.9899   | 0.8333 | 0.8772   | 0.7937      | 0.9352       |
| 0.0013        | 7.0   | 868  | 0.1127          | 0.9853   | 0.7852 | 0.9298   | 0.6795      | 0.9584       |
| 0.0005        | 8.0   | 992  | 0.1341          | 0.9853   | 0.7852 | 0.9298   | 0.6795      | 0.9584       |
| 0.0003        | 9.0   | 1116 | 0.2046          | 0.9909   | 0.8393 | 0.8246   | 0.8545      | 0.9102       |
| 0.0002        | 10.0  | 1240 | 0.1382          | 0.9939   | 0.8929 | 0.8772   | 0.9091      | 0.9373       |


### Framework versions

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