---
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_378
  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_378

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: 0.6314
- Accuracy: 0.8464
- 1-f1: 0.2469
- 1-recall: 0.9423
- 1-precision: 0.1420
- Balanced Acc: 0.8930

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.192         | 1.0   | 19   | 0.6755          | 0.7883   | 0.1922 | 0.9423   | 0.1070      | 0.8632       |
| 0.2465        | 2.0   | 38   | 0.4063          | 0.8417   | 0.2414 | 0.9423   | 0.1384      | 0.8906       |
| 0.0752        | 3.0   | 57   | 0.7120          | 0.7996   | 0.2008 | 0.9423   | 0.1124      | 0.8690       |
| 0.1543        | 4.0   | 76   | 0.3070          | 0.9039   | 0.3345 | 0.9038   | 0.2052      | 0.9039       |
| 0.1197        | 5.0   | 95   | 0.7216          | 0.7924   | 0.1984 | 0.9615   | 0.1106      | 0.8746       |
| 0.0256        | 6.0   | 114  | 0.6314          | 0.8464   | 0.2469 | 0.9423   | 0.1420      | 0.8930       |


### Framework versions

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