---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_large_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_333
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# populism_classifier_333

This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_cased](https://huggingface.co/AnonymousCS/populism_english_bert_large_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7774
- Accuracy: 0.9201
- 1-f1: 0.2564
- 1-recall: 0.1562
- 1-precision: 0.7143
- Balanced Acc: 0.5751

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5971        | 1.0   | 23   | 0.3359          | 0.8402   | 0.4821 | 0.8438   | 0.3375      | 0.8418       |
| 0.2685        | 2.0   | 46   | 0.3264          | 0.8320   | 0.5041 | 0.9688   | 0.3407      | 0.8937       |
| 0.13          | 3.0   | 69   | 0.4028          | 0.8843   | 0.5000 | 0.6562   | 0.4038      | 0.7813       |
| 0.1104        | 4.0   | 92   | 0.4979          | 0.8733   | 0.5208 | 0.7812   | 0.3906      | 0.8317       |
| 0.4235        | 5.0   | 115  | 1.7774          | 0.9201   | 0.2564 | 0.1562   | 0.7143      | 0.5751       |


### Framework versions

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