---
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_356
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_356

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: 0.3258
- Accuracy: 0.9495
- 1-f1: 0.6038
- 1-recall: 0.7273
- 1-precision: 0.5161
- Balanced Acc: 0.8446

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1924        | 1.0   | 26   | 0.1308          | 0.9399   | 0.6377 | 1.0      | 0.4681      | 0.9683       |
| 0.0207        | 2.0   | 52   | 0.1297          | 0.9447   | 0.6567 | 1.0      | 0.4889      | 0.9708       |
| 0.1206        | 3.0   | 78   | 0.1317          | 0.9543   | 0.6984 | 1.0      | 0.5366      | 0.9759       |
| 0.0471        | 4.0   | 104  | 0.1257          | 0.9567   | 0.7097 | 1.0      | 0.55        | 0.9772       |
| 0.2653        | 5.0   | 130  | 0.3578          | 0.9591   | 0.6667 | 0.7727   | 0.5862      | 0.8711       |
| 0.0014        | 6.0   | 156  | 0.2350          | 0.9543   | 0.6545 | 0.8182   | 0.5455      | 0.8901       |
| 0.0013        | 7.0   | 182  | 0.3258          | 0.9495   | 0.6038 | 0.7273   | 0.5161      | 0.8446       |


### Framework versions

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