---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_412
  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_412

This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7918
- Accuracy: 0.7150
- 1-f1: 0.2162
- 1-recall: 1.0
- 1-precision: 0.1212
- Balanced Acc: 0.8517

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0566        | 1.0   | 4    | 1.1299          | 0.6585   | 0.1871 | 1.0      | 0.1032      | 0.8223       |
| 0.0665        | 2.0   | 8    | 0.8764          | 0.7224   | 0.2207 | 1.0      | 0.1240      | 0.8555       |
| 0.0703        | 3.0   | 12   | 0.5920          | 0.8034   | 0.2857 | 1.0      | 0.1667      | 0.8977       |
| 0.0455        | 4.0   | 16   | 0.5149          | 0.8256   | 0.2970 | 0.9375   | 0.1765      | 0.8792       |
| 0.0567        | 5.0   | 20   | 0.9592          | 0.7076   | 0.2119 | 1.0      | 0.1185      | 0.8478       |
| 0.025         | 6.0   | 24   | 0.7918          | 0.7150   | 0.2162 | 1.0      | 0.1212      | 0.8517       |


### Framework versions

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