---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_400
  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_bsample_400

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: 0.6789
- Accuracy: 0.9093
- 1-f1: 0.3577
- 1-recall: 0.88
- 1-precision: 0.2245
- Balanced Acc: 0.8951

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0596        | 1.0   | 9    | 0.6065          | 0.8726   | 0.2930 | 0.92     | 0.1742      | 0.8956       |
| 0.0089        | 2.0   | 18   | 0.6463          | 0.8772   | 0.2914 | 0.88     | 0.1746      | 0.8785       |
| 0.1585        | 3.0   | 27   | 0.4833          | 0.9196   | 0.375  | 0.84     | 0.2414      | 0.8810       |
| 0.0014        | 4.0   | 36   | 0.9014          | 0.8485   | 0.2584 | 0.92     | 0.1503      | 0.8832       |
| 0.0001        | 5.0   | 45   | 0.6789          | 0.9093   | 0.3577 | 0.88     | 0.2245      | 0.8951       |


### Framework versions

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