---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_414
  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_414

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: 0.6349
- Accuracy: 0.9406
- 1-f1: 0.0
- 1-recall: 0.0
- 1-precision: 0.0
- Balanced Acc: 0.5

## 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: 16
- 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
- lr_scheduler_warmup_ratio: 0.06
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4007        | 1.0   | 122  | 0.6496          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.4705        | 2.0   | 244  | 0.7770          | 0.1291   | 0.1127 | 0.9310   | 0.06        | 0.5047       |
| 0.9942        | 3.0   | 366  | 1.1307          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.4023        | 4.0   | 488  | 0.6234          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.729         | 5.0   | 610  | 0.6717          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.4101        | 6.0   | 732  | 0.6214          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.5957        | 7.0   | 854  | 0.6215          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.8498        | 8.0   | 976  | 0.6333          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.5553        | 9.0   | 1098 | 0.6267          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.4796        | 10.0  | 1220 | 0.6599          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.6643        | 11.0  | 1342 | 0.6213          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.5396        | 12.0  | 1464 | 0.6218          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.5217        | 13.0  | 1586 | 0.6359          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.5086        | 14.0  | 1708 | 0.6403          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.6382        | 15.0  | 1830 | 0.6269          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |
| 0.7726        | 16.0  | 1952 | 0.6349          | 0.9406   | 0.0    | 0.0      | 0.0         | 0.5          |


### Framework versions

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