---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_393
  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_393

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: 0.8732
- Accuracy: 0.3254
- 1-f1: 0.1163
- 1-recall: 0.6
- 1-precision: 0.0644
- Balanced Acc: 0.4518

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.8611        | 1.0   | 85   | 0.7354          | 0.0917   | 0.1401 | 1.0      | 0.0753      | 0.5096       |
| 0.7404        | 2.0   | 170  | 0.8947          | 0.0799   | 0.1385 | 1.0      | 0.0744      | 0.5032       |
| 0.7009        | 3.0   | 255  | 0.6590          | 0.2337   | 0.1618 | 1.0      | 0.0880      | 0.5863       |
| 0.4348        | 4.0   | 340  | 0.7461          | 0.2101   | 0.1577 | 1.0      | 0.0856      | 0.5735       |
| 0.8032        | 5.0   | 425  | 0.8210          | 0.2515   | 0.1538 | 0.92     | 0.0839      | 0.5590       |
| 0.4858        | 6.0   | 510  | 0.7814          | 0.2692   | 0.1453 | 0.84     | 0.0795      | 0.5318       |
| 0.6308        | 7.0   | 595  | 0.9987          | 0.0740   | 0.1377 | 1.0      | 0.0740      | 0.5          |
| 0.8048        | 8.0   | 680  | 0.8732          | 0.3254   | 0.1163 | 0.6      | 0.0644      | 0.4518       |


### Framework versions

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