---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_394
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_394

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: 0.5525
- Accuracy: 0.9833
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:|
| 1.2242        | 1.0   | 449  | 0.6769          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 2.4482        | 2.0   | 898  | 0.7154          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.0054        | 3.0   | 1347 | 0.6086          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.0083        | 4.0   | 1796 | 0.5472          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.0095        | 5.0   | 2245 | 0.5068          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.9129        | 6.0   | 2694 | 0.4756          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.8618        | 7.0   | 3143 | 0.5492          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 1.624         | 8.0   | 3592 | 0.5120          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.0052        | 9.0   | 4041 | 0.6046          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.0201        | 10.0  | 4490 | 0.4285          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.0109        | 11.0  | 4939 | 0.5213          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.0068        | 12.0  | 5388 | 0.5858          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.8892        | 13.0  | 5837 | 0.5636          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.8009        | 14.0  | 6286 | 0.5437          | 0.9833   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.8449        | 15.0  | 6735 | 0.5525          | 0.9833   | 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