---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_410
  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_410

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: 0.7024
- Accuracy: 0.1263
- 1-f1: 0.2242
- 1-recall: 1.0
- 1-precision: 0.1263
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.6697        | 1.0   | 50   | 0.6939          | 0.1263   | 0.2242 | 1.0      | 0.1263      | 0.5          |
| 0.6672        | 2.0   | 100  | 0.7424          | 0.1263   | 0.2242 | 1.0      | 0.1263      | 0.5          |
| 0.8553        | 3.0   | 150  | 0.8350          | 0.1263   | 0.2242 | 1.0      | 0.1263      | 0.5          |
| 0.6019        | 4.0   | 200  | 0.7917          | 0.1263   | 0.2242 | 1.0      | 0.1263      | 0.5          |
| 0.5024        | 5.0   | 250  | 0.6939          | 0.1414   | 0.2273 | 1.0      | 0.1282      | 0.5087       |
| 0.6982        | 6.0   | 300  | 0.7261          | 0.1364   | 0.2262 | 1.0      | 0.1276      | 0.5058       |
| 0.8583        | 7.0   | 350  | 0.7103          | 0.1263   | 0.2242 | 1.0      | 0.1263      | 0.5          |
| 0.5487        | 8.0   | 400  | 0.7149          | 0.1364   | 0.2262 | 1.0      | 0.1276      | 0.5058       |
| 0.5309        | 9.0   | 450  | 0.7218          | 0.1313   | 0.2252 | 1.0      | 0.1269      | 0.5029       |
| 0.5436        | 10.0  | 500  | 0.6868          | 0.1919   | 0.2381 | 1.0      | 0.1351      | 0.5376       |
| 0.5617        | 11.0  | 550  | 0.6876          | 0.1919   | 0.2381 | 1.0      | 0.1351      | 0.5376       |
| 0.8479        | 12.0  | 600  | 0.6812          | 0.1919   | 0.2381 | 1.0      | 0.1351      | 0.5376       |
| 1.4176        | 13.0  | 650  | 0.6805          | 0.1818   | 0.2358 | 1.0      | 0.1337      | 0.5318       |
| 0.3742        | 14.0  | 700  | 0.6920          | 0.1566   | 0.2304 | 1.0      | 0.1302      | 0.5173       |
| 0.7671        | 15.0  | 750  | 0.6905          | 0.1465   | 0.2283 | 1.0      | 0.1289      | 0.5116       |
| 0.994         | 16.0  | 800  | 0.6967          | 0.1313   | 0.2252 | 1.0      | 0.1269      | 0.5029       |
| 0.3561        | 17.0  | 850  | 0.6962          | 0.1414   | 0.2273 | 1.0      | 0.1282      | 0.5087       |
| 0.5991        | 18.0  | 900  | 0.7024          | 0.1263   | 0.2242 | 1.0      | 0.1263      | 0.5          |


### Framework versions

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