---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_416
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# populism_classifier_bsample_416

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: 0.7517
- Accuracy: 0.8986
- 1-f1: 0.4694
- 1-recall: 0.8519
- 1-precision: 0.3239
- Balanced Acc: 0.8765

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0293        | 1.0   | 8    | 1.0991          | 0.6823   | 0.2488 | 1.0      | 0.1421      | 0.8323       |
| 0.0368        | 2.0   | 16   | 0.5864          | 0.8928   | 0.4660 | 0.8889   | 0.3158      | 0.8909       |
| 0.001         | 3.0   | 24   | 0.6112          | 0.9337   | 0.5405 | 0.7407   | 0.4255      | 0.8426       |
| 0.0009        | 4.0   | 32   | 0.7517          | 0.8986   | 0.4694 | 0.8519   | 0.3239      | 0.8765       |


### Framework versions

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