---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_415
  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_bsample_415

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: 0.7123
- Accuracy: 0.8870
- 1-f1: 0.4219
- 1-recall: 0.7297
- 1-precision: 0.2967
- Balanced Acc: 0.8131

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.276         | 1.0   | 9    | 0.9888          | 0.5252   | 0.1880 | 0.9730   | 0.1040      | 0.7357       |
| 0.1101        | 2.0   | 18   | 0.6875          | 0.7298   | 0.2834 | 0.9459   | 0.1667      | 0.8314       |
| 0.1145        | 3.0   | 27   | 0.6851          | 0.8015   | 0.3158 | 0.8108   | 0.1961      | 0.8059       |
| 0.0293        | 4.0   | 36   | 0.7586          | 0.8336   | 0.3550 | 0.8108   | 0.2273      | 0.8229       |
| 0.0461        | 5.0   | 45   | 0.6599          | 0.8901   | 0.4098 | 0.6757   | 0.2941      | 0.7893       |
| 0.0044        | 6.0   | 54   | 0.6568          | 0.8824   | 0.4031 | 0.7027   | 0.2826      | 0.7980       |
| 0.0082        | 7.0   | 63   | 0.7689          | 0.8489   | 0.3694 | 0.7838   | 0.2417      | 0.8183       |
| 0.0542        | 8.0   | 72   | 0.7123          | 0.8870   | 0.4219 | 0.7297   | 0.2967      | 0.8131       |


### Framework versions

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