---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_model330
  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_model330

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: 0.7785
- Accuracy: 0.9536
- 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:|
| 0.5308        | 1.0   | 873  | 0.7978          | 0.9536   | 0.0  | 0.0      | 0.0         | 0.5          |
| 1.2614        | 2.0   | 1746 | 0.7574          | 0.9536   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.8156        | 3.0   | 2619 | 0.8353          | 0.9536   | 0.0  | 0.0      | 0.0         | 0.5          |
| 0.6846        | 4.0   | 3492 | 0.8088          | 0.9536   | 0.0  | 0.0      | 0.0         | 0.5          |
| 1.0974        | 5.0   | 4365 | 0.7785          | 0.9536   | 0.0  | 0.0      | 0.0         | 0.5          |


### Framework versions

- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1