---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_411
  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_411

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: 0.7307
- Accuracy: 0.9091
- 1-f1: 0.0
- 1-recall: 0.0
- 1-precision: 0.0
- Balanced Acc: 0.4985

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5911        | 1.0   | 91   | 0.7011          | 0.1515   | 0.1720 | 1.0      | 0.0941      | 0.5347       |
| 0.6288        | 2.0   | 182  | 0.8307          | 0.0882   | 0.1620 | 1.0      | 0.0882      | 0.5          |
| 0.5907        | 3.0   | 273  | 0.6749          | 0.2011   | 0.1808 | 1.0      | 0.0994      | 0.5619       |
| 0.675         | 4.0   | 364  | 0.7471          | 0.0909   | 0.1624 | 1.0      | 0.0884      | 0.5015       |
| 0.8407        | 5.0   | 455  | 0.9201          | 0.0882   | 0.1620 | 1.0      | 0.0882      | 0.5          |
| 0.625         | 6.0   | 546  | 0.6675          | 0.8375   | 0.1449 | 0.1562   | 0.1351      | 0.5298       |
| 0.383         | 7.0   | 637  | 0.6634          | 0.6860   | 0.1972 | 0.4375   | 0.1273      | 0.5737       |
| 1.0487        | 8.0   | 728  | 0.6541          | 0.7879   | 0.2524 | 0.4062   | 0.1831      | 0.6155       |
| 0.655         | 9.0   | 819  | 0.8689          | 0.8485   | 0.0678 | 0.0625   | 0.0741      | 0.4935       |
| 0.7175        | 10.0  | 910  | 0.6738          | 0.8981   | 0.0    | 0.0      | 0.0         | 0.4924       |
| 0.4837        | 11.0  | 1001 | 0.7142          | 0.9091   | 0.0    | 0.0      | 0.0         | 0.4985       |
| 0.257         | 12.0  | 1092 | 0.8252          | 0.9091   | 0.0    | 0.0      | 0.0         | 0.4985       |
| 0.7864        | 13.0  | 1183 | 0.7307          | 0.9091   | 0.0    | 0.0      | 0.0         | 0.4985       |


### Framework versions

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