---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_xlmr_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_197
  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_197

This model is a fine-tuned version of [AnonymousCS/populism_xlmr_base](https://huggingface.co/AnonymousCS/populism_xlmr_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7740
- Accuracy: 0.0865
- 1-f1: 0.1593
- 1-recall: 1.0
- 1-precision: 0.0865
- 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-06
- train_batch_size: 16
- eval_batch_size: 16
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1   | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.6703        | 1.0   | 11   | 0.7609          | 0.0865   | 0.1593 | 1.0      | 0.0865      | 0.5          |
| 0.7166        | 2.0   | 22   | 0.7687          | 0.0865   | 0.1593 | 1.0      | 0.0865      | 0.5          |
| 0.6835        | 3.0   | 33   | 0.7682          | 0.0865   | 0.1593 | 1.0      | 0.0865      | 0.5          |
| 0.6688        | 4.0   | 44   | 0.7699          | 0.0865   | 0.1593 | 1.0      | 0.0865      | 0.5          |
| 0.703         | 5.0   | 55   | 0.7732          | 0.0865   | 0.1593 | 1.0      | 0.0865      | 0.5          |
| 0.7274        | 6.0   | 66   | 0.7740          | 0.0865   | 0.1593 | 1.0      | 0.0865      | 0.5          |


### Framework versions

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