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library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_097
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_097
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3891
- Accuracy: 0.9628
- 1-f1: 0.5238
- 1-recall: 0.5789
- 1-precision: 0.4783
- Balanced Acc: 0.7779
## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1771 | 1.0 | 17 | 0.3657 | 0.9535 | 0.4186 | 0.4737 | 0.375 | 0.7224 |
| 0.2792 | 2.0 | 34 | 0.2884 | 0.9554 | 0.4783 | 0.5789 | 0.4074 | 0.7741 |
| 0.2725 | 3.0 | 51 | 0.3435 | 0.9461 | 0.4528 | 0.6316 | 0.3529 | 0.7946 |
| 0.0743 | 4.0 | 68 | 0.3891 | 0.9628 | 0.5238 | 0.5789 | 0.4783 | 0.7779 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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