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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_103
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_103
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: 0.4698
- Accuracy: 0.9400
- 1-f1: 0.4444
- 1-recall: 0.4571
- 1-precision: 0.4324
- Balanced Acc: 0.7120
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4302 | 1.0 | 21 | 0.3729 | 0.8921 | 0.3571 | 0.5714 | 0.2597 | 0.7406 |
| 0.3379 | 2.0 | 42 | 0.3342 | 0.8051 | 0.3299 | 0.9143 | 0.2013 | 0.8567 |
| 0.3594 | 3.0 | 63 | 0.3794 | 0.7781 | 0.3019 | 0.9143 | 0.1808 | 0.8424 |
| 0.4089 | 4.0 | 84 | 0.4698 | 0.9400 | 0.4444 | 0.4571 | 0.4324 | 0.7120 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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