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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_bsample_090
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_bsample_090
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: 1.1481
- Accuracy: 0.7845
- 1-f1: 0.3385
- 1-recall: 0.9565
- 1-precision: 0.2056
- Balanced Acc: 0.8652
## 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: 3e-05
- 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
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0038 | 1.0 | 12 | 1.5490 | 0.7293 | 0.2987 | 1.0 | 0.1756 | 0.8564 |
| 0.1709 | 2.0 | 24 | 1.0169 | 0.8070 | 0.3529 | 0.9130 | 0.2188 | 0.8568 |
| 0.5129 | 3.0 | 36 | 1.2461 | 0.7393 | 0.3067 | 1.0 | 0.1811 | 0.8617 |
| 0.0028 | 4.0 | 48 | 1.1481 | 0.7845 | 0.3385 | 0.9565 | 0.2056 | 0.8652 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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