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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_095
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_095
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: 0.8900
- Accuracy: 0.8039
- 1-f1: 0.2754
- 1-recall: 0.8636
- 1-precision: 0.1638
- Balanced Acc: 0.8324
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.412 | 1.0 | 13 | 0.8969 | 0.7569 | 0.2439 | 0.9091 | 0.1408 | 0.8295 |
| 0.049 | 2.0 | 26 | 0.6885 | 0.7471 | 0.2543 | 1.0 | 0.1457 | 0.8678 |
| 0.02 | 3.0 | 39 | 1.1921 | 0.6922 | 0.2189 | 1.0 | 0.1229 | 0.8391 |
| 0.1254 | 4.0 | 52 | 0.8900 | 0.8039 | 0.2754 | 0.8636 | 0.1638 | 0.8324 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|