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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_102
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_102
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: 0.7816
- Accuracy: 0.8457
- 1-f1: 0.4
- 1-recall: 0.8929
- 1-precision: 0.2577
- Balanced Acc: 0.8678
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3036 | 1.0 | 14 | 0.6919 | 0.8251 | 0.3796 | 0.9286 | 0.2385 | 0.8737 |
| 0.4483 | 2.0 | 28 | 0.5778 | 0.8498 | 0.4160 | 0.9286 | 0.2680 | 0.8868 |
| 0.0188 | 3.0 | 42 | 0.5454 | 0.8642 | 0.4211 | 0.8571 | 0.2791 | 0.8609 |
| 0.1404 | 4.0 | 56 | 0.9410 | 0.7901 | 0.3544 | 1.0 | 0.2154 | 0.8886 |
| 0.0024 | 5.0 | 70 | 0.7816 | 0.8457 | 0.4 | 0.8929 | 0.2577 | 0.8678 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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