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library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_108
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_108
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4336
- Accuracy: 0.8830
- 1-f1: 0.2313
- 1-recall: 0.8857
- 1-precision: 0.1330
- Balanced Acc: 0.8843
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.4252 | 1.0 | 29 | 0.2576 | 0.9074 | 0.2126 | 0.6286 | 0.1279 | 0.7708 |
| 0.2944 | 2.0 | 58 | 0.2319 | 0.9273 | 0.2558 | 0.6286 | 0.1606 | 0.7810 |
| 0.3545 | 3.0 | 87 | 0.4258 | 0.9069 | 0.2477 | 0.7714 | 0.1475 | 0.8405 |
| 0.3242 | 4.0 | 116 | 0.4336 | 0.8830 | 0.2313 | 0.8857 | 0.1330 | 0.8843 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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