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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_112
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_112
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: 0.9956
- Accuracy: 0.5337
- 1-f1: 0.1942
- 1-recall: 1.0
- 1-precision: 0.1075
- Balanced Acc: 0.7530
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7261 | 1.0 | 12 | 0.8661 | 0.0562 | 0.1064 | 1.0 | 0.0562 | 0.5 |
| 0.6039 | 2.0 | 24 | 0.8458 | 0.0562 | 0.1064 | 1.0 | 0.0562 | 0.5 |
| 0.4807 | 3.0 | 36 | 1.3332 | 0.4860 | 0.1794 | 1.0 | 0.0985 | 0.7277 |
| 0.8063 | 4.0 | 48 | 0.2922 | 0.8483 | 0.4000 | 0.9 | 0.2571 | 0.8726 |
| 0.5137 | 5.0 | 60 | 0.8611 | 0.3567 | 0.1487 | 1.0 | 0.0803 | 0.6592 |
| 0.3056 | 6.0 | 72 | 0.9956 | 0.5337 | 0.1942 | 1.0 | 0.1075 | 0.7530 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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