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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_105
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_105
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: 0.7162
- Accuracy: 0.8453
- 1-f1: 0.3674
- 1-recall: 0.9414
- 1-precision: 0.2282
- Balanced Acc: 0.8909
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.337 | 1.0 | 333 | 0.8790 | 0.6966 | 0.2385 | 0.9955 | 0.1355 | 0.8386 |
| 0.1932 | 2.0 | 666 | 0.8913 | 0.7301 | 0.2589 | 0.9880 | 0.1490 | 0.8526 |
| 0.3488 | 3.0 | 999 | 0.7092 | 0.7569 | 0.2785 | 0.9835 | 0.1622 | 0.8645 |
| 0.1253 | 4.0 | 1332 | 0.5442 | 0.8456 | 0.3723 | 0.9594 | 0.2310 | 0.8997 |
| 0.6639 | 5.0 | 1665 | 0.6545 | 0.9526 | 0.0149 | 0.0075 | 1.0 | 0.5038 |
| 0.0072 | 6.0 | 1998 | 0.7162 | 0.8453 | 0.3674 | 0.9414 | 0.2282 | 0.8909 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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