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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_129
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_129
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: 0.6651
- Accuracy: 0.7145
- 1-f1: 0.2667
- 1-recall: 0.9189
- 1-precision: 0.1560
- Balanced Acc: 0.8106
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7601 | 1.0 | 18 | 0.7731 | 0.2870 | 0.1304 | 0.9459 | 0.07 | 0.5968 |
| 0.714 | 2.0 | 36 | 0.8593 | 0.2580 | 0.1290 | 0.9730 | 0.0691 | 0.5941 |
| 0.7266 | 3.0 | 54 | 0.4779 | 0.9084 | 0.3023 | 0.3514 | 0.2653 | 0.6465 |
| 0.5782 | 4.0 | 72 | 0.5362 | 0.7282 | 0.2521 | 0.8108 | 0.1493 | 0.7671 |
| 0.1827 | 5.0 | 90 | 0.6651 | 0.7145 | 0.2667 | 0.9189 | 0.1560 | 0.8106 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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