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library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_235
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_235
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9723
- Accuracy: 0.6953
- 1-f1: 0.2263
- 1-recall: 0.9338
- 1-precision: 0.1288
- Balanced Acc: 0.8086
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2215 | 1.0 | 167 | 1.2513 | 0.2303 | 0.1102 | 0.9985 | 0.0583 | 0.5951 |
| 0.2192 | 2.0 | 334 | 0.9871 | 0.4950 | 0.1555 | 0.9744 | 0.0845 | 0.7227 |
| 0.2565 | 3.0 | 501 | 0.9863 | 0.6052 | 0.1847 | 0.9368 | 0.1024 | 0.7627 |
| 0.1831 | 4.0 | 668 | 1.0533 | 0.6338 | 0.1945 | 0.9263 | 0.1086 | 0.7727 |
| 0.0799 | 5.0 | 835 | 0.7577 | 0.7237 | 0.2352 | 0.8902 | 0.1355 | 0.8028 |
| 0.0769 | 6.0 | 1002 | 0.9875 | 0.6611 | 0.2088 | 0.9368 | 0.1175 | 0.7921 |
| 0.0708 | 7.0 | 1169 | 0.7383 | 0.7561 | 0.2613 | 0.9038 | 0.1527 | 0.8262 |
| 0.0419 | 8.0 | 1336 | 0.8412 | 0.7274 | 0.2437 | 0.9203 | 0.1405 | 0.8190 |
| 0.1823 | 9.0 | 1503 | 0.9723 | 0.6953 | 0.2263 | 0.9338 | 0.1288 | 0.8086 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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