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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_241
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_241
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: 0.5762
- Accuracy: 0.9485
- 1-f1: 0.5
- 1-recall: 0.625
- 1-precision: 0.4167
- Balanced Acc: 0.7937
## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3564 | 1.0 | 25 | 0.3452 | 0.8557 | 0.3333 | 0.875 | 0.2059 | 0.8649 |
| 0.0732 | 2.0 | 50 | 0.4145 | 0.9433 | 0.4762 | 0.625 | 0.3846 | 0.7910 |
| 0.4557 | 3.0 | 75 | 0.6337 | 0.9562 | 0.5143 | 0.5625 | 0.4737 | 0.7678 |
| 0.062 | 4.0 | 100 | 0.5762 | 0.9485 | 0.5 | 0.625 | 0.4167 | 0.7937 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|