|
--- |
|
library_name: transformers |
|
license: mit |
|
base_model: AnonymousCS/populism_multilingual_roberta_base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- recall |
|
- precision |
|
model-index: |
|
- name: populism_model56 |
|
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_model56 |
|
|
|
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: 0.4856 |
|
- Accuracy: 0.8519 |
|
- F1: 0.3103 |
|
- Recall: 0.6301 |
|
- Precision: 0.2058 |
|
|
|
## 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: 128 |
|
- eval_batch_size: 128 |
|
- 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: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
|
| 0.6562 | 1.0 | 87 | 0.5132 | 0.9247 | 0.1746 | 0.1507 | 0.2075 | |
|
| 0.5 | 2.0 | 174 | 0.4700 | 0.8751 | 0.3086 | 0.5274 | 0.2181 | |
|
| 0.4517 | 3.0 | 261 | 0.4616 | 0.8700 | 0.3214 | 0.5822 | 0.2219 | |
|
| 0.4041 | 4.0 | 348 | 0.4681 | 0.7936 | 0.2692 | 0.7192 | 0.1656 | |
|
| 0.37 | 5.0 | 435 | 0.4856 | 0.8519 | 0.3103 | 0.6301 | 0.2058 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
