|
--- |
|
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_model77 |
|
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_model77 |
|
|
|
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: 0.6334 |
|
- Accuracy: 0.9210 |
|
- F1: 0.2947 |
|
- Recall: 0.4375 |
|
- Precision: 0.2222 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
|
| No log | 1.0 | 27 | 0.3886 | 0.8762 | 0.2759 | 0.625 | 0.1770 | |
|
| 0.3981 | 2.0 | 54 | 0.4590 | 0.9328 | 0.2963 | 0.375 | 0.2449 | |
|
| 0.3981 | 3.0 | 81 | 0.5274 | 0.9104 | 0.2692 | 0.4375 | 0.1944 | |
|
| 0.1863 | 4.0 | 108 | 0.5875 | 0.9175 | 0.3 | 0.4688 | 0.2206 | |
|
| 0.1863 | 5.0 | 135 | 0.6334 | 0.9210 | 0.2947 | 0.4375 | 0.2222 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
