|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: google-bert/bert-base-multilingual-uncased |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: populism_classifier_bsample_027 |
|
|
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_027 |
|
|
|
|
|
This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.6278 |
|
|
- Accuracy: 0.8051 |
|
|
- 1-f1: 0.3155 |
|
|
- 1-recall: 0.9414 |
|
|
- 1-precision: 0.1895 |
|
|
- Balanced Acc: 0.8698 |
|
|
|
|
|
## 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
|
|
| 0.1822 | 1.0 | 167 | 1.1261 | 0.5216 | 0.1655 | 0.9940 | 0.0903 | 0.7460 | |
|
|
| 0.0917 | 2.0 | 334 | 0.6039 | 0.7504 | 0.2638 | 0.9368 | 0.1535 | 0.8389 | |
|
|
| 0.118 | 3.0 | 501 | 0.6889 | 0.7300 | 0.2539 | 0.9624 | 0.1462 | 0.8404 | |
|
|
| 0.3814 | 4.0 | 668 | 0.4434 | 0.8794 | 0.3885 | 0.8030 | 0.2562 | 0.8431 | |
|
|
| 0.0625 | 5.0 | 835 | 0.6553 | 0.8022 | 0.3086 | 0.9248 | 0.1852 | 0.8604 | |
|
|
| 0.0409 | 6.0 | 1002 | 0.6278 | 0.8051 | 0.3155 | 0.9414 | 0.1895 | 0.8698 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.46.3 |
|
|
- Pytorch 2.4.1+cu121 |
|
|
- Datasets 3.1.0 |
|
|
- Tokenizers 0.20.3 |
|
|
|
