|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google-bert/bert-base-multilingual-cased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: populism_model0 |
|
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_model0 |
|
|
|
This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4208 |
|
- Accuracy: 0.8688 |
|
- 1-f1: 0.3284 |
|
- 1-recall: 0.6588 |
|
- 1-precision: 0.2188 |
|
- Balanced Acc: 0.7692 |
|
|
|
## 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 | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
|
| 0.4957 | 1.0 | 55 | 0.5050 | 0.8682 | 0.2722 | 0.5059 | 0.1861 | 0.6963 | |
|
| 0.4629 | 2.0 | 110 | 0.4640 | 0.7788 | 0.2548 | 0.7765 | 0.1524 | 0.7777 | |
|
| 0.3876 | 3.0 | 165 | 0.4342 | 0.7851 | 0.2802 | 0.8588 | 0.1674 | 0.8201 | |
|
| 0.3452 | 4.0 | 220 | 0.4179 | 0.8911 | 0.3493 | 0.6 | 0.2464 | 0.7530 | |
|
| 0.3012 | 5.0 | 275 | 0.4208 | 0.8688 | 0.3284 | 0.6588 | 0.2188 | 0.7692 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.48.0.dev0 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
