|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: google/rembert |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: populism_classifier_414 |
|
|
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_414 |
|
|
|
|
|
This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.6349 |
|
|
- Accuracy: 0.9406 |
|
|
- 1-f1: 0.0 |
|
|
- 1-recall: 0.0 |
|
|
- 1-precision: 0.0 |
|
|
- Balanced Acc: 0.5 |
|
|
|
|
|
## 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: 16 |
|
|
- 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 |
|
|
- lr_scheduler_warmup_ratio: 0.06 |
|
|
- 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
|
|
| 0.4007 | 1.0 | 122 | 0.6496 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.4705 | 2.0 | 244 | 0.7770 | 0.1291 | 0.1127 | 0.9310 | 0.06 | 0.5047 | |
|
|
| 0.9942 | 3.0 | 366 | 1.1307 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.4023 | 4.0 | 488 | 0.6234 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.729 | 5.0 | 610 | 0.6717 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.4101 | 6.0 | 732 | 0.6214 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.5957 | 7.0 | 854 | 0.6215 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.8498 | 8.0 | 976 | 0.6333 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.5553 | 9.0 | 1098 | 0.6267 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.4796 | 10.0 | 1220 | 0.6599 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.6643 | 11.0 | 1342 | 0.6213 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.5396 | 12.0 | 1464 | 0.6218 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.5217 | 13.0 | 1586 | 0.6359 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.5086 | 14.0 | 1708 | 0.6403 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.6382 | 15.0 | 1830 | 0.6269 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
| 0.7726 | 16.0 | 1952 | 0.6349 | 0.9406 | 0.0 | 0.0 | 0.0 | 0.5 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.46.3 |
|
|
- Pytorch 2.4.1+cu121 |
|
|
- Datasets 3.1.0 |
|
|
- Tokenizers 0.20.3 |
|
|
|
