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library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_393
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_393
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: 0.8732
- Accuracy: 0.3254
- 1-f1: 0.1163
- 1-recall: 0.6
- 1-precision: 0.0644
- Balanced Acc: 0.4518
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.8611 | 1.0 | 85 | 0.7354 | 0.0917 | 0.1401 | 1.0 | 0.0753 | 0.5096 |
| 0.7404 | 2.0 | 170 | 0.8947 | 0.0799 | 0.1385 | 1.0 | 0.0744 | 0.5032 |
| 0.7009 | 3.0 | 255 | 0.6590 | 0.2337 | 0.1618 | 1.0 | 0.0880 | 0.5863 |
| 0.4348 | 4.0 | 340 | 0.7461 | 0.2101 | 0.1577 | 1.0 | 0.0856 | 0.5735 |
| 0.8032 | 5.0 | 425 | 0.8210 | 0.2515 | 0.1538 | 0.92 | 0.0839 | 0.5590 |
| 0.4858 | 6.0 | 510 | 0.7814 | 0.2692 | 0.1453 | 0.84 | 0.0795 | 0.5318 |
| 0.6308 | 7.0 | 595 | 0.9987 | 0.0740 | 0.1377 | 1.0 | 0.0740 | 0.5 |
| 0.8048 | 8.0 | 680 | 0.8732 | 0.3254 | 0.1163 | 0.6 | 0.0644 | 0.4518 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|