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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_396
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_396
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: 0.6710
- Accuracy: 0.9355
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 1.1991 | 1.0 | 128 | 0.6415 | 0.9355 | 0.0 | 0.0 | 0.0 | 0.5 |
| 1.2117 | 2.0 | 256 | 0.6960 | 0.9355 | 0.0 | 0.0 | 0.0 | 0.5 |
| 1.4748 | 3.0 | 384 | 1.1384 | 0.9355 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7464 | 4.0 | 512 | 0.7210 | 0.7695 | 0.0167 | 0.0303 | 0.0115 | 0.4254 |
| 0.6122 | 5.0 | 640 | 0.6916 | 0.75 | 0.0303 | 0.0606 | 0.0202 | 0.4291 |
| 0.8029 | 6.0 | 768 | 0.6710 | 0.9355 | 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
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