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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_411
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_411
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: 0.7307
- Accuracy: 0.9091
- 1-f1: 0.0
- 1-recall: 0.0
- 1-precision: 0.0
- Balanced Acc: 0.4985
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.5911 | 1.0 | 91 | 0.7011 | 0.1515 | 0.1720 | 1.0 | 0.0941 | 0.5347 |
| 0.6288 | 2.0 | 182 | 0.8307 | 0.0882 | 0.1620 | 1.0 | 0.0882 | 0.5 |
| 0.5907 | 3.0 | 273 | 0.6749 | 0.2011 | 0.1808 | 1.0 | 0.0994 | 0.5619 |
| 0.675 | 4.0 | 364 | 0.7471 | 0.0909 | 0.1624 | 1.0 | 0.0884 | 0.5015 |
| 0.8407 | 5.0 | 455 | 0.9201 | 0.0882 | 0.1620 | 1.0 | 0.0882 | 0.5 |
| 0.625 | 6.0 | 546 | 0.6675 | 0.8375 | 0.1449 | 0.1562 | 0.1351 | 0.5298 |
| 0.383 | 7.0 | 637 | 0.6634 | 0.6860 | 0.1972 | 0.4375 | 0.1273 | 0.5737 |
| 1.0487 | 8.0 | 728 | 0.6541 | 0.7879 | 0.2524 | 0.4062 | 0.1831 | 0.6155 |
| 0.655 | 9.0 | 819 | 0.8689 | 0.8485 | 0.0678 | 0.0625 | 0.0741 | 0.4935 |
| 0.7175 | 10.0 | 910 | 0.6738 | 0.8981 | 0.0 | 0.0 | 0.0 | 0.4924 |
| 0.4837 | 11.0 | 1001 | 0.7142 | 0.9091 | 0.0 | 0.0 | 0.0 | 0.4985 |
| 0.257 | 12.0 | 1092 | 0.8252 | 0.9091 | 0.0 | 0.0 | 0.0 | 0.4985 |
| 0.7864 | 13.0 | 1183 | 0.7307 | 0.9091 | 0.0 | 0.0 | 0.0 | 0.4985 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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