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library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_base_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_357
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_357
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_base_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1747
- Accuracy: 0.9814
- 1-f1: 0.7727
- 1-recall: 0.8947
- 1-precision: 0.68
- Balanced Acc: 0.9397
## 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: 64
- eval_batch_size: 64
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2952 | 1.0 | 34 | 0.1568 | 0.9796 | 0.7556 | 0.8947 | 0.6538 | 0.9387 |
| 0.0461 | 2.0 | 68 | 0.2817 | 0.9721 | 0.5714 | 0.5263 | 0.625 | 0.7574 |
| 0.0239 | 3.0 | 102 | 0.1524 | 0.9777 | 0.7273 | 0.8421 | 0.64 | 0.9124 |
| 0.0233 | 4.0 | 136 | 0.1413 | 0.9703 | 0.6800 | 0.8947 | 0.5484 | 0.9339 |
| 0.0005 | 5.0 | 170 | 0.3419 | 0.9777 | 0.6667 | 0.6316 | 0.7059 | 0.8110 |
| 0.0005 | 6.0 | 204 | 0.1759 | 0.9814 | 0.7727 | 0.8947 | 0.68 | 0.9397 |
| 0.0004 | 7.0 | 238 | 0.1747 | 0.9814 | 0.7727 | 0.8947 | 0.68 | 0.9397 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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