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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_340
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_340
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: 0.5170
- Accuracy: 0.8951
- 1-f1: 0.2381
- 1-recall: 0.4167
- 1-precision: 0.1667
- Balanced Acc: 0.6657
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3768 | 1.0 | 20 | 0.4651 | 0.9410 | 0.1818 | 0.1667 | 0.2 | 0.5697 |
| 0.3174 | 2.0 | 40 | 0.4922 | 0.9508 | 0.2105 | 0.1667 | 0.2857 | 0.5748 |
| 0.4174 | 3.0 | 60 | 0.4369 | 0.9016 | 0.2857 | 0.5 | 0.2 | 0.7090 |
| 0.3601 | 4.0 | 80 | 0.5736 | 0.9213 | 0.2941 | 0.4167 | 0.2273 | 0.6793 |
| 0.7514 | 5.0 | 100 | 0.6534 | 0.7344 | 0.1474 | 0.5833 | 0.0843 | 0.6620 |
| 0.0811 | 6.0 | 120 | 0.5170 | 0.8951 | 0.2381 | 0.4167 | 0.1667 | 0.6657 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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