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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_351
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_351
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: 0.4898
- Accuracy: 0.9470
- 1-f1: 0.4727
- 1-recall: 0.5652
- 1-precision: 0.4062
- Balanced Acc: 0.7645
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.551 | 1.0 | 35 | 0.2929 | 0.9250 | 0.4058 | 0.6087 | 0.3043 | 0.7738 |
| 0.1891 | 2.0 | 70 | 0.4090 | 0.9452 | 0.4231 | 0.4783 | 0.3793 | 0.7220 |
| 0.1242 | 3.0 | 105 | 0.3443 | 0.9214 | 0.4267 | 0.6957 | 0.3077 | 0.8135 |
| 0.3557 | 4.0 | 140 | 0.4898 | 0.9470 | 0.4727 | 0.5652 | 0.4062 | 0.7645 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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