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library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_large_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_321
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_321
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_cased](https://huggingface.co/AnonymousCS/populism_english_bert_large_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1428
- Accuracy: 0.9517
- 1-f1: 0.3590
- 1-recall: 0.2692
- 1-precision: 0.5385
- Balanced Acc: 0.6285
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2919 | 1.0 | 33 | 0.3111 | 0.9208 | 0.4675 | 0.6923 | 0.3529 | 0.8126 |
| 0.099 | 2.0 | 66 | 0.5101 | 0.9344 | 0.4516 | 0.5385 | 0.3889 | 0.7469 |
| 0.2634 | 3.0 | 99 | 0.5392 | 0.9459 | 0.5172 | 0.5769 | 0.4688 | 0.7712 |
| 0.8945 | 4.0 | 132 | 1.1428 | 0.9517 | 0.3590 | 0.2692 | 0.5385 | 0.6285 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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